Objective: Patients with atherosclerotic cardiovascular disease (ASCVD) following percutaneous coronary intervention (PCI) are classified as very-high-risk individuals in cardiovascular disease (CVD) risk stratification. The distribution pattern of traditional Chinese medicine (TCM) syndromes in this patient population, as well as its association with blood lipid profiles and clinical prognosis, remains unclear. The present prospective cohort study aims to investigate these correlations, thereby providing insights to enrich the research fields. Methods: We enrolled consecutive patients with ASCVD who underwent PCI at the Integrated Cardiology Unit of China-Japan Friendship Hospital between September 1, 2020 and December 31, 2022. Demographics and clinical characteristics, signs and symptoms defining each TCM syndrome, and fasting venous blood samples were collected at baseline and follow up or upon major adverse cardiovascular events (MACEs). We analyzed the correlation between TCM syndromes, blood lipid profiles, and MACEs, and developed a new joint prognostic model incorporating both TCM syndromes and blood lipids using logistic regression. The analyses were based on detailed baseline and one-year follow-up data. Results: A per-protocol analysis was performed on 586 patients with complete data ultimately. During the one-year follow-up, 174 patients (29.69%) experienced a MACE. We performed statistical analyses on comorbidities, medication, and biochemical indicators across groups defined by TCM syndrome differentiation. When comparing different TCM syndromes, no significant differences were found in age, body mass index (BMI), history of revascularization, comorbidities, family history of CVD, smoking or drinking, or statin intensity (P > 0.05). Patients with intertwined phlegm and blood stasis syndrome exhibited significantly higher levels of total cholesterol (TC, 5.27 ± 1.18 mmol/L, P < 0.001), triglyceride (TG, 1.96 ± 1.33 mmol/L, P = 0.008), low-density lipoprotein cholesterol (LDL-C, 3.35 ± 0.79 mmol/L, P < 0.001), and high-density lipoprotein cholesterol (HDL-C, 1.24 ± 0.81 mmol/L, P < 0.001) compared with those with other TCM syndromes combined. A multivariable logistic regression model was constructed to predict MACEs. The model included TCM syndrome type [with intertwined phlegm and blood stasis as a predictor, adjusted odds ratio (OR) = 1.413, 95% confidence interval (CI): 0.517 – 3.864, P = 0.501], age (adjusted OR = 0.97, 95% CI: 0.955 – 1.001, P = 0.057), male gender (adjusted OR = 0.698, 95% CI: 0.416 – 1.170, P = 0.173), TC (adjusted OR = 1.004, 95% CI: 0.513 – 1.965, P = 0.990), and LDL-C (adjusted OR = 5.825, 95% CI: 2.214 – 15.326, P < 0.001). This model demonstrated good discriminatory ability for MACEs in post-PCI ASCVD patients [the area under the receiver operating characteristic (ROC) curve (AUC) = 0.865, 95% CI: 0.816 – 0.914]. Conclusion The intertwined phlegm and blood stasis TCM syndrome is associated with a distinct atherogenic lipid profile characterized by elevated levels of TC and LDL-C. The prognostic model that incorporates this TCM syndrome type along with conventional lipid parameters (TC and LDL-C) shows good discriminatory ability for predicting MACEs in ASCVD patients after PCI, underscoring the potential clinical utility of integrating TCM syndrome differentiation into CVD risk assessment.

Metabolic associated fatty liver disease （MAFLD） is a common chronic liver disease worldwide， and timely and precise intervention can delay disease progression and significantly reduce the risk of serious complications such as liver fibrosis， liver cirrhosis， and liver cancer. Although traditional liver biopsy combined with metabolic markers is the gold standard， it may cause complications such as pain and bleeding as an invasive examination， which has promoted scientific research to shift its focus to the construction of noninvasive assessment systems. In recent years， noninvasive diagnostic technologies based on multi-dimensional detection strategies have been continuously updated， including serological models， imaging techniques， and clinical algorithms. This article systematically reviews the screening methods for MAFLD during the fibrotic stages F1—F3， especially deep learning models based on artificial intelligence， in order to provide ideas for the early screening of MAFLD， as well as a scientific reference for optimizing disease management strategies.

