The biogeomorphological life cycle of poplars during the fluvial biogeomorphological succession: a special focus on Populus nigra L.

Riverine ecosystems are recurrently rejuvenated during destructive flood events and vegetation succession starts again. Poplars (i.e. species from Populus genera) respond to hydrogeomorphological constraints, but, in turn, also influence these processes. Thus, poplar development on bare mineral substrates is not exclusively a one-way vegetative process. Reciprocal interactions and adjustments between poplar species and sediment dynamics during their life cycle lead to the emergence of biogeomorphological entities within the fluvial corridor, such as vegetated islands, benches and floodplains. Based on a review of geomorphological, biological and ecological literature, we have identified and described the co-constructing processes between riparian poplars and their fluvial environment. We have explored the possibility that the modification of the hydrogeomorphological environment exerted, in particular, by the European black poplar (Populus nigra L.), increases its fitness and thus results in positive niche construction. We focus on the fundamental phases of dispersal, recruitment and establishment until sexual maturity of P. nigra by describing the hierarchy of interactions and the pattern of feedbacks between biotic and abiotic components. We explicitly relate the biological life cycle of P. nigra to the fluvial biogeomorphic succession model by referring to the ‘biogeomorphological life cycle’ of P. nigra. Finally, we propose new research perspectives based on this theoretical framework

Deep learning enables spatial mapping of the mosaic microenvironment of myeloma bone marrow trephine biopsies

Bone marrow trephine biopsy is crucial for the diagnosis of multiple myeloma. However, the complexity of bone marrow cellular, morphological, and spatial architecture preserved in trephine samples hinders comprehensive evaluation. To dissect the diverse cellular communities and mosaic tissue habitats, we developed a superpixel-inspired deep learning method (MoSaicNet) that adapts to complex tissue architectures and a cell imbalance aware deep learning pipeline (AwareNet) to enable accurate detection and classification of rare cell types in multiplex immunohistochemistry images. MoSaicNet and AwareNet achieved an area under the curve of >0.98 for tissue and cellular classification on separate test datasets. Application of MoSaicNet and AwareNet enabled investigation of bone heterogeneity and thickness as well as spatial histology analysis of bone marrow trephine samples from monoclonal gammopathies of undetermined significance (MGUS) and from paired newly diagnosed and post-treatment multiple myeloma. The most significant difference between MGUS and newly diagnosed multiple myeloma (NDMM) samples was not related to cell density but to spatial heterogeneity, with reduced spatial proximity of BLIMP1+ tumor cells to CD8+ cells in MGUS compared with NDMM samples. Following treatment of multiple myeloma patients, there was a reduction in the density of BLIMP1+ tumor cells, effector CD8+ T cells, and T regulatory cells, indicative of an altered immune microenvironment. Finally, bone heterogeneity decreased following treatment of MM patients. In summary, deep-learning based spatial mapping of bone marrow trephine biopsies can provide insights into the cellular topography of the myeloma marrow microenvironment and complement aspirate-based techniques

Pattern Formation and Organization of Epithelial Tissues

Developmental biology is a study of how elaborate patterns, shapes, and functions emerge as an organism grows and develops its body plan. From the physics point of view this is very much a self-organization process. The genetic blueprint contained in the DNA does not explicitly encode shapes and patterns an animal ought to make as it develops from an embryo. Instead, the DNA encodes various proteins which, among other roles, specify how different cells function and interact with each other. Epithelial tissues, from which many organs are sculpted, serve as experimentally- and analytically-tractable systems to study patterning mechanisms in animal development. Despite extensive studies in the past decade, the mechanisms that shape epithelial tissues into functioning organs remain incompletely understood. This thesis summarizes various studies we have done on epithelial organization and patterning, both in abstract theory and in close contact with experiments. A novel mechanism to establish cellular left-right asymmetry based on planar polarity instabilities is discussed. Tissue chirality is often assumed to originate from handedness of biological molecules. Here we propose an alternative where it results from spontaneous symmetry breaking of planar polarity mechanisms. We show that planar cell polarity (PCP), a class of well-studied mechanisms that allows epithelia to spontaneously break rotational symmetry, is also generically capable of spontaneously breaking reflection symmetry. Our results provide a clear interpretation of many mutant phenotypes, especially those that result in incomplete inversion. To bridge theory and experiments, we develop quantitative methods to analyze fluorescence microscopy images. Included in this thesis are algorithms to selectively project intensities from a surface in z-stack images, analysis of cells forming short chain fragments, analysis of thick fluorescent bands using steerable ridge detector, and analysis of cell recoil in laser ablation experiments. These techniques, though developed in the context of zebrafish retina mosaic, are general and can be adapted to other systems. Finally we explore correlated noise in morphogenesis of fly pupa notum. Here we report unexpected correlation of noise in cell movements between left and right halves of developing notum, suggesting that feedback or other mechanisms might be present to counteract stochastic noise and maintain left-right symmetry.PHDPhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138800/1/hjeremy_1.pd

