Browsing by Author "Sirivatanauksorn Y."

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    Accurate Prediction of Ion Mobility Collision Cross-Section Using Ion’s Polarizability and Molecular Mass with Limited Data
    (2023-01-01) Wisanpitayakorn P.; Sartyoungkul S.; Kurilung A.; Sirivatanauksorn Y.; Visessanguan W.; Sathirapongsasuti N.; Khoomrung S.; Wisanpitayakorn P.; Mahidol University
    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 (m/z) have the most significant predictive power for traveling-wave IM CCS values in relation to other physicochemical properties of ions. Constructed solely based on these two physicochemical properties, our CCS prediction approach demonstrated high accuracy (mean relative error of <3.0%) even when trained with limited data (15 CCS values). Given its ability to excel with limited data, our approach harbors immense potential for constructing a precisely predicted CCS database tailored to each distinct experimental setup. A Python script for CCS prediction using our approach is freely available at https://github.com/MSBSiriraj/SVR_CCSPrediction under the GNU General Public License (GPL) version 3.
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    CRISP: a deep learning architecture for GC × GC-TOFMS contour ROI identification, simulation and analysis in imaging metabolomics
    (2022-03-10) Mathema V.B.; Duangkumpha K.; Wanichthanarak K.; Jariyasopit N.; Dhakal E.; Sathirapongsasuti N.; Kitiyakara C.; Sirivatanauksorn Y.; Khoomrung S.; Mathema V.B.; Mahidol University
    Two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) provides a large amount of molecular information from biological samples. However, the lack of a comprehensive compound library or customizable bioinformatics tool is currently a challenge in GC × GC-TOFMS data analysis. We present an open-source deep learning (DL) software called contour regions of interest (ROI) identification, simulation and untargeted metabolomics profiler (CRISP). CRISP integrates multiple customizable deep neural network architectures for assisting the semi-automated identification of ROIs, contour synthesis, resolution enhancement and classification of GC × GC-TOFMS-based contour images. The approach includes the novel aggregate feature representative contour (AFRC) construction and stacked ROIs. This generates an unbiased contour image dataset that enhances the contrasting characteristics between different test groups and can be suitable for small sample sizes. The utility of the generative models and the accuracy and efficacy of the platform were demonstrated using a dataset of GC × GC-TOFMS contour images from patients with late-stage diabetic nephropathy and healthy control groups. CRISP successfully constructed AFRC images and identified over five ROIs to create a deepstacked dataset. The high fidelity, 512 × 512-pixels generative model was trained as a generator with a Fréchet inception distance of <47.00. The trained classifier achieved an AUROC of >0.96 and a classification accuracy of >95.00% for datasets with and without column bleed. Overall, CRISP demonstrates good potential as a DL-based approach for the rapid analysis of 4-D GC × GC-TOFMS untargeted metabolite profiles by directly implementing contour images. CRISP is available at https://github.com/vivekmathema/GCxGC-CRISP.
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    Development of Small Interfering RNA Loaded Cationic Lipid Nanoparticles for the Treatment of Liver Cancer with Elevated α-Fetoprotein Expression
    (2024-01-01) Duangchan K.; Limjunyawong N.; Rodponthukwaji K.; Ittiudomrak T.; Thaweesuvannasak M.; Kunwong N.; Metheetrairut C.; Sirivatanauksorn V.; Sirivatanauksorn Y.; Kositamongkol P.; Mahawithitwong P.; Tovikkai C.; Nguyen K.T.; Srisawat C.; Punnakitikashem P.; Duangchan K.; Mahidol University
    α-Fetoprotein (AFP) is an oncogenic glycoprotein that is overexpressed in most patients with liver cancer. Moreover, it significantly affects tumorigenesis and progression, particularly by inhibiting programmed cell death or apoptosis. The treatment of liver cancer with chemotherapy is currently still in use, but its toxicity is a major concern. Alternatively, targeted therapy, especially small interfering RNA (siRNA)-based therapeutics that utilize siRNA to suppress target gene expression, is a promising cancer treatment approach that can help reduce such drawbacks. However, transporting siRNA into cells is a challenge due to its ease of degradation and limited cell membrane permeability. To overcome this limitation, we fabricated cationic lipid nanoparticles (cLNPs) to deliver AFP-targeted siRNA (siAFP) to AFP-producing liver cancer cells. Our results illustrated that these nanoparticles had a high capacity for siRNA encapsulation (>95%) and entered the cancer cells efficiently. Cell internalization of siAFP-loaded cLNPs resulted in the silencing of AFP mRNA expression and led to increased apoptotic cell death by inducing caspase-3/7 activity. This suggested that our cLNPs could be used as a powerful siRNA delivery carrier and siAFP-loaded cLNPs might be a useful strategy for treating liver cancer in the future.
