Storm Development Research Articles

Extreme rainfall events in the West African Sahel: Understanding storm development over the Damergou gap using convection‐permitting simulations in the Weather Research and Forecasting model

AbstractExtreme rainfall events in the West African Sahel can be impactful, yet we do not completely understand why such storms develop. Here, we utilize NASA long‐term Integrated Multi‐satellitE Retrievals for Global precipitation measurement (IMERG) rainfall estimates, various atmospheric reanalyses, and Weather Research and Forecasting (WRF) convection‐permitting simulations to further examine the regional/local conditions that led to the development of two extreme events over the Damergou Gap of Niger/Nigeria identified in a prior study. The August 20, 2019 central Niger event is associated with the passage of a westward‐moving convective line. A strong thermal low over eastern Niger preconditions the environment by increasing the atmospheric moisture and vertical wind shear. Cold‐pool outflow boundaries generated from afternoon convection over the higher terrain ahead of the approaching line enhances convergence along the line while slowing down the system's movement, resulting in higher‐intensity rainfall for a longer time over the region. The July 19, 2001 northern Nigerian event has rainfall developing over the Jos Plateau in the afternoon. Guinean Highland ridging combined with low pressure over Niger/Chad produces a strong low‐level height gradient associated with the development of a strong southwesterly flow surge that transports tropical moisture into the region. This surge interacts with the equatorward migration of the Sahel–tropical Africa dryline, enhancing the convergence and convection north of the Jos Plateau. Our results indicate that while extreme rainfall in the Damergou Gap is likely to occur in anomalously moist environments, it is not necessarily associated with highly unstable environments (e.g., convective available potential energy [CAPE] >2,500 J·kg−1). Furthermore, interactions with cold‐pool outflow boundaries generated from other convective areas is important, and local terrain features are influential in the development of such convective areas.

Hypoglycemia in patients with COVID-19: risk factors and prevention of complications

The aim of the work is to analyze the available scientific information and generalize the main results of modern research on the causes and risk factors of hypoglycemia in patients with COVID-19. Materials and methods. A search and analysis of full-text articles was carried out in the PubMed, Web of Science, Google Scholar, and Scopus databases. The search was conducted using the key terms: COVID-19 and hypoglycemia, hypoglycemia in COVID-19 patients and treatment of COVID-19 and hypoglycemia from the beginning of the pandemic in December 2019 to July 1, 2022. Results. The analysis of literary sources made it possible to identify three groups of factors that lead to the occurrence of hypoglycemia in patients with COVID-19: peculiarities of the diabetes course in patients with COVID-19 and the influence of concomitant diseases, side effects of certain groups of drugs and methods of therapy and prevention; shortcomings in the organization of treatment and patient care. Hypoglycemia has been shown to be a risk factor for cardiovascular and total mortality in patients with diabetes, may trigger the development of a cytokine storm during COVID-19 disease, and negatively impact mortality and length of hospital stay in COVID-19. Conclusions. To prevent hypoglycemic states in patients, one should avoid sudden changes in the type and dose of hypoglycemic drugs, periodically monitor the HbA1c level, expand the reach of patients with virtual consultations and telemedicine programs. In the case of determining the program of treatment and vaccination against COVID-19 in patients with diabetes mellitus, the known and possible hypoglycemic effects of drugs and vaccines should be taken into account.

Monitoring storm evolution using a high-density seismic network

Data acquired by a dense seismic network deployed in the Cerdanya basin (Eastern Pyrenees) is used to track the temporal and spatial evolution of meteorological events such as rainfall episodes or thunderstorms. Comparing seismic and meteorological data, we show that for frequencies above 40 Hz, the dominant source of seismic noise is rainfall and hence the amplitude of the seismic data can be used as a proxy of rainfall. The interstation distance of 1.5 km provides an unprecedented spatial resolution of the evolution of rainfall episodes along the basin. Two specific episodes, one dominated by stratiform rain and the second one dominated by convective rain, are analyzed in detail, using high resolution disdrometer data from a meteorological site near one of the seismic instruments. Seismic amplitude variations follow a similar evolution to radar reflectivity values, but in some stratiform precipitation cases, it differs from the radar-derived precipitation estimates in this region of abrupt topography, where radar may suffer antenna beam blockage. Hence, we demonstrate the added value of seismic data to complement other sources of information such as rain-gauge or weather radar observations to describe the evolution of ground-level rainfall fields at high spatial and temporal resolution. The seismic power and the rainfall intensity have an exponential relationship and the periods with larger seismic power are coincident. The time intervals with rain drops diameters exceeding 3.5 mm do not result in increased seismic amplitudes, suggesting that there is a threshold value from which seismic data are no longer proportional to the size of the drops. Thunderstorms can be identified by the recording of the sonic waves generated by thunders, with. Single thunders detected to distances of a few tens of kilometers. As the propagation of these acoustic waves is expected to be strongly affected by parameters as air humidity, temperature variations or wind, the seismic data could provide an excellent tool to investigate atmospheric properties variations during thunderstorms.

