Minimum Degrees of Minimal Ramsey Graphs for Almost-Cliques

For graphs $F$ and $H$, we say $F$ is Ramsey for $H$ if every $2$-coloring of the edges of $F$ contains a monochromatic copy of $H$. The graph $F$ is Ramsey $H$-minimal if $F$ is Ramsey for $H$ and there is no proper subgraph $F'$ of $F$ so that $F'$ is Ramsey for $H$. Burr, Erdos, and Lovasz defined $s(H)$ to be the minimum degree of $F$ over all Ramsey $H$-minimal graphs $F$. Define $H_{t,d}$ to be a graph on $t+1$ vertices consisting of a complete graph on $t$ vertices and one additional vertex of degree $d$. We show that $s(H_{t,d})=d^2$ for all values $1<d\le t$; it was previously known that $s(H_{t,1})=t-1$, so it is surprising that $s(H_{t,2})=4$ is much smaller. We also make some further progress on some sparser graphs. Fox and Lin observed that $s(H)\ge 2\delta(H)-1$ for all graphs $H$, where $\delta(H)$ is the minimum degree of $H$; Szabo, Zumstein, and Zurcher investigated which graphs have this property and conjectured that all bipartite graphs $H$ without isolated vertices satisfy $s(H)=2\delta(H)-1$. Fox, Grinshpun, Liebenau, Person, and Szabo further conjectured that all triangle-free graphs without isolated vertices satisfy this property. We show that $d$-regular $3$-connected triangle-free graphs $H$, with one extra technical constraint, satisfy $s(H) = 2\delta(H)-1$; the extra constraint is that $H$ has a vertex $v$ so that if one removes $v$ and its neighborhood from $H$, the remainder is connected.Comment: 10 pages; 3 figure

In situ detection of dopamine using nitrogen incorporated diamond nanowire electrode

[[abstract]]Significant difference was observed for the simultaneous detection of dopamine (DA), ascorbic acid (AA), and uric acid (UA) mixture using nitrogen incorporated diamond nanowire (DNW) film electrodes grown by microwave plasma enhanced chemical vapor deposition. For the simultaneous sensing of ternary mixtures of DA, AA, and UA, well-separated voltammetric peaks are obtained using DNW film electrodes in differential pulse voltammetry (DPV) measurements. Remarkable signals in cyclic voltammetry responses to DA, AA and UA (three well defined voltammetric peaks at potentials around 235, 30, 367 mV for DA, AA and UA respectively) and prominent enhancement of the voltammetric sensitivity are observed at the DNW electrodes. In comparison to the DPV results of graphite, glassy carbon and boron doped diamond electrodes, the high electrochemical potential difference is achieved via the use of the DNW film electrodes which is essential for distinguishing the aforementioned analytes. The enhancement in EC properties is accounted for by increase in sp2 content, new C–N bonds at the diamond grains, and increase in the electrical conductivity at the grain boundary, as revealed by X-ray photoelectron spectroscopy and near edge X-ray absorption fine structure measurements. Consequently, the DNW film electrodes provide a clear and efficient way for the selective detection of DA in the presence of AA and UA.[[booktype]]紙

Advanced material against human (Including Covid‐19) and plant viruses: nanoparticles as a feasible strategy

The SARS‐CoV‐2 virus outbreak revealed that these nano‐pathogens have the ability to rapidly change lives. Undoubtedly, SARS‐CoV‐2 as well as other viruses can cause important global impacts, affecting public health, as well as, socioeconomic development. But viruses are not only a public health concern, they are also a problem in agriculture. The current treatments are often ineffective, are prone to develop resistance, or cause considerable adverse side effects. The use of nanotechnology has played an important role to combat viral diseases. In this review three main aspects are in focus: first, the potential use of nanoparticles as carriers for drug delivery. Second, its use for treatments of some human viral diseases, and third, its application as antivirals in plants. With these three themes, the aim is to give to readers an overview of the progress in this promising area of biotechnology during the 2017–2020 period, and to provide a glance at how tangible is the effectiveness of nanotechnology against viruses. Future prospects are also discussed. It is hoped that this review can be a contribution to general knowledge for both specialized and non‐specialized readers, allowing a better knowledge of this interesting topic.REDES‐ANID. Grant Number: 180003 Universidad de La Frontera. Grant Number: DI20‐1003 FAPESP. Grant Numbers: 2018/08194‐2, 2018/02832‐7 CNPq. Grant Numbers: 404815/2018‐9, 313117/2019‐5 CONICYT/FAPESP. Grant Number: 2018/08194‐2 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior. Grant Numbers: 001, ANID/FONDAP/15130015 FCT. Grant Number: PTDC/CTM‐TEX/28295/2017 FEDER POCI Portugal 2020 program COMPETE. Grant Number: UID/CTM/00264/2019 FCT/MCTE

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly