Papers citing PharmaceuticalIntelligence.com
Reporter: Stephen J. Williams, PhD
(10 papers, 5 peer reviewed, 2 web page, 2 teaching lectures, 1 preprint) Search from years 2012 – 2018
UPDATED on 5/22/2022
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Peer Reviewed
- Yan-Fang Guan, Gai-Rui Li, Rong-Jiao Wang, Yu-Ting Yi, Ling Yang, Dan Jiang, Xiao-Ping Zhang, and Yin Peng. Application of next-generation sequencing in clinical oncology to advance personalized treatment of cancer. Chin J Cancer. 2012 Oct; 31(10): 463–470. Using 44. Lev-Ari A. Sunitinib brings Adult acute lymphoblastic leukemia (ALL) to Remission-RNA Sequencing-FLT3 Receptor Blockade. 2012. Available at: http://pharmaceuticalintelligence.com/2012/07/09/sunitinib-brings-adult-all-to-remission-rna-sequencing/
- Pedro A. Moreno. Bioinformática multifractal: Una propuesta hacia la interpretación no-lineal del genoma: Multifractal bioinformatics: A proposal to the nonlinear interpretation of genome. Ing. compet. vol.16 no.1 Cali Jan./June 2014. Using (http://pharmaceuticalintelligence.com/tag/fractal-geometry/).
- Gökmen Altay1* and David E. Neal2. Genome-wide differential gene network analysis R software and its application in LnCap prostate cancer in https://www.biorxiv.org/content/biorxiv/early/2017/04/24/129742.full.pdf citing an R package in the paper citing us in reference to CXC4 inhibitors as (http://pharmaceuticalintelligence.com/2015/12/15/are-cxc4-antagonists-making-a-comebackin-cancer-chemotherapy, 2015).
- D.Sairam Course : Fundamentals of Biology- Life Sciences Course Code: BSBT-201 Course Instructor: Dr. Subhabrata Kar citing in presentation Comparison of Glycolysis between a Normal Tissue and Tumour/ Proliferated Tissue • http://pharmaceuticalintelligence.com/2012/10/17/is-the- warburg-effect-the-cause-or-the-effect-of-cancer-a-21st- century-view/
- Sasaki, Takaaki, Scott J. Rodig, Lucian R. Chirieac, and Pasi A. Janne. “The Biology and Treatment of EML4-ALK Non-Small Cell Lung Cancer.” NCBI. US National Library of Medicine, 24 Apr. 2010. In website https://prezi.com/rbtv_450s3wd/eml4-alk-fusion-gene/ citing us as https://pharmaceuticalintelligence.files.wordpress.com/2014/08/membrane_receptor_tk.jpg?w=500&h=326
- Github project on GENEREGULATION,Deciphering the code of gene regulation using massively parallel assays of designed sequence at https://github.com/arquivo/Research-Websites-Preservation/blob/master/classifier/projects_classification.csv.3 citing us as http://pharmaceuticalintelligence.com/tag/transcription/page/2/,0
- Website https://tginnovations.wordpress.com/2012/05/08/cancer/ citing us as Cancer Metastasis(pharmaceuticalintelligence.com) {one of our chapters in Cancer Volume 1}
- Website https://www.minipiginfo.com/mini-pig-cancer.html citing us https://pharmaceuticalintelligence.com/the-scid-pig-how-pigs-are-becoming-a-great-alternate-model-for-cancer-research
- Shashi Shekhar Anand, Navgeet, Balraj Singh Gill*. In https://www.pharmatutor.org/articles/breakthroughs-in-epigenetics
Citing as figure source for Fig 5. Phosphorylation of serine chain
Fig.source:pharmaceuticalintelligence.com
- Larry H Bernstein. Ca2+-Stimulated Exocytosis: The Role of Calmodulin and Protein Kinase C in Ca2+ Regulation of Hormone and Neurotransmitter in https://www.archivesofmedicine.com/medicine/ca2stimulated-exocytosis-the-role-of-calmodulin-and-protein-kinase-c-in-ca2-regulation-of-hormone-and-neurotransmitter.php?aid=7058
- Description: Multidimensional Representation of Concepts as Cognitive Engrams in the Human Brain. Clinical Trial NCT02834716 on Cognitive Impairment using https://pharmaceuticalintelligence.com/2013/02/27/ustekinumab-new-drug-therapy-for-cognitive-decline-resulting-from-neuroinflammatory-cytokine-signaling-and-alzheimers-disease/
Description: Ustekinumab New Drug Therapy for Cognitive Decline resulting from Neuroinflammatory Cytokine Signaling and Alzheimer’s Disease
- Beckman Coulter promotional material. In Post Translational Modification at https://www.beckman.com/resources/sample-type/bio-molecules/post-translational-modification
Using our material as reference “Overview of Posttranslational Modification (PTM) | Leaders in Pharmaceutical Business Intelligence (LPBI) Group.” Leaders in Pharmaceutical Business Intelligence (LPBI) Group, 29 July 2014, https://pharmaceuticalintelligence.com/2014/07/29/overview-of-posttranslational-modification-ptm/.
DETAILS
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3777453/
Chin J Cancer. 2012 Oct; 31(10): 463–470.
doi: 10.5732/cjc.012.10216
PMCID: PMC3777453
PMID: 22980418
Application of next-generation sequencing in clinical oncology to advance personalized treatment of cancer
Yan-Fang Guan, Gai-Rui Li, Rong-Jiao Wang, Yu-Ting Yi, Ling Yang, Dan Jiang, Xiao-Ping Zhang, and Yin Peng
Author information Article notes Copyright and License information Disclaimer
This article has been cited by other articles in PMC.
Abstract
With the development and improvement of new sequencing technology, next-generation sequencing (NGS) has been applied increasingly in cancer genomics research over the past decade. More recently, NGS has been adopted in clinical oncology to advance personalized treatment of cancer. NGS is used to identify novel and rare cancer mutations, detect familial cancer mutation carriers, and provide molecular rationale for appropriate targeted therapy. Compared to traditional sequencing, NGS holds many advantages, such as the ability to fully sequence all types of mutations for a large number of genes (hundreds to thousands) in a single test at a relatively low cost. However, significant challenges, particularly with respect to the requirement for simpler assays, more flexible throughput, shorter turnaround time, and most importantly, easier data analysis and interpretation, will have to be overcome to translate NGS to the bedside of cancer patients. Overall, continuous dedication to apply NGS in clinical oncology practice will enable us to be one step closer to personalized medicineWith the development and improvement of new sequencing technology, next-generation sequencing (NGS) has been applied increasingly in cancer genomics research over the past decade. More recently, NGS has been adopted in clinical oncology to advance personalized treatment of cancer. NGS is used to identify novel and rare cancer mutations, detect familial cancer mutation carriers, and provide molecular rationale for appropriate targeted therapy. Compared to traditional sequencing, NGS holds many advantages, such as the ability to fully sequence all types of mutations for a large number of genes (hundreds to thousands) in a single test at a relatively low cost. However, significant challenges, particularly with respect to the requirement for simpler assays, more flexible throughput, shorter turnaround time, and most importantly, easier data analysis and interpretation, will have to be overcome to translate NGS to the bedside of cancer patients. Overall, continuous dedication to apply NGS in clinical oncology practice will enable us to be one step closer to personalized medicine.
- Lev-Ari A. Sunitinib brings Adult acute lymphoblastic leukemia (ALL) to Remission-RNA Sequencing-FLT3 Receptor Blockade. 2012. Available at: http://pharmaceuticalintelligence.com/2012/07/09/sunitinib-brings-adult-all-to-remission-rna-sequencing/
http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0123-30332014000100011
Ingeniería y competitividad
Print version ISSN 0123-3033
Ing. compet. vol.16 no.1 Cali Jan./June 2014
Bioinformática multifractal: Una propuesta hacia la interpretación no-lineal del genoma
Multifractal bioinformatics: A proposal to the nonlinear interpretation of genome
Pedro A. Moreno
Escuela de Ingeniería de Sistemas y Computación, Facultad de Ingeniería, Universidad del Valle, Cali, Colombia
E-mail: pedro.moreno@correounivalle.edu.co
Eje temático: Ingeniería de sistemas / System engineering
Recibido: 19 de septiembre de 2012
Aceptado: 16 de diciembre de 2013
Resumen
El primer borrador de la secuencia completa del genoma humano (GH) se publicó en el año 2001 por parte de dos consorcios competidores. Desde entonces, varias características estructurales y funcionales de la organización del GH han sido reveladas. Hoy en día, más de 2000 genomas humanos han sido secuenciados y todos estos hallazgos están impactando fuertemente en la academia y la salud pública. A pesar de esto, un gran cuello de botella llamado la interpretación del genoma persiste; esto es, la falta de una teoría que integre y explique el complejo rompecabezas de características codificantes y no codificantes que componen el GH como un todo. Diez años después de secuenciado el GH, dos trabajos recientes, abordados dentro del formalismo multifractal permiten proponer una teoría no-lineal que ayuda a interpretar la variación estructural y funcional de la información genética de los genomas. El presente artículo de revisión trata acerca de este novedoso enfoque, denominado: “Bioinformática multifractal”.
Palabras clave: Ciencias ómicas, bioinformática, genoma humano, análisis multifractal.
Abstract
The first draft of the human genome (HG) sequence was published in 2001 by two competing consortia. Since then, several structural and functional characteristics for the HG organization have been revealed. Today, more than 2.000 HG have been sequenced and these findings are impacting strongly on the academy and public health. Despite all this, a major bottleneck, called the genome interpretation persists. That is, the lack of a theory that explains the complex puzzles of coding and non-coding features that compose the HG as a whole. Ten years after the HG sequenced, two recent studies, discussed in the multifractal formalism allow proposing a nonlinear theory that helps interpret the structural and functional variation of the genetic information of the genomes. The present review article discusses this new approach, called: “Multifractal bioinformatics”.
- Introduction
Omic Sciences and Bioinformatics
In order to study the genomes, their life properties and the pathological consequences of impairment, the Human Genome Project (HGP) was created in 1990. Since then, about 500 Gpb (EMBL) represented in thousands of prokaryotic genomes and tens of different eukaryotic genomes have been sequenced (NCBI, 1000 Genomes, ENCODE). Today, Genomics is defined as the set of sciences and technologies dedicated to the comprehensive study of the structure, function and origin of genomes. Several types of genomic have arisen as a result of the expansion and implementation of genomics to the study of the Central Dogma of Molecular Biology (CDMB), Figure 1 (above). The catalog of different types of genomics uses the Latin suffix “-omic” meaning “set of” to mean the new massive approaches of the new omics sciences (Moreno et al, 2009). Given the large amount of genomic information available in the databases and the urgency of its actual interpretation, the balance has begun to lean heavily toward the requirements of bioinformatics infrastructure research laboratories Figure 1 (below).
The bioinformatics or Computational Biology is defined as the application of computer and information technology to the analysis of biological data (Mount, 2004). An interdisciplinary science that requires the use of computing, applied mathematics, statistics, computer science, artificial intelligence, biophysical information, biochemistry, genetics, and molecular biology. Bioinformatics was born from the need to understand the sequences of nucleotide or amino acid symbols that make up DNA and proteins, respectively. These analyzes are made possible by the development of powerful algorithms that predict and reveal an infinity of structural and functional features in genomic sequences, as gene location, discovery of homologies between macromolecules databases (Blast), algorithms for phylogenetic analysis, for the regulatory analysis or the prediction of protein folding, among others. This great development has created a multiplicity of approaches giving rise to new types of Bioinformatics, such as Multifractal Bioinformatics (MFB) that is proposed here.
1.1 Multifractal Bioinformatics and Theoretical Background
MFB is a proposal to analyze information content in genomes and their life properties in a non-linear way. This is part of a specialized sub-discipline called “nonlinear Bioinformatics”, which uses a number of related techniques for the study of nonlinearity (fractal geometry, Hurts exponents, power laws, wavelets, among others.) and applied to the study of biological problems (http://pharmaceuticalintelligence.com/tag/fractal-geometry/). For its application, we must take into account a detailed knowledge of the structure of the genome to be analyzed and an appropriate knowledge of the multifractal analysis.
https://www.biorxiv.org/content/biorxiv/early/2017/04/24/129742.full.pdf
Genome-wide differential gene network analysis R software and its application in LnCap prostate cancer
Gökmen Altay1* and David E. Neal2 1*La Jolla Institute for Allergy and Immunology, CA, USA 2Nuffield Department of Surgical Sciences, University of Oxford, Headington, OX3 7DQ , Oxford, United Kingdom *Corresponding author altay@lji.org Abstract We introduce an R software package for condition-specific gene regulatory network analysis based on DC3NET algorithm. We also present an application of it on a real prostate dataset and demonstrate the benefit of the software. We performed genome-wide differential gene network analysis with the software on the LnCap androgen stimulated and deprived prostate cancer gene expression datasets (GSE18684) and inferred the androgen stimulated prostate cancer specific differential network. As an outstanding result, CXCR7 along with CXCR4 appeared to have the most important role in the androgen stimulated prostate specific genome-wide differential network. This blind estimation is strongly supported from the literature. The critical roles for CXCR4, a receptor over-expressed in many cancers, and CXCR7 on mediating tumor metastasis, along with their contributions as biomarkers of tumor behavior as well as potential therapeutic target were studied in several other types of cancers. In fact, a pharmaceutical company had already developed a therapy by inhibiting CXCR4 to block non-cancerous immuno-suppressive and pro-angiogenic cells from populating the tumor for disrupting the cancer environment and restoring normal immune surveillance functions. Considering this strong confirmation, our inferred regulatory network might reveal the driving mechanism of LnCap androgen stimulated prostate cancer. Because, CXCR4 appeared to be in the center of the largest subnetwork of our inferred differential network. Moreover, enrichment analyses for the largest subnetwork of it appeared to be significantly enriched in terms of axon guidance, fc gamma R-mediated phagocytosis and endocytosis. This also conforms with the recent literature in the field of prostate cancer. We demonstrate how to derive condition-specific gene targets from expression datasets on genome-wide level using differential gene network analysis. Our results showed that differential gene network analysis worked well in a prostate cancer dataset, which suggest the use of this approach as essential part of current expression data processing. Availability: The introduced R software package available in CRAN at https://cran.r-project.org/web/packages/dc3net and also at https://github.com/altayg/dc3net
- Discussion By employing differential gene network analysis approach, the present study aims to investigate the molecular mechanisms that may drive disease progression in prostate cancer using our presented software dc3net. Top four hub nodes, identified in the present study, have been strongly associated with prostate cancer metastatic process, including CXCR7, STK39, ELOVL7 and ACSL3. Hub nodes are genes that are highly connected with other genes and they were proposed to have important roles in biological development. Since hub nodes have more complex interactions than other genes, they may have crucial roles in the underlying mechanisms of disease (Guo, 2015). Identification of hub genes involved in progression of prostate cancer may lead to the development of better diagnostic methods and providing therapeutic approaches. According to our analysis, CXCR7 (chemokine (C-X-C motif) receptor 7) is by far the top hub gene in the androgen stimulated differential network and it is also part of the largest independent subnetwork as seen in Figure 3. In (Wang, 2008), it is reported that staining of high-density tissue microarrays shows that the levels of CXCR7/RDC1 expression increase as the tumors become more aggressive. Also, In vitro and in vivo studies with prostate cancer cell lines propose that alterations in CXCR7/RDC1 expressions are associated with enhanced invasive and adhesive activities in addition to a survival