Tracking the clonal dynamics of SARS-CoV-2-specific T cells in children and adults with mild/asymptomatic COVID-19.

Children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop less severe coronavirus disease 2019 (COVID-19) than adults. The mechanisms for the age-specific differences and the implications for infection-induced immunity are beginning to be uncovered. We show by longitudinal multimodal analysis that SARS-CoV-2 leaves a small footprint in the circulating T cell compartment in children with mild/asymptomatic COVID-19 compared to adult household contacts with the same disease severity who had more evidence of systemic T cell interferon activation, cytotoxicity and exhaustion. Children harbored diverse polyclonal SARS-CoV-2-specific naïve T cells whereas adults harbored clonally expanded SARS-CoV-2-specific memory T cells. A novel population of naïve interferon-activated T cells is expanded in acute COVID-19 and is recruited into the memory compartment during convalescence in adults but not children. This was associated with the development of robust CD4+ memory T cell responses in adults but not children. These data suggest that rapid clearance of SARS-CoV-2 in children may compromise their cellular immunity and ability to resist reinfection.

Multisite validation of a host response signature for predicting likelihood of bacterial and viral infections in patients with suspected influenza.

BACKGROUND: Indiscriminate use of antimicrobials and antimicrobial resistance is a public health threat. IMX-BVN-1, a 29-host mRNA classifier, provides two separate scores that predict likelihoods of bacterial and viral infections in patients with suspected acute infections. We validated the performance of IMX-BVN-1 in adults attending acute health care settings with suspected influenza. METHOD: We amplified 29-host response genes in RNA extracted from blood by NanoString nCounter. IMX-BVN-1 calculated two scores to predict probabilities of bacterial and viral infections. Results were compared against the infection status (no infection; highly probable/possible infection; confirmed infection) determined by clinical adjudication. RESULTS: Amongst 602 adult patients (74.9% ED, 16.9% ICU, 8.1% outpatients), 7.6% showed in-hospital mortality and 15.5% immunosuppression. Median IMX-BVN-1 bacterial and viral scores were higher in patients with confirmed bacterial (0.27) and viral (0.62) infections than in those without bacterial (0.08) or viral (0.21) infection, respectively. The AUROC distinguishing bacterial from nonbacterial illness was 0.81 and 0.87 when distinguishing viral from nonviral illness. The bacterial top quartile's positive likelihood ratio (LR) was 4.38 with a rule-in specificity of 88%; the bacterial bottom quartile's negative LR was 0.13 with a rule-out sensitivity of 96%. Similarly, the viral top quartile showed an infinite LR with rule-in specificity of 100%; the viral bottom quartile had a LR of 0.22 and a rule-out sensitivity of 85%. CONCLUSION: IMX-BVN-1 showed high accuracy for differentiating bacterial and viral infections from noninfectious illness in patients with suspected influenza. Clinical utility of IMX-BVN will be validated following integration into a point of care system.

Pathway and Network Analyses Identify Growth Factor Signaling and MMP9 as Potential Mediators of Mitochondrial Dysfunction in Severe COVID-19.

Patients with preexisting metabolic disorders such as diabetes are at a higher risk of developing severe coronavirus disease 2019 (COVID-19). Mitochondrion, the very organelle that controls cellular metabolism, holds the key to understanding disease progression at the cellular level. Our current study aimed to understand how cellular metabolism contributes to COVID-19 outcomes. Metacore pathway enrichment analyses on differentially expressed genes (encoded by both mitochondrial and nuclear deoxyribonucleic acid (DNA)) involved in cellular metabolism, regulation of mitochondrial respiration and organization, and apoptosis, was performed on RNA sequencing (RNASeq) data from blood samples collected from healthy controls and patients with mild/moderate or severe COVID-19. Genes from the enriched pathways were analyzed by network analysis to uncover interactions among them and up- or downstream genes within each pathway. Compared to the mild/moderate COVID-19, the upregulation of a myriad of growth factor and cell cycle signaling pathways, with concomitant downregulation of interferon signaling pathways, were observed in the severe group. Matrix metallopeptidase 9 (MMP9) was found in five of the top 10 upregulated pathways, indicating its potential as therapeutic target against COVID-19. In summary, our data demonstrates aberrant activation of endocrine signaling in severe COVID-19, and its implication in immune and metabolic dysfunction.

