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Our objective was to investigate associations of body size (birth weight and body mass index (BMI)) and growth in height, body fat (adiposity) and lean mass during childhood and adolescence, with risk markers for diabetes in young South Asian adults. We studied 357 men and women aged 21 years from the Pune Children’s Study birth cohort. Exposures were 1) birth weight, 21-year BMI, both of these mutually adjusted, and their interaction, and 2) uncorrelated conditional measures of growth in height and proxies for gain in adiposity and lean mass from birth to 8 years (childhood) and 8 to 21 years (adolescence) constructed from birth weight, and weight, height, and skinfolds at 8 and 21 years. Outcomes were plasma glucose and insulin concentrations during an oral glucose tolerance test and derived indices of insulin resistance and secretion. Higher 21-year BMI was associated with higher glucose and insulin concentrations and insulin resistance, and lower disposition index. After adjusting for 21-year BMI, higher birth weight was associated with lower 120-min glucose and insulin resistance, and higher disposition index. In the growth analysis, greater adiposity gain during childhood and adolescence was associated with higher glucose, insulin and insulin resistance, and lower disposition index, with stronger effects from adolescent gain. Greater childhood lean gain and adolescent height gain were associated with lower 120-min glucose and insulin. Consistent with other studies, lower birth weight and higher childhood weight gain increases diabetes risk. Disaggregation of weight gain showed that greater child/adolescent adiposity gain and lower lean and height gain may increase risk.
Recently, Kit Fine's (1994) view that modal truths are true in virtue of, grounded in, or explained by essentialist truths has been under attack. In what follows we offer two responses to the wave of criticism against his view. While the first response is pretty straightforward, the second is based on the distinction between, what we call, Reductive Finean Essentialism and Non-Reductive Finean Essentialism. Engaging the work of Bob Hale on Non-Reductive Finean Essentialism, we aim to show that the arguments against Fine's view are unconvincing, while we acknowledge the presence of a deep standoff between the two views.
Executive dysfunction is a predominant cognitive symptom in cerebral small vessel disease (SVD). The Institute of Cognitive Neurology Frontal Screening (IFS) is a well-validated screening tool allowing the rapid assessment of multiple components of executive function in Spanish-speaking individuals. In this study, we examined performance on the IFS in subjects with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), an inherited condition leading to the early onset of SVD. We further explored associations between performance on the IFS and magnetic resonance imaging (MRI) markers of SVD.
We recruited 24 asymptomatic CADASIL subjects and 23 noncarriers from Colombia. All subjects underwent a research MRI and a neuropsychological evaluation, including the IFS. Structural MRI markers of SVD were quantified in each subject, together with an SVD Sum Score representing the overall burden of cerebrovascular alterations. General linear model, correlation, and receiver operating characteristic curve analyses were used to explore group differences on the IFS and relationships with MRI markers of SVD.
CADASIL subjects had a significantly reduced performance on the IFS Total Score. Performance on the IFS correlated with all quantified markers of SVD, except for brain atrophy and perivascular spaces enlargement. Finally, while the IFS Total Score was not able to accurately discriminate between carriers and noncarriers, it showed adequate sensitivity and specificity in detecting the presence of multiple MRI markers of SVD.
These results suggest that the IFS may be a useful screening tool to assess executive function and disease severity in the context of SVD.
Impairments of health related quality of life (HR-QoL), as well as effective treatment options, including atomoxetine, are well documented in Attention Deficit/Hyperactivity Disorder (ADHD).
Objectives & aims:
To identify prognostic factors of improvement in HR-QoL in children and adolescents with ADHD, after atomoxetine treatment, as measured by the Child Health and Illness Profile- Child Edition Parent Report Form (CHIP-CE PRF) Achievement (A) and Risk Avoidance (RA) domains.
Pooled data from children and adolescents with ADHD treated with atomoxetine from 3 placebo controlled and separate data from 3 open-label trials were analyzed using logistic regression methodology. Only subjects impaired at baseline in the CHIP-CE PRF A and RA domains with < 40 points were included (n = 190 and 183 in the double-blind pooled sample; 422 and 355 from the open-label studies, respectively). Treatment outcome after 8–16 weeks was categorised as < 2.5 points change, between 2.5 and 10 points or more than 10 points change.
