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Ear wax removal Radstock

Ear wax removal Radstock

Ear wax removal for Radstock is available at the Keynsham hearing centre between Bath and Bristol. Run by Stephen Neal the Keynsham centre covers the whole of Somerset and Wiltshire.  If you are suffering from ear wax issues or in need of a hearing test please book your appointment with Anita at reception.

Out of hours appointments are available at a premium price, there are very limited spaces, pleas call Anita on reception to organise an out of hours ear wax appointment.

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Stephen Neal ear wax removal news:

Researchers Restore Hearing via Gene Therapy in Deaf Mouse Model

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In collaboration with the universities of MiamiColumbia, and San Francisco, scientists from the Institut Pasteur, InsermCNRSCollège de FranceSorbonne University, and the University of Clermont Auvergne have managed to restore hearing in an adult mouse model of DFNB9 deafness, a hearing disorder that represents one of the most frequent cases of congenital genetic deafness, Institut Pasteur announced on its website. Individuals with DFNB9 deafness are profoundly deaf as they are deficient in the gene coding for otoferlin, a protein which is essential for transmitting sound information at the auditory sensory cell synapses. By carrying out an intracochlear injection of this gene in an adult DFNB9 mouse model, the scientists successfully restored auditory synapse function and hearing thresholds to a near-normal level. These findings, published in the journal PNAS, open up new avenues for future gene therapy trials in patients with DFNB9.

The left panel is a schematic representation of the human ear. Sound waves are collected by the outer ear made up of the pinna and ear canal. The middle ear, composed of the eardrum and ossicles, transmits sound waves to the inner ear, which features the cochlea – the hearing organ responsible for transmitting auditory messages to the central nervous system. The right panel shows an immunofluorescence image of the auditory sensory epithelium within an injected cochlea. The inner hair cells have been stained for otoferlin in green. Otoferlin is detected in almost all of these cells. The inset is a high magnification area showing an inner hair cell that has not been transduced. © Institut Pasteur

The left panel is a schematic representation of the human ear. Sound waves are collected by the outer ear made up of the pinna and ear canal. The middle ear, composed of the eardrum and ossicles, transmits sound waves to the inner ear, which features the cochlea – the hearing organ responsible for transmitting auditory messages to the central nervous system. The right panel shows an immunofluorescence image of the auditory sensory epithelium within an injected cochlea. The inner hair cells have been stained for otoferlin in green. Otoferlin is detected in almost all of these cells. The inset is a high magnification area showing an inner hair cell that has not been transduced. © Institut Pasteur

Over half of nonsyndromic profound congenital deafness cases have a genetic cause, and most (~80%) of these cases are due to autosomal recessive forms of deafness (DFNB). Cochlear implants are currently the only option for recovering hearing in these patients.

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Adeno-associated viruses (AAVs) are among the most promising vectors for therapeutic gene transfer to treat human diseases. AAV-based gene therapy is a promising therapeutic option for treating deafness but its application is limited by a potentially narrow therapeutic window. In humans, inner ear development is completed in utero and hearing becomes possible at approximately 20 weeks of gestation. In addition, genetic forms of congenital deafness are generally diagnosed during the neonatal period. Gene therapy approaches in animal models must therefore take this into account, and gene therapy efficacy must be demonstrated following a gene injection when the auditory system is already in place. In other words, therapy must reverse existing deafness. The team led by Saaïd Safieddine, a CNRS researcher in the Genetics and Physiology of Hearing Unit (Institut Pasteur/ Inserm) and coordinator of the project, used a mouse model of DFNB9, a form of human deafness that represents 2-8% of all cases of congenital genetic deafness.

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DFNB9 deafness is caused by mutations in the gene coding for otoferlin, a protein that plays a key role in transmitting sound information at the inner hair cell synapses. Mutant mice deficient in otoferlin are profoundly deaf as these synapses fail to release neurotransmitters in response to sound stimulation, despite the absence of detectable sensory epithelial defects. DFNB9 mice therefore constitute an appropriate model for testing the efficacy of viral gene therapy when it is administered at a late stage. However, as AAVs have limited DNA packaging capacity (approximately 4.7 kilobase (kb)), it is difficult to use this technique for genes whose coding region (cDNA) exceeds 5 kb, such as the gene coding for otoferlin, which has a 6 kb coding region. The scientists have overcome this limitation by adapting an AAV approach known as dual AAV strategy because it uses two different recombinant vectors, one containing the 5’-end and the other the 3’-end of the otoferlin cDNA.

A single intracochlear injection of the vector pair in adult mutant mice was used to reconstruct the otoferlin coding region by recombining 5′ and 3′-end DNA segments, leading to long-term restoration of otoferlin expression in the inner hair cells, and then restored hearing.

The scientists have therefore obtained initial proof of the concept of viral transfer of fragmented cDNA in the cochlea using two vectors, showing that this approach can be used to produce otoferlin and durably correct the profound deafness phenotype in mice.

The outcomes achieved by the scientists suggest that the therapeutic window for local gene transfer in patients with DFNB9 congenital deafness could be wider than thought, and offers hope of extending these findings to other forms of deafness. These results are the subject of a patent application filed.

In addition to the institutions mentioned in the first paragraph, this research was funded by the French Foundation for Medical Research, the European Union (TREAT RUSH), and the French National Research Agency (EargenCure and Lifesenses LabEx).

Original Paper: Akil O, Dyka F, Calvet C, et al. Dual AAV-mediated gene therapy restores hearing in a DFNB9 mouse model. PNAS. 2019. DOI: https://doi.org/10.1073/pnas.1817537116

Source: Institut Pasteur, PNAS

Image: Institute Pasteur

Ear wax removal Radstock

Wells Somerset, ear wax removal

Wells Somerset, ear wax removal

Stephen Neal is the Wells in Somerset premier ear wax removal specialist.  Covering Wells in Somerset, as well as Cheddar, Wookey Hole, Glastonbury, Shepton Mallet, Westbury-sub-Mendip and Street.

Stephen makes a visit to the audiologist a breeze. He is very easy going chap as you can see here on the Microsuction ear wax removal video. 

Stephen Neal is based at the Keynsham Hearing centre, here he can conduct hearing tests, dispense hearing aids and give advice on all aspects of hearing issues.

 

Stephen Neal News:

Widex Announces New Insights into EVOKE Hearing Aid’s AI Function

 

Wells Somerset, hearing tests Wells, Ear wax removal Wells,

Wells hearing centre, Wells ear wax centre, Wells hearing test

Widex announced the first data gathered from the WIDEX EVOKE™ hearing aid, which is said to achieve “a new level of Artificial Intelligence (AI)” through machine learning, and is helping to bring new insights into how users are taking control of their sound environment to improve their hearing experience, according to the company.

Denmark-based Widex launched the WIDEX EVOKE hearing aid in April. The hearing aid is reportedly the first to give users the ability to employ real-time machine learning that can solve the tricky hearing problems that users face in their daily lives.

“We launched WIDEX EVOKE with SoundSense technology to put users back in control of the most difficult hearing situations,” said Jens Brehm Nielsen, data science & machine learning architect at Widex. “And we can see that EVOKE users have taken the opportunity to do that and, in the process, are helping us understand more about them. That information will help us to make the EVOKE and future hearing aids even better.”

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SoundSense Learn is an AI system, because AI is said to refer to systems that solve tasks humans are inherently good at—such as driving a car, doing the dishes, etc. SoundSense Learn expands into entirely new applications by helping end users adjust their hearing aids in the moment, reportedly something that no humans can replicate to the same degree of accuracy, according to Widex.

The SoundSense Learn smartphone app is connected to the EVOKE hearing aids and uses machine learning to guide users in optimizing the settings to their exact needs. The app gathers a variety of anonymous data such as how often they turn the volume up or down, which sound presets they use, and how many custom settings they create—including those made with SoundSense Learn.

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Tagging of custom settings has proved to be one of the interesting pieces of data generated by EVOKE.

“We found that many people have created a setting and tagged it with, for instance, ‘work’ which suggests that it is something that our end users need and want,” said Nielsen. “And from SoundSense Learn we already have an idea of how they like the settings.”

Some hearing aids give users the ability to customize their sound experience by adjusting frequency bands to boost or cut bass, middle or high tones. Adjusting frequencies works well in many situations once the initial settings have been set by a skilled audiologist. However, some situations are so complex that hitting the right combination of adjustments can be difficult.

“Widex hearing aids are well known for the quality of their sound,” said Nielsen. “But SoundSense Learn has added an extra layer of quality sound on top of that by using a machine learning algorithm together with reinforcement learning—the two key ingredients in state-of-the art AI algorithm, that enables the algorithm to learn in the moment.

“The algorithm learns an optimal setting every time a user finds the sound to be a little below expectations in a given sound environment. It learns these settings by simply asking the user to compare two settings that are carefully picked by the algorithm. This allows it to learn an optimal setting in a new environment very fast.”

By collating and analyzing the anonymous data WIDEX EVOKE will continue to become even smarter as time passes.

Source: Widex

Image: Widex