bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring Injectivity for CO2 Injection in Depleted Gas Reservoirs
Authors: de Kok J. 
Published: June 2024

Abstract
Determining the injectivity of CO2 injection wells in depleted gas reservoirs is important, because injectivity directly impacts the operating envelope of the injector. Injectivity evolves over time due to changing fluid properties, but it can also change by processes like hydrate formation or fracturing (summarized in the skin parameter). This paper investigates how accurate injectivity monitoring is, based on coupled well-reservoir simulation and identifies threshold values for identifying injectivity loss or gain.
The relation between bottomhole pressure (BHP) and rate is a function of several reservoir properties and fluid properties, each carrying its own uncertainty. This paper quantifies the impact of these uncertainties on injectivity for CO2 injection into depleted gas reservoirs using a coupled wellbore and reservoir simulator. The analysis is performed for three scenarios with varying pipeline conditions and reservoir properties, representative for CCS projects in the Netherlands. The resulting BHP uncertainty is translated to equivalent skin values. This is the threshold value above or below which the observed bottomhole pressure data conclusively suggests injectivity gain or loss.
A good estimate of the fluid properties is important to accurately determine injectivity (changes). Although the uncertainty in density is small when using the appropriate Equation of State (like Span & Wagner for pure CO2), the deviation when using a standard Equation of State (like Peng-Robinson) is significant.
The parameter having the largest impact is reservoir pressure for high injectivity reservoirs and relative permeability for low injectivity reservoirs. The combined effect of all parameters (with the exception of reservoir pressure) is equivalent to a skin value of approximately 3 for the selected cases. Without reducing the uncertainty, it is not possible to distinguish between uncertainty in injectivity and actual wellbore damage of that magnitude.
There are ways to decrease the uncertainty in both estimated average reservoir pressure and fluid properties, like the collection of bottomhole temperature data. Shut-in pressure data will further reduce the average reservoir pressure estimate. However, the presence of skin will be difficult to assess from pressure transient data due to wellbore storage and near-wellbore cooling. Rate dependent skin can be assessed when there is rate variation. Permeability and relative permeability changes in the near-wellbore will be difficult to distinguish from wellbore damage. History matching the observed data by a coupled wellbore-reservoir simulator will further decrease the uncertainties.
Monitoring tools for CO2 injection in depleted reservoirs are yet to be developed. This paper improves the understanding of the uncertainties related to injectivity monitoring, which haven’t been quantified so far. Also, the value of a coupled wellbore and reservoir simulator is demonstrated in this paper.
Coupled Flow and Wellbore-Integrity Geomechanical Effects During Continuous and Cyclic CO2 Injection
Authors: Lee G. , Barreto Y. , Amro M. , Nassan T. , Alkan H. , Solbakken J. , Zamani N. , Burachok O. 
Published: June 2024

Abstract
The sealing potential of the caprock, wellbore and storage formation integrity, are critical elements to ensure CO2 containment and the success of carbon capture storage (CCS) projects. Injection of CO2 for geological storage, results in cooling and increase of pore pressure leading to mechanical deformation in the wellbore cement, reservoir and caprock, which over time can cause leakage due to potential rock failure and irreversible damage. The CO2 chemical interaction with the rock and cement may also lead to mechanical alteration. Coupling thermodynamics, and fluid flow with deviated stress conditions is important for understanding and predicting the geomechanical behaviour of the wellbore, reservoir and caprock formations. This complex interaction was studied with GEM simulator from CMG using dedicated 3D and 2D reservoir models. The study was performed in multiple steps. First, laboratory experiments on the impact of pressure-temperature cyclicity on well integrity were simulated. Results indicated validity of the modelling concept and allowed proper design and constrains of the reservoir scale model for the second step of the study. Due to computational complexity, simulation of geochemical reactions was excluded. The impact of CO2 injection on the geomechanical properties of the cement and rock was approximated by tabulated dependency of Young’s modulus and cohesion against CO2 saturation.
Overall, the results showed that the main failure type in the near-wellbore region is probably tensile, accounted by the tensile safety factor (TSF), extending laterally up to 20 m in the reservoir rock and 1 m in the caprock. The cement also experiences tensile failure up to 3 m in the vertical direction, and above that the TSF tends to increase steadily, posing no risk to wellbore integrity. Shear failure is not expected.
The Impact of Isoinertial Eccentric Strength Training on Knee Related Quality of Life and Function: An Experimental Trial in Post-acl Reconstruction Patients
Authors: Patra Ramesh Chandra , Gupta Som , Mahajan Sanjeev 
Published: June 2024

Abstract

Background: Patients undergoing ACL reconstruction often experience challenges such as limited range of motion caused by swelling and stiffness post-surgery, along with muscle weakness, often leads to poorer functional outcomes scores and decreased activity levels.Previous researches indicated that flywheel resistance training can enhance eccentric muscle loading and strength. However, there is limited study on isoinertial eccentric strength training with conventional rehabilitation affects knee-related quality of life and function in patients who have undergone ACL reconstruction surgery. Thus, the purpose of this study is to investigate the effect of isoinertial eccentric strength training protocol along with conventional rehabilitation protocol and conventional rehabilitation protocol only on knee related quality of life in postoperative patients who underwent ACL reconstruction surgery.Methodology:A total of 96 out of 136 screened patients aged 18-45 years, 3 weeks postop patients were included as per selection criteria and randomly divided into groups. Group A consisted of 47 patients (n=47) which were administered Isoinertial Eccentric Strength Training with Conventional Rehabilitation Protocol whereas 49 patients in group B(n=49) received conventional rehabilitation protocol only over 6 weeks. The patients were assessed for knee related quality of life using Knee injury and Osteoarthritis Outcome Score (KOOS), and knee related function using Cincinnati knee rating System (CKRS) respectively before and after the 6 weeks of interventions.Results: The study demonstrated statistically significant improvements in the score of KOOS and CKRS in both the groups A and B (p < 0.05).However, the comparison between the two groups showed no statistical significance in the difference in improvement of mean values of KOOS and CKRS (p > 0.05).Conclusion: In conclusion, this study investigated the effectiveness of Isoinertial Eccentric Strength Training with Conventional Rehabilitation Protocolcompared to Conventional Rehabilitation Protocol alone for improving knee-related quality of life and function over a six-week period. While both protocols demonstrated effectiveness, neither proved superior to the other.
Right patient to the right place: The impact of a 6-year regional trauma centre-led prehospital education program on EMS triage and patient outcomes
Authors: Choi Donghwan , Huh Yo , Kang Byung Hee , Kim Sora , Song Seoyoung , Jung Kyoungwon , Jung Hohyung 
Published: June 2024

Abstract

Background
In regional trauma systems, emergency medical service (EMS) providers play a crucial role by performing prehospital triage for severely injured patients and transporting them to regional trauma centres. Since 2016, a regional trauma centre has provided prehospital medical guidance to EMS providers through a trauma hotline, facilitated by trauma surgeon, to guide field triage, treatment, and transport. This study analysed the effects and clinical outcomes of a regional trauma centre-led performance improvement program that followed closed-loop principles for EMS providers.
Methods
Data from the regional trauma centre databases (2016–2021) were collected, and patients with trauma with Injury Severity Scores (ISSs) > 15 in the Gyeonggi Province who were injured, regardless of whether they visited the trauma centre directly or not, were included. After severity and baseline demographic adjustments through propensity score matching, clinical outcomes were analysed using the t-test and chi-squared test, and the results were expressed as medians with interquartile ranges (IQRs) or means with standard deviations (SDs).
Results
We included 3017 patients from the 6-year study period. Correct triage and undertriage were performed in 2528 and 489 patients, respectively. Prehospital medical guidance and feedback were provided 432 times (32.1%) in 2016 and increased to 1505 times (96.8%) in 2021 (p < 0.001). The undertriage rate decreased from 32.7% (n = 55/168) to 6.3% (n = 52/820) (p < 0.001), and the overall mortality decreased from 21.4–10% (p < 0.001). After propensity score matching, 484 correctly triaged and 484 undertriaged patients were identified for subgroup analyses. The in-hospital mortality of undertriaged and correctly triaged patients was 20% (n = 99) and 13% (n = 61) (p = 0.001), respectively. The median (IQR) for undertriaged over correctly-triaged patients regarding hospital length of stay (LOS) and ICU day ratio was 17 (8–37) vs 19 (12–36) (p = 0.024) and 0.4 (0.2-1.0) vs 0.3 (0.2–0.6) (p = 0.059), respectively.
Conclusion
Undertriage was associated with increased in-hospital mortality and hospital LOS. There was a statistically significant difference between the increase in prehospital medical guidance and the decreased undertriage rate. Specifically, in the early stages of regional trauma-system development, the trauma center-led trauma hotline feedback and case-based education programs can be effective models to facilitate prehospital patient triage and patient centralisation.
Association of circulating inflammatory proteins with Nonalcoholic Fatty Liver Diseas: a bidirectional Mendelian randomization study
Authors: Jia Ming-Jie , Chen Long , Li Hui-Lin 
Published: June 2024

Abstract

Objective: Investigating the causal relationship between non-alcoholic fatty liver disease (NAFLD) and inflammatory proteins and identifying and quantifying the role of serum metabolites as a potential mediator.
Methods: Using summary-level data from a genome-wide association study (GWAS), a two-sample Mendelian randomization (MR) analysis of genetically predicted Nonalcoholic Fatty Liver Disease and inflammatory proteins (14,824 participants of primarily European descent) was performed. Then we did a MR analysis of inflammatory factors with non-alcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma.
Results: The IVW method analysis showed that CCL20 (P-value=0.023, OR=0.783, 95% CI=0.644-0.968), IL-1α(P-value=0.039, OR=0.790, 95% CI=0.632-0.988) were protective factors for NAFLD, while TNFRSF9 (P-value<0.001, OR=1.353, 95% CI=1.148-1.594) was a risk factor. IL-10Rα(P-value=0.004, OR=3.274, 95% CI=1.463-7.027), NT-3 (P-value=0.040, OR=2.413, 95% CI=1.040-5.601), SLAM (P-value=0.009, OR=2.183, 95% CI=1.216-3.918) were identified as risk factors for NASH. LIFR (P-value<0.001, OR=0.704, 95% CI=0.595-0.832) was identified as a protective factor for cirrhosis. IL-1α (P-value=0.002, OR=2.274, 95% CI=1.369-3.778) was identified as a risk factor for HCC.
Conclusion:In conclusion, our study identified a causal relationship between inflammatory proteins and Nonalcoholic Fatty Liver Disease.
High Throughput Exsolution Design of CO2 Reduction Reaction Interface in a Copper/High-Entropy Oxide Tandem Electrode
Authors: Bowman William , Xuan ShengQuan , Gurusamy Tamilselvi , Wang Xin , Zheng Hui , Guo Huiming , Vahidi Hasti , Dupuy Alexander , Clarke Liela , Schoenung Julie , Ong Shyue Ping , Ren Hang 
Published: June 2024

Abstract

The entropy design paradigm is yielding advanced materials for many societally crucial applications. While most work focuses on single-phase materials, there are vast opportunities to integrate entropy-designed materials into novel composites. Here we develop a nanocomposite design strategy using exsolution-self-assembly to fabricate Cu nanorods in an entropy-stabilized oxide. Atomic-scale electron probes and energetic calculations elucidate how exsolution-self-assembly is tunable using knowledge of point defect interactions. We leverage this to then demonstrate a high-throughput synthesis and screening strategy to fabricate a library of Cu-ESO tandem CO2 reduction reaction (CO2RR) electrodes. Electrocatalytic mapping and localized physicochemical analyses reveal structure-property relationships between local Cu valence and CO2RR activity, identifying operating potentials and electrode surface chemistries that favor CO2RR over competitive hydrogen evolution. This high-throughput synthesis-screening approach can accelerate development of advanced electrocatalysts and nanocomposite materials for many applications given its compatibility with entropy-designed materials and physical vapor deposition at/near silicon volume manufacturing temperatures.
Development and validation of machine-learning-based survival prediction model for young patients with gastric cancer
Authors: Kang Ha Ye Jin , Ko Minsam , Ryu Kwang Sun 
Published: June 2024

Abstract

Background Despite the global decline in the incidence of gastric cancer, the number of young individuals diagnosed with it continues to rise. Several studies have been conducted to predict the mortality of patients with gastric cancer; however, they employ traditional methodologies and have limitations. Therefore, we propose short-, medium-, and long-term mortality prediction models for young patients with gastric cancer based on a survival machine learning model. Methods Data of 1,200 young (< 50 years) patients diagnosed with gastric cancer between 2013–2015 were obtained from the Gastric Cancer Public Staging Database. Data of 840 and 360 patients were used for training and testing, respectively. We employed the random survival forest (RSF), gradient boosting survival analysis (GBSA), and extra survival tree (EST) prediction models for 1-, 3-, and 5-year survival prediction, and the concordance index (C-index) metric to objectively assess the models. This study also examined the key determinants of mortality based on the prediction time points. Results The results indicate that the EST model (1-year mortality: 97.08 ± 0.01, 3-year mortality: 96.19 ± 0.01, 5-year mortality: 93.68 ± 1) exhibited a slightly better performance than the GBSA (1-year mortality: 96.91 ± 0.01, 3-year mortality: 94.91 ± 0.01, 5-year mortality: 93.57 ± 0.01) and RSF (1-year mortality: 96.67 ± 0.01, 3-year mortality: 95.65 ± 0.01, 5-year mortality: 92.82 ± 0.01) models. Tumour stage and size were the primary variables employed for training the models to predict mortality at different time points. The other variables exhibited varying degrees of consistency for each time point. Conclusions The findings are expected to facilitate the identification of high-risk young patients with gastric cancer who may benefit from aggressive treatment by predicting their risk of death at various time points.
A Novel Highly Invasive Cell-Related Gene Signature for Predicting the Prognosis and Treatment of Osteosarcoma
Authors: Li Zijun , Wang Mengting , Wang Yunlong , Yi Chengfeng , Liu Jun , Han Xie , Bian Erbao , Tian Dasheng 
Published: June 2024

Abstract

Osteosarcoma (OS) is a highly prevalent bone tumor derived from primitive mesenchymal cells that occurs mostly in adolescents and children. OS has a notable propensity for aggressive behavior and resistance to treatment. Additionally, accurately evaluating and predicting the prognosis of OS remains challenging. For this investigation, we utilized scRNA-seq data to identify seven subtypes of OS cells. Survival analysis of each OS cell subtype revealed that highly invasive OS (HIS-OS) had a poorer prognosis. Through differential expression analysis, an entire set of seven genes linked to HIS-OS was identified. Subsequently, these seven genes were employed to construct a predictive model using the LASSO approach. Based on the median risk score, the OS samples in the training set were categorized into high-risk and low-risk groups, and the high-risk group exhibited a significantly shorter survival time. The analysis of immunotherapy and anticancer treatment responsiveness indicated a negative correlation between HIS-OS-related gene signatures and immune checkpoints as well as chemotherapy sensitivity. In addition, functional analysis demonstrated high enrichment of these gene sets throughout the process of tumor invasion. Finally, SERPINE2 was identified as a therapeutically critical gene. Therefore, we subsequently selected an inhibitor, IITZ-01, that targets SERPINE2, and we performed molecular docking simulations. Furthermore, we validated the inhibitory effect of IITZ-01 on OS at the cellular level. The results suggest that HIS-OS-related genes are important for prognostic stratification and therapeutic strategies for OS.
Explainable classification of seizures and other patterns of harmful brain activity in critically ill patients
Authors: A MANIKANDAN , T SANJAY , NAGANDLA CHIRUDEEP 
Published: June 2024

