Porphyrin-Based Conjugated Microporous Polymer Loaded with Nanoscale Zerovalent Iron for the Degradation of Organic Pollutants under Visible Light.

The degradation of organic dye from waterbodies is of great significance for clean production and environmental remediation. Herein, two porphyrin-based conjugated microporous polymers (CMPs) loaded with nanoscale zerovalent iron (named as Por-CMPs-1-2@nZVI) were successfully fabricated by Sonogashira-Hagihara coupling reactions and the liquid-phase method. The as-synthesized Por-CMPs-1-2@nZVI composites were characterized by various means of analysis, and it was confirmed that Por-CMPs-1-2 loaded with nZVI had good photocatalytic performance. Calculated by ultraviolet-visible spectrum, the band-gap energies of Por-CMPs-1@nZVI and Por-CMPs-2@nZVI were 1.45 and 1.32 eV, respectively, indicating that both can be activated by visible light. The photodegradation of organic dye experiments demonstrated that Por-CMPs-2@nZVI degraded 98.0% of 10 ppm Methylene Blue (MB) within 150 min, which is higher than that of Por-CMPs-1-2 and Por-CMPs-1@nZVI. The experiment of active substance capture and mechanism of ESR confirmed that superoxide anion and hydroxyl radical were the primary valid substances in the photodegradation process of MB. In addition, the preparation of membrane materials was shown to be a successful strategy to realize engineered scale-up production.

Porphyrin-Based Conjugated Microporous Polymers for Highly Efficient Adsorption of Metal Ions.

The capture and elimination of anions and cations from water have attracted a great deal of attention and are quite vital for clean production and environmental remediation. In this work, we present the synthesis of four porphyrin (Por)-based conjugated microporous polymers (CMPs, namely, Por-CMP-1-4), which were produced through a Sonogashira-Hagihara linked response using porphyrin and acetylene aromatic compounds as building blocks and used as absorbents to eliminate metal ions from water. The as-synthesized Por-CMP-1-4 exhibit an amorphous porous structure and outstanding caloric and physicochemical properties. Taking advantage of their larger specific surface areas, i.e., 541.47, 614.58, 382.38, and 677.90 m2 g-1 for Por-CMP-1-4, respectively, and their chelating active site that originated from the porphyrin ring, Por-CMP-1-4 show better Zn2+, Cu2+, and Pb2+ adsorption ability. Among them, Por-CMP-3 has the greatest adsorbability of 640 mg g-1 for Zn2+, with an adsorption efficiency of 80%, whereas its adsorption capacities for Cu2+ and Pb2+ ions were both 334 mg g-1, with an adsorption efficiency of 42% for Cu2+ and Pb2+. Employing Por-CMP-3 as a representative example, its adsorption kinetics has been systematically investigated. The adsorption behavior of Por-CMP-3 with respect to the Zn2+ ion is shown to exhibit pseudo-first-order kinetics and Langmuir isotherm modes. Meanwhile, the adsorption mechanism is discussed in detail, and it was thought it might be chelation, in which the nitrogen atoms with a single pair of electrons on the porphyrin ring interacted with metal ions to form stable chelation coordination bonds, thus removing metal ions selectively and effectively. Furthermore, Por-CMP-3 exhibited good reusability, retaining 60% of its Zn2+ removal rate after four continuous adsorptions.

Genetic variants in choline metabolism pathway are associated with the risk of bladder cancer in the Chinese population.

Choline metabolism alteration is considered as a metabolic hallmark in cancer, reflecting the complex interactions between carcinogenic signaling pathways and cancer metabolism, but little is known about whether genetic variants in the metabolism pathway contribute to the susceptibility of bladder cancer. Herein, a case-control study comprising 580 patients and 1,101 controls was carried out to analyze the association of bladder cancer with genetic variants on candidate genes involved in the choline metabolism pathway using unconditional logistic regression. Gene expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were applied for differential gene expression analysis. Cox regression was also applied to estimate the role of candidate genes on bladder cancer prognosis. Our results demonstrated that C allele of rs6810830 in ENPP6 was a significant protective allele of bladder cancer, compared to the T allele [Odds ratio (OR) = 0.74, 95% confidence interval (CI) = 0.64-0.86, P = 7.14 × 10-5 in additive model]. Besides, we also found that the expression of ENPP6 remarkably decreased in bladder tumors compared with normal tissues. Moreover, high expression of ENPP6 was associated with worse overall survival (OS) in bladder cancer patients [hazard ratio (HR) with their 95% CI 1.39 (1.02-1.90), P = 0.039]. In conclusion, our results suggested that SNP rs6810830 (T > C) in ENPP6 might be a potential susceptibility loci for bladder cancer, and these findings provided novel insights into the underlying mechanism of choline metabolism in cancers.

