ObjectiveTo develop traditional Chinese medicine （TCM） formulae for the treatment of nonsevere coronavirus disease 2019 （COVID-19） and to explore its anti-inflammatory mechanism. MethodsThe dysregulated signaling pathways were determined in macrophages from bronchoalveolar lavage fluid of COVID-19 patients and in lung epithelial cells infected with SARS-CoV-2 in vitro based on transcriptome analysis. A total of 102 TCM formulae for the clinical treatment of nonsevere COVID-19 were collected through literature. The pathway-reversing rates of these formulae in macrophages and lung epithelial cells were evaluated based on signature signaling pathways， and the basic formula was determined in conjunction with TCM theory. The commonly used Chinese materia medica for nonsevere COVID-19 were summarized from the 102 TCM formulae as abovementioned. And together with the screening results from the Pharmacopoeia of the People's Republic of China， a “Chinese materia medica pool” was esta-blished for the development of TCM formulae for COVID-19. The regulatory effects of each herb on signaling pathways were obtained based on targeted transcriptome analysis. Oriented at reversing dysregulated signaling pathways of COVID-19， the calculation was carried out， and the artificial intelligent methods for compositing formulae， that are exhaustive method and parallel computing， were used to obtain candidate compound formulas. Finally， with reference to professional experience， an innovative formula for the treatment of nonsevere COVID-19 was developed. The ethanol extract of the formula was evaluated for its anti-inflammatory effects by detecting the mRNA expression of interleukin 1b （Il1b）， C-X-C motif chemokine ligand 2 （Cxcl2）， C-X-C motif chemokine ligand 10 （Cxcl10）， C-C motif chemokine ligand 2 （Ccl2）， nitric oxide synthase 2 （Nos2）， and prostaglandin-endoperoxide synthase 2 （Ptgs2） using reverse transcription-quantitative polymerase chain reaction （RT-qPCR） in RAW264.7 cells treated with lipopolysaccharide （LPS）. ResultsIn macrophages and lung epithelial cells， 34 dysregulated signaling pathways associated with COVID-19 were identified respectively. The effects of the 102 formulae for clinical treatment of nonsevere COVID-19 were evaluated based on the dysregulated signaling pathways and targeted transcriptome， and the result showed that Yinqiao Powder and Pingwei Powder （银翘散合平胃散， YQPWP） ranked first， reversing 91.18% of the dysregulated signaling pathways in macrophages and 100% of the dysregulated signaling pathways in lung epithelial cells. Additionally， YQPWP had the function of scattering wind and clearing heat， resolving toxins and removing dampness in accordance with the pathogenesis of wind-heat with dampness in COVID-19. It was selected as the basic formula， and was further modified and optimized to develop an innovative fomula Qiaobang Zhupi Yin （翘蒡术皮饮， QBZPY） based on expert experience and artificial intelligence in composing formulae. QBZPY can reverse all the dysregulated signaling pathways associated with COVID-19 in macrophages and lung epithelial cells， with the reversing rates of 100%. The chief medicinal of QBZPY， including Lianqiao （Fructus Forsythiae）， Xixiancao （Herba Siegesbeckiae） and Niubangzi （Fructus Arctii）， can down-regulate multiple signaling pathways related with virus infection， immune response， and epithelial damage. RT-qPCR results indicated that compared with the model group， the QBZPY group down-regulated the mRNA expression of Il1b， tumor necrosis factor （Tnf）， Cxcl2， Cxcl10， Ccl2， Nos2 and Ptgs2 induced by LPS in RAW264.7 cells （P＜0.05 or P＜0.01）. ConclusionBased on targeted transcriptome analysis， expert experience in TCM and artificial intelligence， QBZPY has been developed for the treatment of nonsevere COVID-19. The ethanol extract of QBZPY has been found to inhibit mRNA expression of several pro-inflammatory genes in a cellular inflammation model.

