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Objective: Pediatric Veno-Arterial Extra Corporeal Membrane Oxygenation (VA ECMO) is a life saving technology associated with high mortality. A successful VA ECMO course requires attention to multiple aspects of patient care, including ECMO and patient parameters. Early, potentially modifiable, risk factors associated with patient mortality should be analyzed and adjusted for when assessing VA ECMO risk profiles., Method: Retrospective single center experience of pediatric patients requiring VA ECMO from January 2021 to October 2023. Laboratory and ECMO flow parameters were extracted from the patients record and analyzed. Risk factors were analyzed using a Cox proportion hazard regression., Main Results: There were 45 patients studied. Overall survival was 51%. Upon uncorrected analysis there were no significant differences between the patients who survived and those who died. Utilizing a Cox proportion hazard regression, platelet count, fibrinogen level and creatine level were significant risk factors within the first twenty-four hours of a patient's ECMO course., Significance: Although we did not find a significant difference among ECMO flow parameters in this study, this work highlights that granular ECMO flow data can be incorporated to risk analysis profiles and potential modeling in pediatric VA ECMO. This study demonstrated, that when controlling for ECMO flow parameters, kidney dysfunction and clotting regulation remain key risk factors for pediatric VA ECMO mortality.

Objective. Cardiac Index (CI) is a key physiologic parameter to ensure end organ perfusion in the pediatric intensive care unit (PICU). Determination of CI requires invasive cardiac measurements and is not routinely done at the PICU bedside. To date, there is no gold standard non-invasive means to determine CI. This study aims to use a novel non-invasive methodology, based on routine continuous physiologic data, called Pulse Arrival Time (PAT) as a surrogate for CI in patients with normal Ejection Fraction (EF). Approach. Electrocardiogram (ECG) and photoplethysmogram (PPG) signals were collected from beside monitors at a sampling frequency of 250 samples per second. Continuous PAT, derived from the ECG and PPG waveforms was averaged per patient. Pearson's correlation coefficient was calculated between PAT and CI, PAT and heart rate (HR), and PAT and EF. Main Results. Twenty patients underwent right heart cardiac catheterization. The mean age of patients was 11.7 ± 5.4 years old, ranging from 11 months old to 19 years old, the median age was 13.4 years old. HR in this cohort was 93.8 ± 17.0 beats per minute. The average EF was 54.4 ± 9.6%. The average CI was 3.51 ± 0.72 l min -1 m -2 , with ranging from 2.6 to 4.77 l min -1 m -2 . The average PAT was 0.31 ± 0.12 s. Pearson correlation analysis showed a positive correlation between PAT and CI (0.57, p < 0.01). Pearson correlation between HR and CI, and correlation between EF and CI was 0.22 ( p = 0.35) and 0.03 ( p = 0.23) respectively. The correlation between PAT, when indexed by HR (i.e. PAT × HR), and CI minimally improved to 0.58 ( p < 0.01). Significance. This pilot study demonstrates that PAT may serve as a valuable surrogate marker for CI at the bedside, as a non-invasive and continuous modality in the PICU. The use of PAT in clinical practice remains to be thoroughly investigated., (Creative Commons Attribution license.)

Background: Remote ischemic lesions on diffusion-weighted imaging (DWI) occur in one third of patients with intracerebral hemorrhage (ICH) and are associated with worse outcomes. The etiology is unclear and not solely due to blood pressure reduction. We hypothesized that impaired cerebrovascular autoregulation and hypoperfusion below individualized lower limits of autoregulation are associated with the presence of DWI lesions., Methods: This was a retrospective, single-center study of all primary ICH with intraparenchymal pressure monitoring within 10 days from onset and subsequent magnetic resonance imaging. Pressure reactivity index was calculated as the correlation coefficient between mean arterial pressure and intracranial pressure. Optimal cerebral perfusion pressure (CPPopt) is the cerebral perfusion pressure (CPP) with the lowest corresponding pressure reactivity index. The difference between CPP and CPPopt, time spent below the lower limit of autoregulation (LLA), and time spent above the upper limit of autoregulation (ULA) were calculated by using mean hourly physiologic data. Univariate associations between physiologic parameters and DWI lesions were analyzed by using binary logistic regression., Results: A total of 505 h of artifact-free data from seven patients without DWI lesions and 479 h from six patients with DWI lesions were analyzed. Patients with DWI lesions had higher intracranial pressure (17.50 vs. 10.92 mm Hg; odds ratio 1.14, confidence interval 1.01-1.29) but no difference in mean arterial pressure or CPP compared with patients without DWI lesions. The presence of DWI lesions was significantly associated with a greater percentage of time spent below the LLA (49.85% vs. 14.70%, odds ratio 5.77, confidence interval 1.88-17.75). No significant association was demonstrated between CPPopt, the difference between CPP and CPPopt, ULA, LLA, or time spent above the ULA between groups., Conclusions: Blood pressure reduction below the LLA is associated with ischemia after acute ICH. Individualized, autoregulation-informed targets for blood pressure reduction may provide a novel paradigm in acute management of ICH and require further study., (© 2023. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Objectives: This study aimed to establish an artificial intelligence (AI) system to classify vertical level differences between vocal folds during vocalization and to evaluate the accuracy of the classification., Methods: We designed models with different depths between the right and left vocal folds using an excised canine larynx. Video files for the data set were obtained using a high-speed camera system and a color complementary metal oxide semiconductor camera with global shutter. The data sets were divided into training, validation, and testing. We used 20,000 images for building the model and 8000 images for testing. To perform deep learning multiclass classification and to estimate the vertical level difference, we introduced DenseNet121-ConvLSTM., Results: The model was trained several times using different numbers of epochs. We achieved the most optimal results at 100 epochs, and the batch size used during training was 16. The proposed DenseNet121-ConvLSTM model achieved classification accuracies of 99.5% and 88.0% for training and testing, respectively. After verification using an external data set, the overall accuracy, precision, recall, and f1-score were 90.8%, 91.6%, 90.9%, and 91.2%, respectively., Conclusions: The newly developed AI system may be an easy and accurate method for classifying superior and inferior vertical level differences between vocal folds. Thus, this AI system can be applied and may help in the assessment of vertical level differences in patients with unilateral vocal fold paralysis., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024 The Voice Foundation. Published by Elsevier Inc. All rights reserved.)

