The association between hearing impairment and dementia has emerged as a major public health challenge, with significant opportunities for earlier diagnosis, treatment and prevention. However, the nature of this association has not been defined. We hear with our brains, particularly within the complex soundscapes of everyday life: neurodegenerative pathologies target the auditory brain, and are therefore predicted to damage hearing function early and profoundly. Here we present evidence for this proposition, based on structural and functional features of auditory brain organization that confer vulnerability to neurodegeneration, the extensive, reciprocal interplay between ‘peripheral’ and ‘central’ hearing dysfunction, and recently characterized auditory signatures of canonical neurodegenerative dementias . Moving beyond any simple dichotomy of ear and brain, we argue for a reappraisal of the role of auditory cognitive dysfunction and the critical coupling of brain to peripheral organs of hearing in the dementias. We call for a clinical assessment of real-world hearing in these diseases that moves beyond pure tone perception to the development of novel auditory ‘cognitive stress tests’ and proximity markers for the early diagnosis of dementia and management strategies that harness retained auditory plasticity. et al. explore why realising this potential requires understanding hearing as a complex brain function that is especially vulnerable to neurodegeneration.Epidemiological data indicate that mid-life hearing loss is a modifiable risk factor for dementia, with potentially major diagnostic and therapeutic implications. Johnson  Hearing impairment in later life is a major clinical issue and a leading association of cognitive decline . ConversRecent studies addressing the link between hearing impairment and dementia have focused predominantly on audiometric pure tone detection, the ability to detect quiet sounds  Fig. 1)Fig. 1). Evidence that neurodegenerative pathologies target the auditory brain and produce ‘central’ hearing deficits disproportionate to any peripheral hearing loss was first produced some time ago  depends on precise integration of frequency-based  and time-based  information Fig. 1). These functional principles are evident throughout the auditory system  and are The anatomical and functional interactions of auditory processing stages  suggest Moreover, neurodegenerative diseases typically target the ageing brain, and healthy ageing itself affects multiple stages of auditory processing, ranging from cochlea to cortex  spectrum (Parkinson’s disease and dementia with Lewy bodies) and may be a marker of disease onset, evolution and severity .Auditory perceptual dysfunction is emerging as a core feature of nfvPPA  will tend to amplify any degree of peripheral deafness and reduce compensatory capacity under natural (noisy) listening conditions. This reflects the extensive reciprocal interplay between afferent and efferent auditory processing pathways, exquisitely vulnerable to neurodegenerative proteinopathies. Moreover, neurodegenerative pathologies have distinct and relatively specific auditory cognitive phenotypes as well as generic effects on cognitive functions relevant to hearing, in line with the large-scale neural network signatures of these diseases. The synthesis we propose has neurobiological, diagnostic and management implications that should be tackled in future work.Neurobiologically, central auditory dysfunction is likely to be a fundamental, early consequence of neurodegenerative dementias, due both to direct involvement of susceptible auditory processing networks by pathogenic protein spread and remote effects on highly interconnected structures. This requires substantiation using physiologically grounded neuroimaging techniques such as functional MRI and magnetoencephalography that may also help clarify the neural mechanisms of compensatory and therapeutic effects. Detailed, longitudinal disease phenotyping with biomarker and ultimately histopathological support  will be required to elucidate the auditory pathophysiological signatures of particular proteinopathies, to assess the relative importance of hearing impairment in different diseases and to clarify the role of peripheral hearing deficits in potentiating the neurodegenerative process . D.E.B. is supported by a BRC Hearing and Deafness grant. C.J.D.H. is supported by an Action on Hearing Loss-Dunhill Medical Trust Pauline Ashley Fellowship. J.D.W. receives grant support from Action on Hearing Loss, Alzheimer’s Research UK, Alzheimer’s Society, Guarantors of Brain, Brain Research UK, MRC, Wellcome Trust, and the Wolfson Foundation.The authors report no competing interests.


Dendrobium genus are precious traditional herbs with high commercial value and excellent medicinal effects. They are perennial aerophytes or epiphytes of terrestrial orchids growing on cliffs and tree trunks covered with mosses in forests throughout the tropical and subtropical Asia and eastern Australia. The stem contains a variety of bioactive components, including polysaccharides and alkaloids, with strong antioxidant, neuroprotective, and immunomodulatory effects. Great attention has been drawn to the Dendrobium genus regarding its medicinal effectiveness, and the related researches have been accumulating rapidly in recent years. The bioactive components are mainly the intermediates or final products produced in specialized metabolite biosynthesis. Thus far, the activity, molecular structure, and composition of major medicinal ingredients have been partially elucidated, and the sequencing of several transcriptomes has been starting to shed new light on the biosynthesis regulation mechanism. This paper reviewed the advances of researches concerning the biosynthetic pathways of medicinal specialized metabolites from Dendrobium, especially the large number of related genes, with the hope of further promoting the development and utilization of those components and correspondingly protecting the Dendrobium resources in more effective ways.Many plants of  Dendrobium, one of the largest genera in the Orchidaceae family with more than 1500 species worldwide, is mainly distributed throughout India, southern Asia, Japan, Australia, and some Pacific islands , D. huoshanense, and D. chrysanthum, are highly prized folk medicines  pathway (cellulose synthase-like A 6 (DoCSLA6), UDP galacturonate 4-epimerase (DoUGE), UDP-glucose pyrophosphorylase (DoUGP), and GDP-mannose pyrophosphorylase 1 (DoGMP1) have been cloned and functionally characterized in D. officinale . Functional analysis based on KEGG terms revealed 25 genes associated with alkaloid backbone construction that belonged to the TIA class by using the Roche 454 GS FLX Titanium platform , such as cytochrome P450s (CYP450s)-mediated oxidation and hydroxylation reactions  were likely to be involved in hydroxylation steps of alkaloid biosynthesis. In D. huoshanense, 229 unigenes were identified as putative CYP450s, most of which were also the CYP71 family members (7.8%), followed by CYP3A and CYP4 family members  also plays a vital role in coordinating the expression of alkaloid biosynthesis genes, thus affecting the constituents’ composition in higher plants . For exaDendrobium plants are precious medicinal herbs partially because of their abundant polysaccharides found in stems, leaves, and flowers. In recent years, many soluble polysaccharides were extracted from various Dendrobium species, and the structure, composition, and bioactivity were determined , fucosyltransferase (11), mannosyltransferase (16), and xylosyltransferase (17) using BLASTX methods.Polysaccharides are one of the major medicinal components in tivities . Thus fativities  encodingtivities . Enzymescterized . Moreoveficinale . GT is aficinale . A recenficinale  identifiDendrobium species, accounting for as much as 58.3% of the dry weight of the crude polysaccharide fraction in D. officinale (cellulose synthase A (CesA) superfamily genes have also been demonstrated to be involved in the biosynthesis of mannan polysaccharides  were identified and analyzed to provide genetic evidences for their roles in mannan polysaccharide biosynthesis  method. The expression of DoNI was associated with its activities in different tissues and, more importantly, the polysaccharide accumulation  and Susy, respectively . A previtivities . Yan Liativities  analyzedisolated . Alkalinmulation . Uridineficinale . It was ficinale . Sucrosecultures . Thus, DTR homologous genes found in other plant species do not have tropinone reduction activity, except for plants belonging to or closely related to the Solanaceae family  using the NADPH as coenzyme . TRs cane family  and CoTRicinalis . Recentlcoenzyme . Moreovecoenzyme , implyinD. officinale, exhibiting diverse medicinal functions including antioxidant and protective effects on cell toxicity and treatment of various degenerative and age-related diseases , CYP75A, and flavonoid 3′-monooxygenase. Specifically, FLS is involved in the transformation of dihydroquercetin to quercetin, and dihydrokaempferol to kaempferol, which can be subsequently catalyzed into quercetin by CYP75A and flavonoid 3′-monooxygenase  by forming peloton to supply nutrients for their hosts  and stress hormones  can also promote specialized metabolite accumulation. For example, the alkaloid biosynthesis was markedly increased in ectively . The phy species . Exogeno species . Additio. roseus . Likewis. roseus  upregulaDendrobium genus in Orchidaceae is well known worldwide for its high economic and medicinal values. Recently, transcriptomes of Dendrobium have been sequenced for validation of genes involved in specialized metabolite biosynthesis. The resultant datasets will contribute to further research on metabolic pathways, molecular genetic breeding, genetic engineering, excavation, and protection of genetic resources of medicinal Dendrobium plants. Along with the progress of sequencing technology, novel strategies of targeted isolation, purification, nuclear magnetic resonance (NMR) identification, proteomics, and metabolomics will facilitate the full exploration of the molecular mechanism of bioactive ingredient biosynthesis regulation (Dendrobium. Therefore, it is feasible to improve active ingredients production by the combinations of stress stimulation and precursor feeding. Even though the engineering of specialized metabolite production is quite challenging due to incomplete and uncertain information, combinatorial biosynthesis (gulation . Meanwhiynthesis  that recZW and MW conceived the project. ZW drafted the manuscript. ZW, MZ, and HC evaluated and interpreted the data. JL and MW revised the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In addition to the aging process, risk factors for hearing loss in adults include, among others, exposure to noise, use of ototoxic drugs, genetics, and limited access to medical care. Differences in exposure to these factors are bound to be reflected in the prevalence of hearing loss. Assessment of hearing loss can easily be carried out on a large scale and at low cost using mobile apps.This study aimed to conduct a worldwide assessment of the differences in hearing loss prevalence between countries in a group of mobile device users.Hearing tests were conducted using the open-access Android-based mobile app Hearing Test. The app is available free of charge in the Google Play store, provided that consent to the use of the results for scientific purposes is given. This study included hearing tests carried out on device models supported by the app with bundled headphones in the set. Calibration factors for supported models were determined using the biological method. The tests consisted of self-determining the quietest audible tone in the frequency range from 250 Hz to 8 kHz by adjusting its intensity using the buttons. The ambient noise level was optionally monitored using a built-in microphone. Following the test, the user could compare his hearing threshold against age norms by providing his or her age. The user's location was identified based on the phone’s IP address.P<.001), with the highest prevalences for Bangladesh, Pakistan, and India (>28%) and the lowest prevalences for Taiwan, Finland, and South Korea (<11%).From November 23, 2016 to November 22, 2019, 733,716 hearing tests were conducted on 236,716 mobile devices across 212 countries. After rejecting the tests that were incomplete, performed with disconnected headphones, not meeting the time criterion, repeated by the same user, or carried out regularly on one device, 116,733 of 733,716 tests (15.9%) were qualified for further analysis. The prevalence of hearing loss, defined as the average threshold at frequencies 0.5 kHz, 1 kHz, 2 kHz, and 4 kHz above 25 dB HL in the better ear, was calculated at 15.6% (95% CI 15.4-15.8). Statistically significant differences were found between countries (Hearing thresholds measured by means of mobile devices were congruent with the literature data on worldwide hearing loss prevalence. Uniform recruitment criteria simplify the comparison of the hearing loss prevalence across countries. Hearing testing on mobile devices may be a valid tool in epidemiological studies carried out on a large scale. The worldwide prevalence of hearing loss is estimated to be between 4.0% and 18.1% , dependiApart from age, risk factors for hearing loss in adults include, but are not limited to, exposure to noise, use of ototoxic drugs, genetic conditions, infectious diseases, and limited access to medical care ,8-12. InEpidemiological analysis of hearing loss allows the identification of causes and planning of remedies ,12. ActiWorldwide geo-epidemiological investigations of hearing loss have been conducted in the form of meta-analyses of available data from different studies as a consequence of political, financial, cultural, and geographical limitations in the planning of uniform research on such a large scale -3,13. OwSelf-performed hearing tests on mobile devices can be easily carried out on a large scale and at low cost while maintaining a uniform qualification criterion. They are broadly accessible due to widespread use of smartphones, and they do not require engaging qualified personnel, while their results are comparable to pure-tone audiometry -23. The The aim of this study was to assess the worldwide prevalence of hearing loss among Android users by means of the Hearing Test app ,25 and cThis was a cross-sectional study of hearing loss prevalence carried out by means of the open-access, mobile-based Hearing Test app . SubjectThe participants were recruited via the Hearing Test app that runs on Android systems. The app is offered free of charge in the Google Play store, where the user can become familiar with the app's features and download it to a phone or tablet. Thus, eligibility criteria for participants only included access to an Android device that is supported by the app. The test could be carried out by the phone owner or with his or her assistance.The study included tests carried out on mobile devices that supported the Hearing Test app for which calibration coefficients had been determined. All the tests in the study were carried out on bundled headphones that were supplied by the manufacturer in a set with the device. Devices of the same model used common calibration coefficients that were determined by the biological method ,28 on thThe hearing test consisted of self-determining the quietest audible sound by adjusting its intensity using the “I can hear” and “I can't hear” buttons. The intensity of a test tone could be changed many times. The quietest audible sound was confirmed with the “Barely audible” button. A modulated test tone was used, with a 100% modulation depth, 2 Hz modulation frequency, and an intensity changed in steps of 5 dB. When the intensity of the tone exceeded a 40 dB hearing level (HL), a narrowband masking noise was generated contralaterally at an intensity of 40 dB HL. For test tones above 60 dB HL, the intensity of the masking noise was increased to 60 dB HL. By default, the tests were carried out for frequencies from 250 Hz to 8 kHz; however, this range could be changed in the settings. The time to determine the hearing threshold was measured separately for each frequency. The hearing threshold determined in this way has been compared in previous works with pure-tone audiometry. A difference was found at the level of 2.6 dB (SD 8.3) , and theAmbient noise was monitored during the measurement after obtaining the user's consent to access the microphone resources. An equivalent continuous A-weighted sound pressure level LAeq was registered in accordance with the Android specification  that setAt the end of the test, the users could optionally enter their age to compare the obtained hearing threshold against the age-based norm. By design, the app was developed for adults. Therefore, the user chose his or her age by selecting a value from 18-90 years. Providing the age was not obligatory for this study, to minimize the amount of potentially incorrect data. All the entered age values were recorded in the database to eliminate tests for which several different values were given. The age was also determined from the note, where it could optionally be given. User gender was not collected.The user's country was determined using the geoPlugin service  on the bComparison of hearing loss prevalence between countries was conducted by adopting the definition of hearing loss as the average hearing threshold at frequencies 0.5 kHz, 1 kHz, 2 kHz, and 4 kHz above 25 dB HL in the better ear. The minimum number of tests for the country to be included in the analysis was calculated based on the standard deviation of the average hearing threshold determined in preliminary measurements at 17 dB. Assuming a level of statistical significance of .05, test power of .8, and an effect size of 5.0 dB, a sample size of 90 tests was obtained.The tests in this study were unsupervised. Therefore, prior to analysis, they were verified for duration. A very short duration suggests unreliable results that can be manifested by an increased measurement error. To eliminate these tests, the standard deviation of the hearing threshold grand average was analyzed in relation to the test duration. Time threshold was set at the level at which stabilization of the standard deviation was observed. Incomplete tests, test carried out without headphones connected, and tests repeated on the same device were excluded as well.Both the subject’s age and level of ambient noise during the test belong to data for which acquisition required additional action on the part of the user. Preliminary analyses have shown that these are sparse data compared to the hearing threshold, geolocation, and device model. Therefore, the country-specific hearing loss prevalence was calculated based on all the tests, whereas the bias was estimated and discussed basing on subgroup analysis. The tests with age were used to characterize the population and analyze an age-related hearing threshold, while tests with noise were used to calculate the ambient noise effect. Distributions of hearing thresholds in the subgroups were tested for equivalence using the Kolmogorov-Smirnov test. Confidence intervals for the hearing threshold median and the hearing loss prevalence were determined by means of bootstrapping.In the period from November 23, 2016 to November 22, 2019, 733,716 tests were carried out on 236,716 devices in 212 countries. The hearing threshold measurement at the fundamental frequencies 0.25 kHz, 0.5 kHz, 1 kHz, 2 kHz, 4 kHz, 6 kHz, and 8 kHz was performed in 728,674 of 733,716 (99.3%) tests. After examining headphone connection status and rejecting the tests carried out with disconnected headphones, 637,169 of 733,716 (86.8%) tests were obtained .Time limits were introduced to discard tests with a duration that actually prevented a correct measurement. The grand standard deviation of the hearing threshold in relation to the duration of the measurement at a single frequency is presented in Many devices were used for more than one test. To eliminate tests repeated by the same person or carried out in bulk  only one test from each device was qualified for the analysis. The last test was selected, at first considering the test with an age provided. Finally, 116,733 of 733,716 (15.9%) tests were obtained for the analysis. Age was provided for 8194 of 116,733 (7.0%) tests, and monitoring for ambient noise was present in 30,119 of 116,733 (25.8%) tests, whereas only 2556 of 116,733 (2.2%) tests included both age and noise data.The subject's age was provided for 8194 of 116,733 (7.0%) tests that qualified for the analysis. The age characteristics of the research group is shown in P=.05.Tests with age provided were compared with those without age provided to estimate the bias resulting from the generalization of the results for the whole group. There were no statistically significant differences between the distributions of the hearing thresholds at the level of Hearing threshold in relation to age was analyzed based on all 7332 of 116,733 (6.3%) tests for which the age provided was within the range of 20 to 89 years. Tests completed by subjects aged 18, 19, or 90 years were omitted from the analysis to obtain equal age ranges (20-29 to 80-89 years). Moreover, the ages of 18 and 90 years were characterized by a higher number of tests in comparison with the adjacent age groups, suggesting the presence of additional data, such as results for subjects younger than 18 years or older than 90 years, or with incorrectly provided data. The median thresholds by age group and frequency are given in The prevalence of hearing loss was determined based on 733,716 tests conducted in 212 countries. The required sample size of 90 tests was reached for 74 countries. The prevalence of hearing loss, defined as a mean hearing threshold >25 dB HL in the better ear at 0.5-4 kHz, is presented in P<.001, with the monitoring group having a hearing threshold that was lower by 1.25 dB (SD 0.12 dB). This produces an overall effect of ambient noise of 3.78 dB (SD 0.75 dB), which corresponds to a 4.16% (SD 1.46%) reduction in the country-specific prevalence.The effect of