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Clinical evidence suggests that febrile status epilepticus (SE) in children can lead to acute hippocampal injury and subsequent temporal lobe epilepsy. The contribution of febrile SE to the mechanisms underlying temporal lobe epilepsy are however poorly understood. A rat model of temporal lobe epilepsy following hyperthermic SE was previously established in our laboratory, wherein a focal cortical lesion induced at postnatal day 1 (P1), followed by a hyperthermic SE (more than 30 min) at P10, leads to hippocampal atrophy at P22 (dual pathology model) and spontaneous recurrent seizures (SRS) with mild visuospatial memory deficits in adult rats. The goal of this study was to identify the long term electrophysiological, anatomical and molecular changes in this model. Following hyperthermic SE, all cortically lesioned pups developed progressive SRS as adults, characterized by the onset of highly rhythmic activity in the hippocampus. A reduction of hippocampal volume on the side of the lesion preceded the SRS and was associated with a loss of hippocampal neurons, a marked decrease in pyramidal cell spine density, an increase in the hippocampal levels of NMDA receptor NR2A subunit, but no significant change in GABA receptors. These findings suggest that febrile SE in the abnormal brain leads to hippocampal injury that is followed by progressive network reorganization and molecular changes that contribute to the epileptogenesis as well as the observed memory deficits.

During development, the risk of developing mesial temporal lobe epilepsy (MTLE) increases when the developing brain is exposed to more than one insult in early life. Early life insults include abnormalities of cortical development, hypoxic-ischemic injury and prolonged febrile seizures. To study epileptogenesis, we have developed a two-hit model of MTLE characterized by two early-life insults: a freeze lesion-induced cortical malformation at post-natal day 1 (P1), and a prolonged hyperthermic seizure (HS) at P10. As early life stressors lead to sexual dimorphism in both acute response and long-term outcome, we hypothesized that our model could lead to gender-based differences in acute stress response and long-term risk of developing MTLE. Male and female pups underwent a freeze-lesion induced cortical microgyrus at P1 and were exposed to HS at P10. Animals were monitored by video-EEG from P90 to P120. Pre and post-procedure plasma corticosterone levels were used to measure stress response at P1 and P10. To confirm the role of sex steroids, androgenized female pups received daily testosterone injections to the mother pre-natally and post-natally for nine days while undergoing both insults. We demonstrated that after both insults females did not develop MTLE while all males did. This correlated with a rise in corticosterone levels at P1 following the lesion in males only. Interestingly, all androgenized females showed a similar rise in corticosterone at P1, and also developed MTLE. Moreover, we found that the cortical lesion significantly decreased the latency to generalized convulsion during hyperthermia at P10 in both genders. The cortical dysplasia volumes at adulthood were also similar between male and female individuals. Our data demonstrate sexual dimorphism in long-term vulnerability to develop epilepsy in the lesion + hyperthermia animal model of MTLE and suggest that the response to early-life stress at P1 contributes significantly to epileptogenesis in a gender-specific manner.

In recent years, the $T$-linear scattering rate found at low temperatures, defining the strange metal phase of cuprates, has been a subject of interest. Since a wide range of materials have a scattering rate that obeys the equation $ \hbar / \tau ≈ k_B T$, the idea of a universal Planckian limit on the scattering rate has been proposed. However, there is no consensus on proposed theories yet. In this work, we present our results for the $T$-linear scattering rate in the triangular lattice Hubbard model obtained using the dynamical cluster approximation. We find two regions with $T$-linear scattering rate in the $T$-$p$ phase diagram: one emerges from the pseudogap to correlated Fermi liquid phase transition at low doping, whereas the other is solely caused by large interaction strength at large doping.

