Arabidopsis ORP2A mediates ER-autophagosomal membrane contact sites and regulates PI3P in plant autophagy.

Autophagy is an intracellular degradation system for cytoplasmic constituents which is mediated by the formation of a double-membrane organelle termed the autophagosome and its subsequent fusion with the lysosome/vacuole. The formation of the autophagosome requires membrane from the endoplasmic reticulum (ER) and is tightly regulated by a series of autophagy-related (ATG) proteins and lipids. However, how the ER contacts autophagosomes and regulates autophagy remain elusive in plants. In this study, we identified and demonstrated the roles of Arabidopsis oxysterol-binding protein-related protein 2A (ORP2A) in mediating ER-autophagosomal membrane contacts and autophagosome biogenesis. We showed that ORP2A localizes to both ER-plasma membrane contact sites (EPCSs) and autophagosomes, and that ORP2A interacts with both the ER-localized VAMP-associated protein (VAP) 27-1 and ATG8e on the autophagosomes to mediate the membrane contact sites (MCSs). In ORP2A artificial microRNA knockdown (KD) plants, seedlings display retarded growth and impaired autophagy levels. Both ATG1a and ATG8e accumulated and associated with the ER membrane in ORP2A KD lines. Moreover, ORP2A binds multiple phospholipids and shows colocalization with phosphatidylinositol 3-phosphate (PI3P) in vivo. Taken together, ORP2A mediates ER-autophagosomal MCSs and regulates autophagy through PI3P redistribution.

Systemic risk factors of retinopathy in patients with systemic lupus erythematosus.

OBJECTIVE: To investigate the risk factors of lupus retinopathy (LR) in patients with systemic lupus erythematosus (SLE). METHODS: This is a retrospective, cross-sectional study. LR patients admitted at Peking Union Medical College Hospital from June 2013 to April 2023 were reviewed. Age- and gender-matched SLE patients without retinopathy were selected as controls. Medical records including clinical manifestations, laboratory data and ophthalmic examination were collected. Univariate and multivariate logistic regression analyses were conducted. RESULTS: One hundred and twelve LR patients (198 eyes) were included, with 12 cases (14 eyes) presenting with retinal macrovascular obstruction, and 100 cases (184 eyes) only exhibiting microvasculopathy. Multivariate analysis indicated the presence of haemolytic anaemia, decreased haemoglobin (HGB) and higher relative percentage of neutrophils were independent risk factors for LR (p < 0.05). The first two were also risk factors for retinal microvasculopathy, whereas secondary antiphospholipid syndrome (APS) was for macrovascular obstruction. In male group, LR had significant associations with decreased HGB, no matter which types of retinopathy (p < 0.05). In female group, LR was significantly associated with haemolytic anaemia, presence of antiphospholipid antibodies, decreased white blood cells and relative high percentage of neutrophils. Specifically, haemolytic anaemia (p = 0.002) was significantly associated with retinal microvasculopathy, and APS (p = 0.003) was significantly associated with macrovasculature obstruction. CONCLUSION: LR was related to haemolytic anaemia, decreased HGB levels and higher percentage of neutrophils. Retinal microvasculopathy accounted for most cases and macrovasculature obstructions were rare. Male and female patients have distinct risk factors. Early ophthalmic screening is recommended especially for those with risk factors of LR.

Determining individual suitability for neoadjuvant systemic therapy in breast cancer patients through deep learning.

BACKGROUND: The survival advantage of neoadjuvant systemic therapy (NST) for breast cancer patients remains controversial, especially when considering the heterogeneous characteristics of individual patients. OBJECTIVE: To discern the variability in responses to breast cancer treatment at the individual level and propose personalized treatment recommendations utilizing deep learning (DL). METHODS: Six models were developed to offer individualized treatment suggestions. Outcomes for patients whose actual treatments aligned with model recommendations were compared to those whose did not. The influence of certain baseline features of patients on NST selection was visualized and quantified by multivariate logistic regression and Poisson regression analyses. RESULTS: Our study included 94,487 female breast cancer patients. The Balanced Individual Treatment Effect for Survival data (BITES) model outperformed other models in performance, showing a statistically significant protective effect with inverse probability treatment weighting (IPTW)-adjusted baseline features [IPTW-adjusted hazard ratio: 0.51, 95% confidence interval (CI), 0.41-0.64; IPTW-adjusted risk difference: 21.46, 95% CI 18.90-24.01; IPTW-adjusted difference in restricted mean survival time: 21.51, 95% CI 19.37-23.80]. Adherence to BITES recommendations is associated with reduced breast cancer mortality and fewer adverse effects. BITES suggests that patients with TNM stage IIB, IIIB, triple-negative subtype, a higher number of positive axillary lymph nodes, and larger tumors are most likely to benefit from NST. CONCLUSIONS: Our results demonstrated the potential of BITES to aid in clinical treatment decisions and offer quantitative treatment insights. In our further research, these models should be validated in clinical settings and additional patient features as well as outcome measures should be studied in depth.