Phosphoinositides are known to play multiple roles in eukaryotic cells. Although dysregulation of phosphoinositide metabolism in the retina has been reported to cause visual dysfunction in animal models and human patients, our understanding of the phosphoinositide composition of the retina is limited. Here, we report a characterization of the phosphoinositide profile of the mouse retina and an analysis of the subcellular localization of major phosphorylated phosphoinositide forms in light-sensitive photoreceptor neurons. Using chromatography of deacylated phosphatidylinositol headgroups, we established PIP2 and PI(4)P as two major phosphorylated phosphoinositides in the retina. Using high-resolution mass spectrometry, we revealed 18:0/20:4 and 16:0/20:4 as major fatty-acyl chains of retinal phosphoinositides. Finally, analysis of fluorescent phosphoinositide sensors in rod photoreceptors demonstrated distinct subcellular distribution patterns of major phosphoinositides. The PIP2 reporter was enriched in the inner segments and synapses, but was barely detected in the light-sensitive outer segments. The PI(4)P reporter was mostly found in the outer and inner segments and the areas around nuclei, but to a lesser degree in the synaptic region. These findings provide support for future mechanistic studies defining the biological significance of major mono- (PI(4)P) and bisphosphate P2) phosphatidylinositols in photoreceptor biology and retinal health. Phosphoinositide phospholipids are essential components of membranes in every cell. The parent phosphatidylinositol (PI) can be phosphorylated combinatorially on the inositol ring at the 3-, 4-, or 5- position(s). Levels of phosphorylated phosphatidylinositols are tightly controlled by the activities of specific phosphoinositide kinases and phosphatases. Individual forms of phosphorylated phosphoinositides serve as unique signals to engage a variety of phosphoinositide binding proteins, thus affecting diverse cellular processes, including protein transport, cell polarity, cytoskeletal organization, ion-channel function, and gene expression ,2,3,4. D2 as major phosphorylated headgroups and 16:0/20:4 and 18:0/20:4 as dominant fatty acid species of retinal phosphatidylinositols. Furthermore, our analysis identifies distinct patterns of subcellular localization of these lipids within photoreceptors. These findings position PI(4)P and PIP2 lipids as central players in future studies of phosphoinositide metabolism in photoreceptors. Despite accumulating evidence that phosphoinositide signaling plays a critical role in many cellular functions, little is currently known about the phosphoinositide composition of the retina. Historically, phosphoinositides were studied in cell culture using radionuclide labeling approaches. However, the poor viability of the retina in vitro limits the utility of radiolabeling-based approaches in analyzing this tissue. Furthermore, these methods allow monitoring of phosphoinositide turnover, but cannot measure absolute phosphoinositide levels. Therefore, in this study, we took advantage of modern non-radiolabeling techniques to profile phosphorylated phosphoinositides of the mouse retina. Our study establishes PI(4)P and PIPAll procedures conformed to the Association for Research in Vision and Ophthalmology Statement for the Use of Animals in Ophthalmic and Vision Research and were approved by the Institutional Animal Care and Use Committee of University of Florida . Wild type C57BL/6J mice were purchased from Jackson Laboratory (stock # 000664) and housed under a 12/12 h dark/light cycle. Mice were maintained on a plant-based diet . For dark adaptation, mice were kept in a dark room for 12 h. For light conditioning, dark-adapted mice with dilated pupils were exposed to a light intensity of 500 lux for one hour. Animals were euthanized with isoflurane, followed by decapitation after the animals were rendered non-responsive. For lipid analysis, retinas were carefully dissected from enucleated eyes under infrared (for dark adaptation experiments) or room light (for light adaptation experiments) in Ringer’s solution, flash-frozen in liquid nitrogen, and stored at -80 °C. For subcellular localization studies of phosphoinositide sensors, the retinal agarose sections were prepared as previously described . BrieflyChemicals and solvents of ACS  or LC–MS (Liquid Chromatography–Mass Spectrometry) grade were purchased from Sigma-Aldrich, and synthetic lipid standards were purchased from Avanti Polar Lipids. M HCl and centrifugation at 5000× g for 5 min at 4 °C. Lipids were collected from the lower organic phase, dried under a stream of nitrogen, and deacylated as described [2O, and stored at −20 °C.Phosphatidylinositol extraction for HPLC chromatography was performed using a one-step acidified Folch method. It is generally accepted that due to their negative charge, phosphorylated phosphatidylinositols remain tightly bound to proteins and cannot be extracted using standard lipid extraction procedures. However, protonation of phosphoinositides with the addition of hydrochloric acid (HCl) neutralizes the negative charge on phosphoinositides, allowing their efficient extraction from proteins and partitioning from aqueous into organic phase during a standard Folch procedure. Flash-frozen retinas were homogenized in an ice-cold chloroform/methanol mixture (2C:1M supplemented with 0.1% of HCl) in the presence of 200 μL of acid-washed beads  by bead beating . Organic and aqueous phases were separated by the addition of 12 standards were measured by the colorimetric determination of phosphorus after digestion to inorganic phosphate and taking into consideration the number of phosphorus atoms in the corresponding lipid [Delipidated headgroups were separated on the Ionpac AS11-HC column (and AG11-HC guard column) connected to the ICS-2500 Dionex HPLC system. The column was equilibrated first with 10 mM NaOH and then with 1.5 mM NaOH. After sample injection (25 μL), elution was carried out in four stages at a flow rate of 0.38 mL/min: (1) gradient from 1.5 mM to 4 mM NaOH for 7 min; (2) 4 to 16 mM NaOH for 5 min; (3) 16 to 86 mM NaOH for 18 min; (4) 15 min isocratic elution with 86 mM NaOH. Elution was monitored by suppressed conductivity detection with the ED50 electrochemical detector. Commercially available phosphorylated phosphatidylinositols (Avanti Polar Lipids) were used for phosphoinositide profiling after deacylation. For experiments requiring quantification and calibration, concentrations of PI(4)P and PIPng lipid .2 17:0/20:4, (Avanti Polar Lipids), which are not present naturally in the mouse retina and have distinct and non-overlapping mass spectra compared to endogenous phosphoinositides. Phosphorylated phosphoinositides were extracted in the presence of standards containing approximately 1/5th of tissue homogenate of one mouse retina. Phosphatidylinositol profiling of retina was performed as described in [In preliminary studies, we established that due to low abundance and ion suppression, phosphorylated phosphoinositides could not be detected with shotgun lipidomics in crude lipid extracts prepared by the one-step acidified Folch method described above. Therefore, we implemented a two-step procedure allowing preparation of retinal extract enriched for phosphorylated phosphatidylinositols, but significantly depleted of other phospholipids as described . Extractribed in . The pro2 and PI(4)P sensors [Genes of interest were subcloned into a plasmid driving expression under the 2.2 kb bovine rhodopsin promoter . Constru sensors ,27,28,29 sensors . Brieflyp-values below 0.05 (p < 0.05) were considered statistically significant.Statistical analysis, including linear regression fits, was carried out using Graph Pad PRISM 8. Data are expressed as means +/- standard deviation. Moreover, 2, respectively P2  and detection of eluted ions by suppressed conductivity . A typicectively a, arrowsectively b. In theIP2 c.2 standards, we established the linearity of this method in a range from 50 to 800 pmol P, so an identical amount of PIP2 yields a smaller peak than PI(4)P. This is most likely due to a higher negative charge of PIP2, which requires higher concentrations of NaOH for elution and a higher extent of ion suppression for detection. In pilot studies, we found significant variability in the handling of phosphoinositides under 25 pmol; therefore, we aimed our subsequent measurements at around 100 pmol. The absolute amounts of PI(4)P and PIP2 extracted from one mouse retina under optimized extraction and delipidation protocols approached ~150 pmol per retina P and PIP800 pmol d. We notr retina e. This mted mice f. These 2 upon their delipidation. Therefore, we complemented phosphoinositide profiling with shotgun lipidomics and high-resolution mass spectrometry. This method allows the identification of lipid species by accurate mass measurements and the identification of the acyl composition of phospholipids by fragmentation.One limitation of the conductivity detection method is a loss of information about the fatty acid composition of PI(4)P and PIPIn the first set of experiments, we looked at the fatty acid composition of retinal phosphatidylinositols, the precursors of phosphorylated phosphoinositides. The phosphatidylinositol profile was dominated by two species containing arachidonic acid: PI 18:0/20:4 (PI 38:4) and PI 16:0/20:4 (PI 36:4) (2 18:0/20:4 (PIP2 38:4) as standards, we confirmed that these species are detected as single ions in negative mode P 37:4 and PIP2 37:4), we established the linearity of this method and a detection limit as low as 10 pmol P 18:0/20:4 (PIP 38:4) and PIPive mode c. This i 10 pmol e.2 (blue), confirming the results of electroconductivity studies described above. Third, we estimated that phosphorylated inositides account for ~7% of total phosphatidylinositols containing 38:4/36:4 acyls. Finally, we observed that the ratio of 38:4 to 36:4 acyl species is essentially unaffected by the status of inositol phosphorylation.Our analysis of the phosphoinositide composition of the mouse retina is summarized in 2 and PI(4)P into mouse rods by in vivo electroporation. Previous studies had reported light-dependent changes in the levels of these phosphoinositides [In the final set of experiments, we investigated the localization of phosphoinositides in rod photoreceptors. This was accomplished by delivering constructs encoding GFP sensors of PIPositides  and theiositides  and enzyositides ,17,35,362, PLCδ1PH-GFP, was found mostly outside ofouter segments, with an intense labeling of the inner segments and synapses Psynapses a. Localiapses P as the major phosphorylated phosphatidylinositols in the mouse retina. The levels of PIP2 and PI(4)P are comparable, and a mouse retina contains approximately 150 pmol of each lipid. This number most likely represents a low-end estimate due to less than 100% efficiency of lipid extraction from the tissue.Using chromatography of delipidated phosphoinositide headgroups, we have established PP2 in rod outer segments P and PIPiewed in ). Howeveby light  and implby light . In contin vitro . Unfortu2, PIP2, PIP3, were below our detection limit, indicating that their retinal content lies somewhere below single picomolar levels. Although they were not detected here, they are most likely present in the retina and may play significant roles in retinal health. Consistent with this notion, inactivation of enzymes handling PI(3)P was reported to result in defects in mouse photoreceptors and bipolar cells [The contents of other phosphoinositides, PI(3)P, PI(5)P, PIPar cells ,8,40. Fuar cells , will be2 36:4/38:4), which account for ~7% of total retinal phosphatidylinositol. The predominance of arachidonic acid-containing PI(4)P and PIP2 species is largely consistent with phosphoinositide profiles of mammalian membranes and neuronal tissues [Using mass spectrometry-based lipidomics, we found that at least 82% of the total phosphatidylinositide pool in the mouse retina is represented by arachidonic acid-containing species, PI 38:4, and PI 36:4. The same acyl composition was identified for mono- and bisphosphate phosphorylated forms P within rod photoreceptors. The main difference in the subcellular distribution of these phosphoinositide species is that PI(4)P was present in the light-sensitive outer segment, whereas PIP2 was mostly excluded from this compartment. This observation is consistent with a previous study, which reported the presence of PI(4)P but not PIP2 in membranes of bovine outer segments [2 sensor but not the PI(4)P sensor in photoreceptor synapses. The latter is consistent with zebrafish studies demonstrating the critical role of SynJ1 (a phosphatase regulating the levels of 5-phosphate-containing phosphoinositides) in the synapses of photoreceptors [2 in rods. Notably, our overexpression experiments did not reveal dramatic rearrangements of sensors under dark/light conditions. However, we cannot exclude the possibility that this approach is not sensitive enough to detect small light-dependent rearrangements. The development of stable transgenic mice expressing sensors at controlled levels and recent advances in high-resolution microscopy will permit a more rigorous assessment of the role of PI(4)P and PIP2 as key players in inositide signaling in the retina.Finally, we used genetic phosphoinositide sensors to infer the subcellular location of PI4,5)Psegments . We alsoPsegmentseceptors . Admitteeceptors ,45. Sens2 as predominant phosphoinositide species in the mouse retina and describes subcellular distribution patterns of these lipids in rod photoreceptors. Combined with reports linking mutations in enzymes controlling levels of phosphoinositides phosphorylated at the fifth position with retinal disorders in humans [2 lipids in the retina. Phosphatidylinositol can be phosphorylated combinatorially on three positions, producing seven distinct forms of phosphoinositides. Our study establishes PI(4)P and PIPn humans ,10,46, t2 in this tissue and, most importantly in photoreceptors. It would also be interesting to use nonradioactive methods of phosphoinositide detection to compare the phosphoinositide composition of mouse and human retinas. Another future goal is to address whether pathological changes in the levels and distribution of phosphoinositides contribute to blindness in diseases that are not directly caused by disruptions of phosphoinositide metabolism, such as retinitis pigmentosa or syndromic ciliopathies [The goal of future studies is to establish which phosphoinositide kinases and phosphatases are critical for maintaining the levels of PI(4)P and PIPopathies ,50,51,52


Regularly assessing the health and function of older adults who are in the hospital is important for preventing poor outcomes. Such information may also be useful in post-acute care settings, such as skilled nursing facilities (SNFs) to identify older adults who are high risk for poor outcomes. This study had two objectives: Map items from the Acute Care for the Elderly (ACE) Tracker to items from the Minimum Data Set (MDS). (2) Examine the association between ACE Tracker items and improvement in activities of daily living (ADLs) during a SNF stay. We identified Medicare fee-for-service beneficiaries admitted to a SNF within 3 days of hospital discharge for a hip fracture , joint replacement , or stroke . Items from the ACE Tracker were matched to patients’ first MDS assessment. The first and last MDS assessments were used to calculate a total score for self-performance on seven ADLs. Multivariable logistic regression models were used to identify patient characteristics associated with the odds for improvement in ADL function. Severe ADL limitations at admission and greater hours of physical and occupational therapy were associated with significantly higher odds of ADL improvement. Cognitive impairment, vision limitations, indwelling catheters, and unhealed pressure ulcers were associated with significantly lower odds of ADL improvement. The characteristics associated with improved ADL function were similar between patients with joint replacement, hip fracture, and stroke. Many of the health and functional characteristics routinely measured in hospital settings are also collected in SNFs and are associated with improvement in ADL function.


Accumulating evidence points to a relationship between hearing function and cognitive ability in later life. However, the exact mechanisms of this relationship are still unclear. This study aimed to characterise latent cognitive trajectories in recall memory and identify their association with subsequent risk of hearing impairment.We analysed data from the English Longitudinal Study of Ageing Wave 1 (2002/03) until Wave 7 (2014/15). The study population consisted of 3,615 adults aged 50+ who participated in the first wave of the English Longitudinal Study of Ageing, who had no self-reported hearing impairment in Wave 1, and who underwent a hearing test in Wave 7. Respondents were classified as having hearing impairment if they failed to hear tones quieter than 35 dB HL in the better ear.The trajectories of recall memory scores were grouped using latent class growth mixture modelling and were related to the presence of hearing impairment in Wave 7. Models estimating 1-class through 5-class recall memory trajectories were compared and the best-fitting models were 4-class trajectories. The different recall memory trajectories represent different starting points and mean of the memory scores. Compared to respondents with the highest recall memory trajectory, other trajectories were increasingly likely to develop later hearing impairment.Long-term changes in cognitive ability predict hearing impairment. Further research is required to identify the mechanisms explaining the association between cognitive trajectories and hearing impairment, as well as to determine whether intervention for maintenance of cognitive function also give benefit on hearing function among older adults. Hearing impairment has become a major concern for global health. The 2015 Global Burden of Disease estimates showed that hearing impairment was the fourth leading cause of years lived with disability (YLDs) and those YLDs increase from age 35 years to 64 years Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: No**********2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: YesReviewer #2: No**********3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: No**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: This article adds to the growing literature teasing out hearing-cognition relations in later adulthood. Unlike the majority of research in this area which focuses on hearing as a risk-factor for future cognitive decline – this study considers the opposite direction and explores cognitive decline as a predictor of future hearing impairment. This is its key contribution to the literature.The article is clearly written, the research question is justified with good rationale, and the methods relatively sound. I have the following comments to make:Introduction:Page 3, line 68: As I understand it, Kiely et al did include time-dependent measure of cognition and found incidence of cognitive impairment to be linked with higher hearing thresholds. So , yet limitations of Kiely et al remain – they used a verbally administered screen of global cognitive function (the MMSE) and so were unable to look at cognitive domains or actuals trajectories. Thus, the work of this paper provides important addition .https://doi.org/10.1093/gerona/gly268) who used cross-lagged panel regression to explore reciprocal relationship between hearing and cognition over two time points. They did not find prior cognition to predict future hearing levels. I also encourage authors to consider the findings of Lindenberger and Ghisletta 2009 Psych and Aging (https://psycnet.apa.org/record/2009-03151-001) and the earlier work of Baltes and Lindenberger  who laid the theoretical foundations for this research question.One other important study to include is Armstrong et al 2018 Journals of Gerontology , PTA>40dB (moderate) for 500-4000 Hz etc…Cognitive measures appear to be verbally administered – associations between hearing and cognition may therefore be (in part) an artefact of verbal assessment. This is a common limitation in this line of research but should be acknowledged in the discussion.Much more information on the modelling of the latent classes is needed. Are the latent classes derived from intercept and slope factors from a latent growth curve? How was variance within the classes estimated? etc...Table 1Without referring to deep into the results section it is not clear what is meant by “most advantaged”. What is the variable stratifying the sample in the columns? This should be made obvious in the table header.Please ensure consistent reporting to decimal places. (e.g. age SD reported as 7 rather than 7.0 for class 3 and class 4)Table 1 refers to wealth. Is this wealth or income? In text it appears to be referred to as income.Figure 1 and the latent classesThese are interesting, but appear to simply reflect differences in levels? Are there differences in the way these classes are changing over time?Why does the line in figures 1 for most advantaged class stop around age 85 whereas other classes lines continue to age 90? It looks like the grades of cognitive advantaged trajectories are strongly tied with age. Is this true? I would like to see mention of this on page 9-10 (lines 180-184) where a description of characteristics of each class is proved. i.e. most advantaged class has higher income, more education, more social engagement, higher levels of exercise AND is also younger, which may explain all these differences?I wonder if it would have been simpler, and just as instructive, to regress hearing impairment at wave 7 on latent factors for intercept and slope that are estimated from a latent growth curve for