bluuebunny/crossref_metadata_2025 huggingface dataset:
Grey Frequency-Based Methodology for Assessing HeLa Cell Damage
Authors: Li Anqi , Zhao Linying , Liu Changyu , Xu Xiaolong , Jia Jianbo
Published: October 2024

Cell biology techniques offer a solid foundation for evaluating and forecasting the danger of pollutants in the investigations of environmental toxicology. Studies on ecological toxicity, medication development, and illness diagnosis depend on evaluating cellular damage. The morphology of stimulated cells can alter the light scattering and reflection, and the brightness of microscopic images of the cells. This study demonstrated that stimulation-damaged and normal cells had distinct grey value distributions which led to the proposal of a novel theory to measure cellular damage by image brightness. Additionally, an evaluation technique based on grey frequency analysis can be created to determine the extent of cellular damage. This approach provides an effective and helpful tool for cellular damage visualization and quantitative evaluation in environmental toxicity assessment.
Inhibition and Kinetic Studies on Purified Peroxidase from Rhizome of Turmeric (Curcuma Longa L)
Authors: Adedugbe Omowumi Funke , Ilesanmi Olutosin Samuel , Olagunju Victory Ayo , Kolawole Ayodele O.
Published: October 2024

The kinetics, inhibition studies and the interactions of inhibitors and substrates with purified peroxidase from rhizomes of turmeric (Curcuma longa) (ClP) through molecular docking was described. This was with the view to providing information on the catalytic mechanism of the enzyme with substrate and inhibitors for various applications. The crude enzyme was purified in single step purification using aqueous two-phase partitioning system (ATPS). Real kinetic studies on the purified enzyme showed linear patterns with intersection on the x-axis in the third quadrant suggesting sequential ordered bi bi mechanism of substrate addition to the peroxidase. The real kinetic constants − Kmcatechol and KmH2O2 estimated from the secondary replots for the purified peroxidase from turmeric were 168 ± 2.0 mM and 87.4 ± 1.2 mM respectively. The Vmax obtained for the purified enzyme was 68,965 ± 50 units/mg protein. These led to first-order rate constant, kcat/Km of 0.49 × 106 M− 1 s− 1. All the inhibitors had inhibitory effect on the activity of ClP at varying concentrations. The inhibition constant (Ki) values for the inhibitors at increasing order are 0.4 mM for cysteine, 4.9 mM for ascorbic acid, 5 mM for citric acid and 9 mM for EDTA. Cysteine was the most potent inhibitor. From the docking simulation, the calculated docking score of the binding energy for ascorbic acid, citric acid, cysteine and EDTA were − 8.988, -4.147, -3.361 and − 2.206 kcal/mol respectively. The lower binding energy value of the inhibitor represents the higher affinity to the receptor protein. The binding interaction of the purified enzyme showed that ascorbic acid, citric acid and EDTA have 2 hydrogen bonds formed respectively while cysteine had 4 hydrogen bonds. The combination of kinetic and inhibition properties makes the enzyme a successful candidate to be employed for various applications in industrial and biotechnological processes.
Global trends and focuses of Integrins in Colorectal Cancer: a bibliometric analysis and visualization from 2007 to 2023
Authors: Yin Wen , Xiao Lijun , Zhang Chao , Zhang Xu , Wen Chengli , Li Hao , Yu Yuan , Yu Zehui , Lü Muhan
Published: October 2024

Colorectal cancer is one of the most common tumors of the digestive system; however, current treatment methods still have certain limitations. In recent years, researchers have found that integrins play a crucial role in colorectal cancer, making them a hot topic in research. To gain a better understanding of the current status and trends of integrins in colorectal cancer research, this study conducted a bibliometric analysis for the first time to assess the development of integrin-related research in colorectal cancer. The study selected the core dataset from the Web of Science database and included relevant research on integrins and colorectal cancer published between 2007 and 2023. The CiteSpace, VoSviewer, and Bibliometrix R packages were utilized for analyzing the aspects of country/region, authors, institutions, journals, references, and keywords. The analysis revealed steady growth in research on integrins and colorectal cancer over the past 16 years, with a total of 1,339 articles published by 61 countries. Among them, China has the highest number of publications, followed by the United States. The most frequently cited journal is Cancer Research, followed by the Journal of Biological Chemistry and Oncogene. In conclusion, bibliometric analysis provided a comprehensive visualization of the current status and trends in research on integrins in colorectal cancer. These analytical results not only offer valuable insights for researchers but also provide useful information for decision-makers in the scientific and medical communities. This, in turn, can facilitate the improvement and development of treatment methods for colorectal cancer.
Public views on genetics and genetic testing of sudden unexplained death: A survey of the public in China
Authors: Qi Ming , Hong Xutao , Chen Xiaoling , He Yanbin , Wang Jinyuan , Huang Jian , Xu Xiaoyan , Zhang Jungeng , Dong Shuangyong , Wang JianGang
Published: October 2024

