Category: Medical Research & Technology

Categories : Diseases, Syndromes and Conditions Medical Research & TechnologyTags :

Researchers Study Enzyme Processes for New Drugs

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Traditional discovery has produced drugs that effectively target proteins directly involved with disease, but options are starting to run out and researchers are looking to more complex and obscure interactions for drug targets.

So far, drug discovery has used the ‘small molecule’ approach, where a specific protein is targetted in a cancer cell to shut it down and bring down the cancer cell as a whole. Up until this point, traditional drugs have only been able to target proteins that are involved in the disease that also have activities that are amenable to the small molecule approach, leaving a vast number of proteins unaddressed. Many of these other proteins may be involved in disease processes behind the scenes.

“It’s starting to get to the point where we’ve kind of taken traditional drug discovery as far as we can, and we really need something new,” explained University of Nevada, Las Vegas biochemist Gary Kleiger.

“Cancer cells are clever,” Kleiger said. “They can evolve very, very quickly. So, a drug might be working at first—targeting an enzyme and telling that enzyme, ‘stop doing your activity,’ which can stop the cancer cells from growing. Those cancer cells appear to lie dormant, but all the while there are still little things that happen that eventually enable those cancer cells to bypass that drug.” Therefore, in order to stay ahead of cancer’s capacity to evolve drug resistance, it is necessary to target many additional disease-causing proteins, and thus, limiting the landscape of druggable proteins is a serious disadvantage.

The new approach by investigated by Kleiger and collaborators uses a family of human enzymes called ubiquitin ligases found in human cells. Of about 20 000 known proteins in the human body, some 5-10% are enzymes.

Kleiger’s team uses cutting edge cryo electron microscopes that can image the ubiquitin ligases when they’re at work. To test their hypotheses, Kleiger and collaborators measure the activity of ‘mutated’ enzymes that should now be defective in their activities.

Kleiger compared the process to how a 50 000 year old society might view a bicycle. They could identify its purpose and general properties, but could test the importance of a certain gear; if it was bent, the bicycle would no longer function. “We can do that at the molecular level with the enzymes,” he said.

Source: Medical Xpress

Journal information: Daniel Horn-Ghetko et al, Ubiquitin ligation to F-box protein targets by SCF–RBR E3–E3 super-assembly, Nature (2021). DOI: 10.1038/s41586-021-03197-9

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Battery Backups Can Protect People Dependent on Medical Equipment

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A battery. Photo by Danilo Alvesd on Unsplash.

In countries prone to blackouts from extreme weather events (and in some cases solar flares) battery backups could provide a viable alternative to keep the medical support systems for vulnerable family members functioning. As climate change is set to increase the frequency and severity of weather-related blackouts, a study from the Columbia University Mailman School of Public Health examined the value of battery backups.

Millions of people are reliant on home medical equipment – the elderly, ill people, many of whom are poor or otherwise vulnerable. Medical equipment such as oxygen concentrators, nebulisers, ventilators, and dialysis and sleep apnoea machines often have no backup power in case of an outage.

In a 2019 wildfire which caused power outages, many vulnerable residents reported complications, such as one man who awoke, unable to breathe when his sleep apnoea breathing machine stopped functioning.
Community centres such as schools are often turned to for services when power fails, such as using their refrigerators to store food, but many do not have backup power.

“Climate change coupled with aging energy infrastructure is driving extreme weather-related power outages, as we’ve seen recently in Texas,” said study co-author Diana Hernández, PhD, Associate Professor of Sociomedical Sciences, Columbia University, “The technology to improve resiliency and energy independence exists, and it needs to be made more accessible to those who could most benefit. Battery storage units, particularly those powered by the sun, are a critical tool to help vulnerable individuals and communities survive the climate crisis.”

In the US territory of Puerto Rico, following the widespread destruction of the electrical grid by Hurricane Maria, many residents used solar panels instead of diesel generators due to ease of use, low cost, and not emitting fumes that exacerbate asthma and other lung conditions

A review of literature showed that blackouts can result in negative health consequences ranging from carbon monoxide poisoning, temperature-related illness, gastrointestinal illness, and mortality to cardiovascular, respiratory, and hospitalisations for kidney disease, especially for individuals dependent on electrically powered medical equipment.

Beyond electrical backup, in the US, older adults, poorer families, and individuals of non-Hispanic Black and Hispanic race/ethnicity are also less likely to have emergency supplies of food, water and medicine in the event of disaster.

Overall, the researchers found that more work is needed to better define and capture the relevant exposures and outcomes. “There is urgent need for data to inform disaster mitigation, preparedness, and response policies (and budgets) in an increasingly energy-reliant world,” said first author Joan Casey, PhD, assistant professor of environmental health sciences at Columbia Mailman School.

Eskom in South Africa is already facing a shortfall due to users abandoning its services for solar power generation, forcing tariff changes and increases. An uptake of battery backups to complement the solar panels may greatly alleviate vulnerabilities of people dependent on medical equipment in an uncertain power supply environment, as well as improving resilience to natural disasters, without the health hazards of generators.

Source: News-Medical.Net

Journal information: Mango, M., et al. (2021) Resilient Power: Battery storage as a home-based solution to address climate-related power outages for medically vulnerable populations. Futures. doi.org/10.1016/j.futures.2021.102707.

Categories : Diseases, Syndromes and Conditions Medical Research & TechnologyTags :

Novel Magnetic Technique Detects Malaria in Blood

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A new magnetic method has been developed that can detect malaria, leading to faster, accurate and cheap diagnosis of the deadly disease.

An international study field-tested this new tool in Papua New-Guinea, in the hopes of helping the fight against this disease, which had 229 million reported cases in 2019, with 700 000 deaths a year.

“Malaria is easily treated but it is actually hard to diagnose, and because of that there can be over-treatment, which we have seen can lead to the spread of drug-resistant malaria,” said Dr Stephan Karl, a Senior Research Fellow in Malaria and Vector Biology at James Cook University’s Australian Institute of Tropical Health and Medicine.

“Improving malaria diagnosis, especially through the development of practical methods for resource-limited places, is important and timely,” he said.

An international team including the University of Augsburg’s Professor Istvan Kezsmarki, with the PNG Institute of Medical Research and the Burnet Institute, came up with the magnetic detection method, called rotating-crystal magneto-optical detection (RMOD).

When malaria parasites break down blood, the haeme molecules are aggregated by the parasites into biocrystals called haemezoin, which contain magnetic iron. This iron can is detectable by the RMOD method.

“I’ve studied the magnetic properties of malaria infected blood since 2006, and we engaged with Professor Kezsmarki’s team in 2013 to demonstrate the sensitivity of this test using human malaria parasites,” Dr Karl said.

A field study was successfully conducted, involving almost 1000 suspected malaria patients in a high-transmission area of Papua New-Guinea.

“After years of in-lab optimisation of the device, in collaboration with Dr. Karl we demonstrated the great potential of RMOD in fast and reliable malaria field tests performed in Papua New-Guinea,” Prof Kezsmarki said.

“We showed that RMOD performs well in comparison to the most reliable existing method..It’s very promising, as RMOD testing can be conducted after a short training session and provides test results within 10 minutes. From a funding perspective the cost is very low since no expensive reagents are used,” said Dr Karl.

Dr Karl said the aim was to refine the design until a test could be done by a simple button push.

Source: Medical Xpress

Journal information: L. Arndt et al, Magneto-optical diagnosis of symptomatic malaria in Papua New Guinea, Nature Communications (2021). DOI: 10.1038/s41467-021-21110-w

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Neural Network Matches Dermatologists’ Assessment of Skin Lesions

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Researchers have developed an AI-based tool that can use smartphone camera pictures to spot suspicious pigmented lesions (SPLs) with an accuracy close to that of professional dermatologists.

Such technology would hardly put dermatologists out of work; on the contrary, there is a great need for readily available skin cancer screening. In the US, there are only 12 000 practising dermatologists, who would need to see over 27 000 patients each per year in order to screen the entire population for SPLs which could lead to cancer. Computer-aided diagnosis (CAD) has thus been developed over previous years to help assist in diagnosis, but thus far had failed to spot melanomas in a meaningful way. Such CAD programs only analyse individual SPLs, while dermatologists compare other lesions on the same patient to reach a diagnosis, called ‘ugly duckling’ criteria.

This shortcoming has been addressed in a new CAD system that uses convolutional deep neural networks (CDNNs) developed by researchers at the Wyss Institute for Biologically Inspired Engineering at Harvard University and the Massachusetts Institute of Technology (MIT).

The new system was able to distinguish SPLs from non-suspicious lesions in photos of patients’ skin at ~90% accuracy, and established an ‘ugly duckling’ criteria which could match three dermatologists’ consensus 88% of the time.

“We essentially provide a well-defined mathematical proxy for the deep intuition a dermatologist relies on when determining whether a skin lesion is suspicious enough to warrant closer examination,” said first author Luis Soenksen, PhD, a Postdoctoral Fellow at the Wyss Institute who is also a Venture Builder at MIT. “This innovation allows photos of patients’ skin to be quickly analyzed to identify lesions that should be evaluated by a dermatologist, allowing effective screening for melanoma at the population level.”

The researchers used a database of 33 000 images to train the system, which also included background elements and non-skin elements. These extraneous elements were left in so that the CDNN would be able to use normal images taken by consumer-grade cameras. The images contained SPLs and non-suspicious skin lesions identified by three certified dermatologists.
The software then developed a ‘map’ of how far away a lesion was from the others in terms of similarity, giving an ‘ugly duckling’ criteria. To test the software, they used 135 photos from 68 patients, which assigned an ‘oddness’ score to each lesion. This was then compared to dermatologists’ assessments of those lesions, matching individual dermatologists 88% of the time and their consensus 86% of the time
“This high level of consensus between artificial intelligence and human clinicians is an important advance in this field, because dermatologists’ agreement with each other is typically very high, around 90%,” said co-author Jim Collins, PhD, of the Wyss Institute, who is also the Termeer Professor of Medical Engineering and Science at MIT. “Essentially, we’ve been able to achieve dermatologist-level accuracy in diagnosing potential skin cancer lesions from images that can be taken by anybody with a smartphone, which opens up huge potential for finding and treating melanoma earlier.”

Source: Medical Xpress

Journal information: “Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images” Science Translational Medicine, 2021.

Categories : Medical Research & Technology Neurodegenerative DiseasesTags :

Scientists Develop AI Tool to Detect Parkinson’s Disease

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Researchers have developed an AI program that can assist physicians in performing a quantitative analysis when diagnosing Parkinson’s disease. 

As human populations continue to age due to improved medical care, there is an impending ‘Parkinson’s disease pandemic’ where numbers of individuals suffering this age-related neurodegenerative disease threaten to overwhelm healthcare systems. There is a need to distinguish between Parkinson’s and other diseases which have similar motor symptoms.
Assistant Professor Andrey Somov at the Skolkovo Institute of Science and Technology and colleagues developed a machine learning algorithm to analyse video recordings of patients performing certain tasks.

“As part of the research process, we had the opportunity to closely interact with doctors and medical personnel, who shared their ideas and experience. It was fascinating observing how two seemingly different disciplines came together to help people. We also had the opportunity to monitor all parts of the research, from designing the methodology to data analysis and machine learning,” Kovalenko said.

The advantages of the video analysis approach is that it is simple, objective, noninvasive, quick, inexpensive and versatile.

To develop the machine learning algorithm, the researchers recorded 83 patients with and without Parkinson’s performing 15 tasks that they had designed, such as filling a glass with water. These tasks were developed in a prior feasibility study using wearable sensors. The machine learning technology allows for objective analysis which picks up certain features of the disease which may not be visible to the naked eye.

Coauthor of the study Sklotech Assistant Professor Dmitry Dylov, and “Machine learning and computer vision methods we used in this research are already well established in a number of medical applications; they can be trusted, and the diagnostic exercises for Parkinson’s disease have been in development by neurologists for some time. What is truly new about this study is our quantitative ranking of these exercises according to their contribution to a precise and specific final diagnosis. This could only be achieved in collaboration between doctors, mathematicians and engineers.”