Profiling of lung SARS-CoV-2 and influenza virus infection dissects virus-specific host responses and gene signatures.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). A better definition of the pulmonary host response to SARS-CoV-2 infection is required to understand viral pathogenesis and to validate putative COVID-19 biomarkers that have been proposed in clinical studies. METHODS: Here, we use targeted transcriptomics of formalin-fixed paraffin-embedded tissue using the NanoString GeoMX platform to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19, pandemic H1N1 influenza and uninfected control patients. RESULTS: Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs (emphasising the advantages of spatial transcriptomics) with the areas of high viral load associated with an increased type I interferon response. Once the dominant cell type present in the sample, within patient correlations and patient-patient variation, had been controlled for, only a very limited number of genes were differentially expressed between the lungs of fatal influenza and COVID-19 patients. Strikingly, the interferon-associated gene IFI27, previously identified as a useful blood biomarker to differentiate bacterial and viral lung infections, was significantly upregulated in the lungs of COVID-19 patients compared to patients with influenza. CONCLUSION: Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.

Association Between Premorbid Beta-Blocker Exposure and Sepsis Outcomes-The Beta-Blockers in European and Australian/American Septic Patients (BEAST) Study.

OBJECTIVES: To examine the effect of premorbid ß-blocker exposure on mortality and organ dysfunction in sepsis. DESIGN: Retrospective observational study. SETTING: ICUs in Australia, the Czech Republic, and the United States. PATIENTS: Total of 4,086 critical care patients above 18 years old with sepsis between January 2014 and December 2018. INTERVENTION: Premorbid beta-blocker exposure. MEASUREMENTS AND MAIN RESULTS: One thousand five hundred fifty-six patients (38%) with premorbid ß-blocker exposure were identified. Overall ICU mortality rate was 15.1%. In adjusted models, premorbid ß-blocker exposure was associated with decreased ICU (adjusted odds ratio, 0.80; 95% CI, 0.66-0.97; p = 0.025) and hospital (adjusted odds ratio, 0.83; 95% CI, 0.71-0.99; p = 0.033) mortality. The risk reduction in ICU mortality of 16% was significant (hazard ratio, 0.84, 95% CI, 0.71-0.99; p = 0.037). In particular, exposure to noncardioselective ß-blocker before septic episode was associated with decreased mortality. Sequential Organ Failure Assessment score analysis showed that premorbid ß-blocker exposure had potential benefits in reducing respiratory and neurologic dysfunction. CONCLUSIONS: This study suggests that ß-blocker exposure prior to sepsis, especially to noncardioselective ß blockers, may be associated with better outcome. The findings suggest prospective evaluation of ß-blocker use in the management of sepsis.

Sepsis Subclasses: A Framework for Development and Interpretation.

Sepsis is defined as a dysregulated host response to infection that leads to life-threatening acute organ dysfunction. It afflicts approximately 50 million people worldwide annually and is often deadly, even when evidence-based guidelines are applied promptly. Many randomized trials tested therapies for sepsis over the past 2 decades, but most have not proven beneficial. This may be because sepsis is a heterogeneous syndrome, characterized by a vast set of clinical and biologic features. Combinations of these features, however, may identify previously unrecognized groups, or "subclasses" with different risks of outcome and response to a given treatment. As efforts to identify sepsis subclasses become more common, many unanswered questions and challenges arise. These include: 1) the semantic underpinning of sepsis subclasses, 2) the conceptual goal of subclasses, 3) considerations about study design, data sources, and statistical methods, 4) the role of emerging data types, and 5) how to determine whether subclasses represent "truth." We discuss these challenges and present a framework for the broader study of sepsis subclasses. This framework is intended to aid in the understanding and interpretation of sepsis subclasses, provide a mechanism for explaining subclasses generated by different methodologic approaches, and guide clinicians in how to consider subclasses in bedside care.