The signaling pathways involved in acupuncture intervention in post-stroke depression (PSD) mainly include cAMP signaling pathway, MAPK signaling pathway, PI3K/Akt/mTOR signaling pathway, NF-κB signaling pathway, CREB signaling pathway, and CaMK signaling pathway. A variety of regulatory networks are formed between these signaling pathways, which play a key role in reducing inflammation, inhibiting apoptosis, improving neuroplasticity, promoting angiogenesis, and protecting neurons.

Objective To optimize the spray drying process of Banlangen(Isatidis Radix)formula granules based on quality by design(QbD)concept.Methods Using powder yield and the contents of uridine,adenosine,guanosine,and(R,S)-goitron as the critical quality attributes(CQAs),Plackett-Burman design was used to screen out critical process parameters(CPPs)for inlet temperature,spray pressure,liquid temperature,pump speed,and liquid relative density.The central-composite design(CCD)test was used to optimize the CPPs,which were screened.Based on the quadratic polynomial regression model,the design space of spray drying process of Banlangen(Isatidis Radix)formula granules was established,and further validated by experiments.Results Plackett-burman test results show that liquid relative density and inlet velocity are the key parameters for the study.The variance analysis results of CCD test showed that the constructed model in a good prediction ability,since the P-values of model was less than 0.01 and P-values of items lack of fit was more than 0.05.The optimized design space of CPPs was the liquid relative density 1.05-1.08,and pump speed 30%-40%.Conclusion Based on the QbD concept,the design space for the spray drying process of Banlangen(Isatidis Radix)formula granules can improve the stability of its process and help ensure the consistency of product quality.

During the occurrence and development of various heart diseases,continuous deterioration of myocardial fibrosis leads to remodeling and dysfunction of the cardiac structure.As a newly discovered mechanically sensitive ion channel,Piezo1 has opened up a new field of research on cellular mechanical transduction.Piezo1 combines a fine force transducer with Ca2+ influx and participates in the regulation of cellular mechanical transduction,thereby regulating cellular biological functions.Recent studies have shown that the biomechanical changes induced by myocardial injury regulate the expression of Piezo1 in cardiomyocytes and cause an imbalance in calcium homeostasis,which plays an important role in the positive feedback loop of myocardial fibrosis.This review summarizes the theoretical basis and related studies of Piezo1 in regulating cardiac fibrosis and suggests that the Piezo1 channel may become a new target for the treatment of cardiac fibrosis,thereby providing a new research horizon for the prevention and treatment of cardiac fibrosis.

Objective To explore the difference in efficacy of metoprolol versus ivabradine in the treatment of postural orthostatic tachycardia syndrome(POTS)in the elderly after COVID-19 infection.Methods A total of 110 patients diagnosed with POTS at our department from Decem-ber 1,2022 to January 31,2023 were included.According to their drug regimen,they were divided into metoprolol group(62 patients)and ivabradine group(48 patients).On the 28th day of out-patient follow-up,the resting heart rate,heart rate of 10 min of standing,symptom disappearance rate,hospitalization rate,and mortality rate were compared between the two groups.Results On the 28th day of treatment,the resting heart rate and postural heart rate for 10 min were decreased in both groups when compared with the levels at initial diagnosis(P＜0.01).And there were no significant differences in the two types of heart rate between the two groups on the 28th day(71.0±7.0 vs 72.1±7.0,P=0.401;76.5±7.2 vs 77.4±7.6,P=0.573).No obvious differences were observed between the two groups in symptom disappearance rate,hospitalization rate,or mortality rate(88.7％vs 89.6％,3.2％vs2.1％,0％vs 0％,P＞0.05).Conclusion Metoprolol and ivabradine can effectively treat POTS in the elderly patients after COVID-19 infection.

