Machine learning-based longitudinal prediction for GJB2-related sensorineural hearing loss.

BACKGROUND: Recessive GJB2 variants, the most common genetic cause of hearing loss, may contribute to progressive sensorineural hearing loss (SNHL). The aim of this study is to build a realistic predictive model for GJB2-related SNHL using machine learning to enable personalized medical planning for timely intervention. METHOD: Patients with SNHL with confirmed biallelic GJB2 variants in a nationwide cohort between 2005 and 2022 were included. Different data preprocessing protocols and computational algorithms were combined to construct a prediction model. We randomly divided the dataset into training, validation, and test sets at a ratio of 72:8:20, and repeated this process ten times to obtain an average result. The performance of the models was evaluated using the mean absolute error (MAE), which refers to the discrepancy between the predicted and actual hearing thresholds. RESULTS: We enrolled 449 patients with 2184 audiograms available for deep learning analysis. SNHL progression was identified in all models and was independent of age, sex, and genotype. The average hearing progression rate was 0.61 dB HL per year. The best MAE for linear regression, multilayer perceptron, long short-term memory, and attention model were 4.42, 4.38, 4.34, and 4.76 dB HL, respectively. The long short-term memory model performed best with an average MAE of 4.34 dB HL and acceptable accuracy for up to 4 years. CONCLUSIONS: We have developed a prognostic model that uses machine learning to approximate realistic hearing progression in GJB2-related SNHL, allowing for the design of individualized medical plans, such as recommending the optimal follow-up interval for this population.

Combining wireless radar sleep monitoring device with deep machine learning techniques to assess obstructive sleep apnea severity.

STUDY OBJECTIVES: The gold standard for diagnosing obstructive sleep apnea (OSA) is polysomnography (PSG). However, PSG is a time-consuming method with clinical limitations. This study aimed to create a wireless radar framework to screen the likelihood of two levels of OSA severity (i.e., moderate-to-severe and severe OSA) in accordance with clinical practice standards. METHODS: We conducted a prospective, simultaneous study using the wireless radar system and PSG in a Northern Taiwan sleep center, involving 196 patients. The wireless radar sleep monitor, incorporating hybrid models such as deep neural decision trees, estimated the respiratory disturbance index relative to the total sleep time established by PSG (RDIPSG_TST), by analyzing continuous-wave signals indicative of breathing patterns. Analyses were performed to examine the correlation and agreement between the RDIPSG_TST and apnea-hypopnea index (AHI), results obtained through PSG. Cut-off thresholds for RDIPSG_TST were determined using Youden's index, and multiclass classification was performed, after which the results were compared. RESULTS: A strong correlation (ρ = 0.91) and agreement (average difference of 0.59 events/h) between AHI and RDIPSG_TST were identified. In terms of the agreement between the two devices, the average difference between PSG-based AHI and radar-based RDIPSG_TST was 0.59 events/h, while 187 out of 196 cases (95.41%) fell within the 95% confidence interval of differences. A moderate-to-severe OSA model achieved an accuracy of 90.3% (cut-off threshold for RDIPSG_TST: 19.2 events/h). A severe OSA model achieved an accuracy of 92.4% (cut-off threshold for RDIPSG_TST: 28.86 events/h). The mean accuracy of multiclass classification performance using these cut-off thresholds was 83.7%. CONCLUSIONS: The wireless-radar-based sleep monitoring device, with cut-off thresholds, can provide rapid OSA screening with acceptable accuracy, and also alleviate the burden on PSG capacity. However, to independently apply this framework, the function of determining the radar-based total sleep time requires further optimizations and verification in future work.

Otoprotection against aminoglycoside- and cisplatin-induced ototoxicity focusing on the upstream drug uptake pathway.

Aminoglycoside- and cisplatin-induced ototoxicity, which is a significant issue owing to the widespread use of these drugs in clinical practice, involves the entry of aminoglycosides and cisplatin into the endolymph and hair cells via specific channels or transporters, followed by reactive oxygen species (ROS) generation and hair cells apoptosis. Current strategies focalize primarily on interference with downstream ROS effects; however, recent evidence has demonstrated that inhibiting the uptake of aminoglycosides and cisplatin by hair cells is another promising strategy for tackling the upstream drug uptake pathway. With advances in structural biology, the conformations of certain aminoglycoside and cisplatin channels and transporters, such as the mechanoelectrical transduction channel and organic cation transporter-2, have been largely elucidated. These channels and transporters may become potential targets for the introduction of new otoprotective strategies. This review focuses on the strategies for inhibiting ototoxic drugs uptake by auditory hair cells and provides potential targets for recent developments in the field of otoprotection. Molecular dynamics (MD) simulations of these proteins could help identify the molecules that inhibit the uptake of aminoglycosides and cisplatin by hair cells. Integrating upstream drug uptake pathway targets and MD simulations may help dissect molecular mechanisms and develop novel otoprotective strategies for aminoglycoside- and cisplatin-induced ototoxicity.