Based on data of the pooled sample of double-blind studies, baseline impairment in CHIP-CE sub-domains and study (overall study effect: p < 0.001) were associated with treatment outcome for both outcome domains, while having early Treatment Emergent Adverse Events (OR: 2.0) was associated with improved outcome on the RA domain. Additionally, across the 3 open-label studies, initial symptom response (OR: 3.2–15.6) was most robustly associated with treatment outcome.
Baseline impairment in HR-QoL as well as initial treatment response may be prognostic factors of atomoxetine treatment outcome in HR-QoL in children and adolescents with ADHD.
This naturalistic, observational pan-European study assessed the safety and early effectiveness of intramuscular (IM) psychotropic treatments in patients with acute agitation suffering from schizophrenia or bipolar mania. One thousand nine hundred and forty of 1945 patients completed the 24-hour observation period after initial IM treatment. Patients from 12 European countries were included (mean age 39 years; 58% male, 66% schizophrenia). IM treatment was at the physician's discretion. The primary objective was to describe the acute tolerability of IM psychotropic therapies in clinical practice, with particular emphasis on EPS. At baseline, 68% of the patients received IM monotherapy, with IM olanzapine most commonly prescribed (36%). During the first 24hours, 190 (9.8%) patients experienced EPS. The occurrence of EPS was statistically significantly lower in patients treated with IM olanzapine compared to those treated with other IM psychotropic medications (mainly typical antipsychotics and benzodiazepines): acute dystonia: 1.1%, 95% CI 0.5–2.3 and 2.9%, CI 2.0–4.0; akathisia: 2.3%, CI 1.3–3.7 and 5.5%, CI 4.3–6.9; Parkinsonism: 2.9%, CI 1.8–4.4 and 7.8%, CI 6.4–9.4, respectively. Anticholinergic treatment was given to 12% IM olanzapine versus 31% non-olanzapine treated patients. Acute agitation after 24hours was reduced by 1.68 (95% CI 1.46–1.91) points on the Clinical Global Impression of Severity (CGI-S) in IM olanzapine patients and 1.51 (95% CI 1.30–1.73) points in non-olanzapine patients. Additional psychotropic medication was required for 90% of the patients during the first 24hours of treatment. Results provide naturalistic evidence for low EPS rates and improvement of agitation with IM psychotropic medications during acute states of patients suffering from acute mania or schizophrenia.
Studies on relationships between music, visual imagery or therapeutic techniques, like mindfulness and emotions have been undertaken with varying success in predominantly adult populations. Their role in the child and adolescent population remains unclear.
Aims and objectives
We undertook a systematic literature review to assess current evidence in the use of music, guided imagery with/without therapeutic techniques for emotional processing in adults, children and adolescents.
We identified 87 relevant papers (JSTOR, OVID Medline, Cochrane, PubMed, Science Direct, Taylor & Francis and Wiley). We excluded non-English papers and qualitative analyses. Nine studies used quantitative techniques (Neuroimaging) for assessing emotional change using musical and non-musical stimuli (n = 77). Of these, four studies used fMRI and two used PET scans.
fMRI demonstrates a significant relation between amygdalar activation and emotional response to visual imagery (P < 0.05, n = 45). Early information using PET scanning shows a significant association between activation of different parts of brain with varied visual imagery (one study, n = 5) and varied music (one study, n = 10). There is similarity in the activation of specific cortical areas using musical and non-musical stimuli. Two separate studies of patients with damaged amygdala due to disease (n = 6) showed significant impairment of emotional processing and response.
