This study aims to explore the impact of host plants on the quality of Taxilli Herba and provide a theoretical basis for the quality control of Taxilli Herba. The components of Taxilli Herba from three different host plants(Morus alba, Salix babylonica, and Cinnamomum cassia) and its 3 hosts(mulberry branch, willow branch, and cinnamon branch) were detected by widely targeted metabolomics based on ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS). Principal component analysis(PCA), orthogonal partial least squares discriminant analysis(OPLS-DA), and Venn diagram were employed for analysis. A total of 717 metabolites were detected in Taxilli Herba from the three host plants and the branches of these host plants by UPLC-MS/MS. The results of PCA and OPLS-DA of Taxilli Herba from the three different host plants showed an obvious separation trend due to the different effects of host plants. The Venn diagram showed that there were 32, 8, and 26 characteristic metabolites in samples of Taxilli Herba from M. alba host, S. babylonica host, and C. cassia host, respectively. It was found by comparing the characteristic metabolites of Taxilli Herba and its hosts that each host transmits its characteristic components to Taxilli Herba, so that the Taxilli Herba contains the characteristic components of the host. The Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis showed that the differential metabolites of Taxilli Herba from the three hosts were mainly enriched in flavonoid biosynthesis, arginine and proline metabolism, and glycolysis/gluconeogenesis pathways. Furthermore, the differential metabolites enriching pathways of Taxilli Herba from the three hosts were different depending on the host. In a word, host plants have a significant impact on the metabolites of Taxilli Herba, and it may be an important factor for the quality of Taxilli Herba.
Metabolomics/methods* ; Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Quality Control ; Salix/chemistry* ; Cinnamomum aromaticum/metabolism* ; Principal Component Analysis

Targeting drug delivery systems mediated by nanoparticles has shown great potential in the diagnosis and treatment of cancer. However, influences of different tumor progressions on the accumulation of nanoparticles, especially the ligand-modified active targeting nanoparticles are seldom exploited. In this work, the accumulation and penetration of RGD-modified gold nanoparticles (active AuNPs) with different sizes were investigated in orthotopic breast cancer with different tumor progressions. The results showed that the smallest active AuNPs had better accumulation and permeation effects in early tumor tissues with the relatively looser extracellular matrix, larger gaps, lower interstitial fluid pressure, and less receptor expression, which was due to size effects. However, the larger active AuNPs had better accumulation and penetration effects in late tumor tissues with highly expressed target receptors integrin α _v β ₃ because of the multivalent interactions between larger active nanoparticles and integrin α _v β ₃. In the midterm, tumor accumulation of active AuNPs was equally influenced by size effects and multivalent interactions. Therefore, RGD-modified nanoparticles with sizes of 7 and 90 nm accumulated more in tumors. This study will guide a rational design of active targeting nanoparticles for enhancing the diagnosis and treatment of tumors based on their progressions.

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Two methods including gas chromatography tandem mass spectrometry (GC-MS/MS) and high-performance liquid chromatography tandem mass spectrometry (LC-MS/MS) were established to detect common alkyl sulfonates and aryl sulfonates genotoxic impurities. Four alkyl sulfonates and methyl benzenesulfonate were determined by GC-MS/MS using butyl methanesulfonate as the internal standard, the chromatographic column was HP-5MS UI (30 mm × 0.25 mm, 0.25 µm), the carrier gas was helium, the flow rate was 1.0 mL·min^-1 in a constant flow mode, the sample inlet temperature was set to 250 ℃, the split ratio was 10∶1, and the initial temperature of the heating program was 80 ℃, maintained for 1 minute, and then increased to 240 ℃ at a heating rate of 30 ℃·min^-1 for 2 minutes. The mass spectrometry detector was an electron bombardment ion source (EI source), the data collection condition was multi reaction monitoring mode (MRM), and method validation using the raw material of clinical drug citalopram hydrobromide as a sample. The results showed that the linear range of four alkyl sulfonates and methyl benzenesulfonate were good at 3-50 ng·mL^-1 and 9-150 ng·mL^-1, with a correlation coefficient of r > 0.999, The spiked recovery was 80%-120%. The detection limits were 1 and 3 ng·mL^-1; Ten aryl sulfonates determined by LC-MS/MS, the chromatographic column was CSH Fluoro phenyl (100 mm × 2.1 mm, 1.7 µm), the mobile phase was methanol (B)-5 mmol·L^-1 ammonium formate (D), with a flow rate of 0.2 mL·min^-1, and gradient elution was performed. The gradient program (T/% B) was set as 0/20, 25/90, 35/90, 42/20. The mass spectrometer detector was electro spray ionization with positive ionization mode (ESI⁺), the data collection was in dynamic multi reaction monitoring mode (dMRM), and the method was validated using the raw material of the clinical drug citalopram hydrobromide as a sample. The results showed that the linear range of aryl sulfonates were good at 9-2 000 ng·mL^-1, 3-100 ng·mL^-1 and 0.9-30 ng·mL^-1, respectively. The correlation coefficient r > 0.999, the spiked recovery was 80%-120%. The detection limits were 30, 1 and 0.3 ng·mL^-1. Two detection methods did not detect potential sulfonate genotoxicity impurities in the above APIs. The established analytical methods are reliable and effective, which can provide reference for drug quality control and detection.