This study investigated public attitudes towards genetic testing for sudden cardiac death (SCD) in China, particularly in the context of increasing cardiovascular disease incidence and the potential benefits of genetic testing for prevention and treatment. We conducted a telephone follow-ups targeted 199 out-of-hospital cardiac arrest (OHCA) cases in Hangzhou, and a public survey included 536 respondents from various demographic groups, including emergency volunteers, housewives, IT practitioners, Cardiovascular patients' relatives, and drivers. The telephone follow-up revealed a low participation rate in genetic testing among survivors and victims' immediate relatives. The public survey indicated a general lack of awareness and knowledge about genetics and genetic testing for SCD. Significant differences in attitudes were observed based on demographic factors such as age, health insurance, and occupations. Many respondents expressed concerns about the implications of genetic testing and a general distrust in medical recommendations. The study highlights the urgent need for enhanced public education on the importance of genetic testing for SCD and the development of more effective communication strategies to address public concerns. Increasing awareness and understanding of the benefits of genetic testing could improve acceptance and participation, ultimately aiding in the prevention and management of SCD in China.
Total Darkness Activated Intestinal Clock System and Improved Intestinal Barrier Function in Growing Rabbits
Authors: Li Yao , Chen Jiali , Li Fuchang , Liu Lei
Published: October 2024

The aim of study was to investigate the effects of dark environment on production performance, intestinal barrier function and clock-related gene expression in rabbits. Forty weaned rabbits with similar body weight (35-day-old) were randomly divided into 2 treatments (20 replicates per treatment, 1 rabbit per replicate: normal light group (12 L and 12 D) or total dark group (24 D). The experimental period lasted for 10 days, with an adaptation period of 3 days and a subsequent formal experimental period of 7 days. The results showed that feed-to-weight ratio of rabbits in total dark group was significantly decreased compared with normal light group (P<0.05). Dark treatment significantly increased gene expression of claudin-1, mucin1 in duodenum, occludin-1, claudin-1, zona occludens 1 (ZO1), junctional adhesion molecule 2 (JAM2) and interleukin 10 (IL10) in jejunum, claudin-1, mucin1, ZO1 and IL10 in ileum and clock, melatonin 1A, melatonin 1B, and period1 in cecum compared with normal light group (P<0.05). Total dark treatment increased alpha diversity via increasing chao1 index, observed species index and faith_pd index of cecal flora. Total dark treatment significantly reduced percentage of Deferobacterium at phylum level in cecum, but significantly increased percentage of Rumenococci at genus level (P<0.05). There is an increasing tendency of acetic acid and propionic acid content of soft feces in total dark group (0.05<P<0.1). In conclusion, total dark treatment improves feed conversion efficiency in rabbits and activates cecum clock system, which increased diversity of bacterial flora and production of short-chain fatty acids, then increases intestinal barrier function.
Mitochondrial Dysfunction and Programmed Cell Death in Allergic Rhinitis: Potential Biomarkers and Therapeutic Targets
Authors: Xie Yong , Liang Meiying , Fang Meiqing , Ling Tao , Kong Hui
Published: October 2024

Background
Allergic rhinitis (AR) is a prevalent chronic inflammatory disease, and its pathological mechanisms have not been fully elucidated. This study aims to identify potential biomarkers of AR and explore its role in disease development through integrated bioinformatics analysis.
Methods
We downloaded GSE75011 and GSE46171 datasets from public database to screen out differentially expressed genes (DEGs) between AR patients and control samples. Using MitoCarta 3.0 and literature appendices, we identified mitochondria-associated genes (MitoRGs) and programmed cell death-related genes (PCDRGs). Using Spearman correlation analysis, we screened out DE MitoRGs-PCDRGs with significant correlations. Further, we constructed a protein-protein interaction (PPI) network using the search tool for the retrieval of interacting genes/proteins (STRING) database and visualized it by Cytoscape software. Using machine learning algorithms, we identified biomarkers of AR from candidate genes. In addition, we analyzed the biological functions and signaling pathways of these biomarkers by Gene Set Enrichment Analysis (GSEA), and assessed the infiltration of immune cells by immunoinfiltration analysis.
Results
We identified a total of 50 AR-associated DE MitoRGs-PCDRGs that were strongly associated with apoptosis. Through machine learning algorithms, we identified HPDL, PLEKHF1, PFKFB3, and TNFAIP3 as potential biomarkers for AR. The distribution of these biomarkers on chromosomes and the strong correlation between them suggested that they might play a synergistic role in the pathogenesis of AR. GSEA analysis reveals the potential role of these biomarkers in immune response and cell signaling. Immunoinfiltration analysis revealed significant differences in immune cells between AR and normal control (NC) samples, which were closely related to the expression levels of biomarkers.
Conclusion
This study reveals potential biomarkers of AR through comprehensive analysis and explores their possible mechanisms in disease development. These findings provide new perspectives for the diagnosis and treatment of AR and lay the foundation for future research and clinical applications.
Body shape, fat distribution and sarcopenia and risk of liver cancer in European population: a Mendelian randomization study
Authors: Liu Yong-Cai , He Chiyu , Zhang Peiru , Hu Zhihang , Lin Zuyuan , Chen Jinyan , Shen Wei , Chen Hao , Li Huigang , Yang Xinyu , Zhuo Jianyong , Wei Xuyong , Zhuang Li , Xu Xiao , Zheng Shusen , Lu Di
Published: October 2024

