Bayesian sequential experimental design for binary response data with application to electromyographic experiments

We develop a sequential Monte Carlo approach for Bayesian analysis of the experimental design for binary response data. Our work is motivated by surface electromyographic (SEMG) experiments, which can be used to provide information about the functionality of subjects' motor units. These experiments involve a series of stimuli being applied to a motor unit, with whether or not the motor unit res for each stimulus being recorded. The aim is to learn about how the probability of ring depends on the applied stimulus (the so-called stimulus response curve); One such excitability parameter is an estimate of the stimulus level for which the motor unit has a 50% chance of ring. Within such an experiment we are able to choose the next stimulus level based on the past observations. We show how sequential Monte Carlo can be used to analyse such data in an online manner. We then use the current estimate of the posterior distribution in order to choose the next stimulus level. The aim is to select a stimulus level that mimimises the expected loss. We will apply this loss function to the estimates of target quantiles from the stimulus-response curve. Through simulation we show that this approach is more ecient than existing sequential design methods for choosing the stimulus values. If applied in practice, it could more than halve the length of SEMG experiments

INTEGRAL/SPI data segmentation to retrieve sources intensity variations

International audienceContext. The INTEGRAL/SPI, X/γ-ray spectrometer (20 keV–8 MeV) is an instrument for which recovering source intensity variations is not straightforward and can constitute a difficulty for data analysis. In most cases, determining the source intensity changes between exposures is largely based on a priori information.Aims. We propose techniques that help to overcome the difficulty related to source intensity variations, which make this step more rational. In addition, the constructed “synthetic” light curves should permit us to obtain a sky model that describes the data better and optimizes the source signal-to-noise ratios.Methods. For this purpose, the time intensity variation of each source was modeled as a combination of piecewise segments of time during which a given source exhibits a constant intensity. To optimize the signal-to-noise ratios, the number of segments was minimized. We present a first method that takes advantage of previous time series that can be obtained from another instrument on-board the INTEGRAL observatory. A data segmentation algorithm was then used to synthesize the time series into segments. The second method no longer needs external light curves, but solely SPI raw data. For this, we developed a specific algorithm that involves the SPI transfer function.Results. The time segmentation algorithms that were developed solve a difficulty inherent to the SPI instrument, which is the intensity variations of sources between exposures, and it allows us to obtain more information about the sources’ behavior

Oncogene-dependent apoptosis in extracts from drug-resistant cells

Many genotoxic agents kill tumor cells by inducing apoptosis; hence, mutations that suppress apoptosis produce resistance to chemotherapy. Although directly activating the apoptotic machinery may bypass these mutations, how to achieve this activation in cancer cells selectively is not clear. In this study, we show that the drug-resistant 293 cell line is unable to activate components of the apoptotic machinery-the ICE-like proteases (caspases)-following treatment with an anticancer drug. Remarkably, extracts from untreated cells spontaneously activate caspases and induce apoptosis in a cell-free system, indicating that drug-resistant cells have not only the apoptotic machinery but also its activator. Comparing extracts from cells with defined genetic differences, we show that this activator is generated by the adenovirus E1A oncogene and is absent from normal cells. We provide preliminary characterization of this oncogene generated activity (OGA) and show that partially purified OGA activates caspases when added to extracts from untransformed cells. We suggest that agents that link OGA to caspases in cells would kill tumor cells otherwise resistant to conventional cancer therapy. As this killing relies on an activity generated by an oncogene, the effect of these agents should be selective for transformed cells

Kernel Sequential Monte Carlo

We propose kernel sequential Monte Carlo (KSMC), a framework for sampling from static target densities. KSMC is a family of sequential Monte Carlo algorithms that are based on building emulator models of the current particle system in a reproducing kernel Hilbert space. We here focus on modelling nonlinear covariance structure and gradients of the target. The emulator’s geometry is adaptively updated and subsequently used to inform local proposals. Unlike in adaptive Markov chain Monte Carlo, continuous adaptation does not compromise convergence of the sampler. KSMC combines the strengths of sequental Monte Carlo and kernel methods: superior performance for multimodal targets and the ability to estimate model evidence as compared to Markov chain Monte Carlo, and the emulator’s ability to represent targets that exhibit high degrees of nonlinearity. As KSMC does not require access to target gradients, it is particularly applicable on targets whose gradients are unknown or prohibitively expensive. We describe necessary tuning details and demonstrate the benefits of the the proposed methodology on a series of challenging synthetic and real-world examples

Legacy of COVID‐19 – the opportunity to enhance surgical services for patients with colorectal disease

