Plasma Profiles Research Articles

MicroRNAs signatures as potential molecular markers in mild cognitive impairment: a meta-analysis

Mild cognitive impairment (MCI) is characterized by a decline in cognitive functioning without significant interference in daily activities. Its high heterogeneity and elevated conversion rate to dementia pose challenges for accurate diagnosis and monitoring, highlighting the urgent need to identify methodologies focused on the early detection and intervention of MCI. Due to their biological characteristics, microRNAs (miRNAs) are potential candidates as non-invasive molecular markers for the identification and assessment of MCI progression. Therefore, in this study, we conducted a meta-analysis to identify the miRNAs commonly deregulated in MCI, focusing on expression profiles in plasma, serum, and extracellular vesicle samples. Our analysis identified eight upregulated miRNAs, including hsa-miR-149-3p, and four downregulated miRNAs, such as Let-7f-5p. Notably, hsa-miR-149-3p emerged as a central node in interaction networks, suggesting its crucial role in regulating cellular processes relevant to MCI. Additionally, pathway analysis revealed significant enrichment in biological processes associated with transcriptional regulation and neurodegeneration. Our results underscore the potential of circulating miRNAs as non-invasive molecular markers for MCI and open the possibility for new methodologies that enable more accurate diagnosis and monitoring of disease progression. Validating the expression of miRNAs such as hsa-miR-149-3p and Let-7f-5p, along with identifying their functional role in the specific context of MCI, is essential to establish their biological relevance. This work contributes to the understanding of the miRNA profile in mild cognitive impairment using easily accessible samples, which could be useful for the development of various strategies aimed at preventing or delaying MCI in individuals at risk of developing dementia, including Alzheimer’s disease.

Proteomic, metabolomic and lipidomic profiles in community acquired pneumonia for differentiating viral and bacterial infections

Community-acquired pneumonia (CAP) has a significant impact on public health, especially in light of the recent SARS-CoV-2 pandemic. To enhance disease characterization and improve understanding of the underlying mechanisms, a comprehensive analysis of the plasma lipidome, metabolome and proteome was conducted in patients with viral and bacterial CAP infections, including those induced by SARS-CoV-2. Lipidomic, metabolomic and proteomic profiling were conducted on plasma samples of 69 patients suffering either from viral or bacterial CAP. Lipid and metabolite analyses were LC-MS-based, while proteomic analyses were performed using multiple panels of the Olink platform. Statistical methods, machine learning and pathway analyses were conducted investigating differences between the infection types. Through comparison of the bacterial and viral pathogen groups, distinct signatures were observed in the plasma profiles. Notably, linoleic acid-derived inflammation signaling metabolites (EpOME and DiHOME) were increased in viral CAP compared to bacterial CAP. Similarly, proteins involved in cellular immune response and apoptosis (LAG-3 and TRAIL) showed elevated levels in viral CAP, while bacterial CAP exhibited notable elevation in pattern-recognizing receptors (CLEC4D and EN-RAGE). Additionally, within the lipidomic profile at baseline, several lipids displayed notable differences between viral and bacterial pneumonia, including bile acids (GCA, TCA, TCDCA), various tri- and diglycerides (TGs and DGs), and several phosphatidylcholines (PCs). These findings hold promise for facilitating the differential diagnosis of viral and bacterial pulmonary infections based on the systemic lipidome, metabolome and proteome, enabling timely treatment decisions. Additionally, they highlight potential targets for drug research, advancing therapeutic interventions in CAP. By providing valuable insights into the molecular characterization of CAP, this study contributes to the improvement of understanding the disease and, ultimately, the development of effective treatment strategies.

