Showing papers by "Xiamen University published in 2018"

Minimal information for studies of extracellular vesicles 2018 (MISEV2018) : a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines

Abstract: The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.

Global, regional, and national burden of Parkinson's disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Abstract: Summary Background Neurological disorders are now the leading source of disability globally, and ageing is increasing the burden of neurodegenerative disorders, including Parkinson's disease. We aimed to determine the global burden of Parkinson's disease between 1990 and 2016 to identify trends and to enable appropriate public health, medical, and scientific responses. Methods Through a systematic analysis of epidemiological studies, we estimated global, regional, and country-specific prevalence and years of life lived with disability for Parkinson's disease from 1990 to 2016. We estimated the proportion of mild, moderate, and severe Parkinson's disease on the basis of studies that used the Hoehn and Yahr scale and assigned disability weights to each level. We jointly modelled prevalence and excess mortality risk in a natural history model to derive estimates of deaths due to Parkinson's disease. Death counts were multiplied by values from the Global Burden of Disease study's standard life expectancy to compute years of life lost. Disability-adjusted life-years (DALYs) were computed as the sum of years lived with disability and years of life lost. We also analysed results based on the Socio-demographic Index, a compound measure of income per capita, education, and fertility. Findings In 2016, 6·1 million (95% uncertainty interval [UI] 5·0–7·3) individuals had Parkinson's disease globally, compared with 2·5 million (2·0–3·0) in 1990. This increase was not solely due to increasing numbers of older people, because age-standardised prevalence rates increased by 21·7% (95% UI 18·1–25·3) over the same period (compared with an increase of 74·3%, 95% UI 69·2–79·6, for crude prevalence rates). Parkinson's disease caused 3·2 million (95% UI 2·6–4·0) DALYs and 211 296 deaths (95% UI 167 771–265 160) in 2016. The male-to-female ratios of age-standardised prevalence rates were similar in 2016 (1·40, 95% UI 1·36–1·43) and 1990 (1·37, 1·34–1·40). From 1990 to 2016, age-standardised prevalence, DALY rates, and death rates increased for all global burden of disease regions except for southern Latin America, eastern Europe, and Oceania. In addition, age-standardised DALY rates generally increased across the Socio-demographic Index. Interpretation Over the past generation, the global burden of Parkinson's disease has more than doubled as a result of increasing numbers of older people, with potential contributions from longer disease duration and environmental factors. Demographic and potentially other factors are poised to increase the future burden of Parkinson's disease substantially. Funding Bill & Melinda Gates Foundation.

Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

Abstract: In this paper, we designed an end-to-end spectral–spatial residual network (SSRN) that takes raw 3-D cubes as input data without feature engineering for hyperspectral image classification. In this network, the spectral and spatial residual blocks consecutively learn discriminative features from abundant spectral signatures and spatial contexts in hyperspectral imagery (HSI). The proposed SSRN is a supervised deep learning framework that alleviates the declining-accuracy phenomenon of other deep learning models. Specifically, the residual blocks connect every other 3-D convolutional layer through identity mapping, which facilitates the backpropagation of gradients. Furthermore, we impose batch normalization on every convolutional layer to regularize the learning process and improve the classification performance of trained models. Quantitative and qualitative results demonstrate that the SSRN achieved the state-of-the-art HSI classification accuracy in agricultural, rural–urban, and urban data sets: Indian Pines, Kennedy Space Center, and University of Pavia.

Surface-Enhanced Raman Spectroscopy for Bioanalysis: Reliability and Challenges

Abstract: Surface-enhanced Raman spectroscopy (SERS) inherits the rich chemical fingerprint information on Raman spectroscopy and gains sensitivity by plasmon-enhanced excitation and scattering. In particular, most Raman peaks have a narrow width suitable for multiplex analysis, and the measurements can be conveniently made under ambient and aqueous conditions. These merits make SERS a very promising technique for studying complex biological systems, and SERS has attracted increasing interest in biorelated analysis. However, there are still great challenges that need to be addressed until it can be widely accepted by the biorelated communities, answer interesting biological questions, and solve fatal clinical problems. SERS applications in bioanalysis involve the complex interactions of plasmonic nanomaterials with biological systems and their environments. The reliability becomes the key issue of bioanalytical SERS in order to extract meaningful information from SERS data. This review provides a comprehensive over...

