Objective To investigate the load distribution on the more painful and less painful limbs in patients with mild-to-moderate and severe bilateral knee osteoarthritis (KOA) and explore the compensatory mechanisms in both limbs among bilateral KOA patients with different severity levels. Methods A total of 113 participants were enrolled between July 2022 and September 2023. This cohort comprised 43 patients with mild-to-moderate bilateral KOA (Kellgren-Lawrence grade 2-3), 43 patients with severe bilateral KOA (Kellgren-Lawrence grade 4), and 27 healthy volunteers (healthy control group). The visual analogue scale (VAS) score for pain, the Hospital for Special Surgery (HSS) score, passive knee range of motion (ROM), and hip-knee-ankle angle (HKA) were used to assess walking pain intensity, joint function, and lower limb alignment in KOA patients, respectively. Motion trajectories of reflective markers and ground reaction force data during walking were captured using a gait analysis system. Musculoskeletal modeling was then employed to calculate biomechanical parameters, including the peak knee adduction moment (KAM), KAM impulse, peak joint contact force (JCF), and peak medial/lateral contact forces (MCF/LCF). Statistical analyses were performed to compare differences in clinical and gait parameters between bilateral limbs. Additionally, one-dimensional statistical parametric mapping was utilized to analyze temporal gait data. Results Mild-to-moderate KOA patients showed the significantly higher HSS score (67.7±7.9) than severe KOA patients (51.9±8.9; t=8.747, P<0.001). The more painful limb in all KOA patients exhibited significantly greater HKA and higher VAS scores compared to the less painful limb (P<0.05). While bilateral knee ROM did not differ significantly in mild-to-moderate KOA patients (P>0.05), the severe KOA patients had significantly reduced ROM in the more painful limb versus the less painful limb (P<0.05). Healthy controls showed no significant bilateral difference in any biomechanical parameters (P>0.05). All KOA patients demonstrated longer stance time on the less painful limb (P<0.05). Critically, severe KOA patients exhibited significantly higher peak KAM, KAM impulse, and peak MCF in the more painful limb (P<0.05), while mild-to-moderate KOA patients showed the opposite pattern with lower peak KAM and KAM impulse in the more painful limb (P<0.05) and a similar trend for peak MCF. Conclusion Patients with mild-to-moderate KOA effectively reduce load on the more painful limb through compensatory mechanisms in the less painful limb. Conversely, severe bilateral varus deformities in advanced KOA patients nullify compensatory capacity in the less painful limb, paradoxically increasing load on the more painful limb. This dichotomy necessitates personalized management strategies tailored to disease severity.
Mental disorders are a type of behavioral, emotional, cognitive, or thinking disorder that cause pain and social dysfunction, and are one of the top ten global disease burdens. Cannabidiol (CBD) is one of the main components of cannabis, with high safety and tolerability, and is a hot topic in drug research. CBD has a wide range of therapeutic effects, and research has found that CBD has neuropsychiatric effects such as anti-addiction, anti-depression, anti-anxiety, and anti-stress, making it one of the candidate drugs for mental disorders. This article summarizes the mechanism and research progress of CBD for major mental disorders, in order to provide useful references for CBD-related compounds in the treatment of mental disorders.
Diabetes mellitus patients have the characteristics of higher morbidity of ischemic stroke, severe symptoms, more recurrent stroke and higher mortality. Current studies have shown that stroke patients with or without diabetes mellitus have different pathophysiological mechanisms during stroke progress. Accordingly, treatment that is beneficial to non-diabetes mellitus patients may not be beneficial to diabetes mellitus stroke patients. This article reviews the current research status of pathophysiological mechanism of diabetes mellitus complicated with ischemic stroke, and provides reference for the relevant research of drug intervention in diabetes mellitus patients complicated with stroke.
Iron death is an alternative to normal cell death and is regulated by a variety of cellular metabolic pathways. Iron death has become a hot topic of research because it can cause damage to various organs and degenerative diseases in the body. Metabolism, signalling pathways, endoplasmic reticulum stress, and immune cells can all affect the occurrence of iron death, and the blood-retina destruction induced by iron death plays an important role in autoimmune uveitis. Exploring the components of the blood-retina regulatory mechanism of iron death in autoimmune uveitis can lead to the search for targeted drug targets, which can provide a new research idea for the subsequent study of the diagnosis and treatment of autoimmune uveitis.
PNAS-4 is a novel pro-apoptosis gene identified latetly. In recent years, there has been a large number of research reports on the basic studies about PNAS-4 in cancer gene therapy and gene therapy of PNAS-4 alone or combined with chemotherapy or radiotherapy manifested a good application prospect, but its molecular mechanisms to promote apoptosis is not clear yet. In this paper, recent research about PNAS-4 in cancer gene therapy is briefly reviewed, and recent hypotheses on its molecular mechanisms to promote apoptosis are especially elucidated. Based on its newly identified characteristics of structural domain, we made a point that PNAS-4 might regulate functions of some target protein related to apoptosis by deSumoylation as a new deSumoylating isopeptidase, and consequently promote apoptosis.
