Serum metabolites and hypercholesterolemia: insights from a two-sample Mendelian randomization study.

Background: Hypercholesterolemia, a critical contributor to cardiovascular disease, is not fully understood in terms of its relationship with serum metabolites and their role in disease pathogenesis. Methods: This study leveraged GWAS data to explore the relationship between serum metabolites and hypercholesterolemia, pinpointing significant metabolites via Mendelian Randomization (MR) and KEGG pathway enrichment analysis. Data on metabolites were sourced from a European population, with analysis focusing on individuals diagnosed with hypercholesterolemia. Results: Out of 486 metabolites analyzed, ten showed significant associations with hypercholesterolemia, categorized into those enhancing risk and those with protective effects. Specifically, 2-methoxyacetaminophen sulfate and 1-oleoylglycerol (1-monoolein) were identified as risk-enhancing, with odds ratios (OR) of 1.545 (95% CI: 1.230-1.939; P_FDR = 3E-04) and 1.462 (95% CI: 1.036-2.063; P_FDR = 0.037), respectively. On the protective side, 3-(cystein-S-yl)acetaminophen, hydroquinone sulfate, and 2-hydroxyacetaminophen sulfate demonstrated ORs of 0.793 (95% CI: 0.735-0.856; P_FDR = 6.18E-09), 0.641 (95% CI: 0.423-0.971; P_FDR = 0.042), and 0.607 (95% CI: 0.541-0.681; P_FDR = 5.39E-17), respectively. In addition, KEGG pathway enrichment analysis further revealed eight critical pathways, comprising "biosynthesis of valine, leucine, and isoleucine", "phenylalanine metabolism", and "pyruvate metabolism", emphasizing their significant role in the pathogenesis of hypercholesterolemia. Conclusion: This study underscores the potential causal links between particular serum metabolites and hypercholesterolemia, offering innovative viewpoints on the metabolic basis of the disease. The identified metabolites and pathways offer promising targets for therapeutic intervention and warrant further investigation.

DNA Hyper-methylation Associated With Schizophrenia May Lead to Increased Levels of Autoantibodies.

Background and Hypothesis: Environmental stressors may influence immune surveillance in B lymphocytes and stimulate autoimmune responses via epigenetic DNA methylation modifications in schizophrenia (SCZ). Study Design: A total of 2722, Chinese Han origin subjects were recruited in this study (2005-2011), which included a discovery follow-up cohort with 40 remitters of SCZ (RSCZ), 40 nonremitters of SCZ (NRSCZ), and 40 controls (CTL), and a replication follow-up cohort (64 RSCZ, 16 NRSCZ, and 84 CTL), as well as a case-control validation cohort (1230 SCZ and 1208 CTL). Genomic DNA methylation, target gene mRNA transcripts, and plasma autoantibody levels were measured across cohorts. Study Results: We found extensive differences in global DNA methylation profiles between RSCZ and NRSCZ groups, wherein differential methylation sites (DMS) were enriched with immune cell maturation and activation in the RSCZ group. Out of 2722 participants, the foremost DMS cg14341177 was hyper-methylated in the SCZ group and it inhibited the alternative splicing of its target gene BICD2 and may have increased its autoantigen exposure, leading to an increase in plasma anti-BICD2 IgG antibody levels. The levels of cg14341177 methylation and anti-BICD2 IgG decreased significantly in RSCZ endpoint samples but not in NRSCZ endpoint samples. There are strong positive correlations between cg14341177 methylation, anti-BICD2 IgG, and positive and negative syndrome scale (PANSS) scores in the RSCZ groups, but not in the NRSCZ groups. Conclusions: These data suggest that abnormal DNA methylation could affect autoreactive responses in SCZ, and that cg14341177 methylation and anti-BICD2 IgG levels may potentially serve as useful biomarkers.

A joint learning framework for multisite CBCT-to-CT translation using a hybrid CNN-transformer synthesizer and a registration network.

