Skeletal muscle as a molecular and cellular biomarker of disease progression in amyotrophic lateral sclerosis:a narrative review

Amyotrophic lateral sclerosis is a fatal multisystemic neurodegenerative disease with motor neurons being a primary target.Although progressive weakness is a hallmark feature of amyotrophic lateral sclerosis,there is considerable heterogeneity,including clinical presentation,progression,and the underlying triggers for disease initiation.Based on longitudinal studies with families harboring amyotrophic lateral sclerosis-associated gene mutations,it has become apparent that overt disease is preceded by a prodromal phase,possibly in years,where compensatory mechanisms delay symptom onset.Since 85-90%of amyotrophic lateral sclerosis is sporadic,there is a strong need for identifying biomarkers that can detect this prodromal phase as motor neurons have limited capacity for regeneration.Current Food and Drug Administration-approved therapies work by slowing the degenerative process and are most effective early in the disease.Skeletal muscle,including the neuromuscular junction,manifests abnormalities at the earliest stages of the disease,before motor neuron loss,making it a promising source for identifying biomarkers of the prodromal phase.The accessibility of muscle through biopsy provides a lens into the distal motor system at earlier stages and in real time.The advent of“omics”technology has led to the identification of numerous dysregulated molecules in amyotrophic lateral sclerosis muscle,ranging from coding and non-coding RNAs to proteins and metabolites.This technology has opened the door for identifying biomarkers of disease activity and providing insight into disease mechanisms.A major challenge is correlating the myriad of dysregulated molecules with clinical or histological progression and understanding their relevance to presymptomatic phases of disease.There are two major goals of this review.The first is to summarize some of the biomarkers identified in human amyotrophic lateral sclerosis muscle that have a clinicopathological correlation with disease activity,evidence of a similar dysregulation in the SOD1G93A mouse during presymptomatic stages,and evidence of progressive change during disease progression.The second goal is to review the molecular pathways these biomarkers reflect and their potential role in mitigating or promoting disease progression,and as such,their potential as therapeutic targets in amyotrophic lateral sclerosis.

On the Cosmic Evolution of the Quantum Vacuum Using Two Variable G Models and Winterberg’s Thesis

We work within a Winterberg framework where space, i.e., the vacuum, consists of a two component superfluid/super-solid made up of a vast assembly (sea) of positive and negative mass Planck particles, called planckions. These material particles interact indirectly, and have very strong restoring forces keeping them a finite distance apart from each other within their respective species. Because of their mass compensating effect, the vacuum appears massless, charge-less, without pressure, net energy density or entropy. In addition, we consider two varying G models, where G, is Newton’s constant, and G-1, increases with an increase in cosmological time. We argue that there are at least two competing models for the quantum vacuum within such a framework. The first follows a strict extension of Winterberg’s model. This leads to nonsensible results, if G increases, going back in cosmological time, as the length scale inherent in such a model will not scale properly. The second model introduces a different length scale, which does scale properly, but keeps the mass of the Planck particle as, ± the Planck mass. Moreover we establish a connection between ordinary matter, dark matter, and dark energy, where all three mass densities within the Friedman equation must be interpreted as residual vacuum energies, which only surface, once aggregate matter has formed, at relatively low CMB temperatures. The symmetry of the vacuum will be shown to be broken, because of the different scaling laws, beginning with the formation of elementary particles. Much like waves on an ocean where positive and negative planckion mass densities effectively cancel each other out and form a zero vacuum energy density/zero vacuum pressure surface, these positive mass densities are very small perturbations (anomalies) about the mean. This greatly alleviates, i.e., minimizes the cosmological constant problem, a long standing problem associated with the vacuum.

