Search Results (18)

Background and Objectives: Chronic obstructive pulmonary disease (COPD) is heterogeneous, and phenotype-based classification may better capture differences in clinical burden and healthcare needs beyond standard GOLD categories. We aimed to describe the distribution of GesEPOC COPD phenotypes in Turkey and compare their demographic, clinical, functional, radiological, treatment, and healthcare utilization profiles. Materials and Methods: DIPTUR was a multicenter, observational, cross-sectional study conducted prospectively in 26 centers across 17 Turkish cities (October 2019–June 2021). Stable COPD patients (≥40 years; post-bronchodilator FEV1/FVC < 0.7) without exacerbation or major treatment modification within the previous four weeks were enrolled consecutively. Phenotypes were assigned per GesEPOC: exacerbator with emphysema (EE), exacerbator with chronic bronchitis (ECB), asthma–COPD overlap (ACO), and non-exacerbator (NE). Frequent exacerbators were defined as patients who experienced two or more exacerbations during the 12 months preceding enrollment, based on medical records and patient reports. Results: Among 894 patients, phenotype distribution was NE 44.1%, ECB 26.2%, EE 20.5%, and ACO 9.3%. Male predominance was observed across groups (80–89%; p = 0.006). Active smoking was most frequent in ECB (37.6%; p < 0.001), and BMI was lowest in EE (p < 0.001). Comorbidity patterns differed, with hypertension (p < 0.001), diabetes mellitus (p = 0.029), and heart failure (p < 0.001) most prevalent in ECB. Pulmonary function (FEV1 and FVC) was lowest in EE (both p < 0.001), and severe airflow limitation (GOLD III–IV) was most common in EE and ECB (p < 0.001). Dyspnea (mMRC ≥ 2) was more frequent in EE/ECB than in ACO/NE (p < 0.001). Emphysematous changes on thoracic CT predominated in EE (91.7%; p < 0.001). Long-term oxygen therapy was most common in EE (32.4%; p < 0.001). Emergency admissions, hospitalizations, and total length of stay were markedly higher in EE and ECB than in ACO and NE (all p < 0.001). Conclusions: COPD phenotypes in Turkey show substantial heterogeneity in clinical, functional, radiological, and utilization domains. Exacerbator phenotypes—particularly EE and ECB—represent higher-burden groups, supporting phenotype-oriented management and closer monitoring beyond GOLD classification. Full article

The pineal gland is a key component of the avian circadian system, responsible for melatonin (MLT) secretion that reflects and regulates daily rhythmicity. While the post-hatching turkey is known for its highly sensitive and efficient pineal system, the functional development of this gland during embryogenesis has not been described. To determine the measurable onset and regulation of MLT secretion, pineal glands from turkey embryos aged 22, 24, and 26 days (ED 22–26) were incubated in a superfusion culture under various light conditions and with or without norepinephrine (NE). MLT concentrations in the medium were measured by radioimmunoassay. Under the experimental conditions, MLT secretion was first reliably measurable at ED 22 and increased thereafter toward hatching. Under a 12L:12D cycle, pinealocytes exhibited a stable circadian rhythm with a fourfold amplitude between night and day. The glands adapted to a reversed light–dark cycle and responded strongly to a 3 h nocturnal light pulse with a 30% decrease in MLT levels. Rhythmic MLT secretion persisted under constant light or darkness, indicating an active endogenous oscillator. NE markedly suppressed MLT secretion in all embryos, confirming the early development of adrenergic regulation. Thus, by ED 22 the embryonic turkey pineal exhibits photosensitivity, endogenous rhythmicity, and NE responsiveness, although secretion at earlier stages cannot be excluded due to detection limits. These results fill a gap in understanding avian pineal ontogeny and establish the turkey embryo as a good model for studying the early development of circadian regulation in birds. Full article

