SARS-CoV-2 Lurking in the Middle Ear

From the common rhinovirus to infamous coronavirus, respiratory viruses can trigger a cascade of ear complications, including acute otitis media (AOM). This roster includes syncytial virus, rhinovirus, adenovirus, coronavirus, bocavirus, influenza virus, parainfluenza virus, enterovirus, human metapneumovirus and SARS-Cov2. Moreover, Otitis media can often manifest as the initial sign of COVID-19 and be associated with hearing loss. Otitis media secretory is one of the most common ear complications after infection with the Omicron strain of SARS-CoV-2 virus, and the significantly higher incidence is associated with middle ear viral infection. Middle ear effusion SARS-CoV-2 virus antigen test detected the virus, which survived longer in the middle ear effusion than in the nasal cavity. The middle ear effusion test can detect SARS-CoV-2 virus antigen and determine whether the organism contains virus residue. 

Recent findings have unveiled a potentially alarming revelation - individuals diagnosed with otitis media with effusion (OME) post-COVID-19 may harbor traces of the virus within their middle ear. In this study, a striking 12.0% of middle ear effusion samples tested positive for SARS-CoV-2, hinting at the possibility of viral persistence and recurrence.

The study examined 23 patients, ranging from 32 to 84 years of age, who presented with OME following Omicron infection. 91.3% of these patients showcased unilateral symptoms, with fluid accumulation observed in 88.0% of ears. The median duration from infection to middle ear effusion sampling was 21 days, showcasing the potential for prolonged viral presence in this concealed reservoir.

Adding to the intrigue is the elusive nature of OME itself. Characterized by fluid accumulation in the middle ear sans acute infection, OME has long puzzled experts in otolaryngology and audiology. While bacterial infections and immunological responses have been implicated, the precise mechanisms remain veiled in mystery.

REFERENCES

Chengzhou Han, Huifang Wang, Ying Wang, Chao Hang, Yangyang Wang, Xiangming Meng, The silent reservoir? SARS-CoV-2 detection in the middle ear effusion of patients with Otitis media with effusion after omicron infection, American Journal of Otolaryngology, 2024, 104229, ISSN 0196-0709, https://doi.org/10.1016/j.amjoto.2024.104229. 

Zhang Y, Liu J, Yang F, He Y, Yan S, Bai Y, Zhang Z, Luan F. COVID-19-related secretory otitis media in the omicron era: a case series. Eur Arch Otorhinolaryngol. 2023 Oct;280(10):4697-4700. doi: 10.1007/s00405-023-08075-w. Epub 2023 Jun 21. PMID: 37341758.

Fan Y, Gao R, Shang Y, Tian X, Zhao Y, Chen X. Presence of SARS-CoV-2 in middle ear fluid and characterization of otitis media with effusion in patients with COVID-19. International Journal of Infectious Diseases. 2023 Nov 1;136:44-8.

Karimi-Galougahi M, Raad N, Ghorbani J, Mikaniki N, Haseli S. Otitis Media in COVID-19: A Case Series. Authorea Preprints. 2020 Jul 7.

The audio CAPTCHA

Audio CAPTCHAs are a type of CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) used to determine if a user is a human or a bot. Audio CAPTCHAs are designed to be accessible to users with visual impairments, who may have difficulty reading visual CAPTCHAs. Hearing-based "I'm not a robot" quizzes play audio clips that read out the text or letters presented in the CAPTCHA. These recordings usually feature some form of background noise, which is intended to fool bots that try to interpret the audio. They used to be fairly effective since first generation bots struggled to properly interpret audio.  They even were used for shadow crowdsourcing, making people work for others without realizing it - eg, translate old newspapers and characters from street images for Google Maps. 

However, the effectiveness of audio CAPTCHAs has been challenged by the improving accuracy of automated speech recognition (ASR) systems, which are able to solve audio CAPTCHAs even in the presence of background noise. As a result, researchers have focused on developing new audio CAPTCHA designs that are more resistant to ASR attacks, as well as evaluating the performance of different audio CAPTCHA designs under various conditions.

Some of the audio CAPTCHA papers have explored the use of different types of audio signals, such as noise and music, to create audio CAPTCHAs that are more difficult for ASR systems to solve. Other papers have examined the use of multiple audio CAPTCHAs in sequence, or the use of visual and audio CAPTCHAs in combination, in an effort to increase the overall security of the CAPTCHA system.

Both text and image-based CAPTCHAs are becoming difficult for humans to resolve. Bruce Schneier, an internationally renowned security technologist, offered this humorous example on his blog: "select all images where if you were to add a decrescendo it would add to the musicality of the piece without being interpreted as an overly heavy-handed metaphor within the context of the thematic material "

ChatGPT answered to this challenge by writing lyrics to short musical pieces incorporating a decrescendo: 

 Verse 1: (Moderately fast tempo, 8th note = 120 bpm) 

The sun is shining bright, 

The birds are singing sweet, 

My heart is filled with joy, 

As I dance down the street. 

