Circadian rhythm is an endogenous biological clock mechanism that enables organisms to adapt to the earth’s alternation of day and night. It plays a fundamental role in regulating physiological functions and behavioral patterns, such as sleep, feeding, hormone levels and body temperature. By aligning these processes with environmental changes, circadian rhythm plays a pivotal role in maintaining homeostasis and promoting optimal health. However, modern lifestyles, characterized by irregular work schedules and pervasive exposure to artificial light, have disrupted these rhythms for many individuals. Such disruptions have been linked to a variety of health problems, including sleep disorders, metabolic syndromes, cardiovascular diseases, and immune dysfunction, underscoring the critical role of circadian rhythm in human health. Among the numerous systems influenced by circadian rhythm, the skin—a multifunctional organ and the largest by surface area—is particularly noteworthy. As the body’s first line of defense against environmental insults such as UV radiation, pollutants, and pathogens, the skin is highly affected by changes in circadian rhythm. Circadian rhythm regulates multiple skin-related processes, including cyclic changes in cell proliferation, differentiation, and apoptosis, as well as DNA repair mechanisms and antioxidant defenses. For instance, studies have shown that keratinocyte proliferation peaks during the night, coinciding with reduced environmental stress, while DNA repair mechanisms are most active during the day to counteract UV-induced damage. This temporal coordination highlights the critical role of circadian rhythms in preserving skin integrity and function. Beyond maintaining homeostasis, circadian rhythm is also pivotal in the skin’s repair and regeneration processes following injury. Skin regeneration is a complex, multi-stage process involving hemostasis, inflammation, proliferation, and remodeling, all of which are influenced by circadian regulation. Key cellular activities, such as fibroblast migration, keratinocyte activation, and extracellular matrix remodeling, are modulated by the circadian clock, ensuring that repair processes occur with optimal efficiency. Additionally, circadian rhythm regulates the secretion of cytokines and growth factors, which are critical for coordinating cellular communication and orchestrating tissue regeneration. Disruptions to these rhythms can impair the repair process, leading to delayed wound healing, increased scarring, or chronic inflammatory conditions. The aim of this review is to synthesize recent information on the interactions between circadian rhythms and skin physiology, with a particular focus on skin tissue repair and regeneration. Molecular mechanisms of circadian regulation in skin cells, including the role of core clock genes such as Clock, Bmal1, Per and Cry. These genes control the expression of downstream effectors involved in cell cycle regulation, DNA repair, oxidative stress response and inflammatory pathways. By understanding how these mechanisms operate in healthy and diseased states, we can discover new insights into the temporal dynamics of skin regeneration. In addition, by exploring the therapeutic potential of circadian biology in enhancing skin repair and regeneration, strategies such as topical medications that can be applied in a time-limited manner, phototherapy that is synchronized with circadian rhythms, and pharmacological modulation of clock genes are expected to optimize clinical outcomes. Interventions based on the skin’s natural rhythms can provide a personalized and efficient approach to promote skin regeneration and recovery. This review not only introduces the important role of circadian rhythms in skin biology, but also provides a new idea for future innovative therapies and regenerative medicine based on circadian rhythms.

Process analytical technology(PAT) is a key means for digital transformation and upgrading of the traditional Chinese medicine(TCM) manufacturing process, serving as an important guarantee for consistent and controllable TCM product quality. Near-infrared(NIR) spectroscopy has become the core technology for measuring the TCM manufacturing process. By incorporating NIR spectroscopy into PAT and starting from the construction of a smart platform for the TCM manufacturing process, this paper systematically described the development history and innovative application of the combination of NIR spectroscopy with chemometrics in measuring the TCM manufacturing process by the research team over the past two decades. Additionally, it explored the application of a validation method based on accuracy profile(AP) in the practice of NIR spectroscopy. Furthermore, the software development progress driven by NIR spectroscopy supported by modeling technology was analyzed, and the prospect of integrating NIR spectroscopy in smart factory control platforms was exemplified with the construction practices of related platforms. By integrating with the smart platform, NIR spectroscopy could improve production efficiency and guarantee product quality. Finally, the prospect of the smart platform application in measuring the TCM manufacturing process was projected. It is believed that the software development for NIR spectroscopy and the smart manufacturing platform will provide strong technical support for TCM digitalization and industrialization.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/analysis* ; Software ; Medicine, Chinese Traditional ; Quality Control

In recent years, there have been frequent adverse reactions/events associated with traditional Chinese medicine(TCM), especially liver injury related to traditional non-toxic TCM, which requires adequate attention. Liver injury related to traditional non-toxic TCM is characterized by its sporadic and insidious nature and is influenced by various factors, making its detection and identification challenging. There is an urgent need to develop a strategy and method for early detection and recognition of traditional non-toxic TCM-related liver injury. This study was based on national adverse drug reaction monitoring center big data, integrating methodologies such as reporting odds ratio(ROR), network toxicology, and computational chemistry, so as to systematically research the risk signal identification and evaluation methods for TCM-related liver injury. The optimized ROR method was used to discover potential TCM with a risk of liver injury, and network toxicology and computational chemistry were used to identify potentially high-risk TCM. Additionally, typical clinical cases were analyzed for confirmation. An integrated strategy of "discovery via big data, identification via dry/wet method, confirmation via typical cases, and precise risk prevention and control" was developed to identify the risk of TCM-related liver injury. Corydalis Rhizoma was identified as a TCM with high risk, and its toxicity-related substances and potential toxicity mechanisms were analyzed. The results revealed that liver injury is associated with components such as tetrahydropalmatine and tetrahydroberberine, with potential mechanisms related to immune-inflammatory pathways such as the tumor necrosis factor signaling pathway, interleukin-17 signaling pathway, and Th17 cell differentiation. This paper innovatively integrated real-world evidence and computational toxicology methods, offering insights and technical support for establishing a risk discovery and identification strategy for TCM-related liver injury based on real-world big data, providing innovative ideas and strategies for guiding the safe and rational use of medication in clinical practices.
Corydalis/adverse effects* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Chemical and Drug Induced Liver Injury/etiology* ; Medicine, Chinese Traditional/adverse effects* ; Rhizome/adverse effects* ; Male ; Female

To investigate the effects and mechanisms of the water extract from Sorbus tianschanica(STE) on asthmatic airway inflammation, the mice were randomly divided into six groups, including a control group, a model group, a positive drug dexamethasone group(2 mg·kg~(-1)), a low-dose STE group(1 g·kg~(-1)), a medium-dose STE group(2 g·kg~(-1)), and a high-dose STE group(4 g·kg~(-1)). Except for the control group, all groups were subjected to ovalbumin induction to establish an asthma mouse model. The anti-inflammatory effects of STE were evaluated by examining pathological changes in lung tissue and measuring the levels of interleukin(IL)-4 and IL-5 in bronchoalveolar lavage fluid(BALF). Transcriptomic and proteomic methods were further employed to analyze differentially expressed genes and proteins, as well as their associated signaling pathways in lung tissue. Subsequently, the expression changes of key genes were verified by reverse transcription-quantitative polymerase chain reaction(RT-qPCR), and immunohistochemistry and Western blot methods were used to explore the regulatory mechanisms of STE in the pathogenesis of asthma in mice. Molecular docking was performed by using AutoDock Vina software to evaluate the binding affinity of the main active components in STE with the target proteins, including phosphatidylinositol-3-kinase catalytic subunit α(PIK3CA), Toll-like receptor 4(TLR4), protein kinase B1(Akt1), and matrix metallopeptidase 9(MMP9). The results showed significant inflammatory cell infiltration and fibrous tissue proliferation in the lung tissue of mice in the model group. However, these pathological changes were markedly reduced following STE intervention. Compared with those of the control group, the expression levels of IL-4 and IL-5 in the BALF of the model group were significantly increased but notably decreased following STE intervention. Transcriptomic and proteomic analyses identified key genes and proteins associated with allergic asthma, including tumor necrosis factor(TNF), IL-6, TLR4, PIK3CA, and MMP9. RT-qPCR validation revealed that high-dose STE intervention significantly downregulated the expressions of PIK3CA, IL-6, Akt1, MMP9, IL-13, nuclear factor-kappa B(NF-κB), TNF, CXC motif chemokine ligand 1(CXCL1), and TLR4 mRNAs and significantly upregulated the expression of signal transducer and activator of transcription 1(STAT1) mRNA. Western blot and immunohistochemical analyses confirmed that STE significantly downregulated the expressions of MMP9, TLR4, PIK3CA, and phosphorylated protein kinase B(p-Akt) in lung tissue of asthmatic mice. Moreover, molecular docking demonstrated that kaempferol-3,7-diglucoside, isoquercitrin, quercetin-3-gentiobioside, and hyperoside in STE exhibited stable binding affinities with PIK3CA, TLR4, Akt1, and MMP9, suggesting that the active components may exert anti-inflammatory effects by targeting and modulating asthma-related signaling pathways. In summary, STE exerts anti-asthmatic effects by inhibiting the expressions of PIK3CA, MMP9, p-Akt, and TLR4 and regulating the TLR4/PI3K/Akt/MMP9 signaling pathway.
Animals ; Asthma/metabolism* ; Toll-Like Receptor 4/metabolism* ; Signal Transduction/drug effects* ; Mice ; Phosphatidylinositol 3-Kinases/metabolism* ; Proto-Oncogene Proteins c-akt/metabolism* ; Matrix Metalloproteinase 9/metabolism* ; Mice, Inbred BALB C ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Humans ; Lung/immunology* ; Male

