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Yildirim, M.

Publications and source records attributed to Yildirim, M..

16 recordsLinked to original sources

Hemodynamic Signals Reshape Biological Inference in Widefield Calcium Imaging

Widefield calcium imaging is widely used to study cortex-wide neural dynamics, yet fluorescence signals are strongly influenced by hemodynamic fluctuations arising from blood volume and oxygenation changes. Although hemodynamic correction is frequently applied, it remains unclear whether vascular contributions represent a modest preprocessing concern or systematically bias biological interpretations of cortical activity. Here, we used dual-wavelength imaging to determine how hemodynamic correction reshapes inference of cortical dynamics across mouse lines expressing GCaMP6s, GCaMP6f, and jGCaMP8m, across multiple analytical domains, and under healthy and glioblastoma conditions. We systematically compared uncorrected and corrected signals using analyses spanning functional parcellation, connectivity, spectral structure, brain-behavior coupling, and low-dimensional network-state dynamics. Hemodynamic correction consistently reduced global functional connectivity, increased network modularity, redistributed spectral power away from slow-frequency dominance, and reorganized multivariate representations of cortical state space. These findings demonstrate that vascular signals do not behave as unstructured measurement noise but instead introduce organized variance that propagates across analytical pipelines and influences inference of cortical dynamics. The consequences of this bias were particularly relevant in glioblastoma, where tumor-associated vascular remodeling amplifies the mismatch between fluorescence signals and underlying neuronal activity. In this disease setting, correction revealed hemispheric asymmetries, reduced network-state entropy, and constrained trajectories within cortical state space that were obscured in uncorrected recordings, demonstrating that vascular remodeling can fundamentally alter interpretation of tumor-associated brain dynamics. More broadly, vascular signals systematically biased estimates of functional organization, network architecture, brain-behavior relationships, and disease-associated phenotypes. Together, these findings establish hemodynamic correction as a critical determinant of biological interpretation in mesoscale calcium imaging rather than a simple preprocessing refinement.

neuroscience↗

A Deterministically Synchronized Widefield Imaging and Virtual Reality Platform for Multimodal Brain Behavior Recording

ObjectiveSimultaneous recording of brain activity, behaviour, and virtual environments is essential for understanding large-scale neural dynamics during behaviour. However, existing systems often rely on software-based synchronization or post hoc alignment, introducing latency, jitter, and drift that obscure fast brain-behavior interactions. ApproachHere, we present a deterministically synchronized widefield calcium imaging platform that unifies neural imaging, high-speed behavioural monitoring, and closed-loop virtual reality (VR) under a shared hardware-defined clock. This system enables millisecond-precision temporal alignment across modalities, including dual-wavelength hemodynamic correction, pupil and orofacial tracking, locomotion sensing, and VR rendering. Main resultsThe platform achieves stable hardware-level synchronization across neural imaging, behavioural recordings, and VR rendering without reliance on software timestamps. It supports widefield imaging rates up to 100 Hz and integrates seamlessly with both ViRMEn and Blender VR engines, exhibiting a mean locomotion-to-VR update latency of [~]1.5 ms. Multimodal recordings during VR navigation demonstrate robust temporal alignment between cortical activity, facial dynamics, pupil signals, and locomotion. SignificanceThis system provides a deterministic multimodal framework for studying brain-behaviour relationships during active behaviour. By enabling millisecond-precision synchronization across neural imaging, behaviour, and virtual environments, this platform enables causal investigation of brain-behaviour interactions at millisecond precision and provides a foundation for next-generation closed-loop neuroengineering experiments.

neuroscience↗

NeuroPupil: A generalization-first framework for scalable and biologically informative cross-species pupillometry

