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Does age matter? Impact of age on testicular function and pregnancy outcomes following microsurgical varicocelectomy in patients with grade 3 varicocele
No full textObjective
To evaluate the effects of age on semen and hormonal parameters following microsurgical varicocelectomy among patients with grade 3 varicocele, and to compare fertility outcomes between younger (<40 years) and older (≥40 years) men.
Methods
Retrospective cohort study of infertile patients with clinical left grade 3 varicocele who underwent microsurgical subinguinal varicocelectomy (MV). Patients meeting the inclusion criteria (N = 550) were divided into two groups based on their age at the time of MV: <40 (n = 441) and ≥40 years (n = 109). Preoperative semen analysis and hormonal profiles were collected, and follow-up data including pregnancy outcomes were gathered at 3 and 6 months post-surgery.
Results
Post-surgery, the younger group showed significant improvements in sperm count and total motility (p < 0.001 for each) as well as progressive motility (p = 0.005), while older men exhibited a significant increase in progressive motility (p = 0.002). For each group, there were no significant changes in hormonal levels post-surgery. Comparative analysis across the two age groups showed no significant differences in the postoperative extent of semen improvements or pregnancy.
Conclusion
MV is a viable option for older infertile patients as it is for younger infertile men with grade 3 varicocele, and both groups can achieve similarly high rates of pregnancy outcomes.The authors thank the Laboratory technicians and Coordinators at the Male infertility Unit at the Ambulatory care center, Hamad Medical Corporation.Scopu
The Yemeni genetic structure revealed by the Y chromosome STRs
Get PDFYemen, with its rich historical background and strategic geographical position at a major crossroads of trade and migration, offers an ideal setting for exploring population genetics. This study aimed to develop a Y-STR database for a Yemeni population and compare it with existing regional databases in the Middle East. For this investigation, buccal swabs were collected from 128 unrelated males. Genomic DNA was extracted using the QIAamp® DNA Mini Kit, and Y-chromosomal STR profiling was performed with the AmpFℓSTR® Yfiler™ PCR Amplification Kit to generate haplotype data across 17 Y-STR loci. The final dataset exhibited a haplotype diversity of 0.008 and a discrimination capacity of 0.95. Among the STR loci assessed, DYS458 emerged as the most polymorphic, displaying a gene diversity of 0.87 and accounting for the majority of microvariant alleles (62.5%). Additionally, haplogroup analysis using the NevGen haplogroup predictor tool revealed two predominant haplogroups within this Yemeni population: J1a (59.37%) and E1b1b (21.09%). Comparisons with 52 Middle Eastern populations (encompassing 5,568 individuals) through multidimensional scaling, phylogenetic assessments, admixture analyses, and ancestry variability evaluations collectively underscore the unique genetic landscape of Yemen. Overall, the combined findings indicate evidence of a potential founder effect within the Yemeni population. Taken together, these data not only enrich the forensic and population genetic understanding of the region but also emphasize Yemen’s pivotal role in illuminating migration and demographic processes in the Middle East.This work was supported by British Chevening Scholarship (Grant numbers Ref: YE 70010535). Author K.A. has received research support from Company British Chevening Scholarship.Scopu
Health Pulse : World Hand Hygiene Day
No full textWorld Hand Hygiene Day, May 5, 2025 emphasizes hand hygiene as essential for patient safety and infection prevention
A Snapshot of Antimicrobial Resistance in Semi-Wild Oryx: Baseline Data from Qatar
Get PDFBackground/Objectives: The spread of antimicrobial resistance (AMR) is a growing global health concern. Wild animals can play an important role in the amplification and dissemination of AMR and in conservation efforts aiming at controlling diseases in vulnerable wild animal populations. These animals can serve as reservoirs for antibiotic resistance genes and are key in the spread of AMR across ecosystems and hosts. Therefore, monitoring AMR in wild animals is crucial in tackling the spread of resistance in the environment and human population. This study investigated the phenotypic and genotypic resistance of Escherichia coli (E. coli) isolated from semi-wild oryx (Oryx leucoryx) in Qatar. Methods: One hundred fecal samples were collected from oryx in diverse natural reserves across Qatar. A selective agar medium was used to isolate E. coli, and the identity of the isolates was further confirmed using the VITEK 2 Compact system. The Kirby-Bauer disk diffusion method was used to test antibiotic susceptibility. Genetic resistance determinants were identified through polymerase chain reaction (PCR) analyses and sequencing using the Oxford Nanopore Technology (ONT). Results: The results revealed that 18% (n = 18) of the samples harbored E. coli with resistance to a single antibiotic, 28% (n = 28) were resistant to at least one antibiotic, and 2% (n = 2) were multidrug-resistant (MDR). No resistance was observed against colistin. tetA and tetB encode tetracycline resistance were the most frequently detected genes (57.7%). Whole genome sequencing (WGS) was used to expand on AMR gene-PCR analyses and