Search Results (210)

Background/Objectives: Beta-hydroxybutyrate (BHB) exists as two enantiomers with potentially distinct biological activities. While D-BHB is the physiological form produced during ketogenesis, L-BHB is present in equal amounts in racemic supplements, yet its biological effects remain poorly understood. Additionally, the ketone precursor 1,3-butanediol (BD) is used in some formulations despite limited safety data. Methods: We investigated acute (single gavage, 2-h time course) and short-term (daily gavage for 8 days) hepatic effects of D-BHB, L-BHB, and 1,3-butanediol compared to a vehicle control in male C57BL/6 mice. Acute studies assessed hepatic ATP dynamics and lipid peroxidation (MDA) at multiple timepoints. Eight-day protocols evaluated mitochondrial function (oxygen consumption, Complex II activity, SDH activity), lipid accumulation (triglycerides), and inflammatory markers (IL-1β, TNF-α, CRP). Results: Acute ATP responses differed markedly among treatments. Compared to the baseline and the control, L- and D-BHB elicited significant increases in ATP, while BD caused sustained ATP depletion. Over this same time, oxidative stress markers remained stable in the control and both BHB groups but increased dramatically with BD. After 8 days, the mitochondrial effects of BD were more apparent with a significant reduction in complex II-supported respiration and activity. Both forms of BHB maintained control levels of inflammation and BD showed significant effects on all inflammatory markers. Hepatic triglycerides increased only with BD treatment. Conclusions: This study reveals striking hepatic effects of various ketone supplements. In contrast to the positive or inert effects of BHB enantiomers, 1,3-butanediol induces significant hepatic stress. These findings have implications for ketone supplement formulation and highlight the therapeutic potential of D- and L-BHB. Full article

The rapid development of medical technologies requires architects to implement a future-proofing approach while designing medical facilities, despite the inherent uncertainty of long-term change. This challenge is particularly visible within hospital emergency departments (HEDs), which play a critical role as first-contact units and life-saving infrastructures. Due to their specific function, HEDs are a challenging environment for implementing new solutions, as they rely on proven frameworks designed to ensure continuity of care and operational efficiency. This raises the key question: how can modern technologies and architectural strategies streamline workflows in HEDs without overwhelming medical staff? Considering current challenges, an equally important factor in the development of emergency departments is their preparedness for crisis situations, such as pandemics, war threats and natural disasters. How can architectural design enable the implementation of given design strategies, aiming to ensure opportunities for development while simultaneously preparing for all-hazard scenarios? The authors gathered existing trends and solutions aimed at preparing hospital emergency departments for future challenges: positive/neutral, such as technological development, but also negative, such as currently ongoing war threats or risk of the next pandemic. Despite the apparent thematic extremity, certain systematic architectural solutions using a transdisciplinary approach may be the answer to these occurrences. The mentioned architectural solutions and factors were synthesized and subjected to design-oriented review based on existing case studies of a few Polish hospitals, which are simultaneously studied as case studies for broader doctoral research in the field of effectiveness assessment. The selected Polish hospital emergency departments are used as an illustrative, analytical reference to support the interpretation and synthesis of the reviewed literature. The contextual analysis enables the identification of transferable, design-oriented strategies relevant to broader emergence medicine architecture and applicable within European units. Examples from Polish units in particular are used as reference and background for discussion, rather than as empirical case studies. The study provides an overview of contemporary and future-oriented solutions in hospital architecture, focusing on the impact and feasibility within the hospital emergency departments. The synthesis highlights the importance of designing flexible spaces prepared for future technological advances, such as oversized service shafts, increased floor heights, and modular layouts. Additionally, the study focuses on the spatial connotations of emerging technologies like medical robotics, their maintenance areas and possible challenges. All of this is interrelated to social, demographic, and economic trends. These include the development of hospital networks, the evolving patient profile, inter-hospital information flow, and the growing role of highly specialized medical units. In terms of rapid challenges like wars or armed threats, factors revealed within the review indicate levels of HED readiness to face the conflict, mainly in terms of surge capacity but also structural durability and reserve resources. The post-pandemic context, in turn, assumes rapid expansion of the hospital into temporary and flexible structures and reversible zoning allowing for patient segregation and separation. Together, these insights outline pathways for creating resilient, adaptable, and efficient emergency care environments resilient to unforeseen challenges. Considering future scenarios of emergency departments, two main scenarios were identified: “the hospital of the future”, continuing overall development and adapting to rapid technological innovations, and “the crisis-resilient hospital”, resistant to various crisis scenarios, such as pandemics or war threats. The optimal development of the unit assumes both openness to technological changes and preparation of key zones for all-hazard scenarios. This review aims to synthesize architectural implications of technological and socio-demographic changes, not to provide a full empirical study. Adopting an exploratory framework, the review refers to technological innovations and crisis preparedness as external drivers shaping the spatial organization of hospital emergency departments and their adaptability to future challenges. Because of various inhibitors (economic, political, hierarchical), not all hospitals can introduce the described improvements, but the synthesis may serve as a knowledge source for future investments. The review was also conducted to support design decisions under conditions of uncertainty. The choice to address all the external factors collectively was induced to provide transferability of solutions and coherence of possible scenarios, which may happen simultaneously. Full article

