Increase in Weight in Low Birth Weight and Very Low Birth Weight Infants Fed Fortified Breast Milk versus Formula Milk: A Retrospective Cohort Study

There has been a dramatic rise in preterm births in developed countries owing to changes in clinical practices and greater use of assisted reproductive techniques. However, few studies have examined the growth and outcomes of preterm infants according to the type of feeding (with fortified breast milk or formula). The purpose of this study was to examine the effect of breast milk feedings and formula on the growth and short-term outcomes of preterm infants in Hong Kong. In a single-center retrospective cohort study, we included 642 preterm infants at gestational age <37 weeks with birth weights <2200 g. According to World Health Organization criteria, 466 were classified as low birth weight (LBW) infants (≥1500 g and <2200 g) and 176 were classified as very low birth weight (VLBW) infants (<1500 g). The mothers of approximately 80% of VLBW infants and 60% LBW infants initiated breast milk feeding. When compared with no breast milk intake, LBW infants that received breast milk were significantly more likely to have growth z-scores closer to the median of the reference population on admission and experienced slower weight gain from birth to discharge. When breast milk was categorized by percent of total enteral intake, significant differences were seen among LBW infants, with lower percentages of small-for-gestational-age (SGA) status at discharge with increased proportions of breast milk intake. Our results suggest that LBW infants fed breast milk had better growth z-scores and lower SGA status at discharge compared with those predominately fed preterm formula.published_or_final_versio

Listen to genes : dealing with microarray data in the frequency domain

Background: We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes. Methodology: Genes are normalized using an error model based uniform normalization method aimed at identifying and estimating the sources of variations. The model minimizes the correlation among error terms across replicates. The normalized gene expressions are then clustered in terms of their power spectrum density. The method of complex Granger causality is introduced to reveal interactions between sets of genes. Complex Granger causality along with partial Granger causality is applied in both time and frequency domains to selected as well as all the genes to reveal the interesting networks of interactions. The approach is successfully applied to Arabidopsis leaf microarray data generated from 31,000 genes observed over 22 time points over 22 days. Three circuits: a circadian gene circuit, an ethylene circuit and a new global circuit showing a hierarchical structure to determine the initiators of leaf senescence are analyzed in detail. Conclusions: We use a totally data-driven approach to form biological hypothesis. Clustering using the power-spectrum analysis helps us identify genes of potential interest. Their dynamics can be captured accurately in the time and frequency domain using the methods of complex and partial Granger causality. With the rise in availability of temporal microarray data, such methods can be useful tools in uncovering the hidden biological interactions. We show our method in a step by step manner with help of toy models as well as a real biological dataset. We also analyse three distinct gene circuits of potential interest to Arabidopsis researchers

Lung adenocarcinoma originates from retrovirus infection of proliferating type 2 pneumocytes during pulmonary post-natal development or tissue repair

Jaagsiekte sheep retrovirus (JSRV) is a unique oncogenic virus with distinctive biological properties. JSRV is the only virus causing a naturally occurring lung cancer (ovine pulmonary adenocarcinoma, OPA) and possessing a major structural protein that functions as a dominant oncoprotein. Lung cancer is the major cause of death among cancer patients. OPA can be an extremely useful animal model in order to identify the cells originating lung adenocarcinoma and to study the early events of pulmonary carcinogenesis. In this study, we demonstrated that lung adenocarcinoma in sheep originates from infection and transformation of proliferating type 2 pneumocytes (termed here lung alveolar proliferating cells, LAPCs). We excluded that OPA originates from a bronchioalveolar stem cell, or from mature post-mitotic type 2 pneumocytes or from either proliferating or non-proliferating Clara cells. We show that young animals possess abundant LAPCs and are highly susceptible to JSRV infection and transformation. On the contrary, healthy adult sheep, which are normally resistant to experimental OPA induction, exhibit a relatively low number of LAPCs and are resistant to JSRV infection of the respiratory epithelium. Importantly, induction of lung injury increased dramatically the number of LAPCs in adult sheep and rendered these animals fully susceptible to JSRV infection and transformation. Furthermore, we show that JSRV preferentially infects actively dividing cell in vitro. Overall, our study provides unique insights into pulmonary biology and carcinogenesis and suggests that JSRV and its host have reached an evolutionary equilibrium in which productive infection (and transformation) can occur only in cells that are scarce for most of the lifespan of the sheep. Our data also indicate that, at least in this model, inflammation can predispose to retroviral infection and cancer

Direct Formation of Supermassive Black Holes via Multi-Scale Gas Inflows in Galaxy Mergers

