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Abstract Although computerized cognitive training (CCT) is an effective digital intervention for cognitive impairment, its dose-response relationship is understudied. This retrospective cohort study explores the association between training dose and cognitive improvement to find the optimal CCT dose. From 2017 to 2022, 8,709 participants with subjective cognitive decline, mild cognitive impairment, and mild dementia were analyzed. CCT exposure varied in daily dose and frequency, with cognitive improvement measured weekly using Cognitive Index. A mixed-effects model revealed significant Cognitive Index increases across most dose groups before reaching the optimal dose. For participants under 60 years, the optimal dose was 25 to

Abstract Colonial cities in Asia and Africa, developed under the dual influence of native and sovereign cultures during the colonial era, exhibit unique urban morphological characteristics and reflect the planning ideologies of diverse cultures. Thus, the morphological study of colonial cities in Asia and Africa is crucial for understanding and identifying the historical and cultural value of these cities, which in turn enables the formulation of precise conservation strategies. In light of this, the study develops an urban morphological analysis methodology comprising "Colonial Background Analysis—Morphological Characteristics Analysis—Driving Factor Extraction" based on the Conzenian Approach, which is used to examine the morphology of 21 typical colonial cities in Asia and Africa across various colonial periods. As a result, "Dual-City" emerges as the core spatial characteristic of colonial cities in Asia and Africa, reflecting the morphological differences in road layouts, urban fabric, and urban cores between native and European zones. Additionally, as native settlement sizes, social structures, and cultural identities differ between cities, three major spatial patterns of the "Dual-City" model can be identified: separated, mediated, and integrated spatial patterns, resulting from the varied planning approaches applied by colonizers. Furthermore, suggestions for the conservation of colonial heritage are proposed based on the driving factors analysis from the morphological study.

Abstract During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.

Abstract Despite being one of the most prevalent RNA modifications, the role of N6‐methyladenosine (m6A) in amyotrophic lateral sclerosis (ALS) remains ambiguous. In this investigation, we explore the contribution of genetic defects of m6A‐related genes to ALS pathogenesis. We scrutinized the mutation landscape of m6A genes through a comprehensive analysis of whole‐exome sequencing cohorts, encompassing 508 ALS patients and 1660 population‐matched controls. Our findings reveal a noteworthy enrichment of RNA binding motif protein X‐linked (RBMX) variants among ALS patients, with a significant correlation between pathogenic m6A variants and adverse clinical outcomes. Furthermore, Rbmx knockdown in NSC‐34 cells overexpressing mutant TDP43Q331K results in cell death mediated by an augmented p53 response. Similarly, RBMX knockdown in ALS motor neurons derived from induced pluripotent stem cells (iPSCs) manifests morphological defects and activation of the p53 pathway. Transcriptional analysis using publicly available single‐cell sequencing data from the primary motor cortex indicates that RBMX‐regulated genes selectively influence excitatory neurons and exhibit enrichment in ALS‐implicated pathways. Through integrated analyses, our study underscores the emerging roles played by RBMX in ALS, suggesting a potential nexus between the disease and dysregulated m6A‐mediated mRNA metabolism.

Combining green warehousing with wind-solar-storage systems can enhance economic power consumption, energy saving, and emission reduction in green warehousing. To achieve efficient and stable operation of the wind-solar-storage microgrid, this paper proposes an optimal microgrid scheduling strategy based on the Improved Sparrow Algorithm (ISSA). Firstly, a comprehensive benefit model is established based on the economic and environmental benefits of microgrid daily operation. Then, an innovative improved sparrow search algorithm is proposed, which aims to improve the global search and local search capability of the microgrid scheduling problem by introducing improvements such as Logistic-Circle chaotic mapping, Bottle Sea Sheath swarm optimization algorithm, dynamic inertia weights, water wave dynamic factor, and Cauchy-Gaussian variational strategy. Finally, the microgrid optimal scheduling model is solved by the improved sparrow search algorithm and compared with other algorithms. In this paper, Matlab 2016b is used for simulation, and the simulation results show that the ISSA algorithm outperforms other algorithms in terms of solution stability and optimization search capability. Under three modes of operation, ISSA improves the microgrid operation revenue by 6.29%, 5.98%, and 6.31% at least. Therefore, the optimal scheduling scheme obtained based on ISSA improves the daily operating total revenue and the system operation stability of the microgrid.

BackgroundEnterostomy is important for radical resection of colorectal cancer (CRC). Nevertheless, the notable occurrence of complications linked to enterostomy results in a reduction in patients’ quality of life and impedes adjuvant therapy. This study sought to forecast early stoma-related complications (ESRCs) by leveraging easily accessible nutrition-inflammation markers in CRC patients.MethodsThis study involved 470 individuals with colorectal cancer who underwent intestinal ostomy at Changhai Hospital Affiliated with Naval Medical University as the internal cohort. Between January 2016 and December 2018, the patients were enrolled and randomly allocated into a primary training group and a secondary validation group, with a ratio of 2:1 being upheld. The research encompassed collecting data on each patient’s clinical and pathological status, along with preoperative laboratory results. Independent risk factors were identified through Lasso regression and multivariate analysis, leading to the development of clinical models represented by a nomogram. The model’s utility was assessed using decision curve analysis, calibration curve, and ROC curve. The final model was validated using an external validation set of 179 individuals from January 2015 to December 2021.ResultsAmong the internal cohort, stoma complications were observed in 93 cases. Multivariate regression analysis confirmed that age, stoma site, and elevated markers (Mon, NAR, and GLR) in conjunction with diminished markers (GLB and LMR) independently contributed to an increased risk of ESRCs. The clinical model was established based on these seven factors. The training, internal, and external validation groups exhibited ROC curve areas of 0.839, 0.812, and 0.793, respectively. The calibration curve showed good concordance among the forecasted model with real incidence of ostomy complications. The model displayed outstanding predictive capability and is deemed applicable in clinical settings, as evidenced by Decision Curve Analysis.ConclusionThis study identified nutrition-inflammation markers (GLB, NAR, and GLR) in combination with demographic data as crucial predictors for forecasting ESRCs in colorectal cancer patients. A novel prognostic model was formulated and validated utilizing these markers.

Abstract Central African evergreen broadleaved forests around the equator exhibit a double annual cycle for canopy phenology and carbon uptake seasonality. The underlying drivers of this behavior are poorly understood and the double seasonality is not captured by land surface models (LSM). In this study, we developed a new leaf phenology module into the ORCHIDEE LSM (hereafter ORCHIDEE‐AFP), which utilizes short‐wave incoming radiation (SWd) as the main driver of leaf shedding and partial rejuvenation of the canopy, to simulate the double seasonality of central African forests. The ORCHIDEE‐AFP model has been evaluated by using field data from two forest sites and satellite observations of the enhanced vegetation index (EVI), which is a proxy of young leaf area index (LAIYoung) with leafage less than 6 months, as well as six products of GPP or GPP proxies. Results demonstrate that ORCHIDEE‐AFP successfully reproduces observed leaf turnover (R = 0.45) and young leaf abundance (R = 0.74), and greatly improve the representation of the bimodal leaf phenology. The proportion of grid cells with a significant positive correlation between the seasonality of modeled LAIYoung and observed EVI increased from 0.2% in the standard model to 27% in the new model. For photosynthesis, the proportions of grid cells with significant positive correlations between modeled and observed seasonality range from 26% to 65% across the six GPP evaluation products. The improved performance of the ORCHIDEE‐AFP model in simulating leaf phenology and photosynthesis of central African forests will allow a more accurate assessment of the impacts of climate change in tropical forests.

Summary: Background: Hospitals in China are classified into tiers (1, 2 or 3), with the largest (tier 3) having more equipment and specialist staff. Differential health insurance cost-sharing by hospital tier (lower deductibles and higher reimbursement rates in lower tiers) was introduced to reduce overcrowding in higher tier hospitals, promote use of lower tier hospitals, and limit escalating healthcare costs. However, little is known about the effects of differential cost-sharing in health insurance schemes on choice of hospital tiers. Methods: In a 9-year follow-up of a prospective study of 0.5 M adults from 10 areas in China, we examined the associations between differential health insurance cost-sharing and choice of hospital tiers for patients with a first hospitalisation for stroke or ischaemic heart disease (IHD) in 2009–2017. Analyses were performed separately in urban areas (stroke: n = 20,302; IHD: n = 19,283) and rural areas (stroke: n = 21,130; IHD: n = 17,890), using conditional logit models and adjusting for individual socioeconomic and health characteristics. Findings: About 64–68% of stroke and IHD cases in urban areas and 27–29% in rural areas chose tier 3 hospitals. In urban areas, higher reimbursement rates in each tier and lower tier 3 deductibles were associated with a greater likelihood of choosing their respective hospital tiers. In rural areas, the effects of cost-sharing were modest, suggesting a greater contribution of other factors. Higher socioeconomic status and greater disease severity were associated with a greater likelihood of seeking care in higher tier hospitals in urban and rural areas. Interpretation: Patient choice of hospital tiers for treatment of stroke and IHD in China was influenced by differential cost-sharing in urban areas, but not in rural areas. Further strategies are required to incentivise appropriate health seeking behaviour and promote more efficient hospital use. Funding: Wellcome Trust, Medical Research Council, British Heart Foundation, Cancer Research UK, Kadoorie Charitable Foundation, China Ministry of Science and Technology, and National Natural Science Foundation of China.

Abstract Designing promoters with desirable properties is essential in synthetic biology. Human experts are skilled at identifying strong explicit patterns in small samples, while deep learning models excel at detecting implicit weak patterns in large datasets. Biologists have described the sequence patterns of promoters via transcription factor binding sites (TFBSs). However, the flanking sequences of cis-regulatory elements, have long been overlooked and often arbitrarily decided in promoter design. To address this limitation, we introduce DeepSEED, an AI-aided framework that efficiently designs synthetic promoters by combining expert knowledge with deep learning techniques. DeepSEED has demonstrated success in improving the properties of Escherichia coli constitutive, IPTG-inducible, and mammalian cell doxycycline (Dox)-inducible promoters. Furthermore, our results show that DeepSEED captures the implicit features in flanking sequences, such as k-mer frequencies and DNA shape features, which are crucial for determining promoter properties.

Abstract Although the biophysical effects of afforestation or deforestation on local climate are recognized, the biophysical consequences of seasonal and long-term dynamics in forests on understory microclimate, which creates microrefugia for forest organisms under global warming, remain less well understood. To fill this research gap, we combined a three-layered (i.e., canopy, forest air space and understory soil) land surface energy balance model and Intrinsic Biophysical Mechanism Model and quantify seasonal (warm minus cool seasons) and long-term changes (later minus former periods) in the biophysical effects of forest dynamics on understory air temperature (ΔT a) and soil surface temperature (ΔT s). We found that high latitudes forests show strongest negative seasonal variations in both ΔT a and ΔT s, followed by moderate latitudes forests. In contrast, low latitudes forests exhibit positive seasonal variations in ΔT a and weak negative seasonal variations in ΔT s. For the long-term variations, ΔT s increases systematically at all three latitudes. However, the situation differs greatly for ΔT s, with a weak increase at low and moderate latitudes, but a slight decrease at high latitudes. Overall, changes in sensible and latent heat fluxes induced by forest dynamics (such as leaf area index), by altering the aerodynamic resistances of canopy and soil surface layers, are the main factors driving changes in forest microclimate effects. In addition, this study also develops an aerodynamic resistance coefficient $${f}_{{\rm{r}}}^{1}$$ f r 1 to combine the air temperature effects and surface soil temperature effects and proposes an indicator – ΔT Su, that is, $$\Delta {T}_{{\rm{Su}}}=\Delta {T}_{{\rm{s}}}+(\frac{1}{{f}_{{\rm{r}}}^{1}}-1)\Delta {T}_{{\rm{a}}}$$ Δ T Su = Δ T s + ( 1 f r 1 − 1 ) Δ T a , as a possible benchmark for evaluating the total biophysical effects of forests on temperatures.

