Search Results (553)

Parkinson’s disease (PD) is characterized by progressive degeneration of nigrostriatal dopaminergic neurons, leading to motor dysfunction and compensatory postsynaptic dopamine receptor alterations. Valproic acid (VPA), a histone deacetylase inhibitor, has shown neuroprotective properties; however, its dose-dependent effects on dopaminergic integrity and dopamine D2 receptor (D2R) regulation remain unclear. Adult male Wistar rats received VPA (200 or 400 mg/kg, p.o.) or vehicle for 20 days prior to unilateral 6-hydroxydopamine (6-OHDA) lesioning. Motor performance was evaluated using the beam balance test, exploratory behavior in the open field, striatal dopamine levels by PLC-electrochemical detection, and D2R protein expression by Western blot. The 6-OHDA lesion induced marked motor deficits, reduced striatal dopamine content, and significantly increased D2R expression. VPA at 200 mg/kg produced only minor, non-significant effects. In contrast, VPA at 400 mg/kg preserved motor performance, attenuated dopamine depletion, and normalized striatal D2R expression. These findings demonstrate a clear dose-dependent neuroprotective effect of VPA and indicate that stabilization of postsynaptic D2R expression accompanies preservation of dopaminergic terminals in the 6-OHDA rat model. Full article

This study presents the Multi-Method Convergence Protocol (MMCP), a decision-making framework designed to overcome the mono-objective limitations of HOMER Pro (Hybrid Optimization Model for Electric Renewables) and the instability commonly observed among traditional MCDM approaches. Applied to a hybrid PV–wind–grid Smart Grid (Intelligent Electrical Power Grid) in the Provence-Alpes-Côte d’Azur region (France), the protocol transforms techno-economic simulation outputs into robust and explainable multi-criteria decisions. MMCP integrates five sequential stages—normalization, AHP-based (Analytic Hierarchy Process) weighting, multi-method ranking (TOPSIS, PROMETHEE II, ELECTRE II (Elimination and Choice Expressing Reality II), and VIKOR), Borda–Copeland (Borda Count Ranking Method–Copeland Pairwise Aggregation Method) co-aggregation, and statistical validation—using Kendall’s τb (Kendall’s Rank Correlation Coefficient) and Spearman’s ρ (Spearman’s Rank Correlation Coefficient). Results reveal strong convergence between compensatory and non-compensatory models (τb ≥ 0.75; ρ ≥ 0.90), confirming the internal coherence and structural stability of the rankings. Scenario 17 emerges as the optimal configuration, combining low LCOE (Levelized Cost of Energy) with reduced emissions and balanced renewable penetration. The near-linear alignment between aggregation methods validates the protocol’s reliability and methodological transparency. Overall, MMCP provides a scalable and traceable foundation for sustainable Smart Grid planning and evidence-based energy governance. Full article

Background/Objectives: Preterm birth interrupts nephrogenesis during a critical developmental window, resulting in reduced nephron endowment and lifelong renal vulnerability. Evidence indicates that individuals born preterm are at increased risk for hypertension, albuminuria, and chronic kidney disease (CKD) across the life course. This review synthesizes current evidence linking prematurity with adverse renal outcomes, explores key pathophysiological mechanisms, and discusses emerging biomarkers together with therapeutic strategies. Methods: This comprehensive review integrates evidence from clinical cohort studies, population-based registries, meta-analyses and experimental models. Factors such as neonatal acute kidney injury (AKI), nephrotoxic exposures and cardiometabolic interactions were integrated to provide a life-course perspective. Results: Preterm birth leads to reduced nephron endowment, compensatory glomerular hypertrophy, and hyperfiltration, which predispose to progressive nephron loss. Postnatal factors, including neonatal AKI, inflammation, nephrotoxic medications, and later cardiometabolic stress, act as cumulative “hits”, accelerating renal injury trajectories. Clinical studies demonstrate a higher prevalence of reduced estimated glomerular filtration rate, albuminuria, elevated blood pressure, and smaller kidney volumes from childhood into adulthood. Emerging biomarkers such as cystatin C, alongside imaging-based estimates of nephron endowment, may enhance early risk stratification. Conclusions: Preterm birth represents an independent, lifelong risk factor for CKD through combined developmental and postnatal mechanisms. Structured long-term surveillance and early preventive strategies are essential to preserve renal reserve in this population. Advances in biomarker-guided monitoring and targeted interventions may enable earlier identification of high-risk individuals and support precision approaches to nephroprotection after prematurity. Full article

