Continued Expansion Research Articles

Abstract 1293: PMed-TRIAL database: an efficient and intelligent data integration platform shaping the future of drug development

Abstract With the rapid advancements in artificial intelligence (AI) and big data technologies, the fields of precision medicine and drug development have entered a transformative data-driven era. Leveraging years of accumulation and expertise, LIDE launched the PMed-TRIAL Database in 2023. Through continuous iteration and expansion, PMed-TRIAL has evolved into a comprehensive data integration and query platform, encompassing PDX (Patient-Derived Xenograft), CDX (Cell Line-Derived Xenograft), Syngeneic models, and Conditional Reprogramming Cell Lines. The platform enables efficient data retrieval and intelligent integration, providing indispensable support for clinical and drug research in this new era. The database currently hosts nearly 1, 800 PDX models, making it one of the largest PDX repositories worldwide. These models integrate and standardize a wide range of key datasets, including clinical information, treatment history, growth curves, SOC (standard of care), and H&E (hematoxylin and eosin staining) results, among others, which greatly facilitates the filtering and selection of suitable models for drug research. Furthermore, the associated whole-exome sequencing (WES) and RNA sequencing datasets provide critical evidence for drug mechanisms research. In addition to standard PDX models, the database also includes induced drug-resistance models, providing an essential resource for studying drug resistance mechanisms and screening drugs to overcome resistance. In addition to PDX models, the PMed-TRIAL Database incorporates information on Patient/PDX-derived conditional reprograming cell lines, PDXO (PDX Derived Organoids), Syngeneic models, and CDX models. This expanded scope addresses the multi-faceted demands of drug development, accelerating research timelines and enhancing the efficiency of the drug discovery process. Most importantly, the PMed-TRIAL Database standardizes and efficiently integrates diverse model datasets. The accumulation of large-scale, high-quality data not only streamlines current research efforts but also lays the groundwork for advancing AI applications in drug development in the future. By bridging innovative technologies with comprehensive data resources, PMed-TRIAL empowers researchers to unlock new possibilities in precision medicine and therapeutic innovation. Citation Format: Xinlei Chen, Youbing Guo, Loc Van, Josh Caggiula, Danyi Wen. PMed-TRIAL database: an efficient and intelligent data integration platform shaping the future of drug development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1293.

Climate and landscape modification facilitate range expansion in Spinus psaltria (Lesser Goldfinch) across the Pacific Northwest

Abstract Spinus psaltria (Lesser Goldfinch) has undergone significant range expansion throughout the Pacific Northwest in recent decades, expanding farther northward through Oregon, Idaho, and Washington. We used data from Project FeederWatch to reveal a 3.94 decimal degree or ~437.34 km northward expansion in occupancy from 2002 to 2022, with eBird Status and Trends indicating that breeding season populations increased significantly in Oregon (16.9%), Idaho (66.3%), and Washington (110.5%) from 2012 to 2022. We found that S. psaltria was more likely to colonize sites within their expanded range that had higher maximum annual temperatures and annual rainfall, increased surrounding urban development, and closer proximity to major rivers. Additionally, our models showed sites typically remained occupied once colonized, indicating permanent range expansions rather than temporary nomadic movements. Our study highlights how S. psaltria’s range in the Pacific Northwest is shaped by both climate and landscape characteristics and reflects broad ecological responses to climate change and habitat modification, suggesting continued expansion as these factors persist.

Impact of MOOC Participation on Career Advancement and Skills Development

MOOCs are utilized all over the world and can affect prospects for education accessibility, career improvement, and skills improvement. As per the study of this manuscript, it is clear that MOOCs have taken off US, India and China are notable leaders both in student adoption as well without signing on as partners. That finding is more evidence for the crucial role MOOCs have in delivering affordable, flexible and high quality education to millions around the world who don't have access to traditional education. Among the countries like India and China that have localized platforms as SWAYAM and XuetangX, to address regional needs. The United States leads with established platforms Coursera, edX etc. offers over 5000 online courses with no limitation of elective based courses. Latin America, Europe and Russia are also injecting the MOOC ecosystem to some measure but less than the other two. MOOCs help in bridging the educational gap by offering technical & professional skills development Goal and participants have reported that it has greatly improved their career prospects, employability and personal enrichment. Together these studies underscore how MOOCs also promote lifelong learning, a necessity for people in adapting to the ever changing global job market. MOOCs are changing the face of education by equalling learning opportunities on a global scale. This continued expansion underscores the potential to continue changing the face of education or skills development in years to come.

