bluuebunny/crossref_metadata_2025_split huggingface dataset:
Changes in the association between educational achievement, attainment and subsequent mental health: A survival analysis of 21 Swedish graduation cohorts
Authors: Högberg Björn , Strandh Mattias , Petersen Solveig 
Published: October 2024

Abstract
Background
Low academic achievement and low educational attainment in adolescence is associated with higher risks of internalizing disorders later in life. However, less is known regarding if these associations vary over time across cohorts. The aim of this study was to investigate temporal changes in the association between academic achievement or educational attainment and subsequent inpatient treatment for internalizing disorders among Swedish youths.

Methods
Register data on all students graduating from compulsory school in Sweden between 1990 and 2010 (N = 2 252 703) were used. Students were followed for a maximum of 8 years using discrete time proportional hazard models. Internalized disorders were measured by specialized inpatient psychiatric care for depression or anxiety disorders. Academic achievement was measured by grades at the end of compulsory school, and educational attainment by completion of upper secondary school.

Results
The positive association between inpatient treatment for internalizing disorders and both low compulsory school achievement and non-completion of upper secondary school became stronger in more recent cohorts. The results were completely driven by girls and native-born youth.

Conclusions
Low compulsory school achievements and failure to complete upper secondary school has become more important risk factors for inpatient treatment for internalizing disorders, particularly in native-born youth and girls. More research is needed to establish whether youth with internalizing disorders increasingly fail in school or whether low achievement has become more harmful for mental health.
Uncovering the therapeutic potential of green pea waste in breast cancer: a multi-target approach utilizing LC-MS/MS metabolomics, molecular networking, and network pharmacology
Authors: Khalil Asmaa M. , Sabry Omar M. , El-Askary Hesham I. , El Zalabani Soheir M. , Eltanany Basma M. , Pont Laura , Benavente Fernando , Mohamed Ahmed F. , Fayek Nesrin M. 
Published: October 2024

Abstract
Background Pisum sativum
(PS) is a universal legume plant utilized for both human and animal consumption, particularly its seeds, known as green peas. The processing of PS in food industries and households produces a significant amount of waste that needs to be valorized.

Methods
In this study, the metabolite profiles of the 70% ethanolic extracts of PS wastes, namely peels (PSP) and a combination of leaves and stems (PSLS), were investigated by liquid chromatography-electrospray ionization-quadrupole time-of-flight tandem mass spectrometry (LC-ESI-QTOF-MS/MS) followed by molecular networking.

Results
Different classes of metabolites were identified, being flavonoids and their derivatives, along with phenolic acids, the most abundant categories. Additionally, a comprehensive network pharmacology strategy was applied to elucidate potentially active metabolites, key targets, and the pathways involved in cytotoxic activity against breast cancer. This cytotoxic activity was investigated in MCF-7 and MCF-10a cell lines. Results revealed that PSLS extract exhibited a potent cytotoxic activity with a good selectivity index (IC50 = 17.67 and selectivity index of 3.51), compared to the reference drug doxorubicin (IC50 = 2.69 µg/mL and selectivity index of 5.28). Whereas PSP extract appeared to be less potent and selective (IC50 = 32.92 µg/mL and selectivity index of 1.62). A similar performance was also observed for several polyphenolics isolated from the PSLS extract, including methyl cis p-coumarate, trans p-coumaric acid, and liquiritigenin/ 7-methyl liquiritigenin mixture. Methyl cis p-coumarate showed the most potent cytotoxic activity against MCF-7 cell line and the highest selectivity (IC50 = 1.18 µg/mL (6.91 µM) and selectivity index of 27.42). The network pharmacology study revealed that the isolated compounds could interact with several breast cancer-associated protein targets including carbonic anhydrases 1, 2, 4, 9, and 12, as well as aldo-keto reductase family 1 member B1, adenosine A3 receptor, protein tyrosine phosphatase non-receptor type 1, and estrogen receptor 2.

Conclusion
The uncovered therapeutic potential of PSLS and its metabolite constituents pave the way for an efficient and mindful PS waste valorization, calling for further in-vitro and in-vivo research.

Graphical Abstract
3D-printed tooth for caries excavation
Authors: Carnier Lisanne , del Hougne Michael , Schmitter Marc , Höhne Christian 
Published: October 2024

Abstract
Background
To date, no suitable model tooth has been available for all standard restorative and prosthodontic procedures. To fill this gap, a realistic multilayer tooth with enamel, dentin, integrated caries, pulp, and electrometric and X-ray imaging abilities was developed. The aim of this study was to test the printed tooth while focusing on caries excavation and pulp capping.

Methods
Based on micro-CT data, a tooth was designed and produced via 3D printing. A total of 396 teeth were tested and evaluated by 66 fourth- and fifth-year students experienced in caries excavation at standard typodonts, extracted teeth and patients. They excavated the caries and capped the pulp on six teeth and rated them in a questionnaire.

Results
Compared with natural teeth, the printed teeth were generally rated positively and significantly better in all criteria than typodonts used previously (p < .001). They were rated as a suitable training option (Ø 2.3 ± 0.9) with fair examination conditions (Ø 2.1 ± 0.8) and easy to use (Ø 2.0 ± 0.8). Subjective learning success was also significantly greater (Ø 2.3 ± 0.9) than that of standard typodonts (Ø 3.2 ± 1.1) (p < .001). In general, the students desired more exercises with 3D-printed teeth for their studies (Ø 1.8 ± 0.8).

Conclusions
Multilayered 3D-printed teeth were successfully tested and can improve and extend the teaching methods used for caries excavation and pulp capping. Its other abilities will be tested in subsequent studies.

Year of the Study
2023.
Assessing the reliability of medical resource demand models in the context of COVID-19
Authors: Dautel Kimberly , Agyingi Ephraim , Pathmanathan Pras 
Published: October 2024

Abstract
Background
Numerous medical resource demand models have been created as tools for governments or hospitals, aiming to predict the need for crucial resources like ventilators, hospital beds, personal protective equipment (PPE), and diagnostic kits during crises such as the COVID-19 pandemic. However, the reliability of these demand models remains uncertain.

Methods
Demand models typically consist of two main components: hospital use epidemiological models that predict hospitalizations or daily admissions, and a demand calculator that translates the outputs of the epidemiological model into predictions for resource usage. We conducted separate analyses to evaluate each of these components. In the first analysis, we validated various hospital use epidemiological models using a recent validation framework designed for epidemiological models. This allowed us to quantify the accuracy of the models in predicting critical aspects such as the date and magnitude of local COVID-19 peaks, among other factors. In the second analysis, we evaluated a range of demand calculators for ventilators, medical gowns, and COVID-19 test kits. To achieve this, we decoupled these demand calculators from the underlying epidemiological models and provided ground truth data for their inputs. This approach enabled a direct comparison of the demand calculators, comparing them against each other and actual usage data when available. The code is available at https://doi.org/10.5281/zenodo.13712387.

Results
Performance varied greatly across the epidemiological models, with greater variability in COVID-19 hospital use predictions than for COVID-19 deaths as analyzed previously. Some models did not have any peaks. Among those that did, the models under-estimated date of peak approximately as often as they over-estimated, but were more likely to under-estimate magnitude of peak, with typical relative errors around 50%. Regarding demand calculator predictions, there was significant variability, including five-fold differences in predictions for gown models. Validation against actual or surrogate usage data illustrated the potential value of demand models while demonstrating their limitations.

Conclusions
The emerging field of demand modeling holds promise in averting medical resource shortages during future public health emergencies. However, achieving this potential necessitates focused efforts on standardization, transparency, and rigorous model validation before placing reliance on demand models in critical public health decision-making.
The administration of immune checkpoint inhibitors via an elastomeric pump versus conventional intravenous infusion: an economic perspective
Authors: Zietse Michiel , Malmberg Ruben , van Leeuwen Roelof W.F. , Thielen Frederick W. , Uyl – de Groot Carin A. 
Published: October 2024

Abstract
Background
Recent studies have underscored the potential of innovative administration methods to mitigate the capacity burden on healthcare systems, without compromising the quality of care. This study assessed and compared the resource utilization and associated costs of two distinct administration modes of immune checkpoint inhibitors: the innovative elastomeric pump and conventional intravenous infusion. This comparison can inform sustainable healthcare practices and healthcare decision-making to optimize treatment efficiency in an era of escalating healthcare demands.

Methods
In this micro-costing study, data on resource use and time allocation for drug preparation and administration were collected using an observational, non-interventional study design. Data were registered at the oncology daycare unit and hospital pharmacy. Cost categories included drug acquisition, disposable materials, healthcare professional time for drug administration, drug preparation, and patient time spent at the oncology day care unit.

Results
Drug administration through the elastomeric pump resulted in substantially lower healthcare costs when compared to conventional infusion, particularly due to reduced labor and chair time. The elastomeric pump reduced the total chair time by 78% and nurse time by 55%. Total average costs (excluding drug costs) were €103,47 and €77.99 for conventional infusion and the elastomeric pump, respectively, showcasing potential savings of €25.48 (P < 0.001) per administration.

Conclusions
This study demonstrated that the elastomeric pump not only offers substantial cost savings but also enhances the treatment capacity of the oncology day care unit. These findings support the adoption of the elastomeric pump in clinical settings as a cost-saving and efficient alternative to conventional infusion.

Trial registration
This study has been registered in the National Trial Register (NTR), with the reference number NTR NL9473. Registration date: 05-05-2021.
Exosome-based immunotherapy as an innovative therapeutic approach in melanoma
Authors: Babaei Shabnam , Fadaee Manouchehr , Abbasi-kenarsari Hajar , Shanehbandi Dariush , Kazemi Tohid 
Published: October 2024

AbstractThe malignant form of melanoma is one of the deadliest human cancers that accounts for almost all of the skin tumor-related fatalities in its later stages. Achieving an exhaustive understanding of reliable cancer-specific markers and molecular pathways can provide numerous practical techniques and direct the way toward the development of rational curative medicines to increase the lifespan of patients. Immunotherapy has significantly enhanced the treatment of metastatic and late-stage melanoma, resulting in an incredible increase in positive responses to therapy. Despite the increasing occurrence of melanoma, the median survival rate for patients with advanced, inoperable terminal disease has increased from around six months to almost six years. The current knowledge of the tumor microenvironment (TME) and its interaction with the immune system has resulted in the swift growth of innovative immunotherapy treatments. Exosomes are small extracellular vesicles (EVs), ranging from 30 to 150 nm in size, that the majority of cells released them. Exosomes possess natural advantages such as high compatibility with living organisms and low potential for causing immune reactions, making them practical for delivering therapeutic agents like chemotherapy drugs, nucleic acids, and proteins. This review highlights recent advancements in using exosomes as an approach to providing medications for the treatment of melanoma.
A quantitative model using multi-parameters in dual-energy CT to preoperatively predict serosal invasion in locally advanced gastric cancer
Authors: Liu Yiyang , Yuan Mengchen , Zhao Zihao , Zhao Shuai , Chen Xuejun , Fu Yang , Shi Mengwei , Chen Diansen , Hou Zongbin , Zhang Yongqiang , Du Juan , Zheng Yinshi , Liu Luhao , Li Yiming , Gao Beijun , Ji Qingyu , Li Jing , Gao Jianbo 
Published: October 2024

Abstract
Objectives
To develop and validate a quantitative model for predicting serosal invasion based on multi-parameters in preoperative dual-energy CT (DECT).

Materials and methods
A total of 342 LAGC patients who underwent gastrectomy and DECT from six centers were divided into one training cohort (TC), and two validation cohorts (VCs). Dual-phase enhanced DECT-derived iodine concentration (IC), water concentration, and monochromatic attenuation of lesions, along with clinical information, were measured and collected. The independent predictors among these characteristics for serosal invasion were screened with Spearman correlation analysis and logistic regression (LR) analysis. A quantitative model was developed based on LR classifier with fivefold cross-validation for predicting the serosal invasion in LAGC. We comprehensively tested the model and investigated its value in survival analysis.