Background: Cone-beam computed tomography (CBCT) is a convenient method for adaptive radiation therapy (ART), but its application is often hindered by its image quality. We aim to develop a unified deep learning model that can consistently enhance the quality of CBCT images across various anatomical sites by generating synthetic CT (sCT) images. Methods: A dataset of paired CBCT and planning CT images from 135 cancer patients, including head and neck, chest and abdominal tumors, was collected. This dataset, with its rich anatomical diversity and scanning parameters, was carefully selected to ensure comprehensive model training. Due to the imperfect registration, the inherent challenge of local structural misalignment of paired dataset may lead to suboptimal model performance. To address this limitation, we propose SynREG, a supervised learning framework. SynREG integrates a hybrid CNN-transformer architecture designed for generating high-fidelity sCT images and a registration network designed to correct local structural misalignment dynamically during training. An independent test set of 23 additional patients was used to evaluate the image quality, and the results were compared with those of several benchmark models (pix2pix, cycleGAN and SwinIR). Furthermore, the performance of an autosegmentation application was also assessed. Results: The proposed model disentangled sCT generation from anatomical correction, leading to a more rational optimization process. As a result, the model effectively suppressed noise and artifacts in multisite applications, significantly enhancing CBCT image quality. Specifically, the mean absolute error (MAE) of SynREG was reduced to 16.81 ± 8.42 HU, whereas the structural similarity index (SSIM) increased to 94.34 ± 2.85%, representing improvements over the raw CBCT data, which had the MAE of 26.74 ± 10.11 HU and the SSIM of 89.73 ± 3.46%. The enhanced image quality was particularly beneficial for organs with low contrast resolution, significantly increasing the accuracy of automatic segmentation in these regions. Notably, for the brainstem, the mean Dice similarity coefficient (DSC) increased from 0.61 to 0.89, and the MDA decreased from 3.72 mm to 0.98 mm, indicating a substantial improvement in segmentation accuracy and precision. Conclusions: SynREG can effectively alleviate the differences in residual anatomy between paired datasets and enhance the quality of CBCT images.

Assessing the interactive effects of microplastics and acid rain on cadmium toxicity in rice seedlings: Insights from physiological and transcriptomic analyses.

In heavy metal-contaminated areas, the simultaneous occurrence of increasing microplastic pollution and persistent acid rain poses a serious threat to food security. However, the mechanisms of combined exposure to microplastics (MP) and acid rain (AR) on the toxicity of cadmium (Cd) in rice seedlings remain unclear. Our study investigated the combined effects of exposure to polyvinyl chloride microplastics and AR (pH 4.0) on the toxicity of Cd (0.3, 3, and 10 mg/L) in rice seedlings. The results showed that at low Cd concentrations, the combined exposure had no significant effect, but at high Cd concentrations, it alleviated the effects of Cd stress. The combined application of MP and AR alleviated the inhibitory effects of Cd on seedling growth and chlorophyll content. Under high Cd concentration (10 mg/L), the simultaneous addition of MP and AR significantly reduced the production of reactive oxygen species (ROS), the content of malondialdehyde (MDA), and the activity of the superoxide dismutase (SOD) enzyme. Compared to AR or MP alone, the combination of MP and AR reduced root cell damage and Cd accumulation in rice seedlings. Transcriptomic analysis confirmed that under high Cd concentrations, the combination of MP and AR altered the expression levels of genes related to Cd transport, uptake, MAPK kinase, GSTs, MTs, and transcription factors, producing a synergistic effect on oxidative stress and glutathione metabolism. These results indicate that coexposure to MP and AR affects the toxicity of Cd in rice seedlings and alleviates Cd toxicity under high Cd concentrations to some extent. These findings provide a theoretical basis for evaluating the toxicological effects of microplastic and acid rain pollution on crop growth in areas contaminated with heavy metals, and are important for safe agricultural production and ecological security.

Revealing and reconstructing the 3D Li-ion transportation network for superionic poly(ethylene) oxide conductor.

