Comparison of First-Line Dual Combination Treatments in Hypertension: Real-World Evidence from Multinational Heterogeneous Cohorts.

Background and objectives: 2018 ESC/ESH Hypertension guideline recommends 2-drug combination as initial anti-hypertensive therapy. However, real-world evidence for effectiveness of recommended regimens remains limited. We aimed to compare the effectiveness of first-line anti-hypertensive treatment combining 2 out of the following classes: angiotensin-converting enzyme (ACE) inhibitors/angiotensin-receptor blocker (A), calcium channel blocker (C), and thiazide-type diuretics (D).Methods: Treatment-naïve hypertensive adults without cardiovascular disease (CVD) who initiated dual anti-hypertensive medications were identified in 5 databases from US and Korea. The patients were matched for each comparison set by large-scale propensity score matching. Primary endpoint was all-cause mortality. Myocardial infarction, heart failure, stroke, and major adverse cardiac and cerebrovascular events as a composite outcome comprised the secondary measure.Results: A total of 987,983 patients met the eligibility criteria. After matching, 222,686, 32,344, and 38,513 patients were allocated to A+C vs. A+D, C+D vs. A+C, and C+D vs. A+D comparison, respectively. There was no significant difference in the mortality during total of 1,806,077 person-years: A+C vs. A+D (hazard ratio [HR], 1.08; 95% confidence interval [CI], 0.97-1.20; p=0.127), C+D vs. A+C (HR, 0.93; 95% CI, 0.87-1.01; p=0.067), and C+D vs. A+D (HR, 1.18; 95% CI, 0.95-1.47; p=0.104). A+C was associated with a slightly higher risk of heart failure (HR, 1.09; 95% CI, 1.01-1.18; p=0.040) and stroke (HR, 1.08; 95% CI, 1.01-1.17; p=0.040) than A+D.Conclusions: There was no significant difference in mortality among A+C, A+D, and C+D combination treatment in patients without previous CVD. This finding was consistent across multi-national heterogeneous cohorts in real-world practice

Analog Self-Interference Cancellation With Practical RF Components for Full-Duplex Radios

One of the main obstacles in full-duplex radios is analog-to-digital converter (ADC) saturation on a receiver due to the strong self-interference (SI). To solve this issue, researchers have proposed two different types of analog self-interference cancellation (SIC) methods—i) passive suppression and ii) regeneration-and-subtraction of SI. For the latter case, the tunable RF component, such as a multi-tap circuit, reproduces and subtracts the SI. The resolutions of such RF components constitute the key factor of the analog SIC. Indeed, they are directly related to how well the SI is imitated. Another major issue in analog SIC is the inaccurate estimation of the SI channel due to the nonlinear distortions, which mainly come from the power amplifier (PA). In this paper, we derive a closed-form expression for the SIC performance of the multi-tap circuit; we consider how the RF components must overcome such practical impairments as digitally-controlled attenuators, phase shifters, and PA. For a realistic performance analysis, we exploit the measured PA characteristics and carry out a 3D ray-tracing-based, system-level throughput analysis. Our results confirm that the non-idealities of the RF components significantly affect the analog SIC performance. We believe our study provides insight into the design of the practical full-duplex system

Development of a standardized in-hospital cardiopulmonary resuscitation set-up

Objective. This study evaluated whether chest compression in a standardized inhospital cardiopulmonary resuscitation (CPR) set-up can be performed as effectively as when the rescuer is kneeling beside the patient lying on the floor. Specifically, the in-hospital test was standardized according to the rescuers’ average knee height. Methods. Experimental intervention (test 1) was a standardized, in-hospital CPR set-up: first, the bed height was fixed at 70 cm. Second, the height difference between the bed and a step stool was set to the average knee height of the CPR team members (45 cm). Control intervention (test 2) was kneeling on floor. Thirty-eight medical doctors on the CPR team each performed 2 minutes of chest compressions in test 1 and 2 in random order (cross-over trial). A Little Anne was used as a simulated patient who had experienced cardiac arrest. Chest compression parameters, such as average depth and rate, were measured using an accelerometer device. Results. In all tests, the average depths were those recommended in the most recent CPR guidelines (50–60 mm); there were no significant differences between Tests 1 and 2 (53.1 ± 4.3 mm vs. 52.6 ± 4.8 mm, respectively; p = 0.398). The average rate in Test 2 (119.1 ± 12.4 numbers/min) was slightly faster than that in Test 1 (116.4 ± 10.2 numbers/ min; p = 0.028). No differences were observed in any other parameters. Conclusions. Chest compression quality in our standardized in-hospital CPR set-up was similar with that performed in a kneeling position on the floor. Trial Registration: Clinical Research Information Service: KCT000159

Potential redox-sensitive Akt activation by dopamine activates Bad and promotes cell death in melanocytes

