Effects of Anti-Seizure Medication on Neuregulin-1 Gene and Protein in Patients with First-Episode Focal Epilepsy.

Introduction: Neuregulin-1 (NRG-1) appears to play a role in the pathogenesis of several neuropsychiatric disorders, including epilepsy. We conducted a study to investigate the effect of anti-seizure medication on NRG-1 mRNA and NRG-1 protein levels in patients with first-episode focal epilepsy. Methods: The levels of NRG-1 mRNA isoforms (type I, II, III, and IV) in peripheral blood mononuclear cells (PBMCs) of 39 healthy controls, 39 first-episode focal epilepsy patients before anti-seizure medication (ASM) therapy and four weeks after administration of ASM were measured by RT-qPCR, and the levels of NRG-1 protein in the serum of samples of each group were determined using ELISA. In addition the relationship between efficacy, NRG-1 mRNA expression, and NRG-1 protein expression was analyzed. Results: The levels of NRG-1 mRNA progressively increased in patients with first-episode focal epilepsy treated with ASM and were distinctly different from those before medication, but remained lower than in healthy controls (all P < 0.001). Before and after drug administration, NRG-1 protein levels were substantially higher in epileptic patients than in healthy controls, and no significant changes were detected with prolonged follow-up (P < 0.001). Patients with epilepsy who utilized ASM were able to control seizures with an overall efficacy of 97.4%. There was a negative correlation between NRG-1 mRNA levels and efficacy: as NRG-1 mRNA levels increased, seizures reduced (all P < 0.05). Conclusion: Our research indicated that NRG-1 may play a role in the pathophysiology of epilepsy. NRG-1 mRNA may provide ideas for the discovery of novel epilepsy therapeutic markers and therapeutic targets for novel ASM.

A sensitive spectrum entropy-assisted Bayesian online anomaly inference method for bearing incipient degradation dynamic detection.

Incipient degradation dynamic detection is crucial for preventing serious accidents in the context of rolling bearing online automatic condition monitoring and preventive maintenance. This article presents a novel framework, cyclostationarity-sensitive spectrum fuzzy entropy-assisted Bayesian online anomaly inference (CSFE-BOAI), to address this challenge. A new health index, CSFE, is first defined by performing the fuzzy entropy measure on the extracted cyclostationarity-sensitive spectra to promote incipient-degradation sensitivity and robustness to interferences. Next, the BOAI procedure for detecting anomalies in continuously arriving CSFEs is derived using the robust generalized T-distribution as the underlying predictive distribution. Eventually, the CSFE-BOAI framework is constructed for bearing incipient degradation dynamic detection, which possesses double confirmation of valid anomalies through the Pauta criterion and cyclostationarity-sensitive spectrum. Experimental verifications are performed on two typical bearing degradation data and one healthy-to-incipient defect data. Results show that CSFE-BOAI enables effective and timely incipient degradation alarm and identification of rolling bearings. The comparisons with the eight advanced health indexes and four anomaly detection approaches demonstrate that CSFE-BOAI has the lowest false and missed alarms and therefore has good deployment potential for practical applications.

Mitochondrial complex I inhibition by homoharringtonine: A novel strategy for suppression of chronic myeloid leukemia.

Chronic myeloid leukemia (CML) is a hematologic malignancy predominantly driven by the BCR-ABL fusion gene. One of the significant challenges in treating CML lies in the emergence of resistance to tyrosine kinase inhibitors (TKIs), especially those associated with the T315I mutation. Homoharringtonine (HHT) is an FDA-approved, naturally-derived drug with known anti-leukemic properties, but its precise mechanisms of action remain incompletely understood. In this study, we rigorously evaluated the anti-CML activity of HHT through both in vitro and in vivo assays, observing substantial anti-CML effects. To elucidate the molecular mechanisms underpinning these effects, we performed proteomic analysis on BCR-ABL T315I mutation-bearing cells treated with HHT. Comprehensive pathway enrichment analysis identified oxidative phosphorylation (OXPHOS) as the most significantly disrupted, suggesting a key role in the mechanism of action of HHT. Further bioinformatics exploration revealed a substantial downregulation of proteins localized within mitochondrial complex I (MCI), a critical OXPHOS component. These results were validated through Western blot analysis and were supplemented by marked reductions in MCI activity, ATP level, and oxygen consumption rate (OCR) upon HHT exposure. Collectively, our results shed light on the potent anti-CML properties of HHT, particularly its effectiveness against T315I mutant cells through MCI inhibition. Our study underscores a novel therapeutic strategy to overcome BCR-ABL T315I mutation resistance, illuminating a previously uncharted mechanism of action for HHT.

Knowledge correlation graph-guided multi-source interaction domain adaptation network for rotating machinery fault diagnosis.

Leveraging generalized knowledge from multiple source domains with rich labels to the target domain without labeled data is a more realistic and challenging issue compared with single-source domain adaptation. Furthermore, the distribution discrepancies between each source domain and the expansion of data categories increase the difficulty of aligning each source domain with the target domain. To alleviate these issues, a knowledge correlation graph-guided multi-source interaction domain adaptation network (KCGMIDAN) is developed for rotating machinery fault diagnosis. Firstly, a random mini-batch is randomly selected to update comprehensive feature representations (CFR) extracted from each data category across all domains, thus promoting the knowledge interaction of acquired CFR between the current and the next epochs. Then, a knowledge correlation graph (KCG) is established on all CFR to boost knowledge propagation among various domains. To improve the compactness of characteristics within the same category and the separation of various categories, two losses are designed in this procedure to place constraints on the relationships between categories. Finally, query samples are added into KCG to construct the extended KCG, and the recognition of samples is completed by using built deep graph network based on the extended KCG. Extensive experimental results verify that KCGMIDAN can achieve better recognition performance than existing methods.

