bluuebunny/crossref_metadata_2025_split huggingface dataset:
Occurrence of pharmaceutically active compounds in groundwater and their effects to the human health
Authors: Klanovicz Natalia , Pinto Carolina Afonso 
Published: February 2024

Abstract

Groundwater contamination by pharmaceutically active compounds (PhACs) has been considered a public health concern worldwide. Alongside the potential toxicological risk of these organic substances, many countries still rely on groundwater for drinking water supply. Thus, this study identified a priority list of seven licit PhACs, comprising acetaminophen (ACT), tramadol (TRA), carbamazepine (CBZ), erythromycin (ERY), sulfamethoxazole (SMX), metformin (MET), and oxazepam (OXZ). Consumption, concentration, and human toxicity in silico results were collected from open access databases. These three indicators were analyzed separately and grouped through a global risk index (GRI). The consumption index (data from the USA and Brazil) indicated that ACT, TRA, and MET are the most consumed. Monitoring samples from the USA and Europe (n=816) indicated that ERY and ACT stand out as the higher occurrence index considering both regions; but the ranking for each region showed considerable differences. When assessing human health risk, a high index was attributed to ERY, ACT, and MET. Thus, the GRI results indicated that future studies must pay attention to ACT as it has high index values for all three indicators. In addition, human toxicity of CBZ, MET, OXZ, SMX, and TRA indicated the need to be attentive to their effects on human health.
Identification of potential crucial genes and key pathways shared in acute pancreatitis and major depression disorder by bioinformatics analysis
Authors: Zhu Kai , Zhou Yue , Jiang Meiling Jiang , Wu Qiong , Zhao Chen 
Published: February 2024

Abstract
Background
Despite the presence of evidence indicating a correlation between Acute Pancreatitis (AP) and Major Depressive Disorder (MDD), the precise mechanisms underlying the co-occurrence of these two conditions remain unclear. The aim of this study was to investigate potential crosstalk genes, pathways and immune cell between AP and MDD.
Methods
We downloaded the AP and MDD data from the Gene Expression Omnibus (GEO) database. Shared genes were identified using differential expression analysis and weighted gene co-expression network analysis (WGCNA). Subsequently, the differentially expressed genes (DEGs) were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Core genes were screened by cross and overlap of WGCNA and DEGs. The sensitivity and specificity of the candidate genes were evaluated using least absolute shrinkage and selection operator (LASSO) regression, and a receiver operating characteristic (ROC) curve was plotted. Finally, the CIBERSORT was used to analyze immune infiltration, and the Spearman correlation between immune cells and candidate genes was computed using the psych package.
Results
By intersecting the WGCNA and DEGs, the TBC1D2, SFXN, and F12 genes were identified as the key cross-talk genes between AP and MDD. The results of the LASSO analysis demonstrated that these three core genes have significant diagnostic value for AP and MDD. The results of immune infiltration analysis indicated that Macrophages M2, Macrophages M0, memory resting CD4 T cells, and memory B cells are crucially involved in the pathogenesis of AP and MDD.
Conclusion
This study represents the first attempt to investigate the genetic relationship between AP and MDD using bioinformatics tools. The TBC1D2、SFXN and F12 genes were the most important cross-talk genes between AP and MDD. Macrophages, memory resting CD4 T cells and memory B cells-driven immune responses may play an important role in the association between AP and MDD.
Exploring the Perceptions and Experiences of Mobile Teams on COVID-19 Vaccine Uptake at the Community Level: Evidence from Benue and Niger States
Authors: Isiaka Saheed Dipo , Jimoh Akolade Uthman , Samuel Olugbemisola Wuraola , Atobatele Sunday , Sampson Sidney , David Joshua Cinwonsoko , Okoye Irene , Adegoke Zubair , Daniel Victor , Nto Sunday 
Published: February 2024

