There is increasing interest in finding novel approaches to reduce health disparities in readmissions for acute decompensated heart failure (ADHF). Text messaging is a promising platform for improving chronic disease self-management in low-income populations, yet is largely unexplored in ADHF.The purpose of this pre-post study was to assess the feasibility and acceptability of a text message–based (SMS: short message service) intervention in a largely African American population with ADHF and explore its effects on self-management.t tests (composite) and Wilcoxon rank sum tests . Clinical data were collected through chart abstraction.Hospitalized patients with ADHF were enrolled in an automated text message–based heart failure program for 30 days following discharge. Messages provided self-care reminders and patient education on diet, symptom recognition, and health care navigation. Demographic and cell phone usage data were collected on enrollment, and an exit survey was administered on completion. The Self-Care of Heart Failure Index (SCHFI) was administered preintervention and postintervention and compared using sample P=.003) and management  improved at 4 weeks, whereas confidence did not change . Of the 6 SCHFI items that showed a statistically significant improvement, 5 were specifically targeted by the texting intervention.Of 51 patients approached for recruitment, 27 agreed to participate and 15 were enrolled . Barriers to enrollment included not owning a personal cell phone (n=12), failing the Mini-Mental exam (n=3), needing a proxy (n=2), hard of hearing (n=1), and refusal (n=3). Another 3 participants left the study for health reasons and 3 others had technology issues. A total of 6 patients  completed the postintervention surveys. The mean age was 50 years (range 23-69) and over half had Medicaid or were uninsured . The mean ejection fraction for those with systolic dysfunction was 22%, and at least two-thirds had a prior hospitalization in the past year. Participants strongly agreed that the program was easy to use (83%), reduced pills missed (66%), and decreased salt intake (66%). Maintenance (mean composite score 49 to 78, Over half of ADHF patients in an urban, largely African American community were eligible and interested in participating in a text messaging program following discharge. Access to mobile phones was a significant barrier that should be addressed in future interventions. Among the participants who completed the study, we observed a high rate of satisfaction and preliminary evidence of improvements in heart failure self-management. Despite major scientific advances, heart failure continues to be a common and costly condition, and each year over 1 million people are admitted to an inpatient setting for acute decompensated heart failure (ADHF) . NationaApproximately 40% of ADHF hospitalizations are preventable because of varied factors, such as dietary indiscretion, medication nonadherence, and lack of timely medical consultation . PatientMobile technology, in particular text messaging , is emerging as a promising platform for chronic disease management in low-income populations ,11, in pIn this study, we pilot-tested a text message–based self-management intervention in an urban, largely African American population for 30 days following hospitalization for ADHF. Our study aims were to assess the feasibility and acceptability of the intervention and to test the hypothesis that the intervention was associated with improvements in self-management.After study approval was obtained from the Institutional Review Board, patients were recruited from the University of Chicago Medical Center (UCMC) inpatient cardiology service. Patients were recruited until target enrollment was achieved from November 2011 to January 2012 for a 4-week study. Informed consent was obtained prior to recruitment. Eligible patients included adult patients over the age of 18 years who were diagnosed with ADHF either with decreased or preserved systolic function as determined by the admitting physicians. Because the intent of the study was to provide self-management support, individuals who were not their own primary caregiver, were being discharged to a rehab facility, or who had poor mental status  were excluded [Consent was obtained from the attending physicians for contacting their patients for enrollment. Discharge planners were encouraged to notify the study team of any new admissions for ADHF. Study participants received $30 for study participation and to offset the costs of text messages. They were also provided with a scale to measure their weight.The pilot was designed as a single-arm prospective study. The primary endpoint was change in the Self-Care of Heart Failure Index (SCHFI), a well-described measure of self-management in heart failure , which wA text message communication platform developed for health researchers, SMS-Care , was used for this study. Participants were enrolled in SMS-Care prior to discharge from the hospital and began receiving text messages on their personal cell phones the day after discharge. Text messages were composed to reflect literature published for patient education by the American Heart Association . In addi1. Medication adherence: a daily reminder message  and a biweekly adherence question 2. Dietary compliance: educational messages 3. Appointment adherence: a reminder 48 hours before and the day of their cardiology or primary care follow-up appointments 4. Heart failure signs and symptom recognition: warning signs of heart failure 5. Management if experiencing symptoms 6. Health care navigation: knowing how to get in touch with cardiologist, obtaining medications after discharge , and dealing with complications of paying for medications Each participant’s text message programming was personalized to reflect his/her medication regimen and follow-up appointments. Participants were provided a tutorial on receiving, reading, and sending text messages on enrollment. At the time of enrollment, each patient was sent a test message and replied to it, ensuring basic competency with the use of text messages. Participants were regularly reminded that the system was automated and was not an emergency response system.t tests. Individual items were compared using Wilcoxon rank sum tests. Stata version 11 was used for the analysis .Per the most recent scoring procedure , raw scoOf 61 patients initially identified for ADHF, 51 were successfully approached for enrollment prior to discharge and 27 agreed to participate. Twelve of the patients approached did not own a personal cell phone. An additional 6 patients did not meet inclusion criteria because they failed their Mini-Mental exam (n=3), needed a health care proxy (n=2), or were hard of hearing (n=1). Only 3 patients approached for the study who met all inclusion criteria refused to participate. Of the 27 patients who met inclusion criteria, 15 were successfully enrolled. The remainder were unable to be enrolled due to logistical barriers . Eight of 15 enrollees completed the text messaging portion of the study. Of the remaining 7 participants, 2 died, 1 was admitted to a subacute facility, and 4 had technology issues, including their cell phone being disconnected. A total of 6 participants completed the entire study including preintervention and postintervention surveys.All but 1 participant in the study was African American . The aveMost participants  carried their cell phone with them always or almost always . All parAlthough not required, participants were encouraged to text back comments or responses to questions sent via text message. Although responses were not read by research staff during the course of the study, response rate was considered to be a marker of patient engagement and could inform future program design. Over the 30-day intervention, participants sent an average of 5.7 text messages (range 0-27) or approximately 1 message every 5 days. Five participants did not send any text messages; 2 participants sent over 20 messages. Interestingly, both of these participants were near the median in terms of prior usage of text messaging, and 1 reported being only somewhat comfortable with text messaging prior to the study.All  participants reported the highest level of satisfaction with the mobile phone–based heart failure self-management program . AlthougDuring the open-ended survey, participants reported that the intervention improved self-management directly by providing reminders, but also indirectly by increasing disease awareness and reinforcing the importance of self-management. They liked that the system served as a reminder and provided feedback. One participant stated, “I knew I wasn’t being forgotten,” and another that, “It’s nice to know that someone cares.” Only 2 participants identified elements they did not like about the system: 1 complained that it was hard for him to text and the other wanted more text messages. Participants suggested improvements such as providing more instruction on how to text with the system and making the cost of texting with the system free.P=.003). Self-care management increased from 57 to 86, or 30 points . There was no statistically significant change in self-care confidence .Participants’ responses to the SCHFI suggested that the intervention was associated with improvements in heart failure self-management . On a 10Of the 22 individual items comprising the SCHFI, improvements were seen in 6 items: weighing self, eating a low salt diet, forgetting to take medicines, avoiding getting sick, contacting physician in case of worsening symptoms, and confidence in evaluating symptoms . The texThere were no statistically significant differences in preintervention SCHFI measures between the 6 patients who completed the entire intervention and the 9 patients who did not complete the intervention or who were lost to follow-up.We report the results of a text message–based self-management intervention in patients discharged from the hospital with acute decompensated heart failure (ADHF). To the best of our knowledge, this is the first study of a text messaging intervention for ADHF piloted in an urban, largely African American population.The text messaging intervention was associated with improvements in self-care maintenance and management. Guidance from the developers of the SCHFI suggests that an improvement in either of these scales of 0.5 standard deviations or 8 points is clinically relevant and that a cutoff score of 70 can be used to judge self-care adequacy . We obseWithout a control, these results must be interpreted with caution. In addition to a Hawthorne effect, participants were discharged from the hospital and likely seen in clinic at least once or twice between the preintervention and postintervention periods. Self-management teaching at any of these time points, or simply improvement in health status, may account for the observed improvements. However, it is notable that the specific SCHFI items that improved were generally those targeted by the texting intervention, implicating a causal link. Future studies should validate these preliminary findings in a controlled trial.A major aim of this study was to access the feasibility of text messaging interventions in our patient population. Among patients who met the inclusion criteria, 90% agreed to participate in the study, which is high for our institution. Most participants in our study were comfortable with text messaging and had unlimited text messaging plans. This suggests that in our study population, among those with access to a cell phone, text messaging is a familiar and acceptable means of health care communication. In contrast, only one-third of patients had smartphones, suggesting that mobile phone–based interventions requiring Web access or apps would have low feasibility in our study population.However, 24% of patients approached for recruitment did not own a personal cell phone. This differs from national surveys in which high rates of mobile phone access in low-income populations are observed . HoweverThere were considerable challenges to texting in our study. Although all participants reported comfort in texting prior to enrollment, we observed low participant response rates and requests for additional training in texting. Although most participants reported high levels of satisfaction with the system, a few found the system difficult to use and not helpful in improving self-management. More research is needed in how to design technologies that are usable across a wide range of patients and how to best target mobile phone–based interventions to patients most likely to benefit.A major limitation of our study was the rate of completion and loss to follow-up. Of the 15 participants enrolled, only 6 received the entire intervention and completed preintervention and postintervention surveys. Although this largely reflects the challenges with research in our study population, it may bias the results toward those who responded favorably to the system. The study also had no control group, so the effects on self-management should be interpreted with caution. Finally, this was a single institution study with a small sample size and the results may not generalize to other patient populations.Prior mobile phone-based heart failure interventions have had mixed results when studied in clinical trials ,15. In cText messaging may be a useful tool for improving heart failure self-management in urban African Americansafter hospital discharge. More research is needed to target enrollment to those patients most likely to benefit and to evaluate outcomes in a controlled trial.