ambient noise was estimated based on 30,119 of 116,733 (25.8%) tests conducted with ambient noise monitoring. The difference in the hearing threshold in relation to the ambient noise level is presented in The highest ambient noise levels were found in Pakistan, Bangladesh, and India, which corresponded to 10.7%, 8.6%, and 6.2% decreases, respectively, in the prevalences of hearing loss. Nevertheless, these countries still had the highest prevalences of hearing loss.P=.01. These differences result directly from the biological calibration method that is based on determination of the reference sound level in relation to subjects with normal hearing. The standard error of the biological calibration estimated at 4.2 dB for 16 independent measurements [Differences in hearing thresholds between device models were found to be significant at the level of urements  justifieP<.001). Of the 212 countries, 74 countries exceeded the number of tests required for the assumed sample size. Amongst these countries, the highest prevalences were found in Pakistan, Bangladesh, and India at 37.8% (95% CI 31.4-44.2), 32.2% (95% CI 23.6-40.8), and 28.5% (95% CI 27.1-29.9), respectively, whereas the lowest prevalences were found in Taiwan, Finland, and South Korea at 9.6% (95% CI 7.2-12.1), 9.8% (95% CI 5.7-13.9), and 10.2% (95% CI 9.5-10.9), respectively. The risk of hearing loss in Pakistan was 74.6% (95% CI 38.2-110.7) higher than in Taiwan. The absolute difference was 28.2% (95% CI 14.4-41.8).This paper presents the prevalence of hearing loss worldwide based on the 116,733 hearing tests conducted by Android users on mobile devices. The global prevalence of hearing loss was 15.6% (95% CI 15.4-15.8). Statistically significant differences were found across countries  were selected for the analysis. The number of tests rejected due to incompleteness, short duration, lack of headphones, or repetitions on a single device seems reasonable, especially as prior to performing a proper test, users often become familiar with the app by conducting a trial test.In addition to Finland, relatively low hearing loss values were obtained for the other two Scandinavian countries, Sweden and Norway, at 12.1% (95% CI 8.4-15.9) and 12.7% (95% CI 8.1-17.4), respectively. The prevalences of hearing loss for the other two Asian Tigers  were slightly higher, at 14.6% (95% CI 10.0-19.2) and 15.3% (95% CI 10.3-20.4), respectively. The high prevalence of hearing loss in India, which, along with Pakistan and Bangladesh, is one of the most populated countries in the world, is supported by the findings of Garg et al . SimilarIn Italy, 20.0% (95% CI 19.3-20.7) of the subjects had hearing loss, and this value was definitely higher than in the other Western and Central European countries. The credibility of this result is questionable due to the much higher use of apps in this country, being the highest in the world and reaching 222.3 people per million population . AttentiThe required sample size was not reached in a significant number of African countries. In the poorest countries, the limiting factor is access to mobile devices and the internet. The same situation may also occur in countries with significant social stratification, contributing to the lower prevalences of hearing loss resulting from a lack of data from the poorer part of the population. The lack of data from China is related to the lack of active Google Play service in this country.The prevalence of hearing loss in countries has been correlated with the infant mortality rate , which iAge related hearing loss assessed by means of the mobile app was compared with the results from other studies ,31,35-39Increased hearing thresholds in younger age groups may be associated with a tendency for hearing-impaired subjects to take a test more willingly than people with normal hearing as well as with increased ambient noise, which mainly affects soft sounds. Lower values for the oldest groups might be related to an incorrect reaction to the masking noise. The effect of ambient noise and the masking noise is discussed in the Limitations section.The prevalence of hearing loss among users of the Hearing Test app may differ from population values, at least as regards the age structure. However, the value was compared with worldwide estimates. The prevalence of hearing loss was also compared with other studies. Calculations were performed by adopting the criteria for hearing loss and matching age ranges . The preHearing thresholds for older groups at a frequency ≥4 kHz are lower than those reported in the literature . A histoAmbient noise was recorded using a built-in microphone with a working range of 72-102 dB SPL, as guaranteed by the Android specification . Since tA relatively low elevation of the hearing threshold related to a considerable increase in ambient noise may be associated with the measurement method applied in this study and in the study by Na et al . InsteadThe effect of ambient noise on hearing test results was determined assuming that the increase in hearing threshold caused by ambient noise is conditioned by the masking of the test signal by the noise. However, for significant hearing losses, ambient noise values above the normative level need not mask the loud test signal. Therefore, it must be assumed that the effect is present only for soft test signals and the estimated level for the effect of 3.78 dB (SD 0.75 dB) found in the present study should actually be treated as its upper limit. For these reasons, the results broadly correspond to pure-tone audiometry  despite Mobile devices were calibrated using the biological method . This method is less accurate than laboratory calibration. However, it enables semi-automatic calibration, which is crucial for as many as 1336 models. Because the tests were conducted on diverse device models in each country, the error associated with calibration has limited impact on differences between country-specific hearing loss prevalences.This paper presents global country-specific prevalences of hearing loss based on self-tests carried out by Android users. Unsupervised self-tests require additional quality control based on the test duration and connection status of the headphones. Moreover, ambient noise and calibration method introduce additional bias. Despite this, hearing thresholds measured by means of mobile devices were congruent with data reported in the literature, whereas uniform recruitment criteria facilitate the comparison between countries. Hearing tests on mobile devices may be a valid tool in epidemiological studies carried out on a large scale.


As we move around in the world, we process a vast amount of visual information while we interact with objects or events, navigate our way in the environment, and process emotional and social information. Due to changes and interruptions in the visual input, for example during eye movements, task performance often relies on short-lived internal visual representations of the external world. Visual working memory (VWM) is the mechanism in charge of the formation and temporary maintenance of such representations , was enhanced relative to memory for meaningless images. Interestingly, monitoring of real-world objects was less biased.Metacognitive processing has gained little attention in VWM research. Zimmer and Fischer compared VWM for Chinese characters in Chinese and German participants. Across multiple experiments, they found that Chinese participants were better in detecting changes in the characters' shape but not in other aspects of these characters, such as their color or font type. These results provide novel evidence for an influence of LTM on VWM performance within the domain of word forms, contributing to a growing literature investigating the effects of familiarity and expertise on VWM performance (Jackson and Raymond, Similarly investigating the influence of LTM on VWM, Guillory and Kaldy explored 12-month old infants' memory for real-world objects which were embedded in natural scenes. The authors examined whether, similar to adults, infants accumulate visual information in memory over time, and whether the formed memory representations are immune to interruptions. Infants' memory improved with longer exposures, showing accumulation of information over time. The formed representations were fragile as interference impaired memory performance. However, eye-tracking data demonstrated that some aspects of the scene survived the interference. The study adds to our understanding of the development of VWM in ecological contexts.Only few studies investigated the developmental trajectory of VWM for complex materials. Costanzi et al. tested whether memory for spatial locations that were associated with emotional information was enhanced relative to locations that were associated with neutral stimuli. Moreover, they systematically manipulated the level of valence and arousal of the emotional stimuli in four experiments. The results demonstrated that emotions enhance spatial WM performance when neutral and emotional stimuli compete with one another for access into VWM, as well as shedded light on the interplay between arousal and valence in driving information processing into VWM.Three articles in the collection explored the interaction and role of VWM in emotion and social contexts. Gambarota and Sessa provided a comprehensive review on the representation of faces in VWM, through its interaction with LTM and emotional and social cognitive mechanisms. They reviewed studies comparing VWM representations of faces and of other classes of stimuli, summarized the findings on representing static and changeable facial features in VWM, and finally examined research showing qualitative differences in VWM for face representations as a function of psychopathology and personality traits. This review enabled us to have a panorama about the representation of faces in VWM and its potential role in supporting socio-affective cognition.Ye et al. further explored the function of retaining biological movements in VWM. Biological movements are one of the most complex stimuli in our daily life, and contain rich social information. The study revealed that VWM capacity for biological movements not only predicts core social ability (Gao et al., Taken together, the studies in this topic provide a more ecological view of VWM, seen as an adaptive system that evolved to reflect the structure of natural regularities, prioritize social, and emotional information which is necessary for survival, and integrates long-term knowledge of the environment. The articles highlight some of the important topics that need to be studied further and be incorporated into a comprehensive, more ecological model of VWM.All authors listed have made a substantial, direct and intellectual contribution to the work and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


