Development Process Research Articles

Premixed calcium silicate-based ceramic sealers promote osteogenic/cementogenic differentiation of human periodontal ligament stem cells: A microscopy study.

To evaluate the effects of premixed calcium silicate based ceramic sealers on the viability and osteogenic/cementogenic differentiation of human periodontal ligament stem cells (hPDLSCs). The materials evaluated were TotalFill BC Sealer (TFbc), AH Plus Bioceramic Sealer (AHPbc), and Neosealer Flo (Neo). Standardized discs and 1:1, 1:2, and 1:4 eluates of the tested materials were prepared. The following in vitro experiments were carried out: ion release, cell metabolic activity 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, cell migration, immunofluorescence experiment, cell attachment, gene expression, and mineralization assay. Statistical analyses were performed using one-way ANOVA followed by Tukey's post hoc test (p < .05). Increased Ca2+ release was detected in TFbc compared to AHPbc and Neo (*p < .05). Biological assays showed a discrete cell metabolic activity and cell migration in Neo-treated cell, whereas scanning electronic microscopy assay exhibited that TFbc group had a better cell adhesion process of substrate attachment, spreading, and cytoskeleton development on the niche-like structures of the cement than AHPbc and Neo. The sealers tested were able to induce overexpression of the CEMP-1, ALP, and COL1A1 genes in the first days of exposure, particularly in the case of TFbc (***p < .001). All materials tested significantly increased the mineralization of hPDLSCs when compared to the negative control, although more pronounced calcium deposition was observed in the TFbc-treated cells (***p < .001). Our results suggested that TFbc promotes cell differentiation, both by increasing the expression of key osteo/odontogenic genes and by promoting mineralization of the extracellular matrix, whereas this phenomenon was less evident in Neo and AHPbc. RESEARCH HIGHLIGHTS: TFbc group had a better cell adhesion process of substrate attachment, spreading, and cytoskeleton development on the niche-like structures of the cement than AHPbc and Neo. The sealers tested were able to induce overexpression of the CEMP-1, ALP, and COL1A1 genes in the first days of exposure, particularly in the case of TFbc. All materials tested significantly increased the mineralization of hPDLSCs when compared to the negative control, although more pronounced calcium deposition was observed in the TFbc-treated cells.

Ligand- and Structure-based Approaches for Transmembrane Transporter Modeling.

The study of transporter proteins is key to understanding the mechanism behind multi-drug resistance and drug-drug interactions causing severe side effects. While ATP-binding transporters are well-studied, solute carriers illustrate an understudied family with a high number of orphan proteins. To study these transporters, in silico methods can be used to shed light on the basic molecular machinery by studying protein-ligand interactions. Nowadays, computational methods are an integral part of the drug discovery and development process. In this short review, computational approaches, such as machine learning, are discussed, which try to tackle interactions between transport proteins and certain compounds to locate target proteins. Furthermore, a few cases of selected members of the ATP binding transporter and solute carrier family are covered, which are of high interest in clinical drug interaction studies, especially for regulatory agencies. The strengths and limitations of ligand-based and structure-based methods are discussed to highlight their applicability for different studies. Furthermore, the combination of multiple approaches can improve the information obtained to find crucial amino acids that explain important interactions of protein-ligand complexes in more detail. This allows the design of drug candidates with increased activity towards a target protein, which further helps to support future synthetic efforts.

Exploring the Biochemical Mechanisms of Fluoroquinolone Compounds against Tuberculosis by Utilizing Molecular Docking and Quantitative Structure-amino Acid Relationship

