Publications by authors named "Pattipong Wisanpitayakorn"

The collision cross-sections (CCS) measurement using ion mobility spectrometry (IMS) in combination with mass spectrometry (MS) offers a great opportunity to increase confidence in metabolite identification. However, owing to the lack of sensitivity and resolution, IMS has an analytical challenge in studying the CCS values of very low-molecular-weight metabolites (VLMs ≤ 250 Da). Here, we describe an analytical method using ultrahigh-performance liquid chromatography (UPLC) coupled to a traveling wave ion mobility-quadrupole-time-of-flight mass spectrometer optimized for the measurement of VLMs in human urine samples.

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The rotationally averaged collision cross-section (CCS) determined by ion mobility-mass spectrometry (IM-MS) facilitates the identification of various biomolecules. Although machine learning (ML) models have recently emerged as a highly accurate approach for predicting CCS values, they rely on large data sets from various instruments, calibrants, and setups, which can introduce additional errors. In this study, we identified and validated that ion's polarizability and mass-to-charge ratio (/) have the most significant predictive power for traveling-wave IM CCS values in relation to other physicochemical properties of ions.

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The combination of ion mobility mass spectrometry (IM-MS) and chromatography is a valuable tool for identifying compounds in natural products. In this study, using an ultra-performance liquid chromatography system coupled to a high-resolution quadrupole/traveling wave ion mobility spectrometry/time-of-flight MS (UPLC-TWIMS-QTOF), we have established and validated a comprehensive CCS and MS database for 112 plant specialized metabolites. The database included 15 compounds that were isolated and purified in-house and are not commercially available.

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Two dimensional GC (GC × GC)-time-of-flight mass spectrometry (TOFMS) has been used to improve accurate metabolite identification in the chemical industry, but this method has not been applied as readily in biomedical research. Here, we evaluated and validated the performance of high resolution GC × GC-TOFMS against that of GC-TOFMS for metabolomics analysis of two different plasma matrices, from healthy controls (CON) and diabetes mellitus (DM) patients with kidney failure (DM with KF). We found GC × GC-TOFMS outperformed traditional GC-TOFMS in terms of separation performance and metabolite coverage.

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Cytoskeletal filaments, such as microtubules and actin filaments, play important roles in the mechanical integrity of cells and the ability of cells to respond to their environment. Measuring the mechanical properties of cytoskeletal structures is crucial for gaining insight into intracellular mechanical stresses and their role in regulating cellular processes. One of the ways to characterize these mechanical properties is by measuring their persistence length, the average length over which filaments stay straight.

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In tip-growing plant cells, growth results from myosin XI and F-actin-mediated deposition of cell wall polysaccharides contained in secretory vesicles. Previous evidence showed that myosin XI anticipates F-actin accumulation at the cell's tip, suggesting a mechanism where vesicle clustering via myosin XI increases F-actin polymerization. To evaluate this model, we used a conditional loss-of-function strategy by generating moss (Physcomitrium patens) plants harboring a myosin XI temperature-sensitive allele.

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Construction and function of virtually all cilia require the universally conserved process of intraflagellar transport (IFT) [1, 2]. During the atypically fast IFT in the green alga C. reinhardtii, on average, 10 kinesin-2 motors "line up" in a tight assembly on the trains [3], provoking the question of how these motors coordinate their action to ensure smooth and fast transport along the flagellum without standing in each other's way.

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