ObjectiveTo establish an ultra-performance liquid fingerprint and multi-components determination method for Naomaili granules. To evaluate the quality of different batches by chemometrics， and the anti-neuroinflammatory effects of water extract and main components of Naomaili granules were tested in vitro. MethodsThe similarity and common peaks of 27 batches of Naomaili granules were evaluated by using Ultra performance liquid chromatography （UPLC） fingerprint detection. Ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） technology was used to determine the content of the index components in Naomaili granules and to evaluate the quality of different batches of Naomaili granules by chemometrics. LPS-induced BV-2 cell inflammation model was used to investigate the anti-neuroinflammatory effects of the water extract and main components of Naomaili granules. ResultsThe similarity of fingerprints of 27 batches of samples was > 0.90. A total of 32 common peaks were calibrated， and 23 of them were identified and assigned. In 27 batches of Naomaili granules， the mass fractions of 14 components that were stachydrine hydrochloride， leonurine hydrochloride， calycosin-7-O-glucoside， calycosin，tanshinoneⅠ， cryptotanshinone， tanshinoneⅡ_A， ginsenoside Rb₁， notoginsenoside R₁， ginsenoside Rg₁， paeoniflorin， albiflorin， lactiflorin， and salvianolic acid B were found to be 2.902-3.498， 0.233-0.343， 0.111-0.301， 0.07-0.152， 0.136-0.228， 0.195-0.390， 0.324-0.482， 1.056-1.435， 0.271-0.397， 1.318-1.649， 3.038-4.059， 2.263-3.455， 0.152-0.232， 2.931-3.991 mg∙g^-1， respectively. Multivariate statistical analysis showed that paeoniflorin， ginsenoside Rg₁， ginsenoside Rb₁ and staphylline hydrochloride were quality difference markers to control the stability of the preparation. The results of bioactive experiment showed that the water extract of Naomaili granules and the eight main components with high content in the prescription had a dose-dependent inhibitory effect on the release of NO in the cell supernatant. Among them， salvianolic acid B and ginsenoside Rb₁ had strong anti-inflammatory activity， with IC₅₀ values of （36.11±0.15） mg∙L^-1 and （27.24±0.54） mg∙L^-1， respectively. ConclusionThe quality evaluation method of Naomaili granules established in this study was accurate and reproducible. Four quality difference markers were screened out， and eight key pharmacodynamic substances of Naomaili granules against neuroinflammation were screened out by in vitro cell experiments.

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.

Objective: To report the antibody identification, blood management during pregnancy and the monitoring process of fetal hemolytic disease of fetus and newborn (HDFN) in a pregnant woman with a history of blood transfusion and pregnancy who developed anti-Jr . Methods: Saline tube technique and anti-human globulin technique were used for maternal blood typing, unexpected antibody screening and identification, as well as for determining antibody titer and IgG subclasses. PCR-SSP was employed for genotyping of 18 blood group systems. Next-generation sequencing (NGS) was utilized for gene sequencing of 38 blood group systems. Sanger sequencing was applied to verify rare blood group mutations detected by NGS and to investigate the corresponding rare blood group genes in family members. Blood preparation was achieved through anemia management in prenatal clinics and autologous blood collection during pregnancy. The newborn underwent the three primary tests for HDFN and plasma IgG subclass testing. Results: The pregnant woman's blood type was B, RhD positive, with a positive unexpected antibody screen, and the antibody identification pattern was consistent with a high-frequency antigen antibody. Gene sequencing revealed a homozygous ABCG2 c.376C>T mutation in the woman, resulting in the Jr(a-) phenotype, and anti-Jr antibody was present in her plasma. No compatible Jr(a-) blood was found among family members. The maternal anti-Jr IgG titer remained stable at 256 during pregnancy, with no detectable IgG1 or IgG3 subclasses against the Jr antigen. A total of 800 mL of autologous blood was collected in two stages during pregnancy. The newborn was B, RhD positive, Jr(a+), with a positive unexpected antibody screen (anti-Jr ). IgG subclass typing detected no IgG1 or IgG3. The direct antiglobulin test was positive, while the acid elution test was negative. Conclusion: The combination of serology and blood group genetic analysis provides a diagnostic basis for identifying antibodies to high-frequency antigens. Managing perinatal anemia and implementing staged autologous blood storage can secure blood supply for the perioperative period. IgG antibody subclass typing offers a reference for clinical assessment and prevention of HDFN.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

BACKGROUND:Fibromyalgia syndrome,as a common rheumatic disease,is related to central sensitization and immune abnormalities.However,the specific mechanism has not been elucidated,and there is a lack of specific diagnostic markers.Exploring the possible pathogenesis of this disease has important clinical significance. OBJECTIVE:To screen the potential diagnostic marker genes of fibromyalgia syndrome and analyze the possible immune infiltration characteristics based on bioinformatics methods,such as weighted gene co-expression network analysis(WGCNA),and machine learning. METHODS:Gene expression profiles in peripheral serum of fibromyalgia syndrome patients and healthy controls were obtained from the gene expression omnibus(GEO)database.The differentially co-expressed genes were screened in the expression profile by differential analysis and WGCNA analysis.Least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE)machine learning algorithm were further used to identify hub biomarkers,and draw receiver operating characteristic curve(ROC)to evaluate the accuracy of diagnosing fibromyalgia syndrome.Finally,single sample gene set enrichment analysis(ssGSEA)and gene set enrichment analysis(GSEA)were used to evaluate the immune cell infiltration and pathway enrichment in patients with fibromyalgia syndrome. RESULTS AND CONCLUSION:Eight down-regulated differentially expressed genes(DEGs)were obtained after differential analysis of the GSE67311 dataset according to the conditions of log2|(FC)|>0 and P<0.05.After WGCNA analysis,497 genes were included in the module(MEdarkviolet)with the highest positive correlation(r=0.22,P=0.04),and 19 genes were included in the module(MEsalmon2)with the highest negative correlation(r=-0.41,P=6×10-5).After intersecting DEGs and the module genes of WGCNA,seven genes were obtained.Four genes were screened out by LASSO regression algorithm and five genes were screened out by SVM-RFE machine learning algorithm.After the intersection of the two,three core genes were identified,which were germinal center associated signaling and motility like,integrin beta-8,and carboxypeptidase A3.The areas under the ROC curve of the three core genes were 0.744,0.739,and 0.734,respectively,indicating that they have good diagnostic value and can be used as biomarkers for fibromyalgia syndrome.The results of immune infiltration analysis showed that memory B cells,CD56 bright NK cells,and mast cells were significantly down-regulated in patients with fibromyalgia syndrome compared with the control group(P<0.05),and were significantly positively correlated with the above three biomarkers(P<0.05).The enrichment analysis suggested that there were nine fibromyalgia syndrome enrichment pathways,mainly related to olfactory transduction pathway,neuroactive ligand-receptor interaction,and infection pathway.The above results showed that the occurrence and development of fibromyalgia syndrome are related to the involvement of multiple genes,abnormal immune regulation,and multiple pathways imbalance.However,the interactions between these genes and immune cells,as well as their relationships with various pathways need to be further investigated.

ObjectiveTo explore the potential mechanism of action of the combination of Sanguisorbae Radix-Sophorae Flos （DH） in the treatment of ulcerative colitis （UC） using network pharmacology methods and molecular docking technology. MethodsNetwork pharmacology analysis was utilized to predict the potential targets of DH for the treatment of UC. The therapeutic effects were experimentally validated by inducing a UC model in mice with 3% dextran sulfate sodium （DSS）. The experimental groups were the normal group， the model group， the salazosulfapyridine group （100 mg·kg^-1）， and the low， medium， and high dose groups of DH （1.2， 2.4， and 4.8 g·kg^-1）. The efficacy of the treatment was assessed through the general condition of the mice， histopathological examination， and the expression levels of inflammatory markers in the colon. The effect of DH on angiogenesis was explored by messenger RNA （mRNA） detection of colonic angiogenesis-related mediators， vascular endothelial growth factor （VEGF） immunohistochemistry， microvessel density （MVD） detection， and transmission electron microscopy. The phosphatidylinositol-3-kinase （PI3K）-protein kinase B （Akt） signaling pathway proteins were quantitatively analyzed through Western blot to assess whether the suppression of pathological angiogenesis by DH is associated with this pathway. ResultsNetwork pharmacological analysis yielded 112 potential core therapeutic targets for the treatment of UC with DH， of which the core targets were tumor protein 53 （TP53）， JUN， interleukin （IL）-6， Akt1， and tumor necrosis factor （TNF）. Compared with the normal group， mice in the model group showed significant weight loss， colon shortening， and high DAI score， increased expression of inflammatory factors IL-6， IL-1β， and TNF-α， as well as increased mRNA expression levels of angiogenesis-related mediators VEGF， vascular cell adhesion molecule 1 （VCAM1）， angiotensin 1 （Ang1）， matrix metalloproteinase （MMP）-1， MMP-2， and MMP-9. The positive expression of CD31 and VEGF in colonic tissue increased， and the protein expression of the PI3K/Akt pathway was increased （P<0.05）. The endothelial cells of the colonic mucosa and the colonic vasculature were severely damaged. Compared with the model group， mice in the DH groups had significantly reduced weight loss and colon shortening， lower DAI scores， and a significant decrease in mRNA expression of inflammatory factors and angiogenesis-related mediators. In addition， there was decreased positive expression of CD31 and VEGF in colonic tissue and decreased protein expression of the PI3K/Akt pathway （P<0.05）. ConclusionNetwork pharmacology， molecular docking， and experimental validation are applied to explore the mechanism of action of DH in the treatment of UC， and it is found that DH is able to improve the symptoms of colitis and inhibit the pathological angiogenesis in UC mice. Its action might be related to affecting the PI3K/Akt pathway.

