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 Time Distributed Classification of Alzheimer’s Disease on MRI Scans(John Wiley and Sons Ltd, 2026) Dundar, Mehmet Sait; Yilmaz, BulentThe diagnosis of Alzheimer's disease (AD) has progressively depended on sophisticated neuroimaging methods alongside cognitive assessments. This study combines volumetric feature analysis with computational modeling techniques, focusing on spatial and temporal analysis, to categorize individuals as cognitively normal (CN), mild cognitive impairment (MCI), or AD using magnetic resonance imaging (MRI) data. In the initial phase, volumetric changes, comprising cortical thickness, white matter, grey matter, cerebrospinal fluid, and total intracranial volume, were derived from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset utilizing the CAT12 toolbox in statistical parametric mapping (SPM). Linear regression was utilized on these variables over time to create slopes that reflect volumetric change rates, which then served as inputs for machine learning classifiers. The slopes of cortical thickness exhibited the greatest classification accuracy, reaching 82.5% with a random forest model for differentiating AD from CN individuals. During the second phase, a deep learning methodology was utilized, relying solely on the MRI scans and excluding the outcomes from the first phase. A pre-trained 3D ResNet-101 convolutional neural network (CNN) model extracted spatial characteristics from MRI volumes, whereas long short-term memory (LSTM) networks recorded temporal dynamics across subsequent annual scans. This hybrid CNN-LSTM design markedly improved classification performance, attaining 96.7% accuracy for AD against CN and enhancing the distinction of MCI cases. Nonetheless, discrepancies in MCI categorization were chiefly ascribed to the restricted access to annual MRI data and the model's pre-training on CN and AD cohorts. These findings highlight the potential of integrating volumetric statistical analysis with deep learning for automated AD categorization. This work enhances neuroimaging diagnostic methods by utilizing both spatial and temporal MRI data, enabling early diagnosis and better evaluation of disease development.Article Functional Characterization of Loss of RNF43 Reveals Neuronal Defects in a Caenorhabditis Elegans Model(MDPI, 2026) Kazan, Hasan Huseyin; Turkyilmaz, Zafer; Ekim, Burcu; Kaya, Cem; Ergun, Mehmet Ali; Sonmez, Kaan; Güzel, SinemRing finger protein 43 (RNF43) encodes a transmembrane E3 ubiquitin ligase that negatively regulates canonical Wnt signaling and is classically associated with serrated polyposis syndrome and colorectal cancer. In this study, regarding a homozygous truncating RNF43 variant (NM_001305545.1:c.1906C>T; p.Gln636Ter) in a patient segregating with a severe neurodevelopmental phenotype characterized by developmental delay, neonatal hypotonia, recurrent seizures, progressive microcephaly, and bilateral optic atrophy, the loss of polarity defective 1 (plr-1), an ortholog of RNF43, was modeled in Caenorhabditis elegans and the phenotype was primarily characterized. The results demonstrated that loss of the plr-1 disrupted gamma aminobutyric acid (GABA)ergic axon organization, reduced locomotor speed calculated from 60 s recordings, and altered developmental growth. These findings expand the phenotypic spectrum of RNF43 and support a dosage-dependent developmental role.Article A Novel Dental Implant Nut System Designed to Enhance Primary Stability: Mechanical and Finite Element Analysis(Wiley, 2026) Demirbaş, Ahmet Emin; Bal, Burak; Alkan, Alper; Şahin, Mert; Soylu, EmrahPurpose: The present study aimed to evaluate, in a preclinical setting, the biomechanical behavior and mechanical performance of a newly developed dental implant nut system designed to address primary stability challenges in the severely resorbed posterior maxilla. Materials and Methods: The evaluation consisted of two complementary stages: an in vitro mechanical experiment and a finite element analysis (FEA). In the experimental phase, polyurethane jaw models simulating a severely atrophic posterior maxilla with approximately 1 mm residual bone height were used. Four groups were prepared: single implant without nut, single implant with nut, double implant without nut, and double implant with nut (n = 10 per group). Primary stability was measured using resonance frequency analysis (RFA) with an Osstell device. In the computational phase, three-dimensional finite element models were constructed from cone-beam computed tomography (CBCT) data of the same configuration to evaluate detachment forces and stress distribution within