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Morphological characterization and DNA barcoding of Ruellia sp. in Saudi Arabia

The genus Ruellia L. belongs to this family and its plants are herbs or shrubs. This genus was first detected in the tropical and subtropical regions. The primary objective this study is to identify the various species within the genus Ruellia using both morphological characteristics and DNA barcoding methods. For this purpose, plant samples were meticulously collected from eight distinct natural habitats across the region. All vegetative and floral parts were examined using a binocular microscope. All parts are measured and photographed. To ensure accurate identification and characterization, four molecular barcoding markers were employed: Psbk-psbi, trnH-psbA, rbcL, and AtpF-AtpH. Eight Ruellia species were identified from different regions: Abha, Aseer (24651), Jazan (24652), Malacosperma, Patula, Taif (24650 rose), Taif (24650 violet), and Taif (24650 white). The species were confirmed using specimens from the King Saud University herbarium. Notably, the samples collected from Taif, which had flowers of different colors, were determined to represent a single species with different genotypes. The use of four DNA barcode markers (Psbk-psbi, trnH-psbA, rbcL, and AtpF-AtpH) facilitated the identification of five distinct species: R. tweediana, R. sp. SH2010, R. carolinensis, R. simplex, and R. patula. These findings confirmed the dominant Ruellia species in Saudi Arabia and demonstrated the reliability of DNA barcode markers for species identification. Further assessment of these species’ adaptability, molecular genetics, and functional genomics is necessary for their commercial utilization in the region. These species are recorded for the first time in Saudi Arabia and represent the first record.

Evaluating Covid-19 publications for sex and gender-specific health content: A bibliometric analysis

Background Sex and gender are key variables which inform human health and disease. It remained unclear how sex and gender were considered, evaluated, reported, or analyzed within Covid-19 research. This article evaluates the proportion of Covid-19-related articles which highlighted sex- or gender-specific health content and examines associations with author gender. Materials and methods Article records for 134,008 publications indexed in the LitCovid database were extracted on June 1st, 2021. Metadata such as publication year, author names, and country of institutional affiliation were obtained from Elsevier’s SCOPUS database by matching PubMed Identifiers (PMIDs). Only articles with matching SCOPUS records were included in the study, resulting in a final sample of 94,488 articles. First and last author gender was assigned to a subset of 71,597 articles. Article title, abstracts, and keywords were screened for sex or gender-specific health content using a text-based search strategy. Descriptive statistics and regression analyses were used to study associations between author gender and the presence or absence of sex or gender-related health content. Results Only 4% of Covid-19-related articles highlighted sex or gender-related health content. Papers with women first authors were more likely to highlight sex or gender-related health content compared to papers with men as first authors (4.15% n = 1,339 vs 3.68%, n = 1,997) [X2 (1, n = 86,468) = 12,01, p = 0.0005]. Papers with women first and last authors had an increased probability of addressing sex or gender-related health with an odds ratio of 1.16 (95% CI 1.04 – 1.29). While there was no association between author gender and journal impact, articles which highlighted sex or gender-related health content were published in journals with higher CiteScores [Mdn = 5.0, Q1-Q3 (3.5–8.2) vs. Mdn = 4.7, Q1-Q3 (2.8–8.0)]. Conclusions The paucity of publications to highlight sex or gender in the context of the Covid-19 pandemic is alarming. Research that focuses on the influence of sex and or gender is essential for advancing the scientific understanding of disease processes.

Sodium propionate decreases implant-induced foreign body response in mice

The short-chain fatty acid (SCFA) propionate, beyond its actions on the intestine, has been able to lower inflammation and modulate angiogenesis and fibrogenesis in pathological conditions in experimental animal models. Its effects on foreign body reaction (FBR), an abnormal healing process induced by implantation of medical devices, have not been investigated. We have evaluated the effects of sodium propionate (SP) on inflammation, neovascularization and remodeling on a murine model of implant-induced FBR. Polyether-polyurethane sponge discs implanted subcutaneously in C57BL/6 mice provided the scaffold for the formation of the fibrovascular tissue. Fifteen-day old implants of the treated group (SP, 100 mg/kg for 14 days) presented a decrease in the inflammatory response as evaluated by cellular influx (flow cytometry; Neutrophils 54%; Lymphocytes 25%, Macrophages 40%). Myeloperoxidase activity, TNF-α levels and mast cell number were also lower in the treated group relative to the control group. Angiogenesis was evaluated by blood vessel number and VEGF levels, which were downregulated by the treatment. Moreover, the number of foreign body giant cells HE (FBGC) and the thickness of the collagenous capsule were reduced by 58% and 34%, respectively. Collagen deposition inside the implant, TGF-β1 levels, α-SMA and TGF-β1 expression were also reduced. These effects may indicate that SP holds potential as a therapeutic agent for attenuating adverse remodeling processes associated with implantable devices, expanding its applications in biomedical contexts.

Correction: Navigating board dynamics: Configuration analysis of corporate governance’s factors and their impact on bank performance

Correction: Factors which influence ethnic minority women’s participation in maternity research: A systematic review of quantitative and qualitative studies

Mapping women’s work in India: An application of small area estimation

Background Understanding variations in women’s work participation at lower administrative levels, such as districts, is a missing link in identifying trends, patterns and variation that can offer insights into this long-term stagnation. We link data from the 2019–21 Indian National Family Health Survey and the 2011 Indian Population and Housing Census to generate estimates of women’s work within 640 districts of India, and to examine the spatial clustering of women’s work across these districts. We examine women’s work through three outcome variables, namely, district-level estimates of 1) percentage of women who worked in the past 12 months, 2) percentage of women who were self-employed in the past 12 months, and 3) percentage of women who earned cash in the past 12 months. Results Diagnostic measures confirm that our model-based estimates are robust enough to provide reliable district-level estimates of women’s work in India. Women’s work and cash earnings were lowest in the districts of the central, eastern, and northern regions, and highest in the southern region. Self-employment rates for women were generally low in Indian districts, except for districts in Himachal Pradesh and the north-eastern region. Conclusions Considerable spatial heterogeneity in women’s work has been found across 640 districts of India. Our study demonstrates that estimated percentage of women who worked in the past 12 months, estimated percentage of women who earned cash in the past 12 months and estimated percentage of women who were self-employed in the past 12 months all vary substantially at the district level. Having only state-level estimates may thus be inadequate to inform efforts to remediate low levels of women’s work in India. The insights from our current study may help in the formulation and implementation of targeted policies that increase opportunities for women to expand their paid work in India.

How much do opinions regarding cultivated meat vary within the same country? The cases of São Paulo and Salvador, Brazil

The problems related to conventional meat production have been widely discussed globally and alternative proteins emerge as more sustainable and ethical options. Thus, understanding the intention to consume cultivated meat is key. This work aimed to study the intention to consume cultivated meat by residents of São Paulo and Salvador, Brazil, studying demographic differences. An online questionnaire comprising 17 multiple-choice and open-ended questions about opinions on conventional and cultivated meat was administered. The results were analyzed using quantitative methods, including binary logistic regression and ordinal regression models, as well as the qualitative Collective Subject Discourse methodology. With 809 participants, 419 (51.8%) from São Paulo and 390 (48.2%) from Salvador, 265 (32.8%, of which 170 (64.2%) from São Paulo and 95 (35.8%) from Salvador) respondents stated they would eat cultivated meat. Residents of São Paulo demonstrated higher familiarity with cultivated meat (187 (44.6%) had heard of it compared to 123 (31.5%) in Salvador). Such disparity in awareness seems coherent with differences in access to information and educational levels. Our results suggest that the acceptance of cultivated meat varies significantly across different regions of Brazil, likely related to the country’s continental size, uneven economic and educational status and rich cultural diversity. We conclude that the acceptance of cultivated meat correlates with knowledge about it and that efforts to raise such knowledge require the consideration of cultural and socioeconomic aspects on a regional rather than national level, especially for geographically big and culturally diverse countries. Continued research is essential due to dynamics of acceptance and its entanglement with familiarity and knowledge regarding cultivated meat.

