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.

Objective To understand the epidemiological characteristics of Chlamydia trachomatis infection in Hubei province, and to provide scientific basis for prevention and control. Methods The data of Chlamydia trachomatis infection cases reported through the China Information System for Disease Control and Prevention from 2008 to 2022 were collected for epidemiological statistical analysis. Results The incidence of Chlamydia trachomatis infection in Hubei Province showed an increasing trend from 2008 to 2022, with an average annual reported incidence of 2.26/100 000. The top three reported incidence areas were Shiyan (6.04/100 000), Yichang (5.62/100 000) and Shennongjia (3.47/ 100 000). The reported incidence in southeast area was significantly higher than that in other areas (χ²=2869.603 , P < 0.001). The high incidence age group was 20-39 years old, accounting for more than 70%. The reported incidence in females was higher than that in males (χ²=1429.27 , P < 0.001). Housework and unemployment were the most common professions (43.54%). The case reporting institutions were mainly comprehensive hospitals (87.29%). Conclusion To effectively control the infection and transmission of Chlamydia trachomatis, it is necessary to strengthen the health popularization of STD knowledge, intervention and early active screening of high-risk groups.

Objective This study aimed to evaluate the association between the paraoxonase (PON) genes variants and Alzheimer's disease (AD) using systematic review with meta-analysis.Methods Relevant studies were identified by searching English and Chinese databases extensively.Newcastle-Ottawa Scale (NOS) was employed to evaluate the quality of included studies.The odds ratio (OR) was calculated using a random-effects or fixed-effects model.A Q statistic was used to evaluate homogeneity,and fail-safe number,Egger's test and funnel plot were used to assess publication bias.Results A total of 15 studies were included and identified for the current meta-analysis.The NOS scores ranged from 7 to 8,meaning good quality of studies.It was found that the SS genotype of PON2 S311C polymorphism had an significant association with AD in the studied population (OR=0.82,P=0.04).However,there was no significant relationship between other three genetic variants of PON genes and AD.Conclusions Existing evidence indicated that the PON2 S311C polymorphism (SS genotype) was associated with risk of AD in studied population.Future studies with larger sample sizes will be necessary to confirm the present results.