Mobile Networks Research Articles

SPECC1 as a pan-cancer biomarker: unraveling its role in drug sensitivity and resistance mechanisms

Previous studies have shown a relationship between SPECC1 and the prognosis of breast cancer, indicating a potential function for SPECC1 in the initiation and progression of cancer. However, the role played by SPECC1 in other tumors is not yet known. Therefore, we used bioinformatics techniques to conduct a thorough investigation into the possible mechanism of SPECC1 in pan-cancer, analyzing data reported in the literature as well as databases such as GTEx and CCLE, cBioportal, TCGA, and UCSC XENA. Comparing the results with matching normal tissues, the majority of cancers, including pancreatic adenocarcinoma (PAAD) and breast invasive carcinoma (BRCA), exhibited higher levels of SPECC1, while hepatocellular carcinoma (HCC) showed lower expression levels. SPECC1 was also found to be genetically mutated in endometrial cancer, sarcoma, and esophageal cancer. The prognosis of lung adenocarcinoma, kidney papillary cell carcinoma, and breast cancer is highly correlated with dysregulation of SPECC1 expression. This work helps guide clinical therapy by highlighting the sensitivity of tumor-treating medicines and the prognostic importance of SPECC1 in various malignancies. KEGG pathway enrichment analysis revealed focused adhesion, collagen-containing extracellular matrix (collagen), and the primary enrichment domains for SPECC1-related genes. These findings were obtained through gene annotation (GO) examination of SPECC1 expression. Primary mediators of the cytokine-cytokine receptor interaction include PICOC1-associated genes, cell-substrate junction genes, and extracellular matrix containing collagen. PICOC1-associated genes primarily mediate the PI3K-AKT signaling pathway. Drug sensitivity assay showed that SPECC1 high-expressing cell lines were more sensitive to docetaxel, doxorubicin, etc. In conclusion, the current study shows how SPECC1 is expressed in different cancers and how this expression relates to the prognosis of the tumor. It also revealed the mutations and copy number variations of SPECC1 in various tumors and its potential involvement in cellular pathway regulatory networks and cytological processes. This study examines the relationship between immune genes, cellular infiltration, and immunological scores in the tumor microenvironment, which explain the severity of the disease. This study looks at the response of SPEC1 expression to anticancer therapy. Explains the prognostic significance and drug response of SPECC-1.

Study on the Relationship Between Personality Traits and Mobile Internet Addiction -- with Social Support as the Mediating Variable

College students mobile Internet addiction has become a more concerned topic in academia. In this study, 242 college students were investigated by the mobile Internet addiction questionnaire, Big Five personality scale and social support scale, and the test results were analyzed by SPSS23.0. The results show: 1. Mobile Internet addiction of college students is generally good; 2. The difference in grades of social support is significant, while other differences are not significant; 3. The gender differences in neuroticism and pleasure; 4. The significant correlation between personality traits, social support and mobile network addiction; 5. Social support plays a partial intermediary role between college students mobile Internet addiction and personality traits.

Twists to Classical Conditioning of Adult Drosophila.

Memory has been extensively studied in Drosophila since the early 1970s. Straightforward aversive and appetitive conditioning paradigms train populations of flies to associate the pairing of one of two odors with either punishment or reward. After training, the flies show either preferential avoidance or approach behavior, to the appropriate odor, when given a choice between the two odors in a simple T-maze apparatus. These basic experimental approaches have proven useful in understanding the genetic, molecular, cellular, and neuronal network bases of various valence-specific memories in the fly brain. In addition, numerous modifications to these assays have permitted the study of a broad range of memory-related phenomena. Labile short-term avoidance and approach memories can be readily distinguished from more stable "consolidated" long-term memory equivalents. Prior or subsequent experience of the training cues, and manipulations of the flies' condition, have revealed how parallel competing memories and incompatible states can temporarily interfere with memory retrieval, providing insight into mechanisms of forgetting. Recent studies have also modified the training and testing apparatus to allow simultaneous presentation of odors and colors, providing insight into mechanisms of multisensory learning.

Influence of dislocation cells on hydrogen embrittlement in wrought and additively manufactured Inconel 718

Hydrogen embrittlement (HE) is a major issue for the mechanical integrity of high-strength alloys exposed to hydrogen-rich environments, with diffusion and trapping of hydrogen being critical phenomena. Here, the role of microstructure on hydrogen diffusion, trapping and embrittlement in additively manufactured (AM) and wrought Inconel 718 is compared, revealing the key role played by dislocation cells. Trapping behaviour in hydrogen-saturated alloys is analysed by thermal desorption spectroscopy and numerical simulations. A high density of hydrogen traps in cell walls, attributed to dense dislocations and Laves phases, are responsible for the local accumulation of hydrogen, causing significant loss in strength, and triggering cracking along dislocation cell walls. The influential role of dislocation cells alters fracture behaviour from intergranular in the wrought alloy to intragranular for the AM alloy, due to the large proportion of dislocation cells in AM alloys. In addition, the cellular network of dislocations accelerates hydrogen diffusion, enabling faster and deeper penetration of hydrogen in the AM alloy. These results indicate that the higher HE susceptibility of nickel superalloys is intrinsically associated with the interaction of hydrogen with dislocation walls.

Transmit Precoding via Block Diagonalization with Approximately Optimized Distance Measures for Limited Feedback in Dense Cellular Networks with Multiantenna Base Stations

Transmit Precoding via Block Diagonalization with Approximately Optimized Distance Measures for Limited Feedback in Dense Cellular Networks with Multiantenna Base Stations

SHARD: an improved method for staining and visualizing multiplex immunofluorescence in optically cleared postmortem human brain tissue.

Postmortem human brain tissue is a critical resource for studying neurodegenerative disease, providing critical insights into cellular morphology, pathology, and network connectivity. To improve standard microscopy and enable high-resolution, three-dimensional (3D) images of tissues at the subcellular level, tissue-clearing methods have been developed. These 3D images allow for the analysis of large regions of interest and can be used to study structural and spatial changes that occur during neurodegeneration. Additionally, 3D imaging facilitates the visualization of whole-cell morphology, especially in cells with long processes that would otherwise be truncated in single-plane images. Human brain tissue is especially challenging for tissue clearing due to the abundance of lipids in myelin and the need for optimal fixation and low postmortem intervals. Formaldehyde-based fixatives, commonly used in preserving tissue, hinder antibody binding by crosslinking important antibody epitopes, and fluorescent microscopy requires the incorporation of fluorescent labels through passive diffusion or electrophoresis. Recent studies have focused on optimally fixed human brain tissue with short postmortem intervals, limiting the general applicability of these methods. To address these challenges, we developed SHARD (SHIELD, antigen retrieval, and delipidation), a simple and widely applicable method for clearing and labeling human brain tissue, which can be applied to long-term banked human brain tissue preserved in formaldehyde. SHARD is a novel addition to the SHIELD tissue clarification method, combining antigen retrieval, tissue clearing, and staining of 200-μm sections from long-term banked human brain tissue. The SHARD method is effective for postmortem intervals (PMIs) ranging from 10 to 72 h in multiple neurodegenerative diseases and control samples. In this study, we demonstrate that the SHARD method significantly enhances the immunostaining of glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal marker. Overall, the combination of antigen retrieval and tissue delipidation holds great potential for achieving detailed 3D immunostaining in long-term formaldehyde-fixed postmortem human brain tissue, opening new avenues for research and discovery.