the bone-implant complex under vertical loading. Results: In single-implant models, mean implant stability quotient (ISQ) values increased from 10.91 +/- 7.35 to 18.27 +/- 7.11 after nut application. In double-implant models, ISQ values increased from 11.13 +/- 4.14 to 19.24 +/- 4.24 (p < 0.05). FEA results revealed that the detachment force increased from 16.5 to 20.33 N in single-implant models and from 15 to 22.3 N in double-implant models. Compressive stresses on the bone were lower in nut-supported configurations, indicating a more favorable load distribution. Conclusion: The nut system was associated with increased implant primary stability and a more favorable stress distribution under the conditions of this preclinical study. These findings should be interpreted as preliminary biomechanical evidence, as no in vivo or clinical validation was performed. Therefore, this design may be considered a mechanical stabilization concept that warrants further investigation through in vivo and clinical studies.Article A Novel ELF4 Gene Variant Disrupts T and NK Cell Function in a Patient with Immune Thrombocytopenia (ITP)(Springer Basel AG, 2026) Kendirli, Perihan Kader; Gök, Veysel; Eken, Ahmet; Özcan, Alper; Erdem, Şerife; Kısaarslan, Ayşenur Paç; Kayhan, EdaObjective and design In this report, we identified a novel hemizygous ELF4 variant (c.1822G > C; p.Gly608Arg) in an adolescent male with chronic immune thrombocytopenia (ITP) and performed functional immunologic characterization. Materials and methods Peripheral blood mononuclear cells (PBMCs) of the patient and age-matched controls were characterized by flow cytometry with respect to T cell phenotype, activation, proliferation and NK cell cytotoxicity. Results The p.Gly608Arg substitution affects a highly conserved residue in the C-terminal regulatory domain of ELF4 and is predicted to be damaging. Immunophenotyping showed an expanded CD8(+) T-cell compartment, an inverted CD4/CD8 ratio, reduced na & iuml;ve T-cell populations, and accelerated acquisition of memory-like phenotypes upon activation. Both CD4(+) and CD8(+) T cells displayed increased proliferation following TCR stimulation, consistent with impaired ELF4-dependent regulation of effector T-cell expansion. NK cells exhibited reduced granzyme B and perforin expression and markedly diminished cytotoxicity against K562 targets, indicating defects in maturation and effector function. Conclusions These findings suggest that the identified ELF4 variant is associated with combined T- and NK-cell dysfunction. This case expands the clinical spectrum of Deficiency in ELF4, X-linked and underscores the relevance of evaluating ELF4 mutations in patients with unexplained cytopenias accompanied by dysregulated lymphocyte activation and impaired cytotoxic responses.Article Tooth Decay Promotes Senescence in Dental Pulp Stem Cells, Modifying Their Biological and Proteomic Profiles(Wiley, 2026) Durukan, Sebahat Melike; Tez, Banu Cicek; Ozcan, Servet; Simsek, Ahmet; Al-Sammarrie, Sura Hilal Ahmed; Gunaydin, Zeynep; Acar, Mustafa BurakDental caries is a prevalent oral health problem that significantly reduces an individual's quality of life; although, it can be effectively managed through restorative treatments. Even in cases where the caries does not reach the pulp, released microbial products from the lesion can still penetrate the pulp chamber, potentially inducing stress on pulp cells. In this study, we conducted a comparative analysis of the biological and proteomic profiles of dental pulp stem cells (DPSCs) isolated from clinically asymptomatic teeth with dentinal caries that had not reached the pulp and isolated from healthy teeth. Following biological evaluations, we examined proteomes of these DPSCs by conducting a shotgun proteomics approach. Our findings show that DPSCs from decayed teeth exhibit a significantly higher proportion of senescent cells. Proteomic profiling revealed upregulation of inflammatory signaling, extracellular matrix remodeling, and senescence-associated secretory phenotype (SASP) related proteins. Additionally, we observed an upregulation in the expression of proteins associated with extracellular matrix (ECM) remodeling and components of the SASP, which are hallmarks of the senescence process. The study reveals that DPSCs can be affected by stress from carious lesions, even when the pulp appears clinically intact. Senescence and inflammatory response in these affected cells may have deleterious effects on other tissues within the organism. Consequently, restorative treatments should consider targeting not only the decayed tissue but also the senescent cells within the pulp that may have