bluuebunny/crossref_metadata_2025_split huggingface dataset:
Curcuminoids Attenuate Myocardial Ischemia-Reperfusion Injury by
Regulating Total RNA M6a Levels: In Vitro Study
Authors: Cui Jian-Kun , Wang Xin , Fan Mingming , Wang Qinwen 
Published: September 2022

Objective:
Myocardial ischemia-reperfusion (IR) injury is an unresolved medical problem with a high incidence. This study aims to analyze the novel molecular mechanism by which curcuminoids protect cardiomyocytes from IR injury.

Methods:
A IR model in vitro of rat cardiomyocytes H9c2 cells was structured. Curcumin (CUR) and its derivatives, demethoxycurcumin (DMC) and bisdemethoxycurcumin (BDMC) treated H9c2 cells, and reactive oxygen species (ROS) production, viability, apoptosis, mitochondrial membrane potential (MMP), oxidative stress and total RNA m6A levels of H9c2 cells were detected by using DCFH-DA stain, CCK-8, flow cytometry, Hoechst 33342 stain, TMRM stain, ELISA and RT-qPCR. FB23 was used in rescue experiments.

Results:
IR significantly increased ROS production, decreased cell viability, and induced apoptosis, MMP loss, and oxidative stress. In addition, IR induced an increase in total RNA m6A levels and changes in m6A-related proteins expression. CUR (10 μM), DMC (10 μM) and BDMC (10 μM), significantly inhibited IR-induced ROS production, apoptosis, MMP loss and oxidative stress, and enhanced cell viability. Furthermore, CUR, DMC and BDMC altered the expression pattern of m6A-related proteins and reduced IR-induced total m6A levels. There was no significant difference in the effects of the three. FB23 partially offseted the protective effect of CUR

Conclusion:
Curcuminoids attenuate myocardial IR injury by regulating total RNA m6A levels.
Compelling Cyclic Peptide Scaffolds for Antitubercular Action: An
Account (2011-21) of the Natural Source
Authors: Bandyopadhyay Anupam , Chowdhury Arnab 
Published: September 2022

Abstract:
Natural cyclic peptide scaffolds are indispensable in medicinal chemistry, chemical biology,
and drug discovery platforms due to their chemical diversity, structural integrity, proteolytic stability
and biocompatibility. Historically, their isolation and profound understanding of target engagement
have been identified as lead pharmacophore discovery. Natural cyclic peptides are the largest class of
pharmacologically active scaffold, in which most show activity against drug-resistant Mycobacterium
tuberculosis (Mtb). Nevertheless, eight recently discovered cyclic peptide scaffolds exhibit promising
antitubercular activity among numerous naturally occurring antitubercular peptides, and they are amenable
scaffolds to drug development. We examined their biological origin, scaffolds, isolations, chemical
synthesis, and reasons for biological actions against Mtb. Understanding these peptide scaffold details
will further allow synthetic and medicinal chemists to develop novel peptide therapeutics against
tuberculosis-infected deadly diseases. This review emphasizes these cyclic peptides' in vitro and in
vivo activity profiles, including their structural and chemical features.
In Vitro and In Silico Studies of Glycyrrhetinic Acid Derivatives as Antitubercular
Agents
Authors: Khare Naveen K. , Srivastava Santosh K. , Vishwakarma Sadhna , Shukla Aparna , Khan Feroz , Trivedi Priyanka , Chaturvedi Vinita 
Published: September 2022

Background:
Glycyrrhetinic acid (GA) is a biologically active triterpenoid acid, isolated from the root of the Glycyrrhiza plant species. In our earlier studies, the semisynthetic analogs of GA have been reported to possess improved anticancer activities against various cell lines, antimalarial, and antifilarial activities.

Method:
GA was isolated and characterized from roots of Glycyrrhiza glabra and converted to its various C-3 aryl ester derivatives via the protection of C-30 carboxylic group. Antitubercular activity was determined against Mycobacterium tuberculosis H37Ra by Agar dilution assay. The in-silico docking was performed for the most active analogue against three antitubercular targets, catalase peroxidase, dihydrofolate reductase and enoyl-ACP reductase.

Results:
The derivatives, Methyl glycyrrhetinate (GA-1), 3-O-(4-methyl-phenyl)-ethanoyl methyl glycyrrhetinate (GA-1a), 3-O-(4-fluoro phenyl)-ethanoyl methyl glycyrrhetinate (GA-1c), 3-O-(4-methoxy trans cinnamyl)-ethanoyl methyl glycyrrhetinate (GA-1e) and 3-O-{(4-chlorophenyl)-ethanoyl methyl glycyrrhetinate (GA-1g) showed improved antitubercular activity (in the range 38.76 to 51.546 mM) over the parent molecule (MIC >106.157 mM). The derivative, 3-O-(4-aminobenzoyl)- methyl glycyrrhetinate (GA-1h) was found most active (MIC 20.695 mM) which was further supported by high binding affinity with the selected antitubercular target proteins in in silico docking studies.

Conclusion:
Synthetic modifications on GA led to C-3 aryl ester derivatives with improved antitubercular activities. Further studies for the development of GA-1h as potential antitubercular lead is therefore warranted.
Statin in Clinical and Preclinical Knee Osteoarthritis-What E vidence Exists for Future Clinical Use?-A Literature Review
Authors: Siddiq Md Abu Bakar , Jahan Israt , Rasker Johannes J. 
Published: September 2022

Background:Statins are used to lower serum cholesterol. Recent preclinical and clinical research focuses on articular cartilage regeneration aspects of statin. This review summarizes the effects of statins on knee osteoarthritis (OA).Methods:Published preclinical and clinical literature till November 2021 were searched in PubMed and PubMed Central databases. Articles not written in English, not relevant for the review, and un-published evidence were excluded. Finally, 27 papers were reviewed and presented in the study.Results:A total of 27 articles have been included-13 clinical and 14 preclinical studies. Preclinical studies showed statin-induced chondroprotective effects; these included in vitro studies on human or animal-derived degenerated articular cartilage as well as OA animal models. Chondroprotective effects of statins are thought to mediate by inhibiting the Wnt/β-catenin signaling pathway, prevent-ing synovial inflammation, and inhibiting catabolic-stress-induced aging of cartilage. Preclinical study outcomes were based on biochemical, macroscopic, and microscopic (histology) assessments and seemed promising in cartilage regeneration. In the 13 clinical studies, the effect of statins on human OA is inconclusive: some showing improvement of OA symptoms, and others depict signs of aggravation and radiological progression. No randomized controlled trial (RCT) has tested the efficacy of intra-articular statins in clinical knee OA, and it seems feasible to avoid oral statin-associated severe adverse effects.Conclusion:There are no arguments to recommend oral statins in clinical OA-knee. An RCT test-ing the efficacy of oral statins in patients with OA knee was never done and still seems justified, as well as a prospective phase-II clinical trial for intra-articular statins in different types of OA.
Prediction of Breast Cancer Through Random Forest
Authors: S. Safia Naveed 
Published: September 2022

Background:
8% of women are diagnosed with breast cancer. (BC) BC is the second most
common cause of death in both developed and undeveloped countries. BC is characterized by the mutation
of genes, constant pain, changes in the size, color (redness), and skin texture of breasts. Classification
of breast cancer leads pathologists to find a systematic and objective prognostic; generally, the
most frequent classification is binary (benign/malignant).

Introduction:
Machine Learning (ML) techniques are broadly used in breast cancer classification.
They provide high classification accuracy and effective diagnostic capabilities. Breast cancer remains
one of the top diseases that lead to thousands of deaths in women yearly. Artificial intelligence (AI)
has been utilized to rapidly and accurately identify breast tumors and for early diagnosis. This paper
aims to research, determine and classify these tumors.

Methods:
Machine learning algorithm such as Random Forest (RF) is used to classify medical images
into malignant and benign. Moreover, Machine learning has been employed recently for the same purpose.

Results:
The results showed that Random Forest achieved high accuracy; therefore, the researchers
utilized various functions for this algorithm and added more features such as bagging and boosting to
increase its efficacy.