IntroductionPitch mismatch is one of the most important problems of users of bimodal cochlear implants, which affects their life satisfaction. Children with acquired hearing loss cannot explain their pitch mismatch problems, as they have had no auditory experience. This study tries to diagnose pitch mismatch in these children through the sound-induced flash illusion test.Materials and methodsIn this study, 20 children with a bimodal cochlear implant and 20 children with normal hearing, within the age range of 8 to 13 years old, were examined using the sound-induced flash illusion test. In this test, participants received one flash with one to four beep sounds, and they were asked to indicate the number of perceived flashes.ResultsThe results revealed that in the bimodal implantation group, when the flash was provided with one beep, at certain frequencies, children expressed that they saw two flashes. However, the results were not the same in children with normal hearing.ConclusionThe results indicated that at frequencies where the auditory information of the hearing aids and those of the cochlear implants overlap, pitch mismatch develops, which can significantly affect the auditory performance of bimodal users. Children with severe to profound hearing loss have no experience of hearing. Thus, when they receive hearing aids or cochlear implantation, according to the sound they get from the amplifier, the auditory nerves bring the sound to the temporal cortex, where brain mapping occurs for input frequencies . HoweverDespite all the advantages of acoustic-electric stimulation, the users of acoustic-electric stimulation are not permanent users of hearing aids, as they are not fully satisfied with the aids, which is due to the pitch mismatch between the ears . StudiesIn 2002, Shams et al. introduced the sound-induced flash illusion (SIFI). In this phenomenon, an acoustic stimulus can affect the perception of the visual stimulus. The test provides the participant with a flash stimulus, which is accompanied by one to four beep sounds. Then, the participant is asked how many flashes they have seen . For exaAccordingly, in this study, we intend to diagnose pitch mismatch in bimodal implant children through the integration of auditory and visual sensory information. Hence, one flash and one beep sound are provided for the child. According to Shams et al., in this phase the child should report only one flash. However, if the child reports two flashes, it may be assumed that the child has heard two beep sounds due to the pitch mismatch between the hearing aid and the cochlear implant. This test is performed for the frequencies of 125, 250, 500, 750, 1000, and 1500 Hz.In this study, 20 prelingual hearing loss children with a bimodal cochlear implant  within the age range of eight to 12 (mean of 10 and SD of 1.25) and 20 children with normal hearing  within the age range of eight to 13 (mean of 10.03 and SD of 1.09), who had no middle ear infection in the tympanometry test , mental Table In the group of children with bimodal implantation, all children had the Cochlear Nucleus® implant  so that the effect of different processors on the test would be controlled. All participants were tested in terms of the aided hearing threshold at the frequencies of 250 to 4000 Hz for electrical stimulation alone, or hearing aid alone, so that the amplified hearing threshold at the normal level would be confirmed. Table 2 at the angle of 2° out of 5° of the visual field eccentricity on the black display of a laptop with a luminance of 0.02 cd/m2. The time interval between the flashes was 50 ms [In order to ensure the visual health of the participants, all subjects were assessed using a Snellen visual chart. Also, the tympanometry test was performed to rule out middle ear infection in all participants. Written informed consent was obtained from the participants. The study was approved by the Human Research Ethics Committee of the University of Medical Sciences (IR.TUMS.FNM.REC.1398.139). For the hearing stimulus (beep), the frequencies of 125, 250, 500, 750, 1000, and 1500 Hz were played with a duration of 7 ms at 95 dB SPL by a speaker in the center of the monitor. The time interval between the beeps was 57 ms, and the beeps were always played 23 ms before the flash. The flash stimulation was played with a duration of 17 ms and the luminance of 108 cd/mas 50 ms . DetailsTo perform the test, participants sat on a chair 58 cm away from the laptop display (model ASUS X550). They were asked to fixate their eyes on the display continuously and to report the number of flashes they could see. The test was conducted in a dimly lit room and in a quiet environment, where the participants were asked to turn off their cellphone in the room. In the test, a flash was played along with zero to four beep sounds presented via the speaker at each frequency , where the participants were asked to indicate the number of flashes they could observe. Each test was performed randomly five times per participant for each frequency. Then, the results of both groups were recorded at different frequencies and then analyzed. All analyses were performed by SPSS version 22 . Analysis of variance (ANOVA) was used to compare the mean number of flashes perceived by each of the two groups. The Tukey honest significance test (HSD) post-hoc was used for pairwise comparison when ANOVA was significant. The significance level was considered 0.05.There is no significant difference between the aided hearing thresholds between ears in the bimodal group. The results of normal participants and participants with a bimodal cochlear implant revealed that at different frequencies and various trials, there is a significant difference between the two groups. Figure As can be seen at all frequencies for the F1B0 trial, the numbers of perceived flashes are very close to each other, but when the number of beeps increases, the results for the different frequencies are highly variable. At the frequency of 125 Hz for all trials, there is no significant difference  between the two groups. On the other hand, at the frequency of 250 Hz, a significant difference  between the groups can be observed only for the F1B1 and F1B2 trials. From the frequency of 500 Hz to 1500 Hz, there was a significant difference  in the number of perceived flashes for the F1B1, F1B2, F1B3, and F1B4 trials. As can be seen in the F1B1 and F1B2 trials, with the increase in frequency, the mean difference in the number of perceived flashes between the participants with normal hearing and bimodal implant users increased. However, for the F1B3 and F1B4 trials, no specific pattern could be seen upon frequency elevation and the mean number of perceived flashes is very variable in both groups, which is due to applying a more difficult test for these two trials.The present results show that pitch mismatch increases with increasing frequency. This mismatch is due to differences in cochlear implants and hearing aids. For most cochlear implant users, due to the impossibility of inserting the electrode deep into the apex of the cochlea, and the sound processing algorithms, pitch perception for frequencies below 300 Hz is limited, so cochlear implants cannot use frequencies below 300 Hz. This limitation causes them to lose many temporal fine structures related to F0 . In the According to the mean number of perceived flashes between the two groups, we found that in the F1B3 and F1B4 modes, there was a significant difference between the bimodal group and the normal subjects. In this regard, studies have shown that the F1B3 and F1B4 trials are difficult even for people with normal hearing . HoweverIn conclusion, the findings of the study indicated that in bimodal cochlear implant users, loudness and pitch cannot be matched between the two ears completely. The SIFI test helps specialists manage pitch mismatch at various frequencies. Therefore, conducting the SIFI test in cochlear implant centers is recommended.


Cell proliferation and death are key components of wound healing and tissue repair. Telocytes (TCs) represent a newly discovered cell type that can protect tissue from acute injury via cell–cell communication with adjacent cells. The aim of this study was to use a mouse model of skin wound healing and lipopolysaccharide (LPS)-induced cell injury to evaluate the effects of TCs on skin wound healing in vivo and in vitro.Immunohistochemical staining was performed to evaluate the alteration of TCs in tissues from normal and chronic wound patients. Then, a male C57BL/6 mouse wound model of the back was established. The mice were divided randomly into three groups, and wound healing was estimated according to the wound healing rate and histology. An LPS-induced co-culture model of a mouse lung telocyte cell line (TCs) with human keratinocyte (HaCaT), human dermal microvascular endothelial cell (HDMEC) or murine fibroblast (L929) cell lines was established to analyse the effects of TCs on constitutive cell types of the skin. Cell proliferation, migration and apoptosis were examined, and reactive oxygen species (ROS) and inflammatory factors in HaCaT cells, HDMECs, and L929 cells were detected to study the mechanisms involved in TC protection in skin wounds.TCs were significantly increased in tissues from chronic wound patients compared with healthy controls. Wound healing was significantly improved in wound mouse models treated with exogenous TCs compared with LPS-induced models. TCs reversed the LPS-induced inhibition of HaCaT cells and HDMECs and reduced the LPS-induced apoptosis of HaCaT cells and the death ratios of HDMECs and L929 cells. TCs reversed LPS-induced ROS in HDMECs and L929 cells and decreased inflammatory factor mRNA levels in HaCaT cells, HDMECs and L929 cells.TCs reduce wound healing delay, and inflammatory responses caused by LPS might be mediated by inflammatory inhibition, thus restricting apoptosis and promoting migration of the main component cell types in the skin. Chronic wounds are an intractable clinical problem. Although there have already been many management and treatment strategies, treatment remains a major problem since chronic wounds are apt to relapse. Understanding the mechanisms of chronic wounds could provide an opportunity to search for effective methods to treat chronic wounds. The process of wound healing is complex and coherent and involves four stages: inflammation, granulation tissue formation, re-epithelialization, and shaping after wound healing . During Telocytes (TCs) represent a newly discovered interstitial cell type that was found by the Popescu group, and they are widely distributed in the tissues and organs of the body, including the heart, lungs, kidneys, liver and other tissues, even in skin . TCs are+ TCs accumulated in the dermis of chronic wound tissue. Although chronic wounds can be caused by many kinds of reasons, such as venous hypertension/congestion, arterial insufficiency, prolonged unrelieved pressure or diabetes, they experience a common pathophysiological process: excessive inflammation. Since bacterial biofilms contained LPS is a major impediment to the inflammation of wound healing, LPS-induced male C57BL/6 mouse full-thickness cutaneous wound model was established [To investigate whether TCs play roles in cutaneous wound healing, immunohistochemical staining was first conducted to detect the distribution of TCs in tissues from normal and chronic wound patients. And the results showed that PDGFRαablished . The effablished  or murinablished  with TCsOur study enrolled three patients who suffered from diabetic foot, venous ulcers and pressure ulcers. Three normal control tissues were obtained from three patients, one of whom suffered from a benign nevus and 2 from lipoma. All chronic wound patients were subjected to debridement, and all control patients underwent lumpectomy. All patients signed an informed consent form, and ethical approval was provided by the Ethics Committee of Zhongshan Hospital.6 TCs suspended in 0.2 ml PBS; and (iv) LPS-induced and TCs treated combined group (n = 12) was intradermally injected with 10 μg/ml LPS dissolved in 0.1 ml PBS and then treated with 1 × 106 TCs suspended in 0.1 ml PBS local injection. Different reagents and cells were intradermally injected around each wound, and injections were given every other day. Three and seven days after wounding, the tissues were excised for histological analysis. The remainder of the mice were used to evaluate the speed of wound healing. The wound was photographed with a camera after surgery on days 0, 2, 4, 6 and 8. Then, the photos were analysed by using ImageJ software. All the photos were taken accompanied with a ruler that served as the standard. The wound healing rate (percentage) was calculated as follows: the area of the actual wound/the area of the original wound × 100%.Animal studies were performed according to the national guide for the care and use of laboratory animals. Ethical approval was acquired from the Ethics Committee of Zhongshan Hospital. Twenty-four male C57BL/6 mice, aged 8–10 weeks, were used in the experiment. The mice were divided into four groups, and each mouse was anaesthetized with 1% pentobarbital sodium (50 mg/kg) and received a 6-mm skin wound on the back via scissors; after that, different groups received different treatments as follows: (i) the vehicle group (n = 12) received local injections of 0.2 ml phosphate-buffered saline (PBS); (ii) the LPS-induced group (n = 12) was intradermally injected with 10 μg/ml LPS  dissolved in 0.2 ml PBS; (iii) the TCs treated group (n = 12) was intradermally injected with 1 × 105 cells/ml, and the medium was replaced with serum-free medium 24 h before LPS stimulation.Mouse TCs were kindly provided by Dr. Dongli Song . This TCs were isolated from mouse and transfected with SV40 large and small T antigen, and identified with telopodes (Tps) and the expression of ckit, CD34, vimentin and PDGFRα from generation 5 to generation 50 . Human dHistological sections were prepared from tissues excised 3 and 7 days after wounding, fixed in 10% buffered formalin and embedded in paraffin. The 5-μm sections were stained with haematoxylin and eosin (H&E) to detect the infiltration of inflammatory cells.2O2 and blocking nonspecific antigens with blocking solution , the sections were incubated with primary antibodies for PDGFRα at 1:100  overnight at 4 °C, and then the immunohistochemistry kits  were used for 1 h. The sections were observed at × 40 and × 200 magnification, and images were captured using a standard Olympus microscope .Recent studies demonstrated that PDGFRα was a credible marker for TCs identification . For theFresh TCs culture samples were collected in PBS at pH 7.4 and prepared for TEM as previously described . Grids wImmunofluorescent staining for CD34/Vimentin/PDGFα was used as previously reported for TCs identification. In brief, TCs were seeded on glass bottom cell culture dishes with 15 mm diameter glass  overnight. Then, cells were fixed in 4% paraformaldehyde containing 0.05% Triton-X-100 for 20 min and the dishes were washed for three times with 1 × PBS before blocking in 5% Bovine serum albumin (BSA) for 1 h. After incubated with mouse anti-CD34 antibody, goat anti-vimentin antibody or rat anti- PDGFRα antibody  diluted in 1% bovine serum albumin (BSA) in PBS overnight at 4 °C, the dishes were washing in PBS for three times. Cells were incubated with APC conjugated anti-mouse secondary antibodies, PE conjugated anti-rat secondary antibodies and FITC conjugated anti-goat secondary antibodies  for other 1 h at 4 °C in dark. The nuclear were marked with DAPI according to the manufacture . TCs were observed and recorded using Olympus FV3000 Confocal Laser Scanning Microscope .To detect the bio-behaviours of HaCaT cells, HDMECs, and L929 cells, a Cell-IQ cell culturing platform was used  and equipped with a microscope (Nikon CFI Achromat phase contrast objective with 10 magnification) and a camera 20. Bio-behaviours included cell proliferation and cell movement. Images were captured at 2-h intervals for 48 h. Analysis was conducted by using image software . Bio-behaviours of TCs induced by LPS were recorded by Cell-IQ, as well.After processing the cells as described above, the cells were collected in six-well plates, washed with PBS, and then incubated in annexin V conjugated with FITC and pidium iodide (PI)  according to the manufacturer’s instructions. After staining, the cells were analysed with a flow cytometer , and the results were analysed by using FlowJo v10.0.7 software.After processing the cells as described above, the cells were collected and dispensed in serum-free medium containing 10 μmol/L DCFH-DA , incubated at 37 °C for 20 min, turned upside down every 5 min, and washed three times with serum-free medium. The cells were analysed with a flow cytometer , and the results were analysed by using FlowJo v10.0.7 software.−ΔΔCt method.Total RNA was extracted using TRIzol reagent and reverse-transcribed using the cDNA synthesis kit ; SYBR Green PCR Master Mix ; and a real-time PCR system . The primer sequences (5′–3′) used were as follows: forward: 5′-GCGGCATCCAGCTACGAATCTC-3′, reverse: 5′-AACCAGCATCTTCCTCAGCTTGTC-3′ for human IL-1b (interleukin-1b); forward: 5′- CACTGGTCTTTTGGAGTTTGAG-3′, reverse: 5′-GGACTTTTGTACTCATCTGCAC-3′ for human IL-6 (interleukin-6); forward: 5′-GTGATGGCTGAACTGTCGCC-3′, reverse: 5′-CTGGGATGCTCTTCGACCTC-3′ for human IFN-γ (interferon-γ); forward: 5′-CCAATGGCGTGGAGCTGAGAG-3′, reverse: 5′-TCTGGTAGGAGACGGCGATGC-3′ for human TNF-α (tumour necrosis factor α); forward: 5′-TCCTGGTGCTCCTGGTGCTG-3′, reverse: 5′-CTGCCTGTCGGTGAGATTGGTTC-3′ for human MMP9 ; forward: 5′-GACATGGTGGTCGGCTTCGC-3′, reverse: 5′-CGCCTCTGTCATTCGTGCTTCC-3′ for human NFkB (nuclear factor kappa B); forward: 5′-CCTGGCACCCAGCACAAT-3′, reverse: 5′-GGGCCGGACTCGTCATAC for human β-Actin; forward: 5′-TCGCAGCAGCACATCAACAAGAG-3′ reverse: 5′-TGCTCATGTCCTCATCCTGGAAGG-3′ for mouse IL-1b; forward: 5′-ACTTCCATCCAGTTGCCTTCTTGG-3′, reverse: 5′-TTAAGCCTCCGACTTGTGAAGTGG-3′ for mouse IL-6; forward: 5′-CAGGCCATCAGCAACAACATAAGC-3′, reverse: 5′-AGCTGGTGGACCACTCGGATG-3′ for mouse IFN-γ; forward: 5′-GCGACGTGGAACTGGCAGAAG-3′ reverse: 5′-GCCACAAGCAGGAATGAGAAGAGG-3′ for mouse TNF-α; forward: 5′-GGAGCACGGCAACGGAGAAG-3′ reverse: 5′-CCTGGTCATAGTTGGCTGTGGTG-3′ for mouse MMP9; forward: 5′-ATCACCAACCAGCCAGGAATTGC-3′, reverse: 5′-CTGCGTCAAGACTGCTACACTGG-3′ for mouse NFkB; forward: 5′-TGGTCCTGCTGCTCGTCTTGG-3′, reverse: 5′-GTCCGCTGCTGCTCACACTTC-3′ for mouse EGF. The fold change in the relative gene expression to the control levels was determined using the standard 2Data are presented as the mean ± standard error of the mean (SEM). Statistical analysis was performed using by one-way analysis of variance (ANOVA) and Tukey’s multiple comparisons test. P < 0.05 was considered statistically significant. All statistical analysis was performed using SPSS Statistics 20 .Sections stained with anti-PDGFRα indicated that TCs were located in the papillary dermis, and revealed the distribution of TCs in granulation tissues from chronic wound patients. In the dermis of the skin, the quantities of TCs in chronic wounds significantly increased compared with that in the normal skin (P < 0.05), which demonstrated that TCs accumulated in the chronic wounding process Fig. .Fig. 1AcMouse lung TCs were successfully isolated and constructed as a cell line as previously reported. In order to confirm these TCs, we first identified them with the expression of markers typical of TCs. These TCs have special characteristics including relatively small cell body and very long and thin Tps with lots of dilations Fig. a. To furTo investigate the effect of TCs on wound healing, mouse skin wounds were treated with LPS and injected with TCs locally, and observed for 8 days. The results showed that wound healing rate was significantly delayed in the LPS group compared with that of the control on day 2 and day 8 (P < 0.05) (n = 6) Fig. . The ratIn order to study the mechanisms of TCs on incisional wound repair, we cultured HaCaT cells, HDMEC cells or L929 cells with TCs in a transwell system and/or with LPS treatment. The results showed that the proliferation of HaCaT cells was significantly decreased with LPS treatment for 20 h, while co-culture with TCs could reverse the anti-proliferation induced by LPS. LPS inhibited the migration of HaCaT cells in 48 h, and TCs ameliorated the inhibitory effect from treatment for 36 h Fig. a, d. LPSTo further confirm the effect of TCs on apoptosis, annexin V and PI staining were used for apoptosis analysis in cells co-cultured with TCs and treated with LPS for 24 h and 48 h. The death ratios in LPS-induced HaCaT cells was significantly increased compared with that of vehicle group, while the TCs-coculture decreased HaCaT cells death ratio after LPS treated. TCs-coculture reduced the ratios of late apoptosis, early apoptosis and whole apoptosis in LPS-induced HaCaT cells Fig. . The ratThe effects of TCs on ROS in LPS-treated HaCaT cells, HDMECs or L929 cells were further analysed by flow cytometry. The results showed that HaCaT cells, HDMECs or L929 cells induced by LPS exhibited significantly higher ROS than control cells. TCs co-culture significantly decreased LPS-induced ROS in HDMECs and L929 cells. However, TCs did not affect ROS in LPS-induced HaCaT cells, whereas TCs elevated ROS in LPS-induced HaCaT cells Fig. .Fig. 8ROWe further detected the levels of inflammatory cytokines in HaCaT cells, HDMECs and L929 cells co-cultured with TCs and induced with LPS. The results showed that IL-6, IL1β and NFκB mRNA levels were upregulated in HaCaT cells after LPS stimulation for 24 h, and TCs reduced the IL-6, IL1β and NFκB mRNA levels induced with LPS  the exact factors released by TCs or contained in exosomes produced by TCs; (2) the processes that TCs injection and interact with other type of cells such as epithelial cell during inflammation, whether TCs could lead to or reversing epithelial-mesenchymal transition (EMT) et al., (3) were there some other cell types, like immune cells are the target cells of the cell- cell communication of TCs, and whether the recently identified Toll-like receptors (TLR) 4 and 5/iNOS signaling pathway were involved in this processing ? Therefo


