Exponential Increase Research Articles

National serosurvey and risk mapping reveal widespread distribution of Coxiella burnetii in Kenya

Coxiella burnetii, the causative agent of Q fever, is an emerging pathogen that has the potential to cause severe chronic infections in animals and humans worldwide. The detrimental impact on public health is projected to be higher in the low- and middle-income countries given their lower capacity to sustain effective surveillance and response measures. We implemented a national serosurvey of cattle in Kenya to map the spatial distribution of the pathogen. The study used serum samples that were collected from randomly selected cattle in different ago-ecological zones across the country. These samples were screened for the pathogen using PrioCHECK Ruminant Q Fever AB Plate ELISA kit. The laboratory findings were analyzed using INLA package to identify risk factors for C. burnetii exposure from herd- and animal-level factors, area, and bioclimatic datasets accessed from online databases. A total of 6,593 cattle were recruited for the study; of these, 7.9% (95% CI; 7.2–8.5) were seropositive. Outputs from the multivariable analysis revealed that the animal age and some of the geographical variables including wind speed, area under shrubs and “petric calcisols” type of soil were significantly associated with C. burnetii seropositivity. Being a calf, weaner or subadult was associated with lower odds of exposure compared to being an adult by 0.24 (credibility interval: 2.5% and 97.5%), 0.41 (0.30–0.55) and 0.51 (0.38–0.69), respectively. In addition, a unit increase in the wind speed increased the odds of C. burnetii seropositivity by 1.27 (1.05–1.52) while an increase on the land area under shrubs was associated with lower odds of exposure (0.67 [0.47–0.69]). The effect of petric calcisols was non-linear; an increase of the land area with this soil type was associated with an exponential increase in C. burnetii seropositivity. This study provides new data on C. burnetii seroprevalence, information of its risk factors and a prevalence map that can be used for C. burnetii risk surveillance and control. The identification of environmental risk factors for C. burnetii exposure, and the increasing awareness of the zoonotic potential of the pathogen, calls for the need to enhance the existing collaborations for the surveillance and control of C. burnetii in line with the One Health framework. The evidence generated on the potential role of environmental factors can also be used to design nature-based interventions, such as replacement of vegetation in denuded areas, to reduce potential for the aerosolization of the pathogen. Livestock vaccination in the hotspots would also reduce animal infections and hence the contamination of the environment.

Trends in national and ethnic burden of ovarian cancer mortality in South Africa (1999–2018): a population based, age-period-cohort and join point regression analyses

Ovarian cancer is the most lethal and third leading cause of gynaecological cancers globally and in South Africa (SA). However, its current mortality trends have not been evaluated in most sub-Saharan African Countries including South Africa that is currently undergoing epidemiological and health transitions. We evaluate the trends in the ovarian cancer mortality rates in SA over 20 years (1999–2018).MethodsCrude (CMR) and age standardised mortality rates (ASMR) of ovarian cancer was calculated based on national mortality data of South Africa. The overall and ethnic trends of ovarian cancer mortality among women aged 15 years and older from 1999 to 2018 was assessed using the Join point regression model, while Age-period-cohort regression analysis was conducted to evaluate the underlying impact of age, period and cohort on ovarian cancer mortality.ResultsIn all, 12,721 ovarian cancer deaths were reported in South Africa from 1999 to 2018 and the mortality rates increased from 2.34 to 3.21 per 100,00 women at 1.8% per annum. In 2018, the overall mean age at ovarian cancer death in South Africa was 62.30 ± 14.96 years while the mean age at death among Black women (58.07 ± 15.56 years), was about 11 years earlier than among White women (69.48 ± 11.71 years). In 2018, the White ethnic group (4.93 deaths per 100,000 women) had about doubled the ovarian cancer ASMR for the non-Whites (Indian/Asians, 2.92/100,000 women, mixed race, 2.49/100,000 women and Black women (2.36/ 100,000 women). All the ethnic groups had increased ASMR with Black women (Average annual percent change, [AAPC]: 4.7%, P-value < 0.001) and Indian/Asian women (AAPC: 2.5%, P-value < 0.001) having the highest rise. Cohort mortality risk ratio of ovarian cancer increased with successive birth cohort from 0.35 among 1924–1928 birth cohorts to 3.04 among 1999–2003 cohort and the period mortality risk increased by about 13% and 7.5% from 1999 to 2003 to 2004–2008 (RR: 0.87, 95% CI: 0.80–0.94), and from 2004 to 2008 to 2009–2013 (RR: 1.075, 95% CI:1.004–1.152) respectively. The longitudinal age analysis revealed that ovarian cancer increased with age, but there was an exponential increase from 55 years.ConclusionsOur study showed that there was increasing trends in ovarian cancer mortality among all the South African ethnic groups, driven partly by increasing cohort and period mortality risks. We therefore highlight the huge burden of ovarian cancer in SA and the need for targeted intervention. Public health interventions geared towards reducing ovarian cancer mortality should be instituted and ethnic disparity should be incorporated in the cancer control policy.

