Entangling of Peptide Nanofibers Reduces the Invasiveness of SARS-CoV-2.

The viral spike (S) protein on the surface of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to angiotensin-converting enzyme 2 (ACE2) receptors on the host cells, facilitating its entry and infection. Here, functionalized nanofibers targeting the S protein with peptide sequences of IRQFFKK, WVHFYHK and NSGGSVH, which are screened from a high-throughput one-bead one-compound screening strategy, are designed and prepared. The flexible nanofibers support multiple binding sites and efficiently entangle SARS-CoV-2, forming a nanofibrous network that blocks the interaction between the S protein of SARS-CoV-2 and the ACE2 on host cells, and efficiently reduce the invasiveness of SARS-CoV-2. In summary, nanofibers entangling represents a smart nanomedicine for the prevention of SARS-CoV-2.

Deep-Learning-Based COVID-19 Diagnosis and Implementation in Embedded Edge-Computing Device.

The rapid spread of coronavirus disease 2019 (COVID-19) has posed enormous challenges to the global public health system. To deal with the COVID-19 pandemic crisis, the more accurate and convenient diagnosis of patients needs to be developed. This paper proposes a deep-learning-based COVID-19 detection method and evaluates its performance on embedded edge-computing devices. By adding an attention module and mixed loss into the original VGG19 model, the method can effectively reduce the parameters of the model and increase the classification accuracy. The improved model was first trained and tested on the PC X86 GPU platform using a large dataset (COVIDx CT-2A) and a medium dataset (integrated CT scan); the weight parameters of the model were reduced by around six times compared to the original model, but it still approximately achieved 98.80%and 97.84% accuracy, outperforming most existing methods. The trained model was subsequently transferred to embedded NVIDIA Jetson devices (TX2, Nano), where it achieved 97% accuracy at a 0.6-1 FPS inference speed using the NVIDIA TensorRT engine. The experimental results demonstrate that the proposed method is practicable and convenient; it can be used on a low-cost medical edge-computing terminal. The source code is available on GitHub for researchers.

A cationic lipid with advanced membrane fusion performance for pDNA and mRNA delivery.

The success of mRNA vaccines for COVID-19 prevention raised global awareness of the importance of nucleic acid drugs. The approved systems for nucleic acid delivery were mainly formulations of different lipids, yielding lipid nanoparticles (LNPs) with complex internal structures. Due to the multiple components, the relationship between the structure of each component and the overall biological activity of LNPs is hard to study. However, ionizable lipids have been extensively explored. In contrast to former studies on the optimization of hydrophilic parts in single-component self-assemblies, we report in this study on structural alterations of the hydrophobic segment. We synthesize a library of amphiphilic cationic lipids by varying the lengths (C = 8-18), numbers (N = 2, 4), and unsaturation degrees (Ω = 0, 1) of hydrophobic tails. Notably, all self-assemblies with nucleic acid have significant differences in particle size, stability in serum, membrane fusion, and fluidity. Moreover, the novel mRNA/pDNA formulations are characterized by overall low cytotoxicity, efficient compaction, protection, and release of nucleic acids. We find that the length of hydrophobic tails dominates the formation and stability of the assembly. And at a certain length, the unsaturated hydrophobic tails enhance the membrane fusion and fluidity of assemblies and thus significantly affect the transgene expression, followed by the number of hydrophobic tails.

LS-MolGen: Ligand-and-Structure Dual-driven Deep Reinforcement Learning for Target-specific Molecular Generation Improves Binding Affinity and Novelty (preprint)

Molecule generative models based on deep learning have attracted significant attention in de novo drug design. However, most current generative approaches are either only ligand-based or only structure-based, which do not leverage the complementary knowledge from ligands and the structure of binding target. In this work, we proposed a new ligand and structure combined molecular generative model, LS-MolGen, that integrates representation learning, transfer learning, and reinforcement learning. Focus knowledge from transfer learning and special explore strategy in reinforcement learning enables LS-MolGen to generate novel and active molecules efficiently. The results of evaluation using EGFR and case study of inhibitor design for SARS-CoV-2 Mpro showed that LS-MolGen outperformed other state-of-the-art ligand-based or structure-based generative models and was capable of de novo designing promising compounds with novel scaffold and high binding affinity. Thus, we recommend that this proof-of-concept ligand-and-structure-based generative model will provide a promising new tool for target-specific molecular generation and drug design.

