Tracking changes in atmospheric particulate matter at a semi-urban site in Central France over the past decade.

Nearly 10-year (2013-2022) data on atmospheric particulate matters (PMs) were collected to investigate the air quality in a suburban site of Orléans city (France). The PM10 concentration decreased slightly between 2013 and 2022. PMs concentrations showed a monthly variation with higher concentration in cold periods. PM10 presented a clear bimodal diurnal variation peaking at morning rush hour and midnight, whereas the fine PMs such as PM2.5 and PM1.0 only had significant peaks during nighttime. Further, PM10 had more pronounced week-end effect than other fine PMs. COVID-19 lockdown impact on PMs levels was further investigated, showing that the lockdown during cold season could result in an increase of PMs concentrations because of the enhanced household heating. We concluded that PM10 could originate from biomass burning and fossil fuel related activities, air parcels from the western Europe through Paris were also important source of PM10 in the investigated area. Fine PMs, such as PM2.5 and PM1.0, originated mainly from biomass burning in addition to secondary formation at the local scale. This study provides a long-term PMs measurement database to explore the sources and characterization of PMs in central France, which could support future regulation and formulation of air quality standards.

Excess risk for acute myocardial infarction mortality during the COVID-19 pandemic.

The COVID-19 pandemic has had a detrimental impact on the healthcare system. Our study armed to assess the extent and the disparity in excess acute myocardial infarction (AMI)-associated mortality during the pandemic, through the recent Omicron outbreak. Using data from the CDC's National Vital Statistics System, we identified 1 522 669 AMI-associated deaths occurring between 4/1/2012 and 3/31/2022. Accounting for seasonality, we compared age-standardized mortality rate (ASMR) for AMI-associated deaths between prepandemic and pandemic periods, including observed versus predicted ASMR, and examined temporal trends by demographic groups and region. Before the pandemic, AMI-associated mortality rates decreased across all subgroups. These trends reversed during the pandemic, with significant rises seen for the youngest-aged females and males even through the most recent period of the Omicron surge (10/2021-3/2022). The SAPC in the youngest and middle-age group in AMI-associated mortality increased by 5.3% (95% confidence interval [CI]: 1.6%-9.1%) and 3.4% (95% CI: 0.1%-6.8%), respectively. The excess death, defined as the difference between the observed and the predicted mortality rates, was most pronounced for the youngest (25-44 years) aged decedents, ranging from 23% to 34% for the youngest compared to 13%-18% for the oldest age groups. The trend of mortality suggests that age and sex disparities have persisted even through the recent Omicron surge, with excess AMI-associated mortality being most pronounced in younger-aged adults.

Deep Learning-Based Bioactive Therapeutic Peptide Generation and Screening.

Many bioactive peptides demonstrated therapeutic effects over complicated diseases, such as antiviral, antibacterial, anticancer, etc. It is possible to generate a large number of potentially bioactive peptides using deep learning in a manner analogous to the generation of de novo chemical compounds using the acquired bioactive peptides as a training set. Such generative techniques would be significant for drug development since peptides are much easier and cheaper to synthesize than compounds. Despite the limited availability of deep learning-based peptide-generating models, we have built an LSTM model (called LSTM_Pep) to generate de novo peptides and fine-tuned the model to generate de novo peptides with specific prospective therapeutic benefits. Remarkably, the Antimicrobial Peptide Database has been effectively utilized to generate various kinds of potential active de novo peptides. We proposed a pipeline for screening those generated peptides for a given target and used the main protease of SARS-COV-2 as a proof-of-concept. Moreover, we have developed a deep learning-based protein-peptide prediction model (DeepPep) for rapid screening of the generated peptides for the given targets. Together with the generating model, we have demonstrated that iteratively fine-tuning training, generating, and screening peptides for higher-predicted binding affinity peptides can be achieved. Our work sheds light on developing deep learning-based methods and pipelines to effectively generate and obtain bioactive peptides with a specific therapeutic effect and showcases how artificial intelligence can help discover de novo bioactive peptides that can bind to a particular target.

Analysis of psychological status and effect of psychological intervention in quarantined population during the epidemic of SARS-CoV-2.

