bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mobile Spatial Statistics Key to Enhancing Healthcare Planning in Futaba County with Complex Population Flows after the Great East Japan Earthquake
Authors: Higuchi Asaka , Yoshimura Hiroki , Saito Hiroaki , Abe Toshiki , Murakami Michio , Zhao Tianchen , Amir Isamu , Ito Naomi , Yamamoto Chika , Nonaka Saori , Sawano Toyoaki , Shimada Yuki , Ozaki Akihiko , Oikawa Tomoyoshi , Tsubokura Masaharu 
Published: May 2024

Abstract

After the Great East Japan Earthquake, planning the appropriate allocation of healthcare resources is crucial. However, accurately estimating the medical care demand was challenging due to the substantial population fluctuations caused by extensive evacuations. This study employs mobile spatial statistics using NTT DoCoMo’s mobile phone data to conduct a detailed temporal and spatial population estimation (PE) in Futaba County from 2019 to 2020. Originally a complete evacuation zone, the area saw a partially lifted evacuation order. The suitability of the estimated population data for calculating emergency transport (ET) rates was also examined. Our findings reveal that day-to-night population ratios were significantly high in some areas; in Okuma Town and Futaba Town, the daytime population was substantially larger than the nighttime population throughout the two years, with the median day/night population ratio being more than three for both weekdays and weekends. Additionally, sex-age-adjusted ET rates in the study area, based on the estimated population, were more consistent with the national average than those calculated based on census data. This study demonstrates the critical role of PE considering temporal changes in enhancing healthcare planning and ensuring that resources are efficiently allocated to meet the evolving needs of communities during recovery periods.
The association between triglyceride-glucose index and its combination with obesity indicators and stroke: CHARLS 2011-2020
Authors: LIANG Weicai , OUYANG Haichun 
Published: May 2024

Abstract

Background
In the Chinese population, limited research has been conducted on the association between the triglyceride-glucose (TyG) index and its combination with obesity indicators in relation to stroke and its mortality.
Methods
This study enrolled a total of 8,207 participants from the China Health and Retirement Longitudinal Study (CHARLS) 2011–2020. Cox proportional hazards model, restricted cubic spline (RCS) and receiver operating characteristic (ROC) analysis were employed to examine the association between the triglyceride-glucose (TyG) index and its combined obesity-related indicators with stroke and its mortality. Mediation analysis was conducted to explore the mutual potential mediating role of TyG and obesity indicators in the above relationships.
Results
In this study, TyG, TyG-BMI, TyG-WHtR, and TyG-WC were significantly and positively associated with stroke and its mortality. Restricted cubic spline models revealed nonlinear associations between TyG and TyG-BMI with stroke risk, while TyG-WC and TyG-WHtR demonstrated linear associations with stroke mortality after adjusting for relevant covariates. TyG-WHtR, TyG-BMI and TyG-WC had more robust diagnostic efficacy than TyG for risk of stroke. TyG-WHtR or TyG-WC had the highest diagnostic efficacy for stroke and its mortality (AUC:0. 696, 95% CI 0.677–0.715), slightly higher than the other indicators. Associations between TyG, TyG-WC, TyG-WHtR, and TyG-BMI with stroke were found to be stronger among individuals who were ≥ 55 years of age, male. The relationship between TyG and stroke is partially mediated by obesity measures, while the relationship between obesity measures and stroke is partially mediated by TyG.
Conclusion
Compared with the traditional single TyG, the combination of TyG and obesity indicators could improve the prognostic accuracy of stroke mortality, enhance diagnostic efficacy for stroke and its mortality, and uncover additional associations with stroke. These findings carry noteworthy implications for the timely identification of individuals at risk of stroke, and refining risk stratification.
Insights into Medication Adherence among Jordanian Patients with Dyslipidemia: Evaluating Health Literacy, Well-being, and Doctor-Patient Communication
Authors: Barakat Muna , Thiab Samar , Abdulrazzaq Shaymaa B. , Al-Jamal Marah , AlHariri Fotoh , Ammari Rakan Bassam , Mansour Sara , Khatib Sami El , Hallit Souheil , Hosseini Basile , Malaeb Diana , Hosseini Hassan 
Published: May 2024

