Timosaponin AⅢ induces drug-metabolizing enzymes by activating constitutive androstane receptor (CAR) via dephosphorylation of the EGFR signaling pathway

The current study aimed to assess the effect of timosaponin AⅢ(T-AⅢ)on drug-metabolizing enzymes during anticancer therapy.The in vivo experiments were conducted on nude and ICR mice.Following a 24-day administration of T-AⅢ,the nude mice exhibited an induction of CYP2B10,MDR1,and CYP3A11 expression in the liver tissues.In the ICR mice,the expression levels of CYP2B10 and MDR1 increased after a three-day T-AⅢ administration.The in vitro assessments with HepG2 cells revealed that T-AⅢ induced the expression of CYP2B6,MDR1,and CYP3A4,along with constitutive androstane receptor(CAR)activation.Treatment with CAR siRNA reversed the T-AⅢ-induced increases in CYP2B6 and CYP3A4 expression.Furthermore,other CAR target genes also showed a significant increase in the expression.The up-regulation of murine CAR was observed in the liver tissues of both nude and ICR mice.Subsequent findings demonstrated that T-AⅢ activated CAR by inhibiting ERK1/2 phosphorylation,with this effect being partially reversed by the ERK activator t-BHQ.Inhibition of the ERK1/2 signaling pathway was also observed in vivo.Additionally,T-AⅢ inhibited the phosphorylation of EGFR at Tyr1173 and Tyr845,and suppressed EGF-induced phosphorylation of EGFR,ERK,and CAR.In the nude mice,T-AⅢ also inhibited EGFR phosphorylation.These results collectively indicate that T-AⅢ is a novel CAR activator through inhibition of the EGFR pathway.

Digital signal acquisition system for complex nuclear reaction experiments

A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)parametrization was developed to adapt to different experimental sizes.A user-friendly interface was implemented,which allows converting script language expressions into FPGA internal control parameters.The proposed digital system can be combined with a conventional analog data acquisition system to provide more flexibility.The performance of the combined system was veri-fied using experimental data.

Gut microbiota dysbiosis contributes toα-synuclein-related pathology associated with C/EBPβ/AEP signaling activation in a mouse model of Parkinson’s disease

Parkinson’s disease is a neurodegenerative disease characterized by motor and gastrointestinal dysfunction.Gastrointestinal dysfunction can precede the onset of motor symptoms by several years.Gut microbiota dysbiosis is involved in the pathogenesis of Parkinson’s disease,whether it plays a causal role in motor dysfunction,and the mechanism underlying this potential effect,remain unknown.CCAAT/enhancer binding proteinβ/asparagine endopeptidase(C/EBPβ/AEP)signaling,activated by bacterial endotoxin,can promoteα-synuclein transcription,thereby contributing to Parkinson’s disease pathology.In this study,we aimed to investigate the role of the gut microbiota in C/EBPβ/AEP signaling,α-synuclein-related pathology,and motor symptoms using a rotenone-induced mouse model of Parkinson’s disease combined with antibiotic-induced microbiome depletion and fecal microbiota transplantation.We found that rotenone administration resulted in gut microbiota dysbiosis and perturbation of the intestinal barrier,as well as activation of the C/EBP/AEP pathway,α-synuclein aggregation,and tyrosine hydroxylase-positive neuron loss in the substantia nigra in mice with motor deficits.However,treatment with rotenone did not have any of these adverse effects in mice whose gut microbiota was depleted by pretreatment with antibiotics.Importantly,we found that transplanting gut microbiota derived from mice treated with rotenone induced motor deficits,intestinal inflammation,and endotoxemia.Transplantation of fecal microbiota from healthy control mice alleviated rotenone-induced motor deficits,intestinal inflammation,endotoxemia,and intestinal barrier impairment.These results highlight the vital role that gut microbiota dysbiosis plays in inducing motor deficits,C/EBPβ/AEP signaling activation,andα-synuclein-related pathology in a rotenone-induced mouse model of Parkinson’s disease.Additionally,our findings suggest that supplementing with healthy microbiota may be a safe and effective treatment that could help ameliorate the progression of motor deficits in patients with Parkinson’s disease.

