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STRATA+HADOOP WORLD SAN JOSE, Calif., March 14, 2017 (GLOBE NEWSWIRE) -- Cloudera, the company of the main global platform for computing device studying and superior analytics constructed on the latest open supply applied sciences, today unveiled Cloudera records Science Workbench, a brand new self-provider environment for statistics science on Cloudera enterprise which is currently in beta. in response to the company's acquisition of statistics science startup feel.io final year, statistics Science Workbench enables facts scientists to use their favourite open supply languages – together with R, Python, and Scala – and libraries on a comfy enterprise platform with native Apache Spark and Apache Hadoop integration, to speed up analytics tasks from exploration to production.
“Cloudera is focused on improving the consumer adventure for data science and engineering teams, in certain those who need to scale their analytics the usage of Spark for records processing and laptop getting to know,” referred to Charles Zedlewski, senior vice chairman, products at Cloudera. “The acquisition of sense.io and its group offered a strong foundation, and statistics Science Workbench now puts self-service information science at scale close by for our valued clientele.”
Cloudera statistics Science Workbench’s advantages include:
For statistics scientists -
For IT gurus -
As open information science expands past the extensive Python and R ecosystems to consist of deep gaining knowledge of frameworks like Tensorflow, Microsoft Cognitive Toolkit, MXnet, BigDL, and greater, records science groups are seeking for ways to convey these tools to their information, which is increasingly stored in Hadoop environments. Cloudera records Science Workbench grants a secure and relaxed ambiance to combine the latest open supply improvements with the unified platform Cloudera consumers have confidence.
“by featuring equipped access to facts, Cloudera statistics Science Workbench decreases time to price of AI purposes delivered with the DataRobot automated laptop studying platform,” said Jeremy Achin, DataRobot CEO and co-founder. “DataRobot is fully built-in which allows Cloudera users to increase company price from the world's most fulfilling algorithms and information science suggestions via a simple to make use of interface.”
“Our clients’ IT companies often struggle to onboard records scientists to shared environments because their needs are so distinct, specifically where open source tools are concerned. The result is continually duplication, analytic silos, and constrained protection and governance. meanwhile, statistics scientists are perpetually seeking to scale their work to greater datasets and extra powerful compute platforms,” persevered Zedlewski. “With facts Science Workbench, Cloudera is helping IT businesses and statistics scientists work collectively, bringing extra clients to shared environments in a way that offers both flexibility and compliance.”
Meet at Strata + Hadoop World San Jose
To study greater about statistics Science Workbench and Cloudera’s ordinary information science and desktop studying approach, discuss with our booth 809 on the demonstrate ground at Strata+Hadoop World San Jose.
To study about the common complications to seem to be out for when scaling facts science on Hadoop, attend Cloudera’s session titled, ‘Making Self-provider statistics Science a reality’ with Matt Brandwein (director, products, Cloudera), Tristan Zajonc (senior engineering manager, Cloudera) from 1:50pm–2:30pm on Thursday, March sixteen, 2017 in 210 A/E at Strata+Hadoop World San Jose.
Cloudera grants the up to date platform for machine getting to know and advanced analytics constructed on the latest open source applied sciences. the area’s main companies have faith Cloudera to help clear up their most difficult enterprise complications with Cloudera business, the fastest, easiest and most at ease information platform available for the contemporary world. Our purchasers efficiently trap, save, method and analyze great amounts of records, empowering them to make use of superior analytics and laptop researching to force business decisions right now, flexibly and at decrease charge than has been viable before. To be certain our shoppers are a success, we present comprehensive assist, practicing and professional functions. be taught more at cloudera.com.
join with Cloudera
About Cloudera: http://www.cloudera.com/about-cloudera.html
study our blogs: blog.cloudera.com/ and imaginative and prescient.cloudera.com/
follow us on Twitter: twitter.com/cloudera
consult with us on facebook: facebook.com/cloudera
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be a part of the Cloudera neighborhood: neighborhood.cloudera.com
examine our shoppers’ successes: cloudera.com/consumers.html
Cloudera and associated marks are emblems or registered logos of Cloudera Inc. All other enterprise and product names may well be emblems of their respective house owners.
