Molecular Tuning of Reactivity of Zeolite Protons in HZSM-5.

In acidic HZSM-5 zeolite, the reactivity of a methanol molecule interacting with the zeolite proton is amenable to modification via coadsorbing a stochiometric amount of an electron density donor E to form the [(E)(CH3OH)(HZ)] complex. The rate of the methanol in this complex undergoing dehydration to dimethyl ether was determined for a series of E with proton affinity (PA) ranging from 659 kJ mol-1 for C6F6 to 825 kJ mol-1 for C4H8O and was found to follow the expression: Ln(Rate) - Ln(RateN2) = ß(PA - PAN2)γ, where E = N2 is the reference and ß and γ are constants. This trend is probably due to the increased stability of the solvated proton in the [(E)(CH3OH)(HZ)] complex with increasing PA. Importantly, this is also observed in steady-state flow reactions when stoichiometric quantities of E are preadsorbed on the zeolite. As demonstrated with E being D2O, the effect on methanol reactivity diminishes when E is present in excess of the [(E)(CH3OH)(HZ)] complex. It is proposed that the methanol dehydration reaction involves [(E)(CH3OH)(CH3OH)(HZ)] as the transition state, which is supported by the isotopologue distribution of the initial dimethyl ether formed when a flow of CH3OH was passed over ZSM-5 containing one CD3OH per zeolite proton. The implication of this on the mechanism of catalytic methanol dehydration on HZSM-5 is discussed.

Facile synthesis of amino-modified magnetic covalent organic framework for the efficient extraction and determination of anionic azo dyes in carbonated beverages.

In this work, a novel magnetic covalent organic framework (COF (TpPa-NH2) @ Fe3O4) was prepared via two step by simple solvent method for the extraction of anionic azo dye residues in food. The as-prepared COF (TpPa-NH2) @ Fe3O4 nanocomposite was characterised by scanning electron microscope, transmission electron microscope, Fourier transform-infrared spectroscopy, X-ray diffraction and vibrating sample magnetometer. Before high-performance liquid chromatography with ultraviolet detection (HPLC-UV) determination, it was used as magnetic adsorbent for magnetic solid-phase extraction (MSPE) to extract and pre-concentrate three anionic azo dyes in carbonated beverage samples. The several key extraction and desorption parameters affecting the extraction recovery rate were investigated, including extraction time, pH of the solution, amount of material, adsorption time, elution solvent, pH of elution solvent, type of elution solvent, elution volume and elution time. Under optimised conditions, this method has good linearity between 5 and 500 µg L-1 (correlation coefficient > 0.9986). The limit of detection was 2.3-3.4 µg L-1. The recoveries of the samples were between 87.5 and 96.9%, and the relative standard deviation lower than 4.6%. The developed method has broad application prospects for the analysis of anionic azo dyes in carbonated beverages.

The Prevalence of Hyperuricemia and the Association Between Hyperuricemia and Age in Patients with Psychiatric Disorders to a General Hospital: A Cross-Section Study.

Purpose: In clinical work, it has been found that the prevalence of hyperuricemia (HUA) is significantly higher in younger patients with psychiatric disorders, but there are few studies in this area. The present study aims to evaluate the prevalence of HUA and the relationship between the HUA and age in hospitalized patients with psychiatric disorders in the real world, and to provide a theoretical basis for clinical staff to pay attention to the metabolic indicators of younger patients and for future related studies. Methods: This is a cross-sectional evaluation of a cohort of 1761 patients with psychiatric disorders of hospitalized. The categories of disorders designed for study included: Depression, Bipolar disorder, Schizophrenia, Anxiety, Obsessive-Compulsive disorder, Acute and transient psychotic disorder, Dissociative(conversion) disorders, Conduct disorders and Tic disorders. In addition, based on age, the participants are stratified into three groups. The authors used Kruskal-Wallis tests, chi-square tests, and multiple linear logistic regression to verify the relationship between HUA and age among hospitalized patients with psychiatric disorders. Results: Overall, the estimated prevalence of HUA was 35.4%. The prevalence of HUA was significantly higher in individuals with 17 years and under compared to those with 45 years and above (P < 0.001). After adjusting for confounders, the prevalence of HUA remained higher at 17 years and under than at 45 years and above. Bipolar disorder can lead to an increased prevalence of HUA (P<0.05). Conclusion: The prevalence of HUA was higher in hospitalized patients with psychiatric disorders, and the prevalence was inversely proportional to age.

