Tin Hybrid Flow Batteries with Ultrahigh Areal Capacities Enabled by Double Gradients

Tin-based hybrid flow batteries have demonstrated dendrite-free morphology and superior performance in terms of cycle life and energy density. However, the quick accumulation of electrodeposits near the electrode/membrane interface blocks the ion transport pathway during the charging of the battery, resulting to a very limited areal capacity (especially at high current density) that significantly hinders its deployment in long-duration storage applications. Herein, a conductivity-activity dual-gradient design is disclosed by electrically passivating the carbon felt near the membrane/electrode interface and chemically activating the carbon felt near the electrode/current collector interface. In consequence, the tin metals are preferentially plated at the region near electrode/current collector, preventing the ion transport pathway from being easily blocked. The resultant gradient electrode demonstrated an unprecedentedly high areal capacity of 268 mAh cm-2 at a current density of as high as 80 mA cm-2 . Numerical modeling and experimental characterizations show that the dual-gradient electrode differs from conventional electrodes with regard to their reaction current density distribution and electrodeposit distribution during charging. This work demonstrates a new design strategy of 3D electrodes for hybrid flow batteries to induce a desirable distribution of electrodeposits and achieve a high areal capacity at commercially relevant current densities.

Personal relative deprivation impairs the ability to inhibit impulsive responses: an exploratory ERP study

Evidence indicates that personal relative deprivation (PRD) can lead to various impulsive behaviors. Given that impulsive behaviors are usually caused by a failure to exert cognitive control, the purpose of this study was to explore whether PRD affects the ability to exert cognitive control on behavior. Forty-six healthy participants were randomly assigned to PRD or non-PRD group. Participants of the PRD group were told their income would lie below the Chinese average. While their electrophysiological responses were recorded, they underwent a Go/No-Go task simultaneously assessing the ability to detect response conflict and inhibit the predominant response. We found that the individuals with induced PRD show diminished ability to inhibit predominant response. We suggest this is because PRD-related concerns consume cognitive resources, leaving less for other tasks. However, we also found that individuals with induced PRD show enhanced ability to detect conflict. This might be because that individuals with induced PRD were sensitive to potentially threatening information (high-conflict No-Go trials) and they can detect conflict with less cognitive resources. These findings may facilitate future attempts to design interventions for relatively deprived individuals to manage their impulsive behavior.

Building Atomic Scale and Dense Fe─N4 Edge Sites of Highly Efficient Fe─N─C Oxygen Reduction Catalysts Using a Sacrificial Bimetallic Pyrolysis Strategy

Replacing high-cost and scarce platinum (Pt) with transition metal and nitrogen co-doped carbon (M/N/C, M = Fe, Co, Mn, and so on) catalysts for the oxygen reduction reaction (ORR) in proton exchange membrane fuel cells has largely been impeded by the unsatisfactory ORR activity of M/N/C due to the low site utilization and inferior intrinsic activity of the M─N4 active center. Here, these limits are overcome by using a sacrificial bimetallic pyrolysis strategy to synthesize Fe─N─C catalyst by implanting the Cd ions in the backbone of ZIF-8, leading to exposure of inaccessible FeN4 edge sites (that is, increasing active site density (SD)) and high fast mass transport at the catalyst layer of cathode. As a result, the final obtained Fe(Cd)─N─C catalyst has an active site density of 33.01 µmol g-1 (with 33.01% site utilization) over 5.8 times higher than that of Fe─N─C catalyst. Specially, the optimal catalyst delivers a high ORR performance with a half-wave potential of 0.837 (vs RHE) in a 0.1 m HClO4 electrolyte, which surpasses most of Fe-based catalysts.

SSNMDI: a novel joint learning model of semi-supervised non-negative matrix factorization and data imputation for clustering of single-cell RNA-seq data

MOTIVATION

Single-cell RNA sequencing (scRNA-seq) technology attracts extensive attention in the biomedical field. It can be used to measure gene expression and analyze the transcriptome at the single-cell level, enabling the identification of cell types based on unsupervised clustering. Data imputation and dimension reduction are conducted before clustering because scRNA-seq has a high 'dropout' rate, noise and linear inseparability. However, independence of dimension reduction, imputation and clustering cannot fully characterize the pattern of the scRNA-seq data, resulting in poor clustering performance. Herein, we propose a novel and accurate algorithm, SSNMDI, that utilizes a joint learning approach to simultaneously perform imputation, dimensionality reduction and cell clustering in a non-negative matrix factorization (NMF) framework. In addition, we integrate the cell annotation as prior information, then transform the joint learning into a semi-supervised NMF model. Through experiments on 14 datasets, we demonstrate that SSNMDI has a faster convergence speed, better dimensionality reduction performance and a more accurate cell clustering performance than previous methods, providing an accurate and robust strategy for analyzing scRNA-seq data. Biological analysis are also conducted to validate the biological significance of our method, including pseudotime analysis, gene ontology and survival analysis. We believe that we are among the first to introduce imputation, partial label information, dimension reduction and clustering to the single-cell field.

AVAILABILITY AND IMPLEMENTATION

The source code for SSNMDI is available at https://github.com/yushanqiu/SSNMDI.

Genome-Wide Identification and Bioinformatics Analyses of Host Defense Peptides Snakin/GASA in Mangrove Plants

Host defense peptides (HDPs) are components of plant defensive barriers that resist microbial infection. Members of the Snakin/GASA protein family in plants have functions of regulating plant growth, defense, and bacteriostasis. Most mangrove plants grow in coastal zones. In order to survive in harsh environments, mangrove plants have evolved complex adaptations against microbes. In this study, Snakin/GASA family members were identified and analyzed in the genomes of three mangrove species. Twenty-seven, thirteen, and nine candidate Snakin/GASA family members were found in Avicennia marina, Kandelia obovata, and Aegiceras corniculatum, respectively. These Snakin/GASA family members were identified and categorized into three subfamilies via phylogenetic analysis. The genes coding for the Snakin/GASA family members were unevenly distributed on chromosomes. Collinearity and conservative motif analyses showed that the Snakin/GASA family members in K. obovata and A. corniculatum underwent multiple gene duplication events. Snakin/GASA family member expression in normal leaves and leaves infected with pathogenic microorganisms of the three mangrove species was verified using real-time quantitative polymerase chain reaction. The expression of KoGASA3 and 4, AcGASA5 and 10, and AmGASA1, 4, 5, 15, 18, and 23 increased after microbial infection. This study provides a research basis for the verification of HDPs from mangrove plants and suggests directions for the development and utilization of marine biological antimicrobial peptides.

2D Layers of Group VA Semiconductors: Fundamental Properties and Potential Applications

Members of the 2D group VA semiconductors (phosphorene, arsenene, antimonene, and bismuthine) present a new class of 2D materials, which are recently gaining a lot of research interest. These materials possess layered morphology, tunable direct bandgap, high charge carrier mobility, high stability, unique in-plane anisotropy, and negative Poisson's ratio. They prepare the ground for novel and multifunctional applications in electronics, optoelectronics, and batteries. The most recent analytical and empirical developments in the fundamental characteristics, fabrication techniques, and potential implementation of 2D group VA materials in this review, along with presenting insights and concerns for the field's future are analyzed.

A "Missile-Detonation" Strategy to Precisely Supply and Efficiently Amplify Cerenkov Radiation Energy for Cancer Theranostics

Cerenkov radiation (CR) from radionuclides can act as a built-in light source for cancer theranostics, opening a new horizon in biomedical applications. However, considerably low tumor-targeting efficiency of existing radionuclides and radionuclide-based nanomedicines limits the efficacy of CR-induced theranostics (CRIT). It remains a challenge to precisely and efficiently supply CR energy to the tumor site. Here, a "missile-detonation" strategy is reported, in which a high dose of p-SCN-Bn-deferoxamine-porphyrin-PEG nanocomplex (Df-PPN) is first adminstered as a CR energy receiver/missile to passively target to tumor, and then a low dose of the 89 Zr-labeled Df-PPN is administrated as a CR energy donor/detonator, which can be visualized and quantified by Cerenkov energy transfer imaging, positron-emission tomography, and fluorescence imaging. Based on homologous properties, the colocalization of Df-PPN and 89 Zr-Df-PPN in the tumor site is maximized and efficient CR energy transfer is enabled, which maximizes the tumor-targeted CRIT efficacy in an optimal spatiotemporal setting while also reducing adverse off-target effects from CRIT. This precise and efficient CRIT strategy causes significant tumor vascular damage and inhibited tumor growth.

