bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emergency medicine in Nepal: are we going the right way and fast enough?
Authors: Bhandari Sanjeeb S. , Adhikari Subarna 
Published: November 2023

AbstractNepal is a landlocked country with variable topography including the world’s tallest mountains, tropical forests, and Gangetic plains. This topography leads to diverse healthcare needs, from tropical diseases in plains, to road traffic accidents in hills, and to disaster-related emergencies from floods and landslides during monsoon season and unpredictable earthquakes. Emergency medicine care is underdeveloped and is currently being provided by general practitioners. The capital city Kathmandu has a few tertiary healthcare centers with emergency medicine fellowship-trained general practitioners staffing them, but most of the hospitals outside of Kathmandu are staffed by minimally trained or untrained medical officers. Even though emergency medicine is recognized as a specialty, Nepal still does not have an emergency medicine residency training program. To improve emergency care in the country, the government of Nepal should be focused on facilitating the start of emergency medicine residency in Nepal.
Graphical Abstract
Predicting active enhancers with DNA methylation and histone modification
Authors: Luo Ximei , Li Qun , Tang Yifan , Liu Yan , Zou Quan , Zheng Jie , Zhang Ying , Xu Lei 
Published: November 2023

Abstract
Background
Enhancers play a crucial role in gene regulation, and some active enhancers produce noncoding RNAs known as enhancer RNAs (eRNAs) bi-directionally. The most commonly used method for detecting eRNAs is CAGE-seq, but the instability of eRNAs in vivo leads to data noise in sequencing results. Unfortunately, there is currently a lack of research focused on the noise inherent in CAGE-seq data, and few approaches have been developed for predicting eRNAs. Bridging this gap and developing widely applicable eRNA prediction models is of utmost importance.

Results
In this study, we proposed a method to reduce false positives in the identification of eRNAs by adjusting the statistical distribution of expression levels. We also developed eRNA prediction models using joint gene expressions, DNA methylation, and histone modification. These models achieved impressive performance with an AUC value of approximately 0.95 for intra-cell prediction and 0.9 for cross-cell prediction.

Conclusions
Our method effectively attenuates the noise generated by stochastic RNA production, resulting in more accurate detection of eRNAs. Furthermore, our eRNA prediction model exhibited significant accuracy in both intra-cell and cross-cell validation, highlighting its robustness and potential application in various cellular contexts.
Large-scale phosphoproteome analysis in wheat seedling leaves provides evidence for extensive phosphorylation of regulatory proteins during CWMV infection
Authors: Chen Lu , Yang Jin , Hu Haichao , Jiang Yaoyao , Feng Lixiao , Liu Jiaqian , Zhong Kaili , Liu Peng , Ma Youzhi , Chen Ming , Yang Jian 
Published: November 2023

Abstract
Background
Chinese wheat mosaic virus (CWMV) often causes severe damage to wheat (Triticum aestivum L.) growth and yield. It is well known that a successful infection in plants depends on a complex interaction between the host plant and the pathogen. Post-translational modification (PTM) of proteins is considered to be one of the main processes that decides the outcome of the plant-pathogen arms race during this interaction. Although numerous studies have investigated PTM in various organisms, there has been no large-scale phosphoproteomic analysis of virus-infected wheat plants. We therefore aimed to investigate the CWMV infection-induced phosphoproteomics changes in wheat by high-resolution liquid chromatography-tandem mass spectroscopy (LC–MS/MS) using affinity-enriched peptides followed by comprehensive bioinformatics analysis.

Results
Through this study, a total of 4095 phosphorylation sites have been identified in 1968 proteins, and 11.6% of the phosphorylated proteins exhibited significant changes (PSPCs) in their phosphorylation levels upon CWMV infection. The result of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that most of the PSPCs were associated with photosynthesis, plant-pathogen interactions, and MAPK signaling pathways. The protein–protein interaction (PPI) network analysis result showed that these PSPCs were mainly participated in the regulation of biosynthesis and metabolism, protein kinase activities, and transcription factors. Furthermore, the phosphorylation levels of TaChi1 and TaP5CS, two plant immunity-related enzymes, were significantly changed upon CWMV infection, resulting in a significant decrease in CWMV accumulation in the infected plants.

