Project description:The National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support the global academic and industrial communities. With the rapid accumulation of multi-omics data at an unprecedented pace, CNCB-NGDC continuously expands and updates core database resources through big data archiving, integrative analysis and value-added curation. Importantly, NGDC collaborates closely with major international databases and initiatives to ensure seamless data exchange and interoperability. Over the past year, significant efforts have been dedicated to integrating diverse omics data, synthesizing expanding knowledge, developing new resources, and upgrading major existing resources. Particularly, several database resources are newly developed for the biodiversity of protists (P10K), bacteria (NTM-DB, MPA) as well as plant (PPGR, SoyOmics, PlantPan) and disease/trait association (CROST, HervD Atlas, HALL, MACdb, BioKA, BioKA, RePoS, PGG.SV, NAFLDkb). All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.
Project description:Neuropathology-based studies in neurosurgically resected brain tissue obtained from carefully examined patients with focal epilepsies remain a treasure box for excellent insights into human neuroscience, including avenues to better understand the neurobiology of human brain organization and neuronal hyperexcitability at the cellular level including glio-neuronal interaction. It also allows to translate results from animal models in order to develop personalized treatment strategies in the near future. A nice example of this is the discovery of a new disease entity in 2017, termed mild malformation of cortical development with oligodendroglial hyperplasia in epilepsy or MOGHE, in the frontal lobe of young children with intractable seizures. In 2021, a brain somatic missense mutation of the galactose transporter SLC35A2 leading to altered glycosylation of lipoproteins in the Golgi apparatus was detected in 50 % of MOGHE samples. In 2023, the first clinical trial evaluated galactose supplementation in patients with histopathologically confirmed MOGHE carrying brain somatic SLC35A2 mutations that were not seizure free after surgery. The promising results of this pilot trial are an example of personalized medicine in the arena of epileptology. Besides this, neuropathological studies of epilepsy samples have revealed many other fascinating results for the main disease categories in focal epilepsies, such as the first deep-learning based classifier for Focal Cortical Dysplasia, or the genomic landscape of cortical malformations showing new candidate genes such as PTPN11, which is associated with ganglioglioma and adverse clinical outcome. This update will also ask why common pathogenic variants accumulate in certain brain regions, e.g., MTOR in the frontal lobe, and BRAF in the temporal lobe. Finally, I will highlight the ongoing discussion addressing commonalities between temporal lobe epilepsy and Alzheimer's disease, the impact of adult neurogenesis and gliogenesis for the initiation and progression of temporal lobe seizures in the human brain as well as the immunopathogenesis of glutamic acid decarboxylase antibody associated temporal lobe epilepsy as a meaningful disease entity. This review will update the reader on some of these fascinating publications from 2022 and 2023 which were selected carefully, yet subjectively, by the author.
Project description:WikiPathways (wikipathways.org) is an open-source biological pathway database. Collaboration and open science are pivotal to the success of WikiPathways. Here we highlight the continuing efforts supporting WikiPathways, content growth and collaboration among pathway researchers. As an evolving database, there is a growing need for WikiPathways to address and overcome technical challenges. In this direction, WikiPathways has undergone major restructuring, enabling a renewed approach for sharing and curating pathway knowledge, thus providing stability for the future of community pathway curation. The website has been redesigned to improve and enhance user experience. This next generation of WikiPathways continues to support existing features while improving maintainability of the database and facilitating community input by providing new functionality and leveraging automation.
Project description:Figure-ground (FG) segregation that separates an object from the rest of the image is a fundamental problem in vision science. A majority of neurons in monkey V2 showed the selectivity to border ownership (BO) that indicates which side of a contour owns the border. Although BO could be a precursor of FG segregation, the contribution of BO to FG segregation has not been clarified. Because FG segregation is the perception of the global region that belongs to an object, whereas BO determination provides the local direction of figure (DOF) along a contour, a spatial integration of BO might be expected for the generation of FG. To understand the mechanisms underlying the perception of figural regions, we investigated the interaction between the local BO determination and the global FG segregation through the quantitative analysis of the visual perception and the spatiotemporal characteristics of eye movements. We generated a set of novel stimuli in which translucency induces local DOF along the contour and global FG independently so that DOF and FG could be either consistent or contradictory. The perceptual responses showed better performance in DOF discrimination than FG segregation, supporting distinct mechanisms for the DOF discrimination and the FG segregation. We examined whether the contradiction between DOF and FG modulates the eye movement while participants judged DOF and FG. The duration of the first eye fixation was modulated by the contradiction during FG segregation but not DOF discrimination, suggesting a sequential processing from the BO determination to the FG segregation. These results of human perception and eye fixation provide important clues for understanding the visual processing for FG segregation.
Project description:It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles' heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input-output function describing how the level of expression depends upon the parameters of the regulated gene-for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles' heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.
Project description:Quantitative data analysis skills are basic competencies students in a STEM field should master. In this article, we describe a classroom activity using isolated figures from papers as a simple exercise to practice data analysis skills. We call this approach Just Figures. With this technique, instructors find figures from primary papers that address key concepts related to several of their course learning objectives. These figures are assigned as homework prior to class discussion. In class, instructors teach the lesson and include a 10- to 20-minute discussion of the figures assigned. Frequent and repeated discussion of paper figures during class increased students' confidence in reading and analyzing data. The Just Figures approach also increased student accuracy when interpreting data. After six weeks of Just Figures practice, students scored, on average, three points higher on a 20-point data analysis assessment instrument than they had done before the Just Figures exercises. In addition, a course in which students consistently practiced Just Figures performed just as well on the data analysis assessment instrument and on a class exam dedicated to paper reading compared with courses where students practiced reading three entire papers. The Just Figures method is easy to implement and can effectively improve student data analysis skills in microbiology classrooms.