Omnidirectional Absorber by the Void Plasmon Effect in the Visible Region with Greatly Enhanced Localized Electric Field

We propose and investigate a wide-angle and high-efficiency absorber by using the void plasmon (VP) effect in a Fabry-Perot (FP)-like system, which consists of a perforated metal film and a ground metal plane separated by a dielectric spacer. A hybrid FP/VP resonance mode contributes to the high absorption efficiency. Besides the increased absorption, greatly enhanced localized electric-field intensity at "hot spots" (~ 2284 times) can be achieved. In addition, by varying the thickness of the perforated metal layer and the environmental refractive index, the position of resonance peak can be easily controlled. The proposed absorber can also work as a sensor for detecting the surrounding dielectric constant with the maximum value of the figure of merit (FOM) achieving 3.16 in theory. This work creates an alternative design for high-efficiency absorption devices.

Mechanisms of microRNA-mediated gene regulation in unicellular model alga Chlamydomonas reinhardtii

MicroRNAs are a class of endogenous non-coding RNAs that play a vital role in post-transcriptional gene regulation in eukaryotic cells. In plants and animals, miRNAs are implicated in diverse roles ranging from immunity against viral infections, developmental pathways, molecular pathology of cancer and regulation of protein expression. However, the role of miRNAs in the unicellular model green alga Chlamydomonas reinhardtii remains unclear. The mode of action of miRNA-induced gene silencing in C. reinhardtii is very similar to that of higher eukaryotes, in terms of the activation of the RNA-induced silencing complex and mRNA targeting. Certain studies indicate that destabilization of mRNAs and mRNA turnover could be the major possible functions of miRNAs in eukaryotic algae. Here, we summarize recent findings that have advanced our understanding of miRNA regulatory mechanisms in C. reinhardtii.

Structure Shift of GaN Among Nanowall Network, Nanocolumn, and Compact Film Grown on Si (111) by MBE

Structure shift of GaN nanowall network, nanocolumn, and compact film were successfully obtained on Si (111) by plasma-assisted molecular beam epitaxy (MBE). As is expected, growth of the GaN nanocolumns was observed in N-rich condition on bare Si, and the growth shifted to compact film when the Ga flux was improved. Interestingly, if an aluminum (Al) pre-deposition for 40 s was carried out prior to the GaN growth, GaN grows in the form of the nanowall network. Results show that the pre-deposited Al exits in the form of droplets with typical diameter and height of ~ 80 and ~ 6.7 nm, respectively. A growth model for the nanowall network is proposed and the growth mechanism is discussed. GaN grows in the area without Al droplets while the growth above Al droplets is hindered, resulting in the formation of continuous GaN nanowall network that removes the obstacles of nano-device fabrication.

Metabolic responses to ethanol and butanol in Chlamydomonas reinhardtii

BACKGROUND

Microalgae have been demonstrated to be among the most promising phototrophic species for producing renewable biofuels and chemicals. Ethanol and butanol are clean energy sources with good chemical and physical properties as alternatives to gasoline. However, biosynthesis of these two biofuels has not been achieved due to low tolerance of algal cells to ethanol or butanol.

RESULTS

With an eye to circumventing these problems in the future and engineering the robust alcohol-producing microalgal hosts, we investigated the metabolic responses of the model green alga Chlamydomonas reinhardtii to ethanol and butanol. Using a quantitative proteomics approach with iTRAQ-LC-MS/MS technologies, we detected the levels of 3077 proteins; 827 and 730 of which were differentially regulated by ethanol and butanol, respectively, at three time points. In particular, 41 and 59 proteins were consistently regulated during at least two sampling times. Multiple metabolic processes were affected by ethanol or butanol, and various stress-related proteins, transporters, cytoskeletal proteins, and regulators were induced as the major protection mechanisms against toxicity of the organic solvents. The most highly upregulated butanol response protein was Cre.770 peroxidase.

CONCLUSIONS

The study is the first comprehensive view of the metabolic mechanisms employed by C. reinhardtii to defend against ethanol or butanol toxicity. Moreover, the proteomic analysis provides a resource for investigating potential gene targets for engineering microalgae to achieve efficient biofuel production.

A Hypothesis Testing Based Method for Normalization and Differential Expression Analysis of RNA-Seq Data

Next-generation sequencing technologies have made RNA sequencing (RNA-seq) a popular choice for measuring gene expression level. To reduce the noise of gene expression measures and compare them between several conditions or samples, normalization is an essential step to adjust for varying sample sequencing depths and other unwanted technical effects. In this paper, we develop a novel global scaling normalization method by employing the available knowledge of housekeeping genes. We formulate the problem from the hypothesis testing perspective and find an optimal scaling factor that minimizes the deviation between the empirical and the nominal type I error. Applying our approach to various simulation studies and real examples, we demonstrate that it is more accurate and robust than the state-of-the-art alternatives in detecting differentially expression genes.