bluuebunny/crossref_metadata_2025_split huggingface dataset:
BioPathNet: Enhancing Link Prediction in Biomedical Knowledge Graphs through Path Representation Learning
Authors: marsico Annalisa , Hu Yue , Oleshko Svitlana , Firmani Samuele , Zhu Zhaocheng , Cheng Hui , Ulmer Maria , Arnold Matthias , Colome-Tatche Maria , Tang Jian , Xhonneux Sophie 
Published: September 2024

Abstract

Understanding complex interactions in biomedical networks is crucial for advancements in biomedicine, but traditional link prediction (LP) methods are limited in capturing this complexity. Representation-based learning techniques improve prediction accuracy by mapping nodes to low-dimensional embeddings, yet they often struggle with interpretability and scalability.
We present BioPathNet, a novel graph neural network framework based on the Neural Bellman-Ford Network (NBFNet), addressing these limitations through path-based reasoning for LP in biomedical knowledge graphs. Unlike node-embedding frameworks, BioPathNet learns representations between node pairs by considering all relations along paths, enhancing prediction accuracy and interpretability. This allows visualization of influential paths and facilitates biological validation.
BioPathNet leverages a background regulatory graph (BRG) for enhanced message passing and uses stringent negative sampling to improve precision. In evaluations across various LP tasks, such as gene function annotation, drug-disease indication, synthetic lethality, and lncRNA-mRNA interaction prediction, BioPathNet consistently outperformed shallow node embedding methods, relational graph neural networks and task-specific state-of-the-art methods, demonstrating robust performance and versatility. Our study predicts novel drug indications for diseases like acute lymphoblastic leukemia (ALL) and Alzheimer’s, validated by medical experts and clinical trials. We also identified new synthetic lethality gene pairs and regulatory interactions involving lncRNAs and target genes, confirmed through literature reviews. BioPathNet's interpretability will enable researchers to trace prediction paths and gain molecular insights, making it a valuable tool for drug discovery, personalized medicine and biology in general.
Implicit time discretisation as a potential avenue to achieve full coupling between shallow water flow and bedload transport
Authors: Utz Martin , Stadler Leopold , Flemisch Bernd 
Published: September 2024

Abstract

In general, modelling bedload transport requires a full coupling between shallow water equations and sediment balance equations. Nevertheless, in some cases a splitting approach can be applied, depending on the flow state and the degree of interaction between flow and bed topography. This work employs an implicit time discretisation to implement both a fully coupled and a splitting approach. The currently available approaches utilise an appropriate calculation of the numerical flux at the cell faces, e.g. Roe’s scheme, in order to ensure a full coupling. However, this work demonstrates that a fully coupled approach can also be achieved through an implicit time discretisation, as it combines the shallow water and the sediment balance equations into a system of non-linear equations, thereby ensuring full coupling between shallow water flow and bedload transport. The full coupling via implicit time discretisation has the advantage of being applicable to arbitrary bedload transport problems. In contrast, the existing fully coupled approaches are only applicable to uniform bedload transport and are not suitable for mixed size bedload transport with several grain classes or in situations where modifications to the bedload discharge rate are required, such as secondary currents or gravitational transport. Furthermore, this work compares the two presented coupling approaches in terms of computational cost and with regard to the applicability of the splitting approach. The comparison indicates that, where applicable, the splitting approach often offers a superior performance compared to the presented fully coupled approach, particularly in cases involving several grain classes.
Family Justice Involvement in Evidence-Based Home Visiting: Understanding Home Visitor Perceptions and Practices
Authors: Jackson Dylan B. , Oppenheim Shoshana , Shlafer Rebecca , Fauth Rebecca C. , West Allison 
Published: September 2024

Abstract

Evidence-Based Home Visiting (EBHV) is a promising service strategy to promote parent and child health and well-being among families who are justice-involved (JI), such as those in which parents are or have recently been incarcerated, under community supervision, or awaiting or undergoing trial. However, few studies have assessed the capacity of EBHV programs to adequately acknowledge, support, and meet the needs of JI families. The aim of the present study was to examine home visitor (HV) practices, implementation supports (e.g., policies and procedures, curriculum supports), and perceptions of program strength and benefits for parents in JI families. HVs were recruited to participate in a web-based survey using a national practice-based research network (PBRN) – the Home Visiting Applied Research Collaborative (HARC). Findings from our sample of HVs (n = 211) indicated that nearly two-thirds (63.03%) had served JI families, with most having served these families within the 12 months prior to the survey. Supervisor support was significantly and positively associated with HV practices (e.g., screening, modify content of visits) pertaining to JI families, yet cognitive barriers to addressing JI (e.g., belief that discussing JI will ruin trusting relationship, lead to family drop out) were significantly and negatively associated with these practices. HVs’ perceptions of their program’s strengths and benefits for JI families were linked to many implementation supports, as well as HV knowledge and self-efficacy. Additional research is needed to better understand and enhance home visiting services for parents in JI families.
An in-depth Investigation into the Performance of State-of-the-Art zero-shot, single-shot, and few-shot Learning Approaches on an Out-of-Distribution Zero-Day Malware Attack Detection
Authors: Ige Tosin , Kiekintveld Christopher , Piplai Aritran , Wagler Amy , Kolade Olukunle , Matti Bolanle Hafiz 
Published: September 2024

Abstract

N-shot learning has emerge in recent year as potential learning approach to solve the problem of data scarcity by learning underlying pattern from a few training sample. Despite recent state-of-the-art research on model-agnostic metal learning, transfer learning, and optimization strategy to rapidly learn valid information from few sample, there remains a big challenge on an actual out-of-distribution zero-day without any similarity to previously known malware family or new variant of an existing malware family. This ultimately questions the effectiveness of current state-of-the-art few-shot learning approach. In this research, we did an in-depth investigation into the performance of state-of-the-art Zero-shot, Single-shot, and few-shot learning approaches on zero-day out-of-distribution malware attack detection based on their static properties using Malimg and Malevis malware dataset. We ensure our model was aware of an out-of-distribution class during training while varying the number of samples in the out-of-distribution class accordingly zero-shot(no sample), single-shot (1 sample), few-shot(5 samples) while using confusion matrix to get the actual number of correct prediction on out-of-distribution malware validation samples. we assert that the model should be smart enough to detect and classify previously unseen data into an empty family as an out-of-distribution considering that the model was made to be aware of the existence of such distribution during training. Result shows 0, 0, and 3 correct out-of-distribution predictions on Zero-shot, single-shot, and few-shot experiments respectively, thereby showing limitation of the current state-of-the-art N-shot approaches on out-of-distribution attack.
Assessing changes in intra- and inter-annual precipitation variability using advanced statistical inference techniques
Authors: Moreira Elsa Estevão , Augusto Vítor 
Published: September 2024

ABSTRACT
Aiming to find statistically significant changes on the usual monthly weather conditions in Alentejo, Portugal, in the past 40 years, time series of precipitation from a grid of locations in Alentejo were studied using an unconventional approach. The time series were divided into 4 decades and disposed in contingency tables with two factors, Year and Month. Then, log-linear models were fitted to those tables. The model deviances for Year and Month represent the weight of each factor in explaining precipitation variability and Year:Month deviance is an estimate of the lack of independence between both factors, representing changes in intra-annual precipitation variability. The set of all the models deviances, per decade and location, were analysed using ANOVA techniques, first to compare the four decades, then to perform a crossed comparison between decades and between four pre-defined zones. Results indicate significant differences between the oldest and recent decades in terms of intra-annual precipitation variability, which could be interpreted as a trend towards softening the differences in precipitation between the wet months of the year. Furthermore, two homogeneous sub-regions could be defined in Alentejo, a large interior region and a smaller one close to the Atlantic Ocean.
Huopuxialing Decoction: A Promising Candidate for Precancerous Lesions of Gastric Cancer Treatment Based on Bioinformatics and Experimental
Verification
Authors: Wang Jianghong , Wang Xiaoyuan , Song Yanru , Huang Zilin , Wu Han , Chang Liang , Huo Bingjie , Fan Guanwei 
Published: September 2024

Background:
The Precancerous Lesion of Gastric Cancer (PLGC) is an early stage in
the development of gastric cancer. The clinical application of HPXLD has been found to be effective
in treating PLGC, but the mechanism of how HPXLD acts on PLGC is still unclear.

Objective:
The objectives of this study were to reveal the molecular mechanism of how HPXLD
can be used to treat PLGC and investigate this mechanism through bioinformatics and experimental
validation.