cognition.Table 2Am I correct in interpreting the coefficients as the log-odds as the outcome is binary? Is this effectively a logistic regression? Some readers might benefit from reporting of odds ratios.Discussion:Overall the discussion is very nicely presented.Again, I felt the manuscript would benefit from bringing stronger theoretical foundations earlier outlined by Baltes and Lindenberger. Schneider and Pichora-Fuller’s chapter in Craik and Salthouse’ Handbook of Aging and Cognition (2000) also give very thorough account of this.There is discussion of clinical perspectives and managing hearing loss. What is missing (or could at least be made more clearly) is consideration of the implications of these findings for hearing aid use. If cognitive impairment/decline/problems predict future hearing impairment, then this may presents a challenge for adjustment to new hearing aids and effective use of hearing aids among those with cognitive limitations.Reviewer #2: This study evaluates associations between classes of recall memory trajectories and hearing impairment in old age. The classes were derived from latent class growth mixture models fitted to wave 1-7 from the English Longitudinal Study of Aging, and hearing impairment was defined as the inability to hear tones quieter than 35 dH HL at wave 7.Given the way the data analyses were executed, I found it difficult to grasp what is the actual contribution of the study beyond what we already know from previous work, i.e., that memory performance and hearing impairment are correlated (at the population level) in old age. It is unclear what combination of parameters in the growth models are used to derive and define the classes, is it the level, slope, variance/covariance structure, residuals, and so forth? This information is essential for interpretation of the findings.Also, reasons and justification for the model selection is unclear to my. What is actually gained by relying on latent class modelling in the context of the data and research questions? Is a multivariate normal assumption unrealistic for some reasons? Are there any neuronal factors or data patterns that may justify the mixture assumption? To me, it seems more informative to rely on the multivariate normal assumption and simply fit a conventional growth curve model to the data using the hearing impairment as covariate determining recall level and change, unless there are some specific reasons why that model could be misleading.For matter of communicative precision I suggest that you replace “cognitive function” for “recall memory” in the title (and the rest of the manuscript).**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  13 Feb 2020Dear Reviewer,We are very pleased with the review and your efforts in giving feedback on the manuscript. Your recommendations were very useful to strengthen the article. Below you will find your comments numbered and in italic, each followed by a short description of how the comment is implemented in the revised manuscript . We have highlighted the changes within the revised manuscripts using coloured text. The number of page and paragraph in our responses refer to the revised manuscripts. We hope that we succeeded in strengthening the paper.Yours sincerely,The authorsEditor:Conceptual issues:Since there are studies available that have investigated the simultaneous change of hearing ability and recall memory, the main point to address in a revision is a stronger motivation of the study’s research question. Weak points of the study as it stands now are, firstly, the non-availability of objective hearing measurements before wave 7. Thank you for the comments. We have included the non-availability of objective hearing measurements before wave 7 in the limitation section in Discussion :“Firstly, there were no objective data on hearing at baseline. Self-reported hearing a good indicator of hearing status, but tends to under-identify cases of hearing impairment [54]; so people with a hearing impairment may have been included at baseline.”Secondly, as the sample as it is set up is quite selective – limiting to respondents who participate in several waves, excluding those with subjective hearing impairment at first wave – one needs to include weights to speak of a nationally representative sample. We have included weight in the analyses and included the explanation on it in page 9, lines 196-197:“We used sampling weights for all analyses to adjust for non-response and to ensure population representativeness.”Third, I am not fully convinced by the idea to use cognitive tests to predict hearing impairment. There is an individual and societal impact of hearing impairment in terms of years lived with disability, but the impact of memory problems on years lived with disability, plus associated social and healthcare costs are much higher for memory problems.We have included the literature offering explanation on how cognitive tests predict hearing impairment in the Introduction section :“Prior studies has presented some hypotheses to explain the first mechanism, including that the declining cognitive ability results in poorer perception as it places cognitive load on perception . Another hypothesis is the presence of a common cause factor related to ageing underlying both cognitive impairment and poor hearing function [13].”We further point out the potential in looking beyond simply cognitive function when assessing older adults’ limitation. A potential of cognitive test predicting future hearing impairment is that one might propose an assessment which considering future potential to have hearing impairment for older adults who report memory problems or have cognitive impairment :“From a clinical perspective, the findings from the current study emphasise the importance of assessing auditory function for patients with cognitive impairment or dementia to identify those who are at increased risk for future hearing impairment.”Lastly, there is at the moment little hope to be able to dramatically change the course of cognitive trajectories soon – the FINGER intervention only published their results for the two-year follow-up so far, and aside from this study there is little evidence that cognitive decline can be postponed or even reversed. Further, we don’t know anything about the drug that was recently submitted for FDA approval to work against Alzheimer’s at the moment, so a medical cure is also not in immediate sight.We have included the studies looking at the interventions to postpone or reverse cognitive decline, including the FINGER study in our manuscript :“Another suggestion derivable from our findings is that older adults with hearing impairments might profit from interventions designed to prevent cognitive decline, such as physical activity [51] and the multidomain intervention  . Well-designed future studies are needed to determine whether those interventions can attenuate or prevent hearing impairment.”Methodological issues:- I agree with the methodological issues pointed out by both reviewers. I would like to ask you address them by carrying out and reporting the suggested additional analyses.We have carried out and reported the suggested additional analyses:1. We have included survey weight in our analyses.2. We have performed a bivariate analyses to compare the analytic and excluded sample.3. We have performed a correlation analysis between subjective hearing impairment and the objective hearing test at wave 7.- It seems reasonable to select people without subjective hearing impairment at t1, but I suggest to include more information on the differences between this subjective measure  and an objective hearing test.We have included the information on the differences between the analytic sample and excluded sample in Supplementary Table 1 and Methods section (page 6 lines 118-125):“Differences between the analytic sample  and excluded sample (n=726) were tested with Kruskal-Wallis one-way analysis of variance for numerical variables and ordinal chi-square tests for categorical variables as appropriates (Supplementary Table 1). There were more women than men in the analytic sample, conversely in the analytic sample (p<0.001). The excluded sample has lower episodic memory scores on average (p<0.001), lower education attainment (p<0.001), poorer (p<0.001), and older . The proportion of excluded sample with objective hearing impairment in wave 7 (26.8%) was higher than that of analytic sample (6.9).”- What is the correlation between subjective hearing impairment at wave 7 and the objective hearing test?We have performed the Spearman correlation analysis to identify the correlation between subjective hearing function and objective hearing tests at wave 7 :“The objective hearing function (as measured by the number of tones that participants heard in both ears) at wave 7 has significant correlation with the subjective hearing function  at the same wave .”- The claim to predict hearing impairment based on the cognitive trajectories more than a decade in advance needs to be substantiated by a test on the ability of the intercept of these trajectories, i.e. a time point more than a decade earlier than the hearing test, to predict hearing impairment.As we have only the longitudinal information for 14 years, we have revised the words “over the preceding decade” into “during the preceding decade” (page 4 lines 89-91).  