bluuebunny/crossref_metadata_2025_split huggingface dataset:
CFD and experimental analysis of greenhouse climate and plant comfort in mediterranean regions: impact of crop presence and time variations
Authors: Zghal Olfa , Ketata Ahmed , Abid Hasna , Zouari Slim , Gugliuzza Giovanni , Mejri Maroua , Arrabito Emilia , Driss Zied 
Published: February 2025

Abstract

This study investigates indoor climate dynamics within a large-scale soilless greenhouse in Manouba, northern Tunisia, examining the effects of daily environmental variations. By combining experimental and numerical methods, it analyzes how factors such as glazing, ventilation, crop type, and concrete surfaces influence indoor climate conditions. The study validated a numerical model’s accuracy, particularly for temperature profiles, by comparing its outputs with experimental data. To ensure reliability, the model underwent rigorous testing, including grid independence analysis, incorporation of turbulence and radiation models, and optimization to reflect external conditions accurately. Simulations were run with and without crops, showing that the presence of crops raised temperatures by approximately 1 K for lettuce and 2.2 K for tomato, emphasizing the importance of crop optical properties and transpiration on temperature distribution and ventilation. Temperature patterns within the greenhouse varied, with a 1.2% drop in the center between 13 h and 16 h and a 2.4% increase from 9 h to 13 h. Ground-level temperatures were the highest, largely due to solar radiation. The study established a strong correlation to predict indoor temperature changes in response to external factors, accounting for conditions with and without crops. Additionally, the research addresses thermal comfort indicators like vapor pressure deficit (VPD), offering insights into optimal climate management across different crop scenarios. The findings provide valuable guidance for greenhouse engineers on temperature distribution, suggesting effective sensor placement, monitoring techniques, and control strategies to improve greenhouse performance and crop yield.
Integrative Multi-omics Analysis and Mendelian Randomization
Reveal Potential Therapeutic Targets and their Stratification in Lung
Squamous Cell Carcinoma
Authors: Chen Youpeng , Li Enzhong , Chang Zhenglin , Xie Yifei , Chen Xiaoyi , Sun Junquan , Lai Xuntao , Cheng Zhangkai J. , Sun Baoqing 
Published: February 2025

Background:
Lung Squamous Cell Carcinoma (LUSC), a major subtype of non-small cell lung cancer, presents significant treatment challenges due to limited targeted therapy options. This study aims to identify novel therapeutic targets to improve therapeutic
strategies for LUSC.

Methods:
By employing bulk RNA sequencing, Weighted Gene Co-expression Network
Analysis (WGCNA), survival analysis, and Mendelian Randomization (MR), we pinpointed
genes with prognostic relevance to LUSC. These genes were further scrutinized for their
therapeutic potential through LASSO regression, Protein-Protein Interaction (PPI) network
analysis, and immune infiltration assessments. To delve into the roles and cell-specific expressions of these genes within the LUSC microenvironment, pathway enrichment analysis,
single-cell RNA sequencing (scRNA-seq), and pseudotime analysis were conducted.

Results:
Our integrative approach identified 23 prognostically significant therapeutic targets, categorized into tier-one, tier-two, and tier-three genes based on their potential therapeutic relevance. Functional enrichment analyses highlighted the significant role of these
genes in immune response regulation, particularly in T-cell receptor signaling and the complement system. scRNA-seq analysis revealed cell-type-specific expression patterns and
pseudotime analysis provided insights into cellular heterogeneity and developmental trajectories in LUSC.

Conclusions:
In this study, we identified 3 tier-one genes (MCM6, C4B, CTC-463A16.1), 7
tier-two genes (C4A, HLA-DRB9, LIMS2, LINC00654, MYO7B, SIGLEC5, TIE1), and 13
tier-three genes (AC007743.1, AC147651.4, ALDH2, BTN3A2, BTNL9, CCR1, GIPC3,
HLA-DQB1, ICAM5, LIMD1, PM20D1, RP11-302L19.3, RP11-768F21.1).
Skin Aging: Insights into the Role of Fatty Acids
Authors: Kshirsagar Snehal , Thomas Asha , Deshkar Sanjeevani , Kothapalli Lata , Borhade Trupti , Chitlange Sohan , Sanap Avinash , Bhonde Ramesh 
Published: February 2025

Abstract:
The human skin, being the largest organ, provides defense against bacteria, toxins, and ultraviolet radiation.
The skin may experience changes like dryness, photodamage, oxidative damage, and inflammation.
This review explores sources of fatty acids and how they can prevent skin damage, with the goal of determining
their potential for preventing skin aging. The role and significance of various mechanistic pathways and
molecular targets involved in skin aging are highlighted. By using current research findings, this review contributes
to a comprehensive understanding of how fatty acids may serve as a proactive approach to promoting
youthful skin and mitigating the signs of skin aging. In addition to treating specific skin conditions, nutraceuticals
offer immense potential to minimize, postpone, or prevent premature skin aging. The substances that are
most frequently employed include carotenoids, polyunsaturated fatty acids, plant polyphenols, bioactive peptides,
oligosaccharides, and vitamins. Numerous human trials have demonstrated the impact of supplementing
with these items on indicators of aging. The most pertinent clinical and non-clinical investigations are assessed
in this review. Based on the comprehensive understanding of the significant role of fatty acids in addressing
skin aging, this review may open doors and offer avenues for future explorations.
Untargeted Metabolomics Analysis of Vaginal Secretion Reveals Potential Pathogenesis of Atrophic Vaginitis
Authors: Zhang Chenyun , Ren Yali , Li Jiaxiong , Wang Guanghua , Ma Jiehua , Qiu Jin 
Published: February 2025

Introduction:
Atrophic vaginitis (AV) is a common and frequently occurring disease, lacking effective
curative measures. Exploring the mechanism of vaginal mucosal homeostasis from the perspective of
metabolites has great research prospects.

Methods:
We compared the metabolic profiles of vaginal secretions between AV patients and healthy individuals
via liquid chromatography-tandem mass spectrometry (LC-MS/MS). We further explored effective
and sensitive metabolites and metabolic pathways for senile vaginitis through bioinformatics analysis and experimental
verification. Through untargeted metabolomics analysis, we screened 561 differential metabolites
in two groups of vaginal secretion samples. These differential metabolites were mainly concentrated in fatty
acids/carboxylic acids, glycerophospholipids, organic oxides, steroids, and their derivatives. They were mainly
enriched in purine metabolism, diabetic cardiomyopathy generation, and choline metabolism pathways.

Results:
The receiver operating characteristic analysis showed the metabolites (e.g., guggulsterone, umbelliprenin,
and inosinic acid) to have good discrimination ability for the AV group. In addition, we also explored
the potential mechanism of action of umbelliprenin at the cellular level.

Conclusion:
This study is expected to provide a new perspective for understanding the relationship between
metabolites and the pathogenesis of AV.
Potential Alteration of Rifampicin’s Bioavailability by Phyllanthus niruri Supplementation in Tuberculosis Therapy
Authors: Ardana Mirhansyah , Laksitorini Marlyn Dian , Lukitaningsih Endang , Nugroho Agung Endro 
Published: February 2025

Abstract:
Rifampicin is essential for treating TB. The high incidence of resistance to this drug requires efforts to increase the effectiveness of TB therapy. Immunomodulator supplementation is one effort to overcome this problem. Phyllanthus niruri has an immunomodulating effect, which has been proven to influence the clinical improvement of the immunological profile. However, the effect of this plant on rifampicin’s bioavailability should be reviewed to determine potential changes that may affect its antibacterial performance. Several stud-ies have shown an increase in the bioavailability of rifampicin when administered with extracts and active isolates of Carum carvi, Cuminum cyminum, Piper nigrum, and Moringa oleifera through inhibition of the P-gp efflux function in the absorption phase. On the other hand, the decrease occurred in coadministration with Garcinia cola, which activated PXR action and subsequently changed P-gp regulation. Administration of Al-lium sativum and Zingiber officinale extracts did not show significant alteration in bioavailability due to the stimulation of several mechanisms with opposite outputs by each secondary metabolite. In the case of P. niruri supplementation, the potential for a rise in bioavailability could occur due to synergistic effects inhibiting the performance of P-gp, AADAC, and OATP1B. However, the stimulation of PXR and PPARα may reduce or eliminate these effects. Finally, considering that there are so many specific secondary metabolites in P. niruri whose effects on the performance of these functional proteins have not been exposed, in vivo studies are needed to confirm the interactions within complex biological systems.
The Role of Renin-Angiotensin System in Diabetic Nephropathy: An Update
Authors: Sanglard André , Castello Branco Miranda Bárbara , França Vieira Ana Luiza , Miranda Macedo Marcus Vinicius , Lara Santos Rodrigo , Stenner Rodrigues Radicchi Campos Aléxia , Campos Piva Amanda , Simões e Silva Ana Cristina 
Published: February 2025

Background and Aims:
Diabetic nephropathy (DN) is an important complication of diabetes,
leading to end-stage renal disease (ESRD) worldwide. This review aimed to explore the role
of the renin-angiotensin system (RAS) in DN, highlighting current treatments and emerging therapeutic
perspectives.

Methods:
We conducted a narrative review of the literature up to March 2024, focusing on the classical
and alternative RAS axes, their implications in DN, and novel therapeutic approaches. Data
were sourced from Scopus, PubMed, Scielo, and Cochrane databases.

Results:
The classical RAS axis, involving angiotensin-converting enzyme (ACE), Angiotensin II
(Ang II), and the AT1 receptor, promotes vasoconstriction, sodium retention, and fibrosis in DN.
Hyperglycemia-induced Ang II increases oxidative stress, contributing to glomerular hyperfiltration
and kidney damage. Current treatments include ACE inhibitors and angiotensin receptor blockers
(ARBs), which reduce blood pressure and proteinuria, delaying DN progression. In contrast, the
alternative RAS axis, featuring ACE2, Ang-(1-7), and the Mas receptor, offers renoprotective effects
by counteracting Ang II actions. Ang-(1-7) reduces inflammation, fibrosis, and podocyte apoptosis.
ACE2 activators, Ang-(1-7), and Mas receptor agonists show promise in preclinical studies,
reducing glomerular fibrosis and improving renal function. Ang-(1-9) and alamandine may also hold
potential in future treatments. Emerging therapies, such as the SGLT2 inhibitors, also demonstrate
benefits in reducing DN progression.

Conclusion:
While ACE inhibitors, ARBs, and SGLT2 inhibitors remain central to DN management,
the ACE2-Ang-(1-7)-Mas axis presents a promising therapeutic target. Future research should focus on
translating preclinical findings into clinical applications, potentially improving DN treatment.
Translational Informatics Driven Drug Repositioning for Neurodegenerative Disease
Authors: Zheng Xin , Chen Jing , Zhang Yuxin , Hu Shanshan , Bi Cheng , Singla Rajeev K. , Kamal Mohammad Amjad , Horimoto Katsuhisa , Shen Bairong 
Published: February 2025

Abstract:
Neurodegenerative diseases represent a prevalent category of age-associated diseases. As
human lifespans extend and societies become increasingly aged, neurodegenerative diseases pose a
growing threat to public health. The lack of effective therapeutic drugs for both common and rare
neurodegenerative diseases amplifies the medical challenges they present. Current treatments for these
diseases primarily offer symptomatic relief rather than a cure, underscoring the pressing need to
develop efficacious therapeutic interventions. Drug repositioning, an innovative and data-driven approach
to research and development, proposes the re-evaluation of existing drugs for potential application
in new therapeutic areas. Fueled by rapid advancements in artificial intelligence and the burgeoning
accumulation of medical data, drug repositioning has emerged as a promising pathway for
drug discovery. This review comprehensively examines drug repositioning for neurodegenerative
diseases through the lens of translational informatics, encompassing data sources, computational
models, and clinical applications. Initially, we systematized drug repositioning-related databases and
online platforms, focusing on data resource management and standardization. Subsequently, we classify
computational models for drug repositioning from the perspectives of drug-drug, drug-target,
and drug-disease interactions into categories such as machine learning, deep learning, and networkbased
approaches. Lastly, we highlight computational models presently utilized in neurodegenerative
disease research and identify databases that hold potential for future drug repositioning efforts. In the
artificial intelligence era, drug repositioning, as a data-driven strategy, offers a promising avenue for
developing treatments suited to the complex and multifaceted nature of neurodegenerative diseases.
These advancements could furnish patients with more rapid, cost-effective therapeutic options.
Impact of Polyphenol-Rich Chocolate on Microbial Diversity and Human Health: A Comprehensive Review
Authors: Chatterjee Ayan , Chatterjee Parna , Irani Rukshana , Ghosh Sourav , Basu Biswajit , Prajapati Bhupendra 
Published: February 2025

Background:
Compared to many other foods, cocoa and chocolate stand out for their
high concentrations of polyphenols, particularly catechins, anthocyanidins, and procyanidins. These
compounds possess antioxidant, anti-inflammatory, and vasodilatory properties that can confer
multiple health benefits. This present study has been undertaken to assess the effects of polyphenol-
rich chocolate consumption on various aspects of human health, including mood, cognition,
cardiovascular health, insulin sensitivity, immune function, gut microbiota, and cancer risk.
The high polyphenolic content in dark chocolates improves endothelial function, inhibits platelet
aggregation, lowers blood pressure, enhances insulin sensitivity, etc. Cocoa polyphenols have
been found to augment cognitive performance due to their ability to modulate gut microbiota. Potential
antidepressant and anticarcinogenic activities were also reported.

Objective:
The present study aimed to identify the impact of polyphenol-rich chocolate on human
health.

Methods:
Electronic searches were carried out using the databases viz. Google, Google Scholar,
and PubMed for the study. The search was restricted for a period of 48 years, ranging from 1980 -
2022, to make it more systematic and concise. The obtained research and review articles were thoroughly
studied and analyzed to present a comprehensive review.

Findings:
The findings of the present study mainly focus on the impact of polyphenols on human
health, especially cognitive status. Evidence indicates that polyphenol-rich dark chocolate might
offer numerous advantages for cardiovascular and metabolic health, but its effects on cognition,
mental health, gut microbiota, and cancer risk need to be studied further. More research, including
animal experiments and human trials, is needed to understand the health impact and optimal
dosages of dark chocolate. Understanding chocolate’s therapeutic benefits can open new avenues
for human well-being.

Conclusion:
The complex relationship between chocolate and emotion via the gut-brain axis has
been discussed. From the momentary sensory pleasures to the intriguing interplay between cravings
and comfort-seeking behaviors, chocolate has a unique place in the realm of emotional indulgence.
A Graphlet-based Explanation Generator for Graph Neural Networks Over Biological Datasets
Authors: Cetin Selinay , Sefer Emre 
Published: February 2025

Background:
Graph neural networks’ (GNNs) explainability, especially the explanation
of edges and interactions among vertices in GNNs, is demanding mainly owing to dynamics and
groupings between vertices. The existing graph explainability methods ignore the analysis of the following
tasks weights over subgraphs but instead analyze solely sample-level explainability. Such
sample-level explainability decreases their generalizability since it directly searches the explaining
behaviour in the input dataset.

Objective:
In this study, we come up with a novel Orbit-based GNN explainer (OExplainer), which
integrates both sample-level and method-level approaches over a predetermined set of subgraphs. As
part of such analysis of subgraphs, our goal is to interpret graphs more comprehensively and intelligibly
while providing each vertex’s explainability score for a particular graph instance.

Methods:
Our OExplainer decomposes the following graph neural network weights into explaining
subgraph bases while identifying and characterizing particular predictions. By such characterization,
we can carefully and accurately interpret the predetermined graph orbit’s role in vertex representation
determination. In this characterization, we can also clarify the method’s behaviour generally for
the whole input dataset. Moreover, we come up with novel vertex-specific scores in our subgraphbased
approach over nonisomorphic graphlets. Such vertex-specific score encourages sample-level
vertex improvement, and such improvement is related to the graph neural network’s vertex classification
task.

Results:
Our experiments over simulated datasets confirm the importance and criticality of method
weights in vertex classification explanation. In this case, method weight decomposition also has criticality.
Our detailed experiments over multiple real protein-protein interaction datasets and metabolic
interaction networks also exhibit enhanced performance in vertex classification.