It is a vital technical challenge to extract lithium from salt-lake brine which has very high Mg2+ / Li+ mass ratio via green and low-cost methods, as these two cations have quite similar ionic hydration radius. Positively charged nanofiltration membranes can separate Li+ and Mg2+ through Donnan exclusion. In this work, a kind of hollow fiber nanofiltration membrane with positively charged skin layer was successfully fabricated via interfacial polymerization followed by a surface modification with branched polyethyleneimine (BPEI). The resultant membrane has a large number of amine groups, and thus shows positively charged surface with high rejection for divalent cation ions via Donnan exclusion. This gives it very high selectivity for the separation of Li+ ions from salt-lake brine. Under optimized conditions, it achieves a water permeance of up to 126.2 L m-2 h-1 MPa−1 at a transmembrane pressure difference of 4 bar, and a MgCl2 rejection of 94.6% with 2000 mg L-1 aqueous MgCl2 solution as feed. Meanwhile, it achieves a Mg2+ / Li+ selectivity of nearly 24 for MgCl2 and LiCl salt mixture solution with an overall concentration of 2000 mg L-1 and a Mg2+ / Li+ mass ratio of 150 : 1 as feed, which is high as compared with most of the literature, demonstrating its potential in the practical application of Mg2+ and Li+ separation.

Strip cutting has emerged as a new, efficient, and mechanized bamboo forest management model. To shorten the recovery period in strip cutting management, improve bamboo resource quality, prevent soil degradation, and achieve sustainable management, we selected on-year pure Moso bamboo (Phyllostachys edulis) forests for an 8-meter-wide strip cut. Three fertilization methods were applied in a complete two-factor experiment, including spreading, cave, and bamboo stump fertilization, at three fertilization dosages of 600, 900, and 1200 kg/ha (N:P:K = 3.5:1:2). We investigated the effects of different fertilization treatments on the biomass of new bamboo shoots and soil fertility to provide a reference for identifying the optimal fertilization scheme. The results showed that fertilization treatment increased the individual stand biomass of new Moso bamboo shoots, with a decreasing trend in the proportion of branches and leaves and an increasing proportion of culms in biomass allocation. Fertilization treatment significantly increased the total nitrogen, phosphorus, and potassium and available phosphorus contents in the soil. Overall, fertilization at 900 kg/ha using the spreading method showed the best results in promoting individual plant biomass recovery (5% increase in culm proportion and 4.12 kg increase in biomass per plant) and restoring soil fertility (increase the contents of TN, TP, TK, and AP in the entire soil layer) after strip cutting Moso bamboo forests, which addresses these pertinent issues in the strip cut management model.

Abstract Background Studies have reported that a noncoding hexanucleotide repeat in C9ORF72, is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) among Caucasian population, nevertheless it is rare in Chinese population. Therefore, we aimed to investigate the mutation spectrum of Chinese ALS patients with FTD (ALS-FTD). Methods ALS patients with and without cognitive impairments were enrolled. Clinical features were collected including age, sex, disease duration, ALSFRS-r, family history and cognitive evaluation. Thirty-six ALS genes were screened by whole exome sequencing (WES) and repeat-primed polymerase chain reaction (PCR) were used for detection of and abnormal repeat expansions of C9ORF72. Results A total of 1208 patients, including 66 familial ALS (FALS) and 1142 sporadic ALS (SALS) patients were included. Twenty-three patients with sporadic ALS and one familial ALS index had concomitant FTD, which accounts for 1.99% (24/1208) of patients with ALS. In sporadic ALS-FTD, one case harboring C9ORF72 expansion variant, two cases harboring ANXA11 variants and one individual carrying CCNF variant were identified. A recurrent UBQLN2 variant was detected in a familial ALS-FTD patient. All of the ALS-FTD patients carrying variants in known causative genes manifested motor symptom onset (two bulbar onset and three limb onset) and developed cognitive impairment thereafter. It is not easy to draw a conclusion of the genotype-phenotype association in ALS-FTD with certain variants, limited by the small number of patients. Conclusion Our findings provide an overview of spectrum of genetic variants in Chinese ALS-FTD patients. Variants of uncertain significance in UBQLN2, ANXA11 and CCNF were identified and further studies are required for causal relations of these variants with ALS-FTD.

