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What's The Big Data?

Terence Parr: “I am a computer scientist retooling as a machine learning droid and have found the nomenclature used by statisticians to be peculiar to say the least, so I thought I’d put this document together. It’s meant as good-natured teasing of my friends who are statisticians, but it might actually be useful to other computer scientists. I look forward to a corresponding document written by the statisticians about computer science terms!” (Statisticians say the darndest things)

I know of at least one corresponding document, published in 1994 with the rise of Neural Networks or what I have called Statistics on Steroids (SOS), which are responsible, to a large extent, to the success of today’s “AI” or Deep Learning, an advanced version of machine learning.

In Neural Networks and Statistical Models (1994), Warren Sarle explained to his worried and confused fellow statisticians that the ominous-sounding artificial neural…

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Healing traumatic brain injuries with self-assembling peptide hydrogels

Reporter : Irina Robu, PhD

In 2014, TBIs resulted in about 2.53 million emergency department visits in the U.S., according to the Centers for Disease Control and Prevention. A traumatic brain injury (TBI) can range from a mild concussion to a severe head injury. It is caused by a blow to the head or body, a wound that breaks through the skull or another injury that jars or shakes the brain. Individuals with traumatic brain injuries can develop secondary disorders after the initial blow. Researchers, Biplab Sarkar and Vivek Kumar from New Jersey Institute of Technology are hoping to prevent secondary disorders by injecting a self-assembling peptide hydrogel into the brains of rats with traumatic brain injury and see what happens. They observed that the hydrogel helped blood vessels regrow in addition to neuronal survival.

The researchers explained that after traumatic brain injury, the brain can amass glutamate which kills some neurons which is marked by overactive oxygen-containing molecules (oxidative stress), inflammation and disruption of the blood-brain barrier. Furthermore, TBI survivors can experience impaired motor control and depression. Within the experiment, the researchers showed that a week after injecting the gel in rats, the neurons have twice as many neurons at the injury site than the control animals did.

The NJIT researchers distinguished that they needed to inject the hydrogel directly in a rat’s brain just seconds after a TBI, which is not ideal, because it would be impossible to give a patient the treatment within that short period of time. The next step in showing that the self-assembling peptide hydrogel works is to combine their previous blood vessel-growing peptide and the new version to see whether it could enhance recovery. And the researchers plan to inspect whether the hydrogels work for more diffuse brain injuries such as concussions.

SOURCE

https://www.fiercebiotech.com/research/healing-traumatic-brain-injuries-self-assembling-peptide-hydrogels

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Using A.I. to Detect Lung Cancer gets an A!

Reporter: Irina Robu, PhD

Google researchers hypothesized that computers are as good or better than doctors at detecting tiny lung cancers on CT scans, since CT scan combines data from several X-rays to produce a detailed image of a structure inside the body. CT scans produce 2-dimensional images of a slice of the body and the data can also be used to construct 3-D images.

However, the technology published in Nature Medicine offers input in the future of artificial intelligence in medicine. By feeding vast amounts of data from medical imaging into systems called artificial neural networks, scientists can teach computers to identify patterns linked to a specific condition, like pneumonia, cancer or a wrist fracture that would be hard for a person to see. The system trails an algorithm, or set of instructions, and learns as it goes. The more data it receives, the better it becomes at interpretation.

The process, known as deep learning enables computers to identify objects and understand speech but it also created systems to help pathologists read microscope slides to diagnose cancer, and to help ophthalmologists detect eye disease in people with diabetes. In their recent study, the scientist used artificial intelligence to CT scans used to screen people for lung cancer, which caused 160,000 deaths in the United States last year, and 1.7 million worldwide. The scans are recommended for people at high risk because of a long history of smoking.

Screening studies showed that it can reduce the risk of dying from lung cancer and can also identify spots that might later become cancer, so that radiologists can categorize patients into risk groups and decide whether they need biopsies or more frequent follow-up scans to keep track of the suspect regions.

However, the test has errors. It can miss tumors or mistake benign spots for malignancies and shove patients into invasive, risky procedures like lung biopsies or surgery.

SOURCE

https://www.nytimes.com/2019/05/20/health/cancer-artificial-intelligence-ct-scans.html

Other related articles were published in this Online Scientific Open Access Journal including the following:

https://pharmaceuticalintelligence.com/2019/07/21/multiple-barriers-identified-which-may-hamper-use-of-artificial-intelligence-in-the-clinical-setting/

https://pharmaceuticalintelligence.com/2019/06/28/ai-system-used-to-detect-lung-cancer/

 

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Artificial throat may give voice to the voiceless

Reporter
Irina Robu, PhD

Flexible sensors have fascinated more and more attention as a fundamental part of anthropomorphic robot research, medical diagnosis and physical health monitoring. The fundamental mechanism of the sensor is based on triboelectric effect inducing electrostatic charges on the surfaces between two different materials. Just like a plate capacitor, current is produced while the size of the parallel capacitor fluctuations caused by the small mechanical disturbances and therefore the output current/voltage is produced.

