Fluorinated compounds and co-enzymes are being widely researched and employed throughout research community because of their versatile physical, chemical and biological properties. In this work, we synthesized NiS-NiO/S-g-C3N4, a highly effective photocatalyst for C(sp3)-F bond activation and the regeneration of coenzyme (1,4-NADH) employing a new and ecologically acceptable route. The obtained photocatalyst exhibited important photocatalytic properties, such as good solar light harvesting ability, suitability of the optical band-gap, and facilitating efficient charge migrations. As a result, the newly designed NiS-NiO/S-g-C3N4 photocatalyst shows the excellent yield for regenerations of 1,4-NADH (51%). Further, a method of combining C(sp3)-F bond activation with photocatalysis has been demonstrated that represents a very powerful and sustainable approach, that can be a major breakthrough for the field of pharmaceutical.

Expansive soil shows dual swell-shrink which is not suitable for the construction. Several mitigating techniques exist to counteract the problem promulgate by expansive clayey soils. This paper explored the penitential mecho-chemical reinforcement of expansive clayey soil to mitigate the effect of upward swelling pressure and heave. The polypropylene fiber is randomly distributed in the soil for mechanical stabilization, and the industrial residual silica fume is used as a chemical stabilizer. The experimental analysis is made in three phases which involved the tests on mechanical reinforced expansive soil using randomly distributed polypropylene fibers with different percentages (0.25%, 0.50%, and 1.00%), and 12mm length. The second phase of experiments carried out on chemical stabilized expansive soil with different percentages (2%, 4% and 8%) of silica and next phase of the experimental focused in the combination of mecho-chemical stabilization of the expansive soil with different combination of silica (i.e., 2%, 4% and 8%) and polypropylene fibers (i.e., 0.25%, 0.50% and 1.00%). Maximum dry density (MDD), optimum moisture content (OMC), liquid limit (LL), plastic limit (PL), plastic index (PI) grain size, and constant volume swelling pressure test were performed on unreinforced and reinforced expansive soil to investigate the effect of polypropylene fiber and silica fume on the engineering properties of expansive clayey soil. The experimental results illustrate that the inclusion of polypropylene fiber has a significant effect on the upward swelling pressure and expansion property of expansive soil. The reduction in the upward swelling pressure and expansion is a function of fiber content. These results also indicated that the use of silica fume caused a reduction in upward swelling potential, and its effect was considerably more than the influence of fiber.

Globally 30% of landslides occur in the northeastern part of India [1]. One of the major earthquake events in Sikkim, India occurred on 18th September 2011 (Mw 6.9) led to over 300 landslides and 122 human deaths [2]. These landslides not only controlled by natural disasters but initiated due to human activities. The present study considered Lungchok landslide occurred in south district of Sikkim due to 2011 seismic event. The study focused on the failure mechanism of the landslide based on finite element analysis by adopting eight different cases. The deformation characteristic was investigated for dry and saturated slope conditions under static and dynamic behavior considering vehicle loads using GeoStudio software. The FEM analysis has been carried out using load deformation and linear elastic. The analysis shows that the failure of the slope was not sudden due to the 2011 earthquake event, but progressive failure was observed with time and construction activity. The paper demonstrates that, an increase in infrastructure development including construction by hill cutting increased the initiation of landslide with soil erosion. The cracks developed after 2011 earthquake event led to further deformations during future disasters required effective stabilization measures.

We developed a novel hybrid approach for solving global optimization, computer science, bio-medical and engineering real life applications that is based on the coupling of the Whale Optimizer and Sine Cosine Algorithms via a surrogate model. We relate the whale optimizer algorithm to balance between the exploitation and the exploration process in the proposed method. There exist confirmed techniques for searching approximate best optimal solutions, but our algorithm will further guarantee that such numerical and statistical solutions satisfy physical bounds of the standard and real life functions. Our experiments with the benchmark, bio-medical, computer science and engineering real life problems have illustrated the advantages of using a newly hybrid approach based on mixing Whale Optimizer and Sine Cosine algorithms. It holds considerable potential for reducing execution time for solving standard and real life problems and at the same time improving the quality of the solution.

Leaf crude extract (aqueous) of Oroxylum indicum (L.) Kurz induces genomic DNA fragmentation, comet formation, and inhibition of cell proliferation in prostate cancer cell line, PC3 as assessed by agarose gel electrophoresis, comet assay, and MTT assay respectively. The bioactive compound was purified through bioassay-guided fractionation using preparative HPLC and MTT as-say. The brown and water-soluble compound was characterized using 1H and 13C nuclear magnetic resonance (NMR), fourier transform infrared (FT-IR) and electrospray ionization (ESI) mass spectrometry, and the compound was iden-tified as a glycosylated hydroquinone derivative, 2-[p-(2-Carboxyhydrazino)phenoxy]-6-(hydroxymethyl) tetrahy-dro-2H-pyran-3,4,5-triol (molecular formula, C13H18N2O8; molecular mass = 330). The identified phytocompound has not been reported earlier elsewhere. Therefore, the common name of the novel anticancer phytocompound isolated from oroxylum indicum in this current study is named as oroxyquinone. The half-maximal inhibitory concentration (IC50) of oroxyquinone on PC3 cells was 19.44 µg/ml (95% CI = 17.97 to 21.04). Oroxyquinone induced cell cycle arrest at S phases and inhibition of cell migration on PC3 as assessed by flow cytome-try and wound healing assay respectively. On investigating the molecular mechanism of inducing apoptosis, the results indicated that the oroxyquinone induced apoptosis through the p38 pathway and cell cycle arrest, however, not through caspase-3 and PARP pathways. The present study identifies a novel an-ticancer molecule and provides scientific evidence supporting the therapeutic potency of OI for ethnomedicinal uses.

Background –The brinjal is of much importance in the warm areas of Far East, being grown extensively in India, Bangladesh, Pakistan, China and the Philippines. It is also popular in Egypt, France, Italy and United States. Preserving soil fertility throughout time by preserving organic matter and soil biological diversity, mechanical intervention, as well as exercise is highly needed in upcoming future. Effect of six different fertilizer, five organic and one synthetic fertilizers listing vermicompost, poultry manure, mustard cake, neem cake, bonemeal and N:P:K study were main concern of this investigation to find out the most suitable fertilizer for the brinjal.Result - the final growth and development through N:P:K @ 1.5%(19:19:19) outperformed all the organic fertilizers but when considering only organic fertilizer performance vermicompost@5 ton/ha was outperforming all the other organic fertilizers. Coming close to it, mustard [email protected]/ha has shown its inheritance in providing nutrients. Use of other organic fertilizers are also effective use of poultry manure can provide nitrogen in higher amount in short time. Higher temperature above 25 degree Celsius cause slow growth, temperature range between 21 to 14 degrees Celsius was found better in terms of growth of flower and fruit formation.Conclusion – our experiment demonstrate specific organic fertilizer use over other fertilizers in terms of brinjal different developemental parameters and there is even comparision between synthetic fertilizer with organic fertilizer readily available in market. Vermicompost showed promising result followed by mustard cake for this specific brinjal genotype in northern plain of Indian subcontinent.

The main goal of the study is to assess the Decision criteria, and the determining factor for the sustainability of entrepreneurial startups in order to contribute towards social inclusion and capacity building. Both concepts are in the development phase and are the outcome of entrepreneurial ecosystem and individual behavior and traits. The current study observed the research problem as entrepreneurship and the entrepreneurial startups are the continuous phenomena required for every economy. The lack of an efficient ecosystem and incompetent trait of an entrepreneur drags the entrepreneurial startup to a failure. Therefore, an assessment on decision criteria and determining factors categorizing them with their importance may provide requisites to lead a successful entrepreneurial startup contributing to the social inclusion and capacity building. The study solved the research problem by statistical assessment of decision criteria and determining factors and categorizing them with their importance may provide requisites to lead a successful entrepreneurial startup. The research is built on research questions, objectives, conceptual model, and hypothesis which are tested based on the data collected. The collection of data was done through a survey questionnaire on a sample of established entrepreneurs. The study concludes that five components of decision criteria are Region, Competition, Funding Opportunities, Tax System, and Country Economic Situation, whereas the eight components Consciousness and Reliable, Pursuit Results, Flexibility, Stress Resistance, Skills Identification Exploitation Potential Market Opportunities, Leadership, Creativity and Innovation, and Delegation Decision Making of determining factor are required for a successful entrepreneurial startup to be able to work towards social inclusion and capacity building.

Abstract: A. baumannii exhibits resilience in harsh environments and progressively develops resistance to diverse antibacterial agents over time. This adaptability poses a significant challenge in treating an infection caused by this bacterium within healthcare settings. The presence of peptidoglycan, a crucial precursor for cell wall synthesis, contributes to this challenge. Peptidoglycan serves not only as a structural support in bacterial cells but also provides protection against adverse environmental conditions. The synthesis of the peptidoglycan layer involves a group of substrates such as N-acetylglucosamine (GlcNAc) and N-acetylmuramic acid (MurNAc), within a three-partitioned process occurring in the membrane, periplasmic space, and cytoplasm of each bacterium. Initiated in the cytoplasm and extending to the inner cell membrane, this synthesis starts with the production of nucleotide precursors. The first step involves the synthesis of UDP-GlcNAc, orchestrated by Glm (GlmS, GlmM, and GlmU) enzymes using fructose-6-phosphate. Subsequently, enzymes from the Mur family, namely MurB, MurA, MurD, MurC, MurI, MurF, and MurE, synthesize UDP-N-acetylmuramyl-pentapeptide (UDP-Mpp) from UDP-GlcNAc. Concurrently, on the cytosolic side, the production of membrane-surrounded undecaprenyl phosphate occurs, involving membrane-side proteins MraY and MurG in the biosynthesis of peptidoglycan. This review emphasizes updated information on Mur family proteins, encompassing physicochemical properties, nature of binding site, number and type of binding site residues, functional domain details, three-dimensional structural aspects, and their functions within bacterial cells. Special attention is directed towards their enzymatic role in peptidoglycan biosynthesis due to the limited availability of precursors in the market. Additionally, the review provides a comprehensive summary of existing inhibitors and ongoing efforts in identifying new targeted inhibitors, recognizing these enzymes as potential candidates for antibacterial drug design and discovery.

Breast cancer is the second cause of fatality among all cancers for women. Automatic classification of breast cancer lesions in mammograms is a challenging task due to the irregularity and complexity of the location, size, shape, and texture of these lesions. The intensity dissimilarity has been found between breast cancer tissues and normal tissues, when a multi-spectral anatomical mammographic screening scans have been done. In this work, two approaches have been evaluated to classify the breast tumor lesions. The first one is through Gabor wavelet features and the second one is Statistical features. Subsequently, support vector machine, Multilayer Perceptron and KNN classifiers have been used with computer based method for breast tumor classification.

We introduce an information theoretic framework for a quantitative measure of originality to model the impact of various classes of biases, errors and error corrections on scientific research. Some of the open problems are also outlined.

Cytokine and AMH profiling were done in prepubertal Murrah buffalo heifers post-progesterone supplementation and co-synchronization protocol. Cytokines: IFNγ, IL6, IL1, IL13, TNFα, and TGFβ, and, AMH, Progesterone and Estrogen hormone estimations were done. Ovarian follicular pattern and fertility outcome were recorded. Eighteen prepubertal heifers, 15-17 months of age, 250-300 kg BWt were randomly divided into 3 groups, Group1: n=6, supplemented with altrenogest 0.044mg/kg/day/heifer orally for 14 days along with Co-synch programme; Group2: n=6, administered CIDR for 14 days and co-synch programme, Group3: n=6, received co-synch programme. Ultrasonography was done to ovarian follicle status on respective days of sampling. Pregnancy diagnosis was done around 45 and 60 post-AI. Estradiol 17-β level remained constant in altrenogest group, CIDR implanted and Control groups during the Progesterone treatment and Co-synch treatment. Estradiol levels during Co-synch were significantly less on day 9 of Co-synch (14.41 ± 1.97 pg/mL) than day 0 and on day7 in pre pubertal buffalo heifers in altrenogest group. However, no significance was observed in other groups. Progesterone levels in buffalo heifers subjected to synchronisation protocols varied significantly (P< 0.05) on day 7 of P4 treatment between altrenogest supplemented and CIDR implanted groups, as well as, Co-synch groups. Supplementation of altrenogest showed a significant (P= 0.043) increase in Progesterone levels by day 14 of altrenogest treatment. Progesterone varied significantly in all Groups on day 9 of co synch protocol [ Group 1 (P= 0.02), Group 2 (P= 0.041) and Group 3 (P= 0.007)]. Cytokine IFN-γ showed high correlation with progesterone, indicating the role of IFN-γ in puberty in buffalo heifers (r= 0.626, P< 0.01). AMH had a significant positive correlation supplemented with altrenogest with IFN-γ (r= 0.673, P< 0.01) and TGF-β (r= 0.463, P< 0.01), whereas, with TNF-α it was a negatively correlated (r= -0.34, P< 0.05). Based on Karl Pearson correlation coefficients, IL-13 and TGF-β could be considered as markers for puberty in buffalo heifers.

