bluuebunny/crossref_metadata_2025_split huggingface dataset:
Undergraduate Medical Students’ Clinical Supervision at The Primary Health Care Services: A Cross-Sectional Survey Among General Practitioners in Morocco
Authors: Essoli Samira , Houdali Ghita , Mansoury Ouassim , Mansouri Adil , Adarmouch Latifa , Amine Mohamed , Sebbani Majda 
Published: June 2023

Abstract
Clinical supervision is crucial for medical students. The general practitioners do not receive any clinical supervision training in Morocco. We aim to describe the general practitioners pedagogical practices, motivations, barriers and needs at the primary health care services. This is a cross-sectional study among general practitioners in Morocco using a volunteer sampling. Data were collected using an online survey, which has included demographics, pedagogical practices, motivations, barriers and needs of the general practitioners. In addition to descriptive statistics, a bivariate analysis was performed using SPSS to identify the associated factors to interest in clinical supervision. The degree of significance is fixed at 5%. 223 general practitioners have participated. The mean age was 43.0 ± 12.8 years with a sex-ratio female/male of 1.52. More than a half of the general practitioners (56.5%) had been working in the public sector. A majority of general practitioners were interested by clinical supervision (82%). The associated factors with the interest in clinical supervision were the exercise in team (p = 0.02) and low job seniority (p = 0.03), general practitioners motivations and needs. Observation (82.4%), direct supervision (82.6%) and explicative discussion around a case (94.6%) were the main pedagogical practices. The principles barriers for the general practitioners were the lack or absence of training on clinical supervision (75.3%) and, understanding of rotations objectives (67.3%). The general practitioners in Morocco were interested in clinical supervision. The majority of general practitioners were interested in CS (82%). The general practitioners motivations and needs have to be reinforced in order to enhance their interest.
Risk factors affecting the severity of radiation pneumonitis after intensity-modulated radiation therapy
Authors: Li Shuting , Zheng Qixian , Hu Cong , Xue Dan , Yang Sheng , Chen Xiangqi 
Published: June 2023

AbstractPurpose:Radiation pneumonitis (RP) is a prevalent complication of thoracic tumor radiotherapy. The purpose of this study is to examine the correlation between clinical and dosimetric factors and the severity of acute radiation pneumonitis (ARP).Methods:We retroactively analyzed the clinical data of 90 patients treated with intensity-modulated radiation therapy (IMRT) from 2017 to 2019 who developed RP. The CTCAE v4.03 criteria were utilized to grade the severity of pneumonitis. To identify potential predictive factors and their association with the severity of RP, both univariate and multivariate analyses were conducted. For the univariate analysis, Kruskal-Wallis rank sums tests were used to compare clinical and dosimetric data of patients with different severity grades of RP. Whenever applicable, p-values were Bonferroni-adjusted.Results:The study's sample consisted of 90 patients diagnosed with RP, with an average age of 57.4 ± 11.1 years (range: 31-85). Univariate analysis revealed a significant association between the severity of ARP and age, sex, ECOG performance status, smoking history, tumor type, treatment mode, and radiation dose (p< 0.05). In the multivariate logistic regression analysis, ECOG performance status showed a significant association with the severity of ARP (odds ratio (OR) = 5.501, confidence interval (CI) 95% 0.312～3.098,P= 0.016) .Conclusion:The severity of RP following thoracic radiotherapy is associated with several patient-related and dosimetric factors, including age, sex, ECOG performance status, smoking history, tumor type, treatment mode, and radiation dose. Therefore, comprehensive evaluation of these risk factors before radiotherapy are crucial to enhance treatment outcomes and patient prognosis.
An Estimation of Regional Climate Sensitivity Using Annual Atmospheric Carbon Dioxide and Land Use Changes over Iraq
Authors: Tawfeek Yasmin Q. , Al-Saadi Luma M. , Al-Jiboori Monim H. , Mahmood Dalia A. 
Published: June 2023