Chinese scientists combine ultra sensitive motion detectors with thermal sound-emitting technology invented an “artificial throat” that could enable speech in people with damaged or non-functioning vocal cords. Team members from University in Beijing, fabricated a homemade circuit board on which to build out their dual-mode system combining detection and emitting technologies.

Graphene is a wonder material because it is thinnest material in the universe and the strongest ever measured. And graphene is only a one-atom thick layer of graphite and possess a high Young’s modulus as well as superior thermal and electrical conductivities. Graphene-based sensors have attracted much attention in recent years due to their variety of structures, unique sensing performances, room-temperature working conditions, and tremendous application prospects.

The skin like device, wearable artificial graphene throat (WAGT) is as similar as a temporary tattoo, at least as perceived by the wearer. In order to make the device functional and flexible, scientists designed a laser-scribed graphene on a thin sheet of polyvinyl alcohol film. The device is the size of two thumbnails side by side and can use water to attach the film to the skin over the volunteer’s throat and connected to electrodes to a small armband that contained a circuit board, microcomputer, power amplifier and decoder. At the development phase, the system transformed subtle throat movements into simple sounds like “OK” and “No.” During the trial of the device, volunteers imitated throat motions of speech and the device converted these movements into single-syllable words.

It is believed that this device, would be able to train mute people to generate signals with their throats and the device would translate signals into speech.

SOURCE
https://www.aiin.healthcare/topics/robotics/artificial-throat-may-give-voice-voiceless?utm_source=newsletter

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Merck KGaA-owned Sigma-Aldrich has petitioned the US Patent and Trademark Office (USPTO) to open an interference proceeding between its own pending CRISPR-Cas9 patents and patents awarded to the University of California, Berkeley (UC Berkeley).

On Friday, July 19, Sigma-Aldrich submitted the request, available on blog PatentDocs, asking for a parallel interference to the one declared by the USPTO in June between UC Berkeley and the Broad Institute of MIT and Harvard.

Sigma-Aldrich recognizes, of course, that its pending applications’ claims have not yet been allowed, and thus declaring a patent interference now would – in ordinary U.S. Serial Nos. 15/188,911; 15/188,924; & 15/456,204 -2- circumstances – be premature. However, the facts here are truly extraordinary, and Sigma-Aldrich feels compelled to apprise the Director and the CAPJ of the current situation and to briefly explain why the PTAB’s declaration of a parallel interference in this instance would be in the long-term best interests of everyone, including the USPTO, the parties, and the public. Indeed, the sole issue raised by this Petition has already been effectively decided by both the PTAB and the Federal Circuit, and those decisions completely support Sigma-Aldrich’s request here; namely, does UC’s disclosure of CRISPR-Cas9 in in vitro cell-free and nucleus-free test tube environments (hereinafter, “prokaryotic environment”) render obvious claims directed to CRISPR-Cas9 in eukaryotic cells? The controlling answer to this question is decidedly “no.” SigmaAldrich respectfully submits that the PTAB’s and the Federal Circuit’s “no” answer compels the grant of this Petition. The following timeline – which shows the 2012 and early-2013 provisional applications of Sigma-Aldrich, UC, and Broad Inst. – is relevant to the issues presented.

https://patentdocs.typepad.com/files/181_petition.pdf

 

In June, the office revived the dispute between the Broad Institute and UC Berkeley over which first invented the CRISPR gene-editing technology by announcing that it would conduct an interference proceeding between 13 patents and one application to the Broad Institute and ten patent applications filed by UC Berkeley.

All of the Broad Institute and UC Berkeley patents and applications cover the use of CRISPR/Cas9 in eukaryotic cells.

Sigma-Aldrich’s pending patent applications (serial numbers 15/188,911, 15/456,204, and 15/188,924) are also directed to CRISPR-Cas9-based methods in eukaryotic cells.

“Of critical importance here, Sigma-Aldrich’s benefit applications pre-date the earliest possible benefit applications involved in the UC Berkeley v Broad Institute interference with respect to their respective disclosures of CRISPR-Cas9 in eukaryotic cells,” said Sigma-Aldrich in its petition.

The Merck-owned unit said that it “feels compelled to apprise the director and the chief administrative patent judge (CAPJ) of the current situation and to briefly explain why the Patent Trial and Appeal Board’s (PTAB) declaration of a parallel interference in this instance would be in the long-term best interests of everyone, including the USPTO, the parties, and the public”.