The Best Practice Diagnostic Guidelines for Patients Presenting with Breast Symptoms were published in 2010 and suggest patients younger than 40 years should undergo breast ultrasound (US) as first-line imaging, with additional mammography for indeterminate and suspicious clinical or US findings. However, our current departmental guidelines are to use first-line mammography in patients aged 35 and over. The aims were to quantify the use of imaging modalities and cancer detection; to assess whether additional information gained by mammography changed management; and to quantify how many fewer mammograms would have been performed if we had adhered to the 2010 Guidelines.Imaging and histology reports were reviewed over a 6-month period for 35-year-old to 39-year-old females with a symptomatic breast complaint.A total of 247 symptomatic 35 to 39 year olds had breast imaging with a malignancy rate of 4%, all cancers presented with a lump/thickening. Sixty-nine per cent had both US and mammography, 23% mammography only and 9% US only. Four U3 lesions were detected on US with normal mammograms, one of which was malignant. Mammography altered management in three patients, requiring biopsies of the asymptomatic breast, none of which were malignant. If we had adhered to the 2010 Guidelines we would have performed 150 fewer mammograms out of the 171 patients who had both US and mammography.In our study, no malignancy would have been missed and we would have performed 150 fewer mammograms if we had adhered to the 2010 Guidelines and used US as a first-line investigation.


Recently two major manufacturers of hearing aids introduced two distinct frequency-lowering techniques that were designed to compensate in part for the perceptual effects of high-frequency hearing impairments. The Widex “Audibility Extender” is a linear frequency transposition scheme, whereas the Phonak “SoundRecover” scheme employs nonlinear frequency compression. Although these schemes process sound signals in very different ways, studies investigating their use by both adults and children with hearing impairment have reported significant perceptual benefits. However, the modifications that these innovative schemes apply to sound signals have not previously been described or compared in detail.The main aim of the present study was to analyze these schemes'technical performance by measuring outputs from each type of hearing aid with the frequency-lowering functions enabled and disabled. The input signals included sinusoids, flute sounds, and speech material. Spectral analyses were carried out on the output signals produced by the hearing aids in each condition.The results of the analyses confirmed that each scheme was effective at lowering certain high-frequency acoustic signals, although both techniques also distorted some signals. Most importantly, the application of either frequency-lowering scheme would be expected to improve the audibility of many sounds having salient high-frequency components. Nevertheless, considerably different perceptual effects would be expected from these schemes, even when each hearing aid is fitted in accordance with the same audiometric configuration of hearing impairment. In general, these findings reinforce the need for appropriate selection and fitting of sound-processing schemes in modern hearing aids to suit the characteristics and preferences of individual listeners. Two major hearing-aid (HA) manufacturers have recently introduced frequency-lowering sound processing schemes. Although these schemes are technically dissimilar, they are both intended for HA users who have relatively poor hearing at high frequencies. Lowering selected high-frequency components of sound has been shown to help some people with hearing impairment to perceive them The purpose of the present study was to measure and report the technical characteristics of these recently introduced digital frequency-lowering schemes. The first scheme was devised by Widex, a company based in Denmark, and is known as the Audibility Extender. It is a linear frequency transposition (LFT) scheme that has been reported to improve the understanding of some phonemes in speech, at least after training. For example, identification of fricative consonants increased by about 14 percentage points, on average, for eight adults after two months of use The Widex LFT scheme functions by shifting components of sounds present within a source octave into a predetermined target octave The Phonak NLFC scheme is based on different principles To obtain the measurements reported below, each HA was programmed according to the manufacturer' guidelines to provide an appropriate fitting for a sloping, severe-to-profound hearing loss see . The inpMeasurements on each HA with the frequency-lowering functions disabled confirmed, as expected, that the gains and output levels were very similar. Therefore, the spectrum for this condition shown in The short-term spectra for a brief portion of the swept sinusoid at which the input frequency to the HAs was around 3 kHz are shown in the left panel of The right panel of fish, says). The upper panel shows a spectrogram of the original signal, whereas the two lower panels show the outputs of the HAs with NLFC and LFT activated, respectively. The main effect of each type of processing is most evident in a comparison of a vowel sound, such as /i/ in approximately the 0.2–0.4 s portion of the spectrograms, and a consonant sound, such as /∫/ in the following portion up to about 0.7 s. Averaged spectra estimated from these two signals are shown in For the vowel, a comparison of the spectra with the frequency-lowering functions enabled and disabled shows minimal effect for signal components near the first formant frequency . With LFT, components near the second formant (about 2.9 kHz) were lowered to approximately 1.5 kHz. The general effect of linear frequency transposition is clearly evident in that the shape of the spectrum in the source octave above 2.5 kHz with LFT disabled is similar to that with LFT enabled in the target octave below 2.5 kHz. With NLFC, the second-formant spectral peak was lowered to approximately 2.6 kHz, while higher-frequency components were lowered by progressively larger amounts.For the consonant, the spectrum without frequency lowering shows two local peaks at about 2.8 and 4.1 kHz. With LFT, a peak is evident near 1.4 kHz, presumably corresponding to the lower input peak shifted down by 1 oct. There is also a second, relatively broad peak around 2.2 kHz which seems to have resulted from some combination of shifted and unshifted input components. With NLFC, the two input peaks were shifted to approximately 2.6 and 3.2 kHz, respectively. Some interpretations and implications of these results are discussed next.In general, the above measurements are consistent with most expectations of the function of both LFT and NLFC processing. The effect of each scheme to reduce the bandwidth of output signals from the HAs is evident particularly in the spectrograms of The tests with the swept sinusoid indicated that the Widex HA with LFT enabled produced at least two additional frequency components higher than the one expected from transposition of the input signal. Although this suggests some distortion in the LFT processing, it is likely that the levels of the extra components would be lower than the audibility threshold of a HA user with the audiogram used to program both devices see . The tesThe spectra obtained using the vowel sound also showed that some frequency ratios (or differences) between spectral peaks were altered by both LFT and NLFC; see In conclusion, both frequency-lowering schemes may provide perceptual benefits to HA users with hearing impairment at high frequencies. Although only one audiogram configuration was applied in the experiments, it is likely that the findings would be generally similar for other audiogram shapes, provided that they represented types of hearing impairment that would be suitable for fitting of either type of frequency-lowering HA. The technical test results suggest that the Phonak NLFC processing may preserve more details of the overall spectral shape than the Widex LFT scheme, at least for the selected signals and settings. However, the LFT scheme may be more suitable than NLFC for HA users with minimal usable hearing at frequencies above approximately 1.5–2 kHz. This is because the NLFC cut-off frequency is limited to a minimum setting of 1.5 kHz; thus, NLFC is unable to modify lower frequencies. In any case, selection of the optimum fitting for each HA user should depend ultimately on perceptual assessments, including tests of speech understanding in particular.The hearing aids used for the present study were the Widex mind440 m4-19 and the Phonak Naída V SP. Each was programmed to suit the audiogram shown in 3 coupler for later analysis using Adobe Audition 3.0 software. The swept sinusoid, which was used to verify the function of each HA with and without each frequency-lowering scheme, was passed through a low-pass filter with frequency response similar to the long-term average speech spectrum thatch, fish, says, verge) were chosen to include eight different fricative or affricate consonants that are common in English and contain important acoustic components at relatively high frequencies.Output signals were recorded from each HA in each condition for three types of input signal: (1) a sinusoid swept from 0.1 to 10 kHz logarithmically over 10 s; (2) a succession of notes played on a flute; and (3) speech, comprising four monosyllabic words recorded by a female speaker. The average level of all signals was 65 dB SPL. The sounds were delivered to each HA in a Brüel & Kjær Type 4222 anechoic test chamber, and the output signals were recorded via a 2-cmThe audio signals recorded from the HAs were sampled at 44.1 kHz with 16-bit resolution. The spectra shown in Figures00201 and 3 were obtained using a 512-point Fast Fourier Transform (FFT) preceded by a Blackman-Harris windowing function. The spectrograms shown in Audio S1Sound recording from the Widex hearing aid (HA) with the Linear Frequency Transposition (LFT) function disabled. The input signals were four monosyllabic words , a sequence of notes played on a flute, and a swept sinusoid (0.1–10 kHz).(WAV)Click here for additional data file.Audio S2As for , but with LFT enabled.(WAV)Click here for additional data file.Audio S3As for , but for the Phonak HA with the Nonlinear Frequency Compression (NLFC) function disabled.(WAV)Click here for additional data file.Audio S4As for , but with NLFC enabled.(WAV)Click here for additional data file.


