Essential requirement for nicastrin in marginal zone and B-1 B cell development.

γ-secretase is an intramembrane protease complex that catalyzes the proteolytic cleavage of amyloid precursor protein and Notch. Impaired γ-secretase function is associated with the development of Alzheimer's disease and familial acne inversa in humans. In a forward genetic screen of mice with N-ethyl-N-nitrosourea-induced mutations for defects in adaptive immunity, we identified animals within a single pedigree exhibiting both hypopigmentation of the fur and diminished T cell-independent (TI) antibody responses. The causative mutation was in Ncstn, an essential gene encoding the protein nicastrin (NCSTN), a member of the γ-secretase complex that functions to recruit substrates for proteolysis. The missense mutation severely limits the glycosylation of NCSTN to its mature form and impairs the integrity of the γ-secretase complex as well as its catalytic activity toward its substrate Notch, a critical regulator of B cell and T cell development. Strikingly, however, this missense mutation affects B cell development but not thymocyte or T cell development. The Ncstn allele uncovered in these studies reveals an essential requirement for NCSTN during the type 2 transitional-marginal zone precursor stage and peritoneal B-1 B cell development, the TI antibody response, fur pigmentation, and intestinal homeostasis in mice.

Quantitative Proteomics Reveals ß2 Integrin-mediated Cytoskeletal Rearrangement in Vascular Endothelial Growth Factor (VEGF)-induced Retinal Vascular Hyperpermeability.

Retinal vascular hyperpermeability causes macular edema, leading to visual deterioration in retinal diseases such as diabetic retinopathy and retinal vascular occlusion. Dysregulation of junction integrity between endothelial cells by vascular endothelial growth factor (VEGF) was shown to cause retinal vascular hyperpermeability. Accordingly, anti-VEGF agents have been used to treat retinal vascular hyperpermeability. However, they can confer potential toxicity through their deleterious effects on maintenance and survival of neuronal and endothelial cells in the retina. Thus, it is important to identify novel therapeutic targets for retinal vascular hyperpermeability other than VEGF. Here, we prepared murine retinas showing VEGF-induced vascular leakage from superficial retinal vascular plexus and prevention of VEGF-induced leakage by anti-VEGF antibody treatment. We then performed comprehensive proteome profiling of these samples and identified retinal proteins for which abundances were differentially expressed by VEGF, but such alterations were inhibited by anti-VEGF antibody. Functional enrichment and network analyses of these proteins revealed the ß2 integrin pathway, which can prevent dysregulation of junction integrity between endothelial cells through cytoskeletal rearrangement, as a potential therapeutic target for retinal vascular hyperpermeability. Finally, we experimentally demonstrated that inhibition of the ß2 integrin pathway salvaged VEGF-induced retinal vascular hyperpermeability, supporting its validity as an alternative therapeutic target to anti-VEGF agents.

Dual-specificity phosphatase 26 (DUSP26) stimulates Aß42 generation by promoting amyloid precursor protein axonal transport during hypoxia.

