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This study investigated whether prehospital advanced airway management (AAM) is associated with improved survival of out-of-hospital cardiac arrest (OHCA) compared with conventional bag-valve-mask (BVM) ventilation.We investigated the neurologically favorable survival of adult patients with OHCA who underwent BVM or AAM using the Korean Cardiac Arrest Research Consortium (KoCARC), a multicenter OHCA registry of Korea. The differences in clinical characteristics were adjusted by matching or weighting the clinical propensity for use of AAM or by least absolute shrinkage and selection operator (LASSO). The primary outcome was 30-day survival with neurologically favorable status defined by cerebral performance category 1 or 2.Of the 9,616 patients enrolled (median age = 71 years; 65% male), there were 6,243 AAM and 3,354 BVM patients. In unadjusted analysis, the 30-day neurologically favorable survival was lower in the AAM group compared with the BVM group (5.5% vs. 10.0%; hazard ratio [HR] = 1.21, 95% confidence interval [CI] = 1.16 to 1.27; all p 0.001). In propensity score matching-adjusted analysis, these differences were not found (9.6% vs. 10.0%; HR = 0.98, 95% CI = 0.93 to 1.03, p 0.05). Inverse probability of treatment weighting- and LASSO-adjusted analyses replicated these results.In this nationwide real-world data analysis of OHCA, the 30-day neurologically favorable survival did not differ between prehospital AAM and BVM after adjustment for clinical characteristics.

Colorimetric paper sensors are used in various fields due to their convenience and intuitive manner. However, these sensors present low accuracy in practical use because it is difficult to distinguish color changes for a minute amount of analyte with the naked eye. Herein, we demonstrate that a machine learning (ML)-based paper sensor platform accurately determines the color changes. We fabricated a colorimetric paper sensor by adsorbing polyaniline nanoparticles (PAni-NPs), whose color changes from blue to green when the ambient pH decreases. Adding glucose oxidase (GOx) to the paper sensor enables colorimetric glucose detection. Target analytes (10 μL) were aliquoted onto the paper sensors, and their images were taken with a smartphone under the same conditions in a darkroom. The red-green-blue (RGB) data from the images were extracted and used to train and test three regression models: support vector regression (SVR), decision tree regression (DTR), and random forest regression (RFR). Of the three regression models, RFR performed the best at estimating pH levels (

Triple-negative breast cancer (TNBC) is characterized by rapid tumor growth and resistance to cancer therapy, and has a poor prognosis. Accumulating data have revealed that cancer metabolism relies on both the Warburg effect and oxidative phosphorylation (OXPHOS), which are strongly related to the high proliferation and chemoresistance of cancer cells. Phototherapy is considered as a non-invasive method to precisely control drug activity with reduced side effects. Herein, our group introduced an Abraxane-like nanoplatform, named LCIR NPs, which significantly eradicates cancer cells

Formaldehyde emitted from household products is classified as a hazardous substance that can adversely affect human health. Recently, various studies related to adsorption materials for reducing formaldehyde have been widely reported. In this study, mesoporous and mesoporous hollow silicas with amine functional groups introduced were utilized as adsorption materials for formaldehyde. Formaldehyde adsorption characteristics of mesoporous and mesoporous hollow silicas having well-developed pores were compared based on their synthesis methods—with or without a calcination process. Mesoporous hollow silica synthesized through a non-calcination process had the best formaldehyde adsorption characteristics, followed by mesoporous hollow silica synthesized through a calcination process and mesoporous silica. This is because a hollow structure has better adsorption properties than mesoporous silica due to large internal pores. The specific surface area of mesoporous hollow silica synthesized without a calcination process was also higher than that synthesized with a calcination process, leading to a better adsorption performance. This research suggests a facile synthetic method of mesoporous hollow silica and confirms its noticeable potential as a support for the adsorption of harmful gases.

Objective: Prior studies have found metacognitive impairments are linked to a transdiagnostic dimension of anxious-depression, manifesting as reduced confidence in performance (‘metacognitive bias’). However, previous work has been cross-sectional and so it is unclear if under-confidence is a trait-like marker of anxious-depression vulnerability, or if it resolves when anxious-depression improves.Methods: Data were collected as part of the ‘Precision in Psychiatry’ study, a large-scale transdiagnostic, four-week observational study of individuals initiating internet-based cognitive behavioural therapy (iCBT) or antidepressant medication. Self-reported clinical questionnaires and perceptual task performance were gathered to assess anxious-depression and metacognitive bias at baseline and four-week follow-up. Primary analyses were conducted for individuals who received iCBT (n=649), with comparisons between smaller samples that received antidepressant medication (n=88) and a control group receiving no intervention (n=82).Results: Prior to receiving treatment, anxious-depression severity was associated with under-confidence in performance in the iCBT arm, replicating previous work. From baseline to follow-up, levels of anxious-depression were significantly reduced, and this was accompanied by a significant increase in metacognitive confidence (B=0.17, SE=0.02, p

Background: Evidence-based treatments for depression exist but not all patients benefit from them. Efforts to develop predictive models that can assist clinicians in allocating treatments are ongoing, but there are major issues with acquiring the volume and breadth of data needed to train these models. We examined the feasibility, tolerability, patient characteristics, and data quality of a novel protocol for internet-based treatment research in psychiatry that may help advance this field. Methods: A fully internet-based protocol was used to gather repeated observational data from patient cohorts receiving internet-based cognitive behavioural therapy (iCBT) (N = 600) or antidepressant medication treatment (N = 110). At baseline, participants provided > 600 data points of self-report data, spanning socio-demographics, lifestyle, physical health, clinical and other psychological variables and completed 4 cognitive tests. They were followed weekly and completed another detailed clinical and cognitive assessment at week 4. In this paper, we describe our study design, the demographic and clinical characteristics of participants, their treatment adherence, study retention and compliance, the quality of the data gathered, and qualitative feedback from patients on study design and implementation. Results: Participant retention was 92% at week 3 and 84% for the final assessment. The relatively short study duration of 4 weeks was sufficient to reveal early treatment effects; there were significant reductions in 11 transdiagnostic psychiatric symptoms assessed, with the largest improvement seen for depression. Most participants (66%) reported being distracted at some point during the study, 11% failed 1 or more attention checks and 3% consumed an intoxicating substance. Data quality was nonetheless high, with near perfect 4-week test retest reliability for self-reported height (ICC = 0.97). Conclusions: An internet-based methodology can be used efficiently to gather large amounts of detailed patient data during iCBT and antidepressant treatment. Recruitment was rapid, retention was relatively high and data quality was good. This paper provides a template methodology for future internet-based treatment studies, showing that such an approach facilitates data collection at a scale required for machine learning and other data-intensive methods that hope to deliver algorithmic tools that can aid clinical decision-making in psychiatry., BMC Psychiatry, 23 (1), ISSN:1471-244X

Tightly connected symptom networks have previously been linked to treatment resistance, but most findings come from small sample studies comparing single responder vs. non-responder cross-sectional networks. We aimed to estimate the association between baseline network connectivity and treatment response in a large sample and benchmark its prognostic value against baseline symptom severity and variance. N=40,518 patients receiving treatment for depression in routine care in England from 2015-2020 were analysed. Cross-sectional networks were constructed using the Patient Health Questionnaire-9 for responders and non-responders (N=20,259 each). To conduct parametric tests investigating the contribution of mean and variance to connectivity differences, networks were constructed for 160 independent subsamples of responders and non-responders (80 each, n=250 per sample). The baseline network of non-responders was more connected than responders (3.15 vs 2.70, S=0.44, P

The aim of this study was to compare the effect of using depth of invasion (DOI) versus tumor thickness (TT) as a prognostic factor for early-stage oral squamous cell carcinoma (OSCC). A total of 57 patients with early-stage OSCC treated surgically from 2009 to 2014 at our institution were reviewed retrospectively. Histopathological measurement of DOI and TT was performed. The validation of DOI and TT as prognostic factors was conducted using a Kaplan–Meier survival analysis. TT had no association with disease-specific survival (DSS) or progression-free survival (PFS) in this cohort; however, increased DOI was significantly associated with decreased DSS but not correlated to decreased PFS. The T category of the 7th edition of AJCC was statistically associated with both DSS and PFS; however, the T category of the 8th edition of the AJCC was only associated with DSS. In this study group, TT could not be used as a prognostic factor, and DOI was not by itself sufficient to predict prognosis for early-stage OSCC. The T category in AJCC 8th Edition cannot be considered the sole prognostic factor for early OSCC, so additional prognostic factors may need to be considered.

A reliable forecasting model is required for photovoltaic (PV) power output because solar energy is highly volatile. Another driver for the need of a reliable forecasting model is concept drift, which means that the statistical properties of the data change over time. In this paper, an online forecasting method to handle concept drift is proposed. First, the problem of forecasting in batch learning is transformed into a forecasting in online learning setting. Then, an online learning algorithm is applied, which is good for handling concept drift. Through experiments using the real‐world data, it is shown that the method noticeably improves performance compared to the case where a trained model is used. Under various concept drift scenarios, the method improves performance by up to 87.3%. It is also shown that the re‐training method (a representative existing method) has several limitations. This method requires several issues to be solved, such as selection of a proper window size, and this is evident through results showing different performance under different settings. In contrast, the method shows a reliable and desirable performance under various concept drift scenarios and thus outperforms the re‐training method. The method improves performance by up to 79%.

Antiresorptives are the most widely prescribed drugs for the treatment of osteoporosis. They are also used in malignant bone metastases, multiple myeloma, and Paget's disease, and provide therapeutic efficacy on those diseases. However, it was reported that the occurrence of osteonecrosis of the jaw (ONJ) could be related to antiresorptive exposures, and there have been many cases regarding this issue. Therefore, a clearer definition and treatment guidelines were needed for this disease. The American Society for Bone and Mineral Research and the Amnerican Association of Oral and Maxillofacial Surgeons reported statements on bisphosphonate-related ONJ (BRONJ), and a revised version was recently presented. In the revised edition, the diagnosis BRONJ was changed to medication-related ONJ (MRONJ), which reflects consideration of the fact that ONJ also occurs for denosumab, a bone resorption inhibitor of the receptor activator of the nuclear factor-κB ligand antibody family, and bevacizumab, an anti-angiogenesis inhibitor. The Korean Society for Bone and Mineral Research and the Korean Association of Oral and Maxillofacial Surgeons had collectively formed a task force for the preparation of an official statement on MRONJ based on a previous position paper in 2015. The task force reviewed current knowledge and coordinated dental and medical opinions to propose the guideline customized for the local Korean situation.