Advancing Chronic Liver Disease Diagnoses: Targeted Proteomics for the Non-Invasive Detection of Fibrosis

Chronic liver disease poses significant challenges to healthcare systems, which frequently struggle to meet the needs of end-stage liver disease patients. Early detection and management are essential because liver damage and fibrosis are potentially reversible. However, the implementation of population-wide screenings is hindered by the asymptomatic nature of early chronic liver disease, along with the risks and costs associated with traditional diagnostics, such as liver biopsies. This study pioneers the development of innovative, minimally invasive methods capable of improving the outcomes of liver disease patients by identifying liver disease biomarkers using quantification methods with translational potential. A targeted mass spectrometry assay based on stable isotope standard protein epitope signature tags (SIS-PrESTs) was employed for the absolute quantification of 108 proteins in just two microliters of plasma. The plasma profiles were derived from patients of various liver disease stages and etiologies, including healthy controls. A set of potential biomarkers for stratifying liver fibrosis was identified through differential expression analysis and supervised machine learning. These findings offer promising alternatives for improved diagnostics and personalized treatment strategies in liver disease management. Moreover, our approach is fully compatible with existing technologies that facilitate the robust quantification of clinically relevant protein targets via minimally disruptive sampling methods.

Constitutive loss of kynurenine-3-monooxygenase changes circulating kynurenine metabolites without affecting systemic energy metabolism.

Kynurenic acid (KYNA) and quinolinic acid (QUIN) are metabolites of the kynurenine pathway of tryptophan degradation with opposing biological activities in the central nervous system. In the periphery, KYNA is known to positively affect metabolic health, whereas the effects of QUIN remain less explored. Interestingly, metabolic stressors, including exercise and obesity, differentially change the balance between circulating KYNA and QUIN. Here, we hypothesized that chronically elevated levels of circulating KYNA and reduced levels of QUIN would manifest as differences in whole-body energy metabolism. To test this, we used a mouse model lacking the enzyme kynurenine 3-monooxygenase (KMO), thus shunting kynurenine away from QUIN synthesis and towards KYNA production. KMO-deficient and wild-type littermate male and female mice were evaluated under chow and high-fat diets. Comprehensive kynurenine pathway metabolite profiling in plasma showed that the loss of KMO elicits robust changes in circulating levels of kynurenine metabolites. This included a 45-fold increase in kynurenine, a 26-fold increase in KYNA, and a 99% decrease in QUIN levels, depending on the diet. However, despite these changes, loss of KMO did not significantly impact whole-body energy metabolism or change the transcriptomic profile of subcutaneous adipose tissue on either diet. With KMO inhibitors being considered as therapeutic candidates for various disorders, this work shows that chronic systemic KMO inhibition does not have widespread metabolic effects. Our data also indicates that the beneficial effects of KYNA on metabolism may depend on its acute, intermittent elevation in circulation, akin to transient exercise-induced signals that mediate improved metabolic health.

Metabolomics insights into doxorubicin and 5-fluorouracil combination therapy in triple-negative breast cancer: a xenograft mouse model study

BackgroundBreast cancer is one of the most prevalent malignancies and a leading cause of death among women worldwide. Among its subtypes, triple-negative breast cancer (TNBC) poses significant clinical challenges due to its aggressive behavior and limited treatment options. This study aimed to investigate the effects of doxorubicin (DOX) and 5-fluorouracil (5-FU) as monotherapies and in combination using an established MDA-MB-231 xenograft model in female BALB/C nude mice employing advanced metabolomics analysis to identify molecular alterations induced by these treatments.MethodsWe conducted comprehensive plasma and tumor tissue sample profiling using ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS).ResultsEach treatment group exhibited unique metabolic profiles in plasma and tumor analysis. Univariate and enrichment analyses identified alterations in metabolic pathways. The combination treatment of DOX + 5-FU induced the most extensive metabolic alterations disrupting key pathways including purine, pyrimidine, beta-alanine, and sphingolipid metabolism. It significantly reduced critical metabolites such as guanine, xanthine, inosine, L-fucose, and sphinganine, demonstrating enhanced cytotoxic effects compared to individual treatments. The DOX treatment uniquely increased ornithine levels, while 5-FU altered sphingolipid metabolism, promoting apoptosis.SignificanceThis in vivo study highlights TNBC’s metabolic alterations to chemotherapeutics, identifying potential biomarkers like L-fucose and beta-alanine, and provides insights for improving treatment strategies.

Enhanced pedestal transport driven by edge collisionality on Alcator C-Mod and its role in regulating H-mode pedestal gradients

Abstract Experimental measurements of plasma and neutral profiles across the pedestal are used in conjunction with 2D edge modeling to examine pedestal stiffness in Alcator C-Mod H-mode plasmas. Enhanced D α experiments on Alcator C-Mod observed pedestal degradation and loss in confinement below a critical value of net power crossing the separatrix, P net = P net crit ≈ 2.3 MW, in the absence of any external fueling. New analysis of ionization and particle flux profiles reveal saturation of the pedestal electron density, n e ped , despite continuous increases in ionization throughout the pedestal, inversely related to P net . A limit to the pedestal ∇ n e emerges as the particle flux, Γ D , continues to grow, implying increases in the effective particle diffusivity, D eff . This is well-correlated with the separatrix collisionality, ν sep ∗ and a turbulence control parameter, α t , implying a possible transition in type of turbulence. The transition is well correlated with the experimentally observed value of P net crit . SOLPS-ITER modeling is performed for select discharges from the power scan, constrained with experimental electron and neutral densities, measured at the outer midplane. The modeling confirms general growth in D eff , consistent with experimental findings, and additionally suggests even larger growth in χ e at the same P net crit .

Effects of new lipid ingredients during pregnancy and lactation on rat offspring brain gene expression.

Maternal dietary fat intake during pregnancy and lactation may influence the bioavailability of essential lipophilic nutrients, such as docosahexaenoic acid (DHA), that are important for both the mother and her child's development. This study aimed to evaluate the effects of different maternal fat diets on fat absorption and pup brain development by analyzing gene expression. Rats were fed diets with different lipid matrices during pregnancy and lactation: diet A, mono and diglycerides (MDG) + soy lecithin phospholipids (PL); diet B, MDG + soy lecithin PL + milk-derived PL; and a control diet. All diets contained the same amount of DHA. We determined maternal dietary fat absorption, as well as the offspring fatty acid (FA) profile in both plasma and brain samples at birth and in pups at 14 days post-natal. In addition, microarray analysis was performed to characterize the pup brain gene expression. Maternal dietary fat and DHA apparent absorption was enhanced only with diet B. However, we observed higher plasma DHA and total FA concentrations in lactating pups from the experimental groups A and B compared to the control. Both brain DHA and total FA concentrations were also higher in fetuses and 14-day-old pups from group A with respect to the control, with diet B following the same trend. Offspring brain gene expression was affected by both diets A and B, with changes observed in synaptic and developmental processes in the fetuses, and the detoxification process in 14-day-old pups. Incorporating MDG and PL-rich lipid matrices into maternal diets during pregnancy and lactation may be highly beneficial for ensuring proper neurodevelopment of the fetus and newborn.

A study of lipid profile peculiarities and atherogenic index of plasma in patients younger than fifty years of age with newly diagnosed rheumatoid arthritis

ABSTRACT Context: Cardiovascular disease (CVD) is an important cause of mortality in rheumatoid arthritis (RA). Aims: Evaluation of lipid profile and atherogenic index of plasma (AIP) in newly diagnosed DMARD naïve patients of RA younger than 50 years of age, and its comparison with age- and sex-matched healthy controls. Settings and Design: Cross-sectional comparative study. Methods and Material: 48 patients aged 18 to 50 years fulfilling the ACR/EULAR criteria for RA, not yet on DMARD or steroids and 51 healthy controls were included. Disease activity was assessed, and lipid profile was estimated: total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG) and very low-density lipoprotein (VLDL). Atherogenic index of plasma (AIP) was calculated using a standard formula. Statistical Analysis Used: Independent sample t-tests were used to determine the statistical significance of mean values between the case and control groups. Pearson’s correlation test was used to correlate various components of the lipid profile and the atherogenic index with DAS28-ESR. Results: Significantly reduced levels of HDL (39.31 ± 6.52 mg/dl) were found in patients with RA as compared to the healthy controls. Serum TG was significantly higher in the cases (138.35 ± 39.23 mg/dl). TC level was significantly elevated in the cases. Mean atherogenic index in cases was significantly higher (0.17 + 0.14) in some cases. Only a weak correlation was found between lipid profile components and DAS28-ESR. Conclusions: Serum HDL level was significantly lower, and TC, TG levels and AIP were significantly higher in younger patients of early DMARD naïve RA pointing to a higher CV risk.

