Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Plague is a virulent infectious disease caused by Yersinia pestis. There have been three plague pandemics in the world history, of which the third plague pandemic started in Yunnan, China in 1772, and became a global pandemic in 1894, affecting many countries in Asia, Europe, America, Oceania and Africa. It has been reported that the third plague pandemic was caused by the branch of Yersinia pestis 1.ORI. This paper summarizes the origin, transmission route, distribution area and ecological environment of 1.ORI clade and the relationship with the third plague pandemic, which has guiding significance for further understanding and studying the epidemiological pattern of plague, formulating appropriate surveillance programmes and prevention and control measures.

BACKGROUND: Lung cancer is the cancer with the highest mortality at home and abroad at present. The detection of lung nodules is a key step to reducing the mortality of lung cancer. Artificial intelligence-assisted diagnosis system presents as the state of the art in the area of nodule detection, differentiation between benign and malignant and diagnosis of invasive subtypes, however, a validation with clinical data is necessary for further application. Therefore, the aim of this study is to evaluate the effectiveness of artificial intelligence-assisted diagnosis system in predicting the invasive subtypes of early‑stage lung adenocarcinoma appearing as pulmonary nodules. METHODS: Clinical data of 223 patients with early-stage lung adenocarcinoma appearing as pulmonary nodules admitted to the Lanzhou University Second Hospital from January 1st, 2016 to December 31th, 2021 were retrospectively analyzed, which were divided into invasive adenocarcinoma group (n=170) and non-invasive adenocarcinoma group (n=53), and the non-invasive adenocarcinoma group was subdivided into minimally invasive adenocarcinoma group (n=31) and preinvasive lesions group (n=22). The malignant probability and imaging characteristics of each group were compared to analyze their predictive ability for the invasive subtypes of early-stage lung adenocarcinoma. The concordance between qualitative diagnostic results of artificial intelligence-assisted diagnosis of the invasive subtypes of early-stage lung adenocarcinoma and postoperative pathology was then analyzed. RESULTS: In different invasive subtypes of early-stage lung adenocarcinoma, the mean CT value of pulmonary nodules (P<0.001), diameter (P<0.001), volume (P<0.001), malignant probability (P<0.001), pleural retraction sign (P<0.001), lobulation (P<0.001), spiculation (P<0.001) were significantly different. At the same time, it was also found that with the increased invasiveness of different invasive subtypes of early-stage lung adenocarcinoma, the proportion of dominant signs of each group gradually increased. On the issue of binary classification, the sensitivity, specificity, and area under the curve (AUC) values of the artificial intelligence-assisted diagnosis system for the qualitative diagnosis of invasive subtypes of early-stage lung adenocarcinoma were 81.76%, 92.45% and 0.871 respectively. On the issue of three classification, the accuracy, recall rate, F1 score, and AUC values of the artificial intelligence-assisted diagnosis system for the qualitative diagnosis of invasive subtypes of early-stage lung adenocarcinoma were 83.86%, 85.03%, 76.46% and 0.879 respectively. CONCLUSIONS Artificial intelligence-assisted diagnosis system could predict the invasive subtypes of early‑stage lung adenocarcinoma appearing as pulmonary nodules, and has a certain predictive value. With the optimization of algorithms and the improvement of data, it may provide guidance for individualized treatment of patients.
Adenocarcinoma/pathology* ; Adenocarcinoma of Lung/pathology* ; Artificial Intelligence ; Humans ; Lung Neoplasms/pathology* ; Multiple Pulmonary Nodules ; Neoplasm Invasiveness ; Retrospective Studies

Objective:To explore the cause of death of 2 suspected Yunnan sudden unexplained death (YNSUD) cases in Dayao County, Yunnan Province.Methods:The field epidemiological investigation and autopsy of 2 cases of YNSUD in Dayao County from June 15 to 20, 2020 were conducted; and blood and tissue samples were collected for qualitative analysis of common poisons and drugs.Results:The areas where the two cases were located were all seriously ill villages with a history of YNSUD, and the time of death occurred in the onset season of YNSUD. There was no blood relationship between the 2 cases, no obvious abnormal symptoms before death, no special diet, no history of exposure to pesticides and other toxic chemicals, and the test results of common poisons were all negative. Autopsy pathological examination results showed that case 1 died of acute cardiac dysfunction caused by sudden acute myocardial infarction of coronary heart disease, and case 2 died of central respiratory and circulatory failure caused by spontaneous subarachnoid hemorrhage.Conclusions:The two cases are excluded from YNSUD through autopsy, and the cause of death is determined. It is suggested that emergency response should be taken as soon as possible for YNSUD cases, and autopsy should be actively carried out to clarify the cause of death from a pathological point of view.

Organoid models are used to study kidney physiology, such as the assessment of nephrotoxicity and underlying disease processes. Personalized human pluripotent stem cell-derived kidney organoids are ideal models for compound toxicity studies, but there is a need to accelerate basic and translational research in the field. Here, we developed an automated continuous imaging setup with the "read-on-ski" law of control to maximize temporal resolution with minimum culture plate vibration. High-accuracy performance was achieved: organoid screening and imaging were performed at a spatial resolution of 1.1 μm for the entire multi-well plate under 3 min. We used the in-house developed multi-well spinning device and cisplatin-induced nephrotoxicity model to evaluate the toxicity in kidney organoids using this system. The acquired images were processed via machine learning-based classification and segmentation algorithms, and the toxicity in kidney organoids was determined with 95% accuracy. The results obtained by the automated "read-on-ski" imaging device, combined with label-free and non-invasive algorithms for detection, were verified using conventional biological procedures. Taking advantage of the close-to-in vivo-kidney organoid model, this new development opens the door for further application of scaled-up screening using organoids in basic research and drug discovery.
Humans ; Kidney ; Organoids ; Pluripotent Stem Cells

Objective : To investigate the effects of one night of sleep deprivation on adults ’cognitive performance and sleepiness. Methods : The study employed a repeated⁃measures design. Participants performed cognitive performance tasks , which included the Continuous Performance Test and Digit Span Test and Karolinska Sleepiness Scale. The data were analyzed using one⁃way repeated⁃measures ANOVA. Results : 48 participants were included in this study. Sleep deprivation during night shift had a adversely affect on sustained attention performance and alertness (P < 0. 05) . Compared with the beginning of night shift work , the correct number decreased , the number of errors , missed number and reaction time increased , and the score of Karolinska sleepiness scale decreased after the night shift work. The sleep deprivation has no significant effect on working memory performance (P > 0. 05) . Conclusion One night of sleep deprivation has significant deleterious effects on cognitive performance and subjec⁃ tive sleepiness. However, no effect on the working memory performances has been found.

Objective:To investigate the application value of dynamic scintigraphy single-photonemission computed tomography (SPECT) 99m-technetium-galactosyl human serum albumin diethy-lenetriamine pentaacetic ( 99Tc m-GSA) scintigraphy in assessing liver function of perihilar cholangio-carcinoma after portal vein embolization (PVE). Methods:The retrospective and descriptive study was conducted. The clinicopathological data of 16 patients with perihilar cholangiocarcinoma who underwent 99Tc m-GSA scintigraphy after PVE in Beijing Tsinghua Changgung Hospital Affiliated to Tsinghua University from October 2019 to January 2021 were collected. There were 8 males and 8 females, aged from 46 to 78 years, with a median age of 64 years. Observation indicators: (1) liver volume after PVE; (2) liver function after PVE; (3) typical case analysis. Measurement data with normal distribution were represented as Mean± SD. Count data were represented as absolute numbers or percentages. Comparison of data of the same patient was analyzed using the paired t test. Results:(1) Liver volume after PVE:the morphological liver volume and functional liver volume for the 16 patients were (1 420±211)mL and (389±112)mL. The morphological liver volume and functional liver volume were (636±143)mL and (234±106)mL of planning reserved lobe, (784±210)mL and (151±106)mL of planning resection lobe, respectively. The functional liver density (FLD) of planning reserved lobe and planning resection lobe were 0.36±0.12 and 0.19±0.11, showing a significant difference between them ( t=3.794, P<0.05). The planning resection rate of morpholo-gical liver volume and functional liver volume were 37.8%±0.6% and 54.8%±0.2%, showing a significant difference between them ( t=?3.720, P<0.05). (2) Liver function after PVE: 13 of 16 patients completed the indocyanine green (ICG) test, and 3 patients didn't complete the ICG test due to intolerance. For the 13 patients undergoing ICG test, the total ICG-K value was (0.15±0.03)/minutes, and the ICG-K value of planning reserved lobe was (0.07±0.02)/minutes. The total GSA-K value of 16 patients was (0.14±0.10)/minutes, and the GSA-K value of planning reserved lobe was (0.08±0.06)/minutes. (3) Typical case analysis: a 46-year-old male patient with type Bismuth Ⅲa perihilar cholangiocarcinoma was planned to perform perihilar hepatectomy combined with right hepatectomy. The imaging evaluation showed that the volume of reserved liver lobe accounted for 27% of the total liver volume. The serum total bilirubin was 256 μmol/L when admitted and decreased to 118 μmol/L on the day 5 after percutaneous transhepatic biliary drainage. The right anterior and right posterior branches of PVE was performed. SPECT 99Tc m-GSA examination was performed on the day 37 after PVE. The morphological liver volume was 559 mL of planned reserved lobe and 1 461 mL of the whole liver. The planned morphological liver volume resection rate was 61.7%. ICG-K was 0.12/minutes of the whole liver, and 0.04/minutes of planned reserved lobe. The functional liver volume was 134 mL of planned reserved lobe and 309 mL of the whole liver. The planned resection rate of functional liver volume was 56.6%. The GSA-K was 0.20/minutes of the whole liver and 0.09/minutes of planned reserved lobe. R 0 resection was achieved in perihilar hepatectomy combined with right hepatectomy and no liver failure occurred. The survival time of patients was 11 months. Conclusion:Dynamic SPECT 99Tc m-GSA scintigraphy can effectively evaluate the regional function of the reserved liver lobe in patients with perihilar cholangiocarcinoma after PVE.

