bluuebunny/crossref_metadata_2025_split huggingface dataset:
MyoV: a deep learning-based tool for the automated quantification of muscle fibers
Authors: Gu Shuang , Wen Chaoliang , Xiao Zhen , Huang Qiang , Jiang Zheyi , Liu Honghong , Gao Jia , Li Junying , Sun Congjiao , Yang Ning 
Published: January 2024

Abstract
Accurate approaches for quantifying muscle fibers are essential in biomedical research and meat production. In this study, we address the limitations of existing approaches for hematoxylin and eosin-stained muscle fibers by manually and semiautomatically labeling over 660 000 muscle fibers to create a large dataset. Subsequently, an automated image segmentation and quantification tool named MyoV is designed using mask regions with convolutional neural networks and a residual network and feature pyramid network as the backbone network. This design enables the tool to allow muscle fiber processing with different sizes and ages. MyoV, which achieves impressive detection rates of 0.93–0.96 and precision levels of 0.91–0.97, exhibits a superior performance in quantification, surpassing both manual methods and commonly employed algorithms and software, particularly for whole slide images (WSIs). Moreover, MyoV is proven as a powerful and suitable tool for various species with different muscle development, including mice, which are a crucial model for muscle disease diagnosis, and agricultural animals, which are a significant meat source for humans. Finally, we integrate this tool into visualization software with functions, such as segmentation, area determination and automatic labeling, allowing seamless processing for over 400 000 muscle fibers within a WSI, eliminating the model adjustment and providing researchers with an easy-to-use visual interface to browse functional options and realize muscle fiber quantification from WSIs.
Multi-scale topology and position feature learning and relationship-aware graph reasoning for prediction of drug-related microbes
Authors: Xuan Ping , Gu Jing , Cui Hui , Wang Shuai , Toshiya Nakaguchi , Liu Cheng , Zhang Tiangang 
Published: January 2024

Abstract

Motivation
The human microbiome may impact the effectiveness of drugs by modulating their activities and toxicities. Predicting candidate microbes for drugs can facilitate the exploration of the therapeutic effects of drugs. Most recent methods concentrate on constructing of the prediction models based on graph reasoning. They fail to sufficiently exploit the topology and position information, the heterogeneity of multiple types of nodes and connections, and the long-distance correlations among nodes in microbe–drug heterogeneous graph.

Results
We propose a new microbe–drug association prediction model, NGMDA, to encode the position and topological features of microbe (drug) nodes, and fuse the different types of features from neighbors and the whole heterogeneous graph. First, we formulate the position and topology features of microbe (drug) nodes by t-step random walks, and the features reveal the topological neighborhoods at multiple scales and the position of each node. Second, as the features of nodes are high-dimensional and sparse, we designed an embedding enhancement strategy based on supervised fully connected autoencoders to form the embeddings with representative features and the more discriminative node distributions. Third, we propose an adaptive neighbor feature fusion module, which fuses features of neighbors by the constructed position- and topology-sensitive heterogeneous graph neural networks. A novel self-attention mechanism is developed to estimate the importance of the position and topology of each neighbor to a target node. Finally, a heterogeneous graph feature fusion module is constructed to learn the long-distance correlations among the nodes in the whole heterogeneous graph by a relationship-aware graph transformer. Relationship-aware graph transformer contains the strategy for encoding the connection relationship types among the nodes, which is helpful for integrating the diverse semantics of these connections. The extensive comparison experimental results demonstrate NGMDA’s superior performance over five state-of-the-art prediction methods. The ablation experiment shows the contributions of the multi-scale topology and position feature learning, the embedding enhancement strategy, the neighbor feature fusion, and the heterogeneous graph feature fusion. Case studies over three drugs further indicate that NGMDA has ability in discovering the potential drug-related microbes.

