Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

To clarify the occurrence and distribution of broad bean wilt virus 2(BBWV2) on Rehmannia glutinosa, this study collected 87 R. glutinosa samples with typical symptoms of viral disease such as chlorosis and crumple from Wenxian county and Wuzhi county in Jiaozuo city, Henan province and Qiaocheng district in Bozhou city, Anhui province. The BBWV2 CP target band was amplified from 37 R. glutinosa samples by RT-PCR technology. The total detection rate reached 42.5%, among which 43.0% was detected in samples from Henan province. The detection rate in samples from Anhui province was 37.5%. 37 BBWV2 CP sequences were obtained by cloning and sequencing of BBWV2 positive samples(data has been submitted to GenBank, accession numbers: PP407959-PP407995), and the sequence analysis of these CP sequences with 91 other BBWV2 isolates in GenBank showed a high genetic diversity with a consistency rate of 70.8%-100%. Meanwhile, phylogenetic analysis showed that BBWV2 could be divided into three groups according to CP sequences, among which the BBWV2 in R. glutinosa isolates obtained in this study were all located in group 3. This study identified the differences in the occurrence, distribution, and genetic diversity of BBWV2 in R. glutinosa from Henan province and Anhui province and provided a theoretical basis for the prevention and control of BBWV2.
Rehmannia/virology* ; Phylogeny ; Plant Diseases/virology* ; China ; Molecular Sequence Data ; Fabavirus/classification*

Objective To investigate plasma protein expression changes in heatstroke patients using proteomics technology and to identify reliable prognostic biomarkers.Methods A retrospective analysis was conducted on 20 heatstroke patients hospitalized at the 908th Hospital of the Chinese PLA Joint Logistics Support Force from July 2022 to February 2024.Patients were divided into survival(n=16)and death groups(n=4)based on 28-day outcomes.Fasting venous blood samples were collected from both groups for proteomic analysis.Liquid chromatography-mass spectrometry(LC-MS/MS)was used to identify and screen differentially expressed proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)enrichment analyses were performed.LASSO regression was applied to screen key prognostic biomarkers,and receiver operating characteristic(ROC)curve analysis was used to evaluate their predictive value.Results A total of 27 upregulated and 90 downregulated proteins were identified between the two groups.These proteins were primarily involved in biological processes such as immune responses,complement activation,and metabolic processes.LASSO regression analysis indicated that actin-related protein 2(ARP2),cysteine-rich scavenger receptor type 1 M130(CD163),and catalase(CAT)could serve as effective biomarkers for evaluating heatstroke prognosis.ROC curve analysis demonstrated that ARP2 had higher diagnostic efficacy(AUC=0.98,sensitivity=0.80,specificity=1.00)compared to CD163(AUC=0.94,sensitivity=0.76,specificity=1.00),CAT(AUC=0.96,sensitivity=0.67,specificity=1.00),and acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(AUC=0.79,sensitivity=0.44,specificity=1.00).Conclusion Elevated plasma ARP2 level has good clinical value for predicting poor prognosis in heatstroke patients.

Guidelines for Digital Ancient Books of TCM Indexing(T/CIATCM 119-2024)is based on the theoretical knowledge,disciplinary methods,and practical applications of TCM classical cataloging.Taking digital ancient books of TCM as the object,it systematically reveals the content of TCM knowledge,which is an essential indexing processing standard for building an intelligent retrieval system for TCM ancient books,and can provide support for the deep development and innovative utilization of TCM knowledge.It can not only promote the co-construction and sharing of ancient book resources in the TCM industry,but also promote the standardization construction and application of TCM information.This standard specifies the principles,methods,and examples of free indexing of digital ancient books of TCM based on their original content.It is applicable to the indexing and processing of digital ancient books of TCM for TCM professional libraries and related institutions,and to the data processing and construction of various types of TCM ancient book databases.

Objective To analyze the influencing factors of diabetes insipidus after pituitary tumor surgery,thereby providing evidence for enhancing perioperative management of pituitary tumor surgery and preventing diabetes insipidus after pituitary tumor surgery.Methods The clinical data of patients who underwent pituitary tumor surgery in our hospital from January 2014 to December 2024 were retrospectively analyzed.The relationship between each variable and postoperative diabetes insipidus was explored through univariate analysis,and multi-variate regression analysis was used to identify the independent risk factors for the occurrence of postoperative diabetes insipidus.Results Univariate analysis showed that the occurrence of diabetes insipidus after pituitary tumor surgery was related to tumor invasiveness,tumor growth direction,surgical resection degree,surgical time and surgical method(P<0.05).Logistic regression analysis showed that the surgical time>4 hours(P=0.001)and tumor growth breaking through diaphragma sellae(P=0.004)were independent risk factors for the occurrence of postoperative diabetes insipidus.Conclusion The surgical time and tumor growth direction are closely related to diabetes insipidus after pituitary tumor surgery;therefore,in order to reduce the incidence of diabetes insipidus after pituitary tumor surgery,a thorough evaluation should be conducted preoperatively to clarify the direction of tumor growth;minimally invasive surgery should be adopted as much as possible during the operation and the skills of surgeons should be improved to shorten the surgical time;and close observation should performed after surgery.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

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

OBJECTIVE: To investigate the impact of bone mass and volume of low-density zones beneath the tibial plateau on the maximum von Mises stresses experienced by the cartilage and meniscus in the knee joint. METHODS: The study included one healthy adult volunteer, from whom CT scans were obtained, and one patient diagnosed with knee osteoarthrisis (KOA), for whom X-ray films were acquired. A static model of the knee joint featuring a low-density zone was established based on a normal knee model. In the finite element analysis, axial loads of 1 000 N and 1 800 N were applied to the weight-bearing region of the upper surface of the femoral head for model validation and subsequent finite element studies, respectively. The maximum von Mises stresses in the femoral cartilage, as well as the medial and lateral tibial cartilage and menisci, were observed, and the stress percentage of the medial and lateral components were concurrently analyzed. Additionally, HE staining, as well as alkaline magenta staining, were performed on the pathological specimens of patients with KOA in various low-density regions. RESULTS: The results of model validation indicated that the model was consistent with normal anatomical structures and correlated with previous calculations documented in the literature. Static analysis revealed that the maximum von Mises stress in the medial component of the normal knee was the lowest and increased with the advancement of the hypointensity zone. In contrast, the lateral component exhibited an opposing trend, with the maximum von Mises stress in the lateral component being the highest and decreasing as the hypointensity zone progressed. Additionally, the medial component experienced an increasing proportion of stress within the overall knee joint. HE staining demonstrated that the chondrocyte layer progressively deteriorated and may even disappear as the hypointensity zone expanded. Furthermore, alkaline magenta staining indicated that the severity of microfractures in the trabecular bone increased concurrently with the expansion of the hypointensity zone. CONCLUSION The presence of subtalar plateau low-density zone may aggravate joint degeneration. In clinical practice, it is necessary to pay attention to the changes in the subtalar plateau low-density zone and actively take effective measures to strengthen the bone status of the subtalar plateau low-density zone and restore the complete biomechanical function of the knee joint, in order to slow down or reverse the progression of osteoarthritis.
Humans ; Finite Element Analysis ; Knee Joint/physiology* ; Tibia/anatomy & histology* ; Cartilage, Articular/physiology* ; Menisci, Tibial/physiopathology* ; Tomography, X-Ray Computed ; Osteoarthritis, Knee/diagnostic imaging* ; Weight-Bearing ; Bone Density ; Adult ; Stress, Mechanical ; Male ; Middle Aged ; Biomechanical Phenomena ; Female

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness