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| 2. |
- de las Fuentes, Lisa, et al.
(författare)
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Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci
- 2021
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Ingår i: Molecular Psychiatry. - : Springer Nature. - 1359-4184 .- 1476-5578. ; 26:6, s. 2111-2125
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Tidskriftsartikel (refereegranskat)abstract
- Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, “Some College” (yes/no) and “Graduated College” (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10-8). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
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| 3. |
- Kristan, Matej, et al.
(författare)
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The first visual object tracking segmentation VOTS2023 challenge results
- 2023
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Ingår i: 2023 IEEE/CVF International conference on computer vision workshops (ICCVW). - : Institute of Electrical and Electronics Engineers Inc.. - 9798350307443 - 9798350307450 ; , s. 1788-1810
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking Segmentation VOTS2023 challenge is the eleventh annual tracker benchmarking activity of the VOT initiative. This challenge is the first to merge short-term and long-term as well as single-target and multiple-target tracking with segmentation masks as the only target location specification. A new dataset was created; the ground truth has been withheld to prevent overfitting. New performance measures and evaluation protocols have been created along with a new toolkit and an evaluation server. Results of the presented 47 trackers indicate that modern tracking frameworks are well-suited to deal with convergence of short-term and long-term tracking and that multiple and single target tracking can be considered a single problem. A leaderboard, with participating trackers details, the source code, the datasets, and the evaluation kit are publicly available at the challenge website1
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| 4. |
- Liang, Pu-Lin, et al.
(författare)
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Three polymethoxyflavones from the peel of Citrus reticulata "Chachi" inhibits oxidized low-density lipoprotein-induced macrophage-derived foam cell formation
- 2022
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Ingår i: Frontiers in Cardiovascular Medicine. - : Frontiers Media S.A.. - 2297-055X. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Foam cell formation is the hallmark of the development and progression of atherosclerosis. The aim of this study was to investigate the regulatory effects of three polymethoxyflavones (PMFs), namely, tangeretin (TAN), 5,6,7,3 ',4 ',5 '-hexamethoxyflavone (HxMF), and 3,5,6,7,8,3 ',4 '-heptamethoxyflavone (HpMF) on macrophage-derived foam cell formation and to further explore the molecular mechanisms. The RAW264.7 macrophage-derived foam cell model was successfully induced by oxidized low-density lipoprotein (ox-LDL) (80 mu g/ml). It showed that TAN, HxMF, and HpMF alleviated ox-LDL-induced NO release while also inhibiting the expression of IL-1 beta, IL-6, and TNF-alpha in RAW264.7 cells. Uptake of excess ox-LDL was inhibited by TAN, HxMF, and HpMF, resulting in the reduction of its foam cell formation. Moreover, TAN, HxMF, and HpMF promoted HDL-mediated cholesterol efflux. Western blot experiment showed that TAN, HxMF, and HpMF inhibited the expression of scavenger receptor class A type I (SRA1) and cluster of differentiation 36 (CD36), while upregulating peroxisome proliferator-activated receptor gamma (PPAR gamma), liver X receptor alpha (LXR alpha), phospholipid ATP-binding cassette transporter G1 (ABCG1), and scavenger receptor class B type I (SRB1) expression. Together, our findings suggested that PMFs inhibited foam cell formation might inhibit lipid uptake via downregulating SRA1/CD36 expression and promote cholesterol efflux from foam cells via upregulating PPAR gamma/LXR alpha/ABCG1/SRB1 expression. This antiatherosclerotic activity is expected to provide new insights into the development of healthcare uses for PMFs.
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| 5. |
- He, Li, et al.
(författare)
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PRDM16 regulates a temporal transcriptional program to promote progression of cortical neural progenitors
- 2021
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Ingår i: Development. - : The Company of Biologists. - 0950-1991 .- 1477-9129. ; 148:6
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Tidskriftsartikel (refereegranskat)abstract
- Radial glia (RG) in the neocortex sequentially generate distinct subtypes of projection neurons, accounting for the diversity and complex assembly of cortical neural circuits. Mechanismsthat drive the rapid and precise temporal progression of RG are beginning to be elucidated. Here, we reveal that the RG-specific transcriptional regulator PRDM16 promotes the transition of early to late phase of neurogenesis in the mouse neocortex. Loss of Prdm16 delays the timely progression of RG, leading to defective cortical laminar organization. Our genomic analyses demonstrate that PRDM16 regulates a subset of genes that are dynamically expressed between early and late neurogenesis. We show that PRDM16 suppresses target gene expression through limiting chromatin accessibility of permissive enhancers. We further confirm that crucial target genes regulated by PRDM16 are neuronal specification genes, cell cycle regulators and molecules required for neuronal migration. These findings provide evidence to support the finding that neural progenitors temporally shift the gene expression program to achieve neural cell diversity.
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| 6. |
- Surendran, Praveen, et al.
(författare)
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Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals
- 2020
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 52:12, s. 1314-1332
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Tidskriftsartikel (refereegranskat)abstract
- Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to similar to 1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency <= 0.01) variant BP associations (P < 5 x 10(-8)), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were similar to 8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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| 7. |
- Yu, Haiyang, et al.
(författare)
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Association between Parkinson’s Disease and Diabetes Mellitus : From Epidemiology, Pathophysiology and Prevention to Treatment
- 2022
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Ingår i: Aging and Disease. - 2152-5250. ; 13:6, s. 1591-1605
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Tidskriftsartikel (refereegranskat)abstract
- Diabetes mellitus (DM) and Parkinson’s disease (PD) are both age-related diseases of global concern being among the most common chronic metabolic and neurodegenerative diseases, respectively. While both diseases can be genetically inherited, environmental factors play a vital role in their pathogenesis. Moreover, DM and PD have common underlying molecular mechanisms, such as misfolded protein aggregation, mitochondrial dysfunction, oxidative stress, chronic inflammation, and microbial dysbiosis. Recently, epidemiological and experimental studies have reported that DM affects the incidence and progression of PD. Moreover, certain antidiabetic drugs have been proven to decrease the risk of PD and delay its progression. In this review, we elucidate the epidemiological and pathophysiological association between DM and PD and summarize the antidiabetic drugs used in animal models and clinical trials of PD, which may provide reference for the clinical translation of antidiabetic drugs in PD treatment.
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| 8. |
- Yu, Wenjin, et al.
(författare)
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Deep Learning-Based Classification of Cancer Cell in Leptomeningeal Metastasis on Cytomorphologic Features of Cerebrospinal Fluid
- 2022
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Ingår i: Frontiers in Oncology. - : Frontiers Media SA. - 2234-943X. ; 12, s. 1-11
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Tidskriftsartikel (refereegranskat)abstract
- Background: It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope.Objective: This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage.Method: The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly.Results: With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists.Conclusion: A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer’s primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.
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| 9. |
- Bravo, L, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 10. |
- Tabiri, S, et al.
(författare)
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- 2021
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swepub:Mat__t
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