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Abstract Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Abstract Artificial intelligence provides an opportunity to try to redefine disease subtypes based on similar pathobiology. Using a machine-learning algorithm (Subtype and Stage Inference) with cross-sectional MRI from 296 individuals with focal epilepsy originating from the temporal lobe (TLE) and 91 healthy controls, we show phenotypic heterogeneity in the pathophysiological progression of TLE. This study was registered in the Chinese Clinical Trials Registry (number: ChiCTR2200062562). We identify two hippocampus-predominant phenotypes, characterized by atrophy beginning in the left or right hippocampus; a third cortex-predominant phenotype, characterized by hippocampus atrophy after the neocortex; and a fourth phenotype without atrophy but amygdala enlargement. These four subtypes are replicated in the independent validation cohort (109 individuals). These subtypes show differences in neuroanatomical signature, disease progression and epilepsy characteristics. Five-year follow-up observations of these individuals reveal differential seizure outcomes among subtypes, indicating that specific subtypes may benefit from temporal surgery or pharmacological treatment. These findings suggest a diverse pathobiological basis underlying focal epilepsy that potentially yields to stratification and prognostication – a necessary step for precise medicine.

Bulky DNA adducts such as those induced by ultraviolet light are removed from the genomes of multicellular organisms by nucleotide excision repair, which occurs through two distinct mechanisms, global repair, requiring the DNA damage recognition-factor XPC (xeroderma pigmentosum complementation group C), and transcription-coupled repair (TCR), which does not. TCR is initiated when elongating RNA polymerase II encounters DNA damage, and thus analysis of genome-wide excision repair in XPC-mutants only repairing by TCR provides a unique opportunity to map transcription events missed by methods dependent on capturing RNA transcription products and thus limited by their stability and/or modifications (5'-capping or 3'-polyadenylation). Here, we have performed eXcision Repair-sequencing (XR-seq) in the model organism Caenorhabditis elegans to generate genome-wide repair maps in a wild-type strain with normal excision repair, a strain lacking TCR (csb-1), and a strain that only repairs by TCR (xpc-1). Analysis of the intersections between the xpc-1 XR-seq repair maps with RNA-mapping datasets (RNA-seq, long- and short-capped RNA-seq) reveal previously unrecognized sites of transcription and further enhance our understanding of the genome of this important model organism.

High accuracy in text classification can be achieved by simultaneously learning multiple sources of information, such as sequence and word. In this study, we propose a novel learning framework for text classification, called Word-unit Broad Learning System (BLS). The Word-unit BLS utilises a flat neural network known as BLS and offers three key advantages. First, it provides higher accuracy and shorter training time compared to popular machine learning methods, allowing for the simultaneous learning of sequence information and word importance. Second, we incorporate a multi-layer perceptron with attention aggregation in the feature-mapped layer, along with position encoding, to capture the latent relationship between each word and the contextual information in a global context. Lastly, we introduce a novel approach to enhance word representation by employing sememes in the enhancement node layer, thereby improving the feature distribution of each word in the vector space. The effectiveness of the proposed framework was evaluated by conducting experiments on four datasets covering various types of text classifications. The results demonstrate that Word-unit BLS achieves 8.26% higher accuracy than Naive Bayes while requiring 1/33 of the training time. Furthermore, when compared with traditional BLS models, Word-unit BLS outperforms in learning the sequence information. The effectiveness of sememe enhancement in word representation is also demonstrated, particularly in the case of large-scale datasets.

We propose Destin2, a novel statistical and computational method for cross-modality dimension reduction, clustering, and trajectory reconstruction for single-cell ATAC-seq data. The framework integrates cellular-level epigenomic profiles from peak accessibility, motif deviation score, and pseudo-gene activity and learns a shared manifold using the multimodal input, followed by clustering and/or trajectory inference. We apply Destin2 to real scATAC-seq datasets with both discretized cell types and transient cell states and carry out benchmarking studies against existing methods based on unimodal analyses. Using cell-type labels transferred with high confidence from unmatched single-cell RNA sequencing data, we adopt four performance assessment metrics and demonstrate how Destin2 corroborates and improves upon existing methods. Using single-cell RNA and ATAC multiomic data, we further exemplify how Destin2’s cross-modality integrative analyses preserve true cell-cell similarities using the matched cell pairs as ground truths. Destin2 is compiled as a freely available R package available at https://github.com/yuchaojiang/Destin2.

