Structural Changes Research Articles

Blood glucose-lowering activity of protocatechuic acid is mediated by inhibiting α-glucosidase

α-Glucosidase inhibitors are effective in controlling postprandial hyperglycemia, which play crucial roles in the management of type 2 diabetes. Protocatechuic acid (PCA) is one of phenolic acids existing not only in various plant foods but also as a major microbial metabolite of dietary anthocyanins in the large colon. The present study investigated the inhibitory mechanism of PCA on α-glucosidase in vitro and examined its effect on postprandial blood glucose levels in vivo. Results from in vitro experiments demonstrated that PCA was a mix-type inhibitor of α-glucosidase. Driven by hydrogen bonds and van der Waals interactions, PCA reversibly bound with α-glucosidase to form a stable α-glucosidase-PCA complex in a spontaneous manner. The computational simulation found that PCA could insert into the active cavity of α-glucosidase and establish hydrogen bonds with catalytic amino acid residues. PCA binding aroused the steric hindrance for substrates to enter active sites and caused the structural changes of interacted catalytic amino acid residues. PCA also exhibited postprandial hypoglycemic capacity in diabetic mice. This study may provide the theoretical basis for the application of PCA as an active ingredient of functional foods in dietary management of diabetes.

Bilingual Language Control in the Brain: Evidence from Structural and Effective Functional Brain Connectivity.

Experience in bilingual language control is often accompanied by changes in the structure and function of the brain. Brain structural changes are also often closely related to changes in functions. Previous studies, however, have not directly explored the relationship between structural connectivity and effective functional connectivity of the brain during bilingual language control, and whether the two types of connectivity are associated with behavioral performance of language control. Using behavioral performance, functional, and diffusion imaging techniques, we found that: (1) during language control, the left dorsal lateral prefrontal cortex (dlPFC), left caudate nucleus (CN), inferior parietal lobe, precuneus, and dorsal anterior cingulate cortex (dACC)/pre-SMA were significantly activated. (2) In the language control model with left dlPFC, dACC/pre-SMA, and left CN as ROIs (selected based on activation results and language control models from previous studies), stimuli first enter dACC/pre-SMA and then to left CN. At the left CN, a bidirectional effective connectivity is formed with left dlPFC. (3) There is a nonlinear relationship between effective connectivity during language control and the structural connectivity of the second language learners' brains. Specifically, the fiber density between dACC/pre-SMA and left dlPFC has a positive influence on the bidirectional effective connectivity between left dlPFC and left CN. Findings of the present study contribute evidence toward functional effective connectivity during bilingual language control; toward structural connectivity in the brains of second language learners; as well as toward nonlinear relationships between functional effective connectivity, structural connectivity, and behavioral performance in relation to bilingual language control.

A robust internal model control design for low-quality waste heat power generation systems

Recovering low-quality waste heat using industrial waste heat is challenging, and the reuse technology needs to erupt. Moreover, the gas source of low-quality waste heat is relatively volatile, which makes it challenging to keep the actual working condition of the plant stable. Therefore, it is inspiring to research the robustness of root-waste heat power generation processed measurement and control system to improve the stability of the plant operation. Hence, in this paper, we have applied uncertainty theory to analyze it and formulate the uncertainty model based on the Bode diagram. We also proposed a control method based on the uncertainty model, which combines robust control and internal model control to make the roots waste heat power generation system operate stably under the effect of external disturbances and changes of internal structure or parameters in actual operation. Experimental results show that the robust internal model control method has a speed deviation of no more than 7.9 r/min compared with the PID control method. The adjustment time to track the set value does not exceed 73.1 seconds within the allowed fluctuation range. The fluctuation variance is 30.95% of that of the PID controller. The dynamic performance is better, with strong anti-interference capability and significantly improved tracking performance. It ensures the stability of the roots-type waste heat utilization system, which is essential for future intelligent grid-connected power generation.

Insight into the Critical Role of Oxygen Vacancies and V=O Bonds Length in V2O5 for Advanced Zinc Ion Storage.

