Prognosis factors for death within 90 days of discharge in patients with acute kidney injury requiring continuous renal replacement therapy after surgery for Stanford type A acute aortic dissection / 中华外科杂志

Objective: To investigate the prognosis factors for death within 90 days after discharge in patients with acute kidney injury(AKI) treated requiring continuous renal replacement therapy(CRRT) undergoing surgery for acute Standford type A aortic dissection. Methods: The clinic data of 126 patients undergoing CRRT for postoperative AKI after acute type A aortic dissection surgery in the Center for Cardiac Intensive Care, Beijing Anzhen Hospital from July 2016 to February 2019 were analyzed retrospectively. There were 83 males and 43 females, aging (52.9±11.2) years(range: 25 to 70 years). The patients' demographic characteristics, disease-related information, perioperative data, laboratory indexes during CRRT, complications, and survival information within 90 days after discharge were recorded. Independent prognosis factors for death within 90 days of discharge were determined by Kaplan-Meier survival analysis, univariate and multifactorial Cox regression analysis. Results: Totally 57 of 126 patients(45.2%) died over the first 90 days after discharge. Kaplan-Meier survival analysis and univariate Cox regression analysis showed that there were significant differences between the non-survival and survival group including ≥65 years old, high lactate values 12 hours after CRRT, pulmonary infection, liver dysfunction, presence of permanent neurological complications, and postoperative ejection fraction(EF)<45%. Multifactorial Cox regression analysis revealed that ≥65 years old(HR=2.14, 95%CI: 1.09 to 4.21, P=0.03), high lactate values 12 hours after CRRT(HR=1.13, 95%CI: 1.06 to 1.20, P=0.01) and postoperative EF<45%(HR=2.21, 95%CI: 1.09 to 4.51, P=0.03) were independent prognosis factors for patients' death within 90 days after hospital discharge. Conclusions: ≥65 years old, high lactate values 12 hours after CRRT and postoperative EF<45% are independent prognosis factors for death within 90 days after discharge in patients undergoing CRRT for AKI after acute type A aortic dissection surgery. Proper identification and management of prognosis factors could be beneficial to improve patients' outcomes.

Establishment of a deep learning-based visual model for intelligent recognition of Oncomelania hupensis / 中国血吸虫病防治杂志

Objective To establish a deep learning-based visual model for intelligent recognition of Oncomelania hupensis, the intermediate host of Schistosoma japonicum, and evaluate the effects of different training strategies for O. hupensis image recognition. Methods A total of 2 614 datasets of O. hupensis snails and 4 similar snails were generated through field sampling and internet capture, and were divided into training sets and test sets. An intelligent recognition model was created based on deep learning, and was trained and tested. The precision, sensitivity, specificity, accuracy, F1 score and Youden index were calculated. In addition, the receiver operating characteristic (ROC) curve of the model for snail recognition was plotted to evaluate the effects of “new learning”, “transfer learning” and “transfer learning + data enhancement” training strategies on the accuracy of the model for snail recognition. Results Under the “transfer learning + data enhancement” strategy, the precision, sensitivity, specificity, accuracy, Youden index and F1 score of the model were 90.10%, 91.00%, 97.50%, 96.20%, 88.50% and 90.51% for snail recognition, which were all higher than those under both “new learning” and “transfer learning” strategies. There were significant differences in the sensitivity, specificity and accuracy of the model for snail recognition under “new learning”, “transfer learning” and “transfer learning + data enhancement” training strategies (all P values < 0.001). In addition, the area under the ROC curve of the model was highest (0.94) under the “transfer learning + dataenhancement” training strategy. Conclusions This is the first visual model for intelligent recognition of O. hupensis based on deep learning, which shows a high accuracy for snail image recognition. The “transfer learning + data enhancement” training strategy is helpful to improve the accuracy of the model for snail recognition.

Spatio-temporal patterns of Oncomelania hupensis snail habitats in Suzhou, Wuxi and Changzhou cities along the Taihu Lake region / 中国血吸虫病防治杂志

