Decolonising public service television in Aotearoa New Zealand: telling better stories about Indigenous rurality

(c) The Author/s 2022AM accepted for publication in "Media, culture and society" first published online 25 October 2022.In settler-colonial countries like Aotearoa New Zealand, television programmes about rurality are fundamentally entwined with the nation’s colonial history, but how this context impacts on locally made, public service television content and production is seldom examined. Utilising data collected from interviews with programme makers and a novel bi-cultural friendship pair methodology, we examine how a high-rating mainstream programme, Country Calendar, conceptualises and delivers stories about Indigenous Māori and consider the extent to which these stories represent a decolonising of television narratives about rurality. The findings highlight the importance of incorporating Indigenous voices and values, the impact of structural limitations and staffing constraints on public service television’s decolonising aspirations, and challenges reconciling settler-colonialism with the show’s well-established ‘rosy glow’. While rural media are often overlooked by communication scholars, our study demonstrates the contributions they might make to the larger task of decolonising storytelling about national identity.fals

An Evolutionary Perspective on Sedentary Behavior

Funding Information Royal Society wolfson merit award Natural Science Foundation of China. Grant Number: 91731303Peer reviewedPostprin

Observations from a prospective small cohort study suggest that CGRP genes contribute to acute posttraumatic headache burden after concussion

Introduction: Post-traumatic headache (PTH) is commonly reported after concussion. Calcitonin gene-related peptide (CGRP) is implicated in the pathogenesis of migraine. We explored how single nucleotide polymorphisms (SNPs) from CGRP-alpha (CALCA) and the receptor activity modifying protein-1 (RAMP1) related to headache burden during the first week after concussion. Methods: A prospective study was performed in 34 collegiate athletes who sustained a concussion. Participants completed the symptom evaluation checklist from the SCAT3 within 48 h of injury (V1), and again 4 (V2) and 7 (V3) days after injury. For each visit, the self-reported score (0–6) for headache, pressure in head, blurred vision, and sensitivity to light/noise were reported and summed to calculate the headache burden. A saliva sample was obtained and genotyped for CALCA (rs3781719) and RAMP1 (rs10185142). RAMP1 (TT, TC, CC) and CALCA (AA, AG, GG) were dichotomized (A+, A- and T+, T-, respectively), and concatenated (T+A+, T+A-, T-A+, T-A-) for analyses. Results: Headache Burden at Visit 1 was greatest in T+A+ compared to T-A+, and trended toward a significant difference with T+A-. Repeated-measures ANOVA revealed the presence of significant visit main effects (p < 0.001, η2 = 0.404), but the group (p = 0.055) and interaction effects only trended (p = 0.094). Pearson's χ2-tests revealed that 88% of those with return-to play (RTP) exclusions ≥15 days had PTH with multi-sensory symptoms (PTH+SENS) as compared to 35% in those with RTP < 14 day. Conclusion: Knowledge of RAMP1 and CALCA genotypes appear to improve an understanding the presenting features and magnitude of headache burden after concussion injury

Classifying and scoring of molecules with the NGN: new datasets, significance tests, and generalization

<p>Abstract</p> <p/> <p>This paper demonstrates how a Neural Grammar Network learns to classify and score molecules for a variety of tasks in chemistry and toxicology. In addition to a more detailed analysis on datasets previously studied, we introduce three new datasets (BBB, FXa, and toxicology) to show the generality of the approach. A new experimental methodology is developed and applied to both the new datasets as well as previously studied datasets. This methodology is rigorous and statistically grounded, and ultimately culminates in a Wilcoxon significance test that proves the effectiveness of the system. We further include a complete generalization of the specific technique to arbitrary grammars and datasets using a mathematical abstraction that allows researchers in different domains to apply the method to their own work.</p> <p>Background</p> <p>Our work can be viewed as an alternative to existing methods to solve the quantitative structure-activity relationship (QSAR) problem. To this end, we review a number approaches both from a methodological and also a performance perspective. In addition to these approaches, we also examined a number of chemical properties that can be used by generic classifier systems, such as feed-forward artificial neural networks. In studying these approaches, we identified a set of interesting benchmark problem sets to which many of the above approaches had been applied. These included: ACE, AChE, AR, BBB, BZR, Cox2, DHFR, ER, FXa, GPB, Therm, and Thr. Finally, we developed our own benchmark set by collecting data on toxicology.</p> <p>Results</p> <p>Our results show that our system performs better than, or comparatively to, the existing methods over a broad range of problem types. Our method does not require the expert knowledge that is necessary to apply the other methods to novel problems.</p> <p>Conclusions</p> <p>We conclude that our success is due to the ability of our system to: 1) encode molecules losslessly before presentation to the learning system, and 2) leverage the design of molecular description languages to facilitate the identification of relevant structural attributes of the molecules over different problem domains.</p

Multiplexed five-color molecular imaging of cancer cells and tumor tissues with carbon nanotube Raman tags in the near-infrared

Single-walled carbon nanotubes (SWNTs) with five different C13/C12 isotope compositions and well-separated Raman peaks have been synthesized and conjugated to five targeting ligands in order to impart molecular specificity. Multiplexed Raman imaging of live cells has been carried out by highly specific staining of cells with a five-color mixture of SWNTs. Ex vivo multiplexed Raman imaging of tumor samples uncovers a surprising up-regulation of epidermal growth factor receptor (EGFR) on LS174T colon cancer cells from cell culture to in vivo tumor growth. This is the first time five-color multiplexed molecular imaging has been performed in the near-infrared (NIR) region under a single laser excitation. Near zero interfering background of imaging is achieved due to the sharp Raman peaks unique to nanotubes over the low, smooth autofluorescence background of biological species.Comment: Published in Nano Researc

