Simulating doctors' thinking logic for chest X-ray report generation via Transformer-based Semantic Query learning.

Medical report generation can be treated as a process of doctors' observing, understanding, and describing images from different perspectives. Following this process, this paper innovatively proposes a Transformer-based Semantic Query learning paradigm (TranSQ). Briefly, this paradigm is to learn an intention embedding set and make a semantic query to the visual features, generate intent-compliant sentence candidates, and form a coherent report. We apply a bipartite matching mechanism during training to realize the dynamic correspondence between the intention embeddings and the sentences to induct medical concepts into the observation intentions. Experimental results on two major radiology reporting datasets (i.e., IU X-ray and MIMIC-CXR) demonstrate that our model outperforms state-of-the-art models regarding generation effectiveness and clinical efficacy. In addition, comprehensive ablation experiments fully validate the TranSQ model's innovation and interpretation. The code is available at https://github.com/zjukongming/TranSQ.

A bibliometric analysis of the neurotoxicity of anesthesia in the developing brain from 2002 to 2021.

Background: The neurotoxicity effects of anesthetic exposure on the developing brain have been one of the current research hotspots and numerous articles were published in the past decades. However, the quality and comparative information of these articles have not been reported. This research aimed to provide a comprehensive overview of the current state of the field by investigating research hotspots and publication trends concerning the neurotoxicity of anesthesia in the developing brain. Materials and methods: On 15 June 2022, we searched articles on the neurotoxicity of anesthesia in the developing brain through the Science Citation Index databases from 2002 to 2021. Data of the author, title, publication, funding agency, date of publication, abstract, type of literature, country, journal, keywords, number of citations, and research direction were collected for further analysis. Results: We searched and analyzed 414 articles in English on the field of neurotoxicity of anesthesia in the developing brain from 2002 to 2021. The country with the largest number of publications was The United States (US) (n = 226), which also had the largest total number of citations (10,419). Research in this field reached a small peak in 2017. Furthermore, the largest number of articles were published in three journals, Anesthesiology, Anesthesia and Analgesia, and Pediatric Anesthesia. The top 20 articles that were cited most often were studied. In addition, the top hotspots of this area in clinical investigations and basic research were analyzed separately. Conclusion: This study provided an overview of the development in the neurotoxicity of anesthesia in the developing brain using bibliometric analysis. Current clinical studies in this area were mainly retrospective; in the future, we should place more emphasis on prospective, multicenter, long-term monitoring clinical studies. More basic research was also needed on the mechanisms of neurotoxicity of anesthesia in the developing brain.

Effects of Electrical Impedance Tomography-Guided Positive End-Expiratory Pressure on Postoperative Cardiopulmonary Exercise Capacity in Elderly Patients: Study Protocol for a Randomized Controlled Trial.

BACKGROUND Mechanical ventilation can lead to cardiopulmonary complications in elderly patients undergoing abdominal surgery plus general anesthesia. The cardiopulmonary exercise test (CPET) is a dynamic and noninvasive evaluation method for assessing the cardiopulmonary system function under rest and stress. Positive end-expiratory pressure (PEEP) titration guided by electrical impedance tomography (EIT) can individualize lung protection strategies and may be beneficial in postoperative cardiopulmonary exercise capacity for these patients. MATERIAL AND METHODS This study is a prospective, single-center, randomized, and controlled trail that will include 80 elderly patients scheduled for major abdominal surgery. The patients will be divided into 2 groups: (1) intervention group: using individualized PEEP ventilation; and (2) control group: using fixed PEEP ventilation (3-5 cmH2O). RESULTS The primary outcome is the change of postoperative cardiopulmonary exercise capacity. CONCLUSIONS In this study, we will evaluate if EIT-guided PEEP titration can improve postoperative cardiopulmonary exercise capacity and reduce postoperative complications in elderly patients undergoing open abdominal surgery plus general anesthesia. If the result is in accordance with the hypothesis, it would provide evidence to aid the perioperative management for these patients.

Muscle-related parameters-based machine learning model for predicting postinduction hypotension in patients undergoing colorectal tumor resection surgery.

Objectives: This study used machine learning algorithms to identify important variables and predict postinduction hypotension (PIH) in patients undergoing colorectal tumor resection surgery. Methods: Data from 318 patients who underwent colorectal tumor resection under general anesthesia were analyzed. The training and test sets are divided based on the timeline. The Boruta algorithm was used to screen relevant basic characteristic variables and establish a model for the training set. Four models, regression tree, K-nearest neighbor, neural network, and random forest (RF), were built using repeated cross-validation and hyperparameter optimization. The best model was selected, and a sorting chart of the feature variables, a univariate partial dependency profile, and a breakdown profile were drawn. R2, mean absolute error (MAE), mean squared error (MSE), and root MSE (RMSE) were used to plot regression fitting curves for the training and test sets. Results: The basic feature variables associated with the Boruta screening were age, sex, body mass index, L3 skeletal muscle index, and HUAC. In the optimal RF model, R2 was 0.7708 and 0.7591, MAE was 0.0483 and 0.0408, MSE was 0.0038 and 0.0028, and RMSE was 0.0623 and 0.0534 for the training and test sets, respectively. Conclusion: A high-performance algorithm was established and validated to demonstrate the degree of change in blood pressure after induction to control important characteristic variables and reduce PIH occurrence.

A Bibliometric Analysis of Research on Ketamine From 2001 to 2020.

Background: Ketamine is an intravenous anesthetic with analgesic effects that has a rapid onset and short duration of action. Many studies have been conducted on the use of ketamine; however, the quantity and quality of such studies have not been reported. Therefore, we aimed to conduct a bibliometric analysis of research on ketamine from 2001 to 2020. Methods: We used the Web of Science database to get publications on ketamine from January 2001 to December 2020. Various bibliographic information was collected, including the number of publications, year of publication, country of origin, journal name, research hotspots, citation count, and author information. Results: A total of 5,192 articles were included in the analysis. The United States published the highest number of papers on ketamine and the United States participated in publishing the most papers and disclosure funds. The types of articles in clinical trials were cited more frequently. Most articles on ketamine were published in the journal Anesthesia and Analgesia. Furthermore, the antidepressant effect of ketamine has been a research hotspot for the last 20 years. Conclusion: This study provided a comprehensive analysis of research on ketamine and highlighted the growing interest in ketamine and its antidepressant effects.

Bicomponent PLA Nanofiber Nonwovens as Highly Efficient Filtration Media for Particulate Pollutants and Pathogens.

Herein, a novel form of bicomponent nanofiber membrane containing stereo-complex polylactic acid (SC-PLA) was successfully produced by the side-by-side electrospinning of Poly (L-lactic acid) (PLLA) and Poly (D-lactic acid) (PDLA). We demonstrate that through these environmentally sustainable materials, highly efficient nanofiber assemblies for filtration can be constructed at very low basis weight. The physical and morphological structure, crystalline structure, hydrophobicity, porous structure, and filtration performance of the fibrous membranes were thoroughly characterized. It was shown that the fabricated polylactic acid (PLA) side-by-side fiber membrane had the advantages of excellent hydrophobicity, small average pore size, high porosity, high filtration efficiency, low pressure drop as well as superior air permeability. At the very low basis weight of 1.1 g/m2, the filtration efficiency and pressure drop of the prepared side-by-side membrane reached 96.2% and 30 Pa, respectively. Overall, this biomass-based, biodegradable filtration material has the potential to replace the fossil fuel-based polypropylene commercial meltblown materials for the design and development in filtration, separation, biomedical, personal protection and other fields.

Is liver involvement overestimated in COVID-19 patients? A meta-analysis.

Background: Considering transaminase more than the upper limit of normal value as liver injury might overestimate the prevalence of liver involvement in COVID-19 patients. No meta-analysis has explored the impact of varied definitions of liver injury on the reported prevalence of liver injury. Moreover, few studies reported the extent of hypertransaminasemia stratified by COVID-19 disease severity. Methods: A literature search was conducted using PubMed and Embase. The pooled prevalence of liver injury and hypertransaminasemia was estimated. Results: In total, 60 studies were included. The overall prevalence of liver injury was 25%. Compared to subgroups with the non-strict definition of liver injury (33%) and subgroups without giving detailed definition (26%), the subgroup with a strict definition had a much lower prevalence of liver injury (9%). The overall prevalence of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) elevation was 19% and 22%. The prevalence of elevated ALT and AST were significantly higher in severe COVID-19 cases compare to non-severe cases (31% vs 16% and 44% vs 11%). In critically ill and fatal cases, no difference was found in the prevalence of elevated ALT (24% vs 30%) or AST (54% vs 49%). Sensitivity analyses indicated that the adjusted prevalence of ALT elevation, AST elevation, and liver injury decreased to 14%, 7%, and 12%. Conclusion: The overall prevalence of liver injury and hypertransaminasemia in COVID-19 patients might be overestimated. Only a small fraction of COVID-19 patients have clinically significant liver injury. The prevalence of hypertransaminasemia was significantly higher in severe COVID-19 cases compare to non-severe cases. Hence, in severe COVID-19 patients, more attention should be paid to liver function tests.

Simultaneous electrochemical detection of levodapa, paracetamol and l-tyrosine based on multi-walled carbon nanotubes.

Herein multi-walled carbon nanotubes (MWCNTs) were processed by ultrasonication and freeze-drying method. The morphology of the processed MWCNTs was examined by scanning electron microscopy. An original electrochemical sensor for the simultaneous detection of levodapa (LD), paracetamol (PA) and l-tyrosine (Tyr) was developed by dropcasting a mixture of processed MWCNTs and Nafion on a glassy carbon electrode. The as-prepared sensor was studied by cyclic voltammetry and differential pulse voltammetry. The peak currents of LD, PA and Tyr significantly increased compared to those obtained at bare glassy carbon electrodes or unprocessed MWCNTs modified electrodes. The peaks of LD, PA and Tyr were well-defined and obviously separated from each other. The linear ranges for detection of LD, PA and Tyr were 2.0-300.0, 2.0-180.0, and 2.0-120.0 µM, with a detection limit of 0.6, 0.5 and 0.8 µM (S/N = 3), respectively. Finally, the sensor was applied to detect LD, PA and Tyr in serum samples, and the results were satisfactory.

Cloning, localization and bioinformatics analysis of a gene encoding an odorant-binding protein (OBP) in Anoplophora glabripennis (Motschulsky).

Anoplophora glabripennis (Motschulsky) has an advanced and complicated olfactory system to identify hosts, mates and spawning locations, and odorant-binding proteins (OBPs) play a key role by binding to volatile materials from different hosts. The full-length cDNA sequence of an OBP, AglaOBP, was cloned by RACE from an antenna cDNA library, and the protein structure and function were predicted by bioinformatics analysis. Gene temporal and spatial expression was detected by real-time qPCR. AglaOBP had distinctive sequence, location and expression profiles compared with other OBPs of A. glabripennis, as it was found in different tissues, and the highest expression was in the elytrums. The possible physiological functions of this OBP were discussed. These findings help elucidate the physiology of this pest and provide a new potential target for pest control.