advantage. Along other papers on CXCR7 (Zheng, 2010), it was shown that increased CXCR7 expression was found in hepatocellular carcinoma (HCC) tissues. Knockdown of CXCR7 expression by transfected with CXCR7shRNA significantly inhibited SMMC-7721 angiogenesis, adhesion and cells invasion. Moreover, down-regulation of CXCR7 expression leads to a reduction of tumor growth in a xenograft model of HCC (Zheng, 2010). Another study demonstrated that the IL8–regulated Chemokine Receptor CXCR7 stimulates EGFR Signaling to promote prostate cancer growth (Singh, 2011). In a study conducted by Yun et al., it is reported that CXCR7 expression is increased in most of the tumor cells compared with the normal cells and is involved in cell proliferation, migration, survival, invasion and angiogenesis during the initiation and progression of many cancer types including prostate cancer (Yun, 2015). A more recent study indicated that there appeared to be disconnect of the effect of DHT on CXCL12/CXCR4/CXCR7 chemokine axis between transcriptional and translation machinery in androgen-responsive LnCaP cell line. There are many other studies that showed the strong role of CXCR7 in metastatic type cancer that strongly validates our blind foremost prediction is very likely to be true and thus needs further experimental work on its targets that we inferred in this study. However, available under aCC-BY-NC 4.0 International license. not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made bioRxiv preprint doi: https://doi.org/10.1101/129742; this version posted April 24, 2017. The copyright holder for this preprint (which was 11 It was also observed that CXCR7/RDC1 levels are regulated by CXCR4 (Singh, 2011). This is a very interesting supporting information from literature for our blind estimation because in our predicted largest independent subnetwork, as shown in Figure 3, CXCR7 and CXCR4 appear to be very close and interacting over only one gene. Although CRCX4 is not a hub gene, it appears to be as a bridge that connects both halves of the largest subnetwork. According to KEGG analysis, CXCR4 was found in the gene list of two different significantly enriched KEGG pathways, axon guidance and endocytosis which are strongly associated with prostate cancer (Table 3). Considering the prediction was made on global level, this literature confirmation seems assuring but not a coincidence. Therefore, this relation is worth experimenting in LnCap cancer too. It is also reported (Shanmugam, 2011) that inhibition of CXCR4/CXCL12 signaling axis by ursolic acid leads to suppression of metastasis in transgenic adenocarcinoma of mouse prostate model and CXCR4 induced a more aggressive phenotype in prostate cancer (Miki, 2007). In another study, it is reported that CXCR4 and CXCR7 have critical roles on mediating tumor metastasis in various types of cancers as both being a receptor for an important α-chemokine, CXCL12 (Sun, 2010). Furthermore, a more recent study concluded that CXCR4 plays a crucial role in cancer proliferation, dissemination and invasion and the inhibition of CXCR4 strongly affects prostate cancer metastatic disease (Gravina, 2015). The chief officer of Massachusetts based X4 Pharmaceuticals company recently stated that CXCR4 protein “acts as a beacon to attract cells to surround a tumor, effectively hiding the tumor from the body’s T cells that would otherwise destroy them”. He indicated that X4 company is beginning human trials using CXCR4 inhibitors which aims to develop a therapy to block the protein, CXCR4 (http://pharmaceuticalintelligence.com/2015/12/15/are-cxc4-antagonists-making-a-comebackin-cancer-chemotherapy, 2015).
https://www.slideshare.net/dsairamsairam/warburg-effect
- 1. Warburg Effect Presented By: D.Sairam Course : Fundamentals of Biology- Life Sciences Course Code: BSBT-201 Course Instructor: Dr. Subhabrata Kar Presentation Code: U3P1
- 2. Overview Ø Introduction Ø Causes of Warburg Effect Ø Significance of Warburg Effect ØReferences
- 3. Introduction • Warburg, considered by many the pre-eminent bio chemist of the first half of the twentieth century, made vital contributions to many other areas of biochemistry, including respiration, photosynthesis, and the enzymology of intermediary metabolism. • In the mid 1920s Warburg and co-workers showed that, under Aerobic conditions, tumour tissues metabolize approximately tenfold more glucose to lactate in a given time than normal tissues. • This phenomenon later came to be known as “Warburg Effect”. • Warburg purified and crystallized seven of the enzymes of glycolysis. He used a tool called as “ Warburg Manometer” which measured directly the consumption of oxygen by monitoring changes in gas volume, and therefore allowed quantitative measurement of any enzyme with oxidase activity.
- 4. Note: Warburg Effect in Plant Physiology and Oncology are different • In Plant physiology, Warburg Effect refers to the phenomenon in which Oxygen acts as a competitive inhibitor to Carbon dioxide fixation under the influence of RuBisCO, which initiates photosynthesis. Source : Bild-1928
- 5. Comparison of Glycolysis between a Normal Tissue and Tumour/ Proliferated Tissue • http://pharmaceuticalintelligence.com/2012/10/17/is-the- warburg-effect-the-cause-or-the-effect-of-cancer-a-21st- century-view/
https://prezi.com/rbtv_450s3wd/eml4-alk-fusion-gene/
EML4-ALK fusion gene
Published with reusable license by Camille Kawawa-Beaudan
July 2, 2015
Sasaki, Takaaki, Scott J. Rodig, Lucian R. Chirieac, and Pasi A. Janne. “The Biology and Treatment of EML4-ALK Non-Small Cell Lung Cancer.” NCBI. US National Library of Medicine, 24 Apr. 2010. Web. 30 June 2015. <http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC2888755%2F>.
Shaw, Alice T., and Benjamin Solomon. “Targeting Anaplastic Lymphoma Kinase in Lung Cancer.” Clinical Cancer Research. N.p., 2 Feb. 2011. Web. 30 June 2015. <http%3A%2F%2Fclincancerres.aacrjournals.org%2Fcontent%2F17%2F8%2F2081.full>.
Webb, Thomas R., Jake Slavish,et al. “Anaplastic Lymphoma Kinase: Role in Cancer Pathogenesis and Small-molecule Inhibitor Development for Therapy.” Expert Review of Anticancer Therapy. U.S. National Library of Medicine, 1 Jan. 2010. Web. 30 June 2015. <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2780428/>.
Webb, Thomas R., Jake Slavish, et al. “Anaplastic Lymphoma Kinase: Role in Cancer Pathogenesis and Small-molecule Inhibitor Development for Therapy.” Expert Review of Anticancer Therapy. U.S. National Library of Medicine, 1 Jan. 2010. Web. 30 June 2015. <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2780428/>.
| GENEREGULATION,Deciphering the code of gene regulation using massively parallel assays of designed sequence libraries,http://pharmaceuticalintelligence.com/tag/transcription/page/2/,0 | |
| EXACTA, |
https://tginnovations.wordpress.com/2012/05/08/cancer/
Cancer
MAY 8, 2012 · TGI – BIOMARKERS, TGI – CANCER, TGI – EPIGENETICS, TGI – HEALTH, TGI – INTEGRATIVE MEDICINE, TGI – MASS SPECTROMETRY
AUTHORS
2 Votes
Cancer is a broad group of various diseases involving unregulated cell growth. It is medically known as a malignant neoplasm. In cancer, cells divide and grow uncontrollably and invade nearby parts of the body. The cancer may also spread to more distant parts of the body through the lymphatic system or bloodstream, it is called metastasis. However, not all tumors are cancerous. Some tumors do not grow uncontrollably, do not invade neighboring tissues, and do not spread throughout the body which are called Benign tumors.
There are more than 100 types of Cancers. Follow the link to know more:
http://www.cancer.gov/cancertopics/types/alphalist
Main sites of metastases for some common cancer types. Primary cancers are denoted by “…cancer” and their main metastasis sites are denoted by “…metastases”. List of included entries and references is found on main image page in Commons: (Photo credit: Wikipedia)
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https://www.minipiginfo.com/mini-pig-cancer.html
Cancer and pigs
Pig cancer has been widely studied because pigs cancer advantages include the resemblance in anatomy, physiology, and genetic makeup with the human, as well as new methods to manipulate the pig genome. So there is alot of research that continues to be done with regards to pigs and cancer. Some of the articles are older and additonal research has been done, but the studies have not been published publicly, so I am including links to studies that can be viewed by anyone. I do have access to some studies that are published on sites only healthcare personnel can access. These are just a few things you should be aware of when adding a pig to your family. This does not mean your pig may get cancer, but it is certainly a possibility. In the past 15 years (2001–2016), the incidence of reported neoplasia in pet pot-bellied pigs has increased, mostly as a consequence of increased life spans resulting from improved veterinary medical care.
Pigs are predisposed to some genetic cancers as well as other types of cancer. Reproductive cancer is extremely common in pigs that were never spayed/neutered, but especially in the females. I have seen research studies indicating a percentage as high as 75% of ALL females will develop some kind of neoplasm or tumor in the reproductive organs as they age, which is why we let others know the importance of spaying and neutering your pig. These pigs age data were available for 27 of the 32 pigs and ranged from 4 months to 19 years. The study is linked below from Sage Pub.
Sources:
https://www.ccsi.ca/reports/Melanoma_article.pdf
https://pharmaceuticalintelligence.com/2013/10/10/the-scid-pig-how-pigs-are-becoming-a-great-alternate-model-for-cancer-research/
http://journals.sagepub.com/uterine-cancer-in-pigs/full
https://www.ncbi.nlm.nih.gov/pigs-in-research-article
http://pubmedcentralcanada.ca/lukemia-in-mini-pigs/articles
https://www.ncbi.nlm.nih.gov/pmc/hepatocellular-carcinoma-potbellied-pig/articles
http://journals.sagepub.com/full/hepatocelluar-carcinoma-potbellied-pigs
http://journals.sagepub.com/doi/full/oral-squamous-cell-carcinoma-in-potbellied-pig
http://journals.sagepub.com/doi/pdf/gastric-carcinoma-in-mini-pigs
http://illinoisjltp.com/journal/wp-content/uploads/2014/12/Mehta.pdf
But, one key distinction between the Biologics Price Act and the HatchWaxman Act that deserves some attention is that even though the current FDA Draft guidelines are silent on the issue of labeling requirements for follow-on biologic drugs, it is most likely that the FDA will not only permit, but will require follow-on biologic drug manufacturers to maintain warning labels that are unique. (117) What this means is that brand-name biologic drug
- It is worth emphasizing that there is a normative debate amongst industry as to whether follow-on biologics should have unique names. See Biosimilars: Intellectual Property Creation and Protection by Pioneer and by Biosimilar Manufacturers, LEADERS IN PHARMACEUTICAL BUS. INTELLIGENCE, http://pharmaceuticalintelligence.com/tag/BiologicsPriceAct/ (last visited Oct. 27, 2014) (“Having unique names will avoid unintended substitution, minimize risk of medication errors, allow for essential elements of pharmacovigilance such as traceability and follow-up of adverse drug reactions, as well as facilitate prescriberpatient decision making . . . .”). However, the debate seems to be tipping in favor of requiring unique labeling as opposed to identical labeling. See id (“[W]hile all biologics should be uniquely tracked, biosimilars should not require unique International Nonproprietary Names (INNs) from their reference products.
https://www.pharmatutor.org/articles/breakthroughs-in-epigenetics
ABOUT AUTHORS:
Shashi Shekhar Anand, Navgeet, Balraj Singh Gill*
Centre for Biosciences,
School of Basic and Applied Sciences,
Central University of Punjab, Bathinda, India
gillsinghbalraj@gmail.com
ABSTRACT
The word ‘epigenetic’ was first coined by Conrad Waddington in 1946. It deals with functionally relevant modifications to the genome that do not include a change in the nucleotide sequence. Till date observation has focused on the functions of genome sequences and how their regulation occurs. The emerging epigenetic changes and the interactions between cis-acting elements with protein factors plays a central role in gene regulation as well as give insight to various diseases. To evaluate the crosstalk of DNA and protein by taking account of the whole genome, one new evolving technique which is called as ChIP-chip, works on the principle of combining chromatin immunoprecipitation with microarray. ChIP-chip has been recently used in basic biological studies and may be improved further and can be useful for other to aspects, like human diseases. Now a days large amount of discoveries by ChIP-chip and other high-throughput techniques like this may be connected with evolving bioinformatics to add to our knowledge of life and diseases.
Histone Phosphorylation
Histone Phosphorylation is the modification in which there is an addition of a phosphate group. Phosphorylation is catalyzed by the various specific protein kinases, whereas phosphatases mediate removal of the phosphate group (Figure 5). The most studied sites of histone phosphorylation are the serine. Phosphorylation of histones can also be a vital regulatory signal. H2A variant, H2AX that helps in the DNA repair by the process of phosphorylation. It has an important role in DNA damage response and DNA repair.
Fig 5. Phosphorylation of serine chain
Fig.source:pharmaceuticalintelligence.com
Histone H3 phosphorylation has been reported to play important roles in both transcription and chromatin condensation during mitosis.
Archives of Medicine
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Ca2+-Stimulated Exocytosis: The Role of Calmodulin and Protein Kinase C in Ca2+ Regulation of Hormone and Neurotransmitter
Larry H Bernstein*
New York Methodist Hospital, Brooklyn, New York, USA
Corresponding Author:
Larry H Bernstein
New York Methodist Hospital
Brooklyn, New York, USA
Tel: 2032618671
E-mail: larry.bernstein@gmail.com
Visit for more related articles at Archives of Medicine
Abstract
This is a review of the role of calmodulin and protein kinase C inregulation of Ca++ – stimulated secretion. The molecular mechanisms underlying the Ca2+ regulation of hormone and neurotransmitter release are largely unknown. Using a reconstituted [3H] norepinephrine release assay in permeabilized PC12 cells, we found essential proteins that support the triggering stage of Ca2+-stimulated exocytosis are enriched in an EGTA extract of brain membranes. Fractionation of this extract allowed purification of two factors that stimulate secretion in the absence of any other cytosolic proteins. These are calmodulin and protein kinase Ca (PKCa). Their effects on secretion were confirmed using commercial and recombinant proteins. Calmodulin enhances secretion in the absence of ATP, whereas PKC requires ATP to increase secretion, suggesting that phosphorylation is involved in PKC-mediated stimulation but not calmodulin mediated stimulation. Both proteins modulate the half-maximal increase was elicited by 3 nM PKC and 75 nM calmodulin. These results suggest that calmodulin and PKC increase Ca2+-activated exocytosis by directly modulating the membrane- or cytoskeleton-attached exocytic machinery downstream of Ca2+ elevation.
Ca2+-Stimulated Exocytosis: The Role of Calmodulin and Protein Kinase C in Ca2+ Regulation of Hormone and Neurotransmitter
Writer and Curator: Larry H Bernstein, MD, FCAP
and
Curator and Content Editor: Aviva Lev-Ari, PhD, RN
Government Repositories Using our Curations
ClinicalTrials.gov
https://clinicaltrials.gov/ct2/history/NCT02835716?V_3=View
one of our articles used as a reference for this clinical trial entry
see below
Links:URL: http://print.ispub.com/api/0/ispub-article/7521
Description: Multidimensional Representation of Concepts as Cognitive Engrams in the Human Brain
URL: http://ispub.com/IJH/8/1/9567
Description: Evaluation of Cognitive Impairment
URL: https://pharmaceuticalintelligence.com/2013/02/27/ustekinumab-new-drug-therapy-for-cognitive-decline-resulting-from-neuroinflammatory-cytokine-signaling-and-alzheimers-disease/
Description: Ustekinumab New Drug Therapy for Cognitive Decline resulting from Neuroinflammatory Cytokine Signaling and Alzheimer’s Disease
Available IPD/Information:
Submitted Date: September 10, 2016 (v3)
2012pharmaceutical
Amandeep Kaur
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