Unconventional secretion of unglycosylated ORF8 is critical for the cytokine storm during SARS-CoV-2 infection.

Coronavirus disease 2019 is a respiratory infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Evidence on the pathogenesis of SARS-CoV-2 is accumulating rapidly. In addition to structural proteins such as Spike and Envelope, the functional roles of non-structural and accessory proteins in regulating viral life cycle and host immune responses remain to be understood. Here, we show that open reading frame 8 (ORF8) acts as messenger for inter-cellular communication between alveolar epithelial cells and macrophages during SARS-CoV-2 infection. Mechanistically, ORF8 is a secretory protein that can be secreted by infected epithelial cells via both conventional and unconventional secretory pathways. Conventionally secreted ORF8 is glycosylated and loses the ability to recognize interleukin 17 receptor A of macrophages, possibly due to the steric hindrance imposed by N-glycosylation at Asn78. However, unconventionally secreted ORF8 does not undergo glycosylation without experiencing the ER-Golgi trafficking, thereby activating the downstream NF-κB signaling pathway and facilitating a burst of cytokine release. Furthermore, we show that ORF8 deletion in SARS-CoV-2 attenuates inflammation and yields less lung lesions in hamsters. Our data collectively highlights a role of ORF8 protein in the development of cytokine storms during SARS-CoV-2 infection.

Potential Weakening of the June 2012 North American Derecho Under Future Warming Conditions

AbstractDerechos are widespread and long‐lived straight‐line windstorms associated with fast‐moving mesoscale convective systems that cause severe life and property loss. This study investigates how the June 2012 North American derecho could unfold in the future with global warming. Convection‐permitting regional model ensemble simulations of the derecho as observed are compared with simulations under a pseudo‐global warming scenario of the future environments by the end of the 21st century following the Shared Socioeconomic Pathways (SSP5‐8.5). The control simulations can well reproduce the observed derecho features, including storm evolution, surface wind, and precipitation, except for a 2‐hr delay relative to observations. Compared to the control simulations, the derecho shrinks and decays earlier in the future environments, with much less destructive impacts on the Mid‐Atlantic coastal areas. The derecho shrinkage is attributed to lower relative humidity on both sides of the derecho propagation path under global warming, which suppresses updraft and strengthens downdraft, impeding the spatial extent of the derecho. The premature decay is due to the intensification of an isolated deep convection (IDC) event that develops ahead of the derecho. The meridional gradient of future warming strengthens the synoptic environments, enhancing convergence in a corridor of higher instability that facilitates intensification and continuous development of the IDC. By consuming energy and moisture on the derecho propagation path, the IDC hinders the derecho development in the Mid‐Atlantic coastal areas. Focusing on a single derecho, this study reveals how changes in the thermodynamic environment with warming could induce complex changes in the derecho.

Endothelial dysfunction in patients with COVID-19 is a key mechanism for the development of complications

SARS-CoV-2, a novel coronavirus infection that primarily affects the lungs, can induce multi-organ involvement. Arterial hypertension (AH), diabetes mellitus (DM), and obesity increase the risk of severe COVID-19, up to and including the development of a fatal cytokine storm. The risk of severe SARS-CoV-2 infection in persons with obesity and DM is associated with baseline systemic inflammation and immune system dysfunction. In addition, this category of patients is more likely to have post-COVID-19 syndrome and worsen the course of chronic diseases. Endothelial damage – direct (SARS-CoV-2 infection) and indirect (systemic inflammation) may play a crucial role in the development of COVID-19 complications. Angiotensin-converting enzyme 2 (ACE-2) expressed in human endothelium plays a fundamental role in the new coronavirus infection. SARS-CoV-2 uses it as a receptor to enter the cell, which leads to a decrease in the bioavailability of ACE-2 on the endotheliocytes surface. Once inside, the virus induces its apoptosis, leading to the development of a proinflammatory and procoagulant state and, as a result, vascular damage. Drugs including ACE inhibitors, ARB, beta-blockers, and statins are widely prescribed to patients with DM, AH, and CHD, the groups most at risk for COVID-19, and their effects on the endothelium are well known. New classes of hypoglycemic drugs, particularly glucagon-like peptide 1 (GLP-1) receptor agonists, have demonstrated the ability to affect systemic inflammation and improve prognosis in DM and CHD patients. In addition, they have a positive effect on BP and metabolic profile. The proven reduction in weight on the background of the use of GLP-1 may be an additional factor in determining the choice of this class of drugs. These effects can be used in COVID-19 patients with a high risk of severe course, as well as in persons with obesity in the post-COVID-19 condition.

