bluuebunny/crossref_metadata_2025_split huggingface dataset:
Asymptotic analysis of mathematical model describing a new treatment of breast cancer using AZD9496 and palbociclib
Authors: Nave Ophir 
Published: January 2025

IntroductionCancer is a collective name for a group of diseases consisting of dozens of different types of malignant tumors, characterized by rapid and uncontrolled proliferation of cells in the body. Cancer can start almost anywhere in the human body such as the breast, prostate, colorectal, brain, bones, lungs, bladder etc. The main differences between the different types of cancer are related to the organ in which the tumor develops and the type of cells that compose the tumor.MethodThis paper focused on the breast cancer. Breast cancer is a malignant tumor that originates in the breast tissue. It is the most common malignant tumor in women. There are several types of breast cancer, but in all types early diagnosis and treatment is crucial. In this study, the treatment of breast cancer involving a combination of two drugs was investigated: the oral estrogen receptor inhibitor AZD9496 and the CDK4/6 protein inhibitor Palbociclib. The mathematical model that described the interaction between the cancer cells, the treatment, and the immune system cells includes a system of nonlinear ordinary differential equations of the firs order. In general, dynamic variables of a given system change each at a different rate. And it is not possible to know from the mathematical model which variable is fast and which is slow. Therefore, in order to reveal the hierarchy of the system of equations ,a numerical algorithm called the singularly perturbed vector field (SPVF) was applied. This algorithm transform the mathematical model to a new coordinate system in which the rate of change of each dynamic variable of the system can be known.Results and DiscussionAfter writing the mathematical model in new coordinates, the equilibrium point was obtained analytically. The stability of the equilibrium points is investigated, which is essential from a practical perspective. Investigating the stability of the equilibrium points allows determination of when the tumor does not continue to develop and thereby allows adjustment of treatment continuation.
Diagnosis of hepatocellular carcinoma using liquid biopsy-based biomarkers: a systematic review and network meta-analysis
Authors: Jiang Yutong , Qi Shangwen , Zhang Rongrong , Zhao Ruixia , Fu Yu , Fang Yuxuan , Shao Mingyi 
Published: January 2025

IntroductionThe diagnostic performance of liquid biopsy-based biomarkers for HCC was comprehensively compared in this network meta-analysis (NMA).MethodsA thorough literature search was conducted to identify all comparative studies from January 1, 2000, to January 11, 2024. The QUADAS-2 tool was utilized to appraise the quality of studies involving diagnostic performance. R (v4.3.3) and an ANOVA model-based NMA were used to assess the diagnostic accuracy of each biomarker.ResultsThis study included 82 studies comprising a total of 15,024 patients.CircRNA demonstrated significantly superior performance in distinguishing HCC from healthy populations (superiority index: 3.550 (95% CI [0.143-3])) compared to other diagnostic biomarkers for HCC. “mRNA exhibited significantly superior performance in distinguishing HCC from liver disease patients (superiority index:10.621 (95% CI [7-11])) compared to other diagnostic biomarkers for HCC. Further subgroup analysis of the top-ranking liquid biopsy-based diagnostic biomarkers revealed that hsa_circ_000224 (superiority index: 3.091 (95% CI[0.143-9]) ranked remarkably higher in distinguishing HCC from both healthy populations and liver disease patients. Subgroup analysis of mRNA demonstrated that KIAA0101 mRNA (superiority index: 2.434 (95% CI [0.2-5]) ranked remarkably higher in distinguishing HCC from healthy populations and liver disease patients, respectively.DiscussionThe results of this meta-analysis show that circRNA and mRNA are the first choice for HCC diagnosis. Subsequent analysis of circRNA and mRNA highlighted hsa_circ_000224, hsa_circ_0003998, KIAA0101 mRNA and GPC-3mRNA as the optimal diagnostic biomarkers for distinguishing HCC from healthy populations and liver disease patients, respectively. Well-structured prospective studies are crucial to comprehensively validate these findings.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/,identifier CRD42024521299.
Uncertainty quantification in multi-parametric MRI-based meningioma radiotherapy target segmentation
Authors: Wang Lana , Yang Zhenyu , LaBella Dominic , Reitman Zachary , Ginn John , Zhao Jingtong , Adamson Justus , Lafata Kyle , Calabrese Evan , Kirkpatrick John , Wang Chunhao 
Published: January 2025

