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Multiple resistance to EPSPS and ALS inhibitors in Palmer amaranth (<i>Amaranthus palmeri</i>) identified in Turkey
No full text<p>Amaranthus palmeri was first reported in Turkey in 2016, and an immediate heavy infestation of the weed was found in fruit orchards and summer crops such as maize, cotton, and sunflower. There have been farmers' complaints about the ineffective control of Palmer amaranth through the use of glyphosate and some sulfonylureas herbicides. Hence, this study aimed to determine the possible herbicide resistance evolution in Palmer amaranth against glyphosate and acetolactate synthase (ALS) herbicides. Seeds of 21 Palmer amaranth populations were collected from five provinces of Turkey where control problems with glyphosate and ALS inhibitors were reported in maize fields. Seeds of certain biotypes categorized as resistant or susceptible were grown to obtain the F-2 generation. A single-dose experiment determined the possible resistance to ALS inhibitors and glyphosate among the 21 populations. Of this, 18 populations were included in the subsequent dose-response experiments due to evident survival. Based on ED50 values from the dose-response experiment, SNU-04 and ADN-21 biotypes had the highest resistance index for glyphosate which was more than 7. The biotypes ADN-21, OSM-15, and DIR-09 recorded the highest ED50 value with a resistance index of 9.21-10.35 after nicosulfuron application. Whereas, the biotypes SNU-04, OSM-15, and ADN-21 were with the highest ED50 value and resistance index of 6.41-7.44, after the application of foramsulfuron + iodosulfuron methyl-sodium. The increase in genomic 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) copy number has been observed in suspected cases that have been accepted as the molecular basis for the development of resistance against glyphosate. The sequence alignment results for the ALS gene contained Ala122Val and Pro197Arg mutations related to target-site resistance against ALS herbicides.</p>
Comparison of Tissue and Urine Microbiota in Male, Intervention Naive Patients with and without Non-Invasive Bladder Cancer
No full text<p>Introduction: To investigate the presence of dysbiosis in patients with naive bladder cancer. Methods: Twelve male patients with non-invasive bladder cancer and twelve age-matched healthy males had midstream urine and tissue samples taken. A history of endourological interventions was determined as an exclusion criterion, ensuring that the study was designed solely with na & iuml;ve participants. The bacterial 16s ribosomal RNA V3-V4 regions were used to examine urine and tissue samples. We compared the microbiota composition of the bladder cancer and control groups. Results: Escherichia Shigella (p < 0.001), Staphylococcus (p < 0.001), Delftia (p < 0.001), Acinetobacter (p < 0.001), Corynebacterium (p < 0.001), and Enhydrobacter (p < 0.001) were abundant in bladder cancer tissue samples. Escherichia Shigella (p < 0.001), Ureaplasma (p < 0.001), Lactobacillus (p = 0.005), Stenotrophomonas (p < 0.001), Streptococcus (p < 0.001), Corynebacterium (p < 0.001), and Prevotella (p = 0.039) were abundant in bladder cancer urine samples. Midstream urine has a sensitivity of 83% for detecting dysbiotic bacteria in cancer tissue. Conclusions: Our research is the first microbiota study of bladder cancer done with naive patients who have never had an endourological intervention. Escherichia Shigella, Staphylococcus, Acinetobacter, Enhydrobacter, Delftia, Corynebacterium, and Pseudomonas were detected as dysbiotic bacteria in bladder cancer. The sensitivity of the midstream urine sample in detecting dysbiosis in tissue is 83%. (c) 2024 S. Karger AG, Basel</p>
Molecular characterization of some currants (<i>Ribes</i> species) from Türkiye using inter-primer binding site (iPBS) and simple sequence repeat (SSR) markers
