Bacterial community structure and co-occurrence networks in the rhizosphere and root endosphere of the grafted apple.

BACKGROUND: Compared with aerial plant tissues (such as leaf, stem, and flower), root-associated microbiomes play an indisputable role in promoting plant health and productivity. We thus explored the similarities and differences between rhizosphere and root endosphere bacterial community in the grafted apple system. RESULTS: Using pot experiments, three microhabitats (bulk soil, rhizosphere and root endosphere) samples were obtained from two-year-old apple trees grafted on the four different rootstocks. We then investigated the bacterial community composition, diversity, and co-occurrence network in three microhabitats using the Illumina sequencing methods. Only 63 amplicon sequence variants (ASVs) out of a total of 24,485 were shared in the rhizosphere and root endosphere of apple grafted on the four different rootstocks (M9T337, Malus hupehensis Rehd., Malus robusta Rehd., and Malus baccata Borkh.). The core microbiome contained 8 phyla and 25 families. From the bulk soil to the rhizosphere to the root endosphere, the members of the phylum and class levels demonstrated a significant enrichment and depletion pattern. Co-occurrence network analysis showed the network complexity of the rhizosphere was higher than the root endosphere. Most of the keystone nodes in both networks were classified as Proteobacteria, Actinobacteriota and Bacteroidetes and were low abundance species. CONCLUSION: The hierarchical filtration pattern existed not only in the assembly of root endosphere bacteria, but also in the core microbiome. Moreover, most of the core ASVs were high-abundance species, while the keystone ASVs of the network were low-abundance species.

DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery.

Artificial intelligence (AI)-aided drug design has demonstrated unprecedented effects on modern drug discovery, but there is still an urgent need for user-friendly interfaces that bridge the gap between these sophisticated tools and scientists, particularly those who are less computer savvy. Herein, we present DrugFlow, an AI-driven one-stop platform that offers a clean, convenient, and cloud-based interface to streamline early drug discovery workflows. By seamlessly integrating a range of innovative AI algorithms, covering molecular docking, quantitative structure-activity relationship modeling, molecular generation, ADMET (absorption, distribution, metabolism, excretion and toxicity) prediction, and virtual screening, DrugFlow can offer effective AI solutions for almost all crucial stages in early drug discovery, including hit identification and hit/lead optimization. We hope that the platform can provide sufficiently valuable guidance to aid real-word drug design and discovery. The platform is available at https://drugflow.com.

Conditional Molecular Generation Net Enables Automated Structure Elucidation Based on 13C NMR Spectra and Prior Knowledge.

Structure elucidation of unknown compounds based on nuclear magnetic resonance (NMR) remains a challenging problem in both synthetic organic and natural product chemistry. Library matching has been an efficient method to assist structure elucidation. However, it is limited by the coverage of libraries. In addition, prior knowledge such as molecular fragments is neglected. To solve the problem, we propose a conditional molecular generation net (CMGNet) to allow input of multiple sources of information. CMGNet not only uses 13C NMR spectrum data as input but molecular formulas and fragments of molecules are also employed as input conditions. Our model applies large-scale pretraining for molecular understanding and fine-tuning on two NMR spectral data sets of different granularity levels to accommodate structure elucidation tasks. CMGNet generates structures based on 13C NMR data, molecular formula, and fragment information, with a recovery rate of 94.17% in the top 10 recommendations. In addition, the generative model performed well in the generation of various classes of compounds and in the structural revision task. CMGNet has a deep understanding of molecular connectivities from 13C NMR, molecular formula, and fragments, paving the way for a new paradigm of deep learning-assisted inverse problem-solving.

MhCLC-c1, a Cl channel c homolog from Malus hupehensis, alleviates NaCl-induced cell death by inhibiting intracellular Cl- accumulation.

