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Abstract Background Definitive concurrent chemoradiotherapy (CCRT) is the standard treatment for locally advanced, inoperable non-small cell lung cancer (NSCLC). Previous studies have mainly focused on examining local failure and recurrence patterns after surgery and the principles of lymph node metastasis (LNM) in surgical candidates with NSCLC. However, these studies were just only able to guide postoperative radiotherapy (PORT) and the patterns of LNM in patients with resected NSCLC was inadequate to represent that in locally advanced inoperable NSCLC patients for guiding target volume delineation of CCRT. In this study, we aimed to analyze the metastasis regularities and establish the correlations between different lymph node levels in NSCLC patients without any intervention using positron emission tomography/computed tomography (PET/CT) images. Methods Overall, 358 patients with N1–N3 NSCLC admitted in our hospital between 2018 and 2022 were retrospectively analyzed. The diagnosis of metastatic lymph nodes was reviewed and determined using the European Organization for Research and Treatment of Cancer standard and the standardized value of the PET/CT examination. Univariate and multivariate analysis were performed to investigate the correlations between the different levels were evaluated by using of the chi-square test and logistic regression model. Results The lymph nodes with the highest metastasis rates in patients with left lung cancer were in order as follows: 10L, 4L, 5, 4R, and 7; while in those with right lung cancer they were 10R, 4R, 7, 2R, and 1R. Notably, we found left lung patients were more likely to have contralateral hilar, mediastinal and supraclavicular lymph nodes involved, and the right lung group exhibited a higher propensity for ipsilateral mediastinum and supraclavicular lymph node invasion. Furthermore, correlation analysis revealed there were significant correlative patterns in the LNM across different levels. Conclusions This study elucidated the patterns of primary LNM in patients with NSCLC who had not undergone surgery (without any treatment interventions) and the correlations between lymph node levels. These findings were expected to provide useful reference for target volume delineation in definitive concurrent chemoradiotherapy in locally advanced NSCLC patients.

Abstract The purpose of this study was to investigate early stage dynamic changes in relevant indicators in neurocritical patients to identify biomarkers that can predict a poor prognosis at an early stage (1–4 days after admission). This study retrospectively collected clinical data, inflammatory indicators, and nutritional indicators from 77 patients at the neurology intensive care unit. The 3-month modified Rankin scale score was used as the outcome indicator. A linear mixed model was used to analyze changes in inflammatory indicators and nutritional indicators in neurocritical patients over time from 1–4 days after admission. Logistic regression was used to determine the independent risk factors for a poor prognosis in neurocritical patients and to construct a predictive model. The predictive efficacy of the model was verified using leave-one-out cross-validation and decision curve analysis methods. The analysis results showed that 1–4 days after admission, the inflammatory indicators of white blood cell and absolute monocyte counts and the nutritional indicators of body cell mass(BCM), fat-free mass, body cell mass/phase angle (BCM/PA), intracellular water, extracellular water, and skeletal muscle index increased overall, while the nutritional indicators of albumin and visceral fat area decreased overall. The logistic multivariate regression model showed that the Charlson comorbidity index (CCI) (odds ratio (OR) = 2.526, 95% CI [1.202, 5.308]), hemoglobin (Hb)(on admission)-Hb(min) (OR = 1.049, 95% CI [1.015, 1.083), BCM(on admission) (OR = 0.794, 95% CI [0.662, 0.952]), and the change in BCM/PA 1–4 days after admission (OR = 1.157, 95% CI [1.070, 1.252]) were independent risk factors for a poor prognosis in neurocritical patients. The predictive analysis showed that the predictive power of Model 1 with BCM/PA (area under the curve (AUC) = 0.95, 95% CI (0.90, 0.99)) was 93%, 65%, 141%, and 133% higher than that of Model 2 without BCM/PA, the CCI, the APACHE II score, and the NRS2002 score (all P

Abstract Background The short-term prognosis of stroke patients is mainly influenced by the severity of the primary disease at admission and the trend of disease development during the acute phase (1–7 days after admission). Objective The aim of this study is to explore the relationship between the bioelectrical impedance analysis (BIA) parameter trajectories during the acute phase of stroke patients and their short-term prognosis, and to investigate the predictive value of the prediction model constructed using BIA parameter trajectories and clinical indicators at admission for short-term prognosis in stroke patients. Methods A total of 162 stroke patients were prospectively enrolled, and their clinical indicators at admission and BIA parameters during the first 1–7 days of admission were collected. A Group-Based Trajectory Model (GBTM) was employed to identify different subgroups of longitudinal trajectories of BIA parameters during the first 1–7 days of admission in stroke patients. The random forest algorithm was applied to screen BIA parameter trajectories and clinical indicators with predictive value, construct prediction models, and perform model comparisons. The outcome measure was the Modified Rankin Scale (mRS) score at discharge. Results PA in BIA parameters can be divided into four separate trajectory groups. The incidence of poor prognosis (mRS: 4–6) at discharge was significantly higher in the “Low PA Rapid Decline Group” (85.0%) than in the “High PA Stable Group “ (33.3%) and in the “Medium PA Slow Decline Group “(29.5%) (all P

The effects of deoxidation methods on the inclusion characteristics and corrosion behaviour of high-strength low-alloy steels were examined in marine environments using various microcharacterisation techniques and first-principles calculations. After Ca treatment, MnS–MgO–Al2O3 inclusions were modified to CaS–MgO–Al2O3 and microcrevices were existed at the interface between inclusions and Fe. After Zr–Ti-RE deoxidation, spherical CaS + TiN + ZrO2+MgAl2O4+(Ca, La) Al3O7 inclusions appeared. (Ca, La)Al3O7 in steel displayed similar mechanical properties to Fe, reducing the degree of lattice distortion and the formation of microcrevices around the inclusions. Micro-galvanic corrosion between Fe and MnS accelerated the localised corrosion rate and promoted the formation of large pits on the surface. However, the chemical activity of CaS resulted in dissolution of the inclusion, which relatively inhibited the localised corrosion propagation. The enrichment of Cr in the rust layer after Zr–Ti-RE deoxidation improved the compactness, contributed to a reduction in the localised corrosion rate and long-term corrosion rate. Finally, the underlying mechanism influencing corrosion behaviour was established.

