Central South University of Forestry and Technology

fertilization effect. Six Earth system models have consistently projected continuous increases of VPD throughout the current century. Our results highlight that the impacts of VPD on vegetation growth should be adequately considered to assess ecosystem responses to future climate conditions.

Abstract Endowing materials with specific functions that are not readily available is always of great importance, but extremely challenging. Co 4 N, with its beneficial metallic characteristics, has been proved to be highly active for the oxidation of water, while it is notoriously poor for catalyzing the hydrogen evolution reaction (HER), because of its unfavorable d‐band energy level. Herein, we successfully endow Co 4 N with prominent HER catalytic capability by tailoring the positions of the d‐band center through transition‐metal doping. The V‐doped Co 4 N nanosheets display an overpotential of 37 mV at 10 mA cm −2 , which is substantially better than Co 4 N and even close to the benchmark Pt/C catalysts. XANES, UPS, and DFT calculations consistently reveal the enhanced performance is attributed to the downshift of the d‐band center, which helps facilitate the H desorption. This concept could provide valuable insights into the design of other catalysts for HER and beyond.

With a pace of about twice the observed rate of global warming, the temperature on the Qinghai-Tibetan Plateau (Earth's 'third pole') has increased by 0.2 °C per decade over the past 50 years, which results in significant permafrost thawing and glacier retreat. Our review suggested that warming enhanced net primary production and soil respiration, decreased methane (CH(4)) emissions from wetlands and increased CH(4) consumption of meadows, but might increase CH(4) emissions from lakes. Warming-induced permafrost thawing and glaciers melting would also result in substantial emission of old carbon dioxide (CO(2)) and CH(4). Nitrous oxide (N(2)O) emission was not stimulated by warming itself, but might be slightly enhanced by wetting. However, there are many uncertainties in such biogeochemical cycles under climate change. Human activities (e.g. grazing, land cover changes) further modified the biogeochemical cycles and amplified such uncertainties on the plateau. If the projected warming and wetting continues, the future biogeochemical cycles will be more complicated. So facing research in this field is an ongoing challenge of integrating field observations with process-based ecosystem models to predict the impacts of future climate change and human activities at various temporal and spatial scales. To reduce the uncertainties and to improve the precision of the predictions of the impacts of climate change and human activities on biogeochemical cycles, efforts should focus on conducting more field observation studies, integrating data within improved models, and developing new knowledge about coupling among carbon, nitrogen, and phosphorus biogeochemical cycles as well as about the role of microbes in these cycles.

Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) properties and various toxicities (T). Therefore, rapid ADMET evaluation is urgently needed to minimize failures in the drug discovery process. Here, we developed a web-based platform called ADMETlab for systematic ADMET evaluation of chemicals based on a comprehensively collected ADMET database consisting of 288,967 entries. Four function modules in the platform enable users to conveniently perform six types of drug-likeness analysis (five rules and one prediction model), 31 ADMET endpoints prediction (basic property: 3, absorption: 6, distribution: 3, metabolism: 10, elimination: 2, toxicity: 7), systematic evaluation and database/similarity searching. We believe that this web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures. The ADMETlab web platform is designed based on the Django framework in Python, and is freely accessible at http://admet.scbdd.com/ .

Abstract There is currently enormous and growing demand for flexible electronics for personalized mobile equipment, human–machine interface units, wearable medical‐healthcare systems, and bionic intelligent robots. Cellulose is a well‐known natural biopolymer that has multiple advantages including low cost, renewability, easy processability, and biodegradability, as well as appealing mechanical performance, dielectricity, piezoelectricity, and convertibility. Because of its multiple merits, cellulose is frequently used as a substrate, binder, dielectric layer, gel electrolyte, and derived carbon material for flexible electronic devices. Leveraging the advantages of cellulose to design advanced functional materials will have a significant impact on portable intelligent electronics. Herein, the unique molecular structure and nanostructures (nanocrystals, nanofibers, nanosheets, etc.) of cellulose are briefly introduced, the structure–property–application relationships of cellulosic materials summarized, and the processing technologies for fabricating cellulose‐based flexible electronics considered. The focus then turns to the recent advances of cellulose‐based functional materials toward emerging intelligent electronic devices including flexible sensors, optoelectronic devices, field‐effect transistors, nanogenerators, electrochemical energy storage devices, biomimetic electronic skins, and biological detection devices. Finally, an outlook of the potential challenges and future prospects for developing cellulose‐based wearable devices and bioelectronic systems is presented.

