In her new role, Zinchenko will guide the design and execution of ULRI initiatives, including partnership structures and funding strategies that broaden the organization’s global reach. Her mandate centers on translating stakeholder needs into scalable programs, with an emphasis on mission-driven innovation and measurable outcomes in public safety.

Zinchenko’s work will include developing new partnership opportunities and shaping sponsor engagement plans to support multi-partner research programs. She will also help advance commercialization through structured business planning, including the strategic use of ULRI intellectual property, creating pathways for research findings to influence products, standards, and operational practices.

“Elena brings a strong track record of building impactful programs and partnerships that translate science into meaningful outcomes,” said James J. Hudgens, Ph.D., president and chief executive officer for UL Research Institutes. “Her program development and partnership leadership will strengthen our ability to prevent harm and save lives through safety science research excellence.”

Most recently, Zinchenko served as assistant provost for research at the University of Chicago. There, she rebuilt the institution’s large-proposal enterprise and expanded research development capabilities, focusing on the complex coordination required to win competitive federal and philanthropic funding while aligning teams around shared scientific goals.

ULRI’s research portfolio spans fire safety, electrochemical safety, chemical insights, materials discovery, digital safety, and research experiences and education. The organization publishes findings openly and works to inform standards bodies, policymakers, and communities, aiming to transform evidence into decisions, behaviors, standards, and systems that protect infrastructure and people.

With more than 15 years of experience in program development, external funding, and strategic partnerships, Zinchenko brings expertise in creating institutional-scale collaborations. Her background includes building multi-partner efforts across federal, philanthropic, and commercial sectors—an approach that can reduce time-to-impact for safety science initiatives.

Zinchenko earned her bachelor’s degree from the University of Georgia, her doctorate from Harvard University, and completed a postdoctoral fellowship at the University of Chicago.

She will begin her duties as ULRI accelerates efforts to expand research translation and strengthen the partner ecosystem that supports safety-focused innovation.

Subject of Research: Not applicable
Article Title: Elena Zinchenko, Ed.D, joins UL Research Institutes as Chief Program Development Officer
News Publication Date: July 7, 2026
Web References: https://ul.org/
References: None provided
Image Credits: UL Research Institutes
Keywords: Education

In “Charting a Course for AI in Medical Education,” Katie Cottingham examines how medical schools are adopting AI tutors and feedback systems. The practical promise is clear: tools can provide rapid, personalized coaching and help students practice decision-making. But the article stresses a fundamental educational risk—students may become dependent on AI answers rather than developing the cognitive struggle that makes knowledge durable. The piece argues for “scaffolding” rather than replacement, using AI to guide reasoning while preserving the integrity of clinical thinking.

The rare disease report, “AI Models Could Improve Diagnosis and Care for Rare Diseases,” focuses on data scarcity and underdiagnosis. With rare disorders affecting hundreds of millions worldwide, machine learning faces a harsh constraint: limited labeled datasets. Simon Spichak describes deep generative approaches such as popEVE, a foundation-style model designed to learn patterns in genetic variation and propose candidate pathogenic variants.

Crucially, the article notes that these models can surface novel genetic signals—even when the biomedical literature is thin. Yet it also cautions that impressive offline results have not always translated into robust real-world diagnostic performance. Bridging that gap likely requires careful validation, diverse cohorts, and alignment with clinical workflows.

Finally, Liam Critchley reports on progress in e-noses for cancer screening in “Advanced Olfactory Cancer Detection: When E-Noses Sniff the Skin.” Instead of invasive sampling, the approach targets volatile organic compounds carried through skin-exhaled breath.

The pilot study highlighted quantum-dot-based sensing using cadmium sulfide nanocrystals to capture chemical signatures. Researchers report high discrimination between cancer patients and healthy controls, with the potential to classify disease severity—though the clinical validation pathway remains essential before deployment.

Together, these pieces paint a viral, forward-looking picture of digital health: AI can accelerate discovery and learning, but only if systems are engineered for trust, calibration, and meaningful human oversight.

