Geographic differences in Blainville's beaked whale (Mesoplodon densirostris) echolocation clicks

Aim

Understanding cetacean species' distributions and population structure over space and time is necessary for effective conservation and management. Geographic differences in acoustic signals may provide a line of evidence for population-level discrimination in some cetacean species. We use acoustic recordings collected over broad spatial and temporal scales to investigate whether global variability in echolocation click peak frequency could elucidate population structure in Blainville's beaked whale (Mesoplodon densirostris), a cryptic species well-studied acoustically.

Location

North Pacific, Western North Atlantic and Gulf of Mexico.

Time period

2004–2021.

Major taxa studied

Blainville's beaked whale.

Methods

Passive acoustic data were collected at 76 sites and 150 cumulative years of data were analysed to extract beaked whale echolocation clicks. Using an automated detector and subsequent weighted network clustering on spectral content and interclick interval of clicks, we determined the properties of a primary cluster of clicks with similar characteristics per site. These were compared within regions and across ocean basins and evaluated for suitability as population-level indicators.

Results

Spectral averages obtained from primary clusters of echolocation clicks identified at each site were similar in overall shape but varied in peak frequency by up to 8 kHz. We identified a latitudinal cline, with higher peak frequencies occurring in lower latitudes.

Main conclusions

It may be possible to acoustically delineate populations of Blainville's beaked whales. The documented negative correlation between signal peak frequency and latitude could relate to body size. Body size has been shown to influence signal frequency, with lower frequencies produced by larger animals, which are subsequently more common in higher latitudes for some species, although data are lacking to adequately investigate this for beaked whales. Prey size and depth may shape frequency content of echolocation signals, and larger prey items may occur in higher latitudes, resulting in lower signal frequencies of their predators.     

Cyclic dipeptide-based small molecules modulate zinc-mediated liquid–liquid phase separation of tau

Liquid–liquid phase separation (LLPS) is a complex physicochemical phenomenon mediated by multivalent transient weak interactions among macromolecules like polymers, proteins, and nucleic acids. It has implications in cellular physiology and disease conditions like cancer and neurodegenerative disorders. Many proteins associated with neurodegenerative disorders like RNA binding protein FUS (FUsed in Sarcoma), alpha-synuclein (α-Syn), TAR DNA binding protein 43 (TDP-43), and tau are shown to undergo LLPS. Recently, the tau protein responsible for Alzheimer's disease (AD) and other tauopathies is shown to phase separate into condensates in vitro and in vivo. The diverse noncovalent interactions among the biomolecules dictate the complex LLPS phenomenon. There are limited chemical tools to modulate protein LLPS which has therapeutic potential for neurodegenerative disorders. We have rationally designed cyclic dipeptide (CDP)-based small-molecule modulators (SMMs) by integrating multiple chemical groups that offer diverse chemical interactions to modulate tau LLPS. Among them, compound 1c effectively inhibits and dissolves Zn-mediated tau LLPS condensates. The SMM also inhibits tau condensate-to-fibril transition (tau aggregation through LLPS). This approach of designing SMMs of LLPS establishes a novel platform that has potential implication for the development of therapeutics for neurodegenerative disorders.     

Proportional processing of a visual mate choice signal in the green swordtail,Xiphophorus hellerii

During mate choice, receivers often assess the magnitude (duration, size, etc.) of signals that vary along a continuum and reflect variation in signaller quality. It is generally assumed that receivers assess this variation linearly, meaning each difference in signalling trait between signallers results in a commensurate change in receiver response. However, increasing evidence shows receivers can respond to signals non-linearly, for example through Weber's Law of proportional processing, where discrimination between stimuli is based on proportional, rather than absolute, differences in magnitude. We quantified mate preferences of female green swordtail fish, Xiphophorus hellerii, for pairs of males differing in body size. Preferences for larger males were better predicted by the proportional difference between males (proportional processing) than the absolute difference (linear processing). This demonstration of proportional processing of a visual signal implies that receiver perception may be an important mechanism selecting against the evolution of ever-larger signalling traits.     

基于益生菌治疗帕金森病的研究进展

帕金森病是常见的神经退行性疾病,其发病原因至今尚未明确,目前的治疗方法价格昂贵、效果差且副作用大。帕金森病患者常见胃肠道功能障碍,帕金森病和肠道菌群之间的关联已得到实验证实,患者有望通过益生菌改善肠道菌群达到治疗的目的。工程益生菌的出现使得人们可以按照自己的意愿改造益生菌,提高其稳定性和靶向性,展现出其特有的应用潜力。本文将从益生菌治疗帕金森病的研究现状出发,阐述益生菌治疗帕金森病的可能机制,进一步分析工程益生菌治疗帕金森病的可行性,为该疾病的安全治疗提供新的思路。     

Programmed ageing: decline of stem cell renewal,immunosenescence, and Alzheimer's disease