Biodiversity experiments have shown that species loss reduces ecosystem functioning in grassland. To test whether this result can be extrapolated to forests, the main contributors to terrestrial primary productivity, requires large-scale experiments. We manipulated tree species richness by planting more than 150,000 trees in plots with 1 to 16 species. Simulating multiple extinction scenarios, we found that richness strongly increased stand-level productivity. After 8 years, 16-species mixtures had accumulated over twice the amount of carbon found in average monocultures and similar amounts as those of two commercial monocultures. Species richness effects were strongly associated with functional and phylogenetic diversity. A shrub addition treatment reduced tree productivity, but this reduction was smaller at high shrub species richness. Our results encourage multispecies afforestation strategies to restore biodiversity and mitigate climate change.

Advanced flexible batteries with high energy density and long cycle life are an important research target. Herein, the first paradigm of a high‐performance and stable flexible rechargeable quasi‐solid‐state Zn–MnO 2 battery is constructed by engineering MnO 2 electrodes and gel electrolyte. Benefiting from a poly(3,4‐ethylenedioxythiophene) (PEDOT) buffer layer and a Mn 2+ ‐based neutral electrolyte, the fabricated Zn–MnO 2 @PEDOT battery presents a remarkable capacity of 366.6 mA h g −1 and good cycling performance (83.7% after 300 cycles) in aqueous electrolyte. More importantly, when using PVA/ZnCl 2 /MnSO 4 gel as electrolyte, the as‐fabricated quasi‐solid‐state Zn–MnO 2 @PEDOT battery remains highly rechargeable, maintaining more than 77.7% of its initial capacity and nearly 100% Coulombic efficiency after 300 cycles. Moreover, this flexible quasi‐solid‐state Zn–MnO 2 battery achieves an admirable energy density of 504.9 W h kg −1 (33.95 mW h cm −3 ), together with a peak power density of 8.6 kW kg −1 , substantially higher than most recently reported flexible energy‐storage devices. With the merits of impressive energy density and durability, this highly flexible rechargeable Zn–MnO 2 battery opens new opportunities for powering portable and wearable electronics.

During their lifetime, plants encounter numerous biotic and abiotic stresses with diverse modes of attack. Phytohormones, including salicylic acid (SA), ethylene (ET), jasmonate (JA), abscisic acid (ABA), auxin (AUX), brassinosteroid (BR), gibberellic acid (GA), cytokinin (CK) and the recently identified strigolactones (SLs), orchestrate effective defense responses by activating defense gene expression. Genetic analysis of the model plant Arabidopsis thaliana has advanced our understanding of the function of these hormones. The SA- and ET/JA-mediated signaling pathways were thought to be the backbone of plant immune responses against biotic invaders, whereas ABA, auxin, BR, GA, CK and SL were considered to be involved in the plant immune response through modulating the SA-ET/JA signaling pathways. In general, the SA-mediated defense response plays a central role in local and systemic-acquired resistance (SAR) against biotrophic pathogens, such as Pseudomonas syringae, which colonize between the host cells by producing nutrient-absorbing structures while keeping the host alive. The ET/JA-mediated response contributes to the defense against necrotrophic pathogens, such as Botrytis cinerea, which invade and kill hosts to extract their nutrients. Increasing evidence indicates that the SA- and ET/JA-mediated defense response pathways are mutually antagonistic.