No full text<p>This study was carried out to determine the genetic relationships and variation levels among currant genotypes and cultivars in T & uuml;rkiye. Ten currant cultivars and one hybrid Jostaberry cultivar, which are breeding products of Europe but are best known and have high commercial value in T & uuml;rkiye, were used. One black-fruited currant cultivar from T & uuml;rkiye was included. In addition, 14 currant genotypes naturally grown in T & uuml;rkiye were used. In this study, 14 retrotransposon-based inter-primer binding site (iPBS) and 10 microsatellite-based simple sequence repeat (SSR) markers were used for a total of 26 currant samples. By evaluating the allele profiles obtained from PCR and capillary electrophoresis with iPBS and SSR primers, the size range, average number of alleles, total number of alleles, number of polymorphic alleles, polymorphism rate, heterozygosity, polymorphism information content, marker index and discriminating power were determined successfully. In addition, unweighted pair group method with arithmetic mean (UPGMA) dendrograms and principal coordinate analysis (PCoA) were constructed and performed. The amounts of amplification product produced using iPBS and SSR markers for currant species with different fruit colours were also compared. In this study, it was proven that the level of genetic relatedness among currant cultivars and genotypes can be determined with high accuracy by iPBS markers. Moreover, the use of iPBS markers in currants was performed for the first time in this study. On the other hand, with the preferred SSR markers, the level of genetic relatedness among currants was successfully determined.</p>
Stripe Error Correction for Landsat-7 Using Deep Learning
No full text<p>Long-term time series satellite imagery became highly essential for analyzing earth cycles such as global warming, climate change, and urbanization. Landsat-7 satellite imagery plays a key role in this domain since it provides open-access data with expansive coverage and consistent temporal resolution for more than two decades. This paper addresses the challenge of stripe errors induced by Scan Line Corrector sensor malfunction in Landsat-7 ETM+ satellite imagery, resulting in data loss and degradation. To overcome this problem, we propose a Generative Adversarial Networks approach to fill the gaps in the Landsat-7 ETM+ panchromatic images. First, we introduce the YTU_STRIPE dataset, comprising Landsat-8 OLI panchromatic images with synthetically induced stripe errors, for model training and testing. Our results indicate sufficient performance of the Pix2Pix GAN for this purpose. We demonstrate the efficiency of our approach through systematic experimentation and evaluation using various accuracy metrics, including Peak Signal-to-Noise Ratio, Structural Similarity Index Measurement, Universal Image Quality Index, Correlation Coefficient, and Root Mean Square Error which were calculated as 38.5570, 0.9206, 0.7670, 0.7753 and 3.8212, respectively. Our findings suggest promising prospects for utilizing synthetic imagery from Landsat-8 OLI to mitigate stripe errors in Landsat-7 ETM+ SLC-off imagery, thereby enhancing image reconstruction efforts. The datasets and model weights generated in this study are publicly available for further research and development: https://github.com/ynsemrevrl/eliminating-stripe-errors.</p>
A switched full duplex MIMO architecture with digital linear and nonlinear cancellation
No full text<p>Enabling full duplex (FD) in MIMO systems is challenging due to increased hardware complexity and increased training overhead required for canceling not only self-interference (SI) but also cross-link-interference (CLI) signals, considering both linear and nonlinear effects on each stream. In this paper, we propose switched FD MIMO (FD-SW-MIMO) architecture as a low-complexity, low-overhead solution, which enables stream-based nonlinear estimation to be performed independently from channel estimation, so that those nonlinear reference signals are fed to linear SI and CLI cancellation stages. For improved performance at high transmit power levels, the Random Fourier Features- Least Mean Squares (RFF-LMS) algorithm is employed on the residual SI and CLI signals per stream. Our experiments conducted on a software-defined radio based 2x2 FD MIMO test setup reveal that the proposed FD-SW-MIMO architecture can provide up to 12 dB enhancement over linear only digital cancellation. The proposed architecture requires only minor hardware modification(s), avoiding active analog cancellation circuitry and extra Tx/Rx chains. Requiring the same training overhead as linear only cancellation, FD-SW-MIMO architecture can quadruple the rate of HD SISO for low to moderate transmit power levels, and for high transmit power levels, the HD SISO rate is tripled due to slightly increased overhead.</p>
