bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adjustment problem and associated factors among first-year undergraduates at Wollo University, Ethiopia
Authors: Anbesaw Tamrat , Beyene Abeba , Kefale Jerusalem 
Published: September 2022

BackgroundAdjustment problems are characterized by a maladaptive emotional response to a stressful event among fresh first-year students. In Ethiopia, there is limited evidence about the adjustment problem and its determinant factors among undergraduates. Therefore, the present study aimed to assess the prevalence of adjustment problems and associated factors among first-year undergraduates at Wollo University, Dessie, Ethiopia.MethodsAn institutional-based cross-sectional study design was conducted from February 1–20, 2020. A systematic random sampling technique was employed to select the study participants. The resultant adjustment problem was assessed using the student adjustment to college questionnaire (SACQ). Data were analyzed using SPSS version 26. Logistic regression analysis was performed, and variables with a p-value of &lt;0.05 were taken as statistically significant with adjustment problems.ResultsThe prevalence of adjustment problems among first-year undergraduates were found to be 41.4% (95% CI (35.8, 46.9). Students whose hometowns were far (&gt;901 km) from the university, monthly pocket money ≤1,000 ETB, being away from family/home for the first time, and facing great difficulty living in a dormitory were significantly associated with adjustment problems among university students.ConclusionThe prevalence of adjustment problems among Wollo University students was high and positively associated with students' hometowns being far (&gt;901 km) from the university, having monthly pocket money, being away from family/home for the first time, and facing great difficulty in living in a dormitory. Therefore, establishing adjustment problem screening services on the campus and designing proper mental health intervention programs are recommended to tackle the problem.
Statistical analysis of precipitation variations and its forecasting in Southeast Asia using remote sensing images
Authors: Syed Alishbah , Zhang Jiquan , Rousta Iman , Olafsson Haraldur , Ullah Safi , Moniruzzaman Md , Zhang Hao 
Published: September 2022

The Climate Hazard Group InfraRed Precipitation with Stations (CHIRPS) dataset was examined for its variability and performance in explaining precipitation variations, forecasting, and drought monitoring in Southeast Asia (SEA) for the period of 1981–2020. By using time-series analysis, the Standardized Precipitation Index (SPI), and the Autoregressive Integrated Moving Average (ARIMA) model this study established a data-driven approach for estimating the future trends of precipitation. The ARIMA model is based on the Box Jenkins approach, which removes seasonality and keeps the data stationary while forecasting future patterns. Depending on the series, ARIMA model annual estimates can be read as a blend of recent observations and long-term historical trend. Methods for determining 95 percent confidence intervals for several SEA countries and simulating future annual and seasonal precipitation were developed. The results illustrates that Bangladesh and Sri Lanka were chosen as the countries with the greatest inaccuracies. On an annual basis, Afghanistan has the lowest Mean Absolute Error (MAE) values at 33.285 mm, while Pakistan has the highest at 35.149 mm. It was predicted that these two countries would receive more precipitation in the future as compared to previous years.
Enhancer-associated regulatory network and gene signature based on transcriptome and methylation data to predict the survival of patients with lung adenocarcinoma
Authors: Huang Shihao , Chen Shiyu , Zhang Di , Gao Jiamei , Liu Linhua 
Published: September 2022

Accumulating evidence has proved that aberrant methylation of enhancers plays regulatory roles in gene expression for various cancers including lung adenocarcinoma (LUAD). In this study, the transcriptome and methylation data of The Cancer Genome Atlas (TCGA)-LUAD cohort were comprehensively analyzed with a five-step Enhancer Linking by Methylation/Expression Relationships (ELMER) process. Step 1: 131,371 distal (2 kb upstream from the transcription start site) probes were obtained. Step 2: 10,665 distal hypomethylated probes were identified in an unsupervised mode with the get.diff.meth function. Step 3: 699 probe-gene pairs with negative correlations were screened using the get.pair function in an unsupervised mode. Step 4: After mapping with probes, 768 motifs were obtained and 24 of them were enriched. Step 5: 127 transcription factors (TFs) with differential expressions and negative correlations with methylation levels were screened, which were corresponding to 21 motifs. After the ELMER process, a prognostic “TFs-motifs-genes” regulatory network was constructed. The Least absolute shrinkage and selection operator (LASSO) and Stepwise regression analyses were further applied to identify variables in the TCGA-LUAD cohort and an eight-gene signature was constructed for calculating the risk score. The risk score was verified in two independent validation cohorts. The area under curve values of receiver operating characteristic curves predicting 1-, 3-, and 5-years survival ranged from 0.633 to 0.764. With the increase of the risk scores, both the survival statuses and clinical traits showed a worse tendency. There were significant differences in the degrees of immune cell infiltration, TMB values, and TIDE scores between the high-risk and low-risk groups. Finally, a better-performing prognostic nomogram was integrated with the risk score and other clinical traits. In short, this multi-omics analysis demonstrated the application of ELMER in analyzing enhancer-associated regulatory network in LUAD, which provided promising strategies for epigenetic therapy and prognostic biomarkers.
A nine–consensus–prognostic –gene–based prognostic signature, recognizing the dichotomized subgroups of gastric cancer patients with different clinical outcomes and therapeutic strategies
Authors: Ji Dan , Yang Yang , Zhou Fei , Li Chao 
Published: September 2022

Background: The increasing prevalence and mortality of gastric cancer (GC) has promoted the urgent need for prognostic signatures to predict the long-term risk and search for therapeutic biomarkers.Methods and materials: A total of 921 GC patients from three GEO cohorts were enrolled in the current study. The GSE15459 and GSE62254 cohorts were used to select the top prognostic gene via the evaluation of the area under the receiver operating characteristic (ROC) curve (AUC) values. The GSE84437 cohort was used as the external validation cohort. Least absolute shrinkage and selector operation (LASSO) regression analysis was applied to reduce the feature dimension and construct the prognostic signature. Furthermore, a nomogram was constructed by integrating the independent prognostic analysis and validated by calibration plot, decision curve analysis and clinical impact curve. The molecular features and response to chemo-/immunotherapy among risk subgroups were evaluated by the “MOVICS” and “ESTAMATE” R packages and the SubMap algorithm. Lauren classification and ACRG molecular subtype were obtained to compare with the risk model.Results: Forty-four prognosis-associated genes were identified with a preset cutoff AUC value of 0.65 in both the GSE62254 and GSE15459 cohorts. With the 10-fold cross validation analysis of LASSO, nine genes were selected to construct the nine-consensus-prognostic-gene signature. The signature showed good prognostic value in the GSE62254 (p &lt; 0.001, HR: 3.81, 95% CI: 2.44–5.956) and GSE15459 (p &lt; 0.001, HR: 2.65, 95% CI: 1.892–3.709) cohorts and the external validation GSE84437 cohort (p &lt; 0.001, HR: 2.06, 95% CI: 1.554–2.735). The nomogram constructed based on two independent predictive factors, tumor stage and the signature, predicted events tightly consistent with the actual (Hosmer–Lemeshow p value: 1-year, 0.624; 3-years, 0.795; 5-years, 0.824). For the molecular features, we observed the activation of apical junction, epithelial mesenchymal transition, and immune pathways in the high-risk group, while in the low-risk group, cell cycle associated G2M, E2F and MYC target pathways were activated. Based on the results we obtained, we indicated that gastric patients in the low-risk group are more suitable for 5-fluorouracil therapy, while high-risk group patients are more suitable for anti-CTLA4 immunotherapy, these results need more support in the further studies. After compare with proposed molecular subtypes, we realized that the nine-consensus prognostic gene signature is a powerful addition to identify the gastric patients with poor prognosis.Conclusion: In summary, we constructed a robust nine-consensus-prognostic-gene signature for the prediction of GC prognosis, which can also predict the personalized treatment of GC patients.
Revealing the novel ferroptosis-related therapeutic targets for diabetic foot ulcer based on the machine learning
Authors: Wang Xingkai , Jiang Guidong , Zong Junwei , Lv Decheng , Lu Ming , Qu Xueling , Wang Shouyu 
Published: September 2022

