The Secrets of Making profits in Gaming Controller Market

This research report will give you deep insights about the Gaming Controller Market and it will also help you in strategic decision making. The final research document is an exhaustive document comprising of 150 pages. All our reports are usually purchased across industries by Executives, Managers, Senior Managers, Strategy people, Directors, Vice Presidents, CXOs, etc. and help them in understanding about the market trends and analysis, competition, industry landscape, market size, market revenue, forecast, COVID-19 impact analysis, SWOT analysis, etc.

The gaming controller market was valued at US$ 1,663.5 million in 2019 and is projected to reach US$ 2,973.5 million by 2027; it is expected to grow at a CAGR of 8.0% from 2020 to 2027.
The state-of-the-art research on Gaming Controller Market, which is a detailed analysis of business space inclusive of the current market trends, competitive background, and size of the market. Encircling one or more parameters among analysis of the product, application potential, and global and regional growth strategies.

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Speaking about this research report in particular, it includes:

Five Types of Segmentations
Five Major Regions (North America, Europe, Asia Pacific, Middle East & Africa, South & Central America)
Market Information For 10 Years (2017 & 2018 – Historic Years, 2019 – Base Year and 2020-2028 Forecast Period)
Key Industry Dynamics including factors that are Driving the Market, Prevailing Deterrent, Potential Opportunities as Well as Future Trends.
Ten Company Profiles (these are not just Major Players but a Mix of Leading, Emerging Players, Market Disruptors, Niche Market Players, etc.)
Industry Landscape Analysis
Analysis of COVID-19 Impact on this market at Global and Regional Level.
A thoroughgoing evaluation of the market restrains included in the report which represents the difference to drivers of the market and gives scope for strategic insights and developments. The research study has amalgamated the growth analysis of different aspects that enhance the market growth scenario. It constitutes key market drivers, restraints and trends that transform the market in either a positive or negative manner.

Here we have listed the top companies in the world

Bensussen Deutsch and Associates, LLC
Guillemot Corporation S.A.
HORI USA
Logitech
Mad Catz Global Limited
Microsoft Corporation
Nintendo
Razer Inc.
Sony Corporation
Scuf Gaming International LL
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The Table of Content for Gaming Controller Market research study includes:

Introduction
Key Takeaways
Research Methodology
Gaming Controller Market Landscape
Gaming Controller Market – Key Market Dynamics
Gaming Controller Market – Global Market Analysis
Gaming Controller Market – Revenue And Forecasts to 2028 – Type
Gaming Controller Market – Revenue And Forecasts to 2028 – Type of Product
Gaming Controller Market – Revenue And Forecasts to 2028 – Service
Gaming Controller Market Revenue And Forecasts to 2028 – Geographical Analysis
Impact of Covid-19 Pandemic on Global Gaming Controller Market
Industry Landscape
Gaming Controller Market, Key Company Profiles
Appendix
List of Tables
List of Figures
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Public Cloud Storage Service Market 2021 | Detailed Report

Public Cloud Storage Service Market Forecasts report provided to identify significant trends, drivers, influence factors in global and regions, agreements, new product launches and acquisitions, Analysis, market drivers, opportunities and challenges, risks in the market, cost and forecasts to 2027.

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The report provides a comprehensive analysis of company profiles listed below:
– Alibaba Cloud
– Amazon Web Services
– Google
– IBM
– Microsoft
– Oracle
– Rackspace
– Virtustream

Public Cloud Storage Service Market Segment by Type:
– Web Services APIs
– Thin Client Applications

Public Cloud Storage Service Market Segment by Application:
– BFSI
Education
Manufacturing
Telecom & IT
Others

The study report offers a comprehensive analysis of Public Cloud Storage Service Market size across the globe as regional and country level market size analysis, CAGR estimation of market growth during the forecast period, revenue, key drivers, competitive background and sales analysis of the payers. Along with that, the report explains the major challenges and risks to face in the forecast period. Public Cloud Storage Service Market is segmented by Type, and by Application. Players, stakeholders, and other participants in the global Public Cloud Storage Service Market will be able to gain the upper hand as they use the report as a powerful resource.

Scope of this Report:
• This report segments the global Public Cloud Storage Service market comprehensively and provides the closest approximations of the revenues for the overall market and the sub-segments across different verticals and regions.

• The report helps stakeholders understand the pulse of the Public Cloud Storage Service market and provides them with information on key market drivers, restraints, challenges, and opportunities.

• This report will help stakeholders to understand competitors better and gain more insights to better their position in their businesses. The competitive landscape section includes the competitor ecosystem, new product development, agreement, and acquisitions.

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Android Kiosk Software Market Keyplayers and Vendors: 42Gears Mobility Systems Pvt Ltd., Esper, KioWare, Meridian Kiosks, Mitsogo Inc., NoviSign Digital Signage Inc., Photo Booth Solutions, LLC, Provisio GmbH, Scalefusion, Zoho Corp.

An end-to-end conclusive research methodology covers highly descriptive analysis of the Android Kiosk Software market thoroughly encompassing various elements of the industry into an aggregate of statistically accurate and theoretically compelling data. The report consists of pre-established findings, comparative market analysis, valuation and calculations all of which lead to the end goal of the study which is delivering the future forecast of the Android Kiosk Software market. the study applies highly reliable, greater efficiency analytical tool in order to deliver most accurate market values based on the prior records followed by the future predictions that forecast the status of the Android Kiosk Software market.

Competitor Profiling: Android Kiosk Software Market
42Gears Mobility Systems Pvt Ltd.
Esper
KioWare
Meridian Kiosks
Mitsogo Inc.
NoviSign Digital Signage Inc.
Photo Booth Solutions, LLC
Provisio GmbH
Scalefusion
Zoho Corp.

The focal point of the market review remains identification and analysis of the wide-ranging factors including both industrial as well as non-industrial in origin influencing the growth derivative output. Android Kiosk Software market growth is effectively evaluated as a part of the present scenario followed showcasing the estimated values determined largely based upon the growth-altering influential factors. A crisp classification of the growth positive and negative factors is provided in the study along with an analysis briefing the impact of each mentioned factor. In addition to the in-depth study of growth factors, the Android Kiosk Software market is also assessed for an impact posed from the most recent industry trends.

Unraveling Segmentation and Scope of the Android Kiosk Software Market

Analysis by Type:
by Deployment Type (Cloud, On-premise);

Analysis by Application:
End-user (BFSI, Retail, Healthcare, Government, Logistics, Others)

The future of the App Store depends on the difference between a ‘button’ and an ‘external link’

Today the judge in Epic v. Apple issued a lengthy ruling holding that Epic failed to prove that Apple has a monopoly in mobile gaming transactions. Importantly, the court also held that Apple’s rules preventing other payment options in the App Store are anticompetitive, and issued an injunction telling Apple to cut it out.

In particular, the court said that “Apple is participating in anticompetitive direct,” and that “Apple’s enemy of controlling arrangements conceal basic data from purchasers and illicitly smother customer decision.”

To fix that, the court gave the accompanying extremely durable directive banning Apple from having rules against other installment frameworks. I’ve bolded the most important bit:

Apple Inc. what’s more, its officials, specialists, workers, representatives, and any individual in dynamic show or support with them (“Apple”), are thus for all time controlled and urged from forbidding engineers from (I) remembering for their applications and their metadata buttons, outside joins, or different suggestions to take action that immediate clients to buying instruments, notwithstanding In-App Purchasing and (ii) speaking with clients through resources acquired deliberately from clients through account enrollment inside the application.

This specific wording is lifted directly from Apple’s App Store rule 3.1.1, which says “Apps and their metadata may not include buttons, external links, or other calls to action that direct customers to purchasing mechanisms other than in-app purchase,” so it’s tempting to think that the judge just declared that rule anticompetitive and crossed it out.

But it’s a little more complicated than that — now that this text is in a judicial order, it no longer belongs to Apple, or needs to be interpreted how Apple wants. Indeed, the court was clear that it will enforce this rule, and that if anyone thinks Apple is breaking it, it wants to know. Again, my bolding:

The Court will retain jurisdiction over the enforcement and amendment of the injunction. If any part of this Order is violated by any party named herein or any other person, plaintiff may, by motion with notice to the attorneys for defendant, apply for sanctions or other relief that may be appropriate.

So now comes the really complicated part. What does this injunction mean for Apple and the App Store? Let’s break this rule down piece by piece — the difference between a “button” and an “external link” is going to be remarkably important here.

Apple is:

  1. not allowed to prohibit developers from including in their apps and their metadata
  2. buttons
  3. external links, or
  4. other calls to action
  5. that direct customers to purchasing mechanisms
  6. in addition to In-App Purchasing.

We can make some versions of this sentence make sense really easily:

  • Apple is not allowed to prohibit developers from including external links in their apps that direct customers to purchasing mechanisms.
  • Apple is not allowed to prohibit developers from including calls to action in app metadata [like descriptions in the App Store] that direct customers to purchasing mechanisms.

But consider the following version of this sentence:

  • Apple is not allowed to prohibit developers from including buttons in their apps that direct customers to purchasing mechanisms.

Well, shit. Here is an example of a button that takes you to a purchasing mechanism in the Amazon app:

This is the ballgame! What’s the significance here for a button in an application to “direct a client to buying instruments”? Is it a checkout button? Would amazon be able to add a truck, a checkout button, and installments to the Kindle application now? The court isn’t dumb — it indicated buttons and outside joins, which implies they are ventured to be particular. So a button can’t simply be an outer connection that kicks you to Safari.

Apple will attempt to say that “button” simply implies what something resembles, while engineers will say that “button” signifies how something works.

That implies that a reasonable perusing of the plain text of this order proposes that buttons in iOS applications can guide clients to buying components in the application — if the button simply shows you out to the web, it would be an outer connection!

I’m sure a ton of engineers will test this language forcefully, and that Apple will end up growing new guidelines to secure its rewarding in-application buying framework from contest. What’s more, I’m sure Apple will attempt to say that “button” simply implies what something resembles, while engineers will say that “button” signifies how something works. (There is a great deal of incongruity in this for Apple.)

Be that as it may, eventually, it will not be dependent upon Apple to choose what this request implies — it will be up the court. What’s more, that is a sensitive situation to be in, on the grounds that the court unequivocally thinks the counter controlling guideline is exceptionally anticompetitive.

Apple didn’t react to a solicitation for input on the distinction among buttons and outside joins.

Knight Campus scientist is creating molecules for medicine

In her lab at the Phil and Penny Knight Campus for Accelerating Scientific Impact, computational biochemist Parisa Hosseinzadeh is using computer modelling to design synthetic peptides as potential drugs to treat challenging diseases.

Hundreds of synthetic peptides are either in use or in clinical trials, but producing them is time-consuming and costly. Vaccines against COVID-19 have peptides that target the spike protein of the virus, tricking it and thwarting infection.

Peptides are tiny molecules that contain two or more amino acids, the building blocks of proteins. They emerged as a therapeutic in 1922, when a natural, hormone-produced version in pigs was used to regulate insulin in a child with diabetes. The first lab-produced peptide came in 1953 and is commonly used to induce labour.

Hosseinzadeh, an assistant professor, is deploying computational methods to help drug designers move more swiftly in their screening of possible peptides that will bind precisely to targets so they initiate the desired response without causing unintended consequences.

“Researchers have been generating huge libraries of random peptides and then screening them to see if they bind to a target or not. It is a random, trial-and-error process,” she said. “The problem with this method is that the overall space in which you can screen for candidate peptides is vast, like 10 to the 30th (power). In a best-case scenario, we can screen 10 to the 14th. It is impossible to screen everything.”

Her research at the Knight Campus aims to narrow that testing space of more than a hundred trillion possibilities to a smaller and more manageable pool of possible candidates. It builds on work she began before arriving at the UO last September.

Hosseinzadeh has emerged as a leader in her field. While a postdoctoral researcher at the University of Washington, she led a study published in 2017 in the journal Science that led to highly structured, rigid peptides with high accuracy. That work was done with UW colleagues, Howard Hughes Medical Institute investigators and scientists at the Pacific Northwest National Laboratory.

“Accurate design of structured peptides in this scale had never been done before, and many people thought it couldn’t be done,” she said. “If you have something that is rigid you can better predict its behavior with computational analyses. This rigidity allows for tighter binding.”

This year has brought two new published studies from work done prior to her arrival in Eugene.

In a paper published online in Nature Communications, Hosseinzadeh, in her postdoctoral role at the UW, and colleagues from the UW, University of Pennsylvania and Stanford University unveiled a proof-of-concept for a computational approach that reduces the screening time for peptides that will bind.

Her team detailed how their approach used computational modeling to screen hundreds of thousands of peptides, generating 50 candidate peptides for testing. The computations considered all possible combinations of the human body’s 20 amino acids and associated compounds.

Each tested peptide was designed with a non-protein-generating amino acid as an anchor to provide a weak initial binding around which peptides can be designed to enhance the binding.

“Using this method,” Hosseinzadeh said, “we obtained peptides that can inhibit a class of enzymes with low nanomolar affinity without any downstream optimization.”

Low affinity at nanometer scale is important in drug design; it means that a peptide can bind only at a targeted site without affecting other proteins that lead to undesired effects.

“Our method involves fewer experiments and is faster,” she said. “We can weed out candidate peptides in the experimental libraries that will never bind. At this stage, our work is about creating a platform that scientists can use to generalize to meet their specific needs.”

In a paper published March 25 in ACS Catalysis, a journal of the American Chemical Society, Hosseinzadeh and colleagues addressed the applications of peptide design, particularly in probing the mechanism of enzymatic reactions. Their computational modeling and experimental techniques enabled an investigation of the activity of multiple conformations of a peptide catalyst in isolation.

“We determined that the dynamic movement of the lead catalyst plays a crucial role in achieving a site-specific reaction,” Hosseinzadeh said. “This approach may also serve as a valuable method for investigating the mechanism of other peptide-catalyzed transformations.”

Researchers in Hosseinzadeh’s Knight Campus lab are focusing on the fundamentals of synthetic peptide design. They are using computational modeling and analyses to study peptide behavior. She also is seeking to develop peptide- and protein-based biosensors for disease diagnostics.

Peptide-based vaccines are in play or under development by numerous researchers to treat diseases such as influenza, cancers, hepatitis C, HIV and brain disorders.

Synthetic peptides, she said, hold promise as a treatment for disease targets currently out of range of current drugs.

“At this point, my main focus is developing robust and accurate computational methods, but, as this work develops, I look forward to working with anyone who is pursuing specific targets,” Hosseinzadeh said.

She is already collaborating with Knight Campus colleagues who are interested in specific binding capabilities.

“The collaboration with colleagues at the Knight Campus is a huge motivation for me to move this research forward,” she said. “It’s nice to be around people who are more applied in their focus. I can talk with them and ask questions about next steps I might take. It often leads to questions that bring about new challenges that I have not thought about before.”

Source: University of Oregon




Technology.org

Quantum dots keep atoms spaced to boost catalysis

Hold on there, graphene. Seriously, your grip could help make better catalysts.

Rice University engineers have assembled what they say may transform chemical catalysis by greatly increasing the number of transition-metal single atoms that can be placed into a carbon carrier.

The technique uses graphene quantum dots (GQD), 3-5-nanometer particles of the super-strong 2D carbon material, as anchoring supports. These facilitate high-density transition-metal single atoms with enough space between the atoms to avoid clumping.

Rice University engineers have led the development of a process that uses functionalized graphene quantum dots to trap transition metals for higher metal loading single-atom catalysis. Illustration by Wang Group

An international team led by chemical and biomolecular engineer Haotian Wang of Rice’s Brown School of Engineering and Yongfeng Hu of Canadian Light Source at the University of Saskatchewan, Canada, detailed the work in Nature Chemistry.

They proved the value of their general synthesis of high-metal-loading, single-atom catalysts by making a GQD-enhanced nickel catalyst that, in a reaction test, showed a significant improvement in the electrochemical reduction of carbon dioxide as compared to a lower nickel loading catalyst.

Wang said expensive noble metals like platinum and iridium are widely studied by the single-atom catalyst community with the goal of reducing the mass needed for catalytic reactions. But the metals are hard to handle and typically make up a small portion, 5 to 10% by weight or less, of the overall catalyst, including supporting materials.

By contrast, the Wang lab achieved transition-metal loads in an iridium single-atom catalyst of up to 40% by weight, or 3 to 4 spaced-out single metal atoms per every hundred carbon substrate atoms. (That’s because iridium is much heavier than carbon.)

“This work is focused on a fundamental but very interesting question we always ask ourselves: How many more single atoms can we load onto a carbon support and not end up with aggregation?” said Wang, whose lab focuses on energy-efficient catalysis of valuable chemicals.

“When you shrink the size of bulk materials to nanomaterials, the surface area increases and the catalytic activity improves,” he said. “In recent years, people have started to work on shrinking catalysts to single atoms to present better activity and better selectivity. The higher loading you reach, the better performance you could achieve.”

“Single atoms present the maximum surface area for catalysis, and their physical and electronic properties are very different compared to bulk or nanoscale systems,” he said. “In this study, we wanted to push the limit of how many atoms we can load onto a carbon substrate.”

He noted that the synthesis of single-atom catalysts has to now been a “top-down” or “bottom-up” process. The first requires making vacancies in carbon sheets or nanotubes for metal atoms, but because the vacancies are often too large or not uniform, the metals can still aggregate. The second involves annealing metal and other organic precursors to “carbonize” them, but the metals still tend to cluster.

The new process takes a middle approach by synthesizing GQDs functionalized with amine linkers and then pyrolyzing them with the metal atoms. The amines crosslink with the metal ions and keep them spread out, maximizing their availability to catalyze reactions.

“The maximum appears to be about 3-4 atomic per cent using this approach,” Wang said. “Future challenges include how to further increase the density of single atoms, ensure high stability for real applications and scale up their synthesis processes.”

Source: Rice University




Technology.org

Snowed in: Research team finds Arctic was dinosaur nursery

Long-standing images of dinosaurs as cold-blooded creatures needing tropical temperatures could be a relic of the past. 

The University of Alaska Fairbanks and Florida State University palaeontologists have found that nearly all types of dinosaurs — from small bird-like forms to the giant tyrannosaurus — not only reproduced in the region but also remained there year-round. 

Their findings are detailed in a new paper published in the journal Current Biology 

“It wasn’t long ago that people were pretty shocked to find out that dinosaurs lived up in the Arctic 70 million years ago,” said Pat Druckenmiller, the paper’s lead author and director of the University of Alaska Museum of the North. “We now have unequivocal evidence they were nesting up there as well, like nurseries of the north. This is the first time that anyone has ever demonstrated that dinosaurs could reproduce at such high latitudes.” 

The findings counter previous hypotheses that dinosaurs migrated to lower latitudes for the winter and also provides some of the most compelling evidence thus far that these prehistoric creatures were warm-blooded.  