Abstract

Accurate detection and classification of seizures from electroencephalography (EEG) data can potentially enable timely interventions and treatments for neurological diseases. Currently, EEG recordings are exclusively reviewed by human experts, namely neurologists with specialized training. While indispensable, this time-consuming workflow represents a major bottleneck. Review of EEG records is laborious, time-consuming, expensive, prone to fatigue-induced errors, and suffers from inter-rater reliability even among expert reviewers. This paper introduces a new deep neural network (DNN) with interpretable layers for the classification of seizures and other pathologic brain activities such as periodic discharges, rhythmic delta waves and miscellaneous activities. The DNN architecture uses interpretable layers that allow clinicians to evaluate the model’s decision-making pipeline and build trust in the model and support clinical decision making. The combination of deep learning and interpretability layers is novel and addresses the limitations of existing methods. We demonstrate the usefulness of the proposed approach on a publicly available EEG dataset. Our method achieves state-of-the-art performance and provides classification decisions that are interpretable, useful for clinical experts. This paper contributes to the existing body of literature on EEG-based seizure detection and addresses the gap between DNN-based methods and clinical interpretability, leading to accurate and clinically meaningful predictions.
Engineering extracellular vesicles to permeabilize the blood-brain barrier
Authors: Tomatis Francesca , Rosa Susana , Simões Susana , Barão Marta , Barth Emanuel , Marz Manja , Ferreira Lino 
Published: June 2024

Abstract

Background
Drug delivery to the brain is challenging due to the restrict permeability of the blood brain barrier (BBB). Recent studies indicate that BBB permeability increases over time during physiological aging likely due to factors (including extracellular vesicles (EVs)) that exist in the bloodstream. Therefore, inspiration can be taken from aging to develop new strategies for the transient opening of the BBB for drug delivery to the brain.
Results
Here, we evaluated the impact of small EVs (sEVs) enriched with microRNAs (miRNAs) overexpressed during aging, with the capacity to interfere transiently with the BBB. Initially, we investigated whether the miRNAs were overexpressed in sEVs collected from plasma of aged individuals. Next, we evaluated the opening properties of the miRNA-enriched sEVs in a static or dynamic (under flow) human in vitro BBB model. Our results showed that miR-383-3p-enriched sEVs significantly increased BBB permeability in a reversible manner by decreasing the expression of claudin 5, an important tight junction protein of brain endothelial cells (BECs) of the BBB, mediated in part by the knockdown of activating transcription factor 4 (ATF4).
Conclusions
Our findings suggest that engineered sEVs have potential as a strategy for the temporary BBB opening, making it easier for drugs to reach the brain when injected into the bloodstream.
Prevalence and associated factors of psychiatric problems in children aged 6-18 years with type 1 diabetes mellitus in Gondar, Ethiopia: a cross-sectional study
Authors: AlehegnAwoke Birhanu , Alemu Mehretie Kokeb , Genet Geta Bayu , Dubie Addisu Ginbu , Alemayehu Biruk Fanta 
Published: June 2024

Abstract

Background
Diabetes mellitus is one of the most common chronic illnesses in children with multiple psychosocial, economical and developmental effects. Common psychiatric disorders including depression, anxiety, psychological distress, and eating disorders are more common in diabetic patients than their counters without diabetes. The main objective of our study was to assess Prevalence and associated factors of psychiatric problems in children aged 6–18 years with type 1 diabetes mellitus in Gondar, Ethiopia.
Methods
An institution-based prospective cross-sectional study was conducted among 206 children aged 6–18 years with type-1 diabetes mellitus in the University of Gondar comprehensive and specialized hospital (UoGCSH) chronic illness clinic over three months period. Data was collected using a structured questioner by trained general practitioner. Convenient sampling technique was applied and Participants were included taken sequentially until the sample size was achieved. Both bivariate and multivariate logistic regression analyses were used for Model fitness and the strength of association was determined using an OR, p value of < 0.05 and 95% CI.
Results
The prevalence of psychiatric problems was 11.65%and those children living with only either of the parent(AOR = 6.94,95%CI :1.47–32.83), living with other relatives (AOR = 21.49, 95% CI:3.54-130.58), family size > 5 people (AOR = 0.24, 95%CI :0.06–0.97),father attend formal education (AOR = 0.16, 95%CI : 0.03–0.97), patients having good glycemic control (AOR = 0.16, 95% CI : 0.04–0.61)and patients having family history of diabetes mellitus(AOR = 5.07,95%CI:1.20-21.52) were found to have significant association with the occurrence of psychiatric problems in diabetic children.
Conclusion
The prevalence of psychiatric problems in diabetic children were significantly high and children living with single parent, paternal educational status, glycemic control, family history of diabetes, and family size were found to have a significant association with the occurrence of the psychiatric problem in diabetic children.