Simulation-predicted and -explained inheritance model of pathogenicity confirmed by transgenic mice models.

Variants in the gap junction beta-2 (GJB2) gene are the most common cause of hereditary hearing impairment. However, how GJB2 variants lead to local physicochemical and structural changes in the hexameric ion channels of connexin 26 (Cx26), resulting in hearing impairment, remains elusive. In this study, using molecular dynamics (MD) simulations, we showed that detached inner-wall N-terminal "plugs" aggregated to reduce the channel ion flow in a highly prevalent V37I variant in humans. To examine the predictive ability of the computational platform, an artificial mutant, V37M, of which the effect was previously unknown in hearing loss, was created. Microsecond simulations showed that homo-hexameric V37M Cx26 hemichannels had an abnormal affinity between the inner edge and N-termini to block the narrower side of the cone-shaped Cx26, while the most stable hetero-hexameric channels did not. From the perspective of the conformational energetics of WT and variant Cx26 hexamers, we propose that unaffected carriers could result from a conformational predominance of the WT and pore-shrinkage-incapable hetero-hexamers, while mice with homozygous variants can only harbor an unstable and dysfunctional N-termini-blocking V37M homo-hexamer. Consistent with these predictions, homozygous V37M transgenic mice exhibited apparent hearing loss, but not their heterozygous counterparts, indicating a recessive inheritance mode. Reduced channel conductivity was found in Gjb2V37M/V37M outer sulcus and Claudius cells but not in Gjb2WT/WT cells. We view that the current computational platform could serve as an assessment tool for the pathogenesis and inheritance of GJB2-related hearing impairments and other diseases caused by connexin dysfunction.

Association between air pollutant exposure, body water distribution and sleep disorder indices in individuals with low-arousal-threshold obstructive sleep apnoea.

BACKGROUND: Air pollution may alter body water distribution, it may also be linked to low-arousal-threshold obstructive sleep apnoea (low-ArTH OSA). Here, we explored the mediation effects of air pollution on body water distribution and low-ArTH OSA manifestations. METHODS: In this retrospective study, we obtained sleep centre data from healthy participants and patients with low-ArTH OSA (N=1924) in northern Taiwan. Air pollutant exposure at different time intervals (1, 3, 6 and 12 months) was estimated using the nearest station estimation method, and government air-quality data were also obtained. Regression models were used to assess the associations of estimated exposure, sleep disorder indices and body water distribution with the risk of low-ArTH OSA. Mediation analysis was performed to explore the relationships between air pollution, body water distribution and sleep disorder indices. RESULTS: First, exposure to particulate matter (PM) with a diameter of ≤10 µm (PM10) for 1 and 3 months and exposure to PM with a diameter of ≤2.5 µm (PM2.5) for 3 months were significantly associated with the Apnoea-Hypopnoea Index (AHI), Oxygen Desaturation Index (ODI), Arousal Index (ArI) and intracellular-to-extracellular water ratio (I-E water ratio). Significant associations were observed between the risk of low-ArTH OSA and 1- month exposure to PM10 (OR 1.42, 95% CI 1.09 to 1.84), PM2.5 (OR 1.33, 95% CI 1.02 to 1.74) and ozone (OR 1.27, 95% CI 1.01 to 1.6). I-E water ratio alternation caused by 1-month exposure to PM10 and 3-month exposure to PM2.5 and PM10 had partial mediation effects on AHI and ODI. CONCLUSION: Air pollution can directly increase sleep disorder indices (AHI, ODI and ArI) and alter body water distribution, thus mediating the risk of low-ArTH OSA.

Machine learning approaches for predicting sleep arousal response based on heart rate variability, oxygen saturation, and body profiles.