ConDo: Continual Domain Expansion for Absolute Pose Regression

Visual localization is a fundamental machine learning problem. Absolute Pose Regression (APR) trains a scene-dependent model to efficiently map an input image to the camera pose in a pre-defined scene. However, many applications have continually changing environments, where inference data at novel poses or scene conditions (weather, geometry) appear after deployment. Training APR on a fixed dataset leads to overfitting, making it fail catastrophically on challenging novel data. This work proposes Continual Domain Expansion (ConDo), which continually collects unlabeled inference data to update the deployed APR. Instead of applying standard unsupervised domain adaptation methods which are ineffective for APR, ConDo effectively learns from unlabeled data by distilling knowledge from scene-agnostic localization methods. By sampling data uniformly from historical and newly collected data, ConDo can effectively expand the generalization domain of APR. Large-scale benchmarks with various scene types are constructed to evaluate models under practical (long-term) data changes. ConDo consistently and significantly outperforms baselines across architectures, scene types, and data changes. On challenging scenes (Fig.1), it reduces the localization error by >7x (14.8m vs 1.7m). Analysis shows the robustness of ConDo against compute budgets, replay buffer sizes and teacher prediction noise. Comparing to model re-training, ConDo achieves similar performance up to 25x faster.

Sparse Transfer Learning Accelerates and Enhances Certified Robustness: A Comprehensive Study

Certified robustness is a critical measure for assessing the reliability of machine learning systems. Traditionally, the computational burden associated with certifying the robustness of machine learning models has posed a substantial challenge, particularly with the continuous expansion of model sizes. In this paper, we introduce an innovative approach to expedite the verification process for L2-norm certified robustness through sparse transfer learning. Our approach is both efficient and effective. It leverages verification results obtained from pre-training tasks and applies sparse updates to these results. To enhance performance, we incorporate dynamic sparse mask selection and introduce a novel stability-based regularizer called DiffStab. Empirical results demonstrate that our method accelerates the verification process for downstream tasks by as much as 70-80%, with only slight reductions in certified accuracy compared to dense parameter updates. We further validate that this performance improvement is even more pronounced in the few-shot transfer learning scenario.

Emerging Trends and Hot Spots in Epigenetic Modifications in Neurology: A Bibliometric Analysis.

This study employs a bibliometric analysis to examine the evolution and future trajectories in epigenetic modifications in neurology from 2004 to 2024. A total of 12,964 publications were scrutinized via the R bibliometrix package and VOSviewer for network visualization, complemented by Scimagp Graphica to elucidate global collaborative networks. Our extensive review reveals a significant growth in the field of epigenetic neurology studies, driven by an increased output of publications and evidenced by an enhanced focus on epigenetic modifications. The USA and McGill University are recognized as central contributors, with Nature leading as the most prolific journal and J. Mill and E.J. Nestler distinguishing themselves as key authors by publication volume and citation impact, respectively. A detailed keyword analysis highlighted "expression," "DNA methylation," "brain," "gene-expression," and "gene" as the most recurrent terms, indicating core areas of research concentration. Subsequent manual analysis due to software-detected inaccuracies reaffirmed Alzheimer's disease, cancer, and schizophrenia as predominant neurological diseases associated with epigenetic studies. Pathophysiological processes such as DNA methylation, oxidative stress, and synaptic plasticity have been extensively examined in relation to epigenetic modifications in neurology. Synthesis of the reference literature analysis identifies critical themes such as the role of glucocorticoid receptors, the significance of hydroxymethylcytosine in neural DNA, the implications of epigenetic patterns in mental health, and the impact of BDNF gene on memory consolidation. Emerging technologies and underexplored areas further highlight future directions. These insights into epigenetic research in neurology indicate a sustained and intensifying trajectory, hinting at expanding horizons for future therapeutic approaches and interventions. Our findings underscore an active and progressing interest in neurological epigenetics, suggesting a continued expansion and specialization in the exploration of epigenetic mechanisms and their clinical relevance.

