Named-Data Networking (NDN) is a novel network that secures network communication by fetching semantically named and secured data. All data packets in NDN are signed by producers and verified by data consumers. Therefore, it is vital to have producers' certificates available all the time. In this paper, we describe the design of CLedger, a secure distributed certificate ledger, to ensure certificate availability in NDN. CLedger logs certificate records in an immutable Directed Acyclic Graph (DAG) structure and replicates the DAG among a set of distributed loggers. We implemented CLedger using NDN's pub/sub API, and evaluated our design through an emulated deployment setting. Our initial evaluation results show that CLedger is effective, efficient, and resilient to failures.

Objective

Compared with HIV monoinfection, HIV dual infection has been associated with decreased CD4 T-cell counts and increased viral loads. The same markers are also associated with the development of HIV-associated neurocognitive disorder (HAND), which continues to be a prevalent problem in the era of combination antiretroviral therapy (ART). We sought to determine the relationship between dual infection and HAND.

Methods

Participants on ART (N = 38) underwent deep sequencing of four PCR-amplified HIV coding regions derived from peripheral blood mononuclear cell DNA samples. Phylogenetic analyses were performed to evaluate whether two distinct viral lineages, that is, dual infection, were present in the same individual. All study participants underwent neurocognitive, substance use, and neuromedical assessments at each study visit.

Results

Of 38 participants, nine (23.7%) had evidence of dual infection. Using clinical ratings, global neurocognitive impairment was identified in 21 (55%) participants, and multivariate analysis demonstrated a significant association between dual infection and impairment; odds ratio (95% confidence interval) = 18.3 (1.9, 414.2), P = 0.028. Neurocognitive impairment was also associated with lower current (P = 0.028) and nadir (P = 0.043) CD4 T-cell counts.

Conclusions

Deep sequencing of HIV DNA populations in blood mononuclear cell identified dual infection in nearly a quarter of HIV-infected adults receiving ART, and dual infection was associated with HAND. Dual infection may contribute to the development of HAND, perhaps because of increased viral diversity. Further investigation is needed to determine how dual infection results in worse neurocognitive performance.

AIMS: Pulmonary hypertension (PH) is a pulmonary vascular disease characterized by a high mortality rate. Pulmonary arterial endothelium cells (PAECs) serve as a primary sensor of various environmental cues, such as shear stress and hypoxia, but PAEC dysfunction may trigger vascular remodelling during the onset of PH. This study aimed to illustrate the role of Sirtuin 7 (SIRT7) in endothelial dysfunction during PH and explore the potential therapeutic strategy for PH. METHODS AND RESULTS: SIRT7 levels were measured in human and murine experimental PH samples. Bioinformatic analysis, immunoprecipitation, and deacetylation assay were used to identify the association between SIRT7 and Krüpple-like factor 4 (KLF4), a key transcription factor essential for endothelial cell (EC) homeostasis. Sugen5416 + hypoxia (SuHx)-induced PH mouse models and cell cultures were used for the study of the therapeutic effect of SIRT7 for PH. SIRT7 level was significantly reduced in lung tissues and PAECs from PH patients and the SuHx-induced PH mouse model as compared with healthy controls. Pulmonary endothelium-specific depletion of Sirt7 increased right ventricular systolic pressure and exacerbated right ventricular hypertrophy in the SuHx-induced PH model. At the molecular level, we identified KLF4 as a downstream target of SIRT7, which deacetylated KLF4 at K228 and inhibited the ubiquitination-proteasome degradation. Thus, the SIRT7/KLF4 axis maintained PAEC homeostasis by regulating proliferation, migration, and tube formation. PAEC dysfunction was reversed by adeno-associated virus type 1 vector-mediated endothelial overexpression of Sirt7 or supplementation with nicotinamide adenine dinucleotide (NAD)+ intermediate nicotinamide riboside which activated Sirt7; both approaches successfully reversed PH phenotypes. CONCLUSION: The SIRT7/KLF4 axis ensures PAEC homeostasis, and pulmonary endothelium-specific SIRT7 targeting might constitute a PH therapeutic strategy.

The hypoxic conditions at high altitudes present a challenge for survival, causing pressure for adaptation. Interestingly, many high-altitude denizens (particularly in the Andes) are maladapted, with a condition known as chronic mountain sickness (CMS) or Monge disease. To decode the genetic basis of this disease, we sequenced and compared the whole genomes of 20 Andean subjects (10 with CMS and 10 without). We discovered 11 regions genome-wide with significant differences in haplotype frequencies consistent with selective sweeps. In these regions, two genes (an erythropoiesis regulator, SENP1, and an oncogene, ANP32D) had a higher transcriptional response to hypoxia in individuals with CMS relative to those without. We further found that downregulating the orthologs of these genes in flies dramatically enhanced survival rates under hypoxia, demonstrating that suppression of SENP1 and ANP32D plays an essential role in hypoxia tolerance. Our study provides an unbiased framework to identify and validate the genetic basis of adaptation to high altitudes and identifies potentially targetable mechanisms for CMS treatment.

Background

Although it has long been proposed that genetic factors contribute to adaptation to high altitude, such factors remain largely unverified. Recent advances in high-throughput sequencing have made it feasible to analyze genome-wide patterns of genetic variation in human populations. Since traditionally such studies surveyed only a small fraction of the genome, interpretation of the results was limited.

Results

We report here the results of the first whole genome resequencing-based analysis identifying genes that likely modulate high altitude adaptation in native Ethiopians residing at 3,500 m above sea level on Bale Plateau or Chennek field in Ethiopia. Using cross-population tests of selection, we identify regions with a significant loss of diversity, indicative of a selective sweep. We focus on a 208 kbp gene-rich region on chromosome 19, which is significant in both of the Ethiopian subpopulations sampled. This region contains eight protein-coding genes and spans 135 SNPs. To elucidate its potential role in hypoxia tolerance, we experimentally tested whether individual genes from the region affect hypoxia tolerance in Drosophila. Three genes significantly impact survival rates in low oxygen: cic, an ortholog of human CIC, Hsl, an ortholog of human LIPE, and Paf-AHα, an ortholog of human PAFAH1B3.

Conclusions

Our study reveals evolutionarily conserved genes that modulate hypoxia tolerance. In addition, we show that many of our results would likely be unattainable using data from exome sequencing or microarray studies. This highlights the importance of whole genome sequencing for investigating adaptation by natural selection.

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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.