Real-time spatiotemporal action localization algorithm using improved CNNs architecture.

This paper aims to propose a faster and more accurate network for human spatiotemporal action localization tasks. Like the YOWO model, we also use convolutional neural networks (CNNs) for feature extraction, but our model differs from YOWO in three significant ways: firstly, we don't use the feature fusion strategy, we only use spatial features extracted by 2D CNNs for action localization and spatiotemporal features extracted by 3D CNNs for action recognition; secondly, we make an improvement to the 2D CNNs network by introducing a coordinate attention mechanism and utilize the CIoU loss instead of the coordinate offset loss for bounding box regression; thirdly, we provide a more lightweight and faster spatiotemporal action localization architecture, which reduces the number of parameters by 21.76 million and achieves a speed of 39 fps on 16-frame input clips compared to the YOWO model. We test our model's performance on three public datasets: UCF-Sports, JHMDB-21 and UCF101-24. Compared with the YOWO model, we improve frame-mAP (@IoU 0.5) by 17.09% and 7.15% on the UCF-Sports and JHMDB-21 datasets, and for video-mAP, we improve by 2.7%, 8.7% and 14.4% at IoU thresholds of 0.2, 0.5 and 0.75 on the JHMDB-21 dataset.

Advanced nanomaterials for electrochemical sensors: application in wearable tear glucose sensing technology.

In the last few decades, tear-based biosensors for continuous glucose monitoring (CGM) have provided new avenues for the diagnosis of diabetes. The tear CGMs constructed from nanomaterials have been extensively demonstrated by various research activities in this field and are gradually witnessing their most prosperous period. A timely and comprehensive review of the development of tear CGMs in a compartmentalized manner from a nanomaterials perspective would greatly broaden this area of research. However, to our knowledge, there is a lack of specialized reviews and comprehensive cohesive reports in this area. First, this paper describes the principles and development of electrochemical glucose sensors. Then, a comprehensive summary of various advanced nanomaterials recently reported for potential applications and construction strategies in tear CGMs is presented in a compartmentalized manner, focusing on sensing properties. Finally, the challenges, strategies, and perspectives used to design tear CGM materials are emphasized, providing valuable insights and guidance for the construction of tear CGMs from nanomaterials in the future.

Chlorogenic Acid Inhibits Proliferation, Migration and Invasion of Pancreatic Cancer Cells via AKT/GSK-3ß/ß-catenin Signaling Pathway.

BACKGROUND: Chlorogenic acid (CA, United States Patent No. 10772340), a natural biologically active food ingredient, displays potent antitumor activity against a variety of cancer cells. However, the mechanism underlying its anticancer effect is not well elucidated. OBJECTIVE: In the present study, we hope to dissect the mechanism underlying the anticancer effects of CA in pancreatic cancer cells. METHODS: The cytotoxicity of CA in pancreatic cancer cells was determined by MTT assay. Flow cytometry was performed to evaluate the cells apoptosis, while a clonogenic assay was carried out to check the colony formation of cancer cells. Transwell assay was performed to assess the cells migration and invasion. The protein expression of AKT/GSK-3ß/ß-catenin signaling pathway was detected by Western Blot. RESULTS: Our data indicated that CA inhibited the proliferation of PANC-28 and PANC-1 cells in a dose and time-dependent manner. CA was able to inhibit colony formation, migration, and invasion ability and trigger apoptosis in PANC-28 and PANC-1 cells. Further study showed that CA down-regulated the expression of AKT, p-AKT(Thr308), p-GSK-3ß(Ser9), ß-catenin, N-cadherin, and vimentin while enhancing the expression of cleaved-caspase 3 and cleaved-caspase 7 in PANC-28 and PANC-1 cells. CONCLUSION: Our study provides significant evidence that CA is able to inhibit the growth of pancreatic cancer via the AKT/GSK-3ß/ß-catenin signaling pathway.

Comparison of drug concentrations in blood and gastric lavage fluid before and after gastric lavage: A case report.

