Predicting the distribution coefficient of cesium in solid phase groups using machine learning.

The migration and retention of radioactive contaminants such as 137Cesium (137Cs) in various environmental media pose significant long-term storage challenges for nuclear waste. The distribution coefficient (Kd) is a critical parameter for assessing the mobility of radioactive contaminants and is influenced by various environmental conditions. This study presents machine-learning models based on the Japan Atomic Energy Agency Sorption Database (JAEA-SDB) to predict the Kd values for Cs in solid phase groups. We used three different machine learning models: random forest (RF), artificial neural network (ANN), and convolutional neural network (CNN). The models were trained on 14 input variables from the JAEA-SDB, including factors such as the Cs concentration, solid-phase properties, and solution conditions, which were preprocessed by normalization and log-transformation. The performances of the models were evaluated using the coefficient of determination (R2) and root mean squared error (RMSE). The RF, ANN, and CNN models achieved R2 values greater than 0.97, 0.86, and 0.88, respectively. We also analyzed the variable importance of RF using an out-of-bag (OOB) and a CNN with an attention module. Our results showed that the environmental media, initial radionuclide concentration, solid phase properties, and solution conditions were significant variables for Kd prediction. Our models accurately predict Kd values for different environmental conditions and can assess the environmental risk by analyzing the behavior of radionuclides in solid phase groups. The results of this study can improve safety analyses and long-term risk assessments related to waste disposal and prevent potential hazards and sources of contamination in the surrounding environment.

The therapeutic effect of hyperbaric oxygen therapy in patients with severe to profound idiopathic sudden sensorineural hearing loss.

The optimal treatment for sudden sensorineural hearing loss (SSNHL) is unclear. Hyperbaric oxygen therapy (HBOT) has been suggested as a viable option for treatment of SSNHL as it improves vascular dysfunction. In this study, we evaluated the therapeutic effects of HBOT by retrospectively reviewing the records of 2206 patients with SSNHL. 54 who had received HBOT were selected for the HBOT groups, while 59 age-matched controls who had not were selected for the control groups. The HBOT and control groups were divided into subgroups according to intratympanic steroid (ITS) use. Groups A-D had received oral steroids + HBOT, oral steroids only, oral steroids + ITS + HBOT, and oral steroids + ITS, respectively. Of the 113 SSNHL patients, 21 had diabetes mellitus (DM) (2, 0, 9, and 10 patients in Groups A-D, respectively). There was no notable difference in hearing improvement between patients receiving HBOT and those in the control group. However, among diabetic patients, those who underwent HBOT demonstrated a significant improvement in hearing when compared to the control group. The combination of HBOT and steroids could potentially be beneficial for treating severe to profound SSNHL patients with DM.

Early Assessment of Voice Problems in Post-Thyroidectomy Syndrome Using Cepstral Analysis.

Post-thyroidectomy syndrome (PTS), characterized by voice issues after thyroidectomy without recurrent laryngeal nerve injury, was investigated in this study. The Voice Fatigue Index (VFI) and cepstral analysis were employed for subjective and objective voice evaluation. Retrospective analysis involved 96 patients (37 males, 59 females) who underwent thyroidectomy without nerve injury from April 2018 to June 2022. Assessments pre- and post-thyroidectomy included the Voice Handicap Index (VHI) and VFI, along with auditory perceptual, acoustic (including cepstral), aerodynamic, and glottal vibration analyses. In females, although the GRBAS scale showed no significant change, both VHI and VFI increased post-thyroidectomy. Significant correlations were observed between the VHI and VFI in females. Acoustic analysis indicated a decrease in the cepstral peak prominence (CPP) of vowels (/a/) and sentences in females, with significant correlations between changes in the CPP/a/ and VHI/VFI. The maximum fundamental frequency (F0max) exhibited a significant decrease, correlating with the VHI and VFI changes. The VFI demonstrated effectiveness in subjective PTS voice evaluation, comparable to the VHI. The present study highlights the potential of cepstral analysis as an index reflecting subjective voice discomfort, suggesting its promise for a comprehensive PTS voice evaluation.