Due to the larger sizes and stronger positive polarity of Zn2+ than dominant univalent ions, Zn2+ sluggish diffusion within V2O5 host electrodes is an essential issue in developing aqueous zinc-ion batteries (ZIBs) of higher energy densities. Herein, a high-performance V2O5 cathode was developed through subtly synthesizing and tuning V2O5 with oxygen vacancies-enriched and elongated apical V=O1 bond by altering the gradient concentration of hydrazine hydrate in the gas-solid reaction system. This strategy can enhance both intrinsic and extrinsic conductivity to a large extent. The electrochemical testing demonstrated the oxygen vacancies-enriched and elongated apical V=O1 bond can not only increase the intrinsic electronic conductivity of V2O5, but also induce additional pseudocapacitance to enhance the Zn2+ diffusion kinetics. We used infrared spectroscopy and Raman spectroscopy to characterize the change in the bond length structure of V2O5. Simultaneously, the long-term cyclability (capacity retention of 76.9 % after 1200 cycles at 4.0 A g-1) and rate capabilities (218 mAh g-1 at 4.0 A g-1) are promoted as well. We believe that our work might shed light on the bond length engineering of V2O5 and provide insights for the reasonable designing of novel cathodes for practical rechargeable ZIBs.

From export boom to private debt bubble: a macroeconomic policy regime assessment of Canada’s shifting growth regime

This paper examines the emergence of private debt-led growth in Canada since the Global Financial Crisis (GFC) by means of a growth regime and macroeconomic policy regime assessment. Examining each of the four business cycles in the 1983–2020 period, roughly encompassing the entirety of the neoliberal period, results demonstrate the emergence of a ‘rising’ weakly export-led growth regime in the early 1990s, a shift to a ‘falling’ weakly export-led regime by 2001, and a turn to a debt-led private demand regime since the GFC. The macroeconomic policy regime then identifies the structural changes and policy factors that have contributed to Canada’s shifting growth regime. While price competitiveness played an important role in the first three cycles, it failed to re-establish an export-led regime in the post-GFC period due to decreased non-price competitiveness. Instead, the post-GFC combination of low real interest rates, which encouraged the accumulation of private debt and fiscal policy, which ex post did not address the negative financial balances of the household sector, supported the turn to private debt-led growth.

Gd(HB-DO3A)]: Equilibrium, Dissociation Kinetic and Structural Differences in a Simple Homolog of [Gd(HP-DO3A)] (Prohance®).

[Gd(HP-DO3A)] (gadoteridol) as an active compound of ProHance® is a widely employed contrast agent in clinical MRI scans in the last 30 years. Recent concerns about the long-term retention of gadolinium-based contrast agents (GBCAs) led to a deeper investigation of the structural features underlying the integrity of the paramagnetic metal complex. Several human and nonclinical studies have noted marked differences among the macrocyclic GBCAs, with the least retention of Gd traces and most rapid elimination consistently being reported for [Gd(HP-DO3A)]. It was deemed of interest to assess how minor structural/electronic changes associated to the ligand structure may affect basic properties of the metal complex with several [Gd(HP-DO3A)] analogues synthesized and characterized in the last years. We recently reported that the closest homolog of [Gd(HP-DO3A)], i. e.: [Gd(HB-DO3A)], in which a (±)-2-hydroxy-1-propyl pendant arm is replaced by a (±)-2-hydroxy-1-butyl moiety, showed a significantly different retention behaviour in the model interaction with collagen, despite the apparently very minor structural difference. In this paper we report a comprehensive study of the structural, thermodynamic, kinetic and relaxation properties of [Gd(HB-DO3A)], compared to the parent [Gd(HP-DO3A)] and to other closely related macrocyclic GBCAs to assess whether very minor structural changes can modulate the physico-chemical properties of Gd3+ complexes.

Aortic Cellular Heterogeneity in Health and Disease: Novel Insights Into Aortic Diseases From Single-Cell RNA Transcriptomic Data Sets.

Aortic diseases such as atherosclerosis, aortic aneurysms, and aortic stiffening are significant complications that can have significant impact on end-stage cardiovascular disease. With limited pharmacological therapeutic strategies that target the structural changes in the aorta, surgical intervention remains the only option for some patients with these diseases. Although there have been significant contributions to our understanding of the cellular architecture of the diseased aorta, particularly in the context of atherosclerosis, furthering our insight into the cellular drivers of disease is required. The major cell types of the aorta are well defined; however, the advent of single-cell RNA sequencing provides unrivaled insights into the cellular heterogeneity of each aortic cell type and the inferred biological processes associated with each cell in health and disease. This review discusses previous concepts that have now been enhanced with recent advances made by single-cell RNA sequencing with a focus on aortic cellular heterogeneity.

