PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Article Predicting Respiratory Infection and Symptoms Development Using Gene Set Enrichment Scores and Machine Learning(Elsevier Sci Ltd, 2026) Aydin, Zafer; Isik, Yunus EmreRecent advancements in precision medicine enable personalized predictions grounded in individual-level genetic data. However, relying solely on a single type of data can decrease prediction accuracy and limit the biological interpretability of the resulting models. Incorporating predefined genetic knowledge, such as derived gene sets, can improve performance and provide deeper biological insights for complex diseases, including respiratory infections. This study aimed to evaluate the usability of enrichment scores (ES), calculated using gene sets from the Molecular Signatures Database (MSigDB), as a feature representation for machine learning models to predict respiratory viral infections and symptom development. In addition, the proposed feature representation approach was extensively compared with the de facto gene-level expression representation. A total of 36,834 predefined gene sets were compiled from the MSigDB, and their ES values were calculated. Experiments used the GSE73072 dataset from Gene Expression Omnibus, containing gene expression profiles before and after virus exposure. Various machine learning and feature selection algorithms were applied to ES-based and probe-level feature sets. The results showed that both feature representation approaches achieved an area under the precision-recall curve (AUPRC) value greater than 0.90 for all tasks. Compared with the Respiratory Viral DREAM Challenge leaderboard phase, our models showed a 14.8% improvement in pre-exposure predictions (T0) and a 17.4% improvement in symptom classification. Using enrichment scores as a feature representation generally resulted in better performance than probe-level representation when predicting respiratory infections and symptom development. Identifying key gene sets through feature selection and comparing them with essential genes for respiratory viruses enabled a more comprehensive analysis, providing deeper insights into the pathways that contribute to these predictions.Article Dissecting the Strain and Sex Specific Connectome Signatures of Unanesthetized C57BL/6J and DBA/2J Mice Using Magnetic Resonance Imaging(Wiley, 2026) Neuberger, Thomas; Kamens, Helen M.; Zhang, Nanyin; Ünsal, Hayreddin Said; Arefin, Tanzil M.Mouse models are an essential tool for understanding behavior and disease states in neuroscience research. While genetic and sex-specific effects have been reported in many neurodegenerative and psychiatric illnesses, these factors may also alter baseline neuroanatomical features of mice. This raises the question of whether the observed changes are related to the disease being studied (i.e., pathological differences) or if there are baseline strain or sex differences that may predispose animals to different responses. Over the past decade, tremendous effort has been made to map neural architecture at various scales; however, the complex relationships, including identifying genetic and sex-specific differences in brain structure and function, remain understudied. To bridge this gap, we used C57BL/6J and DBA/2J mice, two of the most widely used inbred mouse strains in neuroscience research, to investigate strain and sex-specific features of the brain connectome in awake animals using magnetic resonance imaging (MRI). By combining resting-state functional MRI and diffusion MRI, we found that the motor, sensory, limbic, and salience networks exhibit significant differences in both functional and structural domains between C57BL/6J and DBA/2J mice. Further, functional and structural properties of the brain were significantly correlated in both strains. Our results underscore the importance of considering these baseline differences when interpreting brain-behavior interactions in mouse models of human disorders.Article Comparison of Rapamycin and 3-Methyladenine in Cisplatin-Induced Experimental Cardiotoxicity(Wiley, 2026) Kaymak, Emin; Karabulut, Derya; Yalcin, Betul; Guner, Serife Ayaz; Ozturk, Emel; Findik, Fatma; Boyvat, DuduIn this study, we evaluated how cisplatin cardiotoxicity affects the histological and endocrine functions of the heart and autophagy while using Rapamycin(Rapa) and 3-methyladenine(3-MA) as autophagy activators and inhibitors. Control, Cisplatin (Cis), 3-methyladenine + Cisplatin (3-MA + Cis) and Rapamycin + Cisplatin (Rapa + Cis). Rapa and 3-MA were administered for 15 days, while a single dose of cisplatin was administered on the 7th day. Natriuretic peptide receptor-A(NPR-A), receptor-B(NPR-B) and biochemically atrial natriuretic peptide(ANP) and brain natriuretic peptide(BNP) levels were evaluated in heart tissue. Cis caused a statistically significant increase in NPR-A and NPR-B expression, as well as ANP and BNP levels. However, the levels