Strong light-matter interactions in both the single-emitter and collective strong coupling regimes attract significant attention due to emerging applications in quantum and nonlinear optics as well as opportunities for modifying material-related properties. Exploration of these phenomena is theoretically demanding, as polaritons exist at the intersection between quantum optics, solid state physics, and quantum chemistry. Fortunately, nanoscale polaritons can be realized in small plasmon-molecule systems, enabling treatment with ab initio methods. Here, we show that time-dependent density-functional theory calculations access the physics of nanoscale plasmon-molecule hybrids and predict vacuum Rabi splitting. By considering a system comprising a few-hundred-atom aluminum nanoparticle interacting with benzene molecules, we show that cavity quantum electrodynamics holds down to resonators of a few cubic nanometers in size, yielding a single-molecule coupling strength exceeding 200 meV due to a massive vacuum field of 4.5 V · nm. In a broader perspective, ab initio methods enable parameter-free in-depth studies of polaritonic systems for emerging applications.
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http://dx.doi.org/10.1038/s41467-019-11315-5 | DOI Listing |
Neurosurgery
February 2025
The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix , Arizona , USA.
Anatomic teaching has long informed surgical knowledge, experience, and skills. One tool for teaching that emerged during the Renaissance was the fugitive anatomic sheet, which used flap layers to reveal different levels of anatomy. In 1538, Vogtherr introduced the first fugitive sheets, which included illustrations of male and female figures with a torso paper flap that, when lifted, revealed the internal organs in a cartoonish style.
View Article and Find Full Text PDFInt Urol Nephrol
January 2025
Department of Intensive Care Unit, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, People's Republic of China.
Background: Acute kidney injury (AKI) is a significant clinical condition, and ultrasound examination has emerged as a crucial non-invasive imaging method for assessing kidney status, especially in its diagnosis and management. This study aims to perform a bibliometric analysis to clarify current research trends in ultrasound assessment of AKI.
Methods: We conducted a literature search in the Web of Science database using keywords related to ultrasound examinations of acute kidney injury, up to November 15, 2023.
Eur Biophys J
January 2025
Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China.
Compared to fluorescence, second harmonic generation (SHG) has recently emerged as an excellent signal for imaging probes due to its unmatched advantages in terms of no photobleaching, no phototoxicity, no signal saturation, as well as the superior imaging accuracy with excellent avoidance of background noise. Existing SHG probes are constructed from heavy metals and are cellular exogenous, presenting with high cytotoxicity, difficult cellular uptake, and the limitation of non-heritability. We, therefore, initially propose an innovative gene-encoded bioprotein SHG probe derived from Autographa californica nuclear polyhedrosis virus (AcMNPV) polyhedrin.
View Article and Find Full Text PDFActa Diabetol
January 2025
Division of Cardiology, Department of Internal Medicine, New Taipei Municipal TuCheng Hospital, New Taipei, Taiwan.
Purpose: Glucagon-like peptide 1 (GLP-1) receptor agonists (RAs) and basal insulin are currently used in the treatment of type 2 diabetes mellitus (T2DM) as long-acting injectables. In this study, we aimed to compare the cardiovascular (CV) and renal outcomes of GLP-1 RAs and basal insulin treatment in patients with T2DM.
Method: We conducted a propensity score-matched cohort study of patients from Chang Gung Memorial Hospital institutions between 2013 and 2021.
Handb Exp Pharmacol
January 2025
Genentech Inc, South San Francisco, CA, USA.
In this chapter, we envision the future of Quantitative Systems Pharmacology (QSP) which integrates closely with emerging data and technologies including advanced analytics, novel experimental technologies, and diverse and larger datasets. Machine learning (ML) and Artificial Intelligence (AI) will increasingly help QSP modelers to find, prepare, integrate, and exploit larger and diverse datasets, as well as build, parameterize, and simulate models. We picture QSP models being applied during all stages of drug discovery and development: During the discovery stages, QSP models predict the early human experience of in silico compounds created by generative AI.
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