Availability and implementation
Source codes and Supplementary Material are available at https://github.com/pingxuan-hlju/NGMDA.
MAGE: metafounders-assisted genomic estimation of breeding value, a novel additive-dominance single-step model in crossbreeding systems
Authors: Zhuo Yue , Du Heng , Diao ChenGuang , Li WeiNing , Zhou Lei , Jiang Li , Jiang JiCai , Liu JianFeng 
Published: January 2024

Abstract

Motivation
Utilizing both purebred and crossbred data in animal genetics is widely recognized as an optimal strategy for enhancing the predictive accuracy of breeding values. Practically, the different genetic background among several purebred populations and their crossbred offspring populations limits the application of traditional prediction methods. Several studies endeavor to predict the crossbred performance via the partial relationship, which divides the data into distinct sub-populations based on the common genetic background, such as one single purebred population and its corresponding crossbred descendant. However, this strategy makes prediction inaccurate due to ignoring half of the parental information of crossbreed animals. Furthermore, dominance effects, although playing a significant role in crossbreeding systems, cannot be modeled under such a prediction model.

Results
To overcome this weakness, we developed a novel multi-breed single-step model using metafounders to assess ancestral relationships across diverse breeds under a unified framework. We proposed to use multi-breed dominance combined relationship matrices to model additive and dominance effects simultaneously. Our method provides a straightforward way to evaluate the heterosis of crossbreeds and the breeding values of purebred parents efficiently and accurately. We performed simulation and real data analyses to verify the potential of our proposed method. Our proposed model improved prediction accuracy under all scenarios considered compared to commonly used methods.

Availability and implementation
The software for implementing our method is available at https://github.com/CAU-TeamLiuJF/MAGE.
LRRC52 is likely a functional component of human KSper
Authors: Zhang Jiali , Zheng Liping , Chen Ying , Luo Tao , Zeng Xuhui , Kang Hang 
Published: January 2024

Abstract
Completion of fertilization is orchestrated by various ion channels in sperm membrane. Hyperpolarization of membrane potential, an indispensable event during the capacitation process, is dominated by sperm potassium channel (KSper). In addition to sperm-specific SLO3, which forms the channel pore, the auxiliary subunit leucine-rich-repeat-containing protein 52 (LRRC52) is required to form mKSper to function under physiological conditions. However, in human sperm, although most evidence supports that hSLO3 is the pore-forming subunit, whether hLRRC52 contributes to hKSper conductance and modulates sperm function remains to be understood. Here, using an extracellular segment that is homologous between mice and humans as an antigen, we developed a polyclonal antibody designed as LID1 that specifically detected mLRRC52 and performed co-immunoprecipitation with mSLO3. Additionally, patch-clamp recordings of mouse sperm showed that, physiological activation of mKSper and sperm functions were dramatically attenuated after treatment with LID1, indicating that LID1 functionally disrupted the regulation of mLRRC52 on mKSper. Next, LID1 was used to investigate the significance of hLRRC52 for hKSper activation. As a result, hLRRC52 was expressed in human sperm and might be assembled with hSLO3. More importantly, LID1 inhibited hKSper currents and depolarized sperm membrane potential, supporting essential modulation of hLRRC52 in hKSper. Ca2+ signaling of human sperm was also compromised in the presence of LID1, which impaired sperm motility and acrosome reaction. Because LID1 specifically inhibited both mKSper and hKSper but not mCatSper or hCatSper, our results suggest that hLRRC52 functions as an important component of hKSper and regulates sperm physiological functions.
Role of miRNAs in glucose metabolism of mouse cumulus cells
Authors: Ma Rui-Jie , Zhang Min , Wu Jia-Shun , Wang Zhi-Peng , Wang Guo-Liang , He Nan , Luo Ming-Jiu , Tan Jing-He 
Published: January 2024