Abstract Respiratory disease caused by coronavirus infection remains a global health crisis. Although several SARS-CoV-2-specific vaccines and direct-acting antivirals are available, their efficacy on emerging coronaviruses in the future, including SARS-CoV-2 variants, might be compromised. Host-targeting antivirals provide preventive and therapeutic strategies to overcome resistance and manage future outbreak of emerging coronaviruses. Cathepsin L (CTSL) and calpain-1 (CAPN1) are host cysteine proteases which play crucial roles in coronaviral entrance into cells and infection-related immune response. Here, two peptidomimetic α-ketoamide compounds, 14a and 14b, were identified as potent dual target inhibitors against CTSL and CAPN1. The X-ray crystal structures of human CTSL and CAPN1 in complex with 14a and 14b revealed the covalent binding of α-ketoamide groups of 14a and 14b to C25 of CTSL and C115 of CAPN1. Both showed potent and broad-spectrum anticoronaviral activities in vitro, and it is worth noting that they exhibited low nanomolar potency against SARS-CoV-2 and its variants of concern (VOCs) with EC50 values ranging from 0.80 to 161.7 nM in various cells. Preliminary mechanistic exploration indicated that they exhibited anticoronaviral activity through blocking viral entrance. Moreover, 14a and 14b exhibited good oral pharmacokinetic properties in mice, rats and dogs, and favorable safety in mice. In addition, both 14a and 14b treatments demonstrated potent antiviral potency against SARS-CoV-2 XBB 1.16 variant infection in a K18-hACE2 transgenic mouse model. And 14b also showed effective antiviral activity against HCoV-OC43 infection in a mouse model with a final survival rate of 60%. Further evaluation showed that 14a and 14b exhibited excellent anti-inflammatory effects in Raw 264.7 mouse macrophages and in mice with acute pneumonia. Taken together, these results suggested that 14a and 14b are promising drug candidates, providing novel insight into developing pan-coronavirus inhibitors with antiviral and anti-inflammatory properties.

Abstract Bathyarchaeia (formerly Bathyarchaeota) is a group of highly abundant archaeal communities that play important roles in global biogeochemical cycling. Bathyarchaeia is predominantly found in sediments and hot springs. However, their presence in arable soils is relatively limited. In this study, we aimed to investigate the spatial distributions and diversity of Bathyarchaeia in paddy soils across eastern China, which is a major rice production region. The relative abundance of Bathyarchaeia among total archaea ranged from 3 to 68% in paddy soils, and Bathy-6 was the dominant subgroup among the Bathyarchaeia (70–80% of all sequences). Bathyarchaeia showed higher migration ability and wider niche width based on the neutral and null model simulations. Bathy-6 was primarily assembled by deterministic processes. Soil pH and C/N ratio were identified as key factors influencing the Bathyarchaeia composition, whereas C/N ratio and mean annual temperature influenced the relative abundance of Bathyarchaeia. Network analysis showed that specific Bathyarchaeia taxa occupied keystone positions in the archaeal community and co-occurred with some methanogenic archaea, including Methanosarcina and Methanobacteria, and ammonia-oxidizing archaea belonging to Nitrososphaeria. This study provides important insights into the biogeography and niche differentiation of Bathyarchaeia particularly in paddy soil ecosystems.

Based on the five main activation mechanisms, this study explored the potential activating elements in Al-based sacrificial anodes (SAs) combining electrochemical experiments and theoretical calculation. Mn, Y, Zr, Nb, and Ta, aligning with several activation mechanisms, are expected to be the potential activating elements besides the acknowledged activating elements (In, Sn, Ga, Zn, Bi). In addition, the negative shift of potential effect of In to Al matrix is denied both experimentally and theoretically. This study will contribute to establish a comprehensive understanding for the development of Al SAs.

To achieve regional ecological management and sustainable socio-economic development, it is essential to comprehend the intricate and interdependent relationships among various ecosystem services. The Agro-pastoral ecotone of northern China is a typical ecologically vulnerable area. There is limited research on managing multiple ecosystem services to maximize supply based on understanding the complex relationships among ecosystem services. This study used the InVEST model to quantify habitat quality (HQ), soil conservation (SC), carbon sequestration (CS), and water yield (WY) in the Agro-pastoral ecotone of northern China in 2000, 2010, and 2020 at the 5 km grid and county scales. Their trade-off and synergistic effects were explored using Spearman correlation analysis and the Geographically Weighted Regression (GWR) model. In addition, self-organizing mapping was employed to identify ecosystem service bundles at two scales, whereas the geodetector was employed to determine the primary social-ecological drivers of ES. Finally, management strategies are proposed based on the research results to promote regional ecological sustainability. The results indicate that: (1) The four ESs exhibited an increasing trend during the study period. Except for WY, the other three ES demonstrated a similar spatial distribution while remaining relatively stable over time; (2) there is a synergistic effect between CS, HQ, and SC, whereas WY-related ES show trade-off effects; (3) six ES bundles were identified at the 5 km grid scale, and four ES bundles were identified at the county scale; (4) precipitation is a major driving factor for WY and an important driving factor for CS, HQ, and SC. In summary, natural factors have a greater impact on ES than socio-economic factors. Based on the differences in ecosystem service bundles and drivers at different scales, and in conjunction with China’s existing environmental policies, corresponding ecological management strategies were proposed, potentially providing a reference for sustainable development of the Agro-pastoral ecotone in northern China.

Background and objective: Neurocritical patients often experience uncontrolled high catabolic metabolism state during the acuta phase of the disease. The complex interactions of neuroendocrine, inflammation, and immune system lead to massive protein breakdown and changes in body composition. Bioelectrical impedance analysis (BIA) evaluates the content and proportions of body components based on the principles of bioelectricity. Its parameters reflect the overall health status of the body and the integrity of cellular structure and function, playing an important role in assessing the disease status and predicting prognosis of such patients. This study explored the association of BIA parameters trajectories with clinical outcomes in neurocritical patients. Methods: This study prospectively collected BIA parameters of 127 neurocritical patients in the Department of Neurology admitted to the NICU for the first 1–7 days. All these patients were adults (≥18 years old) experiencing their first onset of illness and were in the acute phase of the disease. The group-based trajectory modeling (GBTM), which aims to identify individuals following similar developmental trajectories, was used to identify potential subgroups of individuals based on BIA parameters. The short-term prognosis of patients in each trajectory group with variations in phase angle (PA) and extracellular water/total body water (ECW/TBW) over time was differentially analyzed, and the logistic regression model was used to analyze the relationship between potential trajectory groups of PA and ECW/TBW and the short-term prognosis of neurocritical patients. The outcome was Glasgow Outcome Scale (GOS) score at discharge. Results: Four PA trajectories and four ECW/TBW trajectories were detected respectively in neurocritical patients. Among them, compared with the other latent subgroups, the “Low PA rapidly decreasing subgroup” and the “High ECW/TBW slowly rising subgroup” had higher incidences of adverse outcomes at discharge (GOS:1–3), in-hospital mortality, and length of neurology intensive care unit stay (all P

Abstract Background The final step in the anaerobic decomposition of biopolymers is methanogenesis. Rice field soils are a major anthropogenic source of methane, with straw commonly used as a fertilizer in rice farming. Here, we aimed to decipher the structural and functional responses of the methanogenic community to rice straw addition during an extended anoxic incubation (120 days) of Philippine paddy soil. The research combined process measurements, quantitative real-time PCR and RT-PCR of particular biomarkers (16S rRNA, mcrA), and meta-omics (environmental genomics and transcriptomics). Results The analysis methods collectively revealed two major bacterial and methanogenic activity phases: early (days 7 to 21) and late (days 28 to 60) community responses, separated by a significant transient decline in microbial gene and transcript abundances and CH4 production rate. The two methanogenic activity phases corresponded to the greatest rRNA and mRNA abundances of the Methanosarcinaceae but differed in the methanogenic pathways expressed. While three genetically distinct Methanosarcina populations contributed to acetoclastic methanogenesis during the early activity phase, the late activity phase was defined by methylotrophic methanogenesis performed by a single Methanosarcina genomospecies. Closely related to Methanosarcina sp. MSH10X1, mapping of environmental transcripts onto metagenome-assembled genomes (MAGs) and population-specific reference genomes revealed this genomospecies as the key player in acetoclastic and methylotrophic methanogenesis. The anaerobic food web was driven by a complex bacterial community, with Geobacteraceae and Peptococcaceae being putative candidates for a functional interplay with Methanosarcina. Members of the Methanocellaceae were the key players in hydrogenotrophic methanogenesis, while the acetoclastic activity of Methanotrichaceae members was detectable only during the very late community response. Conclusions The predominant but time-shifted expression of acetoclastic and methylotrophic methanogenesis by a single Methanosarcina genomospecies represents a novel finding that expands our hitherto knowledge of the methanogenic pathways being highly expressed in paddy soils. Video Abstract