Abstract

Background
The study aimed to assess medication adherence among Jordanian patients with dyslipidemia, in addition to evaluating the impact of health literacy, health well-being, and doctor-patient communication on medication adherence in this population.
Methods
An observational cross-sectional study was conducted between March to July 2023. A convenient sample of adult Jordanians diagnosed with dyslipidemia was surveyed, by two trained researchers in a tertiary hospital. The study tool consisted of demographic data and several validated scales, including the Lebanese Medication Adherence Scale-14 (LMAS-14), the Doctor-Patient Communication Scale (DPC), the World Health Organization (WHO) well-being index, and the health literacy scale. Scores for each scale were computed, and associations were analyzed using bivariant analysis and linear regression models.
Results
A total of 410 participants were included in the study with a mean age of 58.62 ± 12.11 years. The sample mean score for LMAS-14 was 35.10, the DPC score was 55.77, the WHO-5 well-being index score was 47.53, and the health literacy score was 38.96. Linear regression models showed that older age (B = 0.093, p = 0.049), university education (B = 2.872, p = 0.017), prior surgery (B = 2.317, p = 0.021), medium income level (B = 3.605, p = 0.006), and higher doctor-patient communication scores (B = 0.166, p = 0.003) were associated with higher medication adherence. Conversely, cigarette smoking (B=-3.854, p = 0.001) and having health insurance (B=-2.146, p = 0.039) were linked to lower adherence levels.
Conclusion
Results highlight the intricate interplay of various socio-demographic and clinical factors and their impact on medication adherence. Targeted public health interventions that address socio-demographic conditions, communication quality, and health literacy are pivotal to improved adherence and overall patient outcomes.
Glucose and Glutamine Drive Hepatitis E Virus Replication
Authors: Khan Shaheen , Aggarwal Suruchi , Bhatia Pooja , Yadav Amit Kumar , Kumar Yashwant , Veerapu Naga Suresh 
Published: May 2024

Abstract

Viruses have undergone evolutionary adaptations to tune their utilization of carbon sources, enabling them to extract specific cellular substrates necessary for their replication. The lack of a reliable cell culture system and a small animal model has hampered a better understanding of the underlying molecular mechanisms of replication of the genotype 1 hepatitis E virus (HEV). Our recent identification of a replicative ensemble of mutant HEV RNA libraries has allowed us to study the metabolic prerequisites of HEV replication. The initial assessments have revealed increased glucose and glutamine utilization during HEV replication. Inhibition of glycolysis and glycolysis + glutaminolysis have exhibited similar effects in reducing the levels of HEV replication. An integrated analysis of protein-metabolite pathways has suggested that HEV replication markedly altered glycolysis, the TCA cycle, and glutamine-associated metabolic pathways. Cells supporting HEV replication have shown a critical involvement of fructose-6-phosphate and glutamine utilization through hexosamine biosynthetic pathway (HBP), stimulating HSP70 expression to facilitate virus replication. Confirmation of the crucial role of HBP in supporting HEV replication comes from observations of mannose utilization and glutamine dependency. Inhibition of glycolysis and HSP70 activity, or knockdown of glutamine fructose-6-phosphate amidotransferase expression, led to a substantial reduction in HEV RNA and ORF2 expression, accompanied by a significant decrease in HSP70 levels. In conclusion, this study demonstrates that glucose and glutamine play critical roles in facilitating HEV replication.
Using Large Language Models to Better Detect and Handle Software Vulnerabilities and Cyber Security Threats
Authors: Taghavi Seyed Mohammad , Feyzi Farid 
Published: May 2024

