Research Studies Research Articles

Berberine Contents as a Quality Marker in Medicinal Plants and Amounts of Berberine Passing into Serum

Background: Berberine is an alkaloid found in some medicinal plants. Berberine-containing plants have traditionally been used in the treatment of diseases since ancient times. Berberine is a natural compound that has an important place in traditional Chinese medicine. Currently, berberine is being evaluated extensively in clinical trials and is one of the natural products on which most scientific research studies have been published. Numerous clinical and pharmacological research results have been published on the therapeutic effect of berberine against cancer, diabetes, and heart disease Objective: The first purpose of this review is to display the berberine content of plants found in different regions of the world, and the second purpose is to provide the amount of berberine passing into the serum. Methods: Herbal supplements and extracts prepared from plants containing berberine are commercially marketed. The content of berberine in plants varies widely, and berberine is a quality indicator for many medicinal plants. Results: Different analytical methods have been developed for reliable berberine analysis. Plant and serum berberine levels reported between the years 2013 and 2022 in journals covered by SCI are collected in this review article. Conclusion: We hope that this overview of berberine amounts will be useful in future pharmaceutical and pharmacokinetic studies.

Performance of sugarcane molasses in concrete under hot weather

AbstractThe present research studies the effect of adding sugar factory waste sugarcane molasses as an alternative to chemical inhibitory additives manufactured on concrete cast during hot weather in the summer of Iraq. The current study includes a study of the setting time for cement paste and workability for fresh concrete and some mechanical properties of hardened concrete with sugarcane molasses using percentage 0–0.3% of cement weight. The study also included studying the value of pH of concrete to investigate the effect of sugarcane molasses on reinforced concrete. The results showed that the sugarcane molasses can be used by about 0.1% of cement weight for medium projects and between 0.1 and 0.2% for large projects. It was also found that the compression strength increased by about 11.5% and the indirect tensile strength increased by about 7.5 and 7.4% for splitting and flexural test, respectively for concrete mixtures containing 0.2% of sugarcane molasses.

The Implementation of Waiters And Waitresses’ Upselling Techniques At Ticket’s Cafe of Horison Ultima Makassar Hotel

This study aims to analyze the use of upselling techniques among waiters and waitresses at the Ticket’s Café in Hotel Horison Ultima Makassar. This analysis includes the answer to whether or not they use upselling techniques, how they use it, and what the result is. The data in this research are collected during observation and interview. This research studies the waiters and waitresses along with their superiors. The data are then analyzed with descriptive qualitative method which includes data reduction, presentation and conclusion drawing. The result of this research is that the waiter and waitresses have been proven to use some upselling techniques; however the implementation is not as effective as expected because the number of waiters and waitresses is not enough to deliver the best impacts of the techniques and not all of them use the right upselling techniques.

Plain language summary and patient perspective of the American Society for Clinical Oncology guideline: management of stage 3 non-small-cell lung cancer.

This is a plain language summary of a guideline on the management of stage 3 non-small-cell lung cancer, also known as NSCLC. This guideline was written by the American Society for Clinical Oncology (ASCO for short) and published in the Journal of Clinical Oncology. The purpose of the ASCO guideline is to provide recommendations to healthcare professionals in the US including oncologists, surgeons, pathologists, radiologists, and nurses on how best to diagnose and treat people with stage 3 NSCLC. The ASCO guideline is based on the latest research and scientific evidence to make certain the recommendations are up to date and based on reliable data and best practice. In 2021, a group of experts were asked by ASCO to form an Expert Panel. The Expert Panel reviewed the results of 127 clinical research studies on NSCLC that were done between 1990 and 2021. They looked at how NSCLC had been diagnosed and treated in these studies, as well as at patients' survival and quality of life. The Expert Panel used these findings and their own expertise to form their recommendations and produce the 2021 ASCO Guideline called 'Management of Stage 3 Non-Small-Cell Lung Cancer: ASCO Guideline'. The guideline aims to answer the following questions: What are the most precise ways to confirm and stage NSCLC in people suspected of having a stage 3 disease? Which patients with stage 3 NSCLC can be treated most successfully with surgery? Which patients who can be treated with surgery could also have an additional therapy before their surgery? Which patients who can be treated with surgery could also have an additional treatment after their surgery? Which treatment and/or management is most suitable for patients who cannot have surgery?

