bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robot Calibration of Conveyor Chain Countspermeter: Advancing Precision in Industrial Production
Authors: Wang Yunfei 
Published: January 2025

Abstract

In modern industrial automated production, countspermeter parameter accuracy is crucial importance for conveyor chain. However, the current tape measure calibration method restricts accuracy. Industrial robots are used to calibrate in this study. Comparison between tape measure and robot calibration on five conveyor chains. The results show that accuracy is improved by robot calibrate, due to division value is only 1/1000 of tape measure. Although the improvement is only 0.7%, it is significant for conveyor chain. This study can enhance refined production management and quality control level for enterprises.
LncRNA HULC-miR-556-5p axis regulates cardiac microvascular endothelial cell function in chronic heart failure through the AMPK/FOXO3 pathway
Authors: Hao Yafeng , Fu Mingming , Wang Zhiqian 
Published: January 2025

Abstract

Purpose
This study aimed to investigate the regulatory mechanism of miR-556-5p in endothelial cell injury associated with heart failure and its impact on endothelial cell function.
Methods
Human cardiac microvascular endothelial cells (HCMECs) were utilized as the study model. The expression levels of miR-556-5p and related proteins were assessed using techniques such as real-time quantitative PCR and Western blot. Cell apoptosis detection, analysis of inflammatory cytokine release, cell viability assays, and immunoblotting were employed to evaluate cell function and physiological status.
Results
We observed a crucial role of miR-556-5p in Ang II-induced HCMEC injury. Upregulation of miR-556-5p significantly suppressed cell apoptosis and the release of inflammatory cytokines (such as TNF-α, IL-1β, and IL-6), while promoting cell survival. Further experimental results indicated that miR-556-5p regulated cell function by reducing the expression level of FOXO3 and possibly modulating the AMPK signaling pathway to affect the physiological status of endothelial cells. Additionally, miR-556-5p markedly decreased cellular autophagy levels, further supporting its regulatory role in endothelial cell injury associated with heart failure.
Conclusion
This study elucidates the important role of miR-556-5p in endothelial cell injury associated with heart failure, providing new insights into the pathophysiological mechanisms of heart failure.
Characterization and Performance Evaluation of Soybean (Glycine Max (L.) Merr.) Accessionsforagronomic Traits in Assosa Zone, Northwestern Ethiopia
Authors: Paulos Mesay , Atumo Tessema Tesfaye , Yada Gobeze Loha 
Published: January 2025

Abstract

A field experiment was conducted during 2023/24 cropping season at Dabus testing site of Asossa zone to characterize and evaluate soybean genotypes for useful traits. Twenty soybean accessions obtained from three geographic areas of Assosa and laid out in a randomized complete block design with three replications. Qualitative traits dominated were erect type, rounded leaf shape, white flower colour, yellow green testacolour, dense down hair colour, presence of hair and pubescence, dark leaf colour, large sized seed, medium green pod colour and spherical flattened seed shape. Results depicted the presence of sufficient variability among the genotypes for agronomic traits. Higher phenotypic and genotypic variance was observed for grain yield while relatively medium phenotypic variance for days to flowering and maturity, plant height and pods per plant. Branches per plant, pods per plant, seeds per pod and grain yield had higher PCV while a trait plant height exhibited moderate PCV. Genotypic coefficient variance was high for pods per plant and grain yield whereas plant height and seeds per pod showed moderate GCV. Days to flowering and maturity, plant height, pods per plant and seeds per pod had high heritability whereas relatively moderate H2 was recorded for HSW and grain yield. Plant height, pods per plant, seeds per pod and grain yield exhibited high GA. Significant genetic variability in mean performance of all the traits under studied material indicated that genotypes have considerable amount of genetic variation that could be used for further breeding program in variety development.
Dual-fiber optical tweezers integrating high-sensitivity structured-light displacement measurement system on fiber end-face
Authors: Li Guofeng , Xiong Wei , Feng Haining , Feng Zijian , Kuang Tengfang , Lu Zhechun , Han Xiang , He Xin , Chen Xinlin , Yang Junbo , Xiao Guangzong 
Published: January 2025

