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Presently, China has the largest high-speed rail (HSR) system in the world. However, our understanding of the network structure of the world’s largest HSR system remains largely incomplete due to the limited data available. In this study, a publicly available data source, namely, information from a ticketing website, was used to collect an exhaustive dataset on the stations and routes within the Chinese HSR system. The dataset included all 704 HSR stations that had been built as of June, 2016. A classical set of frequently used metrics based on complex network theory were analyzed, including degree centrality, betweenness centrality, and closeness centrality. The frequency distributions of all three metrics demonstrated highly consistent bimodal-like patterns, suggesting that the Chinese HSR network consists of two distinct regimes. The results indicate that the Chinese HSR system has a hierarchical structure, rather than a scale-free structure as has been commonly observed. To the best of our knowledge, such a network structure has not been found in other railway systems, or in transportation systems in general. Follow-up studies are needed to reveal the formation mechanisms of this hierarchical network structure.

Recent studies have interpreted patterns of remotely sensed tree cover as evidence that forest with intermediate tree cover might be unstable in the tropics, as it will tip into either a closed forest or a more open savanna state. Here we show that across all continents the frequency of wildfires rises sharply as tree cover falls below ~40%. Using a simple empirical model, we hypothesize that the steepness of this pattern causes intermediate tree cover (30–60%) to be unstable for a broad range of assumptions on tree growth and fire-driven mortality. We show that across all continents, observed frequency distributions of tropical tree cover are consistent with this hypothesis. We argue that percolation of fire through an open landscape may explain the remarkably universal rise of fire frequency around a critical tree cover, but we show that simple percolation models cannot predict the actual threshold quantitatively. The fire-driven instability of intermediate states implies that tree cover will not change smoothly with climate or other stressors and shifts between closed forest and a state of low tree cover will likely tend to be relatively sharp and difficult to reverse.

Publicly available remote sensing products have boosted science in many ways. The openness of these data sources suggests high reproducibility. However, as we show here, results may be specific to versions of the data products that can become unavailable as new versions are posted. We focus on remotely-sensed tree cover. Recent studies have used this public resource to detect multi-modality in tree cover in the tropical and boreal biomes. Such patterns suggest alternative stable states separated by critical tipping points. This has important implications for the potential response of these ecosystems to global climate change. For the boreal region, four distinct ecosystem states (i.e., treeless, sparse and dense woodland, and boreal forest) were previously identified by using the Collection 3 data of MODIS Vegetation Continuous Fields (VCF). Since then, the MODIS VCF product has been updated to Collection 5; and a Landsat VCF product of global tree cover at a fine spatial resolution of 30 meters has been developed. Here we compare these different remote-sensing products of tree cover to show that identification of alternative stable states in the boreal biome partly depends on the data source used. The updated MODIS data and the newer Landsat data consistently demonstrate three distinct modes around similar tree-cover values. Our analysis suggests that the boreal region has three modes: one sparsely vegetated state (treeless), one distinct ‘savanna-like’ state and one forest state, which could be alternative stable states. Our analysis illustrates that qualitative outcomes of studies may change fundamentally as new versions of remote sensing products are used. Scientific reproducibility thus requires that old versions remain publicly available.

Big data have contributed to deepen our understanding in regards to many human systems, particularly human mobility patterns and the structure and functioning of transportation systems. Resonating the recent call for 'open big data,' big data from various sources on a range of scales have become increasingly accessible to the public. However, open big data relevant to travelers within public transit tools remain scarce, hindering any further in-depth study on human mobility patterns. Here, we explore ticketing-website derived data that are publically available but have been largely neglected. We demonstrate the power, potential and limitations of this open big data, using the Chinese high-speed rail (HSR) system as an example. Using an application programming interface, we automatically collected the data on the remaining tickets (RTD) for scheduled trains at the last second before departure in order to retrieve information on unused transit capacity, occupancy rate of trains, and passenger flux at stations. We show that this information is highly useful in characterizing the spatiotemporal patterns of traveling behaviors on the Chinese HSR, such as weekend traveling behavior, imbalanced commuting behavior, and station functionality. Our work facilitates the understanding of human traveling patterns along the Chinese HSR, and the functionality of the largest HSR system in the world. We expect our work to attract attention regarding this unique open big data source for the study of analogous transportation systems.