Results
A quantitative model was established using IC, 70 keV, 100 keV monochromatic attenuations in the venous phase, and CT-reported T4a, which were independent predictors of serosal invasion. The proposed model had the area-under-the-curve (AUC) values of 0.889 for TC and 0.860 and 0.837 for VCs. Subgroup analysis showed that the model could well discriminate T3 from T4a groups, and T2 from T4a groups in all cohorts (all p < 0.001). Besides, disease-free survival (DFS) (TC, p = 0.015; and VC1, p = 0.043) could be stratified using this quantitative model.

Conclusion
The proposed quantitative model using multi-parameters in DECT accurately predicts serosal invasion for LAGC and showed a significant correlation with the DFS of patients.

Critical relevance statement
This quantitative model from dual-energy CT is a useful tool for predicting the serosal invasion of locally advanced gastric cancer.

Key Points

Serosal invasion is a poor prognostic factor in locally advanced gastric cancer that may be predicted by DECT.

DECT quantitative model for predicting serosal invasion was significantly and positively correlated with pathologic T stages.

This quantitative model was associated with patient postoperative disease-free survival.

Graphical Abstract
Stroke patient and stakeholder engagement (SPSE): concepts, definitions, models, implementation strategies, indicators, and frameworks—a systematic scoping review
Authors: Khankeh Hamidreza , Guyatt Gordon , Shirozhan Shima , Roudini Juliet , Rackoll Torsten , Dirnagl Ulrich 
Published: October 2024

Abstract

Background

Involving stroke patients in clinical research through patient engagement aims to ensure that studies are patient-centered, and may help ensure they are feasible, ethical, and credible, ultimately leading to enhanced trust and communication between researchers and the patient community. In this study, we have conducted a scoping review to identify existing evidence and gaps in SPSE.

Methods
The five-step approach outlined by Arksey and O’Malley, in conjunction with the Preferred Reporting Items for Scoping Reviews (PRISMA-ScR) guidelines, provided the structure for this review. To find relevant articles, we searched PubMed, Web of Science, and Embase databases up to February 2024. Additionally, the review team conducted a hand search using Google Scholar, key journals, and references of highly relevant articles. Reviewers screened articles, selecting eligible English-language ones with available full texts, and extracted data from them into a pre-designed table tested by the research team.

Result
Of the 1002 articles initially identified, 21 proved eligible. Stakeholder engagement primarily occurred during the design phase of studies and within the studies using qualitative methodologies. Although the engagement of stakeholders in the research process is increasing, practice regarding terminology and principles of implementation remains variable. Researchers have recognized the benefits of stakeholder engagement, but have also faced numerous challenges that often arise during the research process.

Conclusion
The current study identifies stakeholder groups and the benefits and challenges researchers face in implementing their engagement. Given existing challenges and limited specific models or frameworks, it is suggested to explore applied recommendations for stakeholder engagement in future studies, that may enhance stakeholder engagement, overcome obstacles, and unify researchers’ understanding of engagement and implementation.
Expanding access to addictions care: Implementation of a 24-hour healthcare provider support line in British Columbia, Canada
Authors: Sergeant Anjali , Giesler Amanda , Goel Nirupa , Bach Paxton 
Published: October 2024

Abstract
Background
Morbidity and mortality related to substance use have risen to catastrophic levels in North America, and treatment services are often difficult to access. In response, the province of British Columbia (BC), Canada, launched a province-wide addiction medicine support phone line that offers clinicians immediate access to phone consultation with an addictions medicine expert. The service operates 24/7 is accessible to any clinician in the province seeking assistance with an addiction-related question. We describe an evaluation of the reach and perceived impact of the service over its first two years.

Methods
The 24/7 Addiction Medicine Clinician Support Line was evaluated prospectively from June 2020 to April 2022. All provider-to-provider encounters were included. Data was collected from two primary sources: health provider demographic information collected at the time of consultation, and optional clinician surveys conducted after the consultation was complete. Descriptive data are presented as numerical values and percentages.

Results
Over the 22-month evaluation period, 1,279 consultations were requested by 631 distinct care providers across British Columbia. The service averaged 15 calls per week across the province, and 51.5% of calls were made outside of business hours. Physicians made the majority of calls to the service (n = 865, 67.6%), followed by nurse practitioners (n = 162, 12.7%). Among those who completed a follow-up survey (n = 258 calls, 20.2% total calls), 81.8% (n = 211) were “very” or “extremely” satisfied with the consultation. Of these respondents, 65.5% (n = 169) reported that the consultation led to the provision of better care for their patient, with 58.1% (n = 150) initiating a new prescription and 22.1% (n = 57) reporting expedited treatment for their patient. The consultation area of focus was most commonly opioid use (n = 417; 59.6%), followed by polysubstance use (n = 98; 14.0%).

Conclusions
The impact of the 24/7 Addiction Clinician Support Line was widespread, and the service increased accessibility to evidence-based addictions treatment across a range of care settings. Clinicians expressed a high degree of satisfaction with the service. To our knowledge, this province-wide program is the first of its kind in North America, offering a scalable and adaptable model to support access to evidence-based addictions care in under-resourced settings.
Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions
Authors: Kumarappan Jayaraman , Rajasekar Elakkiya , Vairavasundaram Subramaniyaswamy , Kotecha Ketan , Kulkarni Ambarish 
Published: October 2024

AbstractPredicting stock market behavior using sentiment analysis has become increasingly popular, as customer responses on platforms like Twitter can influence market trends. However, most existing sentiment-based models struggle with two major issues: inaccuracy and high complexity. These problems lead to frequent prediction errors and make the models difficult to implement in real-time trading systems. To address these challenges, this paper proposes a new method called Siagra-ConSA-HSOA (Siamese Graph Convolutional Split-Attention Network with NLP-based Social Sentiment Data). Two data sources feed the model: specifically, NIFTY-50 Stock Market and real-time Twitter sentiment. Through Natural Language Processing (NLP), the raw data is pre-processed and key features are extracted before they are fused into a unified dataset using a cross-domain transformer, namely CDSFT, and then Circle-Inspired Optimization Algorithm (CIOA) selects the most important features from this dataset. This decreases the complexity of the model without losing essential information. Finally, a Graph Convolutional Split-Attention Network (SGCSAN) for promisingly predicting whether the stock prices are going to hit the ground and fly high again or is going to nosedive with Humboldt Squid Optimization Algorithm (HSOA) is introduced to further improve accuracy with lesser error generation. The proposed model Siagra-ConSA-HSOA achieved 99.9% accuracy and 99.8% recall in the testing stage, meaning that such a model performs better than the current approaches both in prediction accuracy and efficiency. Thus, this is a glimmer that the model shall be able to overcome some of the main problems with the current techniques used in predicting the behavior of the stock market.GitHub Repository: https://github.com/jramans2/Siamese-GCN-SplitAttention-Stock-Prediction.git
Comments on: prevalence and risk factors for tuberculosis and HIV coinfections in Kenyan prison inmates
Authors: Hamza Muhammad , Jalil ZIL-E-Huma , Sattar Abid Jan Abdul , Sohail Hamnah , Oduoye Malik Olatunde 
Published: October 2024

AbstractThe study by Mwatenga et al. found a tuberculosis (TB) prevalence of 10.2% and an HIV prevalence of 19.1% among inmates, with all TB cases co-infected with HIV. Education level, smoking history, and substance use are key predictors of coinfections. Although informative, its single-centred design and reliance on sputum samples may be insufficient for some patient groups, potentially compromising diagnostic accuracy. Expanding the study to include several jails and employing more diagnostic procedures may increase reliability and the ability to generalize. The report also notes the lack of debate on broader socioeconomic variables and structural barriers to healthcare in jails, which are crucial to understanding inmates' health challenges. Overcrowding, malnutrition, and a poor healthcare system are examples of environmental factors that probably contribute to the spread of tuberculosis and make managing HIV more difficult. Additionally, not enough is known about the dietary habits of prisoners and other health conditions like diabetes or mental health, which may have an impact on the course of HIV and TB. Future studies should take these extra characteristics into account to create more comprehensive approaches to controlling HIV coinfections and TB in prison populations. This will help build more effective therapies.