Unpaid work and access to science professions

Unpaid work in the sciences is advocated as an entry route into scientific careers. We compared the success of UK science graduates who took paid or unpaid work six-months after graduation in obtaining a high salary or working in a STEM (Science, Technology Engineering and Mathematics) field 3.5 years later. Initially taking unpaid work was associated with lower earnings and lower persistence in STEM compared with paid work, but those using personal connections to obtain unpaid positions were as likely to persist in STEM as paid workers. Obtaining a position in STEM six months after graduation was associated with higher rates of persistence in STEM compared with a position outside STEM for both paid and unpaid workers, but the difference is considerably smaller for unpaid workers. Socio-economic inequality in the likelihood of obtaining entry in STEM by taking an unpaid position is a well-founded concern for scientific workforce diversity

Prognostic Breast Cancer Signature Identified from 3D Culture Model Accurately Predicts Clinical Outcome across Independent Datasets

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer

Radiation-Induced Bystander Effects in Cultured Human Stem Cells

The radiation-induced "bystander effect" (RIBE) was shown to occur in a number of experimental systems both in vitro and in vivo as a result of exposure to ionizing radiation (IR). RIBE manifests itself by intercellular communication from irradiated cells to non-irradiated cells which may cause DNA damage and eventual death in these bystander cells. It is known that human stem cells (hSC) are ultimately involved in numerous crucial biological processes such as embryologic development; maintenance of normal homeostasis; aging; and aging-related pathologies such as cancerogenesis and other diseases. However, very little is known about radiation-induced bystander effect in hSC. To mechanistically interrogate RIBE responses and to gain novel insights into RIBE specifically in hSC compartment, both medium transfer and cell co-culture bystander protocols were employed.Human bone-marrow mesenchymal stem cells (hMSC) and embryonic stem cells (hESC) were irradiated with doses 0.2 Gy, 2 Gy and 10 Gy of X-rays, allowed to recover either for 1 hr or 24 hr. Then conditioned medium was collected and transferred to non-irradiated hSC for time course studies. In addition, irradiated hMSC were labeled with a vital CMRA dye and co-cultured with non-irradiated bystander hMSC. The medium transfer data showed no evidence for RIBE either in hMSC and hESC by the criteria of induction of DNA damage and for apoptotic cell death compared to non-irradiated cells (p>0.05). A lack of robust RIBE was also demonstrated in hMSC co-cultured with irradiated cells (p>0.05).These data indicate that hSC might not be susceptible to damaging effects of RIBE signaling compared to differentiated adult human somatic cells as shown previously. This finding could have profound implications in a field of radiation biology/oncology, in evaluating radiation risk of IR exposures, and for the safety and efficacy of hSC regenerative-based therapies

Ancient horizontal gene transfer and the last common ancestors

Background The genomic history of prokaryotic organismal lineages is marked by extensive horizontal gene transfer (HGT) between groups of organisms at all taxonomic levels. These HGT events have played an essential role in the origin and distribution of biological innovations. Analyses of ancient gene families show that HGT existed in the distant past, even at the time of the organismal last universal common ancestor (LUCA). Most gene transfers originated in lineages that have since gone extinct. Therefore, one cannot assume that the last common ancestors of each gene were all present in the same cell representing the cellular ancestor of all extant life. Results Organisms existing as part of a diverse ecosystem at the time of LUCA likely shared genetic material between lineages. If these other lineages persisted for some time, HGT with the descendants of LUCA could have continued into the bacterial and archaeal lineages. Phylogenetic analyses of aminoacyl-tRNA synthetase protein families support the hypothesis that the molecular common ancestors of the most ancient gene families did not all coincide in space and time. This is most apparent in the evolutionary histories of seryl-tRNA synthetase and threonyl-tRNA synthetase protein families, each containing highly divergent “rare” forms, as well as the sparse phylogenetic distributions of pyrrolysyl-tRNA synthetase, and the bacterial heterodimeric form of glycyl-tRNA synthetase. These topologies and phyletic distributions are consistent with horizontal transfers from ancient, likely extinct branches of the tree of life. Conclusions Of all the organisms that may have existed at the time of LUCA, by definition only one lineage is survived by known progeny; however, this lineage retains a genomic record of heterogeneous genetic origins. The evolutionary histories of aminoacyl-tRNA synthetases (aaRS) are especially informative in detecting this signal, as they perform primordial biological functions, have undergone several ancient HGT events, and contain many sites with low substitution rates allowing deep phylogenetic reconstruction. We conclude that some aaRS families contain groups that diverge before LUCA. We propose that these ancient gene variants be described by the term “hypnologs”, reflecting their ancient, reticulate origin from a time in life history that has been all but erased”.National Science Foundation (U.S.) (Grant DEB 0830024)Exobiology Program (U.S.) (Grant NNX10AR85G)United States. National Aeronautics and Space Administration (Postdoctoral Program

