Variations In Characteristics Research Articles

Exploration of Risk Factors for Cardiovascular Disease in Patients with Rheumatoid Arthritis: A Retrospective Study.

Patients with rheumatoid arthritis (RA) have increased mortality and morbidity rates owing to cardiovascular diseases (CVD). Timely detection of CVD in RA can greatly improve patient prognosis; however, this technique remains challenging. We aimed to investigate the risk factors for CVD incidence in patients with RA. This retrospective study included RA patients without CVD risk factors (n = 402), RA with CVD risk factors (n = 394), and RA with CVD (n = 201). Their data on routine examination indicators, vascular endothelial growth factor (VEGF), and immune cells were obtained from medical records. The characteristic variables between each group were screened using univariate analysis, least absolute shrinkage and selection operator (LASSO), random forest (RF), and logistic regression (LR) models, and individualized nomograms were further established to more conveniently observe the likelihood of CVD in RA. Univariate analysis revealed significantly elevated levels of white blood cells (WBC), blood urea nitrogen (BUN), creatinine, creatine kinase (CK), lactate dehydrogenase (LDH), VEGF, serum total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), apolipoprotein B100 (ApoB100), and apolipoprotein E (ApoE) in RA patients with CVD, whereas apolipoprotein A1 (ApoA1) and high-density lipoprotein/cholesterol (HDL/TC) were decreased. Furthermore, the ratio of regulatory T (Treg) cells exhibiting excellent separation performance in RA patients with CVD was significantly lower than that in other groups, whereas the ratios of Th1/Th2/NK and Treg cells were significantly elevated. The LASSO, RF, and LR models were also used to identify the risk factors for CVD in patients with RA. Through the final selected indicators screened using the three machine learning models and univariate analysis, a convenient nomogram was established to observe the likelihood of CVD in patients with RA. Serum lipids, lipoproteins, and reduction of Treg cells have been identified as risk factors for CVD in patients with RA. Three nomograms combining various risk factors were constructed to predict CVD occurring in patients with RA (RA with/without CVD risk factors).

The Effect of Lower Limb Combined Neuromuscular Electrical Stimulation on Skeletal Muscle Cross-Sectional Area and Inflammatory Signaling.

In individuals with a spinal cord injury (SCI), rapid skeletal muscle atrophy and metabolic dysfunction pose profound rehabilitation challenges, often resulting in substantial loss of muscle mass and function. This study evaluates the effect of combined neuromuscular electrical stimulation (Comb-NMES) on skeletal muscle cross-sectional area (CSA) and inflammatory signaling within the acute phase of SCI. We applied a novel Comb-NMES regimen, integrating both high-frequency resistance and low-frequency aerobic protocols on the vastus lateralis muscle, to participants early post-SCI. Muscle biopsies were analyzed for CSA and inflammatory markers pre- and post-intervention. The results suggest a potential preservation of muscle CSA in the Comb-NMES group compared to a control group. Inflammatory signaling proteins such as TLR4 and Atrogin-1 were downregulated, whereas markers associated with muscle repair and growth were modulated beneficially in the Comb-NMES group. The study's findings suggest that early application of Comb-NMES post-SCI may attenuate inflammatory pathways linked to muscle atrophy and promote muscle repair. However, the small sample size and variability in injury characteristics emphasize the need for further research to corroborate these results across a more diverse and extensive SCI population.

