Variations in the slope of the resolved star-forming main sequence: A tool for constraining the mass of star-forming regions

The correlation between galaxies' integrated stellar masses and star formation rates (the 'star formation main sequence', SFMS) is a well-established scaling relation. Recently, surveys have found a relationship between the star formation rate (SFR) and stellar mass surface densities on kpc and sub-kpc scales (the 'resolved SFMS', rSFMS). In this work, we demonstrate that the rSFMS emerges naturally in Feedback In Realistic Environments 2 (FIRE-2) zoom-in simulations of Milky Way-mass galaxies. We make SFR and stellar mass maps of the simulated galaxies at a variety of spatial resolutions and star formation averaging time-scales and fit the rSFMS using multiple methods from the literature. While the absolute value of the SFMS slope (αMS) depends on the fitting method, the slope is steeper for longer star formation time-scales and lower spatial resolutions regardless of the fitting method employed. We present a toy model that quantitatively captures the dependence of the simulated galaxies' αMS on spatial resolution and use it to illustrate how this dependence can be used to constrain the characteristic mass of star-forming clumps

What drives the evolution of gas kinematics in star-forming galaxies?

One important result from recent large integral field spectrograph (IFS) surveys is that the intrinsic velocity dispersion of galaxies traced by star-forming gas increases with redshift. Massive, rotation-dominated discs are already in place at z ∼ 2, but they are dynamically hotter than spiral galaxies in the local Universe. Although several plausible mechanisms for this elevated velocity dispersion (e.g. star formation feedback, elevated gas supply, or more frequent galaxy interactions) have been proposed, the fundamental driver of the velocity dispersion enhancement at high redshift remains unclear. We investigate the origin of this kinematic evolution using a suite of cosmological simulations from the FIRE (Feedback In Realistic Environments) project. Although IFS surveys generally cover a wider range of stellar masses than in these simulations, the simulated galaxies show trends between intrinsic velocity dispersion (σ intr ), SFR, and z in agreement with observations. In both observations and simulations, galaxies on the star-forming main sequence have median σ intr values that increase from z ∼ 0 to z ∼ 1–1.5, but this increasing trend is less evident at higher redshift. In the FIRE simulations, σ intr can vary significantly on time-scales of 100 Myr. These variations closely mirror the time evolution of the SFR and gas inflow rate (M gas ). By cross-correlating pairs of σ intr, M gas, and SFR, we show that increased gas inflow leads to subsequent enhanced star formation, and enhancements in σ intr tend to temporally coincide with increases in M gas and SFR

LGBT+ Youth Perspectives on Sexual Orientation and Gender Identity Questions in the Growing Up in Ireland Survey: A Qualitative Study

The increasing importance of identifying lesbian, gay, bisexual and transgender (LGBT+) populations is a key driver in changes to demographic data collection in representative surveys of youth. While such population-based data are rare, Growing Up in Ireland (GUI), an Irish, government-funded, longitudinal survey, includes sexual orientation and gender identity (SOGI) measurements. This qualitative study responds to a query from the GUI study team and aims to identify how best to collect SOGI data in future waves of GUI. A university Human Research Ethics Committee granted approval for online consultations with LGBT+ youth (n = 6) with experiential expertise in policy making. The research is underpinned by rights-based public patient involvement (PPI) with recorded discussions, which were transcribed and imported into NVivo 12, generating the theme “recognition in research, policy and society”. This co-created article, with the LGBT+ young PPI Panel members, commends the inclusion of SOGI data in GUI and recommends changes in question placement and phrasing. Aligning with best practice, the PPI members provide a template for wording on consecutive sex and gender questions, expanded sexual orientation identity categories and maintaining the existing well-phrased transgender question from GUI. This offers potential to improve the quality of the SOGI data collected and the experience of those completing the questionnaire. These findings extend beyond GUI, with relevance for surveys with youth populations. This paper underscores the potential and benefits of participatory approaches to research with youth and views their role beyond simply as sources of data

