bluuebunny/crossref_metadata_2025_split huggingface dataset:
LncRNA KCNQ1OT1 regulates apoptosis and ECM degradation of NP cells via miR-199a-5p/ACTG1 axis in IDD models
Authors: Ma Yuan , Cao Sheng , Yang Hou-zhi , Li Yuqiao , Zhao Hui , Ye Xiang-yang , Li Guang , Liu Yang , Tang Qiong , Sun Tianwei 
Published: September 2022

Abstract
Background: It has been reported that lncRNA KCNQ1 opposite strand/antisense transcript 1 (KCNQ1OT1) involved in various disease progression. However, the role of KCNQ1OT1 in intervertebral disc degeneration (IDD) and its underlying molecular mechanism remains unclear.
Objective: To explore the role of KCNQ1OT1 in IDD progression and its underlying molecular mechanism.
Methods: IL-1β (10 ng/mL) treated NP cells for 24 h to induce IDD models in vitro. The interaction among KCNQ1OT1, miR-199a-5p and ACTG1 was predicted by Starbase bioinformatics and verified by dual-luciferase reporter gene assay and RIP assay. CCK-8 assay was performed to assess cell viability, cell apoptosis was detected by flow cytometry, Western blot and qRT-PCR were performed to examine the level of genes and proteins.
Results: Our results illustrated that overexpression of KCNQ1OT1 inhibited NP cells apoptosis and ECM degradation in IDD models. KCNQ1OT1 bound to miR-199a-5p and deregulated miR-199a-5p expression, and KCNQ1OT1 regulated NP cells apoptosis and ECM degradation via miR-199a-5p in IDD models. Furthermore, miR-199a-5p knockdown inhibited NP cells apoptosis and ECM degradation via targeting ACTG1, and the decrease of NP cells apoptosis and ECM degradation induced by miR-199a-5p knockdown was reversed by inhibiting ACTG1 in IDD models.
Conclusion: KCNQ1OT1 overexpression inhibited NP cells apoptosis and ECM degradation via miR-199a-5p/ACTG1 axis in IDD models. Our findings illustrated the specific molecular mechanism of KCNQ1OT1 regulating IDD progression.
In-vitro inhibitory impacts of fulvic acid-coated iron oxide nanoparticles on the amyloid fibril aggregations
Authors: Jomehpour Dalia , Sheikhlary Sara , Heydari Esmaeil , Ara Mohammad Hossein Majles 
Published: September 2022

Abstract
Alzheimer’s Disease is a multi-factor malady, the main hallmarks of which are, extracellular amyloid-beta and intracellular tau protein aggregations, leading to a pathological cascade of events and ultimately neural death. With this in mind, most of the studies have been concentrated on eliminating the amyloid and tau aggregations. Fulvic acid is one of the polyphenolic compounds which exhibits strong anti-inflammation and anti-amyloidogenic activity. On the other hand, iron oxide nanoparticles exhibit anti-amyloid activity on their own, therefore, this study investigates the interactions between fulvic acid-coated iron oxide nanoparticles and the commonly used in-vitro model, lysozyme from chicken egg white, that forms the amyloid aggregation under acidic pH and appropriate heat. The average size of nanoparticles was 10.7±2.7nm. FESEM, XRD, and FTIR characterization confirmed that fulvic acid was coated onto the surface of the nanoparticles. The inhibitory effects of the fulvic acid coated iron oxide nanoparticles were verified by Thioflavin T assay, circular dichroism (CD), and FESEM analysis. Furthermore, the toxicity of the nanoparticles on the neuroblastoma SH-SY5Y human cell line was assessed through MTT assay. Our results indicate that fulvic acid-coated iron oxide nanoparticles can efficiently inhibit formation of amyloid aggregations while exhibiting no in-vitro toxicity. This data shed light on the anti-amyloid activity of combination of fulvic acid and iron oxide nanoparticles; paving the way for future drug development for treating Alzheimer’s Disease.
21 Multi-level Inverters based on Cascaded H-Bridge Converter using Nearest Level Modulation
Authors: Raja R. , Sudha V. , Kalaivani C. 
Published: September 2022

Abstract
In recent years, due to the increasing demand for electricity from grid users and the emergence of high-power energy-consuming industries, the energy demand from society for grids has significantly increased, which has led to an increase in the global power generation from traditional energy sources. Therefore, the penetration of renewable energy (wind power, photovoltaic power) resources into the grid has increased significantly, making the grid unstable due to fluctuations in its output. In order to overcome grid fluctuations, this research proposes 21 multi-level inverters (MLI) based on cascaded H-bridge inverters to solve the problems mentioned above in large-scale energy storage systems. This article focuses on the number of components in a variety of multi-level converters with different topologies (neutral point clamped inverter (NPC), flying capacitor inverter (FC), cascaded H-bridge multi-level converter), the control program and the complexity of the hardware circuit, the power state and the system loss are studied and compared, and the inverter with the cascaded H-bridge as the main topology is established and its characteristics are studied. This paper depicts the three different modulation techniques, namely phase-disposition sinusoidal pulse width modulation (PD-SPWM), carrier phase shift pulse width modulation (CPS-SPWM), and nearest level modulation (NLM) applied to modular Multiple Stage (MMCs). It further details the implementation and analysis of each modulation technique. The performance of 5,7,9,11,13,15,17,19 and 21 level MMC with three aforementioned modulation techniques is evaluated and compared in terms of output voltage, current and harmonic distortion. The simulation is carried out using Matlab/Simulink software. The simulation results are presented and validated.
Patterns of medication management and associated medical and clinical features among home-dwelling older adults: a cross-sectional study in central Portugal
Authors: Dixe Maria dos Anjos , Pinho Joana , Pereira Filipa , Verloo Henk , Meyer-Massetti Carla , Pereira Sonia Gonçalves 
Published: September 2022

Abstract
Background: Ageing is frequently associated with multimorbidity and polypharmacy. Frailty and cognitive impairment are other important contributors to the multidimensional aspects affecting older adults’ health status. The present study aimed to explore the adequacy of medication management patterns among home-dwelling older adults in central Portugal by considering their medical conditions, frailty and cognitive status. Reducing numbers of adverse events through effective medication management increases the chances of older adults remaining in their homes for longer periods. Providing patients and caregivers with an overview of potential improvements in this area is very relevant for Portugal’s ageing population.
Methods: Within the scope of this cross-sectional observational study, older adults (≥ 65 years) living in the community were assessed via face-to-face interviews. Frailty and cognitive status were assessed using validated tools. Medication management, clinical and sociodemographic variables were assessed by questioning patients or caregivers directly. Descriptive statistics, associations and odds ratios were calculated.
Results: A total of 112 older adults were assessed. Mean participant age was 76.6 ± 7.1 years (median = 76), 53.6% were women, and 40.2% lived alone. More than half were categorised as frail (58.9%), and 19.6% presented moderate cognitive impairment. About 91.1% were multimorbid (3.5 ± 1.5 chronic diseases), and 60.7% were polymedicated (≥ 5 medications per day), with most medications being prescribed by a family physician. No associations were found between polymedication and medication self-management, using over-the-counter medications, living alone, poor understanding of pharmacological therapy and/or pathology, or having more than one prescriber. Self-management was associated with age, the number of medications, frailty and cognitive status. Binary regressions showed that cognitive impairment had statistically dependent correlations with external medication management, a poor understanding of pharmacological therapy and/or pathology, having one prescriber and using over-the-counter medications.
Conclusion: Most of the older adult participants were multimorbid and many were frail, but only two-thirds were polymedicated, potentially suggesting cautious prescription approaches, but further studies are required. Most participants managed their own medication, and only cognitive impairment affected this ability, among a multitude of features. Measures to prevent medication-related problems in home-dwelling older adults are to be recommended.
Serum exosome-mediated expression of ITGAX in hippocampus as a novel mechanism of blood-brain barrier dysfunction in epilepsy
Authors: wei nian , Wang Jing , Tai Zhenzhen , Yu Changyin , Xu Zucai 
Published: September 2022