Objectives: DFU is a serious chronic disease with high disability and fatality rates, yet there is no completely effective therapy. While ferroptosis is integrated to inflammation and infection, its involvement in DFU is still unclear. The study aimed to identify ferroptosis-related genes in DFU, providing potential therapeutic targets.Methods: In the GEO database, two DFU microarray datasets (GSE147890 and GSE80178) were collected. WGCNA was conducted to identify the modular genes most involved in DFU. Subsequently, enrichment analysis and PPI analysis were performed. To yield the DFU-associated ferroposis genes, the ferroposis genes were retrieved from the FerrDb database and overlapped with the modular genes. Eventually, an optimal DFU prediction model was created by combining multiple machine learning algorithms (LASSO, SVM-RFE, Boruta, and XGBoost) to detect ferroposis genes most closely associated with DFU. The accuracy of the model was verified by utilizing external datasets (GSE7014) based on ROC curves.Results: WGCNA yielded seven modules in all, and 1223 DFU-related modular genes were identified. GO analysis revealed that inflammatory response, decidualization, and protein binding were the most highly enriched terms. These module genes were also enriched in the ErbB signaling, IL-17 signaling, MAPK signaling, growth hormone synthesis, secretion and action, and tight junction KEGG pathways. Twenty-five DFU-associated ferroposis genes were obtained by cross-linking with modular genes, which could distinguish DFU patients from controls. Ultimately, the prediction model based on machine learning algorithms was well established, with high AUC values (0.79 of LASSO, 0.80 of SVM, 0.75 of Boruta, 0.70 of XGBoost). MAFG and MAPK3 were identified by the prediction model as the most highly associated ferroposis-genes in DFU. Furthermore, the external dataset (GSE29221) validation revealed that MAPK3 (AUC = 0.81) had superior AUC values than MAFG (AUC = 0.62).Conclusion: As the most related ferroptosis-genes with DFU, MAFG and MAPK3 may be employed as potential therapeutic targets for DFU patients. Moreover, MAPK3, with higher accuracy, could be the more potential ferroptosis-related biomarker for further experimental validation.
Population level variation in reproductive development and output in the golden kelp Laminaria ochroleuca under marine heat wave scenarios
Authors: Strasser Fiona-Elaine , Barreto Luis Matos , Kaidi Soukaina , Sabour Brahim , Serrão Ester A. , Pearson Gareth A. , Martins Neusa 
Published: September 2022

Thermal tolerance is often interpreted as a species-wide thermal niche in the absence of studies focusing on the adaptive potential of populations to exhibit differential thermal tolerance. Thus, considering intraspecific thermal plasticity, local adaptation or both between populations along distributional gradients when interpreting and predicting species responses to warming is imperative. Removing the effect of environmental histories by raising kelp gametophyte generations in vitro under common garden conditions allows unbiased comparison between population-specific adaptive variation under different environmental conditions. Following this approach, this study aims to detect (potentially) adaptive differentiation in microscopic life-stages (gametophytes) between populations of a temperate forest forming kelp, Laminaria ochroleuca from locations with distinct thermal conditions. Gametophytes from four geographically distinct populations were subjected to different temperature treatments (17, marine heat waves of 23, 25 and 27°C) and gametophyte survival during thermal stress as well as reproductive success and photosynthetic responses during recovery were investigated. Intraspecific variation in resilience and reproductive output to thermal stress was found in L. ochroleuca; gametophytes from the most northern population (Brittany, France) were the most thermally sensitive, with mortality onset at 23°C, whereas mortality in the remaining populations was only apparent at 27°C. Gametophytes from northern Spain and Morocco exhibited very low reproductive success during recovery from 23 and 25°C. However, when recovering from the highest thermal treatment (27°C) the reproductive development and sporophyte output was higher than in the gametophytes from France and Italy (Mediterranean). The population-specific responses of gametophyte resilience and reproductive success to temperature stress suggest genetic differentiation in response to variation in local thermal regimes.
Efficacy and safety of methylene blue in patients with vasodilatory shock: A systematic review and meta-analysis
Authors: Zhao Cong-Cong , Zhai Yu-Jia , Hu Zhen-Jie , Huo Yan , Li Zhi-Qiang , Zhu Gui-Jun 
Published: September 2022

