105 research outputs found

    Effect of bis(hydroxymethyl) alkanoate curcuminoid derivative MTH-3 on cell cycle arrest, apoptotic and autophagic pathway in triple-negative breast adenocarcinoma MDA-MB-231 cells: An in vitro study

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    Curcumin has been shown to exert potential antitumor activity in vitro and in vivo involved in multiple signaling pathways. However, the application of curcumin is still limited because of its poor hydrophilicity and low bio-availability. In the present study, we investigated the therapeutic effects of a novel and water soluble bis(hydroxymethyl) alkanoate curcuminoid derivative, MTH-3, on human breast adenocarcinoma MDA-MB-231 cells. This study investigated the effect of MTH-3 on cell viability, cell cycle and induction of autophagy and apoptosis in MDA-MB-231 cells. After 24-h treatment with MTH-3, a concentration-dependent decrease in MDA-MB-231 cell viability was observed, and the IC50 value was 5.37±1.22 μM. MTH-3 significantly triggered G2/M phase arrest and apoptosis in MDA-MB-231 cells. Within a 24-h treatment, MTH-3 decreased the CDK1 activity by decreasing CDK1 and cyclin B1 protein levels. MTH-3-induced apoptosis was further confirmed by morphological assessment and Annexin V/PI staining assay. Induction of apoptosis caused by MTH-3 was accompanied by an apparent increase of DR3, DR5 and FADD and, as well as a marked decrease of Bcl-2 and Bcl-xL protein expression. MTH-3 also decreased the protein levels of Ero1, PDI, PERK and calnexin, as well as increased the expression of IRE1α, CHOP and Bip that consequently led to ER stress and MDA-MB-231 cell apoptosis. In addition, MTH-3-treated cells were involved in the autophagic process and cleavage of LC3B was observed. MTH-3 enhanced the protein levels of LC3B, Atg5, Atg7, Atg12, p62 and Beclin-1 in MDA-MB-231 cells. Finally, DNA microarray was carried out to investigate the level changes of gene expression modulated by MTH-3 in MDA-MB-231 cells. Taken together, our results suggest that MTH-3 might be a novel therapeutic agent for the treatment of triple-negative breast cancer in the near future

    Pyr3 Induces Apoptosis and Inhibits Migration in Human Glioblastoma Cells

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    Background/Aims: Glioblastoma, also known as glioblastoma multiforme (GBM), is a fast-growing type of tumor that is the most aggressive brain malignancy in adults. According to GEO profile analysis, patients with high transient receptor potential canonical 3 (TRPC3) expression have poor survival rates. The aim of this study is to evaluate the effects of Ethyl-1-(4-(2,3,3-trichloroacrylamide)phenyl)-5-(trifluoromethyl)-1H-pyrazole-4-carboxylate (Pyr3), a selective TRPC3 channel blocker, on the proliferation and migration of human glioblastoma cells. Methods: We first analyzed the TRPC3 mRNA expression in Gene Expression Omnibus (GEO) database. Then, TRPC3 protein expression was analyzed by Western blotting in three human GBM cell lines. The survival rate was measured by sulforhodamine B. JC1 staining was used to analyze the mitochondria membrane potential by flow cytometric analysis. Besides, the migration and invasion were evaluated by wound healing and Transwell assays. Annexin V and 7-aminoactinomycin D staining was used to monitor the apoptosis by flow cytometric analysis. The expression of apoptotic-related and migration-related proteins after Pyr3 treatment was detected by Western blotting. In addition, an orthotropic xenograft mouse model was used to assay the effect of Pyr3 in the in vivo study. Results: Basis on the results of bioinformatics study, glioma patients with higher TRPC3 expression had a shorter survival time than those with lower TRPC3 expression. GBM cell proliferation was decreased by Pyr3 treatment. The migration and invasion abilities of glioma cells were also inhibited via focal adhesion kinase and myosin light chain dephosphorization after Pyr3 treatment. Moreover, Pyr3 induced caspase-dependent apoptosis and mitochondria membrane potential imbalance in the GBM cells. In a xenograft animal model, Pyr3 in combination with temozolomide (TMZ) inhibited GBM tumor growth. Conclusion: Pyr3 inhibited GBM tumor growth in vitro and in vivo. Pyr3-TMZ combination therapy could be used to treat glioblastoma in the future

    Deep Complex U-Net with Conformer for Audio-Visual Speech Enhancement

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    Recent studies have increasingly acknowledged the advantages of incorporating visual data into speech enhancement (SE) systems. In this paper, we introduce a novel audio-visual SE approach, termed DCUC-Net (deep complex U-Net with conformer network). The proposed DCUC-Net leverages complex domain features and a stack of conformer blocks. The encoder and decoder of DCUC-Net are designed using a complex U-Net-based framework. The audio and visual signals are processed using a complex encoder and a ResNet-18 model, respectively. These processed signals are then fused using the conformer blocks and transformed into enhanced speech waveforms via a complex decoder. The conformer blocks consist of a combination of self-attention mechanisms and convolutional operations, enabling DCUC-Net to effectively capture both global and local audio-visual dependencies. Our experimental results demonstrate the effectiveness of DCUC-Net, as it outperforms the baseline model from the COG-MHEAR AVSE Challenge 2023 by a notable margin of 0.14 in terms of PESQ. Additionally, the proposed DCUC-Net performs comparably to a state-of-the-art model and outperforms all other compared models on the Taiwan Mandarin speech with video (TMSV) dataset

    Development of Risk Prediction Equations for Incident Chronic Kidney Disease

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    IMPORTANCE ‐ Early identification of individuals at elevated risk of developing chronic kidney disease  could improve clinical care through enhanced surveillance and better management of underlying health  conditions.  OBJECTIVE – To develop assessment tools to identify individuals at increased risk of chronic kidney  disease, defined by reduced estimated glomerular filtration rate (eGFR).  DESIGN, SETTING, AND PARTICIPANTS – Individual level data analysis of 34 multinational cohorts from  the CKD Prognosis Consortium including 5,222,711 individuals from 28 countries. Data were collected  from April, 1970 through January, 2017. A two‐stage analysis was performed, with each study first  analyzed individually and summarized overall using a weighted average. Since clinical variables were  often differentially available by diabetes status, models were developed separately within participants  with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external  cohorts (N=2,253,540). EXPOSURE Demographic and clinical factors.  MAIN OUTCOMES AND MEASURES – Incident eGFR <60 ml/min/1.73 m2.  RESULTS – In 4,441,084 participants without diabetes (mean age, 54 years, 38% female), there were  660,856 incident cases of reduced eGFR during a mean follow‐up of 4.2 years. In 781,627 participants  with diabetes (mean age, 62 years, 13% female), there were 313,646 incident cases during a mean follow‐up of 3.9 years. Equations for the 5‐year risk of reduced eGFR included age, sex, ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, BMI, and albuminuria. For participants  with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction  between the two. The risk equations had a median C statistic for the 5‐year predicted probability of  0.845 (25th – 75th percentile, 0.789‐0.890) in the cohorts without diabetes and 0.801 (25th – 75th percentile, 0.750‐0.819) in the cohorts with diabetes. Calibration analysis showed that 9 out of 13 (69%) study populations had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was  similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 out of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25. CONCLUSIONS AND RELEVANCE – Equations for predicting risk of incident chronic kidney disease developed in over 5 million people from 34 multinational cohorts demonstrated high discrimination and  variable calibration in diverse populations

    Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

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    Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

    Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

    Get PDF
    Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

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    Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD
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