Li Wenliang, a face to the frontline healthcare worker? The first doctor to notify the emergence of the SARS-CoV-2 (COVID-19) outbreak

Dr Li Wenliang, who lost his life to the novel coronavirus, SARS-CoV-2, became the face of the threat of SARS-CoV-2 to frontline workers, the clinicians taking care of patients. Li, 34, was an ophthalmologist at Wuhan Central Hospital. On 30th December, 2019, when the Wuhan municipal health service sent out an alert, he reportedly warned a closed group of ex-medical school classmates on the WeChat social media site of “Seven cases of severe acute respiratory syndrome (SARS) like illness with links with the Huanan Seafood Wholesale Market” at his hospital. He was among eight people reprimanded by security officers for “spreading rumours”. In a tragic turn of events, he subsequently contracted SARS-CoV-2 and, after a period in intensive care, died on the morning of Friday 7th February, 2020 (South China Morning Post, 2020). This case is a stark reminder of the risks of emerging disease outbreaks for healthcare workers (HCWs). Dr Li Wenliang’s name is added to the long list of HCW that were at the forefront of outbreaks of SARS, Ebola, MERS and now SARS-CoV-2. It is important to recognise that it was the clinicians in Wuhan who sounded the alarm about the emergence of SARS-CoV-2 which was rapidly identified after these clinicians sent samples to a reference laboratory for next generation sequencing (NGS) (Zhou et al., 2020)

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Decoding the Impact of Genetic Variants in Gastric Cancer Patients Based on High-Dimensional Copy Number Variation Data Using Next-Generation Knowledge Discovery Methods

Objectives: Despite a reduction in the incidence and mortality rates of gastric cancer (GC), it remains the fifth most frequently diagnosed malignancy globally. A better understanding of the regulatory mechanisms involved in the progression and development of GC is important for developing novel targeted approaches for treatment. We aimed to identify a set of differentially regulated pathways and cellular, molecular, and physiological system development and functions in GC patients infected with H. pylori infection based on copy number variation (CNV) data using next-generation knowledge discovery (NGKD) methods. Methods: In this study, we used our previous CNV data derived from tissue samples from GC patients (n = 33) and normal gastric samples (n = 15) by the comparative genome hybridization (CGH) method using Illumina HumanOmni1-Quad v.1.0 BeadChip (Zenodo Accession No: 1346283). The variant effects analysis of genetic gain or loss of function in GC was conducted using Ingenuity Pathway Analysis (IPA) software. In addition, in silico validation was performed with iPathwayGuide software using high-throughput RNA sequencing (RNAseq) data (GSE83088) from GC patients. Results: We observed 213 unique CNVs in the control group, 420 unique CNVs in the GC group, and 225 common variants. We found that cancer, gastrointestinal diseases, and organismal injury and abnormalities were the three diseases or disorders that were most affected in the GC group. We also identified that the programmed cell death ligand 1 (PD-L1) cancer immunotherapy pathway, T-cell apoptosis, T-cell exhaustion, and Type 1 regulatory T-cell (Tr1 cells) specialization were dysregulated in GC patients. RNAseq data from GC patients showed that the PD-1/PD-L1 pathway was significantly upregulated in GC samples compared with controls. Conclusions: In conclusion, in the present study, we decoded differentially impacted GC-specific diseases and biological functions and pathways based on CNV data using NGKD methods that can be adopted to design personalized therapeutic approaches for patients with GC in a typical clinical milieu

IgY antibodies for the immunoprophylaxis and therapy of respiratory infections

Emergence of drug resistance among the causative organisms for respiratory tract infections represents a critical challenge to the global health care community. Further, although vaccination can prevent disease, vaccine development is impeded by several factors. Therefore, novel approaches to treat and manage respiratory infections are urgently needed. Passive immunization represents a possible alternative to meet this need. Immunoglobulin Y antibodies (IgYs) from the yolk of chicken eggs have previously been used against bacterial and viral infections in human and animals. Their advantages include lack of reaction with mammalian Fc receptors, low production cost, and ease of extraction. Compared to mammalian IgGs, they have higher target specificity and greater binding avidity. They also possess remarkable pathogen-neutralizing activity in the respiratory tract and lungs. In this review, we provide an overview of avian IgYs and describe their potential therapeutic applications for the prevention and treatment of respiratory infections