The signaling complex around voltage-gated sodium (Nav) channels includes accessory proteins and kinases crucial for regulating neuronal firing. Previous studies showed that one such kinase, WEE1—critical to the cell cycle—selectively modulates Nav1.2 channel activity through the accessory protein fibroblast growth factor 14 (FGF14). Here, we tested whether WEE1 exhibits crosstalk with the AKT/GSK3 pathway for coordinated regulation of FGF14/Nav1.2 channel complex assembly and function. Using the in-cell split luciferase complementation assay (LCA), we found that the WEE1 inhibitor II and GSK3 inhibitor XIII reduce FGF14/Nav1.2 complex formation, while the AKT inhibitor triciribine increases it. However, combining WEE1 inhibitor II with either one of the other two inhibitors abolished its effect on FGF14/Nav1.2 complex formation. Whole-cell voltage-clamp recordings of sodium currents (INa) in HEK293 cells co-expressing Nav1.2 channels and FGF14-GFP showed that WEE1 inhibitor II significantly suppresses peak INa density, both alone and in the presence of triciribine or GSK3 inhibitor XIII, despite the latter inhibitors’ opposite effects on INa. Additionally, WEE1 inhibitor II slowed the tau of fast inactivation, and caused depolarizing shifts in the voltage dependence of activation and inactivation. These phenotypes either prevailed or were additive when combined with triciribine but were outcompeted when both WEE1 inhibitor II and GSK3 inhibitor XIII were present. Concerted regulation by WEE1 inhibitor II, triciribine and GSK3 inhibitor XIII were also observed on long-term inactivation and use-dependence of Nav1.2 currents. Overall, these findings suggest a complex role for WEE1 kinase—in concert with the AKT/GSK3 pathway—in regulating the Nav1.2 channelosome.

DevOps is an emerging practice to be followed in the Software Development life cycle. The name DevOps indicates that it’s an integration of the Development and Operation team. It is followed to integrate the various stages of the development cycle. DevOps is an extended version of the existing Agile method. DevOps aims at continuous integration, Continuous Delivery, Continuous Improvement, faster feedback and security. This paper reviews the building blocks of DevOps, challenges in adopting DevOps, Models to improve DevOps practices and Future works on DevOps

Background: The practices of various health-care professionals have been improvised to accommodate the on-going covid-19 pandemic situation. Different guidelines have been set in place to ease the process of re-opening of non-elective healthcare services like out-patient physiotherapy clinics. Although the measures taken should be guided by evidence based information, major consensus amongst practicing therapists needs to guide the India physiotherapy clinics. Objective: To identify and present the opinions of different physiotherapists about the various strategies for re-opening the out-patient physiotherapy clinics. Methods: An online cross-sectional survey was conducted. Over 169 participants were selected to participate in the survey according to the pre-decided inclusion and exclusion criteria. The data was collected and saved via google forms. Result and conclusion: A majority of respondents had a consensus over different strategies for re-opening the physiotherapy OPDs. These were regarding different measures to be adapted including modifications in the clinic infrastructure and the practice pattern. This would help in smoothly re-instating the physiotherapy services post the covid-19 lockdown.

Aortic dissection is a clinicopathological entity caused by rupture of the intima leading to a high mortality if not treated. Over time, diagnostic and investigative methods, antihypertensive therapy, and early referrals have resulted in improving outcomes according to registry data. Some data has also emerged from recent studies suggesting a link between Human Cytomegalovirus (HCMV) infection and aortic dissection. Furthermore, the use of microRNAs have also become increasingly widespread in the literature. These have been noted to play a role in aortic dissections with elevated levels noted in studies as early as 2017. This review aims to provide a broad and holistic overview of the role of miRNAs, while studying the role of HCMV infection in the context of aortic dissections. The role of long non-coding RNAs, circular RNAs and microRNAs are explored to identify changes in expression during aortic dissections. The use of such biomarkers may one day be translated into clinical practice to allow early detection and prognostication of outcomes and drive preventative and therapeutic options in the future.

The Coronavirus 2 (SARS-CoV-2) infection is a global pandemic that has affected millions of people worldwide. The advent of vaccines, however, has permitted some restitution. Aside from the respiratory complications of the infection, there is also a thrombotic risk attributed to both the disease alongside the vaccine. There are no reliable data for the risk of thromboembolism in SARS-CoV-2 infection in patients managed out with the hospital setting. A literature review was performed to identify the pathophysiological mechanism of thrombosis from the SARS-CoV-2 infection including the role of Angiotensin-Converting Enzyme receptors. The impact of the vaccine and likely mechanisms from thrombosis following vaccination was also clarified. Finally, the utility of the vaccines available against the multiple variants is also highlighted. The systemic response to SARS-CoV-2 infection is still relatively poorly understood, but several risk factors have been identified. The roll-out of the vaccines worldwide has also allowed the lifting of lockdown measures and a reduction in the spread of the disease. The experience of the SARS-CoV-2 infection, however, has highlighted the crucial role of epidemiological research and the need for ongoing studies within this field.

The exceptional Jordan algebra is the algebra of $3 \times 3$ Hermitian matrices with octonionic entries. It is the only one from Jordan’s algebraic formulation of quantum mechanics which is not equivalent to the conventional formulation of quantum theory. It has often been suggested that this exceptional algebra could explain physical phenomena not currently explained by the conventional approach, such as values of the fundamental constants of the standard model of particle physics, and their relation to gravitation. We show that this is indeed the case; and this also unravels the connection between general relativity and the weak force. The exceptional Jordan algebra also predicts a new U(1) gravitational interaction which modifies general relativity, and which provides a theoretical basis for understanding the Modified Newtonian Dynamics (MOND).

The paper presents attribute based characterization of nanomaterials method for computer storage and retrieval as knowledgebase. The knowledgebase permits indepth understanding and comparison between nanomaterials available with the scientists and product developers to satisfy their research and development (R & D) needs. Techniques for order preference by similarity to ideal solution (TOPSIS) is proposed to evaluate nanomaterials in the presence of multiple attributes. The method normalizes attributes to nullify the effect of different units and their values in the range of 0 to 1. The relative importance of different attributes for different applications is considered. The weight vector is derived using Eigen value formulation. The positive and negative benchmark solutions are derived. Euclidean distance of alternatives from these best and worst solution leads to the development of proximity /goodness/suitability index for ranking. Final decision is taken by decision makers by SWOT analysis and short and long term strategies of the organisation. The methodology is illustrated with the help of an example and step-by-step procedure. Results, discussion and conclusion highlights the importance and practical application.

This article introduces ten similarity measures that utilize cosine and cotangent functions to compare (m,n)-rung orthopair fuzzy sets, this a super class of q-rung orthopair fuzzy sets. Further, we applied our established weighted similarity measures to medical diagnosis, pattern recognition,and building material problems and also presented the comparison between established measures with the existing cosine and cotangent measures of q-rung orthopair, pythagorean and intuitionistic fuzzy sets. Lastly, we considered a numerical example that demonstrates the effective and scientific application of these similarity measures in plant leaf disease classification. Furthermore, we present graphical interpretations to demonstrate the effectiveness of our established measures.

Global emerge of zoonotic novel corona virus (COVID-19) became a pandemic and its effect to mankind is talk of the town now a days. This tiny, invisible enemy has affected every country in the world and almost every living directly or indirectly and nationwide complete lockdown has triggered a short-term environmental impact. Since 2003, corona virus came into existence in the form of Severe Acute Respiratory Syndrome (SARS) and more evolved Middle East Respiratory Syndrome (MERS) in 2012. This time, at the end of December 2019, outbreak of novel corona virus COVID-19 (also known as SARS-CoV₂, nCoV-2019) draw attention as global health emergency. World Health Organization (WHO) report says that the outbreak of this virus is so immense, it has already affected 35,57,235 people and caused death to 2,45,150 people worldwide and 46,433 Indians got affected with 1568 death as on 5^th May 2020 (2:00 am) and these numbers are increasing exponentially day by day. Virologist, micro-biologist and science community are hammering their head very hard to find out cure and vaccine against this powerful virus and to prevent mass demise of mankind. In order to curb the spread of COVID-19, Janta curfew on 22.03.2020 and nationwide complete lockdown was implemented in India for 21 days (phase-I, from 25.03.2020 to 14.04.2020) to stop community transmission of third stage, for 19 days (phase-II, 15.04.2020 to 03.05.2020) and 14 days (phase-III, 04.05.2020 to 17.05.2020) complete lockdown to minimize the community transmission effect. During complete lockdown and quarantine period a drastic change in Earth’s atmosphere, including reduction in emission of greenhouse gases, air pollution (~50% fall in air quality index), noise pollution, water pollution and solid waste pollution, have been recorded by government agencies as well as private agencies. In this paper we considered data of Janta curfew, phase-I and phase-II lockdown to link between geological and environmental aspect related to environmental impact due to emerge of COVID-19 and massive reduction in pollution level during complete lockdown in India. We propose future lockdown strategies to minimize the emission of greenhouse gas by ~100 Mt to ~200Mt (3.33% to 6.66%) of GHG_total per year by 2-4 days per month nationwide lockdown or ~70 Mt to ~140 Mt (2.33% to 4.66%) of GHG_total per year by 2-4 days per month complete lockdown of energy sectors only.

The antibiotic or antimicrobial resistance is rapidly spreading in microbes relevant to human health. Two visible major contributory factors have been the indiscriminate overuse of antimicrobials for preventing diseases in human and to enhance the productivity in agriculture sector. To mitigate the potential threat posed by post-antibiotic era, the global health stakeholders have been making extra efforts at a war footing to formulate and implement global and national plans of action. In the current article, an endeavour is made to provide a perspective to look beyond the current focus on just use of the antimicrobials. Attention has been drawn towards various obvious and not-so-obvious self-preservation infection-prevention practices in vogue from the pre-antibiotic era whose usage has been on decline in the antibiotic era for various reasons. Particularly, the practices with a clear potential to effectively decrease the spread of pathogens through contact, curtail the evolution and dissemination of the antimicrobial resistance in local environment and its introduction into the global community, should be Identified and strengthened to make them part of comprehensive hygiene and quarantine practices. Broadly, the suggestions pertaining to the personal and community hygiene including bereavement practices, isolation and quarantine of suspected pathogen carriers, and water and environment security have been made to invoke a constructive debate and discussion among various stakeholders for their evaluation and implementation to effectively delay the development of antimicrobial resistance wherever possible and disrupt its spread to pathogens.

There must exist a reformulation of quantum field theory, even at low energies, which does not depend on classical time. The octonionic theory proposes such a reformulation, leading to a pre-quantum pre-spacetime theory. The ingredients for constructing such a theory, which is also a unification of the standard model with gravitation, are : (i) the pre-quantum theory of trace dynamics – a matrix-valued Lagrangian dynamics, (ii) the spectral action principle of non-commutative geometry, (iii) the number system known as the octonions, for constructing a non-commutative manifold and for defining elementary particles via Clifford algebras, (iv) a Lagrangian with $E_8 \times E_8$ symmetry. The split bioctonions define a sixteen dimensional space (with left-right symmetry) whose geometry (evolving in Connes time) relates to the four known fundamental forces, while predicting two new forces, $SU(3)_{grav}$ and $U(1)_{grav}$. This latter interaction is possibly the theoretical origin of MOND. Coupling constants of the standard model result from left-right symmetry breaking, and their values are theoretically determined by the characteristic equation of the exceptional Jordan algebra of the octonions. The quantum-to-classical transition, precipitated by the entanglement of a critical number of fermions, is responsible for the emergence of classical spacetime, and also for the familiar formulation of quantum theory on a spacetime background.

