Stress is a critical inducer in the onset and progression of many chronic diseases. Prolonged or intense stress can disrupt the overall balance between the nervous, immune, and endocrine systems. The resulting biological signals may act on corresponding receptors in the cervical spine region, leading to adverse pathological changes. The vertebral artery and the surrounding muscular and connective tissues are influenced by biomechanical abnormalities and inflammatory cascades associated with cervical spondylosis of vertebral artery type (CSA), which promotes the release of various hormones. These hormones, through the neuroendocrine-immune system, affect the central nervous system, inducing or exacerbating negative emotional feedback and thereby establishing a "central-local-central" vicious cycle. This article explores the mechanisms underlying the impact of stress on the key CSA symptoms through the neuroendocrine-immune network (NEI) theory, providing a more comprehensive framework for targeted therapeutic interventions in CSA.
Humans ; Neurosecretory Systems/immunology* ; Spondylosis/etiology* ; Vertebral Artery/immunology* ; Stress, Psychological/complications* ; Chronic Disease

Strangles,caused by Streptococcus equi subsp.equi,remains one of the most prevalent and high-incidence infectious diseases in intensive donkey farms,posing a significant threat to the healthy development of the donkey industry.Vaccination serves as an effective measure for the pre-vention and control of the disease,however,there is currently no attenuated vaccine against this disease in China.To provide a candidate strain for the development of a live attenuated strangles vaccine,this study focused on a wild-type S.equi subsp.equi strain isolated from donkeys.Using homologous recombination gene knockout technology,the aroA gene(encoding 5-enolpyru-vylshikimate-3-phosphate synthase)and the sag A gene(encoding the precursor of streptolysin S toxin)were sequentially deleted to construct a double-gene-deletion strain(ΔsagA/aroA).The virulence and key biological characteristics of the mutant strain were systematically evaluated.TheΔsagA/aroA strain was successfully generated,exhibiting complete loss of hemolytic activity and maintaining stable genetic inheritance over 60 consecutive passages.Electron microscopy revealed that the mutant retained morphological characteristics compared to the wild-type strain,and its growth rate was significantly slower(P＜0.000 1).Virulence assessment using a challenge dose of 1× 105 CFU/0.2 mL(the minimum fully lethal dose of the wild-type strain)demonstrated markedly attenuated virulence in the mutant.Immunization trials with 1 ×104 CFU/0.2 mL of theΔsagA/aroA strain revealed a increase in ELISA antibody titers by day 7 post-vaccination,and higher levels at days 14 and 21.Notably,antibody levels in the experimental group were significant-ly higher than those in the control group(P＜0.000 1).These findings confirm that the double-gene-deletion strain S.equi subsp.equi ΔsagA/aroA exhibits reduced virulence while retaining im-munogenicity,which suggested it can be used as a promising candidate strain for further develop-ment of a live attenuated strangles vaccine.

Objective:To construct a prediction model for the risk of sarcopenia in middle-aged and elderly patients with knee osteoarthritis (KOA) based on machine learning, and to provide a basis for carrying out the prevention of sarcopenia in patients with KOA.Methods:Clinical data of KOA patients from three tertiary hospitals in Guangdong Province were collected between December 2023 and September 2024 using a convenience sampling method. The data were randomly split into training and test sets at an 8:2 ratio, with the occurrence of sarcopenia as the outcome variable. Risk prediction models for sarcopenia were constructed using eight machine learning algorithms: logistic regression, K-nearest neighbors, support vector machine, decision tree, neural network, random forest, gradient boosting machine (GBM), and eXtreme gradient boosting. Model performance was evaluated based on metrics including the area under the receiver operating characteristic curve (AUC), accuracy, precision, sensitivity, specificity, and F1 score. The optimal model was selected, and feature importance was visualized using the Shapley Additive exPlanations (SHAP) method.Results:Data from 640 KOA patients were analyzed, 143 males and 497 females, (67.51± 7.72) years, with 136 cases (21.25%) developing sarcopenia. All eight prediction models showed high AUC values, with the GBM model demonstrating the best performance. Its metrics included an AUC of 0.926 (95% CI 0.874 - 0.965), accuracy of 0.852, precision of 0.611, sensitivity of 0.815, specificity of 0.861, and F1 score of 0.698. SHAP analysis identified body mass index, calf circumference, body fat percentage, WOMAC score, and age as the most important predictive features. Conclusions:The GBM-based risk prediction model for sarcopenia in middle- aged and elderly KOA patients demonstrated optimal performance, enabling healthcare professionals to accurately and promptly identify high-risk groups among these patients and to develop effective, evidence-based intervention strategies.

