27 research outputs found
Rapid and non-destructive detection and identification of two strains of Wolbachia in Aedes aegypti by near-infrared spectroscopy
The release of Wolbachia infected mosquitoes is likely to form a key component of disease control strategies in the near future. We investigated the potential of using near-infrared spectroscopy (NIRS) to simultaneously detect and identify two strains of Wolbachia pipientis (wMelPop and wMel) in male and female laboratory-reared Aedes aegypti mosquitoes. Our aim is to find faster, cheaper alternatives for monitoring those releases than the molecular diagnostic techniques that are currently in use. Our findings indicate that NIRS can differentiate females and males infected with wMelPop from uninfected wild type samples with an accuracy of 96% (N = 299) and 87.5% (N = 377), respectively. Similarly, females and males infected with wMel were differentiated from uninfected wild type samples with accuracies of 92% (N = 352) and 89% (N = 444). NIRS could differentiate wMelPop and wMel transinfected females with an accuracy of 96.6% (N = 442) and males with an accuracy of 84.5% (N = 443). This non-destructive technique is faster than the standard polymerase chain reaction diagnostic techniques. After the purchase of a NIRS spectrometer, the technique requires little sample processing and does not consume any reagents
Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.
Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discoveryâ+âreplication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles
COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study
Background:
The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms.
Methods:
International, prospective observational study of 60â109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms.
Results:
âTypicalâ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (â€â18 years: 69, 48, 23; 85%), older adults (â„â70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each Pâ<â0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country.
Interpretation:
This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men
Visible-near infrared spectroscopy for detection of blood in sheep faeces
Heavy infestations of the blood-sucking gastrointestinal nematodes, Haemonchus contortus can cause severe anaemia in sheep and leakage of blood into the faeces, leading to morbidity and mortality. Early and accurate diagnosis of infections is critical for timely treatment of sheep, minimizing production and sheep welfare impacts. In pursuit of a quick and easy measure of H. contortus infections, we investigated the use of portable visible near infrared spectrometers for detecting the presence of haemoglobin in sheep faeces as an indicator of H. contortus infection. Calibration models built within the 400â600 nm region by partial least square regression resulted in acceptable prediction accuracies (r > 0.70 and root mean squared error of prediction 0.87 and root mean squared error of prediction 77%). The specificity of the prediction model for detecting haemoglobin in sheep faeces may be improved by adding more variations in faecal composition into the calibration model. Our success in detecting haemoglobin in sheep faeces, following minimal sample preparation, suggests that with further development, visânear infrared spectroscopy can provide a sensitive and convenient method for on-farm diagnosis of H. contortus infections
Detection of Haemonchus contortus nematode eggs in sheep faeces using near and mid-infrared spectroscopy
This paper reports the use of near infrared and mid-infrared spectroscopy to detect the presence and quantity of eggs of the gastrointestinal nematode Haemonchus contortus in sheep faeces. Haemonchus contortus eggs were quantified in dried, finely ground sheep faeces and in moist, coarsely ground faeces using near infrared and mid-infrared bench top spectrometers and a portable near infrared spectrometer. When Haemonchus contortus eggs were presented without faecal medium, it was found that the wavelength region of 1880â2100 nm was most important for detection. Broad classes of chemical properties found in the near infrared region were identified for dried Haemonchus contortus eggs using a mid-infrared spectrometer. However, when Haemonchus contortus eggs were mixed into the complex matrix of sheep faeces, the development of a robust calibration model for egg detection proved to be challenging (R < 0.47). The reliability of this method, if used for the detection of Haemonchus contortus eggs in the field, may be further limited by variations in egg species, faecal moisture content, faecal composition and particle size. Nevertheless, this is the first report identifying near infrared bands for Haemonchus contortus eggs and provides valuable information for future studies towards a spectroscopy-based method for detection of gastrointestinal nematodes
Recommended from our members
Influence of environmental factors on the detection of blood in sheep faeces using visible-near-infrared spectroscopy as a measure of Haemonchus contortus infection.
