A high throughput measurement method of human red blood cells (RBCs) deformability combined with optical tweezers technology and the microfluidic chip was proposed to accurately characterize the deformability of RBCs statistically. Firstly, the effective stretching deformation of RBCs was realized by the interaction of photo-trapping force and fluid viscous resistance. Secondly, the characteristic parameters before and after the deformation of the single cell were extracted through the image processing method to obtain the deformation index of area and circumference. Finally, statistical analysis was performed, and the average deformation index parameters (\begin{document}$ \overline {D{I_S}} $\end{document}, \begin{document}$ \overline {D{I_C}} $\end{document}) were used to characterize the deformability of RBCs. A high-throughput detection system was built, and the optimal experimental conditions were obtained through a large number of experiments. Three groups of samples with different deformability were used for statistical verification. The results showed that the smallest cell component \begin{document}$ \overline {D{I_S}} $\end{document} was 9.71%, and the detection flux of 8-channel structure was about 370 cells/min. High-throughput detection and characterization methods can effectively distinguish different deformed RBCs statistically, which provides a solution for high-throughput deformation analysis of other types of samples.
The number of white blood cells in the leucorrhea microscopic image can indicate the severity of vaginal inflammation. At present, the detection of white blood cells in leucorrhea mainly relies on manual microscopy by medical experts, which is time-consuming, expensive and error-prone. In recent years, some studies have proposed to implement intelligent detection of leucorrhea white blood cells based on deep learning technology. However, such methods usually require manual labeling of a large number of samples as training sets, and the labeling cost is high. Therefore, this study proposes the use of deep active learning algorithms to achieve intelligent detection of white blood cells in leucorrhea microscopic images. In the active learning framework, a small number of labeled samples were firstly used as the basic training set, and a faster region convolutional neural network (Faster R-CNN) training detection model was performed. Then the most valuable samples were automatically selected for manual annotation, and the training set and the corresponding detection model were iteratively updated, which made the performance of the model continue to increase. The experimental results show that the deep active learning technology can obtain higher detection accuracy under less manual labeling samples, and the average precision of white blood cell detection could reach 90.6%, which meets the requirements of clinical routine examination.
Objective To investigate the risk factors of perioperative red blood cells transfusion for coronary artery bypass grafting (CABG) surgery. Method We retrospectively analyzed the clinical data of 534 patients underwent CABG in our hospital from January to March 2014 year. Those patients were divided into two groups:an on-pump coronary artery bypass grafting group (on-pump group) and an off-pump coronary artery bypass grafting group (off-pump group). There were 185 males and 54 females with a mean age of 59.1±9.4 years in the on-pump group. There were 233 males and 62 females with a mean age of 60.3±8.5 years in the off-pump group. Preoperative data, the relative parameters of extracorporeal circulation, the quantity of red blood cells transfusion of those two groups were compared. risk factors associated with red blood cells transfusion were evaluated by multivariate logistic regression analysis. Results The risk factors of perioperative red blood cells transfusion were age (OR=1.04, 95% CI 1.02-1.07, P=0.001) , weight (OR=0.95, 95% CI 0.93-0.97, P<0.001) , smoking (OR=0.61, 95% CI 0.39-0.94, P=0.027) , preoperative level of HCT (OR=0.90, 95% CI 0.85-0.96, P=0.001) and cardiopulmonary bypass (CPB) (OR=4.90, 95% CI 3.11-7.71, P<0.001) . During CPB, the nadir hemoglobin (nHb) (OR=0.63, 95% CI 0.47-0.84, P=0.002) was the only independent risk factor of red blood cell transfusion. Conclusions Age, weight, non-smoking, preoperative level of HCT, CPB are the risk factors for patients underwent CABG perioperatively and the lowest level of Hb in CPB is an independent risk factor of perioperative red blood cells transfusion.
Spectrophotometry is a simple hemolytic evaluation method commonly used in new drugs, biomedical materials and blood products. It is for the quantitative analysis of the characteristic absorption peaks of hemoglobin. Therefore, it is essential to select the correct detection wavelength when the evaluation system has influences on the conformation of hemoglobin. Based on the study of changes in the characteristic peaks over time of the hemolysis supernatant in four systems, namely, cell culture medium, phosphate buffered saline (PBS), physiological saline and banked blood preservation solution, using continuous wavelength scanning, the selections of detection wavelength were proposed as follows. In the cell culture medium system, the wavelength of 415 nm should be selected within 4 h; , near 408 nm should be selected within 4~72 h. In PBS system, within 4 h, 541 nm, 577 nm or 415 nm should be selected; 4~72 h, 541 nm, 577 nm or near 406 nm should be selected. In physiological saline system, within 4 h, 414 nm should be selected; 4~72 h, near 405 nm should be selected; within 12 h, 541 nm or 577 nm could also be selected. In banked blood preservation solution system, within 72 h, 415 nm, 540 nm or 576 nm should be selected.
Objective To explore the predictive value of peripheral blood cells in the efficacy of neoadjuvant immunotherapy combined with chemotherapy for esophageal squamous cell carcinoma. Methods A retrospective study was conducted on patients with esophageal squamous cell carcinoma (clinical stages Ⅱ-Ⅳa) who underwent neoadjuvant immunotherapy combined with chemotherapy at the Department of Thoracic Surgery, Affiliated Hospital of North Sichuan Medical College from April 2020 to November 2023. According to whether the pathology was completely relieved after treatment, patients were divided into a pathological complete remission group and a pathological incomplete remission group. The College of American Pathologists criteria were used to evaluate the tumor pathological regression grade (TRG) after neoadjuvant therapy (TRG=0, 1 defined as a good efficacy group, TRG=2, 3 defined as a poor efficacy group). Results A total of 92 patients with esophageal squamous cell carcinoma were collected, including 72 males and 20 females. The average age was (65.86±7.66) years. The complete remission of pathology was closely related to the number of lymphocytes in the blood before treatment (P=0.019). The area under the curve (AUC) for predicting complete remission of esophageal squamous cell carcinoma after neoadjuvant immunotherapy combined with chemotherapy was 0.678, the maximum Youden index was 0.328, and the optimal cutoff value was 1.845. The incidence of postoperative pulmonary infection in the pathological incomplete remission group was higher than that in the pathological complete remission group (25.0% vs. 5.6%, P=0.030). Using the optimal cutoff value, there were statistically significant differences in pathological N stage and pathological TNM stage between patients with lymphocyte counts <1.845×109/L and ≥1.845×109/L (P<0.05). Treatment response (by TRG) was significantly associated with the pretreatment red blood cell count (P=0.009). The AUC for predicting a good TRG response was 0.669, with a maximum Youden index of 0.385 and an optimal cutoff value of 4.235. Between the good and poor response groups, there were statistically significant differences in postoperative pathological T stage (P<0.001), N stage (P=0.041), and TNM stage (P＜0.001). When stratified by the optimal cutoff value, there were statistically significant differences in age (P＜0.001) and the prevalence of hypertension (P=0.022) between patients with red blood cell counts <4.235×1012/L and ≥4.235×1012/L. Conclusion A pretreatment absolute lymphocyte count ≥1.845×109/L and a red blood cell count <4.235×1012/L are good predictors for pathological complete response and a good pathological response, respectively, following neoadjuvant immunotherapy combined with chemotherapy in patients with esophageal squamous cell carcinoma.