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Abstract Many observational studies and experiments have found a strong association between lipid levels and adipokines and multiple myeloma (MM), but the causal relationship between lipid levels, adipokines and MM remains to be determined. We performed a two-sample and multivariate MR analysis to investigate the causal relationship between lipid levels, adipokines and MM. Total cholesterol(TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) were used to represent lipid levels, and adiponectin, leptin, and resistin were used to represent adipokines. Genetic data for each index and MM were obtained from the Integrated Epidemiology Unit (IEU) Genome-Wide Association Study (GWAS) database, and two-sample MR analyses were performed, as well as multivariate MR analyses of adipokines for causality of MM using BMI as an adjusting factor. In the analyzed results, no significant causal association was found between adipokines, lipid levels and multiple myeloma, and after adjusting for BMI, an association between adipokines and MM was still not found. The results of this MR study do not support an association between genetically predicted adipokines, lipid levels, and risk of MM, but we cannot rule out the existence of a weak association. The mechanisms need to be further investigated.

Photocatalytic CO2 reduction to produce high value-added carbon-based fuel has been proposed as a promising approach to mitigate global warming issues. However, the conversion efficiency and product selectivity are still low due to the sluggish dynamics of transfer processes involved in proton-assisted multi-electron reactions. Lowering the formation energy barriers of intermediate products is an effective method to enhance the selectivity and productivity of final products. In this study, we aim to regulate the surface electronic structure of Bi2WO6 by doping surface chlorine atoms to achieve effective photocatalytic CO2 reduction. Surface Cl atoms can enhance the absorption ability of light, affect its energy band structure and promote charge separation. Combined with DFT calculations, it is revealed that surface Cl atoms can not only change the surface charge distribution which affects the competitive adsorption of H2O and CO2, but also lower the formation energy barrier of intermediate products to generate more intermediate ∗COOH, thus facilitating CO production. Overall, this study demonstrates a promising surface halogenation strategy to enhance the photocatalytic CO2 reduction activity of a layered structure Bi-based catalyst.

Good crystallinity can reduce the charge recombination centers caused by defects, whilst structures with strong polycondensation have high charge mobility, leading to more charge transfer to the material surface for reaction. Much effort has been put into the preparation of a highly efficient g-C3N4 with defects to improve its application potential under the premise in high crystallinity. Hence, this review paper emphasizes the importance to balance the defect and crystallinity of g-C3N4. In addition, detailed discussion on the relationship between defects and activity of g-C3N4 was carried out based on its applications in environmental purification (e.g., VOCs oxidation, NOx oxidation, H2O2 evolution, sterilization, pesticide oxidation) and energy conversion (H2 evolution, N2 fixation and CO2 reduction). Lastly, the challenge in developing more efficient defective g-C3N4 photocatalytic materials is summarized.

The increasing prevalence of endocrine-disrupting chemicals (EDCs) and their potential adverse effects on human health underscore the necessity for robust tools to assess and manage associated risks. The androgen receptor (AR) is a critical component of the endocrine system, playing a pivotal role in mediating the biological effects of androgens, which are male sex hormones. Exposure to androgen-disrupting chemicals during critical periods of development, such as fetal development or puberty, may result in adverse effects on reproductive health, including altered sexual differentiation, impaired fertility, and an increased risk of reproductive disorders. Therefore, androgenic activity data is critical for chemical risk assessment. A large amount of androgenic data has been generated using various experimental protocols. Moreover, the data are reported in different formats and in diverse sources. To facilitate utilization of androgenic activity data in chemical risk assessment, the Molecules with Androgenic Activity Resource (MAAR) was developed. MAAR is the first open-access platform designed to streamline and enhance the risk assessment of chemicals with androgenic activity. MAAR’s development involved the integration of diverse data sources, including data from public databases and mining literature, to establish a reliable and versatile repository. The platform employs a user-friendly interface, enabling efficient navigation and extraction of pertinent information. MAAR is poised to advance chemical risk assessment by offering unprecedented access to information crucial for evaluating the androgenic potential of a wide array of chemicals. The open-access nature of MAAR promotes transparency and collaboration, fostering a collective effort to address the challenges posed by androgenic EDCs.

ObjectiveTo investigate the potential mediating role of inflammatory proteins in the association between lipid species and Deep Venous Thrombosis (DVT).MethodsA comprehensive analysis was conducted using pooled data from genome-wide association studies (GWAS), incorporating double-sample and reverse Mendelian randomization (MR) techniques, to identify the specific inflammatory proteins that act as intermediaries among 91 screened proteins in relation to deep vein thrombosis (DVT). Furthermore, a two-step MR approach was employed to quantify the proportion of DVT risk attributed to lipid effects mediated by these inflammatory proteins.ResultsThe MR Analysis revealed that the two inflammatory proteins, as predicted by genetics, served as mediating factors in the impact of five lipids on DVT. No reverse effect of DVT was observed on 179 lipid species and 91 inflammatory proteins. In the case of TAG(58:7) and its influence on DVT, CCL20 played an intermediary role with an estimated proportion of 12.51% (ranging from 12% to 13%). SIRT2 exhibited a masking effect on DVT for PC(17:0/20:4) and PC(18:0/20:4), while CCL20 masked the impact of DVT on PC(14:0/18:2), PC(15:0/18:2), and PC(18:0/20:5).ConclusionsIn our study, we identified CCL20 as a crucial mediator in the association between TAG(58:7) and DVT, with a mediating proportion of 12.51% (12%-13%). Further investigations are warranted to explore other potential risk factors acting as mediators.

IntroductionSocial media platforms serve as a valuable resource for users to share health-related information, aiding in the monitoring of adverse events linked to medications and treatments in drug safety surveillance. However, extracting drug-related adverse events accurately and efficiently from social media poses challenges in both natural language processing research and the pharmacovigilance domain.MethodRecognizing the lack of detailed implementation and evaluation of Bidirectional Encoder Representations from Transformers (BERT)-based models for drug adverse event extraction on social media, we developed a BERT-based language model tailored to identifying drug adverse events in this context. Our model utilized publicly available labeled adverse event data from the ADE-Corpus-V2. Constructing the BERT-based model involved optimizing key hyperparameters, such as the number of training epochs, batch size, and learning rate. Through ten hold-out evaluations on ADE-Corpus-V2 data and external social media datasets, our model consistently demonstrated high accuracy in drug adverse event detection.ResultThe hold-out evaluations resulted in average F1 scores of 0.8575, 0.9049, and 0.9813 for detecting words of adverse events, words in adverse events, and words not in adverse events, respectively. External validation using human-labeled adverse event tweets data from SMM4H further substantiated the effectiveness of our model, yielding F1 scores 0.8127, 0.8068, and 0.9790 for detecting words of adverse events, words in adverse events, and words not in adverse events, respectively.DiscussionThis study not only showcases the effectiveness of BERT-based language models in accurately identifying drug-related adverse events in the dynamic landscape of social media data, but also addresses the need for the implementation of a comprehensive study design and evaluation. By doing so, we contribute to the advancement of pharmacovigilance practices and methodologies in the context of emerging information sources like social media.

