Reorganization of the cortical connectome functional gradient in age-related hearing loss.

Age-related hearing loss (ARHL), one of the most common sensory deficits in elderly individuals, is a risk factor for dementia; however, it is unclear how ARHL affects the decline in cognitive function. To address this issue, a connectome gradient framework was used to identify critical features of information integration between sensory and cognitive processing centers using resting-state functional magnetic resonance imaging (rs-fMRI) data from 40 individuals with ARHL and 36 healthy controls (HCs). The first three functional gradient alterations associated with ARHL were investigated at the global, network and regional levels. Using a support vector machine (SVM) model, our analysis distinguished individuals with ARHL with normal cognitive function from those with cognitive decline. Compared to HCs, individuals with ARHL had a contracted principal primary-to-transmodal gradient axis, especially in the visual and default mode networks, with an altered gradient explained ratio and variance. Among individuals with ARHL, cognitive decline was detected in the visual network in the principal gradient as well as in the limbic, salience and default mode networks in the third gradient (salience to frontoparietal/default mode). These results suggest that ARHL is associated with disrupted information processing from the primary sensory networks to higher-order cognitive networks and highlight the key nodes closely associated with cognitive decline during cognitive processing in ARHL, providing new insights into the mechanism of cognitive impairment and suggesting potential treatments related to ARHL.

Alteration in resting-state effective connectivity within the Papez circuit in Presbycusis.

Previous studies have suggested that the Papez circuit may be involved in the cognitive impairment observed after hearing loss in presbycusis patients, yet relatively little is known about the pattern of changes in effective connectivity within the circuit. The aim of this study was to investigate abnormal alterations in resting-state effective connectivity within the Papez circuit and their association with cognitive decline in presbycusis patients. The spectral dynamic causal modelling (spDCM) approach was used for resting-state effective connectivity analysis in 61 presbycusis patients and 52 healthy controls (HCs) within the Papez circuit. The hippocampus (HPC), mamillary body (MB), anterior thalamic nuclei (ATN), anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), entorhinal cortex (ERC), subiculum (Sub) and parahippocampal gyrus (PHG) were selected as the regions of interest (ROIs). The fully connected model difference in effective connectivity between the two groups was assessed, and the correlation between effective connectivity alteration and cognitive scale was analysed. We found that presbycusis patients demonstrated decreased effective connectivity from MB, PCC, and Sub to ACC relative to HCs, whereas higher effective connectivity strength was shown from HPC to MB, from ATN to PHG and from PHG to Sub. The effective connectivity from PHG to Sub was significantly negatively correlated with the complex figure test (CFT)-delay score (rho = -0.259, p = 0.044). The results support and reinforce the role of abnormal effective connectivity within the Papez circuit in the pathophysiology of presbycusis-related cognitive impairment and reveal its potential as a novel imaging marker.

RASSF1A promotes radiosensitivity in nasopharyngeal carcinoma by promoting FoxO3a and inhibiting the Nrf2/TXNRD1 signaling pathway.

Radiotherapy is widely used as the first-line treatment for nasopharyngeal carcinoma (NPC). However, the resistance of some patients to treatment lowers its clinical effectiveness. Compared to typical epithelial cells, NPC markedly lowers the Ras-association domain family 1A (RASSF1A) protein expression. RASSF1A overexpression sensitizes NPC cells to radiotherapy. Mechanistically, RASSF1A promotes the expression of Forkhead box O3a (FoxO3a) in the nucleus and inhibits the Nuclear factor E2-related factor 2 (Nrf2) signaling pathway via binding to the Kelch-like ECH-associated protein 1 (Keap1) promoter. Through elevating intracellular ROS levels, RASSF1A overexpression inhibits the expression of thioredoxin reductase 1 (TXNRD1), a crucial Nrf2 target gene, and increases NPC sensitivity to radiation. Immunohistochemical staining of NPC tissue sections revealed that the expression of RASSF1A is negatively correlated with that of TXNRD1. The traditional Chinese medicine component andrographolide (AGP), which induces RASSF1A expression, increased the sensitivity of NPC cells to radiotherapy in vitro and in vivo. Our findings implied that RASSF1A increases the sensitivity of NPC to radiation by increasing FoxO3a expression in the nucleus, inhibiting the Nrf2/TXNRD1 signaling pathway, and elevating intracellular ROS levels. AGP targets RASSF1A and may be a promising adjuvant sensitizer for enhancing radiosensitivity in NPC.

KeMRE: Knowledge-enhanced medical relation extraction for Chinese medicine instructions.

Medicine instructions usually contain rich medical relations, and extracting them is very helpful for many downstream tasks such as medicine knowledge graph construction and medicine side-effect prediction. Existing relation extraction (RE) methods usually predict relations between entities from their contexts and do not consider medical knowledge. However, understanding a part of medical relations may need some expert knowledge in the medical field, making it challenging for existing methods to achieve satisfying performances of medical RE. In this paper, we propose a knowledge-enhanced framework for medical RE, which can exploit medical knowledge of medicines to better conduct medical RE on Chinese medicine instructions. We first propose a BERT-CNN-LSTM based framework for text modeling and learn representations of characters from their contexts. Then we learn representations of each entity by aggregating representations of their characters. Besides, we propose a CNN-LSTM based framework for entity modeling and learn entity representations from their relatedness. In addition, there are usually many different instructions for the same medicine, which usually share general knowledge on this medicine. Thus, to obtain medical knowledge of medicines, we annotate relations on a randomly-sampled instruction of each medicine. Then we build knowledge embeddings to represent potential relations between entities from knowledge of medicines. Finally, we use an MLP network to predict relations between entities from their representations and knowledge embeddings. Extensive experiments on a real-world dataset show that our method can significantly outperform existing methods.

Aberrant cerebral blood flow in tinnitus patients with migraine: a perfusion functional MRI study.

PURPOSE: Migraine is often accompanied with chronic tinnitus that will affect the cerebral blood flow (CBF) and exacerbate the tinnitus distress. However, the potential relationship between migraine and tinnitus remains unclear. This study will investigate whether aberrant CBF patterns exist in migraine patients with tinnitus and examine the influence of migraine on CBF alterations in chronic tinnitus. MATERIALS AND METHODS: Participants included chronic tinnitus patients (n = 45) and non-tinnitus controls (n = 50), matched for age, sex, education, and hearing thresholds. CBF images were collected and analyzed using arterial spin labeling (ASL) perfusion functional magnetic resonance imaging (fMRI). Regions with major CBF differences between tinnitus patients and non-tinnitus controls were first detected. The effects of migraine on tinnitus for CBF alterations were further examined. Correlation analyses illustrated the association between CBF values and tinnitus severity as well as between CBF and severity of migraine. RESULTS: Compared with non-tinnitus controls, chronic tinnitus patients without migraine exhibited decreased CBF, primarily in right superior temporal gyrus (STG), bilateral middle frontal gyrus (MFG), and left superior frontal gyrus (SFG); decreased CBF in these regions was correlated with tinnitus distress. There was a significant effect of migraine on tinnitus for CBF in right STG and MFG. Moreover, the severity of migraine correlated negatively with CBF in tinnitus patients. CONCLUSIONS: Chronic tinnitus patients exhibited reduced CBF in the auditory and prefrontal cortex. Migraine may facilitate a CBF decrease in the setting of tinnitus, which may underlie the neuropathological mechanisms of chronic tinnitus comorbid with migraine.

Fibrous red phosphorene: a promising two-dimensional optoelectronic and photocatalytic material with a desirable band gap and high carrier mobility.