Abstract

Background
After the adoption of several non-pharmaceutical measures, vaccines were developed to ameliorate the menace of the COVID-19 pandemic and improve the global population’s well-being in less than a year, resulting in the largest vaccination campaign in human history. Nigeria received nearly 4 million doses of the COVID-19 vaccine, shipped via the COVAX Facility, marking a historic step towards ensuring equitable distribution of COVID-19 vaccines globally. The NPHCDA in collaboration with implementing partners engaged ad-hoc health workers to facilitate outreaches in different communities and settlements as a strategy to optimize COVID-19 vaccination in Nigeria.
Objective
This study seeks to explore the perceptions and experiences of mobile teams in various communities during their implementation of COVID-19 vaccination.
Methods
Our study adopted an exploratory research design to acquire qualitative data from purposively selected populations in two North Central states in Nigeria. Focus Group Discussions (FDGs) were moderated among 12 mobile vaccination teams from 12 LGAs across Benue and Niger states to elicit information from participants at the Community Level.
Results
A total of 72 health workers including vaccinators, validators, EMID recorders, social mobilizers, and paper recorders participated in the study. Nearly 3 out of every 5 (58.3%) participants were female by gender, as over one-quarter (27.8%) of the study participants are National Certificate Examination (NCE) degree holders. Using the health building blocks, we found that health workers experienced challenges across service delivery, health information systems, finance, and vaccine and logistics. These challenges include misconceptions about the vaccine, requests for incentives in exchange for the vaccine, poor network services, inadequate stipends, distance to communities, lack of transportation, and vaccine stockout.
Conclusion
Our study concludes that stakeholders across all levels directly and indirectly involved in community health interventions should provide all necessary support to mobile health workers to limit their challenges.
Automated Scoring of Open-Ended Question Complexity: A Large Language Model Approach
Authors: Raz Tuval , Luchini Simone , Beaty Roger , Kenett Yoed 
Published: February 2024

Abstract

Question-asking, an essential yet often understudied activity, holds significant implications for learning, creativity, and cognitive development. In particular, the quality and complexity of the questions asked are crucial factors affecting these fields. Previous research has explored open-ended question complexity through frameworks like the Bloom taxonomy of cognitive objectives, but the measurement of complexity remains challenging. Recent advancements in natural language processing have enabled automated scoring of psychological tasks, notably predicting human ratings of creativity. Although some methods have been applied to measure question complexity, there has been scarce research so far on the automatic assessment of open-ended questions. Here, we address this gap by employing a Large Language Model (LLM) to accurately predict human ratings of open-ended question complexity based on the Bloom taxonomy and comparing these predictions to existing baseline measures such as semantic distance and word count. Specifically, this study capitalized on previously collected human-rated responses from a creative question-asking task to train an LLM for scoring questions based on the Bloom taxonomy of complexity. Our results reveal that our LLM-generated Bloom scores correlated strongly with human ratings of complexity (r = .73), whilst also greatly exceeding tested baseline measures. Our study emphasizes the significance of LLM in automating the assessment of open-ended question complexity, fostering cost-effective, automatic, and reliable measurements in this domain. Our study further highlights the exciting possibilities for the continued usage of LLM in education and psychology and their potential in helping study how we ask creative questions.
Interaction of sixth-week body weight and lay-period on egg production and quality of Coturnix coturnix japonica (Japanese quail) layers
Authors: Jesuyon Oluwatosin M. A. , Oseni Saidu O. 
Published: February 2024

Abstract

The joint influence of the 6th week body weight (point of lay) and lay-period on quail egg production and quality was investigated in Ikole, Nigeria. One hundred and eighty quail birds at six weeks, point of lay, were randomized into three body weight treatments (123-130, 131-137, 138-144, g), each treatment consisting of six replicates, of ten birds each. All replicates were fed common diets from 6th week to 15th week. Body weight, feed intake, egg production, internal and external egg quality traits were recorded throughout the period by standard experimental procedures. Data were analysed using the 2-way ANOVA procedure based on factorial treatment design, using body weight as factor-1 and lay-period (6-8, 9-11, 12-15, weeks) as factor-2 in order to generate the interaction effect. Analytical procedures included the General Linear Model (GLM), Duncan Multiple Range Test (DMRT) and regression procedures. Average body weight (ABW), egg height (EHT), egg surface area (ESA), albumen quality index (AQI), yolk quality index (YQI) and Haugh unit (HUT) were significantly (p= 0.036-0.050) influenced by interaction of 6th-week body weight and lay-period. A target minimum sexual maturity body weight target of 131g at 6th week is recommended for high egg production and breeding in tropical environment.
Case Series: Hyperbilirubinemia under elexacaftor/tezacaftor/ivacaftor in the presence of Gilbert’s syndrome
Authors: Weitzel Julia , Welsner Matthias , Taube Christian , Ballmann Manfred , Sutharsan Sivagurunathan 
Published: February 2024