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    Discovery of procyanidin condensed tannins of (−)-epicatechin from Kratom, Mitragyna speciosa, as virucidal agents against SARS-CoV-21
    (2024-07-01) Sureram S.; Chutiwitoonchai N.; Pooprasert T.; Sangsopha W.; Limjiasahapong S.; Jariyasopit N.; Sirivatanauksorn Y.; Khoomrung S.; Mahidol C.; Ruchirawat S.; Kittakoop P.; Sureram S.; Mahidol University
    Kratom, Mitragyna speciosa, is one of the most popular herbs in the West and Southeast Asia. A number of previous works have focused on bioactive alkaloids in this plant; however, non-alkaloids have never been investigated for their biological activities. Antiviral and virucidal assays of a methanol leaf extract of Kratom, M. speciosa, revealed that a crude extract displayed virucidal activity against the SARS-CoV-2. Activity-guided isolation of a methanol leaf extract of Kratom led to the identification of B-type procyanidin condensed tannins of (−)-epicatechin as virucidal compounds against SARS-CoV-2. The fraction containing condensed tannins exhibited virucidal activity with an EC50 value of 8.38 μg/mL and a selectivity index (SI) value >23.86. LC-MS/MS analysis and MALDI-TOF MS identified the structure of the virucidal compounds in Kratom as B-type procyanidin condensed tannins, while gel permeation chromatograph (GPC) revealed weight average molecular weight of 238,946 Da for high molecular-weight condensed tannins. In addition to alkaloids, (−)-epicatechin was found as a major component in the leaves of M. speciosa, but it did not have virucidal activity. Macromolecules of (−)-epicatechin, i.e., procyanidin condensed tannins, showed potent virucidal activity against SARS-CoV-2, suggesting that the high molecular weights of these polyphenols are important for virucidal activity.
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    GC × GC-TOFMS metabolomics analysis identifies elevated levels of plasma sugars and sugar alcohols in diabetic mellitus patients with kidney failure
    (2022-10-01) Duangkumpha K.; Jariyasopit N.; Wanichthanarak K.; Dhakal E.; Wisanpitayakorn P.; Thotsiri S.; Sirivatanauksorn Y.; Kitiyakara C.; Sathirapongsasuti N.; Khoomrung S.; Mahidol University
    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. Several metabolites from both the CON and DM with KF matrices, such as carbohydrates and carbohydrate-conjugate metabolites, were exclusively detected using GC × GC-TOFMS. Additionally, we applied this method to characterize significant metabolites in the DM with KF group, with focused analysis of four metabolite groups: sugars, sugar alcohols, amino acids, and free fatty acids. Our plasma metabolomics results revealed 35 significant metabolites (12 unique and 23 concentration-dependent metabolites) in the DM with KF group, as compared with those in the CON and DM groups (N = 20 for each group). Interestingly, we determined 17 of the 35 (14/17 verified with reference standards) significant metabolites identified from both the analyses were metabolites from the sugar and sugar alcohol groups, with significantly higher concentrations in the DM with KF group than in the CON and DM groups. Enrichment analysis of these 14 metabolites also revealed that alterations in galactose metabolism and the polyol pathway are related to DM with KF. Overall, our application of GC × GC-TOFMS identified key metabolites in complex plasma matrices.
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    Higher Plasma Kynurenine to Tryptophan Correlates with an Increased Incidence of Mild Cognitive Impairment in Treated Metabolic Syndrome Patients
    (2025-12-30) Jariyasopit N.; Phochmak T.; Manocheewa S.; Wanichthanarak K.; Limjiasahapong S.; Kleebkomut N.; Sirivatanauksorn Y.; Sirivatanauksorn V.; Phrommintikul A.; Chattipakorn N.; Chattipakorn S.; Khoomrung S.; Jariyasopit N.; Mahidol University
    An increase in cognitive impairment was observed in metabolic syndrome (MetS) patients. Although alterations in metabolomic profiles have been identified as potential plasma/serum biomarkers of mild cognitive impairment (MCI) and MetS, findings remain inconsistent─probably due to the heterogeneity among MetS patients and the lack of subsequent validation using targeted analysis after the initial untargeted analysis. In this study, we validated mass spectrometry-based quantitation methods and quantified amino acids, fatty acids, and tryptophan metabolites in the kynurenine pathway in the plasma of 95 treated MetS patients with and without MCI assessed by the Montreal Cognitive Assessment. We found that MCI was positively associated with the kynurenine-to-tryptophan ratio (KTR) after the adjustment for age, gender, and BMI, as well as negatively associated with C20:3 [all-Z-8,11,14] and lysine. A one-unit increase in KTR resulted in an increased probability of developing MCI by 371%. In contrast, one-unit increases in C20:3 and lysine were associated with decreased odds of developing MCI by 81 and 78%, respectively. Our finding underscores prominent neuroinflammation, beyond normal aging, in MetS patients, even under ongoing clinical treatment. It also points to the potential of KTR as a risk marker for MCI, offering a valuable complement to the existing cognitive assessments that may be influenced by the educational background. In addition, the validated metabolite data serve as an invaluable resource for future research. They can facilitate comparisons across different studies, contribute to large-scale analyses, and be used in machine learning models for discovering and validating new biomarkers.
