Risk prediction for elderly cognitive impairment by radiomic and morphological quantification analysis based on a cerebral MRA imaging cohort.

Objective: To establish morphological and radiomic models for early prediction of cognitive impairment associated with cerebrovascular disease (CI-CVD) in an elderly cohort based on cerebral magnetic resonance angiography (MRA).

Methods: One-hundred four patients with CI-CVD and 107 control subjects were retrospectively recruited from the 14-year elderly MRA cohort, and 63 subjects were enrolled for external validation. Automated quantitative analysis was applied to analyse the morphological features, including the stenosis score, length, relative length, twisted angle, and maximum deviation of cerebral arteries.

A simple polydopamine-based platform for engineering extracellular vesicles with brain-targeting peptide and imaging probes to improve stroke outcome.

Extracellular vesicles (EVs) have shown great potential for treating various diseases. Translating EVs-based therapy from bench to bedside remains challenging due to inefficient delivery of EVs to the injured area and lack of techniques to visualize the entire targeting process. Here we developed a dopamine surface functionalization platform that facilitates easy and simultaneous conjugation of targeting peptide and multi-mode imaging probes to the surface of EVs.

Shell Dependence of Highly Tunable Circular Dichroism in Chiral Hybrid Plasmonic Nanomaterials for Chiroptical Applications.

Chiral plasmonic nanomaterials with fascinating physical and chemical properties show emerging chirality-dependent applications in photonics, catalysis, and sensing. The capability to precisely manipulate the plasmonic chirality in a broad spectral range plays a crucial role in enabling the applications of chiral nanomaterials in diverse and complex scenarios; however, it remains a challenge yet to be addressed. Here we demonstrate a strategy to significantly enhance the tunability of circular dichroism (CD) spectra of chiral nanomaterials by constructing core-shell hybrid metal-semiconductor structures with tailored shells.

A generalist medical language model for disease diagnosis assistance.

The delivery of accurate diagnoses is crucial in healthcare and represents the gateway to appropriate and timely treatment. Although recent large language models (LLMs) have demonstrated impressive capabilities in few-shot or zero-shot learning, their effectiveness in clinical diagnosis remains unproven. Here we present MedFound, a generalist medical language model with 176 billion parameters, pre-trained on a large-scale corpus derived from diverse medical text and real-world clinical records.

Delocalized Nonbonding Orbitals of Thioxanthone in Polycyclic Aromatic Hydrocarbons for Reduced Energy Gap and Narrowband Emission.

Chalcogen-containing carbonyls, specifically thioxanthone (TX), hold great potential in organic light-emitting diodes (OLEDs). While the development of narrowband OLEDs with chalcogen-containing carbonyls remains challenging due to difficulties in achieving both high device efficiency and narrow emission spectra. Herein, via a strategic incorporation of the TX moiety, two orange-red narrowband emitters, 2TXBN and BNTXBN, are designed and synthesized for the first time.