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Memory, identity, and technology:explicating functionalist positions in the hippocampal cognitive prosthesis
Get PDFResearchers in America are developing a hippocampal cognitive prosthesis. The technology aims to improve or even restore memory for people with Alzheimer’s disease through implanting electrodes into the brain. In this paper we discuss the ways that this technology could affect memory, with concomitant potential for impact on personal identity and related attributes like autonomy, agency, and authenticity. To do this we describe how developers of technologies like this adopt functionalist positions on minds and brains, whereby functionally equivalent technology can undertake functions previously executed by the brain without negative impact on mental states. Our position is that such accounts are too uncertain to adopt uncritically, and after examining some critiques of functionalism, we argue that material differences in function could affect the phenomenological experience of mental state generation, including memory. We conclude with proposals for researchers to consider so as to take into account some of these limitations.</p
Dynamic Predictive Models for Side Effects Following Cancer or Cancer Treatment: A Systematic Review
No full textBackground: Advances in cancer treatments such as surgery, radiotherapy and chemotherapy have increased patient survival rates. However, these treatments often result in complications or late side-effects in patients. Accurate predictions of these side-effects are important to optimize post-treatment care focused on targeted interventions for prevention or management. Dynamic predictive models, which are specifically tailored to adapt to longitudinal patient data, offer an innovative approach to updating patient risk in light of new data. This systematic review aims to summarize the application of dynamic predictive models in predicting cancer treatment-related complications and to synthesize techniques and algorithms used in developing and validating these models.Methods: This review was conducted following the PRISMA guidelines. A systematic search was performed across multiple databases including Scopus, Web of Science, PubMed, and IEEE Xplore to identify studies that have employed dynamic predictive models for cancer or cancer treatment related complications or side-effects. The keywords used included “dynamic prediction”, “predictive models”, “treatment side effects”, “cancer treatment” and “over time”. Studies were included if they have employed longitudinal or time-varying data to update predictions over time, reflecting the incorporation of new data at multiple time points.Preliminary Results: A total of 506 studies were initially screened, resulting in the inclusion of 13 articles. Modelling techniques varied, including statistical models such as Coxproportional hazards and machine learning-based models like Long Short-Term Memory (LSTM) employed for handling time series data. The included studies were found to cover various cancer types, with prostate and head and neck cancers being the most common. Treatment types included surgery, radiation therapy, chemotherapy and hormone therapy. Predicted complications ranged from biochemical recurrence to patient-reported outcomes such as voice impairment. Each model employed different strategies for dynamically incorporating follow-up data. Most studies were from 2020–2024, reflecting a recent focus on dynamic models.Conclusion: Despite their versatility, dynamic models are not often used in oncology applications. This review highlights the diverse applications of dynamic models in predicting cancer or cancer treatment-related complications or side effects over time. These models showcase significant potential for improving post-treatment care by updating predictions as more data becomes available
Plane segmentation from point clouds using the detail preserving optimal-vector-field
Get PDFPlane segmentation in three dimensions is a crucial step for many applications. A recent optimal-vector-field (OVF) technique demonstrated good generality across a variety of models. However, OVF is a rough approach that results in under-segmentation and missing points due to loss of details. Hence, this paper presents a new plane segmentation method that uses the detail-preserving OVF method to address these problems. There are three improvements to our proposed segmentation method. (1) To enlarge the vector difference between points on different planes, we split the model into a set of planar primitives leveraging the fine planar primitives extraction method, and then estimate the normal of each point in the primitive as the vector field. (2) We define a point-based Laplace operator to improve the vector field optimization process, thereby enhancing the accuracy of OVF for detail detection. (3) We innovatively take the magnitude of optimal-vector-field as the criterion for planar primitive-based growth to obtain the final segmentation result. The evaluation of four datasets shows that our method achieves higher average precision and recall than the OVF method by 16.43% and 20.79% respectively, and the global consistency error (GCE) decreases by 6.62%. The evaluation indicates that our method is capable of preserving finer details.</p