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    Hospital length of stay: A cross-specialty analysis and Beta-geometric model
    (2023-01-01) Dehouche N.; Viravan S.; Santawat U.; Torsuwan N.; Taijan S.; Intharakosum A.; Sirivatanauksorn Y.; Mahidol University
    BACKGROUND: The typical hospital Length of Stay (LOS) distribution is known to be right-skewed, to vary considerably across Diagnosis Related Groups (DRGs), and to contain markedly high values, in significant proportions. These very long stays are often considered outliers, and thin-tailed statistical distributions are assumed. However, resource consumption and planning occur at the level of medical specialty departments covering multiple DRGs, and when considered at this decision-making scale, extreme LOS values represent a significant component of the distribution of LOS (the right tail) that determines many of its statistical properties. OBJECTIVE: To build actionable statistical models of LOS for resource planning at the level of healthcare units. METHODS: Through a study of 46, 364 electronic health records over four medical specialty departments (Pediatrics, Obstetrics/Gynecology, Surgery, and Rehabilitation Medicine) in the largest hospital in Thailand (Siriraj Hospital in Bangkok), we show that the distribution of LOS exhibits a tail behavior that is consistent with a subexponential distribution. We analyze some empirical properties of such a distribution that are of relevance to cost and resource planning, notably the concentration of resource consumption among a minority of admissions/patients, an increasing residual LOS, where the longer a patient has been admitted, the longer they would be expected to remain admitted, and a slow convergence of the Law of Large Numbers, making empirical estimates of moments (e.g. mean, variance) unreliable. RESULTS: We propose a novel Beta-Geometric model that shows a good fit with observed data and reproduces these empirical properties of LOS. Finally, we use our findings to make practical recommendations regarding the pricing and management of LOS.
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    Incidence and Risk Factors Associated With Chronic Kidney Disease After Liver Transplantation: A Review of a 20-Year Experience at a Single Center
    (2024-01-01) Tovikkai C.; Sawetwanichakul J.; Kositamongkol P.; Mahawithitwong P.; Dumronggittigule W.; Sangserestid P.; Assawasirisin C.; Limsrichamrern S.; Sirivatanauksorn Y.; Tovikkai C.; Mahidol University
    Background: Chronic kidney disease (CKD) is one of the major complications after liver transplantation (LT), with a significant impact on patient outcomes. This study aims to investigate the incidence and risk factors of CKD in LT recipients at Siriraj Hospital over the past 20 years. Methods: There were 366 adult patients undergoing LT at Siriraj Hospital between January 2002 and December 2021. After excluding patients with pretransplant CKD stages 4 to 5, simultaneous liver–kidney transplantation, and patients who died after LT within 90 days, we retrospectively reviewed a total of 288 patients. Univariable and multivariable binary logistic regression analyses were used to identify the risk factors of post-transplant CKD. Results: Of the 288 patients, 171 (59.4%) developed CKD after LT. The median time to develop CKD was 5.8 months (IQR, 3.8-15.3). Univariable and multivariable analyses revealed that age ≥55 years (odds ratio [OR] = 2.44; 95% CI, 1.34-4.42; P = .003), pretransplant kidney dysfunction defined as estimated glomerular filtration rate <60 mL/min/1.73 m2 (OR = 2.23; 95% CI, 1.16-4.27; P = .016), and postoperative acute kidney injury (OR = 3.06; 95% CI, 1.73-5.42; P < .001) were significantly associated with post-transplant CKD. Patients with preexisting kidney dysfunction who received delayed calcineurin inhibitor introduction without antibody induction protocol had a significantly lower incidence of post-transplant CKD (OR = 0.28; 95% CI, 0.11-0.70; P = .007). Conclusions: Advanced age, pre-transplant kidney dysfunction, and postoperative acute kidney injury are risk factors for CKD after LT. Importantly, delayed calcineurin inhibitor introduction can protect patients with pretransplant kidney dysfunction from developing post-transplant CKD. These results may have important clinical implications in reducing the incidence of CKD after LT.
