The Pharmacovigilance Guidelines for Clinical Application of Traditional Chinese Medicine Injections （hereinafter referred to as the Guidelines） were released by the China Association of Chinese Medicine， with the standard number T/CACM 1563.4—2024. It is the first specialized guideline in China on the approach to pharmacovigilance activities for the clinical application of traditional Chinese medicine injections （TCMIs）. The Guidelines were jointly developed by the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， along with 30 experts in TCM pharmacovigilance， clinical practice （TCM， as well as integrated traditional Chinese and Western medicine），and evidence-based medicine from across the country. This publication filled the gap in standard documents in this field， both domestically and internationally. The Guidelines were formulated according to GB/T1.1—2020 Directives for standardization—Part 1： Rules for the structure and drafting of standardizing documents， the WHO Handbook for Guideline Development，and other methodological norms. Based on international norms，national laws and regulations，and scientific research results in the field of pharmacovigilance， methods adopted included expert interviews，literature research，nominal group technique， and Delphi method. Then， key points for pharmacovigilance for TCM injections were summarized and clarified in the four critical sections of "monitoring"，"identification"，"assessment"，and "control". The development process of the Guidelines included project initiation， international registration， expert interviews， literature search， and evaluation. Based on the research results of these steps，a draft was formed and revised through multiple rounds of in-group expert discussion and peer evaluations by 56 external experts. After revisions by the working group based on the feedback， the final version was formed. The Guidelines came into effect on January 8，2024，providing suggestions and reference norms for pharmacovigilance in the clinical application of TCMIs. To further promote the application and popularization of the Guidelines and help pharmacovigilance personnel better understand the development process，this study elucidates the background，methodological framework，and key development steps of the Guidelines.

The Pharmacovigilance Guidelines for Clinical Application of Traditional Chinese Medicine Injections （hereinafter referred to as the Guidelines） were released by the China Association of Chinese Medicine， with the standard number T/CACM 1563.4—2024. It is the first specialized guideline in China on the approach to pharmacovigilance activities for the clinical application of traditional Chinese medicine injections （TCMIs）. The Guidelines were jointly developed by the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， along with 30 experts in TCM pharmacovigilance， clinical practice （TCM， as well as integrated traditional Chinese and Western medicine），and evidence-based medicine from across the country. This publication filled the gap in standard documents in this field， both domestically and internationally. The Guidelines were formulated according to GB/T1.1—2020 Directives for standardization—Part 1： Rules for the structure and drafting of standardizing documents， the WHO Handbook for Guideline Development，and other methodological norms. Based on international norms，national laws and regulations，and scientific research results in the field of pharmacovigilance， methods adopted included expert interviews，literature research，nominal group technique， and Delphi method. Then， key points for pharmacovigilance for TCM injections were summarized and clarified in the four critical sections of "monitoring"，"identification"，"assessment"，and "control". The development process of the Guidelines included project initiation， international registration， expert interviews， literature search， and evaluation. Based on the research results of these steps，a draft was formed and revised through multiple rounds of in-group expert discussion and peer evaluations by 56 external experts. After revisions by the working group based on the feedback， the final version was formed. The Guidelines came into effect on January 8，2024，providing suggestions and reference norms for pharmacovigilance in the clinical application of TCMIs. To further promote the application and popularization of the Guidelines and help pharmacovigilance personnel better understand the development process，this study elucidates the background，methodological framework，and key development steps of the Guidelines.

This article systematically elucidates the current development status and future trends of robot-assisted surgery worldwide. Currently, robotic surgery led by the Da Vinci Surgical System has been widely adopted across multiple disciplines, including thoracic surgery, urology, and gynecology, demonstrating advantages such as precision, stability, and minimal invasiveness. Significant regional disparities exist in the global distribution of robotic surgery, reflecting inequalities in healthcare resources and economic development worldwide. China is rapidly emerging in the field of robotic surgery, undergoing a strategic transition from technology adoption to independent innovation: domestically developed systems (e.g., Toumai, Surgibot) have demonstrated safety and efficacy in multidisciplinary clinical practice; leveraging the advantages of 5G technology, remote robotic surgery has progressed from proof-of-concept to clinical reality, offering innovative solutions for equitable healthcare resource allocation; meanwhile, a quality control system spanning from national strategic planning to clinical operational standards is under development. Confronted with core challenges such as high costs, technical barriers (e.g., lack of force feedback), steep learning curves, lagging regulatory and ethical frameworks, and uneven regional development, future robotic surgery will deeply integrate artificial intelligence, evolving toward single-port/flexible miniaturization, normalization of remote surgery, and personalized precision treatment. Ultimately, it will drive the transformation of surgical medicine toward a new paradigm characterized by greater precision, intelligence, and accessibility, and is expected to play a strategic role in public health emergencies and disaster relief operations.

