T Cell Responses to Neural Autoantigens Are Similar in Alzheimer’s Disease Patients and Age-Matched Healthy Controls

Alzheimer’s disease (AD), a chronic multifactorial and complex neurodegenerative disorder is a leading cause of dementia. Recently, neuroinflammation has been hypothesized as a contributing factor to AD pathogenesis. The role of adaptive immune responses against neuronal antigens, which can either confer protection or induce damage in AD, has not been fully characterized. Here, we measured T cell responses to several potential antigens of neural origin including amyloid precursor protein (APP), amyloid beta (Aβ), tau, α-synuclein, and transactive response DNA binding protein (TDP-43) in patients with AD and age-matched healthy controls (HC). Antigen-specific T cell reactivity was detected for all tested antigens, and response to tau-derived epitopes was particularly strong, but no significant differences between individuals with AD and age-matched HC were identified. We also did not observe any correlation between the antigen-specific T cell responses and clinical variables including age, gender, years since diagnosis and cognitive score. Additionally, further characterization did not reveal any differences in the relative frequency of major Peripheral Blood Mononuclear Cells (PBMC) subsets, or in the expression of genes between AD patients and HC. These observations have not identified a key role of neuronal antigen-specific T cell responses in AD

Enhanced field emission from carbon nanotube–conducting polymer composites with low loading

Electron field emission measurements were carried out in a vacuum on single-walled (SWNT), double-walled (DWNT) and multi-walled (MWNT) carbon nanotubes (1 wt%) embedded in a conducting polymer polyaniline (PANI) matrix prepared by chemical and electrochemical methods. The turn-on field (Eto) for electron emission ranges from 2 to 3 V/μm and the field enhancement factor β is very high, varying from 6000 to 7500. No field emission was observed from pure PANI films and MWNT (1%) PANI films up to 9 V/μm

Hesitant Intuitionistic Fuzzy Approach in Optimal Irrigation Planning in India

The hesitant intuitionistic fuzzy optimization method optimizes multi-objective optimization problems under uncertainty and hesitation, and reflects the practical aspects of better decision-making. Hesitant intuitionistic fuzzy optimization (HIFO), a new optimization technique, has been suggested in the current study to find the best cropping pattern in the Kakrapar Right Bank Main Canal (KRBMC) command area of Ukai-Kakrapar Water Resources Project in India. The HIFO multi-objective fuzzy linear programming (HIFO MOFLP) result includes three objectives: maximization of net irrigation benefits (NIB), maximization of employment generation (EG), and minimization of cost of cultivation (CC), along with the appropriate constraints set. The performance of the aforesaid model is evaluated based on irrigation intensity, degree of acceptance (αr), and degree of rejection (βr) for inflows corresponding to 75% exceedance probability. The irrigation intensity from the study HIFO MOFLP model has been found to be 82.05%, while NIB, EG, and CC from the proposed model are 5572.31 million Rs, 14,287.27 thousand-man days, and 3429.99 million Rs, respectively. The proposed HIFO MOFLP model has been compared with the IFO MOFLP approach for the same command area and found to give improved results in the form of the irrigation intensity of the command area and objective function values. The current study demonstrates how hesitant fuzzy membership functions and non-membership functions can be applied to deal with uncertainty and hesitation in a real-world problem

Graphene Oxide–MnFe2O4 Magnetic Nanohybrids for Efficient Removal of Lead and Arsenic from Water

We show that the hybrids of single-layer graphene oxide with manganese ferrite magnetic nanoparticles have the best adsorption properties for efficient removal of Pb(II), As(III), and As(V) from contaminated water. The nanohybrids prepared by coprecipitation technique were characterized using atomic force and scanning electron microscopies, Fourier transformed infrared spectroscopy, Raman spectroscopy, X-ray diffraction, and surface area measurements. Magnetic character of the nanohybrids was ascertained by a vibrating sample magnetometer. Batch experiments were carried out to quantify the adsorption kinetics and adsorption capacities of the nanohybrids and compared with the bare nanoparticles of MnFe2O4. The adsorption data from our experiments fit the Langmuir isotherm, yielding the maximum adsorption capacity higher than the reported values so far. Temperature-dependent adsorption studies have been done to estimate the free energy and enthalpy of adsorption. Reusability, ease of magnetic separation, high removal efficiency, high surface area, and fast kinetics make these nanohybrids very attractive candidates for low-cost adsorbents for the effective coremoval of heavy metals from contaminated water

Graphene Oxide–MnFe₂O₄ Magnetic Nanohybrids for Efficient Removal of Lead and Arsenic from Water

We show that the hybrids of single-layer graphene oxide with manganese ferrite magnetic nanoparticles have the best adsorption properties for efficient removal of Pb­(II), As­(III), and As­(V) from contaminated water. The nanohybrids prepared by coprecipitation technique were characterized using atomic force and scanning electron microscopies, Fourier transformed infrared spectroscopy, Raman spectroscopy, X-ray diffraction, and surface area measurements. Magnetic character of the nanohybrids was ascertained by a vibrating sample magnetometer. Batch experiments were carried out to quantify the adsorption kinetics and adsorption capacities of the nanohybrids and compared with the bare nanoparticles of MnFe₂O₄. The adsorption data from our experiments fit the Langmuir isotherm, yielding the maximum adsorption capacity higher than the reported values so far. Temperature-dependent adsorption studies have been done to estimate the free energy and enthalpy of adsorption. Reusability, ease of magnetic separation, high removal efficiency, high surface area, and fast kinetics make these nanohybrids very attractive candidates for low-cost adsorbents for the effective coremoval of heavy metals from contaminated water

Superlattice of resonators on monolayer graphene created by intercalated gold nanoclusters

Here we report on a "new" type of ordering which allows to modify the electronic structure of a graphene monolayer (ML). We have intercalated small gold clusters between the top monolayer graphene and the buffer layer of epitaxial graphene. We show that these clusters perturb the quasiparticles on the ML graphene, and act as quantum dots creating a superlattice of resonators on the graphene ML, as revealed by a strong pattern of standing waves. A detailed analysis of the standing wave patterns using Fourier Transform Scanning Tunneling Spectroscopy strongly indicates that this phenomenon can arise from a strong modification of the band structure of graphene and (or) from Charge Density Waves (CDW)where a large extension of Van Hove singularities are involved.Comment: 12 pages, 5 figure