Combined Methylation of SHOX2 and RASSF1A Genes in Diagnosing Malignant Pleural Effusion.

BACKGROUND: It is a significant challenge to identify pleural effusion (PE) through differential diagnosis in clinical settings. The present study endeavors to devise a strategy to differentiate between malignant pleural effusion (MPE) and benign pleural effusion (BPE) by detecting gene methylation. METHODS: This study recruited 214 patients with PE, among which 104 patients were identified with MPE, while the remaining 110 patients were categorized as having BPE. The methylation levels of short stature homeobox 2 (SHOX2) and RAS association domain family 1, isoform A (RASSF1A) genes were analyzed through methylation-specific polymerase chain reaction (MS-PCR). RESULTS: The methylation status of either SHOX2 or RASSF1A genes was significantly elevated in MPE compared to BPE. The sensitivity and specificity of SHOX2 and RASSF1A methylation in diagnosing PE were 66.3% and 90.9%, respectively. The sensitivity of the combined methylation detection intended to diagnose pulmonary MPE was 73.5% and 52.8% in non-pulmonary MPE (p < 0.05), suggesting that combined detection of SHOX2 and RASSF1A methylation had high diagnostic value for lung cancer. In comparison to the results of cytology and DNA ploidy detection, methylation detection demonstrated a superior diagnostic efficiency in the diagnosis of lung cancer (p < 0.05). Additionally, the combined detection of SHOX2 and RASSF1A methylation was more potent in diagnosing BPE and MPE (p < 0.05), while compensating for the limitations of cytology and DNA ploidy detection. CONCLUSIONS: The detection of SHOX2 and RASSF1A methylation can effectively differentiate between BPE and MPE, especially in diagnosing pulmonary MPE.

Light responsive Fe-Tcpp@ICG for hydrogen peroxide detection and inhibition of tumor cell growth.

In this work, we synthesized Fe-Tcpp@ICG(ICG, Indocyanine green) with light stimuli-response through 5,10,15,20-tetrakis (4-carboxyphenyl) porphyrin (Fe-Tcpp) loaded ICG by electrostatic adsorption. The morphology and properties of Fe-Tcpp and Fe-Tcpp@ICG were characterised by ultraviolet-visible absorption spectrometer, X-ray diffraction, thermogravimetric analyzer and transmission electron microscope, respectively. A non-enzymatic photoelectrochemical sensor based on Fe-Tcpp@ICG was constructed to quantitatively detect hydrogen peroxide in tumor microenvironment. Under the optimal conditions, the linear range of detecting hydrogen peroxide was 0.01-50 mmol/L with detection limit of 0.2 µmol/L (S/N = 3). This sensor proposed a simple, fast, sensitive and label-free method for the detection of hydrogen peroxide. Moreover, the results also showed that the Fe-Tcpp@ICG can catalyze the decomposition of hydrogen peroxide to generate singlet oxygen, which can kill tumor cells. These indicated that this material was expected to be used for detecting hydrogen peroxide and inhibition of tumor cell growth.

Distinguishing structural features between Crohn's disease and gastrointestinal luminal tuberculosis using Mueller matrix derived parameters.

Recently, the incidence of inflammatory bowel diseases, especially the Crohn's disease (CD) and gastrointestinal luminal tuberculosis (ITB), has grown rapidly worldwide. Currently there is no general gold standard to distinguish between CD and ITB tissues, which both have tuberculosis and surrounding fibrous structures. Mueller matrix imaging technique is suitable for describing the location, density and distribution behavior of such fibrous structures. In this study, we apply the Mueller matrix microscopic imaging to the CD and ITB tissue samples. The 2D Mueller matrix images of the CD and ITB tissue slices are measured using the Mueller matrix microscope developed in our previous study, then the Mueller matrix polar decomposition and Mueller matrix transformation parameters are calculated. To evaluate the distribution features of the fibrous structures surrounding the tuberculosis areas more quantitatively and precisely, we analyze the retardance related Mueller matrix derived parameters, which show clear different distribution behaviors between the CD and ITB tissues, using the Tamura image processing method. It is demonstrated that the Mueller matrix derived parameters can reveal the structural features of tuberculosis areas and be used as quantitative indicators to distinguish between CD and ITB tissues, which may be useful for the clinical diagnosis.