Neuronal threshold functions: Determining symptom onset in neurological disorders

Synaptic networks determine brain function. Highly complex interconnected brain synaptic networks provide output even under fluctuating or pathological conditions. Relevant to the treatment of brain disorders, understanding the limitations of such functional networks becomes paramount. Here we use the example of Parkinson’s Disease (PD) as a system disorder, with PD symptomatology emerging only when the functional reserves of neurons, and their interconnected networks, are unable to facilitate effective compensatory mechanisms. We have denoted this the “threshold theory” to account for how PD symptoms develop in sequence. In this perspective, threshold functions are delineated in a quantitative, synaptic, and cellular network context. This provides a framework to discuss the development of specific symptoms. PD includes dysfunction and degeneration in many organ systems and both peripheral and central nervous system involvement. The threshold theory accounts for and explains the reasons why parallel gradually emerging pathologies in brain and peripheral systems generate specific symptoms only when functional thresholds are crossed, like tipping points. New and mounting evidence demonstrate that PD and related neurodegenerative diseases are multisystem disorders, which transcends the traditional brain-centric paradigm. We believe that representation of threshold functions will be helpful to develop new medicines and interventions that are specific for both pre- and post-symptomatic periods of neurodegenerative disorders.

Improving Non-Line-of-Sight Identification in Cellular Positioning Systems Using a Deep Autoencoding and Generative Adversarial Network Model

Positioning service is a critical technology that bridges the physical world with digital information, significantly enhancing efficiency and convenience in life and work. The evolution of 5G technology has proven that positioning services are integral components of current and future cellular networks. However, positioning accuracy is hindered by non-line-of-sight (NLoS) propagation, which severely affects the measurements of angles and delays. In this study, we introduced a deep autoencoding channel transform-generative adversarial network model that utilizes line-of-sight (LoS) samples as a singular category training set to fully extract the latent features of LoS, ultimately employing a discriminator as an NLoS identifier. We validated the proposed model in 5G indoor and indoor factory (dense clutter, low base station) scenarios by assessing its generalization capability across different scenarios. The results indicate that, compared to the state-of-the-art method, the proposed model markedly diminished the utilization of device resources and achieved a 2.15% higher area under the curve while reducing computing time by 12.6%. This approach holds promise for deployment in future positioning terminals to achieve superior localization precision, catering to commercial and industrial Internet of Things applications.

Retraction Note: Optimization of book information search in intelligent library system management based on cellular network

Retraction Note: Optimization of book information search in intelligent library system management based on cellular network

Spatiotemporal Modeling of Mitochondrial Network Architecture

In many cell types, mitochondria undergo extensive fusion and fission to form dynamic, responsive network structures that contribute to a number of homeostatic, metabolic, and signaling functions. The relationship between the dynamic interactions of individual mitochondrial units and the cell-scale network architecture remains an open area of study. In this work, we use coarse-grained simulations and approximate analytic models to establish how the network morphology is governed by local mechanical and kinetic parameters. The transition between fragmented structures and extensive networks is controlled by local fusion-to-fission ratios, network density, and geometric constraints. Similar fusion rate constants are found to account for the very different structures formed by mammalian networks (poised at the percolation transition) and well-connected budding yeast networks. Over a broad parameter range, the simulated network structures can be described by effective mean-field association constants that exhibit a nonlinear dependence on the microscopic nonequilibrium fusion, fission, and transport rates. Intermediate fusion rate constants are shown to result in the highest rates of network remodeling, with mammalian mitochondrial networks situated in a regime of high turnover. This spatially resolved modeling and simulation framework helps elucidate the emergence of cellular scale network structures, and allows for the quantitative extraction of microscopic kinetic parameters from past and future experimental data. Published by the American Physical Society 2024

Retraction Note: Application of quantum computing based on heterogeneous cellular network algorithm in college student entrepreneurship management

Retraction Note: Application of quantum computing based on heterogeneous cellular network algorithm in college student entrepreneurship management

Anomalous power-law behavior in the electrical impedance of endothelial cellular networks

In this paper, we report on the electrical impedance measurement of human endothelial cellular networks and show the existence of emergent power law behavior in its admittance. In particular, we find that the admittance scales with the frequency ω as ωα, with the exponent that varies with the degree of the disruption caused by the inflammation in the endothelial cellular network. We demonstrate that the power law of the measured electrical admittance can be understood by a simple percolation model of a large R–C (resistor–capacitor) network, which allows us to relate quantitatively and the intensity of inflammation. Our results suggest that the electrical properties of heterogeneous biomaterials, like living tissues, behave as a complex microstructural network.

Single-molecule evidence of Entropic Pulling by Hsp70 chaperones.

Hsp70 chaperones are central components of the cellular network that ensures the structural quality of proteins. Despite crucial roles in processes such as protein disaggregation and protein translocation into organelles, their physical mechanism of action has remained hotly debated. To the best of our knowledge, no experimental data has directly proven any of the modelsproposed to date (Power Stroke, Brownian Ratchet, or Entropic Pulling) due to a lack of suitable methods. Here, we use nanopores, a powerful single-molecule tool, to investigate the mechanism of Hsp70s. We demonstrate that Hsp70s extract trapped polypeptide substrates from the nanopore by generating strong forces (equivalent to 46 pN over distances of 1 nm), that rely on the size of Hsp70. The findings provide unambiguous evidence of the Entropic Pulling mechanism, thus solving a long-standing debate, and proposing a potentially universal principle governing diverse cellular processes. Additionally, these results highlight the utility of biological nanopores for protein studies.

NOMA Visible Light Communications with Distinct Optical Beam Configurations

Visible light communication (VLC) has been viewed as one promising candidate to mitigate the challenging spectrum crisis and radio frequency interference in future 6G mobile communications and networking. Due to the relatively limited baseband modulation bandwidth of VLC light sources—typically, light-emitting diodes—non-orthogonal multiple access (NOMA) techniques have been proposed and explored to enhance the spectral efficiency (SE) of VLC systems. However, almost all reported NOMA VLC schemes focus on well-discussed applications employing a Lambertian light beam configuration and ignore the potential applications with distinct non-Lambertian optical beam configurations. To address this issue, in this work, the performance of non-Lambertian optical beam configuration-based NOMA VLC is comparatively investigated for future 6G mobile networks. The numerical results demonstrate that, for a fundamental two-user application scenario with the far user located at the corner position, a maximum sum rate gain of about 15.6 Mbps could be provided by the investigated distinct non-Lambertian beam-based NOMA VLC, compared with the maximum sum rate of about 93.3 Mbps for the conventional Lambertian configuration with the same power splitting factor.

Polynomial synchronization of quaternion-valued fuzzy cellular neural networks with proportional delays

Polynomial synchronization of quaternion-valued fuzzy cellular neural networks with proportional delays

Exploit Vulnerabilities in 4G and 5G Cellular Access Network

Portable gadgets back different specialized highlights and administrations for up-and-coming 2G, 3G, 4G and 5G systems. For illustration, these determinations contain physical layer rate sorts, radio convention data, security calculations, carrier conglomeration groups, and benefit sorts such as GSM-R, Voice over LTE, Within the setting of portable security standardization, these organize determinations and administrations are alluded to as gadget capabilities and are traded with the organize amid the gadget enrolment stage. In this article, we investigate data around indicated gadget capabilities for 4G and 5G gadgets and their part in building up a secure interface between the gadget and the arrange. Our inquire about comes about appear the plausibility of the gadget being traded with the carrier some time recently the confirmation step without any ensures and not affirmed by the carrier. Therefore, we display three unused sorts of assaults that misuse data approximately the capabilities of unprotected gadgets in future 5G systems: Character assaults, sending assaults, and battery deplete assaults against versatile gadgets. Conduct verification of concept assaults utilizing reasonable equipment and computer program arrangements to survey their effect on commercial 4G gadgets and systems. We have detailed the distinguished vulnerabilities to pertinent benchmarks bodies and given countermeasures to relieve assaults against gadget capabilities in up-and-coming 5G systems.

