Stephen J. Fleming
A5021451550- Single-cell and spatial transcriptomics
- Nanopore and Nanochannel Transport Studies
- Neural dynamics and brain function
- Congenital heart defects research
- Cell Image Analysis Techniques
- Gene Regulatory Network Analysis
- Cardiac Fibrosis and Remodeling
- Housing, Finance, and Neoliberalism
- Immune cells in cancer
- Advanced biosensing and bioanalysis techniques
- Aortic aneurysm repair treatments
- Aortic Disease and Treatment Approaches
- DNA and Nucleic Acid Chemistry
- Higher Education Teaching and Evaluation
- Gene expression and cancer classification
- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Anodic Oxide Films and Nanostructures
- Currency Recognition and Detection
- Motor Control and Adaptation
- Obsessive-Compulsive Spectrum Disorders
- Digital Imaging for Blood Diseases
- Library Science and Information Literacy
- Neurobiology of Language and Bilingualism
- COVID-19 Clinical Research Studies
- Electrostatics and Colloid Interactions
Broad Institute
2019-2025
University College London
2018-2025
Wellcome Centre for Human Neuroimaging
2018-2025
Bayer (United States)
2020-2021
Prostate Cancer Research
2018
Harvard University
2015-2017
The human heart requires a complex ensemble of specialized cell types to perform its essential function. A greater knowledge the intricate cellular milieu is critical increase our understanding cardiac homeostasis and pathology. As recent advances in low-input RNA sequencing have allowed definitions transcriptomes at single-cell resolution scale, we applied these approaches assess transcriptional diversity nonfailing heart.
Abstract Droplet-based single-cell assays, including scRNA-seq, snRNA-seq, and CITE-seq, produce a significant amount of background noise counts, the hallmark which is non-zero counts in cell-free droplets off-target gene expression unexpected cell types. The presence such systematic potential source batch effect spurious differential expression. Here we develop deep generative model for noise-contaminated data that structured to reflect phenomenology generation droplet-based assays....
Abstract The SARS-CoV-2 pandemic has caused over 1 million deaths globally, mostly due to acute lung injury and respiratory distress syndrome, or direct complications resulting in multiple-organ failures. Little is known about the host tissue immune cellular responses associated with COVID-19 infection, symptoms, lethality. To address this, we collected tissues from 11 organs during clinical autopsy of 17 individuals who succumbed COVID-19, a bank approximately 420 specimens. We generated...
Metacognitive biases are characteristic of common mental health disorders like depression and obsessive-compulsive disorder (OCD). However, recent transdiagnostic approaches consistently contradict traditional clinical studies, with overconfidence in perception among highly compulsive individuals versus underconfident memory OCD patients. To reconcile these differences, we investigated whether metacognitive divergences may arise due to cognitive domain-specific effects, comorbid...
Abstract Background The molecular underpinnings of organ dysfunction in severe COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these the context liver function, we perform single-nucleus RNA-seq spatial transcriptomic profiling livers from 17 decedents. Results We identify hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells, a central role pro-fibrotic TGFβ signaling cell–cell...
Abstract Voltage imaging enables high-throughput investigation of neuronal activity, yet its utility is often constrained by a low signal-to-noise ratio (SNR). Conventional denoising algorithms, such as those based on matrix factorization, impose limiting assumptions about the noise process and spatiotemporal structure signal. While deep learning techniques offer greater adaptability, existing approaches fail to fully exploit fast temporal dynamics unique short- long-range dependencies...
The aorta is the largest blood vessel in body, and enlargement or aneurysm of can predispose to dissection, an important cause sudden death. While rare syndromes have been identified that aortic aneurysm, common genetic basis for size remains largely unknown. By leveraging a deep learning architecture was originally developed recognize natural images, we trained model evaluate dimensions ascending descending thoracic cardiac magnetic resonance imaging. After manual annotation just 116...
The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these the context liver function, we performed single-nucleus RNA-seq spatial transcriptomic profiling livers from 17 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis comparisons healthy controls revealed extensive changes cellular...
Abstract Established models of perceptual metacognition, the ability to evaluate our judgments, posit that confidence depends on strength or quality feedforward sensory evidence. However, alternative theoretical accounts suggest entire perception-action cycle, and not only variation in evidence, is monitored when evaluating one’s percepts. Such lead counterintuitive prediction should be directly modulated by features motor output. To this proposal here we recorded electromyographic (EMG)...
This paper examines the interaction of different agents involved with production, consumption and control new private housing. The context is central Berkshire, an area high economic residential growth. Continued housing growth urban expansion runs counter to dominant local opinion, which reflected by activity many community groups in planning sphere. Typologies are offered speculative house-builders groups, based partly on their relationship system. role state (planning system) then...
Abstract Introduction The human heart requires a complex ensemble of specialized cell types to perform its essential function. A greater knowledge the intricate cellular milieu is critical increase our understanding cardiac homeostasis and pathology. As recent advances in low input RNA-sequencing have allowed definitions transcriptomes at single resolution scale, here we applied these approaches assess transcriptional diversity non-failing heart. Methods Microfluidic encapsulation barcoding...
Voltage imaging is a powerful technique for studying neuronal activity, but its effectiveness often constrained by low signal-to-noise ratios (SNR). Traditional denoising methods, such as matrix factorization, impose rigid assumptions about noise and signal structures, while existing deep learning approaches fail to fully capture the rapid dynamics complex dependencies inherent in voltage data. Here, we introduce CellMincer, novel self-supervised method specifically developed datasets....
Abstract Spatial transcriptomics allows for the measurement of gene expression within native tissue context, thereby improving our understanding how cell states are modulated by their microenvironment. Despite technological advancements, computational methods to link with microenvironment and perform comparative analysis across different samples conditions still underdeveloped. To address this, we introduce TissueMosaic ( Tissue MOtif-based SpAtial Inference Conditions ), a self-supervised...
Abstract Background Despite the critical role of cardiovascular system, our understanding its cellular and transcriptional diversity remains limited. We therefore sought to characterize composition, phenotypes, molecular pathways, communication networks between cell types at tissue sub-tissue level across system healthy Wistar rat, an important model in preclinical research. obtained high quality samples under controlled conditions that reveal a detail so far inaccessible human studies....