An Excursion-Set Model for the Structure of GMCs and the ISM

The ISM is governed by supersonic turbulence on a range of scales. We use this to develop a rigorous excursion-set model for the formation and time evolution of dense gas structures (GMCs, massive clumps, and cores). Supersonic turbulence drives the density distribution to a lognormal with dispersion increasing with Mach number; we generalize this to include scales >h (the disk scale height), and use it to construct the statistical properties of the density field smoothed on a scale R. We then compare conditions for self-gravitating collapse including thermal, turbulent, and rotational support. We show this becomes a well-defined barrier crossing problem. As such, an exact 'bound object mass function' can be derived, from scales of the sonic length to above the disk Jeans mass. This agrees remarkably well with observed GMC mass functions in the MW and other galaxies; the only inputs are the mass and size of the galaxies (to normalize the model). This explains the mass function cutoff and its power-law slope (close to, but shallower than, -2). The model also predicts the linewidth-size and size-mass relations of clouds and the dependence of their residuals on surface density/pressure. We use this to predict the spatial correlation function/clustering of clouds and star clusters; these also agree well with observations. We predict the size/mass function of ISM 'bubbles' or 'holes', and show this can account for observed HI hole distributions without any local feedback. We generalize the model to construct time-dependent 'merger/fragmentation trees' which can be used to follow cloud evolution and construct semi-analytic models for the ISM. We provide explicit recipes to construct the trees. We use a simple example to show that, if clouds are not destroyed in ~1-5 crossing times, then all ISM mass would be trapped in collapsing objects even if the large-scale turbulence were maintained.Comment: 21 pages, 11 figures, accepted to MNRAS (revised to match accepted version; predictions for high-redshift galaxies added

Leukocyte counts in urine reflect the risk of concomitant sepsis in bacteriuric infants: A retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>When urine infections are missed in febrile young infants with normal urinalysis, clinicians may worry about the risk – hitherto unverified – of concomitant invasion of blood and cerebrospinal fluid by uropathogens. In this study, we determine the extent of this risk.</p> <p>Methods</p> <p>In a retrospective cohort study of febrile 0–89 day old infants evaluated for sepsis in an urban academic pediatric emergency department (1993–1999), we estimated rates of bacteriuric sepsis (urinary tract infections complicated by sepsis) after stratifying infants by urine leukocyte counts higher, or lower than 10 cells/hpf. We compared the global accuracy of leukocytes in urine, leukocytes in peripheral blood, body temperature, and age for predicting bacteruric sepsis. The global accuracy of each test was estimated by calculating the area under its receiver operating characteristic curve (AUC). Chi-square and Fisher exact tests compared count data. Medians for data not normally distributed were compared by the Kruskal-Wallis test.</p> <p>Results</p> <p>Two thousand two hundred forty-nine young infants had a normal screening dipstick. None of these developed bacteremia or meningitis despite positive urine culture in 41 (1.8%). Of 1516 additional urine specimens sent for formal urinalysis, 1279 had 0–9 leukocytes/hpf. Urine pathogens were isolated less commonly (6% vs. 76%) and at lower concentrations in infants with few, compared to many urine leukocytes. Urine leukocytes (AUC: 0.94) were the most accurate predictors of bacteruric sepsis. Infants with urinary leukocytes < 10 cells/hpf were significantly less likely (0%; CI:0–0.3%) than those with higher leukocyte counts (5%; CI:2.6–8.7%) to have urinary tract infections complicated by bacteremia (N = 11) or bacterial meningitis (N = 1) – relative risk, 0 (CI:0–0.06) [RR, 0 (CI: 0–0.02), when including infants with negative dipstick]. Bands in peripheral blood had modest value for detecting bacteriuric sepsis (AUC: 0.78). Cases of sepsis without concomitant bacteriuria were comparatively rare (0.8%) and equally common in febrile young infants with low and high concentrations of urine leukocytes.</p> <p>Conclusion</p> <p>In young infants evaluated for fever, leukocytes in urine reflect the likelihood of bacteriuric sepsis. Infants with urinary tract infections missed because of few leukocytes in urine are at relatively low risk of invasive bacterial sepsis by pathogens isolated from urine.</p

First enantioseparation and circular dichroism spectra of Au38 clusters protected by achiral ligands

Bestowing chirality to metals is central in fields such as heterogeneous catalysis and modern optics. Although the bulk phase of metals is symmetric, their surfaces can become chiral through adsorption of molecules. Interestingly, even achiral molecules can lead to locally chiral, though globally racemic, surfaces. A similar situation can be obtained for metal particles or clusters. Here we report the first separation of the enantiomers of a gold cluster protected by achiral thiolates, Au38(SCH2CH2Ph)24, achieved by chiral high-performance liquid chromatography. The chirality of the nanocluster arises from the chiral arrangement of the thiolates on its surface, forming 'staple motifs'. The enantiomers show mirror-image circular dichroism responses and large anisotropy factors of up to 4×10−3. Comparison with reported circular dichroism spectra of other Au38 clusters reveals that the influence of the ligand on the chiroptical properties is minor