Conclusion:
The random Forest algorithm achieved an enhanced accuracy of 98%.
Plant Alpha-amylase Inhibitors: Steady Kinetic Study, Bidens odorata
Aqueous Infusion Toxicity and Stability in Digestive Tract Simulation
Authors: Valdés Roberto Arredondo , Ceniceros Elda Patricia Segura , Iliná Anna , Hernández José Luis Martínez , Belmares Sonia Yesenia Silva , González Rodolfo Ramos , Kunakova Raihana , Zaynullin Radik 
Published: September 2022

Background:
α-Amylase inhibitors are considered an important therapeutic target to control
type 2 diabetes mellitus, reducing postprandial hyperglycemia. Medicinal plants are an important source
with inhibitory activities of this enzyme but are little studied.

Objective:
The present study explored the α-amylase inhibition with extracts of 11 medicinal plants
available in Saltillo, Mexico; the kinetic mechanism of inhibition of selected extracts and their phytochemical
screening; evaluation of the toxicity of Bidens odorata extract in Artemia salina model, as
well as estimation of its inhibitory effect under in vitro digestive tract conditions.

Methods:
The inhibitory assays were carried out spectrophotometrically with aqueous suspensions of
the extracts obtained after evaporation of solvent from aqueous and ethanolic infusions.

Results:
Eleven plants showed an inhibitory effect of α-amylase above 10% of the initial activity at
666.7 ppm. Four plants were selected for kinetic assay due to the inhibitory effect near or higher than 20
%. The IC50 for the aqueous suspension of the ethanolic extract of Bidens odorata was 851 ppm, similar
to that detected with the drug acarbose. The inhibition mechanism for Bidens odorata, Cinchona succirub,
and Opuntia ficus-indicata was competitive, and for Cnidoscolus chayamansa it was uncompetitive.
All selected extracts presented flavonoids, the majority contained terpenoids, 3 contained tannins
and phenols. The aqueous infusion of Bidens odorata - model of a functional drink showed no toxicity
and was characterized by resistance for 60 min to the simulated stomach and intestinal conditions in
vitro.

Conclusions:
The findings of this study revealed the species of medicinal plants, which were not previously
considered as sources of α-amylase inhibitors, and their kinetic mechanisms of inhibition, which
can be used for functional hypoglycemic food preparation.
A Fuzzy System Classification Approach for QSAR Modeling of α-
Amylase and α-Glucosidase Inhibitors
Authors: Diéguez-Santana Karel , Puris Amilkar , Rivera-Borroto Oscar M. , Casanola-Martin Gerardo M. , Rasulev Bakhtiyor , González-Díaz Humberto 
Published: September 2022

Introduction:
This report proposes the application of a new Machine Learning algorithm
called Fuzzy Unordered Rules Induction Algorithm (FURIA)-C in the classification of druglike
compounds with antidiabetic inhibitory ability toward the main two pharmacological targets:
α-amylase and α-glucosidase.

Methods:
The two obtained QSAR models were tested for classification capability, achieving satisfactory
accuracy scores of 94.5% and 96.5%, respectively. Another important outcome was to
achieve various α-amylase and α-glucosidase fuzzy rules with high Certainty Factor values. Fuzzy-
Rules derived from the training series and active classification rules were interpreted. An important
external validation step, comparing our method with those previously reported, was also
included.

Results:
The Holm’s test comparison showed significant differences (p-value<0.05) between
FURIA-C, Linear Discriminating Analysis (LDA), and Bayesian Networks, the former beating the
two latter according to the relative ranking score of the Holm’s test.

Conclusion:
From these results, the FURIA-C algorithm could be used as a cutting-edge technique
to predict (classify or screen) the α-amylase and α-glucosidase inhibitory activity of new compounds
and hence speed up the discovery of new potent multi-target antidiabetic agents.
A Number of the N-terminal RASSF Family: RASSF7
Authors: Xu Yang , Du Wei , Xiao Yongshuang , Gao Keyu , Li Jie , Li Shuofeng 
Published: September 2022

Abstract:
The Ras association domain family 7 (RASSF7, also named HRC1), a potential tumor-related gene, located
on human chromosome 11p15, has been identified as an important member of the N-terminal RASSF family. Whereas,
the molecular biological mechanisms of RASSF7 in tumorigenesis remain to be further established. We perform a
systematic review of the literature and assessment from PUBMED and MEDLINE databases in this article. RASSF7
plays a significant role in mitosis, microtubule growth, apoptosis, proliferation and differentiation. Many research
literature shows that the RASSF7 could promote the occurrence and advance of human tumors by regulating Aurora B,
MKK4, MKK7, JNK, YAP, MEK, and ERK, whereas, it might inhibit c-Myc and thus lead to the suppression of tumorigenesis.
The pregulation of RASSF7 often occurs in various malignancies such as lung cancer, neuroblastoma,
thyroid neoplasm, hepatocellular cancer, breast cancer and gastric cancer. The expression stage of RASSF7 is positively
correlated with the tumor TNM stage. In this review, we primarily elaborate on the acknowledged structure and
progress in the various biomechanisms and research advances of RASSF7, especially the potential relevant signaling
pathways. We hope that RASSF7 , a prospective therapeutic target for human malignancies, could play an available
role in future anti-cancer treatment.
Neuroinflammation: Molecular Mechanisms And Therapeutic Perspectives
Authors: Meccariello Rosaria , Marino Marianna , Mele Elena , Pastorino Grazia Maria Giovanna , Operto Francesca Felicia , Santoro Antonietta , Viggiano Andrea 
Published: September 2022

Background:
Neuroinflammation is a key component in the etiopathogenesis of neurological diseases and brain aging. This process involves the brain immune system that modulates synaptic functions and protects neurons from infection or damage. Hence, the knowledge of neuroinflammation related-pathways and modulation by drugs or natural compounds is functional to the development of therapeutic strategies aimed at preserving, maintaining and restoring brain health.

Objective:
This review article summarizes the basics in neuroinflammation and related signaling pathways, the success of dietary intervention in clinical practice and the possible development of RNA-based strategies for the treatment of neurological diseases.

Methods:
Pubmed search (2012-2022); keywords: neuroinflammation and molecular mechanisms in combination with diet, miRNA and non-coding RNA.

Results:
Glial cells play a crucial role in neuroinflammation, but several pathways can be activated in response to different inflammatory stimuli, inducing cell death by apoptosis, pyroptosis or necroptosis. Dietary intervention has immunomodulatory effects and could limit the inflammatory process induced by microglia and astrocytes. Thus by ihibiting neuroinflammation and improving the symptoms of a variety of neurological diseases, diet exerts pleiotropic neuroprotective effects independently from the spectrum of pathophysiological mechanisms underlying the specific disorder. Furthermore, data from animal models revealed that altered expression of specific non-coding RNAs, in particular microRNAs, contributes to neuroinflammatory diseases; consequently, RNA-based strategies may be promising to alleviate the consequences of neuroinflammation.

Conclusion:
Further studies are needed to identify the molecular pathways and the new pharmacological targets in neuroinflammation to lay the basis for more effective and selective therapies to be applied, in parallel to dietary intervention, in the treatment of neuroinflammation-based diseases.
A Review of Perception-Based Navigation System for Autonomous Mobile Robots
Authors: Fusic S. Julius , Sugumari T.  
Published: September 2022

Abstract:Perception-based navigation systems have become more popular in robotic applications such as autonomous moving vehicles in hospitals, logistics, packing and forwarding, mines, military, defense, consumer robots, building surveillance, rescuing and carrying a child or physically challenged people, and so on, due to the need, advanced development, and large influence. To improve positioning, localization, and path planning on obstacle-free trajectories, several navigation designs have been developed. In this study, we attempt to analyze various navigation methods and technologies applied by mobile robots in various applications. On paths without obstacles, a number of navigation designs have been created to enhance positioning, localization, and path planning. An overview of many navigation technologies is given in this article. The paper focuses on Measurand-based navigation of mobile robot applications in a diverse environment by taking into account previous research works. Additionally, there is a comparison of technologies, methodologies, applications, algorithms for error reduction, and different kinds of perception systems, in addition to metrics like accuracy and usability. This limited study focuses on the integration of an antenna with an IMU-based navigation system that is suited for all environments, as well as some future trends to detect to aid in the profound-implication of navigation system enhancement in robotic applications.
Association with and Dissociation from Groups in Response to Personal and Social Identity Threats: The Role of Self-Construal and Anxiety
Authors: Dariusz Drążkowski 
Published: September 2022

Background:
In response to an identity threat, some individuals may dissociate themselves from social groups, whereas others may associate with these groups.

Objective:
This study examined how threats to social and personal identity influence the processes of association/dissociation with in-groups and out-groups in individuals with different self-construal types. Further, it explored whether the associative/dissociative processes are linked with physiological anxiety aroused by the identity threat.

Methods:
A total of 204 women were randomly assigned to one of six conditions: identity threat (social vs. personal vs. no threat) and primed self-construal (independent vs. interdependent).

Results and Discussion:
Under identity threat, independent women may dissociate from their out-group, which is manifested in lower ratings for masculine consumer brands. In contrast, interdependent women may associate with their in-group as well as the out-group, which is manifested as higher ratings for feminine and masculine brands, respectively. These findings provide evidence that the response to an identity threat depends not on the type of identity threat but rather on the type of self-construal. The results showed an unexpected possibility of association with the out-group when faced with an identity threat. However, physiological arousal did not mediate these effects, suggesting that associative/dissociative processes are a product of the maintenance of a positive self-concept rather than psycho-physiological efforts to regulate arousal.

Conclusion:
This work contributes to the existing literature on the impact of personal and social identity threats on in-group and out-group association/dissociation, evaluated using brand ratings representing these groups. The results also have several practical implications for marketers.
Pediatric Basic Life Support among Nursing Students in Jordan: Stimulation-Based Education
Authors: Kasem Abedallah , Abuhammad Sawsan 
Published: September 2022

Background:
In the context of seeking to reduce the neonatal mortality rate (NMR) in Jordan, there is a need to use simulation to teach and train nursing students in pediatric basic life support (PBLS) skills. This study aims to measure the preservation of PBLS knowledge and determine whether active observation of an immersive simulation using a simple checklist would improve PBLS skills.

Methods:
A single group pretest-posttest approach design was applied in the Jordan University of Science and Technology (JUST) pediatric simulation lab for 108 nursing students.

Results:
The result of the paired samples t-test showed that there was a statistically significant increase in PBLS knowledge between pretest and post-test. The result of the paired samples t-test in the group showed that there was a statistically significant enhancement in PBLS skills between pretest and post-test. PBLS skills at pretest were poor (M = 4.31, SD = 1.12). It was reported that place of residence is a significant predictor of knowledge in PBLS (p <.05).

Conclusion:
The results of this study showed that a simulation-based PBLS course positively impacted knowledge and skills in pediatric BLS. The findings also suggest that policymakers should establish continued professional development BLS training programs for healthcare providers, especially nurses, which can be provided at low cost in most of the settings around the country.
TAGUCHI OPTIMIZATION OF MULTIPLE PERFORMANCE CHARACTERISTICS IN THE ELECTRICAL DISCHARGE MACHINING OF THE TIGR2
Authors: Akıncıoğlu Sıtkı 
Published: September 2022

Electrical discharge machining (EDM) provides many advantages for the shaping of metallic materials. It also provides better surface quality for Ti alloys used in the defense industry. In this study, experiments were carried out with different EDM parameters using the Titanium (Gr2) alloy. A number of novel industrial processes have been developed as a result of advances in technology. For a product to be developed, these novel approaches must be utilized to determine optimum parameters. The Taguchi method was applied in the experiments with EDM. The impact the test parameters had on the performance characteristics of tool wear rate, material removal rate, depth, and surface roughness were analyzed by the variance analysis (ANOVA). Quadratic regression analyses were carried out to reveal the correlation between the experimental results and the predicted values. According to the ANOVA results for material removal rate (MRR), tool wear rate (TWR), depth, and surface roughness, the most effective factor was amperage, at 99.66%, 99.56%, 87.95%, and 81.12%, respectively. The best value for average surface roughness was determined to be 3.29 µm obtained at 120 μs time-on, 8 A, and 40 μs time-off.