Slippery runs, shifty stops, backward steps and forward hops: -2, -1, +1, +2, +5 and +6 Ribosomal frameshifting

Journal ArticleFrameshift mutations frequently express residual levels of gene activity; that is, they are often leaky. This leakiness can be used as a tool to define the functional components that affect the reading frame during gene expression. Recent technological advances in the capability to efficiently build synthetic DNA sequences have facilitated the construction of small, defined "frameshift windows." These windows are regions where frameshift events can be detected and measured. The cloned synthetic window is fused onto th 5' coding region of an active B-galactosidase gene that provides a sensitive monitor for the frameshift events. Fusions onto the lac Z gene have the advantages of simple colorimetric assays for B-galactosidase activity and little or no effect of the fused sequence on the specific activity or stability of the enzyme. A frameshift event also leaves a clue to its character in the protein sequence translated from the window's m-RNA sequence. Recovery of the frameshift containing B-galactosidase in sufficient yield and purity for determining its amino-terminal sequence provides hard evidence for the occurrence of a frameshift, and this sequence may be used to infer the kind of event generating the loss of reading frame

The interferon-inducible p47 (IRG) GTPases in vertebrates: loss of the cell autonomous resistance mechanism in the human lineage

BACKGROUND: Members of the p47 (immunity-related GTPases (IRG) family) GTPases are essential, interferon-inducible resistance factors in mice that are active against a broad spectrum of important intracellular pathogens. Surprisingly, there are no reports of p47 function in humans. RESULTS: Here we show that the p47 GTPases are represented by 23 genes in the mouse, whereas humans have only a single full-length p47 GTPase and an expressed, truncated presumed pseudo-gene. The human full-length gene is orthologous to an isolated mouse p47 GTPase that carries no interferon-inducible elements in the promoter of either species and is expressed constitutively in the mature testis of both species. Thus, there is no evidence for a p47 GTPase-based resistance system in humans. Dogs have several interferon-inducible p47s, and so the primate lineage that led to humans appears to have lost an ancient function. Multiple p47 GTPases are also present in the zebrafish, but there is only a tandem p47 gene pair in pufferfish. CONCLUSION: Mice and humans must deploy their immune resources against vacuolar pathogens in radically different ways. This carries significant implications for the use of the mouse as a model of human infectious disease. The absence of the p47 resistance system in humans suggests that possession of this resistance system carries significant costs that, in the primate lineage that led to humans, are not outweighed by the benefits. The origin of the vertebrate p47 system is obscure

Detection of Diabetic Foot Ulcers Using SVM Based Classification

Diabetic foot ulcers represent a significant health issue, for both patients’ quality of life and healthcare system costs. Currently, wound care is mainly based on visual assessment of wound size, which suffers from lack of accuracy and consistency. Hence, a more quantitative and computer-based method is needed. Supervised machine learning based object recognition is an attractive option, using training sample images with boundaries labeled by experienced clinicians. We use forty sample images collected from the UMASS Wound Clinic by tracking 8 subjects over 6 months with a smartphone camera. To maintain a consistent imaging environment and facilitate the capture process for patients with limited mobility, an image capture box was designed with two right angled front surface mirrors and LED lighting. We developed a novel foot ulcer recognition system using these sample images as our test data. Instead of operating at the pixel level, we use super-pixels, resulting from the quick shift algorithm, as the basic processing units. Then a support vector machine (SVM) based classifier is trained on the Bag-of-Words histogram representation of local Scale-Invariant Feature Transform (SIFT) features found in each super-pixel. As this classifier is very specific and the resulting histogram is very sparse, we merge the histograms from super-pixels in a size-specified neighborhood into one instance. Finally, to recover more precise boundaries of the foot ulcers, we apply conditional random field techniques to introduce new constraints that allow us to reduce misclassifications that occur near the edges of objects. Experimental results show that our method provides promising recognition results, outperforming the regular SVM-based classification as well as the sliding window based object recognition method when evaluated using the Matthew correlation coefficient (MCC). We are integrating these algorithms into the wound assessment module of our Android phone-based diabetic self-management app

Revising on the run or studying on the sofa: prospective associations between physical activity, sedentary behaviour, and exam results in British adolescents.