Currently, breast screening is implemented with X-ray mammography, but new technology such as digital breast tomosynthesis (DBT) may provide significant advantages because it produces three-dimensional breast images with high spatial resolution. To aid assessment of the cost-effectiveness of DBT, we have compared reading times for DBT images and full-field digital mammograms (FFDM) of the same women.Four consultant radiologists were timed by stopwatch reading FFDM images and then DBT images, with a total of 119 timings of two view cases for each imaging modality. The mammograms used were from women recalled following a screening mammogram and from women who are screened annually due to a family history of breast cancer. The time taken to display the images and to report on them was excluded from the analysis.P < 0.001), with times for FFDM ranging from 4.7 to 109.0 seconds and for DBT from 31.9 seconds to 180.6 seconds. The ratio of reading times DBT:FFDM was approximately 4:1, with readers varying between ratios of 2.4 to 4.9.The reading time was significantly longer for DBT images than for FFDM images, with median times of 66 seconds and 17 seconds, respectively (Reading times were greater for DBT as expected, since the reader has to scroll through the images slices to visualise the entire breast. The images used in this study were likely to have a higher rate of abnormalities than screening mammograms, and to have higher breast density, both of which will increase reading time over routine screening.


Personal genome analysis is now being considered for evaluation of disease risk in healthy individuals, utilizing both rare and common variants. Multiple scores have been developed to predict the deleteriousness of amino acid substitutions, using information on the allele frequencies, level of evolutionary conservation, and averaged structural evidence. However, agreement among these scores is limited and they likely over-estimate the fraction of the genome that is deleterious.This study proposes an integrative approach to identify a subset of homozygous non-synonymous single nucleotide polymorphisms (nsSNPs). An 8-level classification scheme is constructed from the presence/absence of deleterious predictions combined with evidence of association with disease or complex traits. Detailed literature searches and structural validations are then performed for a subset of homozygous 826 mis-sense mutations in 575 proteins found in the genomes of 12 healthy adults.Implementation of the Association-Adjusted Consensus Deleterious Scheme (AACDS) classifies 11% of all predicted highly deleterious homozygous variants as most likely to influence disease risk. The number of such variants per genome ranges from 0 to 8 with no significant difference between African and Caucasian Americans. Detailed analysis of mutations affecting the APOE, MTMR2, THSB1, CHIA, αMyHC, and AMY2A proteins shows how the protein structure is likely to be disrupted, even though the associated phenotypes have not been documented in the corresponding individuals.The classification system for homozygous nsSNPs provides an opportunity to systematically rank nsSNPs based on suggestive evidence from annotations and sequence-based predictions. The ranking scheme, in-depth literature searches, and structural validations of highly prioritized mis-sense mutations compliment traditional sequence-based approaches and should have particular utility for the development of individualized health profiles. An online tool reporting the AACDS score for any variant is provided at the authors’ website. Personal genome interpretation is a process of determining the personal genome sequences and assessing the likely consequences of an individual’s genetic variation. Personalized genome data interpretation can be used, for example, to predict diseases and traits, identify mutations for family planning purposes, and guide medical treatments based on likely drug responses. Developments in next-generation sequencing technologies over the past five years have enabled personal genome interpretation to become feasible and affordable . DespiteSequence-based prediction algorithms are commonly used to categorize nsSNPs into damaging and non-damaging, and to predict the effects  of nsSNPs with respect to undesirable phenotypes. The algorithms score the amino acid changes from the level of sequence conservation observed in homologous sequences or from the degree of physicochemical changes. Structure-based predictions evaluate three-dimensional 3D) structural features, e.g., solvent accessibility, stability, number of residue contacts, which are altered in the mutant proteins. Approaches that include annotation of biological function also support functional assessments of amino acid substitutions. Ng and Henikoff (2006) proposed that the combination of all three types of data may provide the most accurate assessment of likely deleteriousness [D structupredicted to have impact on protein functions [predicted deleterious nsSNPs per individual [predicted damaging nsSNPs is much greater than both the theoretically estimated 15–60 damaging nsSNPs per genome [classified disease-causing nsSNP number of 40–100 per genome [A pioneer study in personal genome interpretation stated that the human reference genome carries 1104 nsSNPs dividual . This nur genome  and the There are many databases that provide useful information about genetic variants. Because genetic polymorphisms found in healthy individuals tend to have small effects, further improvement of available resources is required to more accurately define the set of variants that are likely to be most important for an individual’s health. In this study, we constructed a classification schema . Since the IRB consent does not allow communication of genetic data, given potential negative consequences of knowledge of variants that cannot be acted upon, the identities of the individuals are anonymous and no concerted attempt has been made here to link genotypes to phenotypes directly. Expanded and appropriately consented studies will be required to evaluate the actual utility of the proposed schema as a means of focusing attention on those variants that are most likely to influence personalized health behaviors.Whole genome sequence (WGS) data was obtained for 12 healthy adult participants in the Center for Health Discovery and Well Being (CHDWB) study, including 4 African American women, 4 Caucasian women, and 4 Caucasian men. None of the individuals has any known complex or Mendelian diseases, but they cover a variety of profiles with respect to overall physical and mental health. Prediction of disease risk based on common variants and clinical profiles is described for the Caucasians in . The parWGS was performed on Illumina HiSeq2000 automated sequencers at the University of Washington facility under contract to the Illumina Genome Network. Approximately 125 billion bases passing the Illumina analysis filter were obtained for each genome. Mean non-N reference coverage (after excluding gaps) is ~36X with 95.5% of the positions having an average coverage of at least 10X. The genome sequences were aligned against the human reference genome assembly (hg19 sequence) using CASAVA . On average, 87% of each individual’s quality filtered reads were aligned. High-confidence variants with a quality score above 20 were retained. Accuracy of the generated genome sequences was confirmed by comparison with previously determined genotypes from Illumina OmniQuad arrays, which showed >99% concordance for all individuals.The coding variants were functionally annotated using Variant Annotation Tool (VAT)  which usAmino acid indices for the alternate residues were mapped to the corresponding proteins using transcript IDs for the major isoform. All protein sequences and related information including protein functions and sequence features were obtained from the UniProt database .Evidence for association of each SNP or gene with diseases or traits was obtained from public repositories of amino acid polymorphisms  or were predicted using 3DLigandSite [In order to expand the structure-based predictions to a larger dataset without the requirements of manual inspection or in-depth literature searches, we applied a combination of database searches and computational predictions to a larger set of proteins. In addition to the 6 protein structures described in the main text, we identified an additional 25 protein coordinates from PDB  . 456 of the genes (79%) have a single homozygous variant in the 12 genomes, but two genes (HLA-DRB5 and ANKRD20A4) have more than 10, detected in at least 6 individuals.A total of 797 known homozygous non-synonymous substitutions was observed in 575 different genes Table . The genThe vast majority of all of the variants have been observed previously in the 1000Genomes project, with just 29 private homozygous nsSNPs observed in 25 different genes, with a range of 0 to 5 per genome. Private variants were found in 10 out of 12 genomes of CHDWB dataset and are listed in Additional file Among the 575 genes whose nsSNPs are homozygous and present in dbSNP build 137, the fractions with known functions, putative functions, and unknown functions are ~47, 20, and 33%, respectively  consensus deleterious prediction, (ii) documentation that the SNP causes a disease, and evidence that the SNP is in a gene that has been associated with (iii) a disease or (iv) a quantitative trait Figure . CategorThe list of disease-promoting nsSNPs was retrieved from MSV3d  and SwisG56R in the MYH6 myosin heavy chain, is predicted to be deleterious. Since it is also associated with resting heart rate, it is classified in both categories 2B and 3B. Data for the variant categorization in these 18 disease-associated genes is summarized in Additional file p = 0.21, 2-tailed t-test). All of the remaining predicted deleterious variant that do not have disease or trait associations  are listed in Additional file Among the 93 disease-associated genes with homozygous nsSNPs in our CHDWB genomes, 18 have homozygous variants present in more than one individual, and these account for 40 nsSNPs, observed at 33 different sites. Only one of these sites, The set of 35 disease- or trait-associated SNPs that are also predicted to be deleterious is seven times larger than the set of 5 category 1 “known to be deleterious” mutations. They represent 15% of the 93 disease-associated and 136 trait-associated category 2A and 3A SNPs. Additional file A limitation of our analysis is the uncertainty in the accuracy of phenotypic annotations of SNPs, as well as the variable confidence level in annotations of causal SNPs. We obtained the list of disease-promoting nsSNPs from MSV3d  and Swisin silico analysis of 3D structures can facilitate variant prioritization because it provides systematic screening of nsSNP effects in the context of the protein structure and suggests which mutations may critically alter the function of the protein.Personal genome studies indicate that each healthy individual carries a large number of rare homozygous genetic variants -55. WhilImplementation of the AACDS classification scheme reduces the number of potentially deleterious variants to a number per genome that can feasibly be evaluated manually on a case-by-case basis. For this purpose, we have devised a further pipeline that involves sequence annotations, extracting