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Abstract Neuroinflammation is one of the core pathological features of Parkinson’s disease (PD). Innate immune cells play a crucial role in the progression of PD. Microglia, the major innate immune cells in the brain, exhibit innate immune memory effects and are recognized as key regulators of neuroinflammatory responses. Persistent modifications of microglia provoked by the first stimuli are pivotal for innate immune memory, resulting in an enhanced or suppressed immune response to second stimuli, which is known as innate immune training and innate immune tolerance, respectively. In this study, LPS was used to establish in vitro and in vivo models of innate immune memory. Microglia-specific Hif-1α knockout mice were further employed to elucidate the regulatory role of HIF-1α in innate immune memory and MPTP-induced PD pathology. Our results showed that different paradigms of LPS could induce innate immune training or tolerance in the nigrostriatal pathway of mice. We found that innate immune tolerance lasting for one month protected the dopaminergic system in PD mice, whereas the effect of innate immune training was limited. Deficiency of HIF-1α in microglia impeded the formation of innate immune memory and exerted protective effects in MPTP-intoxicated mice by suppressing neuroinflammation. Therefore, HIF-1α is essential for microglial innate immune memory and can promote neuroinflammation associated with PD.

Summary: Battery health assessment and recuperation play crucial roles in the utilization of second-life Li-ion batteries. However, due to ambiguous aging mechanisms, it is challenging to estimate battery health and devise an effective strategy for cell rejuvenation. This paper presents aging and reconditioning experiments of 62 commercial lithium iron phosphate cells, which allow us to use machine learning models to predict cycle life and identify important indicators of recoverable capacity. An average test error of 16.84% ± 1.87% (mean absolute percentage error) for cycle life prediction is achieved by gradient boosting regressor. Some of the recoverable lost capacity is found to be attributed to the non-uniformity in electrodes. An experimentally validated equivalent circuit model is built to demonstrate how such non-uniformity can be accumulated, and how it can give rise to recoverable capacity loss. Furthermore, Shapley additive explanations (SHAP) analysis also reveals that battery operation history significantly affects the capacity recovery.

Abstract Parkinson’s disease (PD) is mainly characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and neuroinflammation mediated by overactivated microglia and astrocytes. NLRC5 (nucleotide-binding oligomerization domain-like receptor family caspase recruitment domain containing 5) has been reported to participate in various immune disorders, but its role in neurodegenerative diseases remains unclear. In the current study, we found that the expression of NLRC5 was increased in the nigrostriatal axis of mice with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine hydrochloride (MPTP)-induced PD, as well as in primary astrocytes, microglia and neurons exposed to different neurotoxic stimuli. In an acute MPTP-induced PD model, NLRC5 deficiency significantly reduced dopaminergic system degeneration and ameliorated motor deficits and striatal inflammation. Furthermore, we found that NLRC5 deficiency decreased the expression of the proinflammatory genes IL-1β, IL-6, TNF-α and COX2 in primary microglia and primary astrocytes treated with neuroinflammatory stimuli and reduced the inflammatory response in mixed glial cells in response to LPS treatment. Moreover, NLRC5 deficiency suppressed activation of the NF-κB and MAPK signaling pathways and enhanced the activation of AKT–GSK-3β and AMPK signaling in mixed glial cells. Furthermore, NLRC5 deficiency increased the survival of primary neurons treated with MPP+ or conditioned medium from LPS-stimulated mixed glial cells and promoted activation of the NF-κB and AKT signaling pathways. Moreover, the mRNA expression of NLRC5 was decreased in the blood of PD patients compared to healthy subjects. Therefore, we suggest that NLRC5 promotes neuroinflammation and dopaminergic degeneration in PD and may serve as a marker of glial activation.

Although Ni-based anodes are commonly employed in proton-conducting solid oxide fuel cells (H-SOFCs), interfacial diffusion of Ni from the anode to the electrolyte is difficult to avoid, resulting in lower electrolyte and fuel cell performance. In this study, the electrolyte/anode half-cells are co-sintered using a microwave sintering process, providing a lower co-sintering temperature than the standard sintering approach. The lower co-sintering temperature minimizes Ba-evaporation at the electrolyte and mitigates anode/electrolyte interfacial Ni diffusion, resulting in decreased electrolyte and interfacial polarization resistance. The microwave-sintered cell outperforms the traditionally sintered cell in electrochemical performance, with higher fuel cell performance and lower cell resistances. Furthermore, the improved interfacial condition improves the fuel cell's long-term durability, allowing the cell to operate for 200 h without detectable degradation. This study presents an intriguing and simple way to reduce anode/electrolyte interfacial Ni diffusion, which improves fuel cell output and operational stability.

Abstract Rechargeable batteries of high energy density and overall performance are becoming a critically important technology in the rapidly changing society of the twenty-first century. While lithium-ion batteries have so far been the dominant choice, numerous emerging applications call for higher capacity, better safety and lower costs while maintaining sufficient cyclability. The design space for potentially better alternatives is extremely large, with numerous new chemistries and architectures being simultaneously explored. These include other insertion ions (e.g. sodium and numerous multivalent ions), conversion electrode materials (e.g. silicon, metallic anodes, halides and chalcogens) and aqueous and solid electrolytes. However, each of these potential “beyond lithium-ion” alternatives faces numerous challenges that often lead to very poor cyclability, especially at the commercial cell level, while lithium-ion batteries continue to improve in performance and decrease in cost. This review examines fundamental principles to rationalise these numerous developments, and in each case, a brief overview is given on the advantages, advances, remaining challenges preventing cell-level implementation and the state-of-the-art of the solutions to these challenges. Finally, research and development results obtained in academia are compared to emerging commercial examples, as a commentary on the current and near-future viability of these “beyond lithium-ion” alternatives.

In view of the drawbacks of rechargeable batteries, such as low mass and volumetric energy densities, as well as slow charging rate, proton exchange membrane fuel cells (PEMFCs) are reckoned to be promising alternative devices for energy conversion. Currently, commercial PEMFCs mainly use H2 as the fuel, but the challenges in generation, storage, and handling of H2 limit their further development. Among the liquid fuels, formic acid possesses the merits of low flammability, low toxicity, slow crossover rate, faster reaction kinetics, and high volumetric H2 storage capacity, thus being considered as the most promising energy carrier. It can be used as the energy source for direct formic acid fuel cells (DFAFCs) and formic acid-based H2-PEMFCs, which are also called indirect formic acid fuel cells (IFAFCs). A common issue hindering their commercialization is lacking efficient electrocatalysts. In DFAFCs, the anodic electrocatalysts for formic acid oxidation are suffering from stability issue, whereas the cathodic electrocatalysts for oxygen reduction are prone to poisoning by the permeated formic acid. As for IFAFCs, CO and CO2 impurities generated from formic acid dehydrogenation will cause rapid decay in the catalytic activity. High working temperature can improve the CO and CO2 tolerance of catalysts but will accelerate catalyst degradation. This review will discuss the mitigation strategies and recent advances from the aspect of electrocatalysts to overcome the above challenges. Finally, some perspectives and future research directions to develop more efficient electrocatalysts will be provided for this promising field.

Abstract Combining isolated atomic active sites with those in nanoparticles for synergizing complex multistep catalysis is being actively pursued in the design of new electrocatalyst systems. However, these novel systems have been rarely studied due to the challenges with synthesis and analysis. Herein, a synergistically catalytic performance is demonstrated with a 0.89 V (vs reversible hydrogen electrode) onset potential in the four‐step oxygen reduction reaction (ORR) by localizing tungsten single atoms around tungsten nitride nanoparticles confined into nitrogen‐doped carbon (W SAs/WNNC). Through density functional theory calculations, it is shown that each of the active centers in the synergistic entity feature a specific potential‐determining step in their respective reaction pathway that can be merged to optimize the intermediate steps involving scaling relations on individual active centers. Impressively, the W SAs/WNNC as the air cathode in all‐solid‐state Zn‐air and Al‐air batteries demonstrate competitive durability and reversibility, despite the acknowledged low activity of W‐based catalyst toward the ORR.