This study investigates the psychological mechanisms underlying tourists’ carbon offset behavior in air travel by distinguishing between offset choice (OC) and offset spending (OS). Grounded in the Value–Belief–Norm (VBN) framework, the model integrates Environmental Value and Literacy (EVL), Green Identity and Social Motives (GISM), Trust and Risk Perception (TRP), Personal Norm Activation (PNA), and Perceived Effectiveness (PEF). Data were collected onsite from 500 international and domestic tourists at Suvarnabhumi International Airport, Thailand, between June and July 2025, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that EVL and GISM significantly enhance both PNA and PEF, which in turn exert strong positive effects on OC and OS. PNA emerges as the strongest predictor of both participation and financial commitment, highlighting the central role of moral obligation in motivating carbon offset behavior. While TRP significantly strengthens personal moral norms, its direct effect on Perceived Effectiveness is not significant, suggesting that trust primarily operates through ethical pathways rather than cognitive evaluations of program effectiveness. By distinguishing between participation decisions and spending behavior, this study extends VBN theory to the context of carbon offsets in aviation and demonstrates the mediating roles of moral norms and Perceived Effectiveness in translating environmental values and social identity into compensatory climate action. The findings offer practical implications for airlines and policymakers, emphasizing the importance of moral framing, transparency, and social identity engagement to promote voluntary carbon offset adoption in emerging carbon markets. Full article

Background/Objectives: Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by persistent synovial inflammation and vascular abnormalities. Emerging evidence suggests that dysbiosis of the microbiome contributes to the pathogenesis of this disease, while seasonal and meteorological variations represent significant factors influencing microbial community dynamics. However, the specific pathological mechanisms mediated by microbial populations within knee joint effusions of RA patients remain poorly elucidated. The present study employs 16S rRNA high-throughput sequencing technology to characterize seasonal variation patterns affecting microbial communities in knee joint effusions of RA patients and to investigate the relationship between microbial community structures and climatic lag effects. Methods: Microbial communities in knee joint effusion samples obtained from RA patients were analyzed using 16S rRNA high-throughput sequencing methodologies. A Distributed Lag Non-linear Model (DLNM) was applied to quantify the delayed effects of climatic variables on microbial community composition. The correlation patterns between meteorological parameters and community structure were elucidated through the integration of ridge regression and redundancy analysis (RDA). Preliminary identification of potential biomarkers was conducted using random forest algorithms. Results: According to research findings, the microbial composition of knee joint effusions in RA patients shows seasonal fluctuation patterns that are compatible with those seen in RA patients, even though there is no discernible seasonal change in β-diversity. Compared with samples obtained during other seasons, spring specimens exhibited significantly elevated relative abundances of both beneficial microorganisms and opportunistic pathogenic taxa. Random forest modeling identified Escherichia-Shigella and Curtobacterium as preliminary candidate biomarkers; however, external validation is required to establish their specificity as disease indicators. Further analysis revealed that although short-term meteorological fluctuations exert minimal influence on overall microbial diversity, specific alterations in mean wind speed (MWS) and relative humidity (RH) drive compositional changes in the microbial community, manifested as rapid responses from dominant bacterial taxa and compensatory buffering effects from rare taxa. Conclusions: This study suggests that the synovial cavity microbiota in RA patients may exhibit seasonal variation patterns that are statistically associated with environmental parameters, particularly humidity and temperature. Due to the inherent limitations of the cross-sectional study design, the preliminary candidate biomarkers identified herein require validation through external cohorts. Additional investigations incorporating healthy controls and osteoarthritis (OA) cohorts are necessary to confirm specificity and to elucidate the therapeutic potential of these microbial targets for RA microbiome interventions. Currently, insufficient evidence exists to establish causal relationships among microbial populations, joint pathology, and climatic factors. Longitudinal cohort studies are imperative to validate the temporal dynamics and clinical significance of these associations. Full article

