Mitochondrial carrier homolog 1 (Mtch1) antibodies in neuro-Behçet's disease

Cataloged from PDF version of article.Efforts for the identification of diagnostic autoantibodies for neuro-Behcet's disease (NBD) have failed. Screening of NBD patients' sera with protein macroarray identified mitochondrial carrier homolog 1 (Mtch1), an apoptosis-related protein, as a potential autoantigen. ELISA studies showed serum Mtch1 antibodies in 68 of 144 BD patients with or without neurological involvement and in 4 of 168 controls corresponding to a sensitivity of 47.2% and specificity of 97.6%. Mtch1 antibody positive NBD patients had more attacks, increased disability and lower serum nucleosome levels. Mtch1 antibody might be involved in pathogenic mechanisms of NBD rather than being a coincidental byproduct of autoinflammation. © 2013 Elsevier B.V

Forecasting Electric Vehicle Charging Demand in Smart Cities Using Hybrid Deep Learning of Regional Spatial Behaviours

\ua9 2025 by the authors. This study presents a novel predictive framework for estimating electric vehicle (EV) charging demand in smart cities, contributing to the advancement of data-driven infrastructure planning through behavioural and spatial data analysis. Motivated by the accelerating regional demand accompanying EV adoption, this work introduces HCB-Net: a hybrid deep learning model that combines Convolutional Neural Networks (CNNs) for spatial feature extraction with Extreme Gradient Boosting (XGBoost) for robust regression. The framework is trained on user-level survey data from two demographically distinct UK regions, the West Midlands and the North East, incorporating user demographics, commute distance, charging frequency, and home/public charging preferences. HCB-Net achieved superior predictive performance, with a Root Mean Squared Error (RMSE) of 0.1490 and an (Formula presented.) score of 0.3996. Compared to the best-performing traditional model (Linear Regression, (Formula presented.)), HCB-Net improved predictive accuracy by 13.5% in terms of (Formula presented.), and outperformed other deep learning models such as LSTM ((Formula presented.)) and GRU ((Formula presented.)), which failed to capture spatial patterns effectively. The hybrid model also reduced RMSE by approximately 23% compared to the standalone CNN (RMSE = 0.1666). While the moderate (Formula presented.) indicates scope for further refinement, these results demonstrate that meaningful and interpretable demand forecasts can be generated from survey-based behavioural data, even in the absence of high-resolution temporal inputs. The model contributes a lightweight and scalable forecasting tool suitable for early-stage smart city planning in contexts where telemetry data are limited, thereby advancing the practical capabilities of EV infrastructure forecasting

Discovery of New ? Scuti Stars

Pulsating stars are remarkable objects for stellar astrophysics. Their pulsation frequencies allow us to probe the internal structure of stars. One of the most known groups of pulsating stars is delta Scuti variables which could be used to understand the energy transfer mechanism in A-F type stars. Therefore, in the current study, we focused on the discovery of delta Scuti stars. For this investigation, we followed some criteria. First, we inspected TESS database by eye and discovered some single stars that exhibit pulsation-like behaviour. Our second criterion is T-eff and logg range. The delta Scuti stars generally have T-eff and log g value in a range of 6300-8500 K and 3.2-4.3, respectively. Hence, we selected the stars which have TIC T-eff and logg values in these ranges. The other criterion is the pulsating frequency. A frequency analysis was performed for all the candidate stars. In addition, M-V, L and also M-bol parameters of the target stars were determined to calculate the pulsation constants and show their positions in the H-R diagram. The final pulsation type classification was made by considering the frequency ranges and pulsation constants of the stars. As a result of the study, five delta Scuti, one gamma Doradus and four hybrid systems were discovered.Scientific and Technological Research Council (TUBITAK) [120F330]This work has been supported in part by the Scientific and Technological Research Council (TUBITAK) under the grant number 120F330

