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Abstract Background Cardiovascular disease and cancer are the main causes of morbidity and mortality worldwide. Studies have shown that these two diseases may have some common risk factors. Atorvastatin is mainly used for the treatment of atherosclerosis in clinic. A large number of studies show that atorvastatin may produce anti-tumor activities. This study aimed to predict the common targets of atorvastatin against atherosclerosis and non-small cell lung cancer (NSCLC) based on network pharmacology. Methods The target genes of atherosclerosis and NSCLC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The disease–target–component model map and the core network were obtained using Cytoscape 3.7.1. The MTS and wound healing assay were used to detect the effect of atorvastatin on cell viability and migration of A549 cells. The expression of potential common target genes of atorvastatin against atherosclerosis and NSCLC were confirmed in A549 cells and lung cancer tissues of patients. Results We identified 15 identical pathogenic genes, and four of which (MMP9, MMP12, CD36, and FABP4) were considered as the key target genes of atorvastatin in anti-atherosclerosis and NSCLC. The MTS and wound healing assays revealed that atorvastatin decreased A549 cells migration significantly. Atorvastatin markedly decreased the expression of MMP9, MMP12, CD36, and FABP4 in A549 cells and patients were treated with atorvastatin. Conclusions This study demonstrated 15 common pathogenic genes in both atherosclerosis and NSCLC. And verified that MMP 9, MMP 12, CD 36 and FABP 4 might be the common target genes of atorvastatin in anti-atherosclerosis and NSCLC.

This paper addresses the increasing demand for computing power and the challenges associated with adding more core units to a computer processor. It explores the utilization of System-on-Chip (SoC) technology, which integrates Terahertz (THz) wave communication capabilities for intra- and inter-chip communication, using the concept of Wireless Network-on-Chips (WNoCs). Various types of network topologies are discussed, along with the disadvantages of wired networks. We explore the idea of applying wireless connections among cores and across the chip. Additionally, we describe the WNoC architecture, the flip-chip package, and the THz antenna. Electromagnetic fields are analyzed using a full-wave simulation software, Ansys High Frequency Structure Simulator (HFSS). The simulation is conducted with dipole and zigzag antennas communicating within the chip at resonant frequencies of 446 GHz and 462.5 GHz, with transmission coefficients of around −28 dB and −33 to −41 dB, respectively. Transmission coefficient characterization, path loss analysis, a study of electric field distribution, and a basic link budget for transmission are provided. Furthermore, the feasibility of calculated transmission power is validated in cases of high insertion loss, ensuring that the achieved energy expenditure is less than 1 pJ/bit. Finally, employing a similar setup, we study intra-chip communication using the same antennas. Simulation results indicate that the zigzag antenna exhibits a higher electric field magnitude compared with the dipole antenna across the simulated chip structure. We conclude that transmission occurs through reflection from the ground plane of a printed circuit board (PCB), as evidenced by the electric field distribution.

Abstract Background Biallelic mutations in CYP27A1 and CYP7B1, two critical genes regulating cholesterol and bile acid metabolism, cause cerebrotendinous xanthomatosis (CTX) and hereditary spastic paraplegia type 5 (SPG5), respectively. These rare diseases are characterized by progressive degeneration of corticospinal motor neuron axons, yet the underlying pathogenic mechanisms and strategies to mitigate axonal degeneration remain elusive. Methods To generate induced pluripotent stem cell (iPSC)-based models for CTX and SPG5, we reprogrammed patient skin fibroblasts into iPSCs by transducing fibroblast cells with episomal vectors containing pluripotency factors. These patient-specific iPSCs, as well as control iPSCs, were differentiated into cortical projection neurons (PNs) and examined for biochemical alterations and disease-related phenotypes. Results CTX and SPG5 patient iPSC-derived cortical PNs recapitulated several disease-specific biochemical changes and axonal defects of both diseases. Notably, the bile acid chenodeoxycholic acid (CDCA) effectively mitigated the biochemical alterations and rescued axonal degeneration in patient iPSC-derived neurons. To further examine underlying disease mechanisms, we developed CYP7B1 knockout human embryonic stem cell (hESC) lines using CRISPR-cas9-mediated gene editing and, following differentiation, examined hESC-derived cortical PNs. Knockout of CYP7B1 resulted in similar axonal vesiculation and degeneration in human cortical PN axons, confirming a cause-effect relationship between gene deficiency and axonal degeneration. Interestingly, CYP7B1 deficiency led to impaired neurofilament expression and organization as well as axonal degeneration, which could be rescued with CDCA, establishing a new disease mechanism and therapeutic target to mitigate axonal degeneration. Conclusions Our data demonstrate disease-specific lipid disturbances and axonopathy mechanisms in human pluripotent stem cell-based neuronal models of CTX and SPG5 and identify CDCA, an established treatment of CTX, as a potential pharmacotherapy for SPG5. We propose this novel treatment strategy to rescue axonal degeneration in SPG5, a currently incurable condition.

Spastic paraplegia type 11 (SPG11) is a common autosomal recessive form of hereditary spastic paraplegia (HSP) characterized by the degeneration of cortical motor neuron axons, leading to muscle spasticity and weakness. Impaired lipid trafficking is an emerging pathology in neurodegenerative diseases including SPG11, though its role in axonal degeneration of human SPG11 neurons remains unknown. Here, we established a pluripotent stem cell-based SPG11 model by knocking down the SPG11 gene in human embryonic stem cells (hESCs). These stem cells were then differentiated into cortical projection neurons (PNs), the cell types affected in HSP patients, to examine axonal defects and cholesterol distributions. Our data revealed that SPG11 deficiency led to reduced axonal outgrowth, impaired axonal transport, and accumulated swellings, recapitulating disease-specific phenotypes. In SPG11-knockdown neurons, cholesterol was accumulated in lysosome and reduced in plasma membrane, revealing impairments in cholesterol trafficking. Strikingly, the liver-X-receptor (LXR) agonists restored cholesterol homeostasis, leading to the rescue of subsequent axonal defects in SPG11-deficient cortical PNs. To further determine the implication of impaired cholesterol homeostasis in SPG11, we examined the cholesterol distribution in cortical PNs generated from SPG11 disease-mutation knock-in hESCs, and observed a similar cholesterol trafficking impairment. Moreover, LXR agonists rescued the aberrant cholesterol distribution and mitigated the degeneration of SPG11 disease-mutated neurons. Taken together, our data demonstrate impaired cholesterol trafficking underlying axonal degeneration of SPG11 human neurons, and highlight the therapeutic potential of LXR agonists for SPG11 through restoring cholesterol homeostasis.

This paper presents a metasurface-based linear-to-circular polarization converter with a flexible structure for conformal and wearable applications. The converter consists of nested S- and C-shaped split ring resonators in the unit cell and can convert linearly polarized incident waves into left-handed circularly polarized ones at 12.4 GHz. Simulation results show that the proposed design has a high polarization conversion rate and efficiency at the operating frequency. Conformal tests are also conducted to evaluate the performance under curvature circumstances. A minor shift in the operating frequency is observed when the converter is applied on a sinusoidal wavy surface.

Modern smart grids are built based on top of advanced computing and networking technologies, where condition monitoring relies on secure cyberphysical connectivity. Over the network infrastructure, transported data containing confidential information, must be protected as smart grids are vulnerable and subject to various cyberattacks. Various machine learning based classifiers were proposed for intrusion detection in smart grids. However, each of them has respective advantage and disadvantages. Aiming to improve the performance of existing machine learning based classifiers, this paper proposes an adaptive deep learning algorithm with a data pre-processing module, a neural network pre-training module and a classifier module, which work together classify intrusion data types using their high-dimensional data features. The proposed Adaptive Deep Learning (ADL) algorithm obtains the number of layers and the number of neurons per layer by determining the characteristic dimension of the network traffic. With transfer learning, the proposed ADL algorithm can extract the original data dimensions and obtain new abstract features. By combining deep learning models with traditional machine learning-based classification models, the performance of classification of network traffic data is significantly improved. By using the Network Security Laboratory-Knowledge Discovery in Databases (NSL-KDD) dataset, experimental results show that the proposed ADL algorithm improves the effectiveness of existing intrusion detection methods and reduces the training time, indicating a promising candidate to enhance network security in smart grids.

This study compared the physical characteristics, nutritional components, mineral elements, and volatile matter of the muscle of the Yellow River carp (Cyprinus carpio haematopterus) grown under the traditional pond system (TPS), in-pond raceway system (IPRS), and wild (WYRC) to reveal the differences in its muscle quality under aquaculture and natural growth conditions. The results demonstrated a significantly lower water-loss rate in the Yellow River carp muscle of both the WYRC and IPRS groups than that in the TPS group (P IPRS > TPS, and significant differences (P IPRS > TPS, and there was a significant difference between the groups (P IPRS > TPS, and the groups exhibited significant differences (P 0.05). These results suggest that different growth conditions significantly influence the physical characteristics, nutritional components, mineral elements, and volatile substances of the Yellow River carp muscle.