Stable cycling of high-voltage lithium metal batteries in ether electrolytes

Abstract: The key to enabling long-term cycling stability of high-voltage lithium (Li) metal batteries is the development of functional electrolytes that are stable against both Li anodes and high-voltage (above 4 V versus Li/Li+) cathodes. Due to their limited oxidative stability ( 90% over 300 cycles and ~80% over 500 cycles with a charge cut-off voltage of 4.3 V. This study offers a promising approach to enable ether-based electrolytes for high-voltage Li metal battery applications. Ether-based electrolytes offer many advantages compared to other electrolyte systems, but they are not stable in Li metal batteries when operating at high voltages. Here, the authors develop a concentrated ether electrolyte that enables long-term cycling stability of high-voltage Li metal batteries.

Plasma membrane changes during programmed cell deaths

Abstract: Ruptured and intact plasma membranes are classically considered as hallmarks of necrotic and apoptotic cell death, respectively. As such, apoptosis is usually considered a non-inflammatory process while necrosis triggers inflammation. Recent studies on necroptosis and pyroptosis, two types of programmed necrosis, revealed that plasma membrane rupture is mediated by MLKL channels during necroptosis but depends on non-selective gasdermin D (GSDMD) pores during pyroptosis. Importantly, the morphology of dying cells executed by MLKL channels can be distinguished from that executed by GSDMD pores. Interestingly, it was found recently that secondary necrosis of apoptotic cells, a previously believed non-regulated form of cell lysis that occurs after apoptosis, can be programmed and executed by plasma membrane pore formation like that of pyroptosis. In addition, pyroptosis is associated with pyroptotic bodies, which have some similarities to apoptotic bodies. Therefore, different cell death programs induce distinctive reshuffling processes of the plasma membrane. Given the fact that the nature of released intracellular contents plays a crucial role in dying/dead cell-induced immunogenicity, not only membrane rupture or integrity but also the nature of plasma membrane breakdown would determine the fate of a cell as well as its ability to elicit an immune response. In this review, we will discuss recent advances in the field of apoptosis, necroptosis and pyroptosis, with an emphasis on the mechanisms underlying plasma membrane changes observed on dying cells and their implication in cell death-elicited immunogenicity.

Atomic-level insight into super-efficient electrocatalytic oxygen evolution on iron and vanadium co-doped nickel (oxy)hydroxide.

Abstract: It is of great importance to understand the origin of high oxygen-evolving activity of state-of-the-art multimetal oxides/(oxy)hydroxides at atomic level. Herein we report an evident improvement of oxygen evolution reaction activity via incorporating iron and vanadium into nickel hydroxide lattices. X-ray photoelectron/absorption spectroscopies reveal the synergistic interaction between iron/vanadium dopants and nickel in the host matrix, which subtly modulates local coordination environments and electronic structures of the iron/vanadium/nickel cations. Further, in-situ X-ray absorption spectroscopic analyses manifest contraction of metal-oxygen bond lengths in the activated catalyst, with a short vanadium-oxygen bond distance. Density functional theory calculations indicate that the vanadium site of the iron/vanadium co-doped nickel (oxy)hydroxide gives near-optimal binding energies of oxygen evolution reaction intermediates and has lower overpotential compared with nickel and iron sites. These findings suggest that the doped vanadium with distorted geometric and disturbed electronic structures makes crucial contribution to high activity of the trimetallic catalyst.

Down-Conversion Nitride Materials for Solid State Lighting: Recent Advances and Perspectives.

Abstract: Advances in solid state white lighting technologies witness the explosive development of phosphor materials (down-conversion luminescent materials). A large amount of evidence has demonstrated the revolutionary role of the emerging nitride phosphors in producing superior white light-emitting diodes for lighting and display applications. The structural and compositional versatility together with the unique local coordination environments enable nitride materials to have compelling luminescent properties such as abundant emission colors, controllable photoluminescence spectra, high conversion efficiency, and small thermal quenching/degradation. Here, we summarize the state-of-art progress on this novel family of luminescent materials and discuss the topics of materials discovery, crystal chemistry, structure-related luminescence, temperature-dependent luminescence, and spectral tailoring. We also overview different types of nitride phosphors and their applications in solid state lighting, including general ...

