Gallbladder cancer (GBC) has a lower incidence rate among the population relative to other cancer types but is a major contributor to the total number of biliary tract system cancer cases. GBC is distinguished from other malignancies by its high mortality, marked geographical variation and poor prognosis. To date no systemic targeted therapy is available for GBC. The main objective of this study is to determine the molecular signatures correlated with GBC development using integrative systems level approaches. We performed analysis of publicly available transcriptomic data to identify differentially regulated genes and pathways. Differential co-expression network analysis and transcriptional regulatory network analysis was performed to identify hub genes and hub transcription factors (TFs) associated with GBC pathogenesis and progression. Subsequently, we assessed the epithelial-mesenchymal transition (EMT) status of the hub genes using a combination of three scoring methods. The identified hub genes including, CDC6, MAPK15, CCNB2, BIRC7, L3MBTL1 were found to be regulators of cell cycle components which suggested their potential role in GBC pathogenesis and progression. The incidence of GBC cases is highest in the Eastern Europe, East Asian country and Latin American regions, with the incidence ratio of GBC cases being the highest in South American countries such as Chile, Bolivia and Ecuador and Asian countries, mainly including Korea, India, Japan and Pakistan [The gallbladder is a small sac-like structure located beneath the liver that forms an integral component of the biliary tract system. Gallbladder cancer (GBC) is the sixth most frequent cancer of the gastrointestinal tract worldwide. GBC is an aggressive malignancy, with rapid progression, poor prognosis and a high mortality rate resulting in an overall 5-year survival rate of only 5% ,2. The iPakistan ,5.GBC is an orphan disease and its etiology is multifactorial. The pathological spectrum of GBC mainly progresses from metaplasia to dysplasia with subsequent carcinoma-in-situ and cancer metastasis suggesting that an epithelial mesenchymal transition (EMT) event might be an important phenomenon in GBC development. The detailed molecular mechanism of risk factors associated with GBC is not understood yet. There is no targeted therapy available for GBC treatment. Hence, understanding the pathogenesis of GBC is urgently needed ,7. DNA-bAt present, the most common approach for treating GBC is radical resection. However, the majority of patients with GBC cannot undergo surgical resection due to aberrant clinical manifestations. The symptoms become noticeable in cases where the cancer has already invaded the nearby organs. In such situations, non-surgical therapies such as chemo- and radiotherapy are the only options for treatment. According to the National Comprehensive Cancer Network, single-agent therapy, which includes fluoropyrimidine or gemcitabine-based treatment, and combination therapy regimen, which includes oxaliplatin, cisplatin and capecitabine are the two chemotherapeutic options for GBC patients but both of these are still undergoing clinical trials ,14,15,16In recent years, systems approach has been evolving as one of the most promising areas in biology and medicine. Systems-based multidisciplinary approaches can help to understand the complexity of biological systems, as well as contribute to the discovery of novel biomarkers for disease, drug targets and treatments. The advancement of high throughput next generation sequencing (NGS) strategies such as transcriptome sequencing has helped to generate benchmarked cancer-based datasets. Integrative analysis of such datasets using network systems biology approaches provided a basis for investigating biomolecules, and their pathological functions in malignancies. This can further help to determine their potential role in developing efficient cancer treatment strategies ,23. WeigTo this end, we have carried out analysis of GBC RNAseq dataset downloaded from NCBI-GEO database. We have identified the potential genes and TFs associated with GBC progression and pathogenesis through co-expression network analysis of normal and GBC samples followed by transcriptional regulatory network analysis. Functional enrichment analysis and EMT score calculation has also been carried out to identify crucial genes for GBC pathogenesis.A comprehensive and thorough search was conducted in the NCBI database for relevant RNA-seq dataset on GBC. The datasets were checked carefully to be considered for our study based on the following criteria: (i) the dataset must include case-control studies, (ii) the dataset must be paired end and (iii) the sequencing platform for generating the data and experimental protocol should be described in details. Based on the above-mentioned criteria, we selected GSE139682 from NCBI-GEO database (GEO). The dataset comprised of 20 samples in total obtained through resection surgery out of which 10 samples were of GBC tissues and 10 samples were from normal matched tissue.Homo sapiens (GRCh38). The mapped reads were quantified at the gene level to obtain the count matrix for each gene using featureCounts tool [p-adjusted value < 0.05.The GBC dataset was downloaded from NCBI-GEO database in the SRA format. The SRA reads for each sample were converted to fastq reads using fastq-dump. Quality check of the fastq files was done using FastQC. The reads after quality control were aligned using Hisat2  against nts tool . The DESnts tool  was usedThe gene co-expression network gives cluster of genes that are highly correlated. In comparison to other biological network analysis methods, differential co-expression networks can be used to build condition specific sub-networks . The sigZ-summary and medianRank gives overall significance of the preservation of a module based on degree and connectivity. The Z-summary preservation < 2 indicates no preservation, 2 ≤ Z-summary ≤ 10 suggests weak to moderate preservation, and Z-summary preservation > 10 implies strong preservation [Preservation analysis was performed to assess the non-preserved module between the cancer network and control network. The basic statistics behind module preservation is to evaluate the preservation of genes within a module by comparing a test network (cancer) with a reference network (control) . It is aervation p-value < 0.05.For interpreting the biological role of significant DEGs identified from non-preserved modules, functional enrichment and pathway analysis was performed using DAVID . The sigIn network concept, connectivity is generally considered as the degree of nodes in the network. In this study, we have used the intramodular connectivity approach for the screening of hub genes within weakly preserved modules. The intramodular connectivity measures the degree of each gene within a module. The criteria used for this study was to calculate the connectivity from the whole network  and the connectivity within modules (kWithin). This measure of connectivity is useful to determine the biologically significant modules by calculating the degree of genes within modules.STRING database (version 10.0)  was usedp-value cut off 10−4. The TG-TF interactions data along with their prediction scores were represented in the form of interactive network using the Cytoscape software [From the gene regulatory network (GRN) information regarding the regulatory interactions between transcriptional regulators and their target genes can be obtained . Transcrsoftware . ConsideEpithelial-mesenchymal transitions (EMTs) play a critical role in cancer, particularly in cancer metastasis, apoptotic inhibition, and therapeutic drug resistance, which ultimately effects the overall survival of cancer patients. In this study, we have quantified the EMT scores for each sample using three different scoring metrics—76 Gene Signatures (76Gs), Multinomial Logistic Regression (MLR) and Kolmogorov Smirnov test (KS) ,37,38. ITo identify the differentially expressed molecular signatures in GBC, we have carried out analysis of