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New Evidence Adamantly Suggests Epstein-Barr Virus Triggers MS

New research out of Harvard University strongly suggests that infection with the Epstein-Barr virus (EBV) is the leading cause of a debilitating disease of the brain and CNS – multiple sclerosis.   

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New Evidence Adamantly Suggests Epstein-Barr Virus Triggers MS

 

New research out of Harvard University may just spark interest in a new target for vaccination efforts. Evidence uncovered strongly suggests that infection with the Epstein-Barr virus is the leading cause of a debilitating disease of the brain and CNS – multiple sclerosis.   

Epstein-Barr virus, a member of the herpes virus family, is one of the most common human viruses. It’s best known for causing mononucleosis, the kissing disease.  

Science understands the mechanism of how MS disables. The immune system kicks into overdrive, stripping off the myelin sheath that insulates the nerve cell. This stripping results in nerve damage that disrupts the communication between the brain and the body. The symptoms vary and can range from mild to severe. 

What they haven’t been able to pinpoint yet is why the immune system does this. What triggers it? It’s likely that the Epstein-Barr Virus plays a crucial role. 

“The hypothesis that EBV causes MS has been investigated by our group and others for several years, but this is the first study providing compelling evidence of causality,” said Alberto Ascherio, professor of epidemiology and nutrition at Harvard Chan School and senior author of the study. 

To arrive at this conclusion, the team analyzed serum samples from the world’s largest collection of its kind – the Department of Defense Serum Repository. There, scientists have been collecting and storing blood samples from every member of the U.S. military since 1985 and have more than 62 million samples from over 10 million active and reserve duty members. 

Source: BioSpace

These samples are perfect for this kind of study since they are taken from usually young, healthy individuals entering the service. MS typically rears its ugly head in the 20’s and 30’s. In these blood samples, the team looked for signs of the EBV and its antibodies, along with neurofilament light chain (NfL). NfL levels in the bloodstream precede the onset of MS by a couple of years, as evidence that the neurons are under attack in the brain.   

The lack of NfL levels in the samples showing EBV presence proved against reverse pathology that might suggest those with MS are more likely to be infected with EBV.  

It showed clearly that infection with EBV increased the likelihood of developing MS alarmingly by more than 32-fold. Of course, many infected with EBV will never develop MS, making it clear there are other aspects to the pathogenesis of the disease.  

The study also can’t explain how EBV might spark the disease. Hypotheses include the virus carrying proteins that look like myelin, which could later trigger an immune reaction against the actual myelin. Or perhaps EBV resides in B cells, transforming them into in-house assassins against the nerve cells. The disease is multifactorial, meaning there’s not likely to be one clear cause. Genetic disposition, vitamin levels and environmental exposure all likely fill a role to make the perfect storm.  

EBV certainly wouldn’t be the only virus to cause brain inflammation. As we’ve all expanded our scientific knowledge through the global pandemic, we’ve learned that COVID-19 infection can also severely affect the brain, even in mild cases. A study out of Standford published last summer found unmistakable signs of inflammation and impaired circuit pathways in the brains of patients who had died of COVID-19. These findings help explain the mystery of “long COVID” in which many suffer from extended cognition and memory difficulties after infection.  

While COVID-19 now has multiple vaccinations, EBV does not yet. Past efforts have been abandoned for various reasons, and the virus didn’t seem a top priority as the illness it causes is typically not severe enough to be life-threatening. However, EBV has been linked to the development of several cancers and autoimmune diseases as well.  

With this new research, more R&D is likely to come down the vaccine pipeline. In fact, UMass Chan Medical School is already undertaking the job by utilizing Moderna’s mRNA against the Epstein-Barr virus. The study, Eclipse, is a Phase 1 trial in 18–30-year-old healthy adults. They’re testing out three doses against one placebo, targeting four glycoprotein antigens on the virus particle, similar to Moderna’s cytomegalovirus vaccine candidate. The first participant was dosed last week.  