Background & Aims Immunosuppression-related symptom experience has not been covered thoroughly in long-term liver transplant recipients. The aim of this study was to assess the symptom experience of immunosuppressive therapy three years after liver transplantation and to correlate it with adherence to medications and sociodemographic or disease-related characteristics. Methods This study included 94 liver transplant recipients who had survived for more than 3 years after liver transplantation. Symptom experience was measured by the 59-Item Modified Transplant Symptom Occurrence and Symptom Distress Scale (MTSOSD-59R) at the outpatient visits. Adherence to immunosuppressive drugs was assessed using the Basel Assessment of Adherence with Immunosuppressive Medication Scale (BAASIS). Results Itching, concentration or memory problems, and fatigue were the three most frequent or most distressing symptoms. Factors significantly associated with a higher level of symptom frequency and distress were 3- to 5-year time cohort (i.e., time post-transplantation), and younger age. At the item level, concentration or memory problems were the most frequent and distressing symptoms in the 3- to 5-year time cohort. Itching was the most frequent and distressing symptom in the 5- to 9-year time cohort. Finally, relationship was found between symptom experience and nonadherence to immunosuppressive drugs. Conclusions Symptoms related to physical complaints or impairments were more often perceived and more distressing for liver transplant recipients 3 years after transplantation. Furthermore, the 3- to 5-year time cohort and younger age were associated with a higher degree of perceived symptom occurrence and symptom distress. Finally, recipients who perceived higher levels of symptom frequency and symptom distress reported higher levels of nonadherence.

The affiliations of the ninth and last authors are incorrect. Qier Chen is not affiliated with institution number 2, but rather institution number 3, School of Nursing, Sun Yat-sen University, Guangzhou, China. Guihua Chen is not affiliated with institution number 1, but rather institution number 2, Department of Hepatic Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.

The regulation of adult neurogenesis by opiates has been implicated in modulating different addiction cycles. At which neurogenesis stage opiates exert their action remains unresolved. We attempt to define the temporal window of morphine’s inhibition effect on adult neurogenesis by using the POMC-EGFP mouse model, in which newborn granular cells (GCs) can be visualized between days 3–28 post-mitotic. The POMC-EGFP mice were trained under the 3-chambers conditioned place preference (CPP) paradigm with either saline or morphine. We observed after 4 days of CPP training with saline, the number of EGFP-labeled newborn GCs in sub-granular zone (SGZ) hippocampus significantly increased compared to mice injected with saline in their homecage. CPP training with morphine significantly decreased the number of EGFP-labeled GCs, whereas no significant difference in the number of EGFP-labeled GCs was observed with the homecage mice injected with the same dose of morphine. Using cell-type selective markers, we observed that morphine reduced the number of late stage progenitors and immature neurons such as Doublecortin (DCX) and βIII Tubulin (TuJ1) positive cells in the SGZ but did not reduce the number of early progenitors such as Nestin, SOX2, or neurogenic differentiation-1 (NeuroD1) positive cells. Analysis of co-localization between different cell markers shows that morphine reduced the number of adult-born GCs by interfering with differentiation of early progenitors, but not by inducing apoptosis. In addition, when NeuroD1 was over-expressed in DG by stereotaxic injection of lentivirus, it rescued the loss of immature neurons and prolonged the extinction of morphine-trained CPP. These results suggest that under the condition of CPP training paradigm, morphine affects the transition of neural progenitor/stem cells to immature neurons via a mechanism involving NeuroD1.