Background/Objectives: This study aimed to examine the relationship between climate change worry and symptoms of stress, anxiety, and depression in pregnant women. Methods: The cross-sectional study was conducted with 367 pregnant women. Data were collected using the “Personal Information Form,” the “Climate Change Worry Scale (CCWS),” and the “Depression Anxiety Stress Scale (DASS-21).” Spearman rho and Kruskal–Wallis-H Test were used to analyze the data. Results: The mean total score for the CCWS was 20.22 ± 8.20. Significant differences in the scores for the CCWS were found for the levels of education, economic income, stated concern regarding climate change, and perceived effects of climate change for their location (p < 0.05). Significant positive correlations also became apparent between the overall scores and subscale scores for the CCWS and the DASS-21 (p < 0.001). Conclusions: In conclusion, the findings of this study indicate that climate change concern is significantly associated with depression, anxiety, and stress among pregnant women. Full article

The determination of groundwater background levels is a prerequisite for assessing and analyzing groundwater characteristics. Shanghai is among the most economically developed regions in China and is located in the estuary of the Yangtze River, where frequent hydrogeochemical processes occur. Moreover, the frequency of anthropogenic activities in Shanghai is very high. Consequently, assessing groundwater background levels in Shanghai is inherently limited if only statistical methods are adopted or anthropogenic impacts are ignored. In this study, hydrochemical and statistical methods were coupled to identify groundwater anomalies and background levels. The results revealed distinct differences in hydrochemical characteristics between the two selected independent units (Chongming and Qingpu units), highlighting the necessity of reasonably delineating hydrogeological units for obtaining background values. Furthermore, for these two independent units, different optimal methods for identifying and eliminating anthropogenic groundwater anomalies were determined. The use of coupled methods was demonstrated to be substantially superior to the use of purely statistical approaches. Hydro-HCA was identified as the optimal identification method for the Chongming unit, whereas Hydro-Grubbs was determined as the most suitable method for the Qingpu unit. This could be attributed mainly to the coupled methods accounting for not only the dispersion of the data itself but also the intrinsic relationships and evolutionary processes of hydrochemical components. These findings could provide reliable information for subsequent groundwater background surveys and studies on groundwater pollution characteristics in Shanghai and to guide future endeavors aimed at protecting groundwater resources. Full article

Background: Pheochromocytomas (PCCs) and paragangliomas (PGLs), collectively known as PPGLs, are rare neuroendocrine tumors that produce catecholamines. The majority of PPGL cases are caused by germline and/or somatic mutations in over 20 different genes. A study of post-surgical PCC patients revealed a high risk of new tumor recurrence in both hereditary and apparently sporadic cases, suggesting that some germline mutations remain undetected. Since transcript levels can indicate gene dysfunction, our study focuses on the transcriptional profiling of PCC-associated genes in post-surgical patients. Methods: RT-PCR was performed on blood samples from patients and a control group. The t-SNE algorithm was applied to the transcriptional data. Sanger sequencing was used to identify mutations in the coding sequences of the VHL, SDHB, RET, and NF1 genes. Results: We obtained transcriptional profiles for 11 genes involved in the Krebs cycle and for 21 genes involved in the hypoxia, PI3K/AKT/mTOR, and RAS/RAF/ERK signaling pathways. We identified a minimal set of 16 genes with stable transcription levels that can be used to differentiate PCC patients from controls. Germline mutations in the VHL, SDHB, RET and NF1 genes, which correlated with an altered transcriptional profile, were detected in three patients. Conclusions: Our pilot data suggest that transcript levels of the genes involved in Krebs cycle, hypoxia, PI3K/AKT/mTOR, and RAS/RAF/ERK signaling pathways indicate their potential suitability as a candidate diagnostic marker. The results from this pilot study form the basis for a larger project to investigate gene transcription in an expanded cohort of patients who have undergone surgery for PCC. Full article

Background: Parkinson’s disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Speech analysis has emerged as a non-invasive tool for automatic PD detection; however, the scarcity and homogeneity of available datasets often limit the generalization capability of machine learning models, motivating the use of data augmentation strategies to improve robustness. Methods: This study presents a data augmentation-based methodology for speech-based classification between PD patients and healthy control subjects. A deep learning model trained from scratch on Mel spectrograms is evaluated using augmentation techniques applied at both the waveform and time–frequency levels. Multiple training and model selection strategies are analyzed and model performance is assessed through internal validation as well as using an independent dataset Results: Experimental results show that carefully selected data augmentation techniques improve classification performance with respect to the non-augmented counterpart, achieving gains of up to 3% in accuracy. However, when evaluated on an independent dataset, these improvements do not consistently translate into better generalization. Conclusions: These findings demonstrate that, while data augmentation can effectively enhance model performance within a single dataset, this apparent robustness is not sufficient to guarantee generalization on independent speech corpora for PD detection. Full article

Public health impacts of non-optimal temperatures and air pollution have received insufficient attention in Southeast Europe, one of the most air-polluted regions in Europe, simultaneously pressured by climate change. This study employed a multimodal approach to characterize the microclimate and air quality and conduct a health impact assessment in the three biggest cities in Bulgaria. Simulation of atmospheric thermo-hydrodynamics and assessment of urban microclimate relied on the Weather Research and Forecasting model. Concentrations of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) were calculated with a land-use regression model. Ischemic heart disease (IHD) hospital admissions were linked to daily measurements at background air quality stations. The results showed declining trends in PM_2.5 but persistent levels of NO₂, especially in Sofia and Plovdiv. Distributed lag nonlinear models revealed that, in Sofia and Plovdiv, PM_2.5 was associated with IHD hospitalizations, with a fifth of cases in Sofia attributable to PM_2.5. For NO₂, an increased risk was observed only in Sofia. In Sofia, the risk of IHD was increased at cold temperatures, while both high and low temperatures were associated with IHD in Plovdiv and Varna. Short-term effects were observed in response to heat, while the effects of cold weather took up to several weeks to become apparent. These findings highlight the complexity of exposure–health interactions and emphasize the need for integrated policies addressing traffic emissions, urban design, and disease burden. Full article

Background and Objectives: Celiac disease (CD) is a major global public health problem that can occur at any age. Pediatric CD can be typical, atypical, or even asymptomatic. Early diagnosis and early initiation of treatment are essential for improving patients’ quality of life and preventing serious complications later in life. However, it is impossible to identify asymptomatic children and adolescents without screening. In this systematic review, we attempted to identify different mass screening programs that have been reported for CD in apparently healthy children and adolescents across the world, to highlight the advantages and disadvantages of such strategies, and to collect and synthesize data from these studies reporting the prevalence of CD. In addition, where data were available, we also attempted to evaluate the diagnostic accuracy of the tests used, their cost-effectiveness, the reported clinical benefits, and follow-up data from individuals identified through screening. Materials and Methods: Electronic databases, including PubMed and Scopus, were systematically searched. Initially, a total of 316 studies were retrieved. Finally, 55 studies met all inclusion criteria and were included in this review. The included studies were published between 1996 and 2023. Results: The reported age of participants ranged from 6 months to 23 years. Confirmation of CD by biopsy was reported in all but six studies. According to the studies that provided data, the (tTG IgA) seroprevalence of CD in apparently healthy children and adolescents, detected through different mass screening methods around the world, ranged from 0.20% (Turkey) to 3.11% (Italy). In addition, the prevalence of biopsy-confirmed CD ranged from 0.036% (Vietnam) to 3% (Sweden and Spain). Studies from 17 countries reported mass screening strategies based on finger-prick rapid tests. All rapid tests detected CD antibodies, except two, which detected HLA DQ2/DQ8 haplotypes. Rapid tests appeared to be no less sensitive and specific than other screening tests for CD and were probably less expensive, but further studies are needed for more reliable conclusions. Of the 55 studies in the review, only 10 reported follow-up data. After 3 months of a gluten-free diet, the general condition of the patients improved; after 6 months, tTG IgA and EMA IgA levels decreased and hemoglobin values increased; while after 1 year, tTG IgG levels also decreased, symptoms subsided, the children’s weight and height increased, school performance improved, episodes of upper respiratory tract infections decreased, and thyreoperoxidase antibodies that were positive at screening became negative. Conclusions: Mass screening for CD in asymptomatic children and adolescents is a challenge. Future research should provide more answers regarding the most appropriate target age, the frequency of screening, the optimal screening method, the cost-effectiveness, the clinical utility, and the long-term impact of mass screening on patients’ quality of life. Full article

Unmanned aerial vehicles (UAVs) increasingly share low-altitude airspace with birds, making early distinguishing between drones and biological targets critical for safety and security. This work addresses long-range scenarios where objects occupy only a few pixels and appearance-based recognition becomes unreliable. We develop a model-driven simulation pipeline that generates synthetic data with a controlled camera model, atmospheric background and realistic motion of three aerial target types: multicopter, fixed-wing UAV and bird. From these sequences, each track is encoded as a time series of image-plane coordinates and apparent size, and a bidirectional long short-term memory (LSTM) network is trained to classify trajectories as drone-like or bird-like. The model learns characteristic differences in smoothness, turning behavior and velocity fluctuations, and to achieve reliable separation between drone and bird motion patterns on synthetic test data. Motion-trajectory cues alone can support early distinguishing of drones from birds when visual details are scarce, providing a complementary signal to conventional image-based detection. The proposed synthetic data and sequence classification pipeline forms a reproducible testbed that can be extended with real trajectories from radar or video tracking systems and used to prototype and benchmark trajectory-based recognizers for integrated surveillance solutions. The proposed method is designed to generalize naturally to real surveillance systems, as it relies on trajectory-level motion patterns rather than appearance-based features that are sensitive to sensor quality, illumination, or weather conditions. Full article

Background: Early recognition of renal allograft dysfunction requires biochemical markers capable of detecting molecular injury before functional decline becomes apparent. Serum creatinine, a late and nonspecific indicator of renal function, has limited value for early diagnosis. Protein biomarkers implicated in tubular injury, inflammation, and immune activation—including neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), β2-microglobulin, interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α)—have emerged as promising alternatives. This study evaluated early post-transplant serum profiles of these biomarkers and their prognostic relevance for long-term graft outcomes. Methods: Nineteen adult recipients undergoing primary kidney transplantation were prospectively enrolled. Serum creatinine and protein biomarkers were measured 24 h post-transplant using validated immunochemical assays. Biomarker concentrations were compared with values from healthy controls, and correlations with renal function at 12 months were assessed. Receiver operating characteristic (ROC) analysis was used to evaluate predictive performance. Results: Significant biochemical alterations were observed at 24 h post-transplant. KIM-1 levels were markedly elevated compared with controls (74.50 ± 98.45 vs. 10.54 ± 17.19 ng/mL; p = 0.01), consistent with early tubular injury. IL-1β and NGAL showed upward trends without reaching statistical significance. β2-microglobulin and TNF-α levels did not differ substantially from control values. Serum KIM-1 correlated with serum creatinine both at 24 h (r = 0.35) and at 12 months (r = 0.40). ROC analysis identified a KIM-1 threshold of 24.5 ng/mL (AUC = 0.68) as a potential indicator of future graft dysfunction, outperforming serum creatinine (AUC = 0.64). Six patients experienced graft dysfunction at 12 months post-transplant, five of whom had serum creatinine values > 5 mg/dL at 24 h. Based on early creatinine levels, patients were stratified into low-risk (creatinine < 5 mg/dL; n = 10) and high-risk groups (creatinine > 5 mg/dL; n = 9). Mean KIM-1 concentrations were significantly higher in the high-risk group (110.68 ± 115.29 vs. 26.67 ± 18.05 ng/mL; p = 0.05), consistent with more severe early tubular injury. Conclusions: Among the evaluated biomarkers, KIM-1 demonstrated the strongest potential as an early biochemical indicator of renal allograft dysfunction. Its rapid post-transplant elevation underscores its sensitivity to early tubular injury. Further prospective validation in larger, multicenter cohorts is warranted. Full article

Background: Dementia is an increasing public health challenge in Mexico, yet recent national data on mortality patterns remain limited. This study examines temporal trends in dementia-related mortality and its sociodemographic and ecological characteristics among adults aged ≥65 years from 2017 to 2023. Methods: National mortality records from the General Directorate of Health Information were analyzed. Annual dementia-related mortality rates were calculated based on mid-year population estimates from CONAPO. Trends were assessed with regression analysis, including population offsets, and individual- and state-level characteristics were evaluated. Results: Between 2017 and 2023, dementia-related deaths increased from 761 to 1425, corresponding to an observed rise from 7.9 to 14.6 deaths per 100,000 inhabitants aged ≥65 years. Period trend indicated an average annual expected increase of 18.6% in dementia related mortality. A transient decline occurred in 2020–2021, coinciding with the COVID-19 pandemic. At the individual level, higher education was associated with greater odds of dementia certification, whereas Indigenous ethnicity appeared protective, which may reflect patterns consistent with diagnostic and reporting disparities. Higher state-level life expectancy correlated with higher dementia mortality, while greater population aging was inversely associated. Conclusions: Dementia-related mortality in Mexico shows a sustained upward trend with regional heterogeneity and apparent inequities in diagnosis and reporting. Strengthening mortality surveillance, improving certification quality, and integrating dementia indicators into national non-communicable disease registries are essential to guide equitable policy responses. Full article

Background: The vestibular schwannoma (VS) is the most common cerebellopontine angle tumor in adults, exhibiting a highly variable natural history, from stability to rapid growth. Accurate, the non-invasive prediction of tumor behavior is essential to guide personalized management and avoid overtreatment or delayed intervention. Objective: To systematically review and synthesize the evidence on MRI-based biomarkers for predicting VS growth and treatment responses. Methods: We conducted a PRISMA-compliant search of PubMed, EMBASE, and Cochrane databases for studies published between 1 January 2000 and 1 January 2025, addressing MRI predictors of VS growth. Cohort studies evaluating texture features, signal intensity ratios, perfusion parameters, and apparent diffusion coefficient (ADC) metrics were included. Study quality was assessed using the NOS (Newcastle–Ottawa Scale) score, GRADE (Grading of Recommendations, Assessment, Development and Evaluation), and ROBIS (Risk of Bias in Systematic reviews) tool. Data on diagnostic performance, including the area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, and p value, were extracted and descriptively analyzed. Results: Ten cohort studies (five retrospective, five prospective, total n = 525 patients) met the inclusion criteria. Texture analysis metrics, such as kurtosis and gray-level co-occurrence matrix (GLCM) features, yielded AUCs of 0.65–0.99 for predicting volumetric or linear growth thresholds. Signal intensity ratios on gadolinium-enhanced T1-weighted images for tumor/temporalis muscle achieved a 100% sensitivity and 93.75% specificity. Perfusion MRI parameters (K^trans, v_e, ASL, and DSC derived blood-flow metrics) differentiated growing from stable tumors with AUCs up to 0.85. ADC changes post-gamma knife surgery predicted a favorable response, though the baseline ADC had limited value for natural growth prediction. The heterogeneity in growth definitions, MRI protocols, and retrospective designs remains a key limitation. Conclusions: MRI-based biomarkers may provide exploratory signals associated with VS growth and treatment responses. However, substantial heterogeneity in growth definitions and MRI protocols, small single-center cohorts, and the absence of external validation currently limit clinical implementation. Full article

Background and Objectives: This study set out to better understand how posture, spinal level, gender and muscle activation influence the biomechanical properties of the lumbar erector spinae (LES) in healthy young adults. We aimed to measure how these factors influence LES tone, stiffness, and damping using a myotonometry device. Materials and Methods: Thirty healthy young adults (14 males, 16 females; aged 20–25 years) were evaluated at bilateral L3–L5 levels in prone, unsupported sitting, and standing positions, both under relaxed conditions and during submaximal isometric lumbar extension. The myotonometer measured LES tone (Hz), stiffness (N/m), and damping (logarithmic decrement). For each outcome, a mixed-model repeated-measures ANOVA was conducted with Gender as a between-subject factor and Posture, Level, and Action (relaxed vs. contracted) as within-subject factors (Bonferroni-adjusted α = 0.0167). Results: Posture produced the most significant and consistent effects on all properties—stiffness, tone, and damping (p < 0.0167)—with sitting and standing generally increasing stiffness and tone compared to prone, and sitting showing the highest values. Gender significantly impacted stiffness and tone (p < 0.0167), with males showing higher values. Spinal level also significantly influenced damping, stiffness, and tone (all p < 0.0167), with differences more apparent in females. Significant interactions included the influence of Posture × Gender on tone and damping (p < 0.0167), and of Posture × Action on stiffness and tone (p < 0.0167), alongside a strong three-way interaction for Level × Action × Posture across all outcomes, suggesting posture-related responses depend on activation state and spinal level. Conclusions: LES biomechanical properties are strongly affected by posture and further modulated by muscle activation, gender, and spinal level. These results support the creation of posture- and gender-specific reference values and underscore the value of dynamic, posture-specific myotonometer-based assessments for paraspinal muscle evaluation and clinical planning. Full article

Background/Objectives: NANOBODY^® molecules (VHHs) are attractive vectors for radiopharmaceuticals due to their small size and high target affinity, but rapid clearance and pronounced kidney retention limit their therapeutic applicability. Binding to serum albumin is a widely used strategy to prolong circulation, yet the respective contributions of albumin-binding affinity and molecular format remain insufficiently defined. This study aimed to systematically evaluate how affinity and valency modulate VHH pharmacokinetics. Methods: Four monovalent albumin-binding VHHs spanning nanomolar to micromolar affinities and two bivalent constructs were engineered, generated by fusing an albumin-binding VHH to an irrelevant non-binding VHH. All constructs incorporated a site-specific cysteine for DFO* conjugation, enabling uniform zirconium-89 labeling with high radiochemical purity. Pharmacokinetics were assessed in healthy mice using serial blood sampling and positron emission tomography. Blood and kidney exposure were quantified by non-compartmental analysis. Results: All albumin-binding constructs showed increased systemic exposure and reduced kidney uptake relative to a non-binding control. Nanomolar-affinity binders reached maximal exposure, and further affinity increases (K_D < ~100 nM) did not improve pharmacokinetics, suggesting a threshold. The micromolar binder showed intermediate exposure but still reduced renal retention compared with control. Valency effects were affinity-dependent. They were negligible at high affinity but pronounced at low affinity, where bivalency reduced systemic exposure and increased kidney uptake toward control levels. Conclusions: Albumin binding enables tuning of VHH pharmacokinetics in an affinity-dependent manner. Above an apparent affinity threshold, pharmacokinetics become format independent, whereas below this threshold, molecular format substantially influences systemic and renal disposition. Full article

Background: Metabolomic profiling can uncover metabolic differences among seemingly healthy children, providing opportunities for personalized medicine and early detection of risk biomarkers for future metabolic disorders. This study aimed to identify and internally validate metabotypes in apparently healthy schoolchildren using targeted serum metabolomics and to assess the external validity of this metabotype classification tool in two separate groups of children. Methods: Data from schoolchildren aged 6–11 years were analyzed in two phases. In the first phase, we developed and validated a classification tool using targeted serum metabolomics in healthy children. Metabotypes were identified through unsupervised clustering with a self-organizing map, followed by assessment of cluster stability and classification accuracy. In the second phase, we tested the tool’s consistency by applying it to two additional groups: the same children from phase 1 after a 10-month physical activity intervention, and a separate group diagnosed with metabolic syndrome. Results: Three metabotypes were identified in healthy children: METBA (balanced profile), METLI (high lipid and glucose levels), and METAA (high amino acid levels). Internal validation showed strong cluster stability (ARI = 0.79) and high classification accuracy (0.95). After the intervention, 55% of children were reclassified, indicating diverse metabolic responses to physical activity. Among children with metabolic syndrome, 83% were classified as METLI and 13% as METAA. Conclusions. This tool revealed serum metabolomic diversity, enabling classification of healthy children into three distinct metabotypes. It also detects changes in metabotype classification associated with a physical activity intervention and identifies the majority of children diagnosed with metabolic syndrome within two groups. This supports the potential use of metabotypes as biomarkers and eventually for personalized interventions. Full article