Background & Objective: Stroke remains a leading cause of mortality and long-term disability worldwide, demanding rapid and accurate diagnosis to improve patient outcomes. Computed tomography (CT) scans are widely used in emergency settings due to their speed, availability, and cost-effectiveness. This study proposes an artificial intelligence (AI)-based framework for multiclass stroke classification (ischemic, hemorrhagic, and no stroke) using CT scan images from the Ministry of Health of the Republic of Turkey. Methods: We adopted MaxViT, a state-of-the-art Vision Transformer (ViT)-based architecture, as the primary deep learning model for stroke classification. Additional transformer variants, including Vision Transformer (ViT), Transformer-in-Transformer (TNT), and ConvNeXt, were evaluated for comparison. To improve model generalization and handle class imbalance, classical data augmentation techniques were applied. Furthermore, explainable AI (XAI) was integrated using Grad-CAM++ to provide visual insights into model decisions. Results: The MaxViT model with augmentation achieved the highest performance, reaching an accuracy and F1-score of 98.00%, outperforming the baseline Vision Transformer and other evaluated models. Grad-CAM++ visualizations confirmed that the proposed framework effectively identified stroke-related regions, enhancing transparency and clinical trust. Conclusions: This research contributes to the development of a trustworthy AI-assisted diagnostic tool for stroke, facilitating its integration into clinical practice and improving access to timely and optimal stroke diagnosis in emergency departments. Full article

Background/Objectives: Clostridium perfringens is a normal inhabitant of the intestinal tract of poultry, and it has the potential to induce cholangiohepatitis and necrotic enteritis (NE). The poultry industry suffers significant financial losses because of NE, and treatment becomes more challenging due to resistant C. perfringens strains. Methods: The antimicrobial and antibiofilm activities of cellulose nanocrystals/zinc oxide nanocomposite (CNCs/ZnO) were assesses against pan drug-resistant (PDR) C. perfringens isolated from chickens and turkeys using phenotypic and molecular assays. Results: The overall prevalence rate of C. perfringens was 44.8% (43.75% in chickens and 58.33% in turkeys). Interestingly, the antimicrobial susceptibility testing of C. perfringens isolates revealed the alarming PDR (29.9%), extensively drug-resistant (XDR, 54.5%), and multidrug-resistant (MDR, 15.6%) isolates, with multiple antimicrobial resistance (MAR) indices ranging from 0.84 to 1. All PDR C. perfringens isolates could synthesize biofilms; among them, 21.7% were strong biofilm producers. The antimicrobial potentials of CNCs/ZnO against PDR C. perfringens isolates were evaluated by the agar well diffusion and broth microdilution techniques, and the results showed strong antimicrobial activity of the green nanocomposite with inhibition zones’ diameters of 20–40 mm and MIC value of 0.125 µg/mL. Moreover, the nanocomposite exhibited a great antibiofilm effect against the pre-existent biofilms of PDR C. perfringens isolates in a dose-dependent manner [MBIC50 up to 83.43 ± 1.98 for the CNCs/ZnO MBC concentration (0.25 μg/mL)]. The transcript levels of agrB quorum sensing gene and pilA2 type IV pili gene responsible for biofilm formation were determined by the quantitative real time-PCR technique, pre- and post-treatment with the CNCs/ZnO nanocomposite. The expression of both genes downregulated (0.099 ± 0.012–0.454 ± 0.031 and 0.104 ± 0.006–0.403 ± 0.035, respectively) when compared to the non-treated isolates. Conclusions: To the best of our knowledge, this is the first report of CNCs/ZnO nanocomposite’s antimicrobial and antibiofilm activities against PDR C. perfringens isolated from chickens and turkeys. Full article

The present research’s main objective was to apply thorough exploration approaches that combine remote sensing data with geochemical sampling and analysis to predict and identify potential chromitite locations in a complex geological site, particularly in rugged mountainous terrain, and differentiate the ultramafic massif containing chromitite orebodies from other lithologies. The ultramafic massif forming the mantle section of the Kırdağ ophiolite, located within the Erzurum–Kars Ophiolite Zone and emerging in the east of Oltu district (Erzurum, NE Turkey), was selected as the study area. Optimum index factor (OIF), false-color composite (FCC), decorrelation stretch (DS), band rationing (BR), minimum noise fraction (MNF), and principal and independent component analyses (PCA-ICA) were performed to differentiate the lithological features and identify the chromitite host formations. The petrography, mineral chemistry, and whole-rock geochemical properties of the harzburgites, which are the host rocks of chromitites in the research area, were evaluated to verify and confirm the remote sensing results. In addition, detailed petrographic properties of the pyroxenite and chromitite samples are presented. The results support the existence of potential chromitite formations in the mantle section of the Kırdağ ophiolite. Our remote sensing results also demonstrate the successful detection of the spectral anomalies of this ultramafic massif. The mineral and whole-rock geochemical features provide clear evidence of petrological processes, such as partial melting and melt–peridotite interactions during the harzburgite formation. The chromian spinels’ Cr#, Mg#, Fe³⁺, Al₂O₃, and TiO₂ concentrations indicate that the harzburgite formed in a fore-arc environment. The Al₂O₃ content and Mg# of the pyroxenes and the whole-rock Al₂O₃/MgO ratio and V contents of the harzburgite are also compatible with these processes. Consequently, the combined approaches demonstrated clear advantages over conventional chromitite exploration techniques, decreasing the overall costs and supporting the occurrence of chromite production at the site. Full article

