syedzayyan/paper_mill_benchmark huggingface dataset:
Human Umbilical Mesenchymal Stem Cells-Derived Microvesicles Attenuate Formation of Hypertrophic Scar through Multiple Mechanisms

Mesenchymal stem cells and the derived extracellular microvesicles are potential promising therapy for many disease conditions, including wound healing.Since current therapeutic approaches do not satisfactorily attenuate or ameliorate formation of hypertrophic scars, it is necessary to develop novel drugs to achieve better outcomes.In this study, we investigated the effects and the underlying mechanisms of human umbilical mesenchymal stem cells (humscs)-derived microvesicles (humscs-mvs) on hypertrophic scar formation using a rabbit ear model and a human foreskin fibroblasts (hff) culture model.The results showed that humscs-mvs reduced formation of hypertrophic scar tissues in the rabbit model based on appearance observation, and hematoxylin and eosin (h&amp;e), masson, and immunohistochemical stainings.Humscs-mvs inhibited invasion of hff cells and decreased the levels of the α-sma, n-wasp, and cortacin proteins.Humscs-mvs also inhibited cell proliferation of hff cells.The mmp-1, mmp-3, and timp-3 m rna levels were significantly increased, and the timp-4 m rna level and the nf-k b p65/β-catenin protein levels were significantly decreased in hff cells after humscs-mvs treatment.The p-smad2/3 levels and the ratios of p-smad2/3/smad2/3 were significantly decreased in both the wound healing tissues and hff cells after humscs-mvs treatment.Cd34 levels were significantly decreased in both wound healing scar tissues and hff cells after humscs-mvs treatment.The vegf-a level was also significantly decreased in hff cells after humscs-mvs treatment.The magnitudes of changes in these markers by humscs-mvs were mostly higher than those by dexamethasone.These results suggested that humscs-mvs attenuated formation of hypertrophic scar during wound healing through inhibiting proliferation and invasion of fibrotic cells, inflammation and oxidative stress, smad2/3 activation, and angiogenesis.Humscs-mvs is a potential promising drug to attenuate formation of hypertrophic scar during wound healing.

Journal: Stem Cells International (2023)
Publication types: Research Article;
Effect of Fas and Bcl-2 DNA Damages Response Expression in Stem Cells on Apoptosis of Nucleus Pulposus of Intervertebral Disc

The nucleus pulposus is an elastic jelly composed of crisscross fibrous reticular structures, namely, chondrocytes and proteoglycan mucoid matrix.Embryo and adult sc can resist the accumulation of genetic damage and repair them through various dna repair mechanisms, thus preventing them from spreading to daughter cells.Fresh medullary tissue was fixed with 10% formaldehyde solution, embedded in paraffin, and sectioned at 4 m.The nucleus pulposus was stained with he, and its degeneration was observed under light microscope.The average apoptotic index (ai) of 20 denatured nuclei was 50.230, the percentage of fas-positive cells was 74.255%, and the percentage of bcl-2-positive cells was 55.370%.The average apoptotic index (ai) was 28.317.The percentage of fas-positive cells, fas protein-positive cells, and bcl-2 protein-positive cells in six normal nuclei was 41.717%, 41.717%, and 27.167%, respectively.The average ai value, fas protein expression, and bcl-2 protein expression in the two groups were significantly different ( p &lt; 0.05 ).

Journal: Stem Cells International (2023)
Publication types: Research Article;
Design of New Working Environment Based on Artificial Intelligence Algorithm

With the three industrial revolutions sweeping the world, especially since the third industrial revolution, the complexity of human work has greatly increased, and in the new era of technology and information, workers have new standards and new requirements for their work environment, and new form of work environment design has come into being.In this paper, a work environment system is designed by artificial intelligence algorithm to improve the workers’ work environment by assessing the good and bad degree of their natural and social work environment, and an intelligent service system is designed by using artificial intelligence algorithm, which can not only analyze and process the work environment assessment results but also execute the subjective and reasonable requirements made by the workers to help the workers maintain a good mood at work and improve their efficiency.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
Contextualization of Trait Nexus and Gene Action for Quantitative and Qualitative Characteristics in Indian Mustard

