Integrating plasma exosomal miRNAs, ultrasound radiomics and tPSA for the diagnosis and prediction of early prostate cancer: a multi-center study.

INTRODUCTION: This multi-center study aims to explore the roles of plasma exosomal microRNAs (miRNAs), ultrasound (US) radiomics, and total prostate-specific antigen (tPSA) levels in early prostate cancer detection. METHODS: We analyzed the publicly available dataset GSE112264 to identify the differentially expressed miRNAs associated with prostate cancer. Then, PyRadiomics was used to extract image features, and least absolute shrinkage and selection operator (LASSO) was used to screen the data. Subsequently, according to strict inclusion and exclusion criteria, the internal dataset (n = 199) was used to construct a diagnostic model, and the receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA), and DeLong test were used to evaluate its diagnostic performance. Finally, we used an external dataset (n = 158) for further validation. RESULTS: The number of features extracted by PyRadiomics was 851, and the number of features screened by LASSO was 23. We combined the hsa-miR-320c, hsa-miR-944, radiomics, and tPSA features to construct a joint model. The area under the ROC curve of the combined model was 0.935. In the internal validation, the area under the curve (AUC) of the training set was 0.943, and the AUC of the test set was 0.946. The AUC of the external data set was 0.910. The calibration curve and decision curve were consistent with the performance of the combined model. There was a significant difference in the prediction ability between the combined prediction model and the single index prediction model, indicating the high credibility and accuracy of the combined model in predicting PCa. CONCLUSIONS: The combined prediction model, consisting of plasma exosomal miRNAs (hsa-miR-320c and hsa-miR-944), US radiomics, and clinical tPSA, can be utilized for the early diagnosis of prostate cancer.

ΔNp63α promotes cigarette smoke-induced renal cancer stem cell activity via the Sonic Hedgehog pathway.

Cigarette smoke (CS) has been generally recognized as a chief carcinogenic factor in renal cell carcinoma (RCC). The stimulative effect of CS on renal cancer stem cells (RCSCs) has been described previously. The Sonic Hedgehog (SHH) pathway plays an essential role in self-renewal, cell growth, drug resistance, metastasis, and recurrence of cancer stem cells (CSCs). Renal cancer-related gene ΔNp63α is highly expressed in renal epithelial tissues and contributes to the RCSCs characteristics of tumors. The aim of this study was to elucidate the role of ΔNp63α and the SHH pathway on the activity of RCSCs induced by CS through a series of in vivo and in vitro studies. It was shown that in renal cancer tissues, ΔNp63α and RCSCs markers in smokers are expressed higher than that in non-smokers. RCSCs were effectively enriched by tumor sphere formation assay. Besides, CS increased the expression of RCSCs markers and the capability of sphere-forming in vitro and in vivo. Moreover, the SHH pathway was activated, and the specialized inhibitor alleviated the promotion of CS on RCSCs. ΔNp63α activated the SHH pathway and promoted CS-induced enhancement of RCSCs activity. These findings indicate that ΔNp63α positively regulates the activity of CS-induced RCSCs via the SHH pathway.

Magnetoencefalografía: mapeo de la dinámica espaciotemporal de la actividad neuronal / Magnetoencephalography: mapping the spatiotemporal dynamics of neuronal activity

La magnetoencefalografía es una técnica de neuroimagen no invasiva que mide, con gran exactitud temporal, los campos magnéticos en la superficie de la cabeza producidos por corrientes neuronales en regiones cerebrales. Esta técnica es sumamente útil en la investigación básica y clínica, porque además permite ubicar el origen de la actividad neural en el cerebro. En esta revisión se abordan aspectos básicos de la biofísica del método y se discuten los hallazgos sobre procesos como la percepción del habla, la atención auditiva y la integración de la información visual y auditiva, que son importantes en la investigación. Igualmente, se ilustran sus ventajas, sus limitaciones y las nuevas tendencias en la investigación con magnetoencefalografía.

Magnetoencephalography is a noninvasive imaging technique that measures the magnetic fields on the surface of the head --produced by neuronal currents in brain regions -- and provides highly accurate temporal information. Magnetoencephalography is extremely useful in basic and clinical research as it can also locate the sources of neural activity in the brain. This review chiefly approaches biophysics-related aspects of the method; findings are also discussed on issues such as speech perception, auditory attention and integration of visual-auditory information, which are quintessential in this type of research. Lastly, this review discusses the benefits and limitations of magnetoencephalography and outlines new trends in research with this technique.