mRNA therapeutics for disease therapy: principles, delivery, and clinical translation.

Messenger RNA (mRNA) has become a key focus in the development of therapeutic agents, showing significant potential in preventing and treating a wide range of diseases. The COVID-19 pandemic in 2020 has accelerated the development of mRNA nucleic therapeutics and attracted significant investment from global biopharmaceutical companies. These therapeutics deliver genetic information into cells without altering the host genome, making them a promising treatment option. However, their clinical applications have been limited by issues such as instability, inefficient in vivo delivery, and low translational efficiency. Recent advances in molecular design and nanotechnology have helped overcome these challenges, and several mRNA formulations have demonstrated promising results in both animal and human testing against infectious diseases and cancer. This review provides an overview of the latest research progress in structural optimization strategies and delivery systems, and discusses key considerations for their future clinical use.

Efficacy and safety of Paxlovid in severe adult patients with SARS-Cov-2 infection: a multicenter randomized controlled study.

Background: Nirmatrelvir plus ritonavir (Paxlovid) reduced the risk of hospitalization or death by 89% in high-risk, ambulatory adults with COVID-19. We aimed at studying the efficacy and safety of Paxlovid in hospitalized adult patients with SARS-Cov-2 (Omicron BA.2.2 variant) infection and severe comorbidities. Methods: We conducted an open-label, multicenter, randomized controlled trial in which hospitalized adult patients with severe comorbidities were eligible and assigned in a 1:1 ratio to receive either 300 mg of nirmatrelvir plus 100 mg of ritonavir every 12 h for 5 days with standard treatment or only standard treatment. All-cause mortality on day 28, the duration of SARS-CoV-2 RNA clearance, and safety were evaluated. Findings: 264 patients (mean age, 70.35 years; 122 [46.21%] female) who met the criteria were enrolled at 5 sites in Shanghai from April 10 to May 19 in 2022. After randomization, a total of 132 patients were assigned to receive Paxlovid treatment plus standard treatment, and 132 patients were assigned to receive only standard treatment. The overall 28-day mortality was 4.92%, 8 patients died in the standard treatment group and 5 died in the Paxlovid plus standard treatment group. There was no significant difference in mortality from any cause at 28 days between the Paxlovid plus standard treatment group and the standard treatment group (absolute risk difference [ARD], 2.27; 95% CI -2.94 to 7.49, P = 0.39). There was no significant difference in the duration of SARS-CoV-2 RNA clearance among the two groups (mean days, 10 in Paxlovid plus standard treatment group and 10.50 in the standard treatment group; ARD, -0.62; 95% CI -2.29 to 1.05, P = 0.42). The incidence of adverse events that occurred during the treatment period was similar in the two groups (any adverse event, 10.61% with Paxlovid plus standard treatment vs. 7.58% with the standard, P = 0.39; serious adverse events, 4.55% vs. 3.788%, P = 0.76). Interpretation: Paxlovid showed no significant reduction in the risk of all-cause mortality on day 28 and the duration of SARS-CoV-2 RNA clearance in hospitalized adult COVID-19 patients with severe comorbidities. Funding: National Natural Science Foundation of China (grant number: 82172152, 81873944).

Efficacy and safety of Paxlovid in severe adult patients with SARS-Cov-2 infection: a multicenter randomized controlled study

Background Nirmatrelvir plus ritonavir (Paxlovid) reduced the risk of hospitalization or death by 89% in high-risk, ambulatory adults with COVID-19. We aimed at studying the efficacy and safety of Paxlovid in hospitalized adult patients with SARS-Cov-2 (Omicron BA.2.2 variant) infection and severe comorbidities. Methods We conducted an open-label, multicenter, randomized controlled trial in which hospitalized adult patients with severe comorbidities were eligible and assigned in a 1:1 ratio to receive either 300 mg of nirmatrelvir plus 100 mg of ritonavir every 12 h for 5 days with standard treatment or only standard treatment. All-cause mortality on day 28, the duration of SARS-CoV-2 RNA clearance, and safety were evaluated. Findings 264 patients (mean age, 70.35 years;122 [46.21%] female) who met the criteria were enrolled at 5 sites in Shanghai from April 10 to May 19 in 2022. After randomization, a total of 132 patients were assigned to receive Paxlovid treatment plus standard treatment, and 132 patients were assigned to receive only standard treatment. The overall 28-day mortality was 4.92%, 8 patients died in the standard treatment group and 5 died in the Paxlovid plus standard treatment group. There was no significant difference in mortality from any cause at 28 days between the Paxlovid plus standard treatment group and the standard treatment group (absolute risk difference [ARD], 2.27;95% CI −2.94 to 7.49, P = 0.39). There was no significant difference in the duration of SARS-CoV-2 RNA clearance among the two groups (mean days, 10 in Paxlovid plus standard treatment group and 10.50 in the standard treatment group;ARD, −0.62;95% CI −2.29 to 1.05, P = 0.42). The incidence of adverse events that occurred during the treatment period was similar in the two groups (any adverse event, 10.61% with Paxlovid plus standard treatment vs. 7.58% with the standard, P = 0.39;serious adverse events, 4.55% vs. 3.788%, P = 0.76). Interpretation Paxlovid showed no significant reduction in the risk of all-cause mortality on day 28 and the duration of SARS–CoV-2 RNA clearance in hospitalized adult COVID-19 patients with severe comorbidities. Funding 10.13039/501100001809National Natural Science Foundation of China (grant number: 82172152, 81873944).

A practical scoring model to predict the occurrence of critical illness in hospitalized patients with SARS-CoV-2 omicron infection.

Background: The variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged repeatedly, especially the Omicron strain which is extremely infectious, so early identification of patients who may develop critical illness will aid in delivering proper treatment and optimizing use of resources. We aimed to develop and validate a practical scoring model at hospital admission for predicting which patients with Omicron infection will develop critical illness. Methods: A total of 2,459 patients with Omicron infection were enrolled in this retrospective study. Univariate and multivariate logistic regression analysis were performed to evaluate predictors associated with critical illness. Moreover, the area under the receiver operating characteristic curve (AUROC), continuous net reclassification improvement, and integrated discrimination index were assessed. Results: The derivation cohort included 1721 patients and the validation cohort included 738 patients. A total of 98 patients developed critical illness. Thirteen variables were independent predictive factors and were included in the risk score: age > 65, C-reactive protein > 10 mg/L, lactate dehydrogenase > 250 U/L, lymphocyte < 0.8*10^9/L, white blood cell > 10*10^9/L, Oxygen saturation < 90%, malignancy, chronic kidney disease, chronic cardiac disease, chronic obstructive pulmonary disease, diabetes, cerebrovascular disease, and non-vaccination. AUROC in the derivation cohort and validation cohort were 0.926 (95% CI, 0.903-0.948) and 0.907 (95% CI, 0.860-0.955), respectively. Moreover, the critical illness risk scoring model had the highest AUROC compared with CURB-65, sequential organ failure assessment (SOFA) and 4C mortality scores, and always obtained more net benefit. Conclusion: The risk scoring model based on the characteristics of patients at the time of admission to the hospital may help medical practitioners to identify critically ill patients and take prompt measures.

A Privacy-Preserving Crowd Flow Prediction Framework Based on Federated Learning during Epidemics

Predicting and managing the movement of people in a region during epidemics’ outbreak is an important step in preventing outbreaks. The protection of user privacy during the outbreak has become a matter of public concern in recent years, yet deep learning models based on datasets collected from mobile devices may pose privacy and security issues. Therefore, how to develop an accurate crowd flow prediction while preserving privacy is a significant problem to be solved, and there is a tradeoff between these two objectives. In this paper, we propose a privacy-preserving mobility prediction framework via federated learning (CFPF) to solve this problem without significantly sacrificing the prediction performance. In this framework, we designed a deep and embedding learning approach called “Multi-Factors CNN-LSTM” (MFCL) that can help to explicitly learn from human trajectory data (weather, holidays, temperature, and POI) during epidemics. Furthermore, we improve the existing federated learning framework by introducing a clustering algorithm to classify clients with similar spatio-temporal characteristics into the same cluster, and select servers at the center of the cluster as edge central servers to integrate the optimal model for each cluster and improve the prediction accuracy. To address the privacy concerns, we introduce local differential privacy into the FL framework which can facilitate collaborative learning with uploaded gradients from users instead of sharing users’ raw data. Finally, we conduct extensive experiments on a realistic crowd flow dataset to evaluate the performance of our CFPF and make a comparison with other existing models. The experimental results demonstrate that our solution can not only achieve accurate crowd flow prediction but also provide a strong privacy guarantee at the same time.

Transnational white masculinity on Chinese social media: Western male vloggers' self-representations during the covid-19 pandemic

This article explores how white Western male vloggers have sought to maintain their positive images among Chinese netizens on the Chinese video-sharing platform Bilibili during the Covid-19 pandemic, when the West and foreign migrants in China were lampooned and scorned due to rising Chinese nationalism. By analyzing these vloggers' self-representations and the Chinese audience's responses to them, the article discusses how white male identity is negotiated on China's state-regulated social media platforms in this critical time. It shows that while Western male vloggers carefully represent themselves as ideal foreign migrants in China, they are subject to criticisms from their Chinese audience. In this process, the meanings attached to white male identity have become increasingly debated. [ FROM AUTHOR] Copyright of Asian Anthropology (1683478X) is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A Chess and Card Room-Induced COVID-19 Outbreak and Its Agent-Based Simulation in Yangzhou, China.

Objective: To evaluate epidemiological characteristics of the COVID-19 outbreak that resurged in Yangzhou and to simulate the impact of different control measures at different regional scales. Methods: We collected personal information from 570 laboratory-confirmed cases in Yangzhou from 28 July to 26 August 2021, and built a modified susceptible-exposed-infected-removed (SEIR) model and an agent-based model. Results: The SEIR model showed that for passengers from medium-high risk areas, pre-travel nucleic acid testing within 3 days could limit the total number of infected people in Yangzhou to 50; among elderly persons, a 60% increase in vaccination rates could reduce the estimated infections by 253. The agent-based model showed that when the population density of the chess and card room dropped by 40%, the number of infected people would decrease by 54 within 7 days. A ventilation increase in the chess and card room from 25 to 50% could reduce the total number of infections by 33 within 7 days; increasing the ventilation from 25 to 75% could reduce the total number of infections by 63 within 7 days. Conclusions: The SEIR model and agent-based model were used to simulate the impact of different control measures at different regional scales successfully. It is possible to provide references for epidemic prevention and control work.

[Expert statement on the construction criteria of critical care department in municipal and district designated hospitals under the pandemic prevention and control].

The global coronavirus disease 2019 epidemic is still in a pandemic state. Aging population with underlying diseases is prone to become severe, and have a higher mortality. The treatment capacity of the critical care department directly determines the treatment success rate of critical illness. At present, there is still a certain gap between domestic and foreign countries in intensive care unit (ICU), which is not only in the allocation of medical staff, but also in the beds and settings. The current medical model cannot fully meet the needs of development. The experience and lessons of many major public health emergencies suggested that "dual track of peace and war" approach in discipline construction of critical care is the best medical model. Following the concept of "combination of peace and war", strengthening the discipline construction of critical care department in municipal and district designated hospitals, allocating reasonable standard ICU, step-down ICU and combat readiness ICU, establishing rapid response team, and strengthening regular training and scientific management may be the key measures to deal with the epidemic.

Critical Decision-Making Issues in Disaster Relief Supply Management: A Review.

