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1. The physical and chemical structure of Sagittarius B2: VI. UCHii regions in Sgr B2

   https://doi.org/10.1051/0004-6361/202243674  

   Meng, F. ; Sánchez-Monge, Á. ; Schilke, P. ; Ginsburg, A. ; DePree, C. ; Budaiev, N. ; Jeff, D. ; Schmiedeke, A. ; Schwörer, A. ; Veena, V. S. ; et al ( October 2022 , Astronomy & Astrophysics)

   Context. The giant molecular cloud Sagittarius B2 (hereafter SgrB2) is the most massive region with ongoing high-mass star formation in the Galaxy. Two ultra-compact H ii (UCHii ) regions were identified in SgrB2’s central hot cores, SgrB2(M) and SgrB2(N). Aims. Our aim is to characterize the properties of the H ii regions in the entire SgrB2 cloud. Comparing the H ii regions and the dust cores, we aim to depict the evolutionary stages of different parts of SgrB2. Methods. We use the Very Large Array in its A, CnB, and D configurations, and in the frequency band C (~6GHz) to observe the whole SgrB2 complex. Using ancillary VLA data at 22.4 GHz and ALMA data at 96 GHz, we calculated the physical parameters of the UCH ii regions and their dense gas environment. Results. We identify 54 UCHii regions in the 6 GHz image, 39 of which are also detected at 22.4 GHz. Eight of the 54 UCHii regions are newly discovered. The UCHii regions have radii between 0.006 pc and 0.04 pc, and have emission measure between 10 6 pc cm 6 and 10 9 pc cm 6 . The UCHii regions are ionized by stars of types from B0.5 to O6. We found a typical gas density of ~10 6 –10 9 cm 3 around the UCH ii regions. The pressure of the UCH ii regions and the dense gas surrounding them are comparable. The expansion timescale of these UCHii regions is determined to be ~10 4 –10 5 yr. The percentage of the dust cores that are associated with H ii regions are 33%, 73%, 4%, and 1% for SgrB2(N), SgrB2(M), SgrB2(S), and SgrB2(DS), respectively. Two-thirds of the dust cores in SgrB2(DS) are associated with outflows. Conclusions. The electron densities of the UCHii regions we identified are in agreement with that of typical UCHii regions, while the radii are smaller than those of the typical UCHii regions. The dust cores in SgrB2(M) are more evolved than in SgrB2(N). The dust cores in SgrB2(DS) are younger than in SgrB2(M) or SgrB2(N). 

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2. Human brain region-specific variably methylated regions are enriched for heritability of distinct neuropsychiatric traits

   https://doi.org/10.1186/s13059-021-02335-w  

   Rizzardi, Lindsay F. ; Hickey, Peter F. ; Idrizi, Adrian ; Tryggvadóttir, Rakel ; Callahan, Colin M. ; Stephens, Kimberly E. ; Taverna, Sean D. ; Zhang, Hao ; Ramazanoglu, Sinan ; Hansen, Kasper D. ; et al ( December 2021 , Genome Biology)

   Abstract Background DNA methylation dynamics in the brain are associated with normal development and neuropsychiatric disease and differ across functionally distinct brain regions. Previous studies of genome-wide methylation differences among human brain regions focus on limited numbers of individuals and one to two brain regions. Results Using GTEx samples, we generate a resource of DNA methylation in purified neuronal nuclei from 8 brain regions as well as lung and thyroid tissues from 12 to 23 donors. We identify differentially methylated regions between brain regions among neuronal nuclei in both CpG (181,146) and non-CpG (264,868) contexts, few of which were unique to a single pairwise comparison. This significantly expands the knowledge of differential methylation across the brain by 10-fold. In addition, we present the first differential methylation analysis among neuronal nuclei from basal ganglia tissues and identify unique CpG differentially methylated regions, many associated with ion transport. We also identify 81,130 regions of variably CpG methylated regions, i.e., variable methylation among individuals in the same brain region, which are enriched in regulatory regions and in CpG differentially methylated regions. Many variably methylated regions are unique to a specific brain region, with only 202 common across all brain regions, as well as lung and thyroid. Variably methylated regions identified in the amygdala, anterior cingulate cortex, and hippocampus are enriched for heritability of schizophrenia. Conclusions These data suggest that epigenetic variation in these particular human brain regions could be associated with the risk for this neuropsychiatric disorder. 

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3. Intracranial Electroencephalography and Deep Neural Networks Reveal Shared Substrates for Representations of Face Identity and Expressions

   https://doi.org/10.1523/JNEUROSCI.1277-22.2023  

   Schwartz, Emily ; Alreja, Arish ; Richardson, R. Mark ; Ghuman, Avniel ; Anzellotti, Stefano ( May 2023 , The Journal of Neuroscience)

   According to a classical view of face perception (Bruce and Young, 1986; Haxby et al., 2000), face identity and facial expression recognition are performed by separate neural substrates (ventral and lateral temporal face-selective regions, respectively). However, recent studies challenge this view, showing that expression valence can also be decoded from ventral regions (Skerry and Saxe, 2014; Li et al., 2019), and identity from lateral regions (Anzellotti and Caramazza, 2017). These findings could be reconciled with the classical view if regions specialized for one task (either identity or expression) contain a small amount of information for the other task (that enables above-chance decoding). In this case, we would expect representations in lateral regions to be more similar to representations in deep convolutional neural networks (DCNNs) trained to recognize facial expression than to representations in DCNNs trained to recognize face identity (the converse should hold for ventral regions). We tested this hypothesis by analyzing neural responses to faces varying in identity and expression. Representational dissimilarity matrices (RDMs) computed from human intracranial recordings (n= 11 adults; 7 females) were compared with RDMs from DCNNs trained to label either identity or expression. We found that RDMs from DCNNs trained to recognize identity correlated with intracranial recordings more strongly in all regions tested—even in regions classically hypothesized to be specialized for expression. These results deviate from the classical view, suggesting that face-selective ventral and lateral regions contribute to the representation of both identity and expression.

   SIGNIFICANCE STATEMENTPrevious work proposed that separate brain regions are specialized for the recognition of face identity and facial expression. However, identity and expression recognition mechanisms might share common brain regions instead. We tested these alternatives using deep neural networks and intracranial recordings from face-selective brain regions. Deep neural networks trained to recognize identity and networks trained to recognize expression learned representations that correlate with neural recordings. Identity-trained representations correlated with intracranial recordings more strongly in all regions tested, including regions hypothesized to be expression specialized in the classical hypothesis. These findings support the view that identity and expression recognition rely on common brain regions. This discovery may require reevaluation of the roles that the ventral and lateral neural pathways play in processing socially relevant stimuli.

    

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4. The max‐ p ‐compact‐regions problem

   https://doi.org/10.1111/tgis.12874  

   Feng, Xin ; Rey, Sergio ; Wei, Ran ( November 2021 , Transactions in GIS)

   The max‐p‐compact‐regions problem involves the aggregation of a set of small areas into an unknown maximum number (p) of compact, homogeneous, and spatially contiguous regions such that a regional attribute value is higher than a predefined threshold. The max‐p‐compact‐regions problem is an extension of the max‐p‐regions problem accounting for compactness. The max‐p‐regions model has been widely used to define study regions in many application cases since it allows users to specify criteria and then to identify a regionalization scheme. However, the max‐p‐regions model does not consider compactness even though compactness is usually a desirable goal in regionalization, implying ideal accessibility and apparent homogeneity. This article discusses how to integrate a compactness measure into the max‐pregionalization process by constructing a multiobjective optimization model that maximizes the number of regions while optimizing the compactness of identified regions. An efficient heuristic algorithm is developed to address the computational intensity of the max‐p‐compact‐regions problem so that it can be applied to large‐scale practical regionalization problems. This new algorithm will be implemented in the open‐source Python Spatial Analysis Library. One hypothetical and one practical application of the max‐p‐compact‐regions problem are introduced to demonstrate the effectiveness and efficiency of the proposed algorithm.

    

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5. Hemimethylation of CpG dyads is characteristic of secondary DMRs associated with imprinted loci and correlates with 5-hydroxymethylcytosine at paternally methylated sequences

   https://doi.org/10.1186/s13072-019-0309-2  

   Nechin, Julianna ; Tunstall, Emma ; Raymond, Naideline ; Hamagami, Nicole ; Pathmanabhan, Chris ; Forestier, Samantha ; Davis, Tamara L. ( December 2019 , Epigenetics & Chromatin)

   null (Ed.)

   Abstract Background In mammals, the regulation of imprinted genes is controlled by differential methylation at imprinting control regions which acquire parent of origin-specific methylation patterns during gametogenesis and retain differences in allelic methylation status throughout fertilization and subsequent somatic cell divisions. In addition, many imprinted genes acquire differential methylation during post-implantation development; these secondary differentially methylated regions appear necessary to maintain the imprinted expression state of individual genes. Despite the requirement for both types of differentially methylated sequence elements to achieve proper expression across imprinting clusters, methylation patterns are more labile at secondary differentially methylated regions. To understand the nature of this variability, we analyzed CpG dyad methylation patterns at both paternally and maternally methylated imprinted loci within multiple imprinting clusters. Results We determined that both paternally and maternally methylated secondary differentially methylated regions associated with imprinted genes display high levels of hemimethylation, 29–49%, in comparison to imprinting control regions which exhibited 8–12% hemimethylation. To explore how hemimethylation could arise, we assessed the differentially methylated regions for the presence of 5-hydroxymethylcytosine which could cause methylation to be lost via either passive and/or active demethylation mechanisms. We found enrichment of 5-hydroxymethylcytosine at paternally methylated secondary differentially methylated regions, but not at the maternally methylated sites we analyzed in this study. Conclusions We found high levels of hemimethylation to be a generalizable characteristic of secondary differentially methylated regions associated with imprinted genes. We propose that 5-hydroxymethylcytosine enrichment may be responsible for the variability in methylation status at paternally methylated secondary differentially methylated regions associated with imprinted genes. We further suggest that the high incidence of hemimethylation at secondary differentially methylated regions must be counteracted by continuous methylation acquisition at these loci. 

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