Objective: Obstructive sleep apnea is a global health concern, and several tools have been developed to screen its severity. However, most tools focus on respiratory events instead of sleep arousal, which can also affect sleep efficiency. This study employed easy-to-measure parameters-namely heart rate variability, oxygen saturation, and body profiles-to predict arousal occurrence. Methods: Body profiles and polysomnography recordings were collected from 659 patients. Continuous heart rate variability and oximetry measurements were performed and then labeled based on the presence of sleep arousal. The dataset, comprising five body profiles, mean heart rate, six heart rate variability, and five oximetry variables, was then split into 80% training/validation and 20% testing datasets. Eight machine learning approaches were employed. The model with the highest accuracy, area under the receiver operating characteristic curve, and area under the precision recall curve values in the training/validation dataset was applied to the testing dataset and to determine feature importance. Results: InceptionTime, which exhibited superior performance in predicting sleep arousal in the training dataset, was used to classify the testing dataset and explore feature importance. In the testing dataset, InceptionTime achieved an accuracy of 76.21%, an area under the receiver operating characteristic curve of 84.33%, and an area under the precision recall curve of 86.28%. The standard deviations of time intervals between successive normal heartbeats and the square roots of the means of the squares of successive differences between normal heartbeats were predominant predictors of arousal occurrence. Conclusions: The established models can be considered for screening sleep arousal occurrence or integrated in wearable devices for home-based sleep examination.

Rectal administration of tacrolimus protects against post-ERCP pancreatitis in mice.

OBJECTIVE: There is an unmet clinical need for effective, targeted interventions to prevent post-ERCP pancreatitis (PEP). We previously demonstrated that the serine-threonine phosphatase, calcineurin (Cn) is a critical mediator of PEP and that the FDA-approved calcineurin inhibitors, tacrolimus (Tac) or cyclosporine A, prevented PEP. Our recent observations in preclinical PEP models demonstrating that Cn deletion in both pancreatic and hematopoietic compartments is required for maximal pancreas protection, highlighted the need to target both systemic and pancreas-specific Cn signaling. We hypothesized that rectal administration of Tac would effectively mitigate PEP by ensuring systemic and pancreatic bioavailability of Tac. We have tested the efficacy of rectal Tac in a preclinical PEP model and in cerulein-induced experimental pancreatitis. METHODS: C57BL/6 mice underwent ductal cannulation with saline infusion to simulate pressure-induced PEP or were given seven, hourly, cerulein injections to induce pancreatitis. To test the efficacy of rectal Tac in pancreatitis prevention, a rectal Tac suppository (1 mg/kg) was administered 10 min prior to cannulation or first cerulein injection. Histological and biochemical indicators of pancreatitis were evaluated post-treatment. Pharmacokinetic parameters of Tac in the blood after rectal delivery compared to intravenous and intragastric administration was evaluated. RESULTS: Rectal Tac was effective in reducing pancreatic injury and inflammation in both PEP and cerulein models. Pharmacokinetic studies revealed that the rectal administration of Tac helped achieve optimal blood levels of Tac over an extended time compared to intravenous or intragastric delivery. CONCLUSION: Our results underscore the effectiveness and clinical utility of rectal Tac for PEP prophylaxis.

Genetic Factors Contribute to the Phenotypic Variability in GJB2-Related Hearing Impairment.

Recessive variants in GJB2 are the most important genetic cause of sensorineural hearing impairment (SNHI) worldwide. Phenotypes vary significantly in GJB2-related SNHI, even in patients with identical variants. For instance, patients homozygous for the GJB2 p.V37I variant, which is highly prevalent in the Asian populations, usually present with mild-to-moderate SNHI; yet severe-to-profound SNHI is occasionally observed in approximately 10% of p.V37I homozygotes. To investigate the genomic underpinnings of the phenotypic variability, we performed next-generation sequencing of GJB2 and other deafness genes in 63 p.V37I homozygotes with extreme phenotypic severities. We identified additional pathogenic variants of other deafness genes in 5 of the 35 patients with severe-to-profound SNHI. Furthermore, we conducted case-control association analyses for 30 unrelated p.V37I homozygotes with severe-to-profound SNHI against 28 p.V37I homozygotes with mild-to-moderate SNHI, and 120 population controls from the Taiwan Biobank. We found that the severe-to-profound group had a higher frequency of the crystallin lambda 1 (CRYL1) variant (rs14236), located upstream of GJB2, than the mild-to-moderate and Taiwan Biobank groups. Our results demonstrated that pathogenic variants in other deafness genes and a possible modifier, the CRYL1 rs14236 variant, may contribute to phenotypic variability in GJB2-realted SNHI, highlighting the importance of comprehensive genomic surveys to delineate the genotype-phenotype correlations.

