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Elucidating the intricate interplay between enzymes and natural compounds is essential for designing therapeutic strategies. This study employs advanced computational techniques to explore the binding mechanisms between quercetin 2,3-dioxygenase (QDO) and oroxylin A, revealing specific interaction patterns and key residues crucial to the formation of the QDO-oroxylin A complex. Molecular docking simulations revealed a favorable binding affinity (docking score: -5.6 kcal/mol) between Oroxylin A and the active site cavity of QDO, which was supported by Oroxylin A's specific orientation (Pose 3). Despite an observed RMSD value of 2.776 indicating a moderate deviation between the docked pose and the reference structure, the formation of two hydrogen bonds with GLN 93 chain D underscores specific molecular interactions driving the binding process. This hydrogen bond formation suggested the presence of a stable and specific binding mode between Oroxylin A and QDO, likely influencing the functional dynamics of the enzyme, necessitating further refinement and validation of the docking model. The ensuing deliberation on the implications of Oroxylin A include its potential as a modulator of QDO activity, emphasizing the importance of molecular-level insights in comprehending enzyme-compound interactions. Oroxylin A, a quercetin 2,3-dioxygenase inhibitor, was used in combination with other agents to prolong the biological impacts of quercetin, thereby amplifying its antioxidant and anti-inflammatory effects. This strategic approach exhibits promise in augmenting cardioprotective benefits, immune system support, and protection against diverse pathological conditions. Subsequent considerations of dosage, bioavailability, and healthcare professional consultation are imperative for judicious supplementation, particularly in individuals with prevailing health conditions or medications. This ongoing in silico study is dedicated to revealing the potential synergistic interactions of Oroxylin A, potentiating the long-term effects of quercetin and advancing our understanding of these intricacies.

Background: Accurate and rapid detection of COVID-19 remains critical for clinical management, especially in resource-limited settings. Current diagnostic methods face challenges in terms of speed and reliability, creating a need for complementary AI-based models that integrate diverse data sources. Objectives: This study aimed to develop and evaluate a multi-modal machine learning model that combines clinical biomarkers and chest X-ray images to enhance diagnostic accuracy and provide interpretable insights. Methods: We used a dataset of 250 patients (180 COVID-19 positive and 70 negative cases) collected from clinical settings. Biomarkers such as CRP, ferritin, NLR, and albumin were included alongside chest X-ray images. Random Forest and Gradient Boosting models were used for biomarkers, and ResNet and VGG CNN architectures were applied to imaging data. A late-fusion strategy integrated predictions from these modalities. Stratified k-fold cross-validation ensured robust evaluation while preventing data leakage. Model performance was assessed using AUC-ROC, F1-score, Specificity, Negative Predictive Value (NPV), and Matthews Correlation Coefficient (MCC), with confidence intervals calculated via bootstrap resampling. Results: The Gradient Boosting + VGG fusion model achieved the highest performance, with an AUC-ROC of 0.94, F1-score of 0.93, Specificity of 93%, NPV of 96%, and MCC of 0.91. SHAP and LIME interpretability analyses identified CRP, ferritin, and specific lung regions as key contributors to predictions. Discussion: The proposed multi-modal approach significantly enhances diagnostic accuracy compared to single-modality models. Its interpretability aligns with clinical understanding, supporting its potential for real-world application.

Our study aimed to investigate effect of tocilizumab on the lung tissue in the presence of Acinetobacter baumannii infection in immunosuppressed rats. A forty-eight female Wistar albino rats were divided equally into eight groups: Group 1: Healthy (H), Group 2: Immunosuppressed (IM), Group 3: Healthy rats given A. baumannii bacteria (H+BAC), Group 4: Immunosuppressed rats given A. baumannii bacteria (IM+BAC), Group 5: Healthy rats given tocilizumab (H+TCZ), Group 6: Immunosuppressed rats given tocilizumab (IM+TCZ), Group 7: Healthy rats given A. baumannii bacteria and tocilizumab (H+BAC+TCZ), Group 8: Immunosuppressed rats given tocilizumab and A. baumannii bacteria (IM+BAC+TCZ). Fourteen days after the immunosuppression of group 2, 4, 6 and 8 with hydrocortisone, group 3, 4, 7 and 8 were A. baumannii was dropped into the trachea. One hour after A. baumannii application, TCZ was administered to Groups 5, 6, 7 and 8. NF-κB, IL-6 and NLRP3 mRNA expressions were decreased in the IM group compared to the healthy group (P

