Space-efficient computation of k-mer dictionaries for large values of k.

Computing k-mer frequencies in a collection of reads is a common procedure in many genomic applications. Several state-of-the-art k-mer counters rely on hash tables to carry out this task but they are often optimised for small k as a hash table keeping keys explicitly (i.e., k-mer sequences) takes O ( N k w ) computer words, N being the number of distinct k-mers and w the computer word size, which is impractical for long values of k. This space usage is an important limitation as analysis of long and accurate HiFi sequencing reads can require larger values of k. We propose Kaarme, a space-efficient hash table for k-mers using O ( N + u k w ) words of space, where u is the number of reads. Our framework exploits the fact that consecutive k-mers overlap by k - 1 symbols. Thus, we only store the last symbol of a k-mer and a pointer within the hash table to a previous one, which we can use to recover the remaining k - 1 symbols. We adapt Kaarme to compute canonical k-mers as well. This variant also uses pointers within the hash table to save space but requires more work to decode the k-mers. Specifically, it takes O ( σ k ) time in the worst case, σ being the DNA alphabet, but our experiments show this is hardly ever the case. The canonical variant does not improve our theoretical results but greatly reduces space usage in practice while keeping a competitive performance to get the k-mers and their frequencies. We compare canonical Kaarme to a regular hash table storing canonical k-mers explicitly as keys and show that our method uses up to five times less space while being less than 1.5 times slower. We also show that canonical Kaarme uses significantly less memory than state-of-the-art k-mer counters when they do not resort to disk to keep intermediate results.

Atmospheric Boundary Layer Wind Profile Estimation Using Neural Networks, Mesoscale Models, and LiDAR Measurements.

This paper introduces a novel methodology that estimates the wind profile within the ABL by using a neural network along with predictions from a mesoscale model in conjunction with a single near-surface measurement. A major advantage of this solution compared to other solutions available in the literature is that it requires only near-surface measurements for prediction once the neural network has been trained. An additional advantage is the fact that it can be potentially used to explore the time evolution of the wind profile. Data collected by a LiDAR sensor located at the University of León (Spain) is used in the present research. The information obtained from the wind profile is valuable for multiple applications, such as preliminary calculations of the wind asset or CFD modeling.

International Society of Blood Transfusion survey of experiences of blood banks and transfusion services during the COVID-19 pandemic.

BACKGROUND AND OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has impacted blood systems worldwide. Challenges included maintaining blood supplies and initiating the collection and use of COVID-19 convalescent plasma (CCP). Sharing information on the challenges can help improve blood collection and utilization. MATERIALS AND METHODS: A survey questionnaire was distributed to International Society of Blood Transfusion members in 95 countries. We recorded respondents' demographic information, impacts on the blood supply, CCP collection and use, transfusion demands and operational challenges. RESULTS: Eighty-two responses from 42 countries, including 24 low- and middle-income countries, were analysed. Participants worked in national (26.8%) and regional (26.8%) blood establishments and hospital-based (42.7%) institutions. CCP collection and transfusion were reported by 63% and 36.6% of respondents, respectively. Decreases in blood donations occurred in 70.6% of collecting facilities. Despite safety measures and recruitment strategies, donor fear and refusal of institutions to host blood drives were major contributing factors. Almost half of respondents working at transfusion medicine services were from large hospitals with over 10,000 red cell transfusions per year, and 76.8% of those hospitals experienced blood shortages. Practices varied in accepting donors for blood or CCP donations after a history of COVID-19 infection, CCP transfusion, or vaccination. Operational challenges included loss of staff, increased workloads and delays in reagent supplies. Almost half of the institutions modified their disaster plans during the pandemic. CONCLUSION: The challenges faced by blood systems during the COVID-19 pandemic highlight the need for guidance, harmonization, and strengthening of the preparedness and the capacity of blood systems against future infectious threats.

Identification of Novel Conotoxin Precursors from the Cone Snail Conus spurius by High-Throughput RNA Sequencing.

Marine gastropods of the genus Conus, comprising more than 800 species, have the characteristic of injecting worms and other prey with venom. These conopeptide toxins, highly diverse in structure and action, are highly potent and specific for their molecular targets (ion channels, receptors, and transporters of the prey's nervous system), and thus are important research tools and source for drug discovery. Next-generation sequencing technologies are speeding up the discovery of novel conopeptides in many of these species, but only limited information is available for Conus spurius, which inhabits sandy mud. To search for new precursor conopeptides, we analyzed the transcriptome of the venous ducts of C. spurius and identified 55 putative conotoxins. Seven were selected for further study and confirmed by Sanger sequencing to belong to the M-superfamily (Sr3.M01 and Sr3.M02), A-superfamily (Sr1.A01 and Sr1.A02), O-superfamily (Sr15.O01), and Con-ikot-ikot (Sr21.CII01 and Sr22.CII02). Six of these have never been reported. To our knowledge, this report is the first to use high-throughput RNA sequencing for the study of the diversity of C. spurius conotoxins.

