IgG4-related digestive diseases: diagnosis and treatment

IgG4-related digestive diseases encompass a group of chronic inflammatory disorders characterized by autoimmune reactions and fibrosis affecting multiple digestive organs. These diseases are identified by elevated serum levels of IgG4 and the presence of IgG4-positive plasma cell infiltration in the affected sites, along with storiform fibrosis, obliterative phlebitis, and eosinophilic infiltration. Although extensive research has been conducted, a comprehensive understanding of these conditions remains elusive. Current clinical diagnosis often relies on the application of integrated diagnostic criteria for IgG4-related diseases, combined with specific organ involvement criteria. Distinguishing them from malignancies poses considerable challenges. Moreover, further investigations are required to elucidate the underlying pathogenic mechanisms and explore potential therapeutic interventions. This review provides a systematic classification of IgG4-related digestive diseases while discussing their diagnostic strategies, clinical presentations, and treatment modalities. The comprehensive insights shared herein aim to guide clinicians in their practice and contribute to the advancement of knowledge in this field

Kolmogorov-Smirnov Criterion Based Gamma Approximation for Lognormal Shadowing Models

To promote the applications of gamma approximation for lognormal shadowing models in a multitude of applications, we propose to use the Kolmogorov-Smirnov (K-S) criterion to enable channel parameter mapping in this paper. The resulting K-S criterion based lognormal-to-gamma channel model substitution (CMS) technique aims to provide statistically robust parameter mapping relations by minimizing the integrated squared error (ISE) between the original lognormal shadowing model and its gamma substitute. We study the ISE minimization problem in depth for this lognormal-to-gamma CMS technique and for the first time prove its convexity with respect to both the scale and shape parameters of the gamma substitute. Therefore, we can employ numerical optimization methods to solve the ISE minimization problem with the assured convergence and optimality. Numerical results presented in this paper verify the effectiveness and efficiency of the K-S criterion based lognormal-to-gamma CMS technique in comparison with those based on the moment matching (MM) and Kullback-Leibler (K-L) criteria