Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybridization altered the gut microbiota of pigs

Mammalian gut microbiota plays an important role in the host’s nutrient metabolism, growth, and immune regulation. Hybridization can enable a progeny to acquire superior traits of the parents, resulting in the hybridization advantage. However, studies on the effects of hybridization on the pigs’ gut microbiota are lacking. Therefore, this study used multi-omics technologies to compare and analyze the gut microbiota of the primary wild boar and its offspring. The 16S rRNA gene sequencing results revealed that the gut microbiota of F4 exhibited a host-like dominance phenomenon with a significant increase in the abundance of Lactobacillus and Bifidobacterium. The beta diversity of Duroc was significantly different from those of F0, F2, and F4; after the host hybridization, the similarity of the beta diversity in the progeny decreased with the decrease in the similarity of the F0 lineage. The metagenomic sequencing results showed that the significantly enriched metabolic pathways in F4, such as environmental, circulatory system, fatty acid degradation adaptation, and fatty acid biosynthesis, were similar to those in F0. Moreover, it also exhibited similar significantly enriched metabolic pathways as those in Duroc, such as carbohydrate metabolism, starch and sucrose metabolism, starch-degrading CAZymes, lactose-degrading CAZymes, and various amino acid metabolism pathways. However, the alpha-amylase-related KOs, lipid metabolism, and galactose metabolism in F4 were significantly higher than those in Duroc and F0. Non-targeted metabolome technology analysis found that several metabolites, such as docosahexaenoic acid, arachidonic acid, and citric acid were significantly enriched in the F4 pigs as compared to those in F0. Based on Spearman correlation analysis, Lactobacillus and Bifidobacterium were significantly positively correlated with these metabolites. Finally, the combined metagenomic and metabolomic analysis suggested that the metabolic pathways, such as valine, leucine, and isoleucine biosynthesis and alanine aspartate and glutamate metabolism were significantly enriched in F4 pigs. In conclusion, the gut microbiota of F4 showed a similar host “dominance” phenomenon, which provided reference data for the genetics and evolution of microbiota and the theory of microbial-assisted breeding.
Immunogenomic profile at baseline predicts host susceptibility to clinical malaria

Introduction Host gene and protein expression impact susceptibility to clinical malaria, but the balance of immune cell populations, cytokines and genes that contributes to protection, remains incompletely understood. Little is known about the determinants of host susceptibility to clinical malaria at a time when acquired immunity is developing. Methods We analyzed peripheral blood mononuclear cells (PBMCs) collected from children who differed in susceptibility to clinical malaria, all from a small town in Mali. PBMCs were collected from children aged 4-6 years at the start, peak and end of the malaria season. We characterized the immune cell composition and cytokine secretion for a subset of 20 children per timepoint (10 children with no symptomatic malaria age-matched to 10 children with >2 symptomatic malarial illnesses), and gene expression patterns for six children (three per cohort) per timepoint. Results We observed differences between the two groups of children in the expression of genes related to cell death and inflammation; in particular, inflammatory genes such as CXCL10 and STAT1 and apoptotic genes such as XAF1 were upregulated in susceptible children before the transmission season began. We also noted higher frequency of HLA-DR+ CD4 T cells in protected children during the peak of the malaria season and comparable levels cytokine secretion after stimulation with malaria schizonts across all three time points. Conclusion This study highlights the importance of baseline immune signatures in determining disease outcome. Our data suggests that differences in apoptotic and inflammatory gene expression patterns can serve as predictive markers of susceptibility to clinical malaria.
Lactobacillus plantarum GX17 benefits growth performance and improves functions of intestinal barrier/intestinal flora among yellow-feathered broilers

