A Predictive Nomogram for Predicting Improved Clinical Outcome Probability in Patients with COVID-19 in Zhejiang Province, China.

The aim of this research was to develop a quantitative method for clinicians to predict the probability of improved prognosis in patients with coronavirus disease 2019 (COVID-19). Data on 104 patients admitted to hospital with laboratory-confirmed COVID-19 infection from 10 January 2020 to 26 February 2020 were collected. Clinical information and laboratory findings were collected and compared between the outcomes of improved patients and non-improved patients. The least absolute shrinkage and selection operator (LASSO) logistics regression model and two-way stepwise strategy in the multivariate logistics regression model were used to select prognostic factors for predicting clinical outcomes in COVID-19 patients. The concordance index (C-index) was used to assess the discrimination of the model, and internal validation was performed through bootstrap resampling. A novel predictive nomogram was constructed by incorporating these features. Of the 104 patients included in the study (median age 55 years), 75 (72.1%) had improved short-term outcomes, while 29 (27.9%) showed no signs of improvement. There were numerous differences in clinical characteristics and laboratory findings between patients with improved outcomes and patients without improved outcomes. After a multi-step screening process, prognostic factors were selected and incorporated into the nomogram construction, including immunoglobulin A (IgA), C-reactive protein (CRP), creatine kinase (CK), acute physiology and chronic health evaluation II (APACHE II), and interaction between CK and APACHE II. The C-index of our model was 0.962 (95% confidence interval (CI), 0.931-0.993) and still reached a high value of 0.948 through bootstrapping validation. A predictive nomogram we further established showed close performance compared with the ideal model on the calibration plot and was clinically practical according to the decision curve and clinical impact curve. The nomogram we constructed is useful for clinicians to predict improved clinical outcome probability for each COVID-19 patient, which may facilitate personalized counselling and treatment.

HLA-Bw4 in association with KIR3DL1 favors natural killer cell-mediated protection against severe COVID-19.

Replicating SARS-CoV-2 has been shown to degrade HLA class I on target cells to evade the cytotoxic T-cell (CTL) response. HLA-I downregulation can be sensed by NK cells to unleash killer cell immunoglobulin-like receptor (KIR)-mediated self-inhibition by the cognate HLA-I ligands. Here, we investigated the impact of HLA and KIR genotypes and HLA-KIR combinations on COVID-19 outcome. We found that the peptide affinities of HLA alleles were not correlated with COVID-19 severity. The predicted poor binders for SARS-CoV-2 peptides belong to HLA-B subtypes that encode KIR ligands, including Bw4 and C1 (introduced by B*46:01), which have a small F pocket and cannot accommodate SARS-CoV-2 CTL epitopes. However, HLA-Bw4 weak binders were beneficial for COVID-19 outcome, and individuals lacking the HLA-Bw4 motif were at higher risk for serious illness from COVID-19. The presence of the HLA-Bw4 and KIR3DL1 combination had a 58.8% lower risk of developing severe COVID-19 (OR = 0.412, 95% CI = 0.187-0.904, p = 0.02). This suggests that HLA-Bw4 alleles that impair their ability to load SARS-CoV-2 peptides will become targets for NK-mediated destruction. Thus, we proposed that the synergistic responsiveness of CTLs and NK cells can efficiently control SARS-CoV-2 infection and replication, and NK-cell-mediated anti-SARS-CoV-2 immune responses being mostly involved in severe infection when the level of ORF8 is high enough to degrade HLA-I. The HLA-Bw4/KIR3DL1 genotype may be particularly important for East Asians undergoing COVID-19 who are enriched in HLA-Bw4-inhibitory KIR interactions and carry a high frequency of HLA-Bw4 alleles that bind poorly to coronavirus peptides.