Evaluation of genetic variants in nucleosome remodeling and deacetylase (NuRD) complex subunits encoding genes and gastric cancer susceptibility.

Epigenetic complex NuRD (nucleosome remodeling and deacetylase) engages in a range of basic cellular processes, including chromatin modification. Changes in the activity of NuRD complex can influence gastric cancer progression. Multivariate logistic regression analyses were used to estimate the association between single-nucleotide polymorphisms (SNPs) and gastric cancer risk. Expression quantitative trait loci (eQTL) analysis was used to analyze the relationship between the genotypes and gene expression levels using data from the genotype tissue expression project (GTEx). Gene expression was calculated using databases from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO). Kaplan-Meier plotter was used to evaluate the association between gene expression and survival. SNP rs11064275 T allele in CHD4, rs892022 A allele and rs2033481 A allele in GATAD2A were found to contribute to the decreased risk of gastric cancer. The increase in the number of favorable alleles of these three SNPs was associated with a lower risk of gastric cancer. rs2033481 and rs892022 were substantially correlated with GATAD2A mRNA expression levels. Meanwhile, we detected that the CHD4 and GATAD2A mRNA expression was increased in gastric cancer tissues compared with the adjacent normal tissues. Furthermore, we found that patients with higher CHD4 or GATAD2A mRNA expression level had more advantageous overall survival. Our findings indicated that genetic variants in NuRD complex subunits encoding genes may be promising predictors of gastric cancer risk.

Dual-Functional Graphene Oxide-Based Photothermal Materials with Aligned Channels and Oleophobicity for Efficient Solar Steam Generation.

Desalination by solar steam generation (SSG) has emerged as one of the most efficient approaches to address the issue of global water shortage. In this work, novel graphene oxide (GO)-based solar steam generators (GO-SSGs) with aligned channels were prepared by directional freezing and simple carbonization of a hydrogel composed of GO and poly(vinyl alcohol) (PVA). Benefitting from their excellent light absorption (light absorption efficiency exceeds 94%), better thermal insulation (thermal conductivity, 0.259 W/(m K)), and suitable porous structure, which facilitates rapid water transportation, the GO-SSGs show superior SSG performance with a high solar energy conversion efficiency of up to 92% achieved under an irradiation of 1.0 kW/m2. Interestingly, uniquely aligned channels endow them with good salt-rejection performance; the solar energy conversion efficiency of GO-SSGs in 20 wt % NaCl, KCl, and MgCl2 brine can reach more than 85%. To improve their antifouling performance, a chemically hydrophilic and oleophobic modification was conducted, making it possible to run SSG even in oily wastewater; for instance, a solar energy conversion efficiency of 84% was obtained in an aqueous solution containing 10 wt % n-hexadecane. Compared with the existing photothermal materials, these materials show advantages of simple manufacture, high SSG efficiency, superior salt tolerance, and antifouling performance, which make them promising candidates as a kind of new high-performance photothermal materials for desalination even in oily wastewater, thus further expanding the scope of their practical SSG application.

Collective relational inference for learning heterogeneous interactions.

Interacting systems are ubiquitous in nature and engineering, ranging from particle dynamics in physics to functionally connected brain regions. Revealing interaction laws is of fundamental importance but also particularly challenging due to underlying configurational complexities. These challenges become exacerbated for heterogeneous systems that are prevalent in reality, where multiple interaction types coexist simultaneously and relational inference is required. Here, we propose a probabilistic method for relational inference, which possesses two distinctive characteristics compared to existing methods. First, it infers the interaction types of different edges collectively by explicitly encoding the correlation among incoming interactions with a joint distribution, and second, it allows handling systems with variable topological structure over time. We evaluate the proposed methodology across several benchmark datasets and demonstrate that it outperforms existing methods in accurately inferring interaction types. The developed methodology constitutes a key element for understanding interacting systems and may find application in graph structure learning.

Mediating effect of telomere length in a hypertension population exposed to cadmium: a case-control study.

