Standardization of Laboratory Methods for the PERCH Study.

The Pneumonia Etiology Research for Child Health study was conducted across 7 diverse research sites and relied on standardized clinical and laboratory methods for the accurate and meaningful interpretation of pneumonia etiology data. Blood, respiratory specimens, and urine were collected from children aged 1-59 months hospitalized with severe or very severe pneumonia and community controls of the same age without severe pneumonia and were tested with an extensive array of laboratory diagnostic tests. A standardized testing algorithm and standard operating procedures were applied across all study sites. Site laboratories received uniform training, equipment, and reagents for core testing methods. Standardization was further assured by routine teleconferences, in-person meetings, site monitoring visits, and internal and external quality assurance testing. Targeted confirmatory testing and testing by specialized assays were done at a central reference laboratory

The Effect of Antibiotic Exposure and Specimen Volume on the Detection of Bacterial Pathogens in Children With Pneumonia.

BACKGROUND.: Antibiotic exposure and specimen volume are known to affect pathogen detection by culture. Here we assess their effects on bacterial pathogen detection by both culture and polymerase chain reaction (PCR) in children. METHODS.: PERCH (Pneumonia Etiology Research for Child Health) is a case-control study of pneumonia in children aged 1-59 months investigating pathogens in blood, nasopharyngeal/oropharyngeal (NP/OP) swabs, and induced sputum by culture and PCR. Antibiotic exposure was ascertained by serum bioassay, and for cases, by a record of antibiotic treatment prior to specimen collection. Inoculated blood culture bottles were weighed to estimate volume. RESULTS.: Antibiotic exposure ranged by specimen type from 43.5% to 81.7% in 4223 cases and was detected in 2.3% of 4863 controls. Antibiotics were associated with a 45% reduction in blood culture yield and approximately 20% reduction in yield from induced sputum culture. Reduction in yield of Streptococcus pneumoniae from NP culture was approximately 30% in cases and approximately 32% in controls. Several bacteria had significant but marginal reductions (by 5%-7%) in detection by PCR in NP/OP swabs from both cases and controls, with the exception of S. pneumoniae in exposed controls, which was detected 25% less frequently compared to nonexposed controls. Bacterial detection in induced sputum by PCR decreased 7% for exposed compared to nonexposed cases. For every additional 1 mL of blood culture specimen collected, microbial yield increased 0.51% (95% confidence interval, 0.47%-0.54%), from 2% when volume was ≤1 mL to approximately 6% for ≥3 mL. CONCLUSIONS.: Antibiotic exposure and blood culture volume affect detection of bacterial pathogens in children with pneumonia and should be accounted for in studies of etiology and in clinical management

Colonization Density of the Upper Respiratory Tract as a Predictor of Pneumonia-Haemophilus influenzae, Moraxella catarrhalis, Staphylococcus aureus, and Pneumocystis jirovecii.

BACKGROUND.: There is limited information on the association between colonization density of upper respiratory tract colonizers and pathogen-specific pneumonia. We assessed this association for Haemophilus influenzae, Moraxella catarrhalis, Staphylococcus aureus, and Pneumocystis jirovecii. METHODS.: In 7 low- and middle-income countries, nasopharyngeal/oropharyngeal swabs from children with severe pneumonia and age-frequency matched community controls were tested using quantitative polymerase chain reaction (PCR). Differences in median colonization density were evaluated using the Wilcoxon rank-sum test. Density cutoffs were determined using receiver operating characteristic curves. Cases with a pathogen identified from lung aspirate culture or PCR, pleural fluid culture or PCR, blood culture, and immunofluorescence for P. jirovecii defined microbiologically confirmed cases for the given pathogens. RESULTS.: Higher densities of H. influenzae were observed in both microbiologically confirmed cases and chest radiograph (CXR)-positive cases compared to controls. Staphylococcus aureus and P. jirovecii had higher densities in CXR-positive cases vs controls. A 5.9 log10 copies/mL density cutoff for H. influenzae yielded 86% sensitivity and 77% specificity for detecting microbiologically confirmed cases; however, densities overlapped between cases and controls and positive predictive values were poor (<3%). Informative density cutoffs were not found for S. aureus and M. catarrhalis, and a lack of confirmed case data limited the cutoff identification for P. jirovecii. CONCLUSIONS.: There is evidence for an association between H. influenzae colonization density and H. influenzae-confirmed pneumonia in children; the association may be particularly informative in epidemiologic studies. Colonization densities of M. catarrhalis, S. aureus, and P. jirovecii are unlikely to be of diagnostic value in clinical settings

Colonization density of the upper respiratory tract as a predictor of pneumonia—Haemophilus influenzae, Moraxella catarrhalis, Staphylococcus aureus, and Pneumocystis jirovecii

Background There is limited information on the association between colonization density of upper respiratory tract colonizers and pathogen-specific pneumonia. We assessed this association for Haemophilus influenzae, Moraxella catarrhalis, Staphylococcus aureus, and Pneumocystis jirovecii. Methods In 7 low- and middle-income countries, nasopharyngeal/oropharyngeal swabs from children with severe pneumonia and age-frequency matched community controls were tested using quantitative polymerase chain reaction (PCR). Differences in median colonization density were evaluated using the Wilcoxon rank-sum test. Density cutoffs were determined using receiver operating characteristic curves. Cases with a pathogen identified from lung aspirate culture or PCR, pleural fluid culture or PCR, blood culture, and immunofluorescence for P. jirovecii defined microbiologically confirmed cases for the given pathogens. Results Higher densities of H. influenzae were observed in both microbiologically confirmed cases and chest radiograph (CXR)–positive cases compared to controls. Staphylococcus aureus and P. jirovecii had higher densities in CXR-positive cases vs controls. A 5.9 log10 copies/mL density cutoff for H. influenzae yielded 86% sensitivity and 77% specificity for detecting microbiologically confirmed cases; however, densities overlapped between cases and controls and positive predictive values were poor (<3%). Informative density cutoffs were not found for S. aureus and M. catarrhalis, and a lack of confirmed case data limited the cutoff identification for P. jirovecii. Conclusions There is evidence for an association between H. influenzae colonization density and H. influenzae–confirmed pneumonia in children; the association may be particularly informative in epidemiologic studies. Colonization densities of M. catarrhalis, S. aureus, and P. jirovecii are unlikely to be of diagnostic value in clinical settings

Standardization of Laboratory Methods for the PERCH Study

The Pneumonia Etiology Research for Child Health study was conducted across 7 diverse research sites and relied on standardized clinical and laboratory methods for the accurate and meaningful interpretation of pneumonia etiology data. Blood, respiratory specimens, and urine were collected from children aged 1-59 months hospitalized with severe or very severe pneumonia and community controls of the same age without severe pneumonia and were tested with an extensive array of laboratory diagnostic tests. A standardized testing algorithm and standard operating procedures were applied across all study sites. Site laboratories received uniform training, equipment, and reagents for core testing methods. Standardization was further assured by routine teleconferences, in-person meetings, site monitoring visits, and internal and external quality assurance testing. Targeted confirmatory testing and testing by specialized assays were done at a central reference laboratory

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n1⁄42,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n1⁄43,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombinedo5108) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine–cytokine pathways, for which relevant therapies exist

Standardization of laboratory methods for the PERCH study

The Pneumonia Etiology Research for Child Health study was conducted across diverse research sites and relied on standardized clinical and laboratory methods for the accurate and meaningful interpretation of pneumonia etiology data. Blood, respiratory specimens, and urine were collected from children aged 1-5months hospitalized with severe or very severe pneumonia and community controls of the same age without severe pneumonia and were tested with an extensive array of laboratory diagnostic tests. A standardized testing algorithm and standard operating procedures were applied across all study sites. Site laboratories received uniform training, equipment, and reagents for core testing methods. Standardization was further assured by routine teleconferences, in-person meetings, site monitoring visits, and internal

TRAINING RECURRENT NEURAL NETWORKS FOR PARTICULATE MATTER CONCENTRATION PREDICTION

Abstract. A high level of particulate matter in the atmosphere has an adverse long-term effect on human health. It has been associated with increased pulmonary tract and lung infections. It is more common in urban areas, especially megacities due to the confluence of industries and motorized machinery. Considering that most of the world’s population lives in urban areas, there is a need to monitor air pollution arising from particulate matter in order to ensure clean and safe air in cities in accordance with goal 11 of the Sustainable Development Goals. One way of doing this is through the use of Recurrent Neural Networks (RNN), which are suited for time varying data. Particulate matter concentration recorded by a network of low-cost sensors in Stuttgart is trained on three of the most popular RNN variants: Standard LSTM, Peephole LSTM and Gated Recurrent Unit. Two optimizers are used, Stochastic Gradient descent and Adam. Training is done on a single sensor and the optimum weights transferred and used in the prediction of other sensor values. This study concludes that Gated Recurrent Unit with Stochastic Gradient Descent is the most effective of the three variants in predicting particulate matter PM2.5 concentrations. In addition to this, weight transfer between sensors is not affected by temperature, wind direction, wind speed and geographic distance between sensors but rather by atmospheric pressure and the similarity of recorded Particulate matter levels. </jats:p

MULTI-SENSOR TRAFFIC DATA FUSION FOR CONGESTION DETECTION AND TRACKING

Abstract. Traffic management applications including congestion detection and tracking rely on traffic from multiple sources to model the traffic conditions. The sources are either stationary sensors which include inductive loop detectors (ILD), radar stations and Bluetooth/WiFi/BLE sensors or Floating Car Data (FCD) from moving vehicles which transmit their locations and speeds. The different sources have their inherent strengths and weaknesses but when used together, they have the potential to provide traffic information with increased robustness. Multi-sensor data fusion has the potential to enhance the estimation of traffic state in real-time by reducing the uncertainty of individual sources, extending the temporal and spatial coverage and increasing the confidence of data inputs. In this study, we fuse data from different FCD providers to improve travel time and average segment speeds estimation. We use data from INRIX, HERE and TomTom FCD commercial services and fuse the speeds based on their confidence values and granularity on virtual sub-segments of 250 m. Speeds differences between each pair of datasets are evaluated by calculating the absolute mean and standard deviation of differences. The evaluation of systematic differences is also performed for peak periods depending on the day of the week. INRIX FCD speeds are compared with ground truth spot speeds where both datasets are measured at a 1-minute interval which show good agreement with an error rate of between 8–20%. Some issues that affect FCD accuracy which include data availability and reliability problems are identified and discussed. </jats:p