Prediction of posttraumatic functional recovery in middle-aged and older patients through dynamic ensemble selection modeling.

Introduction: Age-specific risk factors may delay posttraumatic functional recovery; complex interactions exist between these factors. In this study, we investigated the prediction ability of machine learning models for posttraumatic (6 months) functional recovery in middle-aged and older patients on the basis of their preexisting health conditions. Methods: Data obtained from injured patients aged ≥45 years were divided into training-validation (n = 368) and test (n = 159) data sets. The input features were the sociodemographic characteristics and baseline health conditions of the patients. The output feature was functional status 6 months after injury; this was assessed using the Barthel Index (BI). On the basis of their BI scores, the patients were categorized into functionally independent (BI >60) and functionally dependent (BI ≤60) groups. The permutation feature importance method was used for feature selection. Six algorithms were validated through cross-validation with hyperparameter optimization. The algorithms exhibiting satisfactory performance were subjected to bagging to construct stacking, voting, and dynamic ensemble selection models. The best model was evaluated on the test data set. Partial dependence (PD) and individual conditional expectation (ICE) plots were created. Results: In total, nineteen of twenty-seven features were selected. Logistic regression, linear discrimination analysis, and Gaussian Naive Bayes algorithms exhibited satisfactory performances and were, therefore, used to construct ensemble models. The k-Nearest Oracle Elimination model outperformed the other models when evaluated on the training-validation data set (sensitivity: 0.732, 95% CI: 0.702-0.761; specificity: 0.813, 95% CI: 0.805-0.822); it exhibited compatible performance on the test data set (sensitivity: 0.779, 95% CI: 0.559-0.950; specificity: 0.859, 95% CI: 0.799-0.912). The PD and ICE plots showed consistent patterns with practical tendencies. Conclusion: Preexisting health conditions can predict long-term functional outcomes in injured middle-aged and older patients, thus predicting prognosis and facilitating clinical decision-making.

Associations between air pollution, intracellular-to-extracellular water distribution, and obstructive sleep apnea manifestations.

Background: Exposure to air pollution may be a risk factor for obstructive sleep apnea (OSA) because air pollution may alter body water distribution and aggravate OSA manifestations. Objectives: This study aimed to investigate the mediating effects of air pollution on the exacerbation of OSA severity through body water distribution. Methods: This retrospective study analyzed body composition and polysomnographic data collected from a sleep center in Northern Taiwan. Air pollution exposure was estimated using an adjusted nearest method, registered residential addresses, and data from the databases of government air quality motioning stations. Next, regression models were employed to determine the associations between estimated air pollution exposure levels (exposure for 1, 3, 6, and 12 months), OSA manifestations (sleep-disordered breathing indices and respiratory event duration), and body fluid parameters (total body water and body water distribution). The association between air pollution and OSA risk was determined. Results: Significant associations between OSA manifestations and short-term (1 month) exposure to PM2.5 and PM10 were identified. Similarly, significant associations were identified among total body water and body water distribution (intracellular-to-extracellular body water distribution), short-term (1 month) exposure to PM2.5 and PM10, and medium-term (3 months) exposure to PM10. Body water distribution might be a mediator that aggravates OSA manifestations, and short-term exposure to PM2.5 and PM10 may be a risk factor for OSA. Conclusion: Because exposure to PM2.5 and PM10 may be a risk factor for OSA that exacerbates OSA manifestations and exposure to particulate pollutants may affect OSA manifestations or alter body water distribution to affect OSA manifestations, mitigating exposure to particulate pollutants may improve OSA manifestations and reduce the risk of OSA. Furthermore, this study elucidated the potential mechanisms underlying the relationship between air pollution, body fluid parameters, and OSA severity.

Predicting Fatigue-Associated Aberrant Driving Behaviors Using a Dynamic Weighted Moving Average Model With a Long Short-Term Memory Network Based on Heart Rate Variability.

