bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of amino acid content of Chebulae Fructus in different origins and different processing states based on microwave digestion
Authors: Xu Zhiqi , Tan Lihong , Wang Yiwu , Yu Jialing , Zeng Chuiming , Wei Jia , Yang Lin , He Dan 
Published: September 2024

Abstract

The microwave digestion method was optimized to extract amino acids from Chebulae Fructus (CF), and the differences of amino acids in CF from different origins and different processing states were analyzed and evaluated. The amount of total amino acid extraction of CF was used an indicator, the influences of digestion temperature, digestion time, and liquid-material ratio on extraction effect were investigated by sing factor test and response surface method (RSM), and the extraction conditions were optimized. The contents of 17 amino acids were determined by an automatic amino acid analyzer. Chemometrics was also applied to analyze the differences in amino acid content between CF from different origins and processing states. The optimal digestion conditions were a digestion temperature of 150 ℃, a digestion time of 18 min, and a liquid-material ratio of 65:1 (mL:g). Under these conditions, the total amino acid content of CF could reach 19.72 mg/g. According to the standards published by FHO/WHO, CF from Lincang city of Yunnan province and unprocessed CF were considered to have higher nutritional value. The results of chemometric analysis showed that there were significant differences in the amino acid content in CF between Guangxi province, Dehong prefecture of Yunnan province and Lincang city of Yunnan province, and six differential amino acids between the three origins were screened out. There were also significant differences in the amino acid content of CF before and after processing, and eight differential amino acids were screened out. The optimized amino acid extraction method had short time and high efficiency, and there was no significant difference from the conventional digestion method. There were differences in amino acid content of CF from different origins and processing states, which can be analyzed by chemometrics and screened for different components. This study can provide references for the quality evaluation of the producing area, the extraction and content research of amino acids of CF.
Viral pseudo-enzyme facilitates KSHV lytic replication via suppressing PFAS-mediated RTA deamidation
Authors: Xu Yang , Zhang Qiushi , Hou Guoli , Hu Liang , Xiao Tiaoyi , Li Deliang , Li Junhua 
Published: September 2024

Abstract

Background
Deamidation, a type of post-translational modification commonly considered a hallmark of protein “aging” and function decay, is increasingly recognized for its pivotal role in regulating biological processes and viral infection. Our previous study has demonstrated that the deamidation of replication and transcription activator (RTA), a master regulator of ubiquitous and oncogenic Kaposi’s sarcoma-associated herpesvirus (KSHV), mediated by phosphoribosylformylglycinamidine synthetase (PFAS), hinders its nuclear import and transcriptional activity.
Results
Here we report that the viral glutamine amidotransferase (vGAT) pseudo-enzyme was exploited to promote KSHV lytic infection through inhibition of PFAS-mediated RTA deamidation, RTA nuclear localization, and NF-κB activation. To be more specific, vGAT competitively interacted with RTA and cellular PFAS, thereby suppressing the deamidation and nuclear localization of RTA, while concomitantly augmenting RTA-mediated transcriptional activation. Consistently, the RTA deamidation-resistant mutant demonstrated elevated levels of transcriptional activity and lytic replication. Lastly, vGAT appeared to regulate the deamidation process of multiple viral proteins in KSHV.
Conclusions
Collectively, these findings unveil that a viral pseudo-enzyme was exploited to enhance viral infection via deamidation regulation.
An improved YOLOv8 method for identifying empty cell and unqualified plug seedling
Authors: Li Lei , Yu Jiajia , Lu Yujun , Gu Yue , Liang Sijia , Hao Shuai 
Published: September 2024

