Objective: To determine demographic predictors and comorbidities in hospitalized children with conduct disorder. Methods: A retrospective analysis was performed using Nationwide Inpatient Sample (2012–2014). All patients were ≤18 years and cases with primary diagnosis of conduct disorder (N = 32345) and a comparison group with another psychiatric diagnosis (N = 410,479) were identified using ICD-9-CM diagnosis codes. A logistic regression model was used to generate the Odds Ratio (OR) between both groups. Results: Children <11 years old have five times greater chances of admission for conduct disorder than adolescent (OR 5.339). African American males are more likely to be admitted for conduct disorder. Children with conduct disorder from low-income families have a 1.5 times higher likelihood for inpatient admission compared to high-income families. These children have about eleven times higher odds of comorbid psychosis (OR 11.810) and seven times for depression (OR 7.093) compared to the comparison group. Conclusion: Conduct disorders are more debilitating for children and families than many providers realize. African American male under 11 years is at the highest risk for inpatient management for conduct disorder. These patients have a higher risk of comorbid psychosis and depression which may further deteriorate the severity of illness and require acute inpatient care.

The cryopreservation of gametes and embryos is an important element of biodiversity conservation. One species in need of conservation is the honey bee Apis mellifera L. Changing environmental factors, especially the anthropogenic factor, have led to a reduction in the numbers of this insect species. In this study, we provide an example of the creation of a biobank of honey bee drone sperm. For sperm cryopreservation, drones of the most common subspecies of honey bees common in Russia were selected. These were the dark forest bee, Apis mellifera mellifera from the Republic of Bashkortostan, with three subspecies (A. m. carnica, A. m. carpatica, and A. m. caucasica) from the southern regions of Russia, as well as two breeding stocks, the Far Eastern bee and Prioksky bee. For subspecies identification, morphometric and genetic methods were used. The subspecies of the studied samples were confirmed by the analysis of the tRNAleu-COII locus of mitochondrial DNA and nine microsatellite markers of nuclear DNA. It was shown that bees of the Prioksky breeding stock belong to the subspecies A. m. caucasica based on phylogenetic analysis, and the Far Eastern breeding stock is a stable hybrid, descending on the maternal line from the evolutionary lineage C or O. The results of the morphometric analysis are consistent with the results of the genetic analysis. For the cryopreservation of sperm, we used a honey diluent. As a result, the viability of frozen–thawed sperm decreased by 20.3% compared to fresh sperm, and overall motility decreased by 25-fold. The measurement of the sperm concentration in the spermatheca of artificially inseminated queens showed that it varied from 0.22 to 4.4 million/μL. Therefore, the use of honey in sperm cryopreservation has great potential.

Honey is a very cost-efficient food source and a valuable export for the country of Uganda, but is commonly adulterated, resulting in consumers not being aware of the contents of their honey. As a result, it is important to be able to authenticate the honey that consumers are purchasing. This study evaluated the physicochemical properties (pH, free acidity, metal determination, moisture content, and FTIR spectra) of Ugandan and Manuka honey. Honey pH values ranged from 3.3 to 4.8 (±0.6) while free acidity values ranged from 34.87 to 62.22 (±8.69). The moisture content values of all honey samples were below 22%. The metal concentrations and functional groups present in Ugandan and Manuka honey were determined. Metal analysis by atomic absorption spectrometry detected five elements (Na, Ca, K, Cu, and Pb) in all honey samples in varying concentrations. The elemental concentrations were found in descending order as follows: sodium (Na) (9.38 ppm), calcium (Ca) (4.99 ppm), potassium (K) (2.48 ppm), copper (Cu) (1.87 ppm), lead (Pb) (0.28 ppm). FTIR analysis revealed similar patterns of spectral curve (O-H stretching and C-H stretching) across all honey samples analyzed, which is consistent with previously analyzed honey samples from other studies. Ugandan honey sample 7 collected in the Masaka Region was found to be most similar to the Manuka honey standard based on its observed physiochemical properties. All properties analyzed suggested Ugandan honey is of good quality and safe for consumption.

Due to the great nutritional and medicinal value of honey, there has been growing consumer’s preference towards honey of a known identity. However, honey now is the third food in the world subjected to adulteration. Therefore, the current study was focused on judging the identity of Sudanese honeys and checking whether there is any misdesignation from originality. Melissopalynology was used as a tool for this purpose. A number of 60 honey samples were purchased from honey sellers. Results indicated that honey bees foraged on a bio-diversified number of plant species constituted of 11 major families [Fabaceae (43.3%), being the predominant family] and 8 minor families. Respectively, 18.3% &amp; 2% of the honey samples were found to be misdesignated by the honey sellers from their botanical and geographical identities. Some samples were predicted by melissopalynology to be originated from Ethiopia by the presence of marker pollens such as Kniphofia foliosa, Guizotia abyssinica, and Acacia abyssinica an indigenous Ethiopian flora. Thus these findings proved that melissopalynology is an effective tool in judging the identity of honey and pro of being inexpensive.

The electronic cigarette or e-cigarette is the new alternative method to deliver nicotine. In 2007, the United States introduced vaping devices on the market. Due to their attractive taste and lack of adverse effects, these vaping devices have gained popularity among youth and adults. However, there has been increasing evidence that vaping can cause severe lung injury, and these devices release toxic chemicals into the body. E-cigarettes are recognized as a global threat to public health. Nicotine, the most prevalent chemical in vaping devices, is associated with neurological problems and cognitive decline. Long-term use of e-cigarettes can cause adverse health problems, including respiratory illnesses, asthma, bronchitis, and lung inflammation. In 2019, the Centers for Disease Control and Prevention (CDC) officially declared vaping-associated illness EVALI (e-cigarette or Vaping Product Associated Lung Injury). The US Surgeon General published an alarm in December 2016 that e-cigarette consumption among adolescents and teens in the US is a "major public health concern" and that more young people are now vaping than smoking traditional cigarettes and cigars. Since its commercial introduction in 2003, modern electronic cigarettes (or E-cigarette s) have become increasingly popular with smokers, non-smokers, and those who used to smoke who have switched to them. With such a rise in consumption, people are becoming more aware of the irritating, harmful, and perhaps cancer-causing effects on the lungs. (Chadi et al., 2019; Dinardo & Rome, 2019; Lyzwinski et al., 2022; Marrocco et al., 2022; O’Callaghan et al., 2022)

The presence of antibiotic residues in honey has recently become a growing public health concern due to the overuse of these products in beekeeping and their transfer to the food industry. The aim of this study was to develop and validate a simple, selective and sensitive method for the simultaneous identification and quantification of residues of twenty-two sulfonamides, trimethoprim and dapsone in honey using a rapid and reliable liquid chromatography–tandem mass spectrometry (LC–MS/MS) method. The developed method showed good linearity, specificity, precision (repeatability and intra-laboratory reproducibility) and recovery. The decision limit (CCalpha) ranged between 2.16-22.12 µg/kg for CCα, while the detection capability (CCbeta) was between 2.16- 2.67-27.36 µg/kg. The method proved to be rapid, reliable and effective for the determination of sulfonamides, trimethoprim and dapsone from honey samples. The average recoveries were estimated to be between 70 and 106%. The relative standard deviations (RSDs) were between 6-18%. In practice, the method is essential to check the honey sold on the market and ensure its safety before it reaches the consumer.

Parkinson's Disease (PD) is a neurodegenerative disorder that affects the motor system of the human body. Currently, the available treatments are limited and often have undesirable side effects. In this context, the aim of this study was to develop a novel combinational formulation of Apomorphine and Quetiapine and evaluate its efficacy in a rat model of PD. The formulation was prepared using the solvent evaporation technique and characterized for its physicochemical properties. The in-vitro drug release was evaluated using the Franz diffusion cell method, and the pharmacokinetics of the combination was studied in rats. The behavioural and biochemical parameters were evaluated in the rats using the Rotarod, pole test, and biochemical assays. The results showed that the developed formulation had satisfactory physicochemical properties and exhibited sustained drug release. The pharmacokinetic studies showed that the combination exhibited a longer residence time than the individual drugs. The behavioural and biochemical parameters showed that the combination was effective in improving motor function and reducing oxidative stress. In conclusion, the developed Apomorphine and Quetiapine combination formulation showed promising results in improving motor function and reducing oxidative stress in rat model of PD. Further studies are required to evaluate the safety and efficacy of the developed formulation in humans.

Although, Artificial intelligence (AI) helps experts with crime analysis, research, and understanding, it has a favourable influence on cyber security. It strengthens the tools that businesses use to safeguard their networks, clients, and workers against dangerous online behaviour. However, artificial intelligence is infamous for requiring a lot of resources. It may not, however, always be relevant. Additionally, it can provide hackers a new tool and advance their abilities. Actually, the VPN industry benefits from AI in the same way. The threat posed by machine learning in AI to user data privacy may be lessened by using a VPN on all of your devices. Because they use machine learning algorithms, VPNs are better equipped to shield their users from internet-based threats. Artificial intelligence (AI) has reportedly being investigated as a means of enhancing internet security for a considerable amount of time, according to Smart Data Collective. We anticipated that AI and machine learning will have a substantial impact on the future of cyber security around two years ago.

Honey has been employed for the treatment of wounds and diseases for ancient time, thanks to its antimicrobial and curative properties. This study aims to present the biochemical characteristics, including the amount of sugar, total phenols, phenolic chemicals, antioxidant properties, and antibacterial activities of a specific type of French honey (Sologne summer forest) in comparison with a manuka honey. According to our findings, the Manuka honey tested has 23% fewer polyphenols total than Sologne summer forest honey. The results showed that the Sologne summer honey had a different polyphenols profile than Manuka honey with specific polyphenol like p- Hydroxybenzoic acid. Additionally, the antioxidant activity of the two honeys is comparable (9 μmole Trolox.g-1 honey). Furthermore, the antibacterial activity of the two honeys is comparable against Pseudomonas aeruginosa and Staphylococcus aureus. Our research indicates for the first time that there are significant nutritional and biological potentials for a French honey from the Sologne summer forest.

Historically, urban development has always been centered on coastal areas – with access to waterbodies – seas, rivers and canals being a significant advantage for movement and trade. With most of the world’s megapolises located on coasts, land reclamation offers a solution for the expansion of city centers which are otherwise restricted by the coastline. The current understanding of urban regeneration and development on reclaimed lands is defined in this study, answering the basic questions of what, why and how. This study aims to assess the urban regeneration on reclaimed coastal land based on the principles of sustainable development defined by existing studies. The literature review establishes a theoretical framework and defines performance-based benchmarks identifying the spatial indicators of urban development. Composite indicators namely open space coverage, land use mix, percentage of coast for people, accessibility to public transportation and amenities, availability of pedestrian paths and cycling tracks and adequate road networks are considered for this framework. The conclusions are drawn based on the results of the analysis of spatial layout using GIS as a tool to map and empirically measure each indicator. The framework is validated using a major land reclamation project, West Bay, in the coastal urban area of ​​the city of Doha. The results determine that West Bay has achieved a good level of sustainability, although there are areas that could be enhanced to further improve the overall sustainability of urban development. These findings can serve as a guide for policymakers and various stakeholders for sustainable urban planning on reclaimed coastal lands.

The 5-hydroxymethylfurfural (HMF) is a six-carbon heterocyclic organic compound with two substituents an aldehyde group and an alcohol group. It is formed from saccharides as a result of two reactions: the Maillard reaction and the caramelization of saccharides. It has both a negative and a positive effect on the human body, which makes it, even more, an attractive research object. The objective of the study was to determine HMF content in honey samples available on the Polish market using three varied methods and compare the results obtained. The methodology used included: two spectrophotometric methods (by White and Winkler) and the HMF determination method based on the LC-MS/MS technique developed uniquely for this study. The determined HMF content in all tested honey samples did not exceed the applicable standard. All results are within the scope of the European Council Directive 2001/110/EC of 20 December 2001, i.e. they do not exceed HMF content in honey, which is 40 mg/kg.

The fields of electronics and information technology have witnessed rapid development during the last decades, providing significant technical support to the field of biological sciences. Radio-Frequency Identification (RFID) technology has been used to automate the monitoring of animal location and behaviors in a wide range of vertebrate and invertebrate species, including social insects such as ants and honey bees (Apis mellifera L.) This technology relies on electromagnetic fields to identify and track transponders attached to objects automatically. Implementing new technologies to serve research purposes could be time-consuming and require technical expertise from entomologists and researchers. Herein, we present a detailed description on how to harness RFID technology to serve honey bee research effectively. We describe how to build and operate a 32-antenna RFID system used to monitor various honey bee behaviors such as foraging, robbing, queen and drone mating, which can be used in other social insects as well. Preliminary data related to queen nuptial flights were obtained using this unit and presented in this study. Virgin queens labeled with ~5mg transponders performed multiple (1-4) nuptial/orientation flights a day (9 am to 5 pm) ranging from 8 to 145 seconds each. Contrary to virgin queens, no hive exit was recorded for mated-queens. At full capacity, this unit can monitor up to 32 honey bee colonies concurrently and is self-sustained by a solar panel to work in remote areas. All materials, hardware and software needed to build and operate this unit are detailed in this study, offering researchers and beekeepers a practical solution and a comprehensive source of information enabling the implementation of RFID technology in their research perspective.

Internet of things security will be a big challenge for the enterprises working behind the build-up of the internet of things, and it’s application. With IoT, another buzzword is blockchain-based cryptocurrency bitcoin. Blockchain technology has proven itself as one of the most secured existing technology. In this paper, we have discussed the significant challenges that will come up in identity management due to the heterogeneity of devices. We have proposed a solution for privacy preservation using secure identity management and possible communication methodology by using public key-based cryptography used in the blockchain. We have taken the ecosystem of smart home management and smart health management. At last, we have concluded with the discussion of futuristic applications of blockchain in other applications of the internet of things.