Melatonin improves synapse development by PI3K/Akt signaling in a mouse model of autism spectrum disorder

Autism spectrum disorders are a group of neurodevelopmental disorders involving more than 1100 genes,including Ctnnd2 as a candidate gene.Ctnnd2knockout mice,serving as an animal model of autis m,have been demonstrated to exhibit decreased density of dendritic spines.The role of melatonin,as a neuro hormone capable of effectively alleviating social interaction deficits and regulating the development of dendritic spines,in Ctnnd2 deletion-induced nerve injury remains unclea r.In the present study,we discove red that the deletion of exon 2 of the Ctnnd2 gene was linked to social interaction deficits,spine loss,impaired inhibitory neurons,and suppressed phosphatidylinositol-3-kinase(PI3K)/protein kinase B(Akt) signal pathway in the prefrontal cortex.Our findings demonstrated that the long-term oral administration of melatonin for 28 days effectively alleviated the aforementioned abnormalities in Ctnnd2 gene-knockout mice.Furthermore,the administration of melatonin in the prefro ntal cortex was found to improve synaptic function and activate the PI3K/Akt signal pathway in this region.The pharmacological blockade of the PI3K/Akt signal pathway with a PI3K/Akt inhibitor,wo rtmannin,and melatonin receptor antagonists,luzindole and 4-phenyl-2-propionamidotetralin,prevented the melatonin-induced enhancement of GABAergic synaptic function.These findings suggest that melatonin treatment can ameliorate GABAe rgic synaptic function by activating the PI3K/Akt signal pathway,which may contribute to the improvement of dendritic spine abnormalities in autism spectrum disorders.

Na^(+)/K^(+)-ATPase:ion pump,signal transducer,or cytoprotective protein,and novel biological functions

Na^(+)/K^(+)-ATPase is a transmembrane protein that has important roles in the maintenance of electrochemical gradients across cell membranes by transporting three Na^(+)out of and two K^(+)into cells.Additionally,Na^(+)/K^(+)-ATPase participates in Ca^(2+)-signaling transduction and neurotransmitter release by coordinating the ion concentration gradient across the cell membrane.Na^(+)/K^(+)-ATPase works synergistically with multiple ion channels in the cell membrane to form a dynamic network of ion homeostatic regulation and affects cellular communication by regulating chemical signals and the ion balance among different types of cells.Therefo re,it is not surprising that Na^(+)/K^(+)-ATPase dysfunction has emerged as a risk factor for a variety of neurological diseases.However,published studies have so far only elucidated the important roles of Na^(+)/K^(+)-ATPase dysfunction in disease development,and we are lacking detailed mechanisms to clarify how Na^(+)/K^(+)-ATPase affects cell function.Our recent studies revealed that membrane loss of Na^(+)/K^(+)-ATPase is a key mechanism in many neurological disorders,particularly stroke and Parkinson's disease.Stabilization of plasma membrane Na^(+)/K^(+)-ATPase with an antibody is a novel strategy to treat these diseases.For this reason,Na^(+)/K^(+)-ATPase acts not only as a simple ion pump but also as a sensor/regulator or cytoprotective protein,participating in signal transduction such as neuronal autophagy and apoptosis,and glial cell migration.Thus,the present review attempts to summarize the novel biological functions of Na^(+)/K^(+)-ATPase and Na^(+)/K^(+)-ATPase-related pathogenesis.The potential for novel strategies to treat Na^(+)/K^(+)-ATPase-related brain diseases will also be discussed.

Hypoglycemic mechanism of Tegillarca granosa polysaccharides on type 2 diabetic mice by altering gut microbiota and regulating the PI3K-akt signaling pathwaye

Type 2 diabetes mellitus(T2DM)is a complex metabolic disease threatening human health.We investigated the effects of Tegillarca granosa polysaccharide(TGP)and determined its potential mechanisms in a mouse model of T2DM established through a high-fat diet and streptozotocin.TGP(5.1×10^(3) Da)was composed of mannose,glucosamine,rhamnose,glucuronic acid,galactosamine,glucose,galactose,xylose,and fucose.It could significantly alleviate weight loss,reduce fasting blood glucose levels,reverse dyslipidemia,reduce liver damage from oxidative stress,and improve insulin sensitivity.RT-PCR and Western blotting indicated that TGP could activate the phosphatidylinositol-3-kinase/protein kinase B signaling pathway to regulate disorders in glucolipid metabolism and improve insulin resistance.TGP increased the abundance of Allobaculum,Akkermansia,and Bifidobacterium,restored the microbiota abundance in the intestinal tracts of mice with T2DM,and promoted short-chain fatty acid production.This study provides new insights into the antidiabetic effects of TGP and highlights its potential as a natural hypoglycemic nutraceutical.