Infectious diseases are still one of the leading causes of morbidity and death globally, affecting public health and life, social and economic development, and even national security. Early detection focuses on detecting the abnormal information of infectious disease outbreaks or epidemics in a timely and sensitive way to conduct field investigation and verification. It is also a precursor to effective surveillance and early warning system. The effective surveillance and early warning system can fully and accurately understand the real conditions, driving forces, and transmission chain of the occurrence of a specific infectious disease outbreak and epidemic and put forward scientific and effective prevention and control strategies and measures. Due to the measurement of the resources support and the particular data collection value, it is not easy to obtain epidemiological, etiological, and other data information in a timely, complete and accurate manner. This paper summarized the theory and technology on early detection, effective surveillance, and early warning information on infectious diseases. It also integrated and utilized the multi-source data, including effective infectious disease surveillance and the country's early warning system, to better understand the outbreak epidemic, causes, risks, processes, and driving forces. Thus, it is possible to set up a sensitive, specific staging measurement innovative technical system to monitor, early warning, and timely respond to acute infectious diseases through multidisciplinary cooperation in China. It provides the basis for strengthening the surveillance and early warning of new emerging and major infectious diseases and public health emergencies, avoiding the spread of inadequate response to infectious disease, and preventing the resources waste of over-response.

Objective:To understand the infection status of HCV and Treponema pallidum (TP) in HIV/AIDS cases in Yunnan province,and identify the risk factors. Methods:Between January 1 and June 30 in 2020,a cross-sectional survey was conducted in Yunnan. Two enzyme-linked immunosorbent assay (ELISA) kits were used to detect anti-HCV, the positive results of both two kits indicated HCV infection. ELISA and syphilis toluidine red untreated serum test were applied to identify TP infection. Both Excel 2016 and SPSS 22.0 software were used for statistical analysis, and logistic regression model was conducted to identify the relevant factors of HCV and TP infection.Results:A total of 5 922 HIV/AIDS cases were included in this study, the infection rates of HCV and TP were 6.5% (383/5 922) and 5.8% (344/5 922) respectively. The co-infection rate of HCV and TP was 0.4% (22/5 922). The risk for HCV infection in HIV/AIDS cases was higher in younger age groups compared with age group ≥50 years (15-19:a OR=3.53;20-29:a OR=3.02;30-39:a OR=2.91;40-49:a OR=3.61), in males than in females (a OR=2.31), in the married and unmarried than in the divorced or widowed (married:a OR=1.61;unmarried:a OR=1.63), in other ethnic groups than in Han ethnic group (a OR=1.70), in people with lower education level than in people with education level of college and above (primary school degree and below:a OR=4.69;middle school:a OR=3.96), in people living in the central and western Yunnan than in people living in eastern Yunnan (central Yunnan:a OR=2.46; western Yunnan:a OR=7.08), in injection drug users than in MSM (a OR=131.08). The risk of TP infection in HIV/AIDS cases was higher in people with education level of college and primary school than in middle school degree (primary school and below:a OR=1.73;college and above:a OR=1.77), in people with other occupations than in farmers (a OR=1.39), in people living in eastern Yunnan than in people living in western Yunnan (a OR=1.75); in MSM than in people with heterosex (a OR=9.75). Conclusions:A certain proportion of HIV/AIDS cases reported between January and June in 2020 in Yunnan were co-infected with HCV and TP, many factors were associated with the co-infection. It is suggested to strengthen HCV and TP tests in HIV/AIDS cases and conduct active treatment of the co-infection.

Objective To identify the causes of nonspecific bands in the detection of a industry standard caf1 gene by polymerase chain reaction(PCR),and to propose a solution to this problem. Methods A total of 112 strains were selected for the experiment, including 40 strains of Yersinia pestis, 72 strains of non-Yersinia pestis;DNA was extracted,and caf1 gene was amplified by PCR;seven non-specific strips were recovered,purified and TA cloning and sequencing; the primer of the caf1 gene was redesigned and validated using all of the strains. Results Using the industry standard caf1 gene primer,DNAs of 40 Yersinia pestis and 72 non-Yersinia pestis were amplified by PCR, 58 non-Yersinia pestis could be amplified with non-specific bands, they were about 400, 500, 600, 700, 800, 900, 1 000 bp. By TA cloning and sequencing, the non-specific bands in the downstream of the industry standard caf1 primer and its reverse complement were amplified. Using the new designed caf1 primer to amplify, 72 non-Yersinia pestis strains showed no non-specific bands. Conclusion Non-specific bands has been amplified in the screening of Yersinia pestis using the primer of the industry standard caf1, and the new caf1 primer can effectively avoid this problem and improve the accuracy of detection.