Intelligent Privacy Protection of End User in Long Distance Education

Long distance education is an important part during the COVID-19 age. An intelligent privacy protection with higher effect for the end users is an urgent problem in long distance education. In view of the risk of privacy disclosure of location, social network and trajectory of end users in the education system, this paper deletes the location information in the location set to protect the privacy of end user by providing the anonymous set to location. Firstly, this paper divides the privacy level of social networks by weighted sensitivity, and collects the anonymous set in social networks according to the level;Secondly, after the best anonymous set is generated by taking the data utility loss function as the standard, it was split to get an anonymous graph to hide the social network information;Finally, the trajectory anonymous set is constructed to hide the user trajectory with the l-difference privacy protection algorithm. Experiments show that the algorithm presented in this paper is superior to other algorithms no matter how many anonymous numbers there are, and the gap between relative anonymity levels is as large as 5.1 and 6.7. In addition, when the privacy protection intensity is 8, the trajectory loss rate presented in this paper tends to be stable, ranging from 0.005 to 0.007, all of which are less than 0.01. Meanwhile, its clustering effect is good. Therefore, the proportion of insecure anonymous sets in the algorithm in this paper is small, the trajectory privacy protection effect is good, and the location, social network and trajectory privacy of distance education end users are effectively protected.

Pregnant women's psychological state and influence factors: anxiety, and depression during COVID-19 outbreak.

OBJECTIVES: The outbreak of COVID-19 affects both physical and mental health of pregnant women. This study focuses on their psychological status, and analyzes the main factors affecting their emotions of pregnant women so as to provide guidance for psychological counseling and social intervention during epidemics. METHODS: Multiple researchers distributed a questionnaire online via the Internet. Pregnant women volunteered, and the questionnaire was automatically collected in the background. RESULTS: The 298 valid questionnaires recovered showed that 82 cases of pregnant women were in states of anxiety, accounting for 27.51%, of which 78.05% were mild (82 cases), 19.51% were moderate (16 cases), and 2.44% were severe (2 cases). Moreover, 31.21% of pregnant women were in states of depression (93 cases), of which 52.69% were mild (49 cases), 40.86% were moderate (38 cases), and 6.45% were severe (6 cases). The risk factors for states of anxiety or depression were fear of fetal malformation or genetic disease, history of adverse pregnancy, can't do routine prenatal examination, and insufficient support and care from husbands and families. Besides, 16 cases had sought psychological help during the epidemic, among whom 62.50% (10 cases) experienced anxiety, 68.75% (11 cases) had depression. CONCLUSIONS: During the outbreak of COVID-19, obstetricians may take use of the Internet, based on the advantages in epidemic prevention, controlling health education, and popularizing science. In addition, husbands and family members should provide greater care for pregnant women, to protect their mental health during public health incidents.

Clinical Characteristics and Factors Associated With Long-Term Viral Excretion in Patients With Severe Acute Respiratory Syndrome Coronavirus 2 Infection: a Single-Center 28-Day Study.

BACKGROUND: Despite the ongoing spread of coronavirus disease 2019 (COVID-19), knowledge about factors affecting prolonged viral excretion is limited. METHODS: In this study, we retrospectively collected data from 99 hospitalized patients with coronavirus disease 2019 (COVID-19) between 19 January and 17 February 2020 in Zhejiang Province, China. We classified them into 2 groups based on whether the virus test results eventually became negative. Cox proportional hazards regression was used to evaluate factors associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shedding. RESULTS: Among 99 patients, 61 patients had SARS-CoV-2 clearance (virus-negative group), but 38 patients had sustained positive results (virus-positive group). The median duration of SARS-CoV-2 excretion was 15 (interquartile range, 12-19) days among the virus-negative patients. The shedding time was significantly increased if the fecal SARS-CoV-2 RNA test result was positive. Male sex (hazard ratio [HR], 0.58 [95% confidence interval {CI}, .35-.98]), immunoglobulin use (HR, 0.42 [95% CI, .24-.76]), APACHE II score (HR, 0.89 [95% CI, .84-.96]), and lymphocyte count (HR, 1.81 [95% CI, 1.05-3.1]) were independent factors associated with a prolonged duration of SARS-CoV-2 shedding. Antiviral therapy and corticosteroid treatment were not independent factors. CONCLUSIONS: SARS-CoV-2 RNA clearance time was associated with sex, disease severity, and lymphocyte function. The current antiviral protocol and low-to-moderate dosage of corticosteroid had little effect on the duration of viral excretion.