Seeking a quantum advantage with trapped-ion quantum simulations of condensed-phase chemical dynamics.

Simulating the quantum dynamics of molecules in the condensed phase represents a longstanding challenge in chemistry. Trapped-ion quantum systems may serve as a platform for the analog-quantum simulation of chemical dynamics that is beyond the reach of current classical-digital simulation. To identify a 'quantum advantage' for these simulations, performance analysis of both analog-quantum simulation on noisy hardware and classical-digital algorithms is needed. In this Review, we make a comparison between a noisy analog trapped-ion simulator and a few choice classical-digital methods on simulating the dynamics of a model molecular Hamiltonian with linear vibronic coupling. We describe several simple Hamiltonians that are commonly used to model molecular systems, which can be simulated with existing or emerging trapped-ion hardware. These Hamiltonians may serve as stepping stones towards the use of trapped-ion simulators for systems beyond the reach of classical-digital methods. Finally, we identify dynamical regimes in which classical-digital simulations seem to have the weakest performance with respect to analog-quantum simulations. These regimes may provide the lowest hanging fruit to make the most of potential quantum advantages.

Angiotensin Receptor Blockers and the Risk of Suspected Drug-Induced Liver Injury: A Retrospective Cohort Study Using Electronic Health Record-Based Common Data Model in South Korea.

INTRODUCTION: Angiotensin receptor blockers are widely used antihypertensive drugs in South Korea. In 2021, the Korea Ministry of Food and Drug Safety acknowledged the need for national compensation for a drug-induced liver injury (DILI) after azilsartan use. However, little is known regarding the association between angiotensin receptor blockers and DILI. OBJECTIVE: We conducted a retrospective cohort study in incident users of angiotensin receptor blockers from a common data model database (1 January, 2017-31 December, 2021) to compare the risk of DILI among specific angiotensin receptor blockers against valsartan. METHODS: Patients were assigned to treatment groups at cohort entry based on prescribed angiotensin receptor blockers. Drug-induced liver injury was operationally defined using the International DILI Expert Working Group criteria. Cox regression analyses were conducted to derive hazard ratios and the inverse probability of treatment weighting method was applied. All analyses were performed using R. RESULTS: In total, 229,881 angiotensin receptor blocker users from 20 university hospitals were included. Crude DILI incidence ranged from 15.6 to 82.8 per 1000 person-years in treatment groups, most were cholestatic and of mild severity. Overall, the risk of DILI was significantly lower in olmesartan users than in valsartan users (hazard ratio: 0.73 [95% confidence interval 0.55-0.96]). In monotherapy patients, the risk was significantly higher in azilsartan users than in valsartan users (hazard ratio: 6.55 [95% confidence interval 5.28-8.12]). CONCLUSIONS: We found a significantly higher risk of suspected DILI in patients receiving azilsartan monotherapy compared with valsartan monotherapy. Our findings emphasize the utility of real-world evidence in advancing our understanding of adverse drug reactions in clinical practice.

CM-GAN: A Cross-Modal Generative Adversarial Network for Imputing Completely Missing Data in Digital Industry.

Multimodal data fusion analysis is essential to model the uncertainty of environment awareness in digital industry. However, due to communication failure and cyberattack, the sampled time-series data often have the issue of data missing. In some extreme cases, part of units are unobservable for a long time, which results in complete data missing (CDM). To impute missing data, many models have been proposed. However, they cannot address the CDM issue, because no observation data of the unobservable units can be obtained in this case. Thus, to address the CDM issue, a novel cross-modal generative adversarial network (CM-GAN) is proposed in this article. It combines the cross-modal data fusion technique and the deep adversarial generation technique to construct a cross-modal data generator. This generator can generate long-term time-series data from widely existing spatio-temporal modal data in modern industrial system, and then impute missing value by replacing them with generated data. To test the performance of CM-GAN, extensive experiments are conducted on photovoltaic (PV) power output dataset. Compared with other baseline models, the performance of CM-GAN is generally better and reaches the state-of-the-art level. Moreover, sufficient ablation studies are conducted to present the contribution of the cross-modal data fusion technique and show the reasonability of parameter settings of CM-GAN. Apart from this, some prediction experiments are also conducted. The results show that the PV data recovered by CM-GAN can provide more predictability information for improving the prediction accuracy of deep learning model.

