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Correction: Correlation between self-regulatory fatigue and physical activity in lung cancer patients undergoing comprehensive treatment
Corrections to the standard retrieval of total ozone column with a Dobson spectrophotometer operated at Belsk, Poland, since 1963
Antimicrobial and antibiofilm evaluation of thymol, sodium azide, and sodium lauryl sulfate against multidrug-resistant pathogens: An integrated experimental and computational study
Multidrug-resistant (MDR) pathogens represent a major global health challenge, underscoring the urgent need for new antimicrobial strategies that can effectively target both planktonic cells and biofilm-associated infections. This study integrated in vitro antimicrobial and antibiofilm assays with comprehensive in silico analyses to evaluate the repurposing potential of thymol (TM), sodium azide (SA), and sodium lauryl sulfate (SLS) against 17 bacterial and two fungal strains, including methicillin-resistant Staphylococcus aureus (MRSA) clinical isolates. TM showed the strongest overall antimicrobial activity, with low MIC/MBC values (0.10–0.20 mg/mL) and potent antibiofilm effects (MBIC: 0.20–0.39 mg/mL; MBEC: 0.39–0.78 mg/mL). In contrast, SA exhibited similar MICs (0.10–0.78 mg/mL) but required much higher concentrations for bactericidal and antibiofilm endpoints (MBC/MBIC/MBEC 6.25–100 mg/mL), whereas SLS displayed variable activity, with low MICs against most Gram-positive bacteria (0.10–0.20 mg/mL) but high MBC/MBIC/MBEC values (50–100 mg/mL), especially for Gram-negative biofilms. Molecular docking and 300 ns molecular dynamics (MD) simulations revealed that TM forms stable complexes with key microbial targets, most notably FtsZ ( ΔG = –11.0 kcal/mol; K d = 3.2 × 10 ⁻ ¹⁰ M), supported by favorable MM/GBSA binding energies and restrained motions in principal component analysis/free-energy landscape (PCA/FEL) analyses. SA and SLS were primarily used as mechanistic comparators (respiratory inhibitors and membrane disruptors, respectively). In contrast, their non-ionic analogs, phenyl azide (PA) and lauryl sulfate (LS), were explored as potential scaffolds. LS showed a very high predicted affinity for UDP-3-O-acyl- N -acetylglucosamine deacetylase (LpxC) ( ΔG = –19.9 kcal/mol; K d = 1.7 × 10 ⁻ ¹¹ M), indicating promise for future optimization. In silico ADMET profiling identified TM as the most balanced candidate, combining broad-spectrum antibiofilm efficacy with a comparatively favorable predicted safety profile. Overall, TM emerges as a viable repurposable antimicrobial agent, whereas LS-based derivatives represent computationally prioritized scaffolds that warrant further experimental validation.
Research on lung nodule detection in X-ray plain films based on improved YOLOv12 model
Peer-coaching interventions for stroke survivors - what works and how: A scoping review
Background Peer-led interventions show potential in supporting stroke survivors’ recovery, but are described using inconsistent terms and definitions in the current literature. Aims Adopting “post-stroke peer-coaching intervention” as the overarching term, this study aims to synthesise the characteristics and outcomes of existing interventions for stroke survivors to develop a standardised definition and a consolidated summary of findings. Summary of review In this scoping review, we searched 6 databases to identify relevant studies from peer-reviewed journal articles published between January 1993 and October 2025. Data were extracted and analysed regarding intervention definitions, characteristics, and outcomes. The search identified 6609 records, and 8 articles were included, which involved 7 post-stroke peer-coaching interventions. An overall inconsistency was observed across intervention definitions and characteristics. Based on common elements across existing interventions, this study developed an integrated definition, describing post-stroke peer-coaching interventions as a time-limited, patient-centred type of psychosocial and psycho-educational intervention that is ideally developed through participatory action research approaches, and delivers informational, emotional, and appraisal support with application of experiential expertise under the guidance of healthcare professionals. The analysis also revealed an inconsistency in intervention outcomes. Conclusion Current post-stroke peer-coaching interventions demonstrated inconsistency across definitions, characteristics, and outcomes. To address the inconsistency, this review established a definition that outlines foundational conceptual parameters of the intervention. This proposed definition can serve as a standardised framework to inform the development of future interventions and ensure the provision of systematic support to individuals with stroke.