Amyloid beta peptide (Aß) is a pathological hallmark of Alzheimer's disease (AD) and is generated through the sequential cleavage of amyloid precursor protein (APP) by ß- and γ-secretases. Hypoxia is a known risk factor for AD and stimulates Aß generation by γ-secretase; however, the underlying mechanisms remain unclear. In this study, we showed that dual-specificity phosphatase 26 (DUSP26) regulates Aß generation through changes in subcellular localization of the γ-secretase complex and its substrate C99 under hypoxic conditions. DUSP26 was identified as a novel γ-secretase regulator from a genome-wide functional screen using a cDNA expression library. The phosphatase activity of DUSP26 was required for the increase in Aß42 generation through γ-secretase, but this regulation did not affect the amount of the γ-secretase complex. Interestingly, DUSP26 induced the accumulation of C99 in the axons by stimulating anterograde transport of C99-positive vesicles. Additionally, DUSP26 induced c-Jun N-terminal kinase (JNK) activation for APP processing and axonal transport of C99. Under hypoxic conditions, DUSP26 expression levels were elevated together with JNK activation, and treatment with JNK inhibitor SP600125, or the DUSP26 inhibitor NSC-87877, reduced hypoxia-induced Aß generation by diminishing vesicle trafficking of C99 to the axons. Finally, we observed enhanced DUSP26 expression and JNK activation in the hippocampus of AD patients. Our results suggest that DUSP26 mediates hypoxia-induced Aß generation through JNK activation, revealing a new regulator of γ-secretase-mediated APP processing under hypoxic conditions. We propose the role of phosphatase dual-specificity phosphatase 26 (DUSP26) in the selective regulation of Aß42 production in neuronal cells under hypoxic stress. Induction of DUSP26 causes JNK-dependent shift in the subcellular localization of γ-secretase and C99 from the cell body to axons for Aß42 generation. These findings provide a new strategy for developing new therapeutic targets to arrest AD progression.

Psychosocial factors for influencing healthy aging in adults in Korea.

BACKGROUND: Healthy aging includes physical, psychological, social, and spiritual well-being in later years. The purpose of this study is to identify the psychosocial factors influencing healthy aging and examining their socio-demographic characteristics. Perceived health status, depression, self-esteem, self-achievement, ego-integrity, participation in leisure activities, and loneliness were identified as influential factors in healthy aging. METHODS: 171 Korean adults aged between 45 and 77 years-old participated in the study. Self-reporting questionnaires were used, followed by descriptive statistics and multiple regressions as inferential statistical analyses. RESULTS: There were significant differences between participants' general characteristics: age, education, religion, housing, hobby, and economic status. The factors related to healthy aging had positive correlation with perceived health status, self-esteem, self-achievements, and leisure activities, and negative correlation with depression and loneliness. The factors influencing healthy aging were depression, leisure activities, perceived health status, ego integrity, and self-achievements. These factors were able to explain 51.9%. CONCLUSIONS: According to the results, depression is the factor with the greatest influence on healthy aging. Perceived health status, ego integrity, self-achievement, self-esteem, participation of leisure activities were also influential on healthy aging as beneficial factors.

Effect of gold subsurface layer on the surface activity and segregation in Pt/Au/Pt3M (where M = 3d transition metals) alloy catalyst from first-principles.

The effect of a subsurface hetero layer (thin gold) on the activity and stability of Pt skin surface in Pt3M system (M = 3d transition metals) is investigated using the spin-polarized density functional theory calculation. First, we find that the heterometallic interaction between the Pt skin surface and the gold subsurface in Pt/Au/Pt3M system can significantly modify the electronic structure of the Pt skin surface. In particular, the local density of states projected onto the d states of Pt skin surface near the Fermi level is drastically decreased compared to the Pt/Pt/Pt3M case, leading to the reduction of the oxygen binding strength of the Pt skin surface. This modification is related to the increase of surface charge polarization of outmost Pt skin atoms by the electron transfer from the gold subsurface atoms. Furthermore, a subsurface gold layer is found to cast the energetic barrier to the segregation loss of metal atoms from the bulk (inside) region, which can enhance the durability of Pt3M based catalytic system in oxygen reduction condition at fuel cell devices. This study highlights that a gold subsurface hetero layer can provide an additional mean to tune the surface activity toward oxygen species and in turn the oxygen reduction reaction, where the utilization of geometric strain already reaches its practical limit.

OCIAD2 activates γ-secretase to enhance amyloid ß production by interacting with nicastrin.