Abstract Background As a result of the technological progress, the use of sensors for crop survey has substantially increased, generating valuable information for modelling agricultural data. Plant spectroscopy jointly with statistical modeling can potentially help to assess certain chemical components of interest present in plants, which may be laborious and expensive to obtain by direct measurements. In this research, the phosphorus content in wheat grain is modeled using reflectance information measured by a hyperspectral sensor at different wavelengths. A Bayesian procedure for selecting variables was used to identify the set of the most important spectral bands. Additionally, three different models were evaluated: the first model assumes that the observations are independent, the other two models assume that the observations are spatially correlated: one of the proposed models, assumes spatial dependence using a Conditionally Autoregressive Model (CAR), and the other through an exponential correlogram. The goodness of fit of the models was evaluated by means of the Deviance Information Criterion, and the predictive power is evaluated using cross validation. Results We have found that CAR was the model that best fits and predicts the data. Additionally, the selection variable procedure in the CAR model reveals which wavelengths in the range of 500–690 nm are the most important. Comparing the vegetative indices with the CAR model, it was observed that the average correlation of the CAR model exceeded that of the vegetative indices by 23.26%, − 1.2% and 22.78% for the year 2010, 2011 and 2012 respectively; therefore, the use of the proposed methodology outperformed the vegetative indices in prediction. Conclusions The proposal to predict the phosphorus content in wheat grain using Bayesian approach, reflect with the results as a good alternative.

Ocean gliders are versatile tools for making ocean observations. This paper summarizes the experience, of nearly two decades, of glider observing activity in Atlantic Canada. It reviews key considerations for operating gliders based on the experience and the lessons learned. This paper has three main goals: 1. To provide new and emerging glider users with guidance and considerations for developing a glider program. 2. Review the literature on sensor development for gliders and the use of gliders. 3. To highlight different mission scenarios that include enough practical considerations to support operating gliders. The use of gliders is rapidly expanding, but the documentation and consolidation of best practices for their operational use in Atlantic Canada remains underdeveloped. This summary provides a guide that should be helpful both to new and experienced glider operators and potential users, to observe the oceanography of this region and addresses regional challenges. We believe documenting our experience will be also helpful to the global glider community. We summarize the most critical considerations of utilizing gliders. We review the issues specific to the platform use and concerns about how to optimize the use of key sensors to contribute to an oceanographic observing program.

Coronavirus disease 2019 (COVID-19) was first reported to the World Health Organization (WHO) in December 2019 and has since unleashed a global pandemic, with over 518 million cases as of May 10, 2022. Neonates represent a very small proportion of those patients. Among reported cases of neonates with symptomatic COVID-19 infection, the rates of hospitalization remain low. Most reported cases in infants and neonates are community acquired with mild symptoms, most commonly fever, rhinorrhea and cough. Very few require intensive care or invasive support for acute infection. We present a case of a 2-month-old former 26-week gestation infant with a birthweight of 915 grams and diagnoses of mild bronchopulmonary dysplasia and a small ventricular septal defect who developed acute respiratory decompensation due to COVID-19 infection. He required veno-arterial extracorporeal membrane oxygenation support for 23 days. Complications included liver and renal dysfunction and a head ultrasound notable for lentriculostriate vasculopathy, extra-axial space enlargement and patchy periventricular echogenicity. The patient was successfully decannulated to conventional mechanical ventilation with subsequent extubation to non-invasive respiratory support. He was discharged home at 6 months of age with supplemental oxygen via nasal cannula and gastrostomy tube feedings. He continues to receive outpatient developmental follow-up. To our knowledge, this is the first case report of a preterm infant during their initial hospitalization to survive ECMO for COVID-19.

The beginning of the end (BOTE) sign has been proposed to describe well-recognized clinical signs of inflammation (including erythema, induration, and scale) that predict imminent resolution of molluscum contagiosum (MC). This phenomenon has never been prospectively studied. An integrated analysis of two prospective, 12-week, randomized, double-blind clinical trials of topical nitric oxide–releasing SB206 gel evaluated an association between BOTE sign and MC lesion reduction. Of 707 randomized patients, ~80% exhibited BOTE signs regardless of treatment assignment. At week 12, MC lesion counts decreased from baseline by 50.7% for baseline BOTE+ versus 29.1% for BOTE– (P = 0.0015) vehicle-treated patients compared with a 63.3% decrease for baseline BOTE+ versus 51.7% for BOTE– (P = 0.0194) SB206-treated patients. Among vehicle-treated patients, 48 (22.3%) who were never BOTE+ had an 18.5% reduction from baseline in MC lesion counts versus a 34.0% reduction in 165 patients (76.7%) who experienced BOTE at any time, suggesting that the projected duration of lesion clearance for patients with 18–20 MC lesions is 15 months for BOTE– versus 6 months for BOTE+ patients. Patients who were both BOTE+ and treated with SB206 had the greatest reduction in MC lesion count. SB206 may trigger BOTE signs and shorten the duration of MC infection. The two studies whose data are analyzed in this study are registered at ClinicalTrials.gov with the identifiers NCT03927703 and NCT03927716