transcriptomic data from 10 tumor samples and 10 adjacent control samples of GBC patients. The resulting data were normalized, and the transformed data were visualized using dispersion and principal component analysis a,b. Two For performing differential gene co-expression network analysis, the log2 transformed gene expression values of significant 2980 DEGs for 10 GBC samples and 10 adjacent control samples identified through DESeq2 were considered. The differential co-expression networks for GBC and control conditions were constructed separately using WGCNA package in R. The co-expression network construction needs the selection of a soft thresholding power β for satisfying scale-free topology of the network. The soft-thresholding power β for GBC and control were 18 and 20, respectively . SubsequZ-summary and medianRank, which calculate the extent of preservation based on the connectivity of genes in each module. In this study, module preservation analysis was performed by the following approaches: (i) GBC vs. control, where the cancer data was considered as the test data and the reference data was the control data; (ii) control vs. GBC, in which the control data was considered as the test data and the GBC data was the reference data. The identification of non-preserved modules in both control and GBC networks has been represented in The module preservation analysis from differential co-expression network was performed to identify non-preserved modules in control and GBC condition using statistical measures- Z-summary—1.4, 1.1, 0.86 and medianRank—20, 18, 19 respectively . The weight of the potential candidate genes identified through intra-modular connectivity analysis is given in Subsequently, PPI networks for the genes in each of the non-preserved modules were constructed, as shown in p-value < 0.05 were considered for determining the important biological processes and KEGG pathways related to GBC progression. The functional annotation analysis identified that the module genes were mostly associated with cell cycle regulation processes, metabolic pathways and signal transduction processes. The top ranked significant biological processes and pathways are tabulated in The functional GO terms and pathways associated with the gene modules were identified using DAVID tool. The statistical significance of Out of the 2980 DEGs, 106 DEGs code for transcription factors (TFs). Considering these TFs as the source nodes and the DEGs (including the TFs) as the target nodes, we created a transcriptional regulatory network. The degree distribution did not follow a Poisson distribution  and hence, the network was not a random network. The topological parameters of the network such as clustering coefficient, path length, network assortativity were calculated using the R package igraph. The assortivity of the network was negative i.e., −0.1024318, meaning the nodes with higher degrees tend to interact with nodes of smaller degrees. This is in compliance with the observation that real-world networks tend to have negative assortivity . The degNext, we quantified the extent of epithelial-mesenchymal transition (EMT) that the GBC samples had gone through. We used three different algorithms  that score the degree of EMT in transcriptomic data—while higher KS and MLR scores indicate a more mesenchymal state, whereas a high 76GS score indicates a more epithelial phenotype . Based oGallbladder cancer is a fatal malignancy of the biliary tract system. Standard molecular screening of GBC is of the utmost necessity for detecting the onset of GBC at an early stage and to reduce the mortality rate of patients suffering from GBC. Next-generation sequencing techniques are being widely used in cancer-related studies. However, omics-based studies have been limited in GBC due to the rarity of the disease. The therapeutic strategies of GBC are also limited due to the lack of specific molecular targets. Hence, the main objective of this study was to identify important genes and TFs potentially related to GBC pathogenesis.To this end, we have used an integrative systems-based approach to identify hub genes  in GBC. Here we have analyzed a transcriptomic dataset consisting of 10 GBC and 10 adjacent control samples. In total, 2980 significant DEGs were identified in GBC samples compared to the controls. The identified DEGs were then used to construct differential gene co-expression networks and to determine significant co-expressed modules in both GBC and control samples. The functional annotations and KEGG pathway analysis were further evaluated to identify significant biological processes and pathways enriched in non-preserved modules. We analyzed and identified the hub transcription factors from significant DEGs that might have important role in gene regulation process during GBC development. The hub genes identified from the non-preserved co-expressed modules were largely associated with cell cycle machinery and signaling processes.The cell cycle machinery is a highly regulated and intricate process which governs cell growth, cell proliferation and cell division through its regulatory genes. Cell cycle regulatory molecule mostly involves growth-regulatory signaling proteins- CDK and CDKI and associated genes/proteins that check for any anomalies throughout the genome. Disruption in the regulation of cell cycle machinery/components are frequently observed in several malignancies where it contributed to malignant transformation and resistance to cancer drugs ,42. NumeDrosophila fly. It binds to the chromatin complex during S-phase of the cell cycle and also regulates the target genes of E2F-RB negatively that are necessary for S-phase initiation. L3MBTL1 was reported to be associated with breast cancer and myeloid leukemia including AML [The hub genes identified through differential gene co-expression networks analysis followed by PPIs analysis were directly or indirectly associated with components of the cell cycle system, apoptotic regulation and cell-cell adhesion process that ultimately give rise to uncontrolled cell proliferation and later on to a full bloom malignancy. The hub genes L3MBTL1, MAPK15, CCNB2 and CDC6 are crucial elements that act as a control system for coordinated regulation of cell cycle system. L3MBTL1 is known to be a potential tumor suppressor gene in ding AML ,49,50. Tding AML . MAPK15 ding AML ,53. CCBNding AML ,55. CDC6ding AML ,57. Aberding AML .ADAM18, a membrane anchored gene  of the ADAM family proteins regulates cell adhesion via interaction with integrins. It plays an important role in the release of biologically important ligands, such as tumor necrosis factor-alpha, epidermal growth factors, transforming growth factor-alpha, and amphiregulin . In humaALPPL2 belongs to the member of the ALPP alkaline phosphatases which are reported to be associated with tumor initiation. It was reported as a specific and targeted tumor cell surface antigen. It is significantly associated with gastric cancer and pancreatic cancer and also acts as a novel protein in pancreatic cancer ,63.BIRC7, a novel member of the IAP family, is found to be highly overexpressed in various cancer types. BIRC7 was found to be overexpressed in 66% of the cancers and to be absent in normal cells/tissues. The function of BIRC7 gene is mainly related to apoptotic regulation and signaling processes. The overexpression of BIRC7 in cancers is reported to be associated with cancer drug and radiotherapy resistance, disease recurrence and poor survival ,65. MoreWe observed that genes related to cell cycle regulatory and signal transduction processes were essential and significant in pathogenesis of GBC. The genes and TFs identified from the non-preserved modules may play key roles in the pathogenesis of GBC. The identified hub genes provided the basis for further in-depth studies for development of prognostic, diagnostic and therapeutic biomarkers. In summary, this study used differentially co-expression network analysis and transcriptional regulatory network analysis to identify key hub genes associated with GBC pathogenesis.


Surgical patients with coronavirus disease 2019 (COVID-19) are vulnerable to increased perioperative complications and postoperative mortality, independent of the risk for contracting COVID-19 pneumonia after endotracheal intubation for general anesthesia. The presumed root cause of postoperative infections, microvascular soft tissue injuries and thromboembolic complications is largely attributed to the profound immune dysfunction induced by COVID-19 as a result of complement activation and the “cytokine storm”. The empirical therapy with anti-inflammatory agents has been shown to attenuate some of the adverse effects of systemic hyperinflammation in COVID-19 patients. In addition, the proactive concept of “immunonutrition” may represent a new promising avenue for mitigating the complex immune dysregulation in COVID-19 and thereby reduce the rates of surgical complications and postoperative mortality. This letter provides a narrative summary of the current state-of-the-art in the field of immunonutrition as it pertains to surgical patient safety in COVID-19 patients. Postoperative mortality rates of surgical patients with coronavirus disease 2019 (COVID-19) have been shown to be dramatically increased compared to COVID-19 negative patients who undergo surgical procedures . The incThe mechanism of cellular infection by SARS-CoV-2 is depicted schematically in Fig. Immunonutrition is an evolving concept designed to improve the potential of modulating the immune system in at-risk patients by providing high-dose supportive nutrients during a phase of increased vulnerability, e.g. due to infection, trauma, or surgery –34. MicrAscorbic acid, commonly known as vitamin C, plays a vital role in regulating immune function and has been shown to support the innate and the adaptive immune system . VitaminVitamin D3  is historically known for its roles in calcium homeostasis and bone health, and also influences the innate and adaptive immune system by supporting antiviral mechanisms and attenuating inflammation , 45. DecThe discovery of the interaction between zinc and immune function dates back to the 1960’s . AlthougGlutamine is considered an essential amino acid in cases of catabolic disease and is the most abundant amino acid in the body and primarily found in skeletal muscle and the lungs , 55. GluOmega-3 fatty acids are polyunsaturated fatty acids consisting of both eicosapentaenoic (EPH) and docosahexaenoic (DHA) acids . PolyunsIn light of the limited specific treatment options for surgical COVID-19 patients who are at risk of high postoperative complication rates and adverse outcomes, supportive immunonutrition appears to represent a safe, feasible, cost-effective, and pragmatically intuitive concept to mitigate the perioperative inflammation and adverse effects related to immune dysfunction , 35. The


Psychological factors can influence susceptibility to viral infections. We examined whether such influences are evident in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.Participants (n = 102) completed measures of anxiety, depression, positive mood, and loneliness and provided a blood sample for the measurement of antibodies to the SARS-CoV-2 spike and nucleocapsid proteins.SARS-CoV-2 was significantly negatively associated with anxiety and depression. The model remained significant after adjustment for age and gender, although anxiety and depression were no longer significant independent predictors.These findings offer early support for the hypothesis that psychological factors may influence susceptibility to SARS-CoV-2 infection. Risk of SARS-CoV-2 seropositivity is associated negatively with anxiety and positively with depression. The least anxious may be more likely to engage in behaviors that increase risk of exposure and infection, whereas depression may be secondary to the original infection. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus 2019 (COVID-19) infection, has proven to be a pernicious adversary. At the time of writing, the virus has resulted in an estimated 150 million infections and over 3 million deaths worldwide. However, what factors determine susceptibility to the infection? Previous research with other respiratory viruses suggests psychological and social factors may also influence susceptibility to the infection [This previous work suggests that several of the psychological and social consequences of the SARS-CoV-2 pandemic  may also have implications for an individual’s risk of contracting SARS-CoV-2. To examine this hypothesis, we conducted an exploratory observational study in which we investigated the relationship between COVID-19 infection (as indicated by the presence of antibodies to the SARS-CoV-2 spike and nucleocapsid proteins) and psychological factors previously shown to be associated with disease susceptibility  and known to have been affected by the pandemic .Eligibility criteria specified that participants should be aged 18 or over. Participants were staff and students at a higher education institution in the United Kingdom participating in the institution’s COVID-19 surveillance program. Participants were recruited through word of mouth and a campus-wide campaign and participation was voluntary. All participants were recruited between March 12, 2020 and February 17, 2021. Because the present sample was recruited opportunistically alongside the COVID-19 surveillance program and the research was exploratory and hypothesis-generating, no sample size target was set a priori.As part of the COVID-19 surveillance program, participants who agreed to antibody testing received a finger-prick blood sample kit including a disposable lance, a barcoded 10-µL Mitre sampling stick (Neoteryx), and sampling instructions. Dried blood samples were assayed for immunoglobulin (Ig)G antibodies to SARS-CoV-2 spike and nucleocapsid proteins using enzyme-linked immunosorbent assay, and all assays were performed on Opentrons OT-2 Precision liquid handling robots. Methods have been reported previously . Seroposhttps://www.onlinesurveys.ac.uk/) that captured the following: demographic information ; and COVID-19 testing history and psychological constructs previously associated with an individual’s risk of contracting a viral infection, ie, depression . Summary statistics were calculated for the total group of participants and split by seropositivity status using counts and percentages and means (with standard deviations) or medians (interquartile range) as appropriate. Anxiety and depression scores were also dichotomized according to established thresholds for diagnosis of “caseness”  [We convened a virtual Patient and Public Involvement Group to support this research. Individuals participated via Microsoft Teams in one-to-one or group discussions that informed the length and structure of the survey  and language of the information sheet .Ethical approval was granted from the University of Nottingham Faculty of Medicine and Health Sciences Ethics Committee (reference number 96-0920).All participants received a participant information sheet outlining the nature of the research and completed an online consent form.Severe acute respiratory syndrome coronavirus 2 antibody status and survey data were available for N = 102 individuals. Of these, N = 85 (83%) were seronegative and N = 17 (17%) were seropositive (as indicated by serum levels of IgG antibody to SARS-CoV-2 spike and nucleocapsid combined). Of participants who reported a previous positive COVID-19 test result (N = 7), the average number of days since their test was 74 days . A summary of the characteristics of the whole cohort and according to seropositivity status is shown in The results from the first step of the multivariable logistic regression model suggested that the likelihood of being seropositive was significantly associated with anxiety and depression: with the likelihood being 23% lower per unit increase in anxiety , and 27% higher per unit increase in depression . After adjusting for age and gender, anxiety and depression were no longer significant independent predictors of seropositivity. Although the overall model remained statistically significant, the direction of the relationships remained unchanged and the effect on ORs was modest see .To our knowledge, this is the first reported analysis of the relationship between psychological factors and SARS-CoV-2 seropositivity. Our findings suggest that psychological factors may be related to the likelihood of SARS-CoV-2 infection, with our unadjusted analyses suggesting that lower levels of anxiety, and higher levels of depression, are significantly and independently associated with SARS-CoV-2 seropositivity. Several issues are worthy of further discussion.First, our approach was predicated on antibody seropositivity being an established surrogate indicator for recent infection with SARS-CoV-2, ie, it is unlikely that someone would be seropositive for SARS-CoV-2 and have not previously been infected with the virus. Our primary analysis is consistent with this assumption. However, it is important to acknowledge several factors that can confound this relationship. First, antibodies are less likely to be detectable several months after natural infection . This meA second issue concerns the direction of the relationship between anxiety and seropositivity. This initially seems to be counterintuitive and contrary to previous work that has more commonly shown that negative moods are positively associated with risk of infection. This more expected relationship relates to negative emotions altering biological or behavioral pathways that lead to immune dysregulation and, in turn, increased disease risk . We hypoA third issue concerns the fact that individuals seropositive for SARS CoV-2 tended to also have higher depression scores. The presence of antibody indicates recent infection, with antibody levels usually detectable within a few weeks of infection and persisting for between 2 and 8 months , dependiFinally, in further post hoc analyses, we included an interaction term to capture the interaction between anxiety and depression and explore its relationship to seropositivity . HoweverIn conclusion, we acknowledge some potential methodological limitations. First, both the sample size and infection rate reported here are modest. This means that only relatively large effect sizes could have been reliably detected as being statistically significant. Therefore, it is important that these results are seen as hypothesis-generating and requiring replication. Second, our study design does not allow us to elucidate the temporal relationship between our psychological risk factors and SARS-CoV-2 infection. All scales asked respondents to indicate their experiences in the previous 2 weeks, and although antibody seropositivity indicates recent infection, we cannot be certain about when the infection occurred. Thus, we are, at best, describing cross-sectional relationships from which the causal direction cannot be determined.Notwithstanding these considerations, these findings suggest that psychological factors may play a role in determining SARS-CoV-2 infection. Specifically, we have observed an inverse relationship between anxiety and SARS-CoV-2 seropositivity, which we hypothesize may be indicative of a behavioral pathway in which the least anxious individuals increase their risk of infection through engaging in more risk-taking behaviors or less engagement with protective behaviors.The Journal of Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.Supplementary materials are available at jiac006_suppl_Supplementary_MaterialClick here for additional data file.