Carotenoid profile in maternal and cord plasma and its trends in breast milk during lactation: a comparative study among three cities in northern China.

Increasing evidence suggests that carotenoids play an important role in visual and cognitive development during early life. This study aimed to depict the carotenoid profile in maternal/cord plasma and breast milk in three northern cities of China while investigating the association between dietary carotenoid intake and breast milk carotenoid levels. We enrolled 990 lactating mothers from three urban northern Chinese cities to collect breast milk (including colostrum, transitional milk, early mature milk, middle mature milk, and late mature milk). Among them, 90 participants also provided maternal/cord blood. The dietary carotenoid intake was recorded in the corresponding stages according to the Food Frequency Questionnaire and 24-hour dietary recall. The levels of carotenoids (lutein, zeaxanthin, β-cryptoxanthin, β-carotene, and lycopene) in maternal/cord plasma and breast milk were analyzed using high-performance liquid chromatography. We found a significant correlation between carotenoid concentrations in maternal and cord plasma. Moreover, carotenoid concentrations in maternal plasma were significantly higher than those in cord plasma. The total carotenoid levels in breast milk decreased from colostrum to late mature milk. β-Carotene predominated in colostrum, whereas lutein dominated in transitional and mature milk. We also found that breast milk carotenoid levels correlated with dietary carotenoid intake to a certain extent, particularly during the early stages of lactation. Therefore, we encourage women to appropriately increase their dietary intake of carotenoid-rich vegetables and fruits during pregnancy and lactation, particularly during work hours after lactation leave. Moreover, the variance of the carotenoid profile in maternal/cord plasma and breast milk across the three cities implied the necessity of further depicting the carotenoid status and influencing factors across different areas in China.

Proteomic and metabolomic profiling of plasma uncovers immune responses in patients with Long COVID-19.

Long COVID is an often-debilitating condition with severe, multisystem symptoms that can persist for weeks or months and increase the risk of various diseases. Currently, there is a lack of diagnostic tools for Long COVID in clinical practice. Therefore, this study utilizes plasma proteomics and metabolomics technologies to understand the molecular profile and pathophysiological mechanisms of Long COVID, providing clinical evidence for the development of potential biomarkers. This study included three age- and gender-matched cohorts: healthy controls (n = 18), COVID-19 recovered patients (n = 17), and Long COVID patients (n = 15). The proteomics results revealed significant differences in proteins between Long COVID-19 patients and COVID-19 recovered patients, with dysregulation mainly focused on pathways such as coagulation, platelets, complement cascade reactions, GPCR cell signal transduction, and substance transport, which can participate in regulating immune responses, inflammation, and tissue vascular repair. Metabolomics results showed that Long COVID patients and COVID-19 recovered patients have similar metabolic disorders, mainly involving dysregulation in lipid metabolites and fatty acid metabolism, such as glycerophospholipids, sphingolipid metabolism, and arachidonic acid metabolism processes. In summary, our study results indicate significant protein dysregulation and metabolic abnormalities in the plasma of Long COVID patients, leading to coagulation dysfunction, impaired energy metabolism, and chronic immune dysregulation, which are more pronounced than in COVID-19 recovered patients.

Follicular fluid and plasma lipidome profiling and associations towards embryonic development outcomes during ART treatment.

It is well acknowledged that lipids assume a critical role in oocyte maturation and early embryonic metabolism, this study aimed to evaluate the relationship between the lipid composition of plasma and follicular fluid (FF), and the consequences of embryonic development. This study compared the lipidomic profiles of paired plasma and FF samples obtained from sixty-five Chinese women who underwent assisted reproductive technology (ART) treatments. Non-targeted lipidomics analysis. Results not only indicated similarities in lipid composition between these biofluids, but also revealed a number of unique differences. The biomatrix distinction was found to be primarily driven by lipids belonging to the lysophosphatidylcholines (LPC), phosphatidylethanolamines (PE), ether PE, and triglyceride (TG) classes. In addition, specific species from these subclasses were discovered to be correlated with embryo development outcomes during ART. Notably, the composition of the fatty acyl chains appeared to play a crucial role in these associations. Furthermore, thirteen plasma lipid variables were identified, represented by Phosphatidylcholine 18:014:0 and PE P-18:020:1, which correlated with successful blastocyst formation (BF). The present study demonstrated that FF has a distinctive lipid composition, setting it apart from plasma; and the association observed with embryonic development underscored an important role of lipid composition in the healthy development of oocytes.