Since the onset of coronavirus disease 2019 (COVID-19) pandemic, the virus kept developing and mutating into different variants over time that also gained increased transmissibility and spread in populations at a higher pace, culminating in successive waves of COVID-19 cases. The scientific community has developed vaccines and antiviral agents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease. Realizing that growing SARS-CoV-2 variations significantly impact the efficacy of antiviral therapies and vaccines, we have summarized the appearance and attributes of SARS-CoV-2 variants for future perspectives in drug design, bringing up-to-date hints for developing therapeutic agents targeting the variants. The Omicron variant is among the most mutated form; its strong transmissibility and immune resistance capacity have prompted international worry. Most mutation sites currently being studied are located in the BCOV_S1_CTD of the S protein. Despite this, several hurdles remain, such as developing vaccination and pharmacological treatment efficacies for emerging mutants of SARS-CoV-2 strains. In this review, we present an updated viewpoint on the current issues faced by the emergence of various SARS-CoV-2 variants. Furthermore, we discuss the clinical studies conducted to assist the development and dissemination of vaccines, small molecule therapeutics, and therapeutic antibodies having broad-spectrum action against SARS-CoV-2 strains.

In this paper the dynamics of spatially extended infected phytoplankton with the Holling type II functional response and logistically growing susceptible phytoplankton system is studied. The proposed model is an extension of temporal model available [6], in spatiotemporal domain. The reaction diffusion system exhibits spatiotemporal chaos in phytoplankton dynamics. This is particularly important for the spatially extended systems that are studied in this paper as they display a wide spectrum of ecologically relevant behavior, including chaos. In this system stability of the system is studied with respect to disease contact rate and the growth fraction of infected phytoplankton indirectly rejoin the susceptible phytoplankton population. The results of numerical experiments in one dimension and two dimensions in space as well as time series in temporal models are presented using MATLAB simulation. Moreover, the stability of the corresponding temporal model is studied analytically. Finally, the comparison of the three types of numerical experimentations are discussed in conclusion.

We have recently proposed a pre-quantum, pre-space-time theory as a matrix-valued Lagrangian dynamics on an octonionic space-time. This pre-theory offers the prospect of unifying the internal symmetries of the standard model with gravity. It can also predict the values of free parameters of the standard model, because these parameters arising in the Lagrangian are related to the algebra of the octonions which define the underlying non-commutative space-time on which the dynamical degrees of freedom evolve. These free parameters are related to the algebra $J_3(\mathbb O)$ [exceptional Jordan algebra] which in turn is related to the three fermion generations. The exceptional Jordan algebra [also known as the Albert algebra] is the finite dimensional algebra of 3x3 Hermitean matrices with octonionic entries. Its automorphism group is the exceptional Lie group $F_4$. These matrices admit a cubic characteristic equation whose eigenvalues are real and depend on the invariant trace, determinant, and an inner product made from the Jordan matrix. Also, there is some evidence in the literature that the groups $F_4$ and $E_6$ could play a role in the unification of the standard model symmetries, including the Lorentz symmetry. The octonion algebra is known to correctly yield the electric charge values (0, 1/3, 2/3, 1) for standard model fermions, via the eigenvalues of a $U(1)$ number operator, identified with $U(1)_{em}$. In the present article, we use the same octonionic representation of the fermions to compute the eigenvalues of the characteristic equation of the Albert algebra, and compare the resulting eigenvalues with the known mass ratios for quarks and leptons. We find that the ratios of the eigenvalues correctly reproduce the [square root of the] known mass ratios for quarks and charged leptons. We also propose a diagrammatic representation of the standard model bosons, Higgs and three fermion generations, in terms of the octonions, exhibiting an $F_4$ and $E_6$ symmetry. In conjunction with the trace dynamics Lagrangian, the Jordan eigenvalues also provide a first principles theoretical derivation of the low energy value of the fine structure constant, yielding the value $1/137.04006$. The Karolyhazy correction to this value gives an exact match with the measured value of the constant, after assuming a specific value for the electro-weak symmetry breaking energy scale.

Landslides are a frequent and recurrent problem in hilly regions of India and predicting them is always a challenging task. In this paper, an attempt was made to deal with this problem using advanced physical and numerical modeling methods. Detailed understanding of the initial slope failures is very interesting, and challenging at the same time, in the design and development of wireless sensor network based on early warning of landslide monitoring. A small scale physical model was developed to assess the instability through a sensor network with variable rain fall intensity. This was achieved by increasing the simulated rain water flow intensity in different time spans (dry condition, at t=0 to t= 30 min, 0.5 mm/min at t=30 to t= 60 min, 0.75 mm/min at t=60 to t=91 min and 1 mm/min at t=91 to t= 120 min). The water level and movement in the slope was recorded by rainfall sensor, vibration sensor, soil moisture sensor and a digital camera. The following changes were observed during the slope failure: a) movement of small particles at top of the slope; b) initial failure of medium size soil particle; c) scouring of soil mass; d) whole slope collapse. The obtained results clearly indicated the superiority and effectiveness of the proposed system in providing a factor of safety for the progressive slope.

Endothelial integrity plays a major role in homeostasis and is responsive to the numerous endogenous factors released. While its functional role in vascular tone is well described, its role in the pathophysiology of cardiovascular disease is of interest as a potential therapeutic target. We performed a systematic review to provide an overview of new therapeutic and diagnostic targets for the treatment of coronary artery disease related to endothelial dysfunction. Databases of PubMed, Ovid’s version of MEDLINE, and EMBASE were interrogated with appropriate search terms. 28 studies met inclusion criteria and were included in the final systematic review. We identified inflammation, pulmonary hypertension, diabetes mellitus and Fabry disease as pathophysiological mechanisms and explored the therapeutic options related to these conditions including medications such as Canakinumab. Endothelial dysfunction has a key role in several different pathophysiological processes which can be targeted for therapeutic options. Ongoing research should be targeted at making the transition to clinical practice. Further research is also needed on understanding the amelioration of endothelial dysfunction with the use of cardiovascular medications.

Staphylococci sp. have become the primary pathogens implicated in infective endocarditis, especially within high-income nations. Coupled with the increasing burden of healthcare with aging populations and the protracted course the infections may take, these infections contribute to a significant challenge for healthcare. A systematic review was conducted using relevant search criteria from PubMed, Ovid’s version of MEDLINE, and EMBASE, and data were tabulated from randomized controlled trials (RCT), observational cohort studies, meta-analysis, and basic research articles. The review was registered with the OSF register of systematic reviews and followed the PRISMA reporting guidelines. 35 studies met the inclusion criteria and were included in the final systematic review. The role of Staphylococcus aureus and its interaction with the protective shield and host protection functions is identified and highlighted in several studies. The interaction between infective endocarditis pathogens, vascular endothelium, and blood constituents is also explored giving rise to the potential use of antiplatelets as preventative and/or curative agents. Several factors allow Staphylococcus aureus infections to proliferate within the host with numerous promoting and perpetuating agents. The complex interaction with the hosts' innate immunity also potentiates its virulence. Ameliorating these molecular pathways may serve as a therapeutic avenue for the prevention and treatment of these infections in the near future.

One of the hallmarks of the SARS-CoV-2 infection has been the inflammatory process that played a role in its pathogenesis, resulting in mortality within susceptible individuals. This uncontrolled inflammatory process leads to severe systemic symptoms via multiple pathways, however, the role of endothelial dysfunction and thrombosis have not been truly explored. This review aims to highlight the pathogenic mechanisms of these inflammatory triggers leading to thrombogenic complications. There are direct and indirect pathogenic pathways of the infection that are examined in detail. We also describe the case of carotid artery thrombosis in a patient following the SARS-CoV-2 infection, while reviewing the literature on the role of ACE2, the endothelium, and the different mechanisms by which SARS-CoV-2 may manifest both acutely and chronically. We also highlight differences from the other coronaviruses that have made this infection pandemic with similarities to the influenza virus.

miRNAs have recently attracted investigators' interest as regulators of valvular diseases pathogenesis, diagnostic biomarkers, and therapeutical targets. Evidence from in-vivo and in-vitro studies demonstrated stimulatory or inhibitory roles in mitral valve prolapse development, aortic leaflet fusion, and calcification pathways, specifically osteoblastic differentiation and transcription factors modulation. Tissue expression assessment and comparison between physiological and pathological phenotypes of different disease entities, including mitral valve prolapse and mitral chordae tendineae rupture, emerged as the best strategies to address miRNAs over or under-representation and thus, their impact on pathogeneses. In this review, we discuss the fundamental intra- and intercellular signals regulated by miRNAs leading to defects in mitral and aortic valves, congenital heart diseases, and the possible therapeutic strategies targeting them. These miRNAs inhibitors comprise of antisense oligonucleotides and sponge vectors. The miRNA mimics, miRNA expression vectors, and small molecules are instead possible practical strategies to increase specific miRNA activity. Advantages and technical limitations of these new drugs, including instability and complex pharmacokinetics, are also presented. Novel delivery strategies, such as nanoparticles and liposomes, are described to improve knowledge on future personalized treatment directions.

Cancer is fundamentally a disease of perturbed genes. Although many mutations can be marked in the genome of a cancer or transformed cell, the initiation and progression were shown to be driven by only a few mutational events viz. driver mutations that progressively govern and execute the functional impacts. The driver mutations are thus believed to dictate and dysregulate the subsequent cellular proliferative function/decisions thereby producing a cancerous state. Therefore, identifying the driver events from the genomic alterations in a patient’s cancer cell gained large attention recently for designing better targeting therapies towards paving way for the precision cancer medicine. With rolling advancements in high-throughput omics technologies, analysis of genetic variations and gene expression profiles for cancer patients has become a routine clinical practice. However, it is anticipated that protein structural alterations resulting from such driver mutations can provide more direct and clinically relevant evidence of disease states than genetic signatures alone. This review comprehensively discusses various aspects and approaches that have been developed for the prediction of cancer drivers using genetic signatures and protein structures, and their potential application in developing precision cancer therapies.Keywords:

Enteroccoccus faecalis is a commensal that is responsible for numerous infections in surgical sites, urinary tract and bloodstream. It is of growing concern given its propensity to affect the elderly population where there is a high prevalence of undiagnosed degenerative valvular disease and the with more invasive procedures and implanted medical devices. Its actions are mediated by specific characteristics of the bacterium such as pili activity and biofilm formation. This confers significant resistance toward a multitude of antibiotic therapy, especially in endocarditis. The current guidelines advocate antimicrobial therapy but the emergence of resistant strains has added a degree of complexity to the management of these patients, especially with the advent of transcatheter therapies which are often used in patients who are poor surgical candidates. Their presentations are often variable with generalized symptoms and can be diagnostically challenging. We present our experience of a case study involving an octogenarian with a TAVI valve who developed endocarditis and performed a literature review to highlight treatment algorithms for these cases.

Tourette syndrome is a complex neuropsychiatric condition that manifests in childhood and is often associated with other psychiatric comorbidities. This case describes a young male with Tourette syndrome with major depressive disorder and attention deficit hyperactivity disorder (ADHD), who experienced troublesome side-effects due to his existing medications (escitalopram, risperidone and methylphenidate). In order to control his tics, ameliorate depressive symptoms, and eliminate side-effects of stiffness and sedation, risperidone was switched to cariprazine, a third-generation antipsychotic medication with D3-D2 partial agonism. In addition, the antidepressant dose was also increased. With the new combination, the patient reported good control of his tics, together with significant improvement in depressive symptoms and no side-effects. Based on this case and the reviewed literature, cariprazine might be a viable option for patients with Tourette syndrome with other comorbid illnesses, whom are prone to side effects of medication.

There must exist a reformulation of quantum field theory which does not refer to classical time. We propose a pre-quantum, pre-spacetime theory, which is a matrix-valued Lagrangian dynamics for gravity, Yang-Mills fields, and fermions. The definition of spin in this theory leads us to an eight dimensional octonionic space-time. The algebra of the octonions reveals the standard model; model parameters are determined by roots of the cubic characteristic equation of the exceptional Jordan algebra. We derive the asymptotic low energy value 1/137 of the fine structure constant, and predict the existence of universally interacting spin one Lorentz bosons, which replace the hypothesised graviton. Gravity is not to be quantized, but is an emergent four-dimensional classical phenomenon, precipitated by the spontaneous localisation of highly entangled fermions.

The flipped classroom is gaining prominence as an active learning pedagogy to engage a new generation of students. However, all courses do not lend themselves to a fully flipped design and instructors are often reluctant to flip lectures. In this study, I experimented with a “partial” flipped classroom design in a first-year undergraduate economics course. In this partial flipped format, traditional lectures were substituted with micro-lectures and the remaining class time was devoted to activities like quizzes, group work and student presentations. The full lectures were panopto recorded and put up on the e-learning site, Blackboard. This format enabled me to combine the benefits of a traditional lecture with a flipped classroom design. In order to evaluate the effectiveness of the partial flipped classroom format, I compared the final exam scores of students in the partial flipped classroom with those in the control group, which followed a traditional lecture-based approach. The key results from the analysis revealed that students in the partial flipped classroom performed better in the final exams vis-à-vis students in the traditional classroom format. Furthermore, the partial flipped classroom format was associated with lower odds of students failing in the module. This format also resulted in better student engagement, more flexibility and enhanced student-tutor interaction within the classroom.