Abstract
Climate sensitivity is the measurement of rising average surface air temperature resulting from doubling the atmospheric carbon dioxide (CO2) concentrations and changes in land cover caused by human activities. Based on annual CO2 concentrations (2003–2016), built-up areas, and average surface air temperature, (1971–2022), this sensitivity is estimated in terms of transient climate response (TCR) and equilibrium climate sensitivity (ECS) and changes in built-up areas for three cities of Iraq: Basra, Baghdad, and Mosul as well as in the whole Iraq. The results show that the values of TCR and ECS in Baghdad are 6.2 and 9.2°C respectively, which are higher than the recommended range by IPCC 5th assessment report, thus the increase in CO2 concentrations will exacerbate regional warming effect, while their values (2.8 and 4.2°C) were found to be within this range for overall Iraq. Also, the results show that built-up area changes have been contributed to increase average air temperature in Basra and Baghdad, while they are not in Mosul, which seems to be affected more by global warming.
Plasma metabolomics indicates potential biomarkers and metabolic pathways of melasma
Authors: Zhang Xiaoli , CHEN Yi , YANG Hedan , Ding Hui , CAI Pingping , GE Yiping , ZHENG Huiying , SUN Xiaojie , YANG Yin , LI Xinyu , LIN Tong 
Published: June 2023

Abstract
Introduction Melasma is a common and chronic pigmentary disorder that has negatively impacted patients’ quality of life. The pathogenesis of melasma is complicated. Metabolomics may contribute to understanding the pathogenesis and identifying intervention strategies for melasma.Objectives To analyze changes in plasma metabolites of female melasma patients and search for disease markers and potential therapeutic targets.Methods Plasma samples from 20 female patients with melasma and 21 age-matched healthy female controls were collected for untargeted metabolomics. Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to analyze the plasma metabolites. Significantly differential metabolites in patients with melasma were identified by metabolic pathways and receiver operating characteristic curves, and correlation analysis was conducted with modified Melasma Area and Severity Index (mMASI) and oxidative stress level.Results Compared with healthy subjects, melasma patients showed significant changes in 125 plasma metabolites, including amino acids, lipids, and carbohydrate-related metabolites. KEGG pathway analysis indicated that tryptophan metabolism and biosynthesis of phenylalanine, tyrosine, and tryptophan pathways may be the main pathways related to melasma pathogenesis. Some metabolites can be considered as biomarkers significantly associated with melasma by ROC analysis and correlation analysis.Conclusions This study identified significant changes in plasma metabolites in melasma patients using UPLC-MS-based metabolomics, which may provide new insights into the pathogenesis of melasma and explore new therapeutic methods.
Controlled v-generalized metric type space and some fixed point theorems with application
Authors: Roy Kushal , Saha Mantu , Parvaneh Vahid , Golkamanesh Farhan , Park Choonkil 
Published: June 2023

Abstract
In this article, the concept of controlled v-generalized metric type space is introduced as a generalization of b v (s)-metric spaces and controlled metric type spaces. Some fixed point theorems are proved for Banach orbital contractions and Bianchini type contractions over such spaces. Several examples are given in respect of our new metric type structure and established theorems. In addition, we use our fixed point theorems to find solutions to nonlinear integral equations.
AMS subject classification (2020): 47H10; 54H25.
State-Dependent Aberrant Gamma-Aminobutyric Acid Reactivity and Downstream Functional Connectivity of Central Autonomic Network Subserve Pathological Intrusive Thinking
Authors: Schettino Martino , Parrillo Chiara , Gazzellini Simone , Cairone Luca , Baldassari Giulia , Thayer Julian F. , Giove Federico , Napolitano Antonio , Ottaviani Christina 
Published: June 2023

Abstract
Alterations in neurotransmission mediated by gamma-aminobutyric acid (GABA), the main inhibitory neurotransmitter, are posited to play a pathophysiological role in stress-related disorders. Evidence, however, comes from the comparisons of pathological and healthy samples at rest and not during specific disease states, making it difficult to understand the processes underlying this assumption. The present study used 3T-proton magnetic resonance spectroscopy to investigate the effects of an experimental induction of intrusive thinking (IT; a transdiagnostic psychiatric symptom) on GABAergic and glutamatergic neurometabolic concentration within the bilateral Anterior Cingulate Cortex (ACC) in individuals with a pathological tendency to engage in IT (n = 29; 11 males) and controls (n = 29; 16 males). To assess physiological and functional concomitants of these neurochemical changes, autonomic measures and resting-state functional magnetic resonance imaging were also acquired before and after induction of IT. While engendering levels of IT amplified ACC GABA and GABA to Glx in the pathological group, an opposite trend emerged for controls. Notably, the pre-to post induction increase in GABAergic neurometabolism in the pathological group was accompanied by a dampened autonomic and resting state functional connectivity within nodes of the Central Autonomic Network. Current results are in line with the view of IT as a “better safe than sorry” strategy, which may be maintained in pathological conditions via a negative reinforcement mechanism through which increased GABAergic neurotransmission fosters avoidance of the transition from a relaxed state to a sudden spike of autonomic activation.
Epitope Generation for Peptide-based Cancer Vaccine using Goal-directed Wasserstein Generative Adversarial Network with Gradient Penalty
Authors: Hsiao Yen-Che , Dutta Abhishek 
Published: June 2023

Abstract
We introduce a novel immunogenicity goal-directed peptide sequence generator in a Wasserstein generative adversarial network (GAN) with gradient penalty. The convolutional neural network-based generator is guided by a critic incorporated with an immunogenicity predictor from DeepImmuno-CNN to generate immunogenic epitopes for bladder cancer vaccines. The convolutional neural network-based critic network is trained to guide the training of the generator with the peptide sequences received from the generator or the training data containing the bladder cancer epitope sequences that are bound with the human leukocyte antigen, HLA-A*0201. We trained the critic with the generated peptide sequences with the immunogenicity scores lower than the average immunogenicity score from a batch of samples. The results show our generator can produce more immunogenic peptides and can produce peptides that are similar to the epitopes shown in bladder cancer cells. Our generator provides more epitope candidates to facilitate the design of peptide-based cancer vaccines.
Factors Influencing Mercury Exposure in Arctic-Breeding Shorebirds
Authors: Perkins Marie , Stenhouse Iain , Lanctot Richard B. , Brown Stephen , Bêty Joël , Boldenow Megan , Cunningham Jenny , English Willow , Gates River , Gilchrist Grant , Giroux Marie-Andrée , Grond Kirsten , Hill Brooke , Kwon Eunbi , Lamarre Jean-Francois , Lank David , Lecomte Nicolas , Pavlik David , Rausch Jennie , Regan Kevin , Robards Martin , Saalfeld Sarah T. , Smith Fletcher , Smith Paul , Wilkinson Bradley , Woodard Paul , Basu Niladri 
Published: June 2023

Abstract
Mercury (Hg) pollution remains a concern to Arctic ecosystems. The objective of this study was to identify factors influencing Hg concentrations in Arctic-breeding shorebirds and highlight regions and species at greatest risk of Hg exposure. We analyzed 2,478 blood and feather samples from 12 shorebird species breeding at nine sites across the North American Arctic during 2012 and 2013. Blood Hg concentrations, which reflect Hg exposure in the local area in individual shorebirds: 1) ranged from 0.01–3.52 µg/g, with an overall mean of 0.30 ± 0.27 µg/g; 2) were influenced by species and study site, but not sampling year, with birds sampled near Utqiaġvik, AK, having the highest concentrations; and 3) were influenced by foraging habitat at some sites. Feather Hg concentrations, which reflected Hg exposure from the wintering grounds, were generally higher than blood, ranging from 0.07–12.14 µg/g in individuals, with a mean of 1.14 ± 1.18 µg/g. Feather Hg concentrations were influenced by species and year. Most Arctic-breeding shorebirds had blood and feather Hg concentrations at levels where no adverse effects of exposure were likely, though some individuals sampled near Utqiaġvik had Hg levels that are certainly of concern. Overall, these data increase our understanding of how Hg is distributed in the various habitats of the Arctic, and what factors predispose Arctic-breeding shorebirds to Hg, and lay the foundation for future monitoring efforts.
Depth-based Multivariate Records: Maximum Likelihood Estimation
Authors: Tat Samaneh , Faridrohani Mohammad Reza 
Published: June 2023

Abstract
In this article, the maximum likelihood estimation approach is considered for estimating the unknown parameters of some members of the elliptical distributions using the depth-based multivariate record values, a new innovative concept of records recently defined by the authors. Unlike other multivariate records, depth-based mul-tivariate records have the advantage that based on these records, inferences about the unknown parameters can be made.The problem is discussed under some scenarios in which the Mahalanobis and projection depth functions are employed. For all the scenarios, the maximum likelihood equations are formulated and the maximum likelihood estimates are obtained through numerical methods. The behavior of which is evaluated by using some simulation studies and studying the drought in Kermanshah, Iran. The results demonstrate the good performance of MLEs.
MSC codes: 62H12, 62G32.
Artificial Intelligence in Cancer Diagnosis: A Systematic Review
Authors: Rangasamy Deepa 
Published: June 2023

