Standard Format Research Articles

In-vitro and In-silico evaluation of antimicrobial and antibiofilm effect of Neem oil and Calcium hydroxide nanoparticles against Mutans Streptococci and Enterococcus faecalis isolated from endodontic infections

Different Streptococcal species including Streptococcus mutans, Streptococcus sobrinus and Enterococcus faecalis are commonly isolated in root canal infections including refractory, recurrent, and persistent cases. Calcium hydroxide (Ca (OH)2) has been widely used in endodontics as an intracanal medicament. However, using new antimicrobial herbal alternatives offers promising potentials which can be additionally enhanced by using nanoparticles (NPs). In this study, we evaluate the antimicrobial efficacy and antibiofilm effect of Neem oil including its NPs preparations and we compare the effect of conventional Ca (OH)2 to Ca (OH)2 NPs using standard disc diffusion method and quantitative microtitre dish biofilm formation assay against common pathogens isolated from root canal samples. Molecular docking was used to test the binding of 10 Streptococcal macromolecules to 5 candidate neem active constituents. Neem NPs 0.125 mg/ml showed better antibacterial effect than both Neem 15 mg/ml and Neem 0.15 mg/ml. Ca (OH)2 NPs 0.125 mg/ml also showed better antibacterial effect than each of Ca (OH)2 10 mg/ml and Ca (OH)2 0.1 mg/ml. Best biofilm mass inhibition was achieved by Neem oil 0.15 mg/ml at 74.55% ( IQ: 67.36–87.65) and Neem NPs 0.0125 mg/ml at 59.33% (IQ: 51-–75.27). For Ca (OH)2, the best biofilm mass inhibition was observed with Ca (OH)2 NPs 0.125 mg/ml at 54.7% (IQ: 42.37– 77.25). Both neem oil and neem NPs show promising antibacterial and antibiofilm potential against Mutans Streptococci group at low concentrations and hence are good candidates for use as endodontic medications. In silico analysis shows that both Sitosterol and Gedunin appear to be important active constituents of neem and possible drug candidates. Additionally, Ca (OH)2 NPs showed significantly higher antimicrobial effect against Mutans streptococci group than conventional Ca (OH)2 preparations.

Chemical thermodynamics of biomass, cellulose, and cellulose derivatives: A review

This article provides a review of the research on the chemical thermodynamics and thermochemistry of biomass, cellulose, and its derivatives such as ethers, esters, and oxycelluloses. For diverse biomass types, gross and net heating values were studied. It has been established that these energetical characteristics of biomass can be calculated using a superposition of the energetical characteristics of the main components of biomass such as cellulose, hemicelluloses, lignin, lipids, proteins, etc. The pelletization of biomass improves its fuel performance. It was shown that, if the ultimate goal is to generate the maximum amount of thermal energy, then it is more profitable to directly burn the initial biomass in the form of pellets than to burn the amount of solid or liquid biofuel that can be extracted from this biomass. After the cellulose study, the direct and exact thermochemical method for determining the crystallinity degree of this biopolymer was proposed. In addition, the standard combustion and formation enthalpies of various cellulose samples were studied. As a result, the thermodynamic characteristics of four crystalline allomorphs of cellulose, CI, CII, CIII, and CIV, were obtained and their thermodynamic stability was evaluated. The thermochemistry of enzymatic hydrolysis of cellulose was studied. In addition. The thermodynamical characteristics of various cellulose derivatives were determined, and the thermochemistry of the reactions of cellulose alkalization, etherification, esterification, and oxidation was studied.

Investigating immersion and migration decisions for agent-based modelling: Acautionary tale.

