Search Results (2,734)

Directive (EU) 2024/3019 on urban wastewater treatment requires municipal wastewater treatment plants (WWTPs) to achieve energy neutrality by 2045. This study assessed the energy efficiency of a WWTP in central Poland over eight years (2015–2022), considering influent variability, electricity use and cost, and biogas recovery. The facility served 41,951–44,506 inhabitants, with treated wastewater volumes of 3.08–3.93 million m³/year and a real population equivalent (PE) of 86,602–220,459. Over the study period, the specific energy demand remained stable at 0.92–1.20 kWh/m³ (average 1.04 ± 0.09 kWh/m³), equivalent to 17.4–36.3 kWh/PE∙year. Energy efficiency indicators (EEIs) per pollutant load removed averaged 1.12 ± 0.28 kWh/kgBODrem, 0.53 ± 0.12 kWh/kgCODrem, 1.18 ± 0.36 kWh/kgTSSrem, 12.1 ± 1.5 kWh/kgTNrem, and 62.3 ± 11.7 kWh/kgTPrem. EEI per cubic meter of treated wastewater proved to be the most reliable metric for predicting energy demand under variable influent conditions. Electricity costs represented 4.48–13.92% of the total treatment costs, whereas co-generation from sludge-derived biogas covered 18.1–68.4% (average 40.8 ± 13.8%) of the total electricity demand. Recommended pathways to energy neutrality include co-digestion with external substrates, improving anaerobic digestion efficiency, integrating photovoltaics, and optimizing electricity use. Despite fluctuations in influent quality and load, the ultimate effluent quality consistently complied with legal requirements, except for isolated cases of exceeded phosphorus levels. Full article

Background: Cryopreservation of hematopoietic stem cells (HSCs) at −80 °C using uncontrolled-rate freezing is frequently employed in resource-constrained settings, yet concerns remain regarding long-term viability and clinical efficacy. Reliable post-thaw assessment is essential to ensure graft quality and engraftment success. Methods: This single-center, retrospective study evaluated 72 cryopreserved stem cell products from 25 patients stored at −80 °C for a median of 868 days. Viability was assessed using both acridine orange (AO) staining and 7-AAD (7-aminoactinomycin D) flow cytometry at three time points: collection (T0), pre-infusion (T1), and delayed post-thaw evaluation (T2). Associations between viability loss, storage duration, and clinical engraftment outcomes were analyzed. Results: Median post-thaw viability remained high (94.8%) despite a moderate time-dependent decline (~1.02% per 100 days; R² = 0.283, p < 0.001). Mean viability loss at T2 was 9.2% (AO) and 6.6% (flow cytometry). AO demonstrated greater sensitivity to delayed degradation, with a significant difference between methods (p < 0.001). Engraftment kinetics were preserved in most patients, with neutrophil and platelet recovery primarily influenced by disease type rather than product integrity. Notably, storage duration and donor age were not significantly associated with engraftment outcomes or CD34⁺ cell dose. Conclusion: Long-term cryopreservation at −80 °C maintains HSC viability sufficient for durable engraftment, despite gradual decline. While transplant outcomes are primarily dictated by disease biology and remission status, AO staining provides enhanced sensitivity for detecting delayed cellular damage. Notably, our viability-loss model offers a practical framework for predicting product quality, potentially supporting graft selection and clinical decision-making in real-world, resource-constrained transplant settings. Full article

Background: Traumatic brain injury (TBI) is a major public health concern. Creatinine (Cr) has been well studied as a marker of renal function, specifically the development of acute kidney injury (AKI) in TBI patients. We aimed to evaluate the effect of Cr on various clinical outcomes in patients with severe TBI. Methods: We investigated the relationship between Cr levels at various time points and a range of clinical variables, using parametric and non-parametric statistical testing. Results: 1000 patients were included in our study. We found a significant association between sex and Cr level at intensive care unit (ICU) admission and ICU discharge. Cr was positively correlated with ISS at hospital admission, ICU admission, ICU discharge, and at death. Conversely, Cr was negatively correlated with GCS at hospital admission, ICU admission, ICU discharge, and at death. Larger decreases in Cr from Hospital to ICU admission were significantly correlated with increased vent days. Larger decreases in Cr from ICU admission to ICU discharge were significantly correlated with increased hospital length of stay (LOS), ICU LOS, and vent days, likely reflecting the degree of initial hypercreatinemia. For all patients, there were significant positive correlations between Cr at admission and ICU LOS, Cr at ICU admission and ICU LOS, and Cr at ICU admission and vent days. Conclusions: Our findings support existing literature that demonstrates a positive relationship between Cr levels, ICU LOS, and vent days amongst patients with severe TBI. These data suggest renal injury is predictive of TBI outcomes. Future research should investigate the role of renal therapeutic interventions in TBI recovery. Full article

Spinal cord injury (SCI) often results in long-term locomotor impairments, and strategies to enhance functional recovery remain limited. While epidural electrical stimulation (EES) has shown clinical promise, our understanding of the mechanisms by which it improves function remains incomplete. Here, we use genetic tools in an animal model to perform neuromodulation and treadmill rehabilitation in a manner similar to EES, but with the benefit of the genetic tools and animal model allowing for targeted manipulation, precise quantification of the cells and circuits that were manipulated, and the gathering of extensive kinematic data. We used a viral construct that selectively transduces large diameter afferent fibers (LDAFs) with a designer receptor exclusively activated by a designer drug (hM3Dq DREADD; a chemogenetic construct) to increase the excitability of large fibers specifically, in the rat contusion SCI model. As changes in locomotion with afferent stimulation can be subtle, we carried out a detailed characterization of the kinematics of locomotor recovery over time. Adult Long-Evans rats received contusion injuries and direct intraganglionic injections containing AAV2-hSyn-hM3Dq-mCherry, a viral vector that has been shown to preferentially transduce LDAFs, or a control with tracer only (AAV2-hSyn-mCherry). These neurons then had their activity increased by application of the designer drug Clozapine-N-oxide (CNO), inducing tonic excitation during treadmill training in the recovery phase. Kinematic data were collected during treadmill locomotion across a range of speeds over nine weeks post-injury. Data were analyzed using a mixed effects model chosen from amongst several models using information criteria. That model included fixed effects for treatment (DREADDs vs. control injection), time (weeks post injury), and speed, with random intercepts for rat and time point nested within rat. Significant effects of treatment and treatment interactions were found in many parameters, with a sometimes complicated dependence on speed. Generally, DREADDs activation resulted in shorter stance duration, but less reduction in swing duration with speed, yielding lower duty factors. Interestingly, our finding of shorter stance durations with DREADDs activation mimics a past study in the hemi-section injury model, but other changes, including the variability of anterior superior iliac spine (ASIS) height, showed an opposite trend. These may reflect differences in injury severity and laterality (i.e., in the hemi-section injury the contralateral limb is expected to be largely functional). Furthermore, as with that study, withdrawal of DREADDs activation in week seven did not cause significant changes in kinematics, suggesting that activation may have dwindling effects at this later stage. This study highlights the utility of high-resolution kinematics for detecting subtle changes during recovery, and will enable the refinement of neuromechanical models that predict how locomotion changes with afferent neuromodulation, injury, and recovery, suggesting new directions for treatment of SCI. Full article

The glyoxalase pathway intermediate S-d-lactoylglutathione was recently implicated in protein post-translational modifications in animal systems. Here, we examined the spontaneous modification of the Arabidopsis thaliana cytosolic glyceraldehyde-3-phosphate dehydrogenase C1 (GAPC1) by this compound. Incubation of GAPC1 with S-d-lactoylglutathione resulted in the inhibition of enzyme activity. The inhibitory effect was concentration dependent and increased at alkaline pHs. Furthermore, the inhibition of GAPC1 by S-d-lactoylglutathione was favored by oxidative conditions and reversed by reduction with dithiothreitol. Analyses of the S-d-lactoylglutathione-treated protein by nanoLC-MS/MS revealed S-glutathionylation of its two Cys residues and N-lactoylation of six Lys residues. Protein structure predictions showed that the double S-glutathionylation is accommodated by the GAPC1 catalytic pocket, which likely explains enzyme inhibition. N-lactoylated sites overlap partially with previously reported N-acetylated sites at the surface of the GAPC1 tetramer. The efficiency of cytosolic glutaredoxin and thioredoxin isoforms was tested for reversing the S-d-lactoylglutathione-induced modification. In these assays, recovery of GAPC1 activity after inhibition by S-d-lactoylglutathione treatment was used as indicator of efficiency. The results show that both types of redoxins were able to reverse inhibition. We propose a model describing the mechanisms involved in the two types of post-translational modifications found on GAPC1 following exposure to S-d-lactoylglutathione. The possible involvement of these findings for the control over glycolytic metabolism is discussed. Full article

Background: Bioelectrical impedance analysis (BIA) is a widely used field technique for assessing body composition in football. However, its reliance on population-specific regression equations limits its accuracy. Objective: This scoping review aimed to map the scientific literature on BIA applications in professional and semi-professional football, highlighting uses, limitations, and research opportunities. Methods: A comprehensive search was conducted in the scientific databases PubMed, EMBASE, Web of Science, and SPORTDiscus. Identified studies involved the use of BIA in professional and semi-professional football players (≥16 years) in the context of routine training and competition. Results: From 14,624 records, 39 studies met the inclusion criteria and were included. Three main applications were identified: (1) quantitative body composition assessment, (2) qualitative/semi-quantitative analysis (e.g., bioelectrical impedance vector analysis (BIVA)), and (3) muscle health and injury monitoring. Seven specific research areas emerged, including hydration monitoring, cross-method validation of body composition analyses, development of predictive models, sport phenotype identification, tracking training adaptations, performance/load assessment via phase angle, and localized BIA for injury diagnosis and recovery. Conclusions: While quantitative BIA estimates may lack individual-level precision, raw parameter analyses may offer valuable insights into hydration, cellular integrity, and muscle injury status, yet further research is needed to fully realize these applications. Full article

Background: Hip fractures are common in the elderly and often require ICU admission post-surgery due to high ASA scores and comorbidities. Length of hospital stay after ICU is a crucial indicator affecting patient recovery, complication rates, and healthcare costs. This study aimed to develop and validate a machine learning-based model to predict the factors associated with extended hospital stay (>7 days from surgery to discharge) in hip fracture patients requiring postoperative ICU care. The findings could help clinicians optimize ICU bed utilization and improve patient management strategies. Methods: In this retrospective single-centre cohort study conducted in a tertiary ICU in Turkey (2017–2024), 366 ICU-admitted hip fracture patients were analysed. Conventional statistical analyses were performed using SPSS 29, including Mann–Whitney U and chi-squared tests. To identify independent predictors associated with extended hospital stay, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied for variable selection, followed by multivariate binary logistic regression analysis. In addition, machine learning models (binary logistic regression, random forest (RF), extreme gradient boosting (XGBoost) and decision tree (DT)) were trained to predict the likelihood of extended hospital stay, defined as the total number of days from the date of surgery until hospital discharge, including both ICU and subsequent ward stay. Model performance was evaluated using AUROC, F1 score, accuracy, precision, recall, and Brier score. SHAP (SHapley Additive exPlanations) values were used to interpret feature contributions in the XGBoost model. Results: The XGBoost model showed the best performance, except for precision. The XGBoost model gave an AUROC of 0.80, precision of 0.67, recall of 0.92, F1 score of 0.78, accuracy of 0.71 and Brier score of 0.18. According to SHAP analysis, time from fracture to surgery, hypoalbuminaemia and ASA score were the variables that most affected the length of stay of hospitalisation. Conclusions: The developed machine learning model successfully classified hip fracture patients into short and extended hospital stay groups following postoperative intensive care. This classification model has the potential to aid in patient flow management, resource allocation, and clinical decision support. External validation will further strengthen its applicability across different settings. Full article

Frame Replication and Elimination for Reliability (FRER) in Time-Sensitive Networking (TSN) enhances fault tolerance by duplicating critical traffic across disjoint paths. However, always-on FRER configurations introduce persistent redundancy overhead, even under nominal network conditions. This paper proposes a predictive FRER activation framework that anticipates faults using a Key Performance Indicator (KPI)-driven bidirectional Long Short-Term Memory (BiLSTM) model. By continuously analyzing multivariate KPIs—such as latency, jitter, and retransmission rates—the model forecasts potential faults and proactively activates FRER. Redundancy is deactivated upon KPI recovery or after a defined minimum protection window, thereby reducing bandwidth usage without compromising reliability. The framework includes a Python-based simulation environment, a real-time visualization dashboard built with Streamlit, and a fully integrated runtime controller. The experimental results demonstrate substantial improvements in link utilization while preserving fault protection, highlighting the effectiveness of anticipatory redundancy strategies in industrial TSN environments. Full article

This study investigates the solubility correlation of oil extracted from Sabah green Robusta coffee (Coffea canephora) beans through supercritical carbon dioxide (SC-CO₂) extraction. Sabah, recognized as the largest coffee-producing region in Malaysia, serves as a significant source of Robusta beans for this research. The solubility of coffee bean oil was evaluated under varying pressures (10–30 MPa) and temperatures (40–80 °C). The maximum solubility, 2.681 mg/g CO₂, was recorded at 30 MPa and 40 °C, whereas the lowest solubility, approximately 0.440 mg/g CO₂, occurred at 20 MPa and 80 °C. A clear inverse relationship between solubility and temperature was observed, with solubility decreasing as temperature increased to 80 °C. Conversely, elevated pressure, particularly at 30 MPa, enhanced solubility due to the increased density and solvent power of SC-CO₂. Experimental data exhibited strong agreement with Chrastil’s equation, yielding a relatively low percentage error of 3.37%, compared with 14.57% for the del Valle-Aguilera model. These findings demonstrate the reliability of Chrastil’s model in predicting the solubility of Sabah green coffee bean oil in SC-CO₂. Overall, the research highlights the potential of SC-CO₂ extraction as a sustainable, solvent-free approach for obtaining high-quality coffee oil extracts, with promising applications in the food industry and possible extension to the recovery of other bioactive compounds in food processing. Full article

Background: Despite advances in surgical techniques and perioperative care, pancreatic resections such as pancreaticoduodenectomy (PD) and distal pancreatectomy (DP) remain high-risk procedures. Postoperative complications significantly impact morbidity, mortality, and patient quality of life. Methods: This narrative review summarizes recent literature on major complications following pancreatic surgery, including postoperative pancreatic fistula (POPF), delayed gastric emptying (DGE), and post-pancreatectomy hemorrhage (PPH), with an emphasis on incidence, risk factors, outcomes, and current preventive strategies. Results: POPF is a leading complication, occurring in 5–22% of cases and often linked with sepsis and hemorrhage. Key risk factors include high BMI, soft pancreatic texture, and small duct size. Preventive measures like Pasireotide, modified anastomosis techniques, and neoadjuvant therapy show variable success. DGE affects up to 57% of PD patients and is associated with prolonged recovery; antecolic reconstruction and erythromycin may reduce incidence. PPH, though less frequent (3–13%), can be life-threatening, particularly when secondary to POPF. Endovascular approaches are now favored for late arterial bleeding. Other complications include wound infections, abscesses, bile leaks, and pulmonary issues, all contributing to extended hospital stays and diminished quality of life. Conclusions: Pancreatic surgery continues to carry significant risks, with POPF, DGE, and PPH being the most impactful complications. While multiple interventions have shown promise, standardized protocols and predictive tools are still needed. Surgery should be performed in high-volume centers with experienced multidisciplinary teams to optimize outcomes. Full article

Isothermal hot compression tests were performed on an Al-4.8Cu-0.25Mg-0.32Mn-0.17Si alloy using a Gleeble-3500 thermomechanical simulator within the temperature range of 350–510 °C and strain rate range of 0.001–10 s⁻¹, achieving a true strain of 0.9. The constitutive equation and hot processing maps were established to predict the flow behavior of the alloy. The hot deformation mechanisms were investigated through microstructural characterization using inverse pole figure (IPF), grain boundary (GB), and grain orientation spread (GOS) analysis. The results demonstrate that both dynamic recovery (DRV) and dynamic recrystallization (DRX) occur during hot deformation. At high lnZ values (high strain rates and low deformation temperatures), discontinuous dynamic recrystallization (DDRX) dominates. Under middle lnZ conditions (low strain rate or high deformation temperature), both continuous dynamic recrystallization (CDRX) and DDRX are the primary mechanisms. Conversely, at low lnZ values (low strain rates and high temperatures), CDRX and geometric dynamic recrystallization (GDRX) become predominant. The DRX process in the Al-Cu-Mg alloy is controlled by the deformation temperature and strain rate. Full article

The increasing penetration of renewable energy presents substantial challenges to frequency stability, particularly in low-inertia microgrids. This study introduces an agent-based microgrid model that integrates generators, loads, an energy storage system (ESS), and renewable sources, mathematically formalized through the discrete-event system specification (DEVS) to ensure both structural clarity and extensibility. To dynamically simulate power system behavior, the model incorporates multiple control strategies—including ESS scheduling, automatic generation control (AGC), predictive AGC, and grid-forming (GFM) inverter control—each posed as an mathematically defined control problem. Simulations on the IEEE 13-bus system demonstrates that the coordinated operation of ESS, GFM, and the proposed strategies markedly enhances frequency stability, reducing frequency peaks by 1.14, 1.14, and 0.72 Hz, and shortening the average recovery time by 9.05, 0.15, and 2.58 min, respectively. Collectively, the model provides a systematic representation of grid behavior and frequency regulation mechanisms under high renewable penetration, and establishes a rigorous mathematical framework for advancing microgrid research. Full article

Background and Objectives: Enhancing recovery after cardiac surgery involves minimally invasive procedures, early extubation/mobilization, and swift discharge. While mechanical ventilation is often essential post-operation, prolonged invasive ventilation (IMV) increases mortality risk. Duration is influenced by patient factors (age and comorbidities), surgical complexity, and complications. Prognostic scores like EuroSCORE II, sequential organ failure assessment (SOFA), the Charlson Comorbidity Index (CCI), and the vasoactive–inotropic score (VIS) help to predict ventilation needs. The aim of this study is to analyze the effect of pre-/post-operation factors and procedure type as predictors of ventilation time. Materials and Methods: This is a retrospective cohort observational study analyzing factors affecting the duration of postoperative mechanical ventilation in elective cardiac surgical patients treated between 1 January and 31 December 2024 in a tertiary center in continental Croatia. Patients were stratified into two groups according to the duration of IMV: normal (first three quartiles) and prolonged (upper quartile). In total, 493 elective cardiac surgical patients operated on under general endotracheal anesthesia with sternotomy or mini-sternotomy were admitted postoperatively to the cardiovascular ICU and mechanically ventilated during the observed period, and 463 patients were included in the final analysis after the exclusion criteria had been applied. Results: The mean age was 64.7 ± 9.8 years, and 28.7% of the cohort were females while 71.3% were males. The median Charlton Comorbidity Index was 4 (IQR 3–5), the VIS was 2 (IQR 0–3), the SOFA score at ICU admission was 5 (IQR 3–6), and the adjusted SOFA score was 3 (IQR 2–4). In the multivariate logistic regression model, a significant effect of female sex (OR 1.98), age (OR 1.05), VIS (OR 1.05), and history of previous cardiac surgery (OR 6.67) on the duration of mechanical ventilation was observed. In the time-to-extubation multivariate analysis, there was a significant effect of re-do surgery (HR 3.70), corrected SOFA score (HR 1.14), and VIS (HR 1.05) on the duration of mechanical ventilation. There was no significant effect of the type of surgery (CABG, aorta, aortic valve, mitral/tricuspid valve, or other) or the amount of chest tube drainage on the duration of mechanical ventilation. Conclusions: A history of previous cardiac surgery and the vasoactive–inotropic score during the first 24 postoperative hours in the ICU are the strongest predictors of the duration of mechanical ventilation after elective cardiac surgery, with a statistically significant effect present in both the logistic regression model and hazard ratio analysis. Further analyses with more variables are warranted in the future to refine the prognostic model. Full article

The estimated ultimate recovery (EUR) is an important parameter for forecasting oil and gas production and informing decisions regarding field development strategies. In this study, we combined site-specific geologic, completion, and operational parameters with the predictive capabilities of machine learning (ML) models to predict EURs of the wells for the Eagle Ford Marl Continuous Oil Assessment Unit. We developed an extensive dataset of wells that have produced from the lower and upper Eagle Ford Shale intervals and reduced the model complexity using principal component analysis. We tested the ML models and estimated the sensitivities of ML-predicted EURs to changes in the values of different input variables. The results of applying the optimized ML model to the Eagle Ford suggest that the approach developed in this study could be promising. The ML estimates of the EURs fit the DCA-based values with an R² ~ 0.9 and a mean absolute error of ~36 × 10³ bbl. In the lower Eagle Ford Shale, the EUR estimates were found to be most sensitive to changes in porosity, net thickness of the interval, clay volume, and the API gravity of the oil; and that in the upper Eagle Ford Shale they were most sensitive to changes in the total organic carbon and water saturation, which suggests that it could be important to consider these parameters in assessing these intervals or close analogs. Full article

Therapeutic plasma exchange (TPE) is increasingly recognized as a critical escalation therapy for managing acute multiple sclerosis (MS) relapses refractory to high-dose corticosteroids. Neuropathological and clinical evidence implicate humoral immune mechanisms, particularly autoantibodies, immune complexes, and complement activation, as key pathogenic drivers in a subset of MS attacks, notably those consistent with immunopathological pattern II. By removing these circulating immune effectors, TPE provides a rational strategy to dampen inflammation and promote neurological recovery. This review integrates current mechanistic insights with clinical efficacy data and practical implementation strategies for TPE in corticosteroid-refractory MS. Evidence from randomized controlled trials and observational cohorts demonstrates moderate-to-marked functional improvement in 40–60% of patients, with the greatest benefit observed when therapy is initiated within 14 days of symptom onset and cases demonstrating active inflammatory lesions on MRI. Predictors of a favorable response include younger age, short disease duration, severe syndromes involving optic nerve, brainstem, or spinal cord, and CSF markers of intrathecal B-cell activity. Although TPE is generally well tolerated in experienced centers, its broader adoption of TPE is limited by variability in access, institutional protocols, and provider familiarity. Standardization of treatment algorithms, validation of predictive biomarkers, and incorporation into streamlined clinical pathways are critical to maximizing its clinical impact. Future priorities include comparative trials against alternative escalation therapies, biomarker-guided patients’ selection, and comprehensive health-economic evaluations. Taken together, current evidence and recommendations from major neurology and apheresis societies support TPE as a valuable therapeutic modality capable of significantly improving relapse outcomes in appropriately selected MS patients. Full article