Background and Objective: NXT15906F6 (TamaFlex TM ) is a proprietary herbal composition containing Tamarindus indica seeds and Curcuma longa rhizome extracts. NXT15906F6 supplementation has been shown clinically effective in reducing knee joint pain and improving musculoskeletal functions in healthy and knee osteoarthritis (OA) subjects. The objective of the present study was to assess the possible molecular basis of the anti-OA efficacy of NXT15906F6 in a monosodium iodoacetate (MIA)-induced model of OA in rats., Methods: Healthy male Sprague Dawley rats (age: 8-9 wk body weight, B.W.: 225-308 g ( n  = 12) were randomly assigned to one of the six groups, (a) vehicle control, (b) MIA control, (c) Celecoxib (10 mg/kg B.W.), (d) TF-30 (30 mg/kg B.W.), (e) TF-60 (60 mg/kg B.W.), and (f) TF-100 (100 mg/kg B.W.). OA was induced by an intra-articular injection of 3 mg MIA into the right hind knee joint. The animals received either Celecoxib or TF through oral gavage over 28 days. The vehicle control animals received intra-articular sterile normal saline., Results: Post-treatment, NXT15906F6 groups showed significant ( p  < 0.05) dose-dependent pain relief as evidenced by improved body weight-bearing capacity on the right hind limb. NXT15906F6 treatment also significantly reduced the serum tumor necrosis factor-α (TNF-α, p  < 0.05) and nitrite ( p  < 0.05) levels in a dose-dependent manner. mRNA expression analyses revealed the up-regulation of collagen type-II (COL2A1) and down-regulation of matrix metalloproteinases (MMP-3, MMP-9 and MMP-13) in the cartilage tissues of NXT15906F6-supplemented rats. Cyclooxygenase-2 and inducible nitric oxide synthase (iNOS) protein expressions were down-regulated. Decreased immunolocalization of NF-κβ (p65) was observed in the joint tissues of NXT15906F6-supplemented rats. Furthermore, microscopic observations revealed that NXT15906F6 preserved MIA-induced rats' joint architecture and integrity., Conclusion: NXT15906F6 reduces MIA-induced joint pain, inflammation, and cartilage degradation in rats.

Delayed cerebral ischemia (DCI) is a complication seen in patients with subarachnoid hemorrhage stroke. It is a major predictor of poor outcomes and is detected late. Machine learning models are shown to be useful for early detection, however training such models suffers from small sample sizes due to rarity of the condition. Here we propose a Federated Learning approach to train a DCI classifier across three institutions to overcome challenges of sharing data across hospitals. We developed a framework for federated feature selection and built a federated ensemble classifier. We compared the performance of FL model to that obtained by training separate models at each site. FL significantly improved performance at only two sites. We found that this was due to feature distribution differences across sites. FL improves performance in sites with similar feature distributions, however, FL can worsen performance in sites with heterogeneous distributions. The results highlight both the benefit of FL and the need to assess dataset distribution similarity before conducting FL.

Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals., (© 2023. The Author(s).)

Background: Despite significant progress in cardiopulmonary resuscitation and post-cardiac arrest care, favorable outcome in out-of hospital sudden cardiac arrest patients remains low. One of the main reasons for mortality in these patients is withdrawal of life-sustaining treatment. There is a need for precise and equitable prognostication tools to support families in avoiding premature or inappropriate WLST. Heart rate (HR) and heart rate variability (HRV) have been noted for their association with outcome, and are positioned to be a useful modality for prognostication., Objectives: The aim of this scoping review is to rigorously explore which electrocardiography features have been shown to predict functional outcome in post-cardiac arrest patients., Methods: The search was performed in Pubmed, EMBASE, and SCOPUS for studies published from January 1, 2011, to September 29, 2022, including papers in English or Korean., Results: Seven studies were included with a total of 1359 patients. Four studies evaluated HR, one study evaluated RR inverval, and two studies evaluated HRV. All studies were retrospective, with 3 multi-center and 4 single-center studies. All seven studies were inclusive of patients who underwent targeted temperature management (TTM) after cardiac arrest, and two studies included patients without TTM. Five studies used cerebral performance category to assess functional outcome, two studies used Glasgow outcome score, and one study used modified Rankin scale. Three studies measured outcome at hospital discharge, one study measured outcome at 14 days after return of spontaneous circulation, two studies measured outcome after 3 months, and one after 1 year. In all studies that evaluated HR, lower HR was associated with favorable functional outcome. Two studies found that higher complexity of HRV was associated with favorable functional outcome., Conclusion: HR and HRV showed clear associations with functional outcome in patients after CA, but cinilcial utility for prognostication is uncertain., Competing Interests: SA declares research funding from the National Institute of Health, National Heart, Lung, and Blood Institute R01 HL153311., (© 2023 The Author(s).)

Using DNA methylation profiles ( n = 15,456) from 348 mammalian species, we constructed phyloepigenetic trees that bear marked similarities to traditional phylogenetic ones. Using unsupervised clustering across all samples, we identified 55 distinct cytosine modules, of which 30 are related to traits such as maximum life span, adult weight, age, sex, and human mortality risk. Maximum life span is associated with methylation levels in HOXL subclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species.

Objective . The objective of this study is to develop and validate a method for automatically identifying segments of intracranial pressure (ICP) waveform data from external ventricular drainage (EVD) recordings during intermittent drainage and closure. Methods . The proposed method uses time-frequency analysis through wavelets to distinguish periods of ICP waveform in EVD data. By comparing the frequency compositions of the ICP signals (when the EVD system is clamped) and the artifacts (when the system is open), the algorithm can detect short, uninterrupted segments of ICP waveform from the longer periods of non-measurement data. The method involves applying a wavelet transform, calculating the absolute power in a specific range, using Otsu thresholding to automatically identify a threshold, and performing a morphological operation to remove small segments. Two investigators manually graded the same randomly selected one-hour segments of the resulting processed data. Performance metrics were calculated as a percentage. Results . The study analyzed data from 229 patients who had EVD placed following subarachnoid hemorrhage between June 2006 and December 2012. Of these, 155 (67.7%) were female and 62 (27%) developed delayed cerebral ischemia. A total of 45 150 h of data were segmented. 2044 one-hour segments were randomly selected and evaluated by two investigators (MM and DN). Of those, the evaluators agreed on the classification of 1556 one-hour segments. The algorithm was able to correctly identify 86% (1338 h) of ICP waveform data. 8.2% (128 h) of the time the algorithm either partially or fully failed to segment the ICP waveform. 5.4% (84 h) of data, artifacts were mistakenly identified as ICP waveforms (false positives). Conclusion . The proposed algorithm automates the identification of valid ICP waveform segments of waveform in EVD data and thus enables the inclusion in real-time data analysis for decision support. It also standardizes and makes research data management more efficient., (© 2023 Institute of Physics and Engineering in Medicine.)

Increased intracranial pressure (ICP) causes disability and mortality in the neurointensive care population. Current methods for monitoring ICP are invasive. We designed a deep learning framework using a domain adversarial neural network to estimate noninvasive ICP, from blood pressure, electrocardiogram, and cerebral blood flow velocity. Our model had a mean of median absolute error of 3.88 ± 3.26 mmHg for the domain adversarial neural network, and 3.94 ± 1.71 mmHg for the domain adversarial transformers. Compared with nonlinear approaches, such as support vector regression, this was 26.7% and 25.7% lower. Our proposed framework provides more accurate noninvasive ICP estimates than currently available. ANN NEUROL 2023;94:196-202., (© 2023 American Neurological Association.)

Background: Cerebral autoregulation (CA) can be impaired in patients with delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH). The Pressure Reactivity Index (PRx, correlation of blood pressure and intracranial pressure) and Oxygen Reactivity Index (ORx, correlation of cerebral perfusion pressure and brain tissue oxygenation, PbtO 2 ) are both believed to estimate CA. We hypothesized that CA could be poorer in hypoperfused territories during DCI and that ORx and PRx may not be equally effective in detecting such local variances., Methods: ORx and PRx were compared daily in 76 patients with aSAH with or without DCI until the time of DCI diagnosis. The ICP/PbtO 2 -probes of DCI patients were retrospectively stratified by being in or outside areas of hypoperfusion via CT perfusion image, resulting in three groups: DCI + /probe + (DCI patients, probe located inside the hypoperfused area), DCI + /probe-  (probe outside the hypoperfused area), DCI-  (no DCI)., Results: PRx and ORx were not correlated (r = - 0.01, p = 0.56). Mean ORx but not PRx was highest when the probe was located in a hypoperfused area (ORx DCI + /probe + 0.28 ± 0.13 vs. DCI + /probe-  0.18 ± 0.15, p < 0.05; PRx DCI + /probe + 0.12 ± 0.17 vs. DCI + /probe-  0.06 ± 0.20, p = 0.35). PRx detected poorer autoregulation during the early phase with relatively higher ICP (days 1-3 after hemorrhage) but did not differentiate the three groups on the following days when ICP was lower on average. ORx was higher in the DCI + /probe + group than in the other two groups from day 3 onward. ORx and PRx did not differ between patients with DCI, whose probe was located elsewhere, and patients without DCI (ORx DCI + /probe-  0.18 ± 0.15 vs. DCI-  0.20 ± 0.14; p = 0.50; PRx DCI + /probe-  0.06 ± 0.20 vs. DCI-  0.08 ± 0.17, p = 0.35)., Conclusions: PRx and ORx are not interchangeable measures of autoregulation, as they likely measure different homeostatic mechanisms. PRx represents the classical cerebrovascular reactivity and might be better suited to detect disturbed autoregulation during phases with moderately elevated ICP. Autoregulation may be poorer in territories affected by DCI. These local perfusion disturbances leading up to DCI may be more readily detected by ORx than PRx. Further research should investigate their robustness to detect DCI and to serve as a basis for autoregulation-targeted treatment after aSAH., (© 2023. The Author(s).)

With advancement of technology, requirements for light-emitting devices are increasing. Various types of packaging technologies have been suggested to improve the performance of light-emitting diode (LED). Among them, phosphor in glass (PiG) is attracting attention due to its manufactural facility and easily tunable characteristics. As PiG draws increasing attention, research on glass materials is also being actively conducted. However, studies about glass in the field of phosphor are mainly conducted on fabrication. Only a few studies about recycling have been reported. Thus, the objective of this study was to recycle waste glass discarded in other fields due to breakage and failure and use it to fabricate phosphor in glass. Cylindrical waste glass was pulverized into powder with an average size of 12 μm, mixed with a phosphor and sintered to be reborn as a phosphor in glass to broaden the recycling route for waste glass., (© 2023. The Author(s).)

Recently, supplying healthcare services with wearable devices has been investigated. To realize this for true wireless stereo (TWS), which has limited resources (e.g. space, power consumption, and area), implementing multiple functions with one sensor simultaneously is required. The Photoplethysmography (PPG) sensor is a representative healthcare sensor that measures repeated data according to the heart rate. However, since the PPG data are biological, they are influenced by motion artifact and subject characteristics. Hence, noise reduction is needed for PPG data. In this paper, we propose the distance estimation algorithm for PPG signals of TWS. For distance estimation, we designed a waveform adjustment (WA) filter that minimizes noise while maintaining the relationship between before and after data, a lightweight deep learning model called MobileNet, and a PPG monitoring testbed. The number of criteria for distance estimation was set to three. In order to verify the proposed algorithm, we compared several metrics with other filters and AI models. The highest accuracy, precision, recall, and f1 score of the proposed algorithm were 92.5%, 92.6%, 92.8%, and 0.927, respectively, when the signal length was 15. Experimental results of other algorithms showed higher metrics than the proposed algorithm in some cases, but the proposed model showed the fastest inference time.

Background: Targeting a cerebral perfusion pressure optimal for cerebral autoregulation (CPPopt) has been gaining more attention to prevent secondary damage after acute neurological injury. Brain tissue oxygenation (PbtO 2 ) can identify insufficient cerebral blood flow and secondary brain injury. Defining the relationship between CPPopt and PbtO 2 after aneurysmal subarachnoid hemorrhage may result in (1) mechanistic insights into whether and how CPPopt-based strategies might be beneficial and (2) establishing support for the use of PbtO 2 as an adjunctive monitor for adequate or optimal local perfusion., Methods: We performed a retrospective analysis of a prospectively collected 2-center dataset of patients with aneurysmal subarachnoid hemorrhage with or without later diagnosis of delayed cerebral ischemia (DCI). CPPopt was calculated as the cerebral perfusion pressure (CPP) value corresponding to the lowest pressure reactivity index (moving correlation coefficient of mean arterial and intracranial pressure). The relationship of (hourly) deltaCPP (CPP-CPPopt) and PbtO 2 was investigated using natural spline regression analysis. Data after DCI diagnosis were excluded. Brain tissue hypoxia was defined as PbtO 2 <20 mmHg., Results: One hundred thirty-one patients were included with a median of 44.0 (interquartile range, 20.8-78.3) hourly CPPopt/PbtO2 datapoints. The regression plot revealed a nonlinear relationship between PbtO 2 and deltaCPP ( P <0.001) with PbtO 2 decrease with deltaCPP <0 mmHg and stable PbtO 2 with deltaCPP ≥0mmHg, although there was substantial individual variation. Brain tissue hypoxia (34.6% of all measurements) was more frequent with deltaCPP <0 mmHg. These dynamics were similar in patients with or without DCI., Conclusions: We found a nonlinear relationship between PbtO 2 and deviation of patients' CPP from CPPopt in aneurysmal subarachnoid hemorrhage patients in the pre-DCI period. CPP values below calculated CPPopt were associated with lower PbtO 2 . Nevertheless, the nature of PbtO 2 measurements is complex, and the variability is high. Combined multimodality monitoring with CPP/CPPopt and PbtO 2 should be recommended to redefine individual pressure targets (CPP/CPPopt) and retain the option to detect local perfusion deficits during DCI (PbtO 2 ), which cannot be fulfilled by both measurements interchangeably.

Background: Prolonged external ventricular drainage (EVD) in patients with subarachnoid hemorrhage (SAH) leads to morbidity, whereas early removal can have untoward effects related to recurrent hydrocephalus. A metric to help determine the optimal time for EVD removal or ventriculoperitoneal shunt (VPS) placement would be beneficial in preventing the prolonged, unnecessary use of EVD. This study aimed to identify whether dynamics of cerebrospinal fluid (CSF) biometrics can temporally predict VPS dependency after SAH., Methods: This was a retrospective analysis of a prospective, single-center, observational study of patients with aneurysmal SAH who required EVD placement for hydrocephalus. Patients were divided into VPS-dependent (VPS+) and non-VPS dependent groups. We measured the bicaudate index (BCI) on all available computed tomography scans and calculated the change over time (ΔBCI). We analyzed the relationship of ΔBCI with CSF output by using Pearson's correlation. A k-nearest neighbor model of the relationship between ΔBCI and CSF output was computed to classify VPS., Results: Fifty-eight patients met inclusion criteria. CSF output was significantly higher in the VPS+ group in the 7 days post EVD placement. There was a negative correlation between delta BCI and CSF output in the VPS+ group (negative delta BCI means ventricles become smaller) and a positive correlation in the VPS- group starting from days four to six after EVD placement (p < 0.05). A weighted k-nearest neighbor model for classification had a sensitivity of 0.75, a specificity of 0.70, and an area under the receiver operating characteristic curve of 0.80., Conclusions: The correlation of ΔBCI and CSF output is a reliable intraindividual biometric for VPS dependency after SAH as early as days four to six after EVD placement. Our machine learning model leverages this relationship between ΔBCI and cumulative CSF output to predict VPS dependency. Early knowledge of VPS dependency could be studied to reduce EVD duration in many centers (intensive care unit length of stay)., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

This study investigates the characteristics of a ceramic phosphor (CP) for the converter of a high-power laser diode-based automobile headlamp synthesized by high-frequency induction heated press (HFP) sintering. The CP prepared by an HFP method exhibits remarkable optical properties that are comparable to spark plasma sintering. The effects of post-treatment process for controlling residual pores, as well as sintering temperature, sintering pressure and heating rate for optimization of the HFP sintering method, were studied. The HFP sintering process can be widely used in ceramics and lighting fields because it is designed relatively low cost compared to other techniques and exhibits excellent productivity., (© 2022. The Author(s).)

The aim of this study was to investigate properties of ceramic phosphors fabricated using nano Lu 3 Al 5 O 12 :Ce 3+ phosphors produced with a sol-gel-combustion method. These nano Lu 3 Al 5 O 12 :Ce 3+ phosphors had a size of about 200 nm, leading to high density when fabricated as a ceramic phosphor. We manufactured ceramic phosphors through vacuum sintering. Alumina powder was added to improve properties. We mounted the manufactured ceramic phosphor in a high-power laser beam projector and drove it to determine its optical performance. Ceramic phosphor manufactured according to our route will have a significant impact on the laser-driven lighting industry.

Background: Dysfunctional cerebral autoregulation often precedes delayed cerebral ischemia (DCI). Currently, there are no data-driven techniques that leverage this information to predict DCI in real time. Our hypothesis is that information using continuous updated analyses of multimodal neuromonitoring and cerebral autoregulation can be deployed to predict DCI., Methods: Time series values of intracranial pressure, brain tissue oxygenation, cerebral perfusion pressure (CPP), optimal CPP (CPPOpt), ΔCPP (CPP - CPPOpt), mean arterial pressure, and pressure reactivity index were combined and summarized as vectors. A validated temporal signal angle measurement was modified into a classification algorithm that incorporates hourly data. The time-varying temporal signal angle measurement (TTSAM) algorithm classifies DCI at varying time points by vectorizing and computing the angle between the test and reference time signals. The patient is classified as DCI+ if the error between the time-varying test vector and DCI+ reference vector is smaller than that between the time-varying test vector and DCI- reference vector. Finally, prediction at time point t is calculated as the majority voting over all the available signals. The leave-one-patient-out cross-validation technique was used to train and report the performance of the algorithms. The TTSAM and classifier performance was determined by balanced accuracy, F1 score, true positive, true negative, false positive, and false negative over time., Results: One hundred thirty-one patients with aneurysmal subarachnoid hemorrhage who underwent multimodal neuromonitoring were identified from two centers (Columbia University: 52 [39.7%], Aachen University: 79 [60.3%]) and included in the analysis. Sixty-four (48.5%) patients had DCI, and DCI was diagnosed 7.2 ± 3.3 days after hemorrhage. The TTSAM algorithm achieved a balanced accuracy of 67.3% and an F1 score of 0.68 at 165 h (6.9 days) from bleed day with a true positive of 0.83, false positive of 0.16, true negative of 0.51, and false negative of 0.49., Conclusions: A TTSAM algorithm using multimodal neuromonitoring and cerebral autoregulation calculations shows promise to classify DCI in real time., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Digital microfluidics (DMF) has garnered considerable interest as a straightforward, rapid, and programmable technique for controlling microdroplets in various biological, chemical, and medicinal research disciplines. This study details the construction of compact and low-cost 3D DMF platforms with programmable contact charge electrophoresis (CCEP) actuations by employing electrode arrays composed of a small commercial pin socket and a 3D-printed housing. We demonstrate basic 3D droplet manipulation on the platform, including horizontal and vertical transport via lifting and climbing techniques, and droplet merging. Furthermore, phenolphthalein reaction and precipitation process are evaluated using the proposed 3D DMF manipulations as a proof of concept for chemical reaction-based analysis and synthesis. The threshold voltage (or electrical field) and maximum vertical transport velocity are quantified as a function of applied voltage and electrode distance to determine the CCEP actuation conditions for 3D droplet manipulations. The ease of manufacturing and flexibility of the proposed 3D DMF platform may provide an effective technique for programmable 3D manipulation of droplets in biochemical and medical applications, such as biochemical analysis and medical diagnostics.

Objectives: Because climatic and air-pollution factors are known to influence the occurrence of respiratory diseases, we used these factors to develop machine learning models for predicting the occurrence of respiratory diseases., Methods: We obtained the daily number of respiratory disease patients in Seoul. We used climatic and air-pollution factors to predict the daily number of patients treated for respiratory diseases per 10,000 inhabitants. We applied the relief-based feature selection algorithm to evaluate the importance of feature selection. We used the gradient boosting and Gaussian process regression (GPR) methods, respectively, to develop two different prediction models. We also employed the holdout cross-validation method, in which 75% of the data was used to train the model, and the remaining 25% was used to test the trained model. We determined the estimated number of respiratory disease patients by applying the developed prediction models to the test set. To evaluate the performance of each model, we calculated the coefficient of determination (R2) and the root mean square error (RMSE) between the original and estimated numbers of respiratory disease patients. We used the Shapley Additive exPlanations (SHAP) approach to interpret the estimated output of each machine learning model., Results: Features with negative weights in the relief-based algorithm were excluded. When applying gradient boosting to unseen test data, R2 and RMSE were 0.68 and 13.8, respectively. For GPR, the R2 and RMSE were 0.67 and 13.9, respectively. SHAP analysis showed that reductions in average temperature, daylight duration, average humidity, sulfur dioxide (SO2), total solar insolation amount, and temperature difference increased the number of respiratory disease patients, whereas increases in atmospheric pressure, carbon monoxide (CO), and particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5) increased the number of respiratory disease patients., Conclusion: We successfully developed models for predicting the occurrence of respiratory diseases using climatic and air-pollution factors. These models could evolve into public warning systems.

