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Ulcerative colitis is an immune-mediated inflammatory bowel disease characterized by recurrent diarrhea, abdominal pain, and mucous, pus, and bloody stools. Both Traditional Chinese Medicine and western medicine have their own strengths in the prevention and control of ulcerative colitis. There is an urgent need of developing effective combination of Traditional Chinese Medicine and western medicine therapy, as well as integrative nursing interventions, for the treatment of ulcerative colitis. By searching the literature at home and abroad, this paper summarized the current research status of Traditional Chinese Medicine and western medicine treatment in the diagnosis and treatment of UC and related clinical nursing practice, in order to provide a certain theoretical basis for clinical treatment and nursing of ulcerative colitis. (溃疡性结肠炎是由免疫介导的炎症性肠病, 临床症状为反复发作的腹泻、腹痛及黏液脓血便。中西医诊疗各有所长, 探索行之有效的中西医结合治疗和护理方法对提高溃疡性结肠炎疗效有着积极意义。本研究总结中西医诊疗溃疡性结肠炎的研究现况及临床护理进展, 以期为临床进一步提升溃疡性结肠炎的诊疗质量提供一定的理论依据。)

Bursting is a crucial form of firing in neurons, laden with substantial information. Studying it can aid in understanding the neural coding to identify human behavioral characteristics conducted by these neurons. However, the high-dimensionality of many neuron models imposes a difficult challenge in studying the generative mechanisms of bursting. On account of the high complexity and nonlinearity characteristic of these models, it becomes nearly impossible to theoretically study and analyze them. Thus, this paper proposed to address these issues by focusing on the midbrain dopamine neurons, serving as the central neuron model for the investigation of the bursting mechanisms and bifurcation behaviors exhibited by the neuron. In this study, we considered the dimensionality reduction of a high-dimensional neuronal model and analyzed the dynamical properties of the reduced system. To begin, for the original thirteen-dimensional model, using the correlation between variables, we reduced its dimensionality and obtained a simplified three-dimensional system. Then, we discussed the changing characteristics of the number of spikes within a burst by simultaneously varying two parameters. Finally, we studied the co-dimension-2 bifurcation in the reduced system and presented the bifurcation behavior near the Bogdanov-Takens bifurcation. [ABSTRACT FROM AUTHOR]

Interactions between proteins and glycans are critical to various biological processes. With databases of carbohydrate-interacting proteins and increasing amounts of structural data, the three-sided right-handed β-helix (RHBH) has emerged as a significant structural fold for glycan interactions. In this review, we provide an overview of the sequence, mechanistic, and structural features that enable the RHBH to interact with glycans. The RHBH is a prevalent fold that exists in eukaryotes, prokaryotes, and viruses associated with adhesin and carbohydrate-active enzyme (CAZyme) functions. An evolutionary trajectory analysis on structurally characterized RHBH-containing proteins shows that they likely evolved from carbohydrate-binding proteins with their carbohydrate-degrading activities evolving later. By examining three polysaccharide lyase and three glycoside hydrolase structures, we provide a detailed view of the modes of glycan binding in RHBH proteins. The 3-dimensional shape of the RHBH creates an electrostatically and spatially favorable glycan binding surface that allows for extensive hydrogen bonding interactions, leading to favorable and stable glycan binding. The RHBH is observed to be an adaptable domain capable of being modified with loop insertions and charge inversions to accommodate heterogeneous and flexible glycans and diverse reaction mechanisms. Understanding this prevalent protein fold can advance our knowledge of glycan binding in biological systems and help guide the efficient design and utilization of RHBH-containing proteins in glycobiology research. [ABSTRACT FROM AUTHOR]

Introduction: The objective of this study was to examine the utility of protein kinase N1 (PKN1) as a biomarker of cardiac surgery-associated AKI (CSA-AKI). Methods: A prospective cohort study of 110 adults undergoing on-pump cardiac surgery was conducted. The associations between post-operative PKN1 and CSA-AKI, AKI severity, need for renal replacement therapy (RRT), duration of AKI, length of ICU stay, and post-operative hospital stay were evaluated. Results: Patients were categorized into three groups according to PKN1 tertiles. The incidence of CSA-AKI in the third tertile was 3.4-fold higher than that in the first. PKN1 was an independent risk factor for CSA-AKI. The discrimination of PKN1 to CSA-AKI assessed by ROC curve indicated that the AUC was 0.70, and the best cutoff was 5.025 ng/mL. This group (>5.025 ng/mL) was more likely to develop CSA-AKI (p < 0.001). The combined AUC of EuroSCORE, aortic cross-clamp time, and PKN1 was 0.82 (p < 0.001). A higher level of PKN1 was related to increased need for RRT, longer duration of AKI, and length of ICU and post-operative hospital stays. Conclusions: PKN1 could be a potential biomarker for the prediction of CSA-AKI. The combination of PKN1, EuroSCORE, and aortic cross-clamp time was likely to predict the occurrence of CSA-AKI. [ABSTRACT FROM AUTHOR]

