Objective To use a quantitative approach to evaluate the literature for quantity, quality, and consistency of studies of maternal and infant characteristics in association with breastfeeding initiation and continuation, and to conduct a meta-analysis to produce summary relative risks (RRs) for selected factors.Study design A systematic review using PubMed and CINAHL through March 2016 was conducted to identify relevant observational studies in developed nations, reporting a measure of risk for 1 or more of 6 quantitatively derived, high impact factors in relation to either breastfeeding initiation or continuation. One author abstracted data using a predesigned database, which was reviewed by a second independent author; data evaluation and interpretation included all co-authors. These factors were summarized using standard metaanalysis techniques. ResultsSix high impact factors were identified (smoking [39 papers], mode of delivery [47 papers], parity [31 papers], dyad separation [17 papers], maternal education [62 papers], and maternal breastfeeding education [32 papers]). Summary RR from random-effects models for breastfeeding initiation were highest for high vs low maternal education (RR 2.28 [95% CI 1.92-2.70]), dyad connection vs not (RR 2.01 [95% CI 1.38-2.92]), and maternal nonsmoking vs smoking (RR = 1.76 [95% CI 1.59-1.95]); results were similar for breastfeeding continuation.Conclusions Despite methodological heterogeneity across studies, relatively consistent results were observed for these perinatally identifiable factors associated with breastfeeding initiation and continuation, which may be informative in developing targeted interventions to provide education and support for successful breastfeeding in more families. (J Pediatr 2018;203:190-6). P-h P value for heterogeneity RR Relative risk SES Socioeconomic status WIC Women, infants, and children From the

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Background: Tumors of the metastatic colorectal cancer (mCRC) patients that are wildtype (WT) for KRAS or NRAS mutations respond more favorably to anti-epidermal growth factor receptor (EGFR) treatments. Treatment guidelines now recommend that all mCRC patients have WT KRAS and NRAS tumor status confirmed prior to initiating anti-EGFR therapy. Evidence also suggests that BRAF mutations may predict lack of response to anti-EGFR therapy. As such, there is now a need for comprehensive data on the prevalence of KRAS, NRAS, and BRAF mutations among patients with mCRC.Methods: A systematic literature review was conducted among studies that described the prevalence of KRAS, NRAS, and BRAF gene mutations in mCRC patients. Observational cohort studies and standard of care arm of randomized clinical trials were included. Random effects meta-analysis models were used to create summary prevalence estimates for each of the mutation types. Subgroup analyses were also conducted to identify potential sources of heterogeneity. Exploratory analyses of overall and progression-free survival by mutation status were also conducted. Results:This systematic review and meta-analysis included 275 studies comprising 77,104 mCRC patients. The summary prevalence estimate was 35.9% for KRAS mutations, 7.1% for BRAF mutations, and 4.1% for NRAS mutations. Female patients had significantly more KRAS and BRAF mutations than males, and significant variation by study location was observed for both KRAS and BRAF mutation prevalence. Overall survival was significantly decreased for patients with KRAS, BRAF, and NRAS mutations compared to those with WT tumors. Progression-free survival was also significantly decreased among patients with KRAS and BRAF mutations.Conclusions: KRAS, NRAS, and BRAF mutation statuses in patients with mCRC are important predictors of treatment success and may also have prognostic value. In this paper we present the first systematic and comprehensive literature review and meta-analysis of the prevalence of KRAS, BRAF, and NRAS mutations and demonstrate the prognostic impact of mutation status on survival.

BackgroundRespiratory syncytial virus (RSV) is an established cause of serious lower respiratory disease in infants, elderly and high-risk populations. The OUTSMART surveillance program aims to characterize patient populations and currently circulating RSV strains, and monitor temporal and geographic evolution of RSV F and G proteins in the U.S.MethodsThe OUTSMART 2016–17 study collected RSV-positive samples from 25 RSVAlert® laboratories from 4 U.S. regions and Puerto Rico during November 2016 through March 2017. Frequencies of A and B subtypes and genotypes were determined for several demographic and geographic variables. To gauge the representativeness of the OUTSMART patients, results were compared to discharge data from the NEDS and NIS databases.ResultsA total of 1,041 RSV-positive samples with associated demographic data were obtained and the RSV F gene and second variable region of the G gene were sequenced. The majority of samples (76.0%) came from children under 2 years old: <1 year (48.4%), 1–2 years (27.6%). The OUTSMART patient sample was similar to NEDS and NIS for age, gender, and geographic location. Both OUTSMART and national RSV cases peaked in January. Of OUTSMART samples, 45.3% were subtype A, 53.7% were subtype B and 1.0% were mixed A and B. The percentage of RSV B cases increased with increasing age. Hospitalization (length of hospital stay, LOS, >24 hrs) occurred in 29.0% of patients of which 52.0% had RSV B. Outpatients (LOS <24 hrs) were 64.4% of total of which 73.3% were diagnosed in the ER and discharged, while only 6% were diagnosed in other outpatient settings.ConclusionsThe OUTSMART 2016–17 study was representative of the U.S. RSV experience. Geographic and temporal information from the RSV surveillance program will be used to establish a molecular baseline of RSV F and G sequence variability and to help inform development of novel agents for RSV prophylaxis and treatment.

Coaggregation between bacterial species is integral to multi-species biofilm development. Difficulties in rapidly and reproducibly identifying and quantifying coaggregation have limited mechanistic studies. This paper demonstrates two complementary quantitative methods to screen for coaggregation. The first approach uses a microplate-based high-throughput approach and the other uses a FlowCam(™) device. The microplate-based approach enables rapid detection of coaggregation between candidate coaggregating pairs of strains simultaneously while controlling for variation between replicates. The FlowCam(™) approach allows for in-depth analysis of the rates of coaggregation and size of aggregates formed.