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Cytokine storm, known as an exaggerated hyperactive immune response characterized by elevated release of cytokines, has been described as a feature associated with life-threatening complications in COVID-19 patients. A critical evaluation of a cytokine storm and its mechanistic linkage to COVID-19 requires innovative immunoassay technology capable of rapid, sensitive, selective detection of multiple cytokines across a wide dynamic range at high-throughput. In this study, we report a machine-learning-assisted microfluidic nanoplasmonic digital immunoassay to meet the rising demand for cytokine storm monitoring in COVID-19 patients. Specifically, the assay was carried out using a facile one-step sandwich immunoassay format with three notable features: (i) a microfluidic microarray patterning technique for high-throughput, multiantibody-arrayed biosensing chip fabrication; (ii) an ultrasensitive nanoplasmonic digital imaging technology utilizing 100 nm silver nanocubes (AgNCs) for signal transduction; (iii) a rapid and accurate machine-learning-based image processing method for digital signal analysis. The developed immunoassay allows simultaneous detection of six cytokines in a single run with wide working ranges of 1–10,000 pg mL–1 and ultralow detection limits down to 0.46–1.36 pg mL–1 using a minimum of 3 μL serum samples. The whole chip can afford a 6-plex assay of 8 different samples with 6 repeats in each sample for a total of 288 sensing spots in less than 100 min. The image processing method enhanced by convolutional neural network (CNN) dramatically shortens the processing time ∼6,000 fold with a much simpler procedure while maintaining high statistical accuracy compared to the conventional manual counting approach. The immunoassay was validated by the gold-standard enzyme-linked immunosorbent assay (ELISA) and utilized for serum cytokine profiling of COVID-19 positive patients. Our results demonstrate the nanoplasmonic digital immunoassay as a promising practical tool for comprehensive characterization of cytokine storm in patients that holds great promise as an intelligent immunoassay for next generation immune monitoring.

Millions of people who survive sepsis each year are rehospitalized and die due to late pulmonary complications. To prevent and treat these complications, biomarkers and molecular mediators must be identified. Persistent immune reprogramming in the form of immunoparalysis and impaired host defense is proposed to mediate late pulmonary complications after sepsis, particularly new pulmonary infections. However, immune reprogramming may also involve enhanced/primed responses to secondary stimuli, although their contribution to long-term sepsis complications remains understudied. We hypothesize that enhanced/primed immune responses in the lungs of sepsis survivors are associated with late pulmonary complications. To this end, we developed a murine sepsis model using cecal ligation and puncture (CLP) followed 3 wk later by administration of intranasal lipopolysaccharide to induce inflammatory lung injury. Mice surviving sepsis exhibit enhanced lung injury with increased alveolar permeability, neutrophil recruitment, and enhanced Ly6Chi monocyte Tnf expression. To determine the mediators of enhanced lung injury, we performed flow cytometry and RNA sequencing of lungs 3 wk after CLP, prior to lipopolysaccharide. Sepsis survivor mice showed expanded Ly6Chi monocytes populations and increased expression of many inflammatory genes. Of these, S100A8/A9 was also elevated in the circulation of human sepsis survivors for months after sepsis, validating our model and identifying S100A8/A9 as a potential biomarker and therapeutic target for long-term pulmonary complications after sepsis. These data provide new insight into the importance of enhanced/primed immune responses in survivors of sepsis and establish a foundation for additional investigation into the mechanisms mediating this response.

Digital protein assays have great potential to advance immunodiagnostics because of their single-molecule sensitivity, high precision, and robust measurements. However, translating digital protein assays to acute clinical care has been challenging because it requires deployment of these assays with a rapid turnaround. Herein, we present a technology platform for ultrafast digital protein biomarker detection by using single-molecule counting of immune-complex formation events at an early, pre-equilibrium state. This method, which we term “pre-equilibrium digital enzyme-linked immunosorbent assay” (PEdELISA), can quantify a multiplexed panel of protein biomarkers in 10 µL of serum within an unprecedented assay incubation time of 15 to 300 seconds over a 104 dynamic range. PEdELISA allowed us to perform rapid monitoring of protein biomarkers in patients manifesting post-chimeric antigen receptor T-cell therapy cytokine release syndrome, with ∼30-minute sample-to-answer time and a sub–picograms per mL limit of detection. The rapid, sensitive, and low-input volume biomarker quantification enabled by PEdELISA is broadly applicable to timely monitoring of acute disease, potentially enabling more personalized treatment.

