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Prognostic value of hematological and biochemical parameters on poor clinical course and mortality in COPD exacerbations
No full textChronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. Exacerbations significantly contribute to poor clinical outcomes and increased mortality. Biomarkers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and eosinophil-to-lymphocyte ratio are useful in predicting the prognosis of COPD exacerbations. This study aimed to evaluate the predictive value of the lactate dehydrogenase-to-albumin ratio (LAR), along with NLR, PLR, and eosinophil-to-lymphocyte ratio, for poor clinical outcomes and mortality in patients hospitalized due to COPD exacerbations. We retrospectively analyzed 216 patients hospitalized for COPD exacerbations between 2018 and 2023. Demographic data, comorbidities, laboratory findings, and clinical outcomes, including mortality, noninvasive mechanical ventilation (NIMV), intensive care unit (ICU) admission, and prolonged hospitalization, were evaluated. Multivariate logistic regression and receiver operating characteristic curve analyses were used to examine the relationships between biomarkers and clinical outcomes. Both NLR and PLR were significantly increased in patients admitted to the ICU (P = .008 and P = .048) and in those who died (P = .005 and P = .019). Deceased patients also had higher levels of urea and blood urea nitrogen (P = .008 and P = .007) and lower lymphocyte counts (P = .012). The risk of mortality was higher in patients with longer hospital stays (odds ratio [OR]: 1.326; P = .025), those requiring NIMV (OR: 20.62; P = .035), patients with elevated blood urea nitrogen levels (OR: 1.126; P = .015), and in those with lower lymphocyte counts (OR: 0.996; P = .039). Receiver operating characteristic analysis showed that NLR predicted mortality with an area under the curve of 0.794 (95% confidence interval: 0.682-0.905; cutoff: 11.84; sensitivity: 75%; specificity: 80.8%, P = .005) and PLR with an area under the curve of 0.745 (95% confidence interval: 0.635-0.855; cutoff: 256.53; sensitivity: 75%; specificity: 70.7%, P = .019). LAR levels were significantly higher in patients who required oxygen therapy (P = .004) and NIMV (P = .049). In this study, NLR and PLR were significantly associated with ICU admission and in-hospital mortality. Although LAR was higher in patients requiring oxygen therapy and NIMV, it was not significantly associated with mortality; therefore, its prognostic value remains uncertain. Future research should focus on prospective multicenter cohorts and incorporate dynamic or serial biomarker monitoring to improve prognostic accuracy and better characterize the temporal behavior of these markers
Bevacizumab combined with irinotecan or temozolomide in recurrent glioblastoma: a Turkish Oncology Group (TOG) study
No full textPurpose: Given the lack of an effective systemic therapy for recurrent glioblastoma, this study aims to compare response rates, progression-free survival, overall survival, and toxicity profiles of bevacizumab in combination with temozolomide (TMZ) versus irinotecan. Methods: We retrospectively analyzed patients with recurrent glioblastoma from seventeen oncology centers in Türkiye who received bevacizumab combined with either TMZ or irinotecan after progression. Outcomes included response rates, progression-free survival (PFS), overall survival (OS), and adverse events assessed by CTCAE v4.0. Results: Among 210 patients with recurrent glioblastoma, the median PFS was 7.9 months overall (5.2 months with TMZ–bevacizumab and 8.2 months with irinotecan–bevacizumab), and the median OS was 10.6 months overall (11.3 and 10.3 months, respectively). Six-month PFS and OS rates were 60% and 68% for the entire cohort, with no statistically significant differences between treatment regimens. Both combinations were generally well tolerated, with hypertension more frequent in the TMZ arm and liver enzyme elevation more common in the irinotecan arm. Conclusion: In this multicenter cohort of patients with recurrent glioblastoma, bevacizumab combined with either temozolomide or irinotecan demonstrated comparable PFS and OS outcomes. Both regimens were generally well tolerated, suggesting that treatment choice may be guided by individual patient profiles and toxicity considerations rather than differences in efficacy
Design and Simulation of Silicon-based EFI Switches Using Substrate-integrated Thyristors: A Cost-effective Alternative to SiC
No full textThis study presents the design and simulation of silicon-based thyristors aimed as exploding foil initiator (EFI) switches. Although recent EFI switch designs focus on devices based on silicon carbide (SiC) due to its wider bandgap and superior thermal performance, our work returns to silicon, a material used in foundational studies in the field, offering a cost-effective alternative for thyristor-based EFI applications. In contrast to SiC-based devices that employ well-controlled epitaxial drift layers, the use of silicon necessitates the integration of the substrate wafer itself as the drift region of the thyristor. This introduces challenges related to doping uniformity, as bulk substrates exhibit greater variation compared to epitaxial layers. This study aims to optimize critical design parameters, including layer dimensions and doping concentrations, to mitigate the effects of wafer variability. TCAD simulations are used to evaluate device behavior, and results are compared with both similar EFI designs from the literature and a commercial product, focusing on key performance metrics such as di/dt, breakdown voltage, and turn-on delay. The findings indicate that the proposed designs achieve comparable or even superior performance. Additionally, the study explores the impact of device type (N-type vs. P-type), doping concentrations, layer dimensions and placements, as well as layout configurations (square vs. cylindrical) on device performance, marking a significant contribution. The results of this study will serve as a valuable resource for researchers developing high-energy switching devices