In vestibular schwannoma patients with functional hearing status, surgical resection while preserving the hearing is feasible. Hearing levels, tumor size, and location of the tumor have been known to be candidates of predictors. We used a machine learning approach to predict hearing outcomes in vestibular schwannoma patients who underwent hearing preservation surgery: middle cranial fossa, or retrosigmoid approach. After reviewing the medical records of 52 patients with a pathologically confirmed vestibular schwannoma, we included 50 patient’s records in the study. Hearing preservation was regarded as positive if the postoperative hearing was within serviceable hearing (50/50 rule). The categorical variable included the surgical approach, and the continuous variable covered audiometric and vestibular function tests, and the largest diameter of the tumor. Four different algorithms were lined up for comparison of accuracy: support vector machine(SVM), gradient boosting machine(GBM), deep neural network(DNN), and diffuse random forest(DRF). The average accuracy of predicting hearing preservation ranged from 62% (SVM) to 90% (DNN). The current study is the first to incorporate machine learning methodology into a prediction of successful hearing preservation surgery. Although a larger population may be needed for better generalization, this study could aid the surgeon’s decision to perform a hearing preservation approach for vestibular schwannoma surgery. It accounts for 6–8% of all intracranial tumors and is the most common cerebellopontine angle tumor2. Recently, with the help of better access to magnetic resonance imaging, the incidence has been increased, and the tumor size at the time of diagnosis has decreased4. With more early detection rates, more patients are asymptomatic when diagnosed. In these patients, the following management options may all be feasible: watchful waiting, surgery, or stereotactic radiosurgery(SRS). However, there are no clear guidelines or consensus on the optimal management of small VSs, and the optimal treatment is still under debate6. Treatment options differ individually and are dependent upon the physician’s experience, the size and growth rate of the tumor, age, patient’s preference, and hearing status. If the tumor is too big, or hearing is below serviceable hearing, hearing preservation is not essential in treatment7. Nevertheless, in small to medium-sized tumors with serviceable hearing, hearing preservation surgeries can be offered. Currently, middle cranial fossa approach(MCFA) and retrosigmoid approach(RSA) are the two most commonly used approaches to remove VSs.Vestibular schwannomas (VSs), or acoustic neuromas are benign tumors arising from the cochleovestibular nerve, which grows slowly8. The heterogenicity of the result makes it difficult to rate one strategy superior to another. Because hearing preservation operation takes longer and is more complex, leading to more post-surgical complications, it is reasonable to select the patients that are likely to have a decent postoperative hearing.The selection between the two approaches depends on the size and location of the tumor, and the surgeon’s preference, as each procedure has its strengths in exposing regions of the internal auditory canal or cerebellopontine angle. The preservation rate of MCFA and RSA varies among studies, ranging from 2% to as high as 93%14. In otology, there are relatively few, but recently, there were studies focused on the automated diagnosis of ear disease using otoendoscopy15, deep-learning-based noise reduction for improvement of speech recognition in cochlear implant patients16, and predicting the outcome of hearing in patients with sudden sensorineural hearing loss17. To our knowledge, despite studies focusing on predictive factors of hearing preservation surgeries20, it is hard to predict the patient’s probability of preserving auditory function following such surgery. We present a new system based on machine learning having input parameters based on preoperative data to predict the outcome of hearing preservation surgery in patients with VSs.Recent advances in machine learning are being adopted to medical fields, especially in image recognition, including radiology, ophthalmology, histology, and dermatologyFifty patients were in the cohort; 19 men and 31 women. Patient demographics are described in Table Four machine learning models  were compared regarding accuracy. The SVM based model showed approximately 62% percent, which is poor performance compared to the other three models. Three models  exhibited a reasonable accuracy of near 90% in 5-fold-cross-validation. The comparison between the four models is summarized in Table 21. It was able to maintain serviceable hearing at four years in 72.2% of the total patient in a study22. However, in a study that observed for a longer time, only 23% of the patient’s hearing was preserved following ten years of treatment23.Management of VSs depends on the individual patient’s status and often relies on the experience of physicians between observation, surgery, or stereotactic radiosurgery(SRS). Since increased usage of magnetic resonance imaging led to earlier diagnosis, more patients are now asymptomatic, and watchful observation is often the choice. When it comes to SRS, the tumor control rate is comparable to conventional microsurgery8. Therefore, it is reasonable to select the patient preoperatively who could benefit from such hearing approaches. Previous studies established a possibility for prediction of the prognosis of hearing preservation surgery in VSs20. Also, there are studies on intraoperative findings of tumor origin, SVN(superior vestibular nerve), and IVN (inferior vestibular nerve), and concludes SVN originating tumors is associated with better hearing preservation24. Preoperative determination of tumor origin (SVN or IVN) has some controversies; a study by Ushio et al. demonstrates no significant correlation of localizing tumor origin25. On the other hand, other papers show the usefulness of caloric and vestibular-evoked myogenic potential(VEMP) for determining tumor origin26.When it comes to surgical resection of VSs, not all hearing preservation approaches of VS microsurgery could spare hearing. The preservation rate ranges from as low as 2% to 93%27.In terms of evidence, this study focuses on previous findings that exhibited the correlation of preoperative tests with hearing outcomes. Preoperative PTA of each frequency, speech reception test results, caloric test results, VEMP asymmetry, and size and location of the tumor are all put into the input parameter of the proposed system. There is also a research with an emphasis on TEOAE (transient evoked otoacoustic emissions) pattern as a prognostic factor, where patients with preserved hearing tend to have TEOAE response in all five frequency  bands28, and better WRS indicates less damage to the nerve, which increases the chance of sparing nerve function in surgery.This study is, in a sense, an ensemble of several studies on predictive factors in hearing preserving VS surgery. With feature importance search, the most important factor seems to be WRS, which consistently was among the top essential features Table , and it Several efforts were made to increase the accuracy of the model. Although there are still debates on whether caloric tests can represent SVN function and VEMP tests can reflect IVN function, at least in some studies, they tend to correlate. These factors were calculated in the model and contributed to increased accuracy. In contrast, training with TEOAEs as input parameters did not improve accuracy. Instead, overall accuracy was decreased, and the gap between training loss and validation loss was increased, which indicates a more overfitting tendency in machine learning. As more input parameters are put, the system becomes vulnerable to overfitting, leading to reduced overall accuracy. In the DNN model, the number of hidden layers was 50 and 20 layers. Increasing the number of hidden layers to 200, 200, and 50 layers (wider and deeper network) led to a broader gap between training loss and validation loss, and lead to worse results, the accuracy of 0.8; again, implying overfitting.Besides machine learning strategies, conventional methods using simple logistic regression with ROC analysis were tried to predict the outcome of VS surgery. Using WRS as a cutoff, we were able to get 82% accuracy with 92.86% sensitivity and 68.18% specificity. Using PTA(3 K) yielded 86% accuracy with 89.29% sensitivity and 81.82% specificity .30. A similar approach could be applied to this study in the future by combining the current study’s data with radiologic and genomic data subnetworks, possibly gaining more accuracy and reliability.Although the accuracy difference between DNN model and other classical machine learning models  is somewhat small, there are still potential benefits of the DNN model. There are studies on the application of combining multi-omics data into individual subnetworks, then merging altogether for a prediction modelThe design of the study is based on domain-specific knowledge. Results of the previous studies to predict hearing preservation in VS surgery were utilized for feature engineering. In the current machine learning model, feature engineering of input variables was based on previous studies on possible predictors of hearing preservation. Likewise, this study’s design could be applied to other fields of medicine, possibly yielding high accuracy of prediction.Thanks to the nature of the prediction system based on machine learning, each patient can be individually predicted whether he/she could preserve hearing after VS surgery with an accuracy of 90 percent. However, we believe this accuracy does not mean that physicians could rely solely on algorithms, while our prediction system’s result may provide an important reference in the decision-making process. We think the treatment of VS should be based on individualized care. It requires a delicate assessment of risks and benefits when it comes to selection between watchful observation, surgical resection, and stereotactic radiosurgery. The attending physician should undergo a comprehensive review of the surgeon’s skills, patient’s preference, symptoms, tumor characteristics, and make a decision, putting it altogether. Our prediction system’s result may provide an additional factor in the decision-making process.There are limitations to this study. The total number of patients is only 50, and the deep learning system can not reach its potential performance, and it may be prone to overfit. Overfitting may cause lower accuracy in the test set or unseen data. Although the current number is small in the field of machine learning, it is relatively big considering the rarity of VSs and even more rarity of hearing preservation surgery candidates in the medical field. In the future, if we have more data, we may reinforce the system to generalize better, and thus, predict better.This is the first study to incorporate machine learning methodology into a prediction of hearing preservation surgery. The system is built based on evidence from previous studies and could aid physicians in deciding whether to perform hearing preservation surgery on patients with VSs with a serviceable hearing status. With better patient selection using our system, individualized medical care