Group ICA (GICA) and Independent Vector Analysis (IVA) are extensions of ICA that enable users to perform group fMRI analyses; however a full comparison of the performance limits of GICA and IVA has not been investigated. Recent interest in resting state fMRI data with potentially higher degree of subject variability makes the evaluation of the above techniques important. In this paper we compare component estimation accuracies of GICA and an improved version of IVA using simulated fMRI datasets. We systematically change the degree of inter-subject spatial variability of components and evaluate estimation accuracy over all spatial maps (SMs) and time courses (TCs) of the decomposition. Our results indicate the following: (1) at low levels of SM variability or when just one SM is varied, both GICA and IVA perform well, (2) at higher levels of SM variability or when more than one SMs are varied, IVA continues to perform well but GICA yields SM estimates that are composites of other SMs with errors in TCs, (3) both GICA and IVA remove spatial correlations of overlapping SMs and introduce artificial correlations in their TCs, (4) if number of SMs is over estimated, IVA continues to perform well but GICA introduces artifacts in the varying and extra SMs with artificial correlations in the TCs of extra components, and (5) in the absence or presence of SMs unique to one subject, GICA produces errors in TCs and IVA estimates are accurate. In summary, our simulation experiments  and our holistic analyses approach indicate that IVA produces results that are closer to ground truth and thereby better preserves subject variability. The improved version of IVA is now packaged into the GIFT toolbox ( Group ICA (GICA), a framework that includes ICA, is widely applied to group fMRI data , a recently developed toolbox that generates data under the spatio-temporal assumption of ICA and IVA  is of great interest to the neuroimaging community. Functional brain connectivity maps are widely used to investigate healthy and diseased populations in order to identify aberrant networks patterns . Application of ICA to individual subject fMRI data is relatively straightforward. FMRI data is separated into a user specified number of SMs and their corresponding TCs. When ICA is applied separately to multiple subjects on an individual basis, comparing SMs across subjects to make group level inferences becomes challenging due to inter-subject spatial variability of SMs. With such spatial variability, especially when the number of SMs is high, it is not easy to cluster similar SMs across subjects to perform statistical analyses at the group level. GICA provides a way to address this problem by estimating a decomposition from all subjects' data  have been made to the IVA algorithm to achieve reliable source separation for linearly dependent Gaussian and non-Gaussian sources and extend the application of IVA to separate sources with linear dependence , we select a lower number of subjects and components to make result presentation easier. In Experiment 4 we repeat with a larger number of subjects and components. We simulate several scenarios of inter-subject variability; Experiment 1: SM amplitude at different noise levels, Experiment 2: different types of spatial variability  in one SM, Experiment 3: combinations of different types of variability in two SMs, Experiment 4: all SMs in all subjects have a combination of spatial variability. Under each experiment, we perform several sub–experiments to address effects of different degrees of variability, slight spatial overlap of SMs, effects of overestimation of component, effects of presence or absence of components, effects of different noise levels and other variations.In this paper, we compare SM and TC estimation accuracies of GICA vs. IVA under spatial variation of SMs between subjects. In addition to comparing estimation accuracies of the component that is varied between subjects, we also inspect changes in all other components of the decomposition. In other words, we investigate all elements of the cross correlation matrices between the ground truth components (GND) and reconstructed or estimated components (EST) of all SMs and TCs. In our initial experiments , C is common to all M subjectsYi [T × V]: fMRI data matrix from the ith subject, i = 1 to M. Yi is formed after the three dimensional brain voxels are stacked along the columns of Yi and time points along the rowsX: Input matrix to ICA/IVA algorithm. For ICA dimensions of X are [C × V], for IVA dimensions of X are [C × V × M].Ṡi [C × V]: Contains the ith subject's C independent spatial maps (SMs) estimated by the algorithmṘi [T × C]: Contains the ith subject's C independent timecourses (TCs) corresponding to the SMsMain steps of Group GICA : Each subject's data matrix (Yi) [T × V] is reduced along the time domain to retain T1 principal components, where T1 < T. Let Y*i [T1 × V] be the subject level PCA reduced matrix of the ith subject.Temporal concatenation of subject data: PCA reduced subject matrices (Y*i) are concatenated along the temporal domain (rows) to form the group fMRI matrix Y* = T of size [MT1 × V].Group level PCA: Perform PCA reduction on the Y* matrix and retain C principal components. Let X [C × V] be the group level PCA reduced matrix.Independent Component Analysis (ICA): Perform spatial ICA on the X matrix to decompose X into group level SMs given by X = AS, where A [C × C] is related to component TCs and S [C × V] contains group level SMs.Subject level back-reconstruction: There are several methods to back-project group level maps to subject data to obtain subject specific SMs (Ṡi) and TCs (Ṙi), as described in Erhardt et al.  [T × V] is reduced in the time domain to compute Y*i [C × V], where C is the number of desired components.Concatenation of subject data: Unlike in GICA, in IVA subject data are concatenated along the third dimension to form the X matrix of dimension [C × V × M].Independent Vector Analysis (IVA): Perform IVA on the X matrix. In IVA, the decomposition is performed on the three-dimensional X matrix while keeping each subject's SMs and mixing matrices unmixed between subjects. The decomposition yields three dimensional matrices given by Xi = AiSi, where i = 1 to M and denotes the ith subject (in third dimension).Subject Maps and time courses: In IVA reconstruction of subject level SMs and TCs are straightforward as each subject's data is in its own space stacked along the third dimension of the matrices. Subject specific spatial map Ṡi is given by Ṡi = A−1iXi and the subject specific timecourse is given by Ṙi = YiṠ−i.http://mialab.mrn.org/software/simtb/index.html), to simulate fMRI datasets. SimTB was designed to generate fMRI datasets under the assumption of spatiotemporal separability of the fMRI data. In other words it is assumed that the fMRI data can be given as a product of spatial and temporal processes (product of SMs and TCs). In SimTB the user defines the number of SMs and selects them from a predesigned set. The TCs of SMs were generated from a zero mean unit variance normal distribution. To create different types of fMRI datasets we changed the following: SM amplitude , baseline intensity, noise, spatial variability of SMs  and varied TCs for each component and subject. The SMs were represented as 2D axial images of size 100 × 100 voxels. We reduced the number of voxels in the SMs  to increase the speed of dataset generation, GICA/IVA decomposition and to reduce the hard disk space needed as a very large number of fMRI datasets were simulated in this study.We used SimTB .In order to better grasp the functionalities of the algorithms, for M = 5 (20)Number of subjects in the group, V) = 7688Size of image slice = 100 × 100 voxels, number of in-brain voxels Number of SMs in the data, GND: Ground truth componentEST: Estimated or reconstructed componentith SubjectSubi: jth SMSMj: jth TCTCj: Main Steps of data simulation, component estimation, and result comparison:Simulate fMRI dataset: In addition to the above parameters the following can be changed in SimTB: SM sources and their presence in subjects, SM translation in voxels, SM rotation in degrees, SM spread (size), baseline signal intensity, SM signal amplitude, and contrast to noise ratio (CNR). SimTB simulates fMRI datasets with the following main steps, for a detailed description of each of these steps refer to Erhardt et al. .SM Make baseline intensity: for each subject a variable baseline intensity map is computed, voxels outside the brain mask are set to zero.Scale SMs: SMs are scaled according to the percentage signal changes. Percentage signal changes are defined as the peak-to-peak signal change relative to the baseline. Varying percentage signal change values can be assigned to each component and subject.Mix SMs with TCs: SMs and TCs are linearly combined as the matrix product and then each subject's baseline frame is added.Add noise: Rician noise is added to the data according to the CNR values assigned to each subject.GICA/IVA Decomposition: Simulated fMRI datasets of the M subjects are fed into the GICA and IVA algorithms separately to reconstruct SMs and TCs. We briefly describe the steps involved in the decomposition and the parameters used for estimation.Subject level PCA: In this project, the actual number of components in the dataset are known and since the main focus is on analyzing the impact of subject variability, we reduce each subject's data to the actual number of components in the simulated data set, that is T1 = C.Group level PCA for ICA: Here again we reduce the temporally concatenated group dataset to C number of principal components (except Experiments 2h and 4c where we perform overestimation). In real applications there are ways to estimate the number of components using methods such as minimum description length  to the Infomax algorithm  to the second order IVA-GL algorithm . The amplitude or the sign of the components do not convey useful information by themselves. The signs of each SM and the corresponding TC were flipped based on the skewness of the SM. If the skewness of the SM was less than zero the signs of both SM and TC were flipped (multiplied by negative one). In an effort to display all recovered SMs in a consistent manner, we scaled all the SMs to values between negative one and positive one. TCs were z-scored, to have zero mean and unit variance. Reconstructed components were matched with GND, based on the spatial cross correlation matrix between the GND and estimated (EST) SMs. Component pairing is made based on the descending