bluuebunny/crossref_metadata_2025_split huggingface dataset:
Foraging strategies of two dominant native ant species associated with Toxoptera aurantii (Hemiptera, Aphididae) on cocoa trees in Centre Region of Cameroon
Authors: Ndzie Paul Arnaud Mballa 
Published: October 2024

Abstract

Mutualism between ants and Hemiptera is well known on specific plant species. Cocoa is a tree-crop with a high economic value and harbour many ant-tending hemipteran species causing damage on shade trees. Herein, we examined the foraging strategies including frequency of ant activity, palpation and honeydew collection patterns used by local ants Myrmicaria opaciventris and Pheidole megacephala associated with Toxoptera aurantii. Field investigations were conducted from january to december 2022 in five locations in Centre Cameroon. At each location, one plot (0.25 ha) containing cocoa trees were monthly selected. Within each plot, only plants showing association between the target local ants and T. aurantii were investigated for our experiment. The overall number of local ants attending hempiterans was counted, and the palpation and honeydew collection duration were determinate following three time bands (8 a.m to 10 a.m; 12 a.m to 2 p.m; 4 p.m to 6 p.m). A total of 20,189 workers (13,015 individuals of M. opaciventris and 7,174 individuals of P. megacephala) was recorded associated with T. aurantii. Myrmicaria opaciventris foraged twice than P. megacephala at different time bands. In both ants, the highest number of workers was recorded between 8 a.m to 10 a.m and the lowest between 12 a.m to 2 p.m. All ants foraging on cocoa trees did not participate in palpation and honeydew collection activities. foraging strategies used by M. opaciventris appear more efficient and detrimental to cocoa growing. There is an urgent need to develop control strategies to reduce their populations and preserve cocoa-agrosystems.
Prediction of the risk of adverse clinical outcomes with machine learning techniques in patients with chronic no communicable diseases
Authors: Hernández-Arango Alejandro , Arias María Isabel , Pérez Viviana , Chavarría Luis Daniel , Jaimes Fabian 
Published: October 2024

Abstract

Background
Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variables based on artificial intelligence requires scientific validation in different populations to optimize the use of limited human, financial, and clinical resources in healthcare systems worldwide.
Methods
In this cohort study, a prediction model was derived by evaluating two algorithms, XGBoost and Elastic Net logistic regression, for three outcomes - mortality, hospitalization, and emergency department visits - to build a clinical decision support system for patients with non-communicable chronic diseases at the Alma Mater Hospital complex in Medellin, Colombia.
Results
We collected 4845 electronic medical record entries from 5000 patients included in the study. The median age was 71.83 years, with 63.8% women and 29.7% receiving home care. The most prevalent medical conditions were diabetes (52.9%), hypertension (67.2%), dyslipidemia (57.3%), and COPD (19.4%). For the mortality outcome, the Elastic Net logistic regression model had an AUCROC of 0.88 (95% CI, 0.8032 to 0.9032), and the XGBoost model had an AUCROC of 0.912 (95% CI, 0.8802 to 0.9437). For the hospitalization outcome, the Elastic Net logistic regression model had an AUCROC of 0.967 (95% CI, 0.957 to 0.9763), while the XGBoost model had an AUCROC of 0.976 (95% CI, 0.9661 to 0.985). For the emergency department visit outcome, the Elastic Net logistic regression model had an AUCROC of 0.930 (95% CI, 0.9158 to 0.945), while the XGBoost model had an AUCROC of 0.982 (95% CI, 0.9755 to 0.9891). We created a dashboard as to interact with the model, segmenting risk in the cohort.
Conclusions
A clinical decision support system based on artificial intelligence using electronic medical records possibly can help segmenting the risk in populations with chronic diseases for effective decision-making.
Glucocorticoid Receptor Expression in Torus Tubarius Hypertrophy Tissue Causing Secretory Otitis Media in Children
Authors: Teng Zhi-pan , Li Qi , Shen Xiao-fei 
Published: October 2024

Abstract

Backgrounds: Torus tubarius hypertrophy (TTH) after adenoidectomy causing nasal obstruction, recurred snoring, sleep apnea, or mouth breathing has been reported more and more recently, partial resection of TTH conducted by a low-temperature plasma technique is a safe and effective therapy, and some benefit from intranasal steroid therapy. However, the expression of glucocorticoid receptor (GCR) in TTH tissue is currently unknown and no paper reported secretory otitis media caused by TTH.
Objectives: To assess the expression patterns of the human GCR in TTH tissue in children with adenoidectomy.
Methods: 5 children from Jan to Jun 2024 were included in this study. All children underwent partial resection of TTH, and TTH tissues were collected for immunofluorescence.
Results: GCR-α and GCR-β were both expressed in TTH tissues in 5 children, the expression of GCR-α was significantly higher than GCR-β. Since it has been reported that the high expression of GCR-α is correlated to glucocorticoid therapy sensitivity, the glucocorticoid therapy may be curative to TTH in children.
Conclusions: TTH after adenoidectomy were reported more often in recently, partial resection of TTH operation conducted by a low-temperature plasma technique under general anesthesia is a safe and effective therapy, intranasal corticosteroids could be a alternative solution of TTH. However the function of GCR in children with TTH still requires further investigation.
Bioinformatics approach to explore the common pathogenic genes between lumbar disc degeneration and osteoarthritis
Authors: Lu Huigen , Zhu Weiguo , Shen Yingying , Ye Zhaoming , Chen Weishan 
Published: October 2024

Abstract

Background
Osteoarthritis (OA) and lumbar disc degeneration disease (IDD) are both degenerative and chronic inflammatory diseases that directly and profoundly impact human quality of life and medical services.
Methods
To better understand how IDD is related to OA, we used transcriptomic and single-cell analysis to look for molecular and cellular overlaps between the two diseases in this work. Two gene expression profiles (GSE124272 and GSE55235) from the Gene Expression Omnibus database are downloaded to detect common differentially expressed genes (DEGs) for OA and IDD diseases to find similar pathways, possible medicines, and regulatory networks. The single-cell transcriptome of synovial tissues sequenced from OA patients was analyzed for the immune characteristics of the shared DEGs.
Results
Based on RNA-seq datasets, 184 DEGs shared by these two diseases were found. 114 hub genes were then identified using degree and Matthew's correlation coefficient algorithms based on creating the Protein-protein interactions network. Interactions between transcription factors and shared hub genes, coregulatory networks between miRNAs and these hub genes, and protein-drug interactions were found. Moreover, scRNA-seq of cells of synovial tissues from OA patients revealed that 30 of these hub genes were highly enriched in the inflammatory macrophages (IL1B+Mac). Finally, CSF1 and S100A12 were identified as potential biomarkers by machine learning, and their area under the curve in IDD and OA is greater than 0.7 by the receiver operating characteristic curve analysis.
Conclusions
IDD might contribute to the advancement of OA by inciting cytokine storms, thereby enhancing comprehension and treatment strategies for OA patients accompanied by IDD. Moreover, the identified candidate drugs, DEG-regulated networks, and potential diagnostic genes (CSF1 and S100A12) offer promising therapeutic avenues for addressing both conditions.
Mutation of a gene with PWWP domain confers salt tolerance in rice
Authors: Seo Hyeon Ung , Jang Cheol Seong 
Published: October 2024

Abstract

Salinity is a major problem due to the continuous increase in the salinization of agricultural lands, particularly, paddy fields. Using a forward genetics approach, salt-insensitive TILLING (targeting-induced local lesions in genomes) line 3, sitl3, was selected from a core population induced by gamma-ray irradiation. Under salt stress, sitl3 had greater fresh weight and chlorophyll content, and lower H2O2 and Na+ contents than the wild-type. In the gene (LOC_Os07g46180) with two PWWP domains (OsPWWP4) of sitl3, a premature stop was caused by an SNP, and was named OsPWWP4p.Gly462* (a stop gain occurred from the 462th amino acid residue). The OsPWWP4 and substrate proteins (OsEULS2, OsEULS3, and OsEULD2) were identified using yeast two-hybrid, bimolecular fluorescence complementation, in vitro pull-down, and in vitro methyltransferase assays. Subcellular localization of OsPWWP4 and OsPWWP4p.Gly462*GFP-tagged proteins revealed they were both localized in the nucleus, while OsEULS2, OsEULS3, and OsEULD2 GFP-tagged proteins were found in the nucleus and cytosol of rice protoplasts. The expression levels of OsEULS2, OsEULS3, OsEULD2 under salt stress were higher in sitl3 than in wild-type plants. In contrast, OsPWWP4 expression was higher in the latter. Genes involved in the salt overly sensitive (SOS) pathway showed higher expression in the aerial tissues of silt3 than in the wild-type. Our data suggest that TILLING line sitl3 is a valuable genetic resource for understanding protein post-translational regulation-related salinity tolerance mechanisms such as methyltransferase activities, and for improving salt tolerance in rice through breeding.
Development of prediction models and predictors analysis for axial neck pain in patients undergoing cervical laminoplasty based on machine learning
Authors: Fan Xiao , Zhou Shuai , Li Lvxue , Zhou Feifei 
Published: October 2024

