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Exercise is widely recognized for its beneficial effects on brain health, yet the extent to which exercise intensity modulates acute neurochemical and cognitive responses remains unclear. Particularly, the role of exercise intensity in shaping brain-derived neurotrophic factor (BDNF), lactate responses, and executive function requires further investigation. This study compared the acute effects of low-intensity continuous training (LICT), moderate-intensity continuous training (MICT), high-intensity interval training (HIIT), and a resting control condition (CTRL) on BDNF levels, blood lactate concentration, and cognitive responses in healthy young adult males. Twelve healthy young adult males completed LICT, MICT, HIIT, and the control condition using a randomized crossover design with a 7-day washout period. Serum BDNF, blood lactate concentration, and executive function assessed by the Stroop Test were measured before and immediately after each experimental condition. HIIT induced significantly greater post-exercise increases in BDNF and lactate compared with all other conditions, while MICT elicited moderate elevations relative to LICT and rest. Lactate responses increased progressively with exercise intensity. Improvements in executive function were observed exclusively following HIIT, reflected by significantly faster Stroop Test completion times. HIIT produced concurrent elevations in lactate and serum BDNF together with improved executive function performance. HIIT may represent an effective acute stimulus for cognitive benefits, with potential relevance for exercise approaches aimed at supporting brain health via neurotrophic signaling.Trial registration: The study was retrospectively registered on ClinicalTrials.gov (identifier: NCT07137611; https://clinicaltrials.gov/study/NCT07137611) on 22 August 2025.

Rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) is crucial for early optimization of antibiotic treatment, but current routine susceptibility testing typically requires 48-72 h. Attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy has emerged as a promising approach for bacterial identification and has recently been used to distinguish MRSA from methicillin-sensitive S. aureus (MSSA) after 60-120 min of β-lactam exposure. Here, we test whether ATR-FTIR can resolve MRSA versus MSSA within the first hour of antibiotic challenge. We exposed three MSSA (ATCC 6538, WKZ1, RN4220) and four MRSA (ATCC 43300, USA300-JE2, WKZ2, CA629) strains to sub-MIC ampicillin (0.5 μg/mL) and acquired spectra from 800 to 1800 cm-1 at 0, 20, 30, and 60 min. We compared classification pipelines based on the full spectrum, PCA-reduced features, and LASSO-selected bands, coupled with linear discriminant analysis, partial least-squares discriminant analysis, and support vector machines. Models based on LASSO-selected features achieved the strongest early performance, with strain-aware classification accuracies of 0.91 at 20 min and 0.92 at 30 min. Leave-one-strain-out cross-validation (LOSO-CV) further showed that focusing on mechanistically relevant difference spectra enabled robust across-strain discrimination, with balanced accuracies of 0.91 at 20 min and 0.90 at 30 min. The most informative early bands mapped primarily to peptidoglycan and carbohydrate precursor regions, while later discrimination increasingly involved lipid-associated bands. Transmission electron microscopy and atomic force microscopy at 20 min independently confirmed antibiotic-induced cell-wall thickening and structural disruption in susceptible strains but not in resistant strains. Together, these results establish a proof of concept that early cell-wall stress signatures captured by ATR-FTIR, combined with lightweight and interpretable machine-learning models, can deliver rapid and accurate phenotypic discrimination between MRSA and MSSA.

Cellulose fibrils are a renewable and biodegradable resource, but their extraction typically requires complete destruction of the original wooden matrix. We present a targeted strategy that enables selective liberation of cellulose microfibrils while preserving the integrity of the surrounding native wood structure. By combining partial delignification with localized surface modification using the ionic liquid 1-butyl-3-methylimidazolium acetate ([Bmim][OAc]), we enable selective liberation and separation of cellulose microfibrils without bulk dissolution or structural damage. This spatially confined treatment exploits the intrinsic anisotropy of the native cellulose architecture, allowing controlled fibril release while maintaining the original orientation and structural framework. These findings reveal how precise chemical interventions can expand the toolbox of cellulose chemistry and unlock new opportunities for advanced wood-based material engineering.

