bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anti-IL-5 treatment, but not neutrophil interference, attenuates inflammation in a mixed granulocytic asthma mouse model, elicited by air pollution
Authors: De Volder Joyceline , Bontinck Annelies , Haelterman Valerie , Boon Louis , Joos Guy F , Brusselle Guy G , Maes Tania 
Published: July 2024

Abstract

Introduction:
Diesel exhaust particles (DEP) have been proven to aggravate asthma pathogenesis. We previously demonstrated that exposure to house dust mite (HDM) and DEP in mice increases both eosinophils and neutrophils in bronchoalveolar lavage fluid (BALF) and also results in higher levels of neutrophil-recruiting chemokines and neutrophil extracellular trap (NET) formation. We aimed to evaluate whether treatment with anti-IL-5 can alleviate the asthmatic features in this mixed granulocytic asthma model. Moreover, we aimed to unravel whether neutrophils modulate the DEP-aggravated eosinophilic airway inflammation.
Material & methods
Female C57BL6/J mice were intranasally exposed to saline or HDM and DEP for 3 weeks (subacute model). Interference with eosinophils was performed by intraperitoneal administration of anti-IL-5. Interference with neutrophils and neutrophil elastase was performed by intraperitoneal anti-Ly6G and sivelestat administration, respectively. Outcome parameters included eosinophils subsets (homeostatic EOS and inflammatory EOS), proinflammatory cytokines, goblet cell hyperplasia and airway hyperresponsiveness.
Results
The administration of anti-IL-5 significantly decreased eosinophilic responses, affecting both inflammatory and homeostatic eosinophil subsets, upon subacute HDM + DEP exposure while BAL neutrophils, NET formation and other asthma features remained present. Neutrophils were significantly reduced after anti-Ly6G administration in BALF, lung and blood without affecting the eosinophilic inflammation upon HDM + DEP exposure. Sivelestat treatment tended to decrease BALF inflammation, including eosinophils, upon HDM + DEP exposure, but did not affect lung inflammation.
Conclusion
Inhibition of IL-5 signalling, but not neutrophil interventions, significantly attenuates eosinophilic inflammation in a mouse model of mixed granulocytic asthma, elicited by air pollution exposure.
Photobiomodulation Combined with Human Umbilical Cord Mesenchymal Stem Cells Modulates the Polarization of Microglia
Authors: Li Na , Zhu Hongyu , Cai Yuanhao , Guo Jun , Liu Pai , Han Zhibo , Wu Huancheng , Liu Yi , Chen Hongli 
Published: July 2024

Abstract

Neuroinflammation develops in neurodegenerative diseases. The severity of neuroinflammation is closely linked to microglial polarization. Different microglial phenotypes release inflammatory cytokines with distinct functions. Modulation of microglial polarization to alter neuroinflammation is a potential therapeutic strategy. Human umbilical cord mesenchymal stem cells (hUCMSCs) possess multiple stem cell properties that can be used to modulate inflammation. Various methods of pre-treatment of stem cells have shown enhanced efficacy in disease treatment. Photobiomodulation (PBM) is a non-invasive intervention that can reduce inflammation. Our in vitro experiments established a microglial cell inflammation model and demonstrated that PBM pre-treated hUCMSCs exhibited reduced the release of pro-inflammatory cytokines while promoting the expression of anti-inflammatory cytokines in microglia. This treatment significantly reduced the expression of Notch pathway-related genes in an inflammatory model, facilitated decreased M1 phenotype polarization, and increased M2 phenotype polarization in microglia. An animal inflammation model was established. In vivo studies showed that 808 nm light combined with hUCMSCs improved memory. and significantly reduced pro-inflammatory cytokines release in serum and brain tissue of male C57BL/6J mice, while promoting the expression of anti-inflammatory cytokines and M2 phenotype polarization of microglia. The results highlight the crucial role of 808 nm PBM in modulating microglial function and attenuating neuroinflammation through interaction with hUCMSCs. The findings offer novel insights into the molecular mechanisms of microglial polarization.
A Privacy Preserving Federated Learning BasedIoT Framework Using Cloud Computing
Authors: Ahmad Wasim , Almaiah Muhammad Amin , Ali Bakht Sher , Ali Aitizaz 
Published: July 2024

Abstract

This abstract explores the transformative impact of IoT on modern life, empha- sizing the integration of Federated Learning (FL), Edge Computing, and Secure Offloading in AI applications. The rapid evolution of IoT has revolutionized com- mercial operations and consumer interactions, driven by advanced sensing and computational capabilities in mobile devices. However, concerns over data privacy and limited computational resources hinder the deployment of compute-intensive applications. FL emerges as a distributed AI paradigm, ensuring privacy and saving network resources. Edge computing optimizes service delivery, reducing latency and energy consumption, supported by intelligent offloading algorithms and blockchain technology for secure and efficient edge services. Challenges like slow learning speeds persist but are addressed through ongoing advancements in neural networks.The proposed framework is compared with the benchmark mod- els and it was observed that the proposed framework suppress the benchmark models.
Investigating Antifungal Effect of Metal Oxide NPs and Carbon Nanodots Synthesized via Green Routes for Candida albicans
Authors: Singh Satya , Chauhan Himanshi , Yadav Himanshi , Hada Vivek , Singh Kumari Neha 
Published: July 2024

Abstract

Fascination using green synthesis methods is growing rapidly, attracting researchers to seek safer and more biocompatible processes for nanoparticle production. This study introduces a pioneering approach to crafting and investigating the antifungal effect of environmentally friendly carbon dots (organic materials) prepared from neem, rosemary, magnesium oxide (MgO), and zinc oxide (ZnO) nanoparticles (inorganic materials). MgO nanoparticles were synthesized using a Salvia hispanica (chia seed) extract. In contrast, ZnO nanoparticles were prepared from zinc acetate dihydrate and an aqueous extract of Dahlia pinnata leaves. Stable carbon nanodots were prepared from Azadirachta Indica leaves (commonly known as neem leaves) and Rosmarinus officinalis L. leaves (commonly known as rosemary leaves). This research delves into the intricate mechanisms governing their efficacy, offering insights into their potential therapeutic applications against microbial illnesses. The study illuminates their structural and functional attributes by employing various characterization methods, including FTIR, SEM, DLS, XRD, UV-vis-nir, and zeta potential. Moreover, it underscores the versatility of these materials in biomedical and environmental realms, highlighting their potential for various applications. Using the crystal violet bioassay method, we evaluated their antifungal potential against Candida albicans biofilm production. This study reveals the significant antifungal properties of these nanomaterials, hinting at their potential in combating fungal infections and advancing the fight against microbial threats. We collected three Candida albicans isolates recovered from clinical samples and examined the antifungal effect of carbon nanodots, MgO, and ZnO NPs by varying their concentrations. We coated the microtiter plate with 2,5-dimercapto-1,3,4-thiadiazole (DMcT) and then coated it with the nanodots. We observed a significant efficacy at higher concentrations. Our study unveils this unexplored area, which has been quite mysterious and more or less not understood scientifically, particularly at the molecular scale. However, it has been a traditional practice for many centuries in certain parts of the world, especially in India, where extracts prepared using plant parts, such as leaves, roots, stems, and flowers, have been used for healing and recovery from certain diseases, such as chicken pox and smallpox.
Exploring the Integration of a Global AI Model with Traditional Data Assimilation in Weather Forecasting
Authors: Xu Hongxiong , Duan Yihong , Xu Xiangde 
Published: July 2024

Abstract

Recent advancements in artificial intelligence (AI) have profoundly transformed weather forecasting, challenging traditional reliance on numerical weather prediction (NWP) models. Despite notable progress, AI models still depend heavily on traditional NWP systems and data assimilation methods to generate analysis fields, a dependency that increases computational demands and might limit forecast accuracy. This study explored the integration of Gridpoint Statistical Interpolation (GSI) with the Pangu-Weather AI forecasting model (GSI-Pangu), and assessed the potential for AI models to autonomously generate forecasts by leveraging mature data assimilation systems. Our experiments commenced by adopting ERA5 reanalysis data for the initial cycle, and then involved assimilation of simulated observations in subsequent cycles, spanning a month-long period. Results demonstrated notable enhancements in forecast accuracy, with reductions in the root mean square error across various atmospheric variables compared with the results of a control experiment without data assimilation. Additionally, the results highlighted GSI-Pangu’s ability to predict large-scale circulation patterns of extreme precipitation events, together with its effectiveness in driving regional models to accurately forecast precipitation intensity and distribution. Successful implementation of GSI within the Pangu-Weather framework underscores the transformative potential of hybrid forecasting systems, which merge conventional meteorological techniques with AI innovations, thereby facilitating accelerated adoption of AI in weather forecasting.
A cluster-based solution for Service Function Chain allocation in large scale infrastructure
Authors: Bezerra Diego de Freitas , Santos Guto Leoni , Rocha Élisson da Silva , Gonçalves Glauco Estacio , Moreira André , Marquezini Maria Valéria , Kelner Judith , Sadok Djamel 
Published: July 2024