We aimed to explore the effect of strip cutting width on the physical and mechanical properties of Moso bamboo (Phyllostachys edulis). Four-year-old hairy bamboo with different cutting bandwidths (3 m, 5 m, 8 m, 12 m and 15 m) was used as the experimental material, and the traditional management forest (CK) was used as the control. Eight physical and mechanical properties—radial line shrinkage, chordal line shrinkage, volume shrinkage, total dry density, basic density, compressive strength, shear strength and flexural strength—were studied. ANOVA, bivariate correlation analysis, and principal component analysis were performed, which showed the effect of strip cutting on the physical and mechanical properties of bamboo. The results showed that the density, the total dry density, basic density, flexural strength and compressive strength of the strip cut bamboo were lower than those of the control stand. The radial line shrinkage and volume shrinkage were higher than those of the control stand. The chordal line shrinkage was higher than that of the control stand when the cutting bandwidth was 3 m and 5 m and lower than that of the control stand when the cutting bandwidth was 8 m, 12 m and 15 m. The shear strength was lower than that of the control stand when the harvesting bandwidth was 3 m, 5 m and 8 m and higher than that of the control stand when the harvesting bandwidth was 12 m and 15 m. There are different degrees of correlation between the eight physical and mechanical performance indicators. The comprehensive score of the physical and mechanical properties of bamboo in the control stand was 1.30, and the comprehensive score of bamboo in strip harvesting was between 0.37 and 1.25, with an average score of 0.95. The results show that strip cutting can save the time and costs associated with harvesting Moso bamboo forests, but different cutting widths can reduce the physical and mechanical properties of Moso bamboo in different degrees.

Bamboo crown width (CW) is a reliable index for evaluating growth, yield, health and vitality of bamboo, and light capture ability and carbon fixation efficiency of bamboo forests. Based on statistical results produced from fitting the eight basic growth functions using data from 1374 Phyllostachys pubescens in Yixing, Jiangsu Province, China, this study identified the most suitable function (logistic function) to construct a two-level mixed effects (NLME) CW model with the forest block and sample plot-level effects included as random effects in the model. Four methods for selecting sample bamboos per sample plot (largest bamboo, medium-sized bamboo, smallest bamboo, and randomly selected bamboos) and eight sample sizes (1–8 selected bamboos per sample plot) were evaluated to calibrate our NLME CW model. Using diameter at breast height (DBH), height to crown base (HCB), arithmetic mean diameter at breast height (MDBH), and height (H) as predictor variables, the model produced the best fit statistics (Max R2, min RMSE, and TRE). This model was further improved by introducing random effects at two levels. The results showed a positive correlation of CW with HCB and DBH and a negative correlation with H. The smallest two bamboo poles per sample plot used to estimate the random effects of the NLME model provided a satisfactory compromise regarding measurement cost, model efficiency, and prediction accuracy. The presented NLME CW model may guide effective management and carbon estimation of bamboo forests.

Abstract Droughts cause extreme anomalies in tropical forest growth, but the direction and magnitude of tropical forests in response to droughts are still widely debated. Here, we used four satellite‐based canopy growth proxies (CGPs), including three optical and one passive microwave, and in situ fluxes observations from eddy covariance (EC) measurements for a retrospective investigation of the impacts of historical droughts on tropical forest growth from a statistical point of view. Results indicate two opposite directions in drought‐related canopy dynamics across pantropical forests. The canopy of tropical forests with higher CGPs is more vulnerable to drought stress and recovers faster in the post‐drought recovery period. In contrast, the canopy of tropical forests with lower CGPs increases during the drought period and declines in the subsequent recovery period, which is beyond general expectation. In situ measurements from eddy‐covariance flux towers showed that forests with higher gross primary production and latent heat flux decreased photosynthesis and evapotranspiration during the drought period but increased photosynthesis and evapotranspiration faster during the post‐drought recovery period, supporting the findings from satellite observations. Our statistical analysis against climatic factors predicts that higher‐CGPs tress with probably taller and bigger canopies are more responsive to shortage of water availability caused by drought; while lower‐CGPs tress with shorter and smaller canopies are more responsive to sunlight availability and tend to increase their canopy leaves and enhance photosynthesis in sunnier days during the drought period. Our results highlight the differences in tropical forests in responding to drought stress, which are worth incorporated in Earth system models for time‐series evaluations.

Using lignin for polyurethane (PU) synthesis is challenging because of its heterogeneous structure, i.e., broad molecule weight (MW) distribution and diverse hydroxyl (OH) functionality. This complexity influences the crosslinking reaction between lignin and isocyanate and affects the quality of PU products. Here, we propose a two-step strategy for lignin structure homogenization by lowering its MW and uniforming OH functionality (step 2). Step 1 involves a bioethanol fractionation process, yielding fractionated lignin with one order lower MW than the raw lignin while exhibiting better processability for the subsequent process. Step 2 is performed by an oxyalkylation process using fractionated lignin that converts phenolic and carboxylic OHs to aliphatic OHs. As a result, we obtained structure-homogenized lignin with good compatibility and crosslinking with hexamethylene diisocyanate for PU coating synthesis. Moreover, PU coatings prepared from structure-homogenized lignin display a defect-free microscopic structure and show better corrosion resistance than coatings fabricated from its raw lignin alternative. Overall, the structure homogenization process is a beneficial way of using lignin as biopolyol in PU synthesis toward the application-oriented design of corrosion-resistant lignin-based PU coatings.

