Secular Evolution and the Formation of Pseudobulges in Disk Galaxies

We review internal processes of secular evolution in galaxy disks, concentrating on the buildup of dense central features that look like classical, merger-built bulges but that were made slowly out of disk gas. We call these pseudobulges. As an existence proof, we review how bars rearrange disk gas into outer rings, inner rings, and gas dumped into the center. In simulations, this gas reaches high densities that plausibly feed star formation. In the observations, many SB and oval galaxies show central concentrations of gas and star formation. Star formation rates imply plausible pseudobulge growth times of a few billion years. If secular processes built dense central components that masquerade as bulges, can we distinguish them from merger-built bulges? Observations show that pseudobulges retain a memory of their disky origin. They have one or more characteristics of disks: (1) flatter shapes than those of classical bulges, (2) large ratios of ordered to random velocities indicative of disk dynamics, (3) small velocity dispersions, (4) spiral structure or nuclear bars in the bulge part of the light profile, (5) nearly exponential brightness profiles, and (6) starbursts. These structures occur preferentially in barred and oval galaxies in which secular evolution should be rapid. So the cleanest examples of pseudobulges are recognizable. Thus a large variety of observational and theoretical results contribute to a new picture of galaxy evolution that complements hierarchical clustering and merging.Comment: 92 pages, 21 figures in 30 Postscript files; to appear in Annual Review of Astronomy and Astrophysics, Vol. 42, 2004, in press; for a version with full resolution figures, see http://chandra.as.utexas.edu/~kormendy/ar3ss.htm

Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application: a prospective, observational study

BACKGROUND: As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. METHODS: In this prospective, observational study, we did modelling using longitudinal, self-reported data from users of the COVID Symptom Study app in England between March 24, and Sept 29, 2020. Beginning on April 28, in England, the Department of Health and Social Care allocated RT-PCR tests for COVID-19 to app users who logged themselves as healthy at least once in 9 days and then reported any symptom. We calculated incidence of COVID-19 using the invited swab (RT-PCR) tests reported in the app, and we estimated prevalence using a symptom-based method (using logistic regression) and a method based on both symptoms and swab test results. We used incidence rates to estimate the effective reproduction number, R(t), modelling the system as a Poisson process and using Markov Chain Monte-Carlo. We used three datasets to validate our models: the Office for National Statistics (ONS) Community Infection Survey, the Real-time Assessment of Community Transmission (REACT-1) study, and UK Government testing data. We used geographically granular estimates to highlight regions with rapidly increasing case numbers, or hotspots. FINDINGS: From March 24 to Sept 29, 2020, a total of 2 873 726 users living in England signed up to use the app, of whom 2 842 732 (98·9%) provided valid age information and daily assessments. These users provided a total of 120 192 306 daily reports of their symptoms, and recorded the results of 169 682 invited swab tests. On a national level, our estimates of incidence and prevalence showed a similar sensitivity to changes to those reported in the ONS and REACT-1 studies. On Sept 28, 2020, we estimated an incidence of 15 841 (95% CI 14 023-17 885) daily cases, a prevalence of 0·53% (0·45-0·60), and R(t) of 1·17 (1·15-1·19) in England. On a geographically granular level, on Sept 28, 2020, we detected 15 (75%) of the 20 regions with highest incidence according to government test data. INTERPRETATION: Our method could help to detect rapid case increases in regions where government testing provision is lower. Self-reported data from mobile applications can provide an agile resource to inform policy makers during a quickly moving pandemic, serving as a complementary resource to more traditional instruments for disease surveillance. FUNDING: Zoe Global, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Alzheimer's Society, Chronic Disease Research Foundation

Attributes and predictors of long COVID

Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called 'long COVID', are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app(1). A total of 558 (13.3%) participants reported symptoms lasting >= 28 days, 189 (4.5%) for >= 8 weeks and 95 (2.3%) for >= 12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76-4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services

Attributes and predictors of long COVID

Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called ‘long COVID’, are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76–4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services