Abstract Hereditary spastic paraplegias (HSPs) are caused by a length-dependent axonopathy of long corticospinal neurons, but how axons of these cortical projection neurons (PNs) degenerate remains elusive. We generated isogenic human pluripotent stem cell (hPSC) lines for two ATL1 missense mutations associated with SPG3A, the most common early-onset autosomal dominant HSP. In hPSC-derived cortical PNs, ATL1 mutations resulted in reduced axonal outgrowth, impaired axonal transport, and accumulated axonal swellings, recapitulating disease-specific phenotypes. Importantly, ATL1 mutations dysregulated proteolipid gene expression, reduced lipid droplet size in astrocytes, and unexpectedly disrupted cholesterol transfer from glia to neurons, leading to cholesterol deficiency in SPG3A cortical PNs. Applying cholesterol or conditioned medium from control astrocytes, a major source of cholesterol in the brain, rescued aberrant axonal transport and swellings in SPG3A cortical PNs. Furthermore, treatment with the NR1H2 agonist GW3965 corrected lipid droplet defects in SPG3A astrocytes and promoted cholesterol efflux from astrocytes, leading to restoration of cholesterol levels and rescue of axonal degeneration in SPG3A cortical PNs. These results reveal a non-cell autonomous mechanism underlying axonal degeneration of cortical PNs mediated by impaired cholesterol homeostasis in glia.

Abstract Background Glioma, the most frequent primary tumor of the central nervous system, has poor prognosis. The epidermal growth factor receptor (EGFR) pathway and angiogenesis play important roles in glioma growth, invasion, and recurrence. The present study aimed to use proteomic methods to probe into the role of the EGF‐EGFR‐angiogenesis axis in the tumorigenesis of glioma and access the therapeutic efficacy of selumetinib on glioma. Methods Proteomic profiling was used to characterize 200 paired EGFR‐positive and EGFR‐negative glioma tissues of all pathological types. The quantitative mass spectrometry data were used for systematic analysis of the proteomic profiles of 10 EGFR‐positive and 10 EGFR‐negative glioma cases. Consensus‐clustering analysis was used to screen target proteins. Immunofluorescence analysis, cell growth assay, and intracranial xenograft experiments were used to verify and test the therapeutic effect of selumetinib on glioma. Results Advanced proteomic screening demonstrated that the expression of EGF‐like domain multiple 7 (EGFL7) was higher in EGFR‐positive tumor tissues than in EGFR‐negative tumor tissues. In addition, EGFL7 could act as an activator in vitro and in vivo to promote glioma cell proliferation. EGFL7 was associated strongly with EGFR and prognosis. EGFL7 knockdown effectively suppressed glioma cell proliferation. Selumetinib treatment showed tumor reduction effect in EGFR‐positive glioblastoma xenograft mouse model. Conclusions EGFL7 is a potential diagnostic biomarker and therapeutic target of glioma. Selumetinib could target the EGFR pathway and possibly improve the prognosis of EGFR‐positive glioma.

In this paper, a low-profile, compact size, inexpensive, and easily integrable frequency reconfigurable antenna system is proposed. The proposed antenna consists of an inverted-F shape antenna, capacitors, and switching PIN diodes. The designed antenna element is fabricated on easy available and less expensive FR-4 substrate (εr = 4.4, tan δ = 0.02). The switching diodes are incorporated within the radiating structure of the antenna design, and by changing the different states of PIN diodes, frequency reconfigurable response is achieved. While adjusting the different states of the diodes, the antenna resonates between 0.841 GHz and 2.12 GHz and covers six different frequency bands. The proposed system has compact size of 44×14×3.2 mm3. The gain of the antenna is between 1.89 and 2.12 dBi. The measurement results shows the good agreement with simulated results for different key performance parameters. Additionally, the proposed antenna shows omni-directional far-field characteristics for various different frequencies.

Charcot-Marie-Tooth (CMT) disease is one of the most common genetically inherited neurological disorders and CMT type 2A (CMT 2A) is caused by dominant mutations in the mitofusin-2 (MFN2) gene. MFN2 is located in the outer mitochondrial membrane and is a mediator of mitochondrial fusion, with an essential role in maintaining normal neuronal functions. Although loss of MFN2 induces axonal neuropathy, the detailed mechanism by which MFN2 deficiency results in axonal degeneration of human spinal motor neurons remains largely unknown. In this study, we generated MFN2-knockdown human embryonic stem cell (hESC) lines using lentivirus expressing MFN2 short hairpin RNA (shRNA). Using these hESC lines, we found that MFN2 loss did not affect spinal motor neuron differentiation from hESCs but resulted in mitochondrial fragmentation and dysfunction as determined by live-cell imaging. Notably, MFN2-knockodwn spinal motor neurons exhibited CMT2A disease-related phenotypes, including extensive perikaryal inclusions of phosphorylated neurofilament heavy chain (pNfH), frequent axonal swellings, and increased pNfH levels in long-term cultures. Importantly, MFN2 deficit impaired anterograde and retrograde mitochondrial transport within axons, and reduced the mRNA and protein levels of kinesin and dynein, indicating the interfered motor protein expression induced by MFN2 deficiency. Our results reveal that MFN2 knockdown induced axonal degeneration of spinal motor neurons and defects in mitochondrial morphology and function. The impaired mitochondrial transport in MFN2-knockdown spinal motor neurons is mediated, at least partially, by the altered motor proteins, providing potential therapeutic targets for rescuing axonal degeneration of spinal motor neurons in CMT2A disease.

