OBJECTIVE: This study investigates the efficacy and mechanisms of Qingjie Fuzheng Granules (QFG) in inhibiting colitis-associated colorectal cancer (CAC) development via RNA sequencing (RNA-seq) and 16S ribosomal RNA (rRNA) correlation analysis. METHODS: CAC was induced in BALB/c mice using azoxymethane (AOM) and dextran sulfate sodium (DSS), and QFG was administered orally to the treatment group. The effects of QFG on CAC were evaluated using disease index, histology, and serum T-cell ratios. RNA-seq and 16S rRNA analysis assessed the transcriptome and microbiome change. Key pharmacodynamic pathways were identified by integrating these data and confirmed via Western blotting and immunofluorescence. The link between microbiota and CAC-related markers was explored using linear discriminant analysis effect size and Spearman correlation analysis. RESULTS: Long-term treatment with QFG prevented AOM/DSS-induced CAC formation, reduced levels of interleukin (IL)-1β, tumor necrosis factor-alpha (TNF-α), IL-6, and interferon γ (IFN-γ), and increased CD3⁺ and CD4⁺/CD8⁺ T cells ratio, without causing hepatic or renal toxicity. A 16S rRNA analysis revealed that QFG rebalanced the Firmicutes/Bacteroidetes ratio and mitigated AOM/DSS-induced microbiota disturbances. Transcriptomics and Western blotting analysis identified the nucleotide-binding oligomerization domain-containing protein 2 (NOD2)/nuclear factor kappa-B (NF-κB) pathway as key for QFG's treatment against CAC. Furthermore, QFG decreased the abundance of Bacilli, Bacillales, Staphylococcaceae, Staphylococcus, Lactobacillales, Aerococcus, Alloprevotella, and Akkermansia, while increasing Clostridiales, Lachnospiraceae, Lachnospiraceae_NK4A136_group, Ruminococcaceae, and Muribaculaceae, which were highly correlated with CAC-related markers or NOD2/NF-κB pathway. CONCLUSION By mapping the relationships between CAC, immune responses, microbiota, and key pathways, this study clarifies the mechanism of QFG in inhibiting CAC, highlighting its potential for clinical use as preventive therapy.

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 develop and validate a model to predict the risk of radiation-induced lung injury (RILI) and assess its clinical feasibility. Methods Clinical data from 125 patients with non-small cell lung cancer (NSCLC) were included in the study. The patients were divided into training group (88 cases) and validation group (38 cases). Key predictive factors were identified using univariate and multivariate logistic regression analyses combined with least absolute shrinkage and selection operator (LASSO) regression. A predictive model was constructed and evaluated using a nomogram, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Results The key variables identified by the model were tumor volume (P = 0.017), Eastern Cooperative Oncology Group performance status score (P = 0.035), 95% of the minimum dose to the target volume (P = 0.028), percentage of bilateral lung volume receiving 20 Gy of radiation (P < 0.001), and neutrophil-to-lymphocyte ratio (P = 0.021). The ROC curve showed that the areas under the curve (AUC) for the model in the training and validation groups were 0.987 and 0.992, respectively, indicating good predictive ability. The calibration curve and decision curve further confirmed the accuracy and clinical practicability of the model. Conclusion The predictive model proposed in this study can accurately assess the risk of developing RILI in patients with NSCLC who have undergone radiotherapy, demonstrating its potential value in clinical practice.

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.

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.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