OBJECTIVE: This study proposed a moving average (MA) approach to dynamically process heart rate variability (HRV) and developed aberrant driving behavior (ADB) prediction models by using long short-term memory (LSTM) networks. BACKGROUND: Fatigue-associated ADBs have traffic safety implications. Numerous models to predict such acts based on physiological responses have been developed but are still in embryonic stages. METHOD: This study recorded the data of 20 commercial bus drivers during their routine tasks on four consecutive days and subsequently asked them to complete questionnaires, including subjective sleep quality, driver behavior questionnaire and the Karolinska Sleepiness Scale. Driving behaviors and corresponding HRV were determined using a navigational mobile application and a wristwatch. The dynamic-weighted MA (DWMA) and exponential-weighted MA were used to process HRV in 5-min intervals. The data were independently separated for training and testing. Models were trained with 10-fold cross-validation strategy, their accuracies were evaluated, and Shapley additive explanation (SHAP) values were used to determine feature importance. RESULTS: Significant increases in the standard deviation of NN intervals (SDNN), root mean square of successive heartbeat interval differences (RMSSD), and normalized spectrum of high frequency (nHF) were observed in the pre-event stage. The DWMA-based model exhibited the highest accuracy for both driver types (urban: 84.41%; highway: 80.56%). The SDNN, RMSSD, and nHF demonstrated relatively high SHAP values. CONCLUSION: HRV metrics can serve as indicators of mental fatigue. DWMA-based LSTM could predict the occurrence of the level of fatigue associated with ADBs. APPLICATION: The established models can be used in realistic driving scenarios.

Topological and random spread models with frozen symbols.

When a symbol or a type has been "frozen" (namely, a type of which an individual only produces one individual of the same type), its spread pattern will be changed and this change will affect the long-term behavior of the whole system. However, in a frozen system, the ξ-matrix and the offspring mean matrix are no longer primitive so that the Perron-Frobenius theorem cannot be applied directly when predicting the spread rates. In this paper, our goal is to characterize these key matrices and analyze the spread rate under more general settings both in the topological and random spread models with frozen symbols. More specifically, we propose an algorithm for explicitly computing the spread rate and relate the rate with the eigenvectors of the ξ-matrix or offspring mean matrix. In addition, we reveal that the growth of the population is exponential and that the composition of the population is asymptotically periodic. Furthermore, numerical experiments are provided as supporting evidence for the theory.

Association of Low Arousal Threshold Obstructive Sleep Apnea Manifestations with Body Fat and Water Distribution.

Obstructive sleep apnea (OSA) with a low arousal threshold (low-ArTH) phenotype can cause minor respiratory events that exacerbate sleep fragmentation. Although anthropometric features may affect the risk of low-ArTH OSA, the associations and underlying mechanisms require further investigation. This study investigated the relationships of body fat and water distribution with polysomnography parameters by using data from a sleep center database. The derived data were classified as those for low-ArTH in accordance with criteria that considered oximetry and the frequency and type fraction of respiratory events and analyzed using mean comparison and regression approaches. The low-ArTH group members (n = 1850) were significantly older and had a higher visceral fat level, body fat percentage, trunk-to-limb fat ratio, and extracellular-to-intracellular (E-I) water ratio compared with the non-OSA group members (n = 368). Significant associations of body fat percentage (odds ratio [OR]: 1.58, 95% confident interval [CI]: 1.08 to 2.3, p < 0.05), trunk-to-limb fat ratio (OR: 1.22, 95% CI: 1.04 to 1.43, p < 0.05), and E-I water ratio (OR: 1.32, 95% CI: 1.08 to 1.62, p < 0.01) with the risk of low-ArTH OSA were noted after adjustments for sex, age, and body mass index. These observations suggest that increased truncal adiposity and extracellular water are associated with a higher risk of low-ArTH OSA.

A Novel Synthetic Oleanolic Acid Derivative Inhibits Glioma Cell Proliferation by Regulating Cell Cycle G2/M Arrest.

2-Cyano-3,12-dioxooleana-1,9(11)-dien-28-oic acid-9,11-dihydro-trifluoroethyl amide (CDDO-dhTFEA) has antioxidant and anti-inflammatory activities; however, whether CDDO-dhTFEA has anticancer effects is unclear. The objective of this research was to investigate the possibility of CDDO-dhTFEA as a potential cancer-fighting treatment in glioblastoma cells. Our experiments were performed on U87MG and GBM8401 cells, and we found that CDDO-dhTFEA was effective in reducing cell proliferation in both cell lines, in a manner that was dependent on both time and concentration. Additionally, we observed that CDDO-dhTFEA had a significant impact on the regulation of cell proliferation, which was evident in the increase in DNA synthesis that was observed in both cell types. CDDO-dhTFEA induced G2/M cell cycle arrest and mitotic delay, which may be associated with the inhibition of proliferation. Treatment with CDDO-dhTFEA led to cell cycle G2/M arrest and inhibited proliferation of U87MG and GBM8401 cells by regulating G2/M cell cycle proteins and gene expression in GBM cells in vitro.

