Attapulgite-intercalated g-C3N4/ZnIn2S4 3D hierarchical Z-scheme heterojunction for boosting photocatalytic hydrogen production.

Construction of hierarchical architecture with suitable band alignment for graphitic carbon nitride (g-C3N4) played a pivotal role in enhancing the efficiency of photocatalysts. In this study, a novel attapulgite-intercalated g-C3N4/ZnIn2S4 nanocomposite material (ZIS/CN/ATP, abbreviated as ZCA) was successfully synthesized using the freeze-drying technique, thermal polymerization, and a simple low-temperature hydrothermal method. Attapulgite (ATP) was intercalated into g-C3N4 to effectively regulate its interlayer structure. The results reveal a substantial enlargement of its internal space, thereby facilitating the provision of additional active sites for improved dispersibility of ZnIn2S4. Notably, the optimized photocatalyst, comprising a mass ratio of ATP, g-C3N4, and ZnIn2S4 at 1:1:2.5 respectively, achieves an outstanding hydrogen evolution rate of 3906.15 µmol g-1h-1, without the need for a Pt co-catalyst. This rate surpasses that of pristine g-C3N4 by a factor of 475 and ZnIn2S4 by a factor of 5, representing a significant improvement in performance. This significant enhancement can be primarily attributed to the higher specific surface area, richer active sites, broadened light response range, and efficient interfacial charge transfer channels of the ZCA composite photocatalyst. Furthermore, the Z-scheme photocatalytic mechanism for the sandwich-like layered structure heterojunction was thoroughly investigated using diverse characterization techniques. This work offers new insights for enhancing photocatalytic performance through the expanded utilization of natural minerals, paving the way for future advancements in this field.

Establishment of a multi-line immunochromatography based on magnetic nanoparticles for simultaneous screening of multiple biomarkers.

Biomarkers screening is a benefit approach for early diagnosis of major diseases. In this study, magnetic nanoparticles (MNPs) have been utilized as labels to establish a multi-line immunochromatography (MNP-MLIC) for simultaneous detection of carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA 19-9), and alpha-fetoprotein (AFP) in a single serum sample. Under the optimal parameters, the three biomarkers can be rapidly and simultaneously qualitative screening within 15 min by naked eye. As for quantitative detection, the MNP-MLIC test strips were precisely positioned and captured by a smartphone, and signals on the test and control lines were extracted by ImageJ software. The signal ratio of test and control lines has been calculated and used to plot quantitative standard curves with the logarithmic concentration, of which the correlation coefficients are more than 0.99, and the limit of detection for CEA, CA 19-9, and AFP were 0.60 ng/mL, 1.21 U/mL, and 0.93 ng/mL, respectively. The recoveries of blank serum were 75.0 ~ 112.5% with the relative standard deviation ranging from 2.5 to 15.3%, and the specificity investigation demonstrated that the MNP-MLIC is highly specific to the three biomarkers. In conclusion, the developed MNP-MLIC offers a rapid, simple, accurate, and highly specific method for simultaneously detecting multiple biomarkers in serum samples, which provides an efficient and accurate approach for the early diagnosis of diseases.

Construction of hierarchical In2O3/In2S3-ZnCdS ternary microsphere heterostructures for efficient photocatalytic nitrogen fixation.

Photocatalytic ammonia production holds immense promise as an environmentally sustainable approach to nitrogen fixation. In this study, In2O3/In2S3-ZnCdS ternary heterostructures were successfully constructed through an innovative in situ anion exchange process, coupled with a low-temperature hydrothermal method for ZnCdS (ZCS) incorporation. The resulting In2O3/In2S3-ZCS photocatalyst was proved to be highly efficient in converting N2 to NH3 under mild conditions, eliminating the need for sacrificial agents or precious metal catalysts. Notably, the NH4+ yield of In2O3/In2S3-0.5ZCS reached a significant level of 71.2 µmol g-1 h-1, which was 10.47 times higher than that of In2O3 (6.8 µmol g-1 h-1) and 3.22 times higher than that of In2O3/In2S3 (22.1 µmol g-1 h-1). This outstanding performance can be attributed to the ternary heterojunction configuration, which significantly extends the lifetime of photogenerated carriers and enhances the spatial separation of electrons and holes. The synergistic interplay between CdZnS, In2S3, and In2O3 in the heterojunction facilitates electron transport, thereby boosting the rate of the photocatalytic nitrogen fixation reaction. Our study not only validates the efficacy of ternary heterojunctions in photocatalytic nitrogen fixation but also offers valuable insights for the design and construction of such catalysts for future applications.