Rice grain with excessive cadmium (Cd) is a major source of dietary Cd intake and a serious threat to health for people who consume rice as a staple food. The development of elite rice cultivars with consistently low Cd content is challenging for conventional breeding approaches, and new strategies urgently need to be developed. Here, we report the development of new indica rice lines with low Cd accumulation and no transgenes by knocking out the metal transporter gene OsNramp5 using CRISPR/Cas9 system. Hydroponic culture showed that Cd concentrations in shoots and roots of osnramp5 mutants were dramatically decreased, resulting in rescue of impaired growth in high Cd condition. Cd-contaminated paddy field trials demonstrated that Cd concentration in osnramp5 grains was consistently less than 0.05 mg/kg, in contrast to high Cd concentrations from 0.33 mg/kg to 2.90 mg/kg in grains of Huazhan (the wild-type indica rice). In particular, the plant yield was not significantly affected in osnramp5 mutants. Furthermore, we developed promising hybrid rice lines with extremely low Cd content in grains. Our work supplies a practical approach to developing Cd pollution-safe indica rice cultivars that minimizes Cd contamination risk in grains.

Identification of catalytic sites for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) in carbon materials remains a great challenge. Here, we construct a pyridinic-N-dominated doped graphene with abundant vacancy defects. The optimized sample with an ultrahigh pore volume (3.43 cm3 g–1) exhibits unprecedented ORR activity with a half-wave potential of 0.85 V in alkaline. For the first time, density functional theory results indicate that the quadri-pyridinic N-doped carbon site synergized with a vacancy defect is the active site, which presents the lowest overpotential of 0.28 V for ORR and 0.28 V for OER. The primary Zn–air batteries display a maximum power density of 115.2 mW cm–2 and an energy density as high as 872.3 Wh kg–1. The rechargeable Zn–air batteries illustrate a low discharge–charge overpotential and high stability (>78 h). This work provides new insight into the correlation between the N configuration synergized with a vacancy defect in electrocatalysis.

Integration of artificial intelligence (AI) techniques in wireless infrastructure, real-time collection, and processing of end-user devices is now in high demand. It is now superlative to use AI to detect and predict pandemics of a colossal nature. The Coronavirus disease 2019 (COVID-19) pandemic, which originated in Wuhan China, has had disastrous effects on the global community and has overburdened advanced healthcare systems throughout the world. Globally; over 4,063,525 confirmed cases and 282,244 deaths have been recorded as of 11th May 2020, according to the European Centre for Disease Prevention and Control agency. However, the current rapid and exponential rise in the number of patients has necessitated efficient and quick prediction of the possible outcome of an infected patient for appropriate treatment using AI techniques. This paper proposes a fine-tuned Random Forest model boosted by the AdaBoost algorithm. The model uses the COVID-19 patient's geographical, travel, health, and demographic data to predict the severity of the case and the possible outcome, recovery, or death. The model has an accuracy of 94% and a F1 Score of 0.86 on the dataset used. The data analysis reveals a positive correlation between patients' gender and deaths, and also indicates that the majority of patients are aged between 20 and 70 years.

The last five years have seen a leap in the development of information technology and social media. Seeking health information online has become popular. It has been widely accepted that online health information seeking behavior has a positive impact on health information consumers. Due to its importance, online health information seeking behavior has been investigated from different aspects. However, there is lacking a systematic review that can integrate the findings of the most recent research work in online health information seeking, and provide guidance to governments, health organizations, and social media platforms on how to support and promote this seeking behavior, and improve the services of online health information access and provision. We therefore conduct this systematic review. The Google Scholar database was searched for existing research on online health information seeking behavior between 2016 and 2021 to obtain the most recent findings. Within the 97 papers searched, 20 met our inclusion criteria. Through a systematic review, this paper identifies general behavioral patterns, and influencing factors such as age, gender, income, employment status, literacy (or education) level, country of origin and places of residence, and caregiving role. Facilitators (i.e., the existence of online communities, the privacy feature, real-time interaction, and archived health information format), and barriers (i.e., low health literacy, limited accessibility and information retrieval skills, low reliable, deficient and elusive health information, platform censorship, and lack of misinformation checks) to online health information seeking behavior are also discovered.

