Objective To investigate the species of sandflies and the prevalence of Leishmania infections in sandflies from selected areas of northern and northwestern China, so as to provide insights into identification of leishmaniasis vectors and assessment of epidemiological trends of leishmaniasis in China. Methods Sandfly samples were collected from Mentougou District of Beijing Municipality, Xiangning County in Linfen City of Shanxi Province, Ejin Banner in Alxa League of Inner Mongolia Autonomous Region, and Payzawat County of Karamay District of Karamay City, Gaochang District of Turpan City in Xinjiang Uygur Autonomous Region from July 2023 to July 2024. Approximately 100 intact female sandfly samples were randomly selected from each site and the species of sandflies was identified according to morphological characteristics and molecular assays. Female sandflies originating from the same habitat were grouped into pools of 10 individuals. Leishmania infection was detected using polymerase chain reaction (PCR) assay targeting the internal transcribed spacer 1 (ITS-1) gene, and the prevalence of Leishmania infection was calculated in sandflies from different sampling sites using the minimum infection rate (MIR) method. In addition, positive amplicons were sequenced and subjected to phylogenetic analysis. Results A total of 6 155 sandflies were collected from different environments at sampling sites across the six aforementioned regions from July 2023 to July 2024. Phlebotomus chinensis (96.00%) was the dominant sandfly species in Mentougou District, Beijing Municipality, with a small proportion of Ph. sergenti (4.00%), and only Ph. chinensis was found in Xiangning County, Linfen City, Shanxi Province. Ph. wui was the only sandfly species detected in Ejin Banner, Alxa League, Inner Mongolia Autonomous Region, and Payzawat County, Kashgar City, Xinjiang Uygur Autonomous Region, and Ph. caucasicus (97.70%) was the dominant sandfly species in Karamay District, Karamay City, Xinjiang Uygur Autonomous Region, with a small proportion of Ph. wui (2.30%), while Ph. alexandri was the only species in Gaochang District, Turpan City, Xinjiang Uygur Autonomous Region. A total of 40, 60, 34, 18, 18, and 22 pools of sandfly samples were tested from Mentougou District in Beijing Municipality, Xiangning County in Linfen City of Shanxi Province, Ejin Banner in Alxa League of Inner Mongolia Autonomous Region, Payzawat County in Kashgar City, Karamay District in Karamay City, and Gaochang District in Turpan City of Xinjiang Uygur Autonomous Region, respectively. L. infantum was detected in Ph. chinensis samples from Mentougou District in Beijing Municipality, and Xiangning County of Linfen City in Shanxi Province, with MIR of 0.25% to 1.00%, and L. donovani was detected in Ph. wui from Ejin Banner in Alxa League of Inner Mongolia Autonomous Region, and Payzawat County in Kashgar City of Xinjiang Uygur Autonomous Region, with MIR of 0.56% to 0.88%; however, no Leishmania infection was detected in Ph. caucasicus from Karamay District in Karamay City or Ph. alexandri from Gaochang District in Turpan City of Xinjiang Uygur Autonomous Region. Phylogenetic analysis showed that the Leishmania ITS-1 gene sequences obtained from Mentougou District in Beijing Municipality and Xiangning County in Linfen City of Shanxi Province were clustered into the same clade with the reference sequences of L. infantum ITS-1 gene, while the Leishmania ITS-1 gene sequences obtained from Ejin Banner in Alxa League of Inner Mongolia Autonomous Region and Payzawat County in Kashgar City of Xinjiang Uygur Autonomous Region were clustered into the same clade with the reference sequences of L. donovani ITS-1 gene. Conclusions There are variations in sandfly species in selected areas of northern and northwestern China, and variations in the species of Leishmania infecting sandflies. Improved surveillance of sandfly vectors and targeted control strategies with adaptations to geographical features and leishmaniasis vectors are recommended.

