Ad
Ad
Ad
Author

user

Browsing

A team of researchers from John Hopkins Medicine has found that in people living with HIV or high levels of cholesterol, a six-week course of medication improved the function of the coronary arteries that provide oxygen to the heart.

A drug names PCSK9 inhibiter was used in the study. This drug lowers the activity of PCSK9, a protein involved in cholesterol metabolism. These levels are higher in people who have HIV and those with high cholesterol levels. The team found that a six-week course of this medicine improved the function of the coronary arteries that supply oxygen to the heart.

PCSK9 levels are higher in people with HIV and those with high cholesterol. Currently, HIV patients receive antiretroviral medications and rarely die from the virus itself. However, the same patients have an increased risk of cardiovascular disease as a result of chronic inflammation due to the virus, and they are significantly more likely to die from cardiovascular disease than the regular population.

The team suggested that there may be a way to control cardiovascular disease risk in those living with HIV and other cardiovascular risk factors, such as high cholesterol, by improving blood vessels’ function. Thorsten M. Leucker, M.D., Ph.D., assistant professor of medicine and the lead author of the study, explained that the team hypothesized that PCSK9 mediates an inflammatory response that impairs vascular function with its effects on cholesterol metabolism. They tested the process with the protein’s inhibitor to learning whether it could help people with impaired blood vessel function.

The team performed the study on 19 people with HIV and 11 people with high blood lipids, but HV patients were given the drug evolocumab, a PCSK9 inhibitor for six weeks. In the beginning, the team used cardiac magnetic resonance imaging (MRI) to measure the area and blood flow in the right coronary artery at rest and during a hand exercise, which usually results in relaxation of the blood vessels. When the test was performed on healthy people, the coronary artery responds to the exercise, and its area increases, allowing more blood to flow through.

In patients with impaired blood vessel function, the artery doesn’t get more substantial or may even constrict. Therefore, the blood flow remains the same or decreases in those with impaired blood vessel function.

After the course, the participants living with HIV had an average 7.9% increase in the coronary artery area and a 10.1% increase in blood flow during the handgrip exercise when compared to the resting value. These changes were higher than the changes from rest to handgrip exercise during the baseline pre-treatment visit. Participants with high blood lipids also had improved coronary artery areas and an increase in blood flow after six weeks of treatment. The team said further studies would be required to include more patients and study them over a longer time.

A team of researchers from the University of Cambridge has developed a “no-touch touchscreen” in collaboration with Jaguar Land Rover. This innovative screen can also have applications in the post-pandemic world by reducing the risk of transmitting pathogens to the surface.  

The patented technology is known as “predictive touch,” uses a combination of artificial intelligence and sensor technology to predict a user’s intended target on the touchscreens and other displays like the control panel, and selecting the correct item before the user’s hand reaches the screen.

Today, more and more cars have touchscreen technology to control navigation, entertainment, and temperature control systems. Users can often miss the correct item, for instance, due to acceleration or vibrations from road conditions, and have to reselect the option. This could lead to diverted attention and increase the risk of an accident.

In the lab-based tests, driving simulators, and road trials, the predictive touch technology reduced interaction effort and time by 50% due to its ability to predict the user’s intended target with high accuracy early in the pointing ability.

Additionally, the technology could be used in smartphones and useful while walking or jogging, allowing users to quickly and accurately select items without any physical contact. It even works in situations such as moving car on a bumpy road, or if the user suffers from a motor disability which causes a tremor or sudden jerks, such as Parkinson’s disease or cerebral palsy.

The technology uses machine learning and artificial intelligence to determine the item the user intends to select on the screen early in the pointing task, speeding up the interaction. It uses a gesture tracker, including vision-based sensors, which are common in consumer electronics, contextual information like user profile, interface design, environmental conditions, and data available from other sensors, including eye-gaze tracker, to determine the user’s intent in real-time.

Lee Skrypchuk, Human Machine Interface Technical Specialist at Jaguar Land Rover, explained that the technology allows the company to make vehicles safer by reducing the cognitive load on the drivers and increasing the amount of time they can spend focused on the road ahead.

It could also be used for display screens that do not have physical touch surfaces such as a 2D, 3D projection, or holograms. Besides, it promotes inclusive design practices and offers extra design flexibilities, since the interface functionality can be seamlessly personalized for given users and the user ability no longer restricts the display size or location to reach-touch.

The solution for contactless interactions has reached a high technology readiness level. It can be seamlessly integrated into existing touchscreens and interactive displays, so long as the correct data is available to support the machine learning algorithm.

Head and neck cancer are one of the most common types of tumors observed worldwide, and squamous cell carcinoma (HNSCC) is responsible for the majority of such cases. According to new research by a team of researchers at the University of California, San Diego School of Medicine and Moores Cancer Centre, a potential drug candidate called tipifarnib showed promise in treating HNSCC tumors with mutations in the HRAS gene.

The findings of the study shed light on the HRAS gene, a member of the RAS family of genes that produce proteins that regulate a variety of cellular processes, including growth, differentiation, and movement. In 4-8 percent of HNSCC tumors, the HRAS gene is mutated. Senior co-author of the study, J. Silvio Gutkind, Ph.D., Distinguished Professor of Pharmacology and associate director of basic science at UC San Diego Moores Cancer Centre, explained that the preclinical research has the potential to extend to the entire HNSCC patient community, whose overall survival rates are limited in recurrent or metastatic disease, and existing therapeutic options that are far from optimal, with response rates of roughly 10-20%.  

These preclinical findings support the idea that HRAS represents a druggable oncogene in HNSCC through tipifarnib’s inhibition of a critical enzyme. It is a precision therapeutic option for HNSCCs harboring HRAS mutations.

Tipifarnib is a selective inhibitor of farnesyltransferase, an enzyme that plays a crucial role in anchoring some RAS family proteins to cellular membranes. Unlike KRAS and NRAS gene mutations, HRAS is dependent on farnesyltransferase activity for function, offering a way to indirectly target an oncogenic RAS isoform using a well-characterized drug with extensive clinical experience.

The team found that cell line and patient-derived HNSCC models harboring HRAS mutations were highly sensitive to tipifarnib, which the authors said has demonstrated encouraging preliminary clinical activity in patients with relapsed or refractory HRAS-mutant HNSCC to date. Currently, a San Diego-based biopharmaceutical company, Kura Oncology, is conducting a nationwide clinical trial to assess the safety and efficacy of tipifarnib in head and neck cancer with HRAS mutations.

Treatment with tipifarnib had a multifaceted effect on the biology of HRAS-mutant HNSCC tumors, reducing oncogenic signaling and proliferation, while increasing apoptosis (cell death), blocking angiogenesis (the development of new blood vessels in tumors) and driving squamous differentiation of tumors.  

Head and neck cancer is the primary reason for approximately 650,000 cases and 330,000 deaths every year worldwide. In the US, about 4% of all cancers are head and neck, with an estimated 65,630 patients diagnosed each year, two-thirds of them men and 14,500 deaths.

In the U.S., around 19% of people have a diagnosable mental disorder. Not all adults get to meet psychologists to diagnose their mental illness because of many reasons, including cost, limited hours, lack of enough certified psychologists and psychiatrists, and difficulty accessing care. In the first of its kind research, a team of researchers studied the impact of a text-messaging-based intervention as a potential tool to a mental health treatment program versus one without text messaging. A texting intervention can be an effective, promising, and potential tool to augment care for adults who require immediate medical attention. The findings of the study have been published in the scientific journal Psychiatric Services.

Approximately 91% of adults found texting intervention to be feasible, 94% stated that it made them feel better, while 87% said they would suggest it to their friend.

Assistant Professor William J. Hudenko of the Department of Psychological and Brain Sciences at Dartmouth, who is also the co-author of the study, said: “This particular research is exciting because we saw real improvement in those who accepted this mode of intervention on top of regular care. This was true for people who have some of the most serious forms of mental disorders and illnesses. The outcomes are promising, and we expect that adults with a less severe form of mental illness may even do better with this type of intervention.”

Because of the current COVID-19 crisis, many individuals’ schedules have been disrupted, which may prevent them from having routine access to a psychiatrist or therapist, such as parents who have children at home. Hudenko explained: “Texting can be a meaningful way to bridge this gap, by providing a means to access mental health services remotely. Text-based psychotherapy is a feasible solution for the current situation, as it provides asynchronous contact with a psychologist.”

For the research, the team assessed the impact of texting intervention as an add-on to an assertive community treatment program versus the latter alone. Those with an assertive community treatment program, people living with serious mental illnesses have a particular team who directs them with finding a job and housing, managing therapeutics, as well as providing clinic-based services.

Individuals having severe mental disorders are more probably to go through symptoms every day, which may result in them requiring additional therapy. The study consisted of 49 participants — with 62% having schizophrenia, 24% having bipolar disorder, and 14 percent having depression. Studies were conducted at baseline, after three months of conducting trials, and during a follow-up six months later.

In the overall trial, around 12,000 messages were sent, and every message was encoded, monitored, and discussed with a clinician. The outcomes suggested that 95% began with the intervention and texted 69% of possible days. On average, study participants sent around 165 or more texts and received 158 or more. The team of researchers further plans to study the impact of texting intervention in mental health on a broader spectrum.