Observational evidence suggests that excessive inflammation with cytokine storm may play a critical role in development of acute respiratory distress syndrome (ARDS) in COVID-19. We report the emergency use of immunomodulatory therapy utilizing an extracorporeal selective cytopheretic device (SCD) in two patients with elevated serum interleukin (IL)-6 levels and refractory COVID-19 ARDS requiring extracorporeal membrane oxygenation (ECMO). The two patients were selected based on clinical criteria and elevated levels of IL-6 (>100 pg/ml) as a biomarker of inflammation. Once identified, emergency/expanded use permission for SCD treatment was obtained and patient consented. Six COVID-19 patients (four on ECMO) with severe ARDS were also screened with IL-6 levels less than 100 pg/ml and were not treated with SCD. The two enrolled patients' PaO2/FiO2 ratios increased from 55 and 58 to 200 and 192 at 52 and 50 hours, respectively. Inflammatory indices also declined with IL-6 falling from 231 and 598 pg/ml to 3.32 and 116 pg/ml, respectively. IL-6/IL-10 ratios also decreased from 11.8 and 18 to 0.7 and 0.62, respectively. The two patients were successfully weaned off ECMO after 17 and 16 days of SCD therapy, respectively. The results observed with SCD therapy on these two critically ill COVID-19 patients with severe ARDS and elevated IL-6 is encouraging. A multicenter clinical trial is underway with an FDA-approved investigational device exemption to evaluate the potential of SCD therapy to effectively treat COVID-19 intensive care unit patients.

The coronavirus disease 2019 (COVID-19) pandemic has forced us to consider the physiologic role of obesity in the response to infectious disease. There are significant disparities in morbidity and mortality by sex, weight, and diabetes status. Numerous endocrine changes might drive these varied responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, including hormone and immune mediators, hyperglycemia, leukocyte responses, cytokine secretion, and tissue dysfunction. Studies of patients with severe COVID-19 disease have revealed the importance of innate immune responses in driving immunopathology and tissue injury. In this review we will describe the impact of the metabolically induced inflammation (meta-inflammation) that characterizes obesity on innate immunity. We consider that obesity-driven dysregulation of innate immune responses may drive organ injury in the development of severe COVID-19 and impair viral clearance.

Sepsis commonly results in acute and chronic brain dysfunction, which dramatically increases the morbidity associated with this common disease. Chronic brain dysfunction in animal models of sepsis survival is linked to persistent neuroinflammation and expression of multiple cytokines. However, we have found previously that microglia predominantly upregulate the damage associated molecule S100A8/A9 after sepsis. In this article, we show that S100A8/A9 is increased in the brains of patients who died of sepsis and that S100A8 is expressed in astrocytes and myeloid cells. Using a mouse model of sepsis survival, we show that S100A8/A9 is persistently expressed in the brain after sepsis. S100A9 expression is necessary for recruitment of neutrophils to the brain and for priming production of reactive oxygen species and TNF-α secretion in microglia and macrophages. However, despite improving these indices of chronic inflammation, S100A9 deficiency results in worsened anxiety-like behavior 2 wk after sepsis. Taken together, these results indicate that S100A8/A9 contributes to several facets of neuroinflammation in sepsis survivor mice, including granulocyte recruitment and priming of microglial-reactive oxygen species and cytokine production, and that these processes may be protective against anxiety behavior in sepsis survivors.

Septic patients frequently develop cognitive impairment that persists beyond hospital discharge. The impact of sepsis on electrophysiological and molecular determinants of learning is underexplored. We observed that mice that survived sepsis or endotoxemia experienced loss of hippocampal long-term potentiation (LTP), a brain-derived neurotrophic factor–mediated (BDNF-mediated) process responsible for spatial memory formation. Memory impairment occurred despite preserved hippocampal BDNF content and could be reversed by stimulation of BDNF signaling, suggesting the presence of a local BDNF inhibitor. Sepsis is associated with degradation of the endothelial glycocalyx, releasing heparan sulfate fragments (of sufficient size and sulfation to bind BDNF) into the circulation. Heparan sulfate fragments penetrated the hippocampal blood-brain barrier during sepsis and inhibited BDNF-mediated LTP. Glycoarray approaches demonstrated that the avidity of heparan sulfate for BDNF increased with sulfation at the 2-O position of iduronic acid and the N position of glucosamine. Circulating heparan sulfate in endotoxemic mice and septic humans was enriched in 2-O– and N-sulfated disaccharides; furthermore, the presence of these sulfation patterns in the plasma of septic patients at intensive care unit (ICU) admission predicted persistent cognitive impairment 14 days after ICU discharge or at hospital discharge. Our findings indicate that circulating 2-O– and N-sulfated heparan sulfate fragments contribute to septic cognitive impairment.

