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PloS One 2023A variety of approaches to reducing the environmental impact of food production and consumption are being explored including technological solutions, such as food...
A variety of approaches to reducing the environmental impact of food production and consumption are being explored including technological solutions, such as food produced via biotechnological processes. However, the development of these technologies requires significant upfront investment and consumer acceptance is not guaranteed. The purpose of this research is to develop a system dynamics model to forecast demand, under multiple marketing and quality scenarios, for foods produced via novel technologies, using cellular agriculture as a case study. The model considers consumer heterogeneity, product awareness, word of mouth marketing (WOM), in-store marketing options, pricing options and product utility to estimate diffusion rates and market penetration. To our knowledge, there is no demand forecasting model available for food produced via novel technologies which relies on purchase intention data and incorporates all these factors. Therefore, this research closes a critical gap for that industry. Ultimately, the model shows that price and the consumers' utility for the product drives the final demand regardless of marketing scenario. Further, the rate of diffusion was highest when product samples are provided in store for all scenarios except when product utility is low and the product price is high. Model results suggest that market saturation was reached within the 32-week trial period when the price of the cellular agriculture product was the same as a traditional product but not when the price was double that of traditional meat. Given the lack of available trial data, the model scenarios should be considered a prior probability which should be refined as more data becomes available.
Topics: Meat; Agriculture; Biotechnology; Diffusion; Industry
PubMed: 37639442
DOI: 10.1371/journal.pone.0290169 -
Journal of Mathematical Biology Nov 2023Malignant gliomas are notoriously invasive, a major impediment against their successful treatment. This invasive growth has motivated the use of predictive partial...
Malignant gliomas are notoriously invasive, a major impediment against their successful treatment. This invasive growth has motivated the use of predictive partial differential equation models, formulated at varying levels of detail, and including (i) "proliferation-infiltration" models, (ii) "go-or-grow" models, and (iii) anisotropic diffusion models. Often, these models use macroscopic observations of a diffuse tumour interface to motivate a phenomenological description of invasion, rather than performing a detailed and mechanistic modelling of glioma cell invasion processes. Here we close this gap. Based on experiments that support an important role played by long cellular protrusions, termed tumour microtubes, we formulate a new model for microtube-driven glioma invasion. In particular, we model a population of tumour cells that extend tissue-infiltrating microtubes. Mitosis leads to new nuclei that migrate along the microtubes and settle elsewhere. A combination of steady state analysis and numerical simulation is employed to show that the model can predict an expanding tumour, with travelling wave solutions led by microtube dynamics. A sequence of scaling arguments allows us reduce the detailed model into simpler formulations, including models falling into each of the general classes (i), (ii), and (iii) above. This analysis allows us to clearly identify the assumptions under which these various models can be a posteriori justified in the context of microtube-driven glioma invasion. Numerical simulations are used to compare the various model classes and we discuss their advantages and disadvantages.
Topics: Humans; Glioma; Anisotropy; Computer Simulation; Diffusion; Travel
PubMed: 38015257
DOI: 10.1007/s00285-023-02025-0 -
International Journal of Molecular... Nov 2023Using the framework of a continuous diffusion model based on the Smoluchowski equation, we analyze particle dynamics in the confinement of a transmembrane nanopore. We... (Review)
Review
Using the framework of a continuous diffusion model based on the Smoluchowski equation, we analyze particle dynamics in the confinement of a transmembrane nanopore. We briefly review existing analytical results to highlight consequences of interactions between the channel nanopore and the translocating particles. These interactions are described within a minimalistic approach by lumping together multiple physical forces acting on the particle in the pore into a one-dimensional potential of mean force. Such radical simplification allows us to obtain transparent analytical results, often in a simple algebraic form. While most of our findings are quite intuitive, some of them may seem unexpected and even surprising at first glance. The focus is on five examples: (i) attractive interactions between the particles and the nanopore create a potential well and thus cause the particles to spend more time in the pore but, nevertheless, increase their net flux; (ii) if the potential well-describing particle-pore interaction occupies only a part of the pore length, the mean translocation time is a non-monotonic function of the well length, first increasing and then decreasing with the length; (iii) when a rectangular potential well occupies the entire nanopore, the mean particle residence time in the pore is independent of the particle diffusivity inside the pore and depends only on its diffusivity in the bulk; (iv) although in the presence of a potential bias applied to the nanopore the "downhill" particle flux is higher than the "uphill" one, the mean translocation times and their distributions are identical, i.e., independent of the translocation direction; and (v) fast spontaneous gating affects nanopore selectivity when its characteristic time is comparable to that of the particle transport through the pore.
Topics: Nanopores; Diffusion
PubMed: 37958906
DOI: 10.3390/ijms242115923 -
ACS Photonics Feb 2024Measuring the orientation dynamics of nanoparticles and nonfluorescent molecules in real time with optical methods is still a challenge in nanoscience and biochemistry....
