Assessing an AI-based Smart Imagery Framing and Truthing (SIFT) system to assist radiologists annotating lung abnormalities on chest X-ray images for development of deep learning models

To assess a Smart Imagery Framing and Truthing (SIFT) system in automatically labeling and annotating chest X-ray (CXR) images with multiple diseases as an assist to radiologists on multi-disease CXRs. SIFT system was developed by integrating a convolutional neural network based-augmented MaskR-CNN and a multi-layer perceptron neural network. It is trained with images containing 307,415 ROIs representing 69 different abnormalities and 67,071 normal CXRs. SIFT automatically labels ROIs with a specific type of abnormality, annotates fine-grained boundary, gives confidence score, and recommends other possible types of abnormality. An independent set of 178 CXRs containing 272 ROIs depicting five different abnormalities including pulmonary tuberculosis, pulmonary nodule, pneumonia, COVID-19, and fibrogenesis was used to evaluate radiologists' performance based on three radiologists in a double-blinded study. The radiologist first manually annotated each ROI without SIFT. Two weeks later, the radiologist annotated the same ROIs with SIFT aid to generate final results. Evaluation of consistency, efficiency and accuracy for radiologists with and without SIFT was conducted. After using SIFT, radiologists accept 93% SIFT annotated area, and variation across annotated area reduce by 28.23%. Inter-observer variation improves by 25.27% on averaged IOU. The consensus true positive rate increases by 5.00% (p=0.16), and false positive rate decreases by 27.70% (p<0.001). The radiologist's time to annotate these cases decreases by 42.30%. Performance in labelling abnormalities statistically remains the same. Independent observer study showed that SIFT is a promising step toward improving the consistency and efficiency of annotation, which is important for improving clinical X-ray diagnostic and monitoring efficiency. © 2023 SPIE.

An observer comparison study to evaluate a machine learning model to quantify the infected pneumonia on lung CT images

Quantification of infected lung volume using computed tomography (CT) images can play a critical role in predicting the severity of pulmonary infectious disease. Manual segmentation of infected areas from several CT image slices, however, is not efficient and viable in clinical practice. To assist clinicians in overcoming this challenge, we developed a new method to automatically segment and quantify the percentage of the infected lung volume. First, we used a public dataset of 20 COVID-19 patients, which consists of manually annotated lung and infection masks, to train a new joint deep learning (DL) model for lung and infection segmentation. As for lung segmentation, a Mask-RCNN model was applied to the lung volume with a novel postprocessing technique. Following that, an ensemble model with a customized residual attention UNet model and feature pyramid network (FPN) models was employed for infection segmentation. Next, we assembled another set of 80 CT scans of Covid-19 patients. Two chest radiologists manually evaluated each CT scan and reported the infected lung volume percentage using a customized graphical user interface (GUI). The developed DL-model was also employed to process these CT images. Then, we compared the agreement between the radiologist (manual) and model-based (automated) percentages of diseased regions. Additionally, the GUI was used to let radiologists rate acceptance of the DL-model generated segmentation results. Analyzing the results demonstrate that the agreement between manual and automated segmentation is >95% in 28 testing cases. Furthermore, >53% of testing cases received the top assessment rating scores from two radiologists (between four-five- score). Thus, this study illustrates the feasibility of developing a DL-model based automated tool to effectively provide quantitative evaluation of infected lung regions to assist in improving the efficiency of radiologists in infection diagnosis. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

The strategy on One Health development in China based on SWOT analysis.

The pandemic of Corona Virus Disease 2019 (COVID-19) worldwide has prompted the use One Health concept to solve health problems and improve the public health governance system. Using the Superiority Weakness Opportunity Threats (SWOT) analysis method to analyze the opportunities and challenges brought by the current development of One Health in China. The results show that the current advantage is that the Chinese government attaches great importance to One Health, and Chinese scholars are also actively involved in the development of One Health, but there are still disadvantages of weak foundation and low international influence. At the same time, with the opportunity for more recognition of the concept of One Health in the world, China is facing challenges such as insufficient talent competitiveness and unbalanced development in the development of One Health. In this regard, this paper puts forward the strategies and key research contents for developing One Health in China to provide ideas for promoting the development of One Health in China.Copyright © 2022, National Institute of Parasitic Diseases. All rights reserved.

