Inquérito sorológico e molecular de Leptospira spp. em cavalos carroceiros de área endêmica para leptospirose humana em Curitiba, Sul do Brasil

Introdução: Cavalos carroceiros são uma população reemergente empregada para transportar materiais recicláveis em cidades. Métodos: Em área endêmica para leptospirose humana foram amostrados 62 cavalos. Soroaglutinação microscópica e reação em cadeia da polimerase em tempo real foram empregadas. Resultados: Observou-se soropositividade em 75,8% com sorovar Icterohaemorrhagiae em 80,8% cavalos. Amostras de sangue e urina foram negativas no qPCR. Observou-se correlação positiva entre SAM e pluviosidade (p = 0,02) e alagamentos (p = 0,03). Conclusão: Embora cavalos possam estar constantemente expostos a Leptospira spp. no ambiente, principalmente por chuvas e inundações, leptospiremia e leptospiruria não foram encontradas neste estudo.Introduction: Cart horses are a re-emerging population employed to carry recyclable material in cities. Methods: Sixty-two horses were sampled in an endemic area of human leptospirosis. The microscopic agglutination test (MAT) and real-time polymerase chain reaction (qPCR) were performed. Results: A seropositivity of 75.8% with serovar Icterohaemorrhagiae in 80.8% of the horses was observed. Blood and urine were qPCR negative. MAT showed positive correlations with rainfall (p = 0.02) and flooding (p = 0.03). Conclusions: Although horses may be constantly exposed to Leptospira spp. in the environment mostly because of rainfall and flooding, no leptospiremia or leptospiruria were observed in this study

A novel bocavirus in canine liver

Background: Bocaviruses are classified as a genus within the Parvoviridae family of single-stranded DNA viruses and are pathogenic in some mammalian species. Two species have been previously reported in dogs, minute virus of canines (MVC), associated with neonatal diseases and fertility disorders; and Canine bocavirus (CBoV), associated with respiratory disease. Findings: In this study using deep sequencing of enriched viral particles from the liver of a dog with severe hemorrhagic gastroenteritis, necrotizing vasculitis, granulomatous lymphadenitis and anuric renal failure, we identified and characterized a novel bocavirus we named Canine bocavirus 3 (CnBoV3). The three major ORFs of CnBoV3 (NS1, NP1 and VP1) shared less than 60% aa identity with those of other bocaviruses qualifying it as a novel species based on ICTV criteria. Inverse PCR showed the presence of concatemerized or circular forms of the genome in liver. Conclusions: We genetically characterized a bocavirus in a dog liver that is highly distinct from prior canine bocaviruses found in respiratory and fecal samples. Its role in this animal’s complex disease remains to be determined. Keywords: Canine bocavirus 3; Episome; Coinfectio

Presence of infectious agents and co-infections in diarrheic dogs determined with a real-time polymerase chain reaction-based panel

BACKGROUND: Infectious diarrhea can be caused by bacteria, viruses, or protozoan organisms, or a combination of these. The identification of co-infections in dogs is important to determine the prognosis and to plan strategies for their treatment and prophylaxis. Although many pathogens have been individually detected with real-time polymerase chain reaction (PCR), a comprehensive panel of agents that cause diarrhea in privately owned dogs has not yet been established. The objective of this study was to use a real-time PCR diarrhea panel to survey the frequencies of pathogens and co-infections in owned dogs attended in a veterinary hospital with and without diarrhea, as well the frequency in different countries. Feces samples were tested for canine distemper virus, canine coronavirus, canine parvovirus type 2 (CPV-2), Clostridium perfringens alpha toxin (CPA), Cryptosporidium spp., Giardia spp., and Salmonella spp. using molecular techniques. RESULTS: In total, 104 diarrheic and 43 control dogs that were presented consecutively at a major private veterinary hospital were included in the study. Overall, 71/104 (68.3%) dogs with diarrhea were positive for at least one pathogen: a single infection in 39/71 dogs (54.9%) and co-infections in 32/71 dogs (45.1%), including 21/32 dogs (65.6%) with dual, 5/32 (15.6%) with triple, and 6/32 (18.8%) with quadruple infections. In the control group, 13/43 (30.2%) dogs were positive, all with single infections only. The most prevalent pathogens in the diarrheic dogs were CPA (40/104 dogs, 38.5%), CPV-2 (36/104 dogs, 34.6%), and Giardia spp. (14/104 dogs, 13.5%). CPV-2 was the most prevalent pathogen in the dual co-infections, associated with CPA, Cryptosporidium spp., or Giardia spp. No statistical difference (P = 0.8374) was observed in the duration of diarrhea or the number of deaths (P = 0.5722) in the presence or absence of single or co-infections. CONCLUSIONS: Diarrheic dogs showed a higher prevalence of pathogen infections than the controls. Whereas the healthy dogs had only single infections, about half the diarrheic dogs had co-infections. Therefore, multiple pathogens should be investigated in dogs presenting with diarrhea. The effects of multiple pathogens on the disease outcomes remain unclear because the rate of death and the duration of diarrhea did not seem to be affected by these factors

A Quantum-mechanical Approach for Constrained Macromolecular Chains

Many approaches to three-dimensional constrained macromolecular chains at thermal equilibrium, at about room temperatures, are based upon constrained Classical Hamiltonian Dynamics (cCHDa). Quantum-mechanical approaches (QMa) have also been treated by different researchers for decades. QMa address a fundamental issue (constraints versus the uncertainty principle) and are versatile: they also yield classical descriptions (which may not coincide with those from cCHDa, although they may agree for certain relevant quantities). Open issues include whether QMa have enough practical consequences which differ from and/or improve those from cCHDa. We shall treat cCHDa briefly and deal with QMa, by outlining old approaches and focusing on recent ones.Comment: Expands review published in The European Physical Journal (Special Topics) Vol. 200, pp. 225-258 (2011

SEROLOGICAL AND MOLECULAR SURVEY OF Leptospira spp. AMONG CART HORSES FROM AN ENDEMIC AREA OF HUMAN LEPTOSPIROSIS IN CURITIBA, SOUTHERN BRAZIL

Introduction: Cart horses are a re-emerging population employed to carry recyclable material in cities. Methods: Sixty-two horses were sampled in an endemic area of human leptospirosis. The microscopic agglutination test (MAT) and real-time polymerase chain reaction (qPCR) were performed. Results: A seropositivity of 75.8% with serovar Icterohaemorrhagiae in 80.8% of the horses was observed. Blood and urine were qPCR negative. MAT showed positive correlations with rainfall (p = 0.02) and flooding (p = 0.03). Conclusions: Although horses may be constantly exposed to Leptospira spp. in the environment mostly because of rainfall and flooding, no leptospiremia or leptospiruria were observed in this study

Plasma Protein Biomarkers Distinguish Multisystem Inflammatory Syndrome in Children From Other Pediatric Infectious and Inflammatory Diseases

Background: Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious hyperinflammatory complication following infection with severe acute respiratory syndrome coronavirus 2. The mechanisms underpinning the pathophysiology of MIS-C are poorly understood. Moreover, clinically distinguishing MIS-C from other childhood infectious and inflammatory conditions, such as Kawasaki disease or severe bacterial and viral infections, is challenging due to overlapping clinical and laboratory features. We aimed to determine a set of plasma protein biomarkers that could discriminate MIS-C from those other diseases. Methods: Seven candidate protein biomarkers for MIS-C were selected based on literature and from whole blood RNA sequencing data from patients with MIS-C and other diseases. Plasma concentrations of ARG1, CCL20, CD163, CORIN, CXCL9, PCSK9 and ADAMTS2 were quantified in MIS-C (n = 22), Kawasaki disease (n = 23), definite bacterial (n = 28) and viral (n = 27) disease and healthy controls (n = 8). Logistic regression models were used to determine the discriminatory ability of individual proteins and protein combinations to identify MIS-C and association with severity of illness. Results: Plasma levels of CD163, CXCL9 and PCSK9 were significantly elevated in MIS-C with a combined area under the receiver operating characteristic curve of 85.7% (95% confidence interval: 76.6%–94.8%) for discriminating MIS-C from other childhood diseases. Lower ARG1 and CORIN plasma levels were significantly associated with severe MIS-C cases requiring inotropes, pediatric intensive care unit admission or with shock. Conclusion: Our findings demonstrate the feasibility of a host protein biomarker signature for MIS-C and may provide new insight into its pathophysiology

