ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Malonylation is an important post-translational modification of proteins.In this work,a comprehensive malonylation proteomics study on hepatocellular carcinoma(HCC)tumorous and non-tumorous tissues using antibody enrichment combined with high performance liquid chromatography-mass spectrometry for discovery of early diagnostic biomarkers or potential new drug targets of HCC was performed.A total of 1299 malonylated peptides containing 1064 malonylated sites were identified from HCC tissues,corresponding to 511 malonylated proteins.Quantitative results showed that 56 and 80 malonylated proteins were up-regulated and down-regulated in HCC tissues,including 60 and 101 malonylated sites,respectively.Kyoto encyclopedia of genes and genomes(KEGG)pathway analysis showed that these differentially modified proteins were involved in various important pathways such as metabolic pathways,fatty acid degradation,and glycolysis/gluconeogenesis.As a key enzyme in glycolysis/gluconeogenesis,phosphoenolpyruvate carboxykinase 1(PCK1)was malonylated at lysine 244(K244)and the malonylation was only detected in HCC tumorous tissues.More importantly,the K244 site served as a binding site for Mn2+and highly conserved across different species.Therefore,it could speculate that the malonylation of K244 would affect its activity and played a role in liver cancer by affecting its binding with Mn2+,which requied further verification through site mutation experiments.Western blot analysis by malonylation pan antibody showed that the malonylation level reduced markedly in HCC tumorous tissues compared with adjacent non-tumorous tissues,which was consistent with mass spectrometry data.In addition,the proliferation and invasion of PLC/PRF/5 cell was significantly inhibited and protein malonylation level was increased obviously when treated with sodium malonate.All the evidence indicated that protein malonylation played an important role in HCC pathogenesis,and its molecular mechanism deserved further investigation.Furthermore,the 136 differentially malonylated proteins provided rich source of candidate targets for further research on HCC pathogenesis.

Objective To explore factors affecting blood pressure control in chronic disease patients in China's na-tional basic public health service chronic disease patient management program and to find their relationships with Bayesian network(BN)model,in order to provide a scientific basis for comprehensive hypertension management.Methods 5 577 Hypertensive patients were selected from eight provinces(including autonomous regions)covering eastern,central and western parts of China during a survey from 2021 to 2022.Researchers collected individual and community-management data to screen influencing factors by Logistic regression,and to describe factor dependencies and to identify key determinants of blood pressure control with BN in.blood pressure control.Results Logistic regression revealed that urban/rural status,education,alcohol use,exercise,overweight/obesity and com-munity-doctor advice on salt reduction,smoking cessation were significantly associated with blood pressure control(P＜0.05).The BN model identified 22 directed edges showing that urban residence and good hypertension knowl-edge were more correlated with better control,while community-doctor management and services directly affected patient lifestyle habits but not blood pressure control.Conclusions Research should focus more on urban-rural dis-parities and hypertension education.Additionally,improving patient habits and community-doctor services is essen-tial for better blood pressure control.

In the context of the development of transplant oncology,it is of great clinical significance to find a drug with both antitumor and immunosuppressive effects for liver transplantation patients with hepatocellular carcinoma(HCC).The antitumor effect of ginkgolic acid(GA)has been confirmed,and some studies suggest that GA may also have an immunosuppressive effect.The immunosuppressive effect of GA was evaluated by histopathology,T-cell subpopulation,and cytokine detection in rat liver transplantation and mouse cardiac transplantation models,and transcriptomic and metabolomic analysis was used to explore the underlying mechanism of the GA immunosuppressive effect.Metabolites,activation,and ferroptosis markers of CD8+T cells were detected in vivo and in vitro.Based on rat liver transplantation and mouse cardiac transplantation models,the immunosuppressive effect of GA was first confirmed by histopathology,T-cell subpopulation,and cytokine detection.In the mouse cardiac transplantation model,transcriptomics combined with metabolomics demonstrated for the first time that GA inhibited lactate dehydrogenase A(LDHA)expression and pyruvate metabolism in CD8+T cells.It was confirmed in vivo and in vitro that GA inhibited pyruvate metabolism of CD8+T cells through LDHA,inhibiting their activation and inducing ferroptosis.Over-expression of LDHA partially reversed the effect of GA on the metabolism,activation,and ferroptosis of CD8+T cells in vitro.GA mediates metabolic reprogramming through LDHA to inhibit the activation and induce ferroptosis of CD8+T cells to exert an immunosuppressive effect,which lays an experimental foundation for the future clinical application of its immunosuppressive effect.

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.