Characterizing the utilization of a federated clinical data network: A bibliometric analysis of TriNetX in Taiwan

ABSTRACT Objectives: TriNetX is a global network of deidentified electronic health record data that participating healthcare institutions can access and analyze. Despite its potential to build research capacity, the research produced using this network has not yet been independently analyzed. This study aims to characterize the research outputs produced by Taiwan-affiliated authors analyzing TriNetX data. Materials and Methods: A systematic search was performed to identify peer-reviewed Science Citation Index Expanded indexed publications with Taiwan-affiliated authors. The articles were screened and included if they were based on an analysis of data from the TriNetX platform. A bibliometric analysis was then performed to examine the composition of authorship teams, collaborations between countries/institutions, the medical specialties present, and the rankings of journals that published the articles. Results: Ninety-two studies with Taiwan affiliations using TriNetX were identified and included. An exponential increase in publications between 2022 and 2024 was identified. 75 (81.52%) of the articles were published in Q1 journals. Most medical specialties were represented in the dataset, with many Allergy, Immunology, and Rheumatology publications present. Chung Shan Medical University Hospital and Chi Mei Medical Center were identified as influential institutions that accounted for most of the publications. Conclusion: TriNetX is used regularly by Taiwan-based clinical researchers to conduct impactful research across a variety of medical specialties. The platform will play an increasingly important role in Taiwan’s medical research. Further studies examining how TriNetX is utilized before publication are needed to better understand how the network influences research capacity building in Taiwan hospitals.

Resurgence of Severe Challenging Behavior and Schedule Thinning with the Terminal Schedule Probe Method

Multiple schedules promote schedule thinning during treatment for challenging behavior. Some strategies for multiple-schedule-thinning progressions include dense-to-lean (DTL; gradually thinning schedules of reinforcement in small steps), fixed lean (FL; abruptly shifting to lean schedules), and terminal probe (TP; probing terminal schedule values to inform subsequent thinning steps) thinning. Recent research indicates that TP thinning offers an empirically derived process for schedule thinning to terminal schedule values. In the current investigation, we replicated, re-analyzed, and extended recent research on the TP-thinning method. The schedule-thinning outcomes were consistent with the initial investigation, indicating that longer periods of reinforcer unavailability were facilitated by TP thinning in comparison with DTL thinning. We also examined resurgence, or the temporary increase in challenging behavior after alternative behavior is placed on extinction, across a wide range of downshifts in reinforcement. When resurgence occurred across ranges of downshifts programmed for both schedule-thinning methods, it occurred more often with DTL thinning. The resurgence analyses did not reveal an exponential increase in challenging behavior as a function of downshifts in reinforcement, which is an interesting departure from recent investigations. Points of discussion include clinical implications and areas for future research on the TP-thinning method.