Inverse design of an ultra-wideband endfire grooved half-mode waveguide (G-HMWG) antenna based on the CNN approach
Retraction: Influence of pozzolanic addition on strength and microstructure of metakaolin-based concrete
Myricetin alleviates testosterone-induced benign prostatic hyperplasia by attenuating inflammation, oxidative stress, apoptosis and androgen signaling
Abstract This study investigates the effect of myricetin as a therapeutic for benign prostatic hyperplasia (BPH) disease using a testosterone-induced BPH animal model. Forty adult male rats were randomly divided into four groups as follows: control group, BPH group that was injected with testosterone subcutaneously (3 mg/kg body weight/day), BPH + myricetin group, which received myricetin (50 mg/kg) subcutaneously every day with the BPH induction, and BPH + finasteride group, which administered finasteride orally with the BPH induction at a daily dose of 5 mg/kg. After 28 days, blood and prostate tissue samples were collected for analysis. Compared to the control group, treatment with myricetin improved the pathohistological signs of BPH and enhanced the antioxidant and anti-inflammatory capacity of the prostatic tissue, as evidenced by its ability to enhance the total antioxidant capacity (TAC) levels and reduce malondialdehyde (MDA) levels, decrease the levels of the inflammatory biomarkers tumor necrosis factor alpha (TNF-α) and interleukin-1 beta (IL1-β) levels, and reduce serum dihydrotestosterone (DHT) levels. In addition, myricetin treatment showed beneficial effects through its ability to reduce the prostatic mRNA expression levels of the anti-apoptotic protein Bcl2, the 5-α reductase enzyme, and the androgen receptor ( AR ), while simultaneously increasing the prostatic mRNA expression levels of the pro-apoptotic protein Bax . Myricetin treatment also exhibited anti-proliferative and anti-angiogenic effects, as evidenced by the reduced prostatic proliferating cell nuclear antigen (PCNA) and vascular endothelial growth factor-A ( VEGF-A ) mRNA expression levels. In summary, myricetin displays potential as a BPH therapy by diminishing inflammation and oxidative stress, hindering 5-α reductase / AR /DHT signaling, and endorsing pro-apoptotic over anti-apoptotic pathways.
Wavelet-based visual compass
For many ant species, successful visual navigation is crucial for the survival of the individual and the colony, meaning these small-brained insects have evolved to be exceptional navigators. This makes them an ideal inspiration for biomimetic robotics research. Visual compass-style snapshot models have been used to model visual navigation in ants and have been applied to visual teach-and-repeat style robot navigation. In these models, images or ‘snapshots’ stored when the ant first travels a route are compared to views experienced when recapitulating the route to derive a bearing that will direct the ant along the route (rather than navigating to a discrete goal location as in visual homing). While the majority of visual-compass snapshot models have used raw images, we have shown in preliminary work that visual pre-processing by Haar wavelets that quantify spatial frequencies at every location in an image can improve the snapshot robustness. These wavelets effectively filter images for oriented edges at certain spatial frequencies in a way that mimics the processing seen in natural visual systems. Here, we extend our findings by investigating the properties and limits of bearing recovery in the face of naturalistic perturbations, focusing on comparing wavelets with edge-processed or raw images of different resolutions. We find that: (1) high frequency localised wavelet coefficients highlight distant objects; (2) The effect disappears when the resolution is decreased, as far away objects blur together; (3) If navigating using visual-compass style snapshot navigation, perturbations in the environment can be compensated solely by choosing suitable image processing. Our work extends the corpus of research on spatial frequency-based encodings for snapshot navigation, which has mainly focused on non-localised encodings (such as Fourier Transforms) applied to visual homing. We do this by providing an in-depth analysis of localised spatial-frequency encodings and their dis-/advantages for route following via visual compass style bearing recovery.
