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Background: There is no diagnostic assessment procedure with moderate or strong evidence of use, and evidence for current means of treating prolonged disorders of consciousness (pDOC) is sparse. This may be related to the fact that the mechanisms of pDOC have not been studied deeply enough and are not clear enough. Therefore, the aim of this study was to explore the mechanism of pDOC using functional near‐infrared spectroscopy (fNIRS) to provide a basis for the treatment of pDOC, as well as to explore preclinical markers for determining the arousal of pDOC patients. Methods: Five minutes resting‐state data were collected from 10 pDOC patients and 13healthy adults using fNIRS. Based on the concentrations of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the time series, the resting‐state cortical brain functional connectivity strengths of the two groups were calculated, and the functional connectivity strengths of homologous and heterologous brain networks were compared at the sensorimotor network (SEN), dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN), frontoparietal network (FPN), and visual network (VIS) levels. Univariate binary logistic regression analyses were performed on brain networks with statistically significant differences to identify brain networks associated with arousal in pDOC patients. The receiver operating characteristic (ROC) curves were further analyzed to determine the cut‐off value of the relevant brain networks to provide clinical biomarkers for the prediction of arousal in pDOC patients. Results: The results showed that the functional connectivity strengths of oxyhemoglobin (HbO)‐based SEN∼SEN, VIS∼VIS, DAN∼DAN, DMN∼DMN, SEN∼VIS, SEN∼FPN, SEN∼DAN, SEN∼DMN, VIS∼FPN, VIS∼DAN, VIS∼DMN, HbR‐based SEN∼SEN, and SEN∼DAN were significantly reduced in the pDOC group and were factors that could reflect the participants' state of consciousness. The cut‐off value of resting‐state functional connectivity strength calculated by ROC curve analysis can be used as a potential preclinical marker for predicting the arousal state of subjects. Conclusion: Resting‐state functional connectivity strength of cortical networks is significantly reduced in pDOC patients. The cut‐off values of resting‐state functional connectivity strength are potential preclinical markers for predicting arousal in pDOC patients. [ABSTRACT FROM AUTHOR]

Long non‐coding RNAs (lncRNA) have an extensive role in the progression and chemoresistance of gastric cancer (GC). Deeply study the regulatory role of lncRNAs could provide potential therapeutic targets. The aim of this study is to explore the regulatory role of HOTAIR in the progression and oxaliplatin resistance of GC. The expression of HOTAIR in GC and cell lines were detected by using qRT‐PCR. Cell proliferation and apoptosis were analysed by CCK‐8, EdU incorporation and flow cytometry. Luciferase reporter assay was used to identify the interaction between HOTAIR and ABCG2 (ATP‐binding cassette (ABC) superfamily G member 2, ABCG2) via miR‐195‐5p. The regulatory functions were verified by using molecular biology experiments. HOTAIR was significantly overexpressed in GC and associated with poor prognosis. Knock‐down of HOTAIR inhibited the GC cells proliferation and oxaliplatin resistance, while overexpression of HOTAIR showed opposite functions. Further studies found that HOTAIR acted as a competing endogenous RNA (ceRNA) to absorb miR‐195‐5p and elevated the expression of ABCG2, which leads to resistance of GC cells to oxaliplatin. Taken together, our findings demonstrated that HOTAIR regulates ABCG2 induced resistance of GC to oxaliplatin through miR‐195‐5p signalling and illustrate the great potential of developing new therapeutic targets for GC patients. [ABSTRACT FROM AUTHOR]