bluuebunny/crossref_metadata_2025_split huggingface dataset:
The significance of long chain non-coding RNA signature genes in the diagnosis and management of sepsis patients, and the development of a prediction model
Authors: Bai Yong , Gao Jing , Yan Yuwen , Zhao Xu 
Published: December 2024

BackgroundSepsis is a life-threatening organ dysfunction condition produced by dysregulation of the host response to infection. It is now characterized by a high clinical morbidity and mortality rate, endangering patients’ lives and health. The purpose of this study was to determine the value of Long chain non-coding RNA (LncRNA) RP3_508I15.21, RP11_295G20.2, and LDLRAD4_AS1 in the diagnosis of adult sepsis patients and to develop a Nomogram prediction model.MethodsWe screened adult sepsis microarray datasets GSE57065 and GSE95233 from the GEO database and performed differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA), and machine learning methods to find the genes by random forest (Random Forest), least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM), respectively, with GSE95233 as the training set and GSE57065 as the validation set. Differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA), boxplot statistical analysis, and ROC analysis by Random Forest, Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine (SVM) machine learning methods were used to identify characteristic genes and build the Nomogram Prediction model.ResultsGSE95233 yielded a total of 1069 genes, 102 of which were sepsis-related and 22 of which were non-sepsis controls. GSE57065 yielded a total of 899 genes, with 467 up-regulated and 432 down-regulated, including 82 sepsis-related genes and 25 non-sepsis control genes. WGCNA analysis excluded outlier samples, leaving 2,029 genes for relationship analysis between sepsis- and non-sepsis patient-associated LncRNA network representation modules, as well as Wein plots of differential genes versus genes in key modules of weighted co-expression network analysis to analyze gene intersections. Machine Learning found the sepsis-related characteristic LncRNAs RP3-508I15.21, RP11-295G20.2, LDLRAD4-AS1, and CTD-2542L18.1. The datasets GSE95233 and GSE57065 were analyzed using Boxplot against the screened genes listed above, respectively. The p-value between the sepsis and non-sepsis groups was less than 0.05, indicating that anomalies were statistically significant. CTD-2542L18.1 in dataset GSE57065 had an AUC value of 0.638, which was less than 0.7 and did not indicate diagnostic significance, but RP3-508I15.21, RP11-295G20.2, and LDLRAD4-AS1 had AUC values more than 0.7 after ROC analysis. All four sepsis-associated LncRNA ROC analyses in dataset GSE95233 exhibited AUC values more than 0.7, indicating diagnostic significance.ConclusionLncRNAs RP3_508I15.21, RP11_295G20.2, and LDLRAD4_AS1 have some utility in the diagnosis and treatment of adult sepsis patients, as well as some reference importance in guiding the diagnosis and treatment of clinical sepsis.
m6A methylation profiling as a prognostic marker in nasopharyngeal carcinoma: insights from MeRIP-Seq and RNA-Seq
Authors: Chen Xiaochuan , Xu Wenqian , Pan Junping , Yang Hanxuan , Li Yi , Chen Xin , Sun Yingming , Liu Qinying , Qiu Sufang 
Published: December 2024

BackgroundNasopharyngeal carcinoma (NPC) is a type of malignant tumors commonly found in Southeast Asia and China, with insidious onset and clinical symptoms. N6-methyladenosine (m6A) modification significantly contributes to tumorigenesis and progression by altering RNA secondary structure and influencing RNA-protein binding at the transcriptome level. However, the mechanism and role of abnormal m6A modification in nasopharyngeal carcinoma remain unclear.MethodsNasopharyngeal Carcinoma tissues from 3 patients and non-cancerous nasopharyngeal tissues from 3 individuals, all from Fujian Cancer Hospital, were sequenced for m6A methylation. These were combined with transcriptome sequencing data from 192 nasopharyngeal cancer tissues. Genes linked to prognosis were discovered using differential analysis and univariate Cox regression. Subsequently, a prognostic model associated with m6A was developed through the application of LASSO regression analysis. The model’s accuracy was verified using both internal transcriptome databases and external databases. An extensive evaluation of the tumor’s immune microenvironment and signaling pathways was performed, analyzing both transcriptomic and single-cell data.ResultsThe m6A methylation sequencing analysis revealed 194 genes with varying expression levels, many of which are predominantly associated with immune pathways. By integrating transcriptome sequencing data, 19 m6A-modified genes were found to be upregulated in tumor tissues, leading to the development of a three-gene (EME1, WNT4, SHISA2) risk prognosis model. The group with lower risk exhibited notable enrichment in pathways related to immunity, displaying traits like enhanced survival rates, stronger immune profiles, and increased responsiveness to immunotherapy when compared to the higher-risk group. Single-cell analysis revealed that malignant cells exhibited the highest risk score levels compared to immune cells, with a high-risk score indicating worse biological behavior. The three hub genes demonstrated significant correlation with m6A modification regulators, and MeRIP-RT-PCR confirmed the occurrence of m6A methylation in these genes within nasopharyngeal carcinoma cells.ConclusionsA prognostic model for nasopharyngeal carcinoma risk based on m6A modification genes was developed, and its prognostic value was confirmed through self-assessment data. The study highlighted the crucial impact of m6A modification on the immune landscape of nasopharyngeal cancer.
The association between sex hormones and prevalence of OA in US adults
Authors: Tian Xiaoyuan , Zhang Bocheng 
Published: December 2024