Background: Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb). It is one of the leading causes of death of 1.5 million people each year. TB can be treated by directly observed treatment short course (DOTS), but due to multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis, consequences can be devastating if the single DOTS dose is missed by the patient. MDR and XDR-TB require much more attention and time to control the infection. The longer period of tuberculosis treatment has side effects and it is expensive. Objectives: This alarming condition demands the development of novel processes to diagnose the disease in its early stage as well as to produce more promising antimicrobial chemotherapeutics. The current study aimed to explore molecular mechanisms involving docking simulation-based quantitative structureamino acid relationship (QSAAR) in order to have a better understanding of the interactions between the fluoroquinolones and Mtb DNA gyrase. Methods: In this study, 24 fluoroquinolone (FQ) compounds present in the literature were selected and docked against the Mtb DNA gyrase. Further, the relationship between the minimum inhibitory concentration of the compounds and interacting amino acids was assessed using QSAAR. Results: The study has established a novel method of formulating a quantitative structure-amino acid relationship. A significant correlation (R-value=0.829) between biological activity and the docked amino acid residues responsible for producing anti-tubercular activities has been obtained. Conclusion: The predicted residues captured in the developed model have been explored to report the Mtb virulence.

Developing an international consensus reporting guideline for intervention Fidelity in non-drug, non-surgical trials: The ReFiND protocol

BackgroundInadequate reporting of fidelity to interventions in trials limits the transparency and interpretation of trial findings. Despite this, most trials of non-drug, non-surgical interventions lack comprehensive reporting of fidelity. If fidelity is poorly reported, it is unclear which intervention components were tested or implemented within the trial, which also hinders research reproducibility. This protocol describes the development process of a reporting guideline for fidelity of non-drug, non-surgical interventions (ReFiND) in the context of trials. MethodsThe ReFiND guideline will be developed in six stages. Stage one: a guideline development group has been formed to oversee the guideline methodology. Stage two: a scoping review will be conducted to identify and summarize existing guidance documents on the fidelity of non-drug, non-surgical interventions. Stage three: a Delphi study will be conducted to reach consensus on reporting items. Stage four: a consensus meeting will be held to consolidate the reporting items and discuss the wording and structure of the guideline. Stage five: a guidance statement, an elaboration and explanation document, and a reporting checklist will be developed. Stage six: different strategies will be used to disseminate and implement the ReFiND guideline. DiscussionThe ReFiND guideline will provide a set of items developed through international consensus to improve the reporting of intervention fidelity in trials of non-drug, non-surgical interventions. This reporting guideline will enhance transparency and reproducibility in future non-drug, non-surgical intervention research.

Neighborhood Gentrification and Food Insecurity Among Urban Older Adults: Evidence From New York City.

Gentrification is a prevalent neighborhood development process in urban areas across the United States. Prior studies have identified the influence of gentrification on late-life health and quality of life, yet little is known about its relationship with food insecurity, an important public health issue for older adult populations. Using New York City as a case study, this study investigated associations between living in a gentrifying neighborhood and food insecurity, as well as the mediating roles of neighborhood environment factors-social cohesion, public transportation, and food environment. This study adopted 2 waves of annual data from the Poverty Tracker Study (2015-2016; N = 703) merged with American Community Survey and spatial data sets to measure gentrification and neighborhood factors. Adjusted logistic regressions were used to examine the associations between gentrification and food insecurity. Further mediation analyses were conducted to test the mechanisms of such associations. Older adults in gentrifying neighborhoods were more likely to have food insecurity than those in moderate- to high-income neighborhoods. Compared to low-income neighborhoods, older adults in gentrifying neighborhoods had a lower likelihood of reporting food insecurity. Two significant mediators were found when comparing gentrification with moderate- to high-income neighborhoods: social cohesion and healthy food outlets. This study highlights the importance of gentrification in determining late-life food insecurity and identifies possible mechanisms with policy and social service implications to reduce the risk of food insecurity in urban areas.

Potential of Growing Energy Crops and Then Producing Liquid Fuels in Marginal Land: A China Scenario

To explore the potential of growing energy crops and then producing liquid fuels in marginal land in China, in this paper, the status quo of existing biomass resources and marginal land utilization in China have been first analyzed and the development process of biomass liquid fuels has then been reviewed. Secondly, using ethyl levulinate (EL) as our research subject, the production capacity of growing energy crops in marginal land and their potential to prepare liquid fuels have been explored. Finally, the problems in developing marginal land have been summarized, and proposed policy recommendations for marginal land development, energy crop cultivation, and liquid fuel development suitable for Chinese conditions. The results showed that the potential of sweet sorghum, cassava, jatropha curcas, and switchgrass cultivation in China in producing is 75.76 million tonnes, 1.52 million tonnes, 4.57 million tonnes, and 5.16 million tonnes, respectively. Among these crops, sweet sorghum and switch grass have a higher production capacity and are more suitable to be planted on marginal land and used to produce liquid fuels. The planting of these two crops has absorbed about a 111.11 million tonnes and 7.57 million tonnes of carbon dioxide (CO2), respectively, presenting significant carbon sequestration and oxygen-producing effects, which provides a theoretical basis for the analysis of land use change.

Development and Validation of the Attitude Towards Surrogacy Scale in a Turkiye Sample

Bacground: Surrogacy is one of the options a lot of ethical, legal and psychological controversy. Surveying attitudes toward surrogacy plays an important role in building awareness of this phenomenon in the society. In this study authors aimed to develop and validate a scale to assess the attitudes towards surrogacy. Methods: In this study cross-sectional design was implemented. Development process of the Attitude towards Surrogacy Scale (ATSS) included items development based on literature reviews, other existing questionnaires, confrmatory factor analysis (CFA), and reliability analysis using internal consistence coefcients. A total of 272 people residing in Büyükçekmece and Beylikdüzü districts of Istanbul were included in the study. Firstly, conceptual structure and item pool were created for the draft scale created by the researchers. Then, the question pool was submitted to expert opinion. After the expert opinion, a pilot study was applied to the statements in the draft scale. After the test-retest reliability was performed, the data collection phase started. Participants who agreed to participate in the study were reached both face-to-face and online. Convenience sampling method was used to reach the participants. Results: IBM SPSS and IBM AMOS package programmes were used to analyse the data obtained within the scope of the study. In the data analysis, firstly, item analysis was performed for internal consistency reliability. After this stage, structural validity analysis was used. As a result of the analysis, a measurement tool consisting of 4 dimensions and 24 statements expressed as “positive impact, negative impact, legal impact and economic impact” was developed. It has been statistically determined that this measurement tool is valid and reliable. Conclusion: The results obtained show that the scale developed for the perception of surrogacy has validity and reliability. Therefore, the “scale developed for the perception of surrogacy” can be used to measure the perception of surrogacy of people in our country.

Composing Serverless Azure Functions in NodeJS with MySQL Database Integration

This paper delves into the concept and implementation of serverless computing, particularly focusing on Azure Functions as a platform for deploying serverless applications. It introduces the notion of a Function app, a container that amalgamates functions into a single logical unit, thereby simplifying management, deployment, and resource sharing. Serverless computing is elucidated as Function as a Service (FaaS), a paradigm where business logic is executed in the form of functions without the need for manual infrastructure management. Azure Functions enables developers to host and execute business logic seamlessly, without the concerns of provisioning infrastructure. The platform supports a multitude of programming languages, including C#, Java, JavaScript, TypeScript, and Python, offering versatility in development approaches. The paper further explores the utilization of triggers, specifically HTTP triggers, for executing code in response to HTTP requests. It highlights the development process within Visual Studio Code, facilitated by the Azure Functions extension, which allows for the comprehensive creation and deployment of projects. Additionally, the distinction between Consumption service plans and App Service Plans is examined, along with the prerequisite of linking every function app to a storage account. Deployment methodologies, both locally and through the Azure portal, are outlined, along with the capabilities for monitoring logs via the Azure portal’s Monitor section. This comprehensive overview provides insights into leveraging Azure Functions for efficient, scalable, and manageable serverless application development.

Lay User Involvement in Developing Human-centric Responsible AI Systems: When and How?

Artificial Intelligence (AI) is increasingly used in mainstream applications to make decisions that affect a large number of people. While research has focused on involving machine learning and domain experts during the development of responsible AI systems, the input of lay users has too often been ignored. By exploring the involvement of lay users, our work seeks to advance human-centric responsible AI development processes. To reflect on lay users’ views, we conducted an online survey of 1,121 people in the United Kingdom. We found that respondents had concerns about fairness and transparency of AI systems, which requires more education around AI to underpin lay user involvement. They saw a need for having their views reflected at all stages of the AI development lifecycle. Lay users mainly charged internal stakeholders to oversee the development process but supported by an ethics committee and input from an external regulatory body. We also probed for possible techniques for involving lay users more directly. Our work has implications for creating processes that ensure the development of responsible AI systems that take lay user perspectives into account.

THE GROWTH OF ILLEGAL CONSTRUCTION IN THE COASTAL PROTECTIVE STRIPS OF THE STRYI RIVER BASIN

Currently, there is of today, there is practically no information about the current state and land use of coastal protection strips (CPS) and water protection zones in the Stryi river basin. This creates many misunderstandings and abuses during their use and leads to intensive degradation of the ecosystem of both this and other rivers of the Dniester basin into which it flows. Using the Google Earth Pro program, an assessment of the CPS structure in the Stryi River basin was carried out by comparing space images for the past 14 years. The analysis showed that illegal construction within the CPS of the river began after 2009, which creates the danger of possible inundation during floods and the development of erosion processes. This is also a threat to the hydroecosystem of the Stryi River, due to the settlement load on the floodplain, as well as non-compliance with sanitary standards and clogging with household waste.

The third space, student and staff co-creation of gamified informal learning: an emerging model of co-design

This article draws from the authors’ exploration of an innovative third space approach to engaging students with informal learning through the use of co-design and co-creation, which sits outside traditional subject delivery spaces. The third space project, the Digital Citizenship Programme, centres on the transformative experience and dialogic encounter for participants. The third space in this context was constituted by co-design and co-production involving students, alumni, academics and professional service staff. The project evaluated third space activity in terms of co-design, through its development process and in what is achieved by participants’ engagement with it. The aims were to analyse the mutuality and relational aspects of the innovative pedagogic intervention; the development of transferable skills and agentic development in the third space; and the dialogic experience for participants. The research data were collected over a period of three years, using focus groups, co-creation workshop observations and field notes. This project builds on the body of research that focuses on partnerships with students that fall under the umbrella of the third space. The article underlines the importance of co-creation approaches in building the relational and dialogic dynamic in higher education spaces.

Evaluation of sand subgrade seepage erosion caused by buried pipeline leakage

Leakage from buried pipelines can lead to an increase in the water content of the subgrade soils and a rise in the water table, leading to soil loosening, erosion and ultimately the formation of hidden voids and roadway collapses. This study presents a discrete-element method and validates its accuracy by utilising cavity data from model experiments. It investigates the mechanism of seepage erosion resulting from pipe leakage and analyses the development of the soil arch effect. Furthermore, it discusses the influence of sand void ratio and particle size on sand seepage erosion. The results indicate that the erosion area is primarily affected by the void ratio and particle size. In comparison to soil particles ranging from 0.1 to 5 mm and from 2 to 5 mm, those with sizes between 0.1 mm and 2 mm generate areas of erosion and loosening that are approximately 40% larger. The proposed model offers a precise analysis of the developmental process and the extent of seepage erosion, thereby contributing to the prediction of potential road cavity areas based on dynamic changes in key factors such as subgrade soil type and groundwater level.

Punching shear tests and design of UHTCC-enhanced RC slab–column joints with shear reinforcements

Reinforced concrete (RC) flat-slab structures may experience progressive collapse, usually caused by the punching shear failure of slab–column joints. Existing research has shown that the use of shear reinforcements or ultra-high toughness cementitious composites (UHTCCs) in slab–column joints is efficient in improving their punching shear performance. In this study, shear reinforcement was introduced into UHTCC-enhanced RC slab–column joints. Specimens of UHTCC-enhanced slab–column joints were tested considering the effect of shear reinforcements. The cracking development process, bearing capacity and ductility were analysed. Yield line theory and critical shear crack theory were adopted to predict flexural and punching shear capacities, respectively. Finally, the failure patterns of the specimens were distinguished by comparing the predicted punching shear and flexural capacities, taking ductility coefficients into account. The theoretical and test results show the effect of shear reinforcement on the behaviour of UHTCC-enhanced joints. Significant improvements in the bearing capacity and ductility of the joints was achieved by applying shear reinforcement. The failure pattern of the joint varied from premature punching shear failure to flexural-triggered punching shear failure with the application of UHTCC, and this transformation was more pronounced with shear reinforcement applied into the UHTCC-enhanced joint.

Advancing Drug Safety in Drug Development: Bridging Computational Predictions for Enhanced Toxicity Prediction.

The attrition rate of drugs in clinical trials is generally quite high, with estimates suggesting that approximately 90% of drugs fail to make it through the process. The identification of unexpected toxicity issues during preclinical stages is a significant factor contributing to this high rate of failure. These issues can have a major impact on the success of a drug and must be carefully considered throughout the development process. These late-stage rejections or withdrawals of drug candidates significantly increase the costs associated with drug development, particularly when toxicity is detected during clinical trials or after market release. Understanding drug-biological target interactions is essential for evaluating compound toxicity and safety, as well as predicting therapeutic effects and potential off-target effects that could lead to toxicity. This will enable scientists to predict and assess the safety profiles of drug candidates more accurately. Evaluation of toxicity and safety is a critical aspect of drug development, and biomolecules, particularly proteins, play vital roles in complex biological networks and often serve as targets for various chemicals. Therefore, a better understanding of these interactions is crucial for the advancement of drug development. The development of computational methods for evaluating protein-ligand interactions and predicting toxicity is emerging as a promising approach that adheres to the 3Rs principles (replace, reduce, and refine) and has garnered significant attention in recent years. In this review, we present a thorough examination of the latest breakthroughs in drug toxicity prediction, highlighting the significance of drug-target binding affinity in anticipating and mitigating possible adverse effects. In doing so, we aim to contribute to the development of more effective and secure drugs.

Ethnic specifics in birth rates in Kazakhstan in the middle of the 20th century

The purpose of this study is to examine ethnic variations in population fertility in the 1950–1960s, formed in the context of socio-economic development of Kazakhstan. The 1959, 1970, 1989 population censuses, and sta-tistical almanacks “National Economy of Kazakhstan” became the source base of this research. The theory of modernization, interpreted as the transition from traditional to modern society and reflecting the details of ethni-cally differentiated process of demographic development of Kazakhstan in the mid-20th century provided the methodological basis of the research. Ethnic differentiation within the settlement system and socio-economic ac-tivities that developed in Kazakhstan in the 1950–1960s led to ethnically distinct birth rates among Kazakhs and Russians. The demographic potential acquired by Kazakhs in the middle of the 20th century became the demo-graphic basis of sovereign Kazakhstan.

A microRNA that controls the emergence of embryonic movement.

Movement is a key feature of animal systems, yet its embryonic origins are not fully understood. Here, we investigate the genetic basis underlying the embryonic onset of movement in Drosophila focusing on the role played by small non-coding RNAs (microRNAs, miRNAs). To this end, we first develop a quantitative behavioural pipeline capable of tracking embryonic movement in large populations of fly embryos, and using this system, discover that the Drosophila miRNA miR-2b-1 plays a role in the emergence of movement. Through the combination of spectral analysis of embryonic motor patterns, cell sorting and RNA in situs, genetic reconstitution tests, and neural optical imaging we define that miR-2b-1 influences the emergence of embryonic movement by exerting actions in the developing nervous system. Furthermore, through the combination of bioinformatics coupled to genetic manipulation of miRNA expression and phenocopy tests we identify a previously uncharacterised (but evolutionarily conserved) chloride channel encoding gene - which we term Movement Modulator (Motor) - as a genetic target that mechanistically links miR-2b-1 to the onset of movement. Cell-specific genetic reconstitution of miR-2b-1 expression in a null miRNA mutant background, followed by behavioural assays and target gene analyses, suggest that miR-2b-1 affects the emergence of movement through effects in sensory elements of the embryonic circuitry, rather than in the motor domain. Our work thus reports the first miRNA system capable of regulating embryonic movement, suggesting that other miRNAs are likely to play a role in this key developmental process in Drosophila as well as in other species.

Artificial Intelligence in Pharmaceutical Industry: Revolutionizing Drug Development and Delivery

Abstract: Artificial Intelligence (AI) has ushered in a profound revolution within the pharmaceutical sector, effectively streamlining the processes of drug development and delivery. The application of AI-driven tools and methodologies, including machine learning and natural language processing, in the realm of pharmaceutical research and development has yielded recent breakthroughs. This accelerated the drug discovery process by meticulously scrutinizing copious data and pinpointing potential drug targets, as expounded upon in this comprehensive review. Furthermore, AI has found utility in optimizing clinical trials, thereby refining trial designs and cost-effectiveness and bolstering patient safety. Notably, AI-based strategies are being harnessed to enhance drug delivery, fostering the creation of intelligent drug delivery systems engineered to target specific cells or organs. This results in heightened efficacy and a concomitant reduction in undesirable side effects. This review also delves into the potential biases residing within AI algorithms and the challenges associated with data quality when integrating AI into the pharmaceutical sphere. The findings of this study underscore the immense potential of artificial intelligence in reshaping the pharmaceutical industry, thereby enhancing the quality of life for patients worldwide.

Comparative analysis of oral fluid metabolism parameters between patients with complicated and uncomplicated implantation

ВACKGROUND: Modern scientific research continues to develop promising areas for diagnosing inflammatory complications after dental implantation. Analysis of studies shows that inflammatory complications depend on various factors, the establishment of which can be challenging. Hence, saliva diagnostics opens up broad prospects for studying the pathogenetic basis of the development of inflammatory processes. АIM: To study in a comparative aspect the metabolic status of complicated and uncomplicated implantation. MATERIALS AND METHODS: This study examined 88 patients (30 with peri-implant mucositis [main group I], 28 with uncomplicated implantation [comparison group II], and 30 controls [control group]) aged 45.3±2.4 years who were followed up for 1–3 years. RESULTS: Based on the results of the studies and comparative analysis of complicated and uncomplicated implantation, previously unknown data on their distinctive metabolic characteristics were obtained and presented. With complicated implantation, these include a characteristic increase in C-reactive protein, iron, and uric acid and a decrease in calcium levels. CONCLUSION: New information revealing prognostically significant factors of gastric cancer metabolism during complicated and uncomplicated implantation has been obtained. The identified changes in metabolism during implantation should be considered and differentiated from early metabolic signs of inflammation. The study of oral fluid is objective and promising in the diagnosis of the inflammatory process and its prognosis.

Development of optimised software fault prediction model using machine learning

Software fault prediction is a crucial task, especially with the rapid improvements in software technology and increasing complexity of software. As identifying and addressing bugs early in the development process can significantly minimize the costs and enhance the software quality. Software fault prediction using machine learning algorithms has gained significant attention due to its potential to improve software quality and save time in the testing phase. This research paper investigates the impact of classification models on bug prediction performance and explores the use of bio-inspired optimization techniques to enhance model results. Through experiments, it is demonstrated that applying bio-inspired algorithms improves the accuracy of fault prediction models. The evaluation is based on multiple performance metrics and the results show that KNN with BACO (Binary Ant Colony Optimization) generally outperform the other models in terms of accuracy. The BACO-KNN fault prediction model attains the accuracy of 96.39% surpassing the previous work.

Analisis Partisipasi Masyarakat dan Pemerintah dalam Pengembangan Sektor Pariwisata Kabupaten Bone, Sulawesi Selatan

The tourism sector is indeed quite promising to help increase foreign exchange reserves and pragmatically also able to increase people's incomes, sustainable tourism development is defined as a tourism development process oriented to the preservation of resources needed for future development where the surrounding community acts as a provider of tourist needs services. Humanitarian factors and local cultural entities should not be ignored, meaning that community life should not be uprooted from its cultural roots only because of the commercial emphasis of tourism, the lifestyle and culture of local communities, so researchers want to see how the role of community and government participation in development tourism as a leading destination and how tourism development is realized as a superior destination.