Deep spatial proteomic exploration of severe COVID-19-related pulmonary injury in post-mortem specimens (preprint)

The lung, as a primary target of SARS-CoV-2, exhibits heterogeneous microenvironment accompanied by various histopathological changes following virus infection. However, comprehensive insight into the protein basis of COVID-19-related pulmonary injury with spatial resolution is currently deficient. Here, we generated a region-resolved quantitative proteomic atlas of seven major pathological structures within the lungs of COVID-19 victims by integrating histological examination, laser microdissection, and ultrasensitive proteomic technologies. Over 10,000 proteins were quantified across 71 dissected FFPE post-mortem specimens. By comparison with control samples, we identified a spectrum of COVID-19-induced protein and pathway dysregulations in alveolar epithelium, bronchial epithelium, and pulmonary blood vessels, providing evidence for the proliferation of transitional-state pneumocytes. Additionally, we profiled the region-specific proteomes of hallmark COVID-19 pulmonary injuries, including bronchiole mucus plug, pulmonary fibrosis, airspace inflammation, and hyperplastic alveolar type 2 cells. Bioinformatic analysis revealed the enrichment of cell-type and functional markers in these regions (e.g. enriched TGFBI in fibrotic region). Furthermore, we identified the up-regulation of proteins associated with viral entry, host restriction, and inflammatory response in COVID-19 lungs, such as FURIN and HGF. Collectively, this study provides spatial proteomic insights for understanding COVID-19-caused pulmonary injury, and may serve as a valuable reference for improving therapeutic intervention for severe pneumonia.

Migrasomes deliver messages from migrating cells (preprint)

Migrasomes are newly discovered extracellular vesicles that can mediate communication between cells. These unique vesicles form exclusively at the rear of migrating cells with the help of a protein called TSPAN4. After they’re left behind, the migrasomes and their contents can be captured by nearby cells and affect the recipient cells’ behavior. They can also serve as “breadcrumb trails” that mark the paths of their migrating parent cells. Migrasomes participate in both health and disease. For example, they can dispose of damaged mitochondria to maintain healthy cells and they help establish left–right patterning in zebrafish embryos by releasing the protein CXCL12 to recruit dorsal forerunner cells (DFCs). However, migrasomes can also deliver molecules that promote tumor growth and metastasis and migrasomes released from platelets promote blood clotting after SARS-CoV-2 infection. Furthermore, migrasomes can facilitate an eye condition called proliferative vitreoretinopathy that leads to retinal detachment and blindness. Better characterization of the contents and roles of migrasomes will help us understand these newly identified vesicles and reveal how they can be leveraged to diagnose and treat diseases.

Quantifying the impacts of COVID-19 on Sustainable Development Goals using machine learning models

The COVID-19 pandemic has posed severe threats to global sustainable development. However, a comprehensive quantitative assessment of the impacts of COVID-19 on Sustainable Development Goals (SDGs) is still lacking. This research quantified the post-COVID-19 SDG progress from 2020 to 2024 using projected GDP growth and population and machine learning models including support vector machine, random forest, and extreme gradient boosting. The results show that the overall SDG performance declined by 7.7% in 2020 at the global scale, with 12 socioeconomic SDG performance decreasing by 3.0-22.3% and 4 environmental SDG performance increasing by 1.6-9.2%. By 2024, the progress of 12 SDGs will lag behind for one to eight years compared to their pre-COVID-19 trajectories, while extra time will be gained for 4 environment-related SDGs. Furthermore, the pandemic will cause more impacts on countries in emerging markets and developing economies than those on advanced economies, and the latter will recover more quickly to be closer to their pre-COVID-19 trajectories by 2024. Post-COVID-19 economic recovery should emphasize in areas that can help decouple economic growth from negative environmental impacts. The results can help government and non-state stakeholders identify critical areas for targeted policy to resume and speed up the progress to achieve SDGs by 2030.

