Effectiveness and Safety of Sodium-Glucose Cotransporter2 Inhibitors Added to Dual or Triple Treatment in Patients with Type2 Diabetes Mellitus

Introduction We evaluated the effectiveness and safety of sodium-glucose cotransporter 2 inhibitor (SGLT2i) add-on treatment in patients with type 2 diabetes mellitus (T2DM) in the real-world setting. Methods This single-center retrospective study used the clinical database of Seoul National University Hospital in South Korea. Patients who received metformin monotherapy or combination therapy with ≥ 1 other oral hypoglycemic medication and had a baseline glycosylated hemoglobin (HbA1c) between 7.0% and 10.5% were included. Propensity score matching was applied between patients treated with and without SGLT2 inhibitors (SGLT2i and non-SGLT2i groups, respectively). Changes in HbA1c from baseline to week 26 were compared between the SGLT2i and non-SGLT2i groups, and risk of adverse events (AE) were also assessed. Results A total of 1106 patients were included. At week 26, HbA1c was significantly more reduced by 0.35 percentage points in the SGLT2i group than in the non-SGLT2i group (95% CI 0.30–0.41, P < 0.001). Likewise, the proportion of patients achieving HbA1c < 7% was also significantly higher (51.9% vs. 37.6%, P < 0.05) in the SGLT2i group than in the non-SGLT2i group. The risk of adverse events in the SGLT2i group was mostly comparable with those in the non-SGLT2i group except for diseases of the liver, pain, hypertensive diseases, and metabolic disorders, which showed significantly higher odds in the SGLT2i group. Conclusions SGLT2i add-on treatment is an effective and safe therapeutic option for patients with T2DM in the real-world practice setting.This research and the journals Rapid Service Fee was supported by the BK21FOUR Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Education (5120200513755). The study was supported by a grant of the Seoul National University Hospital (0620181130

Macrophage Lamin A/C Regulates Inflammation and the Development of Obesity-Induced Insulin Resistance

Obesity-induced chronic low-grade inflammation, in particular in adipose tissue, contributes to the development of insulin resistance and type 2 diabetes. However, the mechanism by which obesity induces adipose tissue inflammation has not been completely elucidated. Recent studies suggest that alteration of the nuclear lamina is associated with age-associated chronic inflammation in humans and fly. These findings led us to investigate whether the nuclear lamina regulates obesity-mediated chronic inflammation. In this study, we show that lamin A/C mediates inflammation in macrophages. The gene and protein expression levels of lamin A/C are significantly increased in epididymal adipose tissues from obese rodent models and omental fat from obese human subjects compared to their lean controls. Flow cytometry and gene expression analyses reveal that the protein and gene expression levels of lamin A/C are increased in adipose tissue macrophages (ATMs) by obesity. We further show that ectopic overexpression of lamin A/C in macrophages spontaneously activates NF-κB, and increases the gene expression levels of proinflammatory genes, such as Il6, Tnf, Ccl2, and Nos2. Conversely, deletion of lamin A/C in macrophages reduces LPS-induced expression of these proinflammatory genes. Importantly, we find that myeloid cell-specific lamin A/C deficiency ameliorates obesity-induced insulin resistance and adipose tissue inflammation. Thus, our data suggest that lamin A/C mediates the activation of ATM inflammation by regulating NF-κB, thereby contributing to the development of obesity-induced insulin resistance

Effectiveness of statin treatment for recurrent stroke according to stroke subtypes

Understanding the effectiveness of statin treatment is essential for developing tailored stroke prevention strategies. We aimed to evaluate the efficacy of statin treatment in preventing recurrent stroke among patients with various ischemic stroke subtypes. Using data from the Clinical Research Collaboration for Stroke-Korea-National Institute for Health (CRCS-K-NIH) registry, we included patients with acute ischemic stroke admitted between January 2011 and July 2020. To evaluate the differential effects of statin treatment based on the ischemic stroke subtype, we analyzed patients with large artery atherosclerosis (LAA), cardio-embolism (CE), and small vessel occlusion (SVO). The primary outcomes were recurrent ischemic stroke and recurrent stroke events. The hazard ratio for outcomes between statin users and nonusers was compared using a Cox proportional hazards model adjusted for covariates. A total of 46,630 patients who met the inclusion criteria were analyzed. Statins were prescribed to 92%, 93%, and 78% of patients with LAA, SVO, and CE subtypes, respectively. The hazards of recurrent ischemic stroke and recurrent stroke in statin users were reduced to 0.79 (95% confidence interval [CI], 0.63-0.99) and 0.77 (95% CI, 0.62-0.95) in the LAA subtype and 0.63 (95% CI, 0.52-0.76) and 0.63 (95% CI, 0.53-0.75) in CE subtype compared to nonusers. However, the hazards of these outcomes did not significantly decrease in the SVO subtype. The effectiveness of statin treatment in reducing the risk of recurrent stroke in patients with LAA and CE subtypes has been suggested. Nonetheless, no significant effect was observed in the SVO subtype, suggesting a differential effect of statins on different stroke subtypes

Assembly of 500,000 inter-specific catfish expressed sequence tags and large scale gene-associated marker development for whole genome association studies

