Showing papers in "Scientific Reports in 2016"

Ultrastructural Characterization of the Lower Motor System in a Mouse Model of Krabbe Disease.

Abstract: Krabbe disease (KD) is a neurodegenerative disorder caused by the lack of β- galactosylceramidase enzymatic activity and by widespread accumulation of the cytotoxic galactosyl-sphingosine in neuronal, myelinating and endothelial cells. Despite the wide use of Twitcher mice as experimental model for KD, the ultrastructure of this model is partial and mainly addressing peripheral nerves. More details are requested to elucidate the basis of the motor defects, which are the first to appear during KD onset. Here we use transmission electron microscopy (TEM) to focus on the alterations produced by KD in the lower motor system at postnatal day 15 (P15), a nearly asymptomatic stage, and in the juvenile P30 mouse. We find mild effects on motorneuron soma, severe ones on sciatic nerves and very severe effects on nerve terminals and neuromuscular junctions at P30, with peripheral damage being already detectable at P15. Finally, we find that the gastrocnemius muscle undergoes atrophy and structural changes that are independent of denervation at P15. Our data further characterize the ultrastructural analysis of the KD mouse model, and support recent theories of a dying-back mechanism for neuronal degeneration, which is independent of demyelination.

MIMIC-III, a freely accessible critical care database

Abstract: MIMIC-III ('Medical Information Mart for Intensive Care') is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital. Data includes vital signs, medications, laboratory measurements, observations and notes charted by care providers, fluid balance, procedure codes, diagnostic codes, imaging reports, hospital length of stay, survival data, and more. The database supports applications including academic and industrial research, quality improvement initiatives, and higher education coursework.

Correction: Corrigendum: The Serum Profile of Hypercytokinemia Factors Identified in H7N9-Infected Patients can Predict Fatal Outcomes

Abstract: Scientific Reports 5: Article number: 10942; published online: 01 June 2015; updated: 23 February 2016 This Article contains typographical errors in Table 2 where ‘Week 2 (N = 32)’ was incorrectly given as ‘Week (N = 2)’.

Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

Abstract: Secondary use of electronic health records (EHRs) promises to advance clinical research and better inform clinical decision making. Challenges in summarizing and representing patient data prevent widespread practice of predictive modeling using EHRs. Here we present a novel unsupervised deep feature learning method to derive a general-purpose patient representation from EHR data that facilitates clinical predictive modeling. In particular, a three-layer stack of denoising autoencoders was used to capture hierarchical regularities and dependencies in the aggregated EHRs of about 700,000 patients from the Mount Sinai data warehouse. The result is a representation we name “deep patient”. We evaluated this representation as broadly predictive of health states by assessing the probability of patients to develop various diseases. We performed evaluation using 76,214 test patients comprising 78 diseases from diverse clinical domains and temporal windows. Our results significantly outperformed those achieved using representations based on raw EHR data and alternative feature learning strategies. Prediction performance for severe diabetes, schizophrenia, and various cancers were among the top performing. These findings indicate that deep learning applied to EHRs can derive patient representations that offer improved clinical predictions, and could provide a machine learning framework for augmenting clinical decision systems.

Correction: Corrigendum: Assembling Composite Dermal Papilla Spheres with Adipose-derived Stem Cells to Enhance Hair Follicle Induction

Abstract: Scientific Reports 6: Article number: 26436; published online: 23 May 2016; updated: 14 November 2016 The original version of this Article contained errors in the affiliations. “Department of Cell Biology and Anatomy, National Cheng Kung University, Tainan, 701, Taiwan” was incomplete, and now reads:

Formation of oxygen vacancies and Ti 3+ state in TiO 2 thin film and enhanced optical properties by air plasma treatment

Abstract: This is the first time we report that simply air plasma treatment can also enhances the optical absorbance and absorption region of titanium oxide (TiO2) films, while keeping them transparent. TiO2 thin films having moderate doping of Fe and Co exhibit significant enhancement in the aforementioned optical properties upon air plasma treatment. The moderate doping could facilitate the formation of charge trap centers or avoid the formation of charge recombination centers. Variation in surface species viz. Ti3+, Ti4+, O2−, oxygen vacancies, OH group and optical properties was studied using X-ray photon spectroscopy (XPS) and UV-Vis spectroscopy. The air plasma treatment caused enhanced optical absorbance and optical absorption region as revealed by the formation of Ti3+ and oxygen vacancies in the band gap of TiO2 films. The samples were treated in plasma with varying treatment time from 0 to 60 seconds. With the increasing treatment time, Ti3+ and oxygen vacancies increased in the Fe and Co doped TiO2 films leading to increased absorbance; however, the increase in optical absorption region/red shift (from 3.22 to 3.00 eV) was observed in Fe doped TiO2 films, on the contrary Co doped TiO2 films exhibited blue shift (from 3.36 to 3.62 eV) due to Burstein Moss shift.