ABSTRACT: During outbreaks of the coronavirus disease 2019 (COVID-19), many countries adopted quarantine to slow the spread of the virus of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Quarantine will cause isolation from families, friends, and the public, which consequently leads to serious psychological pressure with potentially long-lasting effects on the quarantined population. Experience of specific practices to improve the psychological status of the mandatory quarantined population was limited. The aim of this study was to investigate the psychological impact of mandatory quarantine, and evaluate the effect of psychological intervention on the quarantined population.We conducted a prospective cohort study to assess and manage the psychological status of a mandatory quarantined population in Beijing, China. A total of 638 individuals completed 2 questionnaires and were enrolled in this study, of which 372 participants accepted designed psychological intervention while other 266 participants refused it. The SCL-90 questionnaire was used to evaluate the psychological status and its change before and after the intervention. The differences of SCL-90 factor scores between participants and the national norm group were assessed by 2 samples t test. While the SCL-90 factor scores before and after intervention were compared with 2 paired samples t test.Compared with the Chinese norms of SCL-90, the participants had higher SCL-90 factor scores in most items of the SCL-90 inventory. The SCL-90 factor scores of participants with psychological intervention significantly decreased in somatization, obsessive-compulsive, depression, anxiety, phobic anxiety, paranoid ideation, and psychoticism. In contrast, most factor scores of the SCL-90 inventory changed little without statistical significance in participants without psychological intervention.Psychological problems should be emphasized in the quarantined individuals and professional psychological intervention was a feasible approach to improve the psychological status of the mandatory quarantined population in the epidemic of SARS-CoV-2.

Xiang Qin Kang Gan Granules Treated the Human Coronavirus 229E Induced Pneumonia with Damp-Heat Syndrome in Mice.

Coronavirus disease 2019 (COVID-19), which causes severe respiratory illness, was first reported in Wuhan, China. The etiology of the disease is a new novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was reported to share the same origin as SARS-CoV, causing severe public health events in 2002. Unlike the SARS-CoV, which was conquered in the early summer of 2003, this virus was still contagious widely and reached a pandemic level. It can still spread fast even if the season's temperature is raised. Here, we made a model of pneumonia of human coronavirus 229E (HCoV-229E) with damp-heat syndrome treated by Xiangqin Kanggan granules to find a new medicine for treating these kinds of infectious diseases coronaviruses induced.

Excess diabetes mellitus-related deaths during the COVID-19 pandemic in the United States.

Background: Diabetes mellitus (DM) is a critical risk factor for severe SARS-CoV-2 infection, and SARS-CoV-2 infection contributes to worsening glycemic control. The COVID-19 pandemic profoundly disrupted the delivery of care for patients with diabetes. We aimed to determine the trend of DM-related deaths during the pandemic. Methods: In this serial population-based study between January 1, 2006 and December 31, 2021, mortality data of decedents aged ≥25 years from the National Vital Statistics System dataset was analyzed. Decedents with DM as the underlying or contributing cause of death on the death certificate were defined as DM-related deaths. Excess deaths were estimated by comparing observed versus expected age-standardized mortality rates derived from mortality during 2006-2019 with linear and polynomial regression models. The trends of mortality were quantified with joinpoint regression analysis. Subgroup analyses were performed by age, sex, race/ethnicity, and state. Findings: Among 4·25 million DM-related deaths during 2006-2021, there was a significant surge of more than 30% in mortality during the pandemic, from 106·8 (per 100,000 persons) in 2019 to 144·1 in 2020 and 148·3 in 2021. Adults aged 25-44 years had the most pronounced rise in mortality. Widened racial/ethnic disparity was observed, with Hispanics demonstrating the highest excess deaths (67·5%; 95% CI 60·9-74·7%), almost three times that of non-Hispanic whites (23·9%; 95% CI 21·2-26·7%). Interpretation: The United States saw an increase in DM-related mortality during the pandemic. The disproportionate rise in young adults and the widened racial/ethnic disparity warrant urgent preventative interventions from diverse stakeholders. Funding: National Natural Science Foundation of China.

Pirfenidone ameliorates early pulmonary fibrosis in LPS-induced acute respiratory distress syndrome by inhibiting endothelial-to-mesenchymal transition via the Hedgehog signaling pathway.

