Biology subjects

Cardarelli, F.

Publications and source records attributed to Cardarelli, F..

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↗

bioRxiv2026

Autofluorescence intensity patterns encode α/β cell identity in human islets

Understanding the behavior of - and {beta}-cells within intact human islets is essential for elucidating mechanisms of metabolic control in diabetes. Current cell-type identification strategies rely on destructive labeling or on advanced imaging modalities such as Fluorescence Lifetime Imaging Microscopy (FLIM), which provide rich metabolic information but require specialized instrumentation and acquisition protocols. Here we show that structured intracellular intensity patterns derived from endogenous autofluorescence are sufficient to discriminate and {beta} cells in living human islets. Using rotation-invariant Local Ternary Pattern (LTP) descriptors combined with morphological features, we achieve highly accurate classification (AUC = 0.92), improving upon previously reported benchmarks. The resulting framework is lightweight, interpretable, and compatible with standard imaging configurations, enabling accessible and scalable analysis of label-free microscopy data. Interpretability analyses demonstrate that discrimination is driven predominantly by fine-scale intracellular intensity organization rather than global morphology. In the spectral window employed, cytoplasmic autofluorescence is prominently shaped by lipofuscin-rich granules. Consistent with prior reports of higher lipofuscin accumulation in {beta}-cells, the dominant features identified here likely reflect differences in granule abundance and spatial organization between endocrine cell types. These findings indicate that endogenous intensity patterns encode sufficient structural information for reliable /{beta} discrimination, providing a biologically grounded and fully non-destructive framework for the identification of pancreatic islet cell types.

cell biology↗

bioRxiv2025

Nuclear Pore Transport: Toward an Integrated Perspective

Nuclear pore complexes (NPCs) mediate the selective exchange of proteins and RNAs between nucleus and cytoplasm. Despite decades of study, the molecular mechanism of transport remains debated, particularly the role of FG-nucleoporin dynamics in facilitating translocation. Here, we compare high-resolution single-molecule trajectories obtained with MINFLUX microscopy with earlier correlation-based measurements, revealing that actual pore-crossing events are typically completed within 2-4 localization steps, corresponding to 2-6 ms depending on localization rates. These values closely match transit times obtained from fluorescence fluctuation analysis and align with models in which cargo binding induces transient FG-nucleoporin collapse. Together with recent independent observations, this synthesis supports a converging view of NPC transport as a fast, directional, FG-assisted process. We propose that integrating fluctuation-based and trajectory-based approaches provides a robust framework for reconciling mechanistic hypotheses and refining our understanding of selective gating.

biophysics↗

bioRxiv2023

Phasor Identifier: A Cloud-based Analysis of Phasor-FLIM Data on Python Notebooks

This study aims at creating an accessible notebook tool for the versatile analysis of phasor Fluorescence Lifetime Imaging Microscopy (FLIM) data collected from various samples (e.g. cuvette, cells, tissues) and in various input file formats. The presented strategy facilitates morphological segmentations and diverse mask imports. Results derived from three compelling case studies involving cellular metabolism, nanoscale drug encapsulation (doxorubicin), and the impact of pH and metabolic cleavage on small fluorescent drugs (irinotecan), showcase extensive analysis capabilities. The notebook-centered approach accelerates phasor-FLIM data analysis via external servers, supporting multi-scale research and avoiding the need for GPUs, RAM, and disk space.

biophysics↗

bioRxiv2023

Direct optical nanoscopy unveils signatures of cytokine-induced β-cell structural and functional stress

Here we exploit a combination of advanced optical-microscopy tools and fluorescently-labeled molecular targets in rat Insulinoma 1E {beta}-cells exposed to proinflammatory cytokines. Expansion microscopy (ExM) is used to achieve the spatial resolution (~50 nm) needed to analyze the structural features of key subcellular targets, i.e. insulin secretory granules (ISGs), microtubules, actin filaments, and mitochondria; time-lapse live-cell microscopy, on the other hand, provides complementary information on key dynamic and metabolic subcellular parameters. It is found that 24-hours exposure to proinflammatory cytokines induces a neat decrease in the number of ISGs and alteration in the dynamics of the residual pool, marked depolymerization of microtubules, change in mitochondrial morphology and metabolic activity, and decreased cell responsiveness to glucose stimulation. This is accompanied by clear signatures of the production of reactive oxygen species. Reported results provide direct evidence that proinflammatory cytokines act as potent stimulators of insulin secretion and, concomitantly, as cell stressors.

biophysics↗

bioRxiv2022

Metabolic-imaging of human glioblastoma explants: a new precision-medicine model to predict tumor treatment response early

BackgroundGlioblastoma (GB) is the most severe form of brain cancer, with a 12-15 month median survival. Surgical resection, temozolomide (TMZ) treatment, and radiotherapy (RT) remain the primary therapeutic options for GB, and no new therapies have been introduced in recent years. This therapeutic standstill is primarily due to preclinical approaches that do not fully respect the complexity of GB cell biology and fail to test efficiently anti-cancer treatments. Therefore, better treatment screening approaches are needed. In this study, we have developed a novel functional precision medicine approach to test the response to anticancer treatments in organoids derived from the resected tumors of glioblastoma patients. MethodsGB organoids were grown for a short period of time to prevent any genetic and morphological evolution and divergence from the tumor of origin. We chose metabolic imaging by NAD(P)H fluorescence lifetime imaging microscopy (FLIM) to predict early and non-invasively ex-vivo anti-cancer treatment responses of GB organoids. TMZ was used as the benchmark drug to validate the approach. Whole-transcriptome and whole-exome analyses were then performed to characterize tumor cases stratification. ResultsOur functional precision medicine approach was completed within one week after surgery and two groups of TMZ Responder and Non Responder tumors were identified. FLIM-based metabolic tumor stratification was well-reflected at the molecular level, confirming the validity of our approach, highlighting also new target genes associated with TMZ treatment and identifying a new 17 gene molecular signature associated with survival. The number of promoter methylated tumors for the MGMT gene was higher in the responsive group, as expected, however, some non-methylated tumor cases turned out to be nevertheless responsive to TMZ, suggesting that our procedure could be synergistic with the classical MGMT methylation biomarker. ConclusionsFor the first time, FLIM-based metabolic imaging was used on ex-vivo live glioblastoma organoids. Unlike other approaches, ex-vivo patient-tailored drug response is performed at an early stage of tumor culturing with no animal involvement and with minimal tampering with the original tumor cytoarchitecture. This functional precision medicine approach can be exploited in a range of clinical and laboratory settings to improve the clinical management of GB patients and implemented on other cancers as well.

molecular biology↗