bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Cyfluthrin Exposure on Neurobehaviour, Hippocampal Tissue and Synaptic Plasticity in Wistar Rats
Authors: Xie Yong-xin , Zhao Ji , Li Xiao-Yu , Sun Jian , Yang Hui-Fang
Published: November 2023

This experiment was conducted to study the effects of Cyfluthrin (Cy) exposure on neurobehaviour, hippocampal tissue and synaptic plasticity in Wistar rats. First, high-dose Cy exposure can cause nerve injury with symptoms such as deficits in learning and memory ability, spatial exploration and autonomic motor ability. Moreover, it was found that medium- and high-dose Cy exposure can cause disordered energy metabolism in hippocampal cells and an abnormal release of the neurotransmitter Glu. Second, pathological brain sections showed that the middle and high doses of Cy caused deformation, reduction and disorder of hippocampal pyramidal cells, a decrease in the number of Nissl bodies, pyknosis of the hippocampal cell nuclear membrane and serious damage to organelles, indicating that exposure to these doses of Cy may cause hippocampal tissue damage in rats. Third, with the increase in exposure dose, the morphological changes in hippocampal synapses were more obvious, including blurred synaptic spaces, decreased synaptic vesicles and a decreased number of synapses. Moreover, the expression levels of the key synaptic proteins PSD-95 and SYP also decreased in a dose-dependent manner, indicating obvious synaptic damage. Finally, the study found that medium and high doses of Cy could upregulate the expression of A2AR in the hippocampus, and the expression levels of inflammatory factors and apoptosis-related proteins increased in a dose-dependent manner. Moreover, the expression of A2AR mRNA was correlated with neurobehavioural indicators, inflammatory factors, synaptic plasticity factors and apoptosis factors, suggesting that Cy may cause nerve damage in rats and has a close relationship with A2AR.
Research on Measuring Methods and Influencing Factors of Spatial Damage Degree of Historic Sites: A Case Study of Three Ancient Cities in Shanxi, China
Authors: Zhao Bing , Han Weicheng
Published: November 2023

Historic sites are important components of every city's cultural history because they preserve rich historical knowledge and distinctive values passed down from previous generations to the present. Due to the progress of urbanization and modernization, many historic sites face pressure from damage and transformation. In this paper, a method for assessing cultural heritage damage was developed to measure the extent of spatial damage in historic sites. Using sample data obtained in Xiyang, Qixian, and Xiaoyi, all historic cities in Shanxi Province, Mainland China, and combined weights were estimated using the Delphi technique and the CRITIC weight method. Following this, the Spatial Damage Degree Model (SDDM) based on K-means cluster analysis and K-nearest neighbor (KNN) classification was developed. The findings show that the model efficiently solves the problem of assessing spatial damage levels in historic sites. Through multiple linear regression analysis, it was shown that the damage to historic sites was predominantly caused by three factors: natural erosion, construction damage, and planning and policy. SDDM was used to calculate the spatial damage levels of historic sites, allowing conservators to fully comprehend the features and concerns related to historic sites. As a result, more scientific and rational preservation approaches may be developed, improving the efficiency of historic site restoration and conservation and encouraging the sustainable development of urban and rural heritage.
Two-Stages Input Space Image Augmentation and Interpretable Technique for Accurate and Explainable Skin Cancer Diagnosis
Authors: Supriyanto Catur , Salam Abu , Zeniarja Junta , Wijaya Adi
Published: November 2023

This research paper presents a deep learning approach to early detection of skin cancer using image augmentation techniques. The authors propose a two-stage image augmentation technique that involves the use of geometric augmentation and generative adversarial network (GAN) to classify skin lesions as either benign or malignant. This research utilized the public HAM10000 dataset to test the proposed model. Several pre-trained models of CNN were employed, namely Xception, Inceptionv3, Resnet152v2, EfficientnetB7, InceptionresnetV2, and VGG19. Our approach achieved accuracy, precision, recall, and F1-score of 96.90%, 97.07%, 96.87%, 96.97%, respectively, which is higher than the performance achieved by other state-of-the-art methods. The paper also discusses the use of SHapley Additive exPlanations (SHAP), an interpretable technique for skin cancer diagnosis, which can help clinicians understand the reasoning behind the diagnosis and improve trust in the system. Overall, the proposed method presents a promising approach to automated skin cancer detection that could improve patient outcomes and reduce healthcare costs.
What Is a Theory of Physics and How to Develop a New Theory of Physics?
Authors: zhu yin
Published: November 2023

Mathematics first is a logical system. But, the Mathematics Crisis showed that we cannot have a logical self-consistent mathematics system. Physics is a kind of applied science. It first need be valid to invent new production and understand new observation. In one theory of physics, the studied object is usually defined as an abstract concept. For example, the Sun is defined as a point particle in the Newtonian theory of gravity. In different theories of physics, the abstract concept for a same object is different. It determines that logical self-consistent is not needed for different theories of physics. Physics only can be developed from observation and experiment. But, in the past a century, physicists’ main attempt is to have a standard model, such as the Grand Unification or the Theory for Everything, from mathematics derivation. Therefore, the current attempt to develop new physics is questioned. In recent, the strong gravitational field was studied. It is found that the fundamental physical constants which are measured in the weak field shall be varied in a super strong field. For the two reasons, modern physics need be advanced greatly.
Effect of the Light Environment on Image-Based SPAD Value Prediction of Radish Leaves
Authors: Kamiwaki Yuto , Fukuda Shinji
Published: November 2023

This study aims to clarify the influence of photographic environments under different light sources on image-based SPAD value prediction. Radish leaf patches of 1.5 cm diameter were photographed under halogen or LED light. The input variables for the SPAD value prediction using random forests were RGB values, HSL values, and HSV values. Additionally, the light color temperature (LCT) and illuminance (ILL) were used as the input variables. Model performance was assessed using Pearson’s correlation coefficient (COR), Nash-Sutcliffe efficiency (NSE), and root mean squared error (RMSE). SPAD value prediction resulted in high accuracy in a stable light environment; CORRGB+ILL+LCT and CORHSL+ILL+LCT were 0.929 and 0.922, respectively. Image-based SPAD value prediction was effective under halogen light with a similar color temperature at dusk; CORRGB+ILL and CORHSL+ILL were 0.895 and 0.876, respectively. The HSL value under LED could be used to predict the SPAD value with high accuracy; COR, NSE, and RMSE were 0.972, 0.944, and 2.07, respectively. The partial dependence plots of the H value indicate a change from blue to green with increasing SPAD values. Further studies are required to examine this method under outdoor conditions in spatiotemporally dynamic light environments.
Advanced Surgical Approaches for the Rejuvenation of the Submental and Cervicofacial Regions: A Critical Review for a Personalized Approach
Authors: Borisenko Anastasiya S. , Sharobaro Valentin , Burkhonova Nigora , Avdeev Alexey
Published: November 2023

The quest for surgical advancements regarding the enhancement of the submental and cervicofacial regions has witnessed a remarkable upsurge in recent years. Informed patients are actively seeking sophisticated plastic surgery techniques to achieve comprehensive rejuvenation in these specific areas. Our clinical practice encounters an annual influx of approximately 400 patients, with 20% of them aged over 60, seeking facial rejuvenation encompassing the details of lower third of the face and neck. Common concerns expressed by these patients include sagging of the jawline, the emergence of deep perioral wrinkles, and the formation of "marionette lines" within the lower third of the face. Furthermore, the manifestation of age-related signs, including neck laxity, submental adipose accumulation, "witch's chin" deformity, and weakened platysma musculature, is frequently encountered within this intricate anatomical domain. This review aims to summarize the recent technical improvements, historical evolution, indications, postoperative care and challenges for facial rejuvenation of the lower third of the face and neck. Lastly, the application of minimally invasive procedures as part of a comprehensive approach to an aging face will also be discussed.
Nanotechnology-Enabled Scar Removal: Advances, Challenges, and Opportunities
Authors: Tören Elçin , Buzgo Matěj
Published: November 2023

Nanotechnology has become an increasingly promising medical field, particularly scar removal. Scar removal is a complex process involving regenerating damaged skin tissue, and nanotechnology presents unique solutions to this issue. One potential application of nanotechnology is using nanofibers as scaffolds to support the growth of new skin tissue. These fibres can also be loaded with drugs or growth factors to promote tissue regeneration and reduce scarring. Another potential application is nanocarriers for drug delivery to specific body areas, which can promote tissue regeneration and reduce scarring.Additionally, nanotechnology has been utilized to create new materials for skin regeneration, such as "nano skin" that mimics the structure of natural skin. Nanoprobes have also been developed for the detection of scar tissue and the monitoring of its progression. These potential nanotechnology applications offer exciting possibilities for the future of scar removal and skin repair. With further research and development, nanotechnology has the potential to revolutionize scar removal and provide more effective solutions for tissue regeneration.
A Cross-modal Retrieval Method for Image, Audio and Video Based on openKylin
Authors: Zhang Jin , Xie Xin , Liu Xiao dong , Yu Jie , Peng Long , Wang Wen zhu , Zhang Peng fei , Lan Yue , Zhang Chao
Published: November 2023

The need for cross-modal retrieval (CMR) among users is growing because of the swift advancements in computer vision and natural language processing. Promoting home operating systems is greatly aided by the openKylin home operating system. It is focused on enhancing the functionality of the operating system with safe and dependable operating technologies. Practical implications abound for integrating computer vision research into home operating systems. A multimodal retrieval approach based on openKylin is presented to improve the usability of text search graphs, audio, and video. The overview of pertinent domestic and international research is the main topic of this article. This technological advancement. It then offers details on the design, implementation procedure, and final implementation outcomes for demonstration. The works of natural operations show that this strategy has excellent accuracy and performance.
Switch-Transformer Sentiment Analysis Model for Arabic Dialects that Utilizes Mixture of Experts Mechanism
Authors: Baniata Laith H. , Kang Sangwoo
Published: November 2023

In recent times, models like the Transformer have showcased remarkable prowess in tasks related to natural language processing. However, these models tend to be excessively intricate and demand extensive training. Additionally, while the multi-head self-attention mechanism in the Transformer model aims to capture semantic connections between words in a sequence, it encounters limitations when handling short sequences, thereby limiting its effectiveness in 5-polarity Arabic sentiment analysis tasks. The switch-transformer model has recently emerged as a high-performing alternative. Nevertheless, when these models are trained using single-task learning, they often fall short of achieving exceptional performance and struggle to generate robust latent feature representations, especially when working with compact datasets. This challenge is particularly pronounced in the case of the Arabic dialect, which is considered a low-resource language. Given these constraints, this research introduces a novel approach to sentiment analysis in Arabic text. This method leverages multitask learning in tandem with the switch-transformer shared encoder to enhance model adaptability and refine sentence representation. By introducing a mixture of expert (MoE) mechanism that break down the problem into smaller, more manageable sub-problems, the model becomes adept at handling lengthy sequences and intricate input-output relationships, benefiting both five-point and three-polarity Arabic sentiment analysis tasks. This proposed model effectively discerns sentiment in Arabic dialect sentences. The empirical results highlight the outstanding performance of the suggested model, as evidenced in evaluations on the Hotel Arabic-Reviews Dataset, the Book Reviews Arabic Dataset, and the LARB dataset.
Investigating Special Funding Allocations for Teaching and Research on Public Goods Transformation in Neoliberal Higher Education
Authors: Chang Dian-Fu
Published: November 2023

Allocations of funding for higher education have typically focused on competition in neoliberal mechanisms. Surprisingly, much less attention has been paid to considering the effect of fund allocations for public goods purposes in neoliberal contexts. This study aims to examine specific funding schemes and determine the influential factors impacting the funding for teaching, research, and public goods intention. Taking Taiwan's Higher Education Sprout Project (HESP) as a unique example, we explored the effect of policy initiatives on public goods transformation. The data was collected from the Ministry of Education and Scopus database. First, the t-test and ANOVA were used to detect the differences between the system and sector; Second, regression analysis was used to determine influential factors for funding allocations; Final, structural equation modeling (SEM) was used to explore the causal effects among the selected variables. The study found that only diversity was shown in private technology groups receiving less HESP funding. The findings suggest that the funding allocation may not affect teaching and research based on sectors and systems. In contrast, this study demonstrates that transforming the public good through special funding can play a critical role in policy intention in neoliberal higher education.
Exploring CrossFit Performance Prediction and Analysis via Extensive Data and Machine Learning
Authors: Lim Byunggul , Song Wook
Published: November 2023

(1) Background: The analysis of athletic performance has always aroused great interest from sport scientist. This study utilized machine learning methods to build predictive models using a comprehensive CrossFit (CF) dataset, aiming to reveal valuable insights into the factors influencing performance and emerging trends.; (2) Methods: The study used Random Forest (RF) and Multiple Linear Regression (MLR) models to predict performance in four key weightlifting exercises within CF: clean & jerk, snatch, back squat, and deadlift. Performance was evaluated using R-squared (R2) values and Mean Squared Error (MSE). Feature importance analysis was conducted using RF, XGBoost, and AdaBoost models.; (3) Results: The RF model excelled in deadlift performance prediction (R2 = 0.80), while the MLR model demonstrated remarkable accuracy in clean & jerk (R2 = 0.93). Across exercises, clean & jerk consistently emerged as a crucial predictor. The feature importance analysis revealed intricate relationships among exercises, with gender significantly impacting deadlift performance.; (4) Conclusions: This research advances our understanding of performance prediction in CF through machine learning techniques. It provides actionable insights for practitioners, optimize performance, and demonstrates the potential for future advancements in data-driven sports analytics.
Dynamic Stability of Public Debt: Evidence from the Eurozone Countries
Authors: Laopodis Nikiforos T. , Spanos Konstantinos , Katsikas Epameinondas
Published: November 2023

This paper investigates the dynamic stability of public debt and its solvency condition on the face of crises periods (1980-2021) in a sample of 11-euro area countries. The focus is on the feedback loop between dynamic stability of public debt and interest rates, discounted by the economic growth, in conjunction with budget deficits during tranquil and turbulent periods. Using the GMM panel dynamic model, the results show that dynamic stability was the case before the global financial crisis (GFC), while from GFC to pandemic, dynamic instability prevailed on the evolution of public debt. Moreover, dynamic instability exerted a highly persistent effect on the evolution of debt. Furthermore, panel threshold estimates show that dynamic instability of debt starts to violate the solvency condition when the borrowing cost is above 3.29%, becomes even stronger when it is above 4.39% and exerts even more pressure when the level of debt is greater than 91%. However, the debt sustainability condition reverses course when economic growth is higher than 3.4%. The main policy implication drawn from the results is that low interest rates can create a self-reinforcing loop of high debt, which is an issue for further research.
From 3D Modeling to Landscape Mapping.
A Workflow for the Visualization and Communication
of the Asinara Island Park Plan
Authors: Cicalò Enrico , Valentino Michele , Sias Andrea
Published: November 2023