Objective To investigate the clinical efficacy of minimally invasive mitral valvuloplasty (MVP) in the treatment of infective endocarditis (IE) with mitral regurgitation (MR). Methods A retrospective analysis was conducted on the clinical data of patients who underwent MVP for IE with MR at the Department of Cardiovascular Surgery in Zhongshan Hospital, Fudan University from 2016 to 2020. Patients were divided into two groups based on the surgical incision: those with a right mini-thoracotomy were classified as a minimally invasive surgery (MIS) group, and those with a median sternotomy (MS) were classified as an MS group. All patients had isolated mitral valve involvement. Perioperative data were analyzed, and mid- to long-term outcomes were compared between the two groups. Results A total of 86 patients were included, with 40 in the MIS group [22 males and 18 females, with a mean age of (39.78±15.36) years ranging from 14 to 75 years] and 46 in the MS group [27 males and 19 females, with a mean age of (49.94±16.13) years ranging from 14 to 71 years]. The patients in the MIS group were relatively younger (P=0.004) with better preoperative cardiac function (P=0.004). There was no statistical difference in preoperative fever, gender, or comorbidities between the two groups (P>0.05). The MIS group had shorter postoperative ventilation times, less postoperative 24-hour drainage, less blood transfusion, and shorter total hospital stays compared to the MS group (P＜0.05). There was no statistical difference in cardiopulmonary bypass times or ICU stays between the two groups (P>0.05). The perioperative complication rates and mortality rates were not significantly different between the two groups (P>0.05). Follow-up was conducted for 11-92 months, with a mean duration of (49±19) months and an overall follow-up rate of 91.9%. During the follow-up, 3 patients in each group required reoperation for mitral valve issues, with no statistical difference in incidence (7.5% vs. 6.5%, P=0.691). There were no warfarin-related complications, recurrences, or deaths in either group during follow-up. Multivariate regression analysis identified age, preoperative cardiac function, and surgeon experience as influencing factors for the choice of surgical approach. Conclusion Minimally invasive MVP for IE with MR is relatively safe in the perioperative period and shows significant efficacy, with clear mid- to long-term outcomes. It is recommended for younger patients with better preoperative cardiac function and when performed by surgeons with extensive experience in mitral valvuloplasty.

Background Work-related musculoskeletal disorders (WMSDs) are common across industries. Workers in the hairdressing industry are frequently exposed to repetitive upper-limb movements and awkward working postures, which may increase their susceptibility to WMSDs. However, evidence on WMSDs among workers in this industry remains limited. Objective This study aimed to investigate the prevalence of self-reported WMSDs symptoms and associated factors among workers in the hairdressing industry in Hongkou District, Shanghai. Methods A cross-sectional survey was conducted using quota sampling in all eight subdistricts of Hongkou District, Shanghai. Hair salons in each subdistrict were ranked by the number of hairdressers and shampoo workers, and the 6 salons with the largest staff size in each subdistrict were selected, resulting in 48 survey sites. Hairdressers and shampoo workers who met the inclusion and exclusion criteria were surveyed using the Chinese version of the Musculoskeletal Disorders Questionnaire. Information on their individual characteristics, musculoskeletal symptoms, and work-related factors was collected. Chi-square tests and Firth logistic regression were used to estimate the prevalence of self-reported WMSDs symptoms and identify associated factors. Results The overall prevalence of self-reported WMSDs symptoms among workers in the hairdressing industry was 45.72%. Among hairdressers, the most commonly affected body regions were the neck (31.51%), shoulders (25.57%), lower back (15.98%), and feet (14.61%). Among shampoo workers, the most commonly affected regions were the neck (24.17%), lower back (24.17%), shoulders (20.83%), and upper back (10.83%). Firth logistic regression showed that fatigue in the corresponding body region after several hours of continuous work was positively associated with self-reported WMSDs symptoms in both types of workers (OR=6.544-52.838). Regarding individual characteristics, shorter height (female≤160 cm, male≤165 cm) was positively associated with self-reported neck and foot symptoms among hairdressers, and self-reported shoulder symptoms among shampoo workers (OR=16.324, 15.084, 9.680). Female shampoo workers had higher odds of self-reported neck symptoms than male shampoo workers (OR=4.924). Smoking was positively associated with self-reported upper-back and lower-back symptoms among shampoo workers (OR=10.544, 4.381). Among work-related factors, maintaining a fixed neck posture for long periods among hairdressers and prolonged standing among shampoo workers were positively associated with self-reported neck symptoms (OR=6.123, 3.080). Among shampoo workers, frequent overtime and maintaining a twisted posture were positively associated with self-reported upper-back symptoms (OR=11.710, 35.306). Sufficient rest time was negatively associated with self-reported foot symptoms among hairdressers (OR=0.238). Conclusion The prevalence of self-reported WMSDs symptoms was relatively high among workers in the hairdressing industry. Work-related fatigue and awkward working postures were strongly associated with WMSDs symptoms. Measures such as optimizing work-rest schedule, improving ergonomic workplace design, implementing fatigue monitoring and management, promoting work-break exercises, and providing training on appropriate working posture may help reduce the burden of WMSDs symptoms in this occupational group.

ObjectiveTo construct a risk prediction model for carotid artery plaques in high-risk populations of stroke based on five machine learning methods. MethodsThe clinical information of the high-risk population of stroke was collected. Factor analysis and statistical analysis of syndrome elements were conducted on their traditional Chinese medicine （TCM） symptoms and tongue and pulse manifestations. On the basis of the results of factor analysis and variable screening， five machine learning methods-classification and regression tree （CART） decision tree， support vector machine （SVM）， back propagation（BP） neural network， logistic regression， and random forest-were used to construct the risk prediction model for carotid artery plaques. ResultsThe most common TCM syndrome elements in the high-risk population of stroke was Qi deficiency. The scores of Qi deficiency， Yin deficiency， and Yang deficiency in the population with carotid artery plaques were higher than those without carotid artery plaques （P<0.05）. The CART decision tree， SVM， logistic regression， BP neural network， and random forest models showed the areas under the receiver operating characteristic （ROC） curves of 0.71， 0.75， 0.76， 0.76， and 0.75， the accuracy rates of 68.94%， 69.27%， 69.44%， 70.10%， and 69.60%， the precision rates of 68.56%， 68.53%， 68.75%， 69.74%， and 69.42%， the recall rates of 68.91%， 67.93%， 67.92%， 68.10%， and 67.31%， and the F₁ values of 0.69， 0.68， 0.68， 0.68， and 0.68， respectively. ConclusionAmong the high-risk population of stroke， the most frequently distributed TCM syndrome element is Qi deficiency， with the rest mainly being fire heat， Yin deficiency， Yang deficiency， phlegm dampness， blood stasis， and Qi stagnation. Deficiency syndrome may be a major factor leading to carotid artery plaques in the high-risk population of stroke. The BP neural network model demonstrates better performance in predicting the risk of carotid artery plaques in the high-risk population of stroke. People with carotid artery plaques are more likely to present with symptoms such as a heavy head， dizziness， headache， and thready pulse. The primary community benefits more widely when the BP neural network model is adopted to predict the risk of carotid artery plaques in the high-risk population of stroke over 40 years old.

ObjectiveTo construct a risk prediction model for carotid artery plaques in high-risk populations of stroke based on five machine learning methods. MethodsThe clinical information of the high-risk population of stroke was collected. Factor analysis and statistical analysis of syndrome elements were conducted on their traditional Chinese medicine （TCM） symptoms and tongue and pulse manifestations. On the basis of the results of factor analysis and variable screening， five machine learning methods-classification and regression tree （CART） decision tree， support vector machine （SVM）， back propagation（BP） neural network， logistic regression， and random forest-were used to construct the risk prediction model for carotid artery plaques. ResultsThe most common TCM syndrome elements in the high-risk population of stroke was Qi deficiency. The scores of Qi deficiency， Yin deficiency， and Yang deficiency in the population with carotid artery plaques were higher than those without carotid artery plaques （P<0.05）. The CART decision tree， SVM， logistic regression， BP neural network， and random forest models showed the areas under the receiver operating characteristic （ROC） curves of 0.71， 0.75， 0.76， 0.76， and 0.75， the accuracy rates of 68.94%， 69.27%， 69.44%， 70.10%， and 69.60%， the precision rates of 68.56%， 68.53%， 68.75%， 69.74%， and 69.42%， the recall rates of 68.91%， 67.93%， 67.92%， 68.10%， and 67.31%， and the F₁ values of 0.69， 0.68， 0.68， 0.68， and 0.68， respectively. ConclusionAmong the high-risk population of stroke， the most frequently distributed TCM syndrome element is Qi deficiency， with the rest mainly being fire heat， Yin deficiency， Yang deficiency， phlegm dampness， blood stasis， and Qi stagnation. Deficiency syndrome may be a major factor leading to carotid artery plaques in the high-risk population of stroke. The BP neural network model demonstrates better performance in predicting the risk of carotid artery plaques in the high-risk population of stroke. People with carotid artery plaques are more likely to present with symptoms such as a heavy head， dizziness， headache， and thready pulse. The primary community benefits more widely when the BP neural network model is adopted to predict the risk of carotid artery plaques in the high-risk population of stroke over 40 years old.