OBJECTIVE: To investigate whether Buyang Huanwu Decoction (BYHWD) had a good curative effect on the neuroprotection of red nucleus neurons after spinal cord injury (SCI) and the possible molecular mechanism. METHODS: Ninety male Sprague-Dawley rats were divided into 5 groups (n=18 per group) according to a random number table, including the control, model, low- (12.78 g/kg, BL group), medium- (25.65 g/kg, BM group), and high-dose BYHWD groups (51.30 g/kg, BH group). A rubrospinal tract transection model in rats was established, and different doses of BYHWD were intragastrically administrated for 4 weeks. The forelimb locomotor function was recorded using the spontaneous vertical exploration test. Cyclic adenosine monophosphate (cAMP) level in red nucleus was detected through an enzyme-linked immunosorbent assay. The morphology and number of red nucleus neurons were observed using Nissl's staining and axonal retrograde tracing by Fluoro-Gold (FG). The expression of cAMP-dependent protein kinase A (PKA), nuclear factor kappa-B (NF-κB) p65, and brain-derived neurotrophic factor (BDNF) in red nucleus were detected using immunohistochemistry and quantitative real-time polymerase chain reaction. RESULTS: Compared with the control group, the utilization rate of bilateral forelimbs, unilateral right forelimbs, proportion of FG-labeled positive neurons, cAMP level, protein expressions of PKA and BDNF, and BDNF mRNA expression were significantly decreased in the model group (P<0.01), while NF-κB p65 was increased in the model group (P<0.01). Compared with the model group, the utilization rate of bilateral forelimbs and unilateral right forelimbs were significantly higher in the BL, BM and BH groups (P<0.01), the proportion of FG-labeled positive neurons, cAMP level, protein expressions of PKA and BDNF and BDNF mRNA expression in all BYHWD groups were increased (P<0.05 or P<0.01), while NF-κB p65 were decreased in all BYHWD groups (P<0.05 or P<0.01). CONCLUSIONS BYHWD possesses a sound neuroprotective effect on red nucleus neurons after SCI, and the efficacy was dose-related. The mechanism may be related to regulating the cAMP/PKA/NF-κ B p65 signaling pathway, finally promoting expression of BDNF.
Animals ; Spinal Cord Injuries/pathology* ; Drugs, Chinese Herbal/therapeutic use* ; Rats, Sprague-Dawley ; Male ; Cyclic AMP/metabolism* ; Transcription Factor RelA/metabolism* ; Cyclic AMP-Dependent Protein Kinases/metabolism* ; Signal Transduction/drug effects* ; Brain-Derived Neurotrophic Factor/genetics* ; Red Nucleus/metabolism* ; Recovery of Function/drug effects* ; Neurons/metabolism* ; Rats

In the context of the development of transplant oncology, it is of great clinical significance to find a drug with both antitumor and immunosuppressive effects for liver transplantation patients with hepatocellular carcinoma (HCC). The antitumor effect of ginkgolic acid (GA) has been confirmed, and some studies suggest that GA may also have an immunosuppressive effect. The immunosuppressive effect of GA was evaluated by histopathology, T-cell subpopulation, and cytokine detection in rat liver transplantation and mouse cardiac transplantation models, and transcriptomic and metabolomic analysis was used to explore the underlying mechanism of the GA immunosuppressive effect. Metabolites, activation, and ferroptosis markers of CD8⁺ T cells were detected in vivo and in vitro. Based on rat liver transplantation and mouse cardiac transplantation models, the immunosuppressive effect of GA was first confirmed by histopathology, T-cell subpopulation, and cytokine detection. In the mouse cardiac transplantation model, transcriptomics combined with metabolomics demonstrated for the first time that GA inhibited lactate dehydrogenase A (LDHA) expression and pyruvate metabolism in CD8⁺ T cells. It was confirmed in vivo and in vitro that GA inhibited pyruvate metabolism of CD8⁺ T cells through LDHA, inhibiting their activation and inducing ferroptosis. Overexpression of LDHA partially reversed the effect of GA on the metabolism, activation, and ferroptosis of CD8⁺ T cells in vitro. GA mediates metabolic reprogramming through LDHA to inhibit the activation and induce ferroptosis of CD8⁺ T cells to exert an immunosuppressive effect, which lays an experimental foundation for the future clinical application of its immunosuppressive effect.

OBJECTIVE: This study aimed to investigate possible serum 25-hydroxyvitamin D [25(OH)D] cutoffs for the associations between 25(OH)D and Bone turnover markers (BTMs), and how GC gene variation influences such cutoffs in Chinese women of childbearing age. METHODS: In total, 1,505 non-pregnant or non-lactating women (18-45 years) were recruited from the 2015 Chinese Adult Chronic Disease and Nutrition Surveillance. Serum 25(OH)D, osteocalcin (OC), procollagen type 1 N-terminal propeptide (P1NP), β-CrossLaps of type 1 collagen containing cross-linked C-telopeptide (β-CTX), and single nucleotide polymorphisms were determined. Locally weighted regression and smoothing scatterplot and segmented regression were performed to estimate the 25(OH)D thresholds. RESULTS: The median serum 25(OH)D was 16.63 (11.96-22.55) ng/mL and the prevalence of low serum 25(OH)D (< 12 ng/mL) was 25.2%. Women with the lowest 25(OH)D had the highest β-CTX. After adjustment for the confounders, 25(OH)D cutoffs for OC [14.04 (12.84-15.23) ng/mL], β-CTX [13.94 (12.49-15.39) ng/mL], and P1NP [13.87 (12.37-15.37) ng/mL] in the whole population, cutoffs for OC [12.30 (10.68-13.91) ng/mL], β-CTX [12.23 (10.22-14.23) ng/mL], and P1NP [11.85 (10.40-13.31) ng/mL] in women with the GC rs2282679 G allele, and cutoffs for OC [12.75 (11.81-13.68) ng/mL], β-CTX [13.05 (11.78-14.32) ng/mL], and P1NP [12.81 (11.57-14.06) ng/mL] in women with the GC rs2282679 T allele, were observed. Below these cutoffs, BTMs were negatively associated with 25(OH)D, while above these cutoffs, BTMs plateaued. CONCLUSION In Chinese women of childbearing age, there were thresholds effect of serum 25(OH)D concentrations on BTMs. The results indicated that serum 25(OH)D concentrations < 13.87 ng/mL in this population had adverse influences on maintaining bone remodeling. BTMs were suppressed at a relatively lower serum 25(OH)D in women with the GC rs2282679 G allele compared with those with the T allele.
Humans ; Female ; Vitamin D/blood* ; Adult ; Middle Aged ; Polymorphism, Single Nucleotide ; Adolescent ; Young Adult ; China ; Biomarkers/blood* ; Bone Remodeling/genetics* ; Vitamin D-Binding Protein/genetics* ; Procollagen/blood* ; Osteocalcin/blood* ; Peptide Fragments/blood* ; East Asian People