• International Neurourology Journal
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• v.22 no.4
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• pp.228-236
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• 2018

Neuromodulation was introduced for patients with poor outcomes from the existing traditional treatment approaches. It is well-established as an alternative, novel treatment option for voiding dysfunction. The current system of neuromodulation uses an open-loop system that only delivers continuous stimulation without considering the patient's state changes. Though the conventional open-loop system has shown positive clinical results, it can cause problems such as decreased efficacy over time due to neural habituation, higher risk of tissue damage, and lower battery life. Therefore, there is a need for a closed-loop system to overcome the disadvantages of existing systems. The closed-loop neuromodulation includes a system to monitor and stimulate micturition reflex pathways from the lower urinary tract, as well as the central nervous system. In this paper, we reviewed the current technological status to measure biomarker for closed-loop neuromodulation systems for voiding dysfunction.

• Journal of Veterinary Clinics
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• v.38 no.1
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• pp.21-26
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• 2021

Pyometra, a common disorder in intact bitches, can lead to canine sepsis. Identification of biomarkers for sources of infection in the uterus using two-dimensional electrophoresis (2-DE)-mass spectrometry (MS) analysis may enable the discovery of novel diagnostic markers of sepsis. Toward this end, surgically resected uterus samples from four bitches (three pyometra and one healthy) were randomly selected for 2-DE-MS, which identified 32 differentially expressed proteins, including seven inflammatory proteins, five non-inflammatory proteins, and 20 functionally unknown proteins. Despite the limited information on canine uterus proteomics, we suggest the potential use of differentially expressed uterus proteins as candidate biomarkers to discover targets to attenuate inflammation in pyometra. Further identification of the functionally unknown proteins is warranted.

• BMB Reports
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• v.56 no.6
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• pp.341-346
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• 2023

Acute myocardial infarction (AMI) is a multifaceted syndrome influenced by the functions of various extrinsic and intrinsic pathways and pathological processes, which can be detected in circulation using biomarkers. In this study, we investigated the secretome protein profile of induced-hypertrophy cardiomyocytes to identify next-generation biomarkers for AMI diagnosis and management. Hypertrophy was successfully induced in immortalized human cardiomyocytes (T0445) by 200 nM ET-1 and 1 μM Ang II. The protein profiles of hypertrophied cardiomyocyte secretomes were analyzed by nano-liquid chromatography with tandem mass spectrometry and differentially expressed proteins that have been identified by Ingenuity Pathway Analysis. The levels of 32 proteins increased significantly (>1.4 fold), whereas 17 proteins (<0.5 fold) showed a rapid decrease in expression. Proteomic analysis showed significant upregulation of six 14-3-3 protein isoforms in hypertrophied cardiomyocytes compared to those in control cells. Multi-reaction monitoring results of human plasma samples showed that 14-3-3 protein-zeta levels were significantly elevated in patients with AMI compared to those of healthy controls. These findings elucidated the role of 14-3-3 protein-zeta in cardiac hypertrophy and cardiovascular disorders and demonstrated its potential as a novel biomarker and therapeutic strategy.

• Tuberculosis and Respiratory Diseases
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• v.86 no.2
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• pp.94-101
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• 2023

A recent understanding of the dynamic continuous spectrum of Mycobacterium tuberculosis infection has led to the recognition of incipient tuberculosis, which refers to the latent infection state that has begun to progress to active tuberculosis. The importance of early detection of these individuals with a high-risk of progression to active tuberculosis is emphasized to efficiently implement targeted tuberculosis preventive therapy. However, the tuberculin skin test or interferon-γ release assay, which is currently used for the diagnosis of latent tuberculosis infection, does not aid in the prediction of the risk of progression to active tuberculosis. Thus, a novel test is urgently needed. Recently, simultaneous and systematic analysis of differentially expressed genes using a high-throughput platform has enabled the discovery of key genes that may serve potential biomarkers for the diagnosis or prognosis of diseases. This host transcriptional investigation has been extended to the field of tuberculosis, providing promising results. The present review focuses on recent progress and challenges in the field of blood transcriptional signatures to predict progression to active tuberculosis.

• Journal of Microbiology and Biotechnology
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• v.31 no.2
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• pp.233-239
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• 2021

Cyanobacteriochromes (CBCRs) are phytochrome-related photoreceptor proteins in cyanobacteria and cover a wide spectral range from ultraviolet to far-red. A single GAF domain that they contain can bind bilin(s) autocatalytically via heterologous recombination and then fluoresce, with potential applications as biomarkers and biosensors. Here, we report that a novel red/green CBCR GAF domain, SPI1085g2 from Spirulina subsalsa, covalently binds both phycocyanobilin (PCB) and phycoerythrobilin (PEB). The PCB-binding GAF domain exhibited canonical red/green photoconversion with weak fluorescence emission. However, the PEB-binding GAF domain, SPI1085g2-PEB, exhibited an intense orange fluorescence (λabs.max = 520 nm, λfluor.max = 555 nm), with a fluorescence quantum yield close to 1.0. The fluorescence of SPI1085g2-PEB was selectively and instantaneously quenched by copper ions in a concentration-dependent manner and exhibited reversibility upon treatment with the metal chelator EDTA. This study identified a novel PEB-binding cyanobacteriochrome-based fluorescent protein with the highest quantum yield reported to date and suggests its potential as a biosensor for the rapid detection of copper ions.

• Journal of Breast Cancer
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• v.21 no.4
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• pp.363-370
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• 2018

Purpose: Breast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, this study focused on using miRNAs to develop a method for identifying noninvasive biomarkers. Methods: To discover critical candidates, differential expression analysis was performed on tissue-originated miRNA profiles of 409 early breast cancer patients and 87 healthy controls from The Cancer Genome Atlas database. We selected candidates from the differentially expressed miRNAs and then evaluated every possible molecular signature formed by the candidates. The best signature was validated in independent serum samples from 113 early breast cancer patients and 47 healthy controls using reverse transcription quantitative real-time polymerase chain reaction. Results: The miRNA candidates in our method were revealed to be associated with breast cancer according to previous studies and showed potential as useful biomarkers. When validated in independent serum samples, the area under curve of the final miRNA signature (miR-21-3p, miR-21-5p, and miR-99a-5p) was 0.895. Diagnostic sensitivity and specificity were 97.9% and 73.5%, respectively. Conclusion: The present study established a novel and effective method to identify biomarkers for early breast cancer. And the method, is also suitable for other cancer types. Furthermore, a combination of three miRNAs was identified as a prospective biomarker for breast cancer early detection.

• Biomedical Science Letters
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• v.28 no.4
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• pp.260-275
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• 2022

Sterile alpha motif (SAM) domains bind to various proteins, lipids, and RNAs. However, these domains have not yet been analyzed as prognostic biomarkers. In this study, SAM domain containing 13 (SAMD13), a member of the SAM domain, was evaluated to identify a novel prognostic biomarker in various human cancers, including hepatocellular carcinoma (HCC). Moreover, we identified a correlation between SAMD13 expression and immune cell infiltration in HCC. We performed bioinformatics analysis using online databases, such as Tumor Immune Estimation Resource, UALCAN, Kaplan-Meier plotter, LinkedOmics, and Gene Expression Profiling Interactive Analysis2. SAMD13 expression in HCC samples was significantly higher than that in normal liver tissue; additionally, SAMD13 was higher in primary tumors, various stages of cancer and grades of tumor, and status of nodal metastasis. Higher SAMD13 expression was also associated with poorer prognosis. SAMD13 expression positively correlated with CD8+ T cells, CD4+ T cells, B cells, neutrophils, macrophages, and dendritic cells. In the analysis of SAMD13 co-expression networks, positively related genes of SAMD13 were associated with a high hazard ratio in different types of cancer, including HCC. In biological function of SAMD13, SAMD13 mainly include spliceosome, ribosome biogenesis in eukaryote, ribosome, etc. These results suggest that SAMD13 may serve as a novel prognostic biomarker for HCC diagnosis and provide novel insights into tumor immunology in HCC.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.11-16
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• 2014

Accurate diagnosis and proper monitoring of cancer patients remain important obstacles for successful cancer treatment. The search for cancer biomarkers can aid in more accurate prediction of clinical outcome and may also reveal novel predictive factors and therapeutic targets. One such prognostic marker seems to be FOXA1. Many studies have shown that FOXA1 is strongly expressed in a vast majority of cancers, including breast cancer, in which high expression is associated with a good prognosis. In this review, we summarize the role of this transcription factor in the development and prognosis of breast cancer in the hope of providing insights into utility of FOXA1 as a novel biomarker.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.15
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• pp.6065-6070
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• 2014

Background: Breast cancer is the most common malignancy in women worldwide, including Thailand, and is a major cause of mortality and morbidity, despite advances in diagnosis and treatment. Novel gene expression in breast cancer is a focus in searches for prognostic biomarkers and new therapeutic targets. Materials and Methods: The mRNA expression of novel B4GALT4, SLC35B2, and WDHD1 genes in breast cancer were examined in invasive ductal breast carcinoma (IDC) patients using quantitative real-time reverse transcription polymerase chain reaction (QRT-PCR). Results: Among these genes, increased expression of SLC35B2 mRNA was significantly associated with TNM stage III + IV of IDC (p<0.001). Hence, up-regulation of SLC35B2 may serve as a prognostic biomarker for poor prognosis, and is also a potential therapeutic target in breast cancer.

• Journal of Gastric Cancer
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• v.23 no.3
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• pp.410-427
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• 2023

Recent advances in artificial intelligence (AI) have provided novel tools for rapid and precise pathologic diagnosis. The introduction of digital pathology has enabled the acquisition of scanned slide images that are essential for the application of AI. The application of AI for improved pathologic diagnosis includes the error-free detection of potentially negligible lesions, such as a minute focus of metastatic tumor cells in lymph nodes, the accurate diagnosis of potentially controversial histologic findings, such as very well-differentiated carcinomas mimicking normal epithelial tissues, and the pathological subtyping of the cancers. Additionally, the utilization of AI algorithms enables the precise decision of the score of immunohistochemical markers for targeted therapies, such as human epidermal growth factor receptor 2 and programmed death-ligand 1. Studies have revealed that AI assistance can reduce the discordance of interpretation between pathologists and more accurately predict clinical outcomes. Several approaches have been employed to develop novel biomarkers from histologic images using AI. Moreover, AI-assisted analysis of the cancer microenvironment showed that the distribution of tumor-infiltrating lymphocytes was related to the response to the immune checkpoint inhibitor therapy, emphasizing its value as a biomarker. As numerous studies have demonstrated the significance of AI-assisted interpretation and biomarker development, the AI-based approach will advance diagnostic pathology.