Lactobacillus plantarum has recently been found to be a natural source feed additive bacteria with great advantages in food safety and animal welfare. Discovering novel strains with commercial application potentiation could benefit the local poultry industry, and in particular support Chinese farmers. In this study, we tested a recently isolated novel strain of Lactobacillus plantarum GX17 as a feed additive on the growth performance and intestinal barrier functions of 1-day-old Chinese yellow-feather chicks. As good as other commercial probiotics, feeding with Lactobacillus plantarum GX17 showed significant improvements in humoral immune responses and enhanced the immune effect after vaccination for either the Newcastle disease vaccine or the avian influenza vaccine. This study also found that feeding with Lactobacillus plantarum GX17 improved the feed-to-weight ratio and caused a significant increase of the villus length to crypt depth ratio. Furthermore, Lactobacillus plantarum GX17 significantly up-regulated the mRNA expression of CLDN, MUC2, and TLR2, all of which are jejunum-associated barrier genes, indicating an improvement of the intestinal barrier functions by enhancing the tight junction between epithelia cells. These results are comparable to the effects of feeding the commercial complex probiotics that improve the expression levels of CLDN, ocludin, MUC2, TLR2, and TLR4. In terms of maintaining intestinal health, commercial complex probiotics increased the relative abundance of Parabacteroides and Romboutsia, while Lactobacillus plantarum GX17 increased the relative abundance of Pseudoflavonifractor. Our data suggest that Lactobacillus plantarum GX17 could enhance the intestinal absorption of nutrients and therefore improve the growth performance of Chinese yellow-feather chicks. In conclusion, compared with the commercial complex probiotics, Lactobacillus plantarum GX17 has more positive effects on the growth performance and intestinal barrier function of yellow-feather chickens, and can be used as a feed additive.
Anticyclotomic Iwasawa invariants and congruences of modular forms

The main purpose of this article is to examine how congruences between Hecke eigensystems of modular forms affect the Iwasawa invariants of their anticyclotomic p-adic L-functions. We apply Greenberg-Vatsal and Emerton-Pollack-Weston’s ideas on the variation of Iwasawa invariants under congruences to the anticyclotomic setting. As an application, we establish infinitely many new examples of the anticyclotomic main conjecture for modular forms, which are not treated by Skinner-Urban’s work. An explicit example is given.
Κ-means clustering on the space of persistence diagrams

A recent cohort of research aims to apply topological and geometric theory to data analysis. However, more effort is needed to incorporate statistical ideas and structure to these analysis methods. To this end, we present persistent homology clustering techniques through the perspective of data analysis. These techniques provide insight into the structure of the underlying dynamic and are able to recognize important shape properties such as periodicity, chaos, and multi-stability. Moreover, introducing quantitative structure on the topological data space allows for rigorous understanding of the data's geometry, a powerful tool for scrutinizing the morphology of the inherent dynamic. Additionally, we illustrate the advantages of these techniques and results through examples derived from dynamical systems applications.
Role of the Rhamnosyl Residue of Ouabain in the Activation of the Na,K-ATPase Signaling Function

Simple Summary Medicinal treatment of chronic pain prompts finding novel approaches to the creation of safe and effective analgesics. Ouabain, a cardiotonic steroid detected in the human organism at extremely low concentrations, has been previously shown by us to switch off the pain signal produced by peripheral neurons. The current manuscript elucidates the mechanism of ouabain binding to its molecular target, the Na,K-ATPase enzyme. Application of very sensitive physiological techniques demonstrated a complete loss of the ouabain effect upon removal of the rhamnosyl residue, a structural element of the ouabain molecule. Theoretical modeling made it possible to determine the contribution of the rhamnosyl residue to the process of ouabain binding with Na,K-ATPase. It was concluded that intermolecular bonds between the rhamnosyl residue of ouabain and Na,K-ATPase amino acid residues identified through modeling are required for the analgesic effect of ouabain to manifest itself. To facilitate creation of fundamentally new safe and effective analgesics, the mechanisms of their binding to the corresponding molecular receptors should be clarified at the atomic level. Abstract The signaling or non-pumping Na,K-ATPase function was first observed by us in the nociceptive neuron; Na,K-ATPase transduced the signals from the opioid-like receptors to NaV1.8 channels. This study elucidates the role of the rhamnosyl residue of ouabain in the activation of the Na,K-ATPase signaling function. The effects resulting from activation of Na,K-ATPase signaling by the Ca2+ chelate complex of ouabain (EO) are not manifested upon removal of the rhamnosyl residue, as demonstrated in viable cells by the highly sensitive patch-clamp and organotypic cell culture methods. Docking calculations show that the rhamnosyl residue is involved in five intermolecular hydrogen bonds with the Na,K-ATPase α1-subunit, which are fundamentally important for activation of the Na,K-ATPase signaling function upon EO binding. The main contribution to the energy of EO binding is provided by its steroid core, which forms a number of hydrogen bonds and hydrophobic interactions with Na,K-ATPase that stabilize the ligand–receptor complex. Another critically important role in EO binding is expected to be played by the chelated Ca2+ cation, which should switch on strong intermolecular ionic interactions between the EO molecule and two α1-Na,K-ATPase amino acid residues, Glu116 and Glu117.
Investigation of Biochemical Blood Parameters of COVID-19 Patients Short (running) title: Biochemical Blood Parameters of COVID-19 Patients