may result in better patient outcomes.This retrospective study was approved by the Severance Hospital Institutional Review Boards (IRB number 2019-1867-001). The need for written informed consent was waived by the approval process of the review boards, owing to the retrospective nature of the study. All methods were performed complying with the Declaration of Helsinki.Among patients diagnosed with VSs from 2007 to 2017, 52 patients underwent hearing preservation surgery, either via MCFA or RSA. While all patients were included in the analysis, two patients were excluded. One patient was initially considered as VS but later revealed to be facial nerve schwannoma, which is not relevant to hearing abilities. Another patient was diagnosed as Neurofibromatosis type II. Therefore, we included a total of 50 patient’s data in the machine learning model. The detailed patient characteristics are described in Table 27, the following preoperative measures were put into the learning model: 1) Pure-tone threshold of each frequency, 2) maximal word recognition score(WRS), speech detection threshold(SDT), most comfortable level of hearing(MCL), 3) Auditory brainstem response(ABR) latency of wave I-V interval, 4) asymmetry ratio of vestibular-evoked myogenic potential (VEMP), 5) canal paresis(CP) in caloric test of affected site, 6) maximum diameter of the tumor, and 7) type of approach (RSA or MCFA). Since the model was aimed to predict postoperative hearing preservation with preoperative tests, all intraoperative factors were not taken into account. Since RSA and MCFA are preferable in VSs in the cerebellopontine angle: porus and fundus, respectively, it was treated as the relative tumor location and included in preoperative measures.Electronic medical records of 50 pathologically confirmed vestibular schwannoma patients via MCFA or RSA for excision were obtained. After reviewing previous literature for possible predictors of postoperative hearingWe used a binary classification for prediction modeling. The result of the patient’s postoperative hearing was classified as preserved if the patient was able to maintain the pure-tone average better than 50 decibels, and the word recognition score was above 50% (50/50 rule) at six months postoperative audiology test.Some of the patient’s data were not available. VEMP asymmetry data was not available in 22 patients; CP in 1 patient; and I-V interval of ABR latency in 10 patients. In these cases, the median value was filled up for the machine learning model to minimize the missing effects. If the I-V interval of ABR latency was not countable, ten milliseconds were used. The VEMP asymmetry was calculated as the difference ratio of peak-to-peak amplitude between normal and pathologic P13 and N23 wave amplitude:www.pytorch.org) in Python programming language. In the training process, 80% of the patient’s data were used for training; 20% were left out for validation. We conducted five-fold-cross-validation for each model to rule out selection bias. The detailed composition of the model is described in Table The machine learning was performed in a supervised manner. Currently, boosting and bagging are the most popular methods among tabular datasets, choosing GBM and DRF as one of the models’ lineup. SVMs are somewhat classical and were included in the study for comparison of accuracy. Lastly, neural network models have shown to be effective not only in computer visions, but also in tabular datasets, and were added to our models’ lineup. Totally, four learning models  were trained, and a comparison between the models was performed regarding accuracy. MATLAB2019a®  was used for SVM based model. For DRF, GBM, and DNN models, we built the system with Pytorch (Supplementary information.


USH2A variants are associated with altered low-frequency sound perception which, in turn, increases the risk of developmental language disorder. We further show that Ush2a heterozygote mice have low-level hearing impairments, persistent higher-order acoustic processing deficits and altered vocalizations. These findings provide new insights into the complexity of genetic mechanisms serving language development and disorders and the relationships between developmental auditory and neural systems.Language development builds upon a complex network of interacting subservient systems. It therefore follows that variations in, and subclinical disruptions of, these systems may have secondary effects on emergent language. In this paper, we consider the relationship between genetic variants, hearing, auditory processing and language development. We employ whole genome sequencing in a discovery family to target association and gene x environment interaction analyses in two large population cohorts; the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK10K. These investigations indicate that  USH2A linked to a dominant language disorder in a human family and find that these variants are also associated with low-frequency hearing at the population level. They investigate the function of USH2A variants in mice, showing that mutations in this gene are responsible for hearing loss.Peter Perrino et al. identify variants in  These sounds are then mapped onto speech units (phonemes) enabling the extraction of meaningful linguistic constructs (comprehension). Even newborn babies turn their heads towards familiar voices and show a preference for speech over white noise2. These inclinations are fined-tuned over early life such that, at 3 months, infants show a preference for their native tongue over foreign languages and other vocal sounds (e.g. laughter)3. These behavioural distinctions are mirrored at the cognitive level; many studies show that speech evokes distinct neural responses, indicating that language is subject to privileged processing4. Early speech processing skills correlate with later language milestones5 suggesting that they modulate successful language acquisition.Learning to use and understand language requires the coordinated development of a whole host of underlying skills and processes. Assuming an initial bottom-up framework as posited by Tallal & others6), overt disturbance of the contributory processes can directly disrupt language development; congenital hearing loss is associated with widespread cognitive deficits in domains including attention, memory and language7. Less obvious disturbances of audition can also indirectly impact spoken language development, especially if they occur during critical time periods or in addition to other insults. For example, auditory processing disorder (APD), characterized by poor central sound processing despite apparently normal hearing, can lead to difficulties understanding speech in noisy environments8 and, when persistent, is associated with an increased risk of Developmental Language Disorder (DLD) and Attention Deficit, Hyperactivity Disorder (ADHD)9. In the current study we test this framework by assessing whether typical variations across genes that function in auditory pathways may form part of a complex risk mechanism in the emergence of language disorders. In support of our proposed framework, subtle disturbances of auditory processing have been described across many neurodevelopmental disorders where hearing is unaffected . Similarly, declines in later-life auditory processing skills are correlated with altered language function13.While hearing is not strictly essential to successful language development 25. These changes in the field led us to apply an alternative approach to the investigation of molecular mechanisms underlying hearing and language within the current study. More specifically, we investigate the molecular overlaps between hearing, auditory processing and language through the targeted study of a gene that has an established role in audition—USH2A. This gene encodes the Usherin protein, which acts as a lateral link between stereocilium, providing structural organization for hair cell bundle development26. Homozygous pathogenic changes in USH2A, and therefore complete absence of the usherin protein, result in disorganization or loss of cochlear outer hair cells27, leading to congenital hearing loss clinically described as Usher Syndrome (OMIM#276901)29. This syndrome is a monogenic recessive disorder  associated with hearing loss specific to the high-frequency ranges, often accompanied by retinitis pigmentosa. The disorder splits into three clinical categories (Types I–III), relating to severity and age of onset30 and homozygous USH2A mutations result in the majority of Type-II cases in which diagnosed individuals are born with hearing loss and develop retinitis pigmentosa at the onset of puberty, yet do not experience the vestibular dysfunction  found in other types of Usher31. In accordance with currently accepted genetic models, individuals with a heterozygous USH2A mutations are considered to be unaffected carriers.Current research suggests that genetic effects can overlap between syndromes that have traditionally been considered as clinically distinct. Similarly, genetic overlaps are reported between Mendelian forms of disease and more complex forms of disorderUSH2A variants exert direct effects upon low-frequency hearing and indirectly affect the risk of language disorder through the modulation of subsequent auditory perception and language development. These findings suggest a shared genetic etiology between hearing mechanisms, central auditory processing and language development and support the targeted investigation of sub-serving mechanisms in relation to language development.In the current study, we employ whole-genome sequencing in a discovery family to target association and gene x environment interaction analyses in two large population cohorts; the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK10K. We complement these statistical methodologies with the characterization of a mouse model that shows behavioural effects of a heterozygous knockout on hearing, complex acoustic processing, and communicative vocalization. We propose the existence of an “alleleic hierarchy” of variation within which different variant types have divergent effects upon auditory thresholds. We show that USH2A gene (NP_996816:p.Gln4541*) shared by all affected family members  score of 40, placing it in the top 0.01% of deleterious variants in the genome35, and meets clinical guidelines from the American College of Medical Genetics (ACMG) for a “pathogenic variant”36; it confers a stop mutation (Very strong evidence of pathogenicity—PVS1), has previously been described as pathogenic (Strong evidence of pathogenicity—PS1), is absent from population databases (Moderate evidence of pathogenicity—PM2) and cosegregates with disease (Supporting evidence of pathogenicity—PP1)36. No secondary putative pathogenic changes were found in other genes related to Usher syndrome or hearing loss  and full knockout (KO) mice. Hearing and complex acoustic discrimination thresholds were compared against WT controls on a series of prepulse inhibition (PPI) tasks37. Initially, using a simple single-tone detection task at 40 kHz (high-frequency), individual ANOVAs