Abstract Traditional Chinese medicine (TCM) auscultation has a long history, and with advancements in equipment and analytical methods, the quantitative analysis of auscultation parameters has determined. However, the complexity and diversity of auscultation, along with variations in devices, analytical methods, and applications, bring challenges to its standardization and deeper application. This review presents the advancements in auscultation equipment and systems, auscultation characteristic parameters, and their application in the diagnosis of pulmonary diseases and syndromes over the past 10 years, while also exploring the progress and challenges of current digital research of auscultation. This review also proposes the establishment of standardized protocols for the collection and analysis of auscultation data, the incorporation of advanced artificial intelligence (AI) auscultation analysis methods, and an exploration of the diagnostic utility of auscultatory features in pulmonary diseases and syndromes, so as to provide more precise decision support for intelligent diagnosis of pulmonary diseases and syndromes

Objective: To explore the feasibility of constructing a lung cancer early-warning risk model based on facial image features, providing novel insights into the early screening of lung cancer. Methods: This study included patients with pulmonary nodules diagnosed at the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from November 1, 2019 to December 31, 2024, as well as patients with lung cancer diagnosed in the Oncology Departments of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine and Longhua Hospital during the same period. The facial image information of patients with pulmonary nodules and lung cancer was collected using the TFDA-1 tongue and facial diagnosis instrument, and the facial diagnosis features were extracted from it by deep learning technology. Statistical analysis was conducted on the objective facial diagnosis characteristics of the two groups of participants to explore the differences in their facial image characteristics, and the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables. Based on the screened feature variables, four machine learning methods: random forest, logistic regression, support vector machine (SVM), and gradient boosting decision tree (GBDT) were used to establish lung cancer classification models independently. Meanwhile, the model performance was evaluated by indicators such as sensitivity, specificity, F1 score, precision, accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), and the area under the precision-recall curve (AP). Results: A total of 1 275 patients with pulmonary nodules and 1 623 patients with lung cancer were included in this study. After propensity score matching (PSM) to adjust for gender and age, 535 patients were finally included in the pulmonary nodule group and the lung cancer group, respectively. There were significant differences in multiple color space metrics (such as R, G, B, V, L, a, b, Cr, H, Y, and Cb) and texture metrics [such as gray-levcl co-occurrence matrix (GLCM)-contrast (CON) and GLCM-inverse different moment (IDM)] between the two groups of individuals with pulmonary nodules and lung cancer (P < 0.05). To construct a classification model, LASSO regression was used to select 63 key features from the initial 136 facial features. Based on this feature set, the SVM model demonstrated the best performance after 10-fold stratified cross-validation. The model achieved an average AUC of 0.8729 and average accuracy of 0.799 0 on the internal test set. Further validation on an independent test set confirmed the model’s robust performance (AUC = 0.823 3, accuracy = 0.729 0), indicating its good generalization ability. Feature importance analysis demonstrated that color space indicators and the whole/lip Cr components (including color-B-0, wholecolor-Cr, and lipcolor-Cr) were the core factors in the model’s classification decisions, while texture indicators [GLCM-angular second moment (ASM)_2, GLCM-IDM_1, GLCM-CON_1, GLCM-entropy (ENT)_2] played an important auxiliary role. Conclusion The facial image features of patients with lung cancer and pulmonary nodules show significant differences in color and texture characteristics in multiple areas. The various models constructed based on facial image features all demonstrate good performance, indicating that facial image features can serve as potential biomarkers for lung cancer risk prediction, providing a non-invasive and feasible new approach for early lung cancer screening.

