Chromosome Driven Spatial Patterning of Proteins in Bacteria

The spatial patterning of proteins in bacteria plays an important role in many processes, from cell division to chemotaxis. In the asymmetrically dividing bacteria Caulobacter crescentus, a scaffolding protein, PopZ, localizes to both poles and aids the differential patterning of proteins between mother and daughter cells during division. Polar patterning of misfolded proteins in Escherechia coli has also been shown, and likely plays an important role in cellular ageing. Recent experiments on both of the above systems suggest that the presence of chromosome free regions along with protein multimerization may be a mechanism for driving the polar localization of proteins. We have developed a simple physical model for protein localization using only these two driving mechanisms. Our model reproduces all the observed patterns of PopZ and misfolded protein localization - from diffuse, unipolar, and bipolar patterns and can also account for the observed patterns in a variety of mutants. The model also suggests new experiments to further test the role of the chromosome in driving protein patterning, and whether such a mechanism is responsible for helping to drive the differentiation of the cell poles

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council

Methods For Interval Linear Equations

Abstract. We discuss one known and five new interrelated methods for bounding the hull of the solution set of a system of interval linear equations. Each method involves a polynomial amount of computing; but requires considerably more effort than Gaussian elimination. However, each method can yield sharper results for appropriate problems. For certain problems, our methods can obtain sharp bounds for one or more (and perhaps all) components of the hull of the solution set. Consider a set of linear equations 1

A study of surface, 50 meter and 200 meter temperature and salinity fluctuations at ocean weather station November, 1968-1970.

Long and short-term surface, 50 and 200 meter temperature and salinity fluctuations at Ocean Weather Station November during 1968 through 1970 were examined using several statistical techniques. One technique, a unique monthly bi-variate modal analysis of surface temperature and salinity, proved to be a valuable research tool in that the resulting monthly modal cells, when plotted on a T-S diagram, provided a simplified view of the annual T-S relationships. The average range of mean monthly temperatures at the surface was found to be 5.6º C and 4.0 Cº at 50 meters. Salinity at both the surface and 50 meters exhibited a semi-annual periodicity. Range of temperature at 200 meters was 1.5º C. The results of a seasonal linear regression analysis show that surface and 50 meter temperatures were correlated during periods of increasing or decreasing surface temperatures. Surface temperature and salinity were correlated only during the apparent advection of modified subarctic water into the region around OWS November.http://archive.org/details/astudyofsurfacem1094516832Lieutenant, United States NavyApproved for public release; distribution is unlimited

OPTIMAL PROPERTIES OF TWO ACTION DISCRETIZED LINEAR REWARD-INACTION LEARNING AUTOMATA.

A learning automation is a finite state machine which learns the optimal action from a set of actions offered to it by an environment. The automata considered have a variable structure and hence they are completely described by action probability updating functions. The action probabilities can take only a finite number of prespecified values. These values are linearly increasing and divide the interval into a number of equal length subintervals. The automata update the probability only if the environment responds with a reward and hence they are called Discretized Linear Reward-Inaction (DL//R//I) automata. The asymptotic optimality of this family of automata is proved for all environments