Abstract
Liver-related side effects are a known complication of treatment with elexacaftor/tezacaftor/ivacaftor (ETI) for cystic fibrosis (CF). Gilbert’s syndrome is caused by a genetic mutation that reduces activity of the enzyme UDP glucuronosyltransferase 1 polypeptide A1 (UGT1A1), causing elevated levels of unconjugated bilirubin in the blood and duodenal bile. The presence of Gilbert’s syndrome and CF might represent additive risk factors for liver-related adverse events during ETI treatment. This case series describes six people with CF (pwCF) in whom previously unknown Gilbert’s syndrome was unmasked after initiation of treatment with ETI. Although all patients had some level of hepatic dysfunction and/or elevated levels of bilirubin after initiation of ETI, the clinical course varied. Only one patient had to stop ETI therapy altogether, while the others were able to continue treatment (some at a reduced dosage and others at the full recommended daily dosage). All patients, even those using a lower dosage, experienced clinical benefit during ETI therapy. Thus, Gilbert’s syndrome is not necessarily a contraindication for ETI therapy but may be a risk factor for liver-related adverse events in pwCF. This is something that physicians need to be aware of in pwCF who show liver adverse events during ETI therapy.
Development of a river DTM generation algorithm based on SfM point clouds using vegetation and morphological filters
Authors: Lee Hyeokjin , Gou Jaejun , Park Jinseok , Jang Seongju , Song Inhong 
Published: February 2024

Abstract
Developing algorithms for generating accurate Digital Terrain Model (DTM) of rivers is necessary due to the limitations of traditional field survey methods, which are time-consuming and costly and do not provide continuous data. The objective of this study was to develop an advanced algorithm for generating high-quality DTM of rivers using Structur from Motion (SfM) data. A leveling survey was conducted on four cross-sections of the Bokha stream in Icheon City, S. Korea, and SfM-based DTM was produced using the Pix4Dmapper program and Phantom 4 multispectral drone. Two vegetation filters (NDVI and ExG) and two morphological filters (ATIN and CSF) were applied to the data, and the best filter combination was identified based on MAE and RMSE analyses. The integration of NDVI and CSF showed the best performance for the vegetation area, while a single application of NDVI showed the lowest MAE for the bare area. The effectiveness of the SfM method in eliminating waterfront vegetation was confirmed, with an overall MAE of 0.299 m RMSE of 0.375 m. These findings suggest that generating DTMs of riparian zones can be achieved efficiently with a limited budget and time using the proposed methodology.
Orbitrap noise structure and method for noise-unbiased multivariate analysis
Authors: Gilmore Ian , Keenan Michael , Trindade Gustavo , Pirkl Alexander , Newell Clare , Jin Yuhong , Aizikov Konstantin , Zhang Junting , Matjacic Lidija , Arlinghaus Henrik , Eyres Anya , Havelund Rasmus , Bunch Josephine , Gould Alex , Makarov Alexander 
Published: February 2024