BACKGROUND: Overaccumulation of chloride (Cl) when plants suffer NaCl causes cell damage and death, and is regulated by Cl- channel protein (CLC). Apple roots are very sensitive to Cl-, but information associated with CLC is limited in apple crop that widely cultivated in the world. RESULTS: We identified 9 CLCs from the apple genome and divided them into two subclasses. Among them, MdCLC-c1 promoter contained the largest number of cis-acting elements associated with NaCl stress, and only the MdCLC-c1, MdCLC-d, and MdCLC-g were predicted that may be Cl- antiporters or channels. Expression analysis of MdCLCs homologs in the roots of Malus hupehensis showed that most of the MhCLCs expression were response to NaCl stress, especially MhCLC-c1 expression was upregulated continuously and rapidly expressed during NaCl treatment. Therefore, we isolated MhCLC-c1 and observed it was a plasma membrane-localized protein. The MhCLC-c1 suppression significantly increased sensitivity, reactive oxygen species content, and cell death of apple calli; while MhCLC-c1 overexpression decreased sensitivity, reactive oxygen species content, and cell death of apple calli and Arabidopsis by inhibiting intracellular Cl- accumulation under NaCl stress. CONCLUSIONS: The study selected and isolated a CLC-c gene MhCLC-c1 from Malus hupehensis based on identification of CLCs gene family in apple, and their homologs MhCLCs expression patterns during NaCl treatments, revealing that MhCLC-c1 alleviates NaCl-induced cell death by inhibiting intracellular Cl- accumulation. Our findings confer the comprehensive and in-depth upstanding of the mechanism that plants resist salt stress, and might also confer genetic improvement of salt tolerance in horticultural crops and the development and utilization of saline-alkali land.

H2S Enhanced the Tolerance of Malus hupehensis to Alkaline Salt Stress through the Expression of Genes Related to Sulfur-Containing Compounds and the Cell Wall in Roots.

Malus is an economically important plant that is widely cultivated worldwide, but it often encounters saline-alkali stress. The composition of saline-alkali land is a variety of salt and alkali mixed with the formation of alkaline salt. Hydrogen sulfide (H2S) has been reported to have positive effects on plant responses to abiotic stresses. Our previous study showed that H2S pretreatment alleviated the damage caused by alkaline salt stress to Malus hupehensis Rehd. var. pingyiensis Jiang (Pingyi Tiancha, PYTC) roots by regulating Na+/K+ homeostasis and oxidative stress. In this study, transcriptome analysis was used to investigate the overall mechanism through which H2S alleviates alkaline salt stress in PYTC roots. Simultaneously, differentially expressed genes (DEGs) were explored. Transcriptional profiling of the Control-H2S, Control-AS, Control-H2S + AS, and AS-H2S + AS comparison groups identified 1618, 18,652, 16,575, and 4314 DEGs, respectively. Further analysis revealed that H2S could alleviate alkaline salt stress by increasing the energy maintenance capacity and cell wall integrity of M. hupehensis roots and by enhancing the capacity for reactive oxygen species (ROS) metabolism because more upregulated genes involved in ROS metabolism and sulfur-containing compounds were identified in M. hupehensis roots after H2S pretreatment. qRT-PCR analysis of H2S-induced and alkaline salt-response genes showed that these genes were consistent with the RNA-seq analysis results, which indicated that H2S alleviation of alkaline salt stress involves the genes of the cell wall and sulfur-containing compounds in PYTC roots.

Cross-Modal Retrieval between 13C NMR Spectra and Structures for Compound Identification Using Deep Contrastive Learning.

Library matching using carbon-13 nuclear magnetic resonance (13C NMR) spectra has been a popular method adopted in compound identification systems. However, the usability of existing approaches has been restricted as enlarging a library containing both a chemical structure and spectrum is a costly and time-consuming process. Therefore, we propose a fundamentally different, novel approach to match 13C NMR spectra directly against a molecular structure library. We develop a cross-modal retrieval between spectrum and structure (CReSS) system using deep contrastive learning, which allows us to search a molecular structure library using the 13C NMR spectrum of a compound. In the test of searching 41,494 13C NMR spectra against a reference structure library containing 10.4 million compounds, CReSS reached a recall@10 accuracy of 91.64% and a processing speed of 0.114 s per query spectrum. When further incorporating a filter with a molecular weight tolerance of 5 Da, CReSS achieved a new remarkable recall@10 of 98.39%. Furthermore, CReSS has potential in detecting scaffolds of novel structures and demonstrates great performance for the task of structural revision. CReSS is built and developed to bridge the gap between 13C NMR spectra and structures and could be generally applicable in compound identification.

Different Crystal Forms of ZnS Nanomaterials for the Adsorption of Elemental Mercury.

