ObjectiveTo establish an animal model of atrial fibrillation（AF） that accurately reflects the phlegm-heat and blood stasis（TRYZ） pathogenesis in traditional Chinese medicine. MethodsForty SPF-grade SD rats were randomly assigned using a random number table to the following groups：the control group， the TRYZ+AF group，the AF group and the TRYZ group， with ten rats in each group. The TRYZ+AF and TRYZ groups underwent a high-fat diet combined with intraperitoneal lipopolysaccharide（LPS） injection to simulate the pathological alterations of TRYZ syndrome. Groups TRYZ+AF and AF were induced with acetylcholine-calcium chloride（Ach-CaCl₂） via caudal vein injection to induce AF. The control group received no intervention and was maintained under normal conditions. The modeling period lasted 3 weeks. Electrocardiography was used to assess AF episodes and duration， echocardiography evaluated left atrial dimensions and cardiac function， fully automated biochemical analyzer measured the levels of total cholesterol（TC）， triglycerides（TG）， high-density lipoprotein cholesterol（HDL-C） and low-density lipoprotein cholesterol（LDL-C）， hemoreometer analyzed the whole blood viscosity， plasma viscosity， and whole blood reduced viscosity， a coagulation analyzer assessed prothrombin time（PT）， activated partial thromboplastin time（APTT）， thrombin time（TT）， and fibrinogen（FIB）， enzyme-linked immunosorbent assay（ELISA） was used to determine the levels of C-reactive protein（CRP）， interleukin（IL）-1β， IL-6， IL-17， tumour necrosis factor（TNF）-α， matrix metalloproteinase-9（MMP-9）， galectin-3（Gal-3）， Collagen Ⅰ， and α-smooth muscle actin（α-SMA）. Hematoxylin-eosin（HE） staining and Masson's trichrome staining were used to analyze pathological changes in atrial myocardium， Western blot was employed to detect MMP-9， Collagen Ⅰ and α-SMA protein expression in myocardial tissue， real-time quantitative polymerase chain reaction（Real-time PCR） evaluated fibrous factor gene expression levels. Changes in the TRYZ syndrome were assessed via body weight， tongue color［red（R）， green（G）， and blue（B）］， and rectal temperature. Ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was employed to detect differential metabolites between the control group and the TRYZ+AF group. ResultsFollowing three weeks of sustained modeling， compared with the control group， rats in the TRYZ+AF and the TRYZ groups exhibited reduced body weight， dry faeces， elevated rectal temperature， dark red tongue， decreased RGB values on the tongue surface， and markedly elevated TC and LDL-C levels（P<0.05， P<0.01）. The TRYZ+AF， TRYZ， and AF groups exhibited significantly decreased TT， APTT and PT， along with markedly elevated whole blood viscosity and FIB（P<0.05， P<0.01）. Rats in the TRYZ+AF and AF groups exhibited AF rhythm， markedly decreased heart rate， prolonged RR intervals， enlarged left atrium， and significantly reduced ejection fraction and shortening fraction（P<0.05， P<0.01）. Serum levels of CRP， IL-1β， IL-6， IL-17， TNF-α， MMP-9， Gal-3， Collagen Ⅰ， and α-SMA were elevated in rats from the TRYZ+AF， TRYZ， and AF groups compared to the control group， with the most pronounced increase observed in the TRYZ+AF group（P<0.05， P<0.01）. Histopathology revealed that the collagen fiber deposition in the atrial of rats in the TRYZ+AF， TRYZ and AF groups was higher than that in the control group（P<0.05， P<0.01）. Western blot and Real-time PCR results further demonstrated that the protein and mRNA expression levels of MMP-9， Collagen Ⅰ and α-SMA in the myocardial tissue of the TRYZ+AF group were higher than those in the other three groups（P<0.05， P<0.01）. Metabolomic analysis revealed 173 differentially expressed metabolites in the TRYZ+AF group and the control group， primarily enriched in pathways such as glycerophospholipid metabolism and glycolysis/gluconeogenesis. ConclusionThis study successfully establishes a rat model of AF integrated with the TRYZ syndrome， demonstrating the pathological process where the interactions of phlegm， heat and stasis jointly trigger tremor， this provides a reliable experimental tool for in-depth research into the biological basis of this disease syndrome.

OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

Objectives: . This study aimed to explore the role of the Pcdh15 gene in hearing maintenance and to examine the effects of its deficiency on cochlear structure, cochlear function, and hearing loss in mice. Methods: . CRISPR/Cas9 technology was used to generate Pcdh15 knockout (KO) mice. Auditory function was evaluated using hearing tests, while histological approaches were employed to assess morphological changes in cochlear hair cells and spiral ganglion neurons (SGNs). RNA sequencing (RNA-seq) was performed on cochlear tissue from postnatal day 18 (P18) wild-type (WT) and Pcdh15 KO mice to identify differentially expressed genes (DEGs). These DEGs were subjected to functional annotation and pathway analysis, with particular emphasis on oxidative phosphorylation (OXPHOS). Reactive oxygen species (ROS) levels were quantified using flow cytometry and DCFH-DA assays. Results: . Pcdh15 KO mice exhibited progressive sensorineural hearing loss, which worsened to profound deafness by P18. Notably, cochlear hair cells and SGNs showed substantial loss and pronounced morphological abnormalities, particularly within the basal high-frequency region. RNA-seq analysis identified 1,359 DEGs, including 1,024 downregulated and 335 upregulated genes. Pathway analysis indicated that Pcdh15 deficiency was associated with inhibition of the OXPHOS pathway, potentially disrupting mitochondrial respiratory chain complexes I, III, IV, and V and thereby impairing energy production and ATP metabolism. In addition, early-stage cochleae from KO mice demonstrated elevated ROS levels and increased oxidative stress, suggesting that redox imbalance may contribute to hearing damage. Conclusion . Pcdh15 plays a critical role in hearing maintenance. Its deficiency is associated with severe hearing loss and marked cochlear abnormalities, which are linked to inhibition of OXPHOS, disruption of energy metabolism, and exacerbation of oxidative stress. Together, these findings provide new insights into the mechanisms underlying hearing loss and suggest potential targets for therapeutic intervention.

ObjectiveTo construct a prediction model for high responsiveness to short-term aerobic training in patients with Parkinson's disease (PD) based on dual-task gait assessment, and to provide evidence for identifying individuals who are most likely to benefit from such interventions. MethodsA total of 42 patients with PD who visited the outpatient clinic of Tianjin Huanhu Hospital between August 29, 2023 and December 19, 2024 were enrolled. All participants completed a 4-week home-based aerobic cycling training program and underwent dual-task gait assessments pre- and post-training. Patients were classified into high-response group (n = 12) and low-response group (n = 30) according to whether the improvement in gait speed reached the minimal clinically important difference of 0.1 m/s. The clinical validity of this grouping was verified by comparing differences in cardiopulmonary exercise testing parameters and dual-task gait indicators between the two groups pre- and post-training. Based on baseline characteristics, Firth's penalized maximum likelihood logistic regression was applied to construct a predictive model for high responsiveness, and the discriminative performance of the model was assessed preliminarily. ResultsThe high-response group showed significantly greater improvement in gait speed, step length, cadence and the anaerobic threshold to maximal oxygen uptake ratio after training compared with the low-response group (P < 0.05), confirming the clinical validity of the grouping. The baseline anaerobic threshold to maximal oxygen uptake ratio (OR = 3.348), body mass index (OR = 2.229) and age (OR = 0.428) demonstrated certain discriminative ability in the present sample. The area under the receiver operating characteristic curve was 0.831, with an overall prediction accuracy of 81.0%, specificity of 83.3% and sensitivity of 75.0%. Robustness of the model was confirmed via internal validation using the Bootstrap method, which suggested that the results were informative, but further validation was still required. ConclusionThe anaerobic threshold/maximal oxygen uptake ratio, body mass index and age may predict the response to short-term aerobic training in patients with PD.

ObjectiveBased on literature data mining， this study explores the modeling elements of diarrhea-predominant irritable bowel syndrome （IBS-D） animal models in China and abroad， providing references and suggestions for improving modeling methods and evaluation indicators. MethodsRelevant literature on IBS-D animal experiments from 2014 to 2024 was retrieved through computer searches in databases such as China National Knowledge Infrastructure （CNKI）， Wanfang Data， VIP， Chinese Medical Journals Full-text Database， and PubMed. Information on experimental animal species， gender， body weight， modeling methods， modeling periods， intervention controls， modeling standards， and detection indicators was organized. Microsoft Excel 2021 software was used to establish a database and perform statistical analysis to examine the characteristics of IBS-D animal models. ResultsA total of 398 articles that met the inclusion criteria were reviewed. The IBS-D animal models were predominantly established using SD rats， Wistar rats， and C57BL/6 mice. Male animals were more commonly used， with rats typically aged 6-8 weeks and mice aged 4-6 weeks. In terms of interventions， piverium bromide was the main Western medicine， Tongxieyaofang was the primary Chinese medicine， and electroacupuncture was the primary acupuncture method. Among the modeling methods， the multi-factor combined composite modeling approach was the most common. Modeling periods were mainly concentrated between 1-14 days and 15-30 days. The success criteria for modeling were mainly evaluated based on the animal's general condition， fecal appearance， visceral sensitivity， gastrointestinal motility， behavior， and pathology. Detection indicators included apparent indexes， pathological markers， biochemical indicators， oxidative stress， brain-gut peptides， neurotransmitters， inflammatory factors， immune function， intestinal permeability， autophagy， apoptosis， proteins related to relevant signaling pathways， intestinal microbiota and its metabolites， etc. ConclusionThere are various methods for establishing IBS-D animal models， but no unified and universally accepted method has been established. The operation of the same modeling methods and the evaluation standards of the models vary across studies. Based on the results of data mining， the authors suggest that the multi-factor combined composite modeling approach most closely reflects the pathophysiological processes of IBS-D， better simulating the complex clinical symptoms of IBS-D patients， such as abdominal pain and diarrhea， and has a high degree of clinical relevance. This method is relatively recommended. While animal models in general align with Western medicine standards， models incorporating traditional Chinese medicine （TCM） syndromes are relatively few. Therefore， one of the future directions for research is to establish IBS-D animal models that meet the combined clinical disease and syndrome requirements of both Western and Chinese medicine.