Detection method of forward-scatter signal based on Rényi entropy

The application scope of the forward scatter radar(FSR)based on the Global Navigation Satellite System(GNSS)can be expanded by improving the detection capability.Firstly,the forward-scatter signal model when the target crosses the baseline is constructed.Then,the detection method of the for-ward-scatter signal based on the Rényi entropy of time-fre-quency distribution is proposed and the detection performance with different time-frequency distributions is compared.Simula-tion results show that the method based on the smooth pseudo Wigner-Ville distribution(SPWVD)can achieve the best perfor-mance.Next,combined with the geometry of FSR,the influence on detection performance of the relative distance between the target and the baseline is analyzed.Finally,the proposed method is validated by the anechoic chamber measurements and the results show that the detection ability has a 10 dB improvement compared with the common constant false alarm rate(CFAR)detection.

Fanlian Huazhuo Formula alleviates high-fat diet-induced nonalcoholic fatty liver disease by modulating autophagy and lipid synthesis signaling pathway

BACKGROUND Fanlian Huazhuo Formula(FLHZF)has the functions of invigorating spleen and resolving phlegm,clearing heat and purging turbidity.It has been identified to have therapeutic effects on type 2 diabetes mellitus(T2DM)in clinical application.Non-alcoholic fatty liver disease(NAFLD)is frequently diagnosed in patients with T2DM.However,the therapeutic potential of FLHZF on NAFLD and the underlying mechanisms need further investigation.AIM To elucidate the effects of FLHZF on NAFLD and explore the underlying hepatoprotective mechanisms in vivo and in vitro.METHODS HepG2 cells were treated with free fatty acid for 24 hours to induce lipid accumulation cell model.Subsequently,experiments were conducted with the different concentrations of freeze-dried powder of FLHZF for 24 hours.C57BL/6 mice were fed a high-fat diet for 8-week to establish a mouse model of NAFLD,and then treated with the different concentrations of FLHZF for 10 weeks.RESULTS FLHZF had therapeutic potential against lipid accumulation and abnormal changes in biochemical indicators in vivo and in vitro.Further experiments verified that FLHZF alleviated abnormal lipid metabolism might by reducing oxidative stress,regulating the AMPKα/SREBP-1C signaling pathway,activating autophagy,and inhibiting hepatocyte apoptosis.CONCLUSION FLHZF alleviates abnormal lipid metabolism in NAFLD models by regulating reactive oxygen species,autophagy,apoptosis,and lipid synthesis signaling pathways,indicating its potential for clinical application in NAFLD.

2D DOA Estimation of Coherent Signals with a Separated Linear Acoustic Vector-Sensor Array

In this paper, a two-dimensional(2D) DOA estimation algorithm of coherent signals with a separated linear acoustic vector-sensor(AVS) array consisting of two sparse AVS arrays is proposed. Firstly,the partitioned spatial smoothing(PSS) technique is used to construct a block covariance matrix, so as to decorrelate the coherency of signals. Then a signal subspace can be obtained by singular value decomposition(SVD) of the covariance matrix. Using the signal subspace, two extended signal subspaces are constructed to compensate aperture loss caused by PSS.The elevation angles can be estimated by estimation of signal parameter via rotational invariance techniques(ESPRIT) algorithm. At last, the estimated elevation angles can be used to estimate automatically paired azimuth angles. Compared with some other ESPRIT algorithms, the proposed algorithm shows higher estimation accuracy, which can be proved through the simulation results.

