Estimating the number of faults: efficiency of removal, recapture, and seeding

Various experimental designs for estimating the number of faults in a system are studied including: (1) removal of each fault as it is detected; (2) marking of each fault as it is detected; and (3) introduction of a known number of faults into the system followed by (1) or (2). A unified framework is developed for comparing these designs; it also produces simplified estimators having high efficiency relative to maximum likelihood estimators. The designs are compared in terms of: (1) statistical accuracy; and (2) the number of failures that need to occur to achieve a given accuracy. On the basis of these comparisons, some general recommendations are made on the level of seeding as well as the choice of removal or recapture designs. When the testing effort is sufficient so that roughly two thirds of the faults are detected, the removal-design is preferred over the recapture-design, and there are no gains from seeding. However, this conclusion depends on assigning unit cost to all fault detections, which might not always be reasonable.published_or_final_versio

Mammary Stem Cells: Premise, Properties, and Perspectives

Adult mammary stem cells (MaSCs) drive postnatal organogenesis and remodeling in the mammary gland, and their longevity and potential have important implications for breast cancer. However, despite intense investigation the identity, location, and differentiation potential of MaSCs remain subject to deliberation. The application of genetic lineage-tracing models, combined with quantitative 3D imaging and biophysical methods, has provided new insights into the mammary epithelial hierarchy that challenge classical definitions of MaSC potency and behaviors. We review here recent advances - discussing fundamental unresolved properties of MaSC potency, dynamics, and plasticity - and point to evolving technologies that promise to shed new light on this intractable debate. Elucidation of the physiological mammary differentiation hierarchy is paramount to understanding the complex heterogeneous breast cancer landscape.his work was supported by the Medical Research Council ( MR/J001023/1 to C.J.W. and B.L-L.), the Wellcome Trust ( 105377/Z/14/Z to O.B.H.), the National Health and Medical Research Council ( 1071074 to F.M.D.), and a University of Queensland Early Career Researcher Grant ( UQECR1718865 to F.M.D.)

Beyond “planning”: A meta-analysis of implementation intentions to support smoking cessation

Objective: Implementation intentions support behavior change by encouraging people to link critical situations with appropriate responses. Overall effectiveness for smoking cessation is unknown. This systematic review and meta-analysis aimed to evaluate the effectiveness of implementation intentions for smoking cessation. Method: Using PRISMA guidelines, 6 electronic databases were searched (updated February 2018) using key terms. Data were pooled for smoking cessation (categorical variable; yes/no) and entered into random effects models. Analyses assessed: (a) effectiveness as a single intervention, and (b) effectiveness when included as one of multiple intervention components. Results: Twelve studies were identified. Implementation intentions were effective for smoking cessation at follow up, OR = 1.70, CI [1.32, 2.20], p < .001, average 10.7% quit rate for intervention participants (4.9% in controls). Implementation intentions as a single intervention were effective for smoking cessation, OR = 5.69, 95% CI [1.39, 23.25], p = .02 (average quit rate 14.3% in intervention participants vs. 3.6% in controls) and as part of multicomponent interventions, OR = 1.67, 95% CI [1.29, 1.66], p < .001 (average quit rate 8.2% in intervention participants vs. 5.8% in controls). Conclusions: Implementation intentions are effective at helping smokers quit although the review reported substantial heterogeneity across the limited number of included studies. The present review sets the agenda for future research in this area including longer term objectively verified abstinence and identification of potential moderators of effectiveness including population characteristics

Single-cell lineage tracing in the mammary gland reveals stochastic clonal dispersion of stem/progenitor cell progeny.

The mammary gland undergoes cycles of growth and regeneration throughout reproductive life, a process that requires mammary stem cells (MaSCs). Whilst recent genetic fate-mapping studies using lineage-specific promoters have provided valuable insights into the mammary epithelial hierarchy, the true differentiation potential of adult MaSCs remains unclear. To address this, herein we utilize a stochastic genetic-labelling strategy to indelibly mark a single cell and its progeny in situ, combined with tissue clearing and 3D imaging. Using this approach, clones arising from a single parent cell could be visualized in their entirety. We reveal that clonal progeny contribute exclusively to either luminal or basal lineages and are distributed sporadically to branching ducts or alveoli. Quantitative analyses suggest that pools of unipotent stem/progenitor cells contribute to adult mammary gland development. Our results highlight the utility of tracing a single cell and reveal that progeny of a single proliferative MaSC/progenitor are dispersed throughout the epithelium.This work was supported by a grant from the Medical Research Council programme grant no. MR/J001023/1 (B.L-L. and C.J.W). F.M.D. was funded by a National Health and Medical Research Council CJ Martin Biomedical Fellowship (GNT1071074). O.B.H. was funded by a Wellcome Trust PhD studentship (105377/Z/14/Z)

Enhanced IL-2 in early life limits the development of TFH and protective antiviral immunity