The use of different cost of equity models when valuing SMEs: A case study

This study examines the valuation process of small and medium-sized enterprises (SMEs), using a Portuguese SME as a case study. The analysis focuses on calculating the cost of equity, with particular attention to the unique characteristics of these companies. The valuation was conducted using the discounted cash flow (DCF) method, with a preference for the average cost model. Two different approaches were employed to forecast free cash flows: (a) the geometric growth rate of sales, and (b) free cash flow projections derived from a model based on historical results. To calculate the cost of equity, three distinct models were used: (a) the capital asset pricing model (CAPM) with modifications proposed by Damodaran (2014), (b) the model developed by the Spanish Association of Accounting and Business Administration (AECA) from Rojo-Ramírez et al. (2012), and (c) the build-up model proposed by Ibbotson. These models serve as alternatives to the traditional CAPM, which is less suitable for unlisted companies due to the absence of a market beta. The study compares the results obtained from each model, focusing on their impact on the company’s valuation. Valuing SMEs is crucial for enhancing corporate decision-making. Furthermore, the approaches utilized in this study provide valuable guidelines for financial analysts involved in SME valuation.

Enhancing Data Compatibility Through Quantum Computing and AI: A Hybridized Strategy

The exponential increase in data generation across industries necessitates innovative strategies for ensuring seamless integration and interoperability. Conventional computing techniques struggle to cope with the complexities of heterogeneous data formats. This study introduces a hybrid methodology that synergizes Quantum Computing and Artificial Intelligence (AI) to streamline data compatibility. The proposed system employs Quantum Machine Learning (QML) for accelerated data processing and AI-driven adaptive algorithms for precise transformations, reducing computational overhead while enhancing accuracy. The results demonstrate improved efficiency in large-scale data integration scenarios. Key Words: Quantum Computing, Artificial Intelligence, Data Compatibility, Quantum Machine Learning, Interoperability

Model development to assess the impact of a preventive treatment with sarolaner and moxidectin on Dirofilaria immitis infection dynamics in dogs

BackgroundDirofilaria immitis is a mosquito-transmitted filarial parasite causing heartworm disease in dogs. The parasite may cause a significant disease burden to the dog population in high prevalence areas and is mainly managed through prophylactic treatments.MethodsIn this modelling study, the effect of a prophylactic treatment with moxidectin and sarolaner on heartworm disease dynamics was investigated in dogs. A compartmental model was developed to investigate different epidemiological settings considering different values for prevalence and host preference.ResultsWhen the mosquito host preference to dogs is low, a treatment compliance of only 40% decreases the proportion of infectious dogs. When the host preference of the mosquitoes however increases, an exponential increase in infectious dogs was observed, and a higher treatment compliance is required. In high transmission environments, with a high prevalence and a high mosquito host preference, a high treatment compliance (up to 100%) is required to have an impact on the number of infected animals. Notably, in scenarios with higher host preference towards dogs, more mosquitoes are exposed to sarolaner through the blood meal, leading to higher mortality of these mosquitoes and resulting in fewer infected and infectious dogs.ConclusionsThe preventive efficacy, as measured by the number of non-infected dogs, increases with increasing treatment compliance, but the extent of the treatment effect differs with the epidemiological setting. Adding sarolaner to a heartworm prevention has a complimentary impact on mosquito survival and heartworm disease transmission, although this effect depends on the epidemiological settings, emphasizing the true complexity of disease dynamics of a vector-borne disease.Graphical abstract

Transforming Medical Education Through Intelligent Tools: A Bibliometric Exploration of Digital Anatomy Teaching

The teaching of human anatomy is experiencing significant transformation. Particularly in recent years, incorporating new digital technologies has drastically changed the approach to education. Our bibliometric study aims to investigate trends and issues from 2004 to 2024 related to digital technology in human anatomy teaching. The publication trend in the field has steadily increased over the years, peaking in 2022 and declining in 2023. Despite the limited statistics for 2024, we do not project an exponential increase in publications. Co-citation analysis identified notable references that significantly influenced the field, emphasizing modernization through innovative methodologies. Leading a significant portion of global collaboration, the United States promoted robust multilateral partnerships. Co-occurrence word analysis highlighted the merging of current technology with student-centered learning approaches, reflecting a shift towards more interactive and immersive learning experiences. Thematic map analysis identified distinct research areas with emerging or declining themes. The analysis of topic trends over the last five years revealed a persistent interest in terms like “palmar” and “carpal”, as well as innovative technologies like “cone beam computed tomography”, “augmented reality”, and “virtual reality”. Our bibliometric study revealed a sector in constant transformation, presenting a scenario where integrating technology with traditional teaching methods could enhance medical students’ comprehension of human anatomy. On the other hand, it also highlighted the anticipated challenges of ensuring equal access to cutting-edge technology, providing sufficient training for academic staff, and addressing emerging ethical issues.

