Recent advances of hemorrhage management in severe trauma

Trauma is one of the most common causes of mortality worldwide with a substantial percentage of deaths resulting secondary to haemorrhages, which are preventable and treatable when adequately managed. This paper offers a review of the current literature on how to successfully resuscitate patients with major haemorrhage

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Towards a multi-feature enabled approach for optimized expert seeking

With the enormous growth of data, retrieving information from the Web became more desirable and even more challenging because of the Big Data issues (e.g. noise, corruption, bad quality...etc.). Expert seeking, defined as returning a ranked list of expert researchers given a topic, has been a real concern in the last 15 years. This kind of task comes in handy when building scientific committees, requiring to identify the scholars’ experience to assign them the most suitable roles in addition to other factors as well. Due to the fact the Web is drowning with plenty of data, this opens up the opportunity to collect different kinds of expertise evidence. In this paper, we propose an expert seeking approach with specifying the most desirable features (i.e. criteria on which researcher’s evaluation is done) along with their estimation techniques. We utilized some machine learning techniques in our system and we aim at verifying the effectiveness of incorporating influential features that go beyond publications

CARP ::correlation-based approach for researcher profiling

The accelerating progress in science with the active role of the communication media – mainly the web – make person in front of a difficult task, in finding appropriate information during a brief time. In a narrower context, many researches were created in the expertise retrieval domain, as an interesting and complicated task for the scientific community, in face of this huge amount of data scattered across the web. Benefiting from the semantic web technologies and the efforts of data structuring, in this paper we propose a novel approach of correlation based profile building, by exploiting heterogynous web sources. The aim is to generate comprehensive and validated profiles about researchers and experts in the computer science domain

Social networks serving web feeds

A web feed is a new kind of web services that was created in the past two decades to keep remote users updated with the latest news without having to crawl individual web sites. Currently, the existing web feed services get their information from one source (the website hosting the feed) in a standardized format that is normally structured as follows: title, description, link, image and date. In this paper, we propose a new method called NERVES (social Networks sERVing wEb feedS) that connects web feeds to a Social Networking Sites (SNS), and aims at (1) keeping users aware of the wider context taking into account both the source of the feed and the SNS. (2) Our approach enriches existing feeds with extra information harvested from the social web. We validated the efficiency and accuracy of our approach on public data and report on empirical results yielding an accuracy of 94%

Flood Analysis Using HEC-RAS and HEC-HMS: A Case Study of Khazir River (Middle East—Northern Iraq)

Floods frequently threaten villages near the Khazir River’s floodplains, causing crop losses and threatening residential areas. We used flood-related hydrological software, including WMS and HEC-HMS, to study this issue and determine how to reduce the recurrence of flooding. The software can be used to calculate a hydrograph of torrential flows in a river drainage basin and estimate the volume of torrential water and its flow rates on the Earth’s surface. The depth of rain has been evaluated and calculated in the SCS Unit Hydrograph for different return periods of 2, 5, 10, 20, 50, and 100 years. According to our study’s findings, the volume of the river’s drainage basin floods ranged between 29,680 and 2,229,200 m3, and the maximum flow value ranged between 10.4 and 66.4 m3/sec during various reference periods. To analyze and model the flood risks of the Khazir River, the HEC-RAS model was combined with the HEC-GeoRAS extension in ArcGIS. The floods were the focus of two study periods, 2013 and 2018, and were based on the digital elevation model and river discharge during the floods. According to the classification map of the flood depths, the areas of flood risk varied from low to very low (80.31%), medium (16.03%), and high to very high (3.8%). The analysis of the results revealed that the villages closest to the river’s mouth were more affected by the floods than other villages further downstream. HEC-HMS and HEC-RAS have been shown to have a strong correlation in evaluating flood risks and reliably forecasting future floods in the study area

Leveraging co-authorship and biographical information for author ambiguity resolution in DBLP

Many authors can share the same name and this constitutes a serious problem that affects the relevancy of retrieval results and constitutes our motivation of finding such approach to cover this issue at the author names entity level. Solving such a problem may return with positive gain at the level of document retrieval, web search and the quality of data. This entity resolution task can be tackled as an unsupervised problem, where there are set of features that can be employed for the resolution job, or as supervised problem to compute the similarities among two citations and then classify if they are the same or not. Recent approaches usually utilize features such as: co-author, venue, topic similarity, affiliations and title of publications to deal with author ambiguity. In this paper, three attributes are used to treat this problem sequentially. The co-authorship firstly which is a well-known attribute, and then the topic and affiliation extracted from biographies, which can be found inside the publication, and this is our novelty frame in this paper

Glucocorticoid Receptor: A Multifaceted Actor in Breast Cancer

International audienceBreast cancer (BC) is one of the most common cancers in women worldwide. Even though the role of estrogen receptor alpha (ERα) is extensively documented in the development of breast tumors, other members of the nuclear receptor family have emerged as important players. Synthetic glucocorticoids (GCs) such as dexamethasone (dex) are commonly used in BC for their antiemetic, anti-inflammatory, as well as energy and appetite stimulating properties, and to manage the side effects of chemotherapy. However, dex triggers different effects depending on the BC subtype. The glucocorticoid receptor (GR) is also an important marker in BC, as high GR expression is correlated with a poor and good prognosis in ERα-negative and ERα-positive BCs, respectively. Indeed, though it drives the expression of pro-tumorigenic genes in ERα-negative BCs and is involved in resistance to chemotherapy and metastasis formation, dex inhibits estrogen-mediated cell proliferation in ERα-positive BCs. Recently, a new natural ligand for GR called OCDO was identified. OCDO is a cholesterol metabolite with oncogenic properties, triggering mammary cell proliferation in vitro and in vivo. In this review, we summarize recent data on GR signaling and its involvement in tumoral breast tissue, via its different ligands