A clarification of the Goodwin model of the growth cycle

We show that there is a difficulty in the original Goodwin model which isalso found in some more recent applications. In it both the labour share and theproportion employed can exceed unity, properties which are untenable. However, weshow that the underlying dynamic structure of the model can be reformulated toensure that these variables cannot exceed unity. An illustrative example extends theoriginal model, and we argue it is both plausible and satisfies the necessary unit boxrestrictions. We show that there is a difficulty in the original Goodwin model which isalso found in some more recent applications. In it both the labour share and theproportion employed can exceed unity, properties which are untenable. However, weshow that the underlying dynamic structure of the model can be reformulated toensure that these variables cannot exceed unity. An illustrative example extends theoriginal model, and we argue it is both plausible and satisfies the necessary unit boxrestrictions

Carbocations and the Complex Flavor and Bouquet of Wine: Mechanistic Aspects of Terpene Biosynthesis in Wine Grapes.

Computational chemistry approaches for studying the formation of terpenes/terpenoids in wines are presented, using five particular terpenes/terpenoids (1,8-cineole, α-ylangene, botrydial, rotundone, and the wine lactone), volatile compounds (or their precursors) found in wine and/or wine grapes, as representative examples. Through these examples, we show how modern computational quantum chemistry can be employed as an effective tool for assessing the validity of proposed mechanisms for terpene/terpenoid formation

Wagin-Woodanilling (zone 5) : catchment appraisal 2005

The aim of this report is to assess the current extent of salinity and other natural resource degradation issues and provide landholders with the best current management options to address natural resource management issues and enhance sustainable agricultural production

Runs of homozygosity and testicular cancer risk.

BACKGROUND: Testicular germ cell tumour (TGCT) is highly heritable but > 50% of the genetic risk remains unexplained. Epidemiological observation of greater relative risk to brothers of men with TGCT compared to sons has long alluded to recessively acting TGCT genetic susceptibility factors, but to date none have been reported. Runs of homozygosity (RoH) are a signature indicating underlying recessively acting alleles and have been associated with increased risk of other cancer types. OBJECTIVE: To examine whether RoH are associated with TGCT risk. METHODS: We performed a genome-wide RoH analysis using GWAS data from 3206 TGCT cases and 7422 controls uniformly genotyped using the OncoArray platform. RESULTS: Global measures of homozygosity were not significantly different between cases and controls, and the frequency of individual consensus RoH was not significantly different between cases and controls, after correction for multiple testing. RoH at three regions, 11p13-11p14.3, 5q14.1-5q22.3 and 13q14.11-13q.14.13, were, however, nominally statistically significant at p < 0.01. Intriguingly, RoH200 at 11p13-11p14.3 encompasses Wilms tumour 1 (WT1), a recognized cancer susceptibility gene with roles in sex determination and developmental transcriptional regulation, processes repeatedly implicated in TGCT aetiology. DISCUSSION AND CONCLUSION: Overall, our data do not support a major role in the risk of TGCT for recessively acting alleles acting through homozygosity, as measured by RoH in outbred populations of cases and controls

Worldwide Distribution of the MYH9 Kidney Disease Susceptibility Alleles and Haplotypes: Evidence of Historical Selection in Africa

MYH9 was recently identified as renal susceptibility gene (OR 3–8, p<10−8) for major forms of kidney disease disproportionately affecting individuals of African descent. The risk haplotype (E-1) occurs at much higher frequencies in African Americans (≥60%) than in European Americans (<4%), revealing a genetic basis for a major health disparity. The population distributions of MYH9 risk alleles and the E-1 risk haplotype and the demographic and selective forces acting on the MYH9 region are not well explored. We reconstructed MYH9 haplotypes from 4 tagging single nucleotide polymorphisms (SNPs) spanning introns 12–23 using available data from HapMap Phase II, and by genotyping 938 DNAs from the Human Genome Diversity Panel (HGDP). The E-1 risk haplotype followed a cline, being most frequent within sub-Saharan African populations (range 50–80%), less frequent in populations from the Middle East (9–27%) and Europe (0–9%), and rare or absent in Asia, the Americas, and Oceania. The fixation indexes (FST) for pairwise comparisons between the risk haplotypes for continental populations were calculated for MYH9 haplotypes; FST ranged from 0.27–0.40 for Africa compared to other continental populations, possibly due to selection. Uniquely in Africa, the Yoruba population showed high frequency extended haplotype length around the core risk allele (C) compared to the alternative allele (T) at the same locus (rs4821481, iHs = 2.67), as well as high population differentiation (FST(CEU vs. YRI) = 0.51) in HapMap Phase II data, also observable only in the Yoruba population from HGDP (FST = 0.49), pointing to an instance of recent selection in the genomic region. The population-specific divergence in MYH9 risk allele frequencies among the world's populations may prove important in risk assessment and public health policies to mitigate the burden of kidney disease in vulnerable populations

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery