Jimmy Chong

Bio: Jimmy Chong is an academic researcher from Allen Institute for Brain Science. The author has contributed to research in topics: Foot (prosody) & Retrospective cohort study. The author has an hindex of 2, co-authored 2 publications receiving 5995 citations.

Genome-wide atlas of gene expression in the adult mouse brain

Abstract: Molecular approaches to understanding the functional circuitry of the nervous system promise new insights into the relationship between genes, brain and behaviour. The cellular diversity of the brain necessitates a cellular resolution approach towards understanding the functional genomics of the nervous system. We describe here an anatomically comprehensive digital atlas containing the expression patterns of approximately 20,000 genes in the adult mouse brain. Data were generated using automated high-throughput procedures for in situ hybridization and data acquisition, and are publicly accessible online. Newly developed image-based informatics tools allow global genome-scale structural analysis and cross-correlation, as well as identification of regionally enriched genes. Unbiased fine-resolution analysis has identified highly specific cellular markers as well as extensive evidence of cellular heterogeneity not evident in classical neuroanatomical atlases. This highly standardized atlas provides an open, primary data resource for a wide variety of further studies concerning brain organization and function.

An anatomically comprehensive atlas of the adult human brain transcriptome

Abstract: Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ~900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography—the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.

Study of Diabetic Foot Problems Among Patients Attending the Diabetic Foot Clinic at Royal Hampshire County Hospital, United Kingdom: A Single-Centre Experience

Abstract: Background Patients with diabetes mellitus (DM) are on the rise all over the world. Simultaneously, the complications of DM are also increasing. Diabetes-related foot problems have been another concern among health professionals, especially foot ulcers, osteomyelitis, and amputations. Objectives We determined the prevalence of gender, age, types of DM including non-diabetics, various foot-related presentations, complications, and their outcomes. Methods A retrospective descriptive cross-sectional study was conducted among new patients attending a diabetic foot clinic over a period of six months, from January 1, 2019 to June 30, 2019. To confirm the outcome of the study, all of them were followed up for at least four months from the date of diagnosis. Results The study showed that most patients were males (65.5%). The most common age group for diabetic foot problems was 81-90 years, and about 80% of the foot problems were diagnosed in patients over 60 years. The study disclosed that 86.2% of the population had type 2 DM, 56.9% had ulcers, and 13.8% had osteomyelitis. The outcome of our study demonstrated that 65.5% of the patients were cured and discharged within four months of the diagnosis, but 10.3% of the population needed amputation. During the four-month follow-up period, 3.4% of our study population died due to non-foot-related causes. A total of 48.1% of our ulcer patients were discharged within eight weeks of diagnosis. However, 26% of ulcer patients and 75% of osteomyelitis patients needed more than four months to be discharged. Peripheral neuropathy and peripheral arterial disease (PAD) were present in 91% of ulcer patients. Among our osteomyelitis group, 100% had peripheral neuropathy, and 87.5% had PAD. About 20% of ulcer patients and none of the osteomyelitis patients were diagnosed with chronic kidney disease (CKD) stages beyond 3b. About 2/3rd of our ulcer and osteomyelitis population had an HbA1C level of more than 7.5%. Conclusion Male patients over 60 years of age with type 2 DM are more at risk of developing diabetes-related foot issues. Ulcer with or without osteomyelitis was the most common complication among our study population. Results showed that a significant amount of osteomyelitis patients underwent foot amputation. Poor glycaemic control of HbA1C of more than 7.5%, peripheral neuropathy, and PAD were the most common risk factors for developing foot-related complications. Prolonged use of antibiotics and a dedicated professional team may be needed to manage these complications successfully.

A robust and high-throughput Cre reporting and characterization system for the whole mouse brain

Abstract: The Cre/lox system is widely used in mice to achieve cell-type-specific gene expression. However, a strong and universally responding system to express genes under Cre control is still lacking. We have generated a set of Cre reporter mice with strong, ubiquitous expression of fluorescent proteins of different spectra. The robust native fluorescence of these reporters enables direct visualization of fine dendritic structures and axonal projections of the labeled neurons, which is useful in mapping neuronal circuitry, imaging and tracking specific cell populations in vivo. Using these reporters and a high-throughput in situ hybridization platform, we are systematically profiling Cre-directed gene expression throughout the mouse brain in several Cre-driver lines, including new Cre lines targeting different cell types in the cortex. Our expression data are displayed in a public online database to help researchers assess the utility of various Cre-driver lines for cell-type-specific genetic manipulation.

A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain development and function.

Abstract: Understanding the cell–cell interactions that control CNS development and function has long been limited by the lack of methods to cleanly separate neural cell types. Here we describe methods for the prospective isolation and purification of astrocytes, neurons, and oligodendrocytes from developing and mature mouse forebrain. We used FACS (fluorescent-activated cell sorting) to isolate astrocytes from transgenic mice that express enhanced green fluorescent protein (EGFP) under the control of an S100β promoter. Using Affymetrix GeneChip Arrays, we then created a transcriptome database of the expression levels of >20,000 genes by gene profiling these three main CNS neural cell types at various postnatal ages between postnatal day 1 (P1) and P30. This database provides a detailed global characterization and comparison of the genes expressed by acutely isolated astrocytes, neurons, and oligodendrocytes. We found that Aldh1L1 is a highly specific antigenic marker for astrocytes with a substantially broader pattern of astrocyte expression than the traditional astrocyte marker GFAP. Astrocytes were enriched in specific metabolic and lipid synthetic pathways, as well as the draper/Megf10 and Mertk/integrin αvβ5 phagocytic pathways suggesting that astrocytes are professional phagocytes. Our findings call into question the concept of a “glial” cell class as the gene profiles of astrocytes and oligodendrocytes are as dissimilar to each other as they are to neurons. This transcriptome database of acutely isolated purified astrocytes, neurons, and oligodendrocytes provides a resource to the neuroscience community by providing improved cell-type-specific markers and for better understanding of neural development, function, and disease.

Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq

Abstract: The mammalian cerebral cortex supports cognitive functions such as sensorimotor integration, memory, and social behaviors. Normal brain function relies on a diverse set of differentiated cell types, including neurons, glia, and vasculature. Here, we have used large-scale single-cell RNA sequencing (RNA-seq) to classify cells in the mouse somatosensory cortex and hippocampal CA1 region. We found 47 molecularly distinct subclasses, comprising all known major cell types in the cortex. We identified numerous marker genes, which allowed alignment with known cell types, morphology, and location. We found a layer I interneuron expressing Pax6 and a distinct postmitotic oligodendrocyte subclass marked by Itpr2. Across the diversity of cortical cell types, transcription factors formed a complex, layered regulatory code, suggesting a mechanism for the maintenance of adult cell type identity.

Fast, sensitive and accurate integration of single-cell data with Harmony.

Abstract: The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony ( https://github.com/immunogenomics/harmony ), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~106 cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data. Harmony, for the integration of single-cell transcriptomic data, identifies broad and fine-grained populations, scales to large datasets, and can integrate sequencing- and imaging-based data.