Infinium methylation arrays are not available for the vast majority of non-human mammals. Moreover, even if species-specific arrays were available, probe differences between them would confound cross-species comparisons. To address these challenges, we developed the mammalian methylation array, a single custom array that measures up to 36k CpGs per species that are well conserved across many mammalian species. We designed a set of probes that can tolerate specific cross-species mutations. We annotate the array in over 200 species and report CpG island status and chromatin states in select species. Calibration experiments demonstrate the high fidelity in humans, rats, and mice. The mammalian methylation array has several strengths: it applies to all mammalian species even those that have not yet been sequenced, it provides deep coverage of conserved cytosines facilitating the development of epigenetic biomarkers, and it increases the probability that biological insights gained in one species will translate to others., (© 2022. The Author(s).)

Context.—: Recently, an exchangeable copper (CuEXC) assay has been suggested as a robust and feasible diagnostic tool for Wilson disease (WD). Although WD is a disorder that requires lifelong treatment and monitoring, few data are currently available regarding the status of copper levels in children., Objective.—: To evaluate the performance of copper assays and establish a reference interval for total copper and CuEXC in the pediatric population., Design.—: Serum samples from children aged 1-5 (n = 122), 6-12 (n = 125), and 13-18 years (n = 120) were analyzed. Total copper and CuEXC concentrations were directly measured using inductively coupled plasma mass spectrometry, and relative CuEXC levels were calculated. Total copper reference intervals, CuEXC levels, and relative CuEXC levels were determined based on the 2.5th and 97.5th percentiles of the data with 90% confidence intervals., Results.—: There were significant differences in the median concentrations of total copper and relative CuEXC among the age groups. Reference intervals determined for total copper were 82 to 167, 75 to 139, and 64 to 133 μg/dL for children aged 1 to 5, 6 to 12, and 13 to 18 years, respectively. The reference intervals for CuEXC were 4.29 to 9.79, 4.02 to 9.09, and 3.55 to 8.25 μg/dL for children aged 1 to 5, 6 to 12, and 13 to 18 years, respectively. Among 11 patients with suspected WD, relative CuEXC values were elevated in all 3 diagnosed with WD., Conclusions.—: The pediatric reference intervals derived in this study are expected to be useful for the diagnosis, differential diagnosis, treatment, and monitoring of pediatric patients with WD.

Given the global impact and severity of COVID-19, there is a pressing need for a better understanding of the SARS-CoV-2 genome and mutations. Multi-strain sequence alignments of coronaviruses (CoV) provide important information for interpreting the genome and its variation. We apply a comparative genomics method, ConsHMM, to the multi-strain alignments of CoV to annotate every base of the SARS-CoV-2 genome with conservation states based on sequence alignment patterns among CoV. The learned conservation states show distinct enrichment patterns for genes, protein domains, and other regions of interest. Certain states are strongly enriched or depleted of SARS-CoV-2 mutations, which can be used to predict potentially consequential mutations. We expect the conservation states to be a resource for interpreting the SARS-CoV-2 genome and mutations.

Identifying genomic regions with functional genomic properties that are conserved between human and mouse is an important challenge in the context of mouse model studies. To address this, we develop a method to learn a score of evidence of conservation at the functional genomics level by integrating information from a compendium of epigenomic, transcription factor binding, and transcriptomic data from human and mouse. The method, Learning Evidence of Conservation from Integrated Functional genomic annotations (LECIF), trains neural networks to generate this score for the human and mouse genomes. The resulting LECIF score highlights human and mouse regions with shared functional genomic properties and captures correspondence of biologically similar human and mouse annotations. Analysis with independent datasets shows the score also highlights loci associated with similar phenotypes in both species. LECIF will be a resource for mouse model studies by identifying loci whose functional genomic properties are likely conserved.

The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration-particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs., (© 2021 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.)

Representing highly ordered repetitive structures of antigen macromolecular assemblies, virus-like particles (VLPs) serve as a high-priority vaccine platform against emerging viral infections, as alternatives to traditional cell culture-based vaccines. RNAs can function as chaperones (Chaperna) and are extremely effective in promoting protein folding. Beyond their canonical function as translational adaptors, tRNAs may moonlight as chaperones for the kinetic control of macromolecular antigen assembly. Capitalizing on genomic RNA co-assembly in infectious virions, we present the first report of a biomimetic assembly of viral capsids that was assisted by non-viral host RNAs into genome-free, non-infectious empty particles. Here, we demonstrate the assembly of bacterially-produced soluble norovirus VP1 forming VLPs (n = 180) in vitro. A tRNA-interacting domain (tRID) was genetically fused with the VP1 capsid protein, as a tRNA docking tag, in the bacterial host to transduce chaperna function for de novo viral antigen folding. tRID/tRNA removal prompted the in vitro assembly of monomeric antigens into highly ordered repetitive structures that elicited robust protective immune responses after immunization. The chaperna-based assembly of monomeric antigens will impact the development and deployment of VLP vaccines for emerging and re-emerging viral infections., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Purpose: Several studies have been performed using recently developed smartphone-based acoustic analysis techniques. We investigated the effects of septoplasty and turbinoplasty in patients with nasal septal deviation and turbinate hypertrophy accompanied by snoring by recording the sounds of snoring using a smartphone and performing acoustic analysis., Methods: A total of 15 male patients who underwent septoplasty with turbinoplasty for snoring and nasal obstruction were included in this prospective study. Preoperatively and 2 months after surgery, their bed partners or caregivers were instructed to record the snoring sounds. The intensity (dB), formant frequencies (F 1 , F 2 , F 3 , and F 4 ), spectrogram pattern, and visual analog scale (VAS) score were analyzed for each subject., Results: Overall snoring sounds improved after surgery in 12/15 (80%) patients, and there was significant improvement in the intensity of snoring sounds after surgery (from 64.17 ± 12.18 dB to 55.62 ± 9.11 dB, p = 0.018). There was a significant difference in the F 1 formant frequency before and after surgery (p = 0.031), but there were no significant differences in F 2 , F 3 , or F 4 . The change in F 1 indicated that patients changed from mouth breathing to normal breathing. The degree of subjective snoring sounds improved significantly after surgery (VAS: from 5.40 ± 1.55 to 3.80 ± 1.26, p = 0.003)., Conclusion: Our results confirm that snoring is reduced when nasal congestion is improved, and they demonstrate that smartphone-based acoustic analysis of snoring sounds can be useful for diagnosis.