BACKGROUND: Neuroticism has been associated with numerous health outcomes. However, most research has focused on a single specific disorder and has produced controversial results, particularly regarding mortality risk. Here, we aimed to examine the association of neuroticism with morbidity and mortality and to elucidate how neuroticism affects trajectories from a healthy state, to one or more neuroticism-related disorders, and subsequent mortality risk. METHODS: We included 483,916 participants from the UK Biobank at baseline (2006-2010). Neuroticism was measured using the Eysenck Personality Questionnaire. Three clusters were constructed, including worry, depressed affect, and sensitivity to environmental stress and adversity (SESA). Cox proportional hazards regression and multistate models were used. Linear regression was used to examine the association between neuroticism and immune parameters and neuroimaging measures. RESULTS: High neuroticism was associated with 37 non-overlapping diseases, including increased risk of infectious, cardiometabolic, neuropsychiatric, digestive, and respiratory diseases, and decreased risk of cancer. After adjustment for sociodemographic variables, physical measures, healthy behaviors, and baseline diagnoses, moderate-to-high neuroticism was associated with a decreased risk of all-cause mortality. In multistate models, high neuroticism was associated with an increased risk of transitions from a healthy state to a first neuroticism-related disease (hazard ratio [HR] [95% confidence interval (CI)] = 1.09 [1.05-1.13], P  <0.001) and subsequent transitions to multimorbidity (1.08 [1.02-1.14], P  = 0.005), but was associated with a decreased risk of transitions from multimorbidity to death (0.90 [0.84-0.97], P for trend = 0.006). The leading neuroticism cluster showing a detrimental role in the health-illness transition was depressed affect, which correlated with higher amygdala volume and lower insula volume. The protective effect of neuroticism against mortality was mainly contributed by the SESA cluster, which, unlike the other two clusters, did not affect the balance between innate and adaptive immunity. CONCLUSION This study provides new insights into the differential role of neuroticism in health outcomes and into new perspectives for establishing mortality prevention programs for patients with multimorbidity.
Humans ; Neuroticism/physiology* ; Male ; Female ; Middle Aged ; Aged ; Proportional Hazards Models ; Surveys and Questionnaires ; Adult ; Risk Factors

[This corrects the article DOI: 10.1016/j.apsb.2021.07.004.].

The continuous emergence of SARS-CoV-2 variants as well as other potential future coronavirus has challenged the effectiveness of current COVID-19 vaccines. Therefore, there remains a need for alternative antivirals that target processes less susceptible to mutations, such as the formation of six-helix bundle (6-HB) during the viral fusion step of host cell entry. In this study, a novel high-throughput screening (HTS) assay employing a yeast-two-hybrid (Y2H) system was established to identify inhibitors of HR1/HR2 interaction. The compound IMB-9C, which achieved single-digit micromolar inhibition of SARS-CoV-2 and its Omicron variants with low cytotoxicity, was selected. IMB-9C effectively blocks the HR1/HR2 interaction in vitro and inhibits SARS-CoV-2-S-mediated cell-cell fusion. It binds to both HR1 and HR2 through non-covalent interaction and influences the secondary structure of HR1/HR2 complex. In addition, virtual docking and site-mutagenesis results suggest that amino acid residues A930, I931, K933, T941, and L945 are critical for IMB-9C binding to HR1. Collectively, in this study, we have developed a novel screening method for HR1/HR2 interaction inhibitors and identified IMB-9C as a potential antiviral small molecule against COVID-19 and its variants.

Objective:To sort out the development context of precision nursing and compare and analyze the advantages and shortcomings in this field at home and abroad, so as to provide reference for the development of precision nursing in China.Methods:Through Web of Science core collection and CNKI database, literature related to precision nursing at home and abroad from January 1, 2012 to December 31, 2022 was retrieved. CiteSpace software was used to draw a scientific knowledge map for visualization analysis.Results:A total of 509 literatures in Chinese and 1 037 literatures in English were detected, and the annual number of publications showed a significant upward trend since 2015. The high-yielding institutions were mostly located in the United States, and the distribution of domestic institutions was relatively dispersed. From the perspective of research hotspots and frontiers, foreign research focused on health promotion and disease prevention research oriented by biological information, while Chinese research focused on individualized nursing research oriented by patient needs.Conclusions:In recent 10 years, the research of precision nursing in China has developed rapidly, but relatively speaking, the depth and breadth of its research still need to be improved. Chinese research should learn from the experience of foreign precision nursing practice and explore the mode of precision nursing that conforms to national conditions in China.

Objective:To systematically review the risk prediction model for vaginal delivery failure in low-risk primiparas, so as to provide reference for clinical practice and future research.Methods:Literature on the risk prediction model for vaginal delivery failure in low-risk primiparas was retrieved from China National Knowledge Infrastructure, WanFang Data, China Biology Medicine disc, PubMed, Embase, Cochrane Library, CINAHL, Web of Science and so on. The search period was from the establishment of the database to September 20, 2023. Two researchers independently screened literature, extracted data, and evaluated the risk of bias in the included studies.Results:A total of 10 articles were included, involving 14 models. Twelve models were constructed using Logistic regression, and the area under the receiver operating characteristic curve of the models ranged from 0.680 to 0.847. Common predictive factors of the model involved age of pregnant woman, height of pregnant woman, pre-pregnancy body mass index, gestational weight gain, gestational week, fetal birth weight, induction method, fetal biological measurements, and pre-delivery cervical Bishop score.Conclusions:The predictive performance of the vaginal delivery failure risk prediction model for low-risk primiparas is good, but the model construction method is relatively simple, and the overall bias risk is high. The model needs to be further optimized through machine learning, artificial intelligence, and other means, and extensively validated externally.

Purpose To explore the clinicopathological features,diagnosis and differential diagnosis of large B-cell lym-phoma with IRF4 rearrangement(LBCL-IRF4r).Methods Clinical data of 8 cases of LBCL-IRF4r were collect,hematoxy-lin-eosin and immunohistochemical of EnVision two-step stains,in situ hybridization and FISH was used to study the histology,immunotypes and molecular genetic characteristics.The rele-vant literatures were reviewed.Results Among 8 cases of LBCL-IRF4r,the male to female ratio was 1.67:1,with age range 10-53 years(mean 25.8 years).Five cases occurred in tonsils,2 cases in nasopharynx and 1 cases in inguinal lymph node.Microscopically,the tumors presented with a purely follic-ular,purely diffuse or a combined follicular and diffuse architec-ture.The tumor cells were typical centroblasts and less frequent-ly medium-sized blastic cells with smaller nucleoli,apoptosis and nuclear fragmentation were easily seen.Immunophenotypi-cally,the tumor cells of the eight cases of LBCL-IRF4r diffuse strongly expressed CD20(8/8),PAX5(2/2),CD79a(3/3),BCL6(8/8)and MUM-1(8/8),mostly expressed CD10(7/8),partially expressed BCL2(5/8)and CD5(4/8),and did not express Cyclin D1,CD23 and CD30.The percentage of Ki67 index ranged from 70％to 95％.EBER in situ hybridiza-tion was negative in all cases.IRF4 rearrangements were detec-ted in all cases(8/8).BCL6 rearrangements were detected in one case(1/2).MYC(0/4)and BCL2(0/3)rearrangements were not detected in all cases.Conclusion LBCL-IRF4r is more common in children and adolescents with characteristic IG::IRF4 rearrangement and a good prognosis,which needs to be differentiated from other types of large B-cell lymphoma.

Objective To invesigate the feasibility of low radiation dose and low contrast dosage in triple-rule-out computed tomo-graphy angiography(TRO-CTA)on the 320-row detector CT.Methods A total of 120 patients who underwent CTA were prospec-tively selected.All patients were divided into control group(n=90)and experimental group(n=30).The control group employed standard-doses protocol of pulmonary CTA(120 kV tube voltage,45 mL contrast dosage),coronary CTA(120 kV,50-60 mL),and aortic CTA(120 kV,75 mL),while the experimental group received TRO-CTA with 100 kV and 70-80 mL.The peak time of contrast dosage at the pulmonary artery and aorta was measured by low-dose detection method in the experimental group,and the contrast examination was performed sequentially in the control group.Subjective scores and objective image quality of the pulmonary artery,coronary artery,and aorta in the experimental group and the control group were measured and compared,respectively.The effective dose(ED)between the two groups were recorded and compared.Independent samples t-test and Fisher exact probability were used to analyze the statistical differences between the above measures.Results There were no significant differences in CT values,con-trast-to-noise ratio(CNR),signal-to-noise ratio(SNR)of pulmonary artery,coronary artery and aorta between the two groups(P＞0.05).The mean subjective scores of pulmonary artery,coronary artery and aorta segments in the two groups were not less than 3 points,meeting the requirement of clinical diagnosis.There was no statistical difference in subjective scores between the two groups(P＞0.05).There was statistically significant difference in ED between the two groups(P＜0.05).The ED of pulmonary artery,coronary artery,and aorta in the experimental group were 11.49％,13.33％,and 11.46％significantly lower than those in the control group,respec-tively.Conclusion It is feasible to obtain TRO-CTA images used by the low radiation dose and low contrast dosage on the 320-row detector CT,and radiation dose and contrast dosage can be reduced reasonably without alterations of TRO-CTA images quality in clinical practice.