This paper comprehensively reviews the literature related to disaster relief supply management in recent years by taking the perspectives of three critical decision-making issues, i.e., coordination issues, facility location decisions, and inventory decisions. For each decision-making issue discussed, we clarify the barriers of current research papers and identify the major challenges and critical factors that should be considered. In the following, we present the perspectives on the road of coordination between multiple relief actors, characterize the location decisions of relief facilities with a variety of optimization objectives, and emphasize the importance of relief supply varieties and critical factors in the decisions of disaster relief inventories. Future research directions are recommended for further discussions.

Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study

ObjectiveTo delineate the clinical characteristics of patients with coronavirus disease 2019 (covid-19) who died.DesignRetrospective case series.SettingTongji Hospital in Wuhan, China.ParticipantsAmong a cohort of 799 patients, 113 who died and 161 who recovered with a diagnosis of covid-19 were analysed. Data were collected until 28 February 2020.Main outcome measuresClinical characteristics and laboratory findings were obtained from electronic medical records with data collection forms.ResultsThe median age of deceased patients (68 years) was significantly older than recovered patients (51 years). Male sex was more predominant in deceased patients (83;73%) than in recovered patients (88;55%). Chronic hypertension and other cardiovascular comorbidities were more frequent among deceased patients (54 (48%) and 16 (14%)) than recovered patients (39 (24%) and 7 (4%)). Dyspnoea, chest tightness, and disorder of consciousness were more common in deceased patients (70 (62%), 55 (49%), and 25 (22%)) than in recovered patients (50 (31%), 48 (30%), and 1 (1%)). The median time from disease onset to death in deceased patients was 16 (interquartile range 12.0-20.0) days. Leukocytosis was present in 56 (50%) patients who died and 6 (4%) who recovered, and lymphopenia was present in 103 (91%) and 76 (47%) respectively. Concentrations of alanine aminotransferase, aspartate aminotransferase, creatinine, creatine kinase, lactate dehydrogenase, cardiac troponin I, N-terminal pro-brain natriuretic peptide, and D-dimer were markedly higher in deceased patients than in recovered patients. Common complications observed more frequently in deceased patients included acute respiratory distress syndrome (113;100%), type I respiratory failure (18/35;51%), sepsis (113;100%), acute cardiac injury (72/94;77%), heart failure (41/83;49%), alkalosis (14/35;40%), hyperkalaemia (42;37%), acute kidney injury (28;25%), and hypoxic encephalopathy (23;20%). Patients with cardiovascular comorbidity were more likely to develop cardiac complications. Regardless of history of cardiovascular disease, acute cardiac injury and heart failure were more common in deceased patients.ConclusionSevere acute respiratory syndrome coronavirus 2 infection can cause both pulmonary and systemic inflammation, leading to multi-organ dysfunction in patients at high risk. Acute respiratory distress syndrome and respiratory failure, sepsis, acute cardiac injury, and heart failure were the most common critical complications during exacerbation of covid-19.

Twelve-Month Systemic Consequences of Coronavirus Disease 2019 (COVID-19) in Patients Discharged From Hospital: A Prospective Cohort Study in Wuhan, China.

BACKGROUND: Follow-up study of coronavirus disease 2019 (COVID-19) survivors has rarely been reported. We aimed to investigate longitudinal changes in the characteristics of COVID-19 survivors after discharge. METHODS: A total of 594 COVID-19 survivors discharged from Tongji Hospital in Wuhan from February 10 to April 30, 2020 were included and followed up until May 17, 2021. Laboratory and radiological findings, pulmonary function tests, electrocardiogram, symptoms and signs were analyzed. RESULTS: 257 (51.2%) patients had at least one symptom at 3 months post-discharge, which decreased to 169 (40.0%) and 138 (28.4%) at 6-month and 12-month visit respectively. During follow-up period, insomnia, chest tightness, and fatigue were the most prevalent symptoms. Most laboratory parameters returned to normal, whereas increased incidence of abnormal liver and renal function and cardiovascular injury was evidenced after discharge. Fibrous stripes (213; 42.4%), pleural thickening and adhesions (188; 37.5%) and enlarged lymph nodes (120; 23.9%) were the most common radiographical findings at 3 months post-discharge. The abnormalities of pulmonary function included obstructive, restrictive, and mixed, which were 5.5%, 4.0%, 0.9% at 6 months post, and 1.9%, 4.7%, 0.2% at 12 months. Electrocardiogram abnormalities occurred in 256 (51.0%) patients at 3 months post-discharge, including arrhythmia, ST-T change and conduction block, which increased to 258 (61.1%) cases at 6-month visit and were maintained at high frequency (242;49.8%) at 12-month visit. CONCLUSIONS: Physiological, laboratory, radiological, or electrocardiogram abnormalities, particularly those related to renal, cardiovascular, and liver functions are common in patients who recovered from coronavirus disease 2019 (COVID-19) up to 12 months post-discharge.