Measuring the orientation dynamics of nanoparticles and nonfluorescent molecules in real time with optical methods is still a challenge in nanoscience and biochemistry. Here, we examine optoplasmonic sensing taking the rotational diffusion of plasmonic nanorods as an experimental model. Our detection method is based on monitoring the dark-field scattering of a relatively large sensor gold nanorod (GNR) (40 nm in diameter and 112 nm in length) as smaller plasmonic nanorods cross its near field. We observe the rotational motion of single small gold nanorods (three samples with about 5 nm in diameter and 15.5, 19.1, and 24.6 nm in length) in real time with a time resolution around 50 ns. Plasmonic coupling enhances the signal of the diffusing gold nanorods, which are 1 order of magnitude smaller in volume (about 300 nm) than those used in our previous rotational diffusion experiments. We find a better angular sensitivity with plasmonic coupling in comparison to the free diffusion in the confocal volume. Yet, the angle sensitivity we find with plasmonic coupling is reduced compared to the sensitivity expected from simulations at fixed positions due to the simultaneous translational and rotational diffusion of the small nanorods. To get a reliable plasmonic sensor with the full angular sensitivity, it will be necessary to construct a plasmonic assembly with positions and orientations nearly fixed around the optimum geometry.
PubMed: 38405388
DOI: 10.1021/acsphotonics.3c01482 -
Polish Journal of Radiology 2023Diffusion-weighted imaging (DWI) is a valuable diagnostic tool, which provides functional information by exploring the free diffusivity of water molecules into intra-... (Review)
Review
Diffusion-weighted imaging (DWI) is a valuable diagnostic tool, which provides functional information by exploring the free diffusivity of water molecules into intra- and inter-cellular spaces that in tumours mainly depend on cellularity. It provides information regarding the tumour grade and helps with the diagnosis. Often high-grade tumours show restricted diffusion due to a high degree of cellularity, increased nuclear-to-cytoplasmic ratio, and reduced extracellular space. Benign central nervous system (CNS) tumours rarely show restricted diffusion on magnetic resonance imaging (MRI), and most of them have a characteristic imaging appearance. When benign CNS neoplasms reveal restricted diffusion on MRI, the radiologist is compelled to suggest a malignant neoplasm, making their diagnosis challenging. Knowledge of these exceptions helps to avoid possible errors in diagnosis. We present this integrated review with clinical, radiology-pathological correlation.
PubMed: 38020500
DOI: 10.5114/pjr.2023.132536 -
Brain, Behavior, and Immunity Oct 2023It is becoming increasingly apparent that neuroinflammation plays a critical role in an array of neurological and psychiatric disorders. Recent studies have demonstrated...
It is becoming increasingly apparent that neuroinflammation plays a critical role in an array of neurological and psychiatric disorders. Recent studies have demonstrated the potential of diffusion MRI (dMRI) to characterize changes in microglial density and morphology associated with neuroinflammation, but these were conducted mostly ex vivo and/or in extreme, non-physiological animal models. Here, we build upon these studies by investigating the utility of well-established dMRI methods to detect neuroinflammation in vivo in a more clinically relevant animal model of sickness behavior. We show that diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) indicate widespread increases in diffusivity in the brains of rats given a systemic lipopolysaccharide challenge (n = 20) vs. vehicle-treated controls (n = 12). These diffusivity changes correlated with histologically measured changes in microglial morphology, confirming the sensitivity of dMRI to neuroinflammatory processes. This study marks a further step towards establishing a noninvasive indicator of neuroinflammation, which would greatly facilitate early diagnosis and treatment monitoring in various neurological and psychiatric diseases.
Topics: Rats; Animals; Diffusion Tensor Imaging; Lipopolysaccharides; Neuroinflammatory Diseases; Diffusion Magnetic Resonance Imaging; Brain
PubMed: 37482203
DOI: 10.1016/j.bbi.2023.07.010 -
Environmental Science & Technology May 2024Molecular diffusion of chemical species in subsurface environments─rock formations, soil sediments, marine, river, and lake sediments─plays a critical role in a...
Molecular diffusion of chemical species in subsurface environments─rock formations, soil sediments, marine, river, and lake sediments─plays a critical role in a variety of dynamic processes, many of which affect water chemistry. We investigate and demonstrate the occurrence of anomalous (non-Fickian) diffusion behavior, distinct from classically assumed Fickian diffusion. We measured molecular diffusion through a series of five chalk and dolomite rock samples over a period of about two months. We demonstrate that in all cases, diffusion behavior is significantly different than Fickian. We then analyze the results using a continuous time random walk framework that can describe anomalous diffusion in heterogeneous porous materials such as rock. This methodology shows extreme long-time tailing of tracer advance as compared to conventional Fickian diffusion processes. The finding that distinct anomalous diffusion occurs ubiquitously implies that diffusion-driven processes in subsurface zones should be analyzed using tools that account for non-Fickian diffusion.
