Testing Ecological Theory with Lianas

Lianas constitute a diverse polyphyletic plant group that is advancing our understanding of ecological theory. Specifically, lianas are providing new insights into the mechanisms that control plant distribution and diversity maintenance. For example, there is now evidence that a single, scalable mechanism may explain local, regional, and pan‐tropical distribution of lianas, as well as the maintenance of liana species diversity. The ability to outcompete trees under dry, stressful conditions in seasonal forests provides lianas a growth advantage that, over time, results in relatively high abundance in seasonal forests and low abundance in aseasonal forests. Lianas may also gain a similar growth advantage following disturbance, thus explaining why liana density and diversity peak following disturbance at the local, forest scale. The study of ecology, however, is more than the effect of the environment on organisms; it also includes the effects of organisms on the environment. Considerable empirical evidence now indicates that lianas substantially alter their environment by consuming resources, suppressing tree performance, and influencing emergent properties of forests, such as ecosystem functioning, plant and animal diversity, and community composition. These recent studies using lianas are transcending classical tropical ecology research and are now providing novel insights into fundamental ecological theory

Experimental Biological Protocols with Formal Semantics

Both experimental and computational biology is becoming increasingly automated. Laboratory experiments are now performed automatically on high-throughput machinery, while computational models are synthesized or inferred automatically from data. However, integration between automated tasks in the process of biological discovery is still lacking, largely due to incompatible or missing formal representations. While theories are expressed formally as computational models, existing languages for encoding and automating experimental protocols often lack formal semantics. This makes it challenging to extract novel understanding by identifying when theory and experimental evidence disagree due to errors in the models or the protocols used to validate them. To address this, we formalize the syntax of a core protocol language, which provides a unified description for the models of biochemical systems being experimented on, together with the discrete events representing the liquid-handling steps of biological protocols. We present both a deterministic and a stochastic semantics to this language, both defined in terms of hybrid processes. In particular, the stochastic semantics captures uncertainties in equipment tolerances, making it a suitable tool for both experimental and computational biologists. We illustrate how the proposed protocol language can be used for automated verification and synthesis of laboratory experiments on case studies from the fields of chemistry and molecular programming

Efficient video collection association using geometry-aware Bag-of-Iconics representations

Abstract Recent years have witnessed the dramatic evolution in visual data volume and processing capabilities. For example, technical advances have enabled 3D modeling from large-scale crowdsourced photo collections. Compared to static image datasets, exploration and exploitation of Internet video collections are still largely unsolved. To address this challenge, we first propose to represent video contents using a histogram representation of iconic imagery attained from relevant visual datasets. We then develop a data-driven framework for a fully unsupervised extraction of such representations. Our novel Bag-of-Iconics (BoI) representation efficiently analyzes individual videos within a large-scale video collection. We demonstrate our proposed BoI representation with two novel applications: (1) finding video sequences connecting adjacent landmarks and aligning reconstructed 3D models and (2) retrieving geometrically relevant clips from video collections. Results on crowdsourced datasets illustrate the efficiency and effectiveness of our proposed Bag-of-Iconics representation

Synergistic Biomineralization Phenomena Created by a Combinatorial Nacre Protein Model System

In the nacre or aragonite layer of the mollusk shell, proteomes that regulate both the early stages of nucleation and nano-to-mesoscale assembly of nacre tablets from mineral nanoparticle precursors exist. Several approaches have been developed to understand protein-associated mechanisms of nacre formation, yet we still lack insight into how protein ensembles or proteomes manage nucleation and crystal growth. To provide additional insights, we have created a proportionally defined combinatorial model consisting of two nacre-associated proteins, C-RING AP7 (shell nacre, Haliotis rufescens) and pseudo-EF hand PFMG1 (oyster pearl nacre, Pinctada fucata), whose individual in vitro mineralization functionalities are well-documented and distinct from one another. Using scanning electron microscopy, flow cell scanning transmission electron microscopy, atomic force microscopy, Ca(II) potentiometric titrations, and quartz crystal microbalance with dissipation monitoring quantitative analyses, we find that both nacre proteins are functionally active within the same mineralization environments and, at 1:1 molar ratios, synergistically create calcium carbonate mesoscale structures with ordered intracrystalline nanoporosities, extensively prolong nucleation times, and introduce an additional nucleation event. Further, these two proteins jointly create nanoscale protein aggregates or phases that under mineralization conditions further assemble into protein–mineral polymer-induced liquid precursor-like phases with enhanced ACC stabilization capabilities, and there is evidence of intermolecular interactions between AP7 and PFMG1 under these conditions. Thus, a combinatorial model system consisting of more than one defined biomineralization protein dramatically changes the outcome of the in vitro biomineralization process