Herbs Used for the Management of Hypertension: A Systematic Review

Background: Hypertension is characterized by persistent high blood pressure and has emerged as a critical risk factor for severe cardiovascular diseases. Although several drugs have been designated to reduce blood pressure, these drugs can potentially cause side effects for patients. Therefore, medicinal plants are used to complement conventional drugs to treat various ailments. Methods: This study reviews the anti-hypertensive potential of herbs and plants and their mechanism of action in reducing blood pressure at their evaluated effective doses. Databases such as PubMed, Scopus, Science Direct, and Google Scholar were used to search articles from January 2016 to Sept 2022. The key search terms included “hypertension”, “lowers blood pressure”, “anti-hypertensive”, and “plants”. These generated 807 documents and using the PRISMA guidelines, thirty plants were identified for this review. Research studies with similar plant parts extracted from similar solvents, more than one dose, and animal models with a positive control were considered in this review. Studies that did not show significant blood pressure reduction were excluded. Results: Based on this criterion, the mechanism of actions of these plants was thematically grouped into three categories, namely 1) antioxidant, 2) angiotensin-converting enzyme (ACE) inhibition, and 3) calcium influx in vascular smooth muscle. The effective doses, plant parts used, and traditional medicine usage are presented in this review. Conclusion: Further research is highly recommended to identify the active compounds and to potentially develop them into anti-hypertensive drugs as well as to establish the safe doses and standardization of these plant extracts. This review is partially funded by grants from the Ministry of Higher Education.

Development of compliance theory based on self-regulation in chronic kidney failure patients on hemodialysis

Self-management in regulating diet, fluids, activities, and medication in chronic renal failure patients which getting hemodialysis is still worse. This research aimed to develop the theory of compliance based on self-regulation to increase patient obedience and awareness. A cross-sectional approach of 130 respondents was recruited using simple random sampling. Structural equation modeling partial least square (SEM-PLS) was the statistical analysis for this study. All indicators in the outer model showed outer loading value >0.7, it declared feasible to predict each of the latent variables. The R-square value of appraisal latent was 0.576, Coping was 0.897, and self-care compliance was 0.713. The model was relevant when applied in other research studies with a Q-Square value=0.832. The goodness of fit (GoF) was 0.832>0.36, which means that the model was applied well. The appraisal variable is the strongest variable that influences coping, based on the hypothesis test. The self-regulation-based compliance model for blood pressure, interdialytic weight gain (IDWG), sodium levels, and functional independence can be developed through analysis of the structural model.

Event-Based Intermittent Formation Control of Multi-UAV Systems Under Deception Attacks.

This article investigates the problem of event-based intermittent formation control for multi-UAV systems subject to deception attacks. Compared to the available research studies on multi-UAV systems with continuous control strategy, the proposed intermittent control strategy saves a large amount of computation resources. An average method is introduced in developing the event-triggered mechanism (ETM) such that the amount of unexpected triggering events induced by uncertain disturbances is greatly reduced. Moreover, such a mechanism can further decrease the average data-releasing rate, thereby alleviating the burden of network bandwidth. Sufficient conditions for multi-UAV systems with deception attacks to achieve the predefined formation are obtained with the aid of Lyapunov stability theory. Finally, the validity of the proposed theoretical results is demonstrated via a simulation example.

Hypoxia A Typical Target in Human Lung Cancer Therapy.

Lung cancer (LC) is the leading cause of cancer-related death globally. Comprehensive knowledge of the cellular and molecular etiology of LC is perilous for the development of active treatment approaches. Hypoxia in cancer is linked with malignancy, and its phenotype is implicated in the hypoxic reaction, which is being studied as a prospective cancer treatment target. The hypervascularization of the tumor is the main feature of human LC, and hypoxia is a major stimulator of neo-angiogenesis. It was seen that low oxygen levels in human LC are a critical aspect of this lethal illness. However, as there is a considerable body of literature espousing the presumed functional relevance of hypoxia in LC, the direct measurement of oxygen concentration in Human LC is yet to be determined. This narrative review aims to show the importance and as a future target for novel research studies that can lead to the perception of LC therapy in hypoxic malignancies.

