Correlations between ecosystem service value and landscape ecological risk and its spatial heterogeneity in Jilin Province, China.

Exploring the correlations between ecosystem service value (ESV) and landscape ecological risk and the driving factors of their spatial variations is crucial for maintaining regional ecological security and promoting sustainable human well-being. We carried out a grid resampling size of 5 km×5 km assessment units of Jilin Pro-vince based on the remote sensing monitoring data of land use in 2000, 2005, 2010, 2015, and 2020. We quantitatively evaluated the landscape ecological risk and ESV, and analyzed their spatial-temporal variations. Employing bivariate spatial autocorrelation analysis and the geographical detector models, we examined the correlation between the landscape ecological risk and ESV and explored the driving factors for their spatial variations. The results showed that ESV in Jilin Province decreased from 385.895 billion yuan to 378.211 billion yuan during 2000-2020. The eastern region was dominated by extremely low risk, medium risk, and low risk areas. In contrast, the western region was mainly composed of extremely high risk and high risk areas. There was a significant negative correlation and spatial negative correlation between landscape ecological risk and ESV in Jilin Province. Human activity and land use type were the important driving factors for spatial differentiation in both landscape ecological risk and ESV. Our findings suggested that scientific land use regulation and appropriate control of human activities are critically needed to optimize Jilin Province's ecological environment.

The stability issue of fractured rock mass slope under the influences of freeze-thaw cycle.

Freeze-thaw failure of frozen rock slope often occurs during engineering construction and mining in cold area, which poses a great threat to engineering construction and people's life safety. The properties of rock mass in cold region will change with the periodic change of temperature, which makes it difficult to accurately evaluate the stability of slope under the action of freeze-thaw cycle by conventional methods. Based on field investigation and literature review, this paper discusses the characteristics of frozen rock mass and the failure mechanism of frozen rock slope, and gives the types and failure modes of frozen rock slope. Then, the research status of frozen rock slope is analyzed. It is pointed out that the failure of frozen rock slope is the result of thermo-hydro-mechanical (THM) coupling. It is considered that freeze-thaw cycle, rainfall infiltration and fracture propagation have significant effects on the stability of frozen rock slope, and numerical simulation is used to demonstrate. The research shows that the safety factor of frozen rock slope changes dynamically with the surface temperature, and the safety factor of slope decreases year by year with the increase of freeze-thaw cycles, and the fracture expansion will significantly reduce the safety factor. Based on the above knowledge, a time-varying evaluation method of frozen rock slope stability based on THM coupling theory is proposed. This paper can deepen scholars' understanding of rock fracture slope in cold area and promote related research work.

THM model of rock tunnels in cold regions and numerical simulation.

The freezing damage of rock tunnels in cold region involves ice-water phase change and complicated interaction of Thermo-Hydro-Mechanical (THM) field. Taking the fractured rock mass of cold region tunnels as research subject, the THM coupling model of cold region tunnels was established, which is based on the seepage mechanics, heat transfer theory, damage mechanics and equivalent continuum theory. This model could reflect the anisotropic properties of deformation, water migration and heat transfer caused by the initial fracture of rock mass. The construction and operation processes of a rock tunnel in cold region were simulated, and results were compared with the measured value and predecessor's achievements. It shows that proposed model could reflect the anisotropic property of surrounding rock and the simulated deformation and stress are not symmetrical. Compared with the literature, the calculated results in this paper are closer to the measured values. The insulating layer has a significant effect on the stress of the supporting structures. The maximum tension stress of the lining is 4.5 times as that without insulating layer, and the lining will be destroyed for the overlarge tension stress.

Postweaning intermittent sleep deprivation enhances defensive attack in adult female mice via the microbiota-gut-brain axis.

