Inhibition of Brain Glutamate Decarboxylase Activity Is Related to Febrile Seizures in Rat Pups

Because previous work showed that in the newborn brain, but not in the adult brain, glutamate decarboxylase (GAD) is notably susceptible to heat, we have studied the possible involvement of GAD inhibition in febrile convulsions and the related changes in gamma-aminobutyric acid (GABA) content. Rats of different ages were subjected to hyperthermia, and GAD activity was determined in brain homogenates by measuring the release of 14CO2 from labeled glutamate and by measuring the formation of GABA. The latter method gave considerably lower values than the former in the youngest rats, and was considered more reliable. With this method, we found a 37-48% inhibition of GAD activity in rat pups 2-5 days old, which showed febrile seizures at progressively higher body temperatures, whereas in 10- and 15-day-old animals, which did not show convulsions, GAD activity was not affected by hyperthermia. Whole-brain GABA levels, however, did not change at any age. In contrast to GAD, choline acetyltransferase and lactic dehydrogenase activities were not altered by hyperthermia at any of the ages studied. These results suggest that a decreased efficiency of the inhibitory neurotransmission mediated by GABA, consequent to the inhibition of GAD activity, may be a factor related to febrile convulsions.     

Complementary strengths of spatially-explicit and multi-species distribution models

Species distribution models (SDMs) project the outcome of community assembly processes – dispersal, the abiotic environment and biotic interactions – onto geographic space. Recent advances in SDMs account for these processes by simultaneously modeling the species that comprise a community in a multivariate statistical framework or by incorporating residual spatial autocorrelation in SDMs. However, the effects of combining both multivariate and spatially-explicit model structures on the ecological inferences and the predictive abilities of a model are largely unknown. We used data on eastern hemlock Tsuga canadensis and five additional co-occurring overstory tree species in 35 569 forest stands across Michigan, USA to evaluate how the choice of model structure, including spatial and non-spatial forms of univariate and multivariate models, affects ecological inference about the processes that shape community composition as well as model predictive ability. Incorporating residual spatial autocorrelation via spatial random effects did not improve out-of-sample prediction for the six tree species, although in-sample model fit was higher in the spatial models. Spatial models attributed less variation in occurrence probability to environmental covariates than the non-spatial models for all six tree species, and estimated higher (more positive) residual co-occurrence values for most species pairs. The non-spatial multivariate model was better suited for evaluating habitat suitability and hypotheses about the processes that shape community composition. Environmental correlations and residual correlations among species pairs were positively related, perhaps indicating that residual correlations were due to shared responses to unmeasured environmental covariates. This work highlights the importance of choosing a non-spatial model formulation to address research questions about the species–environment relationship or residual co-occurrence patterns, and a spatial model formulation when within-sample prediction accuracy is the main goal.     

Sex differences in the immune response to acute COVID-19 respiratory tract infection

Determine if sex differences exist in clinical characteristics and outcomes of adults hospitalized for coronavirus disease 2019 (COVID-19) in a US healthcare system. Case series study. Sequentially hospitalized adults admitted for COVID-19 at two tertiary care academic hospitals in New Orleans, LA, between 27 February and 15 July 2020. Measures included demographics, comorbidities, presenting symptoms, and laboratory results. Outcomes included intensive care unit admission (ICU), invasive mechanical ventilation (IMV), and in-hospital death. We included 776 patients (median age 60.5 years; 61.4% women, 75% non-Hispanic Black). Rates of ICU, IMV, and death were similar in both sexes. In women versus men, obesity (63.8 vs 41.6%, P < 0.0001), hypertension (77.6 vs 70.1%, P = 0.02), diabetes (38.2 vs 31.8%, P = 0.06), chronic obstructive pulmonary disease (COPD, 22.1 vs 15.1%, P = 0.015), and asthma (14.3 vs 6.9%, P = 0.001) were more prevalent. More women exhibited dyspnea (61.2 vs 53.7%, P = 0.04), fatigue (35.7 vs 28.5%, P = 0.03), and digestive symptoms (39.3 vs 32.8%, P = 0.06) than men. Obesity was associated with IMV at a lower BMI (> 35) in women, but the magnitude of the effect of morbid obesity (BMI ≥ 40) was similar in both sexes. COPD was associated with ICU (adjusted OR (aOR), 2.6; 95%CI, 1.5–4.3) and IMV (aOR, 1.8; 95%CI, 1.2–3.1) in women only. Diabetes (aOR, 2.6; 95%CI, 1.2–2.9), chronic kidney disease (aOR, 2.2; 95%CI, 1.3–5.2), elevated neutrophil-to-lymphocyte ratio (aOR, 2.5; 95%CI, 1.4–4.3), and elevated ferritin (aOR, 3.6; 95%CI, 1.7–7.3) were independent predictors of death in women only. In contrast, elevated D-dimer was an independent predictor of ICU (aOR, 7.3; 95%CI, 2.7–19.5), IMV (aOR, 6.5; 95%CI, 2.1–20.4), and death (aOR, 4.5; 95%CI, 1.2–16.4) in men only. This study highlights sex disparities in clinical determinants of severe outcomes in COVID-19 patients that may inform management and prevention strategies to ensure gender equity.     