Evaluating the structure-based virtual screening performance of SARS-CoV-2 main protease: A benchmarking approach and a multistage screening example against the wild-type and Omicron variants

COVID-19 still poses a worldwide health threat due to continuous viral mutations and potential resistance to vaccination. SARS-CoV-2 viral multiplication hindrance by inhibiting the viral main protease (Mpro) deemed propitious. Structure-based virtual screening (SBVS) is a conventional strategy for discovering new inhibitors. Nonetheless, the SBVS efforts against Mpro variants needed to be benchmarked. Herein, in the first stage of the study, we evaluated four docking tools (FRED, PLANTS, AutoDock Vina and CDOCKER) via an in-depth benchmarking approach against SARS-CoV2 Mpro of both the wild type (WTMpro) and the deadly Omicron P132H variant (OMpro). We started by compiling an active dataset of non-covalent small molecule inhibitors of the WTMpro from literature and the COVID-Moonshot database along with generating a high-quality benchmark set via DEKOIS 2.0. pROC-Chemotype plots revealed superior performance for AutoDock Vina against WTMpro, while both FRED and AutoDock Vina demonstrated excellent performance for OMPro. In the second stage, VS was performed on a focused library of 636 compounds transformed from the early-enriched cluster related to perampanel via a scaffold hopping approach. Subsequently, molecular dynamics (MD) simulation and MM GBSA calculations validated the binding potential of the recommended hits against both explored targets. This study provides an example of how to conduct an in-depth benchmarking approach for both WTMPro and OMPro variants and offering an evaluated SBVS protocol for them both.

TGF-Net: Transformer and gist CNN fusion network for multi-modal remote sensing image classification

In the field of earth sciences and remote exploration, the classification and identification of surface materials on earth have been a significant research area that poses considerable challenges in recent times. Although deep learning technology has achieved certain results in remote sensing image classification, it still has certain challenges for multi-modality remote sensing data classification. In this paper, we propose a fusion network based on transformer and gist convolutional neural network (CNN), namely TGF-Net. To minimize the duplication of information in multimodal data, the TGF-Net network incorporates a feature reconstruction module (FRM) that employs matrix factorization and self-attention mechanism for decomposing and evaluating the similarity of multimodal features. This enables the extraction of distinct as well as common features. Meanwhile, the transformer-based spectral feature extraction module (TSFEM) was designed by combining the different characteristics of remote sensing images and considering the problem of orderliness of the sequence between hyperspectral image (HSI) channels. In order to address the issue of representing the relative positions of spatial targets in synthetic aperture radar (SAR) images, we proposed a spatial feature extraction module called gist-based spatial feature extraction module (GSFEM). To assess the efficacy and superiority of the proposed TGF-Net, we performed experiments on two datasets comprising HSI and SAR data.

Impact of patients’ age and comorbidities on prostate cancer overdiagnosis in clinical practice

Introduction Overdiagnosis in PSA-based prostate cancer (PCa) screening is primarily studied in younger, healthier populations from clinical trials. This study aimed to evaluate the probability of overdiagnosis in PCa screening within a clinical practice context, focusing on its relationship with PSA levels, Gleason scores, and subsequent clinical procedures. Methods We conducted a retrospective cohort analysis of 1,070 asymptomatic men over 40 years old diagnosed with PCa between 2004 and 2022, following a positive PSA test. The patients were followed until December 31, 2022, with a median follow-up time of 5.7 years (IQR 3.2–8.6). The primary outcome was the probability of overdiagnosis, assessed through life expectancy and the Charlson Comorbidity Index, considering lead times of 5, 10, and 15 years. Results We found that patients with PSA levels >10 ng/dL and/or Gleason scores ≥8 were generally older and had more comorbidities than those with PSA levels 4–10 ng/dL and/or Gleason scores ≤7. The probability of overdiagnosis was significantly higher in patients with PSA levels >10 ng/dL (41.4%, IQR 21.5–73.9) and Gleason scores ≥8 (42.6%, IQR 14.9–38.9), compared to those with PSA levels 4–10 ng/dL (20.1%, IQR 12.8–30.4) and Gleason scores ≤7 (26.6%, IQR 23.6–68.6). Notably, 71.7% of patients did not receive pharmacological treatment. Patients with higher PSA levels also experienced greater radiation exposure from diagnostic imaging (median 19.9 mSv vs. 14.7 mSv, p = 0.004). Conclusions These findings underscore the high likelihood of overdiagnosis in older patients with elevated PSA levels and significant comorbidities, highlighting the need for careful consideration of patient comorbidities before PSA testing.

