Biology subjects

De Luca, C.

Publications and source records attributed to De Luca, C..

6 recordsLinked to original sources

bioRxiv2026

Expansion microscopy reveals insulin granule clustering in human β-cells in type 2 diabetes

Aims/hypothesisQuantitative nanoscale analysis of insulin secretory granules (ISGs) in human pancreatic tissue has been limited by the lack of imaging methods that combine high resolution with large-scale sampling. We aimed to establish expansion microscopy (ExM) as a platform for in situ, quantitative analysis of ISG organisation in human {beta}-cells and to assess whether type 2 diabetes (T2D) is associated with alterations in granule size, abundance or spatial organisation. MethodsWe applied Magnify ExM to PFA-fixed, paraffin-embedded pancreatic tissue sections from 6 human donors, 3 non-diabetic (ND) and 3 T2D, enabling super-resolution optical imaging of insulin-labelled granules. Insulin-positive structures were segmented and analysed using a morphometric pipeline to quantitatively assess size, shape and spatial features. Granule clustering was quantified based on combined area and roundness criteria. ResultsThe diameter distribution of highly circular granules was similar between ND and T2D samples and estimates of granule number per cell indicated only a modest reduction in T2D ([~]25%). In contrast, mapping insulin-positive structures in a roundness-area space revealed a marked enrichment of large, irregular objects consistent with granule clustering in T2D. The fraction of clustered granules was significantly increased in T2D and strongly inversely correlated with insulin stimulation index (r = -0.85). Conclusions/interpretationThese results establish expansion microscopy as a powerful platform for quantitative nanoscale analysis of human pancreatic tissue and identify altered spatial organisation of insulin granules, rather than marked granule depletion, as a prominent feature associated with {beta}-cell dysfunction in T2D. Research in contextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LI{beta}-cell dysfunction in type 2 diabetes is often attributed to reduced insulin content or {beta}-cell loss. C_LIO_LIInsulin secretory granules (ISGs) have been characterised ultrastructurally, but quantitative analysis in human tissue remains limited. C_LIO_LISuper-resolution approaches, including expansion microscopy, are emerging tools for nanoscale imaging in biological tissues. C_LI What is the key question?O_LIIs {beta}-cell dysfunction in type 2 diabetes associated with depletion of insulin granules or with altered spatial organisation? C_LI What are the new findings?O_LIInsulin granule size distribution is largely preserved in type 2 diabetes, with only a modest reduction in granule number per cell. C_LIO_LIA significant increase in insulin granule clustering is observed in diabetic {beta}-cells. C_LIO_LIGranule clustering is strongly inversely correlated with insulin secretion in the same donor tissues. C_LI How might this impact on clinical practice in the foreseeable future?O_LIIdentifying altered granule organisation as a feature of {beta}-cell dysfunction may help refine the understanding of disease mechanisms and guide future strategies targeting {beta}-cell function. C_LI

biophysics↗

bioRxiv2025

Mapping glioblastoma spreading: connexin43 and glial dynamic in mouse and human glioblastoma microenvironment

High-grade gliomas (HGGs), including astrocytoma and glioblastoma (GBM), constitute the most prevalent primary tumors of the central nervous system (CNS). GBM cells demonstrate a notable ability to infiltrate the brain parenchyma, precluding complete surgical resection. Here we investigated the spreading of GBM cells and the response of the CNS microenvironment focusing on glial cells, which are essential interactors to GBM. We used acute and organotypic slices from the mouse brain and peritumoral cortex of patients with HGGs. We found that human peritumoral tissue from cortical resection was characterized by high levels of the astrocytic Connexin43 protein (Cx43) and discrete infiltration of microglia. In contrast, the tumor core exhibited high myeloid infiltration and an altered extracellular matrix (ECM) composition, which was poor in CD44. We tracked mouse and primary human-labeled-GBM cells in 2D cultures and in co-culture with organotypic slices generated from mouse brain and human peritumoral tissues. We found that the implanted GBM cells infiltrated the brain tissue, implying early glial modifications including an increase in Cx43 expression and distribution. Furthermore, the blockage of Cx43 hemichannels was accompanied by morphological changes and polarization of human GBM cells, typical for migration phenomena. The present study sheds light on the dynamics of GBM cells spreading in the living brain tissue, suggesting that the progression of the tumor correlates with changes within the host brain. Our findings identify the upregulation of Cx43 expression as a highly consistent modification in both mouse and human tissue that may be crucial for GBM infiltration.

