Search Results (1,637)

Mitochondrial dysfunction in colonic smooth muscle cells (SMCs) is closely associated with impaired gut motility in functional constipation (FC), but the underlying molecular mechanisms remain incompletely understood. The mitochondrial unfolded protein response (UPR^mt) is a critical pathway for maintaining mitochondrial proteostasis, and heat shock factor 1 (HSF1) acts as an important upstream regulator of this response. In the present study, we employed a loperamide-induced FC mouse model, combined with single-cell transcriptomic, molecular, and functional analyses to characterize the HSF1-UPR^mt pathway in colonic SMCs and to investigate its role in FC. Single-cell transcriptomic analysis of colon tissue from FC mice revealed marked downregulation of UPR^mt-associated genes in colonic SMCs. Immunofluorescence, Western blotting, and RT-qPCR analyses of colonic tissue confirmed that HSF1 expression was reduced in colonic SMCs, along with the downregulation of the UPR^mt components, including HSP60, mtHSP70, and LONP1. These molecular changes were accompanied by mitochondrial structural damage, seen by transmission electron microscopy, and by functional impairments, including reduced mitochondrial membrane potential, elevated mtROS production, decreased ATP levels, and diminished activities of respiratory chain complexes I–V. AAV9-mediated overexpression of HSF1 reactivated the UPR^mt pathway, improved mitochondrial function, and ameliorated constipation, whereas shRNA-mediated knockdown of HSF1 further suppressed UPR^mt activity and aggravated mitochondrial damage, indicating that HSF1 bidirectionally regulates this pathway. Complementary experiments in primary colonic SMCs confirmed that this regulatory mechanism operates in a cell-autonomous manner, as modulation of HSF1 expression produced corresponding changes in the UPR^mt pathway, in the expression of mitochondrial respiratory chain complex subunits (ATP5A, NDUFA9, COX1, SDHA, UQCRC1), and in ATP production, mirroring the in vivo findings. Collectively, these results demonstrate that HSF1 plays a pivotal role in maintaining mitochondrial homeostasis in colonic SMCs through regulation of the UPR^mt pathway and that HSF1 dysfunction is closely associated with slowed gut motility in FC. These findings offer a new mechanistic perspective on FC and point to the HSF1–UPR^mt axis as a potential therapeutic target. Full article

Introduction: Stenotrophomonas maltophilia (S. maltophilia) has emerged as an important opportunistic pathogen. It is resistant to most available antibiotics due to its intrinsic resistance, leaving only some antibacterial agents as possible therapeutic options, which is further complicated by acquired mechanisms of antimicrobial resistance. This study aimed to provide a comprehensive genomic characterization of clinical S. maltophilia complex (Smc) isolates, focusing on molecular characterization of its resistance and virulence, since studies tackling this are scarce in Oman. Methods: This study is a prospective cross-sectional study, in which a total of 21 clinical isolates of Smc were collected from different clinical samples and further characterized using Whole Genome Sequencing. Results: Besides S. maltophilia, the isolates included S. hibiscicola, S. pavanii, and S. muris for the first time in Oman. All isolates were found to be susceptible to cefiderocol, levofloxacin, and minocycline. Sequence types (STs) were diverse among the isolates, with more than half of the isolates showing new STs with novel alleles. Additionally, blaOXA-2, sul1, and the recently described aac(6′)-Iap and aph(9)-Ic were detected among the isolates. Moreover, virulence-associated genes (smf-1, pilT, pilQ, gpmA, rmlA, spgM, stmPr1, plcN, clpP, and katE) were highly conserved across all isolates. Mobile genetic elements were detected in most of the isolates (76.20%). Conclusions: The collected isolates showed high ST diversity and showed no specific pattern in terms of antibiotic susceptibility and resistance genes. More studies are needed to establish relationships between the different members of the Smc and the different molecular resistome and virulome. Full article

