BACKGROUND: Spatial disorientation (SD) is a problem that pilots often encounter during a flight. One reason for this problem is that among the three types of SD, there is no validated method to detect the Type I (unrecognized) SD. OBJECTIVE: In this pursuit, initially we reviewed the problems and the evaluation methods of associated with SD. Subsequently, we discussed the advantages and disadvantages of the subjective questionnaire evaluation method and the behavior evaluation method. METHODS: On the basis of these analyses, we proposed a method to detect the unrecognized SD that improved the assessment of SD to a significant extent. We developed a new direction to study the unrecognized SD based on the subjective report and the center of pressure (CoP). RESULTS: The proposed evaluation method can assist the pilots to understand the feelings and physical changes, when exposed to unrecognized SD. CONCLUSION: We hope that this evaluation method can provide a strong support in developing a countermeasure against the unrecognized SD and fundamentally solve the severe flight accidents arising due to them.
Spatial disorientation (SD) is the pilot's wrong judgment of flight altitude, position, and motion in three-dimensional space during flight. SD is among the significant causes of flight accidents that seriously affect flight safety. Unrecognized SD causes most of these accidents. In this study, we analyzed the mechanism of unrecognized SD based on the brain's perceptual process. According to the process of sensation and perception, we put forth a new hypothesis of a classification method for unrecognized SD: unrecognized SD might be subdivided into insensate SD, unperceived SD, and perceived SD. There might be some meaningful differences in brain activity in EEG signals or fMRI between unperceived SD and perceived SD. The classification method in this study was proposed based on some related research reports and provided new ideas and methods for scholars to study unrecognized SD. If the hypothesis can be proved, it will provide a basis for scholars learning the mechanism of unrecognized SD and subsequently putting forward countermeasures in SD training. Moreover, as a consequence, the subdivision will contribute to pilot selection, and some specialized SD training for countermeasures could be put forward to reduce aircraft accidents.
Background/Aims: The biological heterogeneity of hepatocellular carcinoma (HCC) makes prognosis difficult. Although many molecular tools have been developed to assist in stratification and prediction of patients by using microarray analysis, the classification and prediction are still improvable because the high-through microarray contains a large amount of information. Meanwhile, gene expression patterns and their prognostic value for HCC have not been systematically investigated. In order to explore new molecular diagnostic and prognostic biomarkers, the gene expression profiles between HCCs and adjacent nontumor tissues were systematically analyzed in the present study. Materials and Methods: In this study, gene expression profiles were obtained by repurposing five Gene Expression Omnibus databases. Differentially expressed genes were identified by using robust rank aggregation method. Three datasets (GSE14520, GSE36376, and GSE54236) were used to validate the associations between cytochrome P450 (CYP) family genes and HCC. GSE14520 was used as the training set. GSE36376 and GSE54236 were considered as the testing sets. Results: From the training set, a four-CYP gene signature was constructed to discriminate between HCC and nontumor tissues with an area under curve (AUC) of 0.991. Accuracy of this four-gene signature was validated in two testing sets (AUCs for them were 0.973 and 0.852, respectively). Moreover, this gene signature had a good performance to make a distinction between fast-growing HCC and slow-growing HCC (AUC = 0.898), especially for its high sensitivity of 95%. At last, CYP2C8 was identified as an independent risk factor of recurrence-free survival (hazard ratio [HR] =0.865, 95% confidence interval [CI], 0.754–0.992, P = 0.038) and overall survival (HR = 0.849; 95% CI, 0.716–0.995, P = 0.033). Conclusions: In summary, our results confirmed for the first time that a four-CYP gene ( CYP1A2 , CYP2E1 , CYP2A7 , and PTGIS ) signature is associated with fast-growing HCC, and CYP2C8 is associated with patient survival. Our findings could help to identify HCC patients at high risk of rapid growth and recurrence.
In this study, we obtained sequence and population genetic data for three X-linked short tandem repeat markers (X-STRs; DXS7129, DXS2500, G10583). We investigated their population genetics and estimated their forensic parameters in 214 healthy unrelated individuals from the Han population of Northern China (105 males and 109 females). We showed that DXS2500 and G10583 were highly polymorphic and thus have potential for application in forensic medicine. We also estimated the overall linkage disequilibrium between pairs of loci, specific multiallelic or interallelic associations, and haplotype frequencies in males. We showed that the three X-STR loci segregate as stable haplotype blocks; this could be a powerful tool for haplotype analysis in kinship testing.
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