Silk is a globally renowned abundant biopolymer obtained from various sources of the Lepidoptera family, among which the most commonly used and researched are spider silk and silk worm silk. All varieties of silk have beneficial characteristics such as high tensile strength, biocompatibility, producing a reduced immune response in a biological system, biodegradability, and the ability to withstand environmental stresses as well. These features make silk suitable for a number of applications as a biomaterial. The vast potential of silk and its proteins in cosmetics, oncology, tissue engineering, TOC screenings, for preserving food, cosmetic product as a silk gel and bioremediation makes it a well-sought biopolymer among researchers. Experiments over the years have revealed that biomaterials constituting silk are very potent but are yet to be scaled up for commercial uses, but the various advantageous properties of silk biomaterial far overshadows the impeding problems of production.

The pervasive use of plastic for milk packaging has raised significant health concerns, despite its advantages in terms of cost-effectiveness, convenience, and durability. The potential correlation between cancer and plastic packaging is one of these concerns. This mini-review examines the health implications of plastic materials used in milk packaging, with a particular emphasis on their carcinogenic hazards. This work endeavors to summarize the current state of knowledge regarding the influence of plastic components on human health and underscore the importance of ongoing research in this field by utilizing insights from a comprehensive review article. Harmful chemicals have been observed to leach into milk from plastics used in milk packaging, including high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polyethylene terephthalate (PET), particularly under conditions of protracted storage and heat. Bisphenol A (BPA), phthalates, and styrene are among the most prevalent leachates. These chemicals have been associated with a variety of health issues, such as an elevated risk of cancer, and are recognized for their endocrine-disrupting properties. BPA and phthalates, in particular, have the potential to disrupt hormone function, which may result in breast cancer, prostate cancer, and other hormone-related malignancies.This review emphasizes the significance of comprehending the precise components of plastics utilized in milk packaging and their potential health consequences. It advocates for more rigorous research to completely elucidate the long-term health impacts of these materials by emphasizing the current state of knowledge and regulatory initiatives. Additionally, it underscores the necessity of innovative packaging technologies to guarantee consumer protection and mitigate the risk of exposure to carcinogenic substances.

Aiming to improve medical diagnosis and treatment, artificial intelligence (AI) has emerged as a transformational force in the healthcare industry. In this article, we examine how AI is increasingly being used to improve healthcare, with an emphasis on how it is changing medical diagnosis and treatment. We explore the opportunities, threats, and ethical concerns of incorporating AI into healthcare practice. In addition, we feature important AI applications in radiology, pathology, cardiology, and cancer. AI has great potential to improve patient outcomes, diagnostic accuracy, and the ability to provide individualized treatment plans in the future if it is used and refined with care.

Atopic dermatitis (AD) is a chronic inflammatory condition which significantly affects quality of life in both patients and their caregivers. Calcineurin inhibitors (CNI) are a class of immunosuppressive drugs predominantly inhibiting T cell mediated immune processes. CNI form complex by binding with immunophilins and in turn inhibit calcineurin and suppress downstream inflammatory pathway. Tacrolimus and pimecrolimus are topical CNI approved for the treatment of mild to severe AD in both children and adults. Application site reactions are frequently seen. They have been issued with black box warning towards increased risk of malignancies but supportive evidence is lacking. Cyclosporine, though highly effective, is used off-label for AD management. It is used for controlling acute flares of AD due to its very rapid onset of action. Nephrotoxicity and hypertension are its serious complications. CNI have not been reported with teratogenicity and may be used conditionally during pregnancy and lactation.

The relationship between child psychology and the widespread usage of mobile devices in the modern day is examined in "The Mobile Dilemma: Child Psychology and the Era of Technological Dependence." The abstract serves as a brief synopsis of the work, highlighting its important ideas and arguments. Concerns concerning the effects of excessive time spent on mobile devices on children's mental health and development have arisen in this age of technology dependency. The essay opens by pointing out the importance of investigating the psychological effects of kids' exposure to mobile gadgets. The effects of mobile phone addiction on learning, memory, and social and emotional health are investigated. The neurodevelopmental implications are explored further in the abstract, with a focus on the impact of mobile technology on brain plasticity and the formation of the developing brain. It offers advice on how to establish appropriate limits for children's screen time, encourages the development of digital literacy, and promotes responsible behavior.The pros and cons of using mobile devices in the classroom are also examined, along with their effects on students' ability to study and the risks and difficulties that could arise from implementing such a strategy. The emotional and social impacts of mobile device addiction are discussed in the abstract. This includes the impact on one's social life, empathy, ability to communicate, and sense of self-worth. The abstract also stresses the importance of interdisciplinary efforts involving parents, teachers, psychologists, and legislators to combat mobile device addiction through intervention and preventative techniques. Future directions are highlighted, with a focus on topics such as mobile technology development, digital well-being, privacy protection, mental health implications, screen time limits, digital literacy, and the impact of cultural and socioeconomic variables.

Charcot-Marie-Tooth (CMT) syndrome is the most common progressive human motor and sensory peripheral neuropathy. CMT type 1E is a demyelinating neuropathy affecting Schwann cells due to pmp22 mutations, modelized by Trembler-J mice. Curcumin, a natural polyphenol com-pound obtained from turmeric (Curcuma longa), exhibits dose- and time-varying antitumor, antioxidant and neuroprotective properties, however, the neurotherapeutic actions of curcumin still remain elusive. Here, we propose curcumin as a possible natural treatment capable of enhancing cellular detoxification mechanisms, resulting in an improvement of the neurodegenerative Trembler-J phenotype. Using a refined method for obtaining enriched Schwann cell cultures, we evaluated the neurotherapeutic action of low dose curcumin treatment on the PMP22 expression, and on the chaperones (HSF1 and Hsp27) and autophagy/mTOR (HDAC6 and ribosomes) pathways in Trembler-J and wild-type genotypes. In wild-type Schwann cells, the action of cur-cumin resulted in strong stimulation of the chaperone and macroautophagy pathway, whereas the modulation of ribophagy showed a mild effect. However, despite the promising neuroprotective effects for the treatment of neurological diseases, we report (demonstrate?) that the action of cur-cumin in Trembler-J Schwann cells could be impaired due to the irreversible impact of ethanol used as a common curcumin vehicle necessary for administration. These results contribute to expand our still limited understanding of PMP22 biology in neurobiology, and expose the intrinsic lability of the neurodegenerative Trembler-J genotype. Furthermore, they unravel interesting physiological mechanisms of cellular resilience relevant for to the pharmacological treatment of the neurodegenerative Tremble J phenotype with curcumin and ethanol. We conclude that the analysis of the effects of the vehicle itself is an essential and in-escapable step to comprehensibly assess the own effects and full potential of curcumin treatment for therapeutic purposes.

Natural language Processing (NLP) has significantly transformed in the last decade, especially in the field of Language Modeling. Large Language Models (LLMs) have achieved SOTA performances on Natural Language Understanding (NLU) and Natural Language Generation (NLG) tasks by learning language representation in self-supervised ways. This paper provides a comprehensive survey to capture the progression of advances in Language Models. In this paper, we examine the different aspects of Language Models, which started with a few million parameters but have reached the size of a trillion in a very short time. We also look at how these LLMs transitioned from task-specific to task-independent to task-and-language-independent architectures. This paper extensively discusses different pre-training objectives, benchmarks, and transfer learning methods used in LLMs. It also examines different fine-tuning and In-Context learning techniques used in downstream tasks. It also explores how LLMs can perform well across many domains and datasets if sufficiently trained on a large and diverse dataset. Next, it discusses how, over time, the availability of cheap computational power and large datasets have improved LLM’s capabilities and raised new challenges. As part of our study, we also inspect LLMs from the lens of scalability to see how their performance is affected by the model’s depth, width, and data size. Lastly, we provide an empirical comparison of existing trends and techniques and a comprehensive analysis of where the field of LLM currently stand.

We know that the classical Mittag-Leffler function play an important role as solution of fractional order differential and integral equations. We introduce the j-generalized p - k Mittag-Leffler function. We evaluate the second order differential recurrence relation and four different integral representations and introduce a homogeneous linear differential equation whose one of the solution is the j-generalized p-k Mittag-Leffler function. Also we evaluate the certain relations that exist between j-generalized p - k Mittag-Leffler function and Riemann-Liouville fractional integrals and derivatives. We evaluate Mellin-Barnes integral representation of j-generalized p-k Mittag-Le er Function. The relationship of j-generalized p-k Mittag-Leffler Function with Fox H-Function and Wright hypergeometric function is also establish. we obtained its Euler transform, Laplace Transform and Mellin transform. Finally we derive some particular cases.

Comprehensive studies into the various causes of this ubiquitous disease have been prompted by the worldwide increase in cancer incidence. There are many potential causes of cancer, but environmental factors are of particular concern now. This abstract explores the complex link between environmental factors and the growing cancer epidemic, shedding light on the role that our immediate environment plays in the emergence of cancers. The environment can contain carcinogenic agents that gradually influence the course of cancer, including air pollutants, water contaminants, workplace exposures, and industrial activities. The ways through which environmental carcinogens may cause DNA damage and unchecked cell proliferation are discussed in this abstract. Environmental justice and the moral necessity to reduce inequities in exposure and health effects are highlighted to underline the disproportionate impact on vulnerable groups. The study presented here highlights the need for preemptive action to reduce environmental risks. Society can reduce the hidden threat posed by environmental carcinogens through strict legislation, sustainable practices, and community-driven initiatives. In order to lessen the cancer burden and secure a healthier future for all, the authors of this abstract argue that there must be a concerted effort to create surroundings that promote health and well-being.

The body's billions of bacteria—the microbiota—influence health and illness. The microbiome—the genetic material of these microbes—affects digestion, immunological function, and mental health. Due to bacterial variety, complicated relationships, and research technique constraints, investigating the microbiota is difficult. AI and machine learning have expanded microbiome research. Artificial intelligence (AI) systems can efficiently scan large microbiome datasets to help researchers understand microbial populations and their functions. AI-based predictive algorithms can analyze food impacts on microbial communities and forecast illness risks based on gut microbiota composition. AI helps find microbial biomarkers linked to specific health disorders, enabling early illness identification and targeted therapy. AI-driven medication development platforms also modulate microbiome to treat microbiota-related diseases. Understanding microbial populations' involvement in health and illness requires understanding complicated microbial interactions within the microbiome and between it and the host. AI systems improve human health by comprehending these complex relationships. AI in microbiota study must overcome various obstacles. Data quality and AI model interpretability are essential for accurate findings. Diverse and representative datasets avoid biases and strengthen AI-driven conclusions. AI in microbiota research requires data protection, informed permission, and appropriate use of sensitive data. AI is improving our understanding of the human microbiome and its health effects, changing microbiota research. Overcoming difficulties and adhering to ethical norms will enable the proper use of AI-driven findings, leading to microbiome insights and precision medical breakthroughs.

There has been a revolution in crop breeding, the age-old technique of improving plant features for agricultural and nutritional purposes. The merging of Artificial Intelligence (AI) and genetics is the driving force behind these changes. The combination of AI-driven models, genomic data, and cutting-edge tools like CRISPR-Cas9 to speed up genetic improvements in crops is described in this abstract. From increased disease resistance and production potential to better nutritional content, AI plays a crucial role in the identification and improvement of crop features. The time it takes to review, select, and cross several generations of crops is reduced by AI's data-driven selection, precision editing, and predictive modeling. This innovative tool has the potential to transform farming by helping to combat issues like hunger, climate change, and malnutrition on a worldwide scale. Equal access, protecting genetic variety, and assessing risks are only some of the ethical and regulatory issues raised by AI-enhanced agricultural breeding. Responsible and equitable implementation of AI in agricultural breeding relies on successfully navigating these challenges. Finally, the use of artificial intelligence to improve crop breeding marks a revolutionary change in agriculture, speeding up genetic improvements to meet the needs of a growing global population while also addressing urgent environmental and nutritional concerns. This abstract provides a taste of the promise, difficulty, and ethical questions that characterize this innovative subject, where artificial intelligence and genetics join forces to grow a better future for agricultural production around the world.

Probiotics are now being looked at as a possible addition to cancer treatments in both study and clinical settings. This study tries to give an overview of probiotic research as it relates to cancer, with a focus on how it might help avoid cancer, treat it, and improve the health of cancer patients. We look at developmental studies that use cell culture and animal models to look at how well probiotics work in cancer. We focus on how probiotics change the immune system, inflammation, and gut bacteria. The results of clinical studies that looked at probiotics as an add-on therapy for cancer patients are looked at to see how they affected the treatment success, side effects, and quality of life of the patients. We look at the possible benefits of probiotics for certain types of cancer, such as colorectal cancer, breast cancer, and stomach tumors. We also find the best probiotic strains for each type of cancer. We also look at the synergistic benefits of combining probiotics with standard cancer treatments like chemotherapy, radiation therapy, and immunotherapy to improve the effectiveness of treatment and lower side effects. Lastly, we talk about the present problems and future directions of probiotic research for cancer. We focus on personalized methods, ideal doses and treatment plans, finding signs of treatment success, and making probiotic-based therapies. By learning more about how probiotics could be used to treat cancer, we can create personalized, successful, and well-tolerated probiotic treatments to improve cancer outcomes.

Concerns have been made about how children's health and psychology could be hurt by the growing number of mobile apps they use. This abstract looks at intervention methods and best practices for getting kids to use mobile apps in a healthy way, find a balance with technology, and build up their resilience. Key points include promoting digital literacy and critical thinking, setting clear boundaries and rules, encouraging digital balance, modeling healthy tech habits, building resilience and coping skills, encouraging face-to-face communication, setting up tech-free times and spaces, monitoring app usage and content, promoting mindfulness and self-reflection, and getting professional help when needed. By using these tactics, parents, teachers, and other caretakers can help kids build a healthy relationship with technology, live a balanced life, and build the resilience they need to handle the challenges of the digital world. The goal of these interventions is to make sure that kids' app use is good for their general health, helps them learn and get along with others, and sets them up for long-term success in the digital age.

Interactome depicts the arrangement of all atomic communications in cells, particularly with regards to protein-protein collaborations. We look at different strategies for foreseeing protein-protein collaborations utilizing grouping and structure data. A definitive objective of those methodologies is to introduce the total approach for the programmed choice of communication accomplices utilizing their amino corrosive arrangements as well as three dimensional structures, whenever known. The proposed approval of the hypothetical strategies utilizing test information would be a superior appraisal of their exactness.

Artificial Intelligence (AI) has become a hopeful tool for helping parents with different parts of raising children by giving them personalized tips, evidence-based methods, and timely solutions. This paper talks about the difficulties and possibilities of using AI to help parents. It also talks about the possible benefits and its impact on child psychology. There are a lot of ways that AI can help parents, from giving personalized advice that fits the needs of each family to intervening quickly when it spots early signs of developmental problems or parenting stress. AI makes it easier for parents to find tools, workshops, and interactive modules that are based on research. This gives parents the knowledge and trust they need to make choices about their child's growth that are based on facts. Also, AI-powered support can connect parents with similar problems, creating a sense of community and making it less embarrassing to ask for help with parenting or mental health. But there are a few problems that need to be carefully dealt with before AI can be used to help parents in a responsible and effective way. Data privacy and security are very important to protect families' safety and well-being. Important things to think about are the ethical use of data, transparency, and educated permission. Also, the accuracy and dependability of AI programs are very important when it comes to giving good advise and suggestions. To make sure everyone gets fair and equal help, efforts must be made to find and get rid of flaws. Also, AI shouldn't replace human sense and experience; it should add to them. When parents rely too much on AI, they might forget how important human contact and mental support are. To accommodate different parenting styles and views, it is important to be sensitive to culture and circumstances. In conclusion, AI-powered parenting support has a lot of promise to help parents be better parents and help children grow and learn. AI can be a useful tool for helping parents if it can solve problems related to data privacy, ethics, reducing bias, and working together with humans. Finding a balance between technology progress and human connection is important if AI is to be used to its fullest potential to give parents more power and help children grow in the best way possible.

The trillions of bacteria that live in and on our bodies make up the human microbiota, which is a very important part of keeping us healthy and protecting us from pathogenic infections. Dysbiosis is when there are changes in the composition and variety of the microbiota. This can upset the delicate balance between the host and its microbes, making the host more vulnerable to pathogens. Understanding the complicated link between microbiota and pathogens is important for coming up with effective ways to change microbiota and boost the body's defenses against infections. This study looks at how microbiota modulation affects the spread of pathogens and infections. It talks about how the makeup of microbiota affects how susceptible you are to pathogens. It shows how a healthy microbiota can protect you by making it hard for pathogens to grow and take over. The review also goes into detail about how the microbiota protects against pathogens, such as through competitive exclusion, the production of antimicrobial compounds, and the regulation of immune reactions. The study also looks at the idea of dysbiosis and how it is linked to pathogenic shifts. Disruptions in the microbiota can make it easier for pathogens to grow and make it harder for the host to fight off infections. It focuses on the need to recover microbial balance to improve the host's defenses and lower risks caused by pathogens. There is also talk about the use of probiotics, prebiotics, and fecal microbiota transplantation (FMT) as ways to change the microbiome. The goal of these interventions is to restore the diversity and function of microbes, improve the integrity of barriers, and boost the immune system's reaction to pathogens. The review shows how these methods could be used to change the microbiota and make it easier for the body to fight off infections. In conclusion, knowing how the microbiota and pathogens work together in a complicated way can help a lot when it comes to making specific interventions for microbiota modulation. Strategies that restore the balance of microbes and boost the host's defenses could stop pathogens from taking over and making people sick. More study needs to be done in this area to improve therapeutic approaches and use the microbiota to its fullest extent to fight infectious diseases.

Modulating the gut microbiota with probiotics has been identified as a promising therapeutic method for the management of gastrointestinal illnesses. The effectiveness of probiotics in the treatment of gastrointestinal disorders can only be determined by delving into their underlying mechanisms of action. Through an analysis of the underlying processes, this study hopes to provide light on the potential benefits of probiotics for treating a variety of gastrointestinal conditions. The study covers a wide variety of gastrointestinal conditions, such as IBS, IBD, and antibiotic-associated diarrhea. Modifying the gut microbiota composition, strengthening the gut barrier function, modulating the immune system, and producing beneficial metabolites are among mechanisms of action that have been investigated. The strain- and dose-specific variables essential to getting the best treatment results are also highlighted. This review, which synthesizes the current information, gives a thorough overview of the effectiveness of probiotics in treating a variety of gastrointestinal illnesses and illuminates potential avenues for further study and therapeutic use.

Background: COVID-19 has impacted Indian engineering institutions (EIs) enormously. It has tightened its knot around EIs that forced their previous half-shut shades completely down to prevent the risk of spreading COVID-19. In such a situation, fetching new enrollments on EI campuses is a difficult and challenging task, as students’ behavior and family preferences have changed drastically due to mental stress and emotions attached to them. Historically, during crisis situations, institutions have struggled to return to the normal track. Consequently, it becomes a prerequisite to examine the choice characteristics influencing the selection of EI during the COVID-19 pandemic to make it ‘normal’ for ‘new’ enrollments. The purpose of this study is to critically examine choice characteristics that affect students’ choice for EI and consequently to explore relationships between institutions’ characteristics and the suitability of EI during the COVID-19 pandemic across students’ characteristics. Quantitative research, conducted through a self-reported survey composed of a closed-ended structured questionnaire, was purposefully incorporated into the students who recently were enrolled in EIs (batch years 2020-2021) belonging to the North Maharashtra region of India. Results:The findings of this study revealed dissimilarities across students’ characteristics regarding the suitability of EIs under pandemic conditions. Regression analysis revealed that EI characteristics such as proximity, image and reputation, quality education and curriculum delivery have significantly contributed to suitability under COVID-19. At the micro level, multiple relationships were noted between EI characteristics and the suitability of EI under the pandemic across students’ characteristics. Conclusion:Bringing ‘normality’ to ‘new’ enrollments totally depends on EI’s resilience in meeting the needs of diversity in the COVID-19 pandemic situation, which repositions themselves to govern student-centric strategies instituted for the overall suitability of EI under pandemic conditions. The study has successfully demonstrated how choice characteristics can be executed to regulate the ‘suitability’ of EI under the COVID-19 pandemic for the inclusion of diversity. It is useful for policy makers and academicians to reposition EIs that fetch diversity during the pandemic. This study is the first to provide insights into the performance of choice characteristics and their relationship with the suitability of EIs under a pandemic and can be a yardstick in administering new enrollments.

Stress has been identified as a prominent contributor to the development and advancement of bowel cancer, however its specific involvement is intricate and diverse. This abstract tries to offer a concise summary of the correlation between stress and bowel cancer, consolidating significant discoveries from several research fields. The investigation commences by studying the molecular pathways by which chronic stress impacts the development of colon cancer. Chronic stress causes disruption in the functioning of neuroendocrine, immunological, and inflammatory pathways, leading to the development of a microenvironment within the gastrointestinal system that promotes the growth of tumours. Furthermore, changes in the composition of gut microbiota, variations in epigenetics, and alterations in immune function caused by stress also have a role in increasing the risk and advancing the advancement of cancer. Psychological aspects, including how one perceives stress, the tactics they use to cope with it, and the level of psychosocial support they receive, are crucial in determining a person's susceptibility to bowel cancer and impacting the effectiveness of treatment. Stress management therapies, such as cognitive-behavioral therapy and mindfulness-based stress reduction, have demonstrated potential in enhancing patient well-being and promoting adherence to treatment. Moreover, epidemiological studies and clinical trials offer vital knowledge regarding the correlation between stress and the risk, prognosis, and treatment results of bowel cancer. Although the evidence is inconclusive, it is essential to continue researching the intricate relationship between stress and bowel cancer. This will help us understand the connection better and create specific strategies to reduce its impact on patient outcomes.

The COVID-19 pandemic has forced Indian engineering institutions (EIs) to bring their previous half-shut shades completely down. Fetching new admissions to EI campuses during the pandemic has become a ‘now or never’ situation for EIs. During crisis situations, institutions have struggled to return to the normal track. The pandemic has drastically changed students’ behavior and family preferences due to mental stress and the emotional life attached to it. Consequently, it becomes a prerequisite, and emergencies need to examine the choice characteristics influencing the selection of EI during the COVID-19 pandemic. The purpose of this study is to critically examine institutional influence and pandemic influence due to COVID-19 that affects students’ choice about an engineering institution (EI) and consequently to explore relationships between institutional and pandemic influence. The findings of this quantitative research, conducted through a self-reported survey, have revealed that institutional and pandemic influence have governed EI choice under the COVID-19 pandemic. Second, pandemic influence is positively affected by institutional influence. The study demonstrated that EIs will have to reposition themselves to normalize pandemic influence by tuning institutional characteristics that regulate situational influence and new enrollments. It can be yardstick for policy makers to attract new enrollments under pandemic situations.

In this research paper, design and development of pyramidal horn antenna for J-band application is reported. It is particularly designed for 17 dB gain and half beam width about 25 degrees at 6.93 GHz. Horn aperture, horn axial length and distance from the throat of the antenna to aperture are the main design constraints which are calculated and used for the antenna design and simulation. Beam width in E-plane and H-plane horn is calculated and it is 19.18 dB and 22.86 dB respectively. The reported antenna design shows good performance for J-band in radiometry, satellite, and radar applications.

Parkinson’s Disease (PD) is a neurodegenerative and progressive disease that impacts the nerve cells in the brain and varies from person to person. The exact cause of PD is still unknown, and the diagnosis of PD does not include a specific objective test with certainty. Although deep learning has made great progress in medical neuroimaging analysis, these methods are very susceptible to biases present in neuroimaging datasets. An innovative decorrelated deep learning technique is introduced to mitigate class bias and scanner bias while simultaneously focusing on finding distinguishing characteristics in resting-state functional MRI (rs-fMRI) data, which assist in recognizing the PD with good accuracy. The decorrelation function reduces the non-linear correlation between features and bias in order to learn bias-invariant features. The Parkinson’s Progression Markers Initiative (PPMI) dataset, referred to as a single scanner imbalanced dataset in this study used to validate our method. The imbalanced dataset problem affects the performance of the deep learning framework by overfitting to the majority class. To resolve this problem, we propose a new Decorrelated Convolutional Neural Networks (DcCNN) framework by applying decorrelation-based optimization to Convolutional Neural Networks(CNN). An analysis of evaluation metrics comparisons shows that integrating the decorrelation function boosts the performance of PD recognition by removing class bias. Specifically, our DcCNN model performs significantly better than existing traditional approaches to tackle the imbalance problem. Finally, the same framework can be extended to create scanner invariant features without significantly impacting the performance of a model. The obtained dataset is a multi-scanner dataset which leads to scanner bias due to the differences in acquisition protocols and scanners. The multi-scanner dataset is a combination of two datasets, namely PPMI and FTLDNI - frontotemporal lobar degeneration neuroimaging initiative (NIFD) dataset. The results of t-distributed stochastic neighbor embedding (t-SNE) and scanner classification accuracy of our proposed Feature Extraction-DcCNN (FE-DcCNN) model validated the effective removal of scanner bias. Our method achieves an average accuracy of 77.80% on a multi-scanner dataset for differentiating PD from healthy control, which is superior to the DcCNN model trained on a single scanner imbalanced dataset.

Recent years have seen an explosion of interest in the topic of gut health and food, revealing a complex interplay that affects many facets of human health beyond just digestion. This in-depth overview investigates crucial aspects of this connection, illuminating issues including the effects of processed meals, the advantages of fermented foods, individualized diets, and the harmonious relationship between gut bacteria and dietary components. In this article, we'll take a look at how processed foods affect your digestive system, and how their convenience might backfire by upsetting your body's delicate microbial balance. The effects of these diets have been studied, and the results suggest that there may be disruptions in microbial diversity, inflammation, and metabolic health. Instead, fermented foods are explored as potential allies in the fight for gut health. These foods' high probiotic content not only improves digestion and nutrition absorption, but may also have an effect on one's state of mind. There is growing evidence that eating fermented foods can help you maintain a healthy and robust gut microbiome. Recognizing that everyone has a different gut microbiota composition, the idea of individualized nutrition has come to the forefront. One novel strategy for improving digestive health is to provide nutritional advice based on a person's unique microbial profile. This paper looks at how microbiome testing can be combined with professional advice to create food programs that feed specific bacteria communities, improving both diversity and health. In conclusion, this review emphasizes the reciprocal interaction between dietary choices and the gut microbiota, and the significant impact that gut health has on numerous aspects of human health. The more we learn about the complexities of this interplay, the more we can take a holistic approach to nutrition, one that respects the uniqueness of each person's gut microbiome and encourages healthy eating habits. By taking a more all-encompassing view, we are reminded of the critical function of the gut microbiota in determining our health and of the significance of fostering this nuanced symbiotic connection.

The stability of the gut barrier is very important for keeping the gut healthy and stopping dangerous substances from getting into the bloodstream. Several diseases, including cancer, have been linked to the gut barrier being broken. Live bacteria called probiotics that are good for the host have been shown to have the ability to improve the gut barrier and lower the risk of cancer in the gastrointestinal system. This review looks at how probiotics affect the health of the gut barrier and what that might mean for preventing cancer. Researchers have found that probiotics strengthen the connections between intestine cells, encourage the production of protective mucins, and change the make-up and balance of the gut bacteria. These processes help keep the gut barrier strong and stop harmful chemicals from getting into the bloodstream. Probiotics may help lower the chance of cancer by reducing inflammation throughout the body and protecting the GI tract from harmful substances. But more study is needed to fully understand the benefits of different probiotic strains, the best amounts to take, and how they affect the health of the gut barrier. Understanding how probiotics, the health of the gut barrier, and the risk of cancer all work together can help us come up with new ways to avoid and treat cancer.