MetaLAB-HOI: Template standardization of health outcomes enable massive and accurate detection of adverse drug reactions from electronic health records.

PURPOSE: This study aimed to advance the MetaLAB algorithm and verify its performance with multicenter data to effectively detect major adverse drug reactions (ADRs), including drug-induced liver injury. METHODS: Based on MetaLAB, we created an optimal scenario for detecting ADRs by considering demographic and clinical records. MetaLAB-HOI was developed to identify ADR signals using common model-based multicenter electronic health record (EHR) data from the clinical health outcomes of interest (HOI) template and design for drug-exposed and nonexposed groups. In this study, we calculated the odds ratio of 101 drugs for HOI in Konyang University Hospital, Seoul National University Hospital, Chungbuk National University Hospital, and Seoul National University Bundang Hospital. RESULTS: The overlapping drugs in four medical centers are amlodipine, aspirin, bisoprolol, carvedilol, clopidogrel, clozapine, digoxin, diltiazem, methotrexate, and rosuvastatin. We developed MetaLAB-HOI, an algorithm that can detect ADRs more efficiently using EHR. We compared the detection results of four medical centers, with drug-induced liver injuries as representative ADRs. CONCLUSIONS: MetaLAB-HOI's strength lies in fully utilizing the patient's clinical information, such as prescription, procedure, and laboratory results, to detect ADR signals. Considering changes in the patient's condition over time, we created an algorithm based on a scenario that accounted for each drug exposure and onset period supervised by specialists for HOI. We determined that when a template capable of detecting ADR based on clinical evidence is developed and manualized, it can be applied in medical centers for new drugs with insufficient data.

Glucose Deprivation Induces Cancer Cell Death through Failure of ROS Regulation.

In previous work, we showed that cancer cells do not depend on glycolysis for ATP production, but they do on fatty acid oxidation. However, we found some cancer cells induced cell death after glucose deprivation along with a decrease of ATP production. We investigated the different response of glucose deprivation with two types of cancer cells including glucose insensitive cancer cells (GIC) which do not change ATP levels, and glucose sensitive cancer cells (GSC) which decrease ATP production in 24 h. Glucose deprivation-induced cell death in GSC by more than twofold after 12 h and by up to tenfold after 24 h accompanied by decreased ATP production to compare to the control (cultured in glucose). Glucose deprivation decreased the levels of metabolic intermediates of the pentose phosphate pathway (PPP) and the reduced form of nicotinamide adenine dinucleotide phosphate (NADPH) in both GSC and GIC. However, glucose deprivation increased reactive oxygen species (ROS) only in GSC, suggesting that GIC have a higher tolerance for decreased NADPH than GSC. The twofold higher ratio of reduced/oxidized glutathione (GSH/GSSG) in GIS than in GSC correlates closely with the twofold lower ROS levels under glucose starvation conditions. Treatment with N-acetylcysteine (NAC) as a precursor to the biologic antioxidant glutathione restored ATP production by 70% and reversed cell death caused by glucose deprivation in GSC. The present findings suggest that glucose deprivation-induced cancer cell death is not caused by decreased ATP levels, but rather triggered by a failure of ROS regulation by the antioxidant system. Conclusion is clear that glucose deprivation-induced cell death is independent from ATP depletion-induced cell death.

Quantum Simulation of Polarized Light-Induced Electron Transfer with a Trapped-Ion Qutrit System.

Electron transfer within and between molecules is crucial in chemistry, biochemistry, and energy science. This study describes a quantum simulation method that explores the influence of light polarization on electron transfer between two molecules. By implementing precise and coherent control among the quantum states of trapped atomic ions, we can induce quantum dynamics that mimic the electron-transfer dynamics in molecules. We use three-level systems (qutrits), rather than traditional two-level systems (qubits), to enhance the simulation efficiency and realize high-fidelity simulations of electron-transfer dynamics. We treat the quantum interference between the electron coupling pathways from a donor with two degenerate excited states to an acceptor and analyze the transfer efficiency. We also examine the potential error sources that enter the quantum simulations. The trapped-ion systems have favorable scalings with system size compared to those of classical computers, promising access to richer electron-transfer simulations.

Development and Application of an Active Pharmacovigilance Framework Based on Electronic Healthcare Records from Multiple Centers in Korea.