Mercury sources, transport, and transformation in rainfall-runoff processes: Mercury isotope approach.

Mercury (Hg) in runoff water poses significant ecological risks to aquatic ecosystems that can affect organisms. However, accurately identifying the sources and transformation processes of Hg in runoff water is challenging due to complex natural conditions. This study provides a comprehensive investigation of Hg dynamics in water from rainfall to runoff. The Hg isotope fractionation in water was characterized, which allows accurate quantification of Hg sources, transport, and transformations in rainfall-runoff processes. Δ200Hg and corrected Δ199Hg values can serve as reliable tracers for identifying Hg sources in the runoff water and the variation of δ202Hg can be explained by Hg transformation processes. During runoff migration processes, Hg from rainfall is rapidly absorbed on the land surface, while terrestrial Hg entering the water by the dissolution process becomes the primary component of dissolved mercury (DHg). Besides the dissolution and adsorption, microbial Hg(II) reduction and demethylation of MeHg were dominant processes for DHg in the runoff water that flows through the rice paddies, while photochemical Hg(II) reduction was the dominant process for DHg in the runoff water with low water exchange rates. Particulate Hg (PHg) in runoff water is dominantly originated by the terrestrial material and derived from the dissolution and adsorption process. Tracking sources and transformations of Hg in runoff water during the rainfall-runoff process provides a basis for studying Hg pollution in larger water bodies under complex environmental factors.

Baicalin protects against hepatocyte injury caused by aflatoxin B1 via the TP53-related ferroptosis Pathway.

OBJECTIVE: Baicalin has antioxidative, antiviral, and anti-inflammatory properties. However, its ability to alleviate oxidative stress (OS) and DNA damage in liver cells exposed to aflatoxin B1 (AFB1), a highly hepatotoxic compound, remains uncertain. In this study, the protective effects of baicalin on AFB1-induced hepatocyte injury and the mechanisms underlying those effects were investigated. METHODS: Stable cell lines expressing CYP3A4 were established using lentiviral vectors to assess oxidative stress levels by conducting assays to determine the content of reactive oxygen species (ROS), malondialdehyde (MDA), and superoxide dismutase (SOD). Additionally, DNA damage was evaluated by 8-hydroxy-2-deoxyguanosine (8-OHdG) and comet assays. Transcriptome sequencing, molecular docking, and in vitro experiments were conducted to determine the mechanisms underlying the effects of baicalin on AFB1-induced hepatocyte injury. In vivo, a rat model of hepatocyte injury induced by AFB1 was used to evaluate the effects of baicalin. RESULTS: In vitro, baicalin significantly attenuated AFB1-induced injury caused due to OS, as determined by a decrease in ROS, MDA, and SOD levels. Baicalin also considerably decreased AFB1-induced DNA damage in hepatocytes. This protective effect of baicalin was found to be closely associated with the TP53-mediated ferroptosis pathway. To elaborate, baicalin physically interacts with P53, leading to the suppression of the expression of GPX4 and SLC7A11, which in turn inhibits ferroptosis. In vivo findings showed that baicalin decreased DNA damage and ferroptosis in AFB1-treated rat liver tissues, as determined by a decrease in the expression of γ-H2AX and an increase in GPX4 and SLC7A11 levels. Overexpression of TP53 weakened the protective effects of baicalin. CONCLUSIONS: Baicalin can alleviate AFB1-induced OS and DNA damage in liver cells via the TP53-mediated ferroptosis pathway. In this study, a theoretical foundation was established for the use of baicalin in protecting the liver from the toxic effects of AFB1.

DPF2 overexpression correlates with immune infiltration and dismal prognosis in hepatocellular carcinoma.

