Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images

Endoscopy is a widely used imaging modality to diagnose and treat diseases in hollow organs as for example the gastrointestinal tract, the kidney and the liver. However, due to varied modalities and use of different imaging protocols at various clinical centers impose significant challenges when generalising deep learning models. Moreover, the assembly of large datasets from different clinical centers can introduce a huge label bias that renders any learnt model unusable. Also, when using new modality or presence of images with rare patterns, a bulk amount of similar image data and their corresponding labels are required for training these models. In this work, we propose to use a few-shot learning approach that requires less training data and can be used to predict label classes of test samples from an unseen dataset. We propose a novel additive angular margin metric in the framework of prototypical network in few-shot learning setting. We compare our approach to the several established methods on a large cohort of multi-center, multi-organ, and multi-modal endoscopy data. The proposed algorithm outperforms existing state-of-the-art methods.Comment: 10 page

NeAT: a Nonlinear Analysis Toolbox for Neuroimaging

NeAT is a modular, flexible and user-friendly neuroimaging analysis toolbox for modeling linear and nonlinear effects overcoming the limitations of the standard neuroimaging methods which are solely based on linear models. NeAT provides a wide range of statistical and machine learning non-linear methods for model estimation, several metrics based on curve fitting and complexity for model inference and a graphical user interface (GUI) for visualization of results. We illustrate its usefulness on two study cases where non-linear effects have been previously established. Firstly, we study the nonlinear effects of Alzheimer’s disease on brain morphology (volume and cortical thickness). Secondly, we analyze the effect of the apolipoprotein APOE-ε4 genotype on brain aging and its interaction with age. NeAT is fully documented and publicly distributed at https://imatge-upc.github.io/neat-tool/

Whole Genome Sequence of Dermacoccus abyssi MT1.1 Isolated from the Challenger Deep of the Mariana Trench Reveals Phenazine Biosynthesis Locus and Environmental Adaptation Factors

Dermacoccus abyssi strain MT1.1T is a piezotolerant actinobacterium that was isolated from Mariana Trench sediment collected at a depth of 10898 m. The organism was found to produce ten dermacozines (A‒J) that belonged to a new phenazine family and which displayed various biological activities such as radical scavenging and cytotoxicity. Here, we report on the isolation and identification of a new dermacozine compound, dermacozine M, the chemical structure of which was determined using 1D and 2D-NMR, and high resolution MS. A whole genome sequence of the strain contained six secondary metabolite-biosynthetic gene clusters (BGCs), including one responsible for the biosynthesis of a family of phenazine compounds. A pathway leading to the biosynthesis of dermacozines is proposed. Bioinformatic analyses of key stress-related genes provide an insight into how the organism adapted to the environmental conditions that prevail in the deep-sea

Calculation of likelihood ratios for inference of biological sex from human skeletal remains

It is common in forensic anthropology to draw inferences (e.g., inferences with respect to biological sex of human remains) using statistical models applied to anthropometric data. Commonly used models can output posterior probabilities, but a threshold is usually applied in order to obtain a classification. In the forensic-anthropology literature, there is some unease with this “fall-off-the-cliff” approach. Proposals have been made to exclude results that fall within a “zone of uncertainty”, e.g., if the posterior probability for “male” is greater than 0.95 then the remains are classified as male, and if the posterior probability for “male” is less than 0.05 then the remains are classified as female, but if the posterior probability for “male” is between 0.05 and 0.95 the remains are not classified as either male or female. In the present paper, we propose what we believe is a simpler solution that is in line with interpretation of evidence in other branches of forensic science: implementation of the likelihood-ratio framework using relevant data, quantitative measurements, and statistical models. Statistical models that can implement this approach are already widely used in forensic anthropology. All that is required are minor modifications in the way those models are used and a change in the way practitioners and researchers think about the meaning of the output of those models. We explain how to calculate likelihood ratios using osteometric data and linear discriminant analysis, quadratic discriminant analysis, and logistic regression models. We also explain how to empirically validate likelihood-ratio models

DNMT and HDAC inhibition induces immunogenic neoantigens from human endogenous retroviral element-derived transcripts.