More than a decade of genome-wide association studies (GWASs) have identified genetic risk variants that are significantly associated with complex traits. Emerging evidence suggests that the function of trait-associated variants likely acts in a tissue- or cell-type-specific fashion. Yet, it remains challenging to prioritize trait-relevant tissues or cell types to elucidate disease etiology. Here, we present EPIC (cEll tyPe enrIChment), a statistical framework that relates large-scale GWAS summary statistics to cell-type-specific gene expression measurements from single-cell RNA sequencing (scRNA-seq). We derive powerful gene-level test statistics for common and rare variants, separately and jointly, and adopt generalized least squares to prioritize trait-relevant cell types while accounting for the correlation structures both within and between genes. Using enrichment of loci associated with four lipid traits in the liver and enrichment of loci associated with three neurological disorders in the brain as ground truths, we show that EPIC outperforms existing methods. We apply our framework to multiple scRNA-seq datasets from different platforms and identify cell types underlying type 2 diabetes and schizophrenia. The enrichment is replicated using independent GWAS and scRNA-seq datasets and further validated using PubMed search and existing bulk case-control testing results.

Aiming at the requirements for multi-scale Logo detection in natural scene images,a multi-scale Logo detection algorithm based on convolutional neural network was proposed.The algorithm was based on the realization of two-stage object detection.By constructing feature pyramids and adopting layer-by-layer prediction,multi-scale region proposals were generated.The multi-layer feature maps in convolutional neural networks were fused to enhance the feature representation.The experimental results on the FlickrLogos-32 dataset show that compared with the baseline,the proposed algorithm can improve the recall rate of region proposals,and can improve the performance of small Logo detection while ensuring the accuracy of large and middle Logo,proving the superiority of the proposed algorithm.

Although modified electroconvulsive therapy (ECT) has been reported to be effective for the treatment of schizophrenia (SCZ), its action mechanism is unclear. To elucidate the underlying ECT mechanisms of SCZ, this study used a longitudinal cohort including 21 SCZ patients receiving only antipsychotics (DSZ group) and 21 SCZ patients receiving a regular course of ECT combining with antipsychotics (MSZ group) for 4 weeks. All patients underwent magnetic resonance imaging (MRI) scans at baseline (t1) and follow-up (t2) time points. A matched healthy control (HC) group included 23 individuals who were only scanned at baseline. Functional connectivity (FC) within the default mode network (DMN) was evaluated before and after ECT. Significant interaction of the group over time was found in FC between angular gyrus (AG) and middle temporal gyrus (MTG). Post-hoc analysis showed a significantly enhanced FC of left AG(AG.L) and right MTG (MTG.R) in the MSZ group relative to the DSZ group. In addition, the right AG (AG.R) showed significantly enhanced FC between MTG.R and left MTG (MTG.L) after ECT in the MSZ group, but no in the DSZ group. In particular, the FCs change in AG.L-MTG.R and AG.R-MTG.R were positively correlated with the Positive and Negative Syndrome Scale (PANSS) negative score reduction. Furthermore, the FC change in AG.L-MTG.R was also positively correlated with the PANSS general psychopathology score reduction. These findings confirmed a potential relationship between ECT inducing hyperconnectivity within DMN and improvements in symptomatology of SCZ, suggesting that ECT controls mental symptoms by regulating the temporoparietal connectivity within DMN.

