Immunotherapy targeting isoDGR-protein damage extends lifespan in a mouse model of protein deamidation

\ua9 2023 The Authors. Published under the terms of the CC BY 4.0 license. Aging results from the accumulation of molecular damage that impairs normal biochemical processes. We previously reported that age-linked damage to amino acid sequence NGR (Asn-Gly-Arg) results in “gain-of-function” conformational switching to isoDGR (isoAsp-Gly-Arg). This integrin-binding motif activates leukocytes and promotes chronic inflammation, which are characteristic features of age-linked cardiovascular disorders. We now report that anti-isoDGR immunotherapy mitigates lifespan reduction of Pcmt1−/− mouse. We observed extensive accumulation of isoDGR and inflammatory cytokine expression in multiple tissues from Pcmt1−/− and naturally aged WT animals, which could also be induced via injection of isoDGR-modified plasma proteins or synthetic peptides into young WT animals. However, weekly injection of anti-isoDGR mAb (1 mg/kg) was sufficient to significantly reduce isoDGR-protein levels in body tissues, decreased pro-inflammatory cytokine concentrations in blood plasma, improved cognition/coordination metrics, and extended the average lifespan of Pcmt1−/− mice. Mechanistically, isoDGR-mAb mediated immune clearance of damaged isoDGR-proteins via antibody-dependent cellular phagocytosis (ADCP). These results indicate that immunotherapy targeting age-linked protein damage may represent an effective intervention strategy in a range of human degenerative disorders

Influence of the training set on the prediction stability in estimation of acute pancreatitis severity

The small sample size problem is often encountered in data analysis, especially for medical applications. It leads to unstable predictions when including or excluding several observations could change prediction significantly. Prediction stability visualization and measure were proposed and applied to estimation of acute pancreatitis severity. A simulation experiments were carried out to study the stability of ridge-regression, SVM, random forest trained with various subset

Influence of the training set on the prediction stability in estimation of acute pancreatitis severity

The small sample size problem is often encountered in data analysis, especially for medical applications. It leads to unstable predictions when including or excluding several observations could change prediction significantly. Prediction stability visualization and measure were proposed and applied to estimation of acute pancreatitis severity. A simulation experiments were carried out to study the stability of ridge-regression, SVM, random forest trained with various subset