Detection of selection signatures in the genome of a farmed population of anadromous rainbow trout (Oncorhynchus mykiss).

Domestication processes and artificial selection are likely to leave signatures that can be detected at a molecular level in farmed rainbow trout (Oncorhynchus mykiss). These signatures of selection are genomic regions that contain functional genetic variants conferring a higher fitness to their bearers. We genotyped 749 rainbow trout from a commercial population using a rainbow trout Axiom 57 K SNP array panel and identified putative genomic regions under selection using the pcadapt, Composite Likelihood Ratio (CLR) and Integrated Haplotype Score (iHS) methods. After applying quality-control pipelines and statistical analyses, we detected 12, 96 and 16 SNPs putatively under selection, associated with 96, 781 and 115 candidate genes, respectively. Several of these candidate genes were associated with growth, early development, reproduction, behavior and immune system traits. In addition, some of the SNPs were found in interesting regions located in autosomal inversions on Omy05 and Omy20. These findings could represent a genome-wide map of selection signatures in farmed rainbow trout and could be important in explaining domestication and selection for genetic traits of commercial interest.

Atmospheric Boundary Layer Wind Profile Estimation Using Neural Networks Applied to Lidar Measurements.

This paper introduces a new methodology for estimating the wind profile within the ABL (Atmospheric Boundary Layer) using a neural network and a single-point near-ground measurement. An important advantage of this solution when compared with others available in the literature is that it only requires near surface measurements for the prognosis once the neural network is trained. Another advantage is that it can be used to study the wind profile temporal evolution. This work uses data collected by a lidar sensor located at the Universidad de León (Spain). The neural network best configuration was determined using sensibility analyses. The result is a multilayer perceptron with three layers for each altitude: the input layer has six nodes for the last three measurements, the second has 128 nodes and the third consists of two nodes that provide u and v. The proposed method has better performance than traditional methods. The obtained wind profile information obtained is useful for multiple applications, such as preliminary calculations of the wind resource or CFD models.

Sistema hospitalario en situación de crisis: implementación de sistema de comando de incidentes para enfrentar pandemia SARS-CoV-2 en Clínica Las Condes, Chile / Implementation of incident command system to deal with SARS-CoV-2 pandemic in Clínica Las Condes, Chile

La pandemia en Chile generó un desafío de modernización y gestión de los Cuidados Intensivos, haciendo necesario que las unidades de pacientes críticos realizaran un aumento de su capacidad hospitalaria, lo que requiere preparar una infraestructura, un equipamiento mínimo, protocolos y un equipo humano preparado y alineado, para garantizar la seguridad y calidad de atención a los pacientes. Una forma de lograrlo es la incorporación de la estrategia militar de Sistema de Comando de Incidentes, utilizado para enfrentar distintos tipos de desastres, con una estructura modular de comando y sus seccionales de trabajo, con diferentes equipos y líderes para hacer frentes a los variados desafíos. El objetivo de este artículo es describir la instauración del sistema de comando de incidentes en un hospital privado, detallando su conformación y los resultados logrados.

The pandemic in Chile has been a real challenge in terms of modernization and management of intensive care. Critical care units have been forced to increase their hospital capacity in terms of infrastructure, equipment, protocols and human team, while guaranteeing safety and high-quality patient care.One approach to achieve this objective is to develop the army strategy called incident command system that has been used to face different types of disaster. A modular command structure is developed based on the creation of teams each lead by an expert in different areas in order to cope with a variety of upcoming challenges.The objective of this article is to describe the setting up of a successful incident command system in a private hospital, detailing its formation and results obtained.

Paraneoplastic Cerebellar Degeneration Secondary to BRAF Mutant Melanoma Metastasis from an Occult Primary Cancer.

Melanoma metastasis from an unknown primary cancer has an incidence of 3.2% among melanoma patients. Furthermore, paraneoplastic neurological syndromes (PNS) are rare, occurring in 1-3% of patients with malignancies. Paraneoplastic cerebellar degeneration (PCD) is one of the classic PNS and is characterized by acute or subacute onset of ataxia and/or presence of onconeural antibodies. A 61-year-old male with ataxia, vertigo, and headache later developed dysarthria, multidirectional nystagmus, hyperactive delirium, auditory hallucinations, psychomotor agitation, and myoclonus. Toxicological, metabolic, infectious, and autoimmune etiologies were assessed and reported negative. An osteolytic lesion was observed in the right iliac crest via computed tomography (CT). A positron emission tomography-CT reported increased fluorodeoxyglucose uptake of a right iliac and right inguinal ganglion. After biopsy of the right inguinal ganglion, a BRAF mutation-positive melanoma metastasis from an occult primary cancer was diagnosed. Dermatologic, ophthalmologic, and endoscopic gastrointestinal assessment did not reveal a primary malignant melanoma. The patient's movement disorders and neuropsychiatric symptoms improved with quetiapine, prednisone, azathioprine, and cyclophosphamide. Oncological management was conducted with MAPK pathway inhibitors (i.e., dabrafenib and trametinib). Movement disorders associated with neuropsychiatric symptoms are complex to diagnose. PNS are rare and often associated with antibodies against neural antigens expressed by the tumor. The case presented above describes a patient with a BRAF-positive malignant melanoma metastasis from an occult primary associated with PCD - to the best of our knowledge, the first reported in the literature.

