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يتناول كتاب (الأرض) والذي قام بتأليفه (سون-هان كيم) في حوالي (34) صفحة من القطع المتوسط موضوع (القصص الكورية للأطفال) مستعرضا بعض من المحتويات التالية : الأرض بيت، نظرة داخل وكر النمل، قطارات الأنفاق، كيف تتكون الأحافير، الأرض أم، إنها تحتضن الكثير من النبات في تربتها، كما تحتضن ذاعا الأم الدافئتان أطفالها، بعض الحيوانات تعيش على الأشجار، هنالك حيوانات تعيش في باطن الأرض أيضا، إن الناس يعشون على سطح الأرض أيضا تكبر القرى وتتحول إلى مدن، كيف تكون الفحم الحجري، الأرض تشبه مقبرة كبيرة، مما تتكون الأرض، أن الحياة تدب في الأرض.

Sodium–glucose cotransporter 2 (SGLT2) inhibitors reduce cardiovascular events in humans with type 2 diabetes (T2D); however, the underlying mechanism remains unclear. Activation of the NLR family, pyrin domain-containing 3 (NLRP3) inflammasome and subsequent interleukin (IL)-1β release induces atherosclerosis and heart failure. Here we show the effect of SGLT2 inhibitor empagliflozin on NLRP3 inflammasome activity. Patients with T2D and high cardiovascular risk receive SGLT2 inhibitor or sulfonylurea for 30 days, with NLRP3 inflammasome activation analyzed in macrophages. While the SGLT2 inhibitor’s glucose-lowering capacity is similar to sulfonylurea, it shows a greater reduction in IL-1β secretion compared to sulfonylurea accompanied by increased serum β-hydroxybutyrate (BHB) and decreased serum insulin. Ex vivo experiments with macrophages verify the inhibitory effects of high BHB and low insulin levels on NLRP3 inflammasome activation. In conclusion, SGLT2 inhibitor attenuates NLRP3 inflammasome activation, which might help to explain its cardioprotective effects. SGLT2 inhibitors, a class of type 2 diabetes medication, reduce cardiovascular events in patients beyond expectation from blood sugar control. Here the authors report a randomized controlled trial showing that SGLT2 inhibitors reduce inflammasome activation in peripheral macrophages, which may contribute to the cardiovascular protection.

Drug combinations rather than increasing doses of one drug can achieve greater efficacy and lower risks. Thus, as an alternative to high-intensity statin monotherapy, moderate-intensity statin with ezetimibe combination therapy can lower LDL cholesterol concentrations effectively while reducing adverse effects. However, evidence from randomised trials to compare long-term clinical outcomes is needed. In this randomised, open-label, non-inferiority trial, patients with atherosclerotic cardiovascular disease (ASCVD) at 26 clinical centres in South Korea were randomly assigned (1:1) to receive either moderate-intensity statin with ezetimibe combination therapy (rosuvastatin 10 mg with ezetimibe 10 mg) or high-intensity statin monotherapy (rosuvastatin 20 mg). The primary endpoint was the 3-year composite of cardiovascular death, major cardiovascular events, or non-fatal stroke, in the intention-to-treat population with a non-inferiority margin of 2·0%. This trial is registered with ClinicalTrials.gov, NCT03044665 and is complete. Between Feb 14, 2017, and Dec 18, 2018, 3780 patients were enrolled: 1894 patients to the combination therapy group and 1886 to the high-intensity statin monotherapy group. The primary endpoint occurred in 172 patients (9·1%) in the combination therapy group and 186 patients (9·9%) in the high-intensity statin monotherapy group (absolute difference −0·78%; 90% CI −2·39 to 0·83). LDL cholesterol concentrations of less than 70 mg/dL at 1, 2, and 3 years were observed in 73%, 75%, and 72% of patients in the combination therapy group, and 55%, 60%, and 58% of patients in the high-intensity statin monotherapy group (all p<0·0001). Discontinuation or dose reduction of the study drug by intolerance was observed in 88 patients (4·8%) and 150 patients (8·2%), respectively (p<0·0001). Among patients with ASCVD, moderate-intensity statin with ezetimibe combination therapy was non-inferior to high-intensity statin monotherapy for the 3-year composite outcomes with a higher proportion of patients with LDL cholesterol concentrations of less than 70 mg/dL and lower intolerance-related drug discontinuation or dose reduction. Hanmi Pharmaceutical.

