Developing evidence‐based, cost‐effective P4 cancer medicine for driving innovation in prevention, therapeutics, patient care and reducing healthcare inequalities

The cancer problem is expanding, particularly in low‐ and middle‐income countries (LMICs). Preventive measures can reduce the incidence by 40–50%, and cure rates have increased during the past decades in a number of cancers. However, optimizing prevention programmes and increasing cure rates of cancer remain significant research challenges. The main focus of the conference was on P4 Cancer Medicine (Predictive, Preventive, Personalized and Participatory), a comprehensive strategy encompassing Health‐Related Quality of Life (HRQoL) research, aiming to enhance the well‐being of patients and individuals at risk. Addressing the cancer problem requires two key elements: translational cancer research and the development of relevant infrastructures. A Comprehensive Cancer Centre (CCC) acts as an innovation hub by integrating high‐quality, multidisciplinary therapy and care, with healthcare‐dependent prevention, research, and education. The United States has been at the forefront, providing quality‐assured CCCs and the Cancer Moonshot for strategic cancer research. The EU has followed with the European Research Council for basic research, the European Innovation Council to boost disruptive innovation, and two EU initiatives on cancer, Europe's Beating Cancer Plan (EBCP) and the Mission on Cancer. The increasing complexity of cancer biology and technologies presents both a research challenge and a healthcare demand. For most patients, a CCC is not available. A critical discussion focused on quality assurance of healthcare outside the catchment area of a CCC and involving patients in clinical research. The strategic deployment of resources to support collective healthcare efforts and research aimed at reducing the cancer problem was discussed with representatives from the United States, EU, Africa, China, India and Taiwan. Analyses of translational cancer research have revealed important gaps in implementing innovations, assessment of clinical effectiveness, HRQoL, outcome and health economics research. The increased release of new anticancer agents over the last 25 years, accompanied by insufficient information on clinical benefits, presents both an economic and ethical problem. Direct healthcare costs have increased due to expenses for anticancer agents for the treatment of patients with incurable diseases. Evidence‐based treatment based on HRQoL research is an unmet need. Basic/preclinical research aimed at increasing the cure rate should identify new, broader targets for therapy and develop extended diagnostic technologies for stratifying patients, to inform innovative clinical trials. Present research strategies convert cancer to a chronic disease, a growing burden for the healthcare systems. The increasing complexity of cancer biology and technology, the growing need for translational cancer research, and the demand for supporting infrastructures underscore the importance of international collaborations between CCCs. However, funding for cancer research is not currently aligned to reduce the cancer problem. While public funding for cancer research doubled between 2005 and 2024, the pharmaceutical industry's spending on cancer research increased tenfold. Increasing funding by public and non‐profit funding organizations is mandatory. Education is another significant need, but it is currently fragmented and underfunded. The last session of the conference summarized the strategies in a Statement with a strong emphasis on global collaboration addressing the growing cancer burden and pronounced inequalities. Expanding partnerships and fostering innovative, multidisciplinary approaches to cancer prevention, therapeutics/care, as well as research, are not just urgent but essential steps towards reducing incidence, increasing cure rates and enhancing the well‐being of cancer patients. Data‐driven cancer medicine is currently under development, and modern communication technologies for diagnostics may facilitate interactions across geographical distances. A global cancer research agenda can become a model of solidarity, sustainability, and ethical responsibility.

Morphometric characteristics and their influence on soil hydrological properties in Kiltie watershed, Upper Blue Nile Basin, Ethiopia

Abstract Morphometric analysis is crucial for watershed management, especially for estimating infiltration rate and erosion characteristics. However, there is limited research on the relationship between morphometric characteristics and soil hydrological properties in the Kiltie watershed. The study is aimed at exploring the relationship between morphometric characteristics and soil hydrological properties in the Kiltie watershed. The study utilized the Shuttle Radar Topography Mission digital elevation model (30 × 30 m spatial resolution) and ArcGIS 10.7.1 software to extract and analyze morphometric parameters. A numerical scheme was used to evaluate soil hydrological properties in relation to morphometric parameters. The morphometric analysis reveals that drainage pattern was dendritic and the maximum stream order of the watershed was five. Total number of stream of all orders was 560, with a total length of 358.277 km. Out of all order, 53.04% were covered by the first order, 23.03% by the second order, 10% by third order, 9.29% by fourth order, and 4.64% by fifth order. The watershed's higher drainage density (19.21 km/m2) and ruggedness number (3.55) indicate higher erosion sensitivity and lower surface permeability and infiltration, indicating a more resilient ecosystem. The values obtained through morphometric analysis and numerical scheme classification showed the watershed had low surface soil permeability, low infiltration rate, and high runoff, with a total weight score below six. This study and scheme could be useful for planners and decision‐makers as a baseline in implementing successful soil and water conservation strategies. For future studies, we recommended that the extent of the vulnerability to erosion‐prone areas should be identified through multi‐criteria decision‐making methodologies.