The Energetics of the Lagrangian Evolution of Tropical Convective Systems

Abstract The convective life cycle is often conceptualized to progress from congestus to deep convection and develop further to stratiform anvil clouds, accompanied by a systematic change in the vertical structure of vertical motion. This archetype scenario has been developed largely from the Eulerian viewpoint, and it has yet to be explored whether the same life cycle emerges itself in a moving system tracked in the Lagrangian manner. To address this question, Lagrangian tracking is applied to tropical convective systems in combination with a thermodynamic budget analysis forced by satellite-retrieved precipitation and radiation. A new method is devised to characterize the vertical motion profiles in terms of the column import or export of moisture and moist static energy (MSE). The bottom-heavy, midheavy, and top-heavy regimes are identified for every 1° × 1° grid pixel accompanying tracked precipitation systems, making use of the diagnosed column export/import of moisture and MSE. The major findings are as follows. The Lagrangian evolution of convective systems is dominated by a state of dynamic equilibrium among different convective regimes rather than a monotonic progress from one regime to the next. The transition from the bottom-heavy to midheavy regimes is fed with intensifying precipitation presumably owing to a negative gross moist stability (GMS) of the bottom-heavy regime, whereas the transition from the midheavy to top-heavy regimes dissipates the system. The bottom-heavy to midheavy transition takes a relaxation time of about 5 h in the equilibrating processes, whereas the relaxation time is estimated as roughly 20 h concerning the midheavy to top-heavy transition.

Electroluminescence Performance Optimization of Films Based on the Change of Macroscopic Structure and Microscopic Calculation

Electroluminescence Performance Optimization of Films Based on the Change of Macroscopic Structure and Microscopic Calculation

Reliability analysis in distribution system by deep belief neural network

Rapid increase in the usage of intermittent renewable energy, ongoing changes in electrical power system structure and operational needs posing growing problems while ensuring adequate service reliability and retaining the quality of power. Power system reliability is a pertinent factor to consider while planning, designing, and operating distribution systems. utilities are obligated to offer their customers uninterrupted electrical service at the least cost while maintaining a satisfactory level of service quality. The important metrics for gauging the effect of distributed renewable energy on distribution networks is reliability analysis. Reliability analysis in distribution systems involves evaluating the performance and robustness of electrical distribution networks. An artificial intelligence approach is implemented in this paper to improve reliability analysis with dispersed generations in distribution network. Deep belief neural networks (DBNNs) are a type of artificial neural network that can be used for various tasks, including analyzing complex data such as those found in power distribution systems. This paper integrated a DBNN using a particle swarm optimization (PSO) technique. The proposed model performance is assessed using mean square error, mean absolute error, root mean square error, and R squared error. The findings reveal that reliability analysis with this novel technique is more accurate.

DyGCN: Efficient Dynamic Graph Embedding With Graph Convolutional Network.

Graph embedding, aiming to learn low-dimensional representations (aka. embeddings) of nodes in graphs, has received significant attention. In recent years, there has been a surge of efforts, among which graph convolutional networks (GCNs) have emerged as an effective class of models. However, these methods mainly focus on the static graph embedding. In the present work, an efficient dynamic graph embedding approach is proposed, called dynamic GCN (DyGCN), which is an extension of the GCN-based methods. The embedding propagation scheme of GCN is naturally generalized to a dynamic setting in an efficient manner, which propagates the change in topological structure and neighborhood embeddings along the graph to update the node embeddings. The most affected nodes are updated first, and then their changes are propagated to further nodes, which in turn are updated. Extensive experiments on various dynamic graphs showed that the proposed model can update the node embeddings in a time-saving and performance-preserving way.

Structural and functional abnormalities in the medial prefrontal cortex were associated with pain and depressive symptoms in patients with adhesive capsulitis.

Chronic pain and depression have been shown to coexist in patients with adhesive capsulitis (AC). Recent studies identified the shared brain plasticity between pain and depression; however, how such neuroplasticity contributes to AC remains unclear. Here, we employed a combination of psychophysics, structural MRI, and functional MRI techniques to examine the brain's structural and functional changes in AC. Fifty-two patients with AC and 52 healthy controls (HCs) were included in our study. Voxelwise comparisons were performed to reveal the differences in grey matter volume (GMV) and regional homogeneity (ReHo) between AC and HCs. Furthermore, region of interest to whole brain functional connectivity (FC) was calculated and compared between the groups. Finally, Pearson correlation coefficients were computed to reveal the association between clinical data and brain alterations. Mediation analyses were performed to investigate the path association among brain alterations and clinical measures. Three main findings were observed: (1) patients with AC exhibited a higher depression subscale of hospital anxiety and depression scale (HADS-D) score correlating with the GMV within the right medial prefrontal cortices (mPFC) compared with HCs; (2) relative to HCs, patients with AC exhibited lower ReHo within the right mPFC, which largely overlapped with the structural abnormalities; (3) the impact of pain duration on HADS-D score was mediated by ventral part of medial prefrontal cortices (vmPFC) GMV in patients with AC. In summary, our current findings suggest that vmPFC alterations correlate with both the pain duration and the emotional comorbidities experienced by patients with AC. Our research provides an enhanced comprehension of the underlying mechanisms of AC, thereby facilitating the development of more effective treatment approaches for AC.

Impact of aluminum fluoride addition on crystallization, structure and thermal properties of lead borate glasses

The glass composition (70-x)PbO–(30-y)B2O3–(x+y)AlF3, where x and y ranges from 0 to 20 mol%, were prepared using the conventional melt-quenching-annealing technique. The structural and thermal properties of the glasses were comprehensively analyzed using techniques like Differential Thermal Analysis (DTA), Dilatometry, Fourier-Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and Scanning Electron Microscopy (SEM). XRD confirmed the amorphous, non-crystalline structure of the glasses. The glass network was found to be composed of structural units such as PbO4, BO4, BO3 and AlO6 using FTIR spectroscopy. FTIR analysis revealed significant structural changes, including the transformation of BO4 to BO3 units and the increase in non-bridging bonds, particularly with higher AlF3 content. DTA was instrumental in determining characteristic temperatures, such as the glass transition, melting, and peak crystallization temperatures, along with glass stability parameters (∆T, Hr, Tgr) for all samples. The study found that the addition of AlF3 led to a decrease in these characteristic temperatures when replacing B2O3, but an increase when replacing PbO. Variations in the density and thermal expansion of the lead borate glass were observed upon the addition of AlF3, decreasing when substituting for PbO and increasing when substituting for B2O3. These findings provide insights into the properties of oxyfluoride glasses, paving the way for future optimization in their composition for varied applications.

Changes in enamel hardness, wear resistance, surface texture, and surface crystal structure with glass ionomer cement containing BioUnion fillers.

This study investigated the potential of BioUnion filler containing glass ionomer cement (GIC) to enhance the properties of enamel surrounding restorations, with a specific focus on the effect on hardness. The hardness of the bovine enamel immersed in the cement was measured using Vickers hardness numbers. Following sliding and impact wear simulations, the enamel facets were examined using confocal-laser-scanning microscopy and scanning-electron microscopy. Surface properties were further analyzed using energy-dispersive X-ray spectroscopy and X-ray diffraction (XRD). A significant increase in Vickers hardness numbers was observed in the BioUnion filler GIC after 2 days. Furthermore, the mean depth of enamel facets treated with BioUnion filler GIC was significantly less than that of untreated facets. Characteristic XRD peaks indicating the presence of hydroxyapatite were also observed. Our findings imply that GIC with BioUnion fillers enhances the mechanical properties of the tooth surface adjacent to the cement.

A Cheap New Geological Dating Method Developed from Ancient Shells Study

The vast majority of researchers on ancient shells are biologists, who are not familiar with X-ray diffractometers, etc. We are physical chemists who use X-ray diffraction to observe the changes in the crystal structure of ancient shells? Then use WDX electron probe to observe the changes in the microstructure of ancient shells. After discovering shells for a long time, calcite turned into aragonite, overturning the conclusion recorded in geological crystallographic books that aragonite’s structure and physical properties were unstable and would eventually transform into calcite. Unexpectedly discovered that the “Shuang chen Weathering Cave CC” of ancient shells has changed over time, it can be used as a new method for geological dating.The use of carbon 14 (C14) isotope geological dating method is quite expensive and lacks accuracy, causing many jokes. The “Shuang chen Weathering Cave CC” of ancient shells may be used as a new geological dating method, and it is quite cheap!

Quantitative and structural changes of blood platelet cytoskeleton proteins in multiple sclerosis (MS)

Epidemiological studies show that cardiovascular events related to platelet hyperactivity remain the leading causes of death among multiple sclerosis (MS) patients. Quantitative or structural changes of platelet cytoskeleton alter their morphology and function. Here, we demonstrated, for the first time, the structural changes in MS platelets that may be related to their hyperactivity. MS platelets were found to form large aggregates compared to control platelets. In contrast to the control, the images of overactivated, irregularly shaped MS platelets show changes in the cytoskeleton architecture, fragmented microtubule rings. Furthermore, MS platelets have long and numerous pseudopodia rich in actin filaments. We showed that MS platelets and megakaryocytes, overexpress β1-tubulin and β-actin mRNAs and proteins and have altered post-translational modification patterns. Moreover, we identified two previously undisclosed mutations in the gene encoding β1-tubulin in MS. We propose that the demonstrated structural changes of platelet cytoskeleton enhance their ability to adhere, aggregate, and degranulate fueling the risk of adverse cardiovascular events in MS.

Tailoring the physicochemical properties of starch: impact of integrated ultrasonic and ethanol pretreatment on the oil uptake of infrared fried ginkgo seeds.

The structural changes of starch would have a more crucial impact on oil absorption and quality changes in starch-rich fruits and vegetables during frying process with enhanced heat transfer (such as infrared frying). In the present study, the influence of integrated ultrasonic and ethanol (US + ethanol) pretreatment on oil uptake in infrared fried (IF) ginkgo seeds was evaluated regarding modifications in the physicochemical properties of starch. The pretreatment was performed with ultrasonic (40 kHz, 300 W) and ethanol osmotic (95%, v/v) treatment individually or integrated for 40 min. The mass transfer in the pretreatment was facilitated by combined ultrasound and ethanol. The swelling power, solubility, and gelatinization degree of starch was significantly increased. Low-frequency-NMR curves and images revealed that the bound water fraction in ginkgo seeds was increased and the water distribution was homogenized. The results of Fourier transform-infrared spectrum and differential scanning calorimeter revealed that the crystalline regions of starch were reduced and the thermal enthalpy was decreased after US + ethanol pretreatment. The total, surface and structural oil content in IF ginkgo seeds with US + ethanol pretreatment was reduced by 29.10%, 34.52% and 29.73%, respectively. The US + ethanol pretreatment led to a thinner crust layer with increased porosity and smaller-sized pores in the IF ginkgo seeds as observed by stereo microscopy and scanning electron microscopy. The changes in structural and physicochemical properties of starch by combined ultrasound and ethanol affect the crust ratio and pore characteristics in fried high-starch fruits and vegetables, thereby reducing oil absorption. © 2024 Society of Chemical Industry.

Study on thermal cycling ageing resistance of performances of polypropylene/elastomer/boron nitride nanocomposites for high voltage direct current cable insulation

AbstractThe influences of thermal cycling ageing on structures and insulation performances of polypropylene (PP)/elastomer/boron nitride (BN) nanocomposites are investigated. The Melt blending method was used to prepare the nanocomposites, in which propylene‐based elastomer (PBE) or ethylene‐octene copolymer elastomer (EOC) was contained for comparison. Then, the samples were treated using a thermal cycling process with a temperature range from −30 to 150°C, and the number of thermal cycles was set from 0 to 15. Scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry and X‐ray diffraction measurements were taken to facilitate the comprehension of structural changes. Additionally, measurements were taken to assess the trap distribution and direct current (DC) breakdown strength of the samples. The obtained results revealed that following thermal cycling ageing, the morphology and crystallinity of PP/PBE/BN remained almost unchanged. In contrast, PP/EOC/BN exhibited substantial microstructural damage accompanied by a significant reduction in crystallinity. As the number of thermal cycles increased, the trap level and DC breakdown strength of PP/PBE/BN were maintained at high levels, while those of PP/EOC/BN initially remained stable but then experienced a sharp decline. It is suggested that the addition of BN nanoparticles enhances the thermal cycling ageing resistance of the PP/PBE blend, whereas it weakens this resistance of the PP/EOC blend.

Accounting for Greenhouse Gas Emissions in the Agricultural System of China Based on the Life Cycle Assessment Method

Agricultural systems contribute nearly one-third of global anthropogenic GHG emissions and are an important source of GHGs globally. The clarification of the GHG emission pattern from agriculture is of paramount importance in the establishment of an agricultural emission reduction mechanism and the realization of China’s dual-carbon target. Based on the life cycle assessment method (LCA), this paper comprehensively quantifies the greenhouse gas emissions from the agricultural system in China, encompassing rice, wheat, and corn cultivation as well as animal husbandry including cows, horses, donkeys, mules, camels, pigs, and sheep. The analysis covers the period 2000–2020 and examines the spatial distribution, temporal trends, and structural changes in the greenhouse gas emissions within China’s agriculture sector. The main results are as follows: (1) from 2000 to 2020, China witnessed a consistent upward trajectory in its total agricultural GHG emissions, exhibiting an average annual growth rate of 0.73%. Notably, methane (CH4) emissions emerged as the largest contributor, displaying an overall fluctuating pattern. Carbon dioxide (CO2) emissions demonstrated intermittent increases with a noteworthy annual growth rate of 3%, signifying the most rapid expansion within this context. Conversely, nitrous oxide (N2O) emissions experienced decline over the specified period. (2) GHG emissions from cultivation demonstrate an upward trajectory, primarily driven by the CH4 emissions originating from rice cultivation and CO2 resulting from straw incineration. Conversely, GHG emissions stemming from animal husbandry declined, with the primary source being CH4 emissions arising from animal enteric fermentation. Agricultural N2O emissions predominantly arise due to manure management and nitrogen fertilizer application. (3) Agricultural greenhouse gas emissions exhibit significant variations in spatial distribution, gradually concentrating towards the North China Plain, the middle and lower reaches of the Yangtze River, and the northeast. Specifically, agricultural CH4 emissions are progressively concentrated in China’s pivotal rice-growing regions, encompassing the middle and lower reaches of the Yangtze River Plain, as well as livestock breeding areas like Inner Mongolia. Agricultural CO2 emissions primarily concentrate in dryland crop production zones such as North China and Northeast China. Meanwhile, Agricultural N2O emissions predominantly occur in Inner Mongolia and the North China Plain. China’s agricultural greenhouse gas emissions in 2020 show a significant spatial clustering effect, with hotspots primarily concentrated in Shandong, Anhui, Henan, and other regions and cold spots focused in the western and southern areas. The emission patterns of agricultural GHGs are closely intertwined with farming practices, regional development levels, and national policy; hence, tailored measures for emission reduction should be formulated based on specific crop types, livestock categories, agricultural production activities, and regional development characteristics.

Randomized controlled double-blind trial of methylprednisolone versus placebo in patients with post-COVID-19 syndrome and cognitive deficits: study protocol of the post-corona-virus immune treatment (PoCoVIT) trial

IntroductionPost-COVID-19 Syndrome (PCS) includes neurological manifestations, especially fatigue and cognitive deficits. Immune dysregulation, autoimmunity, endothelial dysfunction, viral persistence, and viral reactivation are discussed as potential pathophysiological mechanisms. The post-corona-virus immune treatment (PoCoVIT) trial is a phase 2a randomized, controlled, double-blind trial designed to evaluate the effect of methylprednisolone versus placebo on cognitive impairment in PCS. This trial is designed based on the hypothesised autoimmunological pathogenesis and positive aberrations, employing a series of off-label applications.MethodsRecruitment criteria include a diagnosis of PCS, a minimum age of 18 years and self-reported cognitive deficits at screening. A total of 418 participants will be randomly assigned to either verum or placebo intervention in the first phase of the trial. The trial will consist of a first trial phase intervention with methylprednisolone versus placebo for six weeks, followed by a six-week treatment interruption period. Subsequently, an open second phase will offer methylprednisolone to all participants for six weeks. Outpatient follow-up visits will take place two weeks after each trial medication cessation. The third and final follow-up, at week 52, will be conducted through a telephone interview. The primary outcome measures an intra-patient change of 15 or more points in the memory satisfaction subscale of the Multifactorial Memory Questionnaire (MMQ) from baseline to follow-up 1 (week 8). Key secondary outcomes include long-term intra-patient changes in memory satisfaction from baseline to follow-up 2 (week 20), changes in other MMQ subscales (follow-up 1 and 2), and changes in neuropsychological and cognitive scores, along with assessments through questionnaires focusing on quality of life, fatigue, and mood over the same periods. Exploratory outcomes involve molecular biomarkers variations in serum and cerebrospinal fluid, as well as structural and functional brain magnetic resonance imaging (MRI) parameters changes related to cognition.PerspectiveThis trial aims to contribute novel evidence for treating patients with PCS, with a primary focus on those manifesting cognitive deficits. By doing so, it may enhance comprehension of the underlying pathophysiological mechanisms, thereby facilitating biomarker research to advance our understanding and treatment of patients with PCS.