of Beclin-1 and LC3B were not statistically significant. Rapa was more effective than 3-MA + Cis on NPR-A and NPR-B expressions, but did not show the same effect on ANP and NT-proBNP levels. Cis caused an increase in Beclin-1 and LC3B levels, while a decrease was observed in both 3-MA + Cis and Rapa + Cis groups. Our results revealed that Cis cardiotoxicity disrupts autophagy and endocrine function of the heart. It was concluded that by continuing the activator and inhibitor substances after Cis application, more effective results can be obtained in Beclin-1 expression than LC3B expression and that they can be effective in eliminating the toxicity of Cis.Article Citation - WoS: 5Citation - Scopus: 5Targeting Cholinergic Dysfunction and Neuroinflammation through Rationally Designed Thieno[3,2-d]Pyrimidine Hybrids(Academic Press Inc Elsevier Science, 2026-07) Acar, Ozden Ozgun; Acar, Busra; Senol, Halil; Tokali, Feyzi Sinan; Sen, Alaattin; Demir, Yeliz; Cakir, FurkanNeurodegenerative diseases involve the convergence of cholinergic dysfunction, neuronal loss, and sustained neuroinflammatory responses, necessitating the development of multifunctional therapeutic agents. In this study, a series of novel thieno[3,2-d]pyrimidine-phenolic Mannich base hybrids were rationally designed, synthesized, and evaluated as dual cholinesterase inhibitors with neuroprotective and anti-neuroinflammatory potential. The synthesized compounds exhibited potent inhibition against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), with inhibition constants in the low nanomolar range. Among them, compounds 5 and 9 emerged as the most active derivatives, displaying Ki values of 8.79 and 14.11 nM for AChE and 7.04 and 11.75 nM for BChE, surpassing the reference inhibitors tacrine and donepezil. Molecular docking and molecular dynamics simulations supported the experimental findings, and Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) binding free energy calculations further confirmed their superior binding affinities compared with donepezil. Cytotoxicity profiling in SH-SY5Y neuronal cells and RAW 264.7 and THP-1 immune cells identified a narrow sub-cytotoxic concentration window (EC05-EC10 = 1.2-2.1 mu M), ensuring biological effects independent of nonspecific cell damage. Within this range, both compounds exerted pronounced antineuroinflammatory activity. Notably, compound 9 significantly downregulated pro-inflammatory mediators, reducing IL-1 beta, IL-6, and NF-kappa B1 gene expression by up to 2.78-, 3.37-, and 4.84-fold, respectively. Consistently, it suppressed nitric oxide production in LPS-stimulated macrophages to levels comparable with ascorbic acid and markedly decreased Iba1 expression in activated THP-1 cells. This integrated enzymatic, computational, and cellular investigation identifies compounds 5 and 9 as promising multifunctional lead combining dual cholinesterase inhibition with robust anti-neuroinflammatory activity. The results provide a strong foundation for future in vivo studies and further optimization toward disease-modifying agents for neurodegenerative disorders.Article Non-Contact Acoustic Screening for Sleep Apnea: A Subject-Aware Deep Learning Approach(Springer Science and Business Media Deutschland GmbH, 2026-02-11) Aygün Çakıroğlu, M.; Kizilkaya Aydoǧan, E.; Bolatturk, Ö.F.; Aydoğan, S.; Ismailoǧullari, S.; Delice, Y.Purpose: To explore the feasibility of using camera-derived, non-contact audio synchronized with PSG for clinically relevant sleep-apnea classification, and to benchmark compact deep models under a subject-aware design using a previously unstudied, real-world dataset. Methods: Thirty-two adults underwent simultaneous polysomnography (PSG) and camera-based non-contact audio recording. The synchronized audio segments were used to train and compare three compact deep-learning architectures (convolutional, attention-augmented, and transformer-based) under a subject-aware evaluation design that prevented identity leakage. Model performance and calibration were assessed at both segment and subject levels using standard statistical tests. Results: Subject-level evaluation was based on a very small, imbalanced test set of six subjects (one positive). Within this limited yet previously unstudied local dataset, the CNN_trans model achieved an apparent perfect ranking performance (AUC = 1.00; 95% CI 0.00–1.00), though this likely reflects the small, imbalanced test cohort, with recall = 1.00 and precision = 0.55. The wide confidence interval reflects substantial statistical uncertainty, and DeLong comparisons showed no significant AUC difference between CNN_trans and CNN_att (ΔAUC = − 0.042; p = 0.43). Conclusion: PSG-synchronized, non-contact audio supports accurate and well-calibrated sleep-apnea classification with compact deep models. This subject-aware evaluation suggests that contactless acoustic monitoring may have potential clinical relevance, motivating larger, multi-site validation. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026.Article Citation - WoS: 3Citation - Scopus: 3Two-Local Modifications of Sachdev-Ye Model With Quantum Chaos(American Physical Society, 2026-01-27) Hanada, M.; Van Leuven, S.; Oktay, O.; Tezuka, M.The Sachdev-Ye-Kitaev (SYK) model may provide us with a good starting point for the experimental study of quantum chaos and holography in the laboratory. Still, the four-local interaction of fermions makes quantum simulation challenging, and it would be good to search for simpler models that keep the essence. In this paper, we argue that the four-local interaction may not be important by introducing a few models that have two-local interactions. The first model is a generalization of the spin-SYK model, which is obtained by replacing the spin variables with SU(d) generators. Simulations of this class of models might be straightforward on qudit-based quantum devices. We study the case of d=3,4,5,6 numerically and observe quantum chaos already for two-local interactions in a wide energy range. We also introduce modifications of spin-SYK and SYK models that have similar structures as the SU(d) model (e.g., H=∑p,qJpqχpχp+1χqχq+1 instead of the original SYK Hamiltonian H=∑p,q,r,sJpqrsχpχqχrχs), which shows strongly chaotic features although the interaction is essentially two-local. These models may be a good starting point for the quantum simulation of the original SYK model. ©2026 American Physical Society.Article Deep-Learning Detection of Open-Apex Teeth on Panoramic Radiographs Using YOLO Models(Springer, 2025-12-23) Edik, Merve; Celebi, Fatma; Cukurluoglu, AykaganObjectivesThe use of deep learning in detecting teeth with open apices can prevent the need for additional radiographs for patients. The presented study aims to detect open-apex teeth using You Only Look Once (YOLO)-based deep learning models and compare these models.MethodsA total of 966 panoramic radiographs were included in the study. Open-apex teeth in panoramic radiographs were labeled. During the labeling process, they were divided into 6 classes in the maxilla and mandible, namely incisors, premolars, and molars. AI models YOLOv3, YOLOv4, and YOLOv5 were used. To evaluate the performance of the three detection models, both overall and separately for each class in the test dataset, precision, recall, average precision (mAP), and F1 score were calculated.ResultsYOLOv4 achieved the highest overall performance with a mean average precision (mAP) of 87.84% at IoU (Intersection over Union) 0.5 (mAP@0.5), followed by YOLOv5 with 85.6%, and YOLOv3 with 84.46%. Regarding recall, YOLOv4 also led with 90%, while both YOLOv3 and YOLOv5 reached 89%. Moreover, the F1 score was the highest for YOLOv4 (0.87), followed by YOLOv3 (0.86) and YOLOv5 (0.85).ConclusionsIn this study, YOLOv3, YOLOv4, and YOLOv5 were evaluated for the detection of open-apex teeth, and their mAP, recall, and F1 scores exceeded 84%. Deep learning-based systems can provide faster and more accurate results in the detection of open-apex teeth. This may help reduce the need for additional radiographs from patients and aid dentists by saving time.Article Citation - WoS: 3Citation - Scopus: 3Neuroinflammatory Human Brain Organoids Enable Comprehensive Drug Screening Studies: Fingolimod and Its Analogues in Focus(Bentham Science Publishing Ltd, 2025-10-08) Acar, Busra; Pepe, Nihan Aktas; Zivkovic, Aleksandra; Stark, Holger; Sen, AlaattinIntroduction The absence of physiologically relevant models for neuroinflammatory brain disorders, such as multiple sclerosis (MS), highlights the need for improved drug screening platforms. To bridge this gap, this study aimed to develop a human brain organoid (hBO) model incorporating essential neural cell types, including astrocytes, microglia, and oligodendrocytes.Methods hBOs were generated from H9 stem cells, and neuroinflammatory characteristics were elicited by lipopolysaccharide (LPS). The expression of specific neuronal and inflammatory markers was assessed through qRT-PCR, immunofluorescence staining (IFS), and ELISA.Results IFS of mature hBOs with anti-SOX2, anti-SATB2, anti-MAPT, anti-GFAP, anti-MBP, and anti-IBA1 antibodies and images collected with the confocal microscope confirmed the differentiation of H9 cells into cortical neurons, astrocytes, microglia, and oligodendrocyte cell types. Elevated GFAP, IBA1, NF-kappa B, and IL-6 levels, along with reduced CNPase expression with LPS treatment, were considered reflective of MS-like pathology and were used to test fingolimod and its derivatives. Fingolimod and all its derivatives, specifically ST-1505, decreased MAPT (2.1-fold in ELISA, 1.7-fold in IFS), GFAP (1.8-fold in IFS), TNF alpha (5.4-fold in qRT-PCR), and FABP (1.5-fold in ELISA) levels, and increased IL-10 (11-fold in qRT-PCR) and MBP (2.9-fold in IFS) levels.Discussion The present data collectively showed LPS to evoke neuroinflammation in the hBO