Predicting methane adsorption in coal and shale with white-box and black-box machine learning models
A highly accurate Hermite polynomial-based least-squares approach for solving fractional Volterra-Fredholm integro-differential equations
This paper presents a comprehensive numerical study on the efficacy of a Hermite polynomial-based least-squares method for solving Volterra–Fredholm fractional integro-differential equations (V-FFIDEs). In our approach, we construct an approximate solution as a finite expansion of Hermite polynomials. This trial solution is systematically substituted into the governing V-FFIDE. Following the analytical evaluation of the fractional and integral operators, we formulate a residual function. The core of our method involves minimizing the squared norm of this residual over the problem domain, a process that transforms the original problem into a well-defined system of linear algebraic equations. To validate our methodology, we conducted a series of numerical experiments on a collection of representative examples. The results of our study, presented through detailed tables of numerical outcomes and comparative graphical illustrations, conclusively demonstrate the high accuracy, computational efficiency, and robust convergence of the proposed technique.
Enhancing underwater sensor network security using QKD-enabled acoustic–optical hybrid communication
Differential associations of mental health, mild traumatic brain injury and substance use between male and female university students
Background More severe substance use, defined as higher scores on validated measures of problematic use, is increasing within young adult populations. Substance use has been associated with mild traumatic brain injury (mTBI) and elevated symptoms of depression and anxiety. We aimed to understand the relationship between these factors and sex differences in a university sample. Method 894 university students (372 males and 522 females, aged 18–25 years) self-reported their mTBI history, substance use (Alcohol Use Disorders Identification Test (AUDIT) and the Cannabis Use Disorders Identification Test-Revised (CUDIT-R)), and psychological measures (Patient Health Questionnaire–9 (PHQ-9) and Generalized Anxiety Disorder–7 (GAD-7). Regression analyses examined whether the number of previous mTBIs was associated with increased cannabis (within the past six months) or alcohol use (within the past twelve months) severity. Logistic and linear regression models were used to explore how mTBI history, sex, and mental health symptoms relate to the likelihood and severity of cannabis and alcohol use and were also run separately by sex. Results Individuals with multiple mTBIs reported more problematic substance use and a higher number of substances used. Hazardous substance use, as defined by scores above AUDIT and CUDIT-R cut-offs, was associated with both a previous history of mTBI and greater scores on depression and anxiety measures. Individuals with higher scores on an anxiety measure were more likely to use cannabis, especially if they had a history of mTBI. A history of mTBIs and higher current depression scores among cannabis users was associated with more problematic cannabis use. Among alcohol-using individuals, those with higher depression scores in addition to a history of mTBI were more likely to endorse more problematic alcohol use. Finally, males and females were affected differently by mental health and mTBI risk factors. Conclusion mTBI history and mental health problems may be associated with hazardous substance use, but these findings highlight the importance of considering sex-specific risk patterns when developing interventions or preventive strategies for young adults with a history of mTBI or elevated anxiety/depression symptoms.
