bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anti-inflammatory Effects of Nanoparticles Containing Alpha-Humulene in a Model of Alzheimer's Disease
Authors: Wendler Sabrina Aparecida , Nunes Jéssica Roberta , Dranski Lais Fernanda , Mainardes Rubiana Mara , Machado Christiane Schineider , Bini Ana Carolina Dorigoni , Schiewe João Alfredo , Miranda Livia Hoyer Garcia , Kerppers Ivo Ilvan 
Published: December 2023

Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder that causes impairment in activities of daily living. Although there is no consensus on the pathophysiology, it is known that neuroinflammation is associated with the condition.
Objective:To evaluate the anti-inflammatory effects of nanoparticles containing alpha-humulene (HUM) in an experimental model of AD.
Methodology: 33 animals were part of the sample, 3 of which were in the negative control group. The other 30 received the amyloid-beta peptide in the CA1 hippocampal region for the neuroinflammation process. They rested for 30 days for the inflammatory process to occur. The HUM group was treated with α-humulene particles, the NHUM with α-humulene nanoparticles for 15 days, and the CP group wasn’t treated.
Results:There was a significant difference in IFNconcentration between CP and CN (p=0.0001), HUM and CN (p=0.0003), CP and NHUM (p=0.0006), and HUM and NHUM (p=0.0495) groups. TNF showed no difference between groups. IL-6 showed difference between CP and NHUM (p=0.0078) and CP and CN (p=0.0009). IL-12 showed difference between the CP and CN (p=0.0001) and NHUM and CN (p=0.0160). Among all, the highest concentration was in the CP group. Concerning IL-10, there was a difference between the CP and NHUM (p=0.0003) and NHUM and CN (p=0.0005), with NHUM having the highest concentration. Immunohistochemistry analysis showed in Anti-Tau and Anti-GAPF a strong positive in the CP, a positive in the HUM, and a weak positive in the NHUM group.
Conclusion: The Alzheimer's model used and the treatments with HUM and NHUM were effective.
Effect of perceived crowding on risk perception in leisure sports based on Edward T Hall’s concept of ‘proxemics’
Authors: Kang Seungwoo , Kim Youngjae 
Published: December 2023

Abstract
This study investigates the social distancing measures necessary for participants to safely engage in leisure sports activities and comply with social distancing requirements during epidemics. Based on crowding and risk perception in public spaces in the context of an epidemic, this investigation was conducted in terms of distance in Edward T. Hall’s concept of ‘proxemics’. The participants were males aged 20–65 years who had used spaces for leisure sports in South Korea during COVID-19. An online survey was conducted from 20 September 2021 to 20 October 2021, and data from 391 participants were used for the final analysis. Measures of perceived crowding, risk perception, and Hall’s proxemics were used as tools after they had been modified and validated. The results show that perceived crowding according to space for leisure sports activities during COVID-19 affected individual risk perception in indoor leisure sports and social risk perception in outdoor leisure activities. Perceived crowding according to proxemics influenced (1) personal, social, and public distances in individual risk perception and (2) public and social distances in social risk perception. Therefore, it is necessary to re-examine the scope of social distancing in developing risk perception and reducing the perceived crowding of participants in leisure sports to prevent the spread of infectious diseases such as COVID-19. Individuals must make an effort to maintain a minimum distance from one another, the public must be educated via the media, and warnings must be disseminated to reduce crowding and prevent infection spread.
Closed-loop circularity of mixed biomass waste: cellulose extraction and conversion into cellulose acetate bioplastic for use as growing substrates in plant cultivation
Authors: Chen Yuanyuan , Liu Handai , Portela Alexandre 
Published: December 2023

Abstract

Currently, composting remains the primary method of processing mixed biomass waste, despite being a plentiful and renewable resource, the heterogeneous nature and widespread distribution of the mixed biomass waste have led to its underutilization. Similar situation in space, 80% of space-grown crop results in biomass waste, and the current waste disposal method of storing wastes and returning them to Earth or burning them up in the atmosphere is not suitable for long-duration human space exploration missions. In addition, Rockwool has been currently utilized as the growing substrate for space plant cultivation, which is not sustainable and depends on space logistics. Therefore, this study investigated a novel circular approach of converting mixed biomass waste into bioplastics and using it as a growing substrate to support plant growth, then the plant residue was converted into bioplastics again. Mixed garden waste was collected and treated with alkaline hydrogen peroxide (AHP) to extract cellulose. The cellulose content of the AHP-treated biomass increased by 75%, while the hemicellulose and lignin contents decreased by 46% and 58%, respectively. The cellulose extraction performance of AHP was assessed by FTIR and SEM. A solvent-free acetylation method using anhydride and iodine was used to convert the extracted cellulose into cellulose acetate (CA). A degree of substitution of 2.5 was measured using a titration technique. Triethyl citrate (TEC) was used to plasticize the synthesized CA by dissolving them both in acetone. The plasticization and 3D printability of plasticized CA were assessed with DSC and rheological tests. Porous structures were produced using the plasticized CA and a self-constructed granule-based material extrusion printer. Plant garden peas were able to grow on these porous structures. After the harvesting, the plant residues were reprocessed into CA, showing a circular approach to the mixed biomass waste valorisation.
Climate Extreme Scenarios affecting the Italian Energy System with a Multi-Hazard Approach
Authors: Faggian Paola , Trevisiol Arianna 
Published: December 2023

Abstract
The operation of the energy system can be compromised by extreme weather events that can impact generation, transmission and distribution infrastructure, as well as energy demand, and will face even more critical situations in the coming decades due to ongoing climate change. The challenge concerns particularly the infrastructures with long technical life. To support decision makers in planning adaptation actions for increasing the resilience of the Italian Energy System, some analyses about the expected meteorological threats over Italy have been carried out. The study aims to identify the Italian regions more prone to climate extremes at short- (2021–2050), medium- (2041–2070) and long-term (2071–2100) by using 12 high-resolution Euro-CORDEX models under the emission pathways RCP8.5, RCP4.5 and RCP2.6. For this purpose, a subset of the WMO ETCCDI indices was used. In addition, a multi-hazard analysis was carried out by defining the three indices DRO, STO, and MUHZ to characterize respectively droughts conditions, strong winds and heavy rainfalls, and the areas affected to multiple threats, considering the hazards at which power infrastructure are particularly vulnerable. At short term, under RCP4.5 and RCP8.5 hypotheses, the Southern Italy and Islands will already have to deal with a significant increase of drought conditions, that are projected to progressively extend from summer to autumn and then to spring, whereas the Central-Northern Italy will suffer particularly from storms. A decrease of wet days and, consequently, a lengthening of dry spells are generally expected, but extreme precipitations will be more frequent and more destructive, in particular over Po Valley and the eastern Italian coasts. Po Valley, Adriatic and Tyrrhenian coasts are projected to be the areas most exposed to a plurality of threats, but no Italian region will be safe from an enhancement of climate change hazards both in frequency and intensity during the Century in all three RCPs, with more and more severe conditions from RCP2.6 to RCP8.5 and from short- to long-term.
TEST-Net: Transformer-Enhanced Spatio-Temporal Network for infectious disease prediction
Authors: Chen Kai , Liu Yao , Ji Tianjiao , Zhang Yi , Chen Yang 
Published: December 2023