Background
Body shape, fat and muscle are likely associated with risk of liver cancer. Evidence for the impact of these factor is limited and controversial. Because conventional observational studies cannot sidestep the effect of confounding and reverse causality, it remains unclear whether there is a causal relationship of body shape, composition and its distribution with risk of liver cancer.
Methods
In this study, a two-sample Mendelian randomization (MR) approach was applied to evaluate the potential causal association of 17 risk factors of body shape, fat distribution and sarcopenia with risk of liver cancer in European population. Summary genetic association estimates for 17 exposures and liver cancer were obtained from MRCIEU GWAS database.
Results
MR analysis indicated that genetically predicted body mass index (BMI) and waist-to-hip ratio (WHR) were associated with liver cancer risk [OR: 1.0005, P = 0.037; OR: 1.0014, P = 0.004, respectively]. Whole body fat mass, trunk fat mass, arm fat mass and leg fat mass were associated with liver cancer risk, while the corresponding fat-free mass were not associated with liver cancer risk. Genetically determined sarcopenia was not associated with liver cancer risk, as either. There did not suggest evidence of potential heterogeneity or directional pleiotropy.
Conclusion
Our study found genetically predicted BMI, WHR and fat mass were associated with liver cancer risk, and the positive association between fat mass and liver cancer risk did not change with changes in fat distribution. However, fat-free mass and sarcopenia associated factors were not associated with liver cancer risk.
Enhancing Situational Awareness with LoRa Mesh Networks: Communication in Internet-Deprived Areas
Authors: Hakani Raj , Mishra Aditya , Shah Naman , Rawat Abhishek
Published: October 2024

This paper focuses on the implementation of Meshtastic firmware, showcasing its effectiveness in establishing a decentralized mesh network for communication and location tracking in areas where internet connectivity is unreliable. A thorough analysis of the system's features, including real-time device tracking and secure messaging, highlights its significant potential for military and surveillance applications in remote or off-grid settings. The decentralized mesh framework enhances resilience in dynamic environments, providing a versatile communication solution where conventional infrastructure is lacking or compromised. The experiments successfully demonstrate the real-world application of LoRa communication technology in urban settings, achieving dependable communication between sender and receiver boards over distances of up to 2 kilometers, even in the presence of potential urban interference. Additionally, this research highlights security protocols and ethical considerations relevant to the deployment of Meshtastic firmware in military and surveillance scenarios, offering insightful guidance for future studies and practical implementations.
Factors Associated with Early Infant Survival During the first three months of life in Uganda: A Multilevel Weibull Model Approach
Authors: Prisca Nakawuki , Wandiembe Symon , Atuhaire Leonard , Nsimbe Dick , Tumusiime Sula
Published: October 2024

Background
The burden of early infant mortality is enormous. It directly contributes to under-five mortality and indirectly affects maternal and child health outcomes. Globally, over 8.2 million children under the age of 5 die each year, with more than 40% of these deaths occurring within the first 30 days of life. In sub-Saharan Africa alone, 1.2 million newborns die annually, with the highest risk of death occurring within the first three months of life. The aim of this paper is to investigate the factors associated with the survival of children within the first three months of life in Uganda.
Method
Self-reported data were extracted from the 2016 Uganda Demographic and Health Survey (UDHS), comprising a sub-sample of 10,263 children. The analysis employed a time-to-event approach, utilizing Kaplan-Meier survival curves and a multilevel proportional hazard.
Results
The multi-level Weibull distribution showed that the estimated frailty variance was 0.065, indicating heterogeneity of time to death of children within the first 3 months of life across the different enumeration areas in Uganda. The significant factors found to influence time to death of children within the first three months of life in Uganda included female gender of children (HR = 0.732, 95% CI = 0.57–0.94, p = 0.013), residing in eastern region (HR = 0.520, 95%CI = 0.35–0.79, p = 0.002), children whose mothers received the recommended dose of tetanus injection prior to birth (HR = 0.503, 95%CI = 0.34–0.74, p = 0.001), those whose mothers participated in postnatal check-ups (HR = 0.363, 95% CI = 0.24–0.55, p = 0.000) and survival rates and children with low birth size (HR = 2.216, 95%CI = 0.86–1.62, p = 0.000).
Conclusions
Survival within the first three months of life in Uganda is significantly influenced by child sex, geographical region, contraceptive use, tetanus vaccination, postnatal check-ups, and birth size. These findings highlight the need for targeted interventions that promote maternal health and improve infant outcomes. Strengthening family planning programs, increasing access to and awareness of postnatal care, and ensuring adequate maternal nutrition are essential strategies for improving infant survival. Additionally, health education campaigns encouraging timely medical care before, during, and after childbirth are critical for reducing early infant mortality rates.
Machine Learning Models to Develop Land Suitability Map for Coffee Cultivation by Integrating CHIRPS and SRTM DEM
Authors: Sinchana G. S. , Choodarathnakara A . L . , Arpitha G. A.
Published: October 2024

Kodagu region is a major coffee exporter, with production concentrated in three taluks, including the Somwarpet Taluk. Coffee yields have decreased due to unfavorable factors such as climate change, disease and insect outbreaks, landslides and inadequate land-use planning in turn affecting the family income. Thus, the goal of this research is to identify suitable land for cultivation of coffee based on Food and Agriculture Organization (FAO) land suitability assessment methodology for Somwarpet Taluk of Kodagu District. For this purpose, six soil chemical properties (potential of hydrogen, electrical conductivity, organic carbon, sulphur, iron, potassium and nitrogen), two topographic data (elevation and slope) and one climatic condition (rainfall) was considered to map land suitability for coffee crops. After determining land suitability classes for coffee cultivation, the study area was then mapped using machine learning (ML) methods such as random forest (RF), Naive Bayes (NB), K-Nearest Neigbhor (KNN), Extreme Gradient Boosting Tree (XgBoost) and Decision Tree (DT). The prediction of land suitability classes by ML model showed a significant variation. For example, in case of RF model, results showed the 94% of higher accuracy when compared to the XgBoost (93.5), DT (92%), NB (75%) and KNN (50%) models.
The area of S1 (highly suitable) classified through RF, XgBoost, DT, NB
and KNN was 8.66%, 8.75%, 8.57%, 19.17% and 28% respectively. Similarly, the S2 (moderately suitable) class area via RF, XgBoost, DT, NB and KNN was 84.17%, 82.18%, 81.33 %, 69.61% and 44%, respectively. Conversely, the area of S3 (marginally suitable) classified through RF, XgBoost, DT, NB and KNN was 6.64%, 7.64%, 8.5%, 10.52% and 27.8%. Correspondingly, the N (unsuitable) class area via RF outperformed the land suitability class for XgBoost, DT, NB and KNN by 0.53%, 1.43%, 1.6%, 0.7% and 0.2%. The
sulphur and pH were the major limiting factor affecting the land suitability to map coffee cultivation. Thus, the methodologies developed in this study area can be very useful tool to ensure food security and carry out an effective assessment of land suitability in coffee crop growth and production for Somwarpet Taluk of Kodagu District, Karnataka State.
The effect of repetitive transcranial magnetic stimulation of the cerebellum on cognitive control
Authors: Qu Liangcheng , So Bo , Shi Jingping , Yin Kuiying
Published: October 2024

Background Research on brain interventions utilizing transcranial magnetic stimulation (TMS) technology has advanced significantly, however, studies focusing on the transcranial magnetic stimulation of the cerebellum remain in their preliminary phase. Research in neuroscience has established the cerebellum as a critical component in cognitive control, decision-making, and response regulation.;Methods The present study focused on the Curs II subregion of the cerebellum and involved 125 participants, who were categorized into five distinct groups. Each group received repetitive transcranial magnetic stimulation (rTMS) at frequencies of 1 Hz, 5 Hz, 10 Hz, 20 Hz, as well as a sham stimulation. Participants were evaluated through a go/no-go task both prior to and following the stimulation, while their electroencephalogram (EEG) were concurrently recorded for subsequent analysis.;Results The results indicate that cerebellar transcranial magnetic stimulation has a significant impact on cognitive task performance throughout the brain. High-frequency stimulation at 5 Hz, 10 Hz, and 20 Hz appears to activate neurons in brain regions linked to cognitive functions, leading to an increase in event-related potential (ERP) peaks and enhancements in the global efficiency and clustering coefficient of the overall brain network. Among the high-frequency conditions, stimulation at 10 Hz produced the most pronounced improvement in cognitive task performance and significantly enhanced the global efficiency of brain networks In contrast, low-frequency stimulation at 1 Hz was found to suppress cognitive task performance..;Conclusions TMS of the cerebellum can either enhance or inhibit cognitive control functions, suggesting that the cerebellum plays a significant role in the participation and regulation of cognitive control.
Predicting stochastic distribution characteristics of high- speed train dynamic performance over a service cycle
Authors: Xue Bowen , Tao Zhecheng , Yang Zhenhuan , Huang Caihong , Gao Xu , Wang Yong , Ye Yunguang
Published: October 2024

The wheel-rail interface parameters and suspension parameters of high-speed trains exhibit stochastic distribution characteristics due to the influence of material properties, manufacturing processes, and operational environments, which have a significant impact on vehicle dynamic performance. However, existing simulation methods for dynamic performance prediction often fail to fully account for these stochastic characteristics, affecting both the reliability and practical value of the predictions. To address this limitation, this study first develops a polynomial regression model based on measured wheel wear data to correct conventional wear prediction results. Next, using Latin hypercube sampling (LHS), Monte Carlo (MC) simulations, and Kullback-Leibler (KL) divergence, a method is proposed to predict the stochastic distribution of dynamic performance over a wheel reprofiling cycle. Finally, by analyzing the stochastic combinations of wheel-rail interface geometry, wheel-rail friction coefficient, and suspension parameters, stochastic predictions of dynamic performance are obtained. The results show that after considering the stochastic characteristics of the wheel-rail interface and suspension system, the dynamic performance indicators follow a normal distribution. Moreover, compared to a model that only considers the stochastic nature of the wheel profile, the uncertainties in the lateral Sperling index and bogie lateral acceleration increase significantly. For the high-speed train analyzed in this study, the probability of the lateral Sperling index exceeding 2.5 rises from 0.4% at 50,000 km to 14% at 250,000 km, while the probability of lateral bogie acceleration exceeding 5 m/s² increases from 0–37.6%. Additionally, the probability of exceeding the instability threshold of 8 m/s² reaches 0.8% at 250,000 km, reflecting the increased risk of exceeding safety limits after extended service. This study offers a novel approach to assessing operational risks and improving the accuracy of dynamic performance predictions for high-speed trains under complex operating conditions.
Simultaneous evaluation of sensitivity and side effects of anti-cancer drugs using patient- derived cancer organoids and a microfluidic device
Authors: Kobayashi Yuki , Hashizume Honoka , Takiguchi Sotaro , Jiajue Ji , Kawano Ryuji , Koiwai Keiichiro , Yamamoto Haru , Elbadawy Mohamed , Omatsu Tsutomu , Abugomaa Amira , Kaneda Masahiro , Usui Tatsuya , Sasaki Kazuaki
Published: October 2024

Organoids are stem cell-derived three-dimensional tissue cultures composed of multiple cell types that recapitulate the morphology and functions of their in vivo counterparts. Organ-on-a-chip devices are tiny chips with interconnected wells and channels designed using a perfusion system and microfluidics to precisely mimic the in vivo physiology and mechanical forces experienced by cells in the body. These techniques have recently been used to reproduce the structure and function of organs in vitro and are expected to be promising alternatives for animal experiments in the future. In the present study, we designed and fabricated an organ-on-a-chip system for mounting organoids from mammary tumor-affected cats (FMT organoids) and normal intestinal organoids from mice (MI organoids) and perfused them with anti-cancer drugs. The effects of drug perfusion on FMT and MI organoids were examined by measuring cell viability and performing genetic analysis. After 48 h of perfusion with toceranib (10 µM) or doxorubicin (1 µM), cell viability of FMT organoids was decreased compared to the non-perfusion condition. The expression of apoptosis-related genes, such as p53 and Caspase-9 was significantly upregulated in FMT organoids with drug perfusion. The rate of cell death drastically differed before and after branching in the device, owing to differences in flow velocity and drug infiltration. Perfusion of MI organoids with toceranib also reduced viability, as observed in FMT organoids; however, this was due to the induction of necrosis rather than apoptosis. In conclusion, our established multi-organoid-on-chip system could be used to evaluate anti-cancer drug sensitivity and side effects in vitro, which might contribute to the development of personalized medicine for cancer patients.
A comparative study on the influencing factors and risk prediction models for stroke- associated pneumonia in patients with acute ischemic stroke and atrial fibrillation
Authors: Su Tai , Zhang Peng , Zhang Bingyin , Liu Zihao , Xie Zexing , Xin Tao , Ma Jixiang , Li xiaomei
Published: October 2024

Background
To analyze the factors influencing stroke-associated pneumonia (SAP) in patients with acute ischemic stroke (AIS) and atrial fibrillation (AF), and to explore an optimal model for risk prediction.
Methods
Data were sourced from the Shandong Provincial Center for Disease Control and Prevention, encompassing all patients diagnosed with AIS and AF from 2020 to 2023. First, univariate analysis and LASSO (Least absolute shrinkage and selection operator) regression analysis methods were used to screen predictors. Secondly, the patients with AIS and AF were randomly divided into a training set, validation set, and test set in a ratio of 7:2:1, which were utilized for model training, model parameter adjustment, and model performance evaluation, respectively. The training set was balanced by synthetic minority oversampling technique (SMOTE), logistic regression, random forest (RF), and support vector machine (SVM),extreme gradient boosting (XGboost) models were constructed. Finally, we compared the models based on accuracy, sensitivity, specificity, AUC (area under the curve), and Youden index. We clarified the optimal prediction model and influencing factors ,the nomogram for risk prediction was constructed for SAP in patients with AIS and AF.
Results
Among the 4496 patients with AIS and AF, SAP was identified in 10.16% of cases. In the test set, the AUC for logistic regression, RF, SVM, and XGboost models were 0.866, 0.817, 0.816, and 0.838, respectively. The most predictive factors included coronary heart disease [OR = 1.05 (1.03, 1.07), p < 0.001], hypertension [OR = 1.05 (1.04, 1.07), p < 0.001], consciousness disorder [OR = 1.19 (1.16–1.23), p < 0.001], cognitive impairment [OR = 1.10 (1.08–1.13), p < 0.001], limb movement disorder [OR = 1.07 (1.04–1.09), p < 0.001], dysphagia [OR = 1.13 (1.08–1.19), p < 0.001], nasal feeding [OR = 0.95 (0.92–0.98), p = 0.003], and oxygen intake [OR = 0.65 (0.62–0.67), p < 0.001]. the nomogram average absolute error of calibration curve was 0.014.
Conclusions
Coronary artery disease, hypertension, consciousness disorder, cognitive impairment, limb movement disorder, and dysphagia were identified as independent risk factors for SAP in patients with AIS and AF. In contrast, nasal feeding and oxygen intake served as independent protective factors. The logistic regression model demonstrated the best predictive performance for SAP in patients with AIS and AF compared to RF, SVM, and XGboost models. The risk prediction model established by nomogram can better predict the risk of SAP.
A comparison of the survival outcome of paclitaxel liposome-based chemoradiotherapy with or without rhEndostatin for unresectable esophageal squamous cell carcinoma: a retrospective study
Authors: Pan Xiaofen , Zhu Mengyuan , Wei Min , Huang Shan , Xu Junjie , Li Qun
Published: October 2024

