ObjectiveTo investigate the changes in coagulation system in acute decompensated cirrhosis （ADC） patients with or without sepsis and the association of these changes with short-term prognosis. MethodsA prospective study was conducted among 116 ADC patients who were hospitalized in Nanfang Hospital from January 2021 to July 2023， among whom there were 86 patients with sepsis and 30 patients without sepsis， and 54 patients with sepsis alone who had no chronic liver disease were enrolled as control group. Thromboelastography （TEG） and other conventional coagulation parameters were used to comprehensively evaluate the coagulation function of patients. The data including TEG results and short-term prognosis were collected， and a correlation analysis was performed. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. The Spearman correlation coefficient was calculated to investigate the correlation between different variables. The Logistic regression model was used to perform the univariate and multivariate analyses. ResultsFor the ADC patients with sepsis， the lungs and bloodstream were the main infection sites， and bacteria were the main pathogenic microorganism. TEG results showed that compared with the patients with sepsis alone， the patients with ADC and sepsis had a significant reduction in median maximum amplitude （MA）， a significant increase in coagulation time （K time）， and a significant reduction in α angle （all P<0.05）； the patients with ADC and sepsis had a significantly longer reaction time （R time） than those with ADC alone （P=0.02）， and the patients with sepsis alone had a significantly longer R time than those with ADC and sepsis （P=0.04）. There was no correlation between MA and platelet count in the patients with ADC and sepsis （r=-0.133， P=0.057）， while there was a significant correlation between MA and platelet count in the patients with sepsis alone （r=0.595， P=0.001）. SOFA score was negatively correlated with MA in sepsis patients with or without ADC （r=-0.503 and -0.561， both P<0.001）， and for the patients with ADC and sepsis， R time， K time， and α angle were weakly correlated with SOFA score and had a relatively strong correlation with APTT （all P<0.05）. The patients with ADC alone all survived within 90 days， and compared with the death group， the patients with sepsis alone who survived had significantly higher values of MA and α angle （all P<0.05）； there was a significant difference in α angle on day 90 between the survival group and the death group， no matter whether the patients were comorbid with ADC or not （both P<0.01）， while for the patients with ADC and sepsis， there was no significant difference in MA value on day 90 between the survival group and the death group （P>0.05）. ConclusionFor ADC patients comorbid with sepsis， coagulation function assessment and monitoring should be taken seriously in clinical practice， and TEG parameters and SOFA score should be monitored when necessary to develop individualized treatment regimens.

BACKGROUND: The incidence and mortality rates of lung cancer remain on the rise, creating an urgent need for screening among high-risk populations and early prevention. This study aims to explore the association and interaction between multidimensional lifestyle, socioeconomic status, and the incidence of lung cancer, and to provide scientific evidence for screening high-risk populations and preventing lung cancer. METHODS: Healthy lifestyle score was constructed using information on smoking, alcohol consumption, exercise, diet and sleep obtained through a questionnaire survey. Socioeconomic status was evaluated based on information on education, employment, and family income, and genetic testing data were used to assess the risk of genetic variation. A proportional hazards assumption test was conducted, and the Cox proportional hazards model was applied to analyze the associations between healthy lifestyle scores, socioeconomic status, and lung cancer, as well as the interactions among various factors, after adjusting for the risk of genetic variation, age, gender, diabetes, hypertension and the living environment score. RESULTS: A total of 245,538 samples that entered the cohort from March, 2006 to October, 2010 were included and followed up until December 31, 2022. The participants were divided into the case group (n=1472) and the control group (n=244,066). The analysis results showed that after adjusting for covariates, there was still an association between the healthy lifestyle score, socioeconomic status, and the incidence of lung cancer: compared with participants with a high healthy lifestyle score, the risk of lung cancer in participants with medium and low healthy lifestyle scores was significantly increased, with hazard ratios (HR) of 2.12 (95%CI: 1.86-2.41) and 3.36 (95%CI: 2.82-3.99) respectively; compared with participants with high socioeconomic status, the risk of lung cancer in participants with medium and low socioeconomic status was significantly increased, with HR of 1.29 (95%CI: 1.13-1.48) and 1.67 (95%CI: 1.46-1.90) respectively. Moreover, there were interactions between smoking status and socioeconomic status (Pfor interaction=0.05), as well as the other four lifestyle factors (Pfor interaction=0.02). CONCLUSIONS This study identified the association between multidimensional lifestyle factors and socioeconomic status with the incidence of lung cancer, as well as interactions between smoking and socioeconomic status and four other lifestyle factors, providing a scientific basis for screening and prevention in high-risk populations for lung cancer.
Humans ; Lung Neoplasms/epidemiology* ; Male ; Female ; Middle Aged ; Incidence ; Life Style ; Social Class ; Aged ; Adult ; Risk Factors

