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Fast Neuronal Calcium Signals in Brain Slices Loaded With Fluo-4 AM Ester
No full textStaining brain slices with acetoxymethyl ester (AM) Ca2+ dyes is a straightforward procedure to load multiple cells, and Fluo-4 is a commonly used high-affinity indicator due to its very large dynamic range. It has been shown that this dye preferentially stains glial cells, providing slow and large Ca2+ transients, but it is questionable whether and at which temporal resolution it can also report Ca2+ transients from neuronal cells. Here, by electrically stimulating mouse hippocampal slices, we resolved fast neuronal signals corresponding to 1%–3% maximal fluorescence changes. Specifically, by recording Ca2+ fluorescence at 2000 frames/s from multiple sites both in the CA3 and in the CA1 regions, we observed that the signal measured near the stimulating electrode, positioned on the mossy fibre pathway, was not blocked by perfusion with 10 μM NBQX and 50 μM AP5, preventing excitatory synaptic transmission. In contrast, this signal was fully blocked by additional perfusion with 1 μM tetrodotoxin, inhibiting voltage-gated Na+ channels and neuronal action potentials. We also present recordings obtained in the presence of 10 μM of the GABAA receptor antagonist bicuculline, or of 50 μM of the voltage-gated K+ channel inhibitor 4-aminopyridine, exhibiting a wide propagation of the signal from CA3 to CA1 regions under conditions that mimic epileptic seizures. Altogether, while Fluo-4 AM remains a preferable indicator for reporting Ca2+ signals from astrocytes at slow temporal resolution, we demonstrated that it can be also utilised for analysing fast neuronal network activity elicited by electrical stimulation in brain slices
Optimization of high efficiency blue emissive N-, S-doped graphene quantum dots
No full textGraphene quantum dots (GQDs) with bright emission at short wavelengths have attracted much attention due to their importance in various applications such as light-emitting diodes. During or after synthesis, several parameters can significantly improve the optical properties of GQDs. This study presents a facile solvothermal method with low-cost precursors using glutamic acid as the carbon source to realize blue emitting GQDs. The positive effects of urea and 1-octanethiol as nitrogen and sulfur dopants on the photoluminescence quantum yield (PLQY) of the prepared GQDs were demonstrated and optimized. The results confirmed the formation of 2.2 nm nanoparticles with a bright emission around 381 nm with a full width at half maximum of 58 nm and a PLQY approaching 70 %. The decay lifetime of the emission also showed a tri-exponential profile with an average lifetime of 2.4 ns. The simplicity of the preparation method without any post-treatment process, together with a high PLQY of 70 % at short wavelengths, nominates the prepared GQDs for optoelectronics and UV light-driven biological purposes
Machine learning insights into forecasting solar power generation with explainable AI
No full textMachine learning (ML) algorithms can provide highly accurate predictions, but their complexity often makes them difficult to interpret due to their black-box nature. Combining ML and Explainable Artificial Intelligence (XAI) makes these models more transparent and enables users to understand the key factors behind the predictions. This paper presents a variety of ML approaches combined with XAI to predict solar power generation, aiming to optimize energy management in smart grids. For this purpose, five different ML algorithms, namely Random Forest, Gradient Boosting, eXtreme Gradient Boosting, Light Gradient Boosting Machine, and Decision Three, and three different XAI models, namely Shapley Additive Explanation, Local Interpretable Model-agnostic Explanations, and Permutation Feature Importance were investigated. According to the findings, the Light Gradient Boosting Machine achieved the best performance, showing the lowest root mean squared error of 0.088, mean squared error of 0.007749, mean absolute error of 0.052896, and the highest R-squared value of 0.842645. XAI techniques provided detailed, actionable insights into the model behavior, helping to identify key features influencing predictions. While Permutation Feature Importance identified key features, Shapley Additive Explanations showed how this feature interacts with others, and Local Interpretable Model-Agnostic Explanations clarified individual predictions. This research provides the most comprehensive understanding in the literature on feature impact and model interpretability for solar power forecasting and contributes to sustainable energy applications by combining ML prediction with XAI interpretability for effective smart grid integration
