111 research outputs found
A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification
Unsupervised cross-domain person re-identification (Re-ID) faces two key
issues. One is the data distribution discrepancy between source and target
domains, and the other is the lack of labelling information in target domain.
They are addressed in this paper from the perspective of representation
learning. For the first issue, we highlight the presence of camera-level
sub-domains as a unique characteristic of person Re-ID, and develop
camera-aware domain adaptation to reduce the discrepancy not only between
source and target domains but also across these sub-domains. For the second
issue, we exploit the temporal continuity in each camera of target domain to
create discriminative information. This is implemented by dynamically
generating online triplets within each batch, in order to maximally take
advantage of the steadily improved feature representation in training process.
Together, the above two methods give rise to a novel unsupervised deep domain
adaptation framework for person Re-ID. Experiments and ablation studies on
benchmark datasets demonstrate its superiority and interesting properties.Comment: Accepted by ICCV201
OPML: A One-Pass Closed-Form Solution for Online Metric Learning
To achieve a low computational cost when performing online metric learning
for large-scale data, we present a one-pass closed-form solution namely OPML in
this paper. Typically, the proposed OPML first adopts a one-pass triplet
construction strategy, which aims to use only a very small number of triplets
to approximate the representation ability of whole original triplets obtained
by batch-manner methods. Then, OPML employs a closed-form solution to update
the metric for new coming samples, which leads to a low space (i.e., )
and time (i.e., ) complexity, where is the feature dimensionality.
In addition, an extension of OPML (namely COPML) is further proposed to enhance
the robustness when in real case the first several samples come from the same
class (i.e., cold start problem). In the experiments, we have systematically
evaluated our methods (OPML and COPML) on three typical tasks, including UCI
data classification, face verification, and abnormal event detection in videos,
which aims to fully evaluate the proposed methods on different sample number,
different feature dimensionalities and different feature extraction ways (i.e.,
hand-crafted and deeply-learned). The results show that OPML and COPML can
obtain the promising performance with a very low computational cost. Also, the
effectiveness of COPML under the cold start setting is experimentally verified.Comment: 12 page
Role of Nrf2 in HLC
Generation of hepatocytes from human adipose-derived mesenchymal stem cells (hADSCs) could be a promising alternative source of human hepatocytes. However, mechanisms to differentiate hepatocytes from hADSCs are not fully elucidated. We have previously demonstrated that our three-step differentiation protocol with glycogen synthase kinase (GSK) 3 inhibitor was effective to improve hepatocyte functions. In this study, we investigated the activation of the nuclear factor erythroid-2 related factor 2 (Nrf2) on hADSCs undergoing differentiation to HLC (hepatocyte-like cells). Our three-step differentiation protocol was applied for 21 days (Step 1 : day 1-6, Step2 : day 6-11, Step3 : day 11-21). Our results show that significant nuclear translocation of Nrf2 occurred from day 11 until the end of HLC differentiation. Nuclear translocation of Nrf2 and CYP3A4 activity in the GSK3 inhibitor-treated group was obviously higher than that in Activin A-treated groups at day 11. The maturation of HLCs was delayed in Nrf2-siRNA group compared to control group. Furthermore, CYP3A4 activity in Nrf2-siRNA group was decreased at the almost same level in Activin A-treated group. Nrf2 translocation might enhance the function of HLC and be a target for developing highly functional HLC
Nrf2 signaling in sorafenib-resistant HCC
Background and aim
As a multiple tyrosine kinase inhibitor, sorafenib is widely used to treat hepatocellular carcinoma (HCC), but patients frequently face resistance problems. Because the mechanism controlling sorafenib-resistance is not well understood, this study focused on the connection between tumor characteristics and the Nrf2 signaling pathway in a sorafenib-resistant HCC cell line.
Methods
A sorafenib-resistant HCC cell line (Huh7) was developed by increasing the dose of sorafenib in the culture medium until the target concentration was reached. Cell morphology, migration/invasion rates, and expression of stemness-related and ATP-binding cassette (ABC) transporter genes were compared between sorafenib-resistant Huh7 cells and parental Huh7 cells. Next, a small interfering RNA was used to knock down Nrf2 expression in sorafenib-resistant Huh7 cells, after which cell viability, stemness, migration, and ABC transporter gene expression were examined again.
Results
Proliferation, migration, and invasion rates of sorafenib-resistant Huh7 cells were significantly increased relative to the parental cells with or without sorafenib added to the medium. The expression levels of stemness markers and ABC transporter genes were up-regulated in sorafenib-resistant cells. After Nrf2 was knocked down in sorafenib-resistant cells, cell migration and invasion rates were reduced, and expression levels of stemness markers and ABC transporter genes were reduced.
Conclusion
Nrf2 signaling promotes cancer stemness, migration, and expression of ABC transporter genes in sorafenib-resistant HCC cells
BAFF/NFκB経路はソラフェニブ耐性肝癌と癌関連線維芽細胞の相互作用に重要である
The tumor microenvironment affects malignancy in hepatocellular carcinoma (HCC) cells, and cancer-associated fibroblasts (CAFs) play an important role in the microenvironment. As recent studies indicated a difference between CAFs isolated from chemoresistant and non-resistant cancer tissues, therefore we investigated the intracellular mechanism in resistant HCC co-cultured CAFs and interactions between these CAFs with cancer cells. We established a sorafenib-resistant (SR) Huh7 (human HCC) cell line, and characterized it with cytokine assays, then developed CAFs by co-culturing human hepatic stellate cells with resistant or parental Huh7 cells. The 2 types of CAFs were co-cultured with parental Huh7 cells, thereafter the cell viability of these Huh7 cells was checked under sorafenib treatment. The SR Huh7 (Huh7SR) cells expressed increased B-cell activating factor (BAFF), which promoted high expression of CAF-specific markers in Huh7SR-co-cultured CAFs, showed activated BAFF, BAFF-R, and downstream of the NFκB-Nrf2 pathway, and aggravated invasion, migration, and drug resistance in co-cultured Huh7 cells. When we knocked down BAFF expression in Huh7SR cells, the previously increased malignancy and BAFF/NFκB axis in Huh7SR-co-cultured CAFs reversed, and enhanced chemoresistance in co-cultured Huh7 cells returned as well. In conclusion, the BAFF/NFκB pathway was activated in CAFs co-cultured with cell-culture medium from resistant Huh7, which promoted chemoresistance, and increased the malignancy in co-cultured non-resistant Huh7 cells. This suggests that the BAFF/NFκB axis in CAFs might be a potential therapeutic target in chemoresistance of HCC
Comparing the effectiveness of long-term use of daily and weekly glucagon-like peptide-1 receptor agonists treatments in patients with nonalcoholic fatty liver disease and type 2 diabetes mellitus: a network meta-analysis
ObjectiveIn the present network meta-analysis (NMA), we aimed to compare the effectiveness of daily and weekly treatment with glucagon-like peptide-1 receptor agonists for patients with nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM).MethodWe used Stata 17.0 for the NMA. Eligible Randomized controlled trials (RCTs) were searched in PubMed, Cochrane, and Embase databases until December 2022. Two researchers independently screened the available studies. The Cochrane Risk of Bias tool was used to assess the risk of bias in the included studies. We used GRADEprofiler (version3.6) to analyze the evidence certainty. Primary outcomes such as liver fat content (LFC), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels, as well as secondary outcomes such as γ-glutamyltransferase (γGGT) and body weight, were evaluated. Then, each intervention was ranked by the surface under the cumulative ranking curve (SUCRA). As a supplement, we drew forest plots of subgroup using RevMan (version 5.4).ResultsFourteen RCTs involving 1666 participants were included in the present study. The NMA results showed that exenatide (bid) was the best treatment for improving LFC compared with other agents, liraglutide, dulaglutide, semaglutide (qw) and placebo), and the SUCRA values were 66.8%. Among five interventions (except exenatide (bid) and semaglutide (qw)) evaluated for AST outcome, and six interventions (except exenatide (bid)) evaluated for ALT outcome, semaglutide (qd) was the most effective drug (SUCRA (AST) = 100%, SUCRA (ALT) = 95.6%). The result of LFC in daily group was MD = -3.66, 95% CI [-5.56, -1.76] and in weekly GLP-1RAs group, it was MD = -3.51, 95% CI [-4, -3.02]. As to AST and ALT, the results in daily group versus weekly group were AST: MD = -7.45, 95% CI [-14.57, -0.32] versus MD= -0.58, 95% CI [-3.18, 2.01] and ALT: MD = -11.12, 95% CI [-24.18, 1.95] versus MD = -5.62, 95% CI [-15.25, 4]. The quality of evidence was assessed as moderate or low.ConclusionThe daily GLP-1RAs may be more effective in primary outcomes. And the daily semaglutide may be the most effective treatment for NAFLD and T2DM among the six interventions
Microbial diversity and community composition of fecal microbiota in dual-purpose and egg type ducks
IntroductionDucks are important agricultural animals, which can be divided into egg and dual-purpose type ducks according to economic use. The gut microbiota of ducks plays an important role in their metabolism, immune regulation, and health maintenance.MethodsHere, we use 16S rDNA V4 hypervariable amplicon sequencing to investigate the compositions and community structures of fecal microbiota between egg (five breeds, 96 individuals) and dual-purpose type ducks (four breeds, 73 individuals) that were reared under the same conditions.ResultsThe alpha diversity of fecal microflora in egg type ducks was significantly higher than that in dual-type ducks. In contrast, there is no significant difference in the fecal microbial community richness between the two groups. MetaStat analysis showed that the abundance of Peptostreptococcaceae, Streptococcaceae, Lactobacillus, Romboutsia, and Campylobacter were significantly different between the two groups. The biomarkers associated with the egg and dual-purpose type ducks were identified using LEfSe analysis and IndVal index. Function prediction of the gut microbiota indicated significant differences between the two groups. The functions of environmental information processing, carbohydrate metabolism, lipid metabolism, xenobiotic biodegradation and metabolism, and metabolism of terpenoids and polyketides were more abundant in egg type ducks. Conversely, the genetic information processing, nucleotide metabolism, biosynthesis of amino acids and secondary metabolites, glycan biosynthesis and metabolism, fatty acid elongation, and insulin resistance were significantly enriched in dual-purpose type ducks.DiscussionThis study explored the structure and diversity of the gut microbiota of ducks from different economic-use groups, and provides a reference for improving duck performance by using related probiotics in production
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