Aldosterone resistance, defined as absent kaliuretic response to exogenous hormone, has been described in K depletion. It is not clear whether the absent kaliuresis is due to activation of K-conserving mechanisms or to failure of activation of the Na-K pump in cortical collecting tubules (CCT) by mineralocorticoids. Adrenalectomized male Sprague-Dawley rats were allocated to either a normal or low-K diet. Na-K pump activity (pmol.mm-1.h-1) in microdissected CCT and medullary collecting tubules (MCT, inner stripe of the outer medulla) was determined at 7 or 21 days after allocation to the dietary groups before and after exogenous aldosterone (50 micrograms twice daily, for 3 days). K depletion led to progressive hypertrophic changes in the CCT and MCT manifest in an increase in basal Na-K pump activity. In both K repletion and short-term K depletion (7 days), aldosterone led to the expected increase in CCT Na-K pump activity. With long-term K depletion, the CCT Na-K pump response to aldosterone was blunted. In the MCT where under normal conditions the Na-K pump is aldosterone unresponsive, an increasing aberrant responsiveness to the mineralocorticoid was observed with progressive K depletion. We conclude that apparent aldosterone resistance in short-term K depletion is likely due to activation of K-conserving mechanisms with early preservation of the CCT biochemical response to the hormone. With long-term K depletion, a blunted biochemical response to aldosterone may contribute to the absent kaliuretic response. In the MCT, K depletion led to the development of aberrant responsiveness to aldosterone.
Sampling technology has been widely deployed in measurement systems to control memory consumption and processing overhead. However, most of the existing sampling methods suffer from large estimation errors in analyzing small-size flows. To address the problem, we propose a novel adaptive non-linear sampling (ANLS) method for passive measurement. Instead of statically configuring the sampling rate, ANLS dynamically adjusts the sampling rate for a flow depending on the number of packets having been counted. We provide the generic principles guiding the selection of sampling function for sampling rate adjustment. Moreover, we derive the unbiased flow size estimation, the bound of the relative error, and the bound of required counter size for ANLS. The performance of ANLS is thoroughly studied through theoretic analysis and experiments under synthetic/real network data traces, with comparison to several related sampling methods. The results demonstrate that the proposed ANLS can significantly improve the estimation accuracy, particularly for small-size flows, while maintain a memory and processing overhead comparable to existing methods.
Sampling technology has been widely deployed in measurement systems to control memory consumption and processing overhead. However, most of the existing sampling methods suffer from large estimation errors in analyzing small-size flows. To address the problem, we propose a novel adaptive non-linear sampling (ANLS) method for passive measurement. Instead of statically configuring the sampling rate, ANLS dynamically adjusts the sampling rate for a flow depending on the number of packets having been counted. We provide the generic principles guiding the selection of sampling function for sampling rate adjustment. Moreover, we derive the unbiased flow size estimation, the bound of the relative error, and the bound of required counter size for ANLS. The performance of ANLS is thoroughly studied through theoretic analysis and experiments under synthetic/real network data traces, with comparison to several related sampling methods. The results demonstrate that the proposed ANLS can significantly improve the estimation accuracy, particularly for small-size flows, while maintain a memory and processing overhead comparable to existing methods.
Journal Article Corrected proof Evaluating the effects of surgery on health-related quality of life in asymptomatic meningioma patients Get access YiChun Chen, YiChun Chen College of Life Science, Brigham Young University, Provo, Utah, USA Search for other works by this author on: Oxford Academic Google Scholar Saachi Jhandi, Saachi Jhandi School of Medicine, University of Utah, Salt Lake City, Utah, USA Search for other works by this author on: Oxford Academic Google Scholar Randy L Jensen Randy L Jensen Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USADepartments of Neurosurgery, Radiation Oncology and Medical Oncology, University of Utah, Salt Lake City, Utah, USA Corresponding Author: Randy L. Jensen, MD, PhD, MHPE, Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, 175 N, Medical Drive East, Salt Lake City, UT 84132, USA (neuropub@hsc.utah.edu). Search for other works by this author on: Oxford Academic Google Scholar Neuro-Oncology Practice, npae070, https://doi.org/10.1093/nop/npae070 Published: 12 August 2024 Article history Published: 12 August 2024 Corrected and typeset: 23 August 2024
It is highly desirable and important for end users, with no special privileges, identify and pinpoint faults inside the network that degrade the performance of their applications. However, existing tools are inaccurate to infer the link-level loss rates and have large diagnosis granularity (in terms of the number of hops). To address these problems, we propose a suite of user-level diagnosis approaches in two categories: (1) only need to be deployed at the source and (2) deployed at both source and destination. For the former, we propose two fragmentation aided diagnosis approaches (FAD), Algebraic FAD and Opportunistic FAD, which uses IP fragmentation to enable accurate link-level loss rate inference. For the latter category, we propose Striped Probe Analysis (SPA) which significantly improves the diagnosis granularity over those of the source-only approaches. Internet experiments are applied to evaluate each individual schemes (including an improved version of the state-of-the-art tool, Tulip [1]) and various hybrid approaches. The results indicate that our approaches dramatically outperform existing work (especially for diagnosis granularity) and provide not only the best performance but also smooth tradeoff among deployment requirement, diagnosis accuracy and granularity.
To evaluate whether hypothyroidism alters the adaptive responses of renal transport adenosine-triphosphatases (ATPases) to modifications in dietary K content, we examined the activities of Na-K pump and H-K pump in hypothyroid rats under basal conditions and after dietary K changes. Hypothyroidism led to a decline in Na-K pump activity in all three nephron segments examined [proximal convoluted tubule from 2,333 +/- 103 to 1,099 +/- 32, medullary thick ascending limb from 4,344 +/- 119 to 1,613 +/- 61, and cortical collecting tubule (CCT) from 1,133 +/- 45 to 640 +/- 38 pmol.mm-1 x h-1; all P < 0.01 vs. euthyroid] along with morphological changes manifest in a decrease in tubule diameter. K loading led to an increase in Na-K pump activity in the CCT of both euthyroid (from 1,133 +/- 45 to 2,269 +/- 74, pmol.mm-1 x h-1, P < 0.01) and hypothyroid (from 640 +/- 38 to 1,118 +/- 67 pmol.mm-1 x h-1, P < 0.01) animals. Furthermore, in euthyroid rats, 3 wk of K depletion led to a major increase in H-K pump activity in both the CCT (from 203 +/- 14 to 331 +/- 22 pmol.mm-1 x h-1, P < 0.01) and medullary collecting tubule (MCT, from 137 +/- 9 to 210 +/- 14 pmol.mm-1 x h-1, P < 0.01). Hypothyroidism was associated with a decline in H-K pump activity in the CCT and MCT (to 94 +/- 6 and 55 +/- 5 pmol.mm-1 x h-1, respectively; both P < 0.01 vs. euthyroid).(ABSTRACT TRUNCATED AT 250 WORDS)
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