Development and application of a quantitative LC-MS/MS assay for the analysis of four dental local anesthetics in human plasma and breast milk.

Local anesthetics (LAs: articaine, lidocaine, bupivacaine, and mepivacaine) are essential for dental pain management. However, there are concerns that the lipophilic LAs could cross into breast milk causing toxicity to the infant. Our objective was to establish a multi-analyte LC-MS/MS method for the concurrent quantification of local anesthetics (LAs) in human plasma and breast milk, clarifying the transfer of LAs from plasma to breast milk, thereby offering crucial data for the safe assessment of LAs during the nursing period.

Application of Pharmacometrics in Advancing the Clinical Research of Antibody-Drug Conjugates: Principles and Modeling Strategies.

Antibody-drug conjugates (ADCs) have become a pivotal area in the research and development of antitumor drugs. They provide innovative possibilities for tumor therapy by integrating the tumor-targeting capabilities of monoclonal antibodies with the cytotoxic effect of small molecule drugs. Pharmacometrics, an important discipline, facilitates comprehensive understanding of the pharmacokinetic characteristics of ADCs by integrating clinical trial data through modeling and simulation.

Application of Virtual Drug Study to New Drug Research and Development: Challenges and Opportunity.

In recent years, virtual drug study, as an emerging research strategy, has become increasingly important in guiding and promoting new drug research and development. Researchers can integrate a variety of technical methods to improve the efficiency of all phases of new drug research and development, including the use of artificial intelligence, modeling and simulation for target identification, compound screening and pharmacokinetic characteristics evaluation, and the application of clinical trial simulation to carry out clinical research. This paper aims to elaborate on the application of virtual drug study in the key stages of new drug research and development and discuss the opportunities and challenges it faces in supporting new drug research and development.

Co-Invasion of Congeneric Invasive Plants Adopts Different Strategies Depending on Their Origins.

Plant communities may be co-invaded by invasive plants, sometimes even by congeneric invasive plants (CIPs). Despite the growing understanding of co-invasion in the environment, little is known about how CIP interactions and mechanisms regulate co-invasion. Darwin's naturalisation conundrum predicts that the coexistence of closely related species is difficult due to their structural and behavioural similarities.

Flexible Resource Allocation-Efficient Water Use Strategies Facilitate Invasion of Invasive Vine L.

The invasive vine L. destroys the natural ecosystem of invaded areas. Understanding the differences in growth and development between and other plants is necessary to explore the invasion mechanisms of and implement appropriate prevention and control measures.

Development, validation and application of a UPLC-MS/MS method for simultaneous quantification of OPC-61815 and its metabolites tolvaptan, DM-4103 and DM-4107 in human plasma.

OPC-61815 is an intravenous formulation vasopressin antagonist designed to treat heart failure patients, especially who have difficulty in oral intake. Tolvaptan together with DM-4103 and DM-4107 are considered as the major metabolites of OPC-61815 biotransformed in the liver via cytochrome P450 (CYP) 3A. An efficient and robust ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for quantification of OPC-61815 and its three metabolites in human plasma was developed and fully validated.

Population pharmacokinetic modeling of ilaprazole in healthy subjects and patients with duodenal ulcer in China.

This study aimed to develop a population pharmacokinetic (PopPK) model of ilaprazole in healthy subjects and patients with duodenal ulcer in Chinese and investigate the effect of potential covariates on pharmacokinetic (PK) parameters. Pharmacokinetic data from 4 phase I clinical trials and 1 phase IIa clinical trial of ilaprazole were included in PopPK analysis. Phoenix NLME 8.

NEW PREDICTIVE BIOMARKERS FOR SCREENING COVID-19 PATIENTS WITH RHABDOMYOLYSIS IN COMBINATION WITH CYSTATIN C.

Purpose: Cystatin C (CysC) has been linked to the prognosis of corona virus disease 2019 (COVID-19). The study aims to investigate a predictor correlated with CysC screening for poor prognosis in COVID-19 patients combined with skeletal muscle (SKM) impairment and rhabdomyolysis (RM). Methods: A single-center retrospective cohort analysis was carried out.