Chorus: (8th note = 120 bpm) 

Life is good, life is grand, 

I am free to roam this land. 

Verse 2: (Moderately fast tempo, 8th note = 120 bpm) 

But as the day wears on, The clouds start to roll in. My steps slow down, As the rain begins. 

Chorus: (8th note = 120 bpm) Life is good, life is grand, But sometimes it's hard to understand. 

Bridge:(Moderately slow tempo, 8th note = 60 bpm) The rain falls heavy now, My mood starts to change. I feel a sense of sadness, As I contemplate the pain. 

Outro: (Moderately slow tempo, 8th note = 60 bpm) But even in the darkest times, There is always a way. The rain will eventually stop, And a brighter day will come my way. (Decrescendo from 8th note = 60 bpm to pianissimo) 

In this musical piece, the decrescendo at the end helps to convey a sense of resolution and hopefulness, as the music gradually fades out to a pianissimo dynamic. The use of a decrescendo in this context adds to the musicality of the piece without being overly heavy-handed or interpreting the thematic material in a specific way.

It's a challenge to develop effective CAPTCHAs that are able to differentiate between humans and bots, while also being accessible to all users.

REFERENCES

Alqarni M, Yu F, Raavi R, Sukhai M. An Accessible Web CAPTCHA Design for Visually Impaired Users.

Solanki S, Krishnan G, Sampath V, Polakis J. In (cyber) space bots can hear you speak: Breaking audio captchas using bots speech recognition. InProceedings of the 10th ACM Workshop on Artificial Intelligence and Security 2017 Nov 3 (pp. 69-80).

Reinheimer BM, Islam F, Shumailov I. Audio CAPTCHA with a Few Cocktails: It’s so Noisy I Can’t Hear You. InCambridge International Workshop on Security Protocols 2019 Apr 10 (pp. 20-40). Springer, Cham.

Shirali-Shahreza S, Penn G, Balakrishnan R, Ganjali Y. Seesay and hearsay captcha for mobile interaction. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems 2013 Apr 27 (pp. 2147-2156).

Huang CH, Wu PH, Liu YW, Wu SH. Attacking and Defending Behind A Psychoacoustics-Based Captcha. InICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021 Jun 6 (pp. 895-899). IEEE.

IG: Special thanks to OpenAI's Assistant for their help with writing this article.

The Brain Filters

Our brains have a built-in "noise cancelling" circuit known as a cortical filter that helps us ignore the sounds of our own movements, such as footsteps. This filter is essential for our daily lives, as it allows us to focus on important sounds and conversations without being distracted by the noise of our own actions (or even voice of people we got used to filter out, like mothers or wives). However, in some cases, this filter may not work properly, leading to conditions such as tinnitus, where the brain struggles to filter out certain sounds. For example, a person with tinnitus may hear a constant ringing or buzzing noise, even in a quiet room. 

Cochlear implant recipients may also struggle to adjust to the new sounds they are able to hear after receiving the implant, as their brains may have difficulty filtering out their own movement sounds at first. However, with time and practice, the brain can learn to use the cortical filter more effectively, allowing people to focus on the sounds that matter most to them.

Sounds that arise from our own movements, such as vocalizing or walking, are known as reafferent sounds. These sounds are essential for normal hearing, as they help us to anticipate and distinguish them from sounds that come from the environment. However, the neural circuits that allow us to learn to anticipate and distinguish these sounds are not well understood. 

In order to study these neural circuits, researchers developed a system called acoustic virtual reality (aVR), in which mice were trained to associate a novel sound with their own movements. By using this system, the researchers were able to identify the neural mechanisms that learn to suppress reafferent sounds and study the behavioral consequences of this predictable sensorimotor experience. 

The researchers found that aVR experience gradually and selectively suppressed auditory cortical responses to the reafferent frequency, in part by strengthening motor cortical activation of auditory cortical inhibitory neurons that respond to the reafferent tone. This plasticity, or ability to change in response to experience, was behaviorally adaptive, as mice that had experienced aVR showed an enhanced ability to detect non-reafferent tones during movement. 

Overall, these findings suggest that there is a dynamic sensory filter in the brain that involves motor cortical inputs to the auditory cortex, and that this filter can be shaped by experience to selectively suppress the predictable acoustic consequences of movement.

REFERENCES

Schneider DM, Sundararajan J, Mooney R. A cortical filter that learns to suppress the acoustic consequences of movement. Nature. 2018 Sep;561(7723):391-5.

Big Data of Sounds

Hearing begins with the ears, but it's more than the sum of sounds. We are able to recognize piano notes and experience music, understand speech in noisy surroundings and localize voice in 3D.  Is it because the sound transmitted to the inner ear is broken down into frequencies and mapped onto the brain like musical notes are mapped on a piano keyboard? But are not we able to hear different things at once in three dimensions? Are not we translating frequencies into meanings on the fly, processing Big Data better than any famous statistician? As Jacob Oppenheim and Marcelo Magnasco showed that simple decomposition of sounds into its components by Fourier transform loses important information about the sound's duration, something that our brain is actually able to overcome. Humans can beat the limits of Fourier analysis, and the Brain processes the big data of sounds better than existing algorithms do. As a matter of fact, training our brain on music makes us better in math and problem solving skills. While inability to process signals in the brain leads to developmental disorders. More to discover, more to learn.