Understanding the Li-ions conduction network and transport dynamics in polymer electrolyte is crucial for developing reliable all-solid-state batteries. In this work, advanced nano- X-ray computed tomography combined with Raman spectroscopy and solid state nuclear magnetic resonance are used to multi-scale qualitatively and quantitatively reveal ion conduction network of poly(ethylene) oxide (PEO)-based electrolyte (from atomic, nano to macroscopic level). With the clear mapping of the microstructural heterogeneities of the polymer segments, aluminium-oxo molecular clusters (AlOC) are used to reconstruct a high-efficient conducting network with high available Li-ions (76.7%) and continuous amorphous domains via the strong supramolecular interactions. Such superionic PEO conductor (PEO-LiTFSI-AlOC) exhibites a molten-like Li-ion conduction behaviour among the whole temperature range and delivers an ionic conductivity of 1.87 × 10-4 S cm-1 at 35 °Ï¹. This further endows Li electrochemical plating/stripping stability under 50 µA cm-2 and 50 µAh cm-2 over 2000 h. The as-built Li|PEO-LiTFSI-AlOC|LiFePO4 full batteries show a high rate performance and a capacity retention more than 90% over 200 cycling at 250 µA cm-2, even enabling a high-loading LiFePO4 cathode of 16.8 mg cm-2 with a specific capacity of 150 mAh g-1 at 50 °Ï¹.

High temporal resolution prediction of mortality risk for single AML patient via deep learning.

Acute myeloid leukemia (AML) is highly heterogeneous, necessitating personalized prognosis prediction and treatment strategies. Many of the current patient classifications are based on molecular features. Here, we classified the primary AML patients by predicted death risk curves and investigated the survival-directly-related molecular features. We developed a deep learning model to predict 5-year continuous-time survival probabilities for each patient and converted them to death risk curves. This method captured disease progression dynamics with high temporal resolution and identified seven patient groups with distinct risk peak timing. Based on clusters of death risk curves, we identified two robust AML prognostic biomarkers and discovered a subgroup within the European LeukemiaNet (ELN) 2017 Favorable category with an extremely poor prognosis. Additionally, we developed a web tool, De novo AML Prognostic Prediction (DAPP), for individualized prognosis prediction and expression perturbation simulation. This study utilized deep learning-based continuous-time risk modeling coupled with clustering-predicted risk distributions, facilitating dissecting time-specific molecular features of disease progression.

Salix matsudana fatty acid desaturases: Identification, classification, evolution, and expression profiles for development and stress tolerances.

Fatty acid desaturases (FADs) are enzymes that transform carbon­carbon single bonds into carbon­carbon double bonds within acyl chains, resulting in the production of unsaturated FAs (UFAs). They are crucial for plant growth, development, and adaptation to environmental stress. In our research, we identified 40 FAD candidates in the Salix matsudana genome, grouping them into seven categories. Exon-intron structures and conserved motifs of SmFADs within the same group showed significant conservation. Cis-Element analysis revealed SmFADs are responsive to hormones and stress. Additionally, GO and KEGG analyses linked SmFADs closely with lipid biosynthesis and UFA biosynthesis, which were crucial for the plant's response to environmental stress. Notably, the SmFAB2.4, SmADS1, SmFAD7.5, and SmFAD8.2 were predicted to participate in submergence tolerance, whereas SmFAD8.1 and SmFAD7.1 played an essential role in salt stress response. The diverse expression profiles of SmFADs across willow varieties, in various tissues, and throughout the willow bud development stages revealed a spectrum of functional diversity for these genes. Moreover, specific SmFADs might play a crucial role in callus development and the response to culturing conditions in various willow cultivars. This research underscored the importance of SmFAD profiles and functions and identified potential genes for enhancing forest resilience.

The Research Effects of Variable Temperature and Early Strength Agent on the Mechanical Properties of Cement-Stabilized Macadam.

In cold regions with high daily temperature gradients (>20 °C), the durability of cement-stabilized macadam (CSM) base materials is poor and prone to cracking. To effectively reduce the cracking of semi-rigid base layers in cold regions with high daily temperature gradients and extend fatigue life, this study focused on cracking and fatigue characteristics of CSM with a 10% commercial early strength agent (ESA) added by the external mixing method under different curing conditions. The ESA was manufactured by Jiangsu Subote New Materials Co., Ltd. (Nanjing, China). The curing conditions were divided into variable temperature (0-20 °C) and standard temperature (20 °C). CSM curing was carried out through a programmable curing box. The research results indicated that the variable temperature curing conditions reduced the strength and fatigue resistance of CSM and accelerated the modulus attenuation rate of CSM. At the same time, the drying shrinkage of CSM was greater. The temperature shrinkage coefficient and strain of CSM under variable temperature conditions were smaller than those under standard temperature conditions. The effect of variable temperature conditions on the cracking and durability of CSM could not be ignored in cold regions. Compared to standard temperature curing conditions, the indirect tensile strength of CSM reduced by 31.04% under variable temperature conditions, the coefficient of variation increased by 2.97 times, and the discrete type significantly increased. Compared with CSM without ESA, the dry and temperature shrinkage strains of CSM with 10% ESA were reduced by 24.65% and 26.10%, respectively. At a stress level of 0.6, compared to standard temperature curing conditions, the fatigue life of CSM decreased by 97.19% under variable temperature conditions. Under variable temperature conditions, the fatigue life of CSM with 10% ESA increased by 196 times compared to 0% ESA. Adding ESA enhanced the anti-shrinkage cracking, strength, and durability of CSM under variable temperatures. ESA incorporation effectively compensated for the weakened characteristics of CSM under variable temperature conditions. The study proposed a practical approach for boosting the durability of CSM in cold environments.

Efficacy and safety of telitacicept in patients with lupus nephritis.

Although telitacicept is a promising drug for treating systemic lupus erythematosus, there are limited studies on its efficacy and safety in patients with lupus nephritis in China. This lack of research data restricts its potential for broader application and acceptance on a global scale. The present study aimed to determine the efficacy and safety of telitacicept in patients with lupus nephritis (LN) in China. Using a self-controlled before-after comparison method, patients with LN were recruited at Lishui Central Hospital between February 2022 and April 2023, who received telitacicept weekly as part of the standard treatment. Data on the systemic lupus erythematosus disease activity index 2000 (SLEDAI-2K), glucocorticoid dosing and the quantity of immunosuppressive medicines prescribed was collected. Additionally, serum complements, erythrocyte sedimentation rate (ESR), urinary protein levels, immunoglobulin concentrations, serum creatinine levels, plasma albumin concentrations, platelet counts and renal function parameters were documented throughout the study. A total of 13 patients were enrolled in the trial, comprising 11 women and two men. Following 12-48 weeks of treatment with telitacicept (80 or 160 mg per week), 84.6% (n=11) of all patients experienced symptom relief and their SLEDAI-2K score was reduced by more than four points. By the observation endpoint, the median glucocorticoid dosage of the 13 patients was decreased from 15 to 2.5 mg/d, and six patients discontinued their glucocorticoids. Furthermore, 46.1% of patients (n=6) reduced their dose and number of immunosuppressive medicines, while 15.4% (n=2) stopped their immunosuppressive medicines. Minimal changes were observed in serum creatinine, platelet count, C3 levels and C4 levels among patients. Immunoglobulin levels (IgG, IgA and IgM) remained stable or showed an upward trend. Plasma albumin levels remained within the normal range in three patients and increased in ten patients. It increased to the normal range in three of these ten patients. At the endpoint, ESR levels decreased in all patients. Additionally, three patients displayed varying degrees of renal function improvement, and their estimated glomerular filtration rate (ml/min/l.73 m2) increased from 127.8 to 134.2, 95.1 to 123.1 and 61.5 to 67.3, respectively. Urinary protein levels decreased in all patients. It decreased >0.5 g/l in seven patients and reached the normal levels in three patients. The adverse events of telitacicept were manageable. Among the patients infected with COVID-19, three patients had fever, 10 patients remained asymptomatic and none of them exhibited severe respiratory syndromes. In this study, telitacicept effectively stabilized LN activity and alleviated the clinical symptoms of most patients. Furthermore, it reduced the dose of glucocorticoid and immunosuppressive medicines. Therefore, telitacicept may be a promising treatment option for individuals with lupus nephritis.

The efficacy of levonorgestrelintrauterine system, drospirenone & ethinylestradiol tablets (II) and dydrogesterone in preventing the recurrence of endometrial polyps.

OBJECTIVE: To analyze the efficacy of levonorgestrelintrauterine system, Drospirenone & ethinylestradiol tablets (II), and dydrogesterone in preventing the recurrence of endometrial polyps after hysteroscopic endometrial polypectomy. METHODS: One hundred seventy patients who underwent hysteroscopic endometrial polypectomy in the Gynecology Department of Tianmen First People's Hospital in Hubei Province from January 2022 to June 2023 were randomly divided into the levonorgestrelintrauterine system group, Drospirenone & ethinylestradiol tablets (II) group, dydrogesterone group, and a control group. The recurrence rates, endometrial thickness, and menstrual volume changes at 6 and 12 months post-operation were compared among these four groups. RESULTS: The recurrence rates in the levonorgestrelintrauterine system group, Drospirenone & ethinylestradiol tablets (II) group, and dydrogesterone group were lower than the control group, with statistical significance (P < 0.01), with the levonorgestrelintrauterine system group having the lowest recurrence rate. The endometrial thickness at 6 and 12 months post-operation in the levonorgestrelintrauterine system group, Drospirenone & ethinylestradiol tablets (II) group, and dydrogesterone group was thinner than that of the control group and thinner than pre-operation, with statistical significance (P < 0.01). The menstrual volume at 3 months post-operation in the levonorgestrelintrauterine system group, Drospirenone & ethinylestradiol tablets (II) group, and dydrogesterone group was significantly less than the control group, and less than the pre-operation volume. CONCLUSION: Dydrogesterone, drospirenone & ethinylestradiol tablets (II), and levonorgestrelintrauterine system all play a role in preventing the recurrence of endometrial polyps, but levonorgestrelintrauterine system is significantly better than dydrogesterone and Drospirenone & ethinylestradiol tablets (II) in terms of postoperative recurrence rate, endometrial thickness, menstrual changes, and compliance, and is worth promoting in clinical application.

Designed Synthesis of an Aluminum Molecular Ring Based Rotaxane and Polyrotaxane.

Mechanically interlocked molecules, such as rotaxanes, have drawn significant attention within supramolecular chemistry. Although a variety of macrocycles have been thoroughly explored in rotaxane synthesis, metal-organic macrocycles remain relatively under-investigated. Aluminum molecular rings, with their inner cavities and numerous binding sites, present a promising option for constructing rotaxanes. Here, we introduce an innovative "ring-donor···axle-acceptor" motif utilizing Al8 molecular rings, enabling the stepwise assembly of molecules, complexes, and polymers through tailored coordination chemistry. This novel approach can not only be applied to macrocycle-based systems like catenanes but also enhance specific functionalities progressively.

Physical Adversarial Attack Meets Computer Vision: A Decade Survey.

Despite the impressive achievements of Deep Neural Networks (DNNs) in computer vision, their vulnerability to adversarial attacks remains a critical concern. Extensive research has demonstrated that incorporating sophisticated perturbations into input images can lead to a catastrophic degradation in DNNs' performance. This perplexing phenomenon not only exists in the digital space but also in the physical world. Consequently, it becomes imperative to evaluate the security of DNNs-based systems to ensure their safe deployment in real-world scenarios, particularly in security-sensitive applications. To facilitate a profound understanding of this topic, this paper presents a comprehensive overview of physical adversarial attacks. Firstly, we distill four general steps for launching physical adversarial attacks. Building upon this foundation, we uncover the pervasive role of artifacts carrying adversarial perturbations in the physical world. These artifacts influence each step. To denote them, we introduce a new term: adversarial medium. Then, we take the first step to systematically evaluate the performance of physical adversarial attacks, taking the adversarial medium as a first attempt. Our proposed evaluation metric, hiPAA, comprises six perspectives: Effectiveness, Stealthiness, Robustness, Practicability, Aesthetics, and Economics. We also provide comparative results across task categories, together with insightful observations and suggestions for future research directions.