Description to be added.Cannot be left empt

Mosaic DNA imports with interspersions of recipient sequence after natural transformation of Helicobacter pylori

Helicobacter pylori colonizes the gastric mucosa of half of the human population, causing gastritis, ulcers, and cancer. H. pylori is naturally competent for transformation by exogenous DNA, and recombination during mixed infections of one stomach with multiple H. pylori strains generates extensive allelic diversity. We developed an in vitro transformation protocol to study genomic imports after natural transformation of H. pylori. The mean length of imported fragments was dependent on the combination of donor and recipient strain and varied between 1294 bp and 3853 bp. In about 10% of recombinant clones, the imported fragments of donor DNA were interrupted by short interspersed sequences of the recipient (ISR) with a mean length of 82 bp. 18 candidate genes were inactivated in order to identify genes involved in the control of import length and generation of ISR. Inactivation of the antimutator glycosylase MutY increased the length of imports, but did not have a significant effect on ISR frequency. Overexpression of mutY strongly increased the frequency of ISR, indicating that MutY, while not indispensable for ISR formation, is part of at least one ISR-generating pathway. The formation of ISR in H. pylori increases allelic diversity, and contributes to the uniquely low linkage disequilibrium characteristic of this pathogen

Genome-wide fine-scale recombination rate variation in Drosophila melanogaster

Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and diversity

Wnt signalling in adenomas of familial adenomatous polyposis patients

BACKGROUND: Epigenetic silencing of Wnt antagonists and expression changes in genes associated with Wnt response pathways occur in early sporadic colorectal tumourigenesis, indicating that tumour cells are more sensitive to Wnt growth factors and respond differently. In this study, we have investigated whether similar changes occur in key markers of the Wnt response pathways in the genetic form of the disease, familial adenomatous polyposis (FAP). METHODS: We investigated epigenetic and expression changes using pyrosequencing and real-time RT-PCR in samples from seven patients without neoplasia, and matched normal and tumour tissues from 22 sporadic adenoma and 14 FAP patients. RESULTS: We found that 17 out of 24 (71%) FAP adenomas were hypermethylated at sFRP1, compared with 20 out of 22 (91%) of sporadic cases. This was reflected at the level of sFRP1 transcription, where 73% of FAP and 100% of sporadic cases were downregulated. Increased expression levels of c-myc and FZD3 were less common in FAP (35 and 46% respectively) than sporadic tumours (78 and 67% respectively). CONCLUSION: Overall, the changes in expression and methylation were comparable, although the degree of change was generally lower in the FAP adenomas. Molecular heterogeneity between multiple adenomas from individual FAP patients may reflect different developmental fates for these premalignant tumours

Critical research gaps and recommendations to inform research prioritisation for more effective prevention and improved outcomes in colorectal cancer

OBJECTIVE: Colorectal cancer (CRC) leads to significant morbidity/mortality worldwide. Defining critical research gaps (RG), their prioritisation and resolution, could improve patient outcomes.DESIGN: RG analysis was conducted by a multidisciplinary panel of patients, clinicians and researchers (n=71). Eight working groups (WG) were constituted: discovery science; risk; prevention; early diagnosis and screening; pathology; curative treatment; stage IV disease; and living with and beyond CRC. A series of discussions led to development of draft papers by each WG, which were evaluated by a 20-strong patient panel. A final list of RGs and research recommendations (RR) was endorsed by all participants.RESULTS: Fifteen critical RGs are summarised below: RG1: Lack of realistic models that recapitulate tumour/tumour micro/macroenvironment; RG2: Insufficient evidence on precise contributions of genetic/environmental/lifestyle factors to CRC risk; RG3: Pressing need for prevention trials; RG4: Lack of integration of different prevention approaches; RG5: Lack of optimal strategies for CRC screening; RG6: Lack of effective triage systems for invasive investigations; RG7: Imprecise pathological assessment of CRC; RG8: Lack of qualified personnel in genomics, data sciences and digital pathology; RG9: Inadequate assessment/communication of risk, benefit and uncertainty of treatment choices; RG10: Need for novel technologies/interventions to improve curative outcomes; RG11: Lack of approaches that recognise molecular interplay between metastasising tumours and their microenvironment; RG12: Lack of reliable biomarkers to guide stage IV treatment; RG13: Need to increase understanding of health related quality of life (HRQOL) and promote residual symptom resolution; RG14: Lack of coordination of CRC research/funding; RG15: Lack of effective communication between relevant stakeholders.CONCLUSION: Prioritising research activity and funding could have a significant impact on reducing CRC disease burden over the next 5 years.</p

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis