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Vincenzo Isola,1 Danilo Mazzacane,1 Noemi Defelice,1 Antonio D’Amico,1 Laura Dezza,2 Antonio Marti,3 Alfredo Pece,1,41Department of Ophthalmology, Melegnano Hospital, 2Oncology Service, 3Department of Radiology, 4Fondazione Retina 3000, Milan, ItalyAbstract: This report documents a case of T cell lymphoma manifesting only with a conjunctival mass. A 67-year-old man underwent a diagnostic punch biopsy, histopathological examination, and immunohistochemical study for a pink-yellow colored mass infiltrating the bulbar conjunctiva in the lower fornix of the eyelid. A biopsy specimen of the conjunctival mass was found histopathologically to be a malignant T cell lymphoma. Systemic involvement was diagnosed within four weeks after the initial diagnosis by computed tomography, showing evidence of extension at the level of the ethmoidal cells, optic nerve, periorbital tissue, and pancreas. T cell lymphoma of the conjunctiva as a primary manifestation of systemic cancer is an uncommon entity. Punch biopsy may be the first diagnostic pathway useful to initiate a search for systemic involvement of a malignant lymphoid tumor of T cell lineage.Keywords: conjunctiva, cancer, T cell lymphoma, biopsy

Background: We have an incomplete understanding of COVID-19 characteristics at hospital presentation and whether underlying subphenotypes are associated with clinical outcomes and therapeutic responses., Methods: For this cross-sectional study, we extracted electronic health data from adults hospitalized between 1 March and 30 August 2020 with a PCR-confirmed diagnosis of COVID-19 at five New York City Hospitals. We obtained clinical and laboratory data from the first 24 h of the patient's hospitalization. Treatment with tocilizumab and convalescent plasma was assessed over hospitalization. The primary outcome was mortality; secondary outcomes included intubation, intensive care unit (ICU) admission and length of stay (LOS). First, we employed latent class analysis (LCA) to identify COVID-19 subphenotypes on admission without consideration of outcomes and assigned each patient to a subphenotype. We then performed robust Poisson regression to examine associations between COVID-19 subphenotype assignment and outcome. We explored whether the COVID-19 subphenotypes had a differential response to tocilizumab and convalescent plasma therapies., Results: A total of 4620 patients were included. LCA identified six subphenotypes, which were distinct by level of inflammation, clinical and laboratory derangements and ranged from a hypoinflammatory subphenotype with the fewest derangements to a hyperinflammatory with multiorgan dysfunction subphenotypes. Multivariable regression analyses found differences in risk for mortality, intubation, ICU admission and LOS, as compared to the hypoinflammatory subphenotype. For example, in multivariable analyses the moderate inflammation with fever subphenotype had 3.29 times the risk of mortality (95% CI 2.05, 5.28), while the hyperinflammatory with multiorgan failure subphenotype had 17.87 times the risk of mortality (95% CI 11.56, 27.63), as compared to the hypoinflammatory subphenotype. Exploratory analyses suggested that subphenotypes may differential respond to convalescent plasma or tocilizumab therapy., Conclusion: COVID-19 subphenotype at hospital admission may predict risk for mortality, ICU admission and intubation and differential response to treatment.KEY MESSAGEThis cross-sectional study of COVID patients admitted to the Mount Sinai Health System, identified six distinct COVID subphenotypes on admission. Subphenotypes correlated with ICU admission, intubation, mortality and differential response to treatment.

Was this a case of the "great masquerader"? Or was it something else?

Air pollution exposures during training may impact race preformances. We aggregated data on 334 collegiate male track & field athletes from 46 universities across the United States over 2010-2014. Using distributed lag non-linear models, we analyzed the relationship between race time and PM 2.5 , ozone, and two versions of the Air Quality Index (AQI) exposures up to 21 days prior to the race. We observed a 12.8 (95% CI: 1.3, 24.2) second and 11.5 (95% CI: 0.8, 22.1) second increase in race times from 21 days of PM 2.5 exposure (10.0 versus 5.0 μg/m 3 ) and ozone exposure (54.9 versus 36.9 ppm), respectively. Exposure measured by the two-pollutant threshold (PM 2.5 and ozone) AQI was not significantly associated with race time; however, the association for summed two-pollutant AQI (PM 2.5 plus ozone) was similar to associations observed for the individual pollutants (12.4, 95% CI: 1.8, 23.0 s). Training and competing at elevated air pollution levels, even at exposures within AQI's good-to-moderate classifications, was associated with slower race times. This work provides an initial characterization of the effect of air pollution on running performance and a justification for why coaches should consider approaches to reduce air pollution exposures while training., (© 2023. The Author(s).)

