Anticancer peptides : prospective innovation in cancer therapy

© Springer International Publishing Switzerland 2016Current cancer treatments require improvements in selectivity and efficacy. Surgery, radiation, and chemotherapy approaches result in patient’s suffering over time due to the development of severe side-effects that simultaneously condition adherence to therapy. Biologically active peptides, in particular antimicrobial peptides (AMPs), are versatile molecules in terms of biological activities. The cytotoxic activities of several AMPs turn this group of molecules into an amazing pool of new templates for anticancer drug development. However, several unmet challenges limit application of peptides in cancer therapy. The mechanism(s) of action of the peptides need better description and understanding, and innovative targets have to be discovered and explored, facilitating drug design and development. In this chapter, we explore the natural occurring AMPs as potential new anticancer peptides (ACPs) for cancer prevention and treatment. Their modes of action, selectivity to tumor compared to normal cells, preferential targets, and applications, but also their weaknesses, are described and discussed.info:eu-repo/semantics/publishedVersio

A case study in collaboration: Assessing academic librarian/faculty partnerships

Undergraduates attending The George Washington University are required to take courses in the University Writing Program. When it was introduced in 2004, this innovative program institutionalized collaboration between librarians and writing professors. The program was designed to support the university’s strategic goal to enhance challenge, discovery, and quality in student education. Beginning in 2005, instruction librarians crafted a survey to elicit anonymous feedback from their faculty partners to measure the impact of the library partnership on student learning. The survey is administered annually to explore faculty perceptions and monitor trends. Responses to the survey identify significant strengths resulting from this collaboration as well as specific topics needing further attention

Geographic and Age-Based Variations in Medicare Reimbursement Among ASSH Members.

Background: The purpose of this study was to investigate how American Society for Surgery of the Hand (ASSH) members\u27 Medicare reimbursement depends on their geographical location and number of years in practice. Methods: Demographic data for surgeons who were active members of the ASSH in 2012 were obtained using information publicly available through the US Centers for Medicare and Medicaid Services (CMS). Hand-surgeons-per-capita and average reimbursement per surgeon were calculated for each state. Regression analysis was performed to determine a relationship between (1) each state\u27s average reimbursement versus the number of ASSH members in that state, (2) average reimbursement versus number of hand surgeons per capita, and (3) total reimbursement from Medicare versus number of years in practice. Analysis of variance (ANOVA) was used to detect a difference in reimbursement based on categorical range of years as an ASSH member. Results: A total of 1667 ASSH members satisfied inclusion in this study. Although there was significant variation among states\u27 average reimbursement, reimbursement was not significantly correlated with the state\u27s hand surgeons per capita or total number of hand surgeons in that given state. Correlation between years as an ASSH member and average reimbursement was significant but non-linear; the highest reimbursements were seen in surgeons who had been ASSH members from 8 to 20 years. Conclusions: Peak reimbursement from Medicare for ASSH members appears to be related to the time of surgeons\u27 peak operative volume, rather than any age-based bias for or against treating Medicare beneficiaries. In addition, though geographic variation in reimbursement does exist, this does not appear to correlate with density or availability of hand surgeons

Reactive extrusion : optimization of representative processes

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From antimicrobial to anticancer peptides : a review

Antimicrobial peptides (AMPs) are part of the innate immune defense mechanism of many organisms. Although AMPs have been essentially studied and developed as potential alternatives for fighting infectious diseases, their use as anticancer peptides (ACPs) in cancer therapy either alone or in combination with other conventional drugs has been regarded as a therapeutic strategy to explore. As human cancer remains a cause of high morbidity and mortality worldwide, an urgent need of new, selective, and more efficient drugs is evident. Even though ACPs are expected to be selective toward tumor cells without impairing the normal body physiological functions, the development of a selective ACP has been a challenge. It is not yet possible to predict antitumor activity based on ACPs structures. ACPs are unique molecules when compared to the actual chemotherapeutic arsenal available for cancer treatment and display a variety of modes of action which in some types of cancer seem to co-exist. Regardless the debate surrounding the definition of structure-activity relationships for ACPs, great effort has been invested in ACP design and the challenge of improving effective killing of tumor cells remains. As detailed studies on ACPs mechanisms of action are crucial for optimizing drug development, in this review we provide an overview of the literature concerning peptides' structure, modes of action, selectivity, and efficacy and also summarize some of the many ACPs studied and/or developed for targeting different solid and hematologic malignancies with special emphasis on the first group. Strategies described for drug development and for increasing peptide selectivity toward specific cells while reducing toxicity are also discussed.The authors thank Fundação para a Ciência e a Tecnologia (FCT- MEC, Portugal) for funding—PTDC/QUI-BIO/112929/2009. Diana Gaspar also acknowledges FCT for fellowship SFRH/BPD/ 73500/2010 and A. Salome Veiga for funding within the FCT Investigator Programme (IF/00803/2012