The objectives of the present study were to investigate heavy metal accumulation in 22 vegetable species and to assess the human health risks of vegetable consumption. Six vegetable types were cultivated on farmland contaminated with heavy metals (Pb, Cd, Cu, Zn, and As). The target hazard quotient (THQ) method was used to assess the human health risks posed by heavy metals through vegetable consumption. Clear differences were found in the concentrations of heavy metals in edible parts of the different vegetables. The concentrations of heavy metals decreased in the sequence as leafy vegetables > stalk vegetables/root vegetables/solanaceous vegetables > legume vegetables/melon vegetables. The ability of leafy vegetables to uptake and accumulate heavy metals was the highest, and that of melon vegetables was the lowest. This indicated that the low accumulators (melon vegetables) were suitable for being planted on contaminated soil, while the high accumulators (leafy vegetables) were unsuitable. In Shizhuyuan area, China, the total THQ values of adults and children through consumption of vegetables were 4.12 and 5.41, respectively, suggesting that the residents may be facing health risks due to vegetable consumption, and that children were vulnerable to the adverse effects of heavy metal ingestion.

Cellulose nanocrystals and cellulose nanofibers with I and II crystalline allomorphs (designated as CNC I, CNC II, CNF I, and CNF II) were isolated from bleached wood fibers by alkaline pretreatment and acid hydrolysis. The effects of concentration, particle size, surface charge, and crystal structure on the lyophilization-induced self-assembly of cellulose particles in aqueous suspensions were studied. Within the concentration range of 0.5 to 1.0 wt %, cellulose particles self-organized into lamellar structured foam composed of aligned membrane layers with widths between 0.5 and 3 μm. At 0.05 wt %, CNC I, CNF I, CNC II, and CNF II self-assembled into oriented ultrafine fibers with mean diameters of 0.57, 1.02, 1.50, and 1.00 μm, respectively. The size of self-assembled fibers became larger when more hydroxyl groups and fewer sulfates (weaker electrostatic repulsion) were on cellulose surfaces. Possible formation mechanism was inferred from ice growth and interaction between cellulose nanoparticles in liquid-crystalline suspensions.

The present study aims to investigate the structure–morphology–rheology relationships for cellulose nanoparticles (CNPs), including cellulose nanofibers (CNFs) and cellulose nanocrystals (CNCs). CNCs were extracted from never dried CNFs using sulfuric acid with controlled hydrolysis time. The crystalline structure, surface charge, morphology, and rheological behavior of the CNPs were measured and contrasted. The CNF suspensions exhibited rigid solid-like viscoelastic behavior even at a low concentration due to the formation of a highly entangled network. Upon acid hydrolysis, the network of rigid, long, and highly entangled nanofibers was eliminated, resulting in a significant loss of viscoelastic properties. Both steady-state and dynamic rheological measurements showed that the rheological behavior of the CNC suspensions was strongly dependent on the concentration and acid hydrolysis time. The CNC suspensions exhibited elastic gel-like rheological behavior at high concentrations but viscous liquid-like rheological behavior at low concentrations. Longer acid hydrolysis time produced CNCs with a lower aspect ratio, leading to higher critical transition concentration for the formation of anisotropic phase. The aspect ratio of CNCs was predicted from the intrinsic viscosity using the Simha’s equation. The theoretically predicted aspect ratio values corresponded well with the transmission electron microscopy results. Finally, the network of CNF and CNC suspensions were schematically proposed.

Abstract Metal sulfides for hydrogen evolution catalysis typically suffer from unfavorable hydrogen desorption properties due to the strong interaction between the adsorbed H and the intensely electronegative sulfur. Here, we demonstrate a general strategy to improve the hydrogen evolution catalysis of metal sulfides by modulating the surface electron densities. The N modulated NiCo 2 S 4 nanowire arrays exhibit an overpotential of 41 mV at 10 mA cm −2 and a Tafel slope of 37 mV dec −1 , which are very close to the performance of the benchmark Pt/C in alkaline condition. X-ray photoelectron spectroscopy, synchrotron-based X-ray absorption spectroscopy, and density functional theory studies consistently confirm the surface electron densities of NiCo 2 S 4 have been effectively manipulated by N doping. The capability to modulate the electron densities of the catalytic sites could provide valuable insights for the rational design of highly efficient catalysts for hydrogen evolution and beyond.