Background: Malignant pleural effusion (MPE), a common complication of advanced cancers, is associated with poor prognosis and reduced quality of life. Although host–tumor interactions are known to drive MPE development, the associated immune dynamics during disease progression remain unclear. Using a Lewis lung carcinoma-induced MPE model in C57BL/6JNidfc mice, we systematically evaluated general parameters and immune cell changes at two-day intervals throughout disease progression. Results: The day of Lewis lung carcinoma cell injection into the pleural space was designated as day 0. By day 10 post-injection (p.i.), MPE-bearing mice exhibited ~ 10% body weight loss, marking the experimental endpoint. Pleural tumor mass and pleural effusion volume were minimal up to day 4 p.i. but increased sharply from day 6 onward.CD45⁺ immune cell counts rose over time, and days 6, 8, and 10 p.i. marked key stages of MPE progression. On day 6, B cells, T cells, and natural killer cells, but not macrophages and neutrophils, increased significantly compared to earlier timepoints. By day 8, all immune cell subsets except T cells exceeded day 6 levels, and at day 10, natural killer cell numbers declined while others continued to increase. Besides, the numbers of CD8⁺ T cells, Th1 cells, regulatory T cells, and M2 macrophages progressively increased from day 6 to 10. Based on these data, days 6 and 10 were defined as early and advanced MPE stages, respectively, with distinct immune phenotypes. In advanced MPE, CD8⁺ T cells displayed reduced IFN-γ, TNF-α, Granzyme B, Perforin, FasL, and Ki-67, but upregulated PD-1 and CTLA-4 relative to early stage. Similarly, Th1 cells showed decreased IFN-γ, TNF-α, and IL-2 production along with reduced Ki-67 expression. Advanced-stage M2 macrophages exhibited lower MHC-II levels and impaired phagocytosis, but higher PD-L1 and IL-10 production, while neutrophils showed reduced TNF-α release and phagocytic activity. Conclusions Our findings characterize the temporal immune dynamics associated with MPE progression in a mouse model, revealing a transition from an early immunostimulatory state to a late immunosuppressive state. This study enhances our understanding of MPE immunopathogenesis and provides a foundation for developing precise, stagespecific therapeutic strategies.

ObjectiveThe frequency difference limen (FDL) serves as a fundamental metric utilized for effectively quantifying the precise perceptual capabilities of the central auditory system. However, traditional measurement methods rely heavily on the active behavioral responses of subjects and are consequently highly susceptible to the negative influence of confounding subjective factors. Furthermore, existing research paradigms frequently employ uniform stimulus configurations that overlook critical individual perceptual differences. Based on brain-computer interface (BCI) technology, this comprehensive study aims to establish an objective and quantitative evaluation method for auditory frequency discrimination by systematically analyzing and decoding the specific neural responses elicited at the exact threshold state. MethodsWe designed a personalized rapid serial auditory presentation (RSAP) paradigm customized based on each individual’s precise FDL. A cohort of eleven healthy participants was recruited to evaluate the paradigm using pure-tone sequences at a baseline frequency of 4 000 Hz. This experimental paradigm simulates a realistic auditory perception environment through the continuous presentation of acoustic stimuli, thereby allowing for an in-depth investigation into the specific neural representations evoked by weak frequency deviations at the threshold state. Given that auditory stimulus-evoked response features exhibit complex and differentiated spatiotemporal distribution patterns across multiple frequency domains, this study further deeply integrates the cross-scale feature interaction module with the dynamic spatiotemporal attention allocation strategy, innovatively proposing the Multi-Scale Spatial-Temporal Dual Attention Network (MS-STAMNet). Specifically, the network constructs parallel processing branches with multiple receptive fields and introduces a dynamic adaptive weighting strategy to precisely