Objective:To investigate the effect and potential mechanism of exposure to 20 nm polystyrene nanoplastics (PS-NPs) on lipid metabolism in mice liver.Methods:An animal experimental model was designed, which was completed from September 2022 to July 2023 on the exposure omics platform of the School of Public Health at Capital Medical University and the Key Laboratory of Environment and Population Health at the Chinese Center for Disease Control and Prevention.1 mg/kg and 10 mg/kg PS-NPs tail vein mice exposure models were constructed. After exposure 7 d, serum was collected to measure the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) and air flow assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) analysis were used to analyze the mRNA levels of fatty acid esterification related genes ( Dgat1 and Dgat2) and lipid transport related genes ( ApoB, Cd36, ApoE and Mttp) and metabolites′ spatial changes in liver tissue. In vivo imaging system (IVIS) and tissue shake sections were employed to observe the fluorescence biological distribution of PS-NPs. t-test or one-way ANOVA was used to explore the difference between groups. Results:The serum ALT levels were (83.97±4.58), (91.17±13.69) and (142.43±6.09) U/L in the control group, 1 mg/kg PS-NPs exposure group and 10 mg/kg PS-NPs exposure group respectively ( F=37.281, P<0.05). The relative mRNA levels of Dgat1, Dgat2, ApoB, Cd36 and ApoE were (1.49±0.63, 2.53±0.32, 2.45±0.54), (1.07±0.38, 1.86±0.83, 2.23±0.73), (1.01±0.13, 1.58±0.43, 2.03±0.52), (1.01±0.14, 1.55±0.37, 1.52±0.51), (1.01±0.17, 2.11±0.27, 2.39±0.93) in these three groups respectively. The differences were statistically significant ( F=11.54, 6.95, 14.90, 5.98 and 14.68, P<0.05). AFADESI-MSI analysis found that PS-NPs exposure led to a significant decrease in the levels of glutarylcarnitine and O-Linoleoylcarnitine ( t=4.12 and 3.35, P<0.05), which were associated with lipid beta oxidation. The content of triglycerides (TG) (m/z 921.726 4, t=8.69, P<0.05; m/z 919.711 4, t=3.20, P<0.05), phosphatidylic acid (PA) (m/z 895.712 3, t=3.60, P<0.05; m/z 821.526 6, t=3.36, P<0.05), lysophosphatidylcholine (LysoPC) (m/z 560.310 6, t=3.35, P<0.05; m/z 582.295 3, t=6.28, P<0.05), phosphatidylcholine (PC) (m/z 778.533 9, t=3.53, P<0.05; m/z 804.549 6, t=3.60, P<0.05; m/z 820.523 1, t=3.37, P<0.05), phosphatidylethanolamine (PE) (m/z 772.523 3, t=3.08, P<0.05) showed a significant increase in the PS-NPs exposure group. In vivo and in vitro imaging and in situ cell localization revealed that PS-NPs were mainly enriched in hepatic stellate cells and hepatic Kupffer cells in liver tissue. Conclusion:Exposure to PS-NPs induces disorder of liver lipid metabolism, which may be related to the accumulation of PS-NPs in hepatic stellate cells and hepatic Kupffer cells, providing basis for searching early biomarkers of PS-NPs exposure and further mechanism research.