PurposeThis work investigates the use of a spherical projection-based U-Net (SPU-Net) segmentation model to improve meningioma segmentation performance and allow for uncertainty quantification.MethodsA total of 76 supratentorial meningioma patients treated with radiotherapy were studied. Gross tumor volumes (GTVs) were contoured by a single experienced radiation oncologist on high-resolution contrast-enhanced T1 MRI scans (T1ce), and both T1 and T1ce images were utilized for segmentation. SPU-Net, an adaptation of U-Net incorporating spherical image projection to map 2D images onto a spherical surface, was proposed. As an equivalence of a nonlinear image transform, projections enhance locoregional details while maintaining the global field of view. By employing multiple projection centers, SPU-Net generates various GTV segmentation predictions, the variance indicating the model’s uncertainty. This uncertainty is quantified on a pixel-wise basis using entropy calculations and aggregated through Otsu’s method for a final segmentation.Results/conclusionThe SPU-Net model poses an advantage over traditional U-Net models by providing a quantitative method of displaying segmentation uncertainty. Regarding segmentation performance, SPU-Net demonstrated comparable results to a traditional U-Net in sensitivity (0.758 vs. 0.746), Dice similarity coefficient (0.760 vs. 0.742), reduced mean Hausdorff distance (mHD) (0.612 cm vs 0.744 cm), and reduced 95% Hausdorff distance (HD95) (2.682 cm vs 2.912 cm). SPU-Net not only is comparable to U-Net in segmentation performance but also offers a significant advantage by providing uncertainty quantification. The added SPU-Net uncertainty mapping revealed low uncertainty in accurate segments (e.g., within GTV or healthy tissue) and higher uncertainty in problematic areas (e.g., GTV boundaries, dural tail), providing valuable insights for potential manual corrections. This advancement is particularly valuable given the complex extra-axial nature of meningiomas and involvement with dural tissue. The capability to quantify uncertainty makes SPU-Net a more advanced and informative tool for segmentation, without sacrificing performance.
5-deoxy-rutaecarpine protects against LPS-induced acute lung injury via inhibiting NLRP3 inflammasome-related inflammation
Authors: Luo Jinque , Li Xin , Zhang Li , Deng Meijing , Zhao Jieyang , Zhang Jinghuan , Tang Wenyu , Guo Qinghua , Wang Ling 
Published: January 2025

IntroductionAcute lung injury (ALI) induced by lipopolysaccharide (LPS) is a significant medical condition characterized by severe pulmonary inflammation and tissue damage. NLRP3 inflammasome-driven inflammation is essential in ALI pathogenesis, inspiring novel therapeutic strategies that focus on NLRP3 and inflammation. In this study, we investigated the therapeutic potential of 5-deoxy-rutaecarpine (5-DR), a rutaecarpine derivative, in attenuating LPS-induced ALI.MethodsIn this study, we evaluated the effects of 5-DR treatment in mice exposed to LPS, lung tissues, bronchoalveolar lavage fluid, and serum were collected for analysis. LPS-stimulated J774A.1 mouse macrophages were used to further investigate the anti-inflammatory effects of 5-DR in vitro. Various techniques including histopathology, Western blotting, and luciferase reporter assay were employed.Results5-DR treatment significantly reduced lung edema, inflammatory cell infiltration in mice with LPS burden, and reduced the levels of inflammatory mediators like interleukin-1β in the mice and in LPS-stimulated J774A.1 mouse macrophages. Further western blotting analysis showed 5-DR decreased the levels of NLRP3, cleaved caspase-1, and mature IL-1β in mice and J774A.1 cells exposed to LPS. Additionally, NF-κB pathway activation significantly diminished the inhibition of the NLRP3 inflammasome by 5-DR.DiscussionOur findings highlight the therapeutic potential of 5-DR as a promising candidate for treating LPS-induced ALI, offering insights into its underlying mechanism that targets NLRP3 inflammasome-mediated inflammation.
Efficacy of personalized feedback in encouraging sustainable washing behavior: evidence from a pilot study in Germany
Authors: Höpfl Laura , Đula Ivan , Kiss Francisco , Walter Rebecca , Wirzberger Maria 
Published: January 2025

IntroductionReducing household energy consumption through behavioral changes is a key strategy in addressing the emissions driving the climate crisis. Behavioral changes in affluent households toward more sustainable practices can have a significant positive impact. Prior research highlighted the role of individual values and motivational factors in shaping sustainable clusters. A more personalized approach toward encouraging the resulting clusters of people to adopt more sustainable strategies seems promising. Such an approach could incorporate aligned feedback, which has been proven to be a powerful mechanism throughout learning processes.MethodOver 9 weeks, a pilot study with 50 participants investigated the impact of different types of feedback on washing behavior. The within-subjects design included (1) a baseline condition, (2) feedback on energy consumption (kWh), and (3) feedback on monetary costs per cycle (EUR). Data collection encompassed pre- and post-condition surveys, a final comprehensive survey, and a diary-formatted table. The primary objective was to evaluate the potential for individualization. Asynchronous structured interviews were conducted at the end to explore participants' perceptions and washing behaviors.ResultsWhile we found effects for the feedback manipulation, we found no differences between user clusters in individual washing behaviors. Furthermore, participants qualitatively reported habitual changes, feeling more knowledgeable about the monetary impacts of specific washing programs and temperatures, and wished for a more accessible preset time function. Most participants expressed willingness to switch to a dynamic energy price if it translated to significant cost savings.DiscussionOur findings may support the notion that individualized behavior change strategies are promising. In general, these strategies should be easily applicable, cost-effective, and promote habits to be exerted regularly. Arising methodological limitations suggest further research in this domain. From an applied perspective, our research provides valuable insights for designing products, services, and regulations by governments and companies, empowering them to develop more effective strategies for reducing energy consumption.
Machine learning for the diagnosis accuracy of bipolar disorder: a systematic review and meta-analysis
Authors: Pan Yi , Wang Pushi , Xue Bowen , Liu Yanbin , Shen Xinhua , Wang Shiliang , Wang Xing 
Published: January 2025

BackgroundDiagnosing bipolar disorder poses a challenge in clinical practice and demands a substantial time investment. With the growing utilization of artificial intelligence in mental health, researchers are endeavoring to create AI-based diagnostic models. In this context, some researchers have sought to develop machine learning models for bipolar disorder diagnosis. Nevertheless, the accuracy of these diagnoses remains a subject of controversy. Consequently, we conducted this systematic review to comprehensively assess the diagnostic value of machine learning in the context of bipolar disorder.MethodsWe searched PubMed, Embase, Cochrane, and Web of Science, with the search ending on April 1, 2023. QUADAS-2 was applied to assess the quality of the literature included. In addition, we employed a bivariate mixed-effects model for the meta-analysis.Results18 studies were included, covering 3152 participants, including 1858 cases of bipolar disorder. 28 machine learning models were encompassed. Sensitivity and specificity in discriminating between bipolar disorder and normal individuals were 0.88 (9.5% CI: 0.74~0.95) and 0.89 (95% CI: 0.73~0.96) respectively, and the SROC curve was 0.94(95% CI: 0.92~0.96). The sensitivity and specificity for distinguishing between bipolar disorder and depression were 0.84 (95%CI: 0.80~0.87) and 0.82 (95%CI: 0.75~0.88) respectively. The SROC curve was 0.89 (95%CI: 0.86~0.91).ConclusionsMachine learning methods can be employed for discriminating and diagnosing bipolar disorder. However, in current research, they are predominantly utilized for binary classification tasks, limiting their progress in clinical practice. Therefore, in future studies, we anticipate the development of more multi-class classification tasks to enhance the clinical applicability of these methods.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023427290, identifier CRD42023427290.
Exploring the application of AI in the education of children with autism: a public health perspective
Authors: Lan Liu , Li Ke , Li Diao 
Published: January 2025