Traditional DNA-based electrochemiluminescence (ECL) biosensors generally require a laborious and time-consuming process of electrode modification. Although immobilization-free homogeneous electrochemical approaches have been proposed, the problems of low detectable signals from indicators and high background interferences resulting from label-free sensors remain unsolved. Herein, a new type of homogeneous label-free ECL biosensor for aflatoxin B1 (AFB1) is designed based on a double-driven signal-amplifying strategy (combination of entropy-driven and nuclease-driven) and a background reduction by magnetic graphene oxide (M-GO). The target of AFB1 competitively binds the aptamer in the duplex DNA, leading to the release of the catalyst strand which would further bind the Ru(bpy)32+-Probe (Ru-Probe) absorbed in M-GO based on the principle of entropy increase. In the presence of exonuclease III, the Ru-Probe is degraded to release Ru(bpy)32+ for detection, and the catalyst strand is preserved to trigger much more Ru(bpy)32+ released. So the nuclease-driven combined with entropy-driven amplifying strategy greatly enhances the ECL signal. Moreover, the unreacted Ru-Probes adsorbed in M-GO are removed by the magnetic separation, providing the background signal was reduced as far as possible. Under the optimum conditions, the enhanced ECL signal exhibits a linear relationship with the AFB1 concentration in the range of 1 pM–100 nM with a detection limit of 20 fM. The homogeneous ECL biosensor is successfully applied to determine AFB1 in corn samples with high sensitivity and selectivity. By altering the probes employed, this type of novel ECL biosensor is promising for further determination of diverse targets which are trace contaminants in food, environment, and the disease biomarkers.

This study explored the viability of greenhouse cultivation of Dendrocalamopsis oldhami under the “South Bamboo North Transplanting” initiative. In this study, the effects of planting year and nitrogen application on changes in soil nutrient levels, salinity, and alkalinity over the plant growth period were explored. After the introduction and planting of bamboo in 2017, a soil layer with a thickness of 0–40 cm was sampled at the end of the shooting stage in the greenhouse between 2017 and 2019 (late August), and the bamboo shoot yield and standing culm density were measured. Following the application of nitrogen to the bamboo groves in 2019, three nitrogen levels were established: no nitrogen (N1:0 g grove−1), medium nitrogen (N2:540 g grove−1), and high nitrogen (N3:1080 g grove−1). Soil layers at depths of 0–20 and 20–40 cm were sampled during the shoot elongation stage (late May) and at the end of the shooting stage (late August). The yield and nutrient content of bamboo shoots under different nitrogen treatments were also investigated. The results showed that Ca2+ and HCO3− were the main salt ions in greenhouse soil. With later planting years, the total number of cations (Ca2+, Na+, Mg2+, and K+) decreased, whereas the total number of anions (HCO3−, SO42−, NO3−, and Cl−) increased, resulting in a decrease in the percentage of exchangeable sodium (ESP), pH, and electrical conductivity (EC). The diameter at breast height, individual weight, and quantity of bamboo shoots increased annually, and the standing culm density increased by 1.4 times. Each year, the total nitrogen content decreased, whereas the alkali-hydrolyzed nitrogen, available phosphorus, and available potassium contents increased. Nitrogen application resulted in a significant decrease in ESP and pH and an increase in the total anion, cation, and EC values. It also reduced soil organic carbon, total nitrogen, total phosphorus, total potassium, available phosphorus, and available potassium. Nitrogen application increased the number of bamboo shoots, total yield, and accumulation of N and P; however, there was no significant difference between N2 and N3. In conclusion, the salinization of calcareous soil was alleviated, and the available nutrients were activated following the introduction of D. oldhami from south to north. The mineralization rates of organic matter and soil fertility increased. Soil acidification and EC decreased at the end of the shoot stage. Nitrogen application acidified the soil, and the yield and soil salt accumulation increased with increasing nitrogen levels. The nutrient uptake efficiencies of nutrients at high nitrogen levels were lower than those at medium nitrogen levels. Therefore, soil salt concentrations with values 0.26 < EC < 0.42 hindered the nutrient uptake of D. oldhami.

ObjectivesMultiple sclerosis (MS) is a complex central nervous system (CNS) demyelinating disease, the etiology of which involves the interplay between genetic and environmental factors. We aimed to determine whether genetically predicted peripheral immune cell counts may have a causal effect on MS.MethodsWe used genetic variants strongly associated with cell counts of circulating leukocyte, lymphocyte, monocyte, neutrophil, eosinophil, and basophil, in addition to some subpopulations of T and B lymphocyte, as instrumental variables (IVs) to perform Mendelian randomization (MR) analyses. The effect of immune cell counts on MS risk was measured using the summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) genome-wide association studies (GWAS).ResultsOur findings indicated that higher leucocyte count [odds ratio (OR), 1.24; 95% confidence interval (CI), 1.07 - 1.43; p = 0.0039] and lymphocyte count (OR, 1.17; 95% CI, 1.01 – 1.35; p = 0.0317) were causally associated with MS susceptibility. In addition, we also found that increase of genetically predicted natural killer T (NKT) cell count is also associated with an increase MS risk (OR, 1.24; 95% CI, 1.06 - 1.45; p = 0.0082).ConclusionsThese findings show that the genetic predisposition to higher peripheral immune cell counts can exert a causal effect on MS risk, which confirms the crucial role played by peripheral immunity in MS. Particularly, the causal association between NKT cell count and MS underscores the relevance of exploring the functional roles of NKT cells in disease pathogenesis in future.

The climatic drivers of leaf phenology and water stress regulation strategies in tropical/subtropical forest biomes are poorly understood on the continental scale. Widespread field observations and remotely sensed plant phenology and physiology data across tropical forest ecosystems at various scales provide new insight into the response of tropical forests to climate change. In this study, we collected seasonal litterfall data from 65 sites across tropical/subtropical America for analysis against remotely sensed photosynthetic and climatic indicators. We proposed an integrated field and remote sensing approach for partitioning three rhythms of forest phenology across tropical and subtropical America in response to various wet- and dry-season variabilities in sunlight, liquid water supply and atmospheric dryness. The results showed that in a dry-season leaf shedding and rejuvenation phenology, trees encounter limited soil water stress, shift to a young canopy by replacing old leaves with new leaves, and regulate water use through the xylem to maximize light capture and productivity. In a wet-season leaf shedding & rejuvenation phenology, trees on the contrary shed and rejuvenate canopy leaves to maximize light use and increase photosynthesis during the sunny wet season. Trees show a dominant stomatal regulation of seasonal water use, resulting in considerable seasonal changes in canopy photosynthesis and transpiration. However, in a dry-season leaf shedding and wet-season rejuvenation phenology, trees shed leaves due to water stresses and grew new leaves to maximize photosynthesis with sufficient water availability. Trees shift from wet-season stomatal regulation to dry-season xylem regulation with fewer canopy leaves. Our findings provide new physiological insight into the mechanism of sunlight availability, liquid water supply and atmospheric dryness in driving leaf phenology and photosynthesis across tropical and subtropical forests.