The present study aims to elucidate the effect of melatonin (MEL) on dexamethasone (DEX)-induced reproductive impairments in rats. Rats were procured and acclimatized with adequate food and water ad libitum. Twenty-four rats were divided into four groups (six in each) of Control, DEX (70µg/100g bw), DEX plus MEL, and MEL (200µg/100g bw) for 21 days. After completion, rats were sacrificed, and testes were dissected, weighed, and processed for biochemical, and receptor expression. Serum was collected for hormonal assay. DEX-treated rats showed a significant increase in lipid peroxidation (TBARS), a decrease in weight of the body and testes, and the level of antioxidative enzymes (superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPX), glutathione oxidase (GSH), glutathione reductase (GR), glucose 6-phosphate dehydrogenase (G6PDH), glutathione S-transferase (GST)), total cellular protein content, serum testosterone, corticosterone, LH, FSH, melatonin levels, AR, MT1, and MT2 receptor expression. Marked cellular alterations were noted in the testis histology of the DEX group. Melatonin treated in DEX rats showed recovery and restoration in gravimetric, serum hormonal, biochemical parameters, receptor expression, and cellularity of testes. Therefore, findings suggest that melatonin improved defence against DEX-induced testicular damages suggesting its therapeutic potential for the management of male reproductive health.

With ongoing colony losses driven in part by the Varroa mite and the associated exacerbation of virus load, there is an urgent need to protect honey bees (Apis mellifera) from fatal levels of virus infection and from nontarget effects of insecticides used in agricultural settings. A continuously replicating cell line derived from the honey bee would provide a valuable tool for study of molecular mechanisms of virus – host interaction, for screening of antiviral agents for potential use within the hive, and for assessment of the risk of current and candidate insecticides to the honey bee. However, the establishment of a continuously replicating, honey bee cell line has proved challenging. Here we provide an overview of attempts to establish primary and continuously replicating hymenopteran cell lines, methods (including recent results) for establishing honey bee cell lines, challenges associated with the presence of latent viruses (especially Deformed wing virus), in established cell lines and methods to establish virus-free cell lines. We also describe the potential use of honey bee cell lines in conjunction with infectious clones of honey bee viruses for examination of fundamental virology.

Aim of study:Aim of this meta-analysis is to evaluate post-operative procalcitonin as a marker to predict post- operative infectious complications after pancreatic surgeries.Material and Methods:Systemic literature search was performed using MEDLINE, EMBASE and to identify studies evaluating the diagnostic accuracy of Procalcitonin (PCT) as a predictor for detecting infectious complications on postoperative days (POD) 3 and 5 following pancreatic surgery. A meta-analysis was performed using random effect model and pooled predictive parameters for POD 3 and 5 were derived. Geometric means were calculated for PCT cut offs. Results:6 studies included day 3 PCT analysis, 2 studies included both day 3 and day 5 analysis. Total data of 471 patients were derived. 161 patients developed infectious complications. Pooled sensitivity, specificity, pooled area under curve, diagnostic odds ratio (DOR), positive and negative like hood ratio of day 3 PCT were 74%,79%,0.8453, 11.03,3.17 and 0.31 respectively. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), positive and negative like hood ratio of day 5 PCT were 83%,70%,12.91,2.91 and 0.25 respectively. Geometric means for PCT cut off for day 3 and 5 were 0.80 and 0.43. Conclusion:Postoperative procalcitonin particularly day 3 procalcitonin levels predict post-operative infectious complications following pancreatic surgeries.

Aims: Primary AIM of the study was to evaluate effect of prolonged hospital stay on Surgical site infections We also evaluated effect of prolonged hospital stay on overall morbidity in Gastrointestinal and Hepatobiliary Surgery as secondary outcome. Methods: We retrospectively analysed all the patients who underwent gastrointestinal and hepatobiliary surgery between April 2017 to March 2020. On our analysis we found mean hospital stay in patient who did not develop SSI and/or morbidity was 4 days (Total hospital stay) vs 6 days who developed morbidity (hospital stay before diagnosis of SSI or diagnosis or morbid event). Based on this to avoid selection bias, we did 1:1 propensity score analysis between patients who had 4 or less than hospital stay vs patients who had 5 or more hospital stay before diagnosis of surgical site infection and/or morbid event. We took all the preoperative and intraoperative factors like Age, sex, malignant disease, ASA score, CDC grade of surgery, open or laparoscopic surgery, HPB surgeries, colorectal surgeries, Upper Gastrointestinal surgeries and small intestinal surgeries as covariates. We used nearest neighbor matching protocol with a calipher of 0.2. Cases were not reusable after matching. Statistical analysis was done using SPSS version 23. Results: We included 348 patients operated between April 2017 and March 2020 in our analysis. After 1:1 propensity score matching 58 patients included in study arm (prevent hospital stay more than 4 days) and 56 patients in control arm. Both groups were comparable with regard to Age, Sex, Surgery for malignant disease, ASA score, CDC grade of surgery, HPB surgeries, Small intestinal surgeries, Colorectal surgeries, upper gastrointestinal surgeries, intraoperative blood product requirement, intraoperative hypotension or any other event, operative time. Prolonged hospital stay (> 4 days) was significantly associated with surgical site infections (p<0.0001), morbidity (p=0.001). Open surgeries were associated with prolonged hospital stay. (p=0.032). Conclusion: Prolonged Hospital stay is associated with increase surgical site infection and morbidity in Gastrointestinal and Hepatobiliary Surgery.

AIM: Aim of our study was to evaluate incidence and causative factors for acute kidney injury in gastrointestinal and hepatobiliary surgeries. Material and methods: All the gastrointestinal surgeries performed between April 2018 to March 2020, in our institution have been analysed for acute kidney injury. Acute kidney injury defined according to acute kidney injury network classification. Categorical variables were evaluated by chi square test and continuous variables by Mann Whitney U test. Statistical analysis was done using SPSS version 23. P< 0.05 was considered significant Results: We performed 331 gastrointestinal and hepatobiliary surgery from April 2018 to March 2020. After exclusion 317 patients were included in study population.14 patients (4.4%) were defined as having acute kidney injury according to acute kidney injury network classifications. On univariate analysis acute kidney injury was associated with open surgery (p= 0.002, Intra operative hypotension (p=0.006), CDC grade of surgery (p<0.001), increased used to blood products (p=0.004), higher ASA grade (p<0.0001), increased operative time(p<0.0001). On multivariate logistic regression analysis higher ASA grade (p=0.001) and increased operative time (0.015) independently predicted acute kidney injury. Acute kidney injury was also significantly associated with 90 days mortality. ( p= <0.0001) Conclusion:Post-operative acute kidney injury was associated with significant mortality in gastrointestinal and hepatobiliary surgery. Open surgery, higher CDC grade surgery, more blood products, higher ASA grades, increase operative time predicted acute kidney injury in post operative periods. Higher ASA grades and increased operative time predicted acute kidney injury.

Aim: Aim of our study to evaluate various factors responsible for surgical site infection after gastrointestinal and hepatobiliary surgeries. Material and Methods: Patient who underwent gastrointestinal and hepatobiliary surgery in our department were evaluated retrospectively. Various factors associated with surgical site infection were evaluated using univariate and multivariate analysis. Surgical site infection was defined as any culture positive discharge from the wound within 30 days of surgery.Statistical analysis was done using SPSS version 23. Results: We evaluated total 331 patients operated between April 2018 to March 2020. 14 patients were lost to follow up after discharge and before completing post operative day 30. 18 patients expired before 30 days without developing SSI and were excluded from the study as per exclusion criteria. 299 patient included in the study. Total 20 patients developed surgical site infection. It showed SSI rate in our study population was 6.68%. On univariate analysis prolonged hospital stay, more blood product used, higher cdc grade of surgery, higher ASA grade, more operative time, open surgeries,colorectal and HPB surgeries were associated with surgical site infections. On multivariate analysis only prolonged hospital stay independently predicted Surgical Site Infectins. (p=0.014,0dds ratio 1.223, 95% confidence interal 1.042-1.435). Conclusion: Prolonged hospital stay independently predicts surgical site infections after gastrointestinal and hepatobiliary surgery.

This article explains how resistance alleles have become rare or have disappeared from honey bee populations in Europe (and probably also in North America). Honeybees have the highest recombination frequency of all animals, indicating that pathogenic bacteria, viruses, fungi and microsporidia are an important source of selection. To respond to new virulent strains of pathogens, honeybees need to have access to rare alleles that could foster immunity against a new pathogen. By mating in a large panmictic population, new rare alleles can be recruited, which can then be combined into new genotypes through recombination with useful alleles of other genes. Bee breeders, by selecting small samples from a large population tend to select common alleles and lose the rare ones. Rare alleles can become important when a new virulent pathogen arrives. The loss of rare alleles makes bees vulnerable to disease and parasites and explains, together with the problems caused by modern agriculture, why managed bees have high mortality rates.

New biocements based on a powdered mixture of calcium phosphate/monetite (TTCPM) modified with the honey addition were prepared by mixing the powder and honey liquid components at a non-cytotoxic concentration of honey (up to 10% (w/v)). The setting process of the cements was not affected by the addition of honey, and the set-ting time of ~4 min corresponded to the fast setting calcium phosphate cements (CPC´s). The cement powder mixture was completely transformed into calcium-deficient nanohydroxyapatite after 24 hours of hardening in simulated body fluid, and columnar growth of long needle-like nanohydroxyapatite particles around the original calcium phosphate particles was observed in honey cements. The compressive strength of honey cements was reduced with the content of honey in the cement. The comparable antibacterial activity of cements with honey solutions was found on Escherichia coli, but very low antibacterial activity was found for Staphylococus aureus for all cements. The enhanced antioxidant inhibitory activity of composite extracts was verified. In vitro cytotoxicity testing verified the non-cytotoxic nature of honey cement extracts, and the addition of honey promoted alkaline phosphatase activity, calcium deposit production, and upregulation of osteogenic genes (osteopontin, osteocalcin, and osteonectin) by mesenchymal stem cells, demonstrating a positive synergistic effect of honey and CPC on the bioactivity of cements that could be promising therapeutic candidates for the repair of bone defects.

A two-year study was conducted in Maine wild blueberry fields (Vaccinium angustifolium Aiton) on the health of migratory honey bee colonies in 2014 and 2015. In each year 3-5 colonies were monitored at each of 9 wild blueberry field locations during bloom (mid-May until mid-June). Colony health was measured by assessing percent worker and sealed brood rate of change from the beginning of bloom until the end of bloom. Potential factors that might affect colony health were queen failure or supersedure; pes-ticide residues on trapped pollen, wax comb, and bee bread; and parasites and pathogens. We found that Varroa mite and pesti-cide residues on trapped pollen were significant predictors of colony health as measured by the percent rate of change of sealed brood during bloom. These two factors explained 71% of the variance in colony health over the two years. Pesticide exposure was different in each year as were pathogen prevalence and incidence. We detected high prevalence and abundance of two recently discovered pathogens and one recently discovered parasite, the trypanosome Lotmaria passim Schwartz, the Sinai virus, and the phorid fly, Apocephalus borealis Brues.

The objective of this study was to evaluate the glycemic index and the satiety response of three Mexican kinds of honey. The values of fructose ranged from 272.40-395.10 g/kg, while the glucose value ringed 232.20-355.50 g/kg. The ratio F/G of sample honey was 1.45, 1.00, and 1.17 for Highland, Multifloral, and Avocado honey, respectively. Twenty-six participants completed this study, which was previously approved by the ethics committee of the Facultad de Salud Pública y Nutrición (CE 2/2018-19). Highland and Avocado honey is classified as medium-GI (69.204.07 and 66.365.74, respectively), while Multifloral honey is classified as high-GI (74.245.98). The Highland honey presented the best satiety response. The difference in IG values and the effect of the satiety response of Highland honey could be explained by the different fractions of carbohydrates in samples and other components such as phytochemicals.

Ethanolic extracts of propolis collected from Apis mellifera hives have been shown to reduce Nosema ceranae infection in honey bee workers. This study aimed to determine the propolis concentration that optimizes the control of N. ceranae infection in honey bee workers. Newly emerged worker bees were individually fed 2 μL of 50% sucrose solution (w/v) containing 105 N. ceranae spores per bee, and treated with 0%, 25%, 50%, and 75% ethanolic extracted propolis in 50% sucrose solution (v/v). The treated bees were maintained in cages at 34 ± 2˚C and 55 ± 5% RH throughout the study. The number of dead bees was counted and removed from the cages daily for 30 days to generate survival curves. The number of N. ceranae spores per bee (infectivity) was quantified using a hemocytometer, and the number of infected bees per hundred bees (infection rate) was determined. The survival rates of N. ceranae infected bees fed 25%, 50%, and 75% propolis (NP1, NP2, NP3, respectively) were significantly higher than those of infected bees not fed propolis (NO). Furthermore, the infectivity and infection rates of NP2 and NP3 groups were significantly lower than those of the NO group. The infectivity and infection rates of the NP1 group were not different than those of the NO group. Our data suggest that 50% and 75% propolis extracts are appropriate concentrations for treating N. ceranae infection in honey bees. Ethanolic extracted propolis can be an alternative treatment for N. ceranae infection in Western honey bees.

In this paper we show the results of investigating the presence of organochlorine pesticides in honey and pollen samples from managed colonies of the honey bee, Apis mellifera L. and of the stingless bee Scaptotrigona Mexicana Guérin. We found that 88.44% and 93.33% of honey samples, and 22.22% and 100% of pollen samples of S. mexicana and A. mellifera, respectively, resulted positive to at least one organochlorine. The most abundant pesticides were DDE, DDT, Endrin and heptaclor. Despite the low foraging range of S. mexicana the number of pesticides detected in the honey samples was similar to that of A. mellifera. Paradoxically we a found a small number of organochlorines in pollen samples of S. mexicana, perhaps indicating a rapid turnover of this material as compared to A. mellifera.