either X-ray crystal/NMR structures or homology models from structure databases, and computing a series of predictions that capture protein features. In this way, each of the up to 5 variants in categories 1, 2B or 3B can be assessed in the context of the actual protein. While this approach requires that an individual with experience in protein structures be engaged in the personal genome evaluation, the potential gain in accuracy is likely to be meaningful.Our preliminary analysis utilized sequence features for all amino acid residues in each protein, obtained from UniProt features records . The entAPOE2 allele of Apolipoprotein 2 (SNP category 1/2B/3B). This allele has a major influence on lipid transport and is a protective factor against late-onset Alzheimer’s disease and coronary artery disease [R176C is also associated with Type III hyperlipoproteinemia (HLPP3) in approximately 2% of cases (though 94% of HLPP3 cases have the genotype) [Arg176 does not interact with the LDL receptor, the R176C substitution has been shown to indirectly reduce the receptor-binding activity of APOE [-1).Subsequent detailed analyses involved manual inspection and evaluation of individual proteins. The remainder of this section discusses detailed structural evaluations of two known causative variants, two predicted deleterious variants in proteins that have been associated with a disease or trait, and two predicted deleterious variants for which the clinical associations are inconclusive. The first disease causing nsSNP is the well-known Arginine to Cysteine substitution at residue 176  that defines the  disease -62. Homoenotype) . Onset o of APOE . StabiliAsn545 in a protein domain, but it is not in close proximity with two other causative variants or part of a binding site. This mutation is also predicted to be neutral  , a putative tyrosine kinase that is associated with Charcot-Marie-Tooth disease type 4B (CMT4B) . One Afr2+ ions)  has a prevalence of 8-10% in Europeans [Asn702Ser in THBS2 (homologous to 700 in THBS1) demonstrated that this variant does not alter calcium-binding capability. Instead, it induces a local conformational change leading to destabilization of surrounding structures [-1.One predicted damaging nsSNP was found in Thrombospondin 1 (THBS1), a glycoprotein that stabilizes fibrinogen platelet cross-bridges . The hom) Figure C. This Auropeans  and is auropeans . Howeverructures , consistArg35Trp (SNP category 4) is located in a buried site, where it causes changes in residue side chain volume, charge, polarity, and hydrophobicity . The first two of these replacements are parts of disulfide bonds, while the third substitution resides in the chitin-binding domain. Interestingly, the Arg35Trp mutation is predicted to stabilize the protein , a finding that may appear counter-intuitive. However, it is suggested that protein flexibility is crucial for enzyme catalysis [The second example of a predicted deleterious nsSNP is a mis-sense substitution in Acidic mammalian chitinase (CHIA), an enzyme that stimulates chemokine production by pulmonary epithelial cells. G56R is not one of them, this variant had been previously identified in affected individuals but it does not segregate perfectly with the disease in families of probands [G56R found in one of the CHDWB participants is particularly interesting, since the mutation occurs in a myosin head-like domain, a key component for muscle contraction, and with a large degree of amino acid change (Grantham score = 125). Stability prediction also suggests this variant destabilizes the protein .The last two examples highlight cases where the variant is predicted deleterious but its clinical associations are inconclusive. The first example is a Glycine to Arginine substitution at residue 56 of Myosin heavy chain alpha (MYH6) (SNP category 2B/3B). As mentioned earlier, this is the only predicted deleterious variant among a set of 18 disease-associated genes with variants present in more than one individual ; both are located in the loop regions. It had been suggested that the two residues help accommodate a sharp turn of the β-loop [-1), but highly destabilizing for residue 69 . In any case, strong stability changes are suggested to cause protein malfunction and may lead to disease(s) [The second example of a variant with uncertain functional effect is taken from a set of 143 SNPs (18% of CHDWB dataset) that do not currently have phenotypic annotations. Among these, 117 SNPs have neither disease nor trait association at the gene level. Form 143 SNPs, we identified 15 variants predicted to be damaging, of which 8 are located in genes with no clinical associations. Our example is a Proline to Serine substitution at residue 145 of Pancreatic alpha-amylase (AMY2A) (SNP category 4). In addition to one calcium ion and one chloride ion per subunit, the protein is able to bind to several ligands throughout the structure. Mutagenesis studies identified several amino acid residues that are essential for the protein’s catalytic activity and affinity to calcium and chloride ions, but the impact of ablished ,73. Despe β-loop . Substitsease(s) .To facilitate high throughput evaluation of protein structures, we devised a structural analysis pipeline that assesses the functionality of protein residues using data directly obtained from the atomic coordinates or from computational predictions. Using this approach, a list of potentially deleterious variants from a structural perspective can be generated rapidly, providing a way to integrate structural analysis into the variant categorization scheme.-1) tend to be non-deleterious, but not vice versa. Four amino acid residues have B-factors of Cα atoms larger than 60 Å2, a characteristic which may indicate that the atom is disordered due to dynamic motion, or may be an artifact of crystal imperfection. However, three out of these four amino acids are predicted to be at rigid sites and do not induce conformational switches. Another three residues are predicted to lie within a cluster of conserved residues on a protein surface, but none is categorized as damaging variants. Lastly, we found only one amino acid mutation that is located within the binding site, but the variant is in categories 2A and so not predicted to be damaging.The four areas of automated structure-based variant analysis include stability, flexibility, and potential to disrupt protein-protein or protein-small molecule interactions. Many mutations disrupt these structural features and as a result, lead to altered protein functions or diseases. Our assumption is that the analysis may be able to identify some variants with strong effects. The results are summarized in Additional file Imposing the constraint that the 3D structures must be of high quality, our initial analysis was restricted to only 24 experimentally-determined structures and 1 high quality theoretical model. Their sequence coverage ranges from 23–100% (average 69%)  . Unlike hemophilia A, symptoms of HEMB are usually milder or can be asymptomatic. Three male individuals also carry an identical SNP in FRMD7 gene. Malfunctions of this gene can cause nystagmus congenital X- linked type 1 (NYS1), a condition that appears at birth and up to three months old. The indications are spontaneous and involuntary ocular oscillations. Given that most X-chromosome variants are predicted neutral and there is no indication that either of these individuals have these conditions, it is unlikely that the associated disease or trait will develop.Although 96 homozygous nsSNPs were identified on the X chromosome, only 1 nsSNP has been documented as a causal variant (X:50658966 A) Table . Genes iFHL2 gene encodes a four and a half LIM domain protein that acts as a molecular transmitter between signaling pathways and transcriptional regulation. The wild type amino acid affected by the homozygous mis-sense variant of the FHL2 gene is evolutionarily conserved, but the Arg177Gln substitution is only predicted to be deleterious by one program. This variant is not predicted to affect protein stability and the protein is not associated with a disease or trait. However, we mention it as an example of how this approach may highlight networks of proteins, where subtle modification of multiple partners may result in cumulative disruption that would lead to disease under a multiplicative burden of rare variants model.Finally, we used BioGRID  to evaluin silico predictions play an important role in identifying putative functional variants. While a sequence-based approach is the current standard practice for assessing SNP effects, there are still some concerns that sequence conservation alone is not a reliable predictor of deleteriousness. In this study, we propose the AACDS classification scheme using variant annotation and sequence-based predictions. We used AACDS to classify homozygous nsSNPs found in the genomes of twelve healthy individuals into eight categories according to the consensus sequence-based deleterious prediction, types of mutation , and information on disease- or trait-associations with the gene. The classification scheme provides a comprehensive framework for prioritizing a list of SNPs suitable for detailed evaluation, in this study reducing the evaluation space from 826 to 98 variants . An online tool for computing the AACDS scores for any variant is provided at http://www.cig.gatech.edu/Tools.Intensive resource requirements and the associated costs make it infeasible to experimentally verify the effect of every genetic variation. At this stage of human genome study, Several previous studies have shown that structural information plays an important role in understanding the relationship between genetic variation and the structure and function of the protein. The addition of 3D structural analysis following AACDS classification demonstrates how structure data can complement sequence-based prediction, and highlights how functional interpretation can in some cases be inferred exclusively from 3D structures. By using a combination of solved structures or high quality homology models for all human proteins, we demonstrate that up to 117 of the 575 proteins bearing homozygous mutations in our CHDWB dataset are available for detailed SNP evaluation, providing detailed analysis of the 150 prioritized variants.The authors declare that they have no competing interests.TP carried out the analysis. TP and GG participated in the design of the study and wrote the manuscript. Both authors read and approved the final manuscript.AACDS summary report. The report is provided to the user with the AACDS category of the variant and its relevant information, along with additional variant data.Click here for fileTable S2. List of protein structures used in automated structural analysis. Table S3. List of all private variants in the 12 genomes. Table S4. List of all Categories 2A/2B variants affecting the same gene in more than one individual. Table S5. List of all Category 2B variants. Table S6. List of all Category 3B variants. Table S7. List of all Category 4 Variants. Table S8. Summary of automated structural analysis. Table S9. List of X-linked recessive mutations.List of protein structures used in supervised structural analysis. Click here for fileCumulative distribution plots for the six deleterious prediction scores. The X-axis represents the prediction scores, ordered by deleteriousness such that low and high scores for each prediction algorithm indicate neutral and damaging nsSNPs, respectively. For each prediction program, the score threshold for defining damaging SNPs is indicated by a vertical green line (threshold for LRT is at 0.999). The genes were classified into four groups depending upon population prevalence of their SNPs, using the difference in minor allele frequencies (MAFs) (cutoff of ± 5%) between European American (EA) and African American (AA) populations. The four gene groups are EA bias, AA bias, EA&AA bias, and no bias. For each plot, the dashed lines illustrate the cumulative distribution of deleterious prediction scores for disease-causing SNPs located in each gene group. The numbers of genes and SNPs are as follows: EA bias , AA bias , EA&AA bias , and no bias . All disease-causing nsSNPs were retrieved from MSV3D . PopulatClick here for fileAllele frequency distributions by AACDS score. The three columns indicate the minor allele frequency (MAF) in percent, listed in the order of European American (EA), African American (AA) and all populations (All). Only SNPs with available allele frequency data are represented here and the numbers in each group are 221, 33 and 165, respectively.Click here for fileProportions of the 9 types of annotated protein regions found in all residues in the analyzed proteins vs. in SNP residues. Data were compiled from a set of 520 proteins whose sequence features are available from UniProt database .Click here for fileLocation of SNPs within proteins according to sequence feature type. A relative location near zero indicates the SNP is located near the N-terminus of that sequence feature. For clarity, a few features were excluded due to small sample sizes.Click here for fileComparison of gene functional enrichment in the 12 genomes. The analysis was performed with g:Cocoa . Each ceClick here for fileSTK17A gene.BioGRID network for protein interactions in one person’s genome. The red nodes highlight a subset of the query that is connected by an edge in the network. The black nodes are the immediate neighbors of the red nodes. The one private homozygous nsSNP from this individual is found in the Click here for file


Stress is often associated with an increased occurrence of autonomic, cardiovascular, and immune system pathology. This study was done to evaluate the impact of stress on psychological, physiological parameters, and immune system during medical term -academic examination and the effect of yoga practices on the same.The study was carried out on sixty first-year MBBS students randomly assigned to yoga group and control group (30 each). The yoga group underwent integrated yoga practices for 35 minutes daily in the presence of trained yoga teacher for 12 weeks. Control group did not undergo any kind of yoga practice or stress management. Physiological parameters like heart rate, respiratory rate, and blood pressure were measured. Global Assessment of Recent Stress Scale and Spielbergers State Anxiety score were assessed at baseline and during the examination. Serum cortisol levels, IL-4, and IFN-γ levels were determined by enzyme-linked immunosorbent assay technique.P<0.01) than in the control group (P<0.001). Both the groups demonstrated an increase in serum IL-4 levels, the changes being insignificant for the duration of the study.In the yoga group, no significant difference was observed in physiological parameters during the examination stress, whereas in the control group, a significant increase was observed. Likewise, the indicators of psychological stress showed highly significant difference in control group compared with significant difference in yoga group. During the examination, the increase in serum cortical and decrease in serum IFN-γ in yoga group was less significant (Yoga resists the autonomic changes and impairment of cellular immunity seen in examination stress. Stress may be defined as psychophysiological process usually experienced as a negative emotional state. It is a common condition, a response to a physical threat or psychological distress that generates a host of chemical and hormonal reactions in the body. The health effects of stress involve mainly autonomic, cardiovascular, and immune systems.et al.[et al.[Studies have shown that stress is associated with increased latent viral reactivation, upper re4et al. and Shukl.[et al. in theirl.[et al.12 and otl.[et al.14In response to stress, activation of Hypothalamo-Pituitary-adrenal Axis (HPA) results in secretion of Corticotrophin-Releasing Factor (CRF) from hypothalamus. CRF stimulates the secretion of ACTH from pituitary, which further activates the adrenal glands to produce glucocorticoids, which are powerful immune regulators. The effeThere is preliminary evidence that relaxation therapy may influence endocrine function and counter balance stress-induced endocrine changes. Stress m18The study was carried out on sixty first-year MBBS student volunteers staying in hostel/campus, who did not suffer from any acute or chronic physical illness. Our medical college offers MBBS courses only for girl candidates; hence, all of the students selected were young girls of age 17 to 20 years. These students were randomly assigned to yoga group and control group (30 each). All of the students were assessed twice during the study—the first, at the time of enrolment (baseline levels when no examination stress was there) and the second, 3 months later during their exams (exam stress). The 30 students included in yoga group underwent integrated yoga practices for 35 minutes daily in the presence of a trained yoga teacher for 12 weeks. The control group followed their normal daily routine and did not practice any of the yogic techniques practiced by yoga group.The following yogic techniques were daily practiced by the subjects of yoga group:Yogic prayer 2 minutesSukshma Vyayam (micro exercises) 6 minutesSthula Vyayama (macro exercises) 4 minutesAsanas (postures) 12 minutesPranayama 4 minutesDhyana (meditation) 5 minutesPhysiological parameters like Heart Rate and Respiratory rate were assessed by using Biopac physiology lab version 3.0 after proper calibration. Blood pressure was measured by sphygmomanometer.Rate pressure product was calculated by multiplying the systolic blood pressure with the heart rate and then dividing it by hundred. It is a sensitive index of myocardial oxygen consumption.Global Assessment of Recent Stress Scale (GARS) is a reliable and valid method to estimate present level of perceived short-term stress. It allows evaluation of the amount of stress thought as a feeling of pressure one has been under in a well-defined time . It consists of seven areas (scores 0-9). The students were asked to think of a time when they were under stress and describe it and to compare it with how they felt when they were free from worries, pressures, and stress. The subjects were then asked to think of the past week and describe the stress as “pressure” on a scale of 0-9 (none to severe). The seven areas of life included were work pressure, interpersonal relationship, changes in relationships, sickness or injury, financial issues, unusual happenings, change or lack of change from routine. Total scores were made by adding up individual scores that the students had marked in the questionnaire.The state trait anxiety inventory for adults (STAI-A) is the definitive instrument for measuring anxiety in adults. It clearly differentiates between the temporary condition of “state anxiety” and the more general and long-standing quality of “trait anxiety.” The STAI has forty questions with a range of four possible responses to each. State anxiety may fluctuate over time and can vary in intensity. In contrast, trait anxiety denotes “relatively stable individual differences in anxiety proneness” and refers to a general tendency to respond with anxiety to perceived threats in the environment. At the end of the study period, the questionnaires were scored by adding the weighted (1 to 4) scores of each item, using the directions and scoring key provided in the Manual for State-Trait Inventory (Form Y). The scorAll of the subjects were asked to report at 8 am. Taking all aseptic precautions, 5 ml venous blood sample was drawn from the antecubital vein of each subject on both the occasions of blood sampling (at enrolment and during stress). The serum separated after centrifugation was divided into aliquots and batch analyzed by Enzyme-Linked Immunosorbent Assay (ELISA) after every collection.Serum cortisol was estimated by solid-phase competitive ELISA using a commercial kit .Serum Interleukin (IL-4) was estimated by solid-phase sandwich ELISA using commercial kit .Serum Interferon (IFN-γ) was estimated by solid-phase sandwich ELISA using commercial kit .t-test. For nonparametric data, such as levels of IL-4 and IFN-γ, intragroup comparison was done by Wilcoxon Signed Rank test, and for inter-group comparison, Mann Whitney U test was used.The statistical analysis was done using SPSS for windows 10.0 software . Data are expressed in mean±standard error of mean. Intra-group and inter-group comparison of physiological parameters and biochemical parameter (serum cortisol) was done using paired The students selected in the study and control group were matched for age, height, and weight. Baseline values of heart rate, blood pressure, respiratory rate, rate pressure product, serum cortisol, IL-4, and IFN-γ did not show significant difference between the Yoga group and the control group.A highly significant increase was seen in heart rate and mean rate pressure product and significant increase was seen in systolic blood pressure and mean rate pressure product in control group. However, no significant difference from baseline values was seen in the Yoga Group. There was no significant difference in diastolic blood pressure in any of the group during examination stress GARS scores which signified the level of stress perceived by the student over the preceding week was found to increase in the control group, whereas a highly significant decrease was observed in the Yoga group . The GARP<0.05).When the Spielbergers State Anxiety Scores were compared at the baseline, no significant difference was observed between the Yoga and the control group. The STAI scores were found to increase in both the study and the control group, but the increase in the control group was more in magnitude and very highly significant as compared with the Yoga group . During P<0.001) than in the Yoga group  [Both the study group and the control group showed a significant increase in serum cortisol levels during examination stress when compared with their baseline values. However, the observed increase in control group was higher (187.16%) and statistically more significant ( P<0.01) . On inte P<0.01) .Both the study group and the control group showed a slight increase in serum IL-4 levels during examination stress when compared with their baseline values. However, the observed difference was insignificant for the duration of the study, indicating an increase in humoral immunity during examination stress .Serum IFN-γ levels decreased in both the Yoga group and the control group; however, the decrease was found to be significant in the control group but insignificant in the Yoga group . At baseSerum IFN-γ/IL-4 ratio was comparable in both the groups at the beginning of the study. However, this ratio decreased significantly in control group, whereas the decrease in yoga group was insignificant. During examination, serum IFN-γ/IL-4 ratio was significantly higher in yoga group as compared with control group .The present study was conceived with the intention of studying the effect of integrated yoga practices on immune responses in examination stress. It also addressed the effects of examination stress on autonomic and endocrine variables and the effect of yoga practices on the same.P<0.05), increase in diastolic blood pressure by 1.67% (though not significant), an increase in rate pressure product (P<0.001), increase in respiratory rate (P<0.05) during examination stress. On the contrary, students practicing Yoga demonstrated a decrease in heart rate by 1.74%, with no significant increase in systolic and diastolic blood pressures, a decrease in rate pressure product though not significant, and a decrease in respiratory rate  during examination stress as compared with baseline.In our study, it was observed that the control group students (not practicing yoga) had a 5.98% increase in heart rate, a significant increase in systolic blood pressure , whereas in control group, a 21.61% increase was observed. The State anxiety levels which indicate the anxiety a person feels at a particular point of time was seen to increase both in Yoga group (11.38%) and control group 31.56%). Thus, the observed increase in state anxiety levels was higher in the control group. Examination stress is expected to increase the anxiety and almost all studies done on examination stress are in concordance with this..56%. Thu The effe26et al.