Abstract
It is known that the oocyte has a limited capacity to acquire and metabolize glucose, and it must rely on cumulus cells (CCs) to take up glucose and produce pyruvate for use to produce ATP through oxidative phosphorylation. We therefore propose that miRNAs might regulate glucose metabolism (GM) in CCs and might be used as markers for oocyte quality assessment. Here, mouse CC models with impaired glycolysis or pentose phosphate pathway (PPP) were established, and miRNAs targeting the key enzymes in glycolysis/PPP were predicted using the miRNA target prediction databases. Expression of the predicted miRNAs was compared between CCs with normal and impaired glycolysis/PPP to identify candidate miRNAs. Function of the candidate miRNAs was validated by transfecting CCs or cumulus-oocyte-complexes (COCs) with miRNA inhibitors and observing effects on glucose metabolites of CCs and on competence of oocytes. The results validated that miR-23b-3p, let-7b-5p, 34b-5p and 145a-5p inhibited glycolysis, and miR-24-3p, 3078-3p,183-5p and 7001-5p inhibited PPP of CCs. Our observation using a more physiologically relevant model (intact cultured COCs) further validated the four glycolysis-targeting miRNAs we identified. Furthermore, miR-let-7b-5p, 34b-5p and 145a-5p may also inhibit PPP, as they decreased the production of glucose-6-phosphate. In conclusion, miRNAs play critical roles in GM of CCs and may be used as markers for oocyte quality assessment.
Summary sentence:
We identified and validated eight new miRNAs that inhibit glycolysis and/or pentose phosphate pathways in cumulus cells (CCs) suggesting that miRNAs play critical roles in glucose metabolism of CCs and may be used for oocyte quality markers.
Radiomics-clinical nomogram for preoperative lymph node metastasis prediction in esophageal carcinoma
Authors: Geng Xiaotao , Zhang Yaping , Li Yang , Cai Yuanyuan , Liu Jie , Geng Tianxiang , Meng Xiangdi , Hao Furong 
Published: January 2024

Abstract

Objectives
This research aimed to develop a radiomics-clinical nomogram based on enhanced thin-section CT radiomics and clinical features for the purpose of predicting the presence or absence of metastasis in lymph nodes among patients with resectable esophageal squamous cell carcinoma (ESCC).

Methods
This study examined the data of 256 patients with ESCC, including 140 cases with lymph node metastasis. Clinical information was gathered for each case, and radiomics features were derived from thin-section contrast-enhanced CT with the help of a 3D slicer. To validate risk factors that are independent of the clinical and radiomics models, least absolute shrinkage and selection operator logistic regression analysis was used. A nomogram pattern was constructed based on the radiomics features and clinical characteristics. The receiver operating characteristic curve and Brier Score were used to evaluate the model's discriminatory ability, the calibration plot to evaluate the model's calibration, and the decision curve analysis to evaluate the model’s clinical utility. The confusion matrix was used to evaluate the applicability of the model. To evaluate the efficacy of the model, 1000 rounds of 5-fold cross-validation were conducted.

Results
The clinical model identified esophageal wall thickness and clinical T (cT) stage as independent risk factors, whereas the radiomics pattern was built based on 4 radiomics features chosen at random. Area under the curve (AUC) values of 0.684 and 0.701 are observed for the radiomics approach and clinical model, respectively. The AUC of nomogram combining radiomics and clinical features was 0.711. The calibration plot showed good agreement between the incidence of lymph node metastasis predicted by the nomogram and the actual probability of occurrence. The nomogram model displayed acceptable levels of performance. After 1000 rounds of 5-fold cross-validation, the AUC and Brier score had median values of 0.702 (IQR: 0.65, 7.49) and 0.21 (IQR: 0.20, 0.23), respectively. High-risk patients (risk point &gt;110) were found to have an increased risk of lymph node metastasis [odds ratio (OR) = 5.15, 95% CI, 2.95-8.99] based on the risk categorization.

Conclusion
A successful preoperative prediction performance for metastasis to the lymph nodes among patients with ESCC was demonstrated by the nomogram that incorporated CT radiomics, wall thickness, and cT stage.

Advances in knowledge
This study demonstrates a novel radiomics-clinical nomogram for lymph node metastasis prediction in ESCC, which helps physicians determine lymph node status preoperatively.
Service implications of the revised 2022 National Institute for Health and Care Excellence (NICE) follow-up guidelines for stage IA–IIC melanoma
Authors: Dobbs Thomas D , Jovic Mathew , Ekakkaravichit Nattawan , Ali Stephen R , Gibson John A G , Ibrahim Nader , Hemington-Gorse Sarah , Whitaker Iain S 
Published: January 2024

Abstract

Background
The 2022 National Institute for Health and Care Excellence melanoma guideline update made significant changes to follow-up. The aim of this study was to assess the impact these changes will have on a national melanoma cohort over a 5-year follow-up interval.

