Mitofusin 1 and 2 overexpression reduces AßO-mediated ER stress and apoptosis in N2a APPswe cells.

Alzheimer's disease (AD) is the most common neurodegenerative disorder, and amyloid beta oligomers (AßO), which are pathological markers of AD, are known to be highly toxic. AßO increase mitochondrial dysfunction, which is accompanied by a decrease in mitochondrial fusion. Although mitofusin (Mfn) 1 and Mfn2 are mitochondrial fusion proteins, Mfn2 is known to regulate endoplasmic reticulum (ER) function, as it is located in the ER. Several studies have shown that AßO exacerbates ER stress, however, the exact mechanism requires further elucidation. In this study, we used mouse neuroblastoma cells stably overexpressing the amyloid precursor protein (APP) with the Swedish mutation (N2a APPswe cells) to investigate the role of Mfn in ER stress. Our results revealed that  amyloid beta (Aß) caused cellular toxicity in N2a APPswe cells, upregulated ER stress-related proteins, and promoted ER expansion. The AßO-mediated ER stress was reduced when Mfn1 and Mfn2 were overexpressed. Moreover, Mfn1 and Mfn2 overexpressed resulted in reduced apoptosis of N2a APPswe cells. In conclusion, our results indicate that both Mfn1 and Mfn2 reduce ER stress and apoptosis. Our data provide a foundation for future studies on the roles of Mfn1 and Mfn2 in the molecular mechanisms underlying AßO-mediated ER stress and the pathogenesis of AD.

Dielectric Elastomer Actuators with Enhanced Durability by Introducing a Reservoir Layer.

A Dielectric Elastomer Actuator (DEA) consists of electrodes with a dielectric layer between them. By controlling the design of the electrodes, voltage, and frequency, the operating range and speed of the DEA can be adjusted. These DEAs find applications in biomimetic robots, artificial muscles, and similar fields. When voltage is applied to the DEA, the dielectric layer undergoes compression and expansion due to electrostatic forces, which can lead to electrical breakdown. This phenomenon is closely related to the performance and lifespan of the DEA. To enhance stability and improve dielectric properties, a DEA Reservoir layer is introduced. Here, stability refers to the ability of the DEA to perform its functions even as the applied voltage increases. The Reservoir layer delays electrical breakdown and enhances stability due to its enhanced thickness. The proposed DEA in this paper is composed of a Reservoir layer and electrode layer. The Reservoir layer is placed between the electrode layers and is independently configured, not subjected to applied voltage like the electrode layers. The performance of the DEA was evaluated by varying the number of polymer layers in the Reservoir and electrode designs. Introducing the Reservoir layer improved the dielectric properties of the DEA and delayed electrical breakdown. Increasing the dielectric constant through the DEA Reservoir can enhance output characteristics in response to electrical signals. This approach can be utilized in various applications in wearable devices, artificial muscles, and other fields.

A water-soluble colorimetric chemosensor for sequential probing of Cu2+ and S2- and its practical applications to test strips, reversible test, and water samples.

A water-soluble colorimetric chemosensor NHOP ((E)-1-(2-(2-(2-hydroxy-5-nitrobenzylidene)hydrazineyl)-2-oxoethyl)pyridin-1-ium) chloride) was developed for the sequential probing of Cu2+ and S2-. NHOP underwent a color change from pale yellow to colorless in the presence of Cu2+ in pure water. The binding ratio between NHOP and Cu2+ was confirmed to be 1:1 by the Job plot and ESI-MS (electrospray ionization mass spectrometry). The detection limit of NHOP for Cu2+ was calculated as 0.15 µM, which was far below the EPA (Environmental Protection Agency) standard (20 µM). The NHOP-coated test strip was able to easily monitor Cu2+ in real-time. Meanwhile, the NHOP-Cu2+ complex reverted from colorless to pale yellow in the presence of S2- through the demetallation. The stoichiometric ratio between NHOP-Cu2+ and S2- was determined to be 1:1 by analyzing the Job plot and ESI-MS. The detection limit of NHOP-Cu2+ for S2- was calculated as 0.29 µM, which was very below the WHO (World Health Organization) guideline (14.7 µM). NHOP successfully achieved the quantification for Cu2+ and S2- in water samples. NHOP could work as a sequential probe for Cu2+ and S2- at the biological pH range (7.0-8.4). Moreover, NHOP could successively probe Cu2+ and S2- at least three cycles because of its reversible property. The detection mechanisms of NHOP for Cu2+ and NHOP-Cu2+ for S2- were demonstrated with Job plot, ESI-MS, and DFT (density functional theory) calculations. Therefore, NHOP could work as an efficient sequential probe for Cu2+ and S2- in environmental systems.

Changes in the Prevalence of Metabolic Syndrome before and after the COVID-19 Pandemic According to Household Income Levels.

Background: Since the World Health Organization's pandemic declaration in March 2020, Korea has witnessed shifts in lifestyle behaviors, impacting habits tied to socioeconomic status and contributing to metabolic syndrome (MetS). To investigate this issue, the current study aimed to investigate changes in MetS prevalence, particularly based on income levels before and after the coronavirus disease 2019 (COVID-19) pandemic. Methods: This study used data from the 8th Korea National Health and Nutrition Examination Survey (2019-2020). A total of 6,840 individuals aged 30-65 years were included in this study. Household income was divided into high (≥75th percentile), middle (25-75th percentile), and low (≤25th percentile). A multivariable logistic regression analysis was performed to explore the interaction between this association before and after the COVID-19 pandemic. Results: A statistically significant difference was found in the prevalence of MetS before and after the COVID-19 pandemic (26.7% to 30.2%, P=0.001). These changes differed based on income levels. The increase in the prevalence of MetS was statistically significant in the low- and high-income groups but not in the middle-income group (low: 8.0%p increase [P=0.039], middle: 1.0%p increase [P=0.522], high: 6.4%p increase [P<0.001]). The interaction between household income and the COVID-19 pandemic on MetS was statistically significant (P for interaction= 0.032). Conclusion: This study revealed that P for interaction between household income, MetS, and the period before and after the COVID-19 pandemic was significant. Changes in physical activity and eating habits during the COVID- 19 pandemic may have contributed to these differences.

Fast and easy detection of hypochlorite by a smartphone-based fluorescent turn-on probe: Applications to water samples, zebrafish and plant imaging.

We have developed a fluorescent probe DBT-Cl ((E)-2-(2-(4-(diphenylamino)benzylidene) hydrazinyl)-N,N,N-trimethyl-2-oxoethan-1-aminium chloride) for ClO- with an aggregation-induced emission (AIE) strategy depending on solvent polarity. DBT-Cl possessed a prominent solvatochromic emission property with intramolecular charge transfer (ICT) from the TPA (triphenylamine) to the amide group, which was studied by spectroscopic analysis and DFT calculations. These unique AIE properties of DBT-Cl led to the recognition of ClO- with high fluorescent selectivity. DBT-Cl quickly detected ClO- in less than 1 sec with a fluorescent color change from green to cyan. DBT-Cl had a low detection limit of 9.67 µM to ClO-. Detection mechanism of DBT-Cl toward ClO- was illustrated to be oxidative cleavage of DBT-Cl by 1H NMR titrations, ESI-mass, and DFT calculations. We established the viability for dependable detection of ClO- in actual water samples, as well as zebrafish and plant imaging. In particular, DBT-Cl was capable of easily monitoring ClO- through a smartphone application. Therefore, DBT-Cl assured a promising approach for a fast-responsive and multi-applicable ClO- probe in environmental and living organism systems.

Artificial intelligence for predicting shockable rhythm during cardiopulmonary resuscitation: In-hospital setting.

AIM OF THE STUDY: This study aimed to develop an artificial intelligence (AI) model capable of predicting shockable rhythms from electrocardiograms (ECGs) with compression artifacts using real-world data from emergency department (ED) settings. Additionally, we aimed to explore the black box nature of AI models, providing explainability. METHODS: This study is retrospective, observational study using a prospectively collected database. Adult patients who presented to the ED with cardiac arrest or experienced cardiac arrest in the ED between September 2021 and February 2024 were included. ECGs with a compression artifact of 5 s before every rhythm check were used for analysis. The AI model was designed based on convolutional neural networks. The ECG data were assigned into training, validation, and testing sets on a per-patient basis to ensure that ECGs from the same patient did not appear in multiple sets. Gradient-weighted class activation mapping was employed to demonstrate AI explainability. RESULTS: A total of 1,889 ECGs with compression artifacts from 172 patients were used. The area under the receiver operating characteristic curve (AUROC) for shockable rhythm prediction was 0.8672 (95% confidence interval [CI]: 0.8161-0.9122). The AUROCs for manual and mechanical compression were 0.8771 (95% CI: 0.8054-0.9408) and 0.8466 (95% CI: 0.7630-0.9138), respectively. CONCLUSION: This study was the first to accurately predict shockable rhythms during compression using an AI model trained with actual patient ECGs recorded during resuscitation. Furthermore, we demonstrated the explainability of the AI. This model can minimize interruption of cardiopulmonary resuscitation and potentially lead to improved outcomes.