Introduction. Hemodialysis patients are the group which oxidative stress is found more exacerbated. Ischemia modified albumin (IMA) is a new and sensitive marker for ischemia and oxidative stress. At current study we evaluated relation between IMA and biochemical parameters in hemodialysis patients. Materials and Methods. Thirty-four patients on maintenance hemodialysis were included. Pre-hemodialysis and post-hemodialysis blood samples were taken. Serum IMA and biochemistry parameters were measured. Results. There was a positive correlation between alkaline phosphatase (ALP) and IMA (r=0,268, p

Floating Car Data (FCD) are being increasingly used as an alternative traffic data source due to its lower cost and high coverage area. FCD can be obtained by tracking vehicle trajectories individually or by processing multiple tracks anonymously to produce average speed information commercially. For commercial FCD, the spatio-temporal distribution of these vehicles in actual traffic, traffic Penetration Rate (PR) is the most important factor affecting the accuracy of speed estimations, despite the high number of registered vehicles feeding to an FCD provider, denoting the market PR. This study proposes a method for assessing the traffic PR of commercial FCD by evaluating its speed estimation quality compared to Ground Truth (GT) data. GT speed data were employed to generate different levels of traffic PR using Monte Carlo (MC) simulations, which resulted in the development of Quality-PR (Q-PR) relations for Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) as selected Measures of Effectiveness (MoE). Simulation-based FCD results at an urban road segment in Ankara (Turkey) showed that a quality of FCD with traffic PR of 15% or more would improve significantly. Use of the developed Q-PR relations suggested an approximately 5% traffic PR for the commercial FCD speeds at the location.

This paper presents a novel reflectarray antenna with enhanced beam steering capability. The reflectarray antenna is based on the hexagonal distribution of the unit cells on the antenna surface. The hexagonal topology changes the angle between the principal axes of the unit cell distribution, preventing the formation of the grating lobe, and improving the beam steering capability of the reflectarray antenna. To verify the proposed idea, two different sets of reflectarray antennas, which includes square and hexagonal lattice topologies with inter-element spacings of 0.52λ and 0.6λ, have been designed, fabricated, and measured at 8.23 GHz. The measurements of the all fabricated reflectarray antennas are in very good agreement with the simulations, and the comparison of the square and hexagonal topologies show that the beam steering capability can be improved by 50% for 0.6λ inter-element spacing by using a hexagonal topology. This improvement shows that a simple modification in the array configuration can be a viable solution for satellite and 5G communication applications that require increased beam steering capability.

Salinity is an edaphic stress that dramatically restricts worldwide crop production. Nanomaterials and plant growth-promoting bacteria (PGPB) are currently used to alleviate the negative effects of various stresses on plant growth and development. This study investigates the protective effects of different levels of zinc oxide nanoparticles (ZnO-NPs) (0, 20, and 40 mg L−1) and PGPBs (no bacteria, Bacillus subtilis, Lactobacillus casei, Bacillus pumilus) on DNA damage and cytosine methylation changes in the tomato (Solanum lycopersicum L. ‘Linda’) seedlings under salinity stress (250 mM NaCl). Coupled Restriction Enzyme Digestion-Random Amplification (CRED-RA) and Randomly Amplified Polymorphic DNA (RAPD) approaches were used to analyze changes in cytosine methylation and to determine how genotoxic effects influence genomic stability. Salinity stress increased the polymorphism rate assessed by RAPD, while PGPB and ZnO-NPs reduced the adverse effects of salinity stress. Genomic template stability was increased by the PGPBs and ZnO-NPs application; this increase was significant when Lactobacillus casei and 40 mg L−1 of ZnO-NPs were used.A decreased level of DNA methylation was observed in all treatments. Taken together, the use of PGPB and ZnO-NPs had a general positive effect under salinity stress reducing genetic impairment in tomato seedlings.

For the first time. a deep-water Lower Carbon iferous siliciclasticturbidite-olistostrome unit with many lydites (partly distally turbiditic) can be dated in the Incirbeleni Formation of the Tavas Nappe (Lycian nappes) in southwestern Turkey. These nappes belong to a Hercynian Upper Devonian to Lower Carboniferous flysch Belt that is also known from the Karaburun Zone in western Turkey. A conodont fauna, consisting mainly of Gnathodus bilineatus and few Lochricea commutata without nodose Lochriea species allows the dating of cherty limestone olistoliths as middle to early late Visean age (Visean 2 10 lower Visean 3). The Lower Carboniferous Hercynian deep-sea turbidites and olistostromes confirm a northern origin for the Lycian nappes and a minimum north-south nappe transport of approximatly 200 km. Nevertheless, the Tavas Nappe originated tothe south of the Izmir-Ankara Zone because the ophiolites of theIzmir - Ankara Zone follow in nappe position above the Tavas Nappe.

