FP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n.

To address the limitations of existing deep learning-based algorithms in detecting surface defects on brake pipe ends, a novel lightweight detection algorithm, FP-YOLOv8, is proposed. This algorithm is developed based on the YOLOv8n framework with the aim of improving accuracy and model lightweight design. First, the C2f_GhostV2 module has been designed to replace the original C2f module.

Cytoskeleton dysfunction of motor neuron in spinal muscular atrophy.

Spinal muscular atrophy (SMA) is a neurodegenerative disease caused by deletions or mutations of survival of motor neuron 1 (SMN1) gene. To date, the mechanism of selective cell death of motor neurons as a hallmark of SMA is still unclear. The severity of SMA is dependent on the amount of survival motor neuron (SMN) protein, which is an essential and ubiquitously expressed protein involved in various cellular processes including regulation of cytoskeletal dynamics.

A Novel Brain Network Analysis Method for Pediatric ADHD Using RFE-GA Feature Selection Strategy.

Attention Deficit Hyperactivity Disorder (ADHD) is a highly prevalent childhood disorder, and related research has been increasing in recent years. However, it remains a challenging issue to accurately identify individuals with ADHD. The research proposes a method for ADHD detection using Recursive Feature Elimination-Genetic Algorithm (RFE-GA) for the feature selection of EEG data.

An Immunomodulator-Boosted Lactococcus Lactis Platform For Enhanced In Situ Tumor Vaccine.

In situ vaccination is an attractive type of cancer immunotherapy, and methods of persistently dispersing immune agonists throughout the entire tumor are crucial for maximizing their therapeutic efficacy. Based on the probiotics usually used for dietary supplements, an immunomodulator-boosted Lactococcus lactis (IBL) strategy is developed to enhance the effectiveness of in situ vaccination with the immunomodulators. The intratumoral delivery of OX40 agonist and resiquimod-modified Lactococcus lactis (OR@Lac) facilitates local retention and persistent dispersion of immunomodulators, and dramatically modulates the key components of anti-tumor immune response.

Effect of electroacupuncture on expression of protein phosphorylation in hippocampus tissues of rats with chronic fatigue syndrome.

Objectives: To observe the effect of electroacupuncture (EA) on behavior and hippocampal protein phosphorylation in rats with chronic fatigue syndrome (CFS), so as to explore its mechanisms underlying improvement of CFS.

Methods: Male SD rats were randomly divided into control, model and EA groups (=12 rats in each group). The CFS model was established by chronic multifactor combined with stress stimulation (treadmill training + restraint stress + sleep disturbance + crowded environment).

Acidity-targeting transition-aided universal chimeric antigen receptor T-cell (ATT-CAR-T) therapy for the treatment of solid tumors.

The use of CAR-T cells in treating solid tumors frequently faces significant challenges, mainly due to the heterogeneity of tumor antigens. This study assessed the efficacy of an acidity-targeting transition-aided universal chimeric antigen receptor T (ATT-CAR-T) cell strategy, which is facilitated by an acidity-targeted transition. Specifically, the EGFRvIII peptide was attached to the N-terminus of a pH-low insertion peptide.

Potent antitumor activity of a bispecific T-cell engager antibody targeting the intracellular antigen KRAS G12V.

Kirsten Rat Sarcoma viral oncogene homolog (KRAS) is one of the most frequent oncogenes. However, there are limited treatment options due to its intracellular expression. To address this, we developed a novel bispecific T-cell engager (BiTE) antibody targeting HLA-A2/KRAS G12V complex and CD3 (HLA-G12V/CD3 BiTE).

Cellulose-based materials in environmental protection: A scientometric and visual analysis review.

As sustainable materials, cellulose-based materials have attracted significant attention in the field of environmental protection, resulting in the publication of numerous academic papers. However, there is a scarcity of literature that involving scientometric analysis within this specific domain. This review aims to address this gap and highlight recent research in this field by utilizing scientometric analysis and a historical review.

Strategies to Mitigate Age-Related Bias in Machine Learning: Scoping Review.

Background: Research suggests that digital ageism, that is, age-related bias, is present in the development and deployment of machine learning (ML) models. Despite the recognition of the importance of this problem, there is a lack of research that specifically examines the strategies used to mitigate age-related bias in ML models and the effectiveness of these strategies.

Objective: To address this gap, we conducted a scoping review of mitigation strategies to reduce age-related bias in ML.

Non-destructive detection of defective maize kernels using hyperspectral imaging and convolutional neural network with attention module.

Rapid, effective and non-destructive detection of the defective maize kernels is crucial for their high-quality storage in granary. Hyperspectral imaging (HSI) coupled with convolutional neural network (CNN) based on spectral and spatial attention (Spl-Spal-At) module was proposed for identifying the different types of maize kernels. The HSI data within 380-1000 nm of six classes of sprouted, heat-damaged, insect-damaged, moldy, broken and healthy kernels was collected.

Predicting the role of the human gut microbiome in type 1 diabetes using machine-learning methods.

Gut microbes is a crucial factor in the pathogenesis of type 1 diabetes (T1D). However, it is still unclear which gut microbiota are the key factors affecting T1D and their influence on the development and progression of the disease. To fill these knowledge gaps, we constructed a model to find biomarker from gut microbiota in patients with T1D.

Controlled atmosphere storage drive proteomic change in Chinese Daohuaxiang.

