Exposure to heavy metal elements may significantly increase serum prostate-specific antigen levels with overdosed dietary zinc.

BACKGROUND: Serum prostate-specific antigen (PSA) is a primary metric for diagnosis and prognosis of prostate cancer (PCa). Exposure to heavy metals, such as lead, cadmium, mercury, and zinc can impact PSA levels in PCa patients. However, it is unclear whether this effect also occurs in men without PCa, which may lead to the overdiagnosis of PCa. METHOD: Data on a total of 5089 American men who had never been diagnosed with PCa were obtained from the National Health and Nutrition Examination Survey performed from 2003-2010. The relationship between serum PSA levels (dependent variable) and concentrations of lead (µmol/L), cadmium (nmol/L), and mercury (µmol/L) were investigated with dietary zinc intake being used as a potential modifier or covariate in a weighted linear regression model and a generalized additive model. A series of bootstrapping analyses were performed to evaluate sensitivity and specificity using these models. RESULTS: Regression analyses suggested that, in general, lead, cadmium, or mercury did not show an association with PSA levels, which was consistent with the results of the bootstrapping analyses. However, in a subgroup of participants with a high level of dietary zinc intake (≥14.12 mg/day), a significant positive association between cadmium and serum PSA was identified (1.06, 95% CI, P = 0.0268, P for interaction=0.0249). CONCLUSIONS: With high-level zinc intake, serum PSA levels may rise in PCa-free men as the exposure to cadmium increases, leading to a potential risk of an overdiagnosis of PCa and unnecessary treatment. Therefore, environmental variables should be factored in the current diagnostic model for PCa that is solely based on PSA measurements. Different criteria for PSA screening are necessary based on geographical variables. Further investigations are needed to uncover the biological and biochemical relationship between zinc, cadmium, and serum PSA levels to more precisely diagnose PCa.

Preparation of hyaluronic acid-loaded liquid-core hydrogel beads with acceptable mechanical properties and thermal stability.

BACKGROUND: Hyaluronic acid liquid-core hydrogel beads (HA-LHB) is a good way for oral intake of HA. However, HA may affect the reaction-diffusion of sodium alginate (SA) and Ca2+ leading to poor mechanical properties, since HA is a polyanionic electrolyte having electrostatic effect and a certain spatial site-blocking effect. RESULTS: The mechanical properties of HA-LHB were modified from bathing solution, core solution and secondary calcium bath time. The mechanical properties varied with the SA structure and concentration in bathing solution, where SA with high G (guluronic acid) segment compounded with SA with high M (mannuronic acid) segment at a mass ratio of 7:3 with a 11 g kg-1 concentration showed the best mechanical properties. The secondary calcium bath can greatly improve the mechanical properties due to the tight network formed by bidirectional crosslinking, and 15 min reaction reached the plateau if Ca2+ is sufficient. And the mechanical properties were positively correlated with calcium lactate concentration only at <70 g kg-1 in core solution, but the diffusion of Ca2+ was hindered by the tight gel network at higher concentrations. Moreover, the mechanical properties can be maintained during heat treatment, due to the rearrangement of alginate network structure. CONCLUSION: Our results suggested that the problem of poor mechanical properties of LHB in the presence of high HA concentration can be avoided by process control, which may broaden the development of HA and popping boba market. © 2024 Society of Chemical Industry.

scGRN: a comprehensive single-cell gene regulatory network platform of human and mouse.

Gene regulatory networks (GRNs) are interpretable graph models encompassing the regulatory interactions between transcription factors (TFs) and their downstream target genes. Making sense of the topology and dynamics of GRNs is fundamental to interpreting the mechanisms of disease etiology and translating corresponding findings into novel therapies. Recent advances in single-cell multi-omics techniques have prompted the computational inference of GRNs from single-cell transcriptomic and epigenomic data at an unprecedented resolution. Here, we present scGRN (https://bio.liclab.net/scGRN/), a comprehensive single-cell multi-omics gene regulatory network platform of human and mouse. The current version of scGRN catalogs 237 051 cell type-specific GRNs (62 999 692 TF-target gene pairs), covering 160 tissues/cell lines and 1324 single-cell samples. scGRN is the first resource documenting large-scale cell type-specific GRN information of diverse human and mouse conditions inferred from single-cell multi-omics data. We have implemented multiple online tools for effective GRN analysis, including differential TF-target network analysis, TF enrichment analysis, and pathway downstream analysis. We also provided details about TF binding to promoters, super-enhancers and typical enhancers of target genes in GRNs. Taken together, scGRN is an integrative and useful platform for searching, browsing, analyzing, visualizing and downloading GRNs of interest, enabling insight into the differences in regulatory mechanisms across diverse conditions.

eRNAbase: a comprehensive database for decoding the regulatory eRNAs in human and mouse.