Objectives: Although behavioral studies suggest that syntactic comprehension is relatively preserved in healthy aging, the underlying neural mechanisms remain a subject of intense debate. This review aims to synthesize neuroimaging and electrophysiological evidence to clarify how the aging brain reorganizes to maintain language resilience. Methods: A systematic search was conducted across multiple databases such as PubMed and Web of Science. Twenty-three relevant empirical studies meeting our inclusion criteria were identified. The synthesis focused on regional activation patterns, functional connectivity, and temporal dynamics during syntactic processing in older adults compared to younger controls. Results: The review revealed four key findings. First, the core left-lateralized frontotemporal language network remains resilient during syntactic processing in older adults. Second, age-related changes in functional connectivity within the core network are heterogeneous, with evidence for both reduction and preservation. Third, right-hemisphere homologues are increasingly recruited, but its functional significance is condition-dependent, serving both compensatory and non-compensatory roles. Fourth, older adults increasingly engage domain-general cognitive control regions, such as the dorsolateral prefrontal cortex and pre-supplementary motor area, to support syntactic processing under high cognitive loads. Conclusions: On the basis of these findings, we propose the Graded Compensation and Cognitive Scaffolding (GCCS) model which posits that language resilience is maintained through a graded and condition-dependent adaptation of neural resources. This study critically evaluates the current literature and highlights the need for more methodologically rigorous studies to better understand the effects of aging on syntactic processing and its neural basis. Given the limited number of eligible studies, the findings of this review should be interpreted with caution. More well-powered, longitudinal research is needed to uncover the trajectory of neural reorganization during syntactic processing in older adults. Full article

Background: DNMT3B is frequently overexpressed in molecular subsets of acute myeloid leukemia (AML) and is associated with poor prognosis. Unlike DNMT3A, DNMT3B is rarely mutated, suggesting dysregulation through epigenetic mechanisms. The regulatory basis and downstream consequences of DNMT3B overexpression in AML remain incompletely defined. Methods: We integrated analyses of BeatAML, TCGA, and BLUEPRINT cohorts with multi-omic profiling (RNA-seq, DNA methylation, ATAC-seq, and proteomics) in DNMT3B-high AML models. Nanaomycin A (NanA) was used as a DNMT3B-directed functional probe to interrogate cis-regulatory remodeling, transcriptional circuitry, and apoptotic dependencies. Results: DNMT3B overexpression was linked to enhancer-associated chromatin activation rather than recurrent genetic mutation, particularly in CEBPA- and NPM1-mutant AML. NanA exposure produced focal epigenomic remodeling, including 6900 differentially methylated CpGs, with 268 CpGs located within regions of altered chromatin accessibility. These changes were accompanied by coordinated transcriptomic and proteomic reprogramming enriched for cell-cycle, checkpoint, and stress-response pathways. Functionally, DNMT3B perturbation induced redistribution of cell-cycle phases with increased S-phase fraction and progressive apoptosis. Transcriptional profiling demonstrated induction of BH3-only sensitizers (NOXA, PUMA), repression of BCL2, and compensatory upregulation of MCL1 and BCL-XL, collectively reshaping apoptotic dependency. Combined DNMT3B perturbation and BCL2 inhibition produced cooperative cytotoxicity in DNMT3B-high AML models. Conclusion: DNMT3B functions as a context-dependent epigenetic regulator linking enhancer-associated chromatin organization with proliferative control and apoptotic resistance in AML. DNMT3B-directed epigenetic perturbation remodels cis-regulatory circuitry and is associated with increased venetoclax responsiveness, supporting DNMT3B-governed networks as a candidate co-targeting axis in high-risk AML. Full article

Older adults with disabilities face compounded vulnerabilities due to both functional limitations and socioeconomic disadvantage. In South Korea, where public welfare systems remain fragmented and cultural values emphasize independence and productivity, understanding the mechanisms linking socioeconomic status (SES) to health outcomes is critical. This study investigates whether reserve capacity mediates the relationship between SES and self-rated health (SRH) in older adults with disabilities. Data were drawn from the supplementary survey on people with disabilities in the 18th wave (2023) of the Korea Welfare Panel Study (KWePS). The analytic sample included older adults aged 65 and above with registered disabilities. A multiple mediation analysis was conducted using Model 4 of the PROCESS macro in SPSS to examine whether three dimensions of reserve capacity—intrapsychic resources (self-esteem), interpersonal resources (social support satisfaction), and tangible resources (use of public disability services)—mediated the relationship between SES and SRH. Demographic and health-related covariates were statistically controlled. The results are as follows: The direct effect of SES on SRH was not significant; however, significant indirect effects were found through all three mediators. Higher SES was positively associated with intrapsychic and interpersonal resources and negatively associated with tangible resource use. Among the mediators, interpersonal resources had the strongest positive effect on SRH, while tangible resources showed a negative association—possibly due to compensatory activation or increased disease awareness among service users. The findings highlight the importance of psychosocial and relational resources in shaping perceived health among disabled older adults in Korea. Policy interventions should move beyond material assistance and focus on strengthening social networks and psychological resilience to reduce health disparities in this population. Full article