Traditional permanent magnet synchronous motor (PMSM) control systems rely on mechanical position sensors for high-precision rotor position and speed information, which increases hardware complexity, raises system cost, reduces reliability, and limits adaptability to harsh environments. To overcome the above limitations, this paper proposes a novel high-performance sensorless speed control strategy for PMSMs, which is constructed based on a non-singular terminal sliding mode observer (NTSMO) and a non-singular terminal sliding mode controller (NTSMC). First, an improved fast power reaching law (IFPRL) is proposed, which consists of a variable exponential reaching term and a power reaching term. Specifically, the gain of the exponential reaching term is dynamically adjusted by the absolute value of the sliding mode switching function, enabling the reaching law to operate in two different modes throughout the entire convergence process of the system state. Moreover, the introduction of scaling coefficient c compensates for the performance degradation caused by variations in the range of sliding mode surfaces (SMSs) in different systems. The proposed IFPRL not only effectively mitigates the inherent chattering issue, it also expedites the rate at which the system state converges to its SMS. On this basis, both the NTSMO for rotor position observation and the NTSMC for speed closed-loop control are designed by embedding the proposed IFPRL into the framework of non-singular terminal sliding mode control theory. Finally, the effectiveness of the proposed method is validated through numerical simulations and experimental tests. Experimental results demonstrate that the proposed IFPRL-based NTSMC + NTSMO scheme reduces the root mean square error (RMSE) of speed control by 2.7% relative to the traditional SMC + SMO method. The proposed method realizes reliable sensorless speed control for PMSMs and exhibits superior dynamic response, higher control accuracy, and stronger robustness against disturbances. Full article

Flexible manipulators have attracted increasing attention due to their lightweight structure, high flexibility, and energy efficiency, for which they are suitable for delicate and high-precision tasks. However, their control remains a problem because of strong nonlinearities and uncertainties in the system. Based on the trajectory tracking control problem of the single-link flexible manipulator (SLFM) system, this paper proposes a fractional order adaptive neural network control scheme for SLFM under symmetric time-varying full-state constraints. Firstly, a fractional-order dynamic model is established to better capture the inherent memory and nonlinear characteristics of the SLFM. Secondly, an adaptive radial basis function (RBF) neural network-based control scheme is developed within a backstepping framework, and a symmetric time-varying barrier Lyapunov function (BLF) is incorporated to guarantee that all system states remain within predefined bounds. In addition, command filters are introduced to avoid the “explosion of complexity” caused by backstepping. Next, theoretical analysis based on Lyapunov stability theory is provided to demonstrate that all signals in the closed-loop system are bounded, while the tracking error converges to a small neighborhood of zero. Finally, the proposed method is applied as an SLFM: the simulation results show that the presented controller has excellent control performance, the tracking error is less than 0.02 rad, and the tip polarization angle of the system does not exceed 0.045 rad. Additionally, the comparison with the recent DSC and SMC methods also shows that the designed controller behaves with less tracking error, which in return validates the effectiveness and superiority of the proposed control strategy. Full article

The increasing integration of renewable energy sources into interconnected multi-area power systems (IMAPSs) has led to a significant reduction in synchronous inertia, making frequency regulation considerably more challenging. While existing studies have explored the use of integral sliding mode load frequency control (ISMLFC) schemes to stabilize area frequency and tie-line power flows in IMAPSs, these approaches predominantly rely on conventional two-phase sliding mode control. Such methods, however, have demonstrated notable limitations in maintaining the stability of IMAPSs under increasingly complex operating conditions. In addition, all the IMAPS state variables must be measured, which can cause difficulty in real IMAPS applications. Therefore, this study proposes a novel load frequency control (LFC) strategy that coordinates the single-phase sliding mode control and state observer methods to solve these above limitations. First, a dynamic IMAPS model with single phase sliding mode control based on state observer scheme is established under renewable resource uncertainties and load disturbances. Then, a novel linear matrix inequality (LMI) based on Lyapunov functional is constructed to analyze the stability of the IMAPS. Furthermore, the decentralized single-phase sliding mode load frequency control (DSPSMLFC) method is developed for the LFC of the ISMLFC. Finally, three testing scenarios are employed to verify the efficiency and advantage of the proposed DSPSMLFC approach in MATLAB/Simulink R2023a. The simulation results confirm that the proposed DSPSMLFC scheme can improve the LFC of the IMAPS under renewable resource uncertainties and load disturbances. Full article