Schizophrenia (SZ) is considered as a self-disorder with disordered local synchronous activation. Previous studies have reported widespread dyssynchrony of local activation in patients with SZ, which may be one of the crucial physiological mechanisms of SZ. To further verify this assumption, this work used a surface-based two-dimensional regional homogeneity (2dReHo) approach to compare the local neural synchronous spontaneous oscillation between patients with SZ and healthy controls (HC), instead of the volume-based regional homogeneity approach described in previous study. Ninety-seven SZ patients and 126 HC were recruited to this study, and we found the SZ showed abnormal 2dReHo across the cortical surface. Specifically, at the global level, the SZ patients showed significantly reduced global 2dReHo; at the vertex level, the foci with increased 2dReHo in SZ were located in the default mode network (DMN), frontoparietal network (FPN), and limbic network (LN); however, foci with decreased 2dReHo were located in the somatomotor network (SMN), auditory network (AN), and visual network (VN). Additionally, this work found positive correlations between the 2dReHo of bilateral rectus and illness duration, as well as a significant positive correlation between the 2dReHo of right orbital inferior frontal gyrus (OIFG) with the negative scores of the positive and negative syndrome scale in the SZ patients. Therefore, the 2dReHo could provide some effective features contributed to explore the pathophysiology mechanism of SZ.

Sorafenib is a first-line molecular-target drug for advanced hepatocellular carcinoma (HCC), but its clinical effects are still limited. In this study we identify Quiescin sulfhydryl oxidase 1 (QSOX1) acting as a cellular pro-oxidant, specifically in the context of sorafenib treatment of HCC. QSOX1 disrupts redox homoeostasis and sensitizes HCC cells to oxidative stress by inhibiting activation of the master antioxidant transcription factor NRF2. A negative correlation between QSOX1 and NRF2 expression was validated in tumor tissues from 151 HCC patients. Mechanistically, QSOX1 restrains EGF-induced EGFR activation by promoting ubiquitination-mediated degradation of EGFR and accelerating its intracellular endosomal trafficking, leading to suppression of NRF2 activity. Additionally, QSOX1 potentiates sorafenib-induced ferroptosis by suppressing NRF2 in vitro and in vivo. In conclusion, the data presented identify QSOX1 as a novel candidate target for sorafenib-based combination therapeutic strategies in HCC or other EGFR-dependent tumor types.

Objective: To explore the structural and functional reorganization of contralateral hippocampus in patients with unilateral mesial temporal lobe epilepsy (mTLE) who achieved seizure-freedom after anterior temporal lobectomy (ATL). Methods: We obtained high-resolution structural MRI and resting-state functional MRI data in 28 unilateral mTLE patients and 29 healthy controls. Patients were scanned before and three and 24 months after surgery while controls were scanned only once. Hippocampal gray matter volume (GMV) and functional connectivity (FC) were assessed. Results: No obvious GMV changes were observed in contralateral hippocampus before and after successful surgery. Before surgery, ipsilateral hippocampus showed increased FC with ipsilateral insula (INS) and temporoparietal junction (TPJ), but decreased FC with widespread bilateral regions, as well as contralateral hippocampus. After successful ATL, contralateral hippocampus showed: (1) decreased FC with ipsilateral INS at three months follow-up, without further changes; (2) decreased FC with ipsilateral TPJ, postcentral gyrus and rolandic operculum at three months, with an obvious increase at 24 months follow-up; (3) increased FC with bilateral medial prefrontal cortex (MPFC) and superior frontal gyrus (SFG) at three months follow-up, without further changes. Conclusions: Successful ATL may not lead to an obvious structural reorganization in contralateral hippocampus. Surgical manipulation may lead to a transient FC reduction of contralateral hippocampus. Increased FC between contralateral hippocampus and bilateral MPFC and SFG may be related to postoperative functional remodeling.

Cisplatin, a platinum chemotherapeutic agent, is widely used to treat several cancers. Here Yimit et al. revert to genome-wide approaches to map and analyze cisplatin damage formation and excision repair with single nucleotide resolution across different mice organs following platinum treatment.

Springback is always a technical problem in sheet metal forming. In this article, the rapid springback compensation control of two-dimensional hull plate is realized by theoretical calculation and numerical simulation. For the cylindrical shell, according to the bending forming theory of medium and thick plates, the total elastic-plastic bending moment is established, and the curvature change before and after springback is deduced. The curvature correction coefficient is determined by the precise numerical simulation technology. At the same time, the validity of the method is verified by cold bending experiment. For the shell with variable curvature, it is divided into several cylindrical surfaces according to the curvature gradient of its geometric section line. The compensation curvature array is obtained by the correction compensation algorithm of springback curvature of cylindrical plate, and the algorithm is verified by numerical simulation. The results show that the method is very close to the expected results. Thus, the efficiency and precision of forming will be improved, and the foundation of digitization of sheet metal forming is established.