Druckenmiller and Florida State University Professor of Biological Science and study co-author Gregory Erickson have been conducting fieldwork in the Prince Creek Formation in northern Alaska for more than a decade, unearthing a diversity of dinosaur species, most, if not all of which are new to science. Their latest discovery shows evidence of dinosaurs in the earliest stages of life living close to the ancient Arctic Ocean.  

The researchers found tiny teeth —some less than 2 millimeters in length — and bones from seven species of perinatal dinosaurs, a term that describes baby dinosaurs that are either embryonic (just about to hatch) or have just hatched. 

“One of the biggest mysteries about Arctic dinosaurs was whether they seasonally migrated up to the North or were year-round denizens,” Erickson said. “We unexpectedly found remains of perinates representing almost every kind of dinosaur in the formation. It was like a prehistoric maternity ward”.  

The process of recovering the bones and teeth, some no larger than the head of a pin, is an exercise in perseverance and a sharp eye. In the field, the scientists haul buckets of sediment from the face of the bluffs down to the river’s edge, where they wash the material through smaller and smaller screens until they have removed any large rocks and soil.  

Once back at the lab, they run the material through more screens to remove all the clay, until all that’s left is sandy particles. Then, teaspoon by teaspoon, the team, including graduate and undergraduate students examine the sand under microscopes to find the bones and teeth.  

“Recovering these tiny fossils is like panning for gold,” Druckenmiller said. “It requires a great amount of time and effort to sort through tons of sediment grain-by-grain under a microscope. The fossils we found are rare but are scientifically rich in information.”  

The next step in the process involved identifying and comparing the fossils to those from other sites at lower latitudes, such as Alberta and Montana. Co-authors Caleb Brown and Don Brinkman of the Royal Tyrrell Museum of Paleontology provided valuable information from the extensive collections at their museum.  

Once they knew the dinosaurs were nesting in the Arctic, it was a relatively straight line to the realization that the animals must have lived their entire lives in the region.  

Erickson’s previous research had found that the incubation period for these types of dinosaurs is anywhere between about three to six months, depending on species. Because Arctic summers are short, even if the dinosaurs laid their eggs as soon as it warmed up in the spring, their offspring would be too young to migrate in the fall.   

Global temperatures were much warmer during the Cretaceous, but the angle of the Earth’s axis was much the same as it is today. That means dinosaurs encountered about four months of darkness per year, with temperatures dropping below freezing and periods of snow. There also would have been little to no fresh vegetation for food.  

“Year-round residency in the Arctic provides a natural test of dinosaurian physiology,” Erickson said. “We solved several long-standing mysteries about the dinosaur reign, but opened up a new can of worms — how did they survive Arctic winters?” 

Researchers can only guess for now at how these mysterious creatures lived. Perhaps the smaller ones hibernated through the winter, Druckenmiller said. Perhaps others lived off poor-quality forage, much like today’s moose, until the spring.  

Scientists have found other warm-blooded animal fossils in the region, such as small mammals and birds, but not lizards, snakes, crocodiles, amphibians or turtles. That suggests these cold-blooded animals could not survive the frigid temperatures of the region. 

“This study goes to the heart of one of the longest-standing questions among palaeontologists: Were dinosaurs warm-blooded?” Druckenmiller said. “We think that endothermy was probably an important part of their survival.” 

Source: Florida State University




Technology.org

Blending Old and New Schools: Machine Learning Mixes with Traditional Science Principles

Machine learning came along at just the right time. The world is now awash in more data than ever before, and computer algorithms that can learn and improve as they perform data analysis promise to help scientists handle that information overload.

Yet researchers who think that machine learning by itself can help solve complex problems in science, engineering, and medicine, should strive for a more balanced approach, says Roman Grigoriev, part of a School of Physics team with new research suggesting a hybrid approach for conducting science that blends new era technologies, old school experimentation, and theoretical analysis. The research suggests faster solutions to complex, data-intensive riddles involving such issues as cancer, earthquakes, weather forecasts, and climate change.

“It’s a combination of existing theoretical understanding — as well as experimental data with machine learning,” says Grigoriev, Physics professor and lead investigator of the Dynamics and Control Group. “Oftentimes people who do machine learning kind of forget about theoretical understanding and almost rely totally on data. It’s relatively simple, but when there’s a lot of data and not enough structure in that data, that approach is bound to fail.” Grigoriev explains that there’s often just too much data to meaningfully analyze, at which point “the problem becomes intractable. Essentially, harnessing appropriate domain knowledge is critical for finding structure in the data.”

“Robust learning from noisy, incomplete, high-dimensional experimental data via physically constrained symbolic regression,” was in Nature Communications. Fellow School of Physics researchers involved in the study are Michael Schatz, professor and the School’s interim chair; graduate research assistant Logan Kageorge; and former graduate research assistant Patrick A.K. Reinbold.

The problem with high-dimensional data

Machine learning uses computer algorithms to find patterns in data, but “most popular machine learning approaches present results in a form that is hard to interpret and explain,” Grigoriev says. “Unless you understand the how and the why you can’t really say you understand a problem.”

Understanding and predicting complicated behaviours — by crunching a lot of dense, rich data — can help with fundamental and practical problems in science areas like weather forecasting and characterizing cardiac arrhythmias. The problem is that most of those arenas involve “high-dimensional” data, which means exactly what it sounds like: data with a lot of dimensions or variables, sometimes millions of them.

The dimensionality of the data is so large that “you get lost and it’s hard to see any trends,” Grigoriev says.

His team has come up with a hybrid approach that blends machine learning with elements of the traditional process of scientific discovery. That means a theoretical description, observations, designing experiments to test the description, and “then going back and forth between improving the theories, and designing new experiments. That’s been the traditional approach for hundreds of years.”

The foundation of Science’s understanding and progress relies on that scientific method — the combination of theory and experimentation. “They’re not developed just based on the data. They are developed using both existing knowledges as well as some general fundamental laws.”

An approach that spotlights the beauty of equations

Constraining the data to include just those variables that pertain directly to the experiment in question is vital in working with high-dimensional data, Grigoriev says.

“What this approach allows you to do is identify a simpler model that uses the variables you need. It’s a simplified description that applies to a particular situation but obtained using data that’s computational or experimental. It can do both.”

The result is represented in a mathematical model, Grigoriev says, and “once you see those equations, you understand what the variables are. The equations certainly help explain the essence of a physical problem.” His team’s approach was validated in the research with a fluid dynamics experiment. A thin layer of liquid was suspended in a rectangular tank, with magnetic and electrical fields shot through it to create what physicists call a turbulent flow — irregular shifts happening within the fluid layer that can rapidly change direction and magnitude.

Grigoriev and his team used their hybrid approach to analyze the accessible data, in this case the velocity of the water. Subsequently, they were able to reconstruct variables that couldn’t be measured directly, like water pressure and force.

This is the beauty of the equations — how much they allow you to do, Grigoriev says.

“What we do get is an equation, or set of equations, which are in a familiar form. We know how to explain, how to solve the problem using these equations. This is the nice thing about this approach. We’re working with variables whose meaning we understand; we know how to interpret them.”

The team believes the study’s results will lead to advances like faster, more accurate ways to make predictions of complicated behaviour in those large, real-world problems in science, engineering, and medicine. For example, as Grigoriev’s team’s research states, “the ability to identify and quantify important patterns and sequences in atmospheric turbulence should enable weather forecasts that are better and more rapid than those currently possible today.”

Source: Georgia Tech




Technology.org

Unusual coronavirus protein is potential drug target to fight COVID-19

The SARS-CoV-2 virus contains a gene that codes for a strange protein that could be a good target for drugs to fight COVID-19 and possibly other coronavirus infections, according to a new study from the University of California, Berkeley.

When the virus injects its genome into a cell, the so-called ORF3a gene is expressed to make a protein that moves to the surface of the cell and looks like an ion channel — a passage all cells have for ions like calcium to move in and out as they communicate with other cells.

The structure of the SARS-CoV-2 protein called 3a, as determined by cryoEM. UC Berkeley researchers produced the most detailed structure to date of the protein — an ion channel — which may be a good target for drugs to fight coronavirus infections. Image credit: David Kern

But UC Berkeley researchers, who began investigating the protein’s structure with cryogenic electron microscopy (cryoEM) in January of last year, immediately after the pandemic began, discovered that the protein is nothing like other ion channels known to science. For one thing, it’s half a channel — it only pierces the cell membrane halfway. It also has an unusual fold not seen in other ion channels.

While no one knows why the virus carries a gene to make an ion channel — and a strange one, at that — researchers have found that by knocking out the ORF3a gene in SARS-CoV-2 and a related ORF3a gene in the original SARS virus, SARS-CoV-1, the severity of the disease is reduced, at least in animal models. This, the researchers say, makes it a good target for drugs to reduce the severity of human coronavirus infections. A high-resolution cryoEM structure published by the UC Berkeley team provides key information needed to find such drugs.

The 3a protein of the SARS-CoV-2 virus doubles up as a dimer when it is embedded in a cell membrane, serving as a channel for calcium ions. Image credit: David Kern

“It wasn’t clear how conserved this protein was among coronaviruses, but once we solved the structure, we could look to see if other genes in other coronaviruses are likely to adopt the same fold,” said Stephen Brohawn, one of the senior authors of the study and a UC Berkeley assistant professor of molecular and cell biology. “And it turns out that in all of the coronaviruses that circulate among bats and can infect humans, these 3a proteins exist. So, it could be an even broader possible target than we had thought at the beginning of the project.”