Objective: The purpose of present study was to validate a Korean version of the Voice Catastrophization Index for assessing catastrophization in patients with voice problems in a Korean population., Methods: Case group patients with voice problems (n = 80) and control group patients without voice problems (n = 25) participated in the study. They were asked to complete three questionnaires: Korean Voice Handicap Index, Korean Voice-Related Quality of Life, and Korean Voice Catastrophization Index (K-VCI). Some of case group with voice problems completed the same three questionnaires again to assess test-retest reliability. Clinicians implemented the Consensus Auditory-Perceptual Evaluation of Voice evaluation to rate the overall severity on voice quality., Results: K-VCI scores for case group were significantly higher than those for control group. K-VCI scores were significantly correlated with Korean Voice Handicap Index, Korean Voice-Related Quality of Life, and overall severity. The K-VCI had significant test-retest reliability and its internal consistency was good to excellent (range of Cronbach alpha correlation coefficients: 0.789-0.930). The K-VCI was not affected by patient sex, age, symptom duration, or diagnosis types. K-VCI scores were highest among patients with primary muscle tension dysphonia., Conclusion: We validated the K-VCI questionnaire for use in measuring the degree of catastrophization of voice problems in a Korean population. Future studies with a larger sample size will be necessary to further verify this and determine the clinical usefulness of the K-VCI., (Copyright © 2019 The Voice Foundation. Published by Elsevier Inc. All rights reserved.)

Annotations of evolutionary sequence constraint based on multi-species genome alignments and genome-wide maps of epigenomic marks and transcription factor binding provide important complementary information for understanding the human genome and genetic variation. Here we developed the Constrained Non-Exonic Predictor (CNEP) to quantify the evidence of each base in the genome being in an evolutionarily constrained non-exonic element from an input of over 60,000 epigenomic and transcription factor binding features. We find that the CNEP score outperforms baseline and related existing scores at predicting evolutionarily constrained non-exonic bases from such data. However, a subset of them are still not well predicted by CNEP. We developed a complementary Conservation Signature Score by CNEP (CSS-CNEP) that is predictive of those bases. We further characterize the nature of constrained non-exonic bases with low CNEP scores using additional types of information. CNEP and CSS-CNEP are resources for analyzing constrained non-exonic bases in the genome.

Despite the fact that stability is a critical issue affecting halide perovskite after the materials have been developed, these materials continue to be studied due to their outstanding optoelectronic characteristics such as narrow emission band width, high PLQY. Many methods are suggested and improved, but the limitations for the display and lighting applications are still remaining. Here, we propose the fabrication of stable cesium lead tri-halide (CsPbX₃; X= Cl, Br, I) perovskite films using photocurable polyurethane material, norland optical adhesive 63 (NOA 63), to generate white LEDs by placing films on the InGaN 450 nm blue chip. Comparing with the conventional perovskites, fabricated films well maintained the luminescence properties such as full widths at half maximum (FWHM) of 18 nm and 31 nm for green and red films, respectively. For the stability issue, pristine perovskite without encapsulation is decomposed immediately at high humidity and temperature, but NOA 63 encapsulated perovskite maintained a PL emission property of 60% after four hours in artificial atmosphere. The CIE color triangle reached ~119% of the NTSC standard, exhibiting high color purity. From the results, we confirm that the NOA 63 encapsulated halide perovskites are beneficial when applied in optoelectronic applications due to their improved stability and maintained characteristics.

Knee osteoarthritis (KOA) is characterized by pain and decreased gait function. We aimed to find KOA-related gait features based on patient reported outcome measures (PROMs) and develop regression models using machine learning algorithms to estimate KOA severity. The study included 375 volunteers with variable KOA grades. The severity of KOA was determined using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). WOMAC scores were used to classify disease severity into three groups. A total of 1087 features were extracted from the gait data. An ANOVA and student's t-test were performed and only features that were significant were selected for inclusion in the machine learning algorithm. Three WOMAC subscales (physical function, pain and stiffness) were further divided into three classes. An ANOVA was performed to determine which selected features were significantly related to the subscales. Both linear regression models and a random forest regression was used to estimate patient the WOMAC scores. Forty-three features were selected based on ANOVA and student's t-test results. The following number of features were selected from each joint: 12 from hip, 1 feature from pelvic, 17 features from knee, 9 features from ankle, 1 feature from foot, and 3 features from spatiotemporal parameters. A significance level of < 0.0001 and < 0.00003 was set for the ANOVA and t-test, respectively. The physical function, pain, and stiffness subscales were related to 41, 10, and 16 features, respectively. Linear regression models showed a correlation of 0.723 and the machine learning algorithm showed a correlation of 0.741. The severity of KOA was predicted by gait analysis features, which were incorporated to develop an objective estimation model for KOA severity. The identified features may serve as a tool to guide rehabilitation and progress assessments. In addition, the estimation model presented here suggests an approach for clinical application of gait analysis data for KOA evaluation.

Positional cranial deformities are relatively common conditions, characterized by asymmetry and changes in skull shape. Although three-dimensional (3D) scanning is the gold standard for diagnosing such deformities, it requires expensive laser scanners and skilled maneuvering. We therefore developed an inexpensive, fast, and convenient screening method to classify cranial deformities in infants, based on single two-dimensional vertex cranial images. In total, 174 measurements from 80 subjects were recorded. Our screening software performs image processing and machine learning-based estimation related to the deformity indices of the cranial ratio (CR) and cranial vault asymmetry index (CVAI) to determine the severity levels of brachycephaly and plagiocephaly. For performance evaluations, the estimated CR and CVAI values were compared to the reference data obtained using a 3D cranial scanner. The CR and CVAI correlation coefficients obtained via support vector regression were 0.85 and 0.89, respectively. When the trained model was evaluated using the unseen test data for the three CR and three CVAI classes, an 86.7% classification accuracy of the proposed method was obtained for both brachycephaly and plagiocephaly. The results showed that our method for screening cranial deformities in infants could aid clinical evaluations and parental monitoring of the progression of deformities at home.

Objectives: The acoustic voice quality index (AVQI) is a specific acoustic indicator designed to objectively estimate dysphonia severity and measure the values of acoustic parameters based on the diagnostic category. This study compared the performance of two AVQI versions (2.02 and 3.01, v2 and v3) and PraatCPPS using a voice sample of Korean population., Materials and Methods: Voice samples for sustained vowel and connected speech were elicited from 2257 patients across 14 diagnostic categories. Auditory-perceptual (A-P) assessments of dysphonia severity were compared to acoustic parameters of severity derived from two versions of the AVQI (v2 and v3) as well as the PraatCPPS., Results: The AVQI-estimated severity (v2 and v3) and PraatCPPS severity for concatenated voice samples strongly correlated with each other and were significantly associated with A-P ratings. The AVQI (v2 and v3) and PraatCPPS showed high reliability in differentiating between pathological voice disorders., Conclusion: The AVQI (v2 and v3) and PraatCPPS were strongly correlated with the A-P ratings and provided valid estimates of dysphonia severity. However, the associations of the A-P ratings with the AVQIv2 were significantly stronger than those with the AVQIv3 and PraatCPPS, suggesting that the V2 outperformed the V3 and PraatCPPS., (Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.)

