bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differential Diagnosis of Pulmonary Arterial Hypertension via Deep Multimodal Modeling of Noninvasive Measurements
Authors: Zheng Siqiang , Zheng Enkuo , Guo Liang , Xie Lei , Zhao Bin , Hong Qi , Hu Xuefei , Tao Bo 
Published: December 2024

Abstract

Background
Pulmonary hypertension (PH) is a rare yet progressive disorder characterized by elevated blood pressure in the arteries of the lungs, often presenting without an evident cause. The distinction between pulmonary arterial hypertension (PAH) and PH due to left heart disease (PH-LHD) is crucial due to differences in treatment approach and prognosis. A correct diagnosis is essential to ensuring that patients receive the appropriate treatment. However, the current diagnosis of PAH and PH-LHD faces clinical limitations due to its reliance on invasive hemodynamic measurements or the limits of data modeling.
Methods
We conducted a retrospective study involving 905 PH patients from Shanghai Pulmonary Hospital, incorporating CT images and clinical textual data. A heterogeneous graph neural network was constructed on multimodal data. We developed and validated a heterogeneous network to predict the probability of PAH and PH-LHD. The new method exhibits strong discrimination between PAH and PH-LHD.
Findings
In the multiple cross-validations, it achieved a 0.943 AUC when using a combination of image and textual data, a 0.869 AUC for only textual variables, and a 0.715 AUC for only images. It also evaluated the type-dependent performances, yielding the best AUC (0.896) when using a subgroup of variables. The best performance (AUC=0.809) can be achieved by using only ECG variables in our model.
Interpretation
Our study provides a quantitative rationale for modulating multimodal data to enhance differential diagnosis of PAH and PH-LHD with only noninvasive measurements.
Identifying cell-type-specific spatially variable genes with ctSVG
Authors: Zhuang Haotian , Shang Xinyi , Hou Wenpin , Ji Zhicheng 
Published: December 2024

Abstract

Spatially variable genes (SVGs) reveal the molecular and functional heterogeneity of cells across different spatial regions of a tissue. We found that sample-wide SVGs, identified by previous methods across the whole sample, largely overlap with cell-type marker genes derived from single-cell gene expression, leaving the spatial location information largely underutilized. We developed ctSVG, a computational method specifically tailored for Visium HD spatial transcriptomics at single-cell resolution. ctSVG accurately assigns Visium squares to cells and identifies cell-type-specific SVGs. We show that cell-type-specific SVGs identified by ctSVG include many new genes that do not overlap with sample-wide SVGs or cell-type marker genes, and that these genes reveal important biological functions in real spatial datasets.
Interpreting DETR with Respect to Object Queries
Authors: Farahani Morteza Shahrabi , Haghighi Mohammad Javad Mirshekari , Mohammadi Mohammad Reza 
Published: December 2024

Abstract

In recent years, understanding the decision-making processes of neural network models has become increasingly important. This paper is focusing on this concern and addresses this issue on DETR model which is an object detection framework based on transformers. We explore ways to improve the interpretability and efficiency of this model by proposing and applying new methods for representing this model. A key focus of this research is on object queries specifically analyzing their behavior during the model's validation process. We identify and remove less active object queries from the model, subsequently, measuring the impact on the training time and also the model accuracy. By eliminating 10% of these inactive object queries, we reduce validation time by 3.3% and lower the model’s required FLOPS by 36.25 G. The GitHub repository for this project is available at https://github.com/morteza-shahrabi-farahani/Interpreted-DETR-model
WITHDRAWN: A Systematic Approach to Demulsifier Selection for Crude Oil Dehydration Using Fuzzy TOPSIS
Authors: Mohammad Suleiman Ibrahim Shelash , Vasudevan Asokan , Koka Nisar Ahmad , H. Malathi , Kazmi Syeda Wajida , Chahar Mamata , Ghazaly Nouby M. , Kumar Abhinav , Esanmurodova N. , Shafieezadeh M. Mehdi 
Published: December 2024

Abstract

This study applies the Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method to evaluate and select the optimal demulsifier for crude oil dehydration. Four demulsifiers—Alcopol 500, Polymer-based Demulsifier, Nalco Champion EC7135A, and Schlumberger’s ClearPhase—were assessed based on criteria including separation efficiency, environmental impact, cost-effectiveness, and ease of application. The decision matrix was constructed using fuzzy numbers to account for uncertainty and imprecision in expert evaluations. Nalco Champion EC7135A emerged as the top-ranked demulsifier, with the highest closeness coefficient of 0.751, indicating superior separation efficiency and minimal environmental impact. Alcopol 500 ranked second with a closeness coefficient of 0.708, followed by the Polymer-based Demulsifier (0.692), and Schlumberger’s ClearPhase (0.619). The results validate FTOPSIS as a robust multi-criteria decision-making tool for selecting demulsifiers, offering a systematic and transparent approach to addressing the complex trade-offs between performance, cost, and sustainability. This study highlights the potential of integrating FTOPSIS into industrial decision-making frameworks, recommending further research to incorporate real-time data for more accurate and adaptable selection processes.
Where are my nematodes? Labelling and visualising entomopathogenic nematodes In Vivo using carbon quantum dots
Authors: San-Blas Ernesto , Cornejo María José , Guerra Mayamarú , Olivares Macarena , Faundez Sebastian , Bastidas Brynelly , Morales-Montero Patricia , Pizarro Lorena , Aponte Humberto , Castaneda-Alvarez Carlos , Lankin Gabriela 
Published: December 2024

Abstract

Identifying single or groups of animals has significantly advanced our understanding of animal biology and ecology. However, labelling is extremely difficult in small animals, like soil invertebrates. Due to the complexity of current methods, the dynamics and interactions of these populations are often studied indirectly. Labelling nematodes or microarthropods such as collembolans or soil acari has been challenging due to the high cost, potential toxicity, genetic modification requirements, cellular processes interference, and photobleaching. In this scenario, no methods can be applied to large numbers of microorganisms at once due to their mentioned practical and biological limitations and cost. In this work we show that quantum carbon dots (Cdots) are effective for labelling infective juveniles (IJs) of entomopathogenic nematodes (EPN). In in vitro assays the IJs gradually acquired fluorescence, as Cdots accumulated in the lysosome-related organelles from their intestine cells, peaking at day 14, and with no lethal or sub-lethal effects on IJs. Fluorescence was clearly distinguishable from the natural auto-fluorescence of non-labelled IJs and persisted for months in IJs transferred to water. We and non-experts easily differentiated between similar species of EPNs and between two strains of S. feltiae placed in the same matrix (soil or water). We demonstrated for the first time the feasibility of labelling large numbers of IJs (hundreds of thousands/millions) with Cdots at minimal cost without any adverse effects for over a year. Our findings could be the starting point for detailed and large-scale field investigations on nematodes and other small organisms, allowing deeper understanding of their roles in soil ecosystems. This method provides a cost-effective and reliable tool for advancing research in the ecology of soil invertebrates, such as the interactions occurring in communities or between specific organisms, movement and dispersal, population dynamics or ecosystem services in a cryptic environment difficult to study.
A review of secondary contamination of drinking water quality in distribution systems: sources, mechanisms, and prospects
Authors: Wang Zhi , Yang Xiaozhou , Fu Lei , Li Manjie 
Published: December 2024

ABSTRACT
Drinking water that complies with established standards at treatment plants inevitably undergoes secondary contamination upon entering distribution systems. A bibliometric analysis highlights the expanding body of research on drinking water distribution systems (DWDSs), emphasizing the paramount importance of safeguarding drinking water quality and mitigating secondary contamination within these networks. This study delves into the sources, health implications, and mitigation strategies pertaining to three predominant forms of secondary contamination, namely metal release, microbial regrowth, and disinfectant by-product (DBP) formation, as well as the intricate interactions among these contaminants. The release of heavy metals is inherently linked to the corrosion process of metallic components of pipelines, which is affected by water quality and hydraulic dynamics. Microbial regrowth within DWDSs is potentially associated with the reproduction of waterborne pathogens, which can lead to significant health outcomes including acute gastroenteritis and diarrhea. Consequently, disinfection is commonly employed to prevent pathogen proliferation in DWDSs, whereas the residual disinfectants can react with natural organic matter or halogen ions in waters, resulting in the formation of DBPs. To mitigate the adverse effects of DBPs, various practical interventions are implemented at distinct stages of water distribution, encompassing source control, process control, and end control.
Using Nemerow's Pollution Index to investigate correlations between land use and water quality across a sample of South African catchments
Authors: Locke Kent 
Published: December 2024

ABSTRACT

Water quality indices (WQIs) enable researchers to combine the measurements of multiple parameters into a single unitless score of overall water quality. Nemerow's Pollution Index (NPI) is a flexible and intuitively simple index that uses an ascending scale to indicate overall levels of impairment. This study demonstrates the utility of the NPI, when used in combination with site-specific water quality guidelines, to investigate correlations between land use and water quality across a sample of 58 sub-catchments located along the western, southern, and south-eastern coast of South Africa. NPI scores for 2013–2014 were calculated for each sub-catchment using data from South Africa's National Chemical Monitoring Programme. Land use metrics for urban, agricultural, and natural land cover were estimated from a contemporaneous national land cover map. Correlation analysis revealed statistically significant positive correlations across the sample between pollution levels and proportions of urban and agricultural land (Spearman's ρ = 0.333 and 0.621, respectively), and strong negative correlations between pollution levels and proportions of natural land cover (Spearman's ρ = –0.729). The study concludes that, when used in concert with site-specific water quality standards, the NPI is a useful tool for evaluating overall levels of impairment across a sample of water bodies.
Network Pharmacology and In silico Elucidation of Phytochemicals Extracted from Ajwa Dates (Phoenix dactylifera L.) to Inhibit Akt and PI3K Causing Triple Negative Breast Cancer (TNBC)
Authors: Bashar Md Abul , Hossain Md Arju , Kavey Md Reduanul Haque , Shazib Rayhanuzzaman , Islam Md Shofiqul , Ansari Siddique Akber , Rahman Md Habibur 
Published: December 2024

Background:
About 10-15% of all breast cancers comprise triple-negative breast cancer (TNBC),
defined as cancer cells that lack ER, PR, and HER2 protein receptors. Due to the absence of these receptors,
treating TNBC using conventional chemotherapy is challenging and, therefore, requires the discovery of novel
chemotherapeutic agents derived from natural sources.

Objective:
The current work was intended to study the potential phytochemicals of Ajwa dates (Phoenix
dactylifera L.) with the predicted potential targets (namely, Akt and PI3K) to determine possible TNBC inhibitors.

Methods:
We harnessed network pharmacology, molecular docking, drug-likeness studies, Molecular Dynamics
(MD) simulation, and binding free energy (MM-GBSA) calculation to get phytochemicals with potential
effects against TNBC. Firstly, molecular docking was performed on 125 phytochemicals against the Akt and
PI3K proteins utilizing PyRx. Then, the phytochemicals with the highest binding affinity (≤ -8.1 kcal/mol)
were examined for in silico drug-likeness and toxicity profiles. Finally, phytochemicals with optimal druglikeness
and toxicity profiles were studied by Molecular Dynamics (MD) simulation and binding free energy
(MM-GBSA) to identify compounds that can form stable complexes.

Results:
The results of the network pharmacology revealed that the Akt and PI3K proteins are potential targets
of TNBC for the phytochemicals of Phoenix dactylifera L. used in this study. The outcomes of molecular
docking displayed that among 125 phytochemicals, 42 of them (with a binding affinity ≤ -8.1 kcal/mol) have
potentially inhibiting effects on both proteins PI3K and Akt expressed in TNBC. Then, the results of in silico
drug-likeness identified seven phytochemicals with optimal pharmacokinetic profiles. Furthermore, toxicity
studies showed that three phytochemicals (namely, Chrysoeriol, Daidzein, and Glycitein) did not cause any
toxicities. Finally, the Molecular Dynamics (MD) simulation studies and binding free energy (MM-GBSA)
verified that Daidzein stayed within the binding cavities of both proteins (Akt and PI3K) by establishing a
stable protein-ligand complex during simulation.

Conclusion:
Taken together, the current work emphasizes the potential effects of Daidzein from Phoenix dactylifera
L. against TNBC, and it can be further studied to establish it as a standard chemotherapy for TNBC.
Prognostic and Immunologic Significance of SH2B2 in Colon Adenocarcinoma and its Relationship to Proliferation, Migration, and Invasion
Authors: Bai Nan , Liu Minyan , Li Qinghuai 
Published: December 2024

Background:
SH2B adaptor protein 2 (SH2B2, also named APS) is an adaptor protein
implicated in the modulation of insulin signaling pathways and glucose metabolism. Its role
in colon adenocarcinoma (COAD) is unknown.

Methods:
Data from The Cancer Genome Atlas and Gene Expression Omnibus database were
utilized to assess SH2B2 expression and its clinical significance in COAD. We investigated the
associations between SH2B2 expression with genomic instability, tumor mutational burden
(TMB), DNA methylation, alternative splicing, immune infiltration, and drug sensitivity. A
SH2B2 knockdown model was developed to examine its impact on COAD cellular functions.

Results:
Highly expressed SH2B2 is associated with a poorer prognosis in COAD. SH2B2 expression
in COAD is associated with copy number variations, microsatellite instability, methylation
patterns, and alternative 5’ splicing events, but not with TMB. SH2B2 is positively correlated
with mostly immune cells and the expression of PD-1 and CTLA4. The IC50 values of ten
drugs were significantly correlated with SH2B2 expression. BI-2536_1086 had a strong binding
affinity with SH2B2. Furthermore, the knockdown of SH2B2 reduced the proliferation, migration,
and invasion of COAD cells.

Conclusion:
SH2B2 appears to act as an oncogene in COAD and may serve as a pivotal prognostic
and therapeutic target, deserving further exploration.
Botanical Bounty: Exploring Aphrodisiac Drug Discovery and Development from Nature's Pharmacy
Authors: Bilal Mohd , Jain Divya , Chaitanya M.V.N.L. , Khurrana Navneet , Singh Shivam Kumar , Mazumder Avijit , Singh Kuldeep 
Published: December 2024

Abstract:
Ayurveda, Siddha, and Unani are some important traditional healing systems of India
having long back evidence-based rejuvenation therapies addressing various infertility and reproductive
disorders. Surprisingly, the United Nations has revealed data on infertility that show that
it affects around one in every six individuals, highlighting the utmost importance of actively
questioning and confronting the misunderstanding and lack of discussion related to infertility.
Even though allopathic drugs like Clomiphene citrate, Anastrozole, Letrozole, Human Chronic
Gonadotropin (hCG), and Human Menopausal Gonadotropin (hPG) are available on the market,
there are a range of traditional and indigenous medical techniques that have been used for millennia
to promote and cure health, including Ayurveda, Siddha, and Unani to deliver safe and potent
drugs having reproductive rejuvenation with proven evidence. Various botanicals are proven to
heal both male and female infertility issues with clinical evidence due to the presence of various
potent phytochemicals. Hence this review critically assesses the evidence-based literature focused
on the mapping of botanical sources, phytochemicals, reproductive pharmacology, and their clinical
evidence.
Improved Alzheimer's Detection with a Modified Multi-Focus Attention Mechanism using Computational Techniques
Authors: Pandey Purushottam Kumar , Pruthi Jyoti , Khan Surbhi Bhatia , Alkhaldi Nora A. , Saraee Daniel 
Published: December 2024

Abstract:
Alzheimer disease is a common type of dementia which shrinks the brain cells and
eventually causes death. It disturbs the life quality of patients with progressive symptoms such as
memory loss, conversation, etc. It is vital to identify the disease earlier to get precise treatment.
Besides, it is significant to locate the forms of Alzheimer's such as AD (Alzheimer Disease), CN
(Cognitive Normal), and MCI (Mild Cognitive Impairment). Traditionally, manual screening of
Alzheimer's is carried out by qualified physicians, which is a time-consuming mechanism, expensive,
and prone to human error. To resolve the issue, several conventional researches attempted to
attain better efficiency in the Alzheimer classification but were limited through accuracy, speed,
and inefficacy. To address the challenge of classifying Alzheimer's in its various forms (AD, CN,
and MCI), the proposed system utilizes the Modified Multi-Focus Attention and Hierarchical
Scalerated Convolutional Neural Network (HSCN) mechanisms within the ResNet-101 model.
The system undergoes testing with custom datasets such as OASIS, AIBL, and ADNI, and the
classification performance is assessed using efficiency factors to gauge the effectiveness of the research.