Objective To observe the incidence of pericardial tamponade(PT)after left atrial appendage closure(LAAC)in patients with non-valvular atrial fibrillation(NVAF),and to explore its related factors and outcomes.Methods NVAF patients who were hospitalized and treated with LAAC in Department of Cardiology of our hospital from August 2014 to March 2023 were selected for the study.The general clinical data,preoperative transthoracic echocardiography and transesophageal echocardiography data,results of routine preoperative laboratory tests,intraoperative data and follow-up data of the patients were collected through the hospital medical record management system.The enrolled patients were classified into the non-PT group(n=8)and the PT group(n =1184)according to whether PT occurred after LAAC or not.The incidence of PT,related risk factors and outcomes were statistically analyzed.Results This study included 639 males(53.6%)and 553 females(46.4%),with an average age of 68.1±9.65 years.The CHA2 DS2-VASc score was 4.51±1.72,and the HAS-BLED score was 3.36±1.09.PT occurred in 8 cases(0.67%),among them,6 cases occurred 1 to 33 h after LAAC,and 2 cases occurred on day 19 and day 27 after LAAC.As for the results of transesophageal echocardiography(TEE)and LAA angiography,compared with the non-PT group,the PT group had the significantly larger maximum caliber of the LAA(P=0.025,P=0.015),smaller maximum depth of the LAA(P=0.028,P=0.031),and lower success rate of one-time placement of the occluder(P=0.031);The occluder compression rate of the PT group was significantly greater than that of the non-PT group(P=0.046).Multivariate analysis showed that larger maximum diameter of LAA,smaller average effective depth of LAA and larger compression rate of occluder were the main risk factors for PT.All the 8 PT patients were cured by stopping antithrombotic drugs,pericardiocentesis or surgical drainage.During a mean follow-up of 39±27 months,there were no device-related thrombosis(DRT),ischemic stroke,systemic embolism and other complications in the PT group.Conclusion The incidence of PT after LAAC is low,which is related to the large diameter of LAA,the relatively insufficient depth of the LAA and the large compression rate of the occlude.PT can be cured by stopping antithrombotic drugs and pericardiocentesis/surgical drainage.

GLIl-altered mesenchymal tumors are a relatively rare type of mesenchymal tumor that is common in the head and neck.It is a newly added tumor type in the World Health Organization Tumor Classification of Head and Neck(5th edition).This article reports a case of GLI1-altered mesenchymal tumor occurring at the left tongue and reviews the relevant literature to summarize the pathological morphological characteristics,immunophenotype,molecular changes,clinical manifestations,and prognosis of the disease.

Multiple primary cancers(MPC)refer to the presence of more than one type of cancer with different histological features and sites in the same individual,and it is relatively rare in clinical practice.This article reports a case of decompensated cirrhosis with MPC and discusses the diagnosis,treatment,and clinical implications of this patient with decompensated cirrhosis and MPC.