Drone-based mobile full-duplex optical communication

Wireless optical communication plays a vital role in mobile communication networks, and both drones and vehicles are essential mobile communication nodes. Here, image identification technology, gimbal, and full-duplex optical communication systems are integrated to manage the challenging issues of light alignment and target tracking for mobile full-duplex optical communication under the transmission control protocol/internet protocol (TCP/IP) scheme. Both drones and vehicles are equipped with the proposed setup to realize full-duplex wireless optical data transmission at a communication rate of 2 Mbps in both air-to-ground and air-to-air scenarios. By further integrating wireless-fidelity (Wi-Fi) modules, drone-based mobile optical communication systems (MOCSs) can be interconnected with the network via the TCP/IP scheme, and real-time video transmission can be demonstrated. This work provides a feasible route toward a mobile optical communication network (MOCN) for diverse applications.

6667 IGF1 Induces The Expression of CYR61 In Metastatic Prostate Cancer

Abstract Disclosure: G.L. Ortiz Hernández: None. M. Walker: None. L. Woods-Burnham: None. R.A. Kittles: None. C.A. Casiano: None. S.L. Neuhausen: None. The cysteine-rich angiogenic inducer 61 (CYR61) is a member of the cellular communication network (CCN) protein family that can be induced by growth factors. CYR61-specific functions are dependent on cellular context. In prostate cancer (PCa), CYR61 contributes to cell growth and survival through its interactions with extracellular ligands, such as integrins avb3 and a6b4, in the extracellular matrix space. CYR61 contains an insulin-like growth factor-binding protein domain suggesting that it may interact with insulin-like growth factor-I (IGF1). High serum levels of IGF1 are directly linked to PCa development and recently have been studied as a predictor of metastatic disease. Given the important roles that IGF1 and CYR61 play in PCa and their potential interaction, it is critical to investigate their molecular interplay. The correlation between PCa aggressiveness and circulating levels of CYR61 and IGF1 is poorly studied. Our goal was to assess the contribution of the interaction of CYR61-IGF1 to PCa cell proliferation. Their combined role may explain a proportion of aggressive PCa. This study was designed to characterize the role of IGF1-induced expression of CYR61 in metastatic PCa cellular models and to determine if this interaction contributes to aggressive tumor properties (e.g., proliferation, migration, tumorsphere formation). Using immunoblotting, we demonstrated that CYR61 is upregulated in the metastatic cell line PC3. Furthermore, optimized knockdown of CYR61 using siRNA significantly reduced PC3 cell proliferation, viability, and prostasphere formation. To examine the underlying mechanisms associated with IGF1 signaling, we assessed the activation of either the PI3/Akt and MAPK pathways in PC3 cells with CYR61 silencing. CYR61 siRNA-mediated knockdown decreased activation of the PI3/Akt pathway but did not affect the MAPK pathway. In addition, we found that IGF1 induces protein expression of CYR61 in a time-dependent manner, validated by both immunoblotting and confocal microscopy. PC3 cell lines are androgen receptor negative (AR-) and glucocorticoid receptor positive (GR+), which is characteristic of aggressive, advanced metastatic castration-resistant prostate cancer (mCRPC). Currently, we are conducting the same experiments in LNCaP cells, which are AR+/GR-, to determine if the CYR61-IGF1 interplay also occurs in PCa cells capable of AR signaling. In conclusion, we found that CYR61 expression is induced by IGF1 and its inhibition decreased the capacity of metastatic PCa cells to proliferate. Our results suggest that CYR61 inhibition may have the potential for treating metastatic PCa. Presentation: 6/1/2024