3D mobile regression vision transformer for collateral imaging in acute ischemic stroke.

PURPOSE: The accurate and timely assessment of the collateral perfusion status is crucial in the diagnosis and treatment of patients with acute ischemic stroke. Previous works have shown that collateral imaging, derived from CT angiography, MR perfusion, and MR angiography, aids in evaluating the collateral status. However, such methods are time-consuming and/or sub-optimal due to the nature of manual processing and heuristics. Recently, deep learning approaches have shown to be promising for generating collateral imaging. These, however, suffer from the computational complexity and cost. METHODS: In this study, we propose a mobile, lightweight deep regression neural network for collateral imaging in acute ischemic stroke, leveraging dynamic susceptibility contrast MR perfusion (DSC-MRP). Built based upon lightweight convolution and Transformer architectures, the proposed model manages the balance between the model complexity and performance. RESULTS: We evaluated the performance of the proposed model in generating the five-phase collateral maps, including arterial, capillary, early venous, late venous, and delayed phases, using DSC-MRP from 952 patients. In comparison with various deep learning models, the proposed method was superior to the competitors with similar complexity and was comparable to the competitors of high complexity. CONCLUSION: The results suggest that the proposed model is able to facilitate rapid and precise assessment of the collateral status of patients with acute ischemic stroke, leading to improved patient care and outcome.

Combination Therapy of Radiation and Hyperthermia, Focusing on the Synergistic Anti-Cancer Effects and Research Trends.

Despite significant therapeutic advances, the toxicity of conventional therapies remains a major obstacle to their application. Radiation therapy (RT) is an important component of cancer treatment. Therapeutic hyperthermia (HT) can be defined as the local heating of a tumor to 40-44 °C. Both RT and HT have the advantage of being able to induce and regulate oxidative stress. Here, we discuss the effects and mechanisms of RT and HT based on experimental research investigations and summarize the results by separating them into three phases. Phase (1): RT + HT is effective and does not provide clear mechanisms; phase (2): RT + HT induces apoptosis via oxygenation, DNA damage, and cell cycle arrest; phase (3): RT + HT improves immunological responses and activates immune cells. Overall, RT + HT is an effective cancer modality complementary to conventional therapy and stimulates the immune response, which has the potential to improve cancer treatments, including immunotherapy, in the future.

Puromycin-induced kidney injury and subsequent regeneration in adult zebrafish.

Puromycin treatment can cause glomerular injury to the kidney, leading to proteinuria. However, the pathogenesis of acute kidney injury and subsequent regeneration after puromycin administration in animal models remain unclear. In this work, we examined the characteristics of kidney injury and subsequent regeneration following puromycin treatment in adult zebrafish. We intraperitoneally injected 100 µg of puromycin into zebrafish; sacrificed them at 1, 3, 5, 7, or 14 days post-injection (dpi); and examined the morphological, functional, and molecular changes in the kidney. Puromycin-treated zebrafish presented more rapid clearance of rhodamine dextran than control animals. Morphological changes were observed immediately after the puromycin injection (1-7 dpi) and had recovered by 14 dpi. The mRNA production of lhx1a, a renal progenitor marker, increased during recovery from kidney injury. Levels of NFκB, TNFα, Nampt, and p-ERK increased significantly during nephron injury and regeneration, and Sirt1, FOXO1, pax2, and wt1b showed an increasing tendency. However, TGF-ß1 and smad5 production did not show any changes after puromycin treatment. This study provides evidence that puromycin-induced injury in adult zebrafish kidneys is a potential tool for evaluating the mechanism of nephron injury and subsequent regeneration.

Clinical evaluation of a deep-learning model for automatic scoring of the Alberta stroke program early CT score on non-contrast CT.