Environment of severe storm formations over West Africa on the 26‐28 June 2018

AbstractUnderstanding the environmental evolution of mesoscale convective systems (MCSs) is critical for forecasting weather in West Africa. This study investigated the thermodynamic and synoptic environments of MCSs over West Africa on 26 (storm 1) and 28 (storm 2) June 2018. Primary datasets used to assess the diurnal evolution of the storms were obtained from ERA5. The results showed a trapped gravity wave, enhanced by a well‐established African Easterly Jet and monsoon trough, was responsible for the initiation of storm 1. Both storms also initiated in the presence of several moist lower (925–850 hPa) to mid‐tropospheric (600 hPa) cyclonic and anticyclonic vortices, controlling inland moisture advection. The lower troposphere was moistened through moisture advection by the West African westerly jet for storm 1 and the nocturnal low‐level jet prior to initiation for storm 2. For both storms, the evolution of outgoing longwave radiation showed a consistent atmosphere of deep afternoon convection. Boundary layer height increased significantly during storm evolution to support the increasing ascent of warm air. Vegetation cover differences may have also likely aided the evolution of storm 2. The passage of gravity waves from decaying storms can aid forecasters to nowcast likely regions of afternoon convection with high accuracy. Under the GCRF African Science for Weather Information and Forecasting Techniques (SWIFT), these findings are crucial in fulfilling the project's aims of improving weather forecasting capability and communication over West Africa.

Optical Design of a High Flux Setup in the Extreme Ultraviolet

Extreme ultraviolet (XUV) light applications are still a very promising field that was heavily enlivened by the definition of the new wavelength for semiconductor lithography within the XUV range. But the detection of XUV light is also important for the exploration in the field of space science (i.e., monitoring the formation and evolution of solar storms) and high-energy physics (i.e., dark matter detection). The advancement of this technology mainly depends on the performance optimization of XUV sources, optical systems and related photodetectors. In this work, the optical design of a high flux XUV setup was simulated and defined to optimise the beam path which is the backbone of the initial evaluation process for the characterisation of luminescent materials under XUV irradiation. Additionally, the paper focused on the conceptualisation and realisation of the experimental setup as well as the alignment of the optical components and the detector calibration.

Radar Composite Reflectivity Reconstruction Based on FY-4A Using Deep Learning

Weather radars are commonly used to track the development of convective storms due to their high resolution and accuracy. However, the coverage of existing weather radar is very limited, especially in mountainous and ocean areas. Geostationary meteorological satellites can provide near global coverage and near real-time observations, which can compensate for the lack of radar observations. In this paper, a deep learning method was used to estimate the radar composite reflectivity from observations of China's new-generation geostationary meteorological satellite FY-4A and topographic data. The derived radar reflectivity products from satellite observations can be used over regions without radar coverage. In general, the deep learning model can reproduce the overall position, shape, and intensity of the radar echoes. In addition, evaluation of the reconstruction radar observations indicates that a modified model based on the attention mechanism (Attention U-Net model) has better performance than the traditional U-Net model in terms of all statistics such as the probability of detection (POD), critical success index (CSI), and root-mean-square error (RMSE), and the modified model has stronger capability on reconstructing details and strong echoes.

Cholinergic dysfunction in COVID-19: frantic search and hoping for the best.

A novel coronavirus known as severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is a potential cause of acute respiratory infection called coronavirus disease 2019 (COVID-19). The binding of SARS-CoV-2 with angiotensin-converting enzyme 2 (ACE2) induces a series of inflammatory cellular events with cytopathic effects leading to cell injury and hyperinflammation. Severe SARS-CoV-2 infection may lead to dysautonomia and sympathetic storm due to dysfunction of the autonomic nervous system (ANS). Therefore, this review aimed to elucidate the critical role of the cholinergic system (CS) in SARS-CoV-2 infection. The CS forms a multi-faceted network performing diverse functions in the body due to its distribution in the neuronal and non-neuronal cells. Acetylcholine (ACh) acts on two main types of receptors which are nicotinic receptors (NRs) and muscarinic receptors (MRs). NRs induce T cell anergy with impairment of antigen-mediated signal transduction. Nicotine through activation of T cell NRs inhibits the expression and release of the pro-inflammatory cytokines. NRs play important anti-inflammatory effects while MRs promote inflammation by inducing the release of pro-inflammatory cytokines. SARS-CoV-2 infection can affect the morphological and functional stability of CS through the disruption of cholinergic receptors. SARS-CoV-2 spike protein is similar to neurotoxins, which can bind to nicotinic acetylcholine receptors (nAChR) in the ANS and brain. Therefore, cholinergic receptors mainly nAChR and related cholinergic agonists may affect the pathogenesis of SARS-CoV-2 infection. Cholinergic dysfunction in COVID-19 is due to dysregulation of nAChR by SARS-CoV-2 promoting the central sympathetic drive with the development of the sympathetic storm. As well, nAChR activators through interaction with diverse signaling pathways can reduce the risk of inflammatory disorders in COVID-19. In addition, nAChR activators may mitigate endothelial dysfunction (ED), oxidative stress (OS), and associated coagulopathy in COVID-19. Similarly, nAChR activators may improve OS, inflammatory changes, and cytokine storm in COVID-19. Therefore, nAChR activators like varenicline in virtue of its anti-inflammatory and anti-oxidant effects with direct anti-SARS-CoV-2 effect could be effective in the management of COVID-19.