Previous studies have demonstrated an association between lymphatic vessels and diseases caused by bacterial infections. Listeria monocytogenes (LM) bacterial infection can affect multiple organs, including the intestine, brain, liver and spleen, which can be fatal. However, the impacts of LM infection on morphological and functional changes of lymphatic vessels remain unexplored. In this study, we found that LM infection not only induces meningeal and mesenteric lymphangiogenesis in mice, but also impairs meningeal lymphatic vessels (MLVs)-mediated macromolecules drainage. Interestingly, we found that the genes associated with lymphatic vessel development and function, such as Gata2 and Foxc2, were downregulated, suggesting that LM infection may affect cellular polarization and valve development. On the other hand, photodynamic ablation of MLVs exacerbated inflammation and bacterial load in the brain of mice with LM infection. Overall, our findings indicate that LM infection induces lymphangiogenesis and may affect cell polarization, cavity formation, and valve development during lymphangiogenesis, ultimately impairing MLVs drainage.

Abstract Bacterial infections pose a severe threat to human health due to the exacerbation of antibiotic resistance and intracellular bacterial infections. Research suggests that oligo(p-phenylene vinylene) (OPV), commonly employed in the manufacture of organic solar batteries, can help address this issue. This study demonstrates the ability of OPV to target and sterilize intracellular Porphyromonas gingivalis and methicillin-resistant Staphylococcus aureus (MRSA) photodynamically. Most notably, OPV specifically targets bacteria without affecting healthy cells under dark conditions. Its chemical composition includes a conjugated backbone and ionic imidazole side chains, which allow OPV to bind to cell membranes. Furthermore, dental blue light curing lamps may excite OPV. Compared with antibiotics and traditional photosensitizers, OPV proves to be a potentially superior solution to eradicate intracellular microbial infections, both in fundamental research and clinical applications.

BackgroundThe worldwide incidence of Crohn disease (CD) in childhood and adolescence has an increasing trend, with significant differences between different geographic regions and individual countries. This includes an increase in the incidence of CD in countries and geographic regions where CD was not previously prevalent. In response to the increasing incidence, the pediatric care landscape is facing growing challenges. ObjectiveThis systematic review and meta-analysis were undertaken to comprehensively delineate the incidence rates of CD in pediatric populations across different countries and to explore potential influencing factors. MethodsWe performed a systematic review of PubMed and Embase (via Ovid) for studies from January 1, 1970, to December 31, 2019. In addition, a manual search was performed in relevant and previously published reviews. The results were evaluated quantitatively. For this purpose, random effects meta-analyses and meta-regressions were performed to investigate the overall incidence rate and possible factors influencing the incidence. ResultsA qualitative synthesis of 74 studies was performed, with 72 studies included in the meta-analyses and 52 in the meta-regressions. The results of our meta-analysis showed significant heterogeneity between the individual studies, which cannot be explained by a sample effect alone. Our findings showed geographical differences in incidence rates, which increased with increasing distance from the equator, although no global temporal trend was apparent. The meta-regression analysis also identified geographic location, UV index, and Human Development Index as significant moderators associated with CD incidence. ConclusionsOur results suggest that pediatric CD incidence has increased in many countries since 1970 but varies widely with geographic location, which may pose challenges to the respective health care systems. We identified geographic, environmental, and socioeconomic factors that contribute to the observed heterogeneity in incidence rates. These results can serve as a basis for future research. To this end, implementations of internationally standardized and interoperable registries combined with the dissemination of health data through federated networks based on a common data model, such as the Observational Medical Outcomes Partnership, would be beneficial. This would deepen the understanding of CD and promote evidence-based approaches to preventive and interventional strategies as well as inform public health policies aimed at addressing the increasing burden of CD in children and adolescents. Trial RegistrationPROSPERO International prospective register of systematic reviews CRD42020168644; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=168644 International Registered Report Identifier (IRRID)RR2-10.1136/bmjopen-2020-037669

Abstract Background Spermatogenic dysfunction is an important cause of azoospermia. Numerous studies have focused on germ-cell-related genes that lead to spermatogenic impairment. However, based on the immune-privileged characteristics of the testis, the relationship of immune genes, immune cells or immune microenvironment with spermatogenic dysfunction has rarely been reported. Results Using integrated methods including single-cell RNA-seq, microarray data, clinical data analyses and histological/pathological staining, we found that testicular mast cell infiltration levels were significantly negatively related to spermatogenic function. We next identified a functional testicular immune biomarker, CCL2, and externally validated that testicular CCL2 was significantly upregulated in spermatogenic dysfunctional testes and was negatively correlated with Johnsen scores (JS) and testicular volumes. We also demonstrated that CCL2 levels showed a significant positive correlation with testicular mast cell infiltration levels. Moreover, we showed myoid cells and Leydig cells were two of the important sources of testicular CCL2 in spermatogenic dysfunction. Mechanistically, we drew a potential “myoid/Leydig cells-CCL2-ACKR1-endothelial cells-SELE-CD44-mast cells” network of somatic cell–cell communications in the testicular microenvironment, which might play roles in spermatogenic dysfunction. Conclusions The present study revealed CCL2-relevant changes in the testicular immune microenvironment in spermatogenic dysfunction, providing new evidence for the role of immunological factors in azoospermia.

The opioid crisis in the United States is a significant public health issue, with a nearly threefold increase in opioid-related fatalities between 1999 and 2014. In response to this crisis, society has made numerous efforts to mitigate its impact. Recent advancements in understanding the structural intricacies of the κ opioid receptor (KOR) have improved our knowledge of how opioids interact with their receptors, triggering downstream signaling pathways that lead to pain relief. This review concentrates on the KOR, offering crucial structural insights into the binding mechanisms of both agonists and antagonists to the receptor. Through comparative analysis of the atomic details of the binding site, distinct interactions specific to agonists and antagonists have been identified. These insights not only enhance our understanding of ligand binding mechanisms but also shed light on potential pathways for developing new opioid analgesics with an improved risk-benefit profile.

Understanding the electrochemical deoxygenation pathway of aldehydes and ketones is important yet challenging. Here the authors use acetaldehyde as a model system to elucidate the role of enols in the electroreduction of aldehydes and ketones, which may shed light on the reaction pathway of CO2 to C2 and C3 products.