Deep learning-based efficient drone-borne sensing of cyanobacterial blooms using a clique-based feature extraction approach.

Recent advances in remote sensing techniques provide a new horizon for monitoring the spatiotemporal variations of harmful algal blooms (HABs) using hyperspectral data in inland water. In this study, a hierarchical concatenated variational autoencoder (HCVAE) is proposed as an efficient and accurate deep learning (DL) based bio-optical model. To demonstrate its usefulness in retrieving algal pigments, the HCVAE is applied to bloom-prone regions in Daecheong Lake, South Korea. By abstracting the similarity between highly related features using layer-wise clique-based latent-feature extraction, HCVAE reduces the computational loads in deriving outputs while preventing performance degradation. Graph-based clique-detection uses information theory-based criteria to group the related reflectance spectra. Consequently, six latent features were extracted from 79 spectral bands to consist of a multilevel hierarchy of HCVAE that can simultaneously estimate concentrations of chlorophyll-a (Chl-a) and phycocyanin (PC). Despite the parsimonious model architecture, the Chl-a and PC concentrations estimated by HCVAE closely agree with the measured concentrations, with test R2 values of 0.76 and 0.82, respectively. In addition, spatial distribution maps of algal pigments obtained from HCVAE using drone-borne reflectance successfully capture the blooming spots. Based on its multilevel hierarchical architecture, HCVAE can provide the importance of latent features along with their individual wavelengths using Shapley additive explanations. The most important latent features covered the spectral regions associated with both Chl-a and PC. The lightweight neural network DNNsel, which uses only the spectral bands of highest importance in latent-feature extraction, performed comparably to HCVAE. The study results demonstrate the utility of the multilevel hierarchical architecture as a comprehensive assessment model for near-real-time drone-borne sensing of HABs. Moreover, HCVAE is applicable to a wide range of environmental big data, as it can handle numerous sets of features.

Automatic classification of microplastics and natural organic matter mixtures using a deep learning model.

Several preprocessing procedures are required for the classification of microplastics (MPs) in aquatic systems using spectroscopic analysis. Procedures such as oxidation, which are employed to remove natural organic matter (NOM) from MPs, can be time- and cost-intensive. Furthermore, the identification process is prone to errors due to the subjective judgment of the operators. Therefore, in this study, deep learning (DL) was applied to improve the classification accuracies for mixtures of microplastic and natural organic matter (MP-NOM). A convolutional neural network (CNN)-based DL model with a spatial attention mechanism was adopted to classify substances from their Raman spectra. Subsequently, the classification results were compared with those obtained using conventional Raman spectral library software to evaluate the applicability of the model. Additionally, the crucial spectral band for training the DL model was investigated by applying gradient-weighted class activation mapping (Grad-CAM) as a post-processing technique. The model achieved an accuracy of 99.54%, which is much higher than the 31.44% achieved by the Raman spectral library. The Grad-CAM approach confirmed that the DL model can effectively identify MPs based on their visually prominent peaks in the Raman spectra. Furthermore, by tracking distinctive spectra without relying solely on visually prominent peaks, we can accurately classify MPs with less prominent peaks, which are characterized by a high standard deviation of intensity. These findings demonstrate the potential for automated and objective classification of MPs without the need for NOM preprocessing, indicating a promising direction for future research in microplastic classification.

Treatment Efficacy of Various Maneuvers for Lateral Canal Benign Paroxysmal Positional Vertigo With Apogeotropic Nystagmus: A Randomized Controlled Trial.

