SARS-CoV-2 Enters Human Leydig Cells and Affects Testosterone Production In Vitro.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a SARS-like coronavirus, continues to produce mounting infections and fatalities all over the world. Recent data point to SARS-CoV-2 viral infections in the human testis. As low testosterone levels are associated with SARS-CoV-2 viral infections in males and human Leydig cells are the main source of testosterone, we hypothesized that SARS-CoV-2 could infect human Leydig cells and impair their function. We successfully detected SARS-CoV-2 nucleocapsid in testicular Leydig cells of SARS-CoV-2-infected hamsters, providing evidence that Leydig cells can be infected with SARS-CoV-2. We then employed human Leydig-like cells (hLLCs) to show that the SARS-CoV-2 receptor angiotensin-converting enzyme 2 is highly expressed in hLLCs. Using a cell binding assay and a SARS-CoV-2 spike-pseudotyped viral vector (SARS-CoV-2 spike pseudovector), we showed that SARS-CoV-2 could enter hLLCs and increase testosterone production by hLLCs. We further combined the SARS-CoV-2 spike pseudovector system with pseudovector-based inhibition assays to show that SARS-CoV-2 enters hLLCs through pathways distinct from those of monkey kidney Vero E6 cells, a typical model used to study SARS-CoV-2 entry mechanisms. We finally revealed that neuropilin-1 and cathepsin B/L are expressed in hLLCs and human testes, raising the possibility that SARS-CoV-2 may enter hLLCs through these receptors or proteases. In conclusion, our study shows that SARS-CoV-2 can enter hLLCs through a distinct pathway and alter testosterone production.

Development of a thermostable SARS-CoV-2 variant-based bivalent protein vaccine with cross-neutralizing potency against Omicron subvariants.

SARS-CoV-2 variants have posed significant challenges to the hopes of using ancestral strain-based vaccines to address the risk of breakthrough infection by variants. We designed and developed a bivalent vaccine based on SARS-CoV-2 Alpha and Beta variants (named SCTV01C). SCTV01C antigens were stable at 25 ^oC for at least 6 months. In the presence of a squalene-based oil-in-water adjuvant SCT-VA02B, SCTV01C showed significant protection efficacy against antigen-matched Beta variant, with favorable safety profiles in rodents. Notably, SCTV01C exhibited cross-neutralization capacity against Omicron subvariants (BA.1, BA.1.1, BA.2, BA.3, and BA.4/5) in mice, superior to a WT (D614G)-based vaccine, which reinforced our previously published findings that SCTV01C exhibited broad-spectrum neutralizing potencies against over a dozen pre-Omicron variants and the Omicron BA.1 variant. In summary, variant-based multivalent protein vaccine could be a platform approach to address the challenging issues of emerging variants, vaccine hesitancy and the needs of affordable and thermal stable vaccines.

Preparation of the luciferase-labeled antibody for improving the detection sensitivity of viral antigen.

BACKGROUND: Viral antigen detection test is the most common method used to detect viruses in the field rapidly. However, due to the low sensitivity, it can only be used as an auxiliary diagnosis method for virus infection. Improving sensitivity is crucial for developing more accurate viral antigen tests. Nano luciferase (Nluc) is a sensitive reporter that has not been used in virus detection. RESULTS: In this study, we produced an intracellularly Nluc labeled detection antibody (Nluc-ch2C5) and evaluated its ability to improve the detection sensitivity of respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens. Compared with the traditional horse-radish peroxidase (HRP) labeled antibody (HRP-ch2C5), Nluc-ch2C5 was 41 times more sensitive for inactivated SARS-CoV-2 virus by sandwich chemiluminescence ELISA. Then we applied Nluc-ch2C5 to establish an automatic magnet chemiluminescence immune assay (AMCA) for the SARS-CoV-2 viral spike protein, the limit of detection was 68 pfu/reaction. The clinical sensitivity and specificity reached 75% (24/32) and 100% (48/48) using 32 PCR-positive and 48 PCR-negative swab samples for clinical evaluation, which is more sensitive than the commercial ELSA kit and colloid gold strip kit. CONCLUSIONS: Here, monoclonal antibody ch2C5 served as a model antibody and the SARS-CoV-2 served as a model pathogen. The Nluc labeled detecting antibody (Nluc-ch2C5) significantly improved the detection sensitivity of SARS-CoV-2 antigen. This labeling principle applies to other viral infections, so this labeling and test format could be expected to play an important role in detecting other virus antigens.