Abstract The study of cost‐efficient and high‐performance electrocatalysts for oxygen evolution reaction (OER) has attracted much attention. Here, porous microrod arrays constructed by carbon‐confined NiCo@NiCoO 2 core@shell nanoparticles (NiCo@NiCoO 2 /C PMRAs) are fabricated by the reductive carbonization of bimetallic (Ni, Co) metal–organic framework microrod arrays (denoted as NiCo‐MOF MRAs) and subsequent controlled oxidative calcination. They successfully combine the desired merits including large specific surface areas, high conductivity, and multiple electrocatalytic active sites for OER. In addition, the oxygen vacancies in NiCo@NiCoO 2 /C PMRAs significantly improve the conductivity of NiCoO 2 and accelerate the kinetics of OER. The above advantages obviously enhance the electrocatalytic performance of NiCo@NiCoO 2 /C PMRAs. The experimental results demonstrate that the NiCo@NiCoO 2 /C PMRAs as electrocatalysts exhibit high catalytic activity, low overpotential, and high stability for OER in alkaline media. The strategy reported will open up a new route for the fabrication of porous bimetallic composite electrocatalysts derived from MOFs with controllable morphology for electrochemical energy conversion devices.

Primary lung cancer is one of the most common malignant tumors in China. Approximately 60% of lung cancer patients have distant metastasis at the initial diagnosis, so it is necessary to find new tumor markers for early diagnosis and individualized treatment. Tumor markers contribute to the early diagnosis of lung cancer and play important roles in early detection and treatment, as well as in precision medicine, efficacy monitoring, and prognosis prediction. The pathological diagnosis of lung cancer in small biopsy specimens determines whether there are tumor cells in the biopsy and tumor type. Because biopsy is traumatic and the compliance of patients with multiple biopsies is poor, liquid biopsy has become a hot research direction. Liquid biopsies are advantageous because they are nontraumatic, easy to obtain, reflect the overall state of the tumor, and allow for real-time monitoring. At present, liquid biopsies mainly include circulating tumor cells, circulating tumor DNA, exosomes, microRNA, circulating RNA, tumor platelets, and tumor endothelial cells. This review introduces the research progress and clinical application prospect of liquid biopsy technology for lung cancer.

Agroforestry integrates woody perennials with arable crops, livestock, or fodder in the same piece of land, promoting the more efficient utilization of resources as compared to monocropping via the structural and functional diversification of components. This integration of trees provides various soil-related ecological services such as fertility enhancements and improvements in soil physical, biological, and chemical properties, along with food, wood, and fodder. By providing a particular habitat, refugia for epigenic organisms, microclimate heterogeneity, buffering action, soil moisture, and humidity, agroforestry can enhance biodiversity more than monocropping. Various studies confirmed the internal restoration potential of agroforestry. Agroforestry reduces runoff, intercepts rainfall, and binds soil particles together, helping in erosion control. This trade-off between various non-cash ecological services and crop production is not a serious constraint in the integration of trees on the farmland and also provides other important co-benefits for practitioners. Tree-based systems increase livelihoods, yields, and resilience in agriculture, thereby ensuring nutrition and food security. Agroforestry can be a cost-effective and climate-smart farming practice, which will help to cope with the climate-related extremities of dryland areas cultivated by smallholders through diversifying food, improving and protecting soil, and reducing wind erosion. This review highlighted the role of agroforestry in soil improvements, microclimate amelioration, and improvements in productivity through agroforestry, particularly in semi-arid and degraded areas under careful consideration of management practices.

Significance Estimates of nutrient allocation in different plant tissues and the relationships between the nutrient contents and photosynthetic capacity are critical to predicting ecosystem carbon sequestration under global change. Here, we provide an assessment of large-scale patterns of community-level nitrogen and phosphorus concentrations in different plant tissues and then examine how nutrient allocations are coupled with plant productivity. The results show that nutrient concentrations in leaves are less responsive to abiotic environments than those in woody stems and roots (stable leaf nutrient concentration hypothesis); the relationships between vegetation primary productivity and leaf nutrient contents are stronger when less nutrients are allocated to the woody tissues (productivity–nutrient allocation hypothesis) and are stronger in deciduous than in evergreen vegetation (productivity–leaf lifespan hypothesis).