bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diet affects reproductive development and microbiota composition in honey bees
Authors: Zumkhawala-Cook Anjali , Gallagher Patrick , Raymann Kasie 
Published: October 2024

Abstract

Background Gut microbes are important to the health and fitness of many animals. Many factors have been shown to affect gut microbial communities including diet, lifestyle, and age. Most mammals have very complex physiologies, lifestyles, and microbiomes, making it virtually impossible to disentangle what factors have the largest impact on microbiota composition. Honeybees are an excellent model to study host-microbe interactions due to their relatively simple gut microbiota, experimental tractability, and eusociality. Worker honey bees have distinct gut microbiota from their queen mothers despite being close genetic relatives and living in the same environment. Queens and workers differ in many other ways including development, physiology, pheromone production, diet, and behavior. In the prolonged absence of a queen or Queen Mandibular Pheromones (QMP), some but not all workers will develop ovaries and become “queen-like”. Using this inducible developmental change, we aimed to determine if diet, reproductive development, or pheromone exposure impacts the gut microbiota of honey bee workers.Results Microbiota-depleted newly emerged workers were inoculated with a mixture of queen and worker gut homogenates and reared under four conditions varying in diet and pheromone exposure. Three weeks post-emergence, workers were evaluated for ovary development and their gut microbiota communities were characterized. The proportion of workers with developed ovaries was increased in the absence of QMP but also when fed a queen diet (royal jelly). Overall, we found that diet, rather than reproductive development or pheromone exposure, led to more “queen-like” microbiota in workers. However, we revealed that diet alone cannot explain the microbiota composition of workers.Conclusion Here we demonstrated that diet is one of the main drivers of differences between the gut microbial community compositions of honey bee queens and workers, but cannot fully explain the distinct microbiota of queens. Thus, we hypothesize that behavioral differences play a major role in shaping the microbiota of honey bee workers and queens. Our findings not only contribute to our understanding of the factors affecting the honey bee microbiota, which is important for bee health, but also illustrate the versatility and benefits of utilizing honeybees as a model system to study host-microbe interactions.
Beyond Static Brain Atlases: AI-Powered Open Databasing and Dynamic Mining of Brain-Wide Neuron Morphometry
Authors: Peng Hanchuan , Jiang Shengdian , Wang Lijun , Yun Zhixi , Chen Hanbo , Yao Jianhua 
Published: October 2024

Abstract

We introduce NeuroXiv (neuroxiv.org), a large-scale, AI-powered database that provides detailed 3D morphologies of individual neurons, designed to support a wide array of neuroscience applications. NeuroXiv offers a comprehensive collection of 175,149 atlas-oriented reconstructed morphologies of individual neurons derived from more than 518 mouse brains, classified into 292 distinct types and mapped into the Common Coordinate Framework Version 3 (CCFv3). The platform also allows uploading and databasing custom neuron morphologies, which are systematically mapped to brain atlases for objective comparisons. Powered by a cutting-edge AI engine (AIPOM), NeuroXiv enables interactive, user-specific analysis and data mining. We specifically optimized a mixture-of-experts algorithm to harness the capabilities of multiple large language models, deploying it on a client program to achieve more than 10 times better performance compared to a typical server-side setup. We demonstrate NeuroXiv's scalability, efficiency, flexibility, openness, and robustness through various applications.
Dapagliflozin Ameliorates Myocardial Ischemia/Reperfusion Injury by Modulating EGFR Signaling and Targeting NCOA4-mediated Ferritinophagy
Authors: Yu Peng , Ling Jitao , Chen Feng , Xu Zhou , Hu Kaibo , Liu Fuwei , Zhang Deju , Chen Yixuan , Liu Xiao , Xia Panpan , Wu Yuting , Zhang Jing , Huang Tieqiu , Zhan Yuliang 
Published: October 2024

Abstract

SGLT2 inhibitor dapagliflozin (Dapa) has gained increasing attention in the treatment of myocardial ischemia-reperfusion injury (IRI). However, the mechanism of action of the cardiovascular benefits of Dapa is unclear. The present study aimed to investigate the effects of Dapa on myocardial IRI and the underlying molecular mechanisms. The effects of Dapa on myocardial IRI were investigated using the in vitro perfusion Langendorf model and the in vitro hypoxia/reoxygenation (H/R) cell model. Histological changes, myocardial enzymes, oxidative stress and mitochondrial structure/function were assessed. Mechanistic studies involved various molecular biology methods such as ELISA, immunoprecipitation, western blot, immunofluorescence and Bioinformatics. Our findings demonstrate that Dapa upregulates EGFR phosphorylation, suppresses NHE1 expression in myocardial tissues, modulates NCOA4-mediated ferritinophagy to enhance mitochondrial function, reduces ROS expression, and mitigates myocardial IRI. In the Langendorf model, Dapa effectively attenuates cardiac dysfunction, myocardial injury, mitochondrial damage, and oxidative imbalance induced by ischemia-reperfusion. In vitro experiments revealed that blocking EGFR or autophagy with inhibitors (AG and Baf, respectively) or inducing ferroptosis with Era promotes ROS release, exacerbates mitochondrial injury, and diminishes the protective effects of Dapa. Notably, Era did not affect NCOA4-mediated ferritinophagy. Conversely, the EGFR agonist NSC counteracted these effects, underscoring that Dapa confers cardioprotection by modulating mitochondrial function through EGFR-mediated regulation of NCOA4-mediated ferritinophagy. In summary, Dapa activates EGFR phosphorylation, regulates NCOA4-mediated ferritinophagy, modulates mitochondrial function, and effectively mitigates myocardial IRI. These findings provide a robust theoretical foundation for the clinical application of Dapa in treating cardiovascular conditions.
The Prevalence of Alzheimer's Disease and Hospital Readmissions Rates: A Retrospective Study
Authors: Nekkalapu Hima 
Published: October 2024

Abstract

Alzheimer's disease is a progressive neurodegenerative disease primarily affecting the elderly population and is a major public health challenge worldwide. The objective of this Retrospective quantitative study was to investigate the prevalence rates of Alzheimer’s Disease (AD) in the United States within the population aged 65 and above and explore variations within the study population. In addition, the study also examined the AD prevalence and readmission rates in comparison with other specific chronic conditions to provide a holistic understanding of Alzheimer’s disease. The study’s primary data source was the specific chronic conditions data derived from the CMS (Centers for Medicare and Medicaid Services) from the year 2018, which included specific chronic conditions, patient demographics, prevalence and hospital readmission rates, emergency room visits, beneficiary status, and Medicare payments. The study conducted a comprehensive literature review to better understand the complex interplay of different key variables in the context of Alzheimer’s disease. The next step was data mining, followed by descriptive and inferential analysis to investigate the dataset. The study observed significant correlations between Age and Alzheimer’s disease, along with noteworthy variations based on gender, ethnicity, and location. The study also observed significant differences in the hospital readmission rates and healthcare utilization metrics when compared to other specific chronic conditions. The study findings reflect the unique healthcare challenges associated with Alzheimer’s disease and offer valuable information to the key stakeholders encouraging further research and futuristic healthcare designs to optimize care strategies and resource allocation to mitigate the impact of Alzheimer's disease.
Hospitality's resilience and regenerative adaptations towards sustainability
Authors: Kagisho Stanley , Joao Erica Soa 
Published: October 2024

Abstract

The South African hospitality industry faces challenges such as economic volatility, climate change, and shifting consumer preferences. To address these effectively, hotels must adopt resilience and regenerative strategies. The theoretical framework of this study includes Resilience Theory, Service-Dominant Logic (SDL), and Ecological Modernisation Theory. This qualitative study utilised semi-structured interviews with hotel managers and a literature review. Thematic coding revealed strategies like robust crisis management, income diversification, and community ties. Regenerative practices focus on waste reduction, biodiversity support, and sustainable infrastructure, aligning with Sustainable Development Goals (SDGs) 9 and 1, which address building resilient infrastructure and poverty eradication. The study highlights the need for guest education on sustainability and explores emerging technologies like AI and blockchain to enhance resilience and sustainability. This research advocates for a holistic approach to hospitality management, combining innovation, community engagement, and environmental stewardship for lasting industry change.
Incorporating an attention layer in deep learning models to enhance short-term stock price predictions
Authors: Meena Jitesh Kumar , Banyal Rohitash Kumar 
Published: October 2024

Abstract

In recent years, deep learning models have gained significant attention in the field of stock market prediction. However, accurately forecasting short-term stock prices remains a challenging task due to the inherent volatility and complexity of financial markets. RNN Algorithms like LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Unit) provide decent predictions on stock market time series data. However, these algorithms face bottleneck situations that arise due to the complex nature of the input sequences. This research paper aims to investigate the effectiveness of incorporating attention layers in deep learning models to improve the accuracy of short-term stock price predictions. Subsequently, the layer assigns weights to the attributes based on their scores, highlighting the attributes that are more relevant within the sequence. With the integration of attention layer into the encoder-decoder model, we are able to extract and emphasize pertinent information from the complex time series sequences, thereby enhancing the accuracy of hybrid to 95% and attention reached to 99% accuracy.
Loss of PERIOD2 (PER2) induces HO-1-mediated epithelial-mesenchymal transition and cisplatin resistance in Epi-A ovarian cancer
Authors: Hwang-Verslues Wendy , Tan Grace , Vinothkumar Priyanka , Cheng Li-Tzu , Lin Pei-Yi , Chen Chung-Lien William , Yu Chen-Hsin , Chiu Yi-Chia , Huang Ruby 
Published: October 2024

Abstract

Rapid metastasis and chemoresistance make ovarian cancer (OC) the deadliest gynecological cancer. These malignant phenotypes are strongly associated with epithelial-mesenchymal transition (EMT). OC is highly heterogenous with five distinct gene-expression based molecular subtypes (GEMS) correlated with different EMT levels and patient survival. However, the regulatory mechanisms underlying GEMS-specific EMT and malignancy remain unclear. We found that PER2 gene expression was significantly downregulated in OC compared to normal ovarian tissues. Among the five GEMS, PER2 expression was relatively high in the Epithelial-A (Epi-A) subtype and Epi-A OC patients with higher PER2 level had better overall survival. Notably, PER2 expression was required to maintain the epithelial phenotype. Conversely, PER2 depletion drove EMT and consequently enhanced migration and invasion ability of Epi-A OC cells via upregulation of Heme oxygenase-1 (HO-1). PER2 depletion also increased cisplatin resistance. Inhibition of HO-1 in PER2-depleted Epi-A OC cells impeded invasion and migration, and re-sensitized the cells to cisplatin. Our results revealed new insights into how an epithelial-like, less malignant OC subtype acquires EMT to become more invasive and chemoresistant. These findings also indicate that prevention of PER2 downregulation and targeting HO-1 are promising strategies for treating Epi-A OC progression.
Can the movement ecology of the deep-sea bivalve Acesta excavata lead to a dynamic habitat?
Authors: Sacco Domenico , Cardinale Pierfrancesco , Canese Simonepietro , Greco Silvestro , Danovaro Roberto 
Published: October 2024

Abstract

Acesta excavata is one of the largest and ecologically relevant bivalves along continental margins and is often associated with cold-water coral assemblages of the upper bathyal zone. Like other habitat-forming species, Acesta excavata contributes to increasing the secondary substrates and provides opportunities for the colonization and feeding of other sessile and mobile organisms. Despite most of the bivalves producing byssus are thought to be sessile or sedentary throughout their adult life stages, some species are known to be able to displace. Here we investigated, in mesocosm conditions, the ability of this deep-sea species to move/displace and compared its mobility with that of other shallow-water species. We report here for the first time that Acesta excavata moves almost continuously, a maximum speed of 6.5 cm day− 1 (maximum weekly displacement of ca 28 cm), with average speeds of approximately 0.3–1.3 cm per day. This speed is the highest value reported so far for byssus-attached bivalves (including Mytilus spp and Pictada imbricata radiata). The movement of these bivalves, apparently due to the search for optimal feeding and substrate characteristics, can displace the habitat that they create, also in response to changes in environmental and ecological conditions. These findings offer new opportunities for using this species in restoration protocols of deep-sea habitats and change our view of deep-sea hard bottoms from static to dynamic entities.
Gold Nanoclusters Decorated Hollow ZIF-8 Encapsulating Iron-catecholates as Oxidase Mimetics for Ratiometric Colorimetric Detection of Nitrite
Authors: Wu Cunhui , Dai Mengzhen , Qin Xinguang , Liu Gang , Zhang Haizhi 
Published: October 2024

Abstract

Nitrite detection is of profound significance for guaranteeing food safety and avoiding poisoning incidents. Gold nanoclusters decorated hollow ZIF-8 encapsulating iron-catecholates (Fe-HHTP@HZIF-8@ AuNCs) was formed through self-assembly of Fe3+ and 2,3,6,7,10,11 -hexahydroxytriphenylene (HHTP), in situ embedding of ZIF-8, and Au3+ -Zn2+ exchange reaction. Its morphology and structure were fully characterized by HRTEM, XRD, TEM element mapping and XPS. Additionally, its oxidase-like activity was explored with Km of 0.21 mM and Vmax of 1.74×10− 6 M·s− 1 towards 3,3',5,5'-tetramethylbenzidine (TMB). Due to its excellent catalytic activity and nitrite mediated diazotization of oxTMB, a ratiometric colorimetric method for nitrite detection was established and validated with wide linear range (2.0-400.0 µM), low LOD (0.12 µM), high accuracy (recovery of 95.11-102.14%) and fine selectivity. This method was then utilized to analyze nitrite content in sausages and tap water. This study provided a new idea for developing efficient nanozymes, and offered an accurate approach for nitrite determination.
Joint clustering and feature selection based on trace ratio model and coordinate descent method
Authors: Xu Liang , He Xingshi , Xue Jingjing , Zhang Qingqing 
Published: October 2024

Abstract

Joint clustering and dimensionality reduction methods have great potential involving high-dimensional problems. Feature extraction and feature selection are both of the feature reduction methods. Compared to feature extraction, feature selection retains the original features and has advantages in certain aspects. To achieve the optimized clusters while the distinct features are selected, this paper imposes L2,0 on the discriminative projected matrix based on the trace difference model. For solving the joint optimization model, we use the coordinate descent method for solving the discriminative projected matrix and cluster indicator matrix alternatively. Extensive experiments show that the proposed model have improved on accuracy, NMI and purity compared to other related clustering models, and the proposed algorithm not only has good the convergence is stable across different datasets.
Analysis of Perception Differences in Maxillofacial Aesthetics among the General Population in Northern and Southern China
Authors: Chan Iantong , Huang Jialiang , Mao Yanmin , Lu Yun , Ren Yongzhen , Lyu Jinzhao , Li Qiang 
Published: October 2024

Abstract

Objective: To study the differences in the perception of maxillofacial aesthetics among the general population in the north and south regions.
Materials and Methods: Questionnaires were distributed to investigate the preferences of people in various regions of China regarding the perception of maxillofacial aesthetics and excluded questionnaires in which the actual response time was less than the theoretical calculation of the average time needed to complete the questionnaire. The valid questionnaires were statistically analyzed by taking the Qinling Mountains-Huaihe River Line as the boundary between the north and south, and by adding the factors of gender and age.
Results: (1) Significant differences were observed in the importance attached to unfavorable aesthetics in the lower third of the face between northern and southern populations (P = 0.044). (2) Younger individuals in the south (Post-00s and Post-90s) showed a stronger preference for improving facial harmony through orthodontics than older generations (Post-70s andPost-80s) (P = 0.003). (3) In the north, older groups favored static beauty more than younger groups (P = 0.025), unlike the south (P > 0.05). (4) Southern youth perceived facial convexity as the most unfavorable feature in the lower third of the face (P = 0.021). (5) Northern females’ concern for facial harmony was not statistically significant (P > 0.05), while southern females’ concern was (P = 0.046).
Conclusions: While perceptions of maxillofacial aesthetics are generally similar between northern and southern Chinese populations, subtle differences exist, influenced by age and gender.
Synthesis, Purification, and Photocatalytic Evaluation of Nanostructured N 2 dopped Carbogenic Particles
Authors: Perveen Sonia , Bhatti Ijaz Ahmad , Jamil Saba , Zia Mohammad Anjum 
Published: October 2024

Abstract

Carbon dots (CDs) have brought in significant attention in material science due to their unique characteristics, such as exceptional biocompatibility, physiochemical stability, low toxicity, and photostability. This work aims to synthesize and purify nitrogen-doped carbon dots in a rapid and economical bottom-up (hydrothermal) method. The synthesized material characterization was carried out by utilizing UV spectroscopy, transmission electron microscopy (TEM), X-ray diffraction (XRD), Zeta sizer, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The absorption potential of carbon dots, including dye content, pH, irradiation period, and oxidant concentration, was investigated in batch research. The measurement of parameters related to water quality, including total organic carbon (TOC), biological oxygen demand (BOD), and carbon oxygen demand (COD), was evaluated. Response surface methodology (RSM) was used to enhance operational parameters in wastewater treatment. Additionally, the substrate's (black pumice) reusability was examined for up to fourteen cycles.
Reinforcement Learning-Optimized Personalized Cancer Treatment Strategies: A Case Study of Lung Cancer
Authors: Zhou Chichun , Liu Zhaocong , Li Xinhui , Nai Shuncheng , Zhang Junpeng , Lan Yuanping , Li Lijuan , Liu Yi , Wang Bin , Liu Yaling 
Published: October 2024

Abstract

Personalized cancer treatment strategies (PCTS) tailor treatments on the basis of a patient’s health status, cancer type, and stage. By considering the evolving interactions of treatment options over time, PCTS seeks to balance cancer suppression with minimizing harm and maximizing therapeutic benefits. However, limited clinical trial resources limit the ability to explore optimal PCTSs fully through experimentation, presenting a significant challenge to their development. In this study, we introduce a "digital twin" model that integrates comprehensive patient health data, cancer characteristics, and individual treatment responses and employs reinforcement learning (RL) to identify the optimal PCTS. Using lung cancer as a case study, we calibrated model parameters for various demographic groups, cancer stages, and treatment options, utilizing real clinical data from the SEER dataset. The RL-optimized PCTS significantly outperformed traditional clinician decisions, leading to notable improvements in patient survival. For example, among women aged 45--64 years with stage IIIA, IIIB, IVA, and IVB lung cancer, survival increased by 46%, 59%, 23%, and 149%, respectively. Similarly, for men aged 45--64 years, survival improved by 108%, 97%, 40%, and 62%, respectively, across the same stages. This study lays a critical foundation for the use of AI in optimizing PCTS and paves the way for further research and clinical applications.
Imine based covalent adaptable networks from diacetone acrylamide polymerization
Authors: Chen Hanghang , hou Zihao , Li Liqiong , Deng Haoyu , Ouyang Yixue , Ye Dezhan , Jiang Xiancai 
Published: October 2024

Abstract

The construction of covalent adaptable networks (CANs) without the need for post-modification, complex monomer synthesis routes, or expensive materials is highly desirable for the practical application of dynamic covalent chemistry. In the present study, the commercially available acrylate monomer, diacetone acrylamide (DAAM), was initially polymerized using a traditional radical polymerization method. Subsequently, it was cross-linked with amine agents under hot-processing conditions to form aliphatic imine-based CANs. The resulting materials exhibited glass transition temperatures (Tg) in the range of 95 to 107°C, good thermal stability, mechanical and thermomechanical properties. All samples were amenable to mechanical recycling. Post-recycling, both the tensile strength and Young's Modulus exhibited a slight deterioration, retaining approximately 80% of their original properties. The results from gel content analysis and structural characterization of both pristine and recycled samples indicate that the observed reduction in mechanical properties and Tg (approximately 70°C) can be attributed to a decrease in the degree of cross-linking and the release of aliphatic ketone groups. Furthermore, all samples demonstrated degradability under acidic conditions, attributable to their aliphatic imine structure. By using this facile approach to prepare acrylate-based imine CANs, we establish an important framework for polymer materials that are both reprocessable and biodegradable.