Objective To systematically evaluate the differences in outcomes between functional mitral regurgitation (FMR) and degenerative mitral regurgitation (DMR) in patients treated with transcatheter edge-to-edge repair (TEER) using the MitraClip device. Methods A systematic literature search was conducted in PubMed, Embase, the Cochrane Library, Web of Science, the CNKI, Wanfang Database, VIP Database, and the CBM from their inception to January 2024. Two researchers independently performed study selection, data extraction, and risk of bias assessment. The quality of cohort studies was evaluated using the Newcastle-Ottawa Scale (NOS). A meta-analysis was performed using Stata 18.0 software. Results A total of 13 cohort studies involving 6 402 patients were included, comprising 4 161 patients in the FMR group and 2 241 in the DMR group. All included studies had NOS scores of ≥6 points. The meta-analysis revealed that compared to the DMR group, the FMR group had a higher 1-year all-cause mortality rate [OR=1.53, 95%CI (1.30, 1.81), P＜0.01] and a higher 1-year rehospitalization rate for heart failure [OR=1.90, 95%CI (1.60, 2.26), P＜0.01]. Conversely, the FMR group had a lower post-procedural mean transmitral gradient [SMD=–0.47, 95%CI (–0.65, –0.30), P＜0.01] and a lower rate of subsequent mitral valve surgery [OR=0.41, 95%CI (0.20, 0.83), P=0.01]. Conclusion Following MitraClip therapy, patients with FMR exhibit favorable short-term outcomes, but their mid- to long-term outcomes are inferior to those of patients with DMR. When determining the treatment strategy with MitraClip, the specific etiology of mitral regurgitation should be considered for a more accurate prediction of therapeutic efficacy and prognosis.

In protein engineering, while computational models are increasingly used to predict mutation effects, their evaluations primarily rely on high-throughput deep mutational scanning (DMS) experiments that use surrogate readouts, which may not adequately capture the complex biochemical properties of interest. Many proteins and their functions cannot be assessed through high-throughput methods due to technical limitations or the nature of the desired properties, and this is particularly true for the real industrial application scenario. Therefore, the desired testing datasets, will be small-size (∼10-100) experimental data for each protein, and involve as many proteins as possible and as many properties as possible, which is, however, lacking. Here, we present VenusMutHub, a comprehensive benchmark study using 905 small-scale experimental datasets curated from published literature and public databases, spanning 527 proteins across diverse functional properties including stability, activity, binding affinity, and selectivity. These datasets feature direct biochemical measurements rather than surrogate readouts, providing a more rigorous assessment of model performance in predicting mutations that affect specific molecular functions. We evaluate 23 computational models across various methodological paradigms, such as sequence-based, structure-informed and evolutionary approaches. This benchmark provides practical guidance for selecting appropriate prediction methods in protein engineering applications where accurate prediction of specific functional properties is crucial.

Bacterial biofilms can make traditional antibiotics impenetrable and even promote the development of antibiotic-resistant strains. Therefore, non-antibiotic strategies to effectively penetrate and eradicate the formed biofilms are urgently needed. Here, we demonstrate the development of self-propelled biohybrid microrobots that can enhance the degradation and penetration effects for Pseudomonas aeruginosa biofilms in minimally invasive strategy. The biohybrid microrobots (CR@Alg) are constructed by surface modification of Chlamydomonas reinhardtii (CR) microalgae with alginate lyase (Alg) via biological orthogonal reaction. By degrading the biofilm components, the number of CR@Alg microrobots with fast-moving capability penetrating the biofilm increases by around 2.4-fold compared to that of microalgae. Massive reactive oxygen species are subsequently generated under laser irradiation due to the presence of chlorophyll, inherent photosensitizers of microalgae, thus triggering photodynamic therapy (PDT) to combat bacteria. Our algae-based microrobots with superior biocompatibility eliminate biofilm-infections efficiently and tend to suppress the inflammatory response in vivo, showing huge promise for the active treatment of biofilm-associated infections.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

OBJECTIVE: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult

Endotoxins are common exogenous pyrogens. Excessive endotoxins in medical devices and injections can lead to serious consequences such as sepsis, septic shock, and even death. Therefore, endotoxin detection plays a crucial role in medical, pharmaceutical, and food sectors. The wide application of Limulus amebocyte lysate (LAL) has led to a sharp decline in the number of horseshoe crabs. Moreover, the LAL assay has limitations such as interbatch variations and difficulty in quantification. The recombinant factor C (rFC) assay is stable between batches, highly sensitive, and capable of quantitation, and thus it can be used as an alternative for the LAL assay. However, the high cost and complex procedures involved in producing recombinant factor C have limited the widespread application of this method. In order to simplify the preparation and reduce the production cost of recombinant factor C, this study focuses on the production of recombinant factor C based on the baculovirus expression system. Multiple measures such as a high-yield and anti-apoptotic vector qBac-IIIG, the optimal signal peptide, and the optimized codon were used to reach the goal of endotoxin detection with cell supernatant. This method simplifies the steps of protein purification. The sensitivity of the supernatant reached 0.05 EU/mL in a 1-L fermentation system, and 500 000 detecting reactions can be supported per liter of fermentation broth. This study increases the yield and activity of recombinant factor C, simplifies the procedures of protein purification, and reduces the cost, laying a foundation for the promotion and application of recombinant factor C in endotoxin detection.
Animals ; Recombinant Proteins/genetics* ; Horseshoe Crabs/chemistry* ; Baculoviridae/metabolism* ; Endotoxins/analysis* ; Protein C/biosynthesis* ; Genetic Vectors/genetics* ; Arthropod Proteins/genetics* ; Enzyme Precursors ; Serine Endopeptidases

