Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as *** this understand...
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Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as *** this understanding,the neural circuit mechanisms underlying this phenomenon remain *** this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal *** objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive *** numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive ***,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal *** study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.
Plant root development, like any developmental process, arises from the interplay between processes like gene expression, cell-cell signaling, cell growth and division, and tissue mechanics, which unfold over a wide r...
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Plant root development, like any developmental process, arises from the interplay between processes like gene expression, cell-cell signaling, cell growth and division, and tissue mechanics, which unfold over a wide range of temporal and spatial scales. computational models are uniquely suited to integrate these different processes and spatio-temporal scales to investigate how their interplay determines developmental outcomes and have become part of mainstream plant developmental research. Still, for non-modeling experts, it often remains unclear how models are built, why a particular modeling approach was chosen, and how to interpret and value model outcomes. This review attempts to explain the science behind the art of model building, illustrating the simplifications that are often made to keep models simple to understand and when these are and are not justified. Similarly, it discusses when it is safe to ignore certain processes like growth or tissue mechanics and when it is not. Additionally, this review discusses a range of major breakthrough modeling articles. Their approaches are linked to classical concepts and models in developmental biology like the French flag positional information gradient of Lewis Wolpert and the repetitive patterning mechanism proposed by Turing, in addition to highlighting the lessons they taught us on plant root development.
The delivery of intracellular cargoes by kinesins is modulated at scales ranging from the geometry of the microtubule networks down to interactions with individual tubulins and their code. The complexity of the tubuli...
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The delivery of intracellular cargoes by kinesins is modulated at scales ranging from the geometry of the microtubule networks down to interactions with individual tubulins and their code. The complexity of the tubulin code and the difficulty in directly observing motor-tubulin interactions have hindered progress in pinpointing the precise mechanisms by which kinesin's function is modulated. As one such example, past experiments show that cleaving tubulin C-terminal tails (CTTs) lowers kinesin-1's processivity and velocity on microtubules, but how these CTTs intertwine with kinesin's processive cycle remains unclear. In this work, we formulate and interrogate several plausible mechanisms by which CTTs contribute to and modulate kinesin motion. computational modeling bridges the gap between effective transport observations (processivity, velocities) and microscopic mechanisms. Ultimately, we find that a guiding mechanism can best explain the observed differences in processivity and velocity. Altogether, our work adds a new understanding of how the CTTs and their modulation via the tubulin code may steer intracellular traffic in both health and disease.
In this millennium, computational modeling has become an essential tool to understand the performance of heterogeneous catalysts. In this concept study, it focuses on three different areas, namely theoretical methodol...
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In this millennium, computational modeling has become an essential tool to understand the performance of heterogeneous catalysts. In this concept study, it focuses on three different areas, namely theoretical methodology, model complexity, and comparison to experiment and highlight specific approaches and develop a hierarchy of simulation models. In general, higher quality approaches coincide with a significant increase in computational cost. Therefore, this focuses on one specific example, namely the conversion of methane to methanol over Cu-exchanged zeolites, and illustrates how a cost-benefit analysis can lead to a high-quality, cost-efficient model. This study believes that this work can serve as a guideline for students starting to work in electronic structure calculations, will help researchers to more carefully choose their modeling methodology, and might help experimental researchers to better judge computational work presented to them.
Bone healing is a complex process regulated by intricate biological and mechanical factors and spatially varied regions over time. This scoping review synthesizes current computational models that incorporate cytokine...
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Bone healing is a complex process regulated by intricate biological and mechanical factors and spatially varied regions over time. This scoping review synthesizes current computational models that incorporate cytokines and growth factors, examining their role in bone healing. Through a systematic analysis of 71 studies, this review identifies and categorizes the modeling methodologies used, including mathematical, finite element, agent-based, mechanobiological, pharmacobiological, and hybrid approaches. The findings highlight the predominant use of mathematical models while noting a recent shift toward more sophisticated techniques like finite element and agent-based models. Key cytokines and growth factors, such as TGF-beta, RANK-RANKL-OPG, and PTH, are repeatedly used, underscoring their essential roles in regulating cellular processes. This review also analyzes parameter selection and validation strategies, identifying gaps in current practices and emphasizing the need for high-quality experimental validation to improve model reliability. Some bibliometric analyses provide insights into citation networks and keyword co-occurrence, illustrating influential studies in the field and central themes. The findings offer a foundation for future research to enhance model accuracy, aiming toward more predictive and clinically relevant models accounting for biology and mechanics in bone healing.
To date, computational simulation on compact heat exchangers has been limited to either liquid-to-liquid single-phase flows or two-phase flow boiling across only one single plate despite the fact that heat exchangers ...
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To date, computational simulation on compact heat exchangers has been limited to either liquid-to-liquid single-phase flows or two-phase flow boiling across only one single plate despite the fact that heat exchangers are an indispensable part of any effective active thermal management solution. Here, the transient evaporation rate and liquid-gas maldistribution across a complete stack of three-dimensional cross-flow plate heat exchangers with offset-strip fins in between have been demonstrated. With maldistribution being a known implication of high mass flow rates across plate-fin heat exchangers (PFHXs), our simulations show that maldistribution at lower mass flow rates is primarily implicated by unequal distribution of liquid into each plate through the inlet tube or non-uniform distribution of liquid across the plate-fin, which highlights that the design and optimization of PFHXs require accurate simulation tools. Experiments were conducted on PFHXs within an environmental chamber with controllable conditions, followed by simulations across thermohydraulic parameters including mass flow rates, inlet gas quality and temperature, etc. computational and experimental results were found to be in good agreement given the intricate complexity of two-phase liquid- gas flows with evaporation phase-change. According to the results, the overall heat transfer and effectiveness of the PFHX are strong functions of mass flow rate ((m) over dot(T)) and inlet temperature of the two-phase stream (T-t,T-i). The maximum heat transfer is achieved at (m) over dot(T) = 150 kg/h and T-t,T-i = 18 degrees C while an optimal effectiveness as high as 0.78 is achievable with (m) over dot(T) = 100 kg/h and T-t,T-i = 17.6 degrees C.
Titanium-silicon (Ti-Si) alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength, creep resistance, and oxidation resistance. For Si-containing Ti alloy...
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Titanium-silicon (Ti-Si) alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength, creep resistance, and oxidation resistance. For Si-containing Ti alloys, the sufficient content of Si is critical for achieving these favorable performances, while excessive Si addition will result in mechanical brittleness. Herein, both physical experiments and finite element (FE) simulations are employed to investigate the micro-mechanisms of Si alloying in tailoring the mechanical properties of Ti alloys. Four typical states of Si-containing Ti alloys (solid solution state, hypoeutectoid state, near-eutectoid state, hypereutectoid state) with varying Si content (0.3-1.2 wt.%) were fabricated via in-situ alloying spark plasma sintering. Experimental results indicate that in-situ alloying of 0.6 wt.% Si enhances the alloy's strength and ductility simultaneously due to the formation of fine and uniformly dispersed Ti5 Si3 particles, while higher content of Si (0.9 and 1.2 wt.%) results in coarser primary Ti5 Si3 agglomerations, deteriorating the ductility. FE simulations support these findings, highlighting the finer and more uniformly distributed Ti5 Si3 particles contribute to less stress concentration and promote uniform deformation across the matrix, while agglomerated Ti5 Si3 particles result in increased local stress concentrations, leading to higher chances of particle fracture and reduced ductility. This study not only elucidates the micro-mechanisms of in-situ Si alloying for tailoring the mechanical properties of Ti alloys but also aids in optimizing the design of high-performance Si-containing Ti alloys. (c) 2025 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.
Background: Standard of care (SoC) assessment based on computed tomography (CT) and/or transesophageal echocardiography is suboptimal for adequate preprocedural evaluation for left atrial appendage occlusion (LAAO). T...
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Background: Standard of care (SoC) assessment based on computed tomography (CT) and/or transesophageal echocardiography is suboptimal for adequate preprocedural evaluation for left atrial appendage occlusion (LAAO). This can be improved through CT-based 3D computational modeling of the LAA-device interaction using FEops HEARTguide. This study aims to assess the decisional impact of FEops in preprocedural planning for LAAO. Methods: The PRECISE LAAO is a prospective multi-center self-controlled study evaluating the use of FEops in LAAO with Amulet. Preprocedural device size selection and degree of certainty (scale 0-10) were registered before (Decision SoC) and after accessing FEops (Decision FEops), followed by device implantation. Concordance was compared between the Decisions and the final implanted device. After the procedure, clinicians rated the subjective value of FEops on a scale from -3 (futile) to +3 (most helpful). Results: One hundred two patients were included. Decision SoC was concordant with the implanted device in 61 patients (59.8%), whereas Decision FEops was concordant in 92 (90.2%, p < 0.0001). FEops induced a size change in 35 patients, which was correct in 33 (32.4%). Certainty SoC was 6.7 +/- 1.3 and increased after FEops assessment to 7.6 +/- 1.3 (p < 0.0001). In the 33 patients with FEops-induced positive corrections, Certainty SoC was lower (6.2 +/- 1.5, suggesting a more complex procedure) and increased to 7.2 +/- 1.2 with FEops (p = 0.004). Clinicians rated FEops as helpful (subjective score >= 1) in 90.2% of cases. Conclusions: CT-based computational modeling using FEops has a positive decisional impact in LAAO, inducing a change in Amulet size selection in almost one out of three patients and increasing procedural confidence.
Introduction: Patients with bipolar disorder (BD) demonstrate episodic memory deficits, which may be hippocampal-dependent and may be attenuated in lithium responders. Induced pluripotent stem cell-derived CA3 pyramid...
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Introduction: Patients with bipolar disorder (BD) demonstrate episodic memory deficits, which may be hippocampal-dependent and may be attenuated in lithium responders. Induced pluripotent stem cell-derived CA3 pyramidal cell-like neurons show significant hyperexcitability in lithium-responsive BD patients, while lithium nonresponders show marked variance in hyperexcitability. We hypothesize that this variable excitability will impair episodic memory recall, as assessed by cued retrieval (pattern completion) within a computational model of the hippocampal CA3. Methods: We simulated pattern completion tasks using a computational model of the CA3 with different degrees of pyramidal cell excitability variance. Since pyramidal cell excitability variance naturally leads to a mix of hyperexcitability and hypoexcitability, we also examined what fraction (hyper- vs. hypoexcitable) was predominantly responsible for pattern completion errors in our model. Results: Pyramidal cell excitability variance impaired pattern completion (linear model beta = -2.00, SE = 0.03, p < 0.001). The effect was invariant to all other parameter settings in the model. Excitability variance, specifically hyperexcitability, increased the number of spuriously active neurons, increasing false alarm rates and producing pattern completion deficits. Excessive inhibition also induces pattern completion deficits by limiting the number of correctly active neurons during pattern retrieval. Conclusions: Excitability variance in CA3 pyramidal cell-like neurons observed in lithium nonresponders may predict pattern completion deficits in these patients. These cognitive deficits may not be fully corrected by medications that minimize excitability. Future studies should test our predictions by examining behavioral correlates of pattern completion in lithium-responsive and -nonresponsive BD patients.
Engineered monoclonal antibodies have proven to be highly effective therapeutics in recent viral outbreaks. However, despite technical advancements, an ability to rapidly adapt or increase antibody affinity and by ext...
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Engineered monoclonal antibodies have proven to be highly effective therapeutics in recent viral outbreaks. However, despite technical advancements, an ability to rapidly adapt or increase antibody affinity and by extension, therapeutic efficacy, has yet to be fully realized. We endeavored to stand-up such a pipeline using molecular modeling combined with experimental library screening to increase the affinity of F5, a monoclonal antibody with potent neutralizing activity against Venezuelan Equine Encephalitis Virus (VEEV), to recombinant VEEV (IAB) E1E2 antigen. We modeled the F5/E1E2 binding interface and generated predictions for mutations to improve binding using a Rosetta-based approach and dTERMen, an informatics approach. The modeling was complicated by the fact that a high-resolution structure of F5 is not available and the H3 loop of F5 exceeds the length for which current modeling approaches can determine a unique structure. A subset of the predicted mutations from both methods were incorporated into a phage display library of scFvs. This library and a library generated by error-prone PCR were screened for binding affinity to the recombinant antigen. Results from the screens identified favorable mutations which were incorporated into 12 human-IgG1 variants. The best variant, containing eight mutations, improved KD from 0.63 nM (parental) to 0.01 nM. While this did not improve neutralization or therapeutic potency of F5 against IAB, it did increase cross-reactivity to other closely related VEEV epizootic and enzootic strains, demonstrating the potential of this method to rapidly adapt existing therapeutics to emerging viral strains.
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