T follicular helper cell (TFH)-dependent antibody responses are critical for long-term immunity. Antibody responses are diminished in early life, limiting long-term protective immunity and allowing prolonged or recurrent infection, which may be important for viral lung infections that are highly prevalent in infancy. In a murine model using respiratory syncytial virus (RSV), we show that TFH and the high-affinity antibody production they promote are vital for preventing disease on RSV reinfection. Following a secondary RSV infection, TFH-deficient mice had significantly exacerbated disease characterized by delayed viral clearance, increased weight loss, and immunopathology. TFH generation in early life was compromised by heightened IL-2 and STAT5 signaling in differentiating naive T cells. Neutralization of IL-2 during early-life RSV infection resulted in a TFH-dependent increase in antibody-mediated immunity and was sufficient to limit disease severity upon reinfection. These data demonstrate the importance of TFH in protection against recurrent RSV infection and highlight a mechanism by which this is suppressed in early life

Conservation implications and opportunities of mining activities for terrestrial mammal habitat

Mining companies increasingly commit to a net positive impact on biodiversity. However, assessing the industry's progress toward achieving this goal is limited by knowledge of current mining threats to biodiversity and the relevant opportunities available for them to improve conservation outcomes. Here, we investigate the global exposure of terrestrial mammal habitat to mining activities, revealing the 136 species with &gt; 30% of their habitat within 10 km of a mining property or exploration site. One third (n = 42) of these species are already threatened with extinction according to the International Union for Conservation of Nature (IUCN), suggesting projected increased demand for minerals may push some species beyond critical thresholds. Moreover, 28% (n = 33) of species are Data Deficient, illustrating tangible ways for industry to fill current knowledge gaps. However, large discrepancies between our results and the species currently listed as threatened by mining in the IUCN Red List, suggest other species may be at risk and that conservation tools and analyses based on these data may underestimate the benefits of averting such threats. We recommend ways to better capture mining threats to species within IUCN Red List assessments and discuss how these changes could improve conservation outcomes in mineral-rich areas

The Genetics of Inherited Cholestatic Disorders in Neonates and Infants: Evolving Challenges

Many inherited conditions cause cholestasis in the neonate or infant. Next-generation sequencing methods can facilitate a prompt diagnosis in some of these cases; application of these methods in patients with liver diseases of unknown cause has also uncovered novel gene-disease associations and improved our understanding of physiological bile secretion and flow. By helping to define the molecular basis of certain cholestatic disorders, these methods have also identified new targets for therapy as well patient subgroups more likely to benefit from specific therapies. At the same time, sequencing methods have presented new diagnostic challenges, such as the interpretation of single heterozygous genetic variants. This article discusses those challenges in the context of neonatal and infantile cholestasis, focusing on difficulties in predicting variant pathogenicity, the possibility of other causal variants not identified by the genetic screen used, and phenotypic variability among patients with variants in the same genes. A prospective, observational study performed between 2010–2013, which sequenced six important genes (ATP8B1, ABCB11, ABCB4, NPC1, NPC2 and SLC25A13) in an international cohort of 222 patients with infantile liver disease, is given as an example of potential benefits and challenges that clinicians could face having received a complex genetic result. Further studies including large cohorts of patients with paediatric liver disease are needed to clarify the spectrum of phenotypes associated with, as well as appropriate clinical response to, single heterozygous variants in cholestasis-associated genes

Assessing rotation-invariant feature classification for automated wildebeest population counts

Accurate and on-demand animal population counts are the holy grail for wildlife conservation organizations throughout the world because they enable fast and responsive adaptive management policies. While the collection of image data from camera traps, satellites, and manned or unmanned aircraft has advanced significantly, the detection and identification of animals within images remains a major bottleneck since counting is primarily conducted by dedicated enumerators or citizen scientists. Recent developments in the field of computer vision suggest a potential resolution to this issue through the use of rotation-invariant object descriptors combined with machine learning algorithms. Here we implement an algorithm to detect and count wildebeest from aerial images collected in the Serengeti National Park in 2009 as part of the biennial wildebeest count. We find that the per image error rates are greater than, but comparable to, two separate human counts. For the total count, the algorithm is more accurate than both manual counts, suggesting that human counters have a tendency to systematically over or under count images. While the accuracy of the algorithm is not yet at an acceptable level for fully automatic counts, our results show this method is a promising avenue for further research and we highlight specific areas where future research should focus in order to develop fast and accurate enumeration of aerial count data. If combined with a bespoke image collection protocol, this approach may yield a fully automated wildebeest count in the near future.CJT is supported by a Complex Systems Scholar Award from the James S. McDonnell Foundation. JGCH is supported by a Lord Kelvin Adam Smith Fellowship, funding from the British Ecological Society and the European Union’s Horizon 2020 research and innovation programme under grant agreement No 641918 AfricanBioServices. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

A Copine family member, Cpne8, is a candidate quantitative trait gene for prion disease incubation time in mouse

Prion disease incubation time in mice is determined by many factors including genetic background. The prion gene itself plays a major role in incubation time; however, other genes are also known to be important. Whilst quantitative trait loci (QTL) studies have identified multiple loci across the genome, these regions are often large, and with the exception of Hectd2 on Mmu19, no quantitative trait genes or nucleotides for prion disease incubation time have been demonstrated. In this study, we use the Northport heterogeneous stock of mice to reduce the size of a previously identified QTL on Mmu15 from approximately 25 to 1.2 cM. We further characterised the genes in this region and identify Cpne8, a member of the copine family, as the most promising candidate gene. We also show that Cpne8 mRNA is upregulated at the terminal stage of disease, supporting a role in prion disease. Applying these techniques to other loci will facilitate the identification of key pathways in prion disease pathogenesis