Large language models (LLMs) like GPT have been proposed to support complex clinical decision-making. This study evaluated the performance of GPT-based LLM in analyzing clinical, radiological, and laboratory data from patients with hepatocellular carcinoma (HCC) to assess liver function, assign BCLC stage, and recommend treatment. Data from 106 HCC patients (82% male, median age 65 [22-86]) were compiled into anonymized integrated reports. Four GPT-versions (4, o1, o3, 5.4) were prompted-using both short and long instructions-to calculate MELD, ALBI, and Child-Pugh scores, assign BCLC stage, and generate treatment recommendations based on current guidelines. Outputs were compared to expert consensus and tumor board decisions. Errors were categorized by type and source. Time and cost analyses compared GPT to clinical staff. All GPT versions achieved high accuracy (> 85%) in liver function assessment, with MELD calculation being the most error-prone. BCLC staging accuracy ranged from 46.2% (version 4) to 84.0% (o3), with misclassification of radiological reports as the main error source. Reasoning-optimized models (o1, o3) performed best for treatment recommendations, achieving an overall accuracy (correct suggestions and acceptable alternatives) of up to 90.6%. In 9-14% of cases, GPT suggestions were retrospectively more guideline-concordant than tumor board decisions. GPT processing was significantly faster and reduced costs by approximately 300- to 1300-fold compared to clinical staff. GPT-based LLMs show potential as decision-support tools for liver function assessment, BCLC staging, and treatment guidance in HCC. Particularly with reasoning-optimized models and detailed prompting, LLMs may serve as valuable adjuncts in multidisciplinary HCC workflows. However, a non-negligible error rate requires expert oversight and further model refinement.

Accelerating molecular probe discovery and lead optimization requires accurate and efficient binding affinity prediction. Here we present PBCNet2.0, a Cartesian tensor-based Siamese neural network for protein-ligand relative binding affinity prediction. Trained on 8.6 million protein-ligand complex pairs, PBCNet2.0 achieves zero-shot accuracy similar to computationally intensive physics-based simulations while remaining highly efficient. Retrospective prioritization experiments show that PBCNet2.0 improves optimization efficiency by 7.18-fold and reduces resource use by 41%. Mechanistic analyses indicate that the model captures intermolecular interactions and encodes spatial geometric constraints, enabling sensitivity to subtle effects such as fluorine orthogonal multipolar interactions. Notably, although not trained on mutation data, PBCNet2.0 exhibits an emergent capability to predict affinity changes induced by binding pocket residue variations, supporting resistance analysis. We prospectively validated these capabilities on ENPP1 and ALDH1B1, accurately resolving affinity shifts from minor interaction and conformational differences and identifying critical binding residues with a hit rate of five out of six selected residues.

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

This study aims to comprehensively evaluate the short-term changes in ocular surface parameters and meibomian gland function following Full-incision double-eyelid blepharoplast. In this observational self-controlled study, 50 patients (100 eyes) undergoing full-incision double-eyelid blepharoplasty were enrolled. Assessments were conducted preoperatively and at 1 week, 1 month, and 3 months postoperatively. These included the Ocular Surface Disease Index (OSDI) questionnaire, fluorescein tear film break-up time (FBUT), corneal fluorescein staining (CFS), Schirmer I test, meibum quality, meibomian gland expressibility, meibomian gland dropout (excluding 1-week), lipid layer thickness (LLT), and incomplete blinking rate (IBR). Statistical comparisons were performed using ANOVA with post-hoc analysis. Compared to baseline, OSDI scores, meibum quality, meibomian gland expressibility, and IBR showed statistically significant deterioration at both 1 week and 1 month post-surgery (all p&#x2009;<&#x2009;0.001). In contrast, no significant changes were observed in FBUT, CFS, Schirmer I test, LLT, or meibomian gland dropout at any time point. By the 3-month follow-up, all significantly altered parameters-OSDI, meibum quality, expressibility, and IBR-had recovered to levels that were not statistically different from preoperative baseline values. Full-incision double-eyelid blepharoplasty induces a transient but significant dysfunction of the ocular surface and meibomian glands in the early postoperative period, which is closely associated with a sharp increase in incomplete blinking. These findings underscore the importance of proactive postoperative management, including dry eye counseling, artificial tears, and blink training, to enhance patient comfort during the recovery phase. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

This letter to the editor offers a constructive commentary on a recently published multivariate analysis of predictors of complications in abdominoplasty. The authors commend the original study for its rigorous surgical standardization, consecutive patient enrollment, and single&#x2011;surgeon design, and agree that high body mass index and active smoking are independent risk factors, while preservation of Scarpa's fascia appears protective. However, three methodological limitations are identified. First, the sample size and number of events barely meet the minimum recommended events&#x2011;per&#x2011;variable ratio for multivariate regression. Second, treating seroma, necrosis, and dehiscence as independent outcomes ignores competing risks among these complications, which may bias risk estimates. Third, the single&#x2011;center, single&#x2011;surgeon design limits external validity, and the finding that diabetes is not a risk factor contradicts some existing literature. The letter suggests that future analyses adopt competing&#x2011;risk models and include multicenter external validation. It also notes that no new patient data are provided, so the proposed statistical refinements await empirical verification.Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The widespread adoption of GLP-1 receptor agonists such as semaglutide for weight loss has led to an increasing number of non-diabetic patients seeking body contouring procedures after pharmacologic weight reduction. However, concerns have emerged regarding postoperative complications potentially linked to GLP-1 therapy, particularly when continued up to the time of surgery. This retrospective cohort study aimed to evaluate the impact of preoperative semaglutide discontinuation timing on short-term postoperative outcomes in aesthetic lipoabdominoplasty. Eighty patients who underwent primary lipoabdominoplasty were divided into four groups: continued semaglutide until surgery (Group A), 2-week discontinuation (Group B), 4-week discontinuation (Group C), and semaglutide-na&#xef;ve controls (Group D). All patients were matched for age, BMI, and surgical technique. Postoperative complications within 30 days were assessed. Group A exhibited the highest complication rate (45%), including wound dehiscence, infection, and seroma formation. Group B showed moderate improvement (30% complication rate), while Group C demonstrated a significant reduction in adverse outcomes (10%), comparable to the control group (10%). Gastrointestinal intolerance and prolonged drain duration were also more frequent in patients with ongoing semaglutide use. No reoperations or readmissions occurred. Continuation of semaglutide until surgery significantly increases postoperative complication risk in lipoabdominoplasty. A 4-week preoperative discontinuation period effectively normalizes outcomes, supporting its use as a safety measure in aesthetic surgery candidates. These findings emphasize the need for standardized perioperative management protocols for patients on GLP-1 therapy and underscore the importance of interdisciplinary coordination and nutritional assessment. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The EuroQol Infant and Toddlers Populations (EQ-TIPS) instrument may support both 3-level and 5-level versions, mirroring the structure of the EuroQol Adult and Youth descriptive systems. This study compared the performance of the experimental version 2.0 EQ-TIPS-3L (3&#xa0;L) with EQ-TIPS-5L (5L) in children 0-4 years living with a health condition. Caregivers of children were recruited from specialist outpatient clinics in South Africa. The feasibility of EQ-TIPS-5L and EQ-TIPS-3L was compared using the absolute reduction in the ceiling effect (111111). Discriminatory power was evaluated with Shannon's H' and J' index for absolute and relative informativity. The redistribution of dimension responses between the 5&#xa0;L and 3L versions was evaluated for inconsistency, defined as a 5&#xa0;L response that was two or more levels removed from a 3&#xa0;L response. Convergent validity of EQ-TIPS dimensions was calculated with Kendall Tau B and Gamma correlations. Known-group severity was calculated for the EQ-TIPS-5&#xa0;L and EQ-TIPS-3&#xa0;L LSS scores using severity groupings based on PedsQL total score (&#x2264;&#x2009;74.2) and EQ VAS (&#x2264;&#x2009;80). Data from 176 children with a median age of 29 months, and more males (54%) were included. Most respondents were mothers (78%). Children were grouped by disease category: epilepsy (9%), neuromuscular disease (7%), chronic gastrointestinal disease (16%), renal disease (27%) and oncological or haematological diseases (41%). The ceiling effect (111111) decreased minimally by 2% points from the 3L to 5L. Absolute informativity (H') of dimensions improved by 0.096 on the 5L, with retention of the spread of responses for all dimensions. Convergent validity was similar, with strong correlations on paired 3L and 5L dimensions. The 3L and 5L were similarly able to significantly differentiate between known groups based on PedsQL and EQ VAS severity cut-offs. These results indicate that a 5L version of the EQ-TIPS does not influence the ceiling effect in the same way as the Adult and Youth descriptive system. The modest increase in informativity of the EQ-TIPS-5L suggests the potential advantages of expanded levels of reporting, but this requires testing in samples with more frequent reporting of severe health states.

Disclosure of conflict of interest (COI) is important for surgical societies to minimize bias. The Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) requires committee members to disclose potential COI to promote full transparency. This study investigates compliance with this requirement and quantifies the actual dollar amounts that ineligible companies, collectively "industry", give to committee members. All SAGES committee members were queried in the Centers for Medicare & Medicaid Services Open Payments database (OPD). The query results for 2023 and 2024 were compared to the actual self-reported disclosure statements submitted to SAGES in the spring of 2025. Due to the nature of the database, only US-based physicians were included. Only payments of $500 or more were recorded. Only committees whose rosters were available online were utilized. Incorrect disclosure was defined as a mismatch between the OPD and the member's disclosure. There were 930 individual committee members and 185 were excluded by OPD. Only 51% (382/745) of OPD queries matched disclosures. Correct disclosure occurred in 104/467 who had disclosable COI. Industry paid over $18,000,000 to committee members; one-third came from Intuitive Surgical. Members who received payments received an average of $38,992. The largest total amount to one individual was over $2,500,000. There was no difference in average payments received or appropriate disclosure rate by committee members on one committee versus those on multiple committees. Chair/co-chairs (n&#x2009;=&#x2009;114) did not differ from other members (n&#x2009;=&#x2009;631) in percent of appropriate disclosures (59 vs. 50%). However, chairs/co-chairs did receive larger payments ($37,501 vs. $22,021; p&#x2009;<&#x2009;0.0035). SAGES has set policies for disclosing COI. Enforcement of these policies is challenging. Many committee members receive large payments from industry; thus the actual dollar amount should also be reported. Full and accurate reporting will allow for full transparency and reduce perception of bias.

Though subgroup performance reporting helps ensure the safety of artificial intelligence (AI) products, the extent of this reporting remains unclear. This scoping review identifies studies validating commercially available AI-based products and reports the trends in performance reporting across sex, age, and race/ethnicity demographic subgroups. Peer-reviewed validation studies of commercially available products published after 2010 were collected from the Health AI Register and PubMed on 29 November 2024. Study trends in the reporting of sex, age, and race/ethnicity were mapped with regression analysis. We apply the Wilson confidence interval equation to estimate which tuberculosis detection studies are underpowered for subgroup meta-analysis. Three hundred ninety-two of 545 studies validating 252 products reported subgroup demographic data for any of the three groups. Only 77 of these presented subgroup performance results. Skeletal (20/88) and lung (30/139) studies, and those utilizing chest (24/79) or bone (19/63) radiographs, most often presented subgroup performance data. We found no evidence that more recent studies (OR: 1.039 [95% CI: 0.959-1.127]) or company sponsorship (OR: 1.010 [95% CI: 0.492-1.920]) led to increased subgroup reporting. We show that 14/21 tuberculosis datasets may be underpowered for post-hoc subgroup meta-analysis. This scoping review quantifies how fragmented the commercial validation landscape is, showing that reporting for both the demographics and per-subgroup performance is inadequate for estimating subgroup bias. This systemic problem requires effort from all stakeholders, from researchers to regulatory agencies, encouraging thorough reporting and commercial product validation to support physician and patient trust in medical AI products. Question The number of studies validating the performance of each commercially available radiology AI product for minority subgroup bias is unclear. Findings The currently available commercial AI validation studies often neglect to describe demographic subgroup data, and fewer provide performance results per subgroup, prohibiting algorithmic bias meta-analysis. Clinical relevance Physician and patient trust in the medical AI already used clinically must be built on peer-reviewed literature and meta-analysis. The current literature is insufficient for determining the safety and performance of these products for demographic minorities.

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Type 2 diabetes mellitus (T2DM) is imposing a substantial and rapidly growing global health burden. Disease estimates vary widely across geographies and time periods, reflecting not only true differences in disease occurrence but also variation in demographic structures, risk factor exposures, diagnostic practices, surveillance capacity, and biological heterogeneity within T2DM itself. A narrative, integrative synthesis of global epidemiological evidence was conducted. Data were sourced from major international platforms, supplemented with peer-reviewed literature. Evidence was synthesized across time, place, and person, with explicit attention to differences in case definitions, biomarker use, screening intensity, and modeling assumptions. Conceptual frameworks were applied to interpret observed patterns. Harmonized NCD-RisC analyses show a sustained rise in age-standardized prevalence from 1980 to 2014, increasing from 4.3% to 9.0% in men and from 5.0% to 7.9% in women. According to the IDF, the global burden is projected to reach 852.5&#xa0;million by 2050. Approximately 42.8% (251.7&#xa0;million) of cases remain undiagnosed, with the highest proportions concentrated in low-income regions. Substantial geographic heterogeneity is shaped by population aging, rising adiposity, dietary and physical activity transitions, urbanization, commercial food environments, and health system detection capacity. Subtype distribution and biological heterogeneity further contribute to variation in disease trajectories and complication profiles across populations. Global T2DM prevalence reflects the interaction of biological, social, and health system processes rather than incidence alone. Prevalence trajectories must be interpreted in light of surveillance limitations, diagnostic context, and within-disease heterogeneity. Addressing future burden requires combining improved detection and chronic-care capacity with upstream, life-course-oriented prevention strategies.

Ciprofloxacin (CIP) is a widespread environmental pollutant due to its high chemical stability and frequent presence in aquatic environments. Even at low concentrations, it poses serious risks to human health and ecosystems. This study aimed to optimize the photocatalytic degradation of CIP and evaluate the toxicity of the treated effluent from aqueous solutions. The experiments were conducted in batch mode using a 3&#xa0;L photocatalytic reactor. Experimental optimization was performed using the Central Composite Design (CCD), considering pH, contact time, CIP concentration, and nanoparticle dose as variables. TiO2/Fe3O4 nanocomposites were synthesized via the sol-gel method. Their structure, morphology, and elemental composition were analyzed using Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD (and Energy Dispersive X-Ray Spectroscopy (EDX). CIP residual concentrations were measured using High-Performance Liquid Chromatography )HPLC( according to the experimental design. Effluent toxicity was assessed using a resazurin colorimetric assay based on Escherichia coli activity. The results of the study showed that the synthesized nanoparticles were spherical, with a homogeneous size distribution below 100&#xa0;nm, smooth surface morphology, and no observable aggregation, indicating successful synthesis of structurally stable and well-dispersed nanoparticles. Based on the CCD model, the optimal conditions were a contact time of 67.50&#xa0;min, pH 7.50, an initial CIP concentration of 1&#xa0;mg/L, and a nanocomposite dose of 255&#xa0;mg/L. Under these conditions, CIP removal reached approximately 95%. ANOVA indicated that a second-order regression model with a high coefficient of determination (R2 = 0.9895) best fit the data. The untreated CIP solution exhibited high toxicity toward E. coli, with a Half Maximal Effective Concentration (EC50) of 1.30&#xa0;mg/L. After photocatalytic treatment, EC50, 100% mortality concentration, and No Observed Effect Concentration (NOEC) in the treated effluent were 1.37, 2.27, and 0.92&#xa0;mg/L, respectively; the reduction in toxicity was statistically significant (p&#x2009;<&#x2009;0.05). These results indicate that the synthesized TiO2/Fe3O4 nanocomposite, combined with UV-C ) power&#x2009;=&#x2009;125&#xa0;W, intensity&#x2009;=&#x2009;20 mW/cm2, &#x3bb;max&#x2009;=&#x2009;254&#xa0;nm) radiation, is an effective and stable method for treating wastewater contaminated with antibiotics. The integration of effluent toxicity assessment with experimental modeling (CCD and statistical analysis) represents a novel aspect of this study. This approach has the potential to be scaled up for large-scale environmental applications and to ensure compliance with effluent discharge standards. However, several limitations, including dependence on operational conditions, the formation of potentially toxic intermediate compounds, and challenges in scalability, require further investigation.

Cement is one of the most used materials in the construction industry. Its production contributes about 8% to the global emissions. This study explores the use of eggshell powder (ESP) that contains over 80% calcium carbonate (CaCO3) as a partial substitute for ordinary Portland cement (OPC), such as Types B and D, to substitute limestone within the cement matrix. The physical (consistency and setting time), compressive strength, and chemical (Scanning Electron Microscope with Energy Dispersive Spectroscopy, (SEM-EDS), and X-ray Diffraction (XRD), X-ray fluorescence (XRF)) properties were evaluated against British, Indian, and established standards in the literature. The results showed that cement consistency (31-35%) and setting times were within acceptable limits according to BS EN 197-1 (initial&#x2009;&#x2265;&#x2009;60&#xa0;min) and IS 8112 (initial&#x2009;&#x2265;&#x2009;30&#xa0;min, final&#x2009;&#x2264;&#x2009;600&#xa0;min). The mechanical strength of the samples exceeded the required strength (42.5&#xa0;N/mm2) recommended by the British Standards, except for samples B10N and D10N, which showed strength reductions of 8.4% and 12.3%, respectively. The SEM-EDS and XRD analyses confirmed a high CaCO3 content in the samples. The study suggests that incorporating ESP into OPC should not exceed 5% by weight, as higher proportions could negatively impact the cement's physical and strength properties. This approach will promote environmental sustainability by using agro-waste while ensuring the cement remains suitable for construction.

Hypoalbuminemia is a well-known marker of poor nutritional status and has been linked to adverse outcomes in various surgical specialties. However, its role in mastectomy remains underexplored. This study investigates the impact of hypoalbuminemia on 30-day postoperative outcomes in patients undergoing mastectomy for breast cancer. Using data from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database from 2011 to 2021, we identified 37,848 female breast cancer patients who underwent mastectomy without concurrent reconstructive procedures and had documented preoperative serum albumin levels measured within 30 days of surgery. Patients were stratified by albumin level (<&#x2009;3.5&#xa0;g/dL vs. &#x2265;3.5&#xa0;g/dL). Multivariate logistic regression was used to assess the association between hypoalbuminemia and postoperative 30-day outcomes. ROC analysis identified albumin thresholds predictive of complications. Among 37,848 patients, 3,210 (8.5%) were hypoalbuminemic. Hypoalbuminemia was significantly associated with higher rates of any complication (16% vs. 10%; OR 1.4, p&#x2009;<&#x2009;0.001), surgical complications (10% vs. 5.5%; OR 1.5, p&#x2009;<&#x2009;0.001), medical complications (0.37% vs. 0.13%; OR 1.8, p&#x2009;<&#x2009;0.001). Similarly, readmissions were significantly more frequent in hypoalbuminemic patients (7.0% vs. 3.9%; OR 1.6, p&#x2009;<&#x2009;0.001). The need for transfusion was over three times higher (5.0% vs. 1.4%, p&#x2009;<&#x2009;0.001), and hypoalbuminemia was associated with longer hospital stays (2.2 vs. 1.3 days, p&#x2009;<&#x2009;0.001). Subgroup analysis revealed that these trends persisted across both total and radical mastectomy procedures. Optimal albumin thresholds for predicting complications ranged from 3.7 to 4.1&#xa0;g/dL, depending on the type of complication. Preoperative hypoalbuminemia is an independent predictor of increased postoperative morbidity following mastectomy. Clinicians may consider selective albumin assessment as a pragmatic tool for identifying patients with increased physiological vulnerability who may benefit from targeted preoperative optimization strategies, rather than as a stand-alone indicator of nutritional deficiency; however, further research is needed to establish optimal testing strategies and confirm clinical benefits.

