Search Results (381)

Plasma cell myeloma (PCM) is classified as a blood cancer and is characterized by the abnormal proliferation of plasma cells in the bone marrow and the excessive production of monoclonal immunoglobulins, which lead to permanent damage to vital organs. Although treatment strategies have improved with the development of proteasome inhibitors (PIs), immunomodulatory drugs (IMiDs), and monoclonal antibodies (mAbs), PCM remains an incurable disease due to its molecular heterogeneity and the development of drug resistance. In this review, we discuss the biochemical and molecular foundations underlying the diagnosis and treatment of PCM, emphasizing both traditional and advanced approaches. Classical methods such as serum protein electrophoresis (SPEP), immunofixation electrophoresis (IFE), and serum free light chain (sFLC) determination are highlighted alongside their integration with highly sensitive techniques like mass spectrometry (MS) and next-generation sequencing (NGS). Special attention is given to nanotechnology-based systems, including liposomes, polymeric nanoparticles (NPs), dendrimers, and hybrid nanocapsules, which enable controlled drug release, targeted delivery, and the minimization of systemic toxicity. Increasingly, nanomaterials are being shown to greatly enhance the biodistribution and pharmacokinetics of anticancer drugs, leading to improved therapeutic effects and escaping resistance mechanisms by employing multifunctional strategies that include dual drug co-encapsulation, pH-sensitive release and theranostic applications. Furthermore, the integration of nanotechnology with immunotherapy platforms represents a paradigm shift toward precision and personalized medicine for the treatment of PCM. Overall, this review views nanotechnology as an enabling technology to improve therapeutic effectiveness, minimize toxicity and open new avenues toward next-generation smart and personalized therapeutics for the treatment of PCM. Full article

Diabetic kidney disease (DKD) is a major complication of type 2 diabetes mellitus (T2DM) and a leading cause of morbidity and mortality. Both metabolic and inflammatory pathways have emerged as potential sources of biomarkers that may improve DKD detection and treatment. This study investigated the relationship between gut-derived metabolites, such as acylcarnitines (ACs), uremic toxins (UTs), polyol pathway intermediates (PIs), and amino acid derivatives (AADs), and renal inflammation markers, detected in serum and urine. It included 20 healthy controls and 90 patients with T2DM, divided into normoalbuminuria, microalbuminuria, and macroalbuminuria. Serum and urine metabolites were analyzed using untargeted and targeted metabolomic assessments, whereas inflammatory markers were quantified using the ELISA technique. Statistical analysis consisted of descriptive statistics followed by univariable and multivariable linear regression analyses. Our findings revealed that serum AADs contribute to renal fibrosis progression, whereas urinary AADs indicate impaired tubular reabsorption in inflammatory conditions. Additionally, UTs and PIs are linked to inflammatory processes mediated by TNF-α but not by early renal fibrosis, whereas serum ACs appear to modulate immune responses, exerting pro-inflammatory and cytotoxic effects on tubular epithelial cells in early DKD. Thus, the metabolic and inflammatory pathways are tightly interconnected and synergistically contribute to the pathogenesis of early DKD. Full article

Excessive melanin production causes hyperpigmentation disorders such as freckles, melasma, and age spots, affecting appearance and quality of life. Tyrosinase is the key enzyme controlling melanin synthesis, and natural compounds are being explored as effective tyrosinase inhibitors. Fisetin, a dietary flavonoid found in fruits and vegetables like grapes and onions, is known for its anti-inflammatory and anticancer properties, but its anti-melanogenic activity remains unclear. This study demonstrated that fisetin, up to 60 μM, is non-toxic and significantly decreases tyrosinase activity and melanin content in human melanoma cells. Mechanistically, fisetin activates PKCα, leading to phosphorylation and degradation of β-catenin, thereby downregulating MITF expression. Additionally, it activates ERK and AKT/GSK3β pathways, promoting ubiquitination and proteasomal degradation of MITF, resulting in reduced levels of tyrosinase, TRP-1, and TRP-2. The proteasome inhibitor MG132 confirmed that fisetin accelerates β-catenin and MITF degradation. Additionally, inhibition of the PI3K/AKT pathway by LY294002 or the ERK pathway by PD98059 reversed fisetin’s reduction of tyrosinase activity and melanin synthesis, further verifying the participation of these pathways. Computational docking integrated with deep learning-based CNN scoring revealed that fisetin interacts with PKCα, β-catenin, tyrosinase, and TYRP1. Collectively, these findings suggest that fisetin exerts multi-targeted inhibitory effects on melanogenesis, highlighting its potential as a therapeutic and cosmetic agent for hyperpigmentation. Full article