Abstract

Outbreaks of infectious diseases have caused tremendous human suffering and incalculable economic losses, and infectious diseases are a global public health problem that threatens human society.
Therefore, it is necessary to model the spatial and temporal distribution characteristics of infectious diseases, explore the transmission trend of infectious diseases, establish an infection early warning model and take corresponding preventive and control measures, which can make the prevention and control work more targeted and forward-looking.
Given the complex spatial correlation and temporal variation of infectious diseases, deep learning-based Spatio-temporal sequence prediction is widely employed because of its superior performance in capturing Spatio-temporal features.
However, current deep learning-based infectious disease prediction methods utilize an encoder-decoder structure that provides barely satisfactory accuracy due to a lack of understanding of infectious disease prevalence factors or deficiencies in capturing representative Spatio-temporal patterns.
In this paper, we develop the Transformer-Enhanced Spatio-Temporal Network (TEST-Net) which consists of a temporal location coding module and a Spatio-temporal feature fusion module for Infectious disease prediction.
Temporal information is input in TEST-Net by Temporal Location Encoding (TLE), and temporal and spatial correlation of sequences is extracted by a transformer-based attention network, and temporal features are fused with spatial features by a Spatio-temporal feature fusion network.
Compared with other state-of-the-art methods, qualitative and quantitative results show that TSET-Net has an excellent performance in modeling the spatial and temporal distribution characteristics of data and performs well in the accuracy of long-term prediction of infectious disease.
Failure analysis and numerical simulation of the regulating valve in the black- water treatment system
Authors: Cui Bochao , Chen Ping , Liu Boshen , Zhao Yuanqi , Zheng Jiaqi 
Published: December 2023

Abstract

The black-water regulating valve is very easy to be damaged due to the erosion of the key components, such as valve spool and valve seat. This work presents the failure analysis of the spool and seat of regulating valve in the black-water treatment system. Scanning electron microscopy (SEM) and X-ray energy dispersive spectrometer (EDS) were used to detect the morphology and chemical compositions of failure valve samples. The computational fluid dynamics (CFD) method was also adopted to simulate the medium flow characteristics in black-water regulating valve. The results show that most erosion areas of the valve occur at the spool-seat throttle zone. The erosion profile is mainly manifested in plastic deformation pits, cutting abrasions, furrows, pinhole pits and impact pits. The particles and cavitation bubbles move toward the throttle zone driven by black-water medium, causing particles impact and bubbles collapse. The valve suffered severe particle erosion and cavitation erosion under the particle impact and bubble collapse, finally resulting in its failure.
Single-Cell Transcriptomic, hdWGCNA, and Machine Learning reveal the Role of DYNLL1 in Lung Adenocarcinoma within Epithelial Cells
Authors: Wu Jintao , Liu Haiyun , Yang Xianxin , Liu Xiaohua , Mao Xiaocheng , Li Zhao , Peng Huopin , Li Dou , Mao Junying , Li Xingquan , Ji Daozhi , Fan Yiwei , Han Chunbin 
Published: December 2023

Abstract
Background: Lung cancer has the highest morbidity and mortality worldwide. Lung adenocarcinoma (LUAD) is the most common histological subtype and tends to be diagnosed at advanced stages with poor prognosis. Tumor heterogeneity and lack of prognostic biomarkers pose significant challenges for personalized therapy. Single-cell sequencing provides new opportunities to characterize intratumor heterogeneity and identify prognostic markers for early diagnosis or treatment target.
Methods: In this study, we analyzed single cell RNA sequencing data of 11 normal lung tissue samples and 11 LUAD samples from the GEO dataset GSE131907. High dimensional Weighted gene co-expression network analysis (hdWGCNA) was applied to the single-cell expression profile of epithelial cells to construct gene co-expression modules. Subsequently, a 13-gene prognostic signature was established by integrating 207 models with 15 machine learning algorithms in a cross validation framework. The correlation of the hub gene DYNLL1 with prognosis, clinical characteristics and biological pathways were comprehensively analyzed. Furthermore, loss-of-function assays by siRNA knockdown of DYNLL1 were performed to examine its functional role in LUAD cell lines.
Results: Significant differences in immune cell type distributions were observed between normal and tumor tissues, indicating important immune dysregulations during LUAD development. hdWGCNA identified 27 modules in LUAD epithelial cells potentially associated with tumorigenesis and disease outcomes. The 13-gene prognostic model effectively stratified patients into high- and low-risk groups with distinct survival. DYNLL1 was identified as an independent prognostic biomarker and potential therapeutic target. High expression of DYNLL1 positively correlated with advanced tumor stage and poorer survival. Knockdown of DYNLL1 expression suppressed cancer cell proliferation and invasion capacities.
Conclusions: Our study provided in-depth characterization of LUAD at single-cell resolution, identified key gene modules and prognostic biomarkers, and suggested DYNLL1 as a candidate prognostic predictor and therapeutic target, pending further verification in clinical settings. Keywords: Lung adenocarcinoma、scRNA_seq、hdWGCNA、machine learning 、Prognostic biomarker
Predictors of Two Minute Walk Distance in Healthy Indian Adults (18-40years)
Authors: Vaish Hina , Sharma Digvijay 
Published: December 2023