Generalizing A Person Retrieval Model Hetero- and Homogeneously

Abstract: Person re-identification (re-ID) poses unique challenges for unsupervised domain adaptation (UDA) in that classes in the source and target sets (domains) are entirely different and that image variations are largely caused by cameras. Given a labeled source training set and an unlabeled target training set, we aim to improve the generalization ability of re-ID models on the target testing set. To this end, we introduce a Hetero-Homogeneous Learning (HHL) method. Our method enforces two properties simultaneously: (1) camera invariance, learned via positive pairs formed by unlabeled target images and their camera style transferred counterparts; (2) domain connectedness, by regarding source/target images as negative matching pairs to the target/source images. The first property is implemented by homogeneous learning because training pairs are collected from the same domain. The second property is achieved by heterogeneous learning because we sample training pairs from both the source and target domains. On Market-1501, DukeMTMC-reID and CUHK03, we show that the two properties contribute indispensably and that very competitive re-ID UDA accuracy is achieved. Code is available at: https://github.com/zhunzhong07/HHL.

Predicting Diabetes Mellitus With Machine Learning Techniques.

Abstract: Diabetes mellitus is a chronic disease characterized by hyperglycemia. It may cause many complications. According to the growing morbidity in recent years, in 2040, the world's diabetic patients will reach 642 million, which means that one of the ten adults in the future is suffering from diabetes. There is no doubt that this alarming figure needs great attention. With the rapid development of machine learning, machine learning has been applied to many aspects of medical health. In this study, we used decision tree, random forest and neural network to predict diabetes mellitus. The dataset is the hospital physical examination data in Luzhou, China. It contains 14 attributes. In this study, five-fold cross validation was used to examine the models. In order to verity the universal applicability of the methods, we chose some methods that have the better performance to conduct independent test experiments. We randomly selected 68994 healthy people and diabetic patients' data, respectively as training set. Due to the data unbalance, we randomly extracted 5 times data. And the result is the average of these five experiments. In this study, we used principal component analysis (PCA) and minimum redundancy maximum relevance (mRMR) to reduce the dimensionality. The results showed that prediction with random forest could reach the highest accuracy (ACC = 0.8084) when all the attributes were used.

Weighted Res-UNet for High-Quality Retina Vessel Segmentation

Abstract: Retinal vessel segmentation is a key step towards the accurate visualization, diagnosis, early treatment and surgery planning of ocular diseases. Recently, deep learning based retinal vessel segmentation methods have reached the state-of-the-art performance. Due to the extreme variations in the morphology of the vessels against the noisy background, these methods still have issues of dealing with small thin vessels, low discriminative ability at the optic disk area, etc. In this paper, we proposed a U-Net-like model with the weighted attention mechanism and the skip connection scheme for addressing these issues. Experimental results on two benchmark datasets demonstrate the effectiveness of the proposed methods.

Mini-LED and Micro-LED: Promising Candidates for the Next Generation Display Technology

Abstract: Displays based on inorganic light-emitting diodes (LED) are considered as the most promising one among the display technologies for the next-generation The chip for LED display bears similar features to those currently in use for general lighting, but it size is shrunk to below 200 microns Thus, the advantages of high efficiency and long life span of conventional LED chips are inherited by miniaturized ones As the size gets smaller, the resolution enhances, but at the expense of elevating the complexity of fabrication In this review, we introduce two sorts of inorganic LED displays, namely relatively large and small varieties The mini-LEDs with chip sizes ranging from 100 to 200 μm have already been commercialized for backlight sources in consumer electronics applications The realized local diming can greatly improve the contrast ratio at relatively low energy consumptions The micro-LEDs with chip size less than 100 μm, still remain in the laboratory The full-color solution, one of the key technologies along with its three main components, red, green, and blue chips, as well color conversion, and optical lens synthesis, are introduced in detail Moreover, this review provides an account for contemporary technologies as well as a clear view of inorganic and miniaturized LED displays for the display community

Guidelines for Diagnosis and Treatment of Primary Liver Cancer in China (2017 Edition).

Abstract: Background Hepatocellular carcinoma (HCC) (about 85–90% of primary liver cancer) is particularly prevalent in China because of the high prevalence of chronic hepatitis B infection. HCC is the fourth most common malignancy and the third leading cause of tumor-related deaths in China. It poses a significant threat to the life and health of Chinese people.

NiCo Alloy Nanoparticles Decorated on N-Doped Carbon Nanofibers as Highly Active and Durable Oxygen Electrocatalyst

Abstract: The exploring of catalysts with high-efficiency and low-cost for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is one of the key issues for many renewable energy systems including fuel cells, metal–air batteries, and water splitting. Despite several decades pursuing, bifunctional oxygen catalysts with high catalytic performance at low-cost, especially the one that could be easily scaled up for mass production are still missing and highly desired. Herein, a hybrid catalyst with NiCo alloy nanoparticles decorated on N-doped carbon nanofibers is synthesized by a facile electrospinning method and postcalcination treatment. The hybrid catalyst NiCo@N-C 2 exhibits outstanding ORR and OER catalytic performances, which is even surprisingly superior to the commercial Pt/C and RuO2 catalysts, respectively. The synergetic effects between alloy nanoparticles and the N-doped carbon fiber are considered as the main contributions for the excellent catalytic activities, which include decreasing the intrinsic and charge transfer resistances, increasing CC, graphitic-N/pyridinic-N contents in the hybrid catalyst. This work opens up a new way to fabricate high-efficient, low-cost oxygen catalysts with high production.

Many analysts, one dataset: Making transparent how variations in analytical choices affect results

Abstract: Twenty-nine teams involving 61 analysts used the same data set to address the same research question: whether soccer referees are more likely to give red cards to dark-skin-toned players than to light-skin-toned players. Analytic approaches varied widely across the teams, and the estimated effect sizes ranged from 0.89 to 2.93 (Mdn = 1.31) in odds-ratio units. Twenty teams (69%) found a statistically significant positive effect, and 9 teams (31%) did not observe a significant relationship. Overall, the 29 different analyses used 21 unique combinations of covariates. Neither analysts’ prior beliefs about the effect of interest nor their level of expertise readily explained the variation in the outcomes of the analyses. Peer ratings of the quality of the analyses also did not account for the variability. These findings suggest that significant variation in the results of analyses of complex data may be difficult to avoid, even by experts with honest intentions. Crowdsourcing data analysis, a strategy in which numerous research teams are recruited to simultaneously investigate the same research question, makes transparent how defensible, yet subjective, analytic choices influence research results.

Camera Style Adaptation for Person Re-identification

Abstract: Being a cross-camera retrieval task, person re-identification suffers from image style variations caused by different cameras. The art implicitly addresses this problem by learning a camera-invariant descriptor subspace. In this paper, we explicitly consider this challenge by introducing camera style (CamStyle) adaptation. CamStyle can serve as a data augmentation approach that smooths the camera style disparities. Specifically, with CycleGAN, labeled training images can be style-transferred to each camera, and, along with the original training samples, form the augmented training set. This method, while increasing data diversity against over-fitting, also incurs a considerable level of noise. In the effort to alleviate the impact of noise, the label smooth regularization (LSR) is adopted. The vanilla version of our method (without LSR) performs reasonably well on few-camera systems in which over-fitting often occurs. With LSR, we demonstrate consistent improvement in all systems regardless of the extent of over-fitting. We also report competitive accuracy compared with the state of the art. Code is available at: https://github.com/zhunzhong07/CamStyle

Phase-separation mechanism for C-terminal hyperphosphorylation of RNA polymerase II.

Abstract: Hyperphosphorylation of the C-terminal domain (CTD) of the RPB1 subunit of human RNA polymerase (Pol) II is essential for transcriptional elongation and mRNA processing1–3. The CTD contains 52 heptapeptide repeats of the consensus sequence YSPTSPS. The highly repetitive nature and abundant possible phosphorylation sites of the CTD exert special constraints on the kinases that catalyse its hyperphosphorylation. Positive transcription elongation factor b (P-TEFb)—which consists of CDK9 and cyclin T1—is known to hyperphosphorylate the CTD and negative elongation factors to stimulate Pol II elongation1,4,5. The sequence determinant on P-TEFb that facilitates this action is currently unknown. Here we identify a histidine-rich domain in cyclin T1 that promotes the hyperphosphorylation of the CTD and stimulation of transcription by CDK9. The histidine-rich domain markedly enhances the binding of P-TEFb to the CTD and functional engagement with target genes in cells. In addition to cyclin T1, at least one other kinase—DYRK1A 6 —also uses a histidine-rich domain to target and hyperphosphorylate the CTD. As a low-complexity domain, the histidine-rich domain also promotes the formation of phase-separated liquid droplets in vitro, and the localization of P-TEFb to nuclear speckles that display dynamic liquid properties and are sensitive to the disruption of weak hydrophobic interactions. The CTD—which in isolation does not phase separate, despite being a low-complexity domain—is trapped within the cyclin T1 droplets, and this process is enhanced upon pre-phosphorylation by CDK7 of transcription initiation factor TFIIH1–3. By using multivalent interactions to create a phase-separated functional compartment, the histidine-rich domain in kinases targets the CTD into this environment to ensure hyperphosphorylation and efficient elongation of Pol II. The histidine-rich domain of cyclin T1 promotes phase separation into liquid droplets, which facilitates the hyperphosphorylation of the C-terminal domain repeats of RNA polymerase II.

Oridonin is a covalent NLRP3 inhibitor with strong anti-inflammasome activity.

Abstract: Oridonin (Ori) is the major active ingredient of the traditional Chinese medicinal herb Rabdosia rubescens and has anti-inflammatory activity, but the target of Ori remains unknown. NLRP3 is a central component of NLRP3 inflammasome and has been involved in a wide variety of chronic inflammation-driven human diseases. Here, we show that Ori is a specific and covalent inhibitor for NLRP3 inflammasome. Ori forms a covalent bond with the cysteine 279 of NLRP3 in NACHT domain to block the interaction between NLRP3 and NEK7, thereby inhibiting NLRP3 inflammasome assembly and activation. Importantly, Ori has both preventive or therapeutic effects on mouse models of peritonitis, gouty arthritis and type 2 diabetes, via inhibition of NLRP3 activation. Our results thus identify NLRP3 as the direct target of Ori for mediating Ori’s anti-inflammatory activity. Ori could serve as a lead for developing new therapeutics against NLRP3-driven diseases.

Fenton-Reaction-Acceleratable Magnetic Nanoparticles for Ferroptosis Therapy of Orthotopic Brain Tumors.

Abstract: Cancer is one of the leading causes of morbidity and mortality in the world, but more cancer therapies are needed to complement existing regimens due to problems of existing cancer therapies. Herein, we term ferroptosis therapy (FT) as a form of cancer therapy and hypothesize that the FT efficacy can be significantly improved via accelerating the Fenton reaction by simultaneously increasing the local concentrations of all reactants (Fe2+, Fe3+, and H2O2) in cancer cells. Thus, Fenton-reaction-acceleratable magnetic nanoparticles, i.e., cisplatin (CDDP)-loaded Fe3O4/Gd2O3 hybrid nanoparticles with conjugation of lactoferrin (LF) and RGD dimer (RGD2) (FeGd-HN@Pt@LF/RGD2), were exploited in this study for FT of orthotopic brain tumors. FeGd-HN@Pt@LF/RGD2 nanoparticles were able to cross the blood–brain barrier because of its small size (6.6 nm) and LF-receptor-mediated transcytosis. FeGd-HN@Pt@LF/RGD2 can be internalized into cancer cells by integrin αvβ3-mediated endocytosis and then release Fe2+, Fe3+, and...

Surface Chemistry of Atomically Precise Coinage-Metal Nanoclusters: From Structural Control to Surface Reactivity and Catalysis.

Abstract: ConspectusA comprehensive understanding of chemical bonding and reactions at the surface of nanomaterials is of great importance in the rational design of their functional properties and applicatio...

Interfacial Interaction between FeOOH and Ni–Fe LDH to Modulate the Local Electronic Structure for Enhanced OER Electrocatalysis

Abstract: Toward the pursuit of high-performance Ni2+/Co2+/Fe3+-relevant oxygen evolution reaction (OER) electrocatalysts, the modulation of local electronic structure of the active metal sites provides the fundamental motif, which could be achieved either through direct modifications of local chemical environment or interfacial interaction with a second metal substrate which possesses high electronegativity (typically noble metal Au). Herein, we report that the local electronic structure of Ni–Fe layered double hydroxide (LDH) could be favorably modulated through strong interfacial interactions with FeOOH nanoparticles (NPs). The biphasic and multiscale composites FeOOH/LDH demonstrated an increasingly pronounced synergy effect for OER catalysis when the average size of FeOOH NPs decreases from 18.0 to 2.0 nm. Particularly, the composite with average size of FeOOH NPs of 2.0 nm exhibited an overpotential of 174 mV at 10 mA cm–2 and a tafel slope of 27 mV dec–1 in 1.0 M KOH, outmatching all the noble and non-noble ...

Solar energy-driven lignin-first approach to full utilization of lignocellulosic biomass under mild conditions

Abstract: The lignin-first concept offers an opportunity to utilize the entire lignocellulosic biomass efficiently However, current conversion strategies rely on high-temperature hydrogenolysis by supported metal catalysts, leading to low-functionalized products or difficulty in separation of solid catalyst from cellulose/hemicellulose Here, we report the fractionation and valorization of lignocellulose via solar energy-driven conversion of native lignin at room temperature We found that cadmium sulfide quantum dots not only catalyse the cleavage of β-O-4 bonds in lignin models quantitatively but also are efficient for the conversion of native lignin within biomass into functionalized aromatics under visible light, while cellulose/hemicellulose remain almost intact Further, the colloidal character of quantum dots enables their facile separation and recycling by a reversible aggregation–colloidization strategy The β-O-4 bond in lignin is cleaved by an electron–hole coupled photoredox mechanism based on a Cα radical intermediate, in which both photogenerated electrons and holes participate in the reaction Lignin-first approaches, which prioritize lignin upgrade over cellulose, can open the way to full biomass valorization, but are still hampered by the need of harsh reaction conditions and difficulties in catalyst recovery Now, a photocatalytic strategy based on the use of cadmium sulfide quantum dots is reported that overcomes these limitations

Efficient, Hysteresis-Free, and Stable Perovskite Solar Cells with ZnO as Electron-Transport Layer: Effect of Surface Passivation.

Abstract: The power conversion efficiency of perovskite solar cells (PSCs) has ascended from 3.8% to 22.1% in recent years. ZnO has been well-documented as an excellent electron-transport material. However, the poor chemical compatibility between ZnO and organo-metal halide perovskite makes it highly challenging to obtain highly efficient and stable PSCs using ZnO as the electron-transport layer. It is demonstrated in this work that the surface passivation of ZnO by a thin layer of MgO and protonated ethanolamine (EA) readily makes ZnO as a very promising electron-transporting material for creating hysteresis-free, efficient, and stable PSCs. Systematic studies in this work reveal several important roles of the modification: (i) MgO inhibits the interfacial charge recombination, and thus enhances cell performance and stability; (ii) the protonated EA promotes the effective electron transport from perovskite to ZnO, further fully eliminating PSCs hysteresis; (iii) the modification makes ZnO compatible with perovskite, nicely resolving the instability of ZnO/perovskite interface. With all these findings, PSCs with the best efficiency up to 21.1% and no hysteresis are successfully fabricated. PSCs stable in air for more than 300 h are achieved when graphene is used to further encapsulate the cells.

Distinct patterns and processes of abundant and rare eukaryotic plankton communities following a reservoir cyanobacterial bloom.

Abstract: Plankton communities normally consist of few abundant and many rare species, yet little is known about the ecological role of rare planktonic eukaryotes. Here we used a 18S ribosomal DNA sequencing approach to investigate the dynamics of rare planktonic eukaryotes, and to explore the co-occurrence patterns of abundant and rare eukaryotic plankton in a subtropical reservoir following a cyanobacterial bloom event. Our results showed that the bloom event significantly altered the eukaryotic plankton community composition and rare plankton diversity without affecting the diversity of abundant plankton. The similarities of both abundant and rare eukaryotic plankton subcommunities significantly declined with the increase in time-lag, but stronger temporal turnover was observed in rare taxa. Further, species turnover of both subcommunities explained a higher percentage of the community variation than species richness. Both deterministic and stochastic processes significantly influenced eukaryotic plankton community assembly, and the stochastic pattern (e.g., ecological drift) was particularly pronounced for rare taxa. Co-occurrence network analysis revealed that keystone taxa mainly belonged to rare species, which may play fundamental roles in network persistence. Importantly, covariations between rare and non-rare taxa were predominantly positive, implying multispecies cooperation might contribute to the stability and resilience of the microbial community. Overall, these findings expand current understanding of the ecological mechanisms and microbial interactions underlying plankton dynamics in changing aquatic ecosystems.