Biology subjects

Aydin, O.

Publications and source records attributed to Aydin, O..

8 recordsLinked to original sources

bioRxiv2025

Generating Synthetic MR Perfusion Maps from DWI and FLAIR in Acute Ischemic Stroke using Deep Learning

BackgroundMagnetic resonance imaging (MRI) is critical for acute stroke triage, but time-consuming, and often requires contrast injection for perfusion imaging. This study aimed to synthesize T-map perfusion maps from routinely available, non-contrast DWI and FLAIR using deep generative models. We hypothesized that relevant perfusion information could be inferred from these modalities to streamline imaging and reduce reliance on dynamic susceptibility contrast perfusion. MethodsAcute MRI data from 355 patients with anterior circulation stroke, including dynamic susceptibility contrast perfusion, were retrospectively collected from two European centers (Heidelberg: 2010-2018; Bordeaux: 2021-2022). Six versions of a denoising diffusion probabilistic model (DDPM) and a GAN architecture were trained to generate synthetic T-max perfusion maps from DWI, FLAIR, and infarct core mask as inputs. Performance was assessed by comparing synthetic and ground truth T-max maps using image similarity metrics. Regions with T-max >6s were compared using Dice coefficients, and mismatch volume distributions were analyzed. An ablation study quantified the contribution of each input. ResultsThe best performance was achieved by a DDPM with a 2.5D architecture using DWI, FLAIR, infarct core mask, and a perfusion-weighted loss function. It produced synthetic perfusion T-max maps with high similarity to ground truth under 110 seconds. The model showed strong spatial overlap for T-max >6s regions in internal validation (average Dice = 0.82, SD = 0.08), and external validation average (Dice 0.59, SD = 0.13), respectively. Synthetic maps closely matched ground-truth mismatch distributions, capturing key perfusion patterns. The infarct core mask played a critical role in model performance, alongside DWI and FLAIR inputs. ConclusionsWe propose a non-invasive, scalable framework to generate synthetic T-max perfusion maps from non-contrast MRI. This approach could expand access to perfusion data in acute stroke, shorten imaging protocols, and accelerate treatment decisions by eliminating the need for contrast-enhanced acquisition. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/684079v2_ufig1.gif" ALT="Figure 1"> View larger version (94K): org.highwire.dtl.DTLVardef@164235forg.highwire.dtl.DTLVardef@14e5489org.highwire.dtl.DTLVardef@190214eorg.highwire.dtl.DTLVardef@17a9e3a_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

A fast, muscle-actuated biohybrid swimming robot

The integration of biological actuators with soft scaffolds has led to biohybrid robots including microscale flagellate-like swimmers which generate thrust by waving their flagella-like tails. However, they achieve swimming speeds of only 0.014 body lengths per minute, Reynolds number (Re) [~] 10-3, which is much slower than natural flagellates (O(102 - 103) body lengths per minute). To investigate this, we applied theoretical and experimental methods, including fabrication of a swimmer that converts muscle contractions into large angular tail displacements, reaching swimming speeds of 86.8 m/s (0.58 body lengths per minute), surpassing low-Re predictions. Swimming dynamics sharply transition from a low-Re ([~] 10-3) to an intermediate-Re ([~] 0.1) regime when the actuation angle exceeded 4{degrees}. We used the swimmer to study the ability of muscle to adapt to mechanical stiffness and the beneficial effects of neuromuscular coculture on muscle development. These insights into mechanical and chemical cues will help optimize future biobots. TeaserHow are biological flagellate swimmers like E. coli and sperm cells so fast? We have built a new biohybrid robot to explore the theory.

bioengineering↗

bioRxiv2023

`Mind in Vitro' platforms: Versatile, scalable, robust and open solutions to interfacing with living neurons