Sleep is one of the most important physiological activities in life and promotes the growth and development of an individual. In modern society, sleep deprivation (SD), especially among adolescents, has become a common phenomenon. However, long-term SD severely affected adolescents' neurodevelopment leading to abnormal behavioral phenotypes. Clinical studies indicated that sleep problems caused increased aggressive behavior in adolescents. Aggressive behavior was subordinate to social behaviors, in which defensive attack was often the last line for survival. Meanwhile, increasing studies shown that gut microbiota regulated social behaviors by affecting specific brain regions via the gut-brain axis. However, whether postweaning intermittent SD is related to defensive attack in adulthood, and if so, whether it is mediated by the microbiota-gut-brain axis are still elusive. Combined with microbial sequencing and hippocampal metabolomics, the present study mainly investigated the long-term effects of postweaning intermittent SD on defensive attack in adult mice. Our study demonstrated that postweaning intermittent SD enhanced defensive attack and impaired long-term memory formation in adult female mice. Moreover, microbial sequencing and LC-MS analysis showed that postweaning intermittent SD altered the gut microbial composition and the hippocampal metabolic profile in female mice, respectively. Our attention has been drawn to the neuroactive ligand-receptor interaction pathway and related metabolites. In conclusion, our findings provide a new perspective on the relationship of early-life SD and defensive attack in adulthood, and also highlight the importance of sleep in early-life, especially in females.

Sex-dependent and long-lasting effects of adolescent sleep deprivation on social behaviors in adult mice.

Increasing evidence indicates that sleep deprivation (SD) can exert multiple negative effects on neuronal circuits, resulting in memory impairment, depression, and anxiety, among other consequences. The long-term effects of SD during early life on behavioral phenotypes in adulthood are still poorly understood. In this study, we investigated the long-lasting effects of SD in adolescence on social behaviors, including empathic ability and social dominance, and the role of the gut microbiota in these processes, using a series of behavioral paradigms in mice combined with 16S rRNA gene pyrosequencing. Behavioral assay results showed that SD in adolescence significantly reduced the frequency of licking, the total time spent licking, and the time spent sniffing during the emotional contagion test in male mice, effects that were not observed in female mice. These findings indicated that SD in adolescence exerts long-term, negative effects on empathic ability in mice and that this effect is sex-dependent. In contrast, SD in adolescence had no significant effect on locomotor activities, social dominance but decreased social interaction in male mice in adulthood. Meanwhile, 16S rRNA gene pyrosequencing results showed that gut microbial richness and diversity were significantly altered in adult male mice subjected to SD in adolescence. Our data provide direct evidence that SD in youth can induce alterations in empathic ability in adult male mice, which may be associated with changes in the gut microbiota. These findings highlight the long-lasting effects of sleep loss in adolescence on social behaviors in adulthood and the role played by the brain-gut axis.

The Role of "Hierarchical and Classified Prevention and Control Measures (HCPC)" Strategy for SARS-CoV-2 Delta Variant in Guangzhou: A Modeling Study.

BACKGROUND: The Delta variant of SARS-COV-2 has replaced previously circulating strains around the world in 2021. Sporadic outbreaks of the Delta variant in China have posed a concern about how to properly respond to the battle against evolving COVID-19. Here, we analyzed the "hierarchical and classified prevention and control (HCPC)" measures strategy deployed during the recent Guangzhou outbreak. METHODS: A modified susceptible-exposed-pre-symptomatic-infectious-recovered (SEPIR) model was developed and applied to study a range of different scenarios to evaluate the effectiveness of policy deployment. We simulated severe different scenarios to understand policy implementation and timing of implementation. Two outcomes were measured: magnitude of transmission and duration of transmission. The outcomes of scenario evaluations were presented relative to the reality case (i.e., 368 cases in 34 days) with 95% confidence interval (CI). RESULTS: Based on our simulation, the outbreak would become out of control with 7 million estimated infections under the assumption of the absence of any interventions than the 153 reported cases in reality in Guangzhou. The simulation on delayed implementation of interventions showed that the total case numbers would also increase by 166.67%-813.07% if the interventions were delayed by 3 days or 7 days. CONCLUSIONS: It may be concluded that timely and more precise interventions including mass testing and graded community management are effective measures for Delta variant containment in China.