Fangcang shelter hospitals are modular, rapidly deployable facilities that play a vital role in pandemic response by providing centralized isolation and basic medical care for large patient populations. Artificial intelligence (AI) has the potential to transform Fangcang shelter hospitals into intelligent, responsive systems that are capable of significantly improving emergency preparedness, operational efficiency, and patient outcomes. Key application areas include site selection and design optimization, clinical decision support, AI-assisted clinical documentation and patient engagement, intelligent robotics, and operational management. However, realizing AI's full potential requires overcoming several challenges, including limited data accessibility, privacy and governance concerns, inadequate algorithmic adaptability in dynamic emergency settings, insufficient transparency and accountability in AI-driven decisions, fragmented system architectures due to proprietary formats, high costs disproportionate to the temporary nature of Fangcang shelter hospitals, and hardware reliability in austere environments. Addressing these challenges demands standardized data-sharing frameworks, development of explainable and robust AI algorithms, clear ethical and legal oversight, interoperable modular system designs, and active collaboration among multidisciplinary stakeholders.
Artificial Intelligence ; Humans ; Emergency Shelter ; China ; Hospitals ; COVID-19

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

Inflammatory bowel disease (IBD) is an autoimmune disorder involving complex immune regulation, where balancing localized and systemic immunosuppression is a key challenge. This study aimed to enhance the therapeutic efficacy by engineering the probiotic Escherichia coli Nissle 1917 (EcN). We removed endogenous plasmids pMUT1 and pMUT2 from wild-type EcN and expressed the mPD-L1 (19‒238 aa)-mFc fusion protein on the bacterial surface using a cytolysin A (ClyA) fragment. This modification stabilized mPD-L1 (19‒238 aa) protein expression and promoted its recruitment to outer membrane vesicles (OMVs). The engineered strain, EcNΔ_pMUT1/2-ClyA-mPD-L1-mFc (EcN-ePD-L1-mFc), features conditional ePD-L1-mFc expression under the araBAD promoter, enhancing gut-targeted release and reducing systemic side effects. This strain improved treatment targeting and efficiency by enabling direct ePD-L1-mFc interaction with immune cells at inflammation sites. OMVs from this strain induced Treg proliferation, inhibited effector T cell proliferation in vitro, and significantly improved intestinal inflammation and colonic epithelial barrier repair in vivo. Additionally, the bacterium restored intestinal microbiota balance, increasing Lactobacillaceae and reducing Bacteroides. This study highlights the engineered bacterium's potential for targeted intestinal immune modulation and offers a novel local IBD treatment approach with promising clinical prospects.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To investigate the neuroprotective effect of rhein(RHE)on ischemic mice and its potential mechanism of reducing inflammatory response and neuronal apoptosis by inhibiting Notch/nuclear factor(NF)-κB signaling pathway.Methods The classical middle cerebral artery occlusion(MCAO)method was used to construct ischemic stroke mouse models.The mice were randomly divided into 5 groups including the sham operation group(sham),the model group(MCAO),the MCAO+edaravone group(Eda),the MCAO+RHE-treated group(RHE),and the MCAO+RHE+Notch activitor Jagged 1 group(RHE+J).Each group has 18 mice.The Bederson scoring system,balance beam walking test and accelerated rotating rod test were used to assess the neurological function and locomotor ability of mice in each group.2,3,5-triphenyltetrazolium chloride(TTC)staining,hematoxylin eosin staining,and TUNEL method were used to assess cerebral infarction,hippocampal morphological damage,and neuronal apoptosis.ELISA was used to analysis the levels of interleukin(IL)-6 and tumor necrosis factor α(TNF-α)in hippocampal tissue.Western blotting was used to analysis caspase-3,Notch 1,Hes1,and NF-κB p65 protein expression.Results Compared with the sham group,Bederson score,balance beam score,cerebral infarct volume,IL-6 and TNF-α levels,the proportion of TUNEL-positively stained cells,caspase-3,Notch1,Hes1,and p-NF-κB p65 protein expression were significantly increased in the MCAO group,whereas the latency to fall decreased significantly(P＜0.05).Compared with the MCAO group,Bederson score,balance beam score,cerebral infarct volume,IL-6 and TNF-α levels,proportion of TUNEL-positively stained cells,caspase-3,Notch1,Hes1,and p-NF-κB p65 protein expression were significantly lower in both Eda and RHE groups,whereas the latency to fall increased significantly(P＜0.05).Compared with the RHE group,Bederson score,balance beam score,cerebral infarction volume,IL-6 and TNF-α levels,the proportion of TUNEL-positively stained cells,caspase-3,Notch1,Hes1,and p-NF-κB p65 protein expression increased significantly in the RHE+J group,whereas the latency to fall decreased significantly(P＜0.05).Conclusion Rhein can significantly improve nerve function in ischemic mice by inhibiting Notch/NF-κB signaling pathway activation,suggesting that rhein has potential clinical application value.

ObjectiveTo identify the active components in Maimendong decoction (MMDD) against pulmonary fibrosis (PF) and validate their molecular effects in vitro, while focusing on the role of methylophiopogonanone B in regulating fibrosis.MethodsData on MMDD components and targets were gathered from databases including BATMAN-TCM and PubMed, whereas the PF gene data were sourced from GeneCards, OMIM, and TTD. Shared targets were determined using the STRING database, and molecular docking was used to analyze the essential molecules associated with fibrosis. To simulate PF conditions, human embryonic lung fibroblasts (HPF) and A549 cells were exposed to transforming growth factor-β1 (TGF-β1). Various assays were used to determine the effects of MMDD and methylophiopogonanone B on signaling pathways, apoptosis, and epithelial–mesenchymal transition.ResultsWe identified 11 active components from MMDD extracts that targeted 511 shared proteins associated with PF, revealing 10 key targets in network analysis. Gene ontology analysis indicated that processes and pathways such as apoptosis regulation and PI3K/Akt signaling were involved. In vitro experiments revealed that MMDD downregulated the expression of α-smooth muscle actin (α-SMA), collagen type I (COL-I), and collagen type III and regulated Bcl-2/Bax signaling pathways to promote apoptosis. The flow cytometry apoptosis assay revealed that MMDD promoted the TGF-β1-induced apoptosis of myofibroblasts. The primary active ingredient in MMDD, methylophiopogonanone B, reduced α-SMA, COL-I, and PI3K/Akt/mTOR-related protein levels in TGF-β1-treated HPF cells, decreased Bcl-2 and cleaved caspase 3, and increased Bax. Moreover, methylophiopogonanone B increased E-cadherin levels and reduced α-SMA, fibronectin, N-cadherin, vimentin, and snail in TGF-β1-treated A549 cells.ConclusionMethylophiopogonanone B demonstrated the potential to treat PF by inducing myofibroblast apoptosis and inhibiting EMT. However, despite encouraging initial results, further clinical research is warranted to verify the safety and efficacy of methylophiopogonanone B in the management of PF