Methods:
PLGC-associated target genes were identified through bioinformatics analysis. A rat
model of PLGC was induced using N-methyl-N'-nitro-N-nitrosoquanidine (MNNG) in combination
with ranitidine, hot saline, ethanol, and intermittent fasting, with interventions by HPXLD.
The pathological alterations in gastric mucosa were assessed through Hematoxylin-eosin staining
(HE). Immunohistochemistry (IHC) and Western blot analyses were employed to evaluate the
changes in expression levels of inflammation-related proteins.

Results:
After conducting bioinformatics analysis, it was found that there were 23 HPXLDPLGC
crossover genes, which were significantly enriched in the IL-17 signaling pathway, TNF
signaling pathway, and NF-kappa B signaling pathway. The results of HE showed that HPXLD
was effective in improving gastric mucosal histopathological changes. Additionally, the IHC results
demonstrated that HPXLD was able to downregulate the expression of IL-6, COX-2, MCP-
1, and MMP-9. Furthermore, Western blot analysis revealed that HPXLD was able to downregulate
the expressions of IL-6, IL-17RA, ACT1, NF-κB, and TNF-α.

Conclusion:
HPXLD has been shown to improve PLGC by reducing the expression of inflammation-
related proteins. This suggests that HPXLD may potentially be a treatment option for
PLGC.
Investigation of the Mechanism of Siweixizangmaoru Decoction in Improving CIA-Induced Arthritis in Rats Based on Network Pharmacology
and Experimental Verification
Authors: Niu Yanfei , Yuan Yanxiang , Wang Tong , Yuan Ruiying , Zhang Min , Wang Sicen , Tsering Dikye , Huang Shan , Li Bin 
Published: September 2024

Background:
Rheumatoid Arthritis (RA) is a chronic autoimmune disease with a
complex etiology. Siweixizangmaoru Decoction (SXD) has been used to treat RA in Tibet for a
long history as a classic Tibetan medicine formula. However, the potential pharmacological
mechanism has not been elucidated yet.

Aims:
The aim of this study was to evaluate the efficacy and mechanism of action of SXD in the
treatment of RA using network pharmacology and molecular docking analysis.

Method:
Network pharmacology was employed to identify the potential bioactive components
and key targets of SXD for the treatment of RA. Molecular docking of key targets and potential
compounds was conducted. High-performance liquid chromatography was performed to validate
the predicted active components of SXD. We established a rat model of RA and evaluated the
histopathology of each group of rats. In addition, the levels of inflammatory factors in serum and
the expression levels of PI3K/AKT and MAPK pathway-related proteins in synovial tissue were
detected.

Results:
The results of network pharmacological analyses indicated that apigenin, rhamnolipids,
kaempferol, quercetin, and naringenin are potential bioactive components of SXD for the treatment
of rheumatoid arthritis and that their therapeutic effects may be related to the PI3K-Akt
and MAPK pathways. The results of in vivo experiments show that SXD improved the arthritis
index, significantly reduced joint swelling, and improved synovial inflammation and cartilage
destruction.

Conclusion:
Network pharmacology, along with experimental validation, provided a useful approach
for understanding the pharmacological mechanism of Siweixizangmaoru decoction in
RA.
Ferulic Acid Regulates GSDMD through the ROS/JNK/Bax Mitochondrial Apoptosis Pathway to Induce Pyroptosis in Lung Cancer
Authors: Liu Xingchen , Zhang Xin , Mi Lida , Zhang Hailin , Shi Woda 
Published: September 2024

Background:
To improve the prognosis outcome of lung cancer patients, more investigations
are still needed. Previous reports have demonstrated the function of Ferulic Acid (FA)
in lung cancer; thus, we have attempted to probe more molecular mechanisms underlying FA
application in lung cancer.

Methods:
CCK8 and colony formation experiments have been employed to explore cell viability
and proliferation. Cell apoptosis was evaluated through flow cytometry. Cell morphology was
observed with a microscope. MMP was assessed by JC-1 and LDH activity was evaluated by
relative kit. Western blot assays were performed to examine the expression levels of GSDMD,
GSDMD-N, caspase family proteins, and ROS/JNK/Bax mitochondrial apoptosis pathway
downstream proteins. Flow cytometry analysis also measured the level of ROS. Tissues from
animal models were taken for IHC analysis of C-caspase-1.

Results:
FA was found to inhibit proliferation, change cell morphology, decrease MMP, and
enhance LDH activity, suggesting its ability to induce pyroptosis of lung cancer cells. Both
caspase-1 and GSDMD were found to be involved in the pyroptosis of lung cancer cells treated
with FA, and caspase-1 mediated GSDMD. Moreover, FA was validated to regulate pyroptosis
by ROS/JNK/Bax mitochondrial apoptosis pathway in vitro and in vivo.

Conclusion:
In summary, FA regulates GSDMD through ROS/JNK/Bax mitochondrial apoptosis
pathway to induce pyroptosis in lung cancer cells, which may offer a theoretical basis for
pyroptosis in the occurrence of lung cancer.
Lignin Nanoparticles as pH-responsive Nanocarriers for Gastric-Irritant Oral Drug Aspirin
Authors: Aquib Tahmidul Islam , Hoque Sheikh Manjura , Uddin Mohammad Helal 
Published: September 2024

Introduction:
Although lignin is one of the most naturally abundant biopolymers, the
overall status of its utilization has long been subpar. The ability of Lignin to readily self-assemble
into nanoparticles, along with its good biocompatibility and minimal toxicity, makes it a perfect agent
for nanocarriers and drug delivery.

Method:
Hence, in this study, we have attempted to examine lignin nanoparticles (LNPs) as an efficient
pH-responsive nanocarrier for gastric-irritant oral NSAID, aspirin. Alkali lignin (AL) was extracted
from rice straw via alkaline treatment, and the lignin nanoparticles were synthesized from
lignin using the acid precipitation method. The average particle size was 201.37 ± 1.20 nm, and the
synthesized LNPs exhibited a spherical shape and smooth outer surface along with high polydispersity
(PDI= 0.284 ± 0.012). The LNPs showed moderate hemocompatibility during in vitro hemolysis
studies. The nanoparticles presented nearly similar chemical structures to the AL from which they
were developed, and the FT-IR absorption spectra confirmed the similarity of this chemical structure
to the LNPs and AL. Aspirin was successfully loaded into the LNPs with a satisfactory drug loading
value of 39.12 ± 1.50 and an excellent encapsulation efficiency value of 91.44 ± 0.59.

Results:
Finally, the LNPs were capable of protecting the loaded drug at the acidic pH of the stomach
(1.2) with just 29.20% release of the loaded aspirin after 10 h of observation in vitro. Contrarily, the
LNPs were capable of rapidly releasing the aspirin at the basic pH of the intestine (7.4) with nearly
90% release of the loaded drug after 10 h observation in vitro. The basic pH of the intestine might
lead to gradual dissociation of the LNPs followed by swift release of the loaded cargo.

Conclusion:
These findings substantiate that the LNPs carry the potential to be an apt and safe
nanocarrier for oral drugs like aspirin as well as parenteral drugs, and LNPs can be utilized as an
efficient alternative to enteric coating.
Exploring the Confluence of Animal Medicine and its Implications for
Human Health: A Systematic Literature Review
Authors: Dunn Josie , Schifano Fabrizio , Dudley Ed , Guirguis Amira 
Published: September 2024

Introduction:
The abuse of veterinary drugs has emerged as a concerning trend, with
global fatalities on the rise. Our understanding of this phenomenon remains limited. This study aims
to identify the veterinary drugs being misused, the reasons behind their misuse, and how they are obtained.

Methods:
Utilising PubMed, Scopus, and Web of Science databases, along with related grey literature,
we applied the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA)
framework for data collection. Screening and cross-referencing yielded 66 relevant articles, encompassing
case reports, surveys, reports, and systemic literature reviews. The analysis identified 28
distinct veterinary drugs being misused in humans, primarily falling into categories, e.g., α-2- and
β-2-adrenergic receptor agonists, GABAergic receptor modulators, opioid receptor agonists, nonsteroidal
anti-inflammatory drugs (NSAIDs), and N-methyl-D-aspartate (NMDA) receptor antagonists.
These drugs were used for various purposes, including recreational use, weight loss, bodybuilding,
pain relief, and self-medication for stress-related symptoms.

Results:
Routes of administration predominantly included parenteral, oral, and inhalation methods.
Veterinary workers/assistants and individuals connected to animals were identified as contributors to
the misuse of these medications. Motivations for their utilisation ranged from affordability and accessibility
to the ease of obtaining multiple prescriptions from various veterinary sources, often in
conjunction with other illicit substances. Dependence and addiction were common outcomes of the
misuse of veterinary medicines by humans.

Conclusion:
Overall, this systematic review underscores the increasing popularity of veterinary prescription
drug misuse despite being under-reported with limited available data. Healthcare professionals
are urged to remain vigilant to potential overdose events involving these medications.
The Relationship between Using Renin-Angiotensin System Inhibitors with Mortality of Atrial Fibrillation: A Systematic Review and Meta-Analysis
Authors: Zadeh Reza Faramarz , Masoumi Shahab , Jafari Negar , Rabori Venus Shahabi , Heidari-Soureshjani Saeid 
Published: September 2024

Background:
Atrial fibrillation (AFib) is a highly prevalent cardiac arrhythmia associated
with increased mortality in affected persons. Renin-angiotensin system inhibitors (RASIs)
have been suggested as potential therapeutic agents for cardiovascular and renal diseases.

Objectives:
However, the relationship between RASIs and mortality in AFib patients remains
uncertain. Therefore, the present study was designed and implemented for this purpose.

Methods:
We searched PubMed/MEDLINE, Embase, Web of Science (WOS), Cochrane Library,
and Scopus databases for studies published until 12 February 2024 with relevant keywords.
We included studies that reported mortality outcomes in AFib patients treated with RASIs
and non-users. The data extraction and quality assessment processes were conducted, and
subgroup analyses and sensitivity analyses were done. The data were analyzed by Stata 15 using
statistical tests, such as Chi-square and I2 tests.

Results:
A total of 15 studies (2007-2024; n=2,178,565 patients) examined the association between
RASI drugs and mortality of patients with AFib. The results indicated that compared to
the control group, the odds of AFib mortality in the group receiving RASIs were equal to
0.81(95% CI: 0.71-0.92; P-value ≤0.001). The study results did not indicate publication bias (Pvalue=
0.733). During the meta-regression analysis, none of the study variables demonstrated a
significant relationship with the observed heterogeneity (P-value > 0.20). Cumulative OR results
showed that from 2022 onwards, there was enough evidence to confirm the relationship using
RASIs with mortality of patients with AFib.

Conclusion:
Therefore, this meta-analysis suggests that the use of RASI drugs is associated with
reduced AFib mortality. However, the authors emphasize the need for further high-quality studies
and large-scale randomized clinical trials to validate these findings.
Quantifying Soluble Glucose in Selected Fruits from West Bengal's (India) Local Markets to Enhance Dietary Knowledge
Authors: Hushneara Syed , Roychowdhury Prasun , Chatterjee Moumita , Goswami Swagata , Saha Sneha , Lahiri Shibani 
Published: September 2024

Introduction/Objective:
A fruit, the soft, pulpy part of a flowering plant, is abundant in essential nutrients like fiber, vitamins, minerals, antioxidants, and bioactive compounds. It provides macronutrients such as carbohydrates and energy while being low in protein and lipids. Health authorities advocate a minimum daily intake of five servings of fruits and vegetables for a balanced diet. Fruits contain simple sugars such as glucose, fructose, and sucrose, which are essential for regulating blood sugar levels and supporting brain function. However, excessive sugar consumption can be harmful in certain health conditions. This highlights the importance of accurately estimating glucose content in fruits for the field of nutrition science.

Methods:
In this study, a total of 42 fruit samples from 20 groups were collected from local markets in West Bengal, India, to measure glucose levels using the GOD-POD method.

Results:
Results revealed the top five fruits highest in glucose: green grapes (54.12 ± 5.82 mg/g), java apple (green jamrul: 47.25 ± 8.23 mg/g), red grapes (44.75 ± 5.23 mg/g), Zahedi dates (43.88 ± 3.25 mg/g), and Medjool dates (43.48 ± 3.87 mg/g). Conversely, the five fruits lowest in glucose were Indian gooseberry (amla: 0.84 ± 0.21 mg/g), Bengal currant (koromcha: 1.24 ± 0.15 mg/g), gondhoraj lemon (2.62 ± 0.25 mg/g), himsagar mango (3.46 ± 0.81 mg/g), and pearafuli mango (5.5 ± 0.52 mg/g).

Conclusion:
This study aims to contribute to the development of a comprehensive database on fruit glucose content. Fruits with lower glucose levels are beneficial for diabetic patients, obese individuals, and others, whereas those with higher glucose levels are not recommended for dia-betics but are suitable for athletes and malnourished individuals.