The mechanism underlying extrapulmonary complications of the coronavirus disease 2019 and its therapeutic implication.

The coronavirus disease 2019 (COVID-19) is a highly transmissible disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that poses a major threat to global public health. Although COVID-19 primarily affects the respiratory system, causing severe pneumonia and acute respiratory distress syndrome in severe cases, it can also result in multiple extrapulmonary complications. The pathogenesis of extrapulmonary damage in patients with COVID-19 is probably multifactorial, involving both the direct effects of SARS-CoV-2 and the indirect mechanisms associated with the host inflammatory response. Recognition of features and pathogenesis of extrapulmonary complications has clinical implications for identifying disease progression and designing therapeutic strategies. This review provides an overview of the extrapulmonary complications of COVID-19 from immunological and pathophysiologic perspectives and focuses on the pathogenesis and potential therapeutic targets for the management of COVID-19.

Superoxide Dismutase Prevents SARS-CoV-2-Induced Plasma Cell Apoptosis and Stabilizes Specific Antibody Induction.

The infection of coronavirus disease (COVID-19) seriously threatens human life. It is urgent to generate effective and safe specific antibodies (Abs) against the pathogenic elements of COVID-19. Mice were immunized with SARS-CoV-2 spike protein antigens: S ectodomain-1 (CoV, in short) mixed in Alum adjuvant for 2 times and boosted with CoV weekly for 6 times. A portion of mice were treated with Maotai liquor (MTL, in short) or/and heat stress (HS) together with CoV boosting. We observed that the anti-CoV Ab was successfully induced in mice that received the CoV/Alum immunization for 2 times. However, upon boosting with CoV, the CoV Ab production diminished progressively; spleen CoV Ab-producing plasma cell counts reduced, in which substantial CoV-specific Ab-producing plasma cells (sPC) were apoptotic. Apparent oxidative stress signs were observed in sPCs; the results were reproduced by exposing sPCs to CoV in the culture. The presence of MTL or/and HS prevented the CoV-induced oxidative stress in sPCs and promoted and stabilized the CoV Ab production in mice in re-exposure to CoV. In summary, CoV/Alum immunization can successfully induce CoV Ab production in mice that declines upon reexposure to CoV. Concurrent administration of MTL/HS stabilizes and promotes the CoV Ab production in mice.

Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study.

OBJECTIVE: To evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions. DESIGN: Descriptive and modelling study based on surveillance data of COVID-19 in Beijing. SETTING: Outbreak in Beijing. PARTICIPANTS: The database included 335 confirmed cases of COVID-19. METHODS: To conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing. RESULTS: We found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect. CONCLUSIONS: The non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection.

Development and Validation of a New Prognostic Scoring System for COVID-19.

