bluuebunny/crossref_metadata_2025_split huggingface dataset:
Facilitators and barriers in acceptance of telemedicine among healthcare providers in Pakistan: A cross-sectional survey
Authors: Wasi Abbas Muhammad , Nawaz Tahir Hasan , Jaffar Nazish , Raza Ghana , Aman Ali Syed , Jabeen Rawshan 
Published: July 2024

Objectives: This study aimed to assess healthcare professionals’ awareness and acceptance of telemedicine residing in Pakistan. Materials and Methods: A cross-sectional study was conducted across Pakistan from November 2021 to March 2022. Data entry was done through a self-administered questionnaire. In this survey, the non-probability purposive sampling method was adopted. Medical doctors from all specialties that fall into the age category of 20–60 years were included in this study. Statistical Package for Social Sciences (SPSS) version 22.0 was used for univariate data analysis. Results: Among the 860 healthcare professionals who received the survey, 198 responded (23.0% response rate). The mean ± SD age of the participants was 31.16 ± 8.56. The results were found to be statistically significant for knowledge about telemedicine among healthcare professionals workplace, that is, healthcare professionals working in the private sector indicated a high level of awareness regarding telemedicine as compared to those in the public sector ( p = 0.03). A significant difference ( p-value ⩽ 0.05) in knowledge was seen among doctors working in the public sector and those working in a private setup. Results indicate significant positive associations between telemedicine utilization and perceived benefits over disadvantages ( β = 1.03, p = 0.017), reliance among healthcare professionals (β = 1.22, p = 0.008), and enhancement in healthcare quality ( β = 1.42, p = 0.001). Moreover, familiarity with telemedicine correlates strongly with its usage ( β = 2.56, p < 0.000). Conclusion: Overall, healthcare professionals exhibited satisfactory knowledge regarding telemedicine and showed an accepting attitude toward telemedicine. Our study recommends enhancing the importance of Telemedicine training at the Healthcare professionals’ level to produce quality service delivery in healthcare organizations.
Quality of antiretroviral, antimalarial and antituberculosis medicines in Zambia: Findings of routine post-marketing surveillance
Authors: Jere Elimas , Munkombwe Derrick , Mukosha Moses , Mudenda Steward , Kalungia Aubrey Chichonyi , Chabalenge Billy 
Published: July 2024

Background:There is growing concern in sub-Saharan Africa that poor-quality antimicrobial medicines may negate management of infectious diseases of public health importance should they fail to meet the set criteria of quality, safety and efficacy.Objectives:The objective was to ascertain the quality of antiretroviral, antimalarial and antituberculosis medicines supplied and available in the public health sector in Zambia.Design:A descriptive cross-sectional study was conducted involving the analysis of data from the continuous routine in-country post-marketing surveillance programme in Zambia that assessed the quality of antiretroviral, antimalarial and antituberculosis medicines supplied to public healthcare facilities between January 2018 and June 2023.Methods:Data were extracted from laboratory quality analysis results from samples collected as part of routine post-marketing surveillance by the Zambia Medicines Regulatory Authority between January 2018 and June 2023. The samples were collected from various levels of the pharmaceutical supply chain across Zambia. Samples were analysed according to their respective pharmacopoeia standards at the Medicines Control Authority of Zimbabwe Quality Control Laboratory, a World Health Organization prequalified laboratory. Data were extracted using a structured Excel database and analysed using Microsoft Excel, and GraphPad Prism Software was used for visualizations.Results:Of the 198 samples, 86 (43.43%) were antiretrovirals, 54 (27.27%) antimalarials and 58 (29.29%) antituberculosis medicines. Of these 198 samples, 171 (86.36%) originated from Asia, 19 (9.60%) Africa and 8 (4.04%) Europe. All sampled medicines met their respective quality specifications with respect to tests, which included appearance, identification, assay, uniformity of mass, weight variation, disintegration, dissolution, pH and specific gravity, giving a compliance rate of 100%.Conclusion:Antiretrovirals, antimalarials and antituberculosis medicines obtained from public healthcare facilities in Zambia through routine post-marketing surveillance met their quality standards. This might positively impact treatment outcomes for HIV/AIDS, malaria and tuberculosis. There is a need for large-scale continuous monitoring of the quality of medicines in order to ensure quality is maintained and substandard products removed from the pharmaceutical supply chain.
Multi-parametric MRI-based machine learning model for prediction of pathological grade of renal injury in a rat kidney cold ischemia-reperfusion injury model
Authors: Chen Lihua , Ren Yan , Yuan Yizhong , Xu Jipan , Wen Baole , Xie Shuangshuang , Zhu Jinxia , Li Wenshuo , Gong Xiaoli , Shen Wen 
Published: July 2024

Abstract
Background
Renal cold ischemia-reperfusion injury (CIRI), a pathological process during kidney transplantation, may result in delayed graft function and negatively impact graft survival and function. There is a lack of an accurate and non-invasive tool for evaluating the degree of CIRI. Multi-parametric MRI has been widely used to detect and evaluate kidney injury. The machine learning algorithms introduced the opportunity to combine biomarkers from different MRI metrics into a single classifier.

Objective
To evaluate the performance of multi-parametric magnetic resonance imaging for grading renal injury in a rat model of renal cold ischemia-reperfusion injury using a machine learning approach.

Methods
Eighty male SD rats were selected to establish a renal cold ischemia -reperfusion model, and all performed multiparametric MRI scans (DWI, IVIM, DKI, BOLD, T1mapping and ASL), followed by pathological analysis. A total of 25 parameters of renal cortex and medulla were analyzed as features. The pathology scores were divided into 3 groups using K-means clustering method. Lasso regression was applied for the initial selecting of features. The optimal features and the best techniques for pathological grading were obtained. Multiple classifiers were used to construct models to evaluate the predictive value for pathology grading.

Results
All rats were categorized into mild, moderate, and severe injury group according the pathologic scores. The 8 features that correlated better with the pathologic classification were medullary and cortical Dp, cortical T2*, cortical Fp, medullary T2*, ∆T1, cortical RBF, medullary T1. The accuracy(0.83, 0.850, 0.81, respectively) and AUC (0.95, 0.93, 0.90, respectively) for pathologic classification of the logistic regression, SVM, and RF are significantly higher than other classifiers. For the logistic model and combining logistic, RF and SVM model of different techniques for pathology grading, the stable and perform are both well. Based on logistic regression, IVIM has the highest AUC (0.93) for pathological grading, followed by BOLD(0.90).

Conclusion
The multi-parametric MRI-based machine learning model could be valuable for noninvasive assessment of the degree of renal injury.
Prediction of leukemia peptides using convolutional neural network and protein compositions
Authors: Khawaja Seher Ansar , Farooq Muhammad Shoaib , Ishaq Kashif , Alsubaie Najah , Karamti Hanen , Montero Elizabeth Caro , Alvarado Eduardo Silva , Ashraf Imran 
Published: July 2024

AbstractLeukemia is a type of blood cell cancer that is in the bone marrow’s blood-forming cells. Two types of Leukemia are acute and chronic; acute enhances fast and chronic growth gradually which are further classified into lymphocytic and myeloid leukemias. This work evaluates a unique deep convolutional neural network (CNN) classifier that improves identification precision by carefully examining concatenated peptide patterns. The study uses leukemia protein expression for experiments supporting two different techniques including independence and applied cross-validation. In addition to CNN, multilayer perceptron (MLP), gated recurrent unit (GRU), and recurrent neural network (RNN) are applied. The experimental results show that the CNN model surpasses competitors with its outstanding predictability in independent and cross-validation testing applied on different features extracted from protein expressions such as amino acid composition (AAC) with a group of AAC (GAAC), tripeptide composition (TPC) with a group of TPC (GTPC), and dipeptide composition (DPC) for calculating its accuracies with their receiver operating characteristic (ROC) curve. In independence testing, a feature expression of AAC and a group of GAAC are applied using MLP and CNN modules, and ROC curves are achieved with overall 100% accuracy for the detection of protein patterns. In cross-validation testing, a feature expression on a group of AAC and GAAC patterns achieved 98.33% accuracy which is the highest for the CNN module. Furthermore, ROC curves show a 0.965% extraordinary result for the GRU module. The findings show that the CNN model is excellent at figuring out leukemia illnesses from protein expressions with higher accuracy.
Landscape of clinical drug development of ADCs used for the pharmacotherapy of cancers: an overview of clinical trial registry data from 2002 to 2022
Authors: Zhou Wenjing , Xu Zhiyuan , Liu Shu , Lou Xiaohuan , Liu Pengcheng , Xie Huali , Zhang Shuiyan , Liu Xi , Zhuo Baoshan , Huang Hongbing 
Published: July 2024

