bluuebunny/crossref_metadata_2025 huggingface dataset:
Unveiling interactions between intervertebral disc morphologies and mechanical behavior through personalized finite element modeling
Authors: Muñoz-Moya Estefano , Rasouligandomani Morteza , Ruiz Wills Carlos , Chemorion Francis Kiptengwer , Piella Gemma , Noailly Jérôme
Published: June 2024

Introduction: Intervertebral Disc (IVD) Degeneration (IDD) is a significant health concern, potentially influenced by mechanotransduction. However, the relationship between the IVD phenotypes and mechanical behavior has not been thoroughly explored in local morphologies where IDD originates. This work unveils the interplays among morphological and mechanical features potentially relevant to IDD through Abaqus UMAT simulations.

Methods: A groundbreaking automated method is introduced to transform a calibrated, structured IVD finite element (FE) model into 169 patient-personalized (PP) models through a mesh morphing process. Our approach accurately replicates the real shapes of the patient's Annulus Fibrosus (AF) and Nucleus Pulposus (NP) while maintaining the same topology for all models. Using segmented magnetic resonance images from the former project MySpine, 169 models with structured hexahedral meshes were created employing the Bayesian Coherent Point Drift++ technique, generating a unique cohort of PP FE models under the Disc4All initiative. Machine learning methods, including Linear Regression, Support Vector Regression, and eXtreme Gradient Boosting Regression, were used to explore correlations between IVD morphology and mechanics.

Results: We achieved PP models with AF and NP similarity scores of 92.06\% and 92.10\% compared to the segmented images. The models maintained good quality and integrity of the mesh. The cartilage endplate (CEP) shape was represented at the IVD-vertebra interfaces, ensuring personalized meshes. Validation of the constitutive model against literature data showed a minor relative error of 5.20%.

Discussion: Analysis revealed the influential impact of local morphologies on indirect mechanotransduction responses, highlighting the roles of heights, sagittal areas, and volumes. While the maximum principal stress was influenced by morphologies such as heights, the disc's ellipticity influenced the minimum principal stress. Results suggest the CEPs are not influenced by their local morphologies but by those of the AF and NP. The generated free-access repository of individual disc characteristics is anticipated to be a valuable resource for the scientific community with a broad application spectrum.
Impact of ionizing radiation on cell-ECM mechanical crosstalk in breast cancer
Authors: Mottareale Rocco , Frascogna Crescenzo , La Verde Giuseppe , Arrichiello Cecilia , Muto Paolo , Netti Paolo A. , Fusco Sabato , Panzetta Valeria , Pugliese Mariagabriella
Published: June 2024

The stiffness of the extracellular matrix plays a crucial role in cell motility and spreading, influencing cell morphology through cytoskeleton organization and transmembrane proteins’ expression. In this context, mechanical characterization of both cells and the extracellular matrix gains prominence for enhanced diagnostics and clinical decision-making. Here, we investigate the combined effect of mechanotransduction and ionizing radiations on altering cells’ mechanical properties, analysing mammary cell lines (MCF10A and MDA-MB-231) after X-ray radiotherapy (2 and 10 Gy). We found that ionizing radiations sensitively affect adenocarcinoma cells cultured on substrates mimicking cancerous tissue stiffness (15 kPa), inducing an increased structuration of paxillin-rich focal adhesions and cytoskeleton: this process translates in the augmentation of tension at the actin filaments level, causing cellular stiffness and consequently affecting cytoplasmatic/nuclear morphologies. Deeper exploration of the intricate interplay between mechanical factors and radiation should provide novel strategies to orient clinical outcomes.
Development and application of a novel suspension concentrate for seed coating of rice for controlling bakanae disease and seedling rot disease
Authors: Ren Xue-Xiang , Chen Li , Yu-Chi  , Zhao-Li  , Su Xian-Yan , Shun-He  , Ye Zheng-He
Published: June 2024

The main rice planting areas in the middle and lower reaches of the Yangtze River are primarily affected by two types of rice seedling diseases: bakanae disease and seedling rot disease. These diseases lead to considerable losses. Seed coating technology effectively protects rice from these diseases and mitigates environmental pollution. We determined the antifungal activity of six fungicides, including phenamacril, azoxystrobin, fludioxonil, metconazole, thifluzamide and prothioconazole against Fusarium moniliforme Sheldon and Curvularia lunata in this study. In addition, the impact of fungicides and surfactants on rice seed germination were determined. Furthermore, phenamacril and fludioxonil were selected as the active components of suspension concentrate for seed coating. The antifungal activity of phenamacril against F. moniliforme Sheldon was 0.139 mg/L and fludioxonil against C. lunata was 0.110 mg/L. PEG-2000 was selected as the surfactant due to its promoting effect on rice seedling. Based on the above findings, 6% phenamacril fludioxonil FS was developed via the wet sand grinding method. The toxicity of 6% phenamacril fludioxonil FS to zebrafish was verified, and field experiments were conducted in five different regions of the Yangtze River Basin. The results indicated minimal toxicity of 6% phenamacril fludioxonil FS to zebrafish. Relative to the control agent consisting of 6.25% phenamacril metalaxyl-M FS, 6% phenamacril fludioxonil FS showed better control effect and exhibited superior efficacy in promoting growth and increasing yield in all five regions. Specifically, the control effect of 6% phenamacril fludioxonil FS on bakanae exceeded 84.83% with the highest yield increasing value recorded at 30.48%. Currently, the market offers a limited selection of suspension concentrate for seed coating of rice. The findings of this study may offer a viable alternative formulation and directions for further research concerning the application of suspension concentrate for seed coating of rice.
DNA methylation modification in Idiopathic pulmonary fibrosis
Authors: Ren Lu , Chang Yan-Fen , Jiang Shi-He , Li Xiao-Hong , Cheng Hai-Peng
Published: June 2024

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and irreversible interstitial lung disease with a prognosis worse than lung cancer. It is a fatal lung disease with largely unknown etiology and pathogenesis, and no effective therapeutic drugs render its treatment largely unsuccessful. With continuous in-depth research efforts, the epigenetic mechanisms in IPF pathogenesis have been further discovered and concerned. As a widely studied mechanism of epigenetic modification, DNA methylation is primarily facilitated by DNA methyltransferases (DNMTs), resulting in the addition of a methyl group to the fifth carbon position of the cytosine base, leading to the formation of 5-methylcytosine (5-mC). Dysregulation of DNA methylation is intricately associated with the advancement of respiratory disorders. Recently, the role of DNA methylation in IPF pathogenesis has also received considerable attention. DNA methylation patterns include methylation modification and demethylation modification and regulate a range of essential biological functions through gene expression regulation. The Ten-Eleven-Translocation (TET) family of DNA dioxygenases is crucial in facilitating active DNA demethylation through the enzymatic conversion of the modified genomic base 5-mC to 5-hydroxymethylcytosine (5-hmC). TET2, a member of TET proteins, is involved in lung inflammation, and its protein expression is downregulated in the lungs and alveolar epithelial type II cells of IPF patients. This review summarizes the current knowledge of pathologic features and DNA methylation mechanisms of pulmonary fibrosis, focusing on the critical roles of abnormal DNA methylation patterns, DNMTs, and TET proteins in impacting IPF pathogenesis. Researching DNA methylation will enchance comprehension of the fundamental mechanisms involved in IPF pathology and provide novel diagnostic biomarkers and therapeutic targets for pulmonary fibrosis based on the studies involving epigenetic mechanisms.
Migrasome, a migration-dependent organelle
Authors: Zhang Fuyong , Liu Wendong , Mao Yunpeng , Yang Yuhao , Ling Chenxi , Liu Ya , Yao Feng , Zhen Yunfang , Wang Xiaodong , Zou Mincheng
Published: June 2024

Migrasomes are organelles produced by migrating cells that form on retraction fibers and are released during cell migration. Migrasomes are involved in physiological and pathological processes such as intercellular communication, cell homeostasis maintenance, signal transduction, disease occurrence and development, and cancer metastasis. In addition, methods and techniques for studying migrasomes are constantly evolving. Here, we review the discovery, formation process, regulation, and known functions of migrasomes, summarize the commonly used specific markers of migrasomes, and the methods for observing migrasomes. Meanwhile, this review also discusses the potential applications of migrasomes in physiological processes, disease diagnosis, treatment, and prognosis, and looks forward to their wider application in biomedicine. In addition, the study of migrasomes will also reveal a new perspective on the mechanism of intercellular communication and promote the further development of life science.
Study on the design, synthesis, and activity of anti-tumor staple peptides targeting MDM2/MDMX
Authors: Yang Jian , Liao Xiufei , Hu Damin , Mo Jinqiu , Gao Xiurong , Liao Hongli
Published: June 2024

Staple peptides, which have a significantly enhanced pharmacological profile, are promising therapeutic molecules due to their remarkable resistance to proteolysis and cell-penetrating properties. In this study, we designed and synthesized a series of PMI-M3-based dual-targeting MDM2/MDMX staple peptides and compared them with straight-chain peptides. The staple peptide SM3-4 screened in the study induced apoptosis of tumor cells in vitro at low μM concentrations, and the helix was significantly increased. Studies have shown that the enhancement of staple activity is related to the increase in helicity, and SM3-4 provides an effective research basis for dual-targeted anti-tumor staple peptides.
Temperatures above 37°C increase virulence of a convergent Klebsiella pneumoniae sequence type 307 strain
Authors: Müller Justus U. , Schwabe Michael , Swiatek Lena-Sophie , Heiden Stefan E. , Schlüter Rabea , Sittner Max , Bohnert Jürgen A. , Becker Karsten , Idelevich Evgeny A. , Guenther Sebastian , Eger Elias , Schaufler Katharina
Published: June 2024

Background

Convergence of Klebsiella pneumoniae (KP) pathotypes has been increasingly reported in recent years. These pathogens combine features of both multidrug-resistant and hypervirulent KP. However, clinically used indicators for hypervirulent KP identification, such as hypermucoviscosity, appear to be differentially expressed in convergent KP, potential outbreak clones are difficult to identify. We aimed to fill such knowledge gaps by investigating the temperature dependence of hypermucoviscosity and virulence in a convergent KP strain isolated during a clonal outbreak and belonging to the high-risk sequence type (ST)307.

Methods

Hypermucoviscosity, biofilm formation, and mortality rates in Galleria mellonella larvae were examined at different temperatures (room temperature, 28°C, 37°C, 40°C and 42°C) and with various phenotypic experiments including electron microscopy. The underlying mechanisms of the phenotypic changes were explored via qPCR analysis to evaluate plasmid copy numbers, and transcriptomics.

Results

Our results show a temperature-dependent switch above 37°C towards a hypermucoviscous phenotype, consistent with increased biofilm formation and in vivo mortality, possibly reflecting a bacterial response to fever-like conditions. Furthermore, we observed an increase in plasmid copy number for a hybrid plasmid harboring carbapenemase and rmpA genes. However, transcriptomic analysis revealed no changes in rmpA expression at higher temperatures, suggesting alternative regulatory pathways.

Conclusion

This study not only elucidates the impact of elevated temperatures on hypermucoviscosity and virulence in convergent KP but also sheds light on previously unrecognized aspects of its adaptive behavior, underscoring its resilience to changing environments.
The linkage between global financial crises, corporate social responsibility and climate change: unearthing research opportunities through bibliometric reviews
Authors: Chebo Abdella K. , Dhliwayo Shepherd , Batu Muhdin M.
Published: June 2024

Financial matters, corporate social responsibility (CSR), climate change, and other sustainable solutions all work in tandem. In order to provide a thorough understanding of the integration between various components during crises, it is necessary to provide knowledge of the interaction between financial, societal, and environmental aspects. In order to accomplish this, hundreds of papers were examined and presented using bibliometric analysis. The study demonstrated that, when examining financial crises in relation to CSR and climate change, sustainability issues were clearly examined. Sustainability, environmental economics, governance approaches, and sustainable development are some of the main issues in this comprehensive subject. Besides, the emerging topics that need more research include organizational resilience, global financial crises, and sustainable performance, while there are no specific themes developed in the subject matter that integrate financial crises, CSR, and climate change. Thus, future researchers need to provide new insights on the integration of these concepts.
Acoustic estimation of the manatee population and classification of call categories using artificial intelligence
Authors: Schneider Sebastian , von Fersen Lorenzo , Dierkes Paul Wilhelm
Published: June 2024

The population sizes of manatees in many regions remain largely unknown, primarily due to the challenging nature of conducting visual counts in turbid and inaccessible aquatic environments. Passive acoustic monitoring has shown promise for monitoring manatees in the wild. In this study, we present an innovative approach that leverages a convolutional neural network (CNN) for the detection, isolation and classification of manatee vocalizations from long-term audio recordings. To improve the effectiveness of manatee call detection and classification, the CNN works in two phases. First, a long-term audio recording is divided into smaller windows of 0.5 seconds and a binary decision is made as to whether or not it contains a manatee call. Subsequently, these vocalizations are classified into distinct vocal classes (4 categories), allowing for the separation and analysis of signature calls (squeaks). Signature calls are further subjected to clustering techniques to distinguish the recorded individuals and estimate the population size. The CNN was trained and validated using audio recordings from three different zoological facilities with varying numbers of manatees. Three different clustering methods (community detection with two different classifiers and HDBSCAN) were tested for their suitability. The results demonstrate the ability of the CNN to accurately detect manatee vocalizations and effectively classify the different call categories. In addition, our study demonstrates the feasibility of reliable population size estimation using HDBSCAN as clustering method. The integration of CNN and clustering methods offers a promising way to assess manatee populations in visually challenging and inaccessible regions using autonomous acoustic recording devices. In addition, the ability to differentiate between call categories will allow for ongoing monitoring of important information such as stress, arousal, and calf presence, which will aid in the conservation and management of manatees in critical habitats.
A machine learning-derived risk score to predict left ventricular diastolic dysfunction from clinical cardiovascular magnetic resonance imaging
Authors: Zhou Qingtao , Wang Lin , Craft Jason , Weber Jonathan , Passick Michael , Ngai Nora , Khalique Omar K. , Goldfarb James W. , Barasch Eddy , Cao J. Jane
Published: June 2024

Introduction

The evaluation of left ventricular diastolic dysfunction (LVDD) by clinical cardiac magnetic resonance (CMR) remains a challenge. We aimed to train and evaluate a machine-learning (ML) algorithm for the assessment of LVDD by clinical CMR variables and to investigate its prognostic value for predicting hospitalized heart failure and all-cause mortality.

Methods

LVDD was characterized by echocardiography following the ASE guidelines. Eight demographic and nineteen common clinical CMR variables including delayed enhancement were used to train Random Forest models with a Bayesian optimizer. The model was evaluated using bootstrap and five-fold cross-validation. Area under the ROC curve (AUC) was utilized to evaluate the model performance. An ML risk score was used to stratify the risk of heart failure hospitalization and all-cause mortality.

Results

A total of 606 consecutive patients underwent CMR and echocardiography within 7 days for cardiovascular disease evaluation. LVDD was present in 303 subjects by echocardiography. The performance of the ML algorithm was good using the CMR variables alone with an AUC of 0.868 (95% CI: 0.811–0.917), which was improved by combining with demographic data yielding an AUC 0.895 (95% CI: 0.845–0.939). The algorithm performed well in an independent validation cohort with AUC 0.810 (0.731–0.874). Subjects with higher ML scores (>0.4121) were associated with increased adjusted hazard ratio for a composite outcome than subjects with lower ML scores (1.72, 95% confidence interval 1.09–2.71).

Discussion

An ML algorithm using variables derived from clinical CMR is effective in identifying patients with LVDD and providing prognostication for adverse clinical outcomes.
Case Report: Coil embolization of ascending aortic pseudoaneurysm in patient with Behcet's disease
Authors: Kang Mengyang , Zhang Bo , Pang Honggang , Hu Huishe , Zhang Junbo
Published: June 2024

Background

Behcet's disease (BD) is a systematic vasculitis that affects vessels with various sizes, presenting as venous thrombosis and arterial pseudoaneurysms. The most severe manifestation in BD is ascending aortic pseudoaneurysm, which is associated with high risks of rupture and mortality.

Case presentation

We present a case of ascending aortic pseudoaneurysm in a 50-year-old patient with BD. After preoperative evaluation, coil embolization was successfully performed to treat the pseudoaneurysm, resulting in a satisfactory outcome at the 1-year follow-up.

Conclusion

Coil embolization serves as an effective treatment option for ascending aortic pseudoaneurysm in BD when open surgical repair and stent graft placement are unsuitable.
Association between changes in renal function and clinical outcomes in anticoagulated atrial fibrillation patients with marginal renal function. A nationwide observational cohort study
Authors: Lee Kyung-Yeon , Lee So-Ryoung , Choi Eue-Keun , Choi JungMin , Ahn Hyo-Jeong , Kwon Soonil , Kim Bongseong , Han Kyung-Do , Oh Seil , Lip Gregory Y. H.
Published: June 2024

Background

Renal function is one of the crucial components for determining the dose and type of oral anticoagulants in atrial fibrillation (AF) patients, and is also closely associated with the risks of stroke and bleeding. This study aimed to assess renal function changes and their impact on clinical outcomes in anticoagulated AF patients with marginal renal function.

Methods

From a Korean claims database, patients with AF on anticoagulants and a baseline eGFR of 45 to <60 ml/min/1.73 m2 were studied. Patients were grouped by changes in renal function over two years—maintained, improved (eGFR >60 ml/min/1.73 m2), or worsened (eGFR <45 ml/min/1.73 m2)—the study analyzed outcomes including ischemic stroke, major bleeding, end-stage renal disease (ESRD), all-cause death, and a composite of clinical outcomes.

Results

A total of 5,126 patients were included in the study: 2,170 (42.3%) in the maintained group, 2,276 (44.4%) in the improved group, and 680 (13.1%) in the group with worsened renal function. The worsened group was older and had more prevalent comorbidities than other groups. After multivariable adjustment, the worsened group was associated with significantly higher risks of major bleeding (adjusted hazard ratio, 95% confidence interval; 1.46, 1.03–2.07, p = 0.035), ESRD (1.49, 1.24–1.80, p < 0.001), all-cause death (9.29, 4.92–17.6, p < 0.001), and the composite outcome (1.57, 1.36–1.83, p < 0.001).

Conclusions

In anticoagulated AF patients with marginal renal function, a substantial proportion of patients experienced renal function decline below eGFR 45 ml/min/1.73 m2 within 2 years. Renal function decline was associated with higher risks of major bleeding, ESRD, all-cause death, and the composite outcome compared to those who maintained their baseline renal function.
A parameter inversion method for the probability integral method based on robust ridge estimation
Authors: Lou Jie
Published: June 2024

The probability integral method is one of the most widely used methods for predicting surface subsidence induced by underground mining in China. In its parameter calculation, the least square algorithm is commonly employed for fitting parameters. However, in the process of fitting parameters, the results are easily affected by ill-conditioned normal matrices and the interference of outliers, resulting in divergent problems. To solve these problems, the principle of robust ridge estimation was introduced in this paper, and a parameter calculation model for the probability integral method based on this principle (hereafter referred to as the established model) was established. Besides, a parameter calculation experiment with manual intervention was conducted in combination with engineering examples. The results demonstrate that the parameter calculation method based on robust ridge estimation can suppress the interference of outliers, overcome the problem of ill-conditioned matrix, and ensure the effectiveness and reliability of parameter estimation results. Compared with the conventional least squares method, the robust ridge estimation method demonstrates greater accuracy in predicting surface subsidence parameters, which validates its rationality and accuracy in underground mining engineering. The research findings provide technical support for obtaining similar parameters for surface subsidence in mining areas and hold significant engineering application value.
The injection capacity evaluation of high-pressure water injection in low permeability reservoir: numerical and case study
Authors: Zhu Weiyao , Gao Yubao , Wang Youqi , Liu Ping , Liu Yunfeng
Published: June 2024

Low permeability oil reservoir resources are rich and their efficient development is considered an important way to solve energy security issues. However, the development process of low permeability oil reservoirs is faced with the challenges of insufficient natural energy and rapid production decline. The high-pressure water injection technology is a method that relies on high-pressure and large-volume to inject fluid into the reservoir to replenish energy. It is considered as an important technical means to quickly replenish formation energy. This study focuses on the injection capacity for the high-pressure water injection technology of low permeability oil reservoir. Firstly, the fluid-structure interaction mathematical model for two-phase fluid flow was established. The solution of the mathematical model was then obtained by coupling the phase transport in porous media module and Darcy’s law module on the COMSOL numerical simulation platform. The numerical model established in this study was verified through the Buckley-Leverett model. The study on the injection capacity of high-pressure water injection technology was conducted using the geological background and reservoir physical properties of Binnan Oilfield (Shengli, China). The results show that the production pressure difference is the key factor in determining the injection capacity. When the production pressure difference increases from 5 MPa to 30 MPa, the cumulative injection volume increases by 8.1 times. In addition, sensitivity analysis shows that the injection capacity is significantly influenced by the properties of the reformation area. The effect of these parameters from high to low is as follows: stress sensitivity factor, permeability, rock compressibility, and porosity. Compared to the reformation area, the influence of the physical parameters of the matrix area on the injection capacity is negligible. Therefore, effective reservoir reformation is essential for enhancing the injection capacity. This research provides a theoretical basis for the design and optimization of the high-pressure water injection technology schemes for low permeability oil reservoir.
Effects of the proportion of students with special educational needs on middle school teachers’ well-being
Authors: Chen Yuan
Published: June 2024

This study explores the impact of the proportion of students with special educational needs (SEN) on Chinese middle school teachers’ job stress, satisfaction, and exhaustion, amid increasing emphasis on inclusive education. The research hypothesizes that a higher proportion of SEN students may lead to increased job stress, decreased job satisfaction, and heightened job exhaustion. This study utilized data from the China Education Panel Survey, and Structural equation modeling was used for data analysis. The study found a significant negative association between the proportion of SEN students and teacher job satisfaction (β = −0.09, p < 0.05). No direct relationship was found between the proportion of SEN students and job stress (β = 0.00, p > 0.05) and job exhaustion (β = −0.08, p > 0.05). However, there was an indirect positive impact of the proportion of SEN students on job exhaustion via job satisfaction (β = 0.05, p < 0.05). This research provides valuable insights into potential strategies for enhancing job satisfaction and reducing job exhaustion among teachers with a high proportion of SEN students.
Why don’t students draw when learning from science texts?
Authors: Eidman Leaha , Fiorella Logan
Published: June 2024

This study explored why students rarely create drawings when learning from science texts despite potential learning benefits. Undergraduates (n = 114) studied a 10-part text on the human respiratory system and took notes by choosing their own strategies (free choice group) or by choosing to create a drawing or write a verbal summary (forced choice group). Other students were instructed to create drawings (draw group) or write summaries (summarize group). All students then completed a series of post-tests. The forced choice group chose to draw significantly more frequently than the free choice group; however, both groups still overwhelmingly chose summarizing. Participants across all groups reported lower prior experience, lower expectancies for success, lower perceived value, and higher perceived cost of drawing compared to summarizing. Students’ prior experiences and beliefs about drawing were also associated with how frequently they chose to draw, providing implications for future instructional interventions.
Teacher responses to racially motivated bullying in Scotland
Authors: Hay Nicola , Davies Elisabeth , Sapouna Maria
Published: June 2024

Racially motivated bullying remains pervasive across Scottish schools. Teachers have a critical role in nurturing a safe and inclusive environment and preventing stigmatisation and oppression by intervening when a racially motivated bullying episode occurs but also by actively developing an anti-racist climate within their school by providing an anti-racism curriculum and advocating on behalf of minority ethnic youth. Despite the crucial role teachers can play in providing a safe environment, there is a paucity of literature examining the issue. Whilst some limited research is available in England about the barriers to embedding an anti-racist curriculum, there is no research about how teachers respond to racially motivated bullying episodes, the potential barriers to responding, and the processes and factors that influence teachers’ judgement calls when a racially motivated bullying incident happens. Similarly, in the Scottish context, there is a lacuna of knowledge about the strategies employed by teachers already within the education system and their perceptions on the support that they need to respond to racist incidents. This study aims to add to our knowledge about this issue by investigating Scottish teachers’ strategies when they are confronted with a hypothetical racially motivated bullying incident in their school. Eleven interviews were conducted with a sample of teachers from different levels of education in Scotland. Teacher responses indicated reluctance and, at times, inability to recognise and name incidents as racist. Further data highlighted the reliance on strategies such as using the victim of an incident to educate their peers, one-to-one discussions with both pupils and perpetrators, and a dependence on using their own ‘instinct’ to appraise an incident and response. Further sub themes emerged, including the perceived influence of generational and geospatial factors on both practitioners and the communities in which they practise and the resounding sentiment that practitioners lack engagement with anti-racist training. Our findings highlight the need to invest in schools, communities, and young people in order to create the social conditions in which teachers’ capacities to respond to racism can develop and flourish.
The role of mentoring in developing leaders’ emotional intelligence: exploring mentoring types, emotional intelligence, organizational factors, and gender
Authors: Prummer Katharina , Human-Vogel Salomé , Graham Marien Alet , Pittich Daniel
Published: June 2024

