Min Huang

Prediction of ROR1 and CAV1 expression from whole-exome sequencing of tumor tissue and plasma cfDNA to infer the efficacy of B013 plus nab-paclitaxel in triple-negative breast cancer

The paper predicts ROR1 and CAV1 expression from whole-exome sequencing data to assess response to B013 plus nab-paclitaxel in triple-negative breast cancer, showing agreement with observed responses in 9 out of 10 patients.

Methodological assessment of PDMS passive sampling for skin VOC collection across body sites

This study evaluates a simplified PDMS sampling method for skin VOC collection, finding it captures individual VOC profiles with lower within-donor variability than between-donor variability.

Single-cell Landscape of T Cell Heterogeneity in Kawasaki Disease: STAT3/JAK Axis Regulates the Lineage Differentiation Bias of Th17 Cells

The paper uses scRNA-seq to analyze T-cell subtypes in Kawasaki disease, identifying a Th17 differentiation bias regulated by the STAT3/JAK axis during acute inflammation.

In Vivo Evolution of Monoclonal Antibody CR3022 to Achieve Cross-Neutralization of SARS-CoV-2 and Implications for Vaccine Strategies Against SARS-Related Viruses

This study shows that CR3022-like antibodies can be evolved in vivo through vaccination to neutralize SARS-CoV-2 and related viruses by enhancing affinity and breadth.

Comparative analysis of RNA expression in a single institution cohort of pediatric cancer patients

The paper evaluates the CARE pipeline for identifying druggable targets in pediatric cancers using RNA-Seq data from 33 patients, showing 94% of cases had clinically significant findings.

Uridine Metabolism as a Targetable Metabolic Achilles' Heel for chemo-resistant B-ALL

This study identifies uridine metabolism as a therapeutic target for chemo-resistant B-ALL by linking active signaling to uridine dependency and demonstrating DHODH inhibition as a promising treatment.

High-throughput and scalable single cell proteomics identifies over 5000 proteins per cell

This study improves single-cell proteomics by increasing protein identification from ~2000 to over 5000 per cell and enhancing throughput and reliability.