Evaluation of Xpert® MTB/RIF and ustar easyNAT™ TB IAD for diagnosis of tuberculous lymphadenitis of children in Tanzania : a prospective descriptive study

Fine needle aspiration biopsy has become a standard approach for diagnosis of peripheral tuberculous lymphadenitis. The aim of this study was to compare the performance of Xpert MTB/RIF and Ustar EasyNAT TB IAD nucleic acid amplification assays, against acid-fast bacilli microscopy, cytology and mycobacterial culture for the diagnosis of TB lymphadenitis in children from a TB-endemic setting in Tanzania.; Children of 8 weeks to 16 years of age, suspected of having TB lymphadenitis, were recruited at a district hospital in Tanzania. Fine needle aspirates of lymph nodes were analysed using acid-fast bacilli microscopy, liquid TB culture, cytology, Xpert MTB/RIF and EasyNAT. Latent class analysis and comparison against a composite reference standard comprising "culture and/or cytology" was done, to assess the performance of Xpert MTB/RIF and EasyNAT for the diagnosis of TB lymphadenitis.; Seventy-nine children were recruited; 4 were excluded from analysis. Against a composite reference standard of culture and/or cytology, Xpert MTB/RIF and EasyNAT had a sensitivity and specificity of 58 % and 93 %; and 19 % and 100 % respectively. Relative to latent class definitions, cytology had a sensitivity of 100 % and specificity of 94.7 %.; Combining clinical assessment, cytology and Xpert MTB/RIF may allow for a rapid and accurate diagnosis of childhood TB lymphadenitis. Larger diagnostic evaluation studies are recommended to validate these findings and on Xpert MTB/RIF to assess its use as a solitary initial test for TB lymphadenitis in children

A pipeline to quantify serum and cerebrospinal fluid microRNAs for diagnosis and detection of relapse in paediatric malignant germ-cell tumours

Background:The current biomarkers alpha-fetoprotein and human chorionic gonadotropin have limited sensitivity and specificity for diagnosing malignant germ-cell tumours (GCTs). MicroRNAs (miRNAs) from the miR-371-373 and miR-302/367 clusters are overexpressed in all malignant GCTs, and some of these miRNAs show elevated serum levels at diagnosis. Here, we developed a robust technical pipeline to quantify these miRNAs in the serum and cerebrospinal fluid (CSF). The pipeline was used in samples from a cohort of exclusively paediatric patients with gonadal and extragonadal malignant GCTs, compared with appropriate tumour and non-tumour control groups.Methods:We developed a method for miRNA quantification that enabled sample adequacy assessment and reliable data normalisation. We performed qRT-PCR profiling for miR-371-373 and miR-302/367 cluster miRNAs in a total of 45 serum and CSF samples, obtained from 25 paediatric patients.Results:The exogenous non-human spike-in cel-miR-39-3p and the endogenous housekeeper miR-30b-5p were optimal for obtaining robust serum and CSF qRT-PCR quantification. A four-serum miRNA panel (miR-371a-3p, miR-372-3p, miR-373-3p and miR-367-3p): (i) showed high sensitivity/specificity for diagnosing paediatric extracranial malignant GCT; (ii) allowed early detection of relapse of a testicular mixed malignant GCT; and (iii) distinguished intracranial malignant GCT from intracranial non-GCT tumours at diagnosis, using CSF and serum samples.Conclusions:The pipeline we have developed is robust, scalable and transferable. It potentially promises to improve clinical management of paediatric (and adult) malignant GCTs

Compartmental Model for ²²³Ra-Dichloride in Patients With Metastatic Bone Disease From Castration-Resistant Prostate Cancer.

