Reweighted lp Constraint LMS-Based Adaptive Sparse Channel Estimation for Cooperative Communication System

This paper studies the issue of sparsity adaptive channel reconstruction in time-varying cooperative communication networks through the amplify-and-forward transmission scheme. A new sparsity adaptive system identification method is proposed, namely reweighted norm ( < < ) penalized least mean square（LMS）algorithm. The main idea of the algorithm is to add a norm penalty of sparsity into the cost function of the LMS algorithm. By doing so, the weight factor becomes a balance parameter of the associated norm adaptive sparse system identification. Subsequently, the steady state of the coefficient misalignment vector is derived theoretically, with a performance upper bounds provided which serve as a sufficient condition for the LMS channel estimation of the precise reweighted norm. With the upper bounds, we prove that the ( < < ) norm sparsity inducing cost function is superior to the reweighted norm. An optimal selection of for the norm problem is studied to recover various sparse channel vectors. Several experiments verify that the simulation results agree well with the theoretical analysis, and thus demonstrate that the proposed algorithm has a better convergence speed and better steady state behavior than other LMS algorithms

The conformation change of Bcl-2 is involved in arsenic trioxide-induced apoptosis and inhibition of proliferation in SGC7901 human gastric cancer cells

<p>Abstract</p> <p>Background</p> <p>Arsenic trioxide has been established as a first-line agent for treating acute promyelocytic leukemia. Experimental data suggest that arsenic trioxide also can have a potential use as chemotherapeutic agent for other malignancies. The precise mechanisms of action of arsenic trioxide have though not been elucidated. As the role of Bcl-2 in arsenic trioxide-mediated cell apoptosis and conformation change of Bcl-2 in response to arsenic trioxide treatment has not been studied. The aim of the present study was to determine whether conformation change of Bcl-2 is involved in the action of arsenic trioxide.</p> <p>Methods</p> <p>Human gastric cancer SGC7901 cells were exposed to different concentrations of arsenic trioxide. Proliferation was measured by using the Kit-8 cell counting assay. Analysis of nuclear morphology was observed by DAPI staining. The apoptosis rates of cells treated with arsenic trioxide were analyzed by flow cytometry using Annexin V-FITC staining. The conformation change of Bcl-2 and Bax activation were detected by immunostaining and Western blot analysis. Total expression of Bcl-2 and Bax were examined by Western blot analysis.</p> <p>Results</p> <p>Arsenic trioxide inhibited the growth of human gastric cancer SGC7901 cells and induced apoptosis. There were two Bcl-2 phenotypes coexisting in SGC7901 cells and the Bcl-2 cytoprotective phenotype could change into a cytodestructive phenotype following conformational change of Bcl-2, triggered by arsenic trioxide exposure. Bax activation might also be involved in arsenic trioxide-induced Bcl-2 conformational change. Arsenic trioxide did not change levels of total Bcl-2 expression, but up-regulated total Bax expression for the treatment time ranging from 3 to 24 hours.</p> <p>Conclusion</p> <p>Arsenic trioxide induces apoptosis through induction of Bcl-2 conformational change, Bax activation and up-regulation of total Bax expression rather than affecting total Bcl-2 expression in human gastric cancer SGC7901 cells. The conformational change of Bcl-2 may be a novel described mechanism of arsenic trioxide-induced apoptosis in cancer cells.</p

Feature Allocation for Semantic Communication with Space-Time Importance Awareness

In the realm of semantic communication, the significance of encoded features can vary, while wireless channels are known to exhibit fluctuations across multiple subchannels in different domains. Consequently, critical features may traverse subchannels with poor states, resulting in performance degradation. To tackle this challenge, we introduce a framework called Feature Allocation for Semantic Transmission (FAST), which offers adaptability to channel fluctuations across both spatial and temporal domains. In particular, an importance evaluator is first developed to assess the importance of various features. In the temporal domain, channel prediction is utilized to estimate future channel state information (CSI). Subsequently, feature allocation is implemented by assigning suitable transmission time slots to different features. Furthermore, we extend FAST to the space-time domain, considering two common scenarios: precoding-free and precoding-based multiple-input multiple-output (MIMO) systems. An important attribute of FAST is its versatility, requiring no intricate fine-tuning. Simulation results demonstrate that this approach significantly enhances the performance of semantic communication systems in image transmission. It retains its superiority even when faced with substantial changes in system configuration

GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor Scenes

This paper tackles the challenges of self-supervised monocular depth estimation in indoor scenes caused by large rotation between frames and low texture. We ease the learning process by obtaining coarse camera poses from monocular sequences through multi-view geometry to deal with the former. However, we found that limited by the scale ambiguity across different scenes in the training dataset, a na\"ive introduction of geometric coarse poses cannot play a positive role in performance improvement, which is counter-intuitive. To address this problem, we propose to refine those poses during training through rotation and translation/scale optimization. To soften the effect of the low texture, we combine the global reasoning of vision transformers with an overfitting-aware, iterative self-distillation mechanism, providing more accurate depth guidance coming from the network itself. Experiments on NYUv2, ScanNet, 7scenes, and KITTI datasets support the effectiveness of each component in our framework, which sets a new state-of-the-art for indoor self-supervised monocular depth estimation, as well as outstanding generalization ability. Code and models are available at https://github.com/zxcqlf/GasMonoComment: ICCV 2023. Code: https://github.com/zxcqlf/GasMon

Generation of Monoclonal Antibodies against Highly Conserved Antigens

Background: Therapeutic antibody development is one of the fastest growing areas of the pharmaceutical industry. Generating high-quality monoclonal antibodies against a given therapeutic target is very crucial for the success of the drug development. However, due to immune tolerance, some proteins that are highly conserved between mice and humans are not very immunogenic in mice, making it difficult to generate antibodies using a conventional approach. Methodology/Principal Findings: In this report, the impaired immune tolerance of NZB/W mice was exploited to generate monoclonal antibodies against highly conserved or self-antigens. Using two highly conserved human antigens (MIF and HMGB1) and one mouse self-antigen (TNF-alpha) as examples, we demonstrate here that multiple clones of high affinity, highly specific antibodies with desired biological activities can be generated, using the NZB/W mouse as the immunization host and a T cell-specific tag fused to a recombinant antigen to stimulate the immune system. Conclusions/Significance: We developed an efficient and universal method for generating surrogate or therapeuti

Percutaneous Ultrasound-Guided Laser Ablation with Contrast-Enhanced Ultrasonography for Hyperfunctioning Parathyroid Adenoma: A Preliminary Case Series

The study was to evaluate the safety and effectiveness of ultrasound-guided percutaneous laser ablation (pLA) as a nonsurgical treatment for primary parathyroid adenoma. Surgery was contraindicated in, or refused by, the included patients. No lesion enhancement on contrast-enhanced ultrasound immediately after pLA was considered “complete ablation.” Nodule size, serum calcium, and parathyroid hormone level were compared before and after pLA. Complete ablation was achieved in all 21 patients with 1 (n=20) or 2 (n=1) sessions. Nodule volume decreased from 0.93±0.58 mL at baseline to 0.53±0.38 and 0.48±0.34 mL at 6 and 12 months after pLA (P<0.05). At 1 day, 6 months, and 12 months after pLA, serum PTH decreased from 15.23±3.00 pmol/L at baseline to 7.41±2.79, 6.95±1.78, and 6.90±1.46 pmol/L, serum calcium decreased from 3.77±0.77 mmol/L at baseline to 2.50±0.72, 2.41±0.37, and 2.28±0.26 mmol/L, respectively (P<0.05). At 12 months, treatment success (normalization of PTH and serum calcium) was achieved in 81%. No serious complications were observed. Ultrasound-guided pLA with contrast-enhanced ultrasound is a viable alternative to surgery for primary parathyroid adenoma

Optimization of multi-temporal generation scheduling in power system under elevated renewable penetrations: A review

The traditional power generation mix and the geographical distribution of units have faced structural reform with the increasing renewables. The existing scheduling schemes confront the optimization challenges of multi-source collaborative and multi-temporal coordination. This paper reviews the optimization of generation scheduling in power systems with renewables integration in different time scales, which are medium- and long-term, short-term and real-time, respectively. First, the scheduling model and method are summarized. The connections and differences of the multi-source mathematic model with uncertainty, as well as the market mechanism, including thermal power, hydroelectric power, wind power, solar energy, and energy storage, are also indicated. Second, the scheduling algorithm and approach are sorted out from the two dimensions of certainty and uncertainty. The innovation and difference in algorithm between the traditional scheduling and the scheduling problem with renewables are presented. Meanwhile, the interaction and coupling relationship among the different time scales are pointed out in each section. The challenges and shortcomings of current research and references future directions are also provided for dispatchers

Sequencing and Genetic Variation of Multidrug Resistance Plasmids in Klebsiella pneumoniae