Milk fat globule membrane supplementation protects againstβ-lactoglobul-ininduced food allergy in mice via upregulation of regulatory T cells and enhancement of intestinal barrier in a microbiota-derived short-chain fatty acids manner

Milk fat globule membrane(MFGM),which contains abundant glycoproteins and phospholipids,exerts beneficial effects on intestinal health and immunomodulation.The aim of this study was to evaluate the protective effects and possible underlying mechanisms of MFGM on cow’s milk allergy(CMA)in aβ-lactoglobulin(BLG)-induced allergic mice model.MFGM was supplemented to allergic mice induced by BLG at a dose of 400 mg/kg body weight.Results demonstrated that MFGM alleviated food allergy symptoms,decreased serum levels of lipopolysaccharide,pro-inflammatory cytokines,immunoglobulin(Ig)E,Ig G1,and Th2 cytokines including interleukin(IL)-4,while increased serum levels of Th1 cytokines including interferon-γand regulatory T cells(Tregs)cytokines including IL-10 and transforming growth factor-β.MFGM modulated gut microbiota and enhanced intestinal barrier of BLG-allergic mice,as evidenced by decreased relative abundance of Desulfobacterota,Rikenellaceae,Lachnospiraceae,and Desulfovibrionaceae,while increased relative abundance of Bacteroidetes,Lactobacillaceae and Muribaculaceae,and enhanced expressions of tight junction proteins including Occludin,Claudin-1 and zonula occludens-1.Furthermore,MFGM increased fecal short-chain fatty acids(SCFAs)levels,which elevated G protein-coupled receptor(GPR)43 and GPR109A expressions.The increased expressions of GPR43 and GPR109A induced CD103+dendritic cells accumulation and promoted Tregs differentiation in mesenteric lymph node to a certain extent.In summary,MFGM alleviated CMA in a BLG-induced allergic mice model through enhancing intestinal barrier and promoting Tregs differentiation,which may be correlated with SCFAs-mediated activation of GPRs.These findings suggest that MFGM may be useful as a promising functional ingredient against CMA.

Neuroprotective effects of G9a inhibition through modulation of peroxisome-proliferator activator receptor gamma-dependent pathways by miR-128

Dysregulation of G9a,a histone-lysine N-methyltransferase,has been observed in Alzheimer’s disease and has been correlated with increased levels of chronic inflammation and oxidative stress.Likewise,microRNAs are involved in many biological processes and diseases playing a key role in pathogenesis,especially in multifactorial diseases such as Alzheimer’s disease.Therefore,our aim has been to provide partial insights into the interconnection between G9a,microRNAs,oxidative stress,and neuroinflammation.To better understand the biology of G9a,we compared the global microRNA expression between senescence-accelerated mouse-prone 8(SAMP8)control mice and SAMP8 treated with G9a inhibitor UNC0642.We found a downregulation of miR-128 after a G9a inhibition treatment,which interestingly binds to the 3′untranslated region(3′-UTR)of peroxisome-proliferator activator receptor γ(PPARG)mRNA.Accordingly,Pparg gene expression levels were higher in the SAMP8 group treated with G9a inhibitor than in the SAMP8 control group.We also observed modulation of oxidative stress responses might be mainly driven Pparg after G9a inhibitor.To confirm these antioxidant effects,we treated primary neuron cell cultures with hydrogen peroxide as an oxidative insult.In this setting,treatment with G9a inhibitor increases both cell survival and antioxidant enzymes.Moreover,up-regulation of PPARγby G9a inhibitor could also increase the expression of genes involved in DNA damage responses and apoptosis.In addition,we also described that the PPARγ/AMPK axis partially explains the regulation of autophagy markers expression.Finally,PPARγ/GADD45αpotentially contributes to enhancing synaptic plasticity and neurogenesis after G9a inhibition.Altogether,we propose that pharmacological inhibition of G9a leads to a neuroprotective effect that could be due,at least in part,by the modulation of PPARγ-dependent pathways by miR-128.

Satellite Communications with 5G, B5G, and 6G: Challenges and Prospects

Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.

5G网络安全测评技术研究与实践

随着5G网络的广泛推广,建立有效的网络安全评估机制变得尤为重要,以有效提升网络安全,减少潜在风险.针对5G技术的复杂性、标准的迭代性、应用的多样性所带来的安全风险,提出了标准化的5G网络安全评估流程.给出了基于数字孪生的5G安全平行仿真测试平台、基于ATT&CK模型的安全渗透技术以及5G安全模糊测试等集成技术方案.这些方案被整合到实际的5G安全测评框架中,并通过实际案例验证了其可行性和有效性.研究结果表明,所提出的评估流程和技术能够有效应对新兴的安全挑战,有助于提高5G网络的整体安全性.

