Direct and stable hydrogenation of CO2 to aromatics over a tandem catalyst Zn0.1Ti0.9Ox/HZSM-5.

Direct and stable conversion of CO2 to aromatics (CTA) is an attractive route for reducing CO2 emissions. However, due to the chemical inertness of CO2, direct CTA reaction with high aromatics selectivity is still challenging. In this work, a tandem catalyst Zn0.1Ti0.9Ox/HZSM-5 with appropriate density and strength of acid sites exhibits a high aromatics selectivity of 67.2% and long-term stability over 100 h. Furthermore, the total selectivity of benzene, toluene, and xylene achieves 24.1% over Zn0.1Ti0.9Ox/HZSM-5 with a modified hydrophilic surface. In addition, the CTA via the formate route has been determined in this reaction system.

Spinel Nanostructures for the Hydrogenation of CO2 to Methanol and Hydrocarbon Chemicals.

Composite oxides have been widely applied in the hydrogenation of CO/CO2 to methanol or as the component of bifunctional oxide-zeolite for the synthesis of hydrocarbon chemicals. However, it is still challenging to disentangle the stepwise formation mechanism of CH3OH at working conditions and selectively convert CO2 to hydrocarbon chemicals with narrow distribution. Here, we investigate the reaction network of the hydrogenation of CO2 to methanol over a series of spinel oxides (AB2O4), among which the Zn-based nanostructures offer superior performance in methanol synthesis. Through a series of (quasi) in situ spectroscopic characterizations, we evidence that the dissociation of H2 tends to follow a heterolytic pathway and that hydrogenation ability can be regulated by the combination of Zn with Ga or Al. The coordinatively unsaturated metal sites over ZnAl2Ox and ZnGa2Ox originating from oxygen vacancies (OVs) are evidenced to be responsible for the dissociative adsorption and activation of CO2. The evolution of the reaction intermediates, including both carbonaceous and hydrogen species at high temperatures and pressures over the spinel oxides, has been experimentally elaborated at the atomic level. With the integration of a series of zeolites or zeotypes, high selectivities of hydrocarbon chemicals with narrow distributions can be directly produced from CO2 and H2, offering a promising route for CO2 utilization.

PySOFI: an open source Python package for SOFI.

Super-resolution optical fluctuation imaging (SOFI) is a highly democratizable technique that provides optical super-resolution without requirement of sophisticated imaging instruments. Easy-to-use open-source packages for SOFI are important to support the utilization and community adoption of the SOFI method, they also encourage the participation and further development of SOFI by new investigators. In this work, we developed PySOFI, an open-source Python package for SOFI analysis that offers the flexibility to inspect, test, modify, improve, and extend the algorithm. We provide complete documentation for the package and a collection of Jupyter Notebooks to demonstrate the usage of the package. We discuss the architecture of PySOFI and illustrate how to use each functional module. A demonstration on how to extend the PySOFI package with additional modules is also included in the PySOFI package. We expect PySOFI to facilitate efficient adoption, testing, modification, dissemination, and prototyping of new SOFI-relevant algorithms.

Mapping the structure of depression biomarker research: A bibliometric analysis.

Background: Depression is a common mental disorder and the diagnosis is still based on the descriptions of symptoms. Biomarkers can reveal disease characteristics for diagnosis, prognosis, and treatment. In recent years, many biomarkers relevant to the mechanisms of depression have been identified. This study uses bibliometric methods and visualization tools to analyse the literature on depression biomarkers and its hot topics, and research frontiers to provide references for future research. Methods: Scientific publications related to depression biomarkers published between 2009 and 2022 were obtained from the Web of Science database. The BICOMB software was used to extract high-frequency keywords and to construct binary word-document and co-word matrices. gCLUTO was used for bicluster and visual analyses of high-frequency keywords. Further graphical visualizations were generated using R, CiteSpace and VOSviewer software. Results: A total of 14,403 articles related to depression biomarkers were identified. The United States (34.81%) and China (15.68%), which together account for more than half of all publications, can be considered the research base for the field. Among institutions, the University of California, University of London, and Harvard University are among the top in terms of publication number. Three authors (Maes M, Penninx B.W.J.H., and Berk M) emerged as eminent researchers in the field. Finally, eight research hotspots for depression biomarkers were identified using reference co-citation analysis. Conclusion: This study used bibliometric methods to characterize the body of literature and subject knowledge in the field of depression biomarker research. Among the core biomarkers of depression, functional magnetic resonance imaging (fMRI), cytokines, and oxidative stress are relatively well established; however, research on machine learning, metabolomics, and microRNAs holds potential for future development. We found "microRNAs" and "gut microbiota" to be the most recent burst terms in the study of depression biomarkers and the likely frontiers of future research.