RNA interference is a highly conserved process in which non-coding small RNAs (sRNA) modulate gene expression at the post-transcriptional level influencing plant growth and development. Dicer-like (DCL), Argonaute (AGO) and RNA-dependent RNA polymerase (RDR) are the core elements involved in gene silencing and their gene families have been explored in many plants. However, these genes and their response to abiotic stresses have not yet been well in wheat. In this study, 82 AGO, 31 DCL, and 31 RDR genes were identified and phylogenetic analysis of these proteins showed that clustered into ten, four and four clades respectively. RNA-seq analysis revealed constitutive expression of AGO1, AGO9, and DCL2 family expression analysis in tissues under normal and stress conditions, whereas RDR1 which is known to engage in siRNA biogenesis showed higher expression levels in wheat leaf tissues. Our findings build the foundation for comparative genomics analyses of RNA silencing elements in cereal crops, as well as new insights into the functional complexity of RNA silencing in wheat stress responses, which is critical for understanding the processes underlying wheat stress responses.

Background: The Covid-19 pandemic abruptly disrupted global healthcare systems, necessitating rapid adaptations. This study evaluates the impact on health systems and services in the aftermath of the first wave in the Indian context. It analyses the disruptions, adaptive measures, and changes made, as well as the challenges faced by healthcare providers and seekers. Valuable insights from this study will enhance the resilience and preparedness of healthcare systems for future challenges. Methods: The eligible studies included primary studies conducted in the Indian context that explore the impact of COVID-19 on health services provision, utilisation, and the well-being of healthcare providers and seekers. Electronic searches were conducted in six databases: PubMed, MEDLINE, Embase, Global Health, CINAHL, and the WHO database on COVID-19. The results were analysed using detailed narrative synthesis. Results: The review includes 38 articles, incorporating a total of 22,502 subjects. There has been a substantial impact on health service provision, particularly in outpatient departments (OPD) (n=19) and elective services (n=16), while emergency services continued at sub-optimal levels (n=20). Various adaptations and changes were implemented in precautionary measures, protocols, staff allocation and training, usage of personal protective equipment (PPE), preoperative, operative, and postoperative measures, as well as physical infrastructure and resources. Depression and stress (n=14), fear of contracting the infection (n=6), stigmatisation (n=5), and financial repercussions (n=5) significantly affected the mental health of healthcare providers, and healthcare seekers also faced significant challenges (n=11). Conclusion: The study reveals COVID-19's substantial impact on health services. The healthcare system responded by quickly adjusting staff management, resource allocation, and infection prevention measures. The study also highlights the mental health challenges faced by healthcare providers and the concerns of healthcare seekers regarding delays and suboptimal care. Looking ahead, the findings underscore the importance of preparedness for future pandemics, including improved healthcare infrastructure, resource optimisation, and comprehensive protocols. Lessons learned from COVID-19 should inform strategies to mitigate disruptions and ensure the well-being of healthcare providers and seekers in future outbreaks.

In this research work, we describe the preparation process, characterization, and photo-physical studies of an ionic liquid (IL) based semiconductor Zinc Oxide (ZnO) nanoparticles synthesized by an economical wet chemical precipitation method. For the first time, an IL was synthesized with the help of a chemical reaction between triethylamine (TEA) and bromoacetic acid (BAA). A polyamide dye was prepared by a reaction between two monomers, ethylenediamine (EDA) and trimesoylchloride (TMC), under room temperature conditions. The polyamide dye was capped on ZnO nanoparticles, and the final product was divided into three different samples, A, B, and C, according to level of concentrations of IL and Polyamide dye. These samples were characterized with X-Ray Diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM), Dynamic Light Scattering (DLS) spectra, Ultraviolet-Visible (UV-Vis), and Fluorescence spectroscopies. The formation of polyamide linkages in the ionic liquid has been confirmed by a spectroscopic method using Fourier Transform Infrared (FTIR) spectroscopy. The capping of polyamide dye molecules on the surface of ZnO nanoparticles revealed two things: (i) improved UV absorption spectra and (ii) enhanced luminescence in the photoluminescence spectra. Hence, during investigations, broad absorption bands were observed at peaks 263 nm, 278 nm, and 276 nm respectively for samples A, B, and C. Further, IL was used as an electrolyte or redox mediator and polyamide as a dye material in the fabrication of ZnO Dye-Sensitized Solar Cells (DSSCs). The samples A, B, and C were used in the fabrication of photo-anode assemblies for ZnO DSSCs. The ZnO DSSCs were tested under strong simulated light at Air Mass (AM) 1.5 solar irradiations. The observed photovoltaic results shown that solar cell SCB generated a maximum power conversion efficiency (η) of 5.65%, higher than the power conversion efficiencies of solar cells SCA (3.99%) and SCC (4.46%) respectively. The Incident Photon to Current Conversion Efficiency (IPCE) spectra values of ZnO DSSCs shown a significant improvement in the incident photon to current conversion efficiency of solar cell SCB (IPCE=61%) as compared to SCC (enhanced by 6%) and SCA (enhanced by 4%). Such solar cell assemblies can be suitable for green and clean energy applications.

Fever remains an integral part of the acute clinical diseases management, esp. viral, for which effective therapeutics remain desired. However, the presence of often confusing fever reduction recommendations for COVID-19 in the public domain during the pandemic, as late as 28 April 2021, seems to suggest the reduction of any ‘uncomfortable’ fever ranging from 37.8 - 39oC, as opposed to WHO fever reduction guidelines (≥39oC), urgently need attention. The confusion could percolate down into different agencies who look up to these agencies for guidance in framing their own, denying the benefits of fever to populations, and effectively undo whatever successive WHO’s guidelines have achieved in the last two decades. The existence of conflicting guidelines in public domains which are open to interpretations has consequences to public health and the healthcare infrastructure, on implementation. For controlling acute infectious diseases, esp. viral, the fever remains the most important enabler. Historically, our chief obstacles to harnessing the benefits of fever in acute clinical diseases with limited therapeutics had been: a) widespread myths about ‘fevers’ arising from a general misunderstanding of basic facts; b) presence of confusing guidelines by different agencies which are open to alternate interpretation. The article attempts to briefly indicate the benefits of fever in disease resolution, dispel myths, underline vagueness in illustrative national guidelines and the need to align them with evidence-based WHO guidelines, as it has the potential to perpetuate myths/confusion in masses leading to adverse impact on disease management – more morbidity and mortality from diseases including COVID-19.

Machine reading comprehension aims to teach machines to understand a text like a human, and is a new challenging direction in Artificial Intelligence. Datasets play an important role while describing or building an algorithm for machine reading comprehension. The type of answers we required from developed algorithm depends on datasets.The datasets are classified into two types, namely datasets with extractive answers and datasets with descriptive answers. This article summarize both datasets with an example of each type to get better insight of datasets in machine reading comprehension and which datasets to use depending the requirements.

The system design for Sustainable manufacturing is to consider both ecological and financial constraints. Manufacturing industry demands to advance in sustainable manufacturing by accounting in environment factors in it. All the factors that affect the environment need to be analyzed so that proper amendments or suggestions can be provided. To favour this, Computer aided life cycle inventory model has been presented for CNC milling and turning processes. Based on utilization of resources and stages, whole machining operation time can be divided into three phases named as process (milling or turning), idle and basic times. As parameters are different for evaluating the process times i.e. depth and width of cut in case of milling and initial and final diameters for turning, two different case studies has been presented one for each milling and turning process. Effect of material choice has been studied for different processes. Highly dense and hard materials takes more time in finishing the job due to low cutting speed and feed rates as compared to that of sot materials. In addition, face milling takes more time and consumes more power as compared to peripheral milling due to more retraction time caused by over travel distance and lower vertical transverse speeds than the horizontal transverse speed used in peripheral retraction process.

Genetic variability in rice breeding program plays the very crucial role. It provides outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For the understanding of population structure and genetic relationship among the different rice lines is indispensable prior to setting of correlation among dynamic alleles and traits. In the present investigation, genetic diversity and population structure of 116 rice accessions by using 64 polymorphic SSR markers was targeted for the evaluation of the genetic relatedness and diversity. Genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% of the variation was likely due to differences within groups. The study suggests that the population structure and genetic relatedness should be considered when working with the core collection of 116 rice germplasm lines for association mapping, aiming to establish marker-trait associations.

Spin dependent quantum transport properties in twisted carbon nanotube and stretched carbon nanotube are calculated using density functional theory (DFT) and non-equilibrium green’s function (NEGF) formulation. Twisting and stretching have no effect on spin transport in CNTs at low bias voltages. However, at high bias voltages the effects are significant. Stretching restricts any spin-up current in antiparallel configuration (APC) which results in higher magneto resistance (MR). Twisting allows spin-up current almost equivalent to the pristine CNT case resulting in lower MR. High spin filtration is observed in PC and APC for pristine, stretched and twisted structures at all applied voltages. In APC, at low voltages spin filtration in stretched CNT is higher than in pristine and twisted ones with pristine giving higher spin filtration than twisted CNT.

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.

Proprotein convertase subtilisin/Kexin type 9 (PCSK9) is a proteolytic enzyme that indirectly regulates serum LDL cholesterol by destroying LDL receptors. In clinical studies, the main role of the proprotein convertase subtilisin/Kexin type9 (PCSK9) inhibitor in cholesterol regulation was elucidated. It is produced in the liver but is also present in the kidney and intestine. It prevents HMGCo from synthesizing cholesterol. SREBP-2 is a reductase that is induced by statins. In a dose-dependent manner, increasing SREBP-2 levels enhanced LDL-R and PCSK9 gene expression. At the minimum, two procedures have been developed to overcome the plasma level of PCSK9. This is the LDLR test, polyclonal antibodies, and sentience oligonucleotide. Lower dosage statin treatment with a proprotein convertase subtilisin/Kexin type9 inhibitor will be most efficient in lowering LDL and avoiding statin adverse effects. In multiple long-term trials, statins have been found to reduce cardiovascular mortality by 30% and stroke incidence by 20%. In this way, we conclude the role of PCSK9 in hypercholesterolemia.

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.

This paper provides orthogonal moments (OM) such as, Zernike Moments(ZM), Psuedo Zernike Moments(PZM) and Orthogonal Fourier Mellin Moments(OFMM) for the analysis of melanoma images. The moment invariants may vary with respect to geometric variations. For the analysis of orthogonal moments hundred random melanoma images and hundred non-melanoma images have been taken into consideration from the database of 570 melanoma images and 250 non-melanoma images respectively. Orthoganal moments have been computed by varying the phase angles from 10° to 40° with an equal interval of 10° degree for the orders 2, 4,8,16,32,64,128,256 respectively. For the optimal OMs Particle Swarm Optimization (PSO) technique have been used. These set of extracted optimal OMs have been further applied to classify melanoma images. Support Vector Machine (SVM) has been used for the classification of [1]sensitivity=88.78%.

Natural Fibre Reinforced Composites (NFRCs) represent a significant category of materials that has the capacity to contribute to the worldwide objectives of sustainability and environmental preservation. To maximise the potential of composite materials, it is essential to establish their high quality and cost-effective manufacture. While the basic production procedures for producing items based on NFRCs have reached a high level of development, more research efforts are needed to advance their secondary manufacturing processes, namely in the areas of machining and joining. The primary factor leading to the rejection of composite goods with holes is the damage generated during the drilling process. The present experimental study aims to examine the effectiveness of hole production during the moulding phase. A comparative analysis has been conducted to assess the mechanical characteristics of moulded and drilled holes in jute fibre reinforced epoxy composite. It was observed that the moulded holes exhibit superior performance compared to the drilled holes for jute/epoxy materials. Additionally, the load extension curves indicate that the moulded holes experience greater extension in comparison to the drilled holes.

In the present paper, we introduced a quadratically convergent Newton’s like normal S2 iteration method free from the second derivative for the solution of nonlinear equations permitting 3 f'(x) = 0 at some points in the neighborhood of the root. Our proposed method works well 4 when the Newton method fails. Numerically it has been verified that the Newton’s like normal 5 S-iteration method converges faster than Fang et al. method [A cubically convergent Newton-type 6 method under weak conditions, J. Compute. and Appl. Math., 220 (2008), 409-412]. We studied 7 different aspects of normal S-iteration method. Lastly, fractal patterns support the numerical 8 results and explain the convergence, divergence, and stability of method.

The aim of this work is to assess the influence of Friction Stir Welding (FSW), process parameters, optimized tool traveling speed, and corrosion resistance of the 0.95 Mg-Al-alloy and pure copper weldment. Samples of aluminum-copper with and without deformation were characterized to investigate the metallurgical effects created during the welding deformation process. Effect of process parameters on microstructure and corrosion rate have been investigated for all the samples. All the electrochemical and polarization tests were done in 3.5 wt.% NaCl solution. Scanning Kelvin Probe (SKP) was done to detect the localized corrosion on the surface. Optical micrography observation indicated that the primary α-Al phase, which was formed during solidification can effectively limit the growth of Cu₉Al₄ phase. Finer acicular α-Al precipitates were observed in CuAl matrix during joining process that tends to coarser with the increase in tools travel speed. The electrochemical and polarization results showed that among all the tool travelling speed the specimen joined at tool travelling speed of 40 mm/min shows the best non-corrosive property.

The SnRK gene family is a key regulator playing an important role in plant stress response by phosphorylating the target protein to regulate the signalling pathways. The function of SnRK gene family has been reported in many species but is limited to Triticum asetivum. In this study, SnRK gene family in the wheat genome was identified and its structural characteristics were described. One hundred forty-seven SnRK genes distributed across 21 chromosomes were identified in the Triticum aestivum genome and categorised into three subgroups (SnRK1/2/3) based on phylogenetic analyses and domain types. The gene intron-exon structure and protein-motif composition of SnRKs were similar within each subgroup but different amongst the groups. Gene duplication between the wheat, Arabidopsis, rice and barley genomes was also investigated in order to get insight into the evolutionary aspects of the TaSnRK family genes. SnRK genes showed differential expression patterns in leaves, roots, spike, and grains. Redundant stress-related cis-elements were also found in the promoters of 129 SnRK genes and their expression levels varied widely following drought, ABA and light regulated elements. In particular, TaSnRK2.11 had higher and increased expression under the abiotic stresses and can be a candidate gene for the abiotc stress tolerance. The findings will aid in the functional characterization of TaSnRK genes for further research.

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.

A total of 473 metabolites were identified from 4 sour cherry genotypes using UPLC-TOF-MS. Untargeted metabolomics revealed the dominant chemical groups present in sour cherries. PCA showed that the diversity in sour-cherry metabolites was due to the genotype differences indicating iditol, malic acid, chlorobenzene, 2-mercaptobenzothiazole, and pyroglutamic acid as the predominant contributors. The variable importance in the projection (VIP &gt; 1.0) in partial least-squares–discriminant analysis described 20 biomarker metabolites, representing the cherry metabolome profiles. A heatmap of Pearson’s correlation analysis between the 20 biomarker metabolites and antioxidant activities identified seven antioxidant determinants that displayed the highest correlations with different types of antioxidant activities. This study of correlating metabolomics and antioxidant activities elucidated that the higher nutritional value and biological functions of select sour cherry genotypes can be useful for the development of nutraceutical and functional foods.

The Indian Himalayan Region (IHR), due to its topography, geography, and active tectonics, a rough mountain zone, is among the most vulnerable zones to the landslip danger. The most cutting-edge and accurate ways for creating a landslip susceptibility model (LSM) are advanced statistical techniques. The goal of the current work was to use advanced statistical techniques to analyse and evaluate the updated landslip susceptibility for East District in the NE Himalayas of Sikkim, India. The spatiotemporal landslip inventory for the years are produced using literature surveys, historical satellite imageries and on-site observations. Slope, aspect, elevation, curvature, plane curvature, profile curvature, topographic wetness index (TWI), lithology, distance to faults, distance to streams, distance to roads, normalised difference vegetation index (NDVI), rainfall, drainage density and land use/ land cover (LULC) are some of the topographic, environmental, geologic, and anthropogenic factors that were included in the spatial database. These LCFs were chosen to study the area's periodic landslip vulnerability. An inventory of 151 landslides from historical published records, field visits and Imagery interpretations, respectively, were used in the experimental design. Information Value Model (IVM), was used to evaluate the vulnerability to landslides as determined by fifteen LCFs. The goal of the study is to reduce the number of fatalities and possible economic harm caused by the region's frequent slope instabilities. It is expected that the application of statistical algorithms would assist relevant authorities and organisations in properly planning for and managing the region's landslip threat.

Lung cancer accounts for the highest number of deaths among men and women worldwide. Although extensive therapies, either alone or in conjunction with some specific drugs, continue to be the principal regimen for evolving lung cancer, significant improvements are still needed to understand the inherent biology behind progressive inflammation and its detection. Unfortunately, despite every advancement in its treatment, lung cancer patients display different growth mechanisms and continue to die at significant rates. Autophagy, which is a physiological defense mechanism, serves to meet the energy demands of nutrient-deprived cancer cells and sustain the tumor cells under stressed conditions. In contrast, autophagy is believed to play a dual role during different stages of tumorigenesis. During early stages, it acts as a tumor suppressor, degrading oncogenic proteins; however, during later stages, autophagy supports tumor cell survival by minimizing stress in the tumor microenvironment. The pivotal role of the IL6-IL17-IL23 signaling axis has been observed to trigger autophagic events in lung cancer patients. Since the obvious roles of autophagy are a result of different immune signaling cascades, systems biology can be an effective tool to understand these interconnections and enhance cancer treatment and immunotherapy. In this review, we focus on how systems biology can be exploited to target autophagic processes that resolve inflammatory responses and contribute to better treatment for carcinogenesis.

Maize (Zea mays subsp. mays) is the staple food crop in the world. In this study, multi-layer perceptron (MLP), support vector machine (SVM), genetic algorithm-based multi-layer perceptron (MLP-GA), and genetic algorithm-based support vector machine (SVM-GA) hybrid artificial intelligence algorithms were used for the prediction of drought tolerance and stress tolerance indices in teosinte maize lines. Correspondingly, the gamma test technique was applied to determine efficient input and output vectors. The potential of developed models was evaluated based on statistical indices and graphical representation. Results of gamma test based on the least value of gamma and standard error indices show that day of anthesis (DOA), day of silking (DOS), yield index (YI), and gross yield per plant (GYP) information vector arrangements were determined as efficient information vector combination for drought-tolerant index (DTI) as well as the stress-tolerant index (STI). The results of MLP, SVM, MLP-GA, and SVM-GA algorithms were compared based on statistical indices and visual interpretation that have satisfactory for prediction of the drought-tolerant index and stress-tolerant index in maize crop. It has also seemed that genetic algorithm-based hybrid models (MLP-GA and SVM-GA) were found a better prediction of the drought-tolerant index and stress-tolerant index in maize crop. Similarly, the SVM-GA model has the highest potential to forecast the DTI and STI in maize crops as compared to MLP, SVM, MLP-GA models.

In our recently proposed theory of quantum gravity, a black hole arises from the spontaneous localisation of an entangled state of a large number of atoms of space-time-matter [STM]. Prior to localisation, the non-commutative curvature of an STM atom is described by the spectral action of non-commutative geometry. By using the techniques of statistical thermodynamics from trace dynamics, we show that the gravitational entropy of a Schwarzschild black hole results from the microstates of the entangled STM atoms and is given (subject to certain assumptions) by the classical Euclidean gravitational action. This action, in turn, equals the Bekenstein-Hawking entropy (Area/$4{L_P}^2$) of the black hole. We argue that spontaneous localisation is related to black-hole evaporation through the fluctuation-dissipation theorem.

This paper focuses on the relationship between Mental Health and the Landscape. It aims to find out how people respond to Biophilic inspired landscape design in a healthcare setting. The focal point is not to cure diseases but to help them deal with the physiological, psychological, and psycho-social imbalance and provide a healing environment for the overall well-being of an individual. For this study, a Multispecialty Hospital was selected where an Indoor Healing Garden is used as a retrofitting tool to reduce stress and thus reconnect humans with nature. A multi-method approach is being used for this study. Initially, a questionnaire was conducted for the targeted users categorized into three types – patients, staff, and visitors to know their longing for the landscape. Based on this data and available literature, an evidence-based design was proposed. This conceptual design model is then shown to the targeted user and the response is recorded. The data has then collaborated with similar studies done earlier and design elements are highlighted which helps in creating a restorative environment by reducing stress and increasing recovery rate and thus approaching sustainable development.

Managing sidelobe levels (SLLs) in metasurface-driven beam-steering antennas poses a significant challenge due to intrinsic factors leading to grating lobes. Our proposed method employs an equivalent model to optimize large periodic metasurfaces efficiently. This model predicts complete metasurface performance, accounting for mutual coupling between patches. We introduce an evolutionary optimization algorithm based on the Cross Entropy (CE) method to enhance PGM-based beam-steering antennas and suppress sidelobes. Two strategies were employed: first is to optimize the patch dimensions for a sidelobe-free pattern and the second is to maintain the PGM dimensions while optimizing feed array amplitudes. Both strategies effectively suppressed sidelobes, offering insights into the CE method's applicability and effectiveness for CPU-intensive electromagnetic optimization challenges. The proposed CE method variant retains its simplicity while improving monitoring capabilities, addressing this limitation. Smaller generations yield better improvements per evaluation

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.

Studies at the molecular, systemic, and epidemiological levels have shown that chronic metal exposure is linked to significant health consequences, including cancer, affecting hundreds of millions worldwide. Subtle and convoluted mechanisms underline metals' toxicity and carcinogenicity. The use of sensors for carcinogenic metals' trace detection is on the rise due to their selectivity, simplicity, and affordability. Biotechnology and microelectronics in the development of sensors have grown complementarily in recent years. This study offers a comprehensive overview of current research and advancements in developing sensors for detecting carcinogenic metals. Here, we have focussed on the developed biosensor platforms for group 1 carcinogens, i.e., arsenic, nickel, cadmium, chromium, and beryllium, along with their brief roles in human carcinogenesis. This review also looks at the importance of sensing such metal exposure in humans from a larger perspective, hoping to influence future research toward early prevention and treatment of illnesses like cancer.

Zero-shot learning ability robotics enables robots to generalize their knowledge and perform tasks for which they have not been explicitly trained. This ability is extremely helpful because in classic learning approaches, robots are trained on specific tasks and require extensive data and labeled examples to perform accurately. However, in real-world scenarios, robots often encounter new or unseen tasks that were not part of their training data. We briefly survey works in this area to give the reader a perspective about progresses in this area.

This is an article or technical note which is intended to provides an insight journey of Machine Learning Systems (MLS) testing, its evolution, current paradigm and future work. Machine Learning Models, used in critical applications such as healthcare industry[1], Automobile [2], [3] and Air Traffic control, Share Trading etc., and failure of ML Model can lead to severe consequences in terms of loss of life or property. To remediate this, developers, scientists, and ML community around the world, must build a highly reliable test architecture for critical ML application. At the very foundation layer, any test model must satisfy the core testing attributes such as test properties and its components. This attribute comes from the software engineering [5], [6], but the same cannot be applied in as-is form to the ML testing and we will tell you “why”.

The report details out programming approach for automating warehouse using Answer Set Programming.

One of the biggest demanding situations for food security in the 21^st century is to enhance crop yield stability through the improvement of diseases-resistant crops. Managing plant health is a major challenge for modern food production and compounded by the lack of common ground among the many disease control disciplines involved. All plants simultaneously engage with billions of microbes which can be collectively referred to as the plant microbiome. Most microbes inside the plant microbiome are harmless or even beneficial to the plant as they promote plant growth or provide protection in opposition to diseases. However, some of these microbes also cause disease with devastating effects on crop yields. To prevent pathogen infection, plants have evolved an advanced innate immune system that recognizes conserved cell surface molecules that most pathogen possesses. Activation of the plant immune system stops the invading pathogen, however this comes with fitness cost that significantly reduces plant growth and leads to yield penalty. Apart from their innate immune system controlling pre-programmed defense reactions, plants can also increase the responsiveness of their immune system in response to selected environmental signals. This phenomenon is known as “defense priming”. Although defense priming rarely provides full protection, its broad-spectrum effectiveness, low-fitness cost, long‐lasting durability and inherited to future generations make it attractive for sustainable crop protection.

