Intervertebral disc degeneration （IVDD） is the core cause of chronic low back pain， which severely impairs patients’ quality of life and imposes a heavy social and medical burden. The hypoxia-pyroptosis-inflammation cascade mediated by hypoxia-inducible factor-1α （HIF-1α） is the core pathological mechanism driving the initiation and progression of IVDD. Natural active ingredients derived from traditional Chinese medicine （TCM） have become a research hotspot in the field of IVDD prevention and treatment due to their advantages of multi-target effects， favorable efficacy， and low toxicity. This paper systematically reviews the mechanism of HIF-1α-mediated hypoxia-pyroptosis-inflammation cascade in degenerative nucleus pulposus tissue and the intervention of related active ingredients. It is found that natural active ingredients such as baicalein， curcumin and resveratrol can intervene in the HIF-1α-mediated pathological cascade through four core links to delay IVDD progression： targeting the HIF-1α oxygen sensing pathway to block the initiation of pyroptosis cascade， inhibiting NOD-like receptor protein 3 inflammasome activation to cut off the cascade amplification of inflammatory signals， intervening in the Gasdermin D-mediated pyroptosis execution stage to protect cell membrane integrity， and regulating extracellular matrix metabolism to reconstruct intervertebral disc homeostasis.

ObjectiveAge-related macular degeneration （AMD） is one of the leading causes of low vision and blindness in people over 50 years old， and dry AMD （dAMD） is one type for which there is currently no clear treatment. On the basis of the diagnosis and clinical characteristics of dAMD in traditional Chinese and Western medicine， this paper evaluated the fitting degrees of existing animal models of dAMD with clinical characteristics according to the evaluation methods of animal models， and put forward suggestions and prospects. MethodsLiterature on animal models of dAMD was searched against database， and the characteristics of the models were assigned according to the diagnosis criteria of diseases and syndromes of traditional Chinese and Western medicine， and the fitting degrees of the models with clinical characteristics were analyzed and evaluated. ResultsAt present， the animal models of dAMD are mainly established targeting complement factors， chemokines， oxidative damage， lipid/glucose metabolism， and natural strains. Most of the models can simulate the major pathological changes of dAMD， showing the fitting degree of 25%-50% with clinical characteristics in Western medicine. However， the evaluation of traditional Chinese medicine （TCM） syndromes， especially the evaluation of secondary syndromes， is missing， and the models present low fitting degrees with the clinical characteristics in TCM. ConclusionExisting animal models of dAMD are mostly established under the guidance of Western diagnostic standards， which reproduce the main disease characteristics of Western medicine and lack observation of TCM syndromes. Future studies can pay attention to the intervention factors and evaluation systems of spleen deficiency Qi deficiency and liver-kidney Yin deficiency syndrome and build the animal model of dAMD with integration of disease and syndrome based on clinical characteristics of traditional Chinese and Western medicine.

ObjectiveAge-related macular degeneration （AMD） is one of the leading causes of low vision and blindness in people over 50 years old， and dry AMD （dAMD） is one type for which there is currently no clear treatment. On the basis of the diagnosis and clinical characteristics of dAMD in traditional Chinese and Western medicine， this paper evaluated the fitting degrees of existing animal models of dAMD with clinical characteristics according to the evaluation methods of animal models， and put forward suggestions and prospects. MethodsLiterature on animal models of dAMD was searched against database， and the characteristics of the models were assigned according to the diagnosis criteria of diseases and syndromes of traditional Chinese and Western medicine， and the fitting degrees of the models with clinical characteristics were analyzed and evaluated. ResultsAt present， the animal models of dAMD are mainly established targeting complement factors， chemokines， oxidative damage， lipid/glucose metabolism， and natural strains. Most of the models can simulate the major pathological changes of dAMD， showing the fitting degree of 25%-50% with clinical characteristics in Western medicine. However， the evaluation of traditional Chinese medicine （TCM） syndromes， especially the evaluation of secondary syndromes， is missing， and the models present low fitting degrees with the clinical characteristics in TCM. ConclusionExisting animal models of dAMD are mostly established under the guidance of Western diagnostic standards， which reproduce the main disease characteristics of Western medicine and lack observation of TCM syndromes. Future studies can pay attention to the intervention factors and evaluation systems of spleen deficiency Qi deficiency and liver-kidney Yin deficiency syndrome and build the animal model of dAMD with integration of disease and syndrome based on clinical characteristics of traditional Chinese and Western medicine.

Objective To investigate the association of serum total testosterone(TT),free testosterone(FT),sex hormone-binding globulin(SHBG),and estradiol(E_2)with all-cause mortality rate(AMR)in males and to evaluate their predictive value. Methods Based on data from the National Health and Nutrition Examination Survey(NHANES)cycles(1999—2004 and 2013—2016),the relationships between different sex hormones and AMR was analyzed with Cox proportional hazards regression models. The dose-response relationships between different sex hormones and male AMR were assessed with restricted cubic splines(RCS). The predictive performances of different sex hormones for male AMR were compared with receiver operating characteristic(ROC)curves and the area under the curve(AUC). The survival differences across varying sex hormone levels were evaluated with Kaplan-Meier survival curves and log-rank tests. Results This study involved 3632 adult male participants with a median follow-up of 6.5 years,during which 320 AMR occurred(8.8%). Cox univariate analysis indicated that TT,FT and SHBG were risk factors for AMR(P＜0.001). Cox multivariate analysis revealed that FT and SHBG were independent risk factors for AMR(FT:HR=0.90,95%CI:0.86-0.94; SHBG:HR=1.01,95%CI:1.01-1.02). RCS revealed a U-shaped nonlinear relationship between TT,FT and AMR(P＜0.001); SHBG showed a positive dose-response relationship with AMR(P＜0.001). The AUCs of FT predicting the 5-year,10-year,and 15-year AMR were 0.78(95%CI:0.73-0.82),0.80(95%CI:0.76-0.84),and 0.84(95%CI: 0.80-0.88),respectively,significantly outperforming other indicators. Subgroup analysis revealed that FT was negatively correlated with male AMR,but this association was modulated by age,race,smoking status and diabetes status(P_(interaction)＜0.05). Kaplan-Meier survival analysis showed that different levels of TT and FT(Q1-Q4)were significantly positively correlated with survival rate(P＜0.001),while different levels of SHBG were significantly negatively correlated with survival rate,with patients in the Q4 group having the highest risk of death(P＜0.001). Conclusion Based on US NHANES,studies have shown that the FT and SHBG are independent risk factors for male AMR,and FT demonstrates greater predictive value for male AMR than TT.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Epilepsy is a chronic brain disorder characterized by abnormal synchronous neuronal discharges in the brain, often accompanied by various complications. The pathogenesis of epilepsy has not yet been fully elucidated. Optogenetics, a cutting-edge technique that integrates optics and genetics, enables precise modulation of specific neurons by regulating light-sensitive proteins. Utilizing optogenetic technology has facilitated the dissection of neural circuits involved in epileptic seizures within brain regions such as the hippocampus, thalamus, hypothalamus. It has also helped identify potential therapeutic targets for epilepsy-related complications, including cognitive impairment, sudden unexpected death in epilepsy and mood disorders.However, in the process of advancing from basic research to clinical treatment, its translational path is profoundly influenced by factors such as stimulation modes (the choice between open-loop and closed-loop systems), key parameters (light frequency), and intervention strategies (unilateral or bilateral target selection). The individualized customization of these factors represents the future direction for overcoming current translational bottlenecks and achieving precise treatment.