Pulmonary vascular endothelial dysfunction is a key pathogenic mechanism in acute respiratory distress syndrome (ARDS), resulting in fibrosis in lung tissues, including in the context of COVID-19. Pirfenidone (PFD) has become a novel therapeutic agent for treating idiopathic pulmonary fibrosis (IPF) and can improve lung function, inhibit fibrosis and inhibit inflammation. Recently, endothelial-to-mesenchymal transition (EndMT) was shown to play a crucial role in various respiratory diseases. However, the role of PFD in the course of EndMT in LPS-induced ARDS remains poorly understood. The purpose of this study was to explore the anti-EndMT effects of PFD on pulmonary fibrosis after LPS-induced ARDS. First, we determined that PFD significantly reduced LPS-induced ARDS, as shown by significant pathological alterations, and alleviated the oxidative stress and inflammatory response in vitro and in vivo. Furthermore, PFD decreased pulmonary fibrosis in LPS-induced ARDS by inhibiting EndMT and reduced the expression levels of Hedgehog (HH) pathway target genes, such as Gli1 and α-SMA, after LPS induction. In summary, this study confirmed that inhibiting the HH pathway by PFD could decrease pulmonary fibrosis by downregulating EndMT in LPS-induced ARDS. In conclusion, we demonstrate that PFD is a promising agent to attenuate pulmonary fibrosis following ARDS in the future.

Investigation and influencing factors about well-being level of elderly chronic patients during COVID-19 postpandemic period in Beijing.

ABSTRACT: The Corona Virus Disease 2019 (COVID-19) pandemic has huge impacts on the world, including human health and economic decline. The COVID-19 has severe infectivity, especially the elderly with chronic diseases will cause various complications after infection and accelerate the disease process. In addition, COVID-19 will also affect their mental health. Therefore, the mental health of elderly patients with chronic diseases cannot be ignored. The aim of this study was to investigate the well-being level of elderly people with chronic disease during COVID-19 postpandemic period in Beijing and analysis related influencing factors, so as to provide a basis for improving the well-being level of elderly chronic patients during the postpandemic period.Elderly patients with chronic diseases who met the inclusion criteria in 5 different administrative regions in Beijing were selected to carry out a questionnaire survey. The contents of the questionnaire included general data, the Memorial University of Newfoundland Happiness scale and the awareness situation of the COVID-19 pandemic. A total of 500 questionnaires were distributed by WeChat and 486 valid questionnaires were collected. The t test and one-way analysis of variance were used to compare Memorial University of Newfoundland Happiness scores between 2 or more groups, multiple linear regression analysis was used to conduct multiple factor analysis to explore the related factors about well-being level of elderly chronic patients.A total of 109 cases (22.43%) were evaluated high well-being level, 319 cases (65.64%) were evaluated moderate well-being level and 58 cases (11.93%) were evaluated low well-being according to the Memorial University of Newfoundland Happiness (MUNSH) scores rating. The multiple linear regression indicated that the education level, number of chronic diseases, medical expenses, frequency of children's visits, taking care of grandchildren or not, and group activity frequency significantly affected the well-being of patients with chronic diseases during COVID-19 postpandemic period in Beijing (P < .05).Most elderly patients with chronic diseases had moderate or above sense of well-being during postpandemic period, but we should still pay attention to the mental health of those elderly chronic patients with low education level, much comorbidity, more medical expenses, less visits by children, not take care of grandchildren and never participate in group activities.

Omicron variant of SARS-COV-2 gains new mutations in New Zealand and Hong Kong (preprint)