Twelve cDNA libraries from two species of catfish have been sequenced, resulting in the generation of nearly 500,000 ESTs

Identification and Characterization of Full-Length cDNAs in Channel Catfish (Ictalurus punctatus) and Blue Catfish (Ictalurus furcatus)

Background: Genome annotation projects, gene functional studies, and phylogenetic analyses for a given organism all greatly benefit from access to a validated full-length cDNA resource. While increasingly common in model species, fulllength cDNA resources in aquaculture species are scarce. Methodology and Principal Findings: Through in silico analysis of catfish (Ictalurus spp.) ESTs, a total of 10,037 channel catfish and 7,382 blue catfish cDNA clones were identified as potentially encoding full-length cDNAs. Of this set, a total of 1,169 channel catfish and 933 blue catfish full-length cDNA clones were selected for re-sequencing to provide additional coverage and ensure sequence accuracy. A total of 1,745 unique gene transcripts were identified from the full-length cDNA set, including 1,064 gene transcripts from channel catfish and 681gene transcripts from blue catfish, with 416 transcripts shared between the two closely related species. Full-length sequence characteristics (ortholog conservation, UTR length, Kozak sequence, and conserved motifs) of the channel and blue catfish were examined in detail. Comparison of gene ontology composition between full-length cDNAs and all catfish ESTs revealed that the full-length cDNA set is representative of the gene diversity encoded in the catfish transcriptome. Conclusions: This study describes the first catfish full-length cDNA set constructed from several cDNA libraries. The catfish full-length cDNA sequences, and data gleaned from sequence characteristics analysis, will be a valuable resource fo

How to boost and accelerate new drug development in Korea: business ecosystem perspectives

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Is Curcumin Intake Really Effective for Chronic Inflammatory Metabolic Disease? A Review of Meta-Analyses of Randomized Controlled Trials

This review aimed to examine the effects of curcumin on chronic inflammatory metabolic disease by extensively evaluating meta-analyses of randomized controlled trials (RCTs). We performed a literature search of meta-analyses of RCTs published in English in PubMed®/MEDLINE up to 31 July 2023. We identified 54 meta-analyses of curcumin RCTs for inflammation, antioxidant, glucose control, lipids, anthropometric parameters, blood pressure, endothelial function, depression, and cognitive function. A reduction in C-reactive protein (CRP) levels was observed in seven of ten meta-analyses of RCTs. In five of eight meta-analyses, curcumin intake significantly lowered interleukin 6 (IL-6) levels. In six of nine meta-analyses, curcumin intake significantly lowered tumor necrosis factor α (TNF-α) levels. In five of six meta-analyses, curcumin intake significantly lowered malondialdehyde (MDA) levels. In 14 of 15 meta-analyses, curcumin intake significantly reduced fasting blood glucose (FBG) levels. In 12 of 12 meta-analyses, curcumin intake significantly reduced homeostasis model assessment of insulin resistance (HOMA-IR). In seven of eight meta-analyses, curcumin intake significantly reduced glycated hemoglobin (HbA1c) levels. In eight of ten meta-analyses, curcumin intake significantly reduced insulin levels. In 14 of 19 meta-analyses, curcumin intake significantly reduced total cholesterol (TC) levels. Curcumin intake plays a protective effect on chronic inflammatory metabolic disease, possibly via improved levels of glucose homeostasis, MDA, TC, and inflammation (CRP, IL-6, TNF-α, and adiponectin). The safety and efficacy of curcumin as a natural product support the potential for the prevention and treatment of chronic inflammatory metabolic diseases

Alohomora: Protecting files from ransomware attacks using fine-grained i/o whitelisting

© 2022 ACM.We propose a novel whitelist-based anti-ransomware solution called alohomora. Alohomora is based on our observation that an I/O activity of an application can be an effective abstraction level for managing I/O whitelisting. In alohomora, when a write request is sent to an SSD, its program context value (which is supported by a host CPU register) is passed to the SSD. The SSD checks if the request was pre-approved using the program context value, thus preventing ransomware from modifying files in the SSD. Our experimental results using a prototype alohomora system show that alohomora can achieve a strong security level against sophisticated ransomware attacks without degrading I/O performance.N

Classification and Prediction on Hypertension with Blood Pressure Determinants in a Deep Learning Algorithm

Few studies classified and predicted hypertension using blood pressure (BP)-related determinants in a deep learning algorithm. The objective of this study is to develop a deep learning algorithm for the classification and prediction of hypertension with BP-related factors based on the Korean Genome and Epidemiology Study-Ansan and Ansung baseline survey. We also investigated whether energy intake adjustment is adequate for deep learning algorithms. We constructed a deep neural network (DNN) in which the number of hidden layers and the number of nodes in each hidden layer are experimentally selected, and we trained the DNN to diagnose hypertension using the dataset while varying the energy intake adjustment method in four ways. For comparison, we trained a decision tree in the same way. Experimental results showed that the DNN performs better than the decision tree in all aspects, such as having higher sensitivity, specificity, F1-score, and accuracy. In addition, we found that unlike general machine learning algorithms, including the decision tree, the DNNs perform best when energy intake is not adjusted. The result indicates that energy intake adjustment is not required when using a deep learning algorithm to classify and predict hypertension with BP-related factors