Multi-morbidity and polypharmacy are common in older people and pose a challenge for health and social care systems especially in context of global population ageing. They are complex and interrelated concepts in the care of older people that require early detection and patient centred decision making that are underpinned by the principles of multidisciplinary led comprehensive geriatric assessment (CGA). Personalised care plans need to remain responsive and adaptable to the needs of a patient, enabling an individual to maintain their independence.

Over the centuries, honey is known for its superior usage in culinary, and for its rich nutrition and therapeutic values which are scientifically proven in the medical field. The chemical composition of honey varies depending on its botanical sources and environment. Therefore, the nutrition content in honey is highly likely to be affected by contaminants, such as heavy metals and pesticides. To ensure the quality of honey, parameters such as the heavy metal content should be within the safe range of total standard mineral and trace elements as defined by the International Food Standard (Codex Alimentarius), and pesticides should not be present at all. The high concentration of heavy metal and pesticides not only deteriorates the quality and quantity of honey, but also causes harm to the bee colony itself. In the agriculture sector, the excessive usage of pesticides and fertilizer negatively impacts the overall honey production process. Bees, a pollinating agent, bring the polluted nectar back to their beehives, eventually contaminating the honey and depreciating its value. Hence, this article will comprehensively review the activities that contribute to heavy metal and pesticide contamination, the interactions of bees as a pollinating agent, the impact of the pollutant to the colonies, and subsequently to the honey production.

Social insects, such as honey bees exhibit complex behavioral patterns and their inconspicuous coordination enables decision-making on the colony level. It is thus proposed, that a high-level description of their collective behavior might share commonalities with neural processes in the brains. At the same time, recent research concerning overarching features of neural activity implies that brains are poised at the edge of the critical phase transition and that such a state is enabling maximal computational power and adaptability. In our research, we applied some tools developed in the computational neuroscience field to the dataset of bee trajectories recorded within the hive, during the course of many days. Our results imply that certain characteristics of the system are remarkably similar to the Ising model when it operates at critical temperature and also shares some of the features with the human brain at the resting state

The parasitic mite, Varroa destructor, has shaken the beekeeping and pollination industries since its spread from its native host, the Asian honey bee (Apis cerana), to the naïve European honey bee (A. mellifera) used commercially for pollination and honey production around the globe. Varroa is the greatest threat to honey bee health. Worrying observations include increasing acaricide resistance in the varroa population and sinking economic treatment thresholds, suggesting that the mites or their vectored viruses are becoming more virulent. Highly infested weak colonies facilitate mite dispersal and disease transmission to stronger and healthier colonies. Here, we review recent developments in the biology, pathology and management of varroa, and integrate older knowledge that is less well known.

Honey is a complex sweet food stuff with well-established antimicrobial and antioxidant properties. It has been used for millennia in a variety of applications, but those most noteworthy include treatment of surface wounds, burns and inflammation. A variety of substances in honey have been suggested as the key component to its antimicrobial potential; polyphenolic compounds, hydrogen peroxide, methylglyoxal and bee-defensin 1. These components vary greatly across honey samples due to botanical origin, geographical location and the individual bee. The use of medical grade honey, Medihoney and Revamil, in the treatment of surface wounds and burns has been seen to improve the healing process, reduce healing time, reduce scarring and prevent microbial contamination. Therefore, medical grade honeys should be used for these treatments and reduce the demand for antibiotic usage. In this review, we aim to outline the constituents of honey and how they affect the antibiotic potential of honeys in a clinical setting.

With the increase in technological advancements, architects and engineers over the past couple of decades have been trying to achieve high efficiency within construction projects. Their goals also include reducing global warming effects from construction and building new construction faster for the growing population in urban cities. This requires using a construction method that is less harmful to the environment and faster than other traditional methods. Modular construction, also known as modular construction, is the method that has the potential to make this happen. This review paper discusses what modular construction is and how it is different from the traditional on-site construction. Environmental impacts of using modular construction and what leads to it being more efficient and faster than on-site construction. The study doesn’t suggest that modular construction is the solution to all the problems being faced in the construction industry today, but it is a potential solution that if used in the right situation and correct manner, can have a huge positive impact on the construction industry.

In India, epilepsy is often viewed with superstition, considered a curse rather than a medical condition. Unfortunately, many affected individuals never receive proper medical attention from neurologists, leading them to seek out alternative remedies, including sorcery. Presently, the number of neurologists in India stands at approximately 3000, a concerning figure given the prevalence of epilepsy, which is reported to affect 5.59 to 10 individuals per 1000. This equates to over one million epilepsy patients across the country, representing more than 1% of the total population. Alarmingly, rural areas experience a higher incidence of epilepsy, around 2%, compared to urban centres, where the incidence is approximately 0.5%. This stark contrast underscores the urgent need for improved access to neurological care, particularly in underserved regions.The term "epilepsy" originates from the Greek verb meaning "to seize" or "to get hold of," forming the basis of its etymology. In certain societies, epilepsy is still interpreted as a "penalty for involvement in a forbidden ritual," although perceptions vary among different cultural groups. Individuals diagnosed with epilepsy (PWE) often exhibit behaviours that have led some to speculate about demonic possession or past-life transgressions as causative factors. Consequently, the term "epilepsy" carries diverse social connotations, leading to variations in treatment approaches based on differing perspectives of the condition. Regrettably, some negative attitudes towards epilepsy have fueled stigma, enduring disability, and significant adverse outcomes for those living with the condition.The majority of unreported cases turn to sorcery, exacerbating the already high mortality rates associated with epilepsy disorder and status epilepticus. Various treatment modalities exist for patients with epilepsy to manage their seizures. Given the debilitating and life-altering nature of epilepsy, India offers a range of options including medications (antiepileptic drugs or AEDs), devices, and surgical interventions. When an individual receives a diagnosis of epilepsy (defined as experiencing at least two unprovoked seizures within a short timeframe), life can be dramatically impacted. Several cases highlight the challenges patients face, leading to an increase in Disability Adjusted Life Years (DALY) overall. For newly born infants, constant vigilance from the mother is essential to monitor for any signs of seizure activity around the clock. When a pediatric patient is enrolled in school, their education is often profoundly disrupted. Should the patient be female, her existence would undergo a profound transformation, marked by societal perceptions deeming her as unfortunate and rendering the prospect of marriage untenable. Seizures in young adults precipitate job loss, thereby exacerbating societal burdens. Conclusion: There is a pressing need to raise awareness about epilepsy among the general populace of India. Dispelling misconceptions surrounding epilepsy is essential to steer individuals away from reliance on superstition, and instead, encourage them to seek guidance from certified specialists in nervous system disorders. Thankfully, by following the treatment regimen prescribed by a qualified neurologist, patients can significantly increase their chances of living a life free from seizures, thereby enhancing their overall quality of life and personal fulfilment.

The Voltammetric and polarographic methods are proposed to determine the short time corro-sion rates of brass in 1N HCl solution. It should be noted that it is also possible to determine the corrosion rates of each species present in the solution, simultaneously like Cu (II) and Zn (II) in brass. Samples extracted from bark of Babul (ESBB) is used as corrosion inhibitors. The corrosion inhibition efficiency is 96% at 24h after the test started. These results are compared with the av-erage corrosion rates obtained by using gravimetric (PIT) and some electrochemical methods i.e. galvanostatic and potentiodynamic polarization measurements.

Background: There is ongoing debate regarding the usefulness of laparoscopic pancreaticoduodenectomy. This study aimed to analyze all the randomized control trials published including the most recent one. Material and methods: The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and MOOSE guidelines. Heterogeneity was measured using Q tests and I2. The random-effects models were used to summarise the relative risks, odds ratios, and mean differences as appropriate.Results:4 RCTs were included consisting of 818 patients. 411 patients were in the laparoscopic group and 407 in the open pancreaticoduodenectomy group. Weighted baseline patient characteristics were similar except more patients with pancreatic adenocarcinoma and more males were there in the open pancreaticoduodenectomy group. There was no difference in-hospital stay,90 days complications rate, 90 days mortality, R1 resection, postoperative pancreatic fistula, delayed gastric emptying, post pancreatectomy hemorrhage, bile leak between the two groups. Operative time was more in the laparoscopic group. Blood loss [mean difference -132.12 ml (-172.60,-91.65)] and surgical site infection [Risk ratio 0.41 ( 0.17-1.0)] were significantly lesser in laparoscopic group.Conclusion:There was no benefit in-hospital stay or clinical outcomes after laparoscopic pancreaticoduodenectomy. Blood loss and surgical site infection were lesser in laparoscopic pancreaticoduodenectomy.

Aims and objectives: The primary aim of our study was to evaluate morbidity and mortality following feeding jejunostomy in pancreaticoduodenectomy compared to the control group. We also evaluated individual complications like delayed gastric emptying; post operative pancreatic fistula, superficial and deep surgical site infection. Material and Methods: The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and MOOSE guidelines. Heterogeneity was measured using Q tests and I2.the random-effects model was used. Results: Four studies including Total of 1639 patients were included in the analysis. Total 843 patients were included in Feeding jejunostomy group and 796 patients included in control group without feeding jejunostomy. Over all morbidity was significantly higher in feeding jejunostomy group. (P = 0.001). There was no significant difference between both the groups. (P=0.07). Delayed gastric emptying was significantly higher in feeding jejunostomy group. [P=0.021]. There was no significant difference in development of pancreatic fistula between the two groups. Deep surgical site infection was significantly higher in feeding jejunostomy group. (P=0.013). Hospital stay was significantly more in feeding jejunostomy group (p<0.0001). There was no significant difference between readmission; TPN requirement and time to start oral feed. Conclusion: Feeding jejunostomy seems to be associated with increased morbidity and increased length of stay.

How to align leg segments between the four groups of arthropods (insects, crustaceans, myriapods, and chelicerates) has tantalized researchers for over a century. By comparing the loss-of-function phenotypes of leg patterning genes in diverged arthropod taxa, including a crustacean, insects, and spiders, we show that all arthropod legs can be aligned in a one-to-one fashion. We propose a model wherein insects incorporated two proximal leg segments into the body wall, which moved the ancestral leg lobe (exite) up onto the back to later form wings. For myriapods and chelicerates with seven leg segments, it appears that one proximal leg segment was incorporated into the body wall. According to this model, the chelicerate exopod and the crustacean exopod emerge from different leg segments, and are therefore proposed to have arisen independently. A framework for how to align arthropod appendages now opens up a powerful system for studying the origins of novel structures, the plasticity of developmental fields, and convergent evolution.

Background: Appendicitis is a common cause of emergency department visits and appendectomies in the US, with 250,000 appendectomies performed annually. Current diagnostic methods, such as clinical findings, lead to inaccuracies and missed diagnoses, increasing morbidity and mortality. The only solution is surgery, but current hematological tests are not reliable and may lead to unnecessary surgery if the underlying etiology is self-limiting or requires medical treatment. This study explores the role of MRI as a diagnostic modality that can replace US/CT and supplement traditional clinical diagnostic signs while avoiding ionizing radiation and intravenous contrast medium. The purpose of this meta-analysis is to determine the accuracy of MRI as a diagnostic modality in diagnosing appendicitis, addressing concerns about diagnostic modalities and their adverse effects, and addressing the necessity and success of relevant interventions. Methods: Medical literature was comprehensively searched and reviewed without restrictions to particular study designs, or publication dates using PubMed, Cochrane Library, and Google Scholar databases for all relevant literature formulated in English. The extraction of necessary data proceeded after specific inclusion and exclusion criteria were applied. Meta Analysis was performed for 5206 patients, with 35 RCTs being selected. Analysis was done using the QualSyst tool, wherein two writers independently assessed the caliber of each study as well as the use of the Cochrane tool for bias risk apprehension. The statistical software packages RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20), and Excel in Stata 14 were used to perform the statistical analyses along with other analytical software. Results: MRI had an overall sensitivity of over 95%, an overall specificity of 94.2% with a PPV of 0.875 in comparison to CT scan in the diagnosis and intervention regarding appendicitis. Conclusion: These findings strongly suggest that MRI is a reasonable alternative to CT for the diagnosis of appendicitis in hospitals with appropriate access to this technology for reasons about accuracy, reliability, and reproducibility as well as addressing safety concerns.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological agent of the coronavirus disease 2019 (COVID-19) pandemic which has been a topic of major concern to global human health. The challenge to restrain the COVID-19 pandemic is further compounded by the emergence of several SARS-CoV-2 variants viz. B.1.1.7, B.1.351, P1 and, B.1.617., which show in-creased transmissibility and resistance towards vaccines and therapies. Importantly, the likelihood of susceptibility to SARS-CoV-2 infection among individuals with dysregulated immune response or comorbidities needs greater attention. Herein, we provide a comprehensive perspective regarding ongoing vaccine (mRNA, protein-based, viral vector based etc.) and therapeutic (mono-clonal antibodies, small molecules, plasma therapy, etc.) modalities designed to curb the COVID-19 pandemic. We also discuss in detail the challenges posed by different SARS-CoV-2 variants of concern (VOC) identified across the globe and their effects on therapeutic and prophylactic interventions.

Manuka honey (MH) exhibits potential antitumor activity in preclinical models of a number of human cancers. Treatment in vitro with MH at concentrations ranging from 0.3-5.0% (w/v) led to significant dose-dependent inhibition of proliferation of human breast cancer MCF-7 cells, but anti-proliferative effects of MH were less pronounced in triple-negative MDA-MB-231 breast cancer cells. Effects of MH were also tested on non-malignant human mammary epithelial cells (HMEC) at 2.5% w/v, and it was found that MH reduced proliferation of MCF-7 cells but not that of HMEC. Notably, the antitumor activity of MH was in the range of that exerted by treatment of MCF-7 cells with the antiestrogen tamoxifen. Further, MH treatment stimulated apoptosis of MCF-7 cells in vitro, with most cells exhibiting acute and significant levels of apoptosis that correlated with PARP activation. Additionally, effects of MH induced activation of AMPK and inhibition of AKT/mTOR downstream signaling. Treatment of MCF7 cells with increased concentrations of MH induced AMPK phosphorylation in a dose dependent manner that was accompanied by inhibition of phosphorylation of AKT and mTOR downstream effector protein S6. In addition, MH reduced phosphorylated STAT3 levels in vitro which may correlate with MH and AMPK-mediated anti-inflammatory properties. Further, in vivo, MH administered alone significantly inhibited the growth of established MCF-7 tumors in nude mice by 84%, resulting in an observable reduction in tumor volume. Our findings highlight the need for further research into the use of natural compounds, such as MH, for antitumor efficacy and potential chemoprevention and investigation of molecular pathways underlying these actions.

Abstract: The glucocorticoid receptor (GR), including both alternative spliced isoforms (GRa and GRb), has been implicated in the development of primary open-angle glaucoma (POAG) and iatrogenic glucocorticoid-induced glaucoma (GIG). POAG is the most common form of glaucoma, which is the leading cause of irreversible vision loss and blindness in the world. Glucocorticoids (GCs) are commonly used therapeutically for ocular and numerous other diseases/conditions. One serious side effect of prolonged GC therapy is the development of iatrogenic secondary ocular hypertension (OHT) and OAG (i.e. GC-induced glaucoma (GIG)) that clinically and pathologically mimics POAG. GC-induced OHT is caused by pathogenic damage to the trabecular meshwork (TM), a tissue involved in regulating aqueous humor outflow and intraocular pressure. TM cells derived from POAG eyes (GTM cells) have lower expression of GRb, a dominant negative regulator of GC activity, compared to TM cells from age-matched control eyes. Therefore, GTM cells have a greater pathogenic response to GCs. Almost all POAG patients develop GC-OHT when treated with GCs, in contrast to a GC responder rate of 40% in the normal population. Increased expression of GRb can block GC-induced pathogenic changes in TM cells and reverse GC-OHT in mice. Endogenous expression of GRb in the TM may relate to differences in the development of GC-OHT among the normal population. A number of studies have suggested increased levels of endogenous cortisol in POAG patients as well as differences in cortisol metabolism, suggesting that GCs may be involved in the development of POAG. Additional studies are warranted to better understand the molecular mechanisms involved in POAG and GIG in order to develop new disease modifying therapies to better treat these two sight threatening forms of glaucoma.

Background: World Health Organization (WHO) declared that COVID-19 as a pandemic on March 11, 2020. There is sudden need of statistical modeling due to onset of COVID-19 pandemic across the world. But health planning and policy requirements the estimates of disease problem form clinical data. Objective: To predict recovery rate, cases load rate on the basis of cumulative confirmed Novel Corona virus (NCV) cases, recovered cases and deaths form COVID-19 in India. Methods: The reported COVID-19 cases in the country were obtained from website (https://datahub.io/core/covid-19#resource-covid-19_zip/). The cumulative NCV confirmed cases; recovery cases and deaths were used for estimating recovery rate, cases load rate and death rate till date 24 April 2020. Results: A total of 24530 NCV confirmed cases were reported nationwide in India on 24 April 2020. It is found that the recovery rate increased 22% and case load rate decreased 74%. Death rate is found to be very low 3%. The difference of cases load rate and recovery rate (delta) coincide at 50 % then NCV cases expected would be declined. Conclusion: The epidemic in the country was mainly caused by the importation of India. Lockdown as restricting the migration of population and decided to quarantine of population may greatly reduce the risk of continued spread of the epidemic in India. This study predicts that by 20 May 2020, the cases load rate lesser than recovery rate there after COVID-19 patients would be started to reducing.

Lung cancer, globally recognized as the leading cause of cancer-related mortality, presents a pressing need for innovative treatment strategies. Increasing evidence points towards the potential of monoamine oxidase (MAO) inhibitors in modulating cancer progression, primarily due to their role in regulating cellular metabolism and apoptotic pathways. This extraordinary study delves into the multifaceted therapeutic implications of MAO inhibitors in lung cancer management, elucidating their ability to pave the way for clinical advancement via novel targets and pathways. Capitalizing on recent advances in molecular biology, this research explores the molecular mechanisms underlying the anticancer actions of MAO inhibitors. By examining their impact on cell proliferation, migration, invasion, and apoptosis in lung cancer cell lines, we provide insight into the intricate signaling pathways and biochemical processes modulated by these compounds. The study also investigates the synergistic effects of MAO inhibitors in combination with established chemotherapeutic agents, elucidating their potential to enhance treatment efficacy and reduce cytotoxicity. Furthermore, we delve into the implications of MAO inhibitors on the tumor microenvironment, evaluating their influence on angiogenesis, immune regulation, and the epithelial-mesenchymal transition. This comprehensive analysis enables the identification of novel molecular targets, which hold promise for the development of advanced therapeutics tailored for specific lung cancer subtypes. To substantiate our findings, in this review, we thoroughly analyze the existing literature using state-of-the-art bioinformatics tools." in vivo orthotopic lung cancer models, and clinical patient cohorts. This robust and multidisciplinary approach permits the generation of clinical evidence supporting the integration of MAO inhibitors in lung cancer management. Conclusion: This ground-breaking study establishes the therapeutic potential of monoamine oxidase inhibitors in lung cancer management by unearthing novel pathways and targets for clinical advancement. The outcomes open doors for the development of innovative treatment strategies and inspire continued research efforts to combat the global burden of lung cancer.

In recent years, antimicrobial resistance in many human pathogens has become a serious health concern. Since infections with resistant pathogens cannot be treated with traditional antimicro-bial drugs, new strategies are necessary to fight bacterial infections. Hybrid nano-systems may provide a solution to this problem, by combining multiple mechanisms for killing bacteria to synergistically increase the effectiveness of the antimicrobial treatment. In this review, we high-light recent advances in the development of hybrid nano-systems for the treatment of bacterial infections. We discuss the use of hybrid nano-systems for combinational therapy, focusing on various triggering mechanisms for drug release and the development of biomimetic nanomateri-als. We also examine inherently antimicrobial nano-systems and their uses in preventing infec-tions due to wounds and medical implants. This review summarizes recent advances and pro-vides insight into the future development of antimicrobial treatments using hybrid nanomateri-als.

Aims and Objectives: Our primary aim was to study association between nonsurgical techniques related complications and mortality and our secondary aim was to determine factors responsible for non surgical technique related complications. Material and Methods: All gastrointestinal and hepatobiliary procedures performed in last 3 years have been evaluated retrospectively. Nonsurgical procedure related postoperative complications were defined as perioperative complications nonrelated to surgical procedures or techniques and related to patients’ physiological health or comorbidities. To avoid selection bias in attempt to evaluate effect of non-surgical procedural related complication on mortality, we did 1:1 propensity score matching analysis with nonsurgical technique related complications as dependent factor. Propensity scores were calculated using logistic regression. Pre operative confounding factors like age, sex, American society of Anesthesia score (ASA), emergency surgery, type of surgeries like HPB surgeries, Upper gastrointestinal surgeries, small bowel surgeries, colorectal surgeries, hernia surgeries, open or laparoscopic surgeries were entered in model as covariates. We used nearest neighbor matching protocol with a calipher of 0.2. Cases were not reusable after matching. Statistical analysis was done using SPSS version 23. Results: Total 348 patients underwent various abdominal surgeries (gastrointestinal and hepatobiliary) in our department from April 2017 to March 2020. Total 24 patients developed nonsurgical technique related complications. Before Propensity score matching nonsurgical technique related complications were significantly higher in Upper Gastrointestinal surgeries (gastric and esophageal), emergency surgeries, Open surgeries, in patients who developed intraoperative hypotension, patients operated for malignancies, patients with higher ASA grades, patients in whom more blood products were used and patient who had more operative time. ASA scores independently predicted nonsurgical technique related complications. [P=0.001. Odds Ratio 3.955 (95% C.I.) 1.774-8.813)]. After Matching 24 patients patients were included in nonsurgical complication related complication group and they were compared with 23 matched controls. After matching also nonsurgical procedural related complications were significantly associated with mortality. (p< 0.0001). No intraoperative factors like intraoperative hypotension, blood product requirement, operative time predicted non-surgical technique related complication. Surgery related complications were not associated with mortality after matching. Conclusion: Nonsurgical technique related complications are associated with significant increase risk of mortality.

Aim: Aim of our study was to evaluate incidence and causative factors for acute kidney injury in hepatopancreaticobiliary (HPB) surgeries. Material and Methods: All the HPB surgeries performed between April 2018 to March 2020, in our institution have been analysed for acute kidney injury. Acute kidney injury defined according to acute kidney injury network classification. Categorical variables were evaluated by chi square test and fisher t test wherever approptiate and continuous variables by Mann Whitney U test. Statistical analysis was done using SPSS version 23. P< 0.05 was considered significant. Results: We performed 195 HPB surgeries between April 2018 to March 2020, Which included 114 biliary surgeries, 57 liver surgeries and 23 pancreas surgeries. 10 patients developed Acute Kidney Injuries. (AKI) On Univariate analysis AKI was associated with open surgeries, intra operative hypotension and liver surgeries, higher ASA grade, increase operative time, more blood products used, higher CDC grade of surgery and more hospital stay before diagnosis of AKI. However on multivariate analysis only higher ASA score independently predicted Acute Kidney Injury. (p=0.003, odds ratio 15.659, 95% confidence interval 2.54-93.36). AKI was also significantly associated with mortality. (p <0.0001). Conclusion: Pre operative higher ASA grade independently predicted post operative acute kidney injury. Post operative AKI is significantly associated with mortality.

This paper investigates the feasibility of a backend design for real-time, multiple-channel processing digital phased array system, particularly for high-performance embedded computing platforms constructed of using general purpose digital signal processors. Frist, we obtained the lab-scale backend performance benchmark from simulating beamforming, pulse compression, and Doppler filtering based on MicroTCA chassis using Serial RapidIO protocol in backplane communication. Next, a field-scale demonstrator of a multifunctional phased array radar is emulated by using the similar configuration. Interestingly, the performance of a barebone design is compared to that of emerging tools that systematically take advantage of parallelism and multicore capabilities, including Open Computing Language.

The chemical composition of stingless bee honey and propolis depends on the plant sources they are derived from, and thus reflects the flora available in the vicinity of the hives, the preference of the bee species, and the climate (altitude and temperature). To understand the relative influence of these factors, we studied the composition of honey and propolis. Samples from 24 colonies were analyzed: 12 from each of two Scaptotrigona mexicana meliponiaries located in the state of Chiapas in southern Mexico approximately 8.5 km apart. The chemical composition of honey and propolis was studied using NMR, and GC-MS, respectively. Antioxidant activity of propolis was also studied. Chemometric analyses were applied. The Tuxtla Chico honey samples contained higher concentrations of glucose and fructose, while the Cacahoatán samples displayed a rich composition of di- and trisaccharides. These differences can be attributed to the distinct nectar sources utilized by the bees in each location. Propolis composition in the two locations also demonstrated qualitative differences, indicating a specific choice of resins by the bees. The observed substantial variations in the chemical composition of propolis and honey of S. mexicana from two relatively close locations support the assumption that bee species cannot be regarded as the most important factor determining their chemistry.

We report a theoretical derivation of the Cabibbo-Kobayashi-Maskawa (CKM) matrix parameters and the accompanying mixing angles. These results are arrived at from the exceptional Jordan algebra applied to quark states, and from expressing flavor eigenstates (i.e. left-chiral states) as superposition of mass eigenstates (i.e. the right-chiral states) weighted by square-root of mass. Flavor mixing for quarks is mediated by the square-root mass eigenstates, and the mass ratios used have been derived in earlier work from a left-right symmetric extension of the standard model. This permits a construction of the CKM matrix from first principles. There exist only four normed division algebras, they can be listed as follows - the real numbers $\mathbb{R}$, the complex numbers $\mathbb{C}$, the quaternions $\mathbb{H}$ and the octonions $\mathbb{O}$. The first three algebras are fairly well known; however, octonions as algebra are less studied. Recent research has pointed towards the importance of octonions in the study of high energy physics. Clifford algebras and the standard model are being studied closely. The main advantage of this approach is that the spinor representations of the fundamental fermions can be constructed easily here as the left ideals of the algebra. Also the action of various Spin Groups on these representations too can be studied easily. In this work, we build on some recent advances in the field and try to determine the CKM angles from an algebraic framework. We obtain the mixing angle values as $\theta_{12}=11.093^o, \theta_{13}=0.172^o, \theta_{23}=4.054^o$. In comparison, the corresponding experimentally measured values for these angles are $13.04^o \pm 0.05^o, 0.201^o \pm 0.011^o, 2.38^o \pm 0.06^o $. The agreement of theory with experiment is likely to improve when running of quark masses is taken into account.

An iconic feature of insects is the apparent lack of legs on the abdomen, which is believed to be due to the repression of the leg-patterning gene Distalless (Dll) by abdominal Hox genes. However, in contrast to these molecular observations, it is not widely appreciated that the embryos of most insect groups do in fact form paired protrusions on most abdominal segments that appear to be homologous to the thoracic legs. However, these degenerate before hatching to form the abdominal body wall. To resolve this discordance between molecular and morphological observations, the expression patterns of pannier and araucan, genes known to distinguish proximal leg segments in all arthropods, are examined in embryos of the flour beetle Tribolium castaneum. In Tribolium embryos, all pregenital abdominal segments develop leg-like paired protrusions, and the stripes of pannier and araucan expression that delineate the proximal leg segments of the thorax are also expressed in the same configuration around these abdominal protrusions. This suggests that insect abdominal legs are homologous to only the proximal portion of the thoracic legs, which in insect adults forms the body wall (lateral tergum and pleura). These cryptic, truncated abdominal legs – likely inherited from their crustacean ancestors – appear to be an important wellspring for new functions in insects, such as caterpillar prolegs, gills, and structures for camouflage¹⁶ and aposematic warning.