Inhibitors of heat shock protein 70 (Hsp70) with enhanced metabolic stability reduce tau levels.

The molecular chaperone, Heat Shock Protein 70 (Hsp70), is an emerging drug target for neurodegenerative diseases, because of its ability to promote degradation of microtubule-associated protein tau (MAPT/tau). Recently, we reported YM-08 as a brain penetrant, allosteric Hsp70 inhibitor, which reduces tau levels. However, the benzothiazole moiety of YM-08 is vulnerable to metabolism by CYP3A4, limiting its further application as a chemical probe. In this manuscript, we designed and synthesized seventeen YM-08 derivatives by systematically introducing halogen atoms to the benzothiazole ring and shifting the position of the heteroatom in a distal pyridine. In microsome assays, we found that compound JG-23 has 12-fold better metabolic stability and it retained the ability to reduce tau levels in two cell-based models. These chemical probes of Hsp70 are expected to be useful tools for studying tau homeostasis.

A modular framework for the development of targeted Covid-19 blood transcript profiling panels.

BACKGROUND: Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of targeted blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection. METHODS: We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates. RESULTS: As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: immunological relevance, therapeutic development relevance and SARS biology relevance. CONCLUSION: Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.

Correction to: The association between premorbid beta blocker exposure and mortality in sepsis-a systematic review.

In the publication of this article [1], there was an error in the cited reference 23 [2] within the Family Name. This has now been updated in the original article.

The association between premorbid beta blocker exposure and mortality in sepsis-a systematic review.

BACKGROUND: The effect of premorbid ß-blocker exposure on clinical outcomes in patients with sepsis is not well characterized. We aimed to examine the association between premorbid ß-blocker exposure and mortality in sepsis. METHODS: EMBase, MEDLINE, and Cochrane databases were searched for all studies of premorbid ß-blocker and sepsis. The search was last updated on 22 June 2019. Two reviewers independently assessed, selected, and abstracted data from studies reporting chronic ß-blocker use prior to sepsis and mortality. Main data extracted were premorbid ß-blocker exposure, mortality, study design, and patient data. Two reviewers independently assessed the risk of bias and quality of evidence. RESULTS: In total, nine studies comprising 56,414 patients with sepsis including 6576 patients with premorbid exposure to ß-blockers were eligible. For the primary outcome of mortality, two retrospective studies reported adjusted odds ratios showing a reduction in mortality with premorbid ß-blocker exposure. One study showed that premorbid ß-blocker exposure decreases mortality in patients with septic shock. Another study showed that continued ß-blockade during sepsis is associated with decreased mortality. CONCLUSION: This systematic review suggests that ß-blocker exposure prior to sepsis is associated with reduced mortality. There was insufficient data to conduct a bona fide meta-analysis. Whether the apparent reduction in mortality may be attributed to the mitigation of catecholamine excess is unclear. TRIAL REGISTRATION: PROSPERO, CRD42019130558 registered June 12, 2019.

Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters.