ObjectiveTo explore the potential mechanism of action of the combination of Sanguisorbae Radix-Sophorae Flos （DH） in the treatment of ulcerative colitis （UC） using network pharmacology methods and molecular docking technology. MethodsNetwork pharmacology analysis was utilized to predict the potential targets of DH for the treatment of UC. The therapeutic effects were experimentally validated by inducing a UC model in mice with 3% dextran sulfate sodium （DSS）. The experimental groups were the normal group， the model group， the salazosulfapyridine group （100 mg·kg^-1）， and the low， medium， and high dose groups of DH （1.2， 2.4， and 4.8 g·kg^-1）. The efficacy of the treatment was assessed through the general condition of the mice， histopathological examination， and the expression levels of inflammatory markers in the colon. The effect of DH on angiogenesis was explored by messenger RNA （mRNA） detection of colonic angiogenesis-related mediators， vascular endothelial growth factor （VEGF） immunohistochemistry， microvessel density （MVD） detection， and transmission electron microscopy. The phosphatidylinositol-3-kinase （PI3K）-protein kinase B （Akt） signaling pathway proteins were quantitatively analyzed through Western blot to assess whether the suppression of pathological angiogenesis by DH is associated with this pathway. ResultsNetwork pharmacological analysis yielded 112 potential core therapeutic targets for the treatment of UC with DH， of which the core targets were tumor protein 53 （TP53）， JUN， interleukin （IL）-6， Akt1， and tumor necrosis factor （TNF）. Compared with the normal group， mice in the model group showed significant weight loss， colon shortening， and high DAI score， increased expression of inflammatory factors IL-6， IL-1β， and TNF-α， as well as increased mRNA expression levels of angiogenesis-related mediators VEGF， vascular cell adhesion molecule 1 （VCAM1）， angiotensin 1 （Ang1）， matrix metalloproteinase （MMP）-1， MMP-2， and MMP-9. The positive expression of CD31 and VEGF in colonic tissue increased， and the protein expression of the PI3K/Akt pathway was increased （P<0.05）. The endothelial cells of the colonic mucosa and the colonic vasculature were severely damaged. Compared with the model group， mice in the DH groups had significantly reduced weight loss and colon shortening， lower DAI scores， and a significant decrease in mRNA expression of inflammatory factors and angiogenesis-related mediators. In addition， there was decreased positive expression of CD31 and VEGF in colonic tissue and decreased protein expression of the PI3K/Akt pathway （P<0.05）. ConclusionNetwork pharmacology， molecular docking， and experimental validation are applied to explore the mechanism of action of DH in the treatment of UC， and it is found that DH is able to improve the symptoms of colitis and inhibit the pathological angiogenesis in UC mice. Its action might be related to affecting the PI3K/Akt pathway.

OBJECTIVE To explore the effects of Polygala tenuifolia compatibility on toxicity， anti-inflammatory and analgesic efficacy of sand-ironing Strychnos nux-vomica （SS）. METHODS The preparation of SS single decoction， SS-P. tenuifolia core-removed （PC） （1∶2.5） or （1∶5） combined decoction， and SS-PC （1∶5） mixture were carried out to investigate their median lethal dose （LD50）. Using aspirin as positive control， the number of writhing movements， analgesic rate， pain latency， ear swelling degree and inflammation inhibition rate induced by the above-mentioned medicinal liquids in mice were compared. The contents of the active and toxic components， strychnine and brucine， in the above-mentioned medicinal liquids were also determined. RESULTS The LD50 values of SS single decoction， SS-PC （1∶2.5） combined decoction， SS-PC （1∶5） combined decoction and SS- PC （1∶5） mixture were 302.00， 614.47， 1 445.44 and 1 778.28 mg/kg， respectively. Compared with control group， the number of writhing movements and ear swelling degree in the mice of the above-mentioned medicinal liquid groups were reduced or decreased significantly （P＜0.05 or P＜0.01）； pain latency [at 90 and 120 minutes in the SS single decoction group， at 60 and 90 minutes in the SS-PC （1∶2.5） combined decoction group， and at 60，90， 120 minutes in the SS-PC （1∶5） combined decoction group and SS-PC （1∶5） mixture group] was significantly prolonged （P＜0.05 or P＜0.01）； analgesic rates of the respective medicinal liquids were 39.30%， 70.87%， 80.00% and 82.46%， and inflammation inhibition rates were 38.08%，TD 57.89%， 76.47% and 50.46%； analgesic and anti-inflammatory effects of combined decoction and mixture were generally better than those of the single decoction （P＜0.05 or P＜0.01）. In the above-mentioned four medicinal liquids， the total contents of strychnine were 0.71%， 0.42%， 0.47% and 0.64%， and the total contents of brucine were 0.88%， 0.63%， 0.57% and 0.88%， respectively. CONCLUSIONS The combination of P. tenuifolia can reduce the toxicity of SS and enhance its anti-inflammatory and analgesic effects. Moreover， there is a tendency for the toxicity-reducing and efficacy-enhancing effects to increase with the increasing dosage of P. tenuifolia. Additionally， the combined decoction of SS and P. tenuifolia can reduce the contents of the active and toxic components， strychnine and brucine， in SS.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.