BACKGROUND: Automated measurement of the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) can support clinical decision making. Based on a deep learning algorithm, we developed an automated ASPECTS scoring system (Heuron ASPECTS) and validated its performance in a prespecified clinical trial. METHODS: For model training, we used non-contrast computed tomography images of 487 patients with acute ischemic stroke (AIS). For the clinical trial, 326 patients (87 with AIS, 56 with other acute brain diseases, and 183 with no brain disease) were enrolled. The results of Heuron ASPECTS were compared with the consensus generated by two stroke experts using the Bland-Altman agreement. A mean difference of less than 0.35 and a maximum allowed difference of less than 3.8 were considered the primary outcome target. The sensitivity and specificity of the model for the 10 regions of interest and dichotomized ASPECTS were calculated. RESULTS: The Bland-Altman agreement had a mean difference of 0.03 [95% confidence interval (CI): -0.08 to 0.14], and the upper and lower limits of agreement were 2.80 [95% CI: 2.62 to 2.99] and -2.74 [95% CI: -2.92 to -2.55], respectively. For ASPECTS calculation, sensitivity and specificity to detect the early ischemic change for 10 ASPECTS regions were 62.78% [95% CI: 58.50 to 67.07] and 96.63% [95% CI: 96.18 to 97.09], respectively. Furthermore, in a dichotomized analysis (ASPECTS >4 vs. ≤4), the sensitivity and specificity were 94.01% [95% CI: 91.26 to 96.77] and 61.90% [95% CI: 47.22 to 76.59], respectively. CONCLUSIONS: The current trial results show that Heuron ASPECTS reliably measures the ASPECTS for use in clinical practice.

Myelin-Weighted Imaging Presents Reduced Apparent Myelin Water in Patients with Alzheimer's Disease.

The purpose of this study was to investigate myelin loss in both AD and mild cognitive impairment (MCI) patients with a new myelin water mapping technique within reasonable scan time and evaluate the clinical relevance of the apparent myelin water fraction (MWF) values by assessing the relationship between decreases in myelin water and the degree of memory decline or aging. Twenty-nine individuals were assigned to the cognitively normal (CN) elderly group, 32 participants were assigned to the MCI group, and 31 patients were assigned to the AD group. A 3D visualization of the short transverse relaxation time component (ViSTa)-gradient and spin-echo (GraSE) sequence was developed to map apparent MWF. Then, the MWF values were compared between the three participant groups and was evaluated the relationship with the degree of memory loss. The AD group showed a reduced apparent MWF compared to the CN and MCI groups. The largest AUC (area under the curve) value was in the corpus callosum and used to classify the CN and AD groups using the apparent MWF. The ViSTa-GraSE sequence can be a useful tool to map the MWF in a reasonable scan time. Combining the MWF in the corpus callosum with the detection of atrophy in the hippocampus can be valuable for group classification.

High Bodyweight Variability Increases Depression Risk in Patients With Type 2 Diabetes Mellitus: A Nationwide Cohort Study in Korea.

Objectives: Although obesity is associated with increased risk for depression in patients with type 2 diabetes mellitus (DM), the relationship between body weight variability (BWV) and depression remains poorly studied. This study was to investigate the incidence of depression in patients with type 2 DM according to their BWV. Methods: Intraindividual variation in body weight were measured in the nationwide, population-based retrospective cohort of 540,293 patients with type 2 DM from the Korean national health insurance system between 2009 and 2010. The diagnoses of new-onset depression occurring until the end of 2017 were ascertained. Risk of new-onset depression was examined using multivariate-adjusted Cox proportional hazards regression analysis by BWV quartile. Results: 93,149 (17.2%) patients developed new-onset depression for the follow up. BWV was significantly associated with an increased risk of depression after adjusting for confounding factors. The highest BWV quartile group had a hazard ratio (HR) of 1.17 (95% CI 1.15-1.19) compared to the lowest BWV quartile group as a reference. Obese patients in the highest BWV quartile group showed 12% increased risk of depression (HR 1.12, 95% CI 1.09-1.15) while non-obese patients in the highest BWV quartile group showed 20% increased risk of depression (HR: 1.20, 95% CI: 1.17-1.23) compared to their respective lowest BWV quartile groups. Conclusion: A higher BWV was significantly associated with an increased risk of depression in patients with type 2 DM. Thus, BWV may serve as an indicator for early detection of depression in type 2 DM patients.