Summary: Relationships among productivity, leaf phenology, and seasonal variation in moisture and light availability are poorly understood for evergreen broadleaved tropical/subtropical forests, which contribute 25% of terrestrial productivity. On the one hand, as moisture availability declines, trees shed leaves to reduce transpiration and the risk of hydraulic failure. On the other hand, increases in light availability promote the replacement of senescent leaves to increase productivity. Here, we provide a comprehensive framework that relates the seasonality of climate, leaf abscission, and leaf productivity across the evergreen broadleaved tropical/subtropical forest biome. The seasonal correlation between rainfall and light availability varies from strongly negative to strongly positive across the tropics and maps onto the seasonal correlation between litterfall mass and productivity for 68 forests. Where rainfall and light covary positively, litterfall and productivity also covary positively and are always greater in the wetter sunnier season. Where rainfall and light covary negatively, litterfall and productivity are always greater in the drier and sunnier season if moisture supplies remain adequate; otherwise productivity is smaller in the drier sunnier season. This framework will improve the representation of tropical/subtropical forests in Earth system models and suggests how phenology and productivity will change as climate change alters the seasonality of cloud cover and rainfall across tropical/subtropical forests. Public summary: • Three climate-phenology regimes are identified across tropical and subtropical forest biomes • Where light and water limit plant in dry season, litterfall and productivity peak in sunny wet season • Where light or water alternately limits plant, productivity peaks in wet season with low litterfall • Where water does not limit plant, litterfall and productivity peak in sunny dry season

The rapid and simple detection of Helicobacter pylori (H. pylori) is essential for its clinical eradication. Although various methods for detecting H. pylori have been well established, such as endoscopy in combination with histology or culture, rapid urease test (RUT) and molecular tests using clinical specimens, it is of great importance to develop an ultrasensitive and accurate nucleic acid detection platform and apply it to identify H. pylori. To meet these demands, a novel method based on PCR and CRISPR-Cas13a, called PCR-Cas13a, was developed and validated using the DNA of 84 clinical strains and 71 clinical specimens. PCR primers for the pre-amplification of conservative sequence and CRISPR RNA (crRNA) for the detection of specific sequence were designed according to the principle. The designed primers and crRNA were specific to H. pylori, and the assay showed a high degree of specificity compared with other common pathogens. Our detection system can screen H. pylori with a limit of 2.2 copies/μL within 30 mins after PCR amplification. Using a coincidence analysis with traditional methods, our method exhibited 100% accuracy for the detection of H. pylori. Furthermore, its diagnostic performance was compared, in parallel with a q-PCR. The PCR-Cas13a demonstrates 98% sensitivity and 100% specificity. Moreover, our approach had a lower limit of detection (LOD) than q-PCR. Herein, we present a diagnostic system for the highly sensitive screening of H. pylori and distinguish it from other pathogens. All the results demonstrated that this PCR-based CRISPR assay has wide application prospects for the detection of H. pylori and other slow-growth pathogens.

Organic solvents take up 80% of the total chemicals used in pharmaceutical and related industries, while their reuse rate is less than 50%. Traditional solvent treatment methods such as distillation and evaporation have many disadvantages such as high cost, environmental unfriendliness, and difficulty in recovering heat-sensitive, high-value molecules. Organic solvent nanofiltration (OSN) has been a prevalent research topic for the separation and purification of organic solvent systems since the beginning of this century with the benefits of no-phase change, high operational flexibility, low cost, as well as environmental friendliness. Especially, hollow fiber (HF) OSN membranes have gained a lot of attention due to their high packing density and easy scale-up as compared with flat-sheet OSN membranes. This paper critically reviewed the recent research progress in the preparation of HF OSN membranes with high performance, including different materials, preparation methods, and modification treatments. This paper also predicts the future direction of HF OSN membrane development.

Sodium-ion batteries (SIBs) are regarded as promising alternatives to lithium-ion batteries (LIBs) in the field of energy, especially in large-scale energy storage systems. Tremendous effort has been put into the electrode research of SIBs, and hard carbon (HC) stands out among the anode materials due to its advantages in cost, resource, industrial processes, and safety. However, different from the application of graphite in LIBs, HC, as a disordered carbon material, leaves more to be completely comprehended about its sodium storage mechanism, and there is still plenty of room for improvement in its capacity, rate performance and cycling performance. This paper reviews the research reports on HC materials in recent years, especially the research process of the sodium storage mechanism and the modification and optimization of HC materials. Finally, the review summarizes the sterling achievements and the challenges on the basis of recent progress, as well as the prospects on the development of HC anode materials in SIBs.