IntroductionAutism Spectrum Disorder (ASD) presents significant challenges in social communication and interaction, critically impacting the lives of children with ASD. Traditional interventions, such as Applied Behavior Analysis (ABA) and Social Skills Training (SST), have been widely used to address social skill deficits in these children. While these methods are effective, they often require substantial resources, long-term engagement, and specialized expertise, which limit their accessibility and adaptability to diverse social contexts. Recent advancements in artificial intelligence (Al), particularly Transformer-based models, offer a novel opportunity to enhance and personalize social skills training.MethodsThis study introduces a Public Health-Driven Transformer (PHDT) model specifically designed to improve social skills in children with ASD. By integrating public health principles with state-of-the-art Al methodologies, the PHDT model creates interventions that are adaptable, accessible, and sensitive to individual needs. Leveraging multi-modal data inputs-such as text, audio, and facialcues-PHDT provides real-time social context interpretation and adaptive feedback, enabling a more naturalistic and engaging learning experience.Results and discussionExperimental results reveal that PHDT significantly outperforms traditional methods in fostering engagement, retention, and social skill acquisition. These findings highlight PHDT's potential to improve social competencies in children with ASD and to revolutionize access to specialized support within public health frameworks. This work underscores the transformative impact of Al-driven, public health-oriented interventions in promoting equitable access to essential developmental resources and enhancing the quality of life for children with ASD.
Global burden of burns among children and adolescents: a trend analysis from the global burden of disease study 2019
Authors: Zhu Hao , Wang Ke , Liu Xiong , Ji Jianfeng , Yang Peng , Xu Feng 
Published: January 2025

PreciseThis study investigates global trends in burns among children and adolescents using data from the Global Burden of Disease Study 2019. Analyzing incidence and YLD rates across 204 countries from 1990 to 2019 reveals a general decline in burn-related injuries, with age and sex influencing trends. Notably, in high-SDI regions, incidence rates initially increased before reversing. These findings highlight the need for targeted public health policies and resource allocation to reduce burn-related risks in vulnerable populations.BackgroundGiven the lack of long-term trend studies on global burns among children and adolescents, this study examined trends in the global burden of burns among children and adolescents.MethodsThe Global Burden of Disease (GBD) Study 2019 provided the statistical data. Sex, age, region, and SDI were used as stratification variables in the study to evaluate the prevalence of burns injuries among kids and teenagers across 204 nations and territories between 1990 and 2019. YLD rates per 100,000 people and incidence rates together with their respective average annual percentage changes (AAPC) were computed to evaluate burden trends. Furthermore, AAPC in YLD rates and incidence rates spanning various age cohorts were analyzed using the Joinpoint software.ResultsThe worldwide burns incidence and YLD rates of burns among kids and teenagers exhibited a general declining trend between 1990 and 2019. Concerning the general trend in new cases, incidence rates, and YLD rates, age was positively associated. In 2019, the incidence rate for females surpassed that of males, while YLD rates for females were consistently higher than those of males. New Zealand, Czechia, and Australia rank as the top three among the 204 countries studied. Interestingly, in the high SDI range, the expected values based on incidence rates reversed after first rising with the SDI.ConclusionOverall, the incidence and YLD rates of burns among children and adolescents have declined globally, though significant disparities exist across age groups, sexes, regions, and countries. These findings could help guide the development of more targeted strategies to reduce the burn burden in this population.
Perspectives of health workers on the facilitators and barriers to antiretroviral therapy adherence following intensive adherence counseling in Northern Uganda
Authors: Beja Humphrey , Nakayiwa Daisy , Owachgiu Innocent Ocitti , Edek Micheal Tonny , Kobusinge Veronic , Akaki Oscar , Udho Samson 
Published: January 2025

BackgroundIn some contexts, people living with HIV (PLWH) who are virally non-suppressed and participating in an intensive adherence counseling (IAC) program have demonstrated non-adherence to antiretroviral therapy (ART) even after IAC. There is limited literature on the facilitators and barriers to ART adherence following IAC.ObjectiveThis study aimed to explore the perspectives of healthcare workers (HCWs) on the facilitators and barriers to ART adherence following IAC among PLWH in Northern Uganda.MethodsThis was a descriptive qualitative study conducted among HCWs at the ART clinics of the two highest-volume public health facilities in Lira District. We purposively sampled 15 study participants and conducted face-to-face in-depth interviews using an interview guide formulated based on the components of the Capability, Opportunity, and Motivation framework for Behavior change (COM-B framework). Thematic analysis was used based on the COM-B framework. In this study, the desired behavior was ART adherence following IAC. Factors that were perceived to positively affect any component of the COM-B framework were classified as facilitators and those that were perceived to negatively affect were classified as barriers.ResultsThe majority of the participants were females (53%), diploma holders (40%), and nurses (40%). The perceived facilitators and barriers to ART adherence following IAC emerged as six key themes under the subdivisions of the three domains of the COM-B framework: cognitive and emotional processes, physical and practical skills, accessibility and material resources, social relationships and cultural dynamics, cognitive beliefs and aspirations, and finally, emotional and subconscious drivers. These themes were identified as either facilitators or barriers to ART adherence following IAC depending on the lenses of interpretation.ConclusionsThis study offers a multidimensional insight into the facilitators and barriers to ART adherence following IAC and how the behavior influencing ART adherence can be optimized. The results suggest that optimizing cognitive and emotional processes, physical and practical skills, accessibility and material resources, social relationships and cultural dynamics, cognitive beliefs and aspirations, and emotional and subconscious drivers during IAC and any ART adherence-related intervention could yield the best level of ART adherence among the PLWH who are virally non-suppressed and on ART.
Hypovitaminosis and its association with recurrent aphthous stomatitis: a comprehensive review of clinical correlations and diagnostic considerations
Authors: Rosa Alessio , Cianconi Giovanni , De Angelis Riccardo , Pujia Alberto Maria , Arcuri Claudio 
Published: January 2025

BackgroundHypovitaminosis, or vitamin deficiency, has been increasingly recognized as a potential contributing factor in the development of recurrent aphthous stomatitis (RAS), a condition characterized by the periodic formation of painful ulcers in the oral mucosa.Materials and methodsThis mini review includes a literature search on PubMed, Web of Science, and Scopus databases using keywords “hypovitaminosis AND aphthous ulcers.”ResultsThere is a growing body of evidence supporting the link between various vitamin deficiencies—particularly vitamins B12, C, and folate—and the prevalence of RAS, with implications for both diagnosis and management.ConclusionThis review aims to outline the clinical and biochemical findings associated with hypovitaminosis in individuals presenting with RAS, emphasizing the diagnostic importance of recognizing vitamin deficiencies in these patients and exploring possible therapeutic approaches.
Eating green in Copenhagen: organic consumers’ path to less meat and minimal food waste
Authors: Matthiessen Lea Ellen , Smed Sinne , Jensen Jørgen Dejgård , Średnicka-Tober Dominika , Rossi Laura , Bügel Susanne Gjedsted 
Published: January 2025

IntroductionUnsustainable and unhealthy food consumption is contributing significantly to the global greenhouse gases and leads to severe health problems. The largest contributors are consumers in high-income countries, such as Denmark, with large shares of meat and high amounts of food waste.MethodsTaking Copenhagen (the capital) as a case, we aim to explore more sustainable and healthier dietary behaviours based on the organic food share in combination with dietary composition, food waste and attitudes towards change. This mixed-method study used quantitative data from an anonymous online survey and qualitative data from semi-structured interviews. For statistical analysis, 279 adult survey participants were divided into three subgroups; “low”– with up to 25% organic food share, “medium”– 26-75% organic food share and “high”– 76-100% organic food share.ResultsThis study found significant differences of food intake between the subgroups for fruits &amp; vegetables, legumes, nuts, whole grain cereals and meat. In those food categories, the share of respondents complying with the official dietary recommendations was higher for the “high” and “medium” than for the “low” organic subgroup. At the level of public procurement, meat was reduced to provide “a room for economic manoeuvre” due to higher organic price premiums. In conclusion, in Copenhagen we observed that an increased share of organic food comes along with other sustainable dietary behaviour, both at household and public kitchen level.DiscussionHouseholds appear motivated by societal momentum toward more sustainable diets. The public food procurement has largely been driven by politically determined goals. Further studies are needed to better understand how food systems can support the adoption of healthier, more sustainable diets — emphasizing increased plant-based foods and reduced food waste.