Prosthetic Gait Achievement in an Elderly Patient with Chronic Limb-threatening Ischemia and High Complications Using a Novel Lipoprotein Apheresis.

Background: Chronic limb-threatening ischemia is a condition of the lower extremities that requires therapeutic intervention. It is characterized by ischemia, tissue loss, neuropathy, infection, and risk of amputation.

Case: An 82-year-old woman with a history of bilateral total knee arthroplasty and rheumatoid arthritis underwent a left ankle arthroplasty.

Association between phase angle and sarcopenia in patients with connective tissue diseases.

Background And Aims: Early detection and management of sarcopenia in patients with connective tissue diseases (CTDs) are essential. However, the relationship between the phase angle and sarcopenia in patients with CTDs is unknown. This study investigated the association between the phase angle and sarcopenia in patients with (CTDs) and determined the optimal phase angle cutoff values for the early detection of sarcopenia.

A Novel Deep Learning Approach for Analyzing Glomerular Basement Membrane Lesions in a Mouse Model of X-Linked Alport Syndrome.

Alport syndrome is a rare kidney disease typically more severe in males due to its X-linked inheritance. However, female patients with heterozygous X-linked Alport syndrome (XLAS) can develop renal failure over time, necessitating accurate pathologic assessment for effective therapy. A key pathologic finding in female patients with XLAS is the mosaic pattern of partial loss of α5 chains of type IV collagen (COL4α5).

EventPointMesh: Human Mesh Recovery Solely From Event Point Clouds.

How much can we infer about human shape using an event camera that only detects the pixel position where the luminance changed and its timestamp? This neuromorphic vision technology captures changes in pixel values at ultra-high speeds, regardless of the variations in environmental lighting brightness. Existing methods for human mesh recovery (HMR) from event data need to utilize intensity images captured with a generic frame-based camera, rendering them vulnerable to low-light conditions, energy/memory constraints, and privacy issues. In contrast, we explore the potential of solely utilizing event data to alleviate these issues and ascertain whether it offers adequate cues for HMR, as illustrated in Fig.