Membrane perforation and recovery dynamics in microbubble-mediated sonoporation

Transient sonoporation can essentially be epitomized by two fundamental processes: acoustically induced membrane perforation and its subsequent resealing. To provide insight into these processes, this article presents a new series of direct evidence on the membrane-level dynamics during and after an episode of sonoporation. Our direct observations were obtained from anchored fetal fibroblasts whose membrane topography was imaged in situ using real-time confocal microscopy. To facilitate controlled sonoporation at the single-cell level, microbubbles that can passively adhere to the cell membrane were first introduced at a 1:1 cell-to-bubble ratio. Single-pulse ultrasound exposure (1-MHz frequency, 10-cycle pulse duration, 0.85-MPa peak negative pressure in situ) was then applied to trigger microbubble pulsation/collapse, which, in turn, instigated membrane perforation. With this protocol, five membrane-level phenomena were observed: (i) localized perforation of the cell membrane was synchronized with the instant of ultrasound pulsing; (ii) perforation sites with temporal peak area <30 μm(2) were resealed successfully; (iii) during recovery, a thickened pore rim emerged, and its temporal progression corresponded with the pore closure action; (iv) membrane resealing, if successful, would generally be completed within 1 min of the onset of sonoporation, and the resealing time constant was estimated to be below 20 s; (v) membrane resealing would fail for overly large pores (>100 μm(2)) or in the absence of extracellular calcium ions. These findings serve to underscore the spatiotemporal complexity of membrane-level dynamics in sonoporation.

Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

Quasi-periodic patterns (QPP): large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity

Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders.

Multiscale analysis on spatiotemporal dynamics of energy consumption CO2 emissions in China: Utilizing the integrated of DMSP-OLS and NPP-VIIRS nighttime light datasets

CO₂ emissions caused by socioeconomic development and energy consumption in China have put enormous pressure on emissions reduction for Chinese government. In response to CO₂ emissions reduction in China, this study integrated the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) stable nighttime light (SNL) data and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) composite data, and established the integrated nighttime light datasets from 1992 to 2016. The estimated CO₂ emissions model utilizing the integrated nighttime light datasets and statistical CO₂ emissions at the provincial level from 1995 to 2016 were established. Finally, spatiotemporal dynamics of CO₂ emissions were simulated from multiscale. The results clearly showed that: (1) The fitting results of regression relationship between DMSP-OLS SNL data and NPP-VIIRS composite data met the accuracy requirements. The CO₂ emissions estimated model was valid. (2) The total amount of energy consumption CO₂ emissions in China had increased from 1889.3340 Mt in 1995 to 4683.3165 Mt in 2016, with a total growth of 2.47 times. (3) The high CO₂ emissions regions were clearly agglomerated in eastern coastal China from the pixel scale, the highest CO₂ emissions provinces were concentrated in Hebei and Shandong, the high CO₂ emissions prefecture cities were concentrated in Around Bohai Gulf area, eastern coastal China and some developed cities, and the high CO₂ emissions counties were concentrated in eastern coastal China and western energy intensive counties. (4) The relatively-slow growth accounted for the highest proportion among the five growth types, and the CO₂ emissions rapid growth regions were concentrated in eastern China at provincial, prefectural and county scale. The western regions accounted for the largest area proportion in five growth types at prefectural scale. We provided policy implications based on the results, which was beneficial to propose mitigation CO₂ emissions reduction in China.

Sterols regulate endocytic pathways during flg22-induced defense responses in Arabidopsis

The plant transmembrane receptor kinase FLAGELLIN SENSING 2 (FLS2) is crucial for innate immunity. Although previous studies have reported FLS2-mediated signal transduction and endocytosis via the clathrin-mediated pathway, whether additional endocytic pathways affect FLS2-mediated defense responses remains unclear. Here, we show that the Arabidopsis thaliana sterol-deficient mutant steroid methyltransferase 1 displays defects in immune responses induced by the flagellin-derived peptide flg22. Variable-angle total internal reflection fluorescence microscopy (VA-TIRFM) coupled with single-particle tracking showed that the spatiotemporal dynamics of FLS2-GFP changed on a millisecond time scale and that the FLS2-GFP dwell time at the plasma membrane increased in cells treated with a sterol-extracting reagent when compared with untreated counterparts. We further demonstrate that flg22-induced FLS2 clustering and endocytosis involves the sterol-associated endocytic pathway, which is distinct from the clathrin-mediated pathway. Moreover, flg22 enhanced the colocalization of FLS2-GFP with the membrane microdomain marker Flot 1-mCherry and FLS2 endocytosis via the sterol-associated pathway. This indicates that plants may respond to pathogen attacks by regulating two different endocytic pathways. Taken together, our results suggest the key role of sterol homeostasis in flg22-induced plant defense responses.

Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences

Neuromorphic data, recording frameless spike events, have attracted considerable attention for the spatiotemporal information components and the event-driven processing fashion. Spiking neural networks (SNNs) represent a family of event-driven models with spatiotemporal dynamics for neuromorphic computing, which are widely benchmarked on neuromorphic data. Interestingly, researchers in the machine learning community can argue that recurrent (artificial) neural networks (RNNs) also have the capability to extract spatiotemporal features although they are not event-driven. Thus, the question of "what will happen if we benchmark these two kinds of models together on neuromorphic data" comes out but remains unclear. In this work, we make a systematic study to compare SNNs and RNNs on neuromorphic data, taking the vision datasets as a case study. First, we identify the similarities and differences between SNNs and RNNs (including the vanilla RNNs and LSTM) from the modeling and learning perspectives. To improve comparability and fairness, we unify the supervised learning algorithm based on backpropagation through time (BPTT), the loss function exploiting the outputs at all timesteps, the network structure with stacked fully-connected or convolutional layers, and the hyper-parameters during training. Especially, given the mainstream loss function used in RNNs, we modify it inspired by the rate coding scheme to approach that of SNNs. Furthermore, we tune the temporal resolution of datasets to test model robustness and generalization. At last, a series of contrast experiments are conducted on two types of neuromorphic datasets: DVS-converted (N-MNIST) and DVS-captured (DVS Gesture). Extensive insights regarding recognition accuracy, feature extraction, temporal resolution and contrast, learning generalization, computational complexity and parameter volume are provided, which are beneficial for the model selection on different workloads and even for the invention of novel neural models in the future.

Spatiotemporal variability and key influencing factors of river fecal coliform within a typical complex watershed

Fecal coliform bacteria are a key indicator of human health risks; however, the spatiotemporal variability and key influencing factors of river fecal coliform have yet to be explored in a rural-suburban-urban watershed with multiple land uses. In this study, the fecal coliform concentrations in 21 river sections were monitored for 20 months, and 441 samples were analyzed. Multivariable regressions were used to evaluate the spatiotemporal dynamics of fecal coliform. The results showed that spatial differences were mainly dominated by urbanization level, and environmental factors could explain the temporal dynamics of fecal coliform in different urban patterns except in areas with high urbanization levels. Reducing suspended solids is a direct way to manage fecal coliform in the Beiyun River when the natural factors are difficulty to change, such as temperature and solar radiation. The export of fecal coliform from urban areas showed a quick and sensitive response to rainfall events and increased dozens of times in the short term. Landscape patterns, such as the fragmentation of impervious surfaces and the overall landscape, were identified as key factors influencing urban non-point source bacteria. The results obtained from this study will provide insight into the management of river fecal pollution.

Spatiotemporal dynamics in microbial communities mediating biogeochemical cycling of nutrients across the Xiaowan Reservoir in Lancang River

Microbes drive biogeochemical cycles of nutrients controlling water quality in freshwater ecosystems, yet little is known regarding how spatiotemporal variation in the microbial community affects this ecosystem-level functional processes to resist perturbations. Here we examined spatiotemporal dynamics of microbial communities in paired stratified water columns and sediments collected from the Xiaowan Reservoir of Lancang-Mekong River over a year long period. Results highlighted distinctive spatiotemporal patterns of microbial communities in water columns mainly driven by sulfate, dissolved oxygen, nitrate and temperature, whilst sediment communities only showed a seasonal variation pattern governed by pH, reduced inorganic sulfur, sulfate, organic matter and total nitrogen. Microbial co-occurrence networks revealed the succession of keystone taxa in both water columns and sediments, reflecting core ecological functions in response to altered environmental conditions. Specifically, in shallow water, keystone nitrogen fixers and denitrifiers were responsible for providing nitrogen nutrients in summer, while recalcitrant substance degraders likely supplied microbially available organic matters to maintain ecosystem stability in winter. But in deep water, methane oxidation was the critical process linked to microbial-mediated cycle of carbon, nitrogen and sulfur. In addition, carbon metabolism and mercury methylation mediated by sulfate reducers, denitrifiers and nitrogen fixers were core functioning features of sediments in summer and winter, respectively. This work expands our knowledge of the importance of keystone taxa in maintaining stability of reservoir ecosystems under changing environments, providing new perspectives for water resource conservation and management.

Global and structured waves of rs-fMRI signal identified as putative propagation of spontaneous neural activity

Conventional resting-state fMRI (rs-fMRI) studies have focused on investigating the synchronous neural activity in functionally relevant distant regions that are termed as resting-state networks. On the other hand, less is known about the spatiotemporal dynamics of the spontaneous activity of the brain. By examining the characteristics of both rs-fMRI and vascular time lag that was measured using dynamic susceptibility contrast-enhanced perfusion weighted imaging, the present study identifies several structured propagation of the rs-fMRI signal as putative neural streams. Temporal shift of both rs-fMRI and perfusion imaging data in each voxel compared with the averaged whole-brain signal was computed using cross-correlation analysis. In contrast to the uniformity of the vascular time lag across subjects, whole-brain rs-fMRI time lag was estimated to be composed of three independent components. After regression of vascular time lag, independent component analysis was applied to rs-fMRI data. The putative neural streams showed slow propagation of the signal from task-positive regions to main nodes of the default mode network, which may represent a mode of transmission underlying the interactions among the resting-state networks.

The spatiotemporal dynamics of lung cancer: 30-year trends of epidemiology across 204 countries and territories

BACKGROUND

It has been established that lung cancer is the leading cause of all cancer deaths. This study sought to analyze the epidemiological trends of lung cancer over the past 30 years worldwide.

METHODS

Estimates, including the global, regional, national prevalence, incidence, and years lived with disability (YLDs) of lung cancer from 1990 to 2019, were extracted from the Global Burden of Disease Study 2019 to assess the spatiotemporal dynamics in cases and age-standardized rates (ASR). The estimated annual percentage change (EAPC) was calculated to evaluate the variation in ASR. Besides, estimates of age-sex specific prevalence, decomposition analysis for incident cases, and correlation analysis of the EAPC were conducted in our study.

RESULTS

Globally, the ASR of lung cancer prevalence, incidence and YLDs in 2019 were 38.84/100,000 persons, 27.66/100,000 persons, and 6.62/100,000 persons, respectively. Over the past 30 years, the ASR of incidence (EAPC = -0.09) decreased, although that of prevalence (EAPC = 0.51) and YLDs (EAPC = 0.03) increased. The global prevalence counts was greater in males than females at all age groups and increased with age, peaking in the 65-69 age group for both sexes. The increase in incidence was mainly attributed to population aging. For YLDs, EAPC was negatively correlated with the human development index (p = 0.0008) and ASR (p < 0.0001) in 1990 across nation-level units.

CONCLUSIONS

Lung cancer remains a major public health issue globally, warranting the implementation of scientific and effective measures in different countries and territories to control it.

