A machine learning approach for single cell interphase cell cycle staging

The cell nucleus is a tightly regulated organelle and its architectural structure is dynamically orchestrated to maintain normal cell function. Indeed, fluctuations in nuclear size and shape are known to occur during the cell cycle and alterations in nuclear morphology are also hallmarks of many diseases including cancer. Regrettably, automated reliable tools for cell cycle staging at single cell level using in situ images are still limited. It is therefore urgent to establish accurate strategies combining bioimaging with high-content image analysis for a bona fide classification. In this study we developed a supervised machine learning method for interphase cell cycle staging of individual adherent cells using in situ fluorescence images of nuclei stained with DAPI. A Support Vector Machine (SVM) classifier operated over normalized nuclear features using more than 3500 DAPI stained nuclei. Molecular ground truth labels were obtained by automatic image processing using fluorescent ubiquitination-based cell cycle indicator (Fucci) technology. An average F1-Score of 87.7% was achieved with this framework. Furthermore, the method was validated on distinct cell types reaching recall values higher than 89%. Our method is a robust approach to identify cells in G1 or S/G2 at the individual level, with implications in research and clinical applications.This work was supported by FEDER funds through the Operational Programme for Competitiveness Factors (COMPETE 2020), Programa Operacional de Competitividade e Internacionalização (POCI), Programa Opera-cional Regional do Norte (Norte 2020) and by National Funds through the Portuguese Foundation for Science and Technology (FCT), under the projects PTDC/BBB-IMG/0283/2014, PTDC/BTM-SAL/30383/2017, LARSyS-UIDB/50009/2020, LARSyS-UID/EEA/50009/2019, NORTE-01-0145-FEDER-000029 and doctoral grant SFRH/ BD/114687/2016. The authors acknowledge the American Association of Patients with Hereditary Gastric Cancer “No Stomach for Cancer” for funding Seruca’s research and the support of the i3S Scientific Platform Advanced Light Microscopy, member of the PPBI (PPBI-POCI-01-0145-FEDER-022122)

Murine model for Fusarium oxysporum invasive fusariosis reveals organ-specific structures for dissemination and long-term persistence

Peer reviewedPublisher PD

Genome-wide signatures of complex introgression and adaptive evolution in the big cats.

The great cats of the genus Panthera comprise a recent radiation whose evolutionary history is poorly understood. Their rapid diversification poses challenges to resolving their phylogeny while offering opportunities to investigate the historical dynamics of adaptive divergence. We report the sequence, de novo assembly, and annotation of the jaguar (Panthera onca) genome, a novel genome sequence for the leopard (Panthera pardus), and comparative analyses encompassing all living Panthera species. Demographic reconstructions indicated that all of these species have experienced variable episodes of population decline during the Pleistocene, ultimately leading to small effective sizes in present-day genomes. We observed pervasive genealogical discordance across Panthera genomes, caused by both incomplete lineage sorting and complex patterns of historical interspecific hybridization. We identified multiple signatures of species-specific positive selection, affecting genes involved in craniofacial and limb development, protein metabolism, hypoxia, reproduction, pigmentation, and sensory perception. There was remarkable concordance in pathways enriched in genomic segments implicated in interspecies introgression and in positive selection, suggesting that these processes were connected. We tested this hypothesis by developing exome capture probes targeting ~19,000 Panthera genes and applying them to 30 wild-caught jaguars. We found at least two genes (DOCK3 and COL4A5, both related to optic nerve development) bearing significant signatures of interspecies introgression and within-species positive selection. These findings indicate that post-speciation admixture has contributed genetic material that facilitated the adaptive evolution of big cat lineages

Gender-dependent differences in plasma matrix metalloproteinase-8 elevated in pulmonary tuberculosis.

Tuberculosis (TB) remains a global health pandemic and greater understanding of underlying pathogenesis is required to develop novel therapeutic and diagnostic approaches. Matrix metalloproteinases (MMPs) are emerging as key effectors of tissue destruction in TB but have not been comprehensively studied in plasma, nor have gender differences been investigated. We measured the plasma concentrations of MMPs in a carefully characterised, prospectively recruited clinical cohort of 380 individuals. The collagenases, MMP-1 and MMP-8, were elevated in plasma of patients with pulmonary TB relative to healthy controls, and MMP-7 (matrilysin) and MMP-9 (gelatinase B) were also increased. MMP-8 was TB-specific (p<0.001), not being elevated in symptomatic controls (symptoms suspicious of TB but active disease excluded). Plasma MMP-8 concentrations inversely correlated with body mass index. Plasma MMP-8 concentration was 1.51-fold higher in males than females with TB (p<0.05) and this difference was not due to greater disease severity in men. Gender-specific analysis of MMPs demonstrated consistent increase in MMP-1 and -8 in TB, but MMP-8 was a better discriminator for TB in men. Plasma collagenases are elevated in pulmonary TB and differ between men and women. Gender must be considered in investigation of TB immunopathology and development of novel diagnostic markers

Dark Matter from Minimal Flavor Violation

We consider theories of flavored dark matter, in which the dark matter particle is part of a multiplet transforming nontrivially under the flavor group of the Standard Model in a manner consistent with the principle of Minimal Flavor Violation (MFV). MFV automatically leads to the stability of the lightest state for a large number of flavor multiplets. If neutral, this particle is an excellent dark matter candidate. Furthermore, MFV implies specific patterns of mass splittings among the flavors of dark matter and governs the structure of the couplings between dark matter and ordinary particles, leading to a rich and predictive cosmology and phenomenology. We present an illustrative phenomenological study of an effective theory of a flavor SU(3)_Q triplet, gauge singlet scalar.Comment: 10 pages, 2 figures; v2: references added, minor changes to collider analysis, conclusions unchange

Exploring the Higgs Portal with 10/fb at the LHC

We consider the impact of new exotic colored and/or charged matter interacting through the Higgs portal on Standard Model Higgs boson searches at the LHC. Such Higgs portal couplings can induce shifts in the effective Higgs-gluon-gluon and Higgs-photon-photon couplings, thus modifying the Higgs production and decay patterns. We consider two possible interpretations of the current LHC Higgs searches based on ~ 5/fb of data at each detector: 1) a Higgs boson in the mass range (124-126) GeV and 2) a `hidden' heavy Higgs boson which is underproduced due to the suppression of its gluon fusion production cross section. We first perform a model independent analysis of the allowed sizes of such shifts in light of the current LHC data. As a class of possible candidates for new physics which gives rise to such shifts, we investigate the effects of new scalar multiplets charged under the Standard Model gauge symmetries. We determine the scalar parameter space that is allowed by current LHC Higgs searches, and compare with complementary LHC searches that are sensitive to the direct production of colored scalar states.Comment: 27 pages, 11 figures; v2: references added, correction to scalar form factor, numerical results updated with Moriond 2012 data, conclusions unchange