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Low-grade glioma (LGG) is a malignancy of the central nervous system that is often treatable with surgical resection and chemoradiation. However, despite an initial positive response to standard therapy, most LGG eventually progress to high-grade gliomas which are nearly uniformly fatal. There is a pressing need for more clinical trials and greater clinical trial accessibility to improve the standard of care of LGG to delay or prevent its progression. In this study, we systematically examined the scope and inclusion of clinical trials for LGG based in the United States. This cross-sectional study analyzes trends in trial design and reported demographic data from completed LGG trials registered on ClinicalTrials.gov between 2010 to 2023. Inclusion criteria, investigational therapies, primary outcomes, and preliminary results were compared and summarized. A total of 14 trials with 1067 participants were included in the study. Most of the trials were not exclusive to LGGs and 14% had mutation-specific inclusion criteria. To date, two of the trials have led to new FDA-approved treatments. All trials reported age and sex, while only 57% reported race and 43% reported ethnicity. Individuals identifying as Black or African American and Asian or Pacific Islander were statistically underrepresented. Lastly, we investigated the geographic distributions of trial sites across the United States, which demonstrated several coverage gaps in the Rocky Mountain and Southeast regions. These findings suggest specific areas for improvement in LGG clinical trial reporting and accessibility. [ABSTRACT FROM AUTHOR]

Stargardt atrophy and geographic atrophy (GA) represent pivotal endpoints in FDA-approved clinical trials. Predicting atrophy progression is crucial for evaluating drug efficacy. Fundus autofluorescence (FAF), the standard 2D imaging modality in these trials, has limitations in patient comfort. In contrast, spectral-domain optical coherence tomography (SD-OCT), a 3D imaging modality, is more patient friendly but suffers from lower image quality. This study has two primary objectives: (1) develop an efficient predictive modeling for the generation of future FAF images and prediction of future Stargardt atrophic (as well as GA) regions and (2) develop an efficient predictive modeling with advanced 3D OCT features at ellipsoid zone (EZ) for the comparative performance in the generation of future enface EZ maps and prediction of future Stargardt atrophic regions on OCT as on FAF. To achieve these goals, we propose two deep neural networks (termed ReConNet and ReConNet-Ensemble) with recurrent learning units (long short-term memory, LSTM) integrating with a convolutional neural network (CNN) encoder–decoder architecture and concurrent learning units integrated by ensemble/multiple recurrent learning channels. The ReConNet, which incorporates LSTM connections with CNN, is developed for the first goal on longitudinal FAF. The ReConNet-Ensemble, which incorporates multiple recurrent learning channels based on enhanced EZ enface maps to capture higher-order inherent OCT EZ features, is developed for the second goal on longitudinal OCT. Using FAF images at months 0, 6, and 12 to predict atrophy at month 18, the ReConNet achieved mean (±standard deviation, SD) and median Dice coefficients of 0.895 (±0.086) and 0.922 for Stargardt atrophy and 0.864 (±0.113) and 0.893 for GA. Using SD-OCT images at months 0 and 6 to predict atrophy at month 12, the ReConNet-Ensemble achieved mean and median Dice coefficients of 0.882 (±0.101) and 0.906 for Stargardt atrophy. The prediction performance on OCT images is comparably good to that on FAF. These results underscore the potential of SD-OCT for efficient and practical assessment of atrophy progression in clinical trials and retina clinics, complementing or surpassing the widely used FAF imaging technique. [ABSTRACT FROM AUTHOR]

High-grade glioma is the most frequent and lethal primary tumor of the central nervous system. Despite advances in surgical, pharmacological, and cell-directed therapies, there have been no updates to the standard of care in over a decade. This cross-sectional study analyzes patient and trial data from 201 interventional trials completed between 2010 and 2023, encompassing 18,563 participants. Although we found that all trials reported participant age and sex, only 52% of trials reported participant demographics, resulting in 51% of total participant demographics being unreported. The majority of studies did not report ethnicity, with approximately 60% of participants unreported. Additionally, males were significantly underrepresented in trials, comprising 60% of participants despite representing 75% of glioblastoma patients. Improved demographic reporting has been observed since 2011; however, it is inconsistent. Furthermore, we cataloged the geographic diversity of trials across the United States and found significant coverage deserts in relatively rural, but highly affected, areas such as Montana and Maine. We found a wider distribution of trials in both urban and wealthier regions, which indicates extensive coverage gaps and decreased access to participation for patients of a lower socioeconomic status. [ABSTRACT FROM AUTHOR]

Previous studies on crosslinguistic influence (CLI) on third language (L3) morphosyntactic acquisition have provided support for competing theories about the source(s) of CLI. The present study aimed to test if both L1 and L2 can be the source of CLI, and whether they influence L3 learning in similar or different ways. In particular, we aimed to add to our knowledge of the neural correlates of CLI by conducting an exploratory EEG study to investigate how L1 and L2 CLI affect L3 neural processing. Predictions based on the D/P model, which posited different memory systems sustaining L1 and L2, were tested. The findings confirmed both L1-sourced and L2-sourced facilitation on L3 morphosyntactic acquisition. Specifically, we suggest that L1-similarity showed a consolidating effect on L3 implicit knowledge and neurocognitive internalization, whereas L2-similarity contributed to enhanced L3 metalinguistic knowledge. This preliminary study is the first to investigate the neurocognitive mechanisms underlying CLI in L3 learning by natural language learners. [ABSTRACT FROM AUTHOR]

The expansion of the human SRGAP2 family, resulting in a human-specific paralog SRGAP2C, likely contributed to altered evolutionary brain features. The introduction of SRGAP2C in mouse models is associated with changes in cortical neuronal migration, axon guidance, synaptogenesis, and sensory-task performance. Truncated SRGAP2C heterodimerizes with the full-length ancestral gene product SRGAP2A and antagonizes its functions. However, the significance of SRGAP2 duplication beyond neocortex development has not been elucidated due to the embryonic lethality of complete Srgap2 knockout in mice. Using zebrafish, we show that srgap2 knockout results in viable offspring and that these larvae phenocopy "humanized" SRGAP2C larvae, including altered morphometric features (i.e., reduced body length and inter-eye distance) and differential expression of synapse-, axonogenesis-, and vision-related genes. Through single-cell transcriptome analysis, we demonstrate a skewed balance of excitatory and inhibitory neurons that likely contribute to increased susceptibility to seizures displayed by Srgap2 mutant larvae, a phenotype resembling SRGAP2 loss-of-function in a child with early infantile epileptic encephalopathy. Single-cell data also shows strong endogenous expression of srgap2 in microglia with mutants exhibiting altered membrane dynamics and likely delayed maturation of microglial cells. Microglia cells expressing srgap2 were also detected in the developing eye together with altered expression of genes related to axonogenesis in mutant retinal cells. Consistent with the perturbed gene expression in the retina, we found that SRGAP2 mutant larvae exhibited increased sensitivity to broad and fine visual cues. Finally, comparing the transcriptomes of relevant cell types between human (+ SRGAP2C ) and non-human primates (- SRGAP2C ) revealed significant overlaps of gene alterations with mutant cells in our zebrafish models; this suggests that SRGAP2C plays a similar role altering microglia and the visual system in modern humans. Together, our functional characterization of conserved ortholog Srgap2 and human SRGAP2C in zebrafish uncovered novel gene functions and highlights the strength of cross-species analysis in understanding the development of human-specific features.

Background: Following the signing of the Tobacco 21 Amendment (T21) in December 2019 to raise the minimum legal age for the sale of tobacco products from 18 to 21 years in the United States, there is a need to monitor public responses and potential unintended consequences. Social media platforms, such as Twitter (subsequently rebranded as X), can provide rich data on public perceptions., Objective: This study contributes to the literature using Twitter data to assess the knowledge and beliefs of T21., Methods: Twitter data were collected from November 2019 to February 2021 using the Twitter streaming application programming interface with keywords related to vaping or e-cigarettes, such as "vape," "ecig," etc. The temporal trend of the T21 discussion on Twitter was examined using the mean number of daily T21-related tweets. Inductive methods were used to manually code the tweets into different sentiment groups (positive, neutral, and negative) based on the attitude expressed toward the policy by 3 coders with high interrater reliability. Topics discussed were examined within each sentiment group through theme analyses., Results: Among the collected 3197 tweets, 2169 tweets were related to T21, of which 444 tweets (20.5%) showed a positive attitude, 736 (33.9%) showed a negative attitude, and 989 (45.6%) showed a neutral attitude. The temporal trend showed a clear peak in the number of tweets around January 2020, following the enactment of this legislation. For positive tweets, the most frequent topics were "avoidance of further regulation" (120/444, 27%), "Enforce T21" (110/444, 24.8%), and "health benefits" (81/444, 18.2%). For negative tweets, the most frequent topics were "general disagreement or frustration" (207/736, 28.1%) and "will still use tobacco" (188/736, 25.5%). Neutral tweets were primarily "public service announcements (PSA) or news posts" (782/989, 79.1%)., Conclusions: Overall, we find that one-third of tweets displayed a negative attitude toward T21 during the study period. Many were frustrated with T21 and reported that underage consumers could still obtain products. Social media data provide a timely opportunity to monitor public perceptions and responses to regulatory actions. Continued monitoring can inform enforcement efforts and potential unintended consequences of T21., (©Liane M Schneller-Najm, Zidian Xie, Jiarui Chen, Sarah Lee, Emily Xu, Dongmei Li. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 25.09.2024.)