bluuebunny/crossref_metadata_2025_split huggingface dataset:
A nomogram for predicting T315I-free survival in chronic phase chronic myeloid leukemia patients: a multicenter retrospective study
Authors: Hu Shi-wei , Yang Xiu-di , Wu Di-jiong , Wang Yi , Zhu Xiaoqiong , Feng Weiying , Qian Honglan , Lu Ying , Chen Lili , Cao Lihong , Le Jing , Zhang Li , Shao Yanping , Liu Lirong , Tian Guoyan , Zhou Hui , Chen Yu , Yin Xiufeng , Feng Xiaoning , Huang Li , Zhang Kaifeng , Xia Yongming , Xu Linjuan , Zhang Huiqi , Zhang Gang , Jia Yongqing , Zhou Xiujie , Wu Gongqiang , Tu Jinming , Zhu Feng , Zhang Yuefeng , Yao Guoli , Zhu Jingjing , Tong Hongyan , Jin Jie , Huang Jian 
Published: October 2024

Abstract

The T315I mutation poses a significant threat to patients with chronic phase chronic myeloid leukemia (CP-CML). This study aimed to establish a nomogram to predict the risk of T315I mutation in CP-CML patients. The training cohort included 1,466 patients from 24 hematology centers, and the validation cohort included 820 patients from an additional 20 centers. Peripheral blood blast (PBB), additional chromosomal abnormality (ACA), dasatinib use, non-EMR at 3 months, and BCR::ABLIS > 1% at 6 months were identified as independent risk factors through multivariate Cox regression analysis. The performance of the nomogram was assessed via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The area under the ROC curve (AUC) values at 5, 10, and 15 years were 0.874, 0.925, and 0.930 for the training cohort, and 0.864, 0.814, and 0.803 for the validation cohort, respectively. The calibration curves for both cohorts were close to the ideal diagonal, and the decision curves indicated clinical net benefit. In conclusion, we developed a nomogram to predict the 5-year, 10-year, and 15-year T315I-free survival probabilities of CP-CML patients. This tool can aid clinicians in the early prediction and timely management of high-risk CP-CML patients with the T315I mutation.
External ventricular drainage following purulent meningitis with hydrocephalus in pediatric patients
Authors: Sun Yaning , Xiao Jing , Luo Pengyuan , Yue Yanke , Fang Jiangshun , Wang Shengjuan , Luan Jimei , Cheng Zhenghai , Yang Zhiguo , Chen Zhiguo , Qu Yi 
Published: October 2024

Abstract

Background
External ventricular drain (EVD) placement is standard of care in the management of purulent meningitis with hydrocephalus (PMH). However, there are no guidelines for EVD placement and management after PMH. Optimal EVD insertion location, techniques to reduce the risk of EVD-associated infection and methods of EVD removal are critical, yet incompletely answered management variables.
Methods
The indwelling time of conventional external ventricular drainage is relatively short, 7–10 days. Long-term external drainage devices may lead to retrograde infection. This study has modified the C-EVD procedure. Clinical outcomes, cerebrospinal fluid (CSF) test results, complications, and outcomes were compared between the modified external ventricular drainage (M-EVD) (n = 21) group and C-EVD (n = 25) group.
Results
The two groups were similar regarding age, sex, weight and other general conditions (P > 0.05). There were significant differences in the values of white blood cells (WBC), glucose(GLU) and protein(PR) in cerebrospinal fluid (CSF) between the two groups when the drainage tube was removed, which was statistically significant. The median days of removing the drainage tube in the C-EVD group and the M-EVD group were 9 days and 19 days, respectively. The median days of CSF returning to normal were 19 days and 13 days (P < 0.05). A total of 13 children in the M-EVD group underwent V-P shunt surgery, while 17 children in the C-EVD group were treated with V-P shunt surgery (P = 0.665).
Conclusion
M-EVD has more obvious advantages compared to C-EVD. The modified significantly prolonged the catheterization time, which can more effectively treat PMH in pediatric patients.
Epidemiology of amebiasis around the COVID-19 pandemic period in Japan
Authors: Iida Keisuke , Mori Hirotake , Hadano Yoshiro , Mahittikorn Aongart , Naito Toshio 
Published: October 2024