Impaired axonal development and degeneration underlie debilitating neurodegenerative diseases including hereditary spastic paraplegia, a large group of inherited diseases. Hereditary spastic paraplegia is caused by retrograde degeneration of the long corticospinal tract axons, leading to progressive spasticity and weakness of leg and hip muscles. There are over 70 subtypes with various underlying pathophysiological processes, such as defective vesicular trafficking, lipid metabolism, organelle shaping, axonal transport, and mitochondrial dysfunction. Although hereditary spastic paraplegia consists of various subtypes with different pathological characteristics, defects in mitochondrial morphology and function emerge as one of the common cellular themes in hereditary spastic paraplegia. Mitochondrial morphology and function are remodeled by mitochondrial dynamics regulated by several key fission and fusion mediators. However, the role of mitochondrial dynamics in axonal defects of hereditary spastic paraplegia remains largely unknown. Recently, studies reported perturbed mitochondrial morphology in hereditary spastic paraplegia neurons. Moreover, downregulation of mitochondrial fission regulator dynamin-related protein 1, both pharmacologically and genetically, could rescue axonal outgrowth defects in hereditary spastic paraplegia neurons, providing a potential therapeutic target for treating these hereditary spastic paraplegia. This mini-review will describe the regulation of mitochondrial fission/fusion, the link between mitochondrial dynamics and axonal defects, and the recent progress on the role of mitochondrial dynamics in axonal defects of hereditary spastic paraplegia.

Abstract Due to operational wear and uneven carbon absorption in compressor and turbine wheels, the unbalance (me) vibration is induced and could lead to sub-synchronous vibration accidents for high-speed turbocharger (TC). There are very few research works that focus on the magnitude effects on such induced unbalance vibration. In this paper, a finite element model (FEM) is developed to characterize a realistic automotive TC rotor with floating ring bearings (FRBs). The nonlinear dynamic responses of the TC rotor system with different levels of induced unbalance magnitude in compressor and turbine wheels are calculated. From the results of waterfall and response spectral intensity plots, the bifurcation and instability phenomena depend on unbalance magnitude during the startup of TC. The sub-synchronous component 0.12× caused rotor unstable is the dominant frequency for small induced unbalance. The nonlinear effects of induced unbalance in the turbine wheel is obvious stronger than the compressor wheel. As the unbalance magnitude increases from 0.05 g·mm to 0.2 g·mm, the vibration component changes from mainly 0.12× to synchronous vibration 1×. When unbalance increases continuously, the rotor vibration response amplitude is rapidly growing and the 1× caused by the large unbalance excitation becomes the dominant frequency. A suitable un-balance magnitude of turbine wheel and compressor wheel for the high-speed TC rotor with FRBs is proposed: the value of induced un-balance magnitude should be kept around 0.2 g·mm.

Investigating and classifying sentiments of social media users (e.g., positive, negative) towards an item, situation, and system are very popular among researchers. However, they rarely discuss the underlying socioeconomic factor associations for such sentiments. This study attempts to explore the factors associated with positive and negative sentiments of the people about reopening the economy, in the United States (US) amidst the COVID-19 global crisis. It takes into consideration the situational uncertainties (i.e., changes in work and travel patterns due to lockdown policies), economic downturn and associated trauma, and emotional factors such as depression. To understand the sentiment of the people about the reopening economy, Twitter data was collected, representing the 50 States of the US and Washington D.C, the capital city of the US. State-wide socioeconomic characteristics of the people (e.g., education, income, family size, and employment status), built environment data (e.g., population density), and the number of COVID-19 related cases were collected and integrated with Twitter data to perform the analysis. A binary logit model was used to identify the factors that influence people toward a positive or negative sentiment. The results from the logit model demonstrate that family households, people with low education levels, people in the labor force, low-income people, and people with higher house rent are more interested in reopening the economy. In contrast, households with a high number of family members and high income are less interested in reopening the economy. The accuracy of the model is reasonable (i.e., the model can correctly classify 56.18% of the sentiments). The Pearson chi-squared test indicates that this model has high goodness-of-fit. This study provides clear insights for public and corporate policymakers on potential areas to allocate resources, and directional guidance on potential policy options they can undertake to improve socioeconomic conditions, to mitigate the impact of pandemic in the current situation, and in the future as well.