INTRODUCTION: With the availability of retrospective pharmacovigilance data, the common data model (CDM) has been identified as an efficient approach towards anonymized multicenter analysis; however, the establishment of a suitable model for individual medical systems and applications supporting their analysis is a challenge. OBJECTIVE: The aim of this study was to construct a specialized Korean CDM (K-CDM) for pharmacovigilance systems based on a clinical scenario to detect adverse drug reactions (ADRs). METHODS: De-identified patient records (n = 5,402,129) from 13 institutions were converted to the K-CDM. From 2005 to 2017, 37,698,535 visits, 39,910,849 conditions, 259,594,727 drug exposures, and 30,176,929 procedures were recorded. The K-CDM, which comprises three layers, is compatible with existing models and is potentially adaptable to extended clinical research. Local codes for electronic medical records (EMRs), including diagnosis, drug prescriptions, and procedures, were mapped using standard vocabulary. Distributed queries based on clinical scenarios were developed and applied to K-CDM through decentralized or distributed networks. RESULTS: Meta-analysis of drug relative risk ratios from ten institutions revealed that non-steroidal anti-inflammatory drugs (NSAIDs) increased the risk of gastrointestinal hemorrhage by twofold compared with aspirin, and non-vitamin K anticoagulants decreased cerebrovascular bleeding risk by 0.18-fold compared with warfarin. CONCLUSION: These results are similar to those from previous studies and are conducive for new research, thereby demonstrating the feasibility of K-CDM for pharmacovigilance. However, the low quality of original EMR data, incomplete mapping, and heterogeneity between institutions reduced the validity of the analysis, thus necessitating continuous calibration among researchers, clinicians, and the government.

HLA-A*24:02 increase the risk of allopurinol-induced drug reaction with eosinophilia and systemic symptoms in HLA-B*58:01 carriers in a Korean population; a multicenter cross-sectional case-control study.

Background: HLA-B*58:01 is a well-known risk factor for allopurinol-induced severe cutaneous adverse reactions (SCARs). However, only a minority of HLA-B*58:01 carriers suffer SCARs after taking allopurinol. The aim of this study was to investigate subsidiary genetic markers that could identify those at further increased risk of developing allopurinol-induced drug reaction with eosinophilia and systemic symptoms (DRESS) in subjects with HLA-B*58:01. Methods: Subjects with B*58:01 were enrolled (21 allopurinol-induced DRESS and 52 allopurinol-tolerant control). HLA-A, -B, -C and -DRB1 alleles were compared. Comparison of risk between HLAs and allopurinol-induced SCAR in separate populations was performed to support the results. Kruskal-Wallis test, Pearson's chi-square test, Fisher's exact test and binary logistic regression were used to analyze the risk of SCAR development. Results: Frequencies of A*24:02 (71.4 vs. 17.3%, p < 0.001, odds ratio [OR] = 12.0; 95% confidence interval [CI], 3.6-39.2) were significantly higher in B*58:01 (+) DRESS than B*58:01 (+) tolerant controls. In addition, DRB1*13:02 further increased the risk of DRESS. The phenotype frequency of A*24:02/DRB1*13:02 was significantly higher in the B*58:01 (+) DRESS group than in the B*58:01 (+) tolerant controls (52.4% vs. 5.8%, p < 0.001, OR, 66.0; 95% CI, 6.1-716.2). In 2782 allopurinol user cohort, the overall prevalence of DRESS was 0.22%, which increased to 1.62% and 2.86% in the presence of B*58:01 and B*58:01/A*24:02, respectively. Conclusion: The additional secondary screening with A*24:02 and DRB1*13:02 alleles may identify those at further increased risk of allopurinol-induced DRESS in B*58:01 carriers.

Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma.