BACKGROUND: Gastric lavage (GL) is one of the most important early therapies to remove unabsorbed toxins from the gastrointestinal tract. However, the details of performing gastric lavage remain to be established. There is controversy in clinical practice regarding individual choice of the timing of GL and its efficiency. CASE SUMMARY: We report the case of a young woman who presented to the Emergency Department with drug intoxication for four hours. We used the latest toxicological screening techniques to compare drug concentrations in the patient's blood and gastric lavage fluid before and after gastric lavage. The results confirmed that gastric lavage was effective in reducing drug concentrations in the stomach; a small amount of drug remained in the stomach at the end of gastric lavage. CONCLUSION: Gastric lavage is effective in reducing drug concentrations in the stomach, with a small amount of drug remaining in the stomach at the end of gastric lavage.

Accurate real-time obstacle detection of coal mine driverless electric locomotive based on ODEL-YOLOv5s.

The accurate identification and real-time detection of obstacles have been considered the premise to ensure the safe operation of coal mine driverless electric locomotives. The harsh coal mine roadway environment leads to low detection accuracy of obstacles based on traditional detection methods such as LiDAR and machine learning, and these traditional obstacle detection methods lead to slower detection speeds due to excessive computational reasoning. To address the above-mentioned problems, we propose a deep learning-based ODEL-YOLOv5s detection model based on the conventional YOLOv5s. In this work, several data augmentation methods are introduced to increase the diversity of obstacle features in the dataset images. An attention mechanism is introduced to the neck of the model to improve the focus of the model on obstacle features. The three-scale prediction of the model is increased to a four-scale prediction to improve the detection ability of the model for small obstacles. We also optimize the localization loss function and non-maximum suppression method of the model to improve the regression accuracy and reduce the redundancy of the prediction boxes. The experimental results show that the mean average precision (mAP) of the proposed ODEL-YOLOv5s model is increased from 95.2 to 98.9% compared to the conventional YOLOv5s, the average precision of small obstacle rock is increased from 89.2 to 97.9%, the detection speed of the model is 60.2 FPS, and it has better detection performance compared with other detection models, which can provide technical support for obstacle identification and real-time detection of coal mine driverless electric locomotives.

Comprehensive Analysis of Major Latex-Like Protein Family Genes in Cucumber (Cucumis sativus L.) and Their Potential Roles in Phytophthora Blight Resistance.

Major latex-like proteins (MLPs) play crucial roles in abiotic and biotic stresses. However, little was known about this gene family in cucumbers. In this study, a total of 37 putative cucumber MLP genes were identified on a genome-wide level and classified into three groups by sequence homologous comparison with Arabidopsis thaliana. Chromosome mapping suggested that only tandem duplication occurred in evolution. The multiple regulatory cis-elements related to stress, hormone, light and growth response were found in the promoter region of these CsMLP genes, indicating that CsMLPs might be widely involved in the process of plant growth, development and various stress conditions. Transcriptome analysis indicated a strong reprogramming of MLPs expression in response to Phytophthora melonis infection in cucumber. Knockdown of CsMLP1 reduced the P. melonis tolerance, while transient overexpression of CsMLP1 improved disease tolerance in cucumber. Conversely, the silence of CsMLP5 decreased the lesion area caused by P. melonis in the cotyledons, and overexpression of CsMLP5 promoted lesion expansion. Taken together, our results provide a comprehensive basis for further mining the function of CsMLP members and will also be significant for elucidating the evolutionary relationship in cucumber.

Nursing interruptions in emergency room in China: An observational study.

AIM: To analyse the frequency and core elements of nursing work interruptions in Chinese emergency nursing settings. BACKGROUND: Little is known about nursing interruptions, which affect the quality of services in Chinese emergency nursing setting. METHOD(S): A cross-sectional observational study was conducted in three units of an emergency department in a Chinese tertiary hospital. Participants comprised 60 nurses. Data were collected using a questionnaire developed by the researchers specifically for this study. RESULTS: In total, 25,965 min of work was observed and 2333 interruptions were identified. Most interruptions were from patients, their families and nurses. Therapeutic nursing and patient observation and documentation were the most frequently interrupted procedures. Most interruptions were negative, and a majority of the nurses immediately responded to interruptions. Significant differences existed in the overall distribution of the core elements among the three nursing units. CONCLUSIONS: The frequency of emergency nursing interruptions was moderate. Most interruptions tend to lead to negative treatment outcomes for patients. IMPLICATIONS FOR NURSING MANAGEMENT: Emergency nursing managers should recognize the importance of interruptions, understand work situations better and develop ways to reduce the incidence of interruptions. Thus, nursing risks can be avoided by reducing the adverse outcomes caused by work interruptions.