In our study, using the analysis of DNA barcodes and morphology (wing color, male genitalia, and female sphragis shape), we show that the group of species close to P. mnemosyne comprises the western and eastern phylogenetic lineages. The eastern lineage includes P. stubbendorfii, P. glacialis, and P. hoenei. The western lineage includes three morphologically similar species: P. mnemosyne (Western Eurasia), P. turatii (southwestern Europe), and P. nubilosus stat. nov. (Turkmenistan and NE Iran), as well as the morphologically differentiated P. ariadne (Altai). The latter species differs from the rest of the group in the presence of red spots on the wings. Parnassius mnemosyne s.s. is represented by four differentiated mitochondrial clusters that show clear association with specific geographic regions. We propose to interpret them as subspecies: P. mnemosyne mnemosyne (Central and Eastern Europe, N Caucasus, N Turkey), P. mnemosyne adolphi (the Middle East), P. mnemosyne falsa (Tian Shan), and P. mnemosyne gigantea (Gissar-Alai in Central Asia). We demonstrate that in P. ariadne, the red spots on the wing evolved as a reversion to the ancestral wing pattern. This reversion is observed in Altai, where the distribution areas of the western lineage, represented by P. ariadne, and the eastern lineage, represented by P. stubbendorfii, overlap. These two species hybridize in Altai, and we hypothesize that the color change in P. ariadne is the result of reinforcement of prezygotic isolation in the contact zone. The lectotype of Parnassius mnemosyne var. nubilosus Christoph, 1873, is designated. Full article

This study aimed to investigate groundwater vulnerability to pollution in the Upper Kelkit Valley (NE Turkey). For this purpose, vulnerability index maps were created using the generic DRASTIC and AHP-DRASTICLu models. The latter model was suggested by adding a parameter to the DRASTIC model and weighting its parameters with the analytical hierarchy process with the GIS technique. The results showed that areas with high and very high vulnerabilities are concentrated around the Kelkit Stream, which flows from east to west in the central part of the study area. In contrast, areas with low and very low vulnerability classes are located in the northern and southern parts of the study area. To validate the model results, a physicochemical characterization of groundwater samples and their corresponding vulnerability index values were statistically compared using the Spearman correlation method. In addition, the single-parameter sensitivity method was applied to analyze the models’ sensitivities. Results revealed a stronger correlation between the vulnerability index values of the AHP-DRASTICLu model (compared to the DRASTIC model) in terms of sulfate (R² = 0.75) and chloride (R² = 0.76), while there was a slightly weaker correlation for the electrical conductivity (R² = 0.65) values of the groundwater samples. Sensitivity analysis indicated that the vadose zone, aquifer media, and land use are the most influential parameters responsible for the highest variation in the vulnerability index. Generally speaking, the results indicated that the AHP-DRASTICLu model performs better than the DRASTIC model for investigating groundwater vulnerability to pollution in the Upper Kelkit Valley. Full article

