Carbon Dioxide Levels Research Articles (Page 1)

Pulmonary infections in the elderly are difficult to diagnose due to immunosenescence, atypical symptoms, and frequent polymicrobial or opportunistic infections. Traditional methods often miss pathogens. Targeted next-generation sequencing (tNGS) enables rapid, sensitive, and comprehensive detection of pathogens and resistance genes, offering clear advantages. This retrospective study analyzed bronchoalveolar lavage fluid samples from 306 elderly inpatients with clinically suspected pulmonary infections using tNGS. Detected microbial species, antimicrobial resistance genes, and relevant clinical data were extracted from electronic medical records. Kaplan-Meier survival analysis and an eXtreme gradient boosting (XGBoost) machine learning model were employed to identify predictors of prolonged hospitalization. Viruses were the most frequently identified pathogens (29.6%), followed by bacteria (24.4%) and fungi (9.0%). Fungal co-infections were significantly associated with prolonged hospital stays and disrupted blood gas homeostasis, characterized by elevated partial pressure of carbon dioxide (PaCO₂) and bicarbonate (HCO₃⁻) levels. Antimicrobial resistance genes were detected in 7.5% of patients, with 23S rRNA mutations and mecA being the most prevalent. Inflammatory markers (C-reactive protein, procalcitonin) and gas exchange indices (PaCO₂, partial pressure of oxygen [PaO₂]) showed significantly correlations with overall pathogen burden. The eXtreme gradient boosting model identified PaCO₂, procalcitonin, HCO₃⁻, and fungal infection status as key predictors of prolonged hospitalization. tNGS facilitates comprehensive detection of pathogens and antimicrobial resistance genes in elderly patients with pulmonary infections. Our findings underscore the often overlooked clinical impact of fungal co-infection and respiratory dysfunction on patient outcomes. These results highlight the value of incorporating tNGS into routine diagnostic workflows for geriatric infection management, enhancing both diagnostic accuracy and prognostic assessment.

The rapid urbanization process has led to deteriorating air quality and elevated carbon dioxide levels, highlighting an urgent need for effective urban greening strategies. This study aims to quantify and compare the air pollution removal (APR), carbon sequestration (CS), and oxygen production (OP) capacities of different green space renovation plans in residential areas of a typical arid to semi-arid city in Northwest China. Using the i-Tree Eco model, we simulated the ecological benefits of various vegetation configurations. Our results demonstrated that tree species selection is a critical determinant of ecological performance. Ligustrum (Privet), Magnolia, and Populus (Poplar) were identified as the predominant species, exhibiting distinct effectivities in providing these services. Specifically, we found that species with high APR and CS efficiencies should be prioritized for green space renewal in this water-limited region. Correlation analysis revealed that both APR and CS capacities were most strongly correlated with vegetation greenness, followed by species identity. In contrast, the planning layout of vegetation showed no significant correlation with greenness. For OP, tree species was the most influential factor, ahead of vegetation quantity. This study provides a scientific basis for optimizing plant species selection and spatial arrangement in urban greening projects, offering practical guidance for enhancing ecological benefits in arid and semi-arid cities undergoing renewal.

Objectives: Gastrointestinal bleeding is a common condition in emergency departments and can be fatal if diagnosis and treatment are delayed. In this study, we aimed to explore the relationship between end-tidal carbon dioxide (ETCO2) levels and Glasgow Blatchford Score (GBS) and AIMS65 scores, as well as its impact on assessing morbidity and mortality in patients presenting to the emergency department with gastrointestinal bleeding. Methods: The research involved 103 eligible patients diagnosed with gastrointestinal bleeding. ETCO2 measurements were taken on admission and data on hospitalization, GBS/AIMS65 scores, endoscopically detected active bleeding and 30-day mortality were recorded. Statistical analysis was performed on the collected data. Results: When ETCO2 values obtained from the patients were compared according to hospitalization status, GBS score, AIMS65 score, presence of endoscopically detected active bleeding and mortality status; ETCO2 levels were significantly lower in patients with active bleeding, those who died, patients with AIMS65 scores ≥2, and those with GBS scores ≥12 (P<0.05). Conclusions: This study demonstrates that ETCO2 levels are significantly lower in patients with gastrointestinal bleeding, especially in those with active bleeding, high mortality risk, and elevated GBS or AIMS65 scores. ETCO2 may serve as a rapid and practical marker for assessing hypovolemia and clinical status in emergency settings.

Recent advances in biocathode materials and configurations for reactor applications in microbial electrosynthesis of CO2.

Objective To explore the establishment and application of an early warning scoring system for neonatal pneumonia based on information technology. Methods A total of 140 neonates with pneumonia admitted to our hospital from July 2020 to December 2023 were selected as study subjects. They were randomly divided into a control group (routine care, n = 70) and an observation group (care under an early warning mechanism integrated into the hospital’s electronic health record (EHR) system, which provided real-time alerts to the medical staff, n = 70). The time to symptom resolution was compared between the two groups. An assessment of respiratory status using the Neonatal Respiratory Distress Score (NRDS) and blood gas analysis indicators were compared before (within 1 h of enrollment) and 1 week after care. Incidence of complications was also recorded and analyzed. Results There was no significant difference in birth time, gender, weight, disease course, and mode of delivery between the two groups (p > 0.05). Significant differences were observed in the time to disappearance of cough, dyspnea, pulmonary rales, return to normal temperature, and relief of respiratory distress between the two groups (p < 0.05). Before care (within 1 h), there was no significant difference in NRDS levels between the two groups (p > 0.05). However, one week after care, the NRDS was significantly lower in the observation group than in the control group (p < 0.001). Similarly, oxygen saturation (SpO2), partial pressure of arterial oxygen (PaO2), and arterial oxygen saturation (SaO2) levels were significantly higher in the observation group while partial pressure of arterial carbon dioxide (PaCO2) level was significantly lower compared to the control group one week after care (p < 0.001). Conclusion The application of an early warning scoring system for neonatal pneumonia based on information technology can shorten the time to symptom resolution, improve respiratory status, normalize blood gas indices, and reduce the incidence of complications.

Indoor air quality, particularly carbon dioxide (CO₂) levels, is critical to occupants’ health and comfort. This study developed predictive models for indoor CO₂ concentrations based on environmental variables, including light, temperature, humidity, and the presence of plants. Data collected from sensors within a controlled indoor environment were used to train predictive models using various techniques, including artificial neural networks (ANN), k-Nearest Neighbors (k-NN), Random Forest, and generalized linear models. Among standalone models, the ANN with a 70:30 train-test split yielded the best performance, achieving a root mean square error (RMSE) of 10.960, mean absolute error (MAE) of 7.300, and a coefficient of determination (R²) of 0.640. The study further explored ensemble methods by combining ANN, k-NN, and generalized linear models through soft voting. The optimal ensemble configuration—ANN and k-NN with a 90:10 split ratio—achieved an RMSE of 11.437, MAE of 8.153, and R² of 0.650, outperforming the standalone models. In addition, the results demonstrated that the presence of plants within a room significantly reduced CO₂ levels under specific conditions (20-30°C and 200 lux), highlighting plants' potential to improve indoor air quality. This research suggests that ensemble models offer a viable solution for accurate indoor CO₂ prediction, with practical applications in indoor environmental management, especially when coupled with biophilic design elements such as indoor plants.

Rising Carbon Dioxide (CO2) levels and global warming concerns challenge the sustainability of fossil fuels as primary energy sources. Hydrogen is emerging as a crucial energy carrier, offering reduced carbon emissions and minimal harmful gases. Methods like hydrocarbon reforming and water electrolysis, especially when powered by renewable sources like wind and solar, enable hydrogen production. Hydrogen's purity and compatibility with fuel cells make it an eco-friendly alternative with high energy output. This project models a solar Photovoltaic(PV)-based hydrogen production system to address environmental concerns. Using MATLAB/Simulink for dynamic simulation, it accurately represents and analyses the hydrogen production for different regions which having different irradiances. Initial results highlight V-I and V-P curves for PV systems, revealing optimal conditions for efficient hydrogen production through electrolysis. This research advances sustainable hydrogen generation methods, emphasizing solar PV's potential to foster an eco-friendly and efficient energy landscape.

Abstract Rising atmospheric carbon dioxide (CO 2 ) levels exceeding 400 ppm since 2013 and reaching 36.6 billion tons in 2022 due to fossil fuel combustion have accelerated global climate change, contributing to a 1.2 °C rise in temperature and triggering serious environmental issues such as ocean acidification and extreme weather events. Among emerging mitigation strategies, electrochemical CO₂ reduction offers a promising route to convert CO 2 into valuable fuels and chemicals. This review highlights recent advances in nanomaterial-based CO 2 conversion, focusing on electrochemical processes enabled by catalysts such as metal and metal oxide nanoparticles, graphene, carbon nanotubes, and carbon quantum dots. These nanostructures provide large surface areas, tunable electronic properties, and improved catalytic performance. In-operando characterization techniques including transmission electron microscopy (TEM), X-ray absorption spectroscopy (XAS), Raman spectroscopy, infrared spectroscopy (IR), and electrochemical impedance spectroscopy (EIS) are discussed for their role in offering real-time mechanistic insights that support rational catalyst design. The review also considers photocatalytic, thermocatalytic, and plasma-assisted processes to provide a broader perspective on CO 2 utilization. Strategies such as surface functionalization, hybrid material development, and strain engineering are examined for enhancing efficiency and durability. The review concludes by highlighting challenges and future directions for integrating nanomaterials into sustainable, carbon-neutral technologies. Graphical Abstract

BackgroundHigh frequency oscillation (HFO) is a lung protective ventilation strategy for newborn infants due to the small tidal volume delivery at fast frequencies, but has been associated with an increased risk of brain injury. High-frequency oscillation with volume-targeted ventilation (HFO&VTV) is a new mode of HFO that applies a targeted tidal volume (VThf) set by the clinician and achieves less fluctuations of carbon dioxide levels and therefore reduces the risk of brain injury. The optimal starting VThf values, however, have not been explored to date.This study investigates the optimum starting settings in newborn infants receiving HFO by comparing the cerebral blood flow velocity and cardiac output at different tidal volume targets of HFO&VTV.MethodsThis randomised crossover trial performed at a single tertiary neonatal unit will be recruiting 25 infants of any gestation and at any postnatal age receiving HFO. Each infant will receive three targeted tidal volumes on HFO&VTV in random order with control periods in between. The resistive index (RI) as an indicator of cerebral blood flow in term-born infants and the cardiac output for all infants in the study will be assessed in each period. The primary outcome will be the reduction in the RI that will be measured on term-born infants using the anterior cerebral artery Doppler. The secondary outcome will be the improvement in cardiac output that will be assessed in all infants with bedside ECHO. The study will be performed following informed parental consent and was approved by the London-Hampstead research ethics committee (Protocol version 2, 22/01/25).DiscussionThis trial will investigate the effect of HFO&VTV on cerebral blood flow velocity and cardiac output to further elucidate the optimal volume targeting range in newborn infants.Trial registrationClinicalTrials.Gov, NCT06719284, registered on 04/12/2024.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13063-025-09179-w.

The urgent global issue of climate change caused by rising carbon dioxide (CO2) levels has led to the widespread use of gas separation processes. Among the available processes, chemical absorption has received more attention due to its maturity and higher efficiency compared to others. However, the high energy consumption during the desorption step poses several technical challenges, limiting its industrial applications. To overcome those challenges, several research studies have been conducted to improve the performance of the desorption process. In particular, various types of catalysts have been tested to improve the performance of the CO2 desorption process. Among the available catalysts, Titanium Oxyhydrate (TiO(OH)2) has shown remarkable characteristics for replacing conventional catalysts, mainly due to its stability and the potential for increasing the CO2 desorption rate. However, limited studies have been conducted to evaluate the performance of the CO2 desorption process, especially by utilizing commercial solvents such as piperazine (PZ) promoted methyldiethanolamine (MDEA). Hence, this study aims to evaluate the stability of TiO(OH)2 as a catalyst during the CO2 desorption process using various characterization techniques. The CO2 desorption performance is also assessed under different operating conditions. Moreover, the regeneration energy is determined and reported as the sensible heat duty per released CO2. The results show no significant difference between fresh and cycled TiO(OH)2, indicating its substantial thermal stability. Furthermore, a notable rise of 19.58% is observed in desorption rate while utilizing TiO(OH)2 with a mass concentration of 5 wt%, reflecting less energy consumption. These findings suggest that TiO(OH)2 could serve as a transformative catalyst in industrial-scale CO2 desorption processes, potentially paving the way for more sustainable CO2 capture technologies.

This study investigates the relationship between marine chlorophyll content and environmental factors using ocean observation big data. Through data preprocessing, gray correlation analysis, Spearman correlation analysis, and random forest modeling, the research identifies key environmental drivers of chlorophyll content, including carbon dioxide levels, seawater temperature, salinity, pH, and dissolved oxygen. The results reveal significant negative correlations between carbon dioxide and temperature with chlorophyll content, underscoring the potential role of marine chlorophyll in carbon sequestration. This work enhances understanding of marine ecosystem dynamics and provides a scientific basis for marine resource management and ecological conservation. By integrating multiple analytical methods, the study offers a novel approach for predicting marine chlorophyll content, contributing to global carbon cycle research and supporting sustainable marine resource management under environmental change.

Transportation, being a significant contributor to rising global emissions, underscores the need for alternative fuels like ammonia, methanol, hydrogen, and others. Transient scenarios are crucial to study because they reflect real-world driving conditions where engines frequently transition between different loads and speeds, significantly impacting emissions and performance. There is a significant gap in research on using ammonia and methanol blended fuels in engines, particularly under transient conditions, due to the complexity and challenges in combustion control. This study aims to address this gap by conducting a comprehensive simulative investigation of ammonia-methanol flex-fuel blends for a transient marine engine. Utilizing an experimentally validated GT-Power model, the study evaluates three key characteristics: performance, combustion, and emissions, under various operating conditions involving parameters such as injection timing, spark timing, and different blend ratios of both fuels. The study reveals that increasing the ammonia content in methanol blends results in moderate changes to engine performance, with slight decreases in indicated mean effective pressure and indicated efficiency, despite maintaining constant energy input. These performance reductions are minor compared to pure methanol. However, the most significant advantages are seen in emissions, with carbon dioxide levels decreasing by up to 80% when comparing blends of 25% Methanol and 75% Ammonia to 100% Methanol, highlighting the potential of ammonia-methanol flex-fuels as environmentally friendly alternatives. Furthermore, the air-fuel ratio fluctuation was also observed to be reduced with methanol-ammonia blends, which can make the engine drivability smoother during transient operation with sudden load changes that will minimized the engine vibration during transition stage. This research positions ammonia-methanol blends as a 100% renewable fuel option for engines, offering significant potential for reducing emissions and improving environmental sustainability in the transportation sector.

Kombucha is a fermented beverage with a slightly acidic taste, flavor, and natural carbonation. It has gained popularity due to its health benefits. Traditional kombucha is prepared by fermentation of black tea and sucrose. Today, kombucha products do not have a standard composition and there is a growing demand. Therefore, the purpose of this research was to produce kombucha with hibiscus and two different sweeteners (apple juice concentrate and sucrose), to examine physicochemical properties, ethanol and vitamin B12 contents, to identify volatiles, and to study its compatibility in spherification. Fermentation resulted in a pH drop. Decrease in brix of kombucha with apple juice concentrate was seen whereas brix of kombucha with sucrose did not change. While density and fermentation rate of apple juice concentrate containing sample were higher than those of the sucrose containing one, beverage yields were similar. Negligible color changes were encountered during fermentation. Ethanol, vitamin B12, and carbon dioxide levels were determined as 1.08-1.12 g/L, 0.054-0.071 µg cyanocobalamin/100 g, and 0.40-0.43 g/L, respectively. Decanoic acid, octanoic acid, and lauric acid were the major volatiles. Kombucha spheres with apple juice concentrate had higher diameter and weight whereas spheres with sucrose had more uniform surface and less color change.

PurposeThis study evaluated the predictive value of the pan-immune-inflammation value (PIV) and developed a nomogram that integrated the PIV to predict adverse clinical outcomes in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).Patients and MethodsIn a retrospective, single-center study, 522 patients with AECOPD were randomized 7:3 into the training and validation cohorts. Univariate and multivariate logistic regression were used to determine independent predictors of adverse clinical outcomes. After the optimal cutoff value for the PIV was determined, the training cohort was divided into the high-PIV and low-PIV groups. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were then performed to construct and validate the nomogram.ResultsThe regression results identified age, serum albumin (ALB) level, partial pressure of carbon dioxide (PaCO2) level, and the PIV as independent predictors of adverse clinical outcomes, and they were included in the nomogram model. The AUCs of the nomogram model that included these four variables in the training and validation cohorts were 0.720 (95% confidence interval [CI]: 0.658–0.783) and 0.733 (95% CI: 0.626–0.840), respectively. The calibration curves of the two cohorts showed good prediction accuracy (Hosmer-Lemeshow test: both P > 0.05), and the DCA proved that the prediction model has some clinical value.ConclusionAge, ALB level, PaCO2 level, and the PIV are independent predictors of adverse clinical outcomes in patients with AECOPD and may help healthcare providers identify patients at high risk of adverse outcomes during early admission. Although promising, the nomogram model has only moderate predictive performance. Further studies are required to identify additional significant factors to develop a higher-performing prediction model with which to make more accurate decisions in clinical practice.

A Quick Reference on Respiratory Alkalosis.

BackgroundThis study aims to investigate the effects of postharvest oxalic acid (OA), citric acid (CA) and modified atmosphere packaging (MAP) applications on fruit quality and preservation of biochemical content in persimmon. This research conducted on “Rojo brillante” variety persimmon (Diospyros kaki L), evaluated the effects of various treatment methods on fruit quality during 90 days of storage period. In the study, the parameters such as weight loss, total soluble solids (TSS), titratable acidity, fruit firmness, respiration rate, ethylene production, gas composition, phenolic content, antioxidant activity and organic acids were investigated.MethodIn the study, each application consisted of three replications. The first group was control, the second group was 1 mmol CA, the third group was 1 mM OA, the fourth group was MAP, the fifth group was 1 mmol CA + MAP and the sixth group was 1 mM OA + MAP. The fruits were kept in control, CA and OA solutions for 15 min. The fruits were stored for 90 days at 5 °C and 85 ± 5% relative humidity.ResultsDuring storage period, fruit weight loss, water loss and natural physiological changes increased. OA and CA acid applications were not effective in reducing fruit weight loss, but OA + MAP applications were more effective in preserving fruit quality. MAP prevented water loss and preserved fruit quality by decreasing oxygen levels and increasing carbon dioxide levels. The changes in TSS ratio were observed while MAP and OA + MAP treatments kept TSS constant. Application of OA + MAP increased acidity by preserving the stability of acidic compounds. Flesh firmness decreased with storage time, but MAP and OA + MAP combinations gave better results. As the storage period progressed, color changes and respiration rate increased, MAP application slowed down fruit respiration and delayed ripening. An increase in carbon dioxide levels was observed during storage, the highest levels were recorded in OA + MAP and CA + MAP applications. MAP application kept nitrogen levels the highest, the nitrogen levels reached equilibrium with the combination of OA and MAP. In addition, OA and CA applications increased phenolic content and antioxidant activity while it decreased in MAP and control groups. In terms of acidic compounds, the combination of OA and MAP was effective in preserving fruit acids.ConclussionOA + MAP treatments were more effective in preserving fruit quality by reducing water loss, maintaining acidity, and improving flesh firmness compared to other applications. MAP treatment also slowed respiration, delayed ripening, and maintained nitrogen levels, contributing to overall fruit preservation during storage. The study revealed the potential use of these methods in extending fruit quality and shelf life.

Due to the rising atmospheric carbon dioxide levels driven by human activity, extensive scientific efforts have been dedicated to developing methods aimed at reducing its concentration in the atmosphere. A novel approach involves using hydrates as a long-lasting reservoir of CO2 sequestration. This review provides an initial overview of hydrate characteristics, their formation mechanisms, and the experimental techniques commonly employed for their characterization, including X-ray, Raman spectroscopy, cryoSEM, DSC, and molecular dynamic simulation. One of the main challenges in CO2 sequestration via hydrates is the requirement of high pressures and low temperatures to stabilize CO2 molecules within the hydrate crystalline cavities. However, deviations from classical temperature-pressure phase diagrams observed in natural and engineered environments can be explained by considering that hydrate stability and formation are primarily governed by chemical potentials, not just temperature and pressure. Activity, which reflects concentration and non-ideal interactions, greatly influences chemical potentials, emphasizing the importance of solution composition, salinity, and additives. In this context the role of promoters and inhibitors in facilitating or hindering hydrate formation is discussed. Furthermore, the review presents an overview of the impact of marine sediments and naturally occurring compounds on CO2 hydrate formation, along with the sampling methodologies used in sediments to determine the composition of these natural compounds. Special attention is given to the effect and chemical characterization of dissolved organic matter (DOM) in marine aquatic environments. The focus is placed on the key roles of various natural occurring molecules, such as amino acids, protein derivatives, and humic substances, along with the analytical techniques employed for their chemical characterization, highlighting their central importance in the CO2 gas hydrates formation.

Sepsis is a life-threatening clinical syndrome, and renal impairment associated with sepsis significantly increases patient mortality. Blood purification techniques are crucial in managing sepsis by removing inflammatory mediators and toxic substances from the bloodstream, thereby improving outcomes. Traditional modalities, including continuous renal replacement therapy, hemodialysis, and hemoperfusion, have demonstrated clinical efficacy in this context. Recent advancements in blood purification filters have enhanced sepsis treatment strategies. This review assesses the mechanisms and clinical applications of novel filters such as the oXiris filter, AN69ST membrane, CytoSorb, Hemopurifier, and others, focusing on their effectiveness in eliminating toxins and inflammatory mediators. The oXiris filter has demonstrated superior capacity to remove small molecular toxins, pro-inflammatory cytokines, and endotoxins while promoting renal protection and enhancing microcirculation. In contrast, the AN69ST membrane and CytoSorb filters have shown promising efficacy in cytokine clearance, though their ability to remove endotoxins is limited. The Hemopurifier specifically targets endotoxins like lipopolysaccharides, effectively suppressing inflammatory responses and mitigating renal damage. Furthermore, the integration of Extracorporeal Carbon Dioxide Removal (ECCO2R) with continuous renal replacement therapy (CRRT) offers benefits, including the regulation of carbon dioxide levels, maintenance of acid-base balance, and enhanced clearance of inflammatory factors from circulation. Additionally, selective removal of lipopolysaccharides (LPS) can alleviate leukopenia and immune dysregulation, preserving renal function. This review aims to provide clinical guidance for optimizing individualized treatment protocols to enhance survival rates and improve the quality of life for patients with sepsis-related AKI. Incorporating these advanced filtration technologies into routine clinical practice can transform sepsis management and pave the way for innovative therapeutic strategies in critical care.

Harnessing the biomolecular mechanisms of marine biomineralisation for carbon sequestration.

Deep learning-based colorimetric indicator on polylactic acid packaging for nondestructive monitoring of fresh-cut fruits and vegetables.