Objective To investigate the application value of bronchoalveolar lavage fluid(BALF)met-agenomic next-generation sequencing(mNGS)in elderly patients with severe pneumonia.Methods A total of 48 elderly patients with severe pneumonia admitted to the intensive care unit from January to August 2024 were selected and randomly divided into an observation group and a control group,with 24 patients in each group.BALF samples were collected within 24 hours of ICU admission from both groups,with lavage per-formed at the most radiologically evident lesion site.The control group underwent traditional culture at the hospital,while the observation group had one specimen sent for mNGS testing and another specimen subjected to traditional culture at the hospital.Comparison of detection results between mNGS and traditional culture in the observation group,pathogen distribution,infection markers(on days 4 and 7 of ICU admission),and prog-nostic outcomes were compared between the groups.Results The observation group showed higher positive detection rates and higher rates of detecting ≥2 pathogens by mNGS compared to both traditional culture in the same group and the control group(P＜0.05).Excluding Acinetobacter baumannii,Candida albicans,Can-dida glabrata,and Raoultella planticola,the observation group detected higher quantities of fungi,viruses,and rare pathogens than the control group.On days 4 and 7 of ICU admission,the observation group had signifi-cantly lower body temperature,white blood cell count,C reactive protein,and procalcitonin levels compared to the control group(P＜0.05).The observation group also demonstrated shorter ICU stays,reduced mechanical ventilation duration,and total lower hospitalization costs than the control group(P＜0.05).Conclusion BALF mNGS facilitates early identification of mixed and rare pathogens,improves detection rates,broadens microbial coverage,and shortens testing time.

Objective To explore the predictive value of heel blood thyrotropin stimulating hormone(TSH)and insulin-like growth factor-1(IGF-1)for congenital hypothyroidism(CH).Methods A total of 83 children with CH admitted to the Seventh Medical Center of the Chinese People's Liberation Army General Hospital from January 2021 to January 2024 were selected as the study group,and 53 healthy newborns born and examined in the center during the same period were selected as the control group.Heel blood TSH,IGF-1 and thyroid function were measured in both groups.Heel blood TSH,IGF-1 and thyroid function indexes were compared between the two groups,and the correlation between heel blood TSH,IGF-1 and thyroid function indexes was analyzed,the influencing factors of CH occurrence were analyzed,and the predictive value of heel blood TSH,IGF-1 and thyroid indexes for CH was analyzed.Results Pearson correlation analysis showed that heel blood TSH was negatively correlated with FT4,TT3,FT3 and TT4(r=-0.522,-0.468,-0.539,-0.667,all P＜0.05).IGF-1 was positively correlated with FT4,TT3,FT3,TT4(r=0.394,0.427,0.511,0.562,all P＜0.05).The results of receiver operating characteristic curve analysis showed that the area under the curve of TSH,IGF-1 and their combination were 0.800,0.794 and 0.822,respectively.Univariate and multiple Logistic regression analysis showed that birth weight,family history,TSH,IGF-1,FT4,FT3 were the influencing factors for the occurrence of CH(P＜0.05).Conclusion The combined detection of TSH and IGF-1 levels in heel blood has a certain predictive value for the occurrence of CH,and can provide a basis for the disease assessment of children.

Artificial intelligence(AI)has emerged as a cutting-edge technology leading the future and is a key engine for China's development.In the innovation and research of medical devices,AI has provided critical support in the areas of intelligent diagnostic assistance,intelligent therapeutic assis-tance,intelligent monitoring,life support,et al.Ma-chine learning-enabled device software functions(ML-DSFs)have become an essential component of many medical devices.Recently,the United States Food and Drug Administration(FDA)released a draft guidance titled"Marketing Submission Rec-ommendations for a Predetermined Change Con-trol Plan for Artificial Intelligence/Machine Learn-ing(AI/ML)-Enabled Device Software Functions(Draft)."that aimed to provide a forward-looking approach to foster the development of ML medical devices.By supporting iterative updates through modifications,this approach ensures the continu-ous safety and effectiveness of the devices.This guidance represents the latest in regulatory direc-tion and is especially beneficial for enhancing the quality and efficiency of clinical trials for AI prod-ucts.Therefore,we plan to provide a detailed intro-duction and interpretation of the guidance,with the aim of learning from international advanced regulatory concepts and experiences to promote the development of ML-DSFs with more profound international influence.