Objective: To analyze the distribution characteristics of immunoglobulin A (IgA) concentration in Nanning Zhuang blood donors by measuring the concentration of plasma IgA. Methods: Enzyme-linked immunosorbent assay (ELISA) was performed to measure the absorbance of 2 000 plasma samples from Zhuang blood donors. The IgA concentration in samples was calculated using the ELISA Calc regression/fitting technology program. Results: The standard curve demonstrated that ELISA detection of plasma IgA concentration exhibited good precision. The frequency of IgA deficiency was 0/2 000. No statistically significant difference in the distribution of IgA concentration was observed between males and females (P>0.05). The distribution of IgA concentration varied significantly across age groups: younger individuals (18-39 years old) had lower plasma IgA levels (mg/dL) compared to older individuals (40-56 years old): 5-89.99 mg/dL group, 8.80% (176/2 000) vs 17.20% (344/2 000); 90-450 mg/dL group,20.65% (413/2 000) vs 51.20% (1 024/2 000); >450 mg/dL group, 0.45%, (9/2 000) vs 1.70% (34/2 000), P<0.05. No significant difference in IgA concentration was found among different ABO blood types in Zhuang blood donors (P>0.05). Spearman correlation analysis revealed a positive correlation between age and IgA concentration (R =0.114, P<0.05). Conclusion: No individuals with IgA deficiency were screened out among the Zhuang blood donors in Nanning area, and plasma IgA levels progressively increase with age.

[This corrects the article DOI: 10.1016/j.apsb.2019.01.013.].

Objective:To investigate the value of quantitative parameters of dual-layer detector spectral CT (DLCT) in preoperative prediction of lymphovascular invasion (LVI) in invasive lung adenocarcinoma.Methods:This study employed a cross-sectional design. The data of 91 patients with primary lung adenocarcinoma confirmed by postoperative pathology who underwent DLCT enhanced scanning in the First Affiliated Hospital of Zhengzhou University from March 2022 to July 2024 were retrospectively collected. The patients were divided into LVI positive group and LVI negative group according to the postoperative pathology. Gender, age, smoking status, and lesion location were recorded,the clinical T-stage and N-stage were evaluated. Spectral base data images were generated based on the spectral reconstruction algorithm. Conventional CT features such as the size and density of the lesions were analyzed. The DLCT quantitative parameters such as 40 keV single-energy CT value (CT 40 keV), iodine density (ID), standardized iodine density (NID), and effective atomic number (Z eff) were measured. The differences of parameters between the two groups were compared using t-test, Mann-Whitney U test, or χ2 test. Multivariate logistic regression analysis was used to identify independent factors for predicting invasive lung adenocarcinoma LVI. The predictive performance of individual parameters and their combinations for LVI in invasive lung adenocarcinoma was evaluated using receiver operating characteristic curve analysis and area under the curve (AUC) measurements. Results:There were significant differences in age, T stage, N stage, maximum diameter, focal density, and arteriovenous stage NID and Z eff between the LVI positive group and the LVI negative group ( P<0.05). Multiple logistic regression analysis showed that age ( OR=0.890, 95% CI 0.821-0.966), N stage( OR=12.721, 95% CI 2.676-60.473) and venous stage Z eff( OR=0.012,95% CI 0-0.668) were independent factors for predicting invasive lung adenocarcinoma LVI ( P<0.05). The combination of age, N stage, and venous-phase Z eff values demonstrated the highest predictive efficacy for LVI in invasive lung adenocarcinoma, with an AUC of 0.916. Conclusions:The quantitative parameters of DLCT are helpful for preoperative prediction of LVI status of invasive lung adenocarcinoma. The Z eff in the venous stage is an independent predictor, the combination of multiple parameters can further improve the diagnostic efficiency.