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Soft tissue sarcoma (STS) is a relatively rare malignancy, accounting for about 1% of all adult cancers. It is known to have more than 70 subtypes. Its rarity, coupled with its various subtypes, makes early diagnosis challenging. The current standard treatment for STS is surgical removal. To identify the prognosis and pathophysiology of STS, we conducted untargeted metabolic profiling on pre-operative and post-operative plasma samples from 24 STS patients who underwent surgical tumor removal. Profiling was conducted using ultra-high-performance liquid chromatography–quadrupole time-of-flight/mass spectrometry. Thirty-nine putative metabolites, including phospholipids and acyl-carnitines were identified, indicating changes in lipid metabolism. Phospholipids exhibited an increase in the post-operative samples, while acyl-carnitines showed a decrease. Notably, the levels of pre-operative lysophosphatidylcholine (LPC) O-18:0 and LPC O-16:2 were significantly lower in patients who experienced recurrence after surgery compared to those who did not. Metabolic profiling may identify aggressive tumors that are susceptible to lipid synthase inhibitors. We believe that these findings could contribute to the elucidation of the pathophysiology of STS and the development of further metabolic studies in this rare malignancy.

Hemagglutination assay has been used for blood typing and detecting viruses, thus applicable for the diagnosis of infectious diseases, including COVID-19. Therefore, the development of microfluidic devices for fast detection of hemagglutination is on-demand for point-of-care diagnosis. Here, we present a way to detect hemagglutination in 3D microfluidic devices via optical absorbance (optical density, OD) characterization. 3D printing is a powerful way to build microfluidic structures for diagnostic devices. However, mixing liquid in microfluidic chips is difficult due to laminar flow, which hampers practical applications such as antigen-antibody mixing. To overcome the issue, we fabricated 3D microfluidic chips with embedded microchannel and microwell structures to induce hemagglutination between red blood cells (RBCs) and antibodies. We named it a 3D microtrap chip. We also established an automated measurement system which is an integral part of diagnostic devices. To do this, we developed a novel way to identify RBC agglutination and non-agglutination via the OD difference. By adapting a 3D-printed aperture to the microtrap chip, we obtained a pure absorbance signal from the microchannels by eliminating the background brightness of the microtrap chip. By investigating the underlying optical physics, we provide a 3D device platform for detecting hemagglutination.

The availability of several bioorthogonal reactions that can proceed selectively and efficiently under physiologically relevant conditions has garnered the interest of biochemists and organic chemists alike. Bioorthogonal cleavage reactions represent the latest innovation in click chemistry. Here, we employed the Staudinger ligation reaction to release radioactivity from immunoconjugates, improving target-to-background ratios. In this proof-of-concept study, model systems, including the anti-HER2 antibody trastuzumab, radioisotope I-131, and a newly synthesized bifunctional phosphine, were used. Staudinger ligation occurred when biocompatible N-glycosyl azides reacted with this radiolabeled immunoconjugate, leading to cleavage of the radioactive label from the molecule. We demonstrated this click cleavage in vitro and in vivo. Biodistribution studies in tumor models showed that radioactivity was eliminated from the bloodstream, thereby improving tumor-to-blood ratios. SPECT imaging revealed that tumors could be visualized with enhanced clarity. Our simple approach represents a novel application of bioorthogonal click chemistry in the development of antibody-based theranostics.

Maintaining a pleasant indoor environment with low energy consumption is important for healthy and comfortable living in buildings. In previous studies, we proposed the integrated comfort control (ICC) algorithm, which integrates several indoor environmental control devices, including an air conditioner, a ventilation system, and a humidifier. The ICC algorithm is operated by simple on/off control to maintain indoor temperature and relative humidity within a defined comfort range. This simple control method can cause inefficient building operation because it does not reflect the changes in indoor–outdoor environmental conditions and the status of the control devices. To overcome this limitation, we suggest the artificial intelligence integrated comfort control (AI2CC) algorithm using a double deep Q-network(DDQN), which uses a data-driven approach to find the optimal control of several environmental control devices to maintain thermal comfort with low energy consumption. The suggested AI2CC showed a good ability to learn how to operate devices optimally to improve indoor thermal comfort while reducing energy consumption. Compared to the previous approach (ICC), the AI2CC reduced energy consumption by 14.8%, increased the comfort ratio by 6.4%, and decreased the time to reach the comfort zone by 54.1 min.

Dyslipidemia is a major risk factor for development of atherosclerosis and cardiovascular disease (CVD). Effective lipid-lowering therapies has led to CVD risk reduction. This study evaluated the possible pharmacokinetic interactions between fenofibrate, a peroxisome proliferators-activated receptors α agonist, and pitavastatin, a 3-hydoxy-3-methylglutaryl-coenzyme A reductase inhibitor, in healthy Korean subjects. The study design was an open-label, randomized, multiple-dose, three-period, and six-sequence crossover study with a 10-day washout in 24 healthy volunteers. It had three treatments: 160 mg of micronized fenofibrate once daily for 5 days; 2 mg of pitavastatin once daily for 5 days; and 160 mg of micronized fenofibrate with 2 mg of pitavastatin for 5 days. Serial blood samples were collected at scheduled intervals for up to 48 h after the last dose in each period to determine the steady-state pharmacokinetics of both drugs. Plasma concentrations of fenofibric acid and pitavastatin were measured using a validated high-performance liquid chromatography with the tandem mass spectrometry method. A total of 24 subjects completed the study. Pitavastatin, when co-administered with micronized fenofibrate, had no effect on the Cmax,ss and AUCτ,ss of fenofibric acid. The Cmax,ss and AUCτ,ss of pitavastatin were increased by 36% and 12%, respectively, when co-administered with fenofibrate. Combined treatment with pitavastatin and micronized fenofibrate was generally well tolerated without serious adverse events. Our results demonstrated no clinically significant pharmacokinetic interactions between micronized fenofibrate and pitavastatin when 160 mg of micronized fenofibrate and 2 mg of pitavastatin are co-administered. The treatments were well tolerated during the study, with no serious adverse events.

We aimed to develop a sensitive method for detecting 13 ginsenosides using liquid chromatography−tandem mass spectrometry and to apply this method to pharmacokinetic studies in human following repeated oral administration of red ginseng extract. The chromatograms of Rb1, Rb2, Rc, Rd, Re, Rf, Rg1, Rg3, Rh2, F1, compound K (CK), protopanaxadiol (PPD), and protopanaxatriol (PPT) in human plasma were well separated. The calibration curve range for 13 ginsenosides was 0.5−200 ng/mL and the lower limit of quantitation was 0.5 ng/mL for all ginsenosides. The inter- and intra-day accuracy, precision, and stability were less than 15%. Among the 13 ginsenosides tested, nine ginsenosides (Rb1, Rb2, Rc, Rd, Rg3, CK, Rh2, PPD, and PPT) were detected in the human plasma samples. The plasma concentrations of Rb1, Rb2, Rc, Rd, and Rg3 were correlated with the content in red ginseng extract; however, CK, Rh2, PPD, and PPT were detected although they are not present in red ginseng extract, suggesting the formation of these ginsenosides through the human metabolism. In conclusion, our analytical method could be effectively used to evaluate pharmacokinetic properties of ginsenosides, which would be useful for establishing the pharmacokinetic−pharmacodymic relationship of ginsenosides as well as ginsenoside metabolism in humans.

A rapid and selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous determination of organic anion transporting polypeptide 1B1 (OATP1B1) and cytochrome P450 (P450) probe substrates and their phase I metabolites in human plasma was developed. The OATP1B1 (pitavastatin) and five P450 probe substrates, caffeine (CYP1A2), losartan (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and midazolam (CYP3A) and their metabolites were extracted from human plasma (50 µL) using methanol. Analytes were separated on a C18 column followed by selected reaction monitoring detection using MS/MS. All analytes were separated simultaneously within a 9 min run time. The developed method was fully validated over the expected clinical concentration range for all analytes tested. The intra- and inter-day precisions for all analytes were lower than 11.3% and 8.82%, respectively, and accuracy was 88.5–117.3% and 96.1–109.2%, respectively. The lower limit of quantitation was 0.05 ng/mL for dextromethorphan, dextrorphan, midazolam, and 1′-hydroxymidazolam; 0.5 ng/mL for losartan, EXP-3174, omeprazole, 5′-hydroxyomeprazole, and pitavastatin; and 5 ng/mL for caffeine and paraxanthine. The method was successfully used in a pharmacokinetic study in healthy subjects after oral doses of five P450 and OATP1B1 probes. This analytical method provides a simple, sensitive, and accurate tool for the determination of OATP1B1 and five major P450 activities in vivo drug interaction studies.

Metformin is a first-line medication for type 2 diabetes mellitus (T2DM). Based on its universal use, the consideration of inter-individual variability and development of predictive biomarkers are clinically significant. We aimed to identify endogenous markers of metformin responses using a pharmacometabolomic approach. Twenty-nine patients with early-phase T2DM were enrolled and orally administered metformin daily for 6 months. A total of 22 subjects were included in the final analysis. Patients were defined as responders or non-responders based on changes in their glycated haemoglobin A1c (HbA1c) from baseline, over 3 months. Urine metabolites at baseline, as well as at the 3 and 6 month follow-ups after the start of treatment were analysed using gas chromatography-mass spectrometry and evaluated with multivariate analyses. Metabolites distinguishable between the two response groups were obtained at baseline, as well as at the 3 and 6 month follow-ups, and significantly different metabolites were listed as markers of metformin response. Among the identified metabolites, citric acid, myoinositol, and hippuric acid levels showed particularly significant differences between the non-responder and responder groups. We thus identified different metabolite profiles in the two groups of T2DM patients after metformin administration, using pharmacometabolomics. These results might facilitate a better understanding and prediction of metformin response and its variability in individual patients.