Search Results (9)

Background: Multiple myeloma (MM) is characterised by clonal expansion of plasma cells (PCs) in the bone marrow (BM). Disease assessment and monitoring typically rely on invasive, single-site procedures, such as BM biopsies (BMBs), which may inadequately capture intra- and extra-medullary spatial heterogeneity. Circulating plasma cells (CPCs), enriched from peripheral blood (PB), may represent a minimally invasive alternative or adjunct for molecular profiling. Objectives: This study aimed to evaluate the feasibility of using CPCs, enriched from PB, for mRNA analysis in plasma cell dyscrasia, including MM. A secondary objective was to assess whether mRNA expression levels of the endoplasmic reticulum (ER) stress sensors X-box-binding protein 1 (uXBP1) and activating transcription factor 6 (ATF6), and the chaperone-mediated autophagy marker Lysosomal-Associated Membrane Protein 2 (LAMP2A) by droplet digital PCR (ddPCR), were associated with resistance to the second-generation proteasome inhibitor (PI) carfilzomib (Cfz). Methods: Multiple myeloma (MM) cell lines (H929 and U266) and their carfilzomib-adapted derivatives were used to establish and validate droplet digital PCR (ddPCR) assays targeting ER stress (uXBP1, ATF6) and autophagy-related (LAMP2A) transcripts. Solid tumour cell lines, including serum-starved HeLa cells, served as biological controls to support assay specificity and sensitivity. Total RNA was extracted and reverse-transcribed to complementary DNA prior to analysis. Transcript levels were normalised to those of β-actin or GAPDH, as appropriate. ddPCR was performed using the BioRad QX200 system, with results reported as the normalised transcript copy number per microlitre of reaction. Matched bone marrow aspirate (BMA) and peripheral blood (PB) samples were collected at a single clinical time point from adults undergoing investigation for plasma cell dyscrasia between January 2021 and December 2023. Samples were obtained as part of standard clinical care and/or during treatment with Bortezomib (Btz) or Cfz. Mononuclear cells were isolated by density gradient centrifugation, and CD138⁺ plasma cells were enriched by fluorescence-activated cell sorting. Enrichment purity was assessed qualitatively by immunofluorescence microscopy using CD138 and CD117 markers. Samples yielding fewer than 1000 CD138⁺ plasma cells were excluded, resulting in 10 evaluable matched patient pairs. Results: Carfilzomib-adapted MM cell lines demonstrated reduced levels of uXBP1, ATF6, and LAMP2A mRNA compared to treatment-naïve cells. In matched BM and PB samples, uXBP1 mRNA levels were consistently lower in circulating PCs than in BM-derived PCs, whereas ATF6 mRNA levels were concordant between compartments. LAMP2A mRNA levels exhibited marked inter-patient heterogeneity. Conclusions: This study demonstrates the feasibility of using CPCs as a minimally invasive source for mRNA-based biomarker assessment and highlights ddPCR as a sensitive platform for quantifying ER stress and chaperone-mediated autophagy related transcripts in CPCs. Cfz adaptation was associated with reduced levels of uXBP1 and LAMP2A mRNA in MM cell lines. Future prospective studies evaluating the clinical utility of ER stress and chaperone-mediated autophagy associated transcripts in CPCs as predictors of resistance to PI are warranted. Full article

This study examines dual-area load–frequency control (LFC) in the context of significant renewable energy integration, energy storage systems (ESSs), and collective electric vehicle (EV) involvement. We propose a RBBMO-FO-FuzzyPID+PI(1+DD) hybrid controller in which fractional-order fuzzy regulation shapes the ACE, while an auxiliary PI(1+DD) path adds damping without steady-state penalty. Across ideal linear plants, 3% governor-rate constraints (GRC), and stressed conditions that include contract violations in Area-2, renewable power variations, and partial EV State of Charge (SoC 50–70%), EV participation yields systematic gains for all controller families, and the magnitude depends on the control architecture. Baseline methods improve by 15–25% with EVs, whereas advanced designs—especially the proposed controller—benefit by 25–45%, revealing a clear synergy between controller intelligence and EV flexibility. With EV support, the proposed controller limits frequency overshoot to 0.055 Hz (a 20–55% reduction versus peers), caps the nadir at −0.065 Hz (15–41% better undershoot), and attains 3.5–4.5 s settling (25–61% faster than competitors), while holding tie-line deviations within ±0.02 Hz. Optimization studies confirm the algorithmic advantage: RBBMO achieves 30% lower cost than BBOA and converges 25% faster; EV integration further reduces cost by 15% and speeds convergence by 12%. A strong correlation between optimization cost and closed-loop performance (r² ≈ 0.95) validates the tuning strategy. Collectively, the results establish the proposed hybrid controller with EV participation as a new benchmark for robust, system-wide frequency regulation in renewable-rich multi-area grids. Full article

The increasing integration of renewable energy sources (RES) and rising energy demand have created challenges in maintaining stability in interconnected power systems, particularly in terms of frequency, voltage, and tie-line power. While traditional load frequency control (LFC) and automatic voltage regulation (AVR) strategies have been widely studied, they often fail to address the complexities introduced by RES and nonlinear system dynamics such as boiler dynamics, governor deadband, and generation rate constraints. This study introduces the Arithmetic Optimization Algorithm (AOA)-optimized PI(1+DD) controller, chosen for its ability to effectively optimize control parameters in highly nonlinear and dynamic environments. AOA, a novel metaheuristic technique, was selected due to its robustness, efficiency in exploring large search spaces, and ability to converge to optimal solutions even in the presence of complex system dynamics. The proposed controller outperforms classical methods such as PI, PID, I–P, I–PD, and PI–PD in terms of key performance metrics, achieving a settling time of 7.5 s (compared to 10.5 s for PI), overshoot of 2.8% (compared to 5.2% for PI), rise time of 0.7 s (compared to 1.2 s for PI), and steady-state error of 0.05% (compared to 0.3% for PI). Additionally, sensitivity analysis confirms the robustness of the AOA-optimized controller under ±25% variations in turbine and speed control parameters, as well as in the presence of nonlinearities, demonstrating its potential as a reliable solution for improving grid performance in complex, nonlinear multi-area interconnected power systems. Full article

Renewable energy sources (RESs) are increasingly combined into the power system due to market liberalization and environmental and economic benefits, but their weather-dependent variability causes power production and demand mismatches, leading to issues like frequency and regional power transmission fluctuations. To maintain synchronization in power systems, frequency must remain constant; disruptions in the proper balance of production and load might produce frequency variations, risking serious issues. Therefore, a mechanism known as load frequency control (LFC) or automated generation control (AGC) is needed to keep the frequency and tie-line power within predefined stable limits. In this study, advanced proportional–integral–derivative PID controllers such as fractional-order PID (FOPID), cascaded PI(PDN), and PI(1+DD) for LFC in a two-area power system integrated with RES are optimized using the catch fish optimization algorithm (CFA). The controllers’ optimal gains are attained through using the integral absolute error (IAE) and ITAE objective functions. The performance of LFC with CFA-tuned PID, PI, cascaded PI(PDN), and FOPID, PI(1+DD) controllers is compared to other optimization techniques, including sine cosine algorithm (SCA), particle swarm optimization (PSO), brown bear algorithm (BBA), and grey wolf optimization (GWO), in a two-area power system combined with RESs under various conditions. Additionally, by contrasting the performance of the PID, PI, cascaded PI(PDN), and FOPID, PI(1+DD) controllers, the efficiency of the CFA is confirmed. Additionally, a sensitivity analysis that considers simultaneous modifications of the frequency bias coefficient (B) and speed regulation (R) within a range of ±25% validates the efficacy and dependability of the suggested CFA-tuned PI(1+DD). In the complex dynamics of a two-area interconnected power system, the results show how robust the suggested CFA-tuned PI(1+DD) control strategy is and how well it can stabilize variations in load frequency and tie-line power with a noticeably shorter settling time. Finally, the results of the simulation show that CFA performs better than the GWO, BBA, SCA, and PSO strategies. Full article

This study proposes an enhanced Kepler Optimization (EKO) algorithm, incorporating fractional-order components to develop a Proportional-Integral-First-Order Double Derivative (PI–(1+DD)) controller for frequency stability control in multi-area power systems with wind power integration. The fractional-order element facilitates efficient information and past experience sharing among participants, hence increasing the search efficiency of the EKO algorithm. Furthermore, a local escaping approach is included to improve the search process for avoiding local optimization. Applications were performed through comparisons with the 2020 IEEE Congress on Evolutionary Computation (CEC 2020) benchmark tests and applications in a two-area system, including thermal and wind power. In this regard, comparisons were implemented considering three different controllers of PI, PID, and PI–(1+DD) designs. The simulations show that the EKO algorithm demonstrates superior performance in optimizing load frequency control (LFC), significantly improving the stability of power systems with renewable energy systems (RES) integration. Full article

Background: In previous studies, many imaging analyses have been conducted to explore the changes in the intervertebral disc degeneration (DD), facet joint osteoarthritis (FJOA), L4 inclination angle (L4IA), pelvis-related parameters, lumbar lordosis (LL), and paravertebral muscle (PVM) in the occurrence and development of degenerative spinal diseases via measuring the X-ray, CT, and MRI data of clinical patients. However, few studies have quantitatively investigated the pelvic parameters and the degree of spine degeneration in patients with degenerative lumbar spondylolisthesis (DLS) and isthmic lumbar spondylolisthesis (ILS). This study discusses the changes in the imaging parameters of DLS, ILS, and a control group; explores the correlation between different measurement parameters; and discusses their risk factors. Methods: We evaluated 164 patients with single L4-L5 grade 1 level degenerative lumbar spondylolisthesis (DLS group), 161 patients with single L4-L5 grade 1 level isthmic lumbar spondylolisthesis (ILS group), and 164 patients with non-specific back pain (control group). The grades of DD and FJOA as well as the percentage of the fat infiltration area (%FIA) of multifidus muscle (MM) at the L4-L5 level were measured via CT and MRI. Lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT), the L4 inclination angle (L4IA), and sacral slope (SS) were measured via X-ray film, and the differences among the DLS group, ILS group, and control group were analyzed. Furthermore, the risk factors related to the incidences of the DLS and ILS groups were discussed. Results: First, the pelvis-related parameters of DLS and ILS patients were 51.91 ± 12.23 and 53.28 ± 11.12, respectively, while those of the control group were 40.13 ± 8.72 (p₁ < 0.001, p₂ < 0.001). Lumbar lordosis (LL) in DLS patients (39.34 ± 8.57) was significantly lower than in the control group (44.40 ± 11.79, p < 0.001). On the contrary, lumbar lordosis (LL) in the ILS group (55.16 ± 12.31) was significantly higher than in the control group (44.40 ± 11.79, p < 0.001). Secondly, the three groups of patients were characterized by significant variations in the L4 inclination angle (L4IA), disc degeneration (DD), facet joint osteoarthritis (FJOA), pelvis-related parameters, and paravertebral muscle (PVM) (p < 0.05). Finally, logistic regression suggests that the L4IA, FJOA, and PT may be risk factors for the occurrence of DLS, and the occurrence of ILS is correlated with the L4IA, FJOA, DD, PT, and LL. Conclusions: Compared with the control group, there are changes in pelvic parameters, the L4IA, LL, DD, FJOA, and PVM in DLS and ILS patients, and the degree is different. The parameters within the same group are related to each other, and DLS and ILS have different risk factors. The mechanical stability of the spine is affected by the parameter and angle changes, which may be of great significance for explaining the cause of spondylolisthesis, evaluating the health of the lumbar spine, and guiding the lifestyles of patients. Full article

This study presents an effective control strategy for regulating the DC-link voltage in a variable-speed direct-driven (DD) wind energy conversion system (WECS) using a permanent magnet vernier generator (PMVG). To do this, at first, the overall system is configured using back-to-back (BTB) voltage source converters, and the whole system’s dynamical equations are modeled and presented. Following that, a non-linear sliding mode control strategy is introduced as the grid-side converter’s DC-link voltage controller to improve the dynamic performance of the PMVG system and achieve the stable power transfer with the grid. To accomplish this, a proportional and integral (PI)-based sliding surface is designed, and a hybrid reaching law is proposed to suppress chattering and deliver a faster response of DC-link voltage with negligible steady-state tracking error. Finally, the effectiveness and superiority of the proposed control strategy are validated through comparisons with existing methods using simulation and experimental results from a 5-kW PMVG system. Full article

It is known that keeping the power balance between generation and demand is crucial in containing the system frequency within acceptable limits. This is especially important for renewable based distributed hybrid microgrid (DHμG) systems where deviations are more likely to occur. In order to address these issues, this article develops a prominent dual-level “proportional-integral-one plus double derivative {PI−(1 + DD)} controller” as a new controller for frequency control (FC) of DHμG system. The proposed control approach has been tested in DHμG system that consists of wind, tide and biodiesel generators as well as hybrid plug-in electric vehicle and an electric heater. The performance of the modified controller is tested by comparing it with standard proportional-integral (PI) and classical PID (CPID) controllers considering two test scenarios. Further, a recently developed mine blast technique (MBA) is utilized to optimize the parameters of the newly designed {PI − (1 + DD)} controller. The controller’s performance results are compared with cases where particle swarm optimization (PSO) and firefly (FF) techniques are used as benchmarks. The superiority of the MBA-{PI − (1 + DD)} controller in comparison to other two strategies is illustrated by comparing performance parameters such as maximum frequency overshoot, maximum frequency undershoot and stabilization time. The displayed comparative objective function (J) and J_FOD index also shows the supremacy of the proposed controller. With this MBA optimized {PI − (1 + DD)} controller, frequency deviations can be kept within acceptable limits even with high renewable energy penetration. Full article

Essential oils are odorant liquid oily products consisting of a complex mixture of volatile compounds obtained from a plant raw material. They have been increasingly proven to act as potential natural agents in the treatment of several human conditions, including diabetes mellitus (DM). DM is a metabolic disorder characterized by chronic hyperglycemia closely related to carbohydrate, protein and fat metabolism disturbances. In order to explore novel approaches for the management of DM our group proposes the encapsulation of sucupira essential oil, obtained from the fruits of the Brazilian plants of the genus Pterodon, in nanostructured lipid carriers (NLCs), a second generation of lipid nanoparticles which act as new controlled drug delivery system (DDS). Encapsulation was performed by hot high-pressure homogenization (HPH) technique and the samples were then analyzed by dynamic light scattering (DLS) for mean average size and polydispersity index (PI) and by electrophoretic light scattering (ELS) for zeta potential (ZP), immediately after production and after 24 h of storage at 4 °C. An optimal sucupira-loaded NLC was found to consist of 0.5% (m/V) sucupira oil, 4.5% (m/V) of Kollivax^® GMS II and 1.425% (m/V) of TPGS (formulation no. 6) characterized by a mean particle size ranging from 148.1 ± 0.9815 nm (0 h) to 159.3 ± 9.539 nm (at 24 h), a PI from 0.274 ± 0.029 (0 h) to 0.305 ± 0.028 (24 h) and a ZP from −0.00236 ± 0.147 mV (at 0 h) to 0.125 ± 0.162 (at 24 h). The encapsulation efficiency and loading capacity were 99.98% and 9.6%, respectively. The optimized formulation followed a modified release profile fitting the first order kinetics, over a period of 8 h. In vitro cytotoxicity studies were performed against Caco-2 cell lines, for which the cell viability above 90% confirmed the non-cytotoxic profile of both blank and sucupira oil-loaded NLC. Full article