[et al.[et al.[et al.[All of the students in the study as well as the control group demonstrated a significant increase in serum cortisol levels during examination as compared with their baseline levels; however, the increase in control group were higher and more significant than those observed in the study group. The increase in cortisol levels was expected since cortisol is one of the main hormones involved in stress response. The emotions directly stimulate the limbic system which has profound effects on the hypothalamus to release ACTH, which stimulates the adrenal cortex to secrete cortisol. Similar increase in cortisol levels immediately before and during the examinations has also been reported by various researchers,3536 wher35et al. and Sempl.[et al. did not l.[et al. and Kamel.[et al. have alsP<0.01), whereas decrease in yoga group was not significant. The decrease in serum IFN-γ indicates a decline in cellular immunity with examination stress. However, yoga seems to have some buffering effect on the impairment of cellular immunity as observed from IFN-γ levels of the yoga group during examination stress. From the observed changes in the cytokine levels (IL-4 and IFN-γ) during the examination stress, it appears that Th1 cell activity decreases significantly while Th2 activity remains more or less the same during examination stress. Paik et al. also showed that IL-4 levels increased and IFN-γ levels decreased during examination stress and postulated that immune system biases to Th2 cell activity during examination stress.[et al.[The present study has showed that the mean plasma IL-4 levels rise and serum IFN-γ levels decrease with examination stress. Of this, the decrease in serum IFN-γ in control group was statistically significant  would provide a more definitive view of the role of Yoga and other relaxation therapies on the immune system.Thus, authors conclude that yoga has a significant effect in ameliorating the autonomic, endocrine, and psychological changes brought about by the examination stress. Yoga most probably acts through the cerebro-cortico-limbic pathways on the hypothalamus and the anterior pituitary systems. It thus influences the HPA in such a way that the activation of this system is optimized and a balance is created between the sympathetic and parasympathetic limbs of the autonomic nervous system when the subject is faced with a threat (which in present case is the examination stress). Hence, the subjects practicing yoga do not show as much increase in autonomic variables as seen in the control group. In addition, the circulating levels of cytokines suggest that yoga also has a beneficial effect on the immune system of the individual.


Visual field testing is an essential part of glaucoma care. It is hampered by variability related to the disease itself, response errors and fatigue. In glaucoma, blind parts of the visual field contribute to the diagnosis but - once established – not to progression detection; they only increase testing time. The aims of this study were to describe the persistence and spatial distribution of blind test locations in standard automated perimetry in glaucoma and to explore how the omission of presumed blind test locations would affect progression detection.Data from 221 eyes of 221 patients from a cohort study with the Humphrey Field Analyzer with 30–2 grid were used. Patients were stratified according to baseline mean deviation (MD) in six strata of 5 dB width each. For one, two, three and four consecutive <0 dB sensitivities in the same test location in a series of baseline tests, the median probabilities to observe <0 dB again in the concerning test location in a follow-up test were 76, 86, 88 and 90%, respectively. For <10 dB, the probabilities were 88, 95, 97 and 98%, respectively. Median (interquartile range) percentages of test locations with three consecutive <0 dB sensitivities were 0(0–0), 0(0–2), 4(0–9), 17(8–27), 27(20–40) and 60(50–70)% for the six MD strata. Similar percentages were found for a subset of test locations within 10 degree eccentricity . Omitting test locations with three consecutive <0 dB sensitivities at baseline did not affect the performance of the MD-based Nonparametric Progression Analysis progression detection algorithm.Test locations that have been shown to be reproducibly blind tend to display a reasonable blindness persistence and do no longer contribute to progression detection. There is no clinically useful universal MD cut-off value beyond which testing can be limited to 10 degree eccentricity. Glaucoma is a progressive disease that may cause irreversible blindness. Monitoring of the disease with perimetry is an essential part of glaucoma care, unless patients have a short life expectancy and little glaucomatous damage. Variability hampers the use of perimetry in detecting small changes in visual function. In glaucoma, variability is presumably related to response errors, fatigue effects SITA reduces the test time, amongst others, by predicting the sensitivity in a test location from the sensitivity in neighboring test locations and by incorporating general knowledge on glaucomatous visual field patterns. However, SITA ignores an obvious other source of prior knowledge, being the previous test result. The use of the previous test result can reduce test time The aims of this study were (1) to describe the persistence and spatial distribution of blind test locations in standard automated perimetry in glaucoma and (2) to explore how the omission of presumed blind test locations would affect progression detection. For the first aim, we determined the probability to observe a sensitivity below a certain value as a function of the number of preceding consecutive sensitivities below that value in the concerning test location. This was evaluated for <0, <5, <10 and <20 dB. The value <0 dB corresponds to the maximum stimulus intensity of the HFA perimeter; the values <5 and <10 dB approximately to the maximum stimulus intensities of the Octopus and Oculus perimeters, respectively. Subsequently, we compared the percentages of blind test locations between the regular standard automated perimetry 30–2 grid (with test locations up to 30 degree eccentricity) and the subset of test locations falling within the 10–2 grid (up to 10 degree eccentricity), as a function of disease stage as defined by the mean deviation (MD). The aim here was to determine a clinically useful MD cut-off value for preferring 10–2 testing over 30–2 testing in advanced glaucoma. After all, although glaucoma sometimes starts close to fixation The study protocol was approved by the ethics board of the University Medical Center Groningen. This board approved that for the current study no informed consent had to be obtained because the study comprised a retrospective anonymous analysis of visual field data collected during regular glaucoma care. To ensure a proper glaucoma diagnosis of the included patients, we limited the study population of this study to glaucoma patients that had been included in the Groningen Longitudinal Glaucoma Study (GLGS) in the past. In the GLGS, all glaucoma patients and glaucoma suspects who visited the glaucoma outpatient service of the University Medical Center Groningen between July 1, 2000, and June 30, 2001, and who provided informed consent were included in an observational study with conventional perimetry, frequency-doubling perimetry  and laser polarimetry . Patients received written information at home at least two weeks before their regular care visit that was flagged as the baseline visit of the study. The receipt of the information and agreement to participate was checked verbally during the concerning visit. The aim of the study was explained; participation was voluntary and participation could be stopped also after having agreed to participate. The study essentially comprised the collection of regular care data obtained during regular visits and an additional FDT and GDx test embedded in a regular visit. FDT and GDx are non-invasive diagnostic tests with a very limited additional burden and no additional risk for the patient. The protocol of the original GLGS was approved by the department of Medical Technology Assessment of the University of Groningen. The original health technology assessment research question was if it was possible to replace, in glaucoma patients and/or glaucoma suspects, the lengthy and cumbersome conventional perimetry by FDT and/or GDx. The study followed the tenets of the Declaration of Helsinki.Details of the GLGS have been described earlier Perimetry was performed using the HFA 30–2 SITA fast strategy. For glaucoma, two consecutive, reliable tests had to have defects according to previously published criteria One eye per patient was included. If both eyes met the above-described criteria, one eye was chosen randomly. For anatomical representation, all left-eye threshold data were converted to a right-eye format. Thresholds representing the blind-spot were excluded from the analysis, leaving 74 tests locations for analysis.For this analysis we only included patients who (1) performed at least eight tests and (2) had at least one test location showing a <0 dB sensitivity on four consecutive baseline tests (most stringent criterion for blindness). We defined four subgroups of test locations, based on the first four tests and named VF4<0, VF3-4<0, VF2-4<0 and VF1-4<0. A test location VF4<0 had to have a sensitivity of <0 dB in the fourth visual field test. A test location VF3-4<0 had to have a sensitivity of <0 dB in both the third and the fourth test, and so on. For VF4<0, the sensitivity of the test location in the third test may or may not be <0 dB. Hence, VF3-4<0 is a subset of VF4<0, and so on. We took