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by progressive degeneration of midbrain dopaminergic neurons. The miR-29s family, including miR-29a and miR-29b1 as well as miR-29b2 and miR-29c, are implicated in aging, metabolism, neuronal survival, and neurological disorders. In this study, the roles of miR-29a/b1 in aging and PD were investigated. miR-29a/b1 knockout mice (named as 29a KO hereafter) and their wild-type (WT) controls were used to analyze aging-related phenotypes. After challenged with the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), dopaminergic injuries, glial activation, and mouse behaviors were evaluated. Primary glial cells were further cultured to explore the underlying mechanisms. Additionally, the levels of miR-29s in the cerebrospinal fluid (CSF) of PD patients (n = 18) and healthy subjects (n = 17) were quantified. 29a KO mice showed dramatic weight loss, kyphosis, and along with increased and deepened wrinkles in skins, when compared with WT mice. Moreover, both abdominal and brown adipose tissues reduced in 29a KO mice, compared to their WT counterpart. However, in MPTP-induced PD mouse model, the deficiency of miR-29a/b1 led to less severe damages of dopaminergic system and mitigated glial activation in the nigrostriatal pathway, and subsequently alleviated the motor impairments in 3-month-old mice. Eight-month-old mutant mice maintained such a resistance to MPTP intoxication. Mechanistically, the deficiency of miR-29a/b-1 promoted the expression of neurotrophic factors in 1-Methyl-4-phenylpyridinium (MPP+)-treated primary mixed glia and primary astrocytes. In lipopolysaccharide (LPS)-treated primary microglia, knockout of miR-29a/b-1 inhibited the expression of inflammatory factors, and promoted the expression of anti-inflammatory factors and neurotrophic factors. Knockout of miR-29a/b1 increased the activity of AMP-activated protein kinase (AMPK) and repressed NF-κB/p65 signaling in glial cells. Moreover, we found miR-29a level was increased in the CSF of patients with PD. Our results suggest that 29a KO mice display the peripheral premature senility. The combined effects of less activated glial cells might contribute to the mitigated inflammatory responses and elicit resistance to MPTP intoxication in miR-29a/b1 KO mice.

The opaque polyethylene terephthalate (PET) filaments with different mass fractions of TiO2 particles were prepared by low-speed melt spinning and drafting. Basic structures including surface morphology, linear density, orientation degree and crystallinity, and properties including tensile and optical property of the PET/TiO2 filaments were systematically analyzed, especially the visual shielding property. The results showed that TiO2 particles were well-distributed on the filament surface without obvious aggregation, except when the mass fraction of TiO2 exceeded 6%. The addition of TiO2 increased the linear density of the PET filaments. The orientation degree of the filaments was positively correlated with the drafting ratio but hardly influenced by the mass fraction of TiO2. The crystallinity achieved the maximum when the mass fraction of TiO2 was 3% and then decreased gradually. The tenacity of the filaments reduced and the elongation at break enhanced initially and then decreased with the increasing TiO2 content. The opaque effect of the PET filaments improved significantly when the mass fraction of TiO2 was less than 6%, whereas the improvement of the opaque effect slowed down as the mass fraction of TiO2 increased further.

Abstract With the ever‐rapid miniaturization of portable, wearable electronics and Internet of Things, the volumetric performance is becoming a much more pertinent figure‐of‐merit than the conventionally used gravimetric parameters to evaluate the charge‐storage capacity of electrochemical capacitors (ECs). Thus, it is essential to design the ECs that can store as much energy as possible within a limited space. As the most critical component in ECs, “porous and yet dense” electrodes with large ion‐accessible surface area and optimal packing density are crucial to realize desired high volumetric performance, which have demonstrated to be rather challenging. In this review, the principles and fundamentals of ECs are first observed, focusing on the key understandings of the different charge storage mechanisms in porous electrodes. The recent and latest advances in high‐volumetric‐performance ECs, developed by the rational design and fabrication of “porous and yet dense” electrodes are then examined. Particular emphasis of discussions then concentrates on the key factors impacting the volumetric performance of porous carbon‐based electrodes. Finally, the currently faced challenges, further perspectives and opportunities on those purposely engineered porous electrodes for high‐volumetric‐performance EC are presented, aiming at providing a set of guidelines for further design of the next‐generation energy storage devices.

Abstract Atomically dispersed Pt species are advocated as a promising electrocatalyst for the oxygen reduction reaction (ORR) to boost noble metal utilization efficiency. However, when assembled on various substrates, isolated Pt single atoms are often demonstrated to proceed through the two‐electron ORR pathway due to the unfavorable O─O bond cleavage thermodynamics in the absence of catalytic ensemble sites. In addition, although their distinct local coordination environments at the exact single active sites are intensively explored, the interactions and synergy between closely neighboring single atom sites remain elusive. Herein, atomically dispersed Pt monomers strongly interacting on a Mo2C support is demonstrated as a model catalyst in the four‐electron ORR, and the beneficial interactions between two closely neighboring and yet non‐contiguous Pt single atom sites (named as quasi‐paired Pt single atoms) are shown. Compared to isolated Pt single atom sites, the quasi‐paired Pt single atoms deliver a superior mass activity of 0.224 A mg−1Pt and near‐100% selectivity toward four‐electron ORR due to the synergistic interaction from the two quasi‐paired Pt atom sites in modulating the binding mode of reaction intermediates. Our first‐principles calculations reveal a unique mechanism of such quasi‐paired configuration for promoting four‐electron ORR.

The old mortar attached to recycled aggregate (RA) is the main reason for the difference in water movement between RA concrete (RAC) and natural aggregate concrete. In this study, considering the old and new interfacial transition zones, a five-phase composite model for describing the water transport and distribution in RAC is established at the mesoscale. The key parameters describing water unsaturated transport in two types of mortar, saturated hydraulic conductivity (Ks) and van Genuchten model parameters (α, n), are obtained through the constant-head permeability test and isothermal adsorption test. By using the finite element method, the numerical simulations of unsaturated moisture movement in the homogeneous mortar, natural aggregate concrete, and five-phase RAC are systematically carried out. The proposed water transport model in the matrix is validated by comparison with the available experimental findings from the literature. The results show that the model can well predict unsaturated water transport in cement-based materials, including RAC. A parameter sensitivity analysis is undertaken to ascertain the main influencing factors of water transport in RAC. It is concluded that the RA replacement rate (Rra), the thickness of the old mortar (dm), and the aggregate volume fraction (Fa) are the primary parameters affecting moisture movement in RAC.

In this paper, we investigate the allocation of resource in D2D-aided Fog computing system with multiple mobile user equipments (MUEs). We consider each MUE has a request for task from a task library and needs to make a decision on task performing with a selection of three processing modes which include local mode, fog offloading mode, and cloud offloading mode. Two scenarios are considered in this paper, which mean task caching and its optimization in off-peak time, task offloading, and its optimization in immediate time. In particular, task caching refers to cache the completed task application and its related data. In the first scenario, to maximize the average utility of MUEs, a task caching optimization problem is formulated with stochastic theory and is solved by a GA-based task caching algorithm. In the second scenario, to maximize the total utility of system, the task offloading and resource optimization problem is formulated as a mixed integer nonlinear programming problem (MINLP) with a joint consideration of the MUE allocation policy, task offloading policy, and computational resource allocation policy. Due to the nonconvex of the problem, we transform it into multi-MUEs association problem (MMAP) and mixed Fog/Cloud task offloading optimization problem (MFCOOP). The former problem is solved by a Gini coefficient-based MUEs allocation algorithm which can select the most proper MUEs who contribute more to the total utility. The task offloading optimization problem is proved as a potential game and solved by a distributed algorithm with Lagrange multiplier. At last, the simulations show the effectiveness of the proposed scheme with the comparison of other baseline schemes.

Fog computing is an extension of cloud computing, which emphasizes distributed computing and provides computing service closer to user equipments (UEs). However, due to the limited service coverage of fog computing nodes (FCNs), the moving users may be out of the coverage, which would cause the radio handover and execution results migration when the tasks are off-loaded to FCNs. Furthermore, extra cost, including energy consumption and latency, is generated and affects the revenue of UEs. Previous works rarely consider the mobility of UEs in fog computing networks. In this paper, a generic three-layer fog computing networks architecture is considered, and the mobility of UEs is characterized by the sojourn time in each coverage of FCNs, which follows the exponential distribution. To maximize the revenue of UEs, the off-loading decisions and computation resource allocation are jointly optimized to reduce the probability of migration. The problem is modeled as a mixed integer nonlinear programming (MINLP) problem, which is NP-hard. The problem is divided into two parts: tasks off-loading and resource allocation. A Gini coefficient-based FCNs selection algorithm (GCFSA) is proposed to get a sub-optimal off-loading strategy, and a distributed resource optimization algorithm based on genetic algorithm (ROAGA) is implemented to solve the computation resource allocation problem. The proposed algorithms can handle the scenario of UEs' mobility in fog computing networks by significantly reducing the probability of migration. Simulations demonstrate that the proposed algorithms can achieve quasi-optimal revenue performance compared with other baseline algorithms.

The pathological hallmarks of Parkinson's disease (PD) are the progressive loss of dopaminergic (DA) neurons in the substantia nigra pars compacta (SNpc) and the presence of overactivated glial cells and neuroinflammation. Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) c-Rel subunit is closely related in the pathological progress of PD, however the roles and mechanisms of c-Rel in PD development remain unclear. Here, in neurotoxins-induced PD models, the dynamic changes of NF-κB c-Rel and its functions were evaluated. We found that c-Rel was rapidly activated in the nigrostriatal pathway, which mainly occurred in dopaminergic neurons and microglia. c-Rel could maintain neuronal survival by initiating the anti-apoptotic gene expression in MPP+-treated SH-SY5Y cells and it could inhibit microglial overactivation by suppressing the inflammatory gene expression in LPS-challenged BV2 cells. c-Rel inhibitor IT901 aggravated the damage of MPTP on dopaminergic neurons and promoted the activation of microglia in the nigrostriatal pathway of mice. Moreover, the expression of c-Rel in blood samples of PD patients decreased dramatically. Our results indicate that the NF-κB/c-Rel subunit plays an important role in neuroprotection and neuroinflammation inhibition during PD progression. Keywords: Parkinson's disease, NF-κB/c-Rel, Dopaminergic neurons, Microglia, Neuroprotection, Inflammation

The objectives of this study were to determine the effects of intravenous infusions of L-glutamine (Gln) on the autophagy and apoptosis of duodenum cells in early-weaned calves. Holstein male calves were weaned at day 35 (20 male calves, birth weight 43 ± 1.8 kg; 35 ± 3 d of age) and randomly allocated to four treatments (5 calves/treatment). The treatments were: (1) infusion of NaCl, representing the control group (C); (2) infusion of 10 g/d of Gln solution (L); (3) infusion of 20 g/d of Gln solution (M); and (4) infusion of 40 g/d of Gln solution (H). The solutions were infused for 2 h daily for 3 consecutive days after weaning. All calves were killed on the third day post-weaning. The results showed that the autophagy level of the duodenal cells was increased as the Gln infusions increased from 0 to 20 g/d and dropped with a further increase in dose (40 g/d). We also found that the level of apoptosis was decreased with Gln infusion from 0 to 20 g/d and rose as the dose increased to 40 g/d. This knowledge provides a reference for weaned calf health management.

Background/aims To improve the accuracy of pterygium screening and detection through smartphones, we established a fusion training model by blending a large number of slit-lamp image data with a small proportion of smartphone data. Method Two datasets were used, a slit-lamp image dataset containing 20 987 images and a smartphone-based image dataset containing 1094 images. The RFRC (Faster RCNN based on ResNet101) model for the detection model. The SRU-Net (U-Net based on SE-ResNeXt50) for the segmentation models. The open-cv algorithm measured the width, length and area of pterygium in the cornea. Results The detection model (trained by slit-lamp images) obtained the mean accuracy of 95.24%. The fusion segmentation model (trained by smartphone and slit-lamp images) achieved a microaverage F1 score of 0.8981, sensitivity of 0.8709, specificity of 0.9668 and area under the curve (AUC) of 0.9295. Compared with the same group of patients' smartphone and slit-lamp images, the fusion model performance in smartphone-based images (F1 score of 0.9313, sensitivity of 0.9360, specificity of 0.9613, AUC of 0.9426, accuracy of 92.38%) is close to the model (trained by slit-lamp images) in slit-lamp images (F1 score of 0.9448, sensitivity of 0.9165, specificity of 0.9689, AUC of 0.9569 and accuracy of 94.29%). Conclusion Our fusion model method got high pterygium detection and grading accuracy in insufficient smartphone data, and its performance is comparable to experienced ophthalmologists and works well in different smartphone brands. [ABSTRACT FROM AUTHOR]

Herein, we developed a multifunctional cathode (Co-NiMoO4/NF) based on nickel molybdate nanowires grown on Ni foam (NiMoO4/NF) for a hybrid zinc-nickel (Zn-Ni) and zinc-air (Zn-Air) battery. NiMoO4/NF demonstrated a high capacity and good rate capability in the Zn-Ni battery. The subsequent coating of the Co-based oxygen catalyst resulted in the Co-NiMoO4/NF and enabled the battery to exhibit the advantages of both batteries. [ABSTRACT FROM AUTHOR]