bluuebunny/crossref_metadata_2025_split huggingface dataset:
The palliative care needs of women receiving palliative chemotherapy for breast cancer in an academic hospital in the Volta Region of Ghana
Authors: Gbande Sulleh , Maree Johanna Elizabeth , Obiora Oluchukwu Loveth 
Published: January 2025

Abstract

Background
Cancer is a major public health concern worldwide, with breast cancer affecting approximately 2.3 million women and contributing to (6.9%) cancer-related deaths in 2020. In Africa, breast cancer accounts for 27.7% of all cancer diagnoses, with Sub-Saharan Africa having one of the highest mortality rates. In Ghana, breast cancer is the most prevalent cancer among women, with 60% presenting at advanced stages. Late presentation often necessitates palliative chemotherapy, which has significant physical, psychosocial, spiritual and financial burdens. Despite these challenges, no study has investigated the palliative care needs of women receiving chemotherapy for breast cancer in Ghana. The aim of this study therefore is to describe the palliative care needs of women receiving palliative chemotherapy for breast cancer treated at an academic hospital in the Volta Region of Ghana.
Methods
A qualitative descriptive design was used, twenty-four women aged 18 years and above were purposively selected. The participants provided demographic information and took part in individual, in-depth, face-to-face semi-structured interviews asking one opening question. The data were analyzed using content analyses and an inductive approach.
Results
The participant’s ages ranged between 39 to 79 years with a median age of 54.5. The majority were married (22 of 24), had a university education (21 of 24) and belonged to the Ewe tribe (20 of 24). Five needs were identified; the need for symptom management, professional informational support, psychosocial support, spiritual support, and socio-economic support.
Conclusion
The women’s palliative care needs exceeded the physical and included the need for accurate information from health care professionals that would enable them to make informed health care decisions. They also needed money to pay for their treatment, prayers and pain management. It therefore recommended that a tailored palliative care programme be developed to support women diagnosed with breast cancer receiving palliative chemotherapy.
Practical Pose Estimation Method for Industrial X-ray Radiography Based on Deep Learning and Local Template Matching
Authors: Ou Dongsheng , Xiao Yongshun 
Published: January 2025

Abstract

With the increasing integration of industrial products, critical components are often enclosed within shells, making it difficult to measure their actual positions during assembly using contact measurement techniques. This often results in substandard product quality. X-ray imaging offers a non-destructive solution for inspecting internal structures and accurately positioning internal components. However, traditional pose estimation methods based on X-ray imaging rely on projection optimization, which is time-consuming and cannot meet the timely feedback requirements of assembly processes. In this work, we propose a pose estimation method for industrial X-ray radiography that combines neural networks for initial pose estimation with local template matching for pose refinement. This approach achieves high accuracy and efficiency in positioning internal targets. We conducted real X-ray imaging experiments on several objects, including a terahertz anode tube model. The mean alignment error was approximately 0.2 mm, which is lower than the spatial resolution (about 0.25 mm) of the CT images constructed from the same X-ray projections. The running time for pose estimation of a single object was about 10 seconds, significantly faster than conventional methods that take several minutes, making it suitable for timely feedback in industrial assembly processes.
Advancing COVID-19 Treatment: The Role of Non-covalent Inhibitors Unveiled by Integrated Machine Learning and Network Pharmacology
Authors: Qadir Saba , Alshabrmi Fahad M. , Aba Alkhayl Faris F. , Muzammil Aqsa , Kaur Snehpreet , Rehman Abdur 
Published: January 2025

Introduction:
The COVID-19 pandemic has necessitated rapid advancements in therapeutic discovery.
This study presents an integrated approach combining machine learning (ML) and network pharmacology
to identify potential non-covalent inhibitors against pivotal proteins in COVID-19 pathogenesis, specifically
B-cell lymphoma 2 (BCL2) and Epidermal Growth Factor Receptor (EGFR).

Method:
Employing a dataset of 13,107 compounds, ML algorithms such as k-Nearest Neighbors (kNN),
Support Vector Machine (SVM), Random Forest (RF), and Naïve Bayes (NB) were utilized for screening and
predicting active inhibitors based on molecular features. Molecular docking and molecular dynamics simulations,
conducted over a 100 nanosecond period, enhanced the ML-based screening by providing insights into
the binding affinities and interaction dynamics with BCL2 and EGFR. Network pharmacology analysis identified
these proteins as hub targets within the COVID-19 protein-protein interaction network, highlighting their
roles in apoptosis regulation and cellular signaling.

Results:
The identified inhibitors exhibited strong binding affinities, suggesting potential efficacy in disrupting
viral life cycles and impeding disease progression. Comparative analysis with existing literature affirmed
the relevance of BCL2 and EGFR in COVID-19 therapy and underscored the novelty of integrating network
pharmacology with ML. This multidisciplinary approach establishes a framework for emerging pathogen
treatments and advocates for subsequent in vitro and in vivo validation, emphasizing a multi-targeted drug design
strategy against viral adaptability.

Conclusion:
This study's findings are crucial for the ongoing development of therapeutic agents against
COVID-19, leveraging computational and network-based strategies.

conclusion:
This multidisciplinary approach establishes a framework for emerging pathogen treatments and advocates for subsequent in vitro and in vivo validation. The findings emphasize a multi-targeted drug design strategy against viral adaptability, contributing significantly to the ongoing development of therapeutic agents against COVID-19.
Transcriptome-Based Analysis of the Oxidative Response of Thermotoga maritima to the O2 Stress
Authors: Lakhal Raja , AlMatar Manaf , Alkalaf Tahani , Albarri Osman 
Published: January 2025

Background:
Thermotoga maritima is an anaerobic hyperthermophilic eubacterium
isolated from geothermally heated maritime surfaces. It can grow at temperatures up to 80 degrees
Celsius.

Methods:
A 2.3-L bioreactor was specifically designed to cultivate hyperthermophilic bacteria
under carefully regulated pH, redox potential, temperature, and dissolved O2.

Results:
Using this bioreactor, which was adjusted at 80°C and pH 7.0, it was found that Thermotoga
maritima demonstrated continued growth even after being exposed to oxygen for an extended
period. Transcription studies revealed that following prolonged oxygen exposure, the
genes encoding ROS-scavenging systems, alkyl hydroperoxide reductase (ahp), thioredoxindependent
thiol peroxidase (bcp 2), and, to a lesser extent, neelaredoxin (nlr), were upregulated/
overexpressed. When oxygen was available, the metabolism of glucose was diverted to make
lactate rather than acetate.

Conclusion:
Based on the O/R ratio of 1.0 in anaerobiosis and 1.67 in the presence of O2, we
may conclude that Thermotoga maritima is capable of semi-oxidative metabolism.
A Roadmap Towards the Identification and Validation of Conserved T Cell Epitope Regions in Viral Pathogen Families with Pandemic Potential
Authors: Grifoni Alba , Sidney John , Weiskopf Daniela , Scheuermann Richard H. , Sette Alessandro 
Published: January 2025

Abstract:
The SARS-CoV-2 pandemic has highlighted the need for society, as a whole, to be
prepared against potential pandemics caused by a variety of different viral families of concern.
Here, we describe a roadmap towards the identification and validation of conserved T cell
epitope regions from Viral Families of Pandemic Potential (VFPP). For each viral family, we
select a prototype virus, the sequence of which could be utilized in epitope identification
screens. Examples of viral families considered and their respective prototypes (species/
subspecies) are Coronaviridae (Severe Acute Respiratory Syndrome-related Coronavirus/
SARS-CoV-2), Flaviviridae (Dengue virus/DENV2), Togaviridae (Chikungunya virus/
CHIKV), Paramyixoviridae (Morbillivirus/measles), Arenaviridae (Mammarenavirus/
Lassa), and Picornaviridae (Enterovirus C/poliovirus). The peptide sequences encoded
in each prototype virus are then analyzed to determine their conservation across different viral
taxonomic groups and viral variants derived from each of the VFPP. We outline available
methodologies for epitope discovery based on panels of overlapping peptides and bioinformatics-
based predictions of HLA-peptide binding, along with high-throughput in vitro assays,
with emphasis on addressing coverage of the general worldwide population. Validation can be
achieved by a variety of methodologies, including determining HLA restriction and recognition
in samples from volunteers convalescent from previous infections or immunized with approved
or experimental vaccines, and immunophenotyping of responding T cells. The capacity
of these regions to induce crossreactive T cell responses can be tested experimentally with
homologous peptides derived from the various viral species of interest. Importantly, they
could be considered as a component of pan-viral family vaccines. Conversely, immunogenic
regions that are highly specific to a given virus could be of interest for diagnostic applications.
A Comprehensive Analysis of the Role of PAX9 in Head and Neck Squamous Cell Carcinoma
Authors: Zeng Lang , Yun Wenjing , Luo Wen-long 
Published: January 2025

Background:
Paired box 9 (PAX9) has been linked to several human
disorders; however, its relevance in Head And Neck Squamous Cell Carcinoma
(HNSCC) remains unknown.

Methods:
The difference in PAX9 mRNA expression in pan-cancer was analyzed
utilizing The Cancer Genome Atlas (TCGA), and the level of PAX9 protein expression
across various types of cancer was assessed utilizing the Human Protein Atlas (HPA)
and UALCAN databases, as well as the cellular localization of PAX9. UALCAN studied
the methylation levels of PAX9 in pan-cancer. The predictive significance of PAX9 in
pan-cancer was assessed utilizing the Kaplan-Meier Plotter website. Functional
enrichment analysis was carried out with the "cluster Profiler" program. By employing
CCK8 and colony formation methods, the influence of PAX9 on the growth of HNSCC
cells was evaluated. By conducting a transwell experiment, we assessed the influence
of PAX9 on the migration of HNSCC cells. Western blotting was used to determine the
levels of Bax and Bcl-2, two proteins involved in the regulation of apoptosis. A nude
mouse model was established to study the impact of PAX9 overexpression on the
growth of subcutaneous HNSCC tumors.

Results:
In HNSCC, the expression of PAX9 was found to be low, while levels of
promoter methylation rose considerably. Low PAX9 expression has been linked to a
decrease in overall survival (OS) rates among individuals with HNSCC. Furthermore,
overexpressing the PAX9 gene decreased HNSCC cell proliferation, migration, and
invasion while boosting apoptosis rates.

Conclusion:
The abnormal expression of PAX9 is linked to various cancers. In
HNSCC, PAX9 is a potential tumor suppressor, inhibiting tumor invasion and
migration. The results reveal a potentially significant new therapeutic target for
HNSCC.
MicroRNA-130b Is a Unique Autophagy-Related Epigenetic Predictor of FLOT-Chemotherapy in Gastric Cancers
Authors: Spirina Liudmila V. , Zinnurova Alina B. , Bakina Olga V. , Avgustinovich Alexandra V. , Afanas'ev Sergey G. , Volkov Maxim Yu. , Klyushina Tatyana S. , Volkov Alexandr M. , Tarasenko Natalia V. , Masunova Nadezhda V. 
Published: January 2025

Introduction:
Liquid biopsies have great potential for precision medicine as
they provide information about primary and metastatic tumors using minimally invasive
techniques. MicroRNAs (miRNAs) are promising biomarkers for detecting gastric
cancer (GC). The aim of the study was to identify miR molecules associated with
autophagy in gastric cancer (GC) cells, determine their expression levels in GC and
FLOT-treated patients, and assess the efficacy of FLOT therapy in GC patients.

Methods:
Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology
(GO) pathways were used to analyze cellular pathways. MicroRNAs were isolated
from the tissues.

Results:
The study found a connection between the expression of the let-7a-5p gene
and the size of primary tumors. Bioinformatics analysis identified multiple targets and
signaling pathways associated with this phenomenon. We observed an increase in the
levels of miR-21-3p and hsa-miR-130b-3p with lymph node involvement. miR-21-3p is
associated with the activation of molecular pathways induced by H. pylori in cases of
coinfection. Patients with complete regression had higher levels of expression of hsamir-
130b-3p.

Conclusion:
The bioinformatics analysis allowed us to identify the most significant
targets among microRNAs. Based on the presented data, it becomes clear that GC is
heterogeneous and that the process of autophagy is complex. The association
between hsa-miR-130b-3p and tumor response to therapy is particularly interesting.
The Effect of Risk Factors and Clinical Complications of Chronic Kidney Disease (CKD) on Renal Arterial Resistive Index (RRI)
Authors: souri Zobin , Ramezanzadeh Alireza , Ramezanzadeh Elham , Leyli Ehsan Kazemnezhad , Jalali-Zefrei Fatemeh 
Published: January 2025

Background:
Chronic Kidney Disease (CKD) is a known risk factor for End-Stage Renal
Disease (ESRD) and Cardiovascular Diseases (CVD). Renal Doppler Ultrasound (RDU) can
detect early renal involvement in CKD using the Renal Resistive Index (RRI).

Aims:
This study aimed to investigate the effects of risk factors and clinical complications associated
with CKD on RRI among patients with different stages of CKD.

Methods:
In this analytical cross-sectional study, 186 patients referred to Poursina Hospital for
RDU were categorized into six groups (normal and five stages of CKD). We analyzed the impact
of demographic factors and clinical complications on RRI across all groups.

Results:
Our findings indicated that CKD prevalence was particularly high among older patients
and those with CVD, type 2 diabetes mellitus (DM), and hypertension (HTN). Elevated RRI in
CKD patients was significantly associated with age, CKD stage, CVD, and HTN (p < 0.05). Furthermore,
RRI was higher in CKD patients with elevated serum phosphorus (P) levels, higher
low-density lipoproteins (LDL), and lower calcium (Ca) and hemoglobin (Hb) levels. Based on a
multivariate regression model, CVD, lower Ca, high LDL, and proteinuria were identified as independent
predictors of elevated RRI (p < 0.05).

Conclusion:
This study concludes that elevated RRI is associated with the severity of CKD and
its clinical complications, suggesting that RRI can serve as a reliable indicator for assessing CKD
patients, managing treatment, and preventing early death complications.
Establishment and Validation of the Diagnostic Value of Oligodendrocyte-related Genes in Alzheimer's Disease
Authors: Li Chen , Chen Yan , Yao Yinhui , Shang Yazhen 
Published: January 2025

Background:
AD is a demyelinating disease. Myelin damage initiates the pathological
process of AD, resulting in abnormal synaptic function and cognitive decline. The myelin sheath
formed by oligodendrocytes (OL) is a crucial component of white matter. Investigating AD from the
perspective of OL may offer novel diagnostic and therapeutic perspectives.

Objectives:
This study aimed to analyze the association between OL-related genes and Alzheimer's
disease (AD) using bioinformatics and verify this association via molecular biology experiments.

Methods:
The AD datasets were acquired from the Gene Expression Omnibus (GEO) database of
NCBI. Consensus clustering was employed to determine the subtypes of AD, followed by evaluating
the clinical characteristics of these subtypes. Subsequently, immune infiltration analysis of relevant
genes and Weighted Gene Co-expression Network Analysis (WGCNA) were conducted to
identify modules and hub genes associated with AD progression. The intersection of genes obtained
was analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)
enrichment analyses. To narrow down the scope and identify OL-related genes with diagnostic potential,
three machine learning algorithms were utilized. In addition, the eXtreme Sum (XSum) algorithm
was used to screen small molecule drug candidates based on the connectivity map (CMAP)
database. Finally, these identified genes were validated using Real-time fluorescence quantitative
PCR (RT-qPCR).

Results:
Among the three subtypes of AD, Cluster A and Cluster C exhibited increased levels of
Braak and neurofibrillary tangles compared to Cluster B. The proportion of females was greater than
that of males among the three subclasses of AD. There were no significant differences in age among
the three subclasses, but significant differences in gene expression existed. Through WGCNA analysis,
108 genes were identified. Among these, 16 genes were identified as shared genes by the least
absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machines
(SVM) algorithms, and logistic regression further determined 11 genes. The establishment of
a nomogram demonstrated the significance of these 11 genes in AD. The "XSum" algorithm revealed
five drugs with therapeutic potential for AD. qPCR analysis revealed the upregulation and
downregulation of the highlighted genes. According to this study, 11 genes related to OL were also
found to be associated with immune cell infiltration in AD patients. These genes demonstrated potential
diagnostic value for AD. Additionally, we screened five small molecular drugs that exhibit
potential therapeutic effects on AD.

Conclusion:
This research provides a new perspective for personalized clinical management and
treatment of AD.
Pengaruh Social Media Marketing Dan Brand Image Terhadap Repurchase Intention
Authors: Reza Alif Aulia 
Published: January 2025

This research aims to determine the influence of Social Media Marketing and brand image on Repurchase Intention among customers of UD Mulia Agung in Banyuwangi Regency. This study is an explanatory type of research that explains the causal relationship between research variables through hypothesis testing. The sample was collected using non-probability sampling with a purposive sampling method. Data analysis was performed using Multiple Linear Regression Analysis, and hypothesis testing was conducted using the t-test in SPSS 25 software. Based on the results of testing the three hypotheses, it can be concluded that (1) Social Media Marketing has a positive and significant influence on Repurchase Intention and (2) brand image has a positive and significant influence on Repurchase Intention. The implications of the research include, among others, that UD Mulia Agung can enhance customer interaction through diverse social media strategies, improve the creation of positive product-related information, and consider social media advertisements as an appealing marketing strategy to attract a broader audience of potential customers.