Lyrics of Gabdulla Tukay translated into Russian: history and poetics
No full textThe book is devoted to the study of the history of translations of the lyrics into Russian by the famous Tatar poet of the early 20th century Gabdulla Tukay. Using the example of significant works of the poet, the author makes a historical and artistic analysis of the translations and identifies the features in literary translations. The book is addressed to everyone who deals with the problems of Tatar literature, translations, students and lovers of literature and art.</p
Characterization and monitoring of copper tolerance of Pseudomonas syringae pv. tomato strains from tomato plants in Turkey
No full textTomato is grown in a wide range of climatic conditions and is one of the most important vegetable crops in the world. In this study, we have collected symptomatic leaves of tomato bacterial speck caused by Pseudomonas syringae pv. tomato (Pst) in different districts of Turkey (mainly Mediterranean region) during 2010–2023. The putative causal agent was identified based on the basis of phenotypic, biochemical, genotypic, and pathogenicity tests. All tested strains were pathogenic on tomato, but not on lemon fruit, were confirmed by LOPAT 1a (+ –− +), and produced 650 bp band size in PCR. The genotypic test for differentiation of coronatine-producing bacteria by PCR and pathogenicity tests on lemon fruit allowed clear differentiation of the 78 Pst strains from Pseudomonas syringae pv. syringae (Pss). Among the 78 strains tested using in vitro assay, no copper-sensitive strains were detected, and all strains (n = 77) except one strain (S Pst 2) were resistant with minimum inhibition concentration (MIC) values 1.80–2.60 mM of copper sulfate. Four out of 78 Pst strains (YA-568, S Pst 30, S Pst 46 and S Pst 50) obtained from different tomato cultivars in Turkey possessed the CusCBA genes. All types of copper-based compounds controlled the disease symptoms on tomato plants, and thus, they were considered to be effective to some extent in bacterial speck management. To the best of our knowledge, this is the first study indicating that cusCBA genes responsible for copper resistance are present in Pst strains from tomato cultivars in Turkey
NLRP3 is a BMI-independent mediator of stable COPD
No full textPurposeThe inflammatory response in animal models of chronic obstructive pulmonary disease (COPD) is activated by the NLR-family-pyrin-domain-containing-3 (NLRP3) inflammasome pathway, which is also known to play a role in obesity-related inflammation. The NLRP3/caspase-1/interleukin (IL)-1 beta pathway might be involved in the progression of COPD with increasing body mass index. To our knowledge, no previous studies have explored the role of NLRP3 inflammasome markers in linking COPD and obesity. Here, we aim to investigate this potential connection by examining levels of NLRP3, caspase-1, IL-1 beta, and IL-17A and to provide additional data on the expression of these molecules in relation to smoking status and COPD severity.MethodsA case-control study was conducted between July 2020 and March 2023. Peripheral blood mononuclear cells were isolated, and total RNA was extracted for real-time quantitative polymerase chain reaction (qPCR) analysis to measure the expression levels of inflammasome molecules.Results29 subjects who were diagnosed with stable COPD and 32 controls were included in the data analysis. NLRP3 and IL-17A but not caspase-1 or IL-1 beta expression was significantly greater in the COPD group than in the control group. We detected a significant increase in NLRP3 levels in the smoker COPD group (p = 0.009) and nonsmoker COPD group (p = 0.045) compared with those in the nonsmoker control group. There was no significant correlation between BMI and the inflammasome markers.ConclusionAs proinflammatory biomarkers, NLRP3 and IL-17A are prominent in stable COPD patients. Smoking may trigger NLRP3-mediated inflammation in stable COPD patients. The expression levels of NLRP3 inflammasome molecules did not differ in terms of disease severity or BMI
The Prevalence, Serogroup Distribution and Risk Factors of Meningococcal Carriage in Children, Adolescents and Young Adults in Turkey Meningo-Carr-TR Study PART 3: COVID-19 Pandemic Situation