BioSpace source:

https://www.biospace.com/article/-kissing-disease-virus-could-be-a-trigger-for-multiple-sclerosis-

 

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U.S. COVID-19 cases increased threefold over past month – Walensky

The United States has seen a threefold increase in daily COVID-19 cases over the past month and a steady increase over the past five weeks, U.S. Centers…

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U.S. COVID-19 cases increased threefold over past month – Walensky

WASHINGTON, May 18 (Reuters) – The United States has seen a threefold increase in daily COVID-19 cases over the past month and a steady increase over the past five weeks, U.S. Centers for Disease Control and Prevention Director Rochelle Walenksy said on Wednesday.

The seven-day average of daily cases was up 26% from the previous week to 94,000 cases per day, Walensky said at a White House briefing. The seven-day average for hospitalizations was up 19% to about 3,000 per day and the average for deaths was 275 per day, she said.

People queue to be tested for COVID-19 in Times Square, as the Omicron coronavirus variant continues to spread in Manhattan, New York City, U.S., December 20, 2021. REUTERS/Andrew Kelly/File Photo

“We of course must remember that each person lost to COVID-19 is a tragedy and that nearly 300 deaths a day is still far too many,” said Walensky.

 
Reporting by Susan Heavey and Ahmed Aboulenein

Our Standards: The Thomson Reuters Trust Principles.

 

Reuters source:

https://www.reuters.com/world/us/us-covid-19-cases-increased-threefold-over-past-month-walensky-2022-05-18

 

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In stop-COVID19 trial, Brensocatib did not improve condition of patients with severe COVID-19

Session:  D17, Top Knowledge in COVID Date and Time:  9:25 a.m. PT, Wednesday, May 18,2022 Location:  Room 2018/2020 (West Building, Level 2), Moscone…

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Session:  D17, Top Knowledge in COVID
Date and Time:  9:25 a.m. PT, Wednesday, May 18,2022
Location:  Room 2018/2020 (West Building, Level 2), Moscone Center

Credit: ATS

Session:  D17, Top Knowledge in COVID
Date and Time:  9:25 a.m. PT, Wednesday, May 18,2022
Location:  Room 2018/2020 (West Building, Level 2), Moscone Center

 

ATS 2022, San Francisco, CA – Brensocatib did not improve the clinical status of patients hospitalized with severe SARS-CoV-2 infection in the double-blind randomized, placebo-controlled STOP-COVID19 multicenter clinical trial, according to research published at the ATS 2022 international conference.

The study, which began in June of 2020, took place at 14 UK hospitals, where participants were randomized to receive 25 mg daily of brensocatib or placebo for 28 days.  One-hundred ninety patients received brensocatib, while 214 received placebo.

All patients in the study had confirmed SARS-CoV-2 infection and at least one risk factor for severe COVID-19, such as requiring supplemental oxygen, Individuals on mechanical ventilation were excluded from the study.  All participants received standard of care treatment.

“Treatments currently available to treat COVID-19, such as dexamethasone and anti-IL-6 antibodies, reduce inflammation, but their effect is not primarily on neutrophils or neutrophilic inflammation,” said presenting author Holly Keir, PhD, postdoctoral researcher, University of Dundee School of Medicine, Dundee, United Kingdom. “We performed the STOP-COVID trial to test the hypothesis that directly targeting neutrophilic inflammation by inhibiting dipeptidyl peptidase-1 (DPP1) would provide additional benefits to patients with severe COVID-19 on top of standard of care.”

Severe COVID-19 infection is primarily caused by an excessive and damaging immune response to the virus.  A number of different immune cells are involved in this response, including neutrophils. Neutrophils release enzymes and other substances that cause severe lung damage. Studies have consistently shown that high levels of neutrophilic inflammation are associated with worse outcomes in COVID-19. 

Brensocatib is an investigational oral inhibitor of DPP1, an enzyme responsible for the activation of neutrophil serine proteases.

In STOP-COVID19, time to clinical improvement and time to discharge were not different between groups. Mortality was 10.7 percent and 15.3 percent in the placebo and brensocatib treated groups, respectively. Oxygen and new ventilation use were also numerically greater in the brensocatib treated patients. Prespecified subgroup analyses based on age, sex, baseline severity, co-medications and duration of symptoms supported the primary results. Adverse events were reported in 46.3 percent of placebo treated patients and 44.8 percent of brensocatib treated patients.

