Requirement of dendritic Akt degradation by the ubiquitin–proteasome system for neuronal polarity

Asymmetric distributions of activities of the protein kinases Akt and glycogen synthase kinase 3β (GSK-3β) are critical for the formation of neuronal polarity. However, the mechanisms underlying polarized regulation of this pathway remain unclear. In this study, we report that the instability of Akt regulated by the ubiquitin–proteasome system (UPS) is required for neuron polarity. Preferential distribution in the axons was observed for Akt but not for its target GSK-3β. A photoactivatable GFP fused to Akt revealed the preferential instability of Akt in dendrites. Akt but not p110 or GSK-3β was ubiquitinated. Suppressing the UPS led to the symmetric distribution of Akt and the formation of multiple axons. These results indicate that local protein degradation mediated by the UPS is important in determining neuronal polarity

Interleukin-1-induced Ether-linked Diglycerides Inhibit Calcium-insensitive Protein Kinase C Isotypes IMPLICATIONS FOR GROWTH SENESCENCE

It is hypothesized that inflammatory cytokines and vasoactive peptides stimulate distinct species of diglycerides that differentially regulate protein kinase C isotypes. In published data, we demonstrated that interleukin-1, in contrast to endothelin, selectively generates ether-linked diglyceride species (alkyl, acyl- and alkenyl, acylglycerols) in rat mesangial cells, a smooth muscle-like pericyte in the glomerulus. We now demonstrate both in intact cell and in cell-free preparations that these interleukin-1 receptor-generated ether-linked diglycerides inhibit immunoprecipitated protein kinase C delta and epsilon but not zeta activity. Neither interleukin-1 nor endothelin affect de novo protein expression of these protein kinase C isotypes. As down-regulation of calcium-insensitive protein kinase C isotypes has been linked to antimitogenic activity, we investigated growth arrest as a functional correlate for IL-1-generated ether-linked diglycerides. Cell-permeable ether-linked diglycerides mimic the effects of interleukin-1 to induce a growth-arrested state in both G-protein-linked receptor- and tyrosine kinase receptor-stimulated mesangial cells. This signaling mechanism implicates cytokine receptor-induced ether-linked diglycerides as second messengers that inhibit the bioactivity of calcium-insensitive protein kinase C isotypes resulting in growth arrest

SBSM-Pro: Support Bio-sequence Machine for Proteins

Proteins play a pivotal role in biological systems. The use of machine learning algorithms for protein classification can assist and even guide biological experiments, offering crucial insights for biotechnological applications. We propose a support bio-sequence machine for proteins, a model specifically designed for biological sequence classification. This model starts with raw sequences and groups amino acids based on their physicochemical properties. It incorporates sequence alignment to measure the similarities between proteins and uses a novel MKL approach to integrate various types of information, utilizing support vector machines for classification prediction. The results indicate that our model demonstrates commendable performance across 10 datasets in terms of the identification of protein function and posttranslational modification. This research not only showcases state-of-the-art work in protein classification but also paves the way for new directions in this domain, representing a beneficial endeavour in the development of platforms tailored for biological sequence classification. SBSM-Pro is available for access at http://lab.malab.cn/soft/SBSM-Pro/.Comment: 38 pages, 9 figure

Lie algebras with differential operators of any weights

In this paper, we define a cohomology theory for differential Lie algebras of any weight. As applications of the cohomology, we study abelian extensions and formal deformations of differential Lie algebras of any weight. Finally, we consider homotopy differential operators on $\mathrm{L}_{\infty}$ algebras and 2-differential operators of any weight on Lie 2-algebras, and we prove that the category of 2-term $\mathrm{L}_{\infty}$ algebras with homotopy differential operators of any weight is same as the category of Lie 2-algebras with 2-differential operators of any weight

BINN: A deep learning approach for computational mechanics problems based on boundary integral equations

We proposed the boundary-integral type neural networks (BINN) for the boundary value problems in computational mechanics. The boundary integral equations are employed to transfer all the unknowns to the boundary, then the unknowns are approximated using neural networks and solved through a training process. The loss function is chosen as the residuals of the boundary integral equations. Regularization techniques are adopted to efficiently evaluate the weakly singular and Cauchy principle integrals in boundary integral equations. Potential problems and elastostatic problems are mainly concerned in this article as a demonstration. The proposed method has several outstanding advantages: First, the dimensions of the original problem are reduced by one, thus the freedoms are greatly reduced. Second, the proposed method does not require any extra treatment to introduce the boundary conditions, since they are naturally considered through the boundary integral equations. Therefore, the method is suitable for complex geometries. Third, BINN is suitable for problems on the infinite or semi-infinite domains. Moreover, BINN can easily handle heterogeneous problems with a single neural network without domain decomposition