Neuroevolution for solving multiobjective knapsack problems

The multiobjective knapsack problem (MOKP) is an important combinatorial problem that arises in various applications, including resource allocation, computer science and finance. When tackling this problem by evolutionary multiobjective optimization algorithms (EMOAs), it has been demonstrated that traditional recombination operators acting on binary solution representations are susceptible to a loss of diversity and poor scalability. To address those issues, we propose to use artificial neural networks for generating solutions by performing a binary classification of items using the information about their profits and weights. As gradient-based learning cannot be used when target values are unknown, neuroevolution is adapted to adjust the neural network parameters. The main contribution of this study resides in developing a solution encoding and genotype-phenotype mapping for EMOAs to solve MOKPs. The proposal is implemented within a state-of-the-art EMOA and benchmarked against traditional variation operators based on binary crossovers. The obtained experimental results indicate a superior performance of the proposed approach. Furthermore, it is advantageous in terms of scalability and can be readily incorporated into different EMOAs.Portuguese “Fundação para a Ciência e Tecnologia” under grant PEst-C/CTM/LA0025/2013 (Projecto Estratégico - LA 25 - 2013-2014 - Strategic Project - LA 25 - 2013-2014

Combining artificial neural networks and evolution to solve multiobjective knapsack problems

The multiobjective knapsack problem (MOKP) is a combinatorial problem that arises in various applications, including resource allocation, computer science and finance. Evolutionary multiobjective optimization algorithms (EMOAs) can be effective in solving MOKPs. Though, they often face difficulties due to the loss of solution diversity and poor scalability. To address those issues, our study [2] proposes to generate candidate solutions by artificial neural networks. This is intended to provide intelligence to the search. As gradient-based learning cannot be used when target values are unknown, neuroevolution is adapted to adjust the neural network parameters. The proposal is implemented within a state-of-the-art EMOA and benchmarked against traditional search operators base on a binary crossover. The obtained experimental results indicate a superior performance of the proposed approach. Furthermore, it is advantageous in terms of scalability and can be readily incorporated into different EMOAs.(undefined

Antibodies for the treatment of brain metastases, a dream or a reality?

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).The incidence of brain metastases (BM) in cancer patients is increasing. After diagnosis, overall survival (OS) is poor, elicited by the lack of an effective treatment. Monoclonal antibody (mAb)-based therapy has achieved remarkable success in treating both hematologic and non-central-nervous system (CNS) tumors due to their inherent targeting specificity. However, the use of mAbs in the treatment of CNS tumors is restricted by the blood-brain barrier (BBB) that hinders the delivery of either small-molecules drugs (sMDs) or therapeutic proteins (TPs). To overcome this limitation, active research is focused on the development of strategies to deliver TPs and increase their concentration in the brain. Yet, their molecular weight and hydrophilic nature turn this task into a challenge. The use of BBB peptide shuttles is an elegant strategy. They explore either receptor-mediated transcytosis (RMT) or adsorptive-mediated transcytosis (AMT) to cross the BBB. The latter is preferable since it avoids enzymatic degradation, receptor saturation, and competition with natural receptor substrates, which reduces adverse events. Therefore, the combination of mAbs properties (e.g., selectivity and long half-life) with BBB peptide shuttles (e.g., BBB translocation and delivery into the brain) turns the therapeutic conjugate in a valid approach to safely overcome the BBB and efficiently eliminate metastatic brain cells.This research was funded by the Portuguese Funding Agency, Fundação para a Ciência e Tecnologia, FCT IP, grants PD/BD/128281/2017, PTDC/BBB-BQB/1693/2014 and PTDC/BBB-NAN/1578/2014.info:eu-repo/semantics/publishedVersio