Multiband weights-induced periodic sparse representation for bearing incipient fault diagnosis.

Faulty impulses from incipient damaged bearings are typically submerged in harmonics, random shocks, and noise, making incipient fault diagnosis challenging. The prerequisite to this problem is the robust estimation of faulty impulses; thus, this paper proposes a multiband weights-induced periodic sparse representation (MwPSR) method. Firstly, a multiband weighted generalized minimax-concave induced sparse representation (MwGSR) approach is presented to accelerate the sparse approximation process and eliminate the interference components. A new indicator, coined the frequency-weighted energy operator spectrum's kurtosis-to-entropy ratio, is defined to construct the MwGSR's weights to accentuate faulty impulses. Secondly, to enhance the periodicity of the estimated impulses, a fault period decision strategy with an improved periodic target vector is developed and embedded into MwGSR to form MwPSR eventually. Detailed simulations and experiments demonstrate that MwPSR can achieve periodic sparsity with high accuracy and robustness and is reliable for incipient bearing fault diagnosis.

Elevated peripheral Neuregulin-1 protein levels in non-medicated focal epilepsy patients.

INTRODUCTION: The Neuregulin-1 (NRG-1) gene has been identified as a susceptibility gene for schizophrenia. Schizophrenia and epilepsy shared some common clinical manifestations and common pathogenesis. Therefore, it is necessary to explore whether there is a relationship between NRG-1 and epilepsy. This study aimed to investigate the expression level of NRG-1 in peripheral blood of non-medicated patients with first-onset focal epilepsy. METHODS: A total of 83 non-medicated first-onset focal epilepsy patients and 80 healthy controls were involved in this study. Serum NRG-1 protein levels were determined by ELISA. RESULTS: Compared to healthy controls (mean ± SD, 3.97 ± 2.37), NRG-1 protein levels were statistically significantly higher in patients (mean ± SD, 5.37 ± 3.48) (P = 0.006). CONCLUSIONS: Our findings suggest that NRG-1 protein may play a role in the pathogenesis of focal epilepsy, which provides insights into the search for epilepsy potential therapeutic markers and new drug treatment targets.

Caffeic acid phenethyl ester protects against doxorubicin-induced cardiotoxicity and increases chemotherapeutic efficacy by regulating the unfolded protein response.

Doxorubicin (Dox) is an efficient drug used in breast cancer chemotherapy. However, the clinical application of Dox in cancer treatment is limited due to its cardiotoxicity. Caffeic acid phenethyl ester (CAPE) is a critical bioactive ingredient of honeybee propolis that possesses various beneficial pharmacological properties, such as antioxidant and anticancer activities. Here, we aimed to investigate the protective effect of CAPE on Dox-induced cardiotoxicity and its anti-breast cancer effects. CAPE significantly ameliorated Dox-induced toxicity in H9c2 cells and in a mouse model. Mechanistically, Dox caused endoplasmic reticulum (ER) dysfunction characterized by the activation of the unfolded protein response (UPR) and upregulation of Bax proteins, and CAPE attenuated the Dox-induced UPR in H9c2 cells. In contrast, CAPE significantly enhanced Dox-induced cytotoxicity in human breast cancer cells by upregulating the Dox-induced UPR; it also markedly suppressed tumor growth in 4T1 cancer-bearing BALB/c mice. In conclusion, CAPE could be used as a promising therapy for patients with cancer receiving Dox treatment.

Theory of the Tertiary Instability and the Dimits Shift from Reduced Drift-Wave Models.

Tertiary modes in electrostatic drift-wave turbulence are localized near extrema of the zonal velocity U(x) with respect to the radial coordinate x. We argue that these modes can be described as quantum harmonic oscillators with complex frequencies, so their spectrum can be readily calculated. The corresponding growth rate γ_{TI} is derived within the modified Hasegawa-Wakatani model. We show that γ_{TI} equals the primary-instability growth rate plus a term that depends on the local U^{''}; hence, the instability threshold is shifted compared to that in homogeneous turbulence. This provides a generic explanation of the well-known yet elusive Dimits shift, which we find explicitly in the Terry-Horton limit. Linearly unstable tertiary modes either saturate due to the evolution of the zonal density or generate radially propagating structures when the shear |U^{'}| is sufficiently weakened by viscosity. The Dimits regime ends when such structures are generated continuously.

Wave kinetics of drift-wave turbulence and zonal flows beyond the ray approximation.

Inhomogeneous drift-wave turbulence can be modeled as an effective plasma where drift waves act as quantumlike particles and the zonal-flow velocity serves as a collective field through which they interact. This effective plasma can be described by a Wigner-Moyal equation (WME), which generalizes the quasilinear wave-kinetic equation (WKE) to the full-wave regime, i.e., resolves the wavelength scale. Unlike waves governed by manifestly quantumlike equations, whose WMEs can be borrowed from quantum mechanics and are commonly known, drift waves have Hamiltonians very different from those of conventional quantum particles. This causes unusual phase-space dynamics that is typically not captured by the WKE. We demonstrate how to correctly model this dynamics with the WME instead. Specifically, we report full-wave phase-space simulations of the zonal-flow formation (zonostrophic instability), deterioration (tertiary instability), and the so-called predator-prey oscillations. We also show how the WME facilitates analysis of these phenomena, namely, (i) we show that full-wave effects critically affect the zonostrophic instability, particularly its nonlinear stage and saturation; (ii) we derive the tertiary-instability growth rate; and (iii) we demonstrate that, with full-wave effects retained, the predator-prey oscillations do not require zonal-flow collisional damping, contrary to previous studies. We also show how the famous Rayleigh-Kuo criterion, which has been missing in wave-kinetic theories of drift-wave turbulence, emerges from the WME.