Conclusion:
In both simulated and biological protein-protein interaction datasets, our approach outperforms
the competing explanation approaches
Sweroside Modulates Oxidative Stress and Neuroplasticity-Related Gene Expression in Scopolamine-Treated Zebrafish
Authors: Brinza Ion , Stache Bogdan Alexandru , Mihasan Marius , Gorgan Dragos Lucian , El Raey Mohamed A. , El-Kashak Walaa , Eldahshan Omayma A. , Hritcu Lucian 
Published: February 2025

Background:
A major issue with neurodegenerative diseases is cholinergic depletion, the
development of oxidative stress, and the reduction in the ability to control the expression of genes
involved in the regulation of neurogenesis. The most widespread neurodegenerative disease is
Alzheimer's disease (AD). Current treatments are not able to improve the symptoms of the disease.
Thus, selecting or creating a safe and effective drug is very important.

Objective:
In this context, the potential of sweroside (Swe) to regulate acetylcholinesterase (AChE)
activity, malondialdehyde (MDA) level, and bdnf, npy, egr1, nfr2a, and creb1 gene expression in
the scopolamine (Sco)-induced zebrafish model of cognitive impairment was investigated.

Methods:
Swe was administered daily for 16 days chronically to zebrafish at concentrations of
1 μg/L, 3 μg/L, and 5 μg/L whereas Sco (100 μM) was given to zebrafish for 30 min.

Results:
Exposure to Swe decreased AChE activity and MDA level along with upregulating of gene
expression in the brain of the Sco-induced zebrafish model.

Conclusion:
Overall, our findings suggested that Swe has a positive role in the cholinergic system
activity and brain antioxidant status and showed for the first time that it can restore the downregulated
expression of bdnf, npy, egr1, nfr2a, and creb1 genes in the brain of the Sco-induced zebrafish
model.
A Comprehensive Review on the Botany, Ethnomedicinal Uses, and Pharmacological Effects of Aquilaria sp. Found in Malaysia
Authors: Ong Sheng Wei , Yong Kien Thai , Tan Phui Yee , Low Ying Chiang , Tang Pei Ling , John Oliver Dean , Goh Carolyn , Tan Sheri-Ann 
Published: February 2025

Abstract:
The genus Aquilaria is widely distributed in the rainforest of Indomalesia region with the
existence of 20 different species. There are five species native to Malaysia: Aquilaria beccariana
Teigh., A. hirta Ridl., A. malaccensis Lam., A. microcarpa Baill, and A. rostrata Ridl. In recent
years, three non-native Aquilaria species have been introduced to Malaysia: A. crassna Pierre ex
Lecomte, A. subintegra Ding Hou, and A. sinensis (Lour) Sprengel. Aquilaria genus has often been
associated with the production of agarwood oil, a commodity of high economic value, as it is an
important ingredient in perfumes, incense, and traditional medicines. Nevertheless, besides agarwood
oil, the different parts of the tree itself, which include the bark and leaves, are used by traditional
healers to treat skin infection, diarrhoea, constipation, and even rheumatism. In view of that,
numerous research studies have begun exploring the potential uses of the by-products of agarwood
cultivation. This review focuses on the Aquilaria species found in Malaysia regarding their botany,
traditional uses, and also pharmacological effects. The phytochemical and pharmacological
evaluations of these plant species revealed a range of bioactive compounds that contributed to their
beneficial effects, such as antidiabetic, antimicrobial, and anticancer properties.
A Novel Optical Diagnostic Tool for Fuel Characterization in the Spark Ignition Chamber
Authors: Biswas Rajib 
Published: February 2025

Background:
The Spark Ignition chamber plays a very vital part in internal combustion
engines.

Objective:
In line with this, this short communication dwells upon a novel probing technique that
employs high-speed cameras and a fiber endoscope-based particle velocimeter.

Methods:
The flame propagation and combustion characteristics vary greatly depending on the
fuel type and air mixture, which can be examined using a variety of probing techniques.

Results:
The proposed scheme can give valuable information on flame propagation features, fuel
concentration, and particle velocity, which, either way, is able to optimize the performance of
combustion engine

Conclusion:
The addition of machine learning will ease the process of data acquisition as well as
their effective management in enhancing the optimality of the internal combustion engine. It is
envisioned that the novel design would pave the way for more research in this direction.