By using density-functional theory, we have systematically investigated the structural stabilities, electronic structures, and optical properties of monolayer fibrous red phosphorene. We find the monolayer fibrous red phosphorene lattice to be dynamically and thermodynamically stable based on phonon spectra calculation and ab initio molecular dynamics simulation. A small cleavage energy of approximately 0.88 J m-2 is required for creating it from its bulk, suggesting the possibility of exfoliation in experiments. Furthermore, we find that monolayer fibrous red phosphorene is a semiconductor with an indirect bandgap of approximately 2.46 eV, and the bandgap is less susceptible to the number of stacked atomic layers. Moreover, the monolayer is expected to have highly directional anisotropy effective masses and high carrier mobilities (∼104 cm2 V-1 s-1), comparable with those of monolayer black phosphorene. In addition, fibrous red phosphorene nanosheets can absorb visible light as well as their band edge alignments are well positioned for the feasibility of both photo-oxidation and photo-reduction of water within the range of -5 to 5% biaxial strains. These combined properties make the fibrous red phosphorene nanosheets an alternative to diverse nanodevices, and pave the way for a potential photocatalyst.

Combinatorial expression of different ß-carotene hydroxylases and ketolases in Escherichia coli for increased astaxanthin production.

In natural produced bacteria, ß-carotene hydroxylase (CrtZ) and ß-carotene ketolase (CrtW) convert ß-carotene into astaxanthin. To increase astaxanthin production in heterologous strain, simple and effective strategies based on the co-expression of CrtZ and CrtW were applied in E. coli. First, nine artificial operons containing crtZ and crtW genes from different sources were constructed and, respectively, introduced into E. coli ZF237T, a ß-carotene producing host. Among the nine resulting strains, five accumulated detectable amounts of astaxanthin ranging from 0.49 to 8.07 mg/L. Subsequently, the protein fusion CrtZ to CrtW using optimized peptide linkers further increased the astaxanthin production. Strains expressing fusion proteins with CrtZ rather than CrtW attached to the N-terminus accumulated much more astaxanthin. The astaxanthin production of the best strain ZF237T/CrtZAs-(GS)1-WBs was 127.6% and 40.2% higher than that of strains ZF237T/crtZAsWBs and ZF237T/crtZBsWPs, respectively. The strategies depicted here also will be useful for the heterologous production of other natural products.

Patterns and rates of exonic de novo mutations in autism spectrum disorders.

Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.

The Drosophila melanogaster Genetic Reference Panel.

A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics.

Engineering genome-reduced Bacillus subtilis for acetoin production from xylose.

OBJECTIVES: To investigate the capacity of a genome-reduced Bacillus subtilis strain as chassis cell for acetoin production from xylose. RESULTS: To endow the genome-reduced Bacillus subtilis strain BSK814 with the ability to utilize xylose, we inserted a native xyl operon into its genome and deleted the araR gene. The resulting strain BSK814A2 produced 2.94 g acetoin/l from 10 g xylose/l, which was 39% higher than control strain BSK19A2. The deletion of the bdhA and acoA genes further improved xylose utilization efficiency and increased acetoin production to 3.71 g/l in BSK814A4. Finally, BSK814A4 produced up to 23.3 g acetoin/l from 50 g xylose/l, with a yield of 0.46 g/g xylose. Both the titer and yield were 39% higher than those of control strain BSK19A4. CONCLUSIONS: As a chassis cell, genome-reduced B. subtilis showed significantly improved capacity for the production of the overflow product acetoin from xylose compared with wild-type strain.

Comparative validation of the D. melanogaster modENCODE transcriptome annotation.

Accurate gene model annotation of reference genomes is critical for making them useful. The modENCODE project has improved the D. melanogaster genome annotation by using deep and diverse high-throughput data. Since transcriptional activity that has been evolutionarily conserved is likely to have an advantageous function, we have performed large-scale interspecific comparisons to increase confidence in predicted annotations. To support comparative genomics, we filled in divergence gaps in the Drosophila phylogeny by generating draft genomes for eight new species. For comparative transcriptome analysis, we generated mRNA expression profiles on 81 samples from multiple tissues and developmental stages of 15 Drosophila species, and we performed cap analysis of gene expression in D. melanogaster and D. pseudoobscura. We also describe conservation of four distinct core promoter structures composed of combinations of elements at three positions. Overall, each type of genomic feature shows a characteristic divergence rate relative to neutral models, highlighting the value of multispecies alignment in annotating a target genome that should prove useful in the annotation of other high priority genomes, especially human and other mammalian genomes that are rich in noncoding sequences. We report that the vast majority of elements in the annotation are evolutionarily conserved, indicating that the annotation will be an important springboard for functional genetic testing by the Drosophila community.

Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines.

The Drosophila melanogaster Genetic Reference Panel (DGRP) is a community resource of 205 sequenced inbred lines, derived to improve our understanding of the effects of naturally occurring genetic variation on molecular and organismal phenotypes. We used an integrated genotyping strategy to identify 4,853,802 single nucleotide polymorphisms (SNPs) and 1,296,080 non-SNP variants. Our molecular population genomic analyses show higher deletion than insertion mutation rates and stronger purifying selection on deletions. Weaker selection on insertions than deletions is consistent with our observed distribution of genome size determined by flow cytometry, which is skewed toward larger genomes. Insertion/deletion and single nucleotide polymorphisms are positively correlated with each other and with local recombination, suggesting that their nonrandom distributions are due to hitchhiking and background selection. Our cytogenetic analysis identified 16 polymorphic inversions in the DGRP. Common inverted and standard karyotypes are genetically divergent and account for most of the variation in relatedness among the DGRP lines. Intriguingly, variation in genome size and many quantitative traits are significantly associated with inversions. Approximately 50% of the DGRP lines are infected with Wolbachia, and four lines have germline insertions of Wolbachia sequences, but effects of Wolbachia infection on quantitative traits are rarely significant. The DGRP complements ongoing efforts to functionally annotate the Drosophila genome. Indeed, 15% of all D. melanogaster genes segregate for potentially damaged proteins in the DGRP, and genome-wide analyses of quantitative traits identify novel candidate genes. The DGRP lines, sequence data, genotypes, quality scores, phenotypes, and analysis and visualization tools are publicly available.

Analysis of rare, exonic variation amongst subjects with autism spectrum disorders and population controls.

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD.

[Correction Methods of Temperature Drift for Infrared Spectral Emissivity Measurement System].

For the influence of temperature drift of the spectral responsivity on the repeatability infrared spectral emissivity measurement system, a temperature drift correction method is proposed based on the polynomial fitting. By analyzing the function of detector output voltage depended on its temperature. After studying the functional relationship between the temperature and spectral responsivity of detector, the spectral response curve varies with temperature is fitted and get the fitting equation. Calculating the drift correction factor of spectral responsivity, the output voltage of infrared detector is corrected. The effect of spectral response drift on the output voltage of detector is eliminated. With the development of temperature drift correction device of spectral responsivity, the temperature drift curve of spectral response is measured. Compared to the exponential fitting, the fitting consistency of sixth-order polynomial curve is excellent. Because of the application of this method, the repeatability of spectral emissivity measurement system is improved.

Exome sequencing identification of a GJB1 missense mutation in a kindred with X-linked spinocerebellar ataxia (SCA-X1).

