ObjectiveTo investigate the independent predictive factors for 90-day mortality in patients with acute-on-chronic liver failure （ACLF）， to establish a risk predictive model， and to assess its predictive efficacy in comparison with MELD， MELD-Na， MELD 3.0， and COSSH-ACLF Ⅱ. MethodsA retrospective analysis was performed for the clinical data of 394 patients with ACLF who were admitted to The Affiliated Hospital of Inner Mongolia Medical University and Hohhot Second Hospital from July 2018 to July 2024， and general information and laboratory markers on admission were collected from all patients. The independent-samples t test or the Mann-Whitney U test was used for comparison of quantitative data between two groups， and the chi-square test or the adjusted chi-square test was used for comparison of qualitative data between two groups. The LASSO regression analysis was used to identify related variables， and the multivariate logistic regression analysis was used to establish a predictive model and generate a nomogram. The receiver operating characteristic （ROC） curve， the area under the ROC curve （AUC）， calibration curve， and clinical decision curve were used to assess the performance of the model. ResultsA total of 394 patients with ACLF were included in this study， with 136 patients in the training set， 58 in the internal validation set， and 200 in the external validation set. The cohort had a mean age of 52.9±11.7 years， among whom male patients accounted for 72.84% （287/394）， the patients with HBV infection accounted for 22.33% （88/394）， the patients with alcohol-related causes accounted for 45.94% （181/394）， and the patients with other causes （including drug-induced and autoimmune diseases） accounted for 31.73% （125/394）. The overall 90-day mortality rate was 27.41% （108/394）. The multivariate logistic regression analysis showed that diabetes （odds ratio ［OR］= 5.831， 95% confidence interval ［CI］： 1.587 — 21.424， P=0.008）， cystatin C （Cys-C） （OR=2.984， 95%CI： 1.501 — 5.933， P=0.002）， and spontaneous peritonitis （SBP） （OR=5.692， 95%CI： 2.150 — 15.071， P<0.001） were independent risk factors， and a nomogram was generated based on these factors. This model had an AUC of 0.836 in the training set， 0.881 in the internal validation set， and 0.878 in the external validation set， showing a good discriminatory ability. The calibration curve showed a good degree of fitting， with a relatively high net clinical benefit. The subgroup analysis based on etiology showed that the model had an AUC of 0.850 in the patients with HBV infection， 0.858 in the patients with alcohol-induced ACLF， and 0.908 in the patients with other etiologies， indicating that the model had a good discriminatory ability across the populations with different etiologies. Compared with traditional scores， the model （AUC=0.836） had a significantly better predictive value than MELD （AUC=0.619， Z=3.197， P=0.001）， MELD-Na （AUC=0.651， Z=2.998， P=0.003）， MELD 3.0 （AUC=0.601， Z=3.682， P<0.001）， and COSSH-ACLF Ⅱ （AUC=0.719， Z=2.396， P=0.017） alone. ConclusionDiabetes， SBP， and Cys-C are independent risk factors for 90-day mortality in patients with ACLF. Compared with MELD， MELD-Na， MELD 3.0， and COSSH-ACLF Ⅱ scores， this model has a higher predictive value for 90-day prognosis in patients with ACLF and is suitable for patients with ACLF caused by various etiologies.

Objective To analyze the epidemiological characteristics and disease burden of malignant tumors in Shijiazhuang in 2021. Methods Based on data from the Shijiazhuang City Cancer Registry, incidence and mortality indicators for malignant tumors were calculated, including crude rates, age-standardized rates (using Chinese and world standard populations), and the cumulative rate (0−74 years old), to describe the epidemiological profile. The disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) were calculated to estimate the disease burden of malignant tumors. Results In 2021, a total of 13250 new cancer cases were recorded. The crude incidence rate was 275.50/10⁵, the ASR China was 177.17/10⁵, the ASR world was 172.11/10⁵, and the cumulative rate (0–74 years old) was17.77%. The age-specific incidence of malignant tumors reached its peak in the age group of 80–84 years old. A total of 7165 deaths were noted, and the crude mortality rate was 148.98/10⁵. The ASR China was 85.13/10⁵, the ASR world was 84.52/10⁵, and the cumulative rate (0–74 years old) was 9.49%. The age-specific mortality of malignant tumors reached its peak in the age group of above 85 years old. Lung cancer and breast cancer were the most common malignant tumors in males and females. The DALYs of malignant tumors were 87725.29 person-years, and the DALY rate was 18.24‰. YLL was 85392.09 person-years (97.34%), and YLD was 2333.19 person-years (2.66%). Lung cancer had the heaviest disease burden with DALY of 22687.12 person-years, accounting for 25.86% of all malignant tumors, followed by gastric, liver, colorectal and esophageal cancers. Conclusion Cancers of the lung, liver, female breast, stomach, and colorectum are the major health threats in Shijiazhuang. Malignant tumor brings heavy burden to residents of Shijiazhuang city. To decrease the disease burden of cancer, scholars should pay more attention, and implement preventive measures early.