Tumor-associated microbiota refers to the community of microorganisms found in tumors and is part of the larger tumor microenvironment (TME). The discovery of the complex relationship between these microbial populations and the growth of cancer has prompted the creation of cutting-edge tailored methods to cancer treatment. In recent years, microbiota profiling's potential as a diagnostic, prognostic, and therapeutic optimization tool has been increasingly apparent. The diagnostic and prognostic use of microbiota profiling is explored in this abstract. Microbiota profiling shows potential for early cancer detection, improved risk stratification, and greater prediction of treatment outcomes by identifying different microbial signatures associated with early-stage tumors, aggressive characteristics, and responses to treatment. In addition, this method provides the way for individualized medicinal approaches based on an individual's specific microbiome.Microbiota profiling is investigated as a means of customizing treatment plans, illuminating how knowledge of an individual's microbiome might direct the development of individualized treatments and multimodal approaches. These kind of interventions have the potential to herald in a new era of patient-centered oncology care by increasing treatment efficacy while decreasing side effects. Despite significant promise, microbiota profiling has obstacles that must be overcome before it can be successfully translated into therapeutic practice. This abstract highlights the revolutionary potential of microbiota-based approaches in cancer care and the need for ongoing research and technology improvements to harness the power of the tumor-associated microbiome for improved patient outcomes.

The gut microbiota's part in colon cancer has become an exciting and hopeful area of study because it shows complex links that affect how cancer starts, spreads, and responds to treatments. Dysbiosis, which is an imbalance in the community of germs in the gut, has been linked to a higher risk of colon cancer by causing inflammation and making a place where tumours can grow. Researchers have found that some kinds of bugs can either help colon cancer grow or stop it from doing so. This shows how important it is to maintain a healthy gut bacteria. In both preclinical and clinical research, therapeutic treatments that target the microbiome in the gut have shown promise. Probiotics and prebiotics can change the environment around a tumour, change the balance of microorganisms in the gut, and boost immune responses that fight the cancer. Faecal microbiota transfer (FMT) is being looked at as a new way to change the bacteria in the guts of people with colon cancer. By adding microbiota-targeted drugs to standard cancer treatments, it may be possible to make the treatment more effective and lessen side effects. Microbiota-focused treatments for colon cancer are still in their early stages, but they show promise. More research needs to be done to find out how they work and show that they work in the clinic. The link between the bacteria in the gut and colon cancer opens up new ways to help patients and give them better results. This might make a difference in how colon cancer is handled in the future.

Probiotics have become a potential way to change the microbiota, which allows for more personalized ways to improve health results. This abstract gives an outline of the most important parts of personalized microbiota regulation through probiotics. It focuses on effectiveness and mechanisms, clinical applications, safety and tolerability, formulations and delivery methods, and customized approaches. Many studies have looked into how and why probiotics change the microbiome. These studies show that probiotics can change the makeup and function of microbial communities. Probiotics have been shown to help treat a number of health problems, such as digestive problems, immune system problems, metabolic problems, and mental health problems. It is important for the success of probiotics to find out if they are safe and can be tolerated. Studies have shown that probiotics are usually safe for most people, but there are some things that need to be taken into account to make sure they are safe, especially for people who are weak. Formulations and transport methods are very important for making sure that probiotics are alive, stable, and delivered to the right places in the GI tract. Probiotic strains work better in the gut because of improvements in how probiotic preparation technologies protect and control the release of probiotic strains. Personalized methods take into account how each person's microbiome and health are different. By using individual microbiota profiling, custom probiotic approaches can be made to address specific microbial imbalances and promote a healthier microbial environment, which could improve treatment results. Even though individual methods show promise, there are still problems, such as the need to standardize microbiota profiling techniques, figure out how to understand data, and keep track of people over time. For personalized probiotics to reach their full potential and change the way patients are cared for based on the microbiota-host relationship, more study, technological advances, and teamwork are needed. In conclusion, probiotics can be used to change your microbiome in a way that is specific to you and your health goals. By using the power of individualized microbiota profiling, personalized probiotic treatments might be able to help with certain health problems and make the microbial environment better. Putting personalized probiotics into clinical practice and changing the way patients are cared for will require more study and partnerships between different fields.

Tobacco use is bad for your health in many ways, not just your lungs. It affects many other parts of your body, including your nervous system. This abstract looks at the link between smoking and the nervous system and shows how smoking affects the nerve system in specific ways. There are a lot of different diseases and risks that can come from smoking. By weakening blood vessels and making it easier for blood clots to form, smoking makes the chance of having a stroke much higher. Using tobacco is also linked to a drop in brain function and memory problems, as well as a higher chance of neurodegenerative diseases like Alzheimer's disease and dementia. Also, people who smoke have a higher chance of getting multiple sclerosis, which is a long-term autoimmune disease that affects the central nervous system. It can also cause peripheral neuropathy, which can damage nerves and cause tingling, pain, and stiffness in the limbs. Nicotine, the substance that makes tobacco addicting, changes the brain's reward circuits. This makes it hard to stop smoking because it leads to addiction. In addition to these effects on the body, smoking also has effects on the mind. It makes mood disorders like sadness and anxiety more likely, making the symptoms worse and hurting general health. Understanding the effects of smoking on the brain is important for improving overall health and getting people to stop smoking. Public health efforts, education, and targeted interventions are needed to make people aware of these risks and help them make choices about smoking that are based on accurate information. By looking at how smoking affects the brain, we can try to make people's lives better and protect their and their communities' well-being.

Users on the social networking platform have the freedom to express themselves freely. Towards the same time, this has created a forum for disagreement and hate directed at someone, society, racism, sexual orientation, and so on. Identifying hate online is a challenging task. Researchers from all around the world have contributed major methods for detecting hate speech, but owing to the issue's complexity, there are still many unresolved issues. In this research, we offer a multi-model learning strategy for detecting hate speech on Twitter. We utilised the Kaggle TwitterHate dataset, which had 31962 tweets categorised as binary hate or non-hate, to evaluate our technique. The suggested method is tested using commonly used machine learning classifiers with multi-model technique. Using TF-IDF features, we acquired detection results of 96.29 %, precision of 96%, recall of 96%, and f1-score of 96%.

Nuclear lamins are type V intermediate filament proteins that form a filamentous meshwork beneath the inner nuclear membrane. Additionally, a sub-population of A-type and B-type lamins is localized in the nuclear interior. The nuclear lamina protects the nucleus from mechanical stress and mediates nucleo-cytoskeletal coupling. Lamins form a scaffold that partially tethers chromatin at the nuclear envelope. The nuclear lamina also stabilizes protein-protein interactions involved in gene regulation and DNA repair. The lamin-based protein sub-complexes are implicated in both nuclear and cytoskeletal organization, the mechanical stability of the nucleus, genome organization, transcriptional regulation, genome stability, and cellular differentiation. Here we review recent research in the field of nuclear lamins and their role in modulating various nuclear processes and their impact on cell function.

A significant challenge encountered in mmWave and Sub-terahertz systems used in 5G and 1 the upcoming 6G networks is the rapid fluctuation in signal quality across various beam directions. Extremely high-frequency waves are highly vulnerable to obstruction, making even slight adjustments in device orientation or the presence of blockers capable of causing substantial fluctuations in link quality along a designated path. This issue poses a major obstacle because numerous applications with low-latency requirements necessitate precise forecasting of network quality from many directions and cells. The method that is proposed in this research demonstrates an avant-garde approach for assessing the quality of multi-directional connections in mmWave systems by utilizing the Liquid Time Constant network (LTC) instead of the conventionally used Long Short-Term Memory (LSTM) technique. The method’s validity was tested through an optimistic simulation involving the monitoring of multi-cell connections at 28 GHz in a scenario where humans and various obstructions were moving arbitrarily. The results with LTC are significantly better than those obtained by conventional approaches such as LSTM. The latter resulted in a test Root Mean Squared Error (RMSE) of 3.44 dB, while the former, 0.25 dB, demonstrating a 13-fold improvement. For better interpretability and to illustrate the complexity of prediction, an approximate mathematical expression is also fitted to the simulated signal data using Symbolic Regression.

This paper represents a groundbreaking paradigm shift in network optimization. Departing from traditional static methodologies, this innovative approach harnesses the power of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) to optimize cloud networks dynamically. By integrating advanced AI algorithms, this framework continuously adapts and evolves, ensuring optimal real-time performance. This dynamic optimization enhances efficiency and resilience, allowing cloud networks to adjust seamlessly to changing demands and conditions. Through the fusion of cutting-edge technology and adaptive intelligence, this approach heralds a new era in network optimization, empowering organizations to achieve unprecedent-ed levels of agility and scalability in their cloud infrastructures.

The ubiquitous nature of polymers have led to a widespread demand for sustainable polymers in numerous industrial applications. However, lack of well laid out guidelines, product development pathways and certifications have resulted in a lot of commotions and confusions within the polymer value chain. Herein, a meticulous review is conducted on the topic of polymer sustainability shedding light on the standards, product declarations, biobased-biomass concepts, product carbon footprint etc. It is critical that companies significantly contribute on such sustainability efforts in lieu of market readiness and competitive advantages. Any discussion within the sustainability horizon references a couple of terms/ abbreviations/concepts. In this article, such key terminologies and concepts related to polymer sustainability are reviewed with a holistic outlook on the widespread approaches within the polymer sustainability horizon.

Emerging evidence suggests that sustained diabetes-associated factors such as inflammation, hyperinsulinemia, and hyperglycemia are major contributors to aberrant cell proliferation and subsequent neoplastic transformation. Epidemiological studies have also highlighted that diabetes promoting a sedentary lifestyle, with or without the direct involvement of insulin, is frequently linked to cancer. However, our knowledge regarding the molecular mechanisms that correlate hyperglycemia to oncogenic transformations remains limited. In this regard, a recent study has proved that hyperglycemia inactivates AMPK, which results in the destabilization of the TET2 and its tumour-suppressive role ultimately predisposing diabetes mellitus patients to cancer. To the management of hyperglycemia associated with oncogenesis, we need to explore a reverse pharmacology-based ethnopharmacological approach. Botanical-derived natural products are structurally and functionally more diverse with fewer or no side effects on humans. The present review discusses the molecular link between hyperglycemia and cancer progression with the effect of natural products as therapeutic agents on the hyperglycemia-cancer associated signalling pathway.

In the contemporary era, there has been a notable surge in the systematic utilization of therapeutic drugs that exhibit stimulus-responsive drug release patterns in specific target areas. However, challenges such as premature drug release and limited biocompatibility persist. To address these issues, the application of a lipid coating on mesoporous silica nanoparticles (MSNs) has emerged as a promising strategy. This lipid coating not only enhances the stability and biocompatibility of nanocarriers but also facilitates targeted drug delivery to diseased cells while minimizing drug release throughout the body. MSNs, renowned for their unique attributes including high porosity, morphology, and controllable pore size, have been widely recognized as suitable platforms for drug/gene delivery systems. Furthermore, graphene-based nanomaterials such as graphene oxide and reduced graphene oxide have garnered significant interest in the fields of biology and biomedicine. These materials possess exceptional characteristics such as a large surface area, distinct surface properties, high biocompatibility, and pH sensitivity, making them ideal candidates for incorporating drugs, genes, photosensitizers, and other cargo to design innovative drug delivery systems. This study aims to emphasize the ongoing efforts and advancements in enhancing the capacity and versatility of nanocomposites comprising graphene MSN composites for applications in drug delivery.

The ability to self-direct a research program determines graduate degree completion. Yet, research on incompletion of graduate physics programs assume students’ present level of self-direction adequate and neglects to recognize a lack of self-directed learning as key. One theoretical mathematical physicist focused on changing this challenge of physics graduate education by promoting self-directed learning through the type research flow that has been found to bring the greatest satisfaction to researchers with respect to their insights. This he provided through his space, time, open mindedness and theoretical contributions with his students and in collaboration with his colleagues. A self-directed learner himself, David J. Rowe developed methods of mentoring for encouraging physics graduate students to recognize symmetry as valuable in identifying solutions to problems quickly—helping these students take the lead in finding insightful resolutions to complex, multidimensional, mathematical physics uncertainties. How Rowe set about supporting self-directed learning in his graduate physics education interactions will be examined with the use of narrative research to interpret the texts and conversations with the author he made available. His techniques will be presented and recommendations made regarding how Rowe’s work in this regard can be modeled to improve self-direction in STEM graduate education.

As of not long ago, understanding the administrative conduct of cells has been sought after through autonomous investigation of the transcriptome or the proteome. In view of the focal creed, it was commonly accepted that there exist an immediate correspondence between mRNA records and produced protein articulations. In any case, late examinations have demonstrated that the relationship among's mRNA and Protein articulations can be low because of different factors, for example, unique half lives and post record apparatus. In this manner, a joint investigation of the transcriptomic and proteomic information can give valuable experiences that may not be translated from singular examination of mRNA or protein articulations. This article audits the current significant methodologies for joint investigation of transcriptomic and proteomic information. We order the various methodologies into eight primary classes dependent on the underlying calculation and last investigation objective. We further present analogies with different spaces and talk about the current exploration issues around there.

Sustainability transition theories analyse a systematic shift towards sustainability at micro (niche), meso (regime) and macro (landscape) level. The assessment of technological systems and structures at the firm level in sustainability transition literature is scant. The present study, taking the technological assessment perspective at the firm level, finds answers to questions like (a) how do established corporations move towards sustainable practices? (b) what role does technological innovation play in the firm’s transition towards sustainability? (c) what technological modes are adopted for sustainability transition? We find answers to these questions through an in-depth case analysis of two multi-national companies in the consumer goods industry. Internally developed and externally acquired technologies by firms in the last 15 years are plotted using qualitative and quantitative indicators on pre-designed templates. Technologies for all three sustainability dimensions, namely, environmental, social and economic, are mapped and the impact assessed. The analysis finds a sustainability transition landscape that shows the use of protected (patents, trademarks, designs) and unprotected technologies (open innovation) to generate impacts like production efficiency, consumption reduction, emission reduction, reduce-recycle-reuse among others. Companies implementing sustainable technologies do observe positive impacts. Implementation of reduce-reuse-recycle (3R)-based technologies enhance the achievement of sustainable development targets. Furthermore, the use of trademarks seems common in differentiating their technologies and identities. These and other results are detailed and used to comment on the role of managing intellectual property and harnessing the effect of technological innovations in sustainability transition.

