Incidence of Hearing Loss in Corpus Callosum Agenesis.

OBJECTIVES: Congenital corpus callosum agenesis (CCA) is one of the congenital anomalies in newborns, which usually presents with syndromic features. It can be asymptomatic or have variable neurological deficits. Some studies demonstrated that hearing loss can occur in patients with CCA; however, the exact prevalence remains unclear. Therefore, we aimed to investigate the prevalence of hearing loss in CCA using data from newborn hearing screening in a single tertiary referral center. METHODS: A total of 126 patients with CCA combined with hearing loss diagnosed at our hospital from November 2005 to November 2022 were retrospectively included in our study. All patients had at least one screening or diagnostic auditory brainstem response result. Brain ultrasonography and magnetic resonance imaging were used to diagnose CCA. RESULTS: Among 126 patients, 93 had automated auditory brainstem response within a month from birth. Of the 93 patients, 20 (21.5%) had a "refer" result in the screening tests in at least one ear. The final incidence of hearing loss in patients with CCA was 16.1%. We observed no hearing loss in 22 patients with isolated CCA. CONCLUSIONS: Patients with CCA have a higher incidence of hearing loss. However, this is likely related to the concurrent condition of patients. CCA seems not to be a risk factor for hearing loss.

Endoscopic-Assisted Keyhole Middle Cranial Fossa Approach for Small Vestibular Schwannomas.

The classical middle cranial fossa approach (MCFA) for vestibular schwannoma (VS) removal often requires a large incision and craniotomy, excessive temporal lobe manipulation, and a longer recovery. We describe a keyhole MCFA (KMCFA) with endoscopic assistance that allows for adequate access with minimal temporal lobe manipulation, resulting in a fast recovery and an invisible scar. Eight sides of four cadaveric heads were dissected through the endoscopic-assisted KMCFA to access the internal auditory canal (IAC). Furthermore, five patients with intracanalicular VS underwent tumor removal with the endoscopic-assisted KMCFA. During the endoscopic-assisted KMCFA with fine instruments, a 3-cm supra-auricular incision and a 2-cm diameter keyhole craniotomy achieved exposure of the entire length of the IAC in all cadaveric dissections without unintended violation of the cochlea, semicircular canal, and facial nerve. The gross tumor was totally removed in five patients with no major postoperative complications. The surgical time was reduced, the hearing outcomes were similar to those of the classical MCFA, and the scar was invisible 1 month after the surgery. The endoscopic-assisted KMCFA permits intracanalicular VS removal in a safe, efficient, and cosmetic way. For small intracanalicular VSs, this approach can replace the classical MCFA when indicated.

Patients Requiring Gastrostomy Tube Insertion After Total Laryngectomy Have a Higher Incidence of Otitis Media.

BACKGROUND AND OBJECTIVES: Some reports propose an increased risk of otitis media and hearing impairment after total laryngectomy. However, the incidence of otitis media following laryngectomy and the mechanism remain unclear. This study aimed to identify the incidence and risk factors of otitis media after total laryngectomy. SUBJECTS AND METHODS: This retrospective cohort study assessed 77 patients who underwent total laryngectomy from 2010 to 2020 in a tertiary referral center. Serial imaging studies (computed tomography [CT], magnetic resonance imaging, and positron emission tomography-CT) were used to assess otitis media. RESULTS: The study enrolled 58 patients (mean age, 67.0±7.7 years; male, 56 [96.6%]); nine (15.5%) underwent a gastrostomy tube (four preoperatively and five postoperatively). Otitis media was confirmed in seven (12.1%) patients. Gastrostomy tube insertion was the only significant risk factor for otitis media (p=0.012). Of the nine patients who underwent gastrostomy tube insertion, four developed otitis media; all four had the procedure after laryngectomy. CONCLUSIONS: This study found an increased incidence of otitis media after total laryngectomy. Swallowing difficulties likely contribute to otitis media as it occurred more frequently in patients requiring postoperative gastrostomy tube insertion.

Corrigendum: Supplementary Effect of Choline Alfoscerate on Speech Recognition in Patients With Age-Related Hearing Loss: A Prospective Study in 34 Patients (57 Ears).

[This corrects the article DOI: 10.3389/fnagi.2021.684519.].

Supplementary Effect of Choline Alfoscerate on Speech Recognition in Patients With Age-Related Hearing Loss: A Prospective Study in 34 Patients (57 Ears).

To investigate the effect of choline alfoscerate (CA) on hearing amplification in patients with age related hearing loss, we performed a prospective case-control observational study from March 2016 to September 2020. We assessed patients with bilateral word recognition score (WRS) <50% using monosyllabic words. The patients were 65-85 years old, without any history of dementia, Alzheimer's disease, parkinsonism, or depression. After enrollment, all patients started using hearing aids (HA). The CA group received a daily dose of 800 mg CA for 11 months. We performed between-group comparisons of audiological data, including pure tone audiometry, WRS, HA fitting data obtained using real-ear measurement (REM), and the Abbreviated Profile of Hearing Aid benefit scores after treatment. After CA administration, the WRS improved significantly in the CA group (4.2 ± 8.3%), but deteriorated in the control group (-0.6 ± 8.1%, p = 0.035). However, there was no significant between-group difference in the change in pure tone thresholds and aided speech intelligibility index calculated from REM. These findings suggest that the difference in WRS was relevant to central speech understanding rather than peripheral audibility. Therefore, administering oral CA could effectively enrich listening comprehension in older HA users.

