e-related antigenic epidemiology of MenB is thus similar in both groups. One of the first on-field applications of gMATS and MenDeVAR identifies their major advantage in their accessibility and in the possibility of dynamic data implementation that must be pursued continuously in the future.
  Systematically review the evidence on the association between active and passive tobacco smoking and invasive meningococcal disease (IMD) in adolescents and young adults aged 15-to-24-years.
 
  Electronic searches were conducted in Ovid MEDLINE, EMBASE, and Web of Science to June 2020. Reference lists were hand-searched. Two independent reviewers screened articles for eligibility. Risk of bias was assessed using an adapted Risk of Bias in Non-Randomised Studies - of Interventions tool. Meta-analyses were conducted using random-effects models.
 
  Of 312 records identified, 13 studies were included. Five studies provided data on the association between active smoking and IMD in the target age group; pooled odds ratio (OR) 1.45 (95% CI 0.93-2.26). The overall OR, including eight studies with a wider participant age range, was 1.45 (95% CI 1.12-1.88). For passive smoking, the equivalent ORs were 1.56 (95% CI 1.09-2.25) and 1.30 (95% CI 1.06-1.59) respectively. All studies were at high risk of bias.
 
  Active and passive smoking may be associated with IMD in adolescents and young adults. Since active smoking has also been linked to meningococcal carriage, and passive smoking to IMD in young children, smoking cessation should be encouraged to reduce transmission and IMD risk in all ages.
 Active and passive smoking may be associated with IMD in adolescents and young adults. Since active smoking has also been linked to meningococcal carriage, and passive smoking to IMD in young children, smoking cessation should be encouraged to reduce transmission and IMD risk in all ages.
  To define the best combination of biomarkers for the diagnosis of infection and sepsis in the emergency room.
 
  In this prospective study, consecutive patients with a suspicion of infection in the emergency room were included. Eighteen different biomarkers measured in plasma, and twelve biomarkers measured on monocytes, neutrophils, B and T-lymphocytes were studied and the best combinations determined by a gradient tree boosting approach.
 
  Overall, 291 patients were included and analysed, 148 with bacterial infection, and 47 with viral infection. The best biomarker combination which first allowed the diagnosis of bacterial infection, included HLA-DR (human leukocyte antigen DR) on monocytes, MerTk (Myeloid-epithelial-reproductive tyrosine kinase) on neutrophils and plasma metaloproteinase-8 (MMP8) with an area under the curve (AUC) = 0.94 [95% confidence interval (IC95) 0.91;0.97]. Among patients in whom a bacterial infection was excluded, the combination of CD64 expression, and CD24 on neutrophils and CX3CR1 on monocytes ended to an AUC = 0.98 [0.96;1] to define those with a viral infection.
 
  In a convenient cohort of patients admitted with a suspicion of infection, two different combinations of plasma and cell surface biomarkers were performant to identify bacterial and viral infection.
 In a convenient cohort of patients admitted with a suspicion of infection, two different combinations of plasma and cell surface biomarkers were performant to identify bacterial and viral infection.
  Acute febrile illnesses (AFIs) represent a major disease burden globally; however, the paucity of reliable, rapid point-of-care testing makes their diagnosis difficult. A simple tool for distinguishing bacterial versus non-bacterial infections would radically improve patient management and reduce indiscriminate antibiotic use. Diagnostic tests based on host biomarkers can play an important role here, and a target product profile (TPP) was developed to guide development.
 
  To qualitatively evaluate host biomarkers that can distinguish bacterial from non-bacterial causes of AFI.
 
  The PubMed database was systematically searched for relevant studies published between 2015 and 2019.
 
  Studies comparing diagnostic performances of host biomarkers in patients with bacterial versus non-bacterial infections were included.
 
  Studies involving human participants and/or human samples were included.
 
  We collected information following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline (HNL). Few new biomarkers are in the pipeline; however, some RNA signatures show promise. Further high-quality studies are needed to confirm these findings.
 Most recently assessed biomarkers represent well-known biomarkers, e.g. C-reactive protein and procalcitonin. Some protein biomarkers with the highest reported performances include a combined biomarker signature (CRP, IP-10, and TRAIL) and human neutrophil lipocalin (HNL). Few new biomarkers are in the pipeline; however, some RNA signatures show promise.  https://www.selleckchem.com/products/sulfopin.html  Further high-quality studies are needed to confirm these findings.
  The HPV vaccine has been licensed in mainland China since 2017. This study aimed to assess the epidemiological characteristics of HPV genotypes in the pre-vaccine era in China.
 
  We conducted a multicentric population-based study nested in the largest health clinic chain in China. Between January 1, 2017 and December 31, 2017, 427,401women aged 20 years or older with polymerase chain reaction-based HPV genotyping tests were included in the study. The cervicovaginal infection of 14 high-risk HPV genotypes and 9 low-risk genotypes was assessed using adjusted prevalence, multivariable logistic regression, cluster analysis, and heatmap.
 
  HPV prevalence was 15.0% (95% confidence interval [CI] 14.1-15.9%) in China, with high- and low-risk genotypes being 12.1% (95%CI 11.4-12.7%) and 5.2% (95%CI 4.8-5.7%), respectively. The prevalence of HPV genotypes corresponding to bivalent, quadrivalent, and nonavalent vaccines were 2.1%, 2.4%, and 8.3%, respectively, whereas the prevalence of non-vaccine high-risk genotypes was 5.7%. The most common high-risk genotypes were HPV-52 (3.5%), HPV-58 (2.1%), and HPV-16 (1.6%), and the prevalence of HPV-18 (0.6%), HPV-6 (0.1%), and HPV-11 (0.2%) were relatively low. Infection with HPV genotypes differed significantly across age groups and geographic locations.
 
  HPV prevalence was high in the pre-vaccine era in China, and a population-based HPV vaccination strategy is needed in the future.
 HPV prevalence was high in the pre-vaccine era in China, and a population-based HPV vaccination strategy is needed in the future.