Hand classification of fMRI ICA noise components

We present a practical "how-to" guide to help determine whether single-subject fMRI independent components (ICs) characterise structured noise or not. Manual identification of signal and noise after ICA decomposition is required for efficient data denoising: to train supervised algorithms, to check the results of unsupervised ones or to manually clean the data. In this paper we describe the main spatial and temporal features of ICs and provide general guidelines on how to evaluate these. Examples of signal and noise components are provided from a wide range of datasets (3T data, including examples from the UK Biobank and the Human Connectome Project, and 7T data), together with practical guidelines for their identification. Finally, we discuss how the data quality, data type and preprocessing can influence the characteristics of the ICs and present examples of particularly challenging datasets

Analysis of the Macaca mulatta transcriptome and the sequence divergence between Macaca and human

We report the initial sequencing and comparative analysis of the Macaca mulatta transcriptome. Cloned sequences from 11 tissues, nine animals, and three species (M. mulatta, M. fascicularis, and M. nemestrina) were sampled, resulting in the generation of 48,642 sequence reads. These data represent an initial sampling of the putative rhesus orthologs for 6,216 human genes. Mean nucleotide diversity within M. mulatta and sequence divergence among M. fascicularis, M. nemestrina, and M. mulatta are also reported

The structural basis for the specificity of pyridinylimidazole inhibitors of p38 MAP kinase

AbstractBackground: The p38 mitogen-activated protein (MAP) kinase regulates signal transduction in response to environmental stress. Pyridinylimidazole compounds are specific inhibitors of p38 MAP kinase that block the production of the cytokines interleukin-1 β and tumor necrosis factor α, and they are effective in animal models of arthritis, bone resorption and endotoxin shock. These compounds have been useful probes for studying the physiological functions of the p38-mediated MAP kinase pathway.Results: We report the crystal structure of a novel pyridinylimidazole compound complexed with p38 MAP kinase, and we demonstrate that this compound binds to the same site on the kinase as does ATP. Mutagenesis showed that a single residue difference between p38 MAP kinase and other MAP kinases is sufficient to confer selectivity among pyridinylimidazole compounds.Conclusions: Our results reveal how pyridinylimidazole compounds are potent and selective inhibitors of p38 MAP kinase but not other MAP kinases. It should now be possible to design other specific inhibitors of activated p38 MAP kinase using the structure of the nonphosphorylated enzyme

ICAM-reg: Interpretable Classification and Regression with Feature Attribution for Mapping Neurological Phenotypes in Individual Scans

Feature attribution (FA), or the assignment of class-relevance to different locations in an image, is important for many classification and regression problems but is particularly crucial within the neuroscience domain, where accurate mechanistic models of behaviours, or disease, require knowledge of all features discriminative of a trait. At the same time, predicting class relevance from brain images is challenging as phenotypes are typically heterogeneous, and changes occur against a background of significant natural variation. Here, we present an extension of the ICAM framework for creating prediction specific FA maps through image-to-image translation

ICAM-reg: Interpretable Classification and Regression with Feature Attribution for Mapping Neurological Phenotypes in Individual Scans

An important goal of medical imaging is to be able to precisely detect patterns of disease specific to individual scans; however, this is challenged in brain imaging by the degree of heterogeneity of shape and appearance. Traditional methods, based on image registration to a global template, historically fail to detect variable features of disease, as they utilise population-based analyses, suited primarily to studying group-average effects. In this paper we therefore take advantage of recent developments in generative deep learning to develop a method for simultaneous classification, or regression, and feature attribution (FA). Specifically, we explore the use of a VAE-GAN translation network called ICAM, to explicitly disentangle class relevant features from background confounds for improved interpretability and regression of neurological phenotypes. We validate our method on the tasks of Mini-Mental State Examination (MMSE) cognitive test score prediction for the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, as well as brain age prediction, for both neurodevelopment and neurodegeneration, using the developing Human Connectome Project (dHCP) and UK Biobank datasets. We show that the generated FA maps can be used to explain outlier predictions and demonstrate that the inclusion of a regression module improves the disentanglement of the latent space. Our code is freely available on Github https://github.com/CherBass/ICAM

Post-release reforms for short prison sentences: re-legitimising and widening the net of punishment

