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Abstract Hydrocephalus is characterized by the accumulation of excess cerebrospinal fluid (CSF) in the cranium due to an imbalance between production and absorption of CSF. The standard treatment involves the implantation of a shunt to divert excess CSF into the peritoneal cavity, but these shunts exhibit high failure rates over time. In pursuit of improved reliability and performance, this study proposes a miniaturized valve designed to mimic the natural one-way valve function of the arachnoid granulations and thereby replace the shunts. A benchtop testing setup was employed to characterize the behavior of the fabricated valve. Additionally, an animal study was conducted to assess the valve’s in vivo performance. This involved the injection of saline into the lateral ventricle to elevate intracranial pressure (ICP), followed by the drainage of the saline through the valve inserted into the cisterna magna (CM) to reduce pressure. Our prototype features a silicone duckbill valve design combined with a silicone tube as an inlet. Through benchtop testing, the valve exhibited unidirectional flow with negligible reverse leakage, revealing that critical parameters such as the width of the fluid channel (W) and bill length (L) could be controlled to optimize valve performance. Notably, the valve configuration with W= 0.8mm and L < 0.5mm achieved the lowest cracking pressure (2.22 ± 0.07 mmHg) and outflow resistance (22.00 ± 0.70 mmHg/mL/min) within the low cracking pressure range of conventional shunts. Our observations of the in vivo test demonstrated that when untreated states, pressure differences from baseline to peak exceeded 20 mmHg due to the absence of drainage, resulting in sustained pressure elevation. Conversely, upon treating states by removing the clamp, pressure differences from baseline to peak remained below 5 mmHg, indicating effective drainage of injected saline through the valve. These promising results highlight the potential of the miniaturized duckbill valve as an alternative for ICP management in hydrocephalus, offering improved control and reliability compared to conventional shunting systems. Further research is required to evaluate the valve’s performance as a chronic implant.

Incidental capture, or bycatch, of marine species is a global conservation concern. Interactions with fishing gear can cause mortality in air-breathing marine megafauna, including sea turtles. Despite this, interactions between sea turtles and fishing gear—from a behavior standpoint—are not sufficiently documented or described in the literature. Understanding sea turtle behavior in relation to fishing gear is key to discovering how they become entangled or entrapped in gear. This information can also be used to reduce fisheries interactions. However, recording and analyzing these behaviors is difficult and time intensive. In this study, we present a machine learning-based sea turtle behavior recognition scheme. The proposed method utilizes visual object tracking and orientation estimation tasks to extract important features that are used for recognizing behaviors of interest with green turtles (Chelonia mydas) as the study subject. Then, these features are combined in a color-coded feature image that represents the turtle behaviors occurring in a limited time frame. These spatiotemporal feature images are used along a deep convolutional neural network model to recognize the desired behaviors, specifically evasive behaviors which we have labeled “reversal” and “U-turn.” Experimental results show that the proposed method achieves an average F1 score of 85% in recognizing the target behavior patterns. This method is intended to be a tool for discovering why sea turtles become entangled in gillnet fishing gear.

Hydrocephalus (HCP) is a neurological disease resulting from the disruption of the cerebrospinal fluid (CSF) drainage mechanism in the brain. Reliable draining of CSF is necessary to treat hydrocephalus. The current standard of care is an implantable shunt system. However, shunts have a high failure rate caused by mechanical malfunctions, obstructions, infection, blockage, breakage, and over or under drainage. Such shunt failures can be difficult to diagnose due to nonspecific systems and the lack of long-term implantable pressure sensors. Herein, we present the evaluation of a fully realized and passive implantable valve made of hydrogel to restore CSF draining operations within the cranium. The valves are designed to achieve a non-zero cracking pressure and no reverse flow leakage by using hydrogel swelling. The valves were evaluated in a realistic fluidic environment with ex vivo CSF and brain tissue. They display a successful operation across a range of conditions, with negligible reverse flow leakage. Additionally, a novel wireless pressure sensor was incorporated alongside the valve for in situ intracranial pressure measurement. The wireless pressure sensor successfully replicated standard measurements. Those evaluations show the reproducibility of the valve and sensor functions and support the system’s potential as a chronic implant to replace standard shunt systems.