bluuebunny/crossref_metadata_2025_split huggingface dataset:
Protocol for a systematic review and network meta-analysis of the use of prophylactic antibiotics in hand trauma surgery
Authors: Zhang Chen , Farang Soma , Wade Ryckie George , Wormald Justin Conrad Rosen 
Published: February 2024

Abstract

Background: The use of prophylactic antibiotics in surgery is contentious. With the rise in antimicrobial resistance, evidence based antibiotic use should be followed. This systematic review and network meta-analysis will assess the effectiveness of different antibiotics on the prevention of surgical site infection (SSI) following hand trauma surgery.
Methods and analysis: The databases EMBASE, MEDLINE, CINAHL and CENTRAL, metaRegister of controlled trials, clinicaltrials.gov and the WHO International Clinical Trials Registry Platform will be searched for published and unpublished studies which will then be screened by two persons independently to identify eligible studies.
This systematic review will include both randomised and non-randomised prospective comparative studies in participants with hand and/or wrist injuries requiring surgery. The network meta-analysis will compare the use of different prophylactic antibiotics against each other, placebo and/or no antibiotics on the development of SSI within 30 days of surgery (or 90 days if there is an implanted device).
The Cochrane Risk of Bias tool 2 will be used to assess the risk of methodological bias in randomised controlled trials and the Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) tool will be used to assess the risk of bias in non-randomised studies. The ROB-MEN tool will be used to evaluate the risk of bias due to missing evidence in network meta-analysis.
A random effects network meta-analysis will be conducted along with subgroup analyses looking at antibiotic timing, operation type and injury type. Sensitivity analyses including only low risk of bias studies and the study location will be conducted and the confidence in the results will be assessed using Confidence in Network Meta‐Analysis (CINEMA).
Discussion: This systematic review and network meta-analysis aims to provide an up to date synthesis of the studies assessing the use of antibiotics following hand and wrist trauma to enable evidence-based peri-operative prescribing.
Registration: Prospero registration number CRD42023429618
Efficacy and safety of D-penicillamine, trientine and zinc in pediatric Wilson disease patients
Authors: Lee Eun Joo , Woo Min Hyung , Moon Jin Soo , Ko Jae Sung 
Published: February 2024

Abstract
Objectives
Wilson disease (WD) is a rare genetic disease affecting copper metabolism and the biliary tract’s copper excretion. Lifelong medication is necessary to prevent liver failure, neurological complications, and death. Although D-penicillamine (DPA), trientine, and zinc are used to treat Wilson disease (WD), there is limited research on the long-term outcomes of these drugs, especially in children. This study aimed to evaluate the effecacy and safety of DPA, trientine, and zinc in patients diagnosed with WD during childhood.
Methods
Ninety out of 92 patients were included in the analysis, excluding two patients who underwent liver transplantation without drug treatment due to an acute liver failure diagnosis. Treatment outcomes and reasons for discontinuation of therapy in 148 treatment blocks (37 DPA, 50 trientine, and 61 zinc) were analyzed using Kaplan-Meier analysis.
Results
The median age at diagnosis was 8.3 years. There was a statistically significant difference in drug changes due to treatment ineffectiveness among the three drugs: trientine (22/50, 44%), zinc (15/61, 25%), and DPA (2/37, 5%) (all p < 0.05). Regarding drug changes due to adverse effects, the rate was the highest for DPA, followed by zinc and trientine. There were significant differences between DPA and zinc, zinc and trientine (all p < 0.05), but no significant difference was observed between DPA and zinc (p = 0.22).
Conclusions
In pediatric WD, DPA, zinc, and trientine have therapeutic effects in that order. However, DPA and zinc were associated with more adverse effects than trientine.
Obesity modifies cell fate plasticity of Pdgfrα-expressing adipocyte progenitors to promote an aberrant mammary microenvironment
Authors: Joshi Purna , Kwende Sharon , Nuthalapati Prashant , Singh Jacqulene Sunder , Maity Subhajit , Ning Dun , Shryock Douglas , Xuan Zhenyu 
Published: February 2024

