Cancer is a highly detrimental and fatal illness that poses a significant threat to human well-being. The pattern of cancer treatment is continuously being optimized by the advancement of old treatment approaches and the invention of novel treatment modes. Nanotechnology-based approaches are emerging as powerful candidates in the development of these advanced methods for treating tumors. This article provides a concise overview of nanotechnology for cancer or cancer nanomedicine and its applications. In light of prevalent issues, such as inadequate precision in targeting initial chemotherapy drugs, susceptibility of nucleic acid drugs to degradation, gene delivery, and the occurrence of common immune-related adverse events during immunotherapy, we explore the potential integration of nanomedicine with these treatment approaches and illustrative examples and highlight the benefits that arise from the utilization of nanomedicine.

The plastic pieces of synthetic polymers, which were previously regarded as primary pollutants of the environment, are increasingly being discovered as internal pollutants of the human body. This review provides a comprehensive overview of the available evidence on human exposure, tissue distribution, and associated biological effects of micro- and nanoplastics. Ingesting contaminated food and water is the major exposure pathway, with inhalation and dermal contact being secondary routes. Various organ systems have been identified as containing polymer particles through the use of advanced analytical methods, including blood, liver, lungs, placenta, breast milk, and brain tissue. Experimental animal studies suggest associations with tissue injury, metabolic illness, and neurotoxicity. Polyethylene, polypropylene, polystyrene, and polyethylene terephthalate are the most frequently found polymers in human samples. New clinical findings indicate potential health implications, though current human evidence remains largely associative rather than causal: a cardiovascular study observed more than a two-fold rise in mortality among patients with polymer-containing arterial plaques, and recent evidence demonstrates over-accumulation of polymers in brain tissue, raising questions about neuroinflammatory processes. Detection technologies have advanced substantially, with deep learning-based polymer classification achieving 95–99% accuracy and ultrasensitive electrochemical and surface plasmon resonance biosensors reaching detection limits approaching 10⁻¹¹ M. Despite these advances, critical issues remain, including lack of standardized analytical procedures, absence of chronic exposure models for humans, and insufficient longitudinal epidemiological data. To address these gaps, physiologically relevant experimental systems including organoids and organ-on-chip platforms will be required, in addition to well-designed prospective cohort studies.

Detecting and tracking swimming animals without disturbing them is a central need in fisheries protection and aquatic biological monitoring, yet optical and acoustic methods remain limited underwater. Passive hydrodynamic sensing offers an alternative: harbour seals can follow hydrodynamic wakes over long distances, and biomimetic whiskers respond measurably to the wakes of upstream bodies. Here we quantify how well four independently varied properties of a propulsive source can be discriminated simultaneously from a single force-instrumented whisker, using towing-tank measurements of a 30 × scaled biomimetic seal whisker instrumented with a six-axis force/torque transducer. First, we separate the sensor’s intrinsic response from flow-induced forcing in quiescent flow over Reynolds numbers 4770 – 20 670 . The quiescent-flow spectra show that the whisker’s self-shedding response is weak and separated from the wake-relevant band. We then expose the sensor to wakes from a flapping NACA 0012 airfoil across 1050 conditions in which the source frequency, pitching amplitude, angle of attack, and downstream distance are prescribed independently at the source. The measured force response locks to the source frequency, scales with pitching amplitude, varies systematically in the drag-to-lift fluctuation ratio with angle of attack, and decays approximately exponentially with distance, giving four distinct force signatures of the prescribed source state. A one-dimensional convolutional neural network trained on the raw six-channel time series recovers all four attributes simultaneously with 94.1 % average test accuracy (mean over five random-seed runs; per-task 84 % – 100 % ) and millisecond-scale CPU inference latency. Frequency and source angle of attack are recovered essentially perfectly, whereas the remaining errors are concentrated in adjacent pitching-amplitude and downstream-distance classes, indicating that the model’s failures reflect physically weak separability rather than missing spectral cues. Within the experimentally investigated parameter space, these results establish the force signature of a biomimetic whisker as a compact basis for reading the state of a propulsive wake source.