Development of a thermostable SARS-CoV-2 variant-based bivalent protein vaccine with cross-neutralizing potency against Omicron subvariants

SARS-CoV-2 variants have posed significant challenges to the hopes of using ancestral strain-based vaccines to address the risk of breakthrough infection by variants. We designed and developed a bivalent vaccine based on SARS-CoV-2 Alpha and Beta variants (named SCTV01C). SCTV01C antigens were stable at 25 oC for at least 6 months. In the presence of a squalene-based oil-in-water adjuvant SCT-VA02B, SCTV01C showed significant protection efficacy against antigen-matched Beta variant, with favorable safety profiles in rodents. Notably, SCTV01C exhibited cross-neutralization capacity against Omicron subvariants (BA.1, BA.1.1, BA.2, BA.3, and BA.4/5) in mice, superior to a WT (D614G)-based vaccine, which reinforced our previously published findings that SCTV01C exhibited broad-spectrum neutralizing potencies against over a dozen pre-Omicron variants and the Omicron BA.1 variant. In summary, variant-based multivalent protein vaccine could be a platform approach to address the challenging issues of emerging variants, vaccine hesitancy and the needs of affordable and thermal stable vaccines.

Effectiveness of cloud-based rehabilitation in children with developmental language disorder during the COVID-19 pandemic: A prospective cohort study.

During the coronavirus disease 2019 pandemic, we considered the case of a child with developmental language disorder (DLD) who could not go to the hospital on time to receive timely rehabilitation treatment due to disrupted hospital operations. The application of cloud-based rehabilitation platforms has provided significant advantages and convenience for children with DLD in-home remote rehabilitation. Among them, the JingYun Rehab Cloud Platform is the most widely used in mainland China. It is an interactive telerehabilitation system developed by Weixin Huang that delivers personalized home rehabilitation for special education children. In this study, we used the JingYun Rehab Cloud Platform to investigate the extent to which cloud-based rehabilitation is effective for children with DLD in terms of language and cognitive outcomes. This was a prospective cohort study including all children who were evaluated and diagnosed with DLD through Sign-Significant Relations and were followed up at the rehabilitation clinic of our institute. We followed 162 children with DLD for 3 months, including 84 children with DLD who participated in remote cloud-based rehabilitation on the JingYun Rehab Cloud Platform and 78 children with DLD as the control group who underwent home-based rehabilitation. Language abilities of both groups were assessed using the Chinese version of the Peabody Picture Vocabulary Test-Revised. Several measures of training performance (language, memory, and cognition tasks) were assessed before and after cloud-based rehabilitation in the remote cloud-based rehabilitation group. Children with DLD in the cloud-based rehabilitation group performed significantly better in language abilities, as assessed by the Peabody Picture Vocabulary Test-Revised, than children with DLD in the control group. Furthermore, for children who participated in remote cloud-based rehabilitation, the frequency of training sessions was proportional to their performance on language, memory, and cognition tasks. This study demonstrated the effectiveness of cloud-based rehabilitation on the JingYun Rehab Cloud Platform in treating children with DLD.

Prussian Blue@Zeolitic Imidazolate Framework Composite Toward Solar-triggered Biodecontamination

Metal-organic frameworks (MOFs) featuring composition and bandstructure diversity, are an emerging class of photoresponsive disinfectants. In this study, we demonstrated the superiority of core-shell arranged photoactive MOFs (prussian blue (PB) and zeolitic imidazolate framework (ZIF-8)) for pathogen inactivation in terms of biocidal efficiency and broad-spectrum sensitivity. Reactive oxygen species (ROS) production was significantly promoted after the integration of PB due to the photosensitization effect and initiation of in situ Fenton reaction. Favorably, another inactivation channel was also opened owing to the unique photothermal effect of PB. Attributed to the facilitated ROS intracellular penetration by heat, the composite outperforms not only individual component but anatase TiO2 in pathogen elimination. Specifically, the Staphylococcus aureus (S. aureus) inactivation efficiency of the composite (6.6 log) is 2, 1.8 and 5.1 times higher than that of PB (3.3 log), ZIF-8 (3.7 log) and TiO2 (1.3 log) over 45 min of simulated sunlight illumination. Significantly, the infectivity of Bacillus anthracis and murine coronavirus in droplets on composite-coated filter surface could be greatly reduced (approximately 3 log reduction in colony number/coronavirus titer) within few minutes of solar exposure, indicative of the great potential of MOF composites toward life-threatening microbial infection prevention.

Preparation of the luciferase-labeled antibody for improving the detection sensitivity of viral antigen

Viral antigen detection test is the most common method used to detect viruses in the field rapidly. However, due to the low sensitivity, it can only be used as an auxiliary diagnosis method for virus infection. Improving sensitivity is crucial for developing more accurate viral antigen tests. Nano luciferase (Nluc) is a sensitive reporter that has not been used in virus detection. In this study, we produced an intracellularly Nluc labeled detection antibody (Nluc-ch2C5) and evaluated its ability to improve the detection sensitivity of respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens. Compared with the traditional horse-radish peroxidase (HRP) labeled antibody (HRP-ch2C5), Nluc-ch2C5 was 41 times more sensitive for inactivated SARS-CoV-2 virus by sandwich chemiluminescence ELISA. Then we applied Nluc-ch2C5 to establish an automatic magnet chemiluminescence immune assay (AMCA) for the SARS-CoV-2 viral spike protein, the limit of detection was 68 pfu/reaction. The clinical sensitivity and specificity reached 75% (24/32) and 100% (48/48) using 32 PCR-positive and 48 PCR-negative swab samples for clinical evaluation, which is more sensitive than the commercial ELSA kit and colloid gold strip kit. Here, monoclonal antibody ch2C5 served as a model antibody and the SARS-CoV-2 served as a model pathogen. The Nluc labeled detecting antibody (Nluc-ch2C5) significantly improved the detection sensitivity of SARS-CoV-2 antigen. This labeling principle applies to other viral infections, so this labeling and test format could be expected to play an important role in detecting other virus antigens.

Convolutional Neural Networks Based on Sequential Spike Predict the High Human Adaptation of SARS-CoV-2 Omicron Variants.

The COVID-19 pandemic has frequently produced more highly transmissible SARS-CoV-2 variants, such as Omicron, which has produced sublineages. It is a challenge to tell apart high-risk Omicron sublineages and other lineages of SARS-CoV-2 variants. We aimed to build a fine-grained deep learning (DL) model to assess SARS-CoV-2 transmissibility, updating our former coarse-grained model, with the training/validating data of early-stage SARS-CoV-2 variants and based on sequential Spike samples. Sequential amino acid (AA) frequency was decomposed into serially and slidingly windowed fragments in Spike. Unsupervised machine learning approaches were performed to observe the distribution in sequential AA frequency and then a supervised Convolutional Neural Network (CNN) was built with three adaptation labels to predict the human adaptation of Omicron variants in sublineages. Results indicated clear inter-lineage separation and intra-lineage clustering for SARS-CoV-2 variants in the decomposed sequential AAs. Accurate classification by the predictor was validated for the variants with different adaptations. Higher adaptation for the BA.2 sublineage and middle-level adaptation for the BA.1/BA.1.1 sublineages were predicted for Omicron variants. Summarily, the Omicron BA.2 sublineage is more adaptive than BA.1/BA.1.1 and has spread more rapidly, particularly in Europe. The fine-grained adaptation DL model works well for the timely assessment of the transmissibility of SARS-CoV-2 variants, facilitating the control of emerging SARS-CoV-2 variants.

Convolutional Neural Networks Based on Sequential Spike Predict the High Human Adaptation of SARS-CoV-2 Omicron Variants

The COVID-19 pandemic has frequently produced more highly transmissible SARS-CoV-2 variants, such as Omicron, which has produced sublineages. It is a challenge to tell apart high-risk Omicron sublineages and other lineages of SARS-CoV-2 variants. We aimed to build a fine-grained deep learning (DL) model to assess SARS-CoV-2 transmissibility, updating our former coarse-grained model, with the training/validating data of early-stage SARS-CoV-2 variants and based on sequential Spike samples. Sequential amino acid (AA) frequency was decomposed into serially and slidingly windowed fragments in Spike. Unsupervised machine learning approaches were performed to observe the distribution in sequential AA frequency and then a supervised Convolutional Neural Network (CNN) was built with three adaptation labels to predict the human adaptation of Omicron variants in sublineages. Results indicated clear inter-lineage separation and intra-lineage clustering for SARS-CoV-2 variants in the decomposed sequential AAs. Accurate classification by the predictor was validated for the variants with different adaptations. Higher adaptation for the BA.2 sublineage and middle-level adaptation for the BA.1/BA.1.1 sublineages were predicted for Omicron variants. Summarily, the Omicron BA.2 sublineage is more adaptive than BA.1/BA.1.1 and has spread more rapidly, particularly in Europe. The fine-grained adaptation DL model works well for the timely assessment of the transmissibility of SARS-CoV-2 variants, facilitating the control of emerging SARS-CoV-2 variants.

`Development of a rapid neutralizing antibody test for SARS-CoV-2 and its application for neutralizing antibody screening and vaccinated serum testing

Background : Since the outbreak of coronavirus disease (COVID-19), the high infection rate and mutation frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent, have contributed to the ongoing global pandemic. Vaccination has become the most effective means of controlling COVID-19. Traditional neutralizing tests of sera are complex and labor-intensive, therefore, a rapid test for detecting neutralizing antibodies and antibody status post-immunization is needed. Methods : Based on the fact that antibodies exhibit neutralizing activity by blocking the binding of the S protein receptor-binding domain (S-RBD) to ACE2, we developed a rapid neutralizing antibody test, ACE2-Block-ELISA. To evaluate the sensitivity and specificity, we used 54 positive and 84 negative serum samples. We also tested the neutralizing activities of monoclonal antibodies (mAbs) and 214 sera samples from healthy individuals immunized with the inactivated SARS-CoV-2 vaccine. Results : The sensitivity and specificity of the ACE2-Block ELISA were 96.3% and 100%, respectively. For neutralizing mAb screening, ch-2C5 was selected for its ability to block the ACE2–S-RBD interaction. A plaque assay confirmed that ch-2C5 neutralized SARS-CoV-2, with NT50 values of 4.19, 10.63, and 1.074 μg/mL against the SARS-CoV-2 original strain, and the Beta and Delta variants, respectively. For the immunized sera samples, the neutralizing positive rate dropped from 82.14% to 32.16% within 4 months post-vaccination. Conclusions : This study developed and validated an ACE2-Block-ELISA to test the neutralizing activities of antibodies. As a rapid, inexpensive and easy-to-perform method, this ACE2-Block-ELISA has potential applications in rapid neutralizing mAb screening and SARS-CoV-2 vaccine evaluation.

Dynamic changes in chest CT findings of patients with coronavirus disease 2019 (COVID-19) in different disease stages: a multicenter study.