Although the use of a controlled atmosphere is one of the most successful storage techniques, the mechanism thereof in rice storage remains unclear. We stored aromatic rice cultivar Daohuaxiang in a package filled with 98 % N and 35 % CO for 3 months. We investigated 2-acetyl-1-pyrroline loss, enzyme activities, and proteomics changes of rice during storage.

Indole-3-acetic acid improves periphyton's resistance to ultraviolet-B: From physiological-biochemical properties and bacteria community to livestock-polluted water purification.

Livestock-polluted water is a pressing water environmental issue in plateau pastoral regions, necessitating the adoption of eco-friendly solutions. Despite periphyton being a promising alternative, its efficacy is limited by the prevalence of intense ultraviolet radiation, particularly ultraviolet-B (UVB), in these regions. Therefore, this study employs molecular tools and small-scale trials to explore the crucial role of indole-3-acetic acid (IAA) in modulating periphyton characteristics and mediating nutrient removal from livestock-polluted water under UVB exposure.

Mechanism of effects of electroacupuncture on memory and cognitive impairment in offspring rats with perinatal nicotine exposure.

Objectives: To observe the effects of electroacupuncture(EA) on memory, cognitive impairment, and the brain-derived neurotrophic factor(BDNF)/N-methyl-D-aspartate receptor subtype 1(NMDAR1) pathway in the brains of offspring rat with intrauterine growth restriction(IUGR) induced by perinatal nicotine exposure(PNE), so as to explore the underlying mechanism.

Methods: SD rats were randomly divided into normal, model, and EA groups, with 4 mothers and 10 offspring rats of each mother in each group. The IUGR model was established by subcutaneous injection of nicotine during pregnancy and lactation.

Acupuncture Relieves Cervical Spondylosis Radiculopathy by Regulating Spinal Microglia Activation Through MAPK Signaling Pathway in Rats.

Purpose: Local acupuncture has been found to have a good analgesic effect in rats with cervical spondylosis radiculopathy (CSR), but it lacks a regulatory effect on traditional Chinese medicine syndrome types of CSR. We proposed "Invigorating Qi and activating Blood" (IQAB) acupuncture, compared with Fenbid, and local electroacupuncture (LEA), to observe whether it has advantages in the protection of the CSR rat model and to elucidate its mechanism through the MAPK (mitogen-activated protein kinase) signaling pathway.

Materials And Methods: Male Sprague-Dawley rats were randomly divided into six groups: control, sham, model, Fenbid, LEA, and IQAB.

Integrated 'omics analysis for the gut microbiota response to moxibustion in a rat model of chronic fatigue syndrome.

Objective: To observe the efficacy of moxibustion in the treatment of chronic fatigue syndrome (CFS) and explore the effects on gut microbiota and metabolic profiles.

Methods: Forty-eight male Sprague-Dawley rats were randomly assigned to control group (Con), CFS model group (Mod, established by multiple chronic stress for 35 d), MoxA group (CFS model with moxibustion Shenque (CV8) and Guanyuan (CV4), 10 min/d, 28 d) and MoxB group (CFS model with moxibustion Zusanli (ST36), 10 min/d, 28 d). Open-field test (OFT) and Morris-water-maze test (MWMT) were determined for assessment the CFS model and the therapeutic effects of moxibustion.

P450Rdb: A manually curated database of reactions catalyzed by cytochrome P450 enzymes.

Introduction: Cytochrome P450 enzymes (P450s) are recognized as the most versatile catalysts worldwide, playing vital roles in numerous biological metabolism and biosynthesis processes across all kingdoms of life. Despite the vast number of P450 genes available in databases (over 300,000), only a small fraction of them (less than 0.2 %) have undergone functional characterization.

A Lightweight Network for Contextual and Morphological Awareness for Hepatic Vein Segmentation.

Accurate segmentation of the hepatic vein can improve the precision of liver disease diagnosis and treatment. Since the hepatic venous system is a small target and sparsely distributed, with various and diverse morphology, data labeling is difficult. Therefore, automatic hepatic vein segmentation is extremely challenging.

iPADD: A Computational Tool for Predicting Potential Antidiabetic Drugs Using Machine Learning Algorithms.

Diabetes mellitus is a chronic metabolic disease, which causes an imbalance in blood glucose homeostasis and further leads to severe complications. With the increasing population of diabetes, there is an urgent need to develop drugs to treat diabetes. The development of artificial intelligence provides a powerful tool for accelerating the discovery of antidiabetic drugs.

Multi-Lane Differential Variable Speed Limit Control via Deep Neural Networks Optimized by an Adaptive Evolutionary Strategy.

In advanced transportation-management systems, variable speed limits are a crucial application. Deep reinforcement learning methods have been shown to have superior performance in many applications, as they are an effective approach to learning environment dynamics for decision-making and control. However, they face two significant difficulties in traffic-control applications: reward engineering with delayed reward and brittle convergence properties with gradient descent.

MSU-Net: Multi-scale Sensitive U-Net based on pixel-edge-region level collaborative loss for nasopharyngeal MRI segmentation.

Radiotherapy is the traditional treatment of early nasopharyngeal carcinoma (NPC). Automatic accurate segmentation of risky lesions in the nasopharynx is crucial in radiotherapy. U-Net has been proved its effective medical image segmentation ability.