Subject of Research: People; medical diagnosis; medical genetics; artificial intelligence; education/education technology; clinical training; biomarkers.
Article Title: Charting a Course for AI in Medical Education; AI Models Could Improve Diagnosis and Care for Rare Diseases; Advanced Olfactory Cancer Detection: When E-Noses Sniff the Skin.
News Publication Date: July 17, 2026.
Web References: https://www.jmir.org/2026/1/e106582
References: Cottingham K. Charting a Course for AI in Medical Education. J Med Internet Res 2026;28:e106486. DOI: 10.2196/106486. Spichak S. AI Models Could Improve Diagnosis and Care for Rare Diseases. J Med Internet Res 2026;28:e106852. DOI: 10.2196/106582. Critchley L. Advanced Olfactory Cancer Detection: When E-Noses Sniff the Skin. J Med Internet Res 2026;28:e106481. DOI: 10.2196/100948.
Image Credits: N/A.
Keywords: artificial intelligence; medical education; foundation models; rare diseases; electronic nose; cancer screening; biomarkers; clinical training; volatile organic compounds.

The authors argue that the teaching role has expanded beyond day-to-day lesson delivery. Educators now need practical ways to handle professional logistics, manage evolving curriculum expectations, and interpret education policy in ways that still keep learning priorities at the center. This includes both short-term preparation for new roles and longer-term support structures that sustain teaching quality.

A core focus is the multi-faceted challenge teachers face when balancing immediate student needs with long-range professional development. Dr Loretta Bowshall-Freeman, Deputy Teaching Program Director (Education) at Flinders University, highlights how preparation must include strategies for working with curriculum demands and policy constraints while maintaining reflective practice.

The book also provides technical and instructional frameworks for curriculum navigation and classroom management. It addresses how teachers can design inclusive, engaging learning opportunities and create assessment approaches that are aligned with student thinking rather than only measuring final outputs.

One of the book’s research-informed claims is that classroom decision-making should be guided by observable learner cognition. Co-author Dr Rozi Binte Rahmat explains that teachers continuously “read the room,” tracking which students are engaged, which are struggling, and which ideas are emerging—then adjusting instruction accordingly.

This adaptive approach is presented as a mechanism for formative learning: strategies become meaningful when they help teachers notice how students reason, respond to diverse needs, and enable learners to demonstrate understanding in multiple ways. In other words, assessment is treated as a feedback loop that shapes instruction in real time.

Beyond individual pedagogy, the text explores professional collaboration and networking as methods for long-term growth. It includes case studies, recommended readings, and guided responses designed to help educators translate theory into practical routines.

Teaching Strategies in the 21st Century: Where to Now? by Bowshall-Freeman, Rozi Binte Rahmat, and Michael Colbung is available as an eBook from 16 July, with hardcopy editions available from 30 July.

Subject of Research: Teacher education strategies and adaptive, research-informed classroom practice
Article Title: Where to Now? Teaching in the 21st Century
News Publication Date: 16 July (eBook availability)
Web References: Cambridge University Press (publisher)
References: Not specified in the provided content
Image Credits: Not specified in the provided content
Keywords: teacher training, formative assessment, inclusive teaching, curriculum policy, reflective practice, classroom decision-making, student-centered learning

MicroRNAs function as post-transcriptional regulators: they fine-tune which proteins cells produce and, by doing so, help maintain protein homeostasis (proteostasis). Proteostasis supports proper folding, turnover, and balance of the proteome; when it collapses, cells can shift toward dysfunctional survival programs—an enabling step in cancer.

The work centers on the idea that microRNAs act like molecular traffic lights for cell-state decisions. According to the study’s lead investigator, disrupting proteostasis is a key reason many cancer cells become cancerous. By reintroducing microRNA-15a and microRNA-16 into NSCLC cells, the researchers observed a partial re-establishment of normal regulatory constraints that control metabolism and growth.

Mechanistically, the approach targets signaling downstream of gene expression rather than a single oncogenic protein. This matters because cancer frequently reflects network failures: when multiple “brakes” on cell division are removed, cells can enter a self-reinforcing cycle of growth. MicroRNA replacement appears to restore some of these brakes by altering proteostasis-related pathways.

The investigators emphasize translational caution. The results do not claim cure; instead, they propose that microRNA-based therapy might arrest or slow disease enough to create time for combination treatment. In clinical oncology, such time could improve the effectiveness of surgery, radiation, or pharmacologic regimens delivered later.

The microRNAs were not initially discovered in cancer research. Fluckey’s lab began with skeletal muscle biology, where microRNAs help regulate muscle growth, protein turnover, and insulin sensitivity. Building on those observations, the team suspected the same regulatory RNAs might influence tumor behavior.

Future therapy development will likely require delivery systems that preferentially enter cancer cells while limiting exposure to healthy tissue. One envisioned strategy uses engineered viral vectors to deliver therapeutic genetic material carrying the microRNA program.

The study also highlights the value of cross-disciplinary collaboration within Texas A&M, linking investigators with complementary expertise to generate new experimental directions.

Subject of Research: Cells
Article Title: MicroRNA 15a and 16 Regulate Proteostasis in Non-Small Cell Lung Cancer
News Publication Date: 2-May-2026
Web References: https://pubmed.ncbi.nlm.nih.gov/42077822/
References: 10.1096/fba.2026-00075
Image Credits: Texas A&M University

Keywords: microRNA, lung cancer, NSCLC, proteostasis, proteostasis regulation, molecular regulation, RNA therapeutics, cellular growth control, viral delivery

The paper frames the admissions decision as a tradeoff between “information” and “access.” Test scores can act as a reliable signal when other application components—such as grades, essays, or recommendations—carry different levels of predictive power across student groups. At the same time, removing the test can lower barriers that prevent qualified candidates from applying.

Using a statistical discrimination framework, the researchers show how eliminating a feature like test-score review changes the informational environment faced by admissions officers. In practice, admissions decisions depend on how all application data are observed together and how policy choices shape the applicant pool that reaches the evaluation stage.

Crucially, the study finds that outcomes do not move in only one direction. Dropping testing may lead to improvements in both diversity and academic merit in some settings, while in others it can worsen both simultaneously—demonstrating that policy effects are context dependent rather than universally beneficial or harmful.

The analysis incorporates capacity constraints and fairness goals, and it examines both non-strategic access barriers and strategic behavior by applicants. The team uses calibrated simulations to explore realistic admissions scenarios where results vary sharply depending on how other signals perform and who actually applies.

One striking implication involves student test-taking behavior in multi-school environments. When one institution drops standardized testing while another retains it, some qualified students may decide not to take the test at all, potentially reducing their chances at schools they would otherwise have attended.

The authors also emphasize a modeling insight: changing whether scores are available can alter how admissions systems “learn” from the remaining data. This can shift the observed relationship between application inputs and academic outcomes, not just who is admitted.

“Our results highlight that policymakers and admissions offices need to consider both the informational environment and access barriers, rather than treating the testing decision as a simple ‘tests good vs. tests bad’ debate,” the study notes.

The paper concludes that institutions may benefit from investing in better signals for all applicants while simultaneously reducing access barriers, instead of relying solely on the removal of standardized test-score requirements.

Read the full study via the DOI link and associated materials.

Subject of Research: Admissions policies and algorithmic decision-making
Article Title: Dropping Standardized Testing for Admissions Trades Off Information and Access
News Publication Date: 2-Jun-2026
Web References: https://doi.org/10.1287/mnsc.2023.02573 ; https://drive.google.com/file/d/1unBaPIvY_ZfuCqzH6h1Ji5jTPYuJwyz5/view?usp=sharing
References: 10.1287/mnsc.2023.02573
Image Credits: Not provided
Keywords: Standardized testing, college admissions, statistical discrimination, diversity, academic merit, access barriers, fairness, applicant behavior

A new study in the Chinese Journal of Medical Education Research reports tests of a virtual–physical integrated scenario simulation designed to close that gap. Researchers from Peking Union Medical College School of Nursing and Beijing community health centers compared the approach with conventional laboratory-based scenario training.

A total of 143 third-year undergraduate nursing students (enrolled in 2022) participated in the March–April 2025 intervention period. After the same three-hour teaching block, 128 students completed pre- and post-questionnaires, while 24 students in the integrated-simulation arm also took part in semi-structured interviews.

Both groups trained on the same home-visit workflow: preparing the encounter, conducting inquiry and physical assessment, measuring rapid blood glucose, delivering health education, and finishing documentation and post-visit summaries. The difference was how uncertainty was generated during the scenario.

In the conventional group, classmates acted as the older adult and family member according to a written script. In the integrated group, students worked in a “smart eldercare” laboratory featuring multimedia displays, physical models, and a wireless simulation system in which an intelligent agent represented the older adult.

The system supported AI-assisted inquiry, blood pressure and glucose measurement, and transitions between a community health center context and a simulated home environment. In interviews, students described the intelligent simulator as responsive—questioning, showing impatience, and altering emotional cues in ways that scripts rarely capture.

The strongest quantitative result was “learning immersion.” Students trained with the integrated setup achieved a higher total immersion score than the conventional group (72.42±8.19 vs 69.44±8.41), with gains also reported in emotional engagement and perceived learning experience.

However, immersion did not translate cleanly into immediate competence. After teaching, there was no significant between-group difference in home-visit skills or attitudes. Skill scores were similar (virtual–physical: 60.60±6.85; conventional: 60.89±6.62), suggesting three hours may be insufficient for measurable skill consolidation.

Students also reported friction: response delays, imperfect speech recognition, the need to press buttons during interaction, and occasional breakdowns in conversational flow. The authors argue that technology can increase realism, but instructional design, repeated practice, and smoother interfaces are essential before simulated engagement becomes durable nursing competence.

Subject of Research: People
Article Title: Study on the application effects of virtual-reality integrated scenario simulation in home visit teaching
News Publication Date: 20-May-2026
Web References: http://dx.doi.org/10.3760/cma.j.cn116021-20251129-02253
References: 10.3760/cma.j.cn116021-20251129-02253
Image Credits:
Keywords: nursing education, home visit training, virtual–physical simulation, learning immersion, smart eldercare, AI-assisted scenarios, educational technology

Within the first two years after graduation, resident doctors show prescribing error rates up to twice those of other healthcare professionals. Researchers attribute part of this gap to limited opportunities for deliberate practice and feedback under realistic clinical uncertainty.

During Sense about Science Evidence Week, Taylor & Francis showcased findings highlighting the role of structured, video-enhanced feedback in improving prescribing performance. The core idea is to turn everyday prescribing moments into measurable learning cycles.

In collaboration with Professor Rakesh Patel, Director of Undergraduate Medicine at St Mary’s University, the work draws on evidence published in Medical Teacher. The study evaluates how personalized feedback—paired with short video-based review—can target specific decision points rather than generic coaching.

Importantly, the intervention is designed to close the performance gap between novice and experienced prescribers. That effect is framed as a shift from “knowing what to do” toward reliably demonstrating safe behavior in routine, high-pressure environments.

The program’s feasibility is also emphasized: it is described as cost-effective and scalable across Foundation Training. Scaling matters because training quality often varies, while prescribing risks affect patients at national scale.

Policy implications were a key part of the message delivered at Evidence Week. Speakers argued for accrediting prescribing competence using performance metrics observed in practice, so assessment reflects safe outcomes rather than exam passage alone.

“It is clear that education without structured feedback is not enough,” Patel said, adding that personalized feedback supported by performance data helps newly qualified doctors develop safer prescribing behaviours.

Sense about Science’s Evidence Week—now in its ninth year—brings MPs and scientists together for rapid briefings on policy-relevant research. Organizers say the format helps align government decision-making with real-world evidence.

Subject of Research: Prescribing safety training for newly qualified resident doctors; structured video-enhanced feedback in medical education
Article Title: “published in the journal Medical Teacher” (exact title not provided in the provided content)
News Publication Date: Not provided in the provided content
Web References: https://senseaboutscience.org/evidence-week/ ; https://www.tandfonline.com/doi/full/10.1080/0142159X.2020.1748183
References: Taylor & Francis / Medical Teacher article linked above (exact citation details not provided in the provided content)
Image Credits: Not provided in the provided content
Keywords: prescribing errors, medical education reform, video-enhanced feedback, foundation training, patient safety, performance metrics, resident doctors, clinical decision-making

The study followed 119 child–guardian pairs over two years, using objective activity monitoring. Children wore wrist-based monitors to quantify MVPA, while families also completed structured questionnaires. The research focused on how different types of guidance—content-only versus motivation-focused coaching—shape children’s drive to keep exercising.

Instead of relying on external pressure, the team grounded the coaching strategy in Self-Determination Theory (SDT). SDT emphasizes three psychological needs—autonomy, competence, and relatedness—that, when supported, can sustain intrinsic motivation. Accordingly, guardians were encouraged to offer exercise choices, provide specific positive feedback, and create short parent–child interaction moments during activity sessions.

Participants were randomly assigned to four conditions: an Exercise Only group received video workouts; a Coach Only group received SDT-informed coaching videos; an Exercise-plus-coaching group received both; and a Control group received no intervention. This randomized controlled design allowed the researchers to isolate which components actually changed real-world activity patterns.

After implementation, children in the Exercise Only and Exercise-plus-coaching groups increased average daily MVPA from 34.6 minutes to roughly 41–42 minutes, an improvement of about 6–7 minutes per day. Meanwhile, the Control group’s activity decreased by approximately 14 minutes, highlighting how quickly routines can deteriorate without structured support.

Dr Gary Chow Chi-ching, who led the project, noted that parenting styles based purely on pressure may produce short-lived compliance. In contrast, autonomy-supportive communication appeared to help children maintain motivation and better satisfy their psychological needs—an effect the team believes is key to long-term behavior change.

The exercise library was co-designed with students, aiming for short, fun, and household-friendly sessions that fit space constraints and varying schedules. Importantly for real families, the intervention also worked for parents with full-time jobs, who reportedly found time to join activities with their children.

Funded by the Research Grants Council’s Early Career Scheme, the results were published in the Journal of Exercise Science & Fitness. The team is now planning school-integrated digital platforms and additional support pathways to keep children active beyond the initial trial—an approach that could make home exercise both measurable and viral.

Subject of Research: People
Article Title: An SDT-informed online intervention supporting children’s home-based exercise: A randomized controlled trial
News Publication Date: 1-Jul-2026
Web References: https://www.sciencedirect.com/science/article/pii/S1728869X26000390 , https://www.sdtgames.com/en
References: Journal of Exercise Science & Fitness
Image Credits:
Keywords: physical activity, children, Hong Kong, Self-Determination Theory, randomized controlled trial, MVPA, home-based exercise, parental support, intrinsic motivation

A new push at the University of Toronto’s Data Sciences Institute (DSI) aims to lower that barrier. Anthropic will provide $1 million in Claude API credits to support research and education, giving eligible users programmatic access to Claude models through a hosted API interface. With credits, teams can run experiments, build prototypes, and test AI-assisted workflows without needing to individually shoulder usage costs.

For researchers, the API unlocks a practical development path: model calls can be integrated into analysis pipelines, software tooling, and automation scripts, enabling iterative experimentation. For educators, access can support training scenarios where students evaluate model outputs, compare prompt strategies, and learn responsible deployment patterns.

DSI describes itself as a bridge between interdisciplinary research and real-world impact. The institute convenes faculty, students, and industry partners, translating data science methods into outcomes. This initiative fits that mission by making advanced AI capabilities more widely available across the university.

Rather than distributing credits automatically, DSI will run a competitive process. The institute will leverage prior grant and software support experiences, using scientific review panels to assess project quality and potential impact. Selected teams are expected to use the credits to pursue high-value research questions and build tools that can be adopted or extended.

Since 2021, DSI has awarded $19 million in funding to more than 500 researchers across all three University of Toronto campuses, alongside external research institutes. Those efforts have supported subsequent external grants totaling over $126 million, suggesting the model has worked as a catalyst for follow-on funding.

“As we steward and distribute these credits, we’re focused on safe, high-quality, and impactful research,” said Professor Gary Bader, Associate Director, Research & Software at DSI. The review component is positioned as a quality and safety filter, aligning access with responsible experimentation.

Anthropic’s support reflects a long-term view of AI progress. “We’re glad to be supporting future innovative U of T research with Claude,” said Brian Peters, Head of North America Government Affairs at Anthropic. The partnership is also framed as a continuation of the university’s deep engagement with neural network research.

U of T’s standing in data science and artificial intelligence remains a major draw, and the institute’s approach could help translate that leadership into broader, hands-on access. The call for applications runs from July 20 to September 25, 2026.

Subject of Research: Advanced AI model access via Claude API credits for research and education
Article Title: Anthropic Grants $1M in Claude API Credits to University of Toronto’s Data Sciences Institute
News Publication Date:
Web References: https://datasciences.utoronto.ca/claude-api-credit/ ; https://datasciences.utoronto.ca/partners/
References:
Image Credits:

Keywords: Claude API, Anthropic, Data Sciences Institute, University of Toronto, artificial intelligence, research funding, big data, neural networks, data analysis, information processing

The findings target a less-discussed source of stress: the experienced clinicians who supervise trainees. When preceptors have to explain workflows, documentation logic, and order entry from scratch, the supervisory role can become an additional burden—particularly in busy clinics where time is tight.

Researchers describe EHRs as digital, shareable repositories of patient history designed to coordinate care across settings. In that context, early training functions as workflow familiarization, not simply software instruction. By learning typical navigation paths, documentation structures, and order-entry steps before clinical rotations, students are better prepared to contribute.

UT Arlington researchers Rhonda Winegar and Mari Tietze coauthored the work after integrating an academic EHR platform into family nurse practitioner coursework. The study followed 121 graduate students enrolled in two sequential courses, Family I and Family II, assessing satisfaction and perceived readiness as exposure increased.

Students with prior EHR familiarity reported higher confidence and clearer expectations for clinical work. In contrast, Family I students—those encountering EHRs for the first time in the program—reported lower preparedness and greater frustration, suggesting that “learning on the fly” is not a consistent process at clinical sites.

A key technical nuance emerged: clinical workflows vary by practice setting and by preceptor behavior. In some environments, patient encounters may occur before documentation and order entry are completed, meaning students may not observe the EHR steps that later become essential.

The study also framed the issue within broader workforce concerns. Burnout advisories have highlighted EHR-related strain as a contributing factor, and earlier training may reduce the cascading stress that occurs when supervisors compensate for training gaps.

Tietze emphasized that EHR expectations are shifting quickly, pointing to emerging tools such as ambient listening, where AI can capture conversations and draft clinical notes. That trajectory suggests education must evolve toward earlier, structured, and technologically grounded preparation.

Future research is planned with larger student cohorts to test how reliably early EHR integration improves outcomes across programs and clinical environments. For now, the study’s message is straightforward: prepare students in the classroom, so preceptors aren’t forced to become the first line of technical instruction.

Subject of Research: People
Article Title: Academic EHR integration in family NP education
News Publication Date: 15-Apr-2026
Web References: http://dx.doi.org/10.1097/01.NPR.0000000000000422
References: 10.1097/01.NPR.0000000000000422
Image Credits:
Keywords: electronic health records, nurse practitioner education, clinical training, burnout, preceptors, EHR workflow, ambient listening, academic integration