revealed that KO mice trended to the expected hearing impairment typical of Usher syndrome, while HT mice performed similarly to WT controls , while WT and KO did not differ  = 3.691, p = 0.036; Embedded Tone 10: 10.5 kHz: F = 4.635, p = 0.017)], and for KO mice on higher frequency tasks   across most syllable types  and produced calls that were shorter and louder than WTs   results in impaired expressive communication ability. This could reflect the importance of intact auditory feedback for vocal development , and is consistent with the higher vocal pitch observed in in profoundly deaf speakers38. The putative social impact of any vocalization anomalies will require additional study. Our behavioural investigations of the mouse model indicate that heterozygous disruption of Ush2a leads to altered low-frequency hearing thresholds, a phenotype distinct from the high-frequency hearing loss of Usher syndrome (and replicated in null Ush2a mice). Moreover, these altered low-frequency thresholds were further associated with higher-order auditory processing deficits, as well as disrupted vocalizations.Given the reported comorbidity between auditory processing and language impairments and the presence of dysarthria in the discovery family, we investigated whether pes ) was measured. Subjects were placed on cell-loaded platforms , and presented with varying auditory stimuli generated via RPvdsEx software and a RZ6 multifunction processor . Subject motor reflex responses were recorded via a Biopac MP150 acquisition system and Acqknowledge 4.1 software  connected to the load cell platforms. Tasks are detailed below and included detection of simple tones (15 or 40 kHz) in silence; and of deviant tones (variable duration) in a pure-frequency background . Tone frequencies were determined based on low and high-frequency bounds of the mouse audiogram (~2–50 KHz)77. Testing began at postnatal (P) day 65 and continued to P114. Normal Single Tone consisted of 104 trials conducted over one day, where Embedded Tone and Pitch Discrimination each consisted of 300 trials and were conducted over 5 consecutive days. During cued trials, subjects were presented with an auditory cue (prepulse) 50 ms before the presentation of the SES . If the subject was able to detect the auditory cue, an attenuation (or reduction) of their ASR was expected relative to their ASR during an uncued trial. If the auditory cue was not detected, the response was expected to equate to an uncued trial. Quantification of this phenomenon was termed the “attenuation score” (ATT), which compared the mean amplitude of cued ASR to that of the uncued ASR for each subject, for each session condition.Following puberty, subjects were tested on a battery of auditory processing tasks using a modified prepulse inhibition paradigm which allows free movement during the presentation of sounds that include an unpredictable loud noise burst Subjects were first tested on Normal Single Tone (NST) to measure baseline prepulse inhibition, general auditory ability, and to rule out any underlying auditory processing impairments that might impede performance on subsequent auditory processing tasks (i.e. impaired reflex mechanics). Subjects were required to detect a simple single tone  against a silent background. This cue was presented 50 ms before the SES on half of the trials , at inter-trial intervals (ITI) ranging from 16 s–24 s. Two versions of this task were developed – a 15 kHz version  and a 40 kHz version . All subjects were able to perform both versions of the task . The frequency-matched NST score for each subject was used as a covariate in the analysis of further tasks, specifically to eliminate individual differences in PPI or hearing from subsequent auditory processing analyses.The variable duration Embedded Tone Task (EBT) consisted of 300 pseudorandom trials with ITIs ranging from 16–24 s. Subject’s ability to detect a change in tone frequency from a constant pure-tone background was measured, and ATT scored were calculated. During cued trials, a single cue was presented 100 ms before the SES; for uncued trials, the “cue” was presented 0 ms before the SES (i.e. no cue). Three versions of this task were used: (1) a long-duration EBT task, where the cue duration ranged from 0 ms to 100 ms ; (2) a short-duration EBT task, where the cue duration ranged from 0 ms to 10 ms ; (3) an ultrasonic long-duration EBT task where the cue duration ranged from 0 ms to 100 ms . This combination of frequencies and temporal durations was designed to capture the range of processing capacities, allowing us to test for genotype-specific differences in that range. Non-ultrasonic and ultrasonic versions of the task were necessary to determine any Genotype effects observed were frequency dependent. Both non-ultrasonic versions of the task were administered for five consecutive days, and the ultrasonic version of the task was administered for four consecutive days .Pitch Discrimination (PD) testing assessed the subject’s ability to detect subtle changes in pitch within a constant pure-tone background. Each testing session consisted of 300 pseudorandom trials, with an ITI ranging from 16 s to 24 s. During cued trials, the cue was presented for 300 ms, 100 ms before the SES. “Cues” presented during uncued trials were presented at the same frequency as the pure-tone background. Two versions of this task were used for this study: (1) PD task where the cue frequency deviated 5–75 Hz above or below a 10,500 Hz pure-tone background ; and (2) ultrasonic PD task where the cue frequency deviated 5–75 Hz above or below a 40,500 Hz pure-tone background . A non-ultrasonic PD task was administered for five consecutive days, and an ultrasonic PD task was administered for three consecutive days.78. Using WT female homecage bedding and urine collected 5 days prior to testing, a single experimental male mouse was placed in a standard Plexiglass tub with a single novel WT female mouse and allowed to freely interact for 5 min. In this setting, a male mouse will vocalize while the female does not, such that recoded calls can be attributed to the male. A Brüel & Kjær Type 4954-B microphone , connected to a RME Fireface UC audio interface , was placed 5 cm above the top of the Plexiglass tub. USVs were recorded at 192,000 Hz using DIGICheck 5.92  to ensure all USVs were captured. Following USV recording, sound files (.wav) were analyzed in MATLAB (MathWorks) using MUPET (Mouse Ultrasonic Profile ExTraction79). Syllables in the range of 35,000 Hz to 110,000 Hz, and duration between 8 ms to 200 ms, were analyzed. If syllables occurred less than 5 ms apart, they were excluded from analyses. Following these parameters, a syllable repertoire was generated, illustrating 40 unique syllables  of each syllable was exported from MUPET and used for statistical analyses. Since comparable Genotype effects were seen on all call types, only the mean frequency shift is reported in the text  were recorded and analyzed using methods adapted from Chabout et al.−5. The final UK10K replication set included 1681 individuals (806M:875F) providing 81% power to detect a variant that explains 1% of the trait variance at a Bonferroni-corrected alpha level of 0.0033.The ALPSAC replication set included 7141 children (3615M:3526F), providing 96% power to detect a variant that explains 0.5% of the trait variance at a Bonferroni-corrected alpha level of 7.87 × 1067 and considered five traits (as detailed above) using three SNP selection thresholds  common variants (MAF ≥ 5%)), yielding a Bonferroni significance threshold of P = 0.0033 at an alpha level of 0.05.Gene-based analyses were performed within the UK10K dataset. These analyses employed the SKAT test in RVTESTS42 using a linear model of regression for quantitative traits and a logistic model for discrete traits. Five phenotypes were analyzed across 127 SNPs, yielding a Bonferroni significance threshold of P = 7.87 × 10−5 at an alpha level of 0.05.SNP-based analyses were performed within the ALSPAC dataset. These analyses employed tests of allelic association within PLINK42, which employs a linear regression model. Gene-level analyses were performed for 12 SNPs across the 5′ region of the USH2A gene and comprised of three language outcome measures (Early vocabulary (vocab), nonword repetition (NWR) and DLD status) and one interaction factor (Low-frequency hearing threshold (MinLow)) yielding a Bonferroni significance threshold of P = 0.0014 at an alpha level of 0.05. At the genome level, a single outcome measure (Early vocabulary (vocab)) was modelled with a single interaction factor (Low-frequency hearing threshold (MinLow)) for 488205 autosomal SNPs yielding a Bonferroni significance threshold of P = 1.02 × 10−7 at an alpha level of 0.05.Gene-environment interaction effects were modeled within the ALSPAC dataset at the gene and genome-wide level. These analyses used PLINKGene ontology classes were analyzed for over-representations using a Fisher exact test with FDR multiple test correction.Ush2a KO performance. To account for individual variation in baseline prepulse inhibition and hearing, NST was used a covariate for subsequent statistical analyses . EBT and PD tasks were analyzed using a mixed factorial design. Differences in ATT scores for non-ultrasonic EBT 100 and EBT 10 were conducted using a 3 × 5 × 9 repeated measures ANCOVA, with Genotype  as the between-subjects variable, and Day (five levels) and cue Duration (nine levels) as the within-subjects variables. Ultrasonic EBT 100 data were analyzed using a 3 × 4 × 5 repeated measures ANCOVA with Genotype (three levels) as the between-subjects variable, and Day (four levels) and cue Duration (five levels) as the within-subjects variables. For Pitch Discrimination, a 3 × 5 × 9 and a 3 × 3 × 5  repeated measures ANCOVA was used to determine ATT differences, where Genotype (three levels) was the between-subject variables and Day  and Frequency  were the within-subject effects. Statistical analyses were completed used SPSS 24 with an alpha criterion of 0.05.Normal Single Tone attenuation scores were analyzed using a one-way analysis of variance (ANOVA) comparing WT, HT, and Ush2a KO scores  was analyzed using a one-way analysis of variance (ANOVA) comparing WT, HT and res Fig. .All animal behavioural testing were performed blind to genotype.http://www.bristol.ac.uk/alspac/researchers/research-ethics/). All animal procedures conformed to the Guide for the Care and Use of Laboratory Animals and were approved by the University of Connecticut Institute for Animal Care and Use Committee (IACUC). The current animal study design adheres to the ARRIVE guidelines81.Ethical approval for the discovery family was provided by University of London & St George’s University Hospitals. All members provided informed consent/assent of investigation. Ethical approval for ALSPAC was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees (Further information on research design is available in the Supplementary InformationSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Description of Additional Supplementary FilesReporting SummaryPeer Review File