Characteristics of Facial Asymmetry in Congenital Superior Oblique Palsy according to Trochlear Nerve Absence.

METHODS: A total of 287 consecutive patients diagnosed with congenital SOP and 82 control subjects were included. Congenital SOP patients were grouped according to the presence (present group) or absence (absent group) of the trochlear nerve using thin-section high-resolution MRI of cranial nerves. We developed a computer-aided detection (CAD) system that could automatically analyze objective indices of facial asymmetry using frontal face photographs. RESULTS: Of the 287 patients with congenital SOP, 60% of patients had ipsilateral trochlear nerve absence and superior oblique muscle (SO) hypoplasia (absent group), while the remaining 40% had a normal SO and trochlear nerve (present group). All but one objective indices related to facial asymmetry were significantly different between congenital SOP patients and controls (all P < 0.05). Among these features, the angle of nose deviation was significantly larger in the absent group compared to the present group (P < 0.001). CONCLUSION: Objective analysis of facial asymmetry using our novel CAD system was useful for identifying distinct features of congenital SOP. Deviation of the nose was more prominent in congenital SOP patients with trochlear nerve absence.

Retraction Note to: Analysis of loxoprofen in tablets, patches, and equine urine as tert-butyldimethylsilyl derivative by gas chromatography-mass spectrometry.

The authors have retracted this article [1] because after publication they became aware that the equine urine samples analysed for loxoprofen in this study were in fact equine plasma samples. Therefore the results and conclusions of this article cannot be relied upon. All authors agree to this retraction.

Pharmaceutical Strategies for Stabilizing Drug Nanocrystals.

BACKGROUND: Nanocrystallization technologies have been widely studied in recent years, as the formulation of drug nanocrystals solves problems of poor drug solubility and bioavailability. However, drug nanocrystals in the size range of 1-1000 nm usually need to be accompanied by stabilizers, such as polymers or surfactants, to enhance their stability. Despite their simplicity, improved dissolution rate, and enhanced bioavailability, the limited stability of nanocrystal formulations has prevented further development. OBJECTIVE: The most effective way to handle this instability is to use stabilizers. This paper reviews various factors to consider for the production of stable drug nanocrystals and provides suggestions to overcome the problems associated with instability, such as aggregation and Ostwald ripening. Through various examples of stabilizers acting via electrostatic and steric stabilization, this review highlights the scope of enhancing the stability of drug nanocrystals. CONCLUSION: Studies on stabilizers used in the production of drug nanocrystals are ongoing; various factors, such as the effect of zeta potential on the stability of drug nanosuspensions, have already been revealed. However, it is necessary to determine the most appropriate stabilizer experimentally based on the various mechanisms and factors have been reviewed since the possible interactions between each drug and stabilizer are diverse.

Analysis of loxoprofen in tablets, patches, and equine urine as tert-butyldimethylsilyl derivative by gas chromatography-mass spectrometry.

Loxoprofen is a non-steroidal anti-inflammatory drug of the 2-arylpropionic acid type, which has used to treat musculoskeletal disorders in the horse racing industry. However, it has also used illicitly to mask clinical signs of inflammation and pain in racehorses. Thus, its accurate analysis has become an important issue in horse doping laboratories. In this study, an analytical method of loxoprofen was developed as tert-butyldimethylsilyl (TBDMS) derivative by gas chromatography-mass spectrometry (GC-MS). Characteristic fragment ions of [M-15], [M-57], and [M-139] permitted the accurate and selective detection of loxoprofen. Under optimal conditions, this method showed good linearity (r ≥ 0.999) in the range of 10-500 ng/mL, repeatability (% relative standard deviation = 5.6-8.5), and accuracy (% relative error = - 0.3-0.9) with a detection limit of 1.0 ng. When applied to the analysis of loxoprofen in tablet and patch products, loxoprofen was positively identified as TBDMS derivative by GC-MS. The present method provided rapid and accurate determination of loxoprofen in patch and tablet products. Levels of loxoprofen were highest in equine urine at 0.5 and 1 h after oral administration with single dose (3 mg/kg) to three horses, and then rapidly reduced to below the lower limit of quantification at 24 h. Therefore, the present method will be useful for the pharmacokinetic study and doping tests for loxoprofen and other similar acidic drugs in horses.