Abstract

The dual-fiber optical tweezers have become widespread in trapping, assembling, and sensing due to their simple fabrication process and flexible operation. However, the miniaturization and integration of their displacement measurement optical paths remain challenging. Here, we propose and experimentally demonstrate an integration of structured-light displacement (SLD) measurement method tailored for dual-fiber optical tweezers. A key component split-waveplate is integrated onto the fiber end via coating and etching in the SLD method. The etched fiber and another single mode fiber form an optical tweezers, which enables to trap particle and measure its position simultaneously without additional optics. More importantly, it demonstrates a superior signal-to-noise ratio after filtering out the trapping field by the etched fiber. Our results demonstrate a displacement sensitivity reaching the 0.1 pm/Hz1/2 level, which surpasses the performance of most results using the quadrant photodiode method. Ultimately, we discussed the possibilities of using two etched fibers to detect displacements in different directions, or integrating this method into a single optical fiber. This method has significant potential applications in precision sensing, contributes to the integration of optical tweezers and fosters the development of lab-on-fiber applications.
Real-World Data Analysis of Vascular and Lymphatic Adverse Events Associated with Anti-Tumor Angiogenesis Drugs: A WHO-VigiAccess Study
Authors: Zu Yue , Dai Lingling , Meng Peng 
Published: January 2025

Abstract

Pro-angiogenic factors play a crucial role in the treatment of malignant tumors, particularly in anti-angiogenic therapies. This study evaluated vascular and lymphatic adverse events (AEs) associated with four anti-tumor angiogenesis drugs in the WHO-VigiAccess database. It also compared the adverse drug reaction (ADR) profiles of these drugs to support personalized treatment decisions and optimize therapeutic benefits and safety. Methods:This study was designed as a descriptive retrospective analysis. Adverse reactions of four commonly used drugs for the clinical treatment of malignant tumors were reviewed using reports from the WHO-VigiAccess database. Data collected included demographic characteristics (age group, gender, and region), annual AE reports, and system organ class (SOC) data and symptoms associated with the reported adverse events. The overall characteristics of the ADR reports were examined, and the distribution of the 27 SOC categories was analyzed. The most common vascular and lymphatic AEs associated with these drugs were subsequently compared. Finally, similarities and differences in vascular and lymphatic AEs among the drugs were assessed. Results:A total of 130,801 adverse events (AEs) associated with four anti-VEGF drugs were identified. The analysis revealed that 42.91% of the AEs occurred in females, 36.14% in males, and 20.96% in cases where the gender was unspecified. The age group of 45–64 years had the highest reporting frequency. Nearly half of the AE reports originated from the Americas (49.43%). The ten most common types of AEs were: general disorders and administration site conditions (41.10%), gastrointestinal disorders (30.04%), eye disorders (23.02%), injuries, poisoning, and procedural complications (17.31%), investigations (16.80%), nervous system disorders (16.04%), infections and infestations (12.83%), blood and lymphatic system disorders (12.32%), respiratory, thoracic, and mediastinal disorders (11.85%), and vascular and lymphatic disorders (10.60%). Compared to the other three inhibitors, bevacizumab had a significantly higher reporting rate for vascular and lymphatic disorders. The most common vascular and lymphatic AEs associated with these four anti-VEGF drugs were hypertension, hemorrhage, hypotension, and deep vein thrombosis. However, differences in AE profiles were observed among the drugs. Conclusion:The occurrence of vascular and lymphatic adverse events associated with the clinical use of anti-angiogenic drugs for the treatment of malignant tumors warrants significant clinical attention. Clinicians should carefully evaluate the specific manifestations of these adverse events to optimize the rational use of these costly medications and develop personalized treatment plans tailored to individual patient needs.
Anston: An Attention Mechanism Network Model for Structured Data Classification
Authors: Zhou Feng , Hu Shijing , Du Xiaozheng , Lu Zhihui 
Published: January 2025

