That egg can then be fertilized by a sperm to create a viable embryo that contains the combined genetic data of the skin donor and sperm donor.

The innovative technology will not only help same-sex couples have a child of their own, but also women who are unable to create viable eggs due to advanced age, ill health or other reasons.

“The goal is to produce eggs for patients who don’t have their own eggs,” said senior author Shoukhrat Mitalipov, director of the Oregon Health & Science University Center for Embryonic Cell and Gene Therapy.

The scientists add that this is the same technique that researchers in Scotland used to clone a sheep named Dolly in 1996.

In that case, researchers created a clone of one parent, while the OHSU researchers focused on creating embryos with genetics drawn from both parents.

The OHSU team followed a three-step process to do this in mouse experiments.

They first stripped a mouse egg of its nucleus, then transplanted the nucleus of a mouse skin cell into the mouse egg.

Next, they prompted the implanted skin cell nucleus to discard half its chromosomes, in a process similar to that which occurs in cells dividing to produce mature sperm or egg cells.

Finally, the researchers fertilize the new egg with sperm using in vitro fertilization, resulting in a healthy embryo with two sets of chromosomes equally donated by two parents.

This process could prove a simpler option to a competing technique that other labs around the world are testing, in which skin cells are fully reprogrammed to become either egg or sperm cells.

“We’re skipping that whole step of cell reprogramming. The advantage of our technique is that it avoids the long culture time it takes to reprogram the cell. Over several months, a lot of deleterious genetic and epigenetic changes can happen. This gives us a lot of insight. But there is still a lot of work that needs to be done to understand how these chromosomes pair and how they faithfully divide to actually reproduce what happens in nature”, researcher Dr. Paula Amato, a professor of obstetrics and gynecology in the OHSU School of Medicine, said in a school news release.

However, researchers warn that it will be years before this technique could be available for humans.

While MRI is the imaging technique of choice for assessing a range of cancers, including prostate cancer, in the UK alone, the number of radiologists is predicted to reach 40% by 2027, indicating the need for a streamlined, simplified and accurate means of cancer diagnosis, Med Tech reports.

A clinical study shows that radiologists can miss 12% of significant prostate cancer cases using MRI. The data, presented at the European Society of Urogenital Radiology (ESUR) in September 2023, shows that Pi could help reduce undetected cancers by up to 6% while reducing avoidable biopsies by up to 43%.

According to Med Tech, with the help of artificial intelligence, Pi analyzes MRIs and is fully integrated into the radiologist’s workflow, targeting key issues related to variability, radiologist timing and diagnostic accuracy in prostate cancer. Specifically, Pi is designed to be used by radiologists to evaluate and report prostate MRI studies by automatically creating 3D segmentations, volumes and risk scores. Its results can be used to save radiologists time and to support biopsy and treatment decisions.

“We desperately need to cut waiting times, detect cancer early, and provide patients and clinicians with all the information needed to for optimum treatment. With this CE mark, the results of our investment in AI and clinical research over the last four years can now be used by doctors to provide the best possible diagnosis for men with suspected prostate cancer”, explained co-founder and chief medical officer Professor Evis Sala, chair of radiology at the Università Cattolica del Sacro Cuore and director of the Advanced Radiology Centre at the Policlinico Universitario A. Gemelli, IRCCS.

Lucida Medical will demonstrate Pi at the Radiological Society of North America (RSNA) 2023 Annual Meeting.

What is Pi?
Prostate Intelligence (Pi) is an AI and machine learning based software system designed to help radiologists detect and report the presence of prostate cancer lesions from MR scans (MRI).

How does the technique work?

It spots hidden patterns in the data and learns who is most at risk. The algorithm is suggested to have the power of helping reduce the number of people who may have been falsely diagnosed with dementia.

Data from people who have attended a network of 30 National Alzheimer’s Coordinating Centre memory clinics in the US, was analyzed by the study’s researchers. At the beginning of the study, the attendees didn’t have dementia even though they have had problems with their memory or some other brain functions.

The study started in 2005 and finished in 2015. For that period of time one in ten attendees was diagnosed with dementia within two years after they visited the memory clinic.

So, what did the research find?

According to the study, the machine learning model is able to predict these new dementia cases with up to 92 per cent accuracy. Also, it is even more accurate than two existing alternative research methods.

According to Professor David Llewellyn, who is  from the University of Exeter, they were now able to teach computers to accurately predict who will go on to develop dementia within two years.

Also, he added:

“We’re also excited to learn that our machine learning approach was able to identify patients who may have been misdiagnosed. This has the potential to reduce the guesswork in clinical practice and significantly improve the diagnostic pathway, helping families access the support they need as swiftly and as accurately as possible.”

Dr Janice Ranson, who also worked on the project, commented:

“We know that dementia is a highly feared condition. Embedding machine learning in memory clinics could help ensure diagnosis is far more accurate, reducing the unnecessary distress that a wrong diagnosis could cause.”

Machine learning was found to work effectively, using patient information which is routinely available in clinics such as memory and brain function, performance on cognitive tests and specific lifestyle factors.

Now the team has a new plan which includes conducting follow-up studies in order to evaluate the practical use of the method in clinics, as well as to assess whether it can be rolled out to improve dementia diagnosis, treatment and care.

The head of research at Alzheimer’s Research UK, Dr Rosa Sancho shared:

“Artificial intelligence has huge potential for improving early detection of the diseases that cause dementia and could revolutionise the diagnosis process for people concerned about themselves or a loved one showing symptoms. This technique is a significant improvement over existing alternative approaches and could give doctors a basis for recommending lifestyle changes and identifying people who might benefit from support or in-depth assessments.”

Besides, two years ago, VR was found to help people who are suffering from dementia recall past memories and tackle behavioral issues in 2019.

The structure of the human eye is really complex and it contains more than two million interacting parts. It’s a serious challenge restoring someone’s sight, but now, thanks to all tech advances and many scientists’ hard work, this task is not an impossible one anymore. The bionic eye probably sounds familiar to you because of all the sci-fi movies and TV shows out there which you know very well. Well, it is now a reality – human sight may be restored.

Serge Picaud, who is a director at Institut de la Vision, a leading research center on eye diseases in Paris, France, said:

‘Enabling a patient to see again is our dream. A dream that we believe can come true,’

At this point, Picaud is coordinating entrain vision, a network of experts from all key sciences which are related to visual restoration. Together with 15 early-stage researchers, they are working and giving their best for restoring patients’ vision.

Firstly, the idea of electrically stimulating the human visual system was described more than 200 years ago. However, the advances in neural engineering and micro-electronics have paved the way for more advanced cortically-based visual prosthetic devices. Picaud explained:

‘The idea is to use a type of electronic device to electrically stimulate the remaining nerve cells. So, after having lost part of the “circuit”, you replace it with an electronic device,’

Recently, one of the partners succeeded in implementing a microelectrode array, which was composed of 100 microneedles, into the visual cortex of a blind woman. Thanks to that, she was able to recognize some lines, shapes, and simple letters.  Picaud said:

‘These results are very exciting because they demonstrate both the safety and efficacy of this technology and can help to achieve a long-held dream of many scientists: to transfer information from the outside world directly to the visual cortex of blind individuals, restoring a rudimentary form of sight. This work is likely to become a milestone for the development of new technologies that could help to transform the treatment of blindness. However, more studies are still needed.’

What actually is optogenetics? 

It is a biological technique that uses light to control nerve cells or other cell types. This technique was developed about 21 years ago. Picaus shared a story from his professional experience, explaining that there is already one patient in France who can see using this. This patient was diagnosed with the neurodegenerative eye disease retinitis pigmentosa, which affects more than two million people worldwide, and completely destroys their retinal photoreceptors. However, because of the research with Gensight Biologics, the patient’s sight has been partially restored.

There is one more technology that has been set by the researchers. It is based on virtual reality. Picaud commented:

‘In Paris, we have a setting like a movie theatre (Street lab) where we can test a patient’s vision. It could be, for example, a room full of obstacles. So, once the patient has a device implanted, we can test it using this platform. However, it’s not easy to validate a device in other centers outside of Paris, because the platform cannot be easily recreated elsewhere due to its size. This is where virtual reality steps in.’

Users can be allowed to experience the same conditions as those in the Paris theatre anywhere in the world by the virtual headset. Picaud added:

‘It can also help us understand what the most important parts of an image are for a patient so that they can recognise their friends or ways to move about a room.’

However, have we ever thought about what happens when a human being loses not only their sight but also their hearing?

For many people with different kinds of disabilities, the sense of touch is really important and it is the only way to interact with the world. Nasrine Olson, who is a senior lecturer at the University of Borås and also a coordinator of the SUITCEYES project noted:

‘Being informed and able to communicate is central to everything we do, but you cannot interact with your environment if you are unable to gain information about it or communicate with people and your surroundings. So, we focused on improving communication for people with deafblindness.’

A smart, tactile interface that extends the perception and spatial orientation turned out to be a result. It makes it possible for them. When it comes to technology, it was nominated for an Innovation Radar Prize. Olson also added:

“Being informed and able to communicate is central to everything we do, but you cannot interact with your environment if you are unable to gain information about it or communicate with people and your surroundings. So, we focused on improving communication for people with deafblindness. “

How does computer vision help capture the environment? 

Olson explained:

‘First, our “haptic intelligent personalized interface” also known as HIPI captures the environment using computer vision and sensor technologies. The camera, sensors, and computer vision algorithms collectively detect and recognize objects, scenes, and faces. An object can be “a chair” or “a cup”, a scene can be “a corridor” or “an office” or “a bathroom”. The system also detects faces and whether they are known to the user or not. The sensor technologies also observe the distance between things.”

In other words, if the user is looking for their cup of coffee, for example, the HIPI will observe that it is on a table three meters away, to the left of the user.

Also, in Olson’s words, the haptograms they created were actually a haptic pattern that carries a meaning, for example, “happy” to the user. It does this by using vibrotactile actuators, which are small electronic devices that vibrate. They can be placed on different parts of the body. Then, various prototypes have been developed with the aim of integrating technology into clothing. Olson said that this included a range of vests, as well as a dress to show how the technology can be worn while looking fashionable.

Technologies have their advantages and disadvantages and there is no doubt on that question. Do they actually have the power to change the future? Of course. But the most important is that technologies make the impossible possible. And when it comes to healthcare it makes it more powerful than ever.

The research in this article was funded by the EU.

These days, many state-of-the-art cameras for demanding applications rely on mechanisms that are considerably different from those in consumer-oriented devices. One of these cameras employs what is known as “single-photon imaging,” which can produce vastly superior results in dark conditions and fast dynamic scenes.

This type of imaging has few ways to deal with moving objects; the movement of the object has to be much slower than the exposure time to avoid blurring, which occurs when taking pictures with regular CMOS cameras, like the ones on smartphones. Single-photon cameras capture a rapid burst of consecutive frames with very short individual exposure times. These frames are binary―a grid of 1s and 0s that respectively indicate whether one photon arrived at each pixel or not during exposure. To reconstruct an actual picture from these binary frames (or bit planes), many of them have to be processed into a single non-binary image. This can be achieved by assigning different levels of brightness to all the pixels in the grid, depending on how many of the bit planes had a “1” for each pixel.

The completely digital nature of single-photon imaging allows for designing clever image reconstruction algorithms that can make up for technical limitations or difficult scenarios. At Tokyo University of Science, Japan, Professor Takayuki Hamamoto has been leading a research team focused on taking the capabilities of single-photon imaging further. In the latest study by Prof. Hamamoto and his team, which was published in IEEE Access, they developed a highly effective algorithm to fix the blurring caused by motion in the imaged objects, as well as common blurring of the entire image such as that caused by the shaking of the camera.

A motion estimation algorithm tracks the movement of individual pixels through statistical evaluations on how bit values change over time (over different bit planes). In this way, as demonstrated experimentally by the researchers, the motion of individual objects can be accurately estimated. Prof. Hamamoto remarks:

Our tests show that the proposed motion estimation technique produced results with errors of less than one pixel, even in dark conditions with few incident photons

The team developed a second algorithm that pixels with a similar motion, thereby identifying in each bit plane separate objects moving at different speeds, which allows for deblurring each region of the image independently according to the motions of objects that pass through it. Prof. Hamamoto adds:

Methods for obtaining crisp images in photon-limited situations would be useful in several fields, including medicine, security, and science. Our approach will hopefully lead to new technology for high-quality imaging in dark environments, like outer space, and super-slow recording that will far exceed the capabilities of today’s fastest cameras

He also states that even consumer-level cameras might timely benefit from progress in single-photon imaging.