Background: Double plant homeodomain finger 2 (DPF2), belonging to the d4 family of structural domains, has been associated with various human malignancies. However, its impact on hepatocellular carcinoma (HCC) remains unclear. The objective of this study is to elucidate the role of DPF2 in the diagnosis and prognosis of HCC. Methods: DPF2 gene expression in HCC and adjacent tissues was analyzed using Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, validated by immunohistochemical staining of Guangxi specimens and data from the Human Protein Atlas (HPA). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genome (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to identify DPF2's potential pathways and functions in HCC. DPF2's mutation and methylation statuses were assessed via cBioPortal and MethSurv. The association between DPF2 and immune infiltration was investigated by TIMER. The prognostic value of DPF2 in HCC was established through Kaplan-Meier and Cox regression analyses. Results: DPF2 levels were significantly higher in HCC than normal tissues (p<0.001), correlating with more severe HCC features (p<0.05). Higher DPF2 expression predicted poorer overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). DPF2 involvement was noted in critical signaling pathways including the cell cycle and Wnt. It also correlated with T helper cells, Th2 cells, and immune checkpoints like CTLA-4, PD-1, and PD-L1. Conclusion: High DPF2 expression, associated with poor HCC prognosis, may disrupt tumor immune balance and promote immune evasion. DPF2 could potentially be utilized as a biomarker for diagnosing and prognosticating hepatocellular carcinoma.

Pt(IV) complexes loaded hollow copper sulfide nanoparticles for tumor chemo/photothermal/photodynamic therapy.

Hollow CuS nanoparticles can achieve photothermal and photodynamic therapy (PDT) in tumor treatment. However, excessive GSH in the tumor cells will consume the reactive oxygen species produced by PDT and reduce the PDT effect. Cisplatin is a broad-spectrum antineoplastic drug that can be used in a variety of tumor treatments. However, cisplatin is cytotoxic to normal cells while it kills tumor cells. Therefore, we construct Pt(IV) complexes loaded hollow CuS nanoparticles to attenuate the toxicity of cisplatin and enhance the PDT effect of the hollow CuS nanoparticles. The nanoparticles were proved to be able to accumulate around the tumor site through the enhanced permeability and retention (EPR) effect to achieve a synergistic chemo/photothermal/photodynamic therapy.

Ephedra sinica polysaccharide regulate the anti-inflammatory immunity of intestinal microecology and bacterial metabolites in rheumatoid arthritis.

Introduction: Ephedra sinica polysaccharide (ESP) exerts substantial therapeutic effects on rheumatoid arthritis (RA). However, the mechanism through which ESP intervenes in RA remains unclear. A close correlation has been observed between enzymes and derivatives in the gut microbiota and the inflammatory immune response in RA. Methods: A type II collagen-induced arthritis (CIA) mice model was treated with Ephedra sinica polysaccharide. The therapeutic effect of ESP on collagen-induced arthritis mice was evaluated. The anti-inflammatory and cartilage-protective effects of ESP were also evaluated. Additionally, metagenomic sequencing was performed to identify changes in carbohydrate-active enzymes and resistance genes in the gut microbiota of the ESP-treated CIA mice. Liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry were performed to observe the levels of serum metabolites and short-chain fatty acids in the gut. Spearman's correlational analysis revealed a correlation among the gut microbiota, antibiotic-resistance genes, and microbiota-derived metabolites. Results: ESP treatment significantly reduced inflammation levels and cartilage damage in the CIA mice. It also decreased the levels of pro-inflammatory cytokines interleukin (IL)-6, and IL-1-ß and protected the intestinal mucosal epithelial barrier, inhibiting inflammatory cell infiltration and mucosal damage. Here, ESP reduced the TLR4, MyD88, and TRAF6 levels in the synovium, inhibited the p65 expression and pp65 phosphorylation in the NF-κB signaling pathway, and blocked histone deacetylase (HDAC1 and HDAC2) signals. ESP influenced the gut microbiota structure, microbial carbohydrate-active enzymes, and microbial resistance related to resistance genes. ESP increased the serum levels of L-tyrosine, sn-glycero-3-phosphocholine, octadecanoic acid, N-oleoyl taurine, and decreased N-palmitoyl taurine in the CIA mice. Conclusion: ESP exhibited an inhibitory effect on RA. Its action mechanism may be related to the ability of ESP to effectively reduce pro-inflammatory cytokines levels, protect the intestinal barrier, and regulate the interaction between mucosal immune systems and abnormal local microbiota. Accordingly, immune homeostasis was maintained and the inhibition of fibroblast-like synoviocyte (FLS) proliferation through the HDAC/TLR4/NF-κB pathway was mediated, thereby contributing to its anti-inflammatory and immune-modulating effects.

