Suparat Chaipipat

Dr. Suparat Chaipipat


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Verified
Journal Article
Open access
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KAKyung-Geun Ahn
Kyung-Geun Ahn
JKJin-Wook Chris Kim
Jin-Wook Chris Kim
SGSoonchul Gwoak
Soonchul Gwoak
EOEunkyung Oh
Eunkyung Oh
SLSeyeon Lee
Seyeon Lee
GKGeon A Kim
Geon A Kim
Canine cancer screening has an important limitation in that organ-specific screening strategies used in human medicine cannot be directly applied across routine veterinary clinical practice. Blood-based volatile organic compound (VOC) profiling may provide a practical approach for pan-cancer screening; however, its application in multicenter and multinational settings requires evaluation that accounts for cohort heterogeneity and analytical variability. In this study, we evaluated the canine cancer screening performance of an integrated classification framework using a headspace gas chromatography–mass spectrometry (HS-GC/MS)-based targeted blood VOC panel in a retrospective multicohort dataset comprising dogs recruited in Korea and Thailand. Whole-blood samples from 590 dogs recruited in Korea and Thailand were analyzed, including 167 dogs in the malignant tumor group and 423 dogs in the non-cancer control group. The predefined targeted VOC panel consisted of aromatic compounds and straight-chain alkanes and was analyzed using HS-GC/MS. The Korea and Thailand cohorts were incorporated into a single integrated classification framework rather than being separated into country-specific models. To evaluate performance variability associated with data partitioning, cohort-aware stratified training–validation splitting was repeated 30 times within the integrated retrospective cohort, with both national cohorts represented in the training and validation sets in each repeat. Class imbalance correction was applied only to the training data, and validation performance was assessed using both threshold-dependent and threshold-independent metrics. Across the 30 repeated validations, the integrated framework achieved an AUROC of 0.926 ± 0.019 and an AUPRC of 0.894 ± 0.023. Balanced accuracy, accuracy, sensitivity, specificity, F1-score, MCC, and Cohen’s κ were 0.858 ± 0.024, 0.895 ± 0.018, 0.772 ± 0.048, 0.943 ± 0.022, 0.805 ± 0.033, 0.736 ± 0.046, and 0.734 ± 0.045, respectively. In the sample-level prediction score analysis, the median predicted cancer probabilities for cancer and non-cancer samples were 0.954 and 0.041, respectively, indicating clear probability-based separation between the two groups. In the cohort-specific analysis, the discrimination signal was maintained in both the Korea and Thailand cohorts, although threshold-dependent performance differed between the two cohorts. These findings indicate that an HS-GC/MS-based targeted blood VOC panel provided a consistent cancer-associated classification signal under repeated internal validation within the specific integrated retrospective dataset evaluated in this study. The results demonstrate the feasibility of evaluating a common classification framework across the Korea and Thailand cohorts without constructing separate country-specific models, while not establishing independent external generalizability or platform-independent robustness. Because the Korea and Thailand cohorts were completely confounded with the Agilent and Thermo Fisher analytical platforms, respectively, the independent contributions of cohort characteristics and analytical platform cannot be determined from the present data. Further independent prospective validation in newly recruited populations and institutions, together with disease-control evaluation including clinically relevant controls, cohort-specific calibration, evaluation across analytical platforms, and assessment of clinical utility within real-world workflows, is required before the external generalizability and clinical applicability of the framework can be determined.

19 May 2026 in Veterinary Sciences
Verified
Journal Article
Open access
PDF file
Nattaphong AkrimajirachooteNattaphong Akrimajirachoote
Nattaphong Akrimajirachoote
MPMontri Pattarapanawan
Montri Pattarapanawan
SCSuparat Chaipipat
Suparat Chaipipat
YPYanika Piyasanti
Yanika Piyasanti
KSKornkanok Sritabtim
Kornkanok Sritabtim
PSPiyathip Setthawong
Piyathip Setthawong
The isolation of fibroblast-like cells from crocodile skeletal muscle provides a valuable platform for studies in comparative physiology, reptilian biology, regenerative medicine, and tissue engineering. In this article, we present an optimized protocol for isolating and characterizing fibroblast-like cells derived from the embryonic skeletal muscle of the Siamese crocodile (Crocodylus siamensis). The procedure improved cell yields and viability while maintaining phenotypic and genetic stability. Dorsal and tail skeletal muscle tissue was cultured in flasks pre-coated with collagen. The cells attached and began migrating from the explants within one day. Optimal culture conditions were achieved using Dulbecco’s Modified Eagle Medium/Nutrient Mixture F-12 or Minimum Essential Medium Alpha supplemented with 10% fetal bovine serum, 2% crocodile serum, and growth-promoting factors, incubated at 28 °C without CO2. These conditions supported a shorter population doubling time and enhanced cell proliferation. The established cells displayed a spindle-shaped fibroblastic morphology, expressed the fibroblast-specific marker fibronectin, and maintained a stable karyotype through passage 20. The cell line remained stable and proliferative for at least 30 passages under standard culture conditions. Our study established the first standardized fibroblast-like cell line derived from C. siamensis, thus providing a foundation for future studies in reptilian physiology, cytogenetics, and regenerative biotechnology.