Improvement of aortic valve stenosis by ApoA-I mimetic therapy is associated with decreased aortic root and valve remodelling in mice.

BACKGROUND AND PURPOSE: We have shown that infusions of apolipoprotein A-I (ApoA-I) mimetic peptide induced regression of aortic valve stenosis (AVS) in rabbits. This study aimed at determining the effects of ApoA-I mimetic therapy in mice with calcific or fibrotic AVS. EXPERIMENTAL APPROACH: Apolipoprotein E-deficient (ApoE(-/-) ) mice and mice with Werner progeria gene deletion (Wrn(Δhel/Δhel) ) received high-fat diets for 20 weeks. After developing AVS, mice were randomized to receive saline (placebo group) or ApoA-I mimetic peptide infusions (ApoA-I treated groups, 100 mg·kg(-1) for ApoE(-/-) mice; 50 mg·kg(-1) for Wrn mice), three times per week for 4 weeks. We evaluated effects on AVS using serial echocardiograms and valve histology. KEY RESULTS: Aortic valve area (AVA) increased in both ApoE(-/-) and Wrn mice treated with the ApoA-I mimetic compared with placebo. Maximal sinus wall thickness was lower in ApoA-I treated ApoE(-/-) mice. The type I/III collagen ratio was lower in the sinus wall of ApoA-I treated ApoE(-/-) mice compared with placebo. Total collagen content was reduced in aortic valves of ApoA-I treated Wrn mice. Our 3D computer model and numerical simulations confirmed that the reduction in aortic root wall thickness resulted in improved AVA. CONCLUSIONS AND IMPLICATIONS: ApoA-I mimetic treatment reduced AVS by decreasing remodelling and fibrosis of the aortic root and valve in mice.

An algorithmic approach to the diagnosis of NK and T cell lymphomas.

Lymphomas of natural killer (NK) and T cell lineages are uncommon disorders, although as a group they are more usually encountered in Asia compared to Western populations. In part due to their rarity, diagnosis and classification of T cell lymphomas often pose a challenge to clinicians and pathologists. Although there are morphological features that are characteristic of certain subtypes, correct classification of NK and T cell neoplasms relies heavily on the immunophenotype. With few exceptions, non-random genetic alterations such as translocations are less often seen in T cell neoplasms, adding to the diagnostic difficulty. Given these limitations, pathological diagnosis and classification of NK and T cell lymphomas are anything but straightforward. This paper attempts to present a practical algorithmic approach for the general pathologist who is confronted with these neoplasms.