Multi-omics data integration for hepatocellular carcinoma subtyping with multi-kernel learning.

Hepatocellular carcinoma (HCC) is a leading malignant liver tumor with high mortality and morbidity. Patients at the same stage can be defined as different molecular subtypes associated with specific genomic disorders and clinical features. Thus, identifying subtypes is essential to realize efficient treatment and improve survival outcomes of HCC patients. Here, we applied a regularized multiple kernel learning with locality preserving projections method to integrate mRNA, miRNA and DNA methylation data of HCC patients to identify subtypes. We identified two HCC subtypes significantly correlated with the overall survival. The patient 3-years mortality rates in the high-risk and low-risk group was 51.0% and 23.5%, respectively. The high-risk group HCC patients were 3.37 times higher in death risk compared to the low-risk group after adjusting for clinically relevant covariates. A total of 196 differentially expressed mRNAs, 2,151 differentially methylated genes and 58 differentially expressed miRNAs were identified between the two subtypes. Additionally, pathway activity analysis showed that the activities of six pathways between the two subtypes were significantly different. Immune cell infiltration analysis revealed that the abundance of nine immune cells differed significantly between the two subtypes. We further applied the weighted gene co-expression network analysis to identify gene modules that may affect patients prognosis. Among the identified modules, the key module genes significantly associated with prognosis were found to be involved in multiple biological processes and pathways, revealing the mechanism underlying the progression of HCC. Hub gene analysis showed that the expression levels of CDK1, CDCA8, TACC3, and NCAPG were significantly associated with HCC prognosis. Our findings may bring novel insights into the subtypes of HCC and promote the realization of precision medicine.

Metabolomic biomarkers related to non-suicidal self-injury in patients with bipolar disorder.

BACKGROUND: Non-suicidal self-injury (NSSI) is an important symptom of bipolar disorder (BD) and other mental disorders and has attracted the attention of researchers lately. It is of great significance to study the characteristic markers of NSSI. Metabolomics is a relatively new field that can provide complementary insights into data obtained from genomic, transcriptomic, and proteomic analyses of psychiatric disorders. The aim of this study was to identify the metabolic pathways associated with BD with NSSI and assess important diagnostic and predictive indices of NSSI in BD. METHOD: Nuclear magnetic resonance spectrometry was performed to evaluate the serum metabolic profiles of patients with BD with NSSI (n = 31), patients with BD without NSSI (n = 46), and healthy controls (n = 10). Data were analyzed using an Orthogonal Partial Least Square Discriminant Analysis and a t-test. Differential metabolites were identified (VIP > 1 and p < 0.05), and further analyzed using Metabo Analyst 3.0 to identify associated metabolic pathways. RESULTS: Eight metabolites in the serum and two important metabolic pathways, the urea and glutamate metabolism cycles, were found to distinguish patients with BD with NSSI from healthy controls. Eight metabolites in the serum, glycine and serine metabolism pathway, and the glucose-alanine cycle were found to distinguish patients with BD without NSSI from healthy controls. Five metabolites in the serum and the purine metabolism pathway were found to distinguish patients with BD with NSSI from those with BD without NSSI. CONCLUSIONS: Abnormalities in the urea cycle, glutamate metabolism, and purine metabolism played important roles in the pathogenesis of BD with NSSI.

