Antenatal determinants of child lung development

There are several important antenatal factors including maternal stress, tobacco smoking, air pollution and nutrition that have been shown to influence lung development in utero and beyond. Exposure to these is associated with detrimental lung function and respiratory morbidity in childhood that can persist into adulthood. Environmental factors in utero may influence adult disease, referred to as fetal programming. This chapter reviews the proposed underlying mechanisms behind the effect on lung development including neurohormonal, immune, inflammatory and epigenetic pathways. There is a significant impact of sociodemographic inequalities on each of these antenatal determinants of child lung development, even in countries with a universally free healthcare system. As such, it is important that we do not refer to these simply as "lifestyle choices of expectant mothers", but rather aim to tackle these inequalities and provide equitable antenatal care and education to women in pregnancy to improve lifelong respiratory health

Impact of indoor environment on children's pulmonary health.

IntroductionA child's living environment has a significant impact on their respiratory health, with exposure to poor indoor air quality (IAQ) contributing to potentially lifelong respiratory morbidity. These effects occur throughout childhood, from the antenatal period through to adolescence. Children are particularly susceptible to the effects of environmental insults, and children living in socioeconomic deprivation globally are more likely to breathe air both indoors and outdoors, which poses an acute and long-term risk to their health. Adult respiratory health is, at least in part, determined by exposures and respiratory system development in childhood, starting in utero.Areas coveredThis narrative review will discuss, from a global perspective, what contributes to poor IAQ in the child's home and school environment and the impact that indoor air pollution exposure has on respiratory health throughout the different stages of childhood.Expert opinionAll children have the right to a living and educational environment without the threat of pollution affecting their health. Action is needed at multiple levels to address this pressing issue to improve lifelong respiratory health. Such action should incorporate a child's rights-based approach, empowering children, and their families, to have access to clean air to breathe in their living environment

European Respiratory Society clinical practice guidelines for the diagnosis of asthma in children aged 5-16 years.

Diagnosing asthma in children represents an important clinical challenge. There is no single gold standard test to confirm the diagnosis. Consequently, both over-, and under-diagnosis of asthma are frequent in children.A Task Force (TF) supported by the European Respiratory Society has developed these evidence-based clinical practice guidelines for the diagnosis of asthma in children aged 5-16 years using nine PICO (Population, Intervention, Comparator and Outcome) questions. The TF conducted systematic literature searches for all PICO questions and screened the outputs from these, including relevant full text articles. All TF members approved the final decision for inclusion of research papers. The TF assessed the quality of the evidence using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach.The TF then developed a diagnostic algorithm based on the critical appraisal of the PICO questions, preferences expressed by lay members and test availability. Proposed cut-offs were determined based on the best available evidence. The TF formulated recommendations using the GRADE Evidence to Decision framework.Based on the critical appraisal of the evidence and the Evidence to Decision Framework the TF recommends spirometry, bronchodilator reversibility testing and FeNO as first line diagnostic tests in children under investigation for asthma. The TF recommends against diagnosing asthma in children based on clinical history alone or following a single abnormal objective test. Finally, this guideline also proposes a set of research priorities to improve asthma diagnosis in children in the future

Diversity and distribution of subseafloor Thermococcales populations in diffuse hydrothermal vents at an active deep-sea volcano in the northeast Pacific Ocean

Author Posting. © American Geophysical Union, 2006. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 111 (2006): G04016, doi:10.1029/2005JG000097.The presence, diversity, and distribution of a key group of subseafloor archaea, the Thermococcales, was examined in multiple diffuse flow hydrothermal vents at Axial Seamount, an active deep-sea volcano located in the northeast Pacific Ocean. A polymerase chain reaction (PCR) approach was used to determine if this group of subseafloor indicator organisms showed any phylogenetic distribution that may indicate distinct subseafloor communities at vents with different physical and chemical characteristics. Targeted primers for the Thermococcales 16S rRNA (small subunit ribosomal RNA) gene and intergenic transcribed spacer (ITS) region were designed and applied to organisms filtered in-situ directly from a variety of diffuse flow vents. Thermococcales were amplified from 9 of 11 samples examined, and it was determined that the ITS region is a better phylogenetic marker than the 16S rRNA in defining consistent groups of closely related sequences. Results show a relationship between environmental clone distribution and source vent chemistry. The most highly diluted vents with elevated iron and alkalinity contained a distinct group of Thermococcales as defined by the ITS region, suggesting separate subseafloor Thermococcales populations at diffuse vents within the Axial caldera.This work was supported by Washington Sea Grant (NA76RG0119), National Science Foundation (OCE 9816491), NSF IGERT (DGE- 9870713), NASA Astrobiology Institute through the Carnegie Geophysical Institute, the NOAA/PMEL Vents Program, NOAA West Coast and Polar Undersea Research Center, and by the Joint Institute for the Study of the Atmosphere and Ocean under NOAA Cooperative Agreement No. NA117RJ1232

Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol:prospective observational cohort study

Objective: To characterise the clinical features of patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United Kingdom during the growth phase of the first wave of this outbreak who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study, and to explore risk factors associated with mortality in hospital. Design: Prospective observational cohort study with rapid data gathering and near real time analysis. Setting: 208 acute care hospitals in England, Wales, and Scotland between 6 February and 19 April 2020. A case report form developed by ISARIC and WHO was used to collect clinical data. A minimal follow-up time of two weeks (to 3 May 2020) allowed most patients to complete their hospital admission. Participants: 20 133 hospital inpatients with covid-19. Main outcome measures: Admission to critical care (high dependency unit or intensive care unit) and mortality in hospital. Results: The median age of patients admitted to hospital with covid-19, or with a diagnosis of covid-19 made in hospital, was 73 years (interquartile range 58-82, range 0-104). More men were admitted than women (men 60%, n=12 068; women 40%, n=8065). The median duration of symptoms before admission was 4 days (interquartile range 1-8). The commonest comorbidities were chronic cardiac disease (31%, 5469/17 702), uncomplicated diabetes (21%, 3650/17 599), non-asthmatic chronic pulmonary disease (18%, 3128/17 634), and chronic kidney disease (16%, 2830/17 506); 23% (4161/18 525) had no reported major comorbidity. Overall, 41% (8199/20 133) of patients were discharged alive, 26% (5165/20 133) died, and 34% (6769/20 133) continued to receive care at the reporting date. 17% (3001/18 183) required admission to high dependency or intensive care units; of these, 28% (826/3001) were discharged alive, 32% (958/3001) died, and 41% (1217/3001) continued to receive care at the reporting date. Of those receiving mechanical ventilation, 17% (276/1658) were discharged alive, 37% (618/1658) died, and 46% (764/1658) remained in hospital. Increasing age, male sex, and comorbidities including chronic cardiac disease, non-asthmatic chronic pulmonary disease, chronic kidney disease, liver disease and obesity were associated with higher mortality in hospital. Conclusions: ISARIC WHO CCP-UK is a large prospective cohort study of patients in hospital with covid-19. The study continues to enrol at the time of this report. In study participants, mortality was high, independent risk factors were increasing age, male sex, and chronic comorbidity, including obesity. This study has shown the importance of pandemic preparedness and the need to maintain readiness to launch research studies in response to outbreaks. Study registration: ISRCTN66726260

Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score.

OBJECTIVE: To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). DESIGN: Prospective observational cohort study. SETTING: International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium-ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020. PARTICIPANTS: Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. MAIN OUTCOME MEASURE: In-hospital mortality. RESULTS: 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). CONCLUSIONS: An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. STUDY REGISTRATION: ISRCTN66726260

Clinical characteristics of children and young people admitted to hospital with covid-19 in United Kingdom: prospective multicentre observational cohort study.

OBJECTIVE: To characterise the clinical features of children and young people admitted to hospital with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the UK and explore factors associated with admission to critical care, mortality, and development of multisystem inflammatory syndrome in children and adolescents temporarily related to coronavirus disease 2019 (covid-19) (MIS-C). DESIGN: Prospective observational cohort study with rapid data gathering and near real time analysis. SETTING: 260 hospitals in England, Wales, and Scotland between 17 January and 3 July 2020, with a minimum follow-up time of two weeks (to 17 July 2020). PARTICIPANTS: 651 children and young people aged less than 19 years admitted to 138 hospitals and enrolled into the International Severe Acute Respiratory and emergency Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK study with laboratory confirmed SARS-CoV-2. MAIN OUTCOME MEASURES: Admission to critical care (high dependency or intensive care), in-hospital mortality, or meeting the WHO preliminary case definition for MIS-C. RESULTS: Median age was 4.6 (interquartile range 0.3-13.7) years, 35% (225/651) were under 12 months old, and 56% (367/650) were male. 57% (330/576) were white, 12% (67/576) South Asian, and 10% (56/576) black. 42% (276/651) had at least one recorded comorbidity. A systemic mucocutaneous-enteric cluster of symptoms was identified, which encompassed the symptoms for the WHO MIS-C criteria. 18% (116/632) of children were admitted to critical care. On multivariable analysis, this was associated with age under 1 month (odds ratio 3.21, 95% confidence interval 1.36 to 7.66; P=0.008), age 10-14 years (3.23, 1.55 to 6.99; P=0.002), and black ethnicity (2.82, 1.41 to 5.57; P=0.003). Six (1%) of 627 patients died in hospital, all of whom had profound comorbidity. 11% (52/456) met the WHO MIS-C criteria, with the first patient developing symptoms in mid-March. Children meeting MIS-C criteria were older (median age 10.7 (8.3-14.1) v 1.6 (0.2-12.9) years; P<0.001) and more likely to be of non-white ethnicity (64% (29/45) v 42% (148/355); P=0.004). Children with MIS-C were five times more likely to be admitted to critical care (73% (38/52) v 15% (62/404); P<0.001). In addition to the WHO criteria, children with MIS-C were more likely to present with fatigue (51% (24/47) v 28% (86/302); P=0.004), headache (34% (16/47) v 10% (26/263); P<0.001), myalgia (34% (15/44) v 8% (21/270); P<0.001), sore throat (30% (14/47) v (12% (34/284); P=0.003), and lymphadenopathy (20% (9/46) v 3% (10/318); P<0.001) and to have a platelet count of less than 150 × 109/L (32% (16/50) v 11% (38/348); P<0.001) than children who did not have MIS-C. No deaths occurred in the MIS-C group. CONCLUSIONS: Children and young people have less severe acute covid-19 than adults. A systemic mucocutaneous-enteric symptom cluster was also identified in acute cases that shares features with MIS-C. This study provides additional evidence for refining the WHO MIS-C preliminary case definition. Children meeting the MIS-C criteria have different demographic and clinical features depending on whether they have acute SARS-CoV-2 infection (polymerase chain reaction positive) or are post-acute (antibody positive). STUDY REGISTRATION: ISRCTN66726260

The influence of age, gender and socio-economic status on multimorbidity patterns in primary care. first results from the multicare cohort study

Background: Multimorbidity is a phenomenon with high burden and high prevalence in the elderly. Our previous research has shown that multimorbidity can be divided into the multimorbidity patterns of 1) anxiety, depression, somatoform disorders (ADS) and pain, and 2) cardiovascular and metabolic disorders. However, it is not yet known, how these patterns are influenced by patient characteristics. The objective of this paper is to analyze the association of socio-demographic variables, and especially socio-economic status with multimorbidity in general and with each multimorbidity pattern. Methods: The MultiCare Cohort Study is a multicentre, prospective, observational cohort study of 3.189 multimorbid patients aged 65+ randomly selected from 158 GP practices. Data were collected in GP interviews and comprehensive patient interviews. Missing values have been imputed by hot deck imputation based on Gower distance in morbidity and other variables. The association of patient characteristics with the number of chronic conditions is analysed by multilevel mixed-effects linear regression analyses. Results: Multimorbidity in general is associated with age (+0.07 chronic conditions per year), gender (-0.27 conditions for female), education (-0.26 conditions for medium and -0.29 conditions for high level vs. low level) and income (-0.27 conditions per logarithmic unit). The pattern of cardiovascular and metabolic disorders shows comparable associations with a higher coefficient for gender (-1.29 conditions for female), while multimorbidity within the pattern of ADS and pain correlates with gender (+0.79 conditions for female), but not with age or socioeconomic status. Conclusions: Our study confirms that the morbidity load of multimorbid patients is associated with age, gender and the socioeconomic status of the patients, but there were no effects of living arrangements and marital status. We could also show that the influence of patient characteristics is dependent on the multimorbidity pattern concerned, i.e. there seem to be at least two types of elderly multimorbid patients. First, there are patients with mainly cardiovascular and metabolic disorders, who are more often male, have an older age and a lower socio-economic status. Second, there are patients mainly with ADS and pain-related morbidity, who are more often female and equally distributed across age and socio-economic groups

An image classification approach to analyze the suppression of plant immunity by the human pathogen <it>Salmonella</it> Typhimurium