been affected by the stress induced by caries.Article Immune-Driven Mechanisms in Idiopathic Intracranial Hypertension: A Critical Synthesis(Walter de Gruyter GmbH, 2026) Tuzun, Erdem; Yetimler, BerrakIdiopathic intracranial hypertension (IIH) is increasingly recognised as a complex disorder characterized by elevated intracranial pressure (ICP), with evidence suggesting contributions from dysregulated cerebrospinal fluid (CSF) dynamics as well as metabolic, endocrine, and neurovascular mechanisms. IIH predominantly affects women of reproductive age who are living with obesity. Clinically, IIH may be asymptomatic or present with severe headaches, visual disturbances, and papilledema, with a risk of visual impairment in some untreated or refractory cases. Although the etiopathogenesis of IIH remains unclear, emerging evidence from metabolic and immunological studies suggests that immune-mediated mechanisms may contribute to disease pathophysiology. In this review, we synthesize current literature on the potential contribution of the immune system to IIH, integrating findings across obesity-associated inflammation, circulating cytokine profiles, comorbid inflammatory and autoimmune conditions, and markers of neuroglial stress and injury. We summarize converging data suggesting that IIH may, at least in part, be influenced by a pro-inflammatory milieu that affects CSF dynamics. While available studies highlight intriguing immunological signals, the underlying mechanistic pathways remain poorly resolved. Larger, longitudinal, and mechanistically grounded investigations are needed to clarify causality, identify relevant immune subtypes, and determine whether immune modulation may offer therapeutic opportunities in IIH.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 Parametric Study on the Behavior of CFRP-Strengthened Reinforced Concrete Deep Beams with Cut Circular Web Openings in Shear Spans(Nature Portfolio, 2026-02-17) Yagmur, ErenWeb openings in reinforced concrete deep beams are often necessary for functional purposes but substantially reduce structural performance. Carbon fiber-reinforced polymer (CFRP) strengthening is commonly employed to mitigate these effects. Previous studies typically examined openings in regions without stirrups or assumed closed stirrup configurations, overlooking the frequent stirrup damage that occurs in practice due to the high shear reinforcement in deep beams. In this study, three specimens from a prior experimental program were modeled in ABAQUS, and the numerical results were validated against experimental data. Openings of varying diameters were introduced by cutting reinforcements, and the beams were subsequently strengthened with CFRP laminates, and a parametric study was conducted. Results showed that increasing opening diameter markedly reduces load-carrying capacity and energy absoption, while thicker CFRP laminates partially restore performance. For example, a 300 mm opening in a 500 mm high unstrengthened beam reduced load capacity by 56% and energy absorption by 87%. Even when the opening diameter was less than one-third of the beam height, 1.8 mm CFRP laminates provided only limited improvement. Deep beam performance was strongly influenced by web opening size, and the effectiveness of CFRP strengthening was limited when stirrup integrity was compromised.Article Integrative Bioinformatics Prediction of West Nile Virus-Derived microRNAs Reveals Potential Host Regulatory Interactions(Elsevier Sci Ltd, 2026-08) Demirci, Muserref Duygu Sacar; Orhan, Mehmet Emin; Erginkoc, Altay Nida; Saçar Demirci, Müşerref DuyguWest Nile virus (WNV) is a mosquito-borne flavivirus linked to severe neuroinvasive disease. Although host and vector microRNAs (miRNAs) have been implicated in viral infection, the presence and functional relevance of WNV-encoded miRNAs remain largely unexplored. Here, we developed an integrative bioinformatics pipeline that combines multiple miRNA prediction algorithms with secondary structure screening and host transcriptomic data to identify high-confidence candidate WNV-derived mature miRNAs. Overlap-based confidence scoring and differential expression support from RNA-seq datasets prioritized a small subset of putative miRNA-mRNA interactions with potential roles in infection-associated gene regulation. A competitive endogenous RNA network constructed from predicted mRNA, lncRNA, and circRNA targets highlighted pathways involving innate immunity, GPCR and Wnt signaling, RNA degradation, and viral replication. Together, these findings provide a reproducible computational workflow and nominate testable regulatory interactions for future experimental validation.