Social Media and Plastic Surgery, the Good, the Bad, and Where are We Going?

In recent decades, social networks have experienced an exponential increase involving millions of users and transforming the way they communicate in the medical community, becoming an important tool in medicine, where plastic surgery has not been an exception. We aimed to present a review of the effects of social networks in the area of plastic surgery, the main existing regulatory frameworks, and propose the basic aspects for the adequate use of these platforms in the practice of our profession. A literature search was performed, including scientific articles, specific existing guides from the USA, Australia, Brazil, and Argentina, as well as articles in digital newspapers and Google regarding emblematic cases. These platforms are an important source of information and communication in medicine and are frequently used by different scientific societies, mainly for educational and dissemination purposes. In the area of plastic surgery in particular, there is a high presence of specialists in the field who use these tools mainly for orientation, education, promotion of their brand, and peer-to-peer relationships. The main negative aspects of social networks are a high presence of publications generated by non-professionals in the field, false information, and the generation of esthetic violence. The regulations of several existing scientific societies, although heterogeneous on some points, mostly agree that the need for informed consent, protection of patient privacy and safety, truthfulness of the information published, and patient education campaigns are key points. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Machine Learning Relationships Between Nanoporous Structures and Electrochemical Performance in MOF Supercapacitors.

The development of supercapacitors is impeded by the unclear relationships between nanoporous electrode structures and electrochemical performance, primarily due to challenges in decoupling the complex interdependencies of various structural descriptors. While machine learning (ML) techniques offer a promising solution, their application is hindered by the lack of large, unified databases. Herein, constant-potential molecular simulation is used to construct a unified supercapacitor database with hundreds of metal-organic framework (MOF) electrodes. Leveraging this database, well-trained decision-tree-based ML models achieve fast, accurate, and interpretable predictions of capacitance and charging rate, experimentally validated by a representative case. SHAP analyses reveal that specific surface area (SSA) governs gravimetric capacitance while pore size effects are minimal, attributed to the strong dependence of electrode-ion coordination on SSA rather than pore size. SSA and porosity, respectively, dominate volumetric capacitance in 1D-pore and 3D-pore MOFs, pinnacling the indispensable effects of pore dimensionality. Meanwhile, porosity is found to be the most decisive factor in the charging rate for both 1D-pore and 3D-pore MOFs. Especially for 3D-pore MOFs, an exponential increase in porosity is observed in both ionic conductance and in-pore ion diffusion coefficient, ascribed to loosened ion packing. These findings provide profound insights for the design of high-performance supercapacitor electrodes.

Increasing Research Productivity and Step 2 Score Among Matched Orthopaedic Surgery Residents: A Forecasting Analysis to 2040.

Orthopaedics has consistently been among the most competitive residency specialties in which to match. The purpose of this study was to evaluate trends in important data as provided by the National Resident Matching Program regarding orthopaedic surgery residency and to project future averages for successful applicants. "Charting Outcomes in the Match" are biennial reports published by the National Resident Matching Program, listing applicant characteristics stratified by specialty. We collected data between 2014 and 2024 for allopathic medical school seniors from the United States that successfully matched into orthopaedic surgery residency. Regression analysis was performed to predict research productivity and United States Medical Licensing Examination Step 2 scores to the year 2040. Research productivity and Step 2 score have shown notable trends among matched orthopaedic surgery residency applicants, with research productivity following an exponential increase (R2 = 0.988, P < 0.001) and Step 2 scores following a linear trend (R2 = 0.925, P = 0.002). In accordance with these models, by the year 2040, matched applicants are projected to have an average of 165.6 (95% prediction interval, 107.8 to 254.5) publications, posters, abstracts, and presentations and an average Step 2 score of 266 (95% prediction interval, 261 to 271) points, outperforming the 87th percentile. Specifically, Step 2 score is projected to increase by 1.1 point every 2 years with the limitation that the upper limit score is 300. Research productivity and USMLE Step 2 scores among matched orthopaedic surgery residency applicants are projected to increase in the coming years. These findings can inform medical school administration, residency programs, and orthopaedic leadership to optimize their programs for student, resident, and organizational success. Moreover, it may be time to reconsider the importance of these metrics as a perpetual increase in scores and research activity is not sustainable nor equitable.