Objective To investigate the spatio-temporal distribution characteristics of Oncomelania hupensis snail habitats in three cities of Suzhou, Wuxi and Changzhou along the Taihu Lake region, so as to provide technical supports for establishing a sensitive and highly effective surveillance and forecast system for schistosomiasis. Methods Snail distribution data were collected from Suzhou, Wuxi and Changzhou cities from 1950 to 2018, and the changing trend for snail habitats were described over years. In addition, the clusters of snail habitats were detected using Kernel density analysis and SaTScan space-time scan analysis. Results The number of snail habitats appeared a single-peak distribution in Suzhou, Wuxi and Changzhou cities from 1950 to 2018, which peaked in 1970 and then declined rapidly. There were 62.68% of snail habitats eliminated within 10 years after identification, of which 38.24% were eliminated at the year of identification. Kernel density analysis and SaTScan space-time scan analysis revealed that high-density clusters of snail habitats were mainly distributed in Kunshan City, Wuzhong District and Xiangcheng District from 1970 to 1980, and in Yixing City in 1990; since then, the clusters gradually shrank, and overall appeared a move from northeast to west of Taihu Lake. A total of 4 new clusters were detected after 1970, as revealed by space-time scanning of snail habitats. In current snail habitats, emerging snail habitats are mainly identified in Huqiu District (Dongzhu Town), Wuzhong District (Guangfu Town), Taicang City (Shaxi Town) and Jintan District, and re-emerging snail habitats are scattered in 7 districts. Conclusions The distribution of snail habitats are spatio-temporal aggregation in Suzhou, Wuxi and Changzhou cities. The monitoring and prediction of emerging and re-emerging snail habitats are the key points in the future.

Effects of dendritic cell-based adoptive immunotherapy with over-expressed SOCS1 on Th17- and Treg-related cytokines in the BALF of COPD mice / 医学研究生学报

Objective　Dendritic cells (DCs), helper T cells 17 (Th17) and regulatory T cells (Treg) are closely related to the pathogenesis of chronic obstructive pulmonary disease (COPD). This study aimed to investigate the changes of Th17- and Treg-related cytokines in the bronchoalveolar lavage fluid (BALF) of COPD mice after DC-based adoptive immunotherapy with over-expressed suppressor of cytokine signaling protein 1 (SOCS1) and provide some new ideas for the treatment of COPD.　Methods　A total of 48 male C57BL/6 mice were randomly divided into 5 groups: healthy control, COPD model control, immature DC (imDC), DC-SOCS1 1×106, and DC-SOCS1 2×106. The healthy controls were exposed to air and fed normally, the COPD model controls injected with normal saline at 0.5 mL/ on the first day of modeling by fumigation, the mice of the imDC group injected via the tail vein with 1 ×106 imDCs, and those of the DC-SOCS1 groups injected with 1 ×106 or 2 ×106 DCs with over expressed SOCS1, all via the tail vein on the 1st and 7th day of modeling. Then the lung tissues were collected from the mice for preparation of paraffin sections and HE staining, and ELISA was employed for determination of the levels of Th17-related IL-17 and IL-23 and Treg-related IL-10 and TGF-β in the BALF of the model mice.　Results　Compared with the COPD model controls, the mice in the imDC, DC-SOCS1 1×106 and DC-SOCS1 2×106 groups showed significantly decreased levels of IL-17 on the 1st day ([78.87 ± 1.08] vs [46.46 ± 0.77], [34.09 ± 3.98] and [24.12 ± 0.57] pg/mL, P < 0.05) and 7th day after modeling ([78.87 ± 1.08] vs [55.69 ±0.35], [35.65 ± 0.54] and [27.00 ± 0.58] pg/mL, P < 0.05), and IL-23 on the 1st day ([200.62 ± 0.65] vs [150.19 ± 0.53], [121.09 ± 0. 53] and [70.21 ± 0.91] pg/mL, P < 0.05) and 7th day ([200.62 ± 0.65] vs [167.70 ± 1.73], [136.34 ± 0.90] and [99.35 ± 1.83] pg/mL, P < 0.05), but remarkably increased levels of IL-10 on the 1st day ([39.46 ± 3.88] vs [50.74 ± 1.77], [58.71 ± 3.84] and [70.12 ± 2.62] pg/mL, P < 0.05) and 7th day ([39.46 ± 3.88] vs [44.56 ± 2.63], [54.78 ± 1.43] and [63.00 ± 2.57] pg/mL, P < 0.05), TGF-β on the 1st day ([24.98 ± 0.43] vs [36.46 ± 0.98], [42.40 ± 0.62] and [50.55 ± 0.53] pg/mL, P < 0.05) and 7th day ([24.98 ± 0.43] vs [33.27 ± 0.92], [40.12 ± 0.83] and [44.98 ± 0.52] pg/mL, P < 0.05). The contents of IL-17 and IL-23 were markedly lower while those of IL-10 and TGF-β higher in the DC-SOCS1 1×106 than in the imDC group (P < 0.05), and the levels of the former two significantly higher and those of the latter two lower in the DC-SOCS1 2×106 than in the DC-SOCS1 1×106 group (P < 0.05).　Conclusion　Transfusion of DCs with over-expressed SOCS1 can inhibit the secretion of Th17-related cytokines in COPD, and the effect is better than that of imDCs alone and related to the concentration and time.