###Press Contact: Deborah Wiltshire Cloudera email@example.com +1 (650) 644-3900
LONDON, may additionally 22, 2018 /PRNewswire/ -- STRATA data -- Cloudera, Inc. (NYSE: CLDR), the up to date platform for computer researching and analytics optimized for the cloud, today introduced new innovations to aid organizations operationalize records insights faster with the aid of making records scientists and statistics engineers extra productive. New desktop getting to know capabilities make it less difficult for data scientists to rapidly instruct and install models with greater self belief and lower risk. big increases in efficiency, scale and ability of Cloudera's modern information platform aid businesses maintain tempo with the explosive boom and variety of data in their enterprise. These new capabilities allow information teams to collaborate greater without difficulty and deliver fashions to creation quicker, enabling secure access to enterprise-scale, excessive-performance statistics and compute, each on-premises and across public clouds.Matt Brandwein, Cloudera's Senior Director of items, shares how Cloudera statistics Science Workbench 1.4 extends the platform adventure from analysis to creation. Now information scientists can build, instruct, and deploy models in a unified workflow with new capabilities. prosperous Kizer, Cloudera’s Director of Cloud earnings, speaks to Cloudera Altus records Engineering for Azure, the industry’s first multi-cloud, multi-characteristic PaaS, which empowers valued clientele to use statistics to pressure consumer insights, connect products and functions, and offer protection to their corporations. Fred Koopmans, Cloudera’s VP Product management, talks about Cloudera enterprise 6.0, the enterprise’s strongest platform for mission-crucial computing device gaining knowledge of and analytics functions, capable of running on-premises, within the cloud, or anyplace the records resides.
click on to tweet: news: @Cloudera empowers corporations to propel their digital transformation with updates to #cloud and #datascience choices: http://bit.ly/2Izoqjc #MachineLearning #Analytics
"We believe information could make what is unattainable today, possible day after today. With more advantageous capabilities in laptop gaining knowledge of, analytics, and cloud, the new software products and cloud services we are asserting will allow our clients to more all of a sudden gain competitive merits in the information financial system," pointed out Tom Reilly, Chief govt Officer at Cloudera. "These enhancements demonstrate Cloudera's commitment to market-main improvements that empower companies to safely transform complex information into clear and actionable insights to propel their digital transformation."
Enhancements announced today consist of:
Cloudera information Science Workbench 1.4 hastens popular Workflows for information Scientists
Cloudera data Science Workbench 1.four extends the self-carrier computer researching platform from analysis to construction. usually, statistics science groups fight to operationalize their work. it be difficult to reliably reproduce or install knowledgeable models without inefficient and error-prone reimplementation. With this newest unencumber, information scientists can run and song versioned experiments, in addition to installation models as leisure APIs with a single click on. statistics groups now have a unified workflow to build, instruct, examine, and install models to construction on a standard, relaxed platform that runs anyplace.
"We're delighted to be launching new capabilities in Cloudera information Science Workbench that speed up normal workflows for information scientists, including experiment management and model deployment, with a seamless adventure that also continues statistics at ease and beneath governance," stated Hilary Mason, GM, computer studying at Cloudera.
Cloudera records Science Workbench 1.four can be purchasable this summer. time table a demo today.
Cloudera Altus Powers machine gaining knowledge of on Microsoft Azure
these days, we are excited to announce Cloudera Altus is now commonly purchasable on Microsoft Azure, making Altus the trade's first multi-cloud, multi-characteristic PaaS. Cloudera Altus offers facts Engineering for Azure, which simplifies and speeds ETL (extract, radically change, load), statistics processing, and batch laptop discovering by reducing complexity, enabling engineers and builders to carry greater distinct facts to records scientists, analytics groups, and downstream information items. Azure consumers can additionally take capabilities of the shared data catalog capabilities in Cloudera Altus SDX (beta), that hold company metadata and protection and governance policies so they will also be utilized always across information processing and analytics workloads in the cloud.
"Cloudera continues to be a strategic associate for us as we build out our cloud-based platform, on the way to guide one in all Europe's biggest and most powerful IoT facts marketplaces," stated Dr. Ingo Hofacker, who's answerable for IoT business at Deutsche Telekom, a client and beta user of Cloudera Altus information Engineering on Azure. "we will set up and run data pipelines that help mission-critical laptop learning and analytics applications readily and at a quicker tempo with Cloudera Altus statistics Engineering on Azure."
Cloudera Altus Analytic DB, the primary information warehouse cloud provider that brings the warehouse to the information, is now additionally available on Microsoft Azure (beta). It gives you quick self-carrier BI and SQL analytics to any person simply, reliably, and securely. moreover, through leveraging Altus SDX, the equal records and catalog are purchasable for analysts, facts scientists, information engineers, and others the use of the tools they choose—SQL, Python, R—all without any data flow.
beginning a 30-day free trial of Cloudera Altus for Microsoft Azure now.
Cloudera's most powerful Platform for computing device getting to know and Analytics
Cloudera business 6.0 can provide enormous advances in performance and enterprise nice, showcasing improvements in search, streaming, scale, and control—all designed to assist organizations operationalize records insights sooner. Cloudera continues to make investments the time and abilities to test, curate and make a contribution to the tasks our customers deem advantageous. The newest liberate is Cloudera's most powerful platform for mission-important machine learning and analytics purposes, in a position to working on-premises, within the cloud, or anywhere the records resides. unlock 6.0 additionally introduces GPU support in the cluster and Hive optimizations to significantly speed up desktop getting to know and information engineering functions as compared to the old release—improving end consumer productiveness and further reducing infrastructure expenses.
"business leaders recognize the intrinsic cost of records, but increasingly, it is fitting tricky if not unattainable for them to take skills of the newest innovations corresponding to machine discovering and precise-time streaming with common, single-goal analytic structures. meanwhile, cloud service providers have stirred up the pot by way of opening the opportunity to mixing and matching components to fit the issue, however, cloud providers lack the potential to deliver a single shared governance ambiance spanning from on-premises to the cloud," observed Tony Baer, essential analyst, IT, at Ovum.
"records is the lifeblood of our company and our trade. Cloudera allows for our information processing and analytics, creating the dimensions to in shape our information boom and the velocity to permit true-time insights in an business-equipped, at ease platform," says Steve Hirsch, Chief information Officer, Intercontinental alternate, mother or father company of the ny stock change.
Cloudera business 6.0 beta edition is attainable now. be part of the beta software today.
About ClouderaAt Cloudera, we consider that records can make what's not possible nowadays, possible the following day. We empower individuals to seriously change advanced records into clear and actionable insights. We bring the contemporary platform for laptop studying and analytics optimized for the cloud. the area's largest organisations believe Cloudera to aid solve their most challenging enterprise complications. be taught extra at www.cloudera.com.
join with ClouderaAbout Cloudera: cloudera.com/about-cloudera.html read our imaginative and prescient blog: vision.cloudera.com/ and Engineering blog: weblog.cloudera.com/ comply with us on Twitter: twitter.com/cloudera seek advice from us on fb: facebook.com/cloudera See us on YouTube: youtube.com/consumer/clouderahadoop be a part of the Cloudera neighborhood: group.cloudera.com/ read about our clients' successes: cloudera.com/greater/consumers.html
Cloudera and linked marks are emblems or registered logos of Cloudera, Inc. All other company and product names may well be emblems of their respective house owners.
source Cloudera, Inc.related hyperlinks
application enterprise Cloudera nowadays introduced a slew of laptop gaining knowledge of product updates at the Strata records London conference: Cloudera statistics Science Workbench 1.4, Cloudera Altus facts Engineering on Microsoft Azure, and Cloudera business 6.0. All three are concentrated on facilitating collaboration amongst statistics groups, CEO Tom Reilly talked about.
“We consider facts can make what's impossible these days feasible day after today. With more suitable capabilities in computer gaining knowledge of, analytics, and cloud, the brand new software items and cloud features we are announcing will enable our consumers to greater unexpectedly profit aggressive advantages within the records economic climate,” Reilly talked about in a statement. “These enhancements reveal Cloudera’s commitment to market-leading improvements that empower organizations to securely radically change advanced statistics into clear and actionable insights to propel their digital transformation.”
Cloudera Altus facts Engineering on Azure went are living the previous day with assist for Apache Spark, Apache Hive, Hive on Spark, and MapReduce 2. Cloud enterprise 6.0 and Altus Analytic DB can be found in beta these days, while statistics Science Workbench 1.4 is expected to launch this summer time.
statistics Science Workbench permits records science groups to construct, run, coach, compare, and put in force desktop studying models on a single platform. version 1.four elements an more desirable toolkit for operating and tracking experiments and a one-click on device that enables clients to set up fashions as Representational State transfer (leisure) APIs for networked functions.