We undertook a gene identification and molecular characterization project in a large kindred originally clinically diagnosed with SCA-X1. While presenting with ataxia, this kindred also had some unique peripheral nervous system features. The implicated region on the X chromosome was delineated using haplotyping. Large deletions and duplications were excluded by array comparative genomic hybridization. Exome sequencing was undertaken in two affected subjects. The single identified X chromosome candidate variant was then confirmed to co-segregate appropriately in all affected, carrier and unaffected family members by Sanger sequencing. The variant was confirmed to be novel by comparison with dbSNP, and filtering for a minor allele frequency of <1% in 1000 Genomes project, and was not present in the NHLBI Exome Sequencing Project or a local database at the BCM HGSC. Functional experiments on transfected cells were subsequently undertaken to assess the biological effect of the variant in vitro. The variant identified consisted of a previously unidentified non-synonymous variant, GJB1 p.P58S, in the Connexin 32/Gap Junction Beta 1 gene. Segregation studies with Sanger sequencing confirmed the presence of the variant in all affected individuals and one known carrier, and the absence of the variant in unaffected members. Functional studies confirmed that the p.P58S variant reduced the number and size of gap junction plaques, but the conductance of the gap junctions was unaffected. Two X-linked ataxias have been associated with genetic loci, with the first of these recently characterized at the molecular level. This represents the second kindred with molecular characterization of X-linked ataxia, and is the first instance of a previously unreported GJB1 mutation with a dominant and permanent ataxia phenotype, although different CNS deficits have previously been reported. This pedigree has also been relatively unique in its phenotype due to the presence of central and peripheral neural abnormalities. Other X-linked SCAs with unique features might therefore also potentially represent variable phenotypic expression of other known neurological entities.

Epistasis dominates the genetic architecture of Drosophila quantitative traits.

Epistasis-nonlinear genetic interactions between polymorphic loci-is the genetic basis of canalization and speciation, and epistatic interactions can be used to infer genetic networks affecting quantitative traits. However, the role that epistasis plays in the genetic architecture of quantitative traits is controversial. Here, we compared the genetic architecture of three Drosophila life history traits in the sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and a large outbred, advanced intercross population derived from 40 DGRP lines (Flyland). We assessed allele frequency changes between pools of individuals at the extremes of the distribution for each trait in the Flyland population by deep DNA sequencing. The genetic architecture of all traits was highly polygenic in both analyses. Surprisingly, none of the SNPs associated with the traits in Flyland replicated in the DGRP and vice versa. However, the majority of these SNPs participated in at least one epistatic interaction in the DGRP. Despite apparent additive effects at largely distinct loci in the two populations, the epistatic interactions perturbed common, biologically plausible, and highly connected genetic networks. Our analysis underscores the importance of epistasis as a principal factor that determines variation for quantitative traits and provides a means to uncover genetic networks affecting these traits. Knowledge of epistatic networks will contribute to our understanding of the genetic basis of evolutionarily and clinically important traits and enhance predictive ability at an individualized level in medicine and agriculture.

Finding the missing honey bee genes: lessons learned from a genome upgrade.

BACKGROUND: The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. As only a few Metazoan genomes are approaching finished quality (human, mouse, fly and worm), there is room for improvement of most genome assemblies. The honey bee (Apis mellifera) genome, published in 2006, was noted for its bimodal GC content distribution that affected the quality of the assembly in some regions and for fewer genes in the initial gene set (OGSv1.0) compared to what would be expected based on other sequenced insect genomes. RESULTS: Here, we report an improved honey bee genome assembly (Amel_4.5) with a new gene annotation set (OGSv3.2), and show that the honey bee genome contains a number of genes similar to that of other insect genomes, contrary to what was suggested in OGSv1.0. The new genome assembly is more contiguous and complete and the new gene set includes ~5000 more protein-coding genes, 50% more than previously reported. About 1/6 of the additional genes were due to improvements to the assembly, and the remaining were inferred based on new RNAseq and protein data. CONCLUSIONS: Lessons learned from this genome upgrade have important implications for future genome sequencing projects. Furthermore, the improvements significantly enhance genomic resources for the honey bee, a key model for social behavior and essential to global ecology through pollination.

Enhancing Gastrodin Production in Yarrowia lipolytica by Metabolic Engineering.