This paper presents a design methodology for the implementation of a miniaturized square patch antenna and its circuit model for 5.15 GHz ISM band. The miniaturization is achieved by employing concentric complementary split ring resonator (CSRR) structures in between the patch and ground plane. The results are compared with the traditional square patch antenna in terms of area, bandwidth, and efficiency. The area is reduced with a ratio of 1/4 with respect to the traditional patch. The miniaturized square patch antenna has an efficiency, bandwidth, and reflection coefficient of 78%, 0.4%, and −16 dB, respectively. The measurement and circuit modeling results show a good agreement with the full-wave electromagnetic simulations.

Objective:  This study aimed to assess thermoregulation and humidity within the Skincubator-a novel, wearable skin-to-skin incubator designed to attach to the caregiver., Study Design:  Preterm neonates (PN; born between 24 and 33 weeks gestational age [GA]) received skin-to-skin care (SSC) either via the Skincubator or traditional SSC (t-SSC) with continuous axillary temperature monitoring., Results:  Twenty PN were enrolled in the study and treated in the Skincubator. One couple who consented to Skincubator care during delivery subsequently revoked their consent and the baby was excluded from further analysis. Fifty-four paired sessions of Skincubator and t-SCC were performed and compared for 19 babies. The average GA was 29 weeks (range: 26-32), the average weight was -1,296 ± 271 g, and the average day of life was 5 ± 2. The temperature drop after transfer to Skincubator care was smaller than in t-SSC (0.2°C [0.2-0.3] vs. 0.4°C [0.3-0.6]; Wilcoxon's signed rank test [WSRT], p  < 0.001). The average hypothermia time per session was a median (25th-75th%) of 8.2 minutes (0-9) for Skincubator, compared to 27.8 minutes (0-56) for t-SSC, respectively (WSRT, p  = 0.002). No baby had moderate hypothermia (35.5-35.9°C) during Skincubator care as compared with eight babies who experienced moderate hypothermia during t-SSC (Fisher's exact test p  = 0.003). The average Skincubator humidity was 85 ± 7% and was above 70% during 93% of the time., Conclusion:  Skincubator SSC was superior to t-SSC in maintaining PN temperature while also maintaining an optimally humidified environment. The Skincubator may promote early SSC in very and extremely PN. (Trial registration number MOH&#95;2021-12-13&#95;010470 registration date 24/10/21.) KEY POINTS: · Early prolonged SSC improves preterm infants' outcomes but may be challenging to perform.. · To mitigate several SSC barriers we invented the Skincubator, a wearable incubator for SSC.. · We have shown that the Skincubator reduces transient moderate hypothermia at SSC initiation.. · Average Skincubator humidity was 85 ± 7% and above 70% during 93% of SSC time.., Competing Interests: I.N. is the inventor of the Skincubator and a founder and the chief medical officer of Skincubator Neocare, a company founded to develop the Skincubator and bring it to clinical use. He and Skincubator Neocare have submitted patents regarding the Skincubator system. Other authors do not have any conflict of interest., (Thieme. All rights reserved.)