In vivo evaluation of selenium-tellurium based nanoparticles as a novel treatment for bovine mastitis

BackgroundBovine mastitis is one of the main causes of reduced production in dairy cows. The infection of the mammary gland is mainly caused by the bacterium Staphylococcus aureus, whose resistant strains make the treatment of mastitis with conventional antibiotics very difficult and result in high losses. Therefore, it is important to develop novel therapeutic agents to overcome the resistance of mastitis-causing strains. In this study, novel selenium-tellurium based nanoparticles (SeTeNPs) were synthesized and characterized. Their antibacterial activity and biocompatibility were evaluated both in vitro and in vivo using a bovine model. A total of 10 heifers were divided into experimental and control groups (5 animals each). After intramammary infection with methicillin resistant S. aureus (MRSA) and the development of clinical signs of mastitis, a dose of SeTeNPs was administered to all quarters in the experimental group.ResultsBased on in vitro tests, the concentration of 149.70 mg/L and 263.95 mg/L of Se and Te, respectively, was used for application into the mammary gland. Three days after SeTeNPs administration, MRSA counts in the experimental group showed a significant reduction (P < 0.01) compared to the control group. The inhibitory effect observed within the in vitro experiments was thus confirmed, resulting in the suppression of infection in animals. Moreover, the superior biocompatibility of SeTeNPs in the organism was demonstrated, as the nanoparticles did not significantly alter the inflammatory response or histopathology at the site of application, i.e., mammary gland, compared to the control group (P > 0.05). Additionally, the metabolic profile of the blood plasma as well as the histology of the main organs remained unaffected, indicating that the nanoparticles had no adverse effects on the organism.ConclusionsOur findings suggest that SeTeNPs can be used as a promising treatment for bovine mastitis in the presence of resistant bacteria. However, the current study is limited by its small sample size, making it primarily a proof of the concept for the efficacy of intramammary-applied SeTeNPs. Therefore, further research with a larger sample size is needed to validate these results.

EMC3-EIRENE simulations of edge plasma and impurity transport by toroidally localized argon seeding on CFETR X-divertor

Abstract Three-dimensional (3D) Edge Monte Carlo transport code EMC3-EIRENE has been employed to study edge plasma and impurity transport with toroidally localized argon seeding on Chinese fusion engineering testing reactor (CFETR) X-divertor configuration. The argon impurity seeded at different poloidal locations has been investigated to evaluate the varied profile of the main plasma in the scrape-off layer (SOL) and on the divertor targets, which shows a strong dependence on the poloidal position of argon gas puffing. The argon impurity seeded at the upstream SOL regions can result in a toroidally asymmetric distribution of electron density and temperature, while a toroidally symmetric distribution is obtained for argon seeded at the strike point regions. The deposition pattern of electron density and temperature shows the several lobe-like and island-like structures on the 3D divertor targets of CFETR with upstream argon injections, whereas the perturbed profile is achieved for argon seeding at the strike point regions. In order to verify the toroidal asymmetry of heat loads distribution, the argon impurity seeded at different poloidal locations has been investigated to estimate its influence on toroidal heat loads on divertor plates. The argon injected at the strike point regions gives rise to a toroidal asymmetry of heat loads distribution on divertor targets, while a toroidal symmetry of heat loads distribution is gained for argon injected at the upstream SOL locations.

Advances in Canine Anesthesia: Physiologically Based Pharmacokinetic Modeling for Predicting Propofol Plasma Profiles in Canines with Hepatic Impairment.

Background: A PBPK model allows the prediction of the concentration of drug amounts in different tissues and organs over time and can be used to simulate and optimize different therapeutic protocols in healthy and sick individuals. The objective of this work was to create a PBPK model to predict propofol doses for healthy canines and canines with hepatic impairment. Methods: The study methodology was divided into two major phases, in which the first phase consisted of creating the PBPK model for healthy canines, and in the second phase, this model was adjusted for canines with hepatic impairment. The model for healthy canines presented good predictive performance, evidenced by the value of the performance measure of the geometric mean fold error that ranged from 0.8 to 1.25, meeting the double error criterion. The simulated regimen for healthy canines, i.e., of 5 mg/kg (administered as a bolus) followed by a continuous infusion at a rate of 0.13 mg/kg/min, was sufficient and ensured that all simulated subjects achieved the target plasma concentration. Canines with 60% and 40% liver function had infusion rate adjustments to ensure that individuals did not exceed the therapeutic window for maintenance of anesthesia. Results: The results presented in this manuscript are suggestive of the effectiveness and practicality of a PBPK model for propofol in canines, with a particular focus on hepatic impairment.

Metabolomic and Lipidomic Profiling for Pre-Transplant Assessment of Delayed Graft Function Risk Using Chemical Biopsy with Microextraction Probes

Organ shortage remains a significant challenge in transplantology, prompting efforts to maximize the use of available organs and expand the donor pool, including through extended criteria donors (ECDs). However, ECD kidney recipients often face poorer outcomes, including a higher incidence of delayed graft function (DGF), which is linked to worse graft performance, reduced long-term survival, and an increased need for interventions like dialysis. This underscores the urgent need for strategies to improve early DGF risk assessment and optimize post-transplant management for high-risk patients. This study conducted multi-time point metabolomic and lipidomic analyses of donor kidney tissue and recipient plasma to identify compounds predicting DGF risk and assess the translational potential of solid-phase microextraction (SPME) for graft evaluation and early complication detection. The SPME-based chemical biopsy enabled a direct kidney analysis, while thin-film microextraction facilitated high-throughput plasma preparation. Following high-performance liquid chromatography coupled with a mass spectrometry analysis, the random forest algorithm was applied to identify compounds with predictive potential for assessing DGF risk before transplantation. Additionally, a comparison of metabolomic and lipidomic profiles of recipient plasma during the early post-operative days identified metabolites that distinguish between DGF and non-DGF patients. The selected compounds primarily included amino acids and their derivatives, nucleotides, organic acids, peptides, and lipids, particularly phospholipids and triacylglycerols. In conclusion, this study highlights the significant translational potential of chemical biopsies and plasma metabolite analyses for risk assessments and the non-invasive monitoring of DGF. The identified metabolites provide a foundation for developing a comprehensive DGF assessment and monitoring method, with potential integration into routine clinical practice.

Pharmacokinetic/pharma-codynamic study of pralurbactam (FL058) combined with meropenem in a neutropenic murine thigh infection model.

Pralurbactam (FL058) is a novel β-lactamase inhibitor with good inhibitory activity on class A, C, and D β-lactamases. This study aimed to evaluate the pharmacokinetic/pharmacodynamic (PK/PD) relationship of pralurbactam/meropenem in a neutropenic murine thigh infection model. After 2-h infection, neutropenic mice was treated with meropenem every 2 h alone or in combination with pralurbactam at different dosing frequencies for 24 h, and the colony count in the thighs was determined before and after treatment. The maximum effect model was fit to the PK/PD relationship to determine the PK/PD index and targets for pralurbactam in combination with meropenem resulting in a static effect and 1-log10 kill. The plasma drug concentration-time data demonstrated that the PK profiles of pralurbactam were consistent with a one-compartment model. Pralurbactam demonstrated a linear PK profile in mice plasma. The percent time of free drug above 1 mg/L (%fT > 1 mg/L) was the PK/PD index that best described the bacterial killing effect of pralurbactam/meropenem over 24 h. When the PK/PD index %fT > 1 mg/L reached 38.4% and 63.6%, pralurbactam/meropenem combination would achieve bacteriostatic effect and 1-log10 reduction against Klebsiella pneumoniae in thigh bioburden, respectively. These PK/PD data derived from mouse thigh infection models will be used to inform the optimal dosing regimen of pralurbactam/meropenem combination in clinical trials.