COVID-19 vaccination boosts the potency and breadth of the immune response against SARS-CoV-2 among recovered patients in Wuhan.

The immunity of patients who recover from coronavirus disease 2019 (COVID-19) could be long lasting but persist at a lower level. Thus, recovered patients still need to be vaccinated to prevent reinfection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or its mutated variants. Here, we report that the inactivated COVID-19 vaccine can stimulate immunity in recovered patients to maintain high levels of anti-receptor-binding domain (RBD) and anti-nucleocapsid protein (NP) antibody titers within 9 months, and high neutralizing activity against the prototype, Delta, and Omicron strains was observed. Nevertheless, the antibody response decreased over time, and the Omicron variant exhibited more pronounced resistance to neutralization than the prototype and Delta strains. Moreover, the intensity of the SARS-CoV-2-specific CD4+ T cell response was also increased in recovered patients who received COVID-19 vaccines. Overall, the repeated antigen exposure provided by inactivated COVID-19 vaccination greatly boosted both the potency and breadth of the humoral and cellular immune responses against SARS-CoV-2, effectively protecting recovered individuals from reinfection by circulating SARS-CoV-2 and its variants.

SARS-CoV-2 Variants, Current Vaccines and Therapeutic Implications for COVID-19.

Over the past two years, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused hundreds of millions of infections, resulting in an unprecedented pandemic of coronavirus disease 2019 (COVID-19). As the virus spreads through the population, ongoing mutations and adaptations are being discovered. There is now substantial clinical evidence that demonstrates the SARS-CoV-2 variants have stronger transmissibility and higher virulence compared to the wild-type strain of SARS-CoV-2. Hence, development of vaccines against SARS-CoV-2 variants to boost individual immunity has become essential. However, current treatment options are limited for COVID-19 caused by the SARS-CoV-2 variants. In this review, we describe current distribution, variation, biology, and clinical features of COVID-19 caused by SARS-CoV-2 variants (including Alpha (B.1.1.7 Lineage) variant, Beta (B.1.351 Lineage) variant, Gamma (P.1 Lineage) variant, Delta (B.1.617.2 Lineage) variant, and Omicron (B.1.1.529 Lineage) variant and others. In addition, we review currently employed vaccines in clinical or preclinical phases as well as potential targeted therapies in an attempt to provide better preventive and treatment strategies for COVID-19 caused by different SARS-CoV-2 variants.

Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions (preprint)

Non-coding RNA structure and function are essential to understanding various biological processes, such as cell signaling, gene expression, and post-transcriptional regulations. These are all among the core problems in the RNA field. With the rapid growth of sequencing technology, we have accumulated a massive amount of unannotated RNA sequences. On the other hand, expensive experimental observatory results in only limited numbers of annotated data and 3D structures. Hence, it is still challenging to design computational methods for predicting their structures and functions. The lack of annotated data and systematic study causes inferior performance. To resolve the issue, we propose a novel RNA foundation model (RNA-FM) to take advantage of all the 23 million non-coding RNA sequences through self-supervised learning. Within this approach, we discover that the pre-trained RNA-FM could infer sequential and evolutionary information of non-coding RNAs without using any labels. Furthermore, we demonstrate RNA-FM’s effectiveness by applying it to the downstream secondary/3D structure prediction, SARS-CoV-2 genome structure and evolution prediction, protein-RNA binding preference modeling, and gene expression regulation modeling. The comprehensive experiments show that the proposed method improves the RNA structural and functional modelling results significantly and consistently. Despite only being trained with unlabelled data, RNA-FM can serve as the foundational model for the field.

Potent Anti-SARS-CoV-2 Efficacy of COVID-19 Hyperimmune Globulin from Vaccine-Immunized Plasma.

