Mycoplasma hyopneumoniae and subsequent sequencing were used to analyse these specimens. Mycoplasma hyopneumoniae-positive samples were assayed by multilocus sequence typing (MLST). The aim of the study was to reveal the distribution of M. hyopneumoniae and determine the genotypes of M. hyopneumoniae in pig herds in China based on MLST.Between 2018 and 2020, 989 clinical specimens from pigs showing clinical signs of a variety of swine diseases in 27 provinces in China were sampled and submitted for further testing. Nested PCR targeting the 16S rRNA gene of M. hyopneumoniae-positive. The M. hyopneumoniae positivity rate was 7.2% (35/494) in 2018, 18.4% (38/207) in 2019, and 43.8% (126/288) in 2020. In total, 47 samples were successfully assayed by MLST. Sixteen new M. hyopneumoniae sequence types from 9 provinces were recorded in the present study.Among these 989 samples, 199 samples were M. hyopneumoniae in swine herds in China. MLST has revealed high genotype diversity among M. hyopneumoniae from different provinces of China.This is the first report on sample positivity rates and molecular typing results for  Mycoplasma hyopneumoniae results in large economic losses worldwide. Isolation and cultivation of M. hyopneumoniae is complicated and time-consuming. Genotyping analysis of clinical materials rather than isolates of M. hyopneumoniae has been very useful in field investigations. Multilocus sequence typing (MLST) [adk, rpoB and tpiA) provides the same resolution as the seven-gene scheme [M. hyopneumoniae infection of pigs in China are rare, thus the aim of the present study was to reveal the distribution of M. hyopneumoniae and determine the genotypes of M. hyopneumoniae in pig herds in China based on MLST.Enzootic pneumonia (EP) in pigs caused by g (MLST) , 2, a mog (MLST) –5. The de scheme . MoleculBetween 2018 and 2020, a total of 989 clinical specimens  from 989 pigs with clinical symptoms of a variety of swine diseases in 215 pig herds in 27 provinces in China were sampled. Each homogenate sample was derived from one pig. Among them, 494 clinical specimens were sampled from 146 herds in 18 provinces in 2018  in accordance with the manufacturer’s protocol. Nested-PCR [M. hyopneumoniae. The first PCR amplified a 649-bp region of the 16S rRNA gene. After the second PCR, DNA segments measuring 352 bp in length were cloned into a pMD18-T vector  and sequenced by the BGI Group . Positive samples were confirmed by using the BLAST (http://blast.ncbi.nlm.nih.gov) and subjected to MLST.sted-PCR  was usedadk, ropB, and tpiA genes were obtained from M. hyopneumoniae-positive samples by Sanger sequencing. In brief, the three genes were amplified by primers and conditions described previously [http://pubmlst.org/mhyopneumoniae) for sequence type (ST) designation. The PubMLST database contains nomenclature-allele definitions that provide an identifier for every unique allele sequence and MLST profiles that index each unique combination of alleles with a ST. Sequences were aligned using the CLUSTAL W and cluster analysis was performed using the neighbour-joining method (Kimura two-parameter method) with Molecular Evolutionary Genetics Analysis (MEGA) software . Bootstrap values were based on 1000 replicates. Values of Simpson’s index of diversity were calculated with the help of the Comparing Partitions website (http://www.comparingpartitions.info/index.php?link=Tool).Nucleotide sequence data of the eviously . The PCRM. hyopneumoniae-positive according to nested PCR and BLAST comparison,. The individual positivity rates for M. hyopneumoniae were 7.2% (35/494) in 2018, 18.4% (38/207) in 2019, and 43.8% (126/288) in 2020. The herd positivity rates for M. hyopneumoniae was 14.4% (21/146) in 2018, 54.2% (13/24) in 2019, and 55.6% (25/45) in 2020. The reason for the large percentage increase in M. hyopneumoniae detection may be that much attention had been paid to prevention and control of African Swine Fever (ASF) since its first outbreak in China in 2018(http://www.oie.int/). Also, vaccination against M. hyopneumoniae is not compulsory and vaccines are not widely used on farms. Another reason may be that a series of policies that reduced and eventually forbid the supplementation of antibiotics in animal feed were announced by the Minstry of Agriculture and Rural Affairs in march,2019.The results showed that 199 of 989 samples were M. hyopneumoniae were complicated by coinfection with other pathogens.Among the 199 samples, only 21 samples were sent with accompanying clinical sign information. These clinical signs included respiratory signs , reproductive signs , neurological signs , and gastrointestinal signs (vomiting or diarrhea). We assumed that most infections with M. hyopneumoniae. Positive samples were detected from pig herds distributed throughout different regions of China  were detected in 47 of 199 M. hyopneumoniae-positive samples distributed among 26 herds. MLST allowed the amplification and sequencing of some individual genes (1–2) among 7 targets. However, the successful sequencing of all 7 targets was not possible for the majority of the samples. It is attributed to the low amount of M. hyopneumoniae DNA or the presence of unknown PCR inhibitors in samples [M. hyopneumoniae in China. Among these, ST128 was the most frequent ST identifed, this ST was found in 6 herds (23.08%) in 4 provinces that were geographically unrelated  were present in different herds in different provinces. Among these provinces, Jiangsu and Guangxi were the farthest apart, at 1600 km. The results imply that free movement of pigs is associated with a high risk for the transmision of M. hyopneumoniae has existed in China for a long time and formed individual cluster. Clade II included ST172, ST169 and STs from Hungary, Switzerland, Greece, and France. Subtype III included ST173, ST130 and STs from the Czech Republic and France. No Chinese STs were present in calde IV. Phylogenetic analysis showed that the 16 new STs were clustered into five clades with 37 STs from 15 countries: Ia, I b, II, III, and IV, as shown in Fig. ST151 and ST149, which were detected in samples from different herds in Guangxi Province were phylogenetically related to ST61 representing Chinese strain 168, but only one of 3 alleles was the same Fig. . This rerpoB gene , were phylogenetically close, with a 2-bp difference in tpiA gene by 4 bp. The three alleles of ST173 and ST130 are different but form a distinct cluster (Fig. M. hyopneumoniae among provinces.ST146 and ST148 are phylogenetically close to ST128, which is the most common ST. ST175 and ST145 are phylogenetically close, differing in the M. hyopneumoniae isolates from different provinces of China. All the samples represented new STs based on the PubMLST database, and we hypothesize that they belong to exclusive Chinese genotypes. ST128, which was present in 4 provinces in different regions of China, was the most common ST in this study. The STs from most provinces are possibly prone to formation of their own cluster via evolution. Phylogenetic analysis showed that the Chinese STs belonged to four clades. It is difficult to elucidate the situation of M. hyopneumoniae in China in the long-term because of the high genotype diversity of the pathogen. This is the first study to report sample positivity rates and molecular typing results of M. hyopneumoniae in swine herds in China. To further understand the epidemiology and possible sources of M. hyopneumoniae, a surveillace plan for the disease should be formulated and implemented, and more samples could be collected and genotyped.Positive samples were detected in pig herds distributed throughout different regions of China. MLST revealed high genotype diversity among


Results were compared to four frequently used equations , in addition to a new equation developed recently at the Academic College at Wingate (Nachmani) for overweight individuals. Estimation accuracy was defined as the percentage of subjects with calculated RMR within ±10% of measured RMR. Measured RMR was significantly underestimated by all equations. The equations of Nachmani and Lührmann had the best estimation accuracy: 71.4% in males and 50.9% in females. Skeletal muscle mass, fat mass, hemoglobin A1c (HbA1c), and the use of insulin explained 70.6% of the variability in measured RMR. RMR in elderly participants with T2DM was higher than that calculated using existing equations. The most accurate equations for this specific population were those developed for obesity or the elderly. Unbalanced T2DM may increase caloric demands in the elderly. It is recommended to adjust the RMR equations used for the target population.Measuring resting metabolic rate (RMR) is time-consuming and expensive, and thus various equations for estimating RMR have been developed. This study’s objective was to compare five equations in elderly people with type 2 diabetes (T2DM). RMR was measured in 90 older adults (≥65 years) with T2DM (mean body mass index (BMI) of 31.5 kg/m The continuous spread of type 2 diabetes mellitus (T2DM) represents a global health threat. It is estimated that 463 million people worldwide had diabetes in 2019, with a predicted increase to 700 million by 2045 ) for VOand VCO2  was usedBody mass was measured using an electronic scale with an accuracy of 0.1 kg. Body height was measured to the nearest 0.1 cm, with the subjects in light clothes and without shoes. FFM, skeletal muscle mass (SMM), and fat mass (FM) were evaluated by direct segmental multi-frequency bioelectrical impendence analysis (BIA) using the InBody 770 apparatus . The measurement suggested by the InBody apparatus was found to be a valid tool for the assessment of total body and segmental body composition .The 5 equations with which the measured RMR (RMRm) was compared are presented in t-test for continuous variables and the chi-squared test for categorical variables. A paired t-test was used to evaluate the mean difference between RMRm and the RMR estimated (RMRe) by equations. The mean difference was expressed as the absolute value  and percentage . Relative bias (%) was calculated as follows: Relative bias = (∆RMRmean bias)/RMRm × 100). Estimation accuracy was calculated for all 5 equations and was defined as the percentage of subjects whose RMRe was within ±10% of RMRm. Phang et al. [mean bias. Linear regression was performed to find the variables that explained RMRm using stepwise methods. Variables entered into the regression were chosen based on their clinical relation to the metabolic state among diabetic and older adults and included: anthropometrics , glycemic control (Hemoglobin A1c (HbA1c); insulin use (yes vs. no)), functional status ). We made sure that there was no co-linearity between the confounders/predictors (over-adjustment) using a Spearman correlation matrix. We considered any between-confounder correlation >0.7 as indicative of co-linearity [p-values were lower than 0.05.Results were analyzed with SPSS Statistics 25 for Windows  and are expressed as the mean ± standard deviation (SD). Differences in participant characteristics between the males and the females were examined by unpaired g et al. . The chiinearity . Results2. Age, BMI, FM, smoking, and FGP did not differ between men and women, while the percentage of FM was lower in the men and FFM was lower in the women.Valid measurement was achieved in 90 participants, including 55 women and 35 men. Baseline characteristics by sex are described in mean bias (median bias) values are shown in Mean RMRm was 1585 ± 214 kcal/day in females and 1888 ± 259 kcal/day in males. Mean RMRm differed significantly from all mean RMRe. In total, all equations, except for the NA equation in males, underestimated RMR significantly compared to RMRm . ∆RMRmeaEstimation accuracy is presented in mean bias. In all equations, the ∆RMRmean bias increased as the RMRm was higher, indicating that there was no stable agreement between the RMRe and RMRm. However, the equations of NA and LU had the lowest ∆RMRmean bias.Bland-Altman plots are presented in There was a clear co-linearity between SMM and FFM (r = 0.998), and both were highly correlated with RMRm (r = 0.76 for both) (data not shown). Therefore, only SMM was entered to the model. Using stepwise linear regression, the variables that explained the RMRm were SMM, FM, and HbA1C and whether receiving insulin (yes or no).The final formula was:The variables which entered the model explained 57.8%, 7.2%, 3.7%, and 2% of the variability, respectively .In the present study, the RMR of older patients with T2DM measured by indirect calorimetry was compared to the RMR estimated by five different equations. Estimating RMR in this population is important due to the increasing prevalence of overweight and obesity and the consequent rising number of individuals suffering from T2DM, as well as the aging of the population worldwide. However, all the examined equations underestimated RMR, and their inaccuracy was in a larger proportion in women as compared to men. Only in male participants were the NA and LU equations able to achieve accurate results .Larger individual errors might be covered by group mean data because high positive errors may counterbalance high negative errors. Therefore, they cannot be utilized for practical decisions in individual patients . For thiGougeon et al.  showed tAlthough the sample from which the LU equation was derived had substantial differences in body composition compared to their counterparts in the current study, it was based on people of a similar age. This equation had the same estimation accuracy as that of NA.mean bias: 25.8 ± 99.4 kcal/day) in their study with obese older subjects. This supports the findings of Krems et al. [Noreik et al.  also fous et al. , indicatGougeon et al.  showed tThe general HB and CU equations performed considerably worse compared to the specific equations. Both underestimated RMR significantly by a mean of more than 200 kcal/day and could only obtain accurate measurements in well below 50% of the subjects. The results of other studies were inconclusive. In some studies, the HB equation significantly overestimated RMR ,34,35,36mean bias and RMRm, whereas a higher RMRm was correlated with a larger RMR difference. A population-specific equation is suggested based on the current sample, which includes traditional variables explaining differences in RMR such as SMM and FM Supported by the Bland-Altman test results, it is possible that inaccuracies between the predicted and measured RMR were derived mainly from participants with higher RMR levels. This was expressed by the fact that there was no consistency in the correlation between the ∆RMRThe current study has several limitations. The recruited subjects do not represent all older adults with T2DM, resulting in a possible selection bias that could have influenced external validity. However, for relatively balanced and young/older adults with T2DM, the current suggested equation may be valid. A larger sample size could have resulted in a better understanding of the reasons for the inaccuracies of the equations using data stratifications.To the best of our knowledge this is the first study examining the accuracy of common equations predicting RMR in older adults with T2DM. The population-specific equations performed substantially better than the two general equations. On the group level, the NA equation produced valid estimates of RMR in males. However, on the individual level none of the equations could achieve accurate estimates of RMR in more than 60% of the subjects. Especially in women, the estimation accuracy was found to be weak. If measurement is not possible, equations derived from a sample as similar as possible (including glycemic status) should be used for older subjects with T2DM. Further research is needed to clarify how the presence of T2DM affects RMR.


Identification of epistatic interactions provides a systematic way for exploring associations among different single nucleotide polymorphism (SNP) and complex diseases. Although considerable progress has been made in epistasis detection, efficiently and accurately identifying epistatic interactions remains a challenge due to the intensive growth of measuring SNP combinations.F1-score on the GWAS datasets of 12 DME disease models and 10 DNME disease models. Our experimental results show that GEP-EpiSeeker outperforms comparative methods.In this work, we formulate the detection of epistatic interactions by a combinational optimization problem, and propose a novel evolutionary-based framework, called GEP-EpiSeeker, to detect epistatic interactions using Gene Expression Programming. In GEP-EpiSeeker, we propose several tailor-made chromosome rules to describe SNP combinations, and incorporate Bayesian network-based fitness evaluation into the evolution of tailor-made chromosomes to find suspected SNP combinations, and adopt the Chi-square test to identify optimal solutions from suspected SNP combinations. Moreover, to improve the convergence and accuracy of the algorithm, we design two genetic operators with multiple and adjacent mutations and an adaptive genetic manipulation method with fuzzy control to efficiently manipulate the evolution of tailor-made chromosomes. We compared GEP-EpiSeeker with state-of-the-art methods including BEAM, BOOST, AntEpiSeeker, MACOED, and EACO in terms of power, recall, precision and Here we presented a novel method named GEP-EpiSeeker, based on the Gene Expression Programming algorithm, to identify epistatic interactions in Genome-wide Association Studies. The results indicate that GEP-EpiSeeker could be a promising alternative to the existing methods in epistasis detection and will provide a new way for accurately identifying epistasis. Genome-wide association studies (GWAS) aim at identifying associations between Single Nucleotide Polymorphism (SNP) and disease, which has been an important way for identifying the genetic basis of diseases in the last decade –11.GWAS is capable of finding single-locus SNP that is related to disease trait . Great pWith the rapid development of high-throughput genotyping and sequencing technologies, it is an enormous challenge to analyze the epistatic associations between disease and millions of SNPs in GWAS. Recently, several epistatic interaction detection methods have been designed for efficiently detecting epistasis. These efforts can be divided into three types , 16–21 :Exhaustive search method evaluates all possible multi-locus SNP combinations to detect the associations between disease and SNPs. Therefore, exhaustive search methods can produce stable and global optimum solutions. Some exhaustive search methods, such as MDR , 23, BOOStochastic search-based identifies SNP-SNP interactions by random sampling , 27. BEAHeuristic search , 14, 30 Recently, in addition to the ACO-based algorithm, some other evolutionary methods have also been adopted for the heuristic search of disease-associated SNPs , 26, 32.Heuristic search has become a popular search strategy of epistatic interactions for its heuristic positive feedback and small search space for the past decades. However, heuristic search sometimes may lose the global optimum solutions for its approximate search strategy.In recent years, Gene Expression Programming (GEP) algorithm is a notable evolutionary algorithm, which is a generalized method of Genetic Algorithm (GA) and Genetic Programming (GP) . It has Motivated