Psoriasis, which presents as red, scaly patches on the body, is a common, autoimmune skin disease that affects 2 to 3 percent of the world population. To leverage recent molecular findings into the personalized treatment of psoriasis, we need a strategy that integrates clinical stratification with molecular phenotyping. In this study, we sought to stratify psoriasis patients by histological measurements of epidermal thickness, and to compare their molecular characterizations by gene expression, serum cytokines, and response to biologics. We obtained histological measures of epidermal thickness in a cohort of 609 psoriasis patients, and identified a mixture of two subpopulations—thick and thin plaque psoriasis—from which they were derived. This stratification was verified in a subcohort of 65 patients from a previously published study with significant differences in inflammatory cell infiltrates in the psoriatic skin. Thick and thin plaque psoriasis shared 84.8% of the meta-analysis-derived psoriasis transcriptome, but a stronger dysregulation of the meta-analysis-derived psoriasis transcriptome was seen in thick plaque psoriasis on microarray. RT-PCR revealed that gene expression in thick and thin plaque psoriasis was different not only within psoriatic lesional skin but also in peripheral non-lesional skin. Additionally, differences in circulating cytokines and their changes in response to biologic treatments were found between the two subgroups. All together, we were able to integrate histological stratification with molecular phenotyping as a way of exploring clinical phenotypes with different expression levels of the psoriasis transcriptome and circulating cytokines.

Background Delayed vaccination increases the time infants are at risk for acquiring vaccine-preventable diseases. Factors associated with incomplete vaccination are relatively well characterized in resource-limited settings; however, few studies have assessed immunization timeliness. Methods We conducted a prospective cohort study examining Diphtheria-Tetanus-Pertussis (DTP) vaccination timing among newborns enrolled in a Neonatal Vitamin A supplementation trial (NEOVITA) conducted in urban Dar es Salaam ( n = 11,189) and rural Morogoro Region ( n = 19,767), Tanzania. We used log-binomial models to assess the relationship of demographic, socioeconomic, healthcare access, and birth characteristics with late or incomplete DTP1 and DTP3 immunization. Results The proportion of infants with either delayed or incomplete vaccination was similar in Dar es Salaam (DTP1 11.5% and DTP3 16.0%) and Morogoro (DTP1 9.2% and DTP3 17.3%); however, the determinants of delayed or incomplete vaccination as well as their magnitude of association differed by setting. Both maternal and paternal education were more strongly associated with vaccination status in rural Morogoro region as compared to Dar es Salaam ( p -values for heterogeneity < 0.05). Infants in Morogoro who had fathers and mothers with no education had 36% (95% CI: 22–52%) and 22% (95% CI: 10–34%) increased risk of delayed or incomplete DTP3 vaccination as compared to those with primary school education, respectively. In Dar es Salaam, mothers who attended their first antenatal care (ANC) visit in the 3rd trimester had 1.55 (95% CI: 1.36–1.78) times the risk of delayed or not received vaccination as compared to those with a 2nd trimester booking, while there was no relationship in Morogoro. In rural Morogoro, infants born at home had 17% (95% CI: 8–27%) increased risk for delayed or no receipt of DTP3 vaccination. In both settings, younger maternal age and poorer households were at increased risk for delayed or incomplete vaccination. Conclusion We found some risk factors for delayed and incomplete vaccination were shared between urban and rural Tanzania; however, we found several context-specific risk factors as well as determinants that differed in their magnitude of risk between contexts. Immunization programs should be tailored to address context-specific barriers and enablers to improve timely and complete vaccination. Electronic supplementary material The online version of this article (10.1186/s12879-019-3828-3) contains supplementary material, which is available to authorized users.

Since the onset of the COVID-19 pandemic, countless disease prediction models have emerged, shaping the focus of news media, policymakers, and broader society. We reviewed the accuracy of forecasts made during prior twenty-first century epidemics, namely SARS, H1N1, and Ebola. We found that while disease prediction models were relatively nascent as a research focus during SARS and H1N1, for Ebola, numerous such forecasts were published. We found that forecasts of deaths for Ebola were often far from the eventual reality, with a strong tendency to over predict. Given the societal prominence of these models, it is crucial that their uncertainty be communicated. Otherwise, we will be unaware if we are being falsely lulled into complacency or unjustifiably shocked into action.