Unraveling the complexity of tyrosine kinase inhibitor-resistant populations by ultra-deep sequencing of the BCR-ABL kinase domain

In chronic myeloid leukemia and Philadelphia chromosome-positive acute lymphoblastic leukemia, tyrosine kinase inhibitor (TKI) therapy may select for drug-resistant BCR-ABL mutants. We used an ultra-deep sequencing (UDS) approach to resolve qualitatively and quantitatively the complexity of mutated populations surviving TKIs and to investigate their clonal structure and evolution over time in relation to therapeutic intervention. To this purpose, we performed a longitudinal analysis of 106 samples from 33 patients who had received sequential treatment with multiple TKIs and had experienced sequential relapses accompanied by selection of 1 or more TKI-resistant mutations. We found that conventional Sanger sequencing had misclassified or underestimated BCR-ABL mutation status in 55% of the samples, where mutations with 1% to 15% abundance were detected. A complex clonal texture was uncovered by clonal analysis of samples harboring multiple mutations and up to 13 different mutated populations were identified. The landscape of these mutated populations was found to be highly dynamic. The high degree of complexity uncovered by UDS indicates that conventional Sanger sequencing might be an inadequate tool to assess BCR-ABL kinase domain mutation status, which currently represents an important component of the therapeutic decision algorithms. Further evaluation of the clinical usefulness of UDS-based approaches is warranted

Application of predictive breeding in yam improvement for west Africa

Open Access Journa

Breeding, evaluation and selection of Cassava for high starch content and yield in Tanzania.

Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2009.High starch content is an important component of root quantity and quality for almost all uses of cassava (flour, chips, and industrial raw material). However, there is scanty information on genetic variability for dry matter and starch contents and relatively little attention has been paid to genetic improvement of root dry matter content and starch content in Tanzania. The major objective of this research was to develop improved cassava varieties that are high yielding, with high dry matter and starch content for Tanzania and specifically to: i) identify farmers’ preferences and selection criteria for cassava storage root quality characteristics and other traits of agronomic relevance for research intervention through a participatory rural appraisal; ii) determine the genotypic variability for starch quantity and dry matter content evaluated for three harvesting times in four sites; iii) determine the inheritance of dry matter and starch content in cassava genotypes; and iv) develop and evaluate clones for high storage root yield, high dry matter content and starch. Attributes desired by farmers were yield, earliness, tolerance to pests and diseases. The complementing attributes associated with culinary qualities were sweetness, good cookability, high dry matter content or mealyness and marketability. The preliminary study conducted to evaluate the variability in root dry matter content (RDMC) and starch quantity and yield of ten cassava cultivars indicated that RDMC ranged from 29 to 40% with the mean of 34.3%. The RDMC at 7 months after planting (MAP) was higher than at 11 and 14 MAP. Starch content (StC) ranged from 20.3% to 24.9% with the mean of 22.8%. The StC differed significantly between cultivars, harvesting time and sites. An increase in StC was observed between 0 and 7 MAP, followed by a decline between 7 and 11 MAP, and finally an increase again noted between 11 and 14 MAP. However, for most of the cultivars at Kibaha an increase in StC between 11 and 14 MAP could not surpass values recorded at 7 MAP. At Kizimbani, cultivar Kalolo and Vumbi could not increase in StC after 11 MAP. At Chambezi and Hombolo, a dramatic gain in StC was observed for most of the cultivars between 11 and 14 MAP. Starch yield ranged from 0.54 to 4.09 t ha-1. Both StC and fresh storage root yield are important traits when selecting for commercial cultivars for starch production. Generation of the F1 population was done using a 10 x 10 half diallel design, followed by evaluation of genotypes using a 4 x 10 á-lattice. Results from the diallel analysis indicated that significant differences in fresh storage root yield (FSRY), fresh biomass (FBM), storage root number (SRN), RDMC, starch content (StC), and starch yield (StY), and cassava brown streak disease root necrosis (CBSRN) were observed between families and progeny. The FSRY for the families ranged from 15.0 to 36.3 t ha-1; StC ranged from 23.0 to 29.9%; RDMC ranged from 31.4 to 40.1%; and StY ranged from 3.3 to 8.3 t ha-1. The cassava mosaic disease (CMD) severity ranged from 1.7 to 2.7, while cassava brown streak disease (CBSD) severity for above ground symptoms ranged from 1.0 to 1.9. Additive genetic effects were predominant over non-additive genetic effects for RDMC, StC, and CBSRN, while for FSRY, FBM, SRN, and StY non-additive genetic effects predominated. Negative and non-significant correlation between RDMC and FSRY was observed at the seedling stage (r=-0.018), while at clonal stage the correlation was positive but not significant (0.01). The RDMC and StC were positive and significantly correlated (r=0.55***) at clonal stage. However, the StC negatively and non-significantly correlated with FSRY (r=- 0.01). High, positive and significant correlation (r=0.94; p.0.001) was observed between the StY and FSRY at clonal stage. High, positive and significant correlations between the seedling and clonal stage in FSRM (r=0.50; p.0.01), RDMC (r=0.67; p.0.001), HI (r=0.69; p.0.001), and SRN (r=0.52; p.0.01) were observed, suggesting that indirect selection could start at seedling stage for FSRM, RDMC, HI, and SRN. The best overall genotype for StC was 6256 (40.9%) from family Kiroba x Namikonga followed by genotype 6731 (40.6%; Vumbi x Namikonga). Among the parents, Kiroba and Namikonga were identified as the best combiners in terms of GCA effects for StC. Genotype 6879 from family Vumbi x AR 42-3 had the highest StY value of 34.8 t ha-1 followed by genotype 6086 (30.4 t ha-1; Kalolo x AR 40-6). Among the parents, Kalolo and AR 42-3 were identified as good combiners for the trait. Mid-parent heterosis for StC ranged from 41.6 to 134.1%, while best parent heterosis ranged from 30.4 to 119.6%. Genotype KBH/08/6807 from family Vumbi x TMS 30001 had the highest mid-and best parent heterosis percentage for StC. For StY, mid-parent and best parent heterosis ranged from 168.0 to 1391.0%, and from 140.4 to 1079.0%, respectively, with the genotype 6879 (Vumbi x AR 42-3) exhibiting the highest mid- and best parent heterosis percentage for StY. Improvement for StC, RDMC, and CBSRN may be realized by selecting parents with the highest GCA effects for the traits and hybridize with those that combine well to maximize the positive SCA effects for the StC, RDMC and CBSRN. Selected genotypes from the clonal stage will be evaluated in preliminary yield trial and advanced further to multi-locational trials while implementing participatory approaches involving farmers and processors in selection. New promising lines should be tested at different sites and the best harvesting dates should be established