BACKGROUND: Transcriptomic analysis has been used to elucidate the complex pathogenesis of heterogeneous disease and may also contribute to identify potential therapeutic targets by delineating the hub genes. This study aimed to investigate whether blood transcriptomic clustering can distinguish clinical and immune phenotypes of asthmatics, and microbiome in asthmatics. METHODS: Transcriptomic expression of peripheral blood mononuclear cells (PBMCs) from 47 asthmatics and 21 non-asthmatics was measured using RNA sequencing. A hierarchical clustering algorithm was used to classify asthmatics. Differentially expressed genes, clinical phenotypes, immune phenotypes, and microbiome of each transcriptomic cluster were assessed. RESULTS: In asthmatics, three distinct transcriptomic clusters with numerously different transcriptomic expressions were identified. The proportion of severe asthmatics was highest in cluster 3 as 73.3%, followed by cluster 2 (45.5%) and cluster 1 (28.6%). While cluster 1 represented clinically non-severe T2 asthma, cluster 3 tended to include severe non-T2 asthma. Cluster 2 had features of both T2 and non-T2 asthmatics characterized by the highest serum IgE level and neutrophil-dominant sputum cell population. Compared to non-asthmatics, cluster 1 showed higher CCL23 and IL1RL1 expression while the expression of TREML4 was suppressed in cluster 3. CTSD and ALDH2 showed a significant positive linear relationship across three clusters in the order of cluster 1 to 3. No significant differences in the diversities of lung and gut microbiomes were observed among transcriptomic clusters of asthmatics and non-asthmatics. However, our study has limitations in that small sample size data were analyzed with unmeasured confounding factors and causal relationships or function pathways were not verified. CONCLUSIONS: Genetic clustering based on the blood transcriptome may provide novel immunological insight, which can be biomarkers of asthma immune phenotypes. Trial registration Retrospectively registered.

Adverse drug events leading to emergency department visits: A multicenter observational study in Korea.

Adverse drug events are significant causes of emergency department visits. Systematic evaluation of adverse drug events leading to emergency department visits by age is lacking. This multicenter retrospective observational study evaluated the prevalence and features of adverse drug event-related emergency department visits across ages. We reviewed emergency department medical records obtained from three university hospitals between July 2014 and December 2014. The proportion of adverse drug events among total emergency department visits was calculated. The cause, severity, preventability, and causative drug(s) of each adverse drug event were analyzed and compared between age groups (children/adolescents [<18 years], adults [18-64 years], and the elderly [≥65 years]). Of 59,428 emergency department visits, 2,104 (3.5%) were adverse drug event-related. Adverse drug event-related emergency department visits were more likely to be female and older. Multivariate logistic regression analysis revealed that compared to non- adverse drug event-related cases, adverse drug event-related emergency department visitors were more likely to be female (60.6% vs. 53.6%, p<0.001, OR 1.285, 95% CI 1.025-1.603) and older (50.8 ± 24.6 years vs. 37.7 ± 24.4 years, p<0.001, OR 1.892, 95% CI: 1.397-2.297). Comorbidities such as diabetes, chronic kidney disease, chronic liver disease, and malignancies were also significantly associated with adverse drug event-related emergency department visits. Side effects were the most common type of adverse drug events across age groups, although main types differed substantially depending on age. Serious adverse drug events, hospitalizations, and adverse drug event-related deaths occurred more frequently in the elderly than in adults or children/adolescents. The proportion of adverse drug event-related emergency department visits that were preventable was 15.3%. Causative drugs of adverse drug events varied considerably depending on age group. Adverse drug event features differ substantially according to age group. The findings suggest that an age-specific approach should be adopted in the preventive strategies to reduce adverse drug events.

Cancer depends on fatty acids for ATP production: A possible link between cancer and obesity.

Several metabolic pathways for the supply of adenosine triphosphate (ATP) have been proposed; however, the major source of reducing power for ADP in cancer remains unclear. Although glycolysis is the source of ATP in tumors according to the Warburg effect, ATP levels do not differ between cancer cells grown in the presence and absence of glucose. Several theories have been proposed to explain the supply of ATP in cancer, including metabolic reprograming in the tumor microenvironment. However, these theories are based on the production of ATP by the TCA-OxPhos pathway, which is inconsistent with the Warburg effect. We found that blocking fatty acid oxidation (FAO) in the presence of glucose significantly decreased ATP production in various cancer cells. This suggests that cancer cells depend on fatty acids to produce ATP through FAO instead of glycolysis. We observed that cancer cell growth mainly relies on metabolic nutrients and oxygen systemically supplied through the bloodstream instead of metabolic reprogramming. In a spontaneous mouse tumor model (KrasG12D; Pdx1-cre), tumor growth was 2-fold higher in mice fed a high-fat diet (low-carbo diet) that caused obesity, whereas a calorie-balanced, low-fat diet (high-carbo diet) inhibited tumor growth by 3-fold compared with that in mice fed a control/normal diet. This 5-fold difference in tumor growth between mice fed low-fat and high-fat diets suggests that fat-induced obesity promotes cancer growth, and tumor growth depends on fatty acids as the primary source of energy.