Background: West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement., Methods: We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill., Results: Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill., Conclusions: Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases)., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus that causes coronavirus disease 2019 (COVID-19). One of the main topics of conversation in these past months in the world of immunology has been the issue of how patients with immune defects will fare if they contract this infection. To date there has been limited data on larger cohorts of patients with Inborn Errors of Immunity (IEI) diagnosed with COVID-19. Here, we review the data of COVID-19 infections in a single center cohort of 113 patients from the Mount Sinai Immunodeficiency program, who had 132 infections between January 2020 and June 2022. This included 56 males and 57 females, age range 2 - 84 (median 42). The mortality rate was 3%. Comparison between admitted patients revealed a significantly increased risk of hospitalization amongst the unvaccinated patients, 4% vaccinated vs 40% unvaccinated; odds ratio 15.0 (95% CI 4.2 - 53.4; p <0.00001). Additionally, COVID anti-spike antibody levels, determined in 36 of these patients post vaccination and before infection, were highly variable., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Cousins, DeFelice, Jeong, Feng, Lee, Rotella, Sanchez, Jaber, Agarwal, Ho and Cunningham-Rundles.)

Rationale: Risk factors for coronavirus disease (COVID-19) mortality may include environmental exposures such as air pollution. Objectives: To determine whether, among adults hospitalized with PCR-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), long-term air pollution exposure is associated with the risk of mortality, ICU admission, or intubation. Methods: We performed a retrospective analysis of SARS-CoV-2 PCR-positive patients admitted to seven New York City hospitals from March 8, 2020, to August 30, 2020. The primary outcome was mortality; secondary outcomes were ICU admission and intubation. We estimated the annual average fine particulate matter (particulate matter ⩽2.5 μm in aerodynamic diameter [PM 2.5 ]), nitrogen dioxide (NO 2 ), and black carbon (BC) concentrations at patients' residential address. We employed double robust Poisson regression to analyze associations between the annual average PM 2.5 , NO 2 , and BC exposure level and COVID-19 outcomes, adjusting for age, sex, race or ethnicity, hospital, insurance, and the time from the onset of the pandemic. Results: Among the 6,542 patients, 41% were female and the median age was 65 (interquartile range, 53-77) years. Over 50% self-identified as a person of color ( n  = 1,687 [26%] Hispanic patients; n  = 1,659 [25%] Black patients). Air pollution exposure levels were generally low. Overall, 31% ( n  = 2,044) of the cohort died, 19% ( n  = 1,237) were admitted to the ICU, and 16% ( n  = 1,051) were intubated. In multivariable models, a higher level of long-term exposure to PM 2.5 was associated with an increased risk of mortality (risk ratio, 1.11 [95% confidence interval, 1.02-1.21] per 1-μg/m 3 increase in PM 2.5 ) and ICU admission (risk ratio, 1.13 [95% confidence interval, 1.00-1.28] per 1-μg/m 3 increase in PM 2.5 ). In multivariable models, neither NO 2 nor BC exposure was associated with COVID-19 mortality, ICU admission, or intubation. Conclusions: Among patients hospitalized with COVID-19, a higher long-term PM 2.5 exposure level was associated with an increased risk of mortality and ICU admission.

Background: Air pollution health studies have been increasingly using prediction models for exposure assessment even in areas without monitoring stations. To date, most studies have assumed that a single exposure model is correct, but estimated effects may be sensitive to the choice of exposure model., Methods: We obtained county-level daily cardiovascular (CVD) admissions from the New York (NY) Statewide Planning and Resources Cooperative System (SPARCS) and four sets of fine particulate matter (PM 2.5 ) spatio-temporal predictions (2002-2012). We employed overdispersed Poisson models to investigate the relationship between daily PM 2.5 and CVD, adjusting for potential confounders, separately for each state-wide PM 2.5 dataset., Results: For all PM 2.5 datasets, we observed positive associations between PM 2.5 and CVD. Across the modeled exposure estimates, effect estimates ranged from 0.23% (95%CI: -0.06, 0.53%) to 0.88% (95%CI: 0.68, 1.08%) per 10 µg/m 3 increase in daily PM 2.5 . We observed the highest estimates using monitored concentrations 0.96% (95%CI: 0.62, 1.30%) for the subset of counties where these data were available., Conclusions: Effect estimates varied by a factor of almost four across methods to model exposures, likely due to varying degrees of exposure measurement error. Nonetheless, we observed a consistently harmful association between PM 2.5 and CVD admissions, regardless of model choice., (© 2021. The Author(s).)