ZnS is a promising sorbent in recovering Hg0 from industrial flue gas due to its excellent Hg0 adsorption capacity. However, the internal structure-activity relationship still needs to be further clarified. In this work, ZnS sorbents with different structures were synthesized with the hydrothermal method by tuning the temperature. The samples had significant differences in the crystallinity, morphology, particle size, and sulfur (S) active sites. The results indicated that Hg0 removal performance was determined by the specific surface area and S active sites. ZnS synthesized at low temperatures (80-ZnS and 120-ZnS) had a larger surface area, while the S sites on the high-temperature-synthesized sample (160-ZnS) were more active for Hg0 adsorption. The 160-ZnS sample exhibited a much higher Hg0 adsorption amount per unit surface area. Further characterization revealed that S22- and Sx were the main active sites for Hg0 adsorption. Sx existed in the form of long-chain polysulfur (L-Sx) on 80-ZnS and 120-ZnS, while it exhibited in the form of short-chain polysulfur (S-Sx) on 160-ZnS. L-Sx had negligible adsorption ability, while S-Sx had a high affinity for Hg0. Hg0 can react with S22- and S-Sx, forming α-HgS and ß-HgS, respectively. The new insight in this work can provide theoretical guidance for the design and structure optimization of ZnS, facilitating its practical industrial application.

Microglial Annexin A3 promoted the development of melanoma via activation of hypoxia-inducible factor-1α/vascular endothelial growth factor signaling pathway.

BACKGROUND: Melanoma, a relatively common malignancy, has become one of the tumors with the fastest rising incidence in recent years. The purpose of this study was to investigate the effect of Microglial Annexin A3 (ANXA3) on melanoma. METHODS: Serum samples were obtained from 20 patients with melanoma or 20 healthy controls. Kaplan-Meier survival analysis was performed. Transcriptome were used to analyze the correlation between ANXA3 expression and overall survival in patients with melanoma. Human melanoma cell lines WM-115 cells were transfected with ANXA3, si-ANXA3, ANXA3 + si-hypoxia inducible factor-1α (HIF-1α), si-ANXA3 + HIF-1α, and negative plasmids. Cell proliferation assay, cell invasion assay, and wound healing assay were performed on WM-115 cells. Lactate dehydrogenase (LDH) and caspase-3/9 activities were detected by commercial kits. Western blot and RT-PCR were used to detect the protein and mRNA expression of relation factors. RESULTS: ANXA3 expression was up-regulated in patients with melanoma in comparison with healthy controls. Over-expression of ANXA3 promoted cell growth and migration, and reduced cytotoxicity of WM-115 cells. Overall survival (OS) and disease-free survival (DFS) of patients with high ANXA3 expression were both lower than those of patients with low ANXA3 expression. Down-regulation of ANXA3 reduced cell growth and migration, and promoted cytotoxicity of WM-115 cells. ANXA3 induced vascular endothelial growth factor (VEGF) signaling pathway by activation of HIF-1α. CONCLUSION: In conclusion, our results indicated that ANXA3 promoted cell growth and migration of melanoma via activation of HIF-1α/VEGF signaling pathway.

MhMAPK4 from Malus hupehensis Rehd. decreases cell death in tobacco roots by controlling Cd2+ uptake.

Cadmium (Cd) induces cell death in plant roots. Mitogen-activated protein kinase (MAPK) plays a role in the regulation of cell death induced by Cd in plant roots. In this study, MhMAPK4 was isolated from the roots of Malus hupehensis. Subcellular localization showed that the MhMAPK4 protein was located in the cell membrane and cytoplasm and is a transmembrane protein that is characterized by hydrophily. The expression of MhMAPK4 in the roots of M. hupehensis was up-regulated by Cd sulfate and Cd chloride. Phenotypic comparison under Cd stress showed that the growth of wild-type (WT) tobacco was lower than the transgenic lines overexpressing MhMAPK4. The fresh weight and the root length of WT also was lower than that of the transgenic tobacco. The net Cd2+ influx in the tobacco roots was decreased by the overexpression of MhMAPK4, as was root Cd accumulation. The recovery time of the Cd2+ influx to stable state in the transgenic tobacco was also shorter than the WT. The expression of iron-regulated transporter 1 (NtIRT1) and natural resistance associated macrophage protein 5 (NtNRAMP5) was relatively low in the transgenic lines under Cd stress. Cell death and apoptosis in the tobacco roots was reduced following the overexpression of MhMAPK4. The activity of vacuolar processing enzyme (VPE) and the transcript level of VPE in the transgenic tobacco was lower than that of WT under Cd stress. In addition, the electrolyte leakage and malondialdehyde and hydrogen peroxide contents in the transgenic tobacco were lower than those of WT, whereas the antioxidant enzyme activity and expression were higher. These results suggest that MhMAPK4 regulates Cd accumulation by mediating Cd2+ uptake by the roots, and controls Cd-caused cell death by adjusting VPE activity.

Triglyceride-mediated influence of serum angiopoietin-like protein 8 on subclinical atherosclerosis in type 2 diabetic patients: results from the GDMD study in China.

BACKGROUND: Hypertriglyceridemia, insulin resistance and hyperglycemia are risk factors for atherosclerosis in type 2 diabetes. Angiopoietin-like protein 8 (ANGPTL8) is a newly identified liver-derived hormone related to these risk factors. Hence, we aimed to explore the correlations between serum levels of ANGPTL8 and subclinical atherosclerosis in type 2 diabetes. METHODS: We measured serum ANGPTL8, blood lipids, blood glucose, common carotid artery Intima-Media Thickness (c-IMT) and calculated homeostasis model assessment of insulin resistance in (1) control subjects (n = 100), (2) type 2 diabetic patients without subclinical atherosclerosis (n = 100), and (3) type 2 diabetic patients with subclinical atherosclerosis (n = 100). RESULTS: Serum levels of ANGPTL8 and triglyceride (TG) were significantly increased in type 2 diabetic patients with subclinical atherosclerosis as compared with type 2 diabetic patients without subclinical atherosclerosis and control subjects (P < 0.001). ANGPTL8 was positively associated with age, TG, diabetes duration, and c-IMT in type 2 diabetes. Logistic regression analysis revealed that ANGPTL8 had higher odds of having subclinical atherosclerosis [odds ratio (OR) 2.90, 95% confidence interval (CI) 1.48-5.70, P = 0.002] in type 2 diabetes. Mediation analysis indicated that TG acted as a partial mediator in the relationship between ANGPTL8 and c-IMT. CONCLUSIONS: TG partially mediates the positive relationship between ANGPTL8 and c-IMT. Our data provide the first evidence for a strong link between ANGPTL8 and subclinical atherosclerosis, suggesting ANGPTL8 to be a new biomarker for subclinical atherosclerosis in type 2 diabetes.

Hypermethylation of ATP-binding cassette B1 (ABCB1) multidrug resistance 1 (MDR1) is associated with cisplatin resistance in the A549 lung adenocarcinoma cell line.

Development of multiple drug resistance has been attributed to the overexpression of the ATP-binding cassette B1 (ABCB1) gene. In this study, the major purpose was to assess the expression and methylation levels of ABCB1 in human lung adenocarcinoma and to reveal the relationship between these processes and acquisition of cisplatin (DDP) resistance in the human cancer cell line A549. Methylation and expression levels of the ABCB1 gene ABCB1 in clinical human lung tissue were assessed using bisulphite sequencing, reverse transcription real-time PCR (RT2 -PCR) and Western blot methods. Cell viability, DDP resistance and apoptosis of A549 cells were evaluated using the Cell Counting Kit-8 and fluorescence-activated cell sorter analysis. Our results showed that the onset of resistance to the cisplatin analogue, DDP, was associated with hypermethylation of the ABCB1 gene. Expression of the ABCB1 gene was enhanced at both mRNA and protein levels. Treatment with 5-Aza-C contributed to the hypomethylation of the ABCB1 gene and decreased ABCB1 protein expression in A549 cells. In conclusion, this in vitro and human tissue study of lung adenocarcinoma cells demonstrated that hypermethylation of the ABCB1 gene correlated with increased gene expression and was associated with the acquisition of resistance to the cisplatin analogue, DDP in human lung adenocarcinoma cells. Taken together, our study highlighted the connection between increased ABCB1 methylation level and upregulated expression of the gene in lung cancer. Moreover, the abnormally high expression of ABCB1 in A549 cells contributed to the development of the DDP resistance.

Impact of CAG repeat length in the androgen receptor gene on male infertility - a meta-analysis.

