Self-paced Multi-view Learning for CT-based severity assessment of COVID-19.

Prior studies for the task of severity assessment of COVID-19 (SA-COVID) usually suffer from domain-specific cognitive deficits. They mainly focus on visual cues based on single cognitive functions but fail to reconcile the valuable information from other alternative views. Inspired by the cognitive process of radiologists, this paper shifts naturally from single-symptom measurements to a multi-view analysis, and proposes a novel Self-paced Multi-view Learning (SPML) framework for automated SA-COVID. Specifically, the proposed SPML framework first comprehensively aggregates multi-view contexts in lung infection with different measure paradigms, i.e., Global Feature Branch, Texture Feature Branch, and Volume Feature Branch. In this way, multiple-perspective clues are taken into account to reflect the most essential pathological manifestation on CT images. To alleviate small-sample learning problems, we also introduce an optimization with self-paced learning strategy to cognitively increase the characterization capabilities of training samples by learning from simple to complex. In contrast to traditional batch-wise learning, a pure self-paced way can further guarantee the efficiency and accuracy of SPML when dealing with small and biased samples. Furthermore, we construct a well-established SA-COVID dataset that contains 300 CT images with fine annotations. Extensive experiments on this dataset demonstrate that SPML consistently outperforms the state-of-the-art baselines. The SA-COVID dataset is publicly released at https://github.com/YishuLiu/SA-COVID.

Effect of Salt Substitution on Cardiovascular Events and Death.

BACKGROUND: Salt substitutes with reduced sodium levels and increased potassium levels have been shown to lower blood pressure, but their effects on cardiovascular and safety outcomes are uncertain. METHODS: We conducted an open-label, cluster-randomized trial involving persons from 600 villages in rural China. The participants had a history of stroke or were 60 years of age or older and had high blood pressure. The villages were randomly assigned in a 1:1 ratio to the intervention group, in which the participants used a salt substitute (75% sodium chloride and 25% potassium chloride by mass), or to the control group, in which the participants continued to use regular salt (100% sodium chloride). The primary outcome was stroke, the secondary outcomes were major adverse cardiovascular events and death from any cause, and the safety outcome was clinical hyperkalemia. RESULTS: A total of 20,995 persons were enrolled in the trial. The mean age of the participants was 65.4 years, and 49.5% were female, 72.6% had a history of stroke, and 88.4% a history of hypertension. The mean duration of follow-up was 4.74 years. The rate of stroke was lower with the salt substitute than with regular salt (29.14 events vs. 33.65 events per 1000 person-years; rate ratio, 0.86; 95% confidence interval [CI], 0.77 to 0.96; P = 0.006), as were the rates of major cardiovascular events (49.09 events vs. 56.29 events per 1000 person-years; rate ratio, 0.87; 95% CI, 0.80 to 0.94; P<0.001) and death (39.28 events vs. 44.61 events per 1000 person-years; rate ratio, 0.88; 95% CI, 0.82 to 0.95; P<0.001). The rate of serious adverse events attributed to hyperkalemia was not significantly higher with the salt substitute than with regular salt (3.35 events vs. 3.30 events per 1000 person-years; rate ratio, 1.04; 95% CI, 0.80 to 1.37; P = 0.76). CONCLUSIONS: Among persons who had a history of stroke or were 60 years of age or older and had high blood pressure, the rates of stroke, major cardiovascular events, and death from any cause were lower with the salt substitute than with regular salt. (Funded by the National Health and Medical Research Council of Australia; SSaSS ClinicalTrials.gov number, NCT02092090.).

A New Technique for Diagnosis of Dental Caries on the Children's First Permanent Molar

The current researches have been shown high prevalence and incidence of children's teeth caries, especially for the first permanent molar, which might do a lot of harm to their general health. Fortunately, early detection and protection can reduce the difficulty of treatment and protect children's oral health. However, traditional diagnostic methods such as dentist's visual inspection and radiographic imaging diagnosis are non-automatic and time-consuming. Given the COVID-19 epidemic, these methods should not be taken into consideration, since they fail to practice social distancing and further increase the risk of infection. To address these issues, in this paper we propose a novel caries detection and assessment (UCDA) framework to achieve a new technique for fully-automated diagnosis of dental caries on the children's first permanent molar. Inspired by an efficient in-network feature pyramid and anchor boxes, the proposed UCDA framework mainly contains a backbone network that is initialized with ResNet-FPN, and two parallel task-specific subnetworks for region regression and region classification. Due to the lack of the image database, we also present a novel children's oral image database, namely "Child-OID", which comprises 1, 368 primary school children's oral images with standard diagnostic annotations and labels, to evaluate the effectiveness of our UCDA method. Experiments on the Child-OID database demonstrate that commonly occurring caries on the first permanent molar can be more accurately detected via the proposed UCDA framework. Database and code are available at https://github.com/GipinLinn/UCDA-and-Child-OID.git.

Single Cell RNA-seq Data Analysis Reveals the Potential Risk of SARS-CoV-2 Infection Among Different Respiratory System Conditions.

COVID-19 (Coronavirus Disease 2019) has been an ongoing pandemic, resulting in an increase in people being infected globally. Understanding the potential risk of infection for people under different respiratory system conditions is important and will help prevent disease spreading. We explored and collected five published and one unpublished single-cell respiratory system tissue transcriptome datasets, including idiopathic pulmonary fibrosis (IPF), aging lungs (mouse origin data), lung cancers, and smoked branchial epithelium, for specifically reanalyzing the ACE2 and TMPRSS2 expression profiles. Compared to normal people, we found that smoking and lung cancer increase the risk for COVID-19 infection due to a higher expression of ACE2 and TMPRSS2 in lung cells. Aged lung does not show increased risk for infection. IPF patients may have a lower risk for original COVID-19 infection due to lower expression in AT2 cells but may have a higher risk for severity due to a broader expression spectrum of TMPRSS2. Further investigation and validation on these cell types are required. Nonetheless, this is the first report to predict the risk and potential severity for COVID-19 infection for people with different respiratory system conditions. Our analysis is the first systematic description and analysis to illustrate how the underlying respiratory system conditions contribute to a higher infection risk.