Purpose: Knee osteoarthritis (KOA) is characterized by pain and decreased gait function. This study assessed key features that can be used as mechanical biomarkers for KOA severity and progression. The identified features were validated statistically and were further examined by developing a classification model based on a machine-learning algorithm., Methods: The study included 227 volunteers with various grades of KOA. The severity of KOA was graded using the Kellgren-Lawrence (KL) system. A total of 165 features were extracted from the gait data. The key features were selected using neighborhood component analysis. The selected features were validated using the t-test. Then, the features were examined by building a classification model using a random forest algorithm., Results: Twenty features were identified that could discriminate the grade of KOA, including nine features extracted from the knee joint, seven from the hip, two from the ankle and two from the spatiotemporal gait parameters. The t-test showed that some features differed significantly between health and sever group, while some were significantly different among the severe group, and others were significantly different for all KL grades. The areas under the receiver operating characteristic curves for classification were 0.974, 0.992, 0.845, 0.894, and 0.905 for KL grades 0 through 4, respectively., Conclusion: Key gait features reflecting the grade of KOA were identified. The results of the statistical analysis and machine-learning algorithm show that the features can discriminate the severity of disease according to the KL grade., (Copyright © 2019 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.)

Objective: The purpose of this study was to explore the concurrent validity of the Acoustic Voice Quality Index (AVQI) in a Korean population. We investigated the feasibility of its cutoff values and diagnostic accuracy in discriminating between normal and dysphonic voices., Materials and Methods: A total of 1,524 native Korean subjects with normal voices (n = 113) and with voice disorders (n = 1,411) were asked to speak and sustain the vowel "a" and to read the Korean text "Walk" aloud. A 2-second mid-speech portion of the sustained vowel sound and two sentences (with 26 syllables) were edited and concatenated, and the AVQI was calculated. Additionally, two auditory-perceptual assessments, namely the Grade, Roughness, Breathiness, Asthenia, Strain scale, and the Consensus Auditory-Perceptual Evaluation of Voice were used by five speech language pathologists to rate the severity of dysphonia., Results: Both auditory-perceptual assessments showed high confidence levels among the five speech language pathologists. The AVQI correlated with grade (G) and overall severity (OS). There were statistically significant differences in AVQI, G, and OS between normal and pathological speech groups. In the receiver operating characteristic curve analysis, AVQI, G, and OS cutoff values were <3.33, <0.00, and <22.00, respectively. The receiver operating characteristic curve analysis indicated that AVQI had excellent diagnostic accuracy for discriminating between normal and dysphonic voices (area under the curve: 0.970-0.977)., Conclusions: We demonstrated the concurrent validity of AVQI as a promising tool for assessing overall voice quality and quantifying dysphonia in a Korean-speaking population., (Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.)

Objective: Although laryngeal videostroboscopy is widely utilized in the analysis of vocal fold vibrations, it is often difficult to identify patterns of vocal fold vibrations in patients with aperiodic voice signals due to failure of synchronization during laryngeal videostroboscopy examination. Therefore, the present study aimed to compare the usefulness of simultaneous two-dimensional digital kymography (2D DKG) and traditional DKG for the detection of changes in the pattern of vocal fold vibrations in patients with vocal fold scarring (VFS)., Methods: Seven patients with VFS and one normal subject underwent high-speed videoendoscopy (HSV). DKG and 2D DKG evaluations of vocal fold vibrations were performed simultaneously, following which both qualitative and quantitative analyses were performed., Results: Simultaneous DKG and 2D DKG enabled observation of vibratory patterns as well as amplitude and phase symmetry. DKG revealed and provided temporal information regarding the pattern of vocal fold vibrations at sites of VFS. In contrast, 2D DKG provided real-time information regarding the pattern of vibrations for the whole vocal fold region and regions of increased stiffness, as well as spatial information regarding changes in this pattern., Conclusion: Our findings indicate that 2D DKG enables the assessment of overall vocal fold vibrations, regardless of periodicity, and that simultaneous DKG and 2D DKG can be used to confirm abnormal patterns of vocal fold vibrations in patients with impaired flexibility and elasticity of the vocal folds., (Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.)

Purpose The purpose of this study was to investigate the characteristics of diplophonia using an auditory perception and multimodal simultaneous examination, which included sound waveform analysis, electroglottography (EGG), digital kymography (DKG), and 2-dimensional scanning digital kymography (2D DKG). Additionally, we compared the diagnostic accuracy of each method using a binary classifier in confusion matrix and convenience of discrimination, based on the time required for interpretation. Method One normophonic male, 12 patients with diplophonia, and 12 dysphonia patients without diplophonia were enrolled. A multimodal simultaneous evaluation was used to analyze the vibration pattern of diplophonia. Sensitivity, specificity, accuracy, area under the curve, and interpretation time were used to compare the various diagnostic methods. Discrimination was determined by 3 raters. Results There are 3 types of asymmetric vibratory patterns in diplophonia. The types are based on the oscillators vibrating at different frequencies: asymmetry of the left and right cords (6 subjects with unilateral palsy and 1 subject with vocal polyps), asymmetry of anterior and posterior cords (2 subjects with vocal polyps), and asymmetry of true and false cords (3 subjects with muscle tension dysphonia). All evaluation methods were useful as diagnostic tools, with all areas under the curve > .70. The diagnostic accuracy was highest with DKG (95.83%), followed by 2D DKG (83.33%), EGG (81.94%), auditory-perceptual evaluation (80.56%), and sound waveform (77.78%). The interpretation time was the shortest for auditory-perceptual evaluation (6.07 ± 1.34 s), followed by 2D DKG (10.04 ± 3.00 s), EGG (12.49 ± 2.76 s), and DKG (13.53 ± 2.60 s). Conclusions Auditory-perceptual judgment was the easiest and fastest method for experienced raters, but its diagnostic accuracy was lower than that of DKG or 2D DKG. The diagnostic accuracy of DKG was the highest, but 2D DKG allowed rapid interpretation and showed relatively high diagnostic accuracy, except in cases with space-occupying lesions. Supplemental Material https://doi.org/10.23641/asha.9911786.