Interleukin-36γ (IL-36γ) is a member of novel IL-1-like proinflammatory cytokine family that are highly expressed in epithelial tissues and several myeloid-derived cell types. Little is known about the role of the IL-36 family in mucosal immunity, including lung anti-bacterial responses. We used murine models of IL-36γ deficiency to assess the contribution of IL-36γ in the lung during experimental pneumonia. Induction of IL-36γ was observed in the lung in response to Streptococcus pneumoniae (Sp) infection, and mature IL-36γ protein was secreted primarily in microparticles. IL-36γ-deficient mice challenged with Sp demonstrated increased mortality, decreased lung bacterial clearance and increased bacterial dissemination, in association with reduced local expression of type-1 cytokines, and impaired lung macrophage M1 polarization. IL-36γ directly stimulated type-1 cytokine induction from dendritic cells in vitro in a MyD88-dependent manner. Similar protective effects of IL-36γ were observed in a Gram-negative pneumonia model (Klebsiella pneumoniae). Intrapulmonary delivery of IL-36γ-containing microparticles reconstituted immunity in IL-36γ−/− mice. Enhanced expression of IL-36γ was also observed in plasma and bronchoalveolar lavage fluid of patients with acute respiratory distress syndrome because of pneumonia. These studies indicate that IL-36γ assumes a vital proximal role in the lung innate mucosal immunity during bacterial pneumonia by driving protective type-1 responses and classical macrophage activation.

Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short assay turnaround poses a formidable technological challenge. Here, the authors develop a rapid, accurate, and highly multiplexed microfluidic digital immunoassay by incorporating machine learning-based autonomous image analysis. The assay has achieved 12-plexed biomarker detection in sample volume

Sepsis is a leading cause of death worldwide. After initial trials modulating the hyperinflammatory phase of sepsis failed, generations of researchers have focused on evaluating hypo-inflammatory immune phenotypes. The main goal has been to develop prognostic biomarkers and therapies to reduce organ dysfunction, nosocomial infection, and death. The depressed host defense in sepsis has been characterized by broad cellular reprogramming including lymphocyte exhaustion, apoptosis, and depressed cytokine responses. Despite major advances in this field, our understanding of the dynamics of the septic host response and the balance of inflammatory and anti-inflammatory cellular programs remains limited. This review aims to summarize the epidemiology of nosocomial infections and characteristic immune responses associated with sepsis, as well as immunostimulatory therapies currently under clinical investigation.

Rationale: Sepsis causes brain dysfunction and neuroinflammation. It is unknown whether neuroinflammation in sepsis is initiated by dissemination of bacteria to the brain and sustained by persistent infection, or whether neuroinflammation is a sterile process resulting solely from circulating inflammatory mediators. Objectives: To determine if gut bacteria translocate to the brain during sepsis, and are associated with neuroinflammation. Methods: Murine sepsis was induced using cecal ligation and puncture, and sepsis survivor mice were compared with sham and unoperated control animals. Brain tissue of patients who died of sepsis was compared with patients who died of noninfectious causes. Bacterial taxa were characterized by 16S ribosomal RNA gene sequencing in both murine and human brain specimens; compared among sepsis and nonsepsis groups; and correlated with levels of S100A8, a marker of neuroinflammation using permutational multivariate ANOVA. Measurements and Main Results: Viable gut-associated bacteria were enriched in the brains of mice 5 days after surviving abdominal sepsis (P

Sepsis and the acute respiratory distress syndrome (ARDS) are major causes of mortality without targeted therapies. Although many experimental and clinical observations have implicated gut microbiota in the pathogenesis of these diseases, culture-based studies have failed to demonstrate translocation of bacteria to the lungs in critically ill patients. Here, we report culture-independent evidence that the lung microbiome is enriched with gut bacteria both in a murine model of sepsis and in humans with established ARDS. Following experimental sepsis, lung communities were dominated by viable gut-associated bacteria. Ecological analysis identified the lower gastrointestinal tract, rather than the upper respiratory tract, as the likely source community of post-sepsis lung bacteria. In bronchoalveolar lavage fluid from humans with ARDS, gut-specific bacteria (Bacteroides spp.) were common and abundant, undetected by culture and correlated with the intensity of systemic inflammation. Alveolar TNF-α, a key mediator of alveolar inflammation in ARDS, was significantly correlated with altered lung microbiota. Our results demonstrate that the lung microbiome is enriched with gut-associated bacteria in sepsis and ARDS, potentially representing a shared mechanism of pathogenesis in these common and lethal diseases.

Global eradication of tuberculosis (TB) is an international agenda. Thus understanding effects of treatment of TB in different settings is crucial. In previous work, we introduced the framework for a mathematical model of epidemic TB in demographically distinct, heterogeneous populations. Simulations showed the importance of genetic susceptibility in determining endemic prevalence levels. In the work presented here, we include treatment and investigate different strategies for treatment of latent and active TB disease in heterogeneous populations. We illustrate how the presence of a genetically susceptible subpopulation dramatically alters effects of treatment in the same way a core population does in the setting of sexually transmitted diseases. In addition, we evaluate treatment strategies that focus specifically on this subpopulation, and our results indicate that genetically susceptible subpopulations should be accounted for when designing treatment strategies to achieve the greatest reduction in disease prevalence.

Objective In adults, obesity has been associated with several health outcomes including increased bone density. Our objective was to evaluate the association between percent body fat and fat mass with bone mineral density (BMD) in a nationally representative population of children and adolescents. Study design A total of 8,348 participants 8–18 years of age from the National Health and Nutrition Examination Survey (NHANES) 1999–2006 had whole body DXA scans performed. We conducted linear regressions to examine the relationship between percent body fat and fat mass with outcome variables of total body, pelvic and lumbar spine areal BMD (aBMD), controlling for lean body mass and assessing for gender and race/ethnicity interactions. Results We found evidence of gender and race/ethnicity interactions with percent body fat and total fat mass for the different BMD areas. Generally, there were decreases in total body aBMD (p

We present a patient with congenital lactic acidosis, agenesis of the corpus callosum, and profound developmental delay. Assays of pyruvate dehydrogenase complex function were normal in lymphocytes, but decreased in fibroblasts. Sequencing of the PDHA1 gene did not reveal deleterious mutations, and BAC based microarray analysis did not reveal any chromosomal abnormality. However, gene dosage analysis with oligonucleotide-based chromosomal microarray revealed a deletion of Xp22.12-Xp22.13 involving complete deletion of PDHA1. This is the first report of a whole gene deletion of PDHA1 detected by oligonucleotide-based microarray.

Recent research suggests that domesticated species – due to artificial selection by humans for specific, preferred behavioral traits – are better than wild animals at responding to visual cues given by humans about the location of hidden food. \Although this seems to be supported by studies on a range of domesticated (including dogs, goats and horses) and wild (including wolves and chimpanzees) animals, there is also evidence that exposure to humans positively influences the ability of both wild and domesticated animals to follow these same cues. Here, we test the performance of Asian elephants (Elephas maximus) on an object choice task that provides them with visual-only cues given by humans about the location of hidden food. Captive elephants are interesting candidates for investigating how both domestication and human exposure may impact cue-following as they represent a non-domesticated species with almost constant human interaction. As a group, the elephants (n = 7) in our study were unable to follow pointing, body orientation or a combination of both as honest signals of food location. They were, however, able to follow vocal commands with which they were already familiar in a novel context, suggesting the elephants are able to follow cues if they are sufficiently salient. Although the elephants’ inability to follow the visual cues provides partial support for the domestication hypothesis, an alternative explanation is that elephants may rely more heavily on other sensory modalities, specifically olfaction and audition. Further research will be needed to rule out this alternative explanation.

There is wide variation in endemic tuberculosis (TB) levels between countries and we seek to identify possible causes of these differences. In this study we present an epidemiological model of Mycobacterium tuberculosis infection to investigate the effects of host genetics and demographic factors on epidemic TB. We discuss the general framework for this approach and present analytical results to identify important parameters affecting steady-state prevalence and incidence rates of TB disease. We then use numerical simulations of our model to observe the effects of a genetically susceptible subpopulation on TB disease dynamics at the population level. Finally, we simulate infection within a genetically heterogeneous population in two demographic settings: India (a typical population with high TB prevalence) and the USA (a typical population with low TB prevalence). Results show that changes in transmission parameters, the fraction of the population genetically susceptible to infection, and demographic factors strongly affect TB prevalence and incidence rates.