【Objective】It aims to study the yield performance and source-sink-flow characteristics of new strain of super-large-panicle rice DS23 in early season, and explore the source-flow-sink characteristics and super-high yield potential of DS23, with an aim to provide theoretical basis for high-yield breeding and cultivation of early rice in South China.【Method】The study was conducted under field conditions with the new super-large panicle type strain DS23 as test material and the medium to large panicle type variety YHSM as the control. The leaf area index, SPAD value, accumulation and transport characteristics of non-structural carbohydrate (NSC) in stems, anatomical characteristics of vascular bundles and yield component factors of different panicle types of rice were measured and compared.【Result】The number of grain per panicle, grain weight, sink capacity and yield of DS23 were increased by 37.3%, 4.0%, 33.7% and 15.9% respectively compared to those of YHSM seedlings. The effective number of panicles and seed setting rate were significantly decreased by 6.8% and 15.1% compared to those of YHSM seedlings. There was no significant difference in leaf area index and flag leaf SPAD value between the two varieties at heading stage. Compared with YHSM, total mass of NSC reserved in stem and apparent contribution of transferred NSC to grain yield of DS23 were significantly reduced by 15.3% and 19.8%, respectively, and the apparent transport rate of stem sheath NSC was significantly increased by 10.3%; The DS23 vascular bundle number was significantly increased by 17.3%, and there was no significant difference in the vascular bundle area between the two varieties; DS23 showed no significant change in grain/leaf ratio, with a significant decrease in NSC/spikelet ratio of 34.2% and an increase in vascular bundle load index of 20.4%-60.2%.【Conclusion】The super-large panicle type rice germplasm DS23 planted in early season has a large sink capacity, well-developed vascular bundles transport organization, strong material transformation ability in later stage and great potential for high yield and yield increase. Improvement in seed setting rate is a main direction for exploring its super-high yield potential. The study result lays a theoretical foundation for the breeding of super-large panicle early rice varieties and the research and development of high yield cultivation techniques.

Bacterial assemblages associated with sea urchin are critical to their physiology and ecology within marine ecosystems. In this study, we characterized the bacterial communities in wild sea urchin Anthocidaris crassispina captured in Daya Bay, South China Sea. A total of 363 amplicon sequence variants belonging to nine phyla and 141 genera were classified from intestine, body surface, and surrounding seawater samples. Proteobacteria, Firmicutes, and Bacteroidetes were the dominant bacteria phyla found in this study. A network analysis of bacterial interspecies interactions revealed varying complexity, stability, connectivity, and relationship patterns across the samples, with the most intricate network observed in the surrounding seawater. Metagenomic predictions highlighted the distinct bacterial metabolic pathways, with significant differences between intestine and seawater samples. Notably, pathways associated with polysaccharide degradation, including chitin derivatives, starch, and CoM biosynthesis, were markedly abundant, underscoring the gut microbiota’s key role in digesting algae. In addition, other metabolic pathways in intestine samples were linked to immune response regulation of sea urchins. Overall, this study provides a comprehensive overview of the bacterial community structure and potential functional roles in A. crassispina.

Objective: Rece nt studies ha ve revealed that hemoglobin beta (HBB) plays an important role not only in blood disorders but also in malignancies. The aim of this study is to investigate the clinical significance, diagnostic value, and biological function of HBB in lung cancer. Methods: HBB expression was examined in lung cancer tissues and plasma samples using quantitative real-time polymerase chain reaction, and its relationship with clinical pathological characteristics was analyzed. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic value of HBB in lung cancer. The proliferation of A549 and SPCA1 cells was analyzed using a cell counting kit-8 assay and protein expressions were detected by western blot. Results: The expressions of HBB were found to be down-regulated in both lung cancer tissues and plasma samples. Notably, plasma HBB levels were significantly elevated in postoperative samples when compared to their preoperative counterparts. Across 66 cases of lung cancer tissues, a correlation was observed between HBB levels and both gender and tumor, node, metastasis staging. ROC curve analysis further confirmed the high diagnostic potential of HBB expression in lung cancer. Moreover, the combination of HBB and carcinoembryonic antigen (CEA) had greater significance than HBB or CEA alone in the diagnosis of lung cancer. Knocking out or overexpressing HBB could affect lung cancer cell proliferation through the ERK1/2 signaling pathway. Conclusion: HBB can serve as a novel biomarker for the diagnosis and monitoring of lung cancer, regulating cell proliferation via the ERK1/2 pathway and playing a pivotal role in the oncogenesis and progression of the disease.

In this paper, the multiple constraint least squares solution of the Sylvester equation $ AX+XB = C $ is discussed. The necessary and sufficient conditions for the existence of solutions to the considered matrix equation are given. Noting that the alternating direction method of multipliers (ADMM) is a one-step iterative method, a multi-step alternating direction method of multipliers (MSADMM) to solve the considered matrix equation is proposed and some convergence results of the proposed algorithm are proved. Problems that should be studied in the near future are listed. Numerical comparisons between MSADMM, ADMM and ADMM with Anderson acceleration (ACADMM) are included.

The ecologically fragile agro-pastoral ecotone in northern China is characterized by relatively poor arable land quality. Yunzhou District in Datong City, which is situated within this transitional zone, boasts over 600 years of Hemerocallis citrina Baroni cultivation. Exploring the effects of soil physicochemical properties on daylily yield and related agronomic traits is essential for enhancing the ecological and economic value of dominant crops in ecologically fragile areas. Therefore, in this study, we focused on the daylily, a characteristic cash crop that is grown in the agro-pastoral ecotone in Yunzhou District. Physicochemical property measurement and yield estimation were performed using soil samples collected from 37 sites, with Spearman’s correlation analysis, one-way analysis of variance with multiple comparisons, path analysis, and stepwise regression analysis used to analyze the generated data. The results showed the following: (1) The pathway analysis of daylily yield with each agronomic trait showed that the BN and PH directly affected the yield of daylily with direct pathway coefficients of 0.844 and 0.7, respectively, whereas the SN indirectly affected the yield of daylily through the BD and PH, with indirect pathway coefficients of 0.827 and 0.566, respectively. (2) A total of four principal components were extracted for the soil factors, of which SMC, ST and BD had large loadings on PC1; OM, TN and pH had large loadings on PC2; AK had large loadings on PC3; and AP had large loadings on PC4. (3) From the principal component regression and stepwise regression, it can be seen that SMC is the most critical factor affecting the yield of daylily, as well as the related agronomic traits, and the results also show that yield prediction was affected by OM, ST, and AK, while BN was influenced by OM and ST, and SN and PH were influenced by AP. Comparing the goodness of fit and significance of the two models, it can be concluded that the stepwise regression model is the optimal model for this study.