model, while fingolimod and its derivatives, particularly ST-1505, exhibited significant anti-inflammatory and neuroprotective properties by counteracting these evoked changes in the hBO model.Conclusion The findings supported the applicability of brain organoids as a model system for drug screening studies for neuroinflammatory brain diseases.Article Citation - WoS: 4Citation - Scopus: 4Measuring Eudaimonic and Hedonic Wellbeing: Development and Validation of the Holistic Wellbeing Measure(Routledge, 2025-10-09) Arslan, G.; Coşkun, M.The primary goal of this study was to develop a concise, theoretically grounded tool –the Holistic Wellbeing Measure (HWM)– that captures both hedonic and eudaimonic facets of wellbeing. Items for the HWM were generated through a careful review of existing wellbeing scales and literature, followed by expert consultation, pilot testing, and iterative refinement to ensure conceptual coverage, clarity, and face validity. Data were collected from three distinct samples: adolescents (n = 453), young adults (n = 361), and adults (n = 358). Exploratory and confirmatory factor analyses supported a two-factor structure, with 12 items reflecting independent but related hedonic and eudaimonic wellbeing dimensions. The measure demonstrated strong internal reliability and evidence of convergent, discriminant, and concurrent validity across all age groups. Regression analyses further indicated that the HWM contributed unique variance to the prediction of general health indicators (physical, social, and mental health) and psychological problems (depression, anxiety, and somatization), above the effects of gender, age, and psychological wellbeing. These results suggest that the HWM is a valid and reliable measure for assessing both aspects of wellbeing across age groups and can support strategies aimed at promoting overall mental health. © 2025 Taylor & Francis Group, LLC.Article Citation - WoS: 19Citation - Scopus: 19Understanding and Tailoring Excited State Properties in Solution-Processable Oligo(p-Phenyleneethynylene)s: Highly Fluorescent Hybridized Local and Charge Transfer Character via Experiment and Theory(Amer Chemical Soc, 2021-10-13) Usta, Hakan; Cosut, Bunyemin; Alkan, FahriRod-shaped oligo(p-phenyleneethynylene) (OPE) offers an attractive p-framework for the development of solution-processable highly fluorescent molecules having tunable hybridized local and charge transfer (HLCT) excited states and (reverse) intersystem crossing ((R)ISC) channels. Herein, an HLCT oligo(p-phenyleneethynylene) library was studied for the first time in the literature in detail systematically via experiment and theory. The design, synthesis, and full characterization of a new highly fluorescent (Phi(PL-solution) similar to 1) sky blue emissive 4',4 ''-((2,5-bis((2-ethylhexyl)oxy)-1,4-phenylene)bis(ethyne-2,1-diyl))bis(N,N-diphenyl-[1,1'-bi-phenyl]-4-amine) (2EHO-TPA-PE) was also reported. The new molecule consists of a D'-Ar-pi-D-pi-Ar-D' molecular architecture with an extended pi-spacer and no acceptor unit, and detailed structural, physicochemical, single-crystal, and optoelectronic characterizations were performed. A high solid-state quantum efficiency (Phi(PL-solution) similar to 0.8) was achieved as a result of suppressed exciton-phonon/vibronic couplings (no pi-pi interactions and multiple (14 per dimeric form) strong C-H center dot center dot center dot pi interactions). Strong solution-phase/solid-state dipole-dependent tunable excited state behavior (local excited (LE) -> HLCT -> charge transfer (CT)) and decay dynamics covering a wide spectral region were demonstrated, and the CT state was observed to be highly fluorescent despite extremely large Stokes shift (similar to 130 nm)/fwhm (similar to 125 nm) and significant charge separation (0.75 charge.nm). Employing the Lippert-Mataga model, along with detailed photophysical studies and TDDFT calculations, key relationships between molecular design-electronic structure-exciton characteristics were elucidated with regards to HLCT and hot exciton channel formations. The interstate coupling between CT and LE states and the interplay of this coupling with respect to medium polarity were explored. A key relationship between excited-state symmetry breaking process and the formation of HLCT state was discussed for TPA-ended rod-shaped OPE p-systems. (R)ISC-related delayed fluorescence (tau similar to 2-6 ns) processes were evident following the prompt decays (similar to 0.4-0.9 ns) both in the solution and in the solid-state. As a unique observation, the delayed fluorescence could be tuned and facilitated via small dielectric changes in the medium. Our results and the molecular engineering perspectives presented in this study may provide unique insights into the structural and electronic factors governing tunable excited state and hot-exciton channel formations in OPEs for (un)conventional solution-processed luminescence applications.