BACKGROUND: The development of multidrug resistance is a major problem in the treatment of pathogenic microorganisms by distinct antimicrobial agents. Characterizing the genetic variation among plasmids from different bacterial species or strains is a key step towards understanding the mechanism of virulence and their evolution. RESULTS: We applied a deep sequencing approach to 206 clinical strains of Klebsiella pneumoniae collected from 2002 to 2008 to understand the genetic variation of multidrug resistance plasmids, and to reveal the dynamic change of drug resistance over time. First, we sequenced three plasmids (70 Kb, 94 Kb, and 147 Kb) from a clonal strain of K. pneumoniae using Sanger sequencing. Using the Illumina sequencing technology, we obtained more than 17 million of short reads from two pooled plasmid samples. We mapped these short reads to the three reference plasmid sequences, and identified a large number of single nucleotide polymorphisms (SNPs) in these pooled plasmids. Many of these SNPs are present in drug-resistance genes. We also found that a significant fraction of short reads could not be mapped to the reference sequences, indicating a high degree of genetic variation among the collection of K. pneumoniae isolates. Moreover, we identified that plasmid conjugative transfer genes and antibiotic resistance genes are more likely to suffer from positive selection, as indicated by the elevated rates of nonsynonymous substitution. CONCLUSION: These data represent the first large-scale study of genetic variation in multidrug resistance plasmids and provide insight into the mechanisms of plasmid diversification and the genetic basis of antibiotic resistance

Exploration of altered miRNA expression and function in MSC-derived extracellular vesicles in response to hydatid antigen stimulation

BackgroundHydatid disease is caused by Echinococcus parasites and can affect various tissues and organs in the body. The disease is characterized by the presence of hydatid cysts, which contain specific antigens that interact with the host’s immune system. Mesenchymal stem cells (MSCs) are pluripotent stem cells that can regulate immunity through the secretion of extracellular vesicles (EVs) containing microRNAs (miRNAs).MethodsIn this study, hydatid antigens were isolated from sheep livers and mice peritoneal cavities. MSCs derived from mouse bone marrow were treated with different hydatid antigens, and EVs were isolated and characterized from the conditioned medium of MSCs. Small RNA library construction, miRNA target prediction, and differential expression analysis were conducted to identify differentially expressed miRNAs. Functional enrichment and network construction were performed to explore the biological functions of the target genes. Real-time PCR and Western blotting were used for miRNA and gene expression verification, while ELISA assays quantified TNF, IL-1, IL-6, IL-4, and IL-10 levels in cell supernatants.ResultsThe study successfully isolated hydatid antigens and characterized MSC-derived EVs, demonstrating the impact of antigen concentration on MSC viability. Key differentially expressed miRNAs, such as miR-146a and miR-9-5p, were identified, with functional analyses revealing significant pathways like Endocytosis and MAPK signaling associated with these miRNAs’ target genes. The miRNA-HUB gene regulatory network identified crucial miRNAs and HUB genes, such as Traf1 and Tnf, indicating roles in immune modulation and osteogenic differentiation. Protein–protein interaction (PPI) network analysis highlighted central HUB genes like Akt1 and Bcl2. ALP activity assays confirmed the influence of antigens on osteogenic differentiation, with reduced ALP activity observed. Expression analysis validated altered miRNA and chemokine expression post-antigen stimulation, with ELISA analysis showing a significant reduction in CXCL1 expression in response to antigen exposure.ConclusionThis study provides insights into the role of MSC-derived EVs in regulating parasite immunity. The findings suggest that hydatid antigens can modulate the expression of miRNAs in MSC-derived EVs, leading to changes in chemokine expression and osteogenic capacity. These findings contribute to a better understanding of the immunomodulatory mechanisms involved in hydatid disease and provide potential therapeutic targets for the development of new treatment strategies

A low-cost and eco-friendly recombinant protein expression system using copper-containing industrial wastewater

The development of innovative methods for highly efficient production of recombinant proteins remains a prominent focus of research in the biotechnology field, primarily due to the fact that current commercial protein expression systems rely on expensive chemical inducers, such as isopropyl β-D-thiogalactoside (IPTG). In our study, we designed a novel approach for protein expression by creating a plasmid that responds to copper. This specialized plasmid was engineered through the fusion of a copper-sensing element with an optimized multiple cloning site (MCS) sequence. This MCS sequence can be easily customized by inserting the coding sequences of target recombinant proteins. Once the plasmid was generated, it was introduced into an engineered Escherichia coli strain lacking copA and cueO. With this modified E. coli strain, we demonstrated that the presence of copper ions can efficiently trigger the induction of recombinant protein expression, resulting in the production of active proteins. Most importantly, this expression system can directly utilize copper-containing industrial wastewater as an inducer for protein expression while simultaneously removing copper from the wastewater. Thus, this study provides a low-cost and eco-friendly strategy for the large-scale recombinant protein production. To the best of our knowledge, this is the first report on the induction of recombinant proteins using industrial wastewater