Conclusions
Our results indicate that phosphorylation modification of protein plays a critical role in wheat resistance to CWMV infection. Upon CWMV infection, wheat plants will regulate the levels of extra- and intra-cellular signals and modifications of enzyme activities via protein phosphorylation. This novel information about the strategies used by wheat to resist CWMV infection will help researchers to breed new CWMV-resistant cultivars and to better understand the arms race between wheat and CWMV.
Anti-proliferative activity of RIHMS-Qi-23 against MCF-7 breast cancer cell line is through inhibition of cell proliferation and senescence but not inhibition of targeted kinases
Authors: El-Gamal Randa , Elfarrash Sara , EL-Nablaway Mohammad , Salem Asmaa Ahmed , Zaraei Seyed-Omar , Anbar Hanan S. , Shoma Ashraf , El-Gamal Mohammed I. 
Published: November 2023

Abstract
Background
Breast cancer is the most common malignancy globally, and is considered a major cause of cancer-related death. Tremendous effort is exerted to identify an optimal anticancer drug with limited side effects. The quinoline derivative RIMHS-Qi-23 had a wide-spectrum antiproliferative activity against various types of cancer cells.

Methods
In the current study, the effect of RIMHS-Qi-23 was tested on MCF-7 breast cancer cell line to evaluate its anticancer efficacy in comparison to the reference compound doxorubicin.

Results
Our data suggest an anti-proliferative effect of RIMHS-Qi-23 on the MCF-7 cell line with superior potency and selectivity compared to doxorubicin. Our mechanistic study suggested that the anti-proliferative effect of RIMHS-Qi-23 against MCF-7 cell line is not through targeted kinase inhibition but through other molecular machinery targeting cell proliferation and senescence such as cyclophlin A, p62, and LC3.

Conclusion
RIMHS-Qi-23 is exerting an anti-proliferative effect that is more potent and selective than doxorubicin.
Construction and verification of aggressive behavior risk prediction model in stable patients with schizophrenia
Authors: Sun Yujing , Jiang Wenlong , Yu Hong , Zhang Jing , Zhou Yuqiu , Yin Fei , Su Hong , Jia Yannan 
Published: November 2023

Abstract
Background
Among all types of mental disorders, individuals with schizophrenia exhibit the highest frequency of aggressive behavior. This disrupts the healthcare environment and poses threats to family life and social harmony. Present approaches fail to identify individuals with schizophrenia who are predisposed to aggressive behavior. In this study, we aimed to construct a risk prediction model for aggressive behavior in stable patients with schizophrenia, which may facilitate early identification of patients who are predisposed to aggression by assessing relevant factors, enabling the management of high-risk groups to mitigate and prevent aggressive behavior.

Methods
A convenience sample of stable inpatients with schizophrenia were selected from Daqing Municipal Third Hospital and Chifeng Municipal Anding Hospital from March 2021 to July 2023. A total of 429 patients with stable schizophrenia who met the inclusion criteria were included. A survey was conducted with them using a questionnaire consisting of general information questionnaire, Positive and Negative Symptom Scale, Childhood Trauma Questionnaire-Short Form, Connor-Davidson Resilience Scale and Self-esteem Scale. Patients enrolled in this study were divided into aggressive and non-aggressive groups based on whether there was at least one obvious and recorded personal attack episode (including obvious wounding and self-injurious behavior) following diagnosis. Binary Logistic regression was used to determine the influencing factors, and R software was used to establish a nomogram model for predicting the risk of aggressive behavior. Bootstrap method was used for internal validation of the model, and the validation group was used for external validation. C statistic and calibration curve were used to evaluate the prediction performance of the model.

Results
The model variables included Age, Duration of disease, Positive symptom, Childhood Trauma, Self-esteem and Resilience. The AUROC of the model was 0.790 (95% CI:0.729–0.851), the best cutoff value was 0.308; the sensitivity was 70.0%; the specificity was 81.4%; The C statistics of internal and external validation were 0.759 (95%CI:0.725–0.814) and 0.819 (95%CI:0.733–0.904), respectively; calibration curve and Brier score showed good fit.