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    LC-MS/MS identifies elevated imidazole propionate and gut-derived metabolite alterations in peritoneal dialysis patients
    (2025-01-01) Manokasemsan W.; Jariyasopit N.; Wanichthanarak K.; Poungsombat P.; Kurilung A.; Limjiasahapong S.; Thapa K.; Sirivatanauksorn Y.; Raksasuk S.; Srithongkul T.; Kitiyakara C.; Khoomrung S.; Manokasemsan W.; Mahidol University
    We developed a robust LC–MS/MS method for the simultaneous quantification of 16 uremic toxins (UTs) and 14 bile acids (BAs) in plasma and fecal samples within a single method. The method demonstrated high sensitivity, broad metabolite coverage, and excellent accuracy, precision, and throughput. Using this platform, targeted metabolites were quantified in peritoneal dialysis (PD) patients (n = 31) and healthy controls (HC; n = 60). Of the 30 targeted metabolites included in the validation method, 20 were detected in fecal samples and 12 in plasma in this study. Fecal samples exhibited greater BA diversity, whereas UTs were evenly distributed across both matrices. Fecal profiles showed minimal differences between PD and HC, suggesting limited gut-level alteration. In contrast, plasma analysis revealed nine metabolites significantly elevated in PD, including indoxyl sulfate, phenyl sulfate, hippuric acid, and imidazole propionate (ImP), lithocholic acid, cinnamoylglycine, m-hydroxyhippuric acid, phenylacetylglutamine, and phenylacetylglycine. Notably, plasma ImP—an underexplored metabolite—was elevated independently of diabetes or cardiovascular disease, implicating impaired renal clearance as its primary driver. These results highlight the systemic impact of gut-derived metabolites in kidney failure and position targeted UT–BA profiling as a powerful complementary tool for clinical metabolomics in chronic kidney disease and PD.
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    LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
    (2025-01-01) Kurilung A.; Limjiasahapong S.; Wanichthanarak K.; Manokasemsan W.; Kaewnarin K.; Duangkumpha K.; Manocheewa S.; Tansawat R.; Chaiteerakij R.; Nookaew I.; Sirivatanauksorn Y.; Khoomrung S.; Kurilung A.; Mahidol University
    This study presents the development and validation of a liquid chromatography–quadrupole-time-of-flight mass spectrometry method with data-independent acquisition (LC-QTOF-MSE) for targeted quantification, post-targeted screening, and untargeted metabolite profiling. Using MS1-based precursor ion quantification, the method demonstrated excellent analytical performance with linearity (R² > 0.99), accuracy (84 %–131 %), and precision (1 %–17 % relative standard deviation (RSD)). Although LC-QTOF‑MSE sensitivity is at least nine-fold lower than LC-triple quadrupole MS with multiple reaction monitoring, it remains adequate for quantifying urinary metabolites, particularly those that fragment poorly or yield low‑intensity product ions. For post‑targeted screening and untargeted profiling, an in‑house reference library (the Siriraj Metabolomics Data Warehouse, SiMD), comprising 174 curated metabolite standards, was integrated into the workflow to enhance metabolite identification confidence. The official website for SiMD can be accessed at https://si-simd.com/. To demonstrate the method's utility, 11 amino and organic acids were quantified in urine samples from 100 healthy individuals. Four compounds—L-methionine, L-histidine, L-tryptophan, and trans-ferulic acid—were significantly higher levels in females (P < 0.05), likely reflecting sex-specific physiological or dietary intake differences. Post‑targeted screening identified 29 additional metabolites and assigned them to level 1 (m/z, RT, isotope pattern, and MS/MS spectra matched to reference standards) based on the Metabolomics Standards Initiative guidelines. Untargeted retrospective profiling revealed level 1 seven metabolites, including ribitol, creatine, glucuronic acid, trans-ferulic acid, succinic acid, dimethylglycine, and 3-hydroxyphenylacetic acid related to sex variation (VIP > 1.5). In summary, the LC-QTOF-MSE method coupled with SiMD provides a robust and comprehensive workflow for metabolomics analysis. It enables reliable target quantification and enhances confidence in metabolite identification while also reducing sample and instrumental demands. These features make it particularly well-suited for clinical metabolomics studies.
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    Measurement of very low-molecular weight metabolites by traveling wave ion mobility and its use in human urine samples
    (2024-05-01) Kurilung A.; Limjiasahapong S.; Kaewnarin K.; Wisanpitayakorn P.; Jariyasopit N.; Wanichthanarak K.; Sartyoungkul S.; Wong S.C.C.; Sathirapongsasuti N.; Kitiyakara C.; Sirivatanauksorn Y.; Khoomrung S.; Kurilung A.; Mahidol University
    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. The experimental CCS values, along with mass spectral properties, were reported for the 174 metabolites. The experimental data included the mass-to-charge ratio (m/z), retention time (RT), tandem MS (MS/MS) spectra, and CCS values. Among the studied metabolites, 263 traveling wave ion mobility spectrometry (TWIMS)-derived CCS values (TWCCSN2) were reported for the first time, and more than 70% of these were CCS values of VLMs. The TWCCSN2 values were highly repeatable, with inter-day variations of <1% relative standard deviation (RSD). The developed method revealed excellent TWCCSN2 accuracy with a CCS difference (ΔCCS) within ±2% of the reported drift tube IMS (DTIMS) and TWIMS CCS values. The complexity of the urine matrix did not affect the precision of the method, as evidenced by ΔCCS within ±1.92%. According to the Metabolomics Standards Initiative, 55 urinary metabolites were identified with a confidence level of 1. Among these 55 metabolites, 53 (96%) were VLMs. The larger number of confirmed compounds found in this study was a result of the addition of TWCCSN2 values, which clearly increased metabolite identification confidence.
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    Multi-Pass Arrival Time Correction in Cyclic Ion Mobility Mass Spectrometry for Imaging and Shotgun Lipidomics
    (2024-01-01) Wisanpitayakorn P.; Jariyasopit N.; Duangkumpha K.; Goh J.X.; Palmer M.E.; Sirivatanauksorn Y.; Khoomrung S.; Wisanpitayakorn P.; Mahidol University
    Direct-infusion mass spectrometry (DI-MS) and mass spectrometry imaging (MSI) are powerful techniques for lipidomics research. However, annotating isomeric and isobaric lipids with these methods is challenging due to the absence of chromatographic separation. Recently, cyclic ion mobility mass spectrometry (cIM-MS) has been proposed to overcome this limitation. However, fluctuations in room conditions can affect ion mobility multipass arrival times, potentially reducing annotation confidence. In this study, we developed a multipass arrival time correction method that proved effective across various dates, room temperatures, ion mobility settings, and laboratories using mixtures of reference standards. We observed slight variations in the linear correction lines between lipid and nonlipid molecules, underscoring the importance of choosing appropriate reference molecules. Based on these results, we demonstrated that an accurate multipass arrival time database can be constructed from corrected t0 and tp for interlaboratory use and can effectively identify isomeric lipids in MSI using only a single measurement. This approach significantly simplifies the identification process compared to determining multipass collision cross-section, which requires multiple measurements that are both sample- and time-intensive for MSI. Additionally, we validated our multipass drift time correction method in shotgun lipidomics analyses of human and mouse serum samples and observed no matrix effect for the analysis. Despite variations in dates, room temperatures, instruments, and ion mobility settings, our approach reduced the mean drift time differences from over 2% to below 0.2%.
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    Outcomes of an Early Laparoscopic Cholecystectomy in Acute Cholecystitis, Grades I and II
    (2022-08-01) Noppakunsomboon N.; Swangsri J.; Sirivatanauksorn Y.; Kongkaewpaisan N.; Mahidol University
    Objective: According to the accumulated benefits of laparoscopic cholecystectomy (LC) in acute cholecystitis (AC), early LC is becoming a standard management for selected patients. While patients with mild AC usually gain the advantages of this approach, removing a more inflamed gallbladder in patients with moderate AC has various results, depending on the institute where the procedure is performed. The aim of the study was to compare the outcomes between early LC in patients with grade I and II AC. Materials and Methods: From June, 2015 to December, 2019, electronic medical records in the division of Acute Care Surgery at Siriraj Hospital in Bangkok were reviewed retrospectively. An early LC was performed consecutively in 105 cases of AC grades I and II. The overall results and the outcomes comparing grades I and II AC were evaluated. Results: Forty-two patients were grade I (40%). Patients with grade I AC tended to be younger (56 +/- 17 years vs. 63 +/-15 years, p = 0.03). Among grade II patients, the late onset of more than 72 hours was the most common measure (62%). The estimated blood loss was significantly lower in grade I [30 (5-450) ml. vs. 100 (5-3,000) ml., p =0.018]. The overall conversion rate was 21%, which was significantly higher in grade II AC (28.6% vs. 9.5%, p= 0.026). There were no differences in operating time (125 +/- 47 minutes vs. 117 +/- 44 minutes. p = 0.365), total lengths of stay [4 (2-7) days vs. 5 (3-28) days, p = 0.163], and post-operative complications (19% vs 25%, p = 0.448). The minor bile duct injuries occurred in four patients (3.8%), 2 cases in each group. From the multivariate analysis, grade II AC did not statistically impact the conversion (adjusted OR 2.99, 95% CI 0.5-17.6, p = 0.225). Conclusion: Our study shows that the overall and evolving outcomes of early LC for grade I and II AC were safe and feasible. While a higher conversion rate and estimated blood loss attributed to grade II AC, a pre-operative severity grading can guide surgeons to accommodate their ability so as to maximize the benefits of early LC.
