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Ma, J.

Publications and source records attributed to Ma, J..

At least 55 records · Page 3Linked to original sources

A Decade of Deep Learning-based Biomedical Image Segmentation

Biomedical image segmentation is a fundamental problem in computational biomedicine that aims to precisely delineate anatomical and biological structures, tissue types, or pathological regions in biomedical images. Accurate segmentation is essential for interpretation, decision-making, and quantitative analysis across a wide range of biological and medical applications. Over the past decade, the field has undergone a profound paradigm shift, evolving from task-specific specialist models to universal foundation models. This review provides an in-depth analysis of the evolution, tracing how the limitations of local discriminative learning drove the transition toward transformer-based global modeling, and large-scale generative pre-training. To help navigate the diverse landscape of interaction paradigms, we introduce the first systematic taxonomy of promptable biomedical image segmentation, categorizing existing methods into six distinct types, enabling users to intuitively select appropriate prompting strategies based on visual demonstrations and quickly pinpoint relevant literature (Prompt Type Visualization). Beyond model architectures, we discuss parallel advancements in dataset development, evaluation protocols, and application-specific adaptations across radiology, pathology, and biology. Integrating these powerful foundation models with rigorous domain-specific adaptation has great potential to improve patient outcomes and healthcare efficiency. Finally, we highlight key challenges in trustworthiness and clinical integration that must be overcome to realize the potential of the next generation of biological and medical generalists.

bioengineering↗

Multiscale volume electron microscopy of the human liver maps vascular-cellular architecture, organelle dynamics and inter-organelle communication

The human liver depends on multiscale structural organization from vasculature to cells to organelles to perform its diverse metabolic functions. A unified three-dimensional view linking these hierarchical scales in intact human tissue would be useful for better understanding these levels and how they relate to each other. We present a high-resolution volume electron microscopy reconstruction of human periportal liver tissue (152 x 140 x 33 {micro}m3 at 8 nm pixel size) acquired by serial block-face scanning electron microscopy. Using a multiscale deep learning approach, we performed automated segmentation across the entire volume, enabling comprehensive annotation of vasculature, cells, and organelles. Quantitative analysis of bile duct architecture revealed coordinated scaling between lumen geometry and cholangiocyte number and size. Sinusoidal capillary branches exhibited distinct structural profiles with differential endothelial coverage. Analysis of 35,790 complete mitochondria identified substantial morphological heterogeneity, with elongated mitochondria displaying preferential endoplasmic reticulum (ER) contacts at narrowing sites, a pattern consistent with ER-mediated fission or fusion. This multiscale reconstruction establishes an ultrastructural reference for the healthy human liver and provides a quantitative framework for investigating hepatic physiology and disease.

cell biology↗

Autoluminescence characteristics of 25 Phalaenopsis orchids following transient transformation with eFBP2

Engineering autoluminescent plants, especially horticultural crops, has recently emerged as a promising research area, with one current approach involving the transgenic introduction of fungal bioluminescence pathway genes. Although autoluminescent plants such as tobacco and petunia have been created, it remains unclear whether all horticultural plants have the potential to be autoluminescent after genetic modification, especially those having flowers with dark colors and thick cuticles. To understand whether, and what if any, floral traits affect autoluminescence potential, we assess the autoluminescence characteristics of 25 representative Phalaenopsis cultivars after transient transformation of fungal bioluminescence pathway genes, alongside several key morphological and biochemical traits. Our results demonstrate that autoluminescence characteristics are correlated with floral color lightness, organ textures and epidermal cell types. In contrast, the content of the substrates of luciferin--caffeic acid and tyrosine, and the infiltration ease of inoculation solution into floral organs after injection, have limited effects on autoluminescence characteristics. Autoluminescence intensity can be reasonably predicted using five floral traits investigated, as 80.4% of variation can be explained by these traits. Our study not only identifies specific Phalaenopsis cultivars with high potential for developing autoluminescent lines but also provides a selection framework applicable to other horticultural crops.

plant biology↗

Engineering age-adaptive mRNA lipid nanoparticle cancer vaccines via reprogramming systemic gene expression