Dopamine (DA) is a well known oxidative neurotoxin. In addition, Akt has been reported to deliver a survival signal that inhibits apoptosis. However, it has also been reported that chronic Akt activation leads to apoptosis in response to oxidative stress. The objective of the present study was to investigate the possible role of the Akt pathway in vitiligo and its possible relationship with DA-induced cell death using Mel-Ab cells. Cultured Mel-Ab cells were treated with DA with and without N-Acetyl-L-cysteine (NAC), which is known to have antioxidative properties. Cell viability was then assessed by a crystal violet assay and Annexin staining was performed. The changes in the expression of Akt were analyzed by western blot analysis. The cell viability was reduced by approximately 60% in response to treatment with 500 µM DA, and NAC effectively prevented this cytotoxic effect. Likewise, treatment with DA produced numerous Annexin positive cells, while treatment with NAC prevented this apoptotic cell death. Akt was slowly phosphorylated after treatment with DA, while NAC clearly inhibited the DA-induced Akt activation. Western blot analysis also showed that treatment with DA induced the activation of Bad. Finally, LY294002 exerted a protective effect against DA-induced apoptotic cell death. DA may induce redox-sensitive Akt activation and increase the level of Bad, which can promote cell death by heterodimerization with survival proteins. Moreover, NAC effectively protects against DA-induced melanocyte death via inhibition of DA-induced Akt activation

Anti-Obesity and Anti-Adipogenic Effects of Chitosan Oligosaccharide (GO2KA1) in SD Rats and in 3T3-L1 Preadipocytes Models

Excess body weight is a major risk factor for type 2 diabetes (T2D) and associated metabolic complications, and weight loss has been shown to improve glycemic control and decrease morbidity and mortality in T2D patients. Weight-loss strategies using dietary interventions produce a significant decrease in diabetes-related metabolic disturbance. We have previously reported that the supplementation of low molecular chitosan oligosaccharide (GO2KA1) significantly inhibited blood glucose levels in both animals and humans. However, the effect of GO2KA1 on obesity still remains unclear. The aim of the study was to evaluate the anti-obesity effect of GO2KA1 on lipid accumulation and adipogenic gene expression using 3T3-L1 adipocytes in vitro and plasma lipid profiles using a Sprague-Dawley (SD) rat model. Murine 3T3-L1 preadipocytes were stimulated to differentiate under the adipogenic stimulation in the presence and absence of varying concentrations of GO2KA1. Adipocyte differentiation was confirmed by Oil Red O staining of lipids and the expression of adipogenic gene expression. Compared to control group, the cells treated with GO2KA1 significantly decreased in intracellular lipid accumulation with concomitant decreases in the expression of key transcription factors, peroxisome proliferator-activated receptor gamma (PPARγ) and CCAAT/enhancer-binding protein alpha (CEBP/α). Consistently, the mRNA expression of downstream adipogenic target genes such as fatty acid binding protein 4 (FABP4), fatty acid synthase (FAS), were significantly lower in the GO2KA1-treated group than in the control group. In vivo, male SD rats were fed a high fat diet (HFD) for 6 weeks to induced obesity, followed by oral administration of GO2KA1 at 0.1 g/kg/body weight or vehicle control in HFD. We assessed body weight, food intake, plasma lipids, levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) for liver function, and serum level of adiponectin, a marker for obesity-mediated metabolic syndrome. Compared to control group GO2KA1 significantly suppressed body weight gain (185.8 ± 8.8 g vs. 211.6 ± 20.1 g, p \u3c 0.05) with no significant difference in food intake. The serum total cholesterol, triglyceride, and low-density lipoprotein (LDL) levels were significantly lower in the GO2KA1-treated group than in the control group, whereas the high-density lipoprotein (HDL) level was higher in the GO2KA1 group. The GO2KA1-treated group also showed a significant reduction in ALT and AST levels compared to the control. Moreover, serum adiponectin levels were significantly 1.5-folder higher than the control group. These in vivo and in vitro findings suggest that dietary supplementation of GO2KA1 may prevent diet-induced weight gain and the anti-obesity effect is mediated in part by inhibiting adipogenesis and increasing adiponectin level