Conclusions
The prediction model has a good degree of discrimination and calibration, which can intuitively and easily screen the high risk of aggressive behavior in stable patients with schizophrenia, and provide references for early screening and intervention.
Knowledge, perceptions, beliefs, and opinions of the employees about GBV: a national online study in South Africa
Authors: Davis Corne , Kuhudzai Anesu , Dalal Koustuv 
Published: November 2023

Abstract
Background
GBV has been global public health, family, and social problem for several decades as it is expensive for society and the economy. The study was conducted to determine the possible differences in knowledge, perceptions, beliefs, and opinions about GBV, as a whole, across gender and employment sectors in South Africa.

Methods
This was a cross-sectional study using mixed-method design where we used an online survey with two open-ended questions. Perception about GBV Prevention among Employees (GBVPREV) questionnaire consisting of six Sect. (43 questions) was developed and tested. Cronbach’s alpha, Exploratory factor analysis (EFA), including Kaiser-Meyer Olkin Measure of Sampling Adequacy (KMO) and Bartlett’s test of Sphericity, one-way analysis of variance (ANOVA) and Tukey HSD were used. Content analysis was used for analysing qualitative information from two open-ended questions.

Results
Among the 2 270 employees, more than half (68.1%) were females. Males were 677 (29.8%), and members of the LGBTQIAP + community were 32 (1.4%). There were statistically significant differences among males, females, and LGBTQIAP + on employee knowledge of adult experiences, employee knowledge of violence against children, employee perceptions, employee beliefs, and employee opinions and recommendations. The employees believe that all sectors of society should collaborate in addressing GBV in South Africa. They felt that victims should be encouraged to come forward, that society should be less judgemental, that stigma should be addressed and that there should be more empathy for victims.

Conclusion
Most of the respondents, who were female and had tertiary education, were employed in the private sector, and were very aware of the prevalence of GBV in South Africa, agreed that support for both victims and perpetrators must be provided in private sector organizations. Even though it has been acknowledged for decades that gender inequality and GBV are reciprocal drivers, the persistence of both human rights violations will continue if all stakeholders do not collaborate.
Differential airway resistome and its correlations with clinical characteristics in Haemophilus- or Pseudomonas-predominant microbial subtypes of bronchiectasis
Authors: Yi Xin-zhu , Yang Jun-hao , Huang Yan , Han Xiao-rong , Li Hui-min , Cen Lai-jian , Lin Zhen-hong , Pan Cui-xia , Wang Zhang , Guan Wei-jie 
Published: November 2023

AbstractThe prevalence and clinical correlates of antibiotic resistance genes (ARGs) in bronchiectasis are not entirely clear. We aimed to profile the ARGs in sputum from adults with bronchiectasis, and explore the association with airway microbiome and disease severity and subtypes. In this longitudinal study, we prospectively collected 118 sputum samples from stable and exacerbation visits of 82 bronchiectasis patients and 19 healthy subjects. We profiled ARGs with shotgun metagenomic sequencing, and linked these to sputum microbiome and clinical characteristics, followed by validation in an international cohort. We compared ARG profiles in bronchiectasis according to disease severity, blood and sputum inflammatory subtypes. Unsupervised clustering revealed a Pseudomonas predominant subgroup (n = 16), Haemophilus predominant subgroup (n = 48), and balanced microbiome subgroup (N = 54). ARGs of multi-drug resistance were over-dominant in the Pseudomonas-predominant subgroup, while ARGs of beta-lactam resistance were most abundant in the Haemophilus-predominant subgroup. Pseudomonas-predominant subgroup yielded the highest ARG diversity and total abundance, while Haemophilus–predominant subgroup and balanced microbiota subgroup were lowest in ARG diversity and total abundance. PBP-1A, ksgA and emrB (multidrug) were most significantly enriched in Haemophilus-predominant subtype. ARGs generally correlated positively with Bronchiectasis Severity Index, fluoroquinolone use, and modified Reiff score. 68.6% of the ARG-clinical correlations could be validated in an independent international cohort. In conclusion, ARGs are differentially associated with the dominant microbiome and clinical characteristics in bronchiectasis.
Diagnostic, prognostic and clinical value of left ventricular radial strain to identify paradoxical septal motion in ventilated patients with the acute respiratory distress syndrome: an observational prospective multicenter study
Authors: Evrard Bruno , Woillard Jean-Baptiste , Legras Annick , Bouaoud Misylias , Gourraud Maeva , Humeau Antoine , Goudelin Marine , Vignon Philippe 
Published: November 2023