Sigma-Aldrich went on to claim that the sole issue raised by the petition has already been effectively decided by both the PTAB and the US Court of Appeals for the Federal Circuit.

‘Treated unfairly’

In February 2017, the PTAB held that the Broad Institute’s patents—which are all limited to CRISPR/Cas9 systems in a eukaryotic environment—do not interfere with patent claims (which are not restricted to any environment) filed by UC Berkeley and the University of Vienna.

UC Berkeley and the University of Vienna appealed against the decision, asking the Federal Circuit to determine whether the PTAB committed error in “ignoring overwhelming evidence” that the Broad Institute’s claims are obvious in light of UC Berkeley’s.

The PTAB’s finding was affirmed by the Federal Circuit in September 2018.

“Sigma-Aldrich respectfully submits that the PTAB’s and the Federal Circuit’s ‘no’ answer compels the grant of this petition,” said the Merck subsidiary.

Sigma-Aldrich has claimed that the USPTO is treating it “very differently and unfairly” when compared to the agency’s treatment of the Broad Institute and UC Berkeley.

It said: “Indeed, the USPTO has now granted Broad Inst over a dozen issued patents. In direct contrast, the USPTO continues to reject Sigma-Aldrich’s CRISPR-Cas9 eukaryotic claims as not patentable over those same UC CRISPR-Cas9 prokaryotic provisional applications that the USPTO has repeatedly found have been successfully overcome by Broad Inst’s eukaryotic claims.”

The petition claimed that this “blatant inconsistency” and the unfairness to Sigma-Aldrich could not be “more palpable”.

“In today’s highly charged political environment, certainly the director and CAPJ are sensitive to criticism levelled at the agency regarding issues of fairness and equity, eg whether the USPTO provides ‘a level playing field’,” added the petition.

A spokesperson for the Broad Institute said: “It is time for certainty around CRISPR and for the parties to come together to resolve these disputes and to simplify access to this important technology.”

Sigma-Aldrich is part of Merck’s life science business and, in combination with Merck’s other acquisition Millipore, operates as MilliporeSigma in North America.

A spokesperson for UC Berkeley said: “We remain confident that the USPTO will ultimately recognise that the Doudna and Charpentier team hold the priority of invention specific to the CRISPR-Cas9 gene-editing technology in eukaryotic cells, as well as other settings covered by the Doudna-Charpentier team’s previous patents.”

 

Keywords

Sigma-Aldrich, Merck KGaA, USPTO, CRISPR, Broad Institute, UC Berkeley, MIT, Harvard, Cas9, patent, genome editing

 

SOURCE

https://www.lifesciencesipreview.com/news/sigma-aldrich-submits-crispr-petition-at-uspto-3615

 

Other related articles published in these Open Access Online Scientific Journal include the following:

Multiple UPDATES for original article of April 13, 2017

UPDATED – Gene Editing Consortium of Biotech Companies: CRISPR Therapeutics $CRSP, Intellia Therapeutics $NTLA, Caribou Biosciences, ERS Genomics, UC, Berkeley (Doudna’s IP) and University of Vienna (Charpentier’s IP), is appealing the decision ruled that there was no interference between the two sides, to the U.S. Court of Appeals for the Federal Circuit, targeting patents from The Broad Institute.

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/04/13/gene-editing-consortium-of-biotech-companies-crispr-therapeutics-crsp-intellia-therapeutics-ntla-caribou-biosciences-and-ers-genomics-uc-berkeley-doudnas-ip-and-university-of-vienna-charpe/

Part 2: CRISPR in 

Genomics Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology

https://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/volume-two-genomics-methodologies-ngs-bioinformatics-simulations-and-the-genome-ontology/

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scPopCorn: A New Computational Method for Subpopulation Detection and their Comparative Analysis Across Single-Cell Experiments

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Present day technological advances have facilitated unprecedented opportunities for studying biological systems at single-cell level resolution. For example, single-cell RNA sequencing (scRNA-seq) enables the measurement of transcriptomic information of thousands of individual cells in one experiment. Analyses of such data provide information that was not accessible using bulk sequencing, which can only assess average properties of cell populations. Single-cell measurements, however, can capture the heterogeneity of a population of cells. In particular, single-cell studies allow for the identification of novel cell types, states, and dynamics.

 

One of the most prominent uses of the scRNA-seq technology is the identification of subpopulations of cells present in a sample and comparing such subpopulations across samples. Such information is crucial for understanding the heterogeneity of cells in a sample and for comparative analysis of samples from different conditions, tissues, and species. A frequently used approach is to cluster every dataset separately, inspect marker genes for each cluster, and compare these clusters in an attempt to determine which cell types were shared between samples. This approach, however, relies on the existence of predefined or clearly identifiable marker genes and their consistent measurement across subpopulations.