dbSCI: A manually curated database of SARS-CoV-2 inhibitors forCOVID-19 br

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen of the ongoing coronavirusdisease 2019 (COVID-19) global pandemic. Here, by centralizing published cell-based experiments, clinical trials, andvirtual drug screening data from the NCBI PubMed database, we developed a database of SARS-CoV-2 inhibitors forCOVID-19, dbSCI, which includes 234 SARS-CoV-2 inhibitors collected from publications based on cell-basedexperiments, 81 drugs of COVID-19 in clinical trials and 1305 potential SARS-CoV-2 inhibitors from bioinformaticsanalyses. dbSCI provides four major functions: (1) search the drug target or its inhibitor for SARS-CoV-2, (2) browsetarget/inhibitor information collected from cell experiments, clinical trials, and virtual drug screenings, (3) download,and (4) submit data. Each entry in dbSCI contains 18 types of information, including inhibitor/drug name, targetingprotein, mechanism of inhibition, experimental technique, experimental sample type, and reference information. Insummary, dbSCI provides a relatively comprehensive, credible repository for inhibitors/drugs against SARS-CoV-2and their potential targeting mechanisms and it will be valuable for further studies to control COVID-19

Characteristics and risk factors for persistent breathlessness after hospitalisation for COVID-19

Background: Persisting breathlessness after COVID-19 infection is common and debilitating. We aimed to characterise and identify risk factors for patients with persistent breathlessness following COVID-19 hospitalisation. Method(s): PHOSP-COVID is a multi-centre prospective cohort study of UK adults hospitalised for COVID-19. Clinical data were collected during hospitalisation and at a research visit. Breathlessness was measured by a numeric rating scale of 0-10. We defined post-COVID breathlessness as an increase in score of 1 or more compared to the preCOVID-19 level. Multivariable logistic regression was used to identify risk factors. Result(s): We included 1,226 participants (37% female, median age 59 years, 22% mechanically ventilated). At a median five months after discharge, 50% reported post-COVID breathlessness. Risk factors for post-COVID breathlessness were socio-economic deprivation (adjusted odds ratio, 1.67;95% confidence interval, 1.14-2.44), pre-existing depression/anxiety (1.58;1.06-2.35), female sex (1.56;1.21-2.00) and admission duration (1.01;1.00- 1.02). Black ethnicity (0.56;0.35-0.89) and older age groups (0.31;0.14-0.66) were less likely to report post-COVID breathlessness. Post-COVID breathlessness was associated with worse performance on the shuttle walk test and forced vital capacity, but not with obstructive airflow limitation. Conclusion(s): Half of this national cohort of patients hospitalised for COVID-19 experienced persistent breathlessness at follow up. The risk factors identified for post-COVID breathlessness should inform mechanistic work to understand causal processes and develop future interventions to improve outcomes in this growing population.

[Analysis on the scrap situation of COVID-19 vaccine in Suzhou city].

To analyze the usage and loss of the COVID-19 vaccine in ten districts of Suzhou city from December 18, 2020 to April 30, 2021.The results showed the loss rate was 0.222‰ in Suzhou city. The loss rate of pre-filled packaging COVID-19 vaccine was higher than that of vial packaging. The loss rate of 40 packaging was the lowest in vial packaging. The loss rate of all kinds of COVID-19 vaccine in stable inoculation unit was the lowest. It is recommended to distribute 40 vial packaging COVID-19 vaccine for centralized vaccination to reduce the loss of COVID-19 vaccine.