Antigen-Specific T Cells and SARS-CoV-2 Infection: Current Approaches and Future Possibilities

COVID-19, a significant global health threat, appears to be an immune-related disease. Failure of effective immune responses in initial stages of infection may contribute to development of cytokine storm and systemic inflammation with organ damage, leading to poor clinical outcomes. Disease severity and the emergence of new SARS-CoV-2 variants highlight the need for new preventative and therapeutic strategies to protect the immunocompromised population. Available data indicate that these people may benefit from adoptive transfer of allogeneic SARS-CoV-2-specific T cells isolated from convalescent individuals. This review first provides an insight into the mechanism of cytokine storm development, as it is directly related to the exhaustion of T cell population, essential for viral clearance and long-term antiviral immunity. Next, we describe virus-specific T lymphocytes as a promising and efficient approach for the treatment and prevention of severe COVID-19. Furthermore, other potential cell-based therapies, including natural killer cells, regulatory T cells and mesenchymal stem cells are mentioned. Additionally, we discuss fast and effective ways of producing clinical-grade antigen-specific T cells which can be cryopreserved and serve as an effective "off-the-shelf" approach for rapid treatment of SARS-CoV-2 infection in case of sudden patient deterioration.

Ensemble Cloud Model Application in Simulating the Catastrophic Heavy Rainfall Event

An attempt has been made in the present research to simulate a deadly flash-flood event over the City of Skopje, Macedonia on 6 August 2016. A cloud model ensemble forecast method is developed to simulate a super-cell storm's initiation and evolutionary features. Sounding data are generated using an ensemble approach, that utilizes a triple-nested WRF model. A three-dimensional (3-D) convective cloud model (CCM) with a very fine horizontal grid resolution of 250-m is initialized, using the initial representative sounding data, derived from the WRF 1-km forecast outputs. CCM is configured and run with an open lateral boundary conditions LBC, allowing explicit simulation of convective scale processes. This preliminary study showed that the ensemble approach has some advantages in the generation of the initial data and the model initialization. The applied method minimizes the uncertainties and provides a more qualitative-quantitative assessment of super-cell storm initiation, cell structure, evolutionary properties, and intensity. A high-resolution 3-D run is capable to resolve detailed aspects of convection, including high-intensity convective precipitation. The results are significant not only from the aspect of the cloud model's ability to provide a qualitative-quantitative assessment of intense precipitation but also for a deeper understanding of the essence of storm development, its vortex dynamics, and the meaning of micro-physical processes for the production and release of large amounts of precipitation that were the cause of the catastrophic flood in an urban area. After a series of experiments and verification, such a system could be a reliable tool in weather services for very short-range forecasting (nowcasting) and early warning of weather disasters.

An update on angiotensin-converting enzyme 2 structure/functions, polymorphism, and duplicitous nature in the pathophysiology of coronavirus disease 2019: Implications for vascular and coagulation disease associated with severe acute respiratory syndrome coronavirus infection.

It has been known for many years that the angiotensin-converting enzyme 2 (ACE2) is a cell surface enzyme involved in the regulation of blood pressure. More recently, it was proven that the severe acute respiratory syndrome coronavirus (SARS-CoV-2) interacts with ACE2 to enter susceptible human cells. This functional duality of ACE2 tends to explain why this molecule plays such an important role in the clinical manifestations of coronavirus disease 2019 (COVID-19). At the very start of the pandemic, a publication from our Institute (entitled "ACE2 receptor polymorphism: susceptibility to SARS-CoV-2, hypertension, multi-organ failure, and COVID-19 disease outcome"), was one of the first reviews linking COVID-19 to the duplicitous nature of ACE2. However, even given that COVID-19 pathophysiology may be driven by an imbalance in the renin-angiotensin system (RAS), we were still far from understanding the complexity of the mechanisms which are controlled by ACE2 in different cell types. To gain insight into the physiopathology of SARS-CoV-2 infection, it is essential to consider the polymorphism and expression levels of the ACE2 gene (including its alternative isoforms). Over the past 2 years, an impressive amount of new results have come to shed light on the role of ACE2 in the pathophysiology of COVID-19, requiring us to update our analysis. Genetic linkage studies have been reported that highlight a relationship between ACE2 genetic variants and the risk of developing hypertension. Currently, many research efforts are being undertaken to understand the links between ACE2 polymorphism and the severity of COVID-19. In this review, we update the state of knowledge on the polymorphism of ACE2 and its consequences on the susceptibility of individuals to SARS-CoV-2. We also discuss the link between the increase of angiotensin II levels among SARS-CoV-2-infected patients and the development of a cytokine storm associated microvascular injury and obstructive thrombo-inflammatory syndrome, which represent the primary causes of severe forms of COVID-19 and lethality. Finally, we summarize the therapeutic strategies aimed at preventing the severe forms of COVID-19 that target ACE2. Changing paradigms may help improve patients' therapy.