Spatiotemporal dynamics of grassland aboveground biomass and its driving factors in North China over the past 20 years

Although remote sensing has enabled rapid monitoring of grassland aboveground biomass (AGB) at a regional scale, it is still a difficult challenge to construct an accurate estimation model of grassland AGB in a vast region to support the AGB dynamics analysis over a long time series. In this study, extensive grassland AGB measurements (collected in North China during the grassland growing season of 2000-2019), MODIS data, and environmental factors (climate, topography and soil) were employed to construct the grassland AGB models using four machine learning algorithms (random forest, support vector machine, artificial neural network and extreme learning machine) combined with four variable selections. The spatial distributions of annual grassland AGB from 2000 to 2019 were simulated based on the optimal AGB model. The temporal change and future trend of AGB series from 2000 to 2019 were comprehensively analyzed by the slope model and Hurst exponent. The influences of natural and anthropogenic factors on grassland AGB dynamics were explored quantitatively using the Geodetector model. The results showed that (1) the random forest model constructed from the variables selected by the successive projections algorithm is the optimal grassland AGB model. (2) The 20-year average grassland AGB in North China showed an overall spatial distribution of being low in the central and western parts and high in the southeastern part. (3) The annual maximum grassland AGB in most regions (82.71%) showed an increasing trend during 2000-2019; and most of the grasslands with a decreasing trend of AGB were located in regions with low AGB values and arid climates. (4) The future trend of grassland AGB after the study period may be optimistic, as reflected by more grassland AGB was predicted to increase rather than decrease (70.38% vs. 29.62%). (5) The main driving factors of spatiotemporal dynamics of grassland AGB were precipitation, soil type, and livestock density; the interactive influence of two drivers on AGB showed mutual enhancement.

Optogenetic approaches to investigate spatiotemporal signaling during development

Embryogenesis is coordinated by signaling pathways that pattern the developing organism. Many aspects of this process are not fully understood, including how signaling molecules spread through embryonic tissues, how signaling amplitude and dynamics are decoded, and how multiple signaling pathways cooperate to pattern the body plan. Optogenetic approaches can be used to address these questions by providing precise experimental control over a variety of biological processes. Here, we review how these strategies have provided new insights into developmental signaling and discuss how they could contribute to future investigations.

Spatiotemporal Dynamics of Single and Paired Pulse TMS-EEG Responses

For physiological brain function a particular balance between excitation and inhibition is essential. Paired pulse transcranial magnetic stimulation (TMS) can estimate cortical excitability and the relative contribution of inhibitory and excitatory networks. Combining TMS with electroencephalography (EEG) enables additional assessment of the spatiotemporal dynamics of neuronal responses in the stimulated brain. This study aims to evaluate the spatiotemporal dynamics and stability of single and paired pulse TMS-EEG responses, and assess long intracortical inhibition (LICI) at the cortical level. Twenty-five healthy subjects were studied twice, approximately one week apart. Manual coil positioning was applied in sixteen subjects and robot-guided positioning in nine. Both motor cortices were stimulated with 50 single pulses and 50 paired pulses at each of the five interstimulus intervals (ISIs): 100, 150, 200, 250 and 300 ms. To assess stability and LICI, the intraclass correlation coefficient and cluster-based permutation analysis were used. We found great resemblance in the topographical distribution of the characteristic TMS-EEG components for single and paired pulse TMS. Stimulation of the dominant and non-dominant hemisphere resulted in a mirrored spatiotemporal dynamics. No significant effect on the TMS-EEG responses was found for either stimulated hemisphere, time or coil positioning method, indicating the stability of both single and paired pulse TMS-EEG responses. For all ISIs, LICI was characterized by significant suppression of the late N100 and P180 components in the central areas, without affecting the early P30, N45 and P60 components. These observations in healthy subjects can serve as reference values for future neuropsychiatric and pharmacological studies.

