A Protein Disulfide Isomerase Controls Neuronal Migration through Regulation of Wnt Secretion

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Unexpected Receptor Functional Mimicry Elucidates Activation of Coronavirus Fusion

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Influence of Water Hyacinth Cover on the Physico-chemical Characteristics of Water and Phytoplankton Composition in a Reservoir near Jaipur (India)

Water hyacinth (Eichhornia crassipes (Mart.) Solms.) invaded a eutrophic reservoir receiving domestic sewage near Jaipur (India) during 1975 and gradually developed a complete thick cover over the whole water body during Sept.–Oct. 1978. The physico-chemical characteristics of the water and the phytoplankton composition were studied during Sept. 1977–Sept. 1979 by fortnightly sampling. The changes observed during the second year of study are ascribed to the water hyacinth cover. The important changes were: lowering of water temperature, pH, dissolved oxygen content and nitrate nitrogen, and increase in total alkalinity, free carbon dioxide, chemical oxygen demand, ammonia nitrogen, sulphides, calcium, magnesium and phosphate phosphorus. The changes in the phytoplankton were both qualitative and quantitative. The green algae, particularly the species of Ankistrodesmus, Chlorella, Crucigenia and Selenastrum, increased considerably and replaced the blue-green algae, of which Oscillatoria and Microcystis disappeared totally. The densities of several other taxa changed significantly.     

Fine‐scale ecological and anthropogenic variables predict the habitat use and detectability of sloth bears in the Churia habitat of east Nepal

Once widespread throughout the tropical forests of the Indian Subcontinent, the sloth bears have suffered a rapid range collapse and local extirpations in the recent decades. A significant portion of their current distribution range is situated outside of the protected areas (PAs). These unprotected sloth bear populations are under tremendous human pressures, but little is known about the patterns and determinants of their occurrence in most of these regions. The situation is more prevalent in Nepal where virtually no systematic information is available for sloth bears living outside of the PAs. We undertook a spatially replicated sign survey‐based single‐season occupancy study intending to overcome this information gap for the sloth bear populations residing in the Trijuga forest of southeast Nepal. Sloth bear sign detection histories and field‐based covariates data were collected between 2 October and 3 December 2020 at the 74 randomly chosen 4‐km² grid cells. From our results, the model‐averaged site use probability (ψ ± SE) was estimated to be 0.432 ± 0.039, which is a 13% increase from the naïve estimate (0.297) not accounting for imperfect detections of sloth bear signs. The presence of termite mound and the distance to the nearest water source were the most important variables affecting the habitat use probability of sloth bears. The average site‐level detectability (p ± SE) of sloth bear signs was estimated to be 0.195 ± 0.003 and was significantly determined by the index of human disturbances. We recommend considering the importance of fine‐scale ecological and anthropogenic factors in predicting the sloth bear‐habitat relationships across their range in the Churia habitat of Nepal, and more specifically in the unprotected areas.     

Updating age-specific contact structures to match evolving demography in a dynamic mathematical model of tuberculosis vaccination

We investigated the effects of updating age-specific social contact matrices to match evolving demography on vaccine impact estimates. We used a dynamic transmission model of tuberculosis in India as a case study. We modelled four incremental methods to update contact matrices over time, where each method incorporated its predecessor: fixed contact matrix (M0), preserved contact reciprocity (M1), preserved contact assortativity (M2), and preserved average contacts per individual (M3). We updated the contact matrices of a deterministic compartmental model of tuberculosis transmission, calibrated to epidemiologic data between 2000 and 2019 derived from India. We additionally calibrated the M0, M2, and M3 models to the 2050 TB incidence rate projected by the calibrated M1 model. We stratified age into three groups, children (<15y), adults (≥15y, <65y), and the elderly (≥65y), using World Population Prospects demographic data, between which we applied POLYMOD-derived social contact matrices. We simulated an M72-AS01_E-like tuberculosis vaccine delivered from 2027 and estimated the per cent TB incidence rate reduction (IRR) in 2050 under each update method. We found that vaccine impact estimates in all age groups remained relatively stable between the M0–M3 models, irrespective of vaccine-targeting by age group. The maximum difference in impact, observed following adult-targeted vaccination, was 7% in the elderly, in whom we observed IRRs of 19% (uncertainty range 13–32), 20% (UR 13–31), 22% (UR 14–37), and 26% (UR 18–38) following M0, M1, M2 and M3 updates, respectively. We found that model-based TB vaccine impact estimates were relatively insensitive to demography-matched contact matrix updates in an India-like demographic and epidemiologic scenario. Current model-based TB vaccine impact estimates may be reasonably robust to the lack of contact matrix updates, but further research is needed to confirm and generalise this finding.     