Abstract

Amebiasis cases in Japan are reported to the government according to the Infectious Diseases Control Law. Previous studies have shown significant reductions in total case numbers after 2018 and during the COVID-19 pandemic. This study aimed to clarify the recent trends of amebiasis in Japan, including during the pandemic period, with details on places of infection and disease types, using government surveillance data from January 1, 2001, to December 31, 2022. Multiple comparisons by Dunnett’s test were performed to compare case numbers of three time periods (2015-2017, 2018-2019, and 2020-2022). Significant decreases in reported amebiasis cases were observed in 2018 (24.5%) and in 2020 (45.3%). This downward trend was observed regardless of place of infection (domestic or imported) and disease type (intestinal or extraintestinal). Male cases predominated, with most male cases in their 40s and 50s.Most cases of amebiasis have been reported in metropolitan areas. These results suggest that the decreased case numbers during the COVID-19 pandemic were due to not only the travel ban, but less socioeconomic activity. Furthermore, the epidemiology of amebiasis is similar to that of HIV infection in Japan, but the case numbers of amebiasis have not yet recovered, showing a different trend from HIV infection and syphilis.
Integrated Analysis of Cell Cycle and p53 Signaling Pathways Related Genes in Breast, Colorectal, Lung, and Pancreatic Cancers: Implications for Prognosis and Drug Sensitivity for Therapeutic Potential
Authors: Khan Jiyauddin , Ghosh Priyanjana , Bajpai Urmi , Saluja Daman 
Published: October 2024

Abstract

Cancer, a leading cause of death worldwide, is projected to increase by 76.6% in new cases and 89.7% in mortality by 2050 (WHO 2022). Among various types, lung cancer (LUC) is the most prevalent and lethal, while breast (BRC), colorectal (CRC), and pancreatic (PAC) cancers also show high mortality rates. Cancer progression often involves disruption in cell cycle regulation and signaling pathways, with mutations in genes like TP53, EGFR, and K-RAS playing significant roles. In this study, we analyzed gene expression datasets to identify common molecular signatures across BRC, CRC, LUC, and PAC. Our focus was on genes related to cell cycle regulation and p53 signaling pathway, intending to discover potential biomarkers for improved diagnosis and treatment strategies. The study analyzed GEO datasets; GSE45827, GSE9348, GSE30219, and GSE62165 for BRC, CRC, LUC, and PAC respectively. Differentially expressed genes (DEGs) were identified using GEO2R, and functional annotation and pathway analysis were performed using WebGestalt. Common cell cycle and p53 signaling genes were acquired from MSigDB using GSEA. A protein-protein interaction network was constructed using STRING and Cytoscape, identifying top hub genes. Validation of Hub genes at mRNA and protein levels was done via GEPIA2 and HPA. Survival analysis was conducted using TCGA data, and drug sensitivity was analyzed with the GSCA tool, highlighting potential therapeutic targets. The study identified 411 common DEGs among these four cancers. Pathway and Functional enrichment revealed key biological processes and pathways like p53 signaling, and cell cycle. The intersection of these DEGs with genes involved in cell cycle and p53 signaling, identified 23 common genes that were used for constructing a PPI network. The top 10 hub genes were validated both for mRNA and protein expression, revealing they are significantly overexpressed in all studied cancers. Prognostic relevance showed CCNA2, CDC20, and CHEK1 are associated with poor survival outcome. Additionally, drug sensitivity analysis highlighted key gene-drug interactions, suggesting potential targets for therapeutic intervention.
Clinical outcomes of early remdesivir administration in hospitalized patients at high risk for severe COVID-19 during the Omicron wave
Authors: La Yeon Ju , Oh Won Sup , Kim Changhyup , Lim Myoung-nam , Jeon Yong Duk 
Published: October 2024

Abstract

Background
Early remdesivir administration in high-risk patients with coronavirus disease 2019 (COVID-19) is known to be effective in preventing the progression to severe disease. However, the effect of early remdesivir administration on Omicron variants, which are known to have decreased severity, remains unclear.
Methods
This study aimed to analyze the effects of early remdesivir administration during the Omicron wave in hospitalized patients. Electronic medical records of hospitalized patients with confirmed COVID-19 between February 2022 and February 2023 were reviewed. We included patients aged ≥18 years who had symptom onset within 7 days and had at least one risk factor for disease progression at the time of diagnosis. We compared the clinical outcomes between the early remdesivir administration group and the group not administered early remdesivir. The primary outcome was all-cause mortality within 28 days and the secondary outcome was the need for oxygen supplementation within 28 days. A total of 286 patients were enrolled, with 88 and 198 in the early and control groups, respectively. Results
Clinical outcomes, including all-cause mortality (3.4% vs. 6.1%, P = 0.556) and need for oxygen supplementation (15.9% vs. 14.6%, P= 0.783) within 28 days, were not significantly different between the two groups. Early remdesivir administration was not significantly associated with all-cause mortality (HR, 0.393; 95% CI: 0.109, 1.417; P = 0.154) or the need for oxygen supplementation (OR, 0.823; 95% CI: 0.389, 1.740; P = 0.610).
Conclusions
Considering the decline in the severity of the Omicron variant and the increased vaccination rate reported in previous studies, further studies are needed to establish new indications for the use of early remdesivir in the Omicron variant.
Identifying Optimal Algorithms for Breast Cancer Prediction in Ethiopia
Authors: Takele Kasahun , Abate Jemal , Adamu Gadisa , Jifara Wabi , Dheressa Merga , Shawel Michael 
Published: October 2024