ß-Lapachone, an NQO1 bioactivatable drug, prevents lung tumorigenesis in mice.

Lung cancer is one of the most lethal cancers with high incidence worldwide. The prevention of lung cancer is of great significance to reducing the social harm caused by this disease. An in-depth understanding of the molecular changes underlying precancerous lesions is essential for the targeted chemoprevention against lung cancer. Here, we discovered an increased NQO1 level over time within pulmonary premalignant lesions in both the KrasG12D-driven and nicotine-derived nitrosamine ketone (NNK)-induced mouse models of lung cancer, as well as in KrasG12D-driven and NNK-induced malignant transformed human bronchial epithelial cells (BEAS-2B and 16HBE). This suggests a potential correlation between the NQO1 expression and lung carcinogenesis. Based on this finding, we utilized ß-Lapachone (ß-Lap), an NQO1 bioactivatable drug, to suppress lung tumorigenesis. In this study, the efficacy and safety of low-dose ß-Lap were demonstrated in preventing lung tumorigenesis in vivo. In conclusion, our study suggests that long-term consumption of low-dose ß-Lap could potentially be an effective therapeutic strategy for the prevention of lung premalignant lesions. However, further studies and clinical trials are necessary to validate our findings, determine the safety of long-term ß-Lap usage in human, and promote the use of ß-Lap in high-risk populations.

In Situ Defect Engineering in Carbon by Atomic Self-Activation to Boost the Accessible Low-Voltage Insertion for Advanced Potassium-Ion Full-Cells.

Enhancing the low-potential capacity of anode materials is significant in boosting the operating voltage of full-cells and constructing high energy-density energy storage devices. Graphitic carbons exhibit outstanding low-potential potassium storage performance, but show a low K+ diffusion kinetics. Herein, in situ defect engineering in graphitic nanocarbon is achieved by an atomic self-activation strategy to boost the accessible low-voltage insertion. Graphitic carbon layers grow on nanoscale-nickel to form the graphitic nanosphere with short-range ordered microcrystalline due to nickel graphitization catalyst. Meanwhile, the widely distributed K+ in the precursor induces the activation of surrounding carbon atoms to in situ generate carbon vacancies as channels. The graphite microcrystals with defect channels realize reversible K+ intercalation at low-potential and accessible ion diffusion kinetics, contributing to high reversible capacity (209 mAh g-1 at 0.05 A g-1 under 0.8 V) and rate capacity (103.2 mAh g-1 at 1 A g-1). The full-cell with Prussian blue cathode and graphitic nanocarbon anode maintains an obvious working platform at ca. 3.0 V. This work provides a strategy for the in situ design of carbon anode materials and gives insights into the potassium storage mechanism at low-potential for high-performance full-cells.

Virtual formalin-fixed and paraffin-embedded staining of fresh brain tissue via stimulated Raman CycleGAN model.

Intraoperative histology is essential for surgical guidance and decision-making. However, frozen-sectioned hematoxylin and eosin (H&E) staining suffers from degraded accuracy, whereas the gold-standard formalin-fixed and paraffin-embedded (FFPE) H&E is too lengthy for intraoperative use. Stimulated Raman scattering (SRS) microscopy has shown rapid histology of brain tissue with lipid/protein contrast but is challenging to yield images identical to nucleic acid-/protein-based FFPE stains interpretable to pathologists. Here, we report the development of a semi-supervised stimulated Raman CycleGAN model to convert fresh-tissue SRS images to H&E stains using unpaired training data. Within 3 minutes, stimulated Raman virtual histology (SRVH) results that matched perfectly with true H&E could be generated. A blind validation indicated that board-certified neuropathologists are able to differentiate histologic subtypes of human glioma on SRVH but hardly on conventional SRS images. SRVH may provide intraoperative diagnosis superior to frozen H&E in both speed and accuracy, extendable to other types of solid tumors.