Objective To construct a dynamic prediction model for the risk of developing Alzheimer's disease(AD)based on baseline clinical data and longitudinal neuropsychological scores in patients with mild cognitive impairment(MCI).Methods A total of 380 MCI patients from the Alzheimer's Disease Neuroimaging Initiative 1 study from 2005 to 2011 were selected and were randomly divided into a training set and a test set in a 7∶3 randomization.The Alzheimer's disease assessment scale-cognitive 13 items(ADAS-Cog13),Rey auditory verbal learning test immediate score(RAVLT Immediate),functional activities questionnaire(FAQ),and mini-mental state examination(MMSE)were used as longitudinal neuropsychological score metrics.Random survival forests with multivariate longitudinal endogenous covariates were used to construct a dynamic prediction model of the risk of developing AD in patients with MCI in the training set.The predictive performance of the model was evaluated in the test set using time-dependent areas under the receiver operator characteristic curve(AUC)and Brier score(BS).Results For the prediction of the risk of developing AD in patients with MCI,longitudinal neuropsychological scores were more important predictors than baseline clinical data,with FAQ being the strongest predictor.The dynamic prediction model had high predictive performance in the test set,with AUC ranging from 0.7695 to 0.8987 and BS ranging from 0.1369 to 0.2184.Conclusion Random survival forests with multivariate longitudinal endogenous covariates can be used to combine multivariate longitudinal neuropsychological scores to construct a prediction model for the risk of developing AD in patients with MCI,with high predictive performance and the ability to achieve individual dynamic prediction.

BACKGROUND: Post-stroke disability diminishes the physical activity (PA) level of survivors, potentially affecting their long-term prognosis. This study endeavors to explore the correlation between daily PA level and the all-cause mortality in patients with a history of stoke in the United States. METHODS: Data of stroke survivors were sourced from the National Health and Nutritional Examination Survey (NHANES) 2007-2018. The population was stratified into three groups based on their PA level. Kaplan-Meier method with log-rank tests for significance was used for survival analysis. Weighted Cox proportional hazards regression models were employed to estimate the hazard ratios (HRs) for all-cause mortality. Subgroup analysis was conducted to strengthen the results. RESULTS: A total of 1395 participants were recruited, comprising 679 males and 716 females, with a median age of 68 years. Based on their PA levels, 779 individuals were classified as inactive, 156 as insufficiently active, and 460 as sufficiently active. Following a median observation period of 59 months, there were 476 recorded deaths, with 349, 47, and 80 cases in the three respective groups. Compared to the inactive group, the HRs and 95% confidence intervals (CIs) for all-cause mortality in participants who were insufficiently active and sufficiently active were 0.58 (0.40, 0.84) and 0.47 (0.33, 0.67), respectively. The Kaplan-Meier curve revealed a significant difference in overall survival between the three groups, as confirmed by the log-rank test (P < 0.0001). Subgroup analysis further validated our results and demonstrated that the protective impact of PA on stroke prognosis varies according to distinct characteristics. CONCLUSIONS The results indicate that increased levels of PA are associated with a protective effect on long-term mortality among stroke survivors. Further prospective longitudinal studies are necessary to elucidate the optional PA level and special exercise guideline targeting this population.
Humans ; Male ; Female ; Aged ; Exercise ; Middle Aged ; Nutrition Surveys ; Stroke/mortality* ; United States/epidemiology* ; Survivors/statistics & numerical data* ; Aged, 80 and over ; Mortality