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

Changes in the dates of phenological phases of plants and insects reflect changes in climate. The aim of the study was to determine the phenological patterns and interrelationships of spring-flowering entomophilous plants (Corylus avellana L., Alnus incana Moench., Tussilago farfara L., Salix caprea L., Acer platanoides L., Taraxacum officinale L., Prunus L., Malus domestica Mill.) and the honey bee (Apis mellifera L.) in response to climate change. The research was carried out at Vokė Branch of the Institute of Agriculture, Lithuanian Research Centre for Agriculture and Forestry, using data from phenological observations during 1961–2020. The results of the studies showed that over a 60-year period, a trend towards earlier dates of all phenological events studied was observed. Significant and larger-scale changes occurred starting from the decade 1981–1990. Throughout the entire study period, with the exception of one decade, the dates of honeybee emergence on flowers correlated reliably with the dates of entomophilous plant phenophases. Due to the advance of plants phenophase dates the synchrony with honeybee emergence dates changes however, these changes had a positive effect on the foraging conditions of overwintering honeybees.

Objective: The aim of the study was to characterize varieties of Moringa alfileria honey (unfloral and polyfloral) from Saudi Arabia based on antibacterial, antioxidant activities, physicochemical, melissopalynological analysis, total phenolic and flavonoid contents. Material and Methods: The fresh 376 honey samples (3 kg of each) were kindly provided by Alnahal aljwal Company, 2021 flowering season. The honey samples collected in sterile universal glass containers and kept at 2– 8°C until tested. Antibacterial, antioxidant activities and physiochemical analysis were done. Determination of sediment content, total grains, moisture content, water-soluble solids, acidity, electrical conductivity, total sugars content, inverted sugars, glucose (g/100 g), fructose (g/100 g), total glucose + fructose, fructose/ glucose ratio, sucrose (g/100 g), diastase enzyme activity and HMF were calculated. As well as total phenolic and flavonoid contents Results: Antibacterial activity and physiochemical analysis of honey samples w varied. All parameters studied were significantly different (P < 0.05) among all honey varieties. The results of the physiochemical analysis were compared with Saudi National Standard, Codex standard, as well as published data in the literature. Conclusion: It was obvious that the honey quality was varied based on the botanical origins

This study aimed to select the most effective metabolites for controlling honey bee nosemosis using culture extracts from 342 entomopathogenic fungi of 24 species from 18 genera. The germination inhibitory activity of the fungal culture extract against Nosema ceranae spores was evaluated using an in vitro germination assay method. Among 89 fungal culture extracts showing germination inhibitory activity of approximately 80% or more, 44 culture extracts that maintained their inhibitory activity even at a concentration of 1% were selected. Finally, the honey bee nosemosis inhibitory activity was evaluated using the cultured extracts of 5 fungal isolates having a Nosema inhibitory activity of approximately 60% or more even when the extract was removed after treatment. As a result, the proliferation of Nosema spores was reduced by all fungal culture extract treatments. However, only the treatment of the culture extracts from Paecilomyces marquandii 364 and Pochonia bulbillosa 60 showed a reduction in honey bee mortality due to nosemosis. In particular, the extracts of these two fungal isolates also increased the survival of honey bees.

Abstract: Given the links between parental obesity and eating psychopathology in their children, it is important to understand the mechanisms via which unhealthy relationships with eating are passed from parents to children. The aim was to review research focusing on food-related parenting practices (FPPs) used by parents with overweight/obesity. Web of Science, PubMed and PsycINFO were searched. Twenty studies were included in the review. Single studies suggest differences between parents with healthy-weight vs overweight/obesity with respect to; food accessibility, food availability and modelling. Multiple studies suggest that several parenting strategies do not differ according to parental weight status (child involvement, praise, use of food to control negative emotions, use of food-based threats and bribes, pressure, restriction, meal and snack routines, monitoring, and rules and limits). There was inconclusive evidence with respect to differences in parental control, encouragement and use of unstructured FPPs among parents with healthy-weight vs overweight/obesity. The findings of this review imply some differences between parents with overweight/obesity and healthy-weight and the use of some food-related parenting practices, however they should be interpreted with caution since research remains limited and is generally methodologically weak. The review highlights opportunities for further research and to improve current measures of FPPs and help clarify current study findings.

Glaucoma poses a serious public health concern as it is the second leading cause of blindness after cataracts, while also being the leading cause of irreversible blindness worldwide. Glaucoma is more prevalent among Black, Latino, and Asian populations and it is essential to examine both racial and ethnic disparities that exist in treatment and prevention. As the number of people with glaucoma continues to grow, it is important to review aspects of this condition in order to better care for those affected. This article will review significant forms of glaucoma and what differentiates them in a diagnosis, treatment options, and recommendations on prevention and improving awareness

Tigrai region is one of the potential beekeeping areas in Ethiopia, which is endowed with diversified honeybee plant species. However, its honeybee plants are deforested and degraded due to natural and anthropogenic pressures. Area exclosures (AEs) has been practicing for the last three decades restore degraded habitats of the plant species in Ethiopia. Empirical data on the effectiveness of AE is still limited for restoration of honey bee plant species; this study was conducted to assess the roles of AE for species composition, density, and diversity and regeneration status of honeybee floras. Sixty quadrats were installed, 36 in AE and 24 in CGL (communal grazing lands) using a systematic sampling method. The study showed that a total of 42 honey bee plant species belonging to 23 families in AE and 33 species belonging to 17 families in CGL were recorded. The study also indicated a significant increase in the abundance, diversity, regeneration and the structure of the honey bee plant species was found in the AEs. The list presented herein provides a guide to stakeholders in establishing of AE for the foraging resource of honeybee in order to enhance the abundance, diversity and regeneration and structure. Thus, AE has made a significant contribution to solving the shortage of honeybee forages in the beekeeping industry. Therefore, the development of beekeeping is integrated with conservation of natural resources.

Insect behavior is coordinated mainly by smell, through the diverse odor-binding proteins (OBP) that allow them to identify and recognize their environment. Sensory information collected through smell is then analyzed and interpreted in the brain, allowing for correct insect functioning. The behavior of honey bees (Apis mellifera L.) can be affected by different pathogens, such as deformed wing virus (DWV). In particular, DWV variant A (DWV-A) is capable of altering olfactory sensitivity, reducing the gene expression of different OBPs, including those associated with nursing behavior. DWV is also capable of replicating itself in the sensory lobes of the brain, further compromising the processing of sensory information. This study evaluated the behavioral response of nurse honey bees exposed to a pheromone compound and the alterations in the gene expression of pre- and post-synaptic neuronal genes neuroxins-1 and neurogilin-1 in the bee heads and OBP proteins in antennae of nurse bees inoculated with DWV-A. The behavioral response of nurse bees exposed to the larval pheromone compounds benzyl alcohol was analyzed using a Y-tube olfactometer. The viral load, gene expression of OBP5 and OBP11 in antennae and the neuroxins-1 and neurogilin-1 in the bee heads were analyzed by qPCR. High viral loads significantly reduced the ability of 10- and 15-day-old nurse honey bees to choose the correct pheromone compound. Also, the gene expression of OBP5, OBP11, neuroxin-1 and neurogilin-1 in nurse honey bees decreased when they were highly infected with DWV-A. These results suggest that a DWV-A infection can disturb information processing and cause nurse honey bees to reduce their activity inside the hive, altering internal cohesion.

In this Case Report we analyze the possible causes of the poor health status of a professional Apis mellifera iberiensis apiary located in Gajanejos (Guadalajara, Spain). Several factors that potentially favor colony collapse were identified, including Nosema ceranae infection, alone or in combination with other factors (eg, BQCV and DWV infection), and the accumulation of acaricides commonly used to control Varroa destructor in the beebread (coumaphos and tau-fluvalinate). Based on the levels of residues, the average toxic unit estimated for the apiary, suggests a possible increase in vulnerability to infection by N. ceranae due to the presence of high levels of acaricides. These data highlight the importance of evaluating these factors in future monitoring programs, as well as the need to adopt adequate preventive measures as part of national and international welfare programs aimed at guaranteeing the health and fitness of bees.

Introduction: COVID-19 is an unprecedented global public health emergency currently impacting India in an unprecedented manner. Aim of this study was to assess knowledge, awareness, perceptions and related factors of Indian dentists on COVID-19. Methodology: A cross-sectional, on-line questionnaire-based study was conducted over one week between 3rd May, 2020 to 10th May, 2020. The sample comprised 403 Indian dentists in solo, group practices and in the academic arena. The self-administered questionnaire assessed 1) knowledge/awareness on factors related to COVID-19 patient identification and symptomatology, 2) knowledge/awareness of COVID-19 transmission and 3) perceptions of COVID-19 history taking procedure. Statistical analyses were conducted using Statistical Package for Social Sciences for Windows, version 21.0 (IBM Corp., Armonk, NY., USA). Frequency distributions and logistic regression analyses were used. Results: Indian dentists demonstrated an overall modest level of knowledge on identification of patients with COVID-19. Moreover, they had a high level of awareness of the COVID-19 transmission means, and the generally accepted procedural perceptions on patient history taking. However, there were some gaps in specific aspects of knowledge and perceptions. Those who were aged ≥ 30-years had a significantly higher level of knowledge of patient identification means than those who were < 30-years (OR=1.78:1.12-2.83); p=0.01. Moreover, specialized dentists were significantly knowledgeable of COVID-19 transmission means than the general dentists (OR=1.89:1.22-2.93; p=0.004). Conclusions: Our findings demonstrate identifiable gaps in knowledge/awareness and perceptions of COVID-19 in Indian dental professionals. These gaps should be fulfilled, at the earliest, due to the rising burden of COVID-19 in India, to ensure safe dental care delivery.

In this paper, we introduce Syntax-Enhanced Transformer Model (SET), a groundbreaking approach in the realm of Transformer-based language modeling that seeks to redefine the boundaries of linguistic analysis and comprehension. SET innovatively combine (i) the well-established high-level performance, scalability, and adaptability of traditional Transformers with (ii) a sophisticated analysis of syntactic structures. This synergy is enabled by a novel attention mechanism tailored to parse syntactic nuances and a deterministic process adept at transforming linearized parse trees into meaningful linguistic representations. Our comprehensive experiments reveal that SET significantly advance the field by surpassing existing benchmarks in sentence-level language modeling perplexity. They exhibit exceptional proficiency in tasks that require an acute awareness of syntax, setting new standards for language models in understanding complex linguistic structures. Furthermore, SET demonstrate an enhanced capability to grasp nuanced linguistic patterns that have traditionally been challenging for standard Transformer models. However, our studies also uncover a unique aspect of SET: while they excel in sentence-level tasks, their representation of sentences as singular vectors—owing to the syntactic composition constraints intrinsic to their design—introduces certain limitations in document-level language modeling. This observation points to an intriguing area for future exploration; it suggests the potential need for an alternative or complementary memory mechanism within Transformer models, one that functions independently from, yet in harmony with, syntactic structures. Such a mechanism could be pivotal in enhancing the model's ability to comprehend and process long-form texts effectively. In conclusion, SET mark a significant stride in the journey towards more sophisticated, syntax-aware language models. They offer promising insights into the integration of deep linguistic knowledge with cutting-edge machine learning techniques, potentially opening doors to a new era of natural language understanding and processing.

The paradigm of leveraging code as a dataset has recently gained traction, offering innovative solutions in domains such as automated commit message generation, pull request description automation, and program repair mechanisms. Consider the challenge in generating commit messages: traditional methods treat source code as a mere token sequence, applying neural machine translation models. This approach, however, overlooks the critical syntactic structures inherent in programming languages, which could offer deeper insights and improved accuracy. Building upon prior research, specifically the Code2Seq framework, which utilized Abstract Syntax Tree (AST) structural data for source code representation to automate method name generation, this paper extends and refines this concept. We introduce "CSR", a novel methodology adapted to represent code edits effectively. This paper investigates the impact of employing syntactic structure, focusing on the classification of code edits. Drawing inspiration from Code2Seq, "CSR" utilizes AST's structural properties, particularly the paths connecting leaf nodes, to enhance the task of code edit classification. This approach is rigorously evaluated on two distinct datasets, comprising fine-grained syntactic edits. Our comprehensive experiments reveal that incorporating syntactic structures does not significantly outperform simpler methodologies. While methods like Code2Seq and our proposed "CSR" show potential, our findings highlight that there is considerable scope for improvement and refinement before such techniques can be universally applied for learning representations of code edits. We anticipate that our findings will spark further research in this field, paving the way for more effective use of syntactic structures in code representation.

Contemporary advanced models for aspect-targeted opinion word extraction (ATOWE), which predominantly utilize BERT-based encoders at a word level, have shown limited advancements when integrated with graph convolutional networks (GCNs) for syntactic tree assimilation. Recognizing the prowess of BERT subwords in encapsulating rare or context-poor words, this study pivots from syntactic trees to BERT subwords, omitting GCNs from the structural framework. Our approach, named Aspect-Enhanced Wordpiece Extraction Model (AEWEM), focuses on refining aspect representation during encoding. We propose an input format of paired sentence-aspect, diverging from traditional single-sentence inputs. AEWEM demonstrates superior performance on benchmark datasets, establishing a robust foundation for future explorations in this domain.

The Transformer architecture, while adept at capturing context through self-attention, falls short in encapsulating complex syntactic structures effectively. Addressing this gap, we introduce the Linguistic Structure through Graphical Interpretation with BERT (LSGIB) approach in Machine Translation (MT) frameworks. Combining the strengths of Graph Attention Network (GAT) and BERT, LSGIB intricately captures syntactic dependencies as explicit knowledge from the source language. This enhances the source language representation and aids in more accurate target language generation. Our empirical analysis leverages gold-standard syntax-annotated sentences and employs a Quality Estimation (QE) model. This approach enables us to assess translation improvements in terms of syntactic accuracy, extending beyond traditional BLEU score metrics. The LSGIB model demonstrates superior translation quality across diverse MT tasks, maintaining robust BLEU scores. Our study delves into the optimal sentence lengths benefiting from LSGIB and identifies which syntactic dependencies are more precisely captured. We observe that GAT's ability to learn specific dependency relations directly influences the translation quality of sentences with those relations. Additionally, we discover that incorporating syntactic structure into BERT's intermediate and lower layers offers a novel approach to modeling linguistic structure in source sentences.