Spinal cord stimulation (SCS) is a therapeutic modality for the treatment of various chronic pain conditions that has rapidly evolved over the past 50 years. Unfortunately, over time, patients implanted with SCS undergo a habituation phenomenon leading to decreased pain relief. Consequently, discovery of new stimulation waveforms and SCS applications have shown to prolong efficacy and reduce explantation rates. This article explores various SCS waveforms, their applications and proposes a graded approach to habituation mitigation. We suspect the neural habituation phenomenon parallels that seen in pharmacology. Consequently we urge further exploration of early introduction of these stimulation strategies to abate spinal cord stimulation habituation.

Polymethyl methacrylate (PMMA) polymer is widely used in various fields today. In order to thoroughly reveal the structural impact performance of PMMA materials, this paper is based on the comprehensive Johnson-Cook constitutive model and damage failure model, and accurately confirm the J-C constitutive and damage failure model parameters of PMMA through material test data, The dynamic process of steel bullet impacting PMMA plate structure is analyzed by finite element software ABAQUS. The calculation results show that the numerical simulation results in this paper are in good agreement with the experimental test data. Therefore, the feasibility and accuracy of the impact analysis of PMMA structures based on J-C constitutive and damage failure models in this paper are studied. Finally, based on the J-C constitutive model and damage failure model, the variation of the residual velocity of the bullet with the PMMA plate thickness is analyzed in depth, that is, the results show that the residual velocity of the bullet has a certain linear relationship with the plate thickness.

The transverse momentum distribution of J/ψ mesons produced in pp collisions at the center-of-mass energy 5 TeV, 7 TeV，and 13 TeV is described by the modified Hagedorn function which is based on the Tsallis function and Hagedorn function. The calculated results by the modified Hagedorn function are in accord with experimental data measured by the LHCb Collaboration at LHC. The related parameters are obtained and analyzed.

Considered one of the finest first-generation Nigerian writers, John Pepper Clark-Bekederemo, who passed away on 13th October, 2020, had been categorised as a Eurocentric writer. This work assesses the authenticity or otherwise of this critics’ perception of Clark by critiquing his America, their America. By analysing this autobiography vis-à-vis the notion of self and other which is a theoretical concern in contemporary travel writing, it was established, among other things, that every culture has its dark sides which it must not feel too proud to change as time and situation demand; that Clark vehemently rejects the Americans’ claim of sophistication and superiority of their culture over African culture. The paper concludes that contemporary travel writing should be a rightful site for negotiating cultural, political and diplomatic compromises between the Self and the Other since the gulf may be difficult to close altogether.

A monolayer of endothelial cells (ECs) lines the lumen of blood vessels and as such provides a semi-selective barrier between the blood and the interstitial space. Compromise of the lung EC barrier due to inflammatory or toxic events may results in pulmonary edema, which is a cardinal feature of acute lung injury (ALI) and its more severe form, the acute respiratory distress syndrome (ARDS). The EC functions are controlled, at least in part, via epigenetic mechanisms mediated by histone deacetylases (HDACs). Zinc-dependent HDACs represent the largest group of HDACs and are activated by Zn2+. Members of this HDAC group are involved in the epigenetic regulation primarily via modifying the structure of chromatin upon removal of acetyl groups from histones. In addition, they can deacetylate many non-histone histone proteins, including those located in extra nuclear compartments. Recently, the therapeutic potential of inhibiting zinc-dependent HDACs for EC barrier preservation has gained momentum. However, the role of specific HDAC subtypes in EC barrier regulation remains largely unknown. This review aims to provide an update on the role of zinc-dependent HDACs in endothelial dysfunction and its related diseases. We will broadly focus on biological contributions, signaling pathways and transcriptional roles of HDACs in endothelial pathobiology associated mainly with lung diseases and we will discuss the potential of their inhibitors for lung injury prevention.

Cancer being a multi-factorial disease, a multi-target approach is needed to treat it with minimal side-effects. Therefore, combined use of a proven herbal formula with chemo-therapy could be the better therapeutic. It may maintain homeostasis by synergistically targeting multiple signaling pathways involved in tumorigenesis, thus circumventing recurrence, resistance, and immunosuppression. Here we aim to determine the effectiveness and safety of an FDA-approved herbal formula, SR033 in combination with 5-fluorouracil (5FU) and paclitaxel (PTX). We report chemo-sensitization and chemo-synergy in HeLa and MCF-7 cell lines, immunomodulation of COX-2, PD-L1, VEGF and TGFβ and overall survival in-vitro and in-vivo via oral and topical delivery of SR033. In-vitro, SR033/5FU significantly reverses 5FU and PTX-resistance, lower COX-2, and PD-L1, resulting in TGFβ/ VEGF axis modulation. Furthermore, the study suggests that due to anti-oxidative potential of SR033, oral administration exerts chemo-preventive activity and restores cellular compartment in solid tumor and ascites-bearing mice models. Furthermore, the topical application, SR033L with low-dose 5FU increases survival rate, reduces tumor growth, and completely restores local and peripheral neutrophil-lymphocyte ratio in solid tumor mice model. The study indicates that SR033 could be a strong candidate in combination with low-dose 5FU and PTX for a holistic approach to cancer management.

Novel coronavirus disease (COVID-19) has affected nearly 7 million individuals and claimed more than 0.4 million lives to date. There are several reports of gender differences related to infection and death due to COVID-19. This raises important questions such as “Whether there are differences based on gender in risk and severity of infection or mortality rate?” and “What are the biological explanation and mechanisms underlying these differences?” Emerging evidence has proposed sex-based immunological, genetic, and hormonal differences to explain this ambiguity. Besides biological differences, women have also faced social inequities and economic hardships due to this pandemic. Several recent studies have shown that independent of age males are at higher risk for severity and mortality in COVID-19 patients. Although susceptibility to SARS-CoV-2 was found to be similar across both genders in several disease cohorts, a disproportionate death ratio in men can be partly explained by the higher burden of pre-existing diseases and occupational exposures among men. From an immunological point of view, females can engage a more active immune response, which may protect them and counter infectious diseases as compared to men. This attribute of better immune responses towards pathogens is thought to be due to high estrogen levels in females. Here we review the current knowledge about sex differences in susceptibility, the severity of infection and mortality, host immune responses, and the role of sex hormones in COVID-19 disease.

Present study on land use land cover analysis and taluka wise combination of cropped area, carried out in Beed district of Maharashtra state in India and studied 11 talukas of the district. Secondary data on land use land cover and area in various crops has been collected, compiled and analyzed from various secondary sources. Simple descriptive statistics used to examine the agricultural land use land cover and J.C. Weaver’s crop combination technique was used for taluka wise analysis of crop combinations and on the basis of highest to smallest area engaged in particular crop, crops have been ranked. The study showed that, in the district as a whole, percentage of uncultivated land other than fallow was about 46 percent as compare to net sown area is only 35 percent in total geographical area (1063855ha) of Beed district. The study further revealed that about 42 percent area engaged in food crops and about 58 percent area occupied by nonfood crops, which includes cereals (25%), cotton (19%), pulses (13%), oilseed (12%), sugarcane (5%) and fruits and vegetables (3%). Results of Weaver’s crop combination technique showed that the Wadwani taluka demarcated as most diversified taluka by means of maximum number (sixteen) of crops combinations with the lowest variance value (14) found in the present investigation. Further, the study revealed that the high crop diversity found in Dharur taluka with eighteen crop combinations and the taluka has given first rank amongst others. To derive the crop diversity ranking, taluka wise maximum to minimum number of crop combinations derived in different talukas and given ranks accordingly. The study concluded that, agricultural land use analysis is essential for solving and optimizing the land use problem, maintaining socio-ecological balance, best utilization of scarce resources. The authors enlightened that the rational use of agricultural land has important for food security and biodiversity which increase the productivity and profitability of the agriculture sector and it indicates the decision making ability of farmers in study area.

In this paper, we present a relapse based demonstrating way to deal with investigate various arrangement MTC information. A commonplace use of this displaying approach incorporates three stages: first, define a model that approximates the connection between quality articulation and trial factors, with boundaries consolidated to address the exploration premium; second, utilize least-squares and assessing condition methods to gauge boundaries and their relating standard blunders; third, register test insights, P-qualities and NFD as proportions of factual criticalness. The benefits of this methodology are as per the following. To begin with, it tends to the exploration interest in a particular, precise way, and maximally uses all the information and other important data. Second, it represents both orderly and irregular varieties related with the information, and the consequences of such examination give not just quality explicit data applicable to the exploration objective, yet additionally its dependability, in this way helping agents to settle on better choices for subsequent investigations. Third, this methodology is truly adaptable, and can undoubtedly be stretched out to different sorts of MTC considers or other microarray explores by detailing various models dependent on the test plan of the investigations.

The pregnane X receptor (PXR) is the main nuclear receptor regulating the expression of xenobiotic metabolizing enzymes and is highly expressed in the liver and intestine. Recent studies have highlighted its additional role in lipid homeostasis, however, the mechanisms of these regulations are not fully elucidated. We investigated the transcriptomic signature of PXR activation in the liver of adult wild-type vs Pxr-/- C57Bl6/J male mice treated with the rodent specific ligand pregnenolone 16α-carbonitrile (PCN). PXR activation increased liver triglyceride accumulation and significantly regulated the expression of 1215 genes mostly xenobiotic metabolizing enzymes. Among the down-regulated genes, we identified a strong peroxisome proliferator-activated receptor α (PPARα) signature. Comparison of this signature with a list of fasting-induced PPARα target genes confirmed that PXR activation decreased the expression of more than 25 PPARα target genes, among which the hepatokine fibroblast growth factor 21 (Fgf21). PXR activation abolished plasmatic levels of FGF21. We provide a comprehensive signature of PXR activation in the liver and identify new PXR target genes that might be involved in the steatogenic effect of PXR. Moreover, we show that PXR activation down-regulates hepatic PPARα activity and FGF21 circulation, which could participate in the pleiotropic role of PXR in energy homeostasis.

This paper explores the transformative impact of computational pharmaceutics, integrating AI, multi-scale modeling, quantum computing, AI-driven drug discovery, and blockchain frameworks. Molecular dynamics simulations provide insights into atomic behaviors crucial for drug design. Quantum computing reduces computational costs for simulating protein-drug interactions. AI and Graph Neural Networks accelerate drug discovery and personalized medicine. Blockchain frameworks facilitate secure pharmacogenetic data sharing. These advancements revolutionize drug development, offering unprecedented efficiency, innovation, and personalized treatments.

Glioblastoma multiforme (GBM) is a glioma and the most aggressive type of brain tumor with a dismal average survival time, despite the standard of care. One promising alternative therapy is boron neutron capture therapy (BNCT), which is a noninvasive therapy for treating locally invasive malignant tumors, including glioma. BNCT involves boron-10-released radiation directly into tumor cells with minimal damage to healthy tissues. This therapy lacks clinically approved targeted blood-brain-barrier-permeating delivery vehicles for therapeutic drug/ boron-10. Nanoparticles, particularly gold nanoparticles (GNPs), are selective and effective drug-delivery vehicles because of their desirable properties, facile synthesis, and biocompatibility. This review discusses historical and current GNP therapeutic applications as a drug delivery vehicle for treating glioma. Furthermore, GNPs loaded with therapeutic drugs, imaging agents, and GBM-targeting antibodies/ peptides to treat GBM will be discussed. Additionally, the importance of upper and lower limits on therapeutic efficacy will be described and explored followed by highlighting their advantages, limitations, and possible toxicity. Recent research and selected important findings for GNP-mediated pharmaceutics in GBM will also be considered.

Lichen Amyloidosis (LA) is a type of cutaneous amyloidosis characterized by brownish hyperkeratotic and itchy papules on the lower leg, back, forearm or thigh. It is associated with itching and Atopic Dermatitis (AD) according to an etiopathogenetic mechanism that has not yet been fully elucidated. Currently, available therapies for this condition include oral antihistamines, laser, cyclosporine, topical corticosteroids and phototherapy, but in light of the overlap with AD, Dupilumab may also be indicated. We report the case of a female, 52 years old, suffering from AD and LA for about 27 years. She had lesions attributable to both diseases on the trunk and lower limbs associated with severe itching and had proved resistant to cyclosporine therapy. It was decided to opt for Dupilumab with induction of 2 fl of 300 mg and maintenance with 1 fl every other week. The therapy proved effective, returning a total resolution of both diseases one year after the beginning of the treatment. Dupilumab demonstrated efficacy and safety in LA related to AD and led to clinical and quality of life improvement in this patient. Therefore, Dupilumab should be considered when treating LA. Further studies should be conducted focusing on the efficacy of the drug on LA (whether or not related to AD), changes in skin lesions after discontinuation, and the safety of long-term application.

This paper seeks to model the crack propagation in of AAs (aluminum-alloys) 2524-T3 and 7050-T7452 subjected to fatigue loading at low temperature. Fatigue crack growth tests were performed on AAs 2524-T3 and 7050-T7452 subjected to constant-amplitude and actual random-spectra loading histories at room temperature of about 25 °C and at cryogenic temperature of -70 °C, respectively, to determine their crack growth properties and residual lives. The interaction mechanisms between cryogenic temperature and the fatigue load were deduced on the basis of the results of fractographic analysis. Temperature-dependent residual lives under actual random-spectrum load history were modeled based on a modified accumulation damage rule by accounting for the load interaction. Good correlation was achieved between the predictions and actual experiments, demonstrating the practical and effective use of the proposed method.

Introduction: The association of gene variants for interleukin 6(IL-6) (rs1800796), interleukin 10 (IL-10) (rs1800896) and tumor necrosis factorα (TNFα (rs1800629) with the occurrence of spontaneous preterm birth (PTB) was investigated to determine whether these genetic variants are a risk factor. Materials and methods: 199 blood samples from pregnant women who had given birth prematurely and 200 control blood samples were analyzed to determine single nucleotide polymor-phisms (SNPs) of genes for IL-6 (rs1800796), IL-10 (rs1800896) and TNFα (rs1800629). The control samples were samples from pregnant women with term delivery. Isolation of DNA was per-formed on mini-spin columns according to the manufacturer's protocol. The quality and purity of the isolated DNA were tested using a Qubit 3 fluorometer. Genotyping was performed with an ABI PRISM 7500 SDS using TaqMan SNP genotyping assays. The genotypes obtained were an-alyzed using the 7500 Software v2.3 package. Results: Carriers of the A/A genotype for the rs1800629 of the TNFα gene have 4.81 times greater chance of late-onset PTB compared to carriers of the G/G and A/G genotypes in the recessive inheritance model. The presence of the G/G genotype in the recessive inheritance model compared with the G/A and A/A genotypes for the rs1800896 of the IL-10 gene represents a potentially protective factor, with mothers in the term-birth group having an almost 2-fold lower odds of PTB in general and an almost 10-fold lower odds of early PTB. On the other hand, carriers of the A/G genotype of rs1800896 have a 1.54-fold higher chance of preterm birth in general and a 1.6-fold higher chance of late preterm birth in the super dominant inheritance model compared to the A/A and G/G genotypes in the group of mothers with PTB. In this study, no association was found between PTB and rs1800796 of the IL-6 gene. Conclusion: rs1800629 in mothers was associated with PTB. rs1800896 shows a potentially protective effect for the occurrence of PTB in this study. No association was found between PTB and rs1800796.

Treating central giant cell granuloma (CGCG) is challenging due to high recurrence rates and variable therapy responses. This study examines the efficacy of various treatments in reducing CGCG recurrence. A literature review explored outcomes of surgical excision, curettage, intralesional corticosteroid injection, and adjuvant therapy, considering factors like lesion location, size, and histological features. Aggressive surgical techniques such as en bloc resection were found to potentially lower recurrence rates compared to conservative approaches. However, treatment should be tailored to individual patient needs. Further research is needed to confirm these findings and improve treatment strategies. A concise literature review was conducted using PubMed, MEDLINE, and Google Scholar, focusing on papers published from 1986 to 2024. Search terms included "central giant cell granuloma," "recurrence," "treatment modalities," and "surgical excision". Studies reporting recurrence rates and treatment outcomes for CGCG were analyzed. Twenty-nine studies were reviewed, including six studies on surgical excision and curettage, eight studies on intralesional corticosteroid injections, six studies on calcitonin therapy, five studies on interferon alpha therapy and four studies on the therapy with denosumab. Analysis indicated that aggressive surgical treatments like en bloc resection were associated with lower recurrence rates compared to conservative methods. Predictors of recurrence included lesion size (>3 cm), location (mandible), and aggressive histopathological features. Aggressive surgical excision combined with nonsurgical methods may lower recurrence rates, while conservative techniques remain viable in some cases. Further prospective research is needed to validate these findings and enhance CGCG treatment options.

Cancer is one of the most dreaded illnesses of the 20th century, cancer is continuing to spread and is becoming more common in the 21 st century.As of right now, breast cancer seems to be the most common cancer worldwide and the leading cause of cancer-related fatalities.In present study we used different network pharmacology tools for identification of target that involved in breast cancer that network pharmacology tool used target identification and validation process in drug discovery.In present study we used UniprotKB as text mining tool for identification of breast cancer gene in that we got the 2,658 gene in that we take the 165 in study the we done the GO and KEGG enrichment analysis in that we take pathways related to the breast cancer further we used STRING for determination protein-protein interaction in that we got the interaction between NDUFA1 with NDUFA3 and EREG,MYO1B with ACTN4 and XRCC3 with XRCC2.The interaction network was drawn and the network was analyzed by Cytoscape.

DNA double-strand breaks (DSBs) trigger the Ataxia telangiectasia mutated (ATM)-dependent DNA damage response (DDR), which consists of histone H2AX, MDC1, RNF168, 53BP1, PTIP, RIF1, Rev7, and Shieldin. Early stages of B and T lymphocyte development are dependent on recombination activating gene (RAG)-induced DSBs that form the basis for further V(D)J recombination. Non-homologous end joining (NHEJ) pathway factors recognize, process, and ligate DSBs. Based on numerous loss-of-function studies, DDR factors were thought to be dispensable for the V(D)J recombination. In particular, mice lacking Mediator of DNA Damage Checkpoint Protein 1(MDC1) possessed nearly wild-type levels of mature B and T lymphocytes in the spleen, thymus, and bone marrow. NHEJ factor XRCC4-like factor (XLF)/Cernunnos is functionally redundant with ATM, histone H2AX, and p53-binding protein 1 (53BP1) during the lymphocyte development in mice. Here, we genetically inactivated MDC1, XLF, or both MDC1 and XLF in murine vAbl pro-B cell lines and, using chromosomally integrated substrates, demonstrated that MDC1 stimulates the V(D)J recombination in cells lacking XLF. Moreover, combined inactivation of MDC1 and XLF in mice resulted in synthetic lethality. Together, these findings suggest that MDC1 and XLF are functionally redundant during the mouse development, in general, and the V(D)J recombination, in particular.

Human fungal pathogen Candida albicans causes oral infectious diseases such as oral thrush in immunocompromised patients with hyposalivation, diabetes mellitus, prolonged use of anti-biotics or immunosuppressive medicines and poor oral hygiene. An anti-fungal medication classified as a BCS class II drug, Clotrimazole has high permeability and low solubility in water. It is commercially available as lozenges, which do not uniformly distribute the drug within saliva for local therapy. This results in higher dose frequency and lower patient compliance. Therefore, in this study we proposed a niosomal based subgingival film formulation of clotrimazole for enhancing drug efficacy by improving drug solubilization capacity and improving patient compliance by prolonging the release of drug at the targeted site and reducing the dose frequency to show effective anti-fungal activity. The prepared niosomal film showed good entrapment efficiency and anti-fungal activity. Niosomal film showed better release pattern than drug loaded film.

Biomarker directed selection of targeted anti-neoplastic agents such as immune check-point inhibitors, small molecule inhibitors and monoclonal antibodies form an important aspect of cancer treatment. Immunohistochemistry (IHC) analysis of the tumor tissue is the method of choice to evaluate the presence of these biomarkers. However, a significant barrier to biomarker testing on tissue is the availability of an adequate amount of tissue and need for repetitive sampling due to tumor evolution. Also, tumor tissue testing is not immune to inter- and intra-tumor heterogeneity. We describe the analytical and clinical validation of a Circulating Tumor Cell (CTC) assay to accurately assess the presence of PD-L1 22C3 and PD-L1 28.8, ER, PR and HER2, from patients with solid tumors to guide the choice of suitable targeted therapies. Analytically, the test has high sensitivity, specificity, linearity and precision. Based on a blinded case control study, the clinical sensitivity and specificity for PD-L1 (22C3 and 28.8) was determined to be 90% and 100% respectively. The clinical sensitivity and specificity was 83% and 89% for ER; 80% and 94% for PR; 63% and 89% for HER2 (by ICC); and 100% and 92% for HER2 (by FISH), respectively. The performance characteristics of the test support its suitability and adaptability for routine clinical use.

Cancer is one of the world's most serious health problems and the top cause of mortality today. S. variolaris is a valuable sea creature that has long been used as a folk medicine to cure and prevent ailments. A subcritical water extraction was used method to obtain crude extract from spikes of S. variolaris. The extract had shown antiproliferative effect in HeLa cells with an IC50 of 723.1 ± 9.73 µg/ml, but no toxicity in HEK293. Westernblot was used to detect protein expression; Bax, caspase-8, and IκBα were increased, whereas IKKα and p-NFκB-65(Ser 536) were downregulated. RNA/mRNA expression was revealed by RT-qPCR, and fold changes of caspase-3, cytochrome-c, Bax, Apaf-1, caspase-9, and Bak genes’ expression were raised. Using gel electrophoresis, the treatment groups showed more DNA fragmentation than the control group. GC-MS was used to identify the components in the crude extract; anticancer activity could be attributed to dodecanoic acid, hexadecanoic acid, and tetradecanoic acid content. In conclusion, these results showed the potential use of the crude extract of a spike from S. variolaris with anticancer activity against cervical cancer.

Land transportation is contributing to global greenhouse gas (GHG) emissions significantly. Switching from gasoline-powered vehicles to electric vehicles (EVs) is the most practical way to decarbonize land transportation. Some regions of the world have seen significant advancements in the adoption of electric vehicles, largely due to government policies through subsidies and other rules and laws that globally made the cost of acquisition and ownership more advantageous for EV owners compared to their internal combustion engine (ICE) counterparts. The success of EV adoption in Norway, China, the United States of America (USA), the European Union (EU), and India has been linked to the favorable government policies. At present, China is the largest EV market in the world, enjoying a better advantage than any other market. It also has the highest manufacturing capacity and the largest number of EVs in operation. Norway has the highest EV penetration rate, with over 90% of newly registered cars, and one of the lowest costs of ownership globally. In this review, we present the current state of EV technology and performance, together with consumer perspectives and barriers, EV regulations in the regions with the highest penetration rates, and the decarbonization of land transportation. China is competing with the USA for leadership in manufacturing and technology, especially in the areas of artificial intelligence (AI) and batteries. In order to achieve the goal of decarbonizing road transportation, we proposed that a number of factors, including government energy policies and regulatory standard development, necessary infrastructure investments and developments, AI incorporation in EVs, innovation in EV and battery technologies, and consumer perspectives, play a crucial role.

In the past thirty years, childhood obesity rates have risen significantly worldwide, affecting over 340 million children in affluent nations. This surge is intricately tied to metabolic disorders, notably insulin resistance, type 2 diabetes mellitus (T2DM), and the continually evolving spectrum of metabolic-associated (dysfunction) steatotic liver disease (MASLD). This review underscores the alarming escalation of childhood obesity and delves comprehensively into the evolving and dynamic changes of nomenclature surrounding diverse conditions of hepatic steatosis, from the initial recognition of non-alcoholic fatty liver disease (NAFLD) to the progressive evolution into MASLD. Moreover, it emphasizes the crucial role of pediatric endocrinologists in thoroughly and accurately investigating MASLD onset in children with T2DM where each condition influences and exacerbates the progression of the other. The review critically highlights the inadequacies of current screening strategies and diagnosis, stressing the need for a paradigm shift. A proposed solution involves the integration of hepatic magnetic resonance imaging assessment in the diagnostic arsenal for children showing insufficient glycaemic control and weight loss post-T2DM diagnosis, thereby complementing conventional liver enzyme testing. This holistic approach aims to significantly enhance diagnostic precision, fostering improved outcomes in this vulnerable high-risk pediatric population.

J/ψ, a charmonium bound state made of a charm and an anti-charm quark, has been discovered in the 1970s and confirmed the quark model. Because the mass of charms quarks is significantly above the Quantum Chromodynamics (QCD) scale ΛQCD, charmonia are considered as excellent probes to test perturbative Quantum Chromodynamics (pQCD) calculations. Over the past decades, they have been studied extensively at different high energy colliders. However, their production mechanisms, which involves multiple scales, are still not very well understood. Recently, in high multiplicity p+p collisions at RHIC and at the LHC, a significant enhancement of J/ψ production yield has been observed, which suggests a strong contribution from the Multi-Parton Interaction (MPI). This is different from the traditional pQCD picture where charm quark pairs are produced from a single hard scattering between partons in p+p collisions. In this work, we will report the J/ψ normalized production yield as a function of normalized charged particle multiplicity over a board range of rapidity and event multiplicity in the J/ψ→μ+μ− channel with PHENIX Run 15 p+p data at \sqrt{s}=200 GeV. The results are compared with PYTHIA 8 simulations with the MPI option on and off. Finally, the outlooks of J/ψ in p+Au and Au+p collisions along with Color Glass Condensate (CGC) predictions and of multiplicity dependent ψ(2S)/J/ψ ratio in p+p data will be briefly discussed.

Tumid Lupus Erythematosus has been the subject of heated debate as to its correct nosographic classification. In particular, its definition has changed over time, depending on the different studies performed. In this review we address the initial definition of TLE, the changes that have taken place in the understanding and placement within the classification of Lupus Erythematosus (LE), and focus on clinical, histopathological, immunophenotypical and differential diagnosis aspects.

Background: Colorectal cancer (CRC) patients experienced multiple chemotoxicity affecting treatment compliance, survival, and quality of life (QOL). Prior research shows clinician-reported chemotoxicity (i.e., grading scales or diagnostic codes) predicts rehospitalization and cancer survival. However, a comprehensive synthesis of clinician-reported chemotoxicity is still lacking. Objectives: We conducted a systematic review and meta-analysis to determine the chemotoxicity's prevalence and risk factors in CRC. Methods: A systematic search from 2009 to 2024 yielded 30 studies for review, with 25 included in the meta-analysis. Results: Pooled prevalences of overall, non-hematological, and hematological moderate-to-severe toxicities were 45.7%, 39.2%, and 25.3%, respectively. The most common clinician-reported chemotoxicities were gastrointestinal (GI) toxicity (22.9%) and neuropathy or neutropenia (17.9%). Significant risk factors at baseline were malnutritional status, frailty, impaired immune or hepato-renal functions, short telomere lengths, low gut lactobacillus levels, age, female sex, aggressive chemotherapy, and low QOL. Age was associated with neutropenia (β: -1.44) and GI toxicity (β:1.85) (Ps 65 y.o.) had higher prevalences of overall (OR: 1.14) and GI (OR: 1.65) toxicities, but a lower prevalence of neutropenia (OR: 0.65) than younger adults (Ps

In the global carbon cycle, atmospheric carbon emissions, both ‘natural’ and anthropogenic, are balanced by carbon uptake (i.e. sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago the ratio between emitted and sequestered carbon has varied considerably with atmospheric CO₂ levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil and gas. Relatively low atmospheric CO₂ levels were the norm for the past 10 million years, and during the past million years they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO₂ levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with domestication of crops and livestock leading to urbanisation and development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO₂ emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance it is important to understand the roles of high-capacity carbon sequestration systems, such as natural forests and tropical croplands, and to devise strategies to facilitate net CO₂ uptake.

Driven by the growing interest of the scientific community and the proliferation of research in this field, cranial implants have seen significant advancements in recent years regarding design techniques, structural optimisation, appropriate material selection and fixation system method. Custom implants not only enhance aesthetics and functionality but are also crucial for achieving proper biological integration and optimal blood irrigation, critical aspects in bone regeneration and tissue health. This research aims to optimize the properties of implants designed from triply periodic minimal surface structures. The gyroid architecture is employed for its balance between mechanical and biological properties. Experimental samples were designed varying three parameters of the surface model: cell size, isovalue and shape factor. Computational simulation tools were used for determining the relationship between those parameters and the response variables: the surface area, permeability, porosity and Young modulus. These tools include computer aided design, finite element method and computational fluid dynamics. With the simulated values, the corresponding regression models were fitted. Using the NSGA-II, a multi-objective optimisation was carried out, finding the Pareto set which includes surface area and permeability as targets, and fulfil the constraints related with the porosity and Young modulus. From these non-dominated solutions, the most convenient for a given application was chosen, and an optimal implant was designed, from a patient computed tomography scan. An implant prototype was additively manufactured for validating the proposed approach.

