Accurate and versatile 3D segmentation of plant tissues at cellular resolution

Quantitative analysis of plant and animal morphogenesis requires accurate segmentation of individual cells in volumetric images of growing organs. In the last years, deep learning has provided robust automated algorithms that approach human performance, with applications to bio-image analysis now starting to emerge. Here, we present PlantSeg, a pipeline for volumetric segmentation of plant tissues into cells. PlantSeg employs a convolutional neural network to predict cell boundaries and graph partitioning to segment cells based on the neural network predictions. PlantSeg was trained on fixed and live plant organs imaged with confocal and light sheet microscopes. PlantSeg delivers accurate results and generalizes well across different tissues, scales, acquisition settings even on non plant samples. We present results of PlantSeg applications in diverse developmental contexts. PlantSeg is free and open-source, with both a command line and a user-friendly graphical interface

Cell cycle and aging, morphogenesis, and response to stimuli genes are individualized biomarkers of glioblastoma progression and survival

<p>Abstract</p> <p>Background</p> <p>Glioblastoma is a complex multifactorial disorder that has swift and devastating consequences. Few genes have been consistently identified as prognostic biomarkers of glioblastoma survival. The goal of this study was to identify general and clinical-dependent biomarker genes and biological processes of three complementary events: lifetime, overall and progression-free glioblastoma survival.</p> <p>Methods</p> <p>A novel analytical strategy was developed to identify general associations between the biomarkers and glioblastoma, and associations that depend on cohort groups, such as race, gender, and therapy. Gene network inference, cross-validation and functional analyses further supported the identified biomarkers.</p> <p>Results</p> <p>A total of 61, 47 and 60 gene expression profiles were significantly associated with lifetime, overall, and progression-free survival, respectively. The vast majority of these genes have been previously reported to be associated with glioblastoma (35, 24, and 35 genes, respectively) or with other cancers (10, 19, and 15 genes, respectively) and the rest (16, 4, and 10 genes, respectively) are novel associations. <it>Pik3r1</it>, <it>E2f3, Akr1c3</it>, <it>Csf1</it>, <it>Jag2</it>, <it>Plcg1</it>, <it>Rpl37a</it>, <it>Sod2</it>, <it>Topors</it>, <it>Hras</it>, <it>Mdm2, Camk2g</it>, <it>Fstl1</it>, <it>Il13ra1</it>, <it>Mtap </it>and <it>Tp53 </it>were associated with multiple survival events.</p> <p>Most genes (from 90 to 96%) were associated with survival in a general or cohort-independent manner and thus the same trend is observed across all clinical levels studied. The most extreme associations between profiles and survival were observed for <it>Syne1</it>, <it>Pdcd4</it>, <it>Ighg1</it>, <it>Tgfa</it>, <it>Pla2g7</it>, and <it>Paics</it>. Several genes were found to have a cohort-dependent association with survival and these associations are the basis for individualized prognostic and gene-based therapies. <it>C2</it>, <it>Egfr</it>, <it>Prkcb</it>, <it>Igf2bp3</it>, and <it>Gdf10 </it>had gender-dependent associations; <it>Sox10</it>, <it>Rps20</it>, <it>Rab31</it>, and <it>Vav3 </it>had race-dependent associations; <it>Chi3l1</it>, <it>Prkcb</it>, <it>Polr2d</it>, and <it>Apool </it>had therapy-dependent associations. Biological processes associated glioblastoma survival included morphogenesis, cell cycle, aging, response to stimuli, and programmed cell death.</p> <p>Conclusions</p> <p>Known biomarkers of glioblastoma survival were confirmed, and new general and clinical-dependent gene profiles were uncovered. The comparison of biomarkers across glioblastoma phases and functional analyses offered insights into the role of genes. These findings support the development of more accurate and personalized prognostic tools and gene-based therapies that improve the survival and quality of life of individuals afflicted by glioblastoma multiforme.</p

Controversial issues in science education for functional scientific literacy: A case study of an implemented curriculum in Cyprus Science classrooms

This study has been designed to provide and interpret information from classroom based practice about the implementation of controversial issues in the science curriculum and relate it to the discussion about conceptual frameworks that situate controversial issues in science education. Since no tools were available from the science education research area to fulfil the methodological aims stated above, the study has taken a methodological orientation which resulted in the selection and modification of Schellens’ (1985) argument typology scheme alongside Peirce’s (1905) classification of the sciences to describe the epistemic part of the lesson, and to the selection of Walton’s and Crabbe’s (1995) typology of argumentative dialogues to describe the dialectical context. The application of argument schemes was successful and it has enabled the description of the epistemic practices as situated in dialectical practice. The analysis has revealed the basic structural components in which the complexity of the discussion is built, consequences, needs (ends) and rules, and how these have been used within discussions: either to ground decisions about an issue, or to explain or evaluate societal agents’ and own selves’ actions, desires, decisions, views and positions, or own intentions towards a personal stated dilemma. Furthermore, they have revealed the instances in which each discipline, like Ethics, Natural Sciences, Psychology, and Sociology, had taken place. The results indicate an intersection of the disciplines and provide valuable information about how implementing controversial issues in the science curriculum might be related to enhancing thoughtful decision making, humanizing the science curriculum, or focusing on epistemological issues