The farming–pastoral ecotone in northern China is an ecologically vulnerable area with low-quality arable land, and cash crops are an important economic source for local farmers. Although local governments have introduced supportive policies, there are still several factors that hinder the implementation of the policies: there is a lack of sufficient research on the distribution of specialty crops, and the driving factors for agricultural planting structure adjustment are not yet clear. In this study, the specialty cash crop of the daylily planting industry in Yunzhou District, in the Farming–Pastoral Ecotone in northern China, was selected as the research object. Field surveys were conducted to collect sample points and village-level survey data, which were further combined with Sentinel-1 and Sentinel-2 data, and vegetation indices. Support vector machine (SVM) and random forest (RF) classifiers were utilized to identify daylilies and compare the accuracy using different combinations of input data. Furthermore, the classification results were counted by village, and spatial autocorrelation was used to analyze the spatial distribution pattern of daylilies. Finally, in conjunction with the village-level survey data, Spearman correlation analysis, multiple regression trees (MRT), and random forests were employed to explore the driving factors of daylily cultivation. The results indicate that using an RF classification tree of 300 resulted in the optimal method, as it achieved the highest accuracy for crop classification. The overall accuracy and daylily classification accuracy were 94.6% and 94.75%, respectively. Daylily distributions were mainly concentrated near the Sanggan River, urban areas, and the tourism industry. The distribution area of daylilies in each village was concentrated in 13.4–38.8 hm2. Spatial clustering showed more aggregation of low–low and high–high types. Labor force and daylily yield were identified as the most significant influencing factors. Further analysis of the different regions revealed the importance of industry support policies and technical training. This study provides data to support the distribution of specialty crops in Yunzhou District and a technical basis for adjusting agricultural planting structures.

● Matching nitrification inhibitors with soil properties and nitrifiers is vital to achieve a higher NUE. ● Enhancing BNF, DNRA and microbial N immobilization processes via soil amendments can greatly contribute to less chemical N fertilizer input. ● Plant-associated microbiomes are critical for plant nutrient uptake, growth and fitness. ● Coevolutionary trophic relationships among soil biota need to be considered for improving crop NUE. Soil microbiomes drive the biogeochemical cycling of nitrogen and regulate soil N supply and loss, thus, pivotal nitrogen use efficiency (NUE). Meanwhile, there is an increasing awareness that plant associated microbiomes and soil food web interactions is vital for modulating crop productivity and N uptake. The rapid advances in modern omics-based techniques and biotechnologies make it possible to manipulate soil-plant microbiomes for improving NUE and reducing N environmental impacts. This paper summarizes current progress in research on regulating soil microbial N cycle processes for NUE improvement, plant-microbe interactions benefiting plant N uptake, and the importance of soil microbiomes in promoting soil health and crop productivity. We also proposes a potential holistic (rhizosphere-root-phyllosphere) microbe-based approach to improve NUE and reduce dependence on mineral N fertilizer in agroecosystems, toward nature-based solution for nutrient management in intensive cropping systems.

Wilson's disease (WD) is a genetic disorder with the A7P7B gene mutations. It is difficult to diagnose in clinic. The purpose of this study was to confirm whether amplitude of low-frequency fluctuations (ALFF) is one of the potential biomarkers for the diagnosis of WD. The study enrolled 30 healthy controls (HCs) and 37 WD patients (WDs) to obtain their resting-state functional magnetic resonance imaging (rs-fMRI) data. ALFF was obtained through preprocessing of the rs-fMRI data. To distinguish between patients with WDs and HCs, four clusters with abnormal ALFF-z values were identified through between-group comparisons. Based on these clusters, three machine learning models were developed, including Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR). Abnormal ALFF z-values were also combined with volume information, clinical variables, and imaging features to develop machine learning models. There were 4 clusters where the ALFF z-values of the WDs were significantly higher than that of the HCs. Cluster1 was in the cerebellar region, Cluster2 was in the left caudate nucleus, Cluster3 was in the bilateral thalamus, and Cluster4 was in the right caudate nucleus. In the training set and test set, the models trained with Cluster2, Cluster3, and Cluster4 achieved area of curve (AUC) greater than 0.80. In the Delong test, only the AUC values of models trained with Cluster4 exhibited statistical significance. The AUC values of the Logit model (P = 0.04) and RF model (P = 0.04) were significantly higher than those of the SVM model. In the test set, the LR model and RF model trained with Cluster3 had high specificity, sensitivity, and accuracy. By conducting the Delong test, we discovered that there was no statistically significant inter-group difference in AUC values between the model that integrates multi-modal information and the model before fusion. The LR models trained with multimodal information and Cluster 4, as well as the LR and RF models trained with multimodal information and Cluster 3, have demonstrated high accuracy, specificity, and sensitivity. Overall, these findings suggest that using ALFF based on the thalamus or caudate nucleus as markers can effectively differentiate between WDs and HCs. The fusion of multimodal information did not significantly improve the classification performance of the models before fusion.

Mapping soil organic carbon (SOC) accurately is essential for sustainable soil resource management. Hyperspectral data, a vital tool for SOC mapping, is obtained through both laboratory and satellite-based sources. While laboratory data is limited to sample point monitoring, satellite hyperspectral imagery covers entire regions, albeit susceptible to external environmental interference. This study, conducted in the Yuncheng Basin of the Yellow River Basin, compared the predictive accuracy of laboratory hyperspectral data (ASD FieldSpec4) and GF-5 satellite hyperspectral imagery for SOC mapping. Leveraging fractional order derivatives (FODs), various denoising methods, feature band selection, and the Random Forest model, the research revealed that laboratory hyperspectral data outperform satellite data in predicting SOC. FOD processing enhanced spectral information, and discrete wavelet transform (DWT) proved effective for GF-5 satellite imagery denoising. Stability competitive adaptive re-weighted sampling (sCARS) emerged as the optimal feature band selection algorithm. The 0.6FOD-sCARS RF model was identified as the optimal laboratory hyperspectral prediction model for SOC, while the 0.8FOD-DWT-sCARS RF model was deemed optimal for satellite hyperspectral prediction. This research, offering insights into farmland soil quality monitoring and strategies for sustainable soil use, holds significance for enhancing agricultural production efficiency.