Cloudera Atlus is a bit of more cloud-centric; Cloudera claims it's the first “multi-cloud, multi-function” platform on a carrier. The items under its umbrella consist of information Engineering for Azure, which gives you processing jobs read and write access to Microsoft Azure records Lake store (ADLS), and Altus Analytic DB, a “information warehouse” service that promises database analytics in SQL, Python, R, and other formats by way of Altus SDX. it truly is moreover the Cloudera Altus software building package (SDK), which enables programmatic access to Java and an automatic workload efficiency computer screen that flags capabilities issues.
remaining, but now not least, is Cloudera enterprise, a platform for computing device getting to know and analytics functions. The most recent iteration (edition 6.0) introduces GPU support and Apache Hive statistics warehouse optimizations that “drastically speed up computing device getting to know and information engineering functions” as compared to the previous liberate. It also presents Apache Solr 7.0 (with aid for nested information kinds and JSON facets), Kafka 1.0, and Spark 2.2 as totally native accessories. Cloudera claims that even with as many as 2,500 nodes in a single Cloudera manager 6.0 interface cluster, desktop gaining knowledge of on the platform has the advantage to be as much as 10 times sooner. Analytics workloads leveraging Apache Hive 2.0 can predict as much as 80 percent greater performance.
“We’re thrilled to be launching new capabilities in Cloudera information Science Workbench that accelerate prevalent workflows for facts scientists, including scan management and mannequin deployment, with a seamless journey that also continues statistics comfortable and below governance,” Hilary Mason, established supervisor of desktop learning at Cloudera, noted in a statement.
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“CMOs are consistently being pressed to prove the ROI on digital, eliminate inefficiencies and manage complexity,” said Rick Milenthal, CEO of The Shipyard. “Brand leadership needs data, strategy and ideas to navigate toward success. Marketing Engineering is our approach to ensure their job is ‘future proof.’”
The model, called Marketing Engineering, is a more rigorous and forward-thinking approach to building powerful marketing solutions through the application of tools and techniques. In a departure from traditional agency protocol, The Shipyard’s creative talent work hand-in-hand with data scientists as a cohesive unit of “marketing engineers” to reinforce their 3Ps model—prediction, personalization and performance—that are essential ingredients for campaign success in today’s increasingly data-driven marketplace.
“The Holy Grail of personalization requires marketers to engage in a dialogue with millions of people in order to figure out which messages actually resonate or are likely to motivate or persuade,” said Dave Sonderman, chief creative officer of The Shipyard. “This is a completely different approach to extract rich, real-life insights. Using advanced data techniques to find out what a million customers are doing, or what they believe in, is much more actionable than dissecting the comments of 12 disparate—or, worse, the same—people in a focus group.”
The Shipyard beta tested the Marketing Engineering model for over two years and is now implementing it at full scale, as the need for marketers’ performance continues to intensify. At last month’s ANA “Masters of Marketing” Conference, coverage included hot-button issues that ranged from data privacy to the opaque digital media supply chain. This led to animated discussions amongst attendees during sessions such as one entitled “Fire your CMO.”
The marketing engineers of The Shipyard give the CMO a shot in the arm by boosting the impact of brand advertising; leveraging tools and methods that revolve around creative experimentation and providing deeper predictive insights into the stimuli, which influences purchase behavior. The net effect is braver marketing strategy, providing essential fuel for creatives to experiment, and for analysts to create a more dimensionalized view of how customers perceive a brand.
“Marketing today is clearly not reaching its full potential,” added Milenthal. “In order for it to become mission critical for all companies, it needs to change drastically.”
In their quest for deeper and richer data, marketers often struggle to tell their brand stories, while rightly trying to balance first-party and independent sources of data and technology with creative agency input.
“An overreliance on either side of the data or creativity proverbial coin is the quickest path to failure,” said Milenthal. “Instead, both must learn to live harmoniously without one being sacrificed for or detracted from the other. This is where Marketing Engineering has proven so critical and our team of Marketing Engineers are poised to create great value. By always pushing against each other, and challenging one another, we ultimately come together with the best solutions for our clients.”
For a copy of The Shipyard’s white paper on Marketing Engineering, click here.
Python has seen wide adoption across industries and disciplines by dint of being easy to work with. But it has also been aided by a wealth of third-party projects—libraries, add-ons, and complementary development efforts—that extend the language to an ever widening range of use cases.
Some of these projects, like PyInstaller and WxPython, shine for Python developers who are building desktop and end-user apps. Others, like PyPy, are used to give server-side Python apps extra oomph. And others, like PBR, CFFI, and MyPy, are useful for developing all kinds of Python apps, no matter where they might run.
If you’re a Python developer, all six of these projects are worth getting familiar with. And all six have rolled out major new versions in recent weeks.Essential Python: PyPy What is PyPy used for?
If you want faster Python apps, the easiest way to get them is by way of PyPy, the Python runtime with a just-in-time (JIT) compiler. Python apps JITted with PyPy run on the average 7.5 times faster than their regular Python counterparts. Unfortunately, PyPy hasn’t always played well with many of Python’s star frameworks. PyPy 5.9 makes major strides towards fixing that problem.PyPy 5.9 features
Data science frameworks NumPy and Pandas now run on PyPy’s Python 2.7-compatible version. Most of the problems around those frameworks stemmed from how PyPy interfaced with existing C code. To address that, PyPy 5.9 rolled in improvements to the CFFI library (see below) and PyPy’s Python C API compatibility layer.
Also with the version 5.9 release, PyPy’s JSON parser is now significantly faster when processing many kinds of JSON objects, especially those with repeated uses of the same dictionary keys.Where to download PyPy 5.9
You can download binaries for PyPy directly from its site. Official binaries are available for Windows, Mac OS, and Linux on different CPU architectures. Note that different binaries exist for Python 2.7 and Python 3.5 compatibility, so be sure you're fetching the version that matches the scripts you'll be running.
Source code and bug tracking is available on BitBucket.Essential Python: CFFI What is CFFI used for?
The C Foreign Function Interface library, or CFFI, provides a way for Python applications to interoperate with standalone C libraries. Although the stock version of Python, CPython, has its own library for this kind of work, called Ctypes, CFFI makes interacting with C libraries easier and more idiomatic for Python users than Ctypes does.CFFI 1.11 features
CFFI v1.11, updated in conjunction with PyPy, adds minor but useful changes. It now works with betas for the forthcoming Python 3.7, has better support for external error handling on Windows, and supports more modern standard types in C, such as float/double _Complex and the char16_t and char_32t types. Those last two are most crucial for C libraries that use Unicode internally.Where to download CFFI 1.11
CFFI is available as a standalone download from the Python Package Index, or can be installed with Python's pip tool: pip install cffi. Source code and bug tracking is available on BitBucket.Essential Python: PyInstaller What is PyInstaller used for?
One of the most commonly asked questions about Python is, “How can I generate a standalone executable from a Python script?” PyInstaller has long been one of the best answers.PyInstaller 3.3 features
PyInstaller packages a Python app into a single directory or single-file executable, bundles any needed third-party libraries along with it, and works with the vast majority of common libraries and frameworks.
The biggest improvement in PyInstaller 3.3 is support for Python 3.6, something sorely lacking since Python 3.6 arrived. PyInstaller 3.3 also includes a more broadly compatible bootloader for Windows executables, and expanded support for bundling common libraries like QT, GTK+, NumPy, and Django.
One feature that PyInstaller isn’t likely to add anytime soon is cross-packaging—e.g., creating a Mac-compatible app on Windows. You’ll need to run PyInstaller on the same platform you want to deploy to, whether Windows, Mac, or Linux.Where to download PyInstaller 3.3
PyInstaller can be installed from the Python Package Index, or installed with Python's pip tool: pip install pyinstaller. Source code is available on GitHub for those who want to compile the bootloaders themselves, but most people will not need to do this.Essential Python: Python Build Reasonableness (PBR) What is Python PBR used for?
Setuptools is the standard-issue Python subsystem for packaging Python projects. Managing Setuptools for a given project can become fiddly and tedious, especially when auto-generating requirements, managing documentation files, or editing data on project contributors.Python PBR features
PBR, short for Python Build Reasonableness, is a library for managing Setuptools packaging in a consistent manner. It automates many aspects of Setuptools packaging, such as version numbering, generating Authors and ChangeLog files, and producing Sphinx-style documentation. PBR was originally developed as part of the OpenStack project, but nothing you maintain with PBR has to be connected to OpenStack in any way.Where to download Python PBR
PBR is available on the Python Package Index, and can be installed with pip by typing pip install pbr. Source code is available on GitHub.Essential Python: WxPython What is WxPython used for?
Python developers who want to make cross-platform desktop applications can choose from a number of toolkits. WxPython, a wrapper for the WxWidgets library, uses native UI elements for its supported host platforms, which include Windows, Mac, Linux, and other Unix-like operating systems.WxPython 4.0 features
Earlier versions of WxPython were weighted down with legacy design decisions, making it slower and less appealing to work with. To fix this, the developers of WxPython have made major changes to WxPython’s 4.0 branch.