Gene Expression Profiles Distinguish the Carcinogenic Effects of Aristolochic Acid in Target (Kidney) and Non-target (Liver) Tissues in Rats

BACKGROUND: Aristolochic acid (AA) is the active component of herbal drugs derived from Aristolochia species that have been used for medicinal purposes since antiquity. AA, however, induced nephropathy and urothelial cancer in people and malignant tumors in the kidney and urinary tract of rodents. Although AA is bioactivated in both kidney and liver, it only induces tumors in kidney. To evaluate whether microarray analysis can be used for distinguishing the tissue-specific carcinogenicity of AA, we examined gene expression profiles in kidney and liver of rats treated with carcinogenic doses of AA. RESULTS: Microarray analysis was performed using the Rat Genome Survey Microarray and data analysis was carried out within ArrayTrack software. Principal components analysis and hierarchical cluster analysis of the expression profiles showed that samples were grouped together according to the tissues and treatments. The gene expression profiles were significantly altered by AA treatment in both kidney and liver (p < 0.01; fold change > 1.5). Functional analysis with Ingenuity Pathways Analysis showed that there were many more significantly altered genes involved in cancer-related pathways in kidney than in liver. Also, analysis with Gene Ontology for Functional Analysis (GOFFA) software indicated that the biological processes related to defense response, apoptosis and immune response were significantly altered by AA exposure in kidney, but not in liver. CONCLUSION: Our results suggest that microarray analysis is a useful tool for detecting AA exposure; that analysis of the gene expression profiles can define the differential responses to toxicity and carcinogenicity of AA from kidney and liver; and that significant alteration of genes associated with defense response, apoptosis and immune response in kidney, but not in liver, may be responsible for the tissue-specific toxicity and carcinogenicity of AA

Site directed biotinylation of filamentous phage structural proteins

Filamentous bacteriophages have been used in numerous applications for the display of antibodies and random peptide libraries. Here we describe the introduction of a 13 amino acid sequence LASIFEAQKIEWR (designated BT, which is biotinylated in vivo by E. coli) into the N termini of four of the five structural proteins of the filamentous bacteriophage fd (Proteins 3, 7, 8 and 9). The in vivo and in vitro biotinylation of the various phages were compared. The production of multifunctional phages and their application as affinity reagents are demonstrated

Cytoplasmic CUG RNA Foci Are Insufficient to Elicit Key DM1 Features

The genetic basis of myotonic dystrophy type I (DM1) is the expansion of a CTG tract located in the 3′ untranslated region of DMPK. Expression of mutant RNAs encoding expanded CUG repeats plays a central role in the development of cardiac disease in DM1. Expanded CUG tracts form both nuclear and cytoplasmic aggregates, yet the relative significance of such aggregates in eliciting DM1 pathology is unclear. To test the pathophysiology of CUG repeat encoding RNAs, we developed and analyzed mice with cardiac-specific expression of a beta-galactosidase cassette in which a (CTG)400 repeat tract was positioned 3′ of the termination codon and 5′ of the bovine growth hormone polyadenylation signal. In these animals CUG aggregates form exclusively in the cytoplasm of cardiac cells. A key pathological consequence of expanded CUG repeat RNA expression in DM1 is aberrant RNA splicing. Abnormal splicing results from the functional inactivation of MBNL1, which is hypothesized to occur due to MBNL1 sequestration in CUG foci or from elevated levels of CUG-BP1. We therefore tested the ability of cytoplasmic CUG foci to elicit these changes. Aggregation of CUG RNAs within the cytoplasm results both in Mbnl1 sequestration and in approximately a two fold increase in both nuclear and cytoplasmic Cug-bp1 levels. Significantly, despite these changes RNA splice defects were not observed and functional analysis revealed only subtle cardiac dysfunction, characterized by conduction defects that primarily manifest under anesthesia. Using a human myoblast culture system we show that this transgene, when expressed at similar levels to a second transgene, which encodes expanded CTG tracts and facilitates both nuclear focus formation and aberrant splicing, does not elicit aberrant splicing. Thus the lack of toxicity of cytoplasmic CUG foci does not appear to be a consequence of low expression levels. Our results therefore demonstrate that the cellular location of CUG RNA aggregates is an important variable that influences toxicity and support the hypothesis that small molecules that increase the rate of transport of the mutant DMPK RNA from the nucleus into the cytoplasm may significantly improve DM1 pathology