Quantitative pupillometry provides a noninvasive window into brain state and neurological function, but its broader use across experimental and clinical settings is limited by challenges in achieving accurate, scalable, and generalizable measurements. Here, we present NeuroPupil, a deep learning framework for high-throughput, cross-species pupillometry that emphasizes robust generalization across subjects, behavioral contexts, and imaging conditions. Through systematic benchmarking of training strategies and network architectures, we identify pooled multi-subject training combined with an optimized U-Net architecture as a key determinant of reliable and transferable pupil tracking performance. Across diverse mouse and human datasets, NeuroPupil achieves improved accuracy and substantial gains in computational efficiency compared to existing approaches, enabling practical analysis of large-scale datasets. We further demonstrate that improved pupil tracking fidelity enhances downstream biological inference: NeuroPupil-derived pupil features significantly improve prediction of distributed cortical activity in behaving mice and preserve diagnostically relevant temporal structure in human clinical recordings. These findings highlight the importance of precise and scalable measurement for linking pupil dynamics to brain activity and clinical phenotypes. By integrating benchmarking, scalability, and accessible software tools, NeuroPupil provides a reproducible framework for large-scale pupillometry and facilitates its application in systems and translational neuroscience.

neuroscience↗

Integrated Collagen Architecture and Composition Improve Risk Stratification in Triple-Negative Breast Cancer

PurposeTriple-negative breast cancer (TNBC) exhibits substantial clinical heterogeneity, with some patients experiencing early recurrence and poor survival despite similar clinicopathologic features. We sought to determine whether quantitative measures of intratumoral collagen architecture and composition derived from standard histopathologic specimens can identify patients at risk of recurrence and adverse survival outcomes. Experimental DesignWe analyzed a retrospective cohort of 79 TNBC tumors assembled into a tissue microarray using a multimodal computational pathology framework integrating Massons Trichrome staining with COL1 and COL3 immunohistochemistry. Collagen architecture was quantified using fiber-based image analysis and unsupervised clustering, while collagen composition was assessed using a normalized COL3:COL1 ratio. Associations with recurrence-free interval (RFI) and overall survival (OS) were evaluated using Kaplan-Meier analysis, restricted mean survival time (RMST), and Cox proportional hazards modeling. ResultsUnsupervised analysis identified four distinct collagen architectural states, which were consolidated into low-risk and high-risk groups based on recurrence patterns. High-risk collagen architecture was associated with significantly worse long-term RFI (log-rank p=0.025; RMST difference 10.1 months). Independently, a higher COL3:COL1 ratio was associated with improved OS (log-rank p=0.042; RMST difference 9.4 months). Integration of architectural and compositional biomarkers further refined risk stratification, identifying a subgroup with high-risk architecture and low COL3:COL1 ratio that exhibited the poorest survival outcomes. Notably, collagen-based stratification identified patients with divergent outcomes not readily predicted from tumor stage alone. ConclusionsQuantitative assessment of intratumoral collagen architecture and composition provides clinically meaningful prognostic information in TNBC and enables stratification of recurrence and survival risk. These findings support extracellular matrix phenotyping as a practical and scalable computational pathology approach for refining risk assessment in TNBC. Translational RelevanceTriple-negative breast cancer (TNBC) remains clinically challenging due to heterogeneous outcomes that are not fully captured by standard clinicopathologic variables. In this study, we demonstrate that quantitative features of intratumoral collagen architecture and composition, derived from routine pathology specimens, provide clinically meaningful prognostic information. Collagen-based biomarkers, including distinct collagen architectural phenotypes and the COL3:COL1 ratio, identify patient subgroups with distinct recurrence and survival outcomes, particularly among individuals whose risk is not adequately predicted by conventional staging. Importantly, these features can be extracted from widely available histological stains and immunohistochemistry, supporting the potential integration into existing pathology workflows. These findings support the tumor microenvironment as an underutilized source of biomarkers and suggest that extracellular matrix-based phenotyping may improve risk stratification and inform clinical decision-making in TNBC.

cancer biology↗

DeepFace: A High-Precision and Scalable Deep Learning Pipeline for Predicting Large-Scale Brain Activity from Facial Dynamics in Mice

We present DeepFace, a next-generation facial analysis pipeline that enhances orofacial tracking and cortical activity prediction in mice. Rather than replacing existing tools, DeepFace builds upon DeepLabCut and Facemap to address scalability bottlenecks and improve behavioral quantification. It offers high precision, keypoint customization, and robust performance across GCaMP6s, GCaMP6f, and jGCaMP8m lines. With scalable batch processing and high-performance computing compatibility, DeepFace enables high-throughput brain-behavior analysis in large-scale preclinical neuroscience.

neuroscience↗

Critical-Size Defect Tibialis Anterior (TA) Muscle Regeneration using Ex-Vivo Mice Hindlimbs Culturing under Dynamic Mechanical Loading

In this study, we introduced an innovative computer-controlled ex vivo mice hindlimb culturing platform operating under dynamic loading, coupled with injectable cell-laden nanofibrous matrix (PNCOL), to investigate tissue response and therapeutic outcomes in critical size defect tibialis anterior (TA) muscle regeneration. The combination of mechanical stimulation and cell therapy offers a distinctive opportunity to delve into the regenerative rehabilitation field and create sustainable solutions in musculoskeletal (MSK) tissue regeneration. The application of mechanical loading on the whole mice hindlimbs increased total bone area and marrow area suggesting an increase in periosteal bone formation and resorption on the endosteal surface. Viability assessments confirmed the sustained culturing of the samples throughout the study. Then, the effect of mechanical loading and PNCOL injection on muscle regeneration at the TA defect site was evaluated. Histological analyses revealed enhanced muscle regeneration in PNCOL-treated hindlimbs. Structural analysis of the defect area through scanning electron microscopy (SEM) showed regeneration of ECM fibers at the defect site in PNCOL-treated groups. An analysis of cytokine levels in conditioned media at the end experiment showed changes in the number of proteins with the role in wound healing, muscle regeneration WNT, and IGF-1 signaling suggesting an anabolic effect of mechanical stimulation on muscle and bone. Similarly, gene expression analysis showed a significant upregulation of PAX7, Mrf4, MYF5, and TGF{beta}1 mRNA levels, indicating enhanced muscle regeneration after coupled mechanical loading and PNCOL treatments. Lastly, immunostaining showed an increase in tissue regeneration and anti-inflammatory response (CD206) in PNCOL-treated groups. Overall, the ex vivo hindlimb organ culturing platform- maintained tissue functions under mechanical loading, while PNCOL treatment promoted muscle tissue regeneration and reduced inflammation. These findings demonstrated the potential of multidimensional approaches for enhancing therapeutic outcomes in MSK disorders. In addition, this study aligns with the growing emphasis on minimizing the number of animals used in research and developing a robust sense of responsible animal experimentation through introducing dynamic ex-vivo muscle organ culturing platform.

bioengineering↗

In Vivo Optical Clearing of Mammalian Brain

Established methods for imaging the living mammalian brain have, to date, taken the brains optical properties as fixed; we here demonstrate that it is possible to modify the optical properties of the brain itself to significantly enhance at-depth imaging while preserving native physiology. Using a small amount of any of several biocompatible materials to raise the refractive index of solutions superfusing the brain prior to imaging, we could increase several-fold the signals from the deepest cells normally visible and, under both one-photon and two-photon imaging, visualize cells previously too dim to see. The enhancement was observed for both anatomical and functional fluorescent reporters across a broad range of emission wavelengths. Importantly, visual tuning properties of cortical neurons in awake mice, and electrophysiological properties of neurons assessed ex vivo, were not altered by this procedure.

bioengineering↗

Deconvolution Of Hematopoietic Stem/Progenitor Cell Signaling Predicts Inflammatory Niche Remodeling To Be A Determinant Of Tissue Failure And Outcome In Human AML

Cancer initiation is orchestrated by interplay between tumor-initiating cells and their stromal/immune environment. Here, by adapted scRNAsequencing, we decipher the predicted signaling between tissue-resident hematopoietic stem/progenitor cells (HSPCs) and their neoplastic counterparts with their native niches in the human bone marrow. LEPR+ stromal cells are identified as central regulators of hematopoiesis through predicted interactions with all cells in the marrow. Inflammatory niche remodeling and the resulting deprivation of critical HSPC regulatory factors is predicted to repress distinct high-output HSC subsets in NPM1-mutated AML, with relative resistance of clonal cells. Stromal gene signatures reflective of niche remodeling are associated with reduced relapse rates and favorable outcome after chemotherapy, across all genetic risk categories. Elucidation of the intercellular signaling defining human AML, thus, predicts that inflammatory remodeling of stem cell niches drives tissue repression and clonal selection, but may pose a vulnerability for relapse-initiating cells in the context of chemotherapeutic treatment. statement of significanceTumor-promoting inflammation is considered an enabling characteristic of tumorigenesis, but mechanisms remain incompletely understood. By deciphering the predicted signaling between tissue-resident stem cells and their neoplastic counterparts with their environment, we identify inflammatory remodeling of stromal niches as a determinant of normal tissue repression and clinical outcome in human AML. Key pointsO_LIA comprehensive taxonomy of the predicted interactions between LEPR+ stromal niches, HSPCs and adaptive/innate immune cells in the human NBM. C_LIO_LIInflammation-associated decline of stromal niches in AML represses residual normal hematopoiesis with relative resistance of leukemic cells. C_LIO_LIInflammatory decline of stromal niches is associated with reduced relapse risk and favorable outcome. C_LI

cancer biology↗

Hexokinase 1b is a novel target for non-small-cell lung cancer

Deregulation of glycolysis is common in non-small cell lung cancer (NSCLC). Hexokinase (HK) enzymes catalyze the phosphoryl-group-transfer in glucose metabolism. There are a very few studies that have begun to reveal the connections between glucose metabolism and splicing programs. Unlike HK2 gene, which is expressed as a single transcript, there are several transcripts of the HK1 gene due to alternative splicing. However, the functional differential roles of HK1 isoforms in glucose metabolism and tumor progression are still elusive. Here, we show that primary NSCLC patient tumor cells metabolically differ from the normal lung epithelium where they display predominant expression of one of the HK1 transcripts, hexokinase1b (HK1b). We utilized CRISPR-Cas9 system to selectively target specific HK1b isoform in NSCLC and show that silencing HK1b in NSCLC cells inhibits tumorigenesis through diminishing glycolysis and proliferation. Our findings constitute the first demonstration of the first biochemical distinction between the HK1 splice variants. Finally, HK1b deletion sensitizes NSCLC cells to standard-of-care, cisplatin treatment, and the combination therapy synergistically increases both apoptotic cell death by cisplatin and autophagic cell death by increased formation of LC3-II associated autophagic vesicles and myelinoid bodies. Notably, loss of HK1b leads to cellular DNA damage, further combination with cisplatin therapy showed significantly increased levels of DNA damage. Importantly, we showed that glycolysis and cisplatin resistance can be restored by adding-back HK1b in HK1b knock-out cells. Our findings reveal that targeting HK1b isoform alone or in combination with cisplatin may represent a novel strategy for NSCLC patients.