OBJECTIVES: The aim of this study was to determine the most effective treatment approach by comparing the impacts of various otolith reduction techniques in patients with apogeotropic lateral semicircular canal benign paroxysmal positional vertigo (LC-BPPV). METHODS: We performed a multicenter randomized prospective study from January to December 2015, involving 72 consecutive patients with apogeotropic LC-BPPV. The patients were divided into three treatment groups: therapeutic head-shaking (group A), the Gufoni-Appiani maneuver (group B), and the cupulolith repositioning maneuver (CuRM; group C). Each group underwent evaluation and treatment up to the fourth week. Treatment success was defined as the disappearance of positional vertigo and nystagmus. RESULTS: This study included 72 patients (49 male and 23 female), with a mean (±standard deviation) age of 55.4±13.5 years. The mean duration of vertigo experienced prior to treatment was 3.9±4.4 days. The mean latency and duration of nystagmus were 2.7±3.0 seconds and 47.9±15.8 seconds, respectively. The overall treatment frequency was 2.0±0.9. The number of treatments differed significantly among the three groups (P<0.05). After 4 weeks, the success rates for groups A, B, and C were 90.5%, 92.3%, and 100%, respectively. No significant difference was observed in the success rate across treatment. METHODS: and periods (P>0.05). However, CuRM was the only method with a 100% treatment success rate. CONCLUSION: While no clear difference was observed among the three treatments for LC-BPPV, CuRM was found to be superior to the other approaches in the long term.

Microbiome of Acute Otitis Externa.

BACKGROUND: Ear canal skin is directly attached to bone or cartilage, and is also connected to the eardrum. Acute otitis externa is cellulitis of the ear canal skin and subdermal tissue associated with acute inflammation and variable edema. We characterized the microbiome of the normal ear canal and ear canal with otitis externa. METHODS: In total, 28 samples (14 each from the ear canal skin of patients with acute otitis externa and normal healthy controls) were collected using swabs. DNA extraction and bacterial microbiome analysis via 16S rRNA gene sequencing were performed. RESULTS: The diversity index (mean amplicon sequence variants and Shannon index) were lower in the otitis externa than control group. According to linear discriminant effect size (LEfSe) analysis, a number of taxa differed significantly between the groups. Pseudomonas at the genus level and Staphylococcus warneri at the species level were identified in the otitis externa group. CONCLUSION: Our results show the importance of the microbiome in the pathogenesis of otitis externa and provide a basis for treating acute otitis externa by targeting the microbiome.

Ear, Nose, and Throat Foreign Bodies in Children: A Retrospective Study.

BACKGROUND: This study analyzed the presentation, characteristics, and management of foreign bodies in different age groups of pediatric patients with ear, nose, and throat foreign bodies. METHODS: A retrospective study was performed using data from October 2012 to September 2020. A total of 1285 patients with ear, nose, and throat foreign bodies who were less than 12 years of age and who presented to the emergency room were included in this study. Their biographical data, clinical presentations, foreign body types and locations, and management outcomes were obtained from medical records and analyzed as three age groups (infancy: <2 years old; early childhood: 2-5 years old; and late childhood: 6-12 years old). RESULTS: The early childhood group had the highest number of patients (n = 672; 52.2%). Throat was the most common location (59.2%), and bone was the most common type of foreign body. Among the children who visited our hospital, foreign bodies were actually found in only 657 patients (51.1%) and removed by an otolaryngologist in 625 (95.1%) cases. CONCLUSION: Our study could provide guidance for the diagnosis and management of pediatric patients who present to emergency departments with foreign bodies.

Microbiome of Unilateral Chronic Rhinosinusitis: A Controlled Paired Analysis.

The sinonasal microbiota in human upper airway may play an important role in chronic rhinosinusitis (CRS). Thus, this study aimed to investigate the human upper airway microbiome in patients with unilateral CRS, and compare the sinonasal microbiome of the unilateral diseased site with that of a contralateral healthy site. Thirty samples, 15 each from the diseased and healthy sites, were collected from the middle meatus and/or anterior ethmoid region of 15 patients with unilateral CRS during endoscopic sinus surgery. DNA extraction and bacterial microbiome analysis via 16S rRNA gene sequencing were then performed. Corynebacterium showed the highest relative abundance, followed by Staphylococcus in samples from both the diseased and healthy sites. Further, the relative abundances of Staphylococcus and Pseudomonas were significantly lower in samples from diseased sites than in those from healthy sites. Conversely, anaerobes, including Fusobacterium, Bacteroides, and Propionibacterium, were abundantly present in samples from both sites, more so in samples from diseased sites. However, the sites showed no significant difference with respect to richness or diversity (p > 0.05). Our results indicate that CRS might be a polymicrobial infection, and also suggest that Corynebacterium and Staphylococcus may exist as commensals on the sinus mucosal surface in the upper respiratory tract.