Cadmium (Cd) is associated with telomere length and hypertension, respectively, but the mechanism behind its relationship is unclear. Our study aimed to clarify the role of telomere length in the relationship between Cd and hypertension. A 1:1 matched case-control study was conducted with 213 hypertensive patients and 213 normotensive controls in Taiyuan, Shanxi Province, China, from February and June 2016. General demographic characteristics information and lifestyle were collected using a structured questionnaire. Urine samples were collected to test urinary Cd (UCd) levels and corrected by urinary creatinine (UCr) levels. Peripheral leukocyte absolute telomere length (ATL) was measured using quantitative polymerase chain reaction. Logistic regression was used to screen the influencing factors of hypertension. A mediation effect analysis was used to explore the role of telomere length between Cd exposure and the risk of hypertension. We found that the hypertension group had a significantly higher UCd level compared to the control group (0.91 vs 0.80 µg/g Cr, P < 0.01), while ATL showed the opposite relationship (2.36 vs 2.65 kb, P < 0.01). The Regression analysis of hypertension identified these significant predictors: family history of hypertension (OR = 3.129, 95% confidence interval (95% CI): 1.767-5.540), Body mass index (BMI, OR = 1.088, 95% CI: 1.023-1.157), total cholesterol (TC, OR = 1.277, 95% CI: 1.024-1.592), UCd (OR = 2.092, 95% CI: 1.179-3.710), ATL (OR = 0.105, 95% CI: 0.025-0.453) and 8-hydroxy-2-deoxyguanosine (8-OHdG, OR = 7.864, 95% CI: 3.516-17.589). Mediating effect analysis revealed that ATL was a potential partial mediating factor between Cd and hypertension. Cd may induce hypertension by affecting telomere length, but this requires further exploration.

B7-H3 chimeric antigen receptor-modified T cell shows potential for targeted treatment of acute myeloid leukaemia.

BACKGROUND AND AIMS: Chimeric antigen receptor (CAR)-T cell therapy is a novel type of immunotherapy. However, the use of CAR-T cells to treat acute myeloid leukaemia (AML) has limitations. B7-H3 is expressed in several malignancies, including some types of AML cells. However, its expression in normal tissues is low. Therefore, B7-H3 is ideal for targeted AML therapy. MATERIALS AND METHODS: First, we constructed B7-H3 CAR that can target B7-H3, and then constructed B7-H3-CAR-T cells in vitro, which were co-incubated with six AML cell lines expressing different levels of B7-H3, respectively. The toxicity and cytokines were detected by flow cytometry. In vivo, AML model was established in B-NSG mice to study the toxicity of B7-H3-CAR T on AML cells. RESULTS: In vitro functional tests showed that B7-H3-CAR-T cells were cytotoxic to B7-H3-positive AML tumor cells and had good scavenging effect on B7-H3-expressing AML cell lines, and the cytokine results were consistent. In vivo, B7-H3-CAR-T cells significantly inhibited tumor cell growth in a mouse model of AML, prolonging mouse survival compared with controls. CONCLUSION: B7-H3-CAR-T cells may serve as a novel therapeutic method for the targeted treatment of AML.

Anti-cervical cancer mechanism of bioactive compounds from Alangium platanifolium based on the 'compound-target-disease' network.

In this study, we analyzed the chemical compositions of Alangium platanifolium (Sieb. et Zucc.) Harms (AP) using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) non-targeted plant metabolomics integration MolNetEnhancer strategy. A total of 75 compounds, including flavonoids, alkaloids, terpenes, C21 steroids, among others, were identified by comparing accurate mass-to-charge ratios, MS2 cleavage fragments, retention times, and MolNetenhancer-integrated analytical data, and the cleavage rules of the characteristic compounds were analyzed. A total of 125 potential cervical cancer (CC) therapeutic targets were obtained through Gene Expression Omnibus (GEO) data mining, differential analysis, and database screening. Hub targets were obtained by constructing protein-protein interaction (PPI) networks and CytoNCA topology analysis, including SRC, STAT3, TP53, PIK3R1, MAPK3, and PIK3CA. According to Gene ontology (GO) analysis, AP was primarily against CC by influencing gland development, oxidative stress processes, serine/threonine kinase, and tyrosine kinase activity. Enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that the PI3K/AKT and MAPK signaling pathways play a crucial role in AP treatment for CC. The compound-target-pathway (C-T-P) network revealed that quercetin, methylprednisolone, and caudatin may play key roles in the treatment of CC. The results of molecular docking revealed that the core compound could bind significantly to the core target. In this study, the compounds in AP were systematically analyzed qualitatively, and the core components, core targets, and mechanisms of action of AP in the treatment of CC were screened through a combination of network pharmacology tools. Providing a scientific reference for the therapeutic material basis and quality control of AP.

Learning physics-consistent particle interactions.