Currently, energy security and environmental degradation are the two biggest challenges before humanity that can be surmounted with the use of green and sustainable biofuels produced from lignocellulosic crops. In the future, to ensure adequate and cost-effective supply of biofuels, it requires a sufficient amount of amenable and quality lignocellulosic feedstocks. Therefore, agricultural yields of lignocellulosic biomass crops should be substantially increased by intense genetic maneuvering of key gene regulatory mechanisms and signaling pathways that control plant biomass yield. Recently, numerous miRNAs families are identified, characterized, and validated across the plant kingdom. Plant microRNAs (miRNAs) are 21 to 24 nucleotides long, non-coding small RNAs, act as regulators of their target genes via inducing modifications in transcription, translation, and epigenome. MiRNAs represent many hallmark characteristics like sequence-specific regulation, tissue, and species-specific expression, evolutionary conservation, and functional diversity. They coordinate well physiological and life cycle processes in plants under adverse environmental conditions. Hence, miRNAs offer accurate, precise, and efficient regulatory switches in the miRNA-targeted genetic networks. It is evident from the study of the miR156 family and its target SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) genes network that controls highly significant agronomic traits in crop plants. The miR156/SPL module acts as a master circuit that synchronizes many intricate complex biological functions such as growth and development, and metabolic processes by sensing internal and external environmental signals in plants. Therefore, miR156 can prove a potential target for miRNAs based plant biotechnology to harmonize complex biofuel traits and improve biomass yield in lignocellulosic biomass crops.

This research discusses the business model challenges faced by cag aggregator platform models in developing countries. Technology-based platforms have been disrupting traditional businesses and rewriting the rules of the game. Ola cabs has been instrumental in shaping the Indian platform business landscape in a big way. Using case methodology the author analyses the situation and business model to present the salient features of Ola’s model. However, this paper also puts the spotlight on the inherent challenges in this model and warns the need for continuous business model innovation and service quality.

The recent outbreak of novel coronavirus (SARS-CoV-2 or 2019-nCoV) and its spread to the whole world is currently posing one of the major threats to human health and the world economy. It has been suggested that SARS-CoV-2 is similar to SARS-CoV based on the genome sequence comparison. Despite the genomic similarity between SARS-CoV and SARS-CoV-2, the spike glycoprotein and receptor binding domain in SARS-CoV-2 shows considerable difference compared to SARS-CoV, due to the presence of several point mutations. We analyzed the receptor binding domain (RBD) from recently published 3D structure of spike glycoprotein of SARS-CoV-2 and compared with RBD of SARS-CoV. The observations highlight few important features of RBD in the light of the recently published findings from the 3D structures of spike glycoprotein and its complex with human angiotensin-converting enzyme 2 (ACE2) (Yan, R., et al. (2020); Wrapp, D., et al. (2020); Walls, A. C., et al. (2020)).

The article reviews the constituent’s physico-chemical parameters in the water of the Mansagar Lake of the Jaipur City. The water quality is also investigated using evaluated physico-chemical parameters with in-depth study of their distribution as per sample location-wise and season-wise. A detailed discussion on the associationship among parameters (pH, Conductivity, turbidity, dissolved Oxygen, chemical and Biochemical Oxygen demand, etc.) using the Pearson’s analytical method is also presented. The strength of the article is the graphical presentation of evaluated physico-chemical parameters and the water quality indices for sample station-wise and the season-wise. To our best of understanding, first time such details have been clubbed together and discussion in brief for studied lake.

With this article, impact of effluent mixed water with the quality of the Mansagar Lake has been established by evaluating the physico-chemical parameters and the heavy-metal contents experimentally. The process of calculating water quality and the metal pollution quality indices is also explained in brief with respect to selected sample locations and varied environmental conditions (Pre- and Post-Monsoon season). Distribution trends of Pearson‘s correlation factor have also been discussed to establish their relation among the physico-chemical parameters and the heavy-metal contents for varied environmental conditions. In the end, detailed discussion on observations made during this study and useful recommendations are also elaborated in details. With this article, we intend to present a document for better understanding of the water quality of this lake in view of futuristic management strategies to be adopted to maintain it heritage values.

When gravity is quantum, the point structure of space-time should be replaced by a non-commutative geometry. This is true even for quantum gravity in the infra-red. Using the octonions as space-time coordinates, we construct a pre-spacetime, pre-quantum Lagrangian dynamics. We show that the symmetries of this non-commutative space unify the standard model of particle physics with $SU(2)_R$ chiral gravity. The algebra of the octonionic space yields spinor states which can be identified with three generations of quarks and leptons. The geometry of the space implies quantisation of electric charge, and leads to a theoretical derivation of the mysterious mass ratios of quarks and the charged leptons. Quantum gravity is quantisation not only of the gravitational field, but also of the point structure of space-time.

Carbohydrate composition of lignocellulosic biomass is one of the main factors for production of biofuel from the plant biomass. Various methods like Thermogravimetric analysis (TGA), near infrared spectroscopy (NIR) often used in determination of polysaccharide component of the plant biomass. However, used of such tools is based on the prediction and very costly. This paper discussed about the determination of carbohydrate composition (cellulose, hemicellulose and lignin) using the automatic fibre estimation system. The protocol was developed for the estimation of cellulose, hemicellulose and lignin component of lignocellulosic biomass. This protocol explains a simple method to estimate the polysaccharide component of lignocellulosic biomass. This protocol can be used not only lignocellulosic biomass but also for other hardwood biomass. The advantages and techniques, procedures are presented below.

Transcatheter aortic valve implantation (TAVI) has grown exponentially within the cardiology and cardiac surgical spheres. It has now become a routine approach for treating aortic stenosis. Several uncertainties have been raised about TAVI in comparison to conventional surgical aortic valve replacement (SAVR). The primary concerns are with regards to the longevity of the valves. Several factors have been identified that may predict poor outcomes following TAVI. These include the lesser-used finite element analysis (FEA) to quantify the properties of calcifications that affect TAVI valves. This can also be used in conjunction with other integrated software to ascertain the functionality of these valves. Other imaging modalities are now widely available such as Multi-detector row computed tomography(MDCT) which can accurately size the aortic valve annulus.. This may help reduce the incidence of paravalvular leaks and regurgitation which may necessitate further intervention. Structural valve degeneration (SVD) remains a key factor with varying results from current studies. The true incidence of SVD in TAVI compared to SAVR remains unclear with the lack of long term data. It is now widely accepted that both are part of the armamentarium and are not mutually exclusive. Decision-making for the appropriate intervention should be made via shared decision-making involving the heart team.

SARS-CoV 2 also known as COVID-19 is a fast spreading coronavirus related disease that emerged from China in December 2019 and is currently attained the status of a pandemic. There are currently no drugs/ vaccines against the same and moreover limited diagnostic tests to identify the infection. Additionally, these tests are expensive and hence are exclusive for very highly suspected cases of the disease especially in developing countries. This is causing an under-diagnosis which is an alarming state of affairs, as even a single missed SARS-CoV 2 case would spread the disease exponentially and keep it in the community. Through this entirely in silico study, we have developed a cheaper and faster diagnostic method based on simple PCR and restriction enzyme digestion, commonly used in restriction fragment length polymorphism (RFLP) tests. Through comparative genomics, we found the closest neighbours of SARS-CoV 2 then found the highly conserved regions of the genome which were absent in SARS-CoV 1, its closest neighbour. Then we found restriction sites for various enzymes followed by designing of PCR primers flanking those sites. We have found the primer pair to produce a 401 bp amplicon and when digested by SwaI enzyme, it produces two fragments of lengths 216 bp and 185 bp. As an internal control, GAPDH primers are pooled with the SARS-CoV 2 primers as the patient sample will also include human RNA mixed with the viral RNA. This primer pair gives an amplicon of 131 bp and hence a negative sample should show a single band of 131 bp while a positive digested sample will give three bands of 401 bp, 216 bp and 131 bp. The primers are specific to SARS-CoV 2 only and can additionally be used for SYBR green based real time quantification of viral load. The developed tests have not yet been tested in vitro due to stressed out working hours in the only pathogenic virus handling laboratory in our institute. Nonetheless, this study works as a head start for other laboratories to rapidly test the suggested protocols in vitro and make available a cheaper alternative test for SARS-CoV 2 which would especially be beneficial for the lower to middle income countries.

Assessment of extreme events and climate change on reservoir inflow is important for water and power stressed countries. Projected climate is subject to uncertainties related to climate change scenarios and Global Circulation Models (GCMs’). Extreme climatic events will increase with the rise in temperature as mentioned in the AR5 of the IPCC. This paper discusses the consequences of climate change that include extreme events on discharge. Historical climatic and gauging data were collected from different stations within a watershed. The observed flow data was used for calibration and validation of SWAT model. Downscaling was performed on future GCMs’ temperature and precipitation data, and plausible extreme events were generated. Corrected climatic data was applied to project the influence of climate change. Results showed a large uncertainty in discharge using different GCMs’ and different emissions scenarios. The annual tendency of the GCMs’ is bi-vocal: six GCMs’ projected a rise in annual flow, while one GCM projected a decrease in flow. The change in average seasonal flow is more as compared to annual variations. Changes in winter and spring discharge are mostly positive, even with the decrease in precipitation. The changes in flows are generally negative for summer and autumn due to early snowmelt from an increase in temperature. The change in average seasonal flows under RCPs’ 4.5 and 8.5 are projected to vary from -29.1 to 130.7% and -49.4 to 171%, respectively. In the medium range (RCP 4.5) impact scenario, the uncertainty range of average runoff is relatively low. While in the high range (RCP 8.5) impact scenario, this range is significantly larger. RCP 8.5 covered a wide range of uncertainties, while RCP 4.5 covered a short range of possibilities. These outcomes suggest that it is important to consider the influence of climate change on water resources to frame appropriate guidelines for planning and management.

Plants are immobile, and, to overcome harsh environmental conditions, such as drought, salt, and cold, they have evolved complex signaling pathways. Abscisic acid (ABA), an isoprenoid phytohormone, is a critical signaling mediator that regulates diverse biological processes in various organisms. Significant progress has been made in the determination and characterization of key ABA-mediated molecular factors involved in different stress responses, including stomatal closure and developmental processes, such as seed germination and bud dormancy. Since ABA-signaling is a complex signaling network that integrates with other signaling pathways, the dissection of its intricate regulatory network is necessary to understand the function of essential regulatory genes involved in ABA signaling. In the present review, we focus on two aspects of ABA signaling. First, the perception of the stress signal (abiotic and biotic) and the response network of ABA-signaling components that transduce the signal to the downstream pathway to respond to stress tolerance, regulation of stomata, and ABA signaling component ubiquitination. Second, ABA-signaling in plant development processes, such as lateral root growth regulation, seed germination, and flowering time regulation. Examining such diverse signal integration dynamics could enhance our understanding of the underlying genetic, biochemical, and molecular mechanisms of ABA signaling networks in plants.

Optical fiber sensors based on tapered optical fiber (TOF) structure have attracted a considerable amount of attention from researchers due to the advantages of simple fabrication, high stability, diverse structures, and have great potential for applications in many fields such as physics, chemistry and biology. Compared with ordinary optical fibers, TOF with their unique structural characteristics significantly improve the sensitivity and response speed of fiber-optic sensors and broaden the application range. This review presents an overview of the latest research status and characteristics of fiber-optic sensors and TOF sensors. Then the working principle of TOF sensors, fabrication schemes of TOF structures, novel TOF structures in recent years, and the growing emerging application areas are described. Finally, the development trends and challenges of TOF sensors are prospected. The objective of this review is to convey novel perspectives and strategies for the performance optimization and design of TOF sensors based on fiber-optic sensing technologies.

Heterocycles are unique precursors for the synthesis of various pharmaceuticals and agrochemicals particularly those possessing N- or O- moieties. The development of methods to prepare heterocycles is of great importance in synthesis of organic compounds, especially the heterocycles which can be found in natural products. The synthesis of nitrogen and oxygen containing heterocycles viz. coumarins, dihydropyrimidinones, imidazoles, isoxazoles and benzimidazoles represented an attractive and demanding work for chemists as these nucleus has found extensive applications in several fields such as material science, analytical chemistry and most importantly in medicinal chemistry. Organic synthesis has been attracted towards the development of new environmental friendly procedures to achieve the goals of green chemistry. The fundamental aspects of green chemistry are use of biocatalysts and environmental benign solvents under mild conditions. The present review article summarized the green synthetic methods and biological activities of nitrogen and oxygen containing heterocycles.