The gamma (γ)-secretase holoenzyme is composed of four core proteins and cleaves APP to generate amyloid beta (Aß), a key molecule that causes major neurotoxicity during the early stage of Alzheimer's disease (AD). However, despite its important role in Aß production, little is known about the regulation of γ-secretase. OCIAD2, a novel modulator of γ-secretase that stimulates Aß production, and which was isolated from a genome-wide functional screen using cell-based assays and a cDNA library comprising 6,178 genes. Ectopic expression of OCIAD2 enhanced Aß production, while reduction of OCIAD2 expression suppressed it. OCIAD2 expression facilitated the formation of an active γ-secretase complex and enhanced subcellular localization of the enzyme components to lipid rafts. OCIAD2 interacted with nicastrin to stimulate γ-secretase activity. OCIAD2 also increased the interaction of nicastrin with C99 and stimulated APP processing via γ-secretase activation, but did not affect Notch processing. In addition, a cell-permeable Tat-OCIAD2 peptide that interfered with the interaction of OCIAD2 with nicastrin interrupted the γ-secretase-mediated AICD production. Finally, OCIAD2 expression was significantly elevated in the brain of AD patients and PDAPP mice. This study identifies OCIAD2 as a selective activator of γ-secretase to increase Aß generation.

Synthesis and Characterization of ZIF-7 Membranes by In Situ Method.

Zeolitic imidazolate frameworks (ZIFs) have been the focus of interest in adsorption, catalysis, and membrane applications due to their superior thermal and chemical stability, tunable microporous channels, and tailorable physical/chemical properties. In this study, ZIF-7 membranes were successfully prepared on macroporous a-alumina substrate by in situ solvothermal method, without the necessity of seeding or surface modification step. Addition of sodium formate during the reaction facilitates continuous well-intergrown crystalline ZIF-7 layer. As-synthesized ZIF-7 membrane was characterized by XRD, FE-SEM and gas permeation test. The H2 permeance through 5 µm ZIF-7 membrane was 1.9 x 10(-7) mol/m2 x s x Pa with ideal selectivity of H2/CO2 = 15.2.

Mechanisms of enhanced sulfur tolerance on samarium (Sm)-doped cerium oxide (CeO2) from first principles.

The role of samarium (Sm) 4f states and Sm-perturbed O 2p states in determining the sulfur tolerance of Sm-doped CeO2 was elucidated by using the density functional theory (DFT) + U calculation. We find that the sulfur tolerance of Sm-doped CeO2 is closely related to the modification of O 2p states by the strong interaction between Sm 4f and O 2p states. In particular, the availability of unoccupied O 2p states near the Fermi level is responsible for enhancing the sulfur tolerance of Sm-doped CeO2 compared to the pure CeO2 by increasing the activity of the surface lattice oxygen toward sulfur adsorption, by weakening the interaction between Sm-O, and by increasing the migration tendency of the subsurface oxygen ion toward the surface.

Prediction Model of Delayed Hemothorax in Patients with Traumatic Occult Hemothorax Using a Novel Nomogram.

Background: Delayed hemothorax (dHTX) can occur unexpectedly, even in patients who initially present without signs of hemothorax (HTX), potentially leading to death. We aimed to develop a predictive model for dHTX requiring intervention, specifically targeting those with no or occult HTX. Methods: This retrospective study was conducted at a level 1 trauma center. The primary outcome was the occurrence of dHTX requiring intervention in patients who had no HTX or occult HTX and did not undergo closed thoracostomy post-injury. To minimize overfitting, we employed the least absolute shrinkage and selection operator (LASSO) logistic regression model for feature selection. Thereafter, we developed a multivariable logistic regression (MLR) model and a nomogram. Results: In total, 688 patients were included in the study, with 64 cases of dHTX (9.3%). The LASSO and MLR analyses revealed that the depth of HTX (adjusted odds ratio [aOR], 3.79; 95% confidence interval [CI], 2.10-6.85; p<0.001) and the number of totally displaced rib fractures (RFX) (aOR, 1.90; 95% CI, 1.56-2.32; p<0.001) were significant predictors. Based on these parameters, we developed a nomogram to predict dHTX, with a sensitivity of 78.1%, a specificity of 76.0%, a positive predictive value of 25.0%, and a negative predictive value of 97.1% at the optimal cut-off value. The area under the receiver operating characteristic curve was 0.832. Conclusion: The depth of HTX on initial chest computed tomography and the number of totally displaced RFX emerged as significant risk factors for dHTX. We propose a novel nomogram that is easily applicable in clinical settings.