The field of program classification, a critical aspect of software engineering, facilitates understanding and categorization of code across various applications, including anomaly detection, and code quality assessment. The advancement of cross-language program classification opens up avenues for efficient code translation among different programming languages, significantly aiding developers in rapid coding and reducing development cycles. Existing research primarily focuses on semantic code analysis, with limited emphasis on cross-linguistic challenges. To address this, we introduce an innovative neural network model, CodeSemanticsNN, which leverages a refined Syntax Structure (SS) approach. This model consists of two integral mechanisms: first, it adopts a novel SS representation that combines sequential and graph-based SS structures, enhancing semantic feature capture. Second, it employs a 'unified vocabulary' strategy to bridge the gap between diverse programming languages, facilitating efficient cross-language classification. Additionally, we have compiled a comprehensive dataset of 20,000 files spanning five programming languages, serving as a benchmark for cross-language classification. Our experiments on this dataset demonstrate that CodeSemanticsNN surpasses existing models in four key metrics: Precision, Recall, F1-score, and Accuracy.

The evolution of sentence representation learning, especially with parse tree encoders, has shown remarkable progress. Traditional approaches predominantly rely on recursive encoding of tree structures, which impedes parallel processing capabilities. Additionally, these methods often overlook the significance of dependency tree arc labels. To overcome these limitations, we introduce the Syntax-Enhanced Transformer (SET), incorporating a novel dual-attention mechanism that integrates relation-focused attention alongside traditional self-attention. This design effectively encodes both dependency and spatial positional relationships within sentence dependency trees. Our approach innovatively incorporates syntactic information into the Transformer framework without compromising its inherent parallelizability. The SET demonstrates superior or comparable performance to contemporary methods across various sentence representation tasks, significantly enhancing computational efficiency.

This paper introduces a novel graph polynomial approach for differentiating tree structures in dependency grammar. Utilizing this polynomial representation, we develop a metric to assess the similarity in syntax. This approach offers a detailed and inclusive analysis of the dependency structures and relationships in sentence construction. We employ this polynomial method to examine sentence structures across various languages in the Parallel Universal Dependencies treebanks. Our analysis includes comparing the syntax of original sentences and their translated counterparts in diverse languages, alongside a comprehensive study of syntactic typologies within these treebanks. Additionally, we explore the application of our methodology in evaluating the syntactic diversity within language corpora.

Recent advancements in neural language models, particularly attention-based architectures like the Transformer, have substantially surpassed traditional methods in various natural language processing tasks. These models adeptly generate nuanced token representations by considering contextual relations within a sequence. However, augmenting these models with explicit syntactic knowledge, such as part of speech tags, has been found to remarkably bolster their effectiveness, especially under constrained data scenarios. This study introduces the Linguistic Enhanced Transformer (LET), which integrates multiple syntactic features, showing a notable increase in translation accuracy, evidenced by an improvement of up to 1.99 BLEU points on subsets of the WMT '14 English-German dataset. Furthermore, this paper demonstrates that enriching BERT models with syntax-aware embeddings enhances their performance on several GLUE benchmark tasks.

Conventional text style transfer (TST) methodologies primarily utilize style classifiers to segregate the content and stylistic elements of text for effective style transformation. Despite the pivotal role of these classifiers, their influence on TST techniques remains largely unexplored. This study embarks on a detailed exploration of the limitations inherent in style classifiers within current TST frameworks. We reveal that these classifiers often inadequately comprehend sentence syntax, leading to diminished performance in TST models. In response, we introduce the Syntax-Enhanced Style Transfer (SEST) model, a groundbreaking approach incorporating a syntax-sensitive style classifier. This classifier ensures that the extracted style representations robustly encapsulate syntax nuances, enhancing TST effectiveness. Rigorous evaluations across diverse TST benchmarks demonstrate that SEST significantly surpasses contemporary models in performance. Additionally, our case studies highlight SEST's proficiency in producing syntactically coherent sentences that aptly retain original content.

Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) have been utilised to forecast the foreign exchange market (Forex). However, such models usually exhibit unstable behaviour, as data perturbations often downgrade the functionality of the entire network due to their monolithic architecture. Hence, this study proposes a novel neuroscience-informed modular network applied to the closing prices and the sentiments retrieved from Yahoo Finance and Twitter APIs, aiming to anticipate better price fluctuations in Euro to British Pound Sterling (EUR/GBP) rather than monolithic methods. The proposed model is based on a new modular CNN, replacing pooling layers with orthogonal kernel initialisation RNNs coupled with Monte Carlo Dropout (MCD), namely MCoRNNMCD. It combines two modules: i) a convolutional simple RNN and ii) a convolutional Gated Recurrent Unit (GRU), where orthogonality and MCD are added to reduce the overfitting, assessing each module's uncertainty. These parallel feature extraction modules concatenate their outputs to a final three-layer Artificial Neural Network (ANN) decision-making module. A comprehensive comparison viewing objective evaluation metrics such as the Mean Square Error (MSE) proved that the proposed MCoRNNMCD-ANN outperformed single CNN, LSTM, GRU, and the state-of-the-art hybrid BiCuDNNLSTM, CLSTM, CNN-LSTM, and LSTM-GRU in forecasting hourly EUR/GBP closing price fluctuations.

Navigation is the most challenging issue in autonomous vehicles. Researchers in the current era have developed many Artificial Intelligence techniques to navigate, generate paths, and avoid obstacles for optimum path planning for autonomous vehicles. Different studies have investigated bio-inspired techniques to overcome the navigation issue, including obstacle avoidance. This paper uses new meta-heuristic optimization techniques called Dragonfly Algorithm (DA) to set the goal by detecting and avoiding obstacles with minimum human interference. For effective results, the Dragonfly-Fuzzy hybrid algorithm is analyzed over the unstructured environment because individual techniques may not be sure of an optimal solution over all configurations. The main advantage of the proposed hybrid controller is that it combines the multiple features of different approaches into a single controller. This paper compares simulation and experimental findings over various environmental conditions to the individual algorithm. Regarding time and path optimization, the hybrid Dragonfly-Fuzzy controller performs better than the respective controller.

The most common type of non-Hodgkin lymphoma in adults is diffuse large B-cell (DLBCL). There is a historical unmet need for more effective therapies in the 2nd and 3rd line setting. Emerging immunochemotherapies have shown activity in small studies of heavily pre-treated patients with prolonged remissions achieved in some patients. Anti-CD19 CAR (chimeric antigen receptor) T cells are potentially curative in the 3rd line and beyond setting and are under investigation in earlier lines of therapy.1 Antibody-drug conjugates (ADC’s) such as polatuzumab vedotin targeting the pan-B-cell marker CD79b has proven effectiveness in multiply-relapsed DLBCL patients. Tafasitamab (MOR208) is an anti-CD19 monoclonal antibody producing prolonged remissions when combined with Lenalidomide in patients who were not candidates for salvage chemotherapy or autologous stem cell transplant. Selinexor, an oral, small-molecule selective inhibitor of XPO1-mediated nuclear export (SINE), demonstrated prolonged activity against heavily-pretreated DLBCL without cumulative toxicity and is being investigated as part of an oral, chemotherapy-free regimen for relapsed aggressive lymphoma. This article reviews current strategies and novel therapies for relapsed/refractory DLBCL.

Acetaminophen use during pregnancy and early childhood was accepted in the 1970s, but is now a subject of considerable concern. Careful analysis shows that initial acceptance of the drug was based on false assumptions and ignorance of the impact of the drug on brain development. Fourteen studies now indicate that prenatal exposure to acetaminophen is associated with neurodevelopmental problems. Based on corrections for confounding factors applied to the analyses of available data, it can be concluded that prenatal exposure to acetaminophen causes statistically significant risks of one subtype of autism spectrum disorder (ASD), developmental delays, and attention deficit hyperactivity disorder. In contrast, data regarding postnatal exposure to acetaminophen are limited, and several factors impede a classic multivariate analysis of data to resolve the issue. However, circumstantial evidence regarding postnatal exposure to the drug is abundant, and it can be concluded beyond a reasonable doubt that postnatal exposure to acetaminophen in susceptible children is responsible for many if not most cases of ASD. Circumstantial evidence includes at least three otherwise unexplained temporal relationships, data from laboratory animal studies, several miscellaneous and otherwise unexplained correlations, and the lack of alternative suspects that fit the evidence-derived profile.

Abstract: This study explores the antibacterial and antifungal activity of four floral honey types (12 samples) (A. seyal, Zizuphus spina-christi, Cucurbita maxima and A. nilotica) as related to their phenolic content, antioxidant capacity, and assessing their cytotoxic effects. The cup-plate agar diffusion assay was employed to examine the antimicrobial potency against different pathogens including Bacillus subtilis, Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Aspergillus niger and Candida albicans. Scavenging activity, total phenolic, flavonoid contents, and cytotoxicity were determined by the DPPH radical scavenging, Folin–Ciocalteu, spectrophotometry, and Brine shrimp lethality, bioassays respectively. All assessed honeys significantly inhibited the growth of the tested pathogens. Both Acacias honey exhibited high antioxidants with IC50: 6.68 and 9.08 mg/ml respectively for A. seyal and A. nilotica. The total phenol content varied from 5.75 to 67.95 mg (GAE)/100 g while the overall flavonoid content varied from 0.15 to 0.5mg (QE)/100 g. All honey types expressed no cytotoxicity effects one cell lines. Thus the study, supports the existing antimicrobial activity of honey. However, the strong antimicrobial activity of Cucurbita and Ziziphus honeys, with their corresponded poor antioxidant furtherly provides evidence that the high levels of phenolic substances in honeys is not always the only cause of their antimicrobial potency.

Propionibacterium acnes and Staphylococcus epidermidis are the major skin bacteria that cause the formation of acne. The present study was conducted to investigate antibacterial activity of ethanolic extract of cinnamon bark, honey and their combination against acne bacteria. The antibacterial activity of extract of cinnamon bark and honey were investigated against P. acnes and S. epidermidis using disc diffusion method. Minimum Inhibitory Concentration (MIC) and minimal bactericidal concentration (MBC) were performed using Clinical and Laboratory Standard Institute (CLSI) methods. The interaction combination between extract of cinnamon bark and honey was determined by using a checkerboards method. The results showed that he MIC of extract of cinnamon bark and honey against P. acne were 256 µg/mL and 50% v/v, respectively, while against S. epidermidis were 1024 µg/mL and 50% v/v, respectively. The MBC of extract of cinnamon against P. acnes and S. epidermidis were more than 2048 µg/mL, whereas the MBC for honey against P. acnes and S. epidermidis were 100%. The combination of cinnamon bark extract and honey against against P. acnes and S. epidermidis, showed additive activity with the FICI value 0.625. Therefore, the combination of extract of cinnamon bark and honey has potential activity against acne causing bacteria.

Adult mesenchymal stem cells (MSCs) are a promising cell source for tissue regeneration. However, ex vivo expansion results in cell senescence; cells lose their proliferation and differentiation capacity. Fetal MSCs can be an alternative due to their robust proliferation and differentiation capacities as well as immune privilege properties. Given the rejuvenation effect of decellularized extracellular matrix (dECM) on adult MSCs, it remains unknown whether dECM influences the regenerative potential of fetal stem cells. In this study, passage five fetal nucleus pulposus cells (fNPCs) and fetal synovium-derived stem cells (fSDSCs) were expanded on dECMs deposited by fNPCs (NECM) and fSDSCs (SECM) for one passage with expansion on tissue culture plastic (Plastic) as a control. We found that dECM expanded fNPCs and fSDSCs exhibited both similarities and differences in expression of stemness genes and surface markers. Expanded fNPCs yielded more differentiated pellets after chondrogenic induction but no adipogenic differentiation following adipogenic induction in both Plastic and dECM groups than the corresponding fSDSC group. Despite a significant increase in fNPCs, dECM expanded fSDSCs exhibited no increase in chondrogenic potential; however, compared to the Plastic group, dECM expanded fSDSCs exhibited a small increase in osteogenic potential and a great increase in adipogenic potential. These results suggest that fNPCs are more sensitive to NECM rejuvenation for cartilage tissue engineering and regeneration; in contrast, dECMs exhibited limited effects on fSDSC rejuvenation in chondrogenic capacity except for enhanced adipogenic capacity following expansion on SECM.

Background and objectives: Main aim of the study is to analyze the outcomes of NSTEMI admissions and testing the relevance of TIMI as a risk score in a real-world setting. Also looking at any potential social or health care disparities involved with outcomes of NSTEMI admissions. The study also investigates factors associated with mortality in NSTEMI admissions and correlation between in-hospital mortality and heart catheterization. . Materials and Methods: NSTEMI admissions were analyzed using the National Inpatient Sample. TIMI scores were calculated in the admissions and association between all-cause mortality and calculated TIMI score >=2 was analyzed. Difference in outcomes based on heart catheterization was studied in the subgroup with TIMI score >=2. Correlation between time to heart catheterization and all-cause mortality in NSTEMI admissions were analyzed. Results: No significant social or healthcare disparities were noted amongst outcomes for NSTEMI admissions. NSTEMI admissions with a calculated TIMI score >=2 had a statistically significant association with all-cause mortality during the admission. Prevalence of mortality among NSTEMI admissions with calculated TIMI score >2, who did not undergo heart catheterization was higher with statistical significance when compared to admissions that underwent heart catheterization. NSTEMI admissions with a calculated TIMI score >2 who underwent catheterization on or beyond the 4th day of hospitalization had statistically significant association with all-cause mortality during the admission. Age at admission, presence of CKD and CHF were associated with mortality in NSTEMI admissions, with statistical significance. Keywords: NSTEMI; TMI score; heart catheterization

Magnetron sputtering was used for producing Titanium Vanadium Nitride (TiVN) coatings on a variety of substrates. In this research, we investigate how changing the sputtering power and nitrogen: argon (N2:Ar) gas ratio affects the structural and tribological properties of TiVN coatings. Scanning Electron Microscope (SEM) technique was used to examine TiVN coating surface morphology. Both variants showed a gradual increase in the intensity of the TiVN coating's (111) and (222) peaks. TiVN coating's tribological properties were examined using a pin-on-disc tribometer with varying loads, speeds, and sliding distances. The wear rates of TiVN-coated brass pins were in the range of 2.5×10-4 to 9.14×10-4 mm3/Nm depending on load, sliding distance, and gas ratio variation, when compared to the wear rates of TiVN-coated brass pins deposited at various power, which ranged from 1.76×10-3 to 5.87×10-3 mm3/Nm.

