Functional magnetic resonance imaging (fMRI) provides insights into complex patterns of brain functional changes, making it a valuable tool for exploring addiction-related brain connectivity. However, effectively extracting addiction-related brain connectivity from fMRI data remains challenging due to the intricate and non-linear nature of brain connections. Therefore, this paper proposed the Graph Diffusion Reconstruction Network (GDRN), a novel framework designed to capture addiction-related brain connectivity from fMRI data acquired from addicted rats. The proposed GDRN incorporates a diffusion reconstruction module that effectively maintains the unity of data distribution by reconstructing the training samples, thereby enhancing the model's ability to reconstruct nicotine addiction-related brain networks. Experimental evaluations conducted on a nicotine addiction rat dataset demonstrate that the proposed GDRN effectively explores nicotine addiction-related brain connectivity. The findings suggest that the GDRN holds promise for uncovering and understanding the complex neural mechanisms underlying addiction using fMRI data.
Rice fungal pathogens, responsible for severe rice yield loss and biotoxin contamination, cause increasing concerns on environmental safety and public health. In the paddy environment, we observed that the asymptomatic rice phyllosphere microenvironment was dominated by an indigenous fungus, Aspergillus cvjetkovicii, which positively correlated with alleviated incidence of Magnaporthe oryzae, one of the most aggressive plant pathogens. Through the comparative metabolic profiling for the rice phyllosphere microenvironment, two metabolites were assigned as exclusively enriched metabolic markers in the asymptomatic phyllosphere and increased remarkably in a population-dependent manner with A. cvjetkovicii. These two metabolites evidenced to be produced by A. cvjetkovicii in either a phyllosphere microenvironment or artificial media were purified and identified as 2(3H)-benzofuranone and azulene, respectively, by gas chromatography coupled to triple quadrupole mass spectrometry and nuclear magnetic resonance analyses. Combining with bioassay analysis in vivo and in vitro, we found that 2(3H)-benzofuranone and azulene exerted dissimilar actions at the stage of infection-related development of M. oryzae. A. cvjetkovicii produced 2(3H)-benzofuranone at the early stage to suppress MoPer1 gene expression, leading to inhibited mycelial growth, while azulene produced lately was involved in blocking of appressorium formation by downregulation of MgRac1. More profoundly, the microenvironmental interplay dominated by A. cvjetkovicii significantly blocked M. oryzae epidemics in the paddy environment from 54.7 to 68.5% (p < 0.05). Our study first demonstrated implication of the microenvironmental interplay dominated by indigenous and beneficial fungus to ecological balance and safety of the paddy environment.
Epilepsy of infancy with migrating focal seizures (EIMFS) is one of the early-onset epileptic syndromes characterized by migrating polymorphous focal seizures. Whole exome sequencing (WES) in ten sporadic and one familial case of EIMFS revealed compound heterozygous SLC12A5 (encoding the neuronal K(+)-Cl(-) co-transporter KCC2) mutations in two families: c.279 + 1G > C causing skipping of exon 3 in the transcript (p.E50_Q93del) and c.572 C >T (p.A191V) in individuals 1 and 2, and c.967T > C (p.S323P) and c.1243 A > G (p.M415V) in individual 3. Another patient (individual 4) with migrating multifocal seizures and compound heterozygous mutations [c.953G > C (p.W318S) and c.2242_2244del (p.S748del)] was identified by searching WES data from 526 patients and SLC12A5-targeted resequencing data from 141 patients with infantile epilepsy. Gramicidin-perforated patch-clamp analysis demonstrated strongly suppressed Cl(-) extrusion function of E50_Q93del and M415V mutants, with mildly impaired function of A191V and S323P mutants. Cell surface expression levels of these KCC2 mutants were similar to wildtype KCC2. Heterologous expression of two KCC2 mutants, mimicking the patient status, produced a significantly greater intracellular Cl(-) level than with wildtype KCC2, but less than without KCC2. These data clearly demonstrated that partially disrupted neuronal Cl(-) extrusion, mediated by two types of differentially impaired KCC2 mutant in an individual, causes EIMFS.
Many algorithms to detect copy number variations (CNVs) using exome sequencing (ES) data have been reported and evaluated on their sensitivity and specificity, reproducibility, and precision. However, operational optimization of such algorithms for a better performance has not been fully addressed. ES of 1199 samples including 763 patients with different disease profiles was performed. ES data were analyzed to detect CNVs by both the eXome Hidden Markov Model (XHMM) and modified Nord's method. To efficiently detect rare CNVs, we aimed to decrease sequencing biases by analyzing, at the same time, the data of all unrelated samples sequenced in the same flow cell as a batch, and to eliminate sex effects of X-linked CNVs by analyzing female and male sequences separately. We also applied several filtering steps for more efficient CNV selection. The average number of CNVs detected in one sample was <5. This optimization together with targeted CNV analysis by Nord's method identified pathogenic/likely pathogenic CNVs in 34 patients (4.5%, 34/763). In particular, among 142 patients with epilepsy, the current protocol detected clinically relevant CNVs in 19 (13.4%) patients, whereas the previous protocol identified them in only 14 (9.9%) patients. Thus, this batch-based XHMM analysis efficiently selected rare pathogenic CNVs in genetic diseases.