BackgroundExisting diagnostic methods for the parasitic gastrointestinal nematode, Haemonchus contortus, are time consuming and require specialised expertise, limiting their utility in the field. A practical, on-farm diagnostic tool could facilitate timely treatment decisions, thereby preventing losses in production and flock welfare. We previously demonstrated the ability of visible-near-infrared (Vis-NIR) spectroscopy to detect and quantify blood in sheep faeces with high accuracy. Here we report our investigation of whether variation in sheep type and environment affect the prediction accuracy of Vis-NIR spectroscopy in quantifying blood in faeces.MethodsVisible-NIR spectra were obtained from worm-free sheep faeces collected from different environments and sheep types in South Australia (SA) and New South Wales, Australia and spiked with various sheep blood concentrations. Spectra were analysed using principal component analysis (PCA), and calibration models were built around the haemoglobin (Hb) wavelength region (387-609 nm) using partial least squares regression. Models were used to predict Hb concentrations in spiked faeces from SA and naturally infected sheep faeces from Queensland (QLD). Samples from QLD were quantified using HemastixŸ test strip and FAMACHA© diagnostic test scores.ResultsPrincipal component analysis showed that location, class of sheep and pooled versus individual samples were factors affecting the Hb predictions. The models successfully differentiated 'healthy' SA samples from those requiring anthelmintic treatment with moderate to good prediction accuracy (sensitivity 57-94%, specificity 44-79%). The models were not predictive for blood in the naturally infected QLD samples, which may be due in part to variability of faecal background and blood chemistry between samples, or the difference in validation methods used for blood quantification. PCA of the QLD samples, however, identified a difference between samples containing high and low quantities of blood.ConclusionThis study demonstrates the potential of Vis-NIR spectroscopy for estimating blood concentration in faeces from various types of sheep and environmental backgrounds. However, the calibration models developed here did not capture sufficient environmental variation to accurately predict Hb in faeces collected from environments different to those used in the calibration model. Consequently, it will be necessary to establish models that incorporate samples that are more representative of areas where H. contortus is endemic
Recommended from our members
Influence of environmental factors on the detection of blood in sheep faeces using visible-near-infrared spectroscopy as a measure of Haemonchus contortus infection.
BackgroundExisting diagnostic methods for the parasitic gastrointestinal nematode, Haemonchus contortus, are time consuming and require specialised expertise, limiting their utility in the field. A practical, on-farm diagnostic tool could facilitate timely treatment decisions, thereby preventing losses in production and flock welfare. We previously demonstrated the ability of visible-near-infrared (Vis-NIR) spectroscopy to detect and quantify blood in sheep faeces with high accuracy. Here we report our investigation of whether variation in sheep type and environment affect the prediction accuracy of Vis-NIR spectroscopy in quantifying blood in faeces.MethodsVisible-NIR spectra were obtained from worm-free sheep faeces collected from different environments and sheep types in South Australia (SA) and New South Wales, Australia and spiked with various sheep blood concentrations. Spectra were analysed using principal component analysis (PCA), and calibration models were built around the haemoglobin (Hb) wavelength region (387-609 nm) using partial least squares regression. Models were used to predict Hb concentrations in spiked faeces from SA and naturally infected sheep faeces from Queensland (QLD). Samples from QLD were quantified using HemastixŸ test strip and FAMACHA© diagnostic test scores.ResultsPrincipal component analysis showed that location, class of sheep and pooled versus individual samples were factors affecting the Hb predictions. The models successfully differentiated 'healthy' SA samples from those requiring anthelmintic treatment with moderate to good prediction accuracy (sensitivity 57-94%, specificity 44-79%). The models were not predictive for blood in the naturally infected QLD samples, which may be due in part to variability of faecal background and blood chemistry between samples, or the difference in validation methods used for blood quantification. PCA of the QLD samples, however, identified a difference between samples containing high and low quantities of blood.ConclusionThis study demonstrates the potential of Vis-NIR spectroscopy for estimating blood concentration in faeces from various types of sheep and environmental backgrounds. However, the calibration models developed here did not capture sufficient environmental variation to accurately predict Hb in faeces collected from environments different to those used in the calibration model. Consequently, it will be necessary to establish models that incorporate samples that are more representative of areas where H. contortus is endemic
Percentage accuracy of <i>Wolbachia</i> detection using cross validation and prediction analyses.
<p>Percentage accuracy of <i>Wolbachia</i> detection using cross validation and prediction analyses.</p