Lipid droplets (LDs) are energy-storage organelles that are coated with hundreds of proteins, including members of the perilipin (PLIN) family. PLIN5 is highly expressed in oxidative tissues, including the liver, and is thought to play a key role in uncoupling LD accumulation from lipotoxicity; however, the mechanisms behind this action are incompletely defined. We investigated the role of hepatic PLIN5 in inflammation and lipotoxicity in a murine model under both fasting and refeeding conditions and in hepatocyte cultures. PLIN5 ablation with antisense oligonucleotides triggered a pro-inflammatory response in livers from mice only under fasting conditions. Similarly, PLIN5 mitigated lipopolysaccharide- or palmitic acid-induced inflammatory responses in hepatocytes. During fasting, PLIN5 was also required for the induction of autophagy, which contributed to its anti-inflammatory effects. The ability of PLIN5 to promote autophagy and prevent inflammation were dependent upon signaling through sirtuin 1 (SIRT1), which is known to be activated in response to nuclear PLIN5 under fasting conditions. Taken together, these data show that PLIN5 signals via SIRT1 to promote autophagy and prevent FA-induced inflammation as a means to maintain hepatocyte homeostasis during periods of fasting and FA mobilization.

A greater decrease in 24-h energy expenditure (24EE) during 24h fasting defines a thriftier metabolic phenotype prone to weight gain during overfeeding and resistant to weight loss during caloric restriction. As the thermogenic response to mild cold exposure (COLD) may similarly characterize this human phenotype identified by acute fasting conditions, we analyzed changes in 24EE and sleeping metabolic rate (SLEEP) in a whole-room indirect calorimeter during 24h fasting at thermoneutrality (24°C) and during energy balance both at thermoneutrality (24°C) and mild cold (19°C) in 20 healthy volunteers (80% male, age: 36.6±11.4y, percentage body fat: 34.8±10.5%). Greater decrease in 24EE during fasting (thriftier phenotype) was associated with less increase in 24EE during COLD, i.e. less cold-induced thermogenesis. Greater decreases in plasma fibroblast growth factor 21 (FGF21) after 24h fasting and after COLD were highly correlated and associated with greater decreases in SLEEP in both conditions. We conclude that the metabolic responses to short-term fasting and COLD are associated and mediated by the liver-derived hormone FGF21. Thus, the 24EE response to COLD further identifies the thrifty versus spendthrift phenotype, providing an additional setting to investigate the physiological mechanisms underlying the human metabolic phenotype and characterizing the individual susceptibility to weight change.

Research Event

Event participants

Gavin Barwell, Downing Street Chief of Staff to Prime Minister Theresa May (2017-19)
Chair: Thomas Raines, Director, Europe Programme, Chatham House

Invitation Only Research Event

Event participants

Niels Engelschiøn, Director-General, Department for European Affairs, Norwegian Ministry of Foreign Affairs
Chair: Dr Robin Niblett, Director; Chief Executive, Chatham House

Invitation Only Research Event

Event participants

Duncan Robinson, Charlemagne Columnist; Brussels Bureau Chief, the Economist
Chair: Pepijn Bergsen, Research Fellow, Europe Programme, Chatham House

John J O'Sullivan
Aug 1, 1991; 14:758-760
Short Report

Robert A. Ritzel
Mar 1, 2006; 29:717-718
BR Pathophysiology/Complications

Rob M. van Dam
Dec 1, 2004; 27:2990-2992
Brief Reports

OBJECTIVE

To evaluate the efficacy and safety of fast-acting insulin aspart (faster aspart) compared with insulin aspart (IAsp), both with insulin degludec with or without metformin, in adults with type 2 diabetes not optimally controlled with a basal-bolus regimen.

OBJECTIVE

Acrylamide exposure from daily-consumed food has raised global concern. We aimed to assess the exposure-response relationships of internal acrylamide exposure with oxidative DNA damage, lipid peroxidation, and fasting plasma glucose (FPG) alteration and investigate the mediating role of oxidative DNA damage and lipid peroxidation in the association of internal acrylamide exposure with FPG.

OBJECTIVE

This study aims to evaluate the association of energy and macronutrient intake at dinner versus breakfast with disease-specific and all-cause mortality in people with diabetes.