Plasma metabolites and risk of seven cancers: a two-sample Mendelian randomization study among European descendants.

BACKGROUND: While circulating metabolites have been increasingly linked to cancer risk, the causality underlying these associations remains largely uninterrogated. METHODS: We conducted a comprehensive 2-sample Mendelian randomization (MR) study to evaluate the potential causal relationship between 913 plasma metabolites and the risk of seven cancers among European-ancestry individuals. Data on variant-metabolite associations were obtained from a genome-wide association study (GWAS) of plasma metabolites among 14,296 subjects. Data on variant-cancer associations were gathered from large-scale GWAS consortia for breast (N = 266,081), colorectal (N = 185,616), lung (N = 85,716), ovarian (N = 63,347), prostate (N = 140,306), renal cell (N = 31,190), and testicular germ cell (N = 28,135) cancers. MR analyses were performed with the inverse variance-weighted (IVW) method as the primary strategy to identify significant associations at Bonferroni-corrected P < 0.05 for each cancer type separately. Significant associations were subjected to additional scrutiny via weighted median MR, Egger regression, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and reverse MR analyses. Replication analyses were performed using an independent dataset from a plasma metabolite GWAS including 8,129 participants of European ancestry. RESULTS: We identified 94 significant associations, suggesting putative causal associations between 66 distinct plasma metabolites and the risk of seven cancers. Remarkably, 68.2% (45) of these metabolites were each associated with the risk of a specific cancer. Among the 66 metabolites, O-methylcatechol sulfate and 4-vinylphenol sulfate demonstrated the most pronounced positive and negative associations with cancer risk, respectively. Genetically proxied plasma levels of these two metabolites were significantly associated with the risk of lung cancer and renal cell cancer, with an odds ratio and 95% confidence interval of 2.81 (2.33-3.37) and 0.49 (0.40-0.61), respectively. None of these 94 associations was biased by weak instruments, horizontal pleiotropy, or reverse causation. Further, 64 of these 94 were eligible for replication analyses, and 54 (84.4%) showed P < 0.05 with association patterns consistent with those shown in primary analyses. CONCLUSIONS: Our study unveils plausible causal relationships between 66 plasma metabolites and cancer risk, expanding our understanding of the role of circulating metabolites in cancer genetics and etiology. These findings hold promise for enhancing cancer risk assessment and prevention strategies, meriting further exploration.

Dynamic m6 A profiles reveal the role of YTHDC2-TLR2 signaling axis in Talaromyces marneffei infection.

Talaromyces marneffei (TM) immune evasion is an important factor leading to the high mortality rate of Penicilliosis marneffei. N6 -methyladenosine (m6 A) plays important roles in host immune response to various pathogen infections, yet its role in TM and HIV/TM coinfection remains largely unexplored. Here we reported genome-wide transcriptional m6 A profiles of TM mono-infection and HIV/TM coinfection. Our finding revealed dynamic alterations in global m6 A levels and upregulation of the m6 A reader YTH N6 -methyladenosine RNA binding protein C2 (YTHDC2) in TM-infected macrophages. Knockdown of YTHDC2 in TM-infected cells showed an elevated expression of TLR2 through m6 A-dependence, along with upregulation of TNF-α and IL1-ß. Overall, we characterized the m6 A profiles of the host and fungus before and after TM infection, and demonstrated that YTHDC2 mediates the key m6 A site of TLR2 to exert its function. These findings provide new insights into the underlying mechanisms and novel therapeutic approaches for TM diseases.

Safety, immunogenicity and protective effectiveness of heterologous boost with a recombinant COVID-19 vaccine (Sf9 cells) in adult recipients of inactivated vaccines.