The goal is to allow developers to get started more quickly with WxPython, and to make both the framework and the applications created with it more performant and easier to maintain. Any existing WxPython projects will need to be modified to use WxPython 4.0, however.Where to download WxPython 4.0
WxPython 4.0 is still officially in beta. It's available on the Python Package Index by way of pip install wxpython, but it may be updated several more times before being formally released. Check back often for updates.
Those who want to hack on it directly can check out the GitHub repository. Note that the 4.0 branch of WxPython is branded with the codename "Phoenix" to keep it distinct from earlier versions.Essential Python: Mypy What is Mypy used for?
Python’s dynamism is both a boon and a bother—great for building software fast, but not so great when it makes code difficult to reason about, test, and debug. Mypy adds static type checking to Python at compile time, making Python programs more consistent and maintainable but without adding runtime overhead.Mypy 0.530 features
Mypy 0.530 adds support for protocols, a currently experimental type feature for use in Python subclasses. It also adds the “TypedDict” type for dictionaries that are meant to contain only a specific kind of object, and options to enable stricter checking of types on a file-by-file basis.Where to download Mypy 0.530
Mypy is available in the Python Package Index, and can be installed with pip install mypy. Those interested in hacking directly on Mypy can check out the code on GitHub.Related video: How Python makes programming easier
Alzheimer's disease is thought to be caused by the build-up of a brain peptide called amyloid-beta. That's why eliminating the protein has been the focus of almost all drug research pursuing a cure for the devastating neurodegenerative condition.
But that may be counterproductive, says Dr. Inna Slutsky of Tel Aviv University's Department of Physiology and Pharmacology, Sackler Faculty of Medicine. Her recent research demonstrates that amyloid-beta is also necessary to maintain proper brain functioning.
These findings may shake the foundations of Alzheimer's research.
In a new study published this month in Nature Neuroscience, Dr. Slutsky finds that amyloid-beta is essential for normal day-to-day information transfer through nerve cell networks in the brain. "If this protein is removed from the brain," says Dr. Slutsky, "as some drugs in development attempt to do, it may cause an impairment of neuronal function, as well as a further and faster accumulation of amyloid-beta in Alzheimer's."
A reset button for drug researchers
Without amyloid-beta, a normal product of cellular metabolism, one's ability to learn and remember could be profoundly damaged, so drugs currently in development to eliminate amyloid-beta could be rendered obsolete. With Dr. Slutsky's research, a leap in understanding the cause and development of Alzheimer's disease, however, new, more effective drug therapies could be developed.
By studying synapses in brain slices of healthy mice and in neuronal networks growing in vitro, Dr. Slutsky and her team determined that there is an optimal amount of amyloid-beta needed to keep the neurons working well. Her students Efrat Abramov and Iftach Dolev found that if this precise balance is even slightly disturbed, the effectiveness of information transfer between neurons is greatly impaired.
"Synapses where neurons meet work as filters of information," says Dr. Slutsky. "What is really exciting for us is the fact that amyloid-beta peptide, believed to be toxic, regulates the type of information that neurons transfer."
A new way to prevent Alzheimer's?
The study of Dr. Slutsky's team suggests that the amyloid-beta protein belongs to endogenous molecules regulating normal synaptic transmission in the hippocampus, a brain region involved in learning and memory function. "There is a long list of neuromodulators that help synapses optimize information transfer," she says. "Intriguingly, amyloid-beta seems to be able to modulate this filter and shape its properties."
The new study is discouraging news for those Alzheimer drugs that attempt to block or remove the amyloid-beta aggregation process currently in clinical trials, Dr. Slutsky believes. "Our data shows that after the release of amyloid-beta, synaptic activity in the neurons is increased through a positive feedback loop. Disrupting this positive feedback loop, I believe, is the key for prevention of the earliest signs of Alzheimer's."
Dr. Slutsky completed her post-doctoral work at MIT four years ago, specializing in cellular mechanisms that maintain memory function. She received an international Young Investigator Award in Alzheimer's disease from the Rosalinde and Arthur Gilbert Foundation of American Federation for Aging Research in 2008.
In addition to Dr. Slutsky, Dolev and Abramov, authors of the paper also include Hilla Fogel and Eyal Ruff of TAU's Sackler Faculty of Medicine, and Giuseppe Ciccotosto of the University of Melbourne in Australia.
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