Search

Peripheral blood stem cell transplantation (PBSCT) has made amyloid light‐chain (AL) amyloidosis treatable. After PBSCT, hematological complete remission (HCR) can be achieved, leading to improved renal prognosis. The purpose of this study was to evaluate whether whole slide imaging of biopsy samples shows a post‐treatment reduction in amyloid deposits in patients with AL amyloidosis. Patients were divided into three groups: Group A (n = 8), not eligible for PBSCT and treated with other therapies; Group B (n = 11), treated with PBSCT and achieved HCR; and Group C (n = 5), treated with PBSCT but did not achieve HCR. Clinical findings and amyloid deposition in glomeruli, interstitium, and blood vessels were compared before and after treatment using digital whole‐slide imaging. Proteinuria and hypoalbuminemia improved more in Group B than in the other groups, and in Group B, amyloid deposition improved more in the glomeruli than in the interstitium and blood vessels. The long‐term renal and survival prognosis was better in Group B than in the other groups. PBSCT can be expected to improve long‐term clinical and renal histological prognosis in patients with AL amyloidosis who achieve HCR. Amyloid disappearance from renal tissue may take a long time even after clinical HCR. [ABSTRACT FROM AUTHOR]

Robot manipulation in a physically constrained environment requires compliant manipulation. Compliant manipulation is a manipulation skill to adjust hand motion based on the force imposed by the environment. Recently, reinforcement learning (RL) has been applied to solve household operations involving compliant manipulation. However, previous RL methods have primarily focused on designing a policy for a specific operation that limits their applicability and requires separate training for every new operation. We propose a constraint-aware policy that is applicable to various unseen manipulations by grouping several manipulations together based on the type of physical constraint involved. The type of physical constraint determines the characteristic of the imposed force direction; thus, a generalized policy is trained in the environment and reward designed on the basis of this characteristic. This paper focuses on two types of physical constraints: prismatic and revolute joints. Experiments demonstrated that the same policy could successfully execute various compliant manipulation operations, both in the simulation and reality. We believe this study is the first step toward realizing a generalized household robot. [ABSTRACT FROM AUTHOR]