Objectives To investigate machine learning approaches for radiomics-based prediction of prognostic biomarkers and molecular subtypes of breast cancer using quantification of tumor heterogeneity and angiogenesis properties on magnetic resonance imaging (MRI). Methods This prospective study examined 291 invasive cancers in 288 patients who underwent breast MRI at 3 T before treatment between May 2017 and July 2019. Texture and perfusion analyses were performed and a total of 160 parameters for each cancer were extracted. Relationships between MRI parameters and prognostic biomarkers were analyzed using five machine learning algorithms. Each model was built using only texture features, only perfusion features, or both. Model performance was compared using the area under the receiver-operating characteristic curve (AUC) and the DeLong method, and the importance of MRI parameters in prediction was derived. Results Texture parameters were associated with the status of hormone receptors, human epidermal growth factor receptor 2, and Ki67, tumor size, grade, and molecular subtypes ( p < 0.002). Perfusion parameters were associated with the status of hormone receptors and Ki67, grade, and molecular subtypes ( p < 0.003). The random forest model integrating texture and perfusion parameters showed the highest performance (AUC = 0.75). The performance of the random forest model was the best with a special scale filter of 0 (AUC = 0.80). The important parameters for prediction were texture irregularity (entropy) and relative extracellular extravascular space ( V e ). Conclusions Radiomic machine learning that integrates tumor heterogeneity and angiogenesis properties on MRI has the potential to noninvasively predict prognostic factors of breast cancer. Key Points • Machine learning, integrating tumor heterogeneity and angiogenesis properties on MRI, can be applied to predict prognostic biomarkers and molecular subtypes in breast cancer. • The random forest model showed the best predictive performance among the five machine learning models (logistic regression, decision tree, naïve Bayes, random forest, and artificial neural network). • The most important MRI parameters for predicting prognostic factors in breast cancer were texture irregularity (entropy) among texture parameters and relative extracellular extravascular space (V e ) among perfusion parameters.

Despite the detailed imaging information provided by optical coherence tomography (OCT) during percutaneous coronary intervention (PCI), clinical benefits of this imaging technique in this setting remain uncertain. The aim of the OCCUPI trial was to compare the clinical benefits of OCT-guided versus angiography-guided PCI for complex lesions, assessed as the rate of major adverse cardiac events at 1 year. This investigator-initiated, multicentre, randomised, open-label, superiority trial conducted at 20 hospitals in South Korea enrolled patients aged 19–85 years for whom PCI with drug-eluting stents was clinically indicated. After diagnostic angiography, clinical and angiographic findings were assessed to identify patients who met the criterion of having one or more complex lesions. Patients were randomly assigned 1:1 to receive PCI with OCT guidance (OCT-guidance group) or angiography guidance without OCT (angiography-guidance group). Web-response permuted-block randomisation (mixed blocks of four or six) was used at each participating site to allocate patients. The allocation sequence was computer-generated by an external programmer who was not involved in the rest of the trial. Outcome assessors were masked to group assignment. Patients, follow-up health-care providers, and data analysers were not masked. PCI was done according to conventional standard methods with everolimus-eluting stents. The primary endpoint was major adverse cardiac events (a composite of cardiac death, myocardial infarction, stent thrombosis, or ischaemia-driven target-vessel revascularisation), 1 year after PCI. The primary analysis was done in the intention-to-treat population. The margin used to establish superiority was 1·0 as a hazard ratio. This trial is registered with ClinicalTrials.gov (NCT03625908) and is completed. Between Jan 9, 2019, and Sept 22, 2022, 1604 patients requiring PCI with drug-eluting stents for complex lesions were randomly assigned to receive either OCT-guided PCI (n=803) or angiography-guided PCI (n=801). 1290 (80%) of 1604 patients were male and 314 (20%) were female. The median age of patients at randomisation was 64 years (IQR 57–70). 1588 (99%) patients completed 1-year follow-up. The primary endpoint occurred in 37 (5%) of 803 patients in the OCT-guided PCI group and 59 (7%) of 801 patients in the angiography-guided PCI group (absolute difference –2·8% [95% CI –5·1 to –0·4]; hazard ratio 0·62 [95% CI 0·41 to 0·93]; p=0·023). Rates of stroke, bleeding events, and contrast-induced nephropathy were not significantly different across the two groups. Among patients who required drug-eluting stent implantation for complex lesions, OCT guidance resulted in a lower incidence of major adverse cardiac events at 1 year compared with angiography guidance. These findings indicate the existence of a therapeutic benefit of OCT as an intravascular imaging technique for PCI guidance in patients with complex coronary lesions. Abbott Vascular and Cardiovascular Research Center. For the Korean translation of the abstract see Supplementary Materials section.

Senna tora is a widely used medicinal plant. Its health benefits have been attributed to the large quantity of anthraquinones, but how they are made in plants remains a mystery. To identify the genes responsible for plant anthraquinone biosynthesis, we reveal the genome sequence of S. tora at the chromosome level with 526 Mb (96%) assembled into 13 chromosomes. Comparison among related plant species shows that a chalcone synthase-like (CHS-L) gene family has lineage-specifically and rapidly expanded in S. tora . Combining genomics, transcriptomics, metabolomics, and biochemistry, we identify a CHS-L gene contributing to the biosynthesis of anthraquinones. The S. tora reference genome will accelerate the discovery of biologically active anthraquinone biosynthesis pathways in medicinal plants. Anthraquinones are aromatic polyketides and have been used for treating various diseases, but the biosynthetic pathway is unclear. Here, the authors assemble the genome of an anthraquinone-producing medicinal plant Senna tora and show the evidences that CHS-like genes may be involved in anthraquinone biosynthesis.

Glucosinolates (GSL) are naturally occurring β-d-thioglucosides found across the cruciferous vegetables. Core structure formation and side-chain modifications lead to the synthesis of more than 200 types of GSLs in Brassicaceae. Isothiocyanates (ITCs) are chemoprotectives produced as the hydrolyzed product of GSLs by enzyme myrosinase. Benzyl isothiocyanate (BITC), phenethyl isothiocyanate (PEITC) and sulforaphane ([1-isothioyanato-4-(methyl-sulfinyl) butane], SFN) are potential ITCs with efficient therapeutic properties. Beneficial role of BITC, PEITC and SFN was widely studied against various cancers such as breast, brain, blood, bone, colon, gastric, liver, lung, oral, pancreatic, prostate and so forth. Nuclear factor-erythroid 2-related factor-2 (Nrf2) is a key transcription factor limits the tumor progression. Induction of ARE (antioxidant responsive element) and ROS (reactive oxygen species) mediated pathway by Nrf2 controls the activity of nuclear factor-kappaB (NF-κB). NF-κB has a double edged role in the immune system. NF-κB induced during inflammatory is essential for an acute immune process. Meanwhile, hyper activation of NF-κB transcription factors was witnessed in the tumor cells. Antagonistic activity of BITC, PEITC and SFN against cancer was related with the direct/indirect interaction with Nrf2 and NF-κB protein. All three ITCs able to disrupts Nrf2-Keap1 complex and translocate Nrf2 into the nucleus. BITC have the affinity to inhibit the NF-κB than SFN due to the presence of additional benzyl structure. This review will give the overview on chemo preventive of ITCs against several types of cancer cell lines. We have also discussed the molecular interaction(s) of the antagonistic effect of BITC, PEITC and SFN with Nrf2 and NF-κB to prevent cancer.