Abstract

A lightweight seedling detection model with improved YOLOv8s is proposed to address the seedling identification problem in the replenishment process In industrial vegetable seedling production, First, the CBS module in the network structure is replaced with depthwise separable convolution (DSC) to reduce the number of parameters and GFLOPS of the model. The efficient multiscale attention (EMA) module is added to the structure to improve the feature extraction capability of the network, focusing on the target regions of empty and unqualified seedlings in seedling trays in complex environments. Second, the VoVGSCSP module is utilized to replace the C2f module in Neck to further lighten the model and improve its accuracy. Compared with the original YOLOv8s model, the Precision, Recall, and mAP of the improved model on the test set are 95.9%, 91.6%, and 96.2%, respectively, and its parameters, GFLOPS, and model size are 7.88 M, 20.9, and 16.1 MB, respectively. The detection speed of the algorithm is 116.3 frames per second (FPS), which is higher than that of the original model (107.5 FPS). The results indicate that the improved model can accurately identify empty cell and unqualified seedling in the plug tray in real time and has a smaller number of parameters and GFLOPS, making it suitable for use on embedded or mobile devices for seedling replenishment and contributing to the realization of automated and unmanned seedling replenishment.
Investigating the hub genes and genetic basis regulating fatty acid metabolictraits in chicken breast muscle based on combined genomic and transcriptomic approaches
Authors: Fan Shengxin , Zhang Hongyuan , Li Hongtai , Yuan Pengtao , Dai Yaqi , Li Hong , Liu Xiaojun , Tian Yadong , Kang Xiangtao , Zhang Yanhua , Zhao Yinli , Li Guoxi 
Published: September 2024

Abstract

Background The composition of various fatty acids in meat plays a crucial role in the evaluation of the nutritional indicators of poultry and human health. Fatty acid metabolic indicators can more accurately reflect the nutritional status of meat and its acceptance by the general public. In this study, we utilized two analytical approaches, Genome-Wide Association Study (GWAS) and Weighted Gene Co-expression Network Analysis (WGCNA), to elucidate the genetic mechanisms underlying the fatty acid metabolic traits in chicken breast muscle.Initially, GWAS was conducted based on genotype data obtained by genotyping by sequencing (GBS) from 415 chickens of the Gushi-Anka F2 resource population and phenotypic data of 33 fatty acid metabolism traits in the breast muscle.
Results We identified a total of 291 significant single nucleotide polymorphisms (SNPs) associated with the content of 12 types of fatty acids such as C14:0/C12:0, C18:0/C16:0, C18:1/C18:0, etc., which were mapped on chromosomes (Chr) 1, 2, 3, 4, 5, 7, 9, and 10. The most significant SNP was Chr2:102, 676, 165 (P = 1.20E-06), which explained 2.33% of the phenotypic variation in the polyunsaturated fatty acids (PUFA)/mono-unsaturated fatty acids (MUFA) synthesis pathway. The SNP that explained the highest phenotypic variation was Chr4: 30, 150, 765 (5.85%). Interestingly, significant signals were identified for three fatty acid metabolic traits (C22:4/C18:3, C20:3/C18:3, C22:6/C18:3) within the same gene interval on Chr 9 (Chr9: 5.75 - 8.99Mb). Concurrently, WGCNA was conducted using the 613 candidate genes identified from the linkage disequilibrium regions of the aforementioned significant SNPs, as well as the transcriptome data and fatty acid content phenotypic values of the breast muscle of the Gujshi chicken from three periods, 13 hub genes (FIG4, METTL4, PLD4, IDH1, FH, SDHA, EHHADH, AKT1, PIK3CB, LPIN2, FUT9, PAK2, and ACSL3) were finally determined. Further, we constructed the functional networks involving these candidate genes and deduced the potential fatty acid metabolic pathway.
Conclusion These results enhance our understanding of the genetic regulation mechanisms of fatty acid composition in chicken muscle, providing a theoretical basis for future breeding practices targeting fatty acid composition traits.
Elderly Engagement in the Digital Marketplace: A Study of Douyin's Silver-haired Fashion Influencers through Two-step Flow and Multi-step Flow Models
Authors: Zhang Yuying 
Published: September 2024