Abstract High-throughput DNA sequencing enables detection of copy number variations (CNVs) on the genome-wide scale with finer resolution compared to array-based methods but suffers from biases and artifacts that lead to false discoveries and low sensitivity. We describe CODEX2, as a statistical framework for full-spectrum CNV profiling that is sensitive for variants with both common and rare population frequencies and that is applicable to study designs with and without negative control samples. We demonstrate and evaluate CODEX2 on whole-exome and targeted sequencing data, where biases are the most prominent. CODEX2 outperforms existing methods and, in particular, significantly improves sensitivity for common CNVs.

Aiming at the problem of training sample sparse in Logo recognition task under the deep learning framework,a Logo data synthesis algorithm based on contexts was proposed.The algorithm comprehensively utilizes various types of context information to guide the synthesis of Logo images,such as the interior of Logo object,the neighborhood of Logo object,the link between Logo object and other objects and the scene where Logo object lives in.The experimental results on the FlickrLogos-32 dataset show that the proposed algorithm can improve the performance of the Logo identification algorithm (mAP increase by 8.5%) without relying on additional manual annotation,verifying the effectiveness of the synthesis algorithm.

Summary: Tumor-sequencing studies have revealed the widespread genetic diversity of melanoma. Sequencing of 108 genes previously implicated in melanomagenesis was performed on 462 patient-derived xenografts (PDXs), cell lines, and tumors to identify mutational and copy number aberrations. Samples came from 371 unique individuals: 263 were naive to treatment, and 108 were previously treated with targeted therapy (34), immunotherapy (54), or both (20). Models of all previously reported major melanoma subtypes (BRAF, NRAS, NF1, KIT, and WT/WT/WT) were identified. Multiple minor melanoma subtypes were also recapitulated, including melanomas with multiple activating mutations in the MAPK-signaling pathway and chromatin-remodeling gene mutations. These well-characterized melanoma PDXs and cell lines can be used not only as reagents for a large array of biological studies but also as pre-clinical models to facilitate drug development. : Garman et al. have characterized melanoma PDXs and cell lines described in Krepler et al. (see the related paper in this issue of Cell Reports), identifying major and minor subtypes, some of which were previously not well defined, targeted and immunotherapy resistance, and tumor heterogeneity, creating a set of reagents for future drug discovery and biological studies. Keywords: melanoma, patient-derived xenografts, massively parallel sequencing, cell lines

Most tumours associated with germline BRCA1/BRCA2 loss of function mutations respond to DNA damaging agents, however, some do not. Herein, the authors identify that a subset of breast/ovarian tumors retain a normal allele, which is associated with decreased overall survival after DNA damage-inducing platinum chemotherapy.

Abstract Allele-specific expression is traditionally studied by bulk RNA sequencing, which measures average expression across cells. Single-cell RNA sequencing allows the comparison of expression distribution between the two alleles of a diploid organism and the characterization of allele-specific bursting. Here, we propose SCALE to analyze genome-wide allele-specific bursting, with adjustment of technical variability. SCALE detects genes exhibiting allelic differences in bursting parameters and genes whose alleles burst non-independently. We apply SCALE to mouse blastocyst and human fibroblast cells and find that cis control in gene expression overwhelmingly manifests as differences in burst frequency.

