Unpaired MRI Super Resolution with Contrastive Learning

Magnetic resonance imaging (MRI) is crucial for enhancing diagnostic accuracy in clinical settings. However, the inherent long scan time of MRI restricts its widespread applicability. Deep learning-based image super-resolution (SR) methods exhibit promise in improving MRI resolution without additional cost. Due to lacking of aligned high-resolution (HR) and low-resolution (LR) MRI image pairs, unsupervised approaches are widely adopted for SR reconstruction with unpaired MRI images. However, these methods still require a substantial number of HR MRI images for training, which can be difficult to acquire. To this end, we propose an unpaired MRI SR approach that employs contrastive learning to enhance SR performance with limited HR training data. Empirical results presented in this study underscore significant enhancements in the peak signal-to-noise ratio and structural similarity index, even when a paucity of HR images is available. These findings accentuate the potential of our approach in addressing the challenge of limited HR training data, thereby contributing to the advancement of MRI in clinical applications

What Type of Social Support Is Important for Student Resilience During COVID-19? A Latent Profile Analysis

In the face of the sudden outbreak of coronavirus 2019 (COVID-19), some students showed resilience in coping with difficulties while some did not. While different types of students showed different levels of resilience, are there significant characteristics among students with similar levels of resilience? In this study, 3,454 students (aged 15–25 years) were surveyed to understand students' perceived social support-coping modes while investigating the demographic characteristics and mental health status of subclasses of different modes. We found that (1) in the two subgroups of students with extremely low and low levels of perceived social support, the source of students' perceived social support did not have a clear orientation; in the two subgroups with moderate and high levels of perceived social support, the most perceived emotional support was from family and friends, while the least perceived support was companionship from teachers, classmates, and relatives, and problems related to the dependability of friends and communication with family. (2) The degree of social support perceived by students is directly proportional to the coping tendency, i.e., as the degree of perceived social support increases, the proportion of students adopting active coping strategies increases while that of students adopting negative coping strategies decreases; thus, we concluded that high levels of emotional support from family and friends can increase students' tendency of adopting positive strategies to cope with difficulties, while problems related to the dependability of friends and communication with family decrease students' tendency of adopting positive coping strategies. (3) Gender had a significant impact on the extremely low and low levels of perceived social support-negative coping tendencies; these subgroups accounted for 34.6% of the total students. Gender showed no significant influence on other subgroups, a school type had no impact on the distribution of the subgroups. (4) The higher the degree of perceived social support, the lower is the degree of students' general anxiety, and the lower is the degree of impact by the COVID-19 pandemic. The subdivision of student groups allows us to design more targeted support programmes for students with different psychological characteristics to help them alleviate stress during the COVID-19 epidemic

Unraveling the antimicrobial potential of Lactiplantibacillus plantarum strains TE0907 and TE1809 sourced from Bufo gargarizans: advancing the frontier of probiotic-based therapeutics

IntroductionIn an era increasingly defined by the challenge of antibiotic resistance, this study offers groundbreaking insights into the antibacterial properties of two distinct Lactiplantibacillus plantarum strains, TE0907 and TE1809, hailing from the unique ecosystem of Bufo gargarizans. It uniquely focuses on elucidating the intricate components and mechanisms that empower these strains with their notable antibacterial capabilities.MethodsThe research employs a multi-omics approach, including agar diffusion tests to assess antibacterial efficacy and adhesion assays with HT-29 cells to understand the preliminary mechanisms. Additionally, gas chromatography-mass spectrometry (GC-MS) is employed to analyze the production of organic acids, notably acetic acid, and whole-genome sequencing is utilized to identify genes linked to the biosynthesis of antibiotics and bacteriocin-coding domains.ResultsThe comparative analysis highlighted the exceptional antibacterial efficacy of strains TE0907 and TE1809, with mean inhibitory zones measured at 14.97 and 15.98 mm, respectively. A pivotal discovery was the significant synthesis of acetic acid in both strains, demonstrated by a robust correlation coefficient (cor ≥ 0.943), linking its abundance to their antimicrobial efficiency. Genomic exploration uncovered a diverse range of elements involved in the biosynthesis of antibiotics similar to tetracycline and vancomycin and potential regions encoding bacteriocins, including Enterolysin and Plantaricin.ConclusionThis research illuminates the remarkable antibacterial efficacy and mechanisms intrinsic to L. plantarum strains TE0907 and TE1809, sourced from B. gargarizans. The findings underscore the strains' extensive biochemical and enzymatic armamentarium, offering valuable insights into their role in antagonizing enteric pathogens. These results lay down a comprehensive analytical foundation for the potential clinical deployment of these strains in safeguarding animal gut health, thereby enriching our understanding of the role of probiotic bacteria in the realm of antimicrobial interventions