SARS-COV-2 evolution is a key factor that drives the pandemic. As the previous four variants of concern, omicron variant arose from complete obscurity and have rapidly become the prominent pandemic driver around the world. After initial identification in November 2021, this variant has yielded three different subvariants, BA.1, BA.2 and BA.3. Among them, BA.1 is dominant around the world although BA.2 is gradually taking over this role. BA.1 has acquired spike R346K and yielded a sub-lineage known as BA.1.1. An important question is how these variants continue their evolution. To address this question, I analyzed new SARS-COV-2 genomes identified in Oceania and Asia, where there are many ongoing pandemic hotspots. This analysis revealed that together with BA.2, two different BA.1.1 strains are dominant in New Zealand. Each of them carries two new substitutions, with L133F of NSP10 as the common one. This residue is located at an unstructured C-terminal tail, so the impact of L133F is not obvious. The other new substitutions are T1368I of NSP3 and R289H of NSP14. While T1368I of NSP3 is located close to its first transmembrane domain, R289H of NSP14 is right at a key motif of the binding pocket for S-adenosyl methionine, a cofactor required for the guanine-N7 methyltransferase activity. Analysis of SARS-COV-2 genomes from New Zealand also identified a delta subvariant with over ten new mutations (including spike N481K and R765H), but the subvariant is still negligible in driving the pandemic. Analysis of SARS-COV-2 genomes from Hong Kong uncovered a predominant BA.2 subvariant with three new substitutions: I1221T of spike protein (located at the transmembrane domain), T725I of NSP3 (within the C-terminal third of a SARS-unique domain) and T145I of NSP8 (at a surface area away from the site for interaction with NSP7 and NSP12). By contrast, no dominant mutations are obvious in omicron genomes from Australia, Indonesia, Singapore, Malaysia, Thailand, Japan and South Korea, suggesting that emergence of the dominant omicron subvariants in New Zealand and Hong Kong is of random nature. These findings partly explain the current situation in these two pandemic hotspots and reiterate the importance to continue tracking SARS-COV-2 evolution.

Persistence of SARS-CoV-2 RNA in wastewater after the end of the COVID-19 epidemics.

Although the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widely detected in wastewater in many countries to track the COVID-19 pandemic development, it is still a lack of clear understanding of the persistence of SARS-CoV-2 in raw sewage, especially after the end of the COVID-19 pandemic event. To fill this knowledge gap, this study conducted a field trial on the SARS-CoV-2 presence in various wastewater facilities after the end of the COVID-19 epidemics in Beijing. The result showed that the wastewater treatment facility is a large SARS-CoV-2 repository. The viral RNA was still present in hospital sewage for 15 days and was continually detected in municipal WWTPs for more than 19 days after the end of the local COVID-19 epidemics. The T90 values of the SARS-CoV-2 RNA in raw wastewater were 17.17-8.42 days in the wastewater at 4 â„ƒ and 26 â„ƒ, respectively, meaning that the decay rates of low titer viruses in raw sewage were much faster. The results confirmed that the SARS-CoV-2 RNA could persist in wastewater for more than two weeks, especially at lower temperatures. The sewage systems would be a virus repository and prolong the presence of the residual SARS-CoV-2 RNA. The study could enhance further understanding of the presence of SARS-CoV-2 RNA in raw wastewater.

Relationship between daily physical activity and sleep quality among college students

Objective: To explore the relationship between daily physical activity and sleep quality among college students during COVID-19 epidemic, so as to provide scientific basis for improving physical health and sleep of college students.

Delta subvariants of SARS-COV-2 in Israel, Qatar and Bahrain: Optimal vaccination as an effective strategy to block viral evolution and control the pandemic (preprint)

Delta variant has rapidly become the predominant pandemic driver and yielded four subvariants (delta1, delta2, delta3 and delta4). Among them, delta1 has been mainly responsible for the latest COVID-19 waves in India, Southeast Asia, Europe and the USA. A relevant question is how delta subvariants may have driven the pandemic in the rest of the world. In both Israel and Qatar, mRNA-based vaccination has been rolled out competitively, but the outcomes are quite different in terms of controlling the recent waves resulting from delta variant. This raises the question whether delta subvariants have acted differently in Israel and Qatar. In both countries, delta variant was first identified in April 2021 and delta1 subvariant constituted ~50% delta genomes from April to May 2021. But the situation started to diverge in June 2021: In Israel, delta1 variant was encoded by 92.0% delta genomes, whereas this fraction was only 43.9% in Qatar. Moreover, a delta1 sublineage encoding spike T791I was identified in Israel but not Qatar. This sublineage accounted for 31.8% delta genomes sequenced in June 2021 and declined to 13.3% in October 2021. In August 2021, delta1 also became dominant in Qatar and a major sublineage encoding spike D1259H emerged. This sublineage has evolved further and acquired additional spike substitutions, including K97E, S255F, I693S, I712S, I1104L, E1258D and/or V1177I, in Qatar and other countries, such as Czech Republic, France and Mexico. Monthly distribution of the above sublineages suggests that the one from Qatar is much more of concern than that from Israel. Different from what was in Israel and Qatar, delta2 subvariant has also been important in Bahrain, whereas a delta2 sublineage encoding spike V1264L and A1736V of NSP3 was dominant in June 2021, but was gradually taken over by delta1 subvariant. These results suggest that delta1 and delta2 subvariants continue their evolution in different countries. The recent successful pandemic control in Israel, Qatar and Bahrain supports that delta1 and delta2 subvariants are still sensitive to timed vaccination, thereby urging the use of optimal immunity as a strategy to block SARS-COV-2 evolution and control the pandemic.

Delta-1 variant of SARS-COV-2 acquires spike V1264L and drives the pandemic in Indonesia, Singapore and Malaysia (preprint)

Since April 2021, delta variant of SARS-COV-2 has gradually overtaken all other variants and become a dominant pandemic driver around the world. It has evolved and yielded four subvariants: delta1, delta2, delta3 and delta4. While trying to understand how these subvariants drive the pandemic in Southeast Asia, I noticed that many d1 genomes from Indonesia encode an extra spike substitution, V1264L. Coincidentally, this confers an acidic dileucine motif because residues 1157-1262 are acidic and residue 1265 is leucine. Such a motif may affect subcellular trafficking of the resulting spike protein. Alarmingly, this V1264L-encoding delta1 subvariant (referred to as delta1L) has become the dominant pandemic driver in Indonesia, Singapore, Malaysia and East Timor. Moreover, it has acquired additional spike substitutions: L1234L in Singapore and D215Y/N in Malaysia. On the average, the resulting sublineages carry 46-48 mutations per genome, making them some of the most mutated variants identified so far. Moreover, a d1 sublineage from the United Kingdom has acquired V1264L along with spike Y145H and A222V, a signature substitution of a SARS-COV-2 clade that was a major pandemic driver in Europe during the summer of 2020. A222V improves an extensive hydrophobic interaction network at the N-terminal domain of spike protein and may make this sublineage more virulent than delta1 and delta1L. Some delta2 subvariant genomes identified in the United States of America and other countries also encode V1264L. Thus, V1264L is a recurrent spike substitution frequently acquired by d subvariants during convergent evolution. This recurrence also suggests that V1264L is one key mechanism by which d variant adopts to expand its ‘evolutionary cage.’

SARS-COV-2 δ variant drives the pandemic in India and Europe via two subvariants (preprint)

ABSTRACT SARS-COV-2 evolution generates different variants and drives the pandemic. As the current main driver, δ variant bears little resemblance to the other three variants of concern, raising the question what features future variants of concern may possess. To address this important question, I compared different variant genomes and specifically analyzed δ genomes in the GISAID database for potential clues. The analysis revealed that δ genomes identified in India by April 2021 form four different groups (referred to as δ1, δ2, δ3 and δ4) with signature spike, nucleocapsid and NSP3 substitutions defining each group. Since May 2021, δ1 has gradually overtaken all other subvariants and become the dominant pandemic driver, whereas δ2 has played a less prominent role and the remaining two (δ3 and δ4) are insignificant. This group composition and variant transition are also apparent across Europe. In the United Kingdom, δ1 has quickly become predominant and is the sole pandemic driver underlying the current wave of COVID-19 cases. Alarmingly, δ1 subvariant has evolved further in the country and yielded a sublineage encoding spike V36F, A222V and V1264L. These substitutions may make the sublineage more virulent than δ1 itself. In the rest of Europe, δ1 is also the main pandemic driver, but δ2 still plays a role. In many European countries, there is a δ1 sublineage encoding spike T29A, T250I and Q613H. This sublineage originated from Morocco and has been a key pandemic driver there. Therefore, δ variant drives the pandemic in India and across Europe mainly through δ1 and δ2, with the former acquiring additional substitutions and yielding sublineages with the potential to drive the pandemic further. These results suggest a continuously branching model by which δ variant evolves and generates more virulent subvariants.