Vaccines have proven effective in protecting populations against COVID-19, including the recombinant COVID-19 vaccine (Sf9 cells), the first approved recombinant protein vaccine in China. In this positive-controlled trial with 85 adult participants (Sf9 cells group: n = 44; CoronaVac group: n = 41), we evaluated the safety, immunogenicity, and protective effectiveness of a heterologous boost with the Sf9 cells vaccine in adults who had been vaccinated with the inactivated vaccine, and found a post-booster adverse events rate of 20.45% in the Sf9 cells group and 31.71% in the CoronaVac group (p = 0.279), within 28 days after booster injection. Neither group reported any severe adverse events. Following the Sf9 cells vaccine booster, the geometric mean titer (GMT) of binding antibodies to the receptor-binding domain of prototype SARS-CoV-2 on day 28 post-booster was significantly higher than that induced by the CoronaVac vaccine booster (100,683.37 vs. 9,451.69, p < 0.001). In the Sf9 cells group, GMTs of neutralizing antibodies against pseudo SARS-CoV-2 viruses (prototype and diverse variants of concern [VOCs]) increased by 22.23-75.93 folds from baseline to day 28 post-booster, while the CoronaVac group showed increases of only 3.29-10.70 folds. Similarly, neutralizing antibodies against live SARS-CoV-2 viruses (prototype and diverse VOCs) increased by 68.18-192.67 folds on day 14 post-booster compared with the baseline level, significantly greater than the CoronaVac group (19.67-37.67 folds). A more robust Th1 cellular response was observed with the Sf9 cells booster on day 14 post-booster (mean IFN-γ+ spot-forming cells per 2 × 105 peripheral blood mononuclear cells: 26.66 vs. 13.59). Protective effectiveness against symptomatic COVID-19 was approximately twice as high in the Sf9 cells group compared to the CoronaVac group (68.18% vs. 36.59%, p = 0.004). Our study findings support the high protective effectiveness of heterologous boosting with the recombinant COVID-19 vaccine (Sf9 cells) against symptomatic COVID-19 of diverse SARS-CoV-2 variants of concern, while causing no apparent safety concerns.

A novel serum m7G-harboring microRNA signature for cancer detection.

Background: Emerging evidence points to the exceptional importance and value of m7G alteration in the diagnosis and prognosis of cancers. Nonetheless, a biomarker for precise screening of various cancer types has not yet been developed based on serum m7G-harboring miRNAs. Methods: A total of 20,702 serum samples, covering 12 cancer types and consisting of 7,768 cancer samples and 12,934 cancer-free samples were used in this study. A m7G target miRNA diagnostic signature (m7G-miRDS) was established through the least absolute shrinkage and selection operator (LASSO) analyses in a training dataset (n = 10,351), and validated in a validation dataset (n = 10,351). Results: The m7G-miRDS model, a 12 m7G-target-miRNAs signature, demonstrated high accuracy and was qualified for cancer detection. In the training and validation cohort, the area under the curve (AUC) reached 0.974 (95% CI 0.971-0.977) and 0.972 (95% CI 0.969-0.975), respectively. The m7G-miRDS showed superior sensitivity in each cancer type and had a satisfactory AUC in identifying bladder cancer, lung cancer and esophageal cancer. Additionally, the diagnostic performance of m7G-miRDS was not interfered by the gender, age and benign disease. Conclusion: Our results greatly extended the value of serum circulating miRNAs and m7G in cancer detection, and provided a new direction and strategy for the development of novel biomarkers with high accuracy, low cost and less invasiveness for mass cancer screening, such as ncRNA modification.

Serotonin receptor HTR2B facilitates colorectal cancer metastasis via CREB1-ZEB1 axis mediated epithelial-mesenchymal transition.

A number of neurotransmitters have been detected in tumor microenvironment and proved to modulate cancer oncogenesis and progression. We previously found that biosynthesis and secretion of neurotransmitter 5-hydroxytryptamine (5-HT) was elevated in colorectal cancer (CRC) cells. In this study, we discovered that the HTR2B receptor of 5-HT was highly expressed in CRC tumor tissues, which was further identified as a strong risk factor for CRC prognostic outcomes. Both pharmacological blocking and genetic knocking down HTR2B impaired migration of CRC cell, as well as the epithelial-mesenchymal transition (EMT) process. Mechanistically, HTR2B signaling induced ribosomal protein S6 kinase B1 (S6K1) activation via Akt/mTOR pathway, which triggered cAMP responsive element binding protein 1 (CREB1) phosphorylation (Ser 133) and translocation into the nucleus, then the phosphorylated CREB1 acts as an activator for ZEB1 transcription after binding to CREB1 half-site (GTCA) at ZEB1 promoter. As a key regulator of EMT, ZEB1 therefore enhances migration and EMT process in CRC cells. We also found that HTR2B specific antagonist (RS127445) treatment significantly ameliorated metastasis and reversed EMT process in both HCT116 cell tail-vein-injected pulmonary metastasis and CT26 cell intrasplenic-injected hepatic metastasis mouse models. Implications: These findings uncover a novel regulatory role of HTR2B signaling on CRC metastasis, which provide experimental evidences for potential HTR2B-targeted anti-CRC metastasis therapy.