Transforming Rehabilitation (TR) promised a ‘revolution’ in the way offenders are managed, providing a renewed focus on short sentence prisoners. The TR reforms extends mandatory post-release supervision and tailored through-the-gate resettlement provisions to a group that has predominately faced a ‘history of neglect’ yet often present with the most acute needs within the criminal justice system. However, existing literature underlines that serving short sentences lack ‘utility’ and can be counter-productive to facilitating effective rehabilitation. This article explores the purposes of providing post release supervision for short sentences, firstly exploring a previous attempt to reform short sentences; (the now defunct) ‘Custody Plus’ within the 2003 Criminal Justice Act and then the Offender Rehabilitation Act 2014 within the TR reforms. This article contends that both post release reforms have sought to re-affirm and re-legitimise prison as the dominant form of punishment in society- or what Carlen refers to as ‘carceral clawback’. This article will also use Cohen’s analysis on social control to establish that post release supervision will serve to ‘widen the net’ extend the period of punishment and oversight and will only reinforce a form of enforced ‘state obligated rehabilitation’ that will undermine efforts made to resettle short sentence prisoners

A Case Report Demonstrating How the Clinical Presentation of the Diffuse Sclerosing Variant of Papillary Thyroid Carcinoma Can Mimic Benign Riedel’s Thyroiditis

A 44-year-old female presented with a two-month history of a neck mass, sore throat, hoarseness, and intermittent dysphagia. Examination revealed a “woody” hard swelling arising from the right lobe of the thyroid. Clinically this was felt to be classical Riedel’s thyroiditis (RT). Thyroid ultrasound showed a diffusely enlarged, low echogenicity thyroid with a multinodular goitre. An abnormal nodule extending across the isthmus was noted. Following a nondiagnostic fine needle aspiration, an open core biopsy was performed. This showed dense sclerotic fibrosis punctuated by nodular mononuclear inflammatory cells, which obscured follicular epithelial cells consistent with a fibrosing thyroiditis (Riedel’s thyroiditis). A biopsy of pretracheal lymph nodes showed a sclerotic process throughout the lymph nodes and nests of epithelium bands with squamous differentiation obscured by a fibrous process. These findings raised the differential diagnosis of diffuse sclerosing variant of papillary thyroid carcinoma (DSV-PTC) with metastasis to lymph nodes. A total thyroidectomy and pretracheal lymph node dissection were performed. The final histological diagnosis was DSV-PTC. When managing a patient with presumed RT it is important to consider malignancy in the differential. DSV-PTC is one of the more aggressive forms of thyroid cancer but with early diagnosis and appropriate treatment patients may have excellent outcomes

Protocol optimization of a targeted sequencing panel for genomic profiling of bronchoalveolar lavage fluid in lung cancer

Abstract Introduction We investigated a commercially available sequencing panel to study the effect of sequencing depth, variant calling strategy, and targeted sequencing region on identifying tumor‐derived variants in cell‐free bronchoalveolar lavage (cfBAL) DNA compared with plasma cfDNA. Methods Sequencing was performed at low or high coverage using two filtering algorithms to identify tumor variants on two panels targeting 77 and 197 genes respectively. Results One hundred and four sequencing files from 40 matched DNA samples of cfBAL, plasma, germline leukocytes, and archival tumor specimens in 10 patients with early‐stage lung cancer were analyzed. By low‐coverage sequencing, tumor‐derived cfBAL variants were detected in 5/10 patients (50%) compared with 2/10 (20%) for plasma. High‐coverage sequencing did not affect the number of tumor‐derived variants detected in either biospecimen type. Accounting for germline mutations eliminated false‐positive plasma calls regardless of coverage (0/10 patients with tumor‐derived variants identified) and increased the number of cfBAL calls (5/10 patients with tumor‐derived variants identified). These results were not affected by the number of targeted genes

Integrative proteomic analysis of serum and peritoneal fluids helps identify proteins that are up-regulated in serum of women with ovarian cancer.

We used intensive modern proteomics approaches to identify predictive proteins in ovary cancer. We identify up-regulated proteins in both serum and peritoneal fluid. To evaluate the overall performance of the approach we track the behavior of 20 validated markers across these experiments.Mass spectrometry based quantitative proteomics following extensive protein fractionation was used to compare serum of women with serous ovarian cancer to healthy women and women with benign ovarian tumors. Quantitation was achieved by isotopically labeling cysteine amino acids. Label-free mass spectrometry was used to compare peritoneal fluid taken from women with serous ovarian cancer and those with benign tumors. All data were integrated and annotated based on whether the proteins have been previously validated using antibody-based assays.We selected 54 quantified serum proteins and 358 peritoneal fluid proteins whose case-control differences exceeded a predefined threshold. Seventeen proteins were quantified in both materials and 14 are extracellular. Of 19 validated markers that were identified all were found in cancer peritoneal fluid and a subset of 7 were quantified in serum, with one of these proteins, IGFBP1, newly validated here.Proteome profiling applied to symptomatic ovarian cancer cases identifies a large number of up-regulated serum proteins, many of which are or have been confirmed by immunoassays. The number of currently known validated markers is highest in peritoneal fluid, but they make up a higher percentage of the proteins observed in both serum and peritoneal fluid, suggesting that the 10 additional markers in this group may be high quality candidates