Pesticides are among the most widely used synthetic chemicals worldwide to protect crops, but besides being beneficial, they pose several environmental and health issues. The present study evaluates toxic effects of acetamiprid (ACMP) in rat liver and kidney tissues. Rats were exposed to ACMP (21.7 mg/kg b.wt; 1/10th LD50) for 21 days. Oxidative stress generation, apoptotic progression, and structural changes were evaluated via biochemical assays, semi-quantitative PCR, western blotting, and histopathology. ACMP exposure significantly decreased body weight and altered relative organ weight in hepato-renal tissues. Significant oxidative stress was evident by increased oxidative injuries to lipids and proteins and alterations of endogenous anti-oxidative enzymes. The administration of ACMP upregulated mRNA expression of Bax and caspase-3, while downregulated the mRNA expression of Bcl-2 and released cytochrome c into the cytosol of the liver and kidney tissues. Likewise, exposure to ACMP caused severe degenerative changes in the histo-architecture of hepato-renal tissues. The results of the present study confirmed the toxicity of ACMP in rats’ liver and kidney tissues and emphasized the need for strict regulation and more mechanistic understanding to delineate the toxicity of ACMP in mammals.

The disc brake rotors are designed to withstand both, Maximum possible deceleration (emergency braking) and a series of frequent braking cycles. A effective rotor design and superior heat dissipating material provide better performance during the braking mechanism. In this experiment, modified ventilated disk brake rotors are developed with holes and slots and the stress, deformation, heat flux and temperature distribution has been analysed. Designing of the Finite element models of the rotor are created with SolidWorks and simulated using ANSYS. Structural and thermal characteristics are compared with a reference disk brake rotor of the motorcycle (TVS Apache RTR180). It is found that the modified rotors outperform the conventional one in terms of stress generation, temperature distribution and deformation. Furthermore, this Analysis helps us to find out the best suited material for one of the proposed designs. This experiment provides us an insight of the structural and thermal characteristics of the geometrically modified rotor that can be used to upgrade and outperform the current disc brake rotor used in the motorcycle (TVS Apache RTR180).

The genus Vigna is penta-tropical having more than 200 species with many desirable economically important traits. The aim of study was to validate the in-silico polymorphism of whole genome sequence developed mungbean specific SSR markers and their transferability among the different Vigna species. The present study utilized a set of 200 SSR markers developed from whole genome sequence of mungbean and validated using a diversity panel of 25 accessions which belongs to 13 Vigna species. Out of 200 SSR markers, 130 markers (65%) were polymorphic across the various Vigna species and the number of alleles amplified varied between 7 to24. The SSR markers showed more than 90 percent transferability across the different Vigna species accessions. Based on allelic data, the 25 Vigna accessions grouped into three clusters based upon the unweighted pair group method with arithmetic mean (UPGMA) phylogenetic tree. The principal co-ordinates analysis (PCA) biplot graph and UPGMA based neighbor joining clustering diagram showed similar pattern of Vigna accessions distribution. The population structure assessment has grouped the cultivated and wild species accessions into two sub-population. The estimated marker parameters such as polymorphic information content (0.09 – 0.84), marker index (0.091 – 3.342) and effective multiplex ratio (1.0 – 4.0) suggested their adequacy in several genetic studies such as parental selection, hybrid testing, genetic mapping and marker aided breeding programmes for genetic enhancement of species belonging to the Vigna genus.

Cancer is a catchall term that refers to a collection of more than one chronic disease that can adversely affect the body, including the organs of the body. These diseases can be grouped together under the umbrella term "cancer." Cancer is a catch-all term that is used to refer to a number of different diseases. During the process of looking for new chemical entities, it was found that certain compounds with a basic nucleus of benzoic acid (BA) exhibit a remarkable anticancer potential. This was discovered while the researchers were looking for new chemical entities. In the sixteenth century, the aromatic chemical known as BA, which is also known as an aromatic carboxylic acid, was discovered. BA is also referred to as an aromatic carboxylic acid. When it comes to the chemical synthesis of a wide range of different active molecules, the utilization of a sizeable quantity of BA as a raw material is absolutely necessary. In addition to being present in a variety of other naturally occurring compounds, the BA moiety is the component that is responsible for the activity of the naturally occurring compounds vanillin, gallic acid, and syringic acid. In the synthesis of a wide variety of synthetic bioactive molecules, the BA scaffold is utilized as a building block. The drugs furosemide, bumetanide, benzocaine, tetracaine, and bexarotene are all examples of molecules that fall into this category. The scope of this review article allows for the discussion of a number of noteworthy and recent achievements of BA derivatives in terms of their effectiveness against cancer.

Calcineurin B-like proteins (CBL)-interacting protein kinases (CIPKs) by interacting with CBLs regulate developmental processes, hormone signalling transduction and mediate stress responses in plants. Although the genome of chickpea is available, information of CIPK gene family has been missing in chickpea. Here, a total of 22 CIPK encoding genes were identified in chickpea and characterized by in silico methods. We found a high structural conservation in chickpea CIPK family. Our analysis showed that chickpea CIPKs have evolved with dicots from common ancestors, and extensive gene duplication events have played an important role in evolution and expansion of CIPK family in chickpea. Most chickpea CIPK proteins localize in cytoplasm and nucleus. Promoter analysis revealed various cis-regulatory elements related to plant development, hormone signaling and abiotic stresses. Expression analysis indicated that CIPKs are significantly expressed in a spectrum of developmental stages, tissue/organs that hinted their important role in plant development. Several CIPK genes had specific and overlapping expressions in different abiotic stresses and seed development stages, suggesting the important role of CIPK family in abiotic stress signaling, and seed development in chickpea. Thus, this study provides the avenue for detailed functional characterization of CIPK family in chickpea and other legume crops.

(i) Investigations of stellar systems known as wide binaries suggest that Newton’s law of gravitation breaks down at low accelerations. This can be explained by proposing a fifth force with $U(1)$ gauge symmetry, whose corresponding gauge boson is the sought for dark matter candidate. (ii) Relativistic causality (i.e. no faster than light signalling) permits nonlocal correlations stronger than those permitted by quantum mechanics. This can be explained if our universe possesses a second 4D spacetime with a signature opposite to ours. (iii) Such a fifth force, and a second spacetime, arise naturally in a recently proposed theory of unification based on an $E_8\times E_8$ symmetry. Our spacetime arises from breaking of an $SU(2)_R\times U(1)_{YDEM}$ symmetry, and the second spacetime arises from broken electroweak symmetry.

The enterprise software sector is experiencing a significant transformation driven by rapid technological progress and evolving business needs. An effective release management process is crucial for the solution providers and customers, as they incorporate the principles of Industry 4.0 and 5.0. With the growing dependence on software solutions and services, ensuring their quality, reliability, and security is highly necessary. The release management process incorporates strategic planning, regression testing, accurate deployment, and continuous monitoring of software updates. However, the rapid advancements in artificial intelligence (AI) and machine learning (ML) create a unique challenge to the release management process. The existing research needs to address the necessary adaptations for Industry 5.0, mainly in product-based software organizations, to the release management process without a change management system. After working with several software solution stakeholders, based on the responses from SaaS project stakeholders, we have presented a revised software release readiness workflow by incorporating a change management module. The preliminary result based on data over a limited period of time indicates that the revised workflow has the potential to improve the management of slippage, particularly by more effectively addressing NFR-related issues, thereby resulting in more predictable and reliable release cycles.

Hearing loss in infancy leads to preventable speech, language, and cognitive developmental delay [1, 2]. Sensorineural hearing loss (SNHL) is caused by damages, problems, or issues related to the inner ear such as the cochlea with or without the auditory nerve; cranial nerve VIII, involvement. There are three anatomic areas which include the outer ear: composed of the auricle and external auditory canal and the middle ear: which includes the tympanic membrane, ossicles, and the middle ear space, the inner ear: composed of the cochlea, semi-circular canals, and internal auditory canals. The unique anatomical shape of the auricle catches the incoming sound waves to send them down the external auditory canal. Hearing risk assessment should be part of all health visits while regular hearing screening checks are done for all children from 4 to 21 years [1, 2]. Assessment of hearing loss includes history, physical examination and specific hearing assessment tests.

The members of the Liliaceae family have been regarded as an excellent source of biologically active compounds. However, the work on antimicrobial potential and characterization of the bioactive fractions of Lilium philadelphicum flower is limited and needs to be explored. The present study reports the antimicrobial potential, anti-inflammatory and anticancer potential of the bioactive fraction extracted from the flower of L. philadelphicum (Red Lily) and characterization of these bioactive compounds. The antimicrobial activity was tested against nine different Gram-positive and Gram-negative bacterial strains. The minimum inhibitory concentration (MIC) values of methanolic extract of L. philadelphicum flower against Acinetobacter bouvetii, Achromobacter xylosoxidans, Bacillus subtilis MTCC 121, Candida albicans MTCC 183, Klebsiella pneumoniae MTCC 3384, and Salmonella typhi MTCC 537 were 25, 50, 12.5, 50, 100 and 50 μg mL-1, respectively. The phytochemical analysis of the extract reveals the presence of phenols, flavonoids, tannins, terpenoids, glycosides, coumarins, and quinones. The cytotoxicity of the partially purified compound against the HepG2 cell line in MTT assay demonstrates up to 90% cell viability with a bioactive compound concentration of 50 μg/ml. However, with the increase in bioactive compound concentration up to 1000 μg/ml results into nearly 80% cell viability, just a minor decline in cell viability suggests the importance of bioactive compounds for suitable therapeutic applications. Spectroscopic studies of the bioactive compound by UV-Visible spectroscopy, FT-Infra Red spectroscopy, Gas Chromatography-Mass Spectrometry (GCMS) as well as its phytochemical analysis suggests the presence of terpenoids moiety, responsible for the antimicrobial property of L. philadelphicum flower.

With the continuous improvement and observable benefits of electric vehicles (EVs), major logistic companies are introducing more EVs into their conventional fleets. This gives rise to a new type of vehicle routing problem with mixed vehicles, where heterogeneous internal combustion vehicles (ICVs) and electric vehicles are considered in route planning. In addition, certain deliveries that are not efficient on any type of vehicles, are outsourced to third-party common carriers. In this paper, we define this problem as a mixed vehicle routing problem with common carriers (MVRPC). The objective of such problems is to minimize the transportation costs by considering routes with ICVs and EVs, the possibility of visiting recharging stations, outsourcing options, and drivers’ layover regulations. This variant of the vehicle routing problems has many practical applications, particularly in the design of long-haul transportation and last-mile delivery services. Effective MVRPC solutions play a key role in promoting the going Green image and optimally allocating resources. The problem has received limited attention in the literature likely because addressing all the needed aspects is especially challenging. To solve the large-scale problem, we develop a branch-and-cut pricing framework that relies on strong cuts and customized labeling algorithms. Numerical experiments highlight the effectiveness of our algorithm. This success can be attributed to tailored critical resources, dynamically bounded bidirectional labeling procedures, strong dominance criteria, and implementation strategies.

Genetic disorders are preeminent determinants of infant mortality. The inherited pediatric-onset genetic disorders have consequential stress on child growth and development: several congenital, complex and rare disorders with indistinguishable clinical symptoms where diagnosis always remains a challenging task. Traditional diagnosis methods include biochemical tests followed by chromosomal microarray and sequencing of a single gene or panel of genes. These methods had several limitations, but with the advent of whole-exome sequencing (WES), genetic testing has become cost-effective and transformative. Exome sequencing has been known for its effectiveness, which appropriately elucidates and distinguishes the heterogeneous disorders to avoid misdiagnosis and decode the underlying genetic alterations. WES has led to discovering genes and genomic variants in a broad spectrum of diseases, including autism, epilepsy, congenital heart diseases, neurodevelopmental diseases, cancer, nephrotic disorders, neural tube defects and fetal structural anomalies. WES is significant in producing immense genomic biomarkers that can be made as appropriate pharmacogenomic targets for drug therapy. In this article, we analyze the recent exploration of WES technology to revolutionize not only the process of genetic variation and disease detection but also the convention of preventative and targeted drug discovery.