There is early encouraging data providing evidence of possible relationships between music and visual imagery in emotional processing. Further studies are needed to examine these in detail, especially in children/adolescents. Music with visual imagery may be a useful adjunct in the self-guided processing of milder emotional disorders with components of anxiety, depression, adjustment and emotional dysregulation.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
Dual inhibition (2i) of Ras–MEK–ERK and GSK3β pathways enables the derivation of embryo stem cells (ESCs) from refractory mouse strains and, for permissive strains, allows ESC derivation with no external protein factor stimuli involvement. In addition, blocking of ERK signalling in 8-cell-stage mouse embryos leads to ablation of GATA4/6 expression in hypoblasts, suggesting fibroblast growth factor (FGF) dependence of hypoblast formation in the mouse. In human, bovine or porcine embryos, the hypoblast remains unaffected or displays slight-to-moderate reduction in cell number. In this study, we demonstrated that segregation of the hypoblast and the epiblast in rabbit embryos is FGF independent and 2i treatment elicits only a limited reinforcement in favour of OCT4-positive epiblast populations against the GATA4-/6-positive hypoblast population. It has been previously shown that TGFβ/Activin A inhibition overcomes the pervasive differentiation and inhomogeneity of rat iPSCs, rat ESCs and human iPSCs while prompting them to acquire naïve properties. However, TGFβ/Activin A inhibition, alone or together with Rho-associated, coiled-coil containing protein kinase (ROCK) inhibition, was not compatible with the viability of rabbit embryos according to the ultrastructural analysis of preimplantation rabbit embryos by electron microscopy. In rabbit models ovulation upon mating allows the precise timing of progression of the pregnancy. It produces several embryos of the desired stage in one pregnancy and a relatively short gestation period, making the rabbit embryo a suitable model to discover the cellular functions and mechanisms of maintenance of pluripotency in embryonic cells and the embryo-derived stem cells of other mammals.
An inscribed hexagonal fractal slotted patch antenna with some additional geometry and slots is proposed for the optimization in this paper. This research work is concerned with the optimization of this slotted fractal antenna with the help of the curve-fitting method in conjunction with the modified version of Lightning Attachment Procedure Optimization (MLAPO) technique. The data required for the curve-fitting technique and for the optimization technique have been obtained by varying some of the parameters of the proposed antenna. Different equations are developed to know the relations between these parameters of the proposed antenna. The MLAPO technique is applied thereafter to calculate the different optimized geometrical parameters to optimize the bandwidth for the proposed antenna. The optimized geometrical parameters are verified with the help of a parametric variation to justify the reliable optimization. The bandwidth obtained by the MLAPO technique has been found to be better than that obtained by PSO and normal LAPO algorithm. The prototype of the optimized antenna is fabricated and the experimental results are found to be compatible with the results obtained by simulation. The proposed optimized antenna may be utilized in various applications in C and X bands.
To avoid degradation of silicon anodes in lithium-ion batteries (LIBs), the authors report a new two-dimensional multi-layered Si-intercalated rGO (rGO/Si) anode prepared by direct growth of Si into a porous multi-layered reduced graphene oxide (rGO) film. Direct Si deposition onto the porous rGO film allows the Si layers to be intercalated into the film via in situ replacement of the oxygen groups of the multi-layered graphene oxide (GO) with Si through thermal reduction of the GO film. The porous rGO acts as a cushion against the expansion of the Si layer during lithiation, preventing the Si from being pulverized and producing highly stable LIBs.
We shall begin the chapter by explaining what PageRank is and how it is computed efficiently. Yet the war between those who want to make the Web useful and those who would exploit it for their own purposes is never over. When PageRank was established as an essential technique for a search engine, spammers invented ways to manipulate the PageRank of a Web page, often called link spam. That development led to the response of TrustRank and other techniques for preventing spammers from attacking PageRank. We shall discuss TrustRank and other approaches to detecting link spam. Finally, this chapter also covers some variations on PageRank. These techniques include topic-sensitive PageRank (which can also be adapted for combating link spam) and the HITS, or “hubs and authorities” approach to evaluating pages on the Web.
We include in this chapter a discussion of generalizations of MapReduce, first to systems that support acyclic workflows and then to systems that implement recursive algorithms. Our last topic for this chapter is the design of good MapReduce algorithms, a subject that often differs significantly from the matter of designing good parallel algorithms to be run on a supercomputer. When designing MapReduce algorithms, we often find that the greatest cost is in the communication. We thus investigate communication cost and what it tells us about the most efficient MapReduce algorithms. For several common applications of MapReduce we are able to give families of algorithms that optimally trade the communication cost against the degree of parallelism.