“This collaboration between doctors and scientists in data analysis allows for many important clinical nuances and details that help achieve the best results. We as doctors see great potential in this; apart from differential diagnosis, we need objective tools to assess motor fluctuation in patients with PD. These tools can provide a more personalized approach to therapy and help make decisions on neurosurgical interventions as well as assess the outcomes of surgery later,” noted coauthor of the paper, neurologist Ekaterina Bril.

Source: News-Medical.Net

Journal information: Kovalenko, E., et al. (2021) Distinguishing Between Parkinson’s Disease and Essential Tremor Through Video Analytics Using Machine Learning: a Pilot Study. IEEE Sensors.doi.org/10.1109/JSEN.2020.3035240.

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New Biomaterials Could Boost Vaccines or Self-sterilise PPE

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Researchers from the Indian Institute of Science describe two technologies currently being researched that could be of great benefit in fighting viruses.

These technologies could enhance the effectiveness of vaccines, and also make surfaces destructive to viruses.

“It is important not just in terms of COVID,” explained author Kaushik Chatterjee. “We’ve seen SARS, and MERS, and Ebola, and a lot of other viral infections that have come and gone. COVID has, of course, taken a different turn altogether. Here, we wanted to see how biomaterials could be useful.”

The technologies combine the field of biomaterials, which are designed to interact with biological systems, along with nanotechnology, where structures are engineered on a tiny scale. Biomaterials have been used for dental implants and joint replacements, while nanotechnology has been harnessed for drug delivery systems.

One application the authors describe is the combination of nanotechnology and biomaterial could be used to prepare the immune system to recognise vaccine antigens.

“It is a means of stimulating the immune cells which produce antibodies during the vaccination,” explained author Sushma Kumari. “It is like a helper, like priming the cells. Now, the moment they see the protein, the cells are more responsive to it and would be secreting more antibodies.”

Another technology application is surfaces that disinfect themselves. By putting an electrical charge onto the surfaces, they could be made into a hostile coating that damages or destroys virus particles when they fall onto them. These surfaces could be used for PPEs and high-touch items such as doorknobs. This would save considerable time, effort and expense in regularly disinfecting surfaces with chemicals or UV irradiation. A similar existing technology is the use of silver nanoparticles as antibacterial medical device coatings.

This technology is very much in its early stages, the researchers stressed. Research needs to be done on which biomaterials are suitable for fighting viruses, and the solution for one disease may not be applicable to another.

Source: Medical Xpress

Journal information: “Biomaterials-based formulations and surfaces to combat viral infectious diseases” APL Bioengineering, DOI: 10.1063/5.0029486

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New Type of Sensor ‘Bandage’ Alerts Clinicians to Pressure Sores

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A new type of wearable sensor ‘bandage’ that can monitor blood oxygenation is being developed.

Driven partly by the growing interest in telemedicine as a result of COVID researchers at Missouri S&T are working on a printable, flexible, disposable sensor that can interact with a smartphone. This new kind of inexpensive sensor could alert health care workers early on to developing conditions such as pressure ulcers. Pressure ulcers normally develop from ischaemia caused by pressure and shear, and often occur in hospitalised patients or bedridden patients at home.

“Our current work focuses on designing and optimising a tissue oxygen sensor by using inexpensive inkjet printing techniques,” said Dr Chang-Soo Kim, professor of electrical and computer engineering at Missouri S&T. “Concurrently, we are developing a smartphone app that can interpret sensor images. This prototype will be evaluated using phantom tissue that mimics a pressure ulcer site.”

Dr Kim is working with other researchers to create a cheap, easy-to-use sensor to help prevent pressure sores which are on the rise due to obesity and diabetes. This might speed recovery, reducing the length of hospital stays and saving millions of dollars. 

Current pressure ulcer monitoring involves manual examination, but with this wearable sensor, drops in oxygen levels are sensed at the at-risk site before they have a chance to turn into a sore. The change could even be detected at home, in say a foot ulcer, alerting a clinician via smartphone who could then provide a diagnosis. 

“Our optical sensor bandage functions by detecting a low skin oxygen level caused by compromised circulation,” said Kim. “This low oxygen produces a color change called luminescence intensity. The smartphone can then take a photograph of the dressing and transmit it to enable remote monitoring or encourage timely intervention before major skin decomposition occurs.”

Source: Medical Xpress