Do Hospital Characteristics Predict Racial-and-Ethnic Disparities in Patient Experience? National Results From the HCAHPS Survey.

OBJECTIVE: Assess whether hospital characteristics associated with better patient experiences overall are also associated with smaller racial-and-ethnic disparities in inpatient experience. BACKGROUND: Hospitals that are smaller, non-profit, and serve high proportions of White patients tend to be high-performing overall, but it is not known whether these hospitals also have smaller racial-and-ethnic disparities in care. RESEARCH DESIGN: We used linear mixed-effect regression models to predict a summary measure that averaged eight Hospital CAHPS (HCAHPS) measures (Nurse Communication, Doctor Communication, Staff Responsiveness, Communication about Medicines, Discharge Information, Care Coordination, Hospital Cleanliness, and Quietness) from patient race-and-ethnicity, hospital characteristics (size, ownership, racial-and-ethnic patient-mix), and interactions of race-and-ethnicity with hospital characteristics. SUBJECTS: Inpatients discharged from 4,365 hospitals in 2021 who completed an HCAHPS survey ( N =2,288,862). RESULTS: While hospitals serving larger proportions of Black and Hispanic patients scored lower on all measures, racial-and-ethnic disparities were generally smaller for Black and Hispanic patients who received care from hospitals serving higher proportions of patients in their racial-and-ethnic group. Experiences overall were better in smaller and non-profit hospitals, but racial-and-ethnic differences were slightly larger. CONCLUSIONS: Large, for-profit hospitals and hospitals serving higher proportions of Black and Hispanic patients tend to be lower performing overall but have smaller disparities in patient experience. High-performing hospitals might look at low-performing hospitals for how to provide less disparate care whereas low-performing hospitals may look to high-performing hospitals for how to improve patient experience overall.

Comparative analysis of asian carps parvalbumin reveals the divergence pattern of major fish allergen.

BACKGROUND: Asian carps, a popular freshwater fish globally, are valued for their flavor and serve as a crucial protein source, especially for infants. However, grass carp parvalbumin is highly allergenic, surpassing the allergenicity of fish like salmon and cod. The allergenic potential of parvalbumin in other Asian carps remains unknown, underscoring the need for allergen identification to improve the precision of fish allergy diagnosis and treatment. OBJECTIVE: To identify all parvalbumin homologs in Asian carps and investigate the role of gene divergence in allergenic homolog formation. METHODS: Three annotated genomes of Asian carp, including grass carp, black carp and bighead carp, were constructed using a hybrid assembly approach. Through sequence homology at the genomic level, all the homologs of major fish allergens were identified. Bioinformatics tools were then employed to reveal the gene structures, expression levels, and protein conformations of parvalbumin. RESULTS: Grass carp genome analysis showed nine parvalbumin homologs, with Cid_PV2 most similar to Cten i 1. Bighead and black carp genomes had ten homologs, including potentially allergenic Mpi_PV7 and Hno_PV7. Tissue-specific expression patterns revealed alternative usage of parvalbumin homologs. Gene duplication events expanded parvalbumin copies in bony fish, with two gene clusters identified in Asian carp genomes. CONCLUSION: All the homologs of Asian carps' parvalbumin were accurately identified and gene divergence contributed to the formation of allergenic homologs. Together with a comprehensive gene sequence profile of carps' parvalbumin, those could be applied to achieve a more precise clinical diagnostic test.

An HPLC-SEC-based rapid quantification method for vesicular stomatitis virus particles to facilitate process development.

Virus particle (VP) quantification plays a pivotal role in the development of production processes of VPs for virus-based therapies. The yield based on total VP count serves as a process performance indicator for evaluating process efficiency and consistency. Here, a label-free particle quantification method for enveloped VPs was developed, with potential applications in oncolytic virotherapy, vaccine development, and gene therapy. The method comprises size-exclusion chromatography (SEC) separation using high-performance liquid chromatography (HPLC) instruments. Ultraviolet (UV) was used for particle quantification and multi-angle light scattering (MALS) for particle characterization. Consistent recoveries of over 97% in the SEC were achieved upon mobile phase screenings and addition of bovine serum albumin (BSA) as sample stabilizer. A calibration curve was generated, and the method's performance and applicability to in-process samples were characterized. The assay's repeatability variation was <1% and its intermediate precision variation was <3%. The linear range of the method spans from 7.08 × 108 to 1.72 × 1011 VP/mL, with a limit of detection (LOD) of 7.72 × 107 VP/mL and a lower limit of quantification (LLOQ) of 4.20 × 108 VP/mL. The method, characterized by its high precision, requires minimal hands-on time and provides same-day results, making it efficient for process development.