Dementia and metabolic syndrome: a bibliometric analysis.

Background: Dementia is a progressive neurodegenerative condition, while metabolic syndrome (MetS) is characterized by a combination of metabolic abnormalities such as hypertension, high blood sugar, and obesity. There exists a connection and overlap between the two conditions in certain aspects, and both are influenced to varying degrees by the process of aging. This study presents an overview of the current research landscape regarding dementia and MetS through bibliometric analysis. Methods: A systematic search was conducted to retrieve relevant literature on dementia and MetS published between 1 January 2000, and 30 November 2023, from the Web of Science Core Collection database. Various bibliometric tools, including VOSviewer, CiteSpace, and the R software package "bibliometrix," were utilized for analysis. Results: A total of 717 articles were identified, showing an upward trend in annual publications. Leading contributors included the United States, Italy, and China, with institutions such as the University of California System at the forefront. The Journal of Alzheimer's Disease emerged as the top publisher, while research published in Neurology garnered significant citations. Noteworthy authors encompassed Panza, Francesco; Frisardi, Vincenza; and Feldman, Eva L, with Kristine Yaffe being the most cited author (280 citations). Recent studies have focused on themes like "gut microbiota," "neuroinflammation," "fatty acids," and "microglia." Conclusion: This bibliometric analysis summarizes the foundational knowledge structure in the realm of dementia and MetS from 2000 to 2023. By highlighting current research frontiers and trending topics, this analysis serves as a valuable reference for researchers in the field.

A quadrivalent recombinant influenza Hemagglutinin vaccine induced strong protective immune responses in animal models.

Globally, influenza poses a substantial threat to public health, serving as a major contributor to both morbidity and mortality. The current vaccines for seasonal influenza are not optimal. A novel recombinant hemagglutinin (rHA) protein-based quadrivalent seasonal influenza vaccine, SCVC101, has been developed. SCVC101-S contains standard dose protein (15µg of rHA per virus strain) and an oil-in-water adjuvant, CD-A, which enhances the immunogenicity and cross-protection of the vaccine. Preclinical studies in mice, rats, and rhesus macaques demonstrate that SCVC101-S induces robust humoral and cellular immune responses, surpassing those induced by commercially available vaccines. Notably, a single injection with SCVC101-S can induce a strong immune response in macaques, suggesting the potential for a standard-dose vaccination with a recombinant protein influenza vaccine. Furthermore, SCVC101-S induces cross-protection immune responses against heterologous viral strains, indicating broader protection than current vaccines. In conclusion, SCVC101-S has demonstrated safety and efficacy in preclinical settings and warrants further investigation in human clinical trials. Its potential as a valuable addition to the vaccines against seasonal influenza, particularly for the elderly population, is promising.

Emergence of Erythromycin-Resistant and Pertactin- and Filamentous Hemagglutinin-Deficient Bordetella pertussis Strains - Beijing, China, 2022-2023.

What is already known about this topic?: Pertussis has reemerged as a significant public health threat, primarily due to variations in Bordetella pertussis strains, antimicrobial resistance, and vaccine evasion. What is added by this report?: All isolated strains were identified as ptxA1/ptxC2/ptxP3/prn150/fim2-1/fim3-1/fhaB1/tcfA2 type and exhibited resistance to erythromycin. Two strains showed a deficiency in Fha, thirty in Prn, and one strain exhibited multiple immunogen deficiencies. What are the implications for public health practice?: The emergence and spread of immunogen-deficient strains likely result from prolonged vaccine selection pressure, posing challenges to the efficacy of pertussis vaccines. Additionally, the ongoing dissemination of ptxP3 strains with high-level macrolide resistance presents a significant obstacle to clinical treatment strategies.

Clinical domain knowledge-derived template improves post hoc AI explanations in pneumothorax classification.