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    Pancreatic steatosis endosonographic criteria: A histology-validated EUS diagnostic study
    (2026-01-01) Geeratragool T.; Pausawasdi N.; Angkathunyakul N.; Rugivarodom M.; Charatcharoenwitthaya P.; Maipang K.; Kaosombatwattana U.; Kositamongkol P.; Mahawithitwong P.; Tovikkai C.; Dumronggittigule W.; Assawasirisin C.; Sangserestid P.; Chuesuay K.; Limsirorat N.; Pongpaibul A.; Sirivatanauksorn Y.; Geeratragool T.; Mahidol University
    Background and Objectives: – Pancreatic steatosis (PS) is increasingly recognized as a clinically significant condition. Although EUS is commonly used to evaluate PS, existing diagnostic criteria lack histologic validation. This study aimed to establish histology-validated EUS criteria for diagnosing PS. Methods: – Patients undergoing EUS before pancreatic surgery were prospectively enrolled. Two experienced endosonographers independently assessed predefined EUS features, with interobserver agreement evaluated. Histologic confirmation of PS was obtained from surgical specimens. Features significantly associated with histologic PS were used to develop the pancreatic steatosis endosonographic criteria (PSEC). Results: – Of 132 enrolled patients, 96 completed the study. Histologic PS was confirmed in 27.10% of cases. EUS features independently associated with PS included hyperechoic parenchyma (odds ratio [OR]: 51.96), obscured main pancreatic duct margin (OR: 10.88), obscured “salt-and-pepper” appearance (OR: 8.25), and absence of hyperechoic foci or strands (OR: 5.11). Based on these findings, the PSEC were established, consisting of 1 major criterion (hyperechoic parenchyma) and 3 minor criteria (obscured salt-and-pepper appearance, obscured main pancreatic duct margin, and absence of hyperechoic foci or strands). The optimal diagnostic threshold was defined as either 1 major plus 1 minor criterion or 3 minor criteria. This model achieved an area under the receiver operating characteristic curve of 0.84 (95% confidence interval [CI]: 0.8–0.9), sensitivity of 84.60%, specificity of 87.10%, positive predictive value of 71%, and negative predictive value of 93.80%, with substantial interobserver agreement. Conclusion: – PSEC represents the first histology-validated EUS criteria for PS, demonstrating robust diagnostic performance and practical applicability in clinical practice.
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    Plasma metabolomic analysis in Thai EGFR-mutated non-small cell lung cancer patients
    (2025-01-01) Thamlikitkul L.; Wanichthanarak K.; Manocheewa S.; Limjiasahapong S.; Phonsatta N.; Thangvichien S.; Panya A.; Sirivatanauksorn Y.; Poungvarin N.; Khoomrung S.; Thamlikitkul L.; Mahidol University
    Lung cancer remains the leading cause of cancer-related mortality worldwide, underscoring the urgent need for non-invasive approaches to improve diagnosis, patient stratification, and therapeutic monitoring. Metabolic reprogramming driven by oncogenic alterations—particularly Epidermal Growth Factor Receptor (EGFR) mutations in non-small cell lung cancer (NSCLC)—creates distinctive plasma signatures with clinical relevance. In this study, plasma metabolomic profiling revealed that amino acid and sugar metabolism exhibited the strongest discriminatory patterns. NSCLC patients consistently showed elevated glycine and reduced tryptophan and inositol compared with healthy controls. Distinct amino acid and organic acid shifts further differentiated EGFR-mutated from wild-type NSCLC, while alterations in tryptophan, valine, and oxalic acid characterized patients with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs). These findings underscore biologically relevant metabolic alterations associated with EGFR mutation and TKI resistance, supporting the potential of plasma metabolite profiles as minimally invasive indicators for molecular classification and treatment response in NSCLC.