Abstract

The most prevalent and lethal kind of cancer in Ethiopia is breast cancer. The number of deaths from breast cancer is rising dramatically every year. It is the most common kind of cancer overall and the leading cause of death for women in Ethiopia. Considering this, this study aims to identify optimal machine learning algorithms that can predict the stages of breast cancer. Unlike traditional methods, machine learning approaches have proven to be powerful methods in early detection and prediction of breast cancer. In this study, we have used the breast cancer dataset that was collected from Hiwot Fana Specialized University Hospital and Tikur Anbesa Specialized Hospital from September 2019 to April 2024. We have applied machine learning algorithms on the preprocessed breast cancer dataset; which are random forest, logistic regression, decision tree, and hybrid machine learning algorithms (RF, DT, GBC and SVM). Based on the results obtained from each algorithm, we compared and evaluated the performance of each classifier using evaluation metrics like precision, recall, F1 score, and accuracy to identify the optimal machine-learning algorithm. In order to find the optimal algorithms and improve the accuracy of the model, 13 features were selected as inputs. The model performance evaluation was done using the train split test and the 10-fold cross-validation. The experimental results were based on dataset division (80:20) to predict stages of breast cancer. Python programing language and required libraries were used to analyze dataset. According to the comparative analysis obtained from the dataset, the random forest model performed well in both trains split test and the 10-fold cross validation performance evaluation and surpassed other experimented algorithms. It has better effects, and its recall, precision, accuracy, and F1-scores are equal, which is 99% using train split test and 97% using 10-fold cross validation. Thus, random forest is the optimal machine-learning algorithm that used to determine stages of breast cancer patients in Ethiopia.
Determination of Fibrinolytic Bacteria Ratio by Polymerase Chain Reaction Analysis in Alveolitic Cases Developed After Tooth Extraction
Authors: Akbulut Funda Gökçe , Yılmaz Ayça Dilara , Yurttutan Mehmet Emre , Üçok Cahit 
Published: October 2024

Abstract

Purpose: The research conducted aimed to investigate the presence and abundance of fibrinolytic bacteria in cases of alveolitis post tooth extraction, a common complication known as dry socket.
Material and Methods: The study, involving 56 patients diagnosed with alveolitis, utilized polymerase chain reaction (PCR) analysis to detect specific ratios of fibrinolytic bacteria associated with this condition.
Results: The study involved 56 patients with 59 extraction sockets diagnosed with alveolitis. Bacterial DNA was found in all 50 samples: T. denticola in 76% and P. gingivalis in 32%. T. denticola was present in all P. gingivalis samples. Most patients were female (62%) with an average age of 40.16, and alveolitis occurred mainly after lower third molar extractions (40.16) Postoperatively, 46% used antibiotics and 51% used chlorhexidine (CHX) mouthwash. Statistically, T. denticola was more common in females, while P. gingivalis was linked to lower rates of antibiotic and CHX use
Conclusions: This study suggests a high prevalence of T. denticola and P. gingivalis in alveolitis cases, potentially influenced by gender and postoperative care practices, warranting further investigation into their role in disease development and targeted prevention strategies.
Incidence and factors associated with hemodynamic change At Post Anesthesia Care Unit among adult surgical patients At Wachemo University Nigest Elleni Mohammed Memorial Comprehensive Specialized Hospital, 2023: Ethiopia, A prospective Observational study
Authors: Wolde¹ Yisehak , Samuel¹ Sintayehu , Abebe¹ Teketel 
Published: October 2024