Validation of chest trauma scoring systems in polytrauma: a retrospective study with 1,038 patients in Korea.

Purpose: Appropriate scoring systems can help classify and treat polytrauma patients. This study aimed to validate chest trauma scoring systems in polytrauma patients. Methods: Data from 1,038 polytrauma patients were analyzed. The primary outcomes were one or more complications: pneumonia, chest complications requiring surgery, and mortality. The Thoracic Trauma Severity Score (TTSS), Chest Trauma Score, Rib Fracture Score, and RibScore were compared using receiver operating characteristic (ROC) analysis in patients with or without head trauma. Results: In total, 1,038 patients were divided into two groups: those with complications (822 patients, 79.2%) and those with no complications (216 patients, 20.8%). Sex and body mass index did not significantly differ between the groups. However, age was higher in the complications group (64.1±17.5 years vs. 54.9±17.6 years, P<0.001). The proportion of head trauma patients was higher (58.3% vs. 24.6%, P<0.001) and the Glasgow Coma Scale score was worse (median [interquartile range], 12 [6.5-15] vs. 15 [14-15]; P<0.001) in the complications group. The number of rib fractures, the degree of rib fracture displacement, and the severity of pulmonary contusions were also higher in the complications group. In the area under the ROC curve analysis, the TTSS showed the highest predictive value for the entire group (0.731), head trauma group (0.715), and no head trauma group (0.730), while RibScore had the poorest performance (0.643, 0.622, and 0.622, respectively). Conclusions: Early injury severity detection and grading are crucial for patients with blunt chest trauma. The chest trauma scoring systems introduced to date, including the TTSS, are not acceptable for clinical use, especially in polytrauma patients with traumatic brain injury. Therefore, further revisions and analyses of chest trauma scoring systems are recommended.

Geriatric Trauma Outcome Score in predicting mortality of Korean older adult patients with trauma: Is applicable in all cases?

Purpose: This study aimed to validate the Geriatric Trauma Outcome Score (GTOS) for predicting mortality associated with trauma in older Korean adults and compare the GTOS with the Trauma and Injury Severity Score (TRISS). Methods: This study included patients aged ≥65 years who visited the Chungbuk National University Hospital Regional Trauma Center between January 2016 and December 2022. We used receiver operating characteristic (ROC) curves and calibration plots to assess the discrimination and calibration of the scoring systems. Results: Among 3053 patients, the median age was 77 years, and the mortality rate was 5.2%. The overall GTOS-predicted mortality and 1-TRISS were 5.4% (IQR [3.7-9.5]) and 4.7% (interquartile range [IQR] [4.7-4.7]), respectively. The areas under the curves (AUCs) of 1-TRISS and GTOS for the total population were 0.763 (95% confidence interval [CI], 0.719-0.806) and 0.794 (95%CI, 0.755-0.833), respectively. In the Glasgow Coma Scale (GCS) ≤12 group, the in-hospital mortality rate was 27.5% (79 deaths). The GTOS-predicted mortality and 1-TRISS in this group were 18.6% (IQR [7.5-34.7]) and 26.9% (IQR [11.9-73.1]), respectively. The AUCs of 1-TRISS and GTOS for the total population were 0.800 (95%CI, 0.776-0.854) and 0.744 (95%CI, 0.685-0.804), respectively. Conclusion: The GTOS and TRISS demonstrated comparable accuracy in predicting mortality, while the GTOS offered the advantage of simpler calculations. However, the GTOS tended to underestimate mortality in patients with GCS ≤12; thus, its application requires care in such cases.

Predicting 30-day mortality in severely injured elderly patients with trauma in Korea using machine learning algorithms: a retrospective study.

