Slice Model Research Articles

Simulation study on parameter optimization of transcranial direct current stimulation based on rat brain slices

Transcranial direct current stimulation (tDCS) is an important method for treating mental illnesses and neurodegenerative diseases. This paper reconstructed two ex vivo brain slice models based on rat brain slice staining images and magnetic resonance imaging (MRI) data respectively, and the current densities of hippocampus after cortical tDCS were obtained through finite element calculation. Subsequently, a neuron model was used to calculate the response of rat hippocampal pyramidal neuron under these current densities, and the neuronal responses of the two models under different stimulation parameters were compared. The results show that a minimum stimulation voltage of 17 V can excite hippocampal pyramidal neuron in the model based on brain slice staining images, while 24 V is required in the MRI-based model. The results indicate that the model based on brain slice staining images has advantages in precision and electric field propagation simulation, and its results are closer to real measurements, which can provide guidance for the selection of tDCS parameters and scientific basis for precise stimulation.

Asymptotic solutions for heat transfer and stresses in functionally graded porous sandwich pipes subjected to nonuniform pressures and thermal loads

In this work, thermomechanical behaviors of temperature-dependent (TD) functionally graded porous (FGP) sandwich pipes subjected to nonuniform pressures and thermal loads are studied. Because the material properties are variable across the wall of the pipe, seeking exact solutions for the pipe is almost impossible. We use a slice model where the pipe is partitioned into plenty of annular slices and each slice is assumed to have uniform material properties. First, the nonlinear heat transfer along the pipe wall thickness is obtained by introducing an iterative procedure. Then, by using the Fourier series, the mechanical problem is decomposed into axisymmetric and nonaxisymmetric parts. Both the parts can be treated by the state space method and transfer matrix method, and then the superposition principle is used to obtain the displacement and stress distributions. The model results are in good consistency with those obtained from the numerical simulation and those reported in the literature. Finally, an FGP sandwich pipe is considered to discuss the effects of the temperature dependence of material properties (TDMP), power-law index, porosity, and pressure distribution on its thermomechanical behaviors.

Cellular responses following ex vivo lung exposure to the nerve agent VX – Potential for additional treatment targets?

Following inhalation exposure to organophosphorus nerve agents, symptoms rapidly develop and severe respiratory symptoms, such as bronchorrhea and bronchoconstriction are the leading causes of lethality. Nerve agent-induced lung injury is little investigated and the standard treatment for symptomatic relief targets the enzyme acetylcholinesterase and muscarinic acetylcholine and GABAergic receptors. In the present study, cellular responses in lung tissue during the acute (40 min) and extended phase (24 h) following severe exposure to the nerve agent VX have been investigated using an ex vivo rat precision-cut lung slice model including electrostimulation to induce a cholinergic response. Changes in protein amount, cell viability, together with, inflammatory and oxidative stress markers have been determined in both the lung tissue and incubation medium.During the acute phase, VX caused significantly increased airway contraction and decreased airway relaxation. Five micromolar of VX did not affect the sample protein levels and cell viability in lung tissue. Among seven markers of cellular responses investigated in the lung tissue, increased levels of heme oxygenase-1 and matrix metalloproteinase-9 together with decreased levels of glutathione in the incubation medium were observed in the acute phase following VX-exposure compared to electrostimulation only. No difference in cellular response was observed following VX-exposure for 24 h compared to the air control. In comparison, LPS-exposure resulted in time-dependent changes in all markers of inflammation and oxidative response.In conclusion, the present study demonstrated VX-specific patterns of oxidative responses in the lung, as well as, signs of inflammatory response and remodelling of extracellular matrix. These potential mechanisms of tissue injury should be further investigated for their potential as additional therapeutic targets during the acute phase of intoxication.