The characteristic maximum lifespan varies enormously across animal species from a few hours to hundreds of years. This argues that maximum lifespan, and the ageing process that itself dictates lifespan, are to a large extent genetically determined. Although controversial, this is supported by firm evidence that semelparous species display evolutionarily programmed ageing in response to reproductive and environmental cues. Parabiosis experiments reveal that ageing is orchestrated systemically through the circulation, accompanied by programmed changes in hormone levels across a lifetime. This implies that, like the circadian and circannual clocks, there is a master ‘clock of age’ (circavital clock) located in the limbic brain of mammals that modulates systemic changes in growth factor and hormone secretion over the lifespan, as well as systemic alterations in gene expression as revealed by genomic methylation analysis. Studies on accelerated ageing in mice, as well as human longevity genes, converge on evolutionarily conserved fibroblast growth factors (FGFs) and their receptors, including KLOTHO, as well as insulin-like growth factors (IGFs) and steroid hormones, as key players mediating the systemic effects of ageing. Age-related changes in these and multiple other factors are inferred to cause a progressive decline in tissue maintenance through failure of stem cell replenishment. This most severely affects the immune system, which requires constant renewal from bone marrow stem cells. Age-related immune decline increases risk of infection whereas lifespan can be extended in germfree animals. This and other evidence suggests that infection is the major cause of death in higher organisms. Immune decline is also associated with age-related diseases. Taking the example of Alzheimer's disease (AD), we assess the evidence that AD is caused by immunosenescence and infection. The signature protein of AD brain, Aβ, is now known to be an antimicrobial peptide, and Aβ deposits in AD brain may be a response to infection rather than a cause of disease. Because some cognitively normal elderly individuals show extensive neuropathology, we argue that the location of the pathology is crucial – specifically, lesions to limbic brain are likely to accentuate immunosenescence, and could thus underlie a vicious cycle of accelerated immune decline and microbial proliferation that culminates in AD. This general model may extend to other age-related diseases, and we propose a general paradigm of organismal senescence in which declining stem cell proliferation leads to programmed immunosenescence and mortality.     

Metabolic defects shared by Alzheimer's disease and diabetes: A focus on mitochondria

Type 2 diabetes (T2D) and Alzheimer's disease (AD) are two global epidemics that share several metabolic defects, such as insulin resistance, impaired glucose metabolism, and mitochondrial defects. Importantly, strong evidence demonstrates that T2D significantly increases the risk of cognitive decline and dementia, particularly AD. Here, we provide an overview of the metabolic defects that characterize and link both pathologies putting the focus on mitochondria. The biomarker potential of mitochondrial components and the therapeutic potential of some drugs that target and modulate mitochondria are also briefly discussed.     

Design considerations for two-stage enrichment clinical trials

When there is a predictive biomarker, enrichment can focus the clinical trial on a benefiting subpopulation. We describe a two-stage enrichment design, in which the first stage is designed to efficiently estimate a threshold and the second stage is a “phase III-like” trial on the enriched population. The goal of this paper is to explore design issues: sample size in Stages 1 and 2, and re-estimation of the Stage 2 sample size following Stage 1. By treating these as separate trials, we can gain insight into how the predictive nature of the biomarker specifically impacts the sample size. We also show that failure to adequately estimate the threshold can have disastrous consequences in the second stage. While any bivariate model could be used, we assume a continuous outcome and continuous biomarker, described by a bivariate normal model. The correlation coefficient between the outcome and biomarker is the key to understanding the behavior of the design, both for predictive and prognostic biomarkers. Through a series of simulations we illustrate the impact of model misspecification, consequences of poor threshold estimation, and requisite sample sizes that depend on the predictive nature of the biomarker. Such insight should be helpful in understanding and designing enrichment trials.     

Nonparametric and semiparametric estimation with sequentially truncated survival data

In observational cohort studies with complex sampling schemes, truncation arises when the time to event of interest is observed only when it falls below or exceeds another random time, that is, the truncation time. In more complex settings, observation may require a particular ordering of event times; we refer to this as sequential truncation. Estimators of the event time distribution have been developed for simple left-truncated or right-truncated data. However, these estimators may be inconsistent under sequential truncation. We propose nonparametric and semiparametric maximum likelihood estimators for the distribution of the event time of interest in the presence of sequential truncation, under two truncation models. We show the equivalence of an inverse probability weighted estimator and a product limit estimator under one of these models. We study the large sample properties of the proposed estimators and derive their asymptotic variance estimators. We evaluate the proposed methods through simulation studies and apply the methods to an Alzheimer's disease study. We have developed an R package, seqTrun , for implementation of our method.     

Mechanisms of Glucocerebrosidase Dysfunction in Parkinson’s Disease

Beta-glucocerebrosidase is a lysosomal hydrolase, encoded by GBA1 that represents the most common risk gene associated with Parkinson’s disease (PD) and Lewy Body Dementia. Glucocerebrosidase dysfunction has been also observed in the absence of GBA1 mutations across different genetic and sporadic forms of PD and related disorders, suggesting a broader role of glucocerebrosidase in neurodegeneration. In this review, we highlight recent advances in mechanistic characterization of glucocerebrosidase function as the foundation for development of novel therapeutics targeting glucocerebrosidase in PD and related disorders.     

Recognition of errors in three-dimensional structures of proteins

A major problem in the determination of the three-dimensional structure of proteins concerns the quality of the structural models obtained from the interpretation of experimental data. New developments in X-ray crystallography and nuclear magnetic resonance spectroscopy have acceleratedd the process of structure determination and the biological community is confronted with a steadily increasing number of experimentally determined protein folds. However, in the recent past several experimentally determined protein structures have been proven to contain major errors, indicating that in some cases the interpretation of experimental data is difficult and may yield incorrect models. Such problems can be avoided when computational methods are employed which complement experimental structure determinations. A prerequisite of such computational tools is that they are independent of the parameters obtained from a particular experiment. In addition such techniques are able to support and accelerate experimental structure determinations. Here we present techniques based on knowledge based mean fields which can be used to judge the quality of protein folds. The methods can be used to identify misfolded structures as well as faulty parts of structural models. The techniques are even applicable in cases where only the C_α trace of a protein conformation is available. The capabilities of the technique are demonstrated using correct and incorrect protein folds. © 1993 Wiley-Liss, Inc.