A speculative model of affective illness cyclicity based on patterns of drug tolerance observed in amygdala-kindled seizures

In this article, we discuss molecular mechanisms involved in the evolution of amygdala kindling and the episodic loss of response to pharmacological treatments during tolerance development. These phenomena allow us to consider how similar principles (in different neurochemical systems) could account for illness progression, cyclicity, and drug tolerance in affective disorders. We describe the phenomenon of amygdala-kindled seizures episodically breaking through effective daily pharmacotherapy with carbamazepine and valproate, suggesting that these observations could reflect the balance of pathological vs compensatory illness-induced changes in gene expression. Under certain circumstances, amygdala-kindled animals that were initially drug responsive can develop highly individualized patterns of seizure breakthroughs progressing toward a complete loss of drug efficacy. This initial drug efficacy may reflect the combination of drug-related exogenous neurochemical mechanisms and illness-induced endogenous compensatory mechanisms. However, we postulate that when seizures are inhibited, the endogenous illness-induced adaptations dissipate (the “time-off seizure” effect), leading to the re-emergence of seizures, a re-induction of a new, but diminished, set of endogenous compensatory mechanisms, and a temporary period of renewed drug efficacy. As this pattern repeats, an intermittent or cyclic response to the anticonvulsant treatment emerges, leading toward complete drug tolerance. We also postulate that the cyclic pattern accelerates over time because of both the failure of robust illness-induced endogenous adaptations to emerge and the progression in pathophysiological mechanisms (mediated by long-lasting changes in gene expression and their downstream consequences) as a result of repeated occurrences of seizures. In this seizure model, this pattern can be inhibited and drug responsivity can be temporarily reinstated by several manipulations, including lowering illness drive (decreasing the stimulation current.), increasing drug dosage, switching to a new drug that does not show crosstolerance to the original medication, or temporarily discontinuing treatment, allowing the illness to re-emerge in an unmedicated animal. Each of these variables is discussed in relation to the potential relevance to the emergence, progression, and suppression of individual patterns of episodic cyclicity in the recurrent affective disorders. A variety of clinical studies are outlined that specifically test the hypotheses derived from this formulation. Data from animal studies suggest that illness cyclicity can develop from the relative ratio between primary pathological processes and secondary endogenous adaptations (assisted by exogenous medications). If this proposition is verified, it further suggests that illness cyclicity is inherent to the neurobiological processes of episode emergence and amelioration, and one does not need to postulate a separate defect in the biological clock. The formulation predicts that early and aggressive long-term interventions may be optimal in order to prevent illness emergence and progression and its associated accumulating neurobiological, vulnerability factors.     

Cloning, sequencing and mutational analysis of the cytochrome c552 gene (cycB) from Bradyrhizobium japonicum strain 110

We report the cloning and nucleotide sequence analysis of the cytochrome c552 gene (cycB) of Bradyrhizobium japonicum strain 110. The gene was identified with help of an oligonucleotide that was designed on the basis of the amino acid sequence determined for purified cytochrome c552 of B. japonicum strain CC705. The cycB gene product has an N-terminal 23-amino acid signal peptide that is missing in the mature cytochrome c552 protein. A B. japonicum cycB insertion mutant was constructed which had no observable phenotypic defects in denitrification and symbiotic nitrogen fixation. Thus, the function of c552 remains unknown.     

Identification of a 13-kDa protein associated with the polyhydroxyalkanoic acid granules from Acinetobacter spp.

Abstract Transferrin-binding proteins from Neisseria meningitidis vary among different isolates. We have identified and studied a hypervariable region adjacent to the carboxyl-end of the transferrin-binding domain of the Tbp2 molecule. The tbp2 genes from six strains of N. meningitidis were cloned and sequenced in this particular region. Sequence analysis of these regions along with five other sequences available from pathogenic Neisseria showed a common organisation of seven highly variable nucleotide stretches interspersed with six conserved nucleotide stretches. The variable regions correlated with the location of immunoreactive epitopes in polyclonal antisera raised to transferrin-binding proteins identified by peptide pin technology. Sequence analysis suggested a mosaic-like organisation of the tbp2 genes. Taken together, these data suggest that the antigenic variation in this part of the protein may result from a strong host immune pressure.     

Screening of significant biomarkers related with prognosis of liver cancer by lncRNA-associated ceRNAs analysis

This study aimed to identify significant biomarkers related to the prognosis of liver cancer using long noncoding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) analysis. Differentially expressed mRNA and lncRNAs between liver cancer and paracancerous tissues were screened, and the functions of these mRNAs were predicted by gene ontology and pathway enrichment analyses. A ceRNA network consisting of differentially expressed mRNAs and lncRNAs was constructed. LncRNA FENDRR and lncRNA HAND2-AS1 were hub nodes in the ceRNA network. A risk score assessment model consisting of eight genes (PDE2A, ESR1, FBLN5, ALDH8A1, AKR1D1, EHHADH, ADRA1A, and GNE) associated with prognosis were developed. Multivariate Cox regression suggested that both pathologic_T and risk group could be regarded as independent prognostic factors. Furthermore, a nomogram model consisting of pathologic_T and risk group showed a good prediction ability for predicting the survival rate of liver cancer patients. The nomogram model consisting of pathologic_T and a risk score assessment model could be regarded as an independent factor for predicting prognosis of liver cancer.