analyze the resistome of 12E. coli isolates. WGS identified several important antibiotic resistance determinates, including blaCTX-M-encoding Extended Spectrum Beta-Lactamase (ESBL) resistance, soxR associated with tetracycline target alteration, and mdtE, emrB, AcrE, mdtF, and marA related to ciprofloxacin efflux pump resistance. Conclusions: This study provides essential information regarding AMR in Qatari semi-wild animals, which will guide conservation strategies and wildlife health management in a world experiencing increasing antibiotic-resistant infections. Furthermore, these findings can inform policies to mitigate AMR spread, improve ecosystems, and enhance public and environmental health while paving the way for future research on AMR dynamics in wildlife.This work was financially supported by the Qatar National Research Fund grant no (HSREP05-1014-230038) and by the BRC, Qatar University.Scopu
From values to action: the role of personal and social values in shaping K−12 teachers' wellbeing and professional outcomes
Get PDFThis systematic review explores the values upheld by K−12 teachers, examining their impact on teachers' wellbeing and their professional outcomes. Anchored in Schwartz's theory of human values, this study investigates the close and complex relationships between teachers' core values—namely, conservation, openness to change, self-transcendence, and self-enhancement—and their subsequent influence on wellbeing and professional outcomes. This research provides valuable insights for policymakers and educational leaders, offering a framework for fostering environments that help teachers cultivate values conducive to their wellbeing and professional success. The results serve as a guide for the development of policies and educational strategies that aim to enhance teacher satisfaction, promote teaching self-efficacy, and optimize classroom management practices.The author(s) declare that financial support was received for the research and/or publication of this article. This research was funded by Qatar University (QUHI-CEDU-23/24/293)
Automated Segmentation of Breast Cancer Focal Lesions on Ultrasound Images
Get PDFUltrasound (US) remains the main modality for the differential diagnosis of changes revealed by mammography. However, the US images themselves are subject to various types of noise and artifacts from reflections, which can worsen the quality of their analysis. Deep learning methods have a number of disadvantages, including the often insufficient substantiation of the model, and the complexity of collecting a representative training database. Therefore, it is necessary to develop effective algorithms for the segmentation, classification, and analysis of US images. The aim of the work is to develop a method for the automated detection of pathological lesions in breast US images and their segmentation. A method is proposed that includes two stages of video image processing: (1) searching for a region of interest using a random forest classifier, which classifies normal tissues, (2) selecting the contour of the lesion based on the difference in brightness of image pixels. The test set included 52 ultrasound videos which contained histologically proven suspicious lesions. The average frequency of lesion detection per frame was 91.89%, and the average accuracy of contour selection according to the IoU metric was 0.871. The proposed method can be used to segment a suspicious lesion.The main results of sections \u201CMaterials and Methods\u201D and \u201CResults\u201D were obtained by D.V. Pasynkov and I.A. Egoshin with the support from the Grant of the Russian Science Foundation (Project 22-71-10070, https://rscf.ru/en/project/22-71-10070/ (accessed on 10 February 2025)). Open Access Funding is provided by QU Health, Qatar University.Scopu
The Clinicopathological and Prognostic Value of CCR7 Expression in Breast Cancer Throughout the Literature: A Systematic Review and Meta-Analysis.
Get PDFThis study aimed to determine the clinicopathological findings and prognostic value of chemokine receptor 7 (CCR7) expression in patients with breast cancer (BC). Up to the 25th of March 2025, a search was conducted using five databases: PubMed, Embase, Scopus, Medline, and Web of Science. The methodological standards for the epidemiological research scale were used to assess the quality of the included articles, and Stata software (Stata 19) was used to synthesize the meta-analysis. We considered 12 of 853 studies that included 3119 patients with BC. High CCR7 expression was not associated with age (odds ratio [OR] 0.82, 95% confidence interval [CI] 0.66-1.03); clinicopathological findings, including tumor size (OR 1.062, 95% CI 0.630-1.791); clinical stage (OR 1.753, 95% CI 0.231-13.304); nodal metastasis (OR 1.252, 95% CI 0.571-2.741); or histological differentiation (OR 1.167, 95% CI 0.939-1.450). CCR7 expression did not affect overall survival (hazard ratio 0.996, 95% CI 0.659-1.505). Our quantitative analysis did not reveal an association between CCR7 expression and poor clinicopathological or prognostic features in BC patients. Because of the high heterogeneity and potential publication bias, large high-quality studies are required to further confirm these findings.This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors. APC was provided by the College of Medicine (CMED), QU Health, Qatar University
A novel deep learning framework for automatic scoring of PD-L1 expression in non-small cell lung cancer.
Get PDFA critical predictive marker for anti-PD-1/PD-L1 therapy is programmed death-ligand 1 (PD-L1) expression, assessed by immunohistochemistry (IHC). This paper explores a novel automated framework using deep learning to accurately evaluate PD-L1 expression from whole slide images (WSIs) of non-small cell lung cancer (NSCLC), aiming to improve the precision and consistency of Tumor Proportion Score (TPS) evaluation, which is essential for determining patient eligibility for immunotherapy. Automating TPS evaluation can enhance accuracy and consistency while reducing pathologists' workload. The proposed automated framework encompasses three stages: identifying tumor patches, segmenting tumor areas, and detecting cell nuclei within these areas, followed by estimating the TPS based on the ratio of positively stained to total viable tumor cells. This study utilized a Reference Medicine (Phoenix, Arizona) dataset containing 66 NSCLC tissue samples, adopting a hybrid human-machine approach for annotating extensive WSIs. Patches of size 1000x1000 pixels were generated to train classification models such as EfficientNet, Inception, and Vision Transformer models. Additionally, segmentation performance was evaluated across various UNet and DeepLabV3 architectures, and the pre-trained StarDist model was employed for nuclei detection, replacing traditional watershed techniques. PD-L1 expression was categorized into three levels based on TPS: negative expression (TPS < 1%), low expression (TPS 1-49%), and high expression (TPS ≥ 50%). The Vision Transformer-based model excelled in classification, achieving an F1-score of 97.54%, while the modified DeepLabV3+ model led in segmentation, attaining a Dice Similarity Coefficient of 83.47%. The TPS predicted by the framework closely correlated with the pathologist's TPS at 0.9635, and the framework's three-level classification F1-score was 93.89%. The proposed deep learning framework for automatically evaluating the TPS of PD-L1 expression in NSCLC demonstrated promising performance. This framework presents a potential tool that could produce clinically significant results more efficiently and cost-effectively
Incidental finding of hepatic pseudolesion from aberrant right gastric vein in a breast cancer patient
Get PDFAberrant right gastric veins (ARGV) represent rare anatomical variations that can result in hepatic pseudolesions, mimicking malignancies due to their atypical drainage directly into the liver parenchyma. This case highlights a 44-year-old woman initially presenting with a breast mass incidentally found to have an ARGV-related pseudolesion in hepatic segment IVa. ARGV is clinically significant as it can alter hepatic blood flow dynamics, leading to hyperdense or hypodense regions on imaging. Recognizing these pseudolesions is essential to avoid misdiagnosis, unnecessary procedures, and to distinguish them from true hepatic lesions. This case emphasizes the importance of advanced imaging modalities in diagnosing such anomalies, ensuring accurate patient management
Optimized design of a permanent magnet brushless DC motor for solar water-pumping applications
Get PDFThis paper presents a volume-optimized architecture for a brushless DC (BLDC) motor in the permanent magnet (PM) category. The proposed design minimizes the volume of the PM, achieving a 20 % reduction in material usage and lowering the overall cost of the motor without compromising performance. Efficiency improvements of up to 4.7 % over conventional BLDC motors with equivalent ratings are realized through parametric design optimization. Additionally, a sensorless control system is developed to drive the motor, reducing electronic controller complexity and cost by eliminating the need for position sensors. The control strategy, based on two voltage sensing points, accurately manages electronic commutation and speed control across a wide range, independent of motor parameters, using adaptive error optimization. The motor and solar maximum power are controlled through a single-stage three-phase inverter, making the electronic controller compact and enhancing its suitability for integrated applications. Magnetic and performance characteristics of the optimized motor are analyzed through finite element analysis (FEA). The motor prototype is manufactured in an industrial setting, and experimental validation using the developed sensorless controller demonstrates superior performance and an enhanced efficiency-to-cost ratio, making the proposed design an attractive solution for solar-powered irrigation systems.This publication was made possible by the 1st Cycle of ARG grant no ARG01-0504-230073, from the Qatar Research, Development and Innovation (QRDI) Council, Qatar. The findings herein reflect the work, and are solely the responsibility, of the authors. The authors also gratefully acknowledge support from Qatar University