A feedback control method for phase signal demodulation in fber-optic hydrophones

In the realm of acoustic signal detection,the identification of weak signals,particularly in the presence of negative signal-to-noise ratios,poses a significant challenge.This challenge is further heightened when signals are acquired through fiber-optic hydrophones,as these signals often lack physical significance and resist clear systematic modeling.Conventional processing methods,e.g.,low-pass filter(LPF),require a thorough understanding of the effective signal bandwidth for noise reduction,and may introduce undesirable time lags.This paper introduces an innovative feedback control method with dual Kalman filters for the demodulation of phase signals with noises in fiber-optic hydrophones.A mathematical model of the closed-loop system is established to guide the design of the feedback control,aiming to achieve a balance with the input phase signal.The dual Kalman filters are instrumental in mitigating the effects of signal noise,observation noise,and control execution noise,thereby enabling precise estimation for the input phase signals.The effectiveness of this feedback control method is demonstrated through examples,showcasing the restoration of low-noise signals,negative signal-to-noise ratio signals,and multi-frequency signals.This research contributes to the technical advancement of high-performance devices,including fiber-optic hydrophones and phase-locked amplifiers.

Automatic Extraction of Medical Latent Variables from ECG Signals Utilizing a Mutual Information-Based Technique and Capsular Neural Networks for Arrhythmia Detection

From a medical perspective,the 12 leads of the heart in an electrocardiogram(ECG)signal have functional dependencies with each other.Therefore,all these leads report different aspects of an arrhythmia.Their differences lie in the level of highlighting and displaying information about that arrhythmia.For example,although all leads show traces of atrial excitation,this function is more evident in lead II than in any other lead.In this article,a new model was proposed using ECG functional and structural dependencies between heart leads.In the prescreening stage,the ECG signals are segmented from the QRS point so that further analyzes can be performed on these segments in a more detailed manner.The mutual information indices were used to assess the relationship between leads.In order to calculate mutual information,the correlation between the 12 ECG leads has been calculated.The output of this step is a matrix containing all mutual information.Furthermore,to calculate the structural information of ECG signals,a capsule neural network was implemented to aid physicians in the automatic classification of cardiac arrhythmias.The architecture of this capsule neural network has been modified to perform the classification task.In the experimental results section,the proposed model was used to classify arrhythmias in ECG signals from the Chapman dataset.Numerical evaluations showed that this model has a precision of 97.02%,recall of 96.13%,F1-score of 96.57%and accuracy of 97.38%,indicating acceptable performance compared to other state-of-the-art methods.The proposed method shows an average accuracy of 2%superiority over similar works.

Emotion Measurement Using Biometric Signal

In recent years, research on the estimation of human emotions has been active, and its application is expected in various fields. Biological reactions, such as electroencephalography (EEG) and root mean square successive difference (RMSSD), are indicators that are less influenced by individual arbitrariness. The present study used EEG and RMSSD signals to assess the emotions aroused by emotion-stimulating images in order to investigate whether various emotions are associated with characteristic biometric signal fluctuations. The participants underwent EEG and RMSSD while viewing emotionally stimulating images and answering the questionnaires. The emotions aroused by emotionally stimulating images were assessed by measuring the EEG signals and RMSSD values to determine whether different emotions are associated with characteristic biometric signal variations. Real-time emotion analysis software was used to identify the evoked emotions by describing them in the Circumplex Model of Affect based on the EEG signals and RMSSD values. Emotions other than happiness did not follow the Circumplex Model of Affect in this study. However, ventral attentional activity may have increased the RMSSD value for disgust as the β/θ value increased in right-sided brain waves. Therefore, the right-sided brain wave results are necessary when measuring disgust. Happiness can be assessed easily using the Circumplex Model of Affect for positive scene analysis. Improving the current analysis methods may facilitate the investigation of face-to-face communication in the future using biometric signals.

Special Section on High-Dimensional Signal Processing

Massive amounts of data are acquired in modern and future information technology industries such as communication,radar,and remote sensing.The presence of large dimensionality and size in these data offers new opportunities to enhance the performance of signal processing in such applications and even motivate new ones.However,the curse of dimensionality is always a challenge when processing such high-dimensional signals.In practical tasks,high-dimensional signals need to be acquired,processed,and analyzed with high accuracy,robustness,and computational efficiency.This special section aims to address these challenges,where articles attempt to develop new theories and methods that are best suited to the high dimensional nature of the signals involved,and explore modern and emerging applications in this area.