Multiple Daily Rounds of Theta-Burst Stimulation for Tinnitus: Preliminary Results.

Background and Objectives: Tinnitus is a condition that negatively affects the quality of life and is difficult to treat. Theta burst stimulation (TBS), a new method of repetitive transcranial magnetic stimulation (rTMS), is a promising treatment approach because it shows stronger and more prolonged effects in a shorter time of stimulation than other rTMS protocols. However, the therapeutic effect of TBS for tinnitus was inconsistent. We hypothesized that more stimulation would be more effective. Therefore, this study aimed to explore the safety and effectiveness of multiple daily rounds of TBS over five consecutive days. Materials and Methods: The continuous TBS (cTBS) protocol is 300 pulses/day, but we applied 8 sessions of 300 pulses in a day (total 2400 pulses/day). A total of 15 patients with tinnitus were randomly assigned to treatment and sham groups. Outcome measurements were taken three times: before and after 5-day of stimulation; at a 1-3 month follow-up visit. Outcome measurements were the degree of annoyance due to ear fullness, duration of tinnitus, visual analog scales of tinnitus for annoyance, Tinnitus Handicap Inventory, pitch, loudness, minimum masking level, and residual inhibition. Results: Five-day cTBS was completed without adverse events. We did not find any significant therapeutic effect in the treatment group, but we needed to be cautious to interpret our result due to the small sample size. Conclusions: In conclusion, multiple rounds of cTBS in a day may be safe. Further research is needed in a larger sample size to determine the effectiveness and confirm the safety.

Monitoring the vertical distribution of HABs using hyperspectral imagery and deep learning models.

Remote sensing techniques have been applied to monitor the spatiotemporal variation of harmful algal blooms (HABs) in many inland waters. However, these studies have been limited to monitor the vertical distribution of HABs due to the optical complexity of inland water. Therefore, this study applied a deep neural network model to monitor the vertical distribution of Chlorophyll-a (Chl-a), phycocyanin (PC), and turbidity (Turb) using drone-borne hyperspectral imagery, in-situ measurement, and meteoroidal data. The pigment concentrations were measured between depths of 0 m and 5.0 m with 0.05 m intervals. Here, four state-of-the-art data-driven model structures (ResNet-18, ResNet-101, GoogLeNet, and Inception v3) were adopted for estimating the vertical distributions of the harmful algal pigments. Among the four models, the ResNet-18 model showed the best performance, with an R2 value of 0.70. In addition, Gradient-weighted Class Activation Mapping (Grad-CAM) substantially provided informative reflectance band ranges near 490 nm and 620 nm in the hyperspectral image for the vertical estimation of pigments. Therefore, this study demonstrated that the explainable deep learning model with drone-borne hyperspectral images has the potential to estimate Chl-a, PC, and Turb vertical distributions and to show influential features that contribute to describing the vertical profile phenomena.

Evaluating an on-line cleaning agent for mitigating organic fouling in a reverse osmosis membrane.

Cleaning-in-place (CIP) is a representative fouling management process from which the filtration performances of fouled membranes can be recovered. However, CIP can cause significant inefficiency in water production because frequent system restabilization is necessary for cleaning processes. This study applied a newly developed on-line cleaning agent (OCA, a feed water additive for fouling mitigation), to reduce the number of CIP by enhancing water productivity. Reverse osmosis filtration was performed to evaluate the effect of on-line cleaning on the mitigation of organic fouling originating from humic acid (HA) and bovine serum albumin. OCA increased the permeate flux in proportion to OCA concentration. In particular, OCA effectively reduced the fouling layer thickness by 22% when fouling was influenced by HA-Ca2+ complexation, increasing water production by 5%. It also had a minor influence on bovine serum albumin fouling, producing a 1.4% increase in permeate flux. Furthermore, the pore blockage-cake filtration model was used to evaluate OCA cleaning performance through the reduction in fouling layer resistance and the growth parameter. The results demonstrated the advantages of OCA utilization for mitigating cake layer development. These findings imply that OCA can be an effective cleaning additive, especially in seawater and groundwater treatment processes with a high proportion of HA and calcium ions.