Super-resolution Imaging of Plasmonic Near-Fields: Overcoming Emitter Mislocalizations.

Plasmonic nano-objects have shown great potential in enhancing applications like biological/chemical sensing, light harvesting and energy transfer, and optical/quantum computing. Therefore, an extensive effort has been vested in optimizing plasmonic systems and exploiting their field enhancement properties. Super-resolution imaging with quantum dots (QDs) is a promising method to probe plasmonic near-fields but is hindered by the distortion of the QD radiation pattern. Here, we investigate the interaction between QDs and "L-shaped" gold nanoantennas and demonstrate both theoretically and experimentally that this strong interaction can induce polarization-dependent modifications to the apparent QD emission intensity, polarization, and localization. Based on FDTD simulations and polarization-modulated single-molecule microscopy, we show that the displacement of the emitter's localization is due to the position-dependent interference between the emitter and the induced dipole, and can be up to 100 nm. Our results help pave a pathway for higher precision plasmonic near-field mapping and its underlying applications.

[Distribution and Environmental Significance of Rare Earth Elements in Typical Protected Vegetable Soil, Northern China].

The concentrations of rare earth elements (REEs) in protected vegetable soils in Wuqing district of Tianjin City, Jinzhong district of Shanxi Province, Shenyang district of Liaoning Province, and Wulanchabu district of Inner Mongolia Autonomous Region in northern China were measured to analyze the change characteristics of soil REEs in the process of protected vegetable cultivation. Additionally, we sought to use the REEs parameters to trace the feasibility of characterizing the interference of human activities on the soil ecological environment. The results showed that the total content of REEs (REE) in the topsoil of protected vegetable fields ranged from 146.52 to 158.76 mg·kg-1, with an average of 152.34 mg·kg-1 in Shenyang; 92.16 to 137.69 mg·kg-1, with an average of 115.03 mg·kg-1in Wuqing; 91.38 to 118.84 mg·kg-1, with an average of 108.03 mg·kg-1 in Wulanchabu; and 97.62 to 111.27 mg·kg-1, with an average of 102.43 mg·kg-1in Jinzhong. The REEs distribution patterns in the soils of the four areas, standardized with chondrite, characterized by a right tilt, showed that light rare earth elements were obviously enriched in the soil, demonstrated by the ratios of LREE/HREE and (La/Yb) N, which were greater than 6 and 7, respectively. The values of (La/Sm)N in the soils were higher than 3, suggesting that there was an obvious fractionation between light rare earth elements, whereas the values of (Gd/Yb)N were between 1-2, and there was a weak fractionation between heavy rare earth elements. The values of δEu in the soils were between 0.56 and 0.61, showing that Eu had a negative abnormality. The values of δCe were between 0.89 and 1.11, showing that Ce had no abnormality or weak positive abnormality. The higher LREE/HREE and (La/Yb)N in protected vegetable soil than that in open-air vegetable soil indicated the increasing differentiation degree between light and heavy rare earth elements in protected vegetable soil. The lower (La/Sm)N in protected vegetable soils indicated the reduction in the differentiation among light rare earth elements in soil. Higher δCe values and lower δEu values suggested that Ce and Eu were relatively enriched and depleted, respectively, during vegetable planting. The REE, LREE, (La/Sm)N, and δEu in protective soil decreased with the number of cultivation years, whereas the (Gd/Yb)N and δCe increased, but the HREE values did not change significantly. There was a significant correlation between δCe, δEu, (La/Yb)N, (Gd/Yb)N, and soil bulk density, soil moisture content, and soil organic matter in Tianjin protected vegetable soils, showing preliminarily that rare earth elements can be used as tracer elements to characterize the interference intensity of human activities on soil.

Injectable alginate/hydroxyapatite gel scaffold combined with gelatin microspheres for drug delivery and bone tissue engineering.

