Neuropilin-2 expression in breast cancer: correlation with lymph node metastasis, poor prognosis, and regulation of CXCR4 expression

<p>Abstract</p> <p>Background</p> <p>Neuropilin-2 (Nrp2) is a receptor for vascular endothelial growth factor-C (VEGF-C), which is a well-known lymphangiogenic factor and plays an important role in lymph node metastasis of various human cancers, including breast cancer. Recently, Nrp2 was shown to play a role in cancer by promoting tumor cell metastasis. CXC chemokine receptor 4 (CXCR4) also promotes tumor metastasis. In the previous studies, we demonstrated that VEGF-C and cytoplasmic CXCR4 expressions were correlated with poorer patient prognosis (BMC Cancer 2008,8:340; Breast Cancer Res Treat 2005, 91:125–132).</p> <p>Methods</p> <p>The relationship between Nrp2 expression and lymph node metastasis, VEGF-C expression, CXCR4 expression, and other established clinicopathological variables (these data were cited in our previous papers), including prognosis, was analyzed in human breast cancer. Effects of neutralizing anti-Nrp2 antibody on CXCR4 expression and chemotaxis were assessed in MDA-MB-231 breast cancer cells.</p> <p>Results</p> <p>Nrp2 expression was observed in 53.1% (60 of 113) of the invasive breast carcinomas. Nrp2 expression was significantly correlated with lymph node metastasis, VEGF-C expression, and cytoplasmic CXCR4 expression. Survival curves determined by the Kaplan-Meier method showed that Nrp2 expression was associated with reduced overall survival. In multivariate analysis, Nrp2 expression emerged as a significant independent predictor for overall survival. Neutralizing anti-Nrp2 antibody blocks cytoplasmic CXCR4 expression and CXCR4-induced migration in MDA-MB-231 cells.</p> <p>Conclusion</p> <p>Nrp2 expression was correlated with lymph node metastasis, VEGF-C expression, and cytoplasmic CXCR4 expression. Nrp2 expression may serve as a significant prognostic factor for long-term survival in breast cancer. Our data also showed a role for Nrp2 in regulating cytoplasmic CXCR4 expression <it>in vitro</it>.</p

Trends in template/fragment-free protein structure prediction

Predicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all &gt;0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council

A new theoretical approach to biological self-assembly

Upon biological self-assembly, the number of accessible translational configurations of water in the system increases considerably, leading to a large gain in water entropy. It is important to calculate the solvation entropy of a biomolecule with a prescribed structure by accounting for the change in water–water correlations caused by solute insertion. Modeling water as a dielectric continuum is not capable of capturing the physical essence of the water entropy effect. As a reliable tool, we propose a hybrid of the angle-dependent integral equation theory combined with a multipolar water model and a morphometric approach. Using our methods wherein the water entropy effect is treated as the key factor, we can elucidate a variety of processes such as protein folding, cold, pressure, and heat denaturating of a protein, molecular recognition, ordered association of proteins such as amyloid fibril formation, and functioning of ATP-driven proteins

Monitoring of cutting process in end milling of hard and brittle materials

Glass materials have been widely used in optical components in recent years. The purpose of this study was to develop an effective method for real-time detection of the state of cutting tools used in end milling of hard brittle materials. Cutting tests were performed to identify parameters that are useful in monitoring micro tool wear in glass milling. A specific component of the cutting force was found to be related to the progression of tool wear. Furthermore, using fast Fourier transform (FFT) analysis, the peak amplitudes of the cutting forces were found to occur at a specific frequency