by GEP, we propose a novel evolutionary framework based on the GEP algorithm called GEP-EpiSeeker to detect epistatic interactions. Distinguishing from other evolutionary-based methods, GEP-EpiSeeker contains the screening and cleaning stages to find the SNP interactions associated with specific diseases. In the screening stage, we developed a tailor-made Gene Expression Programming algorithm named EpiGEP for screening suspected SNP interactions. In the cleaning stage, we conducted Chi-square tests for each screened SNP combinations produced by EpiGEP to identify the significant epistatic interactions. Fig. F1-score. Furthermore, we investigated the influence of the proposed fuzzy adaptive genetic manipulation rate on GEP-EpiSeeker performance. The simulation datasets for the 22 disease models, evaluation metrics, and parameter setting are introduced in the Methods section in detail.We conducted experiments on 22 simulated disease models containing 12 disease models with marginal effects (DME) and 10 disease models with no marginal effects (DNME) to investigate the performance of GEP-EpiSeeker. The experimental results of GEP-EpiSeeker were compared with the experimental results gained from five state-of-the-art epistasis detection methods including BEAM , BOOST , AntEpiSh2=0.02. Similarly, as shown in Fig. Figures h2=0.01 and MAF=0.2. The results of Fig. Figure F1 on all disease models. Tables F1 on different disease models, respectively. Note that the values in brackets are the p-values of the t-test between results of GEP-EpiSeeker and the corresponding comparative method. As seen from Tables F1, respectively. In terms of recall, GEP-EpiSeeker just slightly underperforms MACOED and EACO on the disease model 7, slightly underperforms EACO on the disease model 9, and has poor performance than MACOED, EACO, and BOOST on the disease model 18. In terms of precision, GEP-EpiSeeker just slightly underperforms MACOED on the disease models 6 and 17. In terms of F1, GEP-EpiSeeker just slightly underperforms MACOED and EACO on the disease models 6, 7, 9, 17, and 18. These results demonstrate that GEP-EpiSeeker outperforms comparative methods on most disease models. Overall, GEP-EpiSeeker is superior to state-of-the-art methods in the experiment. This indicates that the effective optimization of SNP combinations by the GEP algorithm greatly helps to narrow the search space and improve the power of our method. It is also interesting to see in Tables F1 of the results produced by GEP-EpiSeeker achieves better performances than other comparative methods in most settings of DNME and DME models, demonstrating that the results of GEP-EpiSeeker on DNME and DME models are worth exploring, despite not obtaining correspondingly high levels.To comprehensively evaluate the performance of our proposed method, we also compare the performance of the GEP-EpiSeeker and other methods in terms of recall, precision and F1. These results demonstrate that GEP-EpiSeeker performs well in both recall and precision by coupling the EpiGEP algorithm with the Chi-square test.Although the recalls of MACOED and EACO on disease models 7, 9 and 18 are better than those of GEP-EpiSeeker, the precision of GEP-EpiSeeker is higher than that of MACOED and EACO. Similarly, the recalls of BOOST on models 18, 20 and 21 are higher or equal to those of GEP-EpiSeeker, but the precisions of GEP-EpiSeeker on these models are much higher than those of BOOST, thereby resulting in GEP-EpiSeeker’s superior performance in Note that the values in brackets are the p-values of the t-test between results of GEP-EpiSeeker and the corresponding comparative method. The best performances of each disease model are shown in bold and italics.In this section, we investigate whether fuzzy adaptive control will affect the performance of GEP-EpiSeeker. The comparisons on all metrics are based on the average score of 20 times of each epistasis model. Figures In this work, we presented a novel method named GEP-EpiSeeker, based on the Gene Expression Programming algorithm, to identify epistatic interactions in Genome-wide Association Studies. In GEP-EpiSeeker, we proposed several tailor-made chromosome rules to depict SNP combinations, and integrated Bayesian network-based fitness function into the evolution of the chromosomes to search candidate SNP combinations and used the Chi-square test to identify optimal solutions from candidate SNP combinations.F1-score on all datasets. These results indicate that GEP-EpiSeeker could be a promising alternative to the existing methods in epistasis detection and will provide a new way for accurately identifying epistasis.Furthermore, we proposed two genetic operators with multiple and adjacent mutations and an adaptive genetic manipulation method with fuzzy control to improve the convergence and accuracy of our method. We conducted experiments on 22 disease models including 12 DME models and 10 DNME models to evaluate our method. Experimental results show that GEP-EpiSeeker is comparable or even superior to other comparative methods including BEAM, BOOST, AntEpiSeeker, MACOED and EACO in terms of power, recall, precision and Generally, the length of the GEP chromosome grows as the epistatic order increases, which results in a large increase in computation resources. A possible solution for this problem is to implement high-performance parallel algorithms for detecting epistasis interactions, which would be of interest in future work.For solving the epistasis detection problem with high dimension and small sample size, we transformed the identification of disease-causing SNP combinations into a heuristic combinatorial optimization problem. Then, GEP-EpiSeeker formulates SNP combinations using tailor-made GEP chromosome rules for epistasis detections, and discovers candidate SNP combinations by integrating Bayesian fitness evaluation with the tailor-made chromosome evolution, and finds optimal solutions from candidate SNP combinations by the Chi-square test. Furthermore, two genetic operators with multiple and adjacent mutations and an adaptive genetic manipulation method with fuzzy control are proposed to guide the tailor-made chromosome evolution, which helps to improve the convergence and accuracy of the algorithm.In this section, we first briefly introduce the fundamentals of GEP in the first subsection. Then the proposed method GEP-EpiSeeker is introduced in detail, which involves the definitions of tailor-made chromosome and genetic operators, fuzzy adaptive control of genetic manipulation rate, and Bayesian network-based fitness function in the screening stage, and Chi-square tests for cleaning significant epistasis in the cleaning stage. Finally, we introduce the experimental method in this work, which involves the datasets, evaluation metrics for comparing the performance of the comparative methods, and the parameter setting.F, which contains a series of simple functors, and terminator set T, which contains a series of decision variables and constants. The tail only consists of the terminator set. Assuming that the gene head length is h, the tail length t satisfies the following Exp. (1), where n is the maximum arity of the functors in F.Gene Expression Programming (GEP) is an excellent evolutionary algorithm, which is based on the gene expression law of biological genetics , 39. GEP,*,-,+} and terminators {a,b,c,d,2},The GEP chromosome has two forms of expression, one of which is the Karva expression (K-expression), and the other is the expression tree. Each gene in the chromosome can be expressed in a K-expression and an expression tree. Both K-expression and expression trees can be transformed into each other. We can transform the expression tree into K-expression by traversing the expression tree from top to bottom and left to right. Similarly, we can transform K-expression into an expression tree by filling the expression tree layer by layer with the symbols of K-expression from left to right. For example, Exp. (2) is a GEP chromosome with a gene of length 9, which includes functors {Qwhere Q denotes the square-root function. According to GEP algorithm, the expression tree of the chromosome in Exp. (2) is shown in Fig. Each chromosome of GEP can be regarded as a solution of a target problem and is evaluated by the fitness function of GEP. The higher optimal fitness value of the solution is, the better solution represented in the chromosome is. The chromosomes can gradually evolve after a series of genetic manipulations until obtaining a solution with an acceptable fitness value. The genetic manipulation of GEP mainly includes selection, mutation, and crossover. The flowchart of GEP is shown in Fig. In this section, we will elaborate on our GEP-based algorithm named EpiGEP for detecting epistatic interactions. In EpiGEP, we proposed several tailor-made chromosome rules, two new genetic operators, and a tailor-made fitness function, and a genetic manipulation method with adaptive rate to accurately detect epistatic interactions. Fig. k-way SNP interaction combination that is associated with disease status Y. Recall that each gene in the GEP chromosome consists of a head and a tail. In EpiGEP, each gene consists of a head, a tail and an GT domain. The GT domain represents a genotype of one SNP. Let Chri be ith chromosome in a population with L chromosomes, i=1, 2, …, L. The chromosome Chri can be described by Exp. (4):In EpiGEP, each chromosome in a population is a candidate solution of a Sij is the jth SNP in the SNP dataset, j=1, 2…, k; Gtij is the variable of Sij genotypes with values of {0,1,2};  indicates a gene of the chromosome Chri.where Chrk. Chrk is the kth chromosome with head length h=3 in a population, which is described as a 2-way SNP interaction combination with genotypes 0 and 2. In Exp. (5), Chrk includes two genes:  and . In gene , the head is “*- +”, the tail is “1825” and the GT domain is “0”.Exp. (5) gives an example of an EpiGEP chromosome k-way  SNP interaction combination can be described by Exp. (4). In order to map each EpiGEP chromosome into a valid solution in SNP interaction detections, we define several idealized rules:, n}, n is the total number of SNP in the dataset.EpiGEP only uses functors {+,-,*, /} and terminators {1, 2,…Six and Siy in a chromosome must not be identical (x≠y), or else this chromosome has to be mutated to get a new valid solution. The adjacent mutation is preferable (see section 3.2.2 for details).Each chromosome in EpiGEP cannot contain identical SNP markers. The decoding result of When EpiGEP decoding the expression trees of genes, the decoding results will be performed modulo by the number of SNP in the dataset. EpiGEP takes the absolute value of the modulo results as the final results.In EpiGEP, any th and 29th loci of SNP, respectively. Then a candidate SNP interaction combination of Si49 and Si29 can be derived from the decoding results of these expression trees.The EpiGEP chromosome of Exp.