GSKIP modulates cell aggregation through EMT/MET signaling rather than differentiation in SH-SY5Y human neuroblastoma cells.

GSK3ß interacting protein (GSKIP) is a small A-kinase anchor protein previously reported to mediate the N-cadherin/ß-catenin pool for differentiation in SH-SY5Y cells through overexpression of GSKIP to present the neuron outgrowth phenotype. To further investigate how GSKIP functions in neurons, CRISPR/Cas9 technology was utilized to knock out GSKIP (GSKIP-KO) in SH-SY5Y. Several GSKIP-KO clones resulted in an aggregation phenotype and reduced cell growth without retinoic acid (RA) treatment. However, neuron outgrowth was still observed in GSKIP-KO clones treated with RA. The GSKIP-KO clones exhibited an aggregation phenotype through suppression of GSK3ß/ß-catenin pathways and cell cycle progression rather than cell differentiation. Gene set enrichment analysis indicated that GSKIP-KO was related to epithelial mesenchymal transition/mesenchymal epithelial transition (EMT/MET) and Wnt/ß-catenin/cadherin signaling pathways, suppressing cell migration and tumorigenesis through the inhibition of Wnt/ß-catenin mediated EMT/MET. Conversely, reintroduction of GSKIP into GSKIP-KO clones restored cell migration and tumorigenesis. Notably, phosphor-ß-catenin (S675) and ß-catenin (S552) but not phosphor-ß-catenin (S33/S37/T41) translocated into the nucleus for further gene activation. Collectively, these results suggested that GSKIP may function as an oncogene to form an aggregation phenotype for cell survival in harsh environments through EMT/MET rather than differentiation in the GSKIP-KO of SH-SY5Y cells. GSKIP Implication in Signaling Pathways with Potential Impact on SHSY-5Y Cell Aggregation.

Genetic Underpinnings and Audiological Characteristics in Children With Unilateral Sensorineural Hearing Loss.

OBJECTIVE: Unilateral sensorineural hearing loss (USNHL) is a condition commonly encountered in otolaryngology clinics. However, its molecular pathogenesis remains unclear. This study aimed to investigate the genetic underpinnings of childhood USNHL and analyze the associated audiological features. STUDY DESIGN: Retrospective analysis of a prospectively recruited cohort. SETTING: Tertiary referral center. METHODS: We enrolled 38 children with USNHL between January 1, 2018, and December 31, 2021, and performed physical, audiological, imaging, and congenital cytomegalovirus (cCMV) examinations as well as genetic testing using next-generation sequencing (NGS) targeting 30 deafness genes. The audiological results were compared across different etiologies. RESULTS: Causative genetic variants were identified in 8 (21.1%) patients, including 5 with GJB2 variants, 2 with PAX3 variants, and 1 with the EDNRB variant. GJB2 variants were found to be associated with mild-to-moderate USNHL in various audiogram configurations, whereas PAX3 and EDNRB variants were associated with profound USNHL in flat audiogram configurations. In addition, whole-genome sequencing and extended NGS targeting 213 deafness genes were performed in 2 multiplex families compatible with autosomal recessive inheritance; yet no definite causative variants were identified. Cochlear nerve deficiency and cCMV infection were observed in 9 and 2, respectively, patients without definite genetic diagnoses. CONCLUSION: Genetic underpinnings can contribute to approximately 20% of childhood USNHL, and different genotypes are associated with various audiological features. These findings highlight the utility of genetic examinations in guiding the diagnosis, counseling, and treatment of USNHL in children.

Preclinical safety evaluation of calcineurin inhibitors delivered through an intraductal route to prevent post-ERCP pancreatitis demonstrates endocrine and systemic safety.