Resistant starch and the gut microbiome: Exploring beneficial interactions and dietary impacts.

The intricate relationship between resistant starch (RS) and the gut microbiome presents a dynamic frontier in nutrition science. This review synthesizes current understandings of how RS, an indigestible form of starch found naturally in certain foods and also enhanced through various modification methods, interacts with the gut microbiome. We particularly focus on how RS fermentation in the colon contributes to the production of beneficial volatile fatty acids (VFAs) such as butyrate, acetate, and propionate. These VFAs have been recognized for their vital roles in maintaining gut barrier integrity, modulating inflammation, and potentially influencing systemic health. Additionally, we discuss the dietary implications of consuming foods rich in RS, both in terms of gut health and broader metabolic outcomes. By consolidating these insights, we emphasize the significance of RS in the context of dietary strategies aimed at harnessing the gut microbiome's potential to impact human health.

Y-Shaped Backbone-Rigidified DNA Tiles for the Construction of Supersized Nondeformable Tetrahedrons for Precise Cancer Therapies.

While engineered DNA nanoframeworks have been extensively exploited for delivery of diagnostic and therapeutic regents, DNA tiling-based DNA frameworks amenable to applications in living systems lag much behind. In this contribution, by developing a Y-shaped backbone-based DNA tiling technique, we assemble Y-shaped backbone-rigidified supersized DNA tetrahedrons (RDT) with 100% efficiency for precisely targeted tumor therapy. RDT displays unparalleled rigidness and unmatched resistance to nuclease degradation so that it almost does not deform under the force exerted by the atomic force microscopy tip, and the residual amount is not less than 90% upon incubating in biological media for 24 h, displaying at least 11.6 times enhanced degradation resistance. Without any targeting ligand, RDT enters the cancer cell in a targeted manner, and internalization specificity is up to 15.8. Moreover, 77% of RDT objects remain intact within living cells for 14 h. The drug loading content of RDT is improved by 4-8 times, and RDT almost 100% eliminates the unintended drug leakage in a stimulated physiological medium. Once systemically administrated into HeLa tumor-bearing mouse models, doxorubicin-loaded RDTs preferentially accumulate in tumor sites and efficiently suppress tumor growth without detectable off-target toxicity. The Y-DNA tiling technique offers invaluable insights into the development of structural DNA nanotechnology for precise medicine.

Autologous Transplantation Tooth Guide Design Based on Deep Learning.

BACKGROUND: Autologous tooth transplantation requires precise surgical guide design, involving manual tracing of donor tooth contours based on patient cone-beam computed tomography (CBCT) scans. While manual corrections are time-consuming and prone to human errors, deep learning-based approaches show promise in reducing labor and time costs while minimizing errors. However, the application of deep learning techniques in this particular field is yet to be investigated. PURPOSE: We aimed to assess the feasibility of replacing the traditional design pipeline with a deep learning-enabled autologous tooth transplantation guide design pipeline. STUDY DESIGN, SETTING, SAMPLE: This retrospective cross-sectional study used 79 CBCT images collected at the Guangzhou Medical University Hospital between October 2022 and March 2023. Following preprocessing, a total of 5,070 region of interest images were extracted from 79 CBCT images. PREDICTOR VARIABLE: Autologous tooth transplantation guide design pipelines, either based on traditional manual design or deep learning-based design. MAIN OUTCOME VARIABLE: The main outcome variable was the error between the reconstructed model and the gold standard benchmark. We used the third molar extracted clinically as the gold standard and leveraged it as the benchmark for evaluating our reconstructed models from different design pipelines. Both trueness and accuracy were used to evaluate this error. Trueness was assessed using the root mean square (RMS), and accuracy was measured using the standard deviation. The secondary outcome variable was the pipeline efficiency, assessed based on the time cost. Time cost refers to the amount of time required to acquire the third molar model using the pipeline. ANALYSES: Data were analyzed using the Kruskal-Wallis test. Statistical significance was set at P < .05. RESULTS: In the surface matching comparison for different reconstructed models, the deep learning group achieved the lowest RMS value (0.335 ± 0.066 mm). There were no significant differences in RMS values between manual design by a senior doctor and deep learning-based design (P = .688), and the standard deviation values did not differ among the 3 groups (P = .103). The deep learning-based design pipeline (0.017 ± 0.001 minutes) provided a faster assessment compared to the manual design pipeline by both senior (19.676 ± 2.386 minutes) and junior doctors (30.613 ± 6.571 minutes) (P < .001). CONCLUSIONS AND RELEVANCE: The deep learning-based automatic pipeline exhibited similar performance in surgical guide design for autogenous tooth transplantation compared to manual design by senior doctors, and it minimized time costs.

