renal-artery-function-histopathology-linked-to-plasma-fecal

Renal Artery Function and Histopathology Linked to Plasma and Fecal Metabolites in Heart Failure Patients

The gut microbiota and its associated host-microbe co-metabolites are increasingly recognized as key regulators of systemic metabolic balance and the ...

Peking University

Polarization manipulation is essential in almost every photonic system ranging from telecommunications to bio-sensing to quantum information. This is traditionally achieved using bulk waveplates. With the developing trend of photonic systems towards integration and miniaturization, the need for an on-chip waveguide type waveplate becomes extremely urgent. However, this is very challenging using conventional dielectric waveguides, which usually require complex 3D geometries to alter the waveguide symmetry and are also difficult to create an arbitrary optical axis. Recently, a waveguide waveplate was realized using femtosecond laser writing, but the device length is in millimeter range. Here, for the first time we propose and experimentally demonstrate an ultracompact, on-chip waveplate using an asymmetric hybrid plasmonic waveguide to create an arbitrary optical axis. The device is only in several microns length and produced in a flexible integratable IC compatible format, thus opening up the potential for integration into a broad range of systems.

On-chip plasmonic waveguide optical waveplate.

The importance of tacrolimus in the treatment of myasthenia gravis (MG) as a substitute for corticosteroid-dependent immunosuppressive therapy is increasing. Thus far, however, no population pharmacokinetic (PopPK) analysis of tacrolimus in treating MG patients has been published. This article aimed to construct a PopPK model of tacrolimus for Chinese MG patients with the goal of improving its performance in MG treatment. A total of 253 trough concentration records were obtained from 83 Chinese MG patients. The effects of demographics, lifestyle and health status, biochemical test data, disease progression and treatment-related information (including co-administered medications) as covariates on the various parameters were investigated. The covariate selection was based on biological plausibility, clinical significance, statistical significance and reduction in inter-individual variability (IIV). Bootstrap and normalized prediction distribution error (NPDE) analysis were performed to validate the final model. A one-compartment PopPK model with first-order elimination and a fixed absorption phase was constructed. The estimated apparent oral clearance (CL/F) and apparent oral volume of distribution (V/F) were 3.6 L/h and 1700 L, respectively, in the MG patients. Hematocrit and blood urea nitrogen were identified as two covariates that significantly influenced the CL/F. Immunoglobulin treatment (PRO) also had the potential to influence V/F, which was consistent with the clinical observations and the high protein-binding property of tacrolimus. Other covariates including age, weight, gender and co-administered medications had no obvious influence on CL/F or V/F. The first PopPK model of tacrolimus in MG patients was established. The identified covariates were of biological plausibility and clinical importance to help individualize the dosing schedule in MG patients.

Population pharmacokinetic analysis of tacrolimus in Chinese myasthenia gravis patients.

In chronic hepatitis B (CHB) treatment, hepatitis B surface antigen (HBsAg) is regarded as a promising clinical end point associated with long-term clinical outcomes. We performed a meta-analysis to characterize the dynamics and influencing factors of HBsAg.

Article	Year
On-chip plasmonic waveguide optical waveplate. Scientific reports\| PubMed ID: 26507563	2015
Population pharmacokinetic analysis of tacrolimus in Chinese myasthenia gravis patients. Acta pharmacologica Sinica\| PubMed ID: 28552913	2017
Dynamics of HBV surface antigen related end points in chronic hepatitis B infection: a systematic review and meta-analysis. Antiviral therapy\| PubMed ID: 32609658	2020

Yusi Chen

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