PI3Kδ/γ Inhibitor Duvelisib Modulates Inflammatory Profile in Severe COVID-19 Patients: Results from a Randomized Placebo-Controlled Phase 2 Study

Background: ARDS following SARS-CoV-2 infection (COVID-19) is associated with the development of a hyper-inflammatory cytokine storm. Several anticancer drugs were repurposed for COVID-19 investigational treatment due to their favorable effect on immune profiles. Duvelisib (Copiktra, IPI-145, DUV) is an FDA-approved oral PI3K delta/gamma (PI3Kδ/γ) inhibitor for treating relapsed or refractory CLL/SLL and FL. PI3Kδ/γ inhibitors promote the formation of a pool of T-cells with a memory phenotype by inhibiting aerobic glycolysis, preventing T-cell activation-mediated terminal differentiation and exhaustion. Therefore, we hypothesized that duvelisib might limit hyperactivation of the immune system and mitigate T-cell exhaustion, promoting more effective anti-viral responses to SARS-CoV-2 and limiting the progression of COVID-19. Methods: DAMPEN-CI was a single-center randomized placebo-controlled phase 2 study evaluating the efficacy of duvelisib, a PI3Kδ/γ inhibitor, in reducing inflammation and the incidence of respiratory failure in non-intubated adults with severe (RR>30, HR>125, O2 sat<93%, and PaO2/FiO2<300) PCR- and X-Ray-confirmed COVID-19 pneumonia. Pts were analyzed per-protocol. The primary endpoints were the fraction of subjects who required mechanical ventilation or died within 29 days of randomization. Critical secondary endpoints included serious adverse events (SAE, Grade 3/4), ICU transfer, duration of hospitalization, oxygen use, inflammatory biomarkers (Ferritin, CRP, d-dimer), and serum cytokine levels (e.g COVID-19 progression related) detected by a high-sensitivity multiplex electrochemiluminescent immunoassay. Safety monitoring included serial blood counts and renal and hepatic function measurements. Results: A total of 47 pts (DUV=25, Placebo=22) were enrolled and randomized to receive DUV 25mg orally b.i.d or matching placebo for up to 14 days. The median age of the pts was 57 years. Baseline characteristics were well balanced between both arms (Table) other than pts in the DUV arm had shorter duration of symptoms at enrollment (7 vs. 9.5 days; p=0.003). All pts received remdesivir and dexamethasone as standard treatment. Median doses of study drug and days on treatment were 7 (5 vs. 7.5; p=0.142) and 4 (3 vs. 4.5; p=0.149), comparing DUV vs. placebo arms, respectively. One pt in the placebo arm died on Day 29. No significant difference was found in the primary composite endpoint of death or mechanical ventilation (12% vs. 13.64%; p=1.000) or ICU transfers (3 vs. 3). The PaO2/FiO2 ratio trended higher, and the chest X-ray severity score was lower in the DUV arm during the recovery phase (>Day 17). The SAE numbers (6 (0.24) vs 3 (0.14); p=0.373), median days of hospitalization (4 vs 5.5; p=0.909), oxygen use on day 15 (41.67% vs 40.91%; p=0.958) and day 29 (30.43% vs 28.57%; p=0.868) showed no significant differences in DUV vs. placebo arm (Table). Serum levels of IL-2 was significantly lower at early timepoints (Day 2-4) in subjects randomized to the DUV Arm. IL-2RA, IL-10, TNF-α, and MIP-1α/CCL3 were generally lower in DUV-treated subjects during the first two weeks. IL-6, IL-8, IP-10/CXCL10, and MCP-1/CCL2 levels were not significantly different between arms (Figure). Inflammatory biomarkers (Ferritin, CRP, d-dimer), anti-SARS Cov-2 IgG, and hematological parameters (CBC, CMP) were not significantly different between arms. Conclusions: The administration of short-course duvelisib to pts with severe COVID-19 was safe and did not impair serological response to SARS-CoV-2. While duvelisib reduced levels of IL-2, IL-2RA, and TNF-α, clinical outcomes for duvelisib-treated patients did not significantly improve compared to control subjects. The small sample size and sampling restricted to a short hospitalization may have limited the observed effects of duvelisib on other cytokines in the blood. These data suggest a regulatory role for the PI3K/AKT/mTOR pathway in T cell response to COVID-19 progression and the potential efficacy of duvelisib in treating pts with hyper-inflammatory conditions. Early initiation, and/or higher-dose, longer-term treatment might be necessary to achieve clinical therapeutic benefits. Further high-dimensional analysis on immunophenotyping of immune cells is needed to determine the effect of duvelisib in altering immune profile, mitigating T-cell exhaustion, and enhancing anti-viral adaptive immunity. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

