Turkish journal of biology = Turk biyoloji dergisi最新文献

[This corrects the article on p. 380 in vol. 49, PMID: 40917297.].

Background/aim: Glioblastoma multiforme (GBM) is one of the most aggressive and fatal malignancies of the central nervous system. Despite advancements in treatment strategies, effective therapies for GBM remain insufficient, necessitating further improvements. Notably, miR-22 has been found to be significantly downregulated in both glioblastoma tissues and cell lines. In this study, we aim to evaluate miR-22 expression levels in GBM (U87) and CD133-positive (CD133⁺) GBM stem cells (GSCs) and to investigate its effects on proliferation, colony formation, migration, invasion, and wound-healing in U87 and CD133⁺ U87 cells in vitro.

Materials and methods: We isolated CD133⁺ U87 cells using magnetic-activated cell sorting and determined the percentage of CD133⁺ cells by flow cytometry. qRT-PCR detected miR-22 expression. We transfected miR-22 miRNA into U87, CD133⁺, and CD133^- U87 cells using a lipid-based transfection reagent. Cell viability was assessed spectrophotometrically on days 1, 3, 5, and 7 using the CCK-8 viability assay. Transwell assays were used to analyze migration and invasion. Wound healing was assessed using a scratch assay.

Results: MiR-22 expression was lower in CD133⁺ U87 cells than in U87 cells. MiR-22 overexpression suppressed proliferation in U87, CD133⁺, and CD133^- U87 cells. MiR-22 overexpression also inhibited migration and invasion in both CD133⁺ and CD133^- U87 cells and impaired wound-healing capacity in both U87 and CD133^- U87 cells.

Conclusion: These results suggest that miR-22 acts as a tumor suppressor in GBM and CD133⁺ GSCs. Therefore, miR-22 represents a potential therapeutic target for cancer stem cell-based glioblastoma treatment.

Background/aim: Taxane resistance remains a significant challenge in the effective treatment of castration-resistant prostate cancer (CRPC). Given the association of epigenetic regulation with chemotherapy resistance and cancer progression, this study aims to identify epigenetic vulnerabilities in two CRPC cell lines (DU145 and 22Rv1) established as resistant to two different taxanes, docetaxel (Dtx) and cabazitaxel (Cbz), using a small-molecule screening approach.

Materials and methods: A small-molecule library targeting epigenetic regulators, including histone deacetylases (HDAC), histone methyltransferases, histone demethylases, bromodomain proteins, deoxyribonucleic acid methyltransferases, protein arginine deiminase, and histone acetyltransferase was utilized. Drug screening was performed on parental and taxane-resistant CRPC cell lines. Cell viability was assessed using the sulforhodamine B assay to identify compounds impairing the growth of resistant cells. Selected hits were further evaluated for their impact on colony-forming capacity using clonogenic assays, and cell death was confirmed by Annexin V/PI flow cytometry. Western blotting was used to assess histone modification marks (e.g., H3K27Ac, H3K4me2) and protein targets, including HDAC7 and lysine-specific demethylase 1 (LSD1). In combination studies, resistant cell lines were exposed to fixed-dose taxanes in combination with selected compounds. Combenefit software was used to generate synergy maps.

Results: Screening results revealed that taxane-resistant CRPC cells remained susceptible to multiple epigenetic inhibitors rather than a single dominant class. Among the identified compounds, 4-Iodo-SAHA (HDAC inhibitor) and SP2509 (LSD1 inhibitor) emerged as cytotoxic agents, inducing cell death at levels comparable to those of parental cells. Further validation confirmed their efficacy in impairing cell viability and long-term survival in taxane-resistant CRPC cells, as demonstrated by Annexin V/PI flow cytometry. Both compounds induced epigenetic modulations consistent with their targets, reflected by increased histone marks (H3K27Ac for 4-Iodo-SAHA; H3K4me2 for SP2509), and were also associated with depletion of HDAC7 and LSD1, respectively. Combination assays demonstrated that both compounds potentiated Dtx activity and helped overcome resistance in taxane-resistant CRPC models.

Conclusion: This study highlights epigenetic vulnerabilities in taxane-resistant CRPC and identifies 4-Iodo-SAHA and SP2509 as promising monotherapy candidates, demonstrating their ability to potentiate Dtx activity and overcome resistance.

Background/aim: Artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT and DeepSeek, is being increasingly applied in clinical care, research, and education. The aim of this review is to examine how these tools may transform the conduct of medical and biological research and to define their limitations.

Materials and methods: A narrative synthesis of the literature was performed, encompassing studies published between 2020 and 2025. Peer-reviewed journals, systematic reviews, and high-impact original research articles were included to ensure an evidence-based overview. The principle applications, validation metrics, and clinical implications across orthopedics, oncology, cardiology, internal medicine, and the biological sciences were analyzed.

Results: LLMs demonstrate strong potential in supporting physicians during clinical decision-making, enhancing patient education, and assisting researchers in their work. They are valuable for language-related tasks and for generating structured, clear, and comprehensible content. However, concerns persist regarding data privacy, algorithmic bias, factual accuracy, and excessive dependence on data-driven outputs. Responsible implementation requires safeguards such as human oversight, model transparency, and domain-specific training.

Conclusion: AI tools such as ChatGPT, DeepSeek, and similar models are transforming the way healthcare is delivered and studied. Their current capabilities appear highly promising. However, clinicians, technical experts, and policymakers must collaborate to ensure the safe, equitable, effective, and ethical integration of these technologies into real-world healthcare workflows.

Background/aim: Breast cancer remains a major malignancy among women, and severe side effects and the development of acquired drug resistance frequently hinder current therapeutic strategies. The Notch signaling pathway, a key regulator of cell fate, is commonly dysregulated in breast cancer and associated with poor prognosis. Gamma-secretase inhibitors (GSIs) block Notch receptor activation and have shown potential anticancer efficacy. This study aimed to investigate the synergistic activity of two commonly used GSIs, DAPT and MK0752, combined with docetaxel or cisplatin in both 2D and 3D breast cancer models.

Materials and methods: Triple-negative, highly metastatic MDA-MB-231 and ER+/PR+ MCF-7 breast cancer cell lines were treated with DAPT or MK0752 alone or in combination with docetaxel or cisplatin. Drug efficacy and potential synergism were evaluated in 2D monolayer cultures and 3D spheroid models. Sequential treatment strategies were also assessed, where docetaxel or cisplatin was administered prior to GSI exposure.

Results: Both MDA-MB-231 and MCF-7 cell lines exhibited notable sensitivity to DAPT and MK0752 combinations with docetaxel or cisplatin in 2D and 3D cultures. Synergistic enhancement of cytotoxicity was observed, particularly in sequential treatment regimens. Pretreatment with docetaxel or cisplatin followed by GSI exposure demonstrated superior growth inhibition compared with either monotherapy or simultaneous combination treatments.

Conclusion: This study highlights the therapeutic potential of combining GSIs with standard chemotherapeutics to overcome drug resistance in breast cancer. The observed synergy and sequencing effects provide a strong basis for further mechanistic and translational investigations to optimize GSI-based combinational therapy strategies.

Background/aim: Neurodegenerative diseases such as Alzheimer's, Parkinson's, Huntington's, and ALS are characterized by a progressive loss of nerve cells, for which no definitive cure currently exists. These conditions share common pathological mechanisms, including chronic neuroinflammation, oxidative stress, protein aggregation, and mitochondrial dysfunction. Flavonoids and other plant-derived phenolic compounds have recently attracted attention for the treatment of such conditions due to their antiinflammatory and antioxidant properties. This review explores the neuroprotective mechanisms of flavonoids and evaluates their potential for the prevention and treatment of neurodegenerative diseases.

Materials and methods: A literature search of the Web of Science, PubMed, and ScienceDirect databases was conducted to evaluate the therapeutic potential of flavonoids and phenolic compounds against neurodegenerative diseases. The search terms included "polyphenols", "flavonoids", and related compounds, along with "Alzheimer's", "Parkinson's", "Huntington's", and "Amyotrophic lateral sclerosis". Eligible studies included clinical trials, randomized controlled trials, and in vitro and in vivo research published in English. Priority was given to studies from the last decade, although older but significant publications were also included.

Results: The findings of multiple studies report the ability of flavonoid compounds such as quercetin, myricetin, apigenin, and epigallocatechin gallate (EGCG) to modulate critical signaling pathways, reduce oxidative stress, prevent the accumulation of neurotoxic proteins, and support mitochondrial function. These bioactive molecules have exhibited significant potential in slowing disease progression and preserving neuronal integrity. Their therapeutic application, however, has been limited by their poor bioavailability, low stability, and rapid metabolism.

Conclusion: Flavonoids have shown promise as naturally derived agents with multi-targeted activity against neurodegenerative processes. Enhancing their absorption and stability through novel delivery systems and structural modifications could significantly improve their clinical efficacy. When administered early or as a complementary therapy, flavonoids can be considered a safe and effective approach to the management of neurodegenerative diseases.

Background/aim: Sunflower (Helianthus annuus) is a crop of high economic and nutritional importance that continues to suffer significant yield losses due to foliar diseases. Traditional image-based and laboratory detection techniques remain limited by subjectivity, cost, and scalability. Transfer learning (TL) has recently emerged as an effective approach to overcoming these challenges involving the reuse of pretrained deep models for plant pathology tasks. Presented here is a systematic examination of recent TL-based studies on sunflower disease classification to identify prevailing trends, research gaps, and future opportunities.

Materials and methods: A structured Scopus query was employed to retrieve peer-reviewed articles published between 2021 and 2025. Strict inclusion and exclusion criteria ensured technical relevance to TL-based sunflower disease detection. Subsequently, 30 studies meeting the criteria were critically reviewed and analyzed in terms of model architecture, dataset characteristics, preprocessing strategies, and reported evaluation metrics. The comparative assessment focused on convolutional neural networks (CNNs), transformer-based architectures, and hybrid models.

Results: The analysis revealed a dominant reliance on pretrained CNNs such as ResNet, VGG, Inception, and EfficientNet. Several studies employed lightweight or federated learning variants to enhance deployment feasibility under field conditions. Among the commonly observed challenges were limited dataset diversity, class imbalance, and insufficient explainability. A key word cooccurrence analysis indicated an evolving research focus, transitioning from basic deep learning implementation to explainable and privacy-preserving frameworks optimized for edge devices.

Conclusion: The review revealed substantial progress in TL applications for the diagnosis of sunflower disease but underscored the need for larger, standardized datasets and cross-regional validation. Future studies should prioritize interpretable, adaptive architectures that can function in real-world agricultural environments. The insights drawn from this synthesis extend beyond sunflower pathology, offering a foundation for scalable, domain-transferable TL solutions in broader plant disease detection contexts.

Background/aim: This study aimed to investigate the phenotypic resistance and distribution of efflux pump-associated antimicrobial resistance genes in Staphylococcus spp. isolated from dairy and meat samples. Antimicrobial resistance in foodborne bacteria increases with antibiotic exposure and biocides, particularly through efflux mechanisms. Thus, monitoring potential genetic reservoirs in the food chain is very important.

Materials and methods: A total of 132 dairy and meat samples were collected for the study, and Staphylococcus spp. were isolated using Mannitol salt phenol red agar. Antimicrobial susceptibility was evaluated using the Clinical and Laboratory Standards Institute's microdilution method. Twenty-six resistant isolates were identified by 16S rDNA sequencing. The effect of reserpine on MIC values was evaluated using microdilution tests to assess the role of efflux pumps in antibiotic resistance and biocide tolerance. Antibiotic resistance and efflux pump genes were detected using real-time PCR with specific primers.

