ObjectiveTo evaluate the public health governance capacity in Jiangsu Province and provide an optimized pathway for the construction of a “strong, rich, beautiful, and high-quality” new Jiangsu. MethodsA total of 806 policy documents, 658 public information reports, and 148 research literatures related to public health governance capacity in Jiangsu Province from January 1995 to December 2023 were collected. The status of current public health goverance was assessed based on the evaluation criteria suitable for public health systems, and the strengths and the weaknesses of the system were identified. ResultsThe public health governance capability of Jiangsu Province was scored at 738.3 points, ranking 3rd nationally. Maternal health care and emergency response capacities achieved leading positions nationwide, both ranking 2nd. Jiangsu had exhibited a standardized guidance in the strategic level, a well-established management mechanism, an extensive coverage in information collection, and a scientifically established health targets setting. However, bottlenecks remained, including an unclear division of responsibilities across organizational departments, an insufficient public-health workforce, the absence of a stable growth mechanism for government funding investment, and difficulties in promptly identifying public needs. ConclusionJiangsu’s public-health system demonstrates leading nationally, yet several components remain underdeveloped. Future efforts should consolidate advantages while addressing weaknesses, further diversify content and forms, establish a stable funding increase mechanism, and clarify departmental functions, thereby providing solid health support for realizing the developmental goals of a “strong, rich, beautiful and high-quality” new Jiangsu.

The digitization of traditional Chinese medicine (TCM) has generated vast amounts of data. However, these data are characterized by significant heterogeneity and complex semantic structures, posing substantial challenges for systematic integration and intelligent analysis, and limiting its potential for modern clinical and computational research. To address the challenges posed by the high heterogeneity and complex structure in TCM data, we designed and developed the TCM Data Hub platform, which is powered by the YiYuan large language models (LLMs). This platform aims to enhance intelligent data processing capabilities and unlock the potential for clinical application of TCM data through systematic integration and efficient utilization, thereby bridging the gap between traditional knowledge and modern computational research. This study first analyzed the heterogeneity and complexity of TCM information with respect to data types, structures, and semantics. A standardized data framework was constructed to enhance data integration and interoperability. Based on the TCM Intelligent Computing Platform of the China Academy of Chinese Medical Sciences, we trained the YiYuan LLMs to acquire domain-specific semantic understanding of TCM, thereby improving the platform’s comprehension of specialized terminology and knowledge systems. Leveraging the natural language processing capabilities of the LLMs, we developed a human-in-the-loop data processing system to enable efficient extraction, cleansing, and structured organization of TCM data. In addition, utilizing Vue and Java technologies, we developed multiple LLM-powered intelligent agents and systems, including a human-in-the-loop data processing system, as well as automated prescription mining and network pharmacology analysis agents. Task-specific agents tailored to TCM data processing were developed to enhance the model’s effectiveness in clinical knowledge discovery. System functionality and platform infrastructure were implemented using Java and Vue technologies.The TCM Data Hub platform has completed system construction and core functionality implementation. It supported integrated management and efficient access to 8 key types of TCM data: prescriptions, materia medica, ingredients, targets, diseases (Western medicine), diseases (TCM), syndromes, and therapeutic methods. The human-in-the-loop data processing system achieved an accuracy of 95.34% in structuring TCM data and supported annotation for data requiring manual labeling. The intelligent agent-driven big-data analytics module enabled 1-click, end-to-end workflows for TCM prescription mining, herb-syndrome association analysis, network pharmacology, and molecular biology research, completing a full data mining task in approximately 30 minutes. Users can interact with and manipulate data through a visual front-end interface. The system demonstrated stable performance, strong scalability, and a user-friendly experience. Empowered by the YiYuan LLMs, the TCM Data Hub platform significantly improves the accessibility, usability, and intelligence of TCM data. It effectively bridges traditional TCM knowledge with modern intelligent technologies, providing robust data support and intelligent tools for TCM research and clinical applications.