Tunable dual-band THz metamaterial absorber with regression-learning-enabled numerical redesign
Perceptions of factors influencing Ebola vaccine acceptance among community members, healthcare workers, and response personnel in Eastern Democratic Republic of the Congo
Background The 2018–2020 Ebola Virus Disease (EVD) outbreak in Eastern Democratic Republic of the Congo (DRC) occurred amid armed conflict, institutional mistrust, and fragile health systems. The Ebola vaccine was deployed under emergency pre-licensure use, and concerns about it persisted. This study explored community and healthcare worker (HCW) perceptions of the Ebola vaccine to better understand the sociocultural and structural drivers of vaccine acceptance. Methods We conducted a qualitative study in three heavily affected health zones in North Kivu province (Beni, Butembo, and Mabalako) in 2021. Data were collected through thirty-three focus group discussions and 15 key informant interviews with EVD survivors, community members, HCWs, and local leaders, purposively sampled to capture diverse perspectives. Transcripts were analyzed using thematic and content analysis. Results Participants reported concerns about the safety of the vaccine, mistrust in the institutions delivering it, and confusion due to rumors and inconsistent communication from the Ebola response. HCWs reported feeling coerced into vaccination rather than making a voluntary choice. Misinformation, logistical barriers, and perceptions of favoritism and stigmatization linked to ring vaccination were cited as preventing acceptance. Religion played a dual role, both fostering skepticism and encouraging acceptance depending on the stance of local faith leaders. Participants emphasized the need for transparent and balanced communication, equitable access, and greater involvement of trusted and competent community figures in vaccination efforts. Conclusions Ebola vaccine decision-making in Eastern DRC was shaped by complex interactions between institutional mistrust, perceived risk, religion, and access constraints within a broader context of sociopolitical instability. This study provides a critical baseline of perceptions during the vaccine’s pre-licensure phase and highlights the importance of locally grounded engagement strategies. As vaccines become licensed, understanding local perceptions as well as leveraging the influence of trusted religious and community leaders will be essential for improving vaccine uptake.
Whole genome analysis of selection associated with resistance to heat stress in chickens
Abstract Following their domestication, chickens were translocated around the world to novel environments. Through a combination of natural and artificial selection, chickens adapted to these local conditions, creating significant genetic diversity across populations worldwide. Studying this diversity in the context of local environmental conditions may offer insights into mechanisms of adaptation to environmental stressors. In this study, we analyzed genomic data from the Chicken Genomic Diversity Consortium, applying multiple statistical approaches, including fixation index (F ST ), nucleotide diversity (π), Tajima’s D, and runs of homozygosity (ROH), to identify selective sweeps among indigenous chickens from Afghanistan, China, Indonesia, Iran and Pakistan, compared with White Leghorn chickens. We identified sweeps in 14 genes related to heat tolerance, associated with relevant gene ontology (GO) terms and located within ROH regions. These genes, such as CDH23 , NPSR1 , MCU , TRPV2 , TRPV1 , TRPV3 , ATP2B4 , CALM1 , CACNB2 , TRAT1 , BDNF , SCIN , WIPF3 , PRKD1 , and DNAJC10 play crucial roles in calcium signaling pathways, thermal sensation, and the plasticity of neurodevelopmental processes. These findings illustrate the significant role of selection in shaping genomic differentiation across chicken populations and provide insights into the genetic basis of adaptation to environmental stressors.
MSCNet: Efficient and accurate semantic segmentation of LiDAR data using Multi-scale Convolution
In autonomous driving and intelligent robotics, the semantic information of LiDAR (Light Detection and Ranging) sensor data is crucial for understanding the surrounding environment. However, directly operating on point clouds is computationally expensive. To address this, some researchers have projected three-dimensional LiDAR data onto a two-dimensional spherical range view and used two-dimensional convolutional neural networks to segment the projected images. While the results are promising, many of these models are structurally complex, with high spatiotemporal complexity, which makes them unsuitable for real-time applications. To solve these issues, this paper proposes a multi-scale LiDAR data semantic segmentation method, MSCNet, with fewer parameters and higher segmentation accuracy. In the encoding phase, a single-channel multi-scale feature fusion block is introduced to alleviate the distribution differences between input channels. To obtain more stable local features, multi-scale dilated convolution residual blocks are designed to encode information from different receptive fields. To quickly capture global features, a pyramid pooling module is introduced. Experimental results on the SemanticKITTI, SemanticPOSS, and Pandaset datasets show that MSCNet achieves a good balance between parameter, accuracy, and running time. Particularly on the SemanticPOSS and Pandaset datasets, MSCNet achieves the best performance. Under the same parameter conditions, this method outperforms existing point cloud-based and projection-based methods.