This study evaluated five annual and eleven perennial Indian pasture legumes species for their nutritive value, dry matter, mineral contents and in vitro fermentation parameters, aiming to boost their potential as animal feed. Legume species significantly differed (p<0.05) in organic matter, crud protein (CP), ether extracts, fibres, and protein fractions. Clitoria ternatea (CT) a perennial had higher (p<0.05) buffer soluble protein (477), while neutral detergent soluble protein was highest in annually grown Lablab purpureus (420 g/kg CP). Atylosia scarabaeoides (AS) had higher NSC (392 g/kg DM) than SC (367 g/kg DM). Rapidly degradable fraction (51.7 g/kg tCHO) was lower (p<0.05) than other fractions of carbohydrate. Total digestible nutrients, digestible energy and metabolisable energy varied and values were higher for Desmenthus virgatus and lowest for Stylosanthas seabrana (SSe). The NE values for lactation (NEL), maintenance (NEM) and gain (NEG) were also higher for DV (6.6, 7.95 and 4.28) and lowest for SSe (3.54, 4.24 and 0.58 kJ/g DM), respectively. dry matter intake, digestible DM (DDM) and relative feed value of legumes differed (p<0.05) with mean values of 2.22% body weight, 592 g/kg DM and 102%, respectively. Annual grasses like Dolichos biflorus, Macroptilium atropurpureum, Rhynchosia minima (RM) were found better with micro minerals compared to other perennials. In vitro dry matter degradability, partition factor, short chain fatty acids and microbial protein production of legumes varied (P<0.05) and mean values were 578 g/kg DM, 5.61 mg DDM/mL, 2.42 mm/g and 352 mg/g, respectively. Gas and CH4 production (mL/g and mL/g DDM) varied (p<0.05) being lowest gas from AS (55.5) and highest from CT-blue (141), while CH4 production was lower (p<0.05) from CT-white and AS (8.24 and 9.14) and higher from Arachis glabrata (AG) and Arachis hagenbackii (AH) (15.2 and 15.1). Methane in total gas was low for DV, RM and CT-w (8.99, 9.72 and 9.51%) and loss of DE and ME as CH4 varied (P<0.05) amongst the legumes with mean values of 4.62 and 7.86%, respectively. Based on these findings, each legume offers unique benefits, allowing for tailored combinations of annual and perennial legumes to optimize rumen feed efficiency.

Literature reported the insulin is an important for the humans and it is secreted in the pancreas and controls, regulates the glucose level. It also controls the mechanism and growth. On decreasing the amount of insulin can caused diabetes, several cancers and other disease. Therefore, there is a need to find promising candidates can binds with insulin and stabilize them. Organic compounds containing hetero atoms have lots of biological potency in different area, therefore, researchers are designing new biological potent compounds. Further, insilico studies attracted the researchers in last one decade mainly to get the drug in less time with a clear strategy. In the present work, authors have designed two types of conjugates, xanthenes with trizole as well benzisoxazole and study their interaction with the insulin using computational methods. The library of compounds was screened through molecules docking in terms of binding energy between the designed compound and the active site of the receptor. Further, their ADME properties are investigated. CMPD19 showed best binding affinity with the insulin and may be considered as oral drug based on the bioactive scores.

The discovery of microRNAs and their role in disease today represents a substantial breakthrough that has inspired and propagating research on microRNAs as targets for diagnosis and therapy. Cardiovascular disease is an area where the limitations of early diagnosis and conventional pharmacotherapy are evident and deserve attention. Thus microRNA-based drugs have substantial potential for development. Research and its application can progress considerably as witnessed in preclinical and clinical trials. The use of miRNAs remains experimental at the time of writing but has a promising role in the diagnosis and prognosis of a variety of acute coronary syndrome presentations. Its use, alone or in combination with currently available biomarkers, could be adopted soon, especially if diagnostic ambiguity exists. In this review, we explore the current state of knowledge about microRNAs as potential targets for diagnosis and therapy in the cardiovascular system. We report recent improvements in the acknowledgment and characterization of microRNAs focusing on clinical translation. The new dares and outlooks toward clinical application are discussed.

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.

Cannabis is the most widely cultivated, trafficked and abused illicit drug (“WHO | Cannabis,” n.d.; “World Drug Report 2020,” n.d.). In 2018, an estimated 192 million people aged 15-64 years used cannabis for nonmedical purposes globally (Degenhardt et al., 2013). The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated that, across the globe, there were more than 22·1 million people with cannabis dependence (Degenhardt et al., 2018). Moreover, the same study calculated that cannabis dependence could be accounted for 646 thousand Disability Adjusted Life Years, globally. Importantly, cannabis dependence mostly affects young adults (20-24 years), and thus has significant negative impact on the growth and productivity of not only these individuals but also to the societies and nations (Degenhardt et al., 2013). In addition to the dependence syndrome, cannabis use is associated with increased risk of psychosis, cognitive dysfunction, academic problems, and road side accidents (Volkow et al., 2014). A review showed a fairly consistent associations between cannabis use and both lower educational attainment and increased reported use of other illicit drugs (Macleod et al., 2004). In the United States, Cannabis Use Disorder (CUD) is an escalating problem in young adults by legalization (Cerdá et al., 2020) where National Survey on Drug Use and Health reported increased prevalence from 5.1% in 2015 to 5.9% in 2018 in 18-25 year olds (“2019 NSDUH Detailed Tables | CBHSQ Data,” n.d.). The psychoactive effects are due to type 1 cannabinoid receptor (CB1), the cannabinoid binding protein, that are highly expressed in the cerebellar cortex (Marcaggi, 2015). CB1 is primarily found in the molecular layer at the most abundant synapse type in the cerebellum (Marcaggi, 2015) that can shape the spike activity of cerebellar Purkinje cell (Brown et al., 2019). Moreover, granule cell to Purkinje cell synaptic transmission can trigger endocannabinoid release (Alger and Kim, 2011), which may be important for information processing by cerebellar molecular layer interneurons (Dorgans et al., 2019). This suggests that endocannabinoids could be essential to neurocognitive aspects of cerebellar function (Di Marzo et al., 2015)^,(Marcaggi, 2015)^,(Alger and Kim, 2011). Accumulating evidence also suggests cerebellar modulation of the reward circuitry and social behaviour, via direct cerebellar innervation of the ventral tegmental area (VTA) including dopamine cell bodies (A1) in the VTA (Carta et al., 2019). The VTA-dopamine (DA) signalling in the nucleus accumbens (NAc) and the medial prefrontal cortex (mPFC) (Lohani et al., 2019) play a key role in motivatedbehaviours and cognition. Cerebellar neuropathological changes can result in aberrant dopaminergic activity in the NAc and mPFC (ROGERS et al., 2011)^,(Lohani et al., 2019). Therefore, there is a critical need to determine how cerebellum modulate limbic VTA-DA signalling. Cerebellar Non-Invasive Brain Stimulation (NIBS) is postulated to be most relevant in CUD since endocannabinoids are essential to cerebellar function that includes reward-related behaviours, information processing, and cognitive control. (Di Marzo et al., 2015)^,(Marcaggi, 2015)^,(Alger and Kim, 2011). Furthermore, cerebellar NIBS can facilitate training of cognitive control in CUD during a during visual cue reactivity paradigm using a mobile virtual reality (VR) interface that can also allow remote delivery of cerebellar NIBS in conjunction with VR-based cognitive training for home-based intervention. Specifically, transcranial electrical stimulation (tES) can be translatable to low-cost (<$150) mobile devices that can be used in a low resource home-based setting (Carvalho et al., 2018).

Breast Cancer metastasis remains a formidable challenge in cancer research, contributing significantly to patient mortality despite advances in medical research. Lung metastasis, associated with breast cancer, poses an ongoing clinical dilemma with limited curative treatment options. This study delves into the intricate mechanisms underlying Breast Cancer-Lung Metastasis (BC-LM) primarily focusing on the function of SH3PXD2B in maturation of invadopodia, inducing epithelial-to-mesenchymal transition, disruption of proteostasis network, and ultimately leading to metastasis of Breast Cancer (BC) cells. With an extensive analysis of differential gene expression using RNASeq data, comparing normal breast cancer cells to metastatic sub-populations in lung. Employing the New Tuxedo pipeline our investigation notably observes SH3PXD2B as a key regulator in lung metastasis samples. This trend is further substantiated by data from the Cancer Cell Line Encyclopedia (CCLE), and Human Protein Atlas (HPA) which highlights elevated SH3PXD2B expression in MDA-MB-468 cells, underscoring its significance in metastatic adenocarcinoma. Additionally, we checked the overall survival (OS) of metastatic breast cancer (MBC) patients pinpointing SH3PXD2B and its associated partners like SH3PXD2A, MMPs, CTTN, ADAMs, and EMT markers with substantial expression in both BC and lung cancer, prognosticating poorer patient survival. Further, our transcription factor – target gene (TFTG) network essentially elucidated the role of SH3PXD2B as a key node in the network unveiling its roles in regulating cell migration, communication, and developmental processes. Proteomics and Western blotting assays consistently confirm heightened SH3PXD2B expression in BC cell lines, reaffirming our findings. By employing computational structure biology along with cancer systems biology approach, we generated a high-confidence structural model of SH3PXD2B, indicating its SH3_2 and SH3_3 domains crucial for interactions with the drug molecules. Molecular docking simulations identify Eribulin as a promising therapeutic agent capable of targeting these domains. Thus, our multidisciplinary approach seamlessly amalgamates systems medicine principles, aiming to repurpose existing drugs that target SH3PXD2B based on molecular signatures. Targeted therapies have emerged as a promising avenue for addressing MBC and this mechanistic model introduces novel therapeutic avenues for the treatment of BC-LM patients.

Infective endocarditis remains an illness that carries a significant burden to healthcare resources. In recent times, there has been a shift from Streptococcus sp to Staphylococcus sp as the primary organism of interest. This has significant consequences given the virulence of Staphylococcus and its propensity to form a biofilm, rendering non-surgical therapy ineffective. In addition, antibiotic resistance has affected treatment of this organism. The cohorts at most risk for Staphylococcal endocarditis are the elderly patients with multiple comorbidities. The innovation of transcatheter technologies alongside other cardiac interventions such as implantable devices have contributed to the increased risk attributable to this cohort. We examine the role of the heart team for diagnosis and treatment of this condition. In addition, we examine the determinants of virulence of Staphylococcus aureus, the interaction with hosts immunity and the discovery and emergence of a potential vaccine. We also examine the potential role of prophylactic antibiotics during dental procedures. With increasing rates of transcatheter device implantations, there is a projected increment of endocarditis especially in this high-risk group. A high index of suspicion is needed alongside early initiation of therapy and referral to the heart time to improve outcomes.

: Using line × tester analysis, the current research analyses parental genotypes and their combinations in normal conditions and identifies the genes influencing yield characteristics. In the present study, 15 diverse genotypes, including 10 lines, 5 testers, and 50 F1s hybrids, were evaluated for 13 morphological and 2 biochemical traits. A suitable location was taken to study the effect of 15 characters. The results exposed that ability mean squares were significant for all studied additive and non-additive components. In this direction, the general combining ability of PBW-343, DBW-39, K-402, K-1317, KRL-210, and K-68 were higher than the remaining parents. For morphological traits like yield, the top five crosses were described based on SCA effects, namely, HD-3086 × HD-3171, K-402 × K-9107, K-1317 × K-9107, HD-2967 × K-0307 and K-402 × K-68 in F1 generation. In addition, the high value of heritability was estimated for plant height (77.32%), spike length (32.26%), biological yield/plant (59.52%), and grain yield/plant (68.76%). However, the moderate values of heritability were estimated for days to maturity (22.78%) and phenol color reaction (18.00%). The higher genetic advance was not found for recorded characters; however, a moderate genetic advance was recorded for grain yield per plant (13.15%) and harvest index (11.72%). High heritability coupled with moderate genetic advance was recorded for two characters grain yield per plant and harvest index in F1 and F2 generations.

Nanotechnology has become a popular topic in agricultural and animal research, generating sig-nificant global interest. Nanoparticles (NPs)-enabled agriculture and animal husbandry (AHs) products have three main principles: crop production, protection, and nutrient enrichment. Re-search on this topic has grown exponentially in recent years, with an increasing number of peer-reviewed literature and patents on NPs-enabled agriculture and AH products. This study examines and collects data on the various applications of NPs-enabled agricultural products for crop production, protection, and livestock improvement from the core nanotechnological database. The search returned several types of NPs and products used in agriculture and AH, countries that utilize these products at a commercial level, and analysis of these data by phyton, R-statistical software. Our findings show remarkable growth of nanotechnology in agriculture, AH, and re-search fields for future sustainability goals in the era of climate change

Drug discovery utilizes high-throughput screening (HTS) methods applying target and cell-based assays. This review discusses the challenges and benefits associated with these assays in HTS. Discussed the strategies that can be applied for the development of screening assays through primary and secondary screens for target identification. Further discussion on identify-ing the most efficacious drugs following these approaches in cancer. Even though various drugs have been identified to treat cancer, there is high demand of more relevant phenotypic assays to produce desired diseased phenotype to only highlighting the specific targets instead of off-targets. Hopefully, the new developing strategies could provide innovative drugs to treat cancer patients to reduce mortality rate.