Enhancer RNAs (eRNAs) transcribed from distal active enhancers serve as key regulators in gene transcriptional regulation. The accumulation of eRNAs from multiple sequencing assays has led to an urgent need to comprehensively collect and process these data to illustrate the regulatory landscape of eRNAs. To address this need, we developed the eRNAbase (http://bio.liclab.net/eRNAbase/index.php) to store the massive available resources of human and mouse eRNAs and provide comprehensive annotation and analyses for eRNAs. The current version of eRNAbase cataloged 10 399 928 eRNAs from 1012 samples, including 858 human samples and 154 mouse samples. These eRNAs were first identified and uniformly processed from 14 eRNA-related experiment types manually collected from GEO/SRA and ENCODE. Importantly, the eRNAbase provides detailed and abundant (epi)genetic annotations in eRNA regions, such as super enhancers, enhancers, common single nucleotide polymorphisms, expression quantitative trait loci, transcription factor binding sites, CRISPR/Cas9 target sites, DNase I hypersensitivity sites, chromatin accessibility regions, methylation sites, chromatin interactions regions, topologically associating domains and RNA spatial interactions. Furthermore, the eRNAbase provides users with three novel analyses including eRNA-mediated pathway regulatory analysis, eRNA-based variation interpretation analysis and eRNA-mediated TF-target gene analysis. Hence, eRNAbase is a powerful platform to query, browse and visualize regulatory cues associated with eRNAs.

Dynamic immuno-nanomedicines in oncology.

Anti-cancer therapeutics have achieved significant advances due to the emergence of immunotherapies that rely on the identification of tumors by the patients' immune system and subsequent tumor eradication. However, tumor cells often escape immunity, leading to poor responsiveness and easy tolerance to immunotherapy. Thus, the potentiated anti-tumor immunity in patients resistant to immunotherapies remains a challenge. Reactive oxygen species-based dynamic nanotherapeutics are not new in the anti-tumor field, but their potential as immunomodulators has only been demonstrated in recent years. Dynamic nanotherapeutics can distinctly enhance anti-tumor immune response, which derives the concept of the dynamic immuno-nanomedicines (DINMs). This review describes the pivotal role of DINMs in cancer immunotherapy and provides an overview of the clinical realities of DINMs. The preclinical development of emerging DINMs is also outlined. Moreover, strategies to synergize the antitumor immunity by DINMs in combination with other immunologic agents are summarized. Last but not least, the challenges and opportunities related to DINMs-mediated immune responses are also discussed.

Optimization of pneumonia CT classification model using RepVGG and spatial attention features.

Introduction: Pneumonia is a common and widespread infectious disease that seriously affects the life and health of patients. Especially in recent years, the outbreak of COVID-19 has caused a sharp rise in the number of confirmed cases of epidemic spread. Therefore, early detection and treatment of pneumonia are very important. However, the uneven gray distribution and structural intricacy of pneumonia images substantially impair the classification accuracy of pneumonia. In this classification task of COVID-19 and other pneumonia, because there are some commonalities between this pneumonia, even a small gap will lead to the risk of prediction deviation, it is difficult to achieve high classification accuracy by directly using the current network model to optimize the classification model. Methods: Consequently, an optimization method for the CT classification model of COVID-19 based on RepVGG was proposed. In detail, it is made up of two essential modules, feature extraction backbone and spatial attention block, which allows it to extract spatial attention features while retaining the benefits of RepVGG. Results: The model's inference time is significantly reduced, and it shows better learning ability than RepVGG on both the training and validation sets. Compared with the existing advanced network models VGG-16, ResNet-50, GoogleNet, ViT, AlexNet, MobileViT, ConvNeXt, ShuffleNet, and RepVGG_b0, our model has demonstrated the best performance in a lot of indicators. In testing, it achieved an accuracy of 0.951, an F1 score of 0.952, and a Youden index of 0.902. Discussion: Overall, multiple experiments on the large dataset of SARS-CoV-2 CT-scan dataset reveal that this method outperforms most basic models in terms of classification and screening of COVID-19 CT, and has a significant reference value. Simultaneously, in the inspection experiment, this method outperformed other networks with residual structures.