Candidate Eclipsing Binary Systems with a ? Scuti Star in Northern TESS Field

The existence of pulsating stars in eclipsing binaries has been known for decades. These types of objects are extremely valuable systems for astronomical studies as they exhibit both eclipse and pulsation variations. The eclipsing binaries are the only way to directly measure the mass and radius of stars with a good accuracy (<= 1%), while the pulsations are a unique way to probe the stellar interior via oscillation frequencies. There are different types of pulsating stars existing in eclipsing binaries. One of them is the delta Scuti variables. Currently, the known number of delta Scuti stars in eclipsing binaries is around 90 according to the latest catalog of these variables. An increasing number of these kinds of variables is important to understand the stellar structure, evolution and the effect of binarity on the pulsations. Therefore, in this study, we focus on discovering new eclipsing binaries with delta Scuti component(s). We searched within the northern Transiting Exoplanet Survey Satellite (TESS) field with a visual inspection by following some criteria such as light curve shape, the existence of pulsation like variations in the out-of-eclipse light curve and the T (eff) values of the targets. As a result of these criteria, we discovered some targets. The orbital variations were first removed from the TESS light curves and frequency analysis was performed on the residuals. The luminosity, and absolute and bolometric magnitudes of the targets were calculated as well. To find how much of these parameters represent the primary (more luminous) binary component, we also computed the flux density ratio of the systems by utilizing the area of the eclipses. In addition, the positions of the systems in the H-R diagram were examined considering the flux density ratios. As a consequence of the investigation, we defined 38 candidate delta Scuti stars and also one Maia variable in eclipsing binary systems.Scientific and Technological Research Council (TUBITAK) [120F330]; NASA Explorer ProgramThis work has been supported in part by the Scientific and Technological Research Council (TUBITAK) under Grant No. 120F330. The TESS data presented in this paper were obtained from the Mikulski Archive for Space Telescopes (MAST). F.K.A. thanks Prof. Gerald Handler for showing how to clean binarity with a phenomenological fit. Funding for the TESS mission is provided by the NASA Explorer Program. This work has made use of data from the European Space Agency (ESA) mission Gaia (http://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, http://www.cosmos.esa.int/web/gaia/dpac/consortium).Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. This research has made use of the SIMBAD database, operated at CDS, Strasbourq, France

Halloysite nanotube-enhanced polyacrylonitrile ultrafiltration membranes: fabrication, characterization, and performance evaluation

This research focuses on the production and characterization of pristine polyacrylonitrile (PAN) as well as halloysite nanotube (HNT)-doped PAN ultrafiltration (UF) membranes via the phase inversion technique. Membranes containing 0.1, 0.5, and 1% wt HNT in 16% wt PAN are fabricated, and their chemical compositions are examined using Fourier transform infrared (FTIR) spectroscopy. Scanning electron microscopy (SEM) is utilized to characterize the membranes’ surface and cross-sectional morphologies. Atomic force microscopy (AFM) is employed to assess the roughness of the PAN/HNT membrane. Thermal characterization is conducted using thermal gravimetric analysis (TGA) and differential thermal analysis (DTA), while contact angle and water content measurements reveal the hydrophilic/hydrophobic properties. The pure water flux (PWF) performance of the porous UF water filtration membranes is evaluated at 3 bar, with porosity and mean pore size calculations. The iron (Fe), manganese (Mn), and total organic carbon (TOC) removal efficiencies of PAN/HNT membranes from dam water are examined, and the surfaces of fouled membranes are investigated by using SEM post-treatment. Mechanical characterization encompasses tensile testing, the Mori–Tanaka homogenization approach, and finite element analysis. The findings offer valuable insights into the impact of HNT doping on PAN membrane characteristics and performance, which will inform future membrane development initiatives

Arsenic as an Endocrine Disruptor: Arsenic Disrupts Retinoic Acid Receptor–and Thyroid Hormone Receptor–Mediated Gene Regulation and Thyroid Hormone–Mediated Amphibian Tail Metamorphosis

Background: Chronic exposure to excess arsenic in drinking water has been strongly associated with increased risks of multiple cancers, diabetes, heart disease, and reproductive and developmental problems in humans. We previously demonstrated that As, a potent endocrine disruptor at low, environmentally relevant levels, alters steroid signaling at the level of receptor-mediated gene regulation for all five steroid receptors. Objectives: The goal of this study was to determine whether As can also disrupt gene regulation via the retinoic acid (RA) receptor (RAR) and/or the thyroid hormone (TH) receptor (TR) and whether these effects are similar to previously observed effects on steroid regulation. Methods and results: Human embryonic NT2 or rat pituitary GH3 cells were treated with 0.01–5 μM sodium arsenite for 24 hr, with or without RA or TH, respectively, to examine effects of As on receptor-mediated gene transcription. At low, noncytotoxic doses, As significantly altered RAR-dependent gene transcription of a transfected RAR response element–luciferase construct and the native RA-inducible cytochrome P450 CYP26A gene in NT2 cells. Likewise, low-dose As significantly altered expression of a transfected TR response element–luciferase construct and the endogenous TR-regulated type I deiodinase (DIO1) gene in a similar manner in GH3 cells. An amphibian ex vivo tail metamorphosis assay was used to examine whether endocrine disruption by low-dose As could have specific pathophysiologic consequences, because tail metamorphosis is tightly controlled by TH through TR. TH-dependent tail shrinkage was inhibited in a dose-dependent manner by 0.1– 4.0 μM As. Conclusions: As had similar effects on RAR- and TR-mediated gene regulation as those previously observed for the steroid receptors, suggesting a common mechanism or action. Arsenic also profoundly affected a TR-dependent developmental process in a model animal system at very low concentrations. Because RAR and TH are critical for both normal human development and adult function and their dysregulation is associated with many disease processes, disruption of these hormone receptor–dependent processes by As is also potentially relevant to human developmental problems and disease risk

Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts

As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human–water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of sociohydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, https://doi.org/10.5880/GFZ.4.4.2023.001)

The challenge of unprecedented floods and droughts in risk management

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3