COVID-19 has become a global health concern, due to the high transmissible nature of its causal agent and lack of proper treatment. Early diagnosis and nonspecific medical supports of the patients appeared to be effective strategy so far to combat the pandemic caused by COVID-19 outbreak. Biomarkers can play pivotal roles in timely and proper diagnosis of COVID-19 patients, as well as for distinguishing them from other pulmonary infections. Besides, biomarkers can help in reducing the rate of mortality and evaluating viral pathogenesis with disease prognosis. This article intends to provide a broader overview of the roles and uses of different biomarkers in the early diagnosis of COVID-19, as well as in the classification of COVID-19 patients into multiple risk groups. COVID-19 outbreak has become a global public health issue and brought the world to a standstill . COVID-1SARS-CoV-2 follows a lytic cycle to replicate itself by employing the metabolic machinery of a cell. It invades a human host cell through five significant steps – attachment, penetration, biosynthesis, maturation and release  15,16].,16.15,16Once entered, the viral genome is released, which ultimately leads to the translation of viral polymerase protein. After the translation process, RNA replication takes place. It is then followed with subgenomic transcription and translation of viral structural proteins. S-protein, membrane protein and envelope protein combined with the nucleocapsid. Ultimately, mature virion is formed and exocytosis occurs .A cytokine storm – a physiological phenomenon where the immune system releases excessive level of cytokines – can be observed in COVID-19 following the release of genomic RNA into the cytoplasm. Toll-like receptors, such as TLR-3 and TLR-4, are triggered when double-stranded DNA induces an immune response. While TLR-3 uses a signaling pathway cascade to stimulate type-I interferon, TLR-4 recruits immune cells in the infection site through the activation of pro-inflammatory cytokines ,22.A cytokine storm is the result of a sudden acute increase in circulating levels of pro-inflammatory cytokines, including IL-6, IL-1, TNF-α and interferon. This ultimately leads to the influx of several immune cells like macrophages, T cells and neutrophils into the site of infection. Moreover, the elevated cytokine release, specifically the IL-6 stimulation, leads to an increased level of synthesis of prototypic acute phase reactant like C-reactive protein (CRP) from the liver, in the bloodstream. Eventually, all these events lead to different sequalae like destabilization of endothelial cell-to-cell interaction, destruction of capillary and vascular barrier and damage of multiple organs and tissues, which may ultimately lead to the demise of the infected individual .Another potential receptor for viral infection is DC-SIGN, expressed highly in dendritic cells (DCs) and macrophages. However, further studies need to be conducted for it to be confirmed .A clinical presentation of COVID-19 has several overlapping features with other pulmonary infections including pneumonia, chronic bronchitis and so on . PneumonCOVID-19 patients had a lower proportion of basophils (BASP), lymphocyte count (LYM) and white blood cell count (WBC) compared with the patients with other pulmonary diseases . The mosIt was also found that some of the coagulation parameters were different between these two groups as well. COVID-19 patients having relatively lower PT and INR and relatively higher PTA indicate that they were subjected to higher coagulation. Higher coagulation has the potentiality to blunt inflammation, which could explain why clinical inflammation symptoms are not obvious in COVID-19 patients ,32,33. SProcalcitonin (PCT) is the precursor of the hormone calcitonin, involved in regulating the levels of calcium and phosphate in the bloodstream . PCT hasThe increased concentration of IFN-γ in response to viral infections can inhibit the production of PCT. It is therefore expected that PCT values should remain within the minimum range in patients with noncomplicated COVID-19 infection . NeverthC-reactive protein (CRP), an acute-phase inflammatory protein synthesized primarily by the liver, plays a crucial role in the innate immunity. CRP is a significant indicator of severity in COVID-19 . In normCRP levels are also reported positively correlated with lung lesion during the early stages of SARS-CoV-2 infection . High CRSerum amyloid A or SAA protein, synthesized primarily by the liver, plays an important role in the body's inflammatory responses and lipid metabolism. Amyloid A is also known for its function in central nervous system and its association with multiple neurodegenerative disease has already been postulated. However secreted small amount during the normal conditions of the body, but the SAA levels are elevated during the acute phase of an inflammatory disease due to the stimulated inflammatory mediators including IL-1, IL-6, TNF-α . Thus, SSeveral studies have reported that SAA can be used as an independent predictive biomarker of COVID-19 ,71. An iThe precise mechanism for the elevated release of this acute-phase protein is still unclear, but could be influenced by the increased production and secretion of inflammatory mediators, a characteristic phenomenon of SARS-CoV-2 infection . SAA wasIL-6 is one of the most important cytokines that is produced in response to infections and tissue damages and plays a crucial role in the host immune defense mechanism. It is mostly synthesized during the initial stage of inflammation and then moves to the liver to rapidly induce the secretion of a huge range of acute-phase proteins . As a maMultiple studies have reported a significant difference in the IL-6 levels between complicated and non-complicated COVID-19 cases. It was reported that IL-6 levels were around three-times higher in the severe COVID-19 patients than the non-severe patients ,66. HighAcute respiratory distress syndrome (ARDS) generates a cytokine storm by eliciting the overproduction of many inflammatory mediators including IL-6, and contributes to the mortality and severity of a COVID infection. In COVID-19 patients, the overproduction of IL-6 was found to be linked with complicated outcomes, such as hepatic, renal, cardiac and lung injuries . At presLymphocytopenia (ALC = <1000 cells/μl blood) is a common systemic manifestation of many immunodeficiencies and viral infections . Previou+ and CD8+ cell count was seen to contribute to a reduction in the severity of the disease , bu, bu98], D-Dimer may serve as an indicator for severe viral infection as a viral infection is likely to develop into sepsis and induce coagulation dysfunction, which in turn can serve as a common representation of severe disease progression. Moreover, the cytokine storm generated during a COVID-19 infection can recruit several inflammatory and proinflammatory mediators to create an imbalance in the coagulation process and fibrinolysis, ultimately elevating the level of D-Dimer in patients . In a coLactate dehydrogenase (LDH) is an intracellular glycolytic enzyme implicated in the conversion of lactate to pyruvate and is present in higher amounts in almost all the body cells. It is considered as an inflammatory marker and may serve as a common indicator of acute or severe tissue damage . It has Elevated serum LDH levels have been attributed to increased disease severity and a higher risk of in-hospital COVID-19 mortality. A recent pooled analysis showed a >sixfold increase in odds of developing severe COVID-19 infection outcomes and a >16-fold increase in odds of mortality in patients with high levels of LDH  108–110108–110. Cytokine-mediated lung tissue damage, which is a primary feature of severe SARS-CoV-2 infection, may be responsible for the elevated release of LDH . The greCardiac troponins are a group of cardiac regulatory proteins that control muscular contraction and may serve as an indicator to detect heart muscle injury. Cardiac troponin is still the only standard biomarker for the detection of acute myocardial infarction. The onset of myocardial infarction is demonstrated by an elevated level of cardiac troponin . HoweverCardiac troponin I (cTnI) was found to be marginally increased in the mild severe patients and significantly higher in severe COVID-19 patients . A consiSeveral mechanisms may explain this phenomenon of elevated cardiac troponin in severe COVID-19 patients. ACE-2 is highly expressed in the pericytes of the human heart tissues, which allows SARS-CoV-2 to directly enter the heart cells and cause severe damage . The virFerritin, an iron-storing protein, is a key mediator of immune dysfunction. Serum ferritin is an indicator of inflammation, released by the damaged cells, but whether the presence of this protein in serum is usual or not has yet to