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.

5G数据通信演进研究

在当前的数字时代,上网已成为每个家庭和个人的生活刚需,而上网产生的通信就是数据通信。上网方式主要分为有线和无线两种,无线上网能够做到随时随地冲浪无忧,而5G上网能为用户提供高速上网新体验。文章描述2G时代GPRS(通用分组无线服务)网络和CDMA(码分多址)网络数据通信架构,分析3G时代WCDMA(宽带码分多址)网络数据通信架构变化,给出4G时代LTE(长期演进)上网原理,说明5G时代网络功能对上网的支撑作用。

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.

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向6G演进过程中的发展困境及未来6G发展建议

[目的/意义]5G及下一代移动通信网络作为落实网络强国、数字中国建设的重要新型基础设施之一,为深化传统产业数字化转型提供了升级动力。5G行业应用在我国得到快速发展的同时,也面临诸多的问题与困境,这是5G向6G演进过程中无法绕开的关键。本文旨在借鉴5G经验,探索方法提高6G关键能力和行业需求的匹配程度,为6G走出5G困境寻求方向。[方法/过程]本文结合未来数字化场景针对6G关键能力的全面梳理,从6G发展需要破解的两大困境出发,基于专家调研获取的未来数字化场景针对6G关键能力的需求程度数据,构建6G典型场景需求评估及6G垂直行业潜在价值空间评估模型。在此基础上,识别6G在各行业应用发展中具有共性的、应优先关注或值得推广的典型场景,为6G在不同行业的多波次推进提供策略依据。[结果/结论]基于模型输出,本文提出了“6G发展以场景为引、按需部署,破解需求和效益的发展困境”“尽早推动6G商业闭环顶层设计,提升技术与需求匹配度”“统筹5G和6G发展,加强产业培育,基于5G为6G挖掘需求并验证”等6G发展建议,并指出从需求和效益出发,优先针对潜在价值高的特定场景的技术演进是未来6G可持续发展的重要研究方向。

Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems

The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia content.In light of the data-centric aspect of contemporary communication,the information-centric network(ICN)paradigm offers hope for a solution by emphasizing content retrieval by name instead of location.If 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things(IoT)devices,then effective caching solutions will be required tomaximize network throughput andminimize the use of resources.Hence,an ICN-based Cooperative Caching(ICN-CoC)technique has been used to select a cache by considering cache position,content attractiveness,and rate prediction.The findings show that utilizing our suggested approach improves caching regarding the Cache Hit Ratio(CHR)of 84.3%,Average Hop Minimization Ratio(AHMR)of 89.5%,and Mean Access Latency(MAL)of 0.4 s.Within a framework,it suggests improved caching strategies to handle the difficulty of effectively controlling data consumption in 5G networks.These improvements aim to make the network run more smoothly by enhancing content delivery,decreasing latency,and relieving congestion.By improving 5G communication systems’capacity tomanage the demands faced by modern data-centric applications,the research ultimately aids in advancement.

Historical tillage promotes grass-legume mixtures establishment and accelerates soil microbial activity and organic carbon decomposition

Perennial grass-legume mixtures have been extensively used to restore degraded grasslands,increasing grassland productivity and forage quality.Tillage is crucial for seedbed preparation and sustainable weed management for the establishment of grass-legume mixtures.However,a common concern is that intensive tillage may alter soil characteristics,leading to losses in soil organic carbon(SOC).We investigated the plant community composition,SOC,soil microbial biomass carbon(MBC),soil enzyme activities,and soil properties in long-term perennial grass-legume mixtures under two different tillage intensities(once and twice)as well as in a fenced grassland(FG).The establishment of grass-legume mixtures increased plant species diversity and plant community coverage,compared with FG.Compared with once tilled grassland(OTG),twice tilled grassland(TTG)enhanced the coverage of high-quality leguminous forage species by 380.3%.Grass-legume mixtures with historical tillage decreased SOC and dissolved organic carbon(DOC)concentrations,whereas soil MBC concentrations in OTG and TTG increased by 16.0%and 16.4%,respectively,compared with FG.TTG significantly decreased the activity of N-acetyl-β-D-glucosaminidase(NAG)by 72.3%,whereas soil enzymeβ-glucosidase(βG)in OTG and TTG increased by 55.9%and 27.3%,respectively,compared with FG.Correlation analysis indicated a close association of the increase in MBC andβG activities with the rapid decline in SOC.This result suggested that MBC was a key driving factor in soil carbon storage dynamics,potentially accelerating soil carbon cycling and facilitating biogeochemical cycling.The establishment of grass-legume mixtures effectively improves forage quality and boosts plant diversity,thereby facilitating the restoration of degraded grasslands.Although tillage assists in establishing legume-grass mixtures by controlling weeds,it accelerates microbial activity and organic carbon decomposition.Our findings provide a foundation for understanding the process and effectiveness of restoration management in degraded grasslands.

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.

Design of an Interconnection Architecture and Sizing of Two (2) EPC Core Networks: The Case of Orange-Guinea

With the arrival of the 4G and 5G,the telecommunications networks have experienced a large expansion of these networks.That enabled the integration of many services and adequate flow,thus enabling the operators to respond to the growing demand of users.This rapid evolution has given the operators to adapt,their methods to the new technologies that increase.This complexity becomes more important,when these networks include several technologies to access different from the heterogeneous network like in the 4G network.The dimensional new challenges tell the application and the considerable increase in demand for services and the compatibility with existing networks,the management of mobility intercellular of users and it offers a better quality of services.Thus,the proposed solution to meet these new requirements is the sizing of the EPC(Evolved Packet Core)core network to support the 5G access network.For the case of Orange Guinea,this involves setting up an architecture for interconnecting the core networks of Sonfonia and Camayenne.The objectives of our work are of two orders:(1)to propose these solutions and recommendations for the heart network EPC sizing and the deployment to be adopted;(2)supply and architectural interconnection in the heart network EPC and an existing heart network.In our work,the model of traffic in communication that we use to calculate the traffic generated with each technology has link in the network of the heart.