OBJECTIVE: Pneumothorax is an acute thoracic disease caused by abnormal air collection between the lungs and chest wall. Recently, artificial intelligence (AI), especially deep learning (DL), has been increasingly employed for automating the diagnostic process of pneumothorax. To address the opaqueness often associated with DL models, explainable artificial intelligence (XAI) methods have been introduced to outline regions related to pneumothorax. However, these explanations sometimes diverge from actual lesion areas, highlighting the need for further improvement. METHOD: We propose a template-guided approach to incorporate the clinical knowledge of pneumothorax into model explanations generated by XAI methods, thereby enhancing the quality of the explanations. Utilizing one lesion delineation created by radiologists, our approach first generates a template that represents potential areas of pneumothorax occurrence. This template is then superimposed on model explanations to filter out extraneous explanations that fall outside the template's boundaries. To validate its efficacy, we carried out a comparative analysis of three XAI methods (Saliency Map, Grad-CAM, and Integrated Gradients) with and without our template guidance when explaining two DL models (VGG-19 and ResNet-50) in two real-world datasets (SIIM-ACR and ChestX-Det). RESULTS: The proposed approach consistently improved baseline XAI methods across twelve benchmark scenarios built on three XAI methods, two DL models, and two datasets. The average incremental percentages, calculated by the performance improvements over the baseline performance, were 97.8% in Intersection over Union (IoU) and 94.1% in Dice Similarity Coefficient (DSC) when comparing model explanations and ground-truth lesion areas. We further visualized baseline and template-guided model explanations on radiographs to showcase the performance of our approach. CONCLUSIONS: In the context of pneumothorax diagnoses, we proposed a template-guided approach for improving model explanations. Our approach not only aligns model explanations more closely with clinical insights but also exhibits extensibility to other thoracic diseases. We anticipate that our template guidance will forge a novel approach to elucidating AI models by integrating clinical domain expertise.

The influence of crystal facet on the catalytic performance of MOFs-derived NiO with different morphologies for the total oxidation of propane: The defect engineering dominated by solvent regulation effect.

Crystal facet and defect engineering are crucial for designing heterogeneous catalysts. In this study, different solvents were utilized to generate NiO with distinct shapes (hexagonal layers, rods, and spheres) using nickel-based metal-organic frameworks (MOFs) as precursors. It was shown that the exposed crystal facets of NiO with different morphologies differed from each other. Various characterization techniques and density functional theory (DFT) calculations revealed that hexagonal-layered NiO (NiO-L) possessed excellent low-temperature reducibility and oxygen migration ability. The (111) crystal plane of NiO-L contained more lattice defects and oxygen vacancies, resulting in enhanced propane oxidation due to its highest O2 adsorption energy. Furthermore, the higher the surface active oxygen species and surface oxygen vacancy concentrations, the lower the C-H activation energy of the NiO catalyst and hence the better the catalytic activity for the oxidation of propane. Consequently, NiO-L exhibited remarkable catalytic activity and good stability for propane oxidation. This study provided a simple strategy for controlling NiO crystal facets, and demonstrated that the oxygen defects could be more easily formed on NiO(111) facets, thus would be beneficial for the activation of C-H bonds in propane. In addition, the results of this work can be extended to the other fields, such as propane oxidation to propene, fuel cells, and photocatalysis.

Hallmarks of tumor-experienced T cells are absent in multiple myeloma patients from diagnosis through maintenance therapy.

Dysregulation of the bone marrow (BM) niche in multiple myeloma (MM) alters the composition and state of resident immune cells, potentially impeding anti-tumor immunity. One common mechanism of immune inhibition in solid tumors is the induction of exhaustion in tumor-specific T cells. However, the extent of T cell tumor recognition and exhaustion is not well-characterized in MM. As the specific mechanisms of immune evasion are critical for devising effective therapeutic strategies, we deeply profiled the CD8+ T cell compartment of newly-diagnosed MM (NDMM) patients for evidence of tumor reactivity and T cell exhaustion. We applied single-cell multi-omic sequencing and antigen-specific mass cytometry to longitudinal BM and peripheral blood (PB) samples taken from timepoints spanning from diagnosis through induction therapy, autologous stem cell transplant (ASCT), and maintenance therapy. We identified an exhausted-like population that lacked several canonical exhaustion markers, was not significantly enriched in NDMM patients, and consisted of small, nonpersistent clones. We also observed an activated population with increased frequency in the PB of NDMM patients exhibiting phenotypic and clonal features consistent with homeostatic, antigen-nonspecific activation. However, there was no evidence of "tumor-experienced" T cells displaying hallmarks of terminal exhaustion and/or tumor-specific activation/expansion in NDMM patients at any timepoint.