A phosphatase-like nanomaterial promotes autophagy and reprograms macrophages for cancer immunotherapy.

Macrophages are plastic and play a key role in the maintenance of tissue homeostasis. In cancer progression, macrophages also take part in all processes, from initiation to progression, to final tumor metastasis. Although energy deprivation and autophagy are widely used for cancer therapy, most of these strategies do not target macrophages, resulting in undesired effects and unsatisfactory outcomes for cancer immunotherapy. Herein, we developed a lanthanum nickel oxide (LNO) nanozyme with phosphatase-like activity for ATP hydrolysis. Meanwhile, the autophagy of macrophages induced by LNO promotes the polarization of macrophages from M2-like macrophages (M2) to M1-like macrophages (M1) and reduces tumor-associated macrophages in tumor-bearing mice, exhibiting the capability of killing tumor-associated macrophages and antitumor effects in vivo. Furthermore, pre-coating the surface of LNO with a myeloid cell membrane significantly enhanced antitumor immunity. Our findings demonstrate that phosphatase-like nanozyme LNO can specifically induce macrophage autophagy, which improves therapeutic efficacy and offers valuable strategies for cancer immunotherapy.

Synthesis and photoluminescence properties of polymer chains based on pre-designed heterometallic Al4Ln4 molecular rings.

Presented herein is a series of chain compounds based on pre-designed heterometallic aluminum-lanthanide (Al-Ln) Al4Ln4 molecular rings. Their photoluminescence quantum yield (PLQY) with Eu3+ (30.41%) and Tb3+ (41.44%) is at a high level among the clusters containing four Ln ions. This study significantly extends the family of Al-Ln heterometallic clusters and demonstrates the synergistic effect of heterometallic ions in enhancing their properties.

Streamlining heterologous expression of top carbonic anhydrases in Escherichia coli: bioinformatic and experimental approaches.

BACKGROUND: Carbonic anhydrase (CA) enzymes facilitate the reversible hydration of CO2 to bicarbonate ions and protons. Identifying efficient and robust CAs and expressing them in model host cells, such as Escherichia coli, enables more efficient engineering of these enzymes for industrial CO2 capture. However, expression of CAs in E. coli is challenging due to the possible formation of insoluble protein aggregates, or inclusion bodies. This makes the production of soluble and active CA protein a prerequisite for downstream applications. RESULTS: In this study, we streamlined the process of CA expression by selecting seven top CA candidates and used two bioinformatic tools to predict their solubility for expression in E. coli. The prediction results place these enzymes in two categories: low and high solubility. Our expression of high solubility score CAs (namely CA5-SspCA, CA6-SazCAtrunc, CA7-PabCA and CA8-PhoCA) led to significantly higher protein yields (5 to 75 mg purified protein per liter) in flask cultures, indicating a strong correlation between the solubility prediction score and protein expression yields. Furthermore, phylogenetic tree analysis demonstrated CA class-specific clustering patterns for protein solubility and production yields. Unexpectedly, we also found that the unique N-terminal, 11-amino acid segment found after the signal sequence (not present in its homologs), was essential for CA6-SazCA activity. CONCLUSIONS: Overall, this work demonstrated that protein solubility prediction, phylogenetic tree analysis, and experimental validation are potent tools for identifying top CA candidates and then producing soluble, active forms of these enzymes in E. coli. The comprehensive approaches we report here should be extendable to the expression of other heterogeneous proteins in E. coli.

A Self-Cascade Oxygen-Generating Nanomedicine for Multimodal Tumor Therapy.