Evidence and Prospects of Lycopene as Powerful Red Superfood: Modern Approach to Food Science

Abstract: Lycopene is a plant-derived important nutrient belonging to a group of pigments identified as carotenoids. Lycopene has distinctive chemical and structural features contributing to definite biological properties. Lycopene is a powerful antioxidant and prevents cells and tissues from damage caused by singlet oxygen or free radicals. Research studies have shown the healthpromoting potential of lycopene or its metabolites in the prevention of chronic diseases like diabetes, cancer, asthma, metabolic syndrome, arthritis, and cardiovascular diseases. Lycopene is stable for processing like other natural compounds when present in the plant tissue matrix. Over the last few years, the global lycopene market has increased in different sectors like pharmaceuticals, cosmetics, food and dairy products, and other dietary supplements. The most important aspect of lycopene as a superfood is its synergistic nature with other nutrients. The main aim of this review article is to study chemistry, biosynthetic pathways, biotransformation, sources, and acceptable daily intake. Its characterization as a superfood, therapeutic potential, and wide range of applications in the food industry are also studied.

Recent Advances in Nitrogen-Containing Heterocyclic Scaffolds as Antiviral Agents.

This study aims to provide a thorough analysis of nitrogen-containing heterocycles, focusing on their therapeutic implications for the development of targeted and effective antiviral drugs. To better understand how nitrogen-containing heterocycles can be used to create antiviral drugs, this review adopts a systematic literature review strategy to compile and analyze pertinent research studies. It combines information from various fields to understand better the compounds' mode of action and their therapeutic potential. This review paper summarizes data from multiple sources to highlight the promising potential of heterocycles containing nitrogen as promising possibilities for future antiviral treatments. The capacity to engage selectively and modulate critical pathways bodes well for their use in developing new viral therapies. In conclusion, nitrogen-containing heterocycles are shown to be of utmost importance in the field of medicinal chemistry, as emphasized by the review paper. It emphasizes the central importance of chemical insights and pharmacological potential in developing novel and effective antiviral medicines by bringing them together.

Exploring the Pharmacological Potential of Lobelia trigona and its Bioactive Compounds

Aim:: The aim of this in-depth review is to provide an overview of the pharmacologi-cal effects of Lobelia trigona and its bioactive components, highlighting its potential as a source of medicinal agents for various diseases Methods:: This review involved a comprehensive analysis of existing literature and research studies on the pharmacological effects of Lobelia trigona and its bioactive compounds. A bib-liography survey was carried out using various electronic databases like Google Scholar, Sci-enceDirect, Springer, Scopus, PubMed, Wiley, etc., and other offline as well as online aca-demic libraries were also used for the bibliography survey and compilation of data. Results:: Lobelia trigona was found to exhibit diverse pharmacological effects, primarily me-diated by bioactive alkaloids, such as lobeline, lobelanidine, and lobelanine. It demonstrated bronchodilator effects with potential applications in respiratory conditions, analgesic and anti-inflammatory properties for treating painful and inflammatory conditions, and cardiovascular effects, including vasodilation and hypotensive effects. The alkaloid lobeline was reported to have promising anti-addictive effects, particularly in smoking cessation. Nanocarrier-based formulations have the potential to address limitations, improve dosing schedules, and enhance the pharmacological effects of Lobelia trigona. Conclusion:: Lobelia trigona demonstrates diverse pharmacological effects, primarily attribut-ed to its bioactive alkaloids. It holds promise as a source of medicinal agents for a range of diseases. The potential synergy between the pharmacological effects of Lobelia trigona and nanocarrier technology highlights the significance of nanotechnology in improving Lobelia trigona-based therapeutics. However, further research is warranted to determine the clinical effectiveness, safety, biocompatibility, and long-term effects of nanocarrier-based Lobelia trigona formulations in different disease models.

Nutritional Status in Leprosy Patients: A Systematic Review and Meta-analysis.

Leprosy, a chronic mycobacterial disease, is frequently accompanied by malnutrition. However, it is important to regularly assess the nutritional state of leprosy patients in a resource-poor nation like India, where undernutrition is widespread. This study aimed to compare the nutritional status of leprosy patients to that of normal individuals using the body mass index. The electronic databases PubMed, Google Scholar, and Embase were used to conduct an open literature search. From 1st January 2000 to 31st January 2023, all articles were screened using the following MeSH terms: (nutrition OR body mass index OR body weight) AND (leprosy OR lepra) to find possibly relevant articles. This meta-analysis includes five research studies with a total of 1173 individuals (363 patients in the leprosy group and 810 patients in the non-leprosy group). The weighted mean difference (WMD) for BMI studies was -17.88 (95% CI -27.65 to -8.12), showing that there was a significant difference in BMI < 18.5 between leprosy patients and non-leprosy patients. There was a significant difference in DDS score and HFIAS score between patients with leprosy and non-leprosy. In a total of 342 leprosy patients, 206 developed deformities. This research increases our understanding of nutrition and leprosy. The results found that people with leprosy are nutritionally at a distinct disadvantage when compared to non-leprosy patients. It emphasises the several ways in which diet may generate circumstances that increase the risk of leprosy.

Veratrilla baillonii Franch alleviate the symptoms of diabetes in type 2 diabetic rats induced by high-fat diet and streptozotocin

Our previous research studies have shown that Veratrilla baillonii Franch, a food supplement used by ethnic minorities in Southwest China, has multiple pharmacological activities, such as detoxification, anti-inflammatory, antioxidant, and anti-insulin resistance. However, the detailed signal pathways for its salutary effect on damages in multiple organs due to type 2 diabetes mellitus (T2DM) remains unclear. The current study is to evaluate the therapeutic effects of V. baillonii on T2DM rats and to explore the underlying mechanisms. The T2DM rat model was successfully established by a high-sugar and high-fat diet (HFD) combination with intraperitoneal injection of a small dose of streptozotocin (STZ, 35 mg/kg). Biochemical analysis and histopatholgical examinations were conducted to evaluate the anti-diabetic potential of water extracts of V. baillonii (WVBF). The results showed that the WVBF treatment can improve hyperglycemia and insulin resistance, ameliorate the liver, kidney and pancreas injuries via decreasing inflammatory cytokines such as IL-6 and TNF-α, and oxidative damages. Further investigation suggested that WVBF modulates the signal transductions of the IRS1/PI3K/AKT/GLUT4 and AMPK pathways. These findings demonstrate potentials of WVBF in the treatment of T2DM and possible mechanisms for its hepatoprotective activities.

Effective Instruction and Curricular Models: What Do We Know About Student Learning Outcomes in Physical Education?

This essay aims to elucidate effective teaching through the utilization of instructional models in physical education. In this essay, Rink’s seven essential teaching tasks provide the foundational structure, complemented by an examination of four legitimate student outcomes in physical education: physical, cognitive, social, and affective domains. A literature review of 222 research studies on teaching effectiveness of nine instructional models reporting on teacher behaviors and student outcomes was coded following a four-step reliability coding process to establish a consensus on the articles included. This essay serves as a resource for comprehending the application of instructional models in physical education curricula, highlighting the need for continuous research into their efficacy and the replication of studies to validate outcomes across various educational settings. In addition, it highlights the importance of integrating K–16 teacher assessment data within these models to demonstrate the educational impact across learning domains.

Supervised Rank Aggregation (SRA): A Novel Rank Aggregation Approach for Ensemble-based Feature Selection

Background: Feature selection (FS) is critical for high dimensional data analysis. Ensemble based feature selection (EFS) is a commonly used approach to develop FS techniques. Rank aggregation (RA) is an essential step in EFS where results from multiple models are pooled to estimate feature importance. However, the literature primarily relies on static rule-based methods to perform this step which may not always provide an optimal feature set. The objective of this study is to improve the EFS performance using dynamic learning in RA step. Method: This study proposes a novel Supervised Rank Aggregation (SRA) approach to allow RA step to dynamically learn and adapt the model aggregation rules to obtain feature importance.Method: This study proposes a novel Supervised Rank Aggregation (SRA) approach to allow RA step to dynamically learn and adapt the model aggregation rules to obtain feature importance. Results: We evaluate the performance of the algorithm using simulation studies and implement it into real research studies, and compare its performance with various existing RA methods. The proposed SRA method provides better or at par performance in terms of feature selection and predictive performance of the model compared to existing methods. Conclusion: SRA method provides an alternative to the existing approaches of RA for EFS. While the current study is limited to the continuous cross-sectional outcome, other endpoints such as longitudinal, categorical, and time-to-event data could also be used.

Wearable Activity Trackers: A Survey on Utility, Privacy, and Security

Over the past decade, wearable activity trackers (WATs) have become increasingly popular. However, despite many research studies in different fields (e.g. psychology, health, and design), few have sought to jointly examine the critical aspects of utility (i.e., benefits brought by these devices), privacy, and security (i.e., risks and vulnerabilities associated with them). To fill this gap, we reviewed 236 studies that researched the benefits of using WATs, the implications for the privacy of users of WATs, and the security vulnerabilities of these devices. Our survey revealed that these devices expose users to several threats. For example, WAT data can be mined to infer private information, such as the personality traits of the user. Whereas many works propose empirical findings about users’ privacy perceptions and their behaviors in relation to privacy, we found relatively few studies researching technologies to better protect users’ privacy with these devices. This survey contributes to systematizing knowledge on the utility, privacy, and security of WATs, shedding light on the state-of-the-art approaches with these devices, and discussing open research opportunities.

Intimate Partner Violence-Related Brain Injury: Unmasking and Addressing the Gaps.

Intimate partner violence (IPV) is a significant, global public health concern. Women, individuals with historically underrepresented identities, and disabilities are at high risk for IPV and tend to experience severe injuries. There has been growing concern about the risk of exposure to IPV-related head trauma, resulting in IPV-related brain injury (IPV-BI), and its health consequences. Past work suggests that a significant proportion of women exposed to IPV experience IPV-BI, likely representing a distinct phenotype compared with BI of other etiologies. An IPV-BI often co-occurs with psychological trauma and mental health complaints, leading to unique issues related to identifying, prognosticating, and managing IPV-BI outcomes. The goal of this review is to identify important gaps in research and clinical practice in IPV-BI and suggest potential solutions to address them. We summarize IPV research in five key priority areas: (1) unique considerations for IPV-BI study design; (2) understanding non-fatal strangulation as a form of BI; (3) identifying objective biomarkers of IPV-BI; (4) consideration of the chronicity, cumulative and late effects of IPV-BI; and (5) BI as a risk factor for IPV engagement. Our review concludes with a call to action to help investigators develop ecologically valid research studies addressing the identified clinical-research knowledge gaps and strategies to improve care in individuals exposed to IPV-BI. By reducing the current gaps and answering these calls to action, we will approach IPV-BI in a trauma-informed manner, ultimately improving outcomes and quality of life for those impacted by IPV-BI.

Calibration of Transformer-Based Models for Identifying Stress and Depression in Social Media

In today’s fast-paced world, the rates of stress and depression present a surge. People use social media for expressing their thoughts and feelings through posts. Therefore, social media provide assistance for the early detection of mental health conditions. Existing methods mainly introduce feature extraction approaches and train shallow machine learning (ML) classifiers. For addressing the need of creating a large feature set and obtaining better performance, other research studies use deep neural networks or language models based on transformers. Despite the fact that transformer-based models achieve noticeable improvements, they cannot often capture rich factual knowledge. Although there have been proposed a number of studies aiming to enhance the pretrained transformer-based models with extra information or additional modalities, no prior work has exploited these modifications for detecting stress and depression through social media. In addition, although the reliability of a machine learning (ML) model’s confidence in its predictions is critical for high-risk applications, there is no prior work taken into consideration the model calibration. To resolve the above issues, we present the first study in the task of depression and stress detection in social media, which injects extra-linguistic information in transformer-based models, namely, bidirectional encoder representations from transformers (BERT) and MentalBERT. Specifically, the proposed approach employs a multimodal adaptation gate for creating the combined embeddings, which are given as input to a BERT (or MentalBERT) model. For taking into account the model calibration, we apply label smoothing. We test our proposed approaches in three publicly available datasets and demonstrate that the integration of linguistic features into transformer-based models presents a surge in performance. Also, the usage of label smoothing contributes to both the improvement of the model’s performance and the calibration of the model. We finally perform a linguistic analysis of the posts and show differences in language between stressful and nonstressful texts, as well as depressive and nondepressive posts.

Meta-analysis of the effectiveness of ethnomathematics-based learning on student mathematical communication in Indonesia

This meta-analysis aims to determine the effect of ethnomathematics learning on students’ mathematical communication skills. Data from 28 research studies, including sample size, standard deviation, mean for both experimental and control groups, and other information, were collected using descriptive analysis. Data analysis techniques used meta-analysis on forest plots, with analytical techniques including heterogeneity testing, calculation of effect sizes, calculation of summary effects using random effects models, and identification of publication bias. The results showed that ethnomathematics-based learning improves students’ mathematical communication skills. The effectiveness of ethnomathematical and conventional learning on students’ mathematical communication skills is combined reliably. The effect size of ethnomathematical learning was 0.97 (95%-CI: 0.74; 1.20). Ethnomathematics-based learning is more effective when compared to traditional.

Model Predictive Control of Magnetic Helical Swimmers in Two-Dimensional Plane

Magnetic micro/mini-swimmers have a great potential application in biomedical research and have gained broad attention. Recent research studies focus on the automatic control methods of magnetic micro/mini-swimmers, such as artificial intelligence methods. However, their autonomous manipulation remains a challenge since they are subject to various disturbances from the external environment and model uncertainties. The current methods employ a status observer to estimate these disturbances and uncertainties. In this paper, we apply a data-driven technique that utilizes the nonlinear approximation ability of neural networks (NNs). To be specific, a flexible structure of NNs, Broad Learning System (BLS), is employed to model the input-output mapping relationship between the direction of the rotating magnetic field and the swimming direction of the helical miniature swimmer. Then, according to the dual-variable decoupling control, a levitation controller is formulated and a path following controller is proposed based on a planar three-degree-of-freedom model of magnetic helical swimmers, which is inspired by the model of wheeled mobile robots. Simulations and experiments are conducted to quantitatively validate the proposed control method using different planar paths. The experiment results show that the mean absolute error of the path following control is about 3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\%$</tex-math> </inline-formula> of the body length which is less than 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$mm$</tex-math> </inline-formula> . Our proposed control method provides a preliminary study to alleviate the impact of disturbances and uncertainties on the control performance of magnetic micro/mini-swimmers. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is mainly motivated by the potential application of artificial intelligence methods in magnetic micro/mini-robot community, especially for the applications that reject disturbances and uncertainties. In practice, a path planner is employed to compute a pre-defined reference path that connects the start and the targeted locations. Then our control method is applied to the magnetic helical swimmer and it is guided to follow the reference path. Tackling external disturbances and model uncertainties is still challenging during the control progress. Neural network-based technique is an intuitive approach since their nonlinear modeling ability and generalization are suitable for estimating these disturbances and uncertainties. As for training the neural-network model, the training data about the angle parameters should be recorded by manual control of the helical swimmer. These angle parameters define the rotating axis of the uniform rotating magnetic field and the self-rotating axis of the magnetic helical swimmer. According to the planar motion model, the optimal controller is formulated using the feedback distance error and angle error, and the sum of the control signal and the prediction of the compensating model is used as the final control input. Our electromagnetic coil system features easy operation and configuration of cameras or other sensors. Simulations and experiments validate the performance of the neural network-based compensating method and the proposed optimal control method using magnetic micro/mini-swimmers.