A Comprehensive Understanding of Knife Cutting: Effects of Hardness, Blade Angle and the Micro-Geometry of Blade Edge on the Cutting Performance.

The cutting performance of steel blades is an eternal, attractive topic in the knife industry. It is a complicated process to cut up materials because it usually involves the contact mechanics of the material been cut, the geometry and roughness of the blade edge and the hardness and wear resistance of the blade steel. Therefore, a comprehensive analysis is required to evaluate the cutting performance of knife blades. In this study, such an analysis was conducted based on a quantitative model to describe the cutting depth of paper cards containing SiO2 particles by steel blades, and major contributing factors were summarized. The effect of the micro-geometries of blade edges was thoroughly discussed, and a geometry factor ξ for the micro-geometry of a blade edge was introduced into the model. The experimental results indicated that mechanical processing could produce a rough blade edge and a higher ξ value, accordingly. A similar effect was caused by the carbides in the martensitic steels for blades, and the ξ value was found to increase linearly with the volumetric fraction of the carbides. The extraordinary cutting behavior of the 3V blade implied that fine coherent carbides may result in an efficient improvement (40-50%) in the total cutting depth.

Dabie bandavirus infection induces macrophagic pyroptosis and this process is attenuated by platelets.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infection with a high mortality rate in humans, which is caused by Dabie bandavirus (DBV), formerly known as SFTS virus. Clinical manifestations of SFTS are characterized by high fever, thrombocytopenia, leukopenia, hemorrhage, gastrointestinal symptoms, myalgia and local lymph node enlargement with up to 30% case fatality rates in human. Macrophage depletion in secondary lymphoid organs have important roles in the pathogenic process of fatal SFTS, but its exact cell death mechanism remains largely unknown. Here, we showed for the first time that DBV infection induced macrophagic pyroptosis, as evidenced by swollen cells, pore-forming structures, accumulation of gasdermin D N-terminal (GSDMD-NT) as well as the release of lactate dehydrogenase (LDH) and IL-1ß in human macrophages. In addition to the upregulation of pyronecrosis genes, the expressions of pyroptosis-related proteins (GSDMD, caspase-1 and IL-1ß) were also elevated. To be noted, platelets were found to play a protective role in DBV-derived pyroptosis. Transcriptome analysis and in vitro studies demonstrated that platelets significantly reduced the gene expressions and protein production of pro-pyroptotic markers and inflammatory cytokines in macrophages, whereas platelets conferred a propagation advantage for DBV. Collectively, this study demonstrates a novel mechanism by which DBV invasion triggers pyroptosis as a host defense to remove replication niches in human macrophages and platelets provide an additional layer to reduce cellular death. These findings may have important implications to the pathogenesis of lethal DBV, and provide new ideas for developing novel therapeutics to combat its infection.

Clusterin and Its Isoforms in Oral Squamous Cell Carcinoma and Their Potential as Biomarkers: A Comprehensive Review.

Oral squamous cell carcinoma (OSCC) is a prevalent type of head and neck cancer, ranked as the sixth most common cancer worldwide, accounting for approximately 300,000 new cases and 145,000 deaths annually. Early detection using biomarkers significantly increases the 5-year survival rate of OSCC by up to 80-90%. Clusterin (CLU), also known as apolipoprotein J, is a sulfated chaperonic glycoprotein expressed in all tissues and human fluids and has been reported to be a potential biomarker of OSCC. CLU has been implicated as playing a vital role in many biological processes such as apoptosis, cell cycle, etc. Abnormal CLU expression has been linked with the development and progression of cancers. Despite the fact that there are many studies that have reported the involvement of CLU and its isoforms in OSCC, the exact roles of CLU and its isoforms in OSCC carcinogenesis have not been fully explored. This article aims to provide a comprehensive review of the current understanding of CLU structure and genetics and its correlation with OSCC tumorigenesis to better understand potential diagnostic and prognostic biomarker development. The relationship between CLU and chemotherapy resistance in cancer will also be discussed to explore the therapeutic application of CLU and its isoforms in OSCC.