Rangelands are dynamic ecosystems shaped by fluctuations in precipitation, temperature, and grazing intensity. Accurate assessment of forage availability is critical for optimizing land use, preventing overgrazing, and mitigating degradation, especially under future climate change scenarios. This study employed a multi-scale approach to monitor pasture using Sentinel-2 satellite imagery, calibrated with ground truth measurements, and enhanced with drone-derived vegetation cover estimates. The research was conducted in a Mediterranean grassland ecosystem under varying grazing intensities in northeastern Israel. A time series of Sentinel-2 images from 2018 to 2023 was analyzed to monitor five vegetation growth cycles. We evaluated how climate variables, such as temperature, rainfall, and vapor pressure deficit (VPD), impacted forage availability and nutritional quality. Over the past three decades, significant climatological trends showed increasing temperatures and more concentrated winter rainfall. Correlation analysis between field data and Sentinel-2 imagery demonstrated strong agreement (R 2  = 0.73 for biomass and 0.72 for forage quality), validating the effectiveness of this integrated remote sensing approach. Moderate grazing reduced forage quantity but improved its quality, while extreme weather events, including drought and heatwaves, negatively impacted forage biomass and quality. Key meteorological indices, including the Standardized Precipitation-Evapotranspiration Index (SPEI) and the Simple Daily Intensity Index (SDII), were found to influence forage quantity, indicating that drought stress and concentrated rainfall events reduced biomass production. Higher values of daily temperature range and vapor pressure deficit adversely impacted forage quality. This study highlights the importance of adaptive management strategies to mitigate the projected reductions in forage quantity and quality due to climate change. The methodologies developed offer novel insights into improving ecological monitoring for sustainable rangeland management under changing climatic conditions., Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Aim: To assess the clinical reasoning capabilities of two large language models, ChatGPT-4 and Claude-2.0, compared to those of neonatal nurses during neonatal care scenarios., Design: A cross-sectional study with a comparative evaluation using a survey instrument that included six neonatal intensive care unit clinical scenarios., Participants: 32 neonatal intensive care nurses with 5-10 years of experience working in the neonatal intensive care units of three medical centers., Methods: Participants responded to 6 written clinical scenarios. Simultaneously, we asked ChatGPT-4 and Claude-2.0 to provide initial assessments and treatment recommendations for the same scenarios. The responses from ChatGPT-4 and Claude-2.0 were then scored by certified neonatal nurse practitioners for accuracy, completeness, and response time., Results: Both models demonstrated capabilities in clinical reasoning for neonatal care, with Claude-2.0 significantly outperforming ChatGPT-4 in clinical accuracy and speed. However, limitations were identified across the cases in diagnostic precision, treatment specificity, and response lag., Conclusions: While showing promise, current limitations reinforce the need for deep refinement before ChatGPT-4 and Claude-2.0 can be considered for integration into clinical practice. Additional validation of these tools is important to safely leverage this Artificial Intelligence technology for enhancing clinical decision-making., Impact: The study provides an understanding of the reasoning accuracy of new Artificial Intelligence models in neonatal clinical care. The current accuracy gaps of ChatGPT-4 and Claude-2.0 need to be addressed prior to clinical usage., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Climate change is expected to impact the spring phenology of perennial trees, potentially altering the suitability of land for their cultivation. In this study, we investigate the effects of climate change on the bloom timing of almond orchards, focusing on California, the world's leading region for almond production. By analyzing historical climatic data, employing a model that considers hourly temperatures and fall non-structural carbohydrates to predict bloom dates, and examining various Coupled Model Intercomparison Project Phase 6 (CMIP6) scenarios, we assess the potential impacts of climate shifts on plant phenology and, consequently, on land suitability for almond farming. Our findings reveal that, within the next 30 years, the land suitable for almond production will not undergo significant changes. However, under unchanged emission scenarios, the available land to support almond orchard farming could decline between 48 to 73% by the end of the century. This reduction corresponds with an early shift in bloom time from the average Day of Year (DOY) 64 observed over the past 40 years to a projected earlier bloom between DOY 28-33 by 2100. These results emphasize the critical role climate shifts have in shaping future land use strategies for almond production in Central Valley, California. Consequently, understanding and addressing these factors is essential for the sustainable management and preservation of agricultural land, ensuring long-term food security and economic stability in the face of a rapidly changing climate., (© 2024. The Author(s).)

