Comparison of neurodevelopmental, educational and adult socioeconomic outcomes in offspring of women with and without epilepsy : A systematic review and meta-analysis

Peer reviewe

Comparison of neurodevelopmental, educational and adulthood socioeconomic outcomes in offspring of women with and without epilepsy: A systematic review and meta-analysis

Background: Adequate pre-pregnancy counselling and education planning are essential to improve outcomes for offspring of women with epilepsy (OWWE). The current systematic review and meta-analysis aimed to compare outcomes for OWWE and offspring of women without epilepsy (OWWoE). Methods: We conducted a systematic review and meta-analysis. We searched MEDLINE, EMBASE, CINAHL, PsycINFO (database inception-1st January 2023), OpenGrey, GoogleScholar, and hand-searched journals and reference lists of included studies to identify eligible studies. We placed no language restrictions and included observational studies concerning OWWE and OWWoE. We followed the PRIMSA checklist for abstracting data. The Newcastle-Ottawa Scale for risk of bias assessment was conducted independently by two authors with mediation by a third. We report pooled unadjusted odds ratios (OR) or mean differences (MD) with 95% confidence intervals (95CI) from random (I2&gt;50%) or fixed (I2&lt;50%) effects meta-analyses. Outcomes of interest included offspring autism, attention deficit/hyperactive disorder, intellectual disability, epilepsy, developmental disorder, intelligence, educational, and adulthood socioeconomic outcomes. Results: Of 10,928 articles identified, we included 21 in meta-analyses. OWWE had increased odds of autism (2 articles, 4,502,098 offspring) OR [95CI] 1·67 [1·54, 1·82], attention-deficit/hyperactivity disorder (3 articles, 957,581 offspring) 1·59 [1·44, 1·76], intellectual disability (2 articles, 4,501,786 children) 2·37 [2·13, 2·65], having special educational needs (3 articles, 1,308,919 children) 2·60 [1·07, 6·34]. OWWE had worse mean scores for full-scale intelligence (5 articles, 989 children) -6·05 [-10·31, -1·79]. No studies were identified that investigated adulthood socioeconomic outcomes. Conclusions: Increased odds of poor outcomes are higher with greater anti-seizure medication burden including neurodevelopmental and educational outcomes. In fact, these two outcomes seem to be worse in OWWE compared to OWWoE, even if there was no ASM exposure during pregnancy, but further work is needed to take into account potential confounding factors. Key words: Epilepsy, pregnancy, mother, child, outcomes <br/

Reverse Shock Emission Revealed in Early Photometry in the Candidate Short GRB 180418A

We present observations of the possible short GRB 180418A in $\gamma$-rays, X-rays, and in the optical. Early optical photometry with the TAROT and RATIR instruments show a bright peak ($\approx$ 14.2 AB mag) between $T+28$ and $T+90$ seconds that we interpret as the signature of a reversal shock. Later observations can be modeled by a standard forward shock model and show no evidence of jet break, allowing us to constrain the jet collimation to $\theta_j> 7^\circ$. Using deep late-time optical observations we place an upper limit of $r>24$ AB mag on any underlying host galaxy. The detection of the afterglow in the \textit{Swift} UV filters constrains the GRB redshift to $z<1.3$ and places an upper bound on the $\gamma$-ray isotropic equivalent energy $E_{\rm{\gamma,iso}} < 3 \times 10^{51}$ erg. The properties of this GRB (e.g. duration, hardness ratio, energetic, and environment) lie at the intersection between short and long bursts, and we can not conclusively identify its type. We estimate that the probability that it is drawn from the population of short GRBs is 10\%-30\%.Comment: Accepted por publication in Ap

Machine-Learning Enhanced Photometric Analysis of the Extremely Bright GRB 210822A

We present analytical and numerical models of the bright long GRB 210822A at $z=1.736$. The intrinsic extreme brightness exhibited in the optical, which is very similar to other bright GRBs (e.g., GRBs 080319B, 130427A, 160625A 190114C, and 221009A), makes GRB 210822A an ideal case for studying the evolution of this particular kind of GRB. We use optical data from the RATIR instrument starting at $T+315.9$ s, with publicly available optical data from other ground-based observatories, as well as X-ray data from the Swift/X-ray Telescope (XRT) and data from the Swift/Ultraviolet/Optical Telescope (UVOT). The temporal profiles and spectral properties during the late stages align consistently with the conventional forward shock model, complemented by a reverse shock element that dominates optical emissions during the initial phases ($T<300$ s). Furthermore, we observe a break at $T=80000$ s that we interpreted as evidence of a jet break, which constrains the opening angle to be about $\theta_\mathrm{j}=(3-5)$ degrees. Finally, we apply a machine-learning technique to model the multi-wavelength light curve of GRB 210822A using the AFTERGLOWPY library. We estimate the angle of sight $\theta_{obs}=(6.4 \pm 0.1) \times 10^{-1}$ degrees, the energy $E_0= (7.9 \pm 1.6)\times 10^{53}$ ergs, the electron index $p=2.54 \pm 0.10$, the thermal energy fraction in electrons $\epsilon_e=(4.63 \pm 0.91) \times 10^{-5}$ and in the magnetic field $\epsilon_B= (8.66 \pm 1.01) \times 10^{-6}$, the efficiency $\chi = 0.89 \pm 0.01$, and the density of the surrounding medium $n_\mathrm{0} = 0.85 \pm 0.01$.Comment: Submitted to MNRAS, 11 pages, 6 figures. Fixed typo

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

The transcriptional regulator Sin3A balances IL-17A and Foxp3 expression in primary CD4 T cells

The Sin3 transcriptional regulator homolog A (Sin3A) is the core member of a multiprotein chromatin-modifying complex. Its inactivation at the CD4/CD8 double-negative stage halts further thymocyte development. Among various functions, Sin3A regulates STAT3 transcriptional activity, central to the differentiation of Th17 cells active in inflammatory disorders and opportunistic infections. To further investigate the consequences of conditional Sin3A inactivation in more mature precursors and post-thymic T cell, we have generated CD4-Cre and CD4-CreERT2 Sin3AF/F mice. Sin3A inactivation in vivo hinders both thymocyte development and peripheral T-cell survival. In vitro, in Th17 skewing conditions, Sin3A-deficient cells proliferate and acquire memory markers and yet fail to properly upregulate Il17a, Il23r, and Il22. Instead, IL-2+ and FOXP3+ are mostly enriched for, and their inhibition partially rescues IL-17A+ T cells. Notably, Sin3A deletion also causes an enrichment of genes implicated in the mTORC1 signaling pathway, overt STAT3 activation, and aberrant cytoplasmic ROR¿t accumulation. Thus, together our data unveil a previously unappreciated role for Sin3A in shaping critical signaling events central to the acquisition of immunoregulatory T-cell phenotypes