Functional nanocrystal as effective contrast agents for dual-mode imaging:Live-cell sonoluminescence and contrast-enhanced echography
Get PDFIn the context of molecular imaging, the present work explores an innovative platform made of lipid-coated nanocrystals as contrast-enhanced agent for both ultrasound imaging and sonoluminescence. At first, the dynamics of gas bubbles generation and cavitation under insonation with either pristine or lipid-coated nanocrystals (ZnO-Lip) are described, and the differences between the two colloidal systems are highlighted. These ZnO-Lip show an unprecedented ability to assist cavitation, which is reflected in enhanced sonoluminescent light emission with respect to the pristine nanocrystals or the pure water. Highly defined and sharp sonoluminescent images of cultured cells are indeed obtained, for the first time, when ZnO-Lip are used. Furthermore, ZnO-Lip were adopted as a nanosized agent for contrast-enhanced ultrasound imaging, i.e. echography, first in solutions, and then on ex-vivo tissues. A prolonged over time and bright imaging effect is observed when adopting the developed nanoparticles. Furthermore, their nanometric size and potential targeting with biomolecules would allow ease extravasation and tissue or even cell penetration, achieving enhanced-contrast imaging. Finally, the stimuli-responsive therapeutic applications of ZnO-Lip against tumors is overviewed, aiming to achieve a fully theranostic approach.</p
Skin formation in evaporating colloidal droplets
Get PDFWhen a droplet containing a concentrated suspension evaporates in a dry environment, a layer often forms at the interface accumulating non-volatile material. Such a "skin layer" experiences strong stresses and eventually turns mechanically unstable at the last stage of evaporation. Predicting the formation of such skin layer or particle shell and its properties is a crucial problem for applications and constitutes a multi-scale problem, from the micro/nanoscopic scale of the particles to the millimetric size of the droplets. Interestingly, its physical description lies at the interface between deterministic macroscopic evaporation models and microscopic stochastic particles interactions and diffusion. In this work we present a general theoretical approach to obtain the time-dependent particle concentration profile in an implicit manner, for the general case of diffusion-limited evaporation of spherical droplets, and more generally to all 1D non linear diffusion-limited cases with particles pressure and mobility terms of rational form. This approach is compared successfully to numerical solutions obtained using a finite element solver in the limit of high P\'eclet numbers, and to 2D Brownian dynamics simulations. Our results show that the concentration profiles and shell formation onset depend nontrivially on the initial packing fraction. By analyzing these profiles, we determine the position where the glassy layer forms, whose formation is expected to play a critical role in shell buckling. This model provides a robust framework for predicting the size and maximum aspect ratio of the resulting clusters
Polyelectrolyte Complex Membranes:Sustainable Preparation and Enzyme Functionalization
Get PDFMembranes are widely used in industries, agriculture, and medicine fields. Currently, the dominant NIPS method for membrane preparation relies on unsustainable organic solvents, using polyelectrolytes as membrane materials can eliminate the use of these organic solvents. Polyelectrolyte complexes (PECs) are formed in aqueous solutions and have unique properties for membrane preparation. Aqueous phase separation (APS) and hot-pressing methods have been developed to utilize polyelectrolyte solutions and bulk PECs to prepare porous membranes and dense saloplastics. In this thesis, we aim to prepare and functionalize membranes with enzymes in a sustainable fashion.In Chapter 2, sustainable pH change-induced APS approach was successfully utilized to prepare bio-based PEC membranes using cationic CS and anionic CMC. The influence of pH and concentration of the acetate buffer were studied, and the obtained membranes demonstrated tunable structures and microfiltration performance.In Chapter 3 and 4, we successfully prepared biocatalytic PEI-PSS membranes via the pH change-induced APS. The effects of casting solution pH were investigated in Chapter 3 and the lysozyme-functionalized membranes showed temperature-dependent enzymatic activities. In Chapter 4, the polyelectrolytes mixing ratio and lysozyme concentration were varied to tune the membrane structure and the enzymatic activity. Besides, the enzyme laccase was successfully introduced and showed the versatility of the APS approach for preparing biocatalytic membranes.In Chapter 5, biocatalytic membranes were prepared via lysozyme-functionalized saloplastics through salt annealing. PDADMAC-PSS saloplastics were prepared via hot-pressing. Then the changes in KBr concentration were used for annealing and curing the saloplastics where the temporary opening of pores allowed lysozyme loading. This chapter provides new possibilities for sustainable saloplastics as a straightforward method for functionalization.Chapter 6 discusses the findings and remaining problems in this thesis and gives approaches to solve the problems and improve the membranes’ performance. Moreover, this chapter provides clear outlook for future work.<br/
ASO Author Reflections:Redefining Precision–Insights into Magnetic Sentinel Lymph Node Biopsy for Early Breast Cancer
Get PDFOptimizing bifacial PV performance:The impact of reflectors and free space luminescent solar concentrators on winter yield
Get PDFIn this study, we present a novel solar energy harvesting system incorporating free-space luminescent solar concentrators (FSLSCs) integrated with bifacial photovoltaic (PV) modules. The FSLSC design features a luminophore-doped waveguide, an angle- and wavelength-selective notch filter, and a Lambertian reflector, enabling efficient photon recycling. Unlike traditional luminescent solar concentrators, the FSLSC aims to emit photons into free space within a defined emission cone, enhancing light redirection towards PV modules. We developed a three-dimensional ray tracing model to analyze system performance, including different reflector configurations and emission cones. The study focuses on optimizing energy yield in urban settings, particularly during winter months, by examining the effects of diffuse and specular reflectors, and various FSLSC configurations. Our results demonstrate that FSLSCs can enhance winter energy production in the Netherlands by up to 60 %, compared to a conventional optimal tilt monofacial system. The findings highlight the potential of FSLSCs and specialized reflectors to increase PV system efficiency and offer flexible solutions for improving energy yield throughout the year, particularly during periods of high demand
High-Throughput Single-Cell Analysis of Local Nascent Protein Deposition in 3D Microenvironments via Extracellular Protein Identification Cytometry (EPIC)
Get PDFExtracellular matrix (ECM) guides cell behavior and tissue fate. Cell populations are notoriously heterogeneous leading to large variations in cell behavior at the single-cell level. Although insights into population heterogeneity are valuable for fundamental biology, regenerative medicine, and drug testing, current ECM analysis techniques only provide either averaged population-level data or single-cell data from a limited number of cells. Here, extracellular protein identification cytometry (EPIC) is presented as a novel platform technology that enables high-throughput measurements of local nascent protein deposition at single-cell level. Specifically, human primary chondrocytes are microfluidically encapsulated in enzymatically crosslinked microgels of 16 picoliter at kHz rates, forming large libraries of discrete 3D single-cell microniches in which ECM can be deposited. ECM proteins are labeled using fluorescence immunostaining to allow for nondestructive analysis via flow cytometry. This approach reveals population heterogeneity in matrix deposition at unprecedented throughput, allowing for the identification and fluorescent activated cell sorting-mediated isolation of cellular subpopulations. Additionally, it is demonstrated that inclusion of a second cell into microgels allows for studying the effect of cell-cell contact on matrix deposition. In summary, EPIC enables high-throughput single-cell analysis of nascent proteins in 3D microenvironments, which is anticipated to advance fundamental knowledge and tissue engineering applications.</p
Sediment nourishments to mitigate bed degradation in the River Waal in the Netherlands
No full textOver the past century, the bed level of the River Waal, a Dutch distributary of the River Rhine, has degraded by 1 to 2 metres. The high rate of degradation and its spatial non-uniformity places the various functions of the river under stress. Solutions are therefore sought to mitigate bed degradation. In this research, the effects of sediment nourishments of various sedi-ment compositions, distributions and volumes are investigated. It is shown that nourishments can mitigate bed degradation by orders of centimetres. By choosing the nourishment characteristics, the nourishment behaviour can be influenced. The findings of this study can be used as a basis for the design of sediment nourishments to mitigate bed degradation in the River Waal and similar rivers