Big data driven detection of trees in suburban scenes using visual spectrum eye level photography

The aim of the work described in this paper is to detect trees in eye level view images. Unlike previous work that universally considers highly constrained environments, such as natural parks and wooded areas, or simple scenes with little clutter and clear tree separation, our focus is on much more challenging suburban scenes, which are rich in clutter and highly variable in type and appearance (houses, falls, shrubs, cars, bicycles, pedestrians, hydrants, lamp posts, etc.). Thus, we motivate and introduce three different approaches: (i) a conventional computer vision based approach, employing manually engineered steps and making use of explicit human knowledge of the application domain, (ii) a more machine learning oriented approach, which learns from densely extracted local features in the form of scale invariant features (SIFT), and (iii) a machine learning based approach, which employs both colour and appearance models as a means of making the most of available discriminative information. We also make a significant contribution in regards to the collection of training and evaluation data. In contrast to the existing work, which relies on manual data collection (thus risking unintended bias) or corpora constrained in variability and limited in size (thus not allowing for reliable generalisation inferences to be made), we show how large amounts of representative data can be collected automatically using freely available tools, such as Google’s Street View, and equally automatically processed to produce a large corpus of minimally biased imagery. Using a large data set collected in the manner and comprising tens of thousands of images, we confirm our theoretical arguments that motivated our machine learning based and colour-aware histograms of oriented gradients based method, which achieved a recall of 95% and precision of 97%.Publisher PDFPeer reviewe

Mechanisms of colorectal tumorigenesis associated with Mut-Y (MYH) deficiency and identification of novel predisposition genes in the multiple adenoma phenotype.

The main subjects of my thesis can be divided into three related areas. Firstly, determination of the mechanisms of tumoriogenesis associated with a recently identified, recessively inherited syndrome, AfrTZ-associated polyposis (MAP). MAP results from defective base excision repair (BER) caused by bi-allelic germline mutations in the human Mut-Y homologue (MUTYH, MYH) and leads to the development of colorectal adenomas and cancer. My work includes: further characterisation of the MAP phenotype completion of screening for mutations in other BER enzymes (OGG1 and MTH1) in individuals with multiple colorectal adenomas determination of the genetic pathway(s) involved in MAP tumorigenesis through studying loss of heterozygosity (LOH) and chromosomal abnormalities with array comparitive genomic hybridisation. A mouse model of MAP was developed as part of this thesis in order to study the development of intestinal adenomas from their earliest stages, and to evaluate the impact of environmental modification and chemopreventative therapies. Secondly, I determined to identify novel predisposition genes for the multiple adenoma phenotype. Up to fifty percent of individuals with multiple (5-100) colorectal adenomas (MCRAs) have no germline mutation in known predisposition genes (APC and MYH), but probably have a genetic origin. In these cases I determined to identify novel predisposition genes for the MCRA phenotype utilising various techniques. These included somatic screening of the adenomas for mutational signatures, expression array analysis of lymphoblastoid cell lines from these individuals and candidate gene approaches. Finally, I investigated the clonal origins of colorectal adenomas through studying adenomas from familial adenomatous polyposis (FAP), attenuated FAP (AFAP) and sporadic cases. In this thesis I developed a novel technique which utilises somatic APC mutations as clonal markers. This approach found 100% of FAP adenomas to be polyclonal and 100% of AFAP adenomas to be clonal in their origin

Tissue origin dictates mesenchymal stromal cell chemokine and chemokine receptor repertoire and predicts in vitro chemotactic activity under homeostatic and inflammatory conditions

Due to their anti-inflammatory and immunomodulatory properties, mesenchymal stromal cells (MSCs) are under intense investigation in many pre-clinical and clinical trials as a potential cellular therapy to be used in an array of clinical settings. The majority of the literature surrounding MSC phenotype and function is derived from studies focusing on bone marrow (BM) derived MSCs. Recently however, it has become apparent that MSCs can be isolated in a less invasive manner, from the majority of tissues in the human body. In light of this, many studies have been published promoting the use of alternative tissue sources for MSC isolation with no thorough standardised comparison of the phenotype or potential in vivo function of these MSCs. The advanced therapeutics department within the Scottish National Blood Transfusion Service (SNBTS) is involved in the development and optimisation of several cellular therapies including the use of MSCs within various clinical settings. SNBTS has access to fully consented human tissues rich in MSCs including; pancreatic islets, visceral adipose tissue, liposuction aspirate, bone marrow and umbilical cord. Therefore this study aimed to objectively compare the phenotype and potential in vivo function of MSCs isolated from the aforementioned tissues in a stringent, standardised manner in order to assess if MSCs isolated from one specific tissue source might be optimal for use within the clinic. The beneficial therapeutic effect of MSCs often depends on their ability to migrate to target tissues and interact with residing or migratory immune and non-immune cells, frequently within an inflammatory environment. Therefore this study focussed on how MSCs might migrate in vivo by assessing and comparing MSC chemokine receptor expression, whilst also assessing and comparing MSC chemokine secretion profiles to understand which immune cells MSCs might attract, and therefore potentially interact with, in vivo. This study found that chemokine receptor expression by MSCs isolated from islet, visceral adipose, adipose, bone marrow and umbilical cord tissues was very low, with CXCR4, CCR7 and ACKR3 expression being restricted to visceral adipose and bone marrow derived MSCs. Inflammatory chemokines were secreted at very high levels by MSCs isolated from all of the aforementioned tissues, which induced migration of target immune cells towards all MSCs tested in vitro and in vivo, importantly however, the tissue origin of MSCs dictated the quantities of immune cells attracted. This study highlighted that the tissue origin of MSCs could affect MSC in vivo migratory capacity and their ability to chemoattract surrounding immune cells, thereby potentially influencing their clinical performance

Expression of somatostatin receptors 2 and 5 in circulating tumour cells from patients with neuroendocrine tumours.

BACKGROUND: Neuroendocrine tumours (NET) overexpress somatostatin receptors (SSTR) that can be targeted for therapy. Somatostatin receptor expression is routinely measured by molecular imaging but the resolution is insufficient to define heterogeneity. We hypothesised that SSTR expression could be measured on circulating tumour cells (CTCs) and used to investigate heterogeneity of expression and track changes during therapy. METHODS: MCF-7 cells were transfected with SSTR2 or 5 and spiked into donor blood for analysis by CellSearch. Optimum anti-SSTR antibody concentration and exposure time were determined, and flow cytometry was used to evaluate assay sensitivity. For clinical evaluation, blood was analysed by CellSearch, and SSTR2/5 immunohistochemistry was performed on matched tissue samples. RESULTS: Flow cytometry confirmed CellSearch was sensitive and that detection of SSTR was unaffected by the presence of somatostatin analogue up to a concentration of 100 ng ml(-l). Thirty-one NET patients were recruited: grade; G1 (29%), G2 (45%), G3 (13%), primary site; midgut (58%), pancreatic (39%). Overall, 87% had SSTR-positive tumours according to somatostatin receptor scintigraphy or 68-Ga-DOTATE PET/CT. Circulating tumour cells were detected in 21 out of 31 patients (68%), of which 33% had evidence of heterogeneous expression of either SSTR2 (n=5) or SSTR5 (n=2). CONCLUSIONS: Somatostatin receptors 2 and 5 are detectable on CTCs from NET patients and may be a useful biomarker for evaluating SSTR-targeted therapies and this is being prospectively evaluated in the Phase IV CALMNET trial (NCT02075606)

A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution

Bulk-tissue DNA methylomes represent an average over many different cell types, hampering our understanding of cell-type-specific contributions to disease development. As single-cell methylomics is not scalable to large cohorts of individuals, cost-effective computational solutions are needed, yet current methods are limited to tissues such as blood. Here we leverage the high-resolution nature of tissue-specific single-cell RNA-sequencing datasets to construct a DNA methylation atlas defined for 13 solid tissue types and 40 cell types. We comprehensively validate this atlas in independent bulk and single-nucleus DNA methylation datasets. We demonstrate that it correctly predicts the cell of origin of diverse cancer types and discovers new prognostic associations in olfactory neuroblastoma and stage 2 melanoma. In brain, the atlas predicts a neuronal origin for schizophrenia, with neuron-specific differential DNA methylation enriched for corresponding genome-wide association study risk loci. In summary, the DNA methylation atlas enables the decomposition of 13 different human tissue types at a high cellular resolution, paving the way for an improved interpretation of epigenetic data

Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis : a cohort study in the UK Biobank

Background Prostate cancer is highly heritable, with >250 common variants associated in genome-wide association studies. It commonly presents with non-specific lower urinary tract symptoms that are frequently associated with benign conditions. Methods Cohort study using UK Biobank data linked to primary care records. Participants were men with a record showing a general practice consultation for a lower urinary tract symptom. The outcome measure was prostate cancer diagnosis within 2 years of consultation. The predictor was a genetic risk score of 269 genetic variants for prostate cancer. Results A genetic risk score (GRS) is associated with prostate cancer in symptomatic men (OR per SD increase = 2.12 [1.86-2.41] P = 3.5e-30). An integrated risk model including age and GRS applied to symptomatic men predicted prostate cancer (AUC 0.768 [0.739-0.796]). Prostate cancer incidence was 8.1% (6.7-9.7) in the highest risk quintile. In the lowest quintile, prostate cancer incidence was Conclusions This study is the first to apply GRS in primary care to improve the triage of symptomatic patients. Men with the lowest genetic risk of developing prostate cancer could safely avoid invasive investigation, whilst those identified with the greatest risk could be fast-tracked for further investigation. These results show that a GRS has potential application to improve the diagnostic pathway of symptomatic patients in primary care.Peer reviewe

High-Grade Gastroenteropancreatic Neuroendocrine Neoplasms and Improved Prognostic Stratification With the New World Health Organization 2019 Classification A Validation Study From a Single-Institution Retrospective Analysis

Objectives: There is a pressing need to develop clinical management pathways for grade 3 (G3) gastroenteropancreatic neuroendocrine neoplasms (GEP NEN). Methods: We performed a retrospective study on patients with metastatic G3 GEP NEN. The relationship between baseline characteristics and progression-free survival and overall survival was analyzed using the Kaplan-Meier method. Univariate and multivariate analyses were performed using the Cox proportional hazards model. Results: We included 142 patients (74 well-differentiated neuroendocrine tumors [WDNETs], 68 poorly differentiated neuroendocrine carcinomas [PDNECs]). Patients with WDNET had prolonged survival compared with PDNEC (median, 24 vs 15 months, P = 0.0001), which persisted in both pancreatic and nonpancreatic cohorts. Well-differentiated morphology, Ki-67 <50% and positive somatostatin receptor imaging were independently associated with prolonged survival. Of the subgroup treated with first-line platinum-based chemotherapy, response rates were favorable (partial response, 47%; stable disease, 30%); there was no significant difference in response rates nor progression-free survival between WDNET and PDNEC despite significantly prolonged overall survival in the WDNET cohort. Conclusions: Our study corroborates the knowledge of 2 prognostically distinct subgroups within the World Health Organization 2019 G3 GEP NEN population, observed in both pancreatic and nonpancreatic gastrointestinal cohorts. Definitive management pathways are needed to reflect the differences between G3 WDNET and PDNEC