(5) can be encoded into expression trees and these trees are shown in Fig. The adjacent mutation performs mutation when a random number between 0 and 1 is smaller than the given threshold value called adjacent mutation rate;The adjacent mutation aims at refining the solutions with the neighborhoods of the current solution. To achieve this goal, the adjacent mutation only mutates at the tail or the GT domain of the objective gene. When adjacent mutation takes at the tail, the adjacent mutation randomly replaces the locus of the mutation point with one of the neighboring loci of the mutation point. When adjacent mutation takes at the GT domain, the adjacent mutation replaces the genotype with one of the rest genotypes.EpiGEP inherits the genetic operators of GEP and expands two new genetic operators including adjacent mutation and multi-gene mutation to improve epistatic interaction detection. There are considerable correlations among neighboring SNPs in the genome as measure by linkage disequilibrium (LD) . This isIn addition, we proposed another novel genetic operator Multi-gene mutation for EpiGEP. Multi-gene mutation simultaneously implements mutation operation on multiple points of different genes. The Multi-gene mutation could increase the diversity of population, assisting EpiGEP to jump out of the current search area, which avoids EpiGEP falling into local optimum to some extent and finally enhances the global exploration power of EpiGEP.The crossover rate of evolutionary algorithms will largely influence their convergence efficiency, while the mutation rate determines whether the algorithms can globally find the optimal solution out of the local optimum solution or not . NeverthIn this work, we use a fuzzy control method to dynamically and automatically adjust the genetic manipulation rates of EpiGEP to find the globally optimum solution out of the local optimum solution.d of optimal fitness (Fbest) to average fitness (Fave) of the current population. Equation , the joint probability distribution for the m+1 nodes can be calculated as the following [A Bayesian network (BN) is a probabilistic directed graphical model . In the ollowing , 6:8\docpa(xi) denotes the set of parent nodes of xi. An instance of m-SNP epistasis BN model is given in Fig. m-SNP epistasis BN model, the total number of combinations of SNP and disease state is n is the total number of SNP in the SNP set.where In EpiGEP, we take the K2 score given in  as the fI is the total number of SNP combinations, and I=3m as the possible values of SNP node are 0, 1 or 2. J denotes the state number of disease nodes [ri is the number of ith SNP combination and rij denotes the number of ith SNP combination connected with jth disease state [m-locus epistasis detection in MACOED [m can be set as a positive integer larger than 1 according to the users’ requirement.where se state . K2 scorn MACOED , but theP-value of the Chi-square test is smaller than 0.05 [In the screening stage, GEP-EpiSeeker gets a candidate solution set that consists of all suspected disease-causing SNP combinations. In the cleaning stage, the task of GEP-EpiSeeker is to identify the real disease-causing SNP combinations from candidate solutions. Previous researches , 41 showhan 0.05 , 41.We used 22 GWAS datasets corresponding to 22 epistasis models as GWAS datasets, which were generated by the classic simulation software GAMETES 2.0 . GAMETESα and β are used to control the penetrance table. The disease prevalence P(D), the genetic heritability h2 and the minor allele frequency MAF can be determined by α and β [P(D)=0.1. In the experiments, the multiplicative models, threshold models and concrete models are named as model 1 ~ model 4, model 5 ~ model 8, model 9 ~ model 12, respectively.The 12 DME models contain three types of DME epistasis models including 4 multiplicative models, 4 threshold models and 4 concrete models. These 12 DME models are produced by three different penetrance functions. These penetrance functions of the 12 DME epistasis models are shown in Table  α and β . In thisThe 10 DNME models (model 13 ~ model 22) are limited to the Hardy-Weinberg equilibrium (HWE) constraints but not limited to specific predetermined models. The penetrance table of the DNME models was produced by an exhaustive search.Table F1-score (F1) to evaluate the performance of these comparative methods. These metrics are defined as follows:In this section, we compare the performance of GEP-EpiSeeker with other representative methods , 27, 30.Ns is the number of identified disease-causing models from all Nd datasets . TP denotes the number of SNP combinations associated with disease verified by the comparative algorithm, where the P-value of the Chi-square test is smaller than the given threshold (P<0.05). FN denotes the number of SNP combinations that are truly associated with disease but are identified as not associated with disease by the algorithm. FP denotes the number of SNP combinations that are not associated with disease but are identified as disease-related by the algorithm.where For each epistasis model and comparative method, it was independently run 20 times with the same 100 data files in our experiment to avoid stochastic deviation. For each epistasis model, we conducted some t-tests on 20 results of each method to validate the performance of the comparative models and GEP-EpiSeeker.population_size=100, number_of_iteration=1000, head_length=5, initial_genetic_manipulation_rate = 0.3. EpiGEP will terminate when the number of iteration N_i >1000. For a k-locus epistasis detection, the number of gene N_g in an EpiGEP chromosome is k.Since the Elitism mechanism can guarantee the global convergence of GEP , EpiGEP The parameters for BEAM and BOOST were set as the default of the BEAM and BOOST packages, respectively. Due to AntEpiSeeker, EACO and MACOED being three ACO-based methods, the parameter settings of these ACO-based methods were the same to conduct a fair comparison. The ant number and iteration number were set to 200 and 1000, respectively; the initial pheromone τ0 was set to 100; the parameters and that determine the weights of pheromone and heuristic information were set to 1. The evaporation coefficient of pheromones was set to 0.3. In addition, the rest of parameter settings for AntEpiSeeker were: largesetsize = 6, smallsetsize = 3, iItCountLarge = 150, iItCountSmall = 300.


The Health Assembly called upon the World Health Organization to develop an evidence-based world report on hearing that provides guidance to Member States for improving access to ear- and hearing-care services. The report, developed through a multistakeholder consultative process, and published in March this year, reveals that by 2050 nearly 2.5 billion people will be living with some degree of hearing loss; of these, at least 700 million will require rehabilitation services.The report highlights why investing in preventing and addressing hearing loss is warranted at this time. First, across the life course, hearing loss can be prevented. Over a billion young individuals are at risk of avoidable hearing loss associated with recreational use of personal devices,–The report further elucidates the huge gap in services for ear and hearing care in all parts of the world. For example, there is an estimated gap of 83% between the need for and access to services for such care – taking hearing aid use as a tracer indicator.World report on hearing proposes such a package of interventionsThese challenges can be overcome through strategic government-led planning that integrates people-centred ear and hearing care within national health plans for universal health coverage (UHC). Care services can be implemented through adoption of established public health approaches such as task-sharing and telemedicine. Countries can deliver such people-centred care throughout the life course by ensuring access to evidence-based interventions that are delivered through a strengthened health system. The Without integrated people-centred ear and hearing care, governments risk depriving their citizens of the right to achieve the highest possible standard of health, functioning and well-being; and of the possibility of communicating optimally with others. The report on hearing presents a call to action, inviting Member States to work for the needs of all those who need ear and hearing care and to achieve the target of a 20% relative increase in effective coverage of such services by 2030.


