Significance This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.
T-cell large granular lymphocyte (T-LGL)leukemia is a clonal lymphoproliferation of cytotoxic T cells (CTLs) associated with cytopenias. T-LGL proliferation seems to be triggered/sustained by antigenic drive; it is likely that hematopoietic progenitors are the targets in this process. The antigen-specific portion of the T-cell receptor (TCR), the variable beta (VB)-chain complementarity-determining region 3 (CDR3), can serve as a molecular signature (clonotype) of a T-cell clone. We hypothesized that clonal CTL proliferation develops not randomly but in the context of an autoimmune response. We identified the clonotypic sequence of T-LGL clones in 60 patients, including 56 with known T-LGL and 4 with unspecified neutropenia. Our method also allowed for the measurement of clonal frequencies; a decrease in or loss of the pathogenic clonotype and restoration of the TCR repertoire was found after hematologic remission. We identified 2 patients with identical immunodominant CDR3 sequence. Moreover, we found similarity between multiple immunodominant clonotypes and codominant as well as a nonexpanded, "supporting" clonotypes. The data suggest a nonrandom clonal selection in T-LGL, possibly driven by a common antigen. In contrast, the physiologic clonal CTL repertoire is highly diverse and we were not able to detect any significant clonal sharing in 26 healthy controls.
How do we forecast an emerging pandemic in real time in a purely data-driven manner? How to leverage rich heterogeneous data based on various signals such as mobility, testing, and/or disease exposure for forecasting? How to handle noisy data and generate uncertainties in the forecast? In this paper, we present DeepCOVID, an operational deep learning framework designed for real-time COVID-19 forecasting. DeepCOVID works well with sparse data and can handle noisy heterogeneous data signals by propagating the uncertainty from the data in a principled manner resulting in meaningful uncertainties in the forecast. The framework also consists of modules for both real-time and retrospective exploratory analysis to enable interpretation of the forecasts. Results from real-time predictions (featured on the CDC website and FiveThirtyEight.com) since April 2020 indicates that our approach is competitive among the methods in the COVID-19 Forecast Hub, especially for short-term predictions.
Large granular lymphocytic (LGL) leukemia is a clonal lymphoproliferative disorder of CTL associated with cytopenias resulting from an immune and cytokine attack on hemopoietic progenitor cells. Extreme clonality of CTL expansions seen in LGL leukemia makes it an ideal model to study the role of the T cell repertoire in other less-polarized immune-mediated disorders. Complementarity-determining region 3 (CDR3) of the TCR is a unique Ag-specific region that can serve as a molecular marker, or clonotype, of the disease-specific T cells. We studied the variable portion of the β-chain spectrum in a cohort of LGL leukemia patients. The CDR3 sequences were determined for the immunodominant clones and used to design clonotype-specific primers. By direct and semi-nested amplification, clonotype amplicons were found to be shared by multiple patients and controls. Analysis of the generated sequences demonstrated that the original clonotypes are rarely encountered in normal control samples; however, high levels of homology were found in both controls and patients. Clonotypes derived from individual LGL patients can be used as tumor markers for the malignant clone. More generally, clonotypic analysis and comparison of the variable portion of the β-chain CDR3-specific sequences from a large number of patients may lead to better subclassification of not only LGL but also other immune-mediated disorders.
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. Significance Statement This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.
Highlights We present results from an ethnographic study on Venezuelan migrants’ access to healthcare in seven Latin American cities. COVID-19 has worsened conditions of informality and health inequities for Venezuelan migrants. The main obstacles to healthcare access are legal, financial, and relating to discrimination and information asymmetry. Migrants rely on alternative care, such as telemedicine, extralegal doctors, and pharmacies.
Critical Care 2017, 21(Suppl 1):P349 Introduction Imbalance in cellular energetics has been suggested to be an important mechanism for organ failure in sepsis and septic shock. We hypothesized that such energy imbalance would either be caused by metabolic changes leading to decreased energy production or by increased energy consumption. Thus, we set out to investigate if mitochondrial dysfunction or decreased energy consumption alters cellular metabolism in muscle tissue in experimental sepsis. Methods We submitted anesthetized piglets to sepsis (n = 12) or placebo (n = 4) and monitored them for 3 hours. Plasma lactate and markers of organ failure were measured hourly, as was muscle metabolism by microdialysis. Energy consumption was intervened locally by infusing ouabain through one microdialysis catheter to block major energy expenditure of the cells, by inhibiting the major energy consuming enzyme, N+/K + -ATPase. Similarly, energy production was blocked infusing sodium cyanide (NaCN), in a different region, to block the cytochrome oxidase in muscle tissue mitochondria. Results All animals submitted to sepsis fulfilled sepsis criteria as defined in Sepsis-3, whereas no animals in the placebo group did. Muscle glucose decreased during sepsis independently of N+/K + -ATPase or cytochrome oxidase blockade. Muscle lactate did not increase during sepsis in naïve metabolism. However, during cytochrome oxidase blockade, there was an increase in muscle lactate that was further accentuated during sepsis. Muscle pyruvate did not decrease during sepsis in naïve metabolism. During cytochrome oxidase blockade, there was a decrease in muscle pyruvate, independently of sepsis. Lactate to pyruvate ratio increased during sepsis and was further accentuated during cytochrome oxidase blockade. Muscle glycerol increased during sepsis and decreased slightly without sepsis regardless of N+/K + -ATPase or cytochrome oxidase blocking. There were no significant changes in muscle glutamate or urea during sepsis in absence/presence of N+/K + -ATPase or cytochrome oxidase blockade. ConclusionsThese results indicate increased metabolism of energy substrates in muscle tissue in experimental sepsis. Our results do not indicate presence of energy depletion or mitochondrial dysfunction in muscle and should similar physiologic situation be present in other tissues, other mechanisms of organ failure must be considered. , and long-term follow up has shown increased fracture risk [2]. It is unclear if these changes are a consequence of acute critical illness, or reduced activity afterwards. Bone health assessment during critical illness is challenging, and direct bone strength measurement is not possible. We used a rodent sepsis model to test the hypothesis that critical illness causes early reduction in bone strength and changes in bone architecture. Methods 20 Sprague-Dawley rats (350 ± 15.8g) were anesthetised and randomised to receive cecal ligation and puncture (CLP) (50% cecum length, 18G needle single pass through anterior and posterior wa...
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