bluuebunny/crossref_metadata_2025_split huggingface dataset:
Targeting Alzheimer's Disease with Tinospora cordifolia (Guduchi): A metabolomics and network pharmacology approach highlighting BACE1 and MAO-B as potential targets
Authors: Amrutha S , Parvaje Ravishankar , Abhinand Chandran S. , Prasad Thottethodi Subrahmanya Keshava , Modi Prashant Kumar 
Published: November 2024

Abstract

Tinospora cordifolia has been used for thousands of years to treat various health conditions, including neurodegenerative diseases. The study aimed to elucidate the mechanism of action and protein targets of T. cordifolia in the context of Alzheimer’s disease through untargeted metabolomics and network pharmacology. LC-MS/MS analysis resulted in 1186 metabolites, including known bioactive compounds such as liquiritin, Plastoquinone 3, and Shoyuflavone A, to name a few. The network pharmacology analysis highlighted the metabolite-protein interaction with the enrichment of 591 human proteins, including neurotransmitter receptors and other regulatory proteins. Pathway analysis highlighted the enrichment of cAMP, mTOR, MAPK, and PI3K-Akt signaling pathways along with cholinergic, dopaminergic, serotonergic, glutamatergic synapse, and apoptosis. The docking results suggest that T. cordifolia metabolites could interact with key Alzheimer's disease targets BACE1 and MAO-B, suggesting its role in neuroprotection. These findings provide insights into the biochemical pathways underlying T. cordifolia's therapeutic effects and provides a foundation for future exploration of T. cordifolia in the context of translational research.
Exploring the efficacy of eco-friendly flame-retardant finish for cotton fabric using Banana Pseudostem saps and phytic acid
Authors: Islam Tarikul , Rasel Sm Mahiuddin , Roy Raktim , Hossen Md. Tanvir , Hossain Shahin , Rahman Mahbubur , Kabir Mohashin , Repon Md. Reazuddin , Maurya Sandeep Kumar , Jalil M. Abdul 
Published: November 2024

Abstract

This study investigated the potential of eco-friendly substances, namely Banana PseudostemSap (BPS) and phytic acid (PA), to enhance the flame-retardant properties of cotton fabric. The process involved applying various concentrations of BPS to pre-mordanted bleached cotton fabric. The treated fabrics were then analyzed for vertical flammability and LOI (Limiting Oxygen Index). Notably, fabrics treated with a 400% concentration of BPS showed exceptional flame-retardant properties. They achieved a Limiting Oxygen Index (LOI) of 27.5, while the control fabric had an LOI of 18.0, with a significant increase of 1.5 times. In the vertical flammability test, the BPS-treated fabric burned briefly and self-extinguished. In contrast, the control fabric exhibited sustained burning, with the treated fabric burning nearly 5 times slower, propagating at 30 mm/min. SEM results revealed the deposition of flame-retardant finishes on the fabric surfaces. FTIR and EDX were employed to identify chemical entities in the fabric. Importantly, post-treatment evaluation of tensile strength and breaking elongation revealed no significant changes in the cotton fabrics, reassuring the quality of the fabric. These findings underscore the potential utility of BPS and phytic acid as effective flame-retardant agents for cotton fabrics, offering promising avenues for sustainable textile manufacturing.
Discordance Between Clinical and Pathologic Findings on Post-Induction Kidney Biopsy in Pediatric Patients with Proliferative Lupus Nephritis
Authors: Raschke Robin , Crane Clarkson , Sheets Robert , Nourbakhsh Noureddin , Benador Nadine , Ingulli Elizabeth , Shayan Katayoon , Yorgin Peter , Carter Caitlin 
Published: November 2024

Abstract

Introduction Systemic lupus erythematosus (SLE) diagnosed during childhood is associated with higher rates of mortality and lupus nephritis compared to adult-onset SLE. Lupus nephritis (LN) itself is independently associated with higher mortality and proliferative lupus nephritis (ISN/RPS Class III and Class IV) is associated with an increased risk of progression to end stage kidney disease. Once a diagnosis of LN has been confirmed on initial kidney biopsy, the utility and optimal timing for subsequent biopsies in LN has not been established. There is known discordance between the clinical parameters used to diagnose LN and the histopathologic classification. Often clinicians are uncertain about the impact of titration in immunosuppression when relying solely on clinical parameters. Purpose To explore the utility of a subsequent kidney biopsy in guiding treatment of LN after induction therapy and to determine if the standard clinical signs of kidney disease can be used to target repeat kidney biopsy to the patients most likely to benefit from the information obtained.
Methods This study was a single center retrospective cohort study of SLE patients who underwent kidney biopsy for lupus nephritis at Rady Children’s Hospital, San Diego (RCHSD). Subjects were stratified based on their Childhood Arthritis and Rheumatology Research Alliance (CARRA) renal response into complete renal response (CRR) and incomplete renal response (IRR) groups at the time of the second biopsy. Demographic data were not distributed normally, therefore a non-parametric Wilcoxon paired t-test was used for comparison of continuous variables. The Chi squared test was used for categorical data between remission groups. Single predictor and multiple predictor logistic regression models were utilized to assess the relationship between clinical factors and histologic findings on second biopsy.
Results At the time of second biopsy, both groups had lower SLEDAI scores compared to first biopsy, and CRR group had significantly lower SLEDAI scores compared to IRR group. Of the other clinical markers assessed at time of second biopsy, including age, dsDNA, serum C3, change in C3 between biopsies, and serum C4, none were found to be significantly different between the two groups. Findings on second biopsy influenced immunosuppressive therapy decisions in both CRR and IRR groups.
Conclusions Currently available clinical markers of disease remission in lupus nephritis after induction therapy are insufficient to identify children with ongoing evidence of persistent proliferative nephritis. Follow up kidney biopsy is low risk and can be used to guide therapy in children with SLE and nephritis.
Efficient Classification and Wireless Communication for Electrooculography Signals Based on Internet of Things and Machine Learning (IoT-ML) Algorithms
Authors: El-Gindy Saly Abd-Elateif , El-Samie Fathi E. Abd 
Published: November 2024

Abstract

In this paper, we investigate an Internet of Things (IoT)-based platform utilizing Electrooculography (EOG) to assist, control, and monitor a smart home environment in real-time for patients with motor disabilities. Users can interact with the intelligent environment through a Graphical User Interface (GUI) that offers predefined options for controlling doors, windows, lights, air conditioning, temperature, and TV functions. The proposed approach is based mainly on utilization of two transforms namely Stockwell (S-transform) and Wavelet transforms respectively for detection of abrupt changes EOG signals. Several signal statistical features including maximum, minimum, mean, median, Root Mean Square (RMS), standard deviation, Zero Crossing Rate (ZCR), Mean Curve length (MCL), kurtosis and skewness of the processed signals are utilized to characterize the EOG signals which have been applied for the classification stage to detect one of eye movement directions including: up, down, right, left, no movement or blinking. Two different wavelet families including Daubechies (db4) and Symlets (Sym4) wavelets are considered. The proposed approach was conducted on a data set which acquired by a custom device to measure and record EOG signals. Then, the decomposed horizontal and vertical signals are grouped into a vector to be the inserted as an input to the classification models. Finally, the data are classified using three types of Machine Learning (ML) algorithms including Support Vector Machine (SVM), Kernel Neural Network (KNN) and Ensemble Tree (ET) classifiers. The result of the proposed method outperforms the results of the other previous published methods when using different evaluation metrics. A high average accuracy of 97.7% is achieved from SVM using db4 which demonstrate the superior performance of the proposed method
Antiviral siRNA Delivered Using Attenuated, Anthrax Toxin Protects Cells from the Cytopathic Effects of Zika Virus
Authors: Feron Benedita K. L. , Gomez Timothy , Youens Natalie C. , Mahmoud Nourhan A. M. , Abdelrahman Hadeer K. S. , Bugert Joachim J. , Richardson Simon C. W. 
Published: November 2024

Abstract

Curative drugs are needed for the treatment of viral infections. Small interfering (si)RNA offer such a prospect but require the development of safe, effective and non-hepatotropic subcellular delivery systems. Here, 5 candidate siRNA molecules targeting defined sequences within the Zika virus (ZIKV) genome were assayed for their ability to reduce ZIKV induced cytopathic effects in vitro. The protection of Huh7 cells from ZIKV cytopathic effects was recorded after electroporation and the siRNA Feron-Zv2, resulted in 122.7 ± 5.3% cell viability (n = 3 ± standard error of the mean (SEM), 100nM siRNA) after exposure to ZIKV relative to a virus treated control (35.2 ± 7.1% cell viability (n = 3 ± SEM)). Protection of BHK cells was recorded after transfection with an attenuated anthrax toxin containing an RNA binding domain. Treatment with Feron-Zv4, resulted in 75.1 ± 2.9% cell viability (n = 3 ± SEM, 25nM siRNA) after exposure to ZIKV. This protection was mirrored by a system containing octameric PA where a maximum of 86.2 ± 4.4% cell viability was reported (n = 3 ± SEM, 75nM siRNA)) after treatment with Feron-Zv2. Scrambled siRNA afforded no measurable protection. Here we report for the first time that siRNA delivered by either attenuated anthrax toxin or octamer forming ATx can protect mammalian cells from ZIKV cytopathic effects.
In-Vitro Study of Co-Electrospun PCL/Gelatin/Chitosan Scaffolds Enhanced with Carbon Nanotube for Cartilage Regeneration
Authors: Irani Mohammad , Nasirtabrizi Mohammad Hossein , Ezzatzadeh Elham , Sadeghianmaryan Ali 
Published: November 2024

Abstract

Cartilage tissue regeneration is a significant challenge in orthopedics, especially with the aging population. This study introduces a novel co-electrospun scaffold composed of polycaprolactone (PCL), gelatin, chitosan, and carbon nanotubes (CNT) for cartilage tissue engineering. The scaffold was doped with varying CNT concentrations to optimize its properties. In-vitro tests were performed to assess scaffold morphology, chemical composition, water-scaffold interaction, mechanical properties, and cell viability. Scaffolds with 0.1 and 0.2% CNT (0.2 CNT) showed homogenous morphology, while the 0.4% CNT resulted in non-homogeneity. The 0.2 CNT scaffold demonstrated hydrophilicity (64.5° contact angle), adequate swelling, favorable biodegradation, and suitable mechanical properties for cartilage regeneration. It supported cell viability, and no dead cells were detected in the live/dead test. Additionally, it showed 95.5 ± 1.5% cell viability after seven days in MTT assay. Therefore, the 0.2 CNT scaffold is a promising candidate for cartilage tissue engineering and is proposed for further in-vivo investigation.
Mammalian diversity in the relict semi-natural forest in the campus of Jimma Institute of Technology (JIT), southwester
Authors: Serbesa Debere Hailu , Gadisa Tsegaye , Natea Gadisa , Habitamu Tadese 
Published: November 2024

Abstract

Mammals in small fragmented habitats, particularly those in or adjacent to cities and towns could serve as population stock source with significant economic, ecological, social, cultural and conservation values. This study was conducted to assess the diversity, habitat preference and relative abundances of medium and large sized mammals in the fragmented semi-natural forest and the surrounding wetland and farmland habitats in the Jimma Institute of Technology (JIT) campus, Jimma city, from December 2018 to August, 2019. Three habitat types (forest, wetland and farmland) were identified. Line transect, sensor camera traps and indirect methods were used to collect data from all the three habitat types. A total of 15 species of medium and large sized mammals from six orders and 10 families were recorded from the area. Order Carnivora was represented by five species, Artiodatayla by four, primates by three species, while, orders Lagomorpha, Hyracoidea and Rodentia were represented by a single species each. Comparatively, species diversity was high in the farmland during the wet season (H’ = 2.52) and the least diversity was from the wetland (H’ = 1.4) during the same season. While Chlorocebus aethiopis was the most abundant (26.21%) species in all habitats, Canis aures was the least (1.4%). Despite the dominating human disturbance the small fragmented natural forest and its surrounding wetland and farmland in JIT campus still hosted diverse wildlife species signifying the value of such habitats in cities. Therefore, the authorities of JIT campus are recommended to give special attention and protect the area from any future development activities.
Retinal Bionic Super-Resolution Reconstruction Network: Enhancing Image Details through Hierarchical Feature Fusion
Authors: Jia Xiaofen , Liu Junjun , Zhao Baiting , Liang Zhenhuan 
Published: November 2024