Coronavirus disease 2019 (COVID-19) remains a global public health threat. Hence, more effective and specific antivirals are urgently needed. Here, COVID-19 hyperimmune globulin (COVID-HIG), a passive immunotherapy, is prepared from the plasma of healthy donors vaccinated with BBIBP-CorV (Sinopharm COVID-19 vaccine). COVID-HIG shows high-affinity binding to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein, the receptor-binding domain (RBD), the N-terminal domain of the S protein, and the nucleocapsid protein; and blocks RBD binding to human angiotensin-converting enzyme 2 (hACE2). Pseudotyped and authentic virus-based assays show that COVID-HIG displays broad-spectrum neutralization effects on a wide variety of SARS-CoV-2 variants, including D614G, Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Kappa (B.1.617.1), Delta (B.1.617.2), and Omicron (B.1.1.529) in vitro. However, a significant reduction in the neutralization titer is detected against Beta, Delta, and Omicron variants. Additionally, assessments of the prophylactic and treatment efficacy of COVID-HIG in an Adv5-hACE2-transduced IFNAR-/- mouse model of SARS-CoV-2 infection show significantly reduced weight loss, lung viral loads, and lung pathological injury. Moreover, COVID-HIG exhibits neutralization potency similar to that of anti-SARS-CoV-2 hyperimmune globulin from pooled convalescent plasma. Overall, the results demonstrate the potential of COVID-HIG against SARS-CoV-2 infection and provide reference for subsequent clinical trials.

Twelve-month specific IgG response to SARS-CoV-2 receptor-binding domain among COVID-19 convalescent plasma donors in Wuhan.

To investigate the duration of humoral immune response in convalescent coronavirus disease 2019 (COVID-19) patients, we conduct a 12-month longitudinal study through collecting a total of 1,782 plasma samples from 869 convalescent plasma donors in Wuhan, China and test specific antibody responses. The results show that positive rate of IgG antibody against receptor-binding domain of spike protein (RBD-IgG) to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the COVID-19 convalescent plasma donors exceeded 70% for 12 months post diagnosis. The level of RBD-IgG decreases with time, with the titer stabilizing at 64.3% of the initial level by the 9th month. Moreover, male plasma donors produce more RBD-IgG than female, and age of the patients positively correlates with the RBD-IgG titer. A strong positive correlation between RBD-IgG and neutralizing antibody titers is also identified. These results facilitate our understanding of SARS-CoV-2-induced immune memory to promote vaccine and therapy development.

A human antibody of potent efficacy against SARS-CoV-2 in rhesus macaques showed strong blocking activity to B.1.351.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes coronavirus disease-2019 (COVID-19), interacts with the host cell receptor angiotensin-converting enzyme 2 (hACE2) via its spike 1 protein during infection. After the virus sequence was published, we identified two potent antibodies against the SARS-CoV-2 receptor binding domain (RBD) from antibody libraries using a phage-to-yeast (PtY) display platform in only 10 days. Our lead antibody JMB2002, now in a Phase 1 clinical trial (ChiCTR2100042150), showed broad-spectrum in vitro blocking activity against hACE2 binding to the RBD of multiple SARS-CoV-2 variants, including B.1.351 that was reportedly much more resistant to neutralization by convalescent plasma, vaccine sera and some clinical-stage neutralizing antibodies. Furthermore, JMB2002 has demonstrated complete prophylactic and potent therapeutic efficacy in a rhesus macaque disease model. Prophylactic and therapeutic countermeasure intervention of SARS-CoV-2 using JMB2002 would likely slow down the transmission of currently emerged SARS-CoV-2 variants and result in more efficient control of the COVID-19 pandemic.

Clinical Features and Risk Factors for Secondary Infection in Critically Ill Patients With COVID-19 (preprint)

Background: To analyze the clinical features and the possible risk factors of secondary infection, and explore their impact on prognosis of COVID-19. Methods: A total of 165 severe and critical hospitalized patients diagnosed with COVID-19 were included. The clinical characteristics, laboratory tests, imaging data, secondary infections and outcomes were analyzed. Results: The mean age of total patients was (57.3±15.2) years, of which 111 were males (67.3%). 108 cases were with basic diseases (65.5%), and 1 death (0.6%). The secondary infection rate in critical patients was significantly higher than in severe patients (P <0.05). The secondary infections were mainly lung infections. The pathogens were principally Burkholderia multivorans, Stenotrophomonas maltophilia, Acinetobacter baumannii and Klebsiella pneumoniae. The recovery rate of 28 days in the infected group was significantly lower than that in the non-infected group (p < 0.001).The utilization rate and usage time of invasive ventilator, and deep vein catheterization, catheter indwelling and ECMO were the risk factors for the secondary infected patients.Conclusion: Secondary infection is an extremely common complication in critically ill patients and a trigger point for exacerbation of the disease. An effective control on the secondary infection will do good to the prognosis of COVID-19 patients.

