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An integrated battery system, which integrates solar power and rechargeable battery in the same unit, is recognized as a propective solution for the shortage and inefficiency of power energy. Herein, a hybrid S/N719 dye cathode is proposed in the rechargeable Li-S battery to realize the photo-assisted charging battery system. Specifically, the photo-charge contribution reduces the charge voltage of the sulfur cathode by 0.12 V and accelerates the charge process under light illumination, showing the great potential in saving electric energy and expediting fast-charge capacity of Li-S battery.

The fungus Sporidiobolus pararoseus not only produces carotenoids, but also produces bioactive extracellular polysaccharides (SPP). However, the relationship between SPP and the metabolism of gut microbiome is unclear. The aim of this study was to investigate the mechanism of SPP regulating intestinal health in vivo and in vitro. Results showed that SPP are nondigestible polysaccharides after the digestion with simulated stomach and small intestinal juice in vitro. After SPP was cultured in an in vitro intestinal simulation system for seven days, the concentration of short-chain fatty acids (SCFAs) increased; the microbial diversity changed; the relative abundance of Bifidobacterium and Streptococcus increased; and that of Escherichia Shigella and Lachnospiraceae NK4A136 decreased. In addition, metabolism of SPP by the mice colonic microbiome showed SPP decreased the relative abundance of Firmicutes and Bacteroidota, while the relative abundance of Verrucomicrobiota, Desulfobacterota, and Actinobacteriota increased. Finally, predicted Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolism results also showed that SPP can enhance the metabolism of cofactors, vitamins, amino acids, starch, and sucrose. In conclusion, SPP can multiply the intestinal beneficial bacteria of humans and mice, promote the production of SCFAs and metabolism of amino acids, and promote intestinal health.

High oxygen evolution overpotential and low corrosion resistance are the main challenges for oxygen evolution materials in acidic media. In this study, a novel composite material, Ti/TiO2-NTs/PbO2–CNTs–MnO2, with high oxygen evolution electrocatalytic activity was successfully prepared. First, TiO2 nanotubes (TiO2-NTs) were synthesized in situ on a Ti sheet via anodization and used as an intermediate layer. Subsequently, the adhesion and conductivity of the TiO2-NTs layer were increased through additional anodization, annealing, and electrochemical reduction. Finally, PbO2 was electrodeposited with a constant current in a lead acetate medium and doped with carbon nanotubes (CNTs) and MnO2. The surface morphology, phase composition, and electrochemical performance of the composite materials were investigated. Notably, in an acidic electrolyte (150 g/L H2SO4), Ti/TiO2-NTs/PbO2–CNTs–MnO2 exhibited good stability (30 h) and a low oxygen evolution overpotential of 410 mV at 50 mA/cm2, which is almost equivalent to that of precious metals (RuO2 and IrO2) and 499 mV lower than that of the industrial Pb–0.76 wt% Ag alloy. The outstanding performance is mainly attributed to the high aspect ratio of the TiO2-NT structure, synergistic effects of the active particles, and inherently good electrochemical properties of the active particles. Therefore, this study provides a new synthetic route for oxygen evolution materials in acidic media.

Oxidative damage and intestinal dysbiosis are regarded as crucial culprits in alcoholic liver disease (ALD). This study aimed to examine the protective effects of Echinacea purpurea polysaccharides (EPPs) against ALD and explore the underlying mechanisms based on hepatic oxidative stress, inflammation, and intestinal barrier function. Three polysaccharide fractions, namely, EPP40, EPP60, and EPP80, were obtained by stepwise ethanol precipitation, and their antioxidant activity in vitro was investigated. The results showed that EPP80 with Mw 11.82 kDa had the strongest radical-scavenging capacity against DPPH, ABTS, and •OH radicals. Besides, EPP80 comprised arabinose, galactose, glucose, mannose, galacturonic acid, and glucuronic acid in molar ratios of 13.42:25.12:10.92:8.59:2.07:0.82. The in vivo results showed that EPP80 increased the activities of antioxidant enzymes and reduced the levels of inflammatory cytokines both in mouse serum and liver. Moreover, EPP80 upregulated the expression of Occludin and ZO-1, revealing its protective effect against intestinal barrier dysfunction. Furthermore, EPP80 inhibited alcohol-induced oxidative damage by promoting the expression of Nrf2, HO-1, and NQO1 in the liver. In summary, EPP80 markedly scavenged free radicals in vitro and ameliorated alcohol-induced liver injury via Nrf2/HO-1 pathways in vivo. These findings suggested that EPP80 could provide effective supplementary support in preventing and treating ALD.

