COTS Unmanned Systems and Partner Force Innovation

A Quad, describing CRUSER Seed Research Program funded research.CRUSER Funded ResearchFY22 Funded Research ProposalConsortium for Robotics and Unmanned Systems Education and Research (CRUSER

A microsatellites-based survey on the genetic structure of two Italian local chicken breeds

The biodiversity safeguard is an important goal of poultry production in every developed country. Nowadays, the high chicken meat demand from the world market has been leading to a large spread of strongly producing commercial chicken lines. The creation of these standard types is causing a progressive loss of genetic variability. Ancona and Livorno are two Italian autochthonous chicken breeds which represent a great resource in terms of specific genetic richness. Aim of this study is to investigate the genetic diversity of these breeds as potential valuable genetic variability source. In fact, in spite of their endangered status, these chicken breeds are very appreciated for their ability to adapt themselves to extensive organic rearing systems. Blood samples from 131 individuals were collected and genotyped through a thirty microsatellites-based analysis. All the observed descriptive statistical indexes suggested a heterozygosity deficiency and an inbreeding level (mean observed heterozygosity = 0.46, mean expected heterozygosity = 0.53, Fis in Ancona and Livorno = 0.251 and 0.086). The tree from inter-individual DAS distance using Neighbour-Joining algorithm and the FCA analysis showed a higher internal variability in Livorno than in Ancona. STRUCTURE analysis showed the genetic uniqueness of the breeds and the presence of sub-groups in Ancona originating from a possible genetic isolation. This research could be a suitable starting point to set up improved selection schemes and a potential preliminary genotypic test for all the cocks to be used in the selection

TLC Year in Review

With contributions by Matthew Schehl, Shona Dunn, Ali Rodgers, Betsy Wallace, Miriam Bergue Alves, Michael Guerrero, Aileen B. Houston, Cheryldee Huddleston, Leo Blanken and Cecilia Panella, and a forward by Scott Bischoff, Dennis Lester, and Tom Rosko

Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk

Simple Parameters from Complete Blood Count Predict In-Hospital Mortality in COVID-19

Introduction. The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. Materials and Methods. In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients (F 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. Results. At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) (χ2 10.4; p4.68 was characterized by an odds ratio for in-hospital mortality OR=3.40 (2.40-4.82), while the OR for a RDW>13.7% was 4.09 (2.87-5.83); a platelet count>166,000/μL was, conversely, protective (OR: 0.45 (0.32-0.63)). Conclusion. Our findings arise the opportunity of stratifying COVID-19 severity according to simple lab parameters, which may drive clinical decisions about monitoring and treatment

Infections, antibiotic treatment and mortality in patients admitted to ICUs in countries considered to have high levels of antibiotic resistance compared to those with low levels

Background: Antimicrobial resistance is an increasing concern in ICUs worldwide. Infection with an antibiotic resistant (ABR) strain of an organism is associated with greater mortality than infection with the non-resistant strain, but there are few data assessing whether being admitted to an intensive care unit (ICU) with high levels of antimicrobial resistance is associated with a worse outcome than being admitted to an ICU with low rates of resistance. The aim of this study was, therefore, to compare the characteristics of infections and antibiotic treatments and patient outcomes in patients admitted to ICUs in countries considered as having high levels of antibiotic resistance and those admitted to ICUs in countries considered as having low levels of antibiotic resistance. Methods: Data from the large, international EPIC II one-day point prevalence study on infections in patients hospitalized in ICUs were used. For the current study, we compared the data obtained from patients from two groups of countries: countries with reported MRSA rates of greater than= 25% (highABR: Greece, Israel, Italy, Malta, Portugal, Spain, and Turkey) and countries with MRSA rates of less than 5% (lowABR: Denmark, Finland, Netherlands, Norway, and Sweden). Results: On the study day, 1187/2204 (53.9%) patients in the HighABR ICUs were infected and 255/558 (45.7%) in the LowABR ICUs (P less than 0.01). Patients in the HighABR ICUs were more severely ill than those in the LowABR ICUs, as reflected by a higher SAPS II score (35.6 vs 32.7, P less than 0.05) and had longer median ICU (12 days vs 5 days) and hospital (24 days vs 16 days) lengths of stay. They also had higher crude ICU (20.0% vs 15.4%) and hospital (27.0% vs 21.5%) mortality rates (both P less than 0.05). However, after multivariable adjustment and matched pair analysis there were no differences in ICU or hospital mortality rates between High or LowABR ICU patients overall or among those with infections. Conclusions: Being hospitalized in an ICU in a region with high levels of antimicrobial resistance is not associated per se with a worse outcome