Plasma Protein Biomarkers Distinguish Multisystem Inflammatory Syndrome in Children from Other Pediatric Infectious and Inflammatory Diseases

Background: Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious hyperinflammatory complication following infection with severe acute respiratory syndrome coronavirus 2. The mechanisms underpinning the pathophysiology of MIS-C are poorly understood. Moreover, clinically distinguishing MIS-C from other childhood infectious and inflammatory conditions, such as Kawasaki disease or severe bacterial and viral infections, is challenging due to overlapping clinical and laboratory features. We aimed to determine a set of plasma protein biomarkers that could discriminate MIS-C from those other diseases. Methods: Seven candidate protein biomarkers for MIS-C were selected based on literature and from whole blood RNA sequencing data from patients with MIS-C and other diseases. Plasma concentrations of ARG1, CCL20, CD163, CORIN, CXCL9, PCSK9 and ADAMTS2 were quantified in MIS-C (n = 22), Kawasaki disease (n = 23), definite bacterial (n = 28) and viral (n = 27) disease and healthy controls (n = 8). Logistic regression models were used to determine the discriminatory ability of individual proteins and protein combinations to identify MIS-C and association with severity of illness. Results: Plasma levels of CD163, CXCL9 and PCSK9 were significantly elevated in MIS-C with a combined area under the receiver operating characteristic curve of 85.7% (95% confidence interval: 76.6%-94.8%) for discriminating MIS-C from other childhood diseases. Lower ARG1 and CORIN plasma levels were significantly associated with severe MIS-C cases requiring inotropes, pediatric intensive care unit admission or with shock. Conclusion: Our findings demonstrate the feasibility of a host protein biomarker signature for MIS-C and may provide new insight into its pathophysiology

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Plasma protein biomarkers distinguish Multisystem Inflammatory Syndrome in Children (MIS-C) from other pediatric infectious and inflammatory diseases

ABSTRACT Background Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious hyperinflammatory complication following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The mechanisms underpinning the pathophysiology of MIS-C are poorly understood. Moreover, clinically distinguishing MIS-C from other childhood infectious and inflammatory conditions, such as Kawasaki Disease (KD) or severe bacterial and viral infections is challenging due to overlapping clinical and laboratory features. We aimed to determine a set of plasma protein biomarkers that could discriminate MIS-C from those other diseases. Methods Seven candidate protein biomarkers for MIS-C were selected based on literature and from whole blood RNA-Sequencing data from patients with MIS-C and other diseases. Plasma concentrations of ARG1, CCL20, CD163, CORIN, CXCL9, PCSK9 and ADAMTS2 were quantified in MIS-C (n=22), KD (n=23), definite bacterial (DB; n=28) and viral (DV, n=27) disease, and healthy controls (n=8). Logistic regression models were used to determine the discriminatory ability of individual proteins and protein combinations to identify MIS-C, and association with severity of illness. Results Plasma levels of CD163, CXCL9, and PCSK9 were significantly elevated in MIS-C with a combined AUC of 86% (95% CI: 76.8%-95.1%) for discriminating MIS-C from other childhood diseases. Lower ARG1 and CORIN plasma levels were significantly associated with severe MIS-C cases requiring oxygen, inotropes or with shock. Conclusion Our findings demonstrate the feasibility of a host protein biomarker signature for MIS-C and may provide new insight into its pathophysiology