Abstract

Large Language Models (LLMs) have emerged as powerful tools in the domain of software vulnerability and cybersecurity tasks, offering promising capabilities in detecting and handling security threats. This article explores the utilization of LLMs in various aspects of cybersecurity, including vulnerability detection, threat prediction, and automated code repair. We explain the concept of LLMs, highlighting their various applications, and evaluates their effectiveness and challenges through literature review. We explore the effectiveness of various LLMs across different cybersecurity domains, showcasing their proficiency in tasks like malware detection and code summarization. Comparing LLMs to traditional methods, our work highlights their superior performance in identifying vulnerabilities and proposing fixes. Furthermore, we outline the workflow of LLM models, emphasizing their integration into cyber threat detection frameworks and incident response systems. We also discuss complementary methods and tools that enhance LLMs' capabilities, including static and dynamic code analyzers. Additionally, we synthesize findings from previous research, demonstrating how the utilization of LLMs has significantly enhanced productivity in identifying and addressing software vulnerabilities and cybersecurity threats. Finally, the study offers insights into optimizing the implementation of LLMs based on the lessons learned from existing literature.
A streamlined culturomics approach for the human gut microbiota research
Authors: Park Hyunjoon , Yeo Soyoung , Ryu Chang Beom , Huh Chul Sung 
Published: May 2024

Abstract

Bacterial culturomics is a set of techniques to isolate and identify live bacteria from complex microbial ecosystems. Despite its potential to revolutionize microbiome research, bacterial culturomics has significant challenges when applied to human gut microbiome studies due to its labor-intensive nature. Therefore, we established a streamlined culturomics approach with minimal culture conditions for stool sample preincubation. We evaluated the suitability of non-selective medium candidates for maintaining microbial diversity during a 30-day incubation period based on 16S rRNA amplicon analysis. Subsequently, we applied four culture conditions (two preincubation media under an aerobic/anaerobic atmosphere) to isolate gut bacteria on a large scale from eight stool samples of healthy humans. We identified 8,141 isolates, classified into 263 bacterial species, including 12 novel species candidates. Our analysis of cultivation efficiency revealed that seven days of aerobic and ten days of anaerobic incubation captured approximately 91% and 95% of the identified species within each condition, respectively, with a synergistic effect confirmed when selected preincubation media were combined. Moreover, our culturomics findings expanded the coverage of gut microbial diversity compared to 16S rRNA amplicon sequencing results. In conclusion, this study demonstrated the potential of a streamlined culturomics approach for the efficient isolation of gut bacteria from human stool samples. This approach might pave the way for the broader adoption of culturomics in human gut microbiome studies, ultimately leading to a more comprehensive understanding of this complex microbial ecosystem.
The prognostic impact of surufatinib for the treatment of advanced pancreatic ductal adenocarcinoma: A single center retrospective study
Authors: Yang Yanzhen , Xie Qu , Jiang Lai , Ding Guojun , Long Dan , Luo Cong 
Published: May 2024

Abstract

Background
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive tumor with a poor prognosis, despite the emergence of chemotherapies, unmet medical needs still exist for patients with metastatic PDAC (mPDAC). Surufatinib is a small-molecule tyrosine kinase inhibitor targets vascular endothelial growth factor (VEGFR) 1, 2, 3, fibroblast growth factor receptor 1 (FGFR1), and colony stimulating factor 1 receptor (CSF-1R). It was approved in China for patients with pancreatic and ex-pancreatic neuroendocrine tumors (NETs) based on Phase III trials: SANET-p and SANET-ep.
Method
We conducted a real world retrospective study of mPDAC patients who received the surufatinib between July 2022 and July 2023 at Zhejiang Cancer Hospital. In addition, patients who received first line chemotherapy at the same period were analyzed as comparison.
Result
As of November 30th 2023, 20 eligible patients were identified. The median progression-free survival (mPFS) of patients who received surufatinib treatment was 5.27 months (95% CI, 2.55–7.98). For fist line treatment, 9 patients received surufatinib combined with immune checkpoint inhibitors (ICIs) and the mPFS was 7.5 months (95% CI, 3.14–11.85), compared with an mPFS of 5.43 months (95% CI, 3.89–6.96) for 52 mPDAC patients received chemotherapy at the same period. Grade 3 or above Treatment Related Adverse Event (TRAE) were neutrophil count decreased (10%), and white blood cell count decreased (5%).
Conclusion
The anti-tumor activity of surufatinib in mPDAC patients is promising. Surufatinib combined with ICI may improve the efficacy in mPDAC and provide a potential treatment option for patients, especially in the first-line setting.
Trial registration
The trial was registered at ClinicalTrials, NCT06378580
Real-World data on the first UK Series of MINIject supraciliary implant with six months follow up
Authors: Dimitriou Chrysostomos , Dervenis Panagiotis , Wong Caroline , Tanner Luke , Nitiahpapand Rynda , Fazal Ihsan , Chatzithanasis Georgios , Stavropoulos Dimitrios , Lascaratos Gerassimos 
Published: May 2024