Abstract

In the digital era, China’s aging population poses significant societal challenges. However, silver-haired fashion influencers on Douyin, with a following of millions, have emerged as a positive force, setting a precedent for smart utilization of older people and silver economy growth. Using the two-step and multi-step flow model theories as a framework, this study explores how these influencers can use product placement in their short videos to optimize profits and self-worth. Through qualitative interviews with 11 followers of such influencers, the research found that the influence of product placement on purchase intentions is multifaceted, influenced by the influencers themselves, followers’ product perceptions, and the platform ecology. In order to increase the impact of product placements, the study highlights the significance of developing parasocial interactions and making thoughtful product selections. Silver-haired fashion influencers may drive the silver economy and promote smart ageing solutions by better leveraging their influence when they understand these dynamics.
Effects of urbanization on taxonomic diversity, body size, body mass and body condition of non-volant small mammals in the Coastal Savannah Ecological zone of Ghana
Authors: Ofori Benjamin Yeboah , Mensah John B. , Asomaning Benjamin , Annan Andy , Attuquayefio Daniel K. 
Published: September 2024

Abstract

In the context of rapidly increasing global urbanization, studying urban landscape effects on wildlife is crucial for informing biodiversity conservation in cities. Small mammals are inextricably linked to their environment and respond swiftly to habitat alterations. Yet, the response of small mammals to urbanization in the Afro-tropics is rarely investigated. Here, we assessed the influence of urbanization on taxonomic diversity, body size, body mass and body condition of small mammals in the Coastal Savannah Ecological zone (CSEZ) of Ghana. We live-trapped small mammals in farm-bushes (UFB) and a protected area (UPA) located within the city of Accra, and compared the data with conspecifics from farm-bushes (RFB) and a protected area (RPA) located within rural areas of CSEZ. The data was analyzed using Fisher’s exact test, ANOVA, ANCOVA and F-ratio test. We found that urbanization influenced small mammal composition, but not species richness and diversity. Three species, Taterilus gracilis, Graphiurus nagtglasii and Arvicanthis niloticus occurred in the urban area only. Mastomys natlensis, Mus musculoides and Tatera kempi from the urban sites were significantly smaller and in poorer condition compared with conspecifics from the corresponding rural sites. M. musculoides from the urban area weighed significantly lesser than their rural conspecifics. Our data demonstrate the varied effects of urbanization on small mammals, and highlight the importance of heterogeneous urban green areas in maintaining small mammal biodiversity in cities. Urban developers and land use planners should prioritize integrating green areas into urban planning designs in order to promote and conserve wildlife in cities.
Longitudinal Changes in Preschoolers’ Self-reported Psychological and Social Problems: Feasibility, Reliability, and Cross-informant Agreement
Authors: Chan Meingold Hiu-ming , Feng Xin , Gong Yihui , Inboden Karis 
Published: September 2024

Abstract

For decades, parental report was used to assess children’s psychological symptoms and social problems. The Berkeley Puppet Interview (BPI) utilizes hand puppets to collect questionnaire-style data from children, allowing consideration of children’s own perspective. The current longitudinal study compared the feasibility and reliability of preschoolers’ self-report with BPI at age 4 (M = 4.03, SD = 0.16; 52% boy, 82% White American) and 5 (M = 5.22, SD = 0.36; 51% boy, 85% White American) as well as cross-informant agreement among children, mothers (74% above college education), alternate caregivers (> 90% biological fathers), and coders. Children completed symptomatology, social, and parenting scales of BPI and their parents completed surveys assessing similar constructs. Our findings revealed both similarities and changes across ages. Specifically, the reliability and cross-informant agreement of the broad symptomatology and parenting scales were promising at both timepoints; however, 4-year-olds showed lower internal consistency in social scales.
A novel adaptation of FRAP quantifies the movement of Drosophila Basement Membrane Collagen in vivo
Authors: MacDuff Danielle , Jacobs Roger 
Published: September 2024

