Signal detection is a critical task in drug safety regulation. However, it inevitably generates irrelevant or false signals, posing challenges for resource allocation by marketing authorization holders. To reasonably assess these signals, different countries have established various principles for prioritizing the evaluation of risk signals. This study systematically compares these principles and finds that the U.S. Food and Drug Administration(FDA) focuses on practical issues, such as identifying drug confusion or drug interactions. However, China's Good Pharmacovigilance Practices and the European Medicines Agency(EMA) emphasize a comprehensive evaluation framework. The Council for International Organizations of Medical Sciences(CIOMS) emphasizes the consistency of multiple data sources, highlighting the reliability of signal evaluation. China practices a multidisciplinary approach combining traditional Chinese and western medicine, and the risk signals related to traditional Chinese medicine(TCM) have unique characteristics, including complex components, cumulative toxicity, specific theoretical foundations, and drug interactions. The different priorities in risk signal evaluation principles across countries suggest that China should strengthen clinical trial research, emphasize corroboration with evidence of multiple sources, and pay particular attention to the risks of drug interactions in the TCM regulatory science. Establishing the risk signal prioritization principles that align with the characteristics of TCM enables more precise and efficient scientific regulation of TCM.
Humans ; Medicine, Chinese Traditional/standards* ; China ; Drugs, Chinese Herbal/adverse effects* ; United States ; United States Food and Drug Administration

Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

Tuberculosis(TB),a chronic infectious disease caused by infection with the Mycobacterium tuberculosis complex(MTBC),has re-emerged as the leading cause of death from a single infectious agent worldwide.Because of widespread use and mis-use of anti-tuberculosis drugs,the emergence of multidrug-resistant TB(MDR-TB)and extensively drug-resistant TB(XDR-TB)is increasing,thus posing a serious threat to global health.The current problem of drug resistance is a major prevention and treatment challenge;therefore,the search for new drug targets is urgently needed.In recent years,substantial progress has been made in re-search on anti-tuberculosis drug targets and novel therapeutic strategies.Herein,we summarize recent research progress in anti-tuberculosis drug targets,primarily cell wall synthesis,nucleic acid replication and transcription,and energy metabolism.We also provide an overview of research progress regarding two novel therapeutic strategies,to provide a theoretical basis and research ideas for the development of new clinical drugs.

Tuberculosis(TB),a chronic infectious disease caused by infection with the Mycobacterium tuberculosis complex(MTBC),has re-emerged as the leading cause of death from a single infectious agent worldwide.Because of widespread use and mis-use of anti-tuberculosis drugs,the emergence of multidrug-resistant TB(MDR-TB)and extensively drug-resistant TB(XDR-TB)is increasing,thus posing a serious threat to global health.The current problem of drug resistance is a major prevention and treatment challenge;therefore,the search for new drug targets is urgently needed.In recent years,substantial progress has been made in re-search on anti-tuberculosis drug targets and novel therapeutic strategies.Herein,we summarize recent research progress in anti-tuberculosis drug targets,primarily cell wall synthesis,nucleic acid replication and transcription,and energy metabolism.We also provide an overview of research progress regarding two novel therapeutic strategies,to provide a theoretical basis and research ideas for the development of new clinical drugs.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Abstract: Objective To explore the risk factors for macrolide unresponsive mycoplasma pneumoniae pneumonia (MUMPP) in children and to develop a model for predicting the risk of MUMPP. Methods Children with mycoplasma pneumoniae pneumonia admitted to the Pediatric Department of Leshan People's Hospital who met the inclusion criteria from March 1, 2023, to December 1, 2023, were retrospectively selected and divided into the responsive group and unresponsive group according to their reactions to macrolides. General patient data, laboratory tests, and imaging findings were collected and compared. Logistic regression analysis was used to analyze the risk factors of the Macrolide unresponsive mycoplasma pneumoniae pneumonia, and R language (R4.2.3) to establish the nomogram model. The goodness of fit, discriminative ability, calibration, and clinical utility of the model were assessed using the Hosmer-Lemeshow goodness of fit test, receiver operating characteristic (ROC) curve analysis, calibration curve analysis, and decision curve analysis, respectively. Results A total of 224 patients were included in the analysis of children. Among them, 156 (70%) were randomly selected as the training set, and the remaining 68 cases (30%) were used as the validation set. Logistic regression analysis revealed that pleural effusion (OR=6.986, 95%CI 1.362-35.847), highest temperature before admission (OR=3.095, 95%CI 1.487-6.439), neutrophil count (OR=1.294, 95%CI:1.103-1.519), C-reactive protein (OR=1.030, 95%CI 1.002-1.058), and procalcitonin (OR=2.899, 95%CI:1.353-6.214) were independent risk factors for MUMPP in children (all P<0.05). A nomogram was established using R software. The Hosmer-Lemeshow goodness of fit tests for the training set and the validation set were χ2=4.018 and χ2=4.657 (all P>0.05), indicating a good fit of the model. The AUC values for the training set and validation were 0.825 (95%CI: 0.755-0.894) and 0.828 (95%CI 0.729-0.928), respectively, suggesting good discriminative ability of the model. Calibration curve analysis suggested that the model had good predictive performance, while decision curve analysis indicated a high clinical application value of the predictive model. Conclusions Pleural effusion, highest body temperature before admission, neutrophil count, C-reactive protein, and procalcitonin are independent risk factors for MUMPP in children. The prediction model constructed based on the above variables has high predictive efficacy and clinical application value.

Objective To explore the severity of loneliness among the elderly in communities in Shanghai,and to identify factors associated with social and emotional loneliness respectively.Methods A cross-sectional study was conducted in older adults aged 65 years or above in Pudong New Area,Jing'an District and Huangpu District in Shanghai from Mar to Jun 2021.In Pudong New Area,multi-stage stratified random sampling was conducted based on the age and gender distribution of Shanghai,while in Huangpu District and Jing'an District convenience sampling was conducted.A total of 635 samples were included in the study.Loneliness was assessed using the De Jong Gierveld Loneliness Scale with social and emotional loneliness subscales.Logistic regression analyses were conducted to identify factors associated with social and emotional loneliness.Results Among the 635 participants,only 53 older adults(8.4%)were not lonely.Female(OR=0.46,95%CI:0.31-0.70),higher self-efficacy(OR=0.97,95%CI:0.94-1.00),more objective social support(OR=0.96,95%CI:0.93-0.99)were associated with less severe social loneliness.Meanwhile,higher level of education(secondary education,OR=0.56,95%CI:0.34-0.95;college or above,OR=0.30,95%CI:0.11-0.83)and higher self-efficacy(OR=0.96,95%CI:0.93-0.99)were associated with less severe emotional loneliness,while depression(OR=3.41,95%CI:1.76-6.60)and worse social capital(OR=2.02,95%CI:1.29-3.16)were associated with more severe emotional loneliness.Conclusion Up to 91.6%of the elderly in our study sample were moderately lonely or above.The factors associated with social loneliness include self-efficacy,gender and social support.The factors associated with emotional loneliness are self-efficacy,education level,depression,and social capital.

AIM To investigate the protective effects and the mechanism of the Liuwei Dihuang Pills on mouse brain microvascular endothelial(bEnd.3)cells damaged by β-Amyloid protein1-40(Aβ1-40).METHODS CCK8 method was used to detect the effects of Aβ1-40 and medicated serum of Liuwei Dihuang Pills(MSLDP)on cell activity,and to screen the appropriate concentration.bEnd.3 cells of the control group,the Aβ1-40 group,the MSLDP+Aβ1-40 group and the MSLDP group had their low density lipoprotein-associated protein 1(LRP1),receptor for advanced glycation end products(RAGE),matrix metalloproteinase-2(MMP-2),MMP-9,scaffold protein zonule protein-1(ZO-1)detected by Western blot.bEnd.3 cells assigned into the control group,the Aβ1-40 group,the FPS-ZM1(RAGE inhibitor)+Aβ1-40 group and the FPS-ZM1+Aβ1-40+MSLDP group had their expressions of RAGE,MMP-9,MMP-2 and ZO-1 detected by Western blot as well.RESULTS The cell activity of bEnd.3,was dose-dependently decreased by Aβ1-40(P<0.01),but was protected by MSLDP(P<0.05,P<0.01).And 10 μmol/L Aβ1-40 and 10%MSLDP were selected for subsequent experiments.Compared with the control group,the Aβ1-40 group displayed increased protein expressions of RAGE,MMP-2 and MMP-9(P<0.01),decreased protein expressions of LRP1,ZO-1 and BDNF(P<0.05,P<0.01),and decreased fluorescence intensities of LRP1 and ZO-1(P<0.01).Compared with the Aβ1-40 group,the MSLDP group shared decreased expressions of RAGE,MMP-2,MMP-9 proteins and RAGE fluorescence intensity(P<0.05,P<0.01),and increased expressions of LRP1,ZO-1 and BDNF proteins,and the fluorescence intensity of LRP1 and ZO-1(P<0.05,P<0.01);the Aβ1-40+FPS-ZM1 group displayed decreased protein expressions of MMP-2,MMP9 and RAGE(P<0.05,P<0.01),and increased ZO-1 protein expression(P<0.05);and the Aβ1-40+FPS-ZM1+ MSLDP group displayed an even more decreased protein expressions of MMP-2,MMP9 and RAGE(P<0.01),increased ZO-1 protein expression(P<0.01)due to the the combination use of FPS-ZM1 and MSLDP.CONCLUSION Liuwei Dihuang Pills can protect the tight junction of bEnd.3 injured by Aβ1-40 and neurovascular units from Alzheimer's disease by alleviating the dysfunction of the blood-brain barrier via RAGE-mediated MMP-2/MMP-9 pathway inhibition.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

The usage of pesticides can enhance the production of crops,but their overuses may be hazardous to both people health and the environment.Thus,it is of great significance to develop effective methods to detect pesticides.Metal nanoclusters(MNCs)have become increasingly popular in analytical sensing areas because of their miniscule size,high stability,ease of manufacturing and good biocompatibility.They have exhibited great potential in the field of pesticides detection.In this paper,the detection methods of pesticides by using MNCs and their development in detection of organophosphorus pesticides,organic nitrogen pesticides,organochlorine pesticides and other types of pesticides were reviewed.Finally,the development prospects were discussed.