Cancer is one of the most feared diseases in the world. Its incidence has increased steadily in recent years; it represents a significant burden of disease and is among the leading causes of death globally. Consequently, the search for novel compounds that serve as potential candidates for pharmacotherapeutic options and that can be used as treatments or adjuvants to control this disease is urgent. In this context, plant-derived phenolic diterpenes have shown antitumor activity against several types of cancer, inhibiting DNA synthesis, lipid metabolism, and bioenergetics of these cells, among other mechanisms, making these compounds an excellent alternative to continue investigating. The objective of this research was to evaluate the action of the previously undescribed natural diterpene 3,3′-diisopropyl-2,2′,5,5′-tetramethoxy-6,6′-dimethylbiphenyl-4,4′-diol (biisoespintanolcompound 2), against several human tumor cell lines (A549, MDA-MB-231, DU145, A2780, A2780-cis) and the non-tumor cell line MRC-5. Experiments with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and fluorescence with propidium iodide (PI), 4′,6-diamidino-2-phenylindole dilactate (DAPI), and green plasma revealed the cytotoxicity of 2 against these cells. Furthermore, morphological and chromogenic studies demonstrated the action of 2 on cell morphology and its inhibitory capacity of reproductive viability for colony formation in A549 cells. Furthermore, 3D experiments validated the damage caused by this diterpene in these cells. These results contribute to the search for novel compounds with antitumor potential and serve as a basis for advancing studies into the mechanisms of action of these compounds and the development of synthetic derivatives or analogs with a better antitumor profile. Full article

This paper explores the symmetry of integrated control technology to ensure the smooth operation of shearers, scraper conveyors and hydraulic supports in the context of integrated mechanized coal mining, so as to achieve the dual goals of improving coal mining efficiency and ensuring operation safety. Article paper addresses the critical research gap in system-level coordination for mechanized coal mining. While the shearer, scraper conveyor, and hydraulic support have been extensively studied individually, their integrated control under dynamic and complex geological conditions remains a challenge, often leading to production bottlenecks and safety risks. This study proposes a novel integrated control model to bridge this gap. The study formulates the research problem of achieving continuous and safe mining operations under complex geological conditions and employs modeling and simulation to validate the proposed control methodology. In the subsequent stages, a technological solution for the control of the coal mining process is investigated, and the effectiveness of the constructed model is thoroughly tested through simulation modeling methods. The study shows that through proportional–integral (PI) control, precise interaction between coal mining machines, scraper conveyors and hydraulic supports can be achieved, thereby ensuring the continuity and safety of coal mining operations and effectively preventing production interruptions and potential accidents. The research results are analyzed, and a forecast is made for the future trend of technology development, namely, the movement toward intelligence, automation and precision, so as to further promote technological innovation and industrial upgrading in the coal mining industry. Full article