Abstract

Background
Axial neck pain (ANP) is one of the most common complications after cervical laminoplasty, leading to severe pain, disability and economic loss. By predicting patient outcomes pre-operatively, patients undergoing cervical laminoplasty can benefit from more accurate patient care strategies. However, predicting postoperative ANP is challenging. The aim of this study was to develop a machine learning model to predict at the individual level whether a patient experiences postoperative ANP and to reveal baseline predictors of persistent neck pain after laminoplasty.
Methods
This retrospective study includes 1982 patients. The population characteristics, clinical symptoms and signs, imaging features and preoperative scale of patients were retrospectively collected as input variables. The outcome measure was whether the patient achieved minimal clinically significant difference (MCID) in the visual analogue scale (VAS) score for postoperative ANP. Models were trained and optimized by process of machine learning (ML), including feature engineering, data pre-processing, and 8:2 training/validation-testing split of datasets. The feature-reduced model was established afterwards, and its performance and feature importance were evaluated through internal and external testing.
Results
Among the models generated by 45 features, XGBoost model yielded the highest AUROC of 0.7631 (95% CI, 0.7221–0.8051). Age, preoperative mJOA score, VAS score, SF36-body pain, SF36-mental health, SF36-role emotional, SF36-physiological function, lower limb weakness, and positive Hoffmann’ sign were selected as input features to build the feature-reduced model. In both internal and external testing of the feature-reduced models, model of Logistic_Regression algorithms reached the best performance, with AUROC of 0.9047 (95% CI, 0.8633–0.9406) for internal testing and 0.9200 (95% CI, 0.8678–0.9676) for external testing.
Conclusion
In this study, models for predicting the progress of postoperative ANP based on machine learning were established. The Logistic Regression model had a good ability to predict ANP progression of CSM patients and achieved best performance in a multicenter independent testing cohort. Feature importance analysis revealed key baseline predictors of postoperative ANP. This study proved that the potential of ML to predict the progress of ANP after cervical laminoplasty was significant, providing research basis for the training of machine learning models with larger samples and more features in the future.
Integrative Metabolomic-Proteomic Analysis Uncovers a New Therapeutic Approach in Targeting Rheumatoid Arthritis
Authors: Agnihotri Prachi , Saquib Mohd , Joshi Lovely , Malik Swati , Chakraborty Debolina , Sarkar Ashish , Kumar Uma , Biswas Sagarika 
Published: October 2024

Abstract

Objective: Rheumatoid arthritis (RA) is a chronic inflammatory condition that, despite available approaches to manage the disease, lacks an efficient treatment and timely diagnosis. Using the most advanced omics technique, metabolomics and proteomics approach, we explored varied metabolites and proteins to identify unique metabolite-protein signatures involved in the disease pathogenesis of RA.
Methods: Untargeted metabolomics (n=20) and proteomics (n=60) of RA patients’ plasma were carried out by HPLC/LC-MS/MS and SWATH, respectively and analyzed by Metaboanalyst. The targets of metabolite retrieved by PharmMapper were matched with SWATH data, and joint pathway analysis was carried out. An in-vitro study of metabolites in TNF-α induced SW982 cells was conducted by Western, RT-PCR, scratch, and ROS scavenging assay. The effect of GUDCA was also evaluated in the CIA rat model.
Results: A Total of 82 metabolites and 231 differential proteins were revealed. Porphyrin and chlorophyll pathway and its metabolite Glycoursodeoxycholic acid (GUDCA) was significantly altered. In vitro analysis has shown that GUDCA reduces inflammation thus offering protection against ROS production and cell proliferation. PharmMapper analysis revealed that GUDCA was significantly linked with identified SWATH proteins insulin like growth factor-1(IGF1), and Transthyretin (TTR) and it upregulates the expression of IGF1 and downregulates the expression of TTR in both in vitro and in vivo models.
Conclusion: GUDCA was found to possess antioxidative, antiproliferative properties and an effective anti-inflammatory property at a low dosage. It may be considered as a potential therapeutic option for reducing the inflammatory parameters associated with RA.
Application Trends and Research Hotspots of Endoscopic Enucleation of the Prostate: A Bibliometric and Visualization Analysis
Authors: Lan Xiao-Da , Yu Zhuo-Yang , Jiang Rui , Li Zhi-Cun , Yang Lei , Zhang Kai , Meng Yi-Sen , Zhang Qian 
Published: October 2024

