BACKGROUND:Disruption of biological rhythms(circadian rhythms)is a typical problem associated with aging.Maintaining the normal function of biological rhythms may be a promising anti-aging strategy.Expression of nuclear factor erthroid 2-related factor 2(Nrf2)is biologically regulated.The glycogen synthase kinase 3(GSK3)system represents a"regulatory valve"that controls subtle oscillations in Nrf2 levels.Circadian changes in the transcript levels of antioxidant genes can influence the response of organisms to oxidative stress.However,the specific molecular mechanism of GSK3/Nrf2 in regulating organismal aging is still puzzling. OBJECTIVE:To search for the general pattern of GSK3/Nrf2-regulated biological rhythms in organismal aging by reviewing the literature in this field. METHODS:The bibliographic method was used to search,review and screen the relevant literature using the keywords of"glycogen synthase kinase 3,nuclear factor erthroid 2-related factor 2,biorhythms and aging"to lay a theoretical foundation for the analysis of the whole paper.Comparative analysis method,through reading and analyzing the obtained literature,was performed to compare the similarities and differences between the literature,thereby providing reasonable theoretical support for the argument.Further comparative analysis of the literature was conducted to clarify the relationship between the relevant indicators as well as the ideas for analysis throughout the text. RESULTS AND CONCLUSION:GSK3 can indirectly regulate Nrf2 expression through the regulation of rhythm genes.GSK3 and Nrf2 are components of anti-aging programs and are associated with biological rhythms.In addition,GSK3/Nrf2 is involved in several metabolic pathways,including those associated with age-related diseases(type 2 diabetes and cancer)and neurodegenerative diseases.

BACKGROUND:Previous studies found that the proliferative scar-specific long non-coding RNA lncRNA HSFAS is a novel biomarker that can be used in the diagnosis of hypertrophic scar,but how it functions in hypertrophic scar is not clear. OBJECTIVE:To investigate the role and mechanism of lncRNA HSFAS in hypertrophic scar.METHODS:Fresh scar tissue and surrounding normal skin tissue samples from three patients with hypertrophic scar were collected,and tissue immunofluorescence was used to detect the expression of lncRNA HSFAS in frozen sections of two skin tissues. Primary fibroblasts were isolated from proliferative scarred skin tissue and normal skin tissue and cultured by enzyme digestion method. Quantitative real-time PCR was used to detect the mRNA expression of lncRNA HSFAS in cells. The proteins bound to lncRNA HSFAS were detected by RNA pull-down combined mass spectrometry. GO and KEGG were used to analyze the main functions and pathways of lncRNA HSFAS involved in hypertrophic scar progression. The targeted binding of lncRNA HSFAS to proteins was determined by catRAPID and RPISeq website analysis. RESULTS AND CONCLUSION:Compared with normal skin tissue and fibroblasts from normal skin tissue,the expression of lncRNA HSFAS in human hypertrophic scar tissue and primary fibroblasts from hypertrophic scar tissue was significantly increased (P<0.05). There were 510 proteins clearly bound to lncRNA HSFAS by RNA pull-down combined mass spectrometry. The results of GO and KEGG analyses showed that these proteins were mainly involved in RNA splicing and processing,chromosome synthesis and separation,and cell cycle. Among them,the proteins involved in RNA splicing and processing included scaffold attachment factor B2 and DICER1,and the binding fraction with lncRNA HSFAS was higher. The results of bioinformatics analysis showed that lncRNA HSFAS was bound to scaffold attachment factor B2 and DICER1 proteins. To conclude,lncRNA HSFAS may affect gene expression by interacting with scaffold attachment factor B2 and DICER1 proteins to regulate RNA splicing and processing modification,thus promoting the occurrence and development of hypertrophic scar.

Objective:To establish a rapid detection method based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry(MALDI-TOF MS)for drug resistance of Carbapenem-resistant Enterobacteriaceae(CRE),so as to provide basis for enhancing clinically diagnostic effect.Methods:A total of 120 suspected CRE strains that were isolated from the clinical laboratory of Jiading District Central Hospital Affiliated to Shanghai University of Medicine&Health Sciences during October 2023 and September 2024 were collected,and the experimental detection of 44 strains was finally completed.The 44 suspected CRE bacterial strains were all from hospitalized patients.A rapid detection protocol based on the MALDI-TOF MS platform was initially established and improved,and experimental detection was carried out using the fully automatic rapid microbial mass spectrometry detection system(VITEK MS).The results of identification review and antimicrobial susceptibility test(AST)for VitEK-2 Compact strain was used as the reference standard.The screening results and detection efficacy of two kinds of detection methods were compared.Results:In the 44 suspected CRE strains,31 CRE strains were screened out by MALDI-TOF MS detection,and 31 CRE stains were screened out by VITEK-2 Compact recheck detection.In them,one strain of Enterobacter cloacae was confirmed as negativity by the MALDI-TOF MS test,but it was confirmed as CRE by the VITEK-2 Compact test.One strain of Klebsiella pneumoniae was confirmed as positivity by the MALDI-TOF MS test,but it was confirmed as mediator for carbapenem drugs by the VITEK-2 Compact test.The tested results of VITEK-2 Compact was used as standard,the results of four-grid table(2×2 contingency table)statistical method indicated that the sensitivity,specificity,accuracy rate and Youden index(R)of MALDI-TOF MS were respectively 96.7%,92.3%,100%and 89.1%.Conclusion:The rapid detection method based on the MALDI-TOF MS platform for CRE drug resistance has simple operation process and high accuracy rate,which can provide a basis for the application of targeted antibacterial drugs at early stage.