The researchers also conducted a sub-study at two study sites to directly measure inflammation in patients receiving DPP1 inhibition or placebo.  They observed a strong anti-inflammatory effect of DPP1 inhibition on neutrophil protease enzymes.  Active blood neutrophil elastase levels were reduced by day eight in the treatment group and remained significantly lower up to day 29.

“Although we did not find a beneficial effect of treatment in this population, these results are important for future efforts to target neutrophilic inflammation in the lungs. STOP-COVID19 is the largest completed trial of DPP1 inhibition in humans and we have performed extensive characterization of how DPP1 inhibition affects the immune system’s response,” noted Dr. Keir. “Using state-of-the-art proteomics (the study of the structures, functions, and interactions of proteins) we have already seen important changes in neutrophils with DPP1 inhibition that will help us to better understand the potential role of this treatment in other diseases.”

One of these diseases is bronchiectasis, where a phase 2 trial published in 2020 showed that brensocatib reduced the risk of exacerbations.

The STOP-COVID19 study was an investigator-initiated study sponsored by the University of Dundee and funded by Insmed Incorporated.

 

VIEW ABSTRACT

You may be interested in other newsworthy research on pulmonary infections, such as “A Nine-Gene Blood-Based Signature Meets the World Health Organization Target Product Profiles for Diagnosis of Active Tuberculosis and Predicting Progression from Latent to Active Disease.”

CONTACT FOR MEDIA:

Grant Hill

G.Hill@Dundee.ac.uk


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Next-generation weather models cross the divide to real-world impact

Each winter, spring, and summer, extreme weather forecasters and researchers meet to test the latest, most promising severe weather forecast tools and…

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Each winter, spring, and summer, extreme weather forecasters and researchers meet to test the latest, most promising severe weather forecast tools and innovations to see how they perform in real-world settings.

Credit: NOAA

Each winter, spring, and summer, extreme weather forecasters and researchers meet to test the latest, most promising severe weather forecast tools and innovations to see how they perform in real-world settings.

These testbed experiments, orchestrated by the National Oceanic and Atmospheric Administration (NOAA), forecast winter storms, severe thunderstorms, and flash flooding, respectively.

The Hydrometeorology Testbed recently held the 12th annual Winter Weather Experiment (WWE). An immersive, collaborative, “research-to-operations” experience, it brought together members of the forecasting, research, and academic communities to evaluate and discuss winter weather forecast challenges.

“We generate operational forecasts using new inputs or new models testing how well they work,” said Keith Brewster, senior research scientist and operations director of the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma. “If we promise a forecast where thunderstorms occur, can we expect a forecaster to use it?”

Humming along in the background of the experiment are supercomputers at the Texas Advanced Computing Center (TACC) — among the fastest available to academic researchers in the world.

The CAPS team began using TACC systems for the Hazardous Weather Testbed Spring Experiment in 2011 to better predict severe thunderstorms. They computed at that time on the original Stampede supercomputer at TACC — the 6th fastest in the world in its prime. From 2017-2021, they used Stamepde2 (12th fastest) through the Extreme Science and Engineering Discovery Environment (XSEDE). Since 2021, they have used Frontera, the fastest university supercomputer in the world and currently the 13th fastest overall.

“What TACC and XSEDE offer us is the ability to do these real-time, or near-real-time experiments,” Brewster said.

The CAPS team submits their forecasting simulations by 10:00pm, after weather observations and other input data comes in for the 00 UTC cycle. The simulations run overnight and are ready by 8:00am the next morning, predicting weather events out to three-and-a-half days.

“On Stampede, we worked with TACC to have a special queue set up where we have a dedicated number of cores allocated to us,” Brewster said. This type of ‘urgent computing’ has become a hallmark of TACC, enabling the center to forecast hurricane storm surge, monitor space junk in low Earth orbit, and power COVID-19 models. “More recently, on Frontera, the capacity is such that we can run in the regular queue, using a VIP priority, making our use more efficient and less disruptive to other research users.”

This year’s Winter Weather Experiment had three key science goals: to subjectively gauge the utility of convection-allowing model (CAM) forecasts to improve two-to-three day snowfall forecasts; objectively score the snowfall forecasts using community standard verification systems; and determine the optimal combination of physics to use in next-generation models.