Currently, all the conventional antibiotics have developed corresponding drug-resistant pathogenic strains, which have increasingly become a serious threat to people's health. Development of completely new types of antibiotics is one of effective ways to solve the drug resistance issue. Antimicrobial peptides with broad-spectrum antibacterial and antimicrobial activity and wild variety become the ideal alternative to traditional antibiotics. Antimicrobial peptides are derived from wide range of sources, such as plants, animals, and microorganisms. Mechanism of function of the antimicrobial peptides and the investigation approaches of different antimicrobial peptides also vary dramatically. In this paper, we give an overview of preparation, antibacterial mechanisms, and research methodology of antimicrobial peptides.
ObjectiveTo investigate the neural mechanisms of subjects with anisometropic amblyopia using event-related potential (ERP) technology.MethodsNineteen subjects diagnosed with anisometropic amblyopia were consecutively recruited from the outpatients of the West China Hospital of Sichuan University from June 2013 to February 2014, and twenty normal subjects were recruited as control subjects. All subjects were given different orientation Gabor stimuli with three spatial frequencies (1, 2, 8 cpd) and their ERP was recorded. The differences of P3b, including amplitude and latency, were compared between amblyopic eye and fellow or control eye.ResultsAmong the three groups of amblyopic eye and fellow or control eye, there was no statistically significant difference in accuracy or response time at three spatial frequencies (P>0.05), in latency or amplitude of P3b at low spatial frequencies (1, 2 cpd) ((P>0.05), or in amplitude of P3b at high spatial frequency (8 cpd) (P>0.05). P3b latency of amblyopic eye extended at high spatial frequency (8 cpd), compared to fellow or control eye. Amblyopic eye was most significantly weakened in Brodmann area 17 at the P3b wave of each spatial frequency (1, 2, 8 cpd), and there was most significantly weakened in high spatial frequency (8 cpd).ConclusionThe P3b latency of amblyopic eye extended at high spatial frequency suggests that the cognitive function of amblyopia is impaired, at an extent, in the late visual processing stage.
Obesity is a prevalent metabolic disorder,which seriously affects human health and has become the world's public health problem. Kinase S6K1, an important downstream effector of mammalian target of rapamycin (mTOR), influences specific pathological responses, including obesity, type 2 diabetes and cancer. Presently, S6K1 has become an attractive therapeutic target in the treatment of these disorders. Here, the functions of kinase S6K1, its molecular regulation mechanisms, related pathogenesis of disease and relevant small molecular inhibitors are reviewed. Finally, the prospect of research toward S6K1 is expected as well.
Existing classification methods for myositis ultrasound images have problems of poor classification performance or high computational cost. Motivated by this difficulty, a lightweight neural network based on a soft threshold attention mechanism is proposed to cater for a better IIMs classification. The proposed network was constructed by alternately using depthwise separable convolution (DSC) and conventional convolution (CConv). Moreover, a soft threshold attention mechanism was leveraged to enhance the extraction capabilities of key features. Compared with the current dual-branch feature fusion myositis classification network with the highest classification accuracy, the classification accuracy of the network proposed in this paper increased by 5.9%, reaching 96.1%, and its computational complexity was only 0.25% of the existing method. The obtained results support that the proposed method can provide physicians with more accurate classification results at a lower computational cost, thereby greatly assisting them in their clinical diagnosis.
Skin cancer is a significant public health issue, and computer-aided diagnosis technology can effectively alleviate this burden. Accurate identification of skin lesion types is crucial when employing computer-aided diagnosis. This study proposes a multi-level attention cascaded fusion model based on Swin-T and ConvNeXt. It employed hierarchical Swin-T and ConvNeXt to extract global and local features, respectively, and introduced residual channel attention and spatial attention modules for further feature extraction. Multi-level attention mechanisms were utilized to process multi-scale global and local features. To address the problem of shallow features being lost due to their distance from the classifier, a hierarchical inverted residual fusion module was proposed to dynamically adjust the extracted feature information. Balanced sampling strategies and focal loss were employed to tackle the issue of imbalanced categories of skin lesions. Experimental testing on the ISIC2018 and ISIC2019 datasets yielded accuracy, precision, recall, and F1-Score of 96.01%, 93.67%, 92.65%, and 93.11%, respectively, and 92.79%, 91.52%, 88.90%, and 90.15%, respectively. Compared to Swin-T, the proposed method achieved an accuracy improvement of 3.60% and 1.66%, and compared to ConvNeXt, it achieved an accuracy improvement of 2.87% and 3.45%. The experiments demonstrate that the proposed method accurately classifies skin lesion images, providing a new solution for skin cancer diagnosis.