New Human Papilloma Virus E2 Transcription Factor Mimics: A Tripyrrole-Peptide Conjugate with Tight and Specific DNA-Recognition

BACKGROUND: Human papillomavirus (HPV) is the main causative agent of cervical cancer, particularly high risk strains such us HPV-16, -18 and -31. The viral encoded E2 protein acts as a transcriptional modulator and exerts a key role in viral DNA replication. Thus, E2 constitutes an attractive target for developing antiviral agents. E2 is a homodimeric protein that interacts with the DNA target through an α-helix of each monomer. However, a peptide corresponding to the DNA recognition helix of HPV-16 E2 binds DNA with lower affinity than its full-length DNA binding domain. Therefore, in an attempt to promote the DNA binding of the isolated peptide, we have designed a conjugate compound of the E2 α-helix peptide and a derivative of the antibiotic distamycin, which involves simultaneous minor- and major-groove interactions. METHODOLOGY/PRINCIPAL FINDINGS: An E2 α-helix peptide-distamycin conjugate was designed and synthesized. It was characterized by NMR and CD spectroscopy, and its DNA binding properties were investigated by CD, DNA melting and gel shift experiments. The coupling of E2 peptide with distamycin does not affect its structural properties. The conjugate improves significantly the affinity of the peptide for specific DNA. In addition, stoichiometric amounts of specific DNA increase meaningfully the helical population of the peptide. The conjugate enhances the DNA binding constant 50-fold, maintaining its specificity. CONCLUSIONS/SIGNIFICANCE: These results demonstrate that peptide-distamycin conjugates are a promising tool to obtain compounds that bind the E2 target DNA-sequences with remarkable affinity and suggest that a bipartite major/minor groove binding scaffold can be a useful approach for therapeutic treatment of HPV infection

Building collaboration in multi-agent systems using reinforcement learning

© Springer Nature Switzerland AG 2018. This paper presents a proof-of concept study for demonstrating the viability of building collaboration among multiple agents through standard Q learning algorithm embedded in particle swarm optimisation. Collaboration is formulated to be achieved among the agents via competition, where the agents are expected to balance their action in such a way that none of them drifts away of the team and none intervene any fellow neighbours territory, either. Particles are devised with Q learning for self training to learn how to act as members of a swarm and how to produce collaborative/collective behaviours. The produced experimental results are supportive to the proposed idea suggesting that a substantive collaboration can be build via proposed learning algorithm

Evolving network structure of academic institutions

Today’s colleges and universities consist of highly complex structures that dictate interactions between the administration, faculty, and student body. These structures can play a role in dictating the efficiency of policy enacted by the administration and determine the effect that curriculum changes in one department have on other departments. Despite the fact that the features of these complex structures have a strong impact on the institutions, they remain by-and-large unknown in many cases. In this paper we study the academic structure of our home institution of Trinity College in Hartford, CT using the major and minor patterns between graduating students to build a temporal multiplex network describing the interactions between different departments. Using recent network science techniques developed for such temporal networks we identify the evolving community structures that organize departments’ interactions, as well as quantify the interdisciplinary centrality of each department. We implement this framework for Trinity College, finding practical insights and applications, but also present it as a general framework for colleges and universities to better understand their own structural makeup in order to better inform academic and administrative policy

The Endogenous Th17 Response in NO<inf>2</inf>-Promoted Allergic Airway Disease Is Dispensable for Airway Hyperresponsiveness and Distinct from Th17 Adoptive Transfer

Severe, glucocorticoid-resistant asthma comprises 5-7% of patients with asthma. IL-17 is a biomarker of severe asthma, and the adoptive transfer of Th17 cells in mice is sufficient to induce glucocorticoid-resistant allergic airway disease. Nitrogen dioxide (NO2) is an environmental toxin that correlates with asthma severity, exacerbation, and risk of adverse outcomes. Mice that are allergically sensitized to the antigen ovalbumin by exposure to NO2 exhibit a mixed Th2/Th17 adaptive immune response and eosinophil and neutrophil recruitment to the airway following antigen challenge, a phenotype reminiscent of severe clinical asthma. Because IL-1 receptor (IL-1R) signaling is critical in the generation of the Th17 response in vivo, we hypothesized that the IL-1R/Th17 axis contributes to pulmonary inflammation and airway hyperresponsiveness (AHR) in NO2-promoted allergic airway disease and manifests in glucocorticoid-resistant cytokine production. IL-17A neutralization at the time of antigen challenge or genetic deficiency in IL-1R resulted in decreased neutrophil recruitment to the airway following antigen challenge but did not protect against the development of AHR. Instead, IL-1R-/- mice developed exacerbated AHR compared to WT mice. Lung cells from NO2-allergically inflamed mice that were treated in vitro with dexamethasone (Dex) during antigen restimulation exhibited reduced Th17 cytokine production, whereas Th17 cytokine production by lung cells from recipient mice of in vitro Th17-polarized OTII T-cells was resistant to Dex. These results demonstrate that the IL-1R/Th17 axis does not contribute to AHR development in NO2-promoted allergic airway disease, that Th17 adoptive transfer does not necessarily reflect an endogenously-generated Th17 response, and that functions of Th17 responses are contingent on the experimental conditions in which they are generated. © 2013 Martin et al