The use of the endoscope in otological surgeries has both diagnostic and therapeutic values. It provides an excellent view in difficult nooks and corners. The use of endoscopic sandwich myringoplasty using cartilage and perichondrium has its benefit in hearing outcome and graft uptake in long-term follow-up. The main objective was to compare the long-term with short- term hearing outcomes in those who have undergone endoscopic sandwich myringoplasty with Dhulikhel hospital (D‑HOS) technique.Forty-two patients who underwent endoscopic sandwich myringoplasty with D-HOS technique using tragal cartilage perichondrium were enrolled in the study. The hearing outcome was analyzed by comparing the pre-operative findings with post-operative findings and amongst post-operative patients, long-term with short-term air bone gap (ABG) and ABG closure in speech frequencies  were compared. Amongst forty-two patients, 40 (95.2%) had graft uptake in both short-term (6.08 months) and in long-term (20 months) follow-up. The mean pre-operative ABG was 28.1±9.3dB whereas the mean short-term post-operative ABG was 14.5±7.2dB, it showed statistical significance (P=0.001). Likewise, while comparing pre-operative with long-term post-operative ABG (13.4±4.8 dB), it showed statistical significance of P=0.000. While comparing short-term with long-term post-operative ABG, it did not show any statistical significance (P=0.065).The mean closure in ABG in both short-term and long-term hearing assessment was not statistically significant (P=0.077).Endoscopic sandwich myringoplasty with D-HOS technique is a reliable procedure with good hearing outcome and graft uptake in both short and long-term follow-up. An endoscope is nowadays commonly used in otological surgery as it provides better optics, magnification, adequate visualization and helps proper evaluation of the perforation margins, despite the narrow external auditory canal ‑4. For tEavey first described myringoplasty with the butterfly technique in children with the use of cartilage . Tos M. st July 2017 to 1st July 2020. Informed consent was taken from the patients before conducting the study. The inclusion criteria were: age ≥18 years, gender (both), and patient with chronic otitis media mucosal inactive type. Exclusion criteria were: Mixed or sensorineural hearing loss, revision cases, graft failure, medical or surgical conditions, or treatment that may affect the outcome.This was a prospective and cohort study conducted from 1The data collection was done in pre-operative and then in the six and twenty months post-operatively.Pre-operatively clinical examination of ear, nose, and throat was done. Ear examination under microscope, and tuning fork tests were also performed.Hearing assessmentFor the hearing analysis, a pure‑tone audiogram (PTA) was performed by MAICO MA 41 (Germany) diagnostic audiometer in a sound‑treated double room set up, 7 days prior to the surgery and then after 6 months and 20 months post-operatively. The hearing was analyzed by comparing pre-operative with post-operative air bone gap (ABG) and ABG closure in four speech frequencies . The audiological outcome was recorded as per the guidelines given by the American Academy of Otolaryngology and Head and Neck Surgery .For the surgical procedurePre-operative workout of the patientTablet Ciprofloxacin 500 mg 12 hourly was given orally to the patient a day prior to the surgery and was continued till 7th post-operative day. The surgery was performed under local anesthesia and patients were also given promethazine along with pethidine intramuscularly for sedation which was calculated as per their body weight.Surgical techniqueFive to ten milliliter of 2% Lignocaine with 1:200,000 adrenaline was injected on the tragus and four-quadrants of the ear for ear canal block. The (Karl Storz) Hopkins II rigid endoscope both 0° and 30° with a diameter of 4mm and length of 16cm was inserted permeatally to assess the status of tympanic membrane perforation, middle ear mucosa, the ossicular chain, and the eustachian tube opening. The straight needle was used to refresh the perforation margin . In condFor harvesting of sandwich graft). Prolene suture (4/0) was used for closing the skin incision. The incision on the skin was given directly to the tragus cartilage. The operating surgeon dissected the cartilage along with the perichondrium both medially and laterally with the tympanoplasty scissor. During the procedure, the assistant held the tissue with non–tooth forceps as described in surgical video  Client Version: 4.0.0.14, Pro edition, DB version : INNOFORCE creative solutions, ENT statistics DBIII-3. 0-492 from Liechtenstein, 2019, was used. For analyzing the data, the student’s t‑test was used and the p-value of < 0.05 was set for significance level.Ethical clearanceThe ethical clearance was taken from the Review Committee of Kathmandu University School of Medical Sciences, Dhulikhel (IRC-KUSMS: 34/18). The study was performed as per the Helsinki Declaration principle.A total of 42 patients were enrolled in the study. Among them, two cases had perforated tympanic membrane after surgery due to infection, and hence, only 40 patients were included. Among them, 18 were males and 22 were females. The age distribution ranged from 18 to 55 years with 25.1 ± 1.09 years. The graft uptake rate was 95.2% in both the short-term (6.08 months) and in long-term (20 months) follow-up. We did not observe other complications like blunting of anterior angle, lateralization of graft, myringitis or cholesteatoma formation, sensorineural hearing loss, vertigo, tinnitus, or facial palsy during 20 months follow-up period. The surgical time was 30±13 minutes from skin incision to graft placement. The pre and post‑operative hearing level (HL) is shown in As shown in This study focuses on the surgical outcome and audiological results following endoscopic sandwich myringoplasty with D‑HOS technique in 40 patients. In our technique, we modified in a way, that the perforated tympanic membrane’s lateral part was covered by the elevated part of the perichondrium and the intact cartilage with perichondrium lied medial to the perforation, thus sandwiching the tympanic membrane between cartilage with perichondrium medially and only perichondrium laterally. This particular technique gave stability to the graft and also avoided variation in position of the graft. The tympanic membrane covered laterally by the perichondrium worked as a scaffold for the outer migration of squamous epithelium . We obseThe advantages of our technique are:It is more comfortable technique as there is no need to raise the tympanomeatal flap and less time consuming. The perforated tympanic membrane was sandwiched on either side maintaining the graft position without support, either from the outer canal or the middle ear and there was very minimal oozing .There are certain disadvantages we noticed:Learning curve is more, it requires the exact measurement of the tympanic membrane perforation for preparing the graft, lots of practice is needed in precisely raising the perichondrium flap at lateral side to make island at the center area of the cartilage. Learning curve for using the endoscope is more as it is a single-handed technique; and finally, the theoretical disadvantages of using the cartilage is that it causes opaque appearance of tympanic membrane and can hide the disease in the middle ear cavity .The possth post-operative month in adult group  has both good short-term as well as long-term hearing results. Apart from that, it has an excellent graft uptake rate. It is less time consuming and has very good cosmesis. Hence, we recommend to perform this technique.


