ABSTRACT
Human cells and zebrafish coexposed to nanoplastics and the sunscreen ingredient homosalate showed more plastics in tissues, estrogenic activity, and relevant gene expression changes than they showed after either exposure alone.
Subject(s)
Sunscreening Agents , Zebrafish , Sunscreening Agents/toxicity , Animals , Humans , Estrogens , Ultraviolet Rays , Microplastics/toxicityABSTRACT
In laboratory experiments, e-cigarettes generated aerosols containing nickel, lead, arsenic, manganese, and other toxic metals. None of the MODs, P ODs, or d-P ODs tested delivered completely metalfree aerosol.
Subject(s)
Arsenic , Electronic Nicotine Delivery Systems , Nicotine , Aerosols , ManganeseSubject(s)
Diabetic Nephropathies , Ethnicity , Healthcare Disparities , Racial Groups , Humans , Diabetic Nephropathies/epidemiology , Ethnicity/legislation & jurisprudence , Ethnicity/statistics & numerical data , Health Services Accessibility/legislation & jurisprudence , Health Services Accessibility/statistics & numerical data , Healthcare Disparities/legislation & jurisprudence , Healthcare Disparities/statistics & numerical data , Racial Groups/legislation & jurisprudence , Racial Groups/statistics & numerical dataABSTRACT
Many hospital supply chains in the US follow a "stockless" structure, often implemented with the acquisition of new systems promising improved efficiencies and responsiveness. Despite vendor promises, supply chain gains from new technology are often unfulfilled or result in a reduction of performance. A critical component of achieving promised gains is the hospital's ability to accurately and consistently capture hospital inventory use. In practice, recording demand with perfect, 100% accuracy is infeasible, so our models condition on the level of accuracy in a particular hospital department, or point-of-use (POU) inventory location. Similar to previous literature, we consider actual net inventory and recorded net inventory in developing the system performance measures. We develop two models, optimizing either cost or service level, and we assume a periodic-review, base-stock (or par-level) inventory policy with full backordering. In addition to choosing the optimal order-up-to level, we seek the optimal frequency of inventory counts to reconcile inaccurate records. Results from both models provide insights for supply chain managers in the hospital setting, as well as hospital administrators considering the adoption of similar technologies or systems.