C-Reactive protein(CRP)is an important acute-phase response protein,which is widely used in the assessment of inflammation and cardiovascular disease risk,and acts as a pathogenic factor directly involved in the disease process of certain conditions.Therefore,developing immunosuppressants targeting CRP or investigating its pathogenic mechanisms is of significant importance.Most B-cell epitopes are conformational epitopes,and studying conformational epitopes is typically challenging.To date,no methods have been reported for mapping the conformational epitopes of CRP in solution.In this study,a rapid strategy was developed for studying conformational epitopes by combining hydrogen/deuterium exchange mass spectrometry(HDX-MS)with multiparametric prediction of B-cell epitopes and protein secondary structure analysis.This approach was successfully applied to the binding sites and allosteric targets of the 115 kDa full pentameric CRP and the clinically used monoclonal antibody(mAb)5A8.The results showed that the amino acid residues 84-103,138-146,and 165-173 together form the potential conformational epitopes for mAb 5A8 on CRP,while the amino acid residues 21-32 and 175-178 were identified as potential allosteric targets.The discovery of the mAb 5A8 binding sites and allosteric targets was crucial for improving clinical diagnostic capabilities.Experimental results demonstrated that this workflow allowed rapid conformational epitope mapping of CRP under near-physiological conditions,with advantages such as high speed,high sensitivity,and high throughput.

This study aims to investigate the pharmacological effects and mechanisms of Yougui Yin in treating glucocorticoid-induced osteonecrosis. A rat model of glucocorticoid-associated osteonecrosis of the femoral head(GA-ONFH) was established by intramuscular injection of dexamethasone at 20 mg·kg~(-1) every other day for 8 weeks. Rats were randomly allocated into control, model, and low-and high-dose(1.5 and 3.0 g·kg~(-1), respectively) Yougui Yin groups. After modeling, rats in Yougui Yin groups were administrated with Yougui Yin via gavage, which was followed by femoral specimen collection. Hematoxylin-eosin staining was employed to observe femoral head repair, and immunofluorescence was employed to assess adipogenic differentiation of bone marrow mesenchymal stem cells(BMSCs) within the femoral head. Cell experiments were carried out with dexamethasone(1 μmol·L~(-1))-treated BMSCs to evaluate the effects of Yougui Yin-medicated serum on adipogenic differentiation. Animal experiments demonstrated that compared with the model group, Yougui Yin at both high and low doses significantly improved bone mineral density(BMD), bone volume/total volume(BV/TV) ratio, and trabecular thickness(Tb.Th) in the femoral head. Additionally, Yougui Yin alleviated necrosis-like changes and adipocyte infiltration and significantly reduced the expression level of peroxisome proliferator-activated receptor γ(PPARγ) in the femoral head, thereby suppressing the adipogenic differentiation of BMSCs in GA-ONFH rats. The cell experiments revealed that Yougui Yin-medicated serum markedly inhibited dexamethasone-induced adipogenic differentiation of BMSCs and down-regulated the level of PPARγ. The overexpression of PPARγ attenuated the inhibitory effect of Yougui Yin-medicated serum on the adipogenic differentiation of BMSCs, indicating the critical role of PPARγ in Yougui Yin-mediated suppression of adipogenic differentiation of BMSCs. In conclusion, Yougui Yin exerts therapeutic effects on glucocorticoid-induced osteonecrosis by down-regulating PPARγ expression and inhibiting adipogenic differentiation of BMSCs.
Animals ; Mesenchymal Stem Cells/metabolism* ; PPAR gamma/genetics* ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Glucocorticoids/adverse effects* ; Rats, Sprague-Dawley ; Adipogenesis/drug effects* ; Osteonecrosis/genetics* ; Cell Differentiation/drug effects* ; Bone Marrow Cells/metabolism* ; Femur Head Necrosis/chemically induced* ; Humans

The accurate segmentation of breast ultrasound images is an important precondition for the lesion determination. The existing segmentation approaches embrace massive parameters, sluggish inference speed, and huge memory consumption. To tackle this problem, we propose T ²KD Attention U-Net (dual-Teacher Knowledge Distillation Attention U-Net), a lightweight semantic segmentation method combined double-path joint distillation in breast ultrasound images. Primarily, we designed two teacher models to learn the fine-grained features from each class of images according to different feature representation and semantic information of benign and malignant breast lesions. Then we leveraged the joint distillation to train a lightweight student model. Finally, we constructed a novel weight balance loss to focus on the semantic feature of small objection, solving the unbalance problem of tumor and background. Specifically, the extensive experiments conducted on Dataset BUSI and Dataset B demonstrated that the T ²KD Attention U-Net outperformed various knowledge distillation counterparts. Concretely, the accuracy, recall, precision, Dice, and mIoU of proposed method were 95.26%, 86.23%, 85.09%, 83.59%and 77.78% on Dataset BUSI, respectively. And these performance indexes were 97.95%, 92.80%, 88.33%, 88.40% and 82.42% on Dataset B, respectively. Compared with other models, the performance of this model was significantly improved. Meanwhile, compared with the teacher model, the number, size, and complexity of student model were significantly reduced (2.2×10 ⁶ vs. 106.1×10 ⁶, 8.4 MB vs. 414 MB, 16.59 GFLOPs vs. 205.98 GFLOPs, respectively). Indeedy, the proposed model guarantees the performances while greatly decreasing the amount of computation, which provides a new method for the deployment of clinical medical scenarios.
Humans ; Breast Neoplasms/diagnostic imaging* ; Female ; Ultrasonography, Mammary/methods* ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Neural Networks, Computer ; Breast/diagnostic imaging*