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Abstract Background Epilepsy, a chronic brain disorder characterized by abnormal brain activity that causes seizures and other symptoms, is typically treated using anti-epileptic drugs (AEDs) as the first-line therapy. However, due to the variations in their modes of action, identification of effective AEDs often relies on ad hoc trials, which is particularly challenging for pediatric patients. Thus, there is significant value in computational methods capable of assisting in the selection of AEDs, aiming to minimize unnecessary medication and improve treatment efficacy. Results In this study, we collected 7,507 medical records from 1,000 pediatric epilepsy patients and developed a computational clinical decision-supporting system for AED selection. This system leverages three multi-channel convolutional neural network (CNN) models tailored to three specific AEDs (vigabatrin, prednisolone, and clobazam). Each CNN model predicts whether a respective AED is effective on a given patient or not. The CNN models showed AUROCs of 0.90, 0.80, and 0.92 in 10-fold cross-validation, respectively. Evaluation on a hold-out test dataset further revealed positive predictive values (PPVs) of 0.92, 0.97, and 0.91 for the three respective CNN models, representing that suggested AEDs by our models would be effective in controlling epilepsy with a high accuracy and thereby reducing unnecessary medications for pediatric patients. Conclusion Our CNN models in the system demonstrated high PPVs for the three AEDs, which signifies the potential of our approach to support the clinical decision-making by assisting doctors in recommending effective AEDs within the three AEDs for patients based on their medical history. This would result in a reduction in the number of unnecessary ad hoc attempts to find an effective AED for pediatric epilepsy patients.

Abstract The accumulation of misfolded and aggregated proteins is a hallmark of neurodegenerative proteinopathies. Although multiple genetic loci have been associated with specific neurodegenerative diseases (NDs), molecular mechanisms that may have a broader relevance for most or all proteinopathies remain poorly resolved. In this study, we developed a multi‐layered network expansion (MLnet) model to predict protein modifiers that are common to a group of diseases and, therefore, may have broader pathophysiological relevance for that group. When applied to the four NDs Alzheimer's disease (AD), Huntington's disease, and spinocerebellar ataxia types 1 and 3, we predicted multiple members of the insulin pathway, including PDK1, Akt1, InR, and sgg (GSK‐3β), as common modifiers. We validated these modifiers with the help of four Drosophila ND models. Further evaluation of Akt1 in human cell‐based ND models revealed that activation of Akt1 signaling by the small molecule SC79 increased cell viability in all models. Moreover, treatment of AD model mice with SC79 enhanced their long‐term memory and ameliorated dysregulated anxiety levels, which are commonly affected in AD patients. These findings validate MLnet as a valuable tool to uncover molecular pathways and proteins involved in the pathophysiology of entire disease groups and identify potential therapeutic targets that have relevance across disease boundaries. MLnet can be used for any group of diseases and is available as a web tool at http://ssbio.cau.ac.kr/software/mlnet.

For a long time, the central nervous system was believed to be the only regulator of cognitive functions. However, accumulating evidence suggests that the composition of the microbiome is strongly associated with brain functions and diseases. Indeed, the gut microbiome is involved in neuropsychiatric diseases (e.g., depression, autism spectrum disorder, and anxiety) and neurodegenerative diseases (e.g., Parkinson’s disease and Alzheimer’s disease). In this review, we provide an overview of the link between the gut microbiome and neuropsychiatric or neurodegenerative disorders. We also introduce analytical methods used to assess the connection between the gut microbiome and the brain. The limitations of the methods used at present are also discussed. The accurate translation of the microbiome information to brain disorder could promote better understanding of neuronal diseases and aid in finding alternative and novel therapies.

