Video: Oral COVID-19 Vaccine

Oravax Medical is developing an oral COVID-19 vaccine.

The oral vaccine successfully produced antibodies in a preclinical study after a single dose.

Watch video at You Tube (0:55 minutes) . . . .


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Oramed Forms a Joint Venture, Oravax Medical Inc., for the Development of Novel Oral COVID-19 Vaccines . . . . .

Another Way “Good” Cholesterol Is Good: Combatting Inflammation

Testing how well “good” cholesterol particles reduce inflammation may help predict who is at heightened risk to develop cardiovascular disease caused by narrowed arteries, according to research published today in the American Heart Association’s flagship journal Circulation.

Assessing levels of high-density lipoprotein (HDL) cholesterol, known as “good cholesterol,” are already a standard part of formulas used to predict cardiovascular risk. A new test of the anti-inflammatory function of HDL seems to provide additional information that is independent of the quantity of HDL. If the results are confirmed in broader populations and a test developed for clinical use, adding anti-inflammatory capacity to risk scores may improve risk prediction and help people take steps to protect themselves against heart disease.

“HDL are very complex particles with anti-atherosclerotic functions that are not reflected by measuring just the cholesterol quantity,” said senior study author Uwe J.F. Tietge, M.D., Ph.D., professor and head of the division of clinical chemistry at the Karolinska Institute in Stockholm, Sweden. “Atherosclerosis [plaque build-up in the arteries] underlying cardiovascular disease is increasingly recognized as a disease with a strong inflammatory component, and a central biological function of HDL is to decrease inflammation.”

This study is the first to test whether better anti-inflammatory function of HDL particles protects against heart attacks and other serious heart-related events.

Participants included 680 white adults (average age of 59, 70% male) living in the Netherlands who were part of a large population study that began in 1997. All were healthy when they enrolled in the study. From the larger study participants were identified who’d had a first cardiovascular disease event before the end of the study follow-up. HDL particles were analyzed in 340 people who experienced a first fatal or non-fatal heart attack, were diagnosed with heart problems caused by narrowed heart arteries (ischemic heart disease) or who required a procedure to open clogged coronary arteries during the median 10.5-year follow-up period. These participants were matched to a control group of 340 people of the same age (within 5 years), sex, smoking status and HDL cholesterol levels who had no cardiovascular events during follow-up.

Several lab tests were performed for all participants at enrollment, including measuring the ability of isolated HDL particles to decrease the inflammatory response of endothelial cells lining blood vessels (called the anti-inflammatory capacity). Researchers also measured C-reactive protein, a substance that rises when there is more inflammation throughout the body, and cholesterol efflux capacity, a laboratory assessment of how efficiently HDL can remove cholesterol from cells that resemble those found in plaque.

The researchers found:

  • HDL anti-inflammatory capacity was significantly higher in people who remained healthy (31.6%) than in those who experienced a cardiovascular event (27%);
  • The association of anti-inflammatory capacity with cardiovascular events was independent of the established biomarkers of HDL cholesterol and C-reactive protein levels, and was also independent of cholesterol efflux capacity;
  • For every 22% increase in the ability of HDL particles to suppress inflammation in endothelial cells, participants were 23% less likely to have a cardiovascular event during the next decade;
  • The amount of protection from increased HDL anti-inflammatory capacity was higher in women than in men; and
  • Risk prediction was improved by adding HDL anti-inflammatory capacity to the Framingham Risk Score, or by replacing HDL cholesterol levels with this new measure of HDL function.

“By using a novel research tool, our results provide strong support for the concept that plaque buildup in the arteries has an inflammatory component, and that the biological properties of HDL particles have clinical relevance to cardiovascular disease risk prediction,” said Tietge.

Although the results raise intriguing possibilities for improved screening, the results must be confirmed in different populations. In addition, a simpler and hopefully automated test for anti-inflammatory capacity should be developed first, researchers said.

“The HDL cholesterol level is a good, established, simple and cost-efficient CVD risk biomarker. Our results, however, demonstrate that the anti-inflammatory capacity or assays looking at HDL function in general have the potential to provide clinically relevant information beyond the static HDL cholesterol measurements that are currently used,” Tietge said.

The findings also raise the possibility that medications to improve HDL anti-inflammatory capacity may be developed and used to lower heart disease risk.

Study limitations to be considered include that the study population was white and genetically similar, thus results are not generalizable to other race and ethnic groups. In addition, the researchers did not include stroke incidence in their analysis so conclusions cannot be drawn about HDL and stroke.