This paper aims to present the method of producing visual media for communicating the Asinara Island National Park plan. These products are landscape visualizations able to foster landscape preservation both from the point of view of the management of the landscape and of the citizen's involvement in the communication of the historical and environmental values of the landscape. Starting from landscape information gathering, the research has experimented with an operative method for processing different graphic representations from the same geographic database, calibrating the outputs to different audiences, their needs, objectives, and literacy skills. Three different types of products are presented: the first is a digital, dynamic and multisectoral decision-making GIS tool for park management. The second is a 3D model, aimed to the virtual fruition. The third is a map of the zoning park plan drawn to be easily readable to the non-expert public. This case study emerges as a replicable method to process the landscape information to make different visualization tools from a single geographic model, to meet the different requirements that arise from a complex landscape planning process.
Automatic System for the Study the Interaction Between Porous Media and Atmosphere, Clime Change and Environmental Conditions
Authors: Rodríguez-Pacheco Roberto
Published: November 2023

The paper presents the main experimental capabilities of the automatic system for the study of the interaction between porous media and atmosphere. This system is one of the possible variants of patent 2-241-477. The paper shows the result of a drying and wetting study of a tailings sample. The sample is 32 cm in height and 29 cm in diameter. The saturation and drying process was carried out at 26 degrees Celsius at the sample surface, an air velocity of 2 m/s and a relative humidity of 60%. The recharge applied to the column surface was 0.3 cm3/cm2/minute. The results show the effectiveness of the system in controlling the spatial-temporal variation of different physical properties of the porous medium in the vertical and surface profile. The controlled variables include volumetric water content, suction, relative humidity, sample weight variation due to recharge or drying, shrinkage, temperature, etc. The experiment shows how the tailings saturate very quickly but dry very slowly. Tailings consolidation occurs in the drying and wetting processes, being higher in the first one.
Location Planning of Emergency Medical Facilities using the p-Dispersed-Median Modeling Approach
Authors: Oh Changwha , Chun Yongwan , Kim Hyun
Published: November 2023

This research employs a spatial optimization approach customized for addressing equitable emergency medical facility location problems, through the p-dispersed-median problem (p-DIME). The p-DIME integrates two conflicting classes of spatial optimization problems, dispersion, and median problems, aiming to identify the optimal locations for emergency medical facilities to achieve a balanced spatial distribution of emergency medical services (EMS) while effectively serving demands. To demonstrate the utility of the p-DIME model, we selected Gyeongsangbuk-do in South Korea, recognized as one of the most challenging areas for providing EMS to the elderly population (aged 65 and over). This challenge arises from the significant spatial disparity in the distribution of emergency medical facilities. The results of the model assessment gauge the spatial disparity of EMS, provide significantly enhanced solutions for a more equitable EMS distribution in terms of service coverage, and offer policy implications for future EMS location planning. In addition, to address the computational challenges posed by p-DIME's inherent complexity, involving mixed-integer programming, this study introduces a solution technique through constraint formulations aimed at tightening the lower bounds of the problem's solution space. The computational results confirm the effectiveness of this approach in ensuring reliable computational performance, with significant reductions in solution times, while still producing optimal solutions.
Decoding Cancer’s Metabolic Manipulation: Exploring the Influence of the Tumor Microenvironment on Immune Cell Metabolism and Antitumoral Response
Authors: Youssef Reem , Maniar Rohan , Khan Jaffar , Mesa Hector
Published: November 2023

The TME, consisting of immune cells, fibroblasts, vessels, and the extracellular matrix, regulates tumor progression and therapy responses. TME-targeted therapies aim to transform this environment from supporting tumor growth to impeding it and fostering an effective immune response. This review examines the metabolic disparities between immune cells and cancer cells, their impact on immune function and therapeutic targeting, the TME components, and the complex interplay between cancer cells and non-tumoral cells. The success of TME-targeted therapies highlights their potential in achieving better cancer control or even a cure.
Preferential Expansion of HPV16 E1-Specific T Cells from Healthy Donors’ PBMCs after Ex Vivo Immunization with an E1E2E6E7 Fusion Antigen
Authors: Daradoumis Joana , Müller Mikkel Dons , Neckermann Patrick , Asbach Benedikt , Schrödel Silke , Thirion Christian , Wagner Ralf , Thor Straten Per , Holst Peter Johannes , Boilesen Ditte
Published: November 2023

Persistent human papillomavirus (HPV) infection is responsible for practically all cervical and a high proportion of anogenital and oropharyngeal cancers. Therapeutic HPV vaccines in clinical development show great promise in improving outcomes for patients who mount an anti-HPV T cell response, but far from all patients elicit a sufficient immunological response. This witnesses a translational gap between animal models and human patients. Here, we investigated the potential of a new assay consisting of co-culturing vaccine-transduced dendritic cells (DCs) with syngeneic healthy human peripheral blood mononuclear cells (PBMCs) to mimic a human in vivo immunization. This new promising human ex vivo PBMC assay was evaluated using an innovative therapeutic adenovirus (Adv)-based HPV vaccine encoding the E1, E2, E6, and E7 HPV16 genes. This new method allowed us to show that vaccine-transduced DCs yielded functional effector T cells and unveiled information on immunohierarchy showing E1-specific T cell immunodominance over time. We suggest that this assay can be a valuable translational tool to complement the known animal models, not only for HPV therapeutic vaccines, and supports the use of E1 as an immunotherapeutic target. Nevertheless, the findings reported here need to be validated in a larger number of donors, and preferably in patient samples.
Isolation and Pathogenicity Analysis of a G5P[23] Porcine Rotavirus Strain
Authors: Gao Liguo , Shen Hanqin , Zhao Sucan , Chen Sheng , Zhu Puduo , Lin Wencheng , Chen Feng
Published: November 2023

(1) Background: Group A rotaviruses (RVAs) are the primary cause of severe intestinal diseases in piglets. Porcine rotaviruses (PoRVs) are widely prevalent in Chinese farms, resulting in significant economic losses to the livestock industry. However, isolation of PoRVs is challenging, and their pathogenicity in piglets is not well understood. (2) Methods: We conduct clinical testing on a farm in Jiangsu Province, China, and isolate strains of porcine rotavirus by continuously passaging on MA104 cells. Subsequently, the pathogenicity of the isolated strain in piglets was investigated.The piglets of the PoRV-infection group were orally inoculated with 1 mL of 1.0 × 106 TCID50 PoRV, whereas those of the mock-infection group were fed with an equivalent amount of DMEM. (3) Results: Fecal samples were collected from 28 piglets, all of which tested positive for RVAs. A G5P[23] genotype porcine rotavirus strain was successfully isolated from one of the positive samples and named RVA/Pig/China/JS/2023/G5P[23](JS). The genomic constellation of this strain was G5-P[23]-I5-R1-C1-M1-A8-N1-T1-E1-H1. Sequence analysis revealed that the genes VP3, VP7, NSP2, and NSP4 of the JS strain were closely related to human RVAs, whereas the remaining gene segments were closely related to porcine RVAs, indicating a reassortment between porcine and human strains. Furthermore, infection of 15-day-old piglets with the JS strain resulted in a diarrheal rate of 100% (8 of 8) and mortality rate of 37.5% (3 of 8).(4) Conclusion: The isolated G5P [23] genotype rotavirus strain, which exhibited strong pathogenicity in piglets, may have resulted from recombination between porcine and human strains. It may serve as a potential candidate strain for developing vaccines, and its immunogenicity can be tested in future studies.
Prototype Test on Resilient Friction Materials for Seismic Dampers
Authors: Francavilla Antonella Bianca , Latour Massimo , Rizzano Gianvittorio
Published: November 2023

In recent decades, low-yielding seismic devices based on the use of friction dampers have emerged as an excellent solution for the development of building structures with improved reparability and resilience. Achieving an optimal design for such low-yielding seismic devices requires precise control of bolt preloading levels and predictability of the friction coefficient (CoF) between the damper interfaces. While various types of friction devices exist, capable of providing significant energy dissipation, ongoing research is focused on the development of novel friction materials that exhibit a stable hysteretic response, high CoF values, minimal differences between static and dynamic CoF, and predictable slip resistance. In this context, an experimental campaign was conducted at the STRENGTH Laboratory of the University of Salerno to evaluate the behaviour of new friction shims employing specially developed metal alloys. Specifically, the influence of the characteristics of the contact surfaces in the sliding area on the behaviour and performance of the friction device was analysed. The tests followed the loading protocol recommended by EN12159 for seismic device qualification. Monitored parameters included preloading force values and the evolution of slip resistance. The friction value was determined, along with its degradation over time. Finally, the material's performance in terms of hysteretic behaviour was assessed, providing a comparison of the tested specimens in terms of slip force degradation and energy dissipation capacity.
Entorhinal cortex vulnerability to human APP expression promotes
hyperexcitability and tau pathology
Authors: Rowan Matthew , Goettemoeller Annie , Banks Emmie , McCann Katharine , Kumar Prateek , South Kelly , Olah Viktor , Ramelow Christina , Duong Duc , Seyfried Nicholas , Rangaraju Srikant , Weinshenker David
Published: November 2023

Preventative treatment for Alzheimer’s Disease is of dire importance, and yet, cellular mechanisms underlying early regional vulnerability in Alzheimer’s Disease remain unknown. In human patients with Alzheimer’s Disease, one of the earliest observed pathophysiological correlates to cognitive decline is hyperexcitability1. In mouse models, early hyperexcitability has been shown in the entorhinal cortex, the first cortical region impacted by Alzheimer’s Disease2-4. The origin of hyperexcitability in early-stage disease and why it preferentially emerges in specific regions is unclear. Using cortical-region and cell-type- specific proteomics and patch-clamp electrophysiology, we uncovered differential susceptibility to human-specific amyloid precursor protein (hAPP) in a model of sporadic Alzheimer’s. Unexpectedly, our findings reveal that early entorhinal hyperexcitability may result from intrinsic vulnerability of parvalbumin interneurons, rather than the suspected layer II excitatory neurons. This vulnerability of entorhinal PV interneurons is specific to hAPP, as it could not be recapitulated with increased murine APP expression. Furthermore, the Somatosensory Cortex showed no such vulnerability to adult-onset hAPP expression, likely resulting from PV-interneuron variability between the two regions based on physiological and proteomic evaluations. Interestingly, entorhinal hAPP-induced hyperexcitability was quelled by co-expression of human Tau at the expense of increased pathological tau species. This study suggests early disease interventions targeting non-excitatory cell types may protect regions with early vulnerability to pathological symptoms of Alzheimer’s Disease and downstream cognitive decline.
Solution-processed NO2 gas sensor based on PbS QDs doped with P3HT operating at room temperature
Authors: Kwon JinBeom , Jung Daewoong , Ha Yuntae , Choe Suji , Jung Donggeon
Published: November 2023