Self-adaptive microwave photonics time-frequency signal processing for high-power interference suppression

Radar has become a widely adopted technology in intelligent transportation systems for environmental sensing. However, the exponential increase in the number and functionality of radars, combined with the dynamic traffic scenarios, made the radar’s operating scenarios complex and variable, imposing significant challenges on the radar’s operation. In this paper, we propose a stimulated Brillouin scattering (SBS) based self-adaptive time-frequency signal processing (TFSP) method for dynamic interference scenarios, which can adapt to suppress the high-power interference and enhance the operation performance of radar systems. Unlike current SBS-based microwave photonics technology, this approach exploits the time-frequency characteristic of the chirped optical signal when SBS occurs to achieve two-dimensional self-adaptive suppression for the high-power non-stationary optical signal. Based on this advantage, we develop an interference suppression method for wideband radar, which is transparent to the time-frequency characteristic of the high-power interference, realizing real-time suppression and self-adaptability for different types of interferences in dynamic interference scenarios. Experimentally, we first demonstrate the suppression effect of the proposed TFSP on different types of interference and the performance improvement on radar detection with a maximum signal-to-noise enhancement of 25.68 dB. Then, the self-adaptability of the TFSP to the dynamic interference scenarios is also verified when the interferences change.

China’s Expanding Strategic Investment in the Lithium Triangle

China’s Expanding Strategic Investment in the Lithium Triangle

Research Progress and Prospects of Refrigerant Replacement Under the Background of Greenhouse Gas Emission Reduction: A Visualization Analysis of the CiteSpace Map

As global environmental consciousness continues to expand, the issue of refrigerant alternatives has increasingly become a focal point for scholarly attention. Using CiteSpace visualization technology, a comprehensive and innovative research framework for refrigerant alternatives has been developed. This framework systematically organizes and analyzes not only the volume of publications related to refrigerant alternatives but also the collaborative relationships among authors and research institutions. By employing keyword co-occurrence maps, clustering diagrams, and timeline charts, an in-depth analysis of the academic literature on refrigerant alternatives has been performed, elucidating the core research themes, evolutionary trajectories, and emerging trends in this field. Research indicates an exponential increase in the number of studies on refrigerant alternatives; however, there is insufficient collaboration and communication among researchers and institutions. Key research hotspots in this field encompass the organic Rankine cycle, vapor-liquid equilibria, pressure drop characteristics, vapor compression refrigeration systems, exergy analysis, alternative refrigerants, and performance evaluation of carbon dioxide systems. In future research, the performance of various low GWP refrigerants in refrigeration cycle systems will continue to be a focal point. To address diverse application requirements, developing blended refrigerants represents a pragmatic technical approach. From a sustainability standpoint, natural refrigerants are anticipated to emerge as the ultimate alternative, with the technical challenges associated with their application constituting a critical area for future investigation.

Seascape connectivity with mangroves positively influences tropical saltmarsh blue carbon stocks.

Despite exponential increase in global blue carbon studies over the last decade, critical knowledge gaps remain regarding the role of drivers such as seascape connectivity that mediate the carbon storage in tropical saltmarsh ecosystems. The present study addresses this knowledge gap by investigating how seascape-level drivers, specifically connectivity between ecosystems, sediment traits and plant biomass, influence carbon stocks, in connected versus individual tropical saltmarsh (Porteresia coarctata and Myrostachia wightiana) meadows. This study compared the influence of connected saltmarsh meadows (adjacent to mangroves) with individual saltmarsh meadows across four tropical locations and assessed their carbon (C) and nitrogen (N) content in sediment, biomass, various plant traits and C stocks. Stable isotopes tracers (13C and 15N) were used to determine the C contribution from autochthonous and allochthonous carbon sources. Connectivity resulted in increased of plant shoot density, and biomass by 1.7-fold and 1.5-fold respectively than individual saltmarsh meadows. Connectivity resulted in 2.3-fold higher Corg stocks (sediment + biomass) than individual meadows. Connectivity increased the below -ground biomass contribution to sediment C pool by 2 to 10%, whereas the combined contribution of mangrove leaf biomass was between 7.8 and 26.8% in both saltmarsh species probably depending on the mangrove density, leaf litterfall and organic matter trapping efficiency of these saltmarsh species. The study underscores the positive role of seascape connectivity with mangroves in enhancing the carbon stocks in tropical saltmarsh ecosystems.

IntSDM: An R Package for Building a Reproducible Workflow for the Field of Integrated Species Distribution Models.

There has been an exponential increase in the quantity and type of biodiversity data in recent years, including presence-absence, counts, and presence-only citizen science data. Species Distribution Models (SDMs) have typically been used in ecology to estimate current and future ranges of species and are a common tool used when making conservation prioritization decisions. However, the integration of these data in a model-based framework is needed to address many of the current large-scale threats to biodiversity. Current SDM practice typically underutilizes the large amount of publicly available biodiversity data and does not follow a set of standard best practices. Integrating different data types with open-source tools and reproducible workflows saves time, increases collaboration opportunities, and increases the power of data inference in SDMs. We aim to address this issue by (1) proposing methods and (2) generating a reproducible workflow to integrate different available data types to increase the power of SDMs. We provide the R package intSDM, as well as guidance on how to accommodate users' diverse needs and ecological questions with different data types available on the Global Biodiversity Information Facility (GBIF), the largest biodiversity data aggregator in the world. Finally, we provide a case study of the application of our proposed reproducible workflow by creating SDMs for vascular plants in Norway, integrating presence-only and presence-absence species occurrence data as well as climate data.

The Role of Diagnostic Nasal Endoscopy and Computed Tomography Scan in Chronic Rhinosinusitis in Adults: A Study of Clinical Correlation.

Chronic rhinosinusitis (CRS) is an inflammatory disease affecting the paranasal sinuses (PNS) with a lifetime prevalence of approximately 15%, impacting about 1 in 8 Indians. The condition is rapidly evolving, with an exponential increase in cases due to rising atmospheric pollution and exposure to various allergens. CRS is one of the most common reasons for ENT consultations, significantly impairing patients' quality of life. Defined by inflammation lasting more than 12 weeks, CRS diagnosis relies on EPOS criteria using endoscopy and computed tomography (CT) scans. CRS affects about 11% of the global population and ranks among the top 10 costliest health conditions, highlighting the need for cost-effective and accessible diagnostic tools. This observational study was conducted in a tertiary care hospital and included 53 CRS patients (age 18-70 years) undergoing diagnostic nasal endoscopy (DNE) and non-contrast CT. The Lund-Mackay and Lund-Kennedy scores evaluated CT and DNE findings, respectively. Statistical analysis included descriptive, Mann-Whitney, chi-square tests, and Spearman correlation. Nasal obstruction (98.11%) predominated, with CT revealing maxillary sinus involvement (52.83%) and common anatomical variations such as a deviated nasal septum. DNE identified edema (66.03%) and nasal polyps (15.1%). A strong correlation (0.866) between Lund-Kennedy and Lund-Mackay scores validated DNE. DNE showed 91.31% sensitivity, 71.46% specificity, and 86.44% diagnostic accuracy versus CT. DNE proves to be reliable in CRS assessment, aligning well with CT findings. It offers a cost-effective initial evaluation and management option, crucial in resource-limited settings.

Towards real-world clinical data standardization: A modular FHIR-driven transformation pipeline to enhance semantic interoperability in healthcare.

Given the exponential increase in clinical data, which accounts for around 30% of global data volume, effective information management has become crucial to ensuring robust interoperability. This trend is further expedited by implementing consumer-oriented Internet of Things platforms, contributing to the growth of the $8.3 trillion healthcare industry. These advancements, combined with challenges such as heterogeneous data formats and a lack of incentives, necessitate the development of pragmatic infrastructures and tools that harness contemporary clinical standards like Fast Healthcare Interoperability Resources (FHIR). This study aims to present a modular conversion pipeline employing a templating strategy for translating clinical data into the FHIR model. Emphasis is placed on utilizing a standard mapping specification like FHIR Mapping Language. This ensures essential properties such as platform independence, portability, and code reusability. The pipeline was developed incrementally, dividing its core functionalities into five modules: Input, Refinement, Mapping, Validation, and Export. These were subsequently validated by converting a dataset from a prosthetic fitting and rehabilitation center to demonstrate the approach's validity in a real-world data context. A total of 1962 hospital stay records of 1006 unique patients were converted successfully to 15 distinct types of FHIR resources. The successful conversion states the pipeline's effectiveness, additionally showcasing its capabilities for enhancing semantic interoperability and facilitating the reuse of real-world data. Our approach emerges as a modular data conversion framework that addresses the limitations of existing solutions, making significant contributions to the creation of standardized, interoperable, and high-quality clinical datasets that serve as a foundation for further work.

Evaluating student understanding of pharmacodynamics core concepts.

Pharmacodynamics is an essential subdiscipline of pharmacology that underpins safe and effective prescribing and therapeutic decision-making, as well as drug discovery and development. The exponential increase in the number of therapeutic drugs has prompted members of the pharmacology educator community to question existing pharmacology curricula focused on individual drugs and move toward a curriculum focused on conceptual understanding. A first step towards conceptual understanding is to establish what students currently know about pharmacodynamic core concepts. A total of 218 students from 10 universities were invited to complete a questionnaire that assessed their understanding of drug efficacy, drug-target interaction, drug tolerance, and structure-activity relationship. Pairs of pharmacology experts independently assessed each student's response and flagged any misconceptions that arose. The experts then compared their evaluations, achieved a consensus decision, and grouped the misconceptions into themes. Less than 25% of students provided core concept meanings that fully aligned with those of the expert group. By contrast, more than 75% of students could apply the core concept to a novel scenario at least in part. Overall, 480 misconceptions were identified and grouped into 55 misconception themes. The concept of drug efficacy was the core concept with which students struggled most. It is unclear why students were better able to apply their knowledge than to define the core concepts, although this might reflect a focus on active learning in pharmacology courses globally. The deficits in defining and understanding pharmacodynamic core concepts, and the misconceptions revealed in student responses, can be used by educators to guide their efforts.

Mitigating stress: exploring how our feet change shape with size.

If human skeletal shape increases proportionally with size (isometric scaling), we would expect exponential increases in joint contact stress as individuals become larger. However, if skeletal shape changes as a function of size (allometric scaling), this can mitigate increases in joint contact stress by changing the surface area (SA)-to-volume ratio. Here, we explored whether human foot bones scale with allometry and, if so, to identify the shape features that are associated with bone size. Computed tomography scans of the two largest foot bones (talus, calcaneus) were obtained from 36 healthy individuals. We implemented a scaling analysis for each joint articular surface and bone. We performed a Procrustes ANOVA to establish the shape features associated with bone size. In line with our hypothesis, articular surfaces on the calcaneus scaled with positive allometry relative to bone volume, whereas total bone SA scaled with negative allometry. This indicates that articular surfaces grew at a faster rate than the overall bone SA. Interestingly, the calcaneus appeared more cube-like with increasing size. This may be important for the mitigation of internal bone stresses with increasing skeletal size. Our findings suggest distinct but varied scaling strategies within the foot. This may reflect the requirement to maintain healthy joint contact and internal bone stresses with increasing size.