The availability of genome-wide epigenomic datasets enables in-depth studies of epigenetic modifications and their relationships with chromatin structures and gene expression. Various alignment tools have been developed to align nucleotide or protein sequences in order to identify structurally similar regions. However, there are currently no alignment methods specifically designed for comparing multi-track epigenomic signals and detecting common patterns that may explain functional or evolutionary similarities. We propose a new local alignment algorithm, EpiAlign, designed to compare chromatin state sequences learned from multi-track epigenomic signals and to identify locally aligned chromatin regions. EpiAlign is a dynamic programming algorithm that novelly incorporates varying lengths and frequencies of chromatin states. We demonstrate the efficacy of EpiAlign through extensive simulations and studies on the real data from the NIH Roadmap Epigenomics project. EpiAlign is able to extract recurrent chromatin state patterns along a single epigenome, and many of these patterns carry cell-type-specific characteristics. EpiAlign can also detect common chromatin state patterns across multiple epigenomes, and it will serve as a useful tool to group and distinguish epigenomic samples based on genome-wide or local chromatin state patterns., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: Cardiorespiratory fitness (CRF), an important index of physical fitness, is the ability to inhale and provide oxygen to the exercising muscle. However, despite its importance, the current gold standard for measuring CRF is impractical, requiring maximal exercise from the participants., Objective: This study aimed to develop a convenient and practical estimation model for CRF using data collected from daily life with a wristwatch-type device., Methods: A total of 191 subjects, aged 20 to 65 years, participated in this study. Maximal oxygen uptake (VO 2 max), a standard measure of CRF, was measured with a maximal exercise test. Heart rate (HR) and physical activity data were collected using a commercial wristwatch-type fitness tracker (Fitbit; Fitbit Charge; Fitbit) for 3 consecutive days. Maximal activity energy expenditure (aEEmax) and slope between HR and physical activity were calculated using a linear regression. A VO 2 max estimation model was built using multiple linear regression with data on age, sex, height, percent body fat, aEEmax, and the slope. The result was validated with 2 different cross-validation methods., Results: aEEmax showed a moderate correlation with VO 2 max (r=0.50). The correlation coefficient for the multiple linear regression model was 0.81, and the SE of estimate (SEE) was 3.518 mL/kg/min. The regression model was cross-validated through the predicted residual error sum of square (PRESS). The PRESS correlation coefficient was 0.79, and the PRESS SEE was 3.667 mL/kg/min. The model was further validated by dividing it into different subgroups and calculating the constant error (CE) where a low CE showed that the model does not significantly overestimate or underestimate VO 2 max., Conclusions: This study proposes a CRF estimation method using data collected by a wristwatch-type fitness tracker without any specific protocol for a wide range of the population., (©Soon Bin Kwon, Joong Woo Ahn, Seung Min Lee, Joonnyong Lee, Dongheon Lee, Jeeyoung Hong, Hee Chan Kim, Hyung-Jin Yoon. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 13.06.2019.)

Intrinsic disorders are a common feature of hub proteins in eukaryotic interactomes controlling the signaling pathways. The intrinsically disordered proteins (IDPs) are prone to misfolding, and maintaining their functional stability remains a major challenge in validating their therapeutic potentials. Considering that IDPs are highly enriched in RNA-binding proteins (RBPs), here we reasoned and confirmed that IDPs could be stabilized by fusion to RBPs. Dickkopf2 (DKK2), Wnt antagonist and a prototype IDP, was fused with lysyl-tRNA synthetase (LysRS), with or without the fragment crystallizable (Fc) domain of an immunoglobulin and expressed predominantly as a soluble form from a bacterial host. The functional competence was confirmed by in vitro Wnt signaling reporter and tube formation in human umbilical vein endothelial cells (HUVECs) and in vivo Matrigel plug assay. The removal of LysRS by site-specific protease cleavage prompted the insoluble aggregation, confirming that the linkage to RBP chaperones the functional competence of IDPs. While addressing to DKK2 as a key modulator for cancer and ischemic vascular diseases, our results suggest the use of RBPs as stabilizers of disordered proteinaceous materials for acquiring and maintaining the structural stability and functional competence, which would impact the druggability of a variety of IDPs from human proteome.

Background: Tumor-associated macrophages can promote breast cancer metastasis by secreting cytokines and growth factors. Interleukin (IL)-32θ, a newly identified IL-32 isoform, was previously shown to down-regulate various proinflammatory factors of macrophages. Here, we report the presence of IL-32θ in breast cancer tissues and evaluate its effects on macrophage-regulated breast cancer metastasis., Methods: RT-qPCR was used to analyze the mRNA expression of IL-32θ, Chemokine (C-C motif) ligand 18 (CCL18) in breast cancer tissues. In vitro cell-based experiments using IL-32θ-expressing MDA-MB-231 cells were conducted to examine the effects of IL-32θ on metastasis and its molecular signaling. In vivo xenograft, immunohistochemistry, and optical imaging models were generated to support in vitro and clinical findings., Results: The clinical data displayed opposite expression patterns of CCL18 and IL-32θ mRNA in macrophage-infiltrated breast tumor tissues compared with those in the other tissues tested. In MDA-MB-231 cells, IL-32θ overexpression attenuated migration, invasion, tumor-promoting factors, and increased epithelial markers levels upon treatment with conditioned media from THP-1-derived macrophages. Additionally, IL-32θ expression in a xenograft model led to a remarkable decrease in tumor size and macrophage-stimulated tumor promotion. This inhibition was mediated through a direct interaction with protein kinase C-δ (PKCδ), subsequently eliminating the downstream factors STAT3 and NF-κB. Blocking CCL18 during co-culture of macrophages and breast cancer cells reduced the levels of breast cancer progression-related factors and PKCδ downstream signaling suggesting CCL18 as the main macrophage-secreted factors triggering the signaling pathway inhibited by IL-32θ., Conclusions: Our findings demonstrate a novel role of IL-32θ as an intracellular modulator to suppress macrophage-promoted breast cancer progression by targeting CCL18-dependent signaling.

The multifunctional influenza virus protein PB1-F2 plays several roles in deregulation of host innate immune responses and is a known immunopathology enhancer of the 1918 influenza pandemic. Here, we show that the 1918 PB1-F2 protein not only interferes with the mitochondria-dependent pathway of type I interferon (IFN) signaling, but also acquired a novel IFN antagonist function by targeting the DEAD-box helicase DDX3, a key downstream mediator in antiviral interferon signaling, toward proteasome-dependent degradation. Interactome analysis revealed that 1918 PB1-F2, but not PR8 PB1-F2, binds to DDX3 and causes its co-degradation. Consistent with intrinsic protein instability as basis for this gain-of-function, internal structural disorder is associated with the unique cytotoxic sequences of the 1918 PB1-F2 protein. Infusing mice with recombinant DDX3 protein completely rescued them from lethal infection with the 1918 PB1-F2-producing virus. Alongside NS1 protein, 1918 PB1-F2 therefore constitutes a potent IFN antagonist causative for the severe pathogenicity of the 1918 influenza strain. Our identification of molecular determinants of pathogenesis should be useful for the future design of new antiviral strategies against influenza pandemics., (© 2019 The Authors.)