the fourth test as a reference in order to be able to vary the number of baseline tests without the need of changing the selection of the four follow-up tests, which were the fifth to eighth test.For all test locations with a sensitivity of <0 dB in the fourth test, we analyzed the corresponding sensitivities in the four follow-up tests. Outcome measures were (1) the percentage of follow-up tests showing a sensitivity of <0 dB and (2) the mean sensitivity. Here, test locations with <0 dB were set at -2 dB. This is the arbitrary interpretation of <0 dB as chosen by the manufacturer. For patients, the difference between 0 dB and <0 dB implies seeing the maximum light stimulus of the perimeter (0 dB) or not (<0 dB).Test locations within a single subject cannot be considered independent. Therefore, to avoid that a few patients with many blind test locations would dominate the results, we first determined the averages and corresponding standard deviations of the outcome measures within each patient for each subgroup of test locations . Subsequently, the averages were presented using nonparametric descriptive statistics and the standard deviations of the first outcome measure were averaged over all patients and presented as the “mean within-patient standard deviation”.The analyzes were repeated with blindness of a test location defined as a sensitivity of <5, <10 and <20 dB instead of <0 dB. The influence of the number of consecutive tests  showing blindness in a test location and the definition of blindness  on the persistence of blindness was analyzed with ANOVA, with the persistence of blindness (average percentage of follow-up tests showing blindness in the concerning test locations) as the dependent variable.For this analysis, we included all patients who performed at least four tests. Patients were stratified according to baseline MD in six strata, being above -5 dB, from -5 to -10 dB, -10 to -15 dB, -15 to -20 dB, -20 to -25 dB en beyond -25 dB. We plotted the test locations considered blind based on their sensitivity history and calculated the percentages of these test locations, for all test locations of the 30-2 grid and for a subset laying within the 10-2 area. Percentages were compared with a nonparametric paired test (Wilcoxon).A commonly used progression detection algorithm, the Glaucoma Progression Analysis (GPA) If the sensitivity of a test location has been below a certain value on a number of consecutive tests, it might be an efficient approach to consider such a test location blind in all future tests – in glaucoma – without actually retesting it. This might result in a (slight) underestimation of the MD and thus might affect MD-based progression detection algorithms. To determine the influence of this approach on clinical decision making, we classified all included eyes as stable or progressing according to the MD-based Non-parametric Progression Analysis algorithm (NPA), with progression defined as at least possible progression at the end of the follow-up  http://psy.otago.ac.nz/miller/).Calculations and statistical analyses were performed using SPSS Statistics 18.0 ; the ANOVA was performed using MrF ((P<0.001), while the opposite was the case for all other strata (P<0.001). For the three consecutive <0 dB criterion  increases with increasing disease severity. Interestingly, the percentages of blind test locations appeared to be similar for 30–2 and 10–2 grids for all disease stages.With the introduction of the SITA strategies in the late ninety’s of the previous century, the examination time of standard automated perimetry decreased substantially The time gained by the suggested approach should be interpreted and weighed correctly. Obviously, if the time saving is compared to the total time spent in the hospital, the saving is negligible. However, not testing blind test locations refrains a patient with moderate or advanced glaucoma from long time periods in which he or she does not observe any stimulus but has to stay alert nonetheless. This should increase concentration, thus increasing the reliability of the test result. Second, long time periods without any visible stimulus increase patient frustration by emphasizing not seeing things. Third, the saved time can be used to study the remaining parts of the visual field in more detail without additional visits or costs. This can be done by either adding test locations or determining thresholds more accurately. Obviously, to allow for a reliable progression detection throughout the follow-up, only the test locations belonging to the original grid should contribute to the MD. The added test locations, however, may be analyzed separately and may yield important information A caveat of incorporating our regions-of-no-interest approach is that it may cause propagation of blindness through the visual field if applied to strategies that use some form of spatial smoothing  in order to reduce test time (as possibly occurs in SITA). This will not occur in strategies that use neighboring sensitivities only for estimating a starting value for determining a threshold.The classical picture of glaucoma deterioration is the development of visual field defects initially in the periphery, leaving vision unaltered centrally until the latest stages of the disease. Albeit this picture has been challenged recently The absence of a response to the maximum stimulus intensity is not identical to blindness. The dynamic range of the perimeter can be increased by replacing stimulus size III by size V. Interestingly, this appears to reduce the test-retest variability The exclusion of test locations with a sensitivity of <0, <5 or <10 dB at baseline did not affect progression detection with NPA . Only foOriginally, the SITA fast strategy, as used in the GLGS, was considered a time-saving improvement of the SITA standard strategy and for that reason we adopted it in our study designed in 1999. Later it became clear that the strategies performed slightly different. Two studies reported a slightly higher sensitivity for SITA standard in comparison with SITA fast In conclusion, current perimetric strategies share the inconvenient property that test-time increases in advanced glaucoma, while a smaller residual visual field has to be tested. A more clever customizing to what has to be tested than a default change to 10–2 testing should allow for an improved and uninterrupted long-term monitoring of glaucoma patients with standard automated perimetry.


Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1–human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1–human interaction network. Novel HIV-1–human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed. Interactions between proteins are important biochemical reactions which determine different biological processes. Analysis of the regulation between viral and host proteins in different organisms is an important step to uncover the underlying mechanism of various viral diseases. Human immunodeficiency virus (HIV) is a lentivirus (a member of the retrovirus family with long incubation period) that can lead to acquired immunodeficiency syndrome (AIDS), a condition in humans in which the immune system begins to fail, leading to life-threatening infections et al., new protein interactions have been predicted using a variant of kernel canonical correlation analysis There are several computational approaches for predicting PPIs Most of the above approaches are mainly used for determining PPIs in a single organism, such as yeast, human etc. However, determination of PPIs across multiple organisms such as between viral proteins and the corresponding host proteins can contribute to the development of new therapeutic approaches and design of drugs for these viral diseases. There are some recent computational approaches in predicting and analyzing HIV-1-human PPIs. Tastan et al. The computational methods for predicting HIV-1–human PPIs are mainly based on designing some classifiers which need both positive and negative samples for PPIs. Although there are several online resources that systematically store information about experimentally validated interacting proteins, there is no such resource for non-interacting proteins which should be used as the ideal negative samples. Therefore in most of the works in this area, negative samples are prepared by taking random protein pairs which are not found in the interaction database. This is done with the expectation that this random protein pairs are less likely to interact physically, which may not be true always. The performance of the classifier highly depends on the choice of the negative samples.With this observation, in this article we have proposed an approach based on association rule mining (ARM) In this section, the procedure for mining ARs from HIV-1–human PPI network has been described. First we describe the preparation of the input data set. Thereafter, how to apply the proposed algorithm on the input data set to discover highly confident rules and how these rules are used to predict new interactions are discussed. Finally, the results of mining ARMs from HIV-1-human PPI network are reported and discussed.File S1), and its transpose matrix File S2). An entry of 1 in the matrices denotes the presence of interaction between the corresponding pair of human and HIV-1 proteins, and an entry of 0 represents the absence of any information regarding the interaction of the corresponding human and viral proteins. Initially it is treated as non-interaction. The resulting binary matrices is treated as the input to the BiMax biclustering algorithm The HIV-1–human PPI database As discussed above, the rows of the input binary matrix In a similar fashion, we also extract the ARs from the Here we have used a two-step filtering process to obtain high-confident, non-redundant and most general ARs. The two steps are as follows:In this step, the rules that have confidence less than the provided For removing the redundant rules, the following filtration is adopted: Consider a rule The two steps of the filtering process are applied one by one on the initially extracted rules to obtain high-confident, non-redundant and most general rules for further use.We have utilized the filtered ARs to predict new viral-host interactions as follows: Consider again the rule The following text describes the experimental results. Note that we have two binary matrices in hand: As the HIV-1 proteins are in the columns of By applying the BiMax algorithm with the specified parameters discussed above, we extracted 48 all-1 maximal biclusters, i.e., 48 frequent closed itemsets. From these frequent closed itemsets, 123 unique rules with single consequent are generated. Thereafter, we apply the filters on the extracted rules. After applying the Step-1 and Step-2 of the filtration process, the number of rules reduces to 26 and 15, respectively. Subsequently we apply the proposed method to predict new interactions. When the rules shown in For the Application of BiMax algorithm with the above parameters yields 74 all-1 maximal biclusters, which is equivalent to 74 frequent closed itemsets. Thereafter we extracted 361 unique rules with single consequent from these frequent closed itemsets. Subsequently, the extracted rules are filtered and the Step-1 and Step-2 of the filtration process minimize the number of rules to 50 and 36, respectively. In Next, the proposed method