Analysis of ROS dynamics based on dissolved oxygen sensing in upconversion nanoparticle-based photodynamic therapy
No full textPhotodynamic therapy (PDT) is a promising cancer treatment approach that relies on the localized generation of reactive oxygen species (ROS) to eliminate cancer cells. In particular, the nanophotonic approach based on upconversion nanoparticles (UCNPs) offers a key advantage by enabling the use of near-infrared (NIR) light, which enhances light penetration into tissue and expands clinical applicability of PDT. Real-time monitoring of ROS generation and degradation during the PDT process offers distinct advantages over conventional endpoint assays for elucidating PDT mechanisms, optimizing photosensitizer (PS) formulations and refining treatment protocols. In this study, we not only distinguish and quantify the relative contribution of NaYF4:Yb3+,Tm3+ UC nano-antennas, Rose Bengal (RB) PS, NIR activation laser, and culture medium in UCNP-based PDT for the first time via real-time ROS analysis using dissolved oxygen (DO) data which cannot be achieved by endpoint assays but also introduce new and insightful concepts such as medium activation time (FWHM), maximum PL lifetime change (Δτmax), and time to reach the maximum PL lifetime change (τmax). This is realized by implementation of a 3D-printed optofluidic dissolved oxygen (DO) sensor for indirect analysis of ROS dynamics which infer from changes in the sensor's photoluminescence (PL) lifetime (τ). Thus, performance and optimum concentrations of NaYF4:Yb3+,Tm3+ UCNPs and RB PS are first determined via MTT assays using A375 melanoma cells, and subsequent in-vitro PDT tests using a 980 nm laser. Quantitative analyses show that, UCNPs, RB, and the cell culture medium contribute approximately 25 %, 26 %, and 4 % to the total Δτ respectively. The maximum performance occurs when all components are present and activated, resulting in the highest ROS level with the longest activation time. Interestingly, even laser excitation of the medium alone or UCNPs without PS results in partial ROS generation. These findings provide valuable insights for optimizing UCNP-based PDT drugs for cancer treatment
Some Novel Error Bounds of Boole's Formula-Type Inequalities in Quantum Calculus With Computational Analysis and Applications
No full textQuantum calculus extends classical calculus through the inclusion of a parameter (Formula presented.), thereby broadening the conceptual framework for analysis. The present study provides novel variants of Boole's formula-type inequalities for (Formula presented.) -differentiable convex functions via first deriving an essential quantum-integral identity. The derived results enhance classical findings and highlight the distinctive properties of convex functions in quantum calculus. The application to quadrature formula, special means of real numbers, and the Mittag-Leffler function demonstrates the practical relevance of our newly derived results. Numerical and graphical examples further verify the accuracy and effectiveness of the presented inequalities, indicating their suitability for real-world circumstances. The present work strengthens the theoretical understanding of Boole's formula-type inequalities in quantum and classical domains and offers interesting possibilities for future research in numerical analysis
Analysis of Hereke Asım Kocabıyık Vocational School Energy System and Development of Reference Energy System
No full textDeepening the Diagnosis: Detection of Midline Shift Using an Advanced Deep Learning Architecture
No full textMidline shift (MLS) is one of the conditions that strongly affects mortality and prognosis in critical neurological emergencies such as traumatic brain injury (TBI). Especially, MLS over 5 mm requires urgent diagnosis and treatment. Despite widespread tomography imaging capabilities, the lack of radiologists capable of interpreting the images causes delays in the diagnosis process. Therefore, there is a need for AI-supported diagnostic systems specifically tailored to the field for MLS detection. However, the lack of open, disorder-specific datasets in the literature has limited research in the field and hindered the ability to make comparisons against a reliable reference point. Therefore, the current state of deep learning (DL) methods in the field is not sufficiently addressed. Within the scope of this study, a DL architecture is proposed for MLS detection as a classification task, with millimeter-scale MLS measurements used for evaluation and stratified analysis. This process also comprehensively addresses the status of MLS detection in contemporary DL architecture. Furthermore, to address the lack of open datasets in the literature, two publicly available datasets originally collected with a primary focus on TBI have been annotated for MLS detection. The proposed model was tested on two different open datasets and achieved mean sensitivity values of 0.9467–0.9600 for the Radiological Society of North America (RSNA) dataset and 0.8623–0.8984 for the CQ500 dataset in detecting MLS presence above 5 mm across two different scenarios. It achieved a mean Area Under the Curve-Receiver Operating Characteristic (AUC-ROC) value of 0.9219–0.9816 for the RSNA dataset and 0.9443–0.9690 for the CQ500 dataset. The aim of the study is to detect not only emergency cases but also small MLSs independent of quantity for patient follow-up, so the overall performance of the proposed model (MLS present/absent) was calculated without an MLS quantity threshold. Mean F1 Score values of 0.7403 for the RSNA dataset and 0.7271 for the CQ500 dataset were obtained, along with mean AUC-ROC values of 0.8941 for the RSNA dataset and 0.9301 for the CQ500 dataset. The study presents a clinically applicable, optimized, fast, reliable, up-to-date, and successful DL solution for the rapid diagnosis of MLS, intervention in emergencies, and monitoring of small MLS. It also contributes to the literature by enabling a high level of reproducibility in the scientific community with labeled open data