Neurodegenerative disorders(NDDs)are prevalent chronic conditions characterized by progressive synaptic loss and pathological protein alterations.Increasing evidence suggested that mitochondrial quality control(MQC)serves as the key cellular process responsible for clearing misfolded proteins and impaired mitochondria.Herein,we provided a comprehensive analysis of the mechanisms through which MQC mediates the onset and progression of NDDs,emphasizing mitochondrial dynamic stability,the clearance of damaged mitochondria,and the generation of new mitochondria.In addition,traditional Chinese medicines(TCMs)and their active monomers targeting MQC in NDD treatment have been demonstrated.Consequently,we compiled the TCMs that show great potential in the treatment of NDDs by targeting MQC,aiming to offer novel insights and a scientific foundation for the use of MQC stabilizers in NDD prevention and treatment.

The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which limit its widespread application in practice.In this study,we developed a work-flow,named Evolutionary-Nanobody(EvoNB),to predict key mutation sites of nanobodies by combining protein language models(PLMs)and molecular dynamic(MD)simulations.By fine-tuning the ESM2 model on a large-scale nanobody dataset,the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced.The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies.Additionally,we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations.MD simulations analyzed the energy changes caused by these mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target,further validating the potential of this workflow for designing and optimizing nanobody mutations.Additionally,sequence-based predictions are generally less dependent on structural absence,allowing them to be more easily integrated with tools for structural predictions,such as AlphaFold 3.Through mutation prediction and systematic analysis of key sites,we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes.The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

Background: Normalized creatinine-to-cystatin C ratio (NCCR) was reported to approximate relative skeletal muscle mass and diabetes risk. However, the association between NCCR and cardiometabolic multimorbidity (CMM) remains elusive. This study aimed to explore their relationship in a large-scale prospective cohort. Methods: This study included 5,849 middle-age and older participants from the China Health and Retirement Longitudinal Study (CHARLS) enrolled between 2011 and 2012. The baseline NCCR was determined as creatinine (mg/dL)/cystatin C (mg/L)×10/body mass (kg). CMM was defined as the simultaneous occurrence of two or more of the following conditions: heart disease, stroke, and type 2 diabetes mellitus. Logistic regression analysis and Cox regression analysis were employed to estimate the relationship between NCCR and CMM. The joint effect of body mass index and NCCR on the risk of CMM were further analyzed. Results: During a median 4-year follow-up, 227 (3.9%) participants developed CMM. The risk of CMM was significantly decreased with per standard deviation increase of NCCR (odds ratio, 0.72; 95% confidence interval, 0.62 to 0.85) after adjustment for confounders (P<0.001). Further sex-specific analysis found significant negative associations between NCCR and CMM in female either without or with one CMM component at baseline, which was attenuated in males but remained statistically significant among those with one basal CMM component. Notably, non-obese individuals with high NCCR levels had the lowest CMM risk compared to obese counterparts with low NCCR levels in both genders. Conclusion High NCCR was independently associated with reduced risk of CMM in middle-aged and older adults in China, particularly females.

Neurodegenerative disorders (NDDs) are prevalent chronic conditions characterized by progressive synaptic loss and pathological protein alterations. Increasing evidence suggested that mitochondrial quality control (MQC) serves as the key cellular process responsible for clearing misfolded proteins and impaired mitochondria. Herein, we provided a comprehensive analysis of the mechanisms through which MQC mediates the onset and progression of NDDs, emphasizing mitochondrial dynamic stability, the clearance of damaged mitochondria, and the generation of new mitochondria. In addition, traditional Chinese medicines (TCMs) and their active monomers targeting MQC in NDD treatment have been demonstrated. Consequently, we compiled the TCMs that show great potential in the treatment of NDDs by targeting MQC, aiming to offer novel insights and a scientific foundation for the use of MQC stabilizers in NDD prevention and treatment.

The identification and optimization of mutations in nanobodies are crucial for enhancing their therapeutic potential in disease prevention and control. However, this process is often complex and time-consuming, which limit its widespread application in practice. In this study, we developed a workflow, named Evolutionary-Nanobody (EvoNB), to predict key mutation sites of nanobodies by combining protein language models (PLMs) and molecular dynamic (MD) simulations. By fine-tuning the ESM2 model on a large-scale nanobody dataset, the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced. The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies. Additionally, we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations. MD simulations analyzed the energy changes caused by these mutations to predict their impact on binding affinity to the targets. The results showed that multiple mutations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target, further validating the potential of this workflow for designing and optimizing nanobody mutations. Additionally, sequence-based predictions are generally less dependent on structural absence, allowing them to be more easily integrated with tools for structural predictions, such as AlphaFold 3. Through mutation prediction and systematic analysis of key sites, we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes. The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.