Prediction of Compound Bioactivities Using Heat-Diffusion Equation.

Machine learning is expected to improve low throughput and high assay cost in cell-based phenotypic screening. However, it is still a challenge to apply machine learning to achieving sufficiently complex phenotypic screening due to imbalanced datasets, non-linear prediction, and unpredictability of new chemotypes. Here, we developed a prediction model based on the heat-diffusion equation (PM-HDE) to address this issue. The algorithm was verified as feasible for virtual compound screening using biotest data of 946 assay systems registered with PubChem. PM-HDE was then applied to actual screening. Based on supervised learning of the data of about 50,000 compounds from biological phenotypic screening with motor neurons derived from ALS-patient-induced pluripotent stem cells, virtual screening of >1.6 million compounds was implemented. We confirmed that PM-HDE enriched the hit compounds and identified new chemotypes. This prediction model could overcome the inflexibility in machine learning, and our approach could provide a novel platform for drug discovery.

Brain testosterone deficiency leads to down-regulation of mitochondrial gene expression in rat hippocampus accompanied by a decline in peroxisome proliferator-activated receptor-γ coactivator 1α expression.

Age-related decrease of testosterone levels in blood and brain is believed to be associated with neurodegenerative diseases such as Alzheimer's disease. However, the effect of testosterone on brain function is not well understood. Therefore, we investigated the impact of testosterone deprivation on mitochondrial gene expression in the brain of male gonadectomized (GDX) rats. We found that peripheral castration led to testosterone deficiency in the brain and caused a significant reduction in protein and mRNA expression of genes encoded by mitochondrial DNA, namely NADPH dehydrogenase subunit 1, subunit 4, cytochrome b, and cytochrome c oxidase subunit 1 and subunit 3 in the hippocampus. In addition, gene expression of peroxisome proliferator-activated receptor-γ coactivator 1α (PGC-1α), which is a master regulator of mitochondrial biogenesis, and its downstream transcriptional factors, nuclear respiratory factors 1 and 2 and mitochondrial transcription factors A and B2, were also decreased in the hippocampus of GDX rats. These reductions in the expression of mitochondrial gene and transcriptional coactivators and factors were recovered by androgen replacement. These findings indicate that androgen plays an important role in mitochondrial gene expression in the hippocampus.

[Grouping of observer's visual characteristics on the basis of difference in the criteria of visual detection and selection of the fittest clustering method:verification of observer's group with radiologist-like visual characteristics].

Various clustering methods are used in cluster analyses, with each clustering method demonstrating unique advantages. Therefore, it is important to make the best use of the advantages each method provides. We have recognized that it is necessary in the evaluation of X-ray images to classify observers quantitatively according to visual characteristics (grouping of observers) and have clustered observers using the UPGMA method, which is one of the clustering methods. We found that the observers were clustered into two different groups, one with radiologist-like characteristics and the other with medical physicist-like characteristics. Furthermore, we suggested that the group with radiologist-like characteristics was suitable for QC of X-ray images. However, it is doubtful whether the UPGMA method is most suitable for the grouping of observers. In this work we clustered observers using various clustering methods and examined the most suitable method for the evaluation of X-ray images. The results showed that the ward method was least suitable for the grouping of observers, and they were distinctly grouped into two different categories by using a further method.

Crystallization and preliminary X-ray analysis of two inhibitor complexes of the catalytic domain of death-associated protein kinase.

The catalytic domain of death-associated protein kinase (DAPK) has been overexpressed, purified and crystallized using the sitting-drop vapour-diffusion method with PEG 8000 and magnesium acetate as precipitants. Complexes with the inhibitor staurosporine and its analogue BDB402 were also crystallized in the presence of PEG 400 and PEG 8000, respectively. Diffraction data were collected to 2.4 A for the native catalytic domain, to 2.9 A for the staurosporine complex and to 2.7 A for the BDB402 complex. All three crystals belong to space group P2(1)2(1)2(1), with unit-cell parameters a = 77.992, b = 109.909, c = 50.063 A for the catalytic domain, a = 78.911, b = 113.162, c = 50.658 A for the staurosporine complex and a = 77.337, b = 108.869, c = 50.186 A for the BDB402 complex. In both complexes the inhibitor molecule was clearly assigned in the difference Fourier map calculated on the basis of the phases obtained from the structure of the catalytic domain.

[Classification of observer-groups with cluster analysis and the criteria of visual decision for each group].

It is important that the evaluation of X-ray images include the observer's visual characteristics. However, evaluations of X-ray images that include these characteristics are not performed because of the difficulty of quantitatively elucidating visual characteristics. In this study, we classified observers into groups (clusters) by the same criteria of visual decision, using cluster analysis (unweighted Pair-Group method using arithmetic averages), and evaluated X-ray images on the basis of this separation. Clinical application is also discussed. It was found that observer clustering caused a decrease in between-observer variation. Observers were grouped into two different categories: one with the characteristics of radiologists and the other with the characteristics of medical physicists. Our results indicated that the group with the characteristics of radiologists was suitable for the quality control (QC) of X-ray images.

DAP kinase activity is critical for C(2)-ceramide-induced apoptosis in PC12 cells.

Exposure of PC12 cells to C(2)-ceramide results in dose- dependent apoptosis. Here, we investigate the involvement of death-associated protein (DAP) kinase, initially identified as a positive mediator of the interferon-gamma-induced apoptosis of HeLa cells, in the C(2)-ceramide-induced apoptosis of PC12 cells. DAP kinase is endogenously expressed in these cells. On exposure of PC12 cells to 30 microm C(2)-ceramide, both the total (assayed in the presence of Ca(2+)/calmodulin) and Ca(2+)/calmodulin-independent (assayed in the presence of EGTA) DAP kinase activities were transiently increased 5.0- and 12.2-fold, respectively, at 10 min, and then decreased to 1.7- and 3.4-fold at 90 min. After 10 min exposure to 30 microm C(2)-ceramide, the Ca(2+)/calmodulin independent activity/ total activity ratio increased from 0.22 to 0.60. These effects were dependent on the C(2)-ceramide concentration. C(8)-ceramide, another active ceramide analog, also induced apoptosis and activated DAP kinase, while C(2)-dihydroceramide, an inactive ceramide analog, failed to induce apoptosis and increase DAP kinase activity. Furthermore, transfection studies revealed that overexpression of wild-type DAP kinase enhanced the sensitivity to C(2)- and C(8)-ceramide, while a catalytically inactive DAP kinase mutant and a construct containing the death domain and C-terminal tail of DAP kinase, which act in a dominant-negative manner, rescued cells from C(2)-, and C(8)-ceramide-induced apoptosis. These findings demonstrate that DAP kinase is an important component of the apoptotic machinery involved in ceramide-induced apoptosis, and that the intrinsic DAP kinase activity is critical for ceramide-induced apoptosis.