Abstract Background Non-muscle invasive bladder cancer (NMIBC) represents the majority of bladder neoplasms. It is unusual for NMIBC metastasizing distantly without regional progression, namely metastatic NMIBC (mNMIBC), which is still poorly understood and easily omitted based on current management policies. So far, description of mNMIBC is limited to a few case reports. Methods We reported a 70-year-old man with NMIBC who suffered from cervical metastasis without pelvic recurrence at 41 months after initial diagnosis. Then we performed a collective analysis of this case together with published mNMIBC cases searched from PubMed, Embase, and Web of Science, aiming to illustrate baseline clinicopathologic parameters, metastatic patterns, and treatment outcomes of these patients and analyze associated influencing factors. Results After scrupulous review, 45 cases previous reported and the one from our center were incorporated into the aggregated cohort of mNMIBC, including 34 males and 12 females. Primary tumors from 46.7% of patients were high-grade (HG) or grade 3 (G3) and 65.1% had T1 lesions. Aberrant biomarker expression was found in tumors of some cases. Most (40/46) metastases of mNMIBC occurred at a single site, mainly in lung, bone and lymph nodes. Apart from three cases of de novo mNMIBC, the mean metastasis-free survival (MFS) interval of metachronous mNMIBC was 42.5 months, which was obviously longer than conventional metastatic bladder cancer. Shortened MFS interval was associated with old age, T1 or HG/G3 primary tumors, and non-lung metastases. Systemic chemotherapy and metastasectomy or radiotherapy for oligometastatic lesion were main therapeutic approaches of mNMIBC, and immunotherapy was adopted for the case from our center. Lung and bone metastases correlated with relatively favorable and unfavorable survival outcomes, respectively. Compared with monotherapy, chemotherapy, or immunotherapy combined with local cytoreduction got more favorable outcomes. Conclusion Although rare, mNMIBC occurs more in tumors with high-risk features. Usually, mNMIBC metastasizes later than conventional metastatic bladder cancer and manifests as solitary lesion. Outcomes of mNMIBC would be influenced by metastatic site and post-metastatic treatment. Systemic treatment combined with local cytoreduction may render survival benefit in selected patients.

With the increasing number of cholecystectomy and the high proportion of colorectal cancer in malignant tumors, the question of whether cholecystectomy is a risk factor for colorectal disease has been widely concerned. After reviewing the literature at home and abroad, the authors will summarize the research progress of the correlation between the occurrence of colorectal tumors after cholecystectomy, in order to provide help for the prevention and treatment of colorectal tumors.

The effective sharing of health research data within the healthcare ecosystem can have tremendous impact on the advancement of disease understanding, prevention, treatment, and monitoring. By combining and reusing health research data, increasingly rich insights can be made about patients and populations that feed back into the health system resulting in more effective best practices and better patient outcomes. To achieve the promise of a learning health system, data needs to meet the FAIR principles of findability, accessibility, interoperability, and reusability. Since the inception of the Brain-CODE platform and services in 2012, the Ontario Brain Institute (OBI) has pioneered data sharing activities aligned with FAIR principles in neuroscience. Here, we describe how Brain-CODE has operationalized data sharing according to the FAIR principles. Findable—Brain-CODE offers an interactive and itemized approach for requesters to generate data cuts of interest that align with their research questions. Accessible—Brain-CODE offers multiple data access mechanisms. These mechanisms—that distinguish between metadata access, data access within a secure computing environment on Brain-CODE and data access via export will be discussed. Interoperable—Standardization happens at the data capture level and the data release stage to allow integration with similar data elements. Reusable - Brain-CODE implements several quality assurances measures and controls to maximize data value for reusability. We will highlight the successes and challenges of a FAIR-focused neuroinformatics platform that facilitates the widespread collection and sharing of neuroscience research data for learning health systems.

Abstract Non‐invasive light‐based antibacterial therapy has a good prospect in non‐surgical treatment of peri‐implant infections. However, its applications are severely limited by poor penetration of light into human tissues, leading to unsatisfying outcomes. Moreover, as an essential prerequisite for traditional light therapy, lasers can no longer meet the patients’ needs for convenient treatment at any time. To break through the spatial and temporal limitations of traditional light therapy, a wireless‐powered blue‐light zirconia implant for readily available treatment of peri‐implant infection is proposed. In space, complete irradiation to complex peri‐implant structure is realized by the built‐in wireless‐powered light source, thus improving the efficacy. In time, wireless‐powering allows timely and controllable anti‐infection treatment. Blue micro‐light emitting diodes are used as therapeutic light sources, which effectively kill peri‐implant infection‐related bacteria without exogenous photosensitive agents. Porphyromonas gingivalis biofilm on implant surface can be completely killed after 20 min irradiation in vitro. The bactericidal rate of peri‐implant methicillin‐resistant Staphylococcus aureus infection reaches 99.96 ± 0.03% under 30 min per day blue light exposure in vivo. Within the scope of this study, the treatment of peri‐implant infection with blue‐light implant has preliminary feasibility, giving a new approach to non‐invasive treatment of deep oral infections, including peri‐implant infections.

Abstract Background Dandruff is a chronic, recurring, and common scalp problem that is caused by several etiopathogeneses with complex mechanisms. Management of this condition is typically achieved via antifungal therapies. However, the precise roles played by microbiota in the development of the condition have not been elucidated. Despite their omnipresence on human scalp little is known about the co-occurrence/co-exclusion network of cutaneous microbiota. Results We characterized the scalp and hair surface bacterial and fungal communities of 95 dandruff-afflicted and healthy individuals residing in China. The degree distributions of co-occurrence/co-exclusion network in fungi-bacteria and bacteria-bacteria were higher in the healthy group (P

Objective To investigate the clinical characteristics of neuromyelitis optica spectrum disorders (NMOSDs) with other autoimmune diseases. Methods and Results Retrospective analysis was performed on 55 NMOSDs patients admitted to Peking University Third Hospital from June 2014 to January 2019. There were 10 NMOSDs patients with autoimmune diseases, including 5 patients with Sjögren's syndrome (SS), 2 patients with Hashimone's thyroiditis (HT), one patient with rheumatoid arthritis (RA), one patient with systemic lupus erythematosus (SLE), and one patient with undifferentiated connective tissue disease. The proportion of females with autoimmune disease (adjusted χ2=3.842, P=0.050) and positive of anti⁃AQP4 antibody (adjusted χ2=4.303, P=0.038) was higher than that of females without autoimmune diseases. Among 10 patients of NMOSDs with other autoimmune diseases, 9 patients involved spinal cord, 3 cases only involved cervical spinal, 2 cases only involved thoracic spinal, 4 cases involved both cervical and thoracic spinal at the same time, 4 cases involved optic nerve, one case involved only optic nerve. There was brain lesions in 2 cases, one case involved medulla oblongata. The imaging characteristics of spinal cord lesions were consistent with those of patients with NMOSDs. The length of the lesions were all longer than 3 vertebral bodies, and the longest lesions involved 10 segments. Conclusions NMOSDs is easy to be combined with other autoimmune diseases, which are more common in women, and the rate of positive of anti⁃AQP4 antibody is higher, which should be paid attention to.

Photocatalytic reduction of waste nitrate offers an alternative route for ammonia production. Here the authors report BaO clusters on TiO2 for nitrate-ammonia photosynthesis with high ammonia yield.