order of the GND–EST correlations using a greedy algorithm where once an EST SM is paired with a GND SM, that SM is not selected again to pair up with another GND. The component sorting scheme used is an important step in the performance evaluation of the ICA/IVA algorithms. At higher subject variability, the EST SMs can be a mixture of GND SMs with significant correlations with more than one GND SM.Experiments 1–3 we simulated data for 5 subjects with 6 components each  was preserved in the estimated components. The component amplitude of the estimated components (AmpEST) were calculated as the product of the standard deviation of the TC (σTC) and the maximum intensity of SM (maxSM), a metric introduced by Allen et al. , in Sub5 SM1 is shifted by Δdmax voxels and in Sub2–Sub4 SM1 is shifted by Δd voxels relative to the previous subject, where Δd = Δdmax/M, M = 5 (number of subjects). We then repeat this test five times for incrementing values of Δdmax. The full width half max (FWHM) of SM1 is approximately equal to 10 voxels and Δdmax was incremented as a multiple of the FWHM of SM1. In the first test Δdmax was set to 5 voxels (or 0.5 FWHM) and for tests thereafter we incremented Δdmax by 5 voxels.We translate SM1 .The horizontal separation between the two blobs of SM5 is varied. The FWHM of SM5 is approximately equal to 5 voxels and ΔExperiment 2a. Here we vertically translate SM1 across subjects. Here we set Δdmax to 35 voxels. At this value of Δdmax, SM1 marginally overlaps with SM4 for Sub5 as shown in Figure 4A.The goal of this experiment is to check the effects of slight spatial overlap between SMs; this experiment is a continuation of Experiment 2a (with Δdmax = 25 voxels and C = 6 ground truth components) with 9 estimated components.In experiments 2a–2h the model order of the estimation was exactly matched with the actual number of components in the ground truth data. In this experiment, we test the effect of subject variability if the model order is over estimated. We repeat We perform this experiment in two parts: (i) all 5 subjects have all 6 components except Sub1 where SM1 is not present. (ii) SM1 is present in Sub1 but absent in all other subjects.The purpose of this set of experiments was to check how spatial variation in two components changed estimation accuracy.Experiment 2b nested within Experiment 2a.This experiment is essentially several experiments of Experiment 2c nested within Experiment 2a.This experiment is essentially several experiments of Experiment 2d nested within Experiment 2a.This experiment is essentially several experiments of M = 20 and the number of components to C = 15. We made this to roughly replicate the application of GICA or IVA to a real fMRI study. Here all components in all subjects undergo all forms of spatial variations as introduced in Experiment 2.For this experiment we increased the number of subjects to U , where a and b are varied depending on the type of spatial variability. For SM translations a = −2k and b = 2k (in voxels), for component rotation a = −10k and b = 10k (in degrees) and for component size a = 1 − 0.2k and b = 1 + 2k, where k is an integer from 1 to 5. A higher k-value corresponds to increased subject variability.In this sub-experiment the degree of variability is picked from a uniform distribution, Experiment 4a, with degree of variability drawn from a normal distribution, N  where μ and σ are the mean and standard deviation of the distribution. The mean values in all variability distributions were kept at zero except for size where the mean value was maintained at one. At each value of k the standard deviation of the spatial variability for this experiment and 4a were kept constant.Exact repetition of Experiment 4a applying spatial variability using k = 2 and at each iteration we increase the model order by 5 components from C = 15  to C = 35.We repeat CNRs; CNR = 0.5 to CNR = 0.1 at k = 2.We repeat Experiment 4a for a range of RGi, RCi, RVi of size [C × C] be the GND–GND, GND–GICA, and GND–IVA correlation matrices respectively for the ith subject. There will be two types of correlation matrices: one from SM and the other from TC. Let rCi,l,m be the correlation between the lth GND component and mth GICA component for the ith subject. Let rVi,l,m be the same for IVA. We define the correlation error matrices as the absolute value of the difference between the GND–GND correlations and GND–EST correlations. For GICA let ECi = abs (RGi − RCi) and for IVA EVi = abs (RGi − RVi). We define EC as the mean of ECi across all subjects, similarly EV for IVA. To get a better handle on the performance of the algorithms, we report the averages and standard deviations of the diagonal and the non-diagonal elements of the error matrices separately. Let μd,Ci = mean ) and μn,Ci = mean ) be the ith subject's mean value of the diagonal and non-diagonal elements of ECi and for EVi as μd,Vi and μn,Vi. Let the standard deviations of correlation errors be σd,Ci, σn,Ci, σd,Vi, and σn,Vi. In experiments where we check correlation errors across different degrees of spatial variability (Experiment 2–4), we report the overall mean correlation error across all subjects and all components and this we denote by μd,Call and μn,Call for mean diagonal and non-diagonal errors, respectively, across all subjects for GICA similarly by μd,Vall and μn,Vall for IVA. For standard deviations the following parameters will be used: σd,Call, σn,Call, σd,Vall, and σn,Vall.We use correlation as the primary metric to compare similarity between GND and EST. Let The simulation results of this experiment are presented in Figure Correlation between GND SM and GICA SM were higher than 0.999 for all SMs and all subjects. TC correlations between GND and GICA reconstructions were upwards of 0.999 for all component TCs and subjects. Our results indicate that SMs (and TCs) were very well estimated irrespective of variability in their amplitude.IVA estimates of SMs and TCs were also very close to GND, but the components were less clean than the GICA estimates. As seen in Figure TC) and the maximum intensity of SM (maxSM) vs. the component amplitude. Both methods' estimates had generally a linear association between GND amplitudes (AmpGND) and estimated amplitudes (AmpEST).In Figure dmax, Δsmax, and Δθmax) are along the x-axis and the mean correlation error across all subjects and components , are along y-axis The error bars correspond to the standard deviation of the errors . Only the lower bounds of the error bars are presented to provide more resolution to smaller errors in the plot.Results of this experiment are presented in Figure −3 for both GICA and IVA. The mean error of the non-diagonal elements for both SM and TC gradually increased in GICA (from ~2 × 10−3 to ~3 × 10−3) with increase in Δdmax. In IVA, although the errors were higher than GICA, we did not observe this trend of gradual increase in error with an increase in Δdmax. The important observation from this experiment was that in both algorithms there was no clear break down of estimation accuracy as the amount of translation increased.All mean errors were less than 4.5 × 10−3). Here again, GICA errors were marginally less than IVA but there was a gradual increase in GICA non-diagonal mean correlation errors with an increase in the size variability of the component.Estimates of both GICA and IVA were close to the GND . The non-diagonal elements of the SM correlation matrix show marginal error in both techniques with small standard deviation. The diagonal elements of the TC correlation error matrix show very low errors in both GICA (<10−3) and IVA (<10−2). In Figure Figure In the first part of this experiment, where one SM was missing in just one subject, IVA reconstructed the SMs and TCs very close to the ground truth (correlation errors less than 0.06). In GICA SMs were closer to the ground truth but the TCs showed large errors. The TC of the component corresponding to the component that was not present in Sub1 showed high correlations errors (0.2–0.8). This was observed only in Sub1 and all other subject TCs were more accurately reconstructed in GICA. In the second part of the experiment where SM1 was present in Sub1 and missing in all other subjects, IVA continued to accurately estimate both SMs and TCs. GICA SM estimates were close to ground truth, but TC estimates of the missing component had high correlation errors with other components in some of the subjects.d,Call, μd,Vall, μn,Call, and μn,Vall) as images for each value of Δdmax and Δsmax. The rows in Figure −3 for both GICA and IVA. GICA errors were slightly less that ICA but the errors marginally increased in the diagonal direction, that is, errors were higher at higher variability.In Figure Results were similar to that of the Experiment 3a.dmax translation of 1.5 FWHM of SM1 and 3 FWHM of SM5 GICA estimates are accurate. After this threshold there is a sudden increase in correlation error in the range of 0.1–0.2. For IVA, μd,Vall for both SM and TC correlation errors were less than 10−3, and there was no clear jump in error with increasing level of variability.Results indicate much better estimation accuracy in IVA. The mean values of the diagonal elements of the SM error correlation matrix indicate that up to Δdmax = 20 voxels and SM5 Δdmax = 20 voxels. This level of variability was selected as a representative example to further examine the nature of errors. The mean errors in SM and TC were much higher in GICA than IVA for diagonal and non-diagonal elements of the correlation error matrix.In Figure Motivated by the large error bars, we further investigated the mean correlation error matrices . The mean correlation error images across subjects are presented in Figure In Figures k = 1, all mean correlation errors in both GICA and IVA were less than 0.02. At k = 2, GICA errors begin to become marginally higher than IVA. At k = 3, GICA diagonal errors begin to show much higher errors than IVA in both SM and TC components. Non-diagonal elements of the correlation error matrices are also higher in GICA than in IVA. At k = 4 and 5 GICA diagonal correlation errors increase rapidly compared to errors in IVA. In Figure Mean errors across all subjects and components at increasing levels of variability . At Experiment 4a.Results of this experiment were very similar to results of k = 2. At C = 15, the case where the number of components in the GND and the number of estimated components are equal, the performance of both methods were very similar. At C = 20 GICA SM diagonal errors begin to increase with. GICA SM correlation