BackgroundThe role of methylene blue (MB) in patients with vasodilatory shock is unclear. The purpose of this systematic review and meta-analysis was to evaluate the efficacy and safety of MB in patients with vasodilatory shock.MethodsWe searched MEDLINE at PubMed, Embase, Web of Science, Cochrane, CNKI, CBM and Wanfang Medical databases for all observational and intervention studies comparing the effect of MB vs. control in vasodilatory shock patients. This study was performed in accordance with the PRISMA statement. There were no language restrictions for inclusion.ResultsA total of 15 studies with 832 patients were included. Pooled data demonstrated that administration of MB along with vasopressors significantly reduced mortality [odds ratio (OR) 0.54, 95% confidence interval (CI) 0.34 to 0.85,P= 0.008;I2= 7%]. This benefit in mortality rate was also seen in a subgroup analysis including randomized controlled trials and quasi-randomized controlled trials. In addition, the vasopressor requirement was reduced in the MB group [mean difference (MD) −0.77, 95%CI −1.26 to −0.28,P= 0.002;I2= 80%]. Regarding hemodynamics, MB increased the mean arterial pressure, heart rate and peripheral vascular resistance. In respect to organ function, MB was associated with a lower incidence of renal failure, while in regards to oxygen metabolism, it was linked to reduced lactate levels. MB had no effect on the other outcomes and no serious side effects.ConclusionsConcomitant administration of MB and vasopressors improved hemodynamics, decreased vasopressor requirements, reduced lactate levels, and improved survival in patients with vasodilatory shock. However, further studies are required to confirm these findings.Systematic review registrationIdentifier: CRD42021281847.
A case of disseminated Legionnaires’ disease: The value of metagenome next-generation sequencing in the diagnosis of Legionnaires
Authors: Li Shan , Jiang Wei , Wang Chun-Yao , Weng Li , Du Bin , Peng Jin-Min 
Published: September 2022

BackgroundLegionella rarely causes hospital-acquired pneumonia (HAP), although it is one of the most common pathogens of community-acquired pneumonia. Hospital-acquired Legionnaires’ disease, mainly occurring in immunocompromised patients, is often delayed in diagnosis with high mortality. The use of the metagenome Next-Generation Sequencing (mNGS) method, which is fast and unbiased, allows for the early detection and identification of microorganisms using a culture-independent strategy.Case reportA 52-year-old male, with a past medical history of Goods syndrome, was admitted due to nephrotic syndrome. The patient developed severe pneumonia, rhabdomyolysis, and soft tissue infection after receiving immunosuppressive therapy. He did not respond well to empiric antibiotics and was eventually transferred to the medical intensive care unit because of an acute respiratory failure and septic shock. The patient then underwent a comprehensive conventional microbiological screening in bronchoalveolar lavage fluid (BALF) and blood, and the results were all negative. As a last resort, mNGS of blood was performed. Extracellular cell-free and intracellular DNA fragments of Legionella were detected in plasma and blood cell layer by mNGS, respectively. Subsequent positive results of polymerase chain reaction for Legionella in BALF and soft tissue specimens confirmed the diagnosis of disseminated Legionnaires’ disease involving the lungs, soft tissue, and blood stream. The patient’s condition improved promptly after a combination therapy of azithromycin and moxifloxacin. He was soon extubated and discharged from ICU with good recovery.ConclusionEarly recognition and diagnosis of disseminated Legionnaires’ disease is challenging. The emergence and innovation of mNGS of blood has the potential to address this difficult clinical issue.
The hotspots and publication trends in postoperative delirium: A bibliometric analysis from 2000 to 2020
Authors: Lin Xiaowan , Cao Ying , Liu Xiao , Yu Kang , Miao Huihui , Li Tianzuo 
Published: September 2022

BackgroundPostoperative delirium (POD) is a common aging-associated postoperative complication that has received increasing attention in the context of the aging global population and the number of articles published on POD is gradually increasing. This study aimed to quantify the basic information of scholarly publications on POD and identify the most impactful literature, trends, and hotspots in POD research.Materials and methodsWe searched articles on POD through the Science Citation Index Expanded databases published from 2000 to 2020. Bibliographic information, including year, country, authorship, type, journal, funding, affiliations, subject areas, and hotspots, was collected for further analysis.ResultsA total of 2,114 articles on POD from 2000 to 2020 were identified. The highest number of studies (n = 748) were published in the United States, comprising the most total citations (13,928), followed by China (n = 278), and Germany (n = 209). Inouye, Sharon K. was the most productive author, with 66 publications on POD. The Journal of the American Geriatrics Society published the highest number of articles (n = 80), with the most total citations (4,561) and average (57.01), followed by Anesthesia and Analgesia (n = 52), and the British Journal of Anaesthesia (n = 43). Harvard University was the most productive institute, with the highest H-index (n = 46) and highest degree centrality (n = 191). The top hotspots in the field of POD during this period were “elderly,” “cardiac surgery,” “cognitive impairment,” “hip fracture,” and “intensive care unit.”ConclusionThis study provides an overview of developments in the field of POD over the past 20 years using bibliometric analysis. Overall, research on POD has flourished worldwide. The United States (US) has a relatively high academic impact owing to its productive expertise and institutions in this field. Despite much research illustrating the diagnosis and management of POD in clinical practice, more basic research is needed.
ANXA11 mutations are associated with amyotrophic lateral sclerosis–frontotemporal dementia
Authors: Wang Yu , Duan Xiaohui , Zhou Xiao , Wang Renbin , Zhang Xiangfei , Cao Zhenhua , Wang Xiaoxia , Zhou Zhi , Sun Yu , Peng Dantao 
Published: September 2022

BackgroundThe Annexin A11 (ANXA11) gene has been newly identified as a causative gene of amyotrophic lateral sclerosis (ALS) with or without frontotemporal dementia (FTD). The current study aimed to investigate the ANXA11 mutations in a Chinese ALS–FTD or FTD cohort.MethodsWe included ten probands/patients with suspected ALS–FTD or FTD. Mutational analysis of ANXA11 was performed through Next Generation Sequencing (NGS) and Sanger sequencing. We collected and reviewed clinical presentation, neuropsychology test results, brain-imaging findings, and electrophysiological examination findings.ResultsIn total, six probands presented with ALS–FTD, and four with behavior variant FTD (bv-FTD). We identified a non-synonymous heterozygous mutation (c.119A&gt;G, p.D40G) of ANXA11 in proband 1, which is associated with ALS. However, this is the first report of the mutation causing ALS–FTD. Proband 1 started with abnormal behavior and progressed to classic upper motor nervous disease. Magnetic resonance imaging (MRI) showed significant bilateral temporal lobe atrophy and bilateral hyperintensities along the corticospinal tracts.18F-AV45-PET imaging showed negative amyloid deposits.ConclusionANXA11-related diseases have high clinical and genetic heterogeneity. Our study confirmed the contribution of ANXA11 mutations to ALS–FTD. The ANXA11 mutations established a complex genotype–phenotype correlation in ALS–FTD. Our research further elucidated the genetic mechanism of ALS–FTD and contributed to setting the foundation of future targeted therapy.