Abstract Climatic drivers for canopy leaf shedding and flush of evergreen broadleaved forest biome are still unclear at the continental scale across tropical and subtropical region. This imposes a challenge for modeling pantropical photosynthesis seasonality in Earth system models. Here, we examined three potential climatic triggers, vapor pressure deficit–a proxy of atmospheric water deficit, downward shortwave incoming solar radiation–a proxy of sunlight availability, and terrestrial water storage–a proxy of soil water availability observed by the Gravity Recovery and Climate Experiment, by comparing with two satellite phenological proxies–the Enhanced Vegetation Index and Continuous Solar‐induced chlorophyll fluorescence. Results show that tropical leaf phenology varies greatly from equatorial bimodal seasonality to higher‐latitude unimodal seasonality. Sunlight availability dominantly controls the whole seasonal leaf phenology across the pantropical region. Atmospheric dryness is one main type of water stress for leaf phenology during the first half year. However, soil water stress strongly inhibits the first‐half of leaf phenology in tropical Asia and the second‐half of leaf phenology in Congo, but shows rare constraint on the leaf phenology in Amazon. Ignoring these various roles of soil moisture availability and atmospheric dryness in influencing tropical leaf phenology might lead to unexpected uncertainty for predicting the water and carbon cycles of tropical forest ecosystem in Earth system models.

Multiple methods have been developed to identify the transition threshold from the reconstructed satellite-derived normalized difference vegetation indices (NDVI) time series and to determine the inflection point corresponding to a certain phenology phase (e.g., the spring green-up date (GUD)). We address an issue that large uncertainties might occur in the inflection point identification of spring GUD using the traditional satellite-based methods since different vegetation types exhibit asynchronous phenological phases over a heterogeneous ecoregion. We tentatively developed a Maximum-derivative-based (MDB) method and provided inter-comparisons with two traditional methods to detect the turning points by the reconstructed time-series data of NDVI for identifying the GUD against long-term observations from the sites covered by a mixture of deciduous forest and herbages in the Pan European Phenology network. Results showed that higher annual mean temperature would advance the spring GUD, but the sensitive magnitudes differed depending on the vegetation type. Therefore, the asynchronization of phenological phases among different vegetation types would be more pronounced in the context of global warming. We found that the MDB method outperforms two other traditional methods (the 0.5-threshold-based method and the maximum-ratio-based method) in predicting the GUD of the subsequent-green-up vegetation type when compared with ground observation, especially at sites with observed GUD of herbages earlier than deciduous forest, while the Maximum-ratio-based method showed better performance for identifying GUDs of the foremost-green-up vegetation type. Although the new method improved in our study is not universally applicable on a global scale, our results, however, highlight the limitation of current inflection point identify algorithms in predicting the GUD derived from satellite-based vegetation indices datasets in an ecoregion with heterogeneous vegetation types and asynchronous phenological phases, which makes it helpful for us to better predict plant phenology on an ecoregion-scale under future ongoing climate warming.

Abstract The development of gastritis is associated with an increased risk of gastric cancer. Current invasive gastritis diagnostic methods are not suitable for monitoring progress. In this work based on 78 gastritis patients and 50 healthy individuals, we observed that the variation of tongue-coating microbiota was associated with the occurrence and development of gastritis. Twenty-one microbial species were identified for differentiating tongue-coating microbiomes of gastritis and healthy individuals. Pathways such as microbial metabolism in diverse environments, biosynthesis of antibiotics and bacterial chemotaxis were up-regulated in gastritis patients. The abundance of Campylobacter concisus was found associated with the gastric precancerous cascade. Furthermore, Campylobacter concisus could be detected in tongue coating and gastric fluid in a validation cohort containing 38 gastritis patients. These observations provided biological evidence of tongue diagnosis in traditional Chinese medicine, and indicated that tongue-coating microbiome could be a potential non-invasive biomarker, which might be suitable for long-term monitoring of gastritis.

Quantitative assessment of the intracellular oxidative stress level is a very important problem since it is the basis for elucidation of the fundamental causes of metabolic changes in diseased human cells, particularly cancer. However, the problem proves to be very challenging to solve in vivo because of the complex nature of the problem. Here a computational method is presented for predicting the quantitative level of the intracellular oxidative stress in cancer tissue cells. The basic premise of the predictor is that the genomic mutation level is strongly associated with the intracellular oxidative stress level. Based on this, a statistical analysis is conducted to identify a set of enzyme-encoding genes, whose combined expression levels can well explain the mutation rates in individual cancer tissues in the TCGA database. We have assessed the validity of the predictor by assessing it against genes that are known to have anti-oxidative functions for specific types of oxidative stressors. Then the applications of the predictor are conducted to illustrate its utility.

Abstract Leaf phenology in the humid tropics largely regulates the seasonality of forest carbon and water exchange. However, it is inadequately represented in most global land surface models due to limited understanding of its controls. Based on intensive field studies at four Amazonian evergreen forests, we propose a novel, quantitative representation of tropical forest leaf phenology, which links multiple environmental variables with the seasonality of new leaf production and old leaf litterfall. The new phenology simulates higher rates of leaf turnover (new leaves replacing old leaves) in dry seasons with more sunlight, which is then implemented in ORCHIDEE, together with recent findings of ontogeny‐associated photosynthetic capacity, and is evaluated against ground‐based measurements of leaf phenology (canopy leaf area index and litterfall), eddy covariance fluxes (photosynthesis and latent heat), and carbon allocations from field observations. Results show the periodical cycles of solar radiation and vapor pressure deficit are the two most important environmental variables that are empirically related to new leaf production and old leaf abscission in tropical evergreen forests. The model with new representation of leaf phenology captures the seasonality of canopy photosynthesis at three out of four sites, as well as the seasonality of litterfall, latent heat, and light use efficiency of photosynthesis at all tested sites, and improves the seasonality of carbon allocations to leaves, roots, and sapwoods. This study advances understanding of the environmental controls on tropical leaf phenology and offers an improved modeling tool for gridded simulations of interannual CO2 and water fluxes in the tropics.