CAG repeats are polymorphic nucleotide repeats present in the androgen receptor gene. Many studies have estimated the association between CAG repeat length and male infertility, but the conclusions are controversial. Previous meta-analyses have come to different conclusions; however, new studies have been published. An updated meta-analysis was conducted. PubMed, CBM, CNKI and Web of Science databases were systematically searched for studies published from 1 January 2000 to 1 October 2015. Case-control studies on the association between CAG repeat length and male infertility using appropriate methodology were included. Forty studies were selected, including 3858 cases and 3161 controls. Results showed statistically significantly longer CAG repeat length among cases compared with controls (SMD = 0.14; 95% CI, 0.02-0.26). Shorter repeat length was associated with a lower risk of male infertility compared with a longer repeat length in the overall analysis (OR = 0.79, 95% CI: 0.66-0.95). Moreover, CAG repeat length was associated with male infertility in Caucasian populations, but not Asian or Egyptian populations. Subgroup analysis revealed no significant difference in German populations, but CAG repeat length was associated with male infertility in China and the USA. There were no significant differences between cases and controls in azoospermia and severe oligozoospermia.

Methylation of RASSF1A gene promoter and the correlation with DNMT1 expression that may contribute to esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma is one of the most common malignancies in the world. Studies have confirmed that there are many genes abnormally hypermethylated in esophageal squamous cell carcinoma. The objective is to detect methylation of the RASSF1A gene promoter and the expression of the DNA methyltransferase 1 (DNMT1) protein in esophageal cancer tissue and discuss their relationship with esophageal squamous cell carcinoma. METHODS: The CpG island methylation status of RASSF1A genes were analyzed in 100 cases of tumor specimens as well as their adjacent tissues which was used for methylation-specific polymerase chain reaction (MSP). The expression of DNMT1 protein was determined by immunohistochemistry. Difference between measurement data and categorical data was compared through analysis of t test and chi-square test. All the statistics were taken with a bilateral test. The difference was statistically significant (P < 0.05). RESULTS: The promoter methylation of the RASSF1A gene promoter has been detected in 45 out of 100 (45%) esophageal squamous carcinoma cases, while methylation of RASSF1A gene has been detected in 2 out of 100 adjacent normal tissues (2%). The RASSF1A gene promoter was highly methylated in cancer tissues, and there were significant differences between normal esophagus tissues and esophageal squamous carcinoma (P < 0.05). The expression of DNMT1 protein has been detected in 61 out of 100 (61%) esophageal squamous carcinoma cases, including 41 cases in the above 45 methylated samples of RASSF1A gene promoter, and none in adjacent tissues. DNMT1 proteins are highly expressed in cancer tissues, and there were significant differences (P < 0.05). In positive cases for methylation of RASSF1A, the DNMT1 protein had been detected in 41 out of 45 (91%), while in non-methylated cancer cases, 20 out of 55(36.3%), and the difference is significant (P < 0.05). CONCLUSIONS: Esophageal squamous carcinoma tumorigenesis may be related with hypermethylation of DNMT1 and RASSF1A promoter CpG island due to their high expression and also their hypermethylation.

Effects of robot-assisted upper limb training combined with intermittent theta burst stimulation (iTBS) on cortical activation in stroke patients: A functional near-infrared spectroscopy study.

BACKGROUND: The therapeutic effect and mechanism of robot-assisted upper limb training (RT) combined with intermittent theta burst stimulation (iTBS) for stroke patients are unclear. OBJECTIVE: The purpose of this study was to evaluate changes in brain activation after combination therapy and RT alone using functional near-infrared spectroscopy (fNIRS). METHODS: Patients were randomly assigned to two groups (iTBS + RT Group, n = 18, and RT Group, n = 18). Training was conducted five times a week for four weeks. fNIRS was used to measure changes in oxyhemoglobin in both the primary motor cortex (M1) and pre-motor and supplementary motor area (pSMA) during affected limb movement. Fugl-Meyer Assessment-Upper Extremity (FMA-UE) was employed for evaluating the function of upper limbs. RESULTS: Thirty-two patients with subacute stroke completed the study. The cortex of both hemispheres was extensively activated prior to treatment in the RT group. After training, overactivation decreased. The brain activation of the combined treatment group transferred to the affected side after the treatment. There was a notable enhancement in the FMA-UE scores for both groups, with the combined group's progress significantly surpassing that of the RT group. CONCLUSION: RT combined with iTBS can improve the motor function of stroke patients and promote the balance between cerebral hemispheres.