BackgroundStructural neuroimaging studies have identified similarities in the brains of individuals diagnosed with schizophrenia (SZ) and bipolar I disorder (BP), with overlap in regions of gray matter (GM) deficits between the two disorders. Recent studies have also shown that the symptom phenotypes associated with SZ and BP may allow for a more precise categorization than the current diagnostic criteria. In this study, we sought to identify GM alterations that were unique to each disorder and whether those alterations were also related to unique symptom profiles.Materials and methodsWe analyzed the GM patterns and clinical symptom presentations using independent component analysis (ICA), hierarchical clustering, and n-way biclustering in a large (N ∼ 3,000), merged dataset of neuroimaging data from healthy volunteers (HV), and individuals with either SZ or BP.ResultsComponent A showed a SZ and BP < HV GM pattern in the bilateral insula and cingulate gyrus. Component B showed a SZ and BP < HV GM pattern in the cerebellum and vermis. There were no significant differences between diagnostic groups in these components. Component C showed a SZ < HV and BP GM pattern bilaterally in the temporal poles. Hierarchical clustering of the PANSS scores and the ICA components did not yield new subgroups. N-way biclustering identified three unique subgroups of individuals within the sample that mapped onto different combinations of ICA components and symptom profiles categorized by the PANSS but no distinct diagnostic group differences.ConclusionThese multivariate results show that diagnostic boundaries are not clearly related to structural differences or distinct symptom profiles. Our findings add support that (1) BP tend to have less severe symptom profiles when compared to SZ on the PANSS without a clear distinction, and (2) all the gray matter alterations follow the pattern of SZ < BP < HV without a clear distinction between SZ and BP.

In large smelting plants such as steel plant and coking plant the utilization rate of the byproduct gas is generally low, especially in developing countries. Usually, multiple low-parameter boilers are combined with multiple low-parameter steam turbines, which are built in phases, to drive the smelting accessory machineries. In terms of energy utilization efficiency, this model is definitely not economical. Based on the law of thermodynamics, the direction of efficiency improvement was proposed, and the solution of gas utilization system was put forward, according to the Rankine cycle principle. Finally, with a steel plant as the research object, the proposed scheme was applied in the transformation of this plant, and the economic benefit was estimated. The results show that the proposed scheme in this paper can generate more electricity with the same gas consumption.

Aimed at the limited engineering condition that only gas calorific value but not gas composition can be provided, a new theoretical combustion calculation method based on gas calorific value was proposed, which is suitable for calculating the theoretical dry flue gas volume of metallurgical gas. In the new method, three simplified models were proposed, including blast furnace gas (BFG) model, Linz–Donawitz converter gas (LDG) model and coke oven gas (COG) model. The simplified models were respectively derived from the original model of theoretical combustion calculation, according to the composition characteristics of each metallurgical gas. Finally, the proposed models were verified through large sample of BFG, LDG and COG. The verification results show that the new models for calculating the theoretical dry flue gas volume of metallurgical gas all have high accuracy. The average relative errors of BFG model, LDG model and COG model are only 0.35%, 0.12%, 0.64% respectively. Thus, the new method proposed in this paper is reasonable and feasible. It can meet the accuracy requirement of engineering and can provide a new way for theoretical combustion calculation of metallurgical gas.

