Nurses Improving Care for Healthsystem Elders (NICHE), a program of NYU Rory Meyers College of Nursing, is a national quality and safety program that enhances clinical nursing in the care of older adults. Hospitals, long-term care, and hospice organizations adopt the NICHE practice model to advance professional practice, improve quality of care, and expand capacity to meet the growing demand for age-friendly care. In this month's column, I highlight three clinical improvement projects that were developed during the NICHE Leadership Training Program. These projects represent the range of nurse-led services and clinical interventions that are the foundation of the NICHE philosophy and practice model.
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| http://dx.doi.org/10.1016/j.gerinurse.2023.10.011 | DOI Listing |
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Aerolysin Nanopore Electrochemistry.
Acc Chem Res
January 2025
Molecular Sensing and Imaging Center, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
ConspectusIons are the crucial signaling components for living organisms. In cells, their transportation across pore-forming membrane proteins is vital for regulating physiological functions, such as generating ionic current signals in response to target molecule recognition. This ion transport is affected by confined interactions and local environments within the protein pore.
View Article and Find Full Text PDFPsoas muscle gauge and adverse clinical outcomes in patients on hemodialysis.
J Nephrol
January 2025
Department of Nephrology, Matsunami General Hospital, Gifu, Japan.
Background: The relationship between the psoas muscle gauge (PMG), a combined sarcopenia indicator obtained from psoas muscle index (PMI) and psoas muscle density (PMD), and adverse clinical outcomes in patients on hemodialysis remains unclear. We examined whether psoas muscle gauge could predict all-cause mortality and new cardiovascular events more accurately than psoas muscle index in these patients.
Methods: We retrospectively included 217 hemodialysis patients who underwent abdominal computed tomography.
Purpose: This brief report aims to summarize and discuss the methodologies of eXplainable Artificial Intelligence (XAI) and their potential applications in surgery.
Methods: We briefly introduce explainability methods, including global and individual explanatory features, methods for imaging data and time series, as well as similarity classification, and unraveled rules and laws.
Results: Given the increasing interest in artificial intelligence within the surgical field, we emphasize the critical importance of transparency and interpretability in the outputs of applied models.
Molecular docking and differential rbcl gene expression reveal variation in glyphosate herbicide tolerance of sugarcane varieties.
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Agricultural Research Center(ARC), Sugar Crops Research Institute(SCRI), Giza, Egypt.
Background: Glyphosate is an extensively employed herbicide in agriculture, specifically for sugarcane cultivation. The situation is different with the extensive physiological and genetic effects exerted by this herbicide on a range of plant species, including sugarcane, whose model basis is still poorly characterized, although its primary mode of action, which acts on the EPSPS enzyme in the shikimic acid pathway, is completely elucidated. The current study was aimed at investigating the stability of glyphosate formulation, molecular interactions of glyphosate formulation with rbcL enzyme associated with chlorophyll metabolism, and its effects on varieties of sugarcane.
View Article and Find Full Text PDFImproving molecular subtypes and prognosis of pancreatic cancer through multi group analysis and machine learning.
Discov Oncol
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Department of Laboratory, the Second Hospital of Shanxi Medical University, No. 382, Wuyi Road, Taiyuan, 030001, Shanxi, People's Republic of China.
Background: Pancreatic cancer (PAC) has a complex tumor immune microenvironment, and currently, there is a lack of accurate personalized treatment. Establishing a novel consensus machine learning driven signature (CMLS) that offers a unique predictive model and possible treatment targets for this condition was the goal of this study.
Methods: This study integrated multiple omics data of PAC patients, applied ten clustering techniques and ten machine learning approaches to construct molecular subtypes for PAC, and created a new CMLS.
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