Methods
Anonymized, individual-level, population-scale, linkable primary and secondary care National Health Service data for an 18-year interval (2000–2018) in Wales, UK were analysed. These data were used to predict the number of patients over a 10-year interval (2020–2030) that would be diagnosed with melanoma. Follow-up schedules for the 2015 and 2022 National Institute for Health and Care Excellence melanoma guidelines were then used to calculate the number of clinician-led appointments, the number of radiological investigations, and the total healthcare cost between 2025 and 2030, corresponding to a 5-year patient follow-up interval, for those with stage IA–IIC melanoma.

Results
Between 2025 and 2030 it is predicted that implementation of the 2022 guidelines would lead to 21 122 (range 19 194–23 083) fewer clinician-led appointments for patients with stage IA–IIC melanoma. However, there would be a significant increase in the number of radiological investigations (7812; range 7444–8189). These changes would lead to a €2.74 million (€1.87 million–€3.61 million) reduction in the total cost of follow-up over the interval 2025–2030.

Conclusion
Melanoma follow-up guideline changes will result in a substantial reduction in the number of clinical follow-up appointments, but a significant additional burden to radiological services. The overall cost of follow-up at a national level will be reduced.
Addressing Longevity Inequality: How Retirement Age Differentiation Can Be Implemented
Authors: Jensen Svend E Hougaard , Sveinsson Thorsteinn Sigurdur , Zoega Gylfi 
Published: January 2024

Abstract
Differences in life expectancy across socioeconomic groups create a serious problem of inequality within the public part of the pension system. This article considers two actuarially sound ways of addressing longevity inequality. The first is to allow low life-expectancy workers to retire earlier and delay the retirement of the high life-expectancy workers so that the two groups receive the same amount, equal to the expected discounted value of future pension benefits received by the average worker under the current system. The second, and more radical, is to delegate to occupational pension funds the task of paying out the public pension benefits to each retiree, based on a lump-sum transfer from the government to the pension funds of an amount for each retiree equivalent to the payout in the first scenario. (JEL codes: E21 and E24)
The Leaders in Epidemiology, Antimicrobial Stewardship, and Public Health (LEAP) Fellowship, a Novel Training Program in Public Health for Infectious Diseases Physicians
Authors: Hsueh Kevin , Teherani Arianne , Guzman-Cottrill Judith A 
Published: January 2024

Abstract
The severe acute respiratory syndrome coronavirus 2 pandemic demonstrated a critical need for partnerships between practicing infectious diseases (ID) physicians and public health departments. The soon-to-launch combined ID and Epidemic Intelligence Service fellowship can only address a fraction of this need, and otherwise US ID training lacks development pathways for physicians aiming to make careers working with public health departments. The Leaders in Epidemiology, Antimicrobial Stewardship, and Public Health (LEAP) fellowship is a model compatible with the current training paradigm with a proven track record of developing careers of long-term collaboration. Established in 2017 by the ID Society of America, Society for Healthcare Epidemiology of America, Pediatric ID Society, and supported by the Centers for Disease Control and Prevention, LEAP is a single-year in-place, structured training for senior trainees and early career ID physicians. In this viewpoint, we describe the LEAP fellowship, its outcomes, and how it could be adapted into ID training.
Success of the US Veterans Health Administration's Hepatitis C Virus Care Continuum in the Direct-acting Antiviral Era
Authors: Varley Cara D , Lowy Elliott , Cartwright Emily J , Morgan Timothy R , Ross David B , Rozenberg-Ben-Dror Karine , Beste Lauren A , Maier Marissa M 
Published: January 2024

Abstract

Background
Estimated hepatitis C prevalence within the Veterans Health Administration is higher than the general population and is a risk factor for advanced liver disease and subsequent complications. We describe the hepatitis C care continuum within the Veterans Health Administration 1 January 2014 to 31 December 2022.

Methods
We included individuals in Veterans Health Administration care 2021–2022 who were eligible for direct-acting antiviral treatment 1 January 2014 to 31 December 2022. We evaluated the proportion of Veterans who progressed through each step of the hepatitis C care continuum, and identified factors associated with initiating direct-acting antivirals, achieving sustained virologic response, and repeat hepatitis C viremia.