Objectives: In this study, it was aimed to investigate the effect of biochemical blood values on the course of the disease. Material and Methods: This is a retrospective study. For the treatment of COVID-19, clinical features and biochemical test parameters of 243 patients who applied to Malatya Training and Research Hospital in Malatya province of Turkey between 03 March and 31 December 2021 were used. Results: In the regression analysis performed in patients with Covid, glucose, urea, ALP, LDH, albumin, calcium and potassium levels were found to be effective on the severity of the disease. Conclusion: Biochemical parameters can be used as clinical findings to predict the diagnosis and course of COVID-19. Title: Investigation of Biochemical Blood Parameters of COVID-19 Patients Short (running) title: Biochemical Blood Parameters of COVID-19 Patients Author name: Semih ERITEN, Sultanbeyli State Hospital Department Of Emergency, Battalgazi, Paşaköy st. 34935 İstanbul, Turkey, semiheriten@hotmail.com There is no conflict of interest in the study No financial support was received in the study ABSTRACT Objectives: In this study, it was aimed to investigate the effect of biochemical blood values on the course of the disease. Material and Methods: This is a retrospective study. For the treatment of COVID-19, clinical features and biochemical test parameters of 243 patients who applied to Malatya Training and Research Hospital in Malatya province of Turkey between 03 March and 31 December 2021 were used. Results: In the regression analysis performed in patients with Covid, glucose, urea, ALP, LDH, albumin, calcium and potassium levels were found to be effective on the severity of the disease. Conclusion: Biochemical parameters can be used as clinical findings to predict the diagnosis and course of COVID-19.
From Conspiracy to Hesitancy: The Longitudinal Impact of COVID-19 Vaccine Conspiracy Theories on Perceived Vaccine Effectiveness

The embrace of coronavirus disease 2019 (COVID-19) vaccine conspiracies has been linked to vaccine hesitancy. This study aimed to investigate the relationship between COVID-19 vaccine conspiracy theories and perceived vaccine effectiveness. The study utilized a longitudinal follow-up study in which adults in Chile completed surveys in December 2020 (T1) and May 2021 (T2). The psychometric properties of the five-item instrument on conspiracy theories for the COVID-19 vaccine were evaluated using data from T1 (n = 578). A confirmatory one-factor structure with suitable indicators of reliability was found. The longitudinal analysis (n = 292) revealed that conspiracy theories about the COVID-19 vaccine in T1 were associated with lower beliefs in its effectiveness in T2. However, no significant association was found between beliefs in effectiveness in T1 and conspiracy theories in T2. The study suggests that beliefs in conspiracy theories may temporally precede beliefs in vaccine effectiveness for COVID-19. The results have implications for strategies to address vaccine conspiracy beliefs and their implementation at the public policy level.
An Overview of Carbon Emission Mitigation in the Food Industry: Efforts, Challenges, and Opportunities