OBJECTIVES: To find and validate generalizable sepsis subtypes using data-driven clustering. DESIGN: We used advanced informatics techniques to pool data from 14 bacterial sepsis transcriptomic datasets from eight different countries (n = 700). SETTING: Retrospective analysis. SUBJECTS: Persons admitted to the hospital with bacterial sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A unified clustering analysis across 14 discovery datasets revealed three subtypes, which, based on functional analysis, we termed "Inflammopathic, Adaptive, and Coagulopathic." We then validated these subtypes in nine independent datasets from five different countries (n = 600). In both discovery and validation data, the Adaptive subtype is associated with a lower clinical severity and lower mortality rate, and the Coagulopathic subtype is associated with higher mortality and clinical coagulopathy. Further, these clusters are statistically associated with clusters derived by others in independent single sepsis cohorts. CONCLUSIONS: The three sepsis subtypes may represent a unifying framework for understanding the molecular heterogeneity of the sepsis syndrome. Further study could potentially enable a precision medicine approach of matching novel immunomodulatory therapies with septic patients most likely to benefit.

Glucose-responsive insulin activity by covalent modification with aliphatic phenylboronic acid conjugates.

Since its discovery and isolation, exogenous insulin has dramatically changed the outlook for patients with diabetes. However, even when patients strictly follow an insulin regimen, serious complications can result as patients experience both hyperglycemic and hypoglycemic states. Several chemically or genetically modified insulins have been developed that tune the pharmacokinetics of insulin activity for personalized therapy. Here, we demonstrate a strategy for the chemical modification of insulin intended to promote both long-lasting and glucose-responsive activity through the incorporation of an aliphatic domain to facilitate hydrophobic interactions, as well as a phenylboronic acid for glucose sensing. These synthetic insulin derivatives enable rapid reversal of blood glucose in a diabetic mouse model following glucose challenge, with some derivatives responding to repeated glucose challenges over a 13-h period. The best-performing insulin derivative provides glucose control that is superior to native insulin, with responsiveness to glucose challenge improved over a clinically used long-acting insulin derivative. Moreover, continuous glucose monitoring reveals responsiveness matching that of a healthy pancreas. This synthetic approach to insulin modification could afford both long-term and glucose-mediated insulin activity, thereby reducing the number of administrations and improving the fidelity of glycemic control for insulin therapy. The described work is to our knowledge the first demonstration of a glucose-binding modified insulin molecule with glucose-responsive activity verified in vivo.

A novel immune biomarker IFI27 discriminates between influenza and bacteria in patients with suspected respiratory infection.

Host response biomarkers can accurately distinguish between influenza and bacterial infection. However, published biomarkers require the measurement of many genes, thereby making it difficult to implement them in clinical practice. This study aims to identify a single-gene biomarker with a high diagnostic accuracy equivalent to multi-gene biomarkers.In this study, we combined an integrated genomic analysis of 1071 individuals with in vitro experiments using well-established infection models.We identified a single-gene biomarker, IFI27, which had a high prediction accuracy (91%) equivalent to that obtained by multi-gene biomarkers. In vitro studies showed that IFI27 was upregulated by TLR7 in plasmacytoid dendritic cells, antigen-presenting cells that responded to influenza virus rather than bacteria. In vivo studies confirmed that IFI27 was expressed in influenza patients but not in bacterial infection, as demonstrated in multiple patient cohorts (n=521). In a large prospective study (n=439) of patients presented with undifferentiated respiratory illness (aetiologies included viral, bacterial and non-infectious conditions), IFI27 displayed 88% diagnostic accuracy (AUC) and 90% specificity in discriminating between influenza and bacterial infections.IFI27 represents a significant step forward in overcoming a translational barrier in applying genomic assay in clinical setting; its implementation may improve the diagnosis and management of respiratory infection.

Poly(glycoamidoamine) Brushes Formulated Nanomaterials for Systemic siRNA and mRNA Delivery in Vivo.

Safe and effective delivery is required for siRNA and mRNA-based therapeutics to reach their potential. Here, we report on the development of poly(glycoamidoamine) brush nanoparticles as delivery vehicles for siRNA and mRNA. These polymers were capable of significant delivery of siRNA against FVII and mRNA-encoding erythropoietin (EPO) in mice. Importantly, these nanoparticles were well-tolerated at their effective dose based on analysis of tissue histology, systemic cytokine levels, and liver enzyme chemistry. The polymer brush nanoparticles reported here are promising for therapeutic applications.

Injectable and Glucose-Responsive Hydrogels Based on Boronic Acid-Glucose Complexation.

Injectable hydrogels have been widely used for a number of biomedical applications. Here, we report a new strategy to form an injectable and glucose-responsive hydrogel using the boronic acid-glucose complexation. The ratio of boronic acid and glucose functional groups is critical for hydrogel formation. In our system, polymers with 10-60% boronic acid, with the balance being glucose-modified, are favorable to form hydrogels. These hydrogels are shear-thinning and self-healing, recovering from shear-induced flow to a gel state within seconds. More importantly, these polymers displayed glucose-responsive release of an encapsulated model drug. The hydrogel reported here is an injectable and glucose-responsive hydrogel constructed from the complexation of boronic acid and glucose within a single component polymeric material.

Sociodemographic Correlates and Morbidity in Lottery Gamblers: Results from a Population Survey.

The aim of the current study was to examine the socio-demographic correlates, the association of mental and physical illness, and the prevalence of pathological gambling among three groups (1) those with lottery gambling only (2) those with lottery and other types of gambling and (3) those with other types of gambling only-such as playing cards, sports betting, horse racing, casino gambling etc. Data was used from a nationwide cross-sectional epidemiological nationally representative survey of the resident (Singapore Citizens and Permanent Residents) population in Singapore of 6616 Singaporean adults aged 18 years and older. All respondents were administered the South Oaks Gambling Screen to screen for pathological gambling. The diagnoses of mental disorders were established using the Composite International Diagnostic Interview and relevant socio-demographic data was collected using a structured questionnaire. Lottery gambling was by far the most popular form of gambling in Singapore, with 83.5 % of those who had ever gambled indicating that they had participated in lottery gambling. Those who participated in lottery gambling alone were more likely to belong to the older age group (as compared to the 18-35 years age group), be of Indian ethnicity, have a secondary or vocational education, and earn a lower income as compared to the other two groups. Our findings that those with pure lottery gambling were significantly less likely to be pathological gamblers and had significantly lower odds of psychiatric and physical morbidity as compared to the other two groups are unique and need further research.

Is lactate the new panacea for endothelial dysfunction?

Fluid resuscitation in the critically ill is a hot topic. The current strategy of rapid and adequate resuscitation in shock followed by conservative fluid administration is often difficult to achieve with standard crystalloid solutions. Research into alternative intravenous fluids tailored to individual patient needs is required. In the previous issue of Critical Care, Somasetia and colleagues compare the effects of hypertonic sodium lactate with the World Health Organization-recommended strategy of Ringer's lactate resuscitation in children with severe Dengue, a viral infection for which causal treatment and vaccination are not available. The results not only suggest unimpaired lactate metabolism during shock in children but document improvement in endothelial barrier function, limited coagulopathy, and avoidance of fluid overload with hypertonic sodium lactate. Their study invites several important questions to be answered. Is hypertonicity or lactate per se important for the beneficial effects? Are the metabolic or anti-inflammatory effects responsible? Is the raised lactate in shock an adaptive response? Should reduction in lactate levels be the goal of resuscitation? These questions may trigger further research into the role of lactate and lactate-based intravenous fluids in resuscitation of the critically ill.

Host transcriptomics and machine learning for secondary bacterial infections in patients with COVID-19: a prospective, observational cohort study.

