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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.

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Summary:Copy number variation is an important and abundant source of variation in the human genome, which has been associated with a number of diseases, especially cancer. Massively parallel next-generation sequencing allows copy number profiling with fine resolution. Such efforts, however, have met with mixed successes, with setbacks arising partly from the lack of reliable analytical methods to meet the diverse and unique challenges arising from the myriad experimental designs and study goals in genetic studies. In cancer genomics, detection of somatic copy number changes and profiling of allele-specific copy number (ASCN) are complicated by experimental biases and artifacts as well as normal cell contamination and cancer subclone admixture. Furthermore, careful statistical modeling is warranted to reconstruct tumor phylogeny by both somatic ASCN changes and single nucleotide variants. Here we describe a flexible computational pipeline, MARATHON, which integrates multiple related statistical software for copy number profiling and downstream analyses in disease genetic studies. Availability and implementation:MARATHON is publicly available at https://github.com/yuchaojiang/MARATHON. Supplementary information:Supplementary data are available at Bioinformatics online.

The origins of metal coinage and the monetisation of ancient economies have long been a research focus in both archaeology and economic history. Recent excavations of an Eastern Zhou period (c. 770-220 BC) bronze foundry at Guanzhuang in Henan Province, China, have yielded clay moulds for casting spade coins. The technical characteristics of the moulds demonstrate that the site functioned as a mint for producing standardised coins. Systematic AMS radiocarbon-dating indicates that well-organised minting developed c. 640-550 BC, making Guanzhuang the world's oldest-known, securely dated minting site. This discovery provides important new data for exploring the origin of monetisation in ancient China. Keywords: Central Plains, Bronze Age, Zhou Dynasty, minting, coinage, Introduction The development of standardised metal coinage was a milestone in economic history. Although commodity currencies or weighed precious metals (e.g. cowries, grain, hacksilver) fulfilled rudimentary monetary functions in many [...]

Whole exome sequencing is currently a technology of choice in large-scale cancer genomics studies, where the priority is to identify cancer-associated variants in coding regions. We describe a method for estimating allele-specific copy number using whole exome sequencing data from tumor and matched normal.

Based on realistic engineering geological data in Guangzhou, this study establishes a finite element model for simulating the collapse of the overlying sand stratum after drilling through karst caves roofs.The coupled Euler-Lagrange method (CEL) is employed to simulate the collapse process of the sand stratum. Multiple sets of numerical simulations are conducted using orthogonal experimental design to investigate the influences of different sand stratum thicknesses, cave sizes, and friction angles on the development pattern and to elucidate the mechanism of collapse in the overlying sand stratum. The results indicate that as the thickness of the sandy soil cover layer increases, both the maximum surface displacement and collapse rate of the sand stratum decrease, and the central collapse area becomes noticeably smaller. With an increase in cave size, the collapse range and maximum surface displacement increase. After drilling through karst cave roofs in engineering projects, the vertically adjacent sand near the karst caves undergoes initial instability and failure, with its influence range primarily affected by the thickness of the sand stratum, and the collapse rate mainly influenced by the range of unstable soil. Once the soil in the central collapse area becomes unstable, the surrounding soil is subjected to shear stress and fails, causing displacement towards the center of the karst cave. The amount of soil migration towards the karst cave is mainly influenced by the size of the karst cave, and this portion of the sand exhibits a collapse morphology similar to the angle of repose. [ABSTRACT FROM AUTHOR]

Complete loss of BRCA1 or BRCA2 function is associated with sensitivity to DNA damaging agents. However, not all BRCA1 and BRCA2 germline mutation-associated tumors respond. Herein we report analyses of 160 BRCA1 and BRCA2 germline mutation-associated breast and ovarian tumors. Retention of the normal BRCA1 or BRCA2 allele (absence of locus-specific loss of heterozygosity (LOH)) is observed in 7% of BRCA1 ovarian, 16% of BRCA2 ovarian, 10% of BRCA1 breast, and 46% of BRCA2 breast tumors. These tumors have equivalent homologous recombination deficiency scores to sporadic tumors, significantly lower than scores in tumors with locus-specific LOH (ovarian, P = 0.0004; breast P

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.

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 thtableis important model organism. Author summary: Most RNA sequencing technologies are based on capturing either processed RNA or primary transcripts to define the RNA expression profile of cell lines or organisms. These methods suffer from RNA's inherent instability in revealing a complete view of RNA Polymerase II (RNAPII) transcription. Here, we used a C. elegans xpc-1 mutant which only performs transcription-coupled repair (TCR) to generate a complete RNAPII transcription profile by using the eXcision Repair-sequencing (XR-seq) technology to analyze repair of UV-induced DNA damage. XR-seq captures all the excision products from RNAPII-transcribed regions in the form of 21–28 nucleotide-long DNA oligomers and thus in a sense converts the unstable RNA signal to a more stable DNA signal enabling the generation of the most complete RNAPII transcript profile to date including heretofore unknown transcripts. [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization and underground transportation, as well as the frequent occurrence of extreme weather conditions such as extreme rainfall, flooding disasters for rail transit are becoming severe, and need to be urgently clarified in terms of the mechanism causing them. In this study, a comprehensive model for water damage at the entrance to a rail transit station is proposed, emphasizing the entire process of extreme weather–surface ponding–underground intrusion. The model is validated by the inundation process of Line 5 of the Zhengzhou Metro during the "7.20" event and further applied to Wanqingsha Station of Guangzhou Metro Line 18 in China to determine the surrounding water depth, distribution, total water inflow volume, and water damage time under different rainfall intensities, rain patterns and protection scenarios. It was found that when rainfall reaches the level of a 1-in-2000-years event, the surface water begins to invade the internal rail transit system through the rail transit entrances. When facing extreme rainfall akin to the "7.20" event in Zhengzhou, the rail transit system in Wanqingsha Station meets a heightened risk of water damage, resulting in significantly deeper water levels compared to 1-in-5000-year rainfall event in Guangzhou and exceeds the height of the subway entrances. Analysis of the water intrusion process reveals that, as rainfall intensity escalates, the total inflow water volume into the rail transit system increases while escape time diminishes. Moreover, under identical rainfall intensity, pre-type rainfall yields the highest total water inflow, whereas mid-type rainfall exhibits the shortest escape time. Enhancing the protection conditions can markedly attenuate surface water intrusion into the subterranean rail transit system, thereby enhancing the evacuation time for individuals within the system. [ABSTRACT FROM AUTHOR]