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Knowledge and attitude among Egyptian medical students regarding the role of human papillomavirus vaccine in prevention of oropharyngeal cancer: a questionnaire-based observational study

Abstract Squamous cell carcinomas in several anatomical sites are caused by human papillomaviruses (HPV), and oncogenic double-stranded DNA viruses. There are about 200 genotypes; HPV16 is the most often occurring variant. Potential ways of infection are skin warts, sexual activity, exposure, immunization, or oral sex. The growing incidence of OPSCC in Western countries makes vaccination increasingly vital. The FDA has approved the 9-valent vaccination as an OPSCC prophylactic agent. Still, political will, inadequate financing, and inadequate infrastructure help to explain the slow dissemination of anti-HPV vaccination. This study sought to evaluate Egyptian medical students’ knowledge, awareness, and attitude toward the advantages of HPV vaccination to prevent HPV-associated OPC. The study was a cross-sectional questionnaire-based study consisting of 696 participants from the first to fifth-year students enrolled in any Egyptian medical school registered in the academic year 2023–2024, specifically from June to August 2024, except non-medical, graduate, and non-Egyptian students who met the exclusion criteria. We privately gathered answers via colleagues and electronically via online Google forms posted on social media groups. This study concentrated on the poor knowledge of HPV among Egyptian medical students, particularly urban male students with a mean age of 21.72 ± 1.6 enrolled in clinical years mostly in Cairo, Sharqia, and Gharbia governorates. There was a clear fair attitude regarding the HPV vaccination, especially among urban male students with a mean age of 21.64 ± 1.65 enrolled in clinical years mostly in Cairo, Sharqia, and Alex governorates. Notably, only 7.7% of the students enrolled in the study knew the link between HPV and OPC. However, only 28.5% of participants have received the vaccine. The students said that lack of awareness (82.4%) was the most important obstacle to vaccination; followed by cultural attitudes (44.5%), vaccine accessibility (42.7%), and vaccine cost (41.3%). Ultimately, it was found that Egyptian medical students—especially those enrolled in clinical years in the governorates of Cairo, Sharqia, and Gharbia—have a low degree of knowledge of HPV-related oropharyngeal cancer and its vaccination role. Although preclinical students’ knowledge had greatly improved, the limited awareness—especially among clinical students—was concerning.

Continental influx and pervasive matrilocality in Iron Age Britain

Abstract Roman writers found the relative empowerment of Celtic women remarkable1. In southern Britain, the Late Iron Age Durotriges tribe often buried women with substantial grave goods2. Here we analyse 57 ancient genomes from Durotrigian burial sites and find an extended kin group centred around a single maternal lineage, with unrelated (presumably inward migrating) burials being predominantly male. Such a matrilocal pattern is undescribed in European prehistory, but when we compare mitochondrial haplotype variation among European archaeological sites spanning six millennia, British Iron Age cemeteries stand out as having marked reductions in diversity driven by the presence of dominant matrilines. Patterns of haplotype sharing reveal that British Iron Age populations form fine-grained geographical clusters with southern links extending across the channel to the continent. Indeed, whereas most of Britain shows majority genomic continuity from the Early Bronze Age to the Iron Age, this is markedly reduced in a southern coastal core region with persistent cross-channel cultural exchange3. This southern core has evidence of population influx in the Middle Bronze Age but also during the Iron Age. This is asynchronous with the rest of the island and points towards a staged, geographically granular absorption of continental influence, possibly including the acquisition of Celtic languages.

Exploring the textural characteristics of foods preferred by Chinese elderly individuals based on IDDSI levels