After the UC Berkeley researchers posted their preliminary cryoEM structure on bioRxiv last year, one Twitter follower noticed a surprising image — a pig in a hat — embedded in the structure, at least when viewed from one perspective.

Brohawn and his UC Berkeley colleagues have already identified a drug that blocks the ion channel — though it also blocks other ion channels — and have identified mutations in the ORF3a gene that alter channel function.

“This shows, in principle, that one can find molecules that block this activity,” Brohawn said. “Now one of the goals that we have is to screen for small molecules that block the channel and that are specific for blocking 3a compared to other ion channels.”

High-resolution cryoEM structures

The team’s preliminary results were posted on the open-access preprint server bioRxiv in June of 2020, and the final results — with a much higher resolution cryoEM structure for the 3a protein — were published in the journal Nature Structural & Molecular Biology. The original online paper drew attention from those using computational approaches to find drugs to fight COVID-19, but it also helped improve a computer algorithm — Google DeepMind’s AlphaFold — that predicts a protein’s 3D structure from its amino acid sequence.

Brohawn, who is a member of UC Berkeley’s Helen Wills Neuroscience Institute, uses cryoEM to study the structures of ion channels in neurons. For this project, he teamed up with the lab of Diana Bautista, UC Berkeley professor of molecular and cell biology, who uses other methods to study ion channels, specifically those involved in chronic itch, pain and inflammatory disease. Together, the two labs provided three different pieces of evidence that the 3a protein does act as an ion channel. Though they demonstrated this in artificially-made lipid membranes called liposomes, these membranes are chemically similar to the membranes of cells, so presumably, the proteins also work as ion channels in coronavirus-infected cells.

The odd structure of the 3a protein — specifically, its blind pore, which is totally unlike typical ion channels that contain a tunnel that goes completely through the membrane to allow ions easy passage in and out — suggests that ions may instead diffuse down grooves along the outside of the protein.

According to Brohawn, the 3a protein is the smallest membrane protein channel that has been imaged by cryoEM, which has rapidly become the best way to determine the 3D structure of molecules, down to the level of individual atoms and the water molecules that surround them. Brohawn continues to research the 3a protein and two other potential ion channels — called E and 8a —in the SARS-CoV-2 genome, both to understand how they work and to find potential drugs to inactivate them.

Bautista continues investigating how the virus uses these ion channels to take over human and animal epithelial cells and neurons. Many viruses interfere with calcium signalling in cells, which may help them take over the cells’ molecular machinery and force them to make millions of copies of the virus instead of daily cellular housekeeping.

“We thought 3a was the most understudied and potentially the most interesting of these proteins and something we could probably make a dent in, if we jumped on it right away,” Brohawn said. “We were in a good position to move quickly on this, and it was really exciting to see it come together that fast.”

Source: UC Berkeley




Technology.org

How a trial that mirrors intensive care practices is pinpointing life-saving coronavirus treatments

When the H1N1 swine flu outbreak hit in 2009 it caused typical flu symptoms, but severe cases led to pneumonia and lung failure.

Doctors were unsure which treatments would work, but steroids, which dampen down inflammation, seemed like a good bet. Clinicians in intensive care units decided to set up a trial to see if steroids helped patients severely ill with swine flu.

But this proved impossible. ‘The pandemic came and went and we missed an opportunity to test whether even a simple intervention like steroids worked or not,’ said Professor Alistair Nichol, ICU doctor in St Vincent’s University Hospital in Dublin, Ireland, who worked in an Australian hospital during the 2009 pandemic.

‘There was a peak in intensive care unit (ICU) transmissions and some clinicians got frustrated in trying to set up a drug trial (that never happened),’ recalled Dr Lennie Derde, an intensive care doctor at UMC Utrecht in the Netherlands.

That pandemic killed tens of thousands of people, but ICU clinicians expected worse in the future. ‘This one was moderately bad,’ recalled ICU physician Professor Steve Webb at the Royal Perth Hospital in Australia, ‘but if we had a really bad one, we were just woefully unfit to be able to do drug trials.’ So ICU clinicians came together to be better prepared. ‘Nobody doubted there would be a next time,’ said Prof. Nichol.

Community-acquired pneumonia

Typically, a viral pandemic begins with a spike in unusual pneumonia cases in ICUs.

In March 2020, patients flooded ICUs with SARS-CoV-2 infections. This time, some ICU clinicians were ready from the get-go. A number of coronavirus patients were quickly recruited into an existing clinical trial calledREMAP-CAP, set up in the wake of the 2009 swine flu outbreak, to test which drugs worked on their pneumonia.

It was ‘set up in peacetime,’ explained Prof. Nichol, ‘so as to be ready for wartime if a pandemic was to arrive.’

‘We were able to flick the switch to include pandemic patients,’ said Dr Derde. ‘That is why we were able to include our first patient on the 9th of March.’