Abstract
Background
Acute cor pulmonale (ACP) is prognostic in patients with acute respiratory distress syndrome (ARDS). Identification of paradoxical septal motion (PSM) using two-dimensional echocardiography is highly subjective. We sought to describe feature-engineered metrics derived from LV radial strain changes related to PSM in ARDS patients with ACP of various severity and to illustrate potential diagnostic and prognostic yield.

Methods
This prospective bicentric study included patients under protective ventilation for ARDS related to COVID-19 who were assessed using transesophageal echocardiography (TEE). Transgastric short-axis view at mid-papillary level was used to visually grade septal motion, using two-dimensional imaging, solely and combined with LV radial strain: normal (grade 0), transient end-systolic septal flattening (grade 1), prolonged end-systolic septal flattening or reversed septal curvature (grade 2). Inter-observer variability was calculated. Feature engineering was performed to calculate the time-to-peak and area under the strain curve in 6 LV segments. In the subset of patients with serial TEE examinations, a multivariate Cox model analysis accounting for new-onset of PSM as a time-dependent variable was used to identify parameters associated with ICU mortality.

Results
Overall, 310 TEE examinations performed in 182 patients were analyzed (age: 67 [60–72] years; men: 66%; SAPSII: 35 [29–40]). Two-dimensional assessment identified a grade 1 and grade 2 PSM in 100 (32%) and 48 (15%) examinations, respectively. Inter-rater reliability was weak using two-dimensional imaging alone (kappa = 0.49; 95% CI 0.40–0.58; p < 0.001) and increased with associated LV radial strain (kappa = 0.84, 95% CI 0.79–0.90, p < 0.001). The time-to-peak of mid-septal and mid-lateral segments occurred significantly later in systole and increased with the grade of PSM. Similarly, the area under the strain curve of these segments increased significantly with the grade of PSM, compared with mid-anterior or mid-inferior segments. Severe acute cor pulmonale with a grade 2 PSM was significantly associated with mortality. Requalification in an upper PSM grade using LV radial strain allowed to better identify patients at risk of death (HR: 6.27 [95% CI 2.28–17.2] vs. 2.80 [95% CI 1.11–7.09]).

Conclusions
In objectively depicting PSM and quantitatively assessing its severity, TEE LV radial strain appears as a valuable adjunct to conventional two-dimensional imaging.
Adaptation of the CUGH global health competency framework in the Chinese context: a mixed-methods study
Authors: Ding Wei , Guan Yayi , Peterhans Bernadette , Hoffmann Axel , Zhou Xiao-Nong 
Published: November 2023

Abstract
Background
In 2014, the Consortium of Universities for Global Health (CUGH) developed a global health competency framework and called for its validation. Given China's increasing engagement in global health over the past decade, there is a need for a tailored competency framework to enhance the capacity of its workforce. This study aimed to localize the CUGH global health framework within the Chinese context, offering guidance to public health professionals in China to bolster their capabilities for international endeavors.

Methods
Employing a modified Delphi consultation approach, this study adapted the CUGH global health competency framework through three consultation rounds and a panel discussion. A questionnaire employing a five-point Likert scale was developed to gather opinions from 37 experts on the significance and feasibility of each competency within the Chinese setting. Profiling information, judgment criteria, and familiarity with each competency were collected to assess experts' authority levels. Furthermore, a priority survey was administered to 51 experts to identify key competencies and provide recommendations for bolstering the capabilities of China's public health professionals. Data analysis was performed using Microsoft Excel.