Direct insight into particle swarm dynamics and its effects in dense solid–liquid suspensions using inline image method

Abstract Concentrated suspensions of very high phase fractions (>10%) significantly complicate hydrodynamic characteristics in multiphase reactors. The inline image method proposed recently provides the possibility to peer into dense particle swarm dynamics, previously considered an impossible mission. In this work, the method was further developed to determine the particle‐resolved flow field and comprehensive datasets of particles within a swarm. Transient swarm microstructure demonstrated two aggregation states, that is, doublets and multiplets, accompanied by frequent collisions and friction. Statistical analysis indicated the damping effect on slip velocity and net force induced by the particle swarm became significant as solid holdup reached 13.2%, which markedly enhanced particle suspension. Through correlation analysis of dynamic datasets and relevant mechanisms, the viscous effect and hindrance effect exerted by the particle swarm were quantitatively elucidated for the first time. Accordingly, a correlation was proposed to predict the swarm effect on axial slip velocity, and good agreement was demonstrated across wide concentration ranges.

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

Plastic pollution in water bodies threatens and disrupts aquatic life, requiring effective cleanup solutions. This paper proposes a strategy for plastic cleanup using a fleet of autonomous surface vehicles in a multitask scenario, with a focus on both exploration and cleaning tasks. The mission is decoupled into two phases: an exploration phase for locating trash and a cleaning phase for collection. A Multitask Deep Q‐Network with two heads estimates Q ‐values for each task, and all ASVs share the same policy through an egocentric state formulation to enhance scalability. A multiobjective learning approach is applied, resulting in distinct policies that balance the duration of the exploration and cleaning phases, leading to the construction of a Pareto front, which provides a visual representation of trade‐offs between task priorities. The framework adapts to various environmental conditions, demonstrated in both the larger Malaga Port and the smaller Alamillo Lake. The study also highlights the importance of a dedicated exploration phase for larger areas, while minimal exploration is sufficient for smaller spaces. Compared to the decomposition weighting sum strategy, the approach consistently produces superior Pareto‐optimal policies, ensuring broader and more effective exploration of the objective space.

Insect‐Inspired Resilient Machines

Bio‐Inspired Resilient Locomotion In the Research Article (DOI: 10.1002/aisy.202500270 ), Poramate Manoonpong and co‐workers present decentralized adaptive resilient neural control for legged robots. The neural control method encodes leg movement adaptation strategies from stick insects, enabling robots to autonomously adapt to leg loss to continue their mission.

Case Series of Nizon‐Isidor Syndrome by Heterozygous Variants in MED12L With Further Evidence of Mitotic Instability in One Case With Diploid–Triploid Mosaicism

ABSTRACT Nizon‐Isidor syndrome is a rare disorder caused by heterozygous variants in MED12L , with only eight documented cases in the literature. Here, we present three additional cases of this syndrome. Proband 1 was a 7‐year‐old female who presented with developmental delay, right‐leg hemihypertrophy, laryngeal cleft, esotropia, abnormal skin pigmentation, sectoral iris hypopigmentation, dysphagia, periventricular nodular heterotopia, seizures, morbid obesity, and a pelvic kidney. Genome sequencing (GS) revealed a MED12L variant, NM_053002.5:c.3559+2T>G. Both computational models and transcriptomic analysis confirmed that this variant induced splice loss of MED12L exon 25. Probands 2 and 3 presented with overlapping phenotypes of developmental delay; sequencing confirmed c.3441_3444dup; p.(G1149Nfs*13) and seq[GRCh37] del(3)(q25.1q25.1) chr3:g.?_151075120 variants affecting MED12L . Further investigation found diploid–triploid mosaicism in Proband 1, supporting the hypothesis that loss of MED12L function may increase risk for other cytogenetic abnormalities. Probands 2 and 3 did not harbor evidence of additional cytogenetic aberrations. In Proband 1, caloric restriction and semaglutide–pramlintide combination therapy were started at age eight and were effective in weight reduction. Overall, this report expands the phenotypic spectrum of Nizon‐Isidor syndrome, highlights a potential link between MED12L and cytogenetic abnormalities, and demonstrates a case of weight loss through GLP‐1 therapy in a child with a genetic obesity syndrome.

Next‐generation Alzheimer's therapeutics: target assessment and enablement at the Indiana University School of Medicine–Purdue University TREAT‐AD Center

Abstract The incidence of Alzheimer's disease (AD) continues to increase, despite decades of effort to develop disease‐modifying therapies. In response, the National Institute on Aging (NIA) established the TaRget Enablement to Accelerate Therapy Development for Alzheimer's Disease (TREAT‐AD) centers to address the gap between basic research and translational drug discovery. Situated within a robust AD research environment, the Indiana University School of Medicine (IUSM)–Purdue University TREAT‐AD Center is one of two National Institutes of Health (NIH)‐supported centers funded to accomplish this mission. With a focus on novel biological targets beyond amyloid and tau, our center has assembled the necessary components of a drug discovery engine: project and data management, bioinformatics and computational science, structural biology and biochemistry, assay development and pharmacology, and molecular design and synthesis of small molecules, antibodies, and oligonucleotides. Our objective is to deliver Target Enabling Packages (TEPs) within an open science framework, making data, methods, and research tools broadly accessible through the AD Knowledge Portal. Highlights The Indiana University School of Medicine (IUSM)–Purdue TREAT‐AD Center develops Target Enabling Packages (TEPs) to advance novel targets for the treatment of Alzheimer's disease (AD). The center is overseen by an administrative core and operates through four technical cores – bioinformatics, structural biology, assay development, and medicinal chemistry – within a milestone‐driven and open science framework. Multi‐omics, systems biology, and machine learning (ML) approaches guide the nomination of high‐priority targets beyond amyloid and tau. Cross‐core workflows provide structural insights into novel biological targets, validated assays, biomarkers, and molecular probes that enable lead optimization. All data, methods, and tools are openly shared through the AD Knowledge Portal to accelerate global efforts in AD drug discovery.

Cognitive data harmonization in the ADRC Network and beyond—Past, present, and future

Abstract The National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) includes extensive cognitive data contributed by Alzheimer's Disease Research Centers (ADRCs) since 2005. The UDS has evolved over time and is on its fourth iteration. In addition to this core dataset, individual ADRCs have administered augmented neuropsychological batteries to research participants that go beyond the UDS. Here we describe ongoing efforts and future plans to optimize use of these data with modern psychometric methods. Modern psychometric methods address challenges from an evolving battery of cognitive tests. To date, most efforts using modern psychometric methods have focused on harmonization and co‐calibration of ADRCs’ UDS and non‐UDS cognitive data, while recent efforts address additional areas such as subjective cognitive impairment. Modern psychometric methods provide a workable framework for anticipated future developments, including digital cognitive testing and analyses of spoken responses. These methods facilitate optimal use of NACC's data riches to further its mission to facilitate collaborative research. Highlights National Alzheimer's Coordinating Center (NACC) data collection includes an extensive cognitive battery that has changed over time. An ambitious project has harmonized and co‐calibrated cognitive domain scores for memory, executive functioning, and language. Scores and their standard errors are available from the NACC. Those scores are co‐calibrated with domain scores from many additional studies, facilitating cross‐study scientific investigation. Future opportunities include digital data collection, consideration of neuropsychiatric symptoms and subjective cognitive impairment, and other uses of the granular cognitive data.

Lighting the Pathway and Reflecting on Advancing Our Mission

Radial Velocity Monitoring and Analysis of Gaia Astrometry of Selected Intermediate Mass Stars to Constrain Their Multiplicity Status

ABSTRACT We present new radial velocity measurements of 13 selected intermediate mass stars (2–6 M ⊙ ). The measurements were performed between 29 April and 6 September 2024 at the University Observatory Jena using the échelle spectrograph FLECHAS. The radial velocity of eight stars was found to be constant during our spectroscopic monitoring, namely: 17 Dra A, HD 148374, HD 169487 A, 57 Cnc,γ $$ \gamma $$ And, HD 11031,κ $$ \kappa $$ And, andλ $$ \lambda $$ Cas. In contrast, the radial velocity of five stars showed significant variability throughout or spectroscopic observation, namely: 7 CrB A, 7 CrB B, HD 214007,ι $$ \iota $$ Her, and HD 201433 A. In all these cases, Keplerian orbital solutions were fitted to the observational data and the orbital elements of these spectroscopic binary systems were determined. In addition, we searched for wide companions of our targets using the third data release from ESA's Gaia mission, in order to determine the multiplicity status of these stars and contribute to the census of bright, nearby multiple stars.