In the aging process, the presence of interleukin (IL)-17-producing CD4+CD28-NKG2D+T cells (called pathogenic CD4+ T cells) is strongly associated with inflammation and the development of various diseases. Thus, their presence needs to be monitored. The emergence of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy empowered with machine learning is a breakthrough in the field of medical diagnostics. This study aimed to discriminate between the elderly with a low percentage (LP; ≤3%) and a high percentage (HP; ≥6%) of pathogenic CD4+CD28-NKG2D+IL17+ T cells by utilizing ATR-FTIR coupled with machine learning algorithms. ATR spectra of serum, exosome, and HDL from both groups were explored in this study. Only exosome spectra in the 1700–1500 cm⁻¹ region exhibited possible discrimination for the LP and HP groups based on principal component analysis (PCA). Furthermore, partial least square-discriminant analysis (PLS-DA) could differentiate both groups using the 1700–1500 cm⁻¹ region of exosome ATR spectra with 64% accuracy, 69% sensitivity, and 61% specificity. To obtain better classification performance, several spectral models were then established using advanced machine learning algorithms, including J48 decision tree, support vector machine (SVM), random forest (RF), and neural network (NN). Herein, NN was considered to be the best model with an accuracy of 100%, sensitivity of 100%, and specificity of 100% using serum spectra in the region of 1800–900 cm⁻¹. Exosome spectra in the 1700–1500 and combined 3000–2800 and 1800–900 cm⁻¹ regions using the NN algorithm gave the same accuracy performance of 95% with a variation in sensitivity and specificity. HDL spectra with the NN algorithm also showed excellent test performance in the 1800–900 cm⁻¹ region with 97% accuracy, 100% sensitivity, and 95% specificity. This study demonstrates that ATR-FTIR coupled with machine learning algorithms can be used to study immunosenescence. Furthermore, this approach can possibly be applied to monitor the presence of pathogenic CD4+ T cells in the elderly. Due to the limited number of samples used in this study, it is necessary to conduct a large-scale study to obtain more robust classification models and to assess the true clinical diagnostic performance.

Cholangiocarcinoma (CCA) is a malignancy of the bile duct epithelium. Opisthorchis viverrini infection is a known high-risk factor for CCA and in found, predominantly, in Northeast Thailand. The silent disease development and ineffective diagnosis have led to late-stage detection and reduction in the survival rate. Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) is currently being explored as a diagnostic tool in medicine. In this study, we apply ATR-FTIR to discriminate CCA sera from hepatocellular carcinoma (HCC), biliary disease (BD) and healthy donors using a multivariate analysis. Spectral markers differing from healthy ones are observed in the collagen band at 1284, 1339 and 1035 cm⁻¹, the phosphate band ($vsP{O}_2^{-}$) at 1073 cm⁻¹, the polysaccharides band at 1152 cm⁻¹ and 1747 cm⁻¹ of lipid ester carbonyl. A Principal Component Analysis (PCA) shows discrimination between CCA and healthy sera using the 1400–1000 cm⁻¹ region and the combined 1800—1700 + 1400–1000 cm⁻¹ region. Partial Least Square-Discriminant Analysis (PLS-DA) scores plots in four of five regions investigated, namely, the 1400–1000 cm⁻¹, 1800–1000 cm⁻¹, 3000–2800 + 1800–1000 cm⁻¹ and 1800–1700 + 1400–1000 cm⁻¹ regions, show discrimination between sera from CCA and healthy volunteers. It was not possible to separate CCA from HCC and BD by PCA and PLS-DA. CCA spectral modelling is established using the PLS-DA, Support Vector Machine (SVM), Random Forest (RF) and Neural Network (NN). The best model is the NN, which achieved a sensitivity of 80–100% and a specificity between 83 and 100% for CCA, depending on the spectral window used to model the spectra. This study demonstrates the potential of ATR-FTIR spectroscopy and spectral modelling as an additional tool to discriminate CCA from other conditions.

Cholangiocarcinoma (CCA) is a malignancy arising from cholangiocytes. Currently, the treatment and prognosis for CCA are mostly poor. Recently, we have reported that coiled-coil domain containing 25 (CCDC25) protein level in the sera may be a diagnostic marker for CCA. Subsequently, we identified three binding proteins of CCDC25 and found that kallikrein-11 (KLK11) expression was highest among those binding proteins. In this study, we investigated CCDC25 and KLK11 expression in CCA and adjacent normal tissues (n = 18) using immunohistochemistry. The results demonstrated that the expressions of CCDC25 and KLK11 in CCA tissues were both significantly higher than the adjacent tissues (p < 0.001 and p = 0.001, respectively). Then, using GEPIA bioinformatics analysis, KLK11 mRNA was significantly overexpressed in CCA tumor tissues compared with normal tissues (p < 0.05). Moreover, CCDC25 expression was positively correlated with KLK11 expression in CCA with lymph node metastasis (p = 0.028, r = 0.593). An analysis for the interaction of KLK11 with CCDC25 and other proteins, using STRING version 11.0, revealed that CCDC25 and KLK11 correlated with metastasis-related proteins. In addition, Kaplan-Meier survival curve analysis revealed that a high expression of KLK11 was associated with the poor prognosis of CCA. In conclusion, KLK11 is, as a binding protein for CCDC25, possibly involved in the metastatic process of CCA. KLK11 may be used as a prognostic marker for CCA.

The mortality rate of cholangiocarcinoma (CCA) is high since there is a lack of a non-invasive technique to accurately detect tumors at the early stage. CCA biomarkers are consistently needed for various purposes including screening, early diagnosis, prognosis and follow-up. Herein, using bioinformatic analysis of our mitochondrial proteome database of CCA tissues, we identified cytokine-induced apoptosis inhibitor 1 (CIAPIN1) as a potential prognostic biomarker for CCA. CIAPIN1 levels in the sera of 159 CCA patients and 93 healthy controls (HC) were measured using a dot blot assay. The median level ± quartile deviation of CIAPIN1 level in the sera of CCA patient group was 0.5144 ± 0.34 µg/µL, which was significantly higher than 0.2427 ± 0.09 µg/µL of the HC group (p < 0.0001). In CCA patients, higher serum CIAPIN1 level was significantly associated with lymph node metastasis (p = 0.024) and shorter overall survival time (p = 0.001, Kaplan–Meier test). Cox regression analysis showed that the serum CIAPIN1 level can be an independent prognostic indicator for the survival of CCA patients. Moreover, for the prediction of CCA prognosis, CIAPIN1 is superior to CEA, CA19-9 and ALP. In conclusion, CIAPIN1 can be a serum biomarker candidate for the poor prognosis of CCA.

Cholangiocarcinoma (CCA), a malignancy of the biliary epithelium, can arise at any point in the biliary system. We previously reported that CIAPIN1 is detectable in the sera and that its overexpression was associated with poor prognosis and metastasis of CCA patients. In this study, we investigated further its expression in CCA tissues, biological functions, and related signaling pathways in CCA cells. First, we examined CIAPIN1 expression in CCA tissues of 39 CCA patients using immunohistochemistry (IHC). Then, CIAPIN1-related proteins expressed in CCA cells were identified using RNA interference (siRNA) and liquid chromatography–mass spectrometry (LC–MS/MS). To predict the functions and signaling pathways of CIAPIN1 in CCA cells, the identified proteins were analyzed using bioinformatics tools. Then, to validate the biological functions of CIAPIN1 in the CCA cell line, transwell migration/invasion assays were used. CIAPIN1 was overexpressed in CCA tissues compared with adjacent noncancerous tissues. Its overexpression was correlated with lymph node metastasis. Bioinformatic analyses predicted that CIAPIN1 is connected to the TGF-β/SMADs signaling pathway via nitric oxide synthase 1 (NOS1) and is involved in the metastasis of CCA cells. In fact, cell migration and invasion activities of the KKU-100 CCA cell line were significantly suppressed by CIAPIN1 gene silencing. Our results unravel its novel function and potential signaling pathway in metastasis of CCA cells. CIAPIN1 can be a poor prognostic factor and can be a promising target molecule for CCA chemotherapy.

Glucose-6 phosphate dehydrogenase (G6PD) deficiency is an X-linked blood disease that affects 400 million people globally and is especially prevalent in malaria-endemic regions. A significant portion of carriers are asymptomatic and undiagnosed posing complications in the eradication of malaria as it restricts the types of drugs used for malaria treatment. A simple and accurate diagnosis of the deficiency is vital in the eradication of malaria. In this study, we investigate the potential of attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) as a diagnostic technique for G6PD deficiency. Venous blood samples were collected in lithium heparin anticoagulant tubes from G6PD partial and fully deficient volunteers, n = 17, and normal volunteers, n = 59, in Khon Kaen, Thailand. Spectra of aqueous and dry samples were acquired of whole blood, plasma, and red blood cells, and modeled using partial least squares discriminant analysis (PLS-DA). PLS-DA modeling resulted in a sensitivity of 0.800 and specificity of 0.800 correctly classifying fully deficient participants as well as a majority of partially deficient females who are often misdiagnosed as normal by current screening methods. The viability of utilizing aqueous samples has always been hindered by the variability of hydration in the sample, but by employing multicurve curve resolution-alternating least squares to subtract water from each sample we are able to produce high-quality spectra with minimized water contributions. The approach shows proof of principle that ATR FT-IR combined with multivariate data analysis could become a frontline screening tool for G6PD deficiency by improving tailored drug treatments and ultimately saving lives.