errors in the diagonal element continue to increase with higher number of estimated components. At C = 25, 30, and 35 μd,Call increased to 0.42, 0.52, and 0.57 respectively.Mean correlation errors are presented in the y-axis and the number of estimated components are in the x-axis while the amount of spatial variability was kept at k = 2 and gradually increased the noise level. μd,Call and μd,Vall increased with decrease in CNR.For this experiment we kept the degree of spatial variability at In this simulation study, we evaluated the accuracy of component estimations of group independent component analysis (GICA) and independent vector analysis (IVA) under varying degrees of inter-subject spatial variability of components. By using a simulation toolbox (SimTB) to create sample fMRI data sets and a thorough set of experiments we were able to identify several interesting properties of GICA and IVA. We systematically changed the degree of subject variability and evaluated the performance of component estimation not only by measuring the changes in components that underwent spatial variability but also how this variability affected all other components' spatial maps (SMs) and time courses (TCs).Y) for both approaches are identical, but the X matrix in GICA and IVA algorithms is not the same. In GICA there are two levels of PCA reductions before arriving at X; first the subject level PCA and then the group level PCA. In IVA only a subject level PCA is performed. In GICA the group level PCA ensures that the common variances at the group level are well captured. Simulations from this study provide evidence that GICA can reconstruct individual subject variability but only up to a certain limit of subject variability. GICA maximizes the spatial independence of the components at the group level as it is applied on the two dimensional group level X matrix. IVA jointly maximizes two objectives on the three dimensional X matrix: (1) The spatial independence of within subject components and (2) dependence of “similar” components across subjects, by modeling the dependence structure of similar components.As both GICA and IVA are extensions of ICA, inherent assumptions and limitations of ICA are common to both methods, but there are several methodological differences between GICA and IVA. The initial input data  across subjects to maximize the dependency between the aligned sources. Thus, we can imagine an overlay of the same source (SM) for multiple subjects, where the activation regions within each form a chain of slightly overlapped regions. For GICA, recovering such a source will be difficult because the averaging power will be diminished, while IVA can exploit the overlapping regions by maximizing dependency while preserving the subject variability.In order to better understand how inter-subject component spatial variability affected estimation accuracy, our study was broken into experiments with increasing complexity.ECi and EVi, for i = 1 to 5) indicate that correlations between both corresponding and other components were well estimated. Results of this experiment indicate that GICA estimates are marginally better than IVA, max [diag ((ECi − EVi))] < 10−3  analyses, as our simulation results indicate that spatial overlap between SMs can introduce non-existent artificial correlations in TCs.We investigated the estimation accuracy while GND SMs were slightly overlapped. Our results indicate that both GICA and IVA spatially separate the overlapped components. By “spatially separate” we mean that the spatial correlation that existed between overlapping components was not present (zero correlation) in the estimated components. The estimated maps show negative lobes in the overlapping regions. There was no correlation between the ground TCs of the overlapping components, but the estimated TCs have higher correlation. In other words, both GICA and IVA remove or nullify the spatial correlation between SMs but introduce artificial correlation in the TCs of the same components  present in the data. An approach that has gained popularity in the recent past is to estimate a large number of components. In Experiment 2f we estimated nine components on a dataset that had six original components. IVA produced SMs and TCs with very low correlation errors and the extra estimates (SM7 to SM9) were noise-like and were not correlated with the original GND components. GICA SM of the component with inter-subject variability had poorer correlation with the GND SM and had artifacts (negative lobes) at spatial locations of the SM in other subjects . At inter-subject variability greater than this simulated threshold GICA begins to show large errors for both uniform and Gaussian distributions. We expected that the errors of the Gaussian distribution would be less than that for uniform distribution as more subjects are centered at zero variability in a Gaussian distribution. Results indicate that GICA errors in both cases were similar  and across many different studies. The level of inter-subject spatial variability of components present in real fMRI data is uncertain. Further studies are needed to evaluate the performance of GICA and IVA with respect to results from individual ICA. We intend to do that in our next project.The simulated datasets used possess many realistic properties but unavoidably have many limitations. It should be noted that our simulations model the fMRI data as a weighted linear mixture of spatial SMs, where the weighting is determined by TCs, in other words that the fMRI data can be given as product of SMs and TCs and adheres to the assumptions of ICA. We assigned one single TC to represent the activation changes of all the voxels of a SM. This again is an extension of ICA assumptions. Further, the TCs in our simulations were randomly generated with close to zero correlation between different components of the same subject and similar components across different subjects. The ability of both IVA and GICA to construct good SM estimates when inter-subject TC correlations for similar components are near zero is encouraging and bodes well for the algorithms. Functional network studies have indicated that higher correlations can exist between components of the same subject. In this study we did not investigate how reconstruction accuracy may change at higher correlations between TCs or the correlation limit at which ICA would begin to cluster correlated components. In addition, our datasets did not include effects of subject motion and spatial smoothing. In summary, it should be noted that real fMRI datasets are much more complex than our simple datasets. There are several back reconstruction techniques available to estimate subject specific components from group components and in our experiments we used spatio-temporal regression. We did not test other techniques for all our experiments, but in cases where there was high subject variability we checked the results with other back reconstruction techniques. Our preliminary results indicate that the errors in GICA were higher irrespective of the technique applied, but the nature of errors was different.IVA has a high computation and memory burden compared to GICA. It should be noted that GICA has been highly optimized over many versions of the GIFT toolbox. In future work, we intend to improve these limitations of IVA. Further studies are also needed to examine if a joint framework of GICA and IVA can be developed to capture the advantages of both schemes.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The research team conducted interviews with FQHC providers and staff (n = 12). Individuals experienced depression, sadness, and social isolation, as well as frustration and even anger regarding communication. Family members experienced negative impacts of deteriorating communication, but expressed few coping strategies. There was general agreement across data sources that hearing loss was not routinely addressed within primary care and assistive hearing technology was generally unaffordable. Community members described stigma related to hearing loss and a need for greater access to hearing health care and broader community education. Findings confirm the causal sequence of hearing impairment on quality of life aggravated by socioeconomic conditions and lack of access to hearing health care. Hearing loss requires a comprehensive and innovative public health response across the socio-ecological framework that includes both individual communication intervention and greater access to hearing health resources. CHWs can be effective in tailoring intervention strategies to community characteristics.Hearing loss is associated with cognitive decline and impairment in daily living activities. Access to hearing health care has broad implications for healthy aging of the U.S. population. This qualitative study investigated factors related to the socio-ecological domains of hearing health in a U.S.–Mexico border community experiencing disparities in access to care. A multidisciplinary research team partnered with community health workers (CHWs) from a Federally Qualified Health Center (FQHC) in designing the study. CHWs conducted interviews with people with hearing loss ( Across the world people are living longer, increasingly challenging countries to address the cumulative and chronic disabilities that accompany old age . On a glAlong the U.S.–Mexico border, social and economic conditions contribute to profound disparities in hearing health care comparable to those experienced by developing countries. Mexican Americans with hearing loss are significantly less likely to wear hearing aids compared with Whites . In thisThe socio-ecological model (SEM) is an appropriate framework to study hearing health because it moves beyond the cognitive determinants of individual actions to encompass the larger social, cultural, and economic contexts that influence health-related behavior , 13. In The study utilized a community-based participatory approach (CBPR) that combined local expertise of a federally qualified health center (FQHC), funded by the U.S. government to meet the health needs of vulnerable populations, with research faculty from departments of audiology, public health, and Spanish. CBPR ensures that research questions are culturally appropriate, enhances data collection, and facilitates translation of research findings into social change –22. FQHCSanta Cruz, County is a U.S.