Results
We identified 133 732 Veterans with hepatitis C viremia. Hepatitis C treatment was initiated in 107 134 (80.1%), with sustained virologic response achieved in 98 136 (91.6%). In those who achieved sustained virologic response, 1097 (1.1%) had repeat viremia and 579 (52.8%) were retreated for hepatitis C. Veterans of younger ages were less likely to initiate treatment and achieve sustained virologic response, and more likely to have repeat viremia. Stimulant use and unstable housing were negatively associated with each step of the hepatitis C care continuum.

Conclusions
The Veterans Health Administration has treated 80% of Veterans with hepatitis C in care 2021–2022 and achieved sustained virologic response in more than 90% of those treated. Repeat viremia is rare and is associated with younger age, unstable housing, opioid use, and stimulant use. Ongoing efforts are needed to reach younger Veterans, and Veterans with unstable housing or substance use disorders.
Left-behind places in central and eastern Europe—labour productivity aspect
Authors: Dobrzanski Pawel , Bobowski Sebastian , Clare Karenjit 
Published: January 2024

Abstract
In the 21st century, there have already been a series of economic downturns, particularly the Subprime Crisis 2007–2009 and the Covid-19 pandemic in 2020. All those events triggered changes in productivity, economic performance and structure. The main objective of this study is to identify the regions left behind in the Central and Eastern European (CEE) countries and to analyse the structural and productivity changes taking place within them. In our analysis, we aim to verify the research hypothesis that all left-behind regions in CEE have similar economic structures with a high share of agriculture. The research period covers the years from 2010 until 2020 using data from the Eurostat database. In the first phase of our analysis, we analysed employment, Gross Value Added (GVA) and productivity data for 11 CEE countries. Then, we analysed the Nomenclature of Territorial Units for Statistics at level 3 (NUTS3) regions, and Poland, which is a NUTS2 region. Left-behind regions are defined as those with low productivity and low growth rates. We provide a detailed analysis of the best and worst performing regions in terms of productivity for each country using productivity data and shift-share decomposition of productivity growth rate. Left-behind regions for each CEE country have been identified, and these are BG333, BG342, CZ080, EE004, HR023, HU332, LT027, LV005, PL72, RO216, RO312, SI032, SI035, SI038 and SK032. In our analysis, our hypothesis analysing the relationship between agriculture share in total employment and the productivity level of the region was not confirmed.
Microangiopathy associated with poor outcome of immunoglobulin A nephropathy: a cohort study and meta-analysis
Authors: Dong Lei , Hu Yuncan , Yang Dan , Liu Liu , Li Yueqiang , Ge Shuwang , Yao Ying 
Published: January 2024

ABSTRACT

Background
Microangiopathy (MA) lesions are not rare in immunoglobulin A nephropathy (IgAN) and have been suggested to have a potential role in increasing risk in renal function decline. However, this suggestion has not been universally accepted. We aimed to investigate its role in our cohort and in multiple studies through a systematic meta-analysis.

Methods
This cohort study included 450 IgAN patients, confirmed by renal biopsy, at Tongji Hospital, China, from January 2012 to December 2016. Clinical data were collected and analysed. We systematically searched PubMed and Web of Science for studies investigating the association between MA lesions and IgAN.

Results
In our cohort, IgAN patients with MA were significantly older and had higher blood pressure, more proteinuria, worse kidney function and increased uric acid levels compared with patients without MA. When comparing pathological features with the non-MA group, the MA group exhibited more global glomerulosclerosis and interstitial fibrosis/tubular atrophy. MA lesions were independently associated with a composite kidney outcome in IgAN patients {adjusted hazard ratio 2.115 [95% confidence interval (CI) 1.035–4.320], P = .040}. Furthermore, this relationship was validated in a meta-analysis involving 2098 individuals from five independent cohorts. The combined data showed a 187% adjusted risk of poor renal outcome in IgAN patients with MA compared with patients without MA [adjusted risk ratio 2.87 (95% CI 2.05–4.02; I2 = 53%).

Conclusion
MA lesions could serve as a valuable predictor for disease progression in patients with IgAN, extending beyond the widely recognized Oxford MEST-C score.