A model simulation on the SARS-CoV-2 Omicron variant containment in Beijing, China.

Objective: The Omicron variant of SARS-COV-2 is replacing previously circulating variants around the world in 2022. Sporadic outbreaks of the Omicron variant into China have posed a concern how to properly response to battle against evolving coronavirus disease 2019 (COVID-19). Methods: Based on the epidemic data from website announced by Beijing Center for Disease Control and Prevention for the recent outbreak in Beijing from April 22nd to June 8th in 2022, we developed a modified SEPIR model to mathematically simulate the customized dynamic COVID-zero strategy and project transmissions of the Omicron epidemic. To demonstrate the effectiveness of dynamic-changing policies deployment during this outbreak control, we modified the transmission rate into four parts according to policy-changing dates as April 22nd to May 2nd, May 3rd to 11st, May 12th to 21st, May 22nd to June 8th, and we adopted Markov chain Monte Carlo (MCMC) to estimate different transmission rate. Then we altered the timing and scaling of these measures used to understand the effectiveness of these policies on the Omicron variant. Results: The estimated effective reproduction number of four parts were 1.75 (95% CI 1.66-1.85), 0.89 (95% CI 0.79-0.99), 1.15 (95% CI 1.05-1.26) and 0.53 (95% CI 0.48 -0.60), respectively.  In the experiment, we found that till June 8th the cumulative cases would rise to 132,609 (95% CI 59,667-250,639), 73.39 times of observed cumulative cases number 1,807 if no policy were implemented on May 3rd, and would be 3,235 (95% CI 1,909 - 4,954), increased by 79.03% if no policy were implemented on May 22nd. A 3-day delay of the implementation of policies would led to increase of cumulative cases by 58.28% and a 7-day delay would led to increase of cumulative cases by 187.00%. On the other hand, taking control measures 3 or 7 days in advance would result in merely 38.63% or 68.62% reduction of real cumulative cases. And if lockdown implemented 3 days before May 3rd, the cumulative cases would be 289 (95% CI 211-378), reduced by 84%, and the cumulative cases would be 853 (95% CI 578-1,183), reduced by 52.79% if lockdown implemented 3 days after May 3rd. Conclusion: The dynamic COVID-zero strategy might be able to effectively minimize the scale of the transmission, shorten the epidemic period and reduce the total number of infections.

GCHN-DTI: Predicting drug-target interactions by graph convolution on heterogeneous networks.

Determining the interaction of drug and target plays a key role in the process of drug development and discovery. The calculation methods can predict new interactions and speed up the process of drug development. In recent studies, the network-based approaches have been proposed to predict drug-target interactions. However, these methods cannot fully utilize the node information from heterogeneous networks. Therefore, we propose a method based on heterogeneous graph convolutional neural network for drug-target interaction prediction, GCHN-DTI (Predicting drug-target interactions by graph convolution on heterogeneous net-works), to predict potential DTIs. GCHN-DTI integrates network information from drug-target interactions, drug-drug interactions, drug-similarities, target-target interactions, and target-similarities. Then, the graph convolution operation is used in the heterogeneous network to obtain the node embedding of the drugs and the targets. Furthermore, we incorporate an attention mechanism between graph convolutional layers to combine node embedding from each layer. Finally, the drug-target interaction score is predicted based on the node embedding of the drugs and the targets. Our model uses fewer network types and achieves higher prediction performance. In addition, the prediction performance of the model will be significantly improved on the dataset with a higher proportion of positive samples. The experimental evaluations show that GCHN-DTI outperforms several state-of-the-art prediction methods.

The Effect of Co Content and Annealing Temperatures on the Resistivity in Ag-Co Films.