Immunotherapies targeting cancer-specific neoantigens have revolutionized the treatment of cancer patients. Recent evidence suggests that epigenetic therapies synergize with immunotherapies, mediated by the de-repression of endogenous retroviral element (ERV)-encoded promoters, and the initiation of transcription. Here, we use deep RNA sequencing from cancer cell lines treated with DNA methyltransferase inhibitor (DNMTi) and/or Histone deacetylase inhibitor (HDACi), to assemble a de novo transcriptome and identify several thousand ERV-derived, treatment-induced novel polyadenylated transcripts (TINPATs). Using immunopeptidomics, we demonstrate the human leukocyte antigen (HLA) presentation of 45 spectra-validated treatment-induced neopeptides (t-neopeptides) arising from TINPATs. We illustrate the potential of the identified t-neopeptides to elicit a T-cell response to effectively target cancer cells. We further verify the presence of t-neopeptides in AML patient samples after in vivo treatment with the DNMT inhibitor Decitabine. Our findings highlight the potential of ERV-derived neoantigens in epigenetic and immune therapies

An adverse tumor-protective effect of IDO1 inhibition

By restoring tryptophan, indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors aim to reactivate anti-tumor T cells. However, a phase III trial assessing their clinical benefit failed, prompting us to revisit the role of IDO1 in tumor cells under T cell attack. We show here that IDO1 inhibition leads to an adverse protection of melanoma cells to T cell-derived interferon-gamma (IFNγ). RNA sequencing and ribosome profiling shows that IFNγ shuts down general protein translation, which is reversed by IDO1 inhibition. Impaired translation is accompanied by an amino acid deprivation-dependent stress response driving activating transcription factor-4 (ATF4)high/microphtalmia-associated transcription factor (MITF)low transcriptomic signatures, also in patient melanomas. Single-cell sequencing analysis reveals that MITF downregulation upon immune checkpoint blockade treatment predicts improved patient outcome. Conversely, MITF restoration in cultured melanoma cells causes T cell resistance. These results highlight the critical role of tryptophan and MITF in the melanoma response to T cell-derived IFNγ and uncover an unexpected negative consequence of IDO1 inhibition

3′UTR-Mediated Gene Silencing of the Mixed Lineage Leukemia (MLL) Gene

Translocations involving the Mixed Lineage Leukemia (MLL) gene generate in-frame fusions of MLL with more than 50 different partner genes (PGs). Common to all MLL translocations is the exchange not only of coding regions, but also of MLL and PG 3′-untranslated regions (3′UTRs). As a result, the MLL-PG fusion is normally highly expressed and considered the main driver of leukemia development, whereas the function of the PG-MLL fusions in leukemic disease is unclear. As 3′UTRs have been recognized as determinant regions for regulation of gene expression, we hypothesized that loss of the MLL 3′UTR could have a role in generating high MLL-PG levels and leukemia development. Here, we first tested the MLL-PG and PG-MLL mRNA levels in different leukemic cells and tumours and uncovered differential expression that indicates strong repression by the MLL-3′UTR. Reporter assays confirmed that the 3′UTR of MLL, but not of its main PGs, harbours a region that imposes a strong gene silencing effect. Gene suppression by the MLL 3′UTR was largely microRNA independent and did not affect mRNA stability, but inhibited transcription. This effect can at least partially be attributed to a tighter interaction of the MLL 3′UTR with RNA polymerase II than PG 3′UTRs, affecting its phosphorylation state. Altogether, our findings indicate that MLL translocations relieve oncogenic MLL-PG fusions from the repressive MLL 3′UTR, contributing to higher activity of these genes and leukaemia development

Differential Epigenetic Regulation of TOX Subfamily High Mobility Group Box Genes in Lung and Breast Cancers

Aberrant cytosine methylation affects regulation of hundreds of genes during cancer development. In this study, a novel aberrantly hypermethylated CpG island in cancer was discovered within the TOX2 promoter. TOX2 was unmethylated in normal cells but 28% lung (n = 190) and 23% breast (n = 80) tumors were methylated. Expression of two novel TOX2 transcripts identified was significantly reduced in primary lung tumors than distant normal lung (p<0.05). These transcripts were silenced in methylated lung and breast cancer cells and 5-Aza-2-deoxycytidine treatment re-expressed both. Extension of these assays to TOX, TOX3, and TOX4 genes that share similar genomic structure and protein homology with TOX2 revealed distinct methylation profiles by smoking status, histology, and cancer type. TOX was almost exclusively methylated in breast (43%) than lung (5%) cancer, whereas TOX3 was frequently methylated in lung (58%) than breast (30%) tumors. TOX4 was unmethylated in all samples and showed the highest expression in normal lung. Compared to TOX4, expression of TOX, TOX2 and TOX3 in normal lung was 25, 44, and 88% lower, respectively, supporting the premise that reduced promoter activity confers increased susceptibility to methylation during lung carcinogenesis. Genome-wide assays revealed that siRNA-mediated TOX2 knockdown modulated multiple pathways while TOX3 inactivation targeted neuronal development and function. Although these knockdowns did not result in further phenotypic changes of lung cancer cells in vitro, the impact on tissue remodeling, inflammatory response, and cell differentiation pathways suggest a potential role for TOX2 in modulating tumor microenvironment