–Mexico border county with a population of approximately 46,000 residents. The FQHC, founded in 1980, is the largest health-care provider in the county, serving approximately 21,000 patients, the majority of whom are Hispanic (90%). Given that the focal point of our study was access to hearing health care, it was advantageous that the partnership included the FQHC where the majority of residents who are uninsured or on public insurance receive primary care services. Data collection methods were based on a convenience sample and corresponded to the SEM domains displayed in Table Community health workers are increasingly involved in improving the quality of health research by improving participant recruitment and retention . The CHWOne team member from both audiology and public health conducted content analysis using the SEM domains as a coding guide . AnalysiPeople with hearing loss described various negative emotions in response to hearing loss, including depression, sadness, desperation, frustration, shame, and embarrassment. These feelings were largely related to others’ reactions to their inability to hear.I think that this has caused problems to my self-esteem, my value as a person, as a woman, in everything that I do.Well it makes you ashamed because a lot of times they don’t even know what to say… sometimes I answer and they’re staring at me and I start wondering what I said, and I feel bad.Hearing loss directly impacted their engagement in social interaction, and for some affected the nature of their personality and self-concept.Well, I don’t go out much, I don’t socialize much. My outings are with my daughter on an errand, to the pharmacy, to the doctor, but I hardly go out. Especially because of this problem (hearing loss). It has isolated me and repressed me emotionally, because before I was very social. And all this is getting worse.While several respondents said that they were learning to live with hearing loss, others were motivated to seek assistance.It motivates me, needing to hear better. I was always very active, I worked for years. When I realized I was losing my hearing, it made me- even though I was discouraged and had low self-esteem, it gave me the strength to want to do something.Interview participants were well aware of the scope of the impact of hearing loss on their relationships with their family members.It makes me feel desperate with my kids because they are impatient with me. I tell them, “Write down what you want to say to me in a notebook and I’ll answer.” They get mad at me and they make fun of me. It makes me angry, because they say, “You’re deaf!” But how is that my fault?They treat me well and they understand me. I don’t have any complaints about my family, my daughter, my son-in-law, my grandkids. But it also makes me sad that there is a lot I don’t understand. My daughter says, “Yes, I told you, mom, I told you, but you didn’t hear me.” Well, yeah, I tried but I didn’t hear you.In this low-resource community, none of the people interviewed had hearing aids, but they described personal strategies for adapting to hearing loss. These included asking people to repeat themselves or speak louder, or for those with better hearing in one ear asking people to address them from one side. Participants admitted to pretending to hear when they didn’t, and many had come to rely on lip reading. Notably, participants rarely mentioned a collaborative strategy that involved family members in improving communication. Rather, hearing loss contributed to a chain of misunderstanding.I ask them to repeat themselves, sometimes up to three times, and they say, “What’s going on with you?” Or they don’t believe you can’t hear them.Family and friends were cognizant of the social impact that hearing loss had on their loved ones. They agreed that hearing loss caused people to feel isolated and lonely and to suffer from low self-esteem. A notable difference between the interviews and the focus groups was that people with hearing loss overwhelmingly described being sad and ashamed, while family members also spoke extensively about family members being more angry and irritable.They become rather angry. Their character changes, I imagine it is because of the desperation of not hearing, when before they could hear perfectly. It makes them angry.Sometimes I say to him: “You don’t understand what they’re saying to you, because they say one thing and you answer another. People don’t know you can’t hear. When you don’t understand, please don’t answer.” Other people also start to feel embarrassed and they stop talking. It happens so often that the person just starts isolating themselves. Many times I’m talking and he is not hearing me. Sometimes he talks so loudly that everyone outside can hear him. “I can’t control my voice,” he says. There is too much conflict between me and him. This is very painful.This distinction is at the crux of the communication issue in which individuals become isolated and feel increasingly lonely and sad, expressed as anger and frustration in the eyes of their family and friends. However, family members, particularly spouses, talked of their own frustration caused by the negative impact of disintegrating communication. Participants expressed annoyance over loud television and radio, being ignored or misunderstood, and having to maneuver through social situations. One participant captured many of these emotions in her response:Several focus group participants said that it was not difficult communicating with their family members, yet offered few examples of how they had adapted their communication style beyond repeating themselves or speaking more loudly. A major concern for family members was the desire for hearing aids; however, the financial resources required were an area of distress.This is how I would put it. I need a car for work and I need a hearing aid for my dad, what can I do? Well I’m going to get the car for work so I can feed my kids and the hearing aid for my dad has to wait until next year.I’ll tell you something. Do you know why your dad is like that? Because he is deaf. He is deaf because he worked so that you could eat, get educated, so that you could go to college. And now it’s time for you to do your part and give a little back of everything he has given you.Another participant described convincing her son to help with a hearing aid by saying the following:In our analysis, we triangulated the perspectives of providers, community members, and people with hearing loss for a comprehensive understanding of the experience of seeking hearing health care. Respondents were in agreement that hearing screening was not part of a primary care visit for an older adult, and that they would not ask or refer for hearing unless the patient made it the purpose of the visit. Few people with hearing loss had addressed it in a primary care visit, however, for various reasons. These included barriers in patient–provider communication (including hearing loss), patients did not feel it was enough of a problem to make it the focal point of a visit, or they knew they could not afford hearing aids. By contrast, providers felt limited in their ability to respond because of lack of equipment or scope of practice.There’s only so much as a primary care provider we can do as far as figure that stuff out. We can’t do hearing testing here. There are a lot of neurological tests we can’t do here. We’re limited by what exactly we can do here and the equipment we have.When they were aware of a hearing issue, many providers referred their patients to otolaryngology specialists who come from Tucson. However, for some providers, there was no point in referral due to lack of insurance coverage for hearing aids.Most of the time, I just don’t even give them a referral because (Medicare) says, oh yeah, we’ll cover your visit to go see this specialist, and you send them there, and then they say, oh, we don’t cover the treatment, so you’re spending money to send them somewhere, then they’re not going to pay for the treatment, which means you’re essentially wasting money.While, in general, the focus group and interview respondents desired an opportunity to seek medical care for hearing loss, providers expressed skepticism regarding both patient motivation to seek care and the medical system to respond.The elderly have hearing loss issues and they don’t have a lot of resources. In fact, it’s not covered at all, hearing aids. Nor are hearing aids very good.I don’t know if there are interventions that would really make a difference. If someone is losing their hearing early on, they usually don’t like the hearing aid, it just increases the noise.We sought to investigate three aspects of the community with an eye to identifying factors that could be altered through intervention: awareness of hearing loss, resources, and culture. Community members affirmed the need to build awareness about preventing hearing loss, particularly given that factories with loud, heavy machinery are common workplaces for the population in Nogales.The factories in Nogales Sonora- my mom worked her whole life in those factories, and I think my mom started losing her hearing at age 60, because my mom had a lot of vitality and she never got sick except for her hearing problem.Acceptance of hearing loss was also a common thread across focus groups and interviews, designing efforts to reduce stigma for people with hearing loss, particularly by educating others on how to communicate. Suggestions included developing programs to share information about hearing loss and how to prevent it.It would be good to inform service people, especially those who work behind windows, because sometimes we can’t hear a thing. I always blame the people behind me for making so much noise, but it would be better to instruct the service people that they have to speak more clearly.Community members also suggested hearing screenings at health fairs or as part of routine medical care, and to educate the community not to accept hearing loss as normal. Several people suggested a media campaign to raise the awareness of family and friends.With respect to resources, providers focused on the availability of medical services which included otolaryngologists from Tucson and a hearing aid dispenser across from the clinic. Among community members, few were aware of audiologic services. Participants not only mentioned hearing aids but also expressed concern that hearing aids were not effective. Focus group participants knew people who had purchased hearing aids through the mail and were dissatisfied with their quality. Surprisingly, the local hearing aid dispenser was the only one who mentioned accessing hearing aids from Mexico, but said that the majority of his clients were