Background:
Alzheimer is a century-old disease, still there is no concrete method to diagnose the
disease. Many time diagnosis takes large time and the patient has been referred to many doctors.

Objective:
The objective of the study is to create a prediction model using deep learning which
will be able to classify the patient into three different classes, CN, MCI,, and AD. The model is
trained on hetero dataset, ADNI, AIBL,, and OASIS.

Method:
For the deep learning model, we have used Resnet 101 in which the convolution layer is
changed to Hierarchical Scalerated CNN and the bottleneck layer is changed to modified multi-focus
attention. The preprocessing of the image is also done as the initial step of process.

Results:
Our model accuracy is more than 99% for all three datasets used for the research.

Conclusion:
The model is trained for MRI from different datasets, the same model should be used
for PET scans for Alzheimer's diagnosis, and the same model can be used to diagnose other disease
patients which will be very useful for mankind.
Assessment of the Knowledge of Healthcare Professionals on Nutrition and Diabetes Self-management in Type-2 Diabetes Treatment at a Health Facility in Tshwane, South Africa
Authors: Doriccah Tsatsane , K.E. Hlabyago , C.D. Kabongo 
Published: December 2024

Background
Diabetes mellitus remains an important non-communicable disease globally and is rapidly emerging as a major public health problem. The burden of the disease continues to rise, even in sub-Saharan Africa. Healthcare professionals often lack the necessary skills to lead patients through lifestyle modifications and instead depend on pharmacological therapy. Recent studies advocate for the integration of innovative healthcare approaches and the promotion of non-pharmacological treatment in the context of broader education on lifestyle modifications for the management of diabetes and other conditions.

Aim and Objectives
This study aimed to assess the level of knowledge of nurses on nutrition and diabetes self-management in treating patients with type 2 diabetes mellitus at a community health centre in the Tshwane district.

Methods
A cross-sectional study was conducted amongst 53 nurses. A standardized questionnaire was modified to collect data from the nurses working at the health facility.

Results
Most healthcare professionals with lower knowledge scores were not aware of the DM guideline, with a p-value < 0.05. The healthcare professionals with a high knowledge score were not aware of the DM guideline as well. Overall, healthcare professionals working at the CHC had lower knowledge scores on nutrition and self-management of diabetes.

Conclusion
Healthcare professionals showed a notable gap in knowledge pertaining to nutrition and the self-management of diabetes. Promoting the adoption of current diabetes management guidelines and encouraging continued professional development can effectively address knowledge disparities, particularly among professionals with limited experience and diploma-level credentials.
Perceptions and Experiences of Caregiver-Employees, Employers, and Health Care Professionals With Caregiver-Friendly Workplace Policy in Hong Kong: Thematic Analysis
Authors: Lee Maggie Man-Sin , Yeoh Eng-kiong , Wong Eliza Lai-Yi , Bai Xue , Yeung Nelson Chun-Yiu , French Catherine , Taddese Henock 
Published: December 2024

Background
Caregiver-employees (CEs) for older adults experience a high burden to fulfill their dual roles. Caregiver-friendly workplace policy (CFWP) has been used in many countries to balance employment and caregiving duties, but it is a relatively new concept in Hong Kong.

Objective
This study explored the views and experiences of CEs, employers, and health care professionals regarding CFWP (specifically for older adult caregivers) in Hong Kong.

Methods
This study explored the CFWP-related views and experiences in Hong Kong using 15 in-depth interviews with purposively sampled CEs for older adults, employers, and health care professionals.

Results
Two context-related themes (“lacking leadership” and “unfavorable culture”) were identified with thematic analysis. They explain the absence of CFWP in Hong Kong due to the lack of governmental and organizational leadership, and the additional burden experienced by CEs because of the working culture that underpins work-life separation, overprizing business interest, and unsympathetic corporate attitude. Implicit voice theory was applicable in explaining CEs’ nondisclosure about their status at work due to potential risks. In addition, the two facilitation-related themes (“role struggle” and “inadequate support”) identified in this study exhibit how the dual role had positive and negative spillover effects on each other and the inadequacy of social welfare and health care support systems.

Conclusions
We strongly recommend exploring and adopting potential CFWP in Hong Kong, considering the complexity of factors identified in this study.