Ag-Co films with ultra-high resistivity were prepared on polyimide by magnetron sputtering. The effect of Co content and annealing temperatures on the resistivity and microstructure of Ag-Co films has been thoroughly investigated and the relation between resistivity and microstructure has been discussed. Results show that thicker Ag-Co films without annealing present lower resistivity due to better crystallinity. However, thin Ag-Co films (≤21 nm) annealed at 360 °C present ultra-high film resistivity because of the formation of diffusion pits on the film surface which blocks the transmission of electrons in films to increase film resistivity. Inversely, the resistivity of thick Ag-Co films (≥45 nm) annealed at 360 °C is much less than that annealed at lower than 260 °C owing to no diffusion pits. Furthermore, the addition of Co inhibits the growth of Ag grains and limits the migration of electrons in Ag-Co films further, also resulting in the increase of Ag-Co films' resistivity.

PaCAR: COVID-19 Pandemic Control Decision Making via Large-Scale Agent-Based Modeling and Deep Reinforcement Learning.

BACKGROUND: Policy makers are facing more complicated challenges to balance saving lives and economic development in the post-vaccination era during a pandemic. Epidemic simulation models and pandemic control methods are designed to tackle this problem. However, most of the existing approaches cannot be applied to real-world cases due to the lack of adaptability to new scenarios and micro representational ability (especially for system dynamics models), the huge computation demand, and the inefficient use of historical information. METHODS: We propose a novel Pandemic Control decision making framework via large-scale Agent-based modeling and deep Reinforcement learning (PaCAR) to search optimal control policies that can simultaneously minimize the spread of infection and the government restrictions. In the framework, we develop a new large-scale agent-based simulator with vaccine settings implemented to be calibrated and serve as a realistic environment for a city or a state. We also design a novel reinforcement learning architecture applicable to the pandemic control problem, with a reward carefully designed by the net monetary benefit framework and a sequence learning network to extract information from the sequential epidemiological observations, such as number of cases, vaccination, and so forth. RESULTS: Our approach outperforms the baselines designed by experts or adopted by real-world governments and is flexible in dealing with different variants, such as Alpha and Delta in COVID-19. PaCAR succeeds in controlling the pandemic with the lowest economic costs and relatively short epidemic duration and few cases. We further conduct extensive experiments to analyze the reasoning behind the resulting policy sequence and try to conclude this as an informative reference for policy makers in the post-vaccination era of COVID-19 and beyond. LIMITATIONS: The modeling of economic costs, which are directly estimated by the level of government restrictions, is rather simple. This article mainly focuses on several specific control methods and single-wave pandemic control. CONCLUSIONS: The proposed framework PaCAR can offer adaptive pandemic control recommendations on different variants and population sizes. Intelligent pandemic control empowered by artificial intelligence may help us make it through the current COVID-19 and other possible pandemics in the future with less cost both of lives and economy. HIGHLIGHTS: We introduce a new efficient, large-scale agent-based epidemic simulator in our framework PaCAR, which can be applied to train reinforcement learning networks in a real-world scenario with a population of more than 10,000,000.We develop a novel learning mechanism in PaCAR, which augments reinforcement learning with sequence learning, to learn the tradeoff policy decision of saving lives and economic development in the post-vaccination era.We demonstrate that the policy learned by PaCAR outperforms different benchmark policies under various reality conditions during COVID-19.We analyze the resulting policy given by PaCAR, and the lessons may shed light on better pandemic preparedness plans in the future.

Long-lasting effects of postweaning sleep deprivation on cognitive function and social behaviors in adult mice.

Sleep deprivation (SD) has adverse effects on physical and mental health. Recently increasing attention has been given to SD in the early-life stage. However, the effects and mechanisms of postweaning SD on cognitive function and social behaviors are still unclear. In this study, SD was conducted in mice from postnatal Day 21 (PND21) to PND42, 6 h a day. Meanwhile, changes in body weight, food and water intake were continuously monitored. Behavioral tests were carried out in adulthood of mice. The levels of serum corticosterone, the proinflammatory cytokines interleukin-1ß (IL-1ß) and tumor necrosis factor-α (TNF-α), and the anti-inflammatory cytokines interleukin-10 (IL-10), vasopressin (VP) and oxytocin (OT) were measured by ELISA. Golgi staining was used to calculate neural dendritic spine density in the dorsal hippocampus (dHPC) CA1 region and medial prefrontal cortex (mPFC). We found that postweaning SD increased the food intake and the weight of female mice. Behavioral results showed that postweaning SD caused cognitive impairment and lowered social dominance in adult male mice but not in female mice. ELISA results showed that SD increased the levels of serum corticosterone, VP and OT in male mice and serum OT in female mice. Golgi staining analysis showed that SD decreased neural dendritic spine density in the dHPC in male mice. These results suggest that postweaning SD has a long-term effect on social dominance and cognitive function in male mice, which may provide a new insight into the role of SD in regulating cognitive function and social behaviors.

A Phenogenetic Axis that Modulates Clinical Manifestation and Predicts Treatment Outcome in Primary Myeloid Neoplasms.

Although the concept of "myeloid neoplasm continuum" has long been proposed, few comparative genomics studies directly tested this hypothesis. Here we report a multi-modal data analysis of 730 consecutive newly diagnosed patients with primary myeloid neoplasm, along with 462 lymphoid neoplasm cases serving as the outgroup. Our study identified a "Pan-Myeloid Axis" along which patients, genes, and phenotypic features were all aligned in sequential order. Utilizing relational information of gene mutations along the Pan-Myeloid Axis improved prognostic accuracy for complete remission and overall survival in adult patients of de novo acute myeloid leukemia and for complete remission in adult patients of myelodysplastic syndromes with excess blasts. We submit that better understanding of the myeloid neoplasm continuum might shed light on how treatment should be tailored to individual diseases. Significance: The current criteria for disease diagnosis treat myeloid neoplasms as a group of distinct, separate diseases. This work provides genomics evidence for a "myeloid neoplasm continuum" and suggests that boundaries between myeloid neoplastic diseases are much more blurred than previously thought.

Apparent mass of the seated human body during vertical vibration in the frequency range 2-100 Hz.

We studied the apparent mass during vertical whole-body vibration in the frequency range 2-100 Hz at four magnitudes (sinusoidal sweep signals, 1.0, 1.5, 2.0 and 2.5 ms-2 r.m.s.) in 12 males and 12 females with upright and relaxed sitting postures. The first two peaks of apparent mass decreased with increasing vibration magnitude with both postures. The non-linearity characteristics became obscured at the two largest magnitudes and were less transparent with relaxed sitting posture. The peak frequencies and the normalised apparent masses were similar between males and females with both postures. The standardised three degrees-of-freedom parametric model with modified parameters was proposed to predict well the apparent mass of seated human body during vertical vibration in the frequency range 2-100 Hz and in the magnitude range 1.0-2.5 ms-2 r.m.s. Practitioner summary: This study shows the frequency-dependence and magnitude-dependence of biodynamic responses in the frequency range of 2-100 Hz. The magnitude of apparent mass at frequencies above 20 Hz may not be negligible. The proposed 3 DOF model with modified parameters would help with understanding and developing the human-seat system. Abbreviations: WBV: whole-body vibration; DOF: degrees-of-freedom; CMIFs: complex mode indicator functions.

Analysis of the Gut Microflora in Patients With Parkinson's Disease.

This study was conducted to explore the composition of the fecal microflora of Chinese Parkinson's disease (PD) patients, as well as to explore links between PD clinical features and antiparkinsonian medications on the gut microflora. Seventy-two PD cases [59 patients suffering from PD for >1 year (OPD) and 13 new PD (NPD) patients] were studied. Microflora communities in the feces of the patients and corresponding healthy controls (HCs) were examined using high-throughput Illumina MiSeq sequencing targeting the 16S rRNA gene. The gut microflora of OPD patients contained high levels of Rikenellaceae compared to corresponding HCs. In addition, significantly higher levels of Turicibacteraceae were found in the NPD group compared to the corresponding HCs. The genera Turicibacter and Prevotella were significantly correlated with the PD severity scores. Our findings that some fecal microflora were closely related to PD clinical characteristics may enhance our understanding of the pathogenesis and treatment of PD.

An examination of data from the American Gut Project reveals that the dominance of the genus Bifidobacterium is associated with the diversity and robustness of the gut microbiota.

Bifidobacterium and Lactobacillus are beneficial for human health, and many strains of these two genera are widely used as probiotics. We used two large datasets published by the American Gut Project (AGP) and a gut metagenomic dataset (NBT) to analyze the relationship between these two genera and the community structure of the gut microbiota. The meta-analysis showed that Bifidobacterium, but not Lactobacillus, is among the dominant genera in the human gut microbiota. The relative abundance of Bifidobacterium was elevated when Lactobacillus was present. Moreover, these two genera showed a positive correlation with some butyrate producers among the dominant genera, and both were associated with alpha diversity, beta diversity, and the robustness of the gut microbiota. Additionally, samples harboring Bifidobacterium present but no Lactobacillus showed higher alpha diversity and were more robust than those only carrying Lactobacillus. Further comparisons with other genera validated the important role of Bifidobacterium in the gut microbiota robustness. Multivariate analysis of 11,744 samples from the AGP dataset suggested Bifidobacterium to be associated with demographic features, lifestyle, and disease. In summary, Bifidobacterium members, which are promoted by dairy and whole-grain consumption, are more important than Lactobacillus in maintaining the diversity and robustness of the gut microbiota.

Antibiotic resistance gene reservoir in live poultry markets.

OBJECTIVES: The heavy use of antibiotics in farm animals contributes to the enrichment and spread of antibiotic resistance genes (ARGs) in "one-health" settings. Numerous ARGs have been identified in livestock-associated environments but not in Chinese live poultry markets (LPMs). METHODS: We collected 753 poultry fecal samples from LPMs of 18 provinces and municipalities in China and sequenced the metagenomes of 130 samples. Bioinformatic tools were used to construct the gene catalog and analyze the ARG content. PCR amplification and Sanger sequencing were used to survey the distribution of mcr-1 gene in all 753 fecal samples. RESULTS: We found that a low number of genes but a high percentage of gene functions were shared among the poultry, human and pig gut gene catalogs. The poultry gut possessed 539 ARGs which were classified into 235 types. Both the ARG number and abundance were significantly higher in poultry than that in either pigs or humans. Fourteen ARG types were found present in all 130 samples, and tetracycline resistance (TcR) genes were the most abundant ARGs in both animals and humans. Moreover, 59.63% LPM samples harbored the colistin resistance gene mcr-1, and other mcr gene variants were also found. CONCLUSIONS: We demonstrated that the Chinese LPMs is a repository for ARGs, posing a high risk for ARG dissemination from food animals to humans under such a trade system, which has not been addressed before.

The Gut Microbiome Signatures Discriminate Healthy From Pulmonary Tuberculosis Patients.

Cross talk occurs between the human gut and the lung through a gut-lung axis involving the gut microbiota. However, the signatures of the human gut microbiota after active Mycobacterium tuberculosis infection have not been fully understood. Here, we investigated changes in the gut microbiota in tuberculosis (TB) patients by shotgun sequencing the gut microbiomes of 31 healthy controls and 46 patients. We observed a dramatic changes in gut microbiota in tuberculosis patients as reflected by significant decreases in species number and microbial diversity. The gut microbiota of TB patients were mostly featured by the striking decrease of short-chain fatty acids (SCFAs)-producingbacteria as well as associated metabolic pathways. A classification model based on the abundance of three species, Haemophilus parainfluenzae, Roseburia inulinivorans, and Roseburia hominis, performed well for discriminating between healthy and diseased patients. Additionally, the healthy and diseased states can be distinguished by SNPs in the species of B. vulgatus. We present a comprehensive profile of changes in the microbiota in clinical TB patients. Our findings will shed light on the design of future diagnoses and treatments for M. tuberculosis infections.