Mood Disorders are Associated With Increased Risk of BPPV: A National Sample Cohort.

OBJECTIVES: Few studies have reported that mood disorders increase the risk of benign paroxysmal positional vertigo (BPPV). The purpose of our study was to demonstrate whether the incidence of BPPV in those with mood disorders differs from that in a matched control group. STUDY DESIGN: Nationwide cohort observational study. METHODS: Korean Health Insurance Review and Assessment Service-National Patient Samples were collected from 2002 to 2013. A 1:4 matched mood disorder group (n = 59,340) and control group (n = 237,720) were selected. The crude and adjusted (cerebral stroke, ischemic heart disease, anxiety disorder, and osteoporosis histories) hazard ratios (HRs) for depression and BPPV were analyzed using a stratified Cox proportional hazard model. The results were stratified by age, sex, income, region of residence, hypertension, diabetes, and dyslipidemia in these analyses. RESULTS: The incidence of BPPV was significantly higher in the mood disorder group than in the control group (3.2% vs. 2.1%, P < .001). Mood disorder increased the risk of BPPV (adjusted HR = 1.31, 95% confidence interval [CI] = 1.23-1.39, P < .001). In subgroup analyses, the incidence of BPPV in all age groups and in both sexes was significantly higher in the mood disorder group than in the control group. CONCLUSION: This population-based cohort study demonstrates that mood disorder was significantly associated with BPPV. LEVEL OF EVIDENCE: N/A. Laryngoscope, 131:380-385, 2021.

Comparison of the human microbiome in adults and children with chronic rhinosinusitis.

We hypothesized that differences in the microbiome could be a cause of the substantial differences in the symptoms of and treatment options for adult and pediatric patients with chronic rhinosinusitis (CRS). First, we characterized the differences in the nasal microbiomes of pediatric and adult CRS patients. Swabs were obtained from 19 patients with chronic rhinosinusitis (9 children and 10 adults). The bacterial 16S rRNA gene was pyrosequenced to compare the microbiota of the middle meatus. No significant differences were found in species richness and alpha-diversity indices between the two groups. However, in the comparison of diversity between groups using the unweighted pair group method with arithmetic mean (UPGMA) clustering of microbiome taxonomic profiles, we observed a relatively clear separation between the adult and pediatric groups. Actinobacteria had a significantly higher relative abundance in the adult group than in the pediatric group at the phylum level. At the genus level, Corynebacterium showed significantly higher relative abundance in the adult group than in the pediatric group. This is a comparative study between the microbiomes of adult and pediatric CRS patients. We expect this study to be the first step in understanding the pathogenesis of CRS in adults and children using microbiome analysis.

Psoriasis Increases the Risk of Sudden Sensorineural Hearing Loss: A Longitudinal Follow Up Study Using a National Sample Cohort.

Psoriasis is a well-known immune-mediated disease. Its autoimmune pathophysiology is consistent with the immune-mediated systemic vascular hypothesis regarding the pathogenesis of sudden sensorineural hearing loss (SSNHL). The purpose of our study was to investigate whether psoriasis affects the prevalence of SSNHL in all age groups matched by age, sex, income, and region of residence. Korean Health Insurance Review and Assessment Service-National Patient Samples were collected from 2002 to 2013. A 1:4 matched psoriasis group (n = 12,864) and control group (n = 51,456) were selected. The crude (simple) and adjusted (Charlson comorbidity index) hazard ratios (HR) for psoriasis and SSNHL were analyzed using the stratified Cox proportional hazard model. The incidence of SSNHL was significantly higher in the psoriasis group than in the control group (0.5% vs. 0.4%, p = 0.004). Psoriasis increased the risk of SSNHL (adjusted HR = 1.44, 95% confidence interval (CI) = 1.09-1.90, p = 0.010). In the stratification analysis, the incidence of SSNHL was significantly higher in the 30-59-year-old group than other group SSNHL (adjusted HR = 1.50, 95% CI = 1.06-2.12, p = 0.023). In addition, SSNHL occurred significantly more frequently in men with psoriasis (adjusted HR = 1.70, 95% CI = 1.17-2.49, p = 0.006). Psoriasis increased the risk of SSNHL, and SSNHL was more prevalent in between the age of 30-59-year-olds and men with psoriasis.