Efficient architecture for deep neural networks with heterogeneous sensitivity.

In this study, we present a neural network that consists of nodes with heterogeneous sensitivity. Each node in a network is assigned a variable that determines the sensitivity with which it learns to perform a given task. The network is trained via a constrained optimization that maximizes the sparsity of the sensitivity variables while ensuring optimal network performance. As a result, the network learns to perform a given task using only a few sensitive nodes. Insensitive nodes, which are nodes with zero sensitivity, can be removed from a trained network to obtain a computationally efficient network. Removing zero-sensitivity nodes has no effect on the performance of the network because the network has already been trained to perform the task without them. The regularization parameter used to solve the optimization problem was simultaneously found during the training of the networks. To validate our approach, we designed networks with computationally efficient architectures for various tasks such as autoregression, object recognition, facial expression recognition, and object detection using various datasets. In our experiments, the networks designed by our proposed method provided the same or higher performances but with far less computational complexity.

Modeling nonstationary lens blur using eigen blur kernels for restoration.

Images acquired through a lens show nonstationary blur due to defocus and optical aberrations. This paper presents a method for accurately modeling nonstationary lens blur using eigen blur kernels obtained from samples of blur kernels through principal component analysis. Pixelwise variant nonstationary lens blur is expressed as a linear combination of stationary blur by eigen blur kernels. Operations that represent nonstationary blur can be implemented efficiently using the discrete Fourier transform. The proposed method provides a more accurate and efficient approach to modeling nonstationary blur compared with a widely used method called the efficient filter flow, which assumes stationarity within image regions. The proposed eigen blur kernel-based modeling is applied to total variation restoration of nonstationary lens blur. Accurate and efficient modeling of blur leads to improved restoration performance. The proposed method can be applied to model various nonstationary degradations of image acquisition processes, where degradation information is available only at some sparse pixel locations.

Deep neural networks with a set of node-wise varying activation functions.

In this study, we present deep neural networks with a set of node-wise varying activation functions. The feature-learning abilities of the nodes are affected by the selected activation functions, where the nodes with smaller indices become increasingly more sensitive during training. As a result, the features learned by the nodes are sorted by the node indices in order of their importance such that more sensitive nodes are related to more important features. The proposed networks learn input features but also the importance of the features. Nodes with lower importance in the proposed networks can be pruned to reduce the complexity of the networks, and the pruned networks can be retrained without incurring performance losses. We validated the feature-sorting property of the proposed method using both shallow and deep networks as well as deep networks transferred from existing networks.

Facial Attribute Recognition by Recurrent Learning With Visual Fixation.

This paper presents a recurrent learning-based facial attribute recognition method that mimics human observers' visual fixation. The concentrated views of a human observer while focusing and exploring parts of a facial image over time are generated and fed into a recurrent network. The network makes a decision concerning facial attributes based on the features gleaned from the observer's visual fixations. Experiments on facial expression, gender, and age datasets show that applying visual fixation to recurrent networks improves recognition rates significantly. The proposed method not only outperforms state-of-the-art recognition methods based on static facial features, but also those based on dynamic facial features.

Modeling Non-Stationary Asymmetric Lens Blur by Normal Sinh-Arcsinh Model.

Images acquired by a camera show lens blur due to imperfection in the optical system even when images are properly focused. Lens blur is non-stationary in a sense that the amount of blur depends on pixel locations in a sensor. Lens blur is also asymmetric in a sense that the amount of blur is different in the radial and tangential directions, and also in the inward and outward radial directions. This paper presents parametric blur kernel models based on the normal sinh-arcsinh distribution function. The proposed models can provide flexible shapes of blur kernels with a different symmetry and skewness to model complicated lens blur due to optical aberration in a properly focused images accurately. Blur of single focal length lenses is estimated, and the accuracy of the models is compared with the existing parametric blur models. An advantage of the proposed models is demonstrated through deblurring experiments.

Visual appearance measurement of surfaces containing pearl flakes.

The color, gloss, and texture (i.e., pearliness) of 15 glossy samples containing pearl flakes were investigated. Psychophysical experimental data from 21 observers were compared with measurement data. Color measurement data obtained using the CIE D/0 and ASTM E2539-08 multiangle geometry did not predict the overall color appearance variation of pearly samples. Pearly samples have a lower perceived glossiness than non-pearly surfaces with the same level of gloss treatment, but a much higher measured gloss. Pearliness describes the texture of pearly samples well and can be predicted as a function of the pearl flakes' average size and area coverage measured from magnified surface images. These results suggest that an image statistics approach is required to properly describe the visual appearance of pearly surfaces.

Isolation and characterization of histamine-producing bacteria from fermented fish products.

Histamine is mainly produced by microorganisms that are found in fermented foods, and is frequently involved in food poisoning. Two histamine-producing bacteria were isolated from fermented fish products, anchovy sauce, and sand lance sauce by using a histidine decarboxylating medium. The species were identified as Bacillus licheniformis A7 and B. coagulans SL5. Multiplex PCR analysis showed the presence of the conserved histidine decarboxylase (hdc) gene in the chromosome of these bacteria. B. licheniformis A7 and B. coagulans SL5 produced the maximum amount of histamine (22.3±3.5 and 15.1±1.5 mg/L, respectively). As such, they were determined to be potential histamine-producing bacteria among the tested cultures.