Abstract

Changes in telecommunication services demand the development of a new infrastructure to attend new network applications' requirements. The traditional approach to network functions running over dedicated equipment can no longer handle all the dynamics of these new services. The network function virtualization (NFV) paradigm decouples a function from the underlying dedicated hardware thus making networks more flexible and agile. A set of virtual network functions (VNFs) can be deployed as virtual machines or containers across common servers, and orchestrated to compose a service function chain (SFC).Despite the many benefits of NFV, it raises several challenges. SFC placement is a complex task, since it requires taking into consideration the characteristics of VNFs, the SFC requirements, and the state of network infrastructure. This poses a challenge for large scale networks. Information regarding network resources are stored in a large database, and retrieving such data in order to perform SFC placement according to some strategy can be a problem. Limited memory capacity and the presence of a large number of disk operations can compromise the performance of SFC placement algorithms and make it unfeasible. In addition, the amount of memory available to run the allocation algorithm may not be sufficient to load the large amount of information that describe the network resources (occasionally in the hundreds of gigabytes). We address this problem by using a cluster based solution that stores and retrieves data for large scale infrastructures in order to perform SFC placement. The results demonstrate that the use of clusters in the preprocessing step can drastically reduce the size of the resulting database, as well as the execution time to select candidate nodes for a scalable SFC allocation.
Incidence and Management of Duodenal Trauma in a War Setting: Insights from a Military Hospital in Yemen
Authors: Obadiel Yasser Abdurabo , Saeed Mohammed abdulkarem , Jowah Haitham Mohammed , Al-Brashi Ali 
Published: July 2024

Abstract

Purpose: Duodenal injuries are a significant challenge in war trauma because of their complexity and potential for severe complications. This study evaluated the outcomes of duodenal injury management among patients with war trauma in Yemen, focusing on incidence, severity, surgical approaches, postoperative complications, and factors influencing success or failure.
Patients and Methods: A retrospective analysis was conducted on 520 exploratory laparotomy cases from June 2019 to December 2022 at a military hospital in Yemen. Twenty-seven patients with confirmed duodenal injuries were included. Data on demographic characteristics, injury characteristics, surgical management, and outcomes were collected and analyzed.
Results: The incidence rate of duodenal injuries was 5.2%. The cohort comprised predominantly young males, with a mean age of 21.93 years. Penetrating trauma accounted for 95.7% of cases. The mean Injury Severity Score (ISS) was 20.63, and most injuries were classified as AAST Grade II. The second duodenum part (D2) was the most commonly affected area. Associated injuries were frequent, particularly colonic (73.9%), chest (39.1%), and liver (29.6%) injuries. Surgical management primarily involved exploratory laparotomy (81.5%) and primary closure (66.7%). Postoperative complications were common, affecting 66.7% of patients, with sepsis (55.6%) being the most common. The success and mortality rates were 81.5%, and the mortality rate was 11.1%. Key risk factors for poor outcomes included higher ISS, grade III injury, damage control surgery, and shrapnel injury.
Conclusion: Duodenal injuries in war trauma settings pose significant management challenges, with high rates of associated injuries and postoperative complications. Early diagnosis, appropriate surgical techniques, and vigilant postoperative care is crucial for improved outcomes. Further multicenter research is needed to validate these findings and enhance management strategies in diverse settings.
Neutron activation of stable isotopes in soil and groundwater from a radionuclide production facility, South Africa
Authors: Marazula Thandazile , Malaza Ntokozo Mfanufikile , Conradie Jacobus Lodewikus , Beukes Philip 
Published: July 2024

ABSTRACT
The neutron activation of stable isotopes in environmental matrices, such as soil and groundwater, is a critical aspect of assessing the impact of radionuclide production facilities on the surrounding ecosystem. The envisioned Low-Energy Radioactive Ion Beams (LERIB) facility at the iThemba LABS, South Africa is anticipated to generate significant sources of ionising radiation. The study investigated the possible repercussions of neutron irradiation stemming from the facility, focusing on the activation of stable isotopic compositions in the environment. The investigation employed a combination of experimental and analytical techniques to characterize the neutron activation products in soil and groundwater samples collected from the vicinity. Samples were collected from designated areas for background radiological measurements and were irradiated with neutrons for a period of 1 h. The induced radioactivity measured by the High Purity Germanium detector included 24Na, 22Na, 54Mn, 52Mn, and 46Sc. The application of Darcy's law for groundwater velocity suggests that radionuclides in groundwater will migrate at an average flow velocity of 0.8 m/day. The isotopes with longer half-lives have count rates at background concentrations; therefore, environmental impacts on the site and surrounding communities might be minimal.
The Major Challenges Facing the Development of African Countries, and Algeria in Particular, in the Face of Cybercrime
Authors: Radja O. 
Published: July 2024

The rapid development of information and communication technologies is closely related to the exponential growth in data volumes. At the same time, the development of enterprise strategies coupled with the digital economy has led to changes in business models and infrastructure solutions. The emergence of innovative industries that extensively use the internet has presented significant challenges to the security of systems and sensitive data, particularly in the field of cybercrime. In order to address the growing issue of cybercrime, African nations, among which Algeria is the largest country, need to build a series of digital barriers in the form of legislation, multilateral agreements, and the development of technical capacity in this area, such as the creation of cybersecurity centers. The implementation of an effective cybersecurity strategy is strongly required on a national, regional, and continental scale. According to the last report of the Global Cybersecurity Index 2020, Mauritius is ranked as the most secure country in Africa in terms of cybersecurity, followed by South Africa in the second rank. A successful economy inherently involves a digital economy and a bold strategy to counter all the “nuisance” of cybercrimes. Algeria, despite its relatively low ranking in the last report of the Global Cybersecurity Index, has made significant progress when compared to its neighbors. With its excellent internet connectivity and a young and dynamic population, Algeria’s positive economic indicators are certain to improve even further with the desired membership it seeks in the BRICS organization. Given these considerations, it follows that South Africa as well as Algeria possess the potential to serve as locomotives for the development of the whole of Africa.
Clinical Management of Familial Hypercholesterolemia in Children
Authors: Widhalm Kurt , Fallmann Karin 
Published: July 2024

Abstract:
Familial Hypercholesterolemia (FH) is one of the best-characterized inborn errors of
metabolism, with an estimated prevalence of 1:250 in the general population. Only approximately
10% of the affected subjects are diagnosed and, therefore, under medical care, including drug therapy
or, in severe cases, apheresis. Screening at the age of 6-10 years would be useful and cost-effective.
There is enough evidence that children and adolescents with FH should be treated in order
to reduce elevated Total cholesterol and LDL-c levels and, therefore, avoid the risk of early cardiovascular
diseases.
As FH was described more than 130 years ago, it is surprising that the knowledge of that very important
metabolic disorder is insufficient. The present report describes clinical and pathophysiological
characteristics and nutritional and medical therapies in children with familial hypercholesterolemia.
Pharmacognostic, Phytochemical, Ethnobotanical, and Pharmacological Significance of Silybum marianum (Milk Thistle) – A Comprehensive Review
Authors: Divya Surisetti , Singh Neha , Dixit Ritik , Jaiswal Vaibhavi , -- shiva , Yadav Esha 
Published: July 2024

