Biology subjects

Mahmoodi, M.

Publications and source records attributed to Mahmoodi, M..

4 recordsLinked to original sources

bioRxiv2025

Extracellular Vesicles of Salivary Mesenchymal Stem Cells Mitigate Acute Irradiation Injury: Use of an ex-vivo organotypic human slice tissue culture as a disease model

AbstractIonizing radiation (IR) therapy for cancer patients can damage surrounding healthy tissues, particularly the salivary glands (SGs), leading to oral and systemic health issues reducing the quality of life of the patients. The mechanisms behind IR damage in SGs are not fully understood, and current therapies often fail to meet patient needs adequately. Therefore, identifying targeted pathways and alternative treatments is essential. To address this, we developed an ex vivo model of SG damage using human salivary glands obtained from patients. Healthy submandibular glands were harvested, cultured, and exposed to IR. RNA sequencing revealed elevated markers for DNA damage, inflammation, and ferroptosis, with four specific genes--FDXR, MDM2, H2AX, and p21--showing increases in expression that correlated with the IR dose. Using them, we developed a high-throughput genetic screening method to evaluate stem cell therapies aimed at mitigating IR injury. Conditioned media from mesenchymal stem/stromal cells (MSC-CM) were found to reduce the expression of all four markers, maintain tissue viability, promote cell proliferation, and decrease oxidative stress. Further analysis involved separating MSC-CM into two fractions: Extracellular Vesicles (EV)-rich and EV-depleted. The EV-depleted fractions retained elevated levels of DNA damage response markers, indicating that EVs play a crucial role in mediating tissue repair. In contrast, the EV-rich fractions reduced the markers of DNA damage response and were readily absorbed by the tissue slices. In conclusion, we have developed a genetic screening method to evaluate treatments for acute IR injury, emphasizing the significant role that EVs play in the repair process.

molecular biology↗

bioRxiv2025

Simultaneous particle tracking, phase retrieval and point spread function reconstruction

3D tracking and localization of particles, typically fluorescently labeled biomolecules, provides a direct means of monitoring cellular transport and communication. However, sample-induced wavefront distortions of emitted fluorescent light as it passes through the sample and onto the detector often yield point spread function (PSF) aberrations, presenting an important challenge to 3D particle tracking using pre-calibrated PSFs. PSF calibration is typically performed outside cellular samples, ignoring sample-induced aberrations, which can result in localization errors on the order of tens to hundreds of nanometers, ultimately compromising sub-diffraction limited tracking. In practice, correcting sample-induced aberrations currently requires sample-specific hardware adjustments, such as adaptive optics. Yet, information on sample-induced aberrations and PSF shape can be directly decoded from data collected using a 3D imaging setup (e.g., bi-focal). To this end, we propose a framework for simultaneous particle tracking, phase retrieval, and PSF reconstruction (SPT-PR) directly from the input data themselves. We apply it to sub-diffraction tracking of lytic granules released at the immunological synapse of T cells revealing slower motions in proximity of the plasma cell membrane, consistent with assembly of the fusion machinery and, ultimately, degranulation and release of toxic payloads. To accomplish this, we operate within a Bayesian paradigm, placing continuous priors on all possible pupil phase and amplitudes warranted by the data without limiting ourselves to a finite Zernike set-thereby allowing capture of intricate pupil phase details. We benchmark our framework using a wide range of synthetic and experimental data from static to diffusing particles, and generalize to multiple diffusing particles with overlapping PSFs. Further, as a result of simultaneous particle tracking, phase retrieval, and PSF reconstruction, we retrieve the pupil phase with errors smaller than 10% under a range of realistic scenarios while demonstrating that for tracking lytic granules under an idealized Gaussian PSF assumption, we recover discrepancies as large as hundreds of nanometers.

biophysics↗

bioRxiv2025

SPTnet: a deep learning framework for end-to-end single-particle tracking and motion dynamics analysis

Single-particle tracking (SPT) provides high-resolution spatial-temporal information on biomolecule dynamics. However, localization inaccuracies, limited track lengths, heterogeneous fluorescence backgrounds, and potential molecular motion blur pose significant challenges that hinder the accurate extraction of movement trajectories and their underlying motion behavior. The conventional SPT pipeline struggles to comprehensively address detection, localization, linkage, and motion parameter inference simultaneously, resulting in information loss during sequential processing. To overcome these challenges, we propose SPTnet, an end-to-end deep learning framework that leverages a Transformer-based architecture to optimize trajectory and motion parameter estimations in parallel through a global loss. SPTnet bypasses traditional SPT processes, directly inferring molecular trajectories and motion parameters from fluorescence microscopy videos with a precision approaching the statistical information limit. Our results demonstrate that SPTnet outperforms conventional methods under commonly encountered but challenging conditions such as short trajectories, low signal-to-noise ratio (SNR), heterogeneous backgrounds, motion blur, and especially when molecules exhibit non-Brownian behaviors.

biophysics↗

bioRxiv2024

Circulating plasma fibronectin affects normal adipose tissue insulin sensitivity and adipocyte differentiation

Plasma fibronectin (pFN), a liver-derived, circulating protein, has been shown to affect adipocyte morphology, adipogenesis, and insulin signalling in preadipocytes in vitro. In this study, we show via injections of fluorescence-labelled pFN to mice in vivo its abundant accrual visceral and subcutaneous adipose tissues (VAT and SAT). Diet-induced obesity model of liver-specific conditional Fn1 knockout (pFN KO), showed no altered weight gain or differences, whole-body fat mass or SAT or VAT volumes after 20- week HFD-feeding, however, mice showed significantly improved glucose clearance and whole-body insulin sensitivity on normal diet. Furthermore, in vivo insulin sensitivity assay revealed significant increase in AKT phosphorylation in pFN KO SAT on normal diet as well as in normal and obese VAT of the pFN KO. Histological assessment of the pFN KO depots showed significant increase in small adipocytes on normal diet, which was particularly prominent in SAT. RNA sequencing of the normal diet-fed pFN versus control SAT revealed alterations in fatty acid metabolism and thermogenesis suggesting presence of beige adipocytes. VAT RNA sequencing after HFD showed alternations in genes reflecting stem cell populations. Our data suggests that the absence of pFN alters cell pools in AT favoring cells with increased insulin sensitivity.

cell biology↗