Vitis vinifera L.) Pinot noir and Cabernet Sauvignon seeds over a 24-h incubation period. Only freezing significantly increased seed browning in both cultivars. Subsequent correlations with seed flavan-3-ol monomer concentrations suggest that freezing enhanced the oxidation of these compounds. Interestingly, natural ripening and freezing reduced galloylated flavan-3-ol monomers to a greater extent than non-galloylated ones. This study provides new information regarding the susceptibility of flavan-3-ol monomers to freezing and heating, and also suggests that freezing can advance the maturation the seeds of under-ripe red vinifera grapes.In cool-climate viticulture, the short growing season can influence grape seed maturation by reducing the apparent oxidation of flavan-3-ol monomers and associated increase in seed browning. A reduction in seed maturation increases the potential extraction of flavan-3-ol monomers into wine during maceration operations, heightening bitterness. Here, we carried out a 2 × 2 factorial experiment to test the ability of freezing and heating treatments to advance maturation  of ( The seed color change is also accompanied by seed water loss and a reduction in seed weight3. Grape seed phenolics are predominately represented by flavan-3-ols4. The compounds most susceptible to oxidation are those having the ortho-dihydroxy substitution pattern, particularly those in large concentrations such as ( +)-catechin, (−)-epicatechin, and epicatechin-3-O-gallate6. Oxidative polymerization leads to an apparent decrease in the mean degree of polymerization (mDP) of seed tannins during berry ripening7, which decreases their extractability in wine9.During grape ripening, seeds shift in color from yellow to dark brown. The change in color has been associated with the oxidation of phenolic compounds, which are located in the outer integument cell layer10. Likewise, seed removal in Monastrell wines decreased color intensity11. Canals et al. revealed the positive relationship between seed presence and wine anthocyanin content, and also showed a correlation with wine astringency and bitterness12. The total concentration of seed phenolics in wine was related to increased wine bitterness, but not astringency13, however, more recent work showed that cultivars having a greater proportion of seed weight to berry weight produce more astringent wines14. Additionally, high concentrations of seed phenolics mask desirable wine aromas16. This may be why Sáenz-Navajas et al. revealed that the presence of astringency-related phenolics, including procyanidins, correlated negatively with consumer preference of red wine17. Together, this information suggests that while flavan-3-ols are important to red wine color and organoleptic properties, excessive concentrations can compromise wine flavour and quality.The influence of grape seed tannins on wine quality has been investigated thoroughly through studies that either add or remove grape seeds or seed-derived tannins to wine. The presence of seed tannins improved the color and pigmented polymer stability of Cabernet Sauvignon wines compared to tannins from skins or without tannin fractions from either seeds or skinsvinifera cultivars can fail to reach harvest-quality maturity18. This results in low sugar concentrations and pH in the fruit, the latter of which exacerbates astringency perception in the final wine19. Additionally, seeds of underripe fruit contain higher and more extractable seed flavan-3-ol monomers, as well as procyanidin concentrations with a greater mDP22, which can negatively impact wine quality due to increased astringency and bitterness25. In cool climate viticulture, grapevines are manipulated using management practices to advance ripening and improve harvest fruit quality29. However, these approaches have little effect on seed maturity32, which presents a unique challenge for winemakers. This suggests the need for a technique to alter bitter and astringent flavan-3-ols compounds to improve red wines made with underripe fruit. One such enological approach is to remove seeds from red wine ferments that sink to the bottom of fermentation tanks to limit extraction of seed flavan-3-ols . Lee et al. reported a slight decrease in terminal galloylated catechins using this approach, and a subsequent increase in mDP; however, little difference in wine chemistry and quality were observed33. Based on these results, it was hypothesized that flavan-3-ols from seeds are thoroughly extracted from seeds prior to settling34. Likewise, other enological approaches to improve tannin quality in red wine have fallen short of addressing this issue35.In seasons with low growing degree day accumulation, cool climate-grown red Vitis vinifera L. cultivars36. We hypothesized that this was due to enhanced oxidation of phenolic compounds. In a second study, we observed that the change in seed color accompanied a significant alteration in phenolic compounds. This suggested that ethanol extractable phenolics likely present in the vacuole were significantly reduced37. This was confirmed by microscopy images, which revealed dark masses near cells with compromised structure; indicative of phenolic oxidation37. In the current study, we expanded the experimental design and evaluated the seed extract phenolics to understand how concentrations of individual flavan-3-ols respond to “freezing,” “heating” (thawing temperature), and “incubation time” (thawing time). Our hypothesis was that, in addition to freezing, the higher thawing temperature and greater thawing time would enhance flavan-3-ol oxidation and advance the maturation of both Pinot noir and Cabernet Sauvignon seeds.Our previous work reported that a “freeze–thaw” treatment advanced the maturation of grape seeds by browning the seed coat of ten red vinifera cultivars39. This result may also reflect the larger size of PN seeds compared to other vinifera cultivars, and therefore, a difference between PN and CS in the extractability of flavan-3-ols and their susceptibility to oxidation4. Finally, PN berries were slightly less ripe (−1.5°Brix) than CS despite harvesting fruit based on identical maturity in the field, which could influence the impact of natural ripening  was calculated to link all the three colorimeter parameters and better visualize the change in seed color during natural ripening and in response to treatments. Natural ripening led to a significant decrease in individual colorimeter parameters as well as in seed browning (lower index) in both PN and CS 41. This suggests that the substantial oxidation and polymerization experienced by these compounds during fruit ripening may also influence their cultivar-dependent concentrations2. Meanwhile, alterations in mono-galloylated flavan-3-ols are thought to be more season-dependent41.Among variables in this experiment, cultivar accounted for the largest variability in the seed extract flavan-3-ol profile Table . The majO-gallate, a result observed previously42. Additionally, there was a less visible effect on non-galloylated compounds. This led to both parameters having a significant impact on the ratio of galloylated to non-galloylated flavan-3-ols  compared to non-galloylated ones, such as catechin and epicatechin45. However, the oxygen radical absorbance capacity (ORAC) assay revealed the opposite trend46. This difference in antioxidant results may lie in the enhanced ability of galloylated flavan-3-ols to penetrate lipid bilayers due to their more lipophilic nature47. Our previous work showed that freezing disrupts cell membranes and walls37, suggesting that this may allow galloylated compounds to become exposed to oxygen. Additionally, flavan-3-ols with galloyl groups were less stable at neutral pH25. More recently, Kim et al. revealed that phenolics with a pyrogallol group were highly oxidizable under a pH  1048. This suggests that seeds out of wine-like (low pH) solution may promote oxidation of galloylated phenolics.In general, natural ripening and freezing treatments induced a larger relative change to galloylated compounds compared to non-galloylated ones Fig. , 3. WithHeating treatment had an inconsistent effect on individual flavan-3-ol compounds. B-type, C-type procyanidins, and total procyanidins were significantly increased and decreased in PN and CS, respectively  are displayed in Table 6. It is well established that galloylated flavan-3-ols are a source of astringency in red grapes wines49. Flavan-3-ol monomers are also well known to impact bitterness in wine17. The results from this study provide some implications for wine quality based on these facts. Wines made with seeds subjected to freezing treatment should be less bitter and astringent due to the significant decrease in galloylated phenolics, which are also understood to more strongly interact with bitter taste receptors due to their lipophilic nature25. However, freezing may in turn promote oxidative polymerization of procyanidins; a process known to enhance wine astringency24. The degree of procyanidin polymerization and galloylation were not analyzed in this study but will be a focus of future works. Likewise, given the potential differences in treatment effectiveness in must or wine solution50, future works will consider this aspect to truly understand whether this technique could positively influence red wine quality.Grape growers often utilize seed color and organoleptic properties as a basis for harvest maturity of fruits. This study reveals that seed color may not a be a sufficient marker alone to determine grape ripeness due to the large variability among cultivars in the concentration of compounds related to both of these parametersvinifera cultivars. Future works should evaluate the oenological potential of this technique.To conclude, this work characterized the response of seed flavan-3-ols to natural ripening and several treatments aimed to advance the maturation of seeds of Pinot noir and Cabernet Sauvignon. Seeds were separated from fruits and subjected to a 24-h time-course study following the subjugation of seeds to 2 × 2 factorial treatments of no freezing (20 °C) or freezing (−20 °C) prior to the time-course and no heating (20 °C) or heating (40 °C) during the time course. Cultivar had a large impact on the concentrations of non-galloylated flavan-3-ols, while natural ripening and freezing had a greater effect on galloylated flavan-3-ols than non-galloylated ones. Finally, heating induced negligible changes to compounds, but primarily non-galloylated ones. This study provides new information regarding the sensitivity of flavan-3-ols oxidation to freezing and heating, and suggests a novel approach to improve the quality of seed-derived flavan-3-ols in underripe red 37, two Vitis vinifera L. cultivars were chosen for the experiment; Pinot noir (PN) and Cabernet Sauvignon (CS), which display high and low seed flavan-3-ol monomer and procyanidin concentrations during maturation, respectively4. PN and CS fruit used for the experiment were collected in a commercial vineyard located in Southwest Michigan, 12 Corners Vineyards and Winery, Benton Harbor, MI, 49022, United States  during the 2019 growing season. At veraison  and harvest , 15 representative basal clusters were sampled for each cultivar, placed in plastic bags, and returned immediately to campus in coolers.Based on our previous studies evaluating the impact of a “freeze–thaw” treatment on seed color and phenolics change®, and immediately evaluated for color analysis (2.4). Meanwhile, juice was stored for later analysis of basic fruit quality components (2.3). Each group of 100 berries was randomly assigned to one of four treatments, with each treatment having three replications. The first treatment (T20I20), considered as the control, consisted of seeds subjected to “no freezing” (20 °C) and incubation at 20 °C. The second treatment (T20I40) was also not frozen (20 °C) but incubation at 40 °C. For the third treatment (T-20I20), seeds were frozen at − 20 °C (T-20) for 12 h and then incubated at 20 °C. The fourth treatment (T-20I40) included freezing seeds at − 20 °C for 12 h and incubation at 40 °C. Following seed removal and cleaning, seeds from each treatment were spread in a single layer across a 6 cm plastic weigh boat and incubated for 24 h. For I40 treatments, weigh boats containing seeds were kept in a laboratory convection oven at 40 °C and removed only for measurements during the time course study. For T-20 treatments, seeds in weight boats were placed in a − 20 °C freezer over-night (12 h) to ensure complete freezing of tissues. The following morning, weigh boats were removed from the freezer, and the time course study was initiated. The time course study consisted of taking seed colorimeter and chemical analysis samples at 0 min, 5 min, 1 h, 3 h, 6 h, and 24 h during the incubation time. At each point, seeds were weighed, mixed within the weigh boat, subjected to color and chemical analysis, and quickly returned to the incubation experimental treatments.The experiment was conducted according to a 2 × 2 factorial design  with two cultivars  and two sampling times . From the clusters collected at each sampling time, 1,200 berries were selected (for each cultivar) and distributed equally among 12 trays representing three replications of four treatments. The groups of 100 berries were manually adjusted to reach a similar weight and average berry color. Groups were then placed in separate Ziploc® bags and crushed. The seeds were separated from the pulp, rinsed with DI water, blotted dry with a KimWipeg prior to analysis. Total soluble solids and total acidity  were analysed with an ATAGO digital refractometer specific to grape  and pH was measured with a 370 Thermo Orion pH meter .Juice of PN and CS fruit previously placed in a 50 mL centrifuge tube was allowed to reach room temperature. Then, juice was centrifuged at 20 °C for 5 min at 1000×37. The following factor loading coefficients  were produced from the dataset.Immediately after seed preparation, seeds were placed on a plastic weigh boat for incubation. Color measures occurred after 5 min, 1 h, 3 h, 6 h and 24 h during the incubation and after the freezing treatment. At each time point, a Konica Minolta Chroma Meter CR-400  was used to measure the seed color, and the weigh boat was not visible through the seeds. Afterward, seeds were mixed and re-settled into the weigh boat. This process was repeated an additional nine times, and the 10 technical replicates were averaged. These average values from each parameter  for all samples were combined into a single color index parameter using factor analysis according to our previous work( +)-catechin and procyanidin B1 were used to quantify classes of flavan-3-ol monomers and procyanidins, respectively.After the analysis of seed color at each time point, a subsample of 20 seeds from each treatment at different time points during the incubation time were placed in a 50 mL centrifuge tube containing 20 mL of extract solution  to extract seed flavan-3-ols. The covered tubes were wrapped with aluminum foil to prevent exposure to light and placed on a rotating platform at room temperature (20 °C) for 24 h. After 24 h, the extract solution was poured into another tube and stored at −20 °C, while 15 mL of new extraction solution was added to the seeds and rotated for three hours. After this time, the extract solutions were combined and stored at −20 °C. The extract solution was subjected to LC–MS using a Waters Acquity UHPLC interfaced to a Waters Xevo G2-XS Q-ToF mass spectrometer. Sample (10 μL) was injected onto a Waters HSS-T3 UHPLC column  held at 40 °C using a binary gradient of water with 0.1% v/v formic acid (solvent A) and acetonitrile (solvent B). The solvent flow rate was 0.3 mL/min; it was started at time 0 with 100% A, held for 0.5 min at 100% A, ramped to 50% B at 6 min, ramped to 99% B at 6.5 min, held at 99% B until 8.5 min, reverted back to the starting condition of 100% A at 8.51 min, and held until 10 min. Compounds were ionized by electrospray ionization in negative-ion mode with a capillary voltage of 3.0 kV, a cone voltage at 35 V, a source temperature of 100 °C, and a desolvation temperature of 350 °C. Data were acquired using a data-independent MSE method that consisted of two separate acquisition functions, one with no collision energy and the other with a collision-energy ramp of 20 − 80 V. Compounds were identified on the basis of their accurate masses, relative retention times, and fragmentation patterns. Peak areas were obtained using Quanlynx (part of the Waters Masslynx software). Standards of 37, and statistical analysis was conducted using SPSS statistical software . The heatmaps were generated using RStudio version 3.6.238 and data from treatments tested for significance from the control treatment using t-test (p = 0.05). Our experimental research and field studies on cultivated plants, complies with relevant institutional, national, and international guidelines and legislation.The color index (CI) was determined according to our previous workSupplementary Figures.Supplementary Information.


According to the World Health Organization (WHO), hearing loss (HL) affects up to 15% of the world’s adult population. Coping and personality are hypothesized to underlie quality of life (QoL) and distress scores. We aimed to study the importance of personality and coping in persons with HL for self-reported hearing disability, QoL, and distress.A cross-sectional survey was carried out, including one hundred and fifty-eight adults seeking hearing aids. Pure-tone average hearing thresholds (PTA) were determined for each ear. A revised version of the Abbreviated Profile of Hearing Aid Benefit (APHAB) served as a measure of self-reported hearing disability. Further, the generic part of the European Organization for Research and Treatment (EORTC) QoL questionnaire and the General Health Questionnaire (GHQ) (distress measure) were answered. Levels of neuroticism and the Theoretically Originated Measure of the Cognitive Activation Theory of Stress (TOMCATS) coping expectancy were determined.Hearing disability was determined by PTA (better ear) and level of neuroticism. Distress and QoL were determined by neuroticism and coping.More neuroticism was associated with worse outcome for the variables hearing disability, distress, and QoL. Helplessness and hopelessness were associated with worse hearing disability, increased distress, and lowered QoL. Patient reported hearing disability was also associated with PTA (better ear). There is a need to investigate further the associations between hearing disability and QoL to psychosocial parameters. According to the World Health Organization (WHO), hearing loss (HL) affects up to 15% of the world`s adult population, with 5.3% having disabling HL (> 40 dB HL in the better ear). The prevalence and severity of HL increases with age, mostly because of age-related HL, referred to as presbyacusis .HL in adults is usually assessed by pure-tone audiometry. It is, however, also recommended to ask the patient about their self-perceived degree of hearing disability. This is most often done by a few anamnestic questions, but it can also be done using questionnaires. Using such questionnaires provides more stringent measurements, and it could be argued that they should be used more frequently than presently, especially since they are even included in the European standard for “Services offered by hearing aid professionals” (EN 15927:2010). One way to assess the self-perceived degree of hearing disability is by administrating a shortened and revised version of the Abbreviated Profile of Hearing Aid Benefit (APHAB) , where tPatient-reported outcome measures (PROMs), including measures of patient-reported quality of life (QoL) are important when assessing both the primary consequences of a disability and the outcome of treatment and rehabilitation . It has The US National Comprehensive Cancer Network defines psychological distress as “an unpleasant emotional experience of a psychological, social, or spiritual nature”. Distress extends along a continuum, ranging from common normal feelings of vulnerability, sadness, and fear to problems that can become disabling, such as depression, anxiety, panic, social isolation, and spiritual crisis . Within There are several psychosocial factors that may potentially influence QoL measures. These are, for example, stressors and individual personality traits. Selye  related Personality may be defined as those characteristics of a person that account for consistent patterns of feelings, thinking, and behavior , 17. PerThe relationships between personality traits, choice of coping, and QoL have been studied among patients with cochlear implants (CI). Muigg and colleagues  found thQoL in individuals with HL thus seems to represent a complex measure. Individual variation in QoL may be constructed from personality traits, i.e., neuroticism and choice of coping. These factors may account for some of the QoL variation seen in different respondent groups , includiHence, the main aims of this investigation were to investigate any relationship between hearing disability, pure-tone audiometry, QoL, distress, choice of coping, and personality among subjects with HL referred for first time fitting or renewal of hearing aids (HAs). We hypothesize that