be ascertained . ResearcHigher ferritin levels in COVID-19 are not exclusively driven by SARS-CoV-2 infection; it may also occur due to other inflammatory diseases or several inflammatory cytokines such as IL-6 . MoreoveAlthough the SARS-CoV-2 primarily damages the lung tissues and generates symptoms of acute respiratory failure, it has been found to enter the bloodstream and accumulate in several other organs causing secondary organ damage . Among tVarious degrees of renal dysfunction have been reported in COVID-19 patients, characterized by increased levels of blood urea nitrogen (BUN) and serum creatinine . A studyOne possible explanation of the high incidence of AKI in COVID-19 patients may be related to the mechanism of SARS-CoV-2 entrance in cells. Renal tubular epithelial cells have a high expression of ACE-2 protein, the receptor that binds to and facilitates viral entrance in cells . The higBesides these, a number of other biomarkers can be considered for the diagnosis of COVID-19. Different types of viral protein-coding genes can be used in the appropriate diagnosis of COVID-19 patients. In fact, the most commonly used reverse transcriptase polymerase chain reaction (RT-PCR) technology utilizes the polymerization reaction of different genes of SARS-CoV-2 involved in the expression of structural and nonstructural proteins. These genes are predominantly involved in the expression of spike protein (S), membrane protein (M), nucleocapsid protein (N), RNA-dependent RNA polymerase (RdRp) and so on. Use of nasopharyngeal or oropharyngeal swab of infected patients is enough to extract and amplify the above-mentioned viral genes when using RT-PCR technology for COVID-19 diagnosis ,145. LosVitamin D is an important regulator of host inflammatory and immune response. Recent studies showed that a decreased level of 25 hydroxyvitamin D or 25(OH)D has been associated with the severity of COVID-19. It has been reported that hospitalized COVID-19 patients with vitamin D deficiency experienced a higher risk of developing ARDS compared with patients with normal vitamin D levels . HealthySerum IgA, IgG and IgM immunoglobulins that are produced by the host immune system in response to SARS-CoV-2 infection could serve as a potential biomarker in COVID-19 diagnosis. A recent study demonstrated that IgA levels reached the peak value during the initial 16–20 days after disease onset and then began to decline but continues to remain at relatively high value for a considerable period, IgG level was initially low but started to rise at 15 days after disease onset and stayed at a relatively high value for a considerable period, and IgM levels peaked at early stage, but the reading was comparatively lower than IgA and IgG . OverallSome epidemiological studies suggest that one of the major predictors of COVID-19 severity is age, pre-existing disease conditions and habits associated with an unhealthy lifestyle . So, bioDue to the contagious nature of the virus and lack of any specific approved treatment, it becomes important to ensure early stratification of the infected patients to reduce the risk of transmission among susceptible groups as well as to allocate optimal resources to the patients who are in severe condition. Biomarkers can play a significant role by facilitating timely diagnosis, risk monitoring and directing the optimal treatment of COVID-19 patients. Based on the aforementioned promising evidences, it is apparent that biomarkers are essential to optimize the COVID-19 prognosis and hereby to minimize the mortality rates. However, individual variation among patients in biomarker levels may interrupt the optimal interpretation of disease prognosis. Therefore, further studies must be conducted to evaluate and identify best potential biomarker for COVID-19 diagnosis.The severe global crisis generated by the highly contagious SARS-CoV-2 has affected over 103 million people and has resulted in around 2.24 million deaths worldwide. The spread of the virus is so swift that the general population, healthcare professionals and regulatory authorities from different countries have employed vastly different, but effective strategies to battle against the virus. In this situation, early diagnosis and effective management of the infected population are critical. Biomarkers can play a key role in this regard by ensuring the efficient diagnosis as well as guiding improvements in the clinical management of patients with COVID-19. More significantly, the use of biomarkers can aid the development and approval of biological agents and therapeutics in addition to evaluating COVID-19 pathogenesis and accessing disease prognosis. Although research is still in its early stages, the characteristic features of different biomarkers during the disease progression could help categorizing and understanding the underlying disease pathomechanism. Moreover, the identification of efficient biomarkers can also assist in predicting future complications or severity of the disease. In addition, the identification of integral biomarkers of the SARS-CoV-2 may facilitate a much more robust response against future respiratory viral outbreaks with the potential of creating global pandemics. The accumulated knowledge regarding SARS-CoV-2 infection biomarkers might be utilized to generate a much more efficient resource allocation in tackling future outbreaks and pandemics and more research works are warranted in this regard.Biomarkers can play a significant role in the early diagnosis and differentiation of SARS-CoV-2 infection from other pulmonary infections exhibiting almost similar symptoms.SARS-CoV-2 invades a human host cell through five significant steps – attachment, penetration, biosynthesis, maturation and release.Clinical presentation of chronic obstructive pulmonary disease (COPD) and SARS-CoV-2 infected patients are quite similar which makes it difficult to distinguish the symptoms. Biomarkers have proven to be effective in differentiating between these two classes of patients. The most determining biomarkers between these two groups are BASP, PTA, PT and INR. Some of the coagulation parameters were different between these two groups as well.PCT values were expected to remain within the minimum range in patients with noncomplicated COVID-19 infection as the increased concentration of IFN-γ can inhibit PCT production. Nevertheless, PCT levels were reported to be increased among severe COVID-19 patients, which may be attributed to viral-induced lung tissue damage and bacterial translocation, resulting in bacterial coinfection.Under normal conditions, the concentration of CRP in the blood is less than 10 mg/l, but the concentration may increase up to 1000-fold, serving as a significant indicator of COVID-19 infection severity.SAA levels are significantly increased in severe COVID-19 patients. Studies suggest that SAA can be used as an independent predictive biomarker of COVID-19. The expression level is significantly higher in acute phase infection compared with the convalescent phase infection.IL-6 levels are around three-times higher in the severe COVID-19 patients than the nonsevere patients and can also be linked to higher mortality rates.Lymphocytopenia is associated with a threefold increased risk of disease severity in SARS-CoV-2 infection. The average ALC count is reported to be significantly lower in COVID-19 patients requiring ICU admission compared with patients who do not require ICU admission.Thrombocytopenia can be linked to different cardiovascular events like venous and arterial thrombosis that are highly prevalent as comorbid conditions in COVID-19 patients. Besides, the lower levels of platelets and associated events can eventually lead to multiorgan failure and death of the infected individual.Elevated D-Dimer levels might serve as an indicator for severe COVID-19 infection as the cytokine storm-generated during the viral pathogenesis can recruit several inflammatory mediators to create an imbalance of the coagulation process and fibrinolysis resulting in enhanced D-Dimer secretion.A recent pooled analysis showed a >sixfold increase in odds of developing severe COVID-19 infection outcomes and a >16-fold increase in odds of mortality in patients with elevated levels of LDH suggesting LDH as an effective biomarker to mark disease severity. Besides, this biomarker can also be used as a predictor of comorbid cardiovascular events in COVID-19 patients.High cardiac troponin levels are reported in COVID-19 patients, especially those suffering from cardiac injury or having previous history of cardiovascular diseases.Apart from these, major biomarkers like serum ferritin, AKI indicators, serum immunoglobulins, vitamin D levels, biological age, and loss of smell and taste can also be considered as crucial biomarkers in detecting and accessing COVID-19 disease severity.


