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In recent years, scientific researchers have increasingly become interested in noninvasive sampling methods for therapeutic drug monitoring and disease diagnosis. As a result, dried saliva spot (DSS), which is a sampling technique for collecting dried saliva samples, has been widely used as an alternative matrix to serum for the detection of target molecules. Coupling the DSS method with a highly sensitive detection instrument improves the efficiency of the preparation and analysis of biological samples. Furthermore, dried blood spots, dried plasma spots, and dried matrix spots, which are similar to those of the DSS method, are discussed. Compared with alternative biological fluids used in dried spot methods, including serum, tears, urine, and plasma, saliva has the advantage of convenience in terms of sample collection from children or persons with disabilities. This review aims to provide integral strategies and guidelines for dried spot methods to analyze biological samples by illustrating several dried spot methods. Herein, we summarize recent advancements in DSS methods from June 2014 to March 2021 and discuss the advantages and disadvantages of the key aspects of this method, including sample preparation and method validation. Finally, we outline the challenges and prospects of such methods in practical applications.

The aim of this study was to develop a diagnostic strategy for esophageal squamous cell carcinoma (ESCC) that combines plasma metabolomics with machine learning algorithms. Plasma-based untargeted metabolomics analysis was performed with samples derived from 88 ESCC patients and 52 healthy controls. The dataset was split into a training set and a test set. After identification of differential metabolites in training set, single-metabolite-based receiver operating characteristic (ROC) curves and multiple-metabolite-based machine learning models were used to distinguish between ESCC patients and healthy controls. Kaplan-Meier survival analysis and Cox proportional hazards regression analysis were performed to investigate the prognostic significance of the plasma metabolites. Finally, twelve differential plasma metabolites (six up-regulated and six down-regulated) were annotated. The predictive performance of the six most prevalent diagnostic metabolites through the diagnostic models in the test set were as follows: arachidonic acid (accuracy: 0.887), sebacic acid (accuracy: 0.867), indoxyl sulfate (accuracy: 0.850), phosphatidylcholine (PC) (14:0/0:0) (accuracy: 0.825), deoxycholic acid (accuracy: 0.773), and trimethylamine N-oxide (accuracy: 0.653). The prediction accuracies of the machine learning models in the test set were partial least-square (accuracy: 0.947), random forest (accuracy: 0.947), gradient boosting machine (accuracy: 0.960), and support vector machine (accuracy: 0.980). Additionally, survival analysis demonstrated that acetoacetic acid was an unfavorable prognostic factor (hazard ratio (HR): 1.752), while PC (14:0/0:0) (HR: 0.577) was a favorable prognostic factor for ESCC. This study devised an innovative strategy for ESCC diagnosis by combining plasma metabolomics with machine learning algorithms and revealed its potential to become a novel screening test for ESCC.

In Korea and China, ilaprazole is a widely used proton pump inhibitor in the treatment of gastric ulcers. In this study, a specific and sensitive LC-MS/MS method has been developed and validated for the quantification of ilaprazole enantiomers in the rat plasma, using R-lansoprazole as the internal standard. The enantioseparation was achieved on a CHIRALPAK AS-RH column (4.6 mm × 150 mm, i.d. 5 μm), with a mobile phase composed of 10 mM ammonium acetate aqueous solution and acetonitrile (60:40, V/V), at a flow-rate of 0.5 mL/min. The method was validated over the concentration range of 0.5–300 ng/mL for both, R- and S -ilaprazole. The lower limit of quantification was 0.5 ng/mL for both enantiomers. The relative standard deviation (RSD) of intra- and inter-day precision of R-ilaprazole and S-ilaprazole was less than 10.9%, and the relative error accuracy (RE) ranged from −0.5%–2.0%. Finally, the method was successfully evaluated in rats in a stereoselective pharmacokinetic study of the ilaprazole racemate.

Therapeutic monoclonal antibodies have become one of the central components of the healthcare system and continuous efforts are made to bring innovative antibody therapeutics to patients in need. It is equally critical to acquire sufficient knowledge of their molecular structure and biological functions to ensure the efficacy and safety by incorporating new detection approaches since new challenges like individual differences and resistance are presented. Conventional techniques for determining antibody disposition including plasma drug concentration measurements using LC-MS or ELISA, and tissue distribution using immunohistochemistry and immunofluorescence are now complemented with molecular imaging modalities like positron emission tomography and near-infrared fluorescence imaging to obtain more dynamic information, while methods for characterization of antibody’s interaction with the target antigen as well as visualization of its cellular and intercellular behavior are still under development. Recent progress in detecting therapeutic antibodies, in particular, the development of methods suitable for illustrating the molecular dynamics, is described here.

The recent pneumonia outbreak caused by a novel coronavirus (SARS-CoV-2) is posing a great threat to global public health. Therefore, rapid and accurate identification of pathogenic viruses plays a vital role in selecting appropriate treatments, saving people’s lives and preventing epidemics. It is important to establish a quick standard diagnostic test for the detection of the infectious disease (COVID-19) to prevent subsequent secondary spread. Polymerase chain reaction (PCR) is regarded as a gold standard test for the molecular diagnosis of viral and bacterial infections with high sensitivity and specificity. Isothermal nucleic acid amplification is considered to be a highly promising candidate method due to its fundamental advantage in quick procedure time at constant temperature without thermocycler operation. A variety of improved or new approaches also have been developed. This review summarizes the currently available detection methods for coronavirus nucleic acid. It is anticipated that this will assist researchers and clinicians in developing better techniques for timely and effective detection of coronavirus infection. Keywords: Coronavirus, Nucleic acid detection, PCR-Based methods, Isothermal nucleic acid amplification-based methods, Microarray-based methods

MicroRNAs (miRNAs) are a family of endogenous, small (approximately 22 nucleotides in length), noncoding, functional RNAs. With the development of molecular biology, the research of miRNA biological function has attracted significant interest, as abnormal miRNA expression is identified to contribute to serious human diseases such as cancers. Traditional methods for miRNA detection do not meet current demands. In particular, nanomaterial-based methods, nucleic acid amplification-based methods such as rolling circle amplification (RCA), loop-mediated isothermal amplification (LAMP), strand-displacement amplification (SDA) and some enzyme-free amplifications have been employed widely for the highly sensitive detection of miRNA. MiRNA functional research and clinical diagnostics have been accelerated by these new techniques. Herein, we summarize and discuss the recent progress in the development of miRNA detection methods and new applications. This review will provide guidelines for the development of follow-up miRNA detection methods with high sensitivity and specificity, and applicability to disease diagnosis and therapy. Keywords: MicroRNAs, Detection method, Amplification strategies, Nanomaterial-based methods, Nucleic acid amplification-based methods

Stereoselectivity in drug metabolism can not only influence the pharmacological activities, tolerability, safety, and bioavailability of drugs directly, but also cause different kinds of drug–drug interactions. Thus, assessing stereoselectivity in drug metabolism is of great significance for pharmaceutical research and development (R&D) and rational use in clinic. Although there are various methods available for assessing stereoselectivity in drug metabolism, many of them have shortcomings. The indirect method of chromatographic methods can only be applicable to specific samples with functional groups to be derivatized or form complex with a chiral selector, while the direct method achieved by chiral stationary phases (CSPs) is expensive. As a detector of chromatographic methods, mass spectrometry (MS) is highly sensitive and specific, whereas the matrix interference is still a challenge to overcome. In addition, the use of nuclear magnetic resonance (NMR) and immunoassay in chiral analysis are worth noting. This review presents several typical examples of drug stereoselective metabolism and provides a literature-based evaluation on current chiral analytical techniques to show the significance and challenges of stereoselectivity assessing methods in drug metabolism.

The stereoselective hydrolysis of esmolol in whole blood and in its separated components from rat, rabbit and human was investigated. Blood esterase activities were variable in different species in the order of rat>rabbit>human. Rat plasma showed the high esterase activity and had no stereoselectivity to enantiomers. Rabbit red blood cell (RBC) membrane, RBC cytosol and plasma all hydrolyzed esmolol but with different esterase activity, whereas the hydrolysis in RBC membrane and cytosol showed significant stereoselectivity towards R-(+)-esmolol. Esterase in RBC cytosol from human blood mainly contributed to the esmolol hydrolysis, which was demonstrated with no stereoselctivity. Esterase in human plasma showed a low activity, but a remarkable stereoselectivity with R-(+)-esmolol. In addition, the protein concentration affected the hydrolysis behavior of esmolol in RBC suspension. Protein binding of esmolol enantiomers in human plasma, human serum albumin (HSA) and α1-acid glycoprotein (AGP) revealed that there was a significant difference in bound fractions between two enantiomers, especially for AGP. Our results indicated that the stereoselective protein binding might play a role in the different hydrolysis rates of esmolol enantiomers in human plasma. Keywords: Esmolol enantiomers, Species-dependent, Stereoselective hydrolysis, Protein binding

The protein binding of non-steroidal anti-inflammatory drugs flurbiprofen, ketoprofen and etodolac with human serum albumin (HSA) was investigated using indirect chiral high performance liquid chromatography (HPLC) and ultrafiltration techniques. S-(â)-1-(1-naphthyl)-ethylamine (S-NEA) was utilized as chiral derivatization reagent and pre-column derivatization RP-HPLC method was established for the separation and assay of the three pairs of enantiomer. The method had good linear relationship over the investigated concentration range without interference. The average extraction efficiency was higher than 85% in different systems, and the intra-day and inter-day precisions were less than 15%. In serum albumin, the protein binding of etodolac enantiomers showed significant stereoselectivity that the affinity of S-enantiomer was stronger than R-enantiomer, and the stereoselectivity ratio reached 6.06; Flurbiprofen had only weak stereoselectivity in HSA, and ketoprofen had no stereoselectivity at all. Scatchard curves showed that all the three chiral drugs had two types of binding sites in HSA. Keywords: Protein binding, Non-steroidal anti-inflammatory drugs, Enantiomer, Stereoselectivity, Human serum albumin