A Novel Fuzzy-Based Integrated Drought Index (Fidi) For Holistic Basin Scale Drought Risk Evaluation
No full text<p>Drought is a complex and multidimensional natural hazard that affects various components of the hy drological cycle, with far-reaching socio-economic and environmental consequences. While numerous standardized drought indices such as the Standardized Precipitation Index (SPI), the Standardized Pre cipitation Evapotranspiration Index (SPEI), and the Standardized Streamflow Index (SSFI) are commonly used to quantify specific types of drought (e.g., meteorological or hydrological), they often fall short in providing a comprehensive representation of drought conditions. In this study, a novel Fuzzy-based Inte grated Drought Index (FIDI) is proposed to facilitate a more holistic assessment of drought by combining the complementary strengths of SPI, SPEI, and SSFI within a unified framework. The aim is to transform these well-established indices into fuzzy membership functions representing various levels of drought sever ity, and to integrate them using fuzzy logic rules that reflect the compound nature of drought processes. This approach is expected to improve the interpretation of drought severity through linguistically defined classes, which may be more accessible for decision-makers and stakeholders. In contrast to single-variable indices that provide partial insights, the proposed FIDI framework is designed to capture the full spectrum of drought dynamics at the basin scale, including meteorological and hydrological dimensions. Further more, the performance of FIDI will be comparatively evaluated against its constituent indices as well as a multivariate standardized drought index derived from copula-based joint modeling of precipitation and streamflow. The anticipated outcome is a robust, scalable, and policy-relevant tool for integrated drought risk assessment, supporting more informed drought preparedness and management decisions.</p>
High entropy alloy reinforcement for superior electromagnetic interference shielding performance in carbon fiber-reinforced polymer composites
No full text<p>This study explores the enhancement of electromagnetic interference (EMI) shielding effectiveness (SE) in carbon fiber-reinforced polymer (CFRP) composites through the integration of equatomic CoCuFeNi high entropy alloy (HEA) particles. Employing mechanical alloying (MA), CoCuFeNi HEA powders were synthesized, revealing a face-centered cubic structure with crystallite and particle sizes of 14.7 nm and 11.62 mu m, respectively. The integration of these HEA particles at concentrations of 5%, 10%, and 15% by weight into epoxy resin, followed by the fabrication of composites using the hand lay-up technique. Detailed structural analysis of HEA particles confirmed the successful synthesis of equatomic HEAs via MA. Structural analysis of the HEA integrated composites revealed vacancy regions at 5% concentration, a uniform distribution at 10%, and particle agglomeration causing inhomogeneity and vacancies at 15%. The composites demonstrated significant improvements in EMI SE, with the 10% HEA sample showing superior performance compared to the other samples. Specifically, the 10% HEA composite achieved a peak SE of 73.09 dB at 4.72 GHz, attributed to the optimized distribution of HEA particles that enhanced electrical conductivity and reflective properties.Highlights CoCuFeNi HEA particles were successfully synthesized via MA. HEA particles were added to epoxy at 5, 10, and 15 wt% for composite fabrication. Voids were observed in HEA5, uniformity in HEA10, and clustering in HEA15. EMI shielding was assessed using VNA, SE, dielectric permittivity, and magnetic permeability. The HEA10 composite achieved peak EMI shielding, 73.09 dB at 4.72 GHz.</p>
Experimental study of a novel design bi-fluid based photovoltaic thermal (PVT)-assisted heat pump dryer
No full text<p>This study evaluated the performance of a novel design bi-fluid (air and refrigerant)-based photovoltaic thermal assisted heat pump dryer (BfPVTA-HPD), combining a compact bi-fluid PVT using curved directional fins that direct air at different points to the evaporator/waste aluminum material and HP system with a PVT air outlet mounted micro-channel condenser. BfPVTA-HPD was analyzed regarding energy, exergy, and drying characteristics at two different times, in clear and partially cloudy weather conditions. Mint leaves (Mentha piperita L.) were dried to evaluate BfPVTA-HPD's drying capabilities. The average electrical, thermal, and exergy efficiencies of PV and PVT for Exp-1 and Exp-2 varied to 15.97, 16.54%, 18.21, 18.23%, 55.36%, 42.04%, 30.95%, and 25.08 %, respectively. In Exp-1 and Exp-2, respectively, while an increase of 12.32 % and 9.29% in the average electrical efficiency was achieved by using PVT, an average of 3.15 and 2.86 were reached in the coefficient of performance (COP) of the heat pump. The exergy indicators (the improvement potential, sustainable index, and waste exergy ratio) for the Exp-1 are 839.52, 1.39, and 0.82. The exergy indicators for the Exp-2 are 1166.14, 1.30, and 0.84, respectively. The experiment's average mass transfer coefficients were obtained as 1.17 x 10- 8 and 7.75 x 10-9 m/s respectively. The experiment's average effective diffusivity coefficients were obtained as 2.90 x 10-11 and 2.04 x 10- 11 m2/s, respectively. The recommended BfPVTA-HPD can be used as a new model to improve the ecological footprint and green manufacturing. Furthermore, the electricity and heat production required for the sustainability of the drying system in spring and winter can be realized.</p>
Combination of magnetic hyperthermia and gene therapy for breast cancer
No full text<p>This study presented a novel breast cancer therapy model that uses magnetic field-controlled heating to trigger gene expression in cancer cells. We created silica- and amine-modified superparamagnetic nanoparticles (MSNP-NH2) to carry genes and release heat under an alternating current (AC) magnetic field. The heat-inducible expression plasmid (pHSP-Azu) was designed to encode anti-cancer azurin and was delivered by magnetofection. MCF-7 cells demonstrated over 93% cell viability and 12% transfection efficiency when exposed to 75 mu g/ml of MSNP-NH2, 3 mu g of DNA, and PEI at a 0.75 PEI/DNA ratio (w: w), unlike non-tumorigenic cells (MCF-10 A). Magnetic hyperthermia (MHT) increased azurin expression by heat induction, leading to cell death in dual ways. The combination of MHT and heat-regulated azurin expression induced cell death, specifically in cancer cells, while having negligible effects on MCF-10 A cells. The proposed strategy clearly shows that simultaneous use of MHT and MHT-induced azurin gene expression may selectively target and kill cancer cells, offering a promising direction for cancer therapy.</p>
Dental implants coated with BMP-2-and α-tocopherol-loaded nanofibers enhance osseointegration
No full text<p>Dental implants are widely used to treat edentulism, but the extended osseointegration period can increase infection risk, potentially causing peri-implantitis or implant failure. Bone morphogenetic proteins (BMPs), particularly BMP-2, show promise in bone regeneration but require stability and controlled release for effectiveness. This study developed dental implants coated with polycaprolactone (PCL) nanofibers loaded with BMP2 and alpha-tocopherol. BMP-2 was encapsulated in chitosan nanoparticles (BMP-2-CNPs) with an efficiency of 76.5 +/- 1.01 %, particle size of 234.6 +/- 0.15 nm, polydispersity index (PDI) of 0.284, and zeta potential of 24.97 +/- 0.06 mV. BMP-2-CNPs and alpha-tocopherol were incorporated into PCL nanofibers using electrospinning. SEM imaging confirmed uniform nanofiber coating on implants. BMP-2 release from BMP-2-CNPs lasted 5 days with a 99 % release rate, while BMP-2 release from PCL nanofibers extended to 35 days with a 70 % release rate. alpha-Tocopherol release was 60 % within 24 h, continuing up to 96 h. The specific surface area of coated implants was 0.591-0.601 m2/g. WST-1 analysis showed over 85 % cell viability for both L929 fibroblasts and MC3T3-E1 osteoblasts after 24 and 72 h, with no cytotoxicity or increased inflammatory biomarkers TNF-alpha and IL-1 beta. MC3T3-E1 cells showed up to a 16-fold increase in Alkaline Phosphatase (ALP) activity after 7 and 14 days, and enhanced expression of Runx2, Osteocalcin (OCN), and Osteopontin (OPN) genes, confirmed by Western Blot. Increased biomineralization was observed via Alizarin Red staining. In conclusion, BMP-2-CNPs and alpha-tocopherol-loaded PCL nanofibers on dental implants are a promising strategy to accelerate osseointegration post-implantation.</p>