Background: Among dialysis patients in the last 10 years the incidence of intradialytic dysequilibrium syndrome and symptomatic hypotension has increased significantly. Profiled haemodialysis (PHD), a new dialysis technique based on intradialytic modulation of the dialysate sodium concentration according to pre-elaborated individual profiles, has been set up to reduce intradialytic imbalances and the incidence of dysequilibrium syndrome and symptomatic hypotension. The present paper illustrates a new mathematical model for solute kinetics, single-compartment for sodium and two-compartment for urea, aimed at improving the use of PHD. The model allows the sodium profile to be elaborated a priori, before each dialysis session, according to the patient's clinical needs and respecting the individual sodium mass removal and weight gain.
Method: The mathematical model was first derived and then applied to determining a rational dialysate sodium profile. A procedure which allows the method to be tuned to individual clinical needs on the basis of routine measurements performed before each session is also presented. The proposed method was validated in vivo during seven dialysis sessions, each performed on a different patient.
Results: The comparison between data predicted by the model and those obtained in vivo shows a good correspondence in particular concerning the time pattern of blood urea and sodium. The comparison between the model prediction and in vivo determined sodium and urea plasma curves showed standard deviations (2.25 mEq/l for sodium and 0.87 mmol/l for urea) only slightly higher than those attributable to laboratory measurement errors. Moreover, in vivo implementation of PHD by our model enables one to remove an amount of sodium mass comparable with the a priori quantity predicted by the model.
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Nucl Med Biol
January 2025
State Research Center-Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency, 123182 Moscow, Russia. Electronic address:
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Smartphone-based colorimetric (bio)sensing is a promising alternative to conventional detection equipment for on-site testing, but it is often limited by sensitivity to lighting conditions. These issues are usually avoided using housings with fixed light sources, increasing the cost and complexity of the on-site test, where simplicity, portability, and affordability are a priority. In this study, we demonstrate that careful optimization of color space can significantly boost the performance of smartphone-based colorimetric sensing, enabling housing-free, illumination-invariant detection.
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NIHR Collaboration for Applied Research (Wessex), University of Southampton, Southampton, United Kingdom. Electronic address:
Ongoing challenges in the provision of care, driven by growing care complexity and nursing shortages, prompt us to reconsider the basis for efficient division of nursing labour. In organising nursing work, traditionally the focus has been on identifying nursing tasks that can be delegated to other less expensive and less highly educated staff, in order to make best use of scarce resources. We argue that nursing care activities are connected and intertwined.
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Center for Water Research, Advanced Institute of Natural Sciences, Beijing Normal University, 519087 Zhuhai, China.
The new EU Urban Wastewater Treatment Directive requires stricter limits introducing quaternary treatments and poses significant challenges to achieving a sustainable environment. Advanced membrane-based treatment processes combined with mathematical models can be a good solution for facing the challenges above. Most existing literature on membrane filtration models primarily focuses on membrane bioreactors, lacking mechanistic models on ultrafiltration (UF) membranes.
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State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, China; Chinese Institute for Brain Research, China. Electronic address:
Episodic memories, particularly temporal order memory, are influenced by event boundaries. Although numerous theoretical and computational models have been developed to explain this phenomenon, creating a model that can explain a wide range of behavioral data and is supported by neural evidence remains a significant challenge. This study presented a new model, grounded in ample evidence of position coding, to account for the impact of event boundaries on temporal order memory.
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