On 6 February 2023, a powerful earthquake at the border between Turkey and Syria caused catastrophic consequences and was, unfortunately, one of the deadliest earthquakes of the recent decades. The moment magnitude of the earthquake was estimated to be 7.8, and it was localized in the Kahramanmaraş region of Turkey. This article aims to investigate the behavior of more than 50 different lithosphere–atmosphere–ionosphere (LAI) anomalies obtained from satellite data and different data services in a time period of about six months before the earthquake to discuss the possibility of predicting the mentioned earthquake by an early warning system based on various geophysical parameters. In this study, 52 time series covering six months of data were acquired with: (i) three identical satellites of the Swarm constellation (Alpha (A), Bravo (B) and Charlie (C); and the analyzed parameters: electron density (Ne) and temperature (Te), magnetic field scalar (F) and vector (X, Y and Z) components); (ii) the Google Earth Engine (GEE) platform service data (including ozone, water vapor and surface temperature), (iii) the Giovanni data service (including the aerosol optical depth (AOD), methane, carbon monoxide and ozone); and (iv) the USGS earthquake catalogue (including the daily seismic rate and maximum magnitude for each day), around the location of the seismic event from 1 September 2022 to 17 February 2023, and these were analyzed. The results show that the number of seismic anomalies increased since about 33 days before the earthquake and reached a peak, i.e., the highest number, one day before. The findings of implementing the proposed predictor based on the Mamdani fuzzy inference system (FIS) emphasize that the occurrence of a powerful earthquake could be predicted from about nine days to one day before the earthquake due to the clear increase in the number of seismo-LAI anomalies. However, this study has still conducted a posteriori, knowing the earthquake’s epicenter and magnitude. Therefore, based on the results of this article and similar research, we emphasize the urgency of the creation of early earthquake warning systems in seismic-prone areas by investigating the data of different services, such as GEE, Giovanni and various other global satellite platforms services, such as Swarm. Finally, the path toward earthquake prediction is still long, and the goal is far, but the present results support the idea that this challenging goal could be achieved in the future. Full article

New-generation technologies on vehicles provide many advantages in terms of cost, time, and the environment in the transportation, logistics, freight, and delivery service sectors. This study aimed to measure the effect of using e-scooter vehicles in mail delivery on the energy cost and delivery time in Turkey. Considering the number of test drives in e-scooter applications of potential regions, the amount of energy consumption and driving time data were used. The number of test drives for each e-scooter was assumed as a package or postal delivery amount. The methodology of this study consisted of measuring the effect of input parameters on output variables using the linear response optimization regression method and minimizing the amount of energy consumed and delivery time. The nine input variables and two output variables based on the test drive were analyzed in this study. The distance to the delivery address, region where the delivery address was located, and temperature were found to be statistically significant predictors of the amount of energy required for delivery. The statistical significance levels of time zone, distance, temperature, rainfall, and region factors were calculated as 0.053, 0.001, 0.0033, 0.044, and 0.042, respectively. Driver age, data time zone, distance, wind speed, and delivery region factors affected the time required for delivery with an e-scooter. The statistical significance levels of these factors were calculated as 0.02, 0.001, 0.001, 0.043, and 0.001, respectively. Additionally, N (p; 0.042), NE (p; 0.030), and W (p; 0.057) wind directions directly influenced the delivery time. SE (p; 0.017) was the only wind direction that statistically significantly affected energy consumption. The objective functions were estimated by calculating the optimum values of the input parameters for the minimum energy consumption and delivery time. The optimum values of both input and output variables were calculated based on the desirability values of the optimization models, which were in the optimum solution set. The average data of the optimum values of the objective functions were computed as 2.83 for the number of tests and TRY 0.021 (per 0.098 km) for the energy cost required for delivery. The necessity of using e-scooters, which are more environmentally friendly, economical, and time-saving than traditional delivery vehicles, in postal delivery service is among the prominent suggestions of this study. Full article