Electroconvulsive therapy (ECT) is considered a treatment option in patients with drug-resistant schizophrenia (SZ). However, approximately one-third of patients do not benefit from ECT in the clinic. Thus, it is critical to investigate differences between ECT responders and non-responders. Accumulated evidence has indicated that one region of ECT action is the hippocampus, which also plays an important role in SZ pathophysiology. To date, no studies have investigated differences in ECT effects in the hippocampus between treatment responders and non-responders. This study recruited twenty-one SZ patients treated for four weeks with ECT (MSZ, n = 21) and twenty-one SZ patients who received pharmaceutical therapy (DSZ, n = 21). The MSZ group was further categorized into responders (MSR, n = 10) or non-responders (MNR, n = 11) based on treatment outcomes by the criterion of a 50% reduction in the Positive and Negative Syndrome Scale total scores. Using structural and resting-state functional MRI, we measured the hippocampal volume and functional connectivity (FC) in all SZ patients (before and after treatment) and 23 healthy controls. In contrast to pharmaceutical therapy, ECT induced bilateral hippocampal volume increases in the MSZ. Both the MSR and MNR exhibited hippocampal expansion after ECT, whereas a lower baseline volume in one of hippocampal subfield (hippocampus-amygdala transition area) was found in the MNR. After ECT, increased FC between the hippocampus and brain networks associated with cognitive function was only observed in the MSR. The mechanism of action of ECT in schizophrenia is complex. A combination of baseline impairment level, ECT-introduced morphological changes and post-ECT FC increases in the hippocampus may jointly contribute to the post-ECT symptom improvements in patients with SZ. Keywords: Electroconvulsive therapy, Schizophrenia, Hippocampus, MRI, Functional connectivity, Resting-state fMRI

Objectives: To explore the dynamic changes of white matters following anterior temporal lobectomy (ATL) in mesial temporal lobe epilepsy (MTLE) patients who achieved seizure-free at two-year follow-up. Methods: Diffusion tensor imaging (DTI) was obtained in ten MTLE patients at five serial time points: before surgery, three months, six months, 12 months and 24 months after surgery, as well as in 11 age- and sex-matched healthy controls at one time point. Regions with significant postoperative fractional anisotropy (FA) changes and their dynamic changes were confirmed by comparing all preoperative and postoperative data using Tract-Based Spatial Statistics (TBSS). Results: After successful ATL, significant FA changes were found in widespread ipsilateral and contralateral white matter regions (P

Parkinson’s disease (PD) can be classified into tremor-dominant and akinetic-rigid subtypes, each of which exhibits a unique clinical course and prognosis. The neural basis for these disparate manifestations is not well-understood, however. This study comprehensively investigated the altered functional connectivity patterns of these two subtypes. Twenty-five tremor-dominant patients, 25 akinetic-rigid patients and 26 normal control subjects participated in this study. Resting-state functional MRI data were analyzed using functional connectivity density (FCD) and seed-based functional connectivity approaches. Correlations between neuroimaging measures and clinical variables were also calculated. Compared with normal control, increased global FCD occurred most extensively in frontal lobe and cerebellum in both subtypes. Compared with akinetic-rigid patients, the tremor-dominant patients showed significantly increased global FCD in the cerebellum and decreased global FCD in portions of the bilateral frontal lobe. Furthermore, different subtypes demonstrated different cerebello-cortical functional connectivity patterns. Moreover, the identified FCD and functional connectivity correlated significantly with clinical variables in the PD patients, and particularly the FCD indices distinguished the different subtypes with high sensitivity (95%) and specificity (80%). These findings indicate that the functional connectivity patterns in the cerebellum and frontal lobe are altered in both subtypes of PD, especially cerebellum are highly related to tremor.

Schizophrenia lacks a clear definition at the neuroanatomical level, capturing the sites of origin and progress of this disorder. Using a network-theory approach called epicenter mapping on cross-sectional magnetic resonance imaging from 1124 individuals with schizophrenia, we identified the most likely "source of origin" of the structural pathology. Our results suggest that the Broca's area and adjacent frontoinsular cortex may be the epicenters of neuroanatomical pathophysiology in schizophrenia. These epicenters can predict an individual's response to treatment for psychosis. In addition, cross-diagnostic similarities based on epicenter mapping over of 4000 individuals diagnosed with neurological, neurodevelopmental, or psychiatric disorders appear to be limited. When present, these similarities are restricted to bipolar disorder, major depressive disorder, and obsessive-compulsive disorder. We provide a comprehensive framework linking schizophrenia-specific epicenters to multiple levels of neurobiology, including cognitive processes, neurotransmitter receptors and transporters, and human brain gene expression. Epicenter mapping may be a reliable tool for identifying the potential onset sites of neural pathophysiology in schizophrenia. [ABSTRACT FROM AUTHOR]