Elasticity solutions of clamped laminated arches with temperature-dependent material properties under thermo-mechanical loading

The mechanical behaviors of the clamped laminated arch with temperature-dependent material properties under the thermal and mechanical loadings are studied in this paper. An analytical method based on the theory of thermoelasticity is proposed for predicting the exact solutions of stresses and displacements in the arch with arbitrary thickness and layer numbers. The clamped support is equivalent to a simply support with a support reaction with the unit pulse function and the Dirac function. The space state method is utilized to establish the state equation by employing the displacements and stresses as the state variables. A slice model is introduced to simplify the coefficient matrix. Based on the continuities at the interfaces, the displacement and stress relationships between the internal and external surfaces of the laminated arch are derived with the transfer matrix method. Exact solutions for the displacements and stresses can be obtained according to the stress boundary conditions on the surfaces of the laminated arch. Finally, convergence and comparison studies demonstrate the excellent efficiency and accuracy of the present method. The influences of material dependency with temperature, thermal load, and thickness-to-radius ratio on the distributions of displacements and stresses are discussed in detail.

Fabrication and Testing of Hybrid Polymer Composite Material by Using Carbon, Glass, Kevlar Fibers

Composites which made up of fiber reinforcements are universally endorsed option for the automobiles with a lightweight. Due to the unique properties of fiber-reinforced composites, it became a perfect alternative for traditionally used materials. Most of the automobile industries prefer polymer matrix fiber-reinforced composites for the reason that its light weight helps in carbon emission reduction and Additive manufacturing (AM) produces a complex shaped product from its data, layer by layer, with high precision and much less material wastage. As compared to the conventional manufacturing process, there are many positive environmental advantages of additive manufacturing technologies. Most importantly, there is less waste of raw material and the use of new and smart materials. In this work, we first focused on creating the composite material utilizing the Hand Lay-Up method with materials such as Carbon Fiber/Epoxy Composite with Copper Oxide (CuO) Nanoparticles and Banana Glass Fiber. Following that, we readied ASTMD638 specimens for both compressive and tensile testing. We created an ASTMD638 model for the investigation's tensile and compressive tests using Solid Works design program, and we then saved the design model in STL format. This STL format was uploaded into the CURA software for slicing. The slicing model was then saved into G-code format, and it was printed in a fused deposition modeling machine. Lastly, we tested both specimens using a compressive test setup in a Universal Testing Machine model (INSTRON-3369) UTM, and the results showed 3D printed files. Keywords: Glass Fiber, Banana Fiber, Carbon Fiber, Copper Oxide Nano filler, 3D printing Machine,Corbon Fiber Filament.

Modeling fracture in multilayered teeth using the finite volume-based phase field method

The present work, utilizing the finite volume-based phase field method (FV-based PFM), aims to investigate the initiation and propagation of cracks in the second molar of the left mandible under occlusal loading. By reconstructing cone beam computed tomography scans of the patient, the true morphology and internal mesostructure of the entire tooth are implemented into numerical simulations, including both 2D slice models and a realistic 3D model. Weibull functions are introduced to represent the tooth's heterogeneity, enabling the stochastic distribution characteristics of mechanical parameters. The results indicate that stronger heterogeneity leads to greater crack tortuosity, uneven damage distribution, and lower fracture stress. Additionally, different cusp angles (50° and 70°) and pre-existing fissure morphologies (i.e., U-shape, V-shape, IK-shape, I-shape, and IY-shape) also significantly affect the mechanical performance of the tooth. The study reveals that different cusp angles affect the location of crack initiation. Overall, this work demonstrates the utility of the FV-based PFM framework in capturing the complex fracture behavior of teeth, which can contribute to improved clinical treatment and prevention of tooth fractures. The insights gained from this study can inform the design of dental crown restorations and the optimization of cusp inclination and contact during clinical occlusal adjustments.

A Construction Method for Three-Dimensional Digital Model of Substation Equipments Integrating Grid Information Model

Abstract Building a three-dimensional digital model of a substation is a key technology for achieving intelligent operation and maintenance of substations. However, the widely used GIM technology currently has obvious shortcomings in spatial attribute correlation, and cannot meet the application requirements. This paper proposes a three-dimensional digital model modeling method for substation equipments, which improves the general standardization transplantation and spatial attribute association ability based on GIM. This method integrates the GIM data standard, establishes a mapping relationship between GIM model data and JSON instances, fully preserves the attribute information of the model, and can easily obtain a three-dimensional slice model of substation equipments. The feasibility of the proposed method was verified through experiments.