Predicting language diversity with complex network

Evolution and propagation of the world's languages is a complex phenomenon, driven, to a large extent, by social interactions. Multilingual society can be seen as a system of interacting agents, where the interaction leads to a modification of the language spoken by the individuals. Two people can reach the state of full linguistic compatibility due to the positive interactions, like transfer of loanwords. But, on the other hand, if they speak entirely different languages, they will separate from each other. These simple observations make the network science the most suitable framework to describe and analyze dynamics of language change. Although many mechanisms have been explained, we lack a qualitative description of the scaling behavior for different sizes of a population. Here we address the issue of the language diversity in societies of different sizes, and we show that local interactions are crucial to capture characteristics of the empirical data. We propose a model of social interactions, extending the idea from, that explains the growth of the language diversity with the size of a population of country or society. We argue that high clustering and network disintegration are the most important characteristics of models properly describing empirical data. Furthermore, we cancel the contradiction between previous models and the Solomon Islands case. Our results demonstrate the importance of the topology of the network, and the rewiring mechanism in the process of language change

Aortic dissection at the University hospital of the West Indies: A 20-year clinicopathological study of autopsy cases

<p>Abstract</p> <p>Background</p> <p>An autopsy study of aortic dissection (AD) at our institution was previously reported. In the approximately 20 years since then, however, many aspects of diagnosis and treatment of this disease have changed, with a fall in mortality reported in many centers around the world. An impression amongst our pathologists that, there might be an increase in the prevalence of AD in the autopsy service at our hospital, since that earlier report, led to this repeated study, in an attempt to validate that notion. We also sought to identify any changes in clinicopathological features between the two series or any occurring during this study period itself.</p> <p>Findings</p> <p>All cases of AD identified at autopsy, during the 20-year period since the conclusion of the last study, were collected and pertinent clinical and pathological data were analyzed and compared, both within the two decades of this study period and against the results of the last study.</p> <p>Fifty-six cases comprised this study group including 36 males and 20 females, with a mean age of 63.9 years. There were, more patients in the second decade (n = 33; 59%) compared with the first decade (n = 23; 41%). Hypertension as a risk factor was identified in 52 (93%) cases and rupture occurred in 49 (88%) cases. A clinical diagnosis of AD was considered prior to surgery or autopsy in 25 (45%) cases overall, more during the second decade. Surgery was attempted in 25% of all cases with an increase in the second decade compared with the first.</p> <p>Conclusions</p> <p>Compared with the earlier review, a variety of changes in the profile of patients with AD in the autopsy service has been noted, including a reversal in the female predominance seen previously. Other observations include an increase in cases where the correct clinical diagnosis was considered and in which surgical treatment was attempted, changes also evident when the second decade of the present study was compared with the earlier decade. Overall, there were many positive trends. However, areas that could still be improved include an increased index of suspicion for the diagnosis of AD and perhaps in the initiation of treatment, earlier, in those cases where the correct diagnosis was considered.</p

Correction to: The mycobacterial glycoside hydrolase LamH enables capsular arabinomannan release and stimulates growth (Nature Communications, (2024), 15, 1, (5740), 10.1038/s41467-024-50051-3)

\ua9 The Author(s) 2024.Correction to: Nature Communicationshttps://doi.org/10.1038/s41467-024-50051-3, published online 09 July 2024 The original version of this Article contained an error in Fig. 3, in which the X-axis was incorrectly labelled in panel d. This has been corrected in both the PDF and HTML versions of the Article

The mycobacterial glycoside hydrolase LamH enables capsular arabinomannan release and stimulates growth

\ua9 The Author(s) 2024.Mycobacterial glycolipids are important cell envelope structures that drive host-pathogen interactions. Arguably, the most important are lipoarabinomannan (LAM) and its precursor, lipomannan (LM), which are trafficked from the bacterium to the host via unknown mechanisms. Arabinomannan is thought to be a capsular derivative of these molecules, lacking a lipid anchor. However, the mechanism by which this material is generated has yet to be elucidated. Here, we describe the identification of a glycoside hydrolase family 76 enzyme that we term LamH (Rv0365c in Mycobacterium tuberculosis) which specifically cleaves α−1,6-mannoside linkages within LM and LAM, driving its export to the capsule releasing its phosphatidyl-myo-inositol mannoside lipid anchor. Unexpectedly, we found that the catalytic activity of this enzyme is important for efficient exit from stationary phase cultures, potentially implicating arabinomannan as a signal for growth phase transition. Finally, we demonstrate that LamH is important for M. tuberculosis survival in macrophages