Abstract

Purpose: Endoscopic enucleation of the prostate (EEP) is a preferred treatment for benign prostatic hyperplasia (BPH). Our bibliometric analysis aims to analyze the application trends and research hotspots of EEP.
Methods: We conducted a bibliometric analysis of publications indexed in the Web of Science Core Collection published from 1989 to 2023. The following techniques were examined in the included articles: holmium laser enucleation of the prostate (HoLEP), thulium laser enucleation of the prostate (ThuLEP), bipolar/monopolartransurethral enucleation of the prostate (b-TUEP/m-TUEP), GreenLight laser enucleation (GreenLEP), and diode laser enucleation (DiLEP). VOSviewer, CiteSpace, the R package ‘bibliometrix’ were used to conduct bibliometric analysis.
Results: This analysis of 739 English-language studies showed that there has been a steady increase in EEP-related publications over time. HoLEP was the most commonly studied technique, followed by ThuLEP and b-TUEP. There has been a notable lack of high-quality randomized controlled trials (RCTs) examining GreenLEP, DiLEP and m-TUEP. China, the United States, and Germany were the countries with the highest numbers of relevant publications. We identified several authors who have made significant contributions to the field. Recent research hotspots include postoperative transient urinary incontinence (TUI) and robot-assisted simple prostatectomy (RASP).
Conclusions: EEP is gaining widespread clinical acceptance as a method to treat BPH. Future research should address the lack of high-quality RCTs and focus on reducing the incidence of postoperative TUI. Prospective comparisons between RASP and EEP are essential to optimize surgical approaches for treating BPH.
Evaluating the Mental Health Impacts of parents during the Adjustment of China’s Pandemic Policy: Roles of Socioeconomic Factors, Existing COVID-19 Experiences, and Lifestyles
Authors: Deng Xinmei , Liu Xuan 
Published: October 2024

Abstract

In December 2022, China announced easing measures for COVID-19 as part of a pandemic policy adjustment. Uncertainty following adjustment and widespread infection had negative impacts on parents' mental health. In the present study, we aimed to evaluate the impact of policy change on mental health and identify risk and protective factors linked to parental mental health outcomes in the context of pandemic policy change and widespread public infection. During the first three weeks following the policy adjustment, a sample of 2385 Chinese parents' demographic data, infection conditions, preexisting COVID-19 experiences, perceived impacts, lifestyles, and mental health conditions (anxiety, depression, and parenting stress) were examined. The results revealed that 92.8% of the parents experienced infection after the policy adjustment. After the policy adjustment, parents with worse mental health conditions were linked to younger parents, lower social status scores, lower household income, and more children, and mothers. Parents who were classified as medium to high risk for COVID-19 reported higher levels of depression and felt that policy adjustment had more negative impacts. Quarantined parents experienced less depression, anxiety, and parenting stress. As a protective factor, greater sleep duration was associated with lower levels of depression, anxiety, and parenting stress, as well as more positive perceived impacts of policy adjustment among Chinese parents. Our findings support policy efforts that aid families with socioeconomic disadvantages and unfavorable prior COVID-19 experiences, and that have wide-ranging impacts on Chinese parents related to the adjustment of the COVID-19 pandemic policy. Our findings also imply that parents can support their own physical and mental health during a public mental health crisis by providing enough sleep, which is a straightforward yet effective strategy.
Influence of Fat on Hepatic T2 Relaxation Time Estimation: A Preliminary Investigation
Authors: Kemp Justine , Manhard Mary Kate , Tkach Jean A. , Prasanphanich Adam , Trout Andrew , Dillman Johnathan , Pednekar Amol 
Published: October 2024