The team was primarily interested in predicting the amount of snowfall accumulation, but they also tested their ability to determine the differences between snow, sleet, and freezing rain in forecasts, and predict other facets of winter weather, like wind speed.

“Giving forecasters the opportunity to use these experimental models in real situations allows forecasters and researchers to determine the strengths, operational challenges, and forecaster usability early on in the development stage,” said James Correia Jr., coordinator for the Hydrometeorology Testbed. “This allows us, together, in NOAA testbeds, to make improvements in our forecasting process, models, and the way we approach and solve research and operational challenges.”

Recent testbed programs have also included the important task of evaluating NOAA’s next-generation weather model, the FV3 model. This model has shown success in global-scale forecasting, and the agency plans to also utilize it operationally for much higher resolution regional modeling as represented in the high-impact testbeds. The new multi-scale forecast system is known as the Unified Forecasting System (UFS).

“In addition to real-time testing, CAPS has been using TACC supercomputers to re-run cases to identify the root-cause of issues that were identified during prior testbeds,” Brewster said. “This leads to tuning and other enhancements to the original codes.”

The Winter Weather Experiment ran for 27 case days on Frontera in near-real-time over the course of the winter, including objective verification and machine learning training — a forward-looking aspect of the research. Brewster presented the results as a webinar organized by NOAA in March 2022.

Following the experiment, researchers typically do more detailed studies on specific facets of the forecasts, with funding from NOAA’s Weather Program Office as part of the Testbed competition in collaboration with NOAA’s Weather Prediction Center and Storm Prediction Center – both divisions of the National Weather Service.

Testing Ensemble Consensus Methods

Most weather watchers are familiar with the idea of ensemble models — the swarms of tracks that represent the results from various simulations, which are averaged and interpreted by weather forecasters.

Using Frontera, Brewster’s team generates real-time ensemble forecasts.

“In decision theory, it has been shown that when you get a consensus of experts, you get better advice than from a single person,” Brewster said. “Thanks to TACC, we can generate 13 models — 13 ‘experts’ predicting what the weather is going to be. From there, we’re working on how to develop ensemble consensus products that best help improve forecasts.”

Sometimes useability by a human operator trumps pure prediction skills. Communicating the consensus decision from an ensemble of forecasts is such an example.

“We researchers are in there, observing and participating, for one week — as if we were in the weather office, creating forecasts, so people like myself can see the issues,” Brewster explained. “We try to be realistic: can someone really look at ten to 15 models? Or does it create more uncertainty?”

One approach the CAPS team has been exploring for ensemble consensus methods is the local probability match mean (LPM) method. The LPM method divides an area into patches, calculates the atmospheric dynamics over that patch, and distributes the results locally. (Nathan Snook and the CAPS team described the method, and compared various ways of computing this mean, in a 2020 paper in Geophysical Research Letters.)

An assessment of the accuracy by NOAA showed the local probability match mean (LPM) performed slightly worse than probability match (PM) mean in objective precipitation scoring.

“But this is where the testbed activities come in,” Brewster said. “When a human looks at a forecast, they’re not looking at raw numbers at a site. They’re looking at the shape — consensus reflectivity — and in this respect, LPM was deemed to be better. That was a win for our team.”

The LPM has since been implemented in NOAA’s operational High Resolution Ensemble Forecast system. This is the goal of the NOAA Testbed program: taking research ideas and getting them through testing and evaluation in quasi-operational settings to actual operational deployment.

“That’s what we call technology transfer,” Brewster said. “There’s a tech divide where researchers like our team work on models, produce papers, and it can be hard to get new models or concepts into the operations. Tech transfer happened because it was proven, not just running on TACC and to other researchers, but to other forecasters. That gets us over the divide from journal articles to impacting real-world forecasts.”


The 2022 NOAA Hazardous Weather Testbed Spring Forecasting Experiment is being held from May 3 – June 2 and is again leveraging supercomputers at TACC. For more information about the upcoming experiment, contact: Keli Pirtle, Public Affairs Specialist, NOAA Communications, keli.pirtle@noaa.gov.


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