Strangles,caused by Streptococcus equi subsp.equi,remains one of the most prevalent and high-incidence infectious diseases in intensive donkey farms,posing a significant threat to the healthy development of the donkey industry.Vaccination serves as an effective measure for the pre-vention and control of the disease,however,there is currently no attenuated vaccine against this disease in China.To provide a candidate strain for the development of a live attenuated strangles vaccine,this study focused on a wild-type S.equi subsp.equi strain isolated from donkeys.Using homologous recombination gene knockout technology,the aroA gene(encoding 5-enolpyru-vylshikimate-3-phosphate synthase)and the sag A gene(encoding the precursor of streptolysin S toxin)were sequentially deleted to construct a double-gene-deletion strain(ΔsagA/aroA).The virulence and key biological characteristics of the mutant strain were systematically evaluated.TheΔsagA/aroA strain was successfully generated,exhibiting complete loss of hemolytic activity and maintaining stable genetic inheritance over 60 consecutive passages.Electron microscopy revealed that the mutant retained morphological characteristics compared to the wild-type strain,and its growth rate was significantly slower(P＜0.000 1).Virulence assessment using a challenge dose of 1× 105 CFU/0.2 mL(the minimum fully lethal dose of the wild-type strain)demonstrated markedly attenuated virulence in the mutant.Immunization trials with 1 ×104 CFU/0.2 mL of theΔsagA/aroA strain revealed a increase in ELISA antibody titers by day 7 post-vaccination,and higher levels at days 14 and 21.Notably,antibody levels in the experimental group were significant-ly higher than those in the control group(P＜0.000 1).These findings confirm that the double-gene-deletion strain S.equi subsp.equi ΔsagA/aroA exhibits reduced virulence while retaining im-munogenicity,which suggested it can be used as a promising candidate strain for further develop-ment of a live attenuated strangles vaccine.

Objective:To construct a prediction model for the risk of sarcopenia in middle-aged and elderly patients with knee osteoarthritis (KOA) based on machine learning, and to provide a basis for carrying out the prevention of sarcopenia in patients with KOA.Methods:Clinical data of KOA patients from three tertiary hospitals in Guangdong Province were collected between December 2023 and September 2024 using a convenience sampling method. The data were randomly split into training and test sets at an 8:2 ratio, with the occurrence of sarcopenia as the outcome variable. Risk prediction models for sarcopenia were constructed using eight machine learning algorithms: logistic regression, K-nearest neighbors, support vector machine, decision tree, neural network, random forest, gradient boosting machine (GBM), and eXtreme gradient boosting. Model performance was evaluated based on metrics including the area under the receiver operating characteristic curve (AUC), accuracy, precision, sensitivity, specificity, and F1 score. The optimal model was selected, and feature importance was visualized using the Shapley Additive exPlanations (SHAP) method.Results:Data from 640 KOA patients were analyzed, 143 males and 497 females, (67.51± 7.72) years, with 136 cases (21.25%) developing sarcopenia. All eight prediction models showed high AUC values, with the GBM model demonstrating the best performance. Its metrics included an AUC of 0.926 (95% CI 0.874 - 0.965), accuracy of 0.852, precision of 0.611, sensitivity of 0.815, specificity of 0.861, and F1 score of 0.698. SHAP analysis identified body mass index, calf circumference, body fat percentage, WOMAC score, and age as the most important predictive features. Conclusions:The GBM-based risk prediction model for sarcopenia in middle- aged and elderly KOA patients demonstrated optimal performance, enabling healthcare professionals to accurately and promptly identify high-risk groups among these patients and to develop effective, evidence-based intervention strategies.