Injectable and biodegradable alginate-based composite gel scaffolds doubly integrated with hydroxyapatite (HAp) and gelatin microspheres (GMs) were cross-linked via in situ release of calcium cations. As triggers of calcium cations, CaCO3 and glucono-D-lactone (GDL) were fixed as a mass ratio of 1:1 to control pH value ranging from 6.8 to 7.2 during gelation. Synchronously, tetracycline hydrochloride (TH) was encapsulated into GMs to enhance bioactivity of composite gel scaffolds. The effects of HAp and GMs on characteristics of gel scaffolds, including pH value, gelation time, mechanical properties, swelling ratio, degradation behavior and drug release, were investigated. The results showed that HAp and GMs successfully improved mechanical properties of gel scaffolds at strain from 0.1 to 0.5, which stabilized the gel network and decreased weight loss, as well as swelling ratio and gelation time. TH could be released from this composite gel scaffold into the local microenvironment in a controlled fashion by the organic/inorganic hybrid of hydrogel network. Our results demonstrate that the HAp and GMs doubly integrated alginate-based gel scaffolds, especially the one with 6% (w/v) HAp and 5% (w/v) GMs, have suitable physical performance and bioactive properties, thus provide a potential opportunity to be used for bone tissue engineering. The potential application of this gel scaffold in bone tissue engineering was confirmed by encapsulation behavior of osteoblasts. In combination with TH, the gel scaffold exhibited beneficial effects on osteoblast activity, which suggested a promising future for local treatment of pathologies involving bone loss.

Magnetic hyaluronic acid nanospheres via aqueous Diels-Alder chemistry to deliver dexamethasone for adipose tissue engineering.

Biopolymer-based nanospheres have great potential in the field of drug delivery and tissue regenerative medicine. In this work, we present a flexible way to conjugate a magnetic hyaluronic acid (HA) nanosphere system that are capable of vectoring delivery of adipogenic factor, e.g. dexamethasone, for adipose tissue engineering. Conjugation of nanospheres was established by aqueous Diels-Alder chemistry between furan and maleimide of HA derivatives. Simultaneously, a furan functionalized dexamethasone peptide, GQPGK, was synthesized and covalently immobilized into the nanospheres. The magnetic HA nanospheres were fabricated by encapsulating super-paramagnetic iron oxide nanoparticles, which exhibited quick magnetic sensitivity. The aqueous Diels-Alder chemistry made nanospheres high binding efficiency of dexamethasone, and the vectoring delivery of dexamethasone could be easily controlled by a external magnetic field. The potential application of the magnetic HA nanospheres on vectoring delivery of adipogenic factor was confirmed by co-culture of human adipose-derived stem cells (ASCs). In vitro cytotoxicity tests demonstrated that incorporation of dexamethasone into magnetic HA nanospheres showed high efficiency to promote ASCs viabilities, in particular under a magnetic field, which suggested a promising future for adipose regeneration applications.

Magnetic biopolymer nanogels via biological assembly for vectoring delivery of biopharmaceuticals.

Biopolymer-based nanogels have great potential in the field of tissue regenerative medicine. In this work, a magnetic biopolymer nanogel via specific nucleobase pairing was developed for vectoring delivery of cell growth factors. The biopolymer based nanogels chitosan and heparin were established by the Watson-Crick base pairing between thymine and adenine via the hydrogen bonding. The magnetic biopolymer nanogels exhibit quick magnetic responsibility, which were fabricated by encapsulating super-paramagnetic iron oxide nanoparticles. The potential applications of this magnetic nanogel on vectoring delivery of cell growth factors were confirmed by adsorption and release behaviors of bone morphogenetic protein 2 (BMP-2). The existence of heparin made the nanogel achieve a high loading efficiency of BMP-2, and the vectoring delivery of BMP-2 could be easily controlled by the external magnetic field. In vitro cytotoxicity tests demonstrated that incorporation of BMP-2 into this biopolymer nanogel through binding with heparin showed high efficiency to promote MG-63 cells' viabilities, in particular under a magnetic field, which suggested a promising future for cartilage and bone regeneration applications.