Experimental Studies and Dynamics Modeling Analysis of the Swimming and Diving of Whirligig Beetles (Coleoptera: Gyrinidae)

Whirligig beetles (Coleoptera, Gyrinidae) can fly through the air, swiftly swim on the surface of water, and quickly dive across the air-water interface. The propulsive efficiency of the species is believed to be one of the highest measured for a thrust generating apparatus within the animal kingdom. The goals of this research were to understand the distinctive biological mechanisms that allow the beetles to swim and dive, while searching for potential bio-inspired robotics applications. Through static and dynamic measurements obtained using a combination of microscopy and high-speed imaging, parameters associated with the morphology and beating kinematics of the whirligig beetle\u27s legs in swimming and diving were obtained. Using data obtained from these experiments, dynamics models of both swimming and diving were developed. Through analysis of simulations conducted using these models it was possible to determine several key principles associated with the swimming and diving processes. First, we determined that curved swimming trajectories were more energy efficient than linear trajectories, which explains why they are more often observed in nature. Second, we concluded that the hind legs were able to propel the beetle farther than the middle legs, and also that the hind legs were able to generate a larger angular velocity than the middle legs. However, analysis of circular swimming trajectories showed that the middle legs were important in maintaining stable trajectories, and thus were necessary for steering. Finally, we discovered that in order for the beetle to transition from swimming to diving, the legs must change the plane in which they beat, which provides the force required to alter the tilt angle of the body necessary to break the surface tension of water. We have further examined how the principles learned from this study may be applied to the design of bio-inspired swimming/diving robots. DOI: 10.1371/journal.pcbi.100279

Double-Stranded RNA-Dependent Protein Kinase Regulates the Motility of Breast Cancer Cells

Double-stranded RNA (dsRNA)-dependent protein kinase (PKR) is an interferon-induced protein kinase that plays a central role in the anti-viral process. Due to its pro-apoptotic and anti-proliferative action, there is an increased interest in PKR modulation as an anti-tumor strategy. PKR is overexpressed in breast cancer cells; however, the role of PKR in breast cancer cells is unclear. The expression/activity of PKR appears inversely related to the aggressiveness of breast cancer cells. The current study investigated the role of PKR in the motility/migration of breast cancer cells. The activation of PKR by a synthesized dsRNA (PIC) significantly decreased the motility of several breast cancer cell lines (BT474, MDA-MB231 and SKBR3). PIC inhibited cell migration and blocked cell membrane ruffling without affecting cell viability. PIC also induced the reorganization of the actin cytoskeleton and impaired the formation of lamellipodia. These effects of PIC were reversed by the pretreatment of a selective PKR inhibitor. PIC also activated p38 mitogen-activated protein kinase (MAPK) and its downstream MAPK-activated protein kinase 2 (MK2). PIC-induced activation of p38 MAPK and MK2 was attenuated by the PKR inhibitor and the PKR siRNA, but a selective p38 MAPK inhibitor (SB203580) or other MAPK inhibitors did not affect PKR activity, indicating that PKR is upstream of p38 MAPK/MK2. Cofilin is an actin severing protein and regulates membrane ruffling, lamellipodia formation and cell migration. PIC inhibited cofilin activity by enhancing its phosphorylation at Ser3. PIC activated LIM kinase 1 (LIMK1), an upstream kinase of cofilin in a p38 MAPK-dependent manner. We concluded that the activation of PKR suppressed cell motility by regulating the p38 MAPK/MK2/LIMK/cofilin pathway

The association of long-term trajectories of BMI, its variability, and metabolic syndrome: a 30-year prospective cohort study

Background Limited data exists on how early-life weight changes relate to metabolic syndrome (MetS) risk in midlife. This study examines the association between long-term trajectories of body mass index (BMI), its variability, and MetS risk in Chinese individuals. Methods In the Hanzhong Adolescent Hypertension study (March 10, 1987–June 3, 2017), 1824 participants with at least five BMI measurements from 1987 to 2017 were included. Using group-based trajectory modeling, different BMI trajectories were identified. BMI variability was assessed through standard deviation (SD), variability independent of the mean (VIM), and average real variability (ARV). Logistic regression analyzed the relationship between BMI trajectory, BMI variability, and MetS occurrence in midlife (URL: https://www.clinicaltrials.gov; Unique identifier: NCT02734472). Findings BMI trajectories were categorized as low-increasing (34.4%), moderate-increasing (51.8%), and high-increasing (13.8%). Compared to the low-increasing group, the odds ratios (ORs) [95% CIs] for MetS were significantly higher in moderate (4.27 [2.63–6.91]) and high-increasing groups (13.11 [6.30–27.31]) in fully adjusted models. Additionally, higher BMI variabilities were associated with increased MetS odds (ORs for SDBMI, VIMBMI, and ARVBMI: 2.30 [2.02–2.62], 1.22 [1.19–1.26], and 4.29 [3.38–5.45]). Furthermore, BMI trajectories from childhood to adolescence were predictive of midlife MetS, with ORs in moderate (1.49 [1.00–2.23]) and high-increasing groups (2.45 [1.22–4.91]). Lastly, elevated BMI variability in this period was also linked to higher MetS odds (ORs for SDBMI, VIMBMI, and ARVBMI: 1.24 [1.08–1.42], 1.00 [1.00–1.01], and 1.21 [1.05–1.38]). Interpretation Our study suggests that both early-life BMI trajectories and BMI variability could be predictive of incident MetS in midlife

Mudskipper genomes provide insights into the terrestrial adaptation of amphibious fishes

Mudskippers are amphibious fishes that have developed morphological and physiological adaptations to match their unique lifestyles. Here we perform whole-genome sequencing of four representative mudskippers to elucidate the molecular mechanisms underlying these adaptations. We discover an expansion of innate immune system genes in the mudskippers that may provide defence against terrestrial pathogens. Several genes of the ammonia excretion pathway in the gills have experienced positive selection, suggesting their important roles in mudskippers’ tolerance to environmental ammonia. Some vision-related genes are differentially lost or mutated, illustrating genomic changes associated with aerial vision. Transcriptomic analyses of mudskippers exposed to air highlight regulatory pathways that are up- or down-regulated in response to hypoxia. The present study provides a valuable resource for understanding the molecular mechanisms underlying water-to-land transition of vertebrates

The Asian arowana (<i>Scleropages formosus</i>) genome provides new insights into the evolution of an early lineage of teleosts

The Asian arowana (Scleropages formosus), one of the world’s most expensive cultivated ornamental fishes, is an endangered species. It represents an ancient lineage of teleosts: the Osteoglossomorpha. Here, we provide a high-quality chromosome-level reference genome of a female golden-variety arowana using a combination of deep shotgun sequencing and high-resolution linkage mapping. In addition, we have also generated two draft genome assemblies for the red and green varieties. Phylogenomic analysis supports a sister group relationship between Osteoglossomorpha (bonytongues) and Elopomorpha (eels and relatives), with the two clades together forming a sister group of Clupeocephala which includes all the remaining teleosts. The arowana genome retains the full complement of eight Hox clusters unlike the African butterfly fish (Pantodon buchholzi), another bonytongue fish, which possess only five Hox clusters. Differential gene expression among three varieties provides insights into the genetic basis of colour variation. A potential heterogametic sex chromosome is identified in the female arowana karyotype, suggesting that the sex is determined by a ZW/ZZ sex chromosomal system. The high-quality reference genome of the golden arowana and the draft assemblies of the red and green varieties are valuable resources for understanding the biology, adaptation and behaviour of Asian arowanas

The Asian Arowana (Scleropages formosus) Genome Provides New Insights into the Evolution of an Early Lineage of Teleosts

The Asian arowana (Scleropages formosus), one of the world’s most expensive cultivated ornamental fishes, is an endangered species. It represents an ancient lineage of teleosts: the Osteoglossomorpha. Here, we provide a high-quality chromosome-level reference genome of a female golden-variety arowana using a combination of deep shotgun sequencing and high-resolution linkage mapping. In addition, we have also generated two draft genome assemblies for the red and green varieties. Phylogenomic analysis supports a sister group relationship between Osteoglossomorpha (bonytongues) and Elopomorpha (eels and relatives), with the two clades together forming a sister group of Clupeocephala which includes all the remaining teleosts. The arowana genome retains the full complement of eight Hox clusters unlike the African butterfly fish (Pantodon buchholzi), another bonytongue fish, which possess only five Hox clusters. Differential gene expression among three varieties provides insights into the genetic basis of colour variation. A potential heterogametic sex chromosome is identified in the female arowana karyotype, suggesting that the sex is determined by a ZW/ZZ sex chromosomal system. The high-quality reference genome of the golden arowana and the draft assemblies of the red and green varieties are valuable resources for understanding the biology, adaptation and behaviour of Asian arowanas

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Joint Optimization of Data Freshness and Fidelity for Selection Combining-Based Transmissions

Motivated by big data applications in the Internet of Things (IoT), abundant information arrives at the fusion center (FC) waiting to be processed. It is of great significance to ensure data freshness and fidelity simultaneously. We consider a wireless sensor network (WSN) where several sensor nodes observe one metric and then transmit the observations to the FC using a selection combining (SC) scheme. We adopt the age of information (AoI) and minimum mean square error (MMSE) metrics to measure the data freshness and fidelity, respectively. Explicit expressions of average AoI and MMSE are derived. After that, we jointly optimize the two metrics by adjusting the number of sensor nodes. A closed-form sub-optimal number of sensor nodes is proposed to achieve the best freshness and fidelity tradeoff with negligible errors. Numerical results show that using the proposed node number designs can effectively improve the freshness and fidelity of the transmitted data

Thruster fault identification method for autonomous underwater vehicle using peak region energy and least square grey relational grade

A novel thruster fault identification method for autonomous underwater vehicle is presented in this article. It uses the proposed peak region energy method to extract fault feature and uses the proposed least square grey relational grade method to estimate fault degree. The peak region energy method is developed from fusion feature modulus maximum method. It applies the fusion feature modulus maximum method to get fusion feature and then regards the maximum of peak region energy in the convolution operation results of fusion feature as fault feature. The least square grey relational grade method is developed from grey relational analysis algorithm. It determines the fault degree interval by the grey relational analysis algorithm and then estimates fault degree in the interval by least square algorithm. Pool experiments of the experimental prototype are conducted to verify the effectiveness of the proposed methods. The experimental results show that the fault feature extracted by the peak region energy method is monotonic to fault degree while the one extracted by the fusion feature modulus maximum method is not. The least square grey relational grade method can further get an estimation result between adjacent standard fault degrees while the estimation result of the grey relational analysis algorithm is just one of the standard fault degrees