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Objective To explore the incidence of long CO VID symptoms in patients infected with Omicron variant of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Methods According to the inclusion and exclu-sion criteria of literatures,relevant studies without language restrictions published up to 2024 were retrieved from both Chinese and English databases.The Chinese databases were China National Knowledge Infrastructure(CNKI),Wanfang Database,and VIP databases,and the foreign databases were PubMed,Embase,and Web of Science.Three-step screening was used to select literatures,and Stata 17.0 software was used for analysis.Results The incidence of at least one sequelae in patients infected with Omicron variant was 29.62％.The most common symptoms included fatigue(19.10％),joint or muscle pain(11.06％),memory loss(9.71％),brain fog(8.80％),cough(8.42％),headache(7.26％),and sore throat(6.68％).Subgroup analysis results showed that with the extension of follow-up(3 months vs 6 months),the incidence of smell or taste changes was significantly re-duced(7.22％vs 0.78％).The higher the proportion of women(＜50％vs 50％-65％vs＞65％),the higher the incidence of joint or muscle pain(1.09％vs 4.62％vs 19.53％);the greater the median age(≥45 years vs＜45 years),the higher the incidence of chest pain or chest distress(0.90％vs 3.86％),all with statistically significant differences(all P＜0.05).Conclusion Incidence of long COVID in Omicron-infected patients is high and can cause various symptoms.Follow-up time,median age and gender proportion have significant impacts on the incidence of some symptoms.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To investigate the efficacy and adverse reactions of whole-lung low-dose radiotherapy (LDRT) in patients with severe/critical coronavirus disease 2019 (COVID-19).Methods:Eight patients with severe/critical COVID-19 treated in the Jiangyin Hospital Affiliated to Nantong University from January to June 2023 who were treated with whole-lung LDRT after deteriorating or failing to improve post-medical treatment were enrolled in this single-arm phase I clinical trial. They received anterior-posterior penetrating radiation in a supine or prone position, with a total dose range from 0.5 to 1.5 Gy and a dose weight ratio of 1∶1. The oxygenation status, inflammatory markers, and imaging changes before and after radiotherapy were analyzed, and patients were followed up for acute radiation-induced adverse reactions.Results:One week after LDRT, the SaO 2/FiO 2 or PaO 2/FiO 2 indices increased in seven patients (87.5%), inflammatory markers such as C-reactive protein (CRP) and interleukin-6 (IL-6) decreased in seven patients (87.5%), and chest CT/chest radiographs revealed a significant reduction in the extent of pneumonia involvement in 5 patients (62.5%). No evident acute radiation-related adverse reactions were observed. Conclusions:Whole-lung LDRT with a dose range from 0.5 to 1.5 Gy can reduce inflammatory markers, improve clinical symptoms, and promote inflammatory absorption in patients with severe/critical COVID-19 who responded poorly to medical treatment while not inducing acute adverse reactions.

Lixuwang~® Xuesaitong Soft Capsules(referred to as "Xuesaitong Soft Capsules") have the effects of promoting blood circulation, resolving blood stasis, and dredging meridians and collaterals. They are widely used in the prevention and treatment of cardiovascular and cerebrovascular diseases in clinical practice. Through years of clinical observation, they have shown significant efficacy in ischemic stroke, coronary heart disease, and other diseases, and have been recommended by multiple guidelines, consensus statements, and monographs. Based on the summary of clinical application experience by doctors and existing evidence-based research, following the Technical Specifications for Consensus Development of Chinese Patent Medicine by Clinical Experts issued by Standardization Office of the Chinese Association of Traditional Chinese Medicine, a nominal group method was used to reach 19 recommended opinions/consensus suggestions. This document proposes the timing of medication, syndrome differentiation for medication, therapeutic effects, dosage and administration, treatment duration, economic considerations, and safety considerations in the use of Xuesaitong Soft Capsules for the treatment of ischemic stroke and angina pectoris in coronary heart disease. It is intended for doctors in internal medicine, encephalopathy(neurology), cardiovascular medicine, geriatrics, emergency medicine, general practice, and traditional Chinese medicine departments of various medical institutions, as well as pharmacists in hospitals and pharmacies, as a medication reference when using Xuesaitong Soft Capsules. It is hoped that the widespread application of this consensus can improve the clinical efficacy of Xuesaitong Soft Capsules in the treatment of ischemic stroke and coronary heart disease, promote rational drug use, and reduce medication risks. This consensus has been reviewed and published by the China Association of Traditional Chinese Medicine, with the identification number GS/CACM 323-2023.
Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Coronary Disease/drug therapy* ; Ischemic Stroke/drug therapy* ; Capsules

OBJECTIVES: To explore the application of whole-genome sequencing (WGS) in the rapid clinical diagnosis of critically ill neonates. METHODS: The critically ill neonates who admitted to the neonatal intensive care unit of Children's Hospital of Fudan University and underwent WGS from August to September, 2019 were enrolled in this prospective study. The genetic testing results and clinical outcome were analyzed with reference to the sequencing data and clinical features of the neonates. RESULTS: A total of 15 neonates were tested, among whom there were 9 boys and 6 girls. The main reason for hospitalization included abnormal breathing in 7 neonates, poor response in 2 neonates, feeding difficulty in 2 neonates, fever in 1 neonate, hypothermia in 1 neonate, preterm birth in 1 neonate, and convulsion in 1 neonate. The mean turn-around time was 4.5 days for WGS. Finally a genetic diagnosis was obtained for 3 neonates, with a positive diagnostic rate of 20% (3/15). Among the 3 neonates, 2 neonates were withdrawn from the treatment due to severe conditions and 1 neonate died on the day when the sample was sent for genetic testing, whose etiology could be explained by the results of genetic testing. CONCLUSIONS WGS technique can provide a timely and effective diagnosis for critically ill neonates suspected of genetic diseases and provide genetic evidence for clinical treatment of critically ill cases.
Infant, Newborn ; Male ; Child ; Female ; Humans ; Critical Illness ; Prospective Studies ; Premature Birth ; Dyspnea ; Fever