Abstract

Background: Hemodynamic change, which is an independent risk factor of long-term patient morbidity and duration of stay in the hospital, is a risk for patients in the post-anaesthesia care unit. Multiple predictors contribute to the development of postoperative hemodynamic instability. Prevention and treatment of these factors may minimize patients’ hemodynamic instability, and its associated morbidity and mortality.
Objective: This study aimed to determine the incidence and factors associated with hemodynamic change among adult surgical patients in the postanesthesia care unit.
Method: An institution-based observational study was conducted from December 1, 2023, to June 30, 2024. And 409 adult surgery patients had participated. We employed consecutive sampling technique and both analytical and descriptive statistics to explain our findings. Using both bi-variable and multi-variable logistic regression, we evaluated the strength of the association and determined the crude odds ratio and adjusted odds ratio with a 95% confidence interval. A p-value of less than 0.05 is considered statistically significant in multi variable regression. Result: The total incidence of hemodynamic instability was 53.8.47% (CI: 0.45, 0.64). The incidence of hypotension, hypertension, tachycardia and bradycardia was 24.2%, 17.45%, 31.3%, and 12.6% respectively. ASA class III, procedures longer than 4 intraoperative hemodynamic instability and regional anaesthesia were significantly associated with hemodynamic instability in the postanaesthetic care unit.
Conclusion: In general, the incidence of hemodynamic instability was a significant finding. The intraoperative HDI, ASA class III, postoperative respiratory adverse events, neurologic and gynaecological procedures, use of regional anaesthesia, and prolonged duration of procedures were predictors of hemodynamic instability in the post-anesthesia care unit. Certainly, it is desirable to adopt prediction tools in surgical patients, when the risk of postoperative complications is high, so staffing and medical resources of a particular clinical setup should be considered. Developing risk prediction tools is not enough, but it can be used as a baseline source to develop evidence-based clinical pathways. Implementing and evaluating the adopted clinical pathway to improve the quality of postoperative care.
Spermidine and Chloroquine Enhance Peptide-Based pDNA Transfection Efficiency within the GRP78-Overexpressing DU145 Prostate Cancer Cells
Authors: Daniel Grace , Collak Filiz , Hilan George , Robillard Elissa , Willmore William G. , McKay Bruce C. , Sabatino David 
Published: October 2024

Abstract

This study describes a peptide-based formulation for plasmid gene (pDNA) delivery within the GRP78-overexpressing prostate cancer (DU145) cells. The GRP78-targeting sequence (WIFPWIQL) extended with the nona-arginine (R9) cell-penetrating peptide (WIFPWIQL-R9) effectively enabled capture and release of pDNA, while conferring serum stability, according to agarose gel electrophoresis. Characterization studies based on transmission electron microscopy revealed the formation of stably condensed peptide:pDNA nanoparticles (<200 nm) at excess peptide nitrogen (N) to pDNA phosphate (P) stoichiometric ratios (10:1 N/P) and with CaCl2 functioning as an ionic stabilizer, that rendered the nanoparticles applicable to cell biology. Confocal imaging of the FITC-labeled peptide:pDNA formulation indicated cell uptake and intracellular entrapment within endosomes that restricted pDNA gene expression in the DU145 cells. Optimization studies with a reporter plasmid Green Fluorescent Protein (pGFP) revealed spermidine and chloroquine as the most effective additives for enhancing peptide-based transfection efficiency. Furthermore, blocking with anti-GRP78 confirmed the GRP78-dependent mechanism for cell uptake. Thus, peptide-targeting of GRP78 allows for selective binding and entry within the GRP78-overexpressing cancer cells for gene (pDNA) delivery. Transfection of the tumor suppressor p53-expression vector using the optimized peptide-based transfection conditions revealed elevated levels of p53 within the DU145 prostate cancer cells. These findings indicate the potential anti-cancer utility of the GRP78-targeting peptide gene (pDNA) delivery system.
Lipoprotein(a) as a Predictor of Nonalcoholic Fatty Liver after Pancreatectomy
Authors: Abe Kyohei , Fujioka Shuichi , Takano Yuki , Shirai Yoshihiro , Tsunematsu Masashi , Matsumoto Michinori , Furukawa Kenei , Haruki Koichiro , Onda Shinji , Ikegami Toru 
Published: October 2024