We begin our discussion of locality-sensitive hashing (LSH) with an examination of the problem of finding similar documents – those that share a lot of common text. We first show how to convert documents into sets in a way that lets us view textual similarity of documents as sets having a large overlap. A second key trick we need is minhashing, which is a way to convert large sets into much smaller representations, called signatures, that still enable us to estimate closely the Jaccard similarity of the represented sets. Finally, we see how to apply the bucketing idea inherent in LSH to the signatures. In Section 3.5 we begin our study of how to apply LSH to items other than sets. We consider the general notion of a distance measure that tells to what degree items are similar. Then, we consider the general idea of locality-sensitive hashing, and we see how to do LSH for some data types other than sets. We examine in detail several applications of the LSH idea. Finally, we consider some techniques for finding similar sets that can be more efficient than LSH when the degree of similarity we want is very high.
Clustering is the process of examining a collection of “points,” and grouping the points into “clusters” according to some distance measure. The goal is that points in the same cluster have a small distance from one another, while points in different clusters are at a large distance from one another. A suggestion of what clusters might look like was seen in Fig. 1.1. However, there the intent was that there were three clusters around three different road intersections, but two of the clusters blended into one another because they were not sufficiently separated. Our goal in this chapter is to offer methods for discovering clusters in data. We are particularly interested in situations where the data is very large, and/or where the space either is high-dimensional, or the space is not Euclidean at all. We shall therefore discuss several algorithms that assume the data does not fit in main memory. However, we begin with the basics: the two general approaches to clustering and the methods for dealing with clusters in a non-Euclidean space.
We begin with the essence of data mining and a discussion of how data mining is treated by the various disciplines that contribute to this field. We cover “Bonferroni’s Principle,” which is really a warning about overusing the ability to mine data. We also summarize a few useful ideas that are not data mining per se, but are useful in understanding some important data-mining concepts. These include the TF.IDF measure of word importance, behavior of hash functions and indexes, and identities involving e, the base of natural logarithms. Finally, we give an outline of the topics covered in the balance of the book.
In this chapter we shall explore the idea of dimensionality reduction in more detail. We begin with a discussion of eigenvalues and their use in “principal component analysis” (PCA). We cover singular-value decomposition, a more powerful version of UV-decomposition. Finally, because we are always interested in the largest data sizes we can handle, we look at another form of decomposition, called CUR-decomposition, which is a variant of singular-value decomposition that keeps the matrices of the decomposition sparse if the original matrix is sparse.
In this chapter, we shall consider the design of neural nets, which are collections of perceptrons, or nodes, where the outputs of one rank (or layer of nodes becomes the inputs to nodes at the next layer. The last layer of nodes produces the outputs of the entire neural net. The training of neural nets with many layers requires enormous numbers of training examples, but has proven to be an extremely powerful technique, referred to as deep learning, when it can be used.We also consider several specialized forms of neural nets that have proved useful for special kinds of data. These forms are characterized by requiring that certain sets of nodes in the network share the same weights. Since learning all the weights on all the inputs to all the nodes of the network is in general a hard and time-consuming task, these special forms of network greatly simplify the process of training the network to recognize the desired class or classes of inputs. We shall study convolutional neural networks (CNNs), which are specially designed to recognize classes of images. We shall also study recurrent neural networks (RNNs) and long short-term memory networks (LSTMs), which are designed to recognize classes of sequences, such as sentences (sequences of words).
Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.
By far the most lucrative venue for on-line advertising has been search, and much of the effectiveness of search advertising comes from the “adwords” model of matching search queries to advertisements. We shall therefore devote much of this chapter to algorithms for optimizing the way this assignment is done. The algorithms used are of an unusual type; they are greedy and they are “on-line” in a particular technical sense to be discussed. We shall therefore digress to discuss these two algorithmic issues – greediness and on-line algorithms – in general, before tackling the adwords problem. A second interesting on-line advertising problem involves selecting items to advertise at an on-line store. This problem involves “collaborative filtering,” where we try to find customers with similar behavior in order to suggest they buy things that similar customers have bought. This subject will be treated in Section 9.3.