Abstract

To reduce the pressure on public health services caused by the aging population, nursing homes need to predict disease risks for the elderly periodically. To improve the disease risks predicting ability of nursing homes, we designed Anston (An Attention Mechanism Network Model for Structured Data Classification) in the application scenario of innovative elderly care. The Anston model can use the physiological indicators and pathogenic factors easily collected by nursing homes to predict disease risks. In the study of disease risk prediction based on physiological indicators and pathogenic factors for thoughtful elderly care, we designed a data enhancement method, a feature weight automatic update method, and a multi-layer perceptron neural network to solve the problems of sample shortage, inconsistent feature weights, and sample imbalance. At the same time, we designed an attention mechanism network model for structured data classification based on the multi-layer perceptron neural network developed in this paper. To fit the application scenario of competent elderly care, we propose a disease risk prediction model, Anston, based on the data enhancement method, feature automatic update method, and structured data classification attention mechanism network designed in this paper. We use public data sets and subject data as sample data in the experiment. The experimental results show that the Anston model has an accuracy of 95%, a precision of 92%, a recall of 91%, a specificity of 93%, an F1 score of 91%, and an AUC of 93% in predicting disease risks in the experiment, which have achieved the SOTA result.
Utilizing Machine Learning to Decode Growth Patterns and Yield Dynamics in Potato Cultivation
Authors: RATHER KHALID UL ISLAM 
Published: January 2025

Abstract

Understanding growth patterns and yield dynamics in potato cultivation is essential for optimizing agricultural practices and improving productivity. This study leverages machine-learning techniques to analyze and predict potato growth stages and yield outcomes based on environmental and physiological data. Various machine-learning models were developed using multispectral imaging, soil parameters, and climatic factors collected across diverse cultivation environments. The models were evaluated for their accuracy in identifying growth stages and forecasting yield performance. Key physiological trends were identified during the tuber initiation, bulking, and maturation phases, correlating with specific environmental conditions. Predictions for tuber yield showed high accuracy, with models achieving R² values above 0.90 across validation datasets. Additionally, the study highlights the importance of integrating machine learning with precision agriculture systems to enhance decision-making and resource management. The proposed methodology demonstrates significant potential for advancing potato-farming practices by providing actionable insights into growth and yield optimization.
Impact of surgical urgency on outcomes after coronary artery bypass surgery: A retrospective cohort study
Authors: Abdullah Hemn Abdulrahman , Saeed Darya Nadir , Ismael Sherzad Ali , Flayeh Abdullah Haider , Hussein Marwan Abdullah 
Published: January 2025

Abstract

Background: surgical urgency is a significant factor influencing outcomes of coronary artery bypass grafting. This study aims to assess the impact of urgency on postoperative complications and patient outcomes.
Methods: a retrospective cohort analysis was conducted. out of 205 patients, 38 patients were selected, who underwent coronary artery bypass graft at the Dr. Hemn foundation, Erbil, Iraq, from February 2021 to December 2023. Patients were divided equally into urgent and elective groups, matched for age, gender, chronic disease presence, and type of surgery.
Results: no significant difference was observed in age (p-value = 1.000), gender (p-value = 1.000), and body mass index (p-value = 0.748). the prevalence of posterior descending artery stenosis in the elective group was observed (p-value = 0.039). The urgent group experienced longer total hospital stay and intensive care unit. Postoperatively the urgent group experienced more blood loss compared to the elective group (p-value = 0.019) and had higher serum creatinine levels (p-value = 0.021).
Conclusions: urgent coronary artery bypass grafting was associated with increased postoperative challenges, particularly in terms of renal function, blood loss, and extended hospital stay.
Trial registration: retrospectively registered
Transfer Learning on Protein Language Models Improves Antimicrobial Peptide Classification
Authors: Georgoulis Elias , Zervou Michaela Areti , Pantazis Yannis 
Published: January 2025