Purpose223Ra-Dichloride is used for treatment of patients with metastatic bone disease from castration-resistant prostate cancer. The uptake and mechanism of action of 223Ra-Dichloride is not well understood. The aim of this work was to develop a compartmental model for 223Ra-Dichloride in patients to improve understanding of the underlying mechanisms.Methods and materialsA compartmental model was developed based on activity retention data from 6 patients (2 treatments of 110 kBq/kg 223Ra-Dichloride) for plasma, bone surfaces, small intestines, large intestines, and excretion data. Rate constants were extracted. Rate constant variability between patients and treatments was assessed. A population model was proposed and compared with the established International Commission on Radiological Protection-67 compartmental model.ResultsA single bone compartment cannot accurately describe activity retention in the skeleton. The addition of a second bone compartment improved the fit to skeleton retention data, and the Akaike information criterion decreased. Mean rate constants of 4.0 (range, 1.9-10.9) and 0.15 (0.07-0.39) h-1 were obtained for transport from plasma to first bone compartment and vice versa. Rate constants from first to second bone compartment and back of 0.03 (0.02-0.06) and 0.008 (0.003-0.011) h-1 were calculated. Rate constants for individual patients showed no significant difference between patients and treatments.ConclusionsThe developed compartmental model suggests that 223Ra-Dichloride initially locates at the bone surface and is then incorporated into the bone matrix relatively quickly. This observation could have implications for dosimetry and understanding of the effects of alpha radiation on normal bone tissue. Results suggest that a population model based on patient measurements is feasible

Prediction of 7-year psychopathology from mother-infant joint attention behaviours: a nested case–control study

<br>Background: To investigate whether later diagnosis of psychiatric disorder can be predicted from analysis of mother-infant joint attention (JA) behaviours in social-communicative interaction at 12 months.</br> <br>Method: Using data from a large contemporary birth cohort, we examined 159 videos of a mother-infant interaction for joint attention behaviour when children were aged one year, sampled from within the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Fifty-three of the videos involved infants who were later considered to have a psychiatric disorder at seven years and 106 were same aged controls. Psychopathologies included in the case group were disruptive behaviour disorders, oppositional-conduct disorder, attention-deficit/hyperactivity disorder, pervasive development disorder, anxiety and depressive disorders. Psychiatric diagnoses were obtained using the Development and Wellbeing Assessment when the children were seven years old.</br> <br>Results: None of the three JA behaviours (shared look rate, shared attention rate and shared attention intensity) showed a significant association with the primary outcome of case–control status. Only shared look rate predicted any of the exploratory sub-diagnosis outcomes and was found to be positively associated with later oppositional-conduct disorders (OR [95% CI]: 1.5 [1.0, 2.3]; p = 0.041).</br><br>Conclusions: JA behaviours did not, in general, predict later psychopathology. However, shared look was positively associated with later oppositional-conduct disorders. This suggests that some features of JA may be early markers of later psychopathology. Further investigation will be required to determine whether any JA behaviours can be used to screen for families in need of intervention.</br&gt

Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo

<p>Abstract</p> <p>Background</p> <p>Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tracking the expression of individual <it>C. elegans </it>genes was developed that collects image samples of a developing embryo by 3-D time lapse microscopy. In this protocol, a program called StarryNite performs the automatic recognition of fluorescently labeled cells and traces their lineage. However, due to the amount of noise present in the data and due to the challenges introduced by increasing number of cells in later stages of development, this program is not error free. In the current version, the error correction (<it>i.e</it>., editing) is performed manually using a graphical interface tool named AceTree, which is specifically developed for this task. For a single experiment, this manual annotation task takes several hours.</p> <p>Results</p> <p>In this paper, we reduce the time required to correct errors made by StarryNite. We target one of the most frequent error types (movements annotated as divisions) and train a support vector machine (SVM) classifier to decide whether a division call made by StarryNite is correct or not. We show, via cross-validation experiments on several benchmark data sets, that the SVM successfully identifies this type of error significantly. A new version of StarryNite that includes the trained SVM classifier is available at <url>http://starrynite.sourceforge.net</url>.</p> <p>Conclusions</p> <p>We demonstrate the utility of a machine learning approach to error annotation for StarryNite. In the process, we also provide some general methodologies for developing and validating a classifier with respect to a given pattern recognition task.</p

Diabetes prevalence and diagnosis in US states: analysis of health surveys

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