Mutational and expression analysis of the Ras, Akt and the p53 genes in human brain tumors

Brain tumors are intracranial solid neoplasms of abnormal grown cells, which are created either in the brain itself e.g. from neurons and glial cells (primary brain tumors) or spread from cancers primarily located in other organs (metastatic tumors). The most common brain tumors are glioblastomas and meningiomas. Even though the etiology of the formation of malignant brain tumors is still unknown, a number of genes implicated in the formation and development of tumors, has been found. Some of these genes such as the Ras, Akt and p53 genes have been investigated in this study. The purpose of the present study is to evaluate the molecular mechanisms which are involved in brain carcinogenesis. Therefore, we evaluated the mRNA expression of Ras, Akt, SDF-1, CXCR4 and p53 genes by RT-PCR in gliomas and meningiomas tissue samples and in adjacent normal specimens, derived from the same patients. The results were then correlated with the clinicopathological characteristics and survival data of the patients. Furthermore we evaluated the protein levels of Ras-p21 and we examined the correlation with their mRNA expression levels. We also examined the presence of activating mutations of the three Ras genes and p53. Our goals were: a) to determine the expression profile of the genes of interest to specify their role in malignant transformation of brain cells, b) to examine the possibility of using the expression profile of these genes as a molecular marker for the diagnosis of these malignancies in early stages. Our results show increased Kras transcript levels in normal samples, compared to glioblastomas, anaplastic and fibrillary astrocytomas, while increased Hras mRNA levels were observed in normal specimens compared to glioblastomas samples. Western blot analysis did not result in detectable levels of Ras-p21 protein in our samples. The expression profile of these genes is characterized mainly by underexpression in the three sample groups. Sequencing analysis did not detect the GGT->GTT (Gly12Val) mutation in codon 12 of the three Ras genes, in any of our samples. In Akt family genes, increased Akt-3 mRNA expression in normal samples compared to glioblastomas was observed, while Akt-1 and Akt-2 transcript levels did not show statistical differences between normal and tumor samples. The expression profile of Akt-1 and Akt-3 was characterized mainly by normal expression and underexpression, respectively. SDF-1α and CXCR4 genes were mainly overexpressed in glioblastomas. P53 transcript levels did not show any statistical difference between the sample groups. Sequencing analysis did not detect the CGTTGT (Arg273Cys) of the p53 gene, in any of our samples. Kaplan-Meier survival analysis in glioblastomas revealed that patients who overexpressed p53 gene, had decreased survival compared to those that normally expressed it. In meningiomas, Kras, Nras, Akt-2 θαη p53 transcript levels were increased compared to normal tissues. The GGT→GTT (Gly12Val) mutation in Ras genes was not detected in any of our samples. In Akt family genes, meningiomas were found to have elevated Akt-2 mRNA levels compared to normal samples. The GGT→GTT (Gly12Val) mutation in Ras genes and the CGTTGT (Arg273Cys) mutation of the p53 gene were not detected in any of our samples. Our results in gliomas and meningiomas indicate that different activation mechanisms prevail in malignant transformation of brain cells in each type of cancer

A Growth-Based Framework for Leaf Shape Development and Diversity

How do genes modify cellular growth to create morphological diversity? We study this problem in two related plants with differently shaped leaves: Arabidopsis thaliana (simple leaf shape) and Cardamine hirsuta (complex shape with leaflets). We use live imaging, modeling, and genetics to deconstruct these organ-level differences into their&nbsp;cell-level constituents: growth amount, direction, and differentiation. We show that leaf shape depends&nbsp;on the interplay of two growth modes: a conserved organ-wide&nbsp;growth mode that reflects differentiation; and a local, directional mode that involves the patterning of growth foci along the leaf&nbsp;edge. Shape diversity results from the distinct effects of two homeobox genes on these growth modes: SHOOTMERISTEMLESS broadens organ-wide growth relative to edge-patterning, enabling leaflet emergence, while REDUCED COMPLEXITY inhibits growth locally around emerging leaflets,&nbsp;accentuating shape differences created by patterning. We demonstrate the predictivity of our findings by reconstructing key features of C.&nbsp;hirsuta leaf morphology in A.&nbsp;thaliana