Nutritional status of Tajik children and women: transition towards a double burden of malnutrition

The double burden of malnutrition, an emerging concern in developing countries, can exist at various levels: individual, household, and population. Here, we explore the nutritional status of Tajik women (15-49 years) and children (5-59 months) focusing on overweight/obesity along with undernutrition (underweight, stunting, and micronutrient deficiencies). For this, nutritional markers (haemoglobin (Hb), transferrin receptor (TfR), serum ferritin (Sf), retinol binding protein (RBP), vitamin D, serum folate, and urinary iodine), height, and weight were assessed from 2,145 women and 2,149 children. Dietary intake, weaning, and breastfeeding habits were recorded using a 24-hr recall and a questionnaire. Overweight (24.5%) and obesity (13.0%) are increasing among Tajik women compared with previous national surveys (2003 and 2009). Prevalence of iron deficiency and anaemia was 38.0% and 25.8%, respectively; 64.5% of women were iodine deficient, 46.5% vitamin A deficient, and 20.5% had insufficient folate levels. Women in rural areas had significantly lower iron status and body mass index and higher iodine intake compared with urban areas; 20.9% of children were stunted, 2.8% wasted, 6.2% underweight, 52.4% iron deficient, and 25.8% anaemic; all more prominent in rural areas. Dietary diversity was higher among urban women. Intraindividual or household double burden was not seen. In summary, double burden of malnutrition constituted an increase in overweight among women, especially in urban areas, and persisting levels of undernutrition (stunting, iron, and vitamin A deficiency), predominately in rural areas. A holistic, innovative approach is needed to improve infant and young children feeding and advise mothers to maintain an adequate diet

Handrub Consumption Mirrors Hand Hygiene Compliance

We assessed handrub consumption as a surrogate marker for hand hygiene compliance from 2007 to 2014. Handrub consumption varied substantially between departments but correlated in a mixed effects regression model with the number of patient-days and the observed hand hygiene compliance. Handrub consumption may supplement traditional hand hygiene observations. Infect. Control Hosp. Epidemiol. 2016;1-4

On the relevance of technical variation due to building pools in microarray experiments

Background Pooled samples are frequently used in experiments measuring gene expression. In this method, RNA from different individuals sharing the same experimental conditions and explanatory variables is blended and their concentrations are jointly measured. As a matter of principle, individuals are represented in equal shares in each pool. However, some degree of disproportionality may arise from the limits of technical precision. As a consequence a special kind of technical error occurs, which can be modelled by a respective variance component. Previously published theory - allowing for variable pool sizes - has been applied to four microarray gene expression data sets from different species in order to assess the practical relevance of this type of technical error in terms of significance and size of this variance component. Results The number of transcripts with a significant variance component due to imperfect blending was found to be 4329 (23 %) in mouse data and 7093 (49 %) in honey bees, but only 6 in rats and none whatsoever in human data. These results correspond to a false discovery rate of 5 % in each data set. The number of transcripts found to be differentially expressed between treatments was always higher when the blending error variance was neglected. Simulations clearly indicated overly-optimistic (anti-conservative) test results in terms of false discovery rates whenever this source of variability was not represented in the model. Conclusions Imperfect equality of shares when blending RNA from different individuals into joint pools of variable size is a source of technical variation with relevance for experimental design, practice at the laboratory bench and data analysis. Its potentially adverse effects, incorrect identification of differentially expressed transcripts and overly-optimistic significance tests, can be fully avoided, however, by the sound application of recently established theory and models for data analysis

Extending outbreak investigation with machine learning and graph theory: Benefits of new tools with application to a nosocomial outbreak of a multidrug-resistant organism.

OBJECTIVE From January 1, 2018, until July 31, 2020, our hospital network experienced an outbreak of vancomycin-resistant enterococci (VRE). The goal of our study was to improve existing processes by applying machine-learning and graph-theoretical methods to a nosocomial outbreak investigation. METHODS We assembled medical records generated during the first 2 years of the outbreak period (January 2018 through December 2019). We identified risk factors for VRE colonization using standard statistical methods, and we extended these with a decision-tree machine-learning approach. We then elicited possible transmission pathways by detecting commonalities between VRE cases using a graph theoretical network analysis approach. RESULTS We compared 560 VRE patients to 86,684 controls. Logistic models revealed predictors of VRE colonization as age (aOR, 1.4 (per 10 years), with 95% confidence interval [CI], 1.3-1.5; P < .001), ICU admission during stay (aOR, 1.5; 95% CI, 1.2-1.9; P < .001), Charlson comorbidity score (aOR, 1.1; 95% CI, 1.1-1.2; P < .001), the number of different prescribed antibiotics (aOR, 1.6; 95% CI, 1.5-1.7; P < .001), and the number of rooms the patient stayed in during their hospitalization(s) (aOR, 1.1; 95% CI, 1.1-1.2; P < .001). The decision-tree machine-learning method confirmed these findings. Graph network analysis established 3 main pathways by which the VRE cases were connected: healthcare personnel, medical devices, and patient rooms. CONCLUSIONS We identified risk factors for being a VRE carrier, along with 3 important links with VRE (healthcare personnel, medical devices, patient rooms). Data science is likely to provide a better understanding of outbreaks, but interpretations require data maturity, and potential confounding factors must be considered