The COVID-19 pandemic has yielded disproportionate impacts on communities of color in New York City (NYC). Researchers have noted that social disadvantage may result in limited capacity to socially distance, and consequent disparities. We investigate the association between neighborhood social disadvantage and the ability to socially distance, infections, and mortality in Spring 2020. We combine Census Bureau and NYC open data with SARS-CoV-2 testing data using supervised dimensionality-reduction with Bayesian Weighted Quantile Sums regression. The result is a ZIP code-level index with weighted social factors associated with infection risk. We find a positive association between neighborhood social disadvantage and infections, adjusting for the number of tests administered. Neighborhood disadvantage is also associated with a proxy of the capacity to socially isolate, NYC subway usage data. Finally, our index is associated with COVID-19-related mortality.

Efficient contact tracing and testing are fundamental tools to contain the transmission of SARS-CoV-2. We used multi-agent simulations to estimate the daily testing capacity required to find and isolate a number of infected agents sufficient to break the chain of transmission of SARS-CoV-2, so decreasing the risk of new waves of infections. Depending on the non-pharmaceutical mitigation policies in place, the size of secondary infection clusters allowed or the percentage of asymptomatic and paucisymptomatic (i.e., subclinical) infections, we estimated that the daily testing capacity required to contain the disease varies between 0.7 and 9.1 tests per thousand agents in the population. However, we also found that if contact tracing and testing efficacy dropped below 60% (e.g. due to false negatives or reduced tracing capability), the number of new daily infections did not always decrease and could even increase exponentially, irrespective of the testing capacity. Under these conditions, we show that population-level information about geographical distribution and travel behaviour could inform sampling policies to aid a successful containment, while avoiding concerns about government-controlled mass surveillance., Competing Interests: The authors have declared that no competing interests exist.

Structural variations of neural regions implicated in fear responses have been well documented in the pathophysiology of anxiety and may play an important role in treatment response. We examined whether gray matter volume of three neural regions supporting fear and avoidance responses [bilateral amygdala, nucleus accumbens (NAcc), and ventromedial prefrontal cortex (PFC)] predicted cognitive-behavioral therapy (CBT) and selective serotonin reuptake inhibitor (SSRI) treatment outcome in two independent samples of patients with anxiety disorders. Study 1 consisted of 81 adults with anxiety disorders and Study 2 included 55 children and adolescents with anxiety disorders. In both studies, patients completed baseline structural MRI scans and received either CBT or SSRI treatment. Clinician-rated interviews of anxiety symptoms were assessed at baseline and posttreatment. Among the adult sample, greater pre-treatment bilateral NAcc volume was associated with a greater reduction in clinician-rated anxiety symptoms pre-to-post CBT and SSRI treatment. Greater left NAcc volume also predicted greater decreases in clinician-rated anxiety symptoms pre-to-post CBT and SSRI treatment among youth with current anxiety. Across studies, results were similar across treatments, and findings were maintained when adjusting for patient's age, sex, and total intracranial brain volume. We found no evidence for baseline amygdala or ventromedial PFC volume serving as treatment predictors across the two samples. Together, these findings provide promising support for the role of NAcc volume as an objective marker of anxiety treatment improvement that spans across development. Future studies should clarify the specific mechanisms through which NAcc volume exerts its therapeutic effects.

