Objective To establish a high-precision and highly interpretable predictive model to address the challenges faced by constructing predictive models for high-dimensional omics data,such as many potential predictive factors,limited sample size,and high correlation between predictive factors.Methods Unify spike and slab priors and elastic network penalties into the Cox model and propose the spike and slab priors elastic network Cox model.This model can shrink the coefficients to varying degrees based on the importance of different variables.Use the expectation-maximization algorithm coordinate descent algorithm to fit the model,which estimates parameters by maximizing a posterior probability within a Bayesian framework.Results In different simulation experimental scenarios,the spike and slab prior elastic network Cox model exhibited higher sensitivity,balance accuracy,and concordance index than traditional models.In the validation analysis of real datasets,the concordance index of this model is also higher than that of traditional models.Conclusion The spike and slab prior elastic network Cox model is a new variable screening and survival prediction method that can handle high-dimensional omics data in cancer research.

Objective To establish a high-precision and highly interpretable predictive model to address the challenges faced by constructing predictive models for high-dimensional omics data,such as many potential predictive factors,limited sample size,and high correlation between predictive factors.Methods Unify spike and slab priors and elastic network penalties into the Cox model and propose the spike and slab priors elastic network Cox model.This model can shrink the coefficients to varying degrees based on the importance of different variables.Use the expectation-maximization algorithm coordinate descent algorithm to fit the model,which estimates parameters by maximizing a posterior probability within a Bayesian framework.Results In different simulation experimental scenarios,the spike and slab prior elastic network Cox model exhibited higher sensitivity,balance accuracy,and concordance index than traditional models.In the validation analysis of real datasets,the concordance index of this model is also higher than that of traditional models.Conclusion The spike and slab prior elastic network Cox model is a new variable screening and survival prediction method that can handle high-dimensional omics data in cancer research.

Objective: To investigate the methods for qualitative pathological assessment of dynamic changes in liver fibrosis/cirrhosis after antiviral therapy in patients with chronic hepatitis B (CHB), since antiviral therapy can partially reverse liver fibrosis and cirrhosis caused by hepatitis B and semi-quantitative, rather than qualitative, pathological assessment is often used for the research on liver fibrosis regression. Methods: Previously untreated CHB patients with liver fibrosis and cirrhosis were enrolled, and liver biopsy was performed before treatment and at 78 weeks after the antiviral therapy based on entecavir. The follow-up assessment was performed once every half a year. Based on the proportion of different types of fibrous septum, we put forward the new qualitative criteria called P-I-R classification (predominantly progressive, predominantly regressive, and indeterminate) for evaluating dynamic changes in liver fibrosis. This classification or Ishak fibrosis stage was used to evaluate the change in liver fibrosis after treatment and Ishak liver inflammation score was used to evaluate the change in liver inflammation after treatment. Results: A total of 112 CHB patients who underwent liver biopsy before and after treatment were enrolled, and among these patients, 71 with an Ishak stage of ≥3 and qualified results of live biopsy were included in the final analysis. Based on the P-I-R classification, 58% (41/71) were classified as predominantly progressive, 29% (21/71) were classified as indeterminate, and 13% (9/71) were classified as predominantly regressive; there were no significant differences between the three groups in alanine aminotransferase, aspartate aminotransferase, albumin, HBeAg positive rate, HBV DNA, and liver stiffness (P < 0.05). After treatment, the proportion of predominantly progressive, indeterminate, or predominantly regressive patients changed to 11% (8/71), 11% (8/71), and 78% (55/71), respectively. Among the 35 patients who had no change in Ishak stage after treatment, 72% (25/35) were classified as predominantly regressive and had certain reductions in the Laennec score, percentage of collagen area, and liver stiffness. Conclusion This new P-I-R classification can be used to assess the dynamic changes in liver fibrosis after antiviral therapy in CHB patients.

Mitophagy is an essential intracellular process that eliminates dysfunctional mitochondria and maintains cellular homeostasis. Mitophagy is regulated by the post-translational modification of mitophagy receptors. Fun14 domain-containing protein 1 (FUNDC1) was reported to be a new receptor for hypoxia-induced mitophagy in mammalian cells and interact with microtubule-associated protein light chain 3 beta (LC3B) through its LC3 interaction region (LIR). Moreover, the phosphorylation modification of FUNDC1 affects its binding affinity for LC3B and regulates selective mitophagy. However, the structural basis of this regulation mechanism remains unclear. Here, we present the crystal structure of LC3B in complex with a FUNDC1 LIR peptide phosphorylated at Ser17 (pS), demonstrating the key residues of LC3B for the specific recognition of the phosphorylated or dephosphorylated FUNDC1. Intriguingly, the side chain of LC3B Lys49 shifts remarkably and forms a hydrogen bond and electrostatic interaction with the phosphate group of FUNDC1 pS. Alternatively, phosphorylated Tyr18 (pY) and Ser13 (pS) in FUNDC1 significantly obstruct their interaction with the hydrophobic pocket and Arg10 of LC3B, respectively. Structural observations are further validated by mutation and isothermal titration calorimetry (ITC) assays. Therefore, our structural and biochemical results reveal a working model for the specific recognition of FUNDC1 by LC3B and imply that the reversible phosphorylation modification of mitophagy receptors may be a switch for selective mitophagy.
Crystallography, X-Ray ; Membrane Proteins ; chemistry ; metabolism ; Microtubule-Associated Proteins ; chemistry ; metabolism ; Mitochondrial Degradation ; Mitochondrial Proteins ; chemistry ; metabolism ; Peptides ; chemistry ; metabolism ; Phosphorylation ; Protein Structure, Quaternary