Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Proximity to overhead power lines and childhood leukaemia: an international pooled analysis

© 2018, Cancer Research UK. Background: Although studies have consistently found an association between childhood leukaemia risk and magnetic fields, the associations between childhood leukaemia and distance to overhead power lines have been inconsistent. We pooled data from multiple studies to assess the association with distance and evaluate whether it is due to magnetic fields or other factors associated with distance from lines. Methods: We present a pooled analysis combining individual-level data (29,049 cases and 68,231 controls) from 11 record-based studies. Results: There was no material association between childhood leukaemia and distance to nearest overhead power line of any voltage. Among children living < 50 m from 200 + kV power lines, the adjusted odds ratio for childhood leukaemia was 1.33 (95% CI: 0.92–1.93). The odds ratio was higher among children diagnosed before age 5 years. There was no association with calculated magnetic fields. Odds ratios remained unchanged with adjustment for potential confounders. Conclusions: In this first comprehensive pooled analysis of childhood leukaemia and distance to power lines, we found a small and imprecise risk for residences < 50 m of 200 + kV lines that was not explained by high magnetic fields. Reasons for the increased risk, found in this and many other studies, remains to be elucidated

Kuluttajamarkkinoinnin tehostaminen blogin avulla

Opinnäytetyön tavoitteena oli selvittää, kuinka kuluttajille kohdistettua markkinointia voidaan tehostaa blogin avulla. Markkinoinnin tehostaminen rajattiin käsittelemään tekijöitä, joilla kuluttajia saadaan lukemaan blogia sekä oikeanlaista sisältöä tuottamalla sitoutumaan aktiivisiksi blogin lukijoiksi. Työ toteutettiin toimeksiantona keittiötarvikkeita maahantuovalle RNTM Trading Oy:lle, jolla on myös GN-Store –niminen verkkokauppa. Yritys käyttää markkinoinnissaan blogia, jonka edistämiseen opinnäytetyön tutkimus kohdistui. Tutkimus oli tutkimusotteeltaan laadullinen ja aineisto kerättiin teemahaastattelulla. Viisi haastateltavaa olivat ammatiltaan blogin kirjoittajia sekä sisällöntuottajia. Haastattelut nauhoitettiin ja litteroitiin, jonka jälkeen aineisto analysoitiin käyttäen teemoittelua. Tutkimuksen tuloksista näkyi, että blogin markkinoimiseksi tehokkainta on näkyä Instagramissa ja Facebookissa, samalla selvittäen omaa kohderyhmäänsä. Monipuolisen ja kanavakohtaisesti erilaisen sisällön jakaminen houkuttelee lukijoita blogiin. Lukijoiden sitouttamiseksi blogiin, kirjoittajan on julkaistava artikkeleita säännöllisesti ja ajankohtaisesti. Julkaisuissa olevilla laadukkailla kirjoituksilla ja kuvilla yhdistellään luovuutta ja uskottavuutta sekä herätetään lukijassa tunteita, oivalluksia ja luotettavuutta kirjoittajaa kohtaan. Kuluttajille kohdistettua markkinointia tehostaakseen yrityksen suositellaan laativan blogin sisältömarkkinointia edistävä sisältöstrategia. Strategian tärkeimmät osat ovat blogiartikkeleiden ja niiden mainontaa käsittelevä aikatauluttaminen, markkinoinnin tavoitteiden asettaminen sekä mittaaminen. Sisältömarkkinoinnin ohella yritys hakukoneoptimoi blogisivustonsa sekä järjestää asiakkaan palvelupolun sosiaalisesta mediasta blogiin ja verkkokauppaan

Epidemiological studies of natural sources of radiation and childhood cancer: current challenges and future perspectives

Empirical estimation of cancer risks in children associated with low-dose ionizing radiation (<100 mSv) remains a challenge. The main reason is that the required combination of large sample sizes with accurate and comprehensive exposure assessment is difficult to achieve. An international scientific workshop "Childhood cancer and background radiation" organised by the Institute of Social and Preventive Medicine of the University of Bern brought together researchers in this field to evaluate how epidemiological studies on background radiation and childhood cancer can best improve understanding of the effects of low-dose ionising radiation. This review summarises and evaluates the findings of the existing studies in the light of their methodological differences, identifies key limitations and challenges and proposes ways forward. Large childhood cancer registries, such as those in Great Britain, France and Germany, now allow the conducting of studies that should have sufficient statistical power to detect the effects predicted by standard risk models. Nevertheless, larger studies or pooled studies will be needed to investigate disease subgroups. The main challenge is to accurately assess children's individual exposure to radiation from natural sources and from other sources, as well as potentially confounding non-radiation exposures, in such large study populations. For this, the study groups should learn from each other to improve exposure estimation and develop new ways to validate exposure models with personal dosimetry

The Simple 10-Item Predicting Asthma Risk in Children Tool to Predict Childhood Asthma—An External Validation

Background: External validation of prediction models is important to assess generalizability to other populations than the one used for model development. The Predicting Asthma Risk in Children (PARC) tool, developed in the Leicestershire Respiratory Cohort (LRC), uses information on preschool respiratory symptoms to predict asthma at school age. Objective: We performed an external validation of PARC using the Avon Longitudinal Study of Parents and Children (ALSPAC). Methods: We defined inclusion criteria, prediction score items at baseline and asthma at follow-up in ALSPAC to match those used in LRC using information from parent-reported questionnaires. We assessed performance of PARC by calculating sensitivity, specificity, predictive values, likelihood ratios, area under the curve (AUC), Brier score and Nagelkerke's R2. Sensitivity analyses varied inclusion criteria, scoring items, and outcomes. Results: The validation population included 2690 children with preschool respiratory symptoms of whom 373 (14%) had asthma at school age. Discriminative performance of PARC was similar in ALSPAC (AUC = 0.77, Brier score 0.13) as in LRC (0.78, 0.22). The score cutoff of 4 showed the highest sum of sensitivity (69%) and specificity (76%) and positive and negative likelihood ratios of 2.87 and 0.41, respectively. Changes to inclusion criteria, scoring items, or outcome definitions barely altered the prediction performance. Conclusions: Performing equally well in the validation cohort as in the development cohort, PARC is a valid tool for predicting asthma in population-based cohorts. Its use in clinical practice is ready to be tested