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Integrated in vitro, in silico, and in vivo approaches to elucidate the antidiabetic mechanisms of Cicer arietinum and Hordeum vulgare extract and secondary metabolites
G-protein coupled receptor kinase-2 regulates the migration of chronic lymphocytic leukaemia cells to sphingosine-1 phosphate in vitro and their trafficking in vivo
Computational analysis of a mathematical model of hookworm infection
Robust power management capabilities of integrated energy systems in the smart distribution network including linear and non-linear loads
Diagnostic value of the pregnancy index for acute appendicitis in pregnant women
Air trapping in patients with idiopathic pulmonary fibrosis: a retrospective case—control study
Sex and pressure effects of foam rolling on acute range of motion in the hamstring muscles
This study investigated the effects of pressure levels and sex on acute range of motion (ROM) changes during foam rolling (FR) using a soccer ball. Twenty collegiate athletes (10 males, 10 females) performed FR on their hamstrings at low (15–25% body weight) or high (45–55%) pressure levels for 2 minutes. ROM was assessed through passive straight leg raise (PSLR) and passive knee extension (PKE) tests before, immediately after, and 10 minutes post-intervention. Results showed that FR significantly improved hip and knee ROM across all conditions, with benefits persisting for at least 10 minutes. No notable differences were observed between pressure levels, and sex did not affect the magnitude of improvement. Perceived pain during FR did not significantly influence ROM outcomes. These findings demonstrate that FR using a simple tool like a soccer ball is beneficial for improving ROM in both males and females, regardless of pressure intensity. This suggests that FR provides a practical, accessible method for improving ROM in athletes and other populations.
Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning
Abstract Diffusion magnetic resonance imaging (diffusion MRI) is widely employed to probe the diffusive motion of water molecules within the tissue. Numerous diseases and processes affecting the central nervous system can be detected and monitored via diffusion MRI thanks to its sensitivity to microstructural alterations in tissue. The latter has prompted interest in quantitative mapping of the microstructural parameters, such as the fiber orientation distribution function (fODF), which is instrumental for noninvasively mapping the underlying axonal fiber tracts in white matter through a procedure known as tractography. However, such applications demand repeated acquisitions of MRI volumes with varied experimental parameters demanding long acquisition times and/or limited spatial resolution. In this work, we present a deep-learning-based approach for increasing the spatial resolution of diffusion MRI data in the form of fODFs obtained through constrained spherical deconvolution. The proposed approach is evaluated on high quality data from the Human Connectome Project, and is shown to generate upsampled results with a greater correspondence to ground truth high-resolution data than can be achieved with ordinary spline interpolation methods. Furthermore, we employ a measure based on the earth mover’s distance to assess the accuracy of the upsampled fODFs. At low signal-to-noise ratios, our super-resolution method provides more accurate estimates of the fODF compared to data collected with 8 times smaller voxel volume.
The link between impact-induced tensile strain and dendritic spine morphology in porcine brain tissue
Brain tissue as a material presents unique properties with a multitude of cell types and densities, varying degrees of axonal fiber diameters and blood vessels. These neural components are contained within a very viscous environment that upon impact, can result in a variety of tensile, compressive and rotational forces. The depths of the sulcus appear to be particularly vulnerable to biomechanical forces following an impact. The movement and subsequent forces loaded on to the brain have been shown to produce a variety of biomechanical responses that impair neurophysiological functioning at the cellular level. We recently reported a decrease in microtubule associated protein 2 (MAP2) within the depths of the porcine sulcus in an ex vivo model, along with elevated tensile strain in this region within 1 hour after impact. In the current work, using the same impact model, we explored whether changes in spine morphology and density occurred within the same timeframe following impact. The Golgi-Cox method was used to visualize dendritic spine morphology. Cortical pyramidal neurons within the depths and the arms of the sulcus were reconstructed. One hour after impact, there was a change in the distribution of spine type resulting in an increased proportion of mushroom-type spines compared to nonimpacted tissue. The increased proportion of mushroom-type spines was proportional to tensile strain measurements in the apical dendrites. These results demonstrate the sensitivity of dendritic spine morphology to tensile strain within the porcine cortex and suggest a state of hyperexcitability during the hyperacute phase following an impact.