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    Quantifying fecal and plasma short-chain fatty acids in healthy Thai individuals
    (2024-12-01) Manokasemsan W.; Jariyasopit N.; Poungsombat P.; Kaewnarin K.; Wanichthanarak K.; Kurilung A.; Duangkumpha K.; Limjiasahapong S.; Pomyen Y.; Chaiteerakij R.; Tansawat R.; Srisawat C.; Sirivatanauksorn Y.; Sirivatanauksorn V.; Khoomrung S.; Manokasemsan W.; Mahidol University
    Short-chain fatty acids (SCFAs) are involved in important physiological processes such as gut health and immune response, and changes in SCFA levels can be indicative of disease. Despite the importance of SCFAs in human health and disease, reference values for fecal and plasma SCFA concentrations in healthy individuals are scarce. To address this gap in current knowledge, we developed a simple and reliable derivatization-free GC-TOFMS method for quantifying fecal and plasma SCFAs in healthy individuals. We targeted six linear- and seven branched-SCFAs, obtaining method recoveries of 73–88% and 83–134% in fecal and plasma matrices, respectively. The developed methods are simpler, faster, and more sensitive than previously published methods and are well suited for large-scale studies. Analysis of samples from 157 medically confirmed healthy individuals showed that the total SCFAs in the feces and plasma were 34.1 ± 15.3 µmol/g and 60.0 ± 45.9 µM, respectively. In fecal samples, acetic acid (Ace), propionic acid (Pro), and butanoic acid (But) were all significant, collectively accounting for 89% of the total SCFAs, whereas the only major SCFA in plasma samples was Ace, constituting of 93% of the total plasma SCFAs. There were no statistically significant differences in the total fecal and plasma SCFA concentrations between sexes or among age groups. The data revealed, however, a positive correlation for several nutrients, such as carbohydrate, fat, iron from vegetables, and water, to most of the targeted SCFAs. This is the first large-scale study to report SCFA reference intervals in the plasma and feces of healthy individuals, and thereby delivers valuable data for microbiome, metabolomics, and biomarker research.
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    Revisiting chloroplast genomic landscape and annotation towards comparative chloroplast genomes of Rhamnaceae
    (2023-12-01) Wanichthanarak K.; Nookaew I.; Pasookhush P.; Wongsurawat T.; Jenjaroenpun P.; Leeratsuwan N.; Wattanachaisaereekul S.; Visessanguan W.; Sirivatanauksorn Y.; Nuntasaen N.; Kuhakarn C.; Reutrakul V.; Ajawatanawong P.; Khoomrung S.; Mahidol University
    Background: Massive parallel sequencing technologies have enabled the elucidation of plant phylogenetic relationships from chloroplast genomes at a high pace. These include members of the family Rhamnaceae. The current Rhamnaceae phylogenetic tree is from 13 out of 24 Rhamnaceae chloroplast genomes, and only one chloroplast genome of the genus Ventilago is available. Hence, the phylogenetic relationships in Rhamnaceae remain incomplete, and more representative species are needed. Results: The complete chloroplast genome of Ventilago harmandiana Pierre was outlined using a hybrid assembly of long- and short-read technologies. The accuracy and validity of the final genome were confirmed with PCR amplifications and investigation of coverage depth. Sanger sequencing was used to correct for differences in lengths and nucleotide bases between inverted repeats because of the homopolymers. The phylogenetic trees reconstructed using prevalent methods for phylogenetic inference were topologically similar. The clustering based on codon usage was congruent with the molecular phylogenetic tree. The groups of genera in each tribe were in accordance with tribal classification based on molecular markers. We resolved the phylogenetic relationships among six Hovenia species, three Rhamnus species, and two Ventilago species. Our reconstructed tree provides the most complete and reliable low-level taxonomy to date for the family Rhamnaceae. Similar to other higher plants, the RNA editing mostly resulted in converting serine to leucine. Besides, most genes were subjected to purifying selection. Annotation anomalies, including indel calling errors, unaligned open reading frames of the same gene, inconsistent prediction of intergenic regions, and misannotated genes, were identified in the published chloroplast genomes used in this study. These could be a result of the usual imperfections in computational tools, and/or existing errors in reference genomes. Importantly, these are points of concern with regards to utilizing published chloroplast genomes for comparative genomic analysis. Conclusions: In summary, we successfully demonstrated the use of comprehensive genomic data, including DNA and amino acid sequences, to build a reliable and high-resolution phylogenetic tree for the family Rhamnaceae. Additionally, our study indicates that the revision of genome annotation before comparative genomic analyses is necessary to prevent the propagation of errors and complications in downstream analysis and interpretation.
