bluuebunny/crossref_metadata_2025_split huggingface dataset:
HK2: a potential regulator of osteoarthritis via glycolytic and non-glycolytic pathways
Authors: Bao Chuncha , Zhu Siyi , Song Kangping , He Chengqi 
Published: August 2022

AbstractOsteoarthritis (OA) is an age-related chronic degenerative joint disease where the main characteristics include progressive degeneration of cartilage, varying degrees of synovitis, and periarticular osteogenesis. However, the underlying factors involved in OA pathogenesis remain elusive which has resulted in poor clinical treatment effect. Recently, glucose metabolism changes provide a new perspective on the pathogenesis of OA. Under the stimulation of external environment, the metabolic pathway of chondrocytes tends to change from oxidative phosphorylation (OXPHOS) to aerobic glycolysis. Previous studies have demonstrated that glycolysis of synovial tissue is increased in OA. The hexokinase (HK) is the first rate limiting enzyme in aerobic glycolysis, participating and catalyzing the main pathway of glucose utilization. An isoform of HKs, HK2 is considered to be a key regulator of glucose metabolism, promotes the transformation of glycolysis from OXPHOS to aerobic glycolysis. Moreover, the expression level of HK2 in OA synovial tissue (FLS) was higher than that in control group, which indicated the potential therapeutic effect of HK2 in OA. However, there is no summary to help us understand the potential therapeutic role of glucose metabolism in OA. Therefore, this review focuses on the properties of HK2 and existing research concerning HK2 and OA. We also highlight the potential role and mechanism of HK2 in OA.
Microglia-derived CCL2 has a prime role in neocortex neuroinflammation
Authors: Errede Mariella , Annese Tiziana , Petrosino Valentina , Longo Giovanna , Girolamo Francesco , de Trizio Ignazio , d’Amati Antonio , Uccelli Antonio , Kerlero de Rosbo Nicole , Virgintino Daniela 
Published: August 2022

AbstractBackgroundIn myelin oligodendrocyte glycoprotein (MOG)-induced experimental autoimmune encephalomyelitis (EAE), several areas of demyelination are detectable in mouse cerebral cortex, where neuroinflammation events are associated with scarce inflammatory infiltrates and blood–brain barrier (BBB) impairment. In this condition, the administration of mesenchymal stem cells (MSCs) controls neuroinflammation, attenuating astrogliosis and promoting the acquisition of stem cell traits by astrocytes. To contribute to the understanding of the mechanisms involved in the pathogenesis of EAE in gray matter and in the reverting effects of MSC treatment, the neocortex of EAE-affected mice was investigated by analyzing the cellular source(s) of chemokine CCL2, a molecule involved in immune cell recruitment and BBB-microvessel leakage.MethodsThe study was carried out by immunohistochemistry (IHC) and dual RNAscope IHC/in situ hybridization methods, using astrocyte, NG2-glia, macrophage/microglia, and microglia elective markers combined with CCL2.ResultsThe results showed that in EAE-affected mice, hypertrophic microglia are the primary source of CCL2, surround the cortex neurons and the damaged BBB microvessels. In EAE-affected mice treated with MSCs, microgliosis appeared diminished very soon (6 h) after treatment, an observation that was long-lasting (tested after 10 days). This was associated with a reduced CCL2 expression and with apparently preserved/restored BBB features. In conclusion, the hallmark of EAE in the mouse neocortex is a condition of microgliosis characterized by high levels of CCL2 expression.ConclusionsThis finding supports relevant pathogenetic and clinical aspects of the human disease, while the demonstrated early control of neuroinflammation and BBB permeability exerted by treatment with MSCs may have important therapeutic implications.
Circulating histones contribute to monocyte and MDW alterations as common mediators in classical and COVID-19 sepsis
Authors: Ligi Daniela , Lo Sasso Bruna , Giglio Rosaria Vincenza , Maniscalco Rosanna , DellaFranca Chiara , Agnello Luisa , Ciaccio Marcello , Mannello Ferdinando 
Published: August 2022

Abstract
Objective
Histone proteins are physiologically involved in DNA packaging and gene regulation but are extracellularly released by neutrophil/monocyte extracellular traps and mediate thrombo-inflammatory pathways, associated to the severity of many human pathologies, including bacterial/fungal sepsis and COVID-19. Prominent and promising laboratory features in classic and viral sepsis emphasize monocyte distribution width (MDW), due to its ability to distinguish and stratify patients at higher risk of critical conditions or death. No data are available on the roles of histones as MDW modifiers.

Design
Comparison of MDW index was undertaken by routine hematology analyzer on whole blood samples from patients with COVID-19 and Sepsis. The impact of histones on the MDW characteristics was assessed by the in vitro time-dependent treatment of healthy control whole blood with histones and histones plus lipopolysaccharide to simulate viral and classical sepsis, respectively.

Measurements and main results
We demonstrated the breadth of early, persistent, and significant increase of MDW index in whole blood from healthy subject treated in vitro with histones, highlighting changes similar to those found in vivo in classic and viral sepsis patients. These findings are mechanistically associated with the histone-induced modifications of cell volume, cytoplasmic granularity and vacuolization, and nuclear structure alterations of the circulating monocyte population.

Conclusions
Histones may contribute to the pronounced and persistent monocyte alterations observed in both acute classical and viral sepsis. Assessment of the biological impact of circulating histone released during COVID-19 and sepsis on these blood cells should be considered as key factor modulating both thrombosis and inflammatory processes, as well as the importance of neutralization of their cytotoxic and procoagulant activities by several commercially available drugs (e.g., heparins and heparinoids).
Novel diaminoguanidine functionalized cellulose: synthesis, characterization, adsorption characteristics and application for ICP-AES determination of copper(II), mercury(II), lead(II) and cadmium(II) from aqueous solutions
Authors: Akl Magda A. , Hashem Mohammed A. , Ismail Mohammed A. , Abdelgalil Dina A. 
Published: August 2022

AbstractIn this study, the novel adsorbent diaminoguanidine-modified cellulose (DiGu.MC) was synthesized to extract mercury, copper, lead and cadmium ions from aqueous solutions and environmental water samples. The synthetic strategy involved oxidizing cellulose powder into dialdehyde cellulose (DAC) and reacting DAC with diaminoguanidine to create an imine linkage between the two reactants to form diaminoguanidine-modified cellulose (DiGu.MC). The structure and morphology of the adsorbent were studied using a variety of analytical techniques including Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM) and Brunauer–Emmett–Teller (BET) surface area measurements. Adsorption of mercury, copper, lead, and cadmium ions was optimized by examining the effects of pH, initial concentration, contact time, dose, temperature and competing ions. Under optimal adsorption conditions, the adsorption capacities of Cu2+, Hg2+, Pb2+, and Cd2+ were 66, 55, 70 and 41 mg g−1, respectively. The adsorption isotherm is in very good agreement with the Langmuir isotherm model, indicating that a monomolecular layer is formed on the surface of DiGu.MC. The kinetics of adsorption are in good agreement with the pseudo-second kinetics model that proposes the chemical adsorption of metal ions via the nitrogen functional groups of the adsorbent. Thermodynamic studies have confirmed that the adsorption of heavy metals by DiGu.MC is exothermic and spontaneous. Regeneration studies have shown that the adsorbent can be recycled multiple times by removing metal ions with 0.2 M nitric acid. The removal efficiency for regeneration was over 99%. DiGu.MC is introduced as a unique adsorbent in removing mercury, copper, lead and cadmium with a simple synthetic strategy, with cheap starting materials, a unique chemical structure and fast adsorption kinetics leading to excellent removal efficiency and excellent regeneration. The mechanism of adsorption of the investigated heavy metals, is probably based on the chelation between the metal ions and the N donors of DiCu.MC.
Barriers and facilitators to clinical behaviour change by primary care practitioners: a theory-informed systematic review of reviews using the Theoretical Domains Framework and Behaviour Change Wheel
Authors: Mather Melissa , Pettigrew Luisa M. , Navaratnam Stefan 
Published: August 2022

Abstract
Background
Understanding the barriers and facilitators to behaviour change by primary care practitioners (PCPs) is vital to inform the design and implementation of successful Behaviour Change Interventions (BCIs), embed evidence-based medicine into routine clinical practice, and improve quality of care and population health outcomes.

Methods
A theory-led systematic review of reviews examining barriers and facilitators to clinical behaviour change by PCPs in high-income primary care contexts using PRISMA. Embase, MEDLINE, PsychInfo, HMIC and Cochrane Library were searched. Content and framework analysis was used to map reported barriers and facilitators to the Theoretical Domains Framework (TDF) and describe emergent themes. Intervention functions and policy categories to change behaviour associated with these domains were identified using the COM-B Model and Behaviour Change Wheel (BCW).

Results
Four thousand three hundred eighty-eight reviews were identified. Nineteen were included. The average quality score was 7.5/11. Reviews infrequently used theory to structure their methods or interpret their findings. Barriers and facilitators most frequently identified as important were principally related to ‘Knowledge’, ‘Environmental context and resources’ and ‘Social influences’ TDF domains. These fall under the ‘Capability’ and ‘Opportunity’ domains of COM-B, and are linked with interventions related to education, training, restriction, environmental restructuring and enablement. From this, three key areas for policy change include guidelines, regulation and legislation. Factors least frequently identified as important were related to ‘Motivation’ and other psychological aspects of ‘Capability’ of COM-B. Based on this, BCW intervention functions of persuasion, incentivisation, coercion and modelling may be perceived as less relevant by PCPs to change behaviour.

Conclusions
PCPs commonly perceive barriers and facilitators to behaviour change related to the ‘Capability’ and ‘Opportunity’ domains of COM-B. PCPs may lack insight into the role that ‘Motivation’ and aspects of psychological ‘Capability’ have in behaviour change and/or that research methods have been inadequate to capture their function. Future research should apply theory-based frameworks and appropriate design methods to explore these factors. With no ‘one size fits all’ intervention, these findings provide general, transferable insights into how to approach changing clinical behaviour by PCPs, based on their own views on the barriers and facilitators to behaviour change.

Systematic review registration
A protocol was submitted to the London School of Hygiene and Tropical Medicine via the Ethics and CARE form submission on 16.4.2020, ref number 21478 (available on request). The project was not registered on PROSPERO.
Gut microbiome-targeted therapies in liver cirrhosis: a protocol for systematic review and meta-analysis
Authors: Jiang Honglin , Peng Yan , Zhang Wei , Chen Yue , Jiang Qingwu , Zhou Yibiao 
Published: August 2022

Abstract
Background
Microbiome-targeted therapies (MTTs), including probiotics, prebiotics, synbiotics, and fecal microbiota transplantation (FMT), have been proposed as a potential treatment for cirrhosis via modulation of gut microbiome, while the impact of gut microflora alteration on liver function in cirrhosis trajectory is unclear, and no related systematic review has been published. We aim to comprehensively assess the effects of MTTs in patients with liver cirrhosis.

Methods
We will search databases of MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials (CENTRAL) with no time restriction. Only randomized controlled trials published in English will be included. Two independent reviewers will be responsible for study identification and selection, data extraction, and risk of bias assessment, with discrepancies resolved by consensus or referral to a third author. Heterogeneity of studies will be examined using Cochrane Q-test and I2 statistics. The data will be pooled using either a fixed- or random-effects model based on I2 statistics. The results will be presented as risk ratios (RR) or mean differences (MD) with 95% confidence intervals (CI). We will perform subgroup analysis on the type of MTTs and assess the reporting biases. Sensitivity analysis will be conducted to test the stability of each outcome result.

Discussion
There is no current study about the role of MTTs in developing the liver function, and the therapeutic effects of MTTs are inconsistent. By investigating the liver-specific indicators when treating with multiple MTTs on course of cirrhosis, our findings will give more conclusive and stronger evidence about the efficacy of MTTs and provide new insight into the action mechanisms of these MTTs.

Systematic review registration
PROSPERO CRD42021253198.
DSTS: A hybrid optimal and deep learning for dynamic scalable task scheduling on container cloud environment
Authors: Muniswamy Saravanan , Vignesh Radhakrishnan 
Published: August 2022

AbstractContainers have grown into the most dependable and lightweight virtualization platform for delivering cloud services, offering flexible sorting, portability, and scalability. In cloud container services, planner components play a critical role. This enhances cloud resource workloads and diversity performance while lowering costs. We present hybrid optimum and deep learning approach for dynamic scalable task scheduling (DSTS) in container cloud environment in this research. To expand containers virtual resources, we first offer a modified multi-swarm coyote optimization (MMCO) method, which improves customer service level agreements. Then, to assure priority-based scheduling, we create a modified pigeon-inspired optimization (MPIO) method for task clustering and a rapid adaptive feedback recurrent neural network (FARNN) for pre-virtual CPU allocation. Meanwhile, the task load monitoring system is built on a deep convolutional neural network (DCNN), which allows for dynamic priority-based scheduling. Finally, the presentation of the planned DSTS methodology will be estimated utilizing various test vectors, and the results will be associated to present state-of-the-art techniques.
Cloud-based bug tracking software defects analysis using deep learning
Authors: Hai Tao , Zhou Jincheng , Li Ning , Jain Sanjiv Kumar , Agrawal Shweta , Dhaou Imed Ben 
Published: August 2022

AbstractCloud technology is not immune to bugs and issue tracking. A dedicated system is required that will extremely error prone and less cumbersome and must command a high degree of collaboration, flexibility of operations and smart decision making. One of the primary goals of software engineering is to provide high-quality software within a specified budget and period for cloud-based technology. However, defects found in Cloud-Based Bug Tracking software’s can result in quality reduction as well as delay in the delivery process. Therefore, software testing plays a vital role in ensuring the quality of software in the cloud, but software testing requires higher time and cost with the increase of complexity of user requirements. This issue is even cumbersome in the embedded software design. Early detection of defect-prone components in general and embedded software helps to recognize which components require higher attention during testing and thereby allocate the available resources effectively and efficiently. This research was motivated by the demand of minimizing the time and cost required for Cloud-Based Bug Tracking Software testing for both embedded and general-purpose software while ensuring the delivery of high-quality software products without any delays emanating from the cloud. Not withstanding that several machine learning techniques have been widely applied for building software defect prediction models in general, achieving higher prediction accuracy is still a challenging task. Thus, the primary aim of this research is to investigate how deep learning methods can be used for Cloud-Based Bug Tracking Software defect detection with a higher accuracy. The research conducted an experiment with four different configurations of Multi-Layer Perceptron neural network using five publicly available software defect datasets. Results of the experiments show that the best possible network configuration for software defect detection model using Multi-Layer Perceptron can be the prediction model with two hidden layers having 25 neurons in the first hidden layer and 5 neurons in the second hidden layer.
Research on influencing factors of artificial intelligence multi-cloud scheduling applied talent training based on DEMATEL-TAISM
Authors: Bian Yi-jie , Xie Lu , Li Jing-qi 
Published: August 2022

AbstractWith the rapid development of Internet of Things (IoT) technology and the rising popularity of IoT devices, an increasing number of computing intensive IoT applications have been developed. However, due to the limited resources of IoT devices, cloud computing systems are required to compute intensive IoT applications. Furthermore, to be subject to a single cloud computing service provider, multi-cloud computing has become an IoT service cloud computing solution. As a result of the complexity of multi-cloud scheduling, the application of artificial intelligence is an important technology to solve IoT multi-cloud scheduling. The corresponding talent training plays an important role in the development and implementation of the IoT artificial intelligence multi-cloud scheduling. First, this paper studies the key influencing factors of IoT artificial intelligence multi-cloud scheduling applied talent training. Combined with the characteristics of the development of China’s artificial intelligence industry, this paper summarizes the influencing factors from the four-dimensional training path of government departments, universities, enterprises and scientific research institutes. The purpose of artificial intelligence multi-cloud scheduling applied talent training is to build an artificial intelligence multi-cloud scheduling applied talent training influencing factor index system. Then, the DEMATEL method is used to establish multiple correlation matrices according to the direct influence correlation between the factors and calculate the degree of influence, the degree of being influenced, the center degree and the cause degree of the factors. Using the improved AISM method, based on the idea of game confrontation, from the two opposite extraction rules of result priority and cause priority, a group of confrontation level topological maps with comprehensive influence values reflecting the interacting factors are obtained, and relevant suggestions are presented to provide a reference for the training of artificial intelligence multi-cloud scheduling applied talent.
A cross-sectional study of antimicrobial use among self-medicating COVID-19 cases in Nyeri County, Kenya
Authors: Kimathi George , Kiarie Jackline , Njarambah Lydiah , Onditi Jorum , Ojakaa David 
Published: August 2022