After soybean and palm oil, the world’s third largest oil seed crop is rapeseed mustard.Out of the seven consumable oil seed crops grown in india, rapeseed mustard is responsible for one-third of production.Mustard aphid (lipaphis erysimi kalt) is considered the primary pest causing mayhem in crop production.Understanding the genetics behind resistance will aid breeders in developing a resistant/tolerant strain.Appropriate parent selection and analyzing gene action contribute to economic benefit maximization.The aims of the current study are to use seven lines and five testers to determine the best-performing parents and crosses based on their general and specific capacity to combine and to examine the level of heterosis for yield and related features like mustard aphid resistance.Due to the self-pollination nature of indian mustard, kempthorne’s line x tester method is helpful to judge the combining ability.Therefore, seven lines and five testers of indian mustard (brassica juncea l.) were employed in the present study.The findings suggested that there was substantial genetic variation for all traits examined.The mean oil yield of r1 b2-26 × r1 b2-25, jd6 × r1 b2-25, and jd6 × r1 b2-29 hybrids was more significant than that of the ancestors.The results show that r1 b2-26 × r1 b2-25, jd6 × r1 b2-25, and jd6 × r1 b2-29 hybrids produced more oil than their parents.The variance explained by sca was greater than that explained by gca, as indicated by the ϭ2 gca/ϭ2 sca ratio being less than one for all characters, implying that nonadditive gene actions such as dominance, epistasis, and other interaction effects played an important role in the presence of these attributes.Punjab local was discovered to be an excellent general merge for reducing crop duration, whereas jd6 was an excellent combiner for seed yield per crop, aphid infestation indicator, seed yield per crop, and oil production per plant.The predictability ratio was found to be less than 0.5 for almost all traits, denoting that the nonadditive gene measure is involved in controlling the nature except days to 50% flowering, aphid infestation index, oil content, and oil yield per plant.Thus, based on these four traits, selection for superior plants may be practiced in later generations.

Journal: Journal of Food Quality (2022)
Publication types: Research Article;
Blockchain-Based Secure Traceable Scheme for Food Supply Chain

The typical food traceability system’s data layer is made up of relational databases managed by core businesses, which cannot ensure data security.It is inefficient and requires a lot of upkeep.The food supply chain has numerous actors, making it difficult for consumers to safeguard their rights when purchasing food with quality issues.Due to the numerous organizations involved in the food supply chain, food safety monitoring and traceability have become challenging.The supply chain’s major organizations have control and administrative authority over the data under the current food traceability system, which is overly centralized for traceability information.The safety and dependability of food may be ensured by using the food traceability system to track food information.We can witness a series of detailed insights into food from the manufacturing source to the consumption terminal.A blockchain-based food tracking system is created as a solution to these issues.On the ethereum platform, the system was created.It was also employed in the blockchain system, in addition to its features of decentralization, tamper-proof, and traceability.To implement the data update service and the food recall function, introduce the food and drug administration node.Consumers have the option to not only enquire about food traceability throughout the manufacturing process but also to file complaints regarding the traceability system’s rights protection.

Journal: Journal of Food Quality (2023)
Publication types: Research Article;
Artificial Intelligence-based Blockchain Technology for Skin Cancer Investigation Complemented with Dietary Assessment and Recommendation using Correlation Analysis in Elder Individuals

