83 research outputs found
Hazardous explosive eruptions of a recharging multi-cyclic island arc caldera
Caldera-forming eruptions of silicic volcanic systems are among the most
devastating events on Earth. By contrast, post-collapse volcanic activity
initiating new caldera cycles is generally considered less hazardous.
Formed after Santorini’s latest caldera-forming eruption of ~1600 bce, the
Kameni Volcano in the southern Aegean Sea enables the eruptive evolution
of a recharging multi-cyclic caldera to be reconstructed. Santorini’s
eruptive record has been documented by onshore products and historical
descriptions of mainly effusive eruptions dating back to 197 bce. Here we
combine high-resolution seismic reflection data with cored lithologies
from International Ocean Discovery Program Expedition 398 at four sites to
determine the submarine architecture and volcanic history of intra-caldera
deposits from Kameni. Our shore-crossing analysis reveals the deposits
of a submarine explosive eruption that produced up to 3.1 km3
of pumice
and ash, which we relate to a historical eruption in 726 ce. The estimated
volcanic explosivity index of magnitude 5 exceeds previously considered
worst-case eruptive scenarios for Santorini. Our finding that the Santorini
caldera is capable of producing large explosive eruptions at an early stage
in the caldera cycle implies an elevated hazard potential for the eastern
Mediterranean region, and potentially for other recharging silicic calderas
Lineage Abundance Estimation for SARS-CoV-2 in Wastewater Using Transcriptome Quantification Techniques
Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable
Human Occupancy as a Source of Indoor Airborne Bacteria
Exposure to specific airborne bacteria indoors is linked to infectious and noninfectious adverse health outcomes. However, the sources and origins of bacteria suspended in indoor air are not well understood. This study presents evidence for elevated concentrations of indoor airborne bacteria due to human occupancy, and investigates the sources of these bacteria. Samples were collected in a university classroom while occupied and when vacant. The total particle mass concentration, bacterial genome concentration, and bacterial phylogenetic populations were characterized in indoor, outdoor, and ventilation duct supply air, as well as in the dust of ventilation system filters and in floor dust. Occupancy increased the total aerosol mass and bacterial genome concentration in indoor air PM10 and PM2.5 size fractions, with an increase of nearly two orders of magnitude in airborne bacterial genome concentration in PM10. On a per mass basis, floor dust was enriched in bacterial genomes compared to airborne particles. Quantitative comparisons between bacterial populations in indoor air and potential sources suggest that resuspended floor dust is an important contributor to bacterial aerosol populations during occupancy. Experiments that controlled for resuspension from the floor implies that direct human shedding may also significantly impact the concentration of indoor airborne particles. The high content of bacteria specific to the skin, nostrils, and hair of humans found in indoor air and in floor dust indicates that floors are an important reservoir of human-associated bacteria, and that the direct particle shedding of desquamated skin cells and their subsequent resuspension strongly influenced the airborne bacteria population structure in this human-occupied environment. Inhalation exposure to microbes shed by other current or previous human occupants may occur in communal indoor environments
Lavado de manos, lavado de boca
Introducción: Durante la pandemia por COVID-19, seguimos trabajando virtualmente. Muchas plantas medicinales refuerzan el sistema inmunitario. Usamos la Matricaria Chamomilla Lineé (MC) o “Manzanilla”, en enjuagues bucales (EB), haciendo infusión de su inflorescencia, aplicando su acción antiinflamatoria y anti infecciosa, para prevenir la mayor fuente del contagio a través de las gotitas de Flügge de la saliva, acompañado del cepillado dental. Objetivos: Colaborar contra la pandemia por COVID-19, cuidando la salud de la población. Metodología: Fase I: nos reunimos con el equipo del proyecto, a través de zoom, donde nos reparten las tareas a realizar, en la escuela primaria Nº15 “General Manuel Belgrano” del barrio “Campamento” de Ensenada, que tiene jornada completa y funciona según normativas vigentes y la Unidad Sanitaria “Campamento” de Ensenada, donde atienden los consultorios de Odontología, Obstetricia, Clínica Médica y Vacunación en doble turno. Fase II: colaboramos en la confección de material didáctico para la Escuela y Unidad Sanitaria, que se envían online, para alumnos, docentes, pacientes y profesionales. Fase III: presentamos nuestra experiencia en eventos científicos, Capítulo estudiantil, para la difusión a otros alumnos. Resultados: mejoramos la salud poblacional. Conclusiones: Si informamos sobre los síntomas de la enfermedad, las normas y recomendaciones para evitar la propagación del virus SARS-CoV2,higiene, (EB), en esta población de riesgo, de esta región geográfica, estamos dando batalla a la pandemia.Facultad de Odontologí
NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems
Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS
Wastewater-Based Epidemiology: Global Collaborative to Maximize Contributions in the Fight against COVID-19
Severe acute respiratory syndrome coronavirus 2 (SARSCoV-2), a novel member of the Coronaviridae family, has been identified as the etiologic agent of an ongoing pandemic of severe pneumonia known as COVID-19. To date there have been millions of cases of COVID-19 diagnosed in 184 countries with case fatality rates ranging from 1.8% in Germany to 12.5% in Italy. Limited diagnostic testing capacity and asymptomatic and oligosymptomatic infections result in significant uncertainty in the estimated extent of SARS-CoV-2 infection. Recent reports have documented that infection with SARS-CoV-2 is accompanied by persistent shedding of virus RNA in feces in 27% to 89% of patients at densities from 0.8 to 7.5 log10 gene copies per gram. The presence of SARS-CoV-2 RNA in feces raises the potential to survey sewage for virus RNA to inform epidemiological monitoring of COVID-19, which we refer to as wastewater-based epidemiology (WBE), but is also known as environmental surveillance
Temporal variability and effect of environmental variables on airborne bacterial communities in an urban area of Northern Italy
Despite airborne microorganisms representing a relevant
fraction of atmospheric suspended particles, only a small
amount of information is currently available on their abundance
and diversity and very few studies have investigated the environmental
factors influencing the structure of airborne bacterial
communities. In this work, we used quantitative PCR and Illumina
technology to provide a thorough description of airborne
bacterial communities in the urban area of Milan (Italy). Forty
samples were collected in 10-day sampling sessions, with one
sessionper season.Themeanbacterialabundancewasabout104
ribosomal operons perm3 of air andwas lower inwinter than in
the other seasons. Communitieswere dominated by Actinobacteridae,
Clostridiales, Sphingobacteriales and fewproteobacterial
orders (Burkholderiales, Rhizobiales, Sphingomonadales
andPseudomonadales).Chloroplastswere abundant in all samples.
Ahigher abundanceof Actinobacteridae,which are typical
soil-inhabiting bacteria, and a lower abundance of chloroplasts in samples collected on cold days were observed. The variation
in community composition observed within seasons was comparable
to that observed between seasons, thus suggesting that
airborne bacterial communities showlarge temporal variability,
even between consecutive days. The structure of airborne bacterial
communities therefore suggests that soil and plants are the
sources which contribute most to the airborne communities of
Milan atmosphere, but the structure of the bacterial community
seems to depend mainly on the source of bacteria that predominates
in a given period of time
Lolita dear, would thou wert near, to hear me tell [first line]
Performance Medium: Piano and Voice (with lyrics
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