In agricultural production, it is important to determine where input usage saving can be implemented by taking energy use into consideration and to analyze the greenhouse gas emissions of agricultural activities. This study has been conducted to review orange (Citrus sinensis L.) production in terms of energy balance and greenhouse gas (GHG) emissions. This study was carried out during the 2015/2016 production season in Adana, a province in Turkey. Energy balance and GHG emissions have been defined by calculating the inputs and outputs of agricultural nature used in orange production. The findings of the study indicate that the distribution of energy inputs in orange production are 11,880 MJ ha⁻¹ (34.10%) of electricity, 10,079.75 MJ ha⁻¹ (28.93%) of chemical fertilizer energy, 7630 MJ ha⁻¹ (21.90%) of chemical energy, 3052 MJ ha⁻¹ (8.76%) of diesel fuel energy, 1348.91 MJ ha⁻¹ (3.87%) of human labor energy, 378 MJ ha⁻¹ (1.09%) of irrigation water energy, 351.22 MJ ha⁻¹ (1.01%) of machinery energy and 118.80 MJ ha⁻¹ (0.34%) of lime energy. In total, input energy (IE) in orange production has been calculated as 34,838.68 MJ ha⁻¹ and the output energy (OE) has been calculated as 95,000 MJ ha⁻¹. Energy use efficiency (EUE), specific energy (SE), energy productivity (EP) and net energy (NE) have been calculated as 2.73, 0.70 MJ kg⁻¹, 1.44 kg MJ⁻¹ and 60,161.32 MJ ha⁻¹, respectively. The total energy input in the production of oranges was divided into: 47.82% direct, 52.18% indirect, 4.96% from renewable sources and 95.04% from non-renewable sources. The GHG emissions figure for orange production was 3794.26 kg CO_2–eq ha⁻¹, with electricity having the greatest share, 1983.96 (52.29%); the GHG ratio was 0.08 kg CO_2–eq kg⁻¹. According to the results, the production of orange was considered to be profitable in terms of EUE. Full article

This study contributes to our understanding of the evolution of Halılar Cu-Pb (±Zn) mineralization (NW Turkey) based on mineralogical and geochemical results and sulfur isotope data. The study area represents local Cu-Pb with some Zn brecciated-stockwork vein type mineralization along the NE–SW fault gouge zone at the lower boundary of the Sakarkaya and Düztarla granitoid rocks. Two main zones, consisting of sericite–quartz–chlorite ± kaolinite ± pyrite (i.e., zone-1) and calcite–epidote–albite ± chlorite ± sericite (i.e., zone-2), were observed within the central ore mineral zone at the mining site. Different mineralization assemblages were recorded; the main ore mineral contains chalcopyrite, galena, pyrite, and sphalerite within alteration zone-1, and the oxidation/supergene mineralization includes covellite and goethite. The mass balance calculations show that the samples of zone-1 show an increase in SiO₂, Fe₂O₃, K₂O, and LOI along with Ag, As, Cu, Mo, Pb, S, Sb, and Zn, reflecting high pyritization with sericitization and silicification. On the other hand, the samples from zone-2 are rich in CaO; Na₂O; P₂O₅; TiO₂; LOI; and carbon-reflecting calcite, epidote, and albite alterations. A uniform magmatic sulfur source of Halılar sulfides is suggested by their mean δ³⁴S value of −1.62‰. Furthermore, the primary metal source is metasediments and intrusive Düztarla granitoid magmatism. These observations suggest that the Halılar metasediment-hosted Cu-Pb (±Zn) mineralization was formed by epigenetic hydrothermal processes after sedimentation/diagenesis and metamorphism. Full article

Plant genetic diversity has a significant role in providing traits that can help meet future challenges, such as the need to adapt crops to changing climatic conditions or outbreaks of disease. Our aim in this study was to evaluate the diversity of 61 forage pea specimens (P. sativum ssp. arvense L.) collected from the northeastern Anatolia region of Turkey using 28 simple sequence repeat (SSR) markers. These primers generated a total of 82 polymorphic bands. The number of observed alleles (Na) per primer varied from 2 to 4 with a mean of 2.89 alleles/locus. The mean value of expected heterozygosity (Exp-Het = 0.50) was higher than the mean value of observed heterozygosity (Obs-Het = 0.22). The mean of polymorphic information content (PIC) was 0.41 with a range of 0.03–0.70. The mean number of effective alleles (Ne) was found to be 2.15, Nei’s expected heterozygosity (H) 0.49, and Shannon’s information index (I) 0.81. Cluster analysis through the unweighted pair-group mean average (UPGMA) method revealed that 61 forage pea landraces were divided into three main clusters. Genetic dissimilarity between the genotypes, calculated with the use of NTSYS-pc software, varied between 0.10 (G30 and G34) and 0.66 (G1 and G32). Principal coordinate analysis (PCoA) revealed that three principal coordinates explained 51.54% of the total variation. Moreover, population structure analysis showed that all genotypes formed three sub-populations. Expected heterozygosity values varied between 0.2669 (the first sub-population) and 0.3223 (third sub-population), with an average value of 0.2924. Average population differentiation measurement (Fst) was identified as 0.2351 for the first sub-population, 0.3838 for the second sub-population, and 0.2506 for the third sub-population. In general, current results suggest that SSR markers could be constantly used to illuminate the genetic diversity of forage pea landraces and can potentially be incorporated into future studies that examine the diversity within a larger collection of forage pea genotypes from diverse regions. Full article

