Methacrylate-based copolymers as tunable hosts for triplet-triplet annihilation upconversion.

The ability to convert light to higher energies through triplet-triplet annihilation upconversion (TTA-UC) is attractive for a range of applications including solar energy harvesting, bioimaging and anti-counterfeiting. Practical applications require integration of the TTA-UC chromophores within a suitable host, which leads to a compromise between the high upconversion efficiencies achievable in liquids and the durability of solids. Herein, we present a series of methacrylate copolymers as TTA-UC hosts, in which the glass transition temperature ( ), and hence upconversion efficiency can be tuned by varying the co-monomer ratios (-hexyl methacrylate (HMA) and 2,2,2-trifluoroethyl methacrylate (TFEMA)).

Tibiofemoral cartilage strain and recovery following a 3-mile run measured using deep learning segmentation of bone and cartilage.

Objective: We sought to measure the deformation of tibiofemoral cartilage immediately following a 3-mile treadmill run, as well as the recovery of cartilage thickness the following day. To enable these measurements, we developed and validated deep learning models to automate tibiofemoral cartilage and bone segmentation from double-echo steady-state magnetic resonance imaging (MRI) scans.

Design: Eight asymptomatic male participants arrived at 7 a.

Amplitude and Phase Changes in Electrocochleographic Real-Time Recordings During Cochlear Implantation and Its Relation to Pre- and Postoperative Hearing.

Background: The aim of this study was to relate response patterns of electrocochleography (ECochG) recordings during cochlear implantation to pre- and postoperative hearing.

Methods: Thirty subjects with either flat (FA, n = 9) or sloping (SA, n = 21) audiograms before cochlear implantation were prospectively included. Real-time ECochG recordings were conducted via the cochlear implant.

Integrated View of Baseline Protein Expression in Human Tissues Using Public Data Independent Acquisition Data Sets.

The PRIDE database is the largest public data repository of mass spectrometry-based proteomics data and currently stores more than 40,000 data sets covering a wide range of organisms, experimental techniques, and biological conditions. During the past few years, PRIDE has seen a significant increase in the amount of submitted data-independent acquisition (DIA) proteomics data sets. This provides an excellent opportunity for large-scale data reanalysis and reuse.