from across the border.Finally, we coded the data for to cultural references that would be relevant to a community-level effort to address hearing loss. Participants stressed that the lack of resources was instrumental in fostering a sense of normalcy and inevitability around hearing loss.Since there isn’t any help, any resources, it’s assumed that it’s normal. We need a campaign to open the community’s eyes that it is not normal, that they can get help.Our qualitative study of factors related to the socio-ecological domains of hearing health found that, although not life-threatening, the absence of hearing health care can potentially convert a modifiable disability into a chronic, deteriorating, and debilitating condition. Although hearing aids can assist with mild-to-moderate hearing loss and cochlear implants may be available for those with more severe impairments , not oneOur findings confirm the causal sequence of hearing impairment on quality of life among family members reported in audiology studies , 35 but Table Finally, a sustainable policy response is needed to address the prohibitive cost of hearing assistive technology. Recognizing hearing loss as a public health issue is surely a first step in that process . Toward Our research challenges assumptions that in the absence of an integrated health system that includes hearing health, affected individuals, and their families can effectively manage hearing loss. This qualitative study in a low-resource Mexican American community makes clear the encroaching impact of hearing loss on healthy aging, and underscores the importance of comprehensive and innovative public health approaches across the socio-ecological framework. The engagement of CHWs in assessing and addressing hearing health in communities that suffer from hearing health disparities can be an effective way to tailor intervention strategies to community characteristics.This research was conducted in accordance with the University of Arizona Human Subjects Institutional Review Board.MI was responsible for overseeing qualitative data collection and analysis, collaborative development of data collection instruments, and development of the manuscript. NM was responsible for overall conceptualization of the research design, collaborative development of data collection instruments, and contributed significantly in the writing the manuscript. DS was responsible for collaborative development of data collection instruments, assisting in data collection and analysis, and contributed to the writing of the manuscript. AS was responsible for collaborative development of data collection instruments, data collection, and revising the final manuscript. CN was responsible for collaborative development of data collection instruments, data collection, and contributed to revising the final manuscript. JZ was responsible for collaborative development of data collection instruments, contributed to conceptualization of the qualitative research design, and assisted in the development of the manuscript. SC contributed to the cultural relevancy of qualitative research instruments and provided input into development of the manuscript. FH contributed to overall conceptualization of the research design, collaborative development of data collection instruments, and contributed significantly to the writing of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Mycobacterium smegmatis mc2 155. We also demonstrate the effect of pomegranate (Punica granatum) extract containing ellagic acid, on M. smegmatis as well as their affect on MtbFtsZ (FtsZ from Mycobacterium tuberculosis). The ellagic acid extracts from pomegranate peels inhibit mycobacteria with a MIC of 25 μM and 0.3 to 3.5 mg/mL, respectively, but failed to inhibit the polymerization of MtbFtsZ. However, the coumarins were shown to inhibit the polymerization and GTPase activity of the protein as well as have an inhibitory affect on M. smegmatis mc2 155. Docking of the most active coumarin (7-Dimethyl-4-methyl coumarin with MIC of 38.7 μM) to the GTP binding site suggests that it interacted with the G103 residue. Based on the docking results two mutants of varying activity (G103S and G103A) were constructed to elucidate the interaction of MtbFtsZ and coumarins. Mutation of G103 with Serine (a bulky group) results in an inactive mutant and substitution with alanine produces a variant that retains most of the activity of the wild type. There is a disruption of the protofilament formation of the MtbFtsZ upon interaction with coumarins as demonstrated by TEM. The coumarins increase the length of Mycobacteria five times and MtbFtsZ localization is disturbed. The mutant proteins altered the GTPase and polymerization activity of coumarins as compared to wild type protein. The results here support that coumarins inhibit proliferation of Mycobacteria by targeting the assembly of MtbFtsZ and provide the possible binding site of coumarins on MtbFtsZ. This study may aid in the design of natural products as anti-mycobacterial agents. The currently reported GTP analogs for FtsZ are toxic to the human cell lines; natural coumarins targeting the GTP binding site of MtbFtsZ may hold promise as an important drug lead for tuberculosis treatment.Coumarins are natural polyphenol lactones comprising of fused rings of benzene and α-pyrone. The current study demonstrates the inhibitory effect of coumarins with various substitutions on  Mycobacterium tuberculosis  for their inhibitory effect on Mycobacteria and MtbFtsZ. The coumarins inhibited the activity of MtbFtsZ and the mutations altered their sensitivity further. Based on studies on the mutant enzymes we propose that the binding site of coumarins at MtbFtsZ could be G103 residue.Pomogranate was known for its anti-bacterial, anti-viral, anti-cancer, anti-inflammatory, anti-oxidant properties. Pomegranate peel is a rich source of tannins, flavonoids and polyphenols  Rosetta cells. MtbFtsZ is a soluble protein and it was expressed by induction of IPTG, and purified by Ni-NTA column chromatography  and ethyl acetate fraction of methanol extract (EthAcFr) were prepared from pomegranate peels as mentioned previously  was chosen as the target for docking of coumarins. The protein was downloaded and prepared for docking by removing the water molecules and subsequently minimizing its energy in Molecular operating environment (MOE), 2014.08; Chemical Computing Group, Canada). The structures of coumarins were sketched in Chem Draw  and the energy was minimized using MMF94X force field available in MOE. The GTP binding site was defined by forming a cavity around it and the bound GTP was removed and the coumarins were docked at this site. For docking in the T7 loop a 10 A° radius was chosen around the major T7 loop residue. Docking was performed using the program Genetic Optimization for Ligand Docking (GOLD), suite 5.2   was used to mutate the MtbFtsZ gene at G103 position. pSAR1 plasmid was used as the template to induce mutation at the G103 site to generate G103S and G103A mutants. The primers for the mutations are listed in Table dpn1 digestion and the resultant products were transformed in E. coli DH5α cells. The plasmid was isolated from the resultant colonies and the mutation was confirmed by full-length plasmid sequencing . The protein was expressed in the same host as wild type, purified and concentrated as per the protocol used for the wild type . 6 μM of MtbFtsZ, was polymerized in 25 mM HEPES buffer, pH 6.5, 50 mM KCl and 5 mM MgCl2 on ice, in the presence and absence of compounds. The polymerization reaction was monitored in a fluorescence spectrophotometer (JASCO 6500) with both the excitation and emission wavelengths set at 400 nm, and temperature set at 30°C. At the end of 300 s 1 mM of GTP was added and the light scattering was recorded till 1,000 s  was incubated in MOPS buffer  in the presence and absence of coumarins. GTP was added and the reaction was incubated at 37°C for 15 min. BIOMOL Malachite green reagent  was used to measure the free inorganic phosphate released  was estimated. The coumarins were diluted from 10 to 200 μM while maintaining the DMSO concentration at 1%. The IC50 for each of the compound was estimated by fitting the data obtained between concentrations vs. activity using GraphPad Prisim- version 5. The values represented here is the mean of three independent experiments. The Km and Vmax were also calculated in GraphPad Prisim.Mycobacterium smegmatis mc2 155 (ATCC 14468) was obtained from IMTECH, Chandigarh, India. The susceptibility of this strain toward coumarins was analyzed by Resazurin based Microtiter alamar blue assay (MABA). The bacteria were maintained in Middlebrook 7H9 medium , supplemented with OADC . Rifampicin and streptomycin were included as positive control. Coumarins were diluted in either DMSO or sterile deionized water. The concentration of DMSO was maintained at 1%. One hundred microliter of 7H9 broth was dispensed in each well of a sterile flat bottom 96-well plate and a serial 2-fold dilution of each of these coumarins was added directly in the wells. The cells of M. smegmatis were adjusted to late logarithmic phase (A600 > 0.6) and used for the assay. Untreated cells served as positive control. The plates were incubated at 37°C for 48 h. Alamar blue  was added to each well. A change in color from blue to pink indicated the growth of bacteria and A570 was measured in Enspire Multimode plate reader . MIC was determined based on the lowest concentration of coumarin where no color change was observed. The effect of coumarins on the bacterial cell length was analyzed by incubating the late logarithmic M. smegmatis cells with 50 μM of coumarins and the cells were fixed and mounted to be viewed under a 100 X objective of Carl-Zeiss Bright field Microscope .The polymerization of MtbFtsZ was visualized with TEM. 5 μM of MtbFtsZ in HEPES buffer, in the presence/absence of 100 μM of esculetin and 7-dimethyl-4-methyl coumarin was incubated with GTP (1 mM) for 10 min and applied to a carbon-coated copper grid (300 mesh). They were stained with freshly prepared 2% of sodium tungstate. The grids were blotted dry and the specimens were viewed with Philips JE, 301 electron microscope at × 50,000 magnification.M. smegmatis was determined with immunofluoresence microscopy using anti-FtsZ antibodies  using the GOLD (Genetic Optimization for Ligand Docking) software (CCDC). The GOLD score predicts the binding energy values of the ligands with the protein. Among all the coumarins 7-Dimethyl-4-methylcoumarin and Daphnetin bind to MtbFtsZ with