Abstract

Purpose:This study evaluates the efficacy and safety of the MINIject (iStar Medical, Wavre, Belgium) supraciliary implant.
Methods:Patients with medically uncontrolled primary open angle glaucoma, primary angle closure glaucoma and normal tension glaucoma. This first in the UK, restrospective, single-centre, interventional study evaluated the implantation of the MINIject in 45 eyes, including 11 standalone cases and 34 cases combined with phacoemulsification.
Primary outcome was reduction of intraocular pressure (IOP) at 6 months. Secondary outcomes included success defined as IOP of ≤21 mmHg and >5 mmHg with an IOP reduction of ≥20% without (complete success) or with (qualified success) the use of glaucoma medications, reduction of IOP and glaucoma medications during follow-up and adverse events.
Results:Mean (±SD) baseline IOP was 19.02±5.11 mmHg on 2.22±1.04 medications. At 6 months, 71.1% (n=32) achieved ≥20% IOP reduction with 91% (n=41) of patients being drop-independent. The mean IOP was 13.02±4.74 mmHg (range 4-29 mmHg) with the average percentage decrease being 31.55%. Furthermore, 71.1% (n=32) of eyes achieved an IOP of <15 mmHg. Mean IOP at 6 months in the phaco-combined group was 13.06 mmHg and in the standalone group was 12.91 mmHg. The reduction in IOP in these subgroups was 5.80 mmHg and 6.64 mmHg respectively (p=0.74). At 6 months, 66.67% of patients met the criteria for complete success and 71.11% for qualified success. Adverse events occured in 15.6% (n=7) of eyes. No sight-threatening events occurred.
Conclusion:This study shows promising IOP-lowering results and medication reduction over 6 months with few adverse events.
V activated Ag-O catalytic sites for direct electro-epoxidation to successive producing propylene oxide
Authors: Li Zhongtao , Lin Yan , Miao Xiaodong , Sun Yuanyuan , Li Hui , Ren Hao , Cui Wangyang , Wu Mingbo 
Published: May 2024

Abstract

As one environmentally friendly and sustainable method, direct electrooxidation of propylene (D-EOPO) can successively produce propylene oxide, but the poor selectivity and activity of the catalyst hinder the application. To overcome the issues, a D-EOPO device based on a membrane electrode reactor (MEA) has been developed with optimized Ag-V-O/GDL catalyst to active oxygen formation for propylene epoxidation. In-situ spectroscopy and theoretical calculations have revealed the critical role of introduced V, which can accelerate the formation of Ag-O to decrease the generation energy barriers of O* from absorbed water on the catalyst surface. Moreover, the V doping also can attribute to a positive shift of the d-band center of Ag, and facilitate the adsorption of propylene on the active center. Thus, the formation of the key intermediate (OC3H6*) by coupling O* with adsorbed propylene is synergistic promoted, thereby enabling the efficiency of D-EOPO. Finally, the MEA reactor with the developed Ag/V bimetallic catalyst have been developed for continuous D-EOPO, which can steadily electrooxidize propylene to PO with a yield of 64.48 µmol/h over 72 hours (almost the highest among currently reports).
Network Analyses of Brain Tumor Patients’ Multiomic Data Reveals Pharmacological Opportunities to Alter Cell State Transitions
Authors: Bumbaca Brandon , Birtwistle Marc , Gallo James 
Published: May 2024

Abstract

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e. phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte-like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein-protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.
Data Rescue for Historical Document Tables Using Semi-Supervised Learning
Authors: Singh Loitongbam Gyanendro , Middleton Stuart E. 
Published: May 2024

Abstract

This study uses a novel semi-supervised learning framework to explore Tabular Structure Recognition (TSR) for digitizing historical documents, specifically employing the CascadeTabNet model. TSR is crucial for transforming archival tabular data into digital formats, enhancing accessibility and analysis across various research fields. Challenges like physical degradation, inconsistent lighting, and non-standard handwriting hinder the generation of high-quality annotations of historical documents needed for effective model training. To address these issues, this research explores two research questions: (i) Can a semi-supervised training approach reduce the need for expensive data annotations? and (ii) Does semi-supervised training improve model robustness? We applied our methodology across three datasets: the GloSAT and ICDAR-2019 datasets based on historical documents, and the predominantly modern documents PubTabNet dataset. Our results indicate that semi-supervised learning substantially increases TSR accuracy and decreases dependency on extensive labelled datasets, providing a robust solution for large-scale digitization initiatives and contributing to the preservation and improved accessibility of historical data. All code from this paper is freely available on GitHub.
Study of Kinetics, Thermodynamics and Reaction Time of Corn Starch Acetylation
Authors: Freitas Roberta , Carmo Karina , Pádua Franciane , Botaro Vagner 
Published: May 2024

Abstract

Starch acetylation plays a crucial role in the starch industry, offering enhanced versatility and functionality. The study aimed to analyze the kinetics and thermodynamics of starch acetylation. Corn starch was acetylated in different degrees of substitution by esterification reaction with acetic anhydride, acetic acid and sulfuric acid as a catalyst. Order of the reaction was determined by integral analysis method, defined as a pseudo-first order because it presents correlation factor R2 closest to 1. From thermodynamic models used, it was possible to determine enthalpy of acetylation (-1.33x10-2 J.mol-1), critical temperature (0.0223 K), heat capacity (1.53x10-3J.mol-1.K-1) and entropy change (-2.31x10-4 J.mol-1.K-1). Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM) characterized starch and starch acetates. In analysis, acetylation was confirmed with the appearance of band at 1740 cm-1, corresponding to carbonyl of acetyl group, presence of pores and breakdown of starch granules after acetylation reaction. Starch acetylation increased with reaction time, reaching a maximum degree of substitution of approximately 2.62 after 50 minutes.
Correction method of Mohr-Coulomb strength criterion for rock based on freeze-thaw and residual effects
Authors: Liu Yang , Meng Xiangzhen , Zhang Huimei , Shen Yanjun 
Published: May 2024

Abstract

Considering the characteristics of micro element failure when rock is subjected to freeze-thaw and load, based on the impact of reducing the effective bearing area on each damage, the total damage variable and constitutive model of rock under freeze-thaw and load are established. Starting from the characteristics of the entire process of rock deformation, the revised Mohr-Coulomb (M-C) strength criterion of rock is established by considering the freeze-thaw and residual effects. The results show that: The established damage constitutive model fully reflects the entire process of rock deformation and failure, especially the post peak softening and residual deformation characteristics; with the increasing of freeze-thaw cycles, the strength of rock decreases and the deformation increases; with the increasing of confining pressure, the strength and deformation of the rock also increase, which is consistent with the actual situation. This Revised M-C strength criterion introduces the influence of freeze-thaw cycles and residual stress factors, which not only characterizes the relationship between internal stress parameters in rock limit states under different freeze-thaw cycles, but also makes the theoretical data closer to the test data and more in line with practical engineering. Compared with the Drucker-Prager (D-P) criterion, this criterion addresses the disadvantage of the D-P criterion being more conservative. This method is based on the measured results of rock triaxial test, which makes it more flexible and the calculation results closer to reality.