BackgroundAge and gender are commonly recognized as risk factors for osteoarthritis (OA), implying a potential association between sex hormones and OA pathogenesis. However, the precise role of sex hormones in OA remains elusive. Meanwhile, testosterone to estradiol (TT/E2) ratio is a new biomarker of sex hormone milieu. In this study, we aimed to investigate the relationship between sex hormones, specifically TT/E2 ratio, and the prevalence of OA among adults in the United States.MethodsThis study is a cross-sectional study, and the data sourced from the National Health and Nutrition Examination Survey (NHANES) 2013–2016 cycles. This study primarily focuses on individuals aged 50 and above, employing multivariable logistic regression to examine the association between sex hormones and OA.ResultsWe included 2,615 participants (972 females). No significant association was observed between testosterone or estradiol levels and OA prevalence when analyzed separately. However, the TT/E2 ratio exhibited a robust inverse association with OA, particularly in females (adjusted OR = 0.61, 95% CI: 0.41–0.91, p = 0.02). A nonlinear relationship was observed in females, with a threshold effect indicating reduced OA risk when the TT/E2 ratio exceeded 0.3.ConclusionThe TT/E2 ratio was inversely associated with OA risk, with a stronger and more consistent effect observed in females. These findings suggest the TT/E2 ratio as a potential biomarker for OA risk stratification, particularly in postmenopausal females. Future longitudinal studies are warranted to clarify the causal role of the TT/E2 ratio in OA.
Early detection of Alzheimer’s disease in structural and functional MRI
Authors: Maity Rudrani , Raja Sankari Vellupillai Mariappan , Snekhalatha Umapathy , Velu Shubashini , Alahmadi Tahani Jaser , Alhababi Zaid Ali , Alkahtani Hend Khalid 
Published: December 2024

ObjectivesTo implement state-of-the-art deep learning architectures such as Deep-Residual-U-Net and DeepLabV3+ for precise segmentation of hippocampus and ventricles, in functional magnetic resonance imaging (fMRI). Integrate VGG-16 with Random Forest (VGG-16-RF) and VGG-16 with Support Vector Machine (VGG-16-SVM) to enhance the binary classification accuracy of Alzheimer’s disease, comparing their performance against traditional classifiers.MethodOpenNeuro and Harvard’s Data verse provides Alzheimer’s coronal functional MRI data. Ventricles and hippocampus are segmented using a Deep-Residual-UNet and Deep labV3+ system. The functional features were extracted from each segmented component and classified using SVM, Adaboost, Logistic regression, and VGG 16, DenseNet-169, VGG-16-RF, and VGG-16-SVM classifier.ResultsThis research proposes a precise and efficient deep-learning architecture like DeepLab V3+ and Deep Residual U-NET for hippocampus and ventricle segmentation in detection of AD. DeepLab V3+ has produced a good segmentation accuracy of 94.62% with Jaccard co-efficient of 85.5% and dice co-efficient of 84.75%. Among the three ML classifiers used, SVM has provided a good accuracy of 93%. Among some DL techniques, VGG-16-RF classifier has given better accuracy of 96.87%.ConclusionThe novelty of this work lies in the seamless integration of advanced segmentation techniques with hybrid classifiers, offering a robust and scalable framework for early AD detection. The proposed study demonstrates a significant advancement in the early detection of Alzheimer’s disease by integrating state-of-the-art deep learning models and comprehensive functional connectivity analysis. This early detection capability is crucial for timely intervention and better management of the disease in neurodegenerative disorder diagnostics.
Comparative performance of PtRu/C catalysts synthesized by different methods for direct methanol fuel cells under various operating conditions
Authors: Souza Elson Almeida De , Silva Rudyere Nascimento , Gonçalves Daniel A. , Pocrifka Leandro Aparecido , Passos Raimundo Ribeiro 
Published: December 2024