This study aimed to use a machine-learning method to identify HTR1A/1B methylation and resting-state functional connectivity (rsFC) related to the diagnosis of MDD, then try to build classification models for MDD diagnosis based on the identified features.Peripheral blood samples were collected from all recruited participants, and part of the participants underwent the resting-state fMRI scan. Features including HTR1A/1B methylation and rsFC were calculated. Then, the initial feature sets of epigenetics and neuroimaging were separately input into an all-relevant feature selection to generate significant discriminative power for MDD diagnosis. Random forest classifiers were constructed and evaluated based on identified features. In addition, the SHapley Additive exPlanations (SHAP) method was adapted to interpret the diagnostic model.A combination of selected HTR1A/1B methylation and rsFC feature sets achieved better performance than using either one alone - a distinction between MDD and healthy control groups was achieved at 81.78% classification accuracy and 0.8948 AUC.A high classification accuracy can be achieved by combining multidimensional information from epigenetics and cerebral radiomic features in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD and further exploring the pathogenesis of MDD.

MgO activated slag and bentonite (MASB) slurry is a new and promising vertical barrier material along with excellent performances. Some solid wastes, such as phosphogypsum (PG), red mud (RM), fly ash and so on, show a positive effect on the performances of alkali activated slag. However, few studies focus on the recycling of these solid wastes in the system of MgO activated slag. The purpose of this paper is to study the incorporation of phosphogypsum and red mud on the mechanical property, permeability and hydration process of MASB slurry. The results showed that the addition of PG could significantly improve the mechanical strength and anti-permeability of the MASB slurry at early age (7 days), where the unconfined compressive strength (UCS) increased from 793.1 kPa to 1395.7 kPa and the permeability coefficient declined from 16.1 × 10

Chlorogenic acid (CGA) is a functional phenolic acid widely used in food and medicine-related fields. It has been proved to be effective in the treatment of alcoholic liver disease (ALD). However, the exact mechanism by which CGA prevents ALD, especially from the crosstalk between gut and liver, has not been previously reported. This work was aimed to explore the protective effects of CGA against ALD and its relationships to gut-liver axis abnormalities. Experimental results showed the increased (p 0.05) serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), low density lipoprotein (LDL), total cholesterol (TC) and triglyceride (TG) levels of mice fed with ethanol were ameliorated by supplementing with CGA. Moreover, CGA promoted the production of n-butyric acid by nearly 3 times (1.78 vs 0.62 nM, p 0.01), a short-chain fatty acid that helps maintain the integrity of the intestinal barrier. Furthermore, CGA alleviated microbial dysbiosis, evidenced by the increased relative abundances of beneficial bacteria Muribaculaceae, Bacteroides, Alloprevotella, and Parabacteroides, and decreased that of opportunistic pathogens Eubacterium_nodatum, Eubacterium_ruminantium, and Anaerotruncus. Correlation analysis further elucidated the microbiota altered after CGA intervention was positively correlated with short-chain fatty acids and antioxidant indexes, while negatively correlated with inflammatory cytokines. In summary, these findings suggested the hepatoprotective effect of CGA was ascribed to the modulation of gut-liver axis homeostasis.

Spinel-type oxides have attracted a broad interest in sensing materials research owing to their high catalytic activity and flexibly tunable chemical properties. Here, we report the synthesis of superfine porous NiFe2O4 microspheres by one-step solvothermal approach, in order to fabricate ultra-sensitive acetone sensors for real-time monitoring, relying on the high catalytic activity of NiFe2O4 and effective mass transfer property of porous microspheres structure. The porous NiFe2O4 sensors displayed high selectivity to acetone against other interfering gases, giving a high sensitivity (27.4), fast response time (2 s) towards 100 ppm acetone and low detection limit (200 ppb) at 250 °C. This paper proposed a general approach for fabricating highly sensitive gas sensor based on spinel-type oxides in monitoring volatile organic pollutants.

