Non-coding sequence retrieval system for comparative genomic analysis of gene regulatory elements

BACKGROUND: Completion of the human genome sequence along with other species allows for greater understanding of the biochemical mechanisms and processes that govern healthy as well as diseased states. The large size of the genome sequences has made them difficult to study using traditional methods. There are many studies focusing on the protein coding sequences, however, not much is known about the function of non-coding regions of the genome. It has been demonstrated that parts of the non-coding region play a critical role as gene regulatory elements. Enhancers that regulate transcription processes have been found in intergenic regions. Furthermore, it is observed that regulatory elements found in non-coding regions are highly conserved across different species. However, the analysis of these regulatory elements is not as straightforward as it may first seem. The development of a centralized resource that allows for the quick and easy retrieval of non-coding sequences from multiple species and is capable of handing multi-gene queries is critical for the analysis of non-coding sequences. Here we describe the development of a web-based non-coding sequence retrieval system. RESULTS: This paper presents a Non-Coding Sequences Retrieval System (NCSRS). The NCSRS is a web-based bioinformatics tool that performs fast and convenient retrieval of non-coding and coding sequences from multiple species related to a specific gene or set of genes. This tool has compiled resources from multiple sources into one easy to use and convenient web based interface. With no software installation necessary, the user needs only internet access to use this tool. CONCLUSION: The unique features of this tool will be very helpful for those studying gene regulatory elements that exist in non-coding regions. The web based application can be accessed on the internet at:

Equivariant Hypergraph Diffusion Neural Operators

Hypergraph neural networks (HNNs) using neural networks to encode hypergraphs provide a promising way to model higher-order relations in data and further solve relevant prediction tasks built upon such higher-order relations. However, higher-order relations in practice contain complex patterns and are often highly irregular. So, it is often challenging to design an HNN that suffices to express those relations while keeping computational efficiency. Inspired by hypergraph diffusion algorithms, this work proposes a new HNN architecture named ED-HNN, which provably represents any continuous equivariant hypergraph diffusion operators that can model a wide range of higher-order relations. ED-HNN can be implemented efficiently by combining star expansions of hypergraphs with standard message passing neural networks. ED-HNN further shows great superiority in processing heterophilic hypergraphs and constructing deep models. We evaluate ED-HNN for node classification on nine real-world hypergraph datasets. ED-HNN uniformly outperforms the best baselines over these nine datasets and achieves more than 2\%$\uparrow$ in prediction accuracy over four datasets therein.Comment: Code: https://github.com/Graph-COM/ED-HN

Depression and Sexual Risk Behaviors among Rural-to-urban Migrants in China: The Moderating Roles of Acculturation and Social Capital

Previous studies have documented that depression is positively associated with sexual risk behaviors (SRB) among rural-to-urban migrants. Existing literature has also suggested that acculturation and social capital might moderate this positive relationship. However, data regarding the moderating effects of acculturation and social capital have been inconsistent. The current study aims to examine the relationship between depression and SRB, as well as the moderating roles of acculturation and social capital in this relationship. A sample of 641 young rural-to-urban migrants was recruited through a venue-based sampling approach in Beijing, China. Results indicated that depression was positively associated with SRB. Both acculturation and social capital moderated this relationship, but they showed different moderating effects. Specifically, the level of acculturation was protective against SRB among migrants with a higher level of depression but not among migrants with a lower level of depression. Social capital played a protective role among migrants with a lower level of depression but became a risk factor for those with a higher level of depression. These findings suggested that targeted interventions aiming to reduce depression, improve acculturation stress management skills, and utilize social capital are needed to reduce SRB among rural-to-urban migrants

Evaluating IL-6 and IL-10 as rapid diagnostic tools for Gram-negative bacteria and as disease severity predictors in pediatric sepsis patients in the intensive care unit

BackgroundTo explore the diagnostic performance of interleukin (IL)-6 and IL-10 in discriminating Gram bacteria types and predicting disease severity in intensive care unit (ICU)-hospitalized pediatric sepsis patients.MethodWe retrospectively collected Th1/Th2 cytokine profiles of 146 microbiologically documented sepsis patients. Patients were categorized into Gram-positive (G+) or Gram-negative (G-) sepsis groups, and cytokine levels were compared. Subgroup analysis was designed to eliminate the influence of other inflammatory responses on cytokine levels.ResultsAfter propensity score matching, 78 patients were matched and categorized according to Gram bacteria types. Compared with G+ sepsis, IL-6 and IL-10 were significantly elevated in G- sepsis (p < 0.05). Spearman test proved the linear correlation between IL-6 and IL-10 (r = 0.654, p < 0.001), and their combination indicators (ratio and differences) were effective in identifying G- sepsis. In the subgroup analysis, such cytokine elevation was significant regardless of primary infection site. However, for patients with progressively deteriorating organ function [new or progressive multiple organ dysfunction syndrome (NPMODS)], differences in IL-6 and IL-10 levels were less significant between G+ and G- sepsis. In the receiver operating characteristic (ROC) curves of the G- sepsis group, the area under the curve (AUC) value for IL-6 and IL-10 was 0.679 (95% CI 0.561–0.798) and 0.637 (95% CI 0.512–0.762), respectively. The optimal cutoff value for diagnosing G- sepsis was 76.77 pg/ml and 18.90 pg/ml, respectively. While for the NPMODS group, the AUC for IL-6 and IL-10 was 0.834 (95% CI 0.766–0.902) and 0.781 (95% CI 0.701–0.860), respectively.ConclusionIL-6 and IL-10 are comparably effective in discriminating G+/G- sepsis in pediatric intensive care unit (PICU) patients. The deteriorated organ function observed in ICU patients reveals that complex inflammatory responses might have contributed to the cytokine pattern observed in severe sepsis patients, therefore confounding the discriminating efficacy of Th1/Th2 cytokines in predicting Gram bacteria types

Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks

Temporal networks serve as abstractions of many real-world dynamic systems. These networks typically evolve according to certain laws, such as the law of triadic closure, which is universal in social networks. Inductive representation learning of temporal networks should be able to capture such laws and further be applied to systems that follow the same laws but have not been unseen during the training stage. Previous works in this area depend on either network node identities or rich edge attributes and typically fail to extract these laws. Here, we propose Causal Anonymous Walks (CAWs) to inductively represent a temporal network. CAWs are extracted by temporal random walks and work as automatic retrieval of temporal network motifs to represent network dynamics while avoiding the time-consuming selection and counting of those motifs. CAWs adopt a novel anonymization strategy that replaces node identities with the hitting counts of the nodes based on a set of sampled walks to keep the method inductive, and simultaneously establish the correlation between motifs. We further propose a neural-network model CAW-N to encode CAWs, and pair it with a CAW sampling strategy with constant memory and time cost to support online training and inference. CAW-N is evaluated to predict links over 6 real temporal networks and uniformly outperforms previous SOTA methods by averaged 10% AUC gain in the inductive setting. CAW-N also outperforms previous methods in 4 out of the 6 networks in the transductive setting.Comment: Published in ICLR 2021. A bug in previous versions is fixe

Direct van der Waals Epitaxy of Crack-Free AlN Thin Film on Epitaxial WS2

Van der Waals epitaxy (vdWE) has drawn continuous attention, as it is unlimited by lattice-mismatch between epitaxial layers and substrates. Previous reports on the vdWE of III-nitride thin film were mainly based on two-dimensional (2D) materials by plasma pretreatment or pre-doping of other hexagonal materials. However, it is still a huge challenge for single-crystalline thin film on 2D materials without any other extra treatment or interlayer. Here, we grew high-quality single-crystalline AlN thin film on sapphire substrate with an intrinsic WS2 overlayer (WS2/sapphire) by metal-organic chemical vapor deposition, which had surface roughness and defect density similar to that grown on conventional sapphire substrates. Moreover, an AlGaN-based deep ultraviolet light emitting diode structure on WS2/sapphire was demonstrated. The electroluminescence (EL) performance exhibited strong emissions with a single peak at 283 nm. The wavelength of the single peak only showed a faint peak-position shift with increasing current to 80 mA, which further indicated the high quality and low stress of the AlN thin film. This work provides a promising solution for further deep-ultraviolet (DUV) light emitting electrodes (LEDs) development on 2D materials, as well as other unconventional substrates

Small molecules targeting Pin1 as potent anticancer drugs

Background: Pin1 is a member of the evolutionarily conserved peptidyl-prolyl isomerase (PPIase) family of proteins. Following phosphorylation, Pin1-catalyzed prolyl-isomerization induces conformational changes, which serve to regulate the function of many phosphorylated proteins that play important roles during oncogenesis. Thus, the inhibition of Pin1 provides a unique means of disrupting oncogenic pathways and therefore represents an appealing target for novel anticancer therapies.Methods: As Pin1 is conserved between yeast and humans, we employed budding yeast to establish a high-throughput screening method for the primary screening of Pin1 inhibitors. This effort culminated in the identification of the compounds HWH8-33 and HWH8-36. Multifaceted approaches were taken to determine the inhibition profiles of these compounds against Pin1 activity in vitro and in vivo, including an isomerization assay, surface plasmon resonance (SPR) technology, virtual docking, MTT proliferation assay, western blotting, cell cycle analysis, apoptosis analysis, immunofluorescence analysis, wound healing, migration assay, and nude mouse assay.Results:In vitro, HWH8-33 and HWH8-36 could bind to purified Pin1 and inhibited its enzyme activity; showed inhibitory effects on cancer cell proliferation; led to G2/M phase arrest, dysregulated downstream protein expression, and apoptosis; and suppressed cancer cell migration. In vivo, HWH8-33 suppressed tumor growth in the xenograft mice after oral administration for 4 weeks, with no noticeable toxicity. Together, these results show the anticancer activity of HWH8-33 and HWH8-36 against Pin1 for the first time.Conclusion: In summary, we identified two hit compounds HWH8-33 and HWH8-36, which after further structure optimization have the potential to be developed as antitumor drugs