Compensatory Health Beliefs (CHBs) are cognitions that the negative effects of unhealthy behaviors can be offset by healthy ones. While their role in single behaviors is established, their mechanisms in regulating multiple health behaviors remain empirically unclear, particularly whether CHBs facilitate or inhibit actual cross-behavior compensation between physical activity (PA) and healthy eating (HE). This study tested a dual-path model proposing that CHBs are associated with immediate intention compensation via moral licensing and with long-term cross-behavior inhibition through reduced self-efficacy. A cross-sectional online survey of 366 university students assessed general CHBs, domain-specific social cognitive variables (self-efficacy, intention, planning), and self-reported PA (IPAQ-SF) and HE (calculated from reported food consumption as a dietary guideline adherence score). Data were analyzed using Structural Equation Modeling. We found that CHBs were positively associated with PA intention but negatively linked to HE intention, planning, and behavior. CHBs were also negatively related to HE self-efficacy, which was subsequently associated with lower PA planning, indicating a cross-behavior inhibition pathway. In conclusion, CHBs are linked to lower health behavior engagement through two pathways: short-term intention-based licensing across domains and self-efficacy erosion that inhibits integrated planning. This integrated model highlights the importance of addressing both CHBs and self-efficacy in health interventions. Full article

Dysarthria in patients post-stroke is often accompanied by central facial paralysis, which impairs facial motor control and emotional expression. Current assessments rely on acoustic modalities, overlooking facial pathological cues and their correlation with emotional expression, which hinders comprehensive disease assessment. To address this issue, we propose a multimodal severity classification framework that integrates facial and acoustic features. Firstly, a multi-level annotation algorithm based on a pre-trained model and motion amplitude was designed to overcome the problem of data scarcity. Secondly, facial topology was modeled using Delaunay triangulation, with spatial relationships captured via graph convolutional networks (GCNs), while abnormal muscle coordination is quantified using facial action units (AUs). Finally, we proposed a multimodal feature set fusion technology framework to achieve the compensation of facial visual features for acoustic modalities and the analysis of disease classification. Our experimental results using the THE-POSSD dataset demonstrate an accuracy of 92.0% and an F1 score of 91.6%, significantly outperforming single-modality baselines. This study reveals the changes in facial movements and sensitive areas of patients under different emotional states, verifies the compensatory ability of visual patterns for auditory patterns, and demonstrates the potential of this multimodal framework for objective assessment and future clinical applications in speech disorders. Full article

Manufacturing decarbonization and sustainability improvement require decision-support methods that can prioritise actions across multiple, often conflicting dimensions, including product quality, process stability, resource efficiency, and environmental performance. In industrial practice, such decisions are further complicated by stochastic variability and the presence of dominant drivers, which limit the usefulness of conventional linear, weighted-sum scoring approaches. This paper proposes a non-compensatory decision framework with explicit stochastic uncertainty propagation that integrates quality function deployment (QFD) with life cycle assessment (LCA) to support robust, value-driven prioritisation of manufacturing improvement actions under uncertainty. The approach combines QFD-style influence factor modelling with LCA-based environmental indicators and employs a nonlinear, non-compensatory aggregation scheme to reduce sensitivity to arbitrary weighting and to better capture dominant and tail-risk effects. Uncertainty is propagated using Monte Carlo simulation, and the stability of prioritisation outcomes is analysed using sensitivity measures. The framework is demonstrated on an industrial old corrugated container (OCC) paper machine line using operational data from plant information systems, including quality, process control, laboratory, and maintenance databases. Results show that the proposed integration yields more stable and interpretable prioritisation of improvement actions than conventional compensatory scoring methods, particularly under variable operating conditions. The proposed approach enables practical, data-driven sustainability decision-making in complex manufacturing processes under variable operating conditions and alternative process configurations. Full article

