OBJECTIVE To systematically evaluate the quality of the Heat-clearing and symptom-relieving formula and screen potential marker components that influence the quality of the formula. METHODS The contents of 11 components （calycosin-7- O - β -D-glucoside， ononin， hyperoside， isoquercitrin， baicalin， baicalein， cryptotanshinone， tanshinone Ⅱ A ， tanshinone Ⅰ， senkyunolide A， ferulic acid） in the Heat-clearing and symptom-relieving formula were determined by high-performance liquid chromatography-tandem mass spectrometry （HPLC-MS/MS）. Using the contents of the aforementioned components as variables， cluster analysis （CA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were conducted using OriginPro 2024 software and SIMCA 14.1 software； marker components affecting the quality of the Heat-clearing and symptom-relieving formula were then screened based on the criteria of variable importance in the projection （VIP） value＞1 and P ＜0.05. The comprehensive evaluation of 20 batches of samples was carried out using the entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） and grey correlation analysis （GCA） methods. RESULTS The contents of the above 11 components were 7.993-72.866， 4.542-31.228， 727.666-1 901.884， 496.846-1 293.279， 1 995.501-6 779.150， 54.500-241.280， 150.302-304.339， 79.698-189.206， 257.118-682.418， 5.498-21.687， 7.524-26.935 μg/g. CA， PCA and OPLS-DA results showed that 20 batches of samples were grouped into 2 categories. Q1， Q3， Q4， Q7-Q9， Q12， Q15， Q16 were grouped into one category， and the rest were grouped into another category； VIP values of ferulic acid， tanshinone Ⅱ A ， baicalin， cryptotanshinone， calycosin-7- O - β -D-glucoside and ononin were all greater than 1 （ P ＜0.05）. Both the entropy weight-TOPSIS and GCA methods showed that the samples ranked in the top 11 according to the euclidean distance and relative correlation degree were Q2， Q5， Q6， Q10， Q11， Q13， Q14， Q17-Q20. CONCLUSIONS The established HPLC-MS/MS method is rapid， accurate and highly sens itive. Combined with chemical pattern recognition analysis， entropy weight-TOPSIS and GCA methods， this method can be used to evaluate the quality of the Heat-clearing and symptom-relieving formula. Ferulic acid， tanshinone Ⅱ A ， baicalin， cryptotanshinone， calycosin-7- O - β -D-glucoside and ononin may be the marker components that affect the quality of this formula. The overall quality of 11 batches of the Heat-clearing and symptom-relieving formula， including Q17， is relatively superior.

ObjectiveTo analyze the research status, hotspots and development trends in the application of virtual reality (VR) technology in managing negative emotions and postoperative rehabilitation of perioperative patients over the past decade. MethodsLiteratures related to the application of VR technology in managing negative emotions and postoperative rehabilitation of perioperative patients were retrieved from Web of Science Core Collection database and CNKI, covering the period from January, 2015 to August, 2025, and CiteSpace 6.3.R1 was used for bibliometric analysis. ResultsA total of 267 English literatures and 130 Chinese literatures were included, with the annual number of publications showing an upward trend. The United States was the country with the largest number of publications in English literatures, and Erasmus University Rotterdam was the institution with the largest number of publications. High-frequency keywords included virtual reality, pain, surgery, anxiety and distraction. Research hotspots mainly focused on functional exercise, negative emotions, pain management and multimodal intervention strategies. English researches were deepening towards virtual reality exposure therapy, mechanism exploration and personalized schemes, while Chinese researches focused more on the verification of rehabilitation effects. ConclusionResearches on the application of VR technology in the management of perioperative patients are rapidly developing, with research hotspots shifting from single technology application to multimodal and personalized integrated intervention. Future research should focus on exploring its intervention mechanisms, personalized schemes and the breadth of cross-departmental applications.

Oral squamous cell carcinoma (OSCC) is a common head and neck malignancy. Approximately 50% to 60% of patients with OSCC are diagnosed at a locally advanced stage (clinical staging III-IVa). Even with comprehensive and sequential treatment primarily based on surgery, the 5-year overall survival rate remains below 50%, and patients often suffer from postoperative functional impairments such as difficulties with speaking and swallowing. Programmed death receptor-1 (PD-1) inhibitors are increasingly used in the neoadjuvant treatment of locally advanced OSCC and have shown encouraging efficacy. However, clinical practice still faces key challenges, including the definition of indications, optimization of combination regimens, and standards for efficacy evaluation. Based on the latest research advances worldwide and the clinical experience of the expert group, this expert consensus systematically evaluates the application of PD-1 inhibitors in the neoadjuvant treatment of locally advanced OSCC, covering combination strategies, treatment cycles and surgical timing, efficacy assessment, use of biomarkers, management of special populations and immune related adverse events, principles for immunotherapy rechallenge, and function preservation strategies. After multiple rounds of panel discussion and through anonymous voting using the Delphi method, the following consensus statements have been formulated: 1) Neoadjuvant therapy with PD-1 inhibitors can be used preoperatively in patients with locally advanced OSCC. The preferred regimen is a PD-1 inhibitor combined with platinum based chemotherapy, administered for 2-3 cycles. 2) During the efficacy evaluation of neoadjuvant therapy, radiographic assessment should follow the dual criteria of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and immune RECIST (iRECIST). After surgery, systematic pathological evaluation of both the primary lesion and regional lymph nodes is required. For combination chemotherapy regimens, PD-L1 expression and combined positive score need not be used as mandatory inclusion or exclusion criteria. 3) For special populations such as the elderly (≥ 70 years), individuals with stable HIV viral load, and carriers of chronic HBV/HCV, PD-1 inhibitors may be used cautiously under the guidance of a multidisciplinary team (MDT), with close monitoring for adverse events. 4) For patients with a poor response to neoadjuvant therapy, continuation of the original treatment regimen is not recommended; the subsequent treatment plan should be adjusted promptly after MDT assessment. Organ transplant recipients and patients with active autoimmune diseases are not recommended to receive neoadjuvant PD-1 inhibitor therapy due to the high risk of immune related activation. Rechallenge is generally not advised for patients who have experienced high risk immune related adverse events such as immune mediated myocarditis, neurotoxicity, or pneumonitis. 5) For patients with a good pathological response, individualized de escalation surgery and function preservation strategies can be explored. This consensus aims to promote the standardized, safe, and precise application of neoadjuvant PD-1 inhibitor strategies in the management of locally advanced OSCC patients.

BackgroundMonitoring the blood concentrations of antipsychotic drugs and their metabolites can guide the adjustment of clinical treatment plans， improving therapeutic efficacy while reducing adverse effects. However， there is currently a lack of a method that can accurately and efficiently quantitatively detect multiple antipsychotic drugs and their metabolites. ObjectiveTo establish a ultra-high performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） method for the simultaneous identification and quantitation of 12 antipsychotic drugs and their main metabolites in human serum. MethodsUsing UPLC-MS/MS technology， protein precipitation method was employed for sample pretreatment. An Agela Technologies Durashell C₈ chromatographic column （50 mm×3.0 mm， 5 μm） was selected for chromatographic separation with gradient elution. The flow rate was 0.4 mL/min， and the total analysis time was 5 minutes. The column temperature was 40℃. The mass spectrometry detection was carried out in the multiple reaction monitoring （MRM） mode， and the isotope internal standard method was used for quantification. ResultsThe relative standard deviation （RSD） of the internal standard normalization matrix effect factor for 12 antipsychotic drugs and their main metabolites at low and high quality concentrations was all less than 15%. The extraction recovery rate was 85% to 115%. They showed good linear relationships within their respective standard curve ranges （r>0.995）. At low， medium， and high quality concentrations， the accuracy was 85.24% to 114.71%， and the RSD of intra-batch and inter-batch precision was all ≤14.15%， with good stability. ConclusionAll the analytical performance indicators of this method meet the verification requirements， providing an analytical means for the quantitative detection of antipsychotic drugs and their main metabolites in human serum. ［Funded by The Third Batch of Science and Technology Projects in Chaozhou City in 2023 （number， 202303GY02）］