Lung sounds remain vital in clinical diagnosis as they reveal associations with pulmonary pathologies. With COVID-19 spreading across the world, it has become more pressing for medical professionals to better leverage artificial intelligence for faster and more accurate lung auscultation. This research aims to propose a feature engineering process that extracts the dedicated features for the depthwise separable convolution neural network (DS-CNN) to classify lung sounds accurately and efficiently. We extracted a total of three features for the shrunk DS-CNN model: the short-time Fourier-transformed (STFT) feature, the Mel-frequency cepstrum coefficient (MFCC) feature, and the fused features of these two. We observed that while DS-CNN models trained on either the STFT or the MFCC feature achieved an accuracy of 82.27% and 73.02%, respectively, fusing both features led to a higher accuracy of 85.74%. In addition, our method achieved 16 times higher inference speed on an edge device and only 0.45% less accuracy than RespireNet. This finding indicates that the fusion of the STFT and MFCC features and DS-CNN would be a model design for lightweight edge devices to achieve accurate AI-aided detection of lung diseases. The term lung sounds refers to “all respiratory sounds heard or detected over the chest wall or within the chest” . In clinWhile a variety of lung sound types have been defined by recent research, this paper adopts the classification suggested by Pasterkamp et al. . Lung soLearning-based algorithms, particularly deep learning algorithms, have been driving the development of remote automatic lung sound auscultation in recent years . A convoHowever, the standard CNN models require graphics processing units (GPUs) to support the vast convolutional operations. The depthwise separable (DS) convolution is an approach to reduce the computational operations of the standard convolution . These CThis paper aims to propose a feature engineering process to extract the dedicated features for DS-CNN to classify four types of lung sounds: normal, continuous, discontinuous, and unknown. We shrank a DS-CNN model based on MobileNet  to save The dataset for this research was prepared after preprocessing the acoustic recordings collected by Lin et al. . These WOur feature engineering process was derived from reference . Fusing STFT transforms only the fast-varying part of the signal, which corresponds to the high-frequency domain, and preserves the low-varying trend in the time domain. For a signal sequence w(n) is a window function with the window size L, L, represents the number of samples included in each window when computing the fast Fourier transform , of the 4 × 4 confusion matrix, M, indicates that M samples are predicted to be label j but are indeed label i. The overall accuracy is defined asHere an element, The results of level 1 to level 3 comparison examined our method’s performance across features, model architecture, and levels of inference efficiency on edge devices. The results of level 3 comparison are shown in The confusion matrices of level 1 and level 3 comparisons are shown in The shrunk DS-CNN model performance substantially increased when the model was trained with the fused features of STFT and MFCC. The STFT and MFCC features may complement each other because the MFCC feature represents human auditory perception more closely. Therefore, some acoustic distinctions between different types of lung sounds may be enhanced by the MFCC feature. The fused features of STFT and MFCC extracted from the proposed feature engineering process contributed to the shrunk DS-CNN model’s high accuracy compared with model architectures. Moreover, all CNN-based models outperformed RNN-based models in terms of accuracy. The results of level 2 comparison indicate that the fused features that we extracted are appropriate for DS-CNN-based models. CNN-based models were originally designed for image recognition tasks, whereas RNN-based models were designed for learning the features of sequences. The STFT and MFCC features can resemble either images or multi-dimensional time-series data. However, we fine-tuned the fused features based on DS-CNN-based models rather than RNN-based models. There is inevitably a trade-off between frequency resolution and time resolution when extracting STFT and MFCC features. The demand for frequency or time domain resolution may depend on the model architectures. Hence, the appropriate features for DS-CNN-based models may not have enough time domain resolution for the RNN-based models. Additionally, the proposed feature engineering process can be employed to extract the appropriate features for any other model architectures. Likewise, the lung sound can be replaced by other sound types, such as heart sounds.Compared with RespireNet, our method provided a smaller-sized model, higher inference speed, and comparable model performance. This result presents a trend similar to the study of respiratory sound classification in wearable devices . As obseThe model training process adopted by the original RespireNet is consistent with many previous studies ,21,25. TFurthermore, a possible explanation for our method achieving lower evaluation indexes of the unknown lung sound might be that there is no data augmentation adopted through model training. The unknown lung sound dataset is not as large as any other three types of lung sound dataset. The data augmentation technique originally proposed by RespireNet to handle the data imbalance issue of the ICBHI dataset may lead to better performance for recognizing the unknown lung sounds.Autonomous stethoscopes developed by integrating AI-algorithm into portable digital stethoscopes have been proposed by Glangetas et al. . PortablWe have proposed a feature engineering process to extract dedicated features for the shrunk DS-CNN to classify four types of lung sounds. We observed that fusing the STFT and MFCC features led to a higher accuracy of 85.74%. In contrast, the model trained on only one STFT or MFCC feature achieved the accuracies of 82.27% and 73.02%, respectively. We then evaluated our method by comparing it with RespireNet. While RespireNet was 0.43% better than our method in terms of accuracy, our method achieved 16 times higher inference speed on the edge device.To summarize, these results support the idea that DS-CNN may perform nearly as accurately as standard CNN by training with appropriate features. The feature engineering process that we have proposed can be applied to the extraction of dedicated features for other types of sound signals or for other architectures of deep learning models. However, we did not use any data augmentation techniques in this study. Further research might explore how data augmentation techniques affect the performance of sound recognition models.


To evaluate the role of language proficiency and institutional awareness in explaining excess COVID-19 mortality among immigrants.Cohort study with follow-up between 12 March 2020 and 23 February 2021.Swedish register-based study on all residents in Sweden.3 963 356 Swedish residents in co-residential unions who were 30 years of age or older and alive on 12 March 2020 and living in Sweden in December 2019.Cox regression models were conducted to assess the association between different constellations of immigrant-native couples  and COVID-19 mortality and all other causes of deaths (2019 and 2020). Models were adjusted for relevant confounders.Compared with Swedish-Swedish couples (1.18 deaths per thousand person-years), both immigrants partnered with another immigrant and a native showed excess mortality for COVID-19 , which translates to 1.37 and 1.28 deaths per thousand person-years. Moreover, similar results are found for natives partnered with an immigrant , which translates to 1.29 deaths per thousand person-years. Further analysis shows that immigrants from both high-income and low-income and middle-income countries (LMIC) experience excess mortality also when partnered with a Swede. However, having a Swedish-born partner is only partially protective against COVID-19 mortality among immigrants from LMIC origins.Language barriers and/or poor institutional awareness are not major drivers for the excess mortality from COVID-19 among immigrants. Rather, our study provides suggestive evidence that excess mortality among immigrants is explained by differential exposure to the virus. This study uses total population data with all deaths (from COVID-19 and other causes) in Sweden from 12 March 2020 to 23 February 2021.We identified the origin of co-resident couples to evaluate the role of language proficiency and institutional awareness  in explaining excess COVID-19 mortality among immigrants.We compare COVID-19 mortality with all other causes of death during the pandemic and all-cause mortality 1 year prior to evaluate the relative impact of the pandemic within each group.The analyses do not include information on occupation, however the most vulnerable individuals are beyond retirement age.International evidence has shown that immigrants and ethnic minorities are disproportionately at risk of severe COVID-19 complications and death.in lieu of mandates which are not permitted under Swedish law.Sweden took a distinct approach to dealing with the COVID-19 pandemic as compared with other Western countries by not implementing lock downs or mask mandates and instead relied largely on recommendations. The authorities justified implementing a relatively less rigid approach by arguing that Swedes have a high level of trust in their institutions and as such follow governmental recommendations.More specifically, it has been argued that immigrants may, as a result of inadequate language proficiency and institutional awareness, have a poor understanding of the healthcare system and of the recommendations during the COVID-19 pandemic putting them at higher risk of exposure and vulnerability to the virus. Analysing intermarried immigrants present a unique opportunity to generate evidence for this explanation.Within the field of immigrant integration, intermarriage has been considered the ultimate stage of acculturationin primis) explain the excess mortality, immigrants partnered with a Swede and, in particular, Swedes partnered with an immigrant should have similar mortality to Swedes partnered with a Swede. To this end, the aim of this study is to examine the association between sociocultural integration and COVID-19 mortality by examining native-immigrant couple dyads—a well-regarded measure that has been shown to be a marker and facilitator of integration.If understanding and awareness of recommendations . This age restriction was established to ensure co-resident individuals were family members and not flat mates. The follow-up period was 12 March 2020 up until 23 February 2021. We excluded individuals who had not lived in Sweden in the two prior years (n=40 515), because they could not be linked to all records of data. In addition, we excluded individuals with missing data on country of birth (n=142) and income (n=15 405) of either partner. The final study population consists of 3 963 356 individuals (18.5% immigrants) .No patient was involved.We use information from several Swedish administrative registers linked through personal identity numbers that are unique to each person with legal residence in Sweden. Data on deaths were retrieved from the Cause of Death Register. Socioeconomic and demographic variables  were drawn from the Longitudinal Integrated Database for Health Insurance and Labour Market Studies (LISA), and residential information (type and crowdedness of the dwelling) were drawn from the Dwelling Register. All covariates in our study are time-constant and either measured at the end of 2019  or 2018 . Information on age, sex, country of birth and immigrant density in the neighbourhood stem from the Total Population Register. It is important to note that all individuals registered in Sweden are entitled to healthcare access.Socialstyrelsen), the agency responsible for the Cause of Death Register. COVID-19 mortality was identified using the following International Classification of Diseases (ICD) codes for the underlying cause of death: U07.1 (3915 deaths), U07.2 (127 deaths) and B34.2 (2 deaths); for 522 more deaths ICD codes U07.1, U07.2 or B34.2 were listed as contributing causes of death, excluding mortality from all other causes of death (30 374 deaths). Given the timeliness of the data, the assignment of the underlying cause of death should be understood as preliminary.COVID-19 mortality was identified by the Swedish National Board of Health and Welfare  native-native, (ii) native-immigrant, (iii) immigrant-native and (iv) immigrant-immigrant. We chose (i) native-native couples as the reference group for our analyses as they (a) constitute the largest category among all groups considered and (b) represent the institutional awareness and language of the host population from which we expect other groups to deviate. We further disaggregated the groups by immigrant’s origins defined according to the World Bank classification based on the Gross National Incomes per capita using the WB Atlas methodWe derived individual income and calculated the sum of the two partners’ net incomes (household), categorised into tertiles based on all adult residents of Sweden. We derived education data from Swedish Educational Registers and categorise our population into four categories: those with primary schooling, secondary schooling, postsecondary education and those with missing information on education. Missing information on education is generally very low but 88% of those with missing education are immigrants. We additionally performed multiple imputation to test how the missing values for education impact our results see . In addi10.1136/bmjopen-2021-048952.supp1Supplementary dataWe conducted Cox proportional hazards regressions  to estimate HR and 95% CI for the association between immigrant-native couple type and COVID-19 mortality. Individuals exited the study by (1) dying between 12 March 2020 and 23 February 2021, or (2) being alive on 23 February 2021. We estimated two separate regressions estimating the cause-specific hazard of dying from COVID-19, right-censoring all individuals that die from other causes and (2) the cause-specific hazard of dying from other causes than COVID-19, right-censoring all individuals that die from COVID-19. In addition, we conducted Cox regressions for dying from all causes of death that occurred between 12 March 2019 and 23 February 2020 (31 653 deaths)—the same period we observe COVID-19 deaths 12 contiguous months prior to the start of the pandemic. Since mortality from COVID-19 and other causes of deaths during the study window are not fully independent of each other, our estimates for all-cause mortality between 12 March 2019 and 23 February 2020 were used to evaluate the robustness of our estimates for mortality during the pandemic. In addition, the comparison between all-cause mortality 1 year prior and mortality from causes other than COVID-19 during the pandemic, by immigrant-native couple type, will allow us to examine whether the latter has a distinctive role in relation to the pandemic.Two models were estimated: (1) a simple model with age as the time scale adjusted for sex and (2) the same model with further adjustments. In the latter analysis, we adjust for education, neighbourhood immigrant density and region of residence fixed-effects that are confounders, as well as factors that are on the causal pathway that have been previously used to explain the excess mortality of immigrants . In addition, we conducted two sensitivity analyses. One in which we examined the partner’s origin among Swedish-migrant partnerships (HIC or LMIC) to check whether patterns are consistent across groups and, a second, in which we excluded all individuals born in Sweden with at least one foreign-born parent. All analyses were conducted using Stata Statistical Software: Release 16 .During the 3 759 610 person-years of observation, 4564 COVID-19 deaths occurred in our study population between 12 March 2020 and 23 February 2021. Sensitivity analyses showed that disaggregating the origin of immigrants in native-immigrant partnerships  and exclOur study shows that immigrants have excess COVID-19 mortality regardless of the origin of their partner, where having a Swedish-born partner is only partially protective against COVID-19 mortality among immigrants from LMIC. These findings challenge hypotheses that poor language proficiency and institutional awareness are major contributing factors explaining the excess mortality from COVID-19 among immigrants.Language has been considered a vital component of integration and relevant for accessing information for other types of medical treatments and health outcomes.Prior studies in clinical settings have shown that access to a medical interpreter is associated with better health access and outcomes.In addition to disentangling the role of language barriers and lack of understanding of the healthcare system and recommendations in explaining the excess COVID-19 mortality among immigrants, our study provides suggestive evidence that the main explanation is differential exposure to the virus and not susceptibility.In this study, immigrants in different family constellations show higher levels of COVID-19 deaths than the majority of natives, after adjustment for a wide range of individual-level and contextual-level factors, including education, income, housing conditions and neighbourhood immigrant density. This set of adjustments also partly accounts for a number of socially patterned chronic health conditions and comorbidities, for example, insulin resistance, hypertension, smoking and obesity, which have been suggested as risk factors for severe cases of COVID-19.This study has a number of contributions and strengths, First, this is the only study to date to examine sociocultural integration as the mechanism behind the disproportionate burden that COVID-19 has placed on immigrant communities, by comparing the mortality of native-native, immigrant-native and immigrant-immigrant couples in Sweden. A major strength of our study is that we have complete coverage of the total population and all deaths in Sweden from the start of the pandemic until February 2021 for both COVID-19 and remaining causes of death. Thus, our analysis does not suffer from selection into our study population. We have similar high-quality data for the year prior to the pandemic, which allows for an unbiased comparison of mortality patterns between the 2 years. The comparison between couple types with respect to mortality from all other causes during the pandemic and all-cause mortality in the year prior strengthens our findings as it demonstrates that the excess mortality from COVID-19 is observed in couples that show no excess mortality from other causes before and during the pandemic.de jure rather than de facto characteristics of individuals. With respect to our measure of partnership, 82% of the couples in our data are either married or have shared children while the remaining 18% co-reside unmarried without common children. However, non-marital cohabitation is very common in Sweden, while flat-sharing is not,Despite its strengths, this study has also some limitations that are worth mentioning. Although the Swedish population registers hold high quality and have many advantages, they capture In conclusion, our study shows that being partnered with a native does not close the gap in COVID-19 mortality with natives even after adjusting for a wide range of possible confounders on individual, couple and residential level. As such, these findings show that lack of awareness of the Swedish recommendations and language barriers are not major drivers for the excess COVID-19 mortality of immigrants. At the same time, the fact that Swedes partnered with immigrants also show excess mortality compared with Swedish couples, suggests that excess mortality among immigrants is explained by differential exposure to the virus.