Infections, antibiotic treatment and mortality in patients admitted to ICUs in countries considered to have high levels of antibiotic resistance compared to those with low levels

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Infections, antibiotic treatment and mortality in patients admitted to ICUs in countries considered to have high levels of antibiotic resistance compared to those with low levels

Background: Antimicrobial resistance is an increasing concern in ICUs worldwide. Infection with an antibiotic resistant (ABR) strain of an organism is associated with greater mortality than infection with the non-resistant strain, but there are few data assessing whether being admitted to an intensive care unit (ICU) with high levels of antimicrobial resistance is associated with a worse outcome than being admitted to an ICU with low rates of resistance. The aim of this study was, therefore, to compare the characteristics of infections and antibiotic treatments and patient outcomes in patients admitted to ICUs in countries considered as having high levels of antibiotic resistance and those admitted to ICUs in countries considered as having low levels of antibiotic resistance.Methods: Data from the large, international EPIC II one-day point prevalence study on infections in patients hospitalized in ICUs were used. For the current study, we compared the data obtained from patients from two groups of countries: countries with reported MRSA rates of ≥ 25% (highABR: Greece, Israel, Italy, Malta, Portugal, Spain, and Turkey) and countries with MRSA rates of < 5% (lowABR: Denmark, Finland, Netherlands, Norway, and Sweden).Results: On the study day, 1187/2204 (53.9%) patients in the HighABR ICUs were infected and 255/558 (45.7%) in the LowABR ICUs (P < 0.01). Patients in the HighABR ICUs were more severely ill than those in the LowABR ICUs, as reflected by a higher SAPS II score (35.6 vs 32.7, P < 0.05) and had longer median ICU (12 days vs 5 days) and hospital (24 days vs 16 days) lengths of stay. They also had higher crude ICU (20.0% vs 15.4%) and hospital (27.0% vs 21.5%) mortality rates (both P < 0.05). However, after multivariable adjustment and matched pair analysis there were no differences in ICU or hospital mortality rates between High or LowABR ICU patients overall or among those with infections.Conclusions: Being hospitalized in an ICU in a region with high levels of antimicrobial resistance is not associated per se with a worse outcome. © 2014 Hanberger et al.; licensee BioMed Central Ltd

Candida bloodstream infections in intensive care units: analysis of the extended prevalence of infection in intensive care unit study

Item does not contain fulltextOBJECTIVES: To provide a global, up-to-date picture of the prevalence, treatment, and outcomes of Candida bloodstream infections in intensive care unit patients and compare Candida with bacterial bloodstream infection. DESIGN: A retrospective analysis of the Extended Prevalence of Infection in the ICU Study (EPIC II). Demographic, physiological, infection-related and therapeutic data were collected. Patients were grouped as having Candida, Gram-positive, Gram-negative, and combined Candida/bacterial bloodstream infection. Outcome data were assessed at intensive care unit and hospital discharge. SETTING: EPIC II included 1265 intensive care units in 76 countries. PATIENTS: Patients in participating intensive care units on study day. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: Of the 14,414 patients in EPIC II, 99 patients had Candida bloodstream infections for a prevalence of 6.9 per 1000 patients. Sixty-one patients had candidemia alone and 38 patients had combined bloodstream infections. Candida albicans (n = 70) was the predominant species. Primary therapy included monotherapy with fluconazole (n = 39), caspofungin (n = 16), and a polyene-based product (n = 12). Combination therapy was infrequently used (n = 10). Compared with patients with Gram-positive (n = 420) and Gram-negative (n = 264) bloodstream infections, patients with candidemia were more likely to have solid tumors (p < .05) and appeared to have been in an intensive care unit longer (14 days [range, 5-25 days], 8 days [range, 3-20 days], and 10 days [range, 2-23 days], respectively), but this difference was not statistically significant. Severity of illness and organ dysfunction scores were similar between groups. Patients with Candida bloodstream infections, compared with patients with Gram-positive and Gram-negative bloodstream infections, had the greatest crude intensive care unit mortality rates (42.6%, 25.3%, and 29.1%, respectively) and longer intensive care unit lengths of stay (median [interquartile range]) (33 days [18-44], 20 days [9-43], and 21 days [8-46], respectively); however, these differences were not statistically significant. CONCLUSION: Candidemia remains a significant problem in intensive care units patients. In the EPIC II population, Candida albicans was the most common organism and fluconazole remained the predominant antifungal agent used. Candida bloodstream infections are associated with high intensive care unit and hospital mortality rates and resource use