A team of researchers from the University of Sheffield’s Neuroscience Institute claims that artificial intelligence (AI) could help speed up and improve the diagnosis of Alzheimer’s disease. The study assesses how the practice of AI in healthcare could help save time and the economic impact that few neurodegenerative diseases such as Parkinson’s and Alzheimer’s put on the NHS.

The primary risk factor associated with neurological disorders is the person’s age. With the majority of the population across the world living longer than before, the incidences of them developing a neurodegenerative disease is expected to reach record highs. The number of people living with the disorder is predicted to reach 115 million by 2050, which might pose a real challenge for the healthcare system.

The study’s findings — published in the scientific journal Nature Reviews Neurology — underlines how advanced AI technologies such as machine learning (ML), can detect and identify neurological disorders before its progression. This can improve the chances of the patients profiting from effective disease-modifying treatment.

Dr. Laura Ferraiuolo of the University of Sheffield, who is the lead author of the study, said: “The majority of neurological disorders have no cure and are often diagnosed late because of their molecular complexity. The routine use of AI and advanced technologies may prove helpful in predicting the progression of the disease in patients or how severely their motor skills will decline over time.”

She further included: “AI technologies can be used to help patients discuss their symptoms regardless of where they are, which will be a huge benefit to people with mobility issues.”

AI-powered technologies can be trained to identify changes caused by diseases in medical images, speech recordings, videos showing patients’ behavior, and information about patients’ mobility, making AI a valuable diagnostic aid. For instance, it can also be used by trained professionals to study images instantly and point out critical findings for an immediate follow-up.

The current research is a result of a long-term collaboration between the researchers at the University of Sheffield’s Neuroscience Institute and BenevolentAI, a biotech company. Dr. Guillaume Hautbergue, Monika Myszczynska, and Dr. Richard Mead are the researchers from the Neuroscience Institute who contributed to the research.

Monica Myszczynska, who is the first author of the study, said: “Leveraging the power of AI in clinical settings can result in savings in the NHS by helping patients discuss their condition remotely — which is relevant during the COVID-19 crisis — and the time patients and public health professionals spend in the clinic.”

“It is too soon to predict the results in terms of treatments but, in this research, we evaluated how ML techniques can be used to identify the best treatment for people based on their disease stage or how it could be used to recognize new therapeutic targets and drugs.”

“Further research will be needed to carry out on the improvement of present diagnostic techniques and the development of new algorithms to leverage AI in disease diagnosis and drug discovery. AI needs constant feeding of data; hence collaborations and the generation of international associations are the keys to further endeavors,” she added.

A vaccine is the most effective public health measure to prevent infectious diseases. Vaccines can reduce the risk of infection by working alongside the body’s natural defenses to safely develop immunity to the virus. However, the immune system fights infection in several different ways. To be effective, a vaccine must trigger the right type of immune response to recognize and destroy the virus, bacteria, or parasite.

The majority of vaccines like polio and measles vaccines, stimulate a type of immune response called antibody-mediated immunity. But for some chronic infectious diseases like tuberculosis and malaria, a different kind of immune response, known as cell-mediated immunity is required. Unfortunately, efforts to create a vaccine that prompts a cell-mediated immune response have had limited access.

A team of researchers at the University of Calgary’s Snyder Institute for Chronic Diseases has discovered new insights that may help develop an effective vaccine. Dr. Nathan Peters, Ph.D., lead author of the study, associate professor at the University of Calgary’s Cumming School of Medicine and Faculty of Veterinary Medicine (UCVM) explained that vaccination often involved polarizing the immune system towards the type of immune response believed in protecting a given infection and away from reactions thought to be non-protective.

The team also explained that they had been entirely focused on generating the cell-mediated response that is required to fight these chronic infections directly because of this new approach. The types of immunity that they didn’t think were essential or considered non-protective are critical to regulating the protective cell-mediated response to ensure the immune system mounts a balanced defense.

The research findings show that rather than enhancing protection, a highly polarized cell-mediated response that was believed to be protective was detrimental. Dr. Matheus Carneiro, Ph.D., postdoctoral scholar and co-author of the study, claimed that by studying the body’s immune response to infection, the team has found that excessive polarization can backfire. Understanding the importance of other aspects of the immune response during these infections. The different responses played a significant role in regulating excessive inflammation, which, in the absence of regulation, actually facilitated infection.

The fundamental observation could also inform vaccine design for infectious diseases such as COVID-19, malaria, tuberculosis, and the parasitic disease leishmaniasis. These observations provide new insight into the regulation of immunity against infectious diseases and provide a more holistic framework to design vaccines for those infections that don’t have one.

A team of researchers from the UPMC and University of Pittsburgh developed an artificial intelligence (AI) program that can recognize and characterize prostate cancer up to the highest accuracy to date. The findings of the study have been published in the scientific journal The Lancet Digital Health.

Rajiv Dhar, M.D., M.B.A, and the senior author of the study, said: “Humans are good at identifying anomalies, but they have their own experiences or biases. Machines are not attached to the story. There’s certainly a thing of standardizing care.” Dhar is also the chief pathologist and vice-chair of pathology at UPMC Shadyside and professor of biomedical informatics at the University of Pittsburgh.

In order to train the program to detect prostate cancer, Dhir and his team provided images from a million parts of stained tissue slides taken from biopsies of patients. Expert pathologists labeled every image to teach the AI how to differentiate between healthy and cancerous tissue. The program was then run on a separate set of 1,600 slides taken from 100 individuals who were suspected of having prostate cancer.

While testing, the program showed 98% sensitivity and 97% specificity at identifying prostate cancer — considerably higher than reported in the past for algorithms working from tissue slides.

Moreover, this is the first-ever program that is much more than cancer detection, reporting high accuracy for tumor grading, sizing, and invasion of the healthy nerves. These features are considered equally important in the pathology report. Additionally, the algorithm flagged six slides that were not recognized by the pathologists.

In any case, Dhir said that this doesn’t necessarily imply that the algorithm is superior to humans. For instance, in the course of examining the patients, the pathologist could have easily seen enough in the samples that could tell him whether the patient has a malignant tumor. For less experienced pathologists, although, the AI could act as a failsafe to catch cases that might otherwise be missed.

Dhir further mentioned that algorithms like this are very important in uncommon lesions. A person who is not experienced enough may not be able to make the correct evaluation. That’s the best part of the system. While these findings look promising, Dhir warns that new AI programs will have to be trained to identify different types of cancer, for example, breast cancer.

According to the latest research by Yale University, the differing immune system responses of patients with COVID-19 can help predict who is going to experience moderate and severe consequences of the disease. The findings may be resourceful and help identify individuals at high risk of severe illness earlier in their hospitalization and suggest drugs to treat COVID-19.

The researchers examined 113 patients admitted to Yale New Haven Hospital. They analyzed the patients’ differing immune system responses during their hospital stay, from the time of admittance to discharge until death.

The team found that all the patients shared a common COVID-19 “signature symptom” in their immune system activity early in the course. But those who experienced only moderate symptoms showing diminishing immune system responses and viral load over time. Patients who went on to develop severe cases of the disease exhibited no reduction in viral load or immune system reaction. Many of the immune system signals in these patients accelerated.

But even in the first course of treatment, the team found indicators that predicted which patients were at the highest risk of developing severe forms of illness. Akiko Iwasaki, the Waldemar Von Zedtwitz Professor of Immunobiology and Molecular and Development Biology Investigator for the Howard Hughes Medical Institute, claimed that the team was able to pull out signatures of the disease risk.

The researchers had known that the immune system unleashes a vast and damaging “cytokine storm” in severe cases of COVID-19. But these elements of the immune system response most responsible for the damage were unknown. The analysis found some interesting links to poor outcomes. Curiously, one risk factor was the presence of alpha interferon; a cytokine mobilized to combat viral pathogens like the flu virus. However, COVID-19 patients with high levels of alpha interferon fared worse than those with low levels.

Researchers explained that the virus doesn’t seem to care about alpha interferon. The cytokine appears to be hurting, not helping. Another prognosticator of poor outcomes is the activation of the inflammasome, a complex of proteins that detects pathogens and triggers an inflammatory response to infection. Inflammasome activation was linked to poor results and even death in several patients.

The team also found that people who respond better to the infection tend to express high levels of growth factors, a type of cytokine that repairs tissue damage to the linings of blood vessels and lungs. Together, the data can help predict patients at high risk of poor outcomes. They also said drugs that target specific causes of inflammation identified in the study could help treat the patients at risk of developing severe cases of COVID-19.

The COVID-19 pandemic has kept many people inside their homes, letting them enjoy peace of mind and showing how cities can be like with less noise, congestion, traffic, and pollution. Parking lots and roads take up the majority of the land that can also be used for other useful establishments.

When home quarantine came into effect in the USA in March, streets and parking lots went deserted overnight. Within days, municipalities across the US started shifting these places to other uses that better suited the public. Experts who have studied the transportation behavior claim that people rely on cars, SUVs, and trucks. Various factors like weather, climatic conditions, and time restraints prevent people from using bicycles as their primary mode of transport. A simple step like starting to reconfigure the city streets can break down the transportation barriers and usher into a new culture of getting around town using means of transport.