The emergence of SARS-CoV-2 and subsequent COVID-19 pandemic has resulted in a significant global public health burden, leading to an urgent need for effective therapeutic strategies. In this article, we review the role of SARS-CoV-2 neutralizing antibodies (nAbs) in the clinical management of COVID-19 and provide an overview of recent randomized controlled trial data evaluating nAbs in the ambulatory, hospitalized and prophylaxis settings. Two nAb cocktails (casirivimab/imdevimab and bamlanivimab/etesevimab) and one nAb monotherapy (bamlanivimab) have been granted Emergency Use Authorization by the US Food and Drug Administration for the treatment of ambulatory patients who have a high risk of progressing to severe disease, and the European Medicines Agency has similarly recommended both cocktails and bamlanivimab monotherapy for use in COVID-19 patients who do not require supplemental oxygen and who are at high risk of progressing to severe COVID-19. Efficacy of nAbs in hospitalized patients with COVID-19 has been varied, potentially highlighting the challenges of antiviral treatment in patients who have already progressed to severe disease. However, early data suggest a promising prophylactic role for nAbs in providing effective COVID-19 protection. We also review the risk of treatment-emergent antiviral resistant “escape” mutants and strategies to minimize their occurrence, discuss the susceptibility of newly emerging SARS-COV-2 variants to nAbs, as well as explore administration challenges and ways to improve patient access. In late 2019, the novel betacoronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) emerged from an animal reservoir into humans, causing a respiratory infection known as Coronavirus Disease 2019 (COVID-19) . During At the start of the pandemic, no evidence-based treatments were available for COVID-19 despite the emergence and global spread of the related SARS-CoV-1 (Severe Acute Respiratory Syndrome [SARS]) in 2003, and continued ongoing sporadic infections with another related coronavirus, Middle East Respiratory Syndrome (MERS), that first arose in 2012 . Thus, iConvalescent plasma therapy showed initial promise in the treatment of COVID-19 patients , but phaThis article reviews the nAbs currently in development for COVID-19. The concept of viral neutralization is complex and wide-ranging, and our article defines neutralization as a reduction in viral infectivity caused by binding of antibodies to the surface of viral particles to prevent viral replication . We provSARS-CoV-2 enters host cells through interactions between the viral spike protein and the cellular angiotensin-converting enzyme 2 (ACE2) receptor . The spi®)  vs. 10.3% [23/223]) . Althougopies/mL .Phase 3 trials examining the AZD7442 cocktail are ongoing in both the pre- (NCT04625725) and post-exposure (NCT04625972) prophylaxis settings. AZD7442 is a combination of two nAbs derived from convalescent serum that demonstrated effective SARS-CoV-2 prophylaxis in a rhesus macaque model . An overAs the key viral entry protein, the SARS-CoV-2 spike is uniquely exposed to selective pressure from host antibodies, which can drive rapid antigenic drift and evolution. Therefore, viruses may develop resistance to nAbs either through the natural evolution of the virus  or resistance can arise in an individual patient due to the selection pressure of treatment during viral replication . In the Strategies to minimize the risk of escape mutants include targeting highly conserved regions of the viral spike, or utilizing a cocktail of nAbs rather than monotherapy. As conserved epitopes tend to overlap with regions essential for viral function, mutations in this region would be more likely to compromise viral fitness, and consequently be less likely to become fixed in the viral population . This apCurrent knowledge of mutations leading to nAb resistance remains limited, particularly for bamlanivimab. In the BLAZE-1 study where bamlanivimab treatment was investigated in ambulatory COVID-19 patients, SARS-CoV-2 escape mutants were reported in ~6% of patients treated with placebo, increasing to ~10% in patients receiving the highest dose of bamlanivimab ; howeverIn an in vitro study, the casirivimab/imdevimab cocktail successfully neutralized SARS-CoV-2 spike variants containing mutations identified from publicly available sequence data, as well as escape mutants generated under selection pressure from either casirivimab or imdevimab alone . NotablySignificant attention has been paid in recent months to the emergence of variant SARS-CoV-2 viruses with key mutations in the spike, particularly those that have emerged first in the UK (B.1.1.7), South Africa (B.1.351) and Brazil (P1/B.1.1.28). A recent study found that the so called “South African” virus variants (B.1.351) are resistant to bamlanivimab due to the E484K spike substitution. Of additional concern is that even as a cocktail, bamlanivimab and etesevimab are predicted to have no activity against this variant due to the latter nAb having highly reduced activity due to the K417N substitution that is also present in this variant ,79,80.The E484K and K417N substitutions in the B.1.351 strains are also responsible for reduced inhibition by casirivimab, but because the other nAb in the cocktail (imdevimab) remains unaffected by these mutations, the overall neutralization achieved by the cocktail was reduced by only 5–20-fold, depending on whether the actual variant virus or a pseudovirus was used. . HoweverBesides the challenges associated with cost/access, large-scale manufacturing and storage , the larThe approval of several efficacious COVID-19 vaccines is an integral part of national COVID-19 public health plans, and a thorough understanding of the potential interactions and implications of delivering vaccines after recent infusion with a nAb is warranted. Although no data exist in this regard, the US Centers for Disease Control and Prevention have recommended that vaccination should be deferred for ≥90 days in patients who have received nAbs. This recommendation appears to be based on the potential interference of nAbs in mounting an effective vaccine-induced immune response .SARS-CoV-2 is the third pathogenic novel coronavirus to infect humans within the last 20 years, suggesting there is a high likelihood of other novel coronavirus pandemics in the coming decades . TreatmeSince the beginning of the COVID-19 pandemic, there has been a massive global effort to harness the potential of nAbs for inhibiting the SARS-CoV-2 virus. There are hundreds of nAbs in pre-clinical development for COVID-19 treatment and prophylaxis, and several promising candidates have progressed to evaluation in the clinical trial setting. Emerging data suggest nAbs are particularly effective in preventing patients with risk factors from progressing to severe disease requiring hospitalization. Studies in hospitalized patients are ongoing, and whilst nAbs offer strong potential in this setting, the late timing of treatment onset means the effective window of antiviral effect may be limited. As the clinical data continue to emerge, it is likely that we will see several options for COVID-19 treatment and prophylaxis becoming available, and it will be important to ensure challenges associated with IV administration in the outpatient setting are met to ensure the best possible patient access. The potential for nAb resistant variants to circulate is an ongoing concern; therefore, continued surveillance of circulating viruses and detailed knowledge of the relationship between spike mutations and effectiveness of nAbs will be important to ensure treatment guidelines remain relevant. In this respect, future studies investigating the safety and efficacy of different combinations of nAbs will be important, as well as combination of nAbs with direct-acting antivirals, which may provide an even higher barrier to treatment-emergent resistance.