From microarray to biology: an integrated experimental, statistical and in silico analysis of how the extracellular matrix modulates the phenotype of cancer cells

A statistically robust and biologically-based approach for analysis of microarray data is described that integrates independent biological knowledge and data with a global F-test for finding genes of interest that minimizes the need for replicates when used for hypothesis generation. First, each microarray is normalized to its noise level around zero. The microarray dataset is then globally adjusted by robust linear regression. Second, genes of interest that capture significant responses to experimental conditions are selected by finding those that express significantly higher variance than those expressing only technical variability. Clustering expression data and identifying expression-independent properties of genes of interest including upstream transcriptional regulatory elements (TREs), ontologies and networks or pathways organizes the data into a biologically meaningful system. We demonstrate that when the number of genes of interest is inconveniently large, identifying a subset of "beacon genes" representing the largest changes will identify pathways or networks altered by biological manipulation. The entire dataset is then used to complete the picture outlined by the "beacon genes." This allow construction of a structured model of a system that can generate biologically testable hypotheses. We illustrate this approach by comparing cells cultured on plastic or an extracellular matrix which organizes a dataset of over 2,000 genes of interest from a genome wide scan of transcription. The resulting model was confirmed by comparing the predicted pattern of TREs with experimental determination of active transcription factors

Programme evaluation training for health professionals in francophone Africa: process, competence acquisition and use

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Vitamin A deficiency and inflammatory markers among preschool children in the Republic of the Marshall Islands

BACKGROUND: The exclusion of individuals with elevated acute phase proteins has been advocated in order to improve prevalence estimates of vitamin A deficiency in surveys, but it is unclear whether this will lead to sampling bias. The purpose of the study was to determine whether the exclusion of individuals with elevated acute phase proteins is associated with sampling bias and to characterize inflammation in children with night blindness. METHODS: In a survey in the Republic of the Marshall Islands involving 281 children, aged 1–5 years, serum retinol, C-reactive protein (CRP), and α(1)-acid glycoprotein (AGP) were measured. RESULTS: Of 281 children, 24 (8.5%) had night blindness and 165 (58.7%) had serum retinol <0.70 μmol/L. Of 248 children with AGP and CRP measurements, 123 (49.6%) had elevated acute phase proteins (CRP >5 mg/L and/or AGP >1000 mg/L). Among children with and without night blindness, the proportion with serum retinol <0.70 μmol/L was 79.2% and 56.8% (P = 0.03) and with anemia was 58.3% and 35.7% (P = 0.029), respectively. The proportion of children with serum retinol <0.70 μmol/L was 52.0% after excluding children with elevated acute phase proteins. Among children with and without elevated acute phase proteins, mean age was 2.8 vs 3.2 years (P = 0.016), the proportion of boys was 43.1% vs. 54.3% (P = 0.075), with no hospitalizations in the last year was 11.0% vs 23.6% (P = 0.024), and with anemia was 43.8% vs 31.7% (P = 0.05), respectively. CONCLUSIONS: Exclusion of children with inflammation in this survey of vitamin A deficiency does not improve prevalence estimates for vitamin A deficiency and instead leads to sampling bias for variables such as age, gender, anemia, and hospitalization history

A Rickettsiella Bacterium from the Hard Tick, Ixodes woodi: Molecular Taxonomy Combining Multilocus Sequence Typing (MLST) with Significance Testing

Hard ticks (Acari: Ixodidae) are known to harbour intracellular bacteria from several phylogenetic groups that can develop both mutualistic and pathogenic relationships to the host. This is of particular importance for public health as tick derived bacteria can potentially be transmitted to mammals, including humans, where e.g. Rickettsia or Coxiella act as severe pathogens. Exact molecular taxonomic identification of tick associated prokaryotes is a necessary prerequisite of the investigation of their relationship to both the tick and possible vertebrate hosts. Previously, an intracellular bacterium had been isolated from a monosexual, parthenogenetically reproducing laboratory colony of females of the hard tick, Ixodes woodi Bishopp, and had preliminarily been characterized as a “Rickettsiella-related bacterium”. In the present molecular taxonomic study that is based on phylogenetic reconstruction from both 16 S ribosomal RNA and protein-encoding marker sequences complemented with likelihood-based significance testing, the bacterium from I. woodi has been identified as a strain of the taxonomic species Rickettsiella grylli. It is the first time that a multilocus sequence typing (MLST) approach based on a four genes comprising MLST scheme has been implemented in order to classify a Rickettsiella-like bacterium to this species. The study demonstrated that MLST holds potential for a better resolution of phylogenetic relationships within the genus Rickettsiella, but requires sequence determination from further Rickettsiella-like bacteria in order to complete the current still fragmentary picture of Rickettsiella systematics