An Ex Vivo Monocyte Stimulation Test Predicts Severity of COVID-19 Infection in Patients with Chronic Lymphocytic Leukemia (CLL)

Introduction The severity of coronavirus disease 2019 (COVID-19) is associated with the development of a cytokine storm driven by classical monocytes. Activation of the NLRP3 inflammasome mediates the production of IL-1β - a key pro-inflammatory cytokine that in excessive quantities causes tissue injury. Most CLL patients have an impaired humoral response to vaccination with subsequent higher risk of complications from COVID-19 infection. Currently, no pre-exposure test exists to assess the risk of a dysregulated immune response to COVID-19. We previously reported that open reading frame 8 (ORF8), a SARS-CoV-2 protein, when glycosylated and secreted into the blood, stimulates CD14+ monocytes and activates the NLRP3 pathway to produce IL-1β (Ruan et al, AAI 2022). We hypothesized that functional characteristics of CLL patients’ monocytes may predispose patients to develop severe COVID-19. First, we developed the ORF8 monocyte stimulation test (OMST), which measures monocyte reactivity via flow cytometry after stimulation of patient monocytes ex vivo with ORF8. Secondly, we applied the OMST to CLL patients to learn about its association with severe COVID-19 infection. Methods We identified patients from the Mayo Clinic CLL Database who were diagnosed with COVID-19 infection via a positive SARS-CoV-2 RT-PCR nasal swab between July 2020 to February 2022 and had a cryopreserved pre-COVID-19 peripheral blood mononuclear sample (PBMC) available. Our study was approved by the IRB, and samples were stored in the Mayo Clinic Predolin Biobank. For the OMST, samples were thawed and either stimulated with ORF8 or unstimulated (control) for 24 hours. The samples were harvested and intracellular cytokine/chemokine levels (IL-1β, IL-8, and CCL-2) in monocytes were analyzed by flow cytometry using the depicted gating strategy and formulas to calculate delta MFI (dMFI) and adjusted MFI (Figure 1). Clinical outcomes were abstracted by chart review. Severe infection was defined as hospitalization due to COVID-19 infection. Fisher's exact test, Wilcoxon rank sum test, and matched paired analysis were used to compare categorical, continuous, and paired variables, respectively. Receiver-operating curves (ROC) were used to calculate the area under the curve (AUC), sensitivity, specificity, and optimal cutoff levels for a reactive OMST. The optimal cutoff point was chosen as the point with the highest Youden index. Time to severe COVID-19 infection was calculated using the Kaplan-Meier method and associations of factors with severe COVID-19 were assessed using Cox proportional hazard model (CPHM). Results 60 patients were identified. The median age at COVID-19 diagnosis was 74 years (63-80). The median number of COVID-19 vaccinations before infection was 0 (range 0-3). The median time interval between vaccination and infection was 106 days (2-322). At diagnosis, 25 (42%) patients were receiving CLL-directed therapy and 22 (37%) were on a BTK-inhibitor. 22 patients had severe COVID-19 and 6 patients died. The OMST demonstrated that CD14+ monocytes had a significantly higher dMFI for IL-1β, IL-8, and CCL-2 after ORF8 stimulation compared to controls (495 vs. 158, p<0.0001), (298 vs. 121, p<0.001), and (385 vs. 171, p <0.0001) respectively. By ROC analysis, the AUC for IL-1β adjusted MFI was 0.68, 0.67 for IL-8 adjusted MFI, and 0.37 for CCL-2 adjusted MFI. A reactive OMST was defined by ROC as an IL-1β adjusted MFI >= 0.18 (sensitivity 67%, specificity 75%). The median time to hospitalization after COVID-19 infection for patients with a reactive OMST was 12 days (95% CI: 2 - not reached) versus not reached (NR) for patients with a non-reactive OMST [95% CI: NR-NR] with a hazard ratio of 7.7 (95% CI: 2.4-132, p=0.005) [Figure 2]. The following variables were not significant on univariate CPHM: age, gender, IGHV mutation, CLL-IPI risk, Charlson Comorbidity score, smoking status, number of mRNA COVID-19 vaccinations, receipt of monoclonal antibodies, or on therapy for CLL. Conclusions We have developed a novel assay, the OMST, that measures the reactivity of human monocytes to ORF8 and has significant value in determining the severity of COVID-19 infection in CLL patients. These findings are independent of patient age, sex, comorbidity score, prognostic models, and vaccination status. The OMST has the potential to assess monocyte reactivity and its implications in a broad range of clinical situations. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Quantification of NSSL Warn-on-Forecast System Accuracy by Storm Age Using Object-Based Verification

Abstract The National Severe Storm Laboratory’s Warn-on-Forecast System (WoFS) is a convection-allowing ensemble with rapidly cycled data assimilation (DA) of various satellite and radar datasets designed for prediction at 0–6-h lead time of hazardous weather. With the focus on short lead times, WoFS predictive accuracy is strongly dependent on its ability to accurately initialize and depict the evolution of ongoing storms. Since it takes multiple DA cycles to fully “spin up” ongoing storms, predictive skill is likely a function of storm age at the time of model initialization, meaning that older storms that have been through several DA cycles will be forecast with greater accuracy than newer storms that initiate just before model initialization or at any point after. To quantify this relationship, we apply an object-based spatial tracking and verification approach to map differences in the probability of detection (POD), in space–time, of predicted storm objects from WoFS with respect to Multi-Radar Multi-Sensor (MRMS) reflectivity objects. Object-tracking/matching statistics are computed for all suitable and available WoFS cases from 2017 to 2021. Our results indicate sharply increasing POD with increasing storm age for lead times within 3 h. PODs were about 0.3 for storm objects that emerge 2–3 h after model initialization, while for storm objects that were at least an hour old at the time of model initialization by DA, PODs ranged from around 0.7 to 0.9 depending on the lead time. These results should aid in forecaster interpretation of WoFS, as well as guide WoFS developers on improving the model and DA system. Significance Statement The Warn-on-Forecast System (WoFS) is a collection of weather models designed to predict individual thunderstorms. Before the models can predict storms, they must ingest radar and satellite observations to put existing storms into the models. Because storms develop at different times, more observations will exist for some storms in the model domain than others, which results in WoFS forecasts with different accuracy for different storms. This paper estimates the differences in accuracy for storms that have existed for a long time and those that have not by tracking observed and predicted storms. We find that the likelihood of WoFS accurately predicting a thunderstorm nearly doubles if the storm has existed for over an hour prior to the forecast. Understanding this relationship between storm age and forecast accuracy will help forecasters better use WoFS predictions and guide future research to improve WoFS forecasts.

PSAT316 Thyroid Storm Triggered by Coronavirus Disease-19 (COVID-19) In a Patient With Graves’ Disease

Abstract Background COVID-19 infection affects multiple organ systems including the endocrine system. Its effect on thyroid function has been reported in multiple studies and one of them observed overt thyrotoxicosis in 10.8% of COVID-19 hospitalized patients associated with higher mortality and longer hospital stays. There is paucity of data on the impact of COVID-19 in patients with pre-existing hyperthyroidism, with only few case reports highlighting the clinical course of such patients. We report a young woman diagnosed with Graves’ disease (GD) who was admitted 4 weeks later with thyroid storm precipitated by COVID-19. Case An 18 year old woman presented to the Emergency Room (ER) with fatigue, palpitations, diaphoresis, and diarrhea for 2 weeks. She had sinus tachycardia with heart rate (HR) of 118 beats per minute (bpm). She had diffuse thyromegaly and fine tremors on exam. TSH was &amp;lt; 0.01 uIU/mL and free Thyroxine (FT4) &amp;gt;8 ng/dL. Thyroid Stimulating Immunoglobulin (TSI) was elevated consistent with GD. She was admitted and treated with intravenous fluids (IV), propranolol and methimazole with significant improvement. She was discharged on methimazole and propranolol. FT4 improved to 3.31 ng/dL 3 weeks later with 100% medication compliance. A week later, patient visited ER due to sore throat, left earache, and dry cough. Influenza PCR and COVID-19 nasal antigen tests were negative, and patient was discharged on amoxicillin-clavulanate for suspected otitis media and acute pharyngitis. Her symptoms worsened over the next few days and she was admitted again with nausea, vomiting, anxiety, palpitations, dyspnea and diarrhea. She was febrile to 101F, HR 135 bpm with agitation and reduced concentration. Burch-Wartofsky score was 65, highly suggestive of thyroid storm. FT4 was elevated at 4.46 ng/dL. COVID-19 PCR was positive. She was treated with propylthiouracil, propranolol and IV hydrocortisone with gradual improvement in symptoms. She was discharged on methimazole, propranolol and prednisone 10 mg for 10 days. Due to worsening hyperthyroid symptoms and rise in FT4, 1 week after stopping prednisone, it was restarted, and an urgent out-patient surgical referral was placed. She was advised to repeat thyroid labs in 1 week. Conclusion Thyroid storm is a rare, life-threatening endocrine emergency with a mortality rate of 10-30% that demands prompt recognition and timely intervention. Our case highlights that there must be a high index of suspicion for COVID-19 with worsening hyperthyroidism in patients with GD who are compliant with anti-thyroid medication especially if they have upper or lower respiratory tract symptoms. Patients with GD should be closely monitored during COVID-19 infection for development of thyroid storm. Early initiation of steroids might be considered with worsening thyroid function despite normal respiratory status to counteract inflammatory thyroiditis. Further studies will be useful to see the effect of COVID-19 infection in patients with GD. Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m.

PSAT235 The Role of Systemic Immune Activation in the Development of Thyroid Dysfunction in COVID-19

Abstract Background The research of cytokine-induced thyropathies in the midst of continuing COVID-19 pandemic is a very important and urgent problem. This work is based on the hypothesis that the hyperactivation of the immune system during COVID-19 is accompanied by a massive production of proinflammatory cytokines, and this could lead to thyroid gland disruption. Aim The primary endpoint is to assess the relationship between the levels of thyroid-stimulating hormone (TSH), free triiodothyronine (T3f), and free thyroxine (T4f) with the inflammatory process markers. The secondary endpoint is the identification of an association between TSH, T3f, T4f values, and patient survival. Materials and Methods This retrospective, single-center study included 122 patients hospitalized at the National Endocrinology Research Centre with a clinical and laboratory analysis of COVID-19 and bilateral polysegmental viral pneumonia. To assess the functional status of the thyroid gland all patients underwent observation of the TSH, T3f, T4f, AT-TPO, and AT-recTSH. Additionally, the markers of the inflammatory process were assessed in all patients, including: interleukin-6 (IL-6). Results Five patients (4%) were found with subclinical thyrotoxicosis. Serum TSH values were inversely correlated with IL-6 (r: -0.221; p = 0.024). Analysis of the level of hospital mortality, stratified by TSH, revealed statistically significantly lower TSH values in the group of deceased patients (p = 0.012). The median TSH in surviving patients was 1.34 [0.85; 1.80], for the deceased 0.44 [0.29; 0.99]. Based on the hypothesis that the immunosuppressive effect of genetically engineered biological therapy may have a protective role against thyroid damage in the development of cytokine storm, a comparative analysis of TSH values in two groups of patients with cytokine storm was performed (p=0.080). Conclusion Our research shows that the trigger of thyropathies in coronavirus infection is most likely thyroid tissue damage by the proinflammatory cytokines. In addition to the pathophysiological aspects of thyrotoxicosis, this study shows some specific clinical aspects regarding the clinical relevance in patients with thyrotoxicosis and COVID-19, namely, the high hospital mortality rate. The results obtained indicate a high risk of developing cytokine-induced thyropathies in patients with COVID-19. In support of the hypothesis of thyroid tissue damage being caused by pro-inflammatory cytokines, the differences in detected TSH values rose to the level of a statistical trend in 2 groups of patients with cytokine storm (i.e., patients who received tocilizumab therapy, and patients who received symptomatic therapy). Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m.

Diabetes and severe COVID-19 infection: Connecting the dots.

Diabetes is a significant risk factor for coronavirus disease 2019 (COVID-19) severity, poor prognosis, and mortality. Uncontrolled hyperglycaemia is associated with impaired innate and adaptive immunity predisposing to severe infection. In addition, there are other mechanisms linked to diabetes such as the upregulation of angiotensin-converting enzyme-2 receptor that might aid in viral entry and spread. The chronic low-grade inflammation and endothelial dysfunction might provide the backdrop to the development of cytokine storm and thromboembolic complications. Understanding the pathophysiology behind severe COVID-19 in diabetes will help to optimise management.

Central Effects of Ivermectin in Alleviation of Covid-19-induced Dysauto-nomia.

Covid-19 may be associated with various neurological disorders, including dysautonomia, a dysfunction of the autonomic nervous system (ANS). In Covid-19, hypoxia, immunoinflammatory abnormality, and deregulation of the renin-angiotensin system (RAS) may increase sympathetic discharge with dysautonomia development. Direct SARS-CoV-2 cytopathic effects and associated inflammatory reaction may lead to neuroinflammation, affecting different parts of the central nervous system (CNS), including the autonomic center in the hypothalamus, causing dysautonomia. High circulating AngII, hypoxia, oxidative stress, high pro-inflammatory cytokines, and emotional stress can also provoke autonomic deregulation and high sympathetic outflow with the development of the sympathetic storm. During SARS-CoV-2 infection with neuro-invasion, GABA-ergic neurons and nicotinic acetylcholine receptor (nAChR) are inhibited in the hypothalamic pre-sympathetic neurons leading to sympathetic storm and dysautonomia. Different therapeutic modalities are applied to treat SARS-CoV-2 infection, like antiviral and anti-inflammatory drugs. Ivermectin (IVM) is a robust repurposed drug widely used to prevent and manage mild-moderate Covid-19. IVM activates both GABA-ergic neurons and nAChRs to mitigate SARS-CoV-2 infection- induced dysautonomia. Therefore, in this brief report, we try to identify the potential role of IVM in managing Covid-19-induced dysautonomia.