Zhigancao Tang， derived from the Treatise on Cold Damage，is a classic and renowned formula for treating "intermittent and irregular pulse， and palpitations of the heart". It has an exquisite formulation. By replenishing Qi， nourishing Yin， activating Yang， and restoring the pulse， it achieves the dual supplementation of Yin and Yang， and the simultaneous treatment of Qi and blood. With the practical expansion by practitioners over successive dynasties， the application scope of this formula has been continuously expanding， extending from traditional cardiovascular diseases to diseases of multiple systems， fully reflecting the theoretical characteristics of traditional Chinese medicine （TCM） of "treating different diseases with the same method". Modern research shows that Zhigancao Tang not only has a remarkable curative effect on cardiovascular diseases but is also widely applied to diseases of the respiratory， nervous， digestive， endocrine， oncologic， gynecologic， and otorhinolaryngologic systems， demonstrating its interdisciplinary clinical application value. At the same time， research on the mechanism of action of Zhigancao Tang is also continuously deepening. The mechanisms by which it treats diseases involve multiple aspects， including anti-arrhythmic effects， myocardial protection， anti-fibrosis， antioxidative stress and anti‑inflammatory effects， regulation of glucose and lipid metabolism， enhancing hematopoietic function， and improving hemorheology. These mechanisms work synergistically to jointly regulate the physiological functions of the body and play a role in treating diseases. However， there are still some deficiencies in current research. For example， the sample size of some clinical trials is small， most of the mechanism studies are based on animal models or in vitro experiments， there is insufficient high-quality evidence from clinical trials， the composition of the compound formula is complex， and the pharmacodynamic material basis and the rules of compatibility still need to be deeply analyzed. By consulting relevant literature， this article systematically summarizes the modern clinical application and action mechanism of Zhigancao Tang， aiming to provide new ideas for its subsequent in-depth research and clinical application， promote the integrated development of classic TCM formulas and modern medicine， and further explore its great potential in clinical treatment.

Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Objective: To explore the impact of different blood donation scenarios on population characteristics and blood donation behaviors, and to provide a basis for precise blood donation recruitment. Methods: Eligible voluntary blood donors with complete records from four scenarios in Xi'an: medical institutions, cultural tourism SITES, commercial superstores, and blood centers. After a preliminary analysis of overall donor characteristics across the four scenarios, three core subgroups were defined based on scenarios and donor population differences: the medical subgroup (aged 30-39 years), the blood center subgroup (aged 30-39 years), and the cultural tourism and commercial superstore subgroup (aged 18-29 years). Baseline characteristics, blood donation behaviors, and blood test results were compared among the subgroups. Results: The blood donors in all four scenarios were mainly male, but the proportion of female donors in the medical scenario was the highest (26.4%, 8 878/33 634). In terms of age distribution, the cultural tourism and commercial superstore scenarios were dominated by donors aged 18-29, while the blood center and medical scenarios were dominated by those aged 30-39, with the highest proportion of donors over 40 in the medical scenario. The occupational and educational composition of blood donors in the blood center scenario spanned a wide range, exhibiting a clear bipolar distribution. Significant differences were observed in baseline characteristics, blood donation behaviors, and blood test results among the three core subgroups (P<0.001). The medical subgroup was mainly composed of enterprise/industrial workers and married individuals, with high proportions of first-time blood donors, and the highest unqualified rate of infectious indicators (2.0%, 274/13 509). The cultural tourism and commercial superstore subgroup was mainly unmarried and students, featured high proportions of large-volume donations and evening donations, and had a relatively high unqualified rate for ALT (0.4%, 130/31 443). The blood center subgroup had a complex population structure, a high proportion of repeat blood donors (45.3%, 6449/14 225), and moderate results in all test indicators. Conclusion: There is an inherent correlation between the attributes of blood donation scenarios, population characteristics, and blood donation behaviors. The differences among the three core subgroups provide a clear basis for precise scenario operation. By constructing transformation channels between different scenarios and optimizing scenario-specific strategies, the structure of blood donors can be improved, thereby supporting the sustainable development of voluntary blood donation.

