We conclude that some of Libet et al.'s findings appear more fragile than anticipated in light of the substantial scientific work that built on them.Although emerging evidence suggests that altered functional connectivity (FC) of large-scale neural networks is associated with disturbances in individuals at high-risk for psychosis, the findings are still far to be conclusive. We conducted a meta-analysis of seed-based resting-state functional magnetic resonance imaging studies that compared individuals at clinical high-risk for psychosis (CHR), first-degree relatives of patients with schizophrenia, or subjects who reported psychotic-like experiences with healthy controls. Twenty-nine studies met the inclusion criteria. The MetaNSUE method was used to analyze connectivity comparisons and symptom correlations. Our results showed a significant hypo-connectivity within the salience network (p = 0.012, uncorrected) in the sample of CHR individuals (n = 810). Additionally, we found a positive correlation between negative symptom severity and FC between the default mode network and both the salience network (p  less then  0.001, r = 0.298) and the central executive network (p = 0.003, r = 0.23) in the CHR group. This meta-analysis lends support for the hypothesis that large-scale network dysfunctions represent a core neural deficit underlying psychosis development.Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. Smad family We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.Since Anfinsen demonstrated that the information encoded in a protein's amino acid sequence determines its structure in 1973, solving the protein structure prediction problem has been the Holy Grail of structural biology. The goal of protein structure prediction approaches is to utilize computational modeling to determine the spatial location of every atom in a protein molecule starting from only its amino acid sequence. Depending on whether homologous structures can be found in the Protein Data Bank (PDB), structure prediction methods have been historically categorized as template-based modeling (TBM) or template-free modeling (FM) approaches. Until recently, TBM has been the most reliable approach to predicting protein structures, and in the absence of reliable templates, the modeling accuracy sharply declines. Nevertheless, the results of the most recent community-wide assessment of protein structure prediction experiment (CASP14) have demonstrated that the protein structure prediction problem can be largely solved through the use of end-to-end deep machine learning techniques, where correct folds could be built for nearly all single-domain proteins without using the PDB templates. Critically, the model quality exhibited little correlation with the quality of available template structures, as well as the number of sequence homologs detected for a given target protein. Thus, the implementation of deep-learning techniques has essentially broken through the 50-year-old modeling border between TBM and FM approaches and has made the success of high-resolution structure prediction significantly less dependent on template availability in the PDB library.Pentatricopeptide repeat (PPR) proteins are a large family of proteins that act primarily at different posttranscriptional steps of organellar gene expression. We have previously found that the Schizosaccharomyces pombe PPR protein mpal10 interacts with mitochondrial translational activator Mpa1, and both are essential for mitochondrial protein synthesis. However, it is unclear how these two proteins function in mitochondrial protein synthesis in S. pombe. In this study, we further investigated the role of Ppr10 and Mpa1 in mitochondrial protein synthesis. Mitochondrial translational initiation requires two initiation factors, Mti2 and Mti3, which bind to the small subunit of the mitochondrial ribosome (mt-SSU) during the formation of the mitochondrial translational initiation complex. Using sucrose gradient sedimentation analysis, we found that disruption of ppr10, mpa1, or the PPR motifs in Ppr10 impairs the association of Mti2 and Mti3 with the mt-SSU, suggesting that both Ppr10 and Mpa1 may be required for the interaction of Mti2 and Mti3 with the mt-SSU during the assembly of mitochondrial translational initiation complex. Loss of Ppr10 perturbs the association of mitochondrially encoded cytochrome b (cob1) and cytochrome c oxidase subunit 1 (cox1) mRNAs with assembled mitochondrial ribosomes. Proteomic analysis revealed that a fraction of Ppr10 and Mpa1 copurified with a subset of mitoribosomal proteins. The PPR motifs of Ppr10 are necessary for its interaction with Mpa1 and that disruption of these PPR motifs impairs mitochondrial protein synthesis. Our results suggest that Ppr10 and Mpa1 function together to mediate mitochondrial translational initiation.In a previous study, we showed that replication through the N1-methyl-deoxyadenosine (1-MeA) adduct in human cells is mediated via three different Polι/Polθ, Polη, and Polζ-dependent pathways. Based on biochemical studies with these Pols, in the Polι/Polθ pathway, we inferred a role for Polι in the insertion of a nucleotide (nt) opposite 1-MeA and of Polθ in extension of synthesis from the inserted nt; in the Polη pathway, we inferred that this Pol alone would replicate through 1-MeA; in the Polζ pathway, however, the Pol required for inserting an nt opposite 1-MeA had remained unidentified. In this study, we provide biochemical and genetic evidence for a role for Polλ in inserting the correct nt T opposite 1-MeA, from which Polζ would extend synthesis. The high proficiency of purified Polλ for inserting a T opposite 1-MeA implicates a role for Polλ-which normally uses W-C base pairing for DNA synthesis-in accommodating 1-MeA in a syn confirmation and forming a Hoogsteen base pair with T. The potential of Polλ to replicate through DNA lesions by Hoogsteen base pairing adds another novel aspect to Polλ's role in translesion synthesis in addition to its role as a scaffolding component of Polζ.