Objective:To construct an prediction model based on magnetic resonance imaging (MRI) machine learning algorithm and radiomics and investigate its application value in predicting lymphovascular invasion (LVI) status of rectal cancer without lymph node metastasis.Methods:The retrospective cohort study was conducted. The clinicopathological data of 204 rectal cancer patients without lymph node metastasis who were admitted to Gansu Provincial Hospital from February 2016 to January 2024 were collected. There were 123 males and 81 females, aged (61±7)years. All 204 patients were randomly divided into the training dataset of 163 cases and the testing dataset of 41 cases by a ratio of 8∶2 using the electronic computer randomization method. The training dataset was used to construct the prediction model, and the testing dataset was used to validate the prediction model. The clinical prediction model, radiomics model and joint prediction model were constructed based on the selected clinical and/or imaging features. Measurement data with normal distribution were represented as Mean± SD. Count data were described as absolute numbers, and the chi-square test or Fisher exact probability were used for comparison between the groups. Comparison of ordinal data was conducted using the nonparameter rank sum test. The inter-class correlation coefficient (ICC) was used to evaluate the consistency of the radiomics features of the two doctors, and ICC >0.80 was good consistency. Univariate analysis was conducted by corres-ponding statistic methods. Multivariate analysis was conducted by Logistic stepwise regression model. The receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC), Delong test, decision curve and clinical impact curve were used to evaluate the diagnostic efficiency and clinical utility of the model. Result:(1) Analysis of factors affecting LVI status of patients. Of the 204 rectal cancer patients without lymph node metastasis, there were 71 cases with positive of LVI and 133 cases with negative of LVI. Results of multivariate analysis showed that gender, platelet (PLT) count and carcinoembryonic antigen (CEA) were independent factors affecting LVI status of rectal cancer without lymph node metastasis in training dataset [ odds ratio=2.405, 25.062, 2.528, 95% confidence interval ( CI) as 1.093-5.291, 2.748-228.604, 1.181-5.410, P<0.05]. (2) Construction of clinical prediction model. The clinical prediction model was conducted based on the results of multivariate analysis including gender, PLT count and CEA. Results of ROC curve showed that the AUC, accuracy, sensitivity and specificity of clinical prediction model were 0.721 (95% CI as 0.637-0.805), 0.675, 0.632 and 0.698 for the training dataset, and 0.795 (95% CI as 0.644-0.946), 0.805, 1.000 and 0.429 for the testing dataset. Results of Delong test showed that there was no significant difference in the AUC of clinical prediction model between the training dataset and the testing dataset ( Z=-0.836, P>0.05). (3) Construction of radiomics model. A total of 851 radiomics features were extracted from 204 patients, and seven machine learning algorithms, including logistic regression, support vector machine, Gaussian process, logistic regression-lasso algorithm, linear discriminant analysis, naive Bayes and automatic encoder, were used to construct the prediction model. Eight radiomics features were finally selected from the optimal Gaussian process learning algorithm to construct a radiomics prediction model. Results of ROC curve showed that the AUC, accuracy, sensitivity and specificity of radiomics prediction model were 0.857 (95% CI as 0.800-0.914), 0.748, 0.947 and 0.642 for the training dataset, and 0.725 (95% CI as 0.571-0.878), 0.634, 1.000 and 0.444 for the testing dataset. Results of Delong test showed that there was no significant difference in the AUC of radiomics prediction model between the training dataset and the testing dataset ( Z=1.578, P>0.05). (4) Construction of joint prediction model. The joint prediction model was constructed based on the results of multivariate analysis and the radiomics features. Results of ROC curve showed that the AUC, accuracy, sensitivity and specificity of radiomics prediction model were 0.885 (95% CI as 0.832-0.938), 0.791, 0.912 and 0.726 for the training dataset, and 0.857 (95% CI as 0.731-0.984), 0.854, 0.714 and 0.926 for the testing dataset. Results of Delong test showed that there was no significant difference in the AUC of joint prediction model between the training dataset and the testing dataset ( Z=0.395, P>0.05). (5) Performance comparison of three prediction models. Results of the Hosmer-Lemeshow goodness-of-fit test showed that all of the clinical prediction model, radiomics prodiction model and joint prediction model having good fitting degree ( χ2=1.464, 12.763, 10.828, P>0.05). Results of Delong test showed that there was no signifi-cant difference in the AUC between the clinical prediction model and the joint prediction model or the radiomics model ( Z=1.146, 0.658, P>0.05), and there was a significant difference in the AUC between the joint prediction model and the radiomics model ( Z=2.001, P<0.05). Results of calibra-tion curve showed a good performance in the joint prediction model. Results of decision curve and clinical impact curve showed that the performance of joint prediction model in predicting LVI status of rectal cancer without lymph node metastasis was superior to the clinical prediction model and the radiomics model. Conclusions:The clinical prediction model is constructed based on gender, PLT count and CEA. The radiomics predictive model is constructed based on 8 selected radiomics features. The joint prediction model is constructed based on the clinical prediction model and the radiomics predictive model. All of the three models can predict the LVI status of rectal cancer with-out lymph node metastasis, and the joint prediction model has a superior predictive performance.

