Innovative Platform Research Articles

From Traditional to Digital: The Evolution of Business Models in Hospitality Through Platforms

The hospitality business model has undergone profound changes influenced by successive waves of technological advances and platforms. This paper explores how different waves of technologies and platforms are shaping the evolution of the hospitality business model. Employing a systematic literature review, this research analyzes how platform innovation has driven significant shifts in the industry. The analysis yielded four key findings. Firstly, the incorporation of digital technologies resulted in a radical transformation of conventional business models, prompting substantial alterations in marketing strategies, distribution processes, and consumer behavior patterns. Secondly, the industry has undergone five significant technological revolutions, evolving from steam-powered transportation to the integration of artificial intelligence (AI) and the Internet of Things (IoT), thereby driving a shift towards innovation-centric business models. Thirdly, the advent of digital platforms, most notably online travel agencies (OTAs), posed a challenge to traditional hospitality models by introducing personalized experiences and disrupting established market norms. While digital platforms offer advantages such as enhanced convenience and customization, they also present challenges, including intensified competition and declining profit margins. Nonetheless, technological advancements such as AI, virtual reality (VR), and augmented reality (AR) present a potential avenue for redefining value propositions and enhancing customer experiences. Fourth, the future of the hospitality business model is poised for further disruption, influenced by the emergence of new virtual platforms and services. This could potentially result in a reshaping of the industry’s value chain and value proposition.

Edge Computing Architecture for the Management of Underwater Cultural Heritage

Underwater cultural heritage (UCH) is a valuable resource that preserves humanity’s historical legacy, offering insights into traditions and civilisations. Despite its significance, UCH faces threats from inadequate regulatory frameworks, insufficient conservation technologies, and climate-induced environmental changes. This paper proposes an innovative platform combining the internet of underwater things and edge computing technologies to enhance UCH’s real-time monitoring, localisation, and management. The platform processes data through a central unit installed on a buoy near heritage sites, enabling efficient data analysis and decision making without relying on cloud connectivity. Integrating acoustic communication systems, LoRa technology, and nonterrestrial networks supports a robust multilayered communication infrastructure for continuous operation, even in remote maritime areas. The platform’s edge node deploys artificial intelligence models for real-time risk assessment, focusing on key environmental parameters to predict and mitigate corrosion rates and climate-related threats. A case study illustrates the system’s capabilities in underwater localisation, demonstrating how edge computing and acoustic triangulation techniques enable precise tracking.

Factors, Counter-Trafficking Programs, and Geographical Variations in Human Trafficking Literature (2010–2022)

ABSTRACT This paper provides an overview of key findings from human trafficking studies published between 2010 and 2022. It presents recent research trends and interventions on human trafficking. The purpose of this study was to bridge the research-to-policy gap by identifying priority areas for research and creating an innovative platform, the Human Trafficking Evidence Gap Map (EGM). Through consultations and thematic coding, the most and least commonly studied factors and outcomes related to human trafficking were identified. The study reveals geographical variations in counter-trafficking programs and policies. The paper contributes to developing the Human Trafficking EGM as a tool to facilitate evidence-informed decision-making and supports progress toward the UN Sustainable Development Goals 5, 8 and 10 by enhancing the understanding of trafficking factors and outcomes. The findings empower researchers and policymakers to develop targeted interventions, strengthen legal frameworks, and foster international cooperation. Ultimately, these efforts will advance the efforts to eradicate human trafficking and promote a more just and equitable society.

Experimental demonstration of the equivalence of entropic uncertainty with wave-particle duality.

Wave-particle duality is one of the most notable and counterintuitive features of quantum mechanics, illustrating that two incompatible observables cannot be measured simultaneously with arbitrary precision. In this work, we experimentally demonstrate the equivalence of wave-particle duality and entropic uncertainty relations using orbital angular momentum (OAM) states of light. Our experiment uses an innovative and reconfigurable platform composed of few-mode optical fibers and photonic lanterns, showcasing the versatility of this technology for quantum information processing. Our results provide fundamental insights into the complementarity principle from an informational perspective, with implications for the broader field of quantum technologies.