cancer biology↗

Mixture of Learning Strategies Underlies Rodent Behavior in Dynamic Foraging

In volatile foraging environments, animals need to adapt their learning in accordance with the uncertainty of the environment and knowledge of the hidden structure of the world. In these contexts, previous studies have distinguished between two types of strategies, model-free learning, where reward values are updated locally based on external feedback signals, and inference-based learning, where an internal model of the world is used to make optimal inferences about the current state of the environment. Distinguishing between these strategies during the dynamic foraging behavioral paradigm has been a challenging problem for studies of reward-guided decisions, due to the diversity in behavior of model-free and inference-based agents, as well as the complexities that arise when animals mix between these types of strategies. Here, we developed two solutions that jointly tackle these problems. First, we identified four key behavioral features that together benchmark the switching dynamics of agents in response to a change in reward contingency. We performed computational simulations to systematically measure these features for a large ensemble of model-free and inference-based agents, uncovering an organized structure of behavioral choices where observed behavior can be reliably classified into one of six distinct regimes in the two respective parameter spaces. Second, to address the challenge that arises when animals use multiple strategies within single sessions, we developed a novel state-space method, block Hidden Markov Model (blockHMM), to infer switches in discrete latent states that govern the choice sequences across blocks of trials. Our results revealed a remarkable degree of mixing between different strategies even in expert animals, such that model-free and inference-based learning modes often co-existed within single sessions. Together, these results invite a re-evaluation of the stationarity of behavior during dynamic foraging, provide a comprehensive set of tools to characterize the evolution of learning strategies, and form the basis of understanding neural circuits involved in different modes of behavior within this domain.

neuroscience↗

Label-free three-photon imaging of intact human cerebral organoids: tracking early events in brain development and deficits in Rett Syndrome

Human cerebral organoids are unique in their development of progenitor-rich zones akin to ventricular zones from which neuronal progenitors differentiate and migrate radially. Analyses of cerebral organoids thus far have been performed in sectioned tissue or in superficial layers due to their high scattering properties. Here, we demonstrate label-free three-photon imaging of whole, uncleared intact organoids ([~]2 mm depth) to assess early events of early human brain development. Optimizing a custom-made three-photon microscope to image intact cerebral organoids generated from Rett Syndrome patients, we show defects in the ventricular zone volumetric structure of mutant organoids compared to isogenic control organoids. Long-term imaging live organoids reveals that shorter migration distances and slower migration speeds of mutant radially migrating neurons are associated with more tortuous trajectories. Our label-free imaging system constitutes a particularly useful platform for tracking normal and abnormal development in individual organoids, as well as for screening therapeutic molecules via intact organoid imaging.

neuroscience↗

ORYX-MRSI: A Fully-Automated Open-Source Software for Three-Dimensional Proton Magnetic Resonance Spectroscopic Imaging Data Analysis

Proton magnetic resonance spectroscopic imaging (1H-MRSI) provides noninvasive evaluation of brain metabolism. However, there are some limitations of 1H-MRSI preventing its wider use in the clinics, including the spectral quality issues, partial volume effect and chemical shift artifact. Additionally, it is necessary to create metabolite maps for analyzing spectral data along with other MRI modalities. In this study, a MATLAB-based open-source data analysis software for 3D 1H-MRSI, called Oryx-MRSI, which includes modules for visualization of raw 1H-MRSI data and LCModel outputs, chemical shift correction, tissue fraction calculation, metabolite map production, and registration onto standard MNI152 brain atlas while providing automatic spectral quality control, is presented. Oryx-MRSI implements region of interest analysis at brain parcellations defined on MNI152 brain atlas. All generated metabolite maps are stored in NIfTI format. Oryx-MRSI is publicly available at https://github.com/sevimcengiz/Oryx-MRSI along with six example datasets.

neuroscience↗

SARS-CoV-2 Isolation and Propagation from Turkish COVID-19 patients

The novel coronavirus pneumonia, which was named later as Coronavirus Disease 2019 (COVID-19), is caused by the Severe Acute Respiratory Syndrome Coronavirus 2, namely SARS-CoV-2. It is a positive-strand RNA virus that is the seventh coronavirus known to infect humans. The COVID-19 outbreak presents enormous challenges for global health behind the pandemic outbreak. The first diagnosed patient in Turkey has been reported by the Republic of Turkey Ministry of Health on March 11, 2020. Today, over ninety thousand cases in Turkey, and two million cases around the world have been declared. Due to the urgent need for vaccine and anti-viral drug, isolation of the virus is crucial. Here, we report one of the first isolation and characterization studies of SARS-CoV-2 from nasopharyngeal and oropharyngeal specimens of diagnosed patients in Turkey. This study provides an isolation and replication methodology, and cell culture tropism of the virus that will be available to the research communities. Article SummaryScientists have isolated virus from Turkish COVID-19 patients. The isolation, propagation, and plaque and immune response assays of the virus described here will serve in following drug discovery and vaccine testing.

