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Background: Personalisation strategies of ovarian stimulation for in vitro fertilisation (IVF)/ intracytoplasmic sperm injection (ICSI) treatments using exogenous follicle-stimulating hormone (FSH) have been extensively studied over the past 20 years. This research aimed to develop a FSH population pharmacokinetic (PPK) model taking into account the contribution of gene polymorphisms in Chinese reproductive-age women. Methods: Data from 173 patients undergoing GnRH agonist down-regulation long protocols of IVF/ICSI treatment were collected. PPK analysis was subsequently conducted using the nonlinear mixed-effect model (NONMEM) software. Several covariates, including 18 single nucleotide polymorphisms, demographic factors and biological characteristics, were evaluated. The final PPK model was extensively validated using bootstrapping and normalised prediction error distribution, as well as external validation on an independent group of 35 patients. Results: FSH PPK was accurately described by a one-compartment model with first-order absorption. The typical population value of apparent clearance was estimated to be 0.81 L/h [relative standard errors (RSE) 5.3%] with an inter-individual variability (IIV) of 16.0%. The typical apparent distribution volume was 8.36 L (RSE 9.7%, 59.7% IIV), and the absorption rate constant was estimated to be 0.0444 h−1 (RSE 9.1%). Body weight, basal prolactin concentration and the gene ADIPOQ (rs1501299) showed a significant covariate effect on the FSH clearance rate and exposure concentration. Genotypes of THADA (rs12478601) significantly influenced the distribution volume. Simulation results indicated that patients with the TT genotype of THADA (rs12478601) required a longer time to reach steady state and had less fluctuation in FSH levels. Model evaluations showed that the final model accurately and precisely described the observed data and demonstrated effective prediction performance. Conclusion: PPK models of FSH have been developed, which could potentially be used for FSH dosage individualisation in the clinical setting. Clinical trial registration: This study has been registered with the Chinese Clinical Trials Registry (ChiCTR2100049142). [ABSTRACT FROM AUTHOR]

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel coronavirus causing the COVID-19 pandemic in 2020. High adaptive plasticity on the spike protein of SASR-CoV-2 enables it to transmit across different host species. In the present study, we collected 2092 high-quality genome sequences of SARS-CoV-2 from 160 regions in over 50 countries and reconstructed their phylogeny. We also analyzed the polymorphic interaction between spike protein and human ACE2 (hACE2). Phylogenetic analysis of SARS-CoV-2 suggests that SARS-CoV-2 is probably originated from a recombination event on the spike protein between a bat coronavirus and a pangolin coronavirus that endows it humans infectivity. Compared with other regions in the S gene of SARS-CoV-2, the direct-binding sites of the receptor-binding domain (RBD) is more conserved. We focused on 3,860 amino acid mutations in spike protein RBD (T333-C525) of SARS-CoV-2 and simulated their differential stability and binding affinity to hACE2 (S19-D615). The results indicate no preference for SARS-CoV-2 infectivity on people of different ethnic groups. The variants in the spike protein of SARS-CoV-2 may also be a good indicator demonstrating the transmission route of SARS-CoV-2 from its natural reservoir to human hosts. [ABSTRACT FROM AUTHOR]

The article proposes a fast reconstruction algorithm for ℓ0⩽p⩽1 norm nonconvex model, called Gradient projection nonconvex sparse recovery (GPNSR), which makes a good performance in high-quality image reconstruction. We apply the GPNSR into canonical multiple description coding theory and propose a robust high-quality compressed sensing-based coding method. Combined with iterative weighted technique and fast gradient descent method, the proposed method implicitly implements matrix inverse operations to highly reduce the storage pressure. Also the weighted norm method is taken to optimize the descent steps, which highly increases convergent speed of the algorithm. Taking an image has sparse Fourier representations as an example, the paper presents the detailed image sparse coding and fast reconstruction procedure. By integrating the compressive sensing multi-description coding framework, the simulation demonstrates the superior reconstruction performance of the proposed algorithm. Most importantly, with p close to zero, the reconstruction performance of GPNSR can approximate that of ℓ0 norm optimization result. [ABSTRACT FROM AUTHOR]