Objectives:To explore the effects of interatrial shunt on cardiac function and clinical prognosis of patients with heart failure with reduced ejection fraction(HFrEF). Methods:This study was a prospective single-arm study.From December 2021 to December 2022,15 consecutive patients with HFrEF from Beijing Anzhen Hospital were enrolled in this study.Interatrial shunt was performed with a D-Shant atrial shunt device.Right heart catheterization was performed before and immediately after device implantation,pulmonary capillary wedge pressure(PCWP),mean right atrial pressure(RAP),interatrial gradient pressure,mean pulmonary artery pressure,total pulmonary resistance(TPR),pulmonary vascular resistance(PVR),cardiac index(CI),and pulmonary/systemic blood flow ratio(Qp/Qs)were measured.Patients were followed-up for 12 months after procedure,changes in cardiac structure and function were evaluated by echocardiography.NYHA classification,6-minute walking distance(6MWD),and Kansas City cardiomyopathy questionnaire(KCCQ)were observed.All-cause mortality and rehospitalization for heart failure served as clinical endpoints. Results:Interatrial shunt procedure was successful in all patients.Compared with preoperative value,PCWP,interatrial gradient pressure,mean pulmonary artery pressure,and TPR were significantly decreased,while Qp/Qs was significantly increased immediately after procedure(all P<0.01).There were no significant changes in RAP,PVR,and CI post procedure(all P>0.05).There were no significant differences in shunt size,shunt velocity,and shunt pressure difference between postoperative immediately and at 12-months follow-up(all P>0.05).At 12 months,left ventricular ejection fraction was significantly higher than baseline level(P<0.05),and there were no significant changes in right atrial diameter and right ventricular fractional area change(both P>0.05).Compared with preoperative status,NYHA classification was improved,KCCQ score was increased,and the number of patients with 6MWD>450 m was increased at 12 months(all P<0.05).N-terminal pro-B-type natriuretic peptide value was significantly decreased at 12 months(P<0.05).No patient died during the 12-months follow-up period,and there were no device-related adverse events.Two patients experienced hospital readmission for heart failure. Conclusions:Implantation of interatrial shunt device could effectively improve hemodynamic parameters in patients with HFrEF and is related to significantly improved cardiac function at 12-months follow-up.

Traumatic fractures and stress fractures are common orthopedic diseases,and there is great potential in researching bone turnover,repair,and promotion of fracture healing.Basic medical experiments often use animal models of long bone fractures in limbs to study the mechanisms of various interventions on fracture healing.Fracture healing is a complex process influenced by multiple factors and involves multiple molecules and pathways.Therefore,to explore the mechanisms more deeply,accelerate the translation of results,and improve the clinical efficacy,it is particularly important to choose the appropriate animal fracture modeling methods in experimental research.Based on this,this paper conducts a literature review of animal species and modeling methods commonly used for long bone fracture models in experimental research.It summarizes five methods:bone defect method,physical impact method,mechanical bending method,open osteotomy method,and drilling method.A side-by-side comparison of their advantages,disadvantages,and scope of application is made,aiming to provide suitable fracture models for studyingthe mechanisms of fracture healing interventions.

【Objective】 To investigate the correlation between heart rate variability (HRV) and the degree of nervousness before blood donation. 【Methods】 The psychological state of 253 blood donors before blood donation was assessed by the self-rating anxiety scale (SAS) and the degree of nervousness and their HRV were measured. The correlation between the SAS score, the degree of nervousness and the HRV parameters was analyzed, and the differences were compared among different types of donors by multivariate linear regression. 【Results】 A total of 247 blood donors were included in the study. Five HRV parameters in blood donors aged 18-24 were higher than in those aged 25 years and above(all P<0.05), and the anxiety level was higher in female donors(SAS score 41-46) than in males(SAS score 35-43)(P<0.001); the pre-donation SAS score was consistent with the assessment of the tension level (r=0.970, P<0.001); the pre-donation tension level and the SAS score were all significantly negatively correlated with VLF in HRV parameters(r=0.179, P=0.005), and the associations were independent of confounders such as age, body mass index and gender (P<0.05). 【Conclusion】 Compared with SAS and tension assessment, HRV is more objective, and can be used as one of the tests for assessing the tension level of blood donors. The inclusion of HRV in the routine screening of blood donors deserves further study for its application in assessing the anxiety level of blood donors before blood donation, identifying people prone to blood donation-related vasovagal reaction (DRVR), preventing and reducing the risk of DRVR, and improving the safety of blood donation.