Bibliometric Insights into Terracing Effects on Water Resources Under Climate Change: Advances in Remote Sensing and GIS Applications

With the increasing impacts of global climate change and the continuous expansion of the population, the scarcity of food and water resources, along with the protection of agricultural land, have become significant constraints to sustainable agricultural development. Terraces plays a vital role in controlling water loss and promoting sustainable agriculture, and they have been widely adopted across the globe. Using CiteSpace, this study conducted a bibliometric review of the literature on the application of remote sensing and GISs in terrace studies under global climate change. The dataset included publications from the Web of Science spanning the years 1992 to 2024. Based on a systematical analysis of 508 publications, we investigated major institutions, cross-author collaborations, keyword co-occurrences, and the evolution of the research focus areas regarding the applications of remote sensing and GISs in terrace studies. The results show that the prominent research themes in this domain include remote sensing, erosion, and climate change. China (132, 26%) and the United States (108, 21%) are the top contributors in terms of publication numbers, while European countries and institutions are more active in collaborative efforts. The research emphasis has transitioned from analyzing the environmental characteristics of terraces to a broader consideration of ecological factors and multi-scenario applications. Moreover, analyses of the keyword co-occurrence and temporal trends indicate a rising interest in the application of machine learning, deep learning, and luminescence dating in terrace studies. Moving forward, it is essential to advance the deployment of automated monitoring systems, obtain long-term continuous monitoring data, encourage the adoption of conservation agriculture technology, and strengthen early warning networks for extreme climate events in terrace research. Overall, this study underscores the importance of interdisciplinary approaches and collaborative efforts to address the myriad challenges faced by terraced agriculture in an era of rapid environmental change.

Multi-Scenario Forecasting of Land Use and Ecosystem Service Values in Coastal Regions: A Case Study of the Chaoshan Area, China

Modeling changes in ecosystem service value (ESV) resulting from land use/cover change (LUCC) in coastal regions play a crucial role in promoting regional sustainability and guiding policymaking. This study focuses on the Chaoshan region of China and analyzes the impact of land use changes in 2000, 2010, and 2020 on ESV. The Patch-generating Land Use Simulation (PLUS) model was used to simulate LUCC for 2030 under three different scenarios: natural development (ND), urban development (UD), and ecological protection (EP). The spatial distribution and aggregation degree of ESV were assessed to explore the intrinsic relationship between land use and ecosystem service value in the Chaoshan region. The results showed the following: (1) The cropland area in the Chaoshan region has significantly decreased, with the per capita cropland area dropping to 113.34 m2 (0.028 acres) by 2020. The continuous expansion of construction land has been mainly concentrated in Shantou, Jieyang, and Chaozhou, with an increasingly evident trend of urban integration among these three cities. By 2030, the growth rate of construction land in the EP scenario is expected to decline, indicating a slowdown in urban expansion. (2) Between 2000 and 2020, Shantou was the only city in the region to experience a decline in total ESV. Low ESV values in the Chaoshan region are primarily concentrated in the southeastern area. As urban integration progresses, ESV values in this region are expected to continue to decline. (3) The ongoing trend of urban integration between Shantou, Chaozhou, and Jieyang may result in the region becoming an ecologically vulnerable area. Close monitoring of potential ecological risks in this area is crucial to ensure a balance between urban development and ecological protection. This study will provide important guidance for land use policies and sustainable development in the Chaoshan region, as well as in similar coastal cities globally.

Evaluation of Land Suitability for Construction in the Turpan–Hami Region Based on the Integration of the MaxEnt Model and Regional Planning