Abstract. Objective:. Rubicon is an inhibitory interacting protein of the autophagy-related protein Uvrag. We previously showed that Rubicon deficiency promotes autophagic flux in vivo and that autophagy can degrade lipid droplets. This study aimed to investigate the effects of Rubicon deficiency on fasting-induced hepatic steatosis. Methods:. Two-month-old wild-type (WT) and Rubicon-deficient mice were subjected to feeding or fasting for 24 hours to induce hepatic steatosis. The distribution of liver lipid droplets was revealed by oil red O staining. Hepatic and plasma triglyceride, non-esterified fatty acid (NEFA), and cholesterol levels were detected using commercially available kits. Real-time reverse transcriptase-polymerase chain reaction was performed to analyze the mRNA expression of genes related to lipid metabolism in the liver. Western blot was conducted to assess autophagy-related protein levels in the liver. The animal experiments were approved by the Institutional Animal Care and Use Committee at Shanghai Jiao Tong University, China. Results:. We showed that under fasting conditions, Rubicon-deficient mice had more lipid droplets in the liver than WT controls. Consistent with these results, the hepatic triglyceride, NEFA, and cholesterol levels in fasted Rubicon-deficient mice were significantly higher than those of fasted WT controls. The levels of SREBP-1, a key regulator of lipid synthesis, were significantly lower in livers from fasted WT mice than those of fed WT mice. However, the decrease in SREBP-1 in fasted mice was attenuated by Rubicon deficiency. Western blot analysis demonstrated that the fasting-induced increase in autophagic flux was amplified by Rubicon deficiency. Finally, we showed that Rubicon deficiency in mice led to elevated plasma triglyceride and NEFA acid levels under fasting conditions. Conclusion:. Rubicon deficiency exacerbates fasting-induced hepatic steatosis in mice.

Great progress has been made in recent years in the development of low-temperature direct ammonia fuel cells (DAFCs), motivated by the recognition that ammonia is a carbon-free hydrogen carrier with high energy density, low production cost, and ease in liquefaction at ambient temperature. However, the sluggish kinetics of ammonia electrooxidation and especially complicated mass transport in the anode catalyst layer hinder the further development of DAFCs. In this work, a three-dimensional two-phase multicomponent DAFC model considering the effect of ammonia crossover has been developed. Maxwell-Stefan model, Darcy's law and Brinkman equation are utilized to simulate the multicomponent fluid motion and transport. The predicted polarization curve simulates all experimental results well. The model shows the rate of ammonia crossover decreases with the increase of current density. Besides, the effects of the physicochemical property of the anode catalyst layer, including porosity, thickness and PtIr loading, on cell performance are investigated. The modeling results indicate that decreasing porosity and increasing thickness can slightly improve the electrochemical performance of DAFCs at high current density. Meanwhile, higher PtIr loading can effectively reduce voltage loss before approaching the limiting current density.

Photocatalytic reduction of CO2 into fuels provides a prospective tactic for regulating the global carbon balance utilizing renewable solar energy. However, CO2 molecules are difficult to activate and reduce due to the thermodynamic stability and chemical inertness. In this work, we develop a novel strategy to promote the adsorption and activation of CO2 molecules via the rapid energy exchange between the photoinduced Br vacancies and CO2 molecules. Combining in situ continuous wave-electron paramagnetic resonance (cw-EPR) and pulsed EPR technologies, we observe that the spin–spin relaxation time (T2) of BiOBr is decreased by 198 ns during the CO2 photoreduction reaction, which is further confirmed by the broadened EPR linewidth. This result reveals that there is an energy exchange interaction between in situ formed Br vacancies and CO2 molecules, which promotes the formation of high-energy CO2 molecules to facilitate the subsequent reduction reaction. In addition, theoretical calculations indicate that the bended CO2 adsorption configuration on the surface of BiOBr with Br vacancies caused the decrease of the lowest unoccupied molecular orbital of the CO2 molecule, which makes it easier for CO2 molecules to acquire electrons and get activated. In situ diffuse reflectance infrared Fourier transform spectroscopy further shows that the activated CO2 molecules are favorably converted to key intermediates of COOH*, resulting in a CO generation rate of 9.1 μmol g−1 h−1 and a selectivity of 100%. This study elucidates the underlying mechanism of CO2 activation at active sites and deepens the understanding of CO2 photoreduction reaction.

ObjectiveIn Saxony, the incidence of Crohn's disease (CD) in children and adolescents increased significantly from 3.3 per 100,000 person-years in 2000 to 5.1 in 2014. The aim of this study was to describe the initial characteristics and the clinical course of CD in children and adolescents and to identify drug treatment options associated with an advantage for a mild course or remission.MethodsClinical data were collected from patients who suffered from inflammatory bowel disease (IBD) and were recruited in the Saxon Pediatric IBD-Registry. All children newly diagnosed with CD in this registry in Saxony between 2000 and 2014 were included in this registry study. Characteristics such as age, disease location and extra-intestinal manifestations at diagnosis were accessed. The severity level of the disease at diagnosis as well as at follow-up were analysed by PCDAI index. Patients were divided into 3 groups according to length of follow-up: 1-3 years, 4-6 years and 7-9 years after diagnosis. A logistic regression model was conducted to examine which baseline parameters are associated with disease progression.ResultsThere were 338 children and adolescents with CD included in this registry study. At diagnosis, the median age of patients was 12.0 (0.7-14.9), 61.5% (n = 208) of the patients were male. The most common disease location observed in pediatric CD patients was the L3 (55%, n = 176). Patients aged 10-14 years were significantly more likely to present an L2 than patients aged 0-4 years (80.3%, n = 53 vs. 19.7%, n = 13, p = 0.01). During the follow-up, data from 71.3% (n = 241) othe patients were available. Disease activity measured by PCDAI decreased in 47.7% (n = 115) of the patients, 40.7% (n = 98) of the patients were stable and increased in 11.6% (n = 28) of the patients. Patients with intermediate/severe disease at onset were more likely to have an active disease at the end of follow up, too (p = 0.00). Logistic regression analysis of the initial characteristics showed that the age at diagnosis, gender, initial location and initial extra-intestinal manifestation are not associated with the progression of the disease (p>0.05). Furthermore, drug treatment options could be identified from our data, which are associated with benefits for a milder course or remission.ConclusionFrom 2000 to 2014, the health status of most pediatric patients with CD had improved or remained stable. Initial characteristics including age at diagnosis, initial localization and initial extra-intestinal manifestation are not associated with the progression of the disease, only the initial activity by PCDAI.

As 2 indispensable counterparts in one catalysis system, the independent reduction and oxidation reactions require synergetic regulation for cooperatively promoting redox efficiency. Despite the current success in promoting the catalytic efficiency of half reduction or oxidation reactions, the lack of redox integration leads to low energy efficiency and unsatisfied catalytic performance. Here, we exploit an emerging photoredox catalysis system by combining the reactions of nitrate reduction for ammonia synthesis and formaldehyde oxidation for formic acid production, in which superior photoredox efficiency is achieved on the spatially separated dual active sites of Ba single atoms and Ti3+. High catalytic redox rates are accomplished for respective ammonia synthesis (31.99 ± 0.79 mmol gcat−1 h−1) and formic acid production (54.11 ± 1.12 mmol gcat−1 h−1), reaching a photoredox apparent quantum efficiency of 10.3%. Then, the critical roles of the spatially separated dual active sites are revealed, where Ba single atoms as the oxidation site using h+ and Ti3+ as the reduction site using e− are identified, respectively. The efficient photoredox conversion of contaminants is accomplished with environmental importance and competitive economic value. This study also represents a new opportunity to upgrade the conventional half photocatalysis into the complete paradigm for sustainable solar energy utilization.

High electrochemically active birnessite is always desirable pseudocapacitive material for supercapacitor. Here, two-dimensional (2D) compulsive malposition parallel birnessite standing on β-MnO2 interconnected networks have been designed. Due to the restriction of β-MnO2, compulsive malposition, slippage of MnO6 slab, occurred in birnessite resulting in weaken binding force between birnessite slab and interlayer cations, which enhanced their electrochemical performances. Additionally, the electrical conductivity of the structure was largely promoted by the 2D charge transfer route and double-exchange mechanism in birnessite, also leading to desirable electrochemical properties. Based on the fraction of as-prepared nanostructure, the parallel birnessite exhibited good pseudocapacitance performance (660 ​F ​g−1) with high rate capability. In addition, the asymmetric supercapacitor assembled by reduced graphene oxide (RGO) and as-prepared nanostructure, which respectively served as the negative and positive electrode, delivered an energy density of 33.1 ​Wh kg−1 and a maximum power density of 64.0 ​kW ​kg−1 with excellent cycling stability (95.8% after 10000 cycles). Finally, the study opens new avenues for synthesizing high electrochemically active birnessite structure for high-performance energy storage devices.

With the rising global population, increasing energy demand and rapid climate change, great concerns have been raised for environment and energy security in future. Solar-driven CO2 reduction provides a promising way to deal with energy crisis and global warming, which has been widely concerned. Photoelectrocatalysis technology can effectively utilize solar energy and avoid to use high-temperature and high-voltage reduction environment by integrating the vantages of both photocatalysis and electrocatalysis, which exhibits a broad application prospect of CO2 reduction with a high efficiency and excellent selectivity. In this review, basic principles of CO2 reduction by photocatalysis, electrocatalysis and photoeletrocatalysis are briefly reviewed, also comparing the technical characteristics of the above technologies. Different photoelectrocatalytic systems for CO2 reduction are described and compared. The several key influencing factors of photoelectrocatalytic performance of CO2 reduction are discussed, including interaction between reaction molecules and catalysts, reaction conditions and influence of photoelectrode. Then, the advances on reaction mechanisms and strategies of performance enhancement by optimizing photoexcitation, charge separation efficiency and surface reaction were reviewed. Besides, the challenges and prospects of photoelectrocatalytic CO2 reduction will be also discussed.

Engineering oxygen vacancies is an effective strategy to enhance the catalytic activity of MnO2 based composite oxides in heterogenous reactions, such as volatile organic compounds (VOCs) oxidation reaction. Core-shell structure LaMnO3@α-MnO2 catalysts were prepared by hydrothermal method via varying the concentrations of LaMnO3 and used in toluene oxidation reaction. Irregular core-shell structure L@M-10 catalyst exhibits excellent low temperature catalytic activity and stability, achieving 100% toluene removal efficiency at 200 °C. The light-off temperature (T50) and complete conversion temperature (T90) are 235 and 271 °C even after five repetitive cycles, respectively. The interfacial effect of L@M-10 sample promotes the generation of oxygen vacancies, facilitating the formation of active oxygen species. A possible oxidation reaction mechanism of toluene over L@M-10 catalyst was proposed in combination with the in-situ DRIFTS results. Fast ring-opening reaction and quick transformation of carboxylate or anhydride species into final products CO2 and H2O explains the superior catalytic property and stability of L@M-10 sample. This work highlights the effect of interface on the catalytic activity and stability of LaMnO3@α-MnO2 catalyst towards toluene oxidation and can offer a new insight into the utilization of interfacial effect in thermocatalytic reactions.

Dust storms have large impacts on air quality and meteorological elements; however, their relationships with atmospheric greenhouse gases (e.g., CO2) and radiation components remain uncertain. In this study, the co-variation of dust and CO2 concentrations and its possible influencing mechanism are examined using observations at the Shangdianzi (SDZ) regional Global Atmosphere Watch (GAW) station along with simulations of the Vegetation Photosynthesis and Respiration Model coupled with the Weather Research and Forecasting model (WRF-VPRM), during two dust storm events on 15 and 28 March 2021. During these events, hourly CO2 concentrations decreased by 40–50 ppm at SDZ while dust concentrations increased to 1240.6 and 712.4 µg m−3. The elevated dust increased diffusive shortwave irradiance by 50–60% and decreased direct shortwave irradiance by ~60% along with clouds. The dust events were attributed to the passages of two cold front systems over northern China. At SDZ, during the frontal passages, wind speed increased by 3–6 m s−1, and relative humidity decreased by 50–60%. The CO2 variations associated with the frontal systems were captured by the WRF-VPRM despite the overestimated surface CO2 level at SDZ. Biogenic CO2 flux plays an indistinctive role in the large CO2 variation at SDZ, as it is weak during the non-growing season. The cold fronts pushed polluted air southeastward over the North China Plain and replaced it with low-CO2 air from Northwest China, leading to the decline in CO2. These findings demonstrate that mesoscale synoptic conditions significantly affect the regional transport and dispersion of CO2, which can influence the prediction of terrestrial carbon balance on a regional scale.

Reproductive toxicity is one of the prominent endpoints in the risk assessment of environmental and industrial chemicals. Due to the complexity of the reproductive system, traditional reproductive toxicity testing in animals, especially guideline multigeneration reproductive toxicity studies, take a long time and are expensive. Therefore, machine learning, as a promising alternative approach, should be considered when evaluating the reproductive toxicity of chemicals. We curated rat multigeneration reproductive toxicity testing data of 275 chemicals from ToxRefDB (Toxicity Reference Database) and developed predictive models using seven machine learning algorithms (decision tree, decision forest, random forest, k-nearest neighbors, support vector machine, linear discriminant analysis, and logistic regression). A consensus model was built based on the seven individual models. An external validation set was curated from the COSMOS database and the literature. The performances of individual and consensus models were evaluated using 500 iterations of 5-fold cross-validations and the external validation data set. The balanced accuracy of the models ranged from 58% to 65% in the 5-fold cross-validations and 45%–61% in the external validations. Prediction confidence analysis was conducted to provide additional information for more appropriate applications of the developed models. The impact of our findings is in increasing confidence in machine learning models. We demonstrate the importance of using consensus models for harnessing the benefits of multiple machine learning models (i.e., using redundant systems to check validity of outcomes). While we continue to build upon the models to better characterize weak toxicants, there is current utility in saving resources by being able to screen out strong reproductive toxicants before investing in vivo testing. The modeling approach (machine learning models) is offered for assessing the rat multigeneration reproductive toxicity of chemicals. Our results suggest that machine learning may be a promising alternative approach to evaluate the potential reproductive toxicity of chemicals.