Neferine inhibits BMECs pyroptosis and maintains blood-brain barrier integrity in ischemic stroke by triggering a cascade reaction of PGC-1α.

Blood-brain barrier disruption is a critical pathological event in the progression of ischemic stroke (IS). Most studies regarding the therapeutic potential of neferine (Nef) on IS have focused on neuroprotective effect. However, whether Nef attenuates BBB disruption during IS is unclear. We here used mice underwent transient middle cerebral artery occlusion (tMCAO) in vivo and bEnd.3 cells exposed to oxygen-glucose deprivation/reoxygenation (OGD/R) injury in vitro to simulate cerebral ischemia. We showed that Nef reduced neurobehavioral dysfunction and protected brain microvascular endothelial cells and BBB integrity. Molecular docking, short interfering (Si) RNA and plasmid transfection results showed us that PGC-1α was the most binding affinity of biological activity protein for Nef. And verification experiments were showed that Nef upregulated PGC-1α expression to reduce mitochondrial oxidative stress and promote TJ proteins expression, further improves the integrity of BBB in mice. Intriguingly, our study showed that neferine is a natural PGC-1α activator and illustrated the mechanism of specific binding site. Furthermore, we have demonstrated Nef reduced mitochondria oxidative damage and ameliorates endothelial inflammation by inhibiting pyroptosis to improve BBB permeability through triggering a cascade reaction of PGC-1α via regulation of PGC-1α/NLRP3/GSDMD signaling pathway to maintain the integrity of BBB in ischemia/reperfusion injury.

Understanding the dynamics of TKI-induced changes in the tumor immune microenvironment for improved therapeutic effect.

BACKGROUND: The dynamic interplay between tyrosine kinase inhibitors (TKIs) and the tumor immune microenvironment (TME) plays a crucial role in the therapeutic trajectory of non-small cell lung cancer (NSCLC). Understanding the functional dynamics and resistance mechanisms of TKIs is essential for advancing the treatment of NSCLC. METHODS: This study assessed the effects of short-term and long-term TKI treatments on the TME in NSCLC, particularly targeting epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) mutations. We analyzed changes in immune cell composition, cytokine profiles, and key proteins involved in immune evasion, such as laminin subunit γ-2 (LAMC2). We also explored the use of aspirin as an adjunct therapy to modulate the TME and counteract TKI resistance. RESULTS: Short-term TKI treatment enhanced T cell-mediated tumor clearance, reduced immunosuppressive M2 macrophage infiltration, and downregulated LAMC2 expression. Conversely, long-term TKI treatment fostered an immunosuppressive TME, contributing to drug resistance and promoting immune escape. Differential responses were observed among various oncogenic mutations, with ALK-targeted therapies eliciting a stronger antitumor immune response compared with EGFR-targeted therapies. Notably, we found that aspirin has potential in overcoming TKI resistance by modulating the TME and enhancing T cell-mediated tumor clearance. CONCLUSIONS: These findings offer new insights into the dynamics of TKI-induced changes in the TME, improving our understanding of NSCLC challenges. The study underscores the critical role of the TME in TKI resistance and suggests that adjunct therapies, like aspirin, may provide new strategies to enhance TKI efficacy and overcome resistance.

Investigation and Prediction of Nano-Silver Line Quality upon Various Process Parameters in Inkjet Printing Process Based on an Experimental Method.

