Xia Li

Marine biofouling is a well-known massive problem: within the shortest time, ship hulls and other man-made submerged surfaces are inevitably populated by various marine organisms. Marine biofouling causes severe economic and environmental problems. Thus, effective biofouling control on submerged surfaces is of utmost importance. Since the middle of the 20th century, scientists and engineers have developed antifouling coatings mainly based on the continuous release of toxic metal ions and accompanying booster biocides to repel or kill organisms approaching the surface. However, these coatings caused serious harm to non-target organisms and the ocean. Therefore, the development of environmentally friendly alternative coatings is an urgent need, and research in this field is growing rapidly. This review includes concise basic theory from biology, chemistry, and physics. It provides an introduction into the biofouling formation, as well as physicochemical surface properties that can be manipulated to achieve an effective biofouling control. Furthermore, a complete overview of the currently developed biofouling control coatings is presented and summarized. This overview includes coatings based on surface wettability, self-renewable coatings, coatings containing antifouling agents, switchable coatings, and biomimetic coatings.

Electrospinning is a versatile technique for the construction of microfibrous and nanofibrous structures with considerable potential in applications ranging from textile manufacturing to tissue engineering scaffolds. In the simplest form, electrospinning uses a high voltage of tens of thousands volts to draw out ultrafine polymer fibers over a large distance. However, the high voltage limits the flexible combination of material selection, deposition substrate, and control of patterns. Prior studies show that by performing electrospinning with a well-defined "near-field" condition, the operation voltage can be decreased to the kilovolt range, and further enable more precise patterning of fibril structures on a planar surface. In this work, by using solution dependent "initiators", we demonstrate a further lowering of voltage with an ultralow voltage continuous electrospinning patterning (LEP) technique, which reduces the applied voltage threshold to as low as 50 V, simultaneously permitting direct fiber patterning. The versatility of LEP is shown using a wide range of combination of polymer and solvent systems for thermoplastics and biopolymers. Novel functionalities are also incorporated when a low voltage mode is used in place of a high voltage mode, such as direct printing of living bacteria; the construction of suspended single fibers and membrane networks. The LEP technique reported here should open up new avenues in the patterning of bioelements and free-form nano- to microscale fibrous structures.

Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomography (CT) is integral for treatment planning, offering electron density data crucial for accurate dose calculations. However, accurately representing patient anatomy is challenging, especially in adaptive radiotherapy, where CT is not acquired daily. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast. Still, it lacks electron density information, while cone beam CT (CBCT) lacks direct electron density calibration and is mainly used for patient positioning. Adopting MRI-only or CBCT-based adaptive radiotherapy eliminates the need for CT planning but presents challenges. Synthetic CT (sCT) generation techniques aim to address these challenges by using image synthesis to bridge the gap between MRI, CBCT, and CT. The SynthRAD2023 challenge was organized to compare synthetic CT generation methods using multi-center ground truth data from 1080 patients, divided into two tasks: (1) MRI-to-CT and (2) CBCT-to-CT. The evaluation included image similarity and dose-based metrics from proton and photon plans. The challenge attracted significant participation, with 617 registrations and 22/17 valid submissions for tasks 1/2. Top-performing teams achieved high structural similarity indices (≥0.87/0.90) and gamma pass rates for photon (≥98.1%/99.0%) and proton (≥97.3%/97.0%) plans. However, no significant correlation was found between image similarity metrics and dose accuracy, emphasizing the need for dose evaluation when assessing the clinical applicability of sCT. SynthRAD2023 facilitated the investigation and benchmarking of sCT generation techniques, providing insights for developing MRI-only and CBCT-based adaptive radiotherapy. It showcased the growing capacity of deep learning to produce high-quality sCT, reducing reliance on conventional CT for treatment planning.