MicroRNAs in seminal plasma are able to discern infertile men at increased risk of developing testicular cancer.

Male infertility is a risk factor for the development of testicular germ cell tumors. In this study, we investigated microRNA profiles in seminal plasma to identify potential noninvasive biomarkers able to discriminate the men at highest risk of developing cancer among the infertile population. We compared the microRNA profiles of individuals affected by testicular germ cell tumors and healthy individuals with normal or impaired spermiograms using high-throughput technology and confirmed the results by single-assay digital PCR. We found that miR-221-3p and miR-222-3p were downregulated and miR-126-3p was upregulated in cancer patients compared to both infertile and fertile men. ROC curve analysis confirmed that miR-126 upregulation is able to identify cancer patients among the infertile male population. In addition, in-depth bioinformatics analysis based on weighted gene co-expression networks showed that the identified miRNAs regulate cellular pathways involved in cancer.

Helicon normal modes in radially non-uniform plasma column

Abstract Helicon discharges are often considered somewhat mysterious, exhibiting experimental behaviors that are challenging to explain, such as abrupt plasma density jumps, hysteresis, and 'blue core' formation, among others. A significant part of the difficulty in modeling helicon plasmas stems from the limitations of simple analytical approaches that rely on approximations, such as constant plasma density or collisionless plasma, which fail to accurately describe helicon wave physics. We developed a semi-analytical approach to determine helicon normal modes in a collisional plasma column with an arbitrary radial plasma density profile. The influence of radial density profiles on modes propagation, and particularly on their energy deposition patterns, is then investigated. Notably, the study shows that sharp density drops at the plasma column edge lead to edge-localized power deposition, whereas gently varying radial plasma profiles (bell shapes) result in axially peaked power deposition. In the former case, the rapid damping of the Trivelpiece-Gould (TG) component of the wave at the plasma edge is clearly responsible for the observed energy deposition profile. As the profile sharpness decreases, as in bell-shaped plasmas, the TG component of the modes becomes less dominant, and the radial power deposition profile is mainly determined by the Helicon (H) component. Overall, this study of normal modes also demonstrates that dominant H modes are expected to experience much less axial damping than predicted when considering constant densities. Finally, it is also shown that smooth radial density profiles allow a new family of modes to propagate, characterized by long axial wavelengths and slightly off-axis energy deposition patterns.

168 Proteomic profiling and functional annotation of indigenous Zulu ram seminal plasma

168 Proteomic profiling and functional annotation of indigenous Zulu ram seminal plasma

Assessing the impact of alpha particles on thermal confinement in JET D-T plasmas through global GENE-Tango simulations

Abstract The capability of the global, electromagnetic gyrokinetic GENE code interfaced with the transport Tango solver is exploited to address the impact of fusion alpha particles (in their dual role of fast particles and heating source) on plasma profiles and performance at JET in the discharges with the highest quasi-stationary peak fusion power during the DTE2 experimental campaigns. Employing radially global nonlinear electromagnetic GENE-Tango simulations, we compare results with/without alpha particles and alpha heating. Our findings reveal that alpha particles have a negligible impact on turbulent transport, with GENE-Tango converging to similar plasma profiles regardless of their inclusion as a kinetic species in GENE. On the other hand, alpha heating is found to contribute to the peaking of the electron temperature profiles, leading to a 1 keV drop on the on-axis electron temperature when alpha heating is neglected in Tango. The minimal impact of alpha particles on turbulent transport in this JET discharge–despite this being the shot with the highest fusion output–is attributed to the low content of fusion alpha in this discharge. To assess the potential impact of alpha particles on turbulent transport in regimes with higher alpha particle density, as expected in ITER and fusion reactors, we artificially increased the alpha particle concentration to levels expected for ITER. By performing global nonlinear GENE standalone simulations, we found that increasing the alpha particle density beyond five times the nominal value lead to significant overall turbulence destabilization. These results demonstrate that an increased alpha particle concentration can significantly impact transport properties under simulated JET experimental conditions. However, these findings cannot be directly extrapolated to ITER due to the substantial differences in parameters such as plasma size, magnetic field, plasma current, and thermal pressure.