Abstract

Antimicrobial peptides (AMPs) are essential components of the innate immune system in humans and other organisms, exhibiting potent activity against a broad spectrum of pathogens. Their potential therapeutic applications, particularly in combating antibiotic resistance, have rendered AMP classification a vital task in computational biology. However, the scarcity of labeled AMP sequences, coupled with the diversity and complexity of AMPs, poses significant challenges for the training of standalone AMP classifiers. Self-supervised learning has emerged as a powerful paradigm in addressing such challenges across various fields, leading to the development of Protein Language Models (PLMs). These models leverage vast amounts of unlabeled protein sequences to learn biologically relevant features, providing transferable protein sequence representations (embeddings), that can be fine-tuned for downstream tasks even with limited labeled data. This study evaluates the performance of several publicly-available PLMs in AMP classification utilizing transfer learning techniques and benchmarking them against state-of-the-art neural-based classifiers. Our key findings include: (a) Model scale is crucial, with classification performance consistently improving with increasing model size; (b) State-of-the-art results are achieved with minimal effort utilizing PLM embedding representations alongside shallow classifiers; and (c) Classification performance is further enhanced through efficient fine-tuning of PLMs’ parameters. Code showcasing our pipelines is available at https://github.com/EliasGeorg/PLM_AMP_Classification.
A Fault Diagnosis Method for Analog Circuits Based on VMD-CFOA-ELM
Authors: Ma Shuangbao , Shi Songjie , Wan Li , Zhang Yapeng , Zhang Guoqin 
Published: January 2025

Abstract

Fault feature extraction of analog circuits is the main factor affecting their fault diagnosis accuracy. Therefore, in order to increase the accuracy of analog circuit fault diagnosis, this paper proposes a fault diagnosis method for analog circuit based on VMD-CFOA-ELM and DGCCA(Deep Generalized Canonical Correlation Analysis,DGCCA). The method firstly performs VMD(Variational Mode Decomposition,VMD) on the fault time-domain response signal to obtain all the IMF (Intrinsic Mode Function,IMF) components and calculates the CMSE(Composite Multi-Scale Entropy,CMSE) of each IMF component, treating this as a separate subset of fault features. Next, it extracts the time-frequency domain characteristic features of the fault response signal and uses the DGCCA algorithm for supervised feature fusion extraction, constructing a shared representation feature matrix G, which is spliced with the subset of fault features as the input features of the classifier. Finally, the CFOA(Catch Fish Optimization Algorithm, CFOA)algorithm is relied upon to optimize the ELM (Extreme Learning Machine,ELM) classifier to have good classification accuracy to diagnose the type of faults in the test circuits. Fault simulation diagnostics on a Sallen-Key bandpass filter circuit show that, compared to methods such as KPCA-ELM, KSLPP-ELM, EEMD multi-scale entropy-LSSVM, and WP-ICA energy spectrum-SVM, the proposed method achieves the highest accuracy, reaching 99.20%. Additionally, this method is portable and applicable to fault diagnosis of other analog circuits.
The association between the ZJU index and bone mineral density (BMD) among patients with type 2 diabetes mellitus
Authors: Zhang Yuan , Chen Guanhua , Jing Yali 
Published: January 2025

Abstract

Background
Previous studies have suggested that type 2 diabetes mellitus (T2DM) is associated with poor bone health, including osteoporosis (OP) and osteopenia. The ZJU index, a novel calculation that integrates fasting plasma glucose (FPG), body mass index (BMI), triglyceride (TG), and alanine aminotransferase (ALT) to aspartate aminotransferase (AST) ratio, is strongly associated with glucolipid metabolism and insulin resistance (IR). In this study, we explored the association of ZJU with bone mineral density (BMD) and OP/osteopenia, and investigated the predictive effect of ZJU on OP/osteopenia in patients with T2DM.
Methods
This cross-sectional study included 496 patients with T2DM aged > 50 years. The clinical data were collected and the BMD of femoral neck (FN), left hip (LH), and lumbar spine (LS) were measured. The association between BMDs and ZJU levels was investigated by adjusting for covariates utilizing multiple linear regression analyses. Multivariable logistic regression was constructed to identify independent factors of OP and osteopenia, and receiver operating characteristic (ROC) curves were used to display the diagnostic performance according to the area under the ROC curve (AUC).
Results
OP and osteopenia patients showed significantly higher ZJU levels than those with normal BMD in T2DM (39.387 ± 3.558, 38.112 ± 2.552 vs 35.192 ± 2.600, p < 0.001). Spearman’s correlation analysis showed that ZJU was significantly negatively correlated with the BMD of FN (r = -0.39, p < 0.001), LH (r = -0.35, p < 0.001), and LS (r = -0.32, p < 0.001). The multiple linear regression indicated a negative association between ZJU and BMD of FN (β = -0.006, p = 0.009), LS (β = -0.155, p = 0.011) after adjusted for covariates. Meanwhile, the results of logistic regression revealed that the ZJU was a contributing factor to osteopenia and OP risk in T2DM individuals aged > 50 years (OR 1.446, 95% CI: 1.087 ~ 1.923, p = 0.011; OR 1.878, 95% CI: 1.218 ~ 3.715, p = 0.039, respectively). ZJU provided the AUC value of 0.695 and 0.716 on osteopenia and OP in T2DM, respectively.
Conclusions
A high ZJU index was significantly associated with an increasing risk of osteopenia and OP. The ZJU is expected to be a potential index for detecting decreased BMDs in middle-aged and elderly T2DM patients. Early intervention in T2DM patients with increased ZJU may further reduce the incidence of osteopenia and OP, in addition to focusing on independent biomarker in clinical practice.
Molecular sexing of chick embryos by LAMP and RPA assays: a step toward in ovo egg sexing
Authors: Hofstadt Marc Van Der , l’Helgoualch Nicolas , Houot-Cernettig Juliette , Galindo Thérèse , Martins Priscila , Huguenin Joris , Manso Taciana , Espeut Julien , Molina Franck , VAN Thi Nhu Ngoc 
Published: January 2025