BACKGROUND: Viral respiratory tract infections are frequently complicated by secondary bacterial infections. This study aimed to use machine learning to predict the risk of bacterial superinfection in SARS-CoV-2-positive individuals. METHODS: In this prospective, multicentre, observational cohort study done in nine centres in six countries (Australia, Indonesia, Singapore, Italy, Czechia, and France) blood samples and RNA sequencing were used to develop a robust model of predicting secondary bacterial infections in the respiratory tract of patients with COVID-19. Eligible participants were older than 18 years, had known or suspected COVID-19, and symptoms of a recent respiratory infection. A control cohort of participants without COVID-19 who were older than 18 years and with no infection symptoms was also recruited from one Australian centre. In the pre-analysis phase, data were filtered to include only individuals with complete blood transcriptomics and patient data (ie, age, sex, location, and WHO severity score at the time of sample collection). The dataset was then divided randomly (4:1) into a training set (80%) and a test set (20%). Gene expression data in the training set and control cohort were used for differential expression analysis. Differentially expressed genes, along with WHO severity score, location, age, and sex, were used for feature selection with least absolute shrinkage and selection operator (LASSO) in the training set. For LASSO analysis, samples were excluded if gene expression data were not obtained at study admission, no longitudinal clinical information was available, a bacterial infection at the time of study admission was present, or a fungal infection in the absence of a bacterial infection was detected. LASSO regression was performed using three subsets of predictor variables: patient data alone, gene expression data alone, or a combination of patient data and gene expression data. The accuracy of the resultant models was tested on data from the test set. FINDINGS: Between March, 2020, and October, 2021, we recruited 536 SARS-CoV-2-positive individuals and between June, 2013, and January, 2020, we recruited 74 participants into the control cohort. After prefiltering analysis and other exclusions, samples from 158 individuals were analysed in the training set and 47 in the test set. The expression of seven host genes (DAPP1, CST3, FGL2, GCH1, CIITA, UPP1, and RN7SL1) in the blood at the time of study admission was identified by LASSO as predictive of the risk of developing a secondary bacterial infection of the respiratory tract more than 24 h after study admission. Specifically, the expression of these genes in combination with a patient's WHO severity score at the time of study enrolment resulted in an area under the curve of 0·98 (95% CI 0·89-1·00), a true positive rate (sensitivity) of 1·00 (95% CI 1·00-1·00), and a true negative rate (specificity) of 0·94 (95% CI 0·89-1·00) in the test cohort. The combination of patient data and host transcriptomics at hospital admission identified all seven individuals in the training and test sets who developed a bacterial infection of the respiratory tract 5-9 days after hospital admission. INTERPRETATION: These data raise the possibility that host transcriptomics at the time of clinical presentation, together with machine learning, can forward predict the risk of secondary bacterial infections and allow for the more targeted use of antibiotics in viral infection. FUNDING: Snow Medical Research Foundation, the National Health and Medical Research Council, the Jack Ma Foundation, the Helmholtz-Association, the A2 Milk Company, National Institute of Allergy and Infectious Disease, and the Fondazione AIRC Associazione Italiana per la Ricerca contro il Cancro.

In situ single-cell profiling sheds light on IFI27 localisation during SARS-CoV-2 infection.

The utilization of single-cell resolved spatial transcriptomics to delineate immune responses during SARS-CoV-2 infection was able to identify M1 macrophages to have elevated expression of IFI27 in areas of infection.

Time-tagged ticker tapes for intracellular recordings.

Recording transcriptional histories of a cell would enable deeper understanding of cellular developmental trajectories and responses to external perturbations. Here we describe an engineered protein fiber that incorporates diverse fluorescent marks during its growth to store a ticker tape-like history. An embedded HaloTag reporter incorporates user-supplied dyes, leading to colored stripes that map the growth of each individual fiber to wall clock time. A co-expressed eGFP tag driven by a promoter of interest records a history of transcriptional activation. High-resolution multi-spectral imaging on fixed samples reads the cellular histories, and interpolation of eGFP marks relative to HaloTag timestamps provides accurate absolute timing. We demonstrate recordings of doxycycline-induced transcription in HEK cells and cFos promoter activation in cultured neurons, with a single-cell absolute accuracy of 30-40 minutes over a 12-hour recording. The protein-based ticker tape design we present here could be generalized to achieve massively parallel single-cell recordings of diverse physiological modalities.