urther investigation.This trial was registered at clinicaltrials.gov as NCT02385149.
 In middle-aged overweight and obese adults, a 12-wk WGW intervention increased the relative abundance of a number of bacterial taxa from the family Ruminococcaceae and increased predicted fermentation pathways when compared with an RW intervention. Potential protective health effects of replacement of RW by WGW on metabolic organs, such as the liver, via modulation of the microbiota, deserve further investigation.This trial was registered at clinicaltrials.gov as NCT02385149.A total of 2,184 pigs (DNA 600 × PIC L42) were used to evaluate the effects of weaning age and antibiotic (AB) use on pig performance from weaning to marketing in a commercial production system. Experimental treatments were arranged in a 3 × 2 factorial with main effects of weaning age (18.5, 21.5, or 24.5 d of age) and with the use of ABs or an antibiotic-free (NAE) program. At birth, pigs were ear tagged, and the date of birth and sex recorded. Pigs were weaned from a 4,000-sow farm over four consecutive weeks. Four weaning batches (one per week) of 546 pigs were used. Each weaning batch had one-third of pigs of each weaning age. Pigs were placed in pens by weaning age and then randomly assigned to an AB or NAE program. There were 14 replicate pens per treatment and 26 pigs per pen (13 barrows and 13 gilts). Pigs allocated to the AB program were fed a diet containing 441 mg/kg chlortetracycline (CTC) from day 8 to 21 postweaning. They were also administered 22 mg/kg of body weight (BW) of CTC via drinking w but the AB program did not (P = 0.238). The weight sold (at 197 d of age) per pig weaned was increased (linear, P = 0.050) by increasing weaning age and by using AB in feed and water (P = 0.019). In summary, increasing weaning age linearly improved most of the pig performance criteria and relatively the short-term use of ABs reduced mortality and removals with both factors contributing to increased weight sold per pig weaned.
  Previous studies showed that the epidemic of carbapenem-resistant Klebsiella pneumoniae (CR-KP) observed in Italy since 2010 was sustained mostly by strains of clonal group (CG) 258 producing KPC-type carbapenemases. In the framework of the National Antibiotic-Resistance Surveillance (AR-ISS), a countrywide survey was conducted in 2016 to explore the evolution of the phenotypic and genotypic characteristics of CR-KP isolates.
 
  From March to July 2016, hospital laboratories participating in AR-ISS were requested to provide consecutive, non-duplicated CR-KP (meropenem and/or imipenem MIC >1 mg/L) from invasive infections.  https://www.selleckchem.com/products/purmorphamine.html  Antibiotic susceptibility was determined according to EUCAST recommendations. A WGS approach was adopted to characterize the isolates by investigating phylogeny, resistome and virulome.
 
  Twenty-four laboratories provided 157 CR-KP isolates, of which 156 were confirmed as K. pneumoniae sensu stricto by WGS and found to carry at least one carbapenemase-encoding gene, corresponding in most cases (96.1%) to blaKPC. MLST- and SNP-based phylogeny revealed that 87.8% of the isolates clustered in four major lineages CG258 (47.4%), with ST512 as the most common clone, CG307 (19.9%), ST101 (15.4%) and ST395 (5.1%). A close association was identified between lineages and antibiotic resistance phenotypes and genotypes, virulence traits and capsular types. Colistin resistance, mainly associated with mgrB mutations, was common in all major lineages except ST395.
 
  This WGS-based survey showed that, although CG258 remained the most common CR-KP lineage in Italy, a polyclonal population has emerged with the spread of the new high-risk lineages CG307, ST101 and ST395, while KPC remained the most common carbapenemase.
 This WGS-based survey showed that, although CG258 remained the most common CR-KP lineage in Italy, a polyclonal population has emerged with the spread of the new high-risk lineages CG307, ST101 and ST395, while KPC remained the most common carbapenemase.
  Breast milk is a complex biofluid that provides nutrients and bioactive agents, including bacteria, for the development of the infant gut microbiota. However, the impact of maternal diet and other factors, such as mode of delivery and antibiotic exposure, on the breast milk microbiota has yet to be understood.
 
  This study aimed to examine the association between maternal diet and breast milk microbiota and to ascertain the potential role of mode of delivery and antibiotic exposure.
 
  In a cross-sectional study of the MAMI cohort, breast milk microbiota profiling was assessed in 120 samples from healthy mothers by 16S rRNA gene sequencing. Maternal dietary information was recorded through an FFQ, and clinical characteristics, including mode of delivery, antibiotic exposure, and exclusive breastfeeding, were collected.
 
  Maternal diet was grouped into 2 clusters Cluster I (high intake of plant protein, fiber, and carbohydrates), and Cluster II (high intake of animal protein and lipids). Breast milk microbiotnt microbiota development and contributes to infant health outcomes in the short and long term.This trial was registered at clinicaltrials.gov as NCT03552939.
 Maternal diet shapes the composition and diversity of breast milk microbiota, with the most important contributions coming from dietary fiber and both plant and animal protein intakes. The relation between the maternal diet and the milk microbiota needs further research because it has a key impact on infant microbiota development and contributes to infant health outcomes in the short and long term.This trial was registered at clinicaltrials.gov as NCT03552939.
  The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation.
 
  A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands.
 
  Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals.