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An essential industrial application is the examination of surface flaws in hot-rolled steel strips. While automatic visual inspection tools must meet strict real-time performance criteria for inspecting hot-rolled steel strips, their capabilities are constrained by the accuracy and processing speed of the algorithm used to identify defects. To solve the problems of poor detection accuracy, low detection efficiency, and unsuitability of low computing power platforms of the hot-rolled strip surface defect detection algorithm The Swin-Transformer-YOLOv5 model based on the improved one-stage detector is proposed. By employing GhostNet, the model's lightweight design, and guaranteed detection accuracy are both achieved. The C3 module introduces Swin-Transformer to address the issues of cluttered backdrops of defect photos and easily confused defect categories. With the addition of the CoordAttention module, the model's capacity to extract defective features is improved, and its performance keeps getting better. The issue of huge differences in different scales and poor detection of small flaws is resolved by employing BiFPN for feature fusion, and the detector's capacity to adapt to targets of different scales is improved. The experimental results demonstrate that the improved Swin-Transformer-Yolov5 model significantly outperforms the industry-standard target detection algorithms, and the model's mAP value still improves by 8.39% over the original model while reducing the number of parameters, GFLOPs, and weight by 36.6%, 40.0%, and 34.7%, respectively. The model is better suited for use on low-arithmetic platforms as a result. [ABSTRACT FROM AUTHOR]

The validated therapeutic effects of dihydroartemisinin (DHA) in solid tumors have encouraged us to explore its potential in treating T-cell lymphoma. We found that Jurkat cells (a T-cell lyphoma cell line) were sensitive to DHA treatment with a IC50 of dihydroartemisinin. The cytotoxic effect of DHA in Jurkat cells showed a dose- and time- dependent manner. Interestingly, the cytotoxic effect of DHA was further enhanced by holotransferrin (HTF) due to the high expression of transferrin receptors in T-cell lymphoma. Mechanistically, DHA significantly increased the production of intracellular reactive oxygen species, which led to cell cycle arrest and apoptosis. The DHA treatment also inhibited the expression of protumorgenic factors including VEGF and telomerase catalytic subunit. Our results have proved the therapeutic effect of DHA in T-cell lymphoma. Especially in combination with HTF, DHA may provide a novel efficient approach in combating the deadly disease. [ABSTRACT FROM AUTHOR]

Background and purpose: To date, sepsis remains the main cause of mortality in intensive care units (ICU). This study aimed analyze the risk factors of the prognosis in sepsis patients. Methods: In this case-control study, patients with sepsis admitted to the intensive care unit of a Chinese hospital between January and November 2020 were analyzed. Ultrasound and clinical data were analyzed and compared between non-survivors and survivors. The ROC curve analysis was also performed to determine the best indicator for predicting mortality. Results: A total of 72 patients with sepsis in ICU were included for analysis. The basic characteristics between the survivals and non-survivals were similar, except for acute physiology and chronic health evaluation (APACHE) Ⅱ score, sepsis-related organ failure assessment (SOFA) score, lactate level, ultrasound parameters from superior mesenteric artery (SMA) such as peak systolic velocity (PSV), end-diastolic velocity (EDV) and resistive index (RI). Univariate analysis revealed that the APACHE Ⅱ score, SOFA score, lactate, low PSV, EDV, and RI were potential risk factors for mortality in sepsis, while multivariate analysis suggested that low PSV was an independent risk factor for mortality, and the adjusted odds ratio was 0.295 (95% CI: 0.094–0.925). The ROC analysis showed that the PSV (AUC = 0.99; sensitivity and specificity were 0.99 and 0.96, respectively) had good predictive value for mortality in sepsis. Conclusion: Low PSV as found to be an independent risk factor and good predictor for mortality in patients with sepsis. This study shows the promise of ultrasound in predicting mortality in patients with sepsis; however, further studies are needed to validate these results. [ABSTRACT FROM AUTHOR]