is applied to predict new interactions. The rules shown in The predicted interactions from This final set of 180 predicted interactions involves 17 unique HIV-1 proteins  and 140 human proteins. It is stated in For the purpose of illustration, the predicted bipartite network has been shown in In this section, we examine the properties of human proteins that interact with each HIV-1 proteins based on gene ontology based study. The results of these experiments are reported below.http://david.abcc.ncifcrf.gov). To obtain the significant non-redundant GO terms, we have utilized a recently developed web server REVIGO (http://revigo.irb.hr/) Dispensability values for each term. Lower value of Dispensability indicates lesser redundancy of the corresponding term membrane organization. Also coated membrane (20%). This is an important observation because as stated earlier env_gp120 is embedded in the HIV envelop which helps the virus to attach to and fuse with the target cell. In this process it needs to interact with many membrane proteins and our predicted human proteins seem to be largely related with membrane activities, and there is high chance that env_gp120 interacts with these proteins. From death (18.33%) and regulation of defense response to virus by virus (8.33%), which are important for promoting antiviral immune response mechanism and thereby limiting viral replication. When env_gp120 possibly interacts with these human proteins they affect their activities and as a result the immune response system may fail. This indicates that interaction of env_gp120 with these human proteins may lead to cell death.As stated above, 64 human proteins have been predicted to interact with the viral protein env_gp120. Here we attempt to study the biological relationships among these 64 human proteins. First, we conducted a gene ontology (GO) based study to find whether there are any significant GO terms in the three categories of GO using DAVID functional annotation tool  in the predicted interactions, and thus needs special attention. For Tat also we have conducted similar GO study and the results are shown in 9 in the regulation of apoptosis. This indicates that these human proteins may also be in the viral infection pathway leading to cell death through apoptosis. Interestingly, we found that out of these 15 human proteins, 5 of them are involved in pathways in cancer (KEGG: hsa05200) suggesting that possible viral infection may lead to some type of cancer.The other less-dense HIV-1 hub protein found in the predicted interactions is Vif, the virion infectivity factor. This protein is known to interfere with the immune system’s defences and increases the infectivity of the HIV particle. The 15 human proteins that are predicted to be interacting partners of Vif are found to share many common significant GO terms as depicted in http://string-db.org). Another envelop protein env_gp160 is predicted to interact with 5 human partners ACTB, ACTG1, CASP3, CCL3, and IL10. These five partners have significant involvement in cell motion, regulation of B-cell activation/proliferation, and regulation of T-cell activation/proliferation. Thus these proteins are involved in humoral and cell-mediated immune response and viral infection affects these immune activities. The env_gp141 is predicted to interact with BCL2, MAPK1, NFKB1 and NFKBIA, which are found to be significantly involved in the B-cell/T-cell signaling pathway, apoptosis and programmed cell death. Moreover all of them are involved in the signaling pathway of prostate cancer. This is interesting since it suggests that HIV-1 infection through env_gp41 may indirectly cause prostate cancer. The Gag_Pr55 is predicted to interact with CD4, IFNG, MAPK1 and all these three proteins take part in the positive regulation of immune system process. The proteins are also found in the T-cell receptor signaling pathway. Thus they are responsible for the immunity of the host. The human proteins CD4, IFNA1, MAPK1, MAPK3, SAT1, and TCEB2 are predicted to interact with integrase. Out of these six human proteins three  are found to be in the T-cell receptor signaling pathway and the pathway leading to renal cell carcinoma. The human proteins IL10, NFKBIA are predicted to interact with the viral protein matrix. Both of these human proteins actively participate in maintenance of protein locations in cell and regulation of transcription factor activity. The viral protein Nef is predicted to interact with CYCS and HSPA5. Expression of Nef causes T-cell activation and it also promotes the survival of infected cells by downmodulating the expression of several surface molecules important in host immune function. Interestingly, these two human proteins have involvement in apoptosis and programmed cell death. The HIV-1 protein nucleocapsid is found to interact with CASP3, IFNG and PRKCA, and importantly, these three human proteins are significantly involved in negative regulation of cell proliferation, positive regulation of apoptosis and programmed cell death. Moreover they are involved in the KEGG pathway of natural killer cell mediated cytotoxicity (hsa04650). The human proteins predicted to interact with the HIV-1 proteins p6, retropepsin, Rev, RT, Vpr and Vpu also share many biological activities related to immune response, apoptosis and programmed cell death.The other HIV-1 proteins have smaller degrees in the predicted network. We also studied the relationships among the human proteins that are predicted to interact with some common HIV-1 protein through GO and KEGG pathway enrichment test using DAVID. The HIV-1 protein capsid interacts with ACTG1, MAPK1 and PRKCA. Interestingly, these three proteins interact with each other as found in the STRING database , a more detailed study is needed and initial assumptions are to be revised for more clear overview of the viral replication process. Our future plan is to consider all possible types of interactions present in the database initially to build the interaction matrix (matrix will no longer be a binary one), and also to consider the directions of interactions . Starting with this, the derived rules will then be able to predict the annotated interactions along with their directions. This is expected to more clearly explain the process of HIV-1 replications by predicting interactions in different stages of viral life cycle with possible sub-cellular compartments where the interactions are taking place. The authors are now working in these directions.http://www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions/). The database was accessed in March 2011 to prepare the PPI data set for the present study. There are total 2534 interactions between 19 HIV-1 proteins and 1432 human proteins. The interaction information in the database is derived from small scale protein interactions curated from published materials. The PPIs reported in the database are specifically annotated according to the nature of the interactions including over 68 interaction types such as “binds to”, “interacts with”, “upregulates” and “phosphorylates”. The types of interactions can be broadly classified into direct physical interactions , that comprise of 32% of the interactions and indirect interactions  that comprise of 68% of the interactions. Both direct and indirect interactions are considered in our study since indirect interactions also contain valuable information about the characteristics of the interacting proteins. Including the information, at the beginning of the analysis is expected to be beneficial for predicting novel interactions, both direct as well as indirect. Moreover, the natures of interactions are also not considered separately. We have constructed a binary matrix of human and viral proteins, The interaction information reported between HIV-1 and human proteins has been prepared based on a recently published PPI interaction data set cover of an itemset support of an itemset frequency of an itemset isThe principle of association rule mining (ARM) lies in the market basket or transaction data analysis. Much information is hidden in the day to day transactions taking place in supermarkets. For example a customer who is buying nappy also likes to purchase baby food in the same time. Association analysis is the discovery of rules showing attribute–value associations that occur frequently confident if its confidence value exceeds a threshold The confidence of a rule 1. Find all frequent itemsets.2. Generate strong ARs from the frequent itemsets.Apriori algorithm The number of itemsets grows exponentially with the number of items Apriori is a popular algorithm, its computational complexity becomes intractable for very low value of closed itemsetsAlthough Apriori method is huge since the number of human proteins is 1432 in the data set considered here. This is because the number of possible itemsets to explore is in the order of Apriori algorithm for this data set. Hence, we have proposed a new association rule mining approach based on a biclustering method that efficiently mines the frequent closed itemsets from sparse data sets having low The PPI data set considered in this article is very sparse (only 2534 interacting pairs among 27208 possible protein pairs: 9.31%). Therefore it is required to use low In this section, we first introduce the concept of biclustering and thereafter, the proposed rule mining technique is described.Biclustering technique, usually used in microarray gene expression data, aims to identify a subset of genes that are similarly expressed in a subset of experimental conditions Although biclustering algorithms are in general applied for microarray gene expression data sets, they can be used in any data matrix to discover submatrices with similar values. There are different kinds of biclusters available, viz., constant, row-constant, column-constant, additive pattern, multiplicative pattern, and combination of both additive and multiplicative patterns Suppose a transaction data set is given that contains Among the various biclustering techniques available in literature, we have used Binary inclusion-Maximal (BiMax) biclustering algorithm a priori specification of the number of biclusters to be found.BiMax uses an incremental algorithm to find the inclusion-maximal biclusters exploiting the fact that the matrix Therefore, to find the possible association rules, we use the following steps:1. Given a 2. From each frequent closed Note that for generating the frequent closed itemsets, we ignore the 1-itemsets as they can not produce any association rule. This is done by fixing the minimum number of columns of the biclusters to 2. Moreover, we consider only the rules having single consequent to avoid redundant information, as our primary objective is to predict new PPIs.File S1Excel file containing the 1432 × 19 PPI adjacency matrix with human proteins in rows and HIV-1 proteins in columns.(XLS)Click here for additional data file.File S2Excel file containing the 19 × 1432 PPI adjacency matrix with HIV-1 proteins in rows and human proteins in columns.(XLS)Click here for additional data file.File S3Excel file containing the interactions predicted from HV matrix, from VH matrix and their union.(XLS)Click here for additional data file.File S4Excel file containing intersection of the predicted interactions by the proposed method and that by Tastan et al. .(XLS)Click here for additional data file.