Beam Training and Tracking in mmWave Communication:A Survey

Communicating on millimeter wave(mmWave)bands is ushering in a new epoch of mobile communication which provides the availability of 10 Gbps high data rate transmission.However,mmWave links are easily prone to short transmission range communication because of the serious free space path loss and the blockage by obstacles.To overcome these challenges,highly directional beams are exploited to achieve robust links by hybrid beamforming.Accurately aligning the transmitter and receiver beams,i.e.beam training,is vitally important to high data rate transmission.However,it may cause huge overhead which has negative effects on initial access,handover,and tracking.Besides,the mobility patterns of users are complicated and dynamic,which may cause tracking error and large tracking latency.An efficient beam tracking method has a positive effect on sustaining robust links.This article provides an overview of the beam training and tracking technologies on mmWave bands and reveals the insights for future research in the 6th Generation(6G)mobile network.Especially,some open research problems are proposed to realize fast,accurate,and robust beam training and tracking.We hope that this survey provides guidelines for the researchers in the area of mmWave communications.

人工智能加速GPCR配体的发现

G protein-coupled receptors(GPCRs)are crucial players in various physiological processes,making them attractive candidates for drug discovery.However,traditional approaches to GPCR ligand discovery are time-consuming and resource-intensive.The emergence of artificial intelligence(AI)methods has revo-lutionized the field of GPCR ligand discovery and has provided valuable tools for accelerating the identi-fication and optimization of GPCR ligands.In this study,we provide guidelines for effectively utilizing AI methods for GPCR ligand discovery,including data collation and representation,model selection,and specific applications.First,the online resources that are instrumental in GPCR ligand discovery were sum-marized,including databases and repositories that contain valuable GPCR-related information and ligand data.Next,GPCR and ligand representation schemes that can convert data into computer-readable for-mats were introduced.Subsequently,the key applications of Al methods in the different stages of GPCR drug discovery were discussed,ranging from GPCR function prediction to ligand design and agonist identification.Furthermore,an Al-driven multi-omics integration strategy for GPCR ligand discovery that combines information from various omics disciplines was proposed.Finally,the challenges and future directions of the application of Al in GPCR research were deliberated.In conclusion,continued advance-ments in Al techniques coupled with interdisciplinary collaborations will offer great potential for improv-ing the efficiency of GPCR ligand discovery.

Improving creep strength of the fine-grained heat-affected zone of novel 9Cr martensitic heat-resistant steel via modified thermo-mechanical treatment

The infamous type Ⅳ failure within the fine-grained heat-affected zone (FGHAZ) in G115 steel weldments seriously threatens the safe operation of ultra-supercritical (USC) power plants.In this work,the traditional thermo-mechanical treatment was modified via the replacement of hot-rolling with cold rolling,i.e.,normalizing,cold rolling,and tempering (NCT),which was developed to improve the creep strength of the FGHAZ in G115 steel weldments.The NCT treatment effectively promoted the dissolution of preformed M_(23)C_(6)particles and relieved the boundary segregation of C and Cr during welding thermal cycling,which accelerated the dispersed reprecipitation of M_(23)C_(6) particles within the fresh reaustenitized grains during post-weld heat treatment.In addition,the precipitation of Cu-rich phases and MX particles was promoted evidently due to the deformation-induced dislocations.As a result,the interacting actions between precipitates,dislocations,and boundaries during creep were reinforced considerably.Following this strategy,the creep rupture life of the FGHAZ in G115 steel weldments can be prolonged by 18.6%,which can further push the application of G115 steel in USC power plants.

