Cardiorespiratory fitness predicts clustered cardiometabolic risk in 10-11.9 year olds

The aim of this study was to investigate levels of clustered cardiometabolic risk and the odds of being ‘at risk’ according to cardiorespiratory fitness status in children. Data from 88 10–11.9-year-old children (mean age 11.05 ± 0.51 years), who participated in either the REACH Year 6 or the Benefits of Fitness Circuits for Primary School Populations studies were combined. Waist circumference, systolic blood pressure, diastolic blood pressure, glucose, triglycerides, high-density lipoprotein cholesterol, adiponectin and C-reactive protein were assessed and used to estimate clustered cardiometabolic risk. Participants were classified as ‘fit’ or ‘unfit’ using recently published definitions (46.6 and 41.9 mL/kg/min for boys and girls, respectively), and continuous clustered risk scores between fitness groups were assessed. Participants were subsequently assigned to a ‘normal’ or ‘high’ clustered cardiometabolic risk group based on risk scores, and logistic regression analysis assessed the odds of belonging to the increased cardiometabolic risk group according to fitness. The unfit group exhibited significantly higher clustered cardiometabolic risk scores (p < 0.001) than the fit group. A clear association between fitness group and being at increased cardiometabolic risk (B = 2.509, p = 0.001) was also identified, and participants classed as being unfit were found to have odds of being classified as ‘at risk’ of 12.30 (95 % CI = 2.64–57.33).\ud \ud Conclusion Assessing cardiorespiratory fitness is a valid method of identifying children most at risk of cardiometabolic pathologies. The ROC thresholds could be used to identify populations of children most at risk and may therefore be used to effectively target a cardiometabolic risk-reducing public health intervention

The Complete Genome Sequence of Mycoplasma bovis Strain Hubei-1

Infection by Mycoplasma bovis (M. bovis) can induce diseases, such as pneumonia and otitis media in young calves and mastitis and arthritis in older animals. Here, we report the finished and annotated genome sequence of M. bovis strain Hubei-1, a strain isolated in 2008 that caused calf pneumonia on a Chinese farm. The genome of M. bovis strain Hubei-1 contains a single circular chromosome of 953,114 bp with a 29.37% GC content. We identified 803 open reading frames (ORFs) that occupy 89.5% of the genome. While 34 ORFs were Hubei-1 specific, 662 ORFs had orthologs in the M. bovis type strain PG45 genome. Genome analysis validated lateral gene transfer between M. bovis and the Mycoplasma mycoides subspecies mycoides, while phylogenetic analysis found that the closest M. bovis neighbor is Mycoplasma agalactiae. Glycerol may be the main carbon and energy source of M. bovis, and most of the biosynthesis pathways were incomplete. We report that 47 lipoproteins, 12 extracellular proteins and 18 transmembrane proteins are phase-variable and may help M. bovis escape the immune response. Besides lipoproteins and phase-variable proteins, genomic analysis found two possible pathogenicity islands, which consist of four genes and 11 genes each, and several other virulence factors including hemolysin, lipoate protein ligase, dihydrolipoamide dehydrogenase, extracellular cysteine protease and 5′-nucleotidase

Tegumentary leishmaniasis and coinfections other than HIV

<div><p>Background</p><p>Tegumentary leishmaniasis (TL) is a disease of skin and/or mucosal tissues caused by <i>Leishmania</i> parasites. TL patients may concurrently carry other pathogens, which may influence the clinical outcome of TL.</p><p>Methodology and principal findings</p><p>This review focuses on the frequency of TL coinfections in human populations, interactions between <i>Leishmania</i> and other pathogens in animal models and human subjects, and implications of TL coinfections for clinical practice. For the purpose of this review, TL is defined as all forms of cutaneous (localised, disseminated, or diffuse) and mucocutaneous leishmaniasis. Human immunodeficiency virus (HIV) coinfection, superinfection with skin bacteria, and skin manifestations of visceral leishmaniasis are not included. We searched MEDLINE and other databases and included 73 records: 21 experimental studies in animals and 52 studies about human subjects (mainly cross-sectional and case studies). Several reports describe the frequency of <i>Trypanosoma cruzi</i> coinfection in TL patients in Argentina (about 41%) and the frequency of helminthiasis in TL patients in Brazil (15% to 88%). Different hypotheses have been explored about mechanisms of interaction between different microorganisms, but no clear answers emerge. Such interactions may involve innate immunity coupled with regulatory networks that affect quality and quantity of acquired immune responses. Diagnostic problems may occur when concurrent infections cause similar lesions (e.g., TL and leprosy), when different pathogens are present in the same lesions (e.g., <i>Leishmania</i> and <i>Sporothrix schenckii</i>), or when similarities between phylogenetically close pathogens affect accuracy of diagnostic tests (e.g., serology for leishmaniasis and Chagas disease). Some coinfections (e.g., helminthiasis) appear to reduce the effectiveness of antileishmanial treatment, and drug combinations may cause cumulative adverse effects.</p><p>Conclusions and significance</p><p>In patients with TL, coinfection is frequent, it can lead to diagnostic errors and delays, and it can influence the effectiveness and safety of treatment. More research is needed to unravel how coinfections interfere with the pathogenesis of TL.</p></div

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer