Biology subjects

Safari, N.

Publications and source records attributed to Safari, N..

5 recordsLinked to original sources

bioRxiv2025

Brain morphology network alterations in adolescents with autism spectrum disorder: a sex-stratified study

Neuroimaging studies based on altered functional and structural networks have contributed to better characterizing males and females with Autism Spectrum Disorder (ASD), advancing our understanding of the male prevalence in diagnosis. However, much less is known about how brain networks are altered from a morphological perspective, and whether these alterations may help explain sex-related characteristics in ASD. Here, we used structural MRI from a sex- and diagnosis-balanced sample of 337 individuals in typical neurodevelopmental ages (8-18 years) from the Autism Center of Excellence to elucidate sex-specific alterations in morphology-based connectivity, calculated as the similarity between region-wise multivariate morphological signatures. Network-based statistics showed that ASD males had significantly increased connectivity involving the fusiform gyrus, medial orbitofrontal, entorhinal, and parahippocampal cortices. This network profile was further linked to a core social-communication trait within the autistic group. In females with ASD, increased connectivity was found in a subnetwork primarily implicating the entorhinal cortex, followed by the inferior parietal lobule and lateral occipital cortex. In contrast to males, females fusiform gyrus showed decreased connectivity with the superior temporal sulcus. No overlap between male- and female-specific profiles was found. Together, these findings offer new insights into the neurobiology underlying sex differences in autism.

neuroscience↗

bioRxiv2025

Controlling the Formation of Multiple Condensates in the Synapse

The postsynaptic density (PSD) is a molecule rich structure that continuously adapts its organization controlling synaptic physiology and transmission. Experimental studies have shown that this organization is dominated by the formation of condensates or (nano)clusters and by the seamless transition in their numbers as response to synaptic plasticity. In this study, we utilize different computational modeling frameworks to show that variations in the level of local protein concentrations together with the modulation of protein binding strengths can be key molecular factors in controlling the formation and number of clusters in the synapse. Comparison to MINFLUX data of spatial localization of PSD95 in the postsynapse under different activity conditions allowed us to derive predictions about the correlation between these two factors across a population of synapses. Co-variations of the factors, to mimic a simple LTP protocol, shows that a PSD containing a single cluster can reorganize to form multiple clusters that persists for long periods of time, providing a potential explanation of recent experimental data of PSD reorganization.

molecular biology↗

bioRxiv2024

PyRID: A Brownian dynamics simulator for reacting and interacting particles written in Python

Recent technological developments in molecular biology led to large data sets providing new insights into the molecular organisation of cells. To fully exploit their potential, these developments have to be complemented by computer simulations that allow to gain in-depth understanding on molecular principles. We developed the Python-based, reaction-diffusion simulator PyRID, integrating many features for the efficient simulation of molecular biological systems. Amongst others, PyRID is capable of simulating unimolecular and bimolecular reactions as well as pair-interactions to assess the dynamics resulting from individual interacting proteins to polydisperse substrates consisting of many different molecules. Furthermore, PyRID supports mesh-based compartments and surface diffusion of particles, enabling analyses of the interaction between (trans-)membrane proteins with intra- and extracellular proteins. PyRID is written entirely in Python, which is a programming language being known for its readability and easy accessibility, such that the scientific community can easily extend PyRID to its current and future needs.

neuroscience↗

bioRxiv2023

Plant infection by the necrotrophic fungus Botrytis requires actin-dependent generation of high invasive turgor pressure

The devastating pathogen Botrytis cinerea infects a broad spectrum of host plants, causing great socio-economic losses. The necrotrophic fungus rapidly kills plant cells, nourishing their walls and cellular contents. To this end, necrotrophs secretes a cocktail of cell wall degrading enzymes, phytotoxic proteins and metabolites. Additionally, many fungi produce specialized invasion organs that generate high invasive pressures to force their way into the plant cell. However, for most necrotrophs, including Botrytis, the biomechanics of penetration and its contribution to virulence are poorly understood. Here we use a combination of quantitative micromechanical imaging and CRISPR-Cas guided mutagenesis to show that Botrytis uses substantial invasive pressure, in combination with strong surface adherence, for penetration. We found that the fungus establishes a unique mechanical geometry of penetration that develops over time during penetration events, and which is actin cytoskeleton dependent. Furthermore, interference of force generation by blocking actin polymerization was found to decrease Botrytis virulence, indicating that also for necrotrophs, mechanical pressure is important in host colonization. Our results demonstrate for the first time mechanistically how a necrotrophic fungus such as Botrytis employs this "brute force" approach, in addition to the secretion of lytic proteins and phytotoxic metabolites, to overcome plant host resistance.

biophysics↗

bioRxiv2023

Impact of the Excitatory-Inhibitory Neurons Ratio on Scale-Free Dynamics in a Leaky Integrate-and-Fire Model

The relationship between ratios of excitatory to inhibitory neurons and the brains dynamic range of cortical activity is crucial. However, its full understanding within the context of cortical scale-free dynamics remains an ongoing investigation. To provide insightful observations that can improve the current understanding of this impact, and based on studies indicating that a fully excitatory neural network can induce critical behavior under the influence of noise, it is essential to investigate the effects of varying inhibition within this network. Here, the impact of varying ratios on neural avalanches and phase transition diagrams, considering a range of control parameters in a leaky integrate-and-fire model network, is examined. Our computational results show that the network exhibits critical, sub-critical, and super-critical behavior across different control parameters. In particular, a certain ratio leads to a significantly extended dynamic range compared to others and increases the probability of the system being in the critical regime. To address differences between various ratios, we utilized the Kuramoto order parameter and conducted a finite-size scaling analysis to determine the critical exponents associated with phase transitions. In order to characterize the criticality, we examined the distribution of neuronal avalanches at the critical point and the scaling behavior characterized by specific exponents.

neuroscience↗