B Cells Induce Hypertension, AT1AA, And Complement Activation In Preeclampsia Or In Response To A Prior Covid-19 Infection During Pregnancy

Preeclampsia (PE), new onset hypertension (HTN) during pregnancy, is associated with placental ischemia and chronic inflammation that includes increased CD4+ T cells, B cells secreting agonistic autoantibodies against the angiotensin II type 1 receptor (AT1AA), and activation of the complement system. Previous studies have shown AT1-AA is produced in patients with COVID-19 infection. Interestingly, having had COVID-19 during pregnancy is associated with increased incidence of developing a PE phenotype during pregnancy. We have previously shown an important role for B cell depletion or AT1AA inhibition to attenuate HTN in rat models of PE. Collectively, this data suggests B cells contribute to PE development and that B cells may increase incidence of PE in patients with a history (Hx) of COVID-19 during pregnancy through production of the AT1AA. We hypothesize B cells from PE or CV Hx PE patients produce AT1AA resulting in HTN and complement activation in pregnancy. Placental B cells were isolated from normal pregnant (NP), PE, normotensive (NT) CV Hx, or PE CV Hx patients at delivery. B cells were transferred i.p. into pregnant athymic rats at gestation (GD) 12. On GD18, carotid catheters were inserted. On GD19, blood pressure was measured and tissues collected. PE B cell recipients had increased Mean Arterial Pressure (MAP) (115+/-3 mmHg n=6) compared to NP B cell recipients (97+/-4 mmHg n=6 p<0.05). PE B cell recipients had increased AT1AA (20+/-2 DELTABPM n=4) compared to NP B cell recipients (6+/-1 DELTABPM n=4 p<0.05). PE B cell recipients had increased markers of complement activation such as reduced plasma C4 (1302+/-169 mug/mL n=4) and C3 (516+/-45 mug/mL n=4) compared to recipients of NP B cells (2348+/-338 mug/mL n=4 p<0.05) and (790+/-66 mug/mL n=4 p<0.05) respectively. CV Hx PE B cell recipients had elevated MAP (108+/-3 mmHg n=4) compared to CV Hx NT B cell recipients (101+/-7 mmHg n=4) and increased AT1AA (24+/-3 DELTABPM n=3) compared to CV Hx NT B cell Recipients (4+/-1 DELTABPM n=4 p<0.05). Collectively, this study demonstrates an important role for B cells to cause HTN during pregnancy;and indicates that B cells contribute to a higher incidence of PE in women with a Hx of CV infection during pregnancy possibly by secreting AT1-AA.

The strategy on One Health development in China based on SWOT analysis

The pandemic of Corona Virus Disease 2019 (COVID-19) worldwide has prompted the use One Health concept to solve health problems and improve the public health governance system. Using the Superiority Weakness Opportunity Threats (SWOT) analysis method to analyze the opportunities and challenges brought by the current development of One Health in China. The results show that the current advantage is that the Chinese government attaches great importance to One Health, and Chinese scholars are also actively involved in the development of One Health, but there are still disadvantages of weak foundation and low international influence. At the same time, with the opportunity for more recognition of the concept of One Health in the world, China is facing challenges such as insufficient talent competitiveness and unbalanced development in the development of One Health. In this regard, this paper puts forward the strategies and key research contents for developing One Health in China to provide ideas for promoting the development of One Health in China. © 2022, National Institute of Parasitic Diseases. All rights reserved.

CLINICAL FEATURES AND CHARACTERISTIC OF CHOLANGIOPATHY AFTER SEVERE COVID-19

Introduction Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2), can commonly lead to abnormal liver tests, mostly transaminase elevation. Recently, a novel entity of cholangiopathy was discovered in patients who recovered from critical COVID-19 infection. However, understanding of this disease is limited due to its rarity. Methods We reviewed Pubmed, Embase, and Web of Science Core Collection databases from inception to Nov 30th, 2021, to identify studies reporting cholangiopathy after severe COVID-19 infection. “SARS-CoV-2” or “COVID-19” with “cholangiopathy” were used as keywords to search. Our study is to summarize the clinical features and characteristics of cholangiopathy after severe COVID-19 illness. Results Literature review identified 15 articles including 33 patients for reviews. Most studies were performed in the United States. The mean age of participants from all studies is 52.17 ± 13.98 years old. Among the 33 included patients, the majority are male (29, 88%) and the common medical histories include hypertension (n=11), obesity (n=8), and diabetes mellitus (n=8). The length of stay (LOS) during hospitalization was prolonged with a mean of 80.23 ± 33.14 days. All patients were intubated and put on mechanical ventilation during medical intensive care stay with 12 patients having a history of endotracheal cardiac output monitoring. The mean peak of serum alkaline phosphatase, aspartate aminotransferase, alanine transaminase and total bilirubin were 2106.96 (U/l) ± 784.04, 1456.09 (U/l) ± 2325.10, 983.57 (U/l) ± 1244.44 and 14.04 (mg/dl) ± 8.41, respectively. Cholangiopathy after severe COVID illness mimics secondary sclerosing cholangitis on magnetic resonance cholangiopancreatography and endoscopic retrograde cholangiopancreatography studies with ductal beading but the presence of unique severe cholangiocyte injury and intrahepatic microangiopathy is suggestive of direct hepatic injury due to COVID-19. In terms of outcome, 7 patients were documented as deceased. Eight patients underwent liver transplantation (Table 1). Discussion Cholangiopathy is a late complication of severe COVID-19 after prolonged ICU stay with potential for long-term liver morbidity and liver failure needing liver transplantation. Further studies are warranted to understand pathogenesis, natural history, therapeutic interventions, and prognostic indicators. (Table Presented)