WASHINGTON — Latinos and immigrants are at least twice as likely to lack health insurance coverage as the overall population in three central Kansas City metro counties, a new Migration Policy Institute (MPI) study reveals. In fact, they are four times as likely to be uninsured in Johnson County, Kansas. 

This deliciously warming Ayurvedic gluten-free breakfast idea came from my good friend Brenda when she owned Mondo Organics in Brisbane. I've tweaked it a little to suit what was in my pantry today. The perfect brekky after Sunday morning yoga and a great way to start your surfing day. Rolled rice is available at most good food stores and organic outlets. Best to use fresh turmeric for its antioxidant properties and up to you whether you want yoghurt too. I prefer mine with a squeeze of lime. Om Shanti.

I know, I had you at pizza, and you'll never leave once you've tasted this healthy take on an ol' school favourite. My love for pizza started early, in 1971 to be precise. 'What was this round flying salty saucer like bread thing?' my five year old self wondered as I spat out an anchovy. While my taste for whole anchovies never evolved, my love for the original flatlay has never died. On Lygon street in Melbourne around 1977 pizza burst into my childhood and that shredded ham was the shag pile of my youth. This continued to thrive late into my teens at Pinocchio's Pizza on Toorak Road until the ham shag endured cut backs and resizing. Next thing we knew rectangular gourmet pizza had landed - think walnuts, blue cheese and sun-dried tomatoes - and the market was cornered. Here in Byron Bay pizza just ain't the same, however the locals just love the wood fired goodness and there's a bounty of local produce just waiting for an idea. So here's one with no dough that I prepared earlier - let's call it Sammy's breakfast pizza.

This is a perfect breakfast on-the-go! Rich in omega-3 and omega-6, the chia balls absorb water and become jelly-like. You can make this a few days head and store it in the fridge.

OBJECTIVE

Previous studies suggested that childhood prediabetes may develop prior to obesity and be associated with relative insulin deficiency. We proposed that the insulin-deficient phenotype is genetically determined and tested this hypothesis by longitudinal modeling of insulin and glucose traits with diabetes risk genotypes in the EarlyBird cohort.

The food lowers cravings for high-sugar and high-fat foods and suppresses appetite during the day.

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Clothing trade -- Moral and ethical aspects.

London : [Published not identified], 1876.

Guanyang Wang.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1690--1706.

Abstract:
Uniform sampling of binary matrix with fixed margins is an important and difficult problem in statistics, computer science, ecology and so on. The well-known swap algorithm would be inefficient when the size of the matrix becomes large or when the matrix is too sparse/dense. Here we propose the Rectangle Loop algorithm, a Markov chain Monte Carlo algorithm to sample binary matrices with fixed margins uniformly. Theoretically the Rectangle Loop algorithm is better than the swap algorithm in Peskun’s order. Empirically studies also demonstrates the Rectangle Loop algorithm is remarkablely more efficient than the swap algorithm.

Ryoya Oda, Hirokazu Yanagihara.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1386--1412.

Abstract:
We put forward a variable selection method for selecting explanatory variables in a normality-assumed multivariate linear regression. It is cumbersome to calculate variable selection criteria for all subsets of explanatory variables when the number of explanatory variables is large. Therefore, we propose a fast and consistent variable selection method based on a generalized $C_{p}$ criterion. The consistency of the method is provided by a high-dimensional asymptotic framework such that the sample size and the sum of the dimensions of response vectors and explanatory vectors divided by the sample size tend to infinity and some positive constant which are less than one, respectively. Through numerical simulations, it is shown that the proposed method has a high probability of selecting the true subset of explanatory variables and is fast under a moderate sample size even when the number of dimensions is large.

We consider the problem of clustering with the longest-leg path distance (LLPD) metric, which is informative for elongated and irregularly shaped clusters. We prove finite-sample guarantees on the performance of clustering with respect to this metric when random samples are drawn from multiple intrinsically low-dimensional clusters in high-dimensional space, in the presence of a large number of high-dimensional outliers. By combining these results with spectral clustering with respect to LLPD, we provide conditions under which the Laplacian eigengap statistic correctly determines the number of clusters for a large class of data sets, and prove guarantees on the labeling accuracy of the proposed algorithm. Our methods are quite general and provide performance guarantees for spectral clustering with any ultrametric. We also introduce an efficient, easy to implement approximation algorithm for the LLPD based on a multiscale analysis of adjacency graphs, which allows for the runtime of LLPD spectral clustering to be quasilinear in the number of data points.