CarsiDock: a deep learning paradigm for accurate protein-ligand docking and screening based on large-scale pre-training.

The expertise accumulated in deep neural network-based structure prediction has been widely transferred to the field of protein-ligand binding pose prediction, thus leading to the emergence of a variety of deep learning-guided docking models for predicting protein-ligand binding poses without relying on heavy sampling. However, their prediction accuracy and applicability are still far from satisfactory, partially due to the lack of protein-ligand binding complex data. To this end, we create a large-scale complex dataset containing ∼9 M protein-ligand docking complexes for pre-training, and propose CarsiDock, the first deep learning-guided docking approach that leverages pre-training of millions of predicted protein-ligand complexes. CarsiDock contains two main stages, i.e., a deep learning model for the prediction of protein-ligand atomic distance matrices, and a translation, rotation and torsion-guided geometry optimization procedure to reconstruct the matrices into a credible binding pose. The pre-training and multiple innovative architectural designs facilitate the dramatically improved docking accuracy of our approach over the baselines in terms of multiple docking scenarios, thereby contributing to its outstanding early recognition performance in several retrospective virtual screening campaigns. Further explorations demonstrate that CarsiDock can not only guarantee the topological reliability of the binding poses but also successfully reproduce the crucial interactions in crystalized structures, highlighting its superior applicability.

Surgical treatment of an endobronchial lipoma obstructing the right upper bronchus: Imaging features with pathological correlation.

Endobronchial lipomas are rare benign unusual tumors of the respiratory tract. We describe a 65-year-old Chinese man with a history of cough due to an endobronchial tumor. The endobronchial biopsy was not excisional and was unable to evaluate the whole tumor. Then the mass was successfully resected via a right lateral thoracotomy. The histopathological diagnosis confirmed a benign lipoma arising from the membranous trachea. His CT features and fiberoptic bronchoscopic findings are shown along with the pathological results. In describing the management of this case, we stress that the clinical treatment of such tumors should be individualized according to the characteristics of each patient and mass.

Multi-walled carbon nanotubes promote the accumulation, distribution, and assimilation of 15N-KNO3 in Malus hupehensis by entering the roots.

Introduction: Multi-walled nanotubes (MWCNTs) consist of multiple rolled layers of graphene. Nitrogen plays an important role in apple growth. The effect of MWCNTs on nitrogen utilization in apple needs to be further investigated. Methods: In this study, the woody plant Malus hupehensis seedlings were used as plant materials, the distribution of MWCNTs in the roots was observed, and the effects of MWCNTs on the accumulation, distribution, and assimilation of nitrate by the seedlings were explored. Results: The results showed that MWCNTs could penetrate the roots of Malus hupehensis seedlings, and the 50, 100, and 200 µg·mL-1 MWCNTs significantly promoted the root growth of seedlings, increased root number, root activity, fresh weight, and nitrate content of seedlings, and also increased nitrate reductase activity, free amino acid, and soluble protein content of roots and leaves. 15N tracer experiments indicated that MWCNTs decreased the distribution ratio of 15N-KNO3 in Malus hupehensis roots but increased its distribution ratio in stems and leaves. MWCNTs improved the utilization ratio of 15N-KNO3 in Malus hupehensis seedlings, with the values being increased by 16.19%, 53.04%, and 86.44% following the 50, 100, and 200 µg·mL-1 MWCNTs, respectively. The RT-qPCR analysis showed that MWCNTs significantly affected the expression of genes (MhNRTs) related to nitrate uptake and transport in roots and leaves, and MhNRT1.4, MhNRT1.7, MhNRT1.8, MhNRT2.1, MhNRT2.5, and MhNRT2.7 were notably up-regulated in response to 200 µg·mL-1 MWCNTs. Raman analysis and transmission electron microscopy images indicated that MWCNTs could enter the root tissue of Malus hupehensis and were distributed between the cell wall and cytoplasmic membrane. Pearson correlation analysis showed that root tip number, root fractal dimension, and root activity were the main factors affecting root uptake and assimilation of nitrate. Conclusions: These findings suggest that MWCNTs promoted root growth by entering the root, stimulated the expression of MhNRTs, and increased NR activity, thereby enhancing the uptake, distribution, and assimilation of nitrate by root, and ultimately improved the utilization of 15N-KNO3 by Malus hupehensis seedlings.