Dryland forests worldwide are increasingly threatened by drought stress due to climate change. Understanding the relationships between forest structure and function is essential for managing dryland forests to adapt to these changes. We investigated the structure-function relationships in four dryland conifer forests distributed along a semiarid to subhumid climatic aridity gradient. Forest structure was represented by leaf area index (LAI) and function by gross primary productivity (GPP), evapotranspiration (ET), and the derived efficiencies of water use (WUE = GPP/ET) and leaf area (LAE = GPP/LAI). Estimates of GPP and ET were based on the observed relationships between high-resolution vegetation indices from VENμS and Sentinel-2A satellites and flux data from three eddy covariance towers in the study regions between November 2015 to October 2018. The red-edge-based MERIS Terrestrial Chlorophyll Index (MTCI) from VENμS and Sentinel-2A showed strong correlations to flux tower GPP and ET measurements for the three sites (R 2 cal  > 0.91, R 2 val  > 0.84). Using our approach, we showed that as LAI decreased with decreasing aridity index (AI) (i.e., dryer conditions), estimated GPP and ET decreased (R 2  > 0.8 to LAI), while WUE (R 2  = 0.68 to LAI) and LAE increased. The observed global-scale patterns are associated with a variety of forest vegetation characteristics, at the local scale, such as tree species composition and density. However, our results point towards a canopy-level mechanism, where the ecosystem-LAI and resultant proportion of sun-exposed vs. shaded leaves are primary determinants of WUE and LAE along the studied climatic aridity gradient. This work demonstrates the importance of high-resolution (spatially and spectrally) remote sensing data conjugated with flux tower data for monitoring dryland forests and understanding the intricate structure-function interactions in their response to drying conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The frequency and severity of Mediterranean forest fires are expected to worsen as climate change progresses, heightening the need to evaluate understory fuel management strategies as rigorously as possible. Prescribed small-ruminant foraging is considered a sustainable, cost-effective strategy, but demonstrating a link between animal presence and vegetation change is challenging. This study tested whether the effect of small-ruminant herd presence in Mediterranean woodlands can be detected by integrating remote sensing and herd tracking at the landscape scale. The daily foraging routes of seven shepherded goat herds that exploited a 100-km 2 forested area of the Judean Hills, Israel, were tracked over six years using GPS (Global Positioning System) collars. Herd locations were converted to stocking rates, with units of animal-presence-days per unit area per defined time period, and mapped at a spatial resolution of 10 m. We estimated pixel-level vegetation cover change based on a time series of 63 monthly Landsat-8 images expressed as the normalized soil-adjusted vegetation index (SAVI). Spatiotemporal trend analysis assessed the magnitude and direction of change, and a random forest machine-learning algorithm estimated the relative impact on vegetation cover change of environmental factors as well as the herd-related factors of stocking rate that accrued over six years and distance to the closest corral. The last two factors were among the most influential factors determining vegetation cover change in the regional and individual-herd analyses. In some respects, the permanent herds differed in their spatial pattern of stocking rate from the mobile herds that periodically relocated their night corral throughout the year, but stocking rate scaled logarithmically for all herds individually and combined. The combination of multi-season GPS tracking, remote sensing, and machine-learning techniques, applied at a regional scale, detected herd impacts on vegetation cover trends, consistent with livestock foraging being an effective tool for fuel reduction in Mediterranean woodlands., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Cannabis sativa L. is used to treat a wide variety of medical conditions, in light of its beneficial pharmacological properties of its cannabinoids and terpenes. At present, the quantitative chemical analysis of these active compounds is achieved through the use of laborious, expensive, and time-consuming technologies, such as high-pressure liquid-chromatography- photodiode arrays, mass spectrometer detectors (HPLC-PDA or MS), or gas chromatography-mass spectroscopy (GC-MS). Hence, we aimed to develop a simple, accurate, fast, and cheap technique for the quantification of major cannabinoids and terpenes using Fourier transform near infra-red spectroscopy (FT-NIRS). FT-NIRS was coupled with multivariate classification and regression models, namely partial least square-discriminant analysis (PLS-DA) and partial least squares regression (PLS-R) models. The PLS-DA model yielded an absolute major class separation (high-THC, high-CBD, hybrid, and high-CBG) and perfect class prediction. Using only three latent variables (LVs), the cross-validation and prediction model errors indicated a low probability of over-fitting the data. In addition, the PLS-DA model enabled the classification of chemovars with genetic-chemical similarities. The classification of high-THCA chemovars was more sensitive and more specific than the classifications of the remaining chemovars. The prediction of cannabinoid and terpene concentrations by PLS-R yielded 11 robust models with high predictive capabilities (R 2 CV and R 2 pred > 0.8, RPD >2.5 and RPIQ >3, RMSECV/RMSEC ratio <1.2) and additional 15 models whose performance was acceptable for initial screening purposes (R 2 CV  > 0.7 and R 2 pred < 0.8, RPD >2 and RPIQ <3, 1.2 < RMSECV/RMSEC ratio <2). Our results confirm that there is sufficient information in the FT-NIRS to develop cannabinoid and terpene prediction models and major-cultivar classification models., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Cannabis is used to treat various medical conditions, and lines are commonly classified according to their total concentrations of Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD). Based on their ratio of total THC to total CBD, cannabis cultivars are commonly classified into high-THC, high-CBD, and hybrid classes. While cultivars from the same class have similar compositions of major cannabinoids, their levels of other cannabinoids and their terpene compositions may differ substantially. Therefore, a more comprehensive and accurate classification of medicinal cannabis cultivars, based on a large number of cannabinoids and terpenes is needed. For this purpose, three different chemometric-based classification models were constructed using three sets of chemical profiles. We examined those models to determine which provides the most accurate "chemovar" classification. This was done by analyzing profiles of cannabinoids, terpenes, and the combination of these substances using the partial least square-discriminant analysis multivariate (PLS-DA) technique. The chemical profiles were selected from the three major classes of medicinal cannabis that are most commonly prescribed to patients in Israel: high-THC, high-cannabigerol (CBG), and hybrid. We studied the correlations between cannabinoids and terpenes to identify major bio-indicators representing the plant's terpene and cannabinoid content. All three PLS-DA models provided highly accurate classifications, utilizing six to nine latent variables with an overall accuracy ranging from 2 to 11% CV. The PLS-DA model applied to the combined cannabinoid-and-terpene profile did the best job of differentiating between the chemovars in terms of misclassification error, sensitivity, specificity, and accuracy. The combined cannabinoid-and-terpene PLS-DA profile had cross-validation and prediction misclassification errors of 4% and 0%, respectively. This is the first study to demonstrate the highly accurate classification of samples of medicinal cannabis based on their cannabinoid and terpene profiles, as compared to cannabinoid profiles alone. Furthermore, our correlation analysis indicated that 11 cannabinoids and terpenes might serve as bio-indicators for 32 different active compounds. These findings suggest that the use of multivariate statistics could assist in breeding studies and serve as a tool for minimizing the mislabeling of cannabis inflorescences., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Cell therapy using induced pluripotent stem cell-derived neurons is considered a promising approach to regenerate the injured spinal cord (SC). However, the scar formed at the chronic phase is not a permissive microenvironment for cell or biomaterial engraftment or for tissue assembly. Engineering of a functional human neuronal network is now reported by mimicking the embryonic development of the SC in a 3D dynamic biomaterial-based microenvironment. Throughout the in vitro cultivation stage, the system's components have a synergistic effect, providing appropriate cues for SC neurogenesis. While the initial biomaterial supported efficient cell differentiation in 3D, the cells remodeled it to provide an inductive microenvironment for the assembly of functional SC implants. The engineered tissues are characterized for morphology and function, and their therapeutic potential is investigated, revealing improved structural and functional outcomes after acute and chronic SC injuries. Such technology is envisioned to be translated to the clinic to rewire human injured SC., (© 2022 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Background: Ceramide, important for both neuronal differentiation and dedifferentiation, resides in several membranes, is synthesized in the endoplasmic reticulum, mitochondrial, and nuclear membranes, and can be further processed into glycosphingolipids or sphingomyelin. Ceramide may also be generated by hydrolysis of sphingomyelin by neutral or acidic sphingomyelinases in lysosomes and other membranes. Here we asked whether the differing functions of ceramide derived from different origins., Methods: We added NGF to PC12 cells and to TrkA cells. These latter overexpress NGF receptors and are partially activated to differentiate, whereas NGF is required for PC12 cells to differentiate. We differentiated synthesis from hydrolysis by the use of appropriate inhibitors. Ceramide and sphingomyelin were measured by radiolabeling., Results: When NGF is added, the kinetics and amounts of ceramide and sphingomyelin indicate that the ceramide comes primarily from hydrolysis but, when hydrolysis is inhibited, can also come from neosynthesis. When NGF is removed, the ceramide comes from both neosynthesis and hydrolysis., Conclusion: We conclude that the function of ceramide depends heavily on its intracellular location, and that further understanding of its function will depend on resolving its location during changes of cell status. Video Abstract., (© 2022. The Author(s).)