A low-cost, open-source cylindrical Couette rheometer

Rheology describes the flow of fluids from food and plastics, to coatings, adhesives, and 3D printing inks, and is commonly denoted by viscosity alone as a simplification. While viscometers adequately probe Newtonian (constant) viscosity, most fluids have complex viscosity, requiring tests over multiple shear rates, and transient measurements. As a result, rheometers are typically large, expensive, and require additional infrastructure (e.g., gas lines), rendering them inaccessible for regular use by many individuals, small organizations, and educators. Here, we introduce a low-cost (under USD$200 bill of materials) Open Source Rheometer (OSR), constructed entirely from thermoplastic 3D printed components and off-the-shelf electromechanical components. A sample fluid rests in a cup while a micro stepping motor rotates a tool inside the cup, applying strain-controlled shear flow. A loadcell measures reaction torque exerted on the cup, and viscosity is calculated. To establish the measurement range, the viscosity of four Newtonian samples of 0.1–10 Pa.s were measured with the OSR and compared to benchmark values from a laboratory rheometer, showing under 23% error. Building on this, flow curves of three complex fluids – a microgel (hand sanitizer), foam (Gillette), and biopolymer solution (1% Xanthan Gum) – were measured with a similar error range. Stress relaxation, a transient test, was demonstrated on the biopolymer solution to extract the nonlinear damping function. We finally include detailed exposition of measurement windows, sources of error, and future design suggestions. The OSR cost is ∼1/25th that of commercially available devices with comparable minimum torque (200 µN.m), and provides a fully open-source platform for further innovation in customized rheometry.

“Teledentistry” using a mobile app (Telesmile) to improve oral health among the visually impaired and hearing-impaired populations in Saudi Arabia: a randomized controlled study

ObjectiveTo assess the efficacy of a “teledentistry” method using a mobile app (Telesmile) in enhancing knowledge of oral health conditions and oral hygiene practices among the blind and deaf populations in Jazan Province in Saudi Arabia.MethodsA randomized parallel design controlled study was conducted among 50 blind and 50 deaf subjects between the ages of 12–18 years, randomly chosen from blind and deaf schools. The participants were selected based on the inclusion and exclusion criteria. An innovative teledentistry platform named Telesmile, a mobile application for the Apple iOS App Store and Google Play Store, was developed. Multimedia Arabic dental sign language oral hygiene instructional videos were created and uploaded in the Telesmile mobile application under the deaf category. Similarly, oral hygiene instructions were audio recorded by experts and uploaded under the blind category in the Telesmile mobile application. Group I of the blind (n = 25) and deaf participants (n = 25) received regular oral hygiene instructions while Group II of the blind (n = 25) and deaf (n = 25) participants received the Telesmile mobile application intervention. The knowledge of the participants pertaining to oral health and oral hygiene practices was evaluated using a close-ended questionnaire comprising 14 questions at the initial visit (T0). Training sessions were conducted for all participants and the Telesmile mobile application was distributed among the participants in Group II. After 4 weeks (T1), the knowledge of the participants regarding oral health and hygiene practice was re-evaluated and compared between each group.ResultsThe chi-square test revealed that the marginal mean of the knowledge of the blind and deaf participants pertaining to oral health and oral hygiene practices was very poor at their initial visit (T0) and it significantly increased (p < 0.001) after 4 weeks (T1) of using the Telesmile mobile application.ConclusionThe Telesmile mobile application can significantly enhance oral hygiene knowledge among blind and deaf people. The audio technique was an effective tool to deliver oral health education which could result in improving the oral health status of blind participants. The video demonstrations were also effective in enhancing the oral health and oral hygiene knowledge of deaf individuals.