PURPOSE: The number of elderly patients with trauma is increasing; therefore, precise models are necessary to estimate the mortality risk of elderly patients with trauma for informed clinical decision-making. This study aimed to develop machine learning based predictive models that predict 30-day mortality in severely injured elderly patients with trauma and to compare the predictive performance of various machine learning models. METHODS: This study targeted patients aged ≥65 years with an Injury Severity Score of ≥15 who visited the regional trauma center at Chungbuk National University Hospital between 2016 and 2022. Four machine learning models-logistic regression, decision tree, random forest, and eXtreme Gradient Boosting (XGBoost)-were developed to predict 30-day mortality. The models' performance was compared using metrics such as area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, specificity, F1 score, as well as Shapley Additive Explanations (SHAP) values and learning curves. RESULTS: The performance evaluation of the machine learning models for predicting mortality in severely injured elderly patients with trauma showed AUC values for logistic regression, decision tree, random forest, and XGBoost of 0.938, 0.863, 0.919, and 0.934, respectively. Among the four models, XGBoost demonstrated superior accuracy, precision, recall, specificity, and F1 score of 0.91, 0.72, 0.86, 0.92, and 0.78, respectively. Analysis of important features of XGBoost using SHAP revealed associations such as a high Glasgow Coma Scale negatively impacting mortality probability, while higher counts of transfused red blood cells were positively correlated with mortality probability. The learning curves indicated increased generalization and robustness as training examples increased. CONCLUSIONS: We showed that machine learning models, especially XGBoost, can be used to predict 30-day mortality in severely injured elderly patients with trauma. Prognostic tools utilizing these models are helpful for physicians to evaluate the risk of mortality in elderly patients with severe trauma.

Clinical characteristics and mortality risk factors among trauma patients by age groups at a single center in Korea over 7 years: a retrospective study.

Purpose: In this study, we aimed to compare the characteristics of patients with trauma by age group in a single center in Korea to identify the clinical characteristics and analyze the risk factors affecting mortality. Methods: Patients aged ≥18 years who visited the Chungbuk National University Hospital Regional Trauma Center between January 2016 and December 2022 were included. The accident mechanism, severity of the injury, and outcomes were compared by classifying the patients into group A (18-64 years), group B (65-79 years), and group C (≥80 years). In addition, logistic regression analysis was performed to identify factors affecting death. Results: The most common injury mechanism was traffic accidents in group A (40.9%) and slipping in group B (37.0%) and group C (56.2%). Although group A had the highest intensive care unit admission rate (38.0%), group C had the highest mortality rate (9.5%). In the regression analysis, 3 to 8 points on the Glasgow Coma Scale had the highest odds ratio for mortality, and red blood cell transfusion within 24 hours, intensive care unit admission, age, and Injury Severity Score were the predictors of death. Conclusions: For patients with trauma, the mechanism, injured body region, and severity of injury differed among the age groups. The high mortality rate of elderly patients suggests the need for different treatment approaches for trauma patients according to age. Identifying factors affecting clinical patterns and mortality according to age groups can help improve the prognosis of trauma patients in the future.

Comparing machine learning and logistic regression for acute kidney injury prediction in trauma patients: A retrospective observational study at a single tertiary medical center.

Acute kidney injury (AKI) is common in patients with trauma and is associated with poor outcomes. Therefore, early prediction of AKI in patients with trauma is important for risk stratification and the provision of optimal intensive care unit treatment. This study aimed to compare 2 models, machine learning (ML) techniques and logistic regression, in predicting AKI in patients with trauma. We retrospectively reviewed the charts of 400 patients who sustained torso injuries between January 2016 and June 2020. Patients were included if they were aged > 15 years, admitted to the intensive care unit, survived for > 48 hours, had thoracic and/or abdominal injuries, had no end-stage renal disease, and had no missing data. AKI was defined in accordance with the Kidney Disease Improving Global Outcomes definition and staging system. The patients were divided into 2 groups: AKI (n = 78) and non-AKI (n = 322). We divided the original dataset into a training (80%) and a test set (20%), and the logistic regression with stepwise selection and ML (decision tree with hyperparameter optimization using grid search and cross-validation) was used to build a model for predicting AKI. The models established using the training dataset were evaluated using a confusion matrix receiver operating characteristic curve with the test dataset. We included 400 patients with torso injury, of whom 78 (19.5%) progressed to AKI. Age, intestinal injury, cumulative fluid balance within 24 hours, and the use of vasopressors were independent risk factors for AKI in the logistic regression model. In the ML model, vasopressors were the most important feature, followed by cumulative fluid balance within 24 hours and packed red blood cell transfusion within 4 hours. The accuracy score showed no differences between the 2 groups; however, the recall and F1 score were significantly higher in the ML model (.94 vs 56 and.75 vs 64, respectively). The ML model performed better than the logistic regression model in predicting AKI in patients with trauma. ML techniques can aid in risk stratification and the provision of optimal care.

Successful endovascular treatment of an obstruction following the surgical repair of a traumatic portal vein injury: a case report.

Traumatic portal vein injury is rare, but the associated mortality rate ranges from 50% to 70%. The management of this injury is difficult and remains controversial. In this case report, we describe the successful endovascular treatment of an obstruction that developed following the surgical repair of a traumatic portal vein injury. A man in his mid-40s who had been injured in a car accident presented to our trauma center with abdominal pain, abdominal distension, and open wounds over both knees. Emergency laparotomy revealed a longitudinal rupture from the upper border of the pancreas to the mid-portion of the portal vein; his hemorrhage was successfully controlled surgically. However, postoperative abdominal computed tomography imaging revealed portal vein obstruction. One week after admission to the intensive care unit, an endovascular stent was successfully inserted into the patient's portal vein via a percutaneous transhepatic approach. The associated injuries, including the distal common bile duct obstruction, were successfully managed by choledochojejunostomy. The patient's postoperative recovery was uneventful. Thus, endovascular stent placement is an effective and safe means of treating an obstruction following the surgical repair of a traumatic portal vein injury.

Aberrant role of pyruvate kinase M2 in the regulation of gamma-secretase and memory deficits in Alzheimer's disease.

Toxic amyloid beta (Aß) species cause synaptic dysfunction and neurotoxicity in Alzheimer's disease (AD). As of yet, however, there are no reported regulators for gamma-secretase, which links a risky environment to amyloid accumulation in AD. Here, we report that pyruvate kinase M2 (PKM2) is a positive regulator of gamma-secretase under hypoxia. From a genome-wide functional screen, we identify PKM2 as a gamma-secretase activator that is highly expressed in the brains of both patients and murine models with AD. PKM2 regulates Aß production and the amount of active gamma-secretase complex by changing the gene expression of aph-1 homolog. Hypoxia induces PKM2 expression, thereby promoting gamma-secretase activity. Moreover, transgenic expression of PKM2 in 3xTg AD model mice enhances hippocampal production of Aß and exacerbates the impairment of spatial and recognition memory. Taken together, these findings indicate that PKM2 is an important gamma-secretase regulator that promotes Aß production and memory impairment under hypoxia.

SERP1 is an assembly regulator of γ-secretase in metabolic stress conditions.