Abstract

PURPOSE:
To examine the influence of fat content on hepatic T2 estimation through T2 mapping without and with fat suppression.
MATERIALS AND METHODS:
This prospective IRB-approved study included participants without known liver disease (controls), with hepatic steatosis (proton density fat fraction [PDFF] >6%), or with fibrotic (> 3kPa) liver from other chronic liver diseases. Imaging at 1.5T included a quantitative 3D chemical shift encoded six-echo radiofrequency spoiled gradient echo MRI sequence (mDIXON Quant) for PDFF estimation, nine-echo 2D gradient and spin echo (GRASE) for T2 estimation, and nine-echo 2D GRASE with fat suppression for water-specific T2 (wT2) estimation.
A single blinded observer traced a large freehand region-of-interest (ROI) in the right hepatic lobe on the T2 and wT2 maps, and a circular ROI on the PDFF map. Consistency and agreement of T2 and wT2 estimates were assessed using linear regression, intra-class correlation coefficients (ICC), and Bland-Altman analysis. Pearson’s correlation evaluated the relationship between differences in hepatic T2 and wT2 estimates and PDFF.
RESULTS:
A total of 21 participants (7 controls, 9 with hepatic steatosis, 5 with other liver diseases) with a mean age of 18.4±4.7 years (range: 9-27 years; 9 males) were included. Estimated liver PDFF ranged from 2% to 34% (median 4%, IQR 7.5%). T2 estimates (57±7.3 ms [range: 44.5-70.5 ms]) were significantly longer (p=0.0085) compared to wT2 estimates (52.5±8 ms [range: 43-69.7 ms]) with moderate agreement (ICC = 0.57 [95% CI: 0.19 - 0.80]).
For participants with hepatic steatosis, T2 estimates were significantly longer than wT2 estimates (p=0.0063) with poor agreement (ICC=0.06 [95% CI: -0.59 – 0.67]). Participants without hepatic steatosis showed comparable T2 and wT2 estimates (p=0.3577, p=0.3954) with excellent agreement (ICC = 0.99 [95% CI: 0.96 - 0.99]). The relative bias of T2 to wT2 was very strongly correlated with PDFF (r2 = 0.95), increasing by 0.8 ms (1.22%) for every 1% rise in PDFF.
CONCLUSION:
Liver fat content proportionally increases estimated T2, potentially confounding the quantification of changes in T2 that can be attributed to alteration in tissue water content.
Determination of atmospherically deposited microplastics in moss samples
Authors: Wenzel Mike , Fischer Björn , Wolf Carmen , Kube Christine , Nickel Stefan , Dreyer Annekatrin , Völksen Barbara , Schröder Winfried , Renner Gerrit , Schram Jürgen , Schmidt Torsten C. , Tuerk Jochen 
Published: October 2024

Abstract

Background
Standardized methods for sampling and detection of atmospherically deposited microplastics are lacking. Contrary to that, the use of moss as a biomonitoring system was established concerning other atmospheric pollutants, such as heavy metals and persistent organic pollutants. Only a few research groups actually focus on detecting atmospherically deposited microplastics in moss. In general, the determination of microplastics in environmental samples is commonly performed using a particle-based or mass-based analytical approach. However, a dearth of mass-based investigations is noticeable, especially for atmospherically deposited microplastics. Given this background, this study shows the determination of atmospherically deposited microplastics in moss utilizing thermal extraction desorption gas chromatography-mass spectrometry (TED-GC-MS) and Raman microspectroscopy (µRaman) to acquire both information. The moss samples analyzed were collected as part of the German moss survey 2020/2021, supported by the German Environment Agency. Three distinct sampling sites were investigated, which could be categorized based on their distances from potential emission sources.
Results
Concerning µRaman analysis, most microplastic particles could be determined within a 10 to 100 µm size range. Further, most microplastic aspect ratios were determined in a range of 0.25 to 1.00, indicating a fragmental shape. Additionally, a correlation between the number of microplastic particles determined and the distance of the potential emission source was observable. It was determined to be 688, 474, and 248 particles per sampling site with a distance of 150 m, 225 m, and 360 m. Both analytical approaches (TED-GC-MS & µRaman) concurred in identifying the polymer types (polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET)) in the moss samples. Concerning TED-GC-MS, 7 to 111 µg/g could be determined, depending on the polymer types and distance to the potential emission source.
Conclusion
µRaman and TED-GC-MS investigations demonstrated correlations between microplastic particle numbers, size, types, and mass concentrations with the distance of the potential emission source. The investigation corroborates the mutual complementarity of both analytical approaches, enabling more comprehensive information on samples.