Interacting particle systems play a key role in science and engineering. Access to the governing particle interaction law is fundamental for a complete understanding of such systems. However, the inherent system complexity keeps the particle interaction hidden in many cases. Machine learning methods have the potential to learn the behavior of interacting particle systems by combining experiments with data analysis methods. However, most existing algorithms focus on learning the kinetics at the particle level. Learning pairwise interaction, e.g., pairwise force or pairwise potential energy, remains an open challenge. Here, we propose an algorithm that adapts the Graph Networks framework, which contains an edge part to learn the pairwise interaction and a node part to model the dynamics at particle level. Different from existing approaches that use neural networks in both parts, we design a deterministic operator in the node part that allows to precisely infer the pairwise interactions that are consistent with underlying physical laws by only being trained to predict the particle acceleration. We test the proposed methodology on multiple datasets and demonstrate that it achieves superior performance in inferring correctly the pairwise interactions while also being consistent with the underlying physics on all the datasets. While the previously proposed approaches are able to be applied as simulators, they fail to infer physically consistent particle interactions that satisfy Newton's laws. Moreover, the proposed physics-induced graph network for particle interaction also outperforms the other baseline models in terms of generalization ability to larger systems and robustness to significant levels of noise. The developed methodology can support a better understanding and discovery of the underlying particle interaction laws, and hence, guide the design of materials with targeted properties.

E2ENNet: An end-to-end neural network for emotional brain-computer interface.

Objectve: Emotional brain-computer interface can recognize or regulate human emotions for workload detection and auxiliary diagnosis of mental illness. However, the existing EEG emotion recognition is carried out step by step in feature engineering and classification, resulting in high engineering complexity and limiting practical applications in traditional EEG emotion recognition tasks. We propose an end-to-end neural network, i.e., E2ENNet. Methods: Baseline removal and sliding window slice used for preprocessing of the raw EEG signal, convolution blocks extracted features, LSTM network obtained the correlations of features, and the softmax function classified emotions. Results: Extensive experiments in subject-dependent experimental protocol are conducted to evaluate the performance of the proposed E2ENNet, achieves state-of-the-art accuracy on three public datasets, i.e., 96.28% of 2-category experiment on DEAP dataset, 98.1% of 2-category experiment on DREAMER dataset, and 41.73% of 7-category experiment on MPED dataset. Conclusion: Experimental results show that E2ENNet can directly extract more discriminative features from raw EEG signals. Significance: This study provides a methodology for implementing a plug-and-play emotional brain-computer interface system.

Fine particulate matter induces METTL3-mediated m6A modification of BIRC5 mRNA in bladder cancer.

Long-term exposure to fine particulate matter (PM2.5) is reportedly related to a variety of cancers including bladder cancer. However, little is known about the biological mechanism underlying this association. In the present study, PM2.5 exposure was significantly associated with increased levels of m6A modification in bladder cancer patients and bladder cells. METTL3 expression was aberrantly upregulated after PM2.5 exposure, and METTL3 was involved in PM2.5-induced m6A methylation. Higher METTL3 expression was observed in bladder cancer tissues and METTL3 knockdown dramatically inhibited bladder cancer cell proliferation, colony formation, migration and invasion, inducing apoptosis and disrupting the cell cycle. Mechanistically, PM2.5 enhanced the expression of METTL3 by inducing the promoter hypomethylation of its promoter and increasing the binding affinity of the transcription factor HIF1A. BIRC5 was identified as the target of METTL3 through m6A sequencing (m6A-Seq) and KEGG analysis. The methylated BIRC5 transcript was subsequently recognized by IGF2BP3, which increased its mRNA stability. In particular, PM2.5 exposure promoted the m6A modification of BIRC5 and its recognition by IGF2BP3. In addition, BIRC5 was involved in bladder cancer proliferation and metastasis, as well as VEGFA-regulated angiogenesis. This comprehensive study revealed that PM2.5 exposure exerts epigenetic regulatory effects on bladder cancer via the HIF1A/METTL3/IGF2BP3/BIRC5/VEGFA network.

MUC1-Tn-targeting chimeric antigen receptor-modified Vγ9Vδ2 T cells with enhanced antigen-specific anti-tumor activity.