Abstract

A wealth of knowledge regarding the functions of Extracellular Matrix (ECM) macromolecules from in vitro or disease models strives for validation in intact animals. In particular, the progression of cardiomyopathies is tightly linked to pathological changes in the heart ECM. To address this in the Drosophila model, we developed a novel adaptation of fluorescence recovery after photobleaching (FRAP), which allows us to assess ECM protein incorporation during growth in living, intact larvae. Recovery of fluorescently tagged protein is a proxy for addition or relocation of ECM protein. We focus on Collagen IVα (Viking), a conserved protein thought to be a stable component of the basement membrane (BM). We established a time course for Vkg-GFP fluorescence accretion in three different BMs through larval development, under normal conditions and when Matrix Metalloprotease or its inhibitor, TIMP is overexpressed. We demonstrate that the gain and loss of Collagen trimers from the basement membrane changes over developmental time and between tissues. High variability in measured fluorescence reduced the sensitivity of this approach. During growth, a strong phasic wave of Vkg accumulation was detected at the second to third instar ecdysis, potentially supporting growth of the new instar. Between organs, flux of Vkg was high in somatic muscle, intermediate in the heart and low in trachea. Heart-specific overexpression of mmp2 and its inhibitor timp, modified the dynamics of Vkg-GFP flux. We find that MMPs are positive regulators of Vkg/Col IV turnover in the ECM, in alignment with current models of ECM regulation.
Parameter-Efficient Domain Adaptation for Edge Detectors: A Comparative Study of Colormap Models and LoRA
Authors: Bommireddy Venkat Sumanth Reddy , Raniwala Sophie , Kumar Piyush 
Published: September 2024

Abstract

Edge Detectors are one of the most fundamental tools in Computer Vision applications. Using deep learning, state-of-the-art (SOTA) models can produce sharp, fine edges, mirroring human-level performance. However, most of these SOTA models are trained solely on color images. We experimentally determined that this limited data severely hinders performance on images from other domain spaces. This paper proposes 2 methods to adapt SOTA models to single-channel images with minimal computational overhead. We first propose a feed-forward network (FFN) for domain adaptation. Then, we propose an extension on this network that uses Fourier convolutions to boost performance. Our models serve as an additional layer to existing SOTA edge detectors, allowing the edge detector to generalize well to new domain spaces without undergoing extensive resource or data-heavy retraining. Our models were trained with a single off-the-shelf GPU with trainable parameters less than 60K and a small dataset of 30-50 images. The training of the FFN took 30 minutes and the training of the Fourier convolution model took 2 hours. Using these lightweight models, we could boost the F-score of the resulting edgemaps by over 0.2.
Artificial Intelligence (AI)-Based Simulators versus Simulated Patients in undergraduate programs: a protocol for a randomized controlled trial
Authors: Zidoun Youness , Mardi Abdelmoniem EL 
Published: September 2024

Abstract

Background:
Healthcare simulation is critical for medical education, with traditional methods using simulated patients (SPs). Recent advances in AI offer new possibilities with AI-based simulators. This study compares AI-based simulators and SPs in undergraduate medical education.
Methods:
A randomized controlled trial will be conducted to identify the effectiveness of delivering a simulation session around history taking skills to fifth-year medical students on their clinical years of study. This research protocol aims to examine and compare the effectiveness and user experience of artificial intelligence-based simulators compared to simulated patients.
Discussion:
This study will provide valuable insights into the comparative advantages of artificial intelligence-based simulators and simulated patients, which will guide decisions regarding their integration into health education and training programs.
Forecasting of Solar Power Generation Using Machine Learning and Deep Learning Algorithms
Authors: Sarker Debasish , Karim S. M. Rezaul 
Published: September 2024

Abstract

This study analyses the predictability of solar electricity generation using various machine and deep learning methods on large solar datasets from diverse cities in Saudi Arabia and the United States. According to our most recent article [1], the "Multilayer Perceptron" and "Random Forest" algorithms perform better in forecasting Saudi Arabia's solar power generation. This finding has been validated using additional datasets in the present study. Additionally, the effects of various hidden layer and neuron number combinations on MLP performance are examined. We found beyond a certain point, the number of hidden layers in an MLP became inversely correlated with its prediction accuracy. As the number of neurons in the model increases, the training duration also increases, generally improving predictability. The RMSE of deep learning algorithms such as the feedforward neural network (FFNN), convolutional neural network (CNN), and long short-term memory (LSTM) are compared against the MLP and Random Forest to evaluate their feasibility in estimating solar power generation. We found that FFNN and MLP provide almost similar results and Random Forest gives the best results among all the ML and DL algorithms for predicting solar power generation using our datasets. Future work may explore different aspects of the Random Forest model.
Health-Seeking Behavior Following Injuries in Rural Children at a Sub-District of Bangladesh
Authors: Afreen Nawroz , Nurunnahar Mehejabin , Flora Meerjady S 
Published: September 2024