To explore the feasibility of using UAV-LiDAR for measuring the leaf area index (LAI) of crop canopies, we employed UAV-LiDAR to scan sugarcane canopies during the tillering and elongation stages, acquiring canopy point cloud data. Subsequently, features such as average row height, projected row area, point cloud density at different canopy layers, and the ratios between these parameters were extracted. Three feature selection methods-partial least squares regression (PLSR), XGBoost feature importance (XGBoost-FI), and random forest-recursive feature elimination (RF-RFE)-were adopted to evaluate and identify the optimal input variables for modeling. With these selected variables, LAI inversion models were developed based on random forest (RF) and adaptive boosting (AdaBoost) algorithms, and their performance was assessed. Among the extracted features, the projected row area S_p and the total row point count C_total exhibited strong correlations with LAI, with correlation coefficients of 0.73 and 0.72, respectively. The AdaBoost-based LAI inversion model, using the projected row area S_p, average height H_avg, mid-layer point cloud density C_m, and total row point count C_total as input variables, achieved the best performance, with a coefficient of determination (R_v²) of 0.713 and a root mean square error (RMSE_v) of 0.25 on the validation set. This study provides an effective method for high-throughput acquisition of LAI in field crops, offering valuable scientific support for sugarcane field management and breeding efforts.
Plant Leaves/growth & development* ; Saccharum/growth & development* ; Algorithms ; Unmanned Aerial Devices ; Remote Sensing Technology/methods* ; Crops, Agricultural/growth & development*

Accurately obtaining the crop quantity and density is not only crucial for the demand-based input of water and fertilizer in the field but also vital for ensuring the yield and quality of crops. Aerial photography by unmanned aerial vehicles (UAVs) can quickly acquire the distribution image information of crops over a large area. However, the accurate recognition of a single type of dense targets is a huge challenge for most recognition algorithms. Taking banana seedlings as an example in this study, we captured the images of banana plantations by UAVs from high altitudes to explore an efficient recognition method for dense targets. We proposed a strategy of "cut-recognition-stitch" and constructed a counting method based on the improved Faster R-CNN algorithm. First, the images containing highly dense targets were cropped into a large number of image tiles according to different sizes (simulating different flight altitudes), and the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm was adopted to improve the image quality. A banana seedling dataset containing 36 000 image tiles was constructed. Then, the Faster R-CNN network with optimized parameters was used to train the banana seedling recognition model. Finally, the recognition results were reversely stitched together, and a boundary deduplication algorithm was designed to correct the final counting results to reduce the repeated recognition caused by image cropping. The results show that the recognition accuracy of the Faster R-CNN with optimized parameters for banana image datasets of different sizes can reach up to 0.99 at most. The deduplication algorithm can reduce the average counting error for the original aerial images from 1.60% to 0.60%, and the average counting accuracy of banana seedlings reaches 99.4%. The proposed method effectively addresses the challenge of recognizing dense small objects in high-resolution aerial images, providing an efficient and reliable technical solution for intelligent crop density monitoring in precision agriculture.
Musa/growth & development* ; Crops, Agricultural/growth & development* ; Algorithms ; Neural Networks, Computer ; Unmanned Aerial Devices ; Seedlings/growth & development* ; Image Processing, Computer-Assisted/methods* ; Photography ; Agriculture/methods*

Objective To construct an assay for early infection diagnosis of Angiostrongylus cantonensis based on gold nanorod polymerization.Methods Stable gold nanorods were synthesized by the gold seed growth method,and labeled with different concentrations of sulfhydrylated crude and purified antigens of lar-vae and adults of Angiostrongylus cantonensis,and their excretory and secretory antigens,and then scanned the longitudinal surface plasmon resonance(LSPR)of the stable gold nanorods by ultraviolet-visible(UV-Vis)spectrophotometry,and screened for the optimal labeled antigens for the detection of different infection time after infection of rats with Angiostrongylus cantonensis.The displacement changes were screened to se-lect the best labeled antigens for the detection of serum antibodies and positive sera of series of dilution gradi-ents at different infection times(5,7,14,21 d)after infection with Angiostrongylus cantonensis in rats,and at the same time,the enzyme-linked immunosorbent assay(ELISA)was set up for the same test.Kappa test was used to compare the consistency of the two assays.Results Gold nanorods with stable aspect ratio were suc-cessfully prepared.The gold nanorods labeled with 10 μg/mL of adult purified antigen had a maximum LSPR shift of 40 nm,and were able to detect serum antibodies in rats 5 d after mild,moderate and severe infection with Angiostrongylus cantonensis,as well as positive sera at a maximum dilution of 1∶600.The ELISA was able to detect serum antibodies in rats after 14 d of mild infection,and 7 d of moderate and severe infection,as well as positive sera at a maximum dilution of 1∶200.The ELISA detected positive serum antibodies in rats after 14 d of mild infection and 7 d of moderate and severe infection,as well as in rats at a maximum dilution of 1∶200.The Kappa value of the two methods was 0.750(P<0.01),and the results of the two methods had strong consistency.Conclusion A polymerized gold nanorod assay for early and rapid diagnosis of An-giostrongylus cantonensis infection is successfully constructed.