The allosteric SERCA (Sarcoplasmic/Endoplasmic Reticulum Ca2+-ATPase) activator CDN1163 has been recently added to the group of pharmacological tools for probing SERCA function. We chose to investigate the effects of the compound on T lymphocyte Ca2+ stores, using the well-described Jurkat T lymphocyte as a reliable cell system for Ca2+ signaling pathways. Our study identified the lowest concentrations of the SERCA inhibitors thapsigargin (TG) and 2,5-di-(tert butyl)-1,4-benzohydroquinone (tBHQ) capable of releasing Ca2+, permitting the differentiation of the TG-sensitive SERCA 2b Ca2+ store from the tBHQ-sensitive SERCA 3 Ca2+ store. We proceeded to test the effects of CDN1163 on Ca2+ stores, examining specific actions on the SERCA 2b and SERCA 3 Ca2+ pools using our low dose SERCA blocker regimen. In contrast to previous work, we find CDN1163 exerts complex time-sensitive and SERCA isoform-specific actions on Ca2+ stores. Surprisingly, short-term exposure (0-30 minutes) to CDN1163 perturbs T cell Ca2+ stores by suppressing Ca2+ uptake with diminished Ca2+ release from the SERCA 2b-controlled store. Concomitantly, we find evidence for a SERCA-activating effect of CDN1163 on the SERCA 3 regulated store, given the observation of increased Ca2+ release inducible by low dose tBHQ. Intriguingly, longer-term (>12 hours) CDN1163 exposure reversed this pattern, with increased Ca2+ release from SERCA 2b-regulated pools, yet decreased Ca2+ release responses from tBHQ-sensitive SERCA 3 pool. Our results reveal differential effects of CDN1163 on Ca2+ stores regulated by distinct SERCA isoforms, prompting the need for careful interpretation of the compound’s effects, particularly in cells expressing multiple SERCA isoforms.

OBJECTIVE: Recent worldwide outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of respiratory coronavirus disease 2019 (COVID-19), is a current, ongoing life-threatening crisis and international public health emergency. The early diagnosis and management of the disease remains a major challenge. In this review, we aim to summarize the updated epidemiology, causes, clinical manifestation and diagnosis, as well as prevention and control of the novel coronavirus SARS-CoV-2.MATERIALS AND METHODS: A broad search of the literature was performed in “PubMed” “Medline” “Web of knowledge”, and “Google Scholar” World Health Organization-WHO” using the keywords “severe acute respiratory syndrome coronavirus”, “2019-nCoV”, “COVID-19, “SARS”, “SARS-CoV-2” “Epidemiology” “Transmission” “Pathogenesis” “Clinical Characteristics”. We reviewed and documented the information obtained from literature on epidemiology, pathogenesis and clinical appearances of SARS-CoV-2 infection.RESULTS: The global cases of COVID-19 as of April 2, 2020 have risen to more than 900,000 and morbidity has reached more than 47,000. The incidence rate for COVID-19 has been predicted to be higher than the previous outbreaks of other coronavirus family members, including those of SARS-CoV and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). The main clinical presentation of SARS-CoV-2 infection ranges from asymptomatic stages to severe lower respiratory infection in the form of pneumonia. Most of the patients also presented with fever, cough, sore throat, headache, fatigue, myalgia and breathlessness.Individuals at higher risk for severe illness include elderly people and patients with a weakened immune system or that are suffering from a underlying chronic medical condition like hypertension, diabetes, cancer, respiratory illness or cardiovascular diseases.CONCLUSIONS: SARS-Cov-2 has emerged as a worldwide threat, currently affecting 170 countries and territories across the globe. There is still much to be understood regarding SARS-CoV-2 about its virology, epidemiology and clinical management strategies; this knowledge will be essential to both manage the current pandemic and to conceive comprehensive measures to prevent such outbreaks in the future.

Poly lactic acid (PLA) has made inroads for commercial market segment with lot many unique characteristics such as tenacity, low flame rate, moisture regain percentage, loss of ignition percentage, heat of combustion, UV resistance, Elastic recovery and higher melting point allowed it to be the fastest moving material in today's commercial market. An attempt has been made to test the feasibility and biocompatibility aspect of PLA with cement mix. The basic strength and physical test results were carried out and published in an article, to the continuation of the work, micro-structural study was conducted to evaluate the elemental characteristics. Thermo gravimetric analysis revealed that PLA either in granular form or filament will hold good for the inclusion into construction applications, provided degradation aspects are to be looked out for improvisation. From DSC it was found that PLA in filament form is the best inclusion material for construction application, however the tenacity of fibers has to checked, as currently available filaments in market does not have high tenacity value. From EDX reports, 30% inclusion of PLA as replacement for fine aggregate has constituent members as Calcium carbonate(CaCO3), Silica(SiO2) and Wollastonite (CaK) resulted in best composition among the rest. FESEM images revealed that, proper gradation in size, rough surface of PLA granular form or filament form will definitely enhance the mechanical/physical or even chemical behavior of PLA.

This study presents a detailed computational investigation aimed at identifying and evaluating potential small organic molecular scaffolds as inhibitors targeting the Pks13 protein, a critical enzyme in tuberculosis (TB) drug discovery. Our approach integrates multiple computational techniques, including quantitative structure-activity relationship (QSAR) modelling, compound library generation, molecular docking, biological activity prediction, re-evaluation of screened compounds, molecular dynamics (MD) analysis, and binding free energy estimation using the MM-GBSA approach. We developed a robust QSAR model using multiple linear regression (MLR) techniques, specifically tailored to predict the minimum inhibitory concentration (MIC) values of potential anti-TB agents. This model demonstrated excellent predictive performance, validated through rigorous internal and external validation procedures. Through molecular docking simulations, we identified five promising inhibitors Ethyl (R,Z)-2-(2-((2-chlorobenzyl) oxy)benzylidene)-5-(4-chlorophenyl)-7-methyl-3-oxo-2,3-dihydro-5H-thiazolo [3,2-a] pyrimidine-6-carboxylate (PKD1), (7R,9aR)-7-(2-hydroxyphenyl)-4-(2-methoxyphenyl)-3-methyl-7,8,9,9a-tetrahydroisoxazolo[5,4-b]quinolin-5(6H)-one (PKD2), (7-(4-methoxy phenyl)-2-methyl-3-phenylpyrazolo[1,5-a]pyrimidin-5-yl)(4-(3-(trifluoromethyl)phenyl) piperazin-1-yl)methanone (PKD3), (8S,10S)-10-(((2R,4S,5S,6S)-4-amino-5-hydroxy-6-methyl tetrahydro-2H-pyran-2-yl)oxy)-6,8,11-trihydroxy-8-(2-hydroxyacetyl)-1-methoxy-7,8,9,10-tetra-hydrotetracene-5,12-dione (PKD4), 3-(3,4-dimethylphenyl)-5-((2-(4-fluorophenyl)-2-oxoethyl) thio)-6-phenyl-2-thioxo-2,3,5,7a-tetrahydrothiazolo[4,5-d]pyrimidin-7(6H)-one (PKD5)with high binding affinities, prioritizing them based on their binding energies. These selected compounds were further assessed for their biological activity predictions, guiding the selection of candidates for experimental validation. Subsequent re-evaluation using absolute binding free energy estimation and MD simulations provided insights into the stability and dynamics of the protein-ligand complexes over time. Our findings highlighted the potential of identified compounds as stable binders within the Pks13-TE domain binding pocket, underscoring their viability as drug candidates. Additionally, binding free energy analysis using MM-GBSA reaffirmed the strong affinity of the proposed compounds towards Pks13. Our integrated computational approach offers a systematic and detailed framework for the identification and characterization of potential Pks13 inhibitors with specific relevance to TB drug discovery.

Mitochondria are semiautonomous organelles, which are pivotal for the energy metabolism of eukaryotic cells. These organelles contain their own genetic system (mtDNA, mitogenome) that encodes to some structural RNAs and organellar proteins. The biogenesis and function of mitochondria is tightly regulated by nuclear-encoded protein cofactors. The mtDNAs of land plants are characteristically large, with a complex mode of gene organization and expression, in particularly at the post-transcriptional level. To become functional, the primary organellar transcripts undergo extensive maturation steps, which include endo- and exo-nucleolytic cleavage, RNA-base editing, and both ‘cis’- and ‘trans’-splicing events. These essential processing steps rely on the activities of a large set of nuclear-encoded factors. Among these, the RNA helicases serve as key players in organellar (mt-)RNA metabolism. This review summarizes the important roles played by these factors in regulating the highly dynamic processes of transcription, RNA processing, and translation within the mitochondria of land plants. We further discuss recent advancements in understanding how dysregulation of mitochondrial RNA helicases affects the organellar gene expression, respiratory functions, and hence the growth, development and physiology of land plants.

Medical image segmentation is a critical step in various healthcare applications, aiding in diagnosis, treatment planning, and disease monitoring. In this study, we investigate the efficacy of a segmentation approach based on the 2D wavelet transform. Leveraging a dataset comprising 10 diverse medical images, we evaluate the performance of our segmentation method using three key metrics: accuracy, precision, and recall. Our findings demonstrate that the proposed approach enhances segmentation accuracy, offering promising results compared to existing methods. By harnessing the multi-resolution feature extraction capabilities of the 2D wavelet transform, our method achieves improved delineation of medical image structures, paving the way for more accurate and efficient healthcare interventions.

We describe a forecast system based on the Weather Research and Forecasting (WRF) model for the prediction of high-impact weather events affecting power utilities, particularly conditions conducive to wildfires. The system was developed for Pacific Gas and Electric Corporation (PG&E) to operationally forecast conditions in Northern and Central California. It was established in 2014 and has been periodically improved. In the current configuration, WRF forecasts are routinely performed multiple times each day on a 2-km grid, and the results are used as input to wildfire fuel moisture, fire probability, and wildfire spread models. Components of the system include a stochastically perturbed ensemble; an annually updated reanalysis covering more than 30 years; and validation against PG&E’s extensive mesonet and other observing networks. We describe the development and validation of the next operational edition. Configurations tested include irrigation triggered by crop growing season and an ensemble-based approach with intelligently sub-selected Global Ensemble Forecast System (GEFS) members. The latter approach allows for enhanced uncertainty sampling in WRF forecasts and can greatly improve WRF forecasts when calibrated by observations.

Authentic learning opportunities that simulate full scale design and construction experiences using real materials offer ideal experiential learning environments for construction and civil engineering students by challenging students to apply building concepts in practical settings. However, the excessive cost of real building materials required for this mode of education limits access to the vast majority of students. As a result, educational researchers have explored potential alternatives to provide cost-effective experiential learning through activities using mock-up materials (e.g., plastic straws, popsicle sticks) and simulation of experiences using immersive technologies (e.g., virtual reality or augmented reality). While some of these alternatives approximate the environment and others provide physical interaction with mock-up materials, the lack of authenticity in the building materials used introduces some apparent differences between the “authentic” learning environments and their cost-effective approximations. Therefore, this research aims to identify the learning processes reported by students and faculty who participated in authentic learning experiences to understand the ways in which this mode of education offers unique value to construction education. Their interview responses illustrated characteristics of authentic learning experiences that were believed to be critical to the learning process, some of which included: working in groups; interdisciplinary participants; and use of real construction materials. Although some of these characteristics are intrinsically linked to the use of real materials, others do not explicitly refer to interaction with real materials. This may indicate to aspects of the authentic learning processes that educational researchers can strategically target through more cost-effective learning environments like virtual and augmented reality. The contribution of this paper is in identifying the characteristics of authentic learning experiences that may guide educational investment and research innovations that aim to replicate some of these learning experiences through more accessible learning environments.

Introduction: Vitamin B1 (thiamine) deficiency (TD) after metabolic and bariatric surgery (MBS) is often insidious and, if unrecognized, can lead to irreversible damage or death. As TD symptoms are vague and overlap with other disorders, we aim to identify predictors of recurrent TD and failure to collect B1 labs. Methods: We analyzed a large sample of data from patients with MBS (n=878) to identify potential predictors of TD risk. We modeled recurrent TD and failure to collect B1 labs using classical statistical and machine learning (ML) techniques. Results: We identified clusters of labs associated with increased risk of recurrent TD: micronutrient deficiencies, abnormal blood indices, malnutrition, and fluctuating electrolyte levels (aIRR range: 1.62-4.68). Additionally, demographic variables associated with lower socioeconomic status were predictive of recurrent TD. ML models predicting characteristics associated with failure to collect B1 labs achieved 75-81% accuracy, indicating that clinicians may fail to match symptoms with the underlying condition. Conclusion: Our analysis suggests that both clinical and social factors can increase the risk of life-threatening TD episodes in some MBS patients. Identifying these indicators can help with diagnosis and treatment.

Antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are multi-targeted and variable over time. Multiplex quantitative serological assays are needed to provide accurate and robust seropositivity data for establishment of serological signatures during vaccination and or infection. We describe here, validation and evaluation of an electro-chemiluminescence (ECL) based Mesoscale Discovery assays (MSD), for estimation of total and functional IgG to SARS-CoV-2 spike, nucleocapsid, and receptor binding (RBD) proteins in human serum samples to establish serological signatures of SARS-CoV-2 natural infection and breakthrough cases. The 9-PLEX assay was validated as per ICH, EMA and US FDA guidelines using a panel of sera samples including the NIBSC/WHO international reference panel (20/268). Assay demonstrated high specificity and selectivity in inhibition assays, wherein the homologous inhibition was more than 85% and heterologous inhibition was below 10 %. Assay also met predetermined acceptance criteria for precision (CV < 30 %), accuracy (70-130 %) and dilutional linearity. Method applicability to serological signatures was demonstrated using sera samples (N=45) representing vaccinated, infected and breakthrough cases. The method was able to establish distinct serological signatures and thus provide potential tool for seroprevalence of SARS-COV-2 during vaccination or infection.