Abstract
The application of artificial intelligence (AI) in cancer detection has shown promising potential to improve diagnostic accuracy and patient outcomes. This review aims to provide a comprehensive overview of the current state of AI in cancer detection and its implications in clinical practice. We systematically reviewed the literature to identify relevant studies on AI- based cancer detection. The review covers various cancer types, including breast, lung, skin, and others. We examined the AI algorithms used, such as machine learning and deep learning, and the diagnostic modalities employed, such as medical imaging and pathology. Performance metrics, including sensitivity, specificity, and accuracy, were assessed to evaluate the effectiveness of AI algorithms in cancer detection. The key findings demonstrate that AI algorithms can achieve comparable or even superior performance to human experts in detecting and classifying cancer. However, challenges such as data quality, interpretability, and algorithm robustness need to be addressed for successful implementation in clinical settings. AI in cancer detection holds great promise for improving early diagnosis, personalized treatment, and patient outcomes. Further research and collaboration between clinicians, researchers, and AI experts are essential to overcome challenges and realize the full potential of AI in cancer detection.
How does ChatGPT perform on the European Board of Pediatric Surgery examination? A randomized comparative study
Authors: Azizoğlu Mustafa , Okur Mehmet Hanifi 
Published: June 2023

Abstract
Purpose
The purpose of this study was to conduct a detailed comparison of the accuracy and responsiveness of GPT-3.5 and GPT-4 in the realm of pediatric surgery. Specifically, we sought to assess their ability to correctly answer a series of sample questions of European Board of Pediatric Surgery (EBPS) exam.
Methods
This study was conducted between 20 May 2023 and 30 May 2023. This study undertook a comparative analysis of two AI language models, GPT-3.5 and GPT-4, in the field of pediatric surgery, particularly in the context of EBPS exam sample questions. Two sets of 105 (total 210) sample questions each, derived from the EBPS sample questions, were collated.
Results
In General Pediatric Surgery, GPT-3.5 provided correct answers for 7 questions (46.7%), and GPT-4 had a higher accuracy with 13 correct responses (86.7%) (p = 0.020). For Newborn Surgery and Pediatric Urology, GPT-3.5 correctly answered 6 questions (40.0%), and GPT-4, however, correctly answered 12 questions (80.0%) (p = 0.025). In total, GPT-3.5 correctly answered 46 questions out of 105 (43.8%), and GPT-4 showed significantly better performance, correctly answering 80 questions (76.2%) (p < 0.001). Given the total responses, when GPT-4 was compared with GPT-3.5, the Odds Ratio was found to be 4.1. This suggests that GPT-4 was 4.1 times more likely to provide a correct answer to the pediatric surgery questions compared to GPT-3.5.
Conclusion
This comparative study concludes that GPT-4 significantly outperforms GPT-3.5 in responding to EBPS exam questions.
Non-targeted LC-MS/MS metabolomic profiling of human plasma uncovers a novel Mediterranean diet biomarker panel
Authors: Macias Shirin , Yilmaz Ali , Kirma Joseph , Moore Sarah E. , Woodside Jayne V. , Graham Stewart F. , Green Brian D. 
Published: June 2023

Abstract

• Introduction: Consumption of a Mediterranean diet (MD) has established health benefits, and the identification of novel biomarkers could enable objective monitoring of dietary pattern adherence. • Objectives: The present investigation performed untargeted metabolomics on blood plasma from a controlled study of MD adherence, to identify novel blood-based metabolite biomarkers associated with the MD pattern, and to build a logistic regression model that could be used to characterise MD adherence. • Methods: A hundred and thirty-five plasma samples from n = 58 patients collected at different time points were available. Using a 14-point scale MD Score (MDS) subjects were divided into ‘high’ or ‘low’ MDS adherence groups and liquid chromatography-mass spectrometry (LC-MS/MS) was applied for analysis. • Results: The strongest association with MDS was pectenotoxin 2 seco acid (r = 0.53; ROC = 0.78), a non-toxic marine xenobiotic metabolite. Several lipids were useful biomarkers including eicosapentaenoic acid, the structurally related lysophospholipid (20:5(5Z,8Z,11Z,14Z,17Z)/0:0), a phosphatidylcholine (P-18:1(9Z)/16:0) and also xi-8-hydroxyhexadecanedioic acid. Two metabolites negatively correlated with MDS, these were the monoacylglycerides (0:0/16:1(9Z)/0:0) and (0:0/20:3(5Z,8Z,11Z)/0:0). By stepwise elimination we selected a panel of 3 highly discriminatory metabolites and developed a linear regression model which identified ‘high MDS’ individuals with high sensitivity and specificity (AUC (95% CI) = 0.83 (0.76–0.97)). • Conclusion: Our study highlights the utility of metabolomics as an approach for developing novel panels of dietary biomarkers. Quantitative profiling of these metabolites is required to validate their utility for evaluating dietary adherence.
The decryption of BAB1 Brucella abortus antigen- BCAP31 receptor binding in oral lactococcus lactis vaccine and its effect on activation of casp-8 and IL-10 for immunogenicity
Authors: Doosti Abbas , Kazemi Donya , Shakhsi-Niaei Mostafa 
Published: June 2023