Abstract
Background
During the COVID-19 pandemic, Nyeri County in Kenya was among the regions reporting a high number of confirmed cases. This exemplified the increased need of addressing potential antimicrobial resistance (AMR) and self-medication during disease outbreaks. This study examined the extent of self-medication with antimicrobials among COVID-19 confirmed cases in the County.

Methods
A cross-sectional survey using phone-based interviews was conducted in August 2021 among a sample of 280 out of 2317 confirmed COVID-19 cases in the County using a pre-coded questionnaire. Descriptive analyses of frequencies and causal logistic regression were conducted using STATA version 13.

Results
A total of 193 (68.9%) of the respondents indicated developing COVID-19 related symptoms-mainly cough (41.5%), headache (38.3%), and fatigue (34.7%). Over one-fifth (23.4%) of the respondents had self-medicated with antibiotics, 60.6% of whom did so at the onset of symptoms before the confirmatory test, and 51.5% self-medicating more than once. Common antibiotics used were Azithromycin (40.0%) and Amoxycilline (23.3%), with a considerable 21.7% having difficulty remembering the name of the drugs. Only half (50.4%) of the respondents (128/254) were aware of regulations towards self-medication with antibiotics. Age was the only socio-demographic variable significantly related to reduced self-medication, with older persons less likely to self-medicate. On the other hand, developing COVID-19 symptoms, awareness of COVID regulations, and appreciation of the need for self-medication awareness were related to increased self-medication.

Conclusion
Being older, developing COVID-19 symptoms, and appreciating self-medication awareness have influential effects on the use of antimicrobials. Public health interventions should be timely during infectious disease outbreaks to prevent undesirable health-seeking behavior such as irrational antimicrobial use. AMR policies should enhance awareness of the risks of self-medication and address barriers that deter people from timely access of health services during disease outbreaks. Further research should be conducted on the self-medication and AMR nexus, especially during health emergencies.
External validation of the Tyrolean hip arthroplasty registry
Authors: Wagner Moritz , Neururer Sabrina , Dammerer Dietmar , Nardelli Paul , Kaufmann Gerhard , Braito Matthias , Brunner Alexander 
Published: August 2022

Abstract
Purpose
Arthroplasty registries gained increasing importance to the re-certification of orthopaedic implants according to the European Union (EU) Medical Device Regulation (MDR) adopted in 2017. Until recently, several European countries only had regional arthroplasty registries. Whether regional registries deliver data quality comparable with national registries remained unclear. Therefore, the purpose of this study was to validate the Austrian Tyrolean Hip Arthroplasty Registry (THAR) and to evaluate if this regional registry showed adequate adherence, completeness and correctness when compared with well-established national registries.

Methods
A consecutive series of 1100 primary total hip arthroplasties were identified from our institution’s medical database. Patients were interviewed by phone and completed questionnaires after a mean follow-up period of 8.05 years and were asked if they had had revision surgeries. The data were compared to the corresponding dataset from the THAR.

Results
Adherence was 97.91% for primary total hip arthroplasty. Clinical follow-up identified 10 missing cases, resulting in adherence of 81.48% for revisions. Completeness of patient-reported outcome measurements was 78.55% before surgery and 84.45% 1 year after surgery. Correctness was 99.7% for demographic data, 99.54% for implant specifications, and 99.35% for mode of fixation.

Conclusion
The data of this study showed that regional arthroplasty registries can deliver data quality comparable with well-established national registries. The main reason for unrecorded revision cases and wrongly recoded implants was human error. Further digitalization with more automatic data submission may have the potential to reduce these failure rates in the future. Overall, the THAR represents a valid data source for re-certification of medical implants according to the EU’s MDR.