This work presents a comparative study of three synthesis methods for PtRu/C catalysts for use in polymer electrolyte fuel cells, investigating their activity in methanol oxidation. The evaluated methods were formic acid reduction (FAM), methanol reduction (ARM), and ethylene glycol reduction (ARE). XRD analysis confirmed the formation of a Pt-Ru binary alloy in all syntheses. Electrochemical tests indicated that all catalysts were properly prepared, with the PtRu/CARE catalyst standing out as having the best performance, achieving a power density of 74,88 mW cm−2 at 90°C and an oxygen pressure of 3 atm on the cathode. These results highlight the potential of PtRu/CARE for application in direct methanol fuel cells, surpassing the catalysts obtained through the other methods.
The cardiometabolic benefits of okra-based treatment in prediabetes and diabetes: a systematic review and meta-analysis of randomized controlled trials
Authors: Bahari Hossein , Shahraki Jazinaki Mostafa , Rahnama Iman , Aghakhani Ladan , Amini Mohammad Reza , Malekahmadi Mahsa 
Published: December 2024

BackgroundThis systematic review and meta-analysis examine the effects of okra consumption on cardiometabolic risk factors in individuals with prediabetes and diabetes. Okra is a widely consumed vegetable with potential health benefits, and understanding its impact on metabolic parameters in these populations is important.MethodsA comprehensive search of the literature was conducted up to May 2024 in PubMed/Medline, Scopus, and Web of Science to find relevant randomized clinical trials (RCTs) by using following keyword: (“okra” OR “okras” OR “abelmoschus esculentus”) AND (“intervention” OR “controlled trial” OR “randomized” OR “randomized” OR “randomly” OR “clinical trial” OR “trial” OR “randomized controlled trial” OR “randomized clinical trial” OR “RCT” OR “blinded” OR “placebo” OR “Cross-Over” OR “parallel”). The selected trials were subjected to heterogeneity tests using the I2 statistic. Random effects models were examined based on the heterogeneity tests, and the pooled data were calculated as weighted mean differences (WMD) with a 95% confidence interval (CI). In this meta-analysis, all the analyses were performed by using the STATA version 17 software.ResultsOf the 1,339 papers, nine eligible RCTs were included in the present meta-analysis. Our findings indicated that okra consumption significantly reduced total cholesterol (TC) levels (WMD: −14.40 mg/dL; (95% CI: −20.94 to −7.86); p &lt; 0.001), low-density lipoprotein (LDL) (WMD: −7.90 mg/dL; (95% CI: −13.30 to −2.48); p = 0.004), fasting blood glucose (FBG) (WMD: −39.58 mg/dL; (95% CI: −61.60 to −17.56); p &lt; 0.001), and hemoglobin A1C (HbA1c) (WMD: −0.46 mg/dL; (95% CI: −0.79 to −0.13); p = 0.005). Overall effect size showed that okra intake failed to change triglycerides (TG), high-density lipoprotein (HDL), Insulin, homeostatic model assessment for insulin resistance (HOMA-IR), systolic blood pressure (SBP), diastolic blood pressure (DBP), body weight, and body Mass Index (BMI) significantly.ConclusionOkra decreased TC, LDL, FBG, and HbA1c levels in the intervention compared to the control group. A dose ≤3,000 mg/day caused a significant decrease in TG, TC, LDL, HbA1c, and a significant increase in HDL. More study is needed to determine the optimum dose and duration of intervention.
CT-based radiomics features for the differential diagnosis of nodular goiter and papillary thyroid carcinoma: an analysis employing propensity score matching
Authors: Zhang Haiming , Li Zhenyu , Zhang Fengtao , Li Hengguo 
Published: December 2024

