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This perspective provides a short overview of cancer biomarkers, balancing the technical details with the broad implications for biomarker discovery and innovation; early detection and screening; personalized treatment and monitoring; and emerging technologies. It also briefly discusses challenges in their clinical translation while exploring recent advancements and future implications for clinical practice. Finally, we offer thoughts on the role of artificial intelligence (AI) in biomarker development. AI is accelerating the discovery and validation of biomarkers by mining complex datasets, identifying hidden patterns, and improving the predictive accuracy. AI-powered tools enhance image-based diagnostics, automate genomic interpretation, and facilitate real-time monitoring of treatment responses. By integrating multi-omics data, AI offers new avenues for precision medicine and scalable cancer diagnostics, pushing biomarker development into a new era of intelligent, data-driven oncology. This editorial is a reflection on the state of biomarkers based on the contributions to the Special Issue “Cancer Biomarkers: Recent Progress, Innovations, and Future Clinical Implications”.

Contemporary healthcare remains constrained by models grounded in linear causality, predictive logic, and biomedical reductionism—models that often fail to address the lived, relational, and spiritual dimensions of health, especially under uncertainty. This paper introduces the Multiplex Health (MH) framework as a coherent alternative, rooted in critical complexity theory and multiplex ontology and epistemology. MH advances six core principles: (1) multiplex ontology—viewing humans as multi-layered beings encompassing material, metaphysical, and spiritual domains; (2) multiplex epistemology—integrating empirical, experiential, and interpretive ways of knowing; (3) pluralistic modeling—combining mechanistic, statistical, and semiotic approaches; (4) critical complexity—recognizing health as emergent, open, and irreducible to single models; (5) triangulated science—linking Big Data and Small Data, and balancing prediction with understanding; and (6) comparative multiplex ethics— drawing on Islamic BioFiqh to integrate legal, moral, and spiritual reasoning in health decision-making. By foregrounding the behavioral, ethical, and conceptual dimensions often overlooked in conventional approaches, MH offers a foundational framework for advancing Population Health Management (PHM). A PHM case study focused on mental health illustrates how MH can navigate complexity, enhance relational care, and broaden the scope of well-being beyond reductionist paradigms. MH challenges the dominance of closed, optimization-driven models in precision health and artificial intelligence, instead calling for a “both-and” logic that embraces uncertainty, diversity, and contextual nuance.

This study investigates Chinese consumers' interaction with retail employees and the effects on shopping experience, trust, and loyalty. Survey data help articulate brand comparison, digital interactions, and shopping experience as customer-identification change agents. A structural equation model highlights how consumers' perception of employee identification enhances shopping experience, builds consumer trust, and improves loyalty. The study displays how customer trust mediates the effect of employee identification and retailer adaptability on customer loyalty while digital interaction mediates the effect of brand comparison on customer trust. The theoretical implications of these findings emphasise the importance of consumer-employee interaction in the identification process where the relationships between brand comparison, digital interaction, and shopping experience are highlighted in a retail setting. These results denote that (a) store loyalty is predominantly driven by consumer self-consistence and social conformance and (b) retailer online and offline interaction and coordination influence brand experiences and consumer retention.

Rates of sediment transport predicted by models differ significantly from field observations in both aeolian and underwater environments.Refinement of predictive models requires high quality ground truth data to discern if the discrepancy between models and field observations lie in a given model's ability to properly represent the physics of motion, or if our field observations are inadequately sampling the sediment transport process.Identifying the sources of error can only partially be achieved in a laboratory wind tunnels or wave flumes.The limited length and scale of turbulence recreated in wind tunnels do not follow those of natural boundary layer conditions that exist on a windy beach.Similarly, wave amplitudes and spectral content resulting in seabed sediment transport can only be recreated in limited scope in a wave flume or oscillating water column.Ruggedised point measurement tools are available for measuring fluid velocities in a field environment but are of limited spatial and temporal resolution.Here we describe the adaptation of two high resolution full field velocimetry techniques that fully transition laboratory methods to quantify sediment transport by wind and waves for use in field environments.To measure subaqueous sediment transport, we developed a Stereo Time Resolved Particle Image Velocimetry (SPIV) system that utilizes submersible enclosures for remote operation in an undersea environment at depths of up to 15 meters for a period of several weeks.The system was deployed off the coast of O'ahu near the Makai Research pier.To measure sediment transport by wind in a natural boundary layer, we developed a Time Resolved Volumetric Velocimetry system based on Shake-the-Box 4D Particle Tracking (STBPT).We deployed this system on a secure beach at NASA Wallops Flight Facility in Wallops Island, Virginia.Adapting valuable and sensitive equipment to measure sediment transport by waves and wind in an outdoor environment presents substantial technical and logistical challenges.This paper will describe the two systems mentioned above including design considerations, technical 1019 Lecture spciale innovations, experiences gleaned from the measurement campaigns and examples of data obtained.

Nursing faculty members may need several mentors to succeed in scholarly productivity, career development, work-life balance, and socialization in the academy. Underrepresented (UR) faculty report additional challenges to success. The aim of this study was to search the literature for best practices in mentoring UR faculty. An integrative review was conducted to identify best and evidence-based practices for mentoring UR faculty, including gender, sexual minority, race, ethnicity, and geographic remoteness (rural). Fifteen articles were rated on evidence and methodological quality. Successful mentorship programs include honest communication, including all stakeholders in forming a mentoring program, goals and activities that come from the mentees, and guaranteed resources. Underrepresented nursing faculty may benefit from formal mentoring programs, but more research is needed.

INTRODUCTION: Patients infected with the novel SARSCoV- 2 virus may progress to develop acute respiratory distress syndrome (ARDS) Neuromuscular blockade is often used in ARDS to assist with ventilator synchrony, improve oxygenation, and facilitate prone positioning Current guidelines recommend that neuromuscular blockade may be used in patients with COVID-19 and ARDS Our study aimed to investigate differences in cisatracurium dosing requirements for ARDS in COVID-19 versus non-COVID-19 patients METHODS: We conducted a retrospective cohort analysis of adult patients who received continuous infusion cisatracurium for ARDS or hypoxia from January 2020 to May 2020 Exclusion criteria included patients receiving cisatracurium continuous infusion <24 hours or who were also administered another neuromuscular blocking agent other than cisatracurium The primary outcome was total dose of cisatracurium in COVID-19 versus non-COVID-19 patients Secondary outcomes included total duration of cisatracurium infusion and total number of separate infusions RESULTS: 107 patients were included;72 9% (n=78) had COVID-19 and 27 1% (n=29) did not Non-COVID-19 patients were significantly younger (p<0 001) than COVID-19 patients with a mean age of 44 1 (SD ±14 2) versus 57 3 (SD ±14 5) Other baseline characteristics were similar between the groups The median PaO2/FiO2 ratio was not different between the groups (p=0 563) with a median overall value of 68 (interquartile range [IQR] 60 1, 83 1) There was no difference in SOFA scores (p=0 063) with a mean overall score of 9 6 (SD ±3 1) There was no difference in the primary outcome of total dose of cisatracurium with a mean of 20 6 mg/hour (SD ±8 7) versus 21 6 mg/hour (SD ±11) between COVID-19 and non-COVID-19 patients (p=0 637) No difference was found after comparing weight-adjusted total dose between groups (p=0 113) The total duration of the infusion was similar with a median duration of 4 days (IQR 2 5, 7 5) in COVID-19 patients versus 3 7 days (IQR 2 3, 7) in non-COVID-19 patients (p=0 747) CONCLUSIONS: Dosing and duration of cisatracurium infusion was found to be similar for treatment of ARDS in COVID-19 and non-COVID-19 patients in this study Further evaluation of the benefit and utilization of cisatracurium in the treatment of COVID-19 ARDS is warranted

The structural complexity of composite biomaterials and biomineralized particles arises from the hierarchical ordering of inorganic building blocks over multiple scales. Although empirical observations of complex nanoassemblies are abundant, the physicochemical mechanisms leading to their geometrical complexity are still puzzling, especially for nonuniformly sized components. We report the self-assembly of hierarchically organized particles (HOPs) from polydisperse gold thiolate nanoplatelets with cysteine surface ligands. Graph theory methods indicate that these HOPs, which feature twisted spikes and other morphologies, display higher complexity than their biological counterparts. Their intricate organization emerges from competing chirality-dependent assembly restrictions that render assembly pathways primarily dependent on nanoparticle symmetry rather than size. These findings and HOP phase diagrams open a pathway to a large family of colloids with complex architectures and unusual chiroptical and chemical properties.