Physiological impact of surgical masks and N95 masks on obese operating room staff
Estimating the dietary and health impact of implementing mandatory front-of-package nutrient disclosures in the US: A policy scenario modeling analysis
Background Recognized as a cost-effective policy to promote healthier diets, mandatory front-of-package labeling (FOPL) identifying foods high in sodium, sugar, and saturated fat has been adopted and implemented in ten countries, and is currently under consideration in several others including the US. However, its potential impact on dietary intake and health have not yet been estimated in the US context. Objectives To estimate (1) the potential dietary impact of implementing mandatory nutrient-specific ‘high in’ FOPL among US adults; and (2) the number of diet related non-communicable disease (NCD) deaths that could be averted or delayed due to estimated dietary changes. Methods Baseline and counterfactual dietary intakes of sodium, sugars, saturated fats, and calories were estimated among US adults (n = 7,572) using both available days of 24h recall data from the 2017–2020 National Health and Nutrition Examination Survey (NHANES). The National Cancer Institute method was used to estimate usual intakes and distributions, adjusting for age, sex, misreporting status, weekend/weekday, and sequence of recall. To estimate counterfactual dietary intakes, we modeled two reduction scenarios observed in experimental and observational studies that examined changes in sodium, sugars, saturated fat and calorie content of food and beverage purchases due to nutrient-specific ‘high in’ FOPL. This study used the Preventable Risk Integrated ModEl (PRIME) to estimate potential health impacts. Results Estimated mean dietary reductions of 156 mg and 259 mg/day of sodium, 10.1 g and 7.2 g/day of sugars, 1.08 g and 4.49 g/day of saturated fats, and 38 kcal and 57 kcal/day of calories were observed under the two policy scenarios tested. Between 96,926 (95% UI 89,011–105,284) and 137,261 (95% UI 125,534–148,719) diet related NCD deaths, primarily from cardiovascular diseases (74%), could potentially be averted or delayed by implementing mandatory nutrient-specific FOPL in the US. Overall, more lives would be saved in males than females. Conclusions Findings suggest that implementing mandatory nutrient-specific ‘high in’ FOPL in the US could significantly reduce sodium and total sugar intakes among US adults, resulting in a substantial number of NCD related deaths that could be averted or delayed. Our results can inform current food policy developments in the US regarding the adoption and implementation of FOPL regulations.
Optimizing the zymogram of exogenous proteases in broiler diets by in vitro simulated gastrointestinal digestion and response surface methodology
The alteration of uterine microbiota participated in the activation of the decidual inflammatory response in early spontaneous abortion
Background Early spontaneous abortion (ESA) is one of the most common clinically recognized pregnancy complications. While multiple factors such as embryo abnormalities and maternal conditions may contribute to ESA, early identification and screening of maternal risk factors are increasingly important to explore the potential etiologies and improve prevention and treatment strategies for ESA. This study investigates the changes in uterine microbiota and the decidual immune response in ESA patients without embryo abnormalities. Methods ESA patients without embryo abnormality and artificial abortion (AA) controls were enrolled for clinical characteristics analysis. The decidual endometrium was subsequently collected for histological evaluation and inflammatory indicator detection. Moreover, 16S rRNA gene sequencing of uterine secretions was performed to investigate the differences in uterine microorganisms between the ESA and AA groups. Results Clinical analysis showed higher inflammatory response with elevated neutrophil counts in ESA patients. The increase in leukocytes, including neutrophils, was positively correlated with ESA. ESA patients presented significantly increased IL-1β expression in decidual stromal cells. 16S rRNA gene sequencing revealed greater diversity in the uterine microbiota of the ESA group, which presented decreased Lactobacillus abundance and increased abundance of other bacteria at the genus and species levels. Conclusions Changes in the uterine microbiome are likely related to inflammatory response and lead to early pregnancy loss.
Research on optimal control design of displaced left turn signal at one two way and three one way traffic intersections
Abstract As the nodes of urban road traffic network, intersections serve as an effective means to improve traffic flow efficiency and alleviate traffic congestion through the optimization of reasonable traffic organization and signal schemes for intersections. In recent years, domestic research on unconventional intersections has attracted increasing attention. This paper first summarized the types of single-double traffic intersections and preliminarily discussed the applicability of displaced left-turn (DLT) signal organization. We then constructed a calculation method for determining the important design parameters in the DLT signal traffic organization, based on the design of the channelization form of the intersection of Haihe Road and Xuanqing Street in Harbin City, China. Based on the average delay of vehicles, we established a signal optimization control model with two components: the main signal delay and the pre-signal delay, aiming to minimize the delay of vehicles. The signal optimization control model was established considering both the main signal delay and the pre-signal delay. Finally, the selected examples were compared and verified using VISSIM simulation. The simulation results show that through the design of one two-way and three one-way traffic intersections with DLT signals and signal optimization control, the average vehicle delay at the intersection is significantly reduced, and traffic efficiency is enhanced.