Abstract Background As methane is 84 times more potent than carbon dioxide in exacerbating the greenhouse effect, there is an increasing interest in the utilization of methanotrophic bacteria that can convert harmful methane into various value-added compounds. A recently isolated methanotroph, Methylomonas sp. DH-1, is a promising biofactory platform because of its relatively fast growth. However, the lack of genetic engineering tools hampers its wide use in the bioindustry. Results Through three different approaches, we constructed a tunable promoter library comprising 33 promoters that can be used for the metabolic engineering of Methylomonas sp. DH-1. The library had an expression level of 0.24–410% when compared with the strength of the lac promoter. For practical application of the promoter library, we fine-tuned the expressions of cadA and cadB genes, required for cadaverine synthesis and export, respectively. The strain with PrpmB-cadA and PDnaA-cadB produced the highest cadaverine titre (18.12 ± 1.06 mg/L) in Methylomonas sp. DH-1, which was up to 2.8-fold higher than that obtained from a non-optimized strain. In addition, cell growth and lysine (a precursor of cadaverine) production assays suggested that gene expression optimization through transcription tuning can afford a balance between the growth and precursor supply. Conclusions The tunable promoter library provides standard and tunable components for gene expression, thereby facilitating the use of methanotrophs, specifically Methylomonas sp. DH-1, as a sustainable cell factory. Graphical Abstract

Abstract Background Abnormal activation of human nuclear hormone receptors disrupts endocrine systems and thereby affects human health. There have been machine learning-based models to predict androgen receptor agonist activity. However, the models were constructed based on limited numerical features such as molecular descriptors and fingerprints. Result In this study, instead of the numerical features, 2-D chemical structure images of compounds were used to build an androgen receptor toxicity prediction model. The images may provide unknown features that were not represented by conventional numerical features. As a result, the new strategy resulted in a construction of highly accurate prediction model: Mathews correlation coefficient (MCC) of 0.688, positive predictive value (PPV) of 0.933, sensitivity of 0.519, specificity of 0.998, and overall accuracy of 0.981 in 10-fold cross-validation. Validation on a test dataset showed MCC of 0.370, sensitivity of 0.211, specificity of 0.991, PPV of 0.882, and overall accuracy of 0.801. Our chemical image-based prediction model outperforms conventional models based on numerical features. Conclusion Our constructed prediction model successfully classified molecular images into androgen receptor agonists or inactive compounds. The result indicates that 2-D molecular mimetic diagram would be used as another feature to construct molecular activity prediction models.

Abstract Background Drug candidates often cause an unwanted blockage of the potassium ion channel of the human ether-a-go-go-related gene (hERG). The blockage leads to long QT syndrome (LQTS), which is a severe life-threatening cardiac side effect. Therefore, a virtual screening method to predict drug-induced hERG-related cardiotoxicity could facilitate drug discovery by filtering out toxic drug candidates. Result In this study, we generated a reliable hERG-related cardiotoxicity dataset composed of 2130 compounds, which were carried out under constant conditions. Based on our dataset, we developed a computational hERG-related cardiotoxicity prediction model. The neural network model achieved an area under the receiver operating characteristic curve (AUC) of 0.764, with an accuracy of 90.1%, a Matthews correlation coefficient (MCC) of 0.368, a sensitivity of 0.321, and a specificity of 0.967, when ten-fold cross-validation was performed. The model was further evaluated using ten drug compounds tested on guinea pigs and showed an accuracy of 80.0%, an MCC of 0.655, a sensitivity of 0.600, and a specificity of 1.000, which were better than the performances of existing hERG-toxicity prediction models. Conclusion The neural network model can predict hERG-related cardiotoxicity of chemical compounds with a high accuracy. Therefore, the model can be applied to virtual high-throughput screening for drug candidates that do not cause cardiotoxicity. The prediction tool is available as a web-tool at http://ssbio.cau.ac.kr/CardPred.

Abstract Background Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms. Result We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition. Conclusion Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

Differentiation of oligodendrocytes (ODs) presents a challenge in regenerative medicine due to their role in various neurological diseases associated with dysmyelination and demyelination. Here, we designed a peptide derived from vitronectin (VN) using in silico docking simulation and examined its use as a synthetic substrate to support the differentiation of ODs derived from human pluripotent stem cells. The designed peptide, named VNP2, promoted OD differentiation induced by the overexpression of SOX10 in OD precursor cells compared with Matrigel and full-length VN. ODs differentiated on VNP2 exhibited greater contact with axon-mimicking nanofibers than those differentiated on Matrigel. Transcriptomic analysis revealed that the genes associated with morphogenesis, cytoskeleton remodeling, and OD differentiation were upregulated in cells grown on VNP2 compared with cells grown on Matrigel. This new synthetic VN-derived peptide can be used to develop a culture environment for efficient OD differentiation.

Background and Objectives Natural killer T-cell lymphoma (NKTCL) and diffuse large B-cell lymphoma (DLBCL) are the two most prevalent subtypes of lymphoma in the sinonasal region. Accurately differentiating between sinonasal DLBCL and NKTCL is crucial for determining the appropriate treatment and prognosis. The present study compared the clinical characteristics of these two conditions. Methods We conducted a retrospective review of 173 patients diagnosed with sinonasal lymphoma at a single institute between 2004 and 2017. This review included only patients with DLBCL and NKTCL who had more than 6 months of follow-up records. We analyzed patient data encompassing clinical characteristics, pathologic findings, radiologic findings, treatment modalities, recurrence, and survival. Results Among the patients analyzed, 117 patients were diagnosed with NKTCL and 45 with DLBCL. Endoscopic evaluation revealed a significantly higher incidence of crusting (p

Background and Objectives This study aimed to elucidate the relationship between nasal septal deviation (NSD) and upper lateral cartilage (ULC) collapse. Methods We conducted a retrospective review of 142 paranasal sinus computed tomography scans from patients who had undergone septoplasty due to confirmed NSD. The ULC angle was measured on both the narrow and wide sides of the nasal cavities, and these measurements were compared to evaluate the extent of ULC collapse in relation to the degree of NSD and patient age. The correlation between the degree of NSD and the degree of ULC collapse was also analyzed. Results The mean ULC angle was found to be 13.4°±2.7° on the narrow side and 14.3°±2.7° on the wide side, with a statistically significant difference between the two (p

Although iatrogenic skull base injuries after endoscopic sinus surgery (ESS) are rare (overall complication rate, 0.5%), they can be fatal or cause significant morbidity. Conventionally, skull base injuries were repaired using an external approach. However, in recent years, most skull base injuries after ESS have been repaired using an endoscopic transnasal approach due to its lower morbidity, lower risk of postoperative complications, and shorter hospital stay. We report two cases of iatrogenic skull base injury accompanied by brain injury following ESS and describe the skull base repair techniques employed for each case. In both cases, the skull base defects were successfully repaired using an endoscopic transnasal approach, although craniotomy was also performed in the first case to remove bone fragments from the right frontal base and lateral ventricle. Both patients recovered without residual neurologic deficits.

Abstract Objective Total laryngectomy (TL) patients are good models in which to evaluate the effects of nasal airflow cessation on the sinonasal tract. Here, we evaluated changes in sinonasal structures and association with sinus opacification in the computed tomography (CT) images 3 years post‐TL. Methods Patients who underwent TL from 2005 to 2017 in a teaching academic center were reviewed retrospectively. Patients with a final follow‐up CT taken less than 3 years after TL, tracheoesophageal puncture, inadequate CT image, or history of sinonasal surgery were excluded. The control group included patients who underwent a partial laryngectomy or hypopharyngectomy without requiring a tracheotomy for more than a month. Altogether, 45 TL patients and 38 controls were selected. The volume of all four paranasal sinuses, inferior turbinate soft tissue volume (ITSTV), maxillary sinus natural ostium (MSNO) mucosal width, and Lund–Mackay scores (LMS) were measured on preoperative and postoperative CT scans. Results The mean duration between surgery and the final CT scan was 6.3 ± 2.4 and 5.5 ± 2.3 years for the TL and control groups, respectively. Neither group showed significant changes in the four paranasal sinuses' volume or MSNO mucosa width. The ITSTV decreased significantly, from 4.6 ± 1.3 to 2.8 ± 1.1 mL (p