Agent-based modelling provides an appealing methodological choice for simulating human behaviour and decisions. The currently dominant approaches based on static transition rates or unverified assumptions are restrictive, and could be enhanced with insights from cognitive experiments on actual decision making. Here, one common concern is that standard surveys or experiments may lack ecological validity, limiting the extent to which research findings can be generalised to real-life settings. For complex, highly emotive decision-making scenarios, such as those related to irregular migration, the typically used short, methodical survey questions may not appropriately map onto complex real-world decisions of interest. Immersive contexts may offer more accurate representations of reality, potentially enhancing the usefulness of experimental information in multi-disciplinary modelling endeavours. This preregistered study, aimed directly at examining the effect of immersion on risk-taking in the context of migration decisions, and indirectly at informing a multi-disciplinary construction of an agent-based model of migration, presents a choice-based interactive fiction game in which players make migration decisions to advance through a story. (N = 1000 Prolific users) took part in one of four experimental conditions, three involving different renditions of the game attempting to create immersion, with the last condition presenting the decisions in standard survey format. Although addressing the lack of ecological validity in survey data is important for improving agent-based modelling methodology, the experimental design used to tackle this issue, while responding directly to modelling needs, proved too complex. The created experimental conditions ended up too distinct from each other, involving stimuli that differed in quantity and content. This introduced several unintended and uncontrolled confounds, making it impossible to meaningfully interpret the results of this experiment on its own. Our results act as a cautionary tale for agent-based modellers, highlighting that the modelling needs should not override the principles of experimental design, and provide motivation for more rigorous research on this topic.

Geospatial tools and data for health service delivery: opportunities and challenges across the disaster management cycle.

As extreme weather events increase in frequency and intensity, the health system faces significant challenges, not only from shifting patterns of climate-sensitive diseases but also from disruptions to healthcare infrastructure, supply chains and the physical systems essential for delivering care. This necessitates the strategic use of geospatial tools to guide the delivery of healthcare services and make evidence-informed priorities, especially in contexts with scarce human and financial resources. In this article, we highlight several published papers that have been used throughout the phases of the disaster management cycle in relation to health service delivery. We complement the findings from these publications with a rapid scoping review to present the body of knowledge for using spatial methods for health service delivery in the context of disasters. The main aim of this article is to demonstrate the benefits and discuss the challenges associated with the use of geospatial methods throughout the disaster management cycle. Our scoping review identified 48 articles employing geospatial techniques in the disaster management cycle. Most of them focused on geospatial tools employed for preparedness, anticipatory action and mitigation, particularly for targeted health service delivery. We note that while geospatial data analytics are effectively deployed throughout the different phases of disaster management, important challenges remain, such as ensuring timely availability of geospatial data during disasters, developing standardized and structured data formats, securing pre-disaster data for disaster preparedness, addressing gaps in health incidence data, reducing underreporting of cases and overcoming limitations in spatial and temporal coverage and granularity. Overall, existing and novel geospatial methods can bridge specific evidence gaps in all phases of the disaster management cycle. Improvement and 'operationalization' of these methods can provide opportunities for more evidence-informed decision making in responding to health crises during climate change.

Data ecosystem using smart home technology to support healthy aging

Abstract Background Smart home technology has been widely used to mitigate the challenges that population aging brings. However, the lack of a centralized data ecosystem has prevented these technologies from realizing their full potential. This project aimed to construct a data ecosystem compatible with smart home sensors to monitor healthcare for seniors, improving their quality of life. Methods The infrastructure was constructed using a user-centered design approach, allowing smart devices such as motion, temperature sensors to operate independently and communicate through a Wi-Fi mesh network. API technology provides a reliable channel for real-time data collection. To ensure data privacy and security, extracted data is hosted in a cloud environment that provides comprehensive data protection, and cloud computing is utilized for high-performance computation tasks. Analytical models such as Machine Learning can be implemented to recognize indoor activities, achieving the goal of remote monitoring. Results This data ecosystem advances in privacy and security, interoperability, accessibility, and data-sharing. Unified authentication mechanism ensures data is transmitted among heterogeneous devices with minimal vulnerability. Additionally, the common communication protocol provides the foundation of interoperability between devices. With unobtrusive devices, inhabitants are not burdened with operation, ensuring their accessibility and improving their user experience. Lastly, the data is exchanged in a standardized JSON data format, enabling efficient data-sharing board data integration. Conclusions This project developed a data ecosystem based on existing smart home environments. The ecosystem is compatible with smart devices that families already have, effectively reducing additional healthcare costs. Implications of this study include helping health policy and decision makers to adopt more smart home ecosystems to keep older people healthy at home. Key messages • Study constructed a data ecosystem compatible with smart home sensors, achieving remote monitoring of indoor activities and improving the quality of life for seniors. • The developed ecosystem offers promotion in privacy and security, interoperability, accessibility, and efficient data-sharing, reducing healthcare costs.