With the worldwide industrial development and the increase in means of transportation such as automobiles and ships, the problem of the greenhouse gases has been steadily emerging. Among them, NO2 is a gas that is emitted in large quantities from the automobile and factories, and is unavoidably emitted in modern society. Therefore, a sensor capable of precisely detecting NO2 is required. Among various types of NO2 sensors, metal oxide-based sensors are reported the most. However, it is impossible to operate at room temperature due to its high-temperature operating characteristics, so a heater for heating must be designed inside the sensor or installed outside. On the other hand, the NO2 sensor based on PbS QDs has the advantage of being able to measure at room temperature and being easily manufactured through a solution process rather than a complicated semiconductor process. In this study, NO2 sensor was fabricated by doping P3HT on PbS QDs. As a result of the responsivity of the fabricated sensor to NO2 gas, it was confirmed that the sensor had high responsivity with a resolution of 200 ppb from 20 to 0.4 ppm due to the stability of the thin film and high hole mobility characteristics by P3HT.
Endocannabinoids and their receptors modulate endometriosis pathogenesis and immune response
Authors: Tayade Chandrakant , Lingegowda Harshavardhan , Zutautas Katherine , Wei Yuhong , Yolmo Priyanka , Sisnett Danielle , McCallion Alison , Koti Madhuri
Published: November 2023

Endometriosis (EM), characterized by the presence of endometrial-like tissue outside the uterus, is the leading cause of chronic pelvic pain and infertility in females of reproductive age. Despite its high prevalence, the molecular mechanisms underlying EM pathogenesis remain poorly understood. The endocannabinoid system (ECS) is known to influence several cardinal features of this complex disease including pain, vascularization, and overall lesion survival, but the exact mechanisms are not known. Utilizing CNR1 knockout (k/o), CNR2 k/o, and wild-type (WT) mouse models of EM, we reveal the contributions of ECS and these receptors in disease initiation, progression, and immune modulation. Particularly, we identified EM-specific T cell dysfunction in the CNR2 k/o mouse model of EM. We also demonstrate the impact of decidualization-induced changes on ECS components and the unique disease-associated transcriptional landscape of ECS components in EM. Imaging Mass Cytometry (IMC) analysis revealed distinct features of the microenvironment between CNR1, CNR2, and WT genotypes in the presence or absence of decidualization. This study, for the first time, provides an in-depth analysis of the involvement of the ECS in EM pathogenesis and lays the foundation for the development of novel therapeutic interventions to alleviate the burden of this debilitating condition.
In-depth Inference of Transcriptional Regulatory Networks Identifies NPM1 as a Druggable Master Regulator in Medulloblastoma
Authors: Lin Yifeng , Dong Xinran , Chen Tong , Chen Huiyao , Xia Mingyang , Liao Yunfei , Li Hao , Zhou Wenhao
Published: November 2023

Medulloblastoma (MB) is a highly malignant embryonic brain tumor with distinct cytogenetic heterogeneity in children. Despite elucidating divergent regulatory underpinnings in MB molecular subtypes, the hidden oncogenic signaling drivers with minimal differential expression remain obscure. Here, we leveraged two bulk RNA-seq datasets involving 1055 patients to construct pediatric MB specific co-expression profiles and regulatory networks, unveiling unique attributes of the ribosome pathway in different molecular subtypes. NPM1, a pivotal ribosome regulator, was pinpointed as a promising targetable driver for MB by integrating differentially expressed candidates and reported drug targets. To assess the role of NPM1 in MB progression, we employed NETBID2 gene activity algorithm, Kaplan–Meier survival curves, single-cell RNA-seq (scRNA-seq) analysis, and functional validations in MB cell lines. Our findings highlighted substantial correlations between the activity values of NPM1 and the prognosis of MB patients, eclipsing the significance of its expression levels. Furthermore, NPM1 was extensively and highly expressed in early SOX2 positive neural stem cells and tumor cells. Deficiency of NPM1 impeded MB cell growth, triggered apoptosis and led to a reduction of c-Myc levels. Our findings provide new approaches for exploring underlying pathways and underscore the clinical transformation value of NPM1 as a master regulator for MB.
A taxonomy of patient experiences of access and continuity at team-based primary healthcare clinics
Authors: Deville-Stoetzel Nadia , Gaboury Isabelle , Berbiche Djamal , Breton Mylaine
Published: November 2023

Background
Access to primary healthcare services is a core lever for reducing health inequalities. Population groups living with certain individual social characteristics are disproportionately more likely to experience barriers accessing care. This study identified profiles of access and continuity experiences of patients registered at team-based primary healthcare clinics and explored the associations of these profiles with individual and organizational characteristics.
Methods
A cross-sectional e-survey was conducted between September 2022 and April 2023. All registered adult patients with an email address at 104 team-based primary healthcare clinics in Quebec were invited to participate. Latent class analysis was used to identify patient profiles based on nine components of access to care and continuity experiences. Multinomial logistic regression models were fit to analyze each profile’s association with ten characteristics related to individual sociodemographics and two related to clinic area and size.
Results
Based on 87,155 patient experiences, four profiles were identified. "Easy access and continuity" (42% of respondents) was characterized by ease in almost all access and continuity components. Three profiles were characterized by diverging access and/or continuity difficulties. "Challenging booking" (32%) was characterized by patients having to try several times to obtain an appointment at their clinic. "Challenging continuity" (9%) was characterized by patients having to repeat information that should have been in their file. "Access and continuity barriers" (16%) was characterized by difficulties with all access and continuity components. Female gender and poor perceived health significantly increased the risk of belonging to the three profiles associated with difficulties by 1.5. Being a recently arrived immigrant (p = 0.036), having less than a high school education (p = 0.002) and being registered at a large clinic (p < 0.001) were associated with experiencing booking difficulties. Having at least one chronic condition (p = 0.004) or poor perceived mental health (p = 0.048) were associated with experiencing continuity difficulties.
Conclusions
These results highlight individual social characteristics associated with increased risk of experiencing particular access and/or continuity difficulties. Personalized strategies are recommended, such as facilitating appointment booking for recently arrived immigrants and patients with low education, integrating interprofessional collaboration practices for patients with chronic conditions and improving care coordination and communication for patients with mental health needs.
Factors Influencing Flowability of Microbial Gel Filling Materials and Optimization of Ratios Using Design of Experiments Method
Authors: ZHANG Zhendong , SHI Wenlong , LIU Jiashun , LI Jun , JIANG Cuiping , CUI Chenwei , LI Mengyan , GE Xinyan
Published: November 2023

During coal mining, a significant amount of coal gangue is generated. The coal gangue occupies a considerable amount of land resources and causes environmental damage to the surrounding areas. Currently, the utilization rate of coal gangue is low. To address this issue, this study employed a method that combines a water-absorbent resin with microbially induced calcium carbonate precipitation (MICP) to prepare paste-filling materials. The water retention properties of the water-absorbent resin provide continuous reaction sites for MICP, increasing the calcium carbonate nucleation points and thereby solidifying the coal gangue into paste materials. A design of experiments (DOE) mixture scheme was utilized to conduct tests on the water seepage, slump, and expansion of the paste material, analyze the influence of material composition on its flowability, and optimize the ratios. Through electron microscopy, the morphology and distribution of calcium carbonate crystals during the solidification process were examined. Accordingly, the mechanism by which the water-absorbent resin combined with MICP solidified coal gangue in preparation of paste-filling materials was revealed. The findings of this research provide a theoretical foundation and technical support for engineering applications.
Prevalence and associated factors of suicidal ideation, non-suicidal self-injury and suicide attempt among male construction industry workers in Ireland
Authors: O’Donnell Shane , Egan Tom , Clarke Nicholas , Richardson Noel
Published: November 2023

Background
Suicide among male construction industry workers (CIWs) are reported to be disproportionally high compared to the working age population. However, there is minimal understanding of the prevalence and associated factors of suicidal ideation (SI), non-suicidal self-injury (NSSI), and suicide attempts (SA) among male CIWs.
Methods
A cross-sectional study was conducted on a large sample of male CIWs in Ireland (n = 1,585). We investigated the prevalence of SI, NSSI and SA and sociodemographic, occupational, and mental health factors associated with these three outcomes. Multivariable Poisson regression was performed to estimate the incidence rate ratio (IRR) of SI (model 1 primary outcome), while multivariable logistic regression was used to estimate the odds ratio (OR) of NSSI (model 2 primary outcome), and SA (model 3 primary outcome).
Results.
The lifetime prevalence rate of SI in this study was 22%, 6% for NSSI, and 6% for SA. In univariable modelling, socio-demographic and occupational factors associated with the three outcomes included younger age (SI and NSSI), not being in a relationship (SA) and working 35–44 hours per week (SI and SA). All psychological factors (past mental health difficulties, history of mental health treatment, generalized anxiety disorder (GAD), depression, suicide bereavement) were significantly associated with increased risk of the three outcomes. In fully adjusted multivariable models: (1) past mental health difficulties, higher GAD and depression levels were associated with increased IRR of suicide ideation; (2) past mental health difficulties and higher GAD levels were associated with a higher odds ratio (OR) of NSSI and; (3) past mental health difficulties and higher depression levels were associated with higher ORs for SA.
Conclusion.
SI, NSSI and SA are significant issues for male CIWs that require specific attention. Findings highlight a need to support younger male CIWs and those bereaved by suicide. They also highlight the need for the early detection and treatment of GAD and depression in order to intervene in, and potentially prevent, suicidality among male CIWs.
Predicting LULC changes and assessing their impact on surface runoff with machine learning and remote sensing data.
Authors: Riche Abdelkader , Drias Ammar , Ricci Riccardo , Souissi Boularbah , Melgani Farid
Published: November 2023

This study employs an approach to examine the influence of urbanization-induced land use changes on surface runoff. The research leverages the SCS-CN method, integrating remote sensing and machine learning, to analyze land use and cover (LULC) changes over the years 2000 to 2040. Initial land use classification (2000–2020) utilizes the SVM algorithm, while a novel temporal approach is applied to predict LULC for the years 2025, 2030, and 2040. The accuracy of the LULC prediction model is demonstrated to be 85.05% using the Random Forest (RF) algorithm. Notably, built-up areas increase from 11.73% (2000) to 32.96% (2040), whereas cultivated land and grassland decrease from 46.50–26.67%. The study further utilizes the SCS-CN method to model runoff for precipitation return periods of 5, 10, and 20 years, calculating Curve Number (CN) values. The results reveal variations in runoff patterns across different LULC classes and time periods. Higher return periods are associated with expanded runoff areas, with built-up areas contributing to runoff, while forests mitigate it. The study identifies that land factors, such as interception and permeability, exhibit limited influence during intense rainfall events, primarily due to capacity and saturation constraints. These findings have important implications for water resource management and strategies related to flood risk mitigation, benefiting governmental officials, planners, environmental experts, and hydraulic engineers. It's worth noting that a case study in Algeria was selected for its data availability.
Mutation order in acute myeloid leukemia identifies uncommon patterns of evolution and illuminates phenotypic heterogeneity
Authors: Majeti Ravi , Schwede Matthew , Jahn Katharina , Kuipers Jack , Miles Linde , Bowman Robert , Robinson Troy , Furudate Ken , Uryu Hidetaka , Tanaka Tomoyuki , Sasaki Yuya , Ediriwickrema Asiri , Benard Brooks , Gentles Andrew , Levine Ross , Beerenwinkel Niko , Takahashi Koichi
Published: November 2023

Acute myeloid leukemia (AML) has a poor prognosis and a heterogeneous mutation landscape. Although common mutations are well-studied, little research has characterized how the sequence of mutations relates to clinical features. Using published, single-cell DNA sequencing data from three institutions, we compared clonal evolution patterns in AML to patient characteristics, disease phenotype, and outcomes. Mutation trees, which represent the order of select mutations, were created for 207 patients from targeted panel sequencing data using 1 639 162 cells, 823 mutations, and 275 samples. In 224 distinct orderings of mutated genes, mutations related to DNA methylation typically preceded those related to cell signaling, but signaling-first cases did occur, and had higher peripheral cell counts, increased signaling mutation homozygosity, and younger patient age. Serial sample analysis suggested that NPM1 and DNA methylation mutations provide an advantage to signaling mutations in AML. Interestingly, WT1 mutation evolution shared features with signaling mutations, such as WT1-early being proliferative and occurring in younger individuals, trends that remained in multivariable regression. Some mutation orderings had a worse prognosis, but this was mediated by unfavorable mutations, not mutation order. These findings add a dimension to the mutation landscape of AML, identifying uncommon patterns of leukemogenesis and shedding light on heterogenous phenotypes.
Design and test of a 50 mK CMOS 16 to 1 multiplexing ASIC for high impedance NbSi TES arrays
Authors: Criton Benjamin , Broïse Xavier de la , Sauvageot Jean-Luc
Published: November 2023

Achieving high spectral and spatial resolution of wide astrophysical objects in theX-ray band will be the main focus of the future X-ray space telescopes.We explorea new technological solution based on high impedance TES detectors (∼2MΩ)enabling the transfer of the pre-amplification stage to higher temperatures (4 K)and the use of a 50mK CMOS multiplexer to reduce power dissipation at 50 mK.We present the design and first tests of a 50mK CMOS ASIC multiplexing 16high impedance NbSi TES detectors to 1 amplifier with a total power budgetunder 2μW. In parallel of this development, we fabricated 4-by-4 NbSi pixelmatrices to build a complete demonstrator (comprising the detector array, themultiplexing ASIC and the 4K amplification stage). We aim at a multiplexingcycle time of 48μs leaving 3μs for reading-out each high impedance pixel. Themultiplexing ASIC will embed parasitic capacity compensation techniques.
A novel model of non-singular oscillating cosmology on flat Randall-Sundrum II braneworld
Authors: Sengupta Rikpratik
Published: November 2023

We obtain a \textit{novel} model of oscillating non-singular cosmology on the spatially flat Randall-Sundrum (RS) II brane. At early times, the universe is dominated by a scalar field with an inflationary emergent potential $V(\phi)=A(e^{B\phi}-1)^2$, $A$ and $B$ being constants. Interestingly, we find that such a scalar field can source a non-singular bounce, replacing the big bang on the brane. The turnaround again happens naturally on the brane dominated by a phantom dark energy (favoured by observations\cite{E1,E2,E3} at late times), thus avoiding the big rip singularity and leading upto the following non-singular bounce via a contraction phase. There is a smooth non-singular transition of the brane universe through both the bounce and turnaround, leading to alternate expanding and contracting phases. This is the \textit{first} model where a single braneworld of positive tension can be made to recycle as discussed in details in the concluding section.