OBJECTIVES: Tiletamine, a veterinary anesthetic, has emerged as a novel psychoactive substance and has been abused in many parts of the world, causing great harm to public health. However, the sensitivity of existing detection methods cannot meet the needs of forensic practice. This study aims to establish an ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the determination of tiletamine and its metabolite desethyltiletamine in human biological samples, and to verify its applicability in forensic practice. METHODS: SKF_525A was used as the internal standard. Biological samples were extracted with acetonitrile containing 1 ng/mL SKF_525A, vortexed for 10 min, ultrasonicated for 20 min, centrifuged at 10 000 r/min for 10 min, and 500 μL of the supernatant was filtered through a 0.22 μm membrane. Analyses were performed using an ACQUITY UPLC H-Class PLUS system and an XEVO TQ-S Micro triple quadrupole mass spectrometer. An ACQUITY UPLC^® BEH C18 (1.7 µm, 2.1 mm×100 mm) column at a flow rate of 0.3 mL/min was used, and four mobile phase systems were tested to optimize separation. Detection used positive electrospray ionization (ESI+) in multiple reaction monitoring (MRM) mode, with quantifier ion transitions of mass to charge 224.043→179.016 for tiletamine and mass to charge 196.08→151.06 for desethyltiletamine. Calibration curves were established over 0.1-200 ng/mL in spiked blood samples. The linear range, limit of detection (LOD), and limit of quantification (LOQ) were determined. Low (5 ng/mL), medium (20 ng/mL), and high (100 ng/mL) concentrations of tiletamine were spiked into blood, liver, and kidney to evaluate precision, accuracy, matrix effect, recovery, and stability. Finally, actual forensic case samples were tested to validate applicability. RESULTS: The established UPLC-MS/MS method achieved simultaneous detection of tiletamine and desethyltiletamine in human biological samples, with retention times of 3.42 min and 2.82 min, respectively. Using mobile phase A (20 mmol/L ammonium acetate and 0.1% formic acid in water) and mobile phase B (acetonitrile) produced the best separation. In blood, tiletamine showed good linearity from 0.1-200 ng/mL (r=0.992, R²=0.983), LOD 0.03 ng/mL, LOQ 0.1 ng/mL, recovery 92%-107%, and matrix effect 71%-99%. In liver and kidney, recoveries were 91%-98% and 93%-104%, and matrix effects were 69%-96% and 72%-100%, respectively. Intra- and inter-day precision [expressed as relative standard deviation (RSD)] and accuracy [expressed as relative error (RE)] were within 15%, and samples were stable at -20 ℃. Tiletamine was detected in actual case samples at 0.37 μg/mL (blood), 0.15 μg/g (liver), 0.11 μg/g (kidney) in case 1, and 8.75 ng/mL (blood) in case 2; desethyltiletamine was also detected in blood. CONCLUSIONS The UPLC-MS/MS method is efficient, accurate, and sensitive, and is suitable for detecting tiletamine and desethyltiletamine in human biological samples.
Tandem Mass Spectrometry/methods* ; Humans ; Chromatography, High Pressure Liquid/methods* ; Substance Abuse Detection/methods* ; Liquid Chromatography-Mass Spectrometry

Although clinical evidence suggests that nonalcoholic fatty liver disease is an established major risk factor for heart failure, it remains unexplored whether sleep disorder-caused hepatic damage contributes to the development of cardiovascular disease (CVD). Here, our findings revealed that sleep fragmentation (SF) displayed notable hepatic detrimental phenotypes, including steatosis and oxidative damage, along with significant abnormalities in cardiac structure and function. All these pathological changes persisted even after sleep recovery for 2 consecutive weeks or more, displaying memory properties. Mechanistically, persistent higher expression of nicotinamide adenine dinucleotide phosphate oxidase 4 (NOX4) in the liver was the key initiator of SF-accelerated damage phenotypes. SF epigenetically controlled the acetylation of histone H3 lysine 27 (H3K27ac) enrichment at the Nox4 promoter and markedly increased Nox4 expression in liver even after sleep recovery. Moreover, fine coordination of the circadian clock and hepatic damage was strictly controlled by BMAL1-dependent Sirtuin 1 (Sirt1) transcription after circadian misalignment. Accordingly, genetic manipulation of liver-specific Nox4 or Sirt1, along with pharmacological intervention targeting NOX4 (GLX351322) or SIRT1 (Resveratrol), could effectively erase the epigenetic modification of Nox4 by reducing the H3K27ac level and ameliorate the progression of liver pathology, thereby counteracting SF-evoked sustained CVD. Collectively, our findings may pave the way for strategies to mitigate myocardial injury from persistent hepatic detrimental memory in diabetic patients.