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis

Abstract: Pathologists face a substantial increase in workload and complexity of histopathologic cancer diagnosis due to the advent of personalized medicine. Therefore, diagnostic protocols have to focus equally on efficiency and accuracy. In this paper we introduce 'deep learning' as a technique to improve the objectivity and efficiency of histopathologic slide analysis. Through two examples, prostate cancer identification in biopsy specimens and breast cancer metastasis detection in sentinel lymph nodes, we show the potential of this new methodology to reduce the workload for pathologists, while at the same time increasing objectivity of diagnoses. We found that all slides containing prostate cancer and micro- and macro-metastases of breast cancer could be identified automatically while 30-40% of the slides containing benign and normal tissue could be excluded without the use of any additional immunohistochemical markers or human intervention. We conclude that 'deep learning' holds great promise to improve the efficacy of prostate cancer diagnosis and breast cancer staging.

Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding

Abstract: With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m-bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m-bonacci sequences to detect eavesdropping. Meanwhile, we encode m-bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications.

Correction: Corrigendum: Synchronized age-related gene expression changes across multiple tissues in human and the link to complex diseases

Abstract: Aging is one of the most important biological processes and is a known risk factor for many age-related diseases in human. Studying age-related transcriptomic changes in tissues across the whole body can provide valuable information for a holistic understanding of this fundamental process. In this work, we catalogue age-related gene expression changes in nine tissues from nearly two hundred individuals collected by the Genotype-Tissue Expression (GTEx) project. In general, we find the aging gene expression signatures are very tissue specific. However, enrichment for some well-known aging components such as mitochondria biology is observed in many tissues. Different levels of cross-tissue synchronization of age-related gene expression changes are observed, and some essential tissues (e.g., heart and lung) show much stronger “co-aging” than other tissues based on a principal component analysis. The aging gene signatures and complex disease genes show a complex overlapping pattern and only in some cases, we see that they are significantly overlapped in the tissues affected by the corresponding diseases. In summary, our analyses provide novel insights to the co-regulation of age-related gene expression in multiple tissues; it also presents a tissue-specific view of the link between aging and age-related diseases.

Individual Differences in Rhythmic Cortical Entrainment Correlate with Predictive Behavior in Sensorimotor Synchronization

Abstract: The current study aims at characterizing the mechanisms that allow humans to entrain the mind and body to incoming rhythmic sensory inputs in real time. We addressed this unresolved issue by examining the relationship between covert neural processes and overt behavior in the context of musical rhythm. We measured temporal prediction abilities, sensorimotor synchronization accuracy and neural entrainment to auditory rhythms as captured using an EEG frequency-tagging approach. Importantly, movement synchronization accuracy with a rhythmic beat could be explained by the amplitude of neural activity selectively locked with the beat period when listening to the rhythmic inputs. Furthermore, stronger endogenous neural entrainment at the beat frequency was associated with superior temporal prediction abilities. Together, these results reveal a direct link between cortical and behavioral measures of rhythmic entrainment, thus providing evidence that frequency-tagged brain activity has functional relevance for beat perception and synchronization.

Human gut colonisation may be initiated in utero by distinct microbial communities in the placenta and amniotic fluid

Abstract: Interaction with intestinal microbes in infancy has a profound impact on health and disease in later life through programming of immune and metabolic pathways. We collected maternal faeces, placenta, amniotic fluid, colostrum, meconium and infant faeces samples from 15 mother-infant pairs in an effort to rigorously investigate prenatal and neonatal microbial transfer and gut colonisation. To ensure sterile sampling, only deliveries at full term by elective caesarean section were studied. Microbiota composition and activity assessment by conventional bacterial culture, 16S rRNA gene pyrosequencing, quantitative PCR, and denaturing gradient gel electrophoresis revealed that the placenta and amniotic fluid harbour a distinct microbiota characterised by low richness, low diversity and the predominance of Proteobacteria. Shared features between the microbiota detected in the placenta and amniotic fluid and in infant meconium suggest microbial transfer at the foeto-maternal interface. At the age of 3–4 days, the infant gut microbiota composition begins to resemble that detected in colostrum. Based on these data, we propose that the stepwise microbial gut colonisation process may be initiated already prenatally by a distinct microbiota in the placenta and amniotic fluid. The link between the mother and the offspring is continued after birth by microbes present in breast milk.