Development and validation of a UPLC-MS/MS method for determination of SYHA1807 in a first-in-human study.

SYHA1807 is a novel lysine specific demethylase 1 inhibitor being developed for the treatment of small-cell lung cancer. This study aimed to establish a ultra-performance liquid chromatography-mass spectrometry (UPLC-MS)/MS method for measuring SYHA1807 in human plasma, supporting its application in a first-in-human study. SYHA1807 was separated on an ACQUITY UPLC BEH C18 Column (2.

Safety, tolerability, pharmacokinetics, and pharmacodynamics of single and multiple doses of aficamten in healthy Chinese participants: a randomized, double-blind, placebo-controlled, phase 1 study.

Aficamten is a selective, small-molecule allosteric inhibitor of cardiac sarcomere being developed as a chronic oral treatment for patients with symptomatic obstructive hypertrophic cardiomyopathy. This was the first-in-Chinese study aiming to investigate the safety, tolerability, pharmacokinetics, and pharmacodynamics of aficamten in healthy adults. This double-blind, randomized, placebo-controlled, phase 1 study was conducted in 28 healthy male and female Chinese participants after single ascending dose (SAD) and multi-dose (MD) administrations of aficamten.

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1-4 by Virtual Bioequivalence Model.

To evaluate the influence of solubility and permeability on the pharmacokinetic prediction performance of orally administered drugs using avirtual bioequivalence (VBE) model, a total of 23 orally administered drugs covering Biopharmaceutics Classification System (BCS) classes 1-4 were selected. A VBE model (i.e.

[Application of MIDD in Clinical Research of Antitumor Drugs].

The antitumor drug has become one of the focused areas in new drug research and development. Their clinical research generally consumes a long period of time, with high cost and high risk. Model-informed drug development (MIDD) integrates and quantitatively analyzes physiological, pharmacological, and disease progression information through modeling and simulation, which can reduce the cost of drug development and improve the efficiency of clinical research.

Semi-PBPK Modeling and Simulation to Evaluate the Local and Systemic Pharmacokinetics of OC-01(Varenicline) Nasal Spray.

This study aimed to build a nasal semi-physiologically based pharmacokinetic (PBPK) model to predict the intranasal pharmacokinetic (PK) of the OC-01(varenicline) nasal spray and accelerate the development of this drug. Based on the physiology of the human upper respiratory system, the semi-PBPK model was established and validated using systemic plasma PK data of varenicline previously observed in Americans and Chinese. Drug concentrations, both in respiratory tissue and plasma circulation system, were well simulated, and it was indicated that local concentration at the target site (nasal cavity) was significantly higher than that of plasma when OC-01 nasal spray was administered.

Clinical trials of orphan drugs in China over the decade 2012-2022: Opportunities and challenges.

Rare diseases refer to diseases with very low prevalence. Along with the support of national policies and improvement of research capability, a new landscape for orphan drug is emerging in China. To identity unmet clinical needs and provide insight on the development of orphan drugs, we reviewed the changes over time of orphan drug clinical trials in China from 2012 to 2022.

Review of the Chinese Landscape in Phase 1 Clinical Trials for Noncancer Innovative Drugs Over 2015 to 2020.

In recent years, the research and development (R&D) of innovative drugs in China has been dramatically accelerated. And the early clinical study is crucial for drug R&D. However, little is known involving the change of phase I trials for noncancer drugs.

Development and validation of a high performance liquid chromatography-MS/MS method for determination of SOMCL-15-290 in a first-in-human study.

SOMCL-15-290 is a novel inhibitor that targets FGF receptor, CSF1 receptor and VEGF receptor (kinase insert domain receptor). This study was aiming at developing a specific high performance liquid chromatography-MS/MS method for quantifying SOMCL-15-290 in human plasma and supporting the first-in-human study. Plasma samples were prepared using the protein precipitation method and separated on a C18 110A column with acetonitrile and 0.