This study aimed to develop and validate a bedside risk analysis system for predicting the clinical severity and prognosis of patients with coronavirus disease 2019 (COVID-19). In total, 444 COVID-19 patients were included and randomly assigned in a 2:1 ratio to 2 groups: derivation group and validation group. The new scoring system comprised of the following 8 variables: history of malignant diseases, history of diabetes mellitus, dyspnea, respiratory rate >24 breaths/min, C-reactive protein level >14 mg/L, white blood cell count >8×109/L, platelets count <180 × 1012/L, and lymphocyte count <1 × 109/L. The sensitivity analysis revealed that this new scoring system was more efficient than the sequential organ failure assessment scoring system on the first day of admission. The receiver characteristic curve analysis revealed that the new risk scoring predicted the severe cases of COVID-19 infection with an area under the curve of 0.831 (95% confidence interval [CI]: 0.783-0.879) and 0.798 (95% CI: 0.727-0.869) in the derivation and validation groups, respectively. This proposed risk score system is a fairly reliable and robust tool for evaluating the severity and prognosis of patients with COVID-19. This may help in the early identification of severe COVID-19 patients with poor prognosis, requiring more intense interventions.

Changes in RT-PCR test results and symptoms during the menstrual cycle of female individuals infected with SARS-CoV-2: Report of two cases.

The implications of the menstrual cycle for disease susceptibility, development, and severity of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are largely unknown. Here, we describe two women infected with SARS-CoV-2 whose real-time reverse transcriptase-polymerase chain reaction (RT-PCR) test results and symptoms changed during the menstrual cycle. The first patient developed a fever on the first day of her menstrual period, and again on the first day of her next menstrual period after hospital discharge. RT-PCR test results were positive during the first menstrual period before admission, but turned negative during hospitalization, and then were positive again during the second menstrual period after hospital discharge. Another one also developed a fever again on the first day of her menstrual period after hospital discharge. RT-PCR test results were negative before admission and during hospitalization, but turned positive during the first menstrual period after hospital discharge. The cases indicate sex hormones may play an important role in SARS-CoV-2 infection. For women with history of exposure to SARS-CoV-2, the management protocol should include assessment of the menstrual status.

Immunological Characteristics in Type 2 Diabetes Mellitus Among COVID-19 Patients.

Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT04365634. Context: Diabetes mellitus was associated with increased severity and mortality of disease in COVID-19 pneumonia. So far the effect of type 2 diabetes (T2DM) or hyperglycemia on the immune system among COVID-19 disease has remained unclear. Objective: We aim to explore the clinical and immunological features of type 2 diabetes mellitus (T2DM) among COVID-19 patients. Design and Methods: In this retrospective study, the clinical and immunological characteristics of 306 hospitalized confirmed COVID-19 patients (including 129 diabetic and 177 non-diabetic patients) were analyzed. The serum concentrations of laboratory parameters including cytokines and numbers of immune cells were measured and compared between diabetic and non-diabetic groups. Results: Compared with non-diabetic group, diabetic cases more frequently had lymphopenia and hyperglycemia, with higher levels of urea nitrogen, myoglobin, D-dimer and ferritin. Diabetic cases indicated the obviously elevated mortality and the higher levels of cytokines IL-2R, IL-6, IL-8, IL-10, and TNF-α, as well as the distinctly reduced Th1/Th2 cytokines ratios compared with non-diabetic cases. The longitudinal assays showed that compared to that at week 1, the levels of IL-6 and IL-8 were significantly elevated at week 2 after admission in non-survivors of diabetic cases, whereas there were greatly reductions from week 1 to week 2 in survivors of diabetic cases. Compared with survival diabetic patients, non-survival diabetic cases displayed distinct higher serum concentrations of IL-2R, IL-6, IL-8, IL-10, TNF-α, and lower Th1/Th2 cytokines ratios at week 2. Samples from a subset of participants were evaluated by flow cytometry for the immune cells. The counts of peripheral total T lymphocytes, CD4+ T cells, CD8+ T cells and NK cells were markedly lower in diabetic cases than in non-diabetic cases. The non-survivors showed the markedly declined counts of CD8+ T cells and NK cells than survivors. Conclusion: The elevated cytokines, imbalance of Th1/Th2 cytokines ratios and reduced of peripheral numbers of CD8+ T cells and NK cells might contribute to the pathogenic mechanisms of high mortality of COVID-19 patients with T2DM.