3D tumor spheroid models for in vitro therapeutic screening: a systematic approach to enhance the biological relevance of data obtained

Abstract: The potential of a spheroid tumor model composed of cells in different proliferative and metabolic states for the development of new anticancer strategies has been amply demonstrated. However, there is little or no information in the literature on the problems of reproducibility of data originating from experiments using 3D models. Our analyses, carried out using a novel open source software capable of performing an automatic image analysis of 3D tumor colonies, showed that a number of morphology parameters affect the response of large spheroids to treatment. In particular, we found that both spheroid volume and shape may be a source of variability. We also compared some commercially available viability assays specifically designed for 3D models. In conclusion, our data indicate the need for a pre-selection of tumor spheroids of homogeneous volume and shape to reduce data variability to a minimum before use in a cytotoxicity test. In addition, we identified and validated a cytotoxicity test capable of providing meaningful data on the damage induced in large tumor spheroids of up to diameter in 650 μm by different kinds of treatments.

Correction: Corrigendum: Selective inhibition of EZH2 by ZLD1039 blocks H3K27methylation and leads to potent anti-tumor activity in breast cancer

Abstract: Scientific Reports 6: Article number: 20864; Published online: 12 February 2016; Updated: 29 April 2016 This Article contains typographical errors. In the Results section under subheading ‘Impact of ZLD1039 on breast cancer cell growth’, “Among the cell lines, MCF-7 and ZR-75-1 were the most sensitive to ZLD1039 with IC50 values of 0.

Three-dimensional printing of continuous-fiber composites by in-nozzle impregnation.

Abstract: We have developed a method for the three-dimensional (3D) printing of continuous fiber-reinforced thermoplastics based on fused-deposition modeling. The technique enables direct 3D fabrication without the use of molds and may become the standard next-generation composite fabrication methodology. A thermoplastic filament and continuous fibers were separately supplied to the 3D printer and the fibers were impregnated with the filament within the heated nozzle of the printer immediately before printing. Polylactic acid was used as the matrix while carbon fibers, or twisted yarns of natural jute fibers, were used as the reinforcements. The thermoplastics reinforced with unidirectional jute fibers were examples of plant-sourced composites; those reinforced with unidirectional carbon fiber showed mechanical properties superior to those of both the jute-reinforced and unreinforced thermoplastics. Continuous fiber reinforcement improved the tensile strength of the printed composites relative to the values shown by conventional 3D-printed polymer-based composites.

Cells release subpopulations of exosomes with distinct molecular and biological properties

Abstract: Cells release nano-sized membrane vesicles that are involved in intercellular communication by transferring biological information between cells. It is generally accepted that cells release at least three types of extracellular vesicles (EVs): apoptotic bodies, microvesicles and exosomes. While a wide range of putative biological functions have been attributed to exosomes, they are assumed to represent a homogenous population of EVs. We hypothesized the existence of subpopulations of exosomes with defined molecular compositions and biological properties. Density gradient centrifugation of isolated exosomes revealed the presence of two distinct subpopulations, differing in biophysical properties and their proteomic and RNA repertoires. Interestingly, the subpopulations mediated differential effects on the gene expression programmes in recipient cells. In conclusion, we demonstrate that cells release distinct exosome subpopulations with unique compositions that elicit differential effects on recipient cells. Further dissection of exosome heterogeneity will advance our understanding of exosomal biology in health and disease and accelerate the development of exosome-based diagnostics and therapeutics.

Multimaterial 4D Printing with Tailorable Shape Memory Polymers

Abstract: We present a new 4D printing approach that can create high resolution (up to a few microns), multimaterial shape memory polymer (SMP) architectures. The approach is based on high resolution projection microstereolithography (PμSL) and uses a family of photo-curable methacrylate based copolymer networks. We designed the constituents and compositions to exhibit desired thermomechanical behavior (including rubbery modulus, glass transition temperature and failure strain which is more than 300% and larger than any existing printable materials) to enable controlled shape memory behavior. We used a high resolution, high contrast digital micro display to ensure high resolution of photo-curing methacrylate based SMPs that requires higher exposure energy than more common acrylate based polymers. An automated material exchange process enables the manufacture of 3D composite architectures from multiple photo-curable SMPs. In order to understand the behavior of the 3D composite microarchitectures, we carry out high fidelity computational simulations of their complex nonlinear, time-dependent behavior and study important design considerations including local deformation, shape fixity and free recovery rate. Simulations are in good agreement with experiments for a series of single and multimaterial components and can be used to facilitate the design of SMP 3D structures.