Abstract
The authors have requested that this preprint be removed from Research Square.
Design Optimization of LNA using PSO algorithm with Multi Stage Noise Matching Technique for UWB Application
Authors: Kumar Manish , Kalra Dheeraj , Shukla Aasheesh 
Published: June 2023

Abstract

This manuscript describe optimization of LNA using PSO algorithms. The proposed LNA consist of two stage cascading. In the first stage current reused technique has been used using complementary MOS. Both the MOS use the common biasing current, henceforth saving a lot of power. While second stage is the cascading of two NMOS transistors, to increase the overall gain. Since traditional method of impedance matching is not sufficient to reduce the Noise Figure(NF). Therefore, an approach aiming to minimize high band noise has been used at the cost of increase in NF minimum. All the passive elements and aspect ratio are optimized through PSO in which objective function consist of NF and voltage gain term. Number of iterations used in PSO algorithm is 1500. LNA is simulated in 45 nm CMOS Technology for a wide range of frequency from 1GHz to 20GHz. Simulation show minimum NF of 1.89 Db, power gain(S21) and input reflection coefficient(S11) 16.8dB and − 19.2dB. Process corner simulation for robust ness of LNA has been done and depicted ten percent variation around the typical value of LNA. The power consumption of 32 mW and chip area order of 2.2mm × 1.6mm with core area is 650 µm in layout design.
Cracking the Code of Antibiotic Resistance OF Klebsiella pneumoniae ST16: A Computational Exploration of Whole Genome Sequences for Beta-lactam Resistance and the Discovery of NMD-1 Resistance Gene Inhibitor
Authors: Faleti Ayodele Ifeoluwa , Ibisanmi Tope Abraham 
Published: June 2023

AbstractAntibiotic resistance is a growing concern in the field of healthcare and medicine. This research project involves an exploration of the whole genome sequences ofKlebsiella pneumoniaeST16 from NCBI database with the aim of identifying resistance gene and potentially discovering its inhibitor. The study revealed the existence of several resistance genes to various classes of antibiotics, including macrolides, fluoroquinolones, aminoglycosides, sulphonamides, rifampicin, trimethoprim, and beta-lactams. Among these, blaTEM-1B, blaCTX-M-15, and blaNDM-1 were identified. Additionally, mutations were observed in the genes acrR, ompK36, and gyrA, along with changes in the corresponding amino acids, which are linked to resistance to different antibiotics. This analysis also identified the alleles present in each locus, with FIA having a novel allele, the molecular docking results indicate that Baicalein exhibited the highest docking scores of -7.7 respectively, indicating their strong binding affinity to the NDM-1 found to be associated with beta-lactams. The RMSD plot showed that both the Baicalein and Adapalene complexes of NDM-1 exhibited stable behavior over the 50 ns simulation period. However, the slightly higher Rg of the New Delhi Metallo-Beta-Lactamase 1-Adapalene complex indicates that this complex may be slightly more flexible than the New Delhi Metallo-Beta-Lactamase 1-Baicalein complex. In conclusion, the study provides valuable insights into the mechanisms of antibiotic resistance, particularly the role of the NDM-1 gene in beta-lactam resistance. Furthermore, the molecular docking analysis identified Baicalein, Taxifolin, and Ellagic acid as the top three bioactive compounds that exhibited strong binding affinity to the NDM-1 domain.