Adult Human Brain Tissue Cultures to Study NeuroHIV.

HIV-associated neurocognitive disorders (HAND) persist under antiretroviral therapy as a complex pathology that has been difficult to study in cellular and animal models. Therefore, we generated an ex vivo human brain slice model of HIV-1 infection from surgically resected adult brain tissue. Brain slice cultures processed for flow cytometry showed >90% viability of dissociated cells within the first three weeks in vitro, with parallel detection of astrocyte, myeloid, and neuronal populations. Neurons within brain slices showed stable dendritic spine density and mature spine morphologies in the first weeks in culture, and they generated detectable activity in multi-electrode arrays. We infected cultured brain slices using patient-matched CD4+ T-cells or monocyte-derived macrophages (MDMs) that were exposed to a GFP-expressing R5-tropic HIV-1 in vitro. Infected slice cultures expressed viral RNA and developed a spreading infection up to 9 days post-infection, which were significantly decreased by antiretrovirals. We also detected infected myeloid cells and astrocytes within slices and observed minimal effect on cellular viability over time. Overall, this human-centered model offers a promising resource to study the cellular mechanisms contributing to HAND (including antiretroviral toxicity, substance use, and aging), infection of resident brain cells, and new neuroprotective therapeutics.

Task-dependent Slicing with Convolutional Network Model for Histopathological Image Analysis

Due to its high rates of both mortality and morbidity, cancer stands as the primary cause of death globally. The examination of histopathological images plays a crucial role in the early prediction of cancer, relying on manual practices for each individual affected. However, this phase is prone to errors, time-consuming, and doesn’t facilitate early-stage decision-making for pathologists. Despite significant advancements in computer-aided image processing, the analysis of histopathological morphology remains challenging due to the intricate nature of these images. Moreover, limited annotations restrict sample analysis. This work focuses on developing efficient deep-learning methods to analyze histopathological images by considering both global and local features. It involves the analysis of image patches and features to address issues related to image annotations. A unique task-specific slicing model, integrated with the convolutional network model (ts-CNN) is proposed. This framework aims to conduct patch-level feature examination and combine multiple samples to achieve the necessary outcomes for classification. The envisioned model aims to rectify inefficiencies present in various existing approaches. Using MATLAB 2020a, the proposed model was employed to classify cancer-based histopathological images, demonstrating superior predictive performance. It assisted pathologists in early cancer prediction with an accuracy of 98.2 % and aided in decision-making processes, offering promising results.

Mesoscale modeling of dynamic compressive behavior of microcapsule-based self-healing concrete under impact loading

Microcapsule-based self-healing concrete (MSC) has been widely studied, with a focus on static behavior and self-healing effectiveness. However, the dynamic mechanical properties of MSC have rarely been studied. This study presents a mesoscale numerical investigation of the dynamic compressive behavior of MSC under impact loading. In mesoscale, MSC is regarded as a four-phase composite material mainly composed of coarse aggregates, interface transition zones, cement mortar, and microcapsules. A pseudo 3D numerical model is constructed by combining a slice of a detailed mesoscale model with a homogenous 3D model. The mesoscale MSC slice models with different mass fractions of microcapsules (0%, 2%, 5%, and 8%) are constructed. Different coarse aggregate shapes (i.e., circles, ellipses, and polygons) are considered. The uniaxial dynamic compressive behaviors of MSC materials under loads of different strain rates are numerically simulated and compared with those from split Hopkinson pressure bar tests previously done by the authors. The comparison results show that the present mesoscale model can accurately predict the compressive strength and failure mode of MSC. The effects of the microcapsules ratio and strain rate on the dynamic strength are studied. Results show that the MSC compressive strength decreases with the increase in microcapsules and increases with the increase in strain rate. The dynamic increase factor (DIF) of the specimen is jointly contributed by the material DIF, inertial constraints, and heterogeneity. Different aggregate shapes have little effect on the simulation results of MSC behavior. The obtained dynamic mechanical properties of MSC may assist in designing MSC to resist collisions or explosions.

Geometric mechanics of the vertical slice model

The goals of this work are to: (i) investigate the dynamics of oceanic frontogenesis by taking advantage of the geometric mechanics underlying the class of Vertical Slice Models (VSMs) of ocean dynamics and (ii) illustrate the versatility and utility of deterministic and stochastic variational approaches by deriving several variants of wave–current interaction models which describe the effects of internal waves propagating within a vertical planar slice embedded in a 3D region of constant horizontal gradient of buoyancy in the direction transverse to the vertical plane.

UCHL1-dependent control of hypoxia-inducible factor transcriptional activity during liver fibrosis.

Liver fibrosis is the excessive accumulation of extracellular matrix proteins that occurs in most types of chronic liver disease. At the cellular level, liver fibrosis is associated with the activation of hepatic stellate cells (HSCs) which transdifferentiate into a myofibroblast-like phenotype that is contractile, proliferative and profibrogenic. HSC transdifferentiation induces genome-wide changes in gene expression that enable the cell to adopt its profibrogenic functions. We have previously identified that the deubiquitinase ubiquitin C-terminal hydrolase 1 (UCHL1) is highly induced following HSC activation; however, the cellular targets of its deubiquitinating activity are poorly defined. Here, we describe a role for UCHL1 in regulating the levels and activity of hypoxia-inducible factor 1 (HIF1), an oxygen-sensitive transcription factor, during HSC activation and liver fibrosis. HIF1 is elevated during HSC activation and promotes the expression of profibrotic mediator HIF target genes. Increased HIF1α expression correlated with induction of UCHL1 mRNA and protein with HSC activation. Genetic deletion or chemical inhibition of UCHL1 impaired HIF activity through reduction of HIF1α levels. Furthermore, our mechanistic studies have shown that UCHL1 elevates HIF activity through specific cleavage of degradative ubiquitin chains, elevates levels of pro-fibrotic gene expression and increases proliferation rates. As we also show that UCHL1 inhibition blunts fibrogenesis in a pre-clinical 3D human liver slice model of fibrosis, these results demonstrate how small molecule inhibitors of DUBs can exert therapeutic effects through modulation of HIF transcription factors in liver disease. Furthermore, inhibition of HIF activity using UCHL1 inhibitors may represent a therapeutic opportunity with other HIF-related pathologies.

AN Identification and Prediction Model Based on PSO

According to the spectral characteristics of different Chinese medicinal materials, the types of Chinese medicinal materials and the origin of Chinese medicinal materials are identified. Construct a fragmented clustering model. Firstly, the mid-infrared sample data is preprocessed, the Laida criterion model is established, and the abnormal data is eliminated; then the slicing model is used to divide the spectral wave into different regions according to the spectral characteristics. The data of each slice is clustered through the k-means clustering model. The origin of Chinese medicinal materials is identified by the support vector machine model. The data of Chinese medicinal materials with a known origin of a certain type of Chinese medicinal materials is used as the training sample set, and the data of Chinese medicinal materials with unknown origin is used as the test set.

FE-analytical slice model and verification test for load distribution analysis and optimization of planetary gear train in wind turbine

Load distribution behavior of planetary gear train (PGT) is crucial for the contact and bending fatigue failure of wind turbine transmission system. With the increasing power of wind turbines, the load and failure rate of wind turbine become larger, which leads to the demand of accurate and efficient modeling, analysis and optimization for load distribution of PGT. In this paper, a new efficient and accurate FE-analytical slice model for load distribution analysis and optimization of PGT in wind turbine is proposed, which is explicitly formulated by the geometry slice model of external/internal gear contact, original FE-analytical slice model for local contact deformation, and efficient finite element (FE) model for global structural deformation. In the FE-analytical slice model, geometry errors are effectively descripted by discretizing gears into a series of slices, while gear tooth contact elasticity and structural elasticity are addressed by the FE-analytical method accurately and efficiently. Upon the proposed model, the load distribution behaviors of PGT with coupling effects of elasticity and errors are revealed and optimized by tooth modification and in-phase eccentricity arrangement strategy. The load distribution tests of PGT in wind turbine are conducted, verifying the proposed FE-analytical slice model which is significant to improve the load-bearing capacity and avoid the fatigue failure of wind turbine transmission system.

Selective and brain-penetrant ACSS2 inhibitors target breast cancer brain metastatic cells.

Breast cancer brain metastasis (BCBM) typically results in an end-stage diagnosis and is hindered by a lack of brain-penetrant drugs. Tumors in the brain rely on the conversion of acetate to acetyl-CoA by the enzyme acetyl-CoA synthetase 2 (ACSS2), a key regulator of fatty acid synthesis and protein acetylation. Here, we used a computational pipeline to identify novel brain-penetrant ACSS2 inhibitors combining pharmacophore-based shape screen methodology with absorption, distribution, metabolism, and excretion (ADME) property predictions. We identified compounds AD-5584 and AD-8007 that were validated for specific binding affinity to ACSS2. Treatment of BCBM cells with AD-5584 and AD-8007 leads to a significant reduction in colony formation, lipid storage, acetyl-CoA levels and cell survival in vitro. In an ex vivo brain-tumor slice model, treatment with AD-8007 and AD-5584 reduced pre-formed tumors and synergized with irradiation in blocking BCBM tumor growth. Treatment with AD-8007 reduced tumor burden and extended survival in vivo. This study identifies selective brain-penetrant ACSS2 inhibitors with efficacy towards breast cancer brain metastasis.

A model approach to show that monocytes can enter microporous β-TCP ceramics

β-TCP ceramics are versatile bone substitute materials and show many interactions with cells of the monocyte-macrophage-lineage. The possibility of monocytes entering microporous β-TCP ceramics has however not yet been researched. In this study, we used a model approach to investigate whether monocytes might enter β-TCP, providing a possible explanation for the origin of CD68-positive osteoclast-like giant cells found in earlier works.We used flow chambers to unidirectionally load BC, PRP, or PPP into slice models of either 2 mm or 6 mm β-TCP. Immunofluorescence for CD68 and live/dead staining was performed after the loading process.Our results show that monocytes were present in a relevant number of PRP and BC slices representing the inside of our 2 mm slice model and also present on the actual inside of our 6 mm model. For PPP, monocytes were not found beyond the surface in either model.Our results indicate the possibility of a new and so far neglected constituent in β-TCP degradation, perhaps causing the process of ceramic degradation also starting from inside the ceramics as opposed to the current understanding. We also demonstrated flow chambers as a possible new in vitro model for interactions between blood and β-TCP.

Radial ablation uniformity of cathode and design of double anode micro-cathode arc thruster

Micro-cathode arc thruster offers promising applications in micro–nanosatellite space missions owing to its simple structure, high specific impulse, and low power consumption. However, the non-uniform ablation of the cathode poses a significant limitation on the total impulse of micro-cathode arc thruster. This non-uniformity can be categorized into circumferential and radial types, with previous research primarily focusing on the influence of circumferential ablation non-uniformity. Nevertheless, it has been observed that radial ablation non-uniformity also affects the stability of the thruster, despite the lack of studies in this area. To investigate the mechanism behind the cathode radial ablation, a slice model has been designed to study the motion process of the cathode spots during a single discharge using a high-speed camera. From this analysis aims to identify the root cause of uneven cathode radial ablation. Building upon these findings, a double anode micro-cathode arc thruster has been devised to enhance the uniformity of cathode ablation. Experimental verification has been conducted to assess the performance of the double anode micro-cathode arc thruster. The results indicate that in the traditional micro-cathode arc thruster discharge process, the cathode spots do not migrate towards the outer layer covered by the shell. Instead, they extend to the surface of the shell along the contact area between the shell and cathode. This leads to unequal ablation between the inner and outer layers of the cathode. The double anode micro-cathode arc thruster effectively addresses these issues by providing two discharge channels that maintain the dynamic balance of electrode resistance and increase the ablation amount on the outer layer of the cathode. Consequently, the total impulse of the thruster improved significantly while ensuring the desired performance index.

Is Methylglyoxal a Potential Biomarker for the Warburg Effect Induced by the Lipopolysaccharide Neuroinflammation Model?

Methylglyoxal (MG) is considered a classical biomarker of diabetes mellitus and its comorbidities. However, a role for this compound in exacerbated immune responses, such as septicemia, is being increasingly observed and requires clarification, particularly in the context of neuroinflammatory responses. Herein, we used two different approaches (in vivo and acute hippocampal slice models) to investigate MG as a biomarker of neuroinflammation and the neuroimmunometabolic shift to glycolysis in lipopolysaccharide (LPS) inflammation models. Our data reinforce the hypothesis that LPS-induced neuroinflammation stimulates the cerebral innate immune response by increasing IL-1β, a classical pro-inflammatory cytokine, and the astrocyte reactive response, via elevating S100B secretion and GFAP levels. Acute neuroinflammation promotes an early neuroimmunometabolic shift to glycolysis by elevating glucose uptake, lactate release, PFK1, and PK activities. We observed high serum and cerebral MG levels, in association with a reduction in glyoxalase 1 detoxification activity, and a close correlation between serum and hippocampus MG levels with the systemic and neuroinflammatory responses to LPS. Findings strongly suggest a role for MG in immune responses.

The microtubule-dynamin binding inhibitor peptide PHDP5 rescues spatial learning and memory deficits in Alzheimer’s disease model mice

Dynamin is a microtubule (MT) binding protein playing a key role in vesicle endocytosis. In a brain slice model, tau loaded in presynaptic terminals assembles MTs, thereby impairing vesicle endocytosis via depletion of cytosolic dynamin. The peptide PHDP5, derived from the pleckstrin homology domain of dynamin 1, inhibits dynamin-MT interaction and rescues endocytosis and synaptic transmission impaired by tau when co-loaded in presynaptic terminals. We tested whether in vivo administration of PHDP5 could rescue the learning/memory deficits observed in Alzheimer’s disease (AD) model mice. A modified PHDP5 incorporating a cell-penetrating peptide (CPP) and a FITC fluorescent marker was delivered intranasally to Tau609 transgenic (Tg) and 3xTg-AD mice. FITC-positive puncta were observed in the hippocampus of mice infused with PHDP5 or scrambled (SPHDP5) peptide, but not in saline-infused controls. In the Morris water maze (MWM) test for spatial learning/memory, AD model mice treated with FITC-PHDP5-CPP showed prominent improvements in learning and memory, performing close to the level of saline-infused WT mice control. In contrast, mice treated with a scrambled construct (FITC-SPHDP5-CPP) showed no significant improvement. We conclude that PHDP5 can be a candidate for human AD therapy.

Elasto-plastic simulation of hot shape rolling of steel by a meshless method

This paper describes the development of meshless simulation of thermomechanics of steel in a continuous hot rolling process using a novel meshless solution procedure. During the process, steel billets at high temperatures are transferred through multiple roll passes, each with a specific groove shape and roll gap. The major outcome of this simulation system is to design the rolling schedule and confirm whether the final shape is inside the acceptable range. For this purpose, a perpendicular 2D slice model approach is used to obtain fast and reasonably accurate simulation results. A return mapping algorithm solves the elasto-plastic material model with linear hardening to obtain displacements, strains and stresses. They are calculated by the local radial basis function collocation method (LRBFCM), which uses the local interpolation of the strong form of partial differential equations. The predefined slice positions are entered into the rolling system, and for each position, the slice contact line and amount of reduction are predicted and used as boundary conditions. Thermal and mechanical models are run sequentially, which is repeated until the final slice position reaches the exit from the last roll. The simulation system was validated with multiple rolling schedules provided by the industrial partner and was successfully used in the steel production plant afterwards. The meshless LRBFCM successfully solves a complex elasto-plastic large deformation problem of hot rolling for the first time.