In this data deposit, I describe a dataset that is the result of content mining 167,318 published articles for statistical test results. As a result of this content mining, 688,112 results from 50,845 articles were extracted. In order to provide a comprehensive set of data, the statistical results are supplemented with metadata from the article they originate from. The dataset is provided in a comma separated file (CSV) in long-format. For each of the 688,112 results, 20 variables are included, of which seven are article metadata and 13 pertain to the individual statistical results (e.g., reported and recalculated p-value). A five-pronged approach was taken to generate the dataset: (i) collect journal lists, (ii) spider journal pages for articles, (iii) download articles, (iv) add article metadata, and (v) mine articles for statistical results.

In the dynamic interplay between people and their physical environments, the Global South stands as a mosaic undergoing a multitude of transformative influences in architecture and urbanism where examining social sustainability becomes imperative. While prevailing attention remains on environmental and economic sustainability, this study addresses a persistent gap in the urban literature by focusing on the dynamic and manifold nature of social sustainability. Positioning itself within the context of sustainable development, the study links the pursuit of social aspects of sustainability with selected unique urban contexts from the Global South. Five cases that include Alexandria (Egypt), Tripoli (Libya), Basra (Iraq), Lilongwe (Malawi), and Accra (Ghana) are discussed through multi-layered investigations that involve attitude surveys, interviews, focus groups, participatory systematic observations, and behavioral mapping, engaging directly with inhabitants and stakeholders. Uncovering people-place narratives in the identified contexts, the cases are developed into five knowledge typologies that serve as practical tools for planning and design decision-making, policy formulation, and academic discourse. Discussions are conceived to demonstrate the transformative role people-place narratives play in fostering a more sustainable and equitable urban future. Conclusions are drawn to offer practical insights for stakeholders involved in various capacities in shaping the urban landscape of the Global South.

Peanut hulls (PH) are an edible food waste that is an underutilized food source for human consumption. While edible and palatable, they are mainly diverted to livestock feed or building materials. Here, we describe existing literature on human food valorization of PHs and propose methods to optimize recapturing nutrients (e.g. protein, fiber, polyphenols) lost by treating PHs as waste. Incorporated into common foods, PHs can be processed into functional ingredients to improve nutrient-density and the corresponding positive health outcomes associated with increases in plant foods. PH valorization can also address additional priorities of the UN Sustainable Development Goals using a Food Systems Approach (FSA) including food waste, increasing economic opportunities for farmers, and increasing the availability of healthy shelf-stable foodstuffs to address food security. Recent advances in sustainable food processing technologies can be utilized to safely incorporate peanut hulls into human food streams. We propose future applications that could make meaningful impacts to food availability and the nutritional composition of common foods. While the limited literature on this topic spans several decades, no global operations exist to incorporate peanut hulls and most publications precede the technological ‘green revolution’. The approaches outlined in this review may help bolster commercialization of this underutilized and nutritious food potentially improving opportunities for multiple global stakeholders.

This study investigates the electrical characteristics observed in n- channel and p-channel ferroelectric field effect transistor (FeFET) devices fabricated through a similar process flow with 10 nm of ferroelectric hafnium zirconium oxide (HZO) as the gate dielectric. The n-FeFETs demonstrate a faster complete polarization switching compared to the p-channel counterparts. Detailed and systematic investigations using TCAD simulations reveal the role of fixed charges and interface traps at the HZO-interfacial layer (HZO/IL) interface in modulating the subthreshold characteristics of the devices. A characteristic crossover point observed in the transfer characteristics of n-channel devices is attributed with the temporary switching between ferroelectric-based operation to charge-based operation, caused by the pinning effect due to the presence of different traps. This experimental study helps understand the role of charge trapping effects in switching characteristics of n- and p-channel ferroelectric FETs.

Several lines of evidence indicate that high proliferative bias in eutopic endometrium during secretory phase is a hallmark of endometriosis and that high occurrence of implantation failure in patients resulting in infertility is often associated with endometriosis. ErbB family of proteins, which regulate the proliferation capacity in mammalian cells, appear as potential group of proteins to cause higher proliferation and endometrial hostility to implantation process in endometriosis. However, we have no concrete knowledge regarding the involvement of ErbB family in human endometrium during the ‘implantation window’, i.e., days 20-24 of a typical ovulatory cycle in endometriosis associated infertility. In the present study, the cellular profiles of immunopositive ErbBs-1 to -4 in endometrium of endometriosis-free, infertile women (Group 1; n=11), and in eutopic endometrium of infertile women diagnosed with stage IV ovarian endometriosis (Group 2; n=13) during mid-secretory phase were examined and compared using standardized WERF EPHect guidelines. Computer-aided standardized combinative analysis of immunoprecipitation in different compartments revealed an overexpression of ErbB-1 in the epithelial, stromal and vascular compartments along with marginally higher ErbB-3 expressions (P< 0.06) in the vascular compartment and ErbB-4 expression (P< 0.05) in the glandular epithelium and stroma in endometrium during the window of implantation of women with primary infertility associated with stage IV ovarian endometriosis compared with disease-free endometrium from women. A global overexpression of ErbB-1 in the endometrium during implantation window may induce anomalous proliferative, inflammatory and angiogenic activities in it, which antagonizes endometrial preparation for embryo implantation.

Recently, ice with the stacking disorder structure, consisting of random sequences of cubic ice (Ic) and hexagonal ice (Ih) layers, is reported to be more stable than pure Ih/Ic. While, due to a much lower free energy barrier of heterogeneous nucleation, in practice, the freezing process of water is usually controlled by heterogeneous nucleation which is triggered by an external medium. Herein, molecular dynamic simulations were carried out to explore the polymorph dependence of ice on the lattice structure of substrates. It turns out that, during the nucleation stage, the polymorph of ice nuclei can be severely altered by the graphene substrate, on which the Ih was found to occupy an absolute majority in new-formed ice. This can be attributed to the structure similarity between graphene and basal face of Ih. Besides the nucleation stage, our results suggest that the substrate can not affect the polymorph of ice which is far from the graphene surface. The polymorph selectivity of graphene to Ih will diminish with the growth of ice layer.

The collection of forty-nine 8-hydroxyquinoline derivatives, substituted at C5, C6 or C7, was designed and studied by computational methods of modified POM analysis, using SwissADME, Osiris and Molinspiration tool. POM analysis (Petra/Osiris/Molinspiration) and its modified version using SwissADME instead of Petra software are indisputably tools of modern chemoinformatics, often published in the professional literature as well as in the field of research of new antibacterial active compounds, developed to replace existing antibiotics that fail due to increased resistance of bacteria. NitroxolineTM and the group of 8-hydroxyquinoline derivatives with their broad antibacterial effect and the possibility of extensive derivatization of the skeleton, represent a promising direction in the research of new antibacterial active substances. Twenty 8-hydroxyquinoline derivatives were also evaluated on their antibacterial activity against eight selected G+ and G- bacterial strains with a defined resistance mechanism. All structures were in accordance with Lipinski's criteria, twenty-one structures were interesting from the point of view of individual or average value of the bioactivity prediction score and fourteen structures showed one or more mechanisms of toxicity prediction. Furthermore, eleven structures showed a low rate of GI absorption or the inability to cross the BBB barrier, fourteen substances showed a BRENK or PAIN warning, eleven substances are an undesirable substrate of P-glycoprotein and all structures predicted the same level of bioavailability and a relatively low rate of metabolism in the liver. Five structures were selected by the intersection of the POM criteria. The virtual structures 17, 25, 35 and 43 can be favored for the continuity of next study. The resulting scores of bioactivity can indicate the potential of studied structures to be used for the design and development of new active antibacterial agents.

This study explores the implementation of the ANSI/373: Sustainable Production of Natural Dimension Stone standard within the North American dimension stone industry to identify driving forces behind the initiative and consider potential outcomes as it advances. The method involves a thorough review of ANSI/373, comparing it with voluntary sustainability initiatives (VSIs) in the forest industry to assess its effectiveness and challenges, and semi-structured interviews with contacts in the dimension stone field. Key drivers such as corporate social responsibility and market pressures influence the adoption of sustainability standards. The results highlight the embedded environmental considerations within the emerging dimension stone standards and their implications for sustainable practices in the industry. While the ANSI/373 standard promotes sustainable awareness and practices, it faces challenges in certification credibility and industry acceptance, particularly due to inconsistency among firms in their response, rigorous certification demands, and skepticism about certification credibility. The research advocates for enhanced collaborative frameworks to increase the standard’s adoption and impact, suggesting that industry stakeholders prioritize showcasing dimension stone as a practical, environmentally considerate material.

Since the discovery of transposable elements (TEs) in Maize in the 1940s by Barbara McClintock [1] transposable elements have been described as junk, as selfish elements with no benefit to the host, and more recently as major determinants of genome structure and genome evolution. TEs are DNA sequences that are capable of moving to new sites in the genome and make additional copies while doing so. To limit the propagation of TEs, host silencing mechanisms are directed at transposon-encoded genes that are required for mobilization. The mutagenic properties of TEs, the potential of TEs to form new genes and affect gene expression, together with the host silencing mechanisms shape eukaryotic genomes and drive genome evolution. While TEs constitute more than half of the genome in many higher eukaryotes, transposable elements in the nematode C. ele-gans form a relatively small proportion of genome, about 15% [2]. Genetic studies of transposon silencing and the discovery of RNAi in C. elegans, propelled C. elegans to the forefront of studies of RNA-based mechanisms that silence TEs. Here, I will review the transposable elements that are present and active in the C. elegans genome, and the host defense mechanisms that silence these elements.

Over the last several decades there has been an arms race to acquire credentials as higher education has shifted from an elitist system to mass education. From an individual perspective, given the higher education system and labor market conditions, it is rational to pursue advanced qualifications. However, whether the education system delivers improvements in human capital or is principally a signaling mechanism is questionable. Estimates of the proportion of labor market rewards due to signaling range as high as 80%, suggesting that education is not only expensive but inefficient. In an increasingly transactional environment in which education providers are highly motivated by financial considerations, this situation is only likely to be exacerbated by the rapid developments in AI. The use of AI has the potential to make learning more effective but, given that many students see credential acquisition as transactional, it may reduce both human capital and the value of the signaling effect. If the credibility of the credentials offered is further damaged, the sustainability of the higher education sector in its present form and scale may well be unsustainable. We examine the evidence on credential inflation, returns to education and mismatch of graduates to jobs before analyzing how AI is likely to affect these trends. We then suggest possible responses of prospective students, education providers and employers to the growing adoption of AI in both education and the workplace. We conclude that the current offerings of generalist degrees, as opposed to vocational qualifications, are not sustainable and that to survive, even in a downsized form, the sector must respond to this disruptive technology by changing both the nature of its offerings and its methods of ensuring that the credentials they offer reflect genuine student learning.

This study was conducted to investigate the effect of supplementing different types of methionine (L and D-type) and its precursor (HMBi) on milk protein synthesis using immortalized bovine mammary epithelial cell line (MAC-T Cell); D-methionine (D-Met), L-methionine (L-met) and 2-hydroxy-4-methylthiobutanoic acid I (HMBi), an isopropyl ester of the hydroxy analogue precursor of methionine. The underlying mechanism of milk protein synthesis by adding D- and L-type amino acid as well as HMBi was elucidated through omics analysis to verify the metabolism pathway. Results showed that HMBi group showed the highest beta casein mRNA expression levels compared to D- and L-Met groups and highest medium protein although not different with the L-Met treatment. The observed upregulated (>2 protein expression vs. control) and downregulated (<0.5 protein expression vs. control) proteins in L-Met, D-Met and HMBi treated groups were: 39, 77; 46, 68; and 40, 78, respectively. Interestingly, based on protein pathway analysis, L-Met treated group stimulated the ATP synthesis, PI3 kinase and pyruvate metabolism. On the other hand, the D-Met group stimulated fructose-galactose metabolism, glycolysis pathway, PI3 kinase and pyruvate metabolism. And lastly HMBi-treated group stimulated pentose phosphate pathway and glycolysis pathway. Metabolite analysis revealed that L-Met treated group resulted in the increase in 11 metabolites. On the other hand, D-Met treated group showed increase in 7 metabolites and decreased of uridine monophosphate (UMP). HMBi supplementation caused increases of 3 metabolites and decreased of UMP and N-acetyl-L-glutamate Addition of different isoforms of Met stimulated the production of intermediate metabolites for energy production. Addition of L-Met stimulated the production of energy metabolites such as pyruvate, malate, and fumarate, well-known as intermediates of Krebs cycle. On the other hand, HMBi supplementation resulted in increases of energy metabolite glucose 1-phosphate and 6-phosphogluconate. Results showed that HMBi-treated group exhibited highest expression of β-casein mRNA expression by stimulating proteins and metabolites as well as protein and metabolic pathways involved in protein and energy synthesis. As a result, HMBi-treated group resulted in highest protein concentration but not significantly different with L-Met. Both the D- and L-isoforms has considerably the same medium protein concentration and β-casein mRNA expression higher than the control. So, D- and L-Met isoforms can be used alternatively without any significant change in protein synthesis efficiency in bovine mammary epithelial cells.

Contaminants of Emerging Concern (CECs), a new category of contaminants in limelight, is a major issue of global concern. The pervasive nature of CECs and its harmful effects, such as cancer, reproductive disorders, neurotoxicity etc., make the situation alarming. The perilous nature of CECs lies in the fact that even very small concentration of CECs can cause great impacts on living beings. It also has a nature of bioaccumulation. Thus, it is the ultimate need to have efficient sensors for detection of CECs to ensure safe living environment. Electrochemical sensors are an efficient platform for CEC detection as they are highly selective, sensitive, stable, reproducible, and prompt, and can detect very low concentrations of analyte. Major classes of CECs are pharmaceuticals, illicit drugs, personal care products, endocrine disruptors, newly registered pesticides, and disinfection by-products. This review focusses on CECs, including their sources and pathways, health effects caused by them, and electrochemical sensors as reported in literatures under each category for the detection of major CECs.