The food system plays a significant role in anthropogenic greenhouse gas (GHG) emissions, contributing to over one-third of these emissions. However, there has been limited attention given in the literature on how the food industry can effectively address the carbon issue. This review aims to bridge this research gap through providing a comprehensive overview of anthropogenic GHG emissions and exploring the role of carbon markets in mitigating climate change, with a specific emphasis on the food industry. It delves into the introduction of emission hotspots within the food industry, examines ongoing efforts in GHG emissions mitigation, and addresses the challenges associated with GHG verification and offsetting. Notably, emission hotspots are primarily found in the farm, manufacturing, and post-production stages of the food industry. The emissions from the farm stage, which are often overlooked, make a significant contribution to overall emissions. Carbon verification encounters limitations due to a lack of standardized methodologies, inaccurate data, and insufficient reporting of emissions. Currently, achieving carbon neutrality without relying on carbon offsets presents a significant challenge for the entire food industry. Comprehensive mitigation strategies and collaboration across agricultural producers and the food manufacturing industry are considered potential solutions to achieve genuine sustainability.
Analysis of Genetic Diversity and Development of A Core Collection in Walnut (Juglans regia L.) Germplasm Native to China via Genotyping-by-Sequencing

Popular knowledge of the population structure and genetic diversity of a plant species is essential for designing improvement strategies. The genotyping-by-sequencing (GBS) approach has been used to simplify complex genomes and has become a popular high-throughput molecular tool for selecting and breeding many crop plants, including those with large genomes. This study aimed to construct a core collection of walnut (Juglans regia) germplasm using the GBS approach. A diversity panel of 87 walnut initial genotypes, including 25 landraces, 12 cultivars, and 50 seedling populations, mostly native to the Gansu Province of China, was subjected to GBS. A total of 110,497 high-quality SNPs were identified and used for determining distinct clusters and an optimum number of subpopulations. Structure analysis divided the genotypes into three distinct groups, which coincided with their collection site and year, suggesting a certain degree of separation in the geographical origin and pedigree among the three groups. To maximize germplasm utilization, the genotypes were posteriorly grouped according to the subgroups obtained through GBS analysis. To minimize subsample redundancy, the core collection was designed using a set of 6540 SNPs distributed across all 16 chromosomes. Finally, a core collection comprising nine walnut genotypes (10% of the entire genotype set), including five cultivars, three seedling populations, and one landrace, was assembled. Genetic structure analysis indicated that the core collection has an uneven distribution in the landrace collection, which could be related to environmental conditions, and the genotypes of the landrace collection are similar. Overall, the results of this study and the establishment of the core collection will facilitate the improvement of walnut in future breeding programs.
A Lightweight Crop Pest Detection Algorithm Based on Improved Yolov5s

The real-time target detection of crop pests can help detect and control pests in time. In this study, we built a lightweight agricultural pest identification method based on modified Yolov5s and reconstructed the original backbone network in tandem with MobileNetV3 to considerably reduce the number of parameters in the network model. At the same time, the ECA attention mechanism was introduced into the MobileNetV3 shallow network to meet the aim of effectively enhancing the network’s performance by introducing a limited number of parameters. A weighted bidirectional feature pyramid network (BiFPN) was utilized to replace the path aggregation network (PAnet) in the neck network to boost the feature extraction of tiny targets. The SIoU loss function was utilized to replace the CIoU loss function to increase the convergence speed and accuracy of the model prediction frame. The updated model was designated ECMB-Yolov5. In this study, we conducted experiments on eight types of common pest dataset photos, and comparative experiments were conducted using common target identification methods. The final model was implemented on an embedded device, the Jetson Nano, for real-time detection, which gave a reference for further application to UAV or unmanned cart real-time detection systems. The experimental results indicated that ECMB-Yolov5 decreased the number of parameters by 80.3% and mAP by 0.8% compared to the Yolov5s model. The real-time detection speed deployed on embedded devices reached 15.2 FPS, which was 5.7 FPS higher than the original model. mAP was improved by 7.1%, 7.3%, 9.9%, and 8.4% for ECMB-Yolov5 compared to Faster R-CNN, Yolov3, Yolov4, and Yolov4-tiny models, respectively. It was verified through experiments that the improved lightweight method in this study had a high detection accuracy while significantly reducing the number of parameters and accomplishing real-time detection.
Parameter Identification of a Multilayer Perceptron Neural Network using an Optimized Salp Swarm Algorithm