In larger cities, nearly half of the car trips are less than 4 miles, and using cars for shorter distances costs more. For instance, traffic fatalities are soaring in several cities, even though cycling and walking rates are declining. Pollution from vehicles also contributes to climate change and worsens air quality. New visions for streets, where cars use less space and are replaced by smaller vehicles for individual riders, are gaining importance.

New modes of transport include e-bikes, e-scooters, and hoverboards. These vehicles have already been attracting attention even before COVID-19, complementing the conventional bicycles, whose sales have increased during the pandemic.

Thinking about the future of the cities suggests that solely relying on cars as a form of transport has run its course. By minimally modifying the existing infrastructure, city planners can repurpose roads and parking spaces while ensuring the same ease of reaching daily services. Emerging trends of mobility and changing mindsets can help deliver these opportunities. Bicycles and other small vehicles provide an idea to shift how city streets are used.

Researchers have also demonstrated that people will adopt new ways of getting around town when they are confident enough about the route to be safe to travel. Some streets affected by COVID-19 have reduced traffic lanes and closed roads to traffic as the first step. But they lack the network connectivity. Networks quickly develop as more people use them. The easiest way to build one that is scaled and purposed for people starts by identifying streets used to make short trips.

Experts say that leaders can decide which streets should prioritize vehicles such as bicycles instead of cars. Changes might also include physical demarcations in lanes and signs. These changes might require waivers to exempt them from adhering to current engineering guidelines and standards, restricting innovation.  

Big and small US cities are experimenting with different strategies and contending with long-standing financial concerns about which streets to change. For instance, Minneapolis has closed down parkways to cars, reserving them only for cyclists and walkers. Other cities are using this time to test new ways of sharing a broader array of streets among cyclists, pedestrians, and car drivers. Researchers are providing tools to identify the most promising places to reallocate spaces for pop-up cycleways.

A team of researchers from the George Washington University has built a minuscule device that could allow doctors to diagnose and detect COVID-19 disease using mobile phones instantly.

The team — led by researchers Mona Zaghloul and Yangyang Zhao of the School of Engineering and Applied Science and Jeanne Jordan of the Milken Institute School of Public Health — has been awarded a $50,000 COVID-19 Technology Maturation Grant by the GW’s Technology Commercialization Office (TCO).

Dr. Zaghloul, a professor from the Department of electrical and computer engineering, and Dr. Zhao, her former doctoral student, built the minuscule device with the National Institute of Standards and Technology to diagnose and track various species of gas. George Washington University holds a patent to the device, which is as tiny as a hair strand and covered in a thin layer of gold. When the gold surface combines with other molecules, similar to those of a gas, the wavelength of light bouncing off the surface changes, with the formation of light of different colors. Different gasses should hence cause various shifts in light, which is then tracked and learned by AI programs.

Dr. Jordan joined Dr. Zaghloul, and Dr. Zhao, with the COVID-19 outbreak and the potential applications of the device, became evident. She said that the sensor is regulated directly to test the virus, instead of the antibodies that may be present in the bloodstream of a person after he/she contacts the infection.

The surface of the device could be coated with a reagent, or a solution that contains proteins that bond particularly with the virus that causes COVID-19. The virus binds to the surface with an infected person’s sample, creating an optical change that could be easily sensed by cell phone cameras.

Dr. Jordan said: “These are devices that doctors could go out with into the field to check whether a person has contracted the infection, either at a close-by center or directly in the community. They’re very swift — the turnaround time for the machine to show the results is within minutes — and the testing has to be done right there instead of sending the blood sample to a large commercial laboratory with a huge backlog. Accordingly, public health professionals would know if someone needs to be quarantined immediately and to get the names of their contacts so that they can be diagnosed.

Dr. Zaghloul said that the device would help communities in building trackable real-time databases of those affected with COVID-19. Besides, people can upload information directly to the cloud. The grant will allow the researchers to buy a reagent that is commercially available and samples of the non-infectious inactivated virus. However, they would take some time to reach the marketplace.

Initially, the team will need to ensure that bonding between the reagents applied to the device and the virus takes place, and is noticeable. Later, they’ll have to see if the virus particles can be detected using the device. Moreover, they need to see if the device binds other common human coronaviruses that cause mild flu in those who have contracted the virus. For example, if it does, it will change the reflected light, and it will be distinguishable from the change that occurs when sensing COVID-19 binding.

Dr. Zaghloul said that if further tests happen successfully, it’ll be very good for GW.