Indole Glucosinolate Biosynthesis Limits Phenylpropanoid Accumulation in Arabidopsis thaliana

Plants produce an array of metabolites (including lignin monomers and soluble UV-protective metabolites) from phenylalanine through the phenylpropanoid biosynthetic pathway. A subset of plants, including many related to Arabidopsis thaliana, synthesizes glucosinolates, nitrogen- and sulfur-containing secondary metabolites that serve as components of a plant defense system that deters herbivores and pathogens. Here, we report that the Arabidopsis thaliana reduced epidermal fluorescence5 (ref5-1) mutant, identified in a screen for plants with defects in soluble phenylpropanoid accumulation, has a missense mutation in CYP83B1 and displays defects in glucosinolate biosynthesis and in phenylpropanoid accumulation. CYP79B2 and CYP79B3 are responsible for the production of the CYP83B1 substrate indole-3-acetaldoxime (IAOx), and we found that the phenylpropanoid content of cyp79b2 cyp79b3 and ref5-1 cyp79b2 cyp79b3 plants is increased compared with the wild type. These data suggest that levels of IAOx or a subsequent metabolite negatively influence phenylpropanoid accumulation in ref5 and more importantly that this crosstalk is relevant in the wild type. Additional biochemical and genetic evidence indicates that this inhibition impacts the early steps of the phenylpropanoid biosynthetic pathway and restoration of phenylpropanoid accumulation in a ref5-1 med5a/b triple mutant suggests that the function of the Mediator complex is required for the crosstalk.     

Automated assessment reveals that the extinction risk of reptiles is widely underestimated across space and phylogeny

The Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), is a crucial tool for conservation decision-making. However, despite substantial effort, numerous species remain unassessed or have insufficient data available to be assigned a Red List extinction risk category. Moreover, the Red Listing process is subject to various sources of uncertainty and bias. The development of robust automated assessment methods could serve as an efficient and highly useful tool to accelerate the assessment process and offer provisional assessments. Here, we aimed to (1) present a machine learning–based automated extinction risk assessment method that can be used on less known species; (2) offer provisional assessments for all reptiles—the only major tetrapod group without a comprehensive Red List assessment; and (3) evaluate potential effects of human decision biases on the outcome of assessments. We use the method presented here to assess 4,369 reptile species that are currently unassessed or classified as Data Deficient by the IUCN. The models used in our predictions were 90% accurate in classifying species as threatened/nonthreatened, and 84% accurate in predicting specific extinction risk categories. Unassessed and Data Deficient reptiles were considerably more likely to be threatened than assessed species, adding to mounting evidence that these species warrant more conservation attention. The overall proportion of threatened species greatly increased when we included our provisional assessments. Assessor identities strongly affected prediction outcomes, suggesting that assessor effects need to be carefully considered in extinction risk assessments. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap for other less known taxa.

The Red List of Threatened Species, published by the IUCN, is a crucial tool for conservation decision making, but is subject to various sources of uncertainty and bias. Modelling the threat status of all global reptiles identifies increased threat to many groups of reptiles across many regions of the world, beyond those currently recognized; moreover, it highlights the effects of the IUCN assessment procedure on eventual threat categories.     

Phase II protocol for the evaluation of new treatments in patients with advanced gastric carcinoma: results of ECOG 5282

The study was a Phase II randomized study to evaluate the efficacy of new agents for the treatment of advanced gastric carcinoma. Patients were randomized to receive single agent chemotherapy with mitoxantrone, etoposide, aclacinomycin-A or spirogermanium. The patients were stratified by prior use of chemotherapy, prior doxorubicin use and ECOG performance status. Patients with a history of cardiac disease or prior doxorubicin exceeding a dose of 400 mg/m² were restrictively randomized to sopirogermanium or etoposide only. One hundred and fourteen patients were registered for the study. Among 98 evaluable patients there were only two partial responses (both in the etoposide arm), and one complete response in the mitoxantrone arm. The median survival on the study was 3.3 months. One hundred and six patients were analyzable for toxicity. There were four treatment-related deaths and four life-threatening toxicities. Because of low response rates and relatively high toxicities the studied compounds were not deemed worth further investigation for advanced gastric cancer.