A novel 3D bilateral filtering algorithm with noise level estimation assisted by multi-temporal SAR

The bilateral filter is widely employed in the field of image denoising due to its flexibility and efficiency. It calculates the weights of neighboring pixels based on both spatial and grayscale distances from the pixel to be denoised. By incorporating the information of neighboring pixels through a weighted average, it reduces the disparity between the target pixel and its neighbors, achieving the goal of denoising. However, the extensive imaging range of SAR, coupled with low spatial resolution and the complexity of surface features, results in significant variations in the information expressed by each pixel within the kernel. Consequently, relying solely on neighboring pixel information for denoising can introduce a considerable amount of extraneous data into the target pixel, reducing image contrast and blurring edge contours. Additionally, because the noise levels in pixels of SAR images vary, the uniform filtering approach of the bilateral filter may lead to a degree of information loss in the filtered pixels. Ultimately, while the bilateral filter performs well in addressing additive noise, it is less effective against the multiplicative noise common in SAR images, further diminishing its filtering efficacy. To address these issues, we have developed the 3D bilateral filtering algorithm with noise level estimation assisted by multi-temporal SAR(3D-NLE-BF). This algorithm begins by evaluating the noise content of pixels to be denoised based on their temporal and spatial stability, classifying them into strong noise, weak noise, and noise-free pixels. Given the higher similarity of pixels along the temporal axis in multitemporal SAR data, the algorithm capitalizes on this feature to ensure that denoised pixels contain more useful information. Taking into account the characteristics of multitemporal SAR, the algorithm incorporates range-weight, spatial-weight, confidence-weight, and time-weight, designing corresponding filtering kernels for both strong and weak noise pixels. To verify the superiority of the algorithm, we selected Bilateral, NLM, Kuan, Lee, Lee-Enhanced, and Lee-Sigma as comparison algorithms. Real and simulated SAR denoising experiments were designed, and the denoising results were evaluated using ENL, SSI, PSNR, and QIUI, achieving favorable evaluation results. This demonstrated the effectiveness and general applicability of the algorithm proposed in this paper.

Evaluation of the variations of mandibular molars and the distance from root apex to the inferior alveolar nerve in Saudi Sub-population: Three-dimensional radiographic evaluation

Aim To investigate the prevalence of various morphological variations in the roots and canals of lower mandibular molar teeth in the Saudi subpopulation and measure the distance from the root apices to the inferior alveolar canal (IAC). Materials and methods A cross-sectional analysis was conducted on 149 CBCT scans from Taibah University the College of Dentistry (TUCD). Three evaluators independently reviewed scans for anatomical features such as the number of canals, the presence of radix molaris (RM), and root-to-IANC distances. Teeth observed from the medullary cavity to the root apical layers on the coronal, sagittal and cross-section views. Data was analyzed using SPSS 21.0 software. Statistically significant differences were defined at p < 0.05. Results The prevalence of RM ranged between 0.7%-3.4% in lower first and second molars. The number of the canals in the apex ranged between 2–4 canals, with most molars showing three canals. The prevalence of 2 canals in lower first molars is around 2% and in lower second molars is 9.2%. A significant age-related correlation was noted in distances from the mesial and distal roots to the IAC, with values ranging from 0 to 14.7 mm. Conclusion The study reveals diverse root and canal morphologies and varying distances to the IANC within the Saudi subpopulation, emphasizing the necessity for precise preoperative radiographic assessments to optimize endodontic outcomes and reduce procedural risks. Findings suggest the need for further research into these anatomical variations to refine diagnostic and treatment strategies in endodontics, particularly in diverse populations to improve patient outcomes.