Inhibition of topoisomerase II catalytic activity by two ruthenium compounds: a ligand-dependent mode of action

The ability of two structurally different ruthenium complexes to interfere with the catalytic activity of topoisomerase II was studied to elucidate their molecular mechanism of action and relative antineoplastic activity. The first complex, [RuCl2(C6H6)(dmso)], could completely inhibit DNA relaxation activity of topoisomerase II and form a drug-induced cleavage complex. This strongly suggests that the drug interferes with topoisomerase II activity by cleavage complex formation. The bi-directional binding of [RuCl2(C6H6)(dmso)] to DNA and topoisomerase II was verified by immunoprecipitation experiments which confirmed the presence of DNA and ruthenium in the cleavage complex. The second complex, Ruthenium Salicylaldoxime, could not inhibit topoisomerase II relaxation activity appreciably and also could not induce cleavage complex formation, though its DNA-binding characteristics and antiproliferation activity were almost comparable to those of [RuCl2(C6H6)(dmso)]. The results suggest that the difference in ligands and their orientation around a metal atom may be responsible for topoisomerase II poisoning by the first complex and not by the second. A probable mechanism is proposed for [RuCl2(C6H6)(dmso)], where the ruthenium atom interacts with DNA and ligands of the metal atom form cross-links with topoisomerase II. This may facilitate the formation of a drug-induced cleavage complex.     

A correlation between membrane cholesterol level, cell adhesion and tumourigenicity of polyoma virus transformed cells

We have investigated the implications of the rise in membrane cholesterol levels on several in vitro and in vivo properties of polyoma virus transformed rat fibroblasts (PyF), with a special emphasis on alpha5beta1 integrin functions. We show that increased membrane cholesterol causes the PyF cells to change their shape and become more bipolar in appearance. These cells also show significantly higher adhesion to the cell-binding domain of fibronectin, increased localization of alpha5beta1 integrin and talin molecules in focal adhesions and a more robust actin cytoskeleton organization. PyF cells with increased membrane cholesterol show reduced growth in vitro and tumours caused by these cells in nude mice are slow growing. These changes in the growth properties of PyF cells are reversible when the cholesterol levels of PyF cells become normal. Our results suggest that changes in membrane cholesterol levels influence the growth and morphological properties of transformed cells, which can be exploited in controlling the growth of tumours in vivo.     

Photocatalytic inhibition of microbial adhesion by anodized titanium

Biofouling is one of the concerns in the use of titanium for seawater cooled condensers of power plants. Earlier studies have shown that anodized titanium and its alloys with a thin film of anatase (TiO(2)) on its surface can inhibit attachment of Pseudomonas sp. when illuminated with near-UV light (350 - 380 nm). In the present study, a comparison of the photocatalytic inhibition of microbial attachment on titanium surfaces anodized at different voltages was carried out. Thin films of anatase of varying thickness were produced on titanium grade-2 by anodizing in dilute orthophosphoric acid solution at 30 V, 50 V and 100 V. The photocatalytic efficiency of these anodized surfaces was measured by the methylene blue degradation method. The anodised surfaces were exposed to liquid cultures of Gram-negative Pseudomonas sp., Gram-positive Micrococcus sp. and to a mixed algal culture. Photocatalytic inhibition of microbial attachment was maximum on the titanium surface anodized at 30 V, followed by the surface anodized at 50 V and then at 100 V. The photocatalytic inhibition of microbial attachment was also found to be dependent on the cell wall characteristics of the organism. The Gram-negative Pseudomonas sp. with a lipoproteinaceous outer membrane was the most susceptible to the photocatalytic effect, while the Gram-positive Micrococcus sp. with peptidoglycan cell wall showed moderate susceptibility and the algae with siliceous cell wall showed no susceptibility at all.     

On the structure and initial parameter identification of Gaussian RBF networks

We consider the efficient initialization of structure and parameters of generalized Gaussian radial basis function (RBF) networks using fuzzy decision trees generated by fuzzy ID3 like induction algorithms. The initialization scheme is based on the proposed functional equivalence property of fuzzy decision trees and generalized Gaussian RBF networks. The resulting RBF network is compact, easy to induce, comprehensible, and has acceptable classification accuracy with stochastic gradient descent learning algorithm.