Severe drought has the potential to cause selective mortality within a forest, thereby inducing shifts in forest species composition. The southern Sierra Nevada foothills and mountains of California have experienced extensive forest dieback due to drought stress and insect outbreak. We used high-fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) from the Carnegie Airborne Observatory (CAO) to estimate the effect of forest dieback on species composition in response to drought stress in Sequoia National Park. Our aims were (1) to quantify site-specific conditions that mediate tree mortality along an elevation gradient in the southern Sierra Nevada Mountains, (2) to assess where mortality events have a greater probability of occurring, and (3) to estimate which tree species have a greater likelihood of mortality along the elevation gradient. A series of statistical models were generated to classify species composition and identify tree mortality, and the influences of different environmental factors were spatially quantified and analyzed to assess where mortality events have a greater likelihood of occurring. A higher probability of mortality was observed in the lower portion of the elevation gradient, on southwest- and west-facing slopes, in areas with shallow soils, on shallower slopes, and at greater distances from water. All of these factors are related to site water balance throughout the landscape. Our results also suggest that mortality is species-specific along the elevation gradient, mainly affecting Pinus ponderosa and Pinus lambertiana at lower elevations. Selective mortality within the forest may drive long-term shifts in community composition along the elevation gradient., (© 2017 by the Ecological Society of America.)