Abstract

Utilizing Convolutional Neural Networks (CNNs) for image super-resolution reconstruction has emerged as a pivotal technology to enhance image quality. However, existing deep learning models often lack fine details, resulting in unnaturally appearing reconstructed images. Drawing inspiration from the retinal information processing mechanism, we propose a novel super-resolution reconstruction method named RBSRNet. This method employs a lateral inhibition module (LIM) to mimic the regulatory mechanism of horizontal cells, enabling local inhibition and enhancement of shallow extracted features, thereby efficiently extracting high-frequency information. Furthermore, by simulating the information integration mechanism of bipolar cells, we design an enhanced hierarchical feature fusion block (EHFFB) and a hierarchical fusion network (HFN). These components facilitate effective fusion and enhancement of features at different levels, improving the model's representational capacity. Experimental results on four datasets demonstrate that RBSRNet significantly outperforms advanced methods, particularly in texture detail recovery. Specifically, RBSRNet achieves an average PSNR that is 0.26dB higher than IRN on the Urban100 dataset, with reconstructed images exhibiting superior visual effects and richer texture details. The source code is available at https://github.com/Ljjsisr/RBSRNet.
A Robust Image Forgery Detection and Localization Approach based on Context-Aware Attention Pooling and Convolutional Block Attention Module for Improved Detection Performance
Authors: Ghosh Debolina , Naskar Ruchira , Chakraborty Bidesh 
Published: November 2024

Abstract

Image manipulation technology has emerged and developed quickly, posing a threat to many facets of our society. Consequently, the identification of picture alteration has become more crucial. Though considerable progress has been made, past approaches to forgery detection did not account for the differences in the size of the tampered areas in each fake image. In this research, we argue that the primary cause of the low precision is the network’s incapacity to handle tampering regions of different sizes. We suggest Context-Aware Attentional pooling-based U-Net structures because of their simplicity in implementation, ease of integration , emphasis on feature relevance, scalability, noise reduction, and computing efficiency. It extends the capabilities of the U-Net by incorporating residual propagation and feedback, an attention gate, and Context-aware Attentional pooling (CAP) with Convolutional Block Attention Module (CBAM). The concept of channel mixing is larger in CBAM, which may indicate a more integrated method of managing spatial information and channel dependencies. In order to maximise 1 feature extraction, multiscale context understanding, and ultimately more accurate and dependable forensic analysis, spatial attention, channel attention, and Context-Aware Attentional Pooling (CAP) are integrated into image forensics. This model’s inclusion of Context-Aware Attentional Pooling (CAP) and Channel Attention (CA) improves its robustness against noise and compression, and improves detection accuracy and localisation with both global and local context, making it perform better than other state-of-the-art models. This combination is a potent method in the field of image forensics since it is very good at identifying subtle and intricate image manipulation.
Multiscale Modelling of European Beech Decline: The Role of Long-Term Climate Deviations and Local Environmental Factors
Authors: Lemaire Jean , Vennetier Michel , Prévosto Bernard , Cailleret Maxime 
Published: November 2024

Abstract

Fagus sylvatica L. is a main forest tree species in Europe but has been subjected to massive decline events over the last decades. This phenomenon has been mainly attributed to the increase in drought frequency and intensity, but it is unclear how the local specificities in stand structure, climatic, soil and topographic conditions interact, and if statistical models are able to capture the high spatial and temporal variability in tree decline. To fulfil this objective, we measured 5380 Fagus sylvatica trees from 308 plots distributed in four regions of France with contrasting environmental conditions, and designed models predicting decline at both regional and national scales. These models aimed at assessing the percentage of stems by plot with at least 50% crown biomass loss based on 229 dendrometric, topographic, soil and climatic variables. The climatic factors explained most of the variability in stand decline, especially the long-term deviations from the 30-years mean in maximal temperature and in hydric deficit. Regional models were the most efficient in predicting beech decline in their calibration areas (Q² varied from 0.26 to 0.42) as they better consider the local environmental factors. They were less effective in the other regions, and the national model was an acceptable compromise on a larger scale. These statistical models provide valuable insights for forest managers and could be improved through a more detailed temporal stand monitoring to control the effects of management and decline dynamics.
Addressing Barriers to Migrant Participation in Research
Authors: Price Kathryn , Lenart Andrew , Taknint Joelle T. , Gellatly Resham , Alshabani Nuha 
Published: November 2024

Abstract

This “Notes from the Field” article discusses implementation strategies used to increase equity and access to research study participation among migrants. Common barriers to research participation for this population (e.g. language access, informed consent) limit the perspective of migrants within immigrant and refugee health scholarship, reducing the applicability of findings to diverse populations. We aimed to characterize barriers and solutions to migrants’ participation in research. Study participants included asylum-seeking patients at the largest safety net hospital in New England. Two researchers analyzed field notes, reflexivity notes, and standard operating procedure adaptations. Four themes emerged including challenges of conducting qualitative interviews with interpreters, technology literacy, reimbursement woes, and role of the researcher. The goal of the study was to uplift the experience of migrant research participants, describe challenges in the research process, and present recommendations to migrant participation in research. We provide lessons learned for immigrant and refugee health scholars.
Keywords: qualitative research, research methods, migrants, minoritized populations, and research ethics
Evaluation of short-middle Earth rotation parameter forecasting: multi-scales effects and multi-data solutions
Authors: Shi Kunpeng , Ding H.D , Chen X.C , Hu X.H , Jiang W.J , Sun H.S 
Published: November 2024

Abstract

Predicting Earth Rotation Parameters (ERP) is crucial for the precise positioning and navigation both on Earth’s surface and space. As complex variations of the Earth's rotation, ranging from high-frequency trembles, inter-annual to -decals oscillations, however, high-precision ERP predictions are rather challenging. For the accurate predictions of these stable signals, we develop an simple, adaptive yet high-precision HSA + AR model improved in muti-scales frequencies: (1) Hankel-z quarter-parameters {A, α, f, θ} (amplitude, damping, frequency, phase) harmonic fit of Chandler, Annual/Semi-annual wobbles over the past 10-years; (2) Multiple-peaks low-frequency fit over the 1962-now; both of step (1)-(2) termed as HSA method and (3) AR modelling of the irregular residual variations. In the secular stability test, our results derived from final IERS C04 ERP solutions can largely reduce the forecast errors beyond 60% in each ERP components (within 1–90 days), compared the LS + AR methods. Considering the superior short-term calibration by ERP high-frequency terms and surface fluid excitation, we determine the rapid GNSS ERP (HSA (rapid) + AR, low latency) and GFZ EAM solutions (HSA (rapid) + AR (EAM)) as predictive ERP basis. In the real experiments, HSA (rapid) + AR (EAM) in short-term (1–20 days) and HSA (rapid) + AR in middle-term (20–90 days) predictions significantly surpass the benchmark from the official IERS Bulletin A predictions and mostly studies in the same predictive epochs. Both rapid ERP and EAM solutions are featured with a shorter latency of 1–2 days. Therefore, our strategy further advanced the real-time ERP predictions greatly compared to the existing predictive solutions, which support various scientific and operational applications in future.
Blockade of TREM-1 alleviates alveolar epithelial cell senescence through Nrf2-mediated antioxidant pathways in pulmonary fibrosis
Authors: Xiong Jian-Bing , Zhang Chen-Yu , Jin Ling , Yang Nan-Shi-Yu , Sha Han-Xi , Liu Yu-Biao , Duan Jia-Xi , Guan Cha-Xiang , Zhou Yong , Su Feng , Zhong Wen-Jing 
Published: November 2024

Abstract

Our previous study showed that blocking triggering receptors expressed on myeloid cell-1 (TREM-1) attenuate bleomycin (BLM)-induced pulmonary fibrosis (PF) in mice. However, its underlying mechanism remains unclear. Here, we found that blockade of TREM-1 during the fibrotic phase attenuated BLM-induced PF in mice, with less expression of the senescence-relative protein, including p16, p21, p53, and γ-H2AX in the lung tissue. Moreover, TREM-1 blockade during the fibrosis stage restored the anti-oxidant levels by increasing the percentage of Nrf2- and HO-1-positive cells in PF mice. Notably, TREM-1 was highly expressed in SFTPC-positive alveolar epithelial cells (AECs) in PF mice. In vitro, blocking TREM-1 activated Nrf2 anti-oxidant signaling, thereby decreasing intracellular ROS and diminishing BLM-induced senescence of AECs. Furthermore, inhibition of the Nrf2/HO-1 partially counteracted the anti-senescence effect of blocking TREM-1 in BLM treated-AECs. In conclusion, our findings elucidate new insights into the molecular mechanisms associated with TREM-1 and AEC senescence in the pathogenesis of PF.