Source: American Heart Association

In Pictures: Soups Around the World

Banga – Nigeria

Beef pho (phở bò) – Vietnam

Borscht – Ukraine

Bouillabaisse – France

Caldo verde – Portugal

Chorba frik – Algeria, Libya and Tunisia

New System Uses Smartphone or Computer Cameras to Measure Pulse and Respiration Rate

Sara McQuate wrote . . . . . . . . .

Telehealth has become a critical way for doctors to still provide health care while minimizing in-person contact during COVID-19. But with phone or Zoom appointments, it’s harder for doctors to get important vital signs from a patient, such as their pulse or respiration rate, in real time.

A University of Washington-led team has developed a method that uses the camera on a person’s smartphone or computer to take their pulse and respiration signal from a real-time video of their face. The researchers presented this state-of-the-art system in December at the Neural Information Processing Systems conference.

Now the team is proposing a better system to measure these physiological signals. This system is less likely to be tripped up by different cameras, lighting conditions or facial features, such as skin color. The researchers will present these findings at the ACM Conference on Health, Interference, and Learning.

“Machine learning is pretty good at classifying images. If you give it a series of photos of cats and then tell it to find cats in other images, it can do it. But for machine learning to be helpful in remote health sensing, we need a system that can identify the region of interest in a video that holds the strongest source of physiological information — pulse, for example — and then measure that over time,” said lead author Xin Liu, a UW doctoral student in the Paul G. Allen School of Computer Science & Engineering.

“Every person is different,” Liu said. “So this system needs to be able to quickly adapt to each person’s unique physiological signature, and separate this from other variations, such as what they look like and what environment they are in.”

The team’s system is privacy preserving — it runs on the device instead of in the cloud — and uses machine learning to capture subtle changes in how light reflects off a person’s face, which is correlated with changing blood flow. Then it converts these changes into both pulse and respiration rate.

The first version of this system was trained with a dataset that contained both videos of people’s faces and “ground truth” information: each person’s pulse and respiration rate measured by standard instruments in the field. The system then used spatial and temporal information from the videos to calculate both vital signs. It outperformed similar machine learning systems on videos where subjects were moving and talking.

But while the system worked well on some datasets, it still struggled with others that contained different people, backgrounds and lighting. This is a common problem known as “overfitting,” the team said.

The researchers improved the system by having it produce a personalized machine learning model for each individual. Specifically, it helps look for important areas in a video frame that likely contain physiological features correlated with changing blood flow in a face under different contexts, such as different skin tones, lighting conditions and environments. From there, it can focus on that area and measure the pulse and respiration rate.

While this new system outperforms its predecessor when given more challenging datasets, especially for people with darker skin tones, there’s still more work to do, the team said.

“We acknowledge that there is still a trend toward inferior performance when the subject’s skin type is darker,” Liu said. “This is in part because light reflects differently off of darker skin, resulting in a weaker signal for the camera to pick up. Our team is actively developing new methods to solve this limitation.”

The researchers are also working on a variety of collaborations with doctors to see how this system performs in the clinic.

“Any ability to sense pulse or respiration rate remotely provides new opportunities for remote patient care and telemedicine. This could include self-care, follow-up care or triage, especially when someone doesn’t have convenient access to a clinic,” said senior author Shwetak Patel, a professor in both the Allen School and the electrical and computer engineering department. “It’s exciting to see academic communities working on new algorithmic approaches to address this with devices that people have in their homes.”

Source: University of Washington

Minestrone Milanese

Ingredients

1 oz smoked bacon
4 tablespoons olive oil
parsley, chopped
sage
1 clove of garlic, peeled and finely chopped
1 onion, finely chopped
a few celery stalks
2 carrots
1 leek
1 tomato, chopped
4 potatoes, diced
fresh basil leaves, chopped
3/4 cup fresh beans, or dried beans soaked overnight in cold water and drained
2 stock cubes
salt
pepper
1/2 small Savoy cabbage, separated into leaves
4 oz rice or vermicelli
grated Parmesan cheese to garnish

Method

  1. Chop and sauté the bacon, discarding liquid fat.
  2. In a large pan cook the oil, parsley to taste, sage, and the garlic and onion for a few minutes.
  3. Add the bacon, celery, carrots and leek, all finely sliced, the tomato, 2 potatoes, and 2 whole potatoes, the basil and the beans. Cook for a few minutes, stirring constantly.
  4. Add 10 cups hot, not boiling, water, the stock cubes, and salt and pepper to taste. Bring to a boil. Cook, covered, over low heat for 1-3/4 hours.
  5. Add the cabbage leaves and continue cooking for 45 minutes (in winter, cook cabbage for only 20 minutes).
  6. Add the rice 20 minutes before the end of the cooking time, or the vermicelli 8 minutes before the end of the cooking time. and serve with a generous amount of grated Parmesan cheese served separately.

Makes 4 to 6 servings.

Source: The Cook’s Book


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