Abstract
Background: In recent year the two minute walk test (2MWT) is has been used in different health conditions, but the interpretation of its results is limited due to a shortage of reference values and prediction equations. The distance measured in 2MWT is known as two minute walk distance (2MWD). The aims of this study were 1) to measure 2MWD in healthy Indian adult 2) to determine the applicability of Selman et al. reference equation to Indian adult and 3) to find predictors of 2MWT in healthy Indian adults.
Methods: After initial screening and investigations, 2MWT were conducted in subjects aged 18–40 years.
Results: The mean (±SD) 2MWD was 220.47 ± 12.65m in males and 185.33 ± 17.49m in females. Selman et al. reference equation did not correctly predict distance in an Indian population: 2MWT was overestimated by a mean (±SD) of 24.71+14.31 m. The gender specific regression equations were developed. Predicted 2MWD (m) in males = 196.701+ 0.664 x Height (cm) – 0.715 x Age (years) -2.488 x BMI (kg/m2.) and predicted 2MWD (m) in females = 147.972+0.644 x Height (cm)–1.169 x Age (years)-0.506 x Weight (kg).
Conclusions: Selman et al. equation cannot be used to predict the 2MWD in Indian adult. The new regression equation for 2MWD is expected to prove useful for assessment purposes and prescribing exercises in healthy Indian adults aged 18-40 years.
A Qualitative Study on Community Usage of Antibiotics in Mogadishu-Somalia
Authors: Mohamed Shafi”i Abdulahi Ma’alim , Bashir Ahmed Muhammad 
Published: December 2023

Abstract
Aim
This study examines the knowledge and usage of antibiotics among participants in Somalia. Obtaining antibiotics from pharmacies based on perceived indications is common, driven by self-medication or advice from non-medical sources due to financial constraints.
Methods
The study used qualitative research design and data were gathered primarily through in-depth semi-structured interviews, employing a carefully designed interview guide. Participants were intentionally selected to encompass diverse medical and educational backgrounds, ensuring a comprehensive representation of the community. A total of 20 participants were interviewed, providing a sufficiently robust dataset for analysis.
Results
The study reveals that participants have a basic understanding of antibiotics and use them primarily for treating infections, naming specific examples. Dosage guidance varies, with participants relying on pharmacy salespersons, package leaflets, past prescriptions, or medical advice. Non-compliance with prescribed antibiotic courses is also prevalent. Concerns about the quality of antibiotics in the market are expressed, with participants favouring medicines imported from local markets of exporting countries.
Conclusion
The findings underscore the need for education and awareness campaigns to address knowledge gaps and promote responsible antibiotic use. Improving healthcare access, implementing regulatory measures, enhancing pharmaceutical quality, and properly training pharmacy personnel are necessary to ensure safe antibiotic use and combat antibiotic resistance.
Associated risk factors of gastroenteritis in infancy
Authors: AbdulHassan Shaima’a Dakhel 
Published: December 2023