The enzyme γ-secretase generates ß-amyloid (Aß) peptides by cleaving amyloid protein precursor (APP); the aggregation of these peptides is associated with Alzheimer's disease (AD). Despite the development of various γ-secretase regulators, their clinical use is limited by coincident disruption of other γ-secretase-regulated substrates, such as Notch. Using a genome-wide functional screen of γ-secretase activity in cells and a complementary DNA expression library, we found that SERP1 is a previously unknown γ-secretase activator that stimulates Aß generation in cells experiencing endoplasmic reticulum (ER) stress, such as is seen with diabetes. SERP1 interacted with a subcomplex of γ-secretase (APH1A/NCT) through its carboxyl terminus to enhance the assembly and, consequently, the activity of the γ-secretase holoenzyme complex. In response to ER stress, SERP1 preferentially recruited APP rather than Notch into the γ-secretase complex and enhanced the subcellular localization of the complex into lipid rafts, increasing Aß production. Moreover, SERP1 abundance, γ-secretase assembly, and Aß production were increased both in cells exposed to high amounts of glucose and in diabetic AD model mice. Conversely, Aß production was decreased by knocking down SERP1 in cells or in the hippocampi of mice. Compared to postmortem samples from control individuals, those from patients with AD showed increased SERP1 expression in the hippocampus and parietal lobe. Together, our findings suggest that SERP1 is an APP-biased regulator of γ-secretase function in the context of cell stress, providing a possible molecular explanation for the link between diabetes and sporadic AD.

Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer's Disease Progression.

Alzheimer's disease (AD) displays a long asymptomatic stage before dementia. We characterize AD stage-associated molecular networks by profiling 14,513 proteins and 34,173 phosphosites in the human brain with mass spectrometry, highlighting 173 protein changes in 17 pathways. The altered proteins are validated in two independent cohorts, showing partial RNA dependency. Comparisons of brain tissue and cerebrospinal fluid proteomes reveal biomarker candidates. Combining with 5xFAD mouse analysis, we determine 15 Aß-correlated proteins (e.g., MDK, NTN1, SMOC1, SLIT2, and HTRA1). 5xFAD shows a proteomic signature similar to symptomatic AD but exhibits activation of autophagy and interferon response and lacks human-specific deleterious events, such as downregulation of neurotrophic factors and synaptic proteins. Multi-omics integration prioritizes AD-related molecules and pathways, including amyloid cascade, inflammation, complement, WNT signaling, TGF-ß and BMP signaling, lipid metabolism, iron homeostasis, and membrane transport. Some Aß-correlated proteins are colocalized with amyloid plaques. Thus, the multilayer omics approach identifies protein networks during AD progression.

Azide-assisted cross-linked sulfonated poly(ether sulfone)s as stable and highly conductive membranes with low methanol diffusion coefficients.

Novel cross-linked sulfonated poly(ether sulfone)s, prepared by azide-assisted thermal irradiation, show not only low methanol permeability but also exceptionally high proton conductivity with oxidative and hydrolytic stability.

Detection of apneic events from single channel nasal airflow using 2nd derivative method.

Detection of sleep apnea is one of the major tasks in sleep studies. Several methods, analyzing the various features of bio-signals, have been applied for automatic detection of sleep apnea, but it is still required to detect apneic events efficiently and robustly from a single nasal airflow signal under varying situations. This study introduces a new algorithm that analyzes the nasal airflow (NAF) for the detection of obstructive apneic events. It is based on mean magnitude of the second derivatives (MMSD) of NAF, which can detect respiration strength robustly under offset or baseline drift. Normal breathing epochs are extracted automatically by examining the stability of SaO(2) and NAF regularity for each subject. The standard MMSD and period of NAF, which are regarded as the values at the normal respiration level, are determined from the normal breathing epochs. In this study, 24 Polysomnography (PSG) recordings diagnosed as obstructive sleep apnea (OSA) syndrome were analyzed. By analyzing the mean performance of the algorithm in a training set consisting of three PSG recordings, apnea threshold is determined to be 13% of the normal MMSD of NAF. NAF signal was divided into 1-s segments for analysis. Each segment is compared with the apnea threshold and classified into apnea events if the segment is included in a group of apnea segments and the group satisfies the time limitation. The suggested algorithm was applied to a test set consisting of the other 21 PSG recordings. Performance of the algorithm was evaluated by comparing the results with the sleep specialist's manual scoring on the same record. The overall agreement rate between the two was 92.0% (kappa=0.78). Considering its simplicity and lower computational load, the suggested algorithm is found to be robust and useful. It is expected to assist sleep specialists to read PSG more quickly and will be useful for ambulatory monitoring of apneas using airflow signals.