Abstract
Orbitrap mass spectrometry is widely used in the life-sciences. However, like all mass spectrometers, non-uniform (heteroscedastic) noise introduces bias in multivariate analysis complicating data interpretation. Here, we study the noise structure of a high-field Orbitrap mass analyzer integrated into a secondary ion mass spectrometer (OrbiSIMS). Using a stable primary ion beam to provide a well-controlled source of secondary ions from a silver sample, we find that noise has three characteristic regimes (1) at low signals the ion trap detector noise and a censoring algorithm dominate, (2) at intermediate signals counting noise specific to the SIMS emission process is most significant and has Poisson-like statistical properties, and (3) at high signal levels other sources of measurement variation become important and the data are overdispersed relative to Poisson. We developed a generative model for Orbitrap-based mass spectrometry data that directly incorporates the number of ions and accounts for the noise distribution over the entire intensity range. We find, for silver ions, a detection limit of 3.7 ions independent of ion generation rate. Using this understanding, we introduce a new scaling method, termed WSoR, to reduce the effects of noise bias in multivariate analysis and show it is more effective than the most common data preprocessing methods (root mean scaling, Pareto scaling and log transform) for the simple silver data. For more complex biological images with lower signal intensities the WSoR, Pareto and root mean scaling methods have similar performance and are significantly better than no scaling or, especially, log transform.
Population genetic diversity analyses reveal the determinants of genetic variation of banana endogenous virus sequences in China
Authors: Chen Huazhou , Li Huaping , Rao Xue Qin 
Published: February 2024

Abstract
Banana (Musa spp.) is an economic crop in tropical and subtropical areas, especially in South China. Banana streak virus (BSV) is one of the most important viruses infecting bananas. Banana endogenous virus sequences (BEVs) from badnavirus ancestors are widely present in various bananas. However, the determinants of genetic variation of BEVs are poorly understood. To elucidate the genetic diversity of BEVs, we obtained hundreds of BEVs from different bananas. These BEVs were belonged to Clade II and divided into 26 different BEVs groups. Ten groups were chosen to analyze the genetic diversity of BEVs populations. The results revealed that each BEVs population had an Hd value of 1.0 and a Pi value of more than 0.005 of nucleotide diversity, indicating that there was a great genetic diversity among these BEVs populations. The analyses of genetic variation of various BEVs populations showed that BEV UF populations were the most variable, while BEV GZ20 populations were the most conserved, suggesting that different BEVs populations had different evolutionary rates. Purifying selection, evolutionary rate, and base transition contributed to genetic variation of BEVs populations. Additionally, two recombination events were found in BEV GZ6 populations. This study provided a theoretical basis for further research on the functions and integration mechanisms of BEVs.
Causal Effects of 1400 Blood Metabolites And Sleep Disorders: A Mendelian Randomization Study
Authors: ma zhen , min zhao , huanghong zhao , Qu Nan 
Published: February 2024

Abstract
Background: There is growing evidence that sleep disorders (SD) affect changes in the body's metabolic microbiota, such as serum levels of glucose, lipid metabolites, insulin, adrenaline, and cortisol, which are all modified by sleep. However, the causal relationship between these serum metabolites and SD remains undetermined.
Methods: A comprehensive two-sample Mendelian randomization (MR) study was performed to investigate the causal relationship between blood microbiota characteristics and SD. Additionally, reverse MR analyses were performed to mitigate the effects of reverse causality, genetic correlation, and linkage disequilibrium (LD). Moreover, the screened significant metabolites were further examined in an additional dataset. Finally, potential metabolic pathways associated with SD were exposed by enrichment analysis.
Results: In a survey of 1400 metabolites, 201 exhibited statistical significance (P<0.05) in an inverse variance weighted (IVW) model. Among these, 18 known metabolites and four unknown metabolites were found to be significantly associated with SD (PFDR<0.05), with six of them being validated in the validation set. Enrichment analysis revealed the involvement of five typical metabolites in 23 central metabolic pathways (P<0.05). Notably, glycine, D-lysine, cyclic adenosine monophosphate, guanosine, and arachidonic acid could serve as key markers based on their roles in the pathways, disease characterization prediction, and localization. Furthermore, inverse Mendelian randomization analysis indicated that six known metabolites and three unknown metabolites were significantly associated with SD (PFDR<0.2), and these metabolites were implicated in 15 core metabolic pathways (P<0.05). Among them, cortisone, cortisol, N-acetyl-L-aspartic acid, and arachidonic acid played crucial roles. These findings provide novel insights for early screening, prevention, and treatment of SD.
Conclusions:This study reveals the potential relationship between blood microbiota and SD using a two-sample Mendelian randomization approach, and the findings provide new insights into the role of genetic exposure interactions in the development of SD.
Physio-biochemical responses and crop performance analysis in chickpea upon botanical priming
Authors: Kaushal Kamini , Rajani Kumari , Kumar Ravi Ranjan , Kumar Anand , Ranjan Tushar , Kumar Vinod , Ahmad Feza , Kumar Vikash , Kumar Aman 
Published: February 2024