Abstract
Background
To provide reference for clinical development of ADCs in the industry, we analyzed the landscape and characteristics of clinical trials about antibody-drug conjugates (ADCs).

Method
Clinical trials to study ADCs used for the pharmacotherapy of cancers initiated by the sponsor were searched in the Cite line Pharma Intelligence (Trialtrove database), and the landscape and characteristics of these clinical trials were analyzed from multiple perspectives, such as the number, phases, status, indications, and targets of the clinical trials.

Result
As of December 31, 2022, a total of 431 clinical trials have been initiated to study ADCs used for the pharmacotherapy of cancers, and the number of the last 10 years was 5.5 times as large as the first 11 years. These clinical trials involved 47 indications, including breast cancer, lymphoma (lymphoma, non-Hodgkin’s and lymphoma, Hodgkin’s), unspecified solid tumor, bladder cancer and lung cancer (lung, non-small cell cancer and lung, small cell cancer). As for each of these five indications, 50 + clinical trials have been carried out, accounting for as high as 48.50% (454/936). ADCs involve 38 targets, which are relatively concentrated. Among them, ERBB2 (HER2) and TNFRSF8 (CD30) involve in 100 + registered clinical trials, and TNFRSF17 (BCMA), NECTIN4 and CD19 in 10 + trials. The clinical trials for these five targets account for 79.02% (354/448) of the total number. Up to 93.97% (405/431) of these clinical trials explored the correlation between biomarkers and efficacy. Up to 45.91% (292/636) of Lots (lines of treatment) applied in the clinical trials were the second line. Until December 31, 2022, 54.52% (235/431) of the clinical trials have been completed or terminated.

Conclusion
ADCs are a hotspot of research and development in oncology clinical trials, but the indications, targets, phases, and Lot that have been registered are seemingly relatively concentrated at present. This study provides a comprehensive analysis which can assist researchers/developer quickly grasp relevant knowledge to assess a product and also providing new clues and ideas for future research.
Conducting an objective structured clinical examination under COVID-restricted conditions
Authors: Gotzmann Andrea , Boulet John , Zhang Yichi , McCormick Judy , Wojcik Mathieu , Bartman Ilona , Pugh Debra 
Published: July 2024

Abstract
Background
The administration of performance assessments during the coronavirus disease of 2019 (COVID-19) pandemic posed many challenges, especially for examinations employed as part of certification and licensure. The National Assessment Collaboration (NAC) Examination, an Objective Structured Clinical Examination (OSCE), was modified during the pandemic. The purpose of this study was to gather evidence to support the reliability and validity of the modified NAC Examination.

Methods
The modified NAC Examination was delivered to 2,433 candidates in 2020 and 2021. Cronbach’s alpha, decision consistency, and accuracy values were calculated. Validity evidence includes comparisons of scores and sub-scores for demographic groups: gender (male vs. female), type of International Medical Graduate (IMG) (Canadians Studying Abroad (CSA) vs. non-CSA), postgraduate training (PGT) (no PGT vs. PGT), and language of examination (English vs. French). Criterion relationships were summarized using correlations within and between the NAC Examination and the Medical Council of Canada Qualifying Examination (MCCQE) Part I scores.

Results
Reliability estimates were consistent with other OSCEs similar in length and previous NAC Examination administrations. Both total score and sub-score differences for gender were statistically significant. Total score differences by type of IMG and PGT were not statistically significant, but sub-score differences were statistically significant. Administration language was not statistically significant for either the total scores or sub-scores. Correlations were all statistically significant with some relationships being small or moderate (0.20 to 0.40) or large (> 0.40).