Severe droughts increase physiological stress in woody plant species, which can lead to mortality, fundamentally altering the composition, structure, and biogeography of forests in many regions. Little is known, however, about the factors determining the physiological response of woody plants to drought at landscape scales. Our objective was to understand woody plant species responses to ongoing changes in climate, using remotely sensed canopy water content (CWC) as an indicator of plant physiological and phenological status. We used fused imaging spectroscopy and light detection and ranging from the Carnegie Airborne Observatory to quantify the factors affecting species compositional changes in CWC in a diverse Mediterranean-type ecosystem (Jasper Ridge Biological Preserve, California, USA) between 2013 and 2015. Mapped CWC was spatially variable in both of the observation years, and proved to be most closely tied to species composition and distribution across the landscape. The secondary predictors of CWC were elevation and soil substrate. In contrast, we found that CWC change was much more related to environmental factors than to the species composition. We suggest that the effect of environment on CWC change is mediated through species resistance and resilience to drought. Monitoring CWC change with imaging spectroscopy is a powerful approach to identifying species-level responses to climatic events and long-term change, which may provide support for policy decisions and conservation at large spatial scales., (© 2017 by the Ecological Society of America.)

Land use changes are one of the most important factors causing environmental transformations and species diversity alterations. The aim of the current study was to develop a geoinformatics-based framework to quantify alpha and beta diversity indices in two sites in Israel with different land uses, i.e., an agricultural system of fruit orchards, an afforestation system of planted groves, and an unmanaged system of groves. The framework comprises four scaling steps: (1) classification of a tree species distribution (SD) map using imaging spectroscopy (IS) at a pixel size of 1 m; (2) estimation of local species richness by calculating the alpha diversity index for 30-m grid cells; (3) calculation of beta diversity for different land use categories and sub-categories at different sizes; and (4) calculation of the beta diversity difference between the two sites. The SD was classified based on a hyperspectral image with 448 bands within the 380-2500 nm spectral range and a spatial resolution of 1 m. Twenty-three tree species were classified with high overall accuracy values of 82.57% and 86.93% for the two sites. Significantly high values of the alpha index characterize the unmanaged land use, and the lowest values were calculated for the agricultural land use. In addition, high values of alpha indices were found at the borders between the polygons related to the "edge-effect" phenomenon, whereas low alpha indices were found in areas with high invasion species rates. The beta index value, calculated for 58 polygons, was significantly lower in the agricultural land use. The suggested framework of this study succeeded in quantifying land use effects on tree species distribution, evenness, and richness. IS and spatial statistics techniques offer an opportunity to study woody plant species variation with a multiscale approach that is useful for managing land use, especially under increasing environmental changes., (© 2017 by the Ecological Society of America.)

Aim: This study was designed to analyze serum oxidative stress (OS) levels in healthy young individuals performing a routine maximal aerobic exercise and to evaluate the correlation between OS levels and physiological parameters., Methods: Serum OS levels were studied by thermochemiluminescence (TCL) parameters at rest and following maximal aerobic exercise in 85 healthy young subjects. Levels were measured by a real time on line TCL assay (higher TCL-Ratio and TCL-H3 = lower OS level)., Results: Aerobic capacity had no effect on baseline OS levels. Post-exercise OS levels correlated with maximal oxygen uptake (V.O(2max)) (P<0.005), delta V.O(2) (V.O(2max)- V.O(2)rest) (P<0.005), anaerobic threshold (VTH) (P<0.01), and total oxygen uptake (especially O(2) after VTH), (P<0.005). TCL-Ratio was related to total running time (P<0.01), as well. Post-exercise OS levels for the whole study group did not vary from baseline values. However, individuals with higher fitness level (V.O(2max) >percentile 60) had significantly lower values of TCL-H3 (P=0.04) and tended to have lower TCL-Ratio, indicating they had elevated OS levels. In a multivariate analysis OS level was most affected by V.O(2) after VTH (anaerobic phase of the test) (P=0.003; adjusted odds ratio of 3.41, 95% confidence interval: 1.55-7.48)., Conclusions: In conclusion, acute incremental exercise to maximal performance does not cause alterations in serum oxidant levels of healthy young individuals. In healthy individuals performing maximal aerobic exercise, OS levels correlate with maximal aerobic power.

Classical apoptotic cell death can be defined by certain morphological and biochemical characteristics that distinguish it from other forms of cell death. One such feature, which is a hallmark of apoptosis, is DNA fragmentation. In dying cells, DNA is cleaved by an endonuclease that fragments the chromatin into nucleosomal units, which are multiples of about 180-bp oligomers and appear as a DNA ladder when run on an agarose gel. Here, we present commonly used methods such as conventional agarose gel electrophoresis to analyze fragmented nuclei in cells. The various methods used are dependent on the extent of fragmentation or the amount of fragmented nuclei in a sample. Determining whether a cell exhibits DNA fragmentation can provide information about the type of cell death occurring and the pathways activated in the dying cell.