Strong mitochondrial DNA support for a Cretaceous origin of modern avian lineages

<p>Abstract</p> <p>Background</p> <p>Determining an absolute timescale for avian evolutionary history has proven contentious. The two sources of information available, paleontological data and inference from extant molecular genetic sequences (colloquially, 'rocks' and 'clocks'), have appeared irreconcilable; the fossil record supports a Cenozoic origin for most modern lineages, whereas molecular genetic estimates suggest that these same lineages originated deep within the Cretaceous and survived the K-Pg (Cretaceous-Paleogene; formerly Cretaceous-Tertiary or K-T) mass-extinction event. These two sources of data therefore appear to support fundamentally different models of avian evolution. The paradox has been speculated to reflect deficiencies in the fossil record, unrecognized biases in the treatment of genetic data or both. Here we attempt to explore uncertainty and limit bias entering into molecular divergence time estimates through: (i) improved taxon (<it>n </it>= 135) and character (<it>n = </it>4594 bp mtDNA) sampling; (ii) inclusion of multiple cladistically tested internal fossil calibration points (<it>n </it>= 18); (iii) correction for lineage-specific rate heterogeneity using a variety of methods (<it>n </it>= 5); (iv) accommodation of uncertainty in tree topology; and (v) testing for possible effects of episodic evolution.</p> <p>Results</p> <p>The various 'relaxed clock' methods all indicate that the major (basal) lineages of modern birds originated deep within the Cretaceous, although temporal intraordinal diversification patterns differ across methods. We find that topological uncertainty had a systematic but minor influence on date estimates for the origins of major clades, and Bayesian analyses assuming fixed topologies deliver similar results to analyses with unconstrained topologies. We also find that, contrary to expectation, rates of substitution are not autocorrelated across the tree in an ancestor-descendent fashion. Finally, we find no signature of episodic molecular evolution related to either speciation events or the K-Pg boundary that could systematically mislead inferences from genetic data.</p> <p>Conclusion</p> <p>The 'rock-clock' gap has been interpreted by some to be a result of the vagaries of molecular genetic divergence time estimates. However, despite measures to explore different forms of uncertainty in several key parameters, we fail to reconcile molecular genetic divergence time estimates with dates taken from the fossil record; instead, we find strong support for an ancient origin of modern bird lineages, with many extant orders and families arising in the mid-Cretaceous, consistent with previous molecular estimates. Although there is ample room for improvement on both sides of the 'rock-clock' divide (e.g. accounting for 'ghost' lineages in the fossil record and developing more realistic models of rate evolution for molecular genetic sequences), the consistent and conspicuous disagreement between these two sources of data more likely reflects a genuine difference between estimated ages of (i) stem-group origins and (ii) crown-group morphological diversifications, respectively. Further progress on this problem will benefit from greater communication between paleontologists and molecular phylogeneticists in accounting for error in avian lineage age estimates.</p

The genome of the emerging barley pathogen Ramularia collo-cygni

Background Ramularia collo-cygni is a newly important, foliar fungal pathogen of barley that causes the disease Ramularia leaf spot. The fungus exhibits a prolonged endophytic growth stage before switching life habit to become an aggressive, necrotrophic pathogen that causes significant losses to green leaf area and hence grain yield and quality. Results The R. collo-cygni genome was sequenced using a combination of Illumina and Roche 454 technologies. The draft assembly of 30.3 Mb contained 11,617 predicted gene models. Our phylogenomic analysis confirmed the classification of this ascomycete fungus within the family Mycosphaerellaceae, order Capnodiales of the class Dothideomycetes. A predicted secretome comprising 1053 proteins included redox-related enzymes and carbohydrate-modifying enzymes and proteases. The relative paucity of plant cell wall degrading enzyme genes may be associated with the stealth pathogenesis characteristic of plant pathogens from the Mycosphaerellaceae. A large number of genes associated with secondary metabolite production, including homologs of toxin biosynthesis genes found in other Dothideomycete plant pathogens, were identified. Conclusions The genome sequence of R. collo-cygni provides a framework for understanding the genetic basis of pathogenesis in this important emerging pathogen. The reduced complement of carbohydrate-degrading enzyme genes is likely to reflect a strategy to avoid detection by host defences during its prolonged asymptomatic growth. Of particular interest will be the analysis of R. collo-cygni gene expression during interactions with the host barley, to understand what triggers this fungus to switch from being a benign endophyte to an aggressive necrotroph

Role of Biotransformation Studies in Minimizing Metabolism-Related Liabilities in Drug Discovery

Metabolism-related liabilities continue to be a major cause of attrition for drug candidates in clinical development. Such problems may arise from the bioactivation of the parent compound to a reactive metabolite capable of modifying biological materials covalently or engaging in redox-cycling reactions leading to the formation of other toxicants. Alternatively, they may result from the formation of a major metabolite with systemic exposure and adverse pharmacological activity. To avert such problems, biotransformation studies are becoming increasingly important in guiding the refinement of a lead series during drug discovery and in characterizing lead candidates prior to clinical evaluation. This article provides an overview of the methods that are used to uncover metabolism-related liabilities in a pre-clinical setting and offers suggestions for reducing such liabilities via the modification of structural features that are used commonly in drug-like molecules