Microplastics profile along the Rhine River.

Abstract: Microplastics result from fragmentation of plastic debris or are released to the environment as pre-production pellets or components of consumer and industrial products. In the oceans, they contribute to the 'great garbage patches'. They are ingested by many organisms, from protozoa to baleen whales, and pose a threat to the aquatic fauna. Although as much as 80% of marine debris originates from land, little attention was given to the role of rivers as debris pathways to the sea. Worldwide, not a single great river has yet been studied for the surface microplastics load over its length. We report the abundance and composition of microplastics at the surface of the Rhine, one of the largest European rivers. Measurements were made at 11 locations over a stretch of 820 km. Microplastics were found in all samples, with 892,777 particles km (-2) on average. In the Rhine-Ruhr metropolitan area, a peak concentration of 3.9 million particles km (-2) was measured. Microplastics concentrations were diverse along and across the river, reflecting various sources and sinks such as waste water treatment plants, tributaries and weirs. Measures should be implemented to avoid and reduce the pollution with anthropogenic litter in aquatic ecosystems.

High-Entropy Metal Diborides: A New Class of High-Entropy Materials and a New Type of Ultrahigh Temperature Ceramics.

Abstract: Seven equimolar, five-component, metal diborides were fabricated via high-energy ball milling and spark plasma sintering. Six of them, including (Hf0.2Zr0.2Ta0.2Nb0.2Ti0.2)B2, (Hf0.2Zr0.2Ta0.2Mo0.2Ti0.2)B2, (Hf0.2Zr0.2Mo0.2Nb0.2Ti0.2)B2, (Hf0.2Mo0.2Ta0.2Nb0.2Ti0.2)B2, (Mo0.2Zr0.2Ta0.2Nb0.2Ti0.2)B2, and (Hf0.2Zr0.2Ta0.2Cr0.2Ti0.2)B2, possess virtually one solid-solution boride phase of the hexagonal AlB2 structure. Revised Hume-Rothery size-difference factors are used to rationalize the formation of high-entropy solid solutions in these metal diborides. Greater than 92% of the theoretical densities have been generally achieved with largely uniform compositions from nanoscale to microscale. Aberration-corrected scanning transmission electron microscopy (AC STEM), with high-angle annular dark-field and annular bright-field (HAADF and ABF) imaging and nanoscale compositional mapping, has been conducted to confirm the formation of 2-D high-entropy metal layers, separated by rigid 2-D boron nets, without any detectable layered segregation along the c-axis. These materials represent a new type of ultra-high temperature ceramics (UHTCs) as well as a new class of high-entropy materials, which not only exemplify the first high-entropy non-oxide ceramics (borides) fabricated but also possess a unique non-cubic (hexagonal) and layered (quasi-2D) high-entropy crystal structure that markedly differs from all those reported in prior studies. Initial property assessments show that both the hardness and the oxidation resistance of these high-entropy metal diborides are generally higher/better than the average performances of five individual metal diborides made by identical fabrication processing.

Multiple sclerosis patients have a distinct gut microbiota compared to healthy controls

Abstract: Multiple sclerosis (MS) is an immune-mediated disease, the etiology of which involves both genetic and environmental factors. The exact nature of the environmental factors responsible for predisposition to MS remains elusive; however, it’s hypothesized that gastrointestinal microbiota might play an important role in pathogenesis of MS. Therefore, this study was designed to investigate whether gut microbiota are altered in MS by comparing the fecal microbiota in relapsing remitting MS (RRMS) (n = 31) patients to that of age- and gender-matched healthy controls (n = 36). Phylotype profiles of the gut microbial populations were generated using hypervariable tag sequencing of the V3–V5 region of the 16S ribosomal RNA gene. Detailed fecal microbiome analyses revealed that MS patients had distinct microbial community profile compared to healthy controls. We observed an increased abundance of Psuedomonas, Mycoplana, Haemophilus, Blautia, and Dorea genera in MS patients, whereas control group showed increased abundance of Parabacteroides, Adlercreutzia and Prevotella genera. Thus our study is consistent with the hypothesis that MS patients have gut microbial dysbiosis and further study is needed to better understand their role in the etiopathogenesis of MS.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

Abstract: This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

Abstract: The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.