Systemic Review of Animal Models Used in the Study of Crush Syndrome.

Crush syndrome (CS), also known as traumatic rhabdomyolysis, is the leading cause of death following extrication from structural collapse due to earthquakes. Due to the unfeasibility of human studies, animal models are used to study crush syndrome pathophysiology, including biochemistry and treatment regimes. The aim of this systematic literature review was to identify the differences and benefits of various animal models used in the study of CS and provide valuable information for design of future research.

A Generalized Method for Binary Optimization: Convergence Analysis and Applications.

Binary optimization problems (BOPs) arise naturally in many fields, such as information retrieval, computer vision, and machine learning. Most existing binary optimization methods either use continuous relaxation which can cause large quantization errors, or incorporate a highly specific algorithm that can only be used for particular loss functions. To overcome these difficulties, we propose a novel generalized optimization method, named Alternating Binary Matrix Optimization (ABMO), for solving BOPs.

β1-Blocker improves survival and ventricular remodelling in rats with lethal crush injury.

Background: Crush injury/crush syndrome (CI/CS) is the second most common cause of death during earthquakes. Most studies of CI/CS have mainly focused on kidney injury after decompression. Few studies have focused on myocardial injury caused by crush injury and its potential mechanisms.

STAR: A Structure and Texture Aware Retinex Model.

Retinex theory is developed mainly to decompose an image into the illumination and reflectance components by analyzing local image derivatives. In this theory, larger derivatives are attributed to the changes in reflectance, while smaller derivatives are emerged in the smooth illumination. In this paper, we utilize exponentiated local derivatives (with an exponent γ) of an observed image to generate its structure map and texture map.

Scaled Simplex Representation for Subspace Clustering.

The self-expressive property of data points, that is, each data point can be linearly represented by the other data points in the same subspace, has proven effective in leading subspace clustering (SC) methods. Most self-expressive methods usually construct a feasible affinity matrix from a coefficient matrix, obtained by solving an optimization problem. However, the negative entries in the coefficient matrix are forced to be positive when constructing the affinity matrix via exponentiation, absolute symmetrization, or squaring operations.

Multi-Target Regression via Robust Low-Rank Learning.

Multi-target regression has recently regained great popularity due to its capability of simultaneously learning multiple relevant regression tasks and its wide applications in data mining, computer vision and medical image analysis, while great challenges arise from jointly handling inter-target correlations and input-output relationships. In this paper, we propose Multi-layer Multi-target Regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in a general framework via robust low-rank learning. Specifically, the MMR can explicitly encode inter-target correlations in a structure matrix by matrix elastic nets (MEN); the MMR can work in conjunction with the kernel trick to effectively disentangle highly complex nonlinear input-output relationships; the MMR can be efficiently solved by a new alternating optimization algorithm with guaranteed convergence.

Multitarget Sparse Latent Regression.

Multitarget regression has recently generated intensive popularity due to its ability to simultaneously solve multiple regression tasks with improved performance, while great challenges stem from jointly exploring inter-target correlations and input-output relationships. In this paper, we propose multitarget sparse latent regression (MSLR) to simultaneously model intrinsic intertarget correlations and complex nonlinear input-output relationships in one single framework. By deploying a structure matrix, the MSLR accomplishes a latent variable model which is able to explicitly encode intertarget correlations via -norm-based sparse learning; the MSLR naturally admits a representer theorem for kernel extension, which enables it to flexibly handle highly complex nonlinear input-output relationships; the MSLR can be solved efficiently by an alternating optimization algorithm with guaranteed convergence, which ensures efficient multitarget regression.

Binary Set Embedding for Cross-Modal Retrieval.

Cross-modal retrieval is such a challenging topic that traditional global representations would fail to bridge the semantic gap between images and texts to a satisfactory level. Using local features from images and words from documents directly can be more robust for the scenario with large intraclass variations and small interclass discrepancies. In this paper, we propose a novel unsupervised binary coding algorithm called binary set embedding (BSE) to obtain meaningful hash codes for local features from the image domain and words from text domain.