syedzayyan/paper_mill_benchmark huggingface dataset:
Rhodiola Rosea Extract Counteracts Stress in an Adaptogenic Response Curve Manner via Elimination of ROS and Induction of Neurite Outgrowth

Sustained stress with the overproduction of corticosteroids has been shown to increase reactive oxygen species (ros) leading to an oxidative stress state.Mitochondria are the main generators of ros and are directly and detrimentally affected by their overproduction.Neurons depend almost solely on atp produced by mitochondria in order to satisfy their energy needs and to form synapses, while stress has been proven to alter synaptic plasticity.Emerging evidence underpins that rhodiola rosea, an adaptogenic plant rich in polyphenols, exerts antioxidant, antistress, and neuroprotective effects.Methods.In this study, the effect of rhodiola rosea extract (rre) ws®1375 on neuronal ros regulation, bioenergetics, and neurite outgrowth, as well as its potential modulatory effect on the brain derived neurotrophic factor (bdnf) pathway, was evaluated in the human neuroblastoma sh-sy5y and the murine hippocampal ht22 cell lines.Stress was induced using the corticosteroid dexamethasone.Results.Rre increased bioenergetics as well as cell viability and scavenged ros with a similar efficacy in both cells lines and counteracted the respective corticosteroid-induced dysregulation.The effect of rre, both under dexamethasone-stress and under normal conditions, resulted in biphasic u-shape and inverted u-shape dose response curves, a characteristic feature of adaptogenic plant extracts.Additionally, rre treatment promoted neurite outgrowth and induced an increase in bdnf levels.Conclusion.These findings indicate that rre may constitute a candidate for the prevention of stress-induced pathophysiological processes as well as oxidative stress.Therefore, it could be employed against stress-associated mental disorders potentially leading to the development of a condition-specific supplementation.

Journal: Oxidative Medicine and Cellular Longevity (2022)
Publication types: Research Article;
Research Status of Differentially Expressed Noncoding RNAs in Type 2 Diabetes Patients

S.Noncoding rnas (nc rnas) play an important role in the occurrence and development of type 2 diabetes mellitus (t2dm).This paper summarized the current evidences of the involvement micro rnas, long noncoding rnas (lnc rnas), and circular rnas (circ rnas) in the differential expressions and their interaction with each other in t2dm.Methods.The differentially expressed mi rnas, lnc rnas, and circ rnas in the blood circulation (plasma, serum, whole blood, and peripheral blood mononuclear cells) of patients with t2dm were found in pub med, gcbi, and other databases.The interactions between nc rnas were predicted based on the mi rwalk and the diana tools databases.The indirect and direct target genes of lnc rnas and circ rnas were predicted based on the star base v2.0, diana tools, and lnc rna‐target databases.Then, go and kegg analysis on all mi rna, lnc rna, and circ rna target genes was performed using the mir path and cluster profile software package in r language.The lnc rna–mi rna and circ rna–mi rna interaction diagram was constructed with cytoscape.The aim of this investigation was to construct a mechanism diagram of lnc rna involved in the regulation of target genes on insulin signaling pathways and age–rage signaling pathways of diabetic complications.Results.A total of 317 rnas, 283 mi rnas, and 20 lnc rnas and circ rnas were found in the circulation of t2dm.Dysregulated micro rnas and lnc rnas were found to be involved in signals related to metabolic disturbances, insulin signaling, and age–rage signaling in t2dm.In addition, lnc rnas participate in the regulation of key genes in the insulin signaling and age–rage signaling pathways through micro rnas, which leads to insulin resistance and diabetic vascular complications.Conclusion.Noncoding rnas participate in the occurrence and development of type 2 diabetes and lead to its vascular complications by regulating different signaling pathways.

Journal: BioMed Research International (2020)
Publication types: Review Article;
Research Progress of Deep Learning in the Diagnosis and Prevention of Stroke

In order to evaluate the importance of deep learning techniques in stroke diseases, this paper systematically reviews the relevant literature.Deep learning techniques have a significant impact on the diagnosis, treatment, and prediction of stroke.In addition, this study also discusses the current bottlenecks and the future development prospects of deep learning technology.

Journal: BioMed Research International (2021)
Publication types: Review Article;
Research on Value Co-Creation New Business Model of Import Cross-Border E-Commerce Platform Ecosystem

Since the outbreak of covid-19, the cross-border e-commerce platform has been rising rapidly because of its unique advantages.However, with the widespread application of information technologies such as mobile internet and big data, fundamental changes have taken place in consumer preferences, consumption patterns, and marketing channels in cross-border e-commerce platforms.They also change the logic of value co-creation (vcc).The platform can achieve survive, expansion, and sustainable development by realising the value co-creation of the whole platform ecosystem.Based on the perspective of the platform ecosystem, this paper uses the grounded theory analysis method and nvivo 11.0 software carries out three-level coding on the obtained original data, and finally summarises and extracts four core categories of value co-creation mechanism: connection and interaction of value co-creators, demand mining, resource integration, and system support.The first two categories reflect stakeholders’ internal connection and interaction mechanism, and the last two categories reflect the external support mechanism in value co-creation.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Research on Tourism Route Recommendation Strategy Based on Convolutional Neural Network and Collaborative Filtering Algorithm

With improving people’s living standards, tourism has become essential leisure and entertainment.At present, it has begun to shift from a quantity-oriented tourism method to a quality-oriented tourism method.It is difficult for passengers to choose the route that suits them from the numerous routes.Given the above problems, this study proposes a travel route recommendation algorithm that combines a convolutional neural network and collaborative filtering.The algorithm uses a convolutional neural network to extract the latent features in the customer and travel itinerary data and then uses the matrix factorization method based on collaborative filtering to perform score prediction.The experimental results show that the algorithm can meet the travel requirements of different customers.At the same time, the recommendation accuracy of the tourist route is improved, and technology and method are provided for realizing the personalized recommendation service of the tourist route.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Research on Association between Levels of Serum Adiponectin, Hs-CRP, and sICAM-1 and Hypertensive Cerebrovascular Complications

The study is aimed at studying the association between the levels of serum adiponectin (adpn), high‐sensitivity c‐reactive protein (hs‐crp), and soluble intercellular adhesion molecule‐1 (s icam‐1) and hypertensive cerebrovascular complications.50 patients with hypertensive cerebrovascular disease treated in gansu provincial hospital from december 2016 to december 2018 were selected as the experimental group, and 50 normal people who underwent physical examination were selected as the control group.The blood pressure, heart rate, and the complications were recorded, and the serum blood lipid indexes were detected.Moreover, the content of serum adpn, hs‐crp, and s icam‐1; the neurological indexes; brain‐derived neurotrophic factor (bndf); and neurone‐specific enolase (nse) were also determined using elisa.The content of aspartate aminotransferase (ast), alanine aminotransferase (alt), blood urea nitrogen (bun), and serum creatinine (scr) in the experimental group was significantly higher than that in control group ( p &lt; 0.05); the incidence of cerebrovascular complications, systolic blood pressure, diastolic blood pressure, and heart rate increased ( p &lt; 0.05); the content of total cholesterol (tc), triglyceride (tg), low‐density lipoprotein (ldl), high‐density lipoprotein (hdl), hs‐crp, and s icam‐1 obviously rose ( p &lt; 0.05); and the content of adpn and hdl obviously declined ( p &lt; 0.05).Besides, the experimental group had evidently lower systolic blood flow velocity (vs), diastolic blood flow velocity (vd), and mean blood flow velocity (vm) and evidently higher pulsatility index (pi) ( p &lt; 0.05).The levels of s100 and nse in the experimental group increased significantly, and the level of bndf decreased significantly ( p &lt; 0.05).In patients with hypertensive cerebrovascular disease, the level of adpn declines; the levels of hs‐crp and s icam‐1 rise; the incidence rate of cerebrovascular complications is elevated; and there are changes in the blood lipid, cerebrovascular hemodynamic, and neurological indexes, thereby further promoting the occurrence and development of hypertensive cerebrovascular disease.

Journal: BioMed Research International (2021)
Publication types: Research Article;
Recent Advances in Cell and Functional Biomaterial Treatment for Spinal Cord Injury

Spinal cord injury (sci) is a devastating central nervous system disease caused by accidental events, resulting in loss of sensory and motor function.Considering the multiple effects of primary and secondary injuries after spinal cord injury, including oxidative stress, tissue apoptosis, inflammatory response, and neuronal autophagy, it is crucial to understand the underlying pathophysiological mechanisms, local microenvironment changes, and neural tissue functional recovery for preparing novel treatment strategies.Treatment based on cell transplantation has become the forefront of spinal cord injury therapy.The transplanted cells provide physical and nutritional support for the damaged tissue.At the same time, the implantation of biomaterials with specific biological functions at the site of the sci has also been proved to improve the local inhibitory microenvironment and promote axonal regeneration, etc.The combined transplantation of cells and functional biomaterials for sci treatment can result in greater neuroprotective and regenerative effects by regulating cell differentiation, enhancing cell survival, and providing physical and directional support for axon regeneration and neural circuit remodeling.This article reviews the pathophysiology of the spinal cord, changes in the microenvironment after injury, and the mechanisms and strategies for spinal cord regeneration and repair.The article will focus on summarizing and discussing the latest intervention models based on cell and functional biomaterial transplantation and the latest progress in combinational therapies in sci repair.Finally, we propose the future prospects and challenges of current treatment regimens for sci repair, to provide references for scientists and clinicians to seek better sci repair strategies in the future.

Journal: BioMed Research International (2022)
Publication types: Review Article;
Quercetin Prevents Radiation-Induced Oral Mucositis by Upregulating BMI-1

Radiation‐induced oral mucositis is a major adverse event of radiotherapy.Severe oral mucositis may cause unwanted interruption in radiotherapy and reduce long‐term survival in cancer patients receiving radiotherapy, but until now, there have been no effective options for preventing radiation‐induced oral mucositis.Quercetin is a flavonoid that is widely found in food species and has anti‐inflammatory, antioxidant, and anticancer activities.In this study, we investigated a new role of quercetin in preventing radiation‐induced oral mucositis.Quercetin exerted preventive effects against radiation‐induced oral mucositis induced by single‐dose (25 gy) ionizing radiation or fractionated ionizing radiation (8 gy × 3) in c57bl/6 mice and maintained the proliferation ability of basal epithelial cells.Quercetin pretreatment alleviated reactive oxygen species generation, nf‐ κ b pathway activation, and downstream proinflammatory cytokine production and reduced dna double‐strand breaks and cellular senescence induced by ionizing radiation.Quercetin also upregulated bmi‐1 expression in oral epithelial cells and promoted ulcer repair.In addition, quercetin exerted similar radioprotective effects in irradiated primary cultured normal human keratinocytes, reduced reactive oxygen species generation and proinflammatory cytokine release, and promoted dna double‐strand break repair and wound healing by upregulating the expression of bmi‐1, which is a polycomb group protein.Thus, quercetin can block multiple pathological processes of radiation‐induced oral mucositis by targeting bmi‐1 and may be a potential treatment option for preventing radiation‐induced oral mucositis.

Journal: Oxidative Medicine and Cellular Longevity (2021)
Publication types: Research Article;
Quantifying the Soil Arthropod Diversity in Urban Forest in Dera Ghazi Khan

Arthropods can be either large or too small to be seen from the microscope.Their legs are jointed and perform a specific function in the soil.Several arthropods have been identified to date.Therefore, it is essential to identify them in a different type of soil.An experiment to quantify the soil arthropods in the urban forests of d.g.Khan was conducted at the zoology lab of ghazi university on four tree plants, i.e., neem ( azadirachta indica ), mango ( mangifera indica ), guava ( psidium guajava ), and phalsa ( grewia asiatica ).Soil samples were taken from different areas and on different months.The diversity of arthropods was analyzed through the shannon index.The results were all significant.The total number of arthropods found in the experiment was 5151, with the following distributions: millipedes were 132 in neem, 133 in guava, 113 in mango, and 121 in phalsa; centipedes were 136 in neem, 142 in guava, 118 in mango, and 132 in phalsa; springtails were 138 in neem, 130 in guava, 120 in mango, and 134 in phalsa.There were a total of 12 different species of arthropods found.Neem ( azadirachta indica) have mites, centipede, and ants; guava ( psidium guajava) have centipedes and ants.Mango ( mangifera indica) have millipedes, centipedes, mites, springtail, and ants, and phalsa ( grewia asiatica) have mites, ants, and centipedes.The study reveals that millipedes, centipedes, springtails, and ants were found abundantly in the urban forest area of d.g.Khan, resulting in increased organic matter decomposition and appropriate distribution of nutrients through the soil having beneficial effects on the terrestrial ecosystem.

Journal: BioMed Research International (2022)
Publication types: Research Article;
PSO-Based Evolutionary Approach to Optimize Head and Neck Biomedical Image to Detect Mesothelioma Cancer

Mesothelioma is a form of cancer that is aggressive and fatal.It is a thin layer of tissue that covers the majority of the patient’s internal organs.The treatments are available; however, a cure is not attainable for the majority of patients.So, a lot of research is being done on detection of mesothelioma cancer using various different approaches; but this paper focuses on optimization techniques for optimizing the biomedical images to detect the cancer.With the restricted number of samples in the medical field, a relief‐pso head and mesothelioma neck cancer pathological image feature selection approach is proposed.The approach reduces multilevel dimensionality.To begin, the relief technique picks different feature weights depending on the relationship between features and categories.Second, the hybrid binary particle swarm optimization (hbpso) is suggested to automatically determine the optimum feature subset for candidate feature subsets.The technique outperforms seven other feature selection algorithms in terms of morphological feature screening, dimensionality reduction, and classification performance.

Journal: BioMed Research International (2022)
Publication types: Research Article;
Provisional Decision-Making for Perioperative Blood Pressure Management: A Narrative Review

Blood pressure (bp) is a basic determinant for organ blood flow supply.Insufficient blood supply will cause tissue hypoxia, provoke cellular oxidative stress, and to some extent lead to organ injury.Perioperative bp is labile and dynamic, and intraoperative hypotension is common.It is unclear whether there is a causal relationship between intraoperative hypotension and organ injury.However, hypotension surely compromises perfusion and causes harm to some extent.Because the harm threshold remains unknown, various guidelines for intraoperative bp management have been proposed.With the pending definitions from robust randomized trials, it is reasonable to consider observational analyses suggesting that mean arterial pressures below 65 mm hg sustained for more than 15 minutes are associated with myocardial and renal injury.Advances in machine learning and artificial intelligence may facilitate the management of hemodynamics globally, including fluid administration, rather than bp alone.The previous mounting studies concentrated on associations between bp targets and adverse complications, whereas few studies were concerned about how to treat and multiple factors for decision-making.Hence, in this narrative review, we discussed the way of bp measurement and current knowledge about baseline bp extracting for surgical patients, highlighted the decision-making process for bp management with a view to providing pragmatic guidance for bp treatment in the clinical settings, and evaluated the merits of an automated blood control system in predicting hypotension.

Journal: Oxidative Medicine and Cellular Longevity (2022)
Publication types: Review Article;
Self-Sovereign Identity for Consented and Content-Based Access to Medical Records Using Blockchain

Electronic health records (ehrs) and medical data are classified as personal data in every privacy law, meaning that any related service that includes processing such data must come with full security, confidentiality, privacy, and accountability.Solutions for health data management, as in storing it, sharing and processing it, are emerging quickly and were significantly boosted by the covid-19 pandemic that created a need to move things online.Ehrs make a crucial part of digital identity data, and the same digital identity trends—as in self-sovereign identity powered by decentralized ledger technologies like blockchain, are being researched or implemented in contexts managing digital interactions between health facilities, patients, and health professionals.In this paper, we propose a blockchain-based solution enabling secure exchange of ehrs between different parties powered by a self-sovereign identity (ssi) wallet and decentralized identifiers.We also make use of a consortium ipfs network for off-chain storage and attribute-based encryption (abe) to ensure data confidentiality and integrity.Through our solution, we grant users full control over their medical data and enable them to securely share it in total confidentiality over secure communication channels between user wallets using encryption.We also use dids for better user privacy and limit any possible correlations or identification by using pairwise dids.Overall, combining this set of technologies guarantees secure exchange of ehrs, secure storage, and management along with by-design features inherited from the technological stack.

Journal: Security and Communication Networks (2023)
Publication types: Research Article;
Synergistic Effect of Conventional Medicinal Herbs against Different Pharmacological Activity

Triticum aestivum (family: poaceae), ocimum sanctum (family: lamiaceae), and tinospora cordifolia (family: menispermaceae) are commonly known as wheatgrass, tulsi, and giloy, respectively, which are the plants used as medicines for the treatment of various diseases.All three medicinal plants possess phenolic compounds with other important chemical constituents such as polysaccharides, aliphatic compounds, and alkaloids.The extract of these plants has been prepared and investigated for antioxidant, total phenolic content, total flavonoid content, and antimicrobial study in order to discover potential sources for new pharmaceutical formulations.To determine the antioxidant activity, a free radical scavenging assay for 2,2‐diphenyl‐1‐picrylhydrazyl (dpph) and hydrogen peroxide was performed using ascorbic acid as the standard.The r 2 value of the prepared extract was found to be 0.9964 and 0.990 in dpph and hydrogen peroxide scavenging activity, respectively.The phenolic and flavonoid content was found to be 87.50 μ l/ml and 58.00 μ l/ml, respectively.The diffusion method was used to screen the antimicrobial activity of the prepared extract sample against various microorganisms.This extract showed better results for antioxidant and antimicrobial activity.

Journal: BioMed Research International (2022)
Publication types: Research Article;
Research on Securities Portfolio Model Based on Genetic Optimization Neural Network

Portfolio is an investment management concept different from individual asset management.This consideration leads to an interesting result, that is, investors should buy a variety of securities at the same time instead of one kind of securities for diversified investment.Aiming at the limitations of bpnn (bp neural network) in traditional artificial neural network and its shortcomings such as many iterations, low convergence accuracy, and poor generalization, a portfolio method based on ga_bpnn (genetic optimization neural network) was proposed.The setting of ga (genetic algorithm) parameters and bpnn parameters are discussed in detail, and the implementation steps of genetic bp algorithm are described.The results show that the evaluation indexes of ga_bpnn prediction model are obviously better than those of the comparison prediction model, with the coincidence rate of 77.96% and the average absolute error of 12.451.The combination of ga and bpnn can effectively solve this problem.The simulation results of optimizing securities portfolio show that its optimization scheme is better than quadratic programming method, and this method is more correct, efficient, and practical.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;