Lipid nanoparticle (LNP)-based mRNA vaccines have transformed cancer immunotherapy, yet their efficacy in older individuals, who represent the majority of cancer patients, remains poorly understood. Here, we uncover a critical and previously underappreciated barrier to mRNA LNP cancer vaccine performance in aged hosts: impaired systemic transgene expression. Using the SM-102 mRNA LNPs as a benchmark formulation, we show that while local immune activation and antigen presentation at the injection site and draining lymph nodes remain largely intact with age, transgene expression in peripheral organs, including the liver, lungs, and spleen, is markedly reduced. This deficit limits the magnitude and durability of CD8 and CD4 T cell responses and substantially compromises tumour control. Transcriptomic profiling further reveals that attenuated transgene expression parallels broad attenuation of antigen processing, presentation, and activation pathways in immune cells from aged animals, implicating impaired systemic mRNA translation as a central driver of the downstream immune defects and antitumour efficacy loss. Building on these insights, we identify a rationally selected LNP formulation that reestablishes distal antigen expression across age groups as an engineering strategy to revive T cell immunity, achieving full rescue of therapeutic efficacy in aged mice without additional intervention. Together, these findings establish systemic mRNA translation as a tuneable lever of vaccine performance and highlight that optimizing LNP formulations to sustain systemic transgene expression across age groups may enable next-generation, age-adaptive mRNA vaccines for cancer and other diseases of aging.

bioengineering↗

End-to-end evaluation of pipelines for metagenome-assembled genomes reveals hidden performance gaps

The generation of Metagenome Assembled Genomes (MAGs) has become a standard and basic step in the analysis of metagenomic data. This multi-step process, which includes assembly, binning, refinement, and quality control, has many alternative approaches, algorithms, and parameters. Determining the ideal approach for a given ecosystem and study, or highlighting algorithmic gaps in need of additional research and development, requires rigorous benchmarking. We present MAG-E (MAG pipeline Evaluator), a generalizable and expandable framework for end-to-end evaluation of entire MAG pipelines: from assembly, through binning, to quality control and filtering. MAG-E relies on simulations that are built to match an ecosystem of interest and provide a ground truth for accurate evaluation. To demonstrate the capabilities of MAG-E, we benchmark two assemblers, six binning algorithms, three binning modes, and three quality control and refinement methods in the context of the human gut microbiome. Our findings offer multiple insights into optimal MAG generation in this context. We find that metaSPAdes consistently outperforms MEGAHIT in terms of recall (completeness), and that COMEBin overall outperforms alternative binning algorithms, but has lower precision than SemiBin2. While multi-sample binning results in higher precision, as previously shown, single-sample binning has higher recall and leads to better overall performance with modern binners. Binning refinement, which combines bins from multiple different algorithms, leads to reduced performance. We further show that CheckM2 systematically overestimates completeness and underestimates contamination, and that this is partially ameliorated when using GUNC. Finally, we analyze performance at the contig level, and demonstrate that binning algorithms systematically underperform for prophages and fail to bin contigs that are shared between genomes. Overall, MAG-E offers deep insights into successes and gaps in this important analytic process.

bioinformatics↗

Levosimendan inhibits HIV-1 infection in myeloid cells in the RIOK1-dependent manner

Despite of the highly potent antiretroviral therapies, HIV-1 establishes persistent infection and causes chronic inflammation in AIDS patients. Beyond CD4+ T cells, HIV-1 infects myeloid cells, including circulating monocytes and tissue-resident macrophages, and integrates with host genomes to form stable viral reservoirs. To achieve a functional HIV cure, latency-promoting agents (LPAs) have been developed for the "block-and-lock" strategy to reinforce deep HIV-1 latency and permanently silence proviruses. However, most LPAs have been tested mainly in CD4+ T cells, and their efficacy in myeloid cells remains unclear. In this study, we reported that levosimendan (LSM), a drug approved for clinic use to treat heart failures, is able to inhibit HIV lytic infection and reactivation in myeloid cells. LSM blocked viral lytic reactivation in HIV-1 latently infected monocytic cells (TH89GFP, U1) and microglial cells (HC69). LSM also inhibited HIV infection in human induced pluripotent stem cell (iPSC) derived microglia (iMG), primary human resident liver macrophages (Kupffer cells) as well as human monocyte-derived macrophages (MDMs). Furthermore, we demonstrated that overexpression of a predicted drug target of LSM, the conserved serine/threonine kinase RIOK1 (RIO kinase 1), overcomes LSMs anti-HIV effect. Overall, our studies concluded that LSM is a promising LPA to inhibit HIV-1 infection in myeloid cells in the RIOK1-dependent manner.

microbiology↗

Cell-nanoplastics association impacts cell proliferationand motility

Detection of micro- and nanoplastics (MNPs) in human tissues has raised growing concern about their biological effects on tissue and cell function. While previous studies have examined MNP-cell interaction, most focused on limited cell and plastic types. Here, we present a comprehensive, quantitative investigation into how different types of nanoplastics (NPs) associate with and affect diverse cell types under physiologically relevant conditions. Using microfluidic-calibrated fluorescence microscopy, we quantify NP accumulation in cells in vitro and match cellular NP concentrations to levels reported in human tissues. While cell-associated NPs could be gradually released in vitro, they persist in vivo for over one month without detectable reduction in a mouse model. We discover that NP exposure at these levels broadly impairs cell proliferation across epithelial, endothelial, fibroblast, and immune cells, with cell type-dependent sensitivity. NP exposure also reduces motility in T cells and fibroblasts, with more complex effects observed in macrophages. Mechanistically, NP-cell association and trans-epithelial transport involved not only classical endocytic regulators but also pathways related to ion and water transport. Notably, NP association and release were highly sensitive to the extracellular fluid environment within the physiological range. By testing inhibitors of these pathways, we identified molecules that reduce NP-cell association and promote release. We further compared common NPs found in human samples and widely used in research: polystyrene (PS), polyethylene (PE), and polypropylene (PP). Although these NPs similarly impaired proliferation and motility, they showed markedly different cellular association and release dynamics. These findings reveal the impact of NPs on tissue cell functions and uncover novel regulatory pathways, establishing a quantitative framework for studying NP-cell interactions in biologically relevant conditions.

cell biology↗

Nucleoid-associated proteins sense phage-induced genome damage to elicit abortive infection

Bacteria have evolved diverse immune strategies to detect and neutralize bacteriophage infection. Here, we describe an unprecedented paradigm in which a chromosome-architecting nucleoid-associated protein (NAP) is repurposed as a viral infection sensor. When phage attack leads to genome degradation, the NAP sensor is released from the nucleoid to the cytoplasm, where it binds and activates diverse immune effectors. One such effector is a nucleotide-modifying toxin normally existing as an inactive homotetramer. NAP binding converts it into a catalytically active heterotrimer that halts both transcription and translation. Phylogenetic analyses unveiled the high modularity, polyphyletic origin, and wide distribution of NAP-mediated defenses. Collectively, we define a distinct class of defense systems in which bacteria sense phage-induced genome damage through NAP relocation, highlighting an unexpected but essential role for these proteins as sentinels of genome integrity.

microbiology↗

Top-down regulation of ingestive behavior fragmentation

AbstractIn natural environments, animals rarely feed continuously to satiation; instead, feeding occurs in brief bouts separated by pauses. This fragmentation is thought to balance internal drives with external demands, yet its underlying neural mechanisms remain unclear. By combining bidirectional neural activity mapping and behavioral phenotyping, we identify a projection from the dorsal subiculum (dSub) of the hippocampus to the mammillary body (MB) as a key regulator of this fragmentation. Activity along the dSub-MB pathway tracks and gates the duration of individual feeding bouts, independent of homeostatic state. A simple bistable attractor model captures both dSub-MB neural dynamics and associated behaviors across optogenetic and behavioral perturbations. Together, these findings identify a top-down circuit mechanism that implements action selection in a naturalistic setting.

neuroscience↗

Genetic Impacts on Variability of Body Fat Distribution Uncover Gene-Environment and Gene-Gene Interactions

Body fat distribution is a strong predictor of cardiometabolic disease risk. Gene-environment and gene-gene interactions can affect body fat distribution, resulting in differential phenotypic variance across genotype groups that can be detected through variance quantitative trait loci (vQTLs). Using UK Biobank MRI data in conjunction with genetic data, we explored evidence for vQTLs for body fat distribution phenotypes aiming to uncover potential genetic interactions. We identified three vQTLs for liver fat distribution, including rs738408 (PNPLA3), rs4293458 (APOE), and rs58542926 (TM6SF2), and one vQTL region (FTO) for abdominal subcutaneous adipose tissue. To dissect putative gene-environment and gene-gene interactions underlying these signals, we identified multiple vQTL-environment interactions and one epistatic effect (rs58542926*rs429358) for liver fat. The vQTLs and interaction results were validated in multiple UK Biobank and external replication cohort datasets (Framingham Heart Study, All of Us, and TwinsUK), showing replication of the three liver vQTLs with the greatest reproducibility for vQTL rs738408. Our findings uncover vQTLs and underlying interaction effects on body fat distribution, especially liver fat, that may be useful for the development of precision medicine approaches.

genetics↗

Reduced LACTB expression in myeloid cells is associated with elevated succinylcarnitine levels and reduced Alzheimers disease risk.

BackgroundLactamase {beta} (LACTB) is a serine {beta}-lactamase-like mitochondrial enzyme associated with cancer progression, obesity, and lipid metabolism. LACTB is located in an Alzheimers Disease (AD) risk locus and has been associated with AD in a proteomic study. MethodsWe performed Mendelian Randomization (MR) analysis to estimate the association between LACTB expression, succinylcarnitine levels, and AD risk. We generated LACTB knock-down (KD) THP1 macrophages, LACTB knock-out (KO) iPSC-derived microglia and LACTB enzymatically-dead (ED) mice. The impact of LACTB loss-of-function in myeloid cells was characterized via transcriptomics, metabolomics, lipidomics, and functional assays. Finally, human LACTB KO microglia precursors were xenotransplanted into the brains of mice with amyloid pathology to assess in vivo interactions with amyloid plaques. ResultsMR analyses revealed that lower LACTB expression in myeloid cells may lead to reduced AD risk and higher levels of succinylcarnitine, a metabolite associated with AD risk. We identified LACTB as a primary enzyme responsible for succinylcarnitine hydrolysis. Transcriptional and functional studies showed that loss of LACTB enhances OXPHOS, and reduces protein synthesis and triglycerides. LACTB expression was upregulated following interferon or TNF stimulation, and its loss modified efferocytosis- related functions under inflammatory conditions. In vivo, xenotransplanted human LACTB KO microglia exhibited enhanced association with amyloid plaques. ConclusionsOur findings define a previously unrecognized axis linking LACTB and succinylcarnitine to myeloid cell function and AD susceptibility. Given the druggability of LACTB and the potential for succinylcarnitine to serve as a translational biomarker, this enzyme represents a promising therapeutic target for modulation of neuroinflammation in AD.

neuroscience↗

Complete Genomes of Cultivated Gut Bacteria Reveal Mobile Genetic Element-Driven Functional Diversity with Therapeutic Implications

Cultivated bacterial isolates are essential for elucidating gut microbiota functions, yet reliance on fragmented draft genomes and limited mobile genetic element (MGE) annotation has constrained high-resolution analyses. Here, we present the Cultivated Complete Genome Reference (CCGR), a comprehensive compendium of 1,150 fully circularized human gut bacterial genomes. Overcoming draft limitations, CCGR achieves chromosome-scale resolution and reveals distinct evolutionary strategies shaping gene topological organization in response to bacterial growth. Furthermore, we decode the dynamic landscape of MGEs, demonstrating that broad-host-range phages follow strict positional patterns by integrating at conserved chromosomal hotspots flanked by nutrient transporter loci. Importantly, we provide mechanistic in vivo evidence that accessory genomic elements drive strain-level functional heterogeneity. Specifically, the plasmid-encoded scrK gene in Levilactobacillus brevis involved in fructose catabolism is required to mitigate fructose-diet-exacerbated colitis. Collectively, CCGR establishes a framework linking chromosomal architecture and MGEs to bacterial evolution and host health, enabling precise, strain-resolved functional investigations.

microbiology↗

Stromal asparagine supports tumor adaptation to oxidative phosphorylation inhibition through SLC38A4-mediated metabolic coupling