As an emerging additive manufacturing technology, inkjet printing has been increasingly applied in microelectronics field. However, due to the impacting and rebounding behaviors of conductive ink droplets impinging onto flat substrates, it is challenging to fabricate conductive lines with desired quality, such as suitable line width and line thickness, and matching resistance when it is used for interconnecting multifarious electronic components if there is not a proper configuration of operating parameters. To address this research gap, this article aims to investigate the effect of process parameters on the quality of conductive lines, including the platform temperature, printing speed, number of layers, and delay time (droplet interarrival time), are selected to conduct a full factorial experiment. First, the approximate parameter ranges for ensuring the continuity of conductive lines are determined. Second, this study analyzes the interactive effect among process parameters on line quality. Third, an artificial neural network (ANN) is constructed to predict the quality of printed lines. Results show that the line width does not increase with an increased number of layers, while the line thickness shows an increasing trend. The low resistance and high aspect ratio of printed line are achieved by printing 5 layers with the platform temperature of 70°C, the delay time of 12.2 ms, and the printing speed of 1139.39 mm/min. Moreover, the ANN model can be used to predict line width and line thickness with excellent performance, except for the resistance due to the irregular line edge. This study provides a useful guide for the selection of appropriate printing parameters to realize a diverse range of quality properties for 3D printed conductive lines in integrated circuits.

Synthesis and Application of Salicylhydrazone Probes with High Selectivity for Rapid Detection of Cu2.

Using the aldehyde amine condensation procedure and the triphenylamine group as the skeleton structure, the new triphenylamine-aromatic aldehyde-succinylhydrazone probe molecule DHBYMH was created. A newly created acylhydrazone probe was structurally characterized by mass spectrometry (MS), NMR, and infrared spectroscopy (FTIR). Fluorescence and UV spectroscopy were used to examine DHBYMH's sensing capabilities for metal ions. Notably, DHBYMH achieved a detection limit of 1.62 × 10-7 M by demonstrating exceptional selectivity and sensitivity towards Cu2+ ions in an optimum sample solvent system (DMSO/H2O, (v/v = 7/3); pH = 7.0; cysteine (Cys) concentration: 1 × 10-4 M). NMR titration, high-resolution mass spectrometry analysis, and DFT computation were used to clarify the response mechanism. Ultimately, predicated on DHBYMH's reversible identification of Cu2+ ions in the presence of EDTA, a molecular logic gate was successfully designed.

Rolling Bearing Remaining Useful Life Prediction Based on CNN-VAE-MBiLSTM.

Ensuring precise prediction of the remaining useful life (RUL) for bearings in rolling machinery is crucial for preventing sudden machine failures and optimizing equipment maintenance strategies. Since the significant interference encountered in real industrial environments and the high complexity of the machining process, accurate and robust RUL prediction of rolling bearings is of tremendous research importance. Hence, a novel RUL prediction model called CNN-VAE-MBiLSTM is proposed in this paper by integrating advantages of convolutional neural network (CNN), variational autoencoder (VAE), and multiple bi-directional long short-term memory (MBiLSTM). The proposed approach includes a CNN-VAE model and a MBiLSTM model. The CNN-VAE model performs well for automatically extracting low-dimensional features from time-frequency spectrum of multi-axis signals, which simplifies the construction of features and minimizes the subjective bias of designers. Based on these features, the MBiLSTM model achieves a commendable performance in the prediction of RUL for bearings, which independently captures sequential characteristics of features in each axis and further obtains differences among multi-axis features. The performance of the proposed approach is validated through an industrial case, and the result indicates that it exhibits a higher accuracy and a better anti-noise capacity in RUL predictions than comparable methods.

Fabrication of a MXene-based shape-memory hydrogel and its application in the wound repair of skin.

Wound dressings can generally complete hemostasis and provide temporary protection after skin damage. Herein, a MXene-based hydrogel was prepared from MXene, gelatin, poly(ethylene glycol)diacrylate (PEGDA) and N,N'-methylenebis(acrylamide) (HEAA) to prepare wound-dressing hydrogels for skin repair. HEAA and PEGDA crosslink polymerization formed the first layer of the network. Hydrogen bonds between MXene, PHEAA, and gelatin formed the second layer of the network. To make the hydrogel more suitable for skin repair, the mechanical properties of the hybrid hydrogel were adjusted. The MXene-based hydrogel could recover its original shape in 16 s upon immersion in water or for a few minutes under light irradiation. The obtained hydrogel showed good photothermal properties upon light irradiation (808 nm, 1 W cm-2) for 20 s, and its temperature on the surface could reach 86.4 °C. Due to its good photothermal properties, this MXene-based hydrogel was suitable for skin repair.