High-performance control of surface-mounted permanent magnet synchronous motors (SPMSMs) is critical for unmanned aerial vehicle (UAV) rotor servo systems, which demand fast dynamic response, high steady-state accuracy, and strong robustness against complex disturbances. However, conventional sliding mode control (SMC) methods often suffer from inherent issues like integral windup, persistent chattering, and sensitivity to parameter variations, limiting their effectiveness in such challenging applications. To address these limitations, this paper proposes a novel composite control strategy. The method integrates an improved terminal integral sliding mode controller (ITISMC) with an adaptive super-twisting reaching law (ADSTA) and a terminal integral sliding mode observer (TISMO). The key innovations include: (1) a redesigned sliding surface incorporating a smooth nonlinear function to suppress chattering and a variable-gain integral term to mitigate integral windup; (2) an adaptive reaching law that dynamically adjusts its gains based on the system state to balance convergence speed and chattering suppression; and (3) a disturbance observer that provides real-time estimation and feedforward compensation of total disturbances, significantly enhancing robustness. The proposed ITISMC-ADSTA-TISMO strategy was implemented and validated on a TMS320F28379D DSP-based experimental platform. Comparative results demonstrate its superiority over benchmark methods (e.g., SMC-STA). Key achievements include a rapid no-load startup time of 0.45 s, high steady-state precision with speed fluctuations suppressed to only 3 rpm, and superior disturbance rejection capability under sudden load changes, sinusoidal disturbances, and parameter perturbations. The method also yields favorable q-axis current response. These results confirm that the proposed strategy offers a high-performance, practical solution for advanced UAV servo control systems. Full article

This paper presents a robust fault-tolerant control (FTC) strategy for a multiphase PMSM-based propulsion system. The proposed approach combines an innovative super-twisting sliding mode controller (IST SMC) with a fault-tolerant model of the machine when an open-circuit fault occurs. The electrical propulsion system mainly has a two-line structure with a single DC source, a five-leg inverter and a Five-Phase Permanent Magnet Synchronous Motors (5-Φ PMSM), suitable for marine propulsion applications. Two main scenarios are investigated in this work. Firstly, if an open-phase fault occurs in one of the two 5-Φ PMSMs, a reconfiguration step of the machine control is applied in order to improve the performance of the propulsion system and to ensure the continuity of operation. Then, if the fault occurs in one of the two inverters, the faulty one is removed and the electrical series connection is made between the two machines, where they are powered by a single five-arm inverter, thus ensuring the continuity of operation of the system. Considering these two scenarios, a comparative analysis is made between the IST SMC and the classical PI controllers in terms of robustness to uncertainties, external disturbances and tracking accuracy for healthy and faulty operation modes, and during transient states. Full article

The increasing penetration of nonlinear loads aggravates grid harmonic distortion and imposes higher requirements on the control performance of the shunt active power filter (SAPF). To address the problems of fixed parameters in conventional PI controllers and the dependence of existing improved methods on accurate models with relatively high computational complexity, this paper proposes a TD3-based model-free adaptive control method for online coordinated tuning of dual-loop PI parameters in the SAPF system. The proposed method dynamically adjusts PI parameters through agent–environment interaction without requiring an accurate system model or a complex control structure. Simulation results show that the proposed strategy outperforms fixed-parameter PI control, PI-SMC, and DDPG methods in both steady-state and dynamic performance, and maintains good control performance under unseen composite disturbances such as capacitive inrush and load variation. RT-LAB-based hardware-in-the-loop (HIL) validation further demonstrates that the proposed method can achieve effective harmonic compensation and DC-link voltage regulation on a real-time simulation platform. Meanwhile, during online deployment, only Actor-network forward inference is required to update the PI parameters, indicating a low additional computational burden and engineering implementation potential for SAPF real-time control systems. Full article

Maximum power point tracking (MPPT) is a critical function for maximizing energy extraction in photovoltaic (PV) systems. Due to the inherently dynamic nature of the maximum power point under varying irradiance conditions, achieving fast convergence, low steady-state oscillations, and high tracking efficiency remains a challenging research problem. This paper proposes a hybrid ANN-based MPPT strategy for photovoltaic systems operating under rapidly changing environmental conditions. The proposed approach integrates a rule-based operating-condition estimation stage with a recurrent ANN-based control stage, enabling adaptive duty-cycle generation using measured PV voltage and current signals. Unlike conventional MPPT techniques, the proposed method utilizes operating-region estimation together with an extended ANN input feature vector and a recurrent backpropagation neural network to improve dynamic tracking performance under abrupt irradiance variations. In addition, a composite loss function is adopted to enhance tracking accuracy, guidance consistency, and control smoothness. The ANN is initially trained offline and subsequently refined online using lightweight incremental adaptation to maintain effective operation with a low computational burden. The proposed MPPT strategy is evaluated against P&O, FLC, and SMC. Simulation results demonstrate improved tracking performance, faster dynamic response, and reduced steady-state oscillations under abrupt irradiance variations. Full article