Conclusions
The NAC Examination yields reliable total scores and pass/fail decisions. Expected differences in total scores and sub-scores for defined groups were consistent with previous literature, and internal relationships amongst NAC Examination sub-scores and their external relationships with the MCCQE Part I supported both discriminant and criterion-related validity arguments. Modifications to OSCEs to address health restrictions can be implemented without compromising the overall quality of the assessment. This study outlines some of the validity and reliability analyses for OSCEs that required modifications due to COVID.
Novel hypoxia-induced HIF-1αactivation in asthma pathogenesis
Authors: Wan Mengzhi , Yu Qi , Xu Fei , You Lu Xia , Liang Xiao , kang Ren Kang , Zhou Jing 
Published: July 2024

Abstract
Background
Asthma’s complexity, marked by airway inflammation and remodeling, is influenced by hypoxic conditions. This study focuses on the role of Hypoxia-Inducible Factor-1 Alpha (HIF-1α) and P53 ubiquitination in asthma exacerbation.

Methods
High-throughput sequencing and bioinformatics were used to identify genes associated with asthma progression, with an emphasis on GO and KEGG pathway analyses. An asthma mouse model was developed, and airway smooth muscle cells (ASMCs) were isolated to create an in vitro hypoxia model. Cell viability, proliferation, migration, and apoptosis were assessed, along with ELISA and Hematoxylin and Eosin (H&E) staining.

Results
A notable increase in HIF-1α was observed in both in vivo and in vitro asthma models. HIF-1α upregulation enhanced ASMCs’ viability, proliferation, and migration, while reducing apoptosis, primarily via the promotion of P53 ubiquitination through MDM2. In vivo studies showed increased inflammatory cell infiltration and airway structural changes, which were mitigated by the inhibitor IDF-11,774.

Conclusion
The study highlights the critical role of the HIF-1α-MDM2-P53 axis in asthma, suggesting its potential as a target for therapeutic interventions. The findings indicate that modulating this pathway could offer new avenues for treating the complex respiratory disorder of asthma.
Study of the therapeutic strategy to improve survival outcomes from the perspective of perioperative conditions in elderly gastric cancer patients: a propensity score-matched analysis
Authors: Nomura Eiji , Seki Takatoshi , Yatabe Kentaro , Yoshii Hisamichi , Izumi Hideki , Okada Kazutake , Kayano Hajime , Yamamoto Soichiro , Mukai Masaya , Makuuchi Hiroyasu 
Published: July 2024

Abstract
Background
Elderly gastric cancer patients (EGCPs) require treatment according to not just the stage of their cancer, but also to their general condition and organ function, and rather than full treatment, the appropriate amount of treatment is necessary.

Methods
A total of 425 patients who underwent gastrectomy for primary gastric cancer in our institution between April 2013 and March 2020 were classified by age into two groups: elderly patients (EP, age ≥ 80 years, n = 89); and younger patients (YP, age < 80 years, n = 336). The preoperative, intraoperative, and postoperative conditions of the two groups were then compared. Propensity score matching (PSM) was performed, and factors affecting complications and survival outcomes were examined in detail. In addition, the necessary treatment strategy for EGCPs in the preoperative, intraoperative, and postoperative periods was investigated.

Results
Of the preoperative factors, American Society of Anesthesiologists physical status (ASA-PS) was significantly higher, and respiratory function was significantly lower in the EP group than in the YP group, and the prognostic nutritional index (PNI) also tended to be lower. Of the intraoperative factors, there was no difference in the level of lymph node dissection. However, the EP group had significantly higher rates of postoperative pneumonia and anastomotic leakage. Of the postoperative factors, on simple comparison, postoperative long-term outcomes of the EP group were significantly worse (63.8% vs. 85.4%, p < 0.001), but there was no significant difference in disease-specific survival (DSS), and the DSS survival curves after PSM were almost identical, indicating that the survival rate in the EP group was decreased by death from other disease. Though the survival rate of laparoscopic surgery was significantly better than that of open surgery in the YP group, there was a significantly lower rate of postoperative complications in the EP group after PSM.