Reviewer 1:This article adds to the growing literature teasing out hearing-cognition relations in later adulthood. Unlike the majority of research in this area which focuses on hearing as a risk-factor for future cognitive decline – this study considers the opposite direction and explores cognitive decline as a predictor of future hearing impairment. This is its key contribution to the literature.The article is clearly written, the research question is justified with good rationale, and the methods relatively sound. I have the following comments to make:Introduction:Page 3, line 68: As I understand it, Kiely et al did include time-dependent measure of cognition and found incidence of cognitive impairment to be linked with higher hearing thresholds. So, yet limitations of Kiely et al remain – they used a verbally administered screen of global cognitive function (the MMSE) and so were unable to look at cognitive domains or actuals trajectories. Thus, the work of this paper provides important addition.https://doi.org/10.1093/gerona/gly268) who used cross-lagged panel regression to explore reciprocal relationship between hearing and cognition over two time points. They did not find prior cognition to predict future hearing levels. I also encourage authors to consider the findings of Lindenberger and Ghisletta 2009 Psych and Aging (https://psycnet.apa.org/record/2009-03151-001) and the earlier work of Baltes and Lindenberger  who laid the theoretical foundations for this research question.One other important study to include is Armstrong et al 2018 Journals of Gerontology :“In relation to the possibility that declining cognitive capacity leads to hearing loss, prior study hypothesise that the declining cognitive ability results in poorer auditory perception as reduced cognitive capacity may constrain perceptual processing of stimuli . Alternatively, hearing loss and cognitive decline may be associated because of a shared common factor(s) [13]. A large amount of experimental research demonstrates that cognitive factors – including memory, attention and processing speed – are critical for ‘listening’ [17-20]. Cognitive factors also impact on performance on tests of low level auditory perception, including detection of pure tones [21]. But longitudinal evidence for declining cognitive capacity leading to hearing loss is limited. To our knowledge, only one study has shown that cognitive impairment was associated with faster declines in hearing threshold [22]. That study used data from two-waves of the Mini-Mental State Examination [23], a verbally administered screen of global cognitive function, to measure the cognitive ability. Unfortunately, the MMSE is sensitive to hearing function [24] and this susceptibility may have confounded the results. In contrast, a study using two waves of data from the Baltimore Longitudinal Study of Aging found that cognitive function in the first wave did not correlate with change in audiometrically assessed hearing function in the second wave [25]. However, those studies used data from two time points only 2 years apart which restrict potential to characterise trajectories of the cognitive function.”MethodsA self-rated hearing item has been applied to select the sample. This is appropriate as it restricts the sample to those more likely to be later identified with hearing impairment due to age related processes.The definition of audiometric defined hearing impairment used at wave 7 is also reasonable, but should be made clear that this differs from the more commonly applied PTA>25dB (mild), PTA>40dB (moderate) for 500-4000 Hz etc…We have include the use of the HearCheck Screen in the limitation section :“Thirdly, the objective measures of hearing function involved the HearCheck audiometric screener device instead of full audiometry. The accuracy of HearCheck has been established in a sample of adults a similar age to those in the cohort in this study [55]. HearCheck had 89% sensitivity and 62% specificity with respect of audiometrically tested hearing at 35 dB HL.”We have also included the reasons of using 35 dB HL at 1000 Hz and 3000 Hz as the threshold in this study :“These thresholds have been identified as being the most useful frequencies for screening for hearing impairment, indicating a level of hearing impairment such that a person would likely benefit from a hearing aid [27].”Cognitive measures appear to be verbally administered – associations between hearing and cognition may therefore be (in part) an artefact of verbal assessment. This is a common limitation in this line of research but should be acknowledged in the discussion.We have include the limitation of cognitive measures we used in this study in limitation section :“Fourth, the cognitive ability was measured using verbally administered tests. The significant relationship between the trajectories of recall memory and hearing function in this study may therefore be an artefact of verbal assessment.”Much more information on the modelling of the latent classes is needed. Are the latent classes derived from intercept and slope factors from a latent growth curve? How was variance within the classes estimated? etc.We have included the explanation of the latent class trajectory models in the Method section :“In the first phase, we built latent class trajectory models to identify trajectories of recall memory scores over 13 years. Latent class trajectory models is an extension form of finite mixture modelling, which describes the course of recall memory scores through a regression function using continuous latent growth factors [32]. We used a latent class trajectory model as it could classify respondents into distinct groups based on their response patterns so that respondents within a group are more similar than respondents between groups. The intercept represent the level of recall memory scores at baseline. The change in recall memory scores over time is accounted for by the linear and quadratic slopes of the growth factors. We calculated the posterior probabilities for each trajectory taking into account the respondents’ age (at baseline), sex, and educational level.”Table 1Without referring to deep into the results section it is not clear what is meant by “most advantaged”. What is the variable stratifying the sample in the columns? This should be made obvious in the table header.We have revised the table header to follow the name of four trajectories identified in the manuscript: the highest, 2nd, 3rd, and lowest recall memory trajectories.Please ensure consistent reporting to decimal places. (e.g. age SD reported as 7 rather than 7.0 for class 3 and class 4)We have revised the tables and make sure that the decimal places in all numbers reported are consistent.Table 1 refers to wealth. Is this wealth or income? In text it appears to be referred to as income.We have revised the word “income” into “wealth” in Table 1.Figure 1 and the latent classesThese are interesting, but appear to simply reflect differences in levels? Are there differences in the way these classes are changing over time?Yes, we have explained in Results section (page 12 lines 215-217) regarding the slopes of the different trajectories:“The highest recall memory trajectory took on a strongly curvilinear shape and showed cognitive maintenance after age 50, while the cognitive trajectory of respondents included in the lowest group showed a linear decline.”Why does the line in figures 1 for most advantaged class stop around age 85 whereas other classes lines continue to age 90? It looks like the grades of cognitive advantaged trajectories are strongly tied with age. Is this true? I would like to see mention of this on page 9-10 (lines 180-184) where a description of characteristics of each class is proved. i.e. most advantaged class has higher income, more education, more social engagement, higher levels of exercise AND is also younger, which may explain all these differences?We have provided the description of characteristics of each class in page 12 lines 219-221, including the possible effect of age:“Respondents with the highest recall memory trajectory were likely to perform better on the memory test over time, younger, to be wealthier, and better educated than those with lower recall memory trajectories.”I wonder if it would have been simpler, and just as instructive, to regress hearing impairment at wave 7 on latent factors for intercept and slope that are estimated from a latent growth curve for cognition.We have included the explanation of the latent class trajectory models in the Method section that we used latent class trajectory model as it could identify respondents into distinct groups based on their response patterns so that respondents within a group are more similar than respondents between groups. We further performed logistic regression model to identify the relationships between recall memory trajectories and the odds of having hearing impairment :“In the third phase, a logistic regression of hearing impairment on recall memory trajectories while controlling for other determinants in wave 7 was explored. The previously developed four-class trajectories were maintained.”Table 2Am I correct in interpreting the coefficients as the log-odds as the outcome is binary? Is this effectively a logistic regression? Some readers might benefit from reporting of odds ratios.We have revised the analyses and reporting the results using odds ratio .Discussion:Overall the discussion is very nicely presented.Again, I felt the manuscript would benefit from bringing stronger theoretical foundations earlier outlined by Baltes and Lindenberger. Schneider and Pichora-Fuller’s chapter in Craik and Salthouse’ Handbook of Aging and Cognition (2000) also give very thorough account of this.Thank you for the comment. We are agree with it. We have thus added the information to compliment the potential mechanisms presented in Introduction section (Page 3-4 Lines 64-85):A number of mechanisms are proposed in the literature: declining cognitive capacity leading to hearing loss, poorer hearing function causing accelerated cognitive decline [6-8], and the presence of third factors causing both types of decline . In relation to the possibility that declining cognitive capacity leads to hearing loss, prior study hypothesise that the declining cognitive ability results in poorer auditory perception as reduced cognitive capacity may constrain perceptual processing of stimuli . Alternatively, hearing loss and cognitive decline may be associated because of a shared common factor(s) [13]. A large amount of experimental research demonstrates that cognitive factors – including memory, attention and processing speed – are critical for ‘listening’ [17-20]. Cognitive factors also impact on performance on tests of low level auditory perception, including detection of pure tones [21]. But longitudinal evidence for declining cognitive capacity leading to hearing loss is limited. To our knowledge, only one study has shown that cognitive impairment was associated with faster declines in hearing threshold [22]. That study used data from two-waves of the Mini-Mental State Examination [23], a verbally administered screen of global cognitive function, to measure the cognitive ability. Unfortunately, the MMSE is sensitive to hearing function [24] and this susceptibility may have confounded the results. In contrast, a study using two waves of data from the Baltimore Longitudinal Study of Aging found that cognitive function in the first wave did not correlate with change in audiometrically assessed hearing function in the second wave [25]. However, those studies used data from two time points only 2 years apart which restrict potential to characterise trajectories of the cognitive function.” We further explored those potential mechanisms and included the theoretical foundations in the Discussion section (page 15-16 lines 263-293):“From a theoretical perspective, this study provides the first evidence that decreased recall memory ability predicts hearing impairment. The pathways between cognition and hearing function among older adults are not well understood. One plausible mechanism of the relationship is neurobiological. Research has established the positive correlations between cognitive function and total brain volume [34-36], which may influence the functioning of auditory processes in the brain. Histopathological involvement of auditory cortices has been found in Alzheimer’s disease and other dementias [37-39]. The general process in the central auditory system includes matching new inputs with existing memory as well