The trial tests various drugs – rather than the usual one or two – for community-acquired pneumonia, with all the regulatory and ethical approvals in place. It was set up by a project called PREPARE for patients suffering from severe community-acquired pneumonia caused by bacteria or viruses, which kills about one in five people with it in ICU, although the figures can be much higher.

Results on steroids from the trial contributed to the World Health Organisation recommending them for COVID-19 patients in September 2020. By then, REMAP-CAP, which now involves about 300 hospitals, was testing lots of interventions (it currently has 31).

Doing this sets it apart from a traditional randomised controlled trial, which is the gold standard to prove whether a drug is effective or not. Patients are usually given either one or two drugs or a placebo, and then outcomes are compared. REMAP-CAP is different – and more flexible – in that it tests many types of treatments at the same time. One patient can receive multiple interventions, which is not unusual for someone severely ill. A regimen of treatments is ‘much more in line with your typical clinical treatment,’ said Dr Derde, who is the European coordinator of the trial.

The clinical trial design means that ‘we can analyse the interactions between drugs, which is a huge advantage in a pandemic,’ she said.

‘A single Covid patient can be randomised for up to eight separate aspects of their treatment,’ said Prof. Webb. ‘We’re obviously learning much more quickly, because we’re testing so many different things simultaneously.’ A patient is enrolled in one treatment ‘domain’, and then is randomly assigned to one of a handful of interventions in that domain.

The 12 different ‘domains’ of treatment include anti-coagulation treatments, anti-inflammatory drugs, and immune modulating drugs. ‘One patient might be involved in six or seven different domains of the trial,’ said Prof. Nichol. In fact, this better reflects how a patient with COVID-19 is treated in hospital, according to the doctors.

Monoclonal

A big result – presented in a pre-print study, so not yet peer reviewed – is that two monoclonal antibodies (tocilizumab and sarilumab) reduced death from COVID-19 in severely ill patients, and time spent in ICU. Those benefits seem to be on top of those from steroids, says Prof. Webb.

Tocilizumab and sarilumab block a chemical signal called interleukin-6 (IL-6), which stokes inflammation. In severe COVID-19, the inflammatory response of a patient’s immune system begins to damage body tissue, in friendly fire, while attacking the virus. There was therefore good reason to think the drugs might be effective.

Indeed, once a new disease turns up, and its mechanisms are reported, an array of medications will be considered by physicians. But they do not know which ones work. The results for COVID-19, explains Prof. Webb, ‘was quite a scattergun approach of clinicians using repurposed medicines.’

Sometimes, as in the case of the malaria drug hydroxychloroquine, a small study and lots of hype persuades some that an old drug is worth a try. But it requires a large clinical trial, such as REMAP-CAP, which involves 6,000 patients, to show whether that drug is safe and effective. Physicians can now prescribe the IL-6 blockers and steroids with greater confidence, while hydroxychloroquine is left on the shelf.

Indeed, finding that a drug does not work, or causes a negative effect, can be equally beneficial. ‘The anti-virals and the anti-coagulants have not just been ineffective, but may result in worse outcomes for patients,’ said Prof. Webb, about recent preliminary findings. ‘It is just as important to identify treatments that are harmful.’

It is difficult for a physician to know whether a drug is helping or hindering their patients. ‘For an individual doctor at a patient’s bedside, it can be hard to tease out if giving someone something helped or if they would have gotten better anyway,’ explained Prof. Nichol. Severely ill patients usually receive multiple interventions, which makes knowing which treatment was effective tougher.

Combinations

The REMAP-CAP trial was created to be multifactorial, meaning that the effects of many different treatment combinations on patients can show up in the data. Bayesian statistics, which applies probabilities to statistical problems, makes sense of all the data to answer crucial questions, such as when a treatment reaches a positive result, or if it is shown not to work, or if there are positive interactions between drugs. Such a strategy with multiple treatments had been used for cancer, but never a global ICU study.

At the heart of these trials is a simple fact: it is impossible to guess which treatments will work. Small studies can be biased and inconclusive, which is why large randomised trials are needed.

‘Years ago, I used to think that there were things that definitely would work, and then they didn’t,’ said Prof. Webb. ‘I’ve been doing clinical trials for so long now that the only thing I am confident of is that, when you do trials, you will get surprises.’

Dr Derde praises the European Union’s actions in 2014 ‘because they funded the European part of what is now REMAP-CAP, with the vision that they needed to set up an infrastructure for pandemic research.’ Other funders around the world, from Australia to New Zealand to Canada and the US, subsequently joined the effort.

REMAP-CAP is an international effort now, with 300 hospitals taking part in about 20 countries, testing out 31 different interventions. The trial will continue to prove which treatments work in severely ill COVID-19 patients. As the virus surges in many countries and until the vaccine rollout can control the pandemic, proven drugs are needed to save lives.



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