the highest docking score (around 42) and they interact with the G103 residue through hydrogen bonding . The effect of coumarins on the GTPase activity is similar with IC50 ranging from 60 to 135 μM. Daphnetin, esculetin and 7-dimethyl-4-methylcoumarin inhibited the GTPase activity of the protein the best  as well. But some of them such as Daphnetin, Esculetin, and Umbelliferone exhibit variation in IC50 values among the wild type and mutant proteins.Table TEM images confirm that coumarins strongly inhibit the polymerization and assembly of MtbFtsZ protofilament Figure . The FtsThe secondary structure of the protein was altered upon mutation at the G103 residue with serine as indicated previously Figure . The troMycobacterium smegmatis mc2 155 was studied  of butanol extract from the bark of the Terminalia species. The tannins present in the crude extracts probably augment the inhibitory effect of ellagic acid  and ethyl acetate fraction (EthAcFr) of pomegranate peels on the proliferation of ed Table . The based Table . HoweverM. smegmatis mc2 155. The average length of the cells without treatment is 4.48 ± 1.25 μm . And the activity of G103A mutated protein was decreased only by 22%. Glycine is known to bind with the phosphate of the GTP to enable its hydrolysis and substitution with serine reduces the binding ability of GTP with the protein  were constructed and the effects of coumarins on the polymerization and GTPase activity of these were studied to understand the mechanism. The coumarins perturbed the assembly of MtbFtsZ and the mutation further destabilzed the secondary structure and polymerization of protein.Tuberculosis is the most deadly infectious disease and the emergence of MDR-strains due to irrational usage of drugs has complicated the scenario. With the urgent need to discover new drugs with improved efficacy as well as novel specific targets, FtsZ has received much attention as a promising novel drug target perhaps due to the low sequence homology with tubulin. FtsZ in presence of GTP interact with rest of the proteins viz; FtsA, SulA and ZAP proteins to form the constriction of membrane. Even though such analogs are absent in MtbFtsZ, the mutation of the key residue altered the sensitivity of the coumarins. The current study indicates that coumarins can be well explored as leads for tuberculosis therapy. They are also known to be non-toxic to mammalian cells. Ellagic acid extracts from Pomegranate peels affect the 50 scores for the wild type protein and RA estimated the score for mutant proteins and she performed the CD experiments.DS initiated the idea and performed the site directed mutagenesis of key residues of MtbFtsZ. DS and MD designed the study. RN isolated and characterized the ellagic acid from the pomogranate peels. DS and KS performed MABA assays. KS estimated the ICThe above work is supported by DST-WOSA grant—SR/WOS-A/LS-188/2012.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The aim of this study was to compare the visual field (VF) categorizations (based on the severity of VF defects) between adolescent boys with hearing impairments and those with normal hearing. This cross-sectional study involved the evaluation of the VF of 64 adolescent boys with hearing impairments and 68 age-matched boys with normal hearing at high schools in Tehran, Iran, in 2013. All subjects had an intelligence quotient (IQ) > 70. The hearing impairments were classified based on severity and time of onset. Participants underwent a complete eye examination, and the VFs were investigated using automated perimetry with a Humphrey Visual Field Analyzer. This device was used to determine their foveal threshold (FT), mean deviation (MD), and Glaucoma Hemifield Test (GHT) results. Most (50%) of the boys with hearing impairments had profound hearing impairments. There was no significant between-group difference in age (P = 0.49) or IQ (P = 0.13). There was no between-group difference in the corrected distance visual acuity (P = 0.183). According to the FT, MD, and GHT results, the percentage of boys with abnormal VFs in the hearing impairment group was significantly greater than that in the normal hearing group: 40.6% vs. 22.1%, 59.4% vs. 19.1%, and 31.2% vs. 8.8%, respectively (P < 0.0001). The mean MD in the hearing impairment group was significantly worse than that in the normal hearing group , and the mean FT was also significantly worse . Moreover, there was a significant between-group difference in the GHT results (P < 0.0001). Thus, there were higher percentages of boys with VF abnormalities and higher mean MD, FT, and GHT results among those with hearing impairments compared to those with normal hearing. These findings emphasize the need for detailed VF assessments for patients with hearing impairments. Among children with hearing impairments, having a normal visual system is essential for developing efficient communication skills and for discovering and extracting information from the world . NotablyMany researchers have evaluated the visual performance of patients with hearing impairments. For example, Scott et al. used functional magnetic resonance imaging to show that there was asymmetry in peripheral visual processing among individuals with hearing impairments , and RotStudy Design and Ethics ApprovalThe study is a cross-sectional study that was conducted from March to June 2013, and the study team consisted of an optometrist, an ophthalmologist, a speech therapist, an audiologist, and a psychologist. The ethics committee at Mashhad University of Medical Sciences approved the study protocol in 2012 (registration number: 900857), and the study was performed according to the tenets of the Declaration of Helsinki. After a verbal explanation of the aim of the study and the methods that would be used was provided to the potential subjects and their parents, written informed consent was obtained from all the boys included in the study and their parents. Study SubjectsThe cases were male high school students with IQs > 70 who had hearing impairments, and the controls were male high school students with IQs > 70 and normal hearing. The two samples were randomly selected from the state high schools in Tehran, Iran (with the cases being recruited from high schools for deaf students). Personal information (including age and ethnicity) was documented. Subsequently, to ensure the accuracy of tests , the potWe excluded boys with systemic diseases (such as diabetes), those who took certain medications and consumed special drugs, those who had ocular pathologies, those who had undergone previous eye surgery, and those who cooperated poorly during the examinations. As a result, the study sample consisted of 64 subjects in the hearing impairments group and 68 in the normal hearing group. Due to the correlation between the outcomes for paired eyes of single subjects , the data of only one eye (the right eye) of each subject were included in the analysis.AudiometryThe hearing impairments of the cases were investigated by the audiologist. In accordance with a study by Hollingsworth et al., the subjects were classified into different groups based on the severity of their hearing impairment  .Ocular and Visual Assessmentsi Visual Field Analyzer . All the measurements obtained using this device were done so in a consistent manner, based on the manufacturer’s guidelines, and a representative of the manufacturer checked the calibration of the device before the measurements were taken. The central VF was assessed using the 30-2 Full Threshold program. This program tests 76 points within the central 30°, and it uses a 6°-spaced grid offset from the vertical and horizontal meridians. After the subject was prepared and the ambient lighting in the room was reduced, the 30-2 program was selected from the main menu. The subject was allowed to adapt to the luminance while entering their information. The non-test eye was occluded and the subject held the response button in their hand. Whenever necessary, trial lenses were placed in front of the test eye as close to the eye as possible without touching the eyelashes. All subjects underwent a full ophthalmic examination  to exclude the boys with ocular pathologies . Refractive errors were measured objectively and the results were refined using a subjective refraction assessment. The corrected distance visual acuity (CDVA) was measured using a standard Snellen chart at a distance of 20 ft, and it was recorded in Logarithm of the Minimum Angle of Resolution (logMAR) units. VF was evaluated using a Humphrey 750After ensuring the validity of the results for each subject with respect to the reliability indices , the following variables were recorded: foveal threshold (FT) in dB, mean deviation (MD) in dB, and glaucoma hemifield test (GHT) result. We interpreted the automated perimetry outcomes based on those of previous studies -22. The Statistical AnalysisStatistical analysis was performed using Statistical Package for Social Sciences (SPSS) for Windows version 22 . Descriptive statistics  were calculated. The normality of the data was assessed using the Kolmogorov–Smirnov test, and parametric and nonparametric tests were applied accordingly. We used independent-samples t-tests and Fisher’s exact tests to determine whether there were significant between-group differences in the means and proportions, respectively. P values < 0.05 were considered statistically significant.There was no significant between-group difference in age (P = 0.49), with a mean age of 16 in both groups and a range of 14 – 18 years in both groups. There was also no significant between-group difference in IQ (P = 0.13), with a mean IQ in the hearing impairment and normal hearing group of 97.8 (range: 61 – 129) and 101.1 (range: 61 – 138), respectively. The groups were also well matched in terms of ethnicity. The frequency distribution in the two groups of the VF categorizations (including the distribution by the severity and time of onset of hearing impairment for those in the hearing impairment group) is displayed in The percentage of boys with normal VF and mild, moderate, and severe VF defects in subjects with congenital versus acquired hearing loss was 43.9% vs. 28.6%, 24.6% vs. 42.9%, 10.5% vs. 14.3%, and 21.1% vs. 14.3%, respectively. The percentage of boys with each of the three types of VF defect  was significantly greater in the hearing impairment group compared to those in the normal hearing group: 40.6% vs. 22.1%, 59.4% vs. 19.1%, and 31.2% vs. 8.8%, respectively (P < 0.0001). The mean MD and FT in the two groups is presented in Using a Humphrey Visual Field Analyzer and an automated perimetry method (which is the gold standard method for VF testing ), this sIn this study, 14% of the boys with hearing impairments had a CDVA > 0.00 logMAR. This finding is similar to that of a study by Arming et al., which showed that even after perfect correction of the eyes, 10.8% of the subjects did not have normal visual acuity . The mosIn another study, Codina et al. used a static perimetry technique that was specially designed for children and found that the response to environmental stimuli among children with hearing loss involved significantly shorter reaction times compared to those among children with normal hearing . In contDespite the fact that individuals with hearing impairments are more dependent on a healthy VF in comparison to those with normal hearing, people with hearing loss have a considerable risk of having visual problems. A higher percentage of adolescent boys in the hearing impairment group had VF abnormalities compared to those in the normal hearing group. In addition, the mean MD, FT, and GHT results were worse in boys with hearing impairments compared to those with normal hearing. This indicates the importance of carrying out VF diagnostic tests among people with hearing impairments.