The increasing integration of photovoltaic (PV) systems and nonlinear loads intensifies harmonic distortion and reactive power imbalance in modern power networks. Conventional shunt active power filters (SAPFs) often employ control strategies that perform poorly under uncertain and dynamic grid conditions. This paper develops a hybrid sliding mode control with disturbance observer (SMC+DOB) technique for a PV-integrated SAPF to achieve effective harmonic mitigation, reactive power compensation, and enhanced system robustness. The study models the PV-SAPF system in MATLAB/Simulink (R2025b), where the SMC ensures robust current tracking, while the DOB estimates and suppresses unknown disturbances in real-time. The controller’s performance is evaluated under varying nonlinear and reactive load conditions, as per IEEE 519-2014 standards. Simulation results show that the proposed SMC+DOB scheme reduces total harmonic distortion (THD) by 96.7%—from 31.45% to 1.05%—while maintaining DC-link voltage stability and unity power factor. The integrated control architecture enhances the dynamic performance of SAPF, providing superior harmonic suppression, fast transient recovery, and improved grid stability for PV-connected systems. Full article

This paper presents an experimental comparison between model-based and model-free trajectory-tracking control strategies applied to an omnidirectional mobile robot platform. Classical model-based controllers, including Proportional-Integral-Derivative (PID), Generic Model Control (GMC), and Sliding Mode Control (SMC), are evaluated against a Model-Free Control (MFC) strategy based on an intelligent Proportional–Integral–Derivative (iPID) regulator. An empirical integrator-with-delay model is identified from experimental data and used to design model-based controllers. All strategies were implemented on the Festo Robotino platform under comparable operating conditions and evaluated using circular, lemniscate, and square trajectories. Controller performance is assessed using the Integral of Squared Error (ISE), the settling time ($T_s$), and the control effort quantified by the Integral of Squared Control Output (ISCO). Experimental results show that the model-free controller provides the best overall tracking performance, achieving tracking error reductions of approximately $25\%$ to $90\%$ compared with the evaluated model-based controllers, while maintaining a competitive control effort. The study provides a unified experimental benchmark comparing model-based and model-free control paradigms on the Robotino platform, highlighting the practical advantages of model-free control for robotic systems affected by uncertainties and nonlinearities. Full article

Vascular smooth muscle cell (VSMC) control of phenotypic states through regulation of contractile gene expression is critical for vascular homeostasis and for participation in pathological vascular remodeling, such as atherosclerosis. Cohorts of molecular and cellular processes, including transcriptional and post-transcriptional repression of VSMC contractile genes, context-dependent activation of pathological gene sets, proliferation, and migration, coordinately contribute to SMC phenotypic plasticity. Epigenetic (histone post-translational modifications, DNA methylation) and epitranscriptomic (RNA modifications) mechanisms have been implicated in the activation or repression of the VSMC gene repertoire. Among them, methylation exhibits complex, multifaceted, and, in some instances, opposing roles in regulating gene activation. Methylation-mediated epigenetic programming complexity stems from the multiplicity of methylation substrates and enzymes regulating methylation and demethylation. The role and relevance of methylation in regulating VSMC phenotype are often restricted to a given methylation substrate, methylation enzymes, or subsets of genes. The goal of this review is to integrate in vitro and in vivo studies that uncover methylation-mediated VSMC regulation, to assess the overall contribution of methylation-regulating enzymes. We will explore how atherosclerosis-relevant upstream regulatory mechanisms and rate-limiting cofactors of methylation enzymes, including inflammation, metabolism, and hypoxia, affect methylation enzyme activity. Lastly, we will discuss emerging evidence for non-canonical mechanisms by which methylation enzymes may regulate gene expression and their potential role in regulating VSMC phenotype and function. Full article

