Project description:Metastatic castration-resistant prostate cancer (mCRPC) remains a terminal diagnosis with an aggressive disease course despite currently approved therapeutics. The recent successful development of poly ADP-ribose polymerase (PARP) inhibitors for patients with mCRPC and mutations in DNA damage repair genes has added to the treatment armamentarium and improved personalized treatments for prostate cancer. Other promising therapeutic agents currently in clinical development include the radiotherapeutic 177-lutetium-prostate-specific membrane antigen (PSMA)-617 targeting PSMA-expressing prostate cancer and combinations of immunotherapy with currently effective treatment options for prostate cancer. Herein, we have highlighted the progress in systemic treatments for mCRPC and the promising agents currently in ongoing clinical trials.
Project description:Leptomeningeal metastasis is an uncommon but serious complication in patients with advanced cancers. Leptomeningeal metastasis is diagnosed in approximately 5% of the patients, most commonly among patients with cancers of breast and lung, melanoma, and gastrointestinal malignancies. Treatment goal is to improve survival and quality of the patients. Use of targeted therapies and immunotherapy has led to improved survival of patients with non-small cell lung cancer (NSCLC). In this article, we review emerging data on use of mutation-specific agents and immunotherapy in the treatment of leptomeningeal metastasis among patients with NSCLC.
Project description:The incidence of Clostridium difficile infection (CDI) has been rising in hospitals, long-term care facilities, and within the community. Cases have been more severe with more complications, deaths, and higher healthcare-associated costs. With the emergence of a hypervirulent strain of C. difficile and the increasing prevalence of community-acquired CDI among healthy patients without traditional risk factors, the epidemiology of C. difficile has been evolving. This changing epidemiology requires a change in management. Taking into account new risk factors for CDI and growing subpopulations of affected individuals, diagnostic, treatment, and prevention approaches need to be adjusted.
Project description:BACKGROUND: The problem of approximate string matching is important in many different areas such as computational biology, text processing and pattern recognition. A great effort has been made to design efficient algorithms addressing several variants of the problem, including comparison of two strings, approximate pattern identification in a string or calculation of the longest common subsequence that two strings share. RESULTS: We designed an output sensitive algorithm solving the edit distance problem between two strings of lengths n and m respectively in time O((s - |n - m|).min(m, n, s) + m + n) and linear space, where s is the edit distance between the two strings. This worst-case time bound sets the quadratic factor of the algorithm independent of the longest string length and improves existing theoretical bounds for this problem. The implementation of our algorithm also excels in practice, especially in cases where the two strings compared differ significantly in length. CONCLUSION: We have provided the design, analysis and implementation of a new algorithm for calculating the edit distance of two strings with both theoretical and practical implications. Source code of our algorithm is available online.
Project description:The ability to learn abstract generalized structures of tasks is crucial for humans to adapt to changing environments and novel tasks. In a series of five experiments, we investigated this ability using a Rapid Instructed Task Learning paradigm (RITL) comprising short miniblocks, each involving two novel stimulus-response rules. Each miniblock included (a) instructions for the novel stimulus-response rules, (b) a NEXT phase involving a constant (familiar) intervening task (0-5 trials), (c) execution of the newly instructed rules (2 trials). The results show that including a NEXT phase (and hence, a prospective memory demand) led to relatively more robust abstract learning as indicated by increasingly faster responses with experiment progress. Multilevel modeling suggests that the prospective memory demand was just another aspect of the abstract task structure which has been learned.
Project description:Hepatitis C virus (HCV) is a common cause of increased morbidity and mortality in kidney transplant patients. It is associated with posttransplant glomerulonephritis, chronic allograft nephropathy, and New Onset Diabetes after Transplant (NODAT). In the past, HCV was difficult to treat due to the presence of interferon alpha-based therapies that were difficult to tolerate and were associated with adverse side-effects, such as the risk of rejection. With the advent of oral directly acting antiviral therapies, the landscape for HCV and transplantation has changed. These agents are highly effective and well tolerated with minimal side-effects. Sustained viral response rates in excess of 90% are achieved with most current treatment regimens active against all HCV genotypes. These new agents may show an improvement in graft and patient survival while essentially eliminating the risk of acute rejection from the use of prior interferon-based HCV therapies. These agents may also result in an improvement in organ allocation for HCV donor/HCV recipient transplantation. This review is meant to discuss the epidemiology of HCV, the new oral direct-acting antiviral agents (DAAs) and future opportunities for research in the field of HCV related transplantation.
Project description:The hypothesis that tumors may originate from a rare population of cancer stem cells (CSCs) has gained tremendous popularity in recent years and is supported extensively by several pioneering works. Cancer therapies targeting CSCs have unlimited potential for relapse free survival of cancer patients. As a result, knowledge of biological pathways that govern CSCs is very important and this review is focused on the biology of CSCs with special emphasis on breast CSCs, and recent advances in therapeutic approaches targeting them.
Project description:Triple-negative breast cancer (TNBC) represents a heterogeneous breast cancer subtype with a poor prognosis. The optimal adjuvant chemotherapy regimen is still unknown. Although numerous large randomized trials have established the benefit of adjuvant anthracyclines and/or taxanes in TNBC, there is no preferred regimen for these patients. There is currently no guideline. Moreover, without knowing the optimal treatment backbone, it will not be possible to evaluate whether adding agents such as platinum or other novel therapies is beneficial for TNBC patients. Furthermore, the best duration of adjuvant treatment in TNBC is still unknown. This review will focus on results of clinical trials that analyzed the benefits of extending the duration of adjuvant treatment in TNBCs with maintenance treatments. We will further discuss promising results in favor of other new agents including capecitabine, metronomic treatment, and biological drugs.
Project description:Rebuilding depleted fish stocks is an international policy goal and a 2020 Aichi target under the Convention on Biological Diversity. However, stock productivity may shift with future climate change, with unknown consequences for sustainable harvesting, biomass targets and recovery timelines. Here we develop a stochastic modelling framework to characterize variability in the intrinsic productivity parameter (r) and carrying capacity (K) for 276 global fish stocks worldwide. We use models of dynamic stock productivity fitted via Bayesian inference to forecast rebuilding timelines for depleted stocks. In scenarios without fishing, recovery probabilities are reduced by 19%, on average, relative to models assuming static productivity. Fishing at 90% of the maximum sustainable rate depresses recovery probabilities by 42%, on average, relative to static models. This work reveals how a changing environmental context can delay the rebuilding of depleted fish stocks, and provides a framework to account for the potential impacts of environmental change on the productivity of wildlife populations more broadly.
Project description:MicroRNAs (miRNAs) are small non-coding RNAs that can post-transcriptionally regulate the genes involved in critical cellular processes. The aberrant expressions of oncogenic or tumor suppressor miRNAs have been associated with cancer progression and malignancies. This resulted in the dysregulation of signaling pathways involved in cell proliferation, apoptosis and survival, metastasis, cancer recurrence and chemoresistance. In this review, we will first (i) provide an overview of the miRNA biogenesis pathways, and in vitro and in vivo models for research, (ii) summarize the most recent findings on the roles of microRNAs (miRNAs) that could potentially be used for miRNA-based therapy in the treatment of breast cancer and (iii) discuss the various therapeutic applications.