Supporting the Individualized Use of Digital Tools in Community Mental Health: The Technology Specialist Pilot Study.

This pilot study evaluated the feasibility of the technology specialist intervention, which assists clients in achieving mental health recovery and well-being goals via existing digital tools in a real-world community mental health setting. Thirteen adult clients with serious mental illness and their providers completed baseline, 3-, and 6-month assessments, including goal setting, self-efficacy, activation, and acceptability measures, along with weekly ecological momentary assessments. Clients selected goals and corresponding tools, used the tools steadily, and showed improvement in activation and self-efficacy.

Multiplexed and Multiomic Mass Spectrometry Imaging of MALDI-IHC Photocleavable Mass Tag Tissue Probes, N-Glycomics, and the Extracellular Matrisome from FFPE Tissue Sections.

Recent work in single-cell imaging has allowed unprecedented insight into single-cell interactions that control disease progression. However, approaches to understanding the combined extracellular and cellular microenvironment are limited. In the current protocol, we describe an approach that allows single-cell type imaging using matrix-assisted laser desorption/ionization immunohistochemistry (MALDI-IHC) of UV (ultraviolet) photocleavable mass tags combined with N-glycomic and ECM-targeted proteomic imaging from the same formalin-fixed paraffin-embedded tissue section.

Participation in individual placement support: Ethnoracial differences in the supported employment demonstration.

Objective: The Supported Employment Demonstration (SED), a large, multisite randomized controlled trial, provided evidence-based supported employment to help individuals recently denied Social Security disability benefits for reason of mental illness to gain competitive employment and avoid disability. Monthly, client-level measurement of participation in individual placement and support permitted the first detailed exploration of potential ethnoracial disparities in the IPS participation process, from enrollment to end of follow-along job supports, in a vulnerable population with ready access to the intervention.

Method: Monthly participation data in a subsample of enrollees randomized to receive supported employment enabled decomposition of IPS service participation into take-up, effectiveness, and follow-along support phases, yielding times to participation duration milestones, job start, and end of follow-along supports for 614 non-Hispanic White, non-Hispanic Black, and Hispanic SED enrollees.

Spatial omics-based machine learning algorithms for the early detection of hepatocellular carcinoma.

Background: Worldwide, hepatocellular carcinoma (HCC) is the second most lethal cancer, although early-stage HCC is amenable to curative treatment and can facilitate long-term survival. Early detection has proved difficult, as proteomics, transcriptomics, and genomics have been unable to discover suitable biomarkers.

Methods: To find new biomarkers of HCC, we utilized a spatial omics N-glycan imaging method to identify altered glycosylation in cancer tissue (n = 53) and in paired serum of individuals with HCC (n = 23).

Bridging the Research-to-Practice Gap: The Individual Placement and Support Model.

The Research-to-Practice Gap often hinders the translation of effective healthcare interventions from clinical trials to routine care. Individual Placement and Support (IPS), an evidence-based practice designed to help individuals with mental health conditions achieve and maintain employment, has notably bridged this gap. Unlike many interventions that struggle with widespread implementation, IPS has successfully scaled to over 2,000 programs across all U.