Nosocomial outbreak of vancomycin-resistant Enterococcus faecium (VRE) ST796, Switzerland, 2017 to 2020

A large clonal outbreak caused by vancomycin-resistant Enterococcus faecium (VRE) affected the Bern University Hospital group from the end of December 2017 until July 2020. We describe the characteristics of the outbreak and the bundle of infection prevention and control (IPC) measures implemented. The outbreak was first recognised when two concomitant cases of VRE bloodstream infection were identified on the oncology ward. During 32 months, 518 patients in the 1,300-bed hospital group were identified as vanB VRE carriers. Eighteen (3.5%) patients developed an invasive infection, of whom seven had bacteraemia. In 2018, a subset of 328 isolates were analysed by whole genome sequencing, 312 of which were identified as sequence type (ST) 796. The initial IPC measures were implemented with a focus on the affected wards. However, in June 2018, ST796 caused another increase in cases, and the management strategy was intensified and escalated to a hospital-wide level. The clinical impact of this large nosocomial VRE outbreak with the emergent clone ST796 was modest. A hospital-wide approach with a multimodal IPC bundle was successful against this highly transmissible strain

Nosocomial outbreak of vancomycin-resistant Enterococcus faecium (VRE) ST796, Switzerland, 2017 to 2020

A large clonal outbreak caused by vancomycin-resistant Enterococcus faecium (VRE) affected the Bern University Hospital group from the end of December 2017 until July 2020. We describe the characteristics of the outbreak and the bundle of infection prevention and control (IPC) measures implemented. The outbreak was first recognised when two concomitant cases of VRE bloodstream infection were identified on the oncology ward. During 32 months, 518 patients in the 1,300-bed hospital group were identified as vanB VRE carriers. Eighteen (3.5%) patients developed an invasive infection, of whom seven had bacteraemia. In 2018, a subset of 328 isolates were analysed by whole genome sequencing, 312 of which were identified as sequence type (ST) 796. The initial IPC measures were implemented with a focus on the affected wards. However, in June 2018, ST796 caused another increase in cases, and the management strategy was intensified and escalated to a hospital-wide level. The clinical impact of this large nosocomial VRE outbreak with the emergent clone ST796 was modest. A hospital-wide approach with a multimodal IPC bundle was successful against this highly transmissible strain

Witches, pagans and historians:an extended review of Max Dashu, <i>Witches and Pagans: Women in European Folk Religion, 700-1000 </i>

Additional file 4: Table S4. DEGs associated with the HB sources but not with the behavior. A modified t-test was performed on the log-transformed transcription ratios gained from 82 hybridizations. Oligo Ids, Gene Ids, and Comments are quoted from the UIUC Honey bee oligo 13 K v1 annotation file (May 2007)

Mixing of Honeybees with Different Genotypes Affects Individual Worker Behavior and Transcription of Genes in the Neuronal Substrate

Division of labor in social insects has made the evolution of collective traits possible that cannot be achieved by individuals alone. Differences in behavioral responses produce variation in engagement in behavioral tasks, which as a consequence, generates a division of labor. We still have little understanding of the genetic components influencing these behaviors, although several candidate genomic regions and genes influencing individual behavior have been identified. Here, we report that mixing of worker honeybees with different genotypes influences the expression of individual worker behaviors and the transcription of genes in the neuronal substrate. These indirect genetic effects arise in a colony because numerous interactions between workers produce interacting phenotypes and genotypes across organisms. We studied hygienic behavior of honeybee workers, which involves the cleaning of diseased brood cells in the colony. We mixed ∼500 newly emerged honeybee workers with genotypes of preferred Low (L) and High (H) hygienic behaviors. The L/H genotypic mixing affected the behavioral engagement of L worker bees in a hygienic task, the cooperation among workers in uncapping single brood cells, and switching between hygienic tasks. We found no evidence that recruiting and task-related stimuli are the primary source of the indirect genetic effects on behavior. We suggested that behavioral responsiveness of L bees was affected by genotypic mixing and found evidence for changes in the brain in terms of 943 differently expressed genes. The functional categories of cell adhesion, cellular component organization, anatomical structure development, protein localization, developmental growth and cell morphogenesis were overrepresented in this set of 943 genes, suggesting that indirect genetic effects can play a role in modulating and modifying the neuronal substrate. Our results suggest that genotypes of social partners affect the behavioral responsiveness and the neuronal substrate of individual workers, indicating a complex genetic architecture underlying the expression of behavior