Results
The adapted framework comprises 10 domains and 37 competencies including: 1. Global Burden of Disease; 2. Social-economic, Environmental and Behavioral Determinants of Health; 3. The Impact of Globalization on Population Health, Health Systems, and Healthcare; 4. Major Global health initiatives and efforts; 5. Ethics, Health Equity and Social Justice; 6. Sociocultural, Political Awareness and Policy Promotion; 7. Personal Competencies and Professional Practice; 8. Capacity strengthening; 9. Collaboration, Partnering and Communication; 10. Programme Management. The priority survey underscored Domain 9, 10, and 4 as the foremost concern for Chinese public health professionals, urging active learning, critical thinking, open communication, experiential learning, and case-based studies. Institutions were advised to enhance their capacity, foster partnerships, and discern China's distinct role in the global health arena.

Conclusions
This study adapted the CUGH framework within the Chinese context, evaluating the significance and feasibility of each competency. The adapted framework can serve as a tool for developing global health curricula and delineating roles for Chinese public health professionals. To ensure contextual compatibility, testing of the framework with diverse public health professionals is recommended, enabling precise refinement of competencies based on empirical results.
High performance of a low input, mixed western Australian farming system: public policy implications from the case of Tolga farm
Authors: Plunkett Bradley , Roberts Daniel , Kharel Sudarshan , Foster Kevin , Overheu Tim , Savage Brendon 
Published: November 2023

AbstractTolga is a 5,200 ha sheep and cropping farm located near Kulin in Western Australia (WA). Since 2004, its production system has been a blend of conventional and alternative practices; some of these alternative practices are common in non-broadacre industries. The alternative practices are based on an understanding of soil health gained from the Australian Soil Planners system which aims to improve the farm’s biological functioning and nutrient cycling.This includes use of phase rotations with legume (subclover) pastures tended as a crop, minimal, but necessary synthetic fertilisers and chemicals, supplementary nutritional packages for pastures, animals, and soils, supplementing chemical control with nutrition and grazing management where possible, corrective liming to address soil acidity, and using deep rooted tillage radish to recycle sub soil nutrients, promote root biomass to reduce the impact of soil compaction and possibly, reduce enteric methane emissions.Livestock performance is very high by industry standards, and crop yields, previously similar to district average, are improving in response to a greater proportion of the farm dedicated to livestock / pasture production. The reasons for the high level of livestock performance are not thoroughly understood, emphasising the need for research into the farm’s system. Estimated profitability is around the median of a leading consultant’s cohort of farmers for that rainfall zone; however, the low variability in its profit is reflective of the top 25% of the cohort, ranked on profit (gross margin) per hectare. The business has steadily grown over the past 30 years. Emissions (T/CO2e/ha) are estimated to be low compared to industry benchmarks and evidence exists that the farm’s total organic carbon pool is either reflective of or is as much as 40% higher than the surrounding area.
Graph neural network based approach to automatically assigning common weakness enumeration identifiers for vulnerabilities
Authors: Liu Peng , Ye Wenzhe , Duan Haiying , Li Xianxian , Zhang Shuyi , Yao Chuanjian , Li Yongnan 
Published: November 2023

AbstractVulnerability reports are essential for improving software security since they record key information on vulnerabilities. In a report, CWE denotes the weakness of the vulnerability and thus helps quickly understand the cause of the vulnerability. Therefore, CWE assignment is useful for categorizing newly discovered vulnerabilities. In this paper, we propose an automatic CWE assignment method with graph neural networks. First, we prepare a dataset that contains 3394 real world vulnerabilities from Linux, OpenSSL, Wireshark and many other software programs. Then, we extract statements with vulnerability syntax features from these vulnerabilities and use program slicing to slice them according to the categories of syntax features. On top of slices, we represent these slices with graphs that characterize the data dependency and control dependency between statements. Finally, we employ the graph neural networks to learn the hidden information from these graphs and leverage the Siamese network to compute the similarity between vulnerability functions, thereby assigning CWE IDs for these vulnerabilities. The experimental results show that the proposed method is effective compared to existing methods.