Effect of Annealing Temperature on Electrochemical Properties of Zr56Cu19Ni11Al9Nb5 in PBS Solution.

The electrochemical properties of as-cast Zr56Cu19Ni11Al9Nb5 metallic glass and samples annealed at different temperatures were investigated using potentiodynamic polarization tests and electrochemical impedance spectroscopy (EIS) in phosphate buffer saline (PBS) solution. It was shown that passivation occurred for the as-cast sample and the samples annealed at 623-823 K, indicating good corrosion resistance. At higher annealing temperature, the corrosion resistance first increased, and then decreased. The sample annealed at 823 K exhibited the best corrosion resistance, with high spontaneous corrosion potential Ecorr at -0.045 VSCE, small corrosion current density icorr at 1.549 × 10-5 A·cm-2, high pitting potential Epit at 0.165 VSCE, the largest arc radius, and the largest sum of Rf and Rct at 5909 Ω·cm2. For the sample annealed at 923 K, passivation did not occur, with low Ecorr at -0.075 VSCE, large icorr at 1.879 × 10-5 A·cm-2, the smallest arc radius, and the smallest sum of Rf and Rct at 2173 Ω·cm2, which suggested the worst corrosion resistance. Proper annealing temperature led to improved corrosion resistance due to structural relaxation and better stability of the passivation film, however, if the annealing temperature was too high, the corrosion resistance deteriorated due to the chemical inhomogeneity between the crystals and the amorphous matrix. Optical microscopy and scanning electron microscopy (SEM) examinations indicated that localized corrosion occurred. Results of energy dispersive X-ray spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS) illustrated that the main corrosion products were ZrO2, CuO, Cu2O, Ni(OH)2, Al2O3, and Nb2O5.

Microbiota and functional analyses of nitrogen-fixing bacteria in root-knot nematode parasitism of plants.

BACKGROUND: Root-knot nematodes (RKN) are among the most important root-damaging plant-parasitic nematodes, causing severe crop losses worldwide. The plant rhizosphere and root endosphere contain rich and diverse bacterial communities. However, little is known about how RKN and root bacteria interact to impact parasitism and plant health. Determining the keystone microbial taxa and their functional contributions to plant health and RKN development is important for understanding RKN parasitism and developing efficient biological control strategies in agriculture. RESULTS: The analyses of rhizosphere and root endosphere microbiota of plants with and without RKN showed that host species, developmental stage, ecological niche, and nematode parasitism, as well as most of their interactions, contributed significantly to variations in root-associated microbiota. Compared with healthy tomato plants at different developmental stages, significant enrichments of bacteria belonging to Rhizobiales, Betaproteobacteriales, and Rhodobacterales were observed in the endophytic microbiota of nematode-parasitized root samples. Functional pathways related to bacterial pathogenesis and biological nitrogen fixation were significantly enriched in nematode-parasitized plants. In addition, we observed significant enrichments of the nifH gene and NifH protein, the key gene/enzyme involved in biological nitrogen fixation, within nematode-parasitized roots, consistent with a potential functional contribution of nitrogen-fixing bacteria to nematode parasitism. Data from a further assay showed that soil nitrogen amendment could reduce both endophytic nitrogen-fixing bacteria and RKN prevalence and galling in tomato plants. CONCLUSIONS: Results demonstrated that (1) community variation and assembly of root endophytic microbiota were significantly affected by RKN parasitism; (2) a taxonomic and functional association was found for endophytic nitrogen-fixing bacteria and nematode parasitism; and (3) the change of nitrogen-fixing bacterial communities through the addition of nitrogen fertilizers could affect the occurrence of RKN. Our results provide new insights into interactions among endophytic microbiota, RKN, and plants, contributing to the potential development of novel management strategies against RKN. Video Abstract.

Recent insights into reverse genetics of norovirus.

Norovirus is the leading cause of viral gastroenteritis globally, and poses substantial threats to public health. Despite substantial progress made in preventing norovirus diseases, the lack of a robust virus culture system has hampered biological research and effective strategies to combat this pathogen. Reverse genetic system is the technique to generate infectious viruses from cloned genetic constructs, which is a powerful tool for the investigation of viral pathogenesis and for the development of novel drugs and vaccines. The strategies of reverse genetics include bacterial artificial chromosomes, vaccinia virus vectors, and entirely plasmid-based systems. Since each strategy has its pros and cons, choosing appropriate approaches will greatly improve the efficiency of virus rescue. Reverse genetic systems that have been employed for norovirus greatly extend its life cycle and facilitate the development of medical countermeasures. In this review, we summarize the current knowledge on the structure, transmission, genetic evolution and clinical manifestations of norovirus, and describe recent advances in the studies of norovirus reverse genetics as well as its future prospects for therapeutics and vaccine development.

The genome and antigen proteome analysis of Spiroplasma mirum.

Spiroplasma mirum, small motile wall-less bacteria, was originally isolated from a rabbit tick and had the ability to infect newborn mice and caused cataracts. In this study, the whole genome and antigen proteins of S. mirum were comparative analyzed and investigated. Glycolysis, pentose phosphate pathway, arginine metabolism, nucleotide biosynthesis, and citrate fermentation were found in S. mirum, while trichloroacetic acid, fatty acids metabolism, phospholipid biosynthesis, terpenoid biosynthesis, lactose-specific PTS, and cofactors synthesis were completely absent. The Sec systems of S. mirum consist of SecA, SecE, SecDF, SecG, SecY, and YidC. Signal peptidase II was identified in S. mirum, but no signal peptidase I. The relative gene order in S. mirum is largely conserved. Genome analysis of available species in Mollicutes revealed that they shared only 84 proteins. S. mirum genome has 381 pseudogenes, accounting for 31.6% of total protein-coding genes. This is the evidence that spiroplasma genome is under an ongoing genome reduction. Immunoproteomics, a new scientific technique combining proteomics and immunological analytical methods, provided the direction of our research on S. mirum. We identified 49 proteins and 11 proteins (9 proteins in common) in S. mirum by anti-S. mirum serum and negative serum, respectively. Forty proteins in S. mirum were identified in relation to the virulence. All these proteins may play key roles in the pathogeny and can be used in the future for diagnoses and prevention.

Effects of single- and mixed-bacterial inoculation on the colonization and assembly of endophytic communities in plant roots.

The introduction and inoculation of beneficial bacteria in plants have consistently been considered as one of the most important ways to improve plant health and production. However, the effects of bacterial inoculation on the community assembly and composition of the root endophytic microbiome remain largely unknown. In this study, 55 strains were randomly isolated from tomato roots and then inoculated into wheat seeds singly or in combination. Most of the isolated bacterial strains showed an ability to produce lignocellulose-decomposing enzymes and promote plant growth. The results demonstrated that bacterial inoculation had a significant effect on the wheat root endophytic microbiome. The wheat root samples inoculated with single-bacterial species were significantly separated into two groups (A and B) that had different community structures and compositions. Among these, root endophytic communities for most wheat samples inoculated with a single-bacterial strain (Group A) were predominated by one or several bacterial species, mainly belonging to Enterobacterales. In contrast, only a few of the root samples inoculated with a single-bacterial strain (Group B) harbored a rich bacterial flora with relatively high bacterial diversity. However, wheat roots inoculated with a mixed bacterial complex were colonized by a more diverse and abundant bacterial flora, which was mainly composed of Enterobacterales, Actinomycetales, Bacillales, Pseudomonadales, and Rhizobiales. The results demonstrated that inoculation with bacterial complexes could help plants establish more balanced and beneficial endophytic communities. In most cases, bacterial inoculation does not result in successful colonization by the target bacterium in wheat roots. However, bacterial inoculation consistently had a significant effect on the root microbiome in plants. CAP analysis demonstrated that the variation in wheat root endophytic communities was significantly related to the taxonomic status and lignocellulose decomposition ability of the inoculated bacterial strain (p < 0.05). To reveal the role of lignocellulose degradation in shaping the root endophytic microbiome in wheat, four bacterial strains with different colonization abilities were selected for further transcriptome sequencing analysis. The results showed that, compared with that in the dominant bacterial species Ent_181 and Ent_189 of Group A, the expression of lignocellulose-decomposing enzymes was significantly downregulated in Bac_133 and Bac_71 (p < 0.05). In addition, we found that the dominant bacterial species of the tomato endophytic microbiome were more likely to become dominant populations in the wheat root microbiome. In general, our results demonstrated that lignocellulose-decomposing enzymes played a vital role in the formation of endophytes and their successful colonization of root tissues. This finding establishes a theoretical foundation for the development of broad-spectrum probiotics.

Genomic characterization of Salmonella enterica serovar Kentucky and London recovered from food and human salmonellosis in Zhejiang Province, China (2016-2021).

Increasing human salmonellosis caused by Salmonella enterica serovar Kentucky and London has raised serious concerns. To better understand possible health risks, insights were provided into specific genetic traits and antimicrobial resistance of 88 representative isolates from human and food sources in Zhejiang Province, China, during 2016-2021. Phylogenomic analysis revealed consistent clustering of isolates into the respective serovar or sequence types, and identified plausible interhost transmission via distinct routes. Each serovar exhibited remarkable diversity in host range and disease-causing potential by cgMLST analyses, and approximately half (48.6%, 17/35) of the food isolates were phylogenetically indistinguishable to those of clinical isolates in the same region. S. London and S. Kentucky harbored serovar-specific virulence genes contributing to their functions in pathogenesis. The overall resistance genotypes correlated with 97.7% sensitivity and 60.2% specificity to the identified phenotypes. Resistance to ciprofloxacin, cefazolin, tetracycline, ampicillin, azithromycin, chloramphenicol, as well as multidrug resistance, was common. High-level dual resistance to ciprofloxacin and cephalosporins in S. Kentucky ST198 isolates highlights evolving threats of antibiotic resistance. These findings underscored the necessity for the development of effective strategies to mitigate the risk of food contamination by Salmonella host-restricted serovars.

Combination of multiple functional markers to improve diagnostic accuracy.

Combination of multiple biomarkers to improve diagnostic accuracy is meaningful for practitioners and clinicians, and are attractive to lots of researchers. Nowadays, with development of modern techniques, functional markers such as curves or images, play an important role in diagnosis. There exists rich literature developing combination methods for continuous scalar markers. Unfortunately, only sporadic works have studied how functional markers affect diagnosis in the literature. Moreover, no publication can be found to do combination of multiple functional markers to improve the diagnostic accuracy. It is impossible to apply scalar combination methods to the multiple functional markers directly because of infinite dimensionality of functional markers. In this article, we propose a one-dimension scalar feature motivated by square loss distance, as an alternative of the original functional curve in the sense that, it can retain information to the most extent. The square loss distance is defined as the function of projection scores generated from functional principal component decomposition. Then existing variety of scalar combination methods can be applied to scalar features of functional markers after dimension reduction to improve the diagnostic accuracy. Area under the receiver operating characteristic curve and Youden index are used to assess performances of various methods in numerical studies. We also analyzed the high- or low- hospital admissions due to respiratory diseases between 2010 and 2017 in Hong Kong by combining weather conditions and media information, which are regarded as functional markers. Finally, we provide an R function for convenient application.

Construction of SiOx/nitrogen-doped carbon superstructures derived from rice husks for boosted lithium storage.

Silicon sub-oxides (SiOx) are increasingly becoming a prospective anode material for lithium-ion batteries (LIBs). Nevertheless, inferior electrical conductivity and drastic volume fluctuation upon cycling significantly hamper the electrochemical performance of SiOx. In this work, rice husks (RHs)-derived pitaya-like SiOx/nitrogen-doped carbon (SNC) superstructures have been prepared by a simple electrospray-carbonization approach. SiOx nanoparticles (NPs) are well-dispersed in a spherical nitrogen-doped carbon (NC) matrix. The carbon frameworks discourage the aggregation of SiOx NPs, facilitating the kinetics for ion diffusion and charge transfer, and maintaining structural stability upon cycling, thus bringing about improved electrochemical performance. When the optimized SNC superstructures with SiOx content of 64.3% are utilized as LIBs anodes, a stable specific capacity of 622.8 mA h g-1 after 100 cycles at 0.1 A g-1, and an excellent long cycle performance of 190.1 mA h g-1 after 5000 cycles at 5 A g-1 are obtained. This effective and universal synthetic strategy for fabricating controllable superstructures offers insights into the development of high-performance LIBs.

ZnO@ZIF-8 Core-Shell Structure Gas Sensors with Excellent Selectivity to H2.