Abstract
Background
Epilepsy is one of the most common chronic neurological diseases, of which up to one third of patients have drug-resistant epilepsy. Recently, there is increasing evidence that exosomes play a crucial role in the pathogenesis of neurological diseases. Based on the previous results of serum exosome proteomics, this study aims to explore the pathogenesis of epilepsy from the perspective of exosomes.
Methods
The protein ITGAX was identified in previous proteomic studies. Firstly, ITGAX adeno-associated virus was injected through tail vein and exosome inhibitor was intraperitoneally injected to intervene the content of ITGAX in peripheral circulation and serum exosomes respectively, and then the expression of ITGAX in hippocampus was detected after intervention, so as to confirm the relationship between exosomes and the pathogenesis of epilepsy from the perspective of protein. Then, the effects of ITGAX expression changes on seizure latency and blood-brain barrier were observed by ethology and the detection of the blood-brain barrier-related molecules by Western blotting and ELISA.
Results
The results showed that, for epilepsy model, the expression of ITGAX in serum exosomes and hippocampus were both up-regulated. After reducing the expression of ITGAX in peripheral circulation and exosomes in serum, the level of ITGAX in hippocampus also decreased correspondingly. Behavioral results showed that down-regulation of ITGAX expression in hippocampus could prolong the latency of seizures and ameliorate the damage of blood-brain barrier.
Conclusions
This study is the first to demonstrate that exosomes are involved in the pathogenesis of epilepsy from the perspective of the transport of exosomes from the peripheral circulation to the central nervous system, and it indicates that ITGAX is highly expressed in the hippocampus from peripheral serum into the central nervous system mediated by exosomes, and its involvement in epileptic seizure mechanism may be related to changes in the permeability of the blood-brain barrier.
Dissection of a Cell Atlas of Developing Somatic Embryos in Cotton by Single-cell RNA-sequencing and Spatial Transcriptomic and Metabolomic Analyses
Authors: Ge Xiaoyang , Yu Xiaole , Liu Zhixin , Yuan Jiachen , Qin Aizhi , Wang Ye , Chen Yanli , Qin Wenqiang , Liu Yumeng , Liu Xingxing , Zhou Yaping , Wang Peng , Yang Jincheng , Liu Hao , Zhao Zihao , Hu Mengke , Zhang Yixin , Sun Susu , Herrera-Estrella Luis , Tran Lam-Son Phan , Sun Xuwu , Li Fuguang 
Published: September 2022

Abstract

Somatic embryogenesis is a major pathway for the regeneration of cotton in tissue culture, and a major technique used for cotton breeding and improvement. The signaling pathway regulating the process of somatic embryogenesis in cotton are extremely complex and still poorly characterized. Little is known about the mechanisms regulating the changes that occur in gene expression and metabolites during somatic embryogenesis at a single-cell resolution. Here, we investigated the spatial and single-cell expression profiles of key genes and metabolic patterns of key metabolites by integrated single-cell RNA-sequencing, spatial transcriptomics, and spatial metabolomics. To evaluate the results of the above analyses, we characterized the potential roles of two representative marker genes AATP1 and DOX2 in the regulation of somatic embryo development. A publicly accessible web-based resource database (http://cottonsomaticembryo.cricaas.com.cn) was generated to facilitate future studies designed to analyze the expression patterns of marker genes at specific developmental stages.
The Non-fragile H∞ State Observer Design forthe Uncertain Time-Delay Systems
Authors: Ma Chao , Wang Tianbo , Ding Yang 
Published: September 2022

Abstract
This paper studies the non-fragile H∞ state observer design problem for a classof uncertain time delay systems by using the Lyapunov stability theory and thelinear matrix inequality technique. Several results which ensure these systems tobe asymptotic stability are obtained. The obtained results are given by the linearmatrix inequality and can be solved easily. Moreover, the gain matrix of theobserver can vary appropriately. Finally, a numerical simulation shows that theprovided results are effectiveness.
Federated Learning Design and FunctionalModels: Survey
Authors: A John , Utomo Sapdo , Rouniyar Adarsh , Hsu Hsiu-Chu , Hsiung Pao-Ann 
Published: September 2022

Abstract

Federated learning is a multiple device collaboration setup designed tosolve machine learning problems under framework for aggregation andknowledge transfer in distributed local data. This distributed modelensures the privacy of data at each local node. Owing to its relevance,there has been extensive research activities and outcomes in federatedlearning with expanded applicability to different areas by the researchcommunity. As such, there is a vast research archive made available by thecommunity with research work and articles related to the various aspectsof federated learning such as applications, challenges, privacy, function-alities, and design. With respect to the function and design of federatedlearning, client selection, aggregation, knowledge transfer, managementof distributed data (Non-IID), Incentive of data and communication costare of paramount importance. Any effective design of federated learningrequires these aspects to be well considered.There are numerous surveyarticles found among the available literature that focus on its applica-tion and challenges, opportunities, data privacy and protection, as wellas on federated learning on internet of things, federated learning on edgecomputing, etc.1
In this paper, a review of the available literature on the various ele-ments of design and functionalities in federated learning has been carriedout with an aim to lay emphasis on the important challenges andresearch opportunities. More specifically, this work has endeavored tounderstand and summarize the various functional methods available,along with their techniques and goals. Additionally, it has strived toget a bird’s eye view of how various functions and designs of feder-ated learning have been used in applications, and how it has helpeduncover challenges and promising research directions for the future.
Biomarkers of Amyotrophic lateral sclerosis
Authors: Chen Xiaowen , Li Junrong , Lv Yingying , Zhang Wei , Xu xiujian , Kong Delian 
Published: September 2022

Abstract
Objective The present study was to investigate the potential of uric acid, for predicating neurological function and progression rate of amyotrophic lateral sclerosis.
Methods All enrolled ALS patients were given corresponding serological tests at the initial diagnosis. The Revised ALS Functional Rating Scale (ALSFRS-R) were evaluated. The detected indexes in blood tests wasuric acid. Data analysis was performed by SPSS22.0 statistical software.
Results There were significant differences in uric acid, between the two groups (P<0.05). The levels of uric acid of ALS group were lower than those of the control group, 2.
Conclusion 1. There were significant metabolic abnormalities in ALS patients. 2. Uric acid could be used as reliable indicators to evaluate the ALSFRS-R and DPR of ALS patients.
Deep Q-Learning framework based Solar Energy Generation Prediction
Authors: Bera Souvik , Gupta Gauri Shanker , KUMAR DEEPAK , Kumar S. Shiva , Gupta Karunesh Kumar 
Published: September 2022

Abstract
In the recent years, the power system market has seen a huge shift towards the utilisation of Renewable energy sources (RES) as candidates of power generation since they proved to be a great alternative of conventional sources due to its low carbon footprints and less dependency over fossil fuels, thereby increasing the penetration of RES in microgrids. RES sources like Wind, Tidal, Hydro, Solar etc. are widely available today, among which Solar is the most popular source of energy due to its cheap running cost and easy installation. However, Solar faces complications such as intermittency which is a very big drawback to its applicability and reliability thus requiring additional strategies to increase its resiliency. A short term forecasting of solar generation might be a great solution to observe the intermittency and predict the future generation based on various factors. In this research work a Deep Q-learning framework was proposed to predict the Solar Generation and provide predictive results for special months and days like Spring equinox, Summer Solstice, Autumn Equinox and Winter Solstice. The Deep Q-learning (DQNN) framework is an amalgamation of Deep Learning networks and Q-learning technique that exploits the properties of Deep Learning networks and Q-learning technique to map the state-Q-value pair and perform the prediction process. The simulations of DQN network was performed in an open-source platform known as Keras and the prediction results were compared both in simulated and experimental datasets with other well known Deep learning networks such as CNN, LSTM, GRU and CNN-LSTM.
Learning Approaches Among Medical Undergraduates and Pre-intern Doctors of a Selected University in Sri Lanka
Authors: Edirisinghe Sajith , Silva Dulmini , Devmini Movini Thisara , Pathmaperuma Shanaka , Liyanage Indunil , Niluka Malith , Madushika Kasuni , Deegodagamage Sandeepani , Wijesundara Chanuka , Dissanayake Harsha , Yasawardene Surangi 
Published: September 2022