Natural and artificial enzyme oxygen-generating systems for photodynamic therapy (PDT) are developed for tumor treatment, yet they have fallen short of the desired efficacy. Moreover, both the enzymes and photosensitizers usually need carriers for efficient delivery to tumor sites. Here, a self-cascade-enhanced multimodal tumor therapy is developed by ingeniously integrating self-cascade-enhanced PDT with Zn2+-overloading therapy. Manganese-porphyrin (TCPP-Mn) is chosen both as the photosensitizer and catalase (CAT) mimic, which can be encapsulated within glucose oxidase (GOx). Acid-responsive zeolitic imidazolate framework-8 (ZIF-8) is applied as the carrier for TCPP-Mn@GOx (T@G), attaining TCPP-Mn@GOx@ZIF-8 (T@G@Z). T@G@Z demonstrates robust anti-tumor ability as follows: upon the structural degradation of ZIF-8, GOx can mediate the oxidation of glucose and generate hydrogen peroxide (H2O2); TCPP-Mn can catalyze H2O2 into O2 for self-cascade-enhanced PDT; meanwhile, the released Zn2+ can enhance oxidative stress and induce mitochondrial dysfunction by destroying mitochondrial membrane potential; furthermore, immunotherapy can be activated to resist primary tumor and tumor metastasis. The self-cascade-enhanced T@G@Z exhibited its potential application for further tumor management.

Determining the abundance, composition and spatial distribution of organohalogens in marine sediments using combustion-ion chromatography.

Understanding the distribution of halogenated organic compounds (HOCs) in marine sediments is essential for understanding the marine carbon and halogen cycling, and also important for assessing the ecosystem health. In this study, a method based on combustion-ion chromatography was developed for determination of the composition and abundance of HOCs in marine sediments. The method showed high accuracy, precision and reproducibility in determining the content of adsorbable organic halogens (AOX), including fluorine, chlorine and bromine (AOF, AOCl, AOBr) and the corresponding insoluble organic halogens (IOF, IOCl, IOBr, IOX), as well as total organic halogen contents (TOX). Application of the method in coastal and deep-sea sediments revealed high ratios of organic halogens in the organic carbon pool of marine sediments, suggesting that organic halogen compounds represent an important yet previously overlooked stock of carbon and energy in marine sediments. Both the TOX and the proportion of organohalogens in organic carbon (X:C ratio) showed an increasing trend from the coast to the deep-sea sediments, indicating an increased significance of HOCs in deep-sea environments. The developed method and the findings of this study lay the foundation for further studies on biogeochemical cycling of HOCs in the ocean.

Two-Step Hydrothermal Synthesis of Submicrometric and Hierarchical Hollow SAPO-34 with Superior Catalytic Performance in Methanol to Olefin (MTO) Reaction.

A submicrometric and hierarchical hollow SAPO-34 molecular sieve was synthesized by an easy and low-cost two-step hydrothermal method. First, the crystallized mixture was obtained by direct drying after a first-step hydrothermal reaction. Then, the SAPO-34 product was obtained by adding the crystallized mixture to silicon-free gel and using cheap and common template agents. Compared to conventional SAPO-34, the submicrometric and hierarchical hollow SAPO-34 exhibits superior catalytic activity in the MTO reaction.

Impacts of conventional and biodegradable microplastics in maize-soil ecosystems: Above and below ground.

The increasing accumulation of microplastics (MPs) in agroecosystems has raised significant environmental and public health concerns, facilitating the application of biodegradable plastics. However, the comparative effects of conventional and biodegradable MPs in agroecosystem are still far from fully understood. Here we developed microcosm experiments to reveal the ecological effects of conventional (polyethylene [PE] and polypropylene [PP]) and biodegradable (polyadipate/butylene terephthalate [PBAT] and polycaprolactone [PCL]) MPs (0, 1%, 5%; w/w) in the maize-soil ecosystem. We found that PCL MPs reduced plant production by 73.6-75.2%, while PE, PP and PBAT MPs elicited almost negligible change. The addition of PCL MPs decreased specific enzyme activities critical for soil nutrients cycling by 71.5-95.3%. Biodegradable MPs tended to reduce bacterial α-diversity. The 1% treatments of PE and PBAT, and PCL enhanced bacterial networks complexity, whereas 5% of PE and PBAT, and PP had adverse effect. Moreover, biodegradable MPs appeared to reduce the α-diversity and networks complexity of fungal community. Overall, PCL reduced the ecosystem multifunctionality, mainly by inhibiting the microbial metabolic activity. This study offers evidence that biodegradable MPs can impair agroecosystem multifunctionality, and highlights the potential risks to replace the conventional plastics by biodegradable ones in agricultural practices.