 

Although the aligned data can then be clustered to reveal subpopulations and their correspondence, solving the subpopulation-mapping problem by performing global alignment first and clustering second overlooks the original information about subpopulations existing in each experiment. In contrast, an approach addressing this problem directly might represent a more suitable solution. So, keeping this in mind the researchers developed a computational method, single-cell subpopulations comparison (scPopCorn), that allows for comparative analysis of two or more single-cell populations.

 

The performance of scPopCorn was tested in three distinct settings. First, its potential was demonstrated in identifying and aligning subpopulations from single-cell data from human and mouse pancreatic single-cell data. Next, scPopCorn was applied to the task of aligning biological replicates of mouse kidney single-cell data. scPopCorn achieved the best performance over the previously published tools. Finally, it was applied to compare populations of cells from cancer and healthy brain tissues, revealing the relation of neoplastic cells to neural cells and astrocytes. Consequently, as a result of this integrative approach, scPopCorn provides a powerful tool for comparative analysis of single-cell populations.

 

This scPopCorn is basically a computational method for the identification of subpopulations of cells present within individual single-cell experiments and mapping of these subpopulations across these experiments. Different from other approaches, scPopCorn performs the tasks of population identification and mapping simultaneously by optimizing a function that combines both objectives. When applied to complex biological data, scPopCorn outperforms previous methods. However, it should be kept in mind that scPopCorn assumes the input single-cell data to consist of separable subpopulations and it is not designed to perform a comparative analysis of single cell trajectories datasets that do not fulfill this constraint.

 

Several innovations developed in this work contributed to the performance of scPopCorn. First, unifying the above-mentioned tasks into a single problem statement allowed for integrating the signal from different experiments while identifying subpopulations within each experiment. Such an incorporation aids the reduction of biological and experimental noise. The researchers believe that the ideas introduced in scPopCorn not only enabled the design of a highly accurate identification of subpopulations and mapping approach, but can also provide a stepping stone for other tools to interrogate the relationships between single cell experiments.

 

References:

 

https://www.sciencedirect.com/science/article/pii/S2405471219301887

 

https://www.tandfonline.com/doi/abs/10.1080/23307706.2017.1397554

 

https://ieeexplore.ieee.org/abstract/document/4031383

 

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0927-y

 

https://www.sciencedirect.com/science/article/pii/S2405471216302666

 

 

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Engineered Bacteria used as Trojan Horse for Cancer Immunotherapy

Reporter: Irina Robu, PhD

Researchers are using synthetic biology— design and construction of new biological entities such as enzymes, genetic circuits, and cells or the redesign of existing biological systems—is changing medicine leading to innovative solution in molecular-based therapeutics. To address the issue of designing therapies that can induce a potent, anti-tumor immune response researchers at Columbia Engineering and Columbia Irving Medical Center engineered a strain of non-pathogenic bacteria that can colonize tumors in mice. The non-pathogenic bacteria act as Trojan Horse that can lead to complete tumor regression in a mouse model of lymphoma. Their results are currently published in Nature Medicine.

The scientists led by Nicholas Arpaia, used their expertise in synthetic biology and immunology to engineer a strain of bacteria able to grow and multiply in the necrotic core of tumors. The non-pathogenic E. coli are programmed to self-destruct when the bacteria numbers reach a critical threshold, allowing for actual release of therapeutics and averting them from causing havoc somewhere else in the body. Afterward, a small portion of bacteria survive lysis and repopulate the population which allows repeated rounds of drug delivery inside treated tumors.

In the present study, the scientists release a nanobody that targets CD47 protein, which defends cancer cells from being eaten by distinctive immune cells. The mutual effects of bacteria, induced local inflammation within the tumor and the blockage of the CD47 leads to better ingestion and activation of T-cells within the treated tumors. The team deduced that the treatment with their engineered bacteria not only cleared the treated tumors but also reduced the incidence of tumor metastasis.

Before moving to clinical trials, the team is performing proof-of-concept tests, safety and toxicology studies of their immunotherapeutic bacteria in a rand of advanced solid tumor settings in mouse models. They have currently collaborated with Gary Schwartz, deputy director of the Herbert Irving Comprehensive Cancer and have underway a company to translate their promising technology to patients.

SOURCE

Sreyan Chowdhury, Samuel Castro, Courtney Coker, Taylor E. Hinchliffe, Nicholas Arpaia, Tal Danino. Programmable bacteria induce durable tumor regression and systemic antitumor immunity. Nature Medicine, 2019

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