Integrated Sensing and Communication:Who Benefits More?

This paper compares the benefits of communication-assisted sensing and sensing-assisted communication in the context of integrated sensing and communication(ISAC).Communication-assisted sensing leverages the extensive cellular infrastructure to create a vast and cooperative sensor network,enhancing environmental perception accuracy and coverage.On the other hand,sensing-assisted communication utilizes advanced sensing technologies to improve predictive beamforming and channel estimation performance in high-frequency and highmobility scenarios,thereby increasing communication efficiency and reliability.To validate our analysis,we present an example of channel knowledge map(CKM)-assisted beam tracking.This example demonstrates the practical advantages of incorporating CKM in enhancing beam tracking accuracy.Our analysis confirms that communication-assisted sensing may offer greater development potential due to its wide coverage and cost-effectiveness in large-scale applications.

免疫球蛋白G4相关性疾病研究进展

免疫球蛋白G4相关性疾病(IgG4-related disease IgG4-RD)是一种影响多器官的慢性系统性自身免疫性疾病。几乎可以累及全身任何组织器官,其中消化系统受累较为常见。IgG4-RD病因及发病机制仍未完全阐明,其诊断需联合辅助检查,综合评估,但组织病理活检仍是诊断IgG4-RD的金标准。目前认为糖皮质激素仍是IgG4-RD的一线治疗。本文通过对IgG4-RD的研究进展进行综述,旨在为临床提供参考。

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 revolutionized the field of GPCR ligand discovery and has provided valuable tools for accelerating the identification 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 summarized,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 formats were introduced.Subsequently,the key applications of AI methods in the different stages of GPCR drug discovery were discussed,ranging from GPCR function prediction to ligand design and agonist identification.Furthermore,an AI-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 AI in GPCR research were deliberated.In conclusion,continued advancements in AI techniques coupled with interdisciplina ry collaborations will offer great potential for improving 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.

5G话音通信演进研究

打电话既是人类最原始的通信需求,又是移动通信的初心。文章描述1G/2G/3G时代CS(电路交换)话音的工作原理,分析4G(第4代移动通信)时代CSFB(电路交换回落)和Vo LTE(LTE话音)两种话音解决方案的工作原理和实现流程,给出5G NSA(非独立组网)和SA(独立组网)两种模式下的VoLTE、EPS FB(演进分组系统回落)和VoNR(新无线电话音)三种话音解决方案,最后对各类话音解决方案的MOS(平均意见得分)和接入时延等性能指标进行比较。

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.

Channel assignment and power allocation for throughput improvement with PPO in B5G heterogeneous edge networks

In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver uses interference cancellation.Unfortunately,uncoordinated radio resource allocation can reduce system throughput and lead to user inequity,for this reason,in this paper,channel allocation and power allocation problems are formulated to maximize the system sum rate and minimum user achievable rate.Since the construction model is non-convex and the response variables are high-dimensional,a distributed Deep Reinforcement Learning(DRL)framework called distributed Proximal Policy Optimization(PPO)is proposed to allocate or assign resources.Specifically,several simulated agents are trained in a heterogeneous environment to find robust behaviors that perform well in channel assignment and power allocation.Moreover,agents in the collection stage slow down,which hinders the learning of other agents.Therefore,a preemption strategy is further proposed in this paper to optimize the distributed PPO,form DP-PPO and successfully mitigate the straggler problem.The experimental results show that our mechanism named DP-PPO improves the performance over other DRL methods.

5G Resource Allocation Using Feature Selection and Greylag Goose Optimization Algorithm

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic processes.Prospects of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital solutions.An essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G lines.Integrating Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine learningmodels.Thus,the model performs and yields more accurate results.This work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of K-Nearest Neighbors(KNN),Gradient Boosting,and Extra Trees algorithms.The ensemble model shows better prediction performance with the coefficient of determination R squared value equal to.99348.The proposed framework is supported by several Statistical analyses,such as theWilcoxon signed-rank test.Some of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

Immunoglobulin G4-related spinal pachymeningitis:A case report

BACKGROUND Immunoglobulin G4-related disease(IgG4-RD)is a complex immune-mediated condition that causes fibrotic inflammation in several organs.A significant clinical feature of IgG4-RD is hypertrophic pachymeningitis,which manifests as inflammation of the dura mater in intracranial or spinal regions.Although IgG4-RD can affect multiple areas,the spine is a relatively rare site compared to the more frequent involvement of intracranial structures.CASE SUMMARY A 70-year-old male presented to our hospital with a two-day history of fever,altered mental status,and generalized weakness.The initial brain magnetic resonance imaging(MRI)revealed multiple small infarcts across various cerebral regions.On the second day after admission,a physical examination revealed motor weakness in both lower extremities and diminished sensation in the right lower extremity.Electromyographic evaluation revealed findings consistent with acute motor sensory neuropathy.Despite initial management with intravenous immunoglobulin for presumed Guillain-Barrésyndrome,the patient exhibited progressive worsening of motor deficits.On the 45th day of hospitalization,an enhanced MRI of the entire spine,focusing specifically on the thoracic 9 to lumbar 1 vertebral level,raised the suspicion of IgG4-related spinal pachymeningitis.Subsequently,the patient was administered oral prednisolone and participated in a comprehensive rehabilitation program that included gait training and lower extremity strengthening exercises.CONCLUSION IgG4-related spinal pachymeningitis,diagnosed on MRI,was treated with corticosteroids and a structured rehabilitation regimen,leading to significant improvement.