Survival properties and spread rates in non-autonomous spread models.

As time progresses, the transmission pattern of a disease may change. To more precisely determine the spread behaviors of the disease, we develop non-autonomous topological and random spread models. In this article, we validate the survival characteristics of these spread models and elucidate their connection with mixing properties using the associated ξ-matrices or spread mean matrices.

Impact of PM, relative humidity, and temperature on sleep quality: a cross-sectional study in Taipei.

Introduction: TWe investigated impacts of particulate matter with an aerodynamic diameter of less than 2.5 μm (PM), relative humidity (RH), and temperature on sleep stages and arousal.

Materials And Methods: A cross-sectional analysis involving 8,611 participants was conducted at a sleep center in Taipei.

Trans-differentiation of Jdp2-depleted Gaba-receptor-positive cerebellar granule cells to Purkinje cells.

The Jun dimerization protein (Jdp2) gene is active in mouse cerebellar granule cells and its protein product plays a crucial role in the formation of the cerebellum lobes through programmed cell death. However, the role of Jdp2 in cellular differentiation and pluripotency in the cerebellum, and the effect of the antioxidation reaction on cell plasticity, remain unknown. N-acetyl-L-cysteine (NAC) induced the early commitment of the differentiation of granule cell precursors (GCPs) to neurons, especially Purkinje cells, via the γ-aminobutyric acid type A receptor α6 subunit (Gabra6) axis; moreover, Jdp2 depletion enhanced this differentiation program of GCPs.

Predicting Survival Status in COVID-19 Patients: Machine Learning Models Development with Ventilator-Related and Biochemical Parameters from Early Stages: A Pilot Study.

: Coronavirus disease 2019 (COVID-19) can cause intubation and ventilatory support due to respiratory failure, and extubation failure increases mortality risk. This study, therefore, aimed to explore the feasibility of using specific biochemical and ventilator parameters to predict survival status among COVID-19 patients by using machine learning. : This study included COVID-19 patients from Taipei Medical University-affiliated hospitals from May 2021 to May 2022.

Implementing next-generation sequencing for diagnosis and management of hereditary hearing impairment: a comprehensive review.

Introduction: Sensorineural hearing impairment (SNHI), a common childhood disorder with heterogeneous genetic causes, can lead to delayed language development and psychosocial problems. Next-generation sequencing (NGS) offers high-throughput screening and high-sensitivity detection of genetic etiologies of SNHI, enabling clinicians to make informed medical decisions, provide tailored treatments, and improve prognostic outcomes.

Areas Covered: This review covers the diverse etiologies of HHI and the utility of different NGS modalities (targeted sequencing and whole exome/genome sequencing), and includes HHI-related studies on newborn screening, genetic counseling, prognostic prediction, and personalized treatment.

Exfoliated 2D Nanosheet-Based Conjugated Polymer Composites with P-N Heterojunction Interfaces for Highly Efficient Electrocatalytic Hydrogen Evolution.

We have achieved a significant breakthrough in the preparation and development of two-dimensional nanocomposites with P-N heterojunction interfaces as efficient cathode catalysts for electrochemical hydrogen evolution reaction (HER) and iodide oxidation reaction (IOR). P-type acid-doped polyaniline (PANI) and N-type exfoliated molybdenum disulfide (MoS) nanosheets can form structurally stable composites due to formation of P-N heterojunction structures at their interfaces. These P-N heterojunctions facilitate charge transfer from PANI to MoS structures and thus significantly enhance the catalytic efficiency of MoS in the HER and IOR.

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.

Combining a 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 2 levels of OSA severity (ie, moderate-to-severe and severe OSA) in accordance with clinical practice standards.

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

Variants in the gap junction beta-2 () gene are the most common cause of hereditary hearing impairment. However, how 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.

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.

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.

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.

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 ( = 368) and test ( = 159) data sets.

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.

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.

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.

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.

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.

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

GSK3β interacting protein (GSKIP) is a small A-kinase anchor protein previously reported to mediate the N-cadherin/β-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.