Background: Reactive oxygen species play a key role in the formation of endothelial dysfunction accompanying diabetes mellitus, hypertension, and other cardiovascular diseases., Method: This study compares oxidative stress (OS) in Wistar-Kyoto rats (WKY), spontaneously hypertensive rats (SHR), non-insulin-dependent Cohen Diabetic rats (CDR), and Cohen Rosenthal diabetic hypertensive rats (CRDH), a unique animal model of both diabetes and hypertension. The OS was evaluated with a newly developed thermochemiluminiscence (TCL) analyzer (Lumitest Ltd., Nesher, Israel) that measures the oxidizability (ie, susceptibility to oxidation) of a test sample., Results: The TCL oxidizability test results of sera from the different rats groups showed a time-dependent increase in TCL of up to 145% +/- 7% for WKY, 160% +/- 8% for SHR, 179% +/- 12% for CDR, and 226% +/- 15% for CRDH. These results were significant: P <.001 for SHR and CDR and P <.0001 for CRDH in comparison to WKY. Lipid peroxide levels also increased in each strain of rats: to 80 +/- 7.8 nmol/mL in WKY, 104 +/- 10.1 nmol/mL in SHR, 110 +/- 9.4 nmol/mL in CDR, and 167 +/- 11.7 nmol/mL in CRDH. These results were also significant: P <.001 for SHR, CDR and CRDH in comparison to WKY., Conclusion: The combination of hypertension and diabetes is accompanied by higher oxidative stress than that seen with either disorder alone.

Detection of electronically excited species (EES) in body fluids may constitute an important diagnostic tool in various pathologies. Examples of such products are triplet excited carbonyls (TEC), which can be a source for photon emission in the 400-550 nm range. The aim of the present study was to determine the actual contribution of lipid and protein components (protein carbonyls) to photon emission generated by thermochemiluminescence (TCL) during the heating of biological fluids. In this study, a new TCL Photometer device, designed by Lumitest Ltd, Israel, was used. Samples were heated to a constant temperature of 80 +/- 0.5 degrees C for 280 s and photon emission was measured at several time points. In order to compare the results of TCL measurements to conventional methods of detecting lipid and protein oxidation, each examined sample was also heated in a waterbath at 80 degrees C for 10-280 s. Lipid and protein oxidation were subsequently measured using conventional methods. The TCL of four polyunsaturated fatty acids (PUFA) with three to six double bonds was measured. The elevation of the PUFA TCL amplitude correlated with the increase in the number of double bonds of PUFA. A correlation between the increase in TCL intensity and protein carbonyl generation in bovine serum albumin (BSA) was also observed. In the venous blood serum, our study showed that an increase of TCL intensity during heating reflected the cleavage of TEC of lipid origin. Our study suggests that biological molecules such as proteins, lipids and other molecules, which may become unstable during heating, are capable of generating EES. We demonstrated that a TCL curve can be used as a kinetic model for measuring oxidative processes, which reflects modifications of different molecules involved in the oxidative stress phenomena., (Copyright 2003 John Wiley & Sons, Ltd.)

The mitochondrial component coenzyme Q10 (CoQ10) has been used for many years as a dietary supplement intended to promote good health by trapping free radicals, thus preventing lipid peroxidation and DNA damage. We have tested its use as a generic anti-apoptotic compound and have found that its ability to protect against apoptosis varies depending on both cell type and mode of cell death induction. We have further established that this protection may be mediated by its effect on mitochondrial function and viability. We provide additional evidence that CoQ10's protective effect on mitochondrial membrane potential does not always result in altered mitochondrial enzyme activity and neither does it guarantee survival. These observations open the way for further investigations into the mechanisms involved in mitochondrial control of apoptosis.

Over the course of an organism's life, cells divide, grow, differentiate, and die. For many years cell death has been recognized as significant in normal neuronal development. More recently, interest has grown in the mechanisms that regulate both cell death and cell survival in neurons during homeostasis and aging. Understanding these mechanisms depends largely on the ability to identify dead or dying cells. Several markers have been identified and developed for the detection of cell death in various tissues. In this chapter, we will present an overview of different approaches used to identify cell death in the nervous system while focusing on a few specific protocols.

Effect af antiischemic drug mildronate 3-(2,2,2-trimethylhydrazinium) propionate on oxidation of sodium octanoate and L-palmitoyl carnitine was studied in liver mitochondria of intact rats using polarographic procedure. After 10 days of administration of mildronate at a dose of 200 mg/kg per os oxidation of sodium octanoate was stimulated in liver mitochondria while the rate of L-palmitoyl carnitine oxidation was unaltered. The data obtained suggest that mildronate stimulated the carnitine-independent fatty acid oxidation which appears to occur as a compensation for inhibition of the carnitine-dependent oxidation by the drug.