Experience and Challenges from Clinical Trials with Malaria Vaccines in Africa.

Malaria vaccines are considered amongst the most important modalities for potential elimination of malaria disease and transmission. Research and development in this field has been an area of intense effort by many groups over the last few decades. Despite this, there is currently no licensed malaria vaccine. Researchers, clinical trialists and vaccine developers have been working on many approached to make malaria vaccine available.African research institutions have developed and demonstrated a great capacity to undertake clinical trials in accordance to the International Conference on Harmonization-Good Clinical Practice (ICH-GCP) standards in the last decade; particularly in the field of malaria vaccines and anti-malarial drugs. This capacity is a result of networking among African scientists in collaboration with other partners; this has traversed both clinical trials and malaria control programmes as part of the Global Malaria Action Plan (GMAP). GMAP outlined and support global strategies toward the elimination and eradication of malaria in many areas, translating in reduction in public health burden, especially for African children. In the sub-Saharan region the capacity to undertake more clinical trials remains small in comparison to the actual need.However, sustainability of the already developed capacity is essential and crucial for the evaluation of different interventions and diagnostic tools/strategies for other diseases like TB, HIV, neglected tropical diseases and non-communicable diseases. There is urgent need for innovative mechanisms for the sustainability and expansion of the capacity in clinical trials in sub-Saharan Africa as the catalyst for health improvement and maintained

Nanostructured luminescently labeled nucleic acids

Important and emerging trends at the interface of luminescence, nucleic acids and nanotechnology are: (i) the conventional luminescence labeling of nucleic acid nanostructures (e.g. DNA tetrahedron); (ii) the labeling of bulk nucleic acids (e.g. single‐stranded DNA, double‐stranded DNA) with nanostructured luminescent labels (e.g. copper nanoclusters); and (iii) the labeling of nucleic acid nanostructures (e.g. origami DNA) with nanostructured luminescent labels (e.g. silver nanoclusters). This review surveys recent advances in these three different approaches to the generation of nanostructured luminescently labeled nucleic acids, and includes both direct and indirect labeling methods

METH-2 silencing and promoter hypermethylation in NSCLC

The antiangiogenic factor METH-2 (ADAMTS-8) was identified in a previous dual-channel cDNA microarray analysis to be at least two-fold under-represented in 85% (28 out of 33) of primary non-small-cell lung carcinomas (NSCLCs). This observation has been validated in an independent series of NSCLCs and adjacent normal tissues by comparative multiplex RT—PCR, and METH-2 mRNA expression was dramatically reduced in all 23 tumour samples analysed. Immunohistochemical analysis of the same sample set demonstrated that METH-2 was strongly expressed in 14 out of 19 normal epithelial sites examined but only one out of 20 NSCLCs. DNA methylation analysis of the proximal promoter region of this gene revealed abnormal hypermethylation in 67% of the adenocarcinomas and 50% of squamous cell carcinomas, indicating that epigenetic mechanisms are involved in silencing this gene in NSCLC. No homozygous deletions of METH-2 were found in lung cancer cell lines. Allelic imbalance in METH-2 was assessed by an intronic single nucleotide polymorphism (SNP) assay and observed in 44% of informative primary samples. In conclusion, the downregulation of METH-2 expression in primary NSCLC, often associated with promoter hypermethylation, is a frequent event, which may be related to the development of the disease