Objective: To investigate the correlation between color parameters (L^*, a^*, b^*, Eab^*) and the contents of reducing sugars, total polysaccharides, total oligosaccharides, as well as four saccharides (fructose, glucose, sucrose, and kestose) during the nine cycles of steaming and sun-drying processing of Polygonatum kingianum, and to preliminarily explore the optimal processing duration.
Methods: The color changes were objectively evaluated using a colorimeter. The anthrone-sulfuric acid method was employed to determine total polysaccharides and oligosaccharides. The 3,5-dinitrosalicylic acid (DNS) colorimetric method was used to measure total reducing sugar content. High-performance liquid chromatography coupled with charged aerosol detection (HPLC-CAD) was applied for quantitative analysis of fructose, glucose, sucrose, and kestose. Multivariate statistical analysis was conducted to assess samples from different processing stages.
Results: Significant variations in color and component contents were observed across processing stages. The herbal pieces progressively darkened with increased processing cycles: brightness (L^*) and total color difference (Eab^*) initially decreased then stabilized, while a^* (red-green) and b^* (yellow-blue) values first increased then declined. Total polysaccharides and oligosaccharides showed overall decreasing trends, whereas reducing sugars initially increased before stabilizing. Fructose and glucose levels rose continuously, while sucrose and kestose decreased progressively, becoming undetectable after five cycles.
Conclusion: The chromatic alteration and saccharide composition of P. kingianum showed significant correlation with processing duration. Both total color difference (Eab^*) and reducing sugar content stabilized after four processing cycles (12 hours), suggesting that four cycles of steaming and sun-drying may represent the optimal processing duration.

Objective: To investigate the correlation between the color parameters (L^*, a^*, b^*, Eab^* values) of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques and the contents of 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucopyranoside, emodin, physcion, emodin-8-O-β-D-glucopyranoside, physcion-8-O-β-D-glucopyranoside.
Methods: The L^*, a^*, b^* and Eab^* values of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques were determined by spectrophotometer, and the contents of the five components were determined by high performance liquid chromatography. Secondly, SPSS 26.0 software and Simca 14.1 software were used to analyze the correlation.
Results: Through the hierarchical cluster analysis (HCA), it was found that the steamed samples and black bean steamed samples could be obviously divided into two categories: raw products and processed products. The processed products could be further divided into 2-8 h and 12-48 h. Pearson correlation analysis showed that the content of stilbene glycoside was significantly positively correlated with L^*, a^* and b^* values (P<0.01). The a^* value was significantly positively correlated with the content of emodin and physcion (P<0.01). Emodin-8-O-β-D-glucoside was positively correlated with L^* value and b^* value, while physcion-8-O-β-D-glucoside was negatively correlated with a^* value. Partial least squares discriminant analysis (PLS) showed that 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucoside (VIP=1.69) and emodin-8-O-β-D-glucoside (VIP=1.06) were the key variables affecting chromaticity characteristics (P<0.01).
Conclusion: The three processes of steaming, black bean steaming and black bean stewing are consistent in composition transformation and chromaticity variation, and stilbene glycoside can be used as a specific index component to characterize the processed color. Chromatic parameters can effectively reflect the processing progression and serve as quality monitoring indicators during production.