Deep learning algorithms have the advantages of a powerful time series prediction ability and the real-time processing of massive samples of big data. Herein, a new roller fault distance estimation method is proposed to address the problems of the simple structure and long conveying distance of belt conveyors. In this method, a diagonal double rectangular microphone array is used as the acquisition device, minimum variance distortionless response (MVDR) and long short-term memory network (LSTM) are used as the processing models, and the roller fault distance data are classified to complete the estimation of the idler fault distance. The experimental results showed that this method could achieve high-accuracy fault distance identification in a noisy environment and had better accuracy than the conventional beamforming algorithm (CBF)-LSTM and functional beamforming algorithm (FBF)-LSTM. In addition, this method could also be applied to other industrial testing fields and has a wide range of application prospects.

The traditional power transformer diagnosis method relies on a lot of experience knowledge and a complex sampling process, which brings great difficulties to the fault diagnosis work. To solve this problem, a fault feature extraction method based on fully adaptive noise set empirical mode decomposition (CEEMDAN) is proposed, and the hunter–prey optimization (HPO) algorithm is used to optimize the support vector machine (SVM) to identify and classify the voice print faults of power transformers. Firstly, the CEEMDAN algorithm is used to decompose the voicemarks into several IMF components. IMF components containing fault information are selected according to the envelope kurtosis index and reconstructed to generate new signal sequences. PCA dimensionality reduction is performed on the reconstructed signal, and the principal components are extracted with a high cumulative contribution rate as input to SVM. Then, the HPO-SVM algorithm is used to classify and identify transformer faults. Apply the proposed method to the diagnosis of typical faults in power transformers. The results show that the accuracy of this method in identifying various fault states of power transformers can reach 98.5%, and it has better classification performance than other similar methods.

At present, the fault diagnosis methods for rolling bearings are all based on research with fewer fault categories, without considering the problem of multiple faults. In practical applications, the coexistence of multiple operating conditions and faults can lead to an increase in classification difficulty and a decrease in diagnostic accuracy. To solve this problem, a fault diagnosis method based on an improved convolution neural network is proposed. The convolution neural network adopts a simple structure of three-layer convolution. The average pooling layer is used to replace the common maximum pooling layer, and the global average pooling layer is used to replace the full connection layer. The BN layer is used to optimize the model. The collected multi-class signals are used as the input of the model, and the improved convolution neural network is used for fault identification and classification of the input signals. The experimental data of XJTU-SY and Paderborn University show that the method proposed in this paper has a good effect on the multi-classification of bearing faults.

The electron density of reactive sites significantly affects catalytic performances. Here, authors demonstrate the electron density of different reactive sites can be modulated by regulating the type of vacancy and the size of Au, leading to effective CO2 photoreduction.

Cardamonin is a chalcone that presents at high content in the seeds of Alpinia katsumadai Hayata. In recent decades, researchers have found that it is not only an edible spice, but also a remarkable herb with a wide range of pharmacological properties. However, its specific metabolic routes in vivo remain unclear while these metabolites may accumulate to exert pharmacological effects. Our study aimed to clarify the metabolic pathways of cardamonin after oral administration to rats. Here, an advanced UHPLC-Q-Exactive Orbitrap MS analytical technique was applied for efficient detection of metabolites in vivo, which especially showed benefits in obtainment of the fragment ions with relatively lower contents. We also established a novel strategy to identify metabolites based on typical fragmentation routes. The results indicated that a total of 40 metabolites could be categorized into 3 types with consideration of the particular structures and characteristic fragment ions. Then, diagnostic product ions (DPIs) of each type were summarized for further screening and identification of metabolites derived from cardamonin. Finally, methylation, demethylation, hydrogenation, hydroxylation, dehydroxylation, glucuronidation and sulfation were confirmed to be the major metabolic pathways in vivo. Our observation extended the metabolic mechanism of cardamonin and could be of great benefits to interpreting the action mechanism of cardamonin in vivo.

Abstract RNA-binding proteins (RBPs) predominantly contribute to abnormal posttranscriptional gene modulation and disease progression in cancer. Sorbin and SH3 domain-containing 2 (SORBS2), an RBP, has been reported to be a potent tumor suppressor in several cancer types. Through integrative analysis of clinical specimens, we disclosed that the expression level of SORBS2 was saliently decreased in metastatic tissues and positively correlated with overall survival. We observed that overexpression of SORBS2 brought about decreased metastatic capacity in ccRCC cell lines. Transcriptome-wide analysis revealed that SORBS2 notably increased microtubule-associated tumor-suppressor 1 gene (MTUS1) expression. In-depth mechanistic exploring discovered that the Cys2-His2 zinc finger (C2H2-ZnF) domain of SORBS2 directly bound to the 3′ untranslated region (3′UTR) of MTUS1 mRNA, which increased MTUS1 mRNA stability. In addition, we identified that MTUS1 regulated microtubule dynamics via promoting KIF2CS192 phosphorylation by Aurora B. Together, our research identified SORBS2 as a suppressor of ccRCC metastasis by enhancing MTUS1 mRNA stability, providing a novel understanding of RBPs during ccRCC progression.

Resveratrol is an antitoxin secreted by plants such as Polygonum cuspidatum Sieb. et Zucc and Vitis vinifera L. when they are attacked by pathogens. In the present study, three methods were used to prepare biological samples, and then an efficient strategy based on ultra-high-performance liquid chromatography-linear ion trap-Orbitrap mass spectrometry (UHPLC-LTQ-Orbitrap MS) was developed to screen and identify resveratrol metabolites in rat urine, plasma and faeces. As a result, a total of 56 resveratrol metabolites were screened and characterized. Among them, 39 metabolites were found in rat urine, while 6 and 16 metabolites were characterized from rat plasma and faeces, respectively. In addition, 56, 12 and 15 metabolic products were screened by solid phase extraction (method I), methanol precipitation (method II) and acetonitrile precipitation (method III), respectively, indicating that method I could be adopted as the most acceptable method. The results also demonstrated that resveratrol mainly underwent glucuronidation, glucosylation, sulfation, hydroxylation, dehydrogenation, hydrogenation, methylation and their composite reactions. Moreover, these metabolic reactions occurred to form a possible metabolic network that is similar to a triangular pyramid model. In summary, this research provides an idea for the further study of drug metabolism.

Surface defects with abundant localized electrons on bismuth oxyhalide catalysts are proved to have the capability to capture and activate CO2. However, bismuth oxyhalide materials are susceptible to photocorrosion, making the surface defects easily deactivated and therefore losing their function as active sites. Construction of deactivation-resistant surface defects on catalyst is essential for stable CO2 photoreduction, but is a universal challenge. In this work, the Bi5O7I nanotubes with surface tensile strain are synthesized, which are favorable for the visible light-induced dynamic I defects generation. The CO2 molecules absorbed on I defects are constantly reduced by the incoming photogenerated electrons from I-deficient Bi5O7I nanotubes and the successive protonation of CO2 molecules is thus highly promoted, realizing the selective CO2 conversion process via the route of CO2-COOH--CO. The efficient and stable photoreduction of CO2 into CO with 100% selectivity can be achieved even under visible light (λ >420 nm) irradiation benefited from the dynamic I defects as active sites. The results presented herein demonstrate the unique action mechanism of light-induced dynamic defects during CO2 photoreduction process and provide a new strategy into rational design of deactivation-resistant catalysts for selective CO2 photoreduction.