Feasibility of Powered Intracapsular Tonsillectomy in Pediatric Patients with Tonsil Problem, Including Recurrent Tonsillitis: A Single Surgeon's Experience.

INTRODUCTION: Powered intracapsular tonsillectomy (PIT) is a technique that protects the tonsillar capsule by using a microdebrider, resulting in faster wound-healing and reduced suffering. Many studies have found PIT to be effective, particularly in pediatric patients with obstructive sleep apnea (OSA). However, previous studies have not included patients with a history of recurrent tonsillitis. OBJECTIVE: The aim of this study was to determine the efficacy of PIT in pediatric patients even with a history of recurrent tonsillitis, and therefore, we want to expand the indication for PIT and reveal its safety. METHODS: A total of 886 pediatric patients underwent PIT between February 2013 and March 2016. All patients rated their postoperative pain using a visual analog scale (VAS) and completed the Korean obstructive sleep apnea (KOSA)-18 questionnaire for assessment of their quality of life (QOL). There were 539 males and 347 females. Their mean age was 6.2 years (range 2-14 years). The majority (77.7%) underwent the operation for OSA, and the rest (22.3%) had a history of recurrent tonsillitis. To compare the efficacy of PIT with traditional tonsillectomy, we selected 191 patients who underwent extracapsular tonsillectomy (ECT), a conventional technique, during the same time period. The median follow-up period was 16.7 months. During the follow-up period, instances of delayed bleeding and recurrent pharyngitis were monitored. RESULTS: In comparison to the patients who underwent ECT, the PIT group showed significantly fewer cases of postoperative bleeding (p = 0.027). Thirteen patients in the PIT group (1.5%) visited the hospital during the follow-up period for pharyngitis, while 8 in the ECT group (4.2%) visited for pharyngitis. The mean postoperative pain score, as assessed by a VAS, was 4.6 ± 3.2, and pain improved within an average of 2.9 days after surgery in the PIT group. The mean KOSA-18 score for the QOL of the patients was 65.9 preoperatively and 35.6 postoperatively in the PIT group. CONCLUSIONS: Pediatric tonsillectomy using PIT is valid for reducing postoperative pain and improving the QOL of OSA patients. PIT is also effective and safe for patients with a history of recurrent tonsillitis.

Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil.

Heavy metal contamination in soil disturbs the chemical, biological, and physical soil conditions and adversely affects the health of living organisms. Visible and near-infrared spectroscopy (VNIRS) shows a potential feasibility for estimating heavy metal elements in soil. Moreover, deep learning models have been shown to successfully deal with complex multi-dimensional and multivariate nonlinear data. Thus, this study implemented a deep learning method on reflectance spectra of soil samples to estimate heavy metal concentrations. A convolutional neural network (CNN) was adopted to estimate arsenic (As), copper (Cu), and lead (Pb) concentrations using measured soil reflectance. In addition, a convolutional autoencoder was utilized as a joint method with the CNN for dimensionality reduction of the reflectance spectra. Furthermore, artificial neural network (ANN) and random forest regression (RFR) models were built for heavy metal estimation. Principal component analysis was utilized for dimensionality reduction of the ANN and RFR models. Among these models, the CNN model with convolutional autoencoder showed the highest accuracies for As, Cu, and Pb estimates, having R2 values of 0.86, 0.74, and 0.82, respectively. The convolutional autoencoder disentangled the relevant features of multiple heavy metal elements and delivered robust features to the CNN model, thereby generating relatively accurate estimates.

Biomimetic Gold Nanoshell-Loaded Macrophage for Photothermal Biomedicine.