An Integrated Strategy Designed to Explore the Common and Diverging Mechanisms of Potential Drugs against the Novel Coronavirus Pneumonia Based on Network Pharmacology and in Silico Molecular Docking Technology

Drug repositioning may be a promising way to find potential therapies against coronavirus disease 2019. Although chloroquine and hydroxychloroquine showed controversial results against the coronavirus disease 2019 disease, the potential common and diverging mechanisms of action are not reported and need to be dissected for better understanding them. An integrated strategy was proposed to systematically decipher the common and diverging aspects of mechanism of chloroquine and hydroxychloroquine against coronavirus disease 2019-disease network based on network pharmacology and in silico molecular docking. Potential targets of the two drugs and coronavirus disease 2019 related genes were collected from online public databases. Target function enrichment analysis, tissue enrichment maps and molecular docking analysis were carried out to facilitate the systematic understanding of common and diverging mechanisms of the two drugs. Our results showed that 51 chloroquine targets and 47 hydroxychloroquine targets were associated with coronavirus disease 2019. The core targets include tumor necrosis factor, glyceraldehyde 3-phosphate dehydrogenase, lymphocyte-specific protein-tyrosine kinase, beta-2 microglobulin, nuclear receptor coactivator 1, peroxisome proliferator-activated receptor gamma and glutathione disulfide reductase. Both chloroquine and hydroxychloroquine had good binding affinity towards tumor necrosis factor (affinity=-8.6 and -8.4 kcal/mol, respectively) and glyceraldehyde 3-phosphate dehydrogenase (-7.5 and -7.5 kcal/mol). Chloroquine and hydroxychloroquine both had good affinity with angiotensin-converting enzyme 2, 3-chymotrypsin-like protease and transmembrane serine protease 2. However, hydroxychloroquine manifested better binding affinity with the three proteins comparing with that of chloroquine. Chloroquine and hydroxychloroquine could have potential to inhibit over-activated immunity and inflammation. The potential tissue-specific regulation of the two drugs against severe acute respiratory syndrome coronavirus 2 infection may related with the lung, liver, brain, placenta, kidney, blood, eye, etc. In conclusion, our data systematically demonstrated chloroquine and hydroxychloroquine may have potential regulatory effects on coronavirus disease 2019 disease network, which may affect multiple organs, protein targets and pathways. Routine measurements of the chloroquine and hydroxychloroquine blood concentrations and tailored therapy regimen may be essential. But, further rigorous and high quality randomized controlled clinical trials are warranted to validate the antiviral effects of chloroquine and hydroxychloroquine against severe acute respiratory syndrome coronavirus 2. Our proposed strategy could facilitate the drug repurposing efforts for coronavirus disease 2019 treatment.

Global patterns of daily CO2 emissions reductions in the first year of COVID-19

Observed daily changes in CO2 emissions from across the globe reveal the sectors and countries where pandemic-related emissions declines were most pronounced in 2020. Day-to-day changes in CO2 emissions from human activities, in particular fossil-fuel combustion and cement production, reflect a complex balance of influences from seasonality, working days, weather and, most recently, the COVID-19 pandemic. Here, we provide a daily CO2 emissions dataset for the whole year of 2020, calculated from inventory and near-real-time activity data. We find a global reduction of 6.3% (2,232 MtCO(2)) in CO2 emissions compared with 2019. The drop in daily emissions during the first part of the year resulted from reduced global economic activity due to the pandemic lockdowns, including a large decrease in emissions from the transportation sector. However, daily CO2 emissions gradually recovered towards 2019 levels from late April with the partial reopening of economic activity. Subsequent waves of lockdowns in late 2020 continued to cause smaller CO2 reductions, primarily in western countries. The extraordinary fall in emissions during 2020 is similar in magnitude to the sustained annual emissions reductions necessary to limit global warming at 1.5 degrees C. This underscores the magnitude and speed at which the energy transition needs to advance.

MXT: A New Variant of Pyramid Vision Transformer for Multi-label Chest X-ray Image Classification

Nowadays, the global COVID-19 situation is still serious, and the new mutant virus Delta has already spread all over the world. The chest X-ray is one of the most common radiological examinations for screening catheters and diagnosis of many lung diseases, which plays an important role in assisting clinical diagnosis during the outbreak. This study considers the problem of multi-label catheters and thorax disease classification on chest X-ray images based on computer vision. Therefore, we propose a new variant of pyramid vision Transformer for multi-label chest X-ray image classification, named MXT, which can capture both short and long-range visual information through self-attention. Especially, downsampling spatial reduction attention can reduce the resource consumption of using Transformer. Meanwhile, multi-layer overlap patch (MLOP) embedding is used to tokenize images and dynamic position feed forward with zero paddings can encode position instead of adding a positional mask. Furthermore, class token Transformer block and multi-label attention (MLA) are utilized to offer more effective processing of multi-label classification. We evaluate our MXT on Chest X-ray14 dataset which has 14 disease pathologies and Catheter dataset containing 11 types of catheter placement. Each image is labeled one or more categories. Compared with some state-of-the-art baselines, our MXT can yield the highest mean AUC score of 83.0% on the Chest X-ray14 dataset and 94.6% on the Catheter dataset. According to the ablation study, we can obtain the following results: (1) The proposed MLOP embedding has a better performance than overlap patch (OP) embedding layer and non-overlap patch (N-OP) embedding layer that the mean AUC score is improved 0.6% and 0.4%, respectively. (2) Our demonstrate dynamic position feed forward can replace the traditional position mask which can learn the position information, and the mean AUC increased by 0.6%. (3) The mean AUC score by the designed MLA is more 0.2% and 0.6% than using the class token and calculating the mean scores of all tokens. The comprehensive experiments on two datasets demonstrate the effectiveness of the proposed method for multi-label chest X-ray image classification. Hence, our MXT can assist radiologists in diagnoses of lung diseases and check the placement of catheters, which can reduce the work pressure of medical staff.

Complete genome sequencing and traceability analysis of SARS-CoV-2 in Binhai New Area, Tianjin

Objective: To analyze the whole genome traceability and variation analysis of SARS-CoV-2 in local COVID-19 outbreaks in Binhai New Area, Tianjin. Methods: The whole-genome high-throughput sequencing was performed on throat swab samples collected from one local asymptomatic infected person and five confirmed cases of COVID-19 in Binhai New Area of Tianjin from November 7 to December 5, 2020. The sequencing data were assembled by De novo. MAFFT v7.0 multiple sequence alignment program and MEGA X software were used to compare the above data and construct phylogenetic tree (Neighbor-joining method). Results: The genetic similarity between the sequences of 6 SARS-CoV-2 strains and Wuhan reference sequence (Wuhan-Hu-1) was greater than 99.9%. Two of six strains were genetically identical, conform to the L-Lineage European Branch Ⅱ.1(America Branch)/B.1;The other four strains had the same genes and were in line with the characteristics of L-Lineage European Branch Ⅰ/B.1.1.These six strains belonged to different evolutionary branches and two different transmission chains. There were 18 nucleotide mutation sites in sequences of six SARS-CoV-2 strains, eight of which were synonymous mutation sites, nine of which were missense mutation sites, resulting in nine amino acid mutation sites, and important mutation sites of RDRP-P323L and S-D614G were found in all of the six samples. Conclusions: In this study, there were two COVID-19 outbreaks in Binhai New Area of Tianjin, and the sequences of six SARS-CoV-2 strains belonged to different evolutionary branches and two different transmission chains. It might come from porters' contact with imported cold chain items contaminated with SARS-CoV-2 from different sources. All the sequences of six SARS-CoV-2 strains had P323L and D614G mutations, which indicated that the virus mutation and transmission ability were stronger. The surveillance of important employees of the cold chain in Tianjin and local and imported cases should be continuously strengthened. Copyright © 2021 by the Chinese Medical Association.

Do public awareness and behaviors in rural domestic waste classification help reduce covid-19? A case study in China

Rural domestic waste classification (RDWC) is one of the main strategies for waste management, which plays a significant role in the circular economy and sustainable management. As one of the first pilot cities of waste classification in China, Hangzhou took the lead in promoting the classification and recycling of rural domestic waste. Based on the probability sampling procedure, this study focuses on the influencing factors of residents’ awareness and behaviors toward RDWC in Hangzhou rural areas. The results of the questionnaire survey show that the perception of the importance of RDWC is weak in rural areas of China. Moreover, regression analyses show that the public’s RDWC awareness is positively influenced by the cleanliness of waste rooms, age, and educational level. And their RDWC behaviors are negatively influenced by human supervision but positively influenced by the attitude to waste classification, satisfaction with the situation of RDWC and environment. Besides, exploring the relationship between the number of COVID-19 cases and the waste classification performance shows cities with better waste classification performance have fewer confirmed cases. These results imply that the proper waste classification methods and supporting infrastructure facilities could be fitted to other rural areas. © 2021, HARD Publishing Company. All rights reserved.

Magnetron traps therapeutics for localized bacterial capture and overcome ulcer infection

In addition to the pandemic caused by the coronavirus disease 2019, many pathogenic bacteria have also been posing a devastating threat to human health. The overuse of antibiotics leads to the emergence of ‘superbugs’;therefore, it is urgent to develop effective strategies to fight bacteria. Herein, a superparamagnetic nickel (Ni) colloidal nanocrystal clusters (SNCNCs) that can kill and capture bacteria without any camouflage is reported. It binds to amino groups on the surface of bacteria, imparts magnetism to them, and orients them in response to magnetic fields. SNCNCs kill and capture bacteria to avoid inflammation, infection, and organ damage caused by lipopolysaccharide and exotoxin released by bacterial rupture in the remaining bacterial remains in comparison with other antibacterial agents. In this study, in the treatment of traumatic oral ulcers, we found that SNCNCs could kill and capture and remove bacteria from the ulcers to reduce inflammation at the site of the wound. Furthermore, the fibrin gel sprayed on the ulcer was used as a substrate, and the bacteria captured by the SNCNCs moved to the surface of the fibrin gel after a magnetic field was applied. Therefore, the bacteria in the ulcer could be removed with the SNCNCs and fibrin gel magnet, alleviating inflammation caused by bacteria and promoting ulcer healing. This magnetically controlled method of directional movement of bacteria may provide an applicative perspective for the therapy of bacterial infections. © 2021 The Author(s)

Potential value of extracellular vesicles/exosomes in diagnosis and treatment of COVID-19

Since the outbreak of the novel coronavirus pneumonia (COVID-19), it is urgently to develop the effective strategies for its clinical test or treatments world widely. Extracellular vesicles (EV)/exosomes could function as effective carriers for intercellular communication. Increasing evidence revealed that mesenchymal stem cell-derived EV/exosomes could be considered as an alternative cell-free therapy against the acute respiratory distress syndrome. Moreover, the EV-related metabolomics, proteomics, relapsing, deep-vein-thrombosis, myocardial-toxicity, liquid-biopsy and bio-therapeutic researches focusing on the COVID-19 will not only extended our knowledge for the diagnosis, but also provide novel ideas for treatment of this fatal disease. This article will systemically review the progresses of EV/exosomes in the diagnosis and treatment of COVID-19.