REFERENCES

Oppenheim, Jacob N., and Marcelo O. Magnasco. "Human Time-Frequency Acuity Beats the Fourier Uncertainty Principle." arXiv preprint arXiv:1208.4611(2012).

Díaz, Begoña, et al. "Dysfunction of the auditory thalamus in developmental dyslexia." Proceedings of the National Academy of Sciences 109.34 (2012): 13841-13846.

Temperature-induced hearing loss

There are many reasons why people loose hearing. Environmental factors  - especially prolonged loud noise and infection or injury - are among the leading causes in the US (figure on the right). Drugs, and chemical toxins could also play a role. Genes accounts for less than half of causes. Gene-environment interactions are contributing too. 

• Drug induced - some medications can result in damage to the auditory system with prolonged use. They are called ototoxic. Here are a few drugs that are known to cause hearing loss: aminoglycoside antibiotics (such as streptomycin, neomycin, kanamycin); salicylates in large quantities (aspirin), loop diuretics (Lasix, ethacrynic acid); and drugs used in chemotherapy regimens (cisplatin, carboplatin, nitrogen mustard). Genetics may predispose to vulnerability to drugs.
• Noise-induced hearing loss (NIHL) - this is hearing loss due to exposure to either a sudden, loud noise or exposure to loud noises for a period of time. A dangerous sound is anything that is 85 dB (sound pressure level - SPL) or higher. Genetics may determine vulnerability thresholds to noise.
• Temperature-induced hearing loss.  Genetics could cause temporary hearing loss caused by a high body temperature. They recover some time after their body temperature has returned to normal. Cold weather could also affect hearing (eg, by hardening earwax blocking the ear canal) leading to conditions such as tinnitus. 

It is well known that high fevers cause hearing loss. High fevers account for about 1,200 to 1,800 cases of hearing loss in the US each year. Artificially induced high body temperature - for example by a strenuous workout in a 105-degree room - may be the culprit too.

Mutations in the otoferlin (OTOF) gene - known to cause neurosensory nonsyndromic recessive deafness - have been recently linked to rare temporary hearing loss caused by a high body temperature.

In one of the cases examined, hearing of a young boy in the morning was better than in the afternoon, and temperature measurements showed that his body temperature in the afternoon was generally higher than that in the morning. Hospital examination showed that when his body temperature rose above 36.5°C, the hearing loss was severe (70-80dB HL) and this symptom could last for a whole day. The boy with the temperature-dependent hearing loss had two variant OTOF genes, each of which is not usually seen in normal-hearing people.

Another study of a family with three children whose hearing was sensitive to temperature also linked their ailments to OTOF gene.

References

Fukushima K, Ramesh A, Srisailapathy CR, et al. (1996). An autosomal recessive nonsyndromic form of sensorineural hearing loss maps to 3p-DFNB6. Genome Res. 5 (3): 305–8. PMID 8593615

Varga, R. (2005). OTOF mutations revealed by genetic analysis of hearing loss families including a potential temperature sensitive auditory neuropathy allele Journal of Medical Genetics, 43 (7), 576-581 DOI: 10.1136/jmg.2005.03861

Wang, D., Wang, Y., Weil, D., Zhao, Y., Rao, S., Zong, L., Ji, Y., Liu, Q., Li, J., Yang, H., Shen, Y., Benedict-Alderfer, C., Zheng, Q., Petit, C., & Wang, Q. (2010). Screening mutations of OTOF gene in Chinese patients with auditory neuropathy, including a familial case of temperature-sensitive auditory neuropathy BMC Medical Genetics, 11 (1) DOI: 10.1186/1471-2350-11-79

Marlin, S., Feldmann, D., Nguyen, Y., Rouillon, I., Loundon, N., Jonard, L., Bonnet, C., Couderc, R., Garabedian, E., & Petit, C. (2010). Temperature-sensitive auditory neuropathy associated with an otoferlin mutation: Deafening fever! Biochemical and Biophysical Research Communications, 394 (3), 737-742 DOI: 10.1016/j.bbrc.2010.03.06

The Ear Blog

Welcome to the Ear Blog!

Hearing has always been the Cinderella of the senses, but we can't undermine its importance. Among all the senses, this is the one we are most likely to lose.
The fascinating world of the inner ear consists of the smallest bones, spirals and fluid-field channels, along with tiny sensory units called hair cells. We are born with about 15,000 of them in each ear, and are subjecting these remarkable structures to constant damage from drugs, iPods, many other silence-disrupting technologies, even diets and aging. We'll talk more about it in other bloglications, meanwhile see these animations by TheatricalDesign or play with this one by adjusting the frequency of the sound entering the ear and watch youtube videos.