Improving Channel Estimation in a NOMA Modulation Environment Based on Ensemble Learning

This study presents a layered generalization ensemble model for next generation radio mobiles,focusing on supervised channel estimation approaches.Channel estimation typically involves the insertion of pilot symbols with a well-balanced rhythm and suitable layout.The model,called Stacked Generalization for Channel Estimation(SGCE),aims to enhance channel estimation performance by eliminating pilot insertion and improving throughput.The SGCE model incorporates six machine learning methods:random forest(RF),gradient boosting machine(GB),light gradient boosting machine(LGBM),support vector regression(SVR),extremely randomized tree(ERT),and extreme gradient boosting(XGB).By generating meta-data from five models(RF,GB,LGBM,SVR,and ERT),we ensure accurate channel coefficient predictions using the XGB model.To validate themodeling performance,we employ the leave-one-out cross-validation(LOOCV)approach,where each observation serves as the validation set while the remaining observations act as the training set.SGCE performances’results demonstrate higher mean andmedian accuracy compared to the separatedmodel.SGCE achieves an average accuracy of 98.4%,precision of 98.1%,and the highest F1-score of 98.5%,accurately predicting channel coefficients.Furthermore,our proposedmethod outperforms prior traditional and intelligent techniques in terms of throughput and bit error rate.SGCE’s superior performance highlights its efficacy in optimizing channel estimation.It can effectively predict channel coefficients and contribute to enhancing the overall efficiency of radio mobile systems.Through extensive experimentation and evaluation,we demonstrate that SGCE improved performance in channel estimation,surpassing previous techniques.Accordingly,SGCE’s capabilities have significant implications for optimizing channel estimation in modern communication systems.

Data,digital worlds,and the avatarization of health care

Significant technological trends are impacting health care,from consumerisation,datafication,circular economy,and platformization of services.Web 3.0,or the Internet of Value,enables direct peer-to-peer value exchange,opening up new business models that will impact health care.Among the many technologies that will also be part of the healthcare transformation is artificial intelligence,which shocked the world with the debut of ChatGPT in 2022.This opinion piece will explore how AI underpins the health transformation and,far from being an enemy of health,is the critical friend health care has been waiting for.

Phospholipase A2 enzymes PLA2G2A and PLA2G12B as potential diagnostic and prognostic biomarkers in cholangiocarcinoma

BACKGROUND Phospholipase A2(PLA2)enzymes are pivotal in various biological processes,such as lipid mediator production,membrane remodeling,bioenergetics,and maintaining the body surface barrier.Notably,these enzymes play a significant role in the development of diverse tumors.AIM To systematically and comprehensively explore the expression of the PLA2 family genes and their potential implications in cholangiocarcinoma(CCA).METHODS We conducted an analysis of five CCA datasets from The Cancer Genome Atlas and the Gene Expression Omnibus.The study identified differentially expressed genes between tumor tissues and adjacent normal tissues,with a focus on PLA2G2A and PLA2G12B.Gene Set Enrichment Analysis was utilized to pinpoint associated pathways.Moreover,relevant hub genes and microRNAs for PLA2G2A and PLA2G12B were predicted,and their correlation with the prognosis of CCA was evaluated.RESULTS PLA2G2A and PLA2G12B were discerned as differentially expressed in CCA,manifesting significant variations in expression levels in urine and serum between CCA patients and healthy individuals.Elevated expression of PLA2G2A was correlated with poorer overall survival in CCA patients.Additionally,the study delineated pathways and miRNAs associated with these genes.CONCLUSION Our findings suggest that PLA2G2A and PLA2G12B may serve as novel potential diagnostic and prognostic markers for CCA.The increased levels of these genes in biological fluids could be employed as non-invasive markers for CCA,and their expression levels are indicative of prognosis,underscoring their potential utility in clinical settings.

5G在广播电视直播领域的应用

以5G在广播电视直播领域的应用为重点,全面介绍5G的概念、5G的主要特点以及我国5G发展现状,重点分析5G在广播电视直播中的应用,包括5G+虚拟现实(Virtual Reality,VR)多机位直播、5G+4K/8K多场景直播、5G+慢直播等直播模式,并以实际案例进行说明,为5G与广播电视直播的深度融合应用提供参考,推动广播电视行业直播模式的创新与发展。

Design Framework of Unsourced Multiple Access for 6G Massive IoT

In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.

Mogroside IIE,an in vivo metabolite of sweet agent,alleviates acute lung injury via Pla2g2a-EGFR inhibition

In the face of increasingly serious environmental pollution,the health of human lung tissues is also facing serious threats.Mogroside IIE(M2E)is the main metabolite of sweetening agents mogrosides from the anti-tussive Chinese herbal Siraitia grosvenori.The study elucidated the anti-inflammatory action and molecular mechanism of M2E against acute lung injury(ALI).A lipopolysaccharide(LPS)-induced ALI model was established in mice and MH-S cells were employed to explore the protective mechanism of M2E through the western blotting,co-immunoprecipitation,and quantitative real time-PCR analysis.The results indicated that M2E alleviated LPS-induced lung injury through restraining the activation of secreted phospholipase A2 type IIA(Pla2g2a)-epidermal growth factor receptor(EGFR).The interaction of Pla2g2a and EGFR was identified by co-immunoprecipitation.In addition,M2E protected ALI induced with LPS against inflammatory and damage which were significantly dependent upon the downregulation of AKT and m TOR via the inhibition of Pla2g2a-EGFR.Pla2g2a may represent a potential target for M2E in the improvement of LPS-induced lung injury,which may represent a promising strategy to treat ALI.

Therapeutic strategies targeting the epidermal growth factor receptor signaling pathway in metastatic colorectal cancer

More than 1.9 million new colorectal cancer(CRC)cases and 935000 deaths were estimated to occur worldwide in 2020,representing about one in ten cancer cases and deaths.Overall,colorectal ranks third in incidence,but second in mortality.More than half of the patients are in advanced stages at diagnosis.Treatment options are complex because of the heterogeneity of the patient population,including different molecular subtypes.Treatments have included conventional fluorouracil-based chemotherapy,targeted therapy,immunotherapy,etc.In recent years,with the development of genetic testing technology,more and more targeted drugs have been applied to the treatment of CRC,which has further prolonged the survival of metastatic CRC patients.

网络安全国家标准在5G专网领域下的应用

为了统一和规范5G网络安全工作的基本要求,围绕某外企5G智慧工厂5G专网稳定性、可用性、安全性需求,应用GB/T 37025—2018、GB/T 32922—2023、GB/T 37933—2019等国家标准,分析了5G网络安全保护机制应用到工业互联网领域的方法,统一和规范了5G网络安全工作的基本要求,从而指导行业5G项目在网络安全方面的行为。

Electron G-Factor Anomaly and the Charge Thickness

The electron g-factor relates the magnetic moment to the spin angular momentum. It was originally theoretically calculated to have a value of exactly 2. Experiments yielded a value of 2 plus a very small fraction, referred to as the g-factor anomaly. This anomaly has been calculated theoretically as a power series of the fine structure constant. This document shows that the anomaly is the result of the electron charge thickness. If the thickness were to be zero, g = 2 exactly, and there would be no anomaly. As the thickness increases, the anomaly increases. An equation relating the g-factor and the surface charge thickness is presented. The thickness is calculated to be 0.23% of the electron radius. The cause of the anomaly is very clear, but why is the charge thickness greater than zero? Using the model of the interior structure of the electron previously proposed by the author, it is shown that the non-zero thickness, and thus the g-factor anomaly, are due to the proposed positive charge at the electron center and compressibility of the electron material. The author’s previous publication proposes a theory for splitting the electron into three equal charges when subjected to a strong external magnetic field. That theory is revised in this document, and the result is an error reduced to 0.4% in the polar angle where the splits occur and a reduced magnetic field required to cause the splits.

民航领域5G加速推进背景下通信原理与系统课程教学改革

中国交通教育研究会“十四五”交通教育科研发展规划中明确指出,大力开展5G加速推进背景下专业课程教学创新方面的研究。中国民航大学通信原理与系统课程组立足民航发展需求,紧跟技术进步和行业发展的趋势,重组教学内容,深拓教学资源,探索多元化考核方式,开展“行业为要、内容为新”的课程教学改革,为民航5G加速推进背景下的课程建设提供参考和应用实践。

通信感知一体化在5G-A/6G环境下的无人机应用探究

5G-A/6G网络具备内生感知能力,大带宽的通信能力与高精度感知能力和强大的算力相结合催生了丰富的业务应用。同时,为实现5G-A/6G网络的空天地海无缝覆盖愿景,无人机也将扮演重要角色。因此,5G-A/6G网络通信感知一体化与无人机相结合将大有可为,在无人机辅助通信、无人机群体协同、安全防护、自主导航等领域有着广泛的应用前景,将推动智慧城市建设,助力低空经济产业创新发展。