Convolutional neural network for gesture recognition human-computer interaction system design

Gesture interaction applications have garnered significant attention from researchers in the field of human-computer interaction due to their inherent convenience and intuitiveness. Addressing the challenge posed by the insufficient feature extraction capability of existing network models, which hampers gesture recognition accuracy and increases model inference time, this paper introduces a novel gesture recognition algorithm based on an enhanced MobileNet network. This innovative design incorporates a multi-scale convolutional module to extract underlying features, thereby augmenting the network’s feature extraction capabilities. Moreover, the utilization of an exponential linear unit (ELU) activation function enhances the capture of comprehensive negative feature information. Empirical findings demonstrate that our approach surpasses the accuracy achieved by most lightweight network models on publicly available datasets, all while maintaining real-time gesture interaction capabilities. The accuracy of the proposed model in this paper attains 92.55% and 88.41% on the NUS-II and Creative Senz3D datasets, respectively, and achieves an impressive 98.26% on the ASL-M dataset.

A new troglobitic species of Tychobythinus from Sicily with notes on some Italian species of the genus (Coleoptera, Staphylinidae, Pselaphinae)

A new troglobitic species of the subfamily Pselaphinae (Coleoptera: Staphylinidae), Tychobythinus muxari n. sp., is described from Sicily (Ciavuli cave, Sant’Angelo Muxaro, Agrigento). Major diagnostic features are illustrated based on both male and female specimens. The new species shows some adaptations to cave life, i.e., pale brown color, setation consisting of long and flattened setae and suberect shorter setae, absence of wings, microphthalmia and elongated legs and antennae. It can be easily separated from the related taxa by the different shapes of the head and profemora and protibiae of the male, and of the aedeagus. The new synonymy Tychobythinus cameratensis (Karaman, 1959) =  Tychobythinus gracilicornis (Raffray, 1914) (syn. nov.) is proposed. New data on morphology, taxonomy and/or distribution of T. andreinii (Dodero, 1919), T. controversus Poggi 1923, T. dentimanus (Reitter, 1884), T. foroiuliensis Pace, 1976, T. glabratus (Rye, 1870), T. gladiator gladiator (Reitter, 1885), T. majori (Holdhaus, 1905), T. mirandus (Dodero, 1919), T. myrmido (Reitter, 1882) and T. tibialis (Dodero, 1919) are provided.

Potential blood biomarkers that can be used as prognosticators of spontaneous intracerebral hemorrhage: A systematic review and meta-analysis

Background Predicting nontraumatic spontaneous intracerebral hemorrhage (SICH) patient prognosis has been commonly practiced, particularly when providing informed consent and considering surgical treatment. Biomarkers might provide more real-time evaluation of SICH patients’ condition than clinical prognostic scoring systems. This study aimed to evaluate the reliability of blood biomarkers in predicting prognosis in SICH patients by systematic review and meta-analysis. Methods Studies that evaluated the association of blood biomarker(s) with mortality and/or functional outcome in SICH patients up to October 11, 2024, were identified through PubMed, Google Scholars, Scopus databases, and reference lists. Studies that satisfied the inclusion criteria were included in the meta-analyses. Good functional outcome was defined by patient’s Glasgow Outcome Scale (GOS) ≥ 4 or modified Rankin scale mRS ≤ 2. Blood biomarkers were classified into the following categories: angiogenic factors, growth factors, inflammatory biomarkers, coagulation parameters, blood counts, and others. Individual meta-analysis was performed for every evaluation endpoint:7 days, 30 days, 3 months, 6 months, and 1 year. Meta-analyses were performed using Random Effect Mean-Difference with a 95% Confidence Interval for continuous data and visualized as forest plots in RevMan version 5.3 software. Cochrane Tool to Assess Risk of Bias in Cohort Studies was used to assess potential risk of bias of the included studies. GRADE Profiler was used to assess quality of evidence. Results Seventy-seven studies fulfilled the inclusion criteria. Surviving SICH patients have significantly lower C-reactive protein (CRP), D-dimer, copeptin, S100β, white blood cell (WBC), monocyte, and glucose than non-surviving patients. SICH patients with good functional outcome have lower D-dimer, Interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), WBC count, neutrophil count, monocyte count, copeptin and significantly higher lymphocyte counts and calcium levels. Out of all blood biomarkers that were evaluated, only S100β and copeptin had very high effect size and high certainty of evidence. Conclusion It is interesting to notice that many blood biomarkers significantly associated with SICH patients’ outcomes are related to inflammatory responses. This suggests that modulation of inflammation might be essential to improve SICH patients’ prognosis. We confidently concluded that S100β and copeptin are the most reliable blood biomarkers that can be used as prognosticators in SICH patients. On other biomarkers, in addition to heterogeneities and inconsistencies, several factors might affect the conclusions of current meta-analysis; thus, future studies to increase the certainties of evidence and effect size on other biomarkers are crucial.