localize core neural activity signals, further deeply integrating multi-scale information through cross-branch feature information interaction to achieve robust single-trial decoding of weak auditory evoked responses. ResultsThe comprehensive electrophysiological data analysis demonstrated that subtle auditory frequency deviation stimuli presented at the threshold level successfully elicited pronounced N2 and P3 event-related potential features, reflecting pre-attentive mismatch detection and subsequent cognitive evaluation, which were prominently distributed over the frontal, central, and temporal regions of the scalp. In the complex time-frequency domain, the extracted neural response characteristics exhibited distinct, statistically significant event-related synchronization within both the low-frequency δ and θ frequency bands, which was simultaneously accompanied by a widespread, prominent event-related desynchronization within the higher α band. A comparative analysis of model performance demonstrated that MS-STAMNet achieved an average unweighted average recall (UAR) of (69.67±6.12)% and area under the curve (AUC) of 0.761 8±0.07, significantly outperforming the established baseline models such as EEGNet and PLNet. Furthermore, a distinct dissociation phenomenon was verified between neural decoding and behavioral performance through regression analysis (R²=0.016, P=0.709), indicating that this model can effectively capture the implicit features of subtle frequency deviations, even when they fail to trigger explicit conscious responses. Additionally, attention weight visualization analysis further reveals the highly accurate focus of the network on key features concentrated over the bilateral temporal and fronto-parietal regions. ConclusionThis study systematically and comprehensively uncovers the multi-dimensional spatiotemporal evolutionary patterns of complex neural responses processing subtle acoustic variations under long-sequence threshold auditory stimulation. Concurrently, it verifies the efficacy and robustness of the proposed MS-STAMNet architecture in accurately deciphering weak, single-trial electroencephalogram signals amidst complex background noise. Ultimately, these neurophysiological and algorithmic findings lay a solid theoretical and methodological foundation for the objective and quantitative evaluation of individual auditory cognitive capabilities in clinical applications, transcending the fundamental limitations of traditional behavioral paradigms and providing robust technical support for future auditory research and related clinical assessments.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Aim To investigate the effects of Agrimonia pilosa(AP)on the proliferation and apoptosis of non-small cell lung cancer(NSCLC)H1299 cells using non-targeted metabolomics and other methods,and to explore the underlying molecular mechanisms.Meth-ods Taking H1299 cells as the research object,the effect of AP on cell proliferation and apoptosis was de-tected through CCK-8 method,colony formation,LDH,Hoechst 33258 staining,AO/EB staining,flow cytometry detection,RT qPCR and other experiments.The main differential metabolites were detected by the metabolomics method of ultra-high phase liquid chro-matography and mass spectrometry(UHPLC-Q-Orbi-trap MS),and related metabolic pathways were ana-lyzed.Results Compared with the control group,AP treatment was able to significantly inhibit the prolifera-tion and colony formation of H1299 cells,while the re-lease of LDH increased in a dose-dependent manner.Fluorescence microscopy and flow cytometry and RT-qPCR analysis revealed that H1299 cells underwent crumpling and increased nuclear fragmentation after AP administration,blocked in G0/G1 phase,up-regulated apoptotic genes caspase-3 and Bax,and down-regulated apoptosis-inducing effects of Bcl-2.Metabolomics anal-ysis screened 35 differential metabolites,which were PC(O-30∶1),D-Glutamic acid,PE(18∶0/15∶0),etc.The main metabolic pathways involved includ-ed amino acid metabolism,glycerophospholipid metabo-lism and purine metabolism so on.Conclusions AP may exert its pharmacological effects by interfering with multiple metabolic pathways in H1299 cells,inhibiting cell proliferation and promoting apoptosis.