In 2020, the sudden outbreak of coronavirus disease 2019 (COVID-19) has had a great impact on the health and life of people all over the world, and the sports industry is facing unprecedented challenges due to its participation and strong clustering. Based on the questionnaire survey, literature analysis, and other research methods, this study introduces the stimulus-organism-response (SOR) theory, takes the sports and consumption of Kunshan citizens as the research subject, and draws lessons from the structural equation model (SEM) to build a theoretical model of sports consumption characteristics and future consumption willingness. The results of empirical analysis show that physical sports consumption has been greatly affected by the epidemic, but because people realize the importance of sports, the willingness of residents to consume sports increases, and the venue and other factors affect the ornamental and participating sports consumption willingness decreases. At the same time, the restrictive factors, such as lower educational background, increased age, and lack of time, make the sports consumption willingness of this characteristic group significantly lower than that of other citizens. This study puts forward some suggestions for relevant government departments to improve the sports consumption willingness of citizens. In order to expand the development prospect of sports industry from a long-term perspective, it can provide reference for the development of sports consumption.

Nanostructural two-dimensional compounds are grabbing the attention of researchers all around the world. This research is progressing quickly due to its wide range of applications in numerous industries and enormous promise for future technological breakthroughs. Growing environmental consciousness has made it vital to treat wastewater and avoid releasing hazardous substances into the environment. Rising consumer expectations have led to the emergence of new, frequently nonbiodegradable compounds. Due to their specific chemical and physical properties, MXenes have recently been identified as promising candidates. MXenes are regarded as a prospective route for environmental remediation technologies, such as photocatalysis, adsorption, and membrane separation, and as electrocatalytic sensors for pollution recognition because of their high hydrophilicity, inherent chemical nature, and robust electrochemistry. The development of catalysts based on MXene materials for the photocatalytic breakdown of pharmaceutical wastes in polluted water is critically evaluated in this study. With an emphasis on the degradation mechanism, the photocatalytic degradation of antibiotics using MXenes and MXene-based nanocomposites is explained in depth. We emphasize the significant difficulties in producing MXenes and their composites, as well as in the degradation of drugs. The successful use of MXenes in water filtration and suggestions for future study are also presented.

A voiceprint signal as a non-contact test medium has a broad application prospect in power-transformer operation condition monitoring. Due to the high imbalance in the number of fault samples, when training the classification model, the classifier is prone to bias to the fault category with a large number of samples, resulting in poor prediction performance of other fault samples, and affecting the generalization performance of the classification system. To solve this problem, a method of power-transformer fault voiceprint signal diagnosis based on Mixup data enhancement and a convolution neural network (CNN) is proposed. First, the parallel Mel filter is used to reduce the dimension of the fault voiceprint signal to obtain the Mel time spectrum. Then, the Mixup data enhancement algorithm is used to reorganize the generated small number of samples, effectively expanding the number of samples. Finally, CNN is used to classify and identify the transformer fault types. The diagnosis accuracy of this method for a typical unbalanced fault of a power transformer can reach 99%, which is superior to other similar algorithms. The results show that this method can effectively improve the generalization ability of the model and has good classification performance.

Urinary stones and urinary tract infection (UTI) are the most common diseases in urology and they are characterized by high incidence and high recurrence rate in China. Previous studies have shown that urinary stones are closely associated with gut or urine microbiota. Calcium oxalate stones are the most common type of urinary stones. However, the profile of urinary tract microorganisms of calcium oxalate stones with UTI is not clear. In this research, we firstly found two novel clusters in patients with calcium oxalate stones (OA) that were associated with the WBC/HP (white blood cells per high-power field) level in urine. Two clusters in the OA group (OA1 and OA2) were distinguished by the key microbiota Firmicutes and Enterobacteriaceae. We found that Enterobacteriaceae enriched in OA1 cluster was positively correlated with several infection-related pathways and negatively correlated with a few antibiotics-related pathways. Meantime, some probiotics with higher abundance in OA2 cluster such as Bifidobacterium were positively correlated with antibiotics-related pathways, and some common pathogens with higher abundance in OA2 cluster such as Enterococcus were positively correlated with infection-related pathways. Therefore, we speculated that as a sub-type of OA disease, OA1 was caused by Enterobacteriaceae and the lack of probiotics compared with OA2 cluster. Moreover, we also sequenced urine samples of healthy individuals (CK), patients with UTI (I), patients with uric acid stones (UA), and patients with infection stones (IS). We identified the differentially abundant taxa among all groups. We hope the findings will be helpful for clinical treatment and diagnosis of urinary stones.

Neobavaisoflavone is an important isoflavone component isolated from Psoraleae Fructus. It is used extensively worldwide because of its antibacterial, antioxidant, anti-inflammatory, anticancer, and anti-osteoporotic activities. However, there is no systematic and comprehensive research on the metabolism of neobavaisoflavone in vivo and in vitro. The study aimed to analyze the metabolic characteristics and mechanism of neobavaisoflavone for the first time. Firstly, biological samples were pretreated by the solid-phase extraction (SPE) method, methanol precipitation, and acetonitrile precipitation. Secondly, the samples were analyzed on UHPLC-Q-Exactive Plus Orbitrap MS. Thirdly, metabolites were tentatively identified based on retention time, parallel reaction monitoring strategy, diagnostic product ions, and neutral loss fragments. A total of 72 metabolites of neobavaisoflavone were tentatively identified, including 28 in plasma, 43 in urine, 18 in feces, six in the liver, and four in the liver microsome. The results suggested that neobavaisoflavone mainly underwent glucuronidation, sulfation, hydroxylation, methylation, cyclization, hydration, and their composite reactions in vivo and in vitro. In addition, nine active components with high bioavailability and 191 corresponding targets were predicted by the Swiss Drug Design database. The 1806 items of GO and 183 KEGG signaling pathways were enriched. These results showed that metabolites expanded the potential effects of neobavaisoflavone. The present study would provide the scientific basis for the further exploitation and application of neobavaisoflavone.

Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g., due to manufacturers) and changes in scanner performance (e.g., due to gradual component aging, software and/or hardware upgrades, etc.). As part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI) and the Canadian Biomarker Integration Network in Depression (CAN-BIND), QA phantom scans were conducted approximately monthly for three to four years at 13 sites across Canada with 3T research MRI scanners. QA parameters were calculated for each scan using the functional Biomarker Imaging Research Network's (fBIRN) QA phantom and pipeline to capture between- and within-scanner variability. We also describe a QA protocol to measure the full-width-at-half-maximum (FWHM) of slice-wise point spread functions (PSF), used in conjunction with the fBIRN QA parameters. Variations in image resolution measured by the FWHM are a primary source of variance over time for many sites, as well as between sites and between manufacturers. We also identify an unexpected range of instabilities affecting individual slices in a number of scanners, which may amount to a substantial contribution of unexplained signal variance to their data. Finally, we identify a preliminary preprocessing approach to reduce this variance and/or alleviate the slice anomalies, and in a small human data set show that this change in preprocessing can have a significant impact on seed-based connectivity measurements for some individual subjects. We expect that other fMRI centres will find this approach to identifying and controlling scanner instabilities useful in similar studies.

