RESUMO
Background: In clinic, the subjectivity of diagnosing insomnia disorder (ID) often leads to misdiagnosis or missed diagnosis, as ID may have the same symptoms as those of other health problems. Methods: A novel deep network, the multimodal transformer graph convolution attention isomorphism network (MTGCAIN) is proposed in this study. In this network, graph convolution attention (GCA) is first employed to extract the graph features of brain connectivity and achieve good spatial interpretability. Second, the MTGCAIN comprehensively utilizes multiple brain network atlases and a multimodal transformer (MT) to facilitate coded information exchange between the atlases. In this way, MTGCAIN can be used to more effectively identify biomarkers and arrive at accurate diagnoses. Results: The experimental results demonstrated that more accurate and objective diagnosis of ID can be achieved using the MTGCAIN. According to fivefold cross-validation, the accuracy reached 81.29% and the area under the receiver operating characteristic curve (AUC) reached 0.8760. A total of nine brain regions were detected as abnormal, namely right supplementary motor area (SMA.R), right temporal pole: superior temporal gyrus (TPOsup.R), left temporal pole: superior temporal gyrus (TPOsup.L), right superior frontal gyrus, dorsolateral (SFGdor.R), right middle temporal gyrus (MTG.R), left middle temporal gyrus (MTG.L), right inferior temporal gyrus (ITG.R), right median cingulate and paracingulate gyri (DCG.R), left median cingulate and paracingulate gyri (DCG.L). Conclusions: The brain regions in the default mode network (DMN) of patients with ID show significant impairment (occupies four-ninths). In addition, the functional connectivity (FC) between the right middle occipital gyrus and inferior temporal gyrus (ITG) has an obvious correlation with comorbid anxiety (P=0.008) and depression (P=0.005) among patients with ID.
RESUMO
Baculovirus infection induces apoptosis in host cells, and apoptosis significantly affects virus production. Autographa californica multiple nucleopolyhedrovirus (AcMNPV) can regulate apoptosis, but the regulatory mechanism is unclear. Here, we found that AcMNPV infection induced different apoptosis responses in different Spodoptera exigua cell lines. In the early stages of viral infection (1-6 h), Se-1 cells underwent severe apoptosis, while Se-3 cells underwent very slight apoptosis. In the late stages of viral infection (12-72 h), Se-1 cells continued to undergo apoptosis and formed a large number of apoptotic bodies, while the apoptosis of Se-3 cells was inhibited and no apoptotic bodies were formed. To determine the reasons for the apoptosis differences in the two cell lines, we measured the expression of the six S. exigua cysteine-dependent aspartate specific protease genes (SeCaspase-1 to -6) and the three AcMNPV antiapoptotic protein genes (iap1, iap2 and p35) during viral infection. We found that SeCaspase-1 to -6 were all activated in Se-1 cells and inhibited in Se-3 cells, whereas iap1, iap2 and p35 were all inhibited in Se-1 cells and normally expressed in Se-3 cells. And p35 was expressed earlier than iap1 and iap2 in Se-3 cells. Otherwise, Se-1 and Se-3 cells would all be apoptotic when infected with the recombinant p35 knockout AcMNPV, whereas only Se-1 cells were apoptotic, but Se-3 cells were not apoptotic when infected with the recombinant p35 repair AcMNPV. Combined with the fact that the expression of P35 protein is inhibited in Se-1 cells but normally expressed in Se-3 cells during the infection of recombinant p35 repair AcMNPV, we proposed that the different expression of P35 is an important reason for the apoptosis differences between the two cell lines. We also found that some genes associated with apoptosis can probably regulate the expression of P35. However, the major upstream regulators of P35 and their mechanisms are still unclear and will be studied in the future.