Diagnostic Performance of Antigen Rapid Diagnostic Tests, Chest Computed Tomography, and Lung Point-of-Care-Ultrasonography for SARS-CoV-2 Compared with RT-PCR Testing: A Systematic Review and Network Meta-Analysis.

(1) Background: The comparative performance of various diagnostic methods for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains unclear. This study aimed to investigate the comparison of the 3 index test performances of rapid antigen diagnostic tests (RDTs), chest computed tomography (CT), and lung point-of-care-ultrasonography (US) with reverse transcription-polymerase chain reaction (RT-PCR), the reference standard, to provide more evidence-based data on the appropriate use of these index tests. (2) Methods: We retrieved data from electronic literature searches of PubMed, Cochrane Library, and EMBASE from 1 January 2020, to 1 April 2021. Diagnostic performance was examined using bivariate random-effects diagnostic test accuracy (DTA) and Bayesian network meta-analysis (NMA) models. (3) Results: Of the 3992 studies identified in our search, 118 including 69,445 participants met our selection criteria. Among these, 69 RDT, 38 CT, and 15 US studies in the pairwise meta-analysis were included for DTA with NMA. CT and US had high sensitivity of 0.852 (95% credible interval (CrI), 0.791-0.914) and 0.879 (95% CrI, 0.784-0.973), respectively. RDT had high specificity, 0.978 (95% CrI, 0.960-0.996). In accuracy assessment, RDT and CT had a relatively higher than US. However, there was no significant difference in accuracy between the 3 index tests. (4) Conclusions: This meta-analysis suggests that, compared with the reference standard RT-PCR, the 3 index tests (RDTs, chest CT, and lung US) had similar and complementary performances for diagnosis of SARS-CoV-2 infection. To manage and control COVID-19 effectively, future large-scale prospective studies could be used to obtain an optimal timely diagnostic process that identifies the condition of the patient accurately.

Sodium-Glucose Cotransporter-2 Inhibitor-Related Diabetic Ketoacidosis: Accuracy Verification of Operational Definition.

BACKGROUND: The most important aspect of a retrospective cohort study is the operational definition (OP) of the disease. We developed a detailed OP for the detection of sodium-glucose cotransporter-2 inhibitors (SGLT2i) related to diabetic ketoacidosis (DKA). The OP was systemically verified and analyzed. METHODS: All patients prescribed SGLT2i at four university hospitals were enrolled in this experiment. A DKA diagnostic algorithm was created and distributed to each hospital; subsequently, the number of SGLT2i-related DKAs was confirmed. Then, the algorithm functionality was verified through manual chart reviews by an endocrinologist using the same OP. RESULTS: A total of 8,958 patients were initially prescribed SGLT2i. According to the algorithm, 0.18% (16/8,958) were confirmed to have SGLT2i-related DKA. However, based on manual chart reviews of these 16 cases, there was only one case of SGLT2i-related DKA (positive predictive value = 6.3%). Even after repeatedly narrowing the diagnosis range of the algorithm, the effect of a positive predictive value was insignificant (6.3-10.0%, P > 0.999). CONCLUSION: Owing to the nature of electronic medical record data, we could not create an algorithm that clearly differentiates SGLT2i-related DKA despite repeated attempts. In all retrospective studies, a portion of the samples should be randomly selected to confirm the accuracy of the OP through chart review. In retrospective cohort studies in which chart review is not possible, it will be difficult to guarantee the reliability of the results.

Synthesis and Characterization of a Conductive Polymer Blend Based on PEDOT:PSS and Its Electromagnetic Applications.

The purpose of this study is to prepare a resistive lossy material using conducting polymers for electromagnetic wave absorbers. This paper presents a conductive paste largely composed of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) with a polyurethane binder. The various secondary compounds are added in small amounts to an aqueous blended solution in order to enhance the electrical and mechanical properties of the conductive thin film. The synthesized conductive paste is characterized through electrical, chemical, and morphological analyses. The electrical conductivity of the thin film is measured using a four-point probe and surface profiler. The chemical and morphological changes are studied in various experiments using a Raman microscope, X-ray photoelectron spectroscopy, a scanning electron microscope, and an atomic force microscope. In order to verify the applicability of the synthesized conductive paste, which is composed of 70 wt% PEDOT:PSS, 30 wt% polyurethane, and secondary additives (DMAE 0.4 wt%, A-187 0.5 wt%, DMSO 7 wt%, Dynol 604 0.1 wt%, PUR 40 2.5 wt%), the Salisbury screen absorber is fabricated and evaluated in the X-band. According to the results, the absorber resonates at 9.7 GHz, the reflection loss is -38.6 dB, and the 90% absorption bandwidth is 3.4 GHz (8.2 to 11.6 GHz). Through this experiment, the applicability of the PEDOT:PSS-based conductive paste is sufficiently verified and it is found that excellent radar-absorbing performance can be realized.