Objectives
. This study aimed to compare the survival outcomes of paclitaxel liposome-based chemoradiotherapy, with or without rhEndostatin, in patients with unresectable locally advanced esophageal squamous cell carcinoma (ESCC).
Methods.
Patients with ESCC treated with paclitaxel liposome-based definitive chemoradiotherapy (dCRT), with or without rhEndostatin, between February 2015 and June 2020 were included. Patients received induction chemotherapy followed by concurrent radiochemotherapy, with or without rhEndostatin. The chemotherapy regimen consisted of paclitaxel liposome-based treatments. RhEndostatin was administered at a dose of 30 mg/d from day 1 to day 5 of each chemotherapy cycle. Total radiotherapy dose was 66–68 Gy, delivered in fractions of 2.0-2.2 Gy/d. Follow-up continued until December 2023. The primary endpoints were 3-year progression-free survival (PFS) and 3-year overall survival (OS). Secondary endpoints included objective response rate (ORR), disease control rate (DCR), and toxicity.
Results
A total of 80 patients were included, with 34 in the dCRT group and 46 in the E + dCRT group. The 3-year PFS was 26.47% (95% confidence interval [CI], 13.19–41.81) in the dCRT group and 56.29% (95% CI, 40.79–69.20) in the E + dCRT group (Hazard ratio (HR), 0.50; 95% CI, 0.28–0.89, P = 0.012). Patients in the E + dCRT group had a superior 3-year OS compared to those in the dCRT group (80.44% [95% CI, 65.77–89.30] vs. 47.06% [95% CI, 29.83–62.52]; HR, 0.40; 95% CI, 0.21–0.72; P = 0.003). The ORR was 91.18% in the dCRT group and 95.65% in the E + dCRT group. The most common grade 3–4 toxicities were leukopenia, neutropenia, and thrombocytopenia.
Conclusion
The addition of rhEndostatin to paclitaxel liposome-based dCRT may improve clinical outcomes for patients with unresectable ESCC while maintaining manageable toxicities. However, further prospective randomized controlled studies are necessary to confirm the survival benefits of this treatment strategy.
Enhancing brain image segmentation: A metaheuristic approach to multi-threshold optimization
Authors: Ramirez Fernando , Flores Emilio , Olivares Rodrigo
Published: October 2024

Brain segmentation is vital for the accurate diagnosis and treatment of neurological disorders, given the complexity and vulnerability of the brain to various pathologies such as strokes and tumors. The challenge lies in achieving precise delineation of anatomical and pathological structures within medical images, particularly under varying conditions of image quality and tissue irregularities. To address this, we applied eight metaheuristic optimization algorithms-Reptile Search Algorithm, Orca Predator Algorithm, Bald Eagle Search, Grey Wolf Optimizer, Honey Badger Algorithm, Crow Search Algorithm, Harris Hawk Optimization, and Tuna Swarm Optimization-to improve the accuracy of multi-threshold segmentation methods like Kapur’s entropy, Tsallis entropy, and the Otsu method. The results reveal that the Grey Wolf Optimizer and Tuna Swarm Optimization stand out, with the Grey Wolf Optimizer demonstrating superior performance across key metrics such as Peak Signal to Noise Ratio and Structural Similarity Index. These outcomes highlight the potential of the Grey Wolf Optimizer for advanced brain tissue segmentation, offering significant advantages in clinical and research environments where precision is essential for effective medical intervention.
The association between night eating syndrome and food preferences among Chinese college students: a large-scale cross-sectional study
Authors: Hao Zi xuan , Jing Qi , Zhao Bo yang , Ren Zhong yu
Published: October 2024

Background and aims:
Although the associations between NES and food preferences and the frequency of consumption of three meals a day have been examined among the European population, no studies have yet explored this association specifically among Chinese college students. Therefore, the purpose of this study was to investigate the associations between NES and food preferences and the frequency of consumption of three meals a day in Chinese college students.
Methods
This study used a cross-sectional design and included a sample of 11,856 Chinese university students, with an average age of 18.8 years (SD = 1.2 years). Food preferences were defined as five different food categories: fruits, vegetables, fast food (e.g. pizza, burgers, etc.), snacks (e.g. potato chips, crisps) and sugary beverages (e.g. soft drinks and sugary fruit drinks) and breakfast, lunch and dinner. The participants were invited to express their preferences for five food categories using a 5-point Likert scale, with the anchors "dislike very much" and "like very much". The frequency of consumption of three meals a day (including breakfast, lunch and dinner) was evaluated using a frequency scale ranging from 1 (once) to 7 (7 days per week). To evaluate the presence of Nocturnal Eating Syndrome (NES), we employed the Nocturnal Eating Questionnaire (NEQ) and the following criteria: no NES (total score < 25), mild NES (total score 25–30), and severe NES (total score > 30). Multivariate logistic regression analyses were used to examined the association between the level of NES and each food preference and the frequency of consumption of three meals a day.
Results
After controlling for potential confounding variables including gender, age, annual household income, place of residence, father's education and mother's education, multivariate logistic regression analyses observed a significant positive association between NES and the likelihood of exhibiting 1–6 food behaviors. We further found that, in addition to the fast food and dinner, there were significant positive associations between NES and remained food preferences (including, fruit, vegetable, snack and soft drinks) and two meals (including breakfast and lunch).
Conclusion
The results of this study suggest a strong positive association between NES and food preferences, and meal regularity. This implies that individuals with severe NES may exhibit poor food preferences and irregular meal habits. These findings emphasize the importance of intervening in NES, a condition that can assist individuals to modify their food preferences selection and adopt the habit of three meals a day. Future studies should employ longitudinal prospective or randomized controlled designs to confirm the above associations.
Label-free morphology-based phenotypic analysis of spinal and bulbar muscular atrophy muscle cell models
Authors: Sakakibara Kenji , Tanaka Kenjiro , Imai Yuta , Okada Mai , Iida Madoka , Sahashi Kentaro , Hirunagi Tomoki , Maeda Kentaro , Kato Ryuji , Katsuno Masahisa
Published: October 2024