ObjectiveTo observe the effect of Shenshu Fujian decoction on platelet-derived growth factor （PDGF）/naked cuticle homolog 2 （NKD2） /Wnt signaling pathway in rats with chronic renal failure （CRF）. MethodsSixty male SD rats were randomly divided into normal group， model group， Niaoduqing group （5 g·kg^-1）， low-dose Shenshu Fujian decoction group （5.5 g·kg^-1）， medium-dose Shenshu Fujian decoction group （11 g·kg^-1）， and high-dose Shenshu Fujian decoction group （22 g·kg^-1）， with 10 rats in each group. A CRF rat model was established by feeding a 0.5% adenine diet for 21 days. After successful modeling， intragastric administration was given once daily for 28 consecutive days. After treatment， the renal morphology of rats was observed. Serum creatinine （SCr） and blood urea nitrogen （BUN） levels were detected. Hematoxylin-eosin （HE） staining and Masson staining were used to detect renal histopathological changes， and collagen volume fraction （CVF） was calculated. Serum levels of inflammatory markers interleukin （IL）-1β and IL-6 were measured using enzyme-linked immunosorbent assay （ELISA）. The expressions of fibronectin 1 （FN1）， type Ⅰ collagen （ColⅠ）， α-smooth muscle actin （α-SMA）， platelet-derived growth factor receptor-β （PDGFR-β）， NKD2， dishevelled protein 2 （DVL2） and β-catenin in renal tissue were detected by immunohistochemistry and Western blot. ResultsCompared with the normal group， the model group showed significant renal pathological changes， a markedly increased kidney weight/body weight ratio （P<0.01）， significantly elevated CVF （P<0.01）， and notably increased serum levels of SCr， BUN， IL-1β， and IL-6 （P<0.01）. Expression levels of FN1， ColⅠ， α-SMA， PDGFR-β， NKD2， DVL2， and β-catenin in renal tissue were also significantly increased （P<0.01）. Compared with the model group， all treatment groups showed significantly decreased kidney weight/body weight ratios and CVF （P<0.01）， as well as markedly decreased serum SCr， BUN， IL-1β， and IL-6 levels. Protein expression levels of FN1， ColⅠ， α-SMA， PDGFR-β， NKD2， DVL2， and β-catenin in renal tissue were decreased， with more pronounced effects observed in the Niaoduqing， medium-dose， and high-dose Shenshu Fujian decoction groups （P<0.05， P<0.01）. ConclusionShenshu Fujian decoction improves renal function， reduces inflammation， and reverses renal fibrosis in CRF rats， possibly by downregulating the expression of PDGF/NKD2/Wnt signaling pathway-related proteins.

Objective: To investigate the protective effects and underlying mechanisms of sodium pyruvate (SP) on RBC storage lesions using an oxidative damage model. Methods: Six units of leukocyte-depleted suspended RBCs (discarded for non-infectious reasons within three days post-collection) were randomly assigned to four groups: negative control (NS), positive control (PS), experimental group 1 (SP1), and experimental group 2 (SP2). Oxidative stress was induced in the PS group by the addition of hydrogen peroxide (H O ), while SP1 and SP2 received SP supplementation at different concentrations (25 mM and 50 mM, respectively) in the presence of H O . After 1 hour of incubation, RBC morphology was assessed microscopically, and biochemical indicators including glutathione (GSH), malondialdehyde (MDA), methemoglobin (MetHb), adenosine triphosphate (ATP), and Na /K -ATPase activity were measured. Results: RBCs in the PS group exhibited pronounced morphological damage, including cell shrinkage and echinocyte formation, whereas both SP-treated groups showed significantly reduced structural injury. SP treatment led to elevated GSH levels and decreased concentrations of MDA and MetHb, suggesting attenuation of oxidative stress. Additionally, SP enhanced intracellular ATP levels and Na /K -ATPase activity, thereby contributing to membrane stability. Notably, the SP2 group (50 mM) demonstrated superior protective effects compared to SP1 (25 mM). Conclusion: Sodium pyruvate effectively attenuates oxidative storage lesions in RBCs, primarily through its antioxidant properties, energy metabolism supporting ability, and celluar membrane stabilizing function. These findings suggest SP as a promising additive for enhancing the quality and safety of stored RBCs.

Objective To establish a reliable prediction model for radiation pneumonitis(RP)based on multi-regional radiomics analysis of localizable CT images.Methods A retrospective analysis was conducted on 185 patients who received radiotherapy from January 2021 to June 2023 in the Department of Radiotherapy,Xuzhou Cancer Hospital.Patients were classified as having RP or not based on imaging combined with clinical diagnosis.Three regions of interest(ROI)were defined in the localizable CT images:Lung,Lung-PTV and PTV,and their radiomics features were extracted.After feature screening using methods such as Mann-Whitney Utest,recursive feature elimination,and Lasso,a prediction model was established using support vector machine classification algorithm.The model performance was validated using 6 evaluation metrics:the area under the receiver operating characteristic curve(AUC),accuracy,specificity,sensitivity,positive predictive value,and negative predictive value.Results The prediction model consisted of 7 radiomics features.The clinical model of target-to-lung ratio,PTV model,Lung model,and Lung-PTV model achieved AUC values of 0.535,0.801,0.672,and 0.706 in the test set,respectively.The AUC value and accuracy of PTV model reached 0.843 and 0.775 in the training set,while 0.801 and 0.750 in the test set.PTV model was superior to Lung model,Lung-PTV model,and clinical model in predictive performance.The AUC values of the combined PTV+(Lung-PTV)model in the training and test sets were 0.867 and 0.806,respectively,higher than those of PTV model and Lung-PTV model.Conclusion The predictive ability of the prediction models constructed from radiomics features in different ROI for symptomatic RP varies.The radiomics prediction model using PTV as ROI exhibits superior predictive performance,and the combined multi-regional radiomics model can further improve the predictive ability for RP.