Artificial intelligence(AI)has emerged as a cutting-edge technology leading the future and is a key engine for China's development.In the innovation and research of medical devices,AI has provided critical support in the areas of intelligent diagnostic assistance,intelligent therapeutic assis-tance,intelligent monitoring,life support,et al.Ma-chine learning-enabled device software functions(ML-DSFs)have become an essential component of many medical devices.Recently,the United States Food and Drug Administration(FDA)released a draft guidance titled"Marketing Submission Rec-ommendations for a Predetermined Change Con-trol Plan for Artificial Intelligence/Machine Learn-ing(AI/ML)-Enabled Device Software Functions(Draft)."that aimed to provide a forward-looking approach to foster the development of ML medical devices.By supporting iterative updates through modifications,this approach ensures the continu-ous safety and effectiveness of the devices.This guidance represents the latest in regulatory direc-tion and is especially beneficial for enhancing the quality and efficiency of clinical trials for AI prod-ucts.Therefore,we plan to provide a detailed intro-duction and interpretation of the guidance,with the aim of learning from international advanced regulatory concepts and experiences to promote the development of ML-DSFs with more profound international influence.

Thyroid cancer (TC) is the most common endocrine malignancy. Although most patients have a favorable prognosis following standardized treatment,a subset experiences rapid disease progression and poor outcomes. Recent studies have identified N6-methyladenosine (m6A) methylation as the most prevalent RNA modification,which regulates RNA transcription,maturation,degradation,and stability,playing a role throughout the tumorigenesis process. Consequently,m6A methylation has been extensively studied in tumor treatment and prevention. Changes in m6A levels can lead to abnormal activation or inhibition of oncogenes or tumor suppressor genes in TC,thereby contributing to its initiation and progression. This review summarizes the concept of m6A methylation,the components and functions of its regulatory factors,its role in the development and progression of TC,and its implications for treatment and prognosis.

Objective To explore the reliability and safety of continuous monitoring of vital signs in patients using wireless wearable monitoring devices after video-assisted thoracoscopic surgery (VATS) for lung cancer. Methods The patients undergoing VATS for lung cancer in West China Hospital, Sichuan University from May to August 2023 were prospectively enrolled. Both wireless wearable and traditional wired devices were used to monitor the vital signs of patients after surgery. Spearman correlation analysis, paired sample t test and ratio Bland-Altman method were used to test the correlation, difference and consistency of monitoring data measured by the two devices. The effective monitoring rate of the wireless wearable device within 12 hours was calculated to test the reliability of its continuous monitoring. Results A total of 20 patients were enrolled, including 15 females and 5 males with an average age of 46.20±11.52 years. Data collected by the two monitoring devices were significantly correlated (P<0.001). Respiratory rate and blood oxygen saturation data collected by the two devices showed no statistical difference (P>0.05), while heart rate measured by wireless wearable device was slightly lower (=−0.307±1.073, P<0.001), and the blood pressure (=1.259±5.354, P<0.001) and body temperature(=0.115±0.231, P<0.001) were slightly higher. The mean ratios of heart rate, respiratory rate, blood oxygen saturation, blood pressure and body temperature collected by the two devices were 0.996, 1.004, 1.000, 1.014, and 1.003, respectively. The 95% limits of agreement (LoA) and 95% confidence interval of 95%LoA of each indicator were within the clinically acceptable limit. The effective monitoring rate of each vital signs within 12 hours was above 98%. Conclusion The wireless wearable device has a high accuracy and reliability for continuous monitoring vital signs of patients after VATS for lung cancer, which provides a security guarantee for subsequent large-scale clinical application and further research.