Land resources are fundamental to regional economic development and ecological protection. As a critical tool for the scientific allocation of land resources, land suitability evaluation plays a pivotal role in achieving sustainable development goals. This study integrates the MaxEnt model with regional planning to conduct a multi-period evaluation of the construction land suitability in the Turpan–Hami region, aiming to elucidate the distribution patterns of suitability and their driving mechanisms across different historical periods. By synthesizing natural geographic and socioeconomic data, a comprehensive suitability evaluation framework was developed, enabling a multi-temporal analysis of construction land suitability from 2000 to 2023. The results revealed a clear trend of optimization in construction land suitability within the Turpan–Hami region, characterized by the continuous expansion of highly suitable areas and a significant reduction in unsuitable areas, with the regional suitability distribution becoming increasingly balanced over time. The population density, GDP, and road density were identified as the primary drivers of suitability distribution, with the population density exerting the most substantial influence. Among the natural environmental factors, the Normalized Difference Vegetation Index (NDVI) imposed significant constraints on the land suitability, particularly in ecologically sensitive areas. This study innovatively applied the MaxEnt model to the evaluation of construction land suitability, integrating it with regional planning to comprehensively assess the spatial distribution and dynamic changes in land suitability in the Turpan–Hami region. Furthermore, this research aligns closely with policy frameworks, fully considering the impacts of ecological and agricultural protection constraints within regional planning policies on the suitability distribution, and it explores optimized land use strategies under policy guidance. The findings provide a robust scientific foundation for the efficient allocation of land resources and the enhancement of ecological protection in the Turpan–Hami region.

Electrical Phenotyping of Aged Human Mesenchymal Stem Cells Using Dielectrophoresis

Human mesenchymal stem cells (hMSCs) are widely used in regenerative medicine, but large-scale in vitro expansion alters their function, impacting proliferation and differentiation potential. Currently, a predictive marker to assess these changes is lacking. Here, we used dielectrophoresis (DEP) to characterize the electrical phenotype of hMSCs derived from bone marrow (BM), adipose tissue (AT), and umbilical cord (UC) as they aged in vitro from passage 4 (P4) to passage 9 (P9). The electrical phenotype was defined by the DEP spectra, membrane capacitance, and cytoplasm conductivity. Cell morphology and size, growth characteristics, adipogenic differentiation potential, and osteogenic differentiation potential were assessed alongside label-free biomarker membrane capacitance and cytoplasm conductivity. Differentiation was confirmed by histological staining and RT-qPCR. All hMSCs exhibited typical morphology, though cell size varied, with UC-hMSCs displaying the largest variability across all size metrics. Growth analysis revealed that UC-hMSCs proliferated the fastest. The electrical phenotype varied with cell source and in vitro age, with high passage hMSCs showing noticeable shifts in DEP spectra, membrane capacitance, and cytoplasm conductivity. Correlation analysis revealed that population doubling level (PDL) correlated with membrane capacitance and cytoplasm conductivity, indicating PDL as a more precise marker of in vitro aging than passage number. Additionally, we demonstrate that membrane capacitance correlates with the osteogenic marker COL1A1 and that cytoplasm conductivity correlates with the adipogenic markers ADIPOQ and FABP4, suggesting that DEP-derived electrical properties serve as label-free biomarkers of differentiation potential. While DEP has previously been applied to BM-hMSCs and AT-hMSCs, and more recently to UC-hMSCs, few studies have provided a direct comparison across all three sources or tracked changes across continuous expansion. These findings underscore the utility of DEP as a label-free approach for assessing hMSC aging and function, offering practical applications for optimizing stem cell expansion and stem cell banking in clinical settings.

Modeling the Potential Distribution and Future Dynamics of Important Vector Culex tritaeniorhynchus Under Climate Change Scenarios in China

In the context of global warming, there is an increasing risk of the emergence and re-emergence of vector-borne diseases (VBDs). As one of the most important vectors, Culex tritaeniorhynchus can carry and transmit numerous human and animal infectious pathogens. To better understand the current distribution and possible future dynamics of Cx. tritaeniorhynchus in China, an ecological niche modeling approach (MaxEnt) was adopted to model its current and future habitat suitability. The most comprehensive dataset (1100 occurrence records) in China to date was established for model training. Multiple global climate models (GCMs) and climate change scenarios were introduced into the model to counter the uncertainties of future climate change. Based on the model prediction, Cx. tritaeniorhynchus currently exhibits high habitat suitability in southern, central, and coastal regions of China. It is projected that its suitable niche will experience continuous expansion, and the core distribution is anticipated to shift northward in the future 21st century (by the 2050s, 2070s and 2090s). Several environmental variables that reflect temperature, precipitation, and land-use conditions were considered to have a significant influence on the distribution of Cx. tritaeniorhynchus, among which annual mean temperature and urban land contribute the most to the model. Our study conducted a quantitative analysis of the shift and expansion of the future habitats of Cx. tritaeniorhynchus, providing references for vector monitoring and the prevention and control of VBDs.

Mini review: SHEN26, a novel oral antiviral drug for COVID-19 treatment.

Mini review: SHEN26, a novel oral antiviral drug for COVID-19 treatment.

Phenotypic changes associated with continuous long term invitro expansion of bone marrow-derived mesenchymal stem cells.

Phenotypic changes associated with continuous long term invitro expansion of bone marrow-derived mesenchymal stem cells.

The Evolution of Pediatric Emergency Medicine in the Indian Scenario

Abstract Paediatric Emergency Medicine (PEM) in India has witnessed remarkable growth over the past two decades. Initially, emergencies involving children were predominantly managed by paediatricians and family physicians in homes, walk-in clinics, or general hospital settings. From these beginnings, PEM has evolved into a dynamic and specialized field, driven by dedicated physicians committed to improving access, training, and the quality of emergency care for children. With increasing recognition of the critical role of specialized paediatric emergency care, the field is set for continued expansion. This article offers an overview of the journey and development of PEM in India.

The multiscale brain structural re-organization that occurs from childhood to adolescence correlates with cortical morphology maturation and functional specialization.

From childhood to adolescence, the structural organization of the human brain undergoes dynamic and regionally heterogeneous changes across multiple scales, from synapses to macroscale white matter pathways. However, during this period, the developmental process of multiscale structural architecture, its association with cortical morphological changes, and its role in the maturation of functional organization remain largely unknown. Here, using two independent multimodal imaging developmental datasets aged 6-14 years, we investigated developmental process of multiscale cortical organization by constructing an in vivo multiscale structural connectome model incorporating white matter tractography, cortico-cortical proximity, and microstructural similarity. By employing the gradient mapping method, the principal gradient derived from the multiscale structural connectome effectively recapitulated the sensory-association axis. Our findings revealed a continuous expansion of the multiscale structural gradient space during development, characterized by enhanced differentiation between primary sensory and higher-order transmodal regions along the principal gradient. This age-related differentiation paralleled regionally heterogeneous changes in cortical morphology. Furthermore, the developmental changes in coupling between multiscale structural and functional connectivity were correlated with functional specialization refinement, as evidenced by changes in the participation coefficient. Notably, the differentiation of the principal multiscale structural gradient was associated with improved cognitive abilities, such as enhanced working memory and attention performance, and potentially underpinned by synaptic and hormone-related biological processes. These findings advance our understanding of the intricate maturation process of brain structural organization and its implications for cognitive performance.

Strategic Deployment of EV Charging Infrastructure: An In-Depth Exploration of Optimal Location Selection and CC-CV Charging Strategies

<span lang="EN-US">The continued expansion of the electric vehicle (EV) market necessitates strategic planning for the placement of charging stations to ensure efficient access and utilization of electric infrastructure. This paper presents a comprehensive review of the critical factors in optimizing the selection of EV charging station locations, along with the implementation of Constant Current-Constant Voltage (CC-CV) charging models. The study addresses the challenges and opportunities in identifying the most effective locations for charging stations to accommodate the growing demand for sustainable transportation. Furthermore, it examines the benefits of adopting CC-CV charging models to improve the charging process, achieving a balance between charging speed and battery longevity. Through this analysis, the review aims to provide valuable insights to stakeholders involved in the development and expansion of EV charging infrastructure, thereby supporting the transition to a more sustainable and extensive electric mobility ecosystem.</span>

The continuous expansion and spread of human brucellosis in the Xinjiang Uygur Autonomous Region: evidence from epidemiological and strains’ genotyping-based analysis

Human brucellosis is a severe public health threat in Xinjiang; however, the epidemiological evolution and molecular correlation of strains are still unclear. In this study, join point regression analysis, spatiotemporal scan analysis, conventional biotyping approaches, and multiple locus variable-number tandem repeat analysis (MLVA) were applied to characterize the epidemiological landscape. A total of 78,689 cases were reported from 1957 to 2023. The average annual reported cases and incidence rates were 1174.46 and 5.28/100,000, respectively. Join point analysis revealed that disease incidence trends increased from 2004 (329, 1.77/100,000) to 2023 (9,334, 36.08/100,000) (AAPC = 17.26, P = 0.00), and affected counties expanded from 21 in 2004 to 100 in 2023, implying that human brucellosis continues to worsen. In 2023, the incidence rates in most counties in southern Xinjiang were higher than 2.0/100,000, and human brucellosis has become endemic in southern Xinjiang. These data demonstrate that human brucellosis is continuously spreading and expanding in Xinjiang. High incidence rate of clusters was detected in North Xinjiang from 2013 to 2023, involving 54 counties. The substantial increase in ruminant farming has increased the risk of infection in humans. A total of 28 Brucella strains were isolated in patients, all B. melitensis bv. 3. MLVA revealed that the dominant genotypes consisted of strains from different areas, hosts, and years; strains from a common original continuously spread, small ruminant trade and transfer contributed to the spread of strains in adjacent regions. Therefore, strengthening surveillance and control of animal brucellosis is vital for preventing its further spread.

A critical review of industrial fiber hemp anatomy, agronomic practices, and valorization into sustainable bioproducts

The production of industrial hemp (Cannabis sativa L.) has expanded recently in the US. Limited agronomic knowledge and supply chain issues, however, stemming from a long-standing cultivation ban, pose a barrier to continued market expansion of hemp, which leads to the import of most hemp products. This review examines the most recent cultivation methods, fertilizer and nutrient requirements, soil management practices, environmental parameters, and post-harvest processing methods, particularly in the context of environmental benefits such as soil phytoremediation and CO2 sequestration. Details of the valorization of hemp biomass into sustainable products, such as fibers, papers, packaging, textiles, biocomposites, biofuels, biochar, and bioplastics, along with current limitations and scope for improvements, are explored. Finally, an overall summary of the life cycle and techno-economic analysis aimed at optimizing their environmental performance and economic feasibility are discussed with a focus on intersection with the growing circular economy paradigm.

Correlation between Team Competence and Church Growth: A Survey of Pentecostal Churches in Selected Counties in Kenya

Pentecostal churches in Kenya principally function within a team-oriented leadership model, where the capabilities of leaders and their teams play a crucial role in the church’s growth and sustainability. This study aimed at determining the relationship between team competence and the growth of selected Pentecostal churches in Kenya. A descriptive-correlational survey design was employed. The study targeted 7,626 clergy members from selected Pentecostal churches in five counties: Meru, Tharaka-Nithi, Laikipia, Embu, and Nyeri. Stratified random sampling technique was used to distribute questionnaires to respondents, attracting 321 participants. Data analysis was conducted using mean and standard deviation scores, alongside correlation and regression techniques in SPSS. Findings indicated a moderate yet statistically significant positive correlation between team competence and church growth (r = .279, p < .01). Regression analysis further confirmed that team competence is a significant predictor of church growth, F(1, 318) = 26.94, p < .01, accounting for 7.8% of the variance (R² = .078). These results highlight that team competence is not merely beneficial but essential for the continued expansion of Pentecostal churches in Kenya. The study underscores the importance of cultivating a competent leadership culture as a strategic imperative for ensuring long-term church growth and sustainability.

The Design of a Service-Level Architecture for Handling Big Data Using Mobile Cloud Computing and the Internet of Things -AOS

The rapid and continuous expansion of interconnected devices equipped with sensors and actuators, utilizing diverse technologies, has led to an exponential increase in data generation. Effectively storing and processing this vast amount of data necessitates advanced computational resources, which can be provided by mobile cloud computing systems. The evolution of the Internet of Things (IoT) has facilitated machine-to-machine communication, allowing extensive data collection and prolonged storage for processing using robust cloud-based applications and big data analytics. However, there is currently no established method for managing the enormous volume of data generated by IoT devices in a way that enables seamless communication in both real-time and non-real-time contexts. This results in challenges related to heterogeneity and interoperability. Addressing this issue requires the development of a reference architecture that integrates big data, mobile cloud computing, and IoT, fostering device interoperability and heterogeneity. The proposed service-level architecture aims to unify these technologies, demonstrating their interaction and facilitating scalability, integration, and interoperability across various services. Ultimately, this architecture will provide an innovative approach to handling big data within mobile cloud computing and IoT environments, ensuring seamless communication among devices from different manufacturers.