Orbital hematic cyst is characterized by cystic accumulation of hematogenous debris surrounded by a wall of fibrous tissue without an epithelial lining. It is a relatively uncommon benign cyst and occurs secondary to blunt trauma in most cases. We experienced a case of 53-year-old male who presented with proptosis of the left eye. A cystic lesion was found at the superolateral orbital rim of the patient. We report a case of orbital hematic cyst that was resected completely through the sub-brow approach.

Sleep surgery is part of a continuum of care for obstructive sleep apnea (OSA) that involves medical, pharmacologic, and behavioral therapy. Upper airway surgery for OSA can significantly improve stability by way of modulating the critical negative closing pressure. This is the same mechanism of action as positive airway pressure or oral appliance therapy. The updated surgical algorithm in this review adds precision in three areas: patient selection, identification of previously unaddressed anatomic phenotypes with associated treatment modality, and improved techniques of previously established procedures. While the original Riley and Powell phase 1 and 2 approach to sleep surgery has focused on individual surgical success rate, this algorithm strives for an overall treatment success with multi-modal and patient-centric treatments.

There are many ways to categorize surgery for obstructive sleep apnea (OSA), one of which is to distinguish between intrapharyngeal and extrapharyngeal procedures. While the general otolaryngologist treating OSA is familiar with intrapharyngeal procedures, such as uvulopalatopharyngoplasty and tongue base reduction, extrapharyngeal sleep operations such as maxillomandibular advancement (MMA) and upper airway stimulation (UAS) have evolved rapidly in the recent decade and deserve a dedicated review. MMA and UAS have both shown predictable high success rates with low morbidity. Each approach has unique strengths and limitations, and for the most complex of OSA patients, the two in combination complement each other. Extrapharyngeal airway operations are critical for achieving favorable outcomes for sleep surgeons.

Background: Burr-hole trephination is a widely used surgical technique for chronic subdural hematoma (CSDH). Although various postoperative complications following burr-hole craniostomy have been discussed, no contralateral acute SDH (ASDH) immediately after the initial surgery without concurrent hemorrhages has been reported so far; we experienced this very rare complication in a previously healthy 84 year old male. Details of this very rare case are presented in this report. Materials and methods: 87 patients with chronic SDH underwent a burr hole trephination, that is, craniostomy between July 2012 and June 2014; there were 47 male and 40 female patients. 24 of 87 patients harbored bilateral SDHs. 67 of 111 lesions were drained with two catheters and the remaining 44 employed a single catheter. Results: Unsatisfactory results following the craniastomy included recurrence, insufficient drain, aggravated acute SDH and contralateral development of incracranial hemorrhage. Contralateral intracranial hemorrhage occurred to three patients. One died and the other two were discharged without any sequelae. One of the three contralateral hemorrhages was a mere ASDH which was complicated to a previously healthy 84 year old male within less than an hour after the initial surgery. The patient was discharged without sequelae. Conclusion: This report represents a contralateral ASDH that occurred less than an hour after a burr-hole trephination for CSDH. Several hypotheses concerning the etiology of this rare complication, albeit inconclusive, are worth contemplation. Excessive drain of CSDH must be refrained from in order not to encounter any unexpected complications.

Burkitt's lymphoma is a highly aggressive small B-cell lymphoma. The treatment of choice is complex chemotherapy. As a rare tumor in the head and neck area, Burkitt's lymphoma usually involves cervical lymph nodes, and only fewer than 25% of cases involves extranodal regions. Involvement of the paranasal sinuses has been reported in only 14 cases in the past century. We describe here two patients with rare, sporadic, American type Burkitt's lymphoma involving the nasal cavity and paranasal sinuses manifesting nasal obstruction. We also review clinical and histological features of Burkitt's lymphoma.