Development of a Column-Switching HPLC-MS/MS Method and Clinical Application for Determination of Ethyl Glucuronide in Hair in Conjunction with AUDIT for Detecting High-Risk Alcohol Consumption

Versatile Separators Toward Advanced Lithium-Sulfur Batteries: Status, Recent Progress, Challenges and Perspective

Lithium-sulfur batteries (LSBs) have recently gained extensive attention due to their high energy density, low cost, and environmental friendliness. However, serious shuttle effect and uncontrolled growth of lithium dendrites restrict them from further commercial applications. As "the third electrode", functional separators are of equal significance as both anodes and cathodes in LSBs. The challenges mentioned above are effectively addressed with rational design and optimization in separators, thereby enhancing their reversible capacities and cycle stability. The review discusses the status/operation mechanism of functional separators, then primarily focuses on recent research progress in versatile separators with purposeful modifications for LSBs, and summarizes the methods and characteristics of separator modification, including heterojunction engineering, single atoms, quantum dots, and defect engineering. From the perspective of the anodes, distinct methods to inhibit the growth of lithium dendrites by modifying the separator are discussed. Modifying the separators with flame retardant materials or choosing a solid electrolyte is expected to improve the safety of LSBs. Besides, in-situ techniques and theoretical simulation calculations are proposed to advance LSBs. Finally, future challenges and prospects of separator modifications for next-generation LSBs are highlighted. We believe that the review will be enormously essential to the practical development of advanced LSBs.

Identification of Potential Biomarkers for Diagnosis of Patients with Methamphetamine Use Disorder

The current method for diagnosing methamphetamine use disorder (MUD) relies on self-reports and interviews with psychiatrists, which lack scientific rigor. This highlights the need for novel biomarkers to accurately diagnose MUD. In this study, we identified transcriptome biomarkers using hair follicles and proposed a diagnostic model for monitoring the MUD treatment process. We performed RNA sequencing analysis on hair follicle cells from healthy controls and former and current MUD patients who had been detained in the past for illegal use of methamphetamine (MA). We selected candidate genes for monitoring MUD patients by performing multivariate analysis methods, such as PCA and PLS-DA, and PPI network analysis. We developed a two-stage diagnostic model using multivariate ROC analysis based on the PLS-DA method. We constructed a two-step prediction model for MUD diagnosis using multivariate ROC analysis, including 10 biomarkers. The first step model, which distinguishes non-recovered patients from others, showed very high accuracy (prediction accuracy, 98.7%). The second step model, which distinguishes almost-recovered patients from healthy controls, showed high accuracy (prediction accuracy, 81.3%). This study is the first report to use hair follicles of MUD patients and to develop a MUD prediction model based on transcriptomic biomarkers, which offers a potential solution to improve the accuracy of MUD diagnosis and may lead to the development of better pharmacological treatments for the disorder in the future.

Fusion of Oligopeptide to the C Terminus of α-Glucuronidase from Thermotoga maritima Improves the Catalytic Efficiency for Hemicellulose Biotransformation

Fusion protein combined the oligopeptide (HQAFFHA) with the C terminus of α-glucuronidase from Thermotoga maritima was produced in E. coli and purified for characterization and applications of glucuronic and glucaric acid production. The fusion protein with oligopeptide exhibited a 2.97-fold higher specific activity than individual protein. Their catalytic efficiency k_cat/K_m and k_cat increased from 469.3 ± 2.6 s^-1 (g mL^-1)^-1 and 62.4 ± 0.9 s^-1 to 2209.5 ± 26.3 s^-1 (g mL^-1)^-1 and 293.9 ± 4.9 s^-1, respectively. Fusion protein had similar temperature and pH profiles to those without oligopeptide, but the thermal stability decreases and the pH stability shifts to alkaline. Using beech xylan hydrolysate as a substrate, the glucuronic acid yield of fusion enzyme increased by 9.94% compared with its parent at 65 °C pH 8.5 for 10 h, and can hydrolyze corn cob xylan with xylanase to obtain glucuronic acid, and can be combined with uronate dehydrogenase to obtain high-added value glucaric acid. Homologous modeling analysis revealed the factors contributing to the high catalytic efficiency of fusion enzyme. These results show that the peptide fusion strategy described here may be useful for improving the catalytic efficiency and stability of other industrial enzymes, and has great potential for producing high value-added products from agricultural waste.

Characteristics of Korean patients with methamphetamine use disorder based on the quantitative analysis of methamphetamine and amphetamine in hair

Methamphetamine (MA) is a highly addictive central nervous system stimulant. MA use disorder is characterized by a chronic, relapsing brain disease that is enhanced by a dynamic process of repeated use and withdrawal. The analysis of MA and its metabolite, amphetamine (AM), in hair is routinely performed in forensic laboratories for illegal MA use determination. However, few studies regarding the clinical application of hair analysis have been conducted to monitor the treatment of MA use disorder. Herein, the characteristics of Korean patients with MA use disorder were investigated based on drug abuse screening instruments and quantitative analysis of MA and AM in hair. A HPLC-MS/MS method for the quantification of MA and AM in hair was validated and clinically applied to healthy subjects (HS, n = 30, male) as well as current (CP, n = 33, male) and former (FP, n = 22, male) MA use disorder patients. The validation results of the hair analysis method showed high selectivity, accuracy, and precision with acceptable linearity within the calibration range (0.05-5.0 ng/mg). The limit of detection (LOD) and limit of quantification for both MA and AM were 0.05 ng/mg. The concentrations of MA and AM ranged from ≤ LOD to 166 ng/mg and from not detected (ND) to 9.15 ng/mg in the CP group and from ND to 6.14 ng/mg and from ND to 0.32 ng/mg in the FP group, respectively. No correlation was observed between the hair MA concentrations and the NIDA-modified ASSIST, DUDID extended, or DAST scores in both groups. The hair MA concentrations showed advantages for differentiating the CP and FP groups compared with the scores provided by the above-mentioned drug abuse screening instruments.

Hair Metabolomics in Animal Studies and Clinical Settings

Metabolomics is a powerful tool used to understand comprehensive changes in the metabolic response and to study the phenotype of an organism by instrumental analysis. It most commonly involves mass spectrometry followed by data mining and metabolite assignment. For the last few decades, hair has been used as a valuable analytical sample to investigate retrospective xenobiotic exposure as it provides a wider window of detection than other biological samples such as saliva, plasma, and urine. Hair contains functional metabolomes such as amino acids and lipids. Moreover, segmental analysis of hair based on its growth rate can provide information on metabolic changes over time. Therefore, it has great potential as a metabolomics sample to monitor chronic diseases, including drug addiction or abnormal conditions. In the current review, the latest applications of hair metabolomics in animal studies and clinical settings are highlighted. For this purpose, we review and discuss the characteristics of hair as a metabolomics sample, the analytical techniques employed in hair metabolomics and the consequence of hair metabolome alterations in recent studies. Through this, the value of hair as an alternative biological sample in metabolomics is highlighted.