A big data approach for sequences indexing on the cloud via burrows wheeler transform

Indexing sequence data is important in the context of Precision Medicine, where large amounts of "omics"data have to be daily collected and analyzed in order to categorize patients and identify the most effective therapies. Here we propose an algorithm for the computation of Burrows Wheeler transform relying on Big Data technologies, i.e., Apache Spark and Hadoop. Our approach is the first that distributes the index computation and not only the input dataset, allowing to fully benefit of the available cloud resources. Copyright © 2020 for this paper by its authors

Pneumatic tools for vitreoretinal surgery

One of the difficulties of microsurgery is learning how to control physiological tremors. The pneumatic tool eliminates the physiological tremor, but no tactile feedback is provided. The manual tremor when closing the forceps is completely eliminated and the exact target can be more easily grabbed. Forceps closure pressure can rise up to 50 psi, whereas the scissors can be used in two modes: multicut and proportional. When performing bimanual surgery the pedal range is divided into two steps: in the first step, the forceps are controlled, and in the second step, the forceps remain closed. At the same time the scissors start to work in the preselected mode. No adverse events occurred and no iatrogenic retinal breaks were produced. Precision and control sensation were a grateful surprise

A perceptual sound space for auditory displays based on sung-vowel synthesis

When designing displays for the human senses, perceptual spaces are of great importance to give intuitive access to physical attributes. Similar to how perceptual spaces based on hue, saturation, and lightness were constructed for visual color, research has explored perceptual spaces for sounds of a given timbral family based on timbre, brightness, and pitch. To promote an embodied approach to the design of auditory displays, we introduce the Vowel-Type-Pitch (VTP) space, a cylindrical sound space based on human sung vowels, whose timbres can be synthesized by the composition of acoustic formants and can be categorically labeled. Vowels are arranged along the circular dimension, while voice type and pitch of the vowel correspond to the remaining two axes of the cylindrical VTP space. The decoupling and perceptual effectiveness of the three dimensions of the VTP space are tested through a vowel labeling experiment, whose results are visualized as maps on circular slices of the VTP cylinder. We discuss implications for the design of auditory and multi-sensory displays that account for human perceptual capabilities

Investigation on MMACHC-R161Q pathological mutant from cblC disease

The cblC disease is a rare inborn disorder of the vitamin B12 (cobalamin, Cbl) metabolism characterized by combined methylmalonic aciduria and homocystinuria. The clinical consequences are devastating and, even when early treated with current therapies, the affected children manifest symptoms involving vision, growth, and learning. The molecular genetic cause of the disease was found in the mutations of the gene coding for MMACHC, a 282 amino acid protein that transports and processes the various forms of Cbl. Here we present the biophysical characterization of wild type MMACHC and a variant, p.R161Q, resulting from the most common missense pathological mutation found in cblC patients. By using a biophysical approach we investigated the stability of the two proteins and their ability to bind and transform the vitamin B12, and to assemble in a dimeric structure. Moreover, interesting indications about the behaviour of the proteins resulted from the Molecular Dynamics (MD) simulations. Overall, our results reveal how a biophysical approach based on the complementarity of computational and experimental methods can offer new insights in the study of the specific effects of the pathological cblC mutation and help prospecting new routes for the cblC treatment

Candida albicans AGE3, the Ortholog of the S. cerevisiae ARF-GAP-Encoding Gene GCS1, Is Required for Hyphal Growth and Drug Resistance

BACKGROUND: Hyphal growth and multidrug resistance of C. albicans are important features for virulence and antifungal therapy of this pathogenic fungus. METHODOLOGY/PRINCIPAL FINDINGS: Here we show by phenotypic complementation analysis that the C. albicans gene AGE3 is the functional ortholog of the yeast ARF-GAP-encoding gene GCS1. The finding that the gene is required for efficient endocytosis points to an important functional role of Age3p in endosomal compartments. Most C. albicans age3Delta mutant cells which grew as cell clusters under yeast growth conditions showed defects in filamentation under different hyphal growth conditions and were almost completely disabled for invasive filamentous growth. Under hyphal growth conditions only a fraction of age3Delta cells shows a wild-type-like polarization pattern of the actin cytoskeleton and lipid rafts. Moreover, age3Delta cells were highly susceptible to several unrelated toxic compounds including antifungal azole drugs. Irrespective of the AGE3 genotype, C-terminal fusions of GFP to the drug efflux pumps Cdr1p and Mdr1p were predominantly localized in the plasma membrane. Moreover, the plasma membranes of wild-type and age3Delta mutant cells contained similar amounts of Cdr1p, Cdr2p and Mdr1p. CONCLUSIONS/SIGNIFICANCE: The results indicate that the defect in sustaining filament elongation is probably caused by the failure of age3Delta cells to polarize the actin cytoskeleton and possibly of inefficient endocytosis. The high susceptibility of age3Delta cells to azoles is not caused by inefficient transport of efflux pumps to the cell membrane. A possible role of a vacuolar defect of age3Delta cells in drug susceptibility is proposed and discussed. In conclusion, our study shows that the ARF-GAP Age3p is required for hyphal growth which is an important virulence factor of C. albicans and essential for detoxification of azole drugs which are routinely used for antifungal therapy. Thus, it represents a promising antifungal drug target

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p < 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p < 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p < 0.0001) or urgent (20.4% vs. 38.5%; p < 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p < 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection