•The functional gradient from primary to transmodal networks was disrupted in ARHL.•The DMN and VN may play a key role in auditory brain associated with cognition.•The aberrant gradient among triple ...networks was linked to cognitive decline in ARHL.
Age-related hearing loss (ARHL), one of the most common sensory deficits in elderly individuals, is a risk factor for dementia; however, it is unclear how ARHL affects the decline in cognitive function. To address this issue, a connectome gradient framework was used to identify critical features of information integration between sensory and cognitive processing centers using resting-state functional magnetic resonance imaging (rs-fMRI) data from 40 individuals with ARHL and 36 healthy controls (HCs). The first three functional gradient alterations associated with ARHL were investigated at the global, network and regional levels. Using a support vector machine (SVM) model, our analysis distinguished individuals with ARHL with normal cognitive function from those with cognitive decline. Compared to HCs, individuals with ARHL had a contracted principal primary-to-transmodal gradient axis, especially in the visual and default mode networks, with an altered gradient explained ratio and variance. Among individuals with ARHL, cognitive decline was detected in the visual network in the principal gradient as well as in the limbic, salience and default mode networks in the third gradient (salience to frontoparietal/default mode). These results suggest that ARHL is associated with disrupted information processing from the primary sensory networks to higher-order cognitive networks and highlight the key nodes closely associated with cognitive decline during cognitive processing in ARHL, providing new insights into the mechanism of cognitive impairment and suggesting potential treatments related to ARHL.
In this study, a robust cooperative control methodology is proposed for a class of micro/nano scale systems in the field of biomedical engineering. Due to the complexity of actual environment, the ...dynamic behavior of the micro/nano scale systems changes over time. The time-varying uncertainties are considered to be restricted to a certain range. Then, a robust cooperative control strategy is designed such that the micro-agents with structured uncertainties can securely cooperative with each other to accomplish the tasks. Furthermore, sufficient conditions ensuring the cooperativity of micro/nano scale systems are derived by constructing a novel Lyapunov functional. It is proved that the cooperative control problem for micro/nano scale systems can be solved if the control parameters are appropriately selected. A simulation example is presented to demonstrate the validity of the obtained algorithm.
Tinnitus refers to sound perception in the absence of external sound stimulus. It has become a worldwide problem affecting all age groups especially the elderly. Tinnitus often accompanies hearing ...loss and some mood disorders like depression and anxiety. The comprehensive adverse effects of tinnitus on people determine the severity of tinnitus. Understanding the mechanisms of tinnitus and related discomfort may be beneficial to the prevention and treatment, and then getting patients out of tinnitus distress. Functional magnetic resonance imaging (fMRI) is a powerful technique for characterizing the intrinsic brain activity and making us better understand the tinnitus neural mechanism. In this article, we review fMRI studies published in recent years on the neuroimaging mechanisms of tinnitus. The results have revealed various neural network alterations in tinnitus patients, including the auditory system, limbic system, default mode network, attention system, and some other areas involved in memory, emotion, attention, and control. Moreover, changes in functional connectivity and neural activity in these networks are related to the perception, persistence, and severity of tinnitus. In summary, the neural mechanism of tinnitus is a complex regulatory mechanism involving multiple networks. Future research is needed to study these neural networks more accurately to refine the tinnitus models.
Matrix acidization is an important technique used to enhance oil production at the tertiary recovery stage, but its numerical simulation has never been verified. From one of the earliest models, ...i.e., the two-scale model (Darcy framework), the Darcy–Brinkman–Forchheimer (DBF) framework is developed by adding the Brinkman term and Forchheimer term to the momentum conservation equation. However, in the momentum conservation equation of the DBF framework, porosity is placed outside of the time derivation term, which prevents a good description of the change in porosity. Thus, this work changes the expression so that the modified momentum conservation equation can satisfy Newton’s second law. This modified framework is called the improved DBF framework. Furthermore, based on the improved DBF framework, a thermal DBF framework is given by introducing an energy balance equation to the improved DBF framework. Both of these frameworks are verified by former works through numerical experiments and chemical experiments in labs. Parallelization to the complicated framework codes is also realized, and good scalability can be achieved.
Purpose Sensorineural hearing loss (SNHL) is the most common form of sensory deprivation and is often unrecognized by patients, inducing not only auditory but also nonauditory symptoms. Data-driven ...classifier modeling with the combination of neural static and dynamic imaging features could be effectively used to classify SNHL individuals and healthy controls (HCs). Methods We conducted hearing evaluation, neurological scale tests and resting-state MRI on 110 SNHL patients and 106 HCs. A total of 1,267 static and dynamic imaging characteristics were extracted from MRI data, and three methods of feature selection were computed, including the Spearman rank correlation test, least absolute shrinkage and selection operator (LASSO) and t test as well as LASSO. Linear, polynomial, radial basis functional kernel (RBF) and sigmoid support vector machine (SVM) models were chosen as the classifiers with fivefold cross-validation. The receiver operating characteristic curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated for each model. Results SNHL subjects had higher hearing thresholds in each frequency, as well as worse performance in cognitive and emotional evaluations, than HCs. After comparison, the selected brain regions using LASSO based on static and dynamic features were consistent with the between-group analysis, including auditory and nonauditory areas. The subsequent AUCs of the four SVM models (linear, polynomial, RBF and sigmoid) were as follows: 0.8075, 0.7340, 0.8462 and 0.8562. The RBF and sigmoid SVM had relatively higher accuracy, sensitivity and specificity. Conclusion Our research raised attention to static and dynamic alterations underlying hearing deprivation. Machine learning-based models may provide several useful biomarkers for the classification and diagnosis of SNHL.
Glycogen synthase kinase-3β (GSK3β) is associated with various key biological processes, and it has been considered as a critical therapeutic target for the treatment of many diseases. However, it is ...a big challenge to develop ATP-competition GSK3β inhibitors because of the high sequence homology with other kinases. In this work, a novel parallel virtual screening strategy based on multiple GSK3β protein structures, integrating molecular docking, complex-based pharmacophore, and naive Bayesian classification, was developed to screen a large chemical database, the 50 compounds with top-scores then underwent a luminescent kinase assay, which led to the discovery of two GSK3β inhibitor hits. The high screening enrichment rate indicates the reliability and practicability of the integrated protocol. Finally, molecular docking and molecular dynamics simulation were employed to investigate the binding modes of the GSK3β inhibitors, and some “hot residues” critical to GSK3β affinity were highlighted. The present study may provide some valuable guidance for the development of novel GSK3β inhibitors.
In this paper, the problem of output synchronization is investigated for the heterogeneous network with an uncertain leader. It is assumed that parameter perturbations influence the nonidentical ...linear agents, whose outputs are controlled to track the output of an uncertain leader. Based on the hierarchical structure of the communication graph, a novel control scheme is proposed to guarantee the output synchronization. As there exist parameter uncertainties in the models of the agents, the internal model principle is used to gain robustness versus plant parameter uncertainties. Furthermore, as the precise model of the leader is also not available, the adaptive control principle is adopted to tune the parameters in the local controllers. The developed new technique is able to simultaneously handle uncertainties in the follower parameters as well as the leader parameters. The agents in the upper layers will be treated as the exosystems of the agents in the lower layers. The local controllers are constructed in a sequential order. It is shown that the output synchronization can be achieved globally asymptotically and locally exponentially. Finally, a simulation example is given to illustrate the effectiveness and potential of the theoretic results obtained.
Beta (β)-carotene (C
40
H
56
; a provitamin) is a particularly important carotenoid for human health. Many studies have focused on engineering
Escherichia coli
as an efficient heterologous producer ...of β-carotene. Moreover, several strains with potential for use in the industrial production of this provitamin have already been constructed via different metabolic engineering strategies. In this study, we aimed to improve the β-carotene-producing capacity of our previously engineered
E. coli
strain ZF43Δ
gdhA
through further gene deletion and metabolic pathway manipulations. Deletion of the
zwf
gene increased the resultant strain's β-carotene production and content by 5.1 and 32.5%, respectively, relative to the values of strain ZF43Δ
gdhA
, but decreased the biomass by 26.2%. Deletion of the
ptsHIcrr
operon further increased the β-carotene production titer from 122.0 to 197.4 mg/L, but the provitamin content was decreased. Subsequently, comparative transcriptomic analysis was used to explore the dynamic transcriptional responses of the strains to the blockade of the pentose phosphate pathway and inactivation of the phosphotransferase system. Lastly, based on the analyses of comparative transcriptome and reduction cofactor, several strategies to increase the NADPH supply were evaluated for enhancement of the β-carotene content. The combination of
yjgB
gene deletion and
nadK
overexpression led to increased β-carotene production and content. The best strain, ECW4/p5C-
nadK
, produced 266.4 mg/L of β-carotene in flask culture and 2,579.1 mg/L in a 5-L bioreactor. The latter value is the highest reported from production via the methylerythritol phosphate pathway in
E
.
coli
. Although the strategies applied is routine in this study, the combinations reported were first implemented, are simple but efficient and will be helpful for the production of many other natural products, especially isoprenoids. Importantly, we demonstrated that the use of the methylerythritol phosphate pathway alone for efficient β-carotene biosynthesis could be achieved via appropriate modifications of the cell metabolic functions.
In this paper, the synchronization of Chaotic Lur’e systems subject to aperiodic sampling is investigated. It is shown that sampling interval is bounded and nonuniform. A modified free-matrix-based ...(MFMB) time-dependent Lyapunov functional is developed to capture the information on sampling pattern, which is sufficiently used to analyze stability of Chaotic Lur’e systems. For a special case that the sampled-data controller suffers constant input delay, a discontinuous Lyapunov functional is presented based on the vector extension of Wirtinger’s inequality. The obtained stability condition leads to a less computational complexity than some of existing works. A longer value on the calculation of sampling interval is achieved. Two illustrative examples demonstrate the effectiveness of designed methods and less conservatism of the obtained results.
We sequenced eight melanoma exomes to identify new somatic mutations in metastatic melanoma. Focusing on the mitogen-activated protein (MAP) kinase kinase kinase (MAP3K) family, we found that 24% of ...melanoma cell lines have mutations in the protein-coding regions of either MAP3K5 or MAP3K9. Structural modeling predicted that mutations in the kinase domain may affect the activity and regulation of these protein kinases. The position of the mutations and the loss of heterozygosity of MAP3K5 and MAP3K9 in 85% and 67% of melanoma samples, respectively, together suggest that the mutations are likely to be inactivating. In in vitro kinase assays, MAP3K5 I780F and MAP3K9 W333* variants had reduced kinase activity. Overexpression of MAP3K5 or MAP3K9 mutants in HEK293T cells reduced the phosphorylation of downstream MAP kinases. Attenuation of MAP3K9 function in melanoma cells using siRNA led to increased cell viability after temozolomide treatment, suggesting that decreased MAP3K pathway activity can lead to chemoresistance in melanoma.
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