Early rapid weight gain and subsequent overweight and obesity in middle childhood in Peru

BACKGROUND: Rapid postnatal weight gain is associated with risk of overweight and obesity, but it’s unclear whether this holds in populations exposed to concurrent obesogenic risk factors and for children who have been extensively breastfed. This study investigates whether an increase in weight for age from birth to 1 year (infancy) and from 1 to 5 years (early childhood) predicts overweight and obesity, and waist circumference at 8 years, using data from a longitudinal cohort study in Peru. METHODS: Generalized estimating equations (GEE) models were constructed for overweight and obesity, obesity alone and waist circumference at 8 years versus rapid weight gain in infancy, and early childhood including adjusted models to account for confounders. RESULTS: Rapid weight gain in both periods was associated with double the risk of overweight and obesity, obesity alone at 8 years and increased waist circumference even after controlling for maternal BMI and education level, sex of child, height-for-age at 8 years, consumption of “fast food” and number of days of active exercise. The association was significant, with some differences, for children in both rural and urban environments. CONCLUSIONS: Rapid weight gain in infancy and in early childhood in Peru is associated with overweight and obesity at age 8 years even when considering other determinants of childhood obesity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40608-016-0135-z) contains supplementary material, which is available to authorized users

Early-childhood linear growth faltering in low- and middle-income countries

Globally, 149 million children under 5 years of age are estimated to be stunted (length more than 2 standard deviations below international growth standards) 1,2. Stunting, a form of linear growth faltering, increases the risk of illness, impaired cognitive development and mortality. Global stunting estimates rely on cross-sectional surveys, which cannot provide direct information about the timing of onset or persistence of growth faltering—a key consideration for defining critical windows to deliver preventive interventions. Here we completed a pooled analysis of longitudinal studies in low- and middle-income countries (n = 32 cohorts, 52,640 children, ages 0–24 months), allowing us to identify the typical age of onset of linear growth faltering and to investigate recurrent faltering in early life. The highest incidence of stunting onset occurred from birth to the age of 3 months, with substantially higher stunting at birth in South Asia. From 0 to 15 months, stunting reversal was rare; children who reversed their stunting status frequently relapsed, and relapse rates were substantially higher among children born stunted. Early onset and low reversal rates suggest that improving children’s linear growth will require life course interventions for women of childbearing age and a greater emphasis on interventions for children under 6 months of age

Causes and consequences of child growth faltering in low-resource settings

Growth faltering in children (low length for age or low weight for length) during the first 1,000 days of life (from conception to 2 years of age) influences short-term and long-term health and survival 1,2. Interventions such as nutritional supplementation during pregnancy and the postnatal period could help prevent growth faltering, but programmatic action has been insufficient to eliminate the high burden of stunting and wasting in low- and middle-income countries. Identification of age windows and population subgroups on which to focus will benefit future preventive efforts. Here we use a population intervention effects analysis of 33 longitudinal cohorts (83,671 children, 662,763 measurements) and 30 separate exposures to show that improving maternal anthropometry and child condition at birth accounted for population increases in length-for-age z-scores of up to 0.40 and weight-for-length z-scores of up to 0.15 by 24 months of age. Boys had consistently higher risk of all forms of growth faltering than girls. Early postnatal growth faltering predisposed children to subsequent and persistent growth faltering. Children with multiple growth deficits exhibited higher mortality rates from birth to 2 years of age than children without growth deficits (hazard ratios 1.9 to 8.7). The importance of prenatal causes and severe consequences for children who experienced early growth faltering support a focus on pre-conception and pregnancy as a key opportunity for new preventive interventions