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    Spatial Mapping of Stereoisomeric and Isobaric Alkaloids in Mitragyna speciosa Tissues by High-Resolution DESI-cIM-MS
    (2025-12-02) Wisanpitayakorn P.; Konsue A.; Sartyoungkul T.; In-on A.; Sirivatanauksorn Y.; Gang D.R.; Kittakoop P.; Khoomrung S.; Wisanpitayakorn P.; Mahidol University
    Conventional mass spectrometry imaging (MSI), even when combined with low-resolution ion mobility, lacks the resolving power to distinguish stereoisomers. To address this limitation, we developed a high-resolution desorption electrospray ionization cyclic ion mobility mass spectrometry (DESI-cIM-MS) method for in situ separation and spatial mapping of stereoisomeric compounds, using Mitragyna speciosa (kratom) as a model system. We characterized and validated the separation of four mitragynine-type stereoisomers─mitragynine (MG), speciogynine (SG), mitraciliatine (MC), and speciociliatine (SC)─using chemical standards. Notably, SC exhibited two gas-phase conformers, fast (SC-F) and slow (SC-S), supported by quantum chemical calculations. Using multipass separation and targeted ion slicing, we resolved and mapped SG, MC, and SC-S in surface-spotted standards. To address coelution between MG and SC-F, we developed a pixel-wise subtraction strategy based on the SC-F/SC-S intensity ratio to mitigate SC-F interference in the MG ion image. Direct analysis of kratom twig tissue revealed distinct spatial distributions for each stereoisomer. MG was found broadly throughout the twig except in the xylem. MC was concentrated in the pith, with some presence in the bark. SC and SG were predominantly localized in the bark, especially the epidermis. Furthermore, we resolved two additional important alkaloids, paynantheine and 7-OH-mitragynine, from their isobaric compounds; both were distributed throughout the twig except the xylem. These findings demonstrate the importance of high-resolution ion mobility in MSI for accurately resolving structurally similar compounds and improving spatial analysis in metabolomics and natural product research.
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    Study of siRNA Delivery via Polymeric Nanoparticles in Combination with Angiogenesis Inhibitor for The Treatment of AFP-Related Liver Cancer
    (2022-10-01) Punuch K.; Wongwan C.; Jantana S.; Somboonyosdech C.; Rodponthukwaji K.; Kunwong N.; Nguyen K.T.; Sirivatanauksorn V.; Sirivatanauksorn Y.; Srisawat C.; Punnakitikashem P.; Mahidol University
    Angiogenesis inhibitor drugs have been explored as important pharmacological agents for cancer therapy, including hepatocellular carcinoma. These agents have several drawbacks, such as drug resistance, nonspecific toxicity, and systemic side effects. Therefore, combination therapy of the drug and small interfering RNA could be a promising option to achieve high therapeutic efficacy while allowing a lower systemic dose. Therefore, we studied adding an alpha-fetoprotein siRNA (AFP-siRNA) incorporated on polymeric nanoparticles (NPs) along with angiogenesis inhibitor drugs. The AFP siRNA-loaded NPs were successfully synthesized at an average size of 242.00 ± 2.54 nm. Combination treatment of AFP-siRNA NPs and a low dose of sunitinib produced a synergistic effect in decreasing cell viability in an in vitro hepatocellular carcinoma (HCC) model. AFP-siRNA NPs together with sorafenib or sunitinib greatly inhibited cell proliferation, showing only 39.29 ± 2.72 and 44.04 ± 3.05% cell viability, respectively. Moreover, quantitative reverse transcription PCR (qRT-PCR) demonstrated that AFP-siRNA incorporated with NPs could significantly silence AFP-mRNA expression compared to unloaded NPs. Interestingly, the expression level of AFP-mRNA was further decreased to 28.53 ± 5.10% when sunitinib was added. Therefore, this finding was considered a new promising candidate for HCC treatment in reducing cell proliferation and enhancing therapeutic outcomes.
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    Traveling Wave Ion Mobility-Derived Collision Cross Section Database for Plant Specialized Metabolites: An Application to Ventilago harmandiana Pierre
    (2022-10-07) Jariyasopit N.; Limjiasahapong S.; Kurilung A.; Sartyoungkul S.; Wisanpitayakorn P.; Nuntasaen N.; Kuhakarn C.; Reutrakul V.; Kittakoop P.; Sirivatanauksorn Y.; Khoomrung S.; Mahidol University
    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 TWCCSN2and MS database for 112 plant specialized metabolites. The database included 15 compounds that were isolated and purified in-house and are not commercially available. We obtained accurate m/z, retention times, fragment ions, and TWIMS-derived CCS (TWCCSN2) values for 207 adducts (ESI+and ESI-). The database included novel 158 TWCCSN2values from 79 specialized metabolites. In the presence of plant matrix, the CCS measurement was reproducible and robust. Finally, we demonstrated the application of the database to extend the metabolite coverage of Ventilago harmandiana Pierre. In addition to pyranonaphthoquinones, a group of known specialized metabolites in V. harmandiana, we identified flavonoids, xanthone, naphthofuran, and protocatechuic acid for the first time through targeted analysis. Interestingly, further investigation using IM-MS of unknown features suggested the presence of organonitrogen compounds and lipid and lipid-like molecules, which is also reported for the first time. Data are available on the MassIVE (https://massive.ucsd.edu, data set identifier MSV000090213).