SARS-COV-2 δ variant drives the pandemic in the USA through two subvariants (preprint)

Delta variant of SARS-COV-2 has overtaken all other variants and become a dominant pandemic driver aggressively. In India, it has evolved and yielded delta1, delta2, delta3 and delta4 subvariants. Delta1 has also gradually become the dominant pandemic driver there and across Europe, raising the question whether this is true in other regions around the world. Here I demonstrate that delta1 has also become the dominant pandemic driver in the USA. In April and May 2021, alpha variant was the major pandemic driver, with Ida and gamma variants playing minor roles. Delta variant only started to emerge in April and May, but it rose exponentially and became a major driver one month later. By September, it was detected in ~99% COVID-19 cases and emerged as almost the sole pandemic driver. In the country, ~50% of its population was fully vaccinated in the summer of 2021; vaccination may have selected against all other variants and thereby helped delta variant achieve such an alarming status. One puzzling question is what genomic features make delta variant so highly competitive. Related to this, delta1, but not delta2, delta3 and delta4, has risen exponentially after May 2021, suggesting that unique NSP3 and nucleocapsid mutations that delta1 carries make it so competitive as a predominant pandemic driver. These results indicate that it is not delta variant per se , but its offspring, delta1, that makes delta variant a predominant pandemic driver. Alarmingly, delta1 subvariant has evolved further and gained additional mutations to finetune functions of spike, nucleocapsid and NSP3 proteins. Compared to delta1, delta2 subvariant is less important in driving the ongoing pandemic in the USA, but this subvariant has also evolved further and gained extra mutations. These results suggest a continuously branching model on delta variant evolution and reiterate urgent need to track and block the evolution.

SARS-COV-2 C.1.2 variant is highly mutated but may possess reduced affinity for ACE2 receptor (preprint)

SUMMARY SARS-COV-2 evolution generates different variants and drives the pandemic. As the current main driver, delta variant bears little resemblance to the other three variants of concern (alpha, beta and gamma), raising the question what features the future variants of concern may possess. To address this important question, I searched through the GISAID database for potential clues. While investigating how beta variant has been evolving in South Africa, I noticed a small group of genomes mainly classified as C.1.2 variant, with one-year old boy identified in March 2021 being the index case. Over 80% patients are younger than 60. At the average, there are 46-47 mutations per genome, making this variant one of the most mutated lineages identified. A signature substitution is spike Y449H. Like beta and gamma variants, C.1.2 possesses E484K and N501Y. The genomes are heterogenous and encode different subvariants. Like alpha variant, one such subvariant encodes the spike substitution P681H at the furin cleavage site. In a related genome, this substitution is replaced by P681R, which is present in delta variant. In addition, similar to this variant of concern, three C.1.2 subvariants also encode T478K. Mechanistically, spike Y449 recognizes two key residues of the cell-entry receptor ACE2 and Y449H is known to impair the binding to ACE2 receptor, so C.1.2 variant may show reduced affinity for this receptor. If so, this variant needs other mutations to compensate for such deficiency. These results raise the question whether C.1.2 variant is as virulent as suggested by its unexpected high number of mutations.

SARS-COV-2 γ variant acquires spike P681H or P681R for improved viral fitness (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) evolves and generates different variants through a continuously branching model. Four variants of concern have been the major pandemic drivers around the world. One important question is how they may evolve and generate subvariants, some of which may be even more virulent and drive the pandemic further. While investigating how {gamma} (or P.1) variant has been evolving, I noticed the spike substitution P681H in a group of genomes encoding a new subvariant, which has been designated P.1.7. This subvariant has become the dominant P.1 sublineage in Brazil, Italy, Spain and Peru, supporting that P681H confers evolutionary advantage to P.1.7. In Brazil and Peru, P.1.7 was still responsible for ~30% and ~40% cases, respectively, in August 2021. However, it has been competed out by {delta}1 (a {delta} subvariant) in both countries, Italy and Spain, suggesting that P.1.7 is not as virulent as {delta}1. In addition, 160 P.1 genomes possess a related substitution, P681R, and 120 of them encode a new subvariant, designated P.1.8. This P.1 subvariant carries two additional spike substitutions, T470N and C1235F, located at the receptor-binding pocket and cytoplasmic tail of spike protein, respectively. More P.1.8 genomes have been identified than P.1 genomes that encode P681R but not T470N and C1235F, suggesting that these two substitutions improve virulence of P.1.8 subvariant. Some P.1 genomes carry other substitutions (such as N679K, V687L and C1250F) that affect the furin cleavage site or cytoplasmic tail of spike protein. Thus, to improve viral fitness and expand its evolutionary cage, {gamma} variant acquires mutations to finetune the furin cleavage site and cytoplasmic tail of spike protein.