Abstract Linear and non‐linear models used in applications of genomic selection (GS) can fit different types of responses (e.g., continuous, ordinal, binary). In recent years, several genomic‐enabled prediction models have been developed for predicting complex traits in genomic‐assisted animal and plant breeding. These models include linear, non‐linear and non‐parametric models, mostly for continuous responses and less frequently for categorical responses. Several linear and non‐linear models are special cases of a more general family of statistical models known as artificial neural networks, which provide better prediction ability than other models. In this paper, we propose a Bayesian Regularized Neural Network (BRNNO) for modelling ordinal data. The proposed model was fitted using a Bayesian framework; we used the data augmentation algorithm to facilitate computations. The proposed model was fitted using the Gibbs Maximum a Posteriori and Generalized EM algorithm implemented by combining code written in C and R programming languages. The new model was tested with two real maize datasets evaluated for Septoria and GLS diseases and was compared with the Bayesian Ordered Probit Model (BOPM). Results indicated that the BRNNO model performed better in terms of genomic‐based prediction than the BOPM model.

The OceanGliders program started in 2016 to support active coordination and enhancement of global glider activity. OceanGliders contributes to the international efforts of the Global Ocean Observation System (GOOS) for Climate, Ocean Health, and Operational Services. It brings together marine scientists and engineers operating gliders around the world: (1) to observe the long-term physical, biogeochemical, and biological ocean processes and phenomena that are relevant for societal applications; and, (2) to contribute to the GOOS through real-time and delayed mode data dissemination. The OceanGliders program is distributed across national and regional observing systems and significantly contributes to integrated, multi-scale and multi-platform sampling strategies. OceanGliders shares best practices, requirements, and scientific knowledge needed for glider operations, data collection and analysis. It also monitors global glider activity and supports the dissemination of glider data through regional and global databases, in real-time and delayed modes, facilitating data access to the wider community. OceanGliders currently supports national, regional and global initiatives to maintain and expand the capabilities and application of gliders to meet key global challenges such as improved measurement of ocean boundary currents, water transformation and storm forecast.

There is a growing need for operational oceanographic predictions in both the Arctic and Antarctic polar regions. In the former, this is driven by a declining ice cover accompanied by an increase in maritime traffic and exploitation of marine resources. Oceanographic predictions in the Antarctic are also important, both to support Antarctic operations and also to help elucidate processes governing sea ice and ice shelf stability. However, a significant gap exists in the ocean observing system in polar regions, compared to most areas of the global ocean, hindering the reliability of ocean and sea ice forecasts. This gap can also be seen from the spread in ocean and sea ice reanalyses for polar regions which provide an estimate of their uncertainty. The reduced reliability of polar predictions may affect the quality of various applications including search and rescue, coupling with numerical weather and seasonal predictions, historical reconstructions (reanalysis), aquaculture and environmental management including environmental emergency response. Here, we outline the status of existing near-real time ocean observational efforts in polar regions, discuss gaps, and explore perspectives for the future. Specific recommendations include a renewed call for open access to data, especially real-time data, as a critical capability for improved sea ice and weather forecasting and other environmental prediction needs. Dedicated efforts are also needed to make use of additional observations made as part of the Year of Polar Prediction (YOPP; 2017–2019) to inform optimal observing system design. To provide a polar extension to the Argo network, it is recommended that a network of ice-borne sea ice and upper-ocean observing buoys be deployed and supported operationally in ice-covered areas together with autonomous profiling floats and gliders (potentially with ice detection capability) in seasonally ice covered seas. Finally, additional efforts to better measure and parameterize surface exchanges in polar regions are much needed to improve coupled environmental prediction.