—Effort estimation in software development (SEE) is a crucial concern within the software engineering domain, as it directly impacts cost estimation, scheduling, staffing, planning, and resource allocation accuracy. In this scientific article, the authors aim to tackle this issue by integrating machine learning (ML) techniques with metaheuristic algorithms in order to raise prediction accuracy. For this purpose, they employ a multilayer perceptron neural network (MLP) to perform the estimation for SEE. Unfortunately, the MLP network has numerous drawbacks as well, including weight dependency, rapid convergence, and accuracy limits. To address these issues, the SSA Algorithm is employed to optimize the MLP weights and biases. Simulta-neously, the SSA algorithm has shortcomings in some aspects of the search mechanisms as well, such as rapid convergence and being susceptible to the local optimal trap. As a result, the genetic algorithm (GA) is utilized to address these shortcomings through fine-tuning its parameters. The main objective is to develop a robust and reliable prediction model that can handle a wide range of SEE problems. The developed techniques are tested on twelve benchmark SEE datasets to evaluate their performance. Furthermore, a comparative analysis with state-of-the-art methods is conducted to further validate the effectiveness of the developed techniques. The findings demonstrate that the developed techniques surpass all other methods in all benchmark problems, affirming their superiority.
Postharvest Fish Processing in the Southwest Region of Cameroon and the Effect of Smoke-Drying on Quality

Fish processing in Cameroon is mostly carried out by untrained individuals using different methods which often produce fish products of poor quality. This study was aimed at identifying the main fish processing technologies used in 5 fishing communities in Limbe Subdivision in the Southwest Region of Cameroon. A total of 120 questionnaires were administered in the study area to identify the most popular unit operation in fish processing and to evaluate its effect under controlled conditions on the quality of fish products. It was found that the main fish technology employed was smoke-drying and that most of the processors dried the Ilisha africana species. Smoke-drying of Ilisha africana was carried out under controlled conditions of temperature and time, and smoked fish samples of different colours ranging from pale brown to dark brown were obtained. Laboratory analysis of the fish samples revealed that the moisture content and microbial content of the fish decreased significantly ( p < 0.05 ), while protein content increased significantly ( p < 0.05 ) with an increase in smoking time and temperature. The optimum moisture content was achieved at temperature ranges of 61-70°C for 18 h (12.3%), 71-80°C for 12 h (10.7%), and 18 h (7.3%). The pH and microbial content of all the samples were within the recommended levels for consumption and safe storage. It was concluded that the best temperature ranges and times for smoke-drying Ilisha africana were 61-70°C for 18 h and 71-80°C for 12 h.
Anxiety, Optimism, and COVID-19 Vaccine Hesitancy among Students in a University in Southern Thailand during the 2021 Academic Year

This study examined the prevalence of COVID-19 vaccine hesitancy and its associated factors, including anxiety and optimism, surrounding the COVID-19 pandemic among Thai university students. An online observational cross-sectional study was conducted between November and December 2021. Descriptive analyses and logistic regression were performed using R. In total, 409 university students participated in the study. Most reported high anxiety levels (69.4%), while more than half also expressed high levels of optimism associated with the COVID-19 pandemic (51.1%). Only 4.4% were unvaccinated, among whom 50% were hesitant to receive vaccination (2.2%). Per statistical analysis, those who perceived the available vaccines as low safety were significantly associated with a higher risk of vaccine hesitancy (p = 0.03). In contrast, those who reported that they would likely to receive the COVID-19 vaccine if recommended to by their doctors or pharmacists were significantly associated with lower vaccine hesitancy (p = 0.048). However, both anxiety and optimism regarding the COVID-19 pandemic were not associated with vaccine hesitancy. Thus, healthcare workers play an important role in COVID-19 vaccination counseling to prevent transmission. Health education during the pandemic should focus on COVID-19 infection as well as COVID-19 vaccines, including their safety and their adverse effects.