Objective:To compare the therapeutic effects of combination regimens based on omadacycline or tigecycline in the treatment of patients with carbapenem-resistant acinetobacter baumannii (CRAB) pneumonia.Methods:A retrospective analysis was performed on the case data of 92 patients diagnosed with CRAB pneumonia who were admitted to the Intensive Care Unit (ICU) of Jinhua Municipal Central Hospital between January 2022 and March 2024. Among these cases, 49 patients received combination therapy with omadacycline as the foundation (hereafter referred to as the omadacycline group),A total of 43 cases were treated with tigecycline-based combination therapy (hereafter referred to as the tigecycline group). The demographic and clinical data of the two patient groups, including pre- and post-treatment improvements in inflammatory markers, bacterial clearance rates, ventilator weaning success rates, and 28-day survival rates, were compared.Results:No significant differences were observed in the baseline characteristics between the two patient groups.The body temperature, white blood cell count, C-reactive protein levels, and procalcitonin concentrations in both groups of patients showed significant improvement after 72 hours of treatment.The differences observed were statistically significant ( P<0.05).Following the completion of the treatment regimen, the bacterial clearance rates in the omadacycline and tigecycline groups were 69.4% and 44.2%, respectively ( P = 0.015). Moreover, the success rates for weaning patients from ventilator support were 71.4% and 51.2%, respectively ( P = 0.046).However, no statistically significant difference was observed in the 28-day survival rate.No serious adverse drug reactions were observed in either of the groups. Conclusions:Both omadacycline- and tigecycline-based combination therapies have demonstrated significant efficacy in improving inflammatory markers in patients with CRAB pneumonia. There was no statistically significant difference in the 28-day survival rate between the two patient groups. Furthermore, combination therapy utilizing omadacycline can significantly enhance the efficacy of promoting negative conversion of the etiological agent,minimize the duration of mechanical ventilation.

From January 23, 2020 to May 29, 2021, there were 17,550 clinical research registrations on the China Clinical Trial Registry Platform. The index of clinical research on COVID-19 showed 840 registrations, accounting for 4.79% (840/17 550) of the total registrations. According to the trend chart of epidemic development, 487 clinical research projects of COVID-19 registered from January 23, 2020 to March 18, 2020 were set as the early stage of epidemic discovery in the region, the following 15 months were divided into stable initial stage, stable later stage and the later stage of the first wave of domestic epidemic every five months. The proportion of COVID-19 research projects registered in each stage was 29.80%, 5.87%, 0.76% and 1.15% of all registered projects respectively. The registration ratios of COVID-19 in each clinical stage was 57.98%, 28.81%, 5.95% and 7.26% respectively. Intervention studies were 61.60% (300/487) in the early stage of the epidemic, and most of them were in biological agent and drug therapy, which were 40.49%, 50.00% and 73.77% respectively in the later stages. Stable initial stage biological agent projects decreased. Then the vaccine research program became a focused research program. Among the 58 registration projects involving vaccines, 25 were clinical trials of vaccines in different stages, with the major research units being biopharmaceutical companies. Of the 487 clinical studies registered in the early stage, 10.23%(50/487) were withdrawn, of which 38 were intervention treatment studies, most notably drug studies (17) and blood biological products (16), but they were still registered in the stable initial stage. It is necessary to reflect on the scientific and ethical nature of early COVID-19 clinical trials or research, including whether the three core values of equal respect, help to alleviate pain and fairness can be achieved. Whether the "ethics review meeting should pay special attention to the scientificity, safety, fairness, subject protection, informed consent documents and informed consent process, avoidance of conflicts of interest, etc. of clinical trials or research" has been implemented. Competent government departments at all levels and all clinical medical research institutions should organize evaluation, and then establish an effective evaluation mechanism when new clinical trials or research projects are registered in the future.