Development and Validation of a Trigger Tool for Identifying Drug-Related Emergency Department Visits.

There are various trigger tools for detecting adverse drug events (ADEs), however, a drug-related emergency department (ED) visit trigger tool (DrEDTT) has not yet been developed. We aimed to develop and validate a DrEDTT with a multi-center cohort. In this cross-sectional study, we developed the DrEDTT consisting of 28 triggers through a comprehensive literature review and three phase expert group discussion. Next, we evaluated the performance of the DrEDTT by applying it to relevant medical records retrieved from four hospitals from January 2016 to June 2016. Two experts performed an in-depth chart review of a 25% of random sample of trigger flagged and unflagged ED visits and a true ADE was determined through causality assessment. Among 66,564 patients who visited the ED for reasons other than traffic accident and trauma during the study period, at least one trigger was found in 21,268 (32.0%) patients. A total of 959 true ADE cases (5.8%) were identified from a randomly selected 25% of ED visit cases. The overall positive predictive value was 14.0% (range: 8.3-66.7%). Sensitivity and specificity of DrEDTT were 77.7% and 70.4%, respectively. In conclusion, this newly developed trigger tool might be helpful to detect ADE-related ED visits.

Effects of Monotherapy with Clopidogrel vs. Aspirin on Vascular Function and Hemostatic Measurements in Patients with Coronary Artery Disease: The Prospective, Crossover I-LOVE-MONO Trial.

OBJECTIVES: To evaluate the effect of clopidogrel vs. aspirin monotherapy on vascular function and hemostatic measurement. BACKGROUND: Monotherapy with P2Y12 receptor inhibitor vs. aspirin can be a useful alterative to optimize clinical efficacy and safety in high-risk patients with coronary artery disease (CAD). METHODS: We performed a randomized, open-label, two-period crossover study in stented patients receiving at least 6-month of dual antiplatelet therapy (DAPT). Thirty CAD patients with moderate-to-high ischemic risk were randomly assigned to receive either 75 mg of clopidogrel or 100 mg of aspirin daily for 4 weeks, and were crossed over to the other strategy for 4 weeks. Vascular function was evaluated with reactive hyperemia-peripheral arterial tonometry (RH-PAT) and brachial-ankle pulse wave velocity (baPWV). Hemostatic profiles were measured with VerifyNow and thromboelastography (TEG). The primary endpoint was the reactive hyperemia index (RHI) during clopidogrel or aspirin monotherapy. RESULTS: Clopidogrel vs. aspirin monotherapy was associated with better endothelial function (RHI: 2.11 ± 0.77% vs. 1.87 ± 0.72%, p = 0.045), lower platelet reactivity (130 ± 64 vs. 214 ± 50 P2Y12 reaction unit [PRU], p < 0.001) and prolonged reaction time (TEG R: 5.5 ± 1.2 vs. 5.1 ± 1.1 min, p = 0.037). In multivariate analysis, normal endothelial function (RHI ≥ 2.1) was significantly associated with clot kinetics (TEG angle ≤ 68 degree) and 'PRU ≤ 132'. 'PRU ≤ 132' was achieved in 46.2% vs. 3.8% during clopidogrel administration vs. aspirin monotherapy (odds ratio 21.4, 95% confidence interval 2.7 to 170.1, p < 0.001). CONCLUSIONS: In CAD patients, clopidogrel vs. aspirin monotherapy was associated with better endothelial function, greater platelet inhibition and lower coagulation activity, suggesting pleiotropic effects of clopidogrel on endothelial function and hemostatic profiles.

Lung virome: New potential biomarkers for asthma severity and exacerbation.