Loneliness is becoming prevalent across Japan in spite of its a dense population and communal culture. Surveys show 40% of adults report isolation across demographics. The contradiction emerges due to deteriorating social structure with modernization, economic parity, urbanization, and fading conventional setup. The continually social withdrawals, called “hikikomori." Relief seekers have embraced AI based emotive robots, digital avatars, and immersive VR as low-stakes social surrogates despite limited capacity to cultivate human intimacy. To stabilise government attempts awareness through reforms, scheme and support services. But a concrete transformation can be brough in with work-life balance, gender equality and rewire the metrics for self-esteem. Even a perfectly personalized AI cannot replace the human affection lacking in the society. Lasting solutions demand technological aids be balanced by confronting and reinventing community purpose and bring in structural change. Overall Japan’s endemic isolation reveals the societal fraying when modernization privileges independence over interdependence. The path forward rests on restoring cultural foundations to reverse loneliness and social isolation.

The study was done to determine the effect of supplementing different forms of L-methionine (L-Met) and acetate on protein synthesis in immortalized bovine mammary epithelial cell line (MAC-T Cell): Control, L-Met, conjugated L-Met and acetate (CMA), and non-conjugated L-Met and Acetate (NMA). Protein synthesis mechanism was determined by omics method. NMA group had the highest protein content in the media and β-casein mRNA expression levels (P < 0.05). The number of upregulated and downregulated proteins observed were 77 and 62 in CMA group and 50 and 81 in NMA group from 448 proteins, respectively (P < 0.05). NMA and CMA treatments stimulated pathways related to protein and energy metabolism (P < 0.05). Metabolomic analysis also revealed CMA and NMA treatments resulted in increases of several metabolites (P < 0.05). In conclusion, NMA treatment increased protein concentration and expression level of β-casein mRNA in MAC-T cells compared to CMA.

Macrophages are well known for the involvement in the biocompatibility, as well as biodistribution, of nano(bio)materials. Although there are a number of rodent cell lines, they may not fully recapitulate primary cell responses; particularly for those of human cells. Isolation of tissue resident macrophages, from humans, is difficult and may result in insufficient cells with which to determine the possible interaction with nano(bio)materials. Isolation of primary human monocytes, and differentiation to monocyte-derived macrophages, may provide a useful tool with which to study, further, these interactions. To that end, we developed a standard operating procedure for this differentiation, as part of the REFINE project, and used it to measure the secretion of bioactive molecules from M1 and M2 differentiated monocytes in response to model nano(bio)materials, following an initial assessment of pyrogenic contamination which may confound, potential, observations. The SOP was deployed in two partner institutions with, broadly, similar results. The work presented here shows the utility of this assay but, highlights the relevance of donor variability in responses to nano(bio)materials. Whilst donor variability can provide some, logistical, challenges to application of such assays, this variability is much closer to the heterogeneous cells that are present in vivo, compared to homogeneous, non-human, cell lines.

Purpose: To report a novel application of excimer ablation for normalization of central corneal refractive irregularity, combined with higher fluence CXL in the effective management and visual rehabilitation of progressive keratoconus. Methods: 17 cases with progressive keratoconus were treated with a corneal surface excimer laser ablation normalization using the topographyguided (Contura) myopic ablation for customized corneal re-shaping using a 6mm optical zone. The epithelial removal was accounted for by adding a -2.75 diopters correction in the topographyguided normalizing surface ablation followed by, a second, wavefront-optimized hyperopic excimer treatment of + 2.75 diopters at 6mm optical zone. The 2 sequential excimer ablations were followed by the corneal crosslinking (CXL). Visual acuity, refraction, and keratoconus documentation via keratometry, topography, and pachymetry, as well as endothelial cell density were evaluated over 36 months. Results: Keratoconus stabilized in all cases. The severity of keratoconus stage by Amsler-Krumeich criteria improved for the OD from an average 2.2 to 1. Mean UDVA showed marked improvement at one-year follow-up all values in decimal: from 0.21±0.18 pre-operative to 0.51±0.25 at 12 months, with small additional improvement through the 3 years to 0.51±0.16. CDVA respectively increased from 0.55±0.11 to 0.77±0.14 at 1 year, and to 0.79±0.16 at 3 years. Mean minimal corneal thickness decreased significantly from 466.74±34.25 µm to 396.17±45.17 µm (P<.01) as recorded the first year postoperatively and then slightly increased to 405.17±32.21 µm at the 3-year follow-up. Conclusions: We introduce herein initial clinical data with the use of novel, off-label therapeutic excimer laser surface ablation application: Designed to perform both epithelial removal and anterior corneal stroma reshaping, to be combined with CXL, in order to apply the Athens Protocol CXL with US excimer laser approved specifications.

High-throughput screening technologies continues to produce large amounts of multiomics data from different populations and cell types for various diseases, such as cancer. However, analysis of such data encounters difficulties due to cancer heterogeneity, further exacerbated by human biological complexity and genomic variability. There is a need to redefine the drug discovery development pipeline, bringing an Artificial Intelligence (AI)-powered informational view that integrates relevant biological information and explores new ways to develop effective anticancer approaches. Here, we show SynPred, an interdisciplinary approach that leverages specifically designed ensembles of AI-algorithms, links omics and biophysical traits to predict synergistic anticancer drug synergy. SynPred exhibits state-of-the-art performance metrics: accuracy – 0.85, precision – 0.77, recall – 0.75, AUROC – 0.82, and F1-score - 0.76 in an independent test set. Moreover, data interpretability was achieved by deploying the most current and robust feature importance approaches. A simple web-based application available online at http://www.moreiralab.com/resources/synpred/ was constructed to predict synergistic anticancer drug combinations requiring only the upload of the two drug SMILES to be tested, allowing easy access by non-expert researchers.

BACKGROUND Detecting total cholesterol in dried blood spots could aid in identifying individuals with a high likelihood of familial hypercholesterolemia and could be used as a screening measure. This study aims to assess the diagnostic accuracy of dried blood spots on Whatman 903 paper cards using a manual enzymatic technique. METHODS A total of 394 samples collected as serum and dried blood spots were compared. Cholesterol was determined in serum using the automated reference method, while cholesterol on paper was measured using a manual enzymatic method. Within- and between-day diagnostic variability were analyzed. The correlation between both methods was assessed using Passing-Bablok regression and Bland-Altman plot. Internal validation of our correlation formula was performed on 149 samples, along with external validation of the formula proposed by Corso et al. RESULTS The within- and between-day coefficient of variation was found to be lower than 10.14% and 14.09%, respectively. Method comparison yielded an area under the curve of 0.976, with a standard error of 0.009. Passing-Bablok regression indicated a precision of 0.803 and an accuracy of 0.96. Internal validation precision was measured at 0.716. Regarding internal validation, calculated cholesterol with our regression line did not differ from serum cholesterol analysis, while significant differences were observed in calculated cholesterol levels using the external formula. CONCLUSIONS Total cholesterol analysis in dot blood spots demonstrates high precision and reproducibility. This method reliably enables the incorporation of this biological marker into neonatal screening for familial hypercholesterolemia detection.

Pulmonary hypertension (PH) is a serious condition linked to immune-system dysfunction. Myositis-specific/associated antibodies (MSA/MAA) play a role in idiopathic inflammatory myopathy (IIM) and interstitial lung disease (ILD), but their significance in PH remains unclear. We believe the presence of these antibodies, may be underestimated. This study analyzed adult PH patients without pre-existing IIM for MSA/MAA prevalence using a line-blot assay. We compared PH patients with and without ILD signs to a cohort clinically suspected of IIM/ILD (n=558). Our PH cohort (n=121) showed a significantly higher prevalence of overall weak positive MSA/MAAs and positive overlap syndrome-associated MAAs than the suspected IIM/ILD group (p

Probiotics have been used to ameliorate gastrointestinal symptoms since ancient times. Over the past 40 years, probiotics have been shown to exert major effects on the immune system, both in vivo and in vitro. This interaction is clearly linked to gut microbes, their polysaccharide antigens, and key metabolites produced by these bacteria. At least four metabolic pathways have been implicated in mechanistic studies of probiotics, based on carefully studied animal models. Microbial-immune system crosstalk has been linked to short chain fatty acid production and signaling, tryptophan metabolism and the activation of aryl hydrocarbon receptors, nucleoside signaling in the gut, and activation of the intestinal histamine-2 receptor. Several randomized controlled trials have now shown that microbial modification by probiotics may improve gastrointestinal symptoms and multi-organ inflammation in rheumatoid arthritis, ulcerative colitis, and multiple sclerosis. Future work will need to carefully assess safety issues, selection of optimal strains and combinations, and attempts to prolong the duration of colonization of beneficial microbes.

The use of naturally available materials not conforming to traditional specifications or standards, in the base and sub-base layers of road pavement structures, stabilised with New-age (Nano) Modified Emulsions (NME), have been tested, implemented and successfully verified through Accelerated Pavement Testing (APT) in South Africa. This was made possible through the development and use of a design procedure addressing fundamental principles and based on scientific concepts, which are universally applicable. The understanding of and incorporation of the chemical interaction between the mineralogy of the materials and a NME stabilising agent (compatibility between the chemistry of the reactive agents and material mineralogy) into the design approach is key to achieving the required engineering properties. Stabilised materials evaluation is done using tests indicative of the basic engineering properties (physics) of compressive strengths, tensile strengths and durability. This article describes the basic materials design approach developed to ensure that organofunctional nano-silane modified emulsions can successfully be used for pavement layer construction utilising naturally available materials, at a low risk. The enablement of the use of naturally available materials in all pavement layers can have a considerable impact on the unit cost and life-cycle costs of road transportation infrastructure. TRANSLATE with x English ArabicHebrewPolish BulgarianHindiPortuguese CatalanHmong DawRomanian Chinese SimplifiedHungarianRussian Chinese TraditionalIndonesianSlovak CzechItalianSlovenian DanishJapaneseSpanish DutchKlingonSwedish EnglishKoreanThai EstonianLatvianTurkish FinnishLithuanianUkrainian FrenchMalayUrdu GermanMalteseVietnamese GreekNorwegianWelsh Haitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal Back

While traditionally people relinquish their pets to an animal shelter or pound, the internet provides a newer method to re-home. We analysed advertisements (ads) on the largest website in Australia for trading dogs and cats, gumtree.com.au. Data was collected in 2016. Dogs were sampled on February 7, 16 and 24, 2016 and cats on February 9, 19 and 26, 2016 with 2640 ads for relinquished dogs, and 2093 ads for relinquished cats. It was estimated >31,000 puppies/dogs and >24,000 kittens/cats are relinquished on gumtree.com.au per year. The median age of dogs was 1.42 and cats 0.9 years of age. There were 23% of dog ads and 62% of cat ads for free animals. Compared to the human population there were proportionately more ads in Queensland and fewer ads in Victoria. A total of 15 people were surveyed who had relinquished a dog or cat using gumtree.com.au. The dog owners used gumtree.com.au because they believed the shelters were full (n = 4), and; they wanted to see/interview the new owner (n = 2). For cat owners it was because they had originally got the cat on gumtree.com.au (n = 2); they use gumtree.com.au for other things, and it works (n = 2), and; they wanted to see/interview the new owner (n = 2). The data collected will be valuable for implementation of policy and interventions to protect the welfare of un-wanted dogs and cats.

Despite ample warning and significant lead time, global society has not acted sufficiently to combat climate change, and global carbon dioxide emissions are now about 60% higher today than in 1990 [1]. This paper uses marine fisheries as an analog model to compare with the many similar management issues faced with global climate change. Both marine fisheries and global climate change are complex systems that have similar properties that make management very difficult. A simple fishery prototype model is used to educate citizens about similar issues of dynamic complexity found in climate change models. We highlight how our slow reaction time to global climate change can be thought of as a mismatch between our cognitive abilities and the nature of global collective problems. Understanding the history and system structure of marine fisheries can provide insight into managing global climate change. We suggest ways to improve communication between science and citizens for updating mental models and changing climate policy.

: Nanotechnology options to road surface maintenance offers several advantages compared to traditionally used materials. The small particle sizer of hydrophobic Nano-Silane modified Nano-Polymers (NSNP) enables these nanotechnology products to deeply penetrate existing road surfaces, sealing micro-cracks and render surfacings to be water-resistant for extended periods of time. In comparison, traditionally used products contain minimum partial sizes of about 1 – 5 microns, that provide a superficial protection that wears off in a relatively short period of time. These traditional products are often associated with vehicle contamination while drying and requires the re-instatement of road markings. None of these disadvantages are associated with applicable NSNP technologies that are quick drying, with no vehicle contamination risks and is equivalent to a “clear-seal” requiring no reinstatement of road markings. In a similar vein, pot-hole repairs can be done using applicable, easy to use, pre-packed and treated pot-hole repair kits that are water-repellent and quick-drying at a fraction of the costs of conventional cold-mix products. Resurfacing using NME binder slurries can be done labour-intensively on a pre-treated NSNP surfacing, restoring cracked surfacing and providing a water-resistant long-lasting protective layer without the removal of existing cracked areas. The implementation of nanotechnology solutions for road surface maintenance operations is directly associated with ease of use, labour-intensive operations, prevention of considerable deterioration in riding quality due to removal and manual re-instatement of cracked surfaces, time and cost savings and a reduction in the risk of water damage to the sub-structure. TRANSLATE with x English ArabicHebrewPolish BulgarianHindiPortuguese CatalanHmong DawRomanian Chinese SimplifiedHungarianRussian Chinese TraditionalIndonesianSlovak CzechItalianSlovenian DanishJapaneseSpanish DutchKlingonSwedish EnglishKoreanThai EstonianLatvianTurkish FinnishLithuanianUkrainian FrenchMalayUrdu GermanMalteseVietnamese GreekNorwegianWelsh Haitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal Back TRANSLATE with x English ArabicHebrewPolish BulgarianHindiPortuguese CatalanHmong DawRomanian Chinese SimplifiedHungarianRussian Chinese TraditionalIndonesianSlovak CzechItalianSlovenian DanishJapaneseSpanish DutchKlingonSwedish EnglishKoreanThai EstonianLatvianTurkish FinnishLithuanianUkrainian FrenchMalayUrdu GermanMalteseVietnamese GreekNorwegianWelsh Haitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal Back