The cosmetic industry recognizes the importance of natural sources for functional active constit-uents in meeting consumer expectations for safer and more sustainable beauty care products. Ma-rine macroalgae have emerged as promising resources, offering diverse bioactive constituents with potential applications in cosmetics. In this study, we investigated the biochemical profile of Padina boergesenii, a marine macroalga, using various methods to assess its potential as a cosmetic ingre-dient. The Fourier Transform Infrared (FTIR) analysis revealed the presence of distinct bioactive functional groups associated with numerous skin-beneficial compounds. Furthermore, the ethanolic and methanolic extracts of P. boergesenii were subjected to Gas Chromatography-Mass Spectrom-etry (GC-MS) analysis, which identified a total of six and fifteen significant phytocompounds, re-spectively. Additionally, a comprehensive phytochemical profiling of P. boergesenii was performed using High-Resolution Liquid Chromatography-Mass Spectrometry Quadrupole Time-of-Flight (HRLCMS-Q-TOF), highlighting the presence of various terpenoids, alkaloids, peptides, fatty acids, derivatives, and coumarins with potential cosmetic applications. To further assess its potential as a cosmetic ingredient, P. boergesenii was subjected to several additional estimations. Pigment estima-tion revealed the presence of specific pigments, while the determination of total phenol content and total protein content highlighted the richness of these bioactive components. The antioxidant analysis using the DPPH method demonstrated the antioxidant potential of P. boergesenii extracts, suggesting their ability to combat oxidative stress-related skin damage. Moreover, the tyrosinase inhibition assay indicated the inhibitory effect of P. boergesenii extracts on tyrosinase activity, which is relevant for addressing hyperpigmentation concerns. Furthermore, the elemental composition of P. boergesenii was evaluated using Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES), revealing that silicon (Si) exhibited the highest concentration among the measured elements, while copper (Cu) displayed the lowest concentration. Additionally, HRLCMS-Q-TOF analysis was employed to quantify 21 amino acids, with aspartic acid exhibiting the highest con-centration (2034.99 nmol/mL), and tyrosine demonstrating the lowest concentration (233.26 nmol/mL). The accuracy of all the measured elements and amino acids was deemed acceptable. Taken together, the findings of this study highlight the potential of P. boergesenii as an effective ingredient for enhancing skin health. The incorporation of seaweed-based bioactive components, such as P. boergesenii, into cosmetic products is increasingly common due to their beneficial effects on the skin. Further exploration of the potential applications of P. boergesenii in the cosmetics in-dustry is warranted to harness its valuable bioactive properties.

Marine macroalgae have garnered significant attention in the field of cosmeceutical research due to their rich abundance of bioactive compounds. These compounds offer remarkable skin benefits without inducing any adverse effects on human health, such as cytotoxicity, reproductive toxicity, genotoxicity, mutagenicity, or carcinogenicity. Among the various bioactive compounds found in brown algae, phenolic compounds exhibit diverse chemical structures and are present in high concentrations. In addition to phenolic compounds, brown algae also contain terpenoids, bro-mophenols, mycosporine amino acids (MAAs), and flavonoids, with the well-studied poly-phenol compound, phlorotannin, being particularly prominent. Marine macroalgae further possess an array of pigments derived from their natural pigmentation, including chlorophylls, carotenoids (such as fucoxanthin and β-carotene), phycobiliproteins (such as phycoerythrin and phycocyanin), and melanin. These pigments have been extensively investigated for their potential cos-meceutical applications. The phenolic compounds and pigments derived from marine macroalgae have been thoroughly studied for their beneficial effects on the skin, including skin whitening, moisturizing, photoprotection, anti-aging, anti-wrinkle, anti-melanogenic, and anti-oxidant properties. This comprehensive review aims to explore the extraction, characterization, and skin cosmetic effects of phenolic compounds and pigments derived from marine macroalgae, as documented in the existing literature, thereby enhancing our understanding of their therapeutic potential.

This study investigates the impact of climate change on the efficiency of organic honey production in Türkiye using a machine learning approach. The eXtreme Gradient Boosting (XGBoost) algorithm is employed for the Machine Learning (ML) modelling. The analysis includes data on organic honey production performance from 2004 to 2023, spanning a period of 20 years, and 8 different climate variables (16 variables depending on daytime and nighttime values). The dataset created to investigate the impact of climate change on organic honey yield comprises 28 columns and 120,960 rows. The study aimed to determine the significance of different climatic variables on the efficiency of organic honey production. The study found that, in addition to daytime solar radiation and temperature, wind speed and direction were also important factors. The sensitivity analysis has shown that minor alterations in the variables have a significant impact on the model's predictions. Additionally, non-linear relationships between the variables and honey production were identified. These findings suggest that it may be beneficial to consider implementing climate change adaptation and mitigation strategies in agricultural policies and beekeeping practices. The study suggests that machine learning has the potential to provide valuable insights into the complex relationship between climate change and agricultural production. This could aid in the sustainability and economic optimization of the sector.

Identification of the honey bee (Apis mellifera) subspecies is an important aspect of bee breeding and biodiversity conservation. The identification can be based on molecular or morphological markers. For some markers, including the cytochrome c oxidase subunit, there is a well-established methodology allowing consistent subspecies identification in different laboratories. In the case of morphological markers, identification is hindered by a lack of reference data and a standardized methodology to reuse it. We show here that reference data for the identification of honey bees based on geometric morphometrics can be saved in an XML file. The information in this file can be easily extracted by other users for the identification of unknown samples. We illustrate this procedure using ten samples from north India. The samples were identified as A. mellifera; next, they were identified as lineage C; and finally, most of the samples had high similarity to honey bees from Croatia and Slovenia. We explained what data is required for such identification and how it can be reused. The method described here can be applied not only to honey bee wings but also to all data based on landmark coordinates.

Understanding the subtle signs of carpal instability and other unique injury patterns in the wrist is a critical skill for radiologists. Proper patient management and outcomes are directly dependent on the accurate interpretation of wrist imaging studies. This review will provide a detailed overview of typical imaging features of carpal trauma and instability, management, and complications, using multimodality imaging and original medical illustrations. A detailed overview of the osseous, ligamentous, arterial anatomy of the wrist, arcs of Gilula, and zones of vulnerability will be provided. Carpal fractures, dislocations, special radiographic views, and imaging pearls will be discussed. Instability patterns and the myriad of associate abbreviations (CID, CIND, CIC, CIA, VISI, DISI, SLD, LTD, MCI, SLAC, SNAC) will be clarified. Expected outcomes, potential complications, and management will be reviewed.

The ectoparasitic mite Varroa destructor is the most significant pathological threat to the western honey bee, Apis mellifera, leading to the death of most colonies if left untreated. An alternative approach to chemical treatments is to selectively enhance heritable honey bee traits of resistance or tolerance to the mite through breeding programs, or select for naturally surviving untreated colonies. We conducted a literature review of all studies documenting traits of A. mellifera populations either selectively bred or naturally selected for resistance and tolerance to mite parasitism. This allowed us to conduct an analysis of the diversity, distribution and importance of the traits in different honey bee populations that can survive V. destructor throughout the globe. In a second analysis, we investigated the genetic bases of these different phenotypes by comparing ’omics studies (genomics, transcriptomics, and proteomics) of A. mellifera resistance and tolerance to the parasite. Altogether, this review provides a detailed overview of the current state of the research projects and breeding efforts against the most devastating parasite of A. mellifera. By highlighting the most promising traits of varroa-surviving bees and our current knowledge on their genetic bases, this work will help direct future research efforts and selection programs to control this pest. Additionally, by comparing the diverse populations of honey bees that exhibit the traits, this review highlights the consequences of anthropogenic and natural selection on the interactions between hosts and parasites.

Mineral profile of beef interests human health, but also animal performance and meat quality. This study analyzes the relationships of 20 minerals in beef (ICP-OES) with 3 animal performance and 13 meat quality traits analyzed on 182 samples of Longissimus thoracis. Animals’ breed and sex showed limited effects. The major sources of variation (farm/date of slaughter, individual animal within group and side/sample within animal) differed greatly from trait to trait. Mineral contents were correlated to animal performance and meat quality being significant 52 out of the 320 correlations at the farm/date level, and 101 out of the 320 at the individual animal level. Five latent factors explained 69% of mineral co-variation. The most important, “Mineral quantity” factor correlated with age at slaughter and with the meat color traits. Two latent factors (“Na+Fe+Cu” and “Fe+Mn”) correlated with performance and meat color traits. Two other (“K-B-Pb” and “Zn”) correlated with meat chemical composition and the latter also with carcass weight and daily gain, and meat color traits. Meat cooking losses correlated with “K-B-Pb”. Latent factor analysis appears be a useful means of disentangling the very complex relationships that the minerals in meat have with animal performance and meat quality traits.

Coronaviruses (CoVs) are enveloped positive-sense single-stranded RNA viruses with a genome 27-31kbases in length. Critical genes include the spike (S), envelope (E), membrane (M), nucleocapsid (N) and 9 accessory open reading frames encoding for non-structural proteins (NSPs) that have multiple roles in the replication cycle and immune evasion (1). There are 7 known human CoVs that most likely appeared after zoonotic transfer, the most recent being SARS-CoV-2 responsible for the Covid-19 pandemic. Antivirals that have been approved by the FDA for use against Covid-19 such as Paxlovid can potentially target and successfully inhibit the main protease (MPro) activity of multiple human CoVs, however alternative proteomes encoded by CoV genomes have a closer genetic similarity to each other, suggesting that antivirals could be developed now that target future CoVs. New zoonotic introductions of CoVs to humans are inevitable and unpredictable. Therefore, new antivirals are required to control not only the next human CoV outbreak, but also the 4 common human CoVs (229E, OC43, NL63, HKU1) that circulate frequently and to contain sporadic outbreaks of the severe human CoVs (SARS-CoV, MERS and SARS-CoV-2). The current study found that emerging antiviral drugs, such as Paxlovid, have only been proven to target SARS-CoV-2. Other drugs which have the potential to target other human CoVs, are still within clinical trial and are not yet available for public use. Monoclonal antibody (mAb) treatment and vaccines for SARS-CoV-2 can reduce mortality and hospitalisation rates, however they target the Spike protein whose sequence mutates frequently and drifts. Spike also is not applicable for targeting other HCoVs as these are not well conserved sequences among human CoVs. Thus, there is a need for readily available treatments globally that target all 7 human CoVs and improve the preparedness for inevitable future outbreaks. Here we discuss antiviral research contributing to the control of common and severe CoV replication and transmission, including the current SARS-CoV-2 outbreak. The aim was to identify common features of CoVs for antivirals, biologics and vaccines that could reduce the scientific, political, economic and public health strain caused by CoV outbreaks now and in the future.

Mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome is one of the most frequent maternally inherited mitochondrial disorders.MELAS syndrome is a multi-organ disease that presents with a wide range of symptoms, such as dementia, epilepsy, lactic acidemia, myopathy, hearing loss, stroke-like episodes, diabetes, short stature, and myopathy. MELAS primarily affects tissue with high energy demands such as the brain, muscles, and heart. With 65–76% of affected people presenting at or before the age of 20, childhood is the typical age of onset. Genetic testing, imaging tests such as magnetic resonance imaging (MRI) scans, and other techniques, tests of blood, urine, and cerebrospinal fluid in addition to muscle biopsy (if necessary) may be used to diagnose MELAS syndrome. Management of MELAS remains largely supportive, focusing on symptom alleviation and metabolic stabilization. The long-term prognosis of MELAS is variable, influenced by factors such as age of onset, severity of symptoms, and presence of comorbidities. While some patients experience a relatively stable course with intermittent exacerbations, others may exhibit progressive neurological deterioration and multiorgan involvement. Early recognition, prompt intervention, and close monitoring are essential for optimizing outcomes and mitigating complications.Presenting here a case report of an occurrence of MELAS in a 31-year old male patient with chief complaints of perspiration, uneasiness and weight loss with increase in appetite and past history of bilateral hearing loss and vision loss in left eye.

Attempts to use computers to aid in the detection of breast malignancies date back more than 20 years. Despite significant interest and investment, this has historically led to minimal or no significant improvement in performance and outcomes with traditional computer aided detection. However, recent advances in artificial intelligence and machine learning are now starting to deliver on the promise of improved performance. There are at present more than 20 FDA approved AI applications for breast imaging, but adoption and utilization are widely variable and overall low. Breast imaging is unique and has aspects that create both opportunities and challenges for AI development and implementation. Breast cancer screening programs worldwide rely on screening mammography to reduce the morbidity and mortality of breast cancer and many of the most exciting research and available AI applications focus on cancer detection for mammography. There are however multiple additional potential applications for AI in breast imaging including decision support, risk assessment, breast density quantitation, workflow and triage, quality evaluation, response to neoadjuvant chemotherapy assessment, and image enhancement. In this review the current status, availability, and future directions of investigation of these applications are discussed, as well as the opportunities and barriers to more widespread utilization.