Overview on signal transduction cascades regulation roles of garlic and its bioactive constituents

High-throughput technologies in combination with modern exciting advancements in mass spectrometry-based proteomics and data analysis pipelines have empowered comprehensive characterization of disease phenotypes and their mechanistic regulation by dietary agents and bioactive molecules at unprecedented dimensionality and resolution.Extra-ordinary breakthroughs in the field of nutrigenomics have leveraged our understanding altogether to a new level of maturity.Interdisciplinary researchers have extensively analyzed health promoting and pharmacologically significant properties of garlic(Allium sativum).Importantly,garlic and its biologically active chemicals targeted oncogenic signaling cascades.In this mini-review we have attempted to summarize how garlic and its bioactive constituents regulated signal transduction cascades in cell culture studies and tumor-bearing mice.

Impact of STAT-signaling pathway on cancer-associated fibroblasts in colorectal cancer and its role in immunosuppression

Colorectal cancer(CRC)remains one of the most commonly diagnosed and deadliest types of cancer worldwide.CRC displays a desmoplastic reaction(DR)that has been inversely associated with poor prognosis;less DR is associated with a better prognosis.This reaction generates excessive connective tissue,in which cancer-associated fibroblasts(CAFs)are critical cells that form a part of the tumor microenvironment.CAFs are directly involved in tumorigenesis through different mechanisms.However,their role in immunosuppression in CRC is not well understood,and the precise role of signal transducers and activators of transcription(STATs)in mediating CAF activity in CRC remains unclear.Among the myriad chemical and biological factors that affect CAFs,different cytokines mediate their function by activating STAT signaling pathways.Thus,the harmful effects of CAFs in favoring tumor growth and invasion may be modulated using STAT inhibitors.Here,we analyze the impact of different STATs on CAF activity and their immunoregulatory role.

Machine Learning for Signal Demodulation in Underwater Wireless Optical Communications

The underwater wireless optical communication(UWOC)system has gradually become essential to underwater wireless communication technology.Unlike other existing works on UWOC systems,this paper evaluates the proposed machine learningbased signal demodulation methods through the selfbuilt experimental platform.Based on such a platform,we first construct a real signal dataset with ten modulation methods.Then,we propose a deep belief network(DBN)-based demodulator for feature extraction and multi-class feature classification.We also design an adaptive boosting(Ada Boost)demodulator as an alternative scheme without feature filtering for multiple modulated signals.Finally,it is demonstrated by extensive experimental results that the Ada Boost demodulator significantly outperforms the other algorithms.It also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power.A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio(SNR)is higher.

Prediction of the undrained shear strength of remolded soil with non-linear regression,fuzzy logic,and artificial neural network

This study aims to predict the undrained shear strength of remolded soil samples using non-linear regression analyses,fuzzy logic,and artificial neural network modeling.A total of 1306 undrained shear strength results from 230 different remolded soil test settings reported in 21 publications were collected,utilizing six different measurement devices.Although water content,plastic limit,and liquid limit were used as input parameters for fuzzy logic and artificial neural network modeling,liquidity index or water content ratio was considered as an input parameter for non-linear regression analyses.In non-linear regression analyses,12 different regression equations were derived for the prediction of undrained shear strength of remolded soil.Feed-Forward backpropagation and the TANSIG transfer function were used for artificial neural network modeling,while the Mamdani inference system was preferred with trapezoidal and triangular membership functions for fuzzy logic modeling.The experimental results of 914 tests were used for training of the artificial neural network models,196 for validation and 196 for testing.It was observed that the accuracy of the artificial neural network and fuzzy logic modeling was higher than that of the non-linear regression analyses.Furthermore,a simple and reliable regression equation was proposed for assessments of undrained shear strength values with higher coefficients of determination.