Abstrak
Penelitian ini memiliki tujuan untuk mengetahui pengaruh dari Social Media Marketing dan brand image terhadap niat pembelian ulang atau Repurchase Intention pada pelanggan UD Mulia Agung di Kabupaten Banyuwangi. Penelitian ini merupakan jenis penelitian eksplanatori yang menjelaskan hubungan kausal antar variabel penelitian melalui pengujian hipotesis. Teknik pengambilan sampel menggunakan non-probability sampling dengan metode purposive sampling. Analisis data menggunakan Analisis Regresi Linier Berganda dan uji hipotesis menggunakan Uji t yang diolah pada software SPSS 25. Berdasarkan dari hasil pengujian terhadap ketiga hipotesis dapat disimpulkan bahwa, (1) Social Media Marketing memiliki pengaruh yang positif dan signifikan terhadap Repurchase Intention dan (2) brand image memiliki pengaruh yang positif dan signifikan terhadap Repurchase Intention. Implikasi penelitian antara lain UD Mulia Agung dapat melakukan peningkatan interaksi dengan pelanggan melalui media sosial yang bervariasi, penciptaan informasi positif mengenai produk dapat ditingkatkan, dan perusahaan dapat mempertimbangkan social media advertisement sebagai strategi pemasaran yang dianggap menarik oleh calon pelanggan sehingga dapat meraih audiens yang lebih luas.
Pengaruh Motivasi Terhadap Keterlibatan Konsumen Pada Gamifikasi
Authors: Pitaloka Pandora Diah , Hapsari Raditha Dwi Vata 
Published: January 2025

The objective of this research is to identify the effects of motivation on the involvement of consumers in Shopee Games’ gamification. This causal research corroborates the consequential relationship between its dependent and dependent variables. The samples of this research are 132 people with the minimum age of seventeen years who have played Shopee Games for three months. The data was harvested via questionnaires distributed online via Facebook, Telegram, and WhatsApp and was analyzed using multiple linear regression, from which hypothesis testing was conducted. All of the statistical processes were performed in SPSS. The results of the hypothesis testing indicate that motivation, which takes form in autonomy, competence, and relatedness, positively and significantly influences the consumer involvement. Based on the findings, the Shopee Games’ developer needs to maintain game components that can shape the player’s autonomy, competence, and relatedness in order to increase the said involvement of the consumers to play the games. To attain this, the developer should create games that gives autonomy to the players, design challenges with relevant levels of difficulty, and support the establishment of communities for the players.

Abstrak
Penelitian ini bertujuan untuk mengetahui pengaruh dari motivasi terhadap keterlibatan konsumen pada gamifikasi Shopee Games. Jenis penelitian ini berupa riset kausal yang menjelaskan hubungan sebab akibat antara variabel independen dengan variabel dependen. Penelitian menggunakan sampel sebanyak 132 responden dengan melakukan penyebaran kuesioner secara daring melalui Facebook, Telegram dan WhatsApp. Sampel terdiri dari responden dengan minimal usia 17 tahun dan telah memainkan Shopee Games selama 3 bulan terakhir. Analisis data menggunakan regresi linier berganda dan uji hipotesis dengan data yang telah diolah melalui software SPSS. Dari hasil pengujian keempat hipotesis yang ada dapat disimpulkan bahwa motivasi dalam bentuk otonomi, kompetensi, dan keterhubungan memiliki pengaruh positif signifikan terhadap keterlibatan konsumen. Implikasi dari penelitian ini ialah Shopee Games perlu mempertahankan unsur-unsur games yang dapat membentuk otonomi, kompetensi, dan keterhubungan pemain demi meningkatkan keterlibatan konsumen untuk memainkan games-nya. Beberapa hal yang dapat dilakukan antara lain membentuk games yang memberikan otonomi bagi pemain, mendesain tantangan dengan tingkat kesulitan yang sepadan, dan mendukung terbentuknya komunitas antar pemain.