Abstract

Despite of global efforts, reducing the culling of one-day hatched male chicks in the poultry industry has been a critical priority due to significant socio-economic concerns. Indeed, various molecular assays have been developed to determine the sex of eggs before hatching (in ovo) to eliminate male embryos at early developmental stages. Because of their precision-related complexity, needs for advanced infrastructures and time-consuming processes, there is still no widespread commercialization for these assays. In this study, we developed two novel digital readouts assays employing PCR, LAMP and RPA techniques whose sensitivity, specificity and robustness were validated on 82 chick embryos at day 9. Our data demonstrate that, while the two novel PCR based assays correctly and robustly sex the 82 embryos, the LAMP and RPA based assays propose comparable results. Moreover, LAMP and RPA assays propose isothermal amplification associated with naked-eye colorimetric and/or fluorescent detection in a relatively shorter time (20 minutes at 65°C and 30 min at 37°C, respectively). These newly developed assays, not only significantly reduce the complexity of experimental setting but also being faster and more affordable sexing methods, addressing key barriers to in ovo sexing to a future commercialization of a non-invasive in ovo sexing assay.
Distinct effects of mucin on phage-host interactions in model systems of beneficial and pathogenic bacteria
Authors: Lazar Jaka Jakin , Šimunović Katarina , Dogša Iztok , Mulec Ines Mandić , Middelboe Mathias , Dragos Anna 
Published: January 2025

Abstract

Phage-host interactions that occur in host-associated microbiomes are influenced by a plethora of environmental factors. Mucins are glycoproteins representing the largest proportion of mucus, found in the animal digestive tract and on the surface of certain organs, serving as the first line of defense against toxins and pathogens. Previous studies have shown that lytic phages have an important influence on the microbial composition in mucosal areas. Our study expands this knowledge to interactions between previously untested lytic phages targeting probiotic and pathogenic bacteria, as well as temperate phages targeting probiotic bacteria. These interactions could be important in shaping the microbial communities and host well-being. This study demonstrates that mucins enhance the adherence of Vibrio anguillarum lytic phages and Bacillus subtilis lytic and temperate phages, as well as B. subtilis and V. anguillarum cells to solid surfaces. Our results also show that mucins positively affect the attachment of B. subtilis cells even in the presence of phages. At the same time, this positive effect was not observed in the case of V. anguillarum. This suggests that mucin may shield certain bacteria from phage infections. Our findings also demonstrate that mucin differently influences metabolic activity of the two tested bacterial species, with strong positive effects on V. anguillarum. but not on B. subtilis. The work supports previous findings that phages efficiently adhere to mucus (Barr et al., 2013), extending them to include new beneficial and pathogenic bacterial species. It also reveals that mucins have different effects on phage-host interactions in different phage-host systems, which may have implications for phage therapies or probiotic treatment strategies.