2,350 research outputs found
Role of Nrf2 in bone metabolism
Nuclear factor erythroid 2-related factor 2 (Nrf2) is a transcription factor expressed in many cell types, including osteoblasts, osteocytes, and osteoclasts. Nrf2 has been considered a master regulator of cytoprotective genes against oxidative and chemical insults. The lack of Nrf2 can induce pathologies in multiple organs. Nrf2 deficiency promotes osteoclast differentiation and osteoclast activity, which leads to an increase in bone resorption. The role of Nrf2 in osteoblast differentiation and osteoblast activity is more complex. Nrf2 mediates anabolic effects within an ideal range. Nrf2 deletion suppresses load induced bone formation and delays fracture healing. Overall, Nrf2 plays an important role in the regulation of bone homeostasis in bone cells
Effect of ulinastatin on growth inhibition, apoptosis of breast carcinoma cells is related to a decrease in signal conduction of JNk-2 and NF-κB
<p>Abstract</p> <p>Objective</p> <p>This study aims to investigate the <it>in vitro </it>effects of Ulinastatin (UTI) and Taxotere (TXT) on cell proliferation; cell apoptosis; xenografted tumor growth; and expression of insulin-like growth factor receptor 1 (IGF-1R), platelet-derived growth factor A (PDGFA), nerve growth factor (NGF), c-Jun N-terminal kinase 2 (JNk-2), and NF-κB in a human primary breast cancer cells and breast cancer cell line MDA-MB-231.</p> <p>Methods</p> <p>The cell lines cultured were divided into four groups: 1) control group, 2) UTI group, 3) TXT group, and 4) UTI+TXT group. The method of MTT essay, flow cytometry, and RT-PCR were used to detect cell proliferation, cell apoptosis, and expression of IGF-1R, PDGFA, NGF, NF-κB, JNk-2, respectively. The growth of xenografted tumor in nude mice was used to calculate the anti-tumor rate. Immunohistochemistry staining (SP) was used to detect the expression of IGF-1R, PDGFA, NGF, ki-67, caspase-3, JNk-2, and NF-κB.</p> <p>Results</p> <p>Proliferation of human breast cancer cells and MDA-MB-231 cell lines, and growth rate of xenografted tumor decreased in order of UTI+TXT > TXT > UTI > control, apoptosis increased in the order control < UTI < TXT < UTI+TXT. The gene expression and protein expression of IGF-1R, PDGFA, NGF, NF-κB and JNk-2 in breast cancer cells was inhibited by UTI and TXT.</p> <p>Conclusions</p> <p>UTI 1) inhibits the proliferation of human breast cancer cells and the growth of xenografted tumors, 2) induces cancer cell apoptosis, and 3) enhances the anti-tumor effect of TXT. This mechanism might be related to decreasing signal transduction of JNk-2 and NF-κB, and then expression of IGF-1R, PDGFA, NGF.</p
SelfCF: A Simple Framework for Self-supervised Collaborative Filtering
Collaborative filtering (CF) is widely used to learn an informative latent
representation of a user or item from observed interactions. Existing CF-based
methods commonly adopt negative sampling to discriminate different items. That
is, observed user-item pairs are treated as positive instances; unobserved
pairs are considered as negative instances and are sampled under a defined
distribution for training. Training with negative sampling on large datasets is
computationally expensive. Further, negative items should be carefully sampled
under the defined distribution, in order to avoid selecting an observed
positive item in the training dataset. Unavoidably, some negative items sampled
from the training dataset could be positive in the test set. Recently,
self-supervised learning (SSL) has emerged as a powerful tool to learn a model
without negative samples. In this paper, we propose a self-supervised
collaborative filtering framework (SelfCF), that is specially designed for
recommender scenario with implicit feedback. The main idea of SelfCF is to
augment the output embeddings generated by backbone networks, because it is
infeasible to augment raw input of user/item ids. We propose and study three
output perturbation techniques that can be applied to different types of
backbone networks including both traditional CF models and graph-based models.
By encapsulating two popular recommendation models into the framework, our
experiments on three datasets show that the best performance of our framework
is comparable or better than the supervised counterpart. We also show that
SelfCF can boost up the performance by up to 8.93\% on average, compared with
another self-supervised framework as the baseline. Source codes are available
at: https://github.com/enoche/SelfCF
CD9 may contribute to the survival of human germinal center B cells by facilitating the interaction with follicular dendritic cells
AbstractThe germinal center (GC) is a dynamic microenvironment where antigen (Ag)-activated B cells rapidly expand and differentiate, generating plasma cells (PC) that produce high-affinity antibodies. Precise regulation of survival and proliferation of Ag-activated B cells within the GC is crucial for humoral immune responses. The follicular dendritic cells (FDC) are the specialized stromal cells in the GC that prevent apoptosis of GC-B cells. Recently, we reported that human GC-B cells consist of CD9+ and CD9− populations and that it is the CD9+ cells that are committed to the PC lineage. In this study, we investigated the functional role of CD9 on GC-B cells. Tonsillar tissue section staining revealed that in vivo CD9+ GC-B cells localized in the light zone FDC area. Consistent this, in vitro CD9+ GC-B cells survived better than CD9− GC-B cells in the presence of HK cells, an FDC line, in a cell–cell contact-dependent manner. The frozen tonsillar tissue section binding assay showed that CD9+ GC-B cells bound to the GC area of tonsillar tissues significantly more than the CD9− GC-B cells did and that the binding was significantly inhibited by neutralizing anti-integrin β1 antibody. Furthermore, CD9+ cells bound to soluble VCAM-1 more than CD9− cells did, resulting in activation and stabilization of the active epitope of integrin β1. All together, our data suggest that CD9 on GC-B cells contributes to survival by strengthening their binding to FDC through the VLA4/VCAM-1 axis
Secrecy Throughput Maximization for Full-Duplex Wireless Powered IoT Networks under Fairness Constraints
In this paper, we study the secrecy throughput of a full-duplex wireless
powered communication network (WPCN) for internet of things (IoT). The WPCN
consists of a full-duplex multi-antenna base station (BS) and a number of
sensor nodes. The BS transmits energy all the time, and each node harvests
energy prior to its transmission time slot. The nodes sequentially transmit
their confidential information to the BS, and the other nodes are considered as
potential eavesdroppers. We first formulate the sum secrecy throughput
optimization problem of all the nodes. The optimization variables are the
duration of the time slots and the BS beamforming vectors in different time
slots. The problem is shown to be non-convex. To tackle the problem, we propose
a suboptimal two stage approach, referred to as sum secrecy throughput
maximization (SSTM). In the first stage, the BS focuses its beamforming to
blind the potential eavesdroppers (other nodes) during information transmission
time slots. Then, the optimal beamforming vector in the initial non-information
transmission time slot and the optimal time slots are derived. We then consider
fairness among the nodes and propose max-min fair (MMF) and proportional fair
(PLF) algorithms. The MMF algorithm maximizes the minimum secrecy throughput of
the nodes, while the PLF tries to achieve a good trade-off between the sum
secrecy throughput and fairness among the nodes. Through numerical simulations,
we first demonstrate the superior performance of the SSTM to uniform time
slotting and beamforming in different settings. Then, we show the effectiveness
of the proposed fair algorithms
Triaxially deformed freely precessing neutron stars: continuous electromagnetic and gravitational radiation
The shape of a neutron star (NS) is closely linked to its internal structure and the equation of state of supranuclear matters. A rapidly rotating, asymmetric NS in the Milky Way undergoes free precession, making it a potential source for multimessenger observation. The free precession could manifest in (i) the spectra of continuous gravitational waves (GWs) in the kilohertz (kHz) band for ground-based GW detectors, and (ii) the timing behaviour and pulse-profile characteristics if the NS is monitored as a pulsar with radio and/or X-ray telescopes. We extend previous work and investigate in great detail the free precession of a triaxially deformed NS with analytical and numerical approaches. In particular, its associated continuous GWs and pulse signals are derived. Explicit examples are illustrated for the continuous GWs, as well as timing residuals in both time and frequency domains. These results are ready to be used for future multimessenger observation of triaxially deformed freely precessing NSs, in order to extract scientific implication as much as possible
Triaxially deformed freely precessing neutron stars: continuous electromagnetic and gravitational radiation
The shape of a neutron star (NS) is closely linked to its internal structure and the equation of state of supranuclear matters. A rapidly rotating, asymmetric NS in the Milky Way undergoes free precession, making it a potential source for multimessenger observation. The free precession could manifest in (i) the spectra of continuous gravitational waves (GWs) in the kilohertz (kHz) band for ground-based GW detectors, and (ii) the timing behaviour and pulse-profile characteristics if the NS is monitored as a pulsar with radio and/or X-ray telescopes. We extend previous work and investigate in great detail the free precession of a triaxially deformed NS with analytical and numerical approaches. In particular, its associated continuous GWs and pulse signals are derived. Explicit examples are illustrated for the continuous GWs, as well as timing residuals in both time and frequency domains. These results are ready to be used for future multimessenger observation of triaxially deformed freely precessing NSs, in order to extract scientific implication as much as possible
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