Topics: Diffusion; Porosity; Geologic Sediments
PubMed: 38736287
DOI: 10.1021/acs.est.4c01386 -
Nature Communications Jan 2024Nanoscale optoelectrodes hold the potential to stimulate optically individual neurons and intracellular organelles, a challenge that demands both a high-density of...
Nanoscale optoelectrodes hold the potential to stimulate optically individual neurons and intracellular organelles, a challenge that demands both a high-density of photoelectron storage and significant charge injection. Here, we report that zinc porphyrin, commonly used in dye-sensitized solar cells, can be self-assembled into nanorods and then coated by TiO. The J-aggregated zinc porphyrin array enables long-range exciton diffusion and allows for fast electron transfer into TiO. The formation of TiO(e) attracts positive charges around the neuron membrane, contributing to the induction of action potentials. Far-field cranial irradiation of the motor cortex using a 670 nm laser or an 850 nm femtosecond laser can modulate local neuronal firing and trigger motor responses in the hind limb of mice. The pulsed photoelectrical stimulation of neurons in the subthalamic nucleus alleviates parkinsonian symptoms in mice, improving abnormal stepping and enhancing the activity of dopaminergic neurons. Our results suggest injectable nanoscopic optoelectrodes for optical neuromodulation with high efficiency and negligible side effects.
Topics: Animals; Mice; Action Potentials; Cranial Irradiation; Diffusion; Dopaminergic Neurons
PubMed: 38195782
DOI: 10.1038/s41467-023-44635-8 -
BMC Neurology Aug 2023It is known that blood levels of neurofilament light (NF-L) and diffusion-weighted magnetic resonance imaging (DW-MRI) are both associated with outcome of patients with...
BACKGROUND
It is known that blood levels of neurofilament light (NF-L) and diffusion-weighted magnetic resonance imaging (DW-MRI) are both associated with outcome of patients with mild traumatic brain injury (mTBI). Here, we sought to examine the association between admission levels of plasma NF-L and white matter (WM) integrity in post-acute stage DW-MRI in patients with mTBI.
METHODS
Ninety-three patients with mTBI (GCS ≥ 13), blood sample for NF-L within 24 h of admission, and DW-MRI ≥ 90 days post-injury (median = 229) were included. Mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated from the skeletonized WM tracts of the whole brain. Outcome was assessed using the Extended Glasgow Outcome Scale (GOSE) at the time of imaging. Patients were divided into CT-positive and -negative, and complete (GOSE = 8) and incomplete recovery (GOSE < 8) groups.
RESULTS
The levels of NF-L and FA correlated negatively in the whole cohort (p = 0.002), in CT-positive patients (p = 0.016), and in those with incomplete recovery (p = 0.005). The same groups showed a positive correlation with mean MD, AD, and RD (p < 0.001-p = 0.011). In CT-negative patients or in patients with full recovery, significant correlations were not found.
CONCLUSION
In patients with mTBI, the significant correlation between NF-L levels at admission and diffusion tensor imaging (DTI) measurements of diffuse axonal injury (DAI) over more than 3 months suggests that the early levels of plasma NF-L may associate with the presence of DAI at a later phase of TBI.
Topics: Humans; Brain Concussion; Diffusion Tensor Imaging; Diffusion Magnetic Resonance Imaging; Intermediate Filaments; Brain; White Matter; Brain Injuries, Traumatic
PubMed: 37582732
DOI: 10.1186/s12883-023-03284-6 -
Science Advances Aug 2023The drift diffusion model (DDM) is a prominent account of how people make decisions. Many of these decisions involve comparing two alternatives based on differences of...
The drift diffusion model (DDM) is a prominent account of how people make decisions. Many of these decisions involve comparing two alternatives based on differences of perceived stimulus magnitudes, such as economic values. Here, we propose a consistent estimator for the parameters of a DDM in such cases. This estimator allows us to derive decision thresholds, drift rates, and subjective percepts (i.e., utilities in economic choice) directly from the experimental data. This eliminates the need to measure these values separately or to assume specific functional forms for them. Our method also allows one to predict drift rates for comparisons that did not occur in the dataset. We apply the method to two datasets, one comparing probabilities of earning a fixed reward and one comparing objects of variable reward value. Our analysis indicates that both datasets conform well to the DDM. We find that utilities are linear in probability and slightly convex in reward.
Topics: Humans; Diffusion; Income; Probability; Reward
PubMed: 37611107
DOI: 10.1126/sciadv.adf1665