BACKGROUND: Although some respiratory virus infections are known to contribute to the development and exacerbation of asthma, commensal viromes in airway have not been extensively studied due to technical challenges. OBJECTIVES: This study investigated the characteristics of the virome in asthmatic airways. METHODS: Both the bacteriome and virome profiles in sputum from 12 healthy individuals, 15 patients with nonsevere asthma, and 15 patients with severe asthma were analyzed and assessed for the association with clinical characteristics such as severity, exacerbation, Asthma Control Test (ACT), and lung function. RESULTS: While analysis of the 16S ribosomal RNA bacteriome in the airway showed no differences, clear contrasts in the diversity and composition of airway viromes were observed between healthy controls and patients with asthma. Herpesviruses were the most abundant type of virus in the asthma group (44.6 ± 4.6%), mainly with cytomegalovirus (CMV) and EBV accounting for 24.5 ± 3.3% and 16.9 ± 3.5%, respectively, in contrast to those in the healthy controls (5.4 ± 2.5% and 7.1 ± 3.0%, respectively). CMV and EBV were more abundant in patients with asthma who experienced exacerbation, and their abundance showed correlation with more severe asthma, lower ACT score, and lower lung function. On the contrary, bacteriophage that is abundant in healthy controls was severely reduced in patients with asthma in the order of nonsevere and severe asthma and presented significant positive correlation with ACT and FEV1/forced vital capacity. CONCLUSIONS: Lung viromes, especially, CMV, EBV, and bacteriophage may be potential biomarkers of asthma severity and exacerbation.

Ginsenoside F2 induces cellular toxicity to glioblastoma through the impairment of mitochondrial function.

BACKGROUND: Glioblastoma (GBM) is the most aggressive tumor residing within the central nervous system, with extremely poor prognosis. Although the cytotoxic effects of ginsenoside F2 (GF2) on GBM were previously suggested, the precise anti-GBM mechanism of GF2 remains unclear. The aim of this study was to explore the anti-cancer molecular mechanism of GF2 toward human GBM. METHODS: GF2-driven cellular toxicity was confirmed in two different GBM cells, U373 and Hs683. To test mitochondrial impairment driven by GF2, we examined the mitochondrial membrane potential, OCR, and ATP production. An intracellular redox imbalance was identified by measuring the relative ratio of reduced glutathione to oxidized glutathione (GSH/GSSG), glutaredoxin (GLRX) mRNA expression, intracellular NAD+ level, and AMPK phosphorylation status. RESULTS: GF2 increased the percentage of cleaved caspase 3-positive cells and γH2AX signal intensities, confirming that GF2 shows the cytotoxicity against GBM. GO enrichment analysis suggested that the mitochondrial function could be negatively influenced by GF2. GF2 reduced the mitochondrial membrane potential, basal mitochondrial respiratory rate, and ATP production capacity. Our results showed that GF2 downregulated the relative GSH/GSSG, intracellular NAD+ level, and GLRX expression, suggesting that GF2 may alter the intracellular redox balance that led to mitochondrial impairment. CONCLUSION: GF2 reduces mitochondrial membrane potential, inhibits cellular oxygen consumption, activates AMPK signaling, and induces cell death. Our study examined the potential vulnerability of mitochondrial activity in GBM, and this may hold therapeutic promise.

Universal Multienergy Harvester Architecture.

The energy available in the ambient vibrations, magnetic fields, and sunlight can be simultaneously or independently harvested using universal architecture. The universal harvester design is shown to effectively convert ambient magnetic fields, vibration, and light into electricity. The architecture is composed of a perovskite solar cell integrated onto a magnetoelectric composite cantilever beam. The efficiency of the large-area perovskite solar cell is shown to reach 15.74% (cell area is >1100% larger than traditional perovskite solar cells) by selecting glass/indium tin oxide (ITO) as the cathode that reduces the charge recombination. The magnetoelectric composite beam is designed to include the effect of the mass and volume of the solar cell on power generation. Results demonstrate that universal energy harvester can simultaneously capture vibration, magnetic fields, and solar irradiation to provide an ultrahigh-power density of 18.6 mW/cm3. The total power generated by the multienergy harvester, including vibration, magnetic field, and solar stimuli, is 23.52 mW from a total surface area of 9.6 cm2 and a total volume of 1.26 cm3. These results will have a tremendous impact on the design of the power sources for Internet of Things sensors and wireless devices.