Abstract Objectives Intestinal mucositis is the major side effect during abdominal or pelvic radiotherapy, but the underlying immunogen remains to be further characterised and few radioprotective agents are available. This study investigated the role of dsDNA‐triggered inflammasomes in intestinal mucositis during radiotherapy. Methods Pro‐inflammatory cytokines were detected by ELISA. Radiation‐induced intestinal injury in mice was analyzed by means of survival curves, body weight, HE staining of intestines, and intestinal barrier integrity. Western blot, immunofluorescence staining, co‐immunoprecipitation assay and flow cytometry were used to investigate the regulatory role of dsDNA on inflammasomes. Results Here, we show that a high level of IL‐1β and IL‐18 is associated with diarrhoea in colorectal cancer (CRC) patients during radiotherapy, which accounts for intestinal radiotoxicity. Subsequently, we found that the dose‐dependently released dsDNA from the intestinal epithelial cells (IECs) serves as the potential immunogenic molecule for radiation‐induced intestinal mucositis. Our results further indicate that the released dsDNA transfers into the macrophages in an HMGB1/RAGE‐dependent manner and then triggers absent in melanoma 2 (AIM2) inflammasome activation and the IL‐1β and IL‐18 secretion. Finally, we show that the FDA‐approved disulfiram (DSF), a newly identified inflammasome inhibitor, could mitigate intestinal radiotoxicity by controlling inflammasome. Conclusion These findings indicate that the extracellular self‐dsDNA released from the irradiated IECs is a potential immunogen to stimulate immune cells and trigger the subsequent intestinal mucositis, while blunting the dsDNA‐triggered inflammasome in macrophages may represent an exciting therapeutic strategy for side effects control during abdominal radiotherapy.

Precisely predict the current on the node circuit in advance, which can facilitate the manager to manage and control the risk in advance. The current, voltage, residual current, cable temperature, ambient temperature, and ambient humidity on the circuit constitute a multi-dimensional sequence characteristic sequence data. This paper proposes an improved Long Short-Term Memory (LSTM) cyclic neural network method, which combines multi-dimensional Train the neural network in a specific way to obtain the LSTM current prediction model. The experiment is validated with the perception data in an intelligent building, and compared with the classic neural network and Recurrent Neural Network (RNN) prediction method. The experimental results show that, compared with the prediction methods such as BP neural network and RNN network, the multi-dimensional LSTM has a higher accuracy in predicting the current in the circuit, and the MSE index is as low as 0.5. And this method can detect potential electrical fire hazards and give early warning 1–2 time intervals in advance to avoid electrical fires.

The increasing burden and health risks of antimicrobial resistance (AMR) pose a great threat to society overall. Lipopeptides exhibit great potential as novel and safe alternatives to traditional antibiotics. In this study, the strain YA215, which was isolated from the mangrove area in Beibu Gulf, Guangxi, China, was identified as Bacillus velezensis. Then, YA215 lipopeptide extracts (YA215LE) from B. velezensis was found to exhibit a wide spectrum of antibacterial and antifungal activities. Additionally, YA215LE was identified and found to contain three groups of lipopeptides (surfactin, iturin, and fengycin). Furthermore, one separation fraction (BVYA1) with significant antibacterial activity was obtained. Additionally, liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of BVYA1 showed three molecular ion peaks ([M + H]+: m/z 980.62; 994.66; 1008.66) corresponding to conventional surfactin homologs. By MS/MS analysis, BVYA1 was identified as sufactin with the precise amino acid sequence Glu–Leu/Ile–Leu–Val–Asp–Leu–Leu/Ile and hydroxyl fatty acids with 11–13 carbons. [M + H]+ at m/z 980.62 was detected for the first time in B. velezensis, which demonstrates that the strain corresponds to a new surfactin variant. In particular, BVYA1 showed antibacterial activity with the minimum inhibitory concentration (MIC) values of 7.5–15 μg/ml. Finally, the preliminary mechanism of inhibiting E. coli treated with BVYA1 showed that BVYA1 effectively permeabilized the cytoplasmic membrane and disrupted the morphology of targeted bacterial cells. In conclusion, this study suggests that the YA215LE from B. velezensis YA215 might be a potential candidate for a bactericide.

The effect of different heat inputs of 1.45 kJ/mm, 1.78 kJ/mm and 2.31 kJ/mm on the microstructure and mechanical properties of deposited metals of the self-developed AWS A5.28 E120C-K4 high strength steel flux-cored wire was studied by optical microscope, scanning electron microscope and mechanical property test. With the increase in heat input, the results showed that the microstructure of deposited metals became coarse. Acicular ferrite increased at first and then decreased, granular bainite increased and degenerated upper bainite and martensite decreased slightly. Under the low heat input of 1.45 kJ/mm, the cooling rate was fast and the element diffusion was uneven, which caused composition segregation and easy to form large size inclusions SiO2-TiC-CeAlO3 with weak binding to the matrix. Under the middle heat input of 1.78 kJ/mm, the composite rare earth inclusions in dimples were mainly TiC-CeAlO3. The dimples were small and uniformly distributed, and the dimple fracture mainly depended on the wall-breaking connection between medium-sized dimples rather than an intermediate media. Under the high heat input of 2.31 kJ/mm, SiO2 was easy to adhere to high melting point Al2O3 oxides to form irregular composite inclusions. Such irregular inclusions do not need to absorb too much energy to form necking. Finally, the integrated effects of microstructure and inclusions resulted in the optimum mechanical properties of deposited metals with a heat input of 1.78 kJ/mm, which was a tensile strength of 793 MPa and an average impact toughness at −40 °C of 56 J.

ABSTRACT Enhancing soil phosphate solubilization is a promising strategy for agricultural sustainability, while little is known about the mechanisms of how microorganisms cope with differing phosphorus availability. Using a combination of genome-resolved metagenomics and amplicon sequencing, we investigated the microbial mechanisms involved in phosphorus cycling under three agricultural treatments in a wheat-maize rotation system and two natural reforestation treatments. Available soil phosphorus was the key factor shaping bacterial and fungal community composition and function across our agricultural and reforestation sites. Membrane-bound quinoprotein glucose dehydrogenase (PQQGDH) and exopolyphosphatases (PPX) governed microbial phosphate solubilization in agroecosystems. In contrast, genes encoding glycerol-3-phosphate transporters (ugpB, ugpC, and ugpQ) displayed a significantly greater abundance in the reforestation soils. The gcd gene encoding PQQGDH was found to be the best determinant for bioavailable soil phosphorus. Metagenome-assembled genomes (MAGs) affiliated with Cyclobacteriaceae and Vicinamibacterales were obtained from agricultural soils. Their MAGs harbored not only gcd but also the pit gene encoding low-affinity phosphate transporters. MAGs obtained from reforestation soils were affiliated with Microtrichales and Burkholderiales. These contain ugp genes but no gcd, and thereby are indicative of a phosphate transporter strategy. Our study demonstrates that knowledge of distinct microbial phosphorus acquisition strategies between agricultural and reforestation soils could help in linking microbial processes with phosphorus cycling. IMPORTANCE The soil microbiome is the key player regulating phosphorus cycling processes. Identifying phosphate-solubilizing bacteria and utilizing them for release of recalcitrant phosphate that is bound to rocks or minerals have implications for improving crop nutrient acquisition and crop productivity. In this study, we combined functional metagenomics and amplicon sequencing to analyze microbial phosphorus cycling processes in natural reforestation and agricultural soils. We found that the phosphorus acquisition strategies significantly differed between these two ecosystems. A microbial phosphorus solubilization strategy dominated in the agricultural soils, while a microbial phosphate transporter strategy was observed in the reforestation soils. We further identified microbial taxa that contributed to enhanced phosphate solubilization in the agroecosystem. These microbes are predicted to be beneficial for the increase in phosphate bioavailability through agricultural practices.

The Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature (LST) has been operationally produced for a decade since the Suomi National Polar-orbiting Partnership (SNPP) launched in October 2011. A comprehensive evaluation of its accuracy and precision will be helpful for product users in climate studies and atmospheric models. In this study, the VIIRS LST is validated with ground observations from multiple high-quality radiation networks, including six stations from the Surface Radiation budget (SURFRAD) network, two stations from the Baseline Surface Radiation Network (BSRN), and 13 stations from the Atmospheric Radiation Measurement (ARM) network, to evaluate its performance over various land-cover types. The VNP21A1 LST was validated against the same ground observations as a reference. The results yield a close agreement between the SNPP VIIRS LST and ground LSTs with a bias of −0.4 K and a RMSE of 1.96 K over six SURFRAD sites; a bias of −0.2 K and a RMSE of 1.93 K over two BSRN sites; and a bias of −0.1 K and a RMSE of 1.7 K over the 13 ARM sites. The time series of the LST errors over individual sites indicate seasonal cycles. The data anomaly over the BSRN site in Cabauw and the SURFRAD site in Desert Rock is revealed and discussed in this study. In addition, a method using Landsat-8 data is applied to quantify the heterogeneity level of each ground station and the results provide promising insights. The validation results demonstrate the maturity of the JPSS VIIRS LST products and their readiness for various application studies.

ZnO:Al films were prepared by magnetron sputtering at room temperature. During the growth process, H radicals produced by radio frequency power sources were in situ introduced into ZnO:Al films. By injecting H radicals, the content of Al in ZnO:Al films increased from 3.4 at. % to 6.1 at. %, which could be ascribed to the reaction between H radicals and ZnO as well as the resputtering of the Zn element. Surface morphologies of ZnO:Al films were tuned from smooth shape to sunflower seed-like. Furthermore, ZnO:Al films without injecting H radicals showed highly c-axis preferential orientation and then nearly became amorphous with the addition of H radicals, which corresponds to the results of Raman spectra. The grain boundary potentials decreased due to the removal of oxygen at grain boundaries and an amount of Vo was produced, which was proved by Raman and x-ray photoelectron spectroscopy results. The optimal resistivity of as-grown ZnO:Al films co-doped with H radicals was 1.5 × 10−3 Ω cm at an H2 ratio of 2.3%. The variation of the carrier concentration for annealed ZnO:Al films at different H2 ratios supported the existence of H interstitials and Vo. The optical bandgap varied from 3.44 eV to 3.71 eV with increasing H radicals.

Humic acids (HAs) can function as electron mediators for contaminants transformation in different environments. The humus respiration can facilitate pentachlorophenol (PCP) dechlorination during different biowastes composting. However, different characteristics of synthetic pathways of redox functional groups within HAs during different biowastes composting have never been characterized. Herein, we assessed the synthetic pathways of redox functional groups within HAs from protein-, lignocellulose-, and lignin-rich composts that facilitated the microbially reductive dechlorination of PCP, respectively. The results show that the aromatic systems are the major electron-accepting moieties of HAs and function as electron shuttles to facilitate the PCP dechlorination. Amino acid and reducing sugar are the major precursors for the synthesis of redox functional groups within HAs in protein-rich composts, and polyphenols and amino acids are discerned as the significant components to synthesize redox functional groups of HAs in lignocellulose- and lignin-rich composts. Seven groups of bacterial communities based on relationships among remarkable precursors, key bacterial communities, and redox functional groups within HAs are classified as participants in the precursors’ catabolism and aromatic system’ anabolism. Furthermore, the significant environmental factors on the synthetic pathways of redox functional groups within HAs in composting are confirmed by structural equation models. Conclusively, the regulating methods for promoting PCP dechlorination by HAs during different biowastes composting are proposed. Our results can help in understanding the distinct formative mechanisms of redox functional groups within HAs during different biowastes composting, providing insights into a classification-oriented approach for recycling utilization of different biowastes. Keywords: Different biowaste composting, Humic acid, Redox functional groups, Biological metabolism, Pentachlorophenol

Abstract Background The expected increase in global surface temperature due to climate change may have a tremendous effect on the structure and function of the anaerobic food web in flooded rice field soil. Here, we used the metatranscriptomic analysis of total RNA to gain a system-level understanding of this temperature effect on the methanogenic food web. Results Mesophilic (30 °C) and thermophilic (45 °C) food web communities had a modular structure. Family-specific rRNA dynamics indicated that each network module represents a particular function within the food webs. Temperature had a differential effect on all the functional activities, including polymer hydrolysis, syntrophic oxidation of key intermediates, and methanogenesis. This was further evidenced by the temporal expression patterns of total bacterial and archaeal mRNA and of transcripts encoding carbohydrate-active enzymes (CAZymes). At 30 °C, various bacterial phyla contributed to polymer hydrolysis, with Firmicutes decreasing and non-Firmicutes (e.g., Bacteroidetes, Ignavibacteriae) increasing with incubation time. At 45 °C, CAZyme expression was solely dominated by the Firmicutes but, depending on polymer and incubation time, varied on family level. The structural and functional community dynamics corresponded well to process measurements (acetate, propionate, methane). At both temperatures, a major change in food web functionality was linked to the transition from the early to late stage. The mesophilic food web was characterized by gradual polymer breakdown that governed acetoclastic methanogenesis (Methanosarcinaceae) and, with polymer hydrolysis becoming the rate-limiting step, syntrophic propionate oxidation (Christensenellaceae, Peptococcaceae). The thermophilic food web had two activity stages characterized first by polymer hydrolysis and followed by syntrophic oxidation of acetate (Thermoanaerobacteraceae, Heliobacteriaceae, clade OPB54). Hydrogenotrophic Methanocellaceae were the syntrophic methanogen partner, but their population structure differed between the temperatures. Thermophilic temperature promoted proliferation of a new Methanocella ecotype. Conclusions Temperature had a differential effect on the structural and functional continuum in which the methanogenic food web operates. This temperature-induced change in food web functionality may not only be a near-future scenario for rice paddies but also for natural wetlands in the tropics and subtropics.

A batch of Sn oxides was fabricated by pulse direct current reactive magnetron sputtering (pDC−RMS) using different Ar/O2 flow ratios at 0.3 Pa; the influence of stoichiometry on the physical and electrochemical properties of the films was evaluated by the characterization of scanning electron microscope (SEM), X-ray diffraction (XRD), X-ray reflection (XRR), X-ray photoelectron spectroscopy (XPS) and more. The results were as follows. First, the film surface transitioned from a particle morphology (roughness of 50.0 nm) to a smooth state (roughness of 3.7 nm) when Ar/O2 flow ratios changed from 30/0 to 23/7; second, all SnOx films were in an amorphous state, some samples deposited with low O2 flow ratios (≤2 sccm) still included metallic Sn grains. Therefore, the stoichiometry of SnOx calculated by XPS spectra increased linearly from SnO0.0.08 to SnO1.71 as the O2 flow ratios increased, and the oxidation degree was further calibrated by the average valence method and SnO2 standard material. Finally, the electrochemical performance was confirmed to be improved with the increase in oxidation degree (x) in SnOx, and the SnO1.71 film deposited with Ar/O2 = 23/7 possessed the best cycle performance, reversible capacity of 396.1 mAh/g and a capacity retention ratio of 75.4% after 50 cycles at a constant current density of 44 μA/cm2.