Adaptive Bistable Stochastic Resonance Based Weak Signal Reception in Additive Laplacian Noise

Weak signal reception is a very important and challenging problem for communication systems especially in the presence of non-Gaussian noise,and in which case the performance of optimal linear correlated receiver degrades dramatically.Aiming at this,a novel uncorrelated reception scheme based on adaptive bistable stochastic resonance(ABSR)for a weak signal in additive Laplacian noise is investigated.By analyzing the key issue that the quantitative cooperative resonance matching relationship between the characteristics of the noisy signal and the nonlinear bistable system,an analytical expression of the bistable system parameters is derived.On this basis,by means of bistable system parameters self-adaptive adjustment,the counterintuitive stochastic resonance(SR)phenomenon can be easily generated at which the random noise is changed into a benefit to assist signal transmission.Finally,it is demonstrated that approximately 8dB bit error ratio(BER)performance improvement for the ABSR-based uncorrelated receiver when compared with the traditional uncorrelated receiver at low signal to noise ratio(SNR)conditions varying from-30dB to-5dB.

Aszonapyrone A Isolated from Neosartorya spinosa IFM 47025 Inhibits the NF-κB Signaling Pathway Activated by Expression of the Ependymoma-Causing Fusion Protein ZFTA-RELA

Ependymoma is a rare and chemotherapy-resistant brain tumor, which has resulted in a delay in the development of drugs to treat it. A subclass of supratentorial ependymomas (ST-EPN), designated ST-EPN-zinc finger-translocation-associated (ZFTA, ST-EPN-ZFTA), exhibits the expression of a fusion protein comprising ZFTA and v-rel reticuloendotheliosis viral oncogene homolog A (RELA), an effector transcription factor of the nuclear factor-kappa B (NF-κB) pathway (ZFTA-RELA). The expression of ZFTA-RELA results in the hyperactivation of the oncogenic NF-κB signaling pathway, which ultimately leads to the development of ST-EPN-ZFTA. To identify inhibitors of the NF-κB signaling pathway activated by the expression of ZFTA-RELA, we used a doxycycline-inducible ZFTA-RELA-expressing NF-κB reporter cell line and found that extracts of the fungus Neosartorya spinosa IFM 47025 exhibited NF-κB inhibitory activity. We identified eight compounds [aszonapyrone A (2), sartorypyrone A (3), epiheveadride (4), acetylaszonalenin (5), (R)-benzodiazepinedione (6), aszonalenin (7), sartorypyrone E (8) and (Z, Z)-N,N’-(1,2-bis[(4-methoxyphenyl)methylene]-1,2-ethanediyl)bis-formamide (9)] from N. spinosa IFM 47025 culture extract using a variety of chromatographic techniques. The structures of these compounds were identified through the analysis of various instrumental data (1D, 2D-NMR, MS, and optical rotation). The NF-κB responsive reporter assay indicated that compounds 2, 3, 5, 7, and 9 exhibited inhibitory activity. We further evaluated the inhibitory activity of these compounds against the expression of endogenous NF-κB responsive genes (CCND1, L1CAM, ICAM1, and TNF) and found that compound 2 showed significant inhibitory activity. Further studies are required to elucidate the mechanism of action of compound 2, which may serve as a lead compound for the development of a novel therapy for ST-EPN-ZFTA.

Sounding the alarm:Functionally referential signaling in Azure-winged Magpie

Functionally referential signals are a complex form of communication that conveys information about the external environment.Such signals have been found in a range of mammal and bird species and have helped us understand the complexities of animal communication.Corvids are well known for their extraordinary cognitive abilities,but relatively little attention has been paid to their vocal function.Here,we investigated the functionally referential signals of a cooperatively breeding corvid species,Azure-winged Magpie(Cyanopica cyanus).Through field observations,we suggest that Azure-winged Magpie uses referential alarm calls to distinguish two types of threats:’rasp’ calls for terrestrial threats and ’chatter’ calls for aerial threats.A playback experiment revealed that Azure-winged Magpies responded to the two call types with qualitatively different behaviors.They sought cover by flying into the bushes in response to the ’chatter’ calls,and flew to or stayed at higher positions in response to ’rasp’ calls,displaying a shorter response time to ’chatter’ calls.Significant differences in acoustic structure were found between the two types of calls.Given the extensive cognitive abilities of corvids and the fact that referential signals were once thought to be unique to primates,these findings are important for expanding our understanding of social communication and language evolution.