Global burden of amphetamine, cannabis, cocaine and opioid use in 204 countries, 1990–2023: a Global Burden of Disease Study
No full textDrug use disorders (DUDs) are emerging global public health challenges. Here we investigated the global and regional estimates of the prevalence and burden of DUDs, including amphetamine, cannabis, cocaine and opioid use disorders, from 1990 to 2023 for 204 countries and territories by using the Global Burden of Disease Study 2023. Overall, trends in global age-standardized disability-adjusted life-years of DUDs increased from 169.3 (95% uncertainty interval (95% UI), 134.4–203.9) per 100,000 people in 1990 to 212.0 (95% UI, 179.2–245.6) in 2023. In 2023, both prevalence and burden of DUDs were higher in high-income countries, particularly in the USA. The most prevalent DUDs in 2023 were cannabis use disorder (age-standardized prevalence, 270.8 (95% UI, 201.7–350.0) per 100,000 people) and opioid use disorder (205.9 (95% UI, 178.7–235.0)). Particularly, opioid use disorder showed a nearly twofold increase in prevalence and burden between 1990 and 2023. In 2023, compared with countries where cannabis use was illegal, countries permitting both recreational and medical cannabis use had higher prevalence rates for all types of DUDs. Proactive and effective policies are essential to mitigate the increasing global burden of DUDs
Tuning mechanical and microstructural properties of Bi-2212 ceramics through optimal Nd³⁺ substitution: findings from experimental and theoretical approach
No full textThis study systematically investigates the mechanical and structural behavior of Nd3+-substituted Bi2.0-xNdxSr2.0Ca1.0Cu2.0Oy ceramics synthesized by the conventional solid-state reaction method using combined experimental microhardness (Hv) testing and theoretical modeling approaches. Incorporating Nd ions into the Bi-2212 lattice enhances microstructural stability, grain boundary coupling, and crystallographic coherence, with optimal mechanical performance at x = 0.01. Complementary SEM, XRD, and EDX analyses confirm the correlation between improved surface morphology, crystallinity, and enhanced mechanical performance. EDX results further verified the successful replacement of Bi3+ for Nd3+ and compositional uniformity within the Bi-2212 lattice, supporting the structural integrity and hardness improvements. At this concentration, strong ionic and partial covalent bonding interactions between Nd3+ and the host lattice facilitate charge compensation, defect accommodation, and densification, resulting in superior Vickers hardness and resistance to deformation. As for the mechanical characterization examination, indentation behavior reveals classical Indentation Size Effect (ISE) behavior through all the synthesized compounds, with peak load resistance at x = 0.01 and marked degradation at higher dopant levels due to increased porosity, grain boundary decoupling, and strain localization. Bulk density (ρ) measurements correlate strongly with microhardness trends, confirming the interdependence of atomic packing, structural integrity, porosity, intergranular coherence, and mechanical durability. Accordingly, the optimal mechanical and structural performance is observed at x = 0.01, corresponding to the highest measured ρ value of 5.99 g/cm3 and Hv of 0.498 GPa at 0.295 N. These results indicate that Nd³⁺ substitution at this level promotes enhanced densification and grain boundary cohesion, leading to a defect-minimized microstructure with superior resistance to indentation and load-induced plastic deformation. Beyond this doping level, excessive Nd incorporation deteriorates crystallinity and promotes porosity formation, resulting in reduced mechanical durability and structural integrity. Consequently, the material exhibits increased susceptibility to load-induced plastic deformation and crack propagation along grain boundaries. At the highest substitution level, Hv decreases from 0.333 GPa to 0.280 GPa across the same range of applied loads, confirming the adverse impact of over-doping on mechanical performance. A near-linear relationship between ρ and Hv is observed, validating bulk density as a predictive metric for key mechanical design features in Bi-2212 systems. Additionally, key mechanical performance metrics, including load-independent Hv results, are analyzed within the plateau limit (PL) regions of Nd-substituted Bi-2212 structures using established theoretical models to elucidate structure-property relationships and predict service life and material reliability under practical application conditions. Comparative analysis reveals that the Indentation-Induced Cracking (IIC) model provides the most accurate description of the mechanical response in the doped systems. The experimental findings and theoretical results highlight the critical role of rare-earth substitution at an optimal concentration level in tuning lattice cohesion, defect tolerance, and mechanical resilience, establishing x = 0.01 for Nd/Bi-substituted Bi-2212 as a promising candidate for high-performance structural ceramic applications