BackgroundArrhythmia and obsessive-compulsive disorder （OCD） frequently co-occur in clinical and epidemiological settings， yet their shared genetic basis and potential heart-brain axis mechanisms remain unclear. ObjectiveTo systematically evaluate the genetic correlation between arrhythmia and OCD， and to elucidate their underlying molecular genetic mechanisms， so as to provide molecular evidence for the "heart-brain axis" to support risk assessment and integrated clinical strategies for these comorbidities. MethodsThe aggregated data from the genome-wide association study （GWAS） of arrhythmia in the UK Biobank （7 207 cases and 477 391 controls） and the GWAS data of OCD released by the Psychiatric Genomics Consortium （2 688 cases and 7 037 controls） were integrated， all of which were limited to individuals of European ancestry. The genome-wide genetic correlations were estimated using the linkage disequilibrium score regression （LDSC） and the high-definition likelihood （HDL）. Local genetic correlation analysis was conducted using the local analysis of variance annotation （LAVA）. Multi-trait analysis of GWAS （MTAG） was employed to identify pleiotropic loci. Shared risk genes were identified by combining summary-data based Mendelian randomization （SMR） and transcriptome-wide association study （TWAS）. Functional enrichment analysis was performed based on the functional mapping and annotation （FUMA） platform. ResultsBoth LDSC （r_g=0.248， 95% CI： 0.159–0.336， P=4.82×10^-3） and HDL （r_g=0.294， 95% CI： 0.237–0.351， P=5.87×10^-4） revealed significant positive genetic correlation between arrhythmia and OCD. LAVA identified 23 significantly local correlated regions in the genome （P<2.0×10^-5）. MTAG discovered 11 genome-wide significant pleiotropic SNPs， among which rs12754189 （intron of KCNN3） had potential functional harmfulness （CADD>12.37）. SMR and TWAS jointly identified 20 shared genes， enriched in neural-cardiovascular tissues such as the cerebral cortex， amygdala， and left ventricle， and involved in DNA damage response， RNA metabolism， transcriptional regulation， and FAS signaling pathway （FDR<0.05）. ConclusionArrhythmia and OCD share a common genetic basis. The co-morbidity mechanism may involve the common vulnerability of neurons and cardiac muscle cells in terms of gene expression regulation and stress response， supporting the role of the brain-heart axis in the pathophysiology of both conditions.

Background The contamination of public baths with Legionella pneumophila contamination has become a growing public health concern in recent years. However, research on its association with bacterial community characteristics in water samples remains limited. The integration of 16S rRNA sequencing and random forest modeling provides a new approach to elucidate the bacterial community characteristics of public bath water and their association with Legionella pneumophila contamination. Objective To investigate the bacterial community structure and diversity of public bath water in Shanghai, explore the association between Legionella pneumophila contamination and bacterial community characteristics, and identify key bacterial genera associated with contamination, thereby providing a scientific basis for formulating hygiene management regulations for public bath water. Methods From February to March 2023, water samples were collected from ten public baths in Shanghai which were selected based on business scale, regional distribution, and functional differences. Water quality parameters were evaluated, and the samples were categorized into Legionella-positive and Legionella-negative groups based on the detection results of Legionella pneumophila. The bacterial community structure, α-diversity, and β-diversity were analyzed using 16S rRNA sequencing. Redundancy analysis (RDA) was employed to examine the relationship between physicochemical factors and bacterial community diversity. A random forest model was employed to identify key bacterial genera distinguishing the two groups, with the importance of genera being evaluated based on the mean decrease accuracy (MDA). Results The oxygen consumption in the Legionella-positive group was significantly lower than that in the Legionella-negative group (mean values: 1.85 mg·L⁻¹ vs. 6.81 mg·L⁻¹, P< 0.05), while no significant differences were observed in other physicochemical indicators. The sequencing results revealed a total of 27 bacterial phyla and 454 bacterial genera, with Proteobacteria (63.00%) being the dominant phylum. The dominant genera included Pelomonas (8.50%), Acidovorax (8.13%), Mycobacterium (7.93%), and Acinetobacter (6.59%). The α-diversity analysis indicated that bacterial community richness (Chao1 and ACE indices) was significantly higher in the Legionella-positive group than in the Legionella-negative group (P<0.01). The β-diversity analysis showed no significant difference in the bacterial community structure between the two groups (P>0.05). The RDA analysis demonstrated that the bacterial community diversity was positively correlated with pH and negatively correlated with oxygen consumption and free residual chlorine. The RDA1 and RDA2 explained 23.92% and 21.30% of the bacterial community diversity, respectively. The random forest model identified 20 key genera significantly influencing the microbial community distribution between the two groups, including unclassified_Bradyrhizobiaceae (MDA=2.42), Meiothermus (MDA=2.37), and Flavihumibacter (MDA=2.26). Conclusion The diversity of bacterial communities in public bath water is influenced by pH, oxygen consumption, and free residual chlorine. Samples contaminated with Legionella pneumophila exhibit greater microbial richness and contain characteristic key bacterial genera that contribute to community differences. Machine learning random forest technology helps identify these distinctive key bacterial genera. The findings provide a basis for carrying out risk early warning strategies in such settings.