Central nervous system (CNS) infections are associated with high morbidity and mortality, and their management is challenged by antimicrobial resistance and limited cerebrospinal fluid (CSF) penetration of many antibiotics. Intravenous fosfomycin (FOS) offers broad-spectrum activity, favourable pharmacokinetics and reliable CSF penetration, making it a potential partner in combination therapy for severe CNS infections. This interim subgroup analysis of the prospective FORTRESS study evaluated real-world treatment patterns, effectiveness and safety of FOS in patients with CNS infections. FORTRESS is an ongoing multicentre, non-interventional, international study enrolling patients receiving FOS for severe infections. We analysed patients with documented CNS infections among 1019 enrolled up to June 2025. Effectiveness endpoints at end of treatment (EOT) included clinical success (composite endpoint defined as successful clinical response plus concomitant microbiological cure), successful clinical response (defined as complete or partial resolution of signs and symptoms), microbiological cure, clinical failure and in-hospital mortality. Safety outcomes included adverse drug reactions (ADRs; including serious ADRs) and laboratory parameters. A total of 64 patients with CNS infections were included, of which most were critically ill at baseline, with high rates of ICU admission (90.6%), sepsis (42.2%) and mechanical ventilation (35.9%). Included patients were treated for ventriculitis (53.1%), brain abscess/empyema (26.6%), bacterial meningitis (26.6%) and shunt infections (18.8%), mainly caused by Staphylococcus spp. (48.8%). FOS was administered exclusively in combination regimens, generally as second- or third-line therapy, at high daily doses (median 22.1&#xa0;g/day). At EOT, clinical success was achieved in 82.8% of patients, a successful clinical response in 92.2% and microbiological cure in 85.9%. All-cause in-hospital mortality was 12.5%. Outcomes were especially favourable in bacterial meningitis (94.1% clinical success) and Gram-positive infections (96.6% clinical success). FOS was generally well tolerated. Electrolyte imbalances were the most common ADRs but were mainly mild and did not require treatment modification. These interim real-world data suggest that FOS, used in combination with other antimicrobial agents, is an effective and well-tolerated treatment option for severely ill patients with CNS infections. ClinicalTrials.gov identifier, NCT02979951.

The selection of effective coastal marine pollution monitoring systems requires integrating multiple technical, economic, and operational considerations. A decision-support approach is developed to compare five monitoring configurations using criteria that capture detection capability, spatial and temporal coverage, cost, robustness, and energy-related constraints. Expert input is obtained from 120 participants, with 110 responses meeting the consistency requirements, yielding an average consistency ratio of 0.064. The calculated weights indicate that detection capability (0.29) and coverage (0.24) are the most important factors in the assessment. The analysis identifies the underwater sensor network as the highest-ranked alternative, achieving a closeness coefficient of 0.56, followed by the cabled coastal observatory (0.53) and mobile autonomous platforms (0.49). The influence of parameter uncertainty is examined through a sensitivity analysis, in which&#x2009;&#xb1;&#x2009;20% variations in criterion weights produce only limited changes in the ranking order. Additional stochastic simulations, based on &#xb1;&#x2009;0.5 perturbations in performance scores over 100 runs, show low variability, with standard deviations below 0.02 across all alternatives. The results demonstrate consistent ranking behavior and highlight the importance of balanced system performance. The proposed approach supports informed decision-making and can be adapted to different monitoring contexts and evolving technological conditions.