Patterns of metastasis in colon and rectal cancer

Abstract: Investigating epidemiology of metastatic colon and rectal cancer is challenging, because cancer registries seldom record metastatic sites. We used a population based approach to assess metastatic spread in colon and rectal cancers. 49,096 patients with colorectal cancer were identified from the nationwide Swedish Cancer Registry. Metastatic sites were identified from the National Patient Register and Cause of Death Register. Rectal cancer more frequently metastasized into thoracic organs (OR = 2.4) and the nervous system (1.5) and less frequently within the peritoneum (0.3). Mucinous and signet ring adenocarcinomas more frequently metastasized within the peritoneum compared with generic adenocarcinoma (3.8 [colon]/3.2 [rectum]), and less frequently into the liver (0.5/0.6). Lung metastases occurred frequently together with nervous system metastases, whereas peritoneal metastases were often listed with ovarian and pleural metastases. Thoracic metastases are almost as common as liver metastases in rectal cancer patients with a low stage at diagnosis. In colorectal cancer patients with solitary metastases the survival differed between 5 and 19 months depending on T or N stage. Metastatic patterns differ notably between colon and rectal cancers. This knowledge should help clinicians to identify patients in need for extra surveillance and gives insight to further studies on the mechanisms of metastasis.

BPGA- an ultra-fast pan-genome analysis pipeline

Abstract: Recent advances in ultra-high-throughput sequencing technology and metagenomics have led to a paradigm shift in microbial genomics from few genome comparisons to large-scale pan-genome studies at different scales of phylogenetic resolution. Pan-genome studies provide a framework for estimating the genomic diversity of the dataset, determining core (conserved), accessory (dispensable) and unique (strain-specific) gene pool of a species, tracing horizontal gene-flux across strains and providing insight into species evolution. The existing pan genome software tools suffer from various limitations like limited datasets, difficult installation/requirements, inadequate functional features etc. Here we present an ultra-fast computational pipeline BPGA (Bacterial Pan Genome Analysis tool) with seven functional modules. In addition to the routine pan genome analyses, BPGA introduces a number of novel features for downstream analyses like core/pan/MLST (Multi Locus Sequence Typing) phylogeny, exclusive presence/absence of genes in specific strains, subset analysis, atypical G + C content analysis and KEGG & COG mapping of core, accessory and unique genes. Other notable features include minimum running prerequisites, freedom to select the gene clustering method, ultra-fast execution, user friendly command line interface and high-quality graphics outputs. The performance of BPGA has been evaluated using a dataset of complete genome sequences of 28 Streptococcus pyogenes strains.

Correction: Corrigendum: A subpopulation of high IL-21-producing CD4+ T cells in Peyer’s Patches is induced by the microbiota and regulates germinal centers

Abstract: Scientific Reports 6: Article number: 30784; published online: 08 August 2016; updated: 10 October 2016 .

The Mediterranean plastic soup: synthetic polymers in Mediterranean surface waters

Abstract: The Mediterranean Sea has been recently proposed as one of the most impacted regions of the world with regards to microplastics, however the polymeric composition of these floating particles is still largely unknown. Here we present the results of a large-scale survey of neustonic micro- and meso-plastics floating in Mediterranean waters, providing the first extensive characterization of their chemical identity as well as detailed information on their abundance and geographical distribution. All particles >700 μm collected in our samples were identified through FT-IR analysis (n = 4050 particles), shedding for the first time light on the polymeric diversity of this emerging pollutant. Sixteen different classes of synthetic materials were identified. Low-density polymers such as polyethylene and polypropylene were the most abundant compounds, followed by polyamides, plastic-based paints, polyvinyl chloride, polystyrene and polyvinyl alcohol. Less frequent polymers included polyethylene terephthalate, polyisoprene, poly(vinyl stearate), ethylene-vinyl acetate, polyepoxide, paraffin wax and polycaprolactone, a biodegradable polyester reported for the first time floating in off-shore waters. Geographical differences in sample composition were also observed, demonstrating sub-basin scale heterogeneity in plastics distribution and likely reflecting a complex interplay between pollution sources, sinks and residence times of different polymers at sea.

The world’s road to water scarcity: shortage and stress in the 20th century and pathways towards sustainability

Abstract: Water scarcity is a rapidly growing concern around the globe, but little is known about how it has developed over time. This study provides a first assessment of continuous sub-national trajectories of blue water consumption, renewable freshwater availability, and water scarcity for the entire 20th century. Water scarcity is analysed using the fundamental concepts of shortage (impacts due to low availability per capita) and stress (impacts due to high consumption relative to availability) which indicate difficulties in satisfying the needs of a population and overuse of resources respectively. While water consumption increased fourfold within the study period, the population under water scarcity increased from 0.24 billion (14% of global population) in the 1900s to 3.8 billion (58%) in the 2000s. Nearly all sub-national trajectories show an increasing trend in water scarcity. The concept of scarcity trajectory archetypes and shapes is introduced to characterize the historical development of water scarcity and suggest measures for alleviating water scarcity and increasing sustainability. Linking the scarcity trajectories to other datasets may help further deepen understanding of how trajectories relate to historical and future drivers, and hence help tackle these evolving challenges.

Reconfigurable Complementary Logic Circuits with Ambipolar Organic Transistors.

Abstract: Ambipolar organic electronics offer great potential for simple and low-cost fabrication of complementary logic circuits on large-area and mechanically flexible substrates. Ambipolar transistors are ideal candidates for the simple and low-cost development of complementary logic circuits since they can operate as n-type and p-type transistors. Nevertheless, the experimental demonstration of ambipolar organic complementary circuits is limited to inverters. The control of the transistor polarity is crucial for proper circuit operation. Novel gating techniques enable to control the transistor polarity but result in dramatically reduced performances. Here we show high-performance non-planar ambipolar organic transistors with electrical control of the polarity and orders of magnitude higher performances with respect to state-of-art split-gate ambipolar transistors. Electrically reconfigurable complementary logic gates based on ambipolar organic transistors are experimentally demonstrated, thus opening up new opportunities for ambipolar organic complementary electronics.

High-efficient Synthesis of Graphene Oxide Based on Improved Hummers Method

Abstract: As an important precursor and derivate of graphene, graphene oxide (GO) has received wide attention in recent years. However, the synthesis of GO in an economical and efficient way remains a great challenge. Here we reported an improved NaNO3-free Hummers method by partly replacing KMnO4 with K2FeO4 and controlling the amount of concentrated sulfuric acid. As compared to the existing NaNO3-free Hummers methods, this improved routine greatly reduces the reactant consumption while keeps a high yield. The obtained GO was characterized by various techniques, and its derived graphene aerogel was demonstrated as high-performance supercapacitor electrodes. This improved synthesis shows good prospects for scalable production and applications of GO and its derivatives.

BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine

Abstract: Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM's diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients' target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ's cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the "multi-component, multi-target and multi-pathway" combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM's molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.

Ce3+-ion-induced visible-light photocatalytic degradation and electrochemical activity of ZnO/CeO2 nanocomposite

Abstract: In this study, pure ZnO, CeO2 and ZnO/CeO2 nanocomposites were synthesized using a thermal decomposition method and subsequently characterized using different standard techniques. High-resolution X-ray photoelectron spectroscopy measurements confirmed the oxidation states and presence of Zn(2+), Ce(4+), Ce(3+) and different bonded oxygen species in the nanocomposites. The prepared pure ZnO and CeO2 as well as the ZnO/CeO2 nanocomposites with various proportions of ZnO and CeO2 were tested for photocatalytic degradation of methyl orange, methylene blue and phenol under visible-light irradiation. The optimized and highly efficient ZnO/CeO2 (90:10) nanocomposite exhibited enhanced photocatalytic degradation performance for the degradation of methyl orange, methylene blue, and phenol as well as industrial textile effluent compared to ZnO, CeO2 and the other investigated nanocomposites. Moreover, the recycling results demonstrate that the ZnO/CeO2 (90:10) nanocomposite exhibited good stability and long-term durability. Furthermore, the prepared ZnO/CeO2 nanocomposites were used for the electrochemical detection of uric acid and ascorbic acid. The ZnO/CeO2 (90:10) nanocomposite also demonstrated the best detection, sensitivity and performance among the investigated materials in this application. These findings suggest that the synthesized ZnO/CeO2 (90:10) nanocomposite could be effectively used in various applications.