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Recent advances in numerical relativity provide a detailed description of the waveforms of coalescing massive black hole binaries (MBHBs), expected to be the strongest detectable LISA sources. We present a preliminary study of LISA's sensitivity to MBHB parameters using a hybrid numerical/analytic waveform for equal-mass, non-spinning holes. The Synthetic LISA software package is used to simulate the instrument response, and the Fisher information matrix method is used to estimate errors in the parameters. Initial results indicate that inclusion of the merger signal can significantly improve the precision of some parameter estimates. For example, the median parameter errors for an ensemble of systems with total redshifted mass of 106 M[?] at a redshift of z [?] 1 were found to decrease by a factor of slightly more than two for signals with merger as compared to signals truncated at the Schwarzchild ISCO. [ABSTRACT FROM AUTHOR]

Background: Our aim was to train and test a deep learning-based algorithm for automatically segmenting kidneys and renal cysts in patients with autosomal dominant polycystic kidney disease (ADPKD)., Methods: We retrospectively selected all ADPKD patients who underwent renal MRI with coronal T2-weighted imaging at our institution from 2008 to 2022. The 20 most recent examinations constituted the test dataset, to mimic pseudoprospective enrolment. The remaining ones constituted the training dataset to which eight normal renal MRIs were added. Kidneys and cysts ground truth segmentations were performed on coronal T2-weighted images by a junior radiologist supervised by an experienced radiologist. Kidneys and cysts of the 20 test MRIs were segmented by the algorithm and three independent human raters. Segmentations were compared using overlap metrics. The total kidney volume (TKV), total cystic volume (TCV), and cystic index (TCV divided by TKV) were compared using Bland-Altman analysis., Results: We included 164 ADPKD patients. Dice similarity coefficients ranged from 85.9% to 87.4% between the algorithms and the raters' segmentations and from 84.2% to 86.2% across raters' segmentations. For TCV assessment, the biases ± standard deviations (SD) were 3-19 ± 137-151 mL between the algorithm and the raters, and 22-45 ± 49-57 mL across raters. The algorithm underestimated TKV and TCV in two outliers with TCV > 2800 mL. For cystic index assessment, the biases ± SD were 2.5-6.9% ± 6.7-8.3% between the algorithm and the raters, and 2.1-9.4 ± 7.4-11.6% across raters., Conclusion: The algorithm's performance fell within the range of inter-rater variability, but large TKV and TCV were underestimated., Relevance Statement: Accurate automated segmentation of the renal cysts will enable the large-scale evaluation of the prognostic value of TCV and cystic index in ADPKD patients. If these biomarkers are prognostic, then automated segmentation will facilitate their use in daily routine., Key Points: Cystic volume is an emerging biomarker in ADPKD. The algorithm's performance in segmenting kidneys and cysts fell within interrater variability. The segmentation of very large cysts, under-represented in the training dataset, needs improvement., (© 2024. The Author(s).)

Competing Interests: Declaration of competing interest The authors have no conflicts of interest to declare in relation to this work.

Background: Randomized, comparative studies evaluating augmented secondary intention healing (SIH) compared with conventional SIH in dermatologic surgery are limited. This study aimed to evaluate whether the use of a novel biomaterial enhances SIH, particularly in shortening time to complete re-epithelialization., Objective: The purpose of this study was to elucidate whether a novel biomaterial containing gelatin, manuka honey, and hydroxyapatite enhances SIH when compared with conventional SIH for surgical defects after Mohs micrographic surgery (MMS) on the head and distal lower extremities., Materials and Methods: Thirty-seven patients were enrolled in this randomized controlled trial. Patients undergoing MMS on the head or distal lower extremities were eligible for recruitment. After clear surgical margins were obtained post-MMS, patients were randomized to receive standard SIH or biomaterial enhanced SIH. Patients had regularly scheduled follow-ups with questionnaires at each visit until complete re-epithelialization was achieved., Results: Overall, there was no significant difference in time to re-epithelialization between standard SIH and biomaterial-enhanced SIH. However, there was a significant decrease in pain scores and skin thickness in the biomaterial-enhanced SIH group., Conclusion: Biomaterial-enhanced SIH is noninferior to standard SIH and produces less pain and favorable skin thickness compared with standard SIH. ClinicalTrials.gov listing: NCT04545476., (Copyright © 2023 by the American Society for Dermatologic Surgery, Inc. Published by Wolters Kluwer Health, Inc. All rights reserved.)

Objective: This study aimed to develop and investigate the performance of a deep learning model based on a convolutional neural network (CNN) for the automatic segmentation of polycystic livers at CT imaging., Method: This retrospective study used CT images of polycystic livers. To develop the CNN, supervised training and validation phases were performed using 190 CT series. To assess performance, the test phase was performed using 41 CT series. Manual segmentation by an expert radiologist (Rad1a) served as reference for all comparisons. Intra-observer variability was determined by the same reader after 12 weeks (Rad1b), and inter-observer variability by a second reader (Rad2). The Dice similarity coefficient (DSC) evaluated overlap between segmentations. CNN performance was assessed using the concordance correlation coefficient (CCC) and the two-by-two difference between the CCCs; their confidence interval was estimated with bootstrap and Bland-Altman analyses. Liver segmentation time was automatically recorded for each method., Results: A total of 231 series from 129 CT examinations on 88 consecutive patients were collected. For the CNN, the DSC was 0.95 ± 0.03 and volume analyses yielded a CCC of 0.995 compared with reference. No statistical difference was observed in the CCC between CNN automatic segmentation and manual segmentations performed to evaluate inter-observer and intra-observer variability. While manual segmentation required 22.4 ± 10.4 min, central and graphics processing units took an average of 5.0 ± 2.1 s and 2.0 ± 1.4 s, respectively., Conclusion: Compared with manual segmentation, automated segmentation of polycystic livers using a deep learning method achieved much faster segmentation with similar performance., Key Points: • Automatic volumetry of polycystic livers using artificial intelligence method allows much faster segmentation than expert manual segmentation with similar performance. • No statistical difference was observed between automatic segmentation, inter-observer variability, or intra-observer variability., (© 2022. The Author(s), under exclusive licence to European Society of Radiology.)

Elevated amyloid precursor protein (APP) expression in the choroid plexus suggests an important role for extracellular APP metabolites such as sAPPα in cerebrospinal fluid. Despite widespread App brain expression, we hypothesized that specifically targeting choroid plexus expression could alter animal physiology. Through various genetic and viral approaches in the adult mouse, we show that choroid plexus APP levels significantly impact proliferation in both subventricular zone and hippocampus dentate gyrus neurogenic niches. Given the role of Aβ peptides in Alzheimer disease pathogenesis, we also tested whether favoring the production of Aβ in choroid plexus could negatively affect niche functions. After AAV5-mediated long-term expression of human mutated APP specifically in the choroid plexus of adult wild-type mice, we observe reduced niche proliferation, reduced hippocampus APP expression, behavioral defects in reversal learning, and deficits in hippocampal long-term potentiation. Our findings highlight the unique role played by the choroid plexus in regulating brain function and suggest that targeting APP in choroid plexus may provide a means to improve hippocampus function and alleviate disease-related burdens., (© 2021 Arnaud et al.)

Neural stem cells are maintained in the adult brain, sustaining structural and functional plasticity and to some extent participating in brain repair. A thorough understanding of the mechanisms and factors involved in endogenous stem/progenitor cell mobilization is a major challenge in the promotion of spontaneous brain repair. The main neural stem cell niche in the adult brain is the subventricular zone (SVZ). Following demyelination insults, SVZ-derived progenitors act in concert with oligodendrocyte precursors to repopulate the lesion and replace lost oligodendrocytes. Here, we showed robust vascular reactivity within the SVZ after focal demyelination of the corpus callosum in adult mice, together with a remarkable physical association between these vessels and neural progenitors exiting from their niche. Endogenous progenitor cell recruitment towards the lesion was significantly reduced by inhibiting post-lesional angiogenesis in the SVZ using anti-VEGF blocking antibody injections, suggesting a facilitating role of blood vessels for progenitor cell migration towards the lesion. We identified netrin 1 (NTN1) as a key factor upregulated within the SVZ after demyelination and involved in local angiogenesis and progenitor cell migration. Blocking NTN1 expression using a neutralizing antibody inhibited both lesion-induced vascular reactivity and progenitor cell recruitment at the lesion site. We propose a model in which SVZ progenitors respond to a demyelination lesion by NTN1 secretion that both directly promotes cell emigration and contributes to local angiogenesis, which in turn indirectly facilitates progenitor cell emigration from the niche.

Periventricular nodular heterotopia (PH) is a human brain malformation caused by defective neuronal migration that results in ectopic neuronal nodules lining the lateral ventricles beneath a normal appearing cortex. Most affected patients have seizures and their cognitive level varies from normal to severely impaired. Mutations in the Filamin-A (or FLNA) gene are the main cause of PH, but the underlying pathological mechanism remains unknown. Although two FlnA knockout mouse strains have been generated, none of them showed the presence of ectopic nodules. To recapitulate the loss of FlnA function in the developing rat brain, we used an in utero RNA interference-mediated knockdown approach and successfully reproduced a PH phenotype in rats comparable with that observed in human patients. In FlnA-knockdown rats, we report that PH results from a disruption of the polarized radial glial scaffold in the ventricular zone altering progression of neural progenitors through the cell cycle and impairing migration of neurons into the cortical plate. Similar alterations of radial glia are observed in human PH brains of a 35-week fetus and a 3-month-old child, harboring distinct FLNA mutations not previously reported. Finally, juvenile FlnA-knockdown rats are highly susceptible to seizures, confirming the reliability of this novel animal model of PH. Our findings suggest that the disorganization of radial glia is the leading cause of PH pathogenesis associated with FLNA mutations. Rattus norvegicus FlnA mRNA (GenBank accession number FJ416060).