Objective:To investigate the diagnostic value of urine pH, serum uric acid and related clinical indicators in the diagnosis of urinary infection stones, and to construct a prediction nomogram.Methods:The clinical data of 432 patients with urinary calculi admitted to Xuzhou Central Hospital from August 2018 to November 2023 were retrospectively analyzed. The study included 289 males and 143 females, with an average age of (52.72±13.46) years old. Among the patients, there were 98 cases of hypertension, 67 cases of diabetes, and 100 cases of recurrent calculi. Kidney stones were present in 152 cases, ureteral stones in 242 cases, and bladder stones in 38 cases. Urine bacterial culture yielded positive results in 97 cases. According to the results of postoperative stone composition analysis, the two groups were categorized as infection and no-infection stone groups, and the differences in general data between the two groups were compared. Univariate and multivariate logistic regression analysis were conducted to assess the diagnostic value of urine pH, serum uric acid, and related clinical indicators for urinary infection stones. Receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to evaluate the clinical significance of urine pH, serum uric acid, and combined indexes in preoperatively diagnosing urinary infection stones, as well as constructing a nomogram prediction model.Results:There were 127 cases of infection stones and 305 cases of no-infection stones. The infection stone group exhibited a higher urine pH value [7.0(6.5, 7.5) vs. 6.0(5.5, 6.5), P<0.001], lower serum uric acid levels [(301.38±70.12) vs. (358.88±88.99) μmol/L, P<0.001], a higher proportion of females [55.1%(70/127) vs. 23.9%(73/305), P<0.001], younger age [(48.36±14.83)vs. (53.12±12.61)years old, P<0.001], a higher proportion of recurrence stones [34.6 %(44/127) vs. 18.4%(56/305), P<0.001], and a higher rate of positive urine bacteria culture[29.9%(38/127)vs. 19.3%(59/305), P=0.016]and nitrite test results [18.9%(24/127)vs. 6.3%(19/305), P <0.001]. Univariate logistic regression analysis revealed that urine pH value, serum uric acid levels, gender, age, recurrent stones, urine bacterial culture, and urine nitrite were associated with urinary infection stones ( P< 0.05). Multivariate logistic regression analysis revealed that urine pH value ( OR= 4.836, 95% CI 3.342-6.997), female gender( OR=2.320, 95% CI 1.286-4.186), recurrent stones ( OR=2.225, 95% CI 1.208-4.101), positive urine bacterial culture ( OR=2.061, 95% CI 1.094-3.883), serum uric acid ( OR=0.992, 95% CI 0.949-0.989), age ( OR=0.969, 95% CI 0.949-0.990) were independent risk factors for urinary infection stones ( P<0.05). The combined diagnostic value of six indicators was the highest, with an AUC of 0.874 (95% CI 0.837-0.911). Following this, urine pH exhibited an AUC of 0.818 (95% CI 0.778-0.858), while serum uric acid had an AUC of 0.704 (95% CI 0.652-0.756). The nomogram model was successfully constructed based on the six indicators. The mean AUC of the ROC curve after 1 000 resamples of the Bootstrap method was 0.864 (95% CI 0.828-0.900), and the calibration curve showed that the predicted curve fit the ideal curve well, with a mean absolute error of 0.005 and a Hosmer-Lemeshow test of P>0.05. Clinical decision curve analysis (DCA) showed that the model had a higher net clinical benefit when the model had a threshold probability value≥0.01. Conclusions:Urine pH and serum uric acid are closely related to urinary infection stones. A nomogram model combining these factors with gender, age, recurrent stones, and urine culture results can effectively predict the probability of infection-related stones, providing significant clinical value.