as experience of the auditory world with other sensory systems . In addition to the process within the auditory system, there is a cortico-cortical process that provides integration of the auditory process and other sensory systems, memory, knowledge, and decision-making processes. The neurodegenerative process may disrupt both central auditory and cortico-cortical processes, leading to deficient perception of sounds and a more cautious or impaired decision-making process. A study in the US found that auditory cortical activity as measured by P50 amplitude and P300 latency decreased with normal ageing and decreased additionally with mild cognitive impairment [42]. Another potentially relevant mechanism is a shared underlying pathology, such as vascular diseases or intrinsic cellular ageing, that leads to ageing of both the brain and the auditory organs . However, further explanation is warranted because the association between recall memory trajectories and the presence of hearing impairment in the present analyses remained after controlling for the effects of potential covariates .Finally, recent trajectories of recall memory scores could also potentially predict hearing impairment through the broader influence of cognitive ability on physical activity. Likewise, social networks could mediate the observed association of cognition and a higher probability of hearing impairment. Better cognition may facilitate physical activity [45], which in turn protects older adults against chronic diseases . The presence of chronic diseases, including stroke, diabetes, hypertension and other cardiovascular diseases, are among the risk factors for hearing impairment [28-30]. Better cognitive function is associated with richer social networks [48], and similar to physical activity, social relationships are important for good health .”There is discussion of clinical perspectives and managing hearing loss. What is missing (or could at least be made more clearly) is consideration of the implications of these findings for hearing aid use. If cognitive impairment/decline/problems predict future hearing impairment, then this may presents a challenge for adjustment to new hearing aids and effective use of hearing aids among those with cognitive limitations.We have include the implications of our findings for hearing aid use in page 17 lines 300-303:“Our findings that cognitive decline predicts future hearing impairment may also presents a challenge for adjustment to new hearing aids and effective use of hearing aids among those with cognitive limitations.” Reviewer 2:This study evaluates associations between classes of recall memory trajectories and hearing impairment in old age. The classes were derived from latent class growth mixture models fitted to wave 1-7 from the English Longitudinal Study of Aging, and hearing impairment was defined as the inability to hear tones quieter than 35 dH HL at wave 7.Given the way the data analyses were executed, I found it difficult to grasp what is the actual contribution of the study beyond what we already know from previous work, i.e., that memory performance and hearing impairment are correlated (at the population level) in old age. It is unclear what combination of parameters in the growth models are used to derive and define the classes, is it the level, slope, variance/covariance structure, residuals, and so forth? This information is essential for interpretation of the findings.We have included the explanation of the latent class trajectory models in the Method section :“In the first phase, we built latent class trajectory models to identify trajectories of recall memory scores over 13 years. Latent class trajectory models is an extension form of finite mixture modelling, which describes the course of recall memory scores through a regression function using continuous latent growth factors [32]. We used a latent class trajectory model as it could classify respondents into distinct groups based on their response patterns so that respondents within a group are more similar than respondents between groups. The intercept represent the level of recall memory scores at baseline. The change in recall memory scores over time is accounted for by the linear and quadratic slopes of the growth factors. We calculated the posterior probabilities for each trajectory taking into account the respondents’ age (at baseline), sex, and educational level.”Also, reasons and justification for the model selection is unclear to my. What is actually gained by relying on latent class modelling in the context of the data and research questions? Is a multivariate normal assumption unrealistic for some reasons? Are there any neuronal factors or data patterns that may justify the mixture assumption? To me, it seems more informative to rely on the multivariate normal assumption and simply fit a conventional growth curve model to the data using the hearing impairment as covariate determining recall level and change, unless there are some specific reasons why that model could be misleading.We used latent class trajectory model as it could identify respondents into distinct groups based on their response patterns so that respondents within a group are more similar than respondents between groups.For matter of communicative precision I suggest that you replace “cognitive function” for “recall memory” in the title (and the rest of the manuscript).We have replaced the words “cognitive function” with “recall memory” in the title and the rest of manuscript.AttachmentResponse to reviewers.docxSubmitted filename: Click here for additional data file. 24 Apr 2020PONE-D-19-29591R1Trajectories of recall memory as predictive of hearing impairment: A longitudinal cohort studyPLOS ONEDear Dr Maharani,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.We would appreciate receiving your revised manuscript by Jun 08 2020 11:59PM. When you are ready to submit your revision, log on to If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocolsTo enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. 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Olusanya, MBBS, FMCPaed, FRCPCH, PhDAcademic EditorPLOS ONE[Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: (No Response)Reviewer #3: (No Response)**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #3: Yes**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: YesReviewer #3: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #3: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #3: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: I am satisfied the authors have responded reasonably to all my prior comments, and I thank them for taking on board my suggestions. I only have the following 3 minor suggestions to make:1) Please check citation [22 – Kiely et al] which examined MMSE change over more than 2 waves of data (4 waves spanning 11 years).2) Despite being generally sceptical about GMMs I am overall happy with the methods and results as presented – but there are still details about the GMM I would like to see in supplementary table, as this would help make clear how these were estimated. For example, how was the within-class variance modelled? Was variance fixed to be constant within classes, or was it free to vary within classes? A supplementary table showing the full parameterisation of the GMM would clarify this.3) My queries about Figure 1  and comments about strong age gradient by trajectory classes were not addressed. Even though these models are adjusted for linear effects of age, I still wonder about the extent to which the substantive finding is driven by age?Reviewer #3: In ‘Trajectories of recall memory as predictive of hearing impairment: a longitudinal cohort study,’ Maharani and colleagues examine the relationship in later life between cognitive function and subsequent hearing loss. They find that individuals with lower performance on a recall memory task are significantly more likely to develop hearing loss. The manuscript is clearly written and the analysis appear carefully done. A large sample size offsets some weakness in the assessment of hearing loss, which was self reported at the study onset and based on the HearCheck screener at the final time point. The manuscript should be of interest to readers of PLOS ONE. The main significance of the work is that it provides insight into the directionality of the relationship between cognitive decline and HL .One aspect of the results that is clear from figure 1 but could be clarified more in the text, throughout the manuscript, is that different classes of memory recall trajectory differ more in their starting point or mean than in the rate of decline.A second issue that does not appear to be discussed is that the proportion of individuals with objective hearing loss in the study sample appear rather low for this age group, at 6.9%. This could be related to the requirement for HL at 500 Hz, which typically occurs later.Line 31. It seems important to clarify here that absence of hearing loss was ‘self reported’Lines 34-36. Rather than describing model selection here, it might be more useful to sketch out differences in the identified trajectories including different starting points.Line 49. Remove ‘the’ after ‘1989’.Line 113. Do the authors have information on which individuals used hearing aids? It seems like they should be excluded if possible since the objective hearing screening was likely not performed with a hearing aid.Line 160. Please clarify what how moderate and vigorous exercise were distinguished. Was there a different question for each?Line 194. Please clarify that this was a second analysis.Line 209. It would helpful to have something at the top of the table indicating that ‘Highest’, ‘2nd', etc. refers to the recall trajectory. A header may be missing over ‘Drinking regularly’ since this is not a ‘Smoking Behavior’.Line 215. Here is where it would be good to describe the difference in the intercepts/starting points.Line 217. The decline does not appear ‘linear’ in Fig. 1.Line 238. It would help to indicate the difference between the two columns at the top of the table, i.e., to somehow indicate that the right column includes the recall trajectory. Also, the meaning of the symbols (presumably related to significance) appears to be missing. Finally, the confidence interval for ‘vigorous physical activity’ contains 1 but is marked as significant. Please clarify.Line 255. Noting the different intercepts for the various trajectories would be helpful here. Again, the decline does not appear ‘linear’.**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  25 May 2020Dear Reviewer,We are very pleased with the review and your efforts in giving feedback on the manuscript. Your recommendations were very useful to strengthen the article. Below you will find your comments numbered and in italic, each followed by a short description of how the comment is implemented in the revised manuscript . We have highlighted the changes within the revised manuscripts using coloured text. The number of page and paragraph in our responses refer to the revised manuscripts. We hope that we succeeded in strengthening the paper.Yours sincerely,The authorsReviewer 1:I am satisfied the authors have responded reasonably to all my prior comments, and I thank them for taking on board my suggestions. I only have the following 3 minor suggestions to make:1) Please check citation [22 – Kiely et al] which examined MMSE change over more than 2 waves of data (4 waves spanning 11 years).We have revised the citation in the Page 4 lines 79:‘To our knowledge, only one study has shown that cognitive impairment was associated with faster declines in hearing threshold [22]. That study used data from four waves spanning 11 years of the Mini-Mental State Examination, a verbally administered screen of global cognitive function, to measure the cognitive ability [22].’2) Despite being generally sceptical about GMMs I am overall happy with the methods and results as presented – but there are still details about the GMM I would like to see in supplementary table, as this would help make clear how these were estimated. For example, how was the within-class variance modelled? Was variance fixed to be constant within classes, or was it free to vary within classes? A supplementary table showing the full parameterisation of the GMM would clarify this.In our analysis, we performed latent class growth analysis, in which the variance and covariance estimates for the growth factors within each class are assumed to be fixed to zero. By this assumption, all respondents’ growth trajectories within a class are homogenous. We provide the regression parameters of the latent class models in Supplementary Table 2.3) My queries about Figure 1  and comments about strong age gradient by trajectory classes were not addressed. Even though these models are adjusted for linear effects of age, I still wonder about the extent to which the substantive finding is driven by age?We have added the explanation on Figure 1 in Page 12 lines 220-222:‘The trajectory of recall memory among the respondents in the highest recall memory group ends at 86 as they are younger than other age groups. The oldest respondent in that group was aged 86 in the final wave.’ Reviewer 3In ‘Trajectories of recall memory as predictive of hearing impairment: a longitudinal cohort study,’ Maharani and colleagues examine the relationship in later life between cognitive function and subsequent hearing loss. They find that individuals with lower performance on a recall memory task are significantly more likely to develop hearing loss. The manuscript is clearly written and the analysis appear carefully done. A large sample size offsets some weakness in the assessment of hearing loss, which was self-reported at the study onset and based on the HearCheck screener at the final time point. The manuscript should be of interest to readers of PLOS ONE. The main significance of the work is that it provides insight into the directionality of the relationship between cognitive decline and HL .1. One aspect of the results that is clear from figure 1 but could be clarified more in the text, throughout the manuscript, is that different classes of memory recall trajectory differ more in their starting point or mean than in the rate of decline.We have added the explanation on Figure 1 in Page 12 lines 219-220:‘The recall memory trajectories in Figure 1 differ in the intercepts and mean of the memory scores.’2. A second issue that does not appear to be discussed is that the proportion of individuals with objective hearing loss in the study sample appear rather low for this age group, at 6.9%. This could be related to the requirement for HL at 500 Hz, which typically occurs later.We have added the discussion on the low prevalence of objective hearing impairment in Page 17-18 lines 320-329:‘The proportion of the respondents with objective hearing impairment included in this study was lower for the age group (6.9%). Prior studies using national samples showed that the prevalence of hearing impairment among adults aged 50 years and older ranges from 20 to 40% [55]. The definition of hearing loss in this study was not the usual four frequency average of thresholds at 500, 1000, 2000 and 4000 Hz. It was performance on a pure tone audiometry screen with hearing loss equivalent to better ear threshold >35 dB HL at 1000 or 3000 Hz. Hearing loss usually appears first at higher frequencies, so including lower frequencies in an average hearing loss may make the hearing loss index less sensitive to early hearing loss. The 3000 Hz criterion for our hearing loss measure should make it reasonably sensitive to early hearing loss.’3. Line 31. It seems important to clarify here that absence of hearing loss was ‘self-reported’We have revised the sentence in Page 2 line 31 into:‘The study population consisted of 3,615 adults aged 50+ who participated in the first wave of the English Longitudinal Study of Ageing, who had no self-reported hearing impairment in Wave 1, and who underwent a hearing test in Wave 7.’4. Lines 34-36. Rather than describing model selection here, it might be more useful to sketch out differences in the identified trajectories including different starting points.We have added the explanation in the Page 2 lines 37-38:‘The different recall memory trajectories represent different starting points and mean of the memory scores.’5. Line 49. Remove ‘the’ after ‘1989’.We have removed the word ‘the’ after ‘1989’ in Page 3 line 50.6. Line 113. Do the authors have information on which individuals used hearing aids? It seems like they should be excluded if possible since the objective hearing screening was likely not performed with a hearing aid.We are interested in hearing impairment (pathology) indexed by pure tone audiometry test, not functional hearing. There is thus no basis for removing hearing aid users in our study. Excluding hearing aid users would exclude a high proportion of people with audiometric hearing loss, and reduce sensitivity of the analysis. 7. Line 160. Please clarify what how moderate and vigorous exercise were distinguished. Was there a different question for each?We have included the explanation on Page 7 lines 162-164:‘We categorised respondents as engaging in moderate and vigorous physical exercise if they reported exercising as least once a week. The respondents responded to the questions whether they take part in sports or activities that are vigorous and moderately energetic, respectively.’8. Line 194. Please clarify that this was a second analysis.We have clarified in Page 9 line 196 that the analysis was the second analysis.9. Line 209. It would helpful to have something at the top of the table indicating that ‘Highest’, ‘2nd', etc. refers to the recall trajectory. A header may be missing over ‘Drinking regularly’ since this is not a ‘Smoking Behavior’.We have revised the top of Table 1 and included ‘recall memory’ to better explain the recall trajectory. We have also included the header ‘Drinking behaviour’ in the Table.10. Line 215. Here is where it would be good to describe the difference in the intercepts/starting points.We have added the explanation about the difference in intercepts in the Page 2 lines 37-38:‘The different recall memory trajectories represent different intercepts and mean of the memory scores.’11. Line 217. The decline does not appear ‘linear’ in Fig. 1.We have removed the sentence in Page 12 line 219.12. Line 238. It would help to indicate the difference between the two columns at the top of the table, i.e., to somehow indicate that the right column includes the recall trajectory. Also, the meaning of the symbols (presumably related to significance) appears to be missing. Finally, the confidence interval for ‘vigorous physical activity’ contains 1 but is marked as significant. Please clarify.We have included the information on the different models presented in Table 2, added the information of the symbols and revised the significance for ‘vigorous physical activity’.13. Line 255. Noting the different intercepts for the various trajectories would be helpful here. Again, the decline does not appear ‘linear’.We have rewritten the sentence in Page 15 lines 257-259:‘Supporting prior research [33], we identified the highest recall memory trajectory and the lowest recall memory trajectory over time.’AttachmentResponse to reviewers2_v(2).docxSubmitted filename: Click here for additional data file. 1 Jun 2020Trajectories of recall memory as predictive of hearing impairment: A longitudinal cohort studyPONE-D-19-29591R2Dear Dr. Maharani,We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.Within one week, you will receive an e-mail containing information on the amendments required prior to publication. 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Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact With kind regards,Bolajoko O. Olusanya, MBBS, FMCPaed, FRCPCH, PhDAcademic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments: 9 Jun 2020PONE-D-19-29591R2 Trajectories of recall memory as predictive of hearing impairment: A longitudinal cohort study Dear Dr. Maharani:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. 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P =0 .0011; Cochran-Armitage test). After the first episode of SSNHL, the recurrence-free rate was 69.9% over 1 year and 57.7% over 2 years; the median recurrence time was 32 months. Logarithmic approximation revealed that there is a 25% probability that SSNHL would recur within a year. SSNHL in patients with VS is likely to recur within one year in 25% of cases. Also, recovery rate decreases as a patient experiences increasing episodes of SSNHL.Clinical features of sudden sensorineural hearing loss (SSNHL) associated with vestibular schwannoma (VS) are not fully understood. Determining a treatment plan and explaining it to patients requires clinicians to clearly understand the clinical features related to the tumor, including SSNHL. To identify the full range of clinical features of VS-associated SSNHL, especially recovery of hearing following multiple episodes of SSNHL and what factors predict recovery and recurrence. A multicenter retrospective chart review was conducted in seven tertiary care hospitals between April 1, 2011, and March 31, 2020. We collected and analyzed dose of administered steroid, pure-tone audiometry results, and brain MRIs of patients diagnosed with VS-associated SSNHL. Seventy-seven patients were included. They experienced 109 episodes of audiogram-confirmed SSNHL. The highest proportion of complete recoveries occurred in patients with U-shaped audiograms. The recovery rates for the first, second, and third and subsequent episodes of SSNHL were 53.5%, 28.0%, and 9.1%, respectively. Recovery rate decreased significantly with increasing number of SSNHL episodes ( An estimated 12 to 26% of patients diagnosed with VS develop sudden sensorineural hearing loss (SSNHL)3. Sporadic VSs are often treated with corticosteroids according to treatment protocols used for idiopathic SSNHL6. Although SSNHL is a common symptom of VS, little information exists about the extent to which this symptom resolves and about its recurrence rate. Also, previous studies have generally had few available patients for study6 and some patients with VS-associated SSNHL have one or more additional episodes after initial hearing recovery7.Sporadic vestibular schwannoma (VS) accounts for approximately 80% of cerebellopontine angle tumors8. We hypothesized that the detailed clinical features of VS associated SSNHL would contribute to the decision of surgeons and even patients.From published reports, it is difficult to determine the detailed clinical characteristics of VS-associated SSNHL, the efficacy of a particular plan of treatment, and the long-term status and progression of hearing loss and recovery, as only a small number of cases were analyzed in these studies. Regardless, the detailed clinical features of the first episode of VS-associated SSNHL sufferers has not been sufficiently studied. Other questions also arise: Does recovery rate of VS-associated SSNHL change over time? Is recovery rate related to tumor grade? Is recovery rate related to dosage of steroids administered? Answers to these questions are important, as the indication for surgery of VSs remains controversialIn the present study, we conducted a retrospective chart review of a relatively large sample of VS patients with SSNHL. Seven general tertiary-level hospitals in Japan contributed data to the analysis, with the goal of clarifying the detailed clinical features of VS-associated SSNHL and of determining the recovery rate and recurrence rate.We conducted a retrospective chart review of the patients who developed SSNHL between April 1, 2011, and March 31, 2020, on April 2020 as part of the Keio Academical Otolaryngology Research Unit (KAORU) Project. Participating hospitals in this project are Keio University, National Hospital Organization Tokyo Medical Center, Saiseikai Utsunomiya Hospital, Hiratsuka City Hospital, Japanese Red Cross Shizuoka Hospital, Hino Municipal Hospital, and Inagi Municipal Hospital. This study was approved by the institutional review boards of Keio University School of Medicine Ethics Committee , National Hospital Organization Tokyo Medical Center , Saiseikai Utsunomiya Hospital , Japanese Red Cross Shizuoka Hospital , Inagi Municipal Hospital (dated 23/06/2020), Hiratsuka City Hospital , and Hino Municipal Hospital IRB (dated 24/03/2021). The requirement of written informed consent was waived because of the study’s retrospective design. We defined SSNHL as follows: “The patient is aware of sudden hearing loss, and the patient’s hearing thresholds measured through audiometry testing at 0.25, 0.5, 1, 2, or 4 kHz are increased in one or more frequencies by more than 20 dB.” All candidate patients for this study were being treated with corticosteroids.known VS, and (2) cases of SSNHL that were identified first, followed soon after by a diagnosis of VS. All candidate participants had accompanying audiograms; we excluded cases in which onset of SSNHL was not verified by pure-tone audiometry testing. From every included patient, we gathered and analyzed their chart data on the dose of oral or intravenous steroid administered, their audiogram results, their MRI images related to the VS diagnosis, and the number and timing of recovery and recurrences.We included two kinds of patients presenting with SSNHL: (1) cases of SSNHL in the patients with 9. According to these criteria, hearing severity is categorized into four grades based on hearing thresholds measured with pure-tone audiometry at 0.25, 0.5, 1, 2, and 4 kHz: Grade 1, mean hearing level  is < 40 dB; Grade 2, mean hearing level is ≥ 40 dB but < 60 dB; Grade 3, mean hearing level is ≥ 60 dB but < 90 dB; and Grade 4, mean hearing level is ≥ 90 dB9.The severity classification of SSNHL was defined based on criteria of the Japan Ministry of Health, Labor and Welfare research group9; there were some minor modifications done for this study. First, the mean hearing threshold of each patient was calculated based on thresholds measured at five test frequencies . We used these results to categorize hearing improvement as “complete recovery,” “marked improvement,” “partial improvement,” or “no change”9. The patient’s hearing was considered to be completely recovered for the following three types of audiogram results: (1) if his/her mean hearing threshold was ≤ 20 dB; (2) in cases where hearing threshold on the affected side before onset was known, the mean hearing threshold recovered to within 10 dB of their pre-onset hearing level; (3) in cases where the mean hearing thresholds of the affected and unaffected sides were equivalent before onset, the hearing threshold of the affected side recovered to within 10 dB of the healthy side’s hearing level; (4) in cases with dip form, the hearing threshold of affected frequency recovered to within 10dB of the pre-onset or healthy side's hearing level. A patient was considered to have marked improvement in hearing when the average of the hearing levels measured at the five frequencies improved by ≥ 30 dB. A patient was considered to have partial improvement in hearing when the average hearing level was ≥ 10 dB but < 30 dB. A patient’s hearing outcome was designated as no change when the average hearing improved < 10 dB. Treatment outcome was assessed one or more months after onset of SSNHL by performing audiograms, and a judgment was made using the audiogram after there was no further improvement. We defined recovery rate as the percentage of patients who achieved complete recovery.Our criteria for judging treatment outcome  was also based on the criteria of the Japan Ministry of Health, Labor and Welfare research group for measuring hearing improvement after recovering from SSNHL10, we also evaluated the shape of each patient’s audiograms. The audiogram shapes were defined according to the following characteristics.Since we were interested in whether the configuration of hearing loss  could be a prognostics indicator of recovery rate or recurrenceA–G in audiogram forms 1–7:Reference points A Hearing threshold assessed at 0.125 kHz: B Hearing threshold assessed at 0.25 kHz: C Hearing threshold assessed at 0.5 kHz: D Hearing threshold assessed at 1 kHz: E Hearing threshold assessed at 2 kHz: F Hearing threshold assessed at 4 kHz: GLow-frequency, ascending form:A + B + C) ÷ 3] – [(D + E + F + G) ÷ 4] > 15 dB.[ - (Poorest in A and B) > 15 dB. - (Poorest in F and G) > 15 dB.and (Poorest in High-frequency descending form:F + G) ÷ 2] – [(D + E) ÷ 2] > 15 dB.[(Flat form:B + C) ÷ 2], [(D + E) ÷ 2], and [(F + G) ÷ 2] is < 15 dB.The difference between  at onset of the first episode of SSNHL was significantly younger than that in the survey on idiopathic SSNHL , and the highest proportion of patients in the survey study was in the 60–69 year age range20.In that survey, the recovery rate was 41.2% (1317/3194), while in our study the recovery rate for the first episode of SSNHL was 53.5% (38/71). Although the recovery rate in our study was not markedly different from that in the survey on idiopathic SSNHL, it did tend to be higher than that in the survey study (21. One study reported that 10.9% (90/828) of patients with idiopathic SSNHL exhibit trough-shaped audiograms , a shape that predicts likely hearing recovery22. In the present study, 41.1% (30/73) of patients exhibited the equivalent of the trough-type audiograms; this was a significantly higher percentage than that in the aforementioned report . Taken together, these data indicate that otolaryngologists need to consider VS screening mainly for relatively young patients, even if their hearing loss completely recovers. Recovery of hearing is highly probable, especially in patients that exhibit U-shaped form and dip-shaped form of audiograms.Recovery of hearing in patients with idiopathic sudden hearing loss has been associated with the shape of the patient’s audiogramP = 0.030) between VS tumor growth and recurrence of hearing loss—it is important to continuously assess hearing levels after the first presentation of SSNHL. In addition, repeated imaging in these patients should be judiciously conducted in order to detect possible explanations for clinical changes in patients that might be related to VS growth. A similar conclusion was reached by Lee et al.23.Since we found no clear relationships between MRI findings and hearing-related clinical course in VS patients—except for a modest connection (25, surgery in these patients might be favorably considered before recurrence of hearing loss, even if the patient’s first episode of SSNHL has resolved completely.Kaplan–Meier survival analyses were useful in understanding the detailed clinical features of VS-associated SSNHL. Our logarithmic approximation analyses indicated that in our cohort, SSNHL recurred at a rate of 25% per year and that the recovery rate for the second and subsequent episodes of hearing loss was significantly lower than that for the first episode. Therefore, in VS patients choosing the treatment option of “wait and scan,” it is necessary to inform those with SSNHL that hearing loss may recur. As the success rate of hearing-preservation surgery is improving with recent improvements in surgical procedures and advances in intraoperative hearing monitoring26, we could not assess speech audiometry data in this study. Since speech audiometry is not routinely performed during the follow-up of individuals having a differential diagnosis of idiopathic SSNHL, we were unable to collect enough speech audiometry data for analysis.Although the present study was the largest to date on VS-associated SSNHL cases and the first to elucidate the pattern of recurrence of SSNHL in this patient population, it has some limitations. First, this was a retrospective study, and as such, not all patients who presented with SSNHL underwent imaging tests. In Japan, MRIs are often performed on patients whose hearing loss has not recovered, not on patients who present with no hearing loss. So, there is a possibility that these latter kinds of patients, who have not been imaged, may indeed have a VS. Therefore, the actual recovery rate of SSNHL caused by VS may be higher. Second, although speech audiometry is commonly used as a follow-up test for VSWe found that the recovery rate of VS-associated SSNHL decreases with increasing episodes of hearing loss. This, together with our finding that SSNHL recur within one year in 25% of cases, should prompt otolaryngologists and neurosurgeons to follow up on the hearing status of VS patients in addition to monitoring VS status with MRI. Alternatively, as the success rate of hearing-preservation surgery has improved greatly in recent years, VS patients choosing to wait and scan might consider undergoing surgery before hearing loss recurs.