Objective This study aimed to investigate the textural characteristics of foods preferred by elderly Chinese individuals and their suitability based on the International Dysphagia Diet Standardization Initiative (IDDSI) framework. The goal was to provide objective data to support the development of safe and nutritious diets tailored to the swallowing abilities of the elderly. Methods A cross-sectional observational study was conducted, using web-scraping technology to identify 26 commonly preferred food ingredients among elderly individuals across seven regions of China. These foods were prepared and evaluated according to IDDSI levels 0–7. Texture analysis was performed to measure hardness, cohesiveness, and adhesiveness, with statistical tests including chi-square analysis and multiple linear regression used to explore the relationships between these textural properties and IDDSI levels. Results As IDDSI levels increased, the hardness of various food categories generally showed an upward trend, with significant increases observed in fruits, vegetables, grains, and tubers at IDDSI levels 6–7 (p≤0.05). Cohesiveness varied without a clear linear trend, showing significant changes at specific IDDSI levels for meats, grains, and tubers (p≤0.05). Adhesiveness initially increased and then decreased across the IDDSI spectrum, with the most significant fluctuations occurring in mixed beans, fruits, and grains at levels 5–7 (p≤0.05). Regression analysis revealed that cohesiveness had the most substantial impact on IDDSI levels (coefficient = -5.224, p≤0.05), followed by adhesiveness (coefficient = -0.021, p≤0.05), and hardness (coefficient = 0.002, p≤0.05). Conclusion The findings underscore the importance of considering the textural properties of foods when designing diets for elderly individuals with dysphagia. The study provides empirical evidence supporting the IDDSI framework and offers a predictive model that can assist in the development of customized diets, ensuring both safety and nutritional adequacy. Future research should focus on refining food preparation methods to better meet the specific needs of this population.

Alzheimer’s disease may develop from changes in the immune system, cell cycle, and protein processing following alterations in ribosome function

Methane emissions from the Nord Stream subsea pipeline leaks

The association of muscle weakness with functional disability in older patients with Diabetes mellitus: Measured by three different grip strength thresholds

The association of muscle weakness with poor outcomes is well defined in general older population, but there is insufficient data on the association of muscle weakness with functionality in older patients with diabetes mellitus (DM). We aimed to investigate the predictivity of muscle weakness defined as low grip strength thresholds determined by EWGSOP2, and two regional thresholds in older patients with DM for functional disability. Activities of Daily Living (ADL), Instrumental ADL (IADL), grip strength, comorbidities, anthropometric and biochemical data from outpatient clinic medical records were screened retrospectively. Low grip strength was determined by EWGSOP2, and two regional thresholds. Receiver operating characteristic (ROC) analysis, sensitivity and negative predictive values were conducted to identify the discrimination power of three different grip strength thresholds for functional disability in patients with DM. A total of 197 patients with DM and 215 controls were included. In ROC analyses, regional thresholds were with higher sensitivity and negative predictive values for functional disability in both groups. For patients with DM, regional normative thresholds predicted functional disability both for ADLs and IADLs whereas for patients without DM normative thresholds predicted ADL, and calculated thresholds predicted IADL disability. Regional normative thresholds predicted both ADL and IADL functional disability in older patients with DM.

Stable quantum droplets with high-order vorticity in zero-order Bessel lattice

Potential Azo-8-hydroxyquinoline derivatives as multi-target lead candidates for Alzheimer’s disease: An in-depth in silico study of monoamine oxidase and cholinesterase inhibitors

Cognitive dysfunction in Alzheimer’s disease results from a complex interplay of various pathological processes, including the dysregulation of key enzymes such as acetylcholinesterase (AChE), butyrylcholinesterase (BuChE), and monoamine oxidase B (MAO-B). This study proposes and designs a series of novel molecules derived from 8-hydroxyquinoline (Azo-8HQ) as potential multi-target lead candidates for treating AD. An exhaustive in silico analysis was conducted, encompassing docking studies, ADMET analysis, density functional theory (DFT) studies, molecular dynamics simulations, and subsequent MM-GBSA calculations to examine the pharmacological potential of these molecules with the specific targets of interest. Out of the 63 Azo-8HQ derivatives analysed, two molecules, 14c and 17c, demonstrated strong affinities for AChE, BuChE, and MAO-B, along with favourable pharmacokinetic profiles and electronic properties. Molecular dynamics simulations confirmed the stability of these molecules within the active sites of the targets, and MM-GBSA calculations revealed low binding energies, indicating robust interactions. These findings identify molecules 14c and 17c as promising multi-target candidates for the treatment of AD, based on an in-depth computational study aimed at minimizing drug development costs and time. Future work will include the synthesis of these molecules followed by in-depth in vitro and in vivo testing to validate their potential therapeutic efficacy.

Evaluating 36 years of fishing sustainability in a large reservoir

AutoPVPrimer: A comprehensive AI-Enhanced pipeline for efficient plant virus primer design and assessment

Plant viruses pose a significant threat to global agriculture and require efficient tools for their timely detection. We present AutoPVPrimer, an innovative pipeline that integrates artificial intelligence (AI) and machine learning to accelerate the development of plant virus primers. The pipeline uses Biopython to automatically retrieve different genomic sequences from the NCBI database to increase the robustness of the subsequent primer design. The design_primers_with_tuning module uses a random forest classifier that optimizes parameters and provides flexibility for different experimental conditions. Quality control measures, including the evaluation of poly-X content and melting temperature, increase primer reliability. Unique to AutoPVPrimer is the visualize_primer_dimer module, which supports the visual evaluation of primer dimers—a feature missing in other tools. Primer specificity is validated via primer BLAST, which contributes to the overall efficiency of the pipeline. AutoPVPrimer has been successfully applied to the tomato mosaic virus, proving its adaptability and efficiency. The modular design allows customization by the user and extends the applicability to different plant viruses and experimental scenarios. The pipeline represents a significant advance in primer design and provides researchers with an effective tool to accelerate molecular biology experiments. Future developments aim to extend compatibility and incorporate user feedback to consolidate AutoPVPrimer as an innovative contribution to the bioinformatics toolbox and a promising resource for the advancement of plant virology research.

A new epidemic model of sexually transmittable diseases: a fractional numerical approach

EDEM-based study on the adjustable feeding parameters of square bale maize straw bale-breaking device

One of the primary challenges faced by small rubbing filament machines is the significant variability in material sizes, particularly in the feeding direction. This variability complicates the processing of locally baled straw with a single device. To address this issue, an adjustable feeding and bale-breaking device was developed and tested to enhance the filamentous performance of baled straw. The machine integrates a series of bale-breaking knives along with a pair of feeding and bale-breaking rollers. This paper presents an overview of the machine’s structure and operating principles, alongside an analysis of the forces acting on the straw within the device, which informed the design of key components and devices. A discrete element simulation model suitable for square baled-straw has been established, providing a research foundation for the subsequent optimization of device design parameters. Effects of motor bale-breaking roller rotating speed (x1), bale-breaking roller height (x2) and bale-breaking knife quantity (x3) on the productivity of bonding bond destruction rate (Y1) and the particle average speed (Y2) were explored. Three-dimensional quadratic regression orthogonal rotation central combination experiment method combined with response surface method was used to conduct experiments and explore the interaction effects of influence factors on indicators. A regression model of influence factors and evaluation indicators was established through the analysis of variance. The significant factors affecting Y1 were ordered of x1, x2, x3, and the significant factors affecting Y2 were ordered of x2, x3, x1. In the interaction of factors, x1x2 and x2x3 had an extremely significant impact, and x1x3 had a significant impact on Y1; x1x2, x1x3 and x2x3 had a significant impact on Y2. The optimal structure and working parameters combination were determined to be 1448 rpm for x1, 268 mm for x2, and 14 pieces for x3. Verification experiments demonstrated that the actual values were 96.95% for the straw rubbing rate and 235.13 kg/(kW·h) for the per unit power productivity. The operation of the adjustable feeding and bale-breaking device developed in this study proved effective in enhancing productivity and breaking performance during the feeding of baled straw. It successfully met the design requirements for the grain size necessary for the comprehensive utilization of straw. Overall, this research establishes a foundational basis for the further development of a small, multipurpose straw rubbing filament machine.

Author Correction: Association between depression and diabetes among American adults using NHANES data from 2005 to 2020

Genetic diversity, population structure in a historical panel of Brazilian soybean cultivars

Soybean [Glycine max (L.) Merrill] is one of the most widely grown legumes in the world, with Brazil being its largest producer and exporter. Breeding programs in Brazil have resulted from multiple cycles of selection and recombination starting from a small number of USA cultivar ancestors in the 1950s and 1960s years. This process has led to the successful adaptation of this crop to tropical conditions, a phenomenon known as tropicalization. Many studies describe a narrow genetic background in Brazilian soybean cultivars. Various factors can affect the genetic diversity in species, especially in cultivated crops, such as the reproduction type, artificial selection, and the number and sources of variability in the breeding programs. In turns, the genetic diversity can affect the linkage disequilibrium blocks (LD) patterns and, consequently, molecular breeding strategies for selection of target loci for agronomic traits. We used high-throughput genotyping with SoySNP50K Illumina SNP markers to assess a collection of 370 Brazilian soybean accessions covering more than 60 years of soybean breeding in Brazil. Our goal was to investigate population structure and genetic diversity in the Brazilian germplasm, detect patterns of LD blocks, and identify regions presenting signals of selective swaps linked with quantitative trait loci (QTLs) of agronomic interest. Population structure analysis revealed two major groups among all genotypes, primarily differentiated by the year of release, separating old and new cultivars (before and after 2000´s years), and by growth habit (stem termination type—SST). The group I comprises about 75% of the panel and includes cultivars release before 2000`s years, including the oldest cultivars released in Brazil, most of which exhibit a determinate growth habit and maturity groups VI and VII. Group II includes only 83 materials, but shows higher levels of diversity than group I, representing most recent introductions in Brazilian germplasm. Further analysis of substructure within Group I, identified seven subgroups with no clear trend for segregation based on maturity group, STT or year of release. Instead, these subgroups were based on the contribution of key donors of disease resistance and adaptability, as soybean cultivation expanded from the South to Central region of Brazil. This finding is consistent with the history of soybean expansion in Brazil. We identified 123 genomic regions under selection among the groups of Brazilian cultivars associated with 440 quantitative trait loci (QTLs), revealing regions fixed across the breeding process associated with yield, disease resistance, water efficiency use, and others.

Noninvasive imaging biomarker reveals invisible microscopic variation in acute ischaemic stroke (≤ 24 h): a multicentre retrospective study

Analysis of glutamate-dependent mechanism and optimization of fermentation conditions for poly-gamma-glutamic acid production by Bacillus subtilis SCP017-03

Poly-gamma-glutamic acid (γ-PGA) is mainly synthesized by glutamate-dependent strains in the manufacturing industry. Therefore, understanding glutamate-dependent mechanisms is imperative. In this study, we first systematically analyzed the response of Bacillus subtilis SCP017-03 to glutamate addition by comparing transcriptomics and proteomics. The introduction of glutamate substantially altered gene expression within the central metabolic pathway of cellular carbon. Most genes in the pentose phosphate pathway (PPP), tricarboxylic acid (TCA) cycle, and energy-consuming phase of the glycolysis pathway (EMP) were down-regulated, whereas those in the energy-producing phase of glycolysis and those responsible for γ-PGA synthesis were up-regulated. Based on these findings, the fermentation conditions were optimized, and γ-PGA production was improved by incorporating oxygen carriers. In a batch-fed fermentor with glucose, the γ-PGA production reached 95.2 g/L, demonstrating its industrial production potential. This study not only elucidated the glutamate dependence mechanism of Bacillus subtilis but also identified a promising metabolic target for further enhancing γ-PGA production.

How and why small volcanic ocean islands collapse and move vertically up and down

Fast and accurate imputation of genotypes from noisy low-coverage sequencing data in bi-parental populations

