RESULTS: We show that SYMRK is essential for nodulation and endomycorrhization in Parasponia andersonii. Subsequently, it is revealed that the 5'-intron donor splice site of SYMRK intron 12 is variable and, in most dicotyledon species, doesn't contain the canonical dinucleotide 'GT' signature but the much less common motif 'GC'. Strikingly, in T. orientalis, this motif is converted into a rare non-canonical 5'-intron donor splice site 'GA'. This SYMRK allele, however, is fully functional and spreads in the T. orientalis population of Malaysian Borneo. A further investigation into the occurrence of the non-canonical GA-AG splice sites confirmed that these are extremely rare.
CONCLUSION: SYMRK functioning is highly conserved in legumes, actinorhizal plants, and Parasponia. The gene possesses a non-common 5'-intron GC donor splice site in intron 12, which is converted into a GA in T. orientalis accessions of Malaysian Borneo. The discovery of this functional GA-AG splice site in SYMRK highlights a gap in our understanding of splice donor sites.
METHODS: We introduce a new node representation method based on initial information fusion, called FFANE, which amalgamates PPI networks and protein sequence data to enhance the precision of PPIs' prediction. A Gaussian kernel similarity matrix is initially established by leveraging protein structural resemblances. Concurrently, protein sequence similarities are gauged using the Levenshtein distance, enabling the capture of diverse protein attributes. Subsequently, to construct an initial information matrix, these two feature matrices are merged by employing weighted fusion to achieve an organic amalgamation of structural and sequence details. To gain a more profound understanding of the amalgamated features, a Stacked Autoencoder (SAE) is employed for encoding learning, thereby yielding more representative feature representations. Ultimately, classification models are trained to predict PPIs by using the well-learned fusion feature.
RESULTS: When employing 5-fold cross-validation experiments on SVM, our proposed method achieved average accuracies of 94.28%, 97.69%, and 84.05% in terms of Saccharomyces cerevisiae, Homo sapiens, and Helicobacter pylori datasets, respectively.
CONCLUSION: Experimental findings across various authentic datasets validate the efficacy and superiority of this fusion feature representation approach, underscoring its potential value in bioinformatics.
METHODS: A population-based case-referent study was performed using cases with congenital anomalies (N = 5,131) from EUROCAT Northern Netherlands, a registry of congenital anomalies. The referent population (N = 31,055) was selected from the pregnancy IADB.nl, a pharmacy prescription database.
RESULTS: Ten placental transporters known to have comparable expression levels in the placenta to that of P-gp, were selected in this study. In total, 147 drugs were identified to be substrates, inhibitors or inducers, of these transporters. Fifty-eight of these drugs were used by at least one mother in our cases or referent population, and 28 were used in both. The highest user rate was observed for the substrates of multidrug resistance-associated protein 1, mainly folic acid (6% of cases, 8% of referents), and breast cancer resistance protein, mainly nitrofurantoin (2.3% of cases, 2.9% of referents). In contrast to P-gp, drug interactions involving substrates of these transporters did not have a significant effect on the risk of congenital anomalies.
CONCLUSIONS: Some of the drugs which are substrates or inhibitors of placental transporters were commonly used during pregnancy. No significant effect of transporter inhibition was found on fetal drug exposure, possibly due to a limited number of exposures.