We present new excess risk bounds for general unbounded loss functions including log loss and squared loss, where the distribution of the losses may be heavy-tailed. The bounds hold for general estimators, but they are optimized when applied to $eta$-generalized Bayesian, MDL, and empirical risk minimization estimators. In the case of log loss, the bounds imply convergence rates for generalized Bayesian inference under misspecification in terms of a generalization of the Hellinger metric as long as the learning rate $eta$ is set correctly. For general loss functions, our bounds rely on two separate conditions: the $v$-GRIP (generalized reversed information projection) conditions, which control the lower tail of the excess loss; and the newly introduced witness condition, which controls the upper tail. The parameter $v$ in the $v$-GRIP conditions determines the achievable rate and is akin to the exponent in the Tsybakov margin condition and the Bernstein condition for bounded losses, which the $v$-GRIP conditions generalize; favorable $v$ in combination with small model complexity leads to $ ilde{O}(1/n)$ rates. The witness condition allows us to connect the excess risk to an 'annealed' version thereof, by which we generalize several previous results connecting Hellinger and Rényi divergence to KL divergence.

When the data is distributed across multiple servers, lowering the communication cost between the servers (or workers) while solving the distributed learning problem is an important problem and is the focus of this paper. In particular, we propose a fast, and communication-efficient decentralized framework to solve the distributed machine learning (DML) problem. The proposed algorithm, Group Alternating Direction Method of Multipliers (GADMM) is based on the Alternating Direction Method of Multipliers (ADMM) framework. The key novelty in GADMM is that it solves the problem in a decentralized topology where at most half of the workers are competing for the limited communication resources at any given time. Moreover, each worker exchanges the locally trained model only with two neighboring workers, thereby training a global model with a lower amount of communication overhead in each exchange. We prove that GADMM converges to the optimal solution for convex loss functions, and numerically show that it converges faster and more communication-efficient than the state-of-the-art communication-efficient algorithms such as the Lazily Aggregated Gradient (LAG) and dual averaging, in linear and logistic regression tasks on synthetic and real datasets. Furthermore, we propose Dynamic GADMM (D-GADMM), a variant of GADMM, and prove its convergence under the time-varying network topology of the workers.

This paper revisits the problem of computing empirical cumulative distribution functions (ECDF) efficiently on large, multivariate datasets. Computing an ECDF at one evaluation point requires $mathcal{O}(N)$ operations on a dataset composed of $N$ data points. Therefore, a direct evaluation of ECDFs at $N$ evaluation points requires a quadratic $mathcal{O}(N^2)$ operations, which is prohibitive for large-scale problems. Two fast and exact methods are proposed and compared. The first one is based on fast summation in lexicographical order, with a $mathcal{O}(N{log}N)$ complexity and requires the evaluation points to lie on a regular grid. The second one is based on the divide-and-conquer principle, with a $mathcal{O}(Nlog(N)^{(d-1){vee}1})$ complexity and requires the evaluation points to coincide with the input points. The two fast algorithms are described and detailed in the general $d$-dimensional case, and numerical experiments validate their speed and accuracy. Secondly, the paper establishes a direct connection between cumulative distribution functions and kernel density estimation (KDE) for a large class of kernels. This connection paves the way for fast exact algorithms for multivariate kernel density estimation and kernel regression. Numerical tests with the Laplacian kernel validate the speed and accuracy of the proposed algorithms. A broad range of large-scale multivariate density estimation, cumulative distribution estimation, survival function estimation and regression problems can benefit from the proposed numerical methods.

