bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk factors for the occurrence and recurrence of papillary thyroid carcinoma with Hashimoto's thyroiditis based on next- generation sequencing
Authors: Zhang Wanxue , Liu Bin 
Published: October 2024

Abstract

Purpose To investigate the risk factors for the occurrence and recurrence of Hashimoto's thyroiditis (HT) combined with PTC using Next-Generation Sequencing (NGS). Methods 249 patients who underwent thyroid cancer surgery in the First Affiliated Hospital of Anhui Medical University from October 2020 to December 2020 were included, and the clinical data, NGS results and 4-year follow-up recurrence were collected, analyzing the related risk factors causing HT combined with PTC and its risk factors for recurrence. Results patients with RET rearrangement-positive patients in the HT group had a higher lymph node metastasis(LNM) and recurrence rate (P < 0.05); and patients with BRAF mutation in the HT group had more males and were more often seen with multifocal ( P < 0.05). Binary logistic regression analysis suggested that multifocal, RET rearrangement, low age, and lymph node negativity were risk factors for HT combined with PTC. The results of univariate COX analysis showed that the number of cancer foci, LNM, extrathyroidal extension(ETE), recurrence risk stratification, TSH, RET rearrangement positivity, and RET rearrangement interaction with Hashimoto's effect were risk factors for recurrence after PTC. The results of multifactorial COX regression analysis showed that ETE, recurrence risk stratification were risk factors for recurrence after PTC surgery. Conclusions BRAF mutations are lower in HT combined with PTC but do not have a significant role in recurrence, and the recurrence rate of PTC combined with HT is higher if accompanied by RET rearrangement, and more caution is needed for intraoperative clearance in such patients.
Design of a novel multiple epitope-based vaccine: An immune-informatics approach to combat Dengue virus
Authors: Rahman Md. Bokhtiar , Rahman Simo 
Published: October 2024

Abstract

Dengue fever is a vector-borne viral disease that is responsible for 25,000 people deaths per year globally. Elimination of the virus from the bloodstream of affected individuals is the primary goal of the treatment. However, there is no successful dengue vaccine candidate that can prevent this virus to date. The purpose of this study was to develop a potential vaccine by targeting B cell and T cell epitopes of DENV-1, DENV-2, DENV-3, and DENV-4 serotypes by using bioinformatics approaches. Epitopes were predicted from envelopes protein of DENV-1, DENV-2, and DENV-4 and polyprotein of DENV-3. These epitopes were analyzed and selected by layer-by-layer filtration method based on different bioinformatics approaches. DENV-BkS8 and DENV-BkS10 passed all filtration criteria, among all 21 constructed vaccine models. All selected epitope candidates showed good results in worldwide population coverage. DENV-BkS8 and DENV-BkS10 showed good docking properties against TLR 2, TLR4, HLA- A*02:01, and HLA- DRB1*01:01 and promising immunomodulation properties. Vaccine constructs were cloned into PET28a (+) vector for expression study in Escherichia coli. DENV-BkS8 and DENV-BkS10 proved effective in various computer-based immune response analyses. Laboratory-based studies and clinical trials will be needed for further confirmation of the efficacy and safety of vaccines.
Artificial Intelligence Methods to Assess the Decision Diagnosis in Chronic Wounds: A Systematic Review
Authors: Reifs-Jiménez David , Casanova-Lozano Lorena , Reig-Bolañoo Ramon , Grau-Carrión Sergi 
Published: October 2024

Abstract

Purpose
Chronic wounds, which take over six weeks to heal, are a major global health issue linked to conditions such as diabetes, venous insufficiency, arterial diseases, and pressure ulcers. These wounds cause pain, reduce quality of life, and impose significant economic burdens. This systematic review explores the impact of technological advancements on the diagnosis of chronic wounds, focus- ing on how computational methods in wound image and data analysis improve diagnostic precision and patient outcomes.
Methods
A literature search was conducted in databases including ACM, IEEE, PubMed, Scopus, and Web of Science, covering studies from 2013 to 2023. The focus was on articles applying complex computational techniques to analyze chronic wound images and clinical data. Exclusion criteria were non-image sam- ples, review articles, and non-English or non-Spanish texts. From 2711 articles identified, 93 full-text studies were selected for final analysis.
Results
From 2711 articles identified, 93 full-text studies were selected for final analysis. The review identified significant advancements in tissue classification, wound measurement, segmentation, prediction of wound aetiology, risk indica- tors, and healing potential. The use of image-based and data-driven methods has proven to enhance diagnostic accuracy and treatment efficiency in chronic wound care.
Conclusions
The integration of technology into chronic wound diagnosis has shown a transformative effect, improving diagnostic capabilities, patient care, and reducing healthcare costs. Continued research and innovation in computational techniques are essential to unlock their full potential in managing chronic wounds effectively.
Sociocultural Determinants and Behavioral Risk Factors of COVID-19: A Study of Knowledge, Attitudes, and Practices in Bangladesh
Authors: Das Jewel , Akter Dilruba 
Published: October 2024

Abstract

Experts say that community transmission of coronavirus connects to sociocultural and behavioral contexts. As such, it is necessary to understand the health behaviors of local people to explore the sociocultural determinants and socio-demographic risk factors that might be responsible for coronavirus infections. A study was done in five sub-districts of Chittagong, a southeastern district of Bangladesh, to generate evidence on sociocultural and behavioral perspectives of COVID-19 risk factors. Employing a mixed-methods research approach, this study observed 555 people and administered a vaccination survey to 200 respondents to understand individuals’ knowledge, attitudes, and practices toward COVID-19 safety measures. Researchers also conducted in-depth qualitative interviews with 20 key informants. Interview data was analyzed through thematic analysis, whereas descriptive statistics were used to analyze observational and survey data. Under the framework of the KAP model, the study results show that around half of the observed people do not wear face masks, and more than three-quarters do not maintain social distancing in public. The study also demonstrates no handwashing or hand-sanitizing facilities in over half of the observed places. The vaccination survey indicates that although 60.2% of respondents have been vaccinated, 21% of respondents do not know that they might be infected by the coronavirus even after getting vaccinated, whereas 15.5% do not know that vaccinated people still need to wear masks. Qualitative data shows that individuals’ perception of coronavirus was influenced by their sociocultural context of digesting mass media-generated COVID-19 knowledge and information. Unhealthy behavioral practices and undesirable attitudes of community members are also responsible for COVID-19 infections. From this perspective, examining individuals’ attitudes and views on the causes of COVID-19 might help in proper planning, designing, and implementing risk communication and community engagement interventions and policies to encounter the pandemic in Bangladesh.
A simple method for the measurement of Pelvic Incidence on standard lumbar CT and MRI studies
Authors: İplikçioğlu Ahmet Celal , Karabag Hamza 
Published: October 2024

Abstract

Purpose: This study aimed to describe a simple method for the measurement of pelvic incidence on standard lumbar CT and MRI studies not involving the femoral heads.
Methods: Three groups of asymptomatic participants were recruited according to radiological modalities (X-ray [n = 50], CT [n = 54], and MRI [n = 38]). In each group, the hip axis was found and PI was measured. Then the intersection point (X point) of a line connecting the midpoint of the sacral endplate to the posterior pubic end and a line connecting the anterior pubic edge to the inferior border of the S4 segment was determined and referred to as the new hip axis. Using this point, PI was measured again. The distances between the hip axis and the X point were measured in each group and the corresponding PI values were compared.
Results: The average distance between the hip axis and X point and the average PI difference were 4.39 ± 3.9 mm and 1.91°, 4.14 ± 3.2 mm and 0.80°, and 4.65 ± 2.94 mm and 0.23° in the X-ray, CT, and MRI groups. Likewise, the mean absolute difference between PI values in the X-ray, CT, and MRI groups was 2.4°, 2.9°, and 1.3°, respectively.
Conclusion: Determining the hip axis on standard spinal CT and MRI studies allows almost accurate measurement of PI (difference 1°–2o) without any additional time or cost. This method can be used routinely to measure PI on standard CT or MRI in clinical practice and research.
The Impact of Urbanization-Induced Eviction on Food Security of peri-urban households in Addis Ababa, Ethiopia
Authors: Gnamura Kejela , Antwi Michael , Abenet Belete 
Published: October 2024

Abstract

This study examines the effects of urbanization-induced displacement on the food security status of peri-urban farming households in Addis Ababa, Ethiopia. The study employed a mixed-methods approach to examine the impact of urbanization-induced eviction on food security in peri-urban farming households of Addis Ababa, Ethiopia. We employed multiple techniques of data analysis; namely, binary logistic regression, Sustainable Livelihood Security Index (SLSI), and thematic content analysis. The logistic regression analysis identified key factors influencing food security, including eviction, education levels, social capital, agricultural land security, and composite sustainable livelihood security index. The eviction status’s odds ratio (0.066) suggests that the odds of being food secure for evicted households are 93.4% lower than for non-evicted households. In other words, evicted households have approximately 1/15th the odds of being food secure compared to non-evicted households. The analysis confirms that the null hypothesis is rejected, implying urban eviction without appropriate policy measures would lead the evicted households into food insecurity. The findings highlight the need for targeted policies to protect agricultural land, support displaced communities, and ensure long-term food security in rapidly urbanising areas.
Organic cation transporter 3 on neuronal mitochondria mediates MPP + -induced mitochondrial dysfunction and neurotoxicity in a TIMM22-dependent manner
Authors: Guan Ao , Han Sida , Liang Suzhen , Shen Weiwei , Guo Min , Cui Mei 
Published: October 2024

Abstract

Background
Emerging evidence demonstrates the multifaceted roles of mitochondria in cellular metabolism. The intracellular compartmentalization of metabolites profoundly impacts mitochondrial function and the pathophysiology in many diseases. MPP+ compartmentalization is a well-established phenomenon in MPTP-dependent neurodegeneration. The accumulation of MPP+ in mitochondria contributes to mitochondrial dysfunction, such as respiratory chain inhibition, ultimately leading to neuronal death. However, the mechanisms underlying mitochondrial MPP+ accumulation remain poorly understood. Organic cation transporter 3 (OCT3), a passive transporter mediating MPP+ transport, has been observed on the mitochondrial membrane, but it remains unclear whether mitochondrial OCT3 is involved in MPP+ accumulation in mitochondria.
Results
OCT3 expression was detected in mitochondria fraction extracted from SH-SY5Y cells. Following MPP+ incubation, there was a significant increase in mitochondrial uptake of MPP+, which was mitigated by OCT inhibition. Knockdown of the inner mitochondrial membrane 22 (TIMM22), an important component of mitochondrial protein import apparatus, successfully reduced OCT3 levels on mitochondria without impairing mitochondrial morphology or function. This resulted in a decrease in mitochondrial uptake of MPP+, which in turn rescued MPP+-induced mitochondrial fragmentation, complex Ⅰ inhibition and mitochondrial membrane potential reduction. Furthermore, TIMM22 knockdown suppressed caspase-9 and caspase-3 activation and reversed the alterations of BAX and BCL-xL induced by mitochondrial MPP+ accumulation.
Conclusions
Here we found that OCT3 on neuronal mitochondria serves as an effective MPP+ transporter and plays a crucial role in mitochondrial MPP+ uptake as well as MPP+-induced neurotoxicity. Furthermore, our findings indicated that downregulation of TIMM22 can selectively reduce mitochondrial OCT3 and reverse MPP+-induced mitochondrial dysfunction and neurotoxicity, highlighting TIMM22 and OCT3 as potential therapeutic targets for MPP+-associated neurodegeneration and diseases.
Coronary microvascular disease is a risk factor for left ventricular diastolic dysfunction: An AWARD substudy
Authors: Wen Wei , Gao Mengjie , Chi Yi , Liu Mingwang , Xie Beili , Jiang Lulian , Chen Keji , Zhao Fuhai 
Published: October 2024

Abstract

Background:
Left ventricular diastolic dysfunction (LVDD) caused by myocardial ischemia is an important pathogenetic factor in the development of heart failure with preserved ejection fraction (HFpEF).
Objective:
To explore the differences in LVDD triggered by two ischemic injuries (microvascular lesions and epicardial stenosis).
Methods:
Angiographic function indicators involving angiography-derived index of microcirculatory (AMR) simulating hyperemic velocity (SHV) and diagnostic indicators for LVDD including average E/e', septal e’velocity, and lateral e’velocity (based on echocardiography) were derived from records of enrolled patients suffering from coronary microvascular disease (CMVD) or obstructive coronary artery disease (CAD) (without microvascular dysfunction). The linear correlation between AMR, SHV, and echocardiographic indicators was evaluated by the Spearman's coefficient method. And logistics regression analyses evaluated risk factors for LVDD. Besides, we performed the by stratified analysis to explore Differences in AMR and SHV distribution between LVDD and non-LVDD groups. Finally, receiver operating characteristic (ROC) analyses evaluated the efficacy of AMR in recognizing LVDD.
Results:
CMVD was more susceptible to LVDD compared to obstructive-CAD (18.8% vs. 6.2%). AMR, SHV were linearly correlated with the relevant indicators of LVDD. And in the CMVD group, AMR were higher in the LVDD group than in the non-LVDD group, while SHV was opposite. Furthermore, AMR promoted LVDD (OR=1.02), whereas SHV inhibited the formation of LVDD (OR=0.59). ROC analyses revealed AMR can identify LADD.
Conclusion:
Microvascular lesions are more susceptible to LVDD.
A Patient-Doctor-NLP-System to contest inequality for less privileged
Authors: DIKSHIT SUBRIT , TIWARI RITU , JAIN PRIYANK 
Published: October 2024

Abstract

Transfer Learning (TL) allowed development, generation and availability of various Large Language Models (LLMs) in Natural language processing (NLP) which emerged and became prevalent in this era. In real environments, training of gigantic LLM is not always feasible and there has been less energies put towards implementation of LLM based solutions that focus the least privileged such as visually impaired or who speak native languages such as Hindi while needing medical support in rural areas. To overcome this challenge, our work demonstrates an initiative which utilize our prescribed PDFTEMRA (Performant Distilled Frequency Transformer Ensemble Model with Random Activations) network. This network incorporates multiple advanced additional modifications to transformer-based structure and utilizes underlying concepts, such as, ensemble, distillation, frequency modulation, random activations, and supplementary forward-thinking scientific renovations.
Unraveling Interconnected Dynamics: Herpes Zoster, Postherpetic Neuralgia, and COVID-19 – A Bidirectional Mendelian Randomization Analysis
Authors: Chi Zhang , Xiang Wei , Xiao Li , Kejia Wang , Junyi Zheng 
Published: October 2024

Abstract

Objective: The COVID-19 pandemic has seen an increase in the number of patients experiencing herpes zoster (HZ) and postherpetic neuralgia (PHN), yet the association between these two conditions remains unclear. This study aims to investigate the causal relationship between SARS-CoV-2 infection and HZ as well as PHN, providing guidance for clinical intervention.
Methods: Employing Mendelian randomization to minimize bias at the methodological level, we conducted bidirectional Mendelian randomization to investigate pathogenic associations between diseases. Our research focused on the disease genetic data related to HZ and PHN within European populations sourced from FinnGen. Additionally, we utilized the severity and susceptibility phenotype data of COVID-19 from the largest GWAS dataset of COVID-19 as integral components of our investigation.
Results: Our study revealed that HZ may contribute to the onset of COVID-19, whereas COVID-19 does not elevate the susceptibility to HZ, and there is no apparent causal relationship between PHN and COVID-19.
Conclusion: The findings from this study suggest that the activation of varicella-zoster virus (VZV) may heighten the susceptibility of patients to COVID-19. These insights play a crucial role in guiding the development of more effective clinical intervention strategies, especially in the context of preventing COVID-19 among patients with HZ.
Is Science Driving Technology?
An Investigation in the Field of Breast Cancer:
Analysis of Polymerase Chain Reaction and CRISPR/Cas9
Authors: Grochau Christian 
Published: October 2024

Abstract

The debate about whether science drives technology or conversely remains unresolved. Various approaches have been proposed to determine the driving force and influence of science on technology. Numerous technologies have been analyzed and compared, and in some cases, science has been shown to drive technological progress, particularly in the field of biochemistry. However, whether the influence of science on different technologies within the same sector changes over time has not yet been investigated. This study analyzes how the influence of science on technologies in the field of breast cancer therapy has evolved over the years, using polymerase chain reaction and CRISPR/Cas9 as examples. For the study, two data sets were created for each technology: one for scientific publications and the other for patents. This approach allowed for the inclusion of approximately 1,800 articles and 400 patents. It was observed that in the case of CRISPR, the scientific literature is only slightly ahead of the patents. In addition, a shift in the patenting strategy of China and the USA was observed: from predominantly scientific activity to increased patenting. Although these two technologies are in a science-intensive field, there is little to no evidence of a significant time lag. The country analysis revealed that China, in particular, is increasingly focusing on commercial applications, more so than was previously observed with PCR.
Graph-Root: Prediction of Root-Associated Proteins in Maize, Sorghum, And Soybean Based on Graph Convolutional Network and Network Embedding Method
Authors: Zhou Bo , Liu Siyang , Chen Lei , Dai Qi 
Published: October 2024