Permanent Magnet Synchronous Motors (PMSMs) have been widely applied across various electrical systems due to their significant advantages, including high power density, high-efficiency conversion, and easy controllability. However, the issue of ‘parameter asymmetry’ (a mismatch between the controller’s preset parameters and the actual system parameters) in PMSMs can lead to performance problems, such as delayed speed response and increased overshoot. The destruction of symmetry, including the asymmetric weight distribution between new and old data in the moment-of-inertia identification algorithm and the asymmetry between “measured values and true values” caused by sampling delay, is the core factor limiting the system’s control performance. All these factors significantly affect the accuracy of parameter identification and the system’s stability. To address this, this study focuses on the mechanical parameter identification of PMSMs with the core goal of “symmetric matching between set values and true values”. Firstly, a current-speed dual closed-loop vector control system model is constructed. The PI parameters are tuned to meet the symmetric tracking requirements of “set value-feedback” in the dual loops, and the influence of the PMSM’s moment of inertia on the loop symmetry is analyzed. Secondly, the symmetry defects of traditional algorithms are highlighted, such as the imbalance between “data weight and working condition characteristics” in the least-squares method and the mismatch between “set inertia and true inertia” caused by data saturation. Finally, a Forgetting Factor Recursive Least Squares (FFRLS) scheme is proposed: the timing asymmetry of signals is corrected via a first-order inertial link, a forgetting factor λ is introduced to balance data weights, and a recursive structure is adopted to avoid data saturation. Simulation results show that when λ = 0.92, the identification accuracy reaches +5% with a convergence time of 0.39 s. Moreover, dynamic symmetry can still be maintained under multiple multiples of inertia, thereby improving identification performance and ensuring symmetry in servo control. Full article

The widespread adoption of electric vehicles (EVs) is contingent on high-power fast-charging infrastructure that can also provide grid stabilization services through bidirectional power flow. While the constituent power stages of such off-board chargers are well-known, a critical research gap exists in their system-level integration, where sub-optimal dynamic interaction between independently controlled stages often leads to DC-link instability and poor transient performance. This paper presents a rigorous, system-level study to address this gap by developing and optimizing a unified control framework for a high-power bidirectional EV fast-charging system. The system integrates a three-phase active front-end rectifier with an LCL filter and a four-phase interleaved bidirectional DC/DC converter. The methodology involves a holistic dynamic modeling of the coupled system, the design of a hierarchical control strategy augmented with a battery current feedforward scheme, and the system-wide optimization of all Proportional–Integral (PI) controller gains using the Artificial Bee Colony (ABC) algorithm. Comprehensive simulation results demonstrate that the proposed optimized control framework achieves a critically damped response, significantly outperforming a conventionally tuned baseline. Specifically, it reduces the DC-link voltage settling time during charging-to-discharging transitions by 74% (from 920 ms to 238 ms) and eliminates voltage undershoot, while maintaining excellent steady-state performance with grid current total harmonic distortion below 1.2%. The study concludes that system-wide metaheuristic optimization, rather than isolated component-level design, is key to unlocking the robust, high-performance operation required for next-generation EV fast-charging infrastructure, providing a validated blueprint for future industrial development. Full article

The objective of this work was to study the possibility of upgrading the control system of the drum shear mechanism by using neural network PI controllers to improve the efficiency of the sheet-metal cutting process. The developed detailed model of the mechanism, including a dual DC electric drive with three subordinate control loops for the voltage of the thyristor converter, current and speed of the motors, a 6-mass kinematic system with viscoelastic connections as well as a model of the metal cutting process, made it possible to uncover that the interaction of electric drives with the mechanical part leads to significant speed fluctuations during the cutting process, which worsens the quality of the sheet-metal edge. A modified system of current and speed controllers with built-in three-layer fitting neural networks as nonlinear components of proportional-integral channels is proposed. An algorithm for the fast learning of neural controllers using the gradient descent method in each cycle of calculating the controller signal is also proposed. The developed neuro-regulators make it possible to reduce the amplitude of speed fluctuations during the cutting process by four times, ensuring the effective damping of oscillations and reducing the duration of transient processes to 0.1 s. Full article

Aiming at the significant challenges faced by active power filters (APFs) in suppressing low-order harmonic currents (such as second and fourth), this paper proposes a rarefaction suppression method based on quasi-proportional resonance (QPR) control. Firstly, the harmonic mathematical model of APFs in a synchronous, rotating coordinate system is established to reveal the inherent defects of traditional proportional–integral (PI) control in low-order harmonic suppression. Theoretical analysis shows that although the proportional resonant (PR) controller can achieve zero-steady-state-error tracking of specific frequency harmonics, its narrow bandwidth and low robustness may easily lead to system oscillation. Therefore, the QPR control strategy is introduced. By superimposing a low-pass filter with an adjustable cut-off frequency on the resonant link, the bandwidth is significantly broadened and the anti-frequency disturbance ability of the system is enhanced. In addition, the stability of QPR control parameters is analyzed. Finally, the verification based on the experimental platform demonstrates that the proposed method reduces the total harmonic distortion (THD) of the 380 V bus current from 82.18% to 3.45%, and the low-order harmonic current suppression performance is significantly better than the traditional scheme. This research provides an effective solution for the synergistic suppression of low-order harmonic currents. Full article

Fermentative processes are considered one of the most important technological developments in the modern transforming industry, due to this, the applied research to reach high performance standards with a crucial focus on system intensification, which is the the analysis, optimization, and control issues, are a cornerstone. The goal of this proposal is to show a novel nonlinear feedback control structure to assure a stable closed-loop operation in a continuous flow enzymatic–fermentative bioreactor with chaotic dynamic behavior. The proposed structure contains an adaptive-type gain, which, coupled with a proportional term of the named control error, can lead the feedback control trajectories of the bioreactor to the required reference point or trajectory. The Lyapunov method is used to present the stability analysis of the system within a closed loop, where an adequate choice of the controller gains assures asymptotic stability. Moreover, analyzing the dynamic equation of the control error, under some properties of boundedness of the system, shows that the control error can be diminished to close to zero. Numerical experiments are carried out, where a well-tuned standard proportional–integral (PI) controller is also implemented for comparison purposes, the satisfactory performance of the proposed control scheme is observed, including the diminishing offsets, overshoots, and settling times in comparison with the PI controller. Full article

Aiming at the speed chattering problem caused by high-frequency square wave injection in permanent magnet synchronous motors (PMSMs) during low-speed operation (200–500 r/min), this study intends to improve the rotor position estimation accuracy of sensorless control systems as well as the system’s ability to resist harmonic interference and sudden load changes. The goal is to enhance the control performance of traditional control schemes in this scenario and meet the requirement of stable low-speed operation of the motor. First, the study analyzes the harmonic error propagation mechanism of high-frequency square wave injection and finds that the traditional PI phase-locked loop (PI-PLL) is susceptible to high-order harmonic interference during demodulation, which in turn leads to position estimation errors and periodic speed fluctuations. Therefore, the extended state observer phase-locked loop (ESO-PLL) is adopted to replace the traditional PI-PLL. A third-order extended state observer (ESO) is used to uniformly regard the system’s unmodeled dynamics, external load disturbances, and harmonic interference as “total disturbances”, realizing real-time estimation and compensation of disturbances, and quickly suppressing the impacts of harmonic errors and sudden load changes. Meanwhile, a dynamic pole placement strategy for the speed loop is designed to adaptively adjust the controller’s damping ratio and bandwidth parameters according to the motor’s operating states (loaded/unloaded, steady-state/transient): large poles are used in the start-up phase to accelerate response, small poles are switched in the steady-state phase to reduce errors, and a smooth attenuation function is used in the transition phase to achieve stable parameter transition, balancing the system’s dynamic response and steady-state accuracy. In addition, high-frequency square wave voltage signals are injected into the dq axes of the rotating coordinate system, and effective rotor position information is extracted by combining signal demodulation with ESO-PLL to realize decoupling of high-frequency response currents. Verification through MATLAB/Simulink simulation experiments shows that the improved strategy exhibits significant advantages in the low-speed range of 200–300 r/min: in the scenario where the speed transitions from 200 r/min to 300 r/min with sudden load changes, the position estimation curve of ESO-PLL basically overlaps with the actual curve, while the PI-PLL shows obvious deviations; in the start-up and speed switching phases, dynamic pole placement enables the motor to respond quickly without overshoot and no obvious speed fluctuations, whereas the traditional fixed-pole PI control has problems of response lag or overshoot. In conclusion, the “ESO-PLL + dynamic pole placement” cooperative control strategy proposed in this study effectively solves the problems of harmonic interference and load disturbance caused by high-frequency square wave injection in the low-speed range and significantly improves the accuracy and robustness of PMSM sensorless control. This strategy requires no additional hardware cost and achieves performance improvement only through algorithm optimization. It can be directly applied to PMSM control systems that require stable low-speed operation, providing a reliable solution for the promotion of sensorless control technology in low-speed precision fields. Full article

MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology and cardiovascular disease. miR-106b-5p, a member of the miR-106b-25 cluster, has been widely studied for its oncogenic activity in various malignancies. However, its role as a direct molecular driver of anthracycline-induced cardiotoxicity has only recently been uncovered. This finding highlights new therapeutic possibilities at the intersection of oncology and cardiovascular medicine. This review outlines the dual role of miR-106b-5p as a key modulator in both tumor progression and chemotherapy-induced cardiac dysfunction. miR-106b-5p is upregulated in numerous cancers—including breast, prostate, lung, gastric, colorectal, hepatocellular, and esophageal—and promotes tumorigenesis via suppression of tumor suppressors such as PTEN, BTG3, p21, and SMAD7, leading to activation of oncogenic pathways like PI3K/AKT and TGF-β. Importantly, we present the first evidence that miR-106b-5p is significantly upregulated in the myocardium in response to doxorubicin treatment, where it drives left ventricular dysfunction by targeting PR55α, a key regulator of PP2A activity. This pathway results in cytoplasmic HDAC4 accumulation, aberrant activation of the YY1 transcription factor, and upregulation of sST2, a biomarker linked to adverse cardiac remodeling and poor prognosis. In response, we developed AM106, a novel locked nucleic acid antagomir that silences miR-106 b-5p. Preclinical studies demonstrate that AM106 restores PR55α/PP2A activity, reduces sST2 expression, and prevents structural and functional cardiac damage without compromising anti-tumor efficacy. In parallel, artificial intelligence (AI) tools could be leveraged in the future—based on established AI applications in miRNA cancer research—to accelerate the identification of miR-106b-5p-related biomarkers and guide personalized therapy selection. Our findings position miR-106b-5p as a previously unrecognized molecular bridge between cancer and doxorubicin-induced cardiotoxicity. The development of the AM106 antagomir represents a promising approach with potential clinical applicability in cardio-oncology, offering dual benefits: tumor control and cardioprotection. Coupling this innovation with AI-driven analysis of patient data may enable precision risk stratification, early intervention, and improved outcomes. miR-106b-5p thus emerges as a central therapeutic target and biomarker candidate for transforming the clinical management of cancer patients at risk for heart failure. Full article

Hyperthyroidism features excess thyroid hormone and a hypermetabolic state; although drugs and definitive therapies exist, mechanism-anchored options are still needed. We built a multiscale interactome and applied a biased random-walk diffusion model to prioritize herbal candidates, active ingredients, and mechanisms. Herb–compound records came from OASIS; targets from DrugBank, TTD, and STITCH; and disease genes from DisGeNET. For each herb and compound, we simulated diffusion profiles, computed the correlation with the hyperthyroidism profile, and assessed target overlap ratio. Herbs were ranked by correlation and p < 0.05 overlap, retaining those with ≥5 active compounds linked to disease targets. Top signals included Geranii Herba (0.021), Gastrodiae Rhizoma (0.012), and Veratri Rhizoma Et Radix (0.011), plus seven herbs at 0.010. Herb–disease relationships were strongly enriched. Enrichment analyses highlighted MAPK, PI3K–AKT, p53, HIF-1, and thyroid hormone signaling, with Gene Ontology terms for apoptosis/anoikis, inflammation, and RNA polymerase II-dependent transcription. Compound-level analysis recovered evidence-supported ellagic acid and diosgenin and proposed resveratrol, cardamomin, 20-hydroxyecdysone, and (Z)-anethole as novel candidates. Subnetwork mapping linked these compounds to phosphorylation, GPCR–cAMP/TSH signaling, and transcriptional control. This framework recapitulates known thyroid-modulating herbs and elevates underappreciated leads with testable mechanisms, supporting the discovery of multi-target therapeutics for hyperthyroidism. Full article

This study proposes a hierarchical two-layer control framework aimed at advancing the sustainability of renewable-integrated microgrids. The framework combines droop-based primary control, PI-based voltage and current regulation, and a supervisory Model Predictive Control (MPC) layer to enhance dynamic power sharing and system stability in renewable-integrated microgrids. The proposed method addresses the limitations of conventional control techniques by coordinating real and reactive power flow through an adaptive droop formulation and refining voltage/current regulation with inner-loop PI controllers. A discrete-time MPC algorithm is introduced to optimize power setpoints under future disturbance forecasts, accounting for state-of-charge limits, DC-link voltage constraints, and renewable generation variability. The effectiveness of the proposed strategy is demonstrated on a small hybrid microgrid system that serve a small community of buildings with a solar PV, wind generation, and a battery storage system under variable load and environmental profiles. Initial uncontrolled scenarios reveal significant imbalances in resource coordination and voltage deviation. Upon applying the proposed control, active and reactive power are equitably shared among DG units, while voltage and frequency remain tightly regulated, even during abrupt load transitions. The proposed control approach enhances renewable energy integration, leading to reduced reliance on fossil-fuel-based resources. This contributes to environmental sustainability by lowering greenhouse gas emissions and supporting the transition to a cleaner energy future. Simulation results confirm the superiority of the proposed control strategy in maintaining grid stability, minimizing overcharging/overdischarging of batteries, and ensuring waveform quality. Full article

Ochratoxin A (OTA), a common mycotoxin contaminant, poses significant health risks through its multi-organ toxicity. While OTA is known to cause immune organ dysfunction leading to immunotoxicity, its precise mechanistic pathways remain unclear. The spleen is an important immune organ of the body and plays a key role in immune defense and homeostasis maintenance. Astaxanthin (AST), a potent antioxidant with demonstrated immunomodulatory properties, exhibits a broad therapeutic potential including anti-inflammatory, wound-healing, anti-aging, and hepatoprotective effects. Therefore, this study aimed to explore the mechanism by which AST attenuates OTA-induced immunotoxicity using a chicken OTA/AST treatment model. Sixty 1-day-old, white-feathered, sex-undifferentiated chicks were randomly allocated into four groups (n = 15): (1) Control, (2) OTA (1 mg/kg), (3) AST (100 mg/kg), and (4) OTA + AST (1 mg/kg OTA + 100 mg/kg AST). The experiment lasted for 21 days to establish the model. Subsequently, serum ELISA, antioxidant capacity assays, qRT-PCR, and western blot (WB) analyses were employed to explore the protective role of AST against immunotoxicity. The results showed that AST increased splenic organ coefficients and serum immunoglobulin (IgM and IgG) concentrations (p < 0.01) and decreased the expression of inflammatory factors (IL-8, IL-6, and IL-1β) (p < 0.01). We found that OTA was involved in the expression of the PTEN/PI3K/AKT signaling pathway (PTEN, PI3K, AKT, p-AKT (Ser473)) and apoptotic genes (Bcl-2, Bax, Caspase3, Caspase9). Notably, AST significantly attenuated OTA-induced oxidative damage (ROS, MDA, T-AOC) in the spleen (p < 0.05), upregulated the expression of PI3K and p-AKT (Ser473) (p < 0.05) and inhibited the expression of PTEN and apoptosis-related genes (p < 0.05). In summary, AST attenuates OTA-induced immunotoxicity by alleviating oxidative stress and modulating the PTEN/PI3K/AKT signaling pathway. Full article