A novel CaCO3/graphitic carbon nitride (g-C3N4) photocatalyst was synthesized for the first time via a facile calcination method using CaCO3 and melamine as precursors. The as-prepared samples were characterized using various techniques, such as scanning and transmission electron microscopy, X-ray diffraction, Brunauer-Emmett-Teller analysis, as well as Fourier-transform infrared, X-ray photoelectron, photoluminescence, and UV–vis diffuse reflectance spectroscopy. The results of the experiments confirm the successful coupling of CaCO3 to g-C3N4. The photocatalytic activity of the synthesized CaCO3/g-C3N4 composites was evaluated by assessing their performance in the photocatalytic degradation of crystal violet (CV) in water under visible light irradiation. The analysis shows that CaCO3/g-C3N4 exhibits higher photocatalytic activity towards CV degradation (76.0%) than pristine g-C3N4 (21.6%) and CaCO3 (23.2%). Radical trapping and electron spin resonance experiments show that hydroxyl radicals (·OH) and holes (h+) are the key reactive species in the photocatalytic process. The enhanced photocatalytic activity of the composite is mainly attributed to the efficient separation rate of electron-hole pairs achieved through the incorporation of CaCO3. Keywords: CaCO3/g-C3N4, Calcination, Photocatalysis, Charge separation

Due to the easily controllable interlayer anions, metal cation composition proportion and thickness, which is beneficial to modify surface chemical state and tune bandgap, layered double hydroxides (LDHs) have great promising potential for photocatalytic applications. In this study, we have successfully synthesized the ZnAl–LDH intercalated the single anion between ZnAl cationic interlayer without anionic impurities by using a facile calcining and reconstructing routes. The electron structure and surface chemical state of the prepared products have been investigated by combining the DFT calculation and experimental characterization methods. UV–vis DRS was used to certify the light absorption of the prepared products, and we performed the DFT calculation to demonstrate the density of state and activation of reactant. These results suggested that the ZnAl–LDH–CO3 possessed the more proper band structure and superior ability to activate NO and O2 for accelerating the photocatalytic NO oxidation activity. Moreover, the in situ DRIFTS with dynamically monitoring intermediates and products over the ZnAl–LDH–CO3 was adopted to declare the photocatalytic NO oxidized process during the photocatalytic reaction process. This work illustrated the influence of different interlayer anions to the electron structure and surface chemical state of ZnAl–LDH structure through the experimental verification combined DFT calculation and the photocatalytic NO oxidized process via in situ DRIFTS analyzing, which would provide a novel way to design and fabricate the efficient photocatalysis, and understand the reaction process. Keywords: Photocatalytic NO oxidation, ZnAl–LDH, Reaction process and mechanism, In situ DRIFTS, DFT calculation

Invasive species are a major and growing threat to China’s native freshwater biodiversity. They have caused species extinctions, biodiversity loss, and environmental changes. Mrigal carp (Cirrhinus mrigala), one of the most widespread and invasive of freshwater fish species, now occurs in major rivers throughout southern China. We report the current (to 2017) distribution of mrigal carp throughout southern China, and experiments with temperature, water quality and food availability, that assess possible impacts of this species on populations of native mud carp (C. molitorella)”. In the wild, the mud carp to mrigal carp weight ratio was 1:1.65. Mrigal carp were a dominant species in some rivers of southern China, such as Liuxi River, Zengjiang River and the Zhaoqing section of Xijiang River. Manipulative experiments reveal mrigal carp to be more tolerant of colder temperature, more eutrophic conditions, and lower dissolved oxygen levels than mud carp. In food-limited experiments, mrigal carp displayed no direct aggression towards mud carp, but they did snatch food from them, and excluded them from eating. Mud carp growth was curtailed in the presence of mrigal carp in food-limited treatments, with a growth rate 2.71%, only 17.02% of that in treatments where carp were fed to satiation. In satiation treatments, mrigal carp also grew up to 2.21 times faster than mud carp. Our results indicate that mrigal carp will outcompete mud carp for resources and habitat, and that both its distribution and population will increase in the future.

Metal–organic frameworks (MOFs), a class of porous nanomaterials, have been widely used in gas adsorption-based applications due to their high porosities and chemical tunability. To facilitate the discovery of high-performance MOFs for different applications, a variety of machine learning models have been developed to predict the gas adsorption capacities of MOFs. Most of the predictive models are developed using traditional machine learning algorithms. However, the continuously increasing sizes of MOF datasets and the complicated relationships between MOFs and their gas adsorption capacities make deep learning a suitable candidate to handle such big data with increased computational power and accuracy. In this study, we developed models for predicting gas adsorption capacities of MOFs using two deep learning algorithms, multilayer perceptron (MLP) and long short-term memory (LSTM) networks, with a hypothetical set of about 130,000 structures of MOFs with methane and carbon dioxide adsorption data at different pressures. The models were evaluated using 10 iterations of 10-fold cross validations and 100 holdout validations. The MLP and LSTM models performed similarly with high prediction accuracy. The models for predicting gas adsorption at a higher pressure outperformed the models for predicting gas adsorption at a lower pressure. The deep learning models are more accurate than the random forest models reported in the literature, especially for predicting gas adsorption capacities at low pressures. Our results demonstrated that deep learning algorithms have a great potential to generate models that can accurately predict the gas adsorption capacities of MOFs.

Studies on herbal medicines and fermentation products have become increasingly essential with the development of modern industry and technology. In order to verify that fermentation can bring about changes, Paecilomyces cicadae [Paecilomyces cicadae (Miquel.) Samson] was used to ferment Astragali radix [Astragalus membranaceus (Fisch.) Bge. var. mongho-licus (Bge.) Hsiao]. After solid fermentation for Astragali radix produced by Paecilomyces cicadae (SF-AP) was established, an efficient strategy based on ultra-high performance liquid chromatography-linear ion trap-Orbitrap mass spectrometry (UHPLC-LTQ-Orbitrap MS) was developed to screen and identify the chemical transformations in SF-AP and Astragali radix according to the acquired diagnostic product ions (DPIs). As a result, 114 compounds including 45 saponins and 69 flavonoids were finally identified and validated. Moreover, two kinds of antioxidative tests corresponding to the scavenging of DPPH· and ABTS·+ were applied to evaluate the antioxidative activity of Astragali radix before and after fermentation. The results demonstrated that some significant chemical transformations such as relative content fluctuations and structural isomerism owing to the occurrence of hydrolysis and conversion reactions and the antioxidative activity of SF-AP was much higher than that of the Astragali radix. This study could provide a new method for the utilization of Astragali radix and constructive guidance for the further research of fermented herbal medicines.