Oxidative stress is considered pivotal in the pathophysiology of sepsis. Oxidants modulate heat shock proteins (Hsp), interleukins (IL), and cell death pathways, including apoptosis. This multicenter prospective observational study was designed to ascertain whether an oxidant/antioxidant imbalance is an independent sepsis discriminator and mortality predictor in intensive care unit (ICU) patients with sepsis (n = 145), compared to non-infectious critically ill patients (n = 112) and healthy individuals (n = 89). Serum total oxidative status (TOS) and total antioxidant capacity (TAC) were measured by photometric testing. IL-6, -8, -10, -27, Hsp72/90 (ELISA), and selected antioxidant biomolecules (Ζn, glutathione) were correlated with apoptotic mediators (caspase-3, capsase-9) and the central anti-apoptotic survivin protein (ELISA, real-time PCR). A wide scattering of TOS, TAC, and TOS/TAC in all three groups was demonstrated. Septic patients had an elevated TOS/TAC, compared to non-infectious critically ill patients and healthy individuals (p = 0.001). TOS/TAC was associated with severity scores, procalcitonin, IL-6, -10, -27, IFN-γ, Hsp72, Hsp90, survivin protein, and survivin isoforms -2B, -ΔΕx3, -WT (p < 0.001). In a propensity probability (age-sex-adjusted) logistic regression model, only sepsis was independently associated with TOS/TAC (Exp(B) 25.4, p < 0.001). The AUC_TOS/TAC (0.96 (95% CI = 0.93–0.99)) was higher than AUC_TAC (z = 20, p < 0.001) or AUC_TOS (z = 3.1, p = 0.002) in distinguishing sepsis. TOS/TAC, TOS, survivin isoforms -WT and -2B, Hsp90, IL-6, survivin protein, and repressed TAC were strong predictors of mortality (p < 0.01). Oxidant/antioxidant status is impaired in septic compared to critically ill patients with trauma or surgery and is related to anti-apoptotic, inflammatory, and innate immunity alterations. The unpredicted TOS/TAC imbalance might be related to undefined phenotypes in patients and healthy individuals.

Objective. We assessed the lipopolysaccharide (LPS) or heat shock (HS) induction of heat shock protein-72 (HSP72) in peripheral blood mononuclear cells (PBMCs) of patients with severe sepsis (SS) or trauma-related systemic inflammatory response syndrome (SIRS), compared to healthy individuals (H); we also investigated any pre- or posttreatment modulating glutamine (Gln) effect.Methods. SS (11), SIRS (10), and H (19) PBMCs were incubated with 1 μg/mL LPS or 43°HS. Gln 10 mM was either added 1 h before or 1 h after induction or was not added at all. We measured monocyte (m), lymphocyte (l), mRNA HSP72, HSP72 polymorphisms, interleukins (ILs), monocyte chemoattractant protein-1 (MCP-1), and cortisol levels.Results. Baseline lHSP72 was higher in SSp<0.03, and mHSP72 in SIRSp<0.02, compared to H. Only HS induced l/mHSP72/mRNA HSP72; LPS induced IL-6, IL-8, IL-10, and MCP-1. Induced mRNA was related to l/mHSP72, and was related negatively to cytokines. Intracellular l/mHSP72/HSP72 mRNA was related to serum ILs, not being influenced by cortisol, illness severity, and HSP72 polymorphisms. Gln did not induce mRNA in any group but modified l/mHSP72 after LPS/HS induction unpredictably.Conclusions. HSP72 mRNA and l/mHSP72 are higher among critically ill patients, further induced by HS, not by LPS. HSP72 proteins and HSP72 mRNA are related to serum ILs and are negatively related to supernatant cytokines, not being influenced by HSP72 polymorphisms, cortisol, or illness severity. Gln may depress l/mHSP72 after LPS exposure and enhance them after HS induction, but it may not affect early induced HSP72 mRNA.

Background: Nutrition significantly impacts the outcomes of critically ill children in intensive care units (ICUs). Due to the evolving metabolic, neuroendocrine, and immunological disorders associated with severe illness or trauma, there are dynamically changing phases of energy needs requiring tailored macronutrient intake. Objectives: This study aims to assess the changing dietary needs from the acute phase through recovery, provide recommendations for implementing evidence-based strategies to ensure adequate energy and nutrient provision in pediatric ICUs, and optimize patient outcomes. Methods: A comprehensive search of the MEDLINE-PubMed database was conducted, focusing on randomized controlled trials, meta-analyses, and systematic reviews related to the nutrition of critically ill children. The study highlights recent guidelines using the GRADE approach, supplemented by relevant adult studies, current clinical practices, challenges, gaps in knowledge, and future directions for research aimed at improving nutritional interventions. Results: Early personalized, incremental enteral feeding helps mitigate the negative energy balance during the acute phase, aids organ function restoration in the stabilization phase, and supports growth during the recovery phase and beyond. Conversely, early full nutritional support, high protein doses, or isolated micronutrient administration have not demonstrated benefits due to anabolic resistance in these patients. Moreover, early parenteral nutrition during the acute phase may suppress autophagy and lead to worse outcomes. Accurate assessment of nutritional status and monitoring of daily energy and protein needs are crucial. Conclusions: Strong evidence supports the establishment of a dedicated nutritional team and the implementation of individualized nutritional protocols in the ICU to reduce morbidity and mortality in critically ill children.

Per- and polyfluoroalkyl substances (PFASs) are synthetic chemicals extensively used in various industries due to their unique physicochemical properties. Their persistence in the environment and potential for bioaccumulation have raised significant health concerns. This review aims to elucidate the sources, exposure pathways, toxicological effects, and regulatory measures related to PFASs, with a particular focus on pediatric populations and medical applications. A comprehensive narrative review was conducted using PubMed, Scopus, and Web of Science to identify peer-reviewed literature published between 2000 and 2025. The search focused on PFAS use in healthcare, environmental contamination, exposure pathways, health effects, and regulatory actions. Relevant studies, reports, and policy documents were screened and thematically synthesized by the authors to evaluate clinical and environmental risks, particularly in pediatric populations. PFAS exposure is linked to various adverse health effects, including immunotoxicity, endocrine disruption, metabolic disorders, and carcinogenicity. Children are particularly vulnerable due to developmental susceptibilities and exposure through medical devices and environmental sources. Regulatory measures are evolving, but gaps remain, especially concerning medical device applications. There is an urgent need for comprehensive strategies to monitor and mitigate PFAS exposure, particularly in vulnerable populations. Enhanced regulatory frameworks, safer alternatives in medical devices, and public health interventions are essential to address the challenges posed by PFASs.

Background: Artificial intelligence (AI) is increasingly used in intensive care units (ICUs) to enable personalized care, real-time analytics, and decision support. Nutritional therapy—a major determinant of ICU outcomes—often remains delayed or non-individualized. Objective: This study aimed to review current and emerging AI applications in ICU nutrition, highlighting clinical potential, implementation barriers, and ethical considerations. Methods: A narrative review of English-language literature (January 2018–November 2025) searched in PubMed/MEDLINE, Scopus, and Web of Science, complemented by a pragmatic Google Scholar sweep and backward/forward citation tracking, was conducted. We focused on machine learning (ML), deep learning (DL), natural language processing (NLP), and reinforcement learning (RL) applications for energy/protein estimation, feeding tolerance prediction, complication prevention, and adaptive decision support in critical-care nutrition. Results: AI models can estimate energy/protein needs, optimize EN/PN initiation and composition, predict gastrointestinal (GI) intolerance and metabolic complications, and adapt therapy in real time. Reinforcement learning (RL) and multi-omics integration enable precision nutrition by leveraging longitudinal physiology and biomarker trajectories. Key barriers are data quality/standardization, interoperability, model interpretability, staff training, and governance (privacy, fairness, accountability). Conclusions: With high-quality data, robust oversight, and clinician education, AI can complement human expertise to deliver safer, more targeted ICU nutrition. Implementation should prioritize transparency, equity, and workflow integration.

Optimal energy provision, guided by measured resting energy expenditure (REE) and determined by indirect calorimetry (IC), is fundamental in Intensive Care Units (ICU). Because IC availability is limited, methods to predict REE based on carbon dioxide production (VCO₂) measurements (REE_VCO2) alone have been proposed as a surrogate for REE measured by IC (REE_IC). The study aimed at externally and internally validating the accuracy of the REE_VCO2 as an alternative to REE_IC in mechanically ventilated children. A ventilator’s integrated gas exchange module (E-COVX) was used to prospectively measure REE_IC and predict REE_VCO2 on 107 mechanically ventilated children during the first 24 h of admission. The accuracy of the REE_VCO2 compared to REE_IC was assessed through the calculation of bias and precision, paired median differences, linear regression, and ROC analysis. Accuracy within ±10% of the REE_IC was deemed acceptable for the REE_VCO2 equation. The calculated REE_VCO2 based on respiratory quotient (RQ) 0.89 resulted in a mean bias of −72.7 kcal/day (95% limits of agreement −321.7 to 176.3 kcal/day) and a high coefficient of variation (174.7%), while 51.4% of the calculations fell outside the ±10% accuracy rate. REE_VCO2 derived from RQ 0.80 or 0.85 did not improve accuracy. Only measured RQ (Beta 0.73, p < 0.001) and no-recorded neuromuscular blocking agents (Beta −0.13, p = 0.044) were independently associated with the REE_VCO2−REE_IC difference. Among the recorded anthropometric, metabolic, nutrition, or clinical variables, only measured RQ was a strong predictor of REE_VCO2 inaccuracy (p < 0.001). Cutoffs of RQ = 0.80 predicted 89% of underestimated REE_IC (sensitivity 0.99; specificity 0.89) and RQ = 0.82 predicted 56% of overestimated REE_IC (sensitivity of 0.99; specificity 0.56). REE_VCO2 cannot be recommended as an alternative to REE_IC in mechanically ventilated children, regardless of the metabolic, anthropometric, or clinical status at the time of the evaluation.