6667 IGF1 Induces the Expression of CYR61 in Metastatic Prostate Cancer

Abstract Disclosure: G.L. Ortiz Hernández: None. M. Walker: None. L. Woods-Burnham: None. R.A. Kittles: None. C.A. Casiano: None. S.L. Neuhausen: None. The cysteine-rich angiogenic inducer 61 (CYR61) is a member of the cellular communication network (CCN) protein family that can be induced by growth factors. CYR61-specific functions are dependent on cellular context. In prostate cancer (PCa), CYR61 contributes to cell growth and survival through its interactions with extracellular ligands, such as integrins avb3 and a6b4, in the extracellular matrix space. CYR61 contains an insulin-like growth factor-binding protein domain suggesting that it may interact with insulin-like growth factor-I (IGF1). High serum levels of IGF1 are directly linked to PCa development and recently have been studied as a predictor of metastatic disease. Given the important roles that IGF1 and CYR61 play in PCa and their potential interaction, it is critical to investigate their molecular interplay. The correlation between PCa aggressiveness and circulating levels of CYR61 and IGF1 is poorly studied. Our goal was to assess the contribution of the interaction of CYR61-IGF1 to PCa cell proliferation. Their combined role may explain a proportion of aggressive PCa. This study was designed to characterize the role of IGF1-induced expression of CYR61 in metastatic PCa cellular models and to determine if this interaction contributes to aggressive tumor properties (e.g., proliferation, migration, tumorsphere formation). Using immunoblotting, we demonstrated that CYR61 is upregulated in the metastatic cell line PC3. Furthermore, optimized knockdown of CYR61 using siRNA significantly reduced PC3 cell proliferation, viability, and prostasphere formation. To examine the underlying mechanisms associated with IGF1 signaling, we assessed the activation of either the PI3/Akt and MAPK pathways in PC3 cells with CYR61 silencing. CYR61 siRNA-mediated knockdown decreased activation of the PI3/Akt pathway but did not affect the MAPK pathway. In addition, we found that IGF1 induces protein expression of CYR61 in a time-dependent manner, validated by both immunoblotting and confocal microscopy. PC3 cell lines are androgen receptor negative (AR-) and glucocorticoid receptor positive (GR+), which is characteristic of aggressive, advanced metastatic castration-resistant prostate cancer (mCRPC). Currently, we are conducting the same experiments in LNCaP cells, which are AR+/GR-, to determine if the CYR61-IGF1 interplay also occurs in PCa cells capable of AR signaling. In conclusion, we found that CYR61 expression is induced by IGF1 and its inhibition decreased the capacity of metastatic PCa cells to proliferate. Our results suggest that CYR61 inhibition may have the potential for treating metastatic PCa. Presentation: 6/1/2024

Non-destructive detection of male and female information in ducklings based on near-infrared spectral wavelength selection and deep learning

The technology for sex identification in ducklings can contribute to increased revenue and cost savings in modern duck farming. However, traditional manual identification techniques require high skill levels and involve significant labor intensity. In this study, a non-destructive, user-friendly, and efficient duckling sex identification technique was proposed using near-infrared spectroscopy and deep learning algorithms. Spectral data from 600 groups of newly hatched ducklings were collected. These data were divided into training, testing, and validation sets in a ratio of 7:2:1. The raw spectral data was preprocessed using the Savitzky-Golay convolution derivative method, which was employed for subsequent spectral feature wavelength extraction and modeling. The characteristic wavelengths were extracted using competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA), and uninformative variable elimination combined with SPA (UVE-SPA). Conventional machine learning methods − support vector machine (SVM) and different deep learning models, including multilayer perceptron (MLP), mobile network version 2 (MobileNetV2), and residual neural network (ResNet), were studied and compared. The experiment showed that deep learning algorithms outperform traditional spectral analysis models in terms of classification performance. Furthermore, conducting feature wavelength extraction before constructing the classification model could reduce the model’s testing time and even improve its classification performance. Finally, the four models with better classification performance were validated using a validation set, and the combination of MobileNetV2 model UVE-SPA was selected as the optimized model for ducklings’ gender determination, with a classification accuracy of 98.3 % and an average validation time of 1.1 ms. In summary, the detection model established using near-infrared spectroscopy and MobileNetV2 can achieve non-destructive identification of the gender of ducklings. The findings can provide a preliminary research foundation and technical support for the subsequent design of related online intelligent detection systems.