Abstract:
Milk thistle seeds contain silymarin, a powerful hepatoprotective compound known to
shield liver cells from toxins, increase glutathione levels, and promote cell regeneration. Silybin,
one of the key components of silymarin, is highly valued by herbalists due to its minimal side effects.
Silymarin is ubiquitously distributed across diverse geographic regions, encompassing Europe,
Africa, Asia, Australia, North and South America, India, and China. Silymarin comprises an
array of compounds, specifically silydianin, isosilybin A, isosilybin B, silybin A, and silydianin
flavonoids. Its pharmacological applications are multifaceted, including antidiabetic, hepatoprotective,
hypocholesterolemic, antihypertensive, anti-inflammatory, anticancer, and antioxidant properties.
Milk thistle seeds additionally exhibit anti-spasmodic, neuroprotective, antiviral, immunomodulant,
and cardioprotective characteristics. They can even enhance milk secretion and help treat
uterine disorders. Such an in-depth inquiry is poised to facilitate the meticulous assessment by researchers
of its efficacy in therapeutic applications. Additionally, silymarin exhibits changes in cellular
transporter, P-glycoprotein, as well as estrogenic and nuclear receptors. It also impedes apoptosis
and follicular development during in vitro fertilization, making it a promising option in complementary
medicine. This documented evidence is useful in safeguarding vital organs against an
array of maladies, encompassing cancer, in vitro fertilization, hepatotoxicity, nephrotoxicity, viral
hepatitis challenges, neurotoxicity, depressive disorders, and pulmonary and prostate disorders.
This scholarly article undertakes a comprehensive exploration of the pharmacognostic, morphological,
ethnobotanical, and pharmacological importance of Silybum marianum.
Analisis kuat tekan dan penyerapan air batu bata ditinjau dari berbagai lama pembakaran
Authors: T Panennungi , Rauf Bakhrani A. Rauf A. 
Published: July 2024

This research aims to describe: compressive strength of M-5a module, water absorption, and compressive strength difference 7, 9, and 11 days furnace duration. The methods are: making brick which is composed by 1 of rice husk and 3 of clay to 120 bricks, dehydrating on sunlight for 7 days, then going furnace for 7, 9, and 11 days, examining to compressive strength and water absorption each 20 bricks of 7, 9, and 11 days furnace. The result: average of compressive strength of M-5a module 7 days furnace is 35,80 kg/cm2, 9 days is 37,30 kg/cm2, 11 days is 39,30 kg/cm2, average of water absorption of M-5a module 7 days furnace is 22,96 %, 9 days is 21,50 %, and 11 days is 19,25 %, and no significant difference on compressive strength average amongs module of M-5a on 7 days, 9 days, and 11 days furnace duration.
Consequences of Data Loss on Clinical Decision-Making in Continuous Glucose Monitoring: Retrospective Cohort Study
Authors: den Braber Niala , Braem Carlijn I R , Vollenbroek-Hutten Miriam M R , Hermens Hermie J , Urgert Thomas , Yavuz Utku S , Veltink Peter H , Laverman Gozewijn D 
Published: July 2024

Background
The impact of missing data on individual continuous glucose monitoring (CGM) data is unknown but can influence clinical decision-making for patients.

Objective
We aimed to investigate the consequences of data loss on glucose metrics in individual patient recordings from continuous glucose monitors and assess its implications on clinical decision-making.

Methods
The CGM data were collected from patients with type 1 and 2 diabetes using the FreeStyle Libre sensor (Abbott Diabetes Care). We selected 7-28 days of 24 hours of continuous data without any missing values from each individual patient. To mimic real-world data loss, missing data ranging from 5% to 50% were introduced into the data set. From this modified data set, clinical metrics including time below range (TBR), TBR level 2 (TBR2), and other common glucose metrics were calculated in the data sets with and that without data loss. Recordings in which glucose metrics deviated relevantly due to data loss, as determined by clinical experts, were defined as expert panel boundary error (εEPB). These errors were expressed as a percentage of the total number of recordings. The errors for the recordings with glucose management indicator <53 mmol/mol were investigated.

Results
A total of 84 patients contributed to 798 recordings over 28 days. With 5%-50% data loss for 7-28 days recordings, the εEPB varied from 0 out of 798 (0.0%) to 147 out of 736 (20.0%) for TBR and 0 out of 612 (0.0%) to 22 out of 408 (5.4%) recordings for TBR2. In the case of 14-day recordings, TBR and TBR2 episodes completely disappeared due to 30% data loss in 2 out of 786 (0.3%) and 32 out of 522 (6.1%) of the cases, respectively. However, the initial values of the disappeared TBR and TBR2 were relatively small (<0.1%). In the recordings with glucose management indicator <53 mmol/mol the εEPB was 9.6% for 14 days with 30% data loss.

Conclusions
With a maximum of 30% data loss in 14-day CGM recordings, there is minimal impact of missing data on the clinical interpretation of various glucose metrics.

Trial Registration
ClinicalTrials.gov NCT05584293; https://clinicaltrials.gov/study/NCT05584293