Digital and intelligent technologies serve as the core engine driving the inheritance of the essence and the innovation while upholding the fundamentals of traditional Chinese medicine（TCM）. Currently， the digital and intelligent transformation of TCM has undergone four developmental stages， exhibiting inherent characteristics such as long-term inevitability， objective standardization， and ecological evolution. By introducing quantitative metrics， digital and intelligent technologies have achieved breakthroughs in TCM knowledge inheritance and innovation， clinical diagnosis and treatment， and herbal medicine supply. The practical applicability of methodological innovations has been empirically validated， though significant disparities exist in technological adaptability and application depth across different fields. Overall， the digital and intelligent transformation of TCM remains in its nascent stage， grappling with multiple structural challenges：weak data foundations， inadequate technological adaptability， incomplete institutional frameworks， shortages of multidisciplinary talent， lagging policies and regulations， and urban-rural digital divide. In order to foster sustainable development and modernization of TCM， this paper establishes a six-dimensional collaborative governance framework of encompassing data， technology， organization， institutions， environment and ethics， which is rooted in data governance and digital governance theories. Future efforts should center on standardization， integration， and ecosystem development to build a data and technology foundation. Focus should be placed on deepening innovation and application of key TCM-specific technologies， while simultaneously strengthening interdisciplinary talent cultivation， improving institutional mechanisms and policy frameworks， and increasing support for rural areas. By adopting a people-centered and technology-empowered approach， we can overcome developmental constraints and unleash the powerful driving force of digital and intelligent technologies for the inheritance of TCM.

Objective: To evaluate the diagnostic potential of fluid suppression (FS) techniques combined with amide proton transferweighted imaging (APTw) for assessment of isocitrate dehydrogenase (IDH) mutation status, glioma subtypes, and tumor proliferation. Materials and Methods: This retrospective study included 117 patients with adult-type diffuse gliomas. Conventional APTw, FSAPTw, and spillover-corrected FS-APTw (SCFS-APTw) metrics were calculated from 3T MRI data in tumor parenchyma, necrotic or cystic regions, and contralateral normal-appearing white matter. APTw signals were compared across the three techniques within each region, between IDH-mutant and IDH-wildtype gliomas, and among astrocytoma, oligodendroglioma, and glioblastoma subtypes. Diagnostic performance for distinguishing IDH mutation status and glioma subtypes was assessed using receiver operating characteristic (ROC) analysis. Correlations between APTw metrics and Ki-67 expression were also analyzed. Results: Both FS-APTw and SCFS-APTw significantly reduced signal intensity in tumor parenchyma and necrotic or cystic regions, with SCFS-APTw demonstrating a stronger suppression effect. IDH-wildtype gliomas showed significantly higher APTw metrics than IDH-mutant gliomas (all P < 0.001). Glioblastomas exhibited significantly higher metrics than oligodendrogliomas (all corrected P ≤ 0.015) and astrocytomas (all corrected P < 0.001). SCFS-APTw achieved the highest area under the ROC curve (AUC) of 0.846 for identification of IDH mutation status. For differentiation between astrocytomas and glioblastomas, the 90th percentile of APTw yielded the highest AUC (0.860), followed by SCFS-APTw (0.849). For discrimination between oligodendrogliomas and glioblastomas, the highest AUC (0.832) was obtained using the 90th percentile of SCFS-APTw. None of these metrics successfully differentiated oligodendrogliomas from astrocytomas. SCFS-APTw demonstrated the strongest correlation with Ki-67 expression (r = 0.451). Conclusion FS techniques effectively reduce elevated APTw signals originating from fluid compartments. Their combination with APTw imaging enables evaluation of IDH mutation status, glioma subtypes, and tumor proliferative activity in adulttype diffuse gliomas.

