Critical hubs of renal ischemia-reperfusion injury: endoplasmic reticulum-mitochondria tethering complexes.

Mitochondrial injury and endoplasmic reticulum (ER) stress are considered to be the key mechanisms of renal ischemia-reperfusion (I/R) injury. Mitochondria are membrane-bound organelles that form close physical contact with a specific domain of the ER, known as mitochondrial-associated membranes. The close physical contact between them is mainly restrained by ER-mitochondria tethering complexes, which can play an important role in mitochondrial damage, ER stress, lipid homeostasis, and cell death. Several ER-mitochondria tethering complex components are involved in the process of renal I/R injury. A better understanding of the physical and functional interaction between ER and mitochondria is helpful to further clarify the mechanism of renal I/R injury and provide potential therapeutic targets. In this review, we aim to describe the structure of the tethering complex and elucidate its pivotal role in renal I/R injury by summarizing its role in many important mechanisms, such as mitophagy, mitochondrial fission, mitochondrial fusion, apoptosis and necrosis, ER stress, mitochondrial substance transport, and lipid metabolism.

Machine learning in nephrology: scratching the surface.

Machine learning shows enormous potential in facilitating decision-making regarding kidney diseases. With the development of data preservation and processing, as well as the advancement of machine learning algorithms, machine learning is expected to make remarkable breakthroughs in nephrology. Machine learning models have yielded many preliminaries to moderate and several excellent achievements in the fields, including analysis of renal pathological images, diagnosis and prognosis of chronic kidney diseases and acute kidney injury, as well as management of dialysis treatments. However, it is just scratching the surface of the field; at the same time, machine learning and its applications in renal diseases are facing a number of challenges. In this review, we discuss the application status, challenges and future prospects of machine learning in nephrology to help people further understand and improve the capacity for prediction, detection, and care quality in kidney diseases.

The clinical significance of HRCT in evaluation of patients with rheumatoid arthritis-associated interstitial lung disease: a report from China.

The objective of this study is to describe the interstitial lung disease (ILD) in rheumatoid arthritis (RA) patients of China, and to study clinical significance of high-resolution computed tomography (HRCT) in evaluation and treatment. One hundred and ten Chinese patients (79 women and 31 man) diagnosed with RA between December 2008 to November 2009 were analyzed. According to the HRCT, 47 (42.73%) RA patients were diagnosed as ILD. Old age, smoking and pulmonary rales were closely related to ILD (P < 0.05). The main appearances of ILD were ground-glass (39.09%), honeycombing (4.55%), reticular patterns and consolidation (1.82%). Patients with reticular patterns and honeycombing were more likely to show the respiratory symptoms. It was also common to find other abnormal changes, such as fiber cord shadow (22.73%), lung markings fuzzy disorder (30%), pulmonary nodules (11.82%), emphysema (9.09%), bronchiectasis (3.64%), subpleural nodules (11.82%) and pleural thickening (24.55%). In treatment, honeycombing and subpleural nodules were more common in patients with methotrexate (MTX) and/or leflunomide treatment than without (P < 0.05). Other abnormal changes were no statistical significance (P > 0.05). Pulmonary involvement is common in RA patients, and it is suggested that HRCT could be a sensitive and useful way in evaluating the lung of RA patients.