Association of COVID-19 Lockdown With Gestational Diabetes Mellitus

Importance The ongoing pandemic of COVID-19 is still affecting our life, but the effects of lockdown measures on gestational diabetes mellitus (GDM) in pregnant women remain unclear. Aim To investigate the association between COVID-19 lockdown and GDM. Subjects and Methods Medical records of 140844 pregnant women during 2015-2020 were extracted from 5 hospitals in Guangdong Province, China. Pregnant women who underwent the COVID-19 Level I lockdown (1/23 - 2/24/2020) during pregnancy were defined as the exposed group (N=20472) and pregnant women who underwent the same calendar months during 2015-2019 (1/23 - 2/24) were defined as the unexposed group (N=120372). Subgroup analyses were used to explore the potential susceptible exposure window of COVID-19 lockdown on GDM. Cumulative exposure is quantitatively estimated by assigning different weights to response periods with different exposure intensities. A logistic regression model was used to estimate the association between COVID-19 lockdown exposure and GDM. Results The rates of GDM in the exposed and unexposed groups were 15.2% and 12.4%, respectively. The overall analyses showed positive associations (odds ratio, OR=1.22, 95%CI: 1.17, 1.27) between lockdown exposure and GDM risk in all pregnant women. More pronounced associations were found in women who underwent the COVID-19 lockdown in their first four months of pregnancy, and the adjusted OR values ranged from 1.24 (95%CI: 1.10, 1.39) in women with 5-8 gestational weeks (GWs) to 1.35 (95%CI: 1.20, 1.52) with < 5 GWs. In addition, we found a positive exposure-response association of cumulative lockdown exposure with the risk of GDM. Conclusions The COVID-19 lockdown was associated with an increased risk of GDM, and the first four months of pregnancy may be the window for sensitive exposure.

Looking at MOOC discussion data to uncover the relationship between discussion pacings, learners’ cognitive presence and learning achievements

The MOOCs (Massive Open Online Courses) forum carries rich discussion data that contains multi-level cognition-related behavior patterns, which brings the potential for an in-depth investigation into the development trend of the group and individual cognitive presence in discourse interaction. This paper describes a study conducted in the context of an introductory astronomy course on the Chinese MOOCs platform, examining the relationship between discussion pacings (i.e., instructor-paced or learner-paced discussion), cognitive presence, and learning achievements. Using content analysis, lag sequential analysis, logistic regression, and grouped regression approaches, the study analysed the online discussion data collected from the Astronomy Talk course involving 2603 participants who contributed 24,018 posts. The findings of the study demonstrated the significant cognitive sequential patterns, and revealed the significant differences in the distribution of cognitive presence with different discussion pacings and learning achievement groups, respectively. Moreover, we found that the high-achieving learners were mostly in the exploration, integration, and resolution phase, and learner-paced discussion had a greater moderating effect on the relationship between cognitive presence and learning achievements. Based on the findings and discussion, suggestions for improving the learners’ cognitive presence and learning achievements in the MOOC environment are discussed.

Urban spatial epidemic simulation model: A case study of the second COVID‐19 outbreak in Beijing, China

The second COVID‐19 outbreak in Beijing was controlled by non‐pharmaceutical interventions, which avoided a second pandemic. Until mass vaccination achieves herd immunity, cities are at risk of similar outbreaks. It is vital to quantify and simulate Beijing's non‐pharmaceutical interventions to find effective intervention policies for the second outbreak. Few models have achieved accurate intra‐city spatio‐temporal epidemic spread simulation, and most modeling studies focused on the initial pandemic. We built a dynamic module of infected case movement within the city, and established an urban spatially epidemic simulation model (USESM), using mobile phone signaling data to create scenarios to assess the impact of interventions. We found that: (1) USESM simulated the transmission process of the epidemic within Beijing;(2) USESM showed the epidemic curve and presented the spatial distribution of epidemic spread on a map;and (3) to balance resources, interventions, and economic development, nucleic acid testing intensity could be increased and restrictions on human mobility in non‐epidemic areas eased.

Assessing Impacts of New Subway Stations on Urban Thefts in the Surrounding Areas

Whether newly implemented public transit stations influence the nearby crime pattern has been debated for years. In ZG City, China, 2 new subway lines and 20 new stations were implemented in 2017. This intervention allows us to test the plausible relationship between new public transit stations and thefts in the surrounding areas. We use the difference-in-differences (DID) model to assess the theft in the treatment and control areas before and after the implementation of the new stations, with necessary socioeconomic and land-use variables and time from the addition of the station being controlled. We also explicitly examine the impacts of the proximity of the stations and the Spring Festival on theft. The results suggest the following: (1) theft around the new subway stations significantly increases after the stations’ implementation, while the control area does not see much change in thefts;(2) proximity between the neighboring stations’ increases thefts;and (3) theft near the new stations significantly decreases during the month of the Spring Festival. This study contributes to the literature on the relationship between the subway system and crime, especially from a Chinese perspective. The finding of the research can bring insights to urban transit planning, allocation of the police force, and crime prevention.

Potential monomer compounds for treatment of corona virus disease 2019 (COVID-19) by transmembrane serine proteinase 2 (TMPRSS2)

Objective: To explore the mechanism of monomeric treatment of corona virus disease 2019 (COVID-19) by using transmembrane serine protease 2 (TMPRSS2) as a receptor.

Health Resource Allocation in Western China from 2014 to 2018 (preprint)

Background: Health equity has persistently been a global concern. As a basic material guarantee to ensure health equity, how to allocate the health resources in a fair and reasonable way has always been one of the research hotspots. The coronavirus 2019 (COVID-19) pandemic has also prompted a rethinking of the topic. Based on the previous research, western China is a relatively backward region, coupled with climate, geography, and other factors, which leading the inconvenient transportation and difficult resource allocation. However, the fairness of health resource allocation in western China has received relatively little attention. Methods: : Lorentz curve, Gini coefficient and Theil index were used to analyse the health resources allocation in the western China. The indexes include number of beds, medical (assistant) practitioners, registered nurses from 2014 to 2018 through population and geography dimensions. Results: : The total health resources shows an increasing trend from 2014 to 2018; The Lorentz curve in the population dimension had a smaller curvature than in the geography dimension. The Gini coefficients for health resources in the population dimension were ranged from 0.057 to 0.129, and in geography dimension the Gini coefficients ranged between 0.605 and 0.647. This shows that the distribution of Health resources is fair basing on population dimension. Furthermore, in two dimensions, the intra-group contribution rate of the Theil index was higher than in the inter-group, and the allocation of practicing (assistant) practitioners and registered nurses show a significant inequity in intra-group. This result indicated that the inequity of health resources allocation were mainly came from intra-group, namely the provinces (autonomous regions and municipalities) in western China. Conclusions: : In recent years, China’s various measures have improved the total amount of health resources and its equity of health resources in western China. However, the fairness of the health resources allocation in western China were remind poor. Although the fairness of human resources allocation has been alleviated in population dimension, the inequity of human resources distribution in provinces (autonomous regions and municipalities) are still obvious. In addition, the accessibility of health resources in western China must be further improved.

Establishment of Routine Clinical Indicators-Based Nomograms for Predicting the Mortality in Patients with COVID-19 (preprint)

Background: The aim of the study was to establish and validate nomograms to predict the mortality risk of patients with COVID-19 using routine clinical indicators. Method: This retrospective study included a development cohort enrolled 2119 hospitalized COVID-19 patients and a validation cohort included 1504 COVID-19 patients. The demographics, clinical manifestations, vital signs and laboratory test results of the patients at admission and outcome of in-hospital death were recorded. The independent factors associated with death were identified by a forward stepwise multivariate logistic regression analysis and used to construct two prognostic nomograms. The models were then tested in an external dataset. Results: Nomogram 1 is a full model included nine factors identified in the multivariate logistic regression and nomogram 2 is built by selecting four factors from nine to perform as a reduced model. Nomogram 1 and nomogram 2 established showed better performance in discrimination and calibration than the MuLBSTA score in training. In validation, Nomogram 1 performed better than nomogram 2 for calibration. Conclusion: Nomograms we established performed better than the MuLBSTA score. We recommend the application of nomogram 1 in general hospital which provide robust prognostic performance but more cumbersome; nomogram 2 in mobile cabin hospitals which depend on less laboratory examinations and more convenient. Both nomograms can help clinicians in identifying patients at risk of death with routine clinical indicators at admission, which may reduce the overall mortality of COVID-19.

The importance of education of infection control practices to acute lymphoblastic leukemia patient families for 2019-nCoV prevention (preprint)

Background: With the outbreak of coronavirus disease 2019 (2019-nCoV, also named COVID-19) and growing knowledge of its epidemiological characteristics, it has been clear that children with acute lymphoblastic leukemia (ALL) are also susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: In the past four months, we educated the guardians of children with leukemia with a series of preventative measures, including ⑴ Hand Hygiene and Hand Care; ⑵ the use of masks; ⑶ separation and sterilization of patient items; ⑷ avoiding public transportation; ⑸ Staying at home unless medically necessary; ⑹ Telemedicine; ⑺ Allowing only one caretaker during hospital admission ⑻ minimizing patients and their families visiting or travelling. We conducted a retrospective review to study the relationship between compliance with personal preventive measures and exposure to 2019-nCoV among children will ALL and their caretakers before and during the outbreak of 2019-nCoV in China between Jan 21-May 23 of 2020. Results: Prior to the outbreak of coronavirus 2019-nCoV in Jan 2020, 88.9% of patients washed their hands before meals and 55.6% after they ate. All of the patients who are >3 years old and 91% of the patients <3 years olds wore face masks regularly as a strategy for protection in the outdoors. When in the hospital, 95.5% of the patients who are >3 years old and 78% of the patients <3 years olds wore face masks regularly as a strategy for protection. Since the outbreak of coronavirus 2019-nCoV in China in Jan, 2020, the percentage of compliance to hand-washing before and after meals rose to 100% for all patients, as well as the compliance of regular mask use was 100%. Similar trend is also seen in the caretakers, prior to the outbreak 75% of whom washed their hands before and 66.7% after they ate or handed food. ALL of them wore masks regularly in the hospital or outdoors. Since the outbreak, 100% of caretakers wore masks during outside and in the wards. Regardless of the children with ALL are immunocompromised patients, key message of infection prevention provided to the families were using alcohol to disinfect surfaces, avoid going to public transport and without visitor or travelling. Prior to the outbreak, internet consults consisted of 20% out of all patient consults. As of date, which is 160 days since the outbreak, 80% of patient consults are done via internet. ALL of patients are voiding public transportation. Private cars and taxi are their choices. ALL of them comply with the policy of just one companion and stayed at home unless have to get IV chemo or got likely infection. In April 2019, 21.38% of the ALL patients in inpatient department suffered febrile neutropenia. Otherwise, in April 2020, only 5.18% suffered febrile neutropenia.Conclusion: From Jan 22 of 2020 to the authorship of this report, within the 200 number of ALL patients whom we have provided care for in Shenzhen Children’s hospital, none of the patients as well as their families were infected with 2019-nCoV, and all of them received chemotherapy as planned. The infection rate of ALL patients suffered febrile neutropenia decreased by seventy-five percent. These outcomes demonstrated that our response to the public health emergency was on-time and appropriate. The operational result shows that the control measures taken are effective. Our experience suggest that offering prompt and appropriate instructions in addition to provision of regular education and preventative practices to patients and their families may be considered to other pediatric oncology centers around the world.

COVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining

With the spread and development of new epidemics, it is of great reference value to identify the changing trends of epidemics in public emotions. We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining. A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed. Establish a "Scrapy-Redis-Bloomfilter" distributed crawler framework to collect data. The system can judge the positive and negative emotions of the reviewer based on the comments, and can also reflect the depth of the seven emotions such as Hopeful, Happy, and Depressed. Finally, we improved the sentiment discriminant model of this system and compared the sentiment discriminant error of COVID-19 related comments with the Jiagu deep learning model. The results show that our model has better generalization ability and smaller discriminant error. We designed a large data visualization screen, which can clearly show the trend of public emotions, the proportion of various emotion categories, keywords, hot topics, etc., and fully and intuitively reflect the development of public opinion.

Epidemiological and clinical characteristics of 47 corona virus disease 2019 non-survivors in Huoshenshan Hospital

Objective To provide a basis for further optimizing the diagnosis and treatment strategies of severe and critical corona virus disease 2019 (COVID-19) by investigating and analyzing the epidemiological and clinical characteristics of the death cases. Methods The epidemiological and clinical characteristics of 47 death cases obtained from Huoshenshan Hospital in Whuhan, Hubei Province were retrospectively analyzed. Results All the patients developed initial symptoms in Wuhan. The time from onset to admission was (12.60±5.60) days. Most of them were male (68.09%) with non-nosocomial infection (91.49%), advanced age (>60 years, 89.36%). Over half of the cases (51.06%) reported a history of contact with suspected or confirmed patients, and comorbidity of chronic diseases (70.21%). Multiple organ dysfunction syndrome (MODS) occurred in 29 cases (61.70%) with heart failure (51.06%) and renal failure (36.17%). The main clinical symptoms included fever, fatigue, dyspnea and cough. At admission,most cases were severe (55.32%) or critical (42.55%), and the in-hospital survival was longer for the severe than for the critical (P=0.02). 76.59% of the patients received invasive mechanical ventilation, and they had a longer in-hospital survival than those with non-invasive mechanical ventilation (P<0.05). Conclusions This group of cases occurred during the peak of the COVID-19 outbreak in China, characterized by male, elder and history of chronic diseases. Acute respiratory distress syndrome (ARDS) caused by COVID-19 was responsible for patients' death, and MODS manifestated by heart and kidney failure also implicated in the process. Disease severity and invasive mechanical ventilation were related to in-hospital survival.