No full textBackground:The prevalence of meningococcal carriage and serogroup distribution is crucial for assessing the epidemiology of invasive meningococcal disease, forecasting outbreaks and formulating potential immunization strategies. Following the meningococcal carriage studies conducted in Turkey in 2016 and 2018, we planned to re-evaluate meningococcal carriage in children, adolescents and young adults during the COVID-19 pandemic period.Methods:In the MENINGO-CARR-3 study, we collected nasopharyngeal samples from 1585 participants 0-24 years of age, across 9 different centers in Turkey. We used polymerase chain reaction and serogroup distribution to determine how common it is for people to carry Neisseria meningitidis.Results:The overall meningococcal carriage rate was 8.5% (n = 134). The serogroup distribution was as follows: serogroup A, 6%; serogroup B, 30.6%; serogroup W, 12.7%; serogroup Y, 3.7%; serogroup X, 1.5% and nongroupable as 45.5%. The highest carriage rate was found in 15-17-year-old adolescents (24.1%, 17.9%, and 20.2%, respectively). The carriage rate was higher among participants who had a previous COVID-19 infection (P = 0.05; odds ratio: 1.95; 95% confidence interval: 1.11-3.44). The nasopharyngeal carriage rate was also higher than in the 2016 and 2018 studies (8.45% vs. 6.3% and 7.5%, respectively), and the most prevalent groupable serogroup was B during this study period, followed by serogroup W in 2016 and serogroup X in 2018.Conclusions:The present study found that meningococcal carriage was higher during the post-COVID-19 pandemic period, especially in adolescents and young adults. Severe acute respiratory syndrome coronavirus-2 virus itself and/or pandemic mitigation strategies may affect both meningococcal carriage and serogroup distribution. Serogroup distribution varies between years, and further immunization strategies, including adolescent immunization, may play a role in controlling invasive meningococcal disease
SBA*: An efficient method for 3D path planning of unmanned vehicles
No full textRecently, researchers have stated that the movement of unmanned vehicles (UVs) in 3D environments is more complex compared to 2D due to extra height and depth dimensions, and they have focused on the development of UV technology in this direction. Especially in path planning problems, studies on different parameters such as time, distance and energy consumption have gained importance. This paper focuses on path planning efficiency in complex 3D environments and proposes a method called Segment Based A* (SBA*), which runs on graphs created using random nodes. In this method, the path initially planned with A* on a global graph is divided into segments, and new local graphs are created on these segments for more efficient path planning. Extensive simulations in both 2D and 3D environments with various obstacle configurations demonstrate that SBA* significantly outperforms traditional algorithms in terms of key performance metrics including path length, total rotation angle, number of sharp turns and smoothness ratio. These improvements indicate that SBA* not only enhances path efficiency but also considerably reduces energy consumption, making it a valuable contribution to practical applications in UV technology
Structurally Colored Physically Unclonable Functions with Ultra-Rich and Stable Encoding Capacity
No full textIdentity security and counterfeiting assume a critical importance in the digitized world. An effective approach to addressing these issues is the use of physically unclonable functions (PUFs). The overarching challenge is a simultaneous combination of extremely high encoding capacity, stable operation, practical fabrication, and a widely available readout mechanism. Herein this challenge is addressed by designing an optical PUF via exploiting the thickness-dependent structural color formation in nanoscopic films of ZnO. The structural coloration ensures authentication using widely available bright-field-based optical readout, whereas the metal oxide provides a high degree of structural stability. True physical randomness in spatial position is achieved by physical vapor deposition of ZnO through stencil masks that are fabricated by pore formation in polycarbonate membranes via photothermal processing of stochastically positioned plasmonic nanoparticles. Structural coloration emerges from thin film interference as confirmed via simulation studies. The rich color variation and stochastic definition of domain size and geometry result in chaotic features with an encoding capacity that approaches (6.4 x 105)(2752x2208). Deep learning-based authentication is further demonstrated by transforming these chaotic features into unbreakable codes without field limitations. This ultra-rich encoding capacity, coupled with outstanding thermal and chemical stability, forms a new cutting edge for state-of-the-art PUF-based encoding systems