by Keyword: population

Cañellas-Socias A, Cortina C, Hernando-Momblona X, Palomo-Ponce S, Mulholland EJ, Turon G, Mateo L, Conti S, Roman O, Sevillano M, Slebe F, Stork D, Caballé-Mestres A, Berenguer-Llergo A, Álvarez-Varela A, Fenderico N, Novellasdemunt L, Jiménez-Gracia L, Sipka T, Bardia L, Lorden P, Colombelli J, Heyn H, Trepat X, Tejpar S, Sancho E, Tauriello DVF, Leedham S, Attolini CS, Batlle E, (2022). Metastatic recurrence in colorectal cancer arises from residual EMP1+ cells Nature 611, 603-+

Around 30-40% of patients with colorectal cancer (CRC) undergoing curative resection of the primary tumour will develop metastases in the subsequent years1. Therapies to prevent disease relapse remain an unmet medical need. Here we uncover the identity and features of the residual tumour cells responsible for CRC relapse. An analysis of single-cell transcriptomes of samples from patients with CRC revealed that the majority of genes associated with a poor prognosis are expressed by a unique tumour cell population that we named high-relapse cells (HRCs). We established a human-like mouse model of microsatellite-stable CRC that undergoes metastatic relapse after surgical resection of the primary tumour. Residual HRCs occult in mouse livers after primary CRC surgery gave rise to multiple cell types over time, including LGR5+ stem-like tumour cells2-4, and caused overt metastatic disease. Using Emp1 (encoding epithelial membrane protein 1) as a marker gene for HRCs, we tracked and selectively eliminated this cell population. Genetic ablation of EMP1high cells prevented metastatic recurrence and mice remained disease-free after surgery. We also found that HRC-rich micrometastases were infiltrated with T cells, yet became progressively immune-excluded during outgrowth. Treatment with neoadjuvant immunotherapy eliminated residual metastatic cells and prevented mice from relapsing after surgery. Together, our findings reveal the cell-state dynamics of residual disease in CRC and anticipate that therapies targeting HRCs may help to avoid metastatic relapse.© 2022. The Author(s), under exclusive licence to Springer Nature Limited.

JTD Keywords: colonization, defines, human colon, mutations, plasticity, retrieval, stem-cells, subtypes, underlie, Animal, Animal cell, Animal experiment, Animal model, Animal tissue, Animals, Article, Cancer, Cancer growth, Cancer immunotherapy, Cancer inhibition, Cancer recurrence, Cancer staging, Cell, Cell adhesion, Cell migration, Cell population, Cell surface receptor, Cohort analysis, Colorectal cancer, Colorectal neoplasms, Colorectal tumor, Comprehensive molecular characterization, Controlled study, Crispr-cas9 system, Cytoskeleton, Disease exacerbation, Disease progression, Dynamics, Emp1 gene, Epithelial membrane protein-1, Extracellular matrix, Flow cytometry, Fluorescence intensity, Gene expression, Genetics, Human, Human cell, Humans, Immune response, Immunofluorescence, In situ hybridization, Marker gene, Metastasis potential, Mice, Minimal residual disease, Mouse, Neoplasm proteins, Neoplasm recurrence, local, Neoplasm, residual, Nonhuman, Pathology, Phenotype, Prevention and control, Protein, Receptors, cell surface, Single cell rna seq, Tumor, Tumor protein, Tumor recurrence

Espinoso, A, Andrzejak, RG, (2022). Phase irregularity: A conceptually simple and efficient approach to characterize electroencephalographic recordings from epilepsy patients Physical Review e 105, 34212

The severe neurological disorder epilepsy affects almost 1% of the world population. For patients who suffer from pharmacoresistant focal-onset epilepsy, electroencephalographic (EEG) recordings are essential for the localization of the brain area where seizures start. Apart from the visual inspection of the recordings, quantitative EEG signal analysis techniques proved to be useful for this purpose. Among other features, regularity versus irregularity and phase coherence versus phase independence allowed characterizing brain dynamics from the measured EEG signals. Can phase irregularities also characterize brain dynamics? To address this question, we use the univariate coefficient of phase velocity variation, defined as the ratio of phase velocity standard deviation and the mean phase velocity. Beyond that, as a bivariate measure we use the classical mean phase coherence to quantify the degree of phase locking. All phase-based measures are combined with surrogates to test null hypotheses about the dynamics underlying the signals. In the first part of our analysis, we use the Rössler model system to study our approach under controlled conditions. In the second part, we use the Bern-Barcelona EEG database which consists of focal and nonfocal signals extracted from seizure-free recordings. Focal signals are recorded from brain areas where the first seizure EEG signal changes can be detected, and nonfocal signals are recorded from areas that are not involved in the seizure at its onset. Our results show that focal signals have less phase variability and more phase coherence than nonfocal signals. Once combined with surrogates, the mean phase velocity proved to have the highest discriminative power between focal and nonfocal signals. In conclusion, conceptually simple and easy to compute phase-based measures can help to detect features induced by epilepsy from EEG signals. This holds not only for the classical mean phase coherence but even more so for univariate measures of phase irregularity. © 2022 American Physical Society.

JTD Keywords: brain, entropy, epileptogenic networks, functional connectivity, hilbert transform, seizure onset, surrogate data, synchronization, time-series, Biomedical signal processing, Brain areas, Brain dynamics, Dynamics, Electroencephalographic signals, Electroencephalography, Electrophysiology, Intracranial eeg signals, Localisation, Neurological disorders, Neurology, Phase based, Phase coherence, Signal detection, Simple++, Univariate, Velocity, World population

Auffarth, Benjamin, Gutierrez-Galvez, Agustín, Marco, Santiago, (2011). Continuous spatial representations in the olfactory bulb may reflect perceptual categories Frontiers in Systems Neuroscience 5, (82), 1-8

In sensory processing of odors, the olfactory bulb is an important relay station, where odor representations are noise-filtered, sharpened, and possibly re-organized. An organization by perceptual qualities has been found previously in the piriform cortex, however several recent studies indicate that the olfactory bulb code reflects behaviorally relevant dimensions spatially as well as at the population level. We apply a statistical analysis on 2-deoxyglucose images, taken over the entire bulb of glomerular layer of the rat, in order to see how the recognition of odors in the nose is translated into a map of odor quality in the brain. We first confirm previous studies that the first principal component could be related to pleasantness, however the next higher principal components are not directly clear. We then find mostly continuous spatial representations for perceptual categories. We compare the space spanned by spatial and population codes to human reports of perceptual similarity between odors and our results suggest that perceptual categories could be already embedded in glomerular activations and that spatial representations give a better match than population codes. This suggests that human and rat perceptual dimensions of odorant coding are related and indicates that perceptual qualities could be represented as continuous spatial codes of the olfactory bulb glomerulus population.

JTD Keywords: Glomeruli, Memory organization, Odor quality, Olfaction, Olfactory bulb, Perceptual categories, Population coding, Spatial coding