The Effects of Steroids in Severe Hospitalized Patients with COVID-19: A Retrospective Cohort Study (preprint)

The efficacy of corticosteroids in the treatment of patients with severe COVID-19 remains unknown. We evaluated the impact of corticosteroids on clinical improvement among severe COVID-19 patients. In this retrospective, two-centered, cohort study, we enrolled 101 patients with severe COVID-19: with 39 patients in the steroid group and 63 patients in the non-steroid group. The primary endpoint was Time to Clinical Improvement (TTCI) by up to 28 days after the treatment. Secondary endpoints included the rate of CAT scan improvement, the percentage of negative SARS-Cov-2 RT-PCR tests by Day 28, and the time to discharge. We found that patients in the steroid group did not have significant differences of TTCI from patients in the non-steroid group by 28 days after the treatment (median, 19 days vs. 20 days; hazard ratio, 1.07; p=0.797). The CAT scan improvement rate was not statistically different between the two groups by Day 28 (87.2% vs. 79.0%, p=0.170). The negative test of SARS-CoV2 RT-PCR by Day 28 was 68.4% in the steroid group, 87.1% in the non-steroid group (p= 0.060). Time to discharge was significantly longer in the steroid group than the non-steroid group (35 days vs 21 days, p=0.005). Our findings indicated the short-term corticosteroid at a low to moderate dose did not improve the clinical outcomes for patients with severe COVID-19. Further randomized clinical trials are needed to confirm the findings.

Efficacy of Chloroquine versus Lopinavir/Ritonavir in mild/general COVID-19: a prospective, open-label, multicenter randomized controlled clinical study (preprint)

Background: The outbreak of novel coronavirus pneumonia is very serious, and no effective antiviral treatment has been confirmed. The fresh drug research and development cycle is too long to meet clinical emergency needs, and "old drugs and brand new applications" have a huge therapeutic potential. During our previous treatment, we found that the lopinavir/ritonavir treatment recommended in the Fifth edition of the treatment plan had little effect. Earlier studies have shown that chloroquine can inhibit coronavirus replication through multiple mechanisms. Our previous use of chloroquine to treat patients with SARS-CoV-2(novel coronavirus)-infected pneumonia has a higher negative rate of nucleic acid in throat swabs within 5 days after administration than that using lopinavir/ritonavir. However, the half-life and side effects of chloroquine vary greatly among individuals. Methods/design We plan to conduct a prospective, open-label, multicenter randomized controlled, comprehensive treatment clinical study. The study consisted of three phases: a screening period of 1-110 days, a treatment period of no more than 28 days, and a follow-up period of 1 month. Participants will be assessed at baseline and on days 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 14, 21, and 28 after the intervention begins. In this study, chloroquine and lopinavir/ritonavir tablets were used to treat patients with eligible novel coronavirus pneumonia diagnosed at various centers between February 12, 2020 and May 31, 2020. The efficacy and safety of chloroquine and lopinavir/ritonavir are to be evaluated. At the same time, explore the correlation between patient genetic polymorphisms and chloroquine steady-state concentration, therapeutic effects and adverse reactions in the body. It is an anti-virus for pneumonitis caused by novel coronavirus. The optimization and update of the antiviral treatment plan provides evidence-based evidence. Disscussion Our study is a prospective, open-label, multicenter randomized controlled, comprehensive treatment clinical study to evaluate the efficacy and safety of chloroquine phosphate and lopinavir/ritonavir in patients with mild/general COVID-2019. The results of this study will provide valuable clinical evidence for the treatment of novel coronavirus pneumonia.

A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing (preprint)

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.