BACKGROUND: To investigate the dynamic changes in high-resolution computed tomography (HRCT) findings of coronavirus disease 2019 (COVID-19) patients with different severities in different disease stages. METHODS: We retrospectively collected the clinical and imaging data of 96 patients in Yunnan Province, China, who were diagnosed with COVID-19 between January 22 and March 15, 2020. Based on disease severity, the COVID-19 patients were classified into four types: mild (n=15), moderate (n=59), severe (n=19), and critical (n=3). Based on hospital stay and number of computed tomography (CT) scans, the clinical/disease course was divided into four stages, including stage 1 (days 0-4), stage 2 (days 5-9), stage 3 (days 10-14), and stage 4 (days 15-19). The HRCT findings, CT value, and lesion volume were analyzed for each stage and compared among the four stages of COVID-19 patients. RESULTS: CT findings were negative over the four stages for all mild COVID-19 patients. More lesions were found in the peripheral lung fields than in peripheral + central fields (P<0.05), and the number of negative patients in stage 4 were more than those in stages 1-3 (P<0.05). The left and right lower lobe were the most frequently affected lobes (P<0.05). In moderate patients, round ground glass opacities (GGOs) decreased from stage 1 to stage 4; partial consolidation peaked in stage 2 and then decreased in stages 3-4; fibrous stripes and subpleural lines increased from stage 1 and peaked in stage 4. Partial consolidation and consolidation were more common in severe patients than in moderate patients over the disease course (P<0.05). Critical patients showed significant partial consolidation and consolidation; The CT value, lesion volume and lesion volume percentage significantly decreased from stages 1-2 to stage 4 (all P<0.05). CONCLUSIONS: The dynamic changes in lung HRCT images are clinically related to the disease course of COVID-19.

Adaptation of SARS-CoV-2 in BALB/c mice for testing vaccine efficacy.

The ongoing coronavirus disease 2019 (COVID-19) pandemic has prioritized the development of small-animal models for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We adapted a clinical isolate of SARS-CoV-2 by serial passaging in the respiratory tract of aged BALB/c mice. The resulting mouse-adapted strain at passage 6 (called MASCp6) showed increased infectivity in mouse lung and led to interstitial pneumonia and inflammatory responses in both young and aged mice after intranasal inoculation. Deep sequencing revealed a panel of adaptive mutations potentially associated with the increased virulence. In particular, the N501Y mutation is located at the receptor binding domain (RBD) of the spike protein. The protective efficacy of a recombinant RBD vaccine candidate was validated by using this model. Thus, this mouse-adapted strain and associated challenge model should be of value in evaluating vaccines and antivirals against SARS-CoV-2.

Development of an automatic integrated gene detection system for novel severe acute respiratory syndrome-related coronavirus (SARS-CoV2).

In December 2019, Wuhan, China suffered a serious outbreak of a novel coronavirus infectious disease (COVID) caused by novel severe acute respiratory syndrome-related coronavirus (SARS-CoV 2). To quickly identify the pathogen, we designed and screened primer sets, and established a sensitive and specific qRT-PCR assay for SARS-CoV 2; the lower limit of detection (LOD) was 14.8 (95% CI: 9.8-21) copies per reaction. We combined this qRT-PCR assay with an automatic integration system for nucleic acid extraction and amplification, thereby establishing an automatic integrated gene detection system (AIGS) for SARS-CoV 2. Cross reactive analysis performed in 20 other respiratory viruses and 37 nasopharyngeal swabs confirmed a 100% specificity of the assay. Using two fold diluted SARS-CoV 2 culture, the LOD of AIGS was confirmed to be 365 copies/ml (95% CI: 351-375), which was Comparable to that of conventional q RT-PCR (740 copies/ml, 95% CI: 689-750). Clinical performances of AIGS assay were assessed in 266 suspected COVID-19 clinical respiratory tract samples tested in parallel with a commercial kit. The clinical sensitivity of the AIGS test was 97.62% (95% CI: 0.9320-0.9951) based on the commercial kit test result, and concordance analysis showed a high agreement in SARS-CoV-2 detection between the two assays, Pearson R was 0.9623 (95% CI: 0.9523-0.9703). The results indicated that this AIGS could be used for rapid detection of SARS-CoV 2. With the advantage of simple operation and less time consuming, AIGS could be suitable for SARS-CoV2 detection in primary medical institutions, thus would do a great help to improve detection efficiency and control the spread of COVID-19.