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Lung cancer （LC） is a significant global public health issue， with both its incidence and mortality rates ranking among the highest worldwide. The age-standardized incidence and mortality rates are increasing annually， posing a serious threat to the life and health of LC patients. Radical surgical resection is the primary treatment for malignant lung tumors. However， postoperative multidimensional functional impairments， including respiratory， mucosal， and psychological functions， are common. These impairments not only reduce patients' quality of life and affect their treatment tolerance and duration， but also negatively correlate with prognosis， facilitating disease recurrence and metastasis. At present， postoperative functional dysfunction after LC surgery remains a key clinical challenge that urgently needs to be addressed. There is a lack of standardized and regulated postoperative rehabilitation treatment management and traditional Chinese medicine （TCM） differentiation and treatment strategies for LC. Focusing on the core underlying pathogenesis of "Qi sinking" after LC surgery， and guided by the classical TCM theory of "lungs governing Qi"， this study， based on the core concept of the "five perspectives on treatment" theory， innovatively proposes the respiratory dysfunction as the core pathogenesis of "Qi sinking in the chest" during the rapid rehabilitation phase， mucosal dysfunction as the core pathogenesis of "Yin deficiency and Qi sinking" during the postoperative adjuvant treatment phase， and the psychological dysfunction as the core pathogenesis of "Qi sinking with emotional constraint" during the consolidation phase. Accordingly， stage-specific dynamic functional protection strategies are constructed. In the rapid rehabilitation phase， the strategy emphasizes tonifying Qi and uplifting sinking Qi， with differentiation and treatment based on the principle of ''descending before ascending''. In the adjuvant treatment phase， the approach focuses on nourishing Yin and uplifting Qi， with prescription combinations that integrate unblocking and tonification. In the consolidation phase， the strategy aims to resolve constraint and uplift Qi， with clinical treatment emphasizing a combination of dynamic and static methods. At each stage of functional rehabilitation， clinical differentiation and treatment should support healthy Qi and eliminate pathogenic factors simultaneously. This study is the first to propose the concept of postoperative functional protection in TCM， offering a new approach for TCM differentiation and treatment in the full-cycle， stage-based， and dynamic protection of postoperative function in LC patients. It is expected to contribute to the construction and development of an integrated TCM-Western medicine comprehensive program for cancer prevention and treatment in China.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective To investigate the predictive value of preoperative combined detection of neutrophil-to-lymphocyte ratio (NLR) and prothrombin time-international normalized ratio to albumin ratio (PTAR) for early abdominal infection after liver transplantation. Methods Clinical data of 287 recipients who underwent liver transplantation at the Liver Transplant Center of Beijing Friendship Hospital, Affiliated to Capital Medical University, from January 2020 to April 2024 were retrospectively analyzed. The patients were divided into infection group (n=60) and non-infection group (n=227) based on whether abdominal infection occurred within 30 days after surgery. The distribution characteristics of pathogens and infection time in infected patients were analyzed. Spearman correlation analysis was used to assess the correlation between NLR, PTAR, Child-Pugh score and preoperative model for end-stage liver disease (MELD) score. Univariate and multivariate logistic regression analyses were performed to identify risk factors for abdominal infection. Receiver operating characteristic (ROC) curves were plotted for NLR, PTAR, and the combined prediction model to evaluate their predictive efficacy for abdominal infection after liver transplantation. Based on the cutoff value of the combined model, recipients were divided into low-risk and high-risk groups, and Kaplan-Meier analysis was used to compare the cumulative incidence of abdominal infection within 30 days after surgery between the two groups. Results Among the 287 recipients who underwent liver transplantation, 60 developed bacterial or fungal abdominal infections postoperatively. A total of 86 strains were isolated from infected patients, with Gram-negative bacteria accounting for 58%, Gram-positive bacteria for 36%, and fungi for 5%. Preoperative NLR and PTAR were positively correlated with Child-Pugh and MELD scores (all 1 > r > 0, P < 0.05). Logistic regression analysis showed that preoperative NLR, preoperative PTAR, postoperative ICU stay duration and postoperative biliary leakage were risk factors for abdominal infection within 30 days after surgery. The area under the curve (AUC) for NLR, PTAR, Child-Pugh score and MELD score were 0.771, 0.735, 0.650 and 0.741, respectively. The AUC for the combined NLR and PTAR prediction model was 0.824 (95% confidence interval: 0.763-0.885, P < 0.001), with a cutoff value of 0.168. Kaplan-Meier analysis showed that the cumulative incidence of abdominal infection within 30 days after surgery was lower in the low-risk group than in the high-risk group, with statistically significant difference (P < 0.001). Conclusions Preoperative NLR and PTAR are independent risk factors for abdominal infection within 30 days after liver transplantation. The combined prediction model of NLR and PTAR may effectively identify high-risk recipients for early abdominal infection after liver transplantation, providing basis for early intervention.