OBJECTIVE: There is an urgent need for safe and targeted interventions to mitigate post-ERCP pancreatitis (PEP). Calcineurin inhibitors (CnIs) offer therapeutic promise as calcineurin signaling within acinar cells is a key initiating event in PEP. In previous proof-of-concept studies using experimental models, we showed that concurrent intra-pancreatic ductal administration of the CnIs, tacrolimus (Tac) or cyclosporine A (CsA) with the ERCP radiocontrast agent (RC) prevented PEP. To translate this finding clinically, we investigated potential toxic effects of intraductal delivery of a single-dose RC-CnI formulation on endocrine pancreas function and systemic toxicities in a preclinical PEP model. METHODS: C57BL/6J mice underwent ductal cannulation and received a single, intra-pancreatic ductal infusion of RC or RC with Tac or CsA (treatment groups) or underwent ductal cannulation without infusion ('sham' group). To assess endocrine function, intraperitoneal glucose tolerance test (IPGTT) was performed at two days before infusion and on day 2 and 14 post-surgery. To evaluate off-target tissue toxicities, renal and hepatic function-related parameters including blood urea nitrogen, plasma creatinine, potassium, aspartate aminotransferase, alanine aminotransferase, and total bilirubin were measured at the same time-points as IPGTT. Histological and biochemical indicators of pancreas injury and inflammation were also evaluated. RESULTS: No abnormalities in glucose metabolism, hepatic or renal function were observed on day 2 or 14 in mice administered with intraductal RC or RC with Tac or CsA. CONCLUSION: Intraductal delivery of RC-CnI formulation was safe and well-tolerated with no significant acute or subacute endocrine or systemic toxicities, underscoring its clinical utility to prevent PEP.

Host Invasion Type Is a Phylogenetically Conserved Characteristic of Cephaleuros.

Cephaleuros species cause algal spot diseases, also known as red rust diseases, on many plants, including fruit crops. Most algal species are defined based on their morphological characteristics. Recent phylogenetic studies of Cephaleuros species showed that morphological determination was not congruent with phylogeny. Our study examined the phylogenetic congruence of the host invasion types (or growth habits), which are the most critical characteristics in the taxonomy of Cephaleuros. To ensure that host invasion types and phylogenetic characteristics could be inferred from the same isolate, host invasion types were assessed using microanatomical observation, and rRNA sequences from the same algal spot and/or the derived algal cultures were compared. Host invasion types were found to be conserved classification traits and were congruent with Cephaleuros phylogeny. The results also indicated that more than one Cephaleuros species commonly grew on the same leaf or, in a few cases, the same algal spot, suggesting that identification using different algal spots could result in misidentification. The Cephaleuros isolates were separated into two species complexes by host invasion types: the C. virescens species complex (CVSC) with subcuticular host invasion type and the C. parasiticus species complex (CPSC) with intercellular host invasion type. Molecular phylogenetic analysis indicated that Cephaleuros isolates clustered into 14 clades of CVSC and three clades of CPSC. This study also identified 16 and eight new hosts of CVSC and CPSC in Taiwan, respectively.

Revisiting Genetic Epidemiology with a Refined Targeted Gene Panel for Hereditary Hearing Impairment in the Taiwanese Population.

Hearing impairment is one of the most common sensory disorders in children, and targeted next-generation sequencing (NGS)-based genetic examinations can assist in its prognostication and management. In 2020, we developed a simplified 30-gene NGS panel from the original 214-gene NGS version based on Taiwanese genetic epidemiology data to increase the accessibility of NGS-based examinations. In this study, we evaluated the diagnostic performance of the 30-gene NGS panel and compared it with that of the original 214-gene NGS panel in patient subgroups with different clinical features. Data on the clinical features, genetic etiologies, audiological profiles, and outcomes were collected from 350 patients who underwent NGS-based genetic examinations for idiopathic bilateral sensorineural hearing impairment between 2020 and 2022. The overall diagnostic yield was 52%, with slight differences in genetic etiology between patients with different degrees of hearing impairment and ages of onset. No significant difference was found in the diagnostic yields between the two panels, regardless of clinical features, except for a lower detection rate of the 30-gene panel in the late-onset group. For patients with negative genetic results, where the causative variant is undetectable on current NGS-based methods, part of the negative results may be due to genes not covered by the panel or yet to be identified. In such cases, the hearing prognosis varies and may decline over time, necessitating appropriate follow-up and consultation. In conclusion, genetic etiologies can serve as references for refining targeted NGS panels with satisfactory diagnostic performance.