Objective To construct a machine learning prediction model for postoperative liver injury in patients with non-liver surgery based on preoperative and intraoperative medication indicators.Methods A case-control study was conducted on 315 patients with liver injury after non-liver surgery selected from the databases developed by 3 large general hospitals from January 2014 to September 2022.With the positive/negative ratio of 1 ∶3,928 cases in corresponding period with non-liver surgery and without liver injury were randomly matched as negative control cases.These 1243 patients were randomly divided into the modeling group(n=869)and the validation group(n=374)in a ratio of 7∶3 using the R language setting code.Preoperative clinical indicators(basic information,medical history,relevant scale score,surgical information and results of laboratory tests)and intraoperative medication were used to construct the prediction model for liver injury after non-liver surgery based on 4 machine learning algorithms,k-nearest neighbor(KNN),support vector machine linear(SVM),logic regression(LR)and extreme gradient boosting(XGBoost).In the validation group,receiver operating characteristic(ROC)curve,precision-recall curve(P-R),decision curve analysis(DCA)curve,Kappa value,sensitivity,specificity,Brier score,and F1 score were applied to evaluate the efficacy of model.Results The model established by 4 machine learning algorithms to predict postoperative liver injury after non-liver surgery was optimal using the XGBoost algorithm.The area under the receiver operating characteristic curve(AUROC)was 0.916(95%CI:0.883～0.949),area under the precision-recall curve(AUPRC)was 0.841,Brier score was 0.097,and sensitivity and specificity was 78.95%and 87.10%,respectively.Conclusion The postoperative liver injury prediction model for non-liver surgery based on the XGBoost algorithm has effective prediction for the occurrence of postoperative liver injury.

Objective:To construct a mouse asthma model induced by mugwort pollen and to explore endotyping,providing methods for subsequent precision treatment.Methods:BALB/c mice were intraperitoneally injected with mugwort pollen extract(MPE)to sensitize,following MPE intranasal challenge to construct MPE allergic asthma murine model.Mice were randomly divided into PBS sensitization and PBS challenge(P-P),MPE sensitization and PBS challenge(M-P),MPE sensitization and MPE challenge model(M-M)groups.24 h after final challenge,mice were performed to examine airway responsiveness;bronchoalveolar lavage fluid(BALF)was harvested for cell counting and statistical classification of inflammatory cells through flow cytometry analysis.Pulmonary slides were collected for pathological examination,including HE,PAS,Masson and α-SMA immunohistochemical staining.ELISA was used to detect levels of IFN-γ,IL-4,IL-5,IL-13,IL-17A in lung tissue and serum,as well as serum total IgE and MPE-specific IgE,IgG1,IgG2a levels.Results:Pathological examination showed higher airway reactivity,more inflammatory cells infiltration around airway,obvious goblet metaplasia,thickening of airway smooth muscles and dramatical fibrin deposition around airway in model group.Total cell numbers of BALF were increased from<1×105 cells/ml in P-P group to>5×105 cells/ml in model group,in which eosinophils were predominant cellular type,levels of IL-4,IL-13,IL-17A in lung and IL-5,IL-13 levels in serum were significantly increased,as well as significant increasing levels of total IgE and MPE-specific IgE,IgG1,IgG2a.Conclusion:MPE-sensitized and challenged mice induces typical eosinophilic asthma featured with elevated eosinophils,as well as secretion of inflammatory factors of type 2 and type 17,IgE,IgG1 and IgG2a subtypes soars to high levels.

Thyroid cancer (TC) is the most common endocrine malignancy. Although most patients have a favorable prognosis following standardized treatment,a subset experiences rapid disease progression and poor outcomes. Recent studies have identified N6-methyladenosine (m6A) methylation as the most prevalent RNA modification,which regulates RNA transcription,maturation,degradation,and stability,playing a role throughout the tumorigenesis process. Consequently,m6A methylation has been extensively studied in tumor treatment and prevention. Changes in m6A levels can lead to abnormal activation or inhibition of oncogenes or tumor suppressor genes in TC,thereby contributing to its initiation and progression. This review summarizes the concept of m6A methylation,the components and functions of its regulatory factors,its role in the development and progression of TC,and its implications for treatment and prognosis.

The phosphatase and tensin homolog deleted on chromosome ten (PTEN) is a common oncogene located in the 10q23.3 region on the long arm of human chromosome l0, which regulates a variety of biological processes such as proliferation, survival, cell structure, motility, energy metabolism and genomic stability. Inactivation of PTEN is prevalent in almost all malignancies and correlates with tumor progression. Thyroid malignancies are among the most common endocrine malignancies, and PTEN has been shown to be critically associated with their development. The aim of this review is to describe the structural function of PTEN, as well as to summarize and discuss the recent findings of PTEN in thyroid malignancies.