Background:
The root system plays an irreplaceable role in plant growth. Its improvement
can increase crop productivity. However, such a system is still mysterious for us. The underlying
mechanism has not been fully uncovered. The investigation on proteins related to the root system
is an important means to complete this task. In the previous time, lack of root-related proteins
makes it impossible to adopt machine learning methods for designing efficient models for the discovery
of novel root-related proteins. Recently, a public database on root-related proteins was set up
and machine learning methods can be applied in this field.

Objective:
The purpose of this study was to design an efficient computational method to predict
root-associated proteins in three plants: maize, sorghum, and soybean.

Method:
In this study, we proposed a machine learning based model, named Graph-Root, for the
identification of root-related proteins in maize, sorghum, and soybean. The features derived from
protein sequences, functional domains, and one network were extracted, where the first type of features
were processed by graph convolutional neural network and multi-head attention, the second
type of features reflected the essential functions of proteins, and the third type of features abstracted
the linkage between proteins. These features were fed into the fully connected layer to make predictions.

Results:
The 5-fold cross-validation and independent tests suggested its acceptable performance. It
also outperformed the only previous model, SVM-Root. Furthermore, the importance of each feature
type and component in the proposed model was investigated.

Conclusion:
Graph-Root had a good performance and can be a useful tool to identify novel rootrelated
proteins. BLOSUM62 features were found to be important in determining root-related proteins.
Lokal forankring i storskala skoleutviklingsprosjekter – en evaluering av en modell for skolebasert kompetanseutvikling der mange skoler deltar
Authors: Kvithyld Trygve , Morud Elin Bø , Kvistad Anne Holten 
Published: October 2024

I 2018 ble det lansert en ny strategi for kompetanseutvikling i skolen (Dekom). En viktig intensjon ved denne strategien var at lærere og ledere sammen med UH-sektoren skal utvikle kunnskap om undervisning og læring i de lokale skolekontekstene. I Storbynettverket ble det utviklet en modell for å ivareta intensjonen bak strategien, kalt ressursgruppemodellen. Målet med denne studien er å evaluere ressursgruppemodellen og identifisere hvilke faktorer som synes å være viktige for å lykkes i et storskala skoleutviklingsprosjekt. Det empiriske grunnlaget for studien er data fra spørreundersøkelser og fokusgruppeintervju med involverte parter fra skoler og UH- miljø. Deltakerne fikk spørsmål om erfaringene de hadde gjort seg etter første pulje med Dekom i Storbynettverket. Funnene viser blant annet at ressursgruppemodellen har en fleksibilitet som gjør at mange skoler kan delta parallelt samtidig som opplevde lokale behov kan ivaretas. Samtidig ser stabil ledelse, myndiggjøring av ressursgruppene og reelle samskapingsprosesser mellom UH og skolene ut til å være viktige faktorer for å lykkes med en slik storskala skoleutviklingsmodell.
ENGLISH ABSTRACT
Local Anchoring in Large-Scale School Development Projects – An Evaluation of a Model for Competence Development in which Many Schools Participate
In 2018, a new strategy for competence development in schools (Dekom) was launched in Norway. An important intention of this strategy was for teachers and leaders, together with university employees, to develop knowledge about teaching and learning within local school contexts. In Storbynettverket, a model was developed to uphold the intention behind the strategy, called the resource group model. The aim of this study is to evaluate the resource group model and identify the factors that appear to be important for success in a large-scale school development project. The empirical basis for the study consists of data from surveys and focus group interviews with stakeholders from schools and universities. Participants were asked about their experiences after the first round of Dekom in Storbynettverket. Findings indicate that the resource group model has a flexibility that allows many schools to participate simultaneously while addressing perceived local needs. At the same time, stable leadership, empowerment of the resource groups, and genuine co-creation processes between higher education and schools seem to be important factors for success in a large-scale school development model.