Abstract

Chickpea is a highly nutritious protein-rich source and one of the major crops to alleviate global malnutrition. It is the third-largest legume cultivated globally in arid and semi-arid environments. Chickpea productivity is affected by several factors, among which poor seed quality is one of the significant factors contributing to its decrease in productivity. Seed quality is essential for better crop establishment and higher yields, particularly in the uncertain climate change. The present study investigated the role of botanical priming in enhancing seed quality by investigating physio-biochemical responses and crop performance in chickpeas. The study compared the effects of botanical priming with hydropriming, seed treatment with bavastin and control on medium-vigour chickpea seeds. A detailed physiological (germination percentage, root and shoot length, vigour index) and biochemical (amylase, protease, dehydrogenase, phytase, and lipid peroxidation) analysis was carried out in the laboratory to assess the effect of priming treatments. SDS-PAGE was used to compare seed storage protein expression in primed and control seeds. Seeds treated with 1% turmeric leaf extract displayed a higher germination rate (94.5%) than the control and other priming treatments. Turmeric-primed seeds showed higher seedling length, vigour index, enzyme activity, and lower MDA content. SDS-PAGE analysis revealed the expression of two minor polypeptides of the albumin and three minor polypeptides of the globulin subunit. Moreover, field experiments indicated increased crop growth, vigour, and days to 50% flowering, yield and its attributing traits in turmeric-primed seeds. The study demonstrates that botanical priming can increase the yield of chickpeas by up to 16% over the control group. This study proves that implementing low-cost and eco-friendly seed priming techniques can significantly enhance the genetic potential of chickpeas by improving their physiological and biochemical activities during seed germination and crop growth. Therefore, chickpea growers must adopt botanical priming techniques to improve seed quality and crop performance. This study unequivocally establishes the efficacy of botanical priming as a powerful tool for augmenting chickpea growth. Moreover, this approach is environmentally sustainable and can help conserve natural resources long-term. Therefore, this new approach must be widely adopted across the agricultural industry to ensure sustainable and profitable farming practices.
Modelling and Analysis of Malaria and Ebola Co-Infection Dynamics: Insights, Implications, and Future Perspectives
Authors: Francis John Saqware , Mofi Hawa Omary , Leandry Leonce 
Published: February 2024

Abstract
Background: Malaria and Ebola co-infection refers to the simultaneous presence of the malaria parasite (Plasmodium) and the Ebola virus within an individual's body.
Methodology: This study establishes an epidemiological model employing non-linear differential equations to assess disease transmission via the reproduction number R0, stability, and sensitivity analysis. The conclusion is that the disease-free equilibrium point exists at specific values and is locally asymptotically stable when the reproduction number R0 is less than one, while globally stable under the same conditions.
Results: Sensitivity analysis indicates that parameters such as 'a', 'μh', 'γD', and 'βD' have a substantial impact on the reproduction number. The simulated results highlight that increased contact between individuals infected with malaria and Ebola amplifies co-infection rates. Furthermore, increased contact between malaria-infected individuals and deceased Ebola patients, increased mosquito bite rates ('a'), and the probability of transmission from infected mosquitoes to susceptible humans ('b') all contribute to increased malaria and Ebola co-infections.
Conclusion and future work: The model's capabilities include forecasting total infected cases, mortality rates, and providing information on the spread of the co-infection. Recommendations involve environmental alterations to achieve a disease-free state. Future work entails extending the model by introducing treatment or prevention compartments to address individuals with co-infections of Ebola and malaria. This research significantly contributes to understanding co-infection dynamics, emphasising the need for strategic measures to mitigate the spread and impact of malaria and Ebola co-infections.