PurposeThis study aims to evaluate the effectiveness of CT-based radiomics features in discriminating between nodular goiter (NG) and papillary thyroid carcinoma (PTC).MethodsA retrospective cohort comprising 228 patients with nodular goiter (NG) and 227 patients with papillary thyroid carcinoma (PTC) diagnosed between January 2018 and December 2022 was consecutively enrolled. Propensity score matching (PSM) was applied to align patients with NG and PTC. A total of 851 radiomics features were extracted from CT images acquired during the arterial phase for each individual. Feature selection was carried out utilizing the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm to generate the radiomics score (Rad-score). Subsequently, the Rad-score was incorporated into a multivariate logistic regression analysis to construct a radiomics nomogram for visual representation.ResultsFollowing PSM implementation, 101 patients diagnosed with NG were matched with an equivalent number of patients diagnosed with PTC. The developed radiomics score exhibited excellent predictive performance in distinguishing between NG and PTC, with high values of AUC, sensitivity, and specificity in both the training cohort (AUC = 0.823, accuracy = 0.759, sensitivity = 0.794, specificity = 0.740) and validation cohort (AUC = 0.904, accuracy = 0.820, sensitivity = 0.758, specificity = 0.964).ConclusionThe utilization of CT-based radiomics analysis following PMS offers a quantitative and data-driven approach to enhance the accuracy of distinguishing between nodular goiter (NG) and papillary thyroid carcinoma (PTC).
Prognostic significance of blood immune cells in children with sepsis and establishment of a predictive model for PICU mortality: a retrospective study
Authors: He Mulan , Meng Qiuxia , Wei Zhixin , Yang Zhiyong 
Published: December 2024

ObjectivesThis article aimed to investigate the correlation between blood immune cells and the prognosis in the early phase of pediatric sepsis and construct a prediction model for pediatric intensive care unit (PICU) mortality.MethodsA total of 348 children admitted with sepsis to our PICU were retrospectively collected between January 2020 and June 2024. Of these, 242 children admitted from January 2020 to October 2022 were designated as the modeling group, while 106 children admitted between November 2022 and June 2024 were designated as the prospective validation group. Peripheral blood immune-related parameters, measured from the day of PICU admission to day 7, were analyzed in the modeling group. Risk factors were identified through multivariate logistic regression and integrated into a predictive nomogram. The nomogram was then applied to the prospective validation group to assess its discrimination and calibration. The nomogram's performance was evaluated using the area under the receiver operating characteristic curves (AUC), calibration plots, and decision curve analysis for both groups.ResultsComplicated with underlying diseases, invasive mechanical ventilation, increased pediatric risk of mortality score or pediatric sequential organ failure assessment score, and lymphopenia (d1) were independent risk factors for PICU mortality. The 90-day survival of patients with lymphopenia on the first day after admission was low. In addition, patients with persistent lymphopenia had higher mortality. The nomogram showed an AUC of 0.861 (95% CI: 0.813 to 0.909) in the modeling group and 0.875 (95% CI: 0.797 to 0.953) in the prospective validation group. The nomogram also performed well based on the calibration curve and decision curve analysis.ConclusionAssessing lymphocytes within seven days of PICU admission may be conducive to identifying children with sepsis at increased mortality risk. The nomogram performed well in predicting PICU mortality among patients of interest.
Non-linear association between C-reactive protein levels and length of stay in pediatric appendicitis patients undergoing laparoscopic appendectomy
Authors: Liu Ming , Yang Ping , Gou Yunpeng 
Published: December 2024

ObjectiveTo examine the correlation between C-reactive protein (CRP) levels at hospital admission and the length of stay (LOS) in pediatric patients with appendicitis who underwent laparoscopic appendectomy.MethodsWe retrospectively collected the clinical data from pediatric patients diagnosed with acute appendicitis and treated with laparoscopic appendectomy. Multivariate generalized linear regression analyses were performed to determine the independent relationship between CRP and LOS. Smooth curve fitting was constructed to examine the potential non-linear relationship between CRP and LOS. A segmented regression model was used to calculate threshold effects and determine the inflection point.ResultsA total of 815 participants were included in the study. Multiple linear regression analysis indicated that the higher the CRP levels, the longer the LOS. Fully adjusted smooth curve fitting suggested a non-linear relationship between CRP and LOS. A segmented regression showed that the inflection point value of CRP was 34.13 mg/L. A 1 mg/L increase in CRP levels was significantly associated with a 0.013-day increase in length of stay (95% CI: 0.009, 0.018; P &lt; 0.001) when CRP levels &gt; 34.13 mg/L. However, there was no significant association between CRP and LOS when CRP levels &lt; 34.13 mg/L (P &gt; 0.05).ConclusionThere was a non-linear association and threshold effect between CRP levels and LOS. CRP levels above 34.13 mg/L were associated with longer LOS in pediatric appendicitis patients. These findings contribute to the understanding of inflammatory markers in recovery dynamics and underscore the necessity for further research to investigate their potential clinical implications.
School absenteeism as a predictor of functional gastrointestinal disorders in children
Authors: Tersteeg Seth M. , Borowitz Stephen M. 
Published: December 2024

IntroductionChronic abdominal complaints are common in school-aged children. Most affected children do not have underlying organic diseases but suffer from functional gastrointestinal disorders. While many children with chronic abdominal complaints experience school problems, no prospective studies have examined if school absenteeism is more common among children suffering from functional as opposed to organic gastrointestinal disorders. The purpose of this study was to determine if there is an association between school absenteeism and functional gastrointestinal disorders in children presenting to a pediatric gastroenterology clinic with chronic gastrointestinal complaints.MethodsOver a single year, families of school-aged children presenting to a pediatric gastroenterology clinic with gastrointestinal complaints were asked how many days of school their child had missed in the previous month due to their symptoms. At least six months after their visit, each child's final diagnosis was established and categorized as a functional disorder or an organic disease. Differences between children suffering from each diagnosis type were compared using unpaired t-tests.ResultsChildren with functional gastrointestinal disorders were more likely to experience significant school absenteeism than children with gastrointestinal diseases. Missing more than three days of school in the month prior to their visit had a negative predictive value of 82% for a gastrointestinal disease and being homebound from school during the month prior to their visit had a negative predictive value of 88% for a gastrointestinal disease. As compared to children with functional disorders, those with organic diseases were more likely to have missed three or fewer days of school in the previous month (sensitivity = 93%) and to have attended any school in the previous month (sensitivity = 99%).DiscussionOur data suggest children with functional gastrointestinal disorders are more likely to experience significance school absenteeism than children suffering from organic diseases. We suspect this may be due to higher perceived levels of pain and symptom catastrophizing caused by the duration and character of the diagnostic process, as well as biopsychosocial characteristics of these children.
Factors influencing vancomycin trough concentration in burn patients: a single center retrospective study
Authors: Shi Yan , Yin Zongqi , Zhang Qin , Yi Lei , Dou Yi 
Published: December 2024

ObjectiveTo analyze factors influencing the vancomycin trough concentration in burn patients to provide a basis for the more rational use of vancomycin in these patients.Materials and methodsWe collected the clinical data of adult burn patients treated with vancomycin in a Chinese hospital. Vancomycin was administered at a dosing regimen of 1.0 g q12 h. Patients were divided into a therapeutic group with vancomycin trough concentration in the target therapeutic range (10–20 μg/mL) and a subtherapeutic group with vancomycin trough concentration in the subtherapeutic range (&lt;10 μg/mL).ResultsThe therapeutic group included 14 patients (17.5%), with an average trough concentration of 14.36 ± 2.82 μg/mL; the subtherapeutic group included 66 patients (82.5%), with an average trough concentration of 5.18 ± 2.77 μg/mL. The serum creatinine level was significantly higher in the therapeutic group (84.93 ± 47.26 μmol/L) than that in the subtherapeutic group (62.44 ± 14.49 μmol/L) (p &lt; 0.01). Serum albumin levels were significantly lower in the therapeutic group (30.50 ± 2.28 g/L) than those in the subtherapeutic group (34.00 ± 6.22 g/L) (p &lt; 0.05). Using receiver operating characteristic (ROC) curve analysis, for serum albumin, the area under the ROC curve (AUC) (95% confidence interval [CI]) was 0.67 (0.553, 0.788); the optimal cut-off point was 34.50 g/L (p = 0.046), the sensitivity was 0.379, and the specificity was 1.0. For creatinine clearance, the AUC (95% CI) was 0.72 (0.537, 0.902); the optimal cut-off point was 76.64 mL/min (p = 0.01), the sensitivity was 0.985, and the specificity was 0.5. The linear stepwise regression equation was as follows: trough concentration = 0.14 × age + 0.071 × serum creatinine −4.196.ConclusionIn this study, a high proportion of burn patients had a vancomycin trough concentration below the standard range. Serum creatinine clearance and albumin levels are important indicators for predicting whether the vancomycin trough concentration is within the standard range. Using a linear stepwise regression equation, the vancomycin trough concentration can be estimated using the patient’s age and serum creatinine level.