Pattern-based clustering of daily weigh-in trajectories using dynamic time warping

“Smart”-scales are a new tool for frequent monitoring of weight change as well as weigh-in behavior. These scales give researchers the opportunity to discover patterns in the frequency that individuals weigh themselves over time, and how these patterns are associated with overall weight loss. Our motivating data come from an 18-month behavioral weight loss study of 55 adults classified as overweight or obese who were instructed to weigh themselves daily. Adherence to daily weigh-in routines produces a binary times series for each subject, indicating whether a participant weighed in on a given day. To characterize weigh-in by time-invariant patterns rather than overall adherence, we propose using hierarchical clustering with dynamic time warping (DTW). We perform an extensive simulation study to evaluate the performance of DTW compared to Euclidean and Jaccard distances to recover underlying patterns in adherence time series. In addition, we compare cluster performance using cluster validation indices (CVIs) under the single, average, complete, and Ward linkages and evaluate how internal and external CVIs compare for clustering binary time series. We apply conclusions from the simulation to cluster our real data and summarize observed weigh-in patterns. Our analysis finds that the adherence trajectory pattern is significantly associated with weight loss.     

Dynamic genome-scale modeling of Saccharomyces cerevisiae unravels mechanisms for ester formation during alcoholic fermentation

Fermentation employing Saccharomyces cerevisiae has produced alcoholic beverages and bread for millennia. More recently, S. cerevisiae has been used to manufacture specific metabolites for the food, pharmaceutical, and cosmetic industries. Among the most important of these metabolites are compounds associated with desirable aromas and flavors, including higher alcohols and esters. Although the physiology of yeast has been well-studied, its metabolic modulation leading to aroma production in relevant industrial scenarios such as winemaking is still unclear. Here we ask what are the underlying metabolic mechanisms that explain the conserved and varying behavior of different yeasts regarding aroma formation under enological conditions? We employed dynamic flux balance analysis (dFBA) to answer this key question using the latest genome-scale metabolic model (GEM) of S. cerevisiae. The model revealed several conserved mechanisms among wine yeasts, for example, acetate ester formation is dependent on intracellular metabolic acetyl-CoA/CoA levels, and the formation of ethyl esters facilitates the removal of toxic fatty acids from cells using CoA. Species-specific mechanisms were also found, such as a preference for the shikimate pathway leading to more 2-phenylethanol production in the Opale strain as well as strain behavior varying notably during the carbohydrate accumulation phase and carbohydrate accumulation inducing redox restrictions during a later cell growth phase for strain Uvaferm. In conclusion, our new metabolic model of yeast under enological conditions revealed key metabolic mechanisms in wine yeasts, which will aid future research strategies to optimize their behavior in industrial settings.     

Elastic priors to dynamically borrow information from historical data in clinical trials

Use of historical data and real-world evidence holds great potential to improve the efficiency of clinical trials. One major challenge is to effectively borrow information from historical data while maintaining a reasonable type I error and minimal bias. We propose the elastic prior approach to address this challenge. Unlike existing approaches, this approach proactively controls the behavior of information borrowing and type I errors by incorporating a well-known concept of clinically significant difference through an elastic function, defined as a monotonic function of a congruence measure between historical data and trial data. The elastic function is constructed to satisfy a set of prespecified criteria such that the resulting prior will strongly borrow information when historical and trial data are congruent, but refrain from information borrowing when historical and trial data are incongruent. The elastic prior approach has a desirable property of being information borrowing consistent, that is, asymptotically controls type I error at the nominal value, no matter that historical data are congruent or not to the trial data. Our simulation study that evaluates the finite sample characteristic confirms that, compared to existing methods, the elastic prior has better type I error control and yields competitive or higher power. The proposed approach is applicable to binary, continuous, and survival endpoints.     

Selection of synthetic proteins to modulate the human frataxin function

Frataxin is a kinetic activator of the mitochondrial supercomplex for iron-sulfur cluster assembly. Low frataxin expression or a decrease in its functionality results in Friedreich's Ataxia (FRDA). With the aim of creating new molecular tools to study this metabolic pathway, and ultimately, to explore new therapeutic strategies, we have investigated the possibility of obtaining small proteins exhibiting a high affinity for frataxin. In this study, we applied the ribosome display approach, using human frataxin as the target. We focused on Affi_224, one of the proteins that we were able to select after five rounds of selection. We have studied the interaction between both proteins and discussed some applications of this specific molecular tutor, concerning the modulation of the supercomplex activity. Affi_224 and frataxin showed a K_D value in the nanomolar range, as judged by surface plasmon resonance analysis. Most likely, it binds to the frataxin acidic ridge, as suggested by the analysis of chemical shift perturbations (nuclear magnetic resonance) and computational simulations. Affi_224 was able to increase Cys NFS1 desulfurase activation exerted by the FRDA frataxin variant G130V. Importantly, Affi_224 interacts with frataxin in a human cellular model. Our results suggest quaternary addition may be a new tool to modulate frataxin function in vivo. Nevertheless, more functional experiments under physiological conditions should be carried out to evaluate Affi_224 effectiveness in FRDA cell models.     

Correlation between protein stability and crystal properties of designed ROP variants

Six variants of the ROP protein, designed with the aim to analyze by X-ray crystallography loop formation and core packing interactions in 4-α-helical bundles- have been purified and a search of their crystallization conditions has been carried out. Five mutants yield crystals that are suitable for medium to high resolutionX-ray diffraction studies. For all mutants crystal size- sensitivity to X-irradiation and diffraction limit are correlated to their stability as determined by differential scanning calorimetry- in a manner which is not yet understood in detail. © Wiley-Liss, Inc.     

Population dynamics of japanese serow in relation to social organization and habitat conditions. I. Stability of Japanese serow density in stable habitat conditions

The density of a Japanese serow (Capricornis crispus) population, which has been in stable habitat conditions and free from hunting and predation, was investigated by direct observation of serows at Kusoudomari (336 ha), Wakinosawa village, Aomori Prefecture, Japan, during 1977–89. The vegetation, composed of mature mixed forest ofThujopsis with deciduous trees (43.2%), secondary forest of deciduous trees (23.4%) and a plantation of coniferous trees (30.0%) showed little change during the study period. The serows were counted 17 times each winter for 14 consecutive years. The serow population maintained a stable density with a mean of 12.5 individuals km⁻² (SD=1.4) ranging from 8.6 to 14.6 km⁻². The ratio of the proportion of kids (<1 year old) to serows more than 1 year old decreased, but density did not decrease during the study period. Though extremely severe winters with heavy snowfall in 1984–86 caused a decline in serow density, the density recovered within a few years. It was considered that the stability of the serow density resulted mainly from the stable food supply and the lack of human disturbance, such as forest cutting in the habitat. Stable population density for a long period is probably related to the social organization of the serow.     

Beyond the GTP-cap: Elucidating the molecular mechanisms of microtubule catastrophe

Almost 40 years since the discovery of microtubule dynamic instability, the molecular mechanisms underlying microtubule dynamics remain an area of intense research interest. The “standard model” of microtubule dynamics implicates a “cap” of GTP-bound tubulin dimers at the growing microtubule end as the main determinant of microtubule stability. Loss of the GTP-cap leads to microtubule “catastrophe,” a switch-like transition from microtubule growth to shrinkage. However, recent studies, using biochemical in vitro reconstitution, cryo-EM, and computational modeling approaches, challenge the simple GTP-cap model. Instead, a new perspective on the mechanisms of microtubule dynamics is emerging. In this view, highly dynamic transitions between different structural conformations of the growing microtubule end – which may or may not be directly linked to the nucleotide content at the microtubule end – ultimately drive microtubule catastrophe.     

新疆野核桃自然保护区不同坡向丛生野核桃年龄结构及数量动态

通过对新疆野核桃自然保护区丛生野核桃(Juglans regia)进行普查,以径级结构代替年龄结构,采用匀滑技术编制种群静态生命表,并运用时间序列模型预测种群数量动态,从而获得丛生野核桃树的龄级结构与动态。结果表明,不同坡向丛生野核桃以中龄级为主,年龄结构呈两头小中间大的纺锤型;4个坡向种群年龄结构的动态指数Vpi虽大于0,但最大仅为19.10%,且Vpi’极低,最大为1.12%,阳坡种群增长趋势最高,抗干扰能力最强,种群稳定性最好,半阳坡种群增长趋势最弱,抗干扰能力最弱,种群稳定性最差;各坡向种群均存在多个死亡高峰,阳坡最高峰在15龄级,半阳坡在15和18龄级,阴坡和半阴坡均在9龄级,存活曲线更接近Deevey-Ⅱ型;在未来2、5、10龄级后,中龄级个体数量减少,老龄个体呈增加趋势,丛生野核桃种群稳定性难以长期维持。因此对丛生野核桃幼苗的保护非常关键。