200,704 research outputs found
Exploiting evolution to treat drug resistance: Combination therapy and the double bind
No full textAlthough many anti cancer therapies are successful in killing a large percentage of tumour cells when initially administered, the evolutionary dynamics underpinning tumour progression mean that often resistance is an inevitable outcome, allowing for new tumour phenotypes to emerge that are unhindered by the therapy. Research in the field of ecology suggests that an evolutionary double bind could be an effective way to treat tumours. In an evolutionary double bind two therapies are used in combination such that evolving resistance to one leaves individuals more susceptible to the other. In this paper we present a general evolutionary game theory model of a double bind to study the effect that such approach would have in cancer. Furthermore we use this mathematical framework to understand recent experimental results that suggest a synergistic effect between a p53 cancer vaccine and chemotherapy. Our model recapitulates the experimental data and provides an explanation for its effectiveness based on the commensalistic relationship between the tumour phenotypes
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
ProtCB-bind: Protein-carbohydrate binding site prediction using an ensemble of classifiers
No full textProteins and carbohydrates are fundamental biomolecules that play crucial roles in life processes. The interactions between these molecules are essential for various biological functions, including immune response, cell activation, and energy storage. Therefore, understanding and identifying protein-carbohydrate binding regions is of significant importance.
In this study, we propose ProtCB-Bind, a computational model for predicting protein-carbohydrate interactions. ProtCB-Bind leverages an ensemble of machine learning classifiers and utilizes a common averaging approach to form predictions. The proposed model is trained using a combination of sequence-based and evolutionary-based features of protein sequences, as well as the physicochemical properties of amino acids. To enhance predictive performance, ProtCB-Bind incorporates features derived from recent advancements in transformer-based Natural Language Processing (NLP) for proteins.
ProtCB-Bind was designed by systematically identifying the best combination of classifiers and features, and was evaluated using a state-of-the-art benchmark dataset. Its performance was compared against established predictors, including SPRINT-CBH, StackCB-Pred, and StackCB-Embed. ProtCB-Bind outperformed these state-of-the-art predictors, achieving an approximate 3 % improvement in overall performance on benchmark dataset.
The sources code for ProtCB-Bind is available at https://github.com/Divnesh/ProtCB-Bind.No Full Tex
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
ExtractMotifs package - R script designed to analyse data in a bind-n-seq strategy
No full textR script designed to analyse data in a bind-n-seq strategy: This R package has been designed as a companion for the analysis of MERMADE (available at http://korflab.ucdavis.edu/datasets/BindNSeq/) software results in an improved Bind-n-seq strategy published in "An improved bind-n-seq strategy to determine protein-DNA interactions validated using the bacterial transcriptional regulator YipR" (Shi-qi et al 2020 ) It requires the installation of other R packages available from CRAN ("Plyr", "stringi", "htmltab","stringr" and "devtools") and from Bioconductor ("Biostrings", "DECIPHER") To install this R package use the following commands: install.packages("PathTo/ExtractMotifs_0.1.0.tar.gz",repos = NULL, type="source"
The role of family history of Cancer in Oral Cavity Cancer
No full textObjectives: Oral and oropharyngeal squamous cell carcinoma (SCC) is the 10th most common cancer in the United States (8th in males, 13th in females), with an estimated 54,010 new cases expected in 2021, and is primarily associated with smoked tobacco, heavy alcohol consumption, areca nut use and persistent high-risk human papillomavirus (HPV). Family history of cancer (FHC) and family history of head and neck cancer (FHHNC) have been reported to play an important role in the development of OSCC. We aimed to investigate the role of FHC, FHHNC and personal history of cancer in first/second degree-relatives as co-risk factors for oral cancer. Methods: This was a retrospective study of patients diagnosed with OSCC at the Division of Oral Medicine and Dentistry at Brigham and Women’s Hospital and at the Division of Head and Neck Oncology at Dana Farber Cancer Institute. Conditional logistic regressions were performed to examine whether OSCC was associated with FHC and FHHNC of FDRs and SDRs, personal history of cancer and secondary risk factors. Results: Overall, we did not find an association between FHC, FHHNC and OSCC risk, whereas patients with a cancer history in one of their siblings were 1.6-times more likely to present with an OSCC. When secondary risk factors were considered, patients with a history of oral leukoplakia and dysplasia had a 16-times higher risk of having an OSCC. Conclusions: Our study confirmed that a previous history of oral leukoplakia or dysplasia was an independent risk factor for OSCC. A positive family history of cancer in one or more siblings may be an additional risk factor for OSCC
Letter from R. R. Zellick, Assistant Trust Officer, Anglo California National Bank of San Francisco, to Joseph R. Goodman, October 2, 1942
No full textLetter from R. R. Zellick, Assistant Trust Officer at The Anglo California National Bank of San Francisco, to Joseph R. Goodman, regarding property owned by Dave Tatsuno. Zellick mentions a dispute between current tenants and Tatsuno, and that Tatsuno has asked Goodman to help locate trustworthy tenants.Personal correspondence, organizational records, government documents, publications, and other papers created or collected by Joseph R. Goodman documenting the forced removal and incarceration of Japanese Americans during World War II, as well as organized resistance to incarceration. Included in the collection are records of the Japanese Young Men's Christian Association and the Japanese American Citizens' League in San Francisco, including papers of the Japanese YMCA's executive secretary Lincoln Kanai; Sakai family papers; Goodman's correspondence to and from Japanese American incarcerees, organizations opposing forced removal and incarceration of Japanese Americans, the War Relocation Authority, and others; publications, photographs, and ephemera from the Topaz Relocation Center, where Goodman taught high school; War Relocation Authority records and publications; and newspaper clippings, pamphlets, and reports about forced removal and incarceration created by various government, religious, and civic organizations, in California and nationwide
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
R‑BIND: An Interactive Database for Exploring and Developing RNA-Targeted Chemical Probes
No full textWhile
the opportunities available for targeting RNA with small
molecules have been widely appreciated, the challenges associated
with achieving specific RNA recognition in biological systems have
hindered progress and prevented many researchers from entering the
field. To facilitate the discovery of RNA-targeted chemical probes
and their subsequent applications, we curated the RNA-targeted BIoactive
ligaNd Database (R-BIND). This collection contains an array of information
on reported chemical probes that target non-rRNA and have biological
activity, and analysis has led to the discovery of RNA-privileged
properties. Herein, we developed an online platform to make this information
freely available to the community, offering search options, a suite
of tools for probe development, and an updated R-BIND data set with
detailed experimental information for each probe. We repeated the
previous cheminformatics analysis on the updated R-BIND list and found
that the distinguishing physicochemical, structural, and spatial properties
remained unchanged, despite an almost 50% increase in the database
size. Further, we developed several user-friendly tools, including
queries based on cheminformatic parameters, experimental details,
functional groups, and substructures. In addition, a nearest neighbor
algorithm can assess the similarity of user-uploaded molecules to
R-BIND ligands. These tools and resources can be used to design small
molecule libraries, optimize lead ligands, or select targets, probes,
assays, and control experiments. Chemical probes are critical to the
study and discovery of novel functions for RNA, and we expect this
resource to greatly assist researchers in exploring and developing
successful RNA-targeted probes
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