Strong H-bonding from Zeolite BroÌ·nsted Acid Site to Water: Origin of the Broad IR Doublet.

Hydrogen bonding between water molecules and zeolite BroÌ·nsted acid sites (BAS) has received much attention due to the significant influence of water on the adsorption and catalytic properties of these widely used porous materials. When a single water molecule is adsorbed at the BAS, the zeolite O-H stretch vibration decreases in frequency and splits into two extraordinarily broad bands peaked near 2500 and 2900 cm-1 in the infrared (IR) spectrum. This broad doublet feature is the predominant IR signature used to identify and interpret water-BAS H-bonding at low hydration levels, but the origin of the band splitting is not well understood. In this study, we used broadband two-dimensional infrared (2D IR) spectroscopy to investigate zeolite HZSM-5 prepared with a single water molecule per BAS. We find that the 2D IR spectrum is not explained by the most common interpretation of Fermi resonance coupling between the stretch and the bend of the BAS OH group, which predicts intense excited-state transitions that are absent from the experimental results. We present an alternative model of a double-well proton stretch potential, where the band splitting is caused by excited-state tunneling through the proton-transfer barrier. This one-dimensional model reproduces the basic experimental pattern of transition frequencies and amplitudes, suggesting that the doublet bands may originate from a highly anharmonic potential in which the excited state proton wave functions are delocalized over the H-bond between zeolite BAS and adsorbed H2O. Additional details about molecular orientation and coordination of the adsorbed water molecule are also resolved in the 2D IR spectroscopy.

Harnessing the power of clinical decision support systems: challenges and opportunities.

Clinical decision support systems (CDSSs) are increasingly integrated into healthcare settings to improve patient outcomes, reduce medical errors and enhance clinical efficiency by providing clinicians with evidence-based recommendations at the point of care. However, the adoption and optimisation of these systems remain a challenge. This review aims to provide an overview of the current state of CDSS, discussing their development, implementation, benefits, limitations and future directions. We also explore the potential for enhancing their effectiveness and provide an outlook for future developments in this field. There are several challenges in CDSS implementation, including data privacy concerns, system integration and clinician acceptance. While CDSS have demonstrated significant potential, their adoption and optimisation remain a challenge.

Corrigendum: Development and validation of a m6A -regulated prognostic signature in lung adenocarcinoma.

[This corrects the article DOI: 10.3389/fonc.2022.947808.].

Nondestructive Nonlinear Optical Microscopy Revealed the Blackening Mechanism of Ancient Chinese Jades.

Jade is most valued in Chinese culture since ancient times. For unearthed jade artifacts, the alteration color resulting from weathering effects and human activities provides information for cultural heritage conservation, archaeology, and history. Currently, the noninvasive 3-dimensional characterization of jade artifacts with high chemical and spatial resolution remains challenging. In this work, we applied femtosecond pump-probe microscopy and second harmonic generation microscopy techniques to study the black alteration of an ancient jade artifact of the late Spring and Autumn period (546 to 476 BC). The direct cause of the "mercury alteration" phenomena was discovered to be the conversion of metacinnabar from buried cinnabar in the tomb. Furthermore, a 3-dimensional optical reconstruction of the black alteration was achieved, providing a high-resolution method for analyzing the blackening mechanism without the need of sample damage. Our approach opens up new opportunities to extract microscopic spatiochemical information for a broad range of alteration colors in jade artifacts.