Chromosomal domain formation by archaeal SMC, a roadblock protein, and DNA structure

Based on PCA and SSA-LightGBM oil-immersed transformer fault diagnosis method

A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. The feature matrix is then standardized to obtain joint features. Secondly, principal component analysis is used for feature fusion to eliminate information redundancy between variables and construct fused features. Finally, a transformer diagnostic model based on SSA-LightGBM was constructed, and the ten fold cross validation method was used to verify the classification ability of the model. The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. At the same time, compared with the GA-LightGBM and GWO-LightGBM fault diagnosis models, SSA-LightGBM has improved the diagnostic accuracy by 8.1% and 5.7% respectively, verifying that this method can effectively improve the fault diagnosis performance of oil immersed transformers and is superior to other similar methods.

Ball-and-chain inactivation of a human large conductance calcium-activated potassium channel

A study on the relationship between personality and motivation in leisure participants

Motivation and personality, which are among the most important effects of human behavior, are important in terms of leisure activities. Therefore, this study aimed to examine the relationship between motivation and personality of individuals who participate in physical activity in their leisure time. In the study, the correlational screening model was used, and 370 (m:28.76±10.37) participants who regularly practiced physical activity participated. The relationship between the data obtained in the research was tested with canonical correlation analysis, and the first two canonical correlation functions between the two variable data sets were interpreted. Self-control and extraversion sub-dimensions in the personality data set and internal regulation and external regulation sub-dimensions in the motivation data set were found to make the highest contribution. It was determined that for the first set of canonical functions, the relationship between self-control and internal regulation had a unidirectional correlation, whereas, for the second set of canonical functions, the relationship between extraversion and external regulation had an inverse correlation. Studies show how valuable intrinsic motivation sources are for individuals, and personality traits such as self-control and extraversion support this situation. It is considered that the personality traits of leisure time participants may be a clue to the types of motivation of the participants.

A small signaling domain controls PPIP5K phosphatase activity in phosphate homeostasis

Abstract Inositol pyrophosphates (PP-InsPs) are eukaryotic nutrient messengers. The N-terminal kinase domain of diphosphoinositol pentakisphosphate kinase (PPIP5K) generates the messenger 1,5-InsP 8 , the C-terminal phosphatase domain catalyzes PP-InsP breakdown. The balance between kinase and phosphatase activities regulates 1,5-InsP 8 levels. Here, we present crystal structures of the apo and substrate-bound PPIP5K phosphatase domain from S. cerevisiae (ScVip1 PD ). ScVip1 PD is a phytase-like inositol 1-pyrophosphate histidine phosphatase with two conserved catalytic motifs. The enzyme has a strong preference for 1,5-InsP 8 and is inhibited by inorganic phosphate. It contains an α-helical insertion domain stabilized by a structural Zn 2+ binding site, and a unique GAF domain that channels the substrate to the active site. Mutations that alter the active site, restrict the movement of the GAF domain, or change the substrate channel’s charge inhibit the enzyme activity in vitro, and Arabidopsis VIH2 in planta . Our work reveals the structure, enzymatic mechanism and regulation of eukaryotic PPIP5K phosphatases.