PurposePancreatic ductal adenocarcinoma (PDAC) is characterized by a nutrient-deprived and hypoxic tumor microenvironment (TME) that imposes severe metabolic stress on cancer cells. Under these conditions, tumor cells frequently activate the integrated stress response (ISR) to adapt to TME and develop resistance to therapies. However, how TME components support tumor adaptation to mitochondrial metabolic stress remains incompletely understood. Here, we aimed to identify key metabolite involved in ISR adaptation under oxidative phosphorylation (OXPHOS) inhibition and to elucidate the metabolic symbiosis between cancer-associated fibroblasts (CAFs) and PDAC cells. MethodsWe integrated transcriptomic and metabolomic analyses with functional assays. ISR activation was evaluated by assessing the phosphorylation of eIF2 (p-eIF2) following treatment with carboxyamidotriazole orotate (CTO), an Complex I inhibitor. Metabolomic profiling was used to identify metabolites involved in ISR activation alleviation. Mouse models were used to assess therapeutic responses following depletion of the identified metabolite under CTO treatment. Genetic perturbation of Slc38a4 was performed to assess its functional role in tumor cell adaptation to metabolic stress. ResultsWe identified asparagine (ASN) as a critical metabolite supplied by CAFs to PDAC cells under OXPHOS inhibition. A minimum level of ASN is required for PDAC cells to execute ISR downstream adaptation. ASN depletion significantly enhanced the anti-tumor efficacy of OXPHOS inhibition both in vitro and in vivo. SLC38A4 emerged as a potential mediator of this interaction. SLC38A4 expression was associated with c-Myc, and its loss increased the sensitivity of PDAC cells to CTO-induced metabolic stress. ConclusionOur findings reveal a CAF-tumor metabolic crosstalk in which stromal-derived ASN supports PDAC cell adaptation to mitochondrial metabolic stress. Adaptive outcome of ISR signaling depends on the availability of key metabolic substrates such as ASN. When extracellular ASN supply is limited, the ATF4-dependent adaptive program collapses, converting ISR from a pro-survival response into a therapeutic vulnerability. SLC38A4 may function as a key mediator of this metabolic coupling and represents a potential target for enhancing the efficacy of OXPHOS inhibition in PDAC.

cancer biology↗

Programming Biomolecular Interactions with All-Atom Generative Model

Biomolecular interactions lie at the core of cellular life, spanning diverse molecular modalities from small molecules to nucleic acids and proteins. Nevertheless, design strategies remain separated despite shared physicochemical principles of molecular recognition. Here we present AnewOmni, a unified generative framework trained on more than 5 million biomolecular complexes, that enables transferable molecular design across molecular scales by assembling chemically meaningful building blocks at atomic resolution. We further introduce programmable graph prompts to support user-defined chemical, topological, and geometric steering during generation, exploring hybrid and unconventional chemistries beyond canonical structures. We demonstrate that transferable learning of interaction patterns and physical constraints across molecular modalities is possible, via an atom-to-block latent space capturing both atomic details and structural priors. The framework successfully designed small molecules, peptides, and nanobodies targeting the challenging KRAS G12D switch II pocket, as well as orthosteric peptides and allosteric small-molecule inhibitors for PCSK9 in the absence of known binding site, achieving 23%-75% success with only low-throughput validation, bypassing modality-specific high-throughput screening. AnewOmni is the first to succeed in functional molecular design across all scales, from small chemical entities to large biologics, and represents a stepstone towards general molecular reasoning engines, advocating a generative foundation model for biomolecular interactions to enter regimes where data and human intuition remain limited.

bioengineering↗

Ubiquitination-mediated mitochondrial protein degradation ensures seedling emergence by regulating ER-mitochondrial interaction and mitophagy

Seedling emergence is a pivotal step of plant survival, requiring rapid hypocotyl elongation for soil penetration. This energy-demanding process necessitates active mitochondrial respiration, which inevitably induces oxidative damage. Therefore, plants evolved a quality control mechanism that selectively removes dysfunctional mitochondria through the mitophagy pathway. Here, we identified SPL2, a mitochondrial E3 ligase which is essential for hypocotyl elongation and seedling emergence through degrading mitochondrial outer membrane proteins, such as TRB1 and FIS1A. Intriguingly, these proteins also interact with an ER protein, VAP27-1, forming a complex at the ER-mitochondria contact sites, which is essential for mitophagy initiation. The spl2 mutant exhibits enhanced ER-mitochondrial tethering and mitophagy activation, whereas its overexpression has the opposite effects. The expression of SPL2 increases after light perception, in agreement with the reduced mitophagy. Collectively, our findings reveal novel mechanistic insights into seedling emergence, which are coordinated through protein ubiquitination, ER-mitochondrial interaction, and mitophagy.

plant biology↗

Miniaturized wireless bioelectronics for electrically driven biohybrid robots

Although biohybrid robots offer the potential for soft, adaptive actuation by harnessing living muscle, practical operation in cell culture environments is often limited by the requirement of immersed leads or cumbersome stimulation equipment. Here, we present a thin, miniaturized, wireless bioelectronic stimulator that can electrically drive biohybrid robots while maintaining stability in aqueous cell culture media. Built on a 50-{micro}m liquid crystal polymer (LCP) substrate, the device integrates a planar receiving coil, interconnects, a diode-based rectifier, and a tank capacitor. This enables the device to convert an approximately 4.9-MHz radio-frequency (RF) input into pulsed direct current (DC), which is delivered through integrated stimulation electrodes. The stimulator has a footprint of [~]23 mm2 and a total thickness and mass of [~]100 {micro}m and [~]7 mg, respectively. We integrated the stimulator with a nanopatterned carbon nanotube (CNT)/gelatin hydrogel fin seeded with human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to generate propulsion through fin flapping. By optimizing the thickness of the polydimethylsiloxane (PDMS) encapsulation layer, the density was tuned, and the robot remained freely floating and retained shape integrity during operation. This produced autonomous forward locomotion of [~]70 {micro}m/s. The stimulator generated distance-dependent output voltage pulses of [~]2-6 V and reliably synchronized fin flapping rates of up to 2 Hz without an observable loss of cell attachment or sarcomeric organization. Together, these results establish a compact, media-compatible, wireless, bioelectronic interface suitable for closed-system biohybrid robotics.

bioengineering↗

A Novel Glycoproteomics Platform for High-Throughput Identification of Disease-Associated Glycoforms

Glycosylation is a critical post-translational modification, and its aberrant forms are potent disease biomarkers; however, the comprehensive, site-specific identification of all glycosites and glycoforms across an entire proteome remains prohibitively slow and computationally demanding. To address this bottleneck and accelerate biomarker discovery, we introduce the Glycoproteomics Data Analysis Software (GDAS), a novel, high-throughput platform designed to provide confident, proteome-scale identification of disease-specific glycoforms. GDAS streamlines the analysis through a core, multi-step workflow: it initially employs an ultrafast open search (e.g., MSFragger-Glyco) on mass spectrometry data to rapidly screen and statistically reduce the vast proteome database to a manageable subset of significantly regulated glycoproteins, conserving computational resources for subsequent, in-depth, targeted N- and O-glycosylation analysis using specialized tools (e.g., GlycReSoft and O-Pair). Furthermore, a unique Final Analysis Module utilizes an advanced statistical and machine learning pipeline (incorporating Bootstrap/Bayesian methods, XGBoost, and Random Forest) to integrate quantitative results and generate a robust, comprehensive glycosylation score. We demonstrate GDASs power to recognize biologically relevant glycosylation changes in targeted proteins by validating it using published Alzheimers disease data. GDAS can be downloaded from https://github.com/yang-lab/GDAS. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=92 SRC="FIGDIR/small/708406v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@189b270org.highwire.dtl.DTLVardef@1221045org.highwire.dtl.DTLVardef@15a3f50org.highwire.dtl.DTLVardef@1f2d43f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Myofibroblast lineage mapping and inhibiting subretinal fibrosis by targeting SMAD3 and MRTF pathways via microRNA-24 functional study

Subretinal fibrosis underlies the end-stage pathogenesis of retinal diseases including age-related macular degeneration (AMD). It can disrupt retinal structure and eventually lead to legal blindness by generating contractile force, fibrotic scarring, subretinal hemorrhage, and retinal detachment. Myofibroblasts are the predominant cells critically involved in subretinal fibrosis, however, the cellular contribution to myofibroblasts remains unclear. Here we demonstrate that multiple cell lineages, including macrophages, endothelial cells (EC), retinal pigment epithelial (RPE) cells and pericytes, significantly contribute to myofibroblasts in a laser-induced subretinal fibrosis model. We found microRNA miR-24 is significantly downregulated in the plasma of wet AMD patients. Overexpression of miR-24 represses epithelial-mesenchymal transition (EMT), endothelial-mesenchymal transition (EndMT), and the resulting fibrosis by regulating TGF-{beta}/SMAD3 and PAK4/LIMK2/MRTF pathways. Consistently, a combination of SMAD3 and MRTF inhibitors show superior efficacy to individual inhibitors in repressing fibrosis in vitro and laser-induced subretinal fibrosis in vivo. Together, these suggest the contribution of multiple cell-types in myofibroblast transformation in subretinal fibrosis, and repression of miR-24-regulated TGF-{beta}/SMAD3 and PAK4/LIMK2/MRTF pathways in multiple cell types holds therapeutic potential for treating subretinal fibrosis in AMD and other fibrotic disorders.

molecular biology↗