Importance: West Nile virus (WNV) is the leading cause of domestically acquired arboviral disease., Objective: To develop real-time WNV forecasts of infected mosquitoes and human cases., Design, Setting, and Participants: Real-time forecasts of WNV in 4 geographically dispersed locations in the United States were generated using a WNV model-inference forecasting system previously validated with retrospective data. Analysis was performed to evaluate how observational reporting delays of mosquito WNV assay results and human medical records were associated with real-time forecast accuracy., Exposures: Mosquitoes positive for WNV and human cases., Main Outcomes and Measures: Delays in reporting mosquito WNV assay results and human medical records and the association of these delays with real-time WNV forecast accuracy., Results: Substantial delays in data reporting exist for both infected mosquitoes and human WNV cases. For human cases, confirmed data (n = 37) lagged behind the onset of illness by a mean (SD) of 5.5 (2.3) weeks (range, 2-14 weeks). These human case reporting lags reduced mean forecast accuracy for the total number of human cases over the season in 110 simulated outbreaks for 2 forecasting systems by 26% and 14%, from 2 weeks before to 3 weeks after the predicted peak of infected mosquitoes. This period is the time span during which 47% of human cases are reported. Of 7064 mosquito pools, 500 (7%) tested positive; the reporting lag for these data associated with viral testing at a state laboratory was a mean (SD) of 6.6 (2.6) days (range, 4-11 days). This reporting lag was associated with decreased mean forecast accuracy for the 3 mosquito infection indicators, timing, magnitude, and season, by approximately 5% for both forecasting systems., Conclusions and Relevance: Delays in reporting human WNV disease and infected mosquito information are associated with difficulties in outbreak surveillance and decreased real-time forecast accuracy. Infected mosquito lags were short enough that skillful forecasts could still be generated for mosquito infection indicators, but the human WNV case lags were too great to support accurate forecasting in real time. Forecasting WNV is potentially an important evidence-based decision support tool for public health officials and mosquito abatement districts; however, to operationalize real-time forecasting, more resources are needed to reduce human case reporting lags between illness onset and case confirmation.

Background: This study estimates the potential health gains achievable in the United Arab Emirates (UAE) with improved controls on environmental pollution. The UAE is an emerging economy in which population health risks have shifted rapidly from infectious diseases to chronic conditions observed in developed nations. The UAE government commissioned this work as part of an environmental health strategic planning project intended to address this shift in the nature of the country's disease burden., Methods and Findings: We assessed the burden of disease attributable to six environmental exposure routes outdoor air, indoor air, drinking water, coastal water, occupational environments, and climate change. For every exposure route, we integrated UAE environmental monitoring and public health data in a spatially resolved Monte Carlo simulation model to estimate the annual disease burden attributable to selected pollutants. The assessment included the entire UAE population (4.5 million for the year of analysis). The study found that outdoor air pollution was the leading contributor to mortality, with 651 attributable deaths (95% confidence interval [CI] 143-1,440), or 7.3% of all deaths. Indoor air pollution and occupational exposures were the second and third leading contributors to mortality, with 153 (95% CI 85-216) and 46 attributable deaths (95% CI 26-72), respectively. The leading contributor to health-care facility visits was drinking water pollution, to which 46,600 (95% CI 15,300-61,400) health-care facility visits were attributed (about 15% of the visits for all the diseases considered in this study). Major study limitations included (1) a lack of information needed to translate health-care facility visits to quality-adjusted-life-year estimates and (2) insufficient spatial coverage of environmental data., Conclusions: Based on international comparisons, the UAE's environmental disease burden is low for all factors except outdoor air pollution. From a public health perspective, reducing pollutant emissions to outdoor air should be a high priority for the UAE's environmental agencies.

Human pancreatic islet transplantation offers diabetic patients tight glucose control but has low graft survival rates. The immunosuppressive drugs that are administered to graft recipients lack the antiinflammatory benefits of corticosteroids because of their diabetogenic effects. The serum protease inhibitor alpha1-antitrypsin (AAT) possesses antiinflammatory properties and reduces cytokine-mediated islet damage. In the present study, diabetic mice were grafted with allogeneic islets and treated with AAT monotherapy (n = 24). After 14 days of treatment, mice remained normoglycemic and islet allografts were functional for up to 120 treatment-free days. After graft removal and retransplantation, mice accepted same-strain islets but rejected third-strain islets, thus confirming that specific immune tolerance had been induced. Explanted grafts exhibited a population of T regulatory cells in transplant sites. According to RT-PCR, grafts contained high levels of mRNA for foxp3, cytotoxic T lymphocyte antigen-4, TGF-beta, IL-10, and IL-1 receptor antagonist; expression of proinflammatory mediators was low or absent. After implantation of skin allografts, AAT-treated mice had greater numbers of foxp3-positive cells in draining lymph nodes (DLNs) compared with control treatment mice. Moreover, dendritic cells in DLNs exhibited an immature phenotype with decreased CD86 activation marker. Although the number of CD3 transcripts decreased in the DLNs, AAT did not affect IL-2 activity in vitro. Thus, AAT monotherapy provides allografts with antiinflammatory conditions that favor development of antigen-specific T regulatory cells. Because AAT treatment in humans is safe, its use during human islet transplantation may be considered.