ObjectiveHyperlipidemia （HLP） is a chronic metabolic disease characterized by abnormal lipid metabolism and is one of the important risk factors for the occurrence of cardiovascular and cerebrovascular diseases. Its incidence has increased year by year， showing a trend toward younger onset. The overall prevalence of HLP among adults in China is as high as 40.40%. Although existing animal models provide important tools for research on the mechanisms of HLP， they generally show insufficient clinical concordance and lack the combined disease-syndrome characteristics of traditional Chinese medicine （TCM） and Western medicine. This article systematically reviews the research progress of HLP animal models， integrates the clinicopathological characteristics of TCM and Western medicine， and proposes new model construction strategies， aiming to provide an experimental basis for accurately analyzing the pathogenesis of HLP and developing integrated TCM-Western medicine therapies. MethodsBased on literature included in PubMed， CNKI， and Wanfang databases over the past 30 years， the construction methods and evaluation systems of HLP animal models were systematically retrieved and summarized. The concordance of existing animal models was calculated according to the new animal model evaluation method proposed by Professor MIAO Mingsan. ResultsAmong existing Western medicine modeling approaches， genetically modified models showed the highest concordance （72%）， followed by dietary induction （66%） and chemical drug induction （60%）. The dietary induction method is the most widely used in practice because of its simple operation and mature technology. Existing TCM modeling approaches are classified into three types， i.e.， spleen deficiency type， phlegm syndrome type， and liver-kidney yin deficiency type. Among them， the phlegm syndrome type shows a high degree of concordance. However， all three types have the problem of non-objective evaluation indicators and insufficient application of tongue and pulse assessment. ConclusionThe construction of existing HLP disease-syndrome combined animal models is still mainly based on Western medicine modeling methods and lacks adequate reflection of TCM syndromes. In the future， HLP animal models that conform to the clinical disease-syndrome characteristics of both TCM and Western medicine may be constructed through multifactor composite modeling strategies， intelligent tongue image analysis via robot learning， objective pulse detection， the establishment of objective evaluation systems for TCM syndromes through big data computing， and the application of cutting-edge technologies.

Alzheimer's disease (AD) is a neurodegenerative disease with clinical hallmarks of progressive cognitive impairment. Synergistic effects of the Aβ-Tau cascade reaction are tightly implicated in AD pathology, and microglial NLRP3 inflammasome activation drives neuronal tauopathy. However, the underlying mechanism of how Aβ mediates NLRP3 inflammasome remains unclear. Herein, we determined that oligomeric Aβ (o-Aβ) bound to microglial Kv2.1 and promoted Kv2.1-dependent potassium efflux to activate NLRP3 inflammasome resulting in neuronal tauopathy by using Kv2.1 inhibitor drofenine (Dfe) as a probe. The underlying mechanism has been intensively investigated by assays with Kv2.1 knockdown in vitro (si-Kv2.1) and in vivo (AAV-ePHP-si-Kv2.1). Dfe deprived o-Aβ of its capability to promote microglial NLRP3 inflammasome activation and neuronal Tau hyperphosphorylation by inhibiting the Kv2.1/JNK/NF-κB pathway while improving the cognitive impairment of 5×FAD-AD model mice. Our results have highly addressed that the Kv2.1 channel is required for o-Aβ-driven microglial NLRP3 inflammasome activation and neuronal tauopathy in AD model mice and highlighted that Dfe as a Kv2.1 inhibitor shows potential in the treatment of AD.

Obesity usually exacerbates the immunosuppressive tumor microenvironment (ITME), hindering CD8⁺ T cell infiltration and function, which further represents a significant barrier to the efficacy of immunotherapy. Herein, a multifunctional liposomal system (CR-Lip) for encapsulating celastrol (CEL) was utilized to remodel obesity-related ITME and improve cancer immunotherapy, wherein Ginsenoside Rg3 (Rg3) was detected interspersed in the phospholipid bilayer and its glycosyl exposed on the surface of the liposome. CR-Lip had a relatively uniform size (116.5 nm), facilitating favorable tumor tissue accumulation through the interaction between Rg3 and glucose transporter 1 overexpressed in obese tumor cells. Upon reaching the tumor region, CR-Lip was found to induce the immunogenic cell death (ICD) of HFD tumor cells. Notably, the level of PHD3 in HFD tumor cells was effectively boosted by CR-Lip to effectively block metabolic reprogramming and increase the availability of major free fatty acids fuel sources. In vivo, experiments studies revealed that the easy-obtained nano platform stimulated enhanced the production of various cytokines in tumor tissues, DC maturation, CD8⁺ T-cell infiltration, and synergistic anticancer therapeutic potency with aPD-1 (tumor inhibition rate = 82.1%) towards obesity-related melanoma. Consequently, this study presented an efficacious approach to tumor immunotherapy in obese mice by encompassing tumor eradication, inducing ICD, and reprogramming metabolism. Furthermore, it offered a unique insight into a valuable attempt at the immunotherapy of obesity-associated related tumors.

Objective:To assess the impact of induction chemotherapy sensitivity on the prognosis and larynx preservation rates in patients with locally advanced hypopharyngeal cancer and to identify risk factors influencing induction chemotherapy sensitivity.Methods:This study included patients with locally advanced (stage III-IV) hypopharyngeal cancer who received induction chemotherapy as initial treatment at the Eye & ENT Hospital of Fudan University between August 2017 and September 2022. Based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, enrolled patients were classified into the sensitive group and the resistant group according to their response to induction chemotherapy. Chi-square tests and Log-rank tests were used to compare the objective response rate (ORR), overall survival (OS), progression-free survival (PFS), and laryngeal preservation rate (LPR) between groups. Propensity score matching (PSM) was employed to accurately evaluate the impact of induction chemotherapy sensitivity on prognosis in real-world settings. Univariate and multivariate logistic regression analyses were performed to identify risk factors for induction chemotherapy resistance in locally advanced hypopharyngeal cancer.Results:A total of 197 patients with locally advanced hypopharyngeal cancer who received induction chemotherapy as initial treatment were included in, comprising 195 males and 2 females, with ages ranging from 36 to 74 years. Among them, 155 patients (78.68%) were classified into the sensitive group and 42 patients (21.32%) into the resistant group. The overall response rate (ORR) of induction chemotherapy in this cohort was 78.68%, with a five-year OS rate of 63.7%. The sensitive group had significantly better OS (mOS 6.32 vs. 5.05 year), PFS (mPFS 5.71 vs. 3.09 year) and a significantly higher LPR (91.6% vs. 69.0%) ( P<0.05). After propensity score matching, all covariates were balanced between the two groups, and the sensitive group showed significant improvement in OS ( P<0.05), while, no significant difference was observed in PFS and LPR between the two groups. Logistic regression analysis revealed that risk factors for induction chemotherapy failure in locally advanced hypopharyngeal cancer included: smoking status ( OR [95% CI]=4.751 [1.887-11.961]), tumor location in the posterior pharyngeal wall ( OR [95% CI]=2.988 [1.264-7.063]), and cN2-3 stage ( OR [95% CI]=3.641 [1.109-11.954]) ( P<0.05). Conclusions:Induction chemotherapy sensitivity significantly affects the prognosis of locally advanced hypopharyngeal cancer, which is influenced by various risk factors, including smoking status, tumor sublocation, and clinical N stage.

Objective To understand the epidemiological characteristics of road traffic accident injuries in Beijing can provide a theoretical basis for improving the pre-hospital emergency service capabilities and levels,and increasing patient survival rates while reducing disability,mortality rates.Methods A retrospective analysis was conducted on the medical records of 9207 patients who made pre-hospital emergency calls due to road traffic accident injuries at the Beijing Emergency Medical Center in 2023 to understand the patients' age,gender,injury time,injury location,injury degree and other characteristics.Results Traumatic diseases ranked first in the classification of emergency medical conditions in Beijing.Among them,road traffic accidents account for 37％.The ratio of male to female patients was 1.32∶1.The largest number of patients were aged 31-40,accounting for nearly 25％.The proportion of underage patients and those aged 71 and above was 12.16％.The differences in gender and age distribution were statistically significant,while the differences in gender distribution among different age groups were not statistically significant.Road traffic accident injuries occured most frequently in September and least in January.There were more cases in summer and autumn,and fewer in winter and spring.The most common injury sites in road traffic accidents were limbs/skin and head and neck,accounting for 81.06％.The patients with moderate severity of injuries were the most numerous,accounting for 85.29％.Conclusion To avoid road traffic accidents,prevention should be the priority.It is necessary to strengthen the joint governance of multiple departments and minimize the occurrence of road traffic accident from the source.Pre-hospital emergency care must focus on key populations and key seasons,strengthen professional skills training and resource allocation,ensure efficient and smooth connection between pre-hospital and in-hospital care.Popularize and publicize the importance of self-rescue and mutual rescue,promote first aid knowledge and skills training for the public,and create a social atmosphere where"rescue is right beside us".

Objective: To analyze the differences in bile acid profiles during different pregnancy durations of patients with intrahepatic cholestasis of pregnancy (ICP), so as to provide a reference for early prevention and treatment of ICP and optimization of maternal-infant health outcomes. Methods: Pregnant women who underwent routine prenatal examinations and delivered at Hangzhou Obstetrics and Gynecology Hospital from 2021 to 2023 were selected as study subjects. According to the ICP guidelines (2020), pregnant women were categorized into normal group, mild ICP group, and moderate/severe ICP group. Age, parity, and gravidity were collected through the obstetric electronic medical record system, liver function indicators and seven bile acid levels were collected through the hospital's laboratory information system. Differences in bile acid profiles across pregnancy durations among the three groups were compared. Results: A total of 238 pregnant women were enrolled, including 57 cases (23.95%) in the normal group, 136 cases (57.14%) in the mild ICP group, and 45 cases (18.91%) in the moderate/severe ICP group. There were statistically significant differences between the three groups in total bile acid (TBA), cholic acid (CA), chenodeoxycholic acid (CDCA), glycochenodeoxycholic acid (GCDCA), glycocholic acid (GCA), taurocholic acid (TCA) levels (all P<0.05). Compared with the normal group, CA, GCDCA and GCA, and TCA were higher in the mild and moderate/severe ICP groups; compared with the mild ICP group, GCA was higher in the moderate/severe ICP group (all P<0.05). Significant differences were observed in the levels of GCDCA, GCA, and TCA among three groups pregnant women in the early, mid, and late pregnancy (all P<0.05). Compared with the normal group, mild ICP group had higher GCDCA and GCA in the early and mid pregnancy; moderate/severe ICP group had higher TCA in the early pregnancy and higher GCDCA and GCA in the late pregnancy. Compared with the mild ICP group, mild ICP group had higher TCA in the early pregnancy and the moderate/severe ICP group had higher GCA in the late pregnancy. Conclusions GCDCA, GCA, and TCA levels remain higher in ICP patients than in normal pregnant women across all pregnancy durations. Personalized perinatal management plans can be developed based on bile acid profile dynamics to optimize maternal-fetal outcomes.

Liposomes serve as critical carriers for drugs and vaccines, with their biological effects influenced by their size. The microfluidic method, renowned for its precise control, reproducibility, and scalability, has been widely employed for liposome preparation. Although some studies have explored factors affecting liposomal size in microfluidic processes, most focus on small-sized liposomes, predominantly through experimental data analysis. However, the production of larger liposomes, which are equally significant, remains underexplored. In this work, we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning (ML) model capable of accurately predicting liposomal size. Experimental validation was conducted using a staggered herringbone micromixer (SHM) chip. Our findings reveal that most investigated variables significantly influence liposomal size, often interrelating in complex ways. We evaluated the predictive performance of several widely-used ML algorithms, including ensemble methods, through cross-validation (CV) for both liposome size and polydispersity index (PDI). A standalone dataset was experimentally validated to assess the accuracy of the ML predictions, with results indicating that ensemble algorithms provided the most reliable predictions. Specifically, gradient boosting was selected for size prediction, while random forest was employed for PDI prediction. We successfully produced uniform large (600 nm) and small (100 nm) liposomes using the optimised experimental conditions derived from the ML models. In conclusion, this study presents a robust methodology that enables precise control over liposome size distribution, offering valuable insights for medicinal research applications.

Liposomes serve as critical carriers for drugs and vaccines,with their biological effects influenced by their size.The microfluidic method,renowned for its precise control,reproducibility,and scalability,has been widely employed for liposome preparation.Although some studies have explored factors affecting liposomal size in microfluidic processes,most focus on small-sized liposomes,predominantly through experimental data analysis.However,the production of larger liposomes,which are equally significant,remains underexplored.In this work,we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning(ML)model capable of accurately predicting liposomal size.Experimental validation was conducted using a staggered herringbone micromixer(SHM)chip.Our findings reveal that most investigated variables significantly influence liposomal size,often interrelating in complex ways.We evaluated the predictive performance of several widely-used ML algorithms,including ensemble methods,through cross-validation(CV)for both lipo-some size and polydispersity index(PDI).A standalone dataset was experimentally validated to assess the accuracy of the ML predictions,with results indicating that ensemble algorithms provided the most reliable predictions.Specifically,gradient boosting was selected for size prediction,while random forest was employed for PDI prediction.We successfully produced uniform large(600 nm)and small(100 nm)liposomes using the optimised experimental conditions derived from the ML models.In conclusion,this study presents a robust methodology that enables precise control over liposome size distribution,of-fering valuable insights for medicinal research applications.