Abstract
Excess fat gain culminating in obesity is a mounting global pandemic associated with a myriad of diseases including a higher risk of developing multiple cancers such as breast cancer. The underlying biological basis for obesity-linked breast cancer is attributed to alterations in adipose tissue-derived endocrine, metabolic and inflammatory factors. However, the precise cell types responsible for generating a cancer-susceptible mammary gland in obesity are not well understood. Using diet-induced obesity in conjunction with genetic reporter mouse models, we reveal elevated mammary adipocyte progenitors (MAPs) expressing Platelet-Derived Growth Factor Receptor alpha (PDGFRα) in the mammary tissue microenvironment during obesity. Single-cell RNA sequencing analysis demonstrate intensified obesity-driven trajectories of MAPs to immune and epithelial progenitor cells. Further, lineage tracing indicates an invasive cellular state of MAPs that confers greater access of MAP descendants into the mammary epithelium concomitant with their transition into immune and epithelial cell fates. MAPs in obesity exhibit heightened activation of cancer-associated and inflammatory pathways where Egfr is identified as a common target upregulated in MAPs. Mechanistic studies on purified MAPs with a major obesity diet component and EGFR stimulation corroborate dynamic EGFR-mediated MAP responses. Our findings uncover MAPs as key contributors to forging an aberrant mammary gland in obesity, providing insight into the potential utility of targeting this cell lineage for eradicating cancer risk related to augmented adiposity.
A Feasibility Study on the Vaporization of Liquefied Carbon Dioxide Due to Heat Transfer in Submerged Pipeline with Start-up, Shutdown and Abnormal Dynamic Simulation Scenarios Prediction
Authors: Asante Daniel Owusu , Galanido Russel J. , Cho Jungho , Park Ilsu , Hwang Philsung , Cheol Jungki 
Published: February 2024

Abstract

The vaporization of liquefied carbon dioxide (LCO2) resulting from heat transfer in undersea pipeline flow was examined in this feasibility study. The purpose of the study was to assess how several factors, including flow velocity, temperature and height, affected the rate at which CO2 evaporated in a submerged pipeline. Ansys Fluent and Aspen Plus were two of the simulation tools used for the analysis. For the assessment, the SRK thermodynamic model was chosen. Start-up, shutdown, and abnormal dynamic studies were further conducted to ascertain the safe operation of the pipeline using Aspen Plus and Aspen Dynamics. The study emphasizes the need to take heat transfer into account in the design and operation of these pipelines and offers insightful information about the behavior of CO2 in undersea pipelines. Reliable seabed and oceanographic data were obtained with the corresponding temperatures for the prediction of pipeline landfall. The maximum pressure of 76.61 barg was established at Node 11 but further drop at the last 200m pipe segment (N11 to N13) to achieve an outlet pressure of 59.72 barg. The loss of pressure was due to gravity since the fluid was directed upward to the sea platform. There was a gradual drop in temperature along the pipeline. The temperature at the pipe outlet was calculated to be 3.33oC. The results of this study can be applied to improve efficiency and lower the risk of accidents associated with the design and operation of underwater pipelines for the transportation and storage of CO2. The results in this work is significant since it offers a thorough grasp of how CO2 behaves in submerged pipes, knowledge that may be utilized to guarantee the effective and safe transit and storage of this material.
Benefits of multiple remotely sensed datasets and machine learning models to predict the Chlorophyll-a concentration in the Nakdong River, South Korea
Authors: Lee Byeongwon , Im Jong Kwon , Han Ji Woo , Kang Taegu , Kim Wonkook , Lee Sangchul 
Published: February 2024

Abstract
Machine learning models (MLMs) are increasingly used with remotely sensed data to monitor chlorophyll-a (Chl-a). MLMs require large amounts of remotely sensed data to monitor Chl-a effectively. However, weather conditions, satellite revisit cycles, and coverage constraints can impede the collection of adequate remotely sensed data. To address this, we tested whether MLMs effectively improved the predictions of Chl-a concentrations within the 16 lakes of the Nakdong River in South Korea using two remotely sensed datasets (Sentinel-2 and Landsat-8). This study evaluated four MLMs: Multi-Layer Perceptron (MLP), Support Vector Machine (SVM), Random Forest (RF), and eXetreme Gradient Boosting (XGB) using three different input datasets: 1) two remotely sensed datasets (Sentinel-2 and Landsat-8), 2) Sentinel-2, and 3) Landsat-8. The MLP model with multiple remotely sensed datasets outperformed other MLMs affected by data imbalance. The predictive map of the spatial distribution of Chl-a generated by the MLP model highlighted areas with high and low Chl-a concentrations. In conclusion, this study emphasizes the value of multiple remotely sensed datasets in enhancing the accuracy and reliability of Chl-a estimation, mainly when using the MLP model. This also highlights the need to address data imbalances when predicting Chl-a concentrations using MLMs. These findings provide valuable insights into utilizing MLMs effectively for Chl-a monitoring.
Development and Validation of Prognostic Prediction Model for Submandibular Gland Cancer Based on the SEER Database.
Authors: He Junkun , Zhao Feng , Li Jiangmiao , Wei Fangyu , Li Qiyun , Su Jiping 
Published: February 2024

Abstract

Objective
Accurately predicting the prognosis of submandibular gland carcinoma (SGC) patients remains a challenging task. The purpose of this study was to develop a columnar graph prognostic prediction model for submandibular gland cancer based on the SEER database, using feature selection with lasso regression and modeling with Cox regression.
Methods
This study utilized data from the SEER database, focusing on 1362 cases of SGC. Various clinical and demographic factors, including age, tumor size, histology, and lymph node metastasis, were considered as potential prognostic factors. Feature selection was performed using lasso regression, and a Cox proportional hazards model was constructed, taking into account the complex interactions between variables and their impact on survival outcomes.
Results
The established prognostic prediction model demonstrated good accuracy and reliability. The model effectively identified several important prognostic factors, including age, tumor size, histology, and lymph node metastasis, which strongly influenced the prognosis of SGC. The model showed good discrimination and calibration with c-indexes of 0.802 (0.784–0.821) in the training set and 0.756 (0.725–0.787) in the validation set. The decision curve analysis (DCA) curve reflected clinical utility.
Conclusion
This study suggests that the prognostic prediction model based on Cox regression is a valuable tool for predicting the prognosis of patients with SGC. This approach has the potential to improve patient outcomes by facilitating personalized treatment plans and identifying high-risk patients who may benefit from more aggressive interventions.
Assessing the ductile fracture characteristics of CuZn30 brass under various stress conditions
Authors: Ganjiani Mehdi , Ghobadi Sina 
Published: February 2024

Abstract
This paper focuses on the investigation of ductile fracture in CuZn30 brass under various stress triaxialities and Lode angles. To achieve this, five distinct specimen geometries were fabricated, including dog-bone, notched, two types of in-plane shear, and deep drawing specimens. Every specimen was subjected to testing in three orientations: rolling, diagonal, and transverse, with the aim of investigating the potential presence of anisotropic properties in plastic deformation. A non-linear damage parameter was incorporated into the constitutive equations in two forms: coupled and uncoupled from the hardening law. It is assumed that damage progresses as the Ganjiani ductile fracture model, used as a damage initiation criterion, is established. The von-Mises yield criterion characterizes the plastic behavior of the material. In order to authenticate the experimental results, a combination of experimental and numerical simulations was carried out. In this context, all tests were simulated using ABAQUS/Standard through the implementation of USDFLD and UHARD codes. The outcomes of the simulation demonstrated good concordance with the results obtained through experiment, particularly in terms of force and the softening (necking) zone for all specimen types. It was also observed that when damage is considered as a coupled parameter to the hardening law, the softening (necking) phenomenon could be effectively simulated.
Experimental optical properties explained by Density functional theory of the natural Red Algae for dye-sensitized solar cells application
Authors: Anoua Rania , Touhtouh Samira , Jouad Mohamed El , Hajjaji Abdelowahed , Bakasse Mina , Sahraoui Bouchta , Płóciennik Przemysław , Zawadzka Anna 
Published: February 2024

Abstract

The present study investigates the usage of a novel natural dye derived from Red algae of Morocco in dye-sensitized solar cells (DSSCs) for the first time. The main pigments responsible for sensitizing the semiconductor TiO2 coatings in the red algae were identified as Phycoerythrin, carotenoid, and chlorophyll. The efficiency of a DSSC made from red algae was compared to that of a solar cell made from chlorophyll alone. The photovoltaic performance of the DSSC was evaluated through photocurrent density to photovoltage (J-V) characteristic analysis, and the efficiency was found to be 0.93%. To gain insights into its behavior, the absorbance and photoluminescence in a broad range were studied. Both absorbance and photoluminescence exhibited a broad-spectrum range. Additionally, electronic properties, such as HOMO, LUMO, energy gap, and chemical reactivity parameters, were studied using DFT (density functional theory) calculations.
Multinational Enterprises in India and Climate Change; Opportunities and Challenges
Authors: Anjanappa Janardhana 
Published: February 2024

Abstract
Multinational enterprises (MNEs) play a significant role in the global economy and their operations have a substantial impact on the environment. Climate change is one of the most pressing environmental challenges facing the world today, and MNEs are increasingly being called upon to play a role in addressing it. While there is a growing body of literature on the general role of MNEs in addressing climate change, there is a need for more nuanced research that considers the unique context of India. This paper explores the complex and nuanced relationship between MNEs and climate change in the Indian context. The findings suggest that the Indian government has implemented a number of policies to promote sustainable development and address environmental challenges. However, these policies have had a mixed impact, and there is still much work to be done to address environmental challenges in India. Many MNEs are committed to reducing their environmental impact, but they face a number of challenges in doing so. These challenges include a lack of awareness, a lack of data and metrics, a short-term focus, uncertainty and complexity, a lack of government support, and internal organizational barriers. Governments can play a crucial role in creating an enabling environment by supporting MNEs while also ensuring that their operations are sustainable and responsible. Some effective policy measures include establishing clear and consistent regulations, providing incentives for sustainable practices, promoting transparency and accountability, and encouraging collaboration and knowledge sharing.
Effect of different infusion modes of pirarubicin on recurrence rate and adverse reactions in patients with postoperative chemotherapy for bladder cancer: A Meta-Analysis
Authors: Li Xiaojun , Li Chong , Niu Linyan , Bao Yinan 
Published: February 2024

Abstract
Objective This meta-analysis aims to compare the effect of postoperative pyrazobicin bladder thermal perfusion and plain perfusion in reducing the bladder cancer recurrence rate and the incidence of adverse effects in bladder cancer patients. Methods Computer searches were undertaken on the Cochrane Library, PubMed, the Wanfang database, China Knowledge Network (CNKI) and Wipu databases, all with a search time frame from inception to March 2023. Meta-analysis was performed using the RevMan 5.4.1 software.
Results 18 studies were included, and the results showed that compared to normal perfusion, postoperative pirarubicin bladder thermal perfusion was more effective in reducing the 2-year recurrence rate, the 1-year recurrence rate, and the incidence of urinary pain in bladder cancer patients.
Conclusion Compared to conventional infusion chemotherapy, postoperative pyrazobicin bladder heat infusion reduced the tumour recurrence rate and the incidence of adverse effects in bladder cancer patients more effectively.
Relationships between fixed-site ambient measurements of nitrogen dioxide, ozone, and particulate matter and personal exposures in Grand Paris, France: the MobiliSense study
Authors: Bista Sanjeev , Fancello Giovanna , Zeitouni Karine , Annesi-Maesano Isabella , Chaix Basile 
Published: February 2024

Abstract

Past epidemiological studies using fixed-site outdoor air pollution measurements as a proxy for participants’ exposure might have suffered from exposure misclassification. In the MobiliSense study, personal exposures to ozone (O3), nitrogen dioxide (NO2), and particles with aerodynamic diameters below 2.5 µm (PM2.5) were monitored with a personal air quality monitor. All the spatial location points collected with a personal GPS receiver and mobility survey were used to retrieve background hourly concentrations of air pollutants from the nearest Airparif monitoring station. We modeled 851343 minute-level observations from 246 participants. Visited places including the residence contributed the majority of the minute-level observations, 93.0%, followed by active transport (3.4%), and the rest were from on-road and rail transport, 2.4% and 1.1%, respectively. Comparison of personal exposures and station-measured concentrations for each individual indicated low Spearman correlations for NO2 (median across participants: 0.23), O3 (median: 0.21), and PM2.5 (median: 0.27), with varying levels of correlation by microenvironments. Generally, a large degree of individual variability in the correlation between personal and fixed-site measurements was found for all air pollutants. Results from mixed-effect models indicated that personal exposure was very weakly explained by station-measured concentrations (R2 < 0.07) for all air pollutants. The fit of the model was relatively high for O3 in the active transport microenvironment (R2: 0.25) and for PM2.5 in active transport (R2: 0.16) and in the separated rail transport microenvironment (R2: 0.20). Model fit slightly increased with decreasing distance between participants’ location and the nearest monitoring station. Our results demonstrate a relatively low correlation between personal exposure and station-measured air pollutants, confirming that station-measured concentrations as proxies of personal exposures can lead to exposure misclassification. However, distance and the type of microenvironment are shown to affect the extent of misclassification.
Water Stress Management Based on Groundwater Depletion Estimation in Saudi Arabia: A Hybrid ARIMA-GLS Approach
Authors: Abba Sani , Shah Syed Muzzamil Hussain , Yassin Mohamed A. , Mati Sagiru , Usman Abdullahi G. , Pradipta Arya , Baalousha Husam Musa , Khan Nadeem A , Aljundi Isam H. 
Published: February 2024

Abstract

Water scarcity is a pressing global challenge, and arid regions like Saudi Arabia face the urgent need for effective water stress management. The current study proposes an innovative method to tackle this issue by utilizing a hybrid time series analysis model, comprising of Autoregressive Integrated Moving Average (ARIMA) and Generalized Least Squares (GLS) techniques to estimate groundwater depletion trends in Saudi Arabia. The research employs historical groundwater data, climatic variables, and socioeconomic indicators to formulate comprehensive insight of the factors influencing groundwater depletion. The ARIMA component of the hybrid model captures the temporal dynamics of groundwater levels, while GLS considers the spatial and cross-correlation dependencies among observation points, enhancing the accuracy of depletion estimates. The study also demonstrates the significance of climatic variability and socioeconomic factors in exacerbating water stress in the region. Furthermore, the hybrid ARIMA-GLS model offers a robust tool for forecasting future groundwater depletion trends, aiding proactive decision-making in mitigating water stress. The numerical results for different wells proved to be essential in assessing the Mean Absolute Percent Error (MAPE). For instance, the MAPE values were found to be as (i) hybrid ARIMA-CLS (MAPE = 0.1507), (ii) ARIMA-CLS (MAPE = 0.429834), (iii) ARIMA-CLS (MAPE = 0.109115) for 4-H-84-N, 4-H-86-U, 4-S-316-U, respectively with the expectation of (iv) ARI (MAPE = 6.0285) for DA-45-U well. It is therefore believed that this research contributes to the broader discussion on managing the water resource in arid regions and highlights the significance of integrated approaches that consider both temporal and spatial dimensions. Further, it offers valuable insights and a practical framework for addressing water stress challenges in Saudi Arabia and serves as a model for water management in other arid regions grappling with similar issues.
Energy metabolism, oxidative stress and immunological status in adult hip replacement patients and healthy individuals
Authors: Andruszkiewicz Beata , Flis Damian , Samson Lucjan , Olek Robert , Zrodowski Maciej , Siekierzycka Anna , Kalinowski Leszek , Borkowski Tomasz , Antosiewicz Jędrzej , Ziółkowski Wiesław , Szalewska Dominika 
Published: February 2024

Abstract

The work aimed to compare (1) the activity of energy metabolism enzymes and oxidative stress indicators in homogenates of the tensor fascia lata muscle with peripheral blood mononuclear cell (PBMC) isolates in patients with hip replacement (HRP) and (2) PBMCs energy and stress metabolism, and indicators of inflammation and immunity of HRP and healthy individuals. The study involved 16 HRP patients. Skeletal muscle and blood samples were taken during HR. Moreover, blood samples of 12 control subjects were used to isolate PBMCs. The activity of aerobic (malate dehydrogenase; MDH) and anaerobic (lactate dehydrogenase; LDH) metabolism enzymes and the level of carbonyl groups were measured in skeletal muscle homogenates and PBMC isolates. The indicators of inflammation and immunity were also assessed. The purity level of PBMCs isolates were determined using platelets to PBMC ratio. There was no relationship between MDH and LDH activities and carbonyl groups measured in skeletal muscle homogenate and PBMC isolate. Significantly higher inflammatory indexes (NLR and the number of neutrophils) and the level of protein carbonyl groups were also noted in the HRP group compared to the control group.