neuroscience↗

bioRxiv2025

A canonical cortical electronic circuit for neuromorphic intelligence

Cortical microcircuits play a fundamental role in natural intelligence. While they inspired a wide range neural computation models and artificial intelligence algorithms, few attempts have been made to directly emulate them with an electronic computational substrate that uses the same physics of computation. Here we present a heterogeneous canonical microcircuit architecture compatible with analog neuromorphic electronic circuits that faithfully reproduce the properties of real synapses and neurons. The architecture comprises populations of interacting excitatory and inhibitory neurons, disinhibition pathways, and spike-driven multi-compartment dendritic learning mechanisms. By co-designing the computational model with its neuromorphic hardware implementation, we developed a neural processing system that can perform complex signal processing functions, learning, and classification tasks robustly and reliably, despite the inherent variability of the analog circuits, using ultra-low power energy consumption features comparable to those of their biological counterparts. We demonstrate how both the model architecture and its hardware implementation seamlessly capture the hallmarks of neural computation: attractor dynamics, adaptation, winner-take-all behavior, and resilience to variability, within a compact, low-power computing substrate. We validate the models learning performance both from the algorithmic perspective and with detailed electronic circuit simulation experiments and characterize its robustness to noise. Our results illustrate how local, biologically plausible rules for plasticity and gating can overcome challenges like catastrophic forgetting and parameter variability, enabling effective always-on adaptation. Beyond offering insights into the nature of computation in neural systems, our approach introduces a foundation for ultra-low power, fault-tolerant architectures capable of complex signal processing at the edge. By embracing -rather than mitigating-variability, these neuromorphic circuits exhibit a powerful synergy with emerging memory technologies, suggesting a new paradigm for sophisticated "in-memory" computing. Through such tight integration of neuroscience principles and analog circuit design, we pave the way toward a class of brain-inspired processors that can learn continuously and respond dynamically to real-world inputs.

neuroscience↗

bioRxiv2023

Establishment of beta cell heterogeneity via differential CpG methylation at Nnat

Aims/hypothesisBeta cells within the pancreatic islet represent a heterogenous population wherein individual sub-groups of cells make distinct contributions to the overall control of insulin secretion. These include a subpopulation of highly-connected hub cells, important for the propagation of intercellular Ca2+ waves. Functional subpopulations have also been demonstrated in human beta cells, with an altered subtype distribution apparent in type 2 diabetes. At present, the molecular mechanisms through which beta cell hierarchy is established are poorly understood. Changes at the level of the epigenome provide one such possibility which we explore here by focussing on the imprinted gene neuronatin (Nnat), which is required for normal insulin synthesis and secretion. MethodsSingle cell RNA-seq datasets were examined using Seurat 4.0 and ClusterProfiler running under R. Transgenic mice expressing eGFP under the control of the Nnat enhancer/promoter regions were generated for fluorescence-activated cell (FAC) sorting of beta cells and downstream analysis of CpG methylation by bisulphite and RNA sequencing, respectively. Animals deleted for the de novo methyltransferase, DNMT3A from the pancreatic progenitor stage were used to explore control of promoter methylation. Proteomics was performed using affinity purification mass spectrometry and Ca2+ dynamics explored by rapid confocal imaging of Cal-520 and Cal-590. Insulin secretion was measured using Homogeneous Time Resolved Fluorescence Imaging. ResultsNnat mRNA was differentially expressed in a discrete beta cell population in a developmental stage- and DNA methylation (DNMT3A)-dependent manner. Thus, pseudo-time analysis of embryonic data sets demonstrated the early establishment of Nnat-positive and negative subpopulations during embryogenesis. NNAT expression is also restricted to a subset of beta cells across the human islet that is maintained throughout adult life. NNAT+ beta cells also displayed a discrete transcriptome at adult stages, representing a sub-population specialised for insulin production, reminiscent of recently-described "{beta}HI" cells and were diminished in db/db mice. Hub cells were less abundant in the NNAT+ population, consistent with epigenetic control of this functional specialization. Conclusions/interpretationThese findings demonstrate that differential DNA methylation at Nnat represents a novel means through which beta cell heterogeneity is established during development. We therefore hypothesise that changes in methylation at this locus may thus contribute to a loss of beta cell hierarchy and connectivity, potentially contributing to defective insulin secretion in some forms of diabetes. Research in contextWhat is already known about this subject? - Neuronatin (Nnat/NNAT) is an imprinted gene in humans and mice and is required for glucose-stimulated insulin secretion in vivo - Pancreatic beta cells are functionally heterogeneous with specific highly-connected subpopulations known to coordinate islet wide Ca2+ dynamics - Functional subpopulations have been described in human beta cells and their distribution is altered in type 2 diabetes What is the key question? - Does NNAT mark a discrete subpopulation of functional beta cells and which epigenetic pathways coordinate its formation and maintenance? What are the new findings? - A subpopulation of NNAT+ beta cells is established prior to the first week of postnatal life in mice via de novo DNA methylation at the Nnat promoter - NNAT+ beta cells are transcriptionally highly differentiated and appear to be functionally specialised for insulin production, possibly corresponding to recently-described "{beta}HI" and "CD63hi" beta cells. NNAT is expressed in a subset of beta cells across the human islet, and its deficiency in human beta cells diminishes glucose-stimulated insulin secretion - NNAT+ cells are likelier to belong to the population of follower, rather than hub cells, consistent with a role in insulin production rather than glucose detection How might this impact on clinical practice in the foreseeable future? - Epigenome-modifying compounds may provide a way of enhancing beta cell function and the ensemble behaviour of the islet to stimulate insulin secretion

cell biology↗

bioRxiv2023

Ribonucleoprotein condensation driven by retrotransposon LINE-1 sustains RNA integrity and translation in mouse spermatocytes

Transposable elements (TE) are mobile DNA sequences whose excessive proliferation endangers the host. Although animals have evolved robust TE-targeting defenses, including Piwi-interacting (pi)RNAs, retrotransposon LINE-1 (L1) still thrives in humans and mice. To gain insights into L1 endurance, we characterized L1 Bodies (LBs) and ORF1p complexes in germ cells of piRNA-deficient Maelstrom null mice. We report that ORF1p interacts with TE RNAs, genic mRNAs, and stress granule proteins, consistent with earlier studies. We also show that ORF1p associates with the CCR4-NOT deadenylation complex and PRKRA, a Protein Kinase R factor. Despite ORF1p interactions with these negative regulators of RNA expression, the stability and translation of LB-localized mRNAs remain unchanged. To scrutinize these findings, we studied the effects of PRKRA on L1 in cultured cells and showed that it elevates ORF1p levels and L1 retrotransposition. These results suggest that ORF1p-driven condensates promote L1 propagation, without affecting the metabolism of endogenous RNAs.

molecular biology↗

bioRxiv2022

Nanoscale prognosis of colorectal cancer metastasis from AFM image processing of histological sections

Early ascertainment of metastatic tumour phases is crucial to improve cancer survival, formulate an accurate prognostic report of disease advancement and, most important, quantify the metastatic progression and malignancy state of primary cancer cells with a universal numerical indexing system. This work proposes an early improvement of cancer detection with 97 nm spatial resolution by indexing the metastatic cancer phases from the analysis of atomic force microscopy images of human colorectal cancer histological sections. The procedure applies variograms of residuals of Gaussian filtering and theta statistics of colorectal cancer tissue image settings. The methodology elucidates the early metastatic progression at the nanoscale level by setting metastatic indexes and critical thresholds from relatively large histological sections and categorising the malignancy state of a few suspicious cells not identified with optical image analysis. In addition, we sought to detect early tiny morphological differentiations indicating potential cell transition from epithelial cell phenotypes of low to high metastatic potential. The metastatic differentiation, also identified by higher moments of variograms, sets different hierarchical levels for the metastatic progression dynamic, potentially impacting therapeutic cancer protocols.

cancer biology↗