Abstract

Purpose
Lipoprotein(a) (Lp(a)) is a complex protein that plays a role in transporting insoluble lipids in plasma. Between 70% to more than 90% of Lp(a) expression is genetically determined by the number of Kringle IV type 2 domains. We investigated the association between preoperative serum Lp(a) level and development of post-pancreatectomy nonalcoholic fatty liver disease (NAFLD) in patients underwent pancreatectomy.
Methods
Serum Lp(a) level was measured preoperatively and retrospectively evaluated with other known risk factors for NAFLD, which was defined by a computed tomography-based Hounsfield unit (HU) value for liver parenchyma below 40 HU at the anteroposterior midpoint.
Results
NAFLD developed after pancreatectomy in 40 patients (17.5%) in high Lp(a)-group, which was significantly low as compared with those of low Lp(a)-group (30 patients, 53%) (p = 0.01). There was no other significant background factors which related to preoperative Lp (a) level. Multivariate analysis indicated low Lp(a) level is independent risk factors for postoperative NAFLD as well as pancreatic head resection, small volume of residual pancreatic volume, poor intake of pancrelipase, and postoperative diarrhea
Conclusion
NAFLD after pancreatectomy could be predicted preoperatively to a certain extent by examining serum Lp(a) level.
Forecasting Volume of Patients’ Visits in the Emergency Medicine Department at Muhimbili National Hospital, Tanzania
Authors: Mwalupani Nsajigwa , Pallangyo Edgar 
Published: October 2024

Abstract

Background
Emergency department overcrowding has developed as a severe and mounting problem common worldwide with substantial worldwide public health problems since it impedes the realization of Sustainable Development Goals of good health and well-being, including smooth planning and provision of quality services.
Objective
The main goal of this study is to forecast monthly patients’ visits in the Emergency Medicine Department at Muhimbili National Hospital, Tanzania to provide timely information to aid the decision-making process.
Methodology
Retrospective data of monthly patient visits registered in the Emergency Department at Muhimbili National Hospital from January 2016 to December 2020, with 60 observations, were collected. Time series methods of ARIMA and Multi-layer Perceptron (MLP) neural network models were used to analyze the data. The best model was chosen, and identified based on predicted accuracy between ARIMA and MLP models with the mean absolute percentage error (MAPE), root mean square error (RMSE), and mean absolute error (MAE). The software packages R Studio and Excel 2016 were used for statistical analyses.
Results
It was found that the MLP model with structure 2-(5)-1 performed better in the testing set (RMSE = 372.37, MAPE = 5.7282 and MAE = 304.70) compared to ARIMA (1,1,4) (RMSE = 426.69, MAPE = 6.9489 and MAE = 337.58 respectively). Also, the validation set of the MLP model with structure 2-(5)-1 performed better (RMSE = 763.89, MAPE = 17.3553 and MAE = 751.935) than ARIMA (1,1,4) (RMSE = 974.573, MAPE = 19.4181 and MAE = 893.9388 respectively).
Conclusions
Therefore, the MLP model with structure 2-(5)-1 was chosen for forecasting purposes whereby we predicted forecasts for 20 months. Finally, we recommend That the results of this study be adopted to help decision-makers and planners to be prepared and avoid dire situations.
Flow diverter with or without adjunctive coils in the treatment of large and giant intracranial aneurysms: a meta-analysis
Authors: Sein Matias E. , Ceciliano Alejandro , Navarro Fernando , Molina Silvina , Villasante Francisco , Tejado Eduardo E. , Requena Manuel , Hernandez David , Lascuevas Marta de Dios , Tomasello Alejandro , Diana Francesco 
Published: October 2024

Abstract

Introduction
To evaluate the available evidence on the efficacy and safety of flow diverters (FD) with or without adjunctive coils (C) for the treatment of large and giant aneurysms.
Methods
A systematic review and meta-analysis of relevant studies in PubMed and selected articles up to December 2022 were conducted. The primary objective was to evaluate the rate of favorable occlusion O'Kelly Marotta (OKM) C-D at the last follow-up, while the secondary objective was to assess complication rates. A fixed-effects model was used, and relative risks (RR) and 95% confidence intervals (CI) were calculated.
Results
A total of 146 articles were identified, but only 10 were included in the meta-analysis. This included 541 controlled aneurysms out of a total of 680 large and giant aneurysms from 1,667 patients. We found no statistical differences in favorable OKM C-D outcomes with or without the adjunctive use of coils (RR 1.06 [0.96, 1.17]; p = 0.280). However, FD + C presented fewer complications (RR 0.56 [0.33, 0.95]; I²=0%; p = 0.03). No statistical differences were found for mortality (RR 0.86 [0.34, 2.18]; I²=0%; p = 0.75).
Conclusions
The use of adjunctive coils during treatment of large and giant aneurysms with FD seems to reduce the risk of procedural and delayed complications, while it does not increase the aneurysm occlusion rate.