Nearly two-thirds of patients with vestibular schwannoma (VS) are reporting a significantly impaired quality of life due to tinnitus. VS-associated tinnitus is attributed to an anatomical and physiological damage of the hearing nerve by displacing growth of the tumor. In contrast, the current pathophysiological concept of non-VS tinnitus hypothesizes a maladaptive neuroplasticity of the central nervous system to a (hidden) hearing impairment resulting in a subjective misperception. However, it is unclear whether this concept fits to VS-associated tinnitus. This study aims to determine the clinical predictors of VS-associated tinnitus to ascertain the compatibility of both pathophysiological concepts.This retrospective study includes a group of 478 neurosurgical patients with unilateral sporadic VS evaluated preoperatively regarding the occurrence of ipsilateral tinnitus depending on different clinical factors, i.e., age, gender, tumor side, tumor size (T1–T4 according to the Hannover classification), and hearing impairment , using a binary logistic regression.p = 0.002] and hearing impairment GR3  and GR4  as positive predictors. In contrast, patients with large T4 tumors  and complete hearing loss GR5  were less likely to develop a tinnitus. Yet, 60% of the patients with good clinical hearing (GR1) and 25% of patients with complete hearing loss (GR5) suffered from tinnitus.61.8% of patients complain about a preoperative tinnitus. The binary logistic regression analysis identified male gender [OR 1.90 (1.25–2.75); These data are good accordance with literature about non-VS tinnitus indicating hearing impairment as main risk factor. In contrast, complete hearing loss appears a negative predictor for tinnitus. For the first time, these findings indicate a non-linear relationship between hearing impairment and tinnitus in unilateral sporadic VS. Our results suggest a similar pathophysiology in VS-associated and non-VS tinnitus. Tinnitus is the second most frequent symptom in vestibular schwannoma (VS) patients . ApproxiThe current pathophysiological concept of non-VS tinnitus  hypothesizes a maladaptive neuroplasticity on a cochlear, brain stem, and/or cortical level as a consequence of (hidden) hearing impairment. These neuroplastic changes are supposed to cause a neuronal hyperexcitability for the residual auditory input resulting in the subjective misperception –10. HencWe hypothesize, that in case VS-associated tinnitus is based on similar pathophysiological principles as non-VS tinnitus, a distinct relationship between tinnitus and hearing impairment is expected. Reviewing literature several possible explanations for the inconclusive evidence have been identified. Most studies have applied bivariate statistics that might have obscured the factual relationship between hearing impairment and VS-associated tinnitus. First, there is a known interaction between preoperative hearing impairment and VS size . Second,The objective of this study was to determine clinical predictors  of VS-associated tinnitus in a large neurosurgical patient cohort using a multivariate logistic regression.n = 702) based on their ICD-10 code (ICD-10: D33.3). 21 patients were excluded due to the histological findings other than VS. Second, we excluded all patients with neurofibromatosis II (ICD-10: Q85.0) and bilateral VS (n = 61), patients with relapse or postradiation surgery (n = 40) and known contralateral hearing loss  resulting in 572 patients for bivariate analysis  by a semi-structured interview by experienced neurosurgeons. Finally, the presence of ipsilateral tinnitus symptoms was dichotomized for statistical analysis .Hearing impairment was classified according to the GR scale . As mostIn all patients, a preoperative magnetic resonance image of brain with gadolinium contrast was available, and tumor extent was graded according to Hannover classification . VS weret-test or chi-square test. Binary logistic regression analysis was used to determine the predictive value of gender (GENDER), age (AGE), tumor side (SIDE), tumor size (SIZE), and preoperative hearing impairment (GR) for the occurrence of tinnitus (0: TN+ and 1: TN−). Predictive values of the included variable are provided by their odds ratios (OR) together with the 95% confidence interval (95% CI). Data are shown as mean ± standard deviation (SD). Statistical significance was considered with p < 0.05 for each statistical test.All statistical tests were performed using SPSS . Group differences in distribution of clinical attributes such as gender, age, tumor side, tumor size, and preoperative hearing impairment were evaluated by Student’s 2(10) = 52.50, p < 0.0001]. Of the five predictor variables GR, SIZE, and GENDER were statistically significant (Table p = 0.002) and hearing impairment GR3 (p = 0.026) and GR4 (p = 0.001) as positive predictors. Patients with male gender [OR 1.90 (1.25–2.75)] and higher hearing impairment showed higher odds to exhibit a preoperative tinnitus [GR3: OR 1.90 (1.08–3.35) and GR4: OR 8.21 (2.29–29.50)] than patients with no preoperative hearing impairment (GR1), with severe hearing impairment (GR4) being the strongest predictor of tinnitus. In contrast, large T4 tumors (p = 0.024) and complete hearing loss GR5 (p = 0.017) were identified as negative predictors. Patients with large T4 tumors [OR 0.33 (0.13–0.86)] and complete hearing loss GR5 [OR 0.36 (0.15–0.84)] were less likely to develop a tinnitus. However, 43.2% (127/294) of the patients with good clinical hearing suffer from tinnitus. In contrast, 26.5% (9/34) of patients with complete hearing loss suffered from tinnitus.The bivariate analysis showed significant differences between TN+ and TN− patients for gender, tumor size, and hearing impairment. There was a preponderance of male gender, larger tumors (in particular T3), and better hearing function GR1–GR4) in the TM+ group  = 32.17, p < 0.0001] with PTA being a significant predictor of tinnitus (p = 0.002). Patients with PTA >100 dB were less likely to present a preoperative tinnitus than other patients .This study was carried out in accordance with the recommendations of the ethics committee of the Eberhardt Karls University Tuebingen for retrospective studies of data collected as part of routine diagnosis and treatment.GN and FE have contributed to the design of the work, the interpretation of the data, drafting and final approval of the manuscript and have agreed to be accountable for all aspects of the work. JS, ML, AO, AR, and GM have contributed to the acquisition and interpretation of the data, revising and final approval of the manuscript and have agreed to be accountable for all aspects of the work. MT has contributed to the interpretation of the data, revising and final approval of the manuscript and has agreed to be accountable for all aspects of the work.There was no external funding of the study. None of the authors have potential conflicts of interest to be disclosed.


Pseudophakic presbyopic correction is among the prevalent methods for regaining near vision capacity. The purpose of this study is to compare the impact of pseudophakic monovision correction and multifocal lens implantation on the performance in a series of activities of daily living (ADL) of presbyopic patients.An ADL research framework (10 ADLs) was constructed and validated in a sample of patients divided into three validation groups according to their near visual acuity. Sixty-two participants that underwent mini-monovision (MoG) cataract extraction and 60 that underwent bilateral multifocal lenses implantation (MfG) populated study groups and addressed the ADLs. Binocular uncorrected distant (BdUVA) and near (BnUVA) visual acuity were associated with ADL scores and with subjective satisfaction using the VF-14 questionnaire.p < 0.05) tests indicated sufficient psychometric performance of the ADL framework. Both study groups presented comparable mean ADL scores (p = 0.07) however, MoG patients had lower performance in demanding ADLs (p = 0.02). ADL scores demonstrated significant correlation with BnUVA  VF-14 scores .Test-retest reliability [all Intraclass Correlations Coefficients (ICC) >0.90] and construct validity (all Both methods provide sufficient near vision capacity for the majority of activities of daily living. However, only multifocal lens implantation can address demanding near vision tasks.NCT02431156.ClinicalTrials.gov Identifier:  Presbyopia is an age-related visual disorder that results in a gradual inability to perform activities that require near vision. It is common for emmetropic populations above 40 years old; eventually almost everyone will demonstrate a variable amount of near-vision impairment . ProjectPseudophakic monovision corrections attempt to address presbyopia in those patients who either have already developed cataract or their associated refractive errors and/or ocular biomechanics exclude laser-assisted corrections, intracorneal implants or multifocal lenses implantation. Recently, our group published the outcomes of a new pseudophakic mini-monovision technique with variable bilateral myopic defocus (MM-VD) reporting high patient satisfaction levels and spectacle independence . In accoTraditionally, QoL instruments  have been developed for clinical and research settings as a convenient, self-reported