Numerical simulation study of an Enhanced Geothermal System with a five-spot pattern horizontal well based on thermal-fluid-solid coupling

Abandoned oil wells can potentially have negative impacts on the environment and climate change. Repurposing these wells into geothermal systems for developing geothermal resources holds vast development prospects. This study utilized COMSOL software to establish a numerical model of an Enhanced Geothermal System based on thermal-flow-solid coupling, investigating the effects of fracture connectivity, different injection-production schemes, and parameters on heat extraction efficiency. Results indicate that a partial-bridge fracture Enhanced Geothermal System scheme outperforms a full-bridge scheme, with the optimal injection-production configuration being four injection wells and one central production well. Specific parameters, such as a 40 m fracture spacing, showed the best performance, where high flow rates enhance thermal power while low flow rates maintain high outlet temperatures. Inlet temperature has limited impact initially, whereas high geothermal gradients and larger well spacings favor geothermal extraction. During production, outlet temperature sensitivity to flow rate and geothermal gradient is evident, while in later stages sensitivity shifts to inlet temperature and well spacing. Despite complex variations in the multi-physical characteristics of the thermal reservoir, the study identifies consistent patterns and underlying principles. This research provides a scientific basis and practical guidance for optimizing the operation of multi-well Enhanced Geothermal System.

Multi-Source Remote Sensing Data for Wetland Information Extraction: A Case Study of the Nanweng River National Wetland Reserve

Wetlands play a vital role in regulating the global carbon cycle, providing biodiversity, and reducing flood risks. These functions maintain ecological balance and ensure human well-being. Timely, accurate monitoring of wetlands is essential, not only for conservation efforts, but also for achieving Sustainable Development Goals (SDGs). In this study, we combined Sentinel-1/2 images, terrain data, and field observation data collected in 2020 to better understand wetland distribution. A total of 22 feature variables were extracted from multi-source data, including spectral bands, spectral indices (especially red edge indices), terrain features, and radar features. To avoid high correlations between variables and reduce data redundancy, we selected a subset of features based on recursive feature elimination (RFE) and Pearson correlation analysis methods. We adopted the random forest (RF) method to construct six wetland delineation schemes and incorporated multiple types of characteristic variables. These variables were based on remote sensing image pixels and objects. Combining red-edge features, terrain data, and radar data significantly improved the accuracy of land cover information extracted in low-mountain and hilly areas. Moreover, the accuracy of object-oriented schemes surpassed that of pixel-level methods when applied to wetland classification. Among the three pixel-based schemes, the addition of terrain and radar data increased the overall classification accuracy by 7.26%. In the object-based schemes, the inclusion of radar and terrain data improved classification accuracy by 4.34%. The object-based classification method achieved the best results for swamps, water bodies, and built-up land, with relative accuracies of 96.00%, 90.91%, and 96.67%, respectively. Even higher accuracies were observed in the pixel-based schemes for marshes, forests, and bare land, with relative accuracies of 98.67%, 97.53%, and 80.00%, respectively. This study’s methodology can provide valuable reference information for wetland data extraction research and can be applied to a wide range of future research studies.

Enhancing weathered slope stability assessment through the integration of slake durability index, elastic modulus of knocking ball, and electrical resistivity tomography.

This research assesses the stability of sedimentary rock slopes in Teloi, Sik, Kedah, by focusing on the mechanical properties of the rock layers and their susceptibility to weathering. Key tests include the slake durability index (SDI), elastic modulus of knocking ball (Ekb), and electrical resistivity tomography (ERT). The incorporation of electrical resistivity tomography (ERT) data through the virtual reality platform facilitates the visualization of subsurface conditions. The variability of strength characteristic of interbedded sedimentary rocks leads to the differential weathering of rock layers, which causes deterioration on the slope structure. The testing revealed significant variability in rock strength, with sandstone displaying higher durability (Id > 17.1%) and elasticity (Ekb: 0.97 to 29.31 GPa) compared to shale and siltstone, which exhibited lower durability and elasticity (Id < 2.2%, Ekb: 0.2 to 2.2 GPa). Utilizing the Wenner array setup, three distinct electrical resistivity lines were established to evaluate subsurface anomalies. The ERT profiles revealed variations in electrical resistivity among different rock types, identifying areas of weaker material, which are siltstone and shale, while high resistivity areas indicate sandstone. Kinematic analysis through the stereonet process revealed direct toppling as the primary failure mechanism, driven by the critical orientations of joint sets J1, J2, and J3. This aligns with on-site observations of hanging sandstone blocks prone to toppling failure. The findings of this research show that the slake durability index (SDI) and the elastic modulus of the knocking ball (Ekb) enhance the assessment of mechanical properties and weathering resistance of interbedded sedimentary rocks. The virtual reality platform was particularly helpful in analyzing and visualizing the sub-surface conditions and enhancing the evaluation of complex geological data. As a conclusion, this integrated method was helpful in the comprehensive geotechnical evaluation of the slopes, enabling the selection of effective stabilization measures by assessing the differential weathering of interbedded sedimentary rock and identifying potential failure zones.

Drying out fish ponds, for an entire growth season, as an agroecological practice: maintaining primary producers for fish production and biodiversity conservation.

Agroecology largely focusses on terrestrial agroecosystems, but it can also be applied to fish farming. Indeed, ponds are typically used for fish production in Europe, but are also important reservoirs of biodiversity. Numerous studies demonstrate that both fish production and biodiversity are strongly determined by human management. One key practice in extensive fish farming, although more rare in Europe, is to dry out ponds. They are left dry for a complete year after several years of fish production. However, the extent to which this practice affects the functioning of the ecosystem, its biodiversity and fish production remain unclear. We investigated data from 85 fish ponds in the Dombes region, France, sampled between 2007 and 2014. We related variation in key abiotic characteristics to the time since last dry out. The dataset included organic matter content in pond sediments and concentrations of inorganic nitrogen and phosphorus in the water column, and biotic components such as macrophytes cover and richness, phytoplankton concentration and richness, macroinvertebrates density, and fish yield. Our results show that drying out facilitates the mineralization of organic matter in sediments and results in higher concentrations of inorganic nitrogen in the water column. Macrophytes cover is highest during the first year after drying out, and gradually declines after at the expense of increasing phytoplankton concentration. The diversity of both is highest in the first year after drying out and declines rapidly, especially for macrophytes. Fish yield is at its maximum in the second year. Drying out fish ponds appears to be an important agroecological practice in extensive fish farming with an application every three to four years. By nutrient recycling, this practice has a positive impact on the balance between primary producers and indirectly on the whole food web during two years. It optimizes fish production and allows biodiversity conservation.

Experimental Investigation and Statistical Analysis of Recycled Asphalt Pavement Mixtures Incorporating Nanomaterials

Reclaimed Asphalt Pavement (RAP) materials are used as substitutes for new materials in asphalt pavement construction, leveraging the engineering and commercial benefits of the aged binders and aggregate matrixes in RAP. These asphalt mixtures impart significant variations in volumetric properties and asphalt mixture characteristics. The current study investigates the Marshall properties, moisture susceptibility, and rutting behavior of 24 recycled asphalt mixtures developed with nanosilica and nanoclay. RAP material percent, nanomaterial content, binder grade, and extra binder were considered the factors influencing asphalt mixture performance. The above factors were analyzed using the Response Surface Methodology (RSM) to predict the Marshall and volumetric properties. Also, this investigation covers the moisture susceptibility and rut characteristics of recycled nanomaterial-modified Hot Mix Asphalt (HMA) and Warm Mix Asphalt (WMA) mixes developed with Viscosity Grade 30 (VG-30) and Polymer-Modified Bitumen-40 (PMB-40). The chemical additive Zycotherm was used to develop WMA mixes. The test results indicate that adding RAP material at higher percentages and modifying the binder with nanomaterials affected moisture susceptibility with reduced moisture damage. Recycled nanosilica-modified HMA mixes developed with PMB-40 at higher RAP percentages reported higher tensile strength ratio (TSR) values in contrast with VG-30 mixes, indicating their greater susceptibility toward moisture-induced damage. The rutting potential of all of the recycled asphalt mixture combinations was enhanced by densely packed aggregate structures optimized with nanomaterials, total binder content, and RAP materials developed using the Marshall method. Overall, the nanosilica-modified recycled asphalt mixes developed with PMB40 at higher RAP percentages showed better performance in terms of strength and durability.

DBAII-Net with multiscale feature aggregation and cross-modal attention for enhancing infant brain injury classification in MRI.

MRI is pivotal in diagnosing brain injuries in infants. However, the dynamic development of the brain introduces variability in infant MRI characteristics, posing challenges for MRI-based classification in this population. Furthermore, manual data selection in large-scale studies is labor-intensive, and existing algorithms often underperform with thick-slice MRI data. To enhance research efficiency and classification accuracy in large datasets, we propose an advanced classification model. We introduce the Dual-Branch Attention Information Interactive Neural Network (DBAII-Net), a cutting-edge model inspired by radiologists' use of multiple MRI sequences. DBAII-Net features two innovative modules: (1) the Convolutional Enhancement Module (CEM), which leverages advanced convolutional techniques to aggregate multi-scale features, significantly enhancing information representation; and (2) the Cross-Modal Attention Module (CMAM), which employs state-of-the-art attention mechanisms to fuse data across branches, dramatically improving positional and channel feature extraction. Performances (accuracy, sensitivity, specificity, area under the curve, etc.) of DBAII-Net were compared with eight benchmark models for brain MRI classification in infants aged 6 months to 2 years. Utilizing a self-constructed dataset of 240 thick-slice brain MRI scans (122 with brain injuries, 118 without), DBAII-Net demonstrated superior performance. On a test set of approximately 50 cases, DBAII-Net achieved average performance metrics of 92.53% accuracy, 90.20% sensitivity, 94.93% specificity, and an area under the curve (AUC) of 0.9603. Ablation studies confirmed the effectiveness of CEM and CMAM, with CMAM significantly boosting classification metrics. DBAII-Net with CEM and CMAM outperforms existing benchmarks in enhancing the precision of brain MRI classification in infants, significantly reducing manual effort in infant brain research. Our code is available at https://github.com/jiazhen4585/DBAII-Net.

Emergency cerclage: Neonatal outcomes and evaluation of prognostic scores − A decade of experience at a tertiary center

ObjectivesEmergency cervical cerclage is a high-risk surgical procedure associated with maternal and fetal risks, including preterm birth. Authors have developed scores to try to predict the probability of success following emergency cerclage, but these tools have yet to be externally validated.Our main objective was to assess the preterm birth rate before 32 weeks following emergency cerclage. Secondary objectives included assessing perinatal outcomes and the predictive validity of two published scores in our setting. We hypothesized that predictive scores, such as Fuchs and Kokia scores, may not perform optimally in our population due to variability in clinical and biological characteristics that influence eligibility for cerclage across different settings. Study designWe conducted a retrospective, monocentric study in a tertiary maternity hospital. All patients who underwent emergency cerclage between January 1st, 2010, and December 31st, 2021, were included. The main outcome was preterm birth rate before 32 weeks. Secondary outcomes were need for maternal hospitalization after initial hospitalization for cerclage, preterm premature rupture of membrane, and perinatal death. The rate of preterm birth before 32 weeks and adverse perinatal outcomes were estimated. To assess the predictive validity of Fuchs’ score in our population, we performed a multivariable logistic regression model including the score’s variables and constructed receiver operating characteristic (ROC) curve. To assess the validity of Kokia’s score in our population, we studied the correlation between the initial score and gestational age at delivery using Pearson’s correlation coefficient. ResultsOur population was composed of 64 women who underwent an emergency cerclage. The median gestational age at delivery was 30.6 weeks (IQR (24.2; 37.6)). The preterm birth rate before 32 weeks was 54.7 %. The rate of perinatal death was 30.7 %. There were no statistical differences between the patients delivered before and after 32 weeks. The multivariable logistic regression model showed that none of the variables of Fuchs’s score were significantly associated with preterm birth risk in our population. The AUC of the ROC curve using Fuchs’ score was 0.63. There was a minor yet significant correlation between Kokia’s score and gestational age at delivery (r = 0.26 – p = 0.04). ConclusionsOur study underscores the persistent risks associated with cervical insufficiency, including very preterm birth. It highlights the variability in performance of predictive scores across different populations, underscoring the need for external validation in diverse clinical settings.

Large deformation of variable thickness woven composite preforms considering interlayer difference. Application: Forming simulation of a blade preform

The main objective of this work was to investigate the interlayer difference of 3D orthogonal woven fabrics (3DOWFs) during deformation. Tensile, shear, and compression tests were performed on two types of 3DOWFs with different layer numbers. To determine the variations in the deformation behavior within the fabric, a layer decomposition method was developed. This process involved the decomposition of the fabric into two layers, the inner layer and the outer layer, depending on the difference in structural features of the yarn. Then the deformation characteristics of the inner layer and outer layer were derived based on their series or parallel relationship in the load path. The results indicate that there are noticeable variations in the deformation characteristics among the layers of 3DOWF, which are associated with the interwoven structure of the yarns. In particular, in compression deformation, the difference in yarn structure causes the initial stage (Compressive strain &lt;0.2) of fabric compression deformation to be mostly attributed to the compression of the outer layer. Subsequently, the deformations of the inner layer and outer layer gradually tend to balance. Based on a simple anisotropic hyperelasticity model, the interlayer differences were considered in the blade preform simulation. The simulation result shows a good agreement with the preforming results. The results show that the interlayer difference has a significant impact on the deformation of the blade preform, particularly in the posterior edge region, which is not strongly compressed.

Hepatocellular Carcinoma Situation in Indonesia: A Systematic Review of Clinical Staging and Histological Characteristics at the Time of Diagnosis

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide. However, systematic data on HCC characteristics in Indonesia are limited. Objective: To summarize the body of literature on the characteristics of HCC in Indonesia. Methods: A comprehensive search was conducted in MEDLINE, ScienceDirect, Scopus, Web of Science, and Google Scholar databases without date restrictions. Clinical studies investigating the characteristics of HCC exclusively in Indonesia were eligible for inclusion. Risk-of-bias assessments were conducted, and results were presented descriptively. Results: Ten studies comprising 1,389 HCC patients were included. The Barcelona Clinic Liver Cancer (BCLC) staging system, reported in 5 studies, revealed a predominance of intermediate to advanced stages (B and C) at diagnosis. Child-Pugh scores, available for 7 studies, indicated variability in liver function, with Child-Pugh A ranging from 12.0% to 85.7%. Hepatitis B virus (HBV) infection was the primary etiological factor, with prevalence ranging from 53.8% to 84.0%. Hepatitis C virus (HCV) infection was less common (1.0% to 25.21%). Non-viral etiologies represented a substantial proportion, reaching up to 37.4% of cases. The mean age at diagnosis ranged from 52.43 to 63.1 years. Conclusion: This review highlights the late-stage presentation of HCC in Indonesia, the predominance of HBV as an etiological factor, and a significant burden of non-viral HCC. The findings underscore the need for improved early detection strategies, strengthened HBV prevention efforts, and increased attention to metabolic risk factors. Regional variations in HCC characteristics suggest the need for tailored approaches to HCC management across different parts of Indonesia.

A grey incidence-based algorithm for optimization of accelerated degradation test

PurposeThe purpose of this paper is to optimize the degradation test for products subject to multiple types of inherent stresses and external random shocks. The mechanism that shows how the variables to be optimized influence the considered multiple objectives is also aimed to be explored by using the grey incidence analysis (GIA) model.Design/methodology/approachThe Gamma process is employed to model the influences of different types of stresses and external random shocks. The GIA model is introduced to transfer multiple considered objectives as a comprehensive degree of grey incidence. The particle swarm optimization is integrated to search the globally optimal value of the characteristic variables to be optimized.FindingsThe acceleration of tested stresses and external random shocks both make the engineering systems become more vulnerable to the inherent degradation. And, the Kriging model can provide guidance of searching the optimal values of test characteristic variables and mitigate the computation burden. The grey incidence model can make the optimization focused and improve the optimality of objective values.Originality/valueThe proposed method can effectively overcome the drawbacks brought by the limitation of test data and can specify the dependence strength between the inherent degradation and external random shock. The computation cost and accuracy of optimization can be simultaneously ensured by the proposed model.

Variability of inherent optical properties of seawater in relation to the concentration and composition of suspended particulate matter in the coastal Arctic waters of western Spitsbergen

Inherent optical properties (IOPs) and characteristics of suspended particles in surface seawater samples were measured in summer months of 2021 and 2022 in Arctic fjords and coastal waters of western Spitsbergen in the Svalbard archipelago. The measured IOPs included the spectral backscattering and scattering coefficients of suspended particulate matter, as well as the spectral absorption coefficients of suspended particulate matter and its non-algal particulate and phytoplankton components. The particulate assemblages were characterized by measuring the mass concentrations of suspended particulate matter (SPM), particulate organic matter (POM), particulate inorganic matter (PIM), and phytoplankton pigments including chlorophyll-a (Chla). The investigated coastal waters exhibit high variability of particulate characteristics and associated IOPs. We observed more than two orders of magnitude variation in SPM and particulate IOPs, and Chla varied from below the detection limit to more than 3 mg m−3. The contribution of organic fraction to SPM (POM/SPM ratio) varied from 0.05 to 0.6, and the Chla/SPM ratio spanned more than three orders of magnitude with a maximum value of the order of 10−3. As a result, the mass-specific optical coefficients, especially the mass-specific backscattering and scattering coefficients of particles and mass-specific absorption coefficient of non-algal particulate matter, exhibit large variations. In addition, our study demonstrates the influences of changes in composition of suspended particulate matter parameterized in terms of POM/SPM and Chla/SPM ratios on IOPs. Various variants of spectral parametrizations of optical coefficients in terms of univariate or multivariable relationships with particulate characteristics are provided. These parameterizations are representative of the investigated coastal Arctic waters in Svalbard region and can be used for better interpretation of optical measurements, both in-situ and remote, in this Arctic environment.

Effect of tooth surface pitting on dynamic characteristics under mixed lubrication

The variation of tooth meshing stiffness and frictional characteristics caused by tooth surface pitting increases vibration and noise in the gear transmission system. Assuming a smooth tooth surface and a homogeneous material in studying the gear contact and dynamics is insufficient to reveal the evolution of dynamic contact performance caused by pitting faults. In the present study, we established a coupling analysis model for pitting faults to assess the effect of the tooth surface micro-morphology. The mesh stiffness and static transmission error of gears with randomly distributed pittings were calculated, and the vibration response of gears with different pitting degrees was resolved. Finally, the effectiveness of the applied dynamic response theory analysis was experimentally verified using the constructed pitting fault simulation test bench. The results indicate that pitting failure decreases the effective load-bearing capacity of gear teeth. The mesh stiffness gradually but significantly decreased with the pitting degree, also exhibiting fluctuating values. Pitting faults induced significant periodic features in the vibration response of gear transmission systems, showing complex sidebands around the meshing frequency and its harmonics.

Morphological and geological responses of barrier estuaries to dam-opening systems

River discharge depending on the dam gate operation method is an important factor underlying changes in estuarine sedimentation dynamics, but comprehensive studies are limited by data collection constraints. The hydrological operation of Nakdong Dam, designed to prevent seawater intrusion by opening during ebb tides and heavy rains and closing during flood tides, presents an ideal setting for such investigations. This study focused on the Nakdong River Estuary (NRE), utilizing aerial photography, bathymetry data, and sedimentation rate data to determine alterations in sediment transport and deposition patterns within the two tributary estuaries. Spatial discrepancies in sedimentation patterns across the eastern and western regions of the NRE were particularly evident in the spatial variations of textural characteristics and sedimentation rates. An enhanced ebb tidal prism resulting from dam gate opening in the eastern region caused the development of erosional topography and a rough depositional environment, forming a landward migrating (transgressive) barrier island system. Conversely, the predominantly closed dam gates in the western region maintained a consistent deposition pattern due to a regular tidal prism, facilitating the formation of sedimentary topography and fine sediment deposition. Consequently, barrier islands followed a seaward building (prograding) system. Therefore, the results suggested a role of modern dam gate operation as a major sedimentation mechanism, providing valuable insights for the sustainable management of estuarine sediment environments.

IoT Based Precision Farming

This project focuses on leveraging drone images of the pests equipped with advanced sensors for pest detection in crops, combined with methods for image processing to identify diseases. The ultimate goal is to enhance crop health and productivity through timely and targeted pesticide application. Image processing techniques are used to detect signs of diseases and pests in the captured images. The use of machine learning CNN algorithm enhances the system’s ability to accurately classify and diagnose crop heath issues. Upon detection of pests, the IOT platform triggers a response mechanism to deploy a precision pesticide spraying system. This ensures targeted and localized treatment, reducing the overall use of pesticides and minimizing environmental impact. This project involves capturing images of pests using a camera, followed by processing these images to extract key features using various image processing techniques. The extracted features are analyzed using algorithms, primarily Convolutional Neural Networks (CNNs), to detect variations in color and other dominant characteristics in the images. By comparing these features across samples, the system can identify pests and plant diseases more efficiently. This approach aims to provide a quicker and more cost-effective solution for pest detection and disease management.

A Multiple-physics coupled model for nanoconfined CO2-CH4 mixture transport behavior: Implications for CO2 geological storage in ultra-tight formation

Considerable efforts have been made to examine the feasibility of CO2-enhanced gas recovery (CO2-EGR), a promising approach for improving gas recovery by using CO2 to displace in-situ CH4 in ultra-tight gas reservoirs rich in nanopores. However, most research has focused on either single-component gas flow physics or competitive adsorption of multiple gas components in nanopores. The flow behavior of nanoconfined CO2-CH4 mixtures remains an area of knowledge gap. This work establishes a theoretical framework for CO2-CH4 mixture flow capacity by coupling mixture flow in the bulk region with surface diffusion in the adsorption area. Results indicate that: a) Total mixture flow conductance increases rapidly at pressures below ∼10 MPa, with CO2 contributing over 99 % to surface diffusion conductance; b) Increasing CO2 molar ratio from 0.2 to 0.8 can lead to a 167 % enhancement in total mixture conductance; c) Variations in CO2-CH4 competitive adsorption characteristics have little impact on total conductance.

Why You Gamble Matters: A Systematic Review and Meta-analysis of the Association Between Gambling Motivation and Problem Gambling.

The propensity for individuals to experience problem gambling (PG) varies depending on their motivation to gamble. The present meta-analysis assessed the effect sizes associated with various gambling motives identified in representative population samples. Studies were sourced through PsycINFO, PudMed, and databases maintained by the Alberta Gambling Research Institute and the Greo Evidence Insights. Quantitative studies and technical studies were included if they reported on gambling motivation as a correlate of PG; were published in English, French, or Spanish; used valid and reliable measures PG as an outcome variable; and targeted the general adult population. A random effects meta-analysis was conducted to estimate pooled odds ratios. A total of 26 studies were included from 17 jurisdictions, with most studies conducted in Canadian provinces (k = 17) or specific states of the United States (k = 7). Number of participants varied, depending on the gambling motivation analyzed, and ranged from 2,835 to 51,685. Fourteen unique motives were identified with odds ratios ranging from 0.53 (95% CI, 0.45, 0.63) for gambling for charity to 6.20 (95% CI, 3.83, 10.05) for the motive "to be alone", with high study heterogeneity being observed for many gambling motives, given variability in important study characteristics. The results generally indicate that coping motives were associated with large effect sizes, enhancement motives with medium effect sizes, and all other motives with small or nil effects. Coping motives are on par with other strong risk factors such as participation in online gambling or electronic gaming machines, and are therefore important elements to consider when screening for PG or designing public health messages.

Adherence to Mediterranean diet and asthma control. Results from a small study among asthmatic patients in Greece

Objectives Current variations in asthma prevalence and clinical characteristics suggest that lifestyle choices including dietary habits, may affect the pathogenesis and/or clinical expression of the disease. The purpose of this study is to evaluate the association between adherence to Mediterranean diet (MD) and asthma control, considering disease severity. Methods Adherence to MD was assessed through a questionnaire, the MD Adherence Screener (MEDAS), previously validated in Mediterranean populations. Each participant received a score ranging from 0 to 14. A score higher than 10 indicates high MD adherence. The level of asthma control was assessed by the Asthma Control Test and two groups were formed (controlled vs. partly controlled/uncontrolled). Results The study sample included 105 participants (34% males). About 45% of participants were severe asthmatics. Adherence to MD was associated with 14% higher, though not statistically significant, probability of controlled asthma in the overall study sample (OR = 1.14; 95% CI = 0.46–2.81) and 60% higher probability of controlled asthma among severe asthmatics (OR = 1.60, 95% CI = 0.46–5.59). Conclusions These results indicate a possible association between adherence to MD and asthma control, but findings are restricted by the study’s small sample size which does not allow asserting the inference.

New prefilled syringe aflibercept design. A cause of symptomatic IOP spike after aflibercept PFS?

To describe ocular hypertension cases after using a new aflibercept prefilled syringe and to assess the main characteristics of these eyes and their possible association with intraocular pressure (IOP) changes. Case series. We reported all the cases of ocular hypertension following aflibercept prefilled syringes (PFS) treatment in our department between April 2021 and December 2023. A total of 4183 eyes were treated with aflibercept PSF. Thirteen transitory IOP elevations were observed immediately after injection (0.3%). Two eyes had an IOP between 30-35 mmHg, five eyes had an IOP between 36-55 mmHg and three eyes had an IOP > 56 mmHg. The mean IOP was 45.5 mmHg±11.33. Only six eyes needed anterior chamber paracentesis (37.5%). The other patients were treated conservatively (ocular massage and/or IOP-lowering drops). The mean IOP after treatment was 15.71 mmHg±7.20. Visual acuity improved after treatment in all the patients. Compared with other injectors, reports have indicated a higher incidence of moderate and severe IOP spikes with aflibercept PSF. The European Medicine Agency (EMA) has associated this significant increase with incorrect syringe handling, leading to higher injection volumes. Although plunger misalignment seems to play a role in the IOP spikes, some other characteristics of this new injector could play a role. Factors such as syringe diameter, plunger alignment, and injection force may contribute to this issue. The reason some authors found no significant differences in IOP elevation after IVI, with aflibercept PFS, could be due to variations in patient characteristics, which may also play an important role in post-IVI pressure changes. Intraocular pressure spikes after aflibercept PFS can be explained by injector characteristics. The PFS of aflibercept has a domed plunger. Incorrect alignment between the base of the plunger and the black dosing line could cause an increase in the injected volume. Furthermore, the wider syringe diameter of aflibercept PFS could imply a larger injection force, increasing the risk of IOP elevation. Patient characteristics, such as previous VPP, axial length, or glaucoma history, may also play a role. Further studies are required to develop an ideal intravitreal syringe.