Chimeric antigen receptor (CAR) αß T cell adoptive immunotherapy has shown great promise for improving cancer treatment. However, there are several hurdles to overcome for the wide clinical application of CAR-αß T cells therapy, including side effects and a limited T cells source from cancer patients. Therefore, we sought to identify an alternative T cell subset that could avoid these limitations and improve the effectiveness of CAR-T immunotherapy. γδ T cells are a minor subset of T cells, which share the characteristic of innate immune cells and adaptive immune cells. Vγ9Vδ2 T cells are a predominant γδ T subset in the circulating peripheral blood. In this study, we investigated the antigen-specific antitumor activity of CAR-Vγ9Vδ2 T cells targeting MUC1-Tn antigen. Vγ9Vδ2 T cells were expanded from peripheral blood mononuclear cells of healthy volunteers with zoledronic acid and interleukin-2. CAR-Vγ9Vδ2 T cells were generated by transfection of lentivirus encoding MUC1-Tn CAR. Cytotoxicity assays with various cancer cell lines revealed that CAR-Vγ9Vδ2 T cells could effectively lyse tumor cells in an antigen-specific manner, with similar or stronger effects than CAR-αß T cells. However, CAR-Vγ9Vδ2 T cells had shorter persistence, which could be improved with the addition of IL-2 to maintain the function of CAR-Vγ9Vδ2 T cells with consecutive stimulation of tumor cells. Using a xenograft mouse model, we further showed that CAR-Vγ9Vδ2 T cells more effectively suppressed tumor growth in vivo than Vγ9Vδ2 T cells. Therefore, MUC1-Tn CAR-modified Vγ9Vδ2 T cells may represent a novel, promising ready-to-use product for cancer allogeneic immunotherapy.

Investigation of the Enhancement Interactions between Double Parallel Cracks on Fatigue Growth Behaviors.

In this paper, interactions of double parallel cracks were studied by performing experiments and numerical simulations. Fatigue crack propagation tests were carried out to measure crack growth rates in the specimens with double parallel cracks or a single crack. Finite element method was adopted to calculate stress intensity factors at the crack tips. Results show that the double parallel cracks at different positions present a shielding effect or enhancement effect on crack growth rates and stress intensity factors. When the double parallel cracks are offset, crack interactions mostly behave as enhancement effects. Empirical formulas were obtained to calculate the stress intensity factor at the "dangerous" crack tip of the double parallel cracks. By modifying the material parameters in Paris equation of the single crack, the double parallel cracks are simplified into a single crack with the same crack growth rates.

Determination of the Enhancement or Shielding Interaction between Two Parallel Cracks under Fatigue Loading.

In this paper, the interactions between two parallel cracks are investigated experimentally and numerically. Finite element models have been established to obtain the stress intensity factors and stress distributions of the parallel cracks with different positions and sizes. Fatigue crack growth tests of 304 stainless steel specimens with the single crack and two parallel cracks have been conducted to confirm the numerical results. The numerical analysis results indicate that the interactions between the two parallel cracks have an enhancement or shielding effect on the stress intensity factors, depending on the relative positions of the cracks. The criterion diagram to determine the enhancement or shielding effect between two parallel cracks is obtained. The changes of the stress fields around the cracks have been studied to explain the mechanism of crack interactions.

Fatigue Crack Growth Behavior of the MIG Welded Joint of 06Cr19Ni10 Stainless Steel.

In this paper, the fatigue crack growth behavior of the base metal (BM), the weld metal (WM) and the heat-affected zone (HAZ) in the metal-inert gas (MIG) welded joints of the 06Cr19Ni10 stainless steel are analyzed and studied. Results of the fatigue crack propagation tests show that a new fatigue crack initiates at the crack tip of a pre-existing crack, then propagates perpendicular to the direction of cyclic fatigue loads. This observation indicates that the original mixed-mode crack transforms into the mode I crack. The WM specimen has the largest fatigue crack growth rate, followed by the HAZ specimen and the BM specimen. To illustrate the differences in fatigue crack growth behavior of the three different types of specimens, metallographic structure, fracture morphology and residual stresses of the BM, HAZ and WM are investigated and discussed. The metallographic observations indicate that the mean grain size of the HAZ is relatively larger than that of the BM. The fractographic analysis shows that the WM has the largest fatigue striation width, followed by the HAZ and the BM. It is also found that the depth of dimple in the WM is relatively shallower than the one in the HAZ and BM, implying the poor plasticity behavior of the material. Analysis results of the residual stress analysis demonstrate a high level of tensile residual stress appearance in the WM and HAZ.

A Two-Photon Fluorescent Probe for Lysosomal Thiols in Live Cells and Tissues.

Lysosome-specific fluorescent probes are exclusive to elucidate the functions of lysosomal thiols. Moreover, two-photon microscopy offers advantages of less phototoxicity, better three dimensional spatial localization, deeper penetration depth and lower self-absorption. However, such fluorescent probes for thiols are still rare. In this work, an efficient two-photon fluorophore 1,8-naphthalimide-based probe conjugating a 2,4-dinitrobenzenesulfonyl chloride and morpholine was designed and synthesized, which exhibited high selectivity and sensitivity towards lysosomal thiols by turn-on fluorescence method quantitatively and was successfully applied to the imaging of thiols in live cells and tissues by two-photon microscopy.