The Uzundere district, which is located in NE Turkey, has attractive rural tourism areas with noticeable potentials and rural tourism development activities. This paper concentrates on sustainability development of rural tourism. Sustainable tourism concentrates to conserve environmental and cultural resources and emphasizes on the responsibility of tourists and participation of local people for economic growth of the region. In this study, Delphi method is used to identify important factors for evaluating sustainable development of rural tourism in the Uzundere region. It consists of thirty-three indicators in four dimensions: service quality, facilities, management system, and results. Indicators are advisers for future tourism development activities at all levels of planning. These indicators plainly reflect the situation of area tourism. In this study, a questionnaire was prepared to evaluate the rural tourism developments in the Uzundere region, based on the Delphi method. Expert opinions were taken with the participation of ten experts of the region. This study showed that tourism development projects in this region are promising in order to achieve the goals of sustainable rural tourism. In addition, in cases identified during the research, there is a need to develop approaches and experiences to address the relevant shortcomings and deficiencies. Full article

Italian autochthonous turkey breeds are an important reservoir of genetic biodiversity that should be maintained with an in vivo approach. The aim of this study, part of the TuBAvI national project on biodiversity, was to use run of homozygosity (ROH), together with others statistical approaches (e.g., Wright’s F-statistics, principal component analysis, ADMIXTURE analysis), to investigate the genomic diversity in several heritage turkey breeds. We performed a genome-wide characterization of ROH-rich regions in seven autochthonous turkey breeds, i.e., Brianzolo (Brzl), Bronzato Comune Italiano (BrCI), Bronzato dei Colli Euganei (CoEu), Parma e Piacenza (PrPc), Nero d’Italia (NeIt), Ermellinato di Rovigo (ErRo) and Romagnolo (Roma). ROHs were detected based on a 650K SNP genotyping. ROH_islands were identified as homozygous ROH regions shared by at least 75% of birds (within breed). Annotation of genes was performed with DAVID. The admixture analyses revealed that six breeds are unique populations while the Roma breed consists in an admixture of founder populations. Effective population size estimated on genomic data shows a numeric contraction. ROH_islands harbour genes that may be interesting for target selection in commercial populations also. Among them the PTGS2 and PLA2G4A genes on chr10 were related to reproduction efficiency. This is the first study mapping genetic variation in autochthonous turkey populations. Breeds were genetically different among them, with the Roma breed proving to be a mixture of the other breeds. The ROH_islands identified harboured genes peculiar to the selection that occurred in heritage breeds. Finally, this study releases previously undisclosed information on existing genetic variation in the turkey species. Full article

In this study, geographic information system (GIS)-based, analytic hierarchy process (AHP) techniques were used to identify groundwater potential zones to provide insight to decisionmakers and local authorities for present and future planning. Ten different geo-environmental factors, such as slope, topographic wetness index, geomorphology, drainage density, lithology, lineament density, rainfall, soil type, soil thickness, and land-use classes were selected as the decision criteria, and related GIS tools were used for creating, analysing and standardising the layers. The final groundwater potential zones map was delineated, using the weighted linear combination (WLC) aggregation method. The map was spatially classified into very high potential, high potential, moderate potential, low potential, and very low potential. The results showed that 21.5% of the basin area is characterised by high to very high groundwater potential. In comparison, the very low to low groundwater potential occupies 57.15%, and the moderate groundwater potential covers 21.4% of the basin area. Finally, the GWPZs map was investigated to validate the model, using discharges and depth to groundwater data related to 22 wells scattered over the basin. The validation results showed that GWPZs classes strongly overlap with the well discharges and groundwater depth located in the given area. Full article