This study presents a novel hierarchical hybrid control architecture for the attitude stabilization of a 3-Degree-of-Freedom (3-DOF) hover system. Operating on a linearized state-space model, a Linear Quadratic Regulator (LQR) is deployed as the optimal inner-loop core to guarantee baseline multi-variable stability. To dramatically improve transient performance and suppress high-frequency oscillations, Sliding Mode Control (SMC) and Super-Twisting Sliding Mode Control (STSMC) are incorporated not as conventional additive inputs, but as dynamic reference-reshaping supervisory mechanisms in the outer loop. This structural decoupling preserves the optimal characteristics of the LQR while effectively attenuating chattering, thereby preventing physical actuator fatigue. Furthermore, the Big Bang–Big Crunch (BB-BC) metaheuristic algorithm is employed to systematically optimize the design parameters of the supervisory layers, enabling effective steady-state error reduction with a remarkably low computational cost. Comparative evaluations demonstrate that the proposed LQR-STSMC framework significantly accelerates system responsiveness, reducing rise times by approximately 80% to 90% and consistently lowering settling times across all operational axes while achieving a reduction of up to two orders of magnitude in overall tracking errors (ITAE) relative to the baseline LQR. Although evaluations involving Model Predictive Control (MPC) demonstrate improvements in transient response and a reduction in total error compared to the standard LQR, the proposed LQR-STSMC architecture exhibits significantly better overall performance and superior disturbance rejection capabilities. Simulation results under continuous aerodynamic perturbations (wind disturbances) confirm that the proposed hierarchical methodology effectively eliminates steady-state offsets, fundamentally outperforming both classical LQR and MPC in terms of robustness, precision, and ultra-fast transient performance. Full article

Kombucha quality is largely governed by polyphenol transformation during fermentation. However, interaction between substrate composition and microbial communities regulating phenolic transformation and quality formation remains unclear. In this study, six tea substrates (white, green, yellow, black, oolong, and mint tea) were fermented using three defined microbial communities (SMC1-SMC3) and a traditional symbiotic culture of bacteria and yeast (SCOBY) to evaluate carbon metabolism, phenolic transformation, antioxidant activity, and sensory quality. After 10 d of fermentation, SMC2 and SMC3, containing acetic acid bacteria, showed stronger acidification (pH 2.2–2.5) and lower ethanol (0.34–0.52 mg/mL) than SMC1 (13.09–15.88 mg/mL). Phenolic transformation was substrate-dependent: total phenolics and flavonoids decreased in green tea, both increased in white tea, while flavonoids increased in oolong and black tea. Meanwhile, rutin decreased in white and green tea, whereas gallic acid accumulated in yellow, black, and oolong teas and was positively correlated with antioxidant activity. Sensory evaluation showed SMC3 achieved higher overall acceptability in most substrates, whereas SCOBY performed best in mint tea. These findings indicate substrate-microbiota interactions play a key role in phenolic transformation and quality formation in kombucha. Rational matching of tea substrates with defined microbial communities enables coordinated optimization of antioxidant activity, ethanol control, and sensory quality. Full article

The Structural Maintenance of Chromosomes complex 5/6 (SMC-5/6) safeguards genome stability by coordinating DNA replication, repair, and chromosome organization. Although prior studies have advanced understanding of SMC-6, a domain-resolved view of its functions in vivo, particularly in multicellular organisms, remains incomplete. Because the non-SMC subunit NSE-1 localizes at the SMC-5/6 head interface and reflects complex integrity, we used NSE-1::GFP nuclear localization as a visual readout in an ethyl methanesulfonate (EMS)-based forward genetic screen in Caenorhabditis elegans (C. elegans). We identified three new smc-6 alleles—smc-6(wsh34), smc-6(wsh35), and smc-6(wsh36) through single-nucleotide polymorphism (SNP) mapping and whole-genome sequencing. smc-6(wsh34) and smc-6(wsh35) affect the N-terminal ATPase domain, whereas smc-6(wsh36) lies in the hinge region. ATPase-domain mutants exhibited reduced fertility, decreased progeny viability, hypersensitivity to methyl methanesulfonate and cisplatin, and strong induction of the pro-apoptotic genes egl-1 and ced-13. In contrast, the hinge mutant exhibited moderate fertility defects and partial sensitivity to DNA damage reagents. Structural modeling suggests that the R103 truncation disrupts the SMC-5/6 head interface, whereas the P514L substitution alters hinge dynamics. Together, these findings reveal a functional hierarchy in SMC-6, with the ATPase domain governing repair-associated energy-dependent processes and the hinge maintaining structural integrity. Full article