Emission reduction of PCDD/Fs by flue gas recirculation and activated carbon in the iron ore sintering.

One of the main sources of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in the environment is the sintering of iron ore. Both flue gas recirculation (FGR) and activated carbon (AC), which have the impact of decreasing both PCDD/Fs and conventional pollutants (NOx, SO2, etc.), are significant technologies for the abatement of PCDD/Fs from the sintering exhaust gas. This work involved the first measurement of PCDD/Fs emissions during FGR and a thorough analysis of the impact of PCDD/Fs reduction following the coupling of FGR and AC technologies. According to the measured data, the ratio of PCDFs to PCDDs in the sintered flue gas was 6.8, indicating that during the sintering process, the PCDD/Fs were primarily produced by de novo synthesis. Further investigation revealed that FGR initially removed 60.7% of PCDD/Fs by returning it to the high temperature bed, and AC further removed 95.2% of the remaining PCDD/Fs through physical adsorption. While AC is better at removing PCDFs and can efficiently remove tetra-to octa-chlorinated homologs, FGR is more effective at removing PCDDs and has higher removal efficiency for hexa-to octa-chlorinated PCDD/Fs. Together, they complement each other with a removal rate of 98.1%. The study's findings are instructional for the process design of combining FGR and AC technologies to reduce PCDD/Fs in the sintered flue gas.

Wood biochar in soil enhances the promotion of KNO3 on sulfur accumulation in apple trees by regulating root sulfate assimilation.

To determine how potassium nitrate (KNO3) effect apple roots and sulfate assimilation in the presence of wood biochar in soil, KNO3 was applied to the root-zone soil without or with 150-day naturally aged wood biochar (1% w/w) in soil. Soil properties, root architecture, root activity, the accumulation and distribution of sulfur (S), enzyme activity, and gene expression related to sulfate uptake and assimilation in apple trees were analyzed. Results showed that KNO3 and wood biochar application exhibited synergistic effects on improving S accumulation and root growth. Meanwhile, KNO3 application increased the activities of ATPS, APR, SAT, OASTL and upregulated the expression of ATPS, APR, Sultr3;1, Sultr2;1, Sultr3;4, and Sultr3;5 in both roots and leaves, and the positive effects of KNO3 addition on both genes and enzyme activity were enhanced by wood biochar. Wood biochar amendment alone promoted the activities of enzymes described above, upregulated the expression of ATPS, APR, Sultr3;1, Sultr2;1, Sultr3;4, and Sultr4;2 in leaves, and enhanced S distribution in roots. KNO3 addition alone decreased S distribution in roots and increased that in stems. In the presence of wood biochar in soil, KNO3 application decreased S distribution in roots but increased that in both stems and leaves. These results indicated that the wood biochar in soil enhances the effect of KNO3 on S accumulation by promoting root growth and sulfate assimilation in apple trees.

SDEGen: learning to evolve molecular conformations from thermodynamic noise for conformation generation.

Generation of representative conformations for small molecules is a fundamental task in cheminformatics and computer-aided drug discovery, but capturing the complex distribution of conformations that contains multiple low energy minima is still a great challenge. Deep generative modeling, aiming to learn complex data distributions, is a promising approach to tackle the conformation generation problem. Here, inspired by stochastic dynamics and recent advances in generative modeling, we developed SDEGen, a novel conformation generation model based on stochastic differential equations. Compared with existing conformation generation methods, it enjoys the following advantages: (1) high model capacity to capture multimodal conformation distribution, thereby searching for multiple low-energy conformations of a molecule quickly, (2) higher conformation generation efficiency, almost ten times faster than the state-of-the-art score-based model, ConfGF, and (3) a clear physical interpretation to learn how a molecule evolves in a stochastic dynamics system starting from noise and eventually relaxing to the conformation that falls in low energy minima. Extensive experiments demonstrate that SDEGen has surpassed existing methods in different tasks for conformation generation, interatomic distance distribution prediction, and thermodynamic property estimation, showing great potential for real-world applications.