Formation characteristics of bacteria and fungi in sewers: In terms of signal molecule generation.

Bio-metabolism of diverse communities is the main reason of water quality variation in sewers, and the signal molecule generation of communities is dementated to be the key regulation procedure for community metabolism. To reveal the mechanism of pollutant biotransformation in complex sewer environment, this study explored the formation of bacteria and fungi and the signal molecule transduction characteristics in a pilot sewer. In this study, several kinds of signal molecules that produced by bacteria and fungi (C4-HSL, C6-HSL, C8-HSL, farnesol and tyrosol) were detected along the formation process of sewer biofilms. The results showed that, in the early stage, bacterial AHLs signaling molecules are beneficial to the synthesis of EPS, providing a good material basis for the growth of bacterial flora. In addition, tyrosol stimulates the formation of embryonic tubes in yeast cells, further promoting the growth of hyphae. At the later stage, AHLs signaling molecules and tyrosol jointly promoted the growth of biofilms. In conclusion, it is precisely because of the coexistence of bacteria and fungi in the sewer system that the generated signal molecules can jointly promote the synthesis and growth of biofilms through different pathways, and have positive feedback on the biodegradation of various pollutants. Based on the exploration, the ecological patterns of bacterial-fungal communities in urban sewer system were proposed and it could improve the understanding on the pollutant transformation behaviors in sewers.

Center backbone-rigidified DNA polygonal nanostructures and bottom face-templated polyhedral pyramids with structural stability in a complex biological medium.

Due to the sequence programmability, good biocompatibility, versatile functionalities and vast sequence space, DNA oligonucleotides are considered to be ideal building blocks for the assembly of diverse nanostructures in one, two and three dimensions that are capable of engineering of multiple functional nucleic acids into a useful tool to implement intended tasks in biological and medical field. However, the construction of wireframe nanostructures consisting of only a few DNA strands remains quite challenging mainly because of the molecular flexibility-based uncontrollability of size and shape. In this contribution, utilizing gel electrophoretic analysis and atomic force microscopy, we demonstrate the modeling assembly technique for the construction of wireframe DNA nanostructures that can be divided into two categories: rigid center backbone-guided modeling (RBM) and bottom face-templated assembly (BTA) that are responsible for the construction of DNA polygons and polyhedral pyramids, respectively. The highest assembly efficiency (AE) is about 100%, while the lowest AE is not less than 50%. Moreover, when adding one edge for polygons or one side face for pyramids, we only need to add one oligonucleotide strand. Especially, the advanced polygons (e.g., pentagon and hexagon) of definite shape are for the first time constructed. Along this line, introduction of cross-linking strands enables the hierarchical assembly of polymer polygons and polymer pyramids. These wireframe DNA nanostructures exhibit the substantially enhanced resistance to nuclease degradation and maintain their structural integrity in fetal bovine serum for several hours even if the vulnerable nicks are not sealed. The proposed modeling assembly technique represents important progress toward the development of DNA nanotechnology and is expected to promote the application of DNA nanostructures in biological and biomedical fields. STATEMENT OF SIGNIFICANCE: DNA oligonucleotides are considered to be ideal building blocks for the assembly of diverse nanostructures. However, the construction of wireframe nanostructures consisting of only a few DNA strands remains quite challenging. In this contribution, we demonstrate the modeling technique for the construction of different wireframe DNA nanostructures: rigid center backbone-guided modeling (RBM) and bottom face-templated assembly (BTA) that are responsible for the assembly of DNA polygons and polyhedral pyramids, respectively. Moreover, cross-linking strands enables the hierarchical assembly of polymer polygons and polymer pyramids. These wireframe DNA nanostructures exhibit the substantially enhanced resistance to nuclease degradation and maintain their structural integrity in fetal bovine serum for several hours, promoting the application of DNA nanostructures in biological and biomedical fields.