Objective:To investigate the effects of subcutaneous immunotherapy (SCIT) on patients′ immune markers and metabolic levels in the early stage of allergen treatment, and to gain insight into the role of SCIT in regulating immune responses and metabolic levels, so as to provide reference data for the further discovery of potential biomarkers.Methods:A longitudinal study was used to include 40 subjects who underwent SCIT with dust mite allergens in the Department of Pediatrics of the First Affiliated Hospital of Guangzhou Medical University between November 2017 and February 2022, including 20 subjects each of single mite subcutaneous immunotherapy (SM-SCIT) and double mite subcutaneous immunotherapy (DM-SCIT). In this study, levels of dust mite allergen-specific antibodies and polyunsaturated fatty acid metabolism were measured before and 12 months after treatment, while pulmonary function tests were performed. The therapeutic effects of the patients were followed up by visual analogue scale (VAS), asthma control test (ACT) and total medication scores (TMS). The results were statistically analyzed using t-test and Mann-Whitney U-test. Results:After 12 months of treatment with SCIT, both groups showed a significant decrease in total VAS score (SM-SCIT: Z=-2.298, P<0.05; DM-SCIT: Z=-3.411, P<0.001); total ACT score (SM-SCIT: Z=-2.054, P<0.05; DM-SCIT: Z=-2.014, P<0.05) and total medication scores (SM-SCIT: Z=-3.799, P<0.000 1; DM-SCIT: Z=-3.474, P<0.001) were significantly higher, in addition to significantly higher MMEF75/25 values in the DM-SCIT group ( t=-2.253, P<0.05). There was no significant change in sIgE in the SM-SCIT group ( P>0.05), and the sIgG4 levels of the Der p, Der f, p 1, p 2, f 2, and p 21 fractions were significantly elevated ( Z=-2.651, -3.771, -2.949, -2.912, -2.725, -2.128, and -3.285, respectively, all P<0.05); The sIgE of Der p 2, f 2, p 7 and p 23 fractions( Z=-2.651, -3.771, -2.949, -2.912, -2.725, -2.128, -3.285, all P<0.05) and the sIgG4 levels of the Der p, Der f, p 1, p 2, f 1, f 2, p 10, p 21 and p 23 fractions ( Z=-3.808, -3.845, -3.061, -2.688, -2.464, -3.211, -2.371, -2.091, -2.427, all P<0.05) of the DM-SCIT group were significantly elevated. Metabolomics analysis showed that arachidonic acid, docosahexaenoic acid, docosapentaenoic acid, eicosapentaenoic acid, 5, 9, 12-octadecatrienoic acid, 5(S)-hydroxylated eicosatetraenoic acid, and dihomo-gamma-linolenic acid were significantly elevated at the beginning of the treatment period after SM-SCIT treatment ( Z of -2.191, -2.497, -1.988, -2.090, -2.19, -2.803, -2.073, all P<0.05); 5(S)-hydroxylated eicosatetraenoic acid showed elevated and alpha-linolenic acid, eicosadienoic acid, and eicosapentaenoic acid were significantly decreased in the DM-SCIT group after treatment ( Z=-1.988, -2.090, -2.497, -1.988, respectively, all P<0.05). Correlation analysis showed that arachidonic acid was significantly negatively correlated with changes in dust mite-specific IgG4 ( r=-0.499, P<0.05), and that alpha-linolenic acid, 5, 9, 12-octadecatrienoic acid, and eicosapentaenoic acid were positively correlated with the ΔsIgG4 of the dust mite der p 2 ( r=0.451, 0.420, 0.474, respectively; all P<0.05). Conclusion:Significant changes in allergen-specific antibody levels and polyunsaturated fatty acid metabolism levels occur during SCIT, and the two may interact and influence each other.