Abstract
Introduction
Gastroenteritis is a condition characterized by inflammation of the gastrointestinal tract, resulting in a variety of symptoms like cramps, nausea, vomiting, diarrhoea, abdominal discomfort and dehydration. This ailment can manifest in two forms: acute or chronic. Acute gastroenteritis typically resolves within two weeks, while chronic gastroenteritis may persist for a period ranging from 14 to 30 days. Significantly, gastroenteritis can affect individuals of all age groups and poses a significant health risk, particularly in children. Chronic gastroenteritis stands as a leading cause of childhood mortality, and diarrhea remains a widespread illness among children worldwide.
Patients and Methods
A study was conducted involving 200 children, comprising a hundred cases and a hundred controls, to investigate the issues linked to gastroenteritis in children within their first years of life. The cases included children diagnosed with gastroenteritis, while controls comprised healthy children. To ensure the study's accuracy, children admitted to the Intensive Care Unit (ICU) or severely ill due to conditions other than gastroenteritis were excluded from the cases. Similarly, the control group consisted of children without any underlying diseases.
Results
A notable disparity emerged in various factors, including patient age, gender, maternal education, family structure, socioeconomic status and household income. These findings suggest that less education at home, unfavorable socioeconomic status, and restricted family income are potential risk factors associated with the development of gastroenteritis. Furthermore, the study also revealed significant distinctions in aspects related to child health, such as feeding patterns, the daily intake of meals, maternal responses to a child's diarrhea, consumption of boiled water, the child's penchant for consuming unpreserved food items, and the practice of sterilizing feeding equipment.
Accuracy of “high-quality” rating using the AMSTAR 2 tool for systematic reviews of prospective, controlled, clinical therapy trials. An empirical investigation (Protocol)
Authors: Mickenautsch Steffen , Yengopal Veerasamy 
Published: December 2023

Abstract
Aim: To investigate the likelihood that systematic reviews with “high-quality” AMSTAR 2 rating are affected by high risk of systematic error (bias).
Methods: A systematic literature search of current meta-reviews (systematic reviews of systematic reviews) will be conducted. From the identified meta-reviews, systematic reviews with “high” and “low” or “critically low” AMSTAR 2 quality rating will be extracted. All meta-analysis of the systematic reviews will be statistically tested for selection bias and the reviewed trials re-appraised for bias risk using the CQS-2B tool. From the test and re-appraisal results true positive, true negative, false positive or false negative results will be established and the negative and positive likelihood ratios with 95% Confidence interval computed. From the likelihood ratios the likelihood that systematic reviews with “high-quality” AMSTAR 2 rating are affected by high risk of systematic error will be inferred.
Ethics and dissemination: Ethical approval is not required for methodological studies. The results will be disseminated as a prior preprint version and subsequent peer-reviewed publication.
Genetic Insights into the Therapeutic Targets for Essential Hypertension: Mendelian Randomization and Colocalization Analysis
Authors: Hu Ben , Feng Jun , Luo Chunmiao , Shu Jinlian , Fan Yinguang , Hou Linlin 
Published: December 2023

Abstract
The prevalence of Essential Hypertension (EH) is increasing globally, and the effectiveness of pharmacological treatments remains far from ideal. Combining Mendelian Randomization (MR) to identify potential drug targets may be key to reducing the disease burden and developing potential treatments. We utilized the UK Biobank cohort (ncase = 54358, ncontrol = 408652) to extract summary statistics for EH and further validated in the FinnGen cohort (ncase = 92462, ncontrol = 265626). Cis-expression quantitative trait loci (cis-eQTL) from available druggable genes were retrieved and used as genetic instrumental variables. Two-sample MR analysis and colocalization analysis were conducted to examine whether identified genes and EH share variants, further consolidating MR results. Ten drug targets (FES, SLC22A4, PTK2B, BLK, ITPR1, NEGR1, GRK4, ADM, MAPK3, MAST3) showed significant MR results in two independent datasets, with no reverse causation observed. Colocalization analysis indicated that FES (PP.H4 = 0.99) and SLC22A4 (PP.H4 = 0.82) shared the same variants with EH, providing strong evidence. Additionally, FES showed significant associations with reduced risk of coronary artery disease, systolic blood pressure, and diastolic blood pressure, while SLC22A4 was significantly associated with increased diastolic blood pressure. Our results suggest that targeting FES and SLC22A4 might treat or cause EH, potentially revealing new pathophysiological pathways and treatment targets for EH.
Forms of complicity in a criminal offense under the criminal law of Ukraine
Authors: Grodetsky Yurii Vasylovych 
Published: December 2023

The forms of complicity in a criminal offense under the criminal law of Ukraine are considered: 1) complicity without prior agreement among the accomplices; 2) complicity by prior conspiracy; 3) organized group; 4) criminal organization. Objective and subjective signs of these forms of complicity are investigated. Deficiencies in the legislative regulation of the specified concepts in the Criminal Code of Ukraine were revealed.