QoL, hearing disability and distress in persons with HL are associated with the level of neuroticism and with coping expectancy.Three hundred and one patients were invited to participate in the study by letter before a planned consultation. Both first-time HA users, and patients referred for HA renewals were invited. Invited subjects were adults (age 18–78 years) with HL judged in need for HA fitting at Haukeland University Hospital located in western Norway. In Norway, citizens with hearing loss have a legal right to two hearing aids every six years. Costs of the hearing aids and repairs are covered by the government. One hundred and fifty-eight patients returned the questionnaires (response rate of 52.5%); Table n = 135) or unilateral HL (n = 23) was determined. A better ear with pure-tone hearing thresholds equal to or better than 25 dB HL at octave frequencies 0.125–8 kHz and a worse ear with a PTA ≥ 25 dB HL defined unilateral hearing loss. Experienced hearing aid users (n = 71) were currently fitted with a variety of HAs, in-the-ear (11.1%), behind-the-ear (80%), or bi-CROSS systems (8.9%). A similar distribution of fittings was planned for the first-time HA users (n = 87), with 19% in-the-ear, 76.2% behind-the-ear, and 4.8% bi-CROSS systems.Demographic data and information regarding diagnosis and pure-tone audiograms were collected from medical records. Audiograms were obtained during visits to the clinic, and all equipment was calibrated according to ISO-389-1 . The patAn overview of all included questionnaires is given in Table As a measure of hearing disability, the present study utilized a revised and shortened version of the Norwegian translation of APHAB that examines self-assessed communication ability in both quiet and adverse listening conditions. The queThe general QoL was assessed using the European organization for research and treatment (EORTC) core quality of life QLQ-C30) questionnaire [ questionThe general health questionnaire (GHQ)-12 was used to assess the level of distress . This quThe theoretically originated measure of the cognitive activation theory of stress (TOMCATS) questionnaire was used to measure the degree of general response outcome expectancies as described in the cognitive activation theory of stress (CATS) . This quThe neuroticism dimension of the Eysenck personality inventory was determined . The neuPatients completed the questionnaires by pen and paper at home, and the questionnaires were returned by regular mail. Questionnaires were typically mailed to patients three to four weeks before the hearing aid fitting, and they were encouraged to return the questionnaires within one week. Thus, the data were collected within one month before the hearing aid fitting. For questionnaires that use mean sum scores, scores were not calculated if single items were missing.Statistical analyses were performed using the statistical program package IBM SPSS . Associations between variables were investigated using Pearson product-moment correlation coefficients (Pearson`s r) and partial correlations. The Fisher r-to-z transformation applied a value of z to assess the significance of the difference between the correlation coefficients . The linearity of the relationship between dependent and independent variables was tested with a bivariate plot of the standardized residuals and standardized predicted values. Then, by fitting a Loess curve through the scatterplot, it was ensured that the relationship between standardized predicted and residuals was linear around zero. Further, the normality of residuals was tested by comparing the observed cumulative distribution function (CDF) of standardized residuals to the expected CDF of a normal distribution, using a P–P plot. Additionally, the observed quantile and the theoretical quantile of a normal distribution of residuals was assessed using a Q–Q plot. No variables were transformed prior to the regression analysis. Variables were checked for collinearity. The presence of collinearity was defined as the combination of a value of tolerance < 0.2 and a variance inflation factor (VIF) > 10. Variables from the models revealed by the stepwise procedure were then directly entered in models that also included the variables sex and age. Both the corrected and uncorrected models are presented in Table n = 126, SD ± 18). Most of the included patients suffered from sensorineural HL (n = 145), while 13 patients had mixed HL (Table One hundred and fifty-eight adult patients (27–78 years old) with a mean age of 61 years participated in this study. The sample consisted of 62 females and 96 males. Seventy-one (45%) of the participants were experienced HA users seeking HA renewal, while the others (n = 87) (55%) were first time HA users. Years of living with a HL ranged from 0 to 76 years, with a mean of 22 years , APHAB scores, TOMCATS scores, level of neuroticism, GHQ score, EORTC scores, age and duration of hearing loss are shown in Table Correlations between PTA for better and worst ear, inter-aural difference in PTA . To investigate whether the relationship between coping and QoL was affected by the time of hearing loss onset, we investigated whether correlations between coping and QoL had a statistically significant higher common variance in patients with congenital or hereditable disease compared to patients with presbyacusis or noise-induced HL. These correlations were statistically significantly stronger among the patients with hereditary and congenital causes for their HL versus patients with presbyacusis or noise-induced HL Table .Table 5PF = ,87b, p = 0.56, Wilks` Λ = 0.93, partial η2 = 0.075.Table This study aimed to investigate whether poorer hearing, maladaptive coping expectancies and more neuroticism were associated to poorer QoL, worse hearing disability and more distress in a population of HA users and HA candidates. We have shown that hearing disability, QoL, and distress were associated with each other and to coping expectancies. More neuroticism was associated to poorer QoL, worse hearing disability and more distress.As previously stated, the personality dimension neuroticism is a broad pervasive dimension of normal personality whereby people vary in their tendency to experience dysphoric emotional states , 33. FurVariable coping may have secondary consequences for QoL , 27. PreSome previous studies have suggested gender differences for coping with hearing loss. No such differences were seen in the present study. We suggest that this discrepancy could partly be explained by the type of coping-measure applied. The TOMCATS questionnaire used in this study is a measure of general coping expectancy. Thus, the questions are not related to how the subject copes with hearing loss and/or communication. Studies that have suggested gender differences have used questionnaires that specifically address coping with hearing loss while others have interviewed patients and specifically addressed coping with hearing loss . The disWe have not found any statistically significant relationship between age or gender and QoL, hearing disability or coping in the present cohort. Hearing disability, QoL, and distress were not related to demographic variables. Some previous studies have shown that the discrepancy between hearing disability and pure-tone hearing threshold measures vary with age , 36. ThiWe have previously shown that hearing disability shares a common variance with PTA in the better ear at about 14%. However, hearing disability was associated not only with pure-tone-audiometry, but also with the degree of neuroticism and with coping expectancy with combined common variances to these two parameters at about the same percentage as to PTA. Furthermore, hearing disability correlated to QoL, but a significant association could not be found by multiple stepwise regression analyses, including a wide array of parameters. Taken together, the present measure of hearing disability seems to behave as expected for a symptom specific QoL questionnaire. Regarding QoL, the results support that QoL in persons with HL is constructed as in other patients groups .We have shown that among patients with HL due to hereditary or congenital causes, i.e., patients with early-onset HL, the associations between coping expectancies and QoL scores were significantly stronger compared to patients with other causes of HL. This is in line with previous observations among patients with challenging disease consequences , 38. ThiWe have a limited number of respondents. Thus, any lack of significant differences between groups should be interpreted with caution. This investigation did not include the elderly above 80 years of age with hearing loss. Many investigations regarding HL have focused on this group, and the present results should not be extrapolated to such age groups without taking appropriate precautions. Furthermore, the present response rate is limited. The strong correlations, however, between measures of psychological factors and QoL scores add validity to the findings of this study. In a broader sense, the principally equivalent results have been presented in previous studies regarding other disabilities, and these results support that QoL seen in persons with HL is based on psychosocial interactions also seen in other patient groups –42.. In such cases, the treatment could be adjusted to allow a broader approach to the therapy, with an increased focus on individual counselling and psychosocial therapy.Results from the present study suggest that an axis of causality, from personality, via the choice of coping to hearing disability, may be present. However, the direction of causality cannot be determined by the present cross-sectional design. Nevertheless, this may be taken into consideration when interpreting hearing disability at the individual patient level in clinical settings. It could, for example, be suggested that individuals that demonstrate large discrepancies between hearing disability and pure-tone audiometry and tests of speech perception could be affected by adverse psychosocial factors –42. In sWe have shown that more neuroticism was associated with worse outcome for the variables hearing disability, distress, and QoL. Helplessness and hopelessness were associated with worse hearing disability, increased distress, and lowered QoL. Further, the present study showed that more aspects than previously generally recognized must be taken into consideration when evaluating both hearing disability and QoL scores in persons with HL. Patients with early-onset HL presumably should be closely followed up. Further studies are needed as to how and when psychosocial matters should be taken into special consideration.