Coverage of whole proteome by structural genomics observed through protein homology modeling database

We have been developing FAMSBASE, a protein homology-modeling database of whole ORFs predicted from genome sequences. The latest update of FAMSBASE (http://daisy.nagahama-i-bio.ac.jp/Famsbase/), which is based on the protein three-dimensional (3D) structures released by November 2003, contains modeled 3D structures for 368,724 open reading frames (ORFs) derived from genomes of 276 species, namely 17 archaebacterial, 130 eubacterial, 18 eukaryotic and 111 phage genomes. Those 276 genomes are predicted to have 734,193 ORFs in total and the current FAMSBASE contains protein 3D structure of approximately 50% of the ORF products. However, cases that a modeled 3D structure covers the whole part of an ORF product are rare. When portion of an ORF with 3D structure is compared in three kingdoms of life, in archaebacteria and eubacteria, approximately 60% of the ORFs have modeled 3D structures covering almost the entire amino acid sequences, however, the percentage falls to about 30% in eukaryotes. When annual differences in the number of ORFs with modeled 3D structure are calculated, the fraction of modeled 3D structures of soluble protein for archaebacteria is increased by 5%, and that for eubacteria by 7% in the last 3 years. Assuming that this rate would be maintained and that determination of 3D structures for predicted disordered regions is unattainable, whole soluble protein model structures of prokaryotes without the putative disordered regions will be in hand within 15 years. For eukaryotic proteins, they will be in hand within 25 years. The 3D structures we will have at those times are not the 3D structure of the entire proteins encoded in single ORFs, but the 3D structures of separate structural domains. Measuring or predicting spatial arrangements of structural domains in an ORF will then be a coming issue of structural genomics

Functional Inactivation of EBV-Specific T-Lymphocytes in Nasopharyngeal Carcinoma: Implications for Tumor Immunotherapy

Nasopharyngeal carcinoma (NPC) is an Epstein-Barr virus (EBV) associated malignancy with high prevalence in Southern Chinese. In order to assess whether defects of EBV-specific immunity may contribute to the tumor, the phenotype and function of circulating T-cells and tumor infiltrating lymphocytes (TILs) were investigated in untreated NPC patients. Circulating naïve CD3+CD45RA+ and CD4+CD25− cells were decreased, while activated CD4+CD25+ T-cells and CD3−CD16+ NK-cells were increased in patients compared to healthy donors. The frequency of T-cells recognizing seven HLA-A2 restricted epitopes in LMP1 and LMP2 was lower in the patients and remained low after stimulation with autologous EBV-carrying cells. TILs expanded in low doses of IL-2 exhibited an increase of CD3+CD4+, CD3+CD45RO+ and CD4+CD25+ cells and 2 to 5 fold higher frequency of LMP1 and LMP2 tetramer positive cells compared to peripheral blood. EBV-specific cytotoxicity could be reactivated from the blood of most patients, whereas the TILs lacked cytotoxic activity and failed to produce IFNγ upon specific stimulation. Thus, EBV-specific rejection responses appear to be functionally inactivated at the tumor site in NPC

Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention

A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.N/

The Fecal Viral Flora of Wild Rodents

The frequent interactions of rodents with humans make them a common source of zoonotic infections. To obtain an initial unbiased measure of the viral diversity in the enteric tract of wild rodents we sequenced partially purified, randomly amplified viral RNA and DNA in the feces of 105 wild rodents (mouse, vole, and rat) collected in California and Virginia. We identified in decreasing frequency sequences related to the mammalian viruses families Circoviridae, Picobirnaviridae, Picornaviridae, Astroviridae, Parvoviridae, Papillomaviridae, Adenoviridae, and Coronaviridae. Seventeen small circular DNA genomes containing one or two replicase genes distantly related to the Circoviridae representing several potentially new viral families were characterized. In the Picornaviridae family two new candidate genera as well as a close genetic relative of the human pathogen Aichi virus were characterized. Fragments of the first mouse sapelovirus and picobirnaviruses were identified and the first murine astrovirus genome was characterized. A mouse papillomavirus genome and fragments of a novel adenovirus and adenovirus-associated virus were also sequenced. The next largest fraction of the rodent fecal virome was related to insect viruses of the Densoviridae, Iridoviridae, Polydnaviridae, Dicistroviriade, Bromoviridae, and Virgaviridae families followed by plant virus-related sequences in the Nanoviridae, Geminiviridae, Phycodnaviridae, Secoviridae, Partitiviridae, Tymoviridae, Alphaflexiviridae, and Tombusviridae families reflecting the largely insect and plant rodent diet. Phylogenetic analyses of full and partial viral genomes therefore revealed many previously unreported viral species, genera, and families. The close genetic similarities noted between some rodent and human viruses might reflect past zoonoses. This study increases our understanding of the viral diversity in wild rodents and highlights the large number of still uncharacterized viruses in mammals

Characteristics of therapeutic alliance in musculoskeletal physiotherapy and occupational therapy practice: A scoping review of the literature

© 2017 The Author(s). Background: Most conventional treatment for musculoskeletal conditions continue to show moderate effects, prompting calls for ways to increase effectiveness, including drawing from strategies used across other health conditions. Therapeutic alliance refers to the relational processes at play in treatment which can act in combination or independently of specific interventions. Current evidence guiding the use of therapeutic alliance in health care arises largely from psychotherapy and medicine literature. The objective of this review was to map out the available literature on therapeutic alliance conceptual frameworks, themes, measures and determinants in musculoskeletal rehabilitation across physiotherapy and occupational therapy disciplines. Methods: A scoping review of the literature published in English since inception to July 2015 was conducted using Medline, EMBASE, PsychINFO, PEDro, SportDISCUS, AMED, OTSeeker, AMED and the grey literature. A key search term strategy was employed using physiotherapy , occupational therapy , therapeutic alliance , and musculoskeletal to identify relevant studies. All searches were performed between December 2014 and July 2015 with an updated search on January 2017. Two investigators screened article title, abstract and full text review for articles meeting the inclusion criteria and extracted therapeutic alliance data and details of each study. Results: One hundred and thirty articles met the inclusion criteria including quantitative (33%), qualitative (39%), mixed methods (7%) and reviews and discussions (23%) and most data came from the USA (23%). Randomized trials and systematic reviews were 4.6 and 2.3% respectively. Low back pain condition (22%) and primary care (30.7%) were the most reported condition and setting respectively. One theory, 9 frameworks, 26 models, 8 themes and 42 subthemes of therapeutic alliance were identified. Twenty-six measures were identified; the Working Alliance Inventory (WAI) was the most utilized measure (13%). Most of the therapeutic alliance themes extracted were from patient perspectives. The relationship between adherence and therapeutic alliance was examined by 26 articles of which 57% showed some correlation between therapeutic alliance and adherence. Age moderated the relationship between therapeutic alliance and adherence with younger individuals and an autonomy support environment reporting improved adherence. Prioritized goals, autonomy support and motivation were facilitators of therapeutic alliance. Conclusion: Therapeutic Alliance has been studied in a limited extent in the rehabilitation literature with conflicting frameworks and findings. Potential benefits described for enhancing therapeutic alliance might include better exercise adherence. Several knowledge gaps have been identified with a potential for generating future research priorities for therapeutic alliance in musculoskeletal rehabilitation

A General Model for the CO-H2 Conversion Factor in Galaxies with Applications to the Star Formation Law

The most common means of converting an observed CO line intensity into a molecular gas mass requires the use of a conversion factor (Xco). While in the Milky Way this quantity does not appear to vary significantly, there is good reason to believe that Xco will depend on the larger-scale galactic environment. Utilising numerical models, we investigate how varying metallicities, gas temperatures and velocity dispersions in galaxies impact the way CO line emission traces the underlying H2 gas mass, and under what circumstances Xco may differ from the Galactic mean value. We find that, due to the combined effects of increased gas temperature and velocity dispersion, Xco is depressed below the Galactic mean in high surface density environments such as ULIRGs. In contrast, in low metallicity environments, Xco tends to be higher than in the Milky Way, due to photodissociation of CO in metal-poor clouds. At higher redshifts, gas-rich discs may have gravitationally unstable clumps which are warm (due to increased star formation) and have elevated velocity dispersions. These discs tend to have Xco values ranging between present-epoch gas-rich mergers and quiescent discs at low-z. This model shows that on average, mergers do have lower Xco values than disc galaxies, though there is significant overlap. Xco varies smoothly with the local conditions within a galaxy, and is not a function of global galaxy morphology. We combine our results to provide a general fitting formula for Xco as a function of CO line intensity and metallicity. We show that replacing the traditional approach of using one constant Xco for starbursts and another for discs with our best-fit function produces star formation laws that are continuous rather than bimodal, and that have significantly reduced scatter.Comment: Accepted by MNRAS; major revision includes moving the bulk of the equations to an appendi