microbiology↗

Label-free characterization of visual cortical areas in awake mice via three-photon microscopy reveals correlations between functional maps and structural substrates

Our understanding of the relationship between the structure and function of the intact brain is mainly shaped by magnetic resonance imaging. However, high resolution and deep-tissue imaging modalities are required to capture the subcellular relationship between structure and function, particularly in awake conditions. Here, we utilized a custom-made three-photon microscope to perform label-free third-harmonic generation (THG) microscopy as well as laser ablation to calculate effective attenuation lengths (EAL) of primary visual cortex and five adjacent visual cortical areas in awake mice. We identified each visual area precisely by retinotopic mapping via one-photon imaging of the calcium indicator GCaMP6s. EALs measured by depth-resolved THG microscopy in the cortex and white matter showed correspondence with the functional retinotopic sign map of each cortical area. To examine the basis for this correspondence, we used THG microscopy to examine several structural features of each visual area, including their cytoarchitecture, myeloarchitecture and blood vessel architecture. The cytoarchitecture of each area allowed us to estimate EAL values, which were comparable to experimental EAL values. The orientation of blood vessels and myelin fibers in the six areas were correlated with their EAL values. Ablation experiments, which provide ground truth measurements, generated 17 {+/-} 3 % longer EALs compared to those obtained with THG imaging but were consistent with the latter. These results demonstrate a strong correlation between structural substrates of visual cortical areas, represented by EALs, and their functional visual field representation maps.

neuroscience↗

Aneuploidy and deregulated DNA damage response define haploinsufficiency in breast tissues of BRCA2 mutation carriers

Women harboring heterozygous germline mutations of BRCA2 have a 50-80% risk of developing breast cancer, yet the early pathogenesis of these cancers is poorly understood. We sought to reveal early steps in BRCA2-associated carcinogenesis through analysis of sorted cell populations from freshly-isolated, non-cancerous breast tissues among a cohort of BRCA2 mutation carriers and matched controls. Single-cell whole-genome sequencing demonstrates that >25% of BRCA2 carrier (BRCA2mut/+) luminal progenitor (LP) cells exhibit sub-chromosomal copy number variations (CNVs), which are rarely observed in non-carriers. Correspondingly, primary BRCA2mut/+ breast epithelia exhibit spontaneous and replication stress-induced DNA damage together with attenuated replication checkpoint and apoptotic responses, associated with an age-associated expansion of the LP compartment in human carrier tissues. These phenotypes are not associated with loss of wild-type BRCA2. Collectively, these findings provide evidence for BRCA2 haploinsufficiency and associated DNA damage in vivo that precede histologic abnormalities. These results provide unanticipated opportunities for new cancer risk assessment and prevention strategies in high-risk patients.

cancer biology↗

Reliable sensory processing in mouse visual cortex through inhibitory interactions between Somatostatin and Parvalbumin interneurons

Cortical neurons often respond to identical sensory stimuli with large variability. However, under certain conditions, the same neurons can also respond highly reliably. The circuit mechanisms that contribute to this modulation, and their influence on behavior remains unknown. Here we used novel double transgenic mice, dual-wavelength calcium imaging and temporally selective optical perturbation to identify an inhibitory neural circuit in visual cortex that can modulate the reliability of pyramidal neurons to naturalistic visual stimuli. Our results, supported by computational models, suggest that somatostatin interneurons (SST-INs) increase pyramidal neuron reliability by suppressing parvalbumin interneurons (PV-INs) via the inhibitory SST[->]PV circuit. Using a novel movie classification task, we further show that, by reducing variability, activating SST-INs can improve the ability of mice to discriminate between ambiguous stimuli. Together, these findings reveal a novel role of the SST[->]PV circuit in modulating the fidelity of neural coding critical for visual perception.

neuroscience↗