BMI1, a polycomb group (PcG) protein, plays a critical role in epigenetic regulation of cell differentiation and proliferation, and cancer stem cell self-renewal. BMI1 is upregulated in multiple types of cancer, including prostate cancer. As a key component of polycomb repressive complex 1 (PRC1), BMI1 exerts its oncogenic functions by enhancing the enzymatic activities of RING1B to ubiquitinate histone H2A at lysine 119 and repress gene transcription. Here, we report a PRC1-independent role of BMI1 that is critical for castration-resistant prostate cancer (CRPC) progression. BMI1 binds the androgen receptor (AR) and prevents MDM2-mediated AR protein degradation, resulting in sustained AR signaling in prostate cancer cells. More importantly, we demonstrate that targeting BMI1 effectively inhibits tumor growth of xenografts that have developed resistance to surgical castration and enzalutamide treatment. These results suggest that blocking BMI1 alone or in combination with anti-AR therapy can be more efficient to suppress prostate tumor growth. The polycomb group protein BMI1 is highly expressed in prostate cancer. Here, the authors demonstrate that BMI1 directly interacts with AR leading to increased AR signaling independently of PRC1 complex and that targeting BMI1 inhibits tumor growth of castration-resistant prostate cancer tumors.

Indoor agriculture, especially plant factories, becomes essential because of the advantages of cultivating crops yearly to address global food shortages. Plant factories have been growing in scale as commercialized. Developing an on-site system that estimates the fresh weight of crops non-destructively for decision-making on harvest time is necessary to maximize yield and profits. However, a multi-layer growing environment with on-site workers is too confined and crowded to develop a high-performance system.This research developed a machine vision-based fresh weight estimation system to monitor crops from the transplant stage to harvest with less physical labor in an on-site industrial plant factory. A linear motion guide with a camera rail moving in both the x-axis and y-axis directions was produced and mounted on a cultivating rack with a height under 35 cm to get consistent images of crops from the top view. Raspberry Pi4 controlled its operation to capture images automatically every hour. The fresh weight was manually measured eleven times for four months to use as the ground-truth weight of the models. The attained images were preprocessed and used to develop weight prediction models based on manual and automatic feature extraction. The performance of models was compared, and the best performance among them was the automatic feature extraction-based model using convolutional neural networks (CNN; ResNet18). The CNN-based model on automatic feature extraction from images performed much better than any other manual feature extraction-based models with 0.95 of the coefficients of determination (R ) and 8.06 g of root mean square error (RMSE). However, another multiplayer perceptron model (MLP_2) was more appropriate to be adopted on-site since it showed around nine times faster inference time than CNN with a little less R (0.93). Through this study, field workers in a confined indoor farming environment can measure the fresh weight of crops non-destructively and easily. In addition, it would help to decide when to harvest on the spot.

The long-term outcome of first-line moderate-intensity statin with ezetimibe combination therapy for secondary prevention after percutaneous coronary intervention in patients with acute coronary syndrome (ACS) compared to high-intensity statin monotherapy remains elusive. The objective of this study was to compare the effectiveness of moderate-intensity statin and ezetimibe combination therapy with high-intensity statin monotherapy. We conducted a nationwide, population-based, retrospective, cohort study of patients with ACS from 2013 to 2019. The patients using combination therapy were matched (1:1) to those using monotherapy. The primary outcome was a composite of myocardial infarction, stroke and all-cause mortality. We estimated the hazard ratios (HR) and 95% confidence intervals (CIs) using the Cox proportional hazards regression. After propensity score matching, 10,723 pairs were selected. Men accounted for 70% of the patients and 37% aged > 70 years. The primary endpoint occurred in 1297 patients (12.1%) in the combination group and in 1426 patients (13.3%) in the monotherapy group, and decreased risk (HR 0.85, 95% CI 0.78–0.92, P  < 0.001) in the combination group. Among the patients with ACS, moderate-intensity statin with ezetimibe combination therapy was associated with decreased risk of adverse cardiovascular outcomes compared with high-intensity statin monotherapy in a nationwide population-based study representing routine clinical practice.