Aurophilic interaction-based aggregation of gem-digold(I) aryls towards high spin-orbit coupling and strong phosphorescence.

Luminescent gold(I) compounds have attracted intensive attention due to anticipated strong spin-orbit coupling (SOC) resulting from heavy atom effect of gold atoms. However, some mononuclear gold(I) compounds are barely satisfactory. Here, we unveil that low participation of gold in transition-related orbitals, caused by 6s-π symmetry mismatch, is the cause of low SOCs in monogold(I) compounds.

Simultaneous Isolation and Preparation of Extracellular Vesicles by Circular Multicavity Electrophoresis.

Extracellular vesicles (EVs) play a crucial role in diagnosis and treatment, yet obtaining highly purified EVs from complex biological samples is often hindered by nanoscale contaminants. In this work, considering the charge-to-size characteristics of EVs, a circular multicavity electrophoresis (CME) with gradient pore size distribution was constructed in the gradient electric field to realize the isolation and preparation of EVs. By the gradient gel sieving effect, small cell debris, EVs, and proteins in biological samples were gradually separated.

R(3780) Resonance Interpreted as the 1^{3}D_{1}-Wave Dominant State of Charmonium from Precise Measurements of the Cross Section of e^{+}e^{-}→Hadrons.

We report the precise measurements of the cross section of e^{+}e^{-}→hadrons at center-of-mass energies from 3.645 to 3.871 GeV.

AMPK-regulated glycerol excretion maintains metabolic crosstalk between reductive and energetic stress.

Glucose metabolism has been studied extensively, but the role of glucose-derived excretory glycerol remains unclear. Here we show that hypoxia induces NADH accumulation to promote glycerol excretion and this pathway consumes NADH continuously, thus attenuating its accumulation and reductive stress. Aldolase B accounts for glycerol biosynthesis by forming a complex with glycerol 3-phosphate dehydrogenases GPD1 and GPD1L.

Exploring factors affecting patient satisfaction in online healthcare: A machine learning approach grounded in empathy theory.

Objective: Empathy between doctors and patients is crucial in enhancing patient satisfaction with medical consultations. This study, grounded in empathy theory, employs natural language processing and machine learning algorithms to explore the factors influencing patient satisfaction in online healthcare services, particularly the impact of doctor-patient empathy.

Methods: Utilizing the three dimensions of the Jefferson Scale of Physician Empathy, seven variables were extracted from patient-doctor dialogs as independent variables, with patient satisfaction as the dependent variable.