In this paper, we propose a novel local and global deep matching model to tackle bidirectional image-sentence retrieval. Our proposed matching model can simultaneously exploit the image representation, sentence representation, as well as their complicated matching relationships from both local and global perspectives. For images, two different convolutional neural networks (CNNs) are leveraged to encode the local and global contents, with selective attentions to the image sub-regions and the whole image. For sentences, a CNN based sentence model and Fisher vector are employed to capture the global and local semantic meanings, respectively. Relying on the local and global representations of the image and sentence, the proposed deep matching model learns the complicated image-sentence matching relationships from local and global perspectives by integrating cross-modality correlations with intra-modality similarities. Extensive experimental results demonstrate that the proposed local and global matching model outperforms the state-of-the-art bidirectional retrieval approaches on the Flickr8K, Flickr30K, and MSCOCO datasets. Moreover, the image and sentence representations exploited in local and global levels are demonstrated to play synergic and complementary roles for bidirectional image-sentence retrieval.

Urchin-like hierarchical Zn doped CdS powders were successfully synthesized via simple one-pot hydrothermal process. Their SEM and TEM images indicated that the hierarchical structure were assembled by single crystal nanorods with the hexagonal wurtzite phase. EDS element mapping verified that Zn ions were homogeneously distributed among the hierarchical microstructure. The performances of gas sensors based on pure and Zn doped CdS were measured and compared. The results indicated that Zn doping could enhance their responses to some volatile organic compounds and improve its selectivity to ethanol and toluene as well. The possible reasons for this enhancement were investigated. In addition, the sensor based on Zn doped CdS exhibited the ultrafast response and recovery to ethanol ( τ response 1 , τ recovery = 8 s ), indicating that the Zn doped CdS could be a promising gas sensing candidate for online monitoring of ethanol.

The undoped and 1.0–5.0 mol% La–doped In2O3 hollow microspheres have been successfully synthesized via a simple hydrothermal method without template and gas sensor have been fabricated basing on them. The nanostructures and morphologies of the maintained hollow spheres were characterized by various experimental techniques. The gas sensing properties of these hollow microspheres were investigated systematically. The results indicated that among all the samples (pure, 1.0, 3.0 and 5.0 mol% La–doped In2O3), 3.0 mol% La–doped In2O3 exhibited the highest response toward 10 ppm hydrogen sulfide (H2S) at 200 °C, having a response value of 17.8, approximately 4.8 times higher than pure In2O3. Furthermore, excellent selectivity, good repeatability and outstanding long-term stability were also achieved. The significantly enhanced sensing properties to H2S could be attributed to the changes in distribution of different oxygen components, crystallite size and specific surface area caused by La doping.

Transition metal hydroxides, due to their low cost and high theoretical capacity, are promising candidates for supercapacitors. However, the lower conductivity of hydroxides usually results in devices exhibiting poor specific capacity. Here, Ni(OH)2@Ni12P5 electrodes are designed and prepared, showing great potential for applications. This composite electrode, prepared by simple phosphating treatment and electrodeposition. Compared with the Ni(OH)2 prepared by direct deposition, this rationally designed electrode exhibits more excellent electrochemical properties. The prepared Ni(OH)2@Ni12P5 electrode exhibits a good area specific capacitance of 15.89 F•cm−2 at a current density of 10 mA•cm−2, which is 2.93 times higher than that of the Ni(OH)2 electrode (5.43 F•cm−2). In addition, the assembled Ni(OH)2@Ni12P5//AC asymmetric supercapacitor exhibits an energy density of 0.38 mWh•cm−2 at a power density of 8.00 mW•cm−2 . Therefore, this work provides a new strategy for the synthesis of high-performance supercapacitor electrodes.

Many real-world applications propose the request for sharing knowledge among different tasks or datasets. Transfer learning has been proposed to solve this kind of problems and it has been successfully applied in supervised learning and semi-supervised learning settings. However, its adoption in clustering, one of the most classical research problems in machine learning and data mining, is still scarce. Spectral clustering, as a major clustering algorithm with wide applications and better performance than k-means typically, has not been well incorporated with knowledge transfer. In this paper, we first consider the problem of learning from only one auxiliary unlabeled dataset for spectral clustering and propose a novel algorithm called transfer spectral clustering (TSC). Then, it is extended to the settings with multiple auxiliary tasks. TSC assumes the feature embeddings being shared with the auxiliary tasks and utilizes co-clustering to extract useful information from the auxiliary datasets to improve the clustering performance. TSC involves not only the data manifold information of individual task but also the feature manifold information shared between related tasks. An in-depth explanation of our algorithm together with a convergence analysis are provided. As demonstrated by the extensive experiments, TSC can effectively improve the clustering performance by using auxiliary unlabeled data when compared with other state-of-the-art clustering algorithms.

High concentrations of lead in soil will greatly weaken the stabilization/solidification effect. Humin (HM) is expected to improve this process because it is a neutral, insoluble, porous and green material as well as an eco-friendly adsorbent extracted from natural peat soil. However, HM has not been studied with respect to the stabilization/solidification (S/S) characteristics of potentially toxic element (PTE)-contaminated soil due to its different extraction sources and methods, as well as complex properties. To study these effects, insoluble HM was extracted for treatment of high-lead contaminated soil by cement-based S/S. The experimental results show that HM has a strong adsorption capacity for lead with a maximum adsorption capacity of 200.2 mg kg−1. The negative influence of a high content of lead on the compressive strength over a 0–90-day period is weakened after adding HM to the soil, wherein a competitive mechanism between HM and a high concentration of lead is proposed. The lead leaching concentration of stabilized soil is significantly decreased under different leaching methods from 0 to 60 days and then decreases slowly. The lead speciation results for the stabilized soil determined through the Tessier sequential extraction method show that HM promotes the gradual chemical transformation of lead from exchangeable and carbonate-bound fractions to a more stable state, with respective decreases of 27.5% and 15.1%. In addition, SEM-EDS images show that HM with a high porosity and specific surface area coexists well with cement, which promotes the stabilization of lead. In conclusion, HM contributes to decreasing the mobility and bioavailability of lead and achieving environmental remediation.

In industrial zinc electrowinning, the anodic oxygen evolution reaction (OER) has sluggish kinetics leading to ultrahigh overpotential and energy consumption. Herein, a sandwich-like MnCo2O4 modifying PbO2 composite electrode was fabricated via chemical-bath-deposition and electrodeposition. Consequently, the synthesized PbO2 electrode exhibits low Tafel slope of 0.17 V per decade and an operating potential of 1.68 V vs. SCE for 500 A m−2 in a simulated solution containing 150 g L−1 H2SO4 and 50 g L−1 Zn2+. Compared with traditional Pb-0.76Ag alloy, the overpotential at 500 A m−2 decreased by 357 mV, which ascribe to the incorporation of MnCo2O4 minoring crystal grain size and charge transfer resistance and enlarging active surface area. Furthermore, the composite electrode shows robust durability as long as 95 h at 15,000 A m−2 in 0.5 M H2SO4 electrolyte. Hence, this study offers a facile synthesis route to prepare composite electrodes for zinc electrowinning and provides deep insight into the relationship among modifying substances, microstructures, and electrocatalytic activity.

Although numerous studies have investigated the effect of green space on mental health, as yet, little is known about the association between green space and suicide. To address this deficit, we conducted the first Japan-wide study of the relationship between green space and suicide mortality. Results from spatial analyses of municipality-level panel data for the 1975-2014 period that included 886,440 suicide deaths with a fixed-effect estimator showed that green space was associated with suicide mortality, and that this relationship was conditioned by the form of greenness, level of urbanity and demographic characteristics. In densely populated cities, park density (parks per 1000 of the population) was associated with reduced suicide mortality among females aged 18 and above and among males aged 18 to 39 and aged 65 and above. In small- and medium-sized cities, park coverage (% by area) was linked to fewer suicide deaths among middle-aged and older females (aged 40 and above). In contrast, in non-cities (rural areas), parks were not associated with suicide mortality whereas woodland coverage (% by area) was linked to reduced suicide deaths among middle-aged and older males (aged 40 and above). Our findings suggest that urban green space and rural forest coverage may have a protective effect against self-harming behavior. Future suicide prevention efforts should consider an increased greening of the residential environment in terms of both availability and accessibility, especially with better designs that accommodate population needs and local conditions.

This study aims to explore the early response of antidepressant therapy by measuring the voxel-mirrored homotopic connectivity (VMHC) in major depressive disorder (MDD). Eighty-two MDD patients [n=42 treatment-responsive depression (RD) and n=40 non-responding depression (NRD)] and n=50 normal controls (NC) underwent clinical measures and a magnetic resonance imaging scan, and the VMHC values were calculated. Receiver operating characteristic (ROC) curve analysis was applied to determine the capability of altered VMHC to distinguish NRD. The NRD showed significantly decreased VMHC in bilateral precuneus (PCU) and inferior temporal gyrus (ITG), and increased VMHC in middle frontal gyrus (MFG) and caudate nucleus as compared to RD. When compared with NC, the NRD exhibited reduced VMHC in bilateral cerebellum anterior lobe, thalamus and postcentral gyrus. Moreover, VHMC in medial frontal gyrus, postcentral gyrus and precentral gyrus were significantly decreased in RD. Correlation analysis showed that reduced VMHC in PCU was negatively correlated with the baseline HAMD score of the NRD group. The ROC curve indicated that the combined changes of the three regional VMHC (PCU, ITG and MFG) could effectively identify NRD. The current study suggests that interhemispheric asynchrony may represents a novel neural trait underlying the prediction of early therapeutic outcome in MDD.

Large animal models of optic nerve injury are essential for translating novel findings into effective therapies due to their similarity to humans in many respects. However, most current tests evaluating the integrity of retinal ganglion cells (RGCs) and optic nerve (ON) are based on rodent animal models. We aimed to evaluate and optimize the in vivo methods to assess RGCs and ON's function and structure in large animals in terms of reproducibility, simplicity and sensitivity. Both goats and rhesus macaques were employed in this study. By using goats, we found anesthesia with isoflurane or xylazine resulted in different effects on reproducibility of flash visual evoked potential (FVEP) and pattern electroretinogram (PERG). FVEP with the large-Ganzfeld stimulator was significantly more stable than that with mini-Ganzfeld stimulator. PERG with simultaneous binocular stimulation, with superior simplicity over separate monocular stimulation, was appliable in goats due to undetectable interocular crosstalk of PERG signals. After ON crush in goats, some FVEP components, PERG, OCT and PLR demonstrated significant changes, in line with the histological study. By using rhesus macaque, we found the implicit time of PVEP, FVEP and PERG were significantly more reproducible than amplitudes, and OCT and PLR demonstrated small intersession variation. In summary, we established an optimized system to evaluate integrity of RGCs and ON in large animals in vivo, facilitating usage of large animal models of optic nerve diseases.

MoO3 gas-sensing materials with different Ni2+ doping concentration were prepared by a simple one-step solvothermal method. The phase structure, micro-structure and morphology of the as-prepared samples were characterized by X-ray powder diffraction (XRD), field emission scanning electron microscope (FESEM) and the transmission electron microscope (TEM) etc., respectively. The morphology can be changed by adjusting the doping concentration of Ni2+. Among them, the 5 mol% Ni-doped MoO3 sample with a pompon-like morphology improved gas accessibility significantly. Prominently, the response of the sensors on xylene was increased 18 times from 3.48 to 62.6, the response time was about 1 s and the best selectivity was obtained at the optimum temperature of 250 °C. These breakthroughs are attributed to the increase of surface-active sites and the improvement of micro-morphology caused by Ni2+ doping.

Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings.

Conversion reactions of SnO2-based anode materials have recently been confirmed reversible by using well-designed nanostructures, while the detailed mechanism during charging and discharging is still ambiguous. Unwrapping the real mechanism is helpful to design high-performance SnO2-based anode materials. In this work, we designed and fabricated a nanoarchitecture of ultrafine SnO2 (3–5 nm) anchored on the surfaces of carbon nanofibers (denoted as u-TOCNFs). The u-TOCNFs electrode exhibits high reversible capacity of 1006.4 mAh·g−1, high initial Coulombic efficiency of 71.3% and good cycle stability mainly due to good dispersion of ultrafine SnO2 on the conductive carbon nanofibers. The structure evolution is investigated by TEM observations that confirm the presence of amorphous SnO2 on the delithiated nanoanode at 1.28 V after 100 cycles. Charge/discharge induced amorphization of SnO2 nanocrystals is firstly observed that readily explain the capacity increasing around 100 cycles. In particular, we propose the mechanism of reversible conversion reactions of SnO2 and Sn induced by the amorphization of ultrafine SnO2 during lithiation/delithiation. We believe that it is a new direction to study SnO2-based anode materials to improve the electrochemical performance for lithium ion batteries. Keywords: Ultrafine SnO2, Reversible conversion, Amorphization, Lithium ion battery

Accurate assessment of the left ventricular ejection fraction (LVEF) is crucial for making therapeutic decisions. The echocardiographic method for quantification of LVEF recommended by the American Society of Echocardiography is the biplane Simpson's method. However, this method requires manual

Background Current diagnoses of Schizophrenia (SZ) and related psychiatric disorders are catalogued by phenomenological principles and clinical descriptions. Complicated gene and environmental factor interactions likely play an important role in the onset of SZ and induce great heterogeneity. This unclear etiology and heterogeneity prevent the establishing of accurate subgroups within SZ through clinical observation alone; simultaneously, the boundaries among psychiatric disorders previously drawn by phenomenological findings are merging because there is great overlap, especially in genetic variations and brain imaging findings. By characterizing and quantifying brain regions affected in psychiatric disorders, imaging genetics is a valuable research method to fulfill a new diagnostic system. We review contributions of imaging genetics to SZ diagnosis, limitations, and possible future directions. Methods Among numerous imaging genetic studies, we reviewed recent studies with relatively clear and consistent findings. They were either done in task-phase imaging to indicate certain cognitive impairments of SZ, or the genes included were highlighted in SZ itself or an important cognitive domain related to SZ. Results Some pioneering studies contribute to subtypes and disorder boundaries. The clustering study from Arnedo et al. formed correlations between disjoined networks of symptom groups and Single Nucleotide Polymorphism (SNP) sets, and it may be promising for future SZ subtypes. Bipolar-SZ Network on Intermediate Phenotypes studies combining various clinical biomarkers and brain imaging divided SZ, bipolar disorder and schizoaffective disorder into three different “biotypes” regardless original diagnoses, and it provided meaningful insight into the disorder boundaries. For imaging genetics research, large numbers of associations between functional imaging intermediate phenotypes and genes have been found in working memory, episodic memory, emotion, attention, cognitive control, and theory of mind in SZ or healthy risk allele carriers. Such associations were difficult to identify while using structural brains measures. Discussion Imaging genetics will continue to shape the diagnosis of SZ and related disorders. However, there are still problems to solve. Most importantly, the logic behind imaging genetics has been questioned. Franke et al. reminds us the structural brain deficits believed to be important pathological alterations of SZ may reflect prenatal and later development environmental effects not specific to SZ, or the diagnostic category of SZ may not be uniformly organized. The following aspects need future effort. Firstly, more brain measures need to be introduced, and the criteria of intermediate phenotypes should be carefully checked. The specificity of brain alterations will need careful examination in clinical settings. Secondly, more genetic factors need to be collected. Polygenic risk scores, parallel independent component analysis and other clustering method may be promising. Factors other than SNPs, such as copy number variations and regulatory factors will need to be included. Finally, imaging genetics will need compatible phenomenological assessment scales which need not distinguish current diagnoses but provide a comprehensive scan of clinical features.