A Data Model for Unrecognised Historical Neighbourhood (Case study: Telukbetung, Indonesia)

Abstract. Unrecognised Historical places, which are locations with history but lacking official recognition, particularly prevalent in Southeast Asia, often face a dearth of accessible historical information. To tackle this challenge, there is an urgent need to commence the collection and documentation of historical data concerning Unrecognised Historical places. This initiative aims to prevent the loss of history, given that such sites are frequently subjected to rapid development and commercialization. To date, City Geography Markup Language (CityGML), an Open Geospatial Consortium (OGC) standard 3D data format, has been developed for presenting city models along with semantic data and is often used in the heritage domain for preservation. It aids in digital infrastructure development and the conservation of urban elements. Furthermore, it provides a mechanism to extend the standard data model to meet the requirements of various purposes. While several CityGML extensions tailored to the documentation of Cultural Heritage already exist, there is currently no extension specifically designed to address the requirements of Unrecognised Historical places. The aim of this paper is to identify a suitable approach for developing a new standardised data model that integrates geometric and semantic information, which is demonstrated for the modelling of Telukbetung, an old city in Bandar Lampung through time.

Maximizing the "Functional" in the Functional External Memory Aid Tool for Patient-Centered Treatment Planning in Mild Cognitive Impairment.

The Functional External Memory Aid Tool (FEMAT) is an 11-item performance-based measure that simulates everyday tasks (e.g., medication management) to measure one's use of compensation (e.g., pill organizer). The FEMAT is not a norm-referenced diagnostic tool; rather, it is designed to provide clinicians with information about a patient's function and compensation in a standardized format. To provide further evidence for validity of the FEMAT, the purpose of this study was to conduct a mixed-methods analysis of FEMAT responses to operationalize the types of behaviors elicited during test administration. We adopted an embedded single-case study design to analyze the FEMAT administrations of 12 community-dwelling female participants, ages 73-90 years, who met criteria for mild cognitive impairment. These participants were part of the original validation sample during which they completed the FEMAT (Version 1.0) in a single session with an assessor. Sessions were video-recorded and transcribed. We analyzed the data qualitatively in two phases using theme and subtheme codes and then quantitatively analyzed the data for response trends. Our thematic analysis revealed four themes to operationalize participants' verbal and behavioral FEMAT responses: (a) used an external memory aid (EMA), (b) described using a strategy, (c) discussed memory and comprehension, and (d) discussed functional information. While completing the FEMAT, most participants described using a strategy (85%) and discussed their self-perceived memory and comprehension (33%). Several subthemes also emerged within each theme (e.g., self-perceived memory strengths and barrier). Our analysis suggests that beyond a 4-point item score, the FEMAT elicits behavioral (e.g., used an EMA) and verbal (e.g., discussion of health information) content that may be useful for person-centered treatment planning. This study is part of a comprehensive research agenda establishing the evidence for the validity of the FEMAT to support its use to inform person-centered treatment approaches.

A First-Passage Model of Intravitreal Drug Delivery and Residence Time-Influence of Ocular Geometry, Individual Variability, and Injection Location.

Standard of care for various retinal diseases involves recurrent intravitreal injections. This motivates mathematical modeling efforts to identify influential factors for ocular drug residence time, aiming to minimize administration frequency. We sought to describe the vitreal diffusion of therapeutics in nonclinical species frequently used during drug development assessments. In human eyes, we investigated the impact of variability in vitreous cavity size and eccentricity, and in injection location, on drug disposition. Using a first-passage time approach, we modeled the transport-controlled distribution of two standard therapeutic protein formats (Fab and IgG) and elimination through anterior and posterior pathways. Anatomical three-dimensional geometries of mouse, rat, rabbit, cynomolgus monkey, and human eyes were constructed using ocular images and biometry datasets. A scaling relationship was derived for comparison with experimental ocular half-lives. Model simulations revealed a dependence of residence time on ocular size and injection location. Delivery to the posterior vitreous resulted in increased vitreal half-life and retinal permeation. Interindividual variability in human eyes had a significant influence on residence time (half-life range of 5-7days), showing a strong correlation to axial length and vitreal volume. Anterior exit was the predominant route of drug elimination. Contribution of the posterior pathway displayed a 3% difference between protein formats but varied between species (10%-30%). The modeling results suggest that experimental variability in ocular half-life is partially attributed to anatomical differences and injection site location. Simulations further suggest a potential role of the posterior pathway permeability in determining species differences in ocular pharmacokinetics.

Архитектура создания самообучающегося колледжа

The competence approach has firmly gained its place in the world educational paradigm, distinguishing rigid (professional) and flexible (supra professional) skills. But the high speed of technological changes will significantly transform the landscape of the modern labor market, when within the next decades up to a quarter of traditional professions will disappear, and hard skills will be significantly transformed after them. The most important competitive advantage will be the speed of perception and translation of new knowledge, as well as competencies formed on their basis. The key competences for continuous development will be flexible competences (soft skills), some of which will be enriched with basic hard skills. The traditional conservatism of the educational system, the long period of formation of educational standards of training becomes a certain brake on the training of specialists of the future. If rigid skills can be formed based on the existing production base (jobs of the future, which do not exist yet), flexible skills can be formed now. This actualizes the idea of creating self-learning spaces in secondary vocational education institutions. Copying Chris Argyris' idea will not find a positive response, given our realities and the specifics of the Millennial generation, Z generation and later α generation, it will be a good idea to create self-learning spaces in secondary vocational education institutions. The author's developments on the implementation of approaches to the formation of the model of a self-learning college in the institution of secondary vocational education are presented. This approach can be useful for secondary vocational education organizations developing educational, managerial and financial strategies in order to unpack the expertise of the teaching community.

Modeling Enzyme Kinetics: Current Challenges and Future Perspectives for Biocatalysis.

Biocatalysis is becoming a data science. High-throughput experimentation generates a rapidly increasing stream of biocatalytic data, which is the raw material for mechanistic and novel data-driven modeling approaches for the predictive design of improved biocatalysts and novel bioprocesses. The holistic and molecular understanding of enzymatic reaction systems will enable us to identify and overcome kinetic bottlenecks and shift the thermodynamics of a reaction. The full characterization and modeling of reaction systems is a community effort; therefore, published methods and results should be findable, accessible, interoperable, and reusable (FAIR), which is achieved by developing standardized data exchange formats, by a complete and reproducible documentation of experimentation, by collaborative platforms for developing sustainable software and for analyzing data, and by repositories for publishing results together with raw data. The FAIRification of biocatalysis is a prerequisite to developing highly automated laboratory infrastructures that improve the reproducibility of scientific results and reduce the time and costs required to develop novel synthesis routes.

Evolution of social standards and guarantees in the legal system of Ukraine: current challenges and development prospects

The study is devoted to the evolution of social standards and guarantees in the legal system of Ukraine, the analysis of modern challenges in the field of social protection and the determination of prospects for their further development. In the conditions of economic and political transformations, ensuring the appropriate level of social standards is an urgent task. The article examines the historical development of social standards from the Soviet period to the modern stage of Ukraine’s integration into the European legal space. The impact of international law, in particular the European Social Charter and ILO conventions, on the formation of social standards is analyzed. The importance of adapting national legislation to international standards for increasing the level of social protection and bringing Ukrainian policy closer to European standards is emphasized. The influence of economic and social factors, such as crises, demographic changes, social inequality and migration processes, which create serious challenges for the state, is considered. Special attention is paid to social guarantees for vulnerable population groups, such as pensioners, people with disabilities, internally displaced persons and combatants. The main problems of these groups in the realization of the rights to social protection were identified and recommendations were given for improving the mechanisms of social support. The author emphasizes the need to reform social policy to create a more effective and fair system of social protection. Contemporary challenges in the implementation of social standards are explored, including economic instability, demographic changes, military conflict, inefficiency of public administration, and corruption. Emphasis is placed on a comprehensive approach to overcoming them, increasing the financial stability of the social system, improving legal regulation and cooperation with international organizations. Prospects for the development of social standards depend on the state’s ability to ensure the sustainability of social policy, adapt legislation to international standards, and increase the availability of social services. The successful implementation of these measures will contribute to Ukraine’s integration into the European legal space, which is strategically important for the country’s development. The article offers a comprehensive analysis of the evolution of social standards in the legal system of Ukraine, identifies the main challenges and provides recommendations for the further development of social policy.

TRANSFORMING HEALTHCARE DELIVERY THROUGH BIG DATA IN HOSPITAL MANAGEMENT SYSTEMS: A REVIEW OF RECENT LITERATURE TRENDS

This systematic review investigates the transformative role of big data technologies in biomedical research, analyzing 40 peer-reviewed articles published between 2010 and 2023. The review specifically explores advancements in next-generation sequencing (NGS), multi-omics approaches, machine learning, and artificial intelligence (AI), all of which have significantly enhanced the understanding of complex biological systems and diseases. NGS has emerged as a key tool in personalized medicine, enabling rapid and cost-effective genome sequencing that has facilitated the identification of genetic mutations and biomarkers associated with various diseases, particularly in oncology. Of the 40 studies reviewed, 12 focused on the integration of multi-omics data—genomics, transcriptomics, proteomics, and metabolomics—to provide a comprehensive view of biological processes. These multi-omics approaches have been instrumental in identifying biomarkers for disease progression and response to treatments, offering new avenues for drug development and precision medicine. Additionally, 15 studies highlighted the growing application of machine learning and AI algorithms in managing and analyzing vast biomedical datasets. These tools are now critical in uncovering hidden patterns within large datasets, predicting disease outcomes, and improving the accuracy of clinical decision-making. However, 10 studies emphasized ongoing challenges related to data storage, privacy concerns, and the lack of standardized data formats, which hinder effective data sharing across institutions. Despite these challenges, the integration of AI, IoT devices, and big data analytics is paving the way for more personalized, real-time healthcare monitoring and treatment solutions. This review concludes that while significant advancements have been made, further efforts are required to address the ethical and technical barriers that limit the full potential of big data technologies in biomedical research.

Building the clinical workforce of pediatric infectious diseases in Bolivia for better care of children with cancer

Abstract Background Infections in children with cancer can be fatal if not appropriately managed. Access to trained and competent professionals in infection care and prevention (IC&P) improve care outcomes. Bolivia expects about 1700 new pediatric cancer cases annually. In 2023, 2371 hematological neoplasms were reported in children, cared mainly at 4 public hospitals where, until 2016, 5 pediatric infectious disease (PID) specialists were working in 2 of these 4 hospitals. For better PID clinical workforce for critically ill children, we built a PID medical residency training. In 2017, the training accepted its first trainees at Hospital del Niño “Dr. Ovidio Aliaga Uría” (Hospital del Niño), a public hospital in La Paz. Here, we describe the program, how we built it, and its outcomes. Methods The PID training goal is to train leaders in PID for clinical observations, PID literature interpretation, and to transform them into concepts that can be applied to ID pathogenesis or treatment. At the end of the 2-year PID training program, we expect trainees will gain expertise in PID clinical practice and clinical or translational science research. Our PID program was based on other PID specialty training programs from Mexico, Spain, and the USA of which, we adapted standard topics and formats of training. The content has routine and prevalent PIDs of Bolivia and the region, including on immunocompromised patients. We expected that the trainee dedicate full time to the PID training program plus caring for assigned patients and those requested consultations in the wards and clinics of Hospital del Niño; review articles; participate in clinical discussions; attend the Infection Control Course of St. Jude Children’s Research Hospital; attend and / or present in the PID case-based learning international sessions; visit the virology, bacteriology, parasitology and immunology laboratories of the national reference laboratory; and attend international rotations at participating hospitals. Results Since 2017, 5 new PID pediatricians graduated from our program, 3 work in public hospitals that care for children with cancer and 2 work in government insurance hospitals. They are working in hospitals in La Paz (n=2), Cochabamba (n=1), Santa Cruz (n=1), and Tarija (n=1). These graduates are leaders in ICP, antimicrobial stewardships, and education of hospital staffs. As per December 2023, they produced 5 articles for local journals, 2 for international journals, 7 abstracts for scientific meetings. Currently, 2 pediatricians participate in the PID training program, and post-graduation, they plan to work in departments of Potosí and Sucre where there are no PID specialists. Challenges to establish PID specialists in Bolivia are lack of value attributed to PID and its role in care quality. Conclusion Creating local expertise in PID are essential to improve and sustain the optimum care for children with cancer in Bolivia especially in places where these personnel did not exist before. However, for best investment return of PID trained professionals, having PID job descriptions and paid positions in hospitals will absorb PID specialists to benefit the largest population of children with cancer in Bolivia.

STREAMLINING REGULATORY DOCUMENTATION: EXPLORING THE COMMON TECHNICAL DOCUMENT (CTD) AND ELECTRONIC SUBMISSION, WITH EMPHASIS ON M SERIES ACCORDING TO ICH GUIDELINES

A number of regulatory bodies have worked together to create the Common Technical Document (CTD), including the United States Food and Drug Administration, the European Medicines Agency, and the Japanese Ministry of Health. This standardized format facilitates the collection and submission of regulatory documentation pertaining to applications for new medicines. Since its inception in 2000, the CTD has been widely adopted internationally, including by nations such as Canada, Australia, and India. The CTD aims to streamline the submission process, reduce duplication of effort, and facilitate regulatory evaluations by providing a uniform structure for technical documentation. This article outlines the guidelines and organization of the CTD, including its modules covering administrative information, quality, non-clinical studies, and clinical trials. The CTD’s significance lies in its ability to improve regulatory efficiency, promote data transparency, and expedite the availability of new medicines to patients. However, challenges persist, such as variations in regional requirements and the need for continued adaptation to evolving technological standards. Electronic submissions and improved information management are two ways in which the new electronic CTD (eCTD) has improved submission procedures. Despite some ongoing issues, the CTD and eCTD represent significant advancements in regulatory documentation, with the potential for further innovation and global adoption in the future.

Information accumulation on the item versus source test of source monitoring: Insights from diffusion modeling.

Source monitoring involves attributing previous experiences (e.g., studied words as items) to their origins (e.g., screen positions as sources). The present study aimed toward a better understanding of temporal aspects of item and source processing. Participants made source decisions for recognized items either in succession (i.e., the standard format) or in separate test blocks providing independent measures of item and source decision speed. Comparable speeds of item and source decision across the test formats would suggest a full separation between item and source processing, whereas different speeds would imply their (partial) temporal overlap. To test these alternatives, we used the drift rate parameter of the diffusion model (Ratcliff, Psychological Review, 85, 59-108, 1978). We examined whether the drift rates, together with the other parameters, assessed separately for the item and source decision varied as a function of the test format. Threshold separation and nondecision time differed between the test formats, but item and source decision speeds represented by drift rates did not change significantly. Thus, despite facilitation on the source decision when the item decision was immediately followed by a test for source memory than when item and source were tested in separate blocks, findings did not suggest that source information already begins accumulating in the item test in the standard format. We discuss the temporal sequence of item and source processing in light of different assumptions about the contribution of familiarity and recollection.

Follow Debelyanov‘s Shadow

Georgi Raichev feels the continuous need to remember and tell about his friend Debelyanov and he does so –in practice, until the end of his life. The present text will try to develop the (hypo)thesis that, in addition to the standard memorial formats (in jubilee collections, memorial sheets, etc.), in which Raychev recalls moments from his joint experiences with Dimcho, he implants the personality in a specific way to his friend and in one of his first significant texts – the story “Tiny World” (1919). It is about both the possibility of drawing analogies between character traits of the main character and the poet, as well as the scattering of moments from Debelyanov‘s (pre)war life and/or from his (mainly frontline) lyrics throughout the narrative.

Structured Debriefing to Assess Performance of Entrustable Professional Activities.

Background The medical workplace presents challenges for workplace-based learning. Structured debriefing of shared clinical experiences has been proposed as a way to take advantage of workplace-based learning in a setting that facilitates deep learning conversations. Objective To investigate faculty and learner acceptance of private, face-to-face, structured debriefing of performance of entrustable professional activities (EPAs). Methods During the 2020-2021 academic year, faculty at the University of Colorado (CU) and the University of Utah (UU) debriefed fellow performance of jointly selected EPAs in neonatal-perinatal medicine pertinent to shared 1- to 3-week clinical rotations. Private face-to-face debriefing was structured by a comprehensive EPA-specific list of behavioral anchors describing 3 levels of entrustment/accomplishment. Sessions ended with joint decisions as to level of entrustment/accomplishment and goals for improvement. We used thematic analysis of semistructured fellow interviews and faculty focus groups to identify themes illustrated with representative quotations. Results We interviewed 17 fellows and 18 faculty. CU participants debriefed after clinical rotations; UU usually debriefed during rotations. Debriefing sessions for 1 to 2 EPAs lasted 20 to 40 minutes. Themes represented in fellow interviews and faculty focus groups suggested that debriefing facilitated formative feedback along with shared understanding of clinical performance and assessment criteria. The standardized format and private conversations supported assessment of aspects of performance for which review might otherwise have been overlooked or avoided. The conversations also provided valuable opportunities for formative discussion of other matters of importance to fellows. Conclusions Structured debriefing of recently shared clinical experiences fostered formative assessment viewed positively by teachers and learners.

Blue-button: A tool for institution-agnostic, EHR-integrated regional clinical trial matching.

65 Background: Research indicates that most people with cancer are willing to enroll in clinical trials when offered the chance, but only 7% actually participate in cancer treatment trials. Barriers to screening and enrollment include time and effort for providers to screen patients for trials, and lack of awareness of available regional trials. Stakeholders recommended creation of free, automated screening tools and processes integrated into provider workflows, directly interfacing with site electronic health records (EHRs), that would search for regional trial eligibility. The need for such tools was independently identified in a large national survey of oncology providers. Methods: The Blue-button tool was developed to automatically identify relevant, regional clinical trials. A collaboration between ACS CAN and MITRE, a not-for-profit organization working in the public interest, created the tool’s functionality. Clinical workflow and research protocol were developed in collaboration with University of Texas Southwestern Simmons Comprehensive Cancer Center. This SMART-on-FHIR application works within existing EHR systems by automatically extracting and sending limited, deidentified patient data elements to third-party trial matching services via the FHIR mCODE standard, a core set of non-proprietary, open-source structured data elements that establishes minimum standards for the structure and content of oncology data in health records. Potential trial matches within a specified radius of the practice are returned in a standard format using the FHIR Research Study resource. Results: Blue-button extracts limited patient data from EHR and provides it in an interface allowing users to update data before sending to trial matching services. Only non-identifiable information is sent to the external clinical trial matching services, which then return prescreen trial matches for manual review to confirm patient eligibility. Thus, with a few clicks in a medical record, the tool quickly identifies comprehensive trial availability within a specified distance of the patient’s location. When used by providers, Blue-button reduces the manual burden that often prevents consideration of clinical trials and identifies regional opportunities beyond the treating institution. Conclusions: Successful feasibility testing demonstrated the effectiveness of automated regional trial screening as a model. We have launched a clinical trial at two sites to assess the effectiveness of the Blue-button tool with patients in healthcare settings. We expect patient enrollment to continue through part or all of 2025. This trial of the Blue-button tool will provide additional information on provider accessibility and uptake and will demonstrate whether EHR-integrated regional trial screening leads to increased opportunities and enrollment in cancer clinical trials. Clinical trial information: NCT05885880 .

BracketMaker: Visualization and optimization of chemical protein synthesis.

Chemical protein synthesis (CPS), in which custom peptide segments of ~20-60 aa are produced by solid-phase peptide synthesis and then stitched together through sequential ligation reactions, is an increasingly popular technique. The workflow of CPS is often depicted with a "bracket" style diagram detailing the starting segments and the order of all ligation, desulfurization, and/or deprotection steps to obtain the product protein. Brackets are invaluable tools for comparing multiple possible synthetic approaches and serve as blueprints throughout a synthesis. Drawing CPS brackets by hand or in standard graphics software, however, is a painstaking and error-prone process. Furthermore, the CPS field lacks a standard bracket format, making side-by-side comparisons difficult. To address these problems, we developed BracketMaker, an open-source Python program with built-in graphic user interface (GUI) for the rapid creation and analysis of CPS brackets. BracketMaker contains a custom graphics engine which converts a text string (a protein sequence annotated with reaction steps, introduced herein as a standardized format for brackets) into a high-quality vector or PNG image. To aid with new syntheses, BracketMaker's "AutoBracket" tool automatically performs retrosynthetic analysis on a set of segments to draft and rank all possible ligation orders using standard native chemical ligation, protection, and desulfurization techniques. AutoBracket, in conjunction with an improved version of our previously reported Automated Ligator (Aligator) program, provides a pipeline to rapidly develop synthesis plans for a given protein sequence. We demonstrate the application of both programs to develop a blueprint for 65 proteins of the minimal Escherichia coli ribosome.

PerturbAtlas: a comprehensive atlas of public genetic perturbation bulk RNA-seq datasets.

Manipulating gene expression is crucial for understanding gene function, with high-throughput sequencing techniques such as RNA-seq elucidating the downstream mechanisms involved. However, the lack of a standardized metadata format for small-scale perturbation expression datasets in public repositories hinders their reuse. To address this issue, we developed PerturbAtlas, an add-value resource that re-analyzes publicly archived RNA-seq libraries to provide quantitative data on gene expression, transcript profiles, and alternative splicing events following genetic perturbation. PerturbAtlas assists users in identifying trends at the gene and isoform levels in perturbation assays by re-analyzing a curated set of 122801 RNA-seq libraries across 13 species. This resource is freely available at https://perturbatlas.kratoss.site as both raw data tables and an interactive browser, allowing searches by species, tissueor genomic features. The results provide detailed information on alterations following perturbations, accessible through both forward and reverse approaches, thereby enabling the exploration of perturbation consequences and the identification of potential causal perturbations.