Background
Spinal and bulbar muscular atrophy (SBMA) is a neuromuscular disorder caused by a CAG trinucleotide expansion in the androgen receptor (AR) gene. The pathogenesis of SBMA is not fully understood and there are less effective treatments for SBMA. To improve the quality of in vitro cell-based assays for the evaluation of potential drug candidates for SBMA, we aimed to develop a morphology-based phenotypic analysis for a muscle cell model of SBMA that involves multiparametric morphological profiling to quantitatively assess the therapeutic effects of drugs on muscle cell phenotypes.
Methods
We applied morphology-based phenotypic analysis to a muscle cell model of SBMA. The analysis was validated using dihydrotestosterone (DHT) and pioglitazone (PG), which have been shown to exacerbate and ameliorate the pathophysiology of SBMA, respectively. We then performed gene expression analysis to identify disease-associated pathways. We selected five compounds as potential candidates capable of modulating the disease state of SBMA and compared the morphological profiles using principal component analysis (PCA) and hierarchical clustering.
Results
The quantified morphological phenotypes of SBMA model cells treated with DHT or PG accurately reflected the exacerbation or amelioration of cell pathology. The results of gene expression analysis revealed that the JNK pathway was activated in the SBMA cells compared to the control cells. Phenotypic analysis revealed the effect of naratriptan (NRT), a JNK inhibitor, on the phenotypic changes of SBMA cells, and the results were confirmed by lactate dehydrogenase (LDH) assays. We then trained a predictive machine learning model to classify the drug responses, and it successfully discriminated between PG-type and NRT-type morphological profiles based on their morphological characteristics.
Conclusions
We developed a noninvasive and efficient in vitro drug screening technique using morphology-based phenotypic analysis and SBMA model C2C12 cells. Phenotypic analysis revealed that NRT rescued the morphological phenotype and exerted therapeutic effects via the JNK signaling pathway. Furthermore, the 'drug effect prediction model' was able to distinguish the different morphological changes caused by each drug. Our analysis will accelerate the development of the therapeutics for SBMA.
A new sampling strategy for estimating stand volumes with portable Lidar data
Authors: Wang Ximin , Xu Yanli , Guo Peiqi , Wang Shaobin
Published: October 2024

Accuracy estimation of forest stand volume with stem taper function is an important subject in the field of forestry study. For decreasing the time-intensive and labor-cost fieldwork in traditional forest science, how to select an optimal sampling strategy to precisely estimate stand volume is a focusing question for forest scientists. To deal with forementioned challenges and ensure the precision and reliability of stand volume estimation, we utilized portable Lidar data from 50 conifers to extract the accurate trunk models to build accuracy estimation models of stand volumes with two sampling strategies (the uniform sampling of trunk(UST), the segmented uniform sampling of trunk delineated by breast height diameter (SUST)) and two integration methods (the cumulative summation model(CMM), the Gauss-Legendre numerical integral model(GNIM)),and these were compared with results of stem taper functions and stand volume models constructed with field-measured data.The results showed that: (1) There was no discernible difference between the measured trunk lumber volume and the estimation results of lumber volume in the whole-trunk uniform segmentation and the cumulative accumulation of upper and lower trunk segments bounded by the diameter at breast height (DBH) when the trunk segments were 8 and 6, respectively. (2)when trunks were divided into 8 segments with the UST strategy and 6 segments with the SUST strategy, the fitting accuracies of the corresponding stem taper functions were 0.9512 and 0.9637. Furthermore, by stem taper function and the GNIM method, the estimation accuracies of stand volumes were 0.9137 and 0.9360, respectively. Additionally,the analysis of variance and confidence intervals indicated that two models of estimating stand volume,based on two sampling strategies, demonstrated reliability and consistency. (3)given that the number of trunk segments was smaller and the accuracy of stand volume estimation was higher, the SUST strategy was optimal for those. The strategy can also provide an important reference for forestry research and timber consumption.
The Dynamic Influence of Uncertainty on Sector Equity Funds: A Time-Frequency Analysis of Oil, Gold, and Market Volatility
Authors: Khan Shahzaib , Khan Umair
Published: October 2024

This research employs a time-frequency approach to explore the interrelations among US sector equity ETFs, oil, gold, the overall stock market, and various uncertainty indicators across different time horizons from 2019 to 2023. It utilizes a frequency-dependent spillover index and strategies for portfolio hedging to construct its findings. The analysis reveals that the market's anticipation of volatility in the US stock market for the next 30 days, as measured by the VIX, significantly influences US sector equity ETFs over both short and long durations. This influence is succeeded by expectations of oil price volatility, denoted by OVX. Among the indicators of uncertainty, the impact of US economic policy uncertainty on sector ETFs is found to be minimal. Comparatively, oil exhibits a more pronounced impact on sector ETFs than gold, across both observed time frames. The interactions among sector ETFs, gold, oil, and the uncertainty measures display a non-uniform nature, being more pronounced in the short term and intensifying during periods of financial distress and economic instability. From a portfolio hedging perspective, oil emerges as a superior hedge against sector ETF volatility in both the immediate and extended terms, with the Consumer Staples ETF showing the greatest hedging efficiency.
The Role of PPP2R2B in Pancreatic Cancer Progression: A Novel Pro-Cancer Factor
Authors: Han Fangfang , Chen Zhou , Ye Cheng , Dong Chunlu , Du Yan , Shi Huaqing , Xin Pengfei , Zhou Wence
Published: October 2024