Observations of distant bright quasars suggest that billion solar mass supermassive black holes (SMBHs) were already in place less than a billion years after the Big Bang. Models in which light black hole seeds form by the collapse of primordial metal-free stars cannot explain their rapid appearance due to inefficient gas accretion. Alternatively, these black holes may form by direct collapse of gas at the center of protogalaxies. However, this requires metal-free gas that does not cool efficiently and thus is not turned into stars, in contrast with the rapid metal enrichment of protogalaxies. Here we use a numerical simulation to show that mergers between massive protogalaxies naturally produce the required central gas accumulation with no need to suppress star formation. Merger-driven gas inflows produce an unstable, massive nuclear gas disk. Within the disk a second gas inflow accumulates more than 100 million solar masses of gas in a sub-parsec scale cloud in one hundred thousand years. The cloud undergoes gravitational collapse, which eventually leads to the formation of a massive black hole. The black hole can grow to a billion solar masses in less than a billion years by accreting gas from the surrounding disk.Comment: 26 pages, 4 Figures, submitted to Nature (includes Supplementary Information

Virtual signatures of dark sectors in Higgs couplings

Where collider searches for resonant invisible particles loose steam, dark sectors might leave their trace as virtual effects in precision observables. Here we explore this option in the framework of Higgs portal models, where a sector of dark fermions interacts with the standard model through a strong renormalizable coupling to the Higgs boson. We show that precise measurements of Higgs-gauge and triple Higgs interactions can probe dark fermions up to the TeV scale through virtual corrections. Observation prospects at the LHC and future lepton colliders are discussed for the so-called singlet-doublet model of Majorana fermions, a generalization of the bino-higgsino scenario in supersymmetry. We advocate a two-fold search strategy for dark sectors through direct and indirect observables.Comment: 20 pages, 7 figures, 1 tabl

The frequency of osteogenic activities and the pattern of intermittence between periods of physical activity and sedentary behaviour affects bone mineral content: the cross-sectional NHANES study

BACKGROUND: Sedentary behaviours, defined as non exercising seated activities, have been shown to have deleterious effects on health. It has been hypothesised that too much sitting time can have a detrimental effect on bone health in youth. The aim of this study is to test this hypothesis by exploring the association between objectively measured volume and patterns of time spent in sedentary behaviours, time spent in specific screen-based sedentary pursuits and bone mineral content (BMC) accrual in youth. METHODS: NHANES 2005–2006 cycle data includes BMC of the femoral and spinal region via dual-energy X-ray absorptiometry (DEXA), assessment of physical activity and sedentary behaviour patterns through accelerometry, self reported time spent in screen based pursuits (watching TV and using a computer), and frequency of vigorous playtime and strengthening activities. Multiple regression analysis, stratified by gender was performed on N = 671 males and N = 677 females aged from 8 to 22 years. RESULTS: Time spent in screen-based sedentary behaviours is negatively associated with femoral BMC (males and females) and spinal BMC (females only) after correction for time spent in moderate and vigorous activity. Regression coefficients indicate that an additional hour per day of screen-based sitting corresponds to a difference of −0.77 g femoral BMC in females [95% CI: -1.31 to −0.22] and of −0.45 g femoral BMC in males [95% CI: -0.83 to −0.06]. This association is attenuated when self-reported engagement in regular (average 5 times per week) strengthening exercise (for males) and vigorous playing (for both males and females) is taken into account. Total sitting time and non screen-based sitting do not appear to have a negative association with BMC, whereas screen based sedentary time does. Patterns of intermittence between periods of sitting and moderate to vigorous activity appears to be positively associated with bone health when activity is clustered in time and inter-spaced with long continuous bouts of sitting. CONCLUSIONS: Some specific sedentary pursuits (screen-based) are negatively associated with bone health in youth. This association is specific to gender and anatomical area. This relationship between screen-based time and bone health is independent of the total amount of physical activity measured objectively, but not independent of self-reported frequency of strengthening and vigorous play activities. The data clearly suggests that the frequency, rather than the volume, of osteogenic activities is important in counteracting the effect of sedentary behaviour on bone health. The pattern of intermittence between sedentary periods and activity also plays a role in bone accrual, with clustered short bouts of activity interspaced with long periods of sedentary behaviours appearing to be more beneficial than activities more evenly spread in time

The All-Data-Based Evolutionary Hypothesis of Ciliated Protists with a Revised Classification of the Phylum Ciliophora (Eukaryota, Alveolata)

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The file attached is the published version of the article

Early star-forming galaxies and the reionization of the Universe

Star forming galaxies represent a valuable tracer of cosmic history. Recent observational progress with Hubble Space Telescope has led to the discovery and study of the earliest-known galaxies corresponding to a period when the Universe was only ~800 million years old. Intense ultraviolet radiation from these early galaxies probably induced a major event in cosmic history: the reionization of intergalactic hydrogen. New techniques are being developed to understand the properties of these most distant galaxies and determine their influence on the evolution of the universe.Comment: Review article appearing in Nature. This posting reflects a submitted version of the review formatted by the authors, in accordance with Nature publication policies. For the official, published version of the review, please see http://www.nature.com/nature/archive/index.htm

Gene expression patterns associated with p53 status in breast cancer

BACKGROUND: Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function). METHODS: The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors. RESULTS: Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data. CONCLUSION: In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes that were associated with subtype but not downstream of p53 signaling, and identified a signature for p53 loss that is shared across breast cancer subtypes