<p>Abstract</p> <p>Background</p> <p>The enteric pathogen <it>Salmonella</it> is the causative agent of the majority of food-borne bacterial poisonings. Resent research revealed that colonization of plants by <it>Salmonella</it> is an active infection process. <it>Salmonella</it> changes the metabolism and adjust the plant host by suppressing the defense mechanisms. In this report we developed an automatic algorithm to quantify the symptoms caused by <it>Salmonella</it> infection on <it>Arabidopsis</it>.</p> <p>Results</p> <p>The algorithm is designed to attribute image pixels into one of the two classes: healthy and unhealthy. The task is solved in three steps. First, we perform segmentation to divide the image into foreground and background. In the second step, a support vector machine (SVM) is applied to predict the class of each pixel belonging to the foreground. And finally, we do refinement by a neighborhood-check in order to omit all falsely classified pixels from the second step. The developed algorithm was tested on infection with the non-pathogenic <it>E. coli</it> and the plant pathogen <it>Pseudomonas syringae</it> and used to study the interaction between plants and <it>Salmonella</it> wild type and T3SS mutants. We proved that T3SS mutants of <it>Salmonella</it> are unable to suppress the plant defenses. Results obtained through the automatic analyses were further verified on biochemical and transcriptome levels.</p> <p>Conclusion</p> <p>This report presents an automatic pixel-based classification method for detecting “unhealthy” regions in leaf images. The proposed method was compared to existing method and showed a higher accuracy. We used this algorithm to study the impact of the human pathogenic bacterium <it>Salmonella</it> Typhimurium on plants immune system. The comparison between wild type bacteria and T3SS mutants showed similarity in the infection process in animals and in plants. Plant epidemiology is only one possible application of the proposed algorithm, it can be easily extended to other detection tasks, which also rely on color information, or even extended to other features.</p

Clinical characteristics of children and young people hospitalised with covid-19 in the United Kingdom: prospective multicentre observational cohort study

Objective To characterise the clinical features of children and young people admitted to hospital with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the UK, and explore factors associated with admission to critical care, mortality, and development of multisystem inflammatory syndrome in children and adolescents temporarily related to covid-19 (MIS-C). Design Prospective observational cohort study with rapid data gathering and near real time analysis. Setting 260 acute care hospitals in England, Wales, and Scotland between 17th January and 5th June 2020, with a minimal follow-up time of two weeks (to 19th June 2020). Participants 451 children and young people aged less than 19 years admitted to 116 hospitals and enrolled into the International Severe Acute Respiratory and emergency Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK study with laboratory-confirmed SARS-CoV-2. Main Outcome Measures Admission to critical care (high dependency or intensive care), in-hospital mortality, or meeting the WHO preliminary case definition for MIS-C. Results Median age was 3.9 years [interquartile range (IQR) 0.3-12.9 years], 36% (162/451) were under 12 months old, and 57% (256/450) were male. 56% (224/401) were White, 12% (49/401) South Asian and 10% (40/401) Black. 43% (195/451) had at least one recorded comorbidity. A muco-enteric cluster of symptoms was identified, closely mirroring the WHO MIS-C criteria. 17% of children (72/431) were admitted to critical care. On multivariable analysis this was associated with age under one month odds ratio 5.05 (95% confidence interval 1.69 to 15.72, p=0.004), age 10 to 14 years OR 3.11 (1.21 to 8.55, p=0.022) and Black ethnicity OR 3.02 (1.30 to 6.84, p=0.008). Three young people died (0.7 %, 3/451) aged 16 to 19 years, all of whom had profound comorbidity. Twelve percent of children (36/303) met the WHO MIS-C criteria, with the first patient developing symptoms in mid-March. Those meeting MIS-C criteria were older, (median age 10.8 years ([IQR 8.4-14.1] vs 2.0 [0.2-12.6]), p [less than] 0.001) and more likely to be of non-White ethnicity (70% (23/33) vs 43% (101/237), p=0.005). Children with MIS-C were four times more likely to be admitted to critical care (61% (22/36) vs 15% (40/267, p [less than] 0.001). In addition to the WHO criteria, children with MIS-C were more likely to present with headache (45% (13/29) vs 11% (19/171), p [less than] 0.001), myalgia (39% (11/28) vs 7% (12/170), p [less than] 0.001), sore throat (37% (10/27) vs (13% (24/183, p = 0.004) and fatigue (57% (17/30) vs 31% (60/192), p =0.012) than children who did not and to have a platelet count of less than 150 x109/L (30% (10/33) vs 10% (24/232), p=0.004). Conclusions Our data confirms less severe covid-19 in children and young people than in adults and we provide additional evidence for refining the MIS-C case definition. The identification of a muco-enteric symptom cluster also raises the suggestion that MIS-C is the severe end of a spectrum of disease