AbstractMelanoma poses a challenge in oncology because of its aggressive nature and limited treatment modalities. The tumour microenvironment (TME) in melanoma contains unique properties such as an immunosuppressive and high-density environment, unusual vasculature, and a high number of stromal and immunosuppressive cells. In recent years, numerous experiments have focused on boosting the immune system to effectively remove malignant cells. Adjuvants, consisting of phytochemicals, toll-like receptor (TLR) agonists, and cytokines, have shown encouraging results in triggering antitumor immunity and augmenting the therapeutic effectiveness of anticancer therapy. These adjuvants can stimulate the maturation of dendritic cells (DCs) and infiltration of cytotoxic CD8+ T lymphocytes (CTLs). Furthermore, nanocarriers can help to deliver immunomodulators and antigens directly to the tumour stroma, thereby improving their efficacy against malignant cells. The remodelling of melanoma TME utilising phytochemicals, agonists, and other adjuvants can be combined with current modalities for improving therapy outcomes. This review article explores the potential of adjuvants, drugs, and their nanoformulations in enhancing the anticancer potency of macrophages, CTLs, and natural killer (NK) cells. Additionally, the capacity of these agents to repress the function of immunosuppressive components of melanoma TME, such as immunosuppressive subsets of macrophages, stromal and myeloid cells will be discussed. [ABSTRACT FROM AUTHOR]

Objectives: The authors aimed to assess the performance of a deep learning (DL) model, based on a combination of ultrasound (US) and mammography (MG) images, for predicting malignancy in breast lesions categorized as Breast Imaging Reporting and Data System (BI-RADS) US 4A in diagnostic patients with dense breasts., Methods: A total of 992 patients were randomly allocated into the training cohort and the test cohort at a proportion of 4:1. Another, 218 patients were enrolled to form a prospective validation cohort. The DL model was developed by incorporating both US and MG images. The predictive performance of the combined DL model for malignancy was evaluated by sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The combined DL model was then compared to a clinical nomogram model and to the DL model trained using US image only and to that trained MG image only., Results: The combined DL model showed satisfactory diagnostic performance for predicting malignancy in breast lesions, with an AUC of 0.940 (95% CI: 0.874-1.000) in the test cohort, and an AUC of 0.906 (95% CI: 0.817-0.995) in the validation cohort, which was significantly higher than the clinical nomogram model, and the DL model for US or MG alone ( P <0.05)., Conclusions: The study developed an objective DL model combining both US and MG imaging features, which was proven to be more accurate for predicting malignancy in the BI-RADS US 4A breast lesions of patients with dense breasts. This model may then be used to more accurately guide clinicians' choices about whether performing biopsies in breast cancer diagnosis., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Phage therapy, reemerging as a promising approach to counter antimicrobial-resistant infections, relies on a comprehensive understanding of the specificity of individual phages. Yet the significant diversity within phage populations presents a considerable challenge. Currently, there is a notable lack of tools designed for large-scale characterization of phage receptor-binding proteins, which are crucial in determining the phage host range., Results: In this study, we present SpikeHunter, a deep learning method based on the ESM-2 protein language model. With SpikeHunter, we identified 231,965 diverse phage-encoded tailspike proteins, a crucial determinant of phage specificity that targets bacterial polysaccharide receptors, across 787,566 bacterial genomes from 5 virulent, antibiotic-resistant pathogens. Notably, 86.60% (143,200) of these proteins exhibited strong associations with specific bacterial polysaccharides. We discovered that phages with identical tailspike proteins can infect different bacterial species with similar polysaccharide receptors, underscoring the pivotal role of tailspike proteins in determining host range. The specificity is mainly attributed to the protein's C-terminal domain, which strictly correlates with host specificity during domain swapping in tailspike proteins. Importantly, our dataset-driven predictions of phage-host specificity closely match the phage-host pairs observed in real-world phage therapy cases we studied., Conclusions: Our research provides a rich resource, including both the method and a database derived from a large-scale genomics survey. This substantially enhances understanding of phage specificity determinants at the strain level and offers a valuable framework for guiding phage selection in therapeutic applications., (Published by Oxford University Press on behalf of GigaScience 2024.)