Path Planner for Autonomous Exploration of Underground Mines by Aerial Vehicles.

This paper presents a path planner solution that makes it possible to autonomously explore underground mines with aerial robots (typically multicopters). In these environments the operations may be limited by many factors like the lack of external navigation signals, the narrow passages and the absence of radio communications. The designed path planner is defined as a simple and highly computationally efficient algorithm that, only relying on a laser imaging detection and ranging (LIDAR) sensor with Simultaneous localization and mapping (SLAM) capability, permits the exploration of a set of single-level mining tunnels. It performs dynamic planning based on exploration vectors, a novel variant of the open sector method with reinforced filtering. The algorithm incorporates global awareness and obstacle avoidance modules. The first one prevents the possibility of getting trapped in a loop, whereas the second one facilitates the navigation along narrow tunnels. The performance of the proposed solution has been tested in different study cases with a Hardware-in-the-loop (HIL) simulator developed for this purpose. In all situations the path planner logic performed as expected and the used routing was optimal. Furthermore, the path efficiency, measured in terms of traveled distance and used time, was high when compared with an ideal reference case. The result is a very fast, real-time, and static memory capable algorithm, which implemented on the proposed architecture presents a feasible solution for the autonomous exploration of underground mines.

Whole genome re-sequencing reveals recent signatures of selection in three strains of farmed Nile tilapia (Oreochromis niloticus).

Nile tilapia belongs to the second most cultivated group of fish in the world, mainly because of its favorable characteristics for production. Genetic improvement programs and domestication process of Nile tilapia may have modified the genome through selective pressure, leaving signals that can be detected at the molecular level. In this work, signatures of selection were identified using genome-wide SNP data, by two haplotype-based (iHS and Rsb) and one FST based method. Whole-genome re-sequencing of 326 individuals from three strains (A, B and C) of farmed tilapia maintained in Brazil and Costa Rica was carried out using Illumina HiSeq 2500 technology. After applying conventional SNP-calling and quality-control filters, ~ 1.3 M high-quality SNPs were inferred and used as input for the iHS, Rsb and FST based methods. We detected several candidate genes putatively subjected to selection in each strain. A considerable number of these genes are associated with growth (e.g. NCAPG, KLF3, TBC1D1, TTN), early development (e.g. FGFR3, PFKFB3), and immunity traits (e.g. NLRC3, PIGR, MAP1S). These candidate genes represent putative genomic landmarks that could be associated to traits of biological and commercial interest in farmed Nile tilapia.

Fine Mapping Using Whole-Genome Sequencing Confirms Anti-Müllerian Hormone as a Major Gene for Sex Determination in Farmed Nile Tilapia (Oreochromis niloticus L.).

Nile tilapia (Oreochromis niloticus) is one of the most cultivated and economically important species in world aquaculture. Intensive production promotes the use of monosex animals, due to an important dimorphism that favors male growth. Currently, the main mechanism to obtain all-male populations is the use of hormones in feeding during larval and fry phases. Identifying genomic regions associated with sex determination in Nile tilapia is a research topic of great interest. The objective of this study was to identify genomic variants associated with sex determination in three commercial populations of Nile tilapia. Whole-genome sequencing of 326 individuals was performed, and a total of 2.4 million high-quality bi-allelic single nucleotide polymorphisms (SNPs) were identified after quality control. A genome-wide association study (GWAS) was conducted to identify markers associated with the binary sex trait (males = 1; females = 0). A mixed logistic regression GWAS model was fitted and a genome-wide significant signal comprising 36 SNPs, spanning a genomic region of 536 kb in chromosome 23 was identified. Ten out of these 36 genetic variants intercept the anti-Müllerian (Amh) hormone gene. Other significant SNPs were located in the neighboring Amh gene region. This gene has been strongly associated with sex determination in several vertebrate species, playing an essential role in the differentiation of male and female reproductive tissue in early stages of development. This finding provides useful information to better understand the genetic mechanisms underlying sex determination in Nile tilapia.