Acute kidney injury (AKI) is a critical clinical condition characterized by rapid renal function decline, with high morbidity, mortality, and healthcare costs. Traditional Chinese medicine (TCM) has shown potential effects on mitigating oxidative stress and programmed cell death in AKI models. Scutellaria barbata D. Don (SB) and Scleromitrion diffusum (Willd.) R. J. Wang (SD), a classic TCM herbal pair exhibited anti-inflammatory and antioxidant activities. Using advanced chromatographic separation technology, we enriched the effective fractions of water extracts from SB-SD, obtaining self-assembled herbal nanoparticles (SB and SD nanoparticles, SSNPs) rich in flavonoids and terpenoids. These SSNPs demonstrated robust antioxidant properties in vitro and mitigated AKI progression in vivo by activating the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway. Oral administration of SSNPs in mice resulted in absorption into the bloodstream, formation of a protein corona, reduced macrophage phagocytosis, and enhanced bioavailability and renal targeting. Furthermore, we investigated the self-assembly principle of SSNPs using representative flavonoids and terpenoids. Kinetic studies and in situ transmission electron microscopy (in situ TEM) revealed that these compounds self-assemble via supramolecular forces like hydrogen bonding and π-π interactions, forming stable nanostructures. This study elucidates the renoprotective effects and mechanisms of SB and SD, and provides a novel approach for the development of TCM-based nanomedicines, highlighting the potential of nano-TCM in AKI treatment.

Exosomal circular RNA(circRNAs)are pivotal in cancer biology,and tumor pathophysiology.These stable,non-coding RNAs encapsulated in exosomes participated in cancer progression,tumor growth,metas-tasis,drug sensitivity and the tumor microenvironment(TME).Their presence in bodily fluids positions them as potential non-invasive biomarkers,revealing the molecular dynamics of cancers.Research in exosomal circRNAs is reshaping our understanding of neoplastic intercellular communication.Exploiting the natural properties of exosomes for targeted drug delivery and disrupting circRNA-mediated pro-tumorigenic signaling can develop new treatment modalities.Therefore,ongoing exploration of exoso-mal circRNAs in cancer research is poised to revolutionize clinical management of cancer.This emerging field offers hope for significant breakthroughs in cancer care.This review underscores the critical role of exosomal circRNAs in cancer biology and drug resistance,highlighting their potential as non-invasive biomarkers and therapeutic targets that could transform the clinical management of cancer.

Exosomal circular RNA (circRNAs) are pivotal in cancer biology, and tumor pathophysiology. These stable, non-coding RNAs encapsulated in exosomes participated in cancer progression, tumor growth, metastasis, drug sensitivity and the tumor microenvironment (TME). Their presence in bodily fluids positions them as potential non-invasive biomarkers, revealing the molecular dynamics of cancers. Research in exosomal circRNAs is reshaping our understanding of neoplastic intercellular communication. Exploiting the natural properties of exosomes for targeted drug delivery and disrupting circRNA-mediated pro-tumorigenic signaling can develop new treatment modalities. Therefore, ongoing exploration of exosomal circRNAs in cancer research is poised to revolutionize clinical management of cancer. This emerging field offers hope for significant breakthroughs in cancer care. This review underscores the critical role of exosomal circRNAs in cancer biology and drug resistance, highlighting their potential as non-invasive biomarkers and therapeutic targets that could transform the clinical management of cancer.

Objective To investigate the effects of sample transport and sorting system on the detection results of common clinical bio-chemical and immunological items carried out in our laboratory.Methods A total of 25 patients admitted to Zidong Hospital of Jiangsu Provincial Hospital of Traditional Chinese Medicine in June 2024 were included in this study,and four blood samples were collected from each patients using vacuum blood vessels with separation gel containing coagulant.These samples were transferred to the laboratory department through manual transport or pneumatic logistics transmission,and the manual sorting approach or intelligent blood vessel sorting system was used to encode the samples.The effects of different sample transportation methods and sorting methods on the detec-tion results of 46 clinical biochemical parameters,12 tumor markers and 5 thyroid hormone items,which were carried out in our labora-tory,were analyzed and compared.Results No significant change on hemolytic index(HI)was found through pneumatic tube system(PTS)and intelligent blood vessel sorting system(P＞0.05).The results of AST,CK-MB,α-HBDH,and LDH in clinical biochemical parameters following PTS were significantly different from those in artificial transport group(all P＜0.05).Both the results of Cyfra21-1 and NSE in immunological items in the samples after PTS transport were significantly different from those obtained by either manual transport or intelligent sorting system,with statistical significance(all P＜0.05).Conclusion PTS basically meets the requirements of clinical laboratories,but it can lead to the increase of AST,CK-MB,α-HBDH and LDH in clinical biochemistry,as well as Cyfra21-1 and NSE in immunology,which needs to be further improved,refined,and validated in order to meet the clinical requirements.

Objective To investigate the effects of sample transport and sorting system on the detection results of common clinical bio-chemical and immunological items carried out in our laboratory.Methods A total of 25 patients admitted to Zidong Hospital of Jiangsu Provincial Hospital of Traditional Chinese Medicine in June 2024 were included in this study,and four blood samples were collected from each patients using vacuum blood vessels with separation gel containing coagulant.These samples were transferred to the laboratory department through manual transport or pneumatic logistics transmission,and the manual sorting approach or intelligent blood vessel sorting system was used to encode the samples.The effects of different sample transportation methods and sorting methods on the detec-tion results of 46 clinical biochemical parameters,12 tumor markers and 5 thyroid hormone items,which were carried out in our labora-tory,were analyzed and compared.Results No significant change on hemolytic index(HI)was found through pneumatic tube system(PTS)and intelligent blood vessel sorting system(P＞0.05).The results of AST,CK-MB,α-HBDH,and LDH in clinical biochemical parameters following PTS were significantly different from those in artificial transport group(all P＜0.05).Both the results of Cyfra21-1 and NSE in immunological items in the samples after PTS transport were significantly different from those obtained by either manual transport or intelligent sorting system,with statistical significance(all P＜0.05).Conclusion PTS basically meets the requirements of clinical laboratories,but it can lead to the increase of AST,CK-MB,α-HBDH and LDH in clinical biochemistry,as well as Cyfra21-1 and NSE in immunology,which needs to be further improved,refined,and validated in order to meet the clinical requirements.

"Global cancer statistics 2022" based on the latest GLOBCAN data from the International Agency for Research on Cancer (IARC) was recently released, providing a systematic analysis of the incidence and mortality of 36 types of cancer across 185 countries worldwide. The international burden of cancer is expected to continue to increase over the next 30 years, posing a severe public health and social challenge for many countries, including China. This article offers a key point interpretation of the "Global cancer statistics 2022", focusing on the evolution of cancer epidemiology and future development trends. The aim is to broaden the international perspective on cancer prevention and treatment, with the hope of providing reference and guidance for cancer prevention and treatment efforts in our country.

Objective To analyzes the current status and hot spots of nursing of adverse drug reactions in chemotherapy for cancer patients,and provides reference for future research.Methods Literature related to the nursing of chemotherapy adverse drug reactions in cancer patients from 2018 to 2022 was retrieved from CNKI,Wanfang and VIP databases,and statistical analysis was conducted using bibliometrics.CiteSpace information visualization software was used to describe and analyze high-frequency keywords and to describe their graphs.Results A total of 1112 literatures were included,distributed in 256 domestic journals,and 537 literatures were co-authored,with a co-authored rate of 48.29％.Gastrointestinal reaction,cancer-induced fatigue,traditional Chinese medicine nursing,evidence-based nursing,negative emotion are the hot issues in this field.Conclusion The future nursing intervention for adverse reactions of cancer patients should adopt evidence-based nursing method to develop intervention programs.The research in this field has the problems of small sample size and single institution.It is suggested that the cooperation between authors and institutions should be strengthened in the future research,so as to build a closer cooperation network and a stable cooperation group.To construct nursing intervention plan and effect evaluation criteria suitable for nursing of adverse reactions of chemotherapy drugs in cancer patients.To ensure the safety of the intervention process,we should actively carry out multidisciplinary collaboration.

Objective To propose a heart sound segmentation method based on multi-feature fusion network. Methods Data were obtained from the CinC/PhysioNet 2016 Challenge dataset (a total of 3 153 recordings from 764 patients, about 91.93% of whom were male, with an average age of 30.36 years). Firstly the features were extracted in time domain and time-frequency domain respectively, and reduced redundant features by feature dimensionality reduction. Then, we selected optimal features separately from the two feature spaces that performed best through feature selection. Next, the multi-feature fusion was completed through multi-scale dilated convolution, cooperative fusion, and channel attention mechanism. Finally, the fused features were fed into a bidirectional gated recurrent unit (BiGRU) network to heart sound segmentation results. Results The proposed method achieved precision, recall and F1 score of 96.70%, 96.99%, and 96.84% respectively. Conclusion The multi-feature fusion network proposed in this study has better heart sound segmentation performance, which can provide high-accuracy heart sound segmentation technology support for the design of automatic analysis of heart diseases based on heart sounds.