OBJECTIVE To investigate the stability and compatibility of butorphanol， nicardipine， urapidil， and tirofiban. METHODS A micro-infusion pump was used to simulate the infusion process. Samples were collected in real time from the needle tip at 0， 2， 4， 6， and 8 h after mixing of the four drugs. The appearance， pH， and number of insoluble particles were examined. The contents of butorphanol， nicardipine， urapidil， and tirofiban were determined using the ultra-high-performance liquid chromatography method. RESULTS Within 8 hours， all mixed solutions remained clear and transparent， with no visible turbidity， precipitation， color change， or gas generation. The pH fluctuation ranged from 0.02 to 0.09， both within 0.1 pH units. The number of insoluble particles ≥10 μm in size in each compatibility solution was ≤9， and the number of insoluble particles ≥25 μm was ≤2， meeting the requirements of the 2025 edition of the Chinese Pharmacopoeia （Volume Ⅳ）. The relative percentage contents of butorphanol， nicardipine， urapidil， and tirofiban at 8 hours after compatibility mixing ranged from 92.38% to 113.40%. CONCLUSIONS Within 8 hours under simulated clinical micro-infusion pump infusion conditions， the stability and compatibility of the mixed solution containing butorphanol， nicardipine， urapidil， and tirofiban were satisfactory.

OBJECTIVES: Global epidemiological data indicate that 20% to 30% of intensive care unit (ICU) sepsis patients progress to deep vein thrombosis (DVT) due to coagulopathy, with an associated mortality rate of 25% to 40%. Existing prognostic tools have limitations. This study aims to develop and validate nomogram and machine learning models to predict in-hospital mortality in sepsis patients with DVT and assess their clinical applicability. METHODS: This multicenter retrospective study drew on data from the Medical Information Mart for Intensive Care IV (MIMIC-IV; n=2 235), the eICU Collaborative Research Database (eICU-CRD; n=1 274), and the Patient Admission Dataset from the ICU of Third Xiangya Hospital, Central South University (CSU-XYS-ICU; n=107). MIMIC-IV was split into a training set (n=1 584) and internal validation set (n=651), with the remaining datasets used for external validation. Predictors were selected via least absolute shrinkage and selection operator (LASSO) regression and Bayesian Information Criterion (BIC), and a nomogram model was constructed. An extreme gradient boosting (XGBoost) algorithm was used to build the machine learning model. Model performance was assessed by the concordance index (C-index), calibration curves, Brier score, decision curve analysis (DCA), and net reclassification improvement index (NRI). RESULTS: Five key predictors, age [odds ratio (OR)=1.02, 95% CI 1.01 to 1.03, P<0.001], minimum activated partial thromboplastin (APTT; OR=1.09, 95% CI 1.08 to 1.11, P<0.001), maximum APTT (OR=1.01, 95% CI 1.00 to 1.01, P<0.001), maximum lactate (OR=1.56, 95% CI 1.39 to 1.75, P<0.001), and maximum serum creatinine (OR=2.03, 95% CI 1.79 to 2.30, P<0.001), were included in the nomogram. The model showed robust performance in internal validation (C-index=0.845, 95% CI 0.811 to 0.879) and external validation (eICU-CRD: C-index=0.827, 95% CI 0.800 to 0.854; CSU-XYS-ICU: C-index=0.779, 95% CI 0.687 to 0.871). Calibration curves indicated good agreement between predicted and observed outcomes (Brier score<0.25), and DCA confirmed clinical benefit. The XGBoost model achieved an area under the receiver operating characteristic curve (AUC) of 0.982 (95% CI 0.969 to 0.985) in the training set, but performance declined in external validation (eICU-CRD, AUC=0.825, 95% CI 0.817 to 0.861; CSU-XYS-ICU, AUC=0.766, 95% CI 0.700 to 0.873), though it remained above clinical thresholds. Net reclassification improvement was slightly lower for XGBoost compared with the nomogram (NRI=0.58). CONCLUSIONS Both the nomogram and XGBoost models effectively predict in-hospital mortality in sepsis patients with DVT. However, the nomogram offers superior generalizability and clinical usability. Its visual scoring system provides a quantitative tool for identifying high-risk patients and implementing individualized interventions.
Humans ; Sepsis/complications* ; Machine Learning ; Nomograms ; Venous Thrombosis/complications* ; Retrospective Studies ; Hospital Mortality ; Male ; Female ; Middle Aged ; Aged ; Intensive Care Units ; Prognosis ; Bayes Theorem