As the energy crisis becomes worse, hydrogen as a clean energy source is more and more widely used in industrial production and people's daily life. However, there are hidden dangers in hydrogen storage and transportation, because of its flammable and explosive features. Gas detection is the key to solving this problem. High quality sensors with more practical and commercial value must be able to accurately detect target gases in the environment. Emerging porous metal-organic framework (MOF) materials can effectively improve the selectivity of sensors as a result of high surface area and coordinated pore structure. The application of MOFs for surface modification to improve the selectivity and sensitivity of metal oxides sensors to hydrogen has been widely investigated. However, the influence of MOF modified film thickness on the selectivity of hydrogen sensors is seldom studied. Moreover, the mechanism of the selectivity improvement of the sensors with MOF modified film is still unclear. In this paper, we prepared nano-sized ZnO particles by a homogeneous precipitation method. ZnO nanoparticle (NP) gas sensors were prepared by screen printing technology. Then a dense ZIF-8 film was grown on the surface of the gas sensor by hydrothermal synthesis. The morphology, the composition of the elements and the characters of the product were analyzed by X-ray diffraction analysis (XRD), transmission electron microscope (TEM), scanning electron microscope (SEM), energy dispersive spectrometer (EDS), Brunauer-Emmett-Teller (BET) and differential scanning calorimetry (DSC). It is found that the ZIF-8 film grown for 4 h cannot form a dense core-shell structure. The thickness of ZIF-8 reaches 130 nm at 20 h. Through the detection and analysis of hydrogen (1000 ppm), ethanol (100 ppm) and acetone (50 ppm) from 150 °C to 290 °C, it is found that the response of the ZnO@ZIF-8 sensors to hydrogen has been significantly improved, while the response to ethanol and acetone was decreased. By comparing the change of the response coefficient, when the thickness of ZIF-8 is 130 nm, the gas sensor has a significantly improved selectivity to hydrogen at 230 °C. The continuous increase of the thickness tends to inhibit selectivity. The mechanism of selectivity improvement of the sensors with different thickness of the ZIF-8 films is discussed.

Enhancing Formaldehyde Selectivity of SnO2 Gas Sensors with the ZSM-5 Modified Layers.

High performance formaldehyde gas sensors are widely needed for indoor air quality monitoring. A modified layer of zeolite on the surface of metal oxide semiconductors results in selectivity improvement to formaldehyde as gas sensors. However, there is insufficient knowledge on how the thickness of the zeolite layer affects the gas sensing properties. In this paper, ZSM-5 zeolite films were coated on the surface of the SnO2 gas sensors by the screen printing method. The thickness of ZSM-5 zeolite films was controlled by adjusting the numbers of screen printing layers. The influence of ZSM-5 film thickness on the performance of ZSM-5/SnO2 gas sensors was studied. The results showed that the ZSM-5/SnO2 gas sensors with a thickness of 19.5 µm greatly improved the selectivity to formaldehyde, and reduced the response to ethanol, acetone and benzene at 350 °C. The mechanism of the selectivity improvement to formaldehyde of the sensors was discussed.

ESRRA promotes gastric cancer development by regulating the CDC25C/CDK1/CyclinB1 pathway via DSN1.

Background: Estrogen-related receptor-α (ESRRA) is an orphan nuclear receptor, expressing at high level in exuberant metabolism organs and acting as transcription factor. High expression was found in many malignances but no research was done in gastric cancer (GC), where lipid metabolism disorder is common. Methods: Kaplan-Meier plot was utilized to find the relationship between ESRRA expression and patients' prognoses. The expression level of ESRRA was measured by real-time PCR. The protein expression levels were tested with western-blot and immunohistochemistry. Cell cycle and apoptosis was identified with flow cytometry. RNA-seq, bioinformatics analysis, dual-luciferase assay and ChIP assay were used to predict and validate ESRRA's target gene and binding motif. Animal models were also introduced in our study. Results: ESRRA expression is notably higher in GC cell lines and high ESRRA levels are correlated to poor prognoses. ESRRA silencing decreased GC cell viability, migration, and invasion capacities. Its downstream gene DSN1 was spotted by RNA-seq and confirmed by later bioinformatics analyses, dual-luciferase, and ChIP assays. Western-blot showed G2M arrest caused by ESRRA silencing was via CDC25C-CDK1-Cyclin B1 pathway. Conclusion: ESRRA/DSN1/CDC25C-CDK1-Cyclin B1 is of great importance in GC development. ESRRA could be a potential target as well as prognostic marker in GC.