Objective:To construct a risk prediction model for urinary retention in patients undergoing radical cervical cancer surgery based on machine learning, and the prediction effect of the model was internally verified and evaluated, in order to provide reference for the early prevention and treatment of urinary retention in patients undergoing radical cervical cancer surgery.Methods:A total of 981 patients who underwent radical cervical cancer surgery in the First Affiliated Hospital of Anhui Medical University from June 2017 to February 2022 were selected and divided into the training set (687 cases) and the test set (294 cases) according to a ratio of 7∶3. Through literature review and risk factor analysis, the influencing factors of urinary retention after radical treatment of cervical cancer were explored, and the risk prediction model of urinary retention was constructed by using XGBoost, random forest, support vector machine and decision tree in machine learning. The accuracy rate, recall rate, F1 value and AUC of four machine learning algorithms were calculated by using the method of 10-fold cross-validation, and the model with the highest predictive efficiency was selected.Results:Among the 981 patients included, the incidence of urinary retention after radical cervical cancer surgery was 18.86% (185/981). The median age of urinary retention group was 51 years old, and that of non urinary retention group was 50 years old. Statistically significant variables in the univariate analysis and influencing factors summarized by literature review were featured, including patient age, intraoperative blood loss, body mass index (BMI), cancer stage, surgical method, surgical resection scope, whether pelvic lymph node dissection was performed, comorbidities and residual urine. Among the four model building methods of machine learning, the random forest model has the best effect, its training set F1 value was 0.94, the test set F1 value was 0.77, the ROC was plotted and the AUC was calculated to be 0.73. Age, intraoperative blood loss, BMI, cancer stage and surgical method contributed significantly to the classification of random forest model.Conclusions:The prediction model of urinary retention risk after radical cervical cancer surgery based on random forest method has the best efficacy. It is useful to help nursing personnel evaluate the risk of the uroschesis for a patient and then take targeted nursing interventions to actively prevent postoperative urinary retention.

Objective To conduct an epidemiological survey of common congenital heart disease(CHD)among children in ethnic minority areas in southeastern Guizhou and to explore the influencing factors of delayed medical treatment.Methods From January 2019 to July 2022,18 850 children aged 3 months to 14 years in Qiandongnan Miao and Dong Autonomous Prefecture were selected;105 children with CHD were included in the training set,and they were divided into delayed group(80 cases)and non-delayed group(25 cases)according to whether or not to delay medical treatment.In addition,children with CHD(35 cases)from July 2022 to December 2022 were included in the validation set.The general data of the subjects in the two groups were compared and ana-lyzed.Multivariate logistic regression was performed and risk scoring model was constructed.Results The preva-lence of CHD in 18 850 children was 5.57‰(105/18 850),with the highest prevalence in Liping County,and the lowest in Huangping County.The proportion of children with secondary atrial septal defect was the highest,and that of the aortic valve malformation was the lowest.Among the complex cases of CHD,the proportion of children with single type was the highest,and that of children with three or more types were the lowest.Among children with CHD,the rate of delayed medical treatment was 76.19% (80/105).The median delay in medical treatment was 12 months,with an average of(18.78±4.77)months.Multifactor logistic regression analysis showed that heart murmur(level 2～3),less-educated(primary and secondary school)guardian,family per capita income<2 000 yuan,and frequent drinking of the guardian were independent risk factors for delayed medical treatment(P<0.05),and commercial settlement of medical expenses was independent protective factor(P<0.05).Risk scoring model divided the children into three groups:low risk(≤80 points),medium risk(>80 points and≤134 points)and high(>134 points)risk group.The evaluation of the model show that it was accurate,effective,safe,and reliable.Conclusion The highest prevalence is observed in Liping County.The proportion of children with secondary atrial septal defect and the proportion of children with single type are the highest.Delayed medical treat-ment is found in most of the children with CHD.Cardiac murmur,education background of the guardian,per capita family income,guardian alcohol consumption,and medical expense settlement method are all independent influencing factors for delayed medical treatment.

  Objective  To establish and evaluate the clinical teaching and training model for refresher anesthesiologists.  Methods  A total of 25 refresher anesthesiologists from the Department of Anesthesiology in Peking Union Medical College Hospital during the period of March to September 2023 were enrolled. They were taught with the clinical teaching and training model, namely "tutorial system-knowledge update-clinical practice". The refresher anesthesiologists completed the same structured pre-designed questionnaire at the beginning and the end of training respectively. The scores were recorded and compared to evaluate the effectiveness of the clinical training model. Feedback from refresher anesthesiologists about the teaching and training model was also collected.  Results  Altogether 84%(21/25) and 100%(25/25) of questionnaires distributed were completed respectively, and 92% students gave positive feedback. The mean score at the end of training (10.1±1.1) was significantly higher than that at the beginning (5.6±1.8)(P < 0.01).  Conclusion  The "tutorial system-knowledge update-clinical practice" clinical teaching and training model was significantly useful to elevate the effectiveness of training refresher anesthesiologists and their satisfaction.