Year-to-year variation in the density of Ixodes ricinus ticks and the prevalence of the rodent-associated human pathogens Borrelia afzelii and B. miyamotoi in different forest types

The human pathogens Borrelia afzelii, which causes Lyme borreliosis and B. miyamotoi, which causes relapsing fever, both circulate between Ixodes ricinus ticks and rodents. The spatiotemporal dynamics in the prevalence of these pathogens have not yet been fully elucidated, but probably depend on the spatiotemporal population dynamics of small rodents. We aimed to evaluate the effect of different forest types on the density of infected nymphs in different years and to obtain more knowledge about the spatial and temporal patterns of ticks and tick-borne pathogens. We analysed unfed nymphal ticks from 22 stands of four different forest types in Belgium in 2009, 2010, 2013 and 2014 and found that the density of nymphs in general and the density of nymphs infected with B. afzelii and B. miyamotoi varied yearly, but without temporal variation in the infection prevalence. The yearly variation in density of infected nymphs in our study thus seems to be caused most by the variation in the density of nymphs, which makes it a good predictor of disease risk. The risk for rodent-associated tick-borne diseases also varied between forest types. We stress the need to elucidate the contribution of the host community composition to tick-borne disease risk.

Spatiotemporal dynamics of cell abundance, colony size and intracellular toxin concentrations of pelagic and benthic Microcystis in Lake Caohai, China

Lake Caohai has experienced extensive Microcystis blooms in recent years, and to improve its water quality, the local government carried out a series of water control measures. To better understand the dynamics of both pelagic and benthic Microcystis and their characteristics in Lake Caohai, we conducted a 1-year investigation from December 2015 to December 2016 to gain a seasonal outlook on the distribution and dynamics of cell abundance, colony size and intracellular microcystins (MCs) of Microcystis. The results indicated that the Microcystis bloom occupied primarily the northeastern region and then moved gradually from lakeshore to lake center. The perennial southwesterly winds and the water inflow from northeast to southwest in Lake Caohai determined the spatiotemporal distribution of pelagic Microcystis. Benthic Microcystis was mainly distributed in the northeastern region in summer, occupied the lake center in autumn and then occupied the southeastern region in winter, determined by the sedimentation of pelagic Microcystis and the death of benthic Microcystis. Small colonies (20-60 μm) overwintered more easily in both water column and sediment. The concentrations of intracellular toxin of benthic Microcystis were observed to be significantly higher than those of pelagic Microcystis. This might be because Microcystis synthesized large amount of MCs to acclimate to an unfavorable benthic environment. This knowledge on the dynamics of Microcystis expands our understanding of mechanisms underpinning the formation of Microcystis blooms.

Using land use/land cover trajectories to uncover ecosystem service patterns across the Alps

Managing multiple ecosystem services (ES) in agricultural landscapes is a challenging task, especially in regions with complex topographical and agro-ecological conditions. These challenges require ES assessment approaches that go beyond the case study level and provide multi-temporal information at a transnational level. We used a spatiotemporal approach to examine the impact of specific land use/land cover (LULC) trajectories on eight ES for the past 150 years. We show how a spatially explicit ES upscaling procedure, from case study to an Alpine-wide level, based on topographical, agro-ecological and socioeconomic parameters, can improve our understanding of ES dynamics and bundles. Our results indicated that the provision of multiple ES was not stable during the 150 years surveyed, mainly depending on the prevailing land management type and the biophysical conditions. ES bundle mapping enabled us to identify landscapes with consistent socioecological characteristics that are most likely to either enhance or diminish the provision of specific types of services. By introducing a spatiotemporal perspective into ES assessment, we provide clear evidence of the dynamic nature of ES provision and contribute to identifying processes and drivers behind these interactions. Our results emphasize that mountain ES supply is particularly sensitive to long-term LULC change, to biophysical characteristics and to regional socioeconomic conditions. They indicate the benefit of integrating of ES bundles into environmental policies at national and transnational level.

Characterizing spatiotemporal dynamics of anthropogenic heat fluxes: A 20-year case study in Beijing-Tianjin-Hebei region in China

Rapid urbanization, which is closely related to economic growth, human health, and micro-climate, has resulted in a considerable amount of anthropogenic heat emissions. The lack of estimation data on long-term anthropogenic heat emissions is a great concern in climate and urban flux research. This study estimated the annual average anthropogenic heat fluxes (AHFs) in Beijing-Tianjin-Hebei region in China between 1995 and 2015 on the basis of multisource remote sensing images and ancillary data. Anthropogenic heat emissions from different sources (e.g., industries, buildings, transportation, and human metabolism) were also estimated to analyze the composition of AHFs. The spatiotemporal dynamics of long-term AHFs with high spatial resolution (500 m) were estimated by using a refined AHF model and then analyzed using trend and standard deviation ellipse analyses. Results showed that values in the region increased significantly from 0.15 W· m^-2 in 1995 to 1.46 W· m^-2 in 2015. Heat emissions from industries, transportation, buildings, and human metabolism accounted for 64.1%, 17.0%, 15.5%, and 3.4% of the total anthropogenic heat emissions, respectively. Industrial energy consumption was the dominant contributor to the anthropogenic heat emissions in the region. During this period, industrial heat emissions presented an unstable variation but showed a growing trend overall. Heat emissions from buildings increased steadily. Spatial distribution was extended with an increasing tendency of the difference between the maximum and the minimum and was generally dominated by the northeast-southwest directional pattern. The spatiotemporal distribution patterns and trends of AHFs could provide vital support on management decision in city planning and environmental monitoring.

Interplay between reaction and diffusion processes in governing the dynamics of virus infections

Spreading of viral infection in the tissues such as lymph nodes or spleen depends on virus multiplication in the host cells, their transport and on the immune response. Reaction-diffusion systems of equations with delays in cell proliferation and death by apoptosis represent an appropriate model to study this process. The properties of the cells of the immune system and the initial viral load determine the spatiotemporal regimes of infection spreading. Infection can be completely eliminated or it can persist at some level together with a certain chronic immune response in a spatially uniform or oscillatory mode. Finally, the immune cells can be completely exhausted leading to a high viral load persistence in the tissue. It has been found experimentally, that virus proteins can affect the immune cell migration. Our study shows that both the motility of immune cells and the virus infection spreading represented by the diffusion rate coefficients are relevant control parameters determining the fate of virus-host interaction.

Dynamics, differences, influencing factors of eco-efficiency in China: A spatiotemporal perspective analysis

Eco-efficiency can effectively measure the relationship between economy, resources, environment, and development. Understanding eco-efficiency is of great practical significance for decision makers tasked with addressing and delivering sustainable socioeconomic development. Based on an "undesirable output Slacks-Based Measure models," this study evaluated the eco-efficiency of 285 Chinese cities during the period 2004-2014, analyzing spatiotemporal dynamics and influencing factors using a Spatial Autocorrelation Panel Data Model. The main results are as follows: From the spatial perspective, eco-efficiency in Chinese cities generally evidenced an M-shaped trend (increasing-decreasing-increasing-decreasing), and imbalanced spatiotemporal dynamics. Furthermore, the urban eco-efficiency generally presented a distinct convergence of HH cluster and LL cluster clubs, with the latter being the most dominant. From the regional point of view, there existed a decreasing trend in the efficiencies of cities, from eastern China to central and western China. In addition, we identified significant differences in the eco-efficiency of different cities in China, and the coefficient of variation of eco-efficiency showed a general decrease. The results of our estimation of the factors affecting urban eco-efficiency showed that the economic development level, the industrial structure, import and export trade, and the information level all had significant positive influence, and local government expenditure, social retail sales of consumer goods, and infrastructure all had a negative effect on urban eco-efficiency. This paper puts forward numbers of suggestions for ways to promote social, ecological, and economic development in Chinese cities, based on our findings.

Spatial variations in CO2 fluxes in a subtropical coastal reservoir of Southeast China were related to urbanization and land-use types

Carbon dioxide (CO₂) emissions from aquatic ecosystems are important components of the global carbon cycle, yet the CO₂ emissions from coastal reservoirs, especially in developing countries where urbanization and rapid land use change occur, are still poorly understood. In this study, the spatiotemporal variations in CO₂ concentrations and fluxes were investigated in Wenwusha Reservoir located in the southeast coast of China. Overall, the mean CO₂ concentration and flux across the whole reservoir were 41.85 ± 2.03 µmol/L and 2.87 ± 0.29 mmol/m²/h, respectively, and the reservoir was a consistent net CO₂ source over the entire year. The land use types and urbanization levels in the reservoir catchment significantly affected the input of exogenous carbon to water. The mean CO₂ flux was much higher from waters adjacent to the urban land (5.05 ± 0.87 mmol/m²/hr) than other land use types. Sites with larger input of exogenous substance via sewage discharge and upstream runoff were often the hotspots of CO₂ emission in the reservoir. Our results suggested that urbanization process, agricultural activities, and large input of exogenous carbon could result in large spatial heterogeneity of CO₂ emissions and alter the CO₂ biogeochemical cycling in coastal reservoirs. Further studies should characterize the diurnal variations, microbial mechanisms, and impact of meteorological conditions on reservoir CO₂ emissions to expand our understanding of the carbon cycle in aquatic ecosystems.

Spatiotemporal trajectories in resting-state FMRI revealed by convolutional variational autoencoder

Recent resting-state fMRI studies have shown that brain activity exhibits temporal variations in functional connectivity by using various approaches including sliding window correlation, co-activation patterns, independent component analysis, quasi-periodic patterns, and hidden Markov models. These methods often model the brain activity as a discretized hopping among several brain states that are defined by the spatial configurations of network activity. However, the discretized states are merely a simplification of what is likely to be a continuous process, where each network evolves over time following its unique path. To model these characteristic spatiotemporal trajectories, we trained a variational autoencoder using rs-fMRI data and evaluated the spatiotemporal features of the latent variables obtained from the trained networks. Our results suggest that there are a relatively small number of approximately orthogonal whole-brain spatiotemporal patterns that capture the most prominent features of rs-fMRI data, which can serve as the building blocks to construct all possible spatiotemporal dynamics in resting state fMRI. These spatiotemporal patterns provide insight into how activity flows across the brain in concordance with known network structures and functional connectivity gradients.

Reduced spatiotemporal brain dynamics are associated with increased depressive symptoms after a relationship breakup

Depressive symptoms following a stressful life event, such as a relationship breakup, are common, and constitute a potent risk factor for the onset of a major depressive episode. Resting-state neuroimaging studies have increasingly identified abnormal whole-brain communication in patients with depression, but it is currently unclear whether depressive symptoms in individuals without a clinical diagnosis have reliable neural underpinnings. We investigated to what extent the severity of depressive symptoms in a non-clinical sample was associated with imbalances in the complex dynamics of the brain during rest. To this end, a novel intrinsic ignition approach was applied to resting-state neuroimaging data from sixty-nine participants with varying degrees of depressive symptoms following a relationship breakup. Ignition-based measures of integration, hierarchy, and metastability were calculated for each participant, revealing a negative correlation between these measures and depressive ratings. We found that the severity of depressive symptoms was associated with deficits in the brain's capacity to globally integrate and process information over time. Furthermore, we found that increased depressive symptoms were associated with reduced spatial diversity (i.e., hierarchy) and reduced temporal variability (i.e., metastability) in the functional organization of the brain. These findings suggest the merit of investigating constrained dynamical complexity as it is sensitive to the level of depressive symptoms even in a non-clinical sample.

Quantitative assessment of the habitat quality dynamics in Yellow River Basin, China

Habitat quality is an important indicator for measuring regional biodiversity and ecosystem service value. A change in habitat quality is the direct result of the interaction between human activities and the natural environment. In this study, the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was used to evaluate the habitat quality of the Yellow River Basin (YRB) from 1980 to 2018. We further analyzed the quantity and spatial transfer status of habitat quality quantitatively using the Geo-informatic Tupu method. The results show that the habitat degradation degree under human disturbance showed a trend of increasing first and then decreasing, with values of 0.0196 in 1980, 0.0200 in 2000, and 0.0199 in 2018. In addition, it presents two ring structures: light-severe-high-moderate and light-moderate-high-severe in space. The overall level of habitat quality in the basin is relatively good, but there is a trend of decline, which are 0.6091, 0.6069, and 0.6049 in the three stages respectively. The spatial distribution of habitat quality showed a pattern of high in the middle and low on both sides. The habitat quality has been restored in some areas. The transition between good and medium and good and excellent in the Tupu change units of the habitat quality grade is the most intense. Both stages are mainly the transformation from high-grade to low-grade habitat quality, but there is a trend of gradual improvement. The findings could have theoretical support and policy implications for the maintenance of biodiversity and the protection of the natural environment in the Yellow River Basin.

Reclamation shifts the evolutionary paradigms of tidal channel networks in the Yellow River Delta, China

Tidal channel networks are ubiquitous features of coastal landforms that control the input and output of intertidal water, sediment and nutrients. Nevertheless, those intertidal platforms have undergone extensive losses due to human activities such as land reclamation. Identifying how tidal channel networks respond to land reclamation is critical to our prediction of the fate of residual tidal landforms. However, the morphological changes in the channel networks in the Yellow River Delta (YRD) impacted by severe reclamation remain unclear. Here, we analyzed the spatiotemporal dynamics of channel networks on two scales (the delta scale and the zone scale) under the double stress of land reclamation and natural pressure by comparing a comprehensive suite of morphological channel characteristics, including channel segment count, channel order, length, fractal dimension, drainage density and drainage efficiency. The results show that the interannual dynamics of tidal channel networks in the delta over the last three decades have experienced two periods: a favorable period during 1984-2000 and an adverse period during 2001-2018. The spatiotemporal patterns of channel networks varied with zones. Land reclamation exerted a dominant influence on shifting the evolutionary trend of channel networks on both the delta scale and the zone scale when reclamation proportion exceeded a certain threshold. Sediment siltation could to a certain degree mitigate the impact of reclamation on tidal channel networks development. Our study highlighted the effect of reclamation on the geomorphological evolution of tidal channel networks and identified its impact threshold which could further be used to guide coastal zone restoration and management.

Health risks facing travelers to Russia with special reference to natural-focal diseases

BACKGROUND

Russia, an enormous country almost completely located within temperate latitudes, has a broad spectrum of natural landscapes which attract increasing numbers of tourists, from arctic deserts in the north to steppes and deserts in the south. Currently, tourism is undergoing active development in Russia: new travel routes, including ones that involve visiting the wilderness, are steadily appearing. Among the multitude of infectious diseases that can endanger travelers, natural-focal diseases, whose agents and/or carriers are integral to natural landscapes, are especially prominent. Some of the results of the study of natural-focal infections and parasitoses, which are necessary to evaluate the recreational and travel potential of the Russian Federation, are presented and discussed in this article.

METHOD

A cartographical and statistical analysis of infectious and parasitic natural-focal diseases, spanning more than a decade (1997-2013), is the basis of this article.

RESULTS

This analysis, along with that of additional cartographical and textual sources, reveals that natural-focal infections are most diverse between 48° N and 60° N and least diverse in the northern regions of the Far East of Russia. Different regions have different numbers of nosoforms and different morbidity level, which signifies an irregularity in the distribution of parasitic diseases.

CONCLUSIONS

This medico-geographical information may be useful both for individual tourists planning trips to Russia and tour agencies organizing tour groups. It also can be used by health advisers when they consult people before a trip, to assess the actual risks, suggest a number of precautions and pick the particular diseases out of those listed that actually constitute a risk in certain regions, and suggest a suitable preventative treatment if needed.