Objective To develop a method for accurate identification of multiscale carotid plaques in ultrasound images.Methods We proposed a two-stage carotid plaque detection method based on deep convolutional neural network(SM-YOLO).A series of algorithms such as median filtering,histogram equalization,and Gamma transformation were used to preprocess the dataset to improve image quality.In the first stage of the model construction,a candidate plaque set was built based on the YOLOX_l target detection network,using multiscale image training and multiscale image prediction strategies to accommodate carotid artery plaques of different shapes and sizes.In the second stage,the Histogram of Oriented Gradient(HOG)features and Local Binary Pattern(LBP)features were extracted and fused,and a Support Vector Machine(SVM)classifier was used to screen the candidate plaque set to obtain the final detection results.This model was compared quantitatively and visually with several target detection models(YOLOX_l,SSD,EfficientDet,YOLOV5_l,Faster R-CNN).Results SM-YOLO achieved a recall of 89.44%,an accuracy of 90.96%,a F1-Score of 90.19%,and an AP of 92.70%on the test set,outperforming other models in all performance indicators and visual effects.The constructed model had a much shorter detection time than the Faster R-CNN model(only one third of that of the latter),thus meeting the requirements of real-time detection.Conclusion The proposed carotid artery plaque detection method has good performance for accurate identification of carotid plaques in ultrasound images.

Objective To develop a method for accurate identification of multiscale carotid plaques in ultrasound images.Methods We proposed a two-stage carotid plaque detection method based on deep convolutional neural network(SM-YOLO).A series of algorithms such as median filtering,histogram equalization,and Gamma transformation were used to preprocess the dataset to improve image quality.In the first stage of the model construction,a candidate plaque set was built based on the YOLOX_l target detection network,using multiscale image training and multiscale image prediction strategies to accommodate carotid artery plaques of different shapes and sizes.In the second stage,the Histogram of Oriented Gradient(HOG)features and Local Binary Pattern(LBP)features were extracted and fused,and a Support Vector Machine(SVM)classifier was used to screen the candidate plaque set to obtain the final detection results.This model was compared quantitatively and visually with several target detection models(YOLOX_l,SSD,EfficientDet,YOLOV5_l,Faster R-CNN).Results SM-YOLO achieved a recall of 89.44%,an accuracy of 90.96%,a F1-Score of 90.19%,and an AP of 92.70%on the test set,outperforming other models in all performance indicators and visual effects.The constructed model had a much shorter detection time than the Faster R-CNN model(only one third of that of the latter),thus meeting the requirements of real-time detection.Conclusion The proposed carotid artery plaque detection method has good performance for accurate identification of carotid plaques in ultrasound images.

Objective:To explore the relationship between prognostic nutritional index (PNI) and cognitive impairment (CI) in maintenance hemodialysis (MHD) patients.Methods:It was a multicenter cross-sectional study that included adult patients who received MHD treatment at 18 hemodialysis centers in Guizhou province from June to October 2020 as the study subjects. Cognitive function was assessed with the mini-mental state examination score. According to the scale score, the patients were divided into CI group (≤27 scores) and non-CI group (>27 scores), and the differences between the two groups were compared. The patients were divided into Q1 (PNI<38.0), Q2 (38.0≤PNI<40.4), Q3 (40.4≤PNI<43.0), and Q4 (PNI≥43.0) groups based on the PNI quartiles. The PNI was estimated based on the serum albumin and lymphocyte count. Multivariate logistic regression analysis was used to analyze the correlation between PNI and CI, and subgroup analysis was conducted.Results:A total of 1 740 MHD patients were enrolled in the study, with 1 021 males (62.9%) and 719 females (37.1%). The age was (55±15) years old. There were 411 patients (23.6%) with CI. The age, C-reactive protein, and the proportions of females, current smoking/drinking and diabetes in the CI group were significantly higher than those in the non-CI group, and the education level, blood lymphocyte count, blood prealbumin, serum albumin, serum creatinine, blood uric acid and PNI were significantly lower than those in the non-CI group (all P<0.05). The risk of CI in Q1 group was 1.88 times higher than that of Q4 group after adjusting for confounding factors such as sex, age, body mass index, education level, comorbidities, current smoking/drinking, dialysis age and C-reactive protein ( OR=1.88, 95% CI 1.17-2.30, P=0.008). Subgroup analysis showed that there was an interaction between age and PNI on CI ( P=0.040 for interaction). Q1 group in the patients aged 18 to 45 years old had a higher risk of CI compared to Q4 group ( OR=3.30, 95% CI 1.19-9.10). Conclusions:Low PNI significantly increases the risk of CI in MHD patients, in particularly in the patients aged <45 years old.

Objective:To compare the accuracy and generalized robustness of three predictive models of knowledge-based treatment strategies for radiotherapy for optimized model selection.Methods:The clinical radiotherapy plans of 45 prostate cancer (PC) cases and 25 nasopharyngeal cancer (NPC) cases were collected, and analyzed using three models (Z, L and S model), proposed by Zhu et al, Appenzoller et al and Shiraishi et al, respectively, to predict the dose-volume histogram (DVH) of bladder and rectum on PC cases and that of left and right parotid on NPC cases. The prediction error was measured by the difference of area under the predicted DVH and the clinical DVH curves (|V (pre_DVH)-V (clin_DVH)|), where a smaller prediction error implies a greater prediction accuracy. The accuracies of these three models were compared on the single organ at risk (OAR), and the generalized robustness of models was evaluated and compared by calculating the standard deviation of the prediction accuracy on different OAR. Results:For bladder and rectum, the prediction error of L model (0.114 and 0.163, respectively) was significantly higher than those values of Z and S models (≤0.071, P<0.05); for left parotid gland, the predicted error of S model (0.033) did not present significant difference from those values of Z and L models (≤0.025, P>0.05); for right parotid gland, S model (0.033) demonstrated significantly higher prediction error than those of Z and L models (≤0.028, P<0.05). Regarding different OAR, S model showed a lower standard deviation of prediction accuracy when comparing to Z and L models (0.016, 0.018 and 0.060, respectively). Conclusions:In the prediction of DVH in bladder and rectum of PC, Z and S models were more accurate than L model. In contrast, Z and L models demonstrated higher accuracy than S model in the prediction of left and right parotid glands of NPC. In respect to different OAR, the generalized robustness of S model was superior than the other two models.

Objective To explore the efficacy and toxicities of S-1 in the maintenance treatment of advanced esophageal cancer. Methods A total of 52 advanced esophageal cancer patients who benefited from the first-line treatment were randomly divided into experimental group (26 cases received S-1 orally as maintenance treatment) and control group (26 cases received placebo orally) by means of coin toss. After treatment, the efficacy and toxicities of the two groups were observed comparatively. Results The overall response rates (ORR) in experimental group and control group were 84.6% (22/26) and 76.9% (20/26), respectively, and there was significant difference between the two groups (χ2=3.885, P=0.049). The median progression free survival (PFS) time of experimental group was 14.4 months, and that of control group was 12.5 months (χ2= 3.885, P= 0.049). The main adverse reactions of the two groups were grade 1-2, and grade 4 adverse reactions did not appear in all patients. Conclusion S-1 is effective and well-tolerated in the maintenance treatment of advanced esophageal cancer.

Objective To investigate the prevalence of PLA2R1 in renal biopsy specimens of patients with idiopathic membranous nephropathy (IMN) and explore the relationship between PLA2R1 and IMN. Methods A total of 108 adult patients with biopsy-proved glomerular diseases were enrolled in this study, including 41 with IMN, 2 with hepatitis B-associated membranous nephropathy, 8 with V lupus nephritis, 27 with IgA nephropathy, 19 with minimal change nephropathy, 5 with mild mesangial proliferative glomerulonephritis, and 6 with focal segmental glomeruloselerosis (FSGS). Indirect immunofluorescence assay was used to detect PLA2R1 in the biopsy specimens and the clinical variables of the IMN patients were analyzed. Results In 35 of the 41 (85.37%) patients with IMN, PLA2R1 was detected with a fine granular pattern in the subepithelial deposits along the glomerular capillary loops. PLA2R1 antigen was not detected in patients with other glomerulopathies. No significant differences were found in age, serum creatinine, serum albumin, or 24-h urinary protein level between PLA2R1-positive and negative patients with IMN (P>0.05). Conclusion According to our results, 85.37% of adult patients with biopsy-proven IMN are positive for PLA2R1 antigen, which, however, does not contribute to variations of the patients' clinical manifestations.

Objective To investigate the prevalence of PLA2R1 in renal biopsy specimens of patients with idiopathic membranous nephropathy (IMN) and explore the relationship between PLA2R1 and IMN. Methods A total of 108 adult patients with biopsy-proved glomerular diseases were enrolled in this study, including 41 with IMN, 2 with hepatitis B-associated membranous nephropathy, 8 with V lupus nephritis, 27 with IgA nephropathy, 19 with minimal change nephropathy, 5 with mild mesangial proliferative glomerulonephritis, and 6 with focal segmental glomeruloselerosis (FSGS). Indirect immunofluorescence assay was used to detect PLA2R1 in the biopsy specimens and the clinical variables of the IMN patients were analyzed. Results In 35 of the 41 (85.37%) patients with IMN, PLA2R1 was detected with a fine granular pattern in the subepithelial deposits along the glomerular capillary loops. PLA2R1 antigen was not detected in patients with other glomerulopathies. No significant differences were found in age, serum creatinine, serum albumin, or 24-h urinary protein level between PLA2R1-positive and negative patients with IMN (P>0.05). Conclusion According to our results, 85.37% of adult patients with biopsy-proven IMN are positive for PLA2R1 antigen, which, however, does not contribute to variations of the patients' clinical manifestations.

OBJECTIVETo explore the relationship between the major allergens of 6 common allergic foods and IgA nephropathy.

METHODSA sensitive sandwich enzyme-linked immunosorbent assay (ELISA) was used to detect the serum levels of food-specific IgA1, IgG and IgE in 31 patients with IgA nephropathy and 80 healthy volunteers. All the patients were examined for a history of food allergy using a questionnaire.

RESULTSSerum levels of IgA1 and IgG against the major allergens of the 6 common allergic foods were significantly higher in patients with IgA nephropathy than in healthy volunteers (P<0.05). There was no detectable food-specific IgE antibodies in the two groups. No patients had a clear history of food allergy. All the patients with increased IgG levels specific to 4 or more foods simultaneously had proteinuria.

CONCLUSIONSSome foods especially the highly allergic ones may participate in the pathogenesis and progression of IgA nephropathy.

Adult ; Antibody Specificity ; Case-Control Studies ; Female ; Food Hypersensitivity ; classification ; immunology ; Glomerulonephritis, IGA ; blood ; immunology ; Humans ; Immunoglobulin A ; blood ; Immunoglobulin E ; blood ; Immunoglobulin G ; blood ; Male ; Young Adult

Objective To explore the relationship between the major allergens of 6 common allergic foods and IgA nephropathy. Methods A sensitive sandwich enzyme-linked immunosorbent assay (ELISA) was used to detect the serum levels of food-specific IgA1, IgG and IgE in 31 patients with IgA nephropathy and 80 healthy volunteers. All the patients were examined for a history of food allergy using a questionnaire. Results Serum levels of IgA1 and IgG against the major allergens of the 6 common allergic foods were significantly higher in patients with IgA nephropathy than in healthy volunteers (P<0.05). There was no detectable food-specific IgE antibodies in the two groups. No patients had a clear history of food allergy. All the patients with increased IgG levels specific to 4 or more foods simultaneously had proteinuria. Conclusion Some foods especially the highly allergic ones may participate in the pathogenesis and progression of IgA nephropathy.

Objective To explore the relationship between the major allergens of 6 common allergic foods and IgA nephropathy. Methods A sensitive sandwich enzyme-linked immunosorbent assay (ELISA) was used to detect the serum levels of food-specific IgA1, IgG and IgE in 31 patients with IgA nephropathy and 80 healthy volunteers. All the patients were examined for a history of food allergy using a questionnaire. Results Serum levels of IgA1 and IgG against the major allergens of the 6 common allergic foods were significantly higher in patients with IgA nephropathy than in healthy volunteers (P<0.05). There was no detectable food-specific IgE antibodies in the two groups. No patients had a clear history of food allergy. All the patients with increased IgG levels specific to 4 or more foods simultaneously had proteinuria. Conclusion Some foods especially the highly allergic ones may participate in the pathogenesis and progression of IgA nephropathy.