Motivation Genotyping of bi-parental populations can be performed with low-coverage next-generation sequencing (LC-NGS). This allows the creation of highly saturated genetic maps at reasonable cost, precisely localized recombination breakpoints (i.e., the crossovers), and minimized mapping intervals for quantitative-trait locus analysis. The main issues with these low-coverage genotyping methods are (1) poor performance at heterozygous loci, (2) high percentage of missing data, (3) local errors due to erroneous mapping of sequencing reads and reference genome mistakes, and (4) global, technical errors inherent to NGS itself. Recent methods like Tassel-FSFHap or LB-Impute are excellent at addressing issues 1 and 2, but nonetheless perform poorly when issues 3 and 4 are persistent in a dataset (i.e., “noisy” data). Here, we present a new algorithm for imputation of LC-NGS data that eliminates the need of complex pre-filtering of noisy data, accurately types heterozygous chromosomal regions, precisely estimates crossover positions, corrects erroneous data, and imputes missing data. The imputation of genotypes and recombination breakpoints is based on maximum-likelihood estimation. We compare its performance with Tassel-FSFHap and LB-Impute using simulated data and two real datasets. NOISYmputer is consistently more efficient than the two other software tested and reaches average breakpoint precision of 99.9% and average recall of 99.6% on illumina simulated dataset. NOISYmputer consistently provides precise map size estimations when applied to real datasets while alternative tools may exhibit errors ranging from 3 to 1845 times the real size of the chromosomes in centimorgans. Furthermore, the algorithm is not only highly effective in terms of precision and recall but is also particularly economical in its use of RAM and computation time, being much faster than Hidden Markov Model methods. Availability NOISYmputer and its source code are available as a multiplatform (Linux, macOS, Windows) Java executable at the URL https://gitlab.cirad.fr/noisymputer/noisymputerstandalone/-/tree/1.0.0-RELEASE?reftype=tags.

Deep learning-based malaria parasite detection: convolutional neural networks model for accurate species identification of Plasmodium falciparum and Plasmodium vivax

Abstract Accurate malaria diagnosis with precise identification of Plasmodium species is crucial for an effective treatment. While microscopy is still the gold standard in malaria diagnosis, it relies heavily on trained personnel. Artificial intelligence (AI) advances, particularly convolutional neural networks (CNNs), have significantly improved diagnostic capabilities and accuracy by enabling the automated analysis of medical images. Previous models efficiently detected malaria parasites in red blood cells but had difficulty differentiating between species. We propose a CNN-based model for classifying cells infected by P. falciparum, P. vivax, and uninfected white blood cells from thick blood smears. Our best-performing model utilizes a seven-channel input and correctly predicted 12,876 out of 12,954 cases. We also generated a cross-validation confusion matrix that showed the results of five iterations, achieving 63,654 out of 64,126 true predictions. The model’s accuracy reached 99.51%, a precision of 99.26%, a recall of 99.26%, a specificity of 99.63%, an F1 score of 99.26%, and a loss of 2.3%. We are now developing a system based on real-world quality images to create a comprehensive detection tool for remote regions where trained microscopists are unavailable.

Carotid artery stenosis and ischemic cerebrovascular events after radiotherapy in patients with head and neck cancer

Radiotherapy is the main treatment for patients with head and neck cancer (HNC) and is associated with an increased risk of ischemic cerebrovascular events (ICVE). The purpose of this cross-sectional study was to determine the incidence of ICVE and carotid artery stenosis (CAS) in patients with HNC who receive radiotherapy and the risk factors for CAS. We enrolled 907 patients with HNC who underwent radiotherapy between February 2011 and June 2022 and obtained information on their clinical and tumor characteristics and their treatment from the clinical records. Data on risk factors for atherosclerosis, medications used, and radiotherapy were also collected. The patients were followed through to the end of 2023 unless they died or were lost to follow-up. The overall incidence of ICVE was 1.98%, with a cumulative incidence of 1.65% over 5 years. In patients who did not have a preexisting carotid artery lesion, the cumulative incidence of significant CAS was 1.3% at 12 months, 2.2% at 24 months, and 2.5% at 36 months post-radiotherapy. The most important risk factors for new CAS were age >65 years (aHR = 2.60, p = 0.008, 95% confidence Interval: 1.28–5.30), laryngeal cancer (aHR = 2.36, p<0.017, 95% confidence Interval: 1.01–5.55), and total plaque score (aHR = 1.38, p<0.001, 95% confidence Interval: 1.23–1.56). There was a significant increase in stenosis, plaque score, and wall thickness in all areas in the carotid artery (p<0.001). The incidence of ICVE and the cumulative incidence of CAS was found to be lower in the Thai population than in other populations. The main risk factors for new CAS were age >65 years, laryngeal cancer, and total plaque score. Changes in the carotid artery were detected early and affected all areas in the artery. Patients with HNC treated by radiotherapy should be assessed for risk factors for CAS and undergo vascular surveillance during follow-up.