assessment of visual capacity –11. HoweIdeally, any functional incapacity should be objectively evaluated for each patient in his/her home or working environment, by careful assessment of his/her performance in specific activities of daily living (ADL). However, the inconsistent methods of such data collection make them unsuitable for comparative studies. To provide a common data collection methodology, simulated environments have been developed for a series of chronic diseases where study participants are objectively evaluated in specific ADLs , 14. UnfWithin this context, the primary objective of this study was to evaluate the objective performance in a series of ADLs of patients who had undergone pseudophakic presbyopic surgery either with MM-VD or bilateral multifocal lenses implantation. Among the objectives of the study were: a) to develop a valid framework of ADLs for presbyopic patients, and, b) to compare ADL scores with subjective reports from the VF-14 instrument.Participants were recruited from the Cataract Service in a consecutive-if-eligible basis, and randomly populated two study groups: a) MoG study group (participants that underwent uncomplicated lens-extraction surgery with MM-VD), and, b) MfG study group . The exclusion criteria for both groups included preoperative manifest astigmatism above one diopter (D), glaucoma, IOP-lowering medications, former incisional surgery, former diagnosis of corneal or fundus disease, diabetes, autoimmune, mental diseases, or the inability to perform ADL tasks for reasons not related to visual capacity.All operations were performed by the same surgeon (G.L.) in a consistent manner using the Alcon Infiniti VisionSystem platform (80% continuous amplitude with 350 mmHg vacuum limit and 40 ml/min aspiration flow rate), as described previously ., PupilsAmong the priorities of the study was to identify those ADLs that require near vision and better reflect visual capacity. The literature review regarding a validated methodology on ADL performance following presbyopia correction was not found. Thus, an exploratory interview study was carried out to ascertain a baseline for the ADL development. A panel consisting of three refractive surgeons and a psychologist were recruited for the exploratory study. A number of ADLs that require near vision were constructed. A sample of patients were interviewed in which they performed the ADLs. The interviews were analyzed and the findings served as the basis for identifying those ADLs that would be operationalized and be used in a universal validated methodology for assessing presbyopia. The final list consisted of ten ADL tasks: Phone Book Search (PBS), Supermarket receipt (SR), Book reading (BR), Cellular message (CM), Cellular entry search (CES), Reading computer screen (RCS), Drops bottle reading (DR), Subtitles reading (SuR), Open door test (ODT), and, Screwdriver test (ST). A detailed description of ADL tasks is presented in Table Following construction of the ADLs, validation of the study framework was executed using a sample of 30 participants who visited our outpatient service in a consecutive-if-eligible recruitment method. These participants populated three validation groups according to their near vision acuity: a) Validation group J1  with binocular near visual acuity Jaeger 1, b) Validation group J3  with binocular near visual acuity Jaeger 3, and, c) Validation group J6  with binocular near visual acuity Jaeger 6.Test-retest reliability was assessed in the aforementioned validation groups by calculating intraclass correlation coefficients (ICCs) for all ADLs in two different visits with an average time-window of 1 month, to prevent memory effect. Construct validity was assessed with one-step analysis of variance (ANOVA) in order to confirm that all ADL tasks could efficiently discriminate validation groups based on their near visual acuity.Within the ADL portfolio, PBS, SR, CES, and DR were a priori since these were especially demanding for near vision capacity and formed the subcategory of “difficult” ADLs (dADL). On the other hand, CM, CES, RCS and SuR reflect the minimal necessary near vision capacity of a citizen in a western society. Accordingly, they formed a separate subcategory (wADL) that was used for group comparisons. For all tasks, both ADL score and subjective difficulty were assessed. The latter was evaluated using 10 point-Likert scales . In case a participant was unable to complete a task, the ADL score was not calculated; only the perceived difficulty was assessed. Overall ADL evaluation required an average of 30 min and was scored by an independent researcher blinded to the surgical technique performed to each participant.Functional capacity of all participants was evaluated with the Visual Function Index-14 (VF-14) questionnaire, which was handed to the patients prior to their ADL assessment. In addition to the total score, two other VF-14 scores were calculated: a) Near vision VF score (VF-NV) derived from the items that assessed the perceived difficulty in near vision activities , and, b) Distant vision VF score (VF-DV) derived from the items that assessed the perceived difficulty in distant vision activities . Among other clinical indexes, the following parameters were evaluated: a) binocular uncorrected distant visual acuity (BdUVA) using the Greek version of the Early Treatment Diabetic Retinopathy Study Chart at four meters distance then converted to a logarithm of the minimum angle of resolution (logMAR) acuity value to allow for statistical analysis, and, b) binocular uncorrected near visual acuity (BnUVA). All postoperative data collection was done within a 6 months timeframe starting from the patient’s last operation.t-test. Non-parametric data were assessed with the Mann-Whitney U test. Values at p < 0.05 were considered as statistically significant. All statistical analyses were performed with the Medcalc version 9.6.2.0 .The normality of measured data was evaluated by Kolmogorov-Smirnov test. Normal distribution data were assessed by Student’s Results from the test-rest reliability analysis are presented in Table p < 0.01] and MoG  participants. Although postoperative BdUVA differences were non-significant between groups (p = 0.09), MfG participants demonstrated significantly better BnUVA (p = 0.04) (Table p < 0.01), Supermarket Receipt , and Drops Bottle Reading  tasks. The Drops Bottle Reading task was identified as the most difficult by all participants, with 16.67% (10/60) of MfG and 85.49% (53/62) of MoG subjects being unable to complete it. In fact, MoG participants presented worse ADL scores and perceived more difficulty in almost all ADLs especially the demanding ones (dADLs). The latter resulted in: a) more MoG participants failing to complete those tasks , and b) MoG participants scoring significantly worse in the dADL subcategory . On the other hand, non-significant differences could be detected in the wADL subcategory . Moreover, overall ADLs score and difficulty was not significant among groups , difficulty: MfG: 8.67 ± 1.18, MoG: 7.99 ± 1.77, p = 0.08). Within this context, only VF-NV scores presented a borderline difference in favor of MfG participants (p = 0.05) while non-significant differences could be detected in the total scores for VF-14 and VF-DV  and MoG (62 participants) study groups. Non-significant differences could be detected in demographic data and the preoperative best spectacles corrected visual acuity . Furthermore, ADL and VF-NV scores presented excellent correlation .Correlation analysis was performed for ADL score, VF-NV score and near BnUVA. Both ADL score and VF-NV score demonstrated significant linear correlation with BnUVA  provide consistent outcomes when near visual acuity does not change and b) sufficiently differentiate presbyopes according to their near vision capacity. Both reliability and validity tests suggested that our ADL study framework was valid for group comparisons. Moreover, we could evaluate the level of agreement between the objective performance derived from ADL scores and with subjective QoL scores derived from the VF-14 questionnaire.Regarding our study outcomes, we detected non-significant differences in the average ADL scores between bilateral multifocal lens implantation and our mini-monovision technique. However, the monovision group demonstrated reduced performance in almost all ADLs, especially for the demanding ones. This average ADL performance resulted in a significant number of MoG participants that were unable to address a series of tasks, resulting in significant difference in the mean scores for the demanding ADLs vs. the MfG group. A different monovision strategy  could perhaps provide better results. Overall, there was a 5-fold likelihood for a MoG participant to be unable to complete a demanding near vision task in comparison with a patient who received multifocal IOLs. On the other hand, both MoG and MfG participants performed equally well in the wADL category. Therefore, we can prospectively conclude that both mini-monovision and multifocal lens implantation provide adequate visual competency to the modern middle-aged citizen of a Western society for the majority of their tasks.Our correlation analysis indicate that ADL scores demonstrated sufficient correlation with near vision acuity and VF-14 scores. However, since VF-14 was developed as a subjective instrument of functional impairment due to cataract, it cannot fully address the presbyopic patient. Therefore, VF-14 presented a borderline significant difference in favor of MfG participants with no further information with respect to how demanding the tasks were. However, we are convinced that VF-14 is a convenient questionnaire for subjective evaluation of surgical outcomes, at least in clinical settings.Evaluation of potential visual disturbances or stereopsis was beyond the scope of this study. Both our group and a series of former investigators have already published their results , 27. MorTo our knowledge, this is first study that objectively compares multifocal lens implantation and mini-monovision in a simulated environment using a predetermined ADL methodology. Our study outcomes could provide the necessary methodological framework for group comparisons among participants with different socio-demographic profile, lifestyle or working mandates and reveal the most compatible surgical approach for their presbyopia. Studies with larger cohorts and/or a different set of ADLs are necessary to confirm our results and further evaluate the long-term efficacy of these prevalent surgical options.