Model of a fluid at small and large length scales and the hydrophobic effect

We present a statistical field theory to describe large length scale effects induced by solutes in a cold and otherwise placid liquid. The theory divides space into a cubic grid of cells. The side length of each cell is of the order of the bulk correlation length of the bulk liquid. Large length scale states of the cells are specified with an Ising variable. Finer length scale effects are described with a Gaussian field, with mean and variance affected by both the large length scale field and by the constraints imposed by solutes. In the absence of solutes and corresponding constraints, integration over the Gaussian field yields an effective lattice gas Hamiltonian for the large length scale field. In the presence of solutes, the integration adds additional terms to this Hamiltonian. We identify these terms analytically. They can provoke large length scale effects, such as the formation of interfaces and depletion layers. We apply our theory to compute the reversible work to form a bubble in liquid water, as a function of the bubble radius. Comparison with molecular simulation results for the same function indicates that the theory is reasonably accurate. Importantly, simulating the large length scale field involves binary arithmetic only. It thus provides a computationally convenient scheme to incorporate explicit solvent dynamics and structure in simulation studies of large molecular assemblies

Microbial biopesticides for integrated crop management : an assessment of environmental and regulatory sustainability

Herbivorous insects and mites, plant diseases and weeds are major impediments to the production of food crops and are increasingly difficult to control with conventional chemicals. This paper focuses on microbial control agents with an emphasis on augmentation. There are marked differences in the availability of products in different countries which can be explained in terms of differences in their regulatory systems. Regulatory failure arises from the application of an inappropriate synthetic pesticides model. An understanding of regulatory innovation is necessary to overcome these problems. Two attempts at remedying regulatory failure in the UK and the Netherlands are assessed. Scientific advances can feed directly into the regulatory process and foster regulatory innovation

An Examination of Chimpanzee Use in Human Cancer Research

Advocates of chimpanzee research claim the genetic similarity of humans and chimpanzees make them an indispensable research tool to combat human diseases. Given that cancer is a leading cause of human death worldwide, one might expect that if chimpanzees were needed for, or were productive in, cancer research, then they would have been widely used. This comprehensive literature analysis reveals that chimpanzees have scarcely been used in any form of cancer research, and that chimpanzee tumours are extremely rare and biologically different from human cancers. Often, chimpanzee citations described peripheral use of chimpanzee cells and genetic material in predominantly human genomic studies. Papers describing potential new cancer therapies noted significant concerns regarding the chimpanzee model. Other studies described interventions that have not been pursued clinically. Finally, available evidence indicates that chimpanzees are not essential in the development of therapeutic monoclonal antibodies. It would therefore be unscientific to claim that chimpanzees are vital to cancer research. On the contrary, it is reasonable to conclude that cancer research would not suffer, if the use of chimpanzees for this purpose were prohibited in the US. Genetic differences between humans and chimpanzees, make them an unsuitable model for cancer, as well as other human diseases

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Development of a field petrographic analysis system and its application to the study of socioeconomic interaction networks of the early Harappan Northwestern Indus Valley of Pakistan

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