Objective To investigate the mechanism of Jisuishang Formula on cervical myelopathy based on Wnt/β-catenin signaling pathway.Methods Thirty-six adult male SD rats were randomly divided into sham operation group,model group,positive control group(TAK-715,50 mg/kg),Jisuishang Formula low(9.7 g/kg),medium(19.4 g/kg)and high(38.8 g/kg)dose groups,with 6 rats in each group for 4 weeks.The BBB score and inclined plate test were observed at 1,2 and 4 weeks after surgery.HE and Nissl staining were used to observe the histopathology and neuronal condition of the spinal cord.Immunofluorescence was used to detect the protein expres-sions of BDNF,β-catenin,Bax and Bcl-2.Western blot and qRT-PCR were used to detect the expression of Wnt/β-catenin signaling pathway-related proteins and mRNAs.Results Compared with the sham group,the BBB score and inclined plate test score were significantly decreased(P<0.05),the expressions of BDNF,β-catenin and Bcl-2 decreased(P<0.05),the expression of Bax increased(P<0.05),the expressions of β-catenin,LRP-6 and p-GSK-3βdecreased(P<0.05),and the expressions of Caspase-3 and Caspase-9 increased(P<0.05).Compared with the model group,the BBB score and inclined plate test score were significantly increased in the high-dose Jisuishang Formula group(P<0.05),the expressions of BDNF,β-catenin and Bcl-2 increased(P<0.05),the expression of Bax decreased(P<0.05),the expressions of β-catenin,LRP-6 and p-GSK-3βincreased(P<0.05),and the expressions of Caspase-3 and Caspase-9 decreased(P<0.05).Conclusion Jisuishang Formula prescription can inhibit neuronal apoptosis,improve spinal cord microenvironment,and promote neurological function recovery by activating the Wnt/β-catenin signaling pathway.

Objective To investigate the incidence and types of patient-ventilator asynchrony(PVA)in mechanically ventilated patients within the intensive care unit(ICU),and to identify associated high-risk factors,thereby providing a basis for reducing PVA,enhancing mechanical ventilation efficiency,and refining ventilation strategies.Methods A prospective observational study was conducted among patients admitted to the general ICU of the Affiliated Hospital of Guizhou Medical University from October to December 2024 who were receiving mechanical ventilation.Inclusion criteria were as follows:age ≥18 years and mechanical ventilation duration ≥12 hours.Exclusion criteria included complete controlled mechanical ventilation,palliative care or do-not-resuscitate status,and lack of informed consent.Senior respiratory therapists performed daily bedside observations of ventilator waveforms for 10～15 minutes between 08:00 and 12:00.PVA was diagnosed based on pressure-time and flow-time waveforms,with the types of PVA being recorded.Demographic and clinical data,including age,sex,body mass index(BMI),primary diagnosis,comorbidities,APACHEⅡ score at ICU admission,blood gas analysis,ventila-tion mode and parameters,analgesia and sedation status,duration of mechanical ventilation,and length of ICU stay,were collected.The incidence and types of PVA during the observation period were analyzed.Univariate and multivariate logistic regression analyses were performed to identify high-risk factors for PVA.Clinical outcomes were compared between patients with and without PVA.Results A total of 105 patients and 453 episodes of assisted mechanical ventilation waveforms were analyzed.Among these,60.95％(64/105)experienced at least one episode of PVA.Of the 453 ventilation waveforms assessed,35.76％(162/453)demonstrated PVA.The types of PVA,ranked by incidence,were as follows:cycling mismatch(12.58％,57/453),double triggering(11.92％,54/453),ineffective triggering(9.49％,43/453),flow starvation(5.30％,24/453),and exhalation flow limitation(1.77％,8/453).The incidence of PVA varied significantly across different ventilation modes:45.7％in volume-assist/control ventilation(V-A/C),38.1％in pressure-assist/control ventilation(P-A/C),42.9％in synchronized intermittent mandatory ventilation(SIMV),and 16.7％in pressure support ventilation(PSV)(P<0.001).Multi-variate logistic regression analysis revealed that the mechanical ventilation mode[reference:PSV;V-A/C:OR=4.687,95％CI:2.140～10.263,P<0.001;P-A/C:OR=2.922,95％CI:1.489～5.734,P=0.002;SIMV:OR=4.682,95％CI:1.758～12.466,P=0.002]and actual respiratory rate(OR=1.07,95％CI:1.016～1.127,P=0.011)were significant high-risk factors for PVA.Patients with PVA had a significantly longer duration of mechanical ventilation[8.21(5.35,13.91)days vs.3.00(1.96,5.71)days,P<0.001]compared to those without PVA.Conclusions PVA is commonly observed in ICU patients receiving assisted invasive mechanical ventilation,with cycling mismatch,double triggering,and ineffective triggering being the most prevalent types.The incidence of PVA tends to be lower when using the PSV mode.Clinically,real-time monitoring of patient-ventilator synchrony via ventilator waveforms,along with the optimization of ventilator modes and parameters,should be employed to minimize the occurrence of PVA and enhance the efficiency of mechanical ventilation.