Emotional awareness, emotional regulation, empathy, and resilience are key components of emotional intelligence. Twenty-first-century leaders require such competencies, and prior research establishes a positive impact of emotional intelligence on leadership and well-being. The mechanisms through which leaders develop these competencies remain unclear. Mentoring, a developmental tool linked with well-being, has not been extensively studied for its role in emotional intelligence development. The current study investigates this relationship within the context of vocational education and training in South Africa. The mentoring framework includes individual, peer group, and key performance area mentoring. In previous research on this mentoring framework, leaders perceived emotional well-being as the most important outcome of mentoring and development, constituting another vital factor. Data were collected from a treatment group of leaders who have participated in the mentoring framework and a control group of leaders and lecturers (N = 139). The present study used exploratory and confirmatory factor analysis to validate the Schutte Self-Report Emotional Intelligence Test within this context. In the next step, we employed descriptive analysis to answer which mentoring type was best perceived to support emotional intelligence. Using the Mann–Whitney U test, we tested for significant differences in the identified factors between treatment and control group. Mediated and moderated mediation analyses explored variables such as gender, occupational role, organization, and work sector. Results indicate a six-factor structure of emotional intelligence, with significant differences observed between groups in the factor empathy difficulty. Peer group mentoring emerged as an effective method for emotional intelligence development among leaders. The perceived importance of emotional intelligence for one’s job position, the organization, and the work sector mediated five of the six factors. The moderated mediation analyses showed an indirect effect of gender, where being male was associated with more trustworthy visionary and empathy. The findings underscore the significance of peer mentoring practices and organizational factors in nurturing emotional intelligence, highlighting its value for personal and organizational well-being. Overall, the study sheds light on developing emotional intelligence at all organizational levels to support individual and collective well-being.
Evaluation of co-designed online teacher training program for providing neuroscience- informed mental health intervention to Japanese children
Authors: Takizawa Yu , Bambling Matthew , Teoh Hsien-Jin , Edirippulige Sisira
Published: June 2024

Introduction

While mental health problems are prevalent among children, Japanese schools face challenges in providing effective mental health support to children partly due to a lack of training in mental health intervention. This study aimed to address this problem by evaluating a co-designed online teacher training program to provide a neuroscience-informed mental health intervention (NIMHI) to Japanese children.

Method

The present study evaluated the effectiveness of an online teacher training program by conducting a single-arm trial involving a group of 20 teachers and 245 children aged 8–12 from a regional Japanese primary school. The researcher delivered online training to Japanese teachers, who subsequently administered NIMHI to Japanese children over a 4-week period. The evaluation involved the administration of pre- and post-intervention student questionnaires, pre- and post-training teacher questionnaires, and post-intervention teacher interviews.

Results

After the delivery of the training program, 80% of Japanese teachers expressed strong or moderate satisfaction with the training. There were significant improvements in teachers' knowledge, perceived skills, self-efficacy, and acceptability of using NIMHI. Teachers implemented intervention strategies at least twice a week over four weeks. Following the intervention, 70% of teachers reported qualitative changes in students' mental health, such as more stable emotions. However, there were no significant changes in students' emotional problems, school enjoyment, and psychological wellbeing.

Discussion

The findings offer a fresh perspective on the effectiveness of utilizing digital technology, as a modality for delivering training to Japanese teachers. However, the absence of quantitative changes in students' mental health could suggest that the effectiveness of the online teacher-training program may not have been sufficiently robust. Further improvements in the online teacher-training program would be useful, such as providing tablet applications to assist teachers in implementing suitable intervention strategies and teaching a more focused range of strategies.
#InstaMind: teachers’ beliefs on educational technology to promote seamless technology integration in early education
Authors: Peretti Sara , Kubiatko Milan , Caruso Federica , Di Mascio Tania , Giancola Marco , D’Amico Simonetta , Pino Maria Chiara
Published: June 2024

Background

The digital revolution has deeply affected every aspect of our daily lives, including education, transforming how we learn and teach. In Italy, this transformation has occurred naturally for the alpha generation, born in the era in which technology is an integral part of their education. Conversely, for teachers who are not digital natives, adapting to this technological era is a considerable challenge. This challenge is increasing for Italian teachers working with preschoolers. Indeed, prior to the COVID-19 pandemic, such technologies were sparsely utilized within early education. This study aims to explore Italian teachers’ beliefs through internal factors—i.e., self- efficacy, outcome expectations, and interest, toward the integration of educational technology in teaching.

Methods

To this end, the standardized Intrapersonal Technology Integration Scale was selected to measure the Italian teachers’ beliefs. The study includes 180 teachers working with the alpha generation, which encompasses children currently attending pre-kindergarten, kindergarten, and primary education.

Results

The results obtained from the comparison among the three groups of teachers (pre- kindergarten, kindergarten, and primary education) on the internal factors are manifold. Mainly, although all teachers are interested in educational technologies, there is a reluctance and low self-efficacy perception to use them with preschoolers. Specifically, pre-kindergarten teachers perceive themselves as less effective and satisfied using such technologies than kindergarten and primary teachers. Moreover, greater teachers’ age and greater teaching experience predict a lower level of perceived self-efficacy and outcome expectations, highlighting resistance toward technological change. All results and their implications are detailed in this text.

Discussion

This study suggests focusing on perceived self-efficacy, offering customized training to enhance it, exploiting the teachers’ interest, enriching teachers’ knowledge through scientific dissemination seminars, and using an effective method. To conclude, understanding teachers’ beliefs is a challenge to better meet the needs of the digital-native generation and harness the potential of educational technologies in childhood education.
Case report: A novel somatic SDHB variant in a patient with bladder paraganglioma
Authors: Nguyen Thao , Ordulu Zehra , Shrestha Sunaina , Patel Urja , Crispen Paul L. , Brown Lisa , Falzarano Sara M. , Ghayee Hans K. , Perdomo Rodriguez Juan Pablo
Published: June 2024

Background

Paragangliomas (PGL) are rare neuroendocrine tumors derived from the autonomic nervous system paraganglia. Urinary bladder paragangliomas (UBPGL) originate from the sympathetic neurons of the urinary bladder wall and represent 0.7% of all paragangliomas and <0.05% of all bladder tumors. PGL and UBPGL can be associated with SDHB, SDHD, NF1, and VHL gene variants, with the most common germline alterations found in SDHB and VHL.

Case report

We report a case of a 42-year-old woman who presented with menorrhagia/hematuria, uterine leiomyomas, as well as cardiac and bladder masses. The cardiac mass was favored to be a myxoma based on clinical findings, while the bladder mass was diagnosed as UBPGL. A novel SDHB mutation (c.642G>A, p Q214Q), detected in the UBPGL, was proven to be somatic. Although this variant was seemingly synonymous, it was predicted to have a loss of function due to the splice site effect, which was further supported by the immunohistochemical loss of SDHB.

Conclusion

This case highlights the challenges of diagnosing an extremely rare entity, bladder paraganglioma, with an emphasis on the multidisciplinary approach to navigate various clinical and imaging findings that may initially be misleading. In addition, a novel loss of function SDHB variant that could have been overlooked as a synonymous variant is herein reported, while also illustrating the importance of both germline and somatic mutation testing.
Association of the hemoglobin glycation index with cardiovascular and all-cause mortality in individuals with hypertension: findings from NHANES 1999–2018
Authors: Shangguan Qing , Yang Jingqi , Li Bin , Chen Huaigang , Yang Liu
Published: June 2024

Background

This study examines the association between Hemoglobin Glycation Index (HGI) and the risk of mortality among individuals with hypertension and to explore gender-specific effects.

Methods

Data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 were analyzed. Three models were constructed to assess the relationship between HGI and mortality risks, controlling for various covariates. Nonlinear relationships were explored using restricted cubic splines (RCS) and threshold effect analysis.

Results

The findings reveal a U-shaped relationship between HGI and the cardiovascular disease (CVD) and all-cause mortality after adjusting for multiple covariates. Gender- specific analysis indicated a U-shaped relationship in men, with threshold points of -0.271, and 0.115, respectively. Before the threshold point, HGI was negatively associated with CVD mortality (HR: 0.64, 95%CI: 0.44, 0.93, P=0.02) and all-cause mortality (HR: 0.84, 95%CI: 0.71, 0.99), and after the threshold point, HGI was positively associated with CVD mortality (HR: 1.48, 95%CI: 1.23, 1.79, P<0.01) and all-cause mortality (HR: 1.41, 95%CI: 1.24, 1.60). In contrast, HGI had a J-shaped relationship with CVD mortality and a L-shaped relationship with all-cause mortality in females. Before the threshold points, the risk of all-cause mortality decreased (HR: 0.66, 95%CI:0.56, 0.77, P=0.04) and after the threshold points, the risk of CVD mortality increased (HR: 1.39, 95%CI:1.12, 1.72, P<0.01) progressively with increasing HGI.

Conclusion

The research highlights the significance of maintaining proper HGI levels in individuals with hypertension and validates HGI as a notable indicator of cardiovascular and all-cause mortality risks. It also highlights the significant role of gender in the relationship between HGI and these risks.
Ultra-short-term prediction of microgrid source load power considering weather characteristics and multivariate correlation
Authors: Huang Zhenning , Sun Ning , Shao Huaqiang , Li Yunjing
Published: June 2024

Multiple microgrids interconnect to form a microgrid cluster. To fully exploit the comprehensive benefits of the microgrid cluster, it is imperative to optimize dispatch based on the matching degree between the sources and loads of each microgrid. The power of distributed energy sources such as wind and photovoltaic systems and the sensitive loads in microgrids is related to the regional weather characteristics. Given the relatively small geographical scope of microgrid areas and the fact that distributed energy sources and loads within the grid share the same weather characteristics, simultaneous ultra-short-term forecasting of power for both sources and loads is essential in the same environmental context. Firstly, the introduction of the multi-variable uniform information coefficient (MV-UIC) is proposed for extracting the correlation between weather characteristics and the sequences of source and load power. Subsequently, the application of factor analysis (FA) is introduced to reduce the dimensionality of input feature variables. Drawing inspiration from the concept of combination forecasting models, a combined forecasting model based on Error Back Propagation Training (BP), Long Short-Term Memory (LSTM), and Bidirectional Long Short-Term Memory Neural Network (BiLSTM) is constructed. This model is established on the MV-UIC-FA foundation for the joint ultra-short-term forecasting of source and load power in microgrids. Simulation is conducted using the DTU 7K 47-bus system as an example to analyze the accuracy, applicability, and effectiveness of the proposed joint forecasting method for sources and loads.
Single-cell analysis and machine learning identify psoriasis-associated CD8+ T cells serve as biomarker for psoriasis
Authors: He Sijia , Liu Lyuye , Long Xiaoyan , Ge Man , Cai Menghan , Zhang Junling
Published: June 2024

Psoriasis is a chronic inflammatory skin disease, the etiology of which has not been fully elucidated, in which CD8+ T cells play an important role in the pathogenesis of psoriasis. However, there is a lack of in-depth studies on the molecular characterization of different CD8+ T cell subtypes and their role in the pathogenesis of psoriasis. This study aims to further expound the pathogenesy of psoriasis at the single-cell level and to explore new ideas for clinical diagnosis and new therapeutic targets. Our study identified a unique subpopulation of CD8+ T cells highly infiltrated in psoriasis lesions. Subsequently, we analyzed the hub genes of the psoriasis-specific CD8+ T cell subpopulation using hdWGCNA and constructed a machine-learning prediction model, which demonstrated good efficacy. The model interpretation showed the influence of each independent variable in the model decision. Finally, we deployed the machine learning model to an online website to facilitate its clinical transformation.
Genome-wide comparative analysis reveals selection signatures for reproduction traits in prolific Suffolk sheep
Authors: Yang Hua , Zhu Mengting , Wang Mingyuan , Zhou Huaqian , Zheng Jingjing , Qiu Lixia , Fan Wenhua , Yang Jinghui , Yu Qian , Yang Yonglin , Zhang Wenzhe
Published: June 2024

The identification of genome-wide selection signatures can reveal the potential genetic mechanisms involved in the generation of new breeds through natural or artificial selection. In this study, we screened the genome-wide selection signatures of prolific Suffolk sheep, a new strain of multiparous mutton sheep, to identify candidate genes for reproduction traits and unravel the germplasm characteristics and population genetic evolution of this new strain of Suffolk sheep. Whole-genome resequencing was performed at an effective sequencing depth of 20× for genomic diversity and population structure analysis. Additionally, selection signatures were investigated in prolific Suffolk sheep, Suffolk sheep, and Hu sheep using fixation index (FST) and heterozygosity H) analysis. A total of 5,236.338 Gb of high-quality genomic data and 28,767,952 SNPs were obtained for prolific Suffolk sheep. Moreover, 99 selection signals spanning candidate genes were identified. Twenty-three genes were significantly associated with KEGG pathway and Gene Ontology terms related to reproduction, growth, immunity, and metabolism. Through selective signal analysis, genes such as ARHGEF4, CATIP, and CCDC115 were found to be significantly correlated with reproductive traits in prolific Suffolk sheep and were highly associated with the mTOR signaling pathway, the melanogenic pathway, and the Hippo signaling pathways, among others. These results contribute to the understanding of the evolution of artificial selection in prolific Suffolk sheep and provide candidate reproduction-related genes that may be beneficial for the establishment of new sheep breeds.
Mouse models of chronic lymphocytic leukemia and Richter transformation: what we have learnt and what we are missing
Authors: Bertilaccio Maria Teresa Sabrina , Chen Shih-Shih
Published: June 2024

Although the chronic lymphocytic leukemia (CLL) treatment landscape has changed dramatically, unmet clinical needs are emerging, as CLL in many patients does not respond, becomes resistant to treatment, relapses during treatment, or transforms into Richter. In the majority of cases, transformation evolves the original leukemia clone into a diffuse large B-cell lymphoma (DLBCL). Richter transformation (RT) represents a dreadful clinical challenge with limited therapeutic opportunities and scarce preclinical tools. CLL cells are well known to highly depend on survival signals provided by the tumor microenvironment (TME). These signals enhance the frequency of immunosuppressive cells with protumor function, including regulatory CD4+ T cells and tumor-associated macrophages. T cells, on the other hand, exhibit features of exhaustion and profound functional defects. Overall immune dysfunction and immunosuppression are common features of patients with CLL. The interaction between malignant cells and TME cells can occur during different phases of CLL development and transformation. A better understanding of in vivo CLL and RT biology and the availability of adequate mouse models that faithfully recapitulate the progression of CLL and RT within their microenvironments are “conditio sine qua non” to develop successful therapeutic strategies. In this review, we describe the xenograft and genetic-engineered mouse models of CLL and RT, how they helped to elucidate the pathophysiology of the disease progression and transformation, and how they have been and might be instrumental in developing innovative therapeutic approaches to finally eradicate these malignancies.