δ1 variant of SARS-COV-2 acquires spike V1176F and yields a highly mutated subvariant in Europe (preprint)

Genomic surveillance of SARS-COV-2 has revealed that in addition to many variants of interests, this virus has yielded four variants of concern, , {beta}, {gamma} and {delta}, as designated by the World Health Organization. Delta variant has recently become the predominant pandemic driver around the world and yielded four different subvariants ({delta}1, {delta}2, {delta}3 and {delta}4). Among them, {delta}1 has emerged as the key subvariant that drives the pandemic in India, Europe and the USA. A relevant question is whether {delta}1 subvariant continues to evolve and acquires additional mutations. Related to this, this subvariant has acquired spike V1176F, a signature substitution of {gamma} variant, and yielded a new sublineage, {delta}1F. The substitution alters heptad repeat 2 of spike protein and is expected to improve interaction with heptad repeat 1 and enhance virus entry. Moreover, there are {delta}1F sublineages encoding spike N501Y, A783, Q836E and V1264L. While N501Y is a signature substitution shared by , {beta}, {gamma} variants, V1264L is a key substitution in a {delta}1 sublineage that is a major pandemic driver in Southeast Asia. The Q836E-encoding lineage carries an average of 50 mutations per genome, making it the most mutated variant identified so far. Similar to {delta}1 subvariant, {delta}2 subvariant has also acquired spike V1176F and yielded new sublineages. Together, these results suggest that V1176F is a recurrent spike substitution that is frequently acquired by SARS-COV-2 variants to improve viral fitness. It is thus important to track the evolutionary trajectory of related variants for considering and instituting the most effective public health measures.

Bioinformatic analysis of SMN1-ACE/ACE2 interactions hinted at a potential protective effect of spinal muscular atrophy against COVID-19-induced lung injury.

Patients with spinal muscular atrophy (SMA) are susceptible to the respiratory infections and might be at a heightened risk of poor clinical outcomes upon contracting coronavirus disease 2019 (COVID-19). In the face of the COVID-19 pandemic, the potential associations of SMA with the susceptibility to and prognostication of COVID-19 need to be clarified. We documented an SMA case who contracted COVID-19 but only developed mild-to-moderate clinical and radiological manifestations of pneumonia, which were relieved by a combined antiviral and supportive treatment. We then reviewed a cohort of patients with SMA who had been living in the Hubei province since November 2019, among which the only 1 out of 56 was diagnosed with COVID-19 (1.79%, 1/56). Bioinformatic analysis was carried out to delineate the potential genetic crosstalk between SMN1 (mutation of which leads to SMA) and COVID-19/lung injury-associated pathways. Protein-protein interaction analysis by STRING suggested that loss-of-function of SMN1 might modulate COVID-19 pathogenesis through CFTR, CXCL8, TNF and ACE. Expression quantitative trait loci analysis also revealed a link between SMN1 and ACE2, despite low-confidence protein-protein interactions as suggested by STRING. This bioinformatic analysis could give hint on why SMA might not necessarily lead to poor outcomes in patients with COVID-19.

Previously unrecognized non-reproducible antibody-antigen interactions and their implications for diagnosis of viral infections including COVID-19 (preprint)

Antibody-antigen (Ab-Ag) interactions are canonically described by a model which exclusively accommodates non-interaction (0) or reproducible-interaction (RI) states, yet this model is inadequate to explain often-encountered non-reproducible signals. Here, by monitoring diverse experimental systems and confirmed COVID-19 clinical sera using a peptide microarray, we observed that non-specific interactions (NSI) comprise a substantial proportion of non-reproducible antibody-based results. This enabled our discovery and capacity to reliably identify non-reproducible Ab-Ag interactions (NRI), as well as our development of a powerful explanatory model ("0-RI-NRI-Hook four-state model") that is [mAb]-dependent, regardless of specificity, which ultimately shows that both NSI and NRI are not predictable yet certain-to-happen. In experiments using seven FDA-approved mAb drugs, we demonstrated the use of NSI counts in predicting epitope type. Beyond challenging the centrality of Ab-Ag interaction specificity data in serology and immunology, our discoveries also facilitated the rapid development of a serological test with uniquely informative COVID-19 diagnosis performance.