Vertical distribution of methanotrophic archaea in an iron-rich groundwater discharge zone
Anaerobic oxidation of methane coupled to iron reduction (Fe-AOM) is a crucial process for methane removal in terrestrial environments. However, the occurrence of Fe-AOM in natural environments is rare, and the mechanisms behind the direct coupling of methane oxidation and iron reduction remain poorly understood. In this study, we investigated the environmental factors influencing the distribution of methanotrophic archaea in an iron-rich zone of a freshwater pond in Hiroshima Prefecture, Japan. High concentration of dissolved ferrous iron supplied by groundwater discharge led to considerable ferrihydrite precipitation. Pore water methane increased with sediment depth, while nitrate and sulfate concentrations were near detection limits throughout the sediment column. The coexistence of ferric iron and methane suggests the ongoing process of Fe-AOM. Tracer-based experiments using 14C showed potential Fe-AOM rates up to 110 pmol mL-1 day-1. Throughout the sediment core, except at the surface, PCR-based molecular ecological analyses of the 16S rRNA gene and functional genes for anaerobic oxidation of methane revealed abundant sequences belonging to the family “Candidatus Methanoperedenaceae”. These geochemical and microbiological findings suggest that Fe-AOM plays a key role in biogeochemical cycles of iron and methane, positioning this environment as a modern analogue of early Earth conditions.
FmCFA: a feature matching method for critical feature attention in multimodal images
Enhancing communication in healthcare: Supports for interactions between adults with hearing loss and healthcare providers
Background Communication between a healthcare provider and an adult with hearing loss can be challenging and potentially contribute to health outcomes. To overcome this challenge, researchers have called for urgent multidisciplinary action on communication support in hearing healthcare. Objective This scoping review examines the existing literature on communication support that can be provided to adults with hearing loss during their interactions with healthcare professionals. Methods An online search was conducted using EMBASE, MEDLINE, CINAHL, and PsycINFO. All studies were imported into the Covidence platform for screening. The studies included in this analysis were published in English between 2013 and 2024. Results Twelve articles were included in this review, and seven themes were identified: supportive nonverbal strategies, supportive verbal strategies, human support, environmental and physical adaptations, technological support, education and training, and psychological support and counseling. Conclusions When communicating with a healthcare provider, adults with hearing loss can be assisted through supportive communication strategies.
Correlation between gut microbiota dysbiosis, metabolic syndrome and breast cancer
Abstract Breast cancer is a widespread cancer with a high death rate globally. The incidence of breast cancer is expected to increase, particularly in low and middle-income countries due to environmental factors and lifestyle changes. Several risk factors, such as age, family history, hormonal and reproductive factors, have been identified to influence breast cancer development. Metabolic syndrome, is a metabolic disorder that has also been linked to breast cancer risk. The gut microbiome has been suggested as one of the environmental factors leading to breast cancer. The human microbiome is mainly colonized in the intestine by various bacterial species, including Lactobacillus, Bifidobacterium, and Streptococcus and protect the host against pathogenic microorganisms and regulate the immune system. This study included 50 female breast cancer patients and 50 healthy controls with matched ages. Stool fresh samples were taken from test and control groups and stored at − 20 °C until further investigations. DNA of the bacteria in stool samples was extracted using reverse transcription-quantitative polymerase chain reaction to check for the bacterial 16s rRNA gene. The exclusion criteria included other malignancies, recent intestinal surgery, infectious diarrhea, prolonged use of antibiotics, substance addiction, and pregnancy or lactation. Our findings exhibited that breast cancer patients had a higher incidence of metabolic syndrome (60%) compared to cancer-free controls (40%). Furthermore, breast cancer patients had significantly lower Bifidobacterium and Lactobacillus counts than the controls. No significant difference was found in Streptococcus counts between groups. These findings support the relationship between breast cancer and metabolic syndrome and suggest the potential involvement of Lactobacillus and Bifidobacterium in breast cancer pathophysiology. Our study supports the relation between breast cancer and disorder of metabolic syndrome and suggests the potential involvement of Lactobacillus and Bifidobacterium in breast cancer pathophysiology. Further research is necessary to investigate the complex interactions between genes, the environment, and the gut microbiome in breast cancer development. Understanding these interactions could lead to the progress of novel strategies for breast cancer prevention and treatment.
Optimizing Bi-LSTM networks for improved lung cancer detection accuracy
Lung cancer remains a leading cause of cancer-related deaths worldwide, with low survival rates often attributed to late-stage diagnosis. To address this critical health challenge, researchers have developed computer-aided diagnosis (CAD) systems that rely on feature extraction from medical images. However, accurately identifying the most informative image features for lung cancer detection remains a significant challenge. This study aimed to compare the effectiveness of both hand-crafted and deep learning-based approaches for lung cancer diagnosis. We employed traditional hand-crafted features, such as Gray Level Co-occurrence Matrix (GLCM) features, in conjunction with traditional machine learning algorithms. To explore the potential of deep learning, we also optimized and implemented a Bidirectional Long Short-Term Memory (Bi-LSTM) network for lung cancer detection. The results revealed that the highest performance using hand-crafted features was achieved by extracting GLCM features and utilizing Support Vector Machine (SVM) with different kernels, reaching an accuracy of 99.78% and an AUC of 0.999. However, the deep learning Bi-LSTM network surpassed both methods, achieving an accuracy of 99.89% and an AUC of 1.0000. These findings suggest that the proposed methodology, combining hand-crafted features and deep learning, holds significant promise for enhancing early lung cancer detection and ultimately improving diagnosis systems.