Conclusions
In EGCPs, one needs to be aware of short-term complications such as pneumonia and anastomotic leakage due to respiratory dysfunction and malnutrition that are present before surgery. Furthermore, to suppress deaths from other diseases that reduce postoperative survival rates, prevention of postoperative complications (particularly pneumonia) through minimally invasive surgery can be effective.
Predictors of functional improvement and pain reduction in rheumatoid arthritis patients who achieved low disease activity with disease-modifying antirheumatic drugs: a retrospective study of the FIRST Registry
Authors: Ochi Sae , Sonomoto Koshiro , Nakayamada Shingo , Tanaka Yoshiya 
Published: July 2024

Abstract
Background
Rheumatoid arthritis (RA) patients sometimes exhibit different levels of improvement in health assessment questionnaire-disability index (HAQ-DI) and subjective pain visual analogue score (VAS) even after achieving low disease activities (LDA). This study aimed to identify factors associated with improvement in HAQ-DI and pain VAS among those who achieved LDA.

Methods
Data of the FIRST registry, a multi-institutional cohort of RA patients treated with biological and targeted-synthetic DMARDs (b/tsDMARDs) were analyzed. Patients who were enrolled from August 2013 to February 2023 and who achieved clinical LDA [clinical disease activity index (CDAI) ≤ 10.0] at 6 months after starting treatment were included. Multiple logistic regression analyses were conducted to identify the factors that associated with achieving HAQ-DI normalization (< 0.5), HAQ-DI improvement (by > 0.22), or pain VAS reduction (≤ 40 mm).

Results
Among 1424 patients who achieved LDA at 6 months, 732 patients achieved HAQ-DI normalization and 454 achieved pain VAS reduction. The seropositivity and the use of JAK inhibitor compared with TNF inhibitor were associated with both HAQ-DI < 0.5 and pain VAS reduction at 6 months. On the other hand, older age, past failure in ≥ 2 classes of b/tsDMARDs, higher HAQ-DI at baseline, and use of glucocorticoid were associated with the lower likelihood of HAQ-DI normalization and pain VAS reduction. Longer disease duration, being female, and higher disease activity at baseline was negatively associated HAQ-DI normalization alone. Comorbidities were not associated with the outcomes.

Conclusions
These results suggest some preferable treatment may exist for improvement of HAQ-DI and pain VAS reduction in the early stage of the treatment, which is a clue to prevention of a criteria of difficult-to-treat RA.
CRISPR-Cas guide RNA indel analysis using CRISPResso2 with Nanopore sequencing data
Authors: McFarlane Gus Rowan , Polanco Jenin Victor Cortez , Bogema Daniel 
Published: July 2024

Abstract
Objective
Insertion and deletion (indel) analysis of CRISPR-Cas guide RNAs (gRNAs) is crucial in gene editing to assess gRNA efficiency and indel frequency. This study evaluates the utility of CRISPResso2 with Oxford Nanopore sequencing data (nCRISPResso2) for gRNA indel screening, compared to two common Sanger sequencing-based methods, TIDE and ICE. To achieve this, sheep and horse fibroblasts were transfected with Cas9 and a gRNA targeting the myostatin (MSTN) gene. DNA was subsequently extracted, and PCR products exceeding 600 bp were sequenced using both Sanger and Nanopore sequencing. Indel profiling was then conducted using TIDE, ICE, and nCRISPResso2.

Results
Comparison revealed close correspondence in indel formation among methods. For the sheep MSTN gRNA, indel percentages were 52%, 58%, and 64% for TIDE, ICE, and nCRISPResso2, respectively. Horse MSTN gRNA showed 81%, 87%, and 86% edited amplicons for TIDE, ICE, and nCRISPResso2. The frequency of each type of indel was also comparable among the three methods, with nCRISPResso2 and ICE aligning the closest. nCRISPResso2 offers a viable alternative for CRISPR-Cas gRNA indel screening, especially with large amplicons unsuitable for Illumina sequencing. CRISPResso2’s compatibility with Nanopore data enables cost-effective and efficient indel profiling, yielding results comparable to common Sanger sequencing-based methods.