BACKGROUND: We investigated prospective associations between physical activity/sedentary behaviour (PA/SED) and General Certificate of Secondary Education (GCSE) results in British adolescents. METHODS: Exposures were objective PA/SED and self-reported sedentary behaviours (screen (TV, Internet, Computer Games)/non-screen (homework, reading)) measured in 845 adolescents (14·5y ± 0·5y; 43·6 % male). GCSE results at 16y were obtained from national records. Associations between exposures and academic performance (total exam points) were assessed using multilevel mixed-effects linear regression adjusted for mood, BMI z-score, deprivation, sex, season and school; potential interactions were investigated. RESULTS: PA was not associated with academic performance. One-hour more accelerometer-assessed SED was associated with (β(95 % CI)) 6·9(1·5,12·4) more GCSE points. An extra hour of screen time was associated with 9.3(-14·3,-4·3) fewer points whereas an extra hour of non-screen time (reading/homework) was associated with 23·1(14·6,31·6) more points. Screen time was still associated with poorer scores after adjusting for objective PA/SED and reading/homework. CONCLUSIONS: An extra hour/day of screen time at 14·5y is approximately equivalent to two fewer GCSE grades (e.g., from B to D) at 16y. Strategies to achieve the right balance between screen and non-screen time may be important for improving academic performance. Concerns that encouraging more physical activity may result in decreased academic performance seem unfounded.The work of Kirsten Corder, Andrew J Atkin, and Esther M F van Sluijs was supported, wholly or in part, by the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence (RES-590-28-0002). Funding from the British Heart Foundation, Department of Health, Economic and Social Research Council, Medical Research Council, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. The work of Kirsten Corder, Esther M F van Sluijs, Ulf Ekelund and Soren Brage was supported by the Medical Research Council (MC_UP_1001/2, MC_U106179473, MC_UU_12015/3). The ROOTS data collection was supported by a programme grant to Ian Goodyer 074296/Z/04/Z from the Wellcome Trust and by the Medical Research Council Epidemiology Unit. The funders had no role in preparation of this manuscript. We thank Rebekah Steele and Charlotte Ridgway for assistance during data collection, and Kate Westgate and Stefanie Mayle from the physical activity technical team, and Paul Collings from the Physical Activity Programme, at the MRC Epidemiology Unit for their assistance in processing Actiheart data.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s12966-015-0269-

TCR-engineered adoptive cell therapy effectively treats intracranial murine glioblastoma

BACKGROUND: Adoptive cellular therapies with chimeric antigen receptor T cells have revolutionized the treatment of some malignancies but have shown limited efficacy in solid tumors such as glioblastoma and face a scarcity of safe therapeutic targets. As an alternative, T cell receptor (TCR)-engineered cellular therapy against tumor-specific neoantigens has generated significant excitement, but there exist no preclinical systems to rigorously model this approach in glioblastoma. METHODS: We employed single-cell PCR to isolate a TCR specific for the Imp3 RESULTS: We isolated and characterized the 3×1.1C TCR that displayed a high affinity for mImp3 but no wild-type cross-reactivity. To provide a source of mImp3-specific T cells, we generated the MISTIC mouse. In a model of adoptive cellular therapy, the infusion of activated MISTIC T cells resulted in rapid intratumoral infiltration and profound antitumor effects with long-term cures in a majority of GL261-bearing mice. The subset of mice that did not respond to the adoptive cell therapy showed evidence of retained neoantigen expression but intratumoral MISTIC T cell dysfunction. The efficacy of MISTIC T cell therapy was lost in mice bearing a tumor with heterogeneous mImp3 expression, showcasing the barriers to targeted therapy in polyclonal human tumors. CONCLUSIONS: We generated and characterized the first TCR transgenic against an endogenous neoantigen within a preclinical glioma model and demonstrated the therapeutic potential of adoptively transferred neoantigen-specific T cells. The MISTIC mouse provides a powerful novel platform for basic and translational studies of antitumor T-cell responses in glioblastoma

Large‐scale modelling of deep‐diving cetacean habitats

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Single-cell profiling of human dura and meningioma reveals cellular meningeal landscape and insights into meningioma immune response

BACKGROUND: Recent investigations of the meninges have highlighted the importance of the dura layer in central nervous system immune surveillance beyond a purely structural role. However, our understanding of the meninges largely stems from the use of pre-clinical models rather than human samples. METHODS: Single-cell RNA sequencing of seven non-tumor-associated human dura samples and six primary meningioma tumor samples (4 matched and 2 non-matched) was performed. Cell type identities, gene expression profiles, and T cell receptor expression were analyzed. Copy number variant (CNV) analysis was performed to identify putative tumor cells and analyze intratumoral CNV heterogeneity. Immunohistochemistry and imaging mass cytometry was performed on selected samples to validate protein expression and reveal spatial localization of select protein markers. RESULTS: In this study, we use single-cell RNA sequencing to perform the first characterization of both non-tumor-associated human dura and primary meningioma samples. First, we reveal a complex immune microenvironment in human dura that is transcriptionally distinct from that of meningioma. In addition, we characterize a functionally diverse and heterogenous landscape of non-immune cells including endothelial cells and fibroblasts. Through imaging mass cytometry, we highlight the spatial relationship among immune cell types and vasculature in non-tumor-associated dura. Utilizing T cell receptor sequencing, we show significant TCR overlap between matched dura and meningioma samples. Finally, we report copy number variant heterogeneity within our meningioma samples. CONCLUSIONS: Our comprehensive investigation of both the immune and non-immune cellular landscapes of human dura and meningioma at single-cell resolution builds upon previously published data in murine models and provides new insight into previously uncharacterized roles of human dura