Progressive Multifocal Leukoencephalopathy in a Patient with Alzheimer??s Disease

Mb, Kelleher; Galutira, Dante; Td, Duggan; Gj, Nuovo

doi:10.1097/00019606-199406000-00007

Cited by 9 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Of these, 14 were HIV-seronegative, and 19 had not been tested (marked by an asterisk in table 1), including 12 diagnosed as having PML before the beginning of the AIDS epidemic in 1984 3–32. There were five patients with kidney disease (no 1–5),4 11 14 19 20 five patients with liver disease (no 5–8 and no 10),5 13 20 27 30 two pregnant women (no 13–14),22 24 two patients with dementia (no 15–16)16 32 and 20 other cases (no 9, no 11–12 and no 17–33) 3 6–10 12 15 17 18 21 23 25–29 31. Of note, case no 5 had kidney failure and liver cirrhosis, and is therefore counted once in each category.…”

Section: Results and Review Of Literaturementioning

confidence: 99%

Progressive multifocal leukoencephalopathy in individuals with minimal or occult immunosuppression

Gheuens

Pierone

Peeters

et al. 2009

Journal of Neurology, Neurosurgery & Psychiatry

170

131

View full text Add to dashboard Cite

Background-Progressive multifocal leukoencephalopathy (PML) is a deadly demyelinating disease of the brain, caused by reactivation of the polyomavirus JC (JCV). PML has classically been described in individuals with profound cellular immunosuppression such as patients with AIDS, hematological malignancies, organ transplant recipients or those treated with immunosuppressive or immunomodulatory medications for autoimmune diseases.

show abstract

Section: Results and Review Of Literaturementioning

confidence: 99%

Progressive multifocal leukoencephalopathy in individuals with minimal or occult immunosuppression

Gheuens

Pierone

Peeters

et al. 2009

Journal of Neurology, Neurosurgery & Psychiatry

170

131

View full text Add to dashboard Cite

show abstract

“…With checking "ENCODE and ChEA Consensus TFs from ChIP-X" category in Enrichr, we found that the target genes of TFs, MYC, NELFE, TAF7, KAT2A, SPI1, RELA, TAF1 and PML are top ranked ten TFs associated with adjusted P -values less than 1 × 10 −7 (They are less than ten, because some are ranked in multiple times within top 10). Among them, MYC [30], KAT2A [31], SPI1 [32], RELA [33], TAF1 [34], and PML [35] were reported to be related to AD. These TFs were also identified within top ranked 10 TFs, with other two additional threshold P-values, less than 0.005 and 0.05, with similar associated adjusted P-values; no additional TFs were ranked within top 10.…”

Section: Application Of Hosvd To Real Data Setmentioning

confidence: 99%

Neurological Disorder Drug Discovery from Gene Expression with Tensor Decomposition

Taguchi

Turki

2020

CPD

View full text Add to dashboard Cite

Background: Identifying effective candidate drug compounds in patients with neurological disorders based on gene expression data is of great importance to the neurology field. By identifying effective candidate drugs to a given neurological disorder, neurologists would (1) reduce the time searching for effective treatments; and (2) gain additional useful information that leads to a better treatment outcome. Although there are many strategies to screen drug candidate in pre-clinical stage, it is not easy to check if candidate drug compounds can also be effective to human. Objective: We tried to propose a strategy to screen genes whose expression is altered in model animal experiments to be compared with gene expressed differentially with drug treatment to human cell lines. Methods: Recently proposed tensor decomposition (TD) based unsupervised feature extraction (FE) is applied to single cell (sc) RNA-seq experiments of Alzheimer’s disease model animal mouse brain. Results: Four hundreds and one genes are screened as those differentially expressed during A946 accumulation as age progresses. These genes are significantly overlapped with those expressed differentially with the known drug treatments for three independent data sets: LINCS, DrugMatrix, and GEO. Conclusion: Our strategy, application of TD based unsupervised FE, is useful one to screen drug candidate compounds using scRNA-seq data set.

show abstract

“…With checking "ENCODE and ChEA Consensus TFs from ChIP-X" category in Enrichr, we found that 313 the target genes of TFs, MYC, NELFE, TAF7, KAT2A, SPI1, RELA, TAF1 314 and PML are top ranked ten TFs associated with adjusted P -values less than 315 1 × 10 −7 (They are less than ten, because some are ranked in multiple times 316 within top 10). Among them, MYC [30], KAT2A [31], SPI1 [32], RELA [33], 317 TAF1 [34], and PML [35] were reported to be related to AD. These TFs were 318 also identified within top ranked 10 TFs, with other two additional threshold 319 P-values, less than 0.005 and 0.05, with similar associated adjusted P-values; 320 no additional TFs were ranked within top 10.…”

mentioning

confidence: 99%

Neurological disorder drug discovery from gene expression with tensor decomposition

Taguchi

Turki

2019

Preprint

View full text Add to dashboard Cite

1Background: Identifying effective candidate drug compounds in patients 2 with neurological disorders based on gene expression data is of great im-3 portance to the neurology field. By identifying effective candidate drugs 4 to a given neurological disorder, neurologists would (1) reduce the time 5 searching for effective treatments; and (2) gain additional useful informa-6 tion that leads to a better treatment outcome. Although there are many 7 strategies to screen drug candidate in pre-clinical stage, it is not easy to 8 check if candidate drug compounds can be also effective to human. 9Objective: We tried to propose a strategy to screen genes whose expres-10 sion is altered in model animal experiments to be compared with gene 11 expressed differentically with drug treatment to human cell lines. 12 Methods: Recently proposed tensor decomposition (TD) based unsu-13 pervised feature extraction (FE) is applied to single cell (sc) RNA-seq 14 experiments of Alzheimer's disease model animal mouse brain. 15 Results: Four hundreds and one genes are screened as those differentially 16 expressed during Aβ accumulation as age progresses. These genes are sig-17 nificantly overlapped with those expressed differentially with the known 18 drug treatments for three independent data sets: LINCS, DrugMatrix and 19 GEO.20 Conclusion: Our strategy, application of TD based unsupervised FE, is 21 useful one to screen drug candidate compounds using scRNA-seq data set. 22 keywords: Amyloid, Alzheimer Disease, Gene Expression, Single-Cell Anal-23 ysis, Drug Discovery, Cell Line 24 1 Introduction 25 Drug discovery for neurological disorder has never been successful in spite of 26 massive efforts spent [1]. One possible reason is because we generally do not 27 1 have suitable model animals for human neurological disorder [2]. Although a 28 huge number of compounds are screened using model animals, only a few of 29 them passed the human level screening. In this sense, it is required to screen 30 candidate compounds using information retrieved from human at the earliest 31 stage. One possible strategy to do this is the usage of human cell lines; Nev-32 ertheless, it is also not easy to perform, since generating cell line from human 33 neurological disorder patients is not easy. In contrast to the cancer cell lines, 34 which can be easily generated by immortalizing tumor cells, neuronal cells are 35 hardly converted to cell lines, since mature neurons do not undergo cell divi-36 sion [3]. Therefore, it is difficult to test if candidate drugs work for human 37 during pre-clinical stages. 38 In order to overcome this difficulty, we proposed an alternative strategy; com-39 paring disease gene expression with that of compound treated animals and/or 40 human cell lines. Generally, compound screening is based upon phenotype; i.e., 41 evaluation of compounds efficiency is tested based upon if drug treatment can 42 produce symptomatic improvement. Nevertheless, since it has been recently 43 found that various neurological disorders share gene expre...

show abstract

Progressive Multifocal Leukoencephalopathy in a Patient with Alzheimer??s Disease

Cited by 9 publications

References 0 publications

Progressive multifocal leukoencephalopathy in individuals with minimal or occult immunosuppression

Progressive multifocal leukoencephalopathy in individuals with minimal or occult immunosuppression

Neurological Disorder Drug Discovery from Gene Expression with Tensor Decomposition

Neurological disorder drug discovery from gene expression with tensor decomposition

Contact Info

Product

Resources

About