Abstract
Background: Medical education is constantly evolving to suit the changes in the field. It is a challenge to acquire the necessary knowledge, attitudes and skills within limited time period in order to become a proficient doctor. This study aims to determine and compare the learning approaches (deep, strategic, superficial) used by medical undergraduates and pre-intern doctors.
Methods: Learning approaches of 138 pre-clinical medical undergraduates and pre-intern doctors of the University of Sri Jayewardenepura were assessed using the Approaches and Study Skills Inventory for Students (ASSIST) questionnaire. Data were analyzed using SPSS v-16 and Brown-Forsythe test.
Results: The strategic approach was identified as the predominant learning approach among 138 participants. One hundred and eight (108) participants (78.3%) used this method while 21 (15.2%) and 9 (6.5%) participants used the deep approach and the surface apathetic approach, respectively. Majority of both undergraduates [77.6% (83/107)] and pre-interns [80.6% (25/31)] used the strategic approach. This finding was also consistent between the 2 genders with a majority of males [69.6% (32/46)] as well as females [82.6% (76/92)] who follow the strategic approach. No significant difference in learning approaches was found to be present between undergraduate and pre-intern groups.
Conclusions: This study demonstrates that a majority of medical undergraduates and pre-intern doctors prefer the strategic learning approach. This implies that the medical curriculum has not promoted the deep learning approach over the five-year period of studentship and this needs to be addressed in a subsequent curriculum change in order to promote a deep learning approach.
Network Pharmacology Integrated Molecular Docking to Reveal the Autism and
Mechanism of Baohewan Heshiwei Wen Dan Tang
Authors: Chen Yongjian , Ma Kang , Si Hongzong , Duan Yunbo , Zhai Honglin 
Published: September 2022

Background:
In recent years, the prevalence and mortality of autism spectrum disorder (ASD) have
been increasing. The clinical features are different with different cases, so the treatment ways are different for
each one.

Objective:
Baohewan Heshiwei Wen Dan Tang (BHWDT) has been recommended for treating autistic
spectrum disorder. To investigate the mechanism of action and how the compounds interact with ASD targets,
network pharmacology and molecular docking methods were used in this study.

Methods:
Traditional Chinese Medicine Systems Pharmacology (TCMSP) was used to screen the active components
according to index of oral bio-activity and drug-likeness. Then, TCMSP and Swiss Target Prediction
databases were used to screen potential target genes of active components. The related target genes of ASD
were obtained from the Gene Cards database. Matescape database was utilized to get gene ontology (GO) function
enrichment and Kyoto Encyclopedia of Genes and Genomes pathway annotation of gene targets. Composition-
target-pathway (C-T-P) and a protein-protein interaction (PPI) networks were built with Cytoscape 3.8.2
software.

Results:
The interaction of the main active components of BHWDT was verified by molecular docking.
The key targets of MAPK1, IL6, CXCL8 and TP53 of BHWDT were obtained. The key active components
Quercetin, Kaempferol and Iuteolin of BHWDT could bind with MAPK1, IL6, CXCL8 and TP53 of BHWDT,
respectively.

Conclusion:
BHWDT can be highly effective for treating ASD and this study can help us to understand multiple
targets and multiple pathways mechanism.
Study on Multi-Target Synergistic Treatment of Alzheimer’s Disease
Based on Metal Chelators
Authors: Shen Rui , Kou Xiaodi , Yang Aihong , Wu Jianhua , Chen Yuhong 
Published: September 2022

Abstract:
Alzheimer's disease (AD) has become the fourth leading cause of death in the world. Due to its complex pathogenesis, there is still a lack of effective drug treatments. Studies have found that the metal dyshomeostasis is closely related to other pathogeneses of AD such as oxidative stress, β-amyloid protein deposits, etc. Therefore, it becomes an important target to find the appropriate metal chelating agents to regulate the metal homeostasis. At the same time, because of the complex pathogenesis, single target drugs cannot achieve good effects. Therefore, current studies are mainly focused on exploring multi-target therapy for AD. In this work, the multi-target studies based on metal chelators and other targets with synergistic anti-AD activities were reviewed. The structural characteristics of different chelating agents were summarized and the structure-activity relationship was analyzed, which provided some valuable clues for the subsequent development of anti-AD multi-target drugs based on metal chelating agents.