Delivery of siRNAs against MERS-CoV in Vero and HEK-293 cells: A comparative evaluation of transfection reagents

Background: A new coronavirus was identified in Jeddah, Saudi Arabia in 2012 and designated as Middle East Respiratory Syndrome Coronavirus (MERS-CoV). To date, this virus has been reported in 27 countries. The virus transmission to humans has already been reported from camels. Currently, there is no vaccine or antiviral therapy available against this virus. Methods: The siRNAs were in silico predicted, designed, and chemically synthesized by using the MERS-CoV-orf1ab region as a target. The antiviral activity was experimentally evaluated by delivering the siRNAs with Lipofectamine™ 2000 and JetPRIMER as transfection reagents in both Vero cell and HEK-293-T cell lines at two different concentrations (10.0 nM and 5.0 nM). The Ct value of quantitative Real-Time PCR (qRT-PCR) was used to calculate and determine the reduction of viral RNA level in both cell supernatant and cell lysate isolated from both cell lines. Results: The sequence alignment resulted in the selection of highly conserved regions. The orf1ab region was used to predict and design the siRNAs and a total of twenty-one siRNAs were finally selected from four hundred and twenty-six siRNAs generated by online software. Inhibition of viral replication and significant reduction of viral RNA was observed against selected siRNAs in both cell lines at both concentrations. Based on the Ct value, the siRNAs # 11, 12, 18, and 20 were observed to be the best performing in both cell lines at both concentrations. Conclusion: Based on the results and data analysis, it is concluded that the use of two different transfection reagents was significantly effective. But the Lipofectamine™ 2000 was found to be a better transfection reagent than the JetPRIMER for the delivery of siRNAs in both cell lines

Legionella saoudiensis sp nov., isolated from a sewage water sample

International audienceA Gram-stain-negative, bacilli-shaped bacterial strain, LS-1(T), was isolated from a sewage water sample collected in Jeddah, Saudi Arabia. The taxonomic position of strain LS-1(T) was investigated using a polyphasic taxonomic approach. Phylogenetic analysis based on 16S rRNA gene sequences and those of four other genes indicated that strain LS-1(T) belongs to the genus Legionella in the family Legionellaceae. Regarding the 16S rRNA gene, the most closely related species are Legionella rowbothamii LLAP-6(T) (98.6 %) and Legionella lytica L2(T) (98.5 %). The mip gene sequence of strain LS-1(T) showed 94% sequence similarity with that of L. lytica L2(T) and 93% similarity with that of L. rowbothamii LLAP-6(T). Strain LS-1(T) grew optimally at a temperature of 32 degrees C on a buffered charcoal yeast extract (BCYE) agar plate in a 5% CO2 atmosphere and had a flagellum. The combined phylogenetic, phenotypic and genomic sequence data suggest that strain LS-1(T) represents a novel species of the genus Legionella, for which the name Legionella saoudiensis sp. nov. is proposed. The type strain is LS-1(T) (= DSM 101682(T) = CSUR P2101(T))

Exploring plant-derived small molecules as inhibitors of Marburg virus RNA binding protein activity

The search for antiviral medications is greatly influenced by the hunt for potent inhibitors of viral proteins. To find possible inhibitors of the RNA binding activity of the Marburg virus VP35 protein, we used a thorough in silico drug discovery approach in this investigation. A comprehensive virtual screening process, followed by a detailed MMGBSA analysis, led to the discovery of four potential inhibitory compounds viz. Kudzuisoflavone A, Miquelianin, Rutin, and Protopseudohypericin. They were identified from an extensive library of phytomolecules derived from three medicinal plants: Adiantum capillus-veneris, Hypericum perforatum, and Pueraria montana. In molecular dynamics (MD) simulations, all these compounds showed steady binding to the target protein and favourable interactions. Notably, the free binding energies of all the selected compounds were better than the myricetin, a well-known blocker of the VP35 protein of the Ebola virus. Overall, this investigation offers insightful information about the molecular interactions and binding dynamics of the identified inhibitors’ binding to the VP35 protein of the Marburg virus. The findings highlight the potential of three particular medicinal plants as sources of key chemicals for the creation of brand-new Marburg virus antiviral drugs. More experimental validation and optimization of the identified inhibitors are necessary in order to transform these findings into effective medicines for treating Marburg virus infections. Communicated by Ramaswamy H. Sarma</p

Isolation of Yasminevirus, the First Member of Klosneuvirinae Isolated in Coculture with Vermamoeba vermiformis , Demonstrates an Extended Arsenal of Translational Apparatus Components

International audienc

Saudi Moumouvirus, the First Group B Mimivirus Isolated from Asia

International audienceThe number of novel giant viruses identified and characterized from the recently proposed order Megavirales has increased in recent years and new questions have been raised regarding viral diversity and evolution. Here, we describe the isolation and characterization of Saudi moumouvirus (SDMV), a new giant virus belonging to Mimivirus lineage B, isolated from a sewage sample taken from the King Abdulaziz University hospital in Jeddah, Saudi Arabia. SDMV presented 500 nm icosahedral particles with a 1,046,087 bp genome, which is larger than moumouvirus-like genomes which have been described in the past. The SDMV genome was predicted to encode 868 ORFs, ranging in size from 54 to 2,914 amino acids, with a mean size of 349 aa. Furthermore, this genome was predicted to encode 40 new genes (ORFans) without similarity with other sequences (ORFan L850 transcript was detected by qPCR in infected amoeba), in addition to 42 hypothetical proteins (pseudo-ORFs) with less than 100 aa, which matched other sequences in the NCBI nr database. Phylogenetic analysis showed that SDMV clustered together with mimiviruses from lineage B, including moumouvirus-like strains. It is, therefore, the third Mimivirus to be isolated in Asia and the first of group B

Exploration of Microbially Derived Natural Compounds against Monkeypox Virus as Viral Core Cysteine Proteinase Inhibitors

Monkeypox virus (MPXV) is a member of the Orthopoxvirus genus and the Poxviridae family, which instigated a rising epidemic called monkeypox disease. Proteinases are majorly engaged in viral propagation by catalyzing the cleavage of precursor polyproteins. Therefore, proteinase is essential for monkeypox and a critical drug target. In this study, high-throughput virtual screening (HTVS) and molecular dynamics simulation were applied to detect the potential natural compounds against the proteinase of the monkeypox virus. Here, 32,552 natural products were screened, and the top five compounds were selected after implementing the HTVS and molecular docking protocols in series. Gallicynoic Acid F showed the minimum binding score of −10.56 kcal/mole in the extra precision scoring method, which reflected the highest binding with the protein. The top five compounds showed binding scores ≤−8.98 kcal/mole. These compound complexes were tested under 100 ns molecular dynamics simulation, and Vaccinol M showed the most stable and consistent RMSD trend in the range of 2 Å to 3 Å. Later, MM/GBSA binding free energy and principal component analysis were performed on the top five compounds to validate the stability of selected compound complexes. Moreover, the ligands Gallicynoic Acid F and H2-Erythro-Neopterin showed the lowest binding free energies of −61.42 kcal/mol and −61.09 kcal/mol, respectively. Compared to the native ligand TTP-6171 (ΔGBind = −53.86 kcal/mol), these two compounds showed preferable binding free energy, suggesting inhibitory application against MPXV proteinase. This study proposed natural molecules as a therapeutic solution to control monkeypox disease