Abstract

Objectives
Knowing health-seeking behavior of family or caregiver is necessary to identify and include scopes of intervention in any injury prevention program, though Bangladesh lacks in recent information. Therefore, this cross-sectional study aimed to provide an updated understanding of health-seeking behavior of family or caregiver following major and minor injuries in rural children.
Methods
It was conducted between May-June 2018 in children (< 18-years) from a selected sub-district following probability sampling. A non-fatal injury occurring within previous three months and hampering regular activities < 30 days was minor, and one occurring within last year and hampering regular activities ≥ 30 days was major. Health-seeking responses for injured children were descriptively analyzed.
Results
Of enrolled 918 children, prevalence of major and minor injuries were 2.4% and 7.4% respectively. Except one child, all other sought for some sort of treatment after an injury. After a major injury (n = 22), 17 children received first aid, mainly provided by relatives (47%) and doctors/trained Health Care Workers (HCWs) (41%). Further treatment was pursued in 64% (n = 22) children; 50% (n = 16) adhered to treatment of doctors/trained HCWs. Median (IQR) suffering was 35 (30–75) days and 18% (n = 22) were hospitalized. After a minor injury (n = 68), 59 children received first aid, mainly provided by relatives (54%) and non-qualified HCWs (25.5%). Further treatment was pursued in 60% (n = 68) children; 71% (n = 49) adhered to treatment of non-qualified HCWs. Median (IQR) suffering was 7 (4–15) days and 3% (n = 68) were hospitalized. Family or caregiver often applied different substances (oil, water, toothpaste, ointment, leaves) over injured part as first aid irrespective of injury pattern and type, though substances varied.
Conclusion
The study identifies nearly similar first aid practices as seen earlier with a treatment adherence more towards non-qualified HCWs. A qualitative study is recommended for in-depth understanding of such behavior before designing targeted interventions, policies, and educational campaigns.
Evaluating the Cost Utility and Budget Impact of Telehealth services: A Systematic Review and Meta-Analysis
Authors: S Aviraj K , Mohanty Manjeet , Gnanasekaran Sridevi , Pachori Ravi 
Published: September 2024

Abstract

Introduction:Telehealth, a rapidly advancing sector within the healthcare industry, has become a key tool in shaping policy decisions and the future of the healthcare delivery. However, the quality of evidence on telehealth's economic impact is somewhat limited, as many studies treat economic findings as secondary results rather than conducting thorough cost-utility or budget impact analyses. The lack of systematic and generalizable research on the routine use of telehealth limits understanding of its costs, benefits, and barriers to broader adoption.Methods:A systematic literature review was conducted, searching databases such as PubMed, Embase, and Cochrane Library for relevant systematic reviews from the past decade. The search terms used were a combination of keywords and Medical Subject Headings (MeSH) terms related to "telehealth," "cost-utility," "economic outcomes," "QALY" (Quality-Adjusted Life Year), "Incremental Cost-Effectiveness Ratio" (ICER), "cost-effectiveness," "cost-benefit," "cost-analysis," and "economic evaluation."Results:Based on inclusion and exclusion criteria, 24 studies were finally included in the analysis. The results suggest that telehealth interventions are generally cost-saving on a per-patient basis, but the total financial impact can be higher due to broader implementation or additional costs associated with scaling the intervention.Conclusion:Telehealth has great promise for bettering patient outcomes and the delivery of healthcare by facilitating access to treatment and relieving pressure on healthcare systems. However, considering both average and total costs in budget impact analyses is important, as cost savings at an individual level do not always translate into lower overall expenditures. Hence, any decision regarding its implementation should be taken keeping this in mind.