45 research outputs found
Aging of human bone marrow – functional and epigenetic changes in senescent mesenchymal stromal cells
Aging is a complex process that is associated with changes in many parts of the body
over the lifespan of an individual. In this work, various aspects of aging in the human
bone marrow were investigated.
As the regenerative power of a tissue is linked to the potential of its stem cells to
replace the accumulated damages, the aging process in somatic stem cells was
studied focusing on the influence of the niche in regulating stem cell aging. The
hematopoietic stem cells (HSC) together with elements that constitute the bone
marrow niche were investigated as a model for somatic stem cell aging as HSCs are
accessible in healthy human individuals. The subjects ranged from 20 to 60 years
with a median age of 33.2 years.
From each bone marrow sample, the CD34+ population as HSCs and four other cell
subpopulations, lymphocytes and precursors (LYM), monocytes/macrophages
precursors (MON), granulocytic (GRA), and erythroid precursors (ERP) were isolated
by flow cytometry. The mesenchymal stromal cells (MSC) were isolated by in vitro
culture. We found that the relative proportions, cell size as well as cell granularity of
the major bone marrow constituents did not correlate with the biological age of the
donors. However, further downstream analysis indicated that age-associated
changes were prominent on protein level in HSCs as well as in other cell types of the
niche such as MSCs.
The interactions between the HSCs and the niche were studied in vitro using a coculture
system of CD34+ cells and mesenchymal stromal cells (MSC). As previous
studies indicated that the supportive function of MSCs as well as their differentiation
potentials towards adipocytes and osteocytes change significantly with age, we have
examined the supportive ability of the undifferentiated MSCs versus adipogenically
differentiated MSCs (ADI-MSCs) and osteogenically differentiated MSCs (OST-MSCs)
for HSCs. We showed that MSCs, ADI-MSCs and OST-MSCs were able to support
the proliferation of HSCs and maintain their primitive immunephenotype. Compared
to undifferentiated MSCs and OST-MSCs, the co-culture with ADI-MSCs increased
the proliferation of HSCs much stronger while still maintaining the HSCs at a high
expression level of CD34.
As the impact of the MSCs on HSCs might be caused by epigenetic changes, the
aging-associated alterations in the marrow niche were studied at the chromatin level.
To this end, changes in chromatin accessibility were studied in MSCs by ATAC-seq.
After establishing the protocol for performing ATAC-seq using primary MSCs, we
studied the MSC samples derived from 16 healthy human subjects of different ages
between 21 and 59 years. A set of 122,884 ATAC-seq peaks was identified. We have
demonstrated that donor age is associated with alterations in open chromatin profiles.
Moreover, at a false discovery rate of 5%, we could identify 4,579 differential
chromatin accessible sites upon aging. A functional analysis of these sites showed
enrichment of cell development and differentiation processes. Additionally, genes of
the hippo signaling pathway, TGF-beta signaling pathway, cancer pathways and cell
adhesion pathways were also found to be enriched. A motif enrichment analysis
suggested that TATA box motifs and binding sites for transcription factors TFAP2C,
KLF16, HIC1.p2, WT1 and MTF.p2 were enriched in promoter regions of differential
chromatin accessible sites upon aging.
In conclusion, this study showed that the interplay with the stem cell niche controls
HSC functions. The differentiation of MSCs affects the proliferation and stemness of
HSCs in vitro. Furthermore, we have demonstrated that aging is associated with
chromatin accessibility alterations in MSCs, which provides a foundation for further
in-depth mechanistic analyses
A BAC-NOMA Design for 6Â G umMTC With Hybrid SIC: Convex Optimization or Learning-Based?
This paper presents a new backscattering communication (BackCom)-assisted non-orthogonal multiple access (BAC-NOMA) transmission scheme for device-to-device (D2D) communications. This scheme facilitates energy and spectrum cooperation between BackCom devices and cellular downlink users in 6Â G ultra-massive machine -type communications (umMTC) scenarios. Given its quasi-uplink nature, the hybrid successive interference cancellation (SIC) is applied to further improve performance. The data rate of BackCom devices with high quality of service (QoS) requirements is maximized by jointly optimizing backscatter coefficients and the beamforming vector. The use of hybrid SIC and BackCom yields two non-concave sub-problems involving transcendental functions. To address this problem, this paper designs and compares convex optimization-based and unsupervised deep learning-based algorithms. In the convex optimization, the closed-form backscatter coefficients of the first sub-problem are obtained, and then semi-definite relaxation (SDR) is utilized to design the beamforming vector. On the other hand, the second sub-problem is approximated by using a combination of sequential convex approximation (SCA) and SDR. For unsupervised deep learning-based optimization, a loss function is properly designed to satisfy constraints. Computer simulations show the following instructive results: i) the superiority of the hybrid SIC strategy; ii) the distinct sensitivities and efficacies of these two algorithms in response to varying parameters; iii) the superior robustness of the unsupervised deep learning-based optimization
A Contrastive Cross-Channel Data Augmentation Framework for Aspect-based Sentiment Analysis
Aspect-Based Sentiment Analysis is a fine-grained sentiment analysis task,
which focuses on detecting the sentiment polarity towards the aspect in a
sentence. However, it is always sensitive to the multi-aspect challenge, where
features of multiple aspects in a sentence will affect each other. To mitigate
this issue, we design a novel training framework, called Contrastive
Cross-Channel Data Augmentation (C3DA). A source sentence will be fed a
domain-specific generator to obtain some synthetic sentences and is
concatenated with these generated sentences to conduct supervised training and
proposed contrastive training. To be specific, considering the limited ABSA
labeled data, we also introduce some parameter-efficient approaches to complete
sentences generation. This novel generation method consists of an Aspect
Augmentation Channel (AAC) to generate aspect-specific sentences and a Polarity
Augmentation (PAC) to generate polarity-inverted sentences. According to our
extensive experiments, our C3DA framework can outperform those baselines
without any augmentations by about 1\% on accuracy and Macro-F1
Local application of silver nitrate as an adjuvant treatment before deep lamellar keratoplasty for fungal keratitis poorly responsive to medical treatment
ObjectiveThe purpose of this study is to evaluate the efficacy and safety of the local application of silver nitrate (LASN) as an adjuvant treatment before deep lamellar keratoplasty (DLKP) for fungal keratitis responding poorly to medical treatment.MethodsA total of 12 patients (12 eyes) with fungal keratitis responding poorly to medical treatment (for at least 2 weeks) were included. LASN was performed using 2% silver nitrate, the ulcer was cleaned and debrided, and then, the silver nitrate cotton stick was applied to the surface of the ulcer for a few seconds. The effect of LASN was recorded. The number of hyphae before and after treatment was determined by confocal microscope. After the condition of the ulcer improved, DLKP was performed. Fungal recurrence, best-corrected visual acuity (BCVA), loose sutures, and endothelial cell density (ECD) were recorded in detail.ResultsClinical resolution of corneal infiltration and edema was observed, and the ulcer boundary became clear in all 12 patients after 7–9 days of LASN. Confocal microscopy showed that the number of hyphae was significantly reduced. Ocular pain peaked on days 1 and 2 after treatment, and 9 patients (75%, day 1) and 1 patient (8.3%, day 2) required oral pain medication. During the follow-up period after DLKP, no fungal recurrence and loose sutures were observed. After the operation, the BCVA of all patients improved. The mean corneal ECD was 2,166.83 ± 119.75 cells/mm2.ConclusionThe LASN was safe and effective and can be well tolerated by patients. Eye pain can be relieved quickly. LASN as an adjuvant treatment before DLKP might be a promising therapeutic strategy
Joint Optimization of Beamforming, Phase-Shifting and Power Allocation in a Multi-cluster IRS-NOMA Network
The combination of non-orthogonal multiple access (NOMA) and intelligent
reflecting surface (IRS) is an efficient solution to significantly enhance the
energy efficiency of the wireless communication system. In this paper, we focus
on a downlink multi-cluster NOMA network, where each cluster is supported by
one IRS. We aim to minimize the transmit power by jointly optimizing the
beamforming, the power allocation and the phase shift of each IRS. The
formulated problem is non-convex and challenging to solve due to the coupled
variables, i.e., the beamforming vector, the power allocation coefficient and
the phase shift matrix. To address this non-convex problem, we propose an
alternating optimization based algorithm. Specifically, we divide the primal
problem into the two subproblems for beamforming optimization and phase
shifting feasiblity, where the two subproblems are solved iteratively.
Moreover, to guarantee the feasibility of the beamforming optimization problem,
an iterative algorithm is proposed to search the feasible initial points. To
reduce the complexity, we also propose a simplified algorithm based on partial
exhaustive search for this system model. Simulation results demonstrate that
the proposed alternating algorithm can yield a better performance gain than the
partial exhaustive search algorithm, OMA-IRS, and NOMA with random IRS phase
shift
Deep Reinforcement Learning Based Optimization for IRS Based UAV-NOMA Downlink Networks
This paper investigates the application of deep deterministic policy gradient
(DDPG) to intelligent reflecting surface (IRS) based unmanned aerial vehicles
(UAV) assisted non-orthogonal multiple access (NOMA) downlink networks. The
deployment of the UAV equipped with an IRS is important, as the UAV increases
the flexibility of the IRS significantly, especially for the case of users who
have no line of sight (LoS) path to the base station (BS). Therefore, the aim
of this letter is to maximize the sum rate by jointly optimizing the power
allocation of the BS, the phase shifting of the IRS and the horizontal position
of the UAV. Because the formulated problem is not convex, the DDPG algorithm is
utilized to solve it. The computer simulation results are provided to show the
superior performance of the proposed DDPG based algorithm