High-throughput sequencing-based high-throughput screening （HTS²） technology， as a new advancement in the field of high-throughput biotechnology， is the world's first technology to integrate high-throughput sequencing into large-scale drug screening and target discovery. The artificially designed DNA probes were bound to the undetermined mRNAs of thousands of genes in cell lysates， and then the probes were ligated with ligases. The large-scale simultaneous detection of gene expression changes in thousands of drug-treated cell samples was performed using barcoding， automated operating platforms， and high-throughput sequencers. This technology enables high-throughput identification of drugs that significantly perturb the gene expression profiles characteristic of diseases. It can also take gene expression signature as the readout and exert great high-throughput advantages in the screening of multi-drug， multi-component， and multi-target drugs， as well as the research on complex mechanisms. Therefore， it is particularly suitable for elucidating the multi-target mechanisms of traditional Chinese medicine and identifying its multi-effective components. Its main technical advantages include high throughput， automation， and low cost. In recent years， HTS² technology has yielded important achievements in the elucidation of the mechanism of action of traditional Chinese medicine formulas， the scientific connotation analysis of the regional characteristics of traditional Chinese medicine， the targeted isolation of active compounds of traditional Chinese medicine， and the discovery of novel pharmacological functions of monomeric compounds of traditional Chinese medicine. In the era of artificial intelligence， HTS² technology will serve as a powerful tool for generating high-quality， original big data of traditional Chinese medicine， providing core data support and promoting AI-driven traditional Chinese medicine research. Ultimately， HTS² technology offers new strategies and critical data support for deeply analyzing the scientific connotation of traditional Chinese medicine and discovering novel traditional Chinese medicine-based drugs， thereby accelerating the modernization and internationalization of traditional Chinese medicine in China.

Background: Bone cancer pain (BCP) is not adequately addressed by current treatment methods, making the exploration of effective management strategies a topic of significant interest. Bone marrow mesenchymal stem cells (BMSCs) seem to be a potential way for managing BCP, yet little is known about the mechanisms underlying the efficacy of this potential treatment. Methods: We established the male C57BL/6 mice BCP models. Behavioral tests, X-ray, bone histology, western blotting, and immunofluorescence were used to verify the analgesic effect of BMSCs. Results: Intramedullary injection of Lewis lung carcinoma cells into the femur successfully generated the mice BCP models. The number of c-Fos-positive neurons and phosphorylated mitogen-activated protein kinase (MAPK) proteins in the spinal dorsal horn of the BCP mice increased. Intrathecal injection of BMSCs temporarily improved the BCP mice’s mechanical and thermal hyperalgesia without affecting motor function. This effect may be related to inhibiting spinal microglia and p-p38 MAPK activation. The analgesic effect of BMSCs may be related to the homing effect mediated by CXCR4. Conclusions Intrathecal injection of BMSCs can temporarily inhibit mechanical and thermal hyperalgesia in BCP mice without affecting motor function. This effect may be related to the inhibition of p-p38 protein expression and the inhibition of microglia but not to p-ERK and p-JNK.

