5-Fluorouracil (5-FU) is a standard chemotherapeutic agent to treat solid cancers such as breast, colon, head, and neck. Computational modeling plays an essential role in predicting the outcome of ...chemotherapy and developing optimal dosing strategies. We developed an integrated mechanistic pharmacokinetics/pharmacodynamics (PK/PD) model examining the influence of 5-FU, as an S-phase specific double-strand break (DSB)-inducing agent, on tumor proliferation. The proposed mechanistic PK/PD model simulates the dynamics of critical intermediate components and provides the accurate tumor response prediction. The integrated model is composed of PK, cellular, and tumor growth inhibition (TGI) sub-models, quantitatively capturing the essential drug-related physiological processes. In the cellular model, thymidylate synthase (TS) inhibition, resultant deoxynucleoside triphosphate (dNTP) pool imbalance, and DSB induction are considered, as well as 5-FU incorporation into RNA and DNA. The amount of 5-FU anabolites and DSBs were modeled to drive the kinetics of the pharmacological tumor response. Model parameters were estimated by fitting to literature data. Our simulation results successfully describe the kinetics of the intermediates regulating the 5-FU cytotoxic events and the pattern of tumor suppression. The comprehensive model simulated the tumor volume change under various dose regimens, and its generalizability was attested by comparing it with literature data. The potential causes of the tumor resistance to 5-FU are also investigated through Monte Carlo analysis. The simulation of various dosage regimens helps quantify the relationship between treatment protocols and chemotherapy potency, which will lead to the development of efficacy optimization.
A three-dimensional flower-like NiCo
2
S
4
formed by two-dimensional nanosheets is synthesized by a facile hydrothermal method and utilized as the anode for sodium-ion batteries. Studies have shown ...that materials can achieve the best performance under the ether-based electrolyte system with voltage ranging from 0.3 to 3 V, which could effectively avoid the dissolution of polysulfides and over-discharge of the material. Here, sodium storage mechanism and charge compensation behaviors of this ternary metal sulfide are comprehensively investigated by
ex situ
X-ray diffraction. Moreover,
ex situ
Raman spectra,
ex situ
X-ray photoelectron spectroscopy and transmission electron microscopy measurements are used to related tests for the first time. Additionally, quantitative kinetic analysis unravels that sodium storage partially depends on the pseudocapacitance mechanism, resulting in good specific capacity and excellent rate performance. The initial discharge capacity is as high as 748 mAh·g
−1
at a current density of 0.1 A·g
−1
with the initial coulomb efficiency of 94%, and the capacity can still maintain at 580 mAh·g
−1
with the Coulomb efficiency close to 100% after following 50 cycles. Moreover, by the long cycle test at a high current density of 2 A·g
−1
, the capacity can still reach at 376 mAh·g
−1
after over 500 cycles.
Remote sensing scene classification is still a challenging task in remote sensing applications. How to effectively extract features from a dataset with limited scale is crucial for improvement of ...scene classification. Recently, convolutional neural network (CNN) performs impressively in different fields of computer vision and has been used for remote sensing. However, most works focus on the feature maps of the last convolution layer and pay little attention to the benefits of additional layers. In fact, the feature information hidden in different layers has potential for feature discrimination capacity. The most attention of this work is how to explore the potential of multiple layers from a CNN model. Therefore, this paper proposes multi-layers feature fusion based on CNN and designs a fusion module to solve relevant issues of fusion. In this module, firstly, all the feature maps are transformed to match sizes mutually due to infeasible fusion of feature maps with different scales; then, two fusion methods are introduced to integrate feature maps from different layers instead of the last convolution layer only; finally, the fusion of features are delivered to the next layer or classifier as the routine CNN does. The experimental results show that the suggested methods achieve promising performance on public datasets.
The process of separating stages is crucial for multistage rockets, directly influencing the success of the launch plan. Different separation timing methods alter the flow field structure within the ...interlevel zone at separation, influencing the separation of the two-stage rockets. This paper employs the SST k-ω turbulence model to investigate the structure of the flow field and its aerodynamic and motion characteristics under different nozzle baffle opening and separation times, taking into account variable properties, supersonic compressibility, and the upstream–downstream interference. First, we examined the standard flow field structure, considering the engine jet, the lateral jet between stages, and the disturbance from the external supersonic inflow. Then, we discussed the displacement characteristics and axial force coefficient curves of the first and second steps of the separation process. Finally, we explored the impact of baffle opening and separation times on the flow field structure and axial force coefficients of the two stages at the onset of separation. For the flow field structure, a delay in the baffle opening and separation moment led to a gradual increase in downstream and separation regions until they stabilized after a certain range. However, the axial force coefficients displayed different behavior before and after the design point.
Type II innate lymphoid cells (ILC2) play a very important role in the pathogenesis of allergic asthma. This study aims to investigate whether miR-146a inhibition of asthma is related with ...interleukin (IL)-33 signaling path way in ILC2 and the underlying mechanisms. Asthma mice model was induced by ovalbumin. miRNA146a mimics was administrated to asthma mice or transfected to activated ILC2 purified from asthma mice lung. RT-PCR was used to detect miRNA146a level in lung tissue and ILC2. IL-5 and IL-13 levels in culture supernatant were detected by flow cytometry. Interleukin-1 receptor-associated kinase 1 (IRAK1), TNF receptor-associated factor 6 (TRAF6), signal transducer and activator of transcription 1 (STAT1) protein expression levels were detected by western blot. miR-146a directly inhibited ILC2 function and suppressed ILC2 proliferation both in vivo and in vitro. During stimulation of ILC2, miR-146a expression gradually increased with a decrease of cell proliferation. Modulation of ILC2 function by miR-146a may depend on IL-33/interleukin 1 receptor-like 1 (IL1RL1 or ST2) signaling through inhibiting IRAK1 and TRAF6.miR-146a can inhibit IRAK1 and TRAF6, downstream molecules of ST2 signal pathway, thereby negatively regulate IL-33/ST2-activated ILC2 to inhibit asthma. Targeting miR-146 maybe a novel strategy for the treatment of allergic asthma.
Abstract This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting ...their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.
Unsupervised domain adaptation (UDA) based on adversarial learning for remote-sensing scene classification has become a research hotspot because of the need to alleviating the lack of annotated ...training data. Existing methods train classifiers according to their ability to distinguish features from source or target domains. However, they suffer from the following two limitations: (1) the classifier is trained on source samples and forms a source-domain-specific boundary, which ignores features from the target domain and (2) semantically meaningful features are merely built from the adversary of a generator and a discriminator, which ignore selecting the domain invariant features. These issues limit the distribution matching performance of source and target domains, since each domain has its distinctive characteristic. To resolve these issues, we propose a framework with error-correcting boundaries and feature adaptation metric. Specifically, we design an error-correcting boundaries mechanism to build target-domain-specific classifier boundaries via multi-classifiers and error-correcting discrepancy loss, which significantly distinguish target samples and reduce their distinguished uncertainty. Then, we employ a feature adaptation metric structure to enhance the adaptation of ambiguous features via shallow layers of the backbone convolutional neural network and alignment loss, which automatically learns domain invariant features. The experimental results on four public datasets outperform other UDA methods of remote-sensing scene classification.
Session-based recommendation is a task to recommend the next clicked item when the user’s current interaction sequence is given. Accurately modeling the session representation is critical for ...session-based recommendation. However, we find that most current methods for session-based recommendation just use conscious behavior and information in the current session, ignoring the information of unconscious behavior in the current session and preference interaction with neighborhood sessions. In this paper, we propose a Mixed Behaviors and Preference Interaction model (MBPI), which utilizes conscious and unconscious behaviors and parallel co-attention mechanism, for session-based recommendation. In MBPI, we apply a Gated Recurrent Unit (GRU) to generate the session global preference, and employ another GRU with an item-level attention mechanism to explore the session local preference, with the multi-feature behaviors. Then, we introduce a parallel co-attention mechanism to capture the preference interaction with the help of the current session and neighborhood sessions and to update the two preferences of the current session. Finally, we combine the session global preference and session local preference as session representation and make recommendation. Experimental results on three real-world datasets show our method outperforms the state-of-the-art methods and validate the effectiveness of our approach.
The content and size of stone cell clusters affects the quality of pear fruit, and monolignol polymerization and deposition in the cell walls constitute a required step for stone cell formation. ...Laccase (LAC) is the key enzyme responsible for the polymerization of monolignols. However, there are no reports on the LAC family in pear (Pyrus bretschneideri), and the identity of the members responsible for lignin synthesis has not been clarified. Here, 41 LACs were identified in the whole genome of pear. All Pyrus bretschneideri LACs (PbLACs) were distributed on 13 chromosomes and divided into four phylogenetic groups (I-IV). In addition, 16 segmental duplication events were found, implying that segmental duplication was a primary reason for the expansion of the PbLAC family. LACs from the genomes of three Rosaceae species (Prunus mummer, Prunus persica, and Fragaria vesca) were also identified, and an interspecies collinearity analysis was performed. The phylogenetic analysis, sequence alignments and spatiotemporal expression pattern analysis suggested that PbLAC1, 5, 6, 29, 36 and 38 were likely associated with lignin synthesis and stone cell formation in fruit. The two target genes of Pyr-miR1890 (a microRNA identified from pear fruit that is associated with lignin and stone cell accumulation), PbLAC1 and PbLAC14, were selected for genetic transformation. Interfamily transfer of PbLAC1 into Arabidopsis resulted in a significant increase (approximately 17%) in the lignin content and thicker cell walls in interfascicular fibre and xylem cells, which demonstrated that PbLAC1 is involved in lignin biosynthesis and cell wall development. However, the lignin content and cell wall thickness were not changed significantly in the PbLAC14-overexpressing transgenic Arabidopsis plants. This study revealed the function of PbLAC1 in lignin synthesis and provides important insights into the characteristics and evolution of the PbLAC family.
microRNA-146a has been reported to be a regulator in the process of attenuating asthma by inhibiting Toll-like receptor 2 (TLR2) pathway. This study aimed to investigate how miR146a-inhibitor affect ...the symptom of asthma and the underlying mechanisms.
Ovalbumin (OVA)-induced allergic asthma mice model was established by intraperitoneal injection with 20 μg of OVA. Total cells and differential inflammatory cells in bronchoalveolar lavage fluid were counted by flow cytometry. The expression levels of molecules and cytokines in TLR2 signaling pathway were detected by Q-PCR and ELISA.
miR146a-inhibitor attenuated OVA-induced allergic asthma by increasing Th1 cytokines in OVA-induced allergic asthma model, and the treatment of miR146a-inhibitor can reduce the inflammation caused by asthma, followed by the down-regulation of IL-5 and IL-13 in sorted ILC2. The inhibition of miR-146a significantly reduced symptoms of asthma model with TLR2-related molecules being up-regulated.
It was found that miR-146a is an important regulator in OVA-induced allergic asthma model, which can relieve symptoms of asthma through regulating TLR2 pathway. These findings provide a theoretical basis for solving asthma in clinical treatment.
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