Results: Of the 77 isolates evaluated, 26 (33.8%) were resistant to at least one antibiotic. Resistance to tetracycline (69.2%) and cefuroxime (38.5%) were the most common. The administration of reserpine reduced minimum inhibitory concentration (MIC) values across all cefuroxime-resistant isolates and in a subset of tetracycline- and nitrofurantoin-resistant strains, suggesting the potential involvement of efflux pumps. It also lowered MICs for triclosan (46.7%) and povidone-iodine (32%). The most frequently detected efflux pump genes were smr (88.5%), efrA (84.6%), efrB (80.8%), mdeA (84.6%), and norE (80.8%). qacA/B was not detected in any isolate.

Conclusion: Genes encoding efflux pump proteins were commonly found in Staphylococcus spp. isolated from dairy and meat samples. Reserpine inhibition tests confirmed the phenotypic effects of these genes. These results suggest efflux-mediated resistance can significantly impact antibiotic tolerance and biocides in foodborne isolates. Continued surveillance and control strategies are essential to limit the spread of these resistance genes in the food chain.

As the demand for greater quantities of higher-quality food grows with population expansion, climate change, urbanization, and unsustainable agricultural practices accelerate the loss of arable land, ultimately threatening agricultural sustainability. Population growth necessitates a transition to nutritious, safe, and healthy food production systems that ensure higher yields, less reduced waste, improved social outcomes, and the integration of economic, social, and environmental sustainability principles. Urgent global challenges such as resource depletion, biodiversity loss, and climate change necessitate the protection of ecosystems and the sustainable use of natural resources. Agricultural systems must enhance food production and supply productivity, strengthen system resilience, and improve resource efficiency and sustainability. The sustainable development of agricultural systems based on resilience and productivity is important to ensure food security. The aim of this review is to compile, describe, and propose future strategies for promising food systems-including transformative innovations and alternative farming techniques-to facilitate the transition toward resilient, resource-efficient, and sustainable agriculture, and to mitigate long-term challenges. It also provides recommendations for future research, sustainability, resilience, and emerging food trends aimed at promoting sustainable food systems and green technologies, protecting ecosystems, resources, and biodiversity, and optimizing waste management and natural resource use. This article focuses on future sustainable food production and security, environmental protection, alternative protein sources, and innovative agricultural techniques; it highlights scientific and technological advancements, emerging research directions, and offers a comprehensive perspective on resilient, resource-efficient, and sustainable food production systems.

Background/aim: Fibroblast Growth Factor Receptor (FGFR) gene fusions are recognized as pivotal oncogenic drivers, contributing to cancer initiation and progression across diverse malignancies. These fusions often represent significant therapeutic targets, particularly in challenging malignancies like cholangiocarcinoma. This study aimed to characterize the novel FGFR2::SHTN1 fusion, identify it as a de novo chimeric protein, and elucidate its precise oncogenic mechanism.

Materials and methods: FGFR2::SHTN1 fusions were identified via cancer genomics databases and modeled using AlphaFold and HADDOCK. SHTN1 variants were expressed in Neuro-2a cells for coimmunoprecipitation, purification, and native polyacrylamide gel electrophoresis to assess oligomerization. Structural modeling included membrane embedding with Chemistry at HARvard Macromolecular Mechanics-Graphical User Interface (CHARMM-GUI).

Results: We found that FGFR2::SHTN1 is an in-frame fusion formed by the joining of upstream FGFR2 exons 1-17 with downstream SHTN1 exons 7-17 in human, resulting in a chimeric protein retaining the intact FGFR2 tyrosine kinase domain. Our analyses revealed that Shootin1 inherently forms oligomers through its coiled-coil domains, which, within the fusion, mediate ligand-independent dimerization and constitutive activation of FGFR2.

Conclusion: Our findings establish FGFR2::SHTN1 as a potent oncogenic driver in various cancers, particularly in cholangiocarcinoma, highlighting a unique mechanism of constitutive activation mediated by Shootin1's CCD-II domain. This study represents the first molecular characterization of the FGFR2::SHTN1 fusion, advances understanding of FGFR2 fusion biology, and identifies a particular target for future diagnostic and therapeutic strategies in relevant malignancies.