Objective:To evaluate the dynamic changes in fibrinolytic states after initial resuscitation in severe trauma patients, and to analyze the relationship between the changes and clinical outcomes.Methods:A prospective cohort study was conducted on severe trauma patients admitted to the trauma center in Taicang Hospital, affiliated with Soochow University, from July 2021 to December 2022. Resuscitation treatments, including tranexamic acid (TXA), were administered. Thromboelastography was performed at three intervals: upon admission, 1 hour and 8 hours after initial resuscitation. Fibrinolytic states were categorized into three phenotypes based on clot lysis at 30 minutes: fibrinolysis shutdown (SD), physiologic fibrinolysis (PY), and hyperfibrinolysis (HF). The primary outcomes included all-cause mortality at 24 hours and 28 days. Multivariate logistic regression was used to analyze the association between early fibrinolytic changes and clinical outcomes.Results:A total of 132 patients with severe trauma were included. Upon admission, fibrinolytic phenotypes were distributed as follows: SD in 61 patients (46.2%), PY in 59 patients (44.7%), and HF in 12 patients (9.1%). After resuscitation with TXA and other interventions, SD and PY remained predominant, whereas HF further decreased. Compared with the SD and PY groups, the HF group had significantly higher 24-hour mortality (25.0% vs. 3.3% vs. 3.4%, P<0.05) and 28-day mortality (58.3% vs. 32.8% vs. 11.9%, P<0.05), with massive hemorrhage being the primary cause of death. Among the non-HF groups, 28-day mortality was significantly higher in the SD group than in the PY group (32.8% vs. 11.9%, P<0.05), with traumatic brain injury as the leading cause of death. After the exclusion of 12 HF patients, multivariate logistic regression showed that after adjusting for age, Glasgow Coma Scale score ≤ 8, prothrombin time, and 24-hour crystalloid infusion volume, identified persistent SD was a risk factor for 28-day mortality in severe trauma patients, compared with sustained PY status ( OR=7.009, 95% CI: 1.141-43.079, P=0.036). Conclusions:In patients with severe trauma, SD and PY are the predominant fibrinolysis phenotypes after initial and early resuscitation. Persistent SD following resuscitation is significantly associated with an increased risk of 28-day mortality.

Objective:To investigate the current application of blood purification in the treatment of acute poisoning within Jiangsu Province and to evaluate the impact of extracorporeal blood purification on the clinical outcomes of critically poisoned patients.Methods:This multicenter, cross-sectional real-world observational study followed patients presenting with poisoning to the emergency departments of nine hospitals in Jiangsu Province between June 2015 and May 2019. Data were collected on demographic characteristics, vital signs within the first hour of emergency presentation, treatment modalities, length of hospital stay, and survival outcomes. Clinical data from patients who underwent extracorporeal blood purification were compared with those who did not, using the Wilcoxon rank-sum test and Chi-square test.Results:A total of 4 178 poisoning cases were included between June 2015 and May 2019. Among them, 21.7% (908/4 178) received blood purification therapy, while 78.3% (3 270/4 178) did not. Hemoperfusion (90.4%) was the most frequently employed method, followed by continuous renal replacement therapy (CRRT) (4.4%). In combined blood purification modalities, 4.8% underwent hemoperfusion combined with CRRT, 0.1% received hemoperfusion with plasma exchange, and another 0.1% underwent hemoperfusion combined with both CRRT and plasma exchange. Among patients who underwent blood purification, pesticide poisoning was the most prevalent (76.3%), with the most common toxic agents being paraquat (23.7%), dichlorvos (8.7%), methamidophos (5.2%), omethoate (4.0%), and glyphosate (3.7%). Compared to the non-blood purification group, patients in the blood purification group were more likely to present within the first hour with a low Glasgow Coma Scale (GCS) score (3-8) (22.6% vs. 9.7%, P <0.05), low mean arterial pressure (8.0% vs. 3.2%, P <0.05), longer hospital stays [5(3,9) days vs. 2(1,4) days, P <0.05] and a higher in-hospital mortality rate (21.1% vs. 5.3%, P <0.05). Follow-up via telephone 28 days after discharge revealed a survival rate of 78.9%, with a mortality rate of 21.1% in the blood purification group. Conclusions:Hemoperfusion is the most commonly utilized blood purification technique for treating poisoning in Jiangsu Province, with pesticides being the primary toxic agents treated. Although the mortality rate is higher in the blood purification group, the intervention may still contribute to improved patient outcomes.