Gastrodin, 4-hydroxybenzyl alcohol-4-O-ß-D-glucopyranoside, has been widely used in the treatment of neurogenic and cardiovascular diseases. Currently, gastrodin biosynthesis is being achieved in model microorganisms. However, the production levels are insufficient for industrial applications. In this study, we successfully engineered a Yarrowia lipolytica strain to overproduce gastrodin through metabolic engineering. Initially, the engineered strain expressing the heterologous gastrodin biosynthetic pathway, which comprises chorismate lyase, carboxylic acid reductase, phosphopantetheinyl transferase, endogenous alcohol dehydrogenases, and a UDP-glucosyltransferase, produced 1.05 g/L gastrodin from glucose in a shaking flask. Then, the production was further enhanced to 6.68 g/L with a productivity of 2.23 g/L/day by overexpressing the key node DAHP synthases of the shikimate pathway and alleviating the native tryptophan and phenylalanine biosynthetic pathways. Finally, the best strain, Gd07, produced 13.22 g/L gastrodin in a 5 L fermenter. This represents the highest reported production of gastrodin in an engineered microorganism to date, marking the first successful de novo production of gastrodin using Y. lipolytica.

Evaluation of glymphatic system activity by diffusion tensor image analysis along the perivascular space in presbycusis.

PURPOSE: Previous studies have suggested that presbycusis (age-related hearing loss) is accompanied with cognitive decline and dementia. However, the neural mechanism underlying the cognitive decline in presbycusis remains unclear. This study aimed to evaluate the glymphatic system function in presbycusis patients compared to healthy controls using diffusion tensor imaging (DTI) with the perivascular space (DTI-ALPS) method. METHODS: DTI scans were obtained from 30 presbycusis patients with cognitive decline (PCD), 30 presbycusis patients with no cognitive decline (PNCD) and 40 age-, gender-, and education-matched healthy controls (HCs). The DTI-ALPS index was calculated for each group. We evaluated the differences in the DTI-ALPS index among PCD, PNCD and HCs. In addition, we conducted a correlation analysis between the DTI-ALPS index and cognitive performance. RESULTS: There were significant differences of the DTI-ALPS index among three groups. Post-hoc analysis suggested that the DTI-ALPS index in PCD was significantly lower patients in relative to PNCD and HCs (1.49147 vs. 1.57441 vs. 1.62020, p < 0.001). After correcting for age, gender, and education, the DTI-ALPS index is positively correlated with the MoCA scores (rho = 0.426, p = 0.026). CONCLUSION: Presbycusis patients with cognitive impairment exhibited decreased glymphatic activity than those without cognitive impairment and HCs. The DTI-ALPS index may provide useful disease progression or treatment biomarkers for patients with presbycusis as an indicator of modulation of glymphatic activity.

Combination of static and dynamic neural imaging features to distinguish sensorineural hearing loss: a machine learning study.

Purpose: Sensorineural hearing loss (SNHL) is the most common form of sensory deprivation and is often unrecognized by patients, inducing not only auditory but also nonauditory symptoms. Data-driven classifier modeling with the combination of neural static and dynamic imaging features could be effectively used to classify SNHL individuals and healthy controls (HCs). Methods: We conducted hearing evaluation, neurological scale tests and resting-state MRI on 110 SNHL patients and 106 HCs. A total of 1,267 static and dynamic imaging characteristics were extracted from MRI data, and three methods of feature selection were computed, including the Spearman rank correlation test, least absolute shrinkage and selection operator (LASSO) and t test as well as LASSO. Linear, polynomial, radial basis functional kernel (RBF) and sigmoid support vector machine (SVM) models were chosen as the classifiers with fivefold cross-validation. The receiver operating characteristic curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated for each model. Results: SNHL subjects had higher hearing thresholds in each frequency, as well as worse performance in cognitive and emotional evaluations, than HCs. After comparison, the selected brain regions using LASSO based on static and dynamic features were consistent with the between-group analysis, including auditory and nonauditory areas. The subsequent AUCs of the four SVM models (linear, polynomial, RBF and sigmoid) were as follows: 0.8075, 0.7340, 0.8462 and 0.8562. The RBF and sigmoid SVM had relatively higher accuracy, sensitivity and specificity. Conclusion: Our research raised attention to static and dynamic alterations underlying hearing deprivation. Machine learning-based models may provide several useful biomarkers for the classification and diagnosis of SNHL.