Highly transparent indium-free multilayers of TiO2/Cu/TiO2 were obtained by means of annealing. The effects of Cu thickness and annealing temperature on the electrical and optical properties were investigated. The critical thickness of Cu mid-layer with optimal electrical and optical properties was 10 nm, with the figure of merit reaching as high as 5 × 10−3 Ω−1. Partial crystallization of the TiO2 layer enhanced the electrical and optical properties upon annealing. Electrothermal experiments showed that temperatures of more than 100 °C can be reached at a heating rate of 2 °C/s without any damage to the multilayers. The experimental results indicate that reliable transparent TiO2/Cu/TiO2 multilayers can be used for electrothermal application.

Albedo characterizes the radiometric interface of land surfaces, especially vegetation, and the atmosphere. Albedo is a critical input to many models, such as crop growth models, hydrological models and climate models. For the extensive attention to crop monitoring, a physical albedo model for crops is developed based on the law of energy conservation and spectral invariants, which is derived from a prior forest albedo model. The model inputs have been efficiently and physically parameterized, including the dependency of albedo on the solar zenith/azimuth angle, the fraction of diffuse skylight in the incident radiance, the canopy structure, the leaf reflectance/transmittance and the soil reflectance characteristics. Both the anisotropy of soil reflectance and the clumping effect of crop leaves at the canopy scale are considered, which contribute to the improvement of the model accuracy. The comparison between the model results and Monte Carlo simulation results indicates that the canopy albedo has high accuracy with an RMSE < 0.005. The validation using ground measurements has also demonstrated the reliability of the model and that it can reflect the interaction mechanism between radiation and the canopy-soil system.

A land-cover-based linear BRDF (bi-directional reflectance distribution function) unmixing (LLBU) algorithm based on the kernel-driven model is proposed to combine the compact airborne spectrographic imager (CASI) reflectance with the moderate resolution imaging spectroradiometer (MODIS) daily reflectance product to derive the BRDF/albedo of the two sensors simultaneously in the foci experimental area (FEA) of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER), which was carried out in the Heihe River basin, China. For each land cover type, an archetypal BRDF, which characterizes the shape of its anisotropic reflectance, is extracted by linearly unmixing from the MODIS reflectance with the assistance of a high-resolution classification map. The isotropic coefficients accounting for the differences within a class are derived from the CASI reflectance. The BRDF is finally determined by the archetypal BRDF and the corresponding isotropic coefficients. Direct comparisons of the cropland archetypal BRDF and CASI albedo with in situ measurements show good agreement. An indirect validation which compares retrieved BRDF/albedo with that of the MCD43A1 standard product issued by NASA and aggregated CASI albedo also suggests reasonable reliability. LLBU has potential to retrieve the high spatial resolution BRDF/albedo product for airborne and spaceborne sensors which have inadequate angular samplings. In addition, it can shorten the timescale for coarse spatial resolution product like MODIS.

The adjacency effect and non-uniform responses complicate the precise delimitation of the surface support of remote sensing data and their derived products. Thus, modeling spatial response characteristics (SRCs) prior to using remote sensing information has become important. A point spread function (PSF) is typically used to describe the SRCs of the observation cells from remote sensors and is always estimated in a laboratory before the sensor is launched. However, research on the SRCs of high-order remote sensing products derived from the observations remains insufficient, which is an obstacle to converting between multi-scale remote sensing products and validating coarse-resolution products. This study proposed a method that combines simulation and validation to establish SRC models of coarse-resolution albedo products. Two series of commonly used 500-m/1-km resolution albedo products, which are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data, were investigated using 30-m albedo products that provide the required sub-pixel information. The analysis proves that the size of the surface support of each albedo pixel is larger than the nominal resolution of the pixel and that the response weight is non-uniformly distributed, with an elliptical Gaussian shape. The proposed methodology is generic and applicable for analyzing the SRCs of other advanced remote sensing products.

How to obtain the “truth” of land surface parameter as reference value to validate the remote sensing retrieved parameter in heterogeneous scene and coarse-resolution pixel is one of the most challenging topics in environmental studies. In this paper, a distributed sensor network system named CPP-WSN was established to capture the spatial and temporal variation of land surface parameters at coarse-resolution satellite pixel scale around the Huailai Remote Sensing Station, which locates in the North China Plain. The system consists of three subnetworks that are RadNet, SoilNet, and VegeNet. Time series observations of typical land surface parameters, including UVR, PAR, SWR, LWR, albedo, and land surface temperature (LST) from RadNet, multilayer soil moisture and soil temperature from SoilNet, and fraction of vegetation cover (FVC), clumping index (CI), and leaf area index (LAI) from VegeNet, have been obtained and shared on the web. Compared with traditional single-point measurement, the “true” reference value of coarse pixel is obtained by averaging or representativeness-weighted averaging the multipoint measurements acquired using the sensor network. The preliminary applications, which validate several remote sensing products with CPP-WSN data, demonstrate that a high quality ground “truth” dataset has been available for remote sensing as well as other applications.

Ice albedo feedback amplifies climate change signals and thus affects the global climate. Global long-term records on sea-ice albedo are important to characterize the regional or global energy budget. As the successor of MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite) started its observation from October 2011 on S-NPP (Suomi National Polar-orbiting Partnership). It has improved upon the capabilities of the operational Advanced Very High Resolution Radiometer (AVHRR) and provides observation continuity with MODIS. We used a direct estimation algorithm to produce a VIIRS sea-ice albedo (VSIA) product, which will be operational in the National Oceanic and Atmospheric Administration’s (NOAA) S-NPP Data Exploration (NDE) version of the VIIRS albedo product. The algorithm is developed from the angular bin regression method to simulate the sea-ice surface bidirectional reflectance distribution function (BRDF) from physical models, which can represent different sea-ice types and vary mixing fractions among snow, ice, and seawater. We compared the VSIA with six years of ground measurements at 30 automatic weather stations from the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Greenland Climate Network (GC-NET) as a proxy for sea-ice albedo. The results show that the VSIA product highly agreed with the station measurements with low bias (about 0.03) and low root mean square error (RMSE) (about 0.07) considering the Joint Polar Satellite System (JPSS) requirement is 0.05 and 0.08 at 4 km scale, respectively. We also evaluated the VSIA using two datasets of field measured sea-ice albedo from previous field campaigns. The comparisons suggest that VSIA generally matches the magnitude of the ground measurements, with a bias of 0.09 between the instantaneous albedos in the central Arctic and a bias of 0.077 between the daily mean albedos near Alaska. The discrepancy is mainly due to the scale difference at both spatial and temporal dimensions and the limited sample size. The VSIA data will serve for weather prediction applications and climate model calibrations. Combined with the historical observations from MODIS, current S-NPP VIIRS, and NOAA-20 VIIRS observations, VSIA will dramatically contribute to providing high-accuracy routine sea-ice albedo products and irreplaceable records for monitoring the long-term sea-ice albedo for climate research.