Is it possible that the addition of wild-growing flowers with anti-inflammatory applications can improve the antioxidant properties of rapeseed and multifloral honey? The study objective was a comparative analysis of two honey varieties enriched by flowers of six plant species, based on the content of the antioxidant capacity as well as total flavonoids and phenolic content. Experiments demonstrated that at each level of enrichment there was an improvement in antioxidant properties compared to honey of both varieties without additives, especially in the case of dried flowers. Primula veris L. and Pulmonaria officinalis L. improved the antioxidant properties and phenolic content most effectively in honey at all levels of enrichment. Rapeseed-type honey produces a better matrix for the incorporation of natural plant metabolites into honey. The content of biologically active substances in honey enriched with flowers gives hope for new applications of health-promoting substances contained in wild plants.

Background: Neuroendocrine tumors (NET) are a rare group of epithelial neoplasm present in gastrointestinal tract (GI) (67.5%), bronchopulmonary tree (25.3-30%), and in 15% of cases, the primary sites cannot be identified. Although endoscopic screening, improvement in pathological techniques, and early detection have shown improvement in NET survival rates, the prognosis of advanced, metastatic, and poorly differentiated NET is very poor. In this study, we aimed to evaluate the effect of Gastrointestinal and pancreatic (GEPs) NETs grade on overall survival. Method: We searched observational studies describing the overall survival or prognostic factors of primary GEP NETs from May 2011 -May 2021 following PRISMA guidelines. Studies describing the effect of primary grade 3 GEP NETs on overall survival were included. Meta-analysis was performed, and pooled hazard ratio and their 95% confidence interval (95% CI) were obtained. The forest plots were created using random-effects models and sensitivity analysis was performed to account for the heterogeneity. Results: Seven studies with 7692 confirmed patients were included. In our meta-analysis grade 3 GEP NET were associated with higher odds of poor survival (pooled HR: 2.73; 95% CI: 1.36–5.47; p = 0.005), with 92% heterogeneity between studies (p < 0.0001). To account for heterogeneity, sensitivity analysis was performed by removing two outlying studies (Fathi et al. and Foubert et al.) on funnel plots. The results after sensitivity analysis did not change and still showed significant association of grade 3 with poor survival (pooled HR: 4.53; 95% CI: 3.54–5.78; p < 0.00001), with no heterogeneity between studies (p = 0.72; I2 = 0%). Conclusion: Our meta-analysis found that grade 3 GEP NETs are associated with poor survival and additional future studies are needed to identify other risk factors associated with poor survival in GEP NETs to improve mortality.

The COLOSS research association has been assessing honey bee colony losses, associated risk factors and management, focusing on Western countries but with a progressive international expansion. Here, we report the first survey on the loss rates of colonies in 2022/23 in Ethiopia using COLOSS monitoring survey tools. A face-to-face interview questionnaire survey was conducted on 64 beekeepers selected from Oromia and Tigray regions. This covered 1,713 honey bee colonies distributed in 68 apiaries. The percentages of colonies lost were significantly different between Oromia (24.1%) and Tigray (66.4%) regions. Colony losses were attributed as unsolvable queen problems (8% in Oromia; 10% in Tigray), natural disaster (32%; 82%), and empty hives or dead colonies (60%; 8%). The loss rate was significantly affected by queen replacement (p

Despite the implementation of control strategies, the invasive parasitic mite Varroa destructor remains one of the principal causes of honey bee (Apis mellifera) colony losses in numerous countries. For this reason, the parasite represents a serious threat to beekeeping and to agro-ecosystems that benefit from the pollination services provided by honey bees. Numerous selection programmes have been initiated over the last three decades with the aim of promoting the establishment of balance in the host–parasite relationship and, thus, helping European honey bees to survive in the presence of the parasite without the need for acaricide treatments. Such programmes have focused on either selective breeding for putative resistance traits or natural selection. To date, no clear overview of these attempts has been available, which has prevented building on past successes or failures and, therefore, hindered the development of a sustainable strategy for solving the V. destructor problem. In the present study, we review past and current selection strategies, report on their outcomes and discuss their limitations. Based on this state-of-the-art knowledge, we propose a strategy for increasing response to selection and colony survival against V. destructor infestations. Developing in-depth knowledge regarding the selected traits, optimising selection programmes and communicating their outcomes are all crucial to our efforts to establish a balanced relationship between the invasive parasite and its new host.

UEDVT still remains an underdiagnosed entity due to a significant percentage of patients who remain asymptomatic. The etiology of UEDVT is overwhelmingly attributed to secondary causes including but not limited to central venous access devices and malignancy. Treatment modalities include anticoagulation, catheter directed thrombolysis, percutaneous mechanical thrombectomy or a multimodality approach along with the management of underlying etiology. We describe a case of a female with breast cancer, who came with left UEDVT and CVC malfunction and was successfully treated using the ClotTriever system to maintain continuous intravenous access.

Neuromyelitis optica spectrum disorder (NMOSD), previously known as Devic disease or neuromyelitis optica (NMO), represents inflammatory conditions affecting the central nervous system. These disorders are characterized by severe immune-mediated demyelination and axonal damage, with a predilection for targeting optic nerves and the spinal cord. Key clinical features of NMOSD encompass acute episodes of bilateral or rapid sequential optic neuritis and transverse myelitis, typically exhibiting a relapsing course. These attacks endure for several days, and recovery varies, spanning from weeks to months. In this report, we present the case of a 35-year-old individual who initially complained of urinary retention, followed by decreasing vision in the left eye and subsequently in the right eye. These visual symptoms were succeeded by weakness in the right upper and lower limbs.

The art of representing source code is pivotal in numerous programming analysis applications. Recent strides in neural networks have marked notable successes in this realm. However, the peculiar structural characteristics inherent in programming languages have not been fully exploited in existing models. While neural models based on abstract syntax trees (ASTs) adeptly manage the tree-like nature of source codes, they fall short in discerning the diverse substructural nuances within programs. This paper introduces the Dynamic Syntax Tree Model (DSTM), an innovative approach that fuses various neural network modules into tree architectures tailored to the specific AST of the input. Distinct from preceding tree-based neural models, DSTM adeptly discerns the semantic variances across different AST substructures. We validate DSTM through rigorous testing in program classification and code clone detection, outperforming contemporary methods and demonstrating the benefits of harnessing intricate source code structures.

COVID-19 transmission models have conferred great value in informing public health understanding, planning, and response. However, the pandemic also demonstrated the infeasibility of basing public health decision-making on transmission models with pre-set assumptions. No matter how favourably evidenced when built, a model with fixed assumptions is challenged by numerous factors that are difficult to predict. Ongoing planning associated with rolling back and re-instituting measures, initiating surge planning, and issuing public health advisories can benefit from approaches that allow state estimates for transmission models to be continuously updated in light of unfolding time series. A model being continuously regrounded by empirical data in this way can provide a consistent, integrated depiction of the evolving underlying epidemiology and acute care demand, offer the ability to project forward such a depiction in a fashion suitable for triggering the deployment of acute care surge capacity or public health measures, support quantative evaluation of tradeoffs associated with prospective interventions in light of the latest estimates of the underlying epidemiology. We describe here the design, implementation and multi-year daily use for public health and clinical support decision-making of a particle filtered COVID-19 compartmental model, which served Canadian federal and provincial governments via regular reporting starting in June 2020. The use of the Bayesian Sequential Monte Carlo algorithm of Particle Filtering allows the model to be re-grounded daily and adapt to new trends within daily incoming data – including test volumes and positivity rates, endogenous and travel-related cases, hospital census and admissions flows, daily counts dose-specific vaccinations administered, measured concentration of SARS-CoV-2 in wastewater, and mortality. Important model outputs include estimates (via sampling) of the count of undiagnosed infectives, the count of individuals at different stages of the natural history of frankly and pauci-symptomatic infection, the current force of infection, effective reproductive number, and current and cumulative infection prevalence. Following a brief description of model design, we describe how the machine learning algorithm of particle filtering is used to continually reground estimates of dynamic model state, support probabilistic model projection of epidemiology and health system capacity utilization and service demand and probabilistically evaluate trade-offs between potential intervention scenarios. We further note aspects of model use in practice as an effective reporting tool in a manner that is parameterized by jurisdiction, including support of a scripting pipeline that permits a fully automated reporting pipeline other than security-restricted new data retrieval, including automated model deployment, data validity checks, and automatic post-scenario scripting and reporting. As demonstrated by this multi-year deployment of Bayesian machine learning algorithm of particle filtering to provide industrial-strength reporting to inform public health decision making across Canada, such methods offer strong support for evidence-based public health decision making informed by ever-current articulated transmission models whose probabilistic state and parameter estimates are continually regrounded by diverse data streams.

The microsporidium Nosema ceranae is a high prevalent parasite of the European honey bee (Apis mellifera). This parasite is spreading across the world into its novel host. The developmental process and some mechanisms of N. ceranae infected honey bees has been studied thoroughly, however, few studies have been carried out in the mechanism of gene expression in N. ceranae during infection process. We therefore performed suppressive subtractive hybridization (SSH) approach to investigate the candidate genes of N. ceranae during its infection process. Each 96 clones of infected (forward) and non-infected (reverse) library were dipped onto the membrane for hybridization. A total of 118 differentially expressed sequence tags (ESTs) had been sequenced. For the host responses, 20% of ESTs (13 ESTs, 10 genes and 1 non-coding RNA) from forward library and 83% of ESTs (44 ESTs, 28 genes) from reverse library were identified as differentially expressed genes (DEGs) of the hosts. High percentage of DEGs involved in catalytic activity and metabolic processes, revealed the host gene expression change after N. ceranae infection might lead to the unbalance of physiological mechanism. Among the ESTs from forward library, 75.4% ESTs (49 ESTs belonged to 24 genes) were identified as N. ceranae genes. Of 24 N. ceranae genes, nine DEGs were subjected to real-time quantitative reverse transcription PCR (real-time qRT-PCR) for validation. The results indicated that these genes showed highly up-regulated during N. ceranae infection. Among nine N. ceranae genes, one N. ceranae gene (AAJ76_1600052943) showed the highest expression level after infection. These identified differentially expressed genes from this SSH could provide information about the pathological effects of N. ceranae. Validation of nine up-regulated N. ceranae genes revealed highly potential for the detection of early nosemosis in the field and provide insight for further applications.

We developed a honey bee RNA-virus vector based on the genome of a picorna-like Deformed wing virus (DWV), the main viral pathogen of the honey bee (Apis mellifera). To test the potential of DWV to be utilized as a vector, the 717 nt sequence coding for the enhanced green fluorescent protein (eGFP), flanked by the peptides targeted by viral protease, was inserted into an infectious cDNA clone of DWV in-frame between the leader protein and the virus structural protein VP2 genes. The in vitro RNA transcripts from egfp-tagged DWV cDNA clones were infectious when injected into honey bee pupae. Stable DWV particles containing genomic RNA of the recovered DWV with egfp inserts were produced, as evidenced by cesium chloride density gradient centrifugation. These particles were infectious to honey bee pupae when injected intra-abdominally. Fluorescent microscopy showed GFP expression in the infected cells and Western blot analysis demonstrated accumulation of free eGFP rather than its fusions with DWV LP and/or VP2 proteins. Analysis of the progeny egfp-tagged DWV showed gradual accumulation of genome deletions for egfp, providing estimates for the rate of loss of a non-essential gene an insect RNA virus genome during natural infection.

The thermal properties of a building envelope are key indicators of the energy performance of the building. Therefore, methods are needed to determine quantities like U-values or heat capacitance in a fast, reliable way and with as little impact on the use of the building as possible. In this paper a technique is proposed that relies on a simplified electrical analogical model of building envelope components which can cover their dynamic thermal behavior. The parameters of this model are optimized to produce the best fit between simulated and measured outside surface temperatures. As the temperatures can be measured remotely with an infrared camera this approach requires significantly less installation effort and intrusion in the building than other methods. At the same time, a single measurement provides data for a large range of locations on a facade or a roof. The paper describes the method and a first experimental implementation of it. The experiment indicates that this method has the potential to produce results which have an accuracy that is comparable to standardized reference methods.

Solid asperity interactions are common and inevitable under severe loading conditions for any lubricated contact. Heavy-duty machine components (gear, bearings etc.) generally operate under Mixed Lubrication, where uneven surface features contact each other when generated fluid pressure is not enough to support the external load. The Reynolds equation is commonly used to simulate smooth lubricated contacts numerically. In rough lubricated interfaces where opposite surface asperities make contact, the Reynolds equation alone cannot accurately predict pressure using the traditional numerical simulation method. In this paper, Lubrication-Contact interface conditions (LCICs) have been implemented and extended to solve the multiple asperity contact problem using the full-multigrid approach. The developed novel algorithm has significantly accelerated the solution process and improved the accuracy and efficiency of pressure calculation for fluid-solid sub-interactions that can occur under ML regions. The Finite Difference Method (FDM) results have been compared with Computational Fluid Dynamics (CFD) simulation to validate the newly developed model. Hence, the proposed optimized solution method will provide valuable insight to researchers and industry engineers interested in simulating the ML problem where the effect of the fluid-solid interface can be captured effectively to improve reliability in the calculation of the life expectancy of the lubricated parts.

The most widely spread and neglected zoonotic disease – Leptospirosis, with an estimated 1.03 million cases and 58,900 deaths occurring annually, is a concern and can be prevented only by effective immunization. Due to the urgent need for a novel vaccine, various research organizations have been evaluating the protective immune response elicited by recombinant vaccines. In this study amino-acid sequences of Outermembrane protein (OMPL) 1, LipL 32, 41 and 46 from ten pathogenic serovars of Leptospira were selected to obtain epitopes that induce CD4+ and CD8+ T cell responses by binding to the MHC molecules. These B cell and T cell epitopes were used to design multi-epitope vaccine to which an adjuvant sequence was added at the N-terminal end and appropriate linkers were used to join the different epitopes to increase the efficiency of the vaccine constructs. Using an immuno-informatics approach, constructs were analyzed for the physiochemical properties, secondary and tertiary structure and its validation, docking with different receptors and prediction of binding affinity for each docked complex, followed by molecular dynamics simulation. Taking in consideration all the results, multi-epitope constructs designed may prove to be promising vaccine candidates against Leptospirosis and warrants experimental validation.