OBJECTIVE To investigate the effects of total flavonoids of Drynariae Rhizoma （TFRD） on autophagy and apoptosis in LPS-induced chondrocytes via the regulation of the Notch1/hairy and enhancer of split 1 （Notch1/Hes1） signaling axis. METHODS Human chondrocyte cell line C28/I2 cells were cultured with 5 μg/mL LPS to esta blish in vitro inflammatory injury model. The cells were separated into normal control group， model group， TFRD group （200 μg/mL）， TFRD+peroxiredoxin 1 （Prdx1） small interfering RNA （si-Prdx1） group and TFRD+si-Prdx1 negative control （si-NC） group， with 6 replicate wells in each group. Cells were transfected with si-Prdx1 or si-NC for 24 hours， pretreated with TFRD for 2 hours， and then exposed to LPS， with a total culture duration of 48 hours. Apoptotic rate， the proportion of apoptotic cells， monodansylcadaverine （MDC） fluorescence intensity， as well as the contents of matrix metalloproteinase-13 （MMP-13）， a disintegrin and metalloproteinase with thrombospondin motifs 5 （ADAMTS5）， and cartilage oligomeric matrix protein （COMP） were measured. Additionally， the protein expression levels of X-linked inhibitor of apoptosis protein （XIAP）， poly（ADP-ribose） polymerase 1 （PARP1）， Beclin-1， microtubule-associated protein 1 light chain 3 Ⅱ/Ⅰ （LC3-Ⅱ/Ⅰ）， PTEN-induced putative kinase 1 （PINK1）， Notch1， Hes1， and Prdx1 were assessed. RESULTS Compared with model group， the apoptotic rate， the proportion of apoptotic cells， the contents of MMP-13 and ADAMTS5 as well as protein expressions of PARP1 were significantly decreased， while MDC fluorescence intensity， COMP content， protein expressions of XIAP， Beclin-1， LC3-Ⅱ/Ⅰ， PINK1， Notch1， Hes1 and Prdx1 were significantly increased （ P ＜0.05）. Compared with TFRD+si-NC group， the changes in the aforementioned indicators （except for Notch1 and Hes1） in the cells of the TFRD+si-Prdx1 group were significantly reversed （ P ＜0.05）. CONCLUSIONS TFRD may activate the Notch1/Hes1 signaling axis， and up-regulate the expression of the downstream target molecule Prdx1， thereby inhibiting LPS-induced chondrocyte apoptosis， promoting protective autophagy， and consequently improving cartilage metabolic homeostasis.

Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

During orthodontic treatment, clinical monitoring of patients is a crucial factor in determining treatment success. It aids in timely problem detection and resolution, ensuring adherence to the intended treatment plan. In recent years, digital technology has increasingly permeated orthodontic clinical diagnosis and treatment, facilitating clinical decision-making, treatment planning, and follow-up monitoring. This review summarizes recent advancements in digital technology for monitoring orthodontic tooth movement, related complications, and appliance-wearing compliance. It aims to provide insights for researchers and clinicians to enhance the application of digital technology in orthodontics, improve treatment outcomes, and optimize patient experience. The digitization of diagnostic data and the visualization of dental models make chair-side follow-up monitoring more convenient, accurate, and efficient. At the same time, the emergence of remote monitoring technology allows orthodontists to promptly identify oral health issues in patients and take corresponding measures. Furthermore, the multimodal data fusion method offers valuable insights into the monitoring of the root-alveolar relationship. Artificial intelligence technology has made initial strides in automating the identification of orthodontic tooth movement, associated complications, and patient compliance evaluation. Sensors are effective tools for monitoring patient adherence and providing data-driven support for clinical decision-making. The application of digital technology in orthodontic monitoring holds great promise. However, challenges like technical bottlenecks, ethical considerations, and patient acceptance remain.

Objective: To evaluate the safety and efficacy of ABO non-identical platelets with reduced plasma (ABO-NPRP) transfusion in patients with hematological diseases. Methods: A retrospective analysis was conducted on 52 therapeutic doses of apheresis platelets with reduced plasma prepared at Chongqing Blood Center of the Chinese People's Liberation Army. The transfusion efficacy (24 h CCI) and the transfusion adverse reactions of these apheresis platelets were also observed in 35 patients with hematological diseases in First Affiliated Hospital of Army Medical University. Comparisons were made with a control group consisting of patients who received only identical apheresis platelets during the same period. Meanwhile, the effect of ABO-NPRP on the subsequent platelet transfusion efficacy was observed. Results: There was no statistically significant difference in PDW, MPV, and PLCR before and after the preparation of apheresis platelets with reduced plasma (P>0.05), while the difference in platelet count was statistically significant [(2.86±0.34)×10 per therapeutic dose vs (2.46±0.28)×10 per therapeutic dose, P<0.001]; there was no statistically significant difference in the 24 h CCI transfusion efficacy between conventional identical apheresis platelets and ABO-NPRP, with transfusion efficacy rates of 76.60% and 78.85%, respectively (P>0.05); there was no statistically significant difference in platelet transfusion efficacy between the group with ABO-NPRP and the group without ABO-NPRP (completely identical transfusion group), with transfusion efficacy rates of 77.78% and 75.25%, respectively (P>0.05). Conclusion: ABO-NPRP transfusion is safe, effective, demonstrating comparable efficacy to conventional identical transfusion. It can serve as an important complementary strategy to optimize the utilization of blood resources.

Objective: To evaluate the safety and efficacy of ABO non-identical platelets with reduced plasma (ABO-NPRP) transfusion in patients with hematological diseases. Methods: A retrospective analysis was conducted on 52 therapeutic doses of apheresis platelets with reduced plasma prepared at Chongqing Blood Center of the Chinese People's Liberation Army. The transfusion efficacy (24 h CCI) and the transfusion adverse reactions of these apheresis platelets were also observed in 35 patients with hematological diseases in First Affiliated Hospital of Army Medical University. Comparisons were made with a control group consisting of patients who received only identical apheresis platelets during the same period. Meanwhile, the effect of ABO-NPRP on the subsequent platelet transfusion efficacy was observed. Results: There was no statistically significant difference in PDW, MPV, and PLCR before and after the preparation of apheresis platelets with reduced plasma (P>0.05), while the difference in platelet count was statistically significant [(2.86±0.34)×10 per therapeutic dose vs (2.46±0.28)×10 per therapeutic dose, P<0.001]; there was no statistically significant difference in the 24 h CCI transfusion efficacy between conventional identical apheresis platelets and ABO-NPRP, with transfusion efficacy rates of 76.60% and 78.85%, respectively (P>0.05); there was no statistically significant difference in platelet transfusion efficacy between the group with ABO-NPRP and the group without ABO-NPRP (completely identical transfusion group), with transfusion efficacy rates of 77.78% and 75.25%, respectively (P>0.05). Conclusion: ABO-NPRP transfusion is safe, effective, demonstrating comparable efficacy to conventional identical transfusion. It can serve as an important complementary strategy to optimize the utilization of blood resources.

Objective To systematically evaluate the efficacy and safety of proximal gastrectomy (PG) versus total gastrectomy (TG) for the treatment of Siewert type Ⅱ/Ⅲ adenocarcinoma of the esophagogastric junction (AEG). Methods PubMed, The Cochrane Library, Web of Science, EMbase, CNKI, Wanfang, and VIP databases were searched for literature comparing the efficacy and safety of PG and TG for the treatment of Siewert type Ⅱ/Ⅲ AEG. The search period was from database inception to March 2023. Meta-analysis was performed using Review Manager 5.4 software. Results A total of 23 articles were included, including 16 retrospective cohort studies, 5 prospective cohort studies, and 2 randomized controlled trials. The total sample size was 2 826 patients, with 1 389 patients undergoing PG and 1 437 patients undergoing TG. Meta-analysis results showed that compared with TG, PG had less intraoperative blood loss [MD=−19.85, 95%CI (−37.20, −2.51), P=0.02] and shorter postoperative hospital stay [MD=−1.23, 95%CI (−2.38, −0.08), P=0.04]. TG had a greater number of lymph nodes dissected [MD=−6.20, 95%CI (−7.68, −4.71), P<0.001] and a lower incidence of reflux esophagitis [MD=3.02, 95%CI (1.24, 7.34), P=0.01]. There were no statistically significant differences between the two surgical approaches in terms of operative time, postoperative survival rate (1-year, 3-year, 5-year), and postoperative overall complications (P>0.05). Conclusion PG has advantages in terms of intraoperative blood loss and postoperative hospital stay, while TG has advantages in terms of the number of lymph nodes dissected and the incidence of reflux esophagitis. There is no significant difference in long-term survival between the two surgical approaches.

OBJECTIVE To innovatively apply the pre-intelligent precision dosing and verification system （hereinafter referred to as “the system”）， and to provide a reference for the high-level “intelligent” transformation of inpatient pharmacy. METHODS The limitations of the triple-serial dispensing mode， which comprised the automatic medicine packaging machine （ATC）， intelligent tablet dispensing table （ITDT） and medication detection machine （MDM）， were analyzed. The application of the system and the adoption of the barcode scanning verification method optimized the pre-dosing management， whole-tablet drug dispensing process and ATC temporary dosing management. The comparative analysis was conducted to assess dosing time， labor cost and packaging error of the eight-month period， before and after the system application. RESULTS The triple-serial dispensing mode had a weak ability to avoid error risks in the manual dosing stage， and also had errors in the verification stage. Through the innovative application system， the pre-dosing management had been upgraded， the whole-tablet drug dispensing process had been optimized， and the ATC temporary dosing management had been improved. The average time required for each drug for pre-dosing， whole-tablet drug dispensing and ATC temporary dosing was significantly shortened after the application of the system， compared with before the application of the system （P＜0.001）. The number of pharmacists was reduced from two to one. The error rate of ATC decreased significantly from 0.220‰ to 0.029‰ （P＜0.001）. Specifically， the rate of pharmacist-related errors （pre-dosing error， ITDT dosing error， and ATC temporary dosing error） decreased from 0.116‰ to 0.001‰ （P＜0.001）， and machine-related errors decreased from 0.096‰ to 0.023‰ （P＜0.001）. CONCLUSIONS This innovative integration mode greatly improves the working efficiency and quality of inpatient pharmacy. It enhances refined management of drug expiration and inventory， saves time and labor costs， improves the accuracy of drug dispensing， and ensures patient medication safety.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.