3D garment digitisation for virtual wardrobe using a commodity depth sensor

5-Aminovaleric acid (5AVA) is an important five-carbon platform chemical that can be used for the synthesis of polymers and other chemicals of industrial interest. Enzymatic conversion of L-lysine to 5AVA has been achieved by employing lysine 2-monooxygenase encoded by the davB gene and 5-aminovaleramidase encoded by the davA gene. Additionally, a recombinant Escherichia coli strain expressing the davB and davA genes has been developed for bioconversion of L-lysine to 5AVA. To use glucose and xylose derived from lignocellulosic biomass as substrates, rather than L-lysine as a substrate, we previously examined direct fermentative production of 5AVA from glucose by metabolically engineered E. coli strains. However, the yield and productivity of 5AVA achieved by recombinant E. coli strains remain very low. Thus, Corynebacterium glutamicum, a highly efficient L-lysine producing microorganism, should be useful in the development of direct fermentative production of 5AVA using L-lysine as a precursor for 5AVA. Here, we report the development of metabolically engineered C. glutamicum strains for enhanced fermentative production of 5AVA from glucose.Various expression vectors containing different promoters and origins of replication were examined for optimal expression of Pseudomonas putida davB and davA genes encoding lysine 2-monooxygenase and delta-aminovaleramidase, respectively. Among them, expression of the C. glutamicum codon-optimized davA gene fused with His-Tag at its N-Terminal and the davB gene as an operon under a strong synthetic H promoter (plasmid p36davAB3) in C. glutamicum enabled the most efficient production of 5AVA. Flask culture and fed-batch culture of this strain produced 6.9 and 19.7\ua0g/L (together with 11.9\ua0g/L glutaric acid as major byproduct) of 5AVA, respectively. Homology modeling suggested that endogenous gamma-aminobutyrate aminotransferase encoded by the gabT gene might be responsible for the conversion of 5AVA to glutaric acid in recombinant C. glutamicum. Fed-batch culture of a C. glutamicum gabT mutant-harboring p36davAB3 produced 33.1\ua0g/L 5AVA with much reduced (2.0\ua0g/L) production of glutaric acid.Corynebacterium glutamicum was successfully engineered to produce 5AVA from glucose by optimizing the expression of two key enzymes, lysine 2-monooxygenase and delta-aminovaleramidase. In addition, production of glutaric acid, a major byproduct, was significantly reduced by employing C. glutamicum gabT mutant as a host strain. The metabolically engineered C. glutamicum strains developed in this study should be useful for enhanced fermentative production of the novel C5 platform chemical 5AVA from renewable resources

A Case of Duodenal Anisakiasis with Duodenal Ulcer

Humans can be incidentally parasitized by third-stage larvae of Anisakis species following the ingestion of raw or undercooked seafood. Acute gastric anisakiasis is one of the most frequently encountered complaints in Korea. However, duodenal anisakiasis with duodenal ulcer had not been reported in Korea, despite the habit of eating raw fish. In this case, a 47-year-old man was hospitalized because of sharp epigastric pain and repeated vomiting after eating raw fish 3 days previously. On admission, esophagogastroduodenoscopic examination revealed an active duodenal bulb ulcer. At 5 mm away from the ulcer margin, a whitish linear worm was found with half of its body penetrating the duodenal mucosa. Herein, we report this case of duodenal anisakiasis accompanied by duodenal ulcer

Effect of Varying the Semiconducting/Metallic Tube Ratio on the Performance of Mixed Single-Walled Carbon Nanotube Network Gas Sensors

The sensing properties of mixed networks consisting of semiconducting and metallic single-walled carbon nanotubes (SWCNTs) have been found to largely vary depending on the ratio of semiconducting to metallic tubes. Solution-deposited 99% semiconductor-enriched nanotube networks exhibited a sensitivity of 1.908%/ppm, whereas the unenriched 66% and 90% enriched samples exhibited a sensitivity of 0.027%/ppm and 0.113%/ppm, respectively. These results suggest that it is extremely important to minimize the metallic pathways to achieve high sensitivity. After an oxygen plasma treatment, the unenriched 66% sample exhibited a 526% increase in sensitivity (0.142%/ppm) compared to the untreated one, whereas the 90% device demonstrated a sensitivity of 1.521%/ppm, which corresponds to an improvement in the sensitivity of 13.5 times the pristine 90% sample. In addition, the plasma-treated sensors exhibited a much faster response time than the untreated one. The significant improvement in the performance of the highly enriched network sensors was explained by the large increase in the anchoring sites for ammonia molecules on the surface of the semiconducting single-walled CNTs and the faster charge transfer from absorbed molecules

A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data

Background and objective: As a response to the ongoing COVID-19 pandemic, several prediction models in the existing literature were rapidly developed, with the aim of providing evidence-based guidance. However, none of these COVID-19 prediction models have been found to be reliable. Models are commonly assessed to have a risk of bias, often due to insufficient reporting, use of non-representative data, and lack of large-scale external validation. In this paper, we present the Observational Health Data Sciences and Informatics (OHDSI) analytics pipeline for patient-level prediction modeling as a standardized approach for rapid yet reliable development and validation of prediction models. We demonstrate how our analytics pipeline and open-source software tools can be used to answer important prediction questions while limiting potential causes of bias (e.g., by validating phenotypes, specifying the target population, performing large-scale external validation, and publicly providing all analytical source code). Methods: We show step-by-step how to implement the analytics pipeline for the question: ‘In patients hospitalized with COVID-19, what is the risk of death 0 to 30 days after hospitalization?’. We develop models using six different machine learning methods in a USA claims database containing over 20,000 COVID-19 hospitalizations and externally validate the models using data containing over 45,000 COVID-19 hospitalizations from South Korea, Spain, and the USA. Results: Our open-source software tools enabled us to efficiently go end-to-end from problem design to reliable Model Development and evaluation. When predicting death in patients hospitalized with COVID-19, AdaBoost, random forest, gradient boosting machine, and decision tree yielded similar or lower internal and external validation discrimination performance compared to L1-regularized logistic regression, whereas the MLP neural network consistently resulted in lower discrimination. L1-regularized logistic regression models were well calibrated. Conclusion: Our results show that following the OHDSI analytics pipeline for patient-level prediction modelling can enable the rapid development towards reliable prediction models. The OHDSI software tools and pipeline are open source and available to researchers from all around the world.</p