In the modern world, due to the usage of high-power chemical-based cosmetics, climate change, and other major factors, skin cancer has been increasing among individuals.Skin cancer is considered as the most common malignant disorder, and there are more than a million cases being recorded with this disease every year.Extensive studies have already been performed to identify the risk factors and causative agents for skin cancer, including lifestyle changes and eatery patterns among individuals.The most common type of skin cancer is classified into basal cell carcinoma and squamous cell carcinoma.The researcher intends to conduct the research with the primary goal of determining the important factors in blockchain technology in the treatment of skin cancer in senior people.The application of new technologies such as blockchain has enabled offering better promises to health care professionals in addressing skin cancer in a more effective manner.These tools supported in evaluating the nature and severity of psoriasis has been regarded as much support for health care professionals in detecting skin cancer and offer better health care guidance for better living.The detection of melanomas supports the patient in enhancing the prognosis and support in discriminating between the melanomas and less impact lesions.The blockchain-based classification system offers more benefits and reduces the cost of detecting skin cancer in an effective manner.It also helps the medical professionals by assisting them in developing a custom diet plan for each patient on the basis of their health records and food intake.The researchers are focused on applying both the primary data sources and secondary data sources for performing the study.A detailed questionnaire is designed, and it is shared with the participants through university hospitals, support groups, etc.So as to gather the information.Nearly 156 respondents were chosen through nonprobability sampling, and the information was collected.The researcher performs critical descriptive analysis, and correlation analysis is performed to understand the overall association between the variables.The researchers intend to perform the study with the basic goal of understanding the critical factors in blockchain technology in skin cancer for elderly individuals.The major factors involved are enhanced data privacy, support in forecasting patterns, and enhanced medical services to patients complemented with personalized dietary assessment and recommendations.The result demonstrates that artificial intelligence-based blockchain technology allows for the efficient processing of huge amounts of data in order to complete the assigned task and correctly determine and predict the model.

Journal: Journal of Food Quality (2022)
Publication types: Research Article;
An Investigation in Analyzing the Food Quality Well-Being for Lung Cancer Using Blockchain through CNN

Deep learning (dl) is a new approach that provides exceptional speed in healthcare activities with greater accuracy.In this regard, “convolutional neural network” or cnn and blockchain are two important parts that together fasten the disease detection procedures securely.Cnn can detect and predict diseases like lung cancer and help determine food quality, and blockchain is responsible for data.This research is going to analyze the extension of blockchain with the help of cnn for lung cancer prediction and making food safer.Cnn algorithm has been trained with a huge number of images by altering the filters, features, epoch values, padding value, kernel size, and resolution.Subsequently, the cnn accuracy has been measured to understand how these factors affect the accuracy.A linear regression analysis has been carried out in ibm spss where the independent variables selected are image dataset augmentation, epochs, features, pixel size (90 × 90 to 512 × 512), kernel size (0–7), filters (10–40), and padding.The dependent variable is the accuracy of cnn.Findings suggested that a larger number of epochs improve the cnn accuracy; however, when more than 12 epochs are considered, the accuracy may decrease.A greater pixel/resolution also improves the accuracy of cancer and food image detection.When images are provided with excellent features and filters, the cnn accuracy improves.The main objective of this research is to comprehend how the independent variables affect the accuracy (dependent), but the reading may not be fully exact, and thus, the researcher has conceded out a minor task, which delivered evidence supportive of the analysis and against the analysis.As a result, it can be determined that image augmentation and a large number of images develop the cnn accuracy in lung cancer prediction and food safety determination when features and filters are applied correctly.A total of 10–12 epochs are desirable for cnn to receive 99% accuracy with 1 padding.

Journal: Journal of Food Quality (2022)
Publication types: Research Article;
A Novel Model to Detect and Classify Fresh and Damaged Fruits to Reduce Food Waste Using a Deep Learning Technique

Due to a lack of efficient measures for dealing with food waste at many levels, including food supply chains, homes, and restaurants, the world’s food supply is shrinking at an alarming pace.In both homes and restaurants, overcooking and other factors are to be blamed for the majority of food that is wasted.Families are the primary source of food waste, and we sought to reduce this by identifying fresh and damaged food.In agriculture, the detection of rotting fruits becomes crucial.Despite the fact that people routinely classify healthy and rotten fruits, fruit growers find it ineffective.In contrast to humans, robots do not grow tired from doing the same thing again and again.Because of this, finding faults in fruits is a declared objective of the agricultural business in order to save labour, waste, manufacturing costs, and time spent on the process.An infected apple may infect a healthy one if the defects are not discovered.Food waste is more likely to occur as a consequence of this, which causes several problems.Input images are used to identify healthy and deteriorated fruits.Various fruits were employed in this study, including apples, bananas, and oranges.For classifying photographs into fresh and decaying fruits, softmax is used, while cnn obtains fruit image properties.A dataset from kaggle was used to evaluate the suggested model’s performance, and it achieved a 97.14 percent accuracy rate.The suggested cnn model outperforms the current methods in terms of performance.

Journal: Journal of Food Quality (2022)
Publication types: Research Article;
Dynamic Data Infrastructure Security for Interoperable e-Healthcare Systems: A Semantic Feature-Driven NoSQL Intrusion Attack Detection Model

The exponential rise in advanced software computing and low‐cost hardware has broadened the horizon for the internet of medical things (io mt), interoperable e‐healthcare systems serving varied purposes including electronic healthcare records (ehrs) and telemedicine.However, being heterogeneous and dynamic in nature, their database security remains a challenge forever.Numerous intrusion attacks including bot‐attack and malware have confined major classical databases towards e‐healthcare.Despite the robustness of no sql over the structured query language databases, the dynamic data nature over a heterogeneous environment makes it vulnerable to intrusion attacks, especially over interoperable e‐healthcare systems.Considering these challenges, this work proposed a first of its kind semantic feature‐driven no sql intrusion attack (no sql‐ia) detection model for interoperable e‐healthcare systems.This work assessed the efficacy of the different semantic feature‐extraction methods like word2vec, continuous bag of words, n‐skip gram (skg), count vectorizer, tf‐idf, and glove towards no sql‐ia prediction.Subsequently, to minimize computational exhaustion, different feature selection methods including wilcoxon rank sum test (wrst), significant predictor test, principal component analysis, select k‐best, and variance threshold feature selection algorithms were employed.To alleviate the data imbalance problem, it applied different resampling methods including upsampling, downsampling, and synthetic minority oversampling technique (smote) over the selected features.Later, min–max normalization was performed over the input feature vectors to alleviate any possibility of overfitting.Towards no sql‐ia prediction, different machine learning methods like multinomial naïve bayes, decision tree, logistic regression, support vector machine, k‐nn, ada boost, extra tree classifier, random forest ensemble, and xg‐boost were applied, which classified each input query as the regular query or the no sql‐ia attack query.The depth performance assessment revealed that the use of word2vec features skg in sync with vtfs feature selection and smote resampling processed with the bootstrapped random forest classifier can provide the best performance in terms of high accuracy (98.86%), f‐measure (0.974), and area under the curve (auc) (0.981), thus enabling it suitable for interoperable e‐healthcare database security.

Journal: BioMed Research International (2022)
Publication types: Research Article;
Downregulation of miR-221-3p by LncRNA TUG1 Promoting the Healing of Closed Tibial Fractures in Mice

To probe into the effect of lnc rna tug1 on the healing of closed tibial fracture in mice.Methods .The closed tibial fracture model of mice was established, selecting the mouse osteoblast line mc3t3‐e1, with the cells separated into four groups.The expression levels of tug1 and mi r‐221‐3p were determined by rt‐q pcr analysis, with the targeting relationship between tug1 and mi r‐221‐3p authenticated by dual luciferase reporter (dlr) assay, detection of cell migration (cm) ability based on transwell cell migration (tcm) assay, and cell proliferation (cp) acquired by cell counting kit‐8 (cck‐8).Results .Prediction results of the target gene by bioinformatics software showed that mi r‐221‐3p had binding sites with the 3′‐utr of tug1, and dlr assay authenticated the targeting relationship between lnc rna tug1 and mi r‐221‐3p.Downregulation of tug1 inhibited osteoblast cp and cm and promoted osteoblast cell apoptosis (ca).Cell cycle analysis indicated that mi r‐221‐3p provoked cell cycle arrest in g1 stage of mc3t3‐e1 cells.The si lnc rna‐nc group had higher anticyclin d1 and d3 levels than the si lnc rna tug1 group, with a lower ca rate in the former, implying that mi r‐221‐3p overexpression inhibited osteoblast cp and cm and lnc rna tug1 inhibited ca.Downregulation of mi r‐221‐3p partly reversed the retardation out of downregulating tug1 on osteoblast cp and cm.Bcl‐2 level was higher in the lnc rna tug1 group compared to the si lnc rna tug1 and mi r‐221‐3p overexpression groups, with remarkably lower sdf‐1 level in the mi r‐221‐3p overexpression group than those in the control, mi rna‐nc, and lnc rna tug1 groups.Conclusion .The downregulation of mi r‐221‐3p by lnc rna tug1 can promote the healing of closed tibial fractures in mice.

Journal: BioMed Research International (2022)
Publication types: Research Article;
The Effects of Rural Residents’ Sleep Quality on the Incidence of Agricultural Injuries: A Meta-Analysis

To collect relevant literature on the impact of rural residents' sleep quality on the incidence of agricultural injuries, the search time range is 1990~2019.We use rev man 5.3 software for statistical processing.A total of 7 articles were included.Meta‐analysis showed that sleep quality was closely related to agricultural injury.The combined effect was 1.49, 95% ci [1.31, 1.70], z = 5.93, p &lt; 0.00001.The difference was statistically significant, so poor sleepers had a higher incidence of agricultural injuries than good sleepers.Sleep disturbances and agricultural injuries are two common and significant health problems.Investigations suggest that sleep might increase the risk of agricultural injuries.The aim of the present study was to systematically review and meta‐analyze the predictive effect of sleep on agricultural injuries.

Journal: Contrast Media & Molecular Imaging (2022)
Publication types: Meta-Analysis;
RUNX3-Regulated GALNT6 Promotes the Migration and Invasion of Hepatocellular Carcinoma Cells by Mediating O-Glycosylation of MUC1

Hepatocellular carcinoma (hcc) is a leading cause of cancer-related death worldwide.Dysregulation of messenger rnas (m rna) has been recognized to be associated with hcc carcinogenesis and development.Polypeptide gal nac transferase 6 (galnt6), an o-type glycosyltransferase, has been confirmed as tumor promoter in different cancers.However, the function of galnt6 in hcc remains to be studied.Methods.Rt-q pcr and western blot experiments were, respectively, performed for evaluating rna expressions and protein levels.Supported by bioinformatics analysis, mechanism assays were conducted for validating the potential relation between different genes.Functional assays were implemented to analyze hcc cell migration and invasion after different transfections.Results.Galnt6 was aberrantly upregulated in hcc cells.Knockdown of galnt6 could repress hcc cell migration and invasion.Runx3 was verified to bind to galnt6 promoter and activate galnt6 transcription.Galnt6 depletion led to inhibited o-glycosylation and aggravated degradation of muc1.Muc1 overexpression could rescue the impeded hcc cell migration and invasion induced by galnt6 knockdown.Conclusion.To sum up, galnt6 transcriptionally activated by runx3 mediated the o-glycosylation of muc1, thus exerting promoting influence on hcc cell migration and invasion.

Journal: Disease Markers (2022)
Publication types: Research Article;
Regulation of Quality of Life and Immune Function in Patients with Thyroid Cancer Treated by Deep Learning Technology

In order to explore the regulation of quality of life and immune function in patients with thyroid cancer after radiotherapy, a method based on deep learning technology was proposed.A deep learning detection method for thyroid cancer is proposed.Methods .It mainly includes three main modules: data preprocessing, thyroid cancer regional detection module, and thyroid cancer benign and malignant classification module.The data set in the experiment comes from lidc‐idri and is processed by the data preprocessing module to generate a standard data format that can be processed by the framework.The treatment of thyroid cancer can help patients relapse malignant thyroid cancer and prevent recurrence in advance.Results .The results showed that most patients are diagnosed because of obvious swelling of local thyroid mass and conscious compression symptoms in the neck.At this time, they often miss the best treatment time, so as to reduce the surgical effect.Conclusions .The metastasis and invasion of cancer cells are fast, the cancerous lesions are easy to form adhesion with the surrounding tracheal tissue, and the cancer cells invade the surrounding soft tissue, which is also easy to cause the cancerous tissue not to be completely removed.Clinical trial registration .Therefore, deep learning technology is used to treat residual cancerous lesions to ensure the surgical effect.

Journal: Contrast Media & Molecular Imaging (2022)
Publication types: Research Article;