CT findings of patients infected with SARS-CoV-2 (preprint)

Objective: We aimed to describe the chest CT findings in sixty-seven patients infected by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Method and material: We retrospectively reviewed 67 patients hospitalized in Ruian People's Hospital. All the patients received the positive diagnosis of SARS-CoV-2 infection. The CT and clinical data were collected between January 23 rd , 2020 and February 10 th , 2020. The CT images were analyzed by the senior radiologists. Conclusion: There are 54 patients with positive CT findings and 13 patients with negative CT findings. The typical CT findings in hospitalized patients with SARS-CoV-2 infection were ground glass opacities (42/54), lesions located in the peripheral area (50/54), multiple lesions (46/54), and lesions located in the lower lobes (42/54). There were less typical CT findings, including air bronchogram (18/54), pleural thickening or pleural effusion (14/54), consolidation (12/54), lesions in the upper lobes (12/54), interlobular septal thickening (11/54), reversed halo sign (9/54), single lesion (8/54), air cavities (4/54), bronchial wall thickening (3/54), and intrathoracic lymph node enlargement (2/54).

Development of a COVID-19 vaccine based on the receptor binding domain displayed on virus-like particles (preprint)

The recently ermerging disease COVID-19 is caused by the new SARS-CoV-2 virus first detected in the city of Wuhan, China. From there it has been rapidly spreading inside and outside China. With initial death rates around 4%, COVID-19 patients at longer distances from Wuhan showed reduced mortality as was previously observed for the SARS coronavirus. However, the new coronavirus spreads more strongly, as it sheds long before onset of symptoms or may be transmitted by people without symptoms. Rapid development of a protective vaccine against COVID-19 is therefore of paramount importance. Here we demonstrate that recombinantly expressed receptor binding domain (RBD) of the spike protein homologous to SARS binds to ACE2, the viral receptor. Higly repetitive display of RBD on immunologically optimized virus-like particles derived from cucumber mosaic virus resulted in a vaccine candidate (RBD-CuMVTT) that induced high levels of specific antibodies in mice which were able to block binding of spike protein to ACE2 and potently neutralized the SARS-CoV-2 virus in vitro.

Clinical and Radiographic Characteristics, Management and Short-term Outcomes of Patients with COVID-19 in Wenzhou, China (preprint)

Background: Coronavirus disease 2019 (COVID-19) is an emerging viral disease. Here, we reported the clinical features, management, and short-term outcomes of COVID-19 patients in Wenzhou, an area outside Wuhan.Methods: Patients admitted to the Infectious Diseases Department of Ruian People's Hospital in Wenzhou, from January 21 to February 7, 2020, were recruited. Medical data on epidemiological history, demographics, clinical characteristics, laboratory tests, computerized tomography (CT) examination, treatment, and short-term outcomes were retrospectively reviewed. Blood biochemistry and routine tests were examined using standard methods and automatic machines. CT examination was performed again for several times during the hospitalization as necessary.Results: A total of 67 confirmed COVID-19 cases were diagnosed; 64 (95.4%) were common cases and three (4.5%) severe cases. The most common symptoms at admission were fever (86.6%), cough (77.6%), productive cough (52.2%), chest distress (17.9%), and sore throat (11.9%), followed by diarrhea (7.4%), headache (7.4%), shortness of breath (6.0%), dizziness (4.5%), muscular soreness (4.5%), and running nose (4.5%). Thirty patients (47.8%) had increased C-reactive protein levels. The CT radiographs at admission showed abnormal findings in 54 (80.6%) patients. The patients were treated mainly by oxygen therapy and antiviral drugs. By February 17, 2020, none of the 67 patients died and no infection occurred among medical staff in the department. Fifty-four (80.6%) patients were completely recovered and all others were improving.Conclusion: Cases in Wenzhou are mild, with good prognosis. Timely and appropriate screening, diagnosis, and treatment are the key to achieve the good outcomes.

The Psychological Hotline Services Quality Survey during the Pandemic of COVID-19 in Mainland China

The outbreak of the COVID-19 pandemic has provoked a significant amount of panic due to dramatic changes in daily routines for residents all over China In response, more than 600 psychological hotlines have been built or modified and have supplied mental health services for the public. Regarding the service quality of the hotlines, a survey has been conducted to investigate the running of hotline services during the COVID-19 pandemic. The results reveal that the more successful hotlines all had better trained hotline counselors, and in the meanwhile, the key features of providing supervision arrangements and training resources. Moreover, the referral list should be adjusted according to the accessibility of the recourses during the pandemic.