The well-documented energy balance dynamics within forest ecosystems are poorly implemented in studies of the biophysical effects of forests. This results in limitations to the accurate quantification of forest cooling/warming on local air temperature. Taking into consideration the forest air space, this study proposes a three-layered (canopy, forest air space and soil [CAS]) land surface energy balance model to simulate air temperature within forest spaces (Taf) and subsequently to evaluate its biophysical effects on forest cooling/warming, i.e., the air temperature gradient (∆Ta) between the Taf and air temperature of open spaces (Tao) (∆Ta = Taf − Tao). We test the model using field data for 23 sites across 10 cities worldwide; the model shows satisfactory performance with the test data. High-latitude forests show greater seasonal dynamics of ∆Ta, generating considerable cooling of local air temperatures in warm seasons but minimal cooling or even warming effects during cool seasons, while low-latitude tropical forests always exert cooling effects with less interannual variability. The interannual dynamics of ∆Ta are significantly related to the seasonality of solar geometry and canopy leaf phenology. The differences between forest canopy temperature (Tc) and Tao, which are the two most important terms attributed by the CAS model in impacting Taf, explain a large part of forest cooling and warming (May–July: R2 = 0.35; November–January: R2 = 0.51). The novel CAS model provides a feasible way to represent the energy balance within forest ecosystems and to assess its impacts on local air temperatures globally. Keywords: Forest cooling/warming, Forest biophysical effects, Radiative transfer equation, Land-atmosphere model, Local environmental health, Climate warming mitigation

Digitizing the land surface temperature (Ts) and surface soil moisture (mv) is essential for developing the intelligent Digital Earth. Here, we developed a two parameter physical-based passive microwave remote sensing model for jointly retrieving Ts and mv using the dual-polarized Tb of Aqua satellite advanced microwave scanning radiometer (AMSR-E) C-band (6.9 GHz) based on the simplified radiative transfer equation. Validation using in situ Ts and mv in southern China showed the average root mean square errors (RMSE) of Ts and mv retrievals reach 2.42 K (R2 = 0.61, n = 351) and 0.025 g cm−3 (R2 = 0.68, n = 663), respectively. The results were also validated using global in situ Ts (n = 2362) and mv (n = 1657) of International Soil Moisture Network. The corresponding RMSE are 3.44 k (R2 = 0.86) and 0.039 g cm−3 (R2 = 0.83), respectively. The monthly variations of model-derived Ts and mv are highly consistent with those of the Moderate Resolution Imaging Spectroradiometer Ts (R2 = 0.57; RMSE = 2.91 k) and ECV_SM mv (R2 = 0.51; RMSE = 0.045 g cm−3), respectively. Overall, this paper indicates an effective way to jointly modeling Ts and mv using passive microwave remote sensing.

Despite its perennial canopy, the Amazonian tropical evergreen forest shows significant canopy growth seasonality, which has been represented by optical satellite-based observations. In this paper, a new Microwave Temperature–Vegetation Drought Index (MTVDI) based on Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) sensors was used to capture the canopy seasonality from 2003 to 2010 in comparison with four climatic dryness indicators (Palmer Drought Severity Index (PDSI), Climatological Water Deficit (CWD), Terrestrial Water Storage (TWS), Vapor Pressure Deficit (VPD)) and two photosynthesis proxies (Enhanced Vegetation Index (EVI) and Solar-Induced chlorophyll Fluorescence (SIF)), respectively. Our results suggest that the MTVDI shows opposite seasonal variability with two photosynthesis proxies and performs better than the four climatic dryness indicators in reflecting the canopy photosynthesis seasonality of tropical forests in the Amazon. Besides, the MTVDI captures wet regions that show green-up during the dry season with mean annual precipitation higher than 2000 mm per year. The MTVDI provides a new way for monitoring the canopy seasonality of tropical forests from microwave signals.

The interception of rainfall by vegetation canopies plays an important role in the hydrologic process of ecosystems. Most estimates of canopy rainfall interception in present studies are mainly through field observations at the plot region. However, it is difficult, yet important, to map the regional rainfall interception by vegetation canopy at a larger scale, especially in the southern rainy areas of China. To obtain a better understanding of the spatiotemporal variation of vegetation canopy rainfall interception with regard to the basin scale in this region, we extended a rainfall interception model by combining the observed rainfall data and moderate resolution imaging spectroradiometer leaf area index (MODIS_LAI) data to quantitatively estimate the vegetation canopy rainfall interception rate (CRIR) at small/medium basin scales in Guangdong Province, which is undergoing large changes in vegetation cover due to rapid urban expansion in the area. The results showed that the CRIR in Guangdong declined continuously during 2004−2012, but increased slightly in 2016, and the spatial variability of CRIR showed a diminishing yearly trend. The CRIR also exhibited a distinctive spatial pattern, with a higher rate to the east and west of the mountainous areas and a lower rate in the central mountainous and coastal areas. This pattern was more closely related to the spatial variation of the LAI than that of rainfall due to frequent extreme rainfall events saturating vegetation leaves. Further analysis demonstrated that forest coverage, instead of background climate, has a certain impact on the canopy rainfall interception, especially the proportion of broad-leaved forests in the basin, but more in-depth study is warranted in the future. In conclusion, the results of this study provide insights into the spatiotemporal variation of canopy rainfall interception at the basin scale of the Guangdong Province, and suggest that forest cover should be increased by adjusting the species composition to increase the proportion of native broad-leaved species based on the local condition within the basin. In addition, these results would be helpful in accurately assessing the impacts of forest ecosystems on regional water cycling, and provide scientific and practical implications for water resources management.