Pancreatic cancer (PC) is one of the most lethal types of cancer, as current treatments are largely ineffective. Our research uncovers that PPP2R2B is overexpressed in a majority of PC cases, playing a significant role in the growth and spread of PC tumors. Further analysis showed that reducing PPP2R2B levels in PC inactivates the MAPK pathways—ERK, JNK, and p38—impacting epithelial-mesenchymal transition (EMT) and apoptosis processes, ultimately promoting PC growth. Our experiments in live subjects demonstrate that removing PPP2R2B inhibits tumor growth in PC mouse models and alters the levels of proteins involved in EMT and cell death. Thus, our work highlights the crucial role of PPP2R2B as a new factor that promotes cancer progression by influencing EMT and cell death through the MAPK pathway in pancreatic cancer.
Vibration-treated water alter metabolic activity of mouse peritoneal macrophages and RAW 264.7 cells
Authors: Sherstoboev Evgenii Yu. , Danilets Marina G. , Ligacheva Anastasia A. , Trofimova Evgenia S. , Selivanova Natalia S.
Published: October 2024

Background: It has recently been shown that by sequential vibrational processing (named 'crossing') of two closely located test tubes with the initial substance in one of them and water or lactose in the other, it is possible to obtain artificial material objects, or vibrational iterations. Iterations reproduce some properties of the initial substance and, in some cases, are capable of exerting a modifying effect on the original substance or its target, on the basis of which they are classified into several groups (fractions). Since water is the environment in which metabolic processes occur in cells, organs, and tissues, vibrational iterations of water can potentially affect their course.
Methods: In this work, we assessed the effect of two different fractions of vibrational iterations of water on the metabolic activity of peritoneal macrophages of C57BL/6 mice and macrophage-like tumor cells of the RAW 264.7 line.
Results: It was shown that the "Native" fraction of the vibrational iteration of water increased the metabolic activity of peritoneal macrophages and suppressed the metabolic activity of tumor cells. At the same time, the "Active" fraction did not influence the metabolic activity of peritoneal macrophages but decreased the metabolic activity of tumor cells.
Conclusions: Probably, taking into account the modifying activity of vibrational iterations, their action is aimed at changing the properties (possibly, structuring) of intracellular water. The results obtained by us show the possibility of a fundamentally new differentiated effect on the metabolic activity of healthy and tumor cells, which opens up new prospects for antitumor therapy.
Mendelian randomization and pharmacovigilance analyses reveal the causal relationship between antidiabetic drugs and psychiatric disorders
Authors: Dong Wenjie , He Long , Tu Kun , Li Qiuyu , Yang Xuping , Huang Yilan
Published: October 2024

Background
Several studies have reported that antidiabetic drugs are associated with psychiatric disorders, but whether they have a causal relationship is unclear. The aim of this study was to explore the causal relationship between antidiabetic drugs and psychiatric disorders using two-sample Mendelian randomization (MR).
Methods
In this study, we used a two-sample Mendelian randomization approach to analyse the causal relationship between antidiabetic drugs and eight psychiatric disorders. The summary data for both exposure and outcomes were obtained from the Integrative Epidemiology Unit (IEU) online database. Inverse-variance-weighted (IVW) and wald ratio were used as the main analysis methods. Heterogeneity, horizontal pleiotropy test and leave-one-out method were used as sensitivity analyses. And finally we had a pharmacovigilance analysis.
Results
IVW method showed that sulfonylureas may be causally associated with the following three psychiatric disorders: bipolar disorder (OR = 2.55, 95% CI: 1.27–5.13, P = 0.008), anorexia nervosa (OR = 10.71, 95% CI: 1.20-95.54, P = 0.03), attention deficit hyperactivity disorder (ADHD) (OR = 5.21, 95% CI: 1.47–18.49, P = 0.01). Sulfonylureas pharmacovigilance analyses have also identified some signals of adverse effects in psychiatric disorders.
Conclusion
This study found some psychiatric adverse effects of sulfonylureas but more clinical trials and animal studies are needed to confirm this.
The Impact of COVID-19 and Policy Changes on Telehealth Consultations for Mental Health Treatment in Australia: An Interrupted Time Series Analysis
Authors: Olaleye Abiola Olukayode , Kabir Enamul , KHANAM RASHEDA
Published: October 2024

Background Mental health care is a major component of the services offered in Australia. Rapid adaptations in healthcare delivery occurred worldwide, with telehealth emerging as a pivotal solution due to the impact of COVID-19 pandemic. The Australian health care environment was also transformed by policy changes in March 2020 which expanded telehealth services, significantly impacting mental health care.Objectives This study examined the effects of the COVID-19 pandemic and subsequent telehealth policy changes on telehealth consultations for mental health treatment in Australia. by general practitioners (GPs) in Australia.Methods An Interrupted Time Series (ITS) analysis was employed using data from March 2017 to February 2023. The study analysed the impact of the pandemic and telehealth policies across three periods: immediate impact (March 2020 - February 2021), recovery (March 2021 - February 2022), and post-pandemic (March 2022 - February 2023), focusing on in-person, phone, and video consultations.Results The introduction of telehealth services mitigated the decline in in-person consultations caused by the pandemic. While in-person consultations showed a significant immediate reduction, telehealth consultations increased, maintaining overall mental health service levels. However, the long-term trend in total GP consultations significantly changed post-intervention (2022 March to 2023 February).Conclusions Telehealth effectively ensured continued access to mental health services during the pandemic. Despite the immediate benefits, telehealth did not significantly alter long-term consultation patterns. Further integration of telehealth into routine care requires addressing technological, infrastructural, and policy barriers to sustain its usage beyond the pandemic.