An innovative cellular medicine approach via the utilization of novel nanotechnology-based biomechatronic platforms as a label-free biomarker for early melanoma diagnosis

Innovative cellular medicine (ICM) is an exponentially emerging field with a promising approach to combating complex and ubiquitous life-threatening diseases such as multiple sclerosis (MS), arthritis, Parkinson’s disease, Alzheimer’s, heart disease, and cancer. Together with the advancement of nanotechnology and bio-mechatronics, ICM revolutionizes cellular therapy in understanding the essence and nature of the disease initiated at a single-cell level. This paper focuses on the intricate nature of cancer that requires multi-disciplinary efforts to characterize it well in order to achieve the objectives of modern world contemporary medicine in the early detection of the disease at a cellular level and potentially arrest its proliferation mechanism. This justifies the multidisciplinary research backgrounds of the authors of this paper in advancing cellular medicine by bridging the gap between experimental biology and the engineering field. Thus, in pursuing this approach, two novel miniaturized and highly versatile biomechatronic platforms with dedicated operating software and microelectronics are designed, modeled, nanofabricated, and tested in numerous in vitro experiments to investigate a hypothesis and arrive at a proven theorem in carcinogenesis by interrelating cellular contractile force, membrane potential, and cellular morphology for early detection and characterization of melanoma cancer cells. The novelties that flourished within this work are manifested in sixfold: (1) developing a mathematical model that utilizes a Heaviside step function, as well as a pin-force model to compute the contractile force of a living cell, (2) deriving an expression of cell-membrane potential based on Laplace and Fourier Transform and their Inverse Transform functions by encountering Warburg diffusion impedance factor, (3) nano-fabricating novel biomechatronic platforms with associated microelectronics and customized software that extract cellular physics and mechanics, (4) developing a label-free biomarker, (5) arrive at a proved theorem in developing a mathematical expression in relating cancer cell mechanobiology to its biophysics in connection to the stage of the disease, and (6) to the first time in literature, and to the best of the authors’ knowledge, discriminating different stages and morphology of cancer cell melanoma based on their cell-membrane potentials, and associated contractile forces that could introduce a new venue of cellular therapeutic modalities, preclinical early cancer diagnosis, and a novel approach in immunotherapy drug development. The proposed innovative technology-based versatile bio-mechatronic platforms shall be extended for future studies, investigating the role of electrochemical signaling of the nervous system in cancer formation that will significantly impact modern oncology by pursuing a targeted immunotherapy approach. This work also provides a robust platform for immunotherapy practitioners in extending the study of cellular biophysics in stalling neural-cancer interactions, of which the FDA-approved chimeric antigen receptor (CAR)-T cell therapies can be enhanced (genetically engineered) in a lab by improving its receptors to capture cancer antigens. This work amplifies the importance of studying neurotransmitters and electrochemical signaling molecules in shaping the immune T-cell function and its effectiveness in arresting cancer proliferation rate (mechanobiology mechanism).

Exploration and Practice of Innovative and Entrepreneurial Talent Training Model in Medical Colleges under the Background of “New Medicine”

Innovation and entrepreneurship education has become one of the important directions of higher education reform, but innovation and entrepreneurship education in medical colleges generally lags behind other discipline universities or comprehensive universities. Actively exploring the training mode of innovation and entrepreneurship talents is of great significance for cultivating innovative medical talents needed by the country and society. At present, innovation and entrepreneurship education in higher medical colleges is facing many challenges, the most important of which include the lack of concept in innovation and entrepreneurship education, medical students’ weak awareness of innovation and entrepreneurship, and poor construction of innovation and entrepreneurship teaching staff. To address these challenges, we will introduce incentive measures for innovation and entrepreneurship education at the college level, and improve the guarantee and incentive mechanisms for innovation and entrepreneurship education; create an “Innovation and Entrepreneurship Education Platform” for teachers and students to exchange ideas on innovation and entrepreneurship; start building a high-quality team of innovation and entrepreneurship teachers, promote the continuous improvement of the quality of innovation and entrepreneurship education, and ensure the quality of medical talent training.

Biomimetic Cell Membrane Layers for the Detection of Insulin and Glucagon.

The growing need for reliable and rapid insulin testing to enhance glycemic management has spurred intensive exploration of new insulin-binding bioreceptors and innovative biosensing platforms for detecting this hormone, along with glucagon, in biological samples. Here, by leveraging the native protein receptors on the HepG2 cell membrane, we construct a simple and chemical-free biomimetic molecular recognition layer for the detection of insulin and glucagon. Unlike traditional affinity sensors, which require lengthy surface modifications on the electrochemical transducers and use of two different capture antibodies to recognize each analyte, this new biomimetic sensing strategy employs a simple drop-casting of a natural cell membrane recognition layer onto the electrochemical transducer. This approach allows for the concurrent capture and detection of both insulin and glucagon. We investigate the presence of insulin and glucagon receptors on the HepG2 cell membrane and demonstrate its multiplexing bioelectronic sensing capabilities through the binding of the captured insulin and glucagon to enzyme-tagged signaling antibodies. This new molecular recognition layer offers highly sensitive simultaneous detection of insulin and glucagon under decentralized conditions, holding considerable promise for the management of diabetes and the development of diverse biomimetic diagnostic platforms.

Information provision and financial incentives in Catalonia's public primary care (2010–2019): an interrupted time series analysis

The relative efficacy of information provision versus financial incentives in improving primary care quality remains a critical, unresolved question. We investigated these two strategies in Catalonia's public primary care system from 2010 to 2019: an innovative online platform providing real-time quality indicator information and targeted economic incentives for achieving indicator goals. We conducted a comprehensive interrupted time series regression analysis on data from 272 primary care practices (5,628,080 patients). This analysis used linear regression models with Newey-West standard errors, and a sensitivity analysis including logit transformations to address ceiling effects. We evaluated 1) immediate post-intervention changes (step changes) in indicator results and inter-practice variability (coefficient of variation, CV), and 2) shifts in pre-intervention trends (slopes). We scrutinized 39 indicators after rigorous quality control: 23 novel (12 informed, 11 incentivized) and 16 derived from existing incentivized indicators. Robustness checks included 14 consistently incentivized and 10 non-intervened indicators. Overall, we assessed 63 indicators: 18 control, 13 follow-up, 9 quaternary prevention, 7 treatment, 7 diagnosis, 6 screening and 3 vaccination indicators. Informed indicators showed positive impacts in 75% (9/12) of cases, and incentivized indicators in 64% (7/11) of cases. Incentivized indicators displayed improvements in annual trends ranging from 6.66 to 1.25 percentage points, with step changes up to 8.87 percentage points. Information led to step changes ranging from 19.67 to 1.07 percentage points, along with trend improvements between 1.09 and 0.34 percentage points annually. Both interventions were associated with step reductions in variability (up to-0.18 CV reduction) and significant trend improvements. Derived indicators showed limited improvements in results or variability (31%, 5/16), with minor step increases up to 2.22 percentage points. Our findings reveal that information provision alone can match or even surpass the impact of financial incentives in improving care quality and reducing practice variability. This challenges conventional wisdom and offers a cost-effective, scalable approach to primary care quality enhancement, with far-reaching implications for global health policy. European Union, Horizon Europe.

Strong multi-mode upconversion luminescence of YbVO4: Er3+ phosphors for multimode optical thermometry

This study explored the multi-mode upconversion luminescence in YbVO4: Er3+ under a 980nm laser. The optimal doping concentration of Er3+ ions in YbVO4: Er3+ is 0.02. The phosphor exhibits green (527nm, 2H11/2→4I15/2 and 553nm, 4S3/2→4I15/2), red (654nm, 4F9/2→4I15/2) and near-infrared emissions (803nm, 4I9/2→4I15/2). A multi-mode temperature sensor of YbVO4: Er3+ was developed, featuring three temperature sensing modes based on the luminescent intensity ratio (LIR) of 2H11/2/4S3/2 thermally coupled level, as well as the LIR of 2H11/2/4F9/2 and 4S3/2/4I9/2 non-thermally coupled levels. Corresponding maximum relative sensitivities were determined to be 1.21% K−1 at 298K, 0.93% K−1 at 298K, and 0.33% K−1 at 473K, respectively. The phosphor demonstrates notable temperature sensitivity, highlighting its potential in optical temperature sensing. This study introduces an innovative platform for crafting multi-mode self-reference optical temperature sensors, presenting substantial advancements in the field.

Smart Machine Learning Analysis and Blockchain Healthcare Platform

The Smart Machine Learning Medical Analysis and Blockchain Healthcare Platform (SMLMAP) represents a transformative approach to medical diagnostics and data management by integrating advanced machine learning algorithms with blockchain technology. This platform is designed to accurately diagnose seven critical diseases, achieving impressive diagnostic outcomes across various conditions, including diabetes, breast cancer, heart disease, kidney disease, liver disease, malaria, and pneumonia. SMLMAP employs Random Forest algorithms for text data analysis and Convolutional Neural Networks (CNNs) for image data, ensuring rapid and precise diagnostic results. In addition to enhancing diagnostic capabilities, SMLMAP addresses significant privacy and security concerns inherent in healthcare data management. The integration of blockchain technology facilitates secure, transparent, and tamper-proof storage of patient records, empowering individuals with greater control over their medical information. This dual approach not only improves the accuracy of diagnoses but also fosters trust between patients and healthcare providers by safeguarding sensitive data against unauthorized access. Key functionalities of SMLMAP include the ability to schedule doctor appointments conveniently through the platform, ensuring that patients can receive timely medical attention. Additionally, the application provides users with a weekly healthcare magazine, delivering valuable information on health tips, disease management, and wellness advice to promote informed health decisions. By leveraging the strengths of machine learning and blockchain, SMLMAP paves the way for a more efficient, accurate, and secure healthcare ecosystem. This innovative platform not only enhances the quality of medical diagnostics but also represents a significant step forward in addressing the critical challenges of data privacy and security in the healthcare sector. The findings underscore the potential of SMLMAP to revolutionize patient care and data management in the evolving landscape of healthcare technology.

Adapting smallholder irrigation systems to extreme events: a case of the Transforming Irrigation in Southern Africa (TISA) project in Zimbabwe

ABSTRACT Smallholder irrigation schemes are vulnerable to increased climate variability and change, particularly increased water stress. This paper explores whether the introduction of Agricultural Innovation Platforms and soil monitoring tools in smallholder irrigation schemes can improve the adaptive capacity of farmers and schemes in the Insiza District. Drawing on household survey and qualitative data, collected through the Transforming Irrigation in Southern Africa project, we analyse a comprehensive set of measures across four domains: field, household, community and markets. We find that social capacity and increased climate adaptation can be built with modest cost through combined social and technological interventions.

El papel de los <i>food system living labs</i> en el establecimiento de sistemas agroalimentarios sostenibles y resilientes en Colombia

Agrifood systems are crucial in food security, sustainability, and social equity. In a global context marked by challenges such as climate change and population growth, it is essential to propose new methodologies to understand the complex interconnections between the different actors and activities of the food system. In this context, food system living labs (FSLL) emerge as an effective strategy to generate alternative solutions that enable an efficient transition to resilient and sustainable agrifood systems. This review explores the concept and relevance of food system living labs, focusing on their importance, the innovations implemented, the economic, social, and environmental impacts they generate, and the challenges and successful strategies in their implementation. In addition, it analyzes four key aspects for their success: i) collaborative innovation platforms, ii) innovation for sustainability, iii) experimentation in real environments, and iv) development and adoption of new technologies, all within the framework of multisectoral participation and co-creation processes with local actors in rural and urban contexts. Finally, it proposes a model for implementation in Colombia.

Development of a doxepin-loaded chitosan nanogel as an innovative nano platform for oral mucositis treatment

Oral mucositis is a prevalent complication in patients undergoing chemotherapy. This study aimed to develop and characterize a doxepin-loaded chitosan nanogel (DX-CN) as a topical treatment option. DX-CN and chitosan nanogel (CN) were synthesized using ionic gelation and characterized by Fourier transform infrared spectroscopy (FTIR) and field emission scanning electron microscopy (FESEM). FTRI confirmed the spectral compatibility of DX-CN. The nanogels exhibited spherical morphology. Particle sizes were 322.7 nm for DX-CN and 302.8 nm for CN. Polydispersity indices (PdI) were 0.732 for DX-CN and 0.51 for CN. Zeta potentials (ZP) were +52.7 mV for DX-CN and +52.8 mV for CN. In vitro assays included drug loading capacity (96.2 % for DX-CN), drug release profile (83.39 % cumulative release over 10 h), cytotoxicity, and antioxidative effects. DX-CN exhibited significant cytocompatibility with human umbilical vein endothelial cells (HUVEC) and selective cytotoxicity against oral squamous cell carcinoma (OSCC) cells. Furthermore, DX-CN demonstrated reduced oxidative stress, as indicated by lower lipid peroxidation, lactate dehydrogenase leakage, and reactive oxygen species formation compared to doxepin alone. The findings suggest that DX-CN, with its efficient drug loading, sustained release, and targeted biocompatibility, holds promise as a therapeutic platform for the topical treatment of chemotherapy-induced oral mucositis.

Electrochemically induced release of a model dye from a pH-sensitive and electroactive microgel monolayer attached to an electrode surface

We present a novel electrochemically-induced release system featuring a pH-responsive and electroactive microgel monolayer specifically designed to enhance drug delivery mechanisms. This microgel, synthesized from acrylic acid and a ferrocene derivative, was formed on a conductive electrode surface, providing a robust platform for controlled release applications. The physical and chemical properties of the microgel were meticulously characterized using dynamic light scattering (DLS), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS), nuclear magnetic resonance (NMR), and electrochemical techniques. The microgel particles modified the electrode surface by forming a monolayer through interactions between the sulfur present in the crosslinking agent and the gold surface of the electrode. Cyclic voltammetry was used to analyze the properties of the modified electrode, and the morphology of the monolayer was confirmed by scanning electron microscopy (SEM). Notably, we demonstrated that the incorporation of positively charged crystal violet (CV) dye molecules was facilitated through electrostatic interactions with the negatively charged carboxylic groups of the microgel, resulting in effective dye retention. Our investigation revealed that the electrochemical oxidation of the ferrocene groups significantly weakens the interactions between the crystal violet (CV) dye and the polymer chains within the microgel network, facilitating controlled dye release. The release process was successfully monitored using quartz crystal microbalance with dissipation monitoring (QCM-D), confirming the system's potential for innovative drug delivery platforms and implant construction.

SmartGraphAI: Real Time Graph Generation with AI

SmartGraphAI, an innovative web platform, is designed to revolutionize the way users generate graphs in real-time using AI and large language models (LLMs). By processing natural language queries, SmartGraphAI intelligently breaks down user requests into multiple sub-queries that retrieve relevant data from the internet. This data is then integrated into user-friendly visualizations through dynamic graphs that adapt to the user’s requirements. The platform leverages advanced LLM technology for query interpretation and utilizes web scraping APIs for real-time data extraction, ensuring that users receive up-to-date, accurate insights. The backend, built on FastAPI, manages the data flow seamlessly, while the frontend, developed with React, provides a smooth and intuitive interface for users to engage with. SmartGraphAI empowers professionals across industries to quickly transform complex data into meaningful visual insights, automating the entire process from query input to graph generation, and thus, enhancing decision-making and efficiency in data analysis. Keywords AI, Graph Generation, Real-Time, Large Language Models, Data Visualization, Web Scraping

The Game of Heritage: Enhancing Virtual Museum Visits Through Gamification for Tourists

This study delves into the integration of gamification within virtual museum experiences, focusing on its effects on visitor engagement and knowledge acquisition. In today's digital cultural heritage landscape, virtual museums emerge as innovative platforms for the dissemination of educational and cultural content. This research specifically assesses the impact of gamified elements namely points, badges, and leaderboards on enhancing the visitor experience in a virtual environment dedicated to the Himmapan creatures, a crucial aspect of Thai mythology exhibited at the Roitawarabarn Baandhawalai Museum in Chiang Mai, Thailand. Utilizing a quantitative methodology that includes the user engagement scale and a knowledge acquisition questionnaire, this study compares visitor interactions between gamified and non-gamified approach of the virtual museum. The findings reveal that gamification substantially enhances visitor engagement, especially in aspects such as focused attention and rewards, and significantly boosts knowledge acquisition when compared to non-gamified experiences. These outcomes emphasize the crucial importance of integrating gamification strategies within virtual museums to cultivate an experience that is interactive, engaging, and educational for visitors.

How does artificial intelligence promote teaching innovation in basic education? Teaching experience from Macau, China

Artificial intelligence has transformed teachers’ teaching models. This article explores the application of artificial intelligence in basic education in Macao middle schools. This study adopts case analysis in qualitative research, using a total of eight cases from the innovative technology education platform of the Macau education and Youth Development Bureau. These data illustrate how Macao’s artificial intelligence technology promotes teaching innovation in basic education. These eight cases are closely related to the application of artificial intelligence in basic education in Macao. The survey results show that Macao’s education policy has a positive effect on teaching innovation in artificial intelligence education. In teaching practice, the school also cooperates with the government’s policy. The application of AI technology in teaching, students’ learning styles, changes in teachers’ roles, and new needs for teacher training are all influential.

3D in vitro modelling of post-partum cardiovascular health reveals unique characteristics and signatures following hypertensive disorders in pregnancy

BackgroundHypertensive disorders of pregnancy (HDP) affect 2–8% of pregnancies and are associated postpartum with increased cardiovascular disease (CVD) risk, although mechanisms are poorly understood.MethodsHuman induced pluripotent stem cells (iPSC)-derived cardiomyocytes, cardiac fibroblasts and coronary artery endothelial cells were cocultured to form cardiac spheroids (CSs) in collagen type-1 hydrogels containing 10% patient plasma collected five years postpartum [n = 5 per group: normotensive control, gestational hypertension (GH) and preeclampsia (PE)]. Plasma-treated CSs were assessed for cell viability and contractile function and subjected to immunofluorescence staining and imaging. A quantitative proteomic analysis of plasma samples was conducted (controls n = 21; GH n = 5; PE n = 12).ResultsContraction frequency (CF) was increased in PE-treated CSs (CF: 45.5 ± 3.4 contractions/minute, p < 0.001) and GH-treated CSs (CF: 45.7 ± 4.0 contractions/minute, p < 0.001), compared to controls (CF = 21.8 ± 2.6 contractions/min). Only PE-treated CSs presented significantly increased fractional shortening (FS) % (9.95 ± 1.8%, p < 0.05) compared to controls (3.7 ± 1.1%). GH-treated CSs showed a reduction in cell viability (p < 0.05) and an increase in α-SMA expression (p < 0.05). Proteomics analyses identified twenty differentially abundant proteins, with hemoglobin A2 being the only protein perturbed in both GH and PE versus control plasma (p < 0.05).ConclusionsThe innovative patient-relevant CS platforms led to the discovery of biomarkers/targets linked to cell death signaling and cardiac remodeling in GH-induced CVD and vascular/endothelial cell dysfunction in PE-induced CVD.