Parkinson’s disease (PD) is a heterogeneous clinical syndrome representing the final stage of a complex and long-lasting neurodegenerative process that involves not only dysfunction of the dopaminergic system but also impairments in other neurotransmitter systems. The diversity of the clinical presentation of PD, together with the existence of Parkinsonian syndromes and atypical Parkinsonism—such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and dementia with Lewy bodies (DLB)—has important implications for rehabilitation outcomes and underscores the need for individualized, stage-dependent therapeutic approaches. Juggling is a complex motor activity that integrates cognitive, visuomotor, and balance processes, requiring a high level of concentration, precision, and motor adaptation. In recent years, there has been growing interest in this form of activity as a potential tool for supporting neuroplasticity, cognitive functions, and neurological rehabilitation. The aim of this review was to summarize current scientific evidence on the effects of juggling training on cognitive functions, visuomotor coordination, and balance, as well as to discuss the potential benefits of combining it with controlled hypoxia in patients with Parkinson’s disease (PD). This narrative review additionally considers how disease heterogeneity and stage of progression may influence the effectiveness of such multimodal interventions. This paper reviews the literature concerning the neurophysiological basis of learning to juggle and the mechanisms of brain plasticity, including increases in gray matter volume, improvements in white matter integrity, and reorganization of neuronal networks in motor and associative regions. Attention is drawn to the synergistic potential of combining juggling training with exposure to moderate, controlled hypoxia, which may induce an adaptive response involving the transcription factor HIF-1α, enhance the expression of brain-derived neurotrophic factor (BDNF), and promote angiogenesis and mitochondrial biogenesis. Although juggling and hypoxia are not directly related to training stimuli, both interventions activate overlapping and complementary neuroplastic pathways, providing a conceptual rationale for their parallel consideration and potential integration within future rehabilitation protocols. Juggling delivers task-specific motor–cognitive learning, whereas hypoxia may amplify molecular plasticity signaling, potentially enhancing responsiveness to motor interventions, particularly in patients at early stages of PD when compensatory mechanisms and neuroplastic capacity are relatively preserved. Findings from existing studies suggest that juggling under controlled hypoxic conditions may represent an innovative, safe, and multimodal form of training that supports both cognitive and motor components. Such effects may be particularly relevant in patients at early stages of PD, when compensatory mechanisms and neuroplastic potential are relatively preserved. Such an intervention may contribute to improvements in balance, attention, executive functions, and cognitive flexibility, which is particularly relevant in the context of rehabilitation for patients with neurodegenerative diseases. Importantly, to date, no randomized clinical trials have directly examined juggling performed under controlled hypoxic conditions in PD. Therefore, the present concept should be regarded as translational and exploratory, integrating evidence from juggling-induced neuroplasticity and hypoxia-related physiological adaptations. In this context, the proposed approach represents a proof-of-concept framework for future multimodal interventions rather than an established therapeutic strategy. Available evidence suggests that combining complex sensorimotor skill training with physiological modulation of the internal environment may constitute a novel direction in PD rehabilitation, extending beyond conventional exercise-based models. Despite promising reports, further well-designed clinical studies are needed to determine the optimal training parameters (frequency, intensity, duration, and degree of hypoxia), to evaluate the long-term sustainability of therapeutic effects, and to account for the heterogeneity of PD and related Parkinsonian disorders. Full article

Addressing the challenge of balancing high-precision positioning with strict safety constraints for underactuated bridge cranes subject to model parameter mismatch and stochastic wind disturbances, an adaptive hybrid control framework is presented integrating a Safety-Aware Dynamic Gain Sliding Mode Controller (DG-SMC) with a TD3-based residual deep reinforcement learning network. By designing a gain scheduling mechanism based on swing angle amplitude, the proposed method physically limits trolley acceleration to strictly constrain the payload swing angle within a safe range ($\pm 7°$). Simultaneously, a TD3 agent is introduced as a residual compensator to adaptively learn system dynamics through environmental interaction, generating real-time compensatory control forces to counteract unmodeled dynamics arising from system parameter deviations and continuous wind resistance. Numerical simulations demonstrate that, under conditions involving payload mass deviations of up to 25% and stochastic wind disturbances, the proposed control method effectively reduces steady-state positioning errors, suppresses payload swing during operation, and significantly enhances the system’s energy dissipation efficiency and global robustness in uncertain environments. Full article

Under the context of global warming, accelerated glacier melting poses a severe threat to regional water security, necessitating systematic quantification of the spatiotemporal evolution of glacier mass balance (GMB) and its impacts on runoff. This study employed the Spatial Processes in Hydrology (SPHY) distributed hydrological model, integrated with remote sensing data, meteorological observations, and Coupled Model Intercomparison Project Phase 6 (CMIP6) climate scenarios, to reconstruct the spatiotemporal evolution of glacier mass balance in the Manas River Basin on the northern slope of Tianshan Mountains from 2000 to 2014, quantify the coupling relationships between glacier mass balance and climate factors as well as glacier meltwater runoff, and project future trends from 2015 to 2045. Results showed that glaciers in the basin experienced persistent negative mass balance during the study period, with a 15-year mean glacier mass balance of −0.87 $\mathrm{m} \mathrm{w}.\mathrm{e}.·{\mathrm{a}}^{-1}$, cumulative loss of 12.16 $\mathrm{m} \mathrm{w}.\mathrm{e}.$, and glacier area shrinkage of 11.9%. Glacier mass balance exhibited significant spatiotemporal heterogeneity, with the most severe mass loss occurring in steep south-facing slopes, and glacier thickness change displayed a “single-peak” altitudinal dependence with the ablation peak elevation stabilized at approximately 4400 m. Glacier mass balance showed a significant negative correlation with melt-season positive accumulated temperature (r = −0.9, p < 0.01), with a temperature sensitivity coefficient of 55.17 %·°C⁻¹. The contribution rate of glacier meltwater runoff increased from 19.93% to 29.50%, showing a significant negative correlation with glacier mass balance (r = −0.73, p < 0.01), revealing the phenomenon of “compensatory runoff increase”. Under three future scenarios, glacier mass balance loss exhibited an intensifying trend, with the most severe loss in high-altitude areas, and glacier meltwater runoff continued to increase but demonstrated unsustainability. This study provides a scientific basis for predicting “peak water” timing and adaptive water resource management in high mountain glacierized basins under climate change. Full article

Viral infections have been implicated in psychiatric outcomes through immune-mediated pathways. This 12-month prospective cohort study, designed as a pilot and hypothesis-generating investigation, compared psychiatric symptoms and inflammatory cytokine profiles in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), hepatitis C virus (HCV), and tick-borne encephalitis virus (TBEV), and explored their potential predictive value. Thirty-seven patients hospitalized with viral infections and 32 healthy controls were evaluated, acknowledging the limited sample size. Psychiatric interviews and the Hospital Anxiety and Depression Scale (HADS) were used for assessment. The study was divided into two stages. In Stage 1, during the acute infection, a psychiatric assessment was conducted, and cytokine levels were measured in the patients’ blood. In Stage 2, one year later, the psychiatric assessment was repeated. No significant differences were found in psychiatric diagnosis rates or symptom severity between infection groups, regardless of viral type or neuroinvasive capacity. However, these findings should be interpreted as preliminary given the limited sample size. Some cytokines, eg., interleukin-1β (IL-1β), tumor necrosis factor-alpha (TNF-α), interleukin-10 (IL-10), and soluble interleukin-2 receptor subunit alpha (sIL-2Rα), showed associations with individual symptoms, but these were inconsistent and did not demonstrate robust predictive value. Cluster analysis identified two distinct inflammatory profiles—one characterized by higher cytokine levels (predominantly in Coronavirus disease 2019 (COVID-19) and TBEV cases) and the other by lower cytokine levels (mostly in HCV and controls). However, different cytokine profiles did not correspond to clinical outcomes. The results suggest that psychiatric sequelae after viral infections are not directly driven by specific cytokines or infection type but rather emerge from a complex interaction of immune, psychological, and environmental factors. Single cytokine measurement is insufficient and cannot be used as a tool for assessing the risk of developing psychiatric disorders. Given the exploratory nature of the study, all results require confirmation in larger, adequately powered cohorts. Future studies should focus on composite biomarkers and systems-based models such as neuroimmune-metabolic-oxidative pathways (NIMETOX), or Immune-Inflammatory Response System (IRS)/Compensatory Immune Response System (CIRS)/Oxidative & Nitrosative Stress (O&NS) for improved predictive accuracy. Full article