The University of Pennsylvania Glioblastoma (UPenn-GBM) cohort: Advanced MRI, clinical, genomics, & radiomics

Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have reported results from either private institutional data or publicly available datasets. However, current public datasets are limited in terms of: a) number of subjects, b) lack of consistent acquisition protocol, c) data quality, or d) accompanying clinical, demographic, and molecular information. Toward alleviating these limitations, we contribute the University of Pennsylvania Glioblastoma Imaging, Genomics, and Radiomics (UPenn-GBM) dataset, which describes the currently largest publicly available comprehensive collection of 630 patients diagnosed with de novo glioblastoma. The UPenn-GBM dataset includes (a) advanced multi-parametric magnetic resonance imaging scans acquired during routine clinical practice, at the University of Pennsylvania Health System, (b) accompanying clinical, demographic, and molecular information, (d) perfusion and diffusion derivative volumes, (e) computationally-derived and manually-revised expert annotations of tumor sub-regions, as well as (f) quantitative imaging (also known as radiomic) features corresponding to each of these regions. This collection describes our contribution towards repeatable, reproducible, and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments

Denosumab treatment for fibrous dysplasia

Fibrous dysplasia (FD) is a skeletal disease caused by somatic activating mutations of the cyclic adenosine monophosphate (cAMP)‐regulating protein, α‐subunit of the Gs stimulatory protein (G s α). These mutations lead to replacement of normal bone by proliferative osteogenic precursors, resulting in deformity, fracture, and pain. Medical treatment has been ineffective in altering the disease course. Receptor activator of NF‐κB ligand (RANKL) is a cell‐surface protein involved in many cellular processes, including osteoclastogenesis, and is reported to be overexpressed in FD‐like bone cells. Denosumab is a humanized monoclonal antibody to RANKL approved for treatment of osteoporosis and prevention of skeletal‐related events from bone metastases. We present the case of a 9‐year‐old boy with severe FD who was treated with denosumab for a rapidly expanding femoral lesion. Immunohistochemical staining on a pretreatment bone biopsy specimen revealed marked RANKL expression. He was started on monthly denosumab, with an initial starting dose of 1 mg/kg and planned 0.25 mg/kg dose escalations every 3 months. Over 7 months of treatment he showed marked reduction in pain, bone turnover markers (BTMs), and tumor growth rate. Denosumab did not appear to impair healing of a femoral fracture that occurred while on treatment. With initiation of treatment he developed hypophosphatemia and secondary hyperparathyroidism, necessitating supplementation with phosphorus, calcium, and calcitriol. BTMs showed rapid and sustained suppression. With discontinuation there was rapid and dramatic rebound of BTMs with cross‐linked C‐telopeptide (reflecting osteoclast activity) exceeding pretreatment levels, accompanied by severe hypercalcemia. In this child, denosumab lead to dramatic reduction of FD expansion and FD‐related bone pain. Denosumab was associated with clinically significant disturbances of mineral metabolism both while on treatment and after discontinuation. Denosumab treatment of FD warrants further study to confirm efficacy and determine potential morbidity, as well as to determine the mechanism of RANKL in the pathogenesis of FD and related bone marrow stromal cell diseases. © 2012 American Society for Bone and Mineral Research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92121/1/1603_ftp.pd