The Clumping Index (Ω) was introduced to quantify the spatial distribution pattern of vegetation elements. It is crucial to improve the estimation accuracy of vital vegetation parameters, such as Leaf Area Index (LAI) and Gross Primary Production (GPP). Meanwhile, the parameterization of Ω is challenging partly due to the varying observations of canopy gaps from different view angles. Many previous studies have shown the increase of Ω with view zenith angle through samples of gap size distribution from in situ measurements. In contrast, remote sensing retrieval algorithms only assign a constant value for each biome type to roughly correct the clumping effect as a compromise between the accuracy and efficiency. In this paper, analytical models are proposed that estimate the directional clumping index (Ω(θ)) of crop and forest at canopy level. The angular variation trend and magnitude of crop Ω(θ) was analyzed within row structure where vegetation elements are randomly spaced along rows. The forest model predicts Ω(θ) with tree density, distribution pattern, crown shape, trunk size, and leaf area and angle distribution function. The models take into account the main directional characteristics of clumping index using easy-to-measure parameters. Test cases showed that Ω(θ) magnitude variation for black spruce forest was 102.3% of the hemispherical average clumping index ( Ω ˜ ), whereas the Larch forest had 48.7% variation, and row crop variation reached 32.4%. This study provided tools to assess Ω(θ) of discontinuous canopies.

In contrast to herbaceous canopies and forests, savannas are grassland ecosystems with sparsely distributed individual trees, so the canopy is spatially heterogeneous and open, whereas the woody cover in savannas, e.g., tree cover, adversely affects ecosystem structures and functions. Studies have shown that the dynamics of canopy structure are related to available water, climate, and human activities in the form of porosity, leaf area index (LAI), and clumping index (CI). Therefore, it is important to identify the biophysical parameters of savanna ecosystems, and undertake practical actions for savanna conservation and management. The canopy openness presents a challenge for evaluating canopy LAI and other biophysical parameters, as most remotely sensed methods were developed for homogeneous and closed canopies. Clumping index is a key variable that can represent the clumping effect from spatial distribution patterns of components within a canopy. However, it is a difficult task to measure the clumping index of the moderate resolution savanna pixels directly using optical instruments, such as the Tracing Radiation and Architecture of Canopies, LAI-2000 Canopy Analyzer, or digital hemispherical photography. This paper proposed a new method using hemispherical photographs combined with high resolution remote sensing images to estimate the clumping index of savanna canopies. The effects of single tree LAI, crown density, and herbaceous layer on the clumping index of savanna pixels were also evaluated. The proposed method effectively calculated the clumping index of moderate resolution pixels. The clumping indices of two study regions located in Ejina Banner and Weichang were compared with the clumping index product over China’s landmass.

Mountainous areas with rugged terrains are widely distributed around the world. Remotely sensed values of the fraction of absorbed photosynthetically active radiation (FAPAR) suffer from the effect of rugged terrain. In this study, the effect of rugged terrain was incorporated into the FAPAR model based on recollision probability (FAPAR-P), which was improved in two aspects: calculating the sky viewing factor to correct for the fraction of diffuse sky radiation to the total radiation, and correcting the interception probability according to the slope and aspect of each pixel. The newly developed model is called FAPAR-PR (FAPAR-P Model for Rugged Terrain Area). Two study areas were chosen to validate the proposed model: the Dayekou watershed in Gansu Province, and Weichang in Hebei Province, China. The FAPAR values derived from the models were compared with FAPAR values measured in situ using photon flux sensors and the SunScan canopy analysis system (Delta-T Devices Ltd., Cambridge, UK). The validation results show that the FAPAR-PR model is applicable to rugged terrain areas, and it achieves a high level of accuracy. The FAPAR retrieval at different scales was also conducted to estimate the effect of terrain on the FAPAR-P and FAPAR-PR models. In our chosen study area, the effect of rugged terrain was significant in fine resolution pixels, but it was not obvious at larger scales, as the effects of slope and aspect were partly eliminated by the upscaling of the digital elevation model.

tRNase Z is the endonuclease responsible for removing the 3'-trailer sequences from precursor tRNAs, a prerequisite for the addition of the CCA sequence. It occurs in the short (tRNase Z(S)) and long (tRNase Z(L)) forms. Here we report the identification and sequence analysis of candidate tRNase Zs from 81 metazoan species. We found that the vast majority of deuterostomes, lophotrochozoans and lower metazoans have one tRNase Z(S) and one tRNase Z(L) genes, whereas ecdysozoans possess only a single tRNase Z(L) gene. Sequence analysis revealed that in metazoans, a single nuclear tRNase Z(L) gene is likely to encode both the nuclear and mitochondrial forms of tRNA 3'-end processing enzyme through mechanisms that include alternative translation initiation from two in-frame start codons and alternative splicing. Sequence conservation analysis revealed a variant PxKxRN motif, PxPxRG, which is located in the N-terminal region of tRNase Z(S)s. We also identified a previously unappreciated motif, AxDx, present in the C-terminal region of both tRNase Z(S)s and tRNase Z(L)s. The AxDx motif consisting mainly of a very short loop is potentially close enough to form hydrogen bonds with the loop containing the PxKxRN or PxPxRG motif. Through complementation analysis, we demonstrated the likely functional importance of the AxDx motif. In conclusion, our analysis supports the notion that in metazoans a single tRNase Z(L) has evolved to participate in both nuclear and mitochondrial tRNA 3'-end processing, whereas tRNase Z(S) may have evolved new functions. Our analysis also unveils new evolutionarily conserved motifs in tRNase Zs, including the C-terminal AxDx motif, which may have functional significance.

The development of new procedures and protocols that allow researchers to obtain recombinant proteins is of fundamental importance in the biotechnology field. A strategy was explored to overcome inclusion-body formation observed when expressing an aggregation-prone fungal xylanase in Escherichia coli. pHsh is an expression plasmid that uses a synthetic heat-shock (Hsh) promoter, in which gene expression is regulated by an alternative sigma factor (σ(32)). A derivative of pHsh was constructed by fusing a signal peptide to xynA2 gene to facilitate export of the recombinant protein to the periplasm. The xylanase was produced in a soluble form. Three factors were essential to achieving such soluble expression of the xylanase: 1) the target gene was under the control of the Hsh promoter, 2) the gene product was exported into the periplasm, and 3) gene expression was induced by a temperature upshift. For the first time we report the expression of periplasmic proteins under the control of an Hsh promoter regulated by σ(32). One unique feature of this approach was that over 200 copies of the Hsh promoter in an E. coli cell significantly increased the concentration of σ(32). The growth inhibition of the recombinant cells corresponded to an increase in the levels of soluble periplasmic protein. Therefore, an alternative protocol was designed to induce gene expression from pHsh-ex to obtain high levels of active soluble enzymes.