The purpose of this study was to investigate the effect of photothermal treatment (PTT) with gold nanoshell (ANS) using a macrophage-mediated delivery system in a head and neck squamous cell carcinoma (HNSCC) cell line. To achieve this, ANS-loaded rat macrophages (ANS-MAs) were prepared via the coculture method with ANS. The human HNSCC (FaDu cell) and macrophage (rat macrophage; NR8383 cell) hybrid spheroid models were generated by the centrifugation method to determine the possibility of using ANS-MAs as a cancer therapy. These ANS-MAs were set into the tumor and macrophage hybrid spheroid model to measure PTT efficacy. Kinetic analysis of the spheroid growth pattern revealed that this PTT process caused a decreasing pattern in the volume of the hybrid model containing ANS-MAs (p < 0.001). Comparison with empty macrophages showed harmony between ANS and laser irradiation for the generation of PTT. An annexin V/dead cell marker assay indicated that the PTT-treated hybrid model induced increasing apoptosis and dead cells. Further studies on the toxicity of ANS-MAs are needed to reveal whether it can be considered biocompatible. In summary, the ANS was prepared with a macrophage as the delivery method and protective carrier. The ANS was successfully localized to the macrophages, and their photoabsorption property was stationary. This strategy showed significant growth inhibition of the tumor and macrophage spheroid model under NIR laser irradiation. In vivo toxicology results suggest that ANS-MA is a promising candidate for a biocompatible strategy to overcome the limitations of fabricated nanomaterials. This ANS-MA delivery and PTT strategy may potentially lead to improvements in the quality of life of patients with HNSCC by providing a biocompatible, minimally invasive modality for cancer treatment.

Automatic detection of tympanic membrane and middle ear infection from oto-endoscopic images via convolutional neural networks.

Convolutional neural networks (CNNs), a popular type of deep neural network, have been actively applied to image recognition, object detection, object localization, semantic segmentation, and object instance segmentation. Accordingly, the applicability of deep learning to the analysis of medical images has increased. This paper presents a novel application of state-of-the-art CNN models, such as DenseNet, to the automatic detection of the tympanic membrane (TM) and middle ear (ME) infection. We collected 2,484 oto-endoscopic images (OEIs) and classified them into one of three categories: normal, chronic otitis media (COM) with TM perforation, and otitis media with effusion (OME). Our results indicate that CNN models have significant potential for the automatic recognition of TM and ME infections, demonstrating a competitive accuracy of 95% in classifying TM and middle ear effusion (MEE) from OEIs. In addition to accuracy measurement, our approach achieves nearly perfect measures of 0.99 in terms of the average area under the receiver operating characteristics curve (AUROC). All these results indicate robust performance when recognizing TM and ME effusions in OEIs. Visualization through a class activation mapping (CAM) heatmap demonstrates that our proposed model performs prediction based on the correct region of OEIs. All these outcomes ensure the reliability of our method; hence, the study can aid otolaryngologists and primary care physicians in real-world scenarios.

Analysis of the Microbiome in the Adenoids of Korean Children with Otitis Media with Effusion.

OBJECTIVES: The adenoid pad, which is located between the orifice of the Eustachian tube (ET) and posterior nasal cavity, can affect the development of otitis media with effusion (OME) because of its anatomical location. The aim of the present study was to evaluate adenoid microbial colonization through 16S ribosomal RNA (rRNA) pyrosequencing, an advanced molecular technique, and to document the relationship with OME. MATERIALS AND METHODS: Adenoid samples were collected using sterile cotton from 32 children during ventilation tube insertion. Sixteen children with OME who underwent tonsillectomy and adenoidectomy due to obstructive symptoms were assigned to the OME group and sixteen children without OME were assigned to the control group. We performed a 16S rRNA-based culture-independent survey of bacterial communities using the MiSeq platform. RESULTS: The diversity index, mean operational taxonomic units, and Shannon index were lower in the OME group than those in the control group. A taxonomic analysis showed differences in microbiota distribution between the OME and control groups at the phylum, genus, and species levels. The analysis, which was based on weighted UniFrac distances, revealed differences in microbial composition between the two groups. CONCLUSION: Bacterial community analysis using 16S rRNA pyrosequencing allows us to understand the relationship between the microbial communities of adenoids and the development of OME better.