Increased Expression of Apolipoprotein D Following Experimental Traumatic Brain Injury

Increasing evidence suggests that apolipoprotein D (apoD) could play a major role in mediating neuronal degeneration and regeneration in the CNS and the PNS. To investigate further the temporal pattern of apoD expression after experimental traumatic brain injury in the rat, male Sprague-Dawley rats were subjected to unilateral cortical impact injury. The animals were killed and examined for apoD mRNA and protein expression and for immunohistological analysis at intervals from 15 min to 14 days after injury. Increased apoD mRNA and protein levels were seen in the cortex and hippocampus ipsilateral to the injury site from 48 h to 14 days after the trauma. Immunohistological investigation demonstrated a differential pattern of apoD expression in the cortex and hippocampus, respectively: Increased apoD immunoreactivity in glial cells was detected from 2 to 3 days after the injury in cortex and hippocampus. In contrast, increased expression of apoD was seen in cortical and hippocampal neurons at later time points following impact injury. Concurrent histopathological examination using hematoxylin and eosin demonstrated dark, shrunken neurons in the cortex ipsilateral to the injury site. In contrast, no evidence of cell death was observed in the hippocampus ipsilateral to the injury site up to 14 days after the trauma. No evidence of increased apoD mRNA or protein expression or neuronal pathology by hematoxylin and eosin staining was detected in the contralateral cortex and hippocampus. Our results reveal induction of apoD expression in the cortex and hippocampus following traumatic brain injury in the rat. Our data also suggest that increased apoD expression may play an important role in cortical neuronal degeneration after brain injury in vivo. However, increased expression of apoD in the hippocampus may not necessarily be indicative of neuronal death.     

Akt Activation Emulates Chk1 Inhibition and Bcl2 Overexpression and Abrogates G2 Cell Cycle Checkpoint by Inhibiting BRCA1 Foci

Akt is perhaps the most frequently activated oncoprotein in human cancers. Overriding cell cycle checkpoint in combination with the inhibition of apoptosis are two principal requirements for predisposition to cancer. Here we show that the activation of Akt is sufficient to promote these two principal processes, by inhibiting Chk1 activation with concomitant inhibition of apoptosis. These activities of Akt cannot be recapitulated by the knockdown of Chk1 alone or by overexpression of Bcl2. Rather the combination of Chk1 knockdown and Bcl2 overexpression is required to recapitulate Akt activities. Akt was shown to directly phosphorylate Chk1. However, we found that Chk1 mutants in the Akt phosphorylation sites behave like wild-type Chk1 in mediating G2 arrest, suggesting that the phosphorylation of Chk1 by Akt is either dispensable for Chk1 activity or insufficient by itself to exert an effect on Chk1 activity. Here we report a new mechanism by which Akt affects G2 cell cycle arrest. We show that Akt inhibits BRCA1 function that induces G2 cell cycle arrest. Akt prevents the translocation of BRCA1 to DNA damage foci and, thereby, inhibiting the activation of Chk1 following DNA damage.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Profiling SARS-CoV-2 HLA-I peptidome reveals T cell epitopes from out-of-frame ORFs

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A Toxoplasma type 2C serine-threonine phosphatase is involved in parasite growth in the mammalian host cell

Toxoplasma gondii is a human protozoan parasite that belongs to the phylum of Apicomplexa and causes toxoplasmosis. As the other members of this phylum, T. gondii obligatory multiplies within a host cell by a peculiar type of mitosis that leads to daughter cell assembly within a mother cell. Although parasite growth and virulence have been linked for years, few molecules controlling mitosis have been yet identified and they include a couple of kinases but not the counteracting phosphatases. Here, we report that in contrast to other animal cells, type 2C is by far the major type of serine threonine phosphatase activity both in extracellular and in intracellular dividing parasites. Using wild type and transgenic parasites, we characterized the 37 kDa TgPP2C molecule as an abundant cytoplasmic and nuclear enzyme with activity being under tight regulation. In addition, we showed that the increase in TgPP2C activity significantly affected parasite growth by impairing cytokinesis while nuclear division still occurred. This study supports for the first time that type 2C protein phosphatase is an important regulator of cell growth in T. gondii.     

Flood Risk Analysis Based on Information Diffusion Theory

Due to the fact that the flood data series of small drainage basins is relatively short, available data are often not sufficient for flood risk analysis. This presents the problem of risk analysis using very small data samples. One method that can be applied is to regard the available small samples as fuzzy information and optimize them using information diffusion technology to yield analytical results with greater reliability. In this article a risk analysis method based on information diffusion theory is applied to create a new flood risk analysis model. Application of the model is illustrated taking the Jinhuajiang and Qujiang drainage basins as examples. This is a new attempt at applying information diffusion theory in flood risk analysis. Computations based on this analytical flood risk model can yield an estimated flood damage value that is relatively accurate. This study indicates that the aforementioned model exhibits fairly stable analytical results, even when using a small set of sample data. The results also indicate that information diffusion technology is highly capable of extracting useful information and therefore improves system recognition accuracy. This method can be easily applied and the analytical results produced are easy to understand. Results are accurate enough to act as a guide in disaster situations.     

The Schizosaccharomyces pombe cdc6 gene encodes the catalytic subunit of DNA polymerase δ

The cdc6 mutants of Schizosaccharomyces pombe have been classified as being defective in progression through the G2 phase of the cell cycle. We cloned an S. pombe gene that could complement the temperature-sensitive growth of the cdc6-23 mutant. Unexpectedly, the cloned gene was allelic to pol3, which encodes the catalytic subunit of DNA polymerase δ. Integration mapping confirmed that cdc6 and pol3 are identical. The cdc6-23 mutant carries one amino acid substitution in the conserved N3 region of Pol3. Received: 17 October 1996 / Accepted: 19 November 1996