In this study, the color of the dry fruiting bodies, fresh weight (FW): dry weight (DW) ratio, amino acids, and total phenolics, which are of nutritional or commercial interest, were compared among different drying temperature treatments. The effect of rehydration methods and color protection reagents on the fruiting body color, polyphenol oxidase (PPO) activity, and browning inhibition rate were evaluated. The results showed that drying with hot air at 65℃ was quickest and resulted in a better color without compromising the FW:DW ratio and rehydration ratio of the fruiting bodies. Furthermore, some reactions that occurred under high temperatures increased the content of protein, amino acids, and total phenolics. Soaking after boiling was the most suitable rehydration method, leading to the lowest PPO activity (39.87 ± 1.35 U/g). All of the four analyzed color protection reagents could significantly inhibit the browning of Yu Muer fruiting bodies under room temperature water rehydration conditions, with a citric acid content of 6 g/L showing the best performance. These results provide technical support for the development of the Yu Muer industry and for promoting the commercial processing of Yu Muer fruiting bodies slices. The drying with hot air at 65℃ was quickest and resulted in a better color without compromising the drying ratio and rehydration ratio of the fruiting bodies. Soaking after boiling was the most suitable rehydration method, leading to the lowest PPO activity (39.87 ± 1.35 U/g). All of the four analyzed color protection reagents could significantly inhibit the browning of Yu Muer fruiting bodies under room temperature water rehydration conditions, with a citric acid content of 6 g/L showing the best performance. Yu Muer) is a new white variety of edible fungus that was selected from a mutant of Auricularia cornea by the Engineering Research Center of the Ministry of Education, Jilin Agricultural University. Yu Muer is in genus Auricularia, family Auriculariaceae, order Auriculariales, class Agaricomycetes, and phylum Basidiomycota. It is an edible fungus and is also used in medicine , oyster mushroom (Pleurotus ostreatus), and Agaricus bisporus, as well as wild mushrooms such as Macrolepiota procera , and honey fungus (Armillaria mellea) . PPO is the key enzyme causing browning in agricultural products , citric acid, sodium ascorbate, and L‐cysteine. Ascorbic acid exists widely in fresh fruits and vegetables and is a Generally Regarded As Safe (GRAS) substance that can be utilized in the preservation of In our study, fresh Yu Muer was processed by HD. Their change in commercial properties, such as color and wet‐to‐dry ratio, and their nutritional composition, such as amino acids, total phenolics, and proteins, were compared under different drying temperatures, and suitable drying temperature for the processing of Yu Muer fruiting bodies was screened. Furthermore, the combinations of Yu Muer fruiting bodies rehydration methods and color protection agents were tested and optimized. Our study provides a theoretical basis and practical reference for improving the drying process, marketability of the fresh products, cold chain transportation, and shelf life of Yu Muer. It may also provide a new technical approach for the rehydration processing of dried Yu Muer fruiting bodies.22.1Fresh Yu Muer fruiting bodies were collected from the Fungus and Vegetable Base, Jilin Agricultural University . Test kits for determining PPO, amino acid (AA) content, plant total phenolics, protein content (BCA assay), and total sugar content were purchased from Suzhou Keming Biotechnology Co., Ltd. Sodium erythorbate and L‐cysteine were purchased from Beijing Solarbio Science and Technology Co., Ltd. Ascorbic acid was purchased from Shanghai Yuanye Biotechnology Co., Ltd. Citric acid was purchased from Tianjin Fuchen Chemical Reagent Factory.2.2The following instruments were used in the study: Furuite 770C Fruit and Vegetable Dryer , Spectramax i3x Multi‐Function Microplate Reader , Legend Micro21R Benchtop Microcentrifuge , Baijie‐100 high‐speed multifunction pulverizer , and ColorFlex 45/0 spectrophotometer .2.32 levels were maintained at less than 1,200 ppm. Mature fruiting bodies of 4–5 cm, thickness of fruiting bodies is 0.1–0.2 cm and with white spores on the ventral surface were collected.Indoor cultivation was used to produce the Yu Muer fungus. The spawn running period was conducted at a temperature of 24–26℃ and relative air humidity of 30%–40%. During collection, the temperature was maintained at 20–25℃, and the humidity was at 85%–90%.Furthermore, CO2.4SD: Fresh fruiting bodies were evenly spread in a single layer on a drying net. The temperature was 20–35℃. The fruiting bodies were naturally dried until a constant weight was reached.2) on the trays. They were respectively dried at 35, 45, 55, and 65 ℃ in the dryer until they reached a constant weight.HD at constant temperature: The fresh fruiting bodies were spread in a single layer  soaking in room temperature water for 5 hr, 2) soaking in boiling water for 5 hr, or 3) boiling in water for 10 min and then soaking for 5 hr.Calculation of water loss ratio: The weight of the fruiting bodies under different drying temperatures was recorded every 0.5 hr. The water loss ratio was calculated by the following equation according to the published method , a* , and b*  values of the samples were measured. The calculation of ΔE followed the method reported by Ref.; 45℃ (8 hr), 55℃ (7 hr), and 65℃ (5 hr). Drying was completed at all of the HD temperatures within 12 hr, which is significantly shorter than the drying time needed for outdoor SD. Drying at 65℃ took 5 hr, which was only half of the time required by drying at 35 ℃. This method not only realizes the completion of drying and packaging on the same day, but also efficiently utilizes the drying equipment, increases the working efficiency, and reduces labor costs.3.2The dry fruiting bodies subjected to 65℃ HD for 5 hr were used to compare the different rehydration methods. During the room temperature, water rehydration process, the fruiting bodies exhibited browning, becoming a reddish brown to black color. Previous studies have shown that the PPO causes this browning in the fruiting bodies. We determined the PPO activity of the fruiting bodies that were rehydrated using different methods. Also, to explore whether the oxygen in the air affected the oxidation of the fruiting bodies, we compared the difference between film‐wrapped and unwrapped fruiting bodies.We found that wrapping did not prevent the oxidation reaction of the fruiting bodies, but was able to reduce browning to some extent. Among the three rehydration methods, boiling for 10 min and then soaking for 5 hr resulted in the best fruiting body color. Soaking in boiling water did not avoid browning. The fruiting bodies soaked in water at room temperature were dark reddish, brown, or black. The PPO activity in these fruiting bodies was the highest and was significantly higher than that of the other treatments regardless of whether they were wrapped or not. The order of PPO activity was: soaking at room temperature water >boiling >boiling and then soaking (Table 3.3L* (lightness and darkness), a* (red and green), and b* (yellow and blue) values of the dry fruiting bodies showed irregular changes, and the dry fruiting bodies obtained by HD at four different temperatures showed significant differences in chromaticity. The △E value of the fruiting bodies dried at 35 and 45 ℃ was significantly lower than that of the other treatments, and the color was the closest to that of SD, though the drying took longer. For the fruiting bodies dried at 65℃, the L* value was the highest, representing the highest brightness, and the a* value was the lowest, indicating a small redness, which suggests that the fruiting bodies had good color  and the lowest △E, indicating that the color of the latter was similar to that of the fresh fruiting bodies, which meets market requirements  is a typical drying method that is widely used for processing cultivated edible fungi , essential oils, and high‐pressure carbon dioxide (HPCD), could also be adapted to inhibit the PPO reaction (Alikhani‐Koupaei, Mazlumzadeh, Sharifani, & Adibian, Through the analysis of the main nutrients of the dry products processed by different drying methods, we found the highest amino acid content in the fruiting bodies dried at 65℃ and the lowest seen in the fruiting bodies dried at 45℃ Figure . This phYu Muer fruiting bodies were white, and this was most important commodity character. Developing appropriate rehydration methods and screening chemical agents for protecting color during rehydration in the water at room temperature is essential in the development of the Yu Muer industry. In this study, we found the 6 g/L citric acid has the highest browning inhibition rate Figure . We thusIn conclusion, through the comparative analysis of HD and SD methods, we found that HD at 65℃ could significantly shorten the drying time of the Yu Muer fruiting bodies. This treatment did not affect the FW:DW ratio and rehydration ratio; the dried and rehydrated fruiting bodies demonstrated better color, and the main nutrients were slightly higher than the fruiting bodies subjected to SD. Soaking after boiling was the most suitable method for rehydration, which could significantly inhibit PPO activity. Four‐color protection reagents were screened, and the suitable concentrations were as follows: 1.6 g/L sodium erythorbate, 1.6 g/L ascorbic acid, 2 g/L L‐cysteine, and 6 g/L citric acid, of which 6 g/L citric acid had the highest browning inhibition rate. Application of high‐temperature HD and color protection reagents during rehydration in the water at room temperature may facilitate the development of the Yu Muer industry.The authors declare that they have no conflict of interest.CTL, BS, and YL acquired funding; YQC conceptualized the research project; LX investigated; YQC, ZWL, FLS, and ZRL performed the experiments; analyzed the data; and drafted the manuscript; YQC and BS curated the data and edited the manuscript.This article does not contain any studies with animals or human participants performed by any of the authors.Informed consent was obtained from all individual participants included in the study.Table S1Click here for additional data file.