Glycyrrhizic Acid for COVID-19: Findings of Targeting Pivotal Inflammatory Pathways Triggered by SARS-CoV-2

Background: Coronavirus disease 2019 (COVID-19) is now a worldwide public health crisis. The causative pathogen is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Novel therapeutic agents are desperately needed. Because of the frequent mutations in the virus and its ability to cause cytokine storms, targeting the viral proteins has some drawbacks. Targeting cellular factors or pivotal inflammatory pathways triggered by SARS-CoV-2 may produce a broader range of therapies. Glycyrrhizic acid (GA) might be beneficial against SARS-CoV-2 because of its anti-inflammatory and antiviral characteristics and possible ability to regulate crucial host factors. However, the mechanism underlying how GA regulates host factors remains to be determined.Methods: In our report, we conducted a bioinformatics analysis to identify possible GA targets, biological functions, protein-protein interactions, transcription-factor-gene interactions, transcription-factor-miRNA coregulatory networks, and the signaling pathways of GA against COVID-19.Results: Protein-protein interactions and network analysis showed that ICAM1, MMP9, TLR2, and SOCS3 had higher degree values, which may be key targets of GA for COVID-19. GO analysis indicated that the response to reactive oxygen species was significantly enriched. Pathway enrichment analysis showed that the IL-17, IL-6, TNF-α, IFN signals, complement system, and growth factor receptor signaling are the main pathways. The interactions of TF genes and miRNA with common targets and the activity of TFs were also recognized.Conclusions: GA may inhibit COVID-19 through its anti-oxidant, anti-viral, and anti-inflammatory effects, and its ability to activate the immune system, and targeted therapy for those pathways is a predominant strategy to inhibit the cytokine storms triggered by SARS-CoV-2 infection

Study of Influencing Factors and the Mechanism of Preparing Triazinedithiol Polymeric Nanofilms on Aluminum Surfaces

Triazinedithiol polymeric nanofilm was prepared on a pure aluminum surface by electrochemical polymerization of AF17N. The mechanism of the process was proposed and electrochemical polymerization parameters were investigated. The triazinedithiol polymeric nanofilm had notable lubricity, high dielectric property and superhydrophobic property due to the allyl and fluoro alkyl groups in the AF17N monomer. The chemical structure of poly (6-(N-allyl-1,1,2,2-tetrahydroperfluorodecyl)amino-1,3,5-triazine-2,4-dithiol monosodium) nanofilm (PAF17) was investigated by analysis of FT-IR spectra and X-ray photoelectron spectroscopy (XPS). The optimal conditions for the preparation process were based on the data of film weight and thickness. The optimal parameters of monomer concentration, electropolymerization time and temperature were 5 mM, 6 min and 15 °C, respectively. The electropolymerization mechanism was a radical polymerization reaction. It is expected that this technique will be applied in industrial fields for aluminum and aluminum alloy to achieve functional surfaces

The CircHAS2/RPL23/MMP9 Axis Facilitates Brain Tumor Metastasis

Background: Circular RNAs (circRNAs) regulate tumor development by interacting with microRNAs. However, limited research has been conducted on the roles of circRNAs in gliomas. Therefore, we sought to demonstrate the function and molecular mechanism of circHAS2 in gliomas. Methods: CircHAS2, hsa-miR-508-3p, RPL23, and MMP9 mRNA levels were assessed with qRT-PCR. RPL23 and MMP9 protein levels were determined with western blotting and immunohistochemical staining. Glioma cell migration and invasion were assessed with Transwell assays. The interaction between hsa-miR-508-3p and circHAS2 or RPL23 was predicted with RNAhybrid and miRanda, and confirmed through luciferase reporter assays. The effects of circHAS2 on glioma cells were demonstrated in a nude mouse orthotopic xenograft glioma model. Results: We computationally analyzed the differentially expressed circRNAs in glioma tissues by using the GEO database. The screening indicated that circHAS2 was located primarily in the cytoplasm. Functionally, silencing of circHAS2 inhibited glioma migration and invasion. Mechanically, hsa-miR-508-3p was identified as a downstream target of circHAS2. CircHAS2 was found to regulate RPL23 and influence MMP9 via hsa-miR-508-3p, thereby promoting glioma migration and invasion. Moreover, inhibition of circHAS2 impeded the progression of U87 glioma cells in vivo. Conclusion: CircHAS2 regulates RPL23 and subsequent MMP9 expression by sponging hsa-miR508-3p in glioma cells

Threshold conditions for curbing COVID‑19 with a dynamic zero‑case policy derived from 101 outbreaks in China

By 31 May 2022, original/Alpha, Delta and Omicron strains induced 101 outbreaks of COVID-19 in mainland China. Most outbreaks were cleared by combining non-pharmaceutical interventions (NPIs) with vaccines, but continuous virus variations challenged the dynamic zero-case policy (DZCP), posing questions of what are the prerequisites and threshold levels for success? And what are the independent effects of vaccination in each outbreak? Using a modified classic infectious disease dynamic model and an iterative relationship for new infections per day, the effectiveness of vaccines and NPIs was deduced, from which the independent effectiveness of vaccines was derived. There was a negative correlation between vaccination coverage rates and virus transmission. For the Delta strain, a 61.8% increase in the vaccination rate (VR) reduced the control reproduction number (CRN) by about 27%. For the Omicron strain, a 20.43% increase in VR, including booster shots, reduced the CRN by 42.16%. The implementation speed of NPIs against the original/Alpha strain was faster than the virus’s transmission speed, and vaccines significantly accelerated the DZCP against the Delta strain. The CRN ( Rc1 ) during the exponential growth phase and the peak time and intensity of NPIs were key factors affecting a comprehensive theoretical threshold condition for DZCP success, illustrated by contour diagrams for the CRN under different conditions. The DZCP maintained the Rc1 of 101 outbreaks below the safe threshold level, but the strength of NPIs was close to saturation especially for Omicron, and there was little room for improvement. Only by curbing the rise in the early stage and shortening the exponential growth period could clearing be achieved quickly. Strengthening China’s vaccine immune barrier can improve China’s ability to prevent and control epidemics and provide greater scope for the selection and adjustment of NPIs. Otherwise, there will be rapid rises in infection rates and an extremely high peak and huge pressure on the healthcare system, and a potential increase in excess mortality

Automatic Detection and Classification of Breast Tumors in Ultrasonic Images Using Texture and Morphological Features

Due to severe presence of speckle noise, poor image contrast and irregular lesion shape, it is challenging to build a fully automatic detection and classification system for breast ultrasonic images. In this paper, a novel and effective computer-aided method including generation of a region of interest (ROI), segmentation and classification of breast tumor is proposed without any manual intervention. By incorporating local features of texture and position, a ROI is firstly detected using a self-organizing map neural network. Then a modified Normalized Cut approach considering the weighted neighborhood gray values is proposed to partition the ROI into clusters and get the initial boundary. In addition, a regional-fitting active contour model is used to adjust the few inaccurate initial boundaries for the final segmentation. Finally, three textures and five morphologic features are extracted from each breast tumor; whereby a highly efficient Affinity Propagation clustering is used to fulfill the malignancy and benign classification for an existing database without any training process. The proposed system is validated by 132 cases (67 benignancies and 65 malignancies) with its performance compared to traditional methods such as level set segmentation, artificial neural network classifiers, and so forth. Experiment results show that the proposed system, which needs no training procedure or manual interference, performs best in detection and classification of ultrasonic breast tumors, while having the lowest computation complexity