Motivated by the unexplored potential of in vitro neural systems for computing, and by the corresponding need of versatile, scalable interfaces for multimodal interaction, we present an accurate, modular, fully customizable and portable recording/stimulation solution that can be easily fabricated, robustly operated, and broadly disseminated. A reconfigurable platform that works across multiple industry standards enables a complete signal chain, from neural substrates sampled through high-density Micro-Electrode Arrays (MEAs) to data acquisition, downstream analysis and cloud storage. Built-in modularity supports the seamless integration of electrical/optical stimulation and fluidic interfaces. Custom MEA fabrication leverages maskless photolithography, favoring the rapid prototyping of a variety of configurations and spatial topologies. Through a native analysis and management software suite, the utility and robustness of our system is demonstrated across neural cultures and applications, including embryonic stem cell-derived and primary neurons, organotypic brain slices, 3D engineered tissue mimics, concurrent calcium imaging and long-term recording. Overall, our technology, termed Mind in Vitro to underscore the computing inspiration, provides an end-to-end solution that can be widely deployed due to its affordable (>10X cost-reduction) and open-source nature, catering to the expanding needs of both conventional and unconventional electrophysiology.

neuroscience↗

bioRxiv2023

Engineering 3D neuronal networks with directional endogenous neuronal plasticity pathways

The forward engineering of the structure and function of three-dimensional millimeter to centimeter scale living Neuronal Tissue Mimics (NTMs) can advance many engineering and biomedical applications. While hydrogels and 3D printing have achieved major breakthroughs in the development of cm-scale neural tissues that mimic structural morphologies in native neural networks, controlling and programming the resulting function of these NTMs have remained elusive. In this work, using human embryonic stem cell derived optogenetic neurons, we report the in-situ formation of the NTMs on a 2-dimensional micro electrode array with an intimate electrical contact between the electrodes and the tissue. These NTMs were optimized during the differentiation phase of the cells to enrich for neuronal populations that expressed receptors responsible for activating spike-timing dependent plasticity (STDP). Using an optical stimulation regiment with millisecond temporal and micrometer spatial resolution, we were able to program the otherwise omnidirectional spontaneous firing in the NTMs to demonstrate directional firing across different shapes of the NTMs. Our work can pave the way for developing cellular based computational devices, bio-processors, and biological memories.

bioengineering↗

bioRxiv2022

Systems analysis of metabolic responses to a mixed meal test in an obese cohort reveals links between tissue metabolism and the gut microbiota

Individuals with prediabetes and type 2 diabetes mellitus (T2DM) have poor ability to adapt to diet-triggered perturbations. We investigated global metabolic responses to a mixed meal test (MMT) in morbidly obese individuals with different diabetic status by performing plasma metabolomic profiling. Abnormal metabolism of carbohydrates, (branched-chain) amino acids, fatty acids and acylcholines in individuals with (pre)diabetes was observed. Moreover, differences in metabolic responses were associated with altered fecal metagenomics and transcriptomes of liver, jejunum and adipose tissues, which revealed a modified gut microbiome and multi-tissue metabolism in individuals having insulin resistance. Finally, using integrative machine learning models, we built a predictive model based on metabolomics data after 2h MMT, and identified possible new biomarkers for glycemic control including N-acetylaspartate and phenylalanine-derived metabolites that may be useful for diagnosis, intervention and prevention of T2DM.

systems biology↗

bioRxiv2021

Empowering Engineered Muscle in Biohybrid Pump by Extending Connexin 43 Duration with Reduced Graphene Oxides

Engineered skeletal muscle act as therapeutics invaluable to treat injured or diseased muscle and a "living" material essential to assemble biological machinery. For normal development, skeletal myoblasts should express connexin 43, one of the gap junction proteins that promote myoblast fusion and myogenesis, during the early differentiation stage. However, myoblasts cultured in vitro often down-regulate connexin 43 before differentiation, limiting myogenesis and muscle contraction. This study demonstrates that tethering myoblasts with reduced graphene oxide (rGO) slows connexin 43 regression during early differentiation and increases myogenic mRNA synthesis. The whole RNA sequencing also confirms that the rGO on cells increases regulator genes for myogenesis, including troponin, while decreasing negative regulator genes. The resulting myotubes generated a three-fold larger contraction force than the rGO-free myotubes. Accordingly, a valveless biohybrid pump assembled with the rGO-tethered muscle increased the fluid velocity and flow rate considerably. The results of this study would provide an important foundation for developing physiologically relevant muscle and powering up biomachines that will be used for various bioscience studies and unexplored applications.