Ridge regression (RR) is a regularization technique that penalizes the L2-norm of the coefficients in linear regression. One of the challenges of using RR is the need to set a hyperparameter ($alpha$) that controls the amount of regularization. Cross-validation is typically used to select the best $alpha$ from a set of candidates. However, efficient and appropriate selection of $alpha$ can be challenging, particularly where large amounts of data are analyzed. Because the selected $alpha$ depends on the scale of the data and predictors, it is not straightforwardly interpretable. Here, we propose to reparameterize RR in terms of the ratio $gamma$ between the L2-norms of the regularized and unregularized coefficients. This approach, called fractional RR (FRR), has several benefits: the solutions obtained for different $gamma$ are guaranteed to vary, guarding against wasted calculations, and automatically span the relevant range of regularization, avoiding the need for arduous manual exploration. We provide an algorithm to solve FRR, as well as open-source software implementations in Python and MATLAB (https://github.com/nrdg/fracridge). We show that the proposed method is fast and scalable for large-scale data problems, and delivers results that are straightforward to interpret and compare across models and datasets.

Yanjun Qian, Jianhua Z. Huang, Chiwoo Park, Yu Ding.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1537--1563.

Abstract:
In situ transmission electron microscope (TEM) adds a promising instrument to the exploration of the nanoscale world, allowing motion pictures to be taken while nano objects are initiating, crystalizing and morphing into different sizes and shapes. To enable in-process control of nanocrystal production, this technology innovation hinges upon a solution addressing a statistical problem, which is the capability of online tracking a dynamic, time-varying probability distribution reflecting the nanocrystal growth. Because no known parametric density functions can adequately describe the evolving distribution, a nonparametric approach is inevitable. Towards this objective, we propose to incorporate the dynamic evolution of the normalized particle size distribution into a state space model, in which the density function is represented by a linear combination of B-splines and the spline coefficients are treated as states. The closed-form algorithm runs online updates faster than the frame rate of the in situ TEM video, making it suitable for in-process control purpose. Imposing the constraints of curve smoothness and temporal continuity improves the accuracy and robustness while tracking the probability distribution. We test our method on three published TEM videos. For all of them, the proposed method is able to outperform several alternative approaches.

Xin Bing, Florentina Bunea, Marten Wegkamp.

Source: Bernoulli, Volume 26, Number 3, 1765--1796.

Abstract:
Topic models have become popular for the analysis of data that consists in a collection of n independent multinomial observations, with parameters $N_{i}inmathbb{N}$ and $Pi_{i}in[0,1]^{p}$ for $i=1,ldots,n$. The model links all cell probabilities, collected in a $p imes n$ matrix $Pi$, via the assumption that $Pi$ can be factorized as the product of two nonnegative matrices $Ain[0,1]^{p imes K}$ and $Win[0,1]^{K imes n}$. Topic models have been originally developed in text mining, when one browses through $n$ documents, based on a dictionary of $p$ words, and covering $K$ topics. In this terminology, the matrix $A$ is called the word-topic matrix, and is the main target of estimation. It can be viewed as a matrix of conditional probabilities, and it is uniquely defined, under appropriate separability assumptions, discussed in detail in this work. Notably, the unique $A$ is required to satisfy what is commonly known as the anchor word assumption, under which $A$ has an unknown number of rows respectively proportional to the canonical basis vectors in $mathbb{R}^{K}$. The indices of such rows are referred to as anchor words. Recent computationally feasible algorithms, with theoretical guarantees, utilize constructively this assumption by linking the estimation of the set of anchor words with that of estimating the $K$ vertices of a simplex. This crucial step in the estimation of $A$ requires $K$ to be known, and cannot be easily extended to the more realistic set-up when $K$ is unknown. This work takes a different view on anchor word estimation, and on the estimation of $A$. We propose a new method of estimation in topic models, that is not a variation on the existing simplex finding algorithms, and that estimates $K$ from the observed data. We derive new finite sample minimax lower bounds for the estimation of $A$, as well as new upper bounds for our proposed estimator. We describe the scenarios where our estimator is minimax adaptive. Our finite sample analysis is valid for any $n,N_{i},p$ and $K$, and both $p$ and $K$ are allowed to increase with $n$, a situation not handled well by previous analyses. We complement our theoretical results with a detailed simulation study. We illustrate that the new algorithm is faster and more accurate than the current ones, although we start out with a computational and theoretical disadvantage of not knowing the correct number of topics $K$, while we provide the competing methods with the correct value in our simulations.

Quan Zhou, Yongtao Guan.

Source: Bayesian Analysis, Volume 14, Number 2, 573--594.

Abstract:
Bayesian variable selection regression (BVSR) is able to jointly analyze genome-wide genetic datasets, but the slow computation via Markov chain Monte Carlo (MCMC) hampered its wide-spread usage. Here we present a novel iterative method to solve a special class of linear systems, which can increase the speed of the BVSR model-fitting tenfold. The iterative method hinges on the complex factorization of the sum of two matrices and the solution path resides in the complex domain (instead of the real domain). Compared to the Gauss-Seidel method, the complex factorization converges almost instantaneously and its error is several magnitude smaller than that of the Gauss-Seidel method. More importantly, the error is always within the pre-specified precision while the Gauss-Seidel method is not. For large problems with thousands of covariates, the complex factorization is 10–100 times faster than either the Gauss-Seidel method or the direct method via the Cholesky decomposition. In BVSR, one needs to repetitively solve large penalized regression systems whose design matrices only change slightly between adjacent MCMC steps. This slight change in design matrix enables the adaptation of the iterative complex factorization method. The computational innovation will facilitate the wide-spread use of BVSR in reanalyzing genome-wide association datasets.

Affected by the dark reality of hopelessness she’s encountered in Madagascar, Caitlin Red prays that God will do miraculous things amongst the Malagasy people.

The Passover season leads to a young Israeli woman asking about the Passover Lamb.

By the single most important metric, charter schools are succeeding, argues Bruno V. Manno.

Heart rate continues to be the single most important indicator of well-being in a newborn. Availability of a reliable method to determine heart rate in the first minute would help determine resuscitation interventions, particularly for the extremely premature infant.

Electrocardiograms can provide a reliable, continuous heart rate in the most premature infants in the first minute of resuscitation compared with pulse oximeters. (Read the full article)

Mobile devices are ubiquitous in children’s lives, but how caregivers and children use them in everyday situations, and how use of devices affects caregiver–child interactions, has not been studied.

In naturalistic mealtime observations, we documented the behavior of many caregivers whose attention was highly absorbed in their mobile devices, with varying child reactions to this absorption. This study raises several hypotheses about mobile device use and caregiver-child interaction. (Read the full article)

Menu labels depicting physical activity calorie equivalents may lead to ordering of fast food meals totaling fewer calories for adults. The effects of physical activity calorie equivalent labeling on parents’ fast food decisions for their children have not been examined.

Parents shown menus with any type of caloric content label may order fast food meals totaling fewer calories for their children. Menu labels showing physical activity equivalents may be more likely to influence parents to encourage their children to exercise. (Read the full article)

With a fledgling democratic government and a formal peace process finally in place in the Democratic Republic of Congo (DRC), the country will celebrate its 50th year of independence next month.

The 8TB SSD prototype includes SuperSpeed USB 20Gbps support; WD also showed off a portable Luxe drive with USB-C and five WD_Black drives for console and PC gamers

It's an 802.11ax versus 802.11ac speed showdown! We pit three Wi-Fi 6 routers against our top-performing Wi-Fi 5 router to see what you can gain by upgrading.

Nearly every state in the nation has experienced enrollment declines, with some states seeing steep declines of more than 50 percent.

A new supercapacitor based on manganese oxide could combine the storage capacity of batteries with the high power and fast charging of other supercapacitors, according to researchers at Penn State and two universities in China.

Google's quantum computer performed a computation in 200 seconds that would have taken the world's fastest supercomputer 10,000 years to calculate. But IBM is dismissing Google's claim that it achieved quantum supremacy.

Somerset West stands out as one of the fastest growing property areas – commercial, residential and industrial - in the Western Cape, according to a new report on the state of the property sector in the Western Cape.

The third Saturday of every month OM Chile organises a free breakfast, during which team members present missions initiatives in Chile and worldwide.

As tough taskmasters, challenges have a way of helping us expand the horizons of what we believe to be possible, and put our creativity to the best use while navigating around a tense situation.

The Bombay toasty is a special sandwich sold on the streets of Bombay which is made with lots of fresh vegetables, mint chutney and butter.