Right Bundle Branch Block: A Predictor of Mortality in Early Systemic Sclerosis

Objective

To evaluate the prognostic significance of baseline electrocardiogram (ECG) abnormalities in a multiethnic cohort of patients with early systemic sclerosis (SSc) and to determine the serological, clinical, and echocardiogram correlates of ECG findings.

Methods

SSc patients with disease duration of≤5 years were enrolled in the GENISOS (Genetics versus Environment in Scleroderma Outcome Study) cohort. At the first visit, a standard 12 lead ECG was obtained along with demographic information, clinical data, and autoantibodies. The results of echocardiograms were also recorded. All ECGs were interpreted by a cardiologist unaware of the patients'' clinical data.

Results

Of 265 SSc patients with average disease duration at enrollment of 2.5 years, 140 (52.8%) had abnormal ECG findings. These findings were not associated with SSc disease type or autoantibody profile but were associated with more severe heart and lung involvement. A total of 75 patients (28.3%) died over a follow up time of 9.9 years. Complete right bundle branch block (± left anterior hemiblock) on ECG, present in 7 (2.6%) patients, predicted a higher risk of mortality (HR: 5.3; 95% CI: 2.1 to 13.4; p<0.001). The predictive significance of right bundle branch block was independent of age at enrollment, gender, ethnicity and risk factors for coronary artery disease.

Conclusion

ECG abnormalities are common in patients with early SSc and are associated with the severity of lung and heart involvement. Right bundle branch block is an independent predictor of mortality, and should be considered a marker of disease severity in SSc.     

Phylogeographic Reconstruction of African Yellow Fever Virus Isolates Indicates Recent Simultaneous Dispersal into East and West Africa

Yellow fever virus (YFV) is a mosquito-borne flavivirus that is a major public health problem in tropical areas of Africa and South America. There have been detailed studies on YFV ecology in West Africa and South America, but current understanding of YFV circulation on the African continent is incomplete. This inadequacy is especially notable for East and Central Africa, for which the unpredictability of human outbreaks is compounded by limitations in both historical and present surveillance efforts. Sparse availability of nucleotide sequence data makes it difficult to investigate the dispersal of YFV in these regions of the continent. To remedy this, we constructed Bayesian phylogenetic and geographic analyses utilizing 49 partial genomic sequences to infer the structure of YFV divergence across the known range of the virus on the African continent. Relaxed clock analysis demonstrated evidence for simultaneous divergence of YFV into east and west lineages, a finding that differs from previous hypotheses of YFV dispersal from reservoirs located on edges of the endemic range. Using discrete and continuous geographic diffusion models, we provide detailed structure of YFV lineage diversity. Significant transition links between extant East and West African lineages are presented, implying connection between areas of known sylvatic cycling. The results of demographic modeling reinforce the existence of a stably maintained population of YFV with spillover events into human populations occurring periodically. Geographically distinct foci of circulation are reconstructed, which have significant implications for studies of YFV ecology and emergence of human disease. We propose further incorporation of Bayesian phylogeography into formal GIS analyses to augment studies of arboviral disease.     

Effects of Landscape Fragmentation and Climate on Lyme Disease Incidence in the Northeastern United States

Lyme disease is the most frequently reported vector borne illness in the United States, and incidences are increasing steadily year after year. This study explores the influence of landscape (e.g., land use pattern and landscape fragmentation) and climatic factors (e.g., temperature and precipitation) at a regional scale on Lyme disease incidence. The study area includes thirteen states in the Northeastern United States. Lyme disease incidence at county level for the period of 2002–2006 was linked with several key landscape and climatic variables in a negative binomial regression model. Results show that Lyme disease incidence has a relatively clear connection with regional landscape fragmentation and temperature. For example, more fragmentation between forests and residential areas results in higher local Lyme disease incidence. This study also indicates that, for the same landscape, some landscape variables derived at a particular scale show a clearer connection to Lyme disease than do others. In general, the study sheds more light on connections between Lyme disease incidence and climate and landscape patterns at the regional scale. Integrating findings of this regional study with studies at a local scale will further refine understanding of the pattern of Lyme disease as well as increase our ability to predict, prevent, and respond to disease.     

Energy based pharmacophore mapping of HDAC inhibitors against class I HDAC enzymes

Histone deacetylases (HDACs) are important class of enzymes that deacetylate the ε-amino group of the lysine residues in the histone tails to form a closed chromatin configuration resulting in the regulation of gene expression. Inhibition of these HDACs enzymes have been identified as one of the promising approaches for cancer treatment. The type-specific inhibition of class I HDAC enzymes is known to elicit improved therapeutic effects and thus, the search for promising type-specific HDAC inhibitors compounds remains an ongoing research interest in cancer drug discovery. Several different strategies are employed to identify the features that could identify the isoform specificity factors in these HDAC enzymes. This study combines the insilico docking and energy-optimized pharmacophore (e-pharmacophore) mapping of several known HDACi's to identify the structural variants that are significant for the interactions against each of the four class I HDAC enzymes. Our hybrid approach shows that all the inhibitors with at least one aromatic ring in their linker regions hold higher affinities against the target enzymes, while those without any aromatic rings remain as poor binders. We hypothesize the e-pharmacophore models for the HDACi's against all the four Class I HDAC enzymes which are not reported elsewhere. The results from this work will be useful in the rational design and virtual screening of more isoform specific HDACi's against the class I HDAC family of proteins.