bioengineering↗

bioRxiv2021

Gut-derived bacterial flagellin induces beta-cell inflammation and dysfunction

ObjectiveHyperglycemia and type 2 diabetes (T2D) are caused by failure of pancreatic beta cells. The role of the gut microbiota in T2D has been studied but causal links remain enigmatic. DesignObese individuals with or without T2D were included from two independent Dutch cohorts. Human data was translated in vitro and in vivo by using pancreatic islets from C57BL6/J mice and by injecting flagellin into obese mice. ResultsFlagellin is part of the bacterial locomotor appendage flagellum, present on gut bacteria including Enterobacteriaceae, which we show to be more abundant in the gut of individuals with T2D. Subsequently, flagellin induces a pro-inflammatory response in pancreatic islets mediated by the Toll-like receptor (TLR)-5 expressed on resident islet macrophages. This inflammatory response associated with beta-cell dysfunction, characterized by reduced insulin gene expression, impaired proinsulin processing and stress-induced insulin hypersecretion in vitro and in vivo in mice. ConclusionWe postulate that increased systemically disseminated flagellin in T2D is a contributing factor to beta cell failure in time and represents a novel therapeutic target. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/463317v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@b719aeorg.highwire.dtl.DTLVardef@f72958org.highwire.dtl.DTLVardef@bb7af5org.highwire.dtl.DTLVardef@859c70_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2020

Development of an objective index, neural activity score (NAS), reveals neural network ontogeny and treatment effects on microelectrode arrays

Microelectrode arrays (MEAs) are valuable tools for electrophysiological analysis at a cellular population level, providing assessment of neural network health and development. Analysis can be complex, however, requiring intensive processing of large high-dimensional data sets consisting of many activity parameters. As a result, valuable information is lost, as studies subjectively report relatively few metrics in the interest of simplicity and clarity. From a screening perspective, many groups report simple overall activity; we are more interested in culture health and changes in network connectivity that may not be evident from basic activity parameters. For example, general changes in overall firing rate - the most commonly reported parameter - provide no information on network development or burst character, which could change independently. Our goal was to develop a fast objective process to capture most, if not all, the valuable information gained when using MEAs in neural development and toxicity studies. We implemented principal component analysis (PCA) to reduce the high dimensionality of MEA data. Upon analysis, we found that the first principal component was strongly correlated to time, representing neural culture development; therefore, factor loadings were used to create a single index score - named neural activity score (NAS) - reflective of neural maturation. To validate this score, we applied it to studies analyzing various treatments. In all cases, NAS accurately recapitulated expected results, suggesting this method is viable. This approach may be improved with larger training data sets and can be shared with other researchers using MEAs to analyze complicated treatment effects and multicellular interactions. Author SummaryAnalyzing neural activity has important applications such as basic neuroscience research, understanding neurological diseases, drug development, and toxicity screening. Technology for recording neural activity continues to develop, producing large data sets that provide complex information about neuronal function. One specific technology, microelectrode arrays (MEAs), has recently given researchers the ability to record developing neural networks with potential to provide valuable insight into developmental processes and pathological conditions. However, the complex data generated by these systems can be challenging to analyze objectively and quantitatively, hindering the potential of MEAs, especially for high-throughput approaches, such as drug development and toxicity screening, which require quick, simple, and accurate quantification. Therefore, we have developed an index for simple quantification and evaluation of neural network maturation and the effects of perturbation. We present validation of our approach using several treatments and culture conditions, as well as a meta-analysis of toxicological screening data to compare our approach to current methods. In addition to providing a simple quantification method for neural network activity in various conditions, our method provides potential for improved results interpretation in toxicity screening and drug development.

neuroscience↗