Frontiers in Immunology最新文献

Background: A bibliometric and visual analysis of articles related to glioblastoma metabolism was conducted to reveal the dynamics of scientific development and to assist researchers in gaining a global perspective when exploring hotspots and trends.

Methods: The Web of Science Core Collection (WoSCC) was employed to search, screen, and download articles about glioblastoma metabolism published between 2014 and 2024. The relevant literature was analyzed using CiteSpace, VOSviewer and Microsoft Excel.

Results: A total of 729 articles were included for bibliometric analysis between 2014 and 2024, and the number of articles published each year showed an overall increasing trend, except for a decrease in the number of articles published in 2018 compared to 2017. Collaboration network analysis showed that the United States, Germany and China are influential countries in this field, with a high number of articles published, citations and collaborations with other countries. The journal with the largest number of published articles is the International Journal of Molecular Sciences. Mischel PS is the most prolific author with 14 articles, and Guo DL received the most citations with 104 citations. Keyword analysis of the literature showed that the "Warburg effect" achieved the highest burst intensity, and "central nervous system", "classification" and "fatty acids" showed stronger citation bursts in 2024, indicating that they are still popular topics so far.

Conclusion: This article elucidates the research trends and focal points in the field of glioblastoma metabolism, furnishes invaluable insights into the historical and contemporary status of this field, and offers guidance for future research. Further research into glioblastoma metabolism will undoubtedly yield new insights that will inform the diagnosis and treatment of this disease.

The genesis and progression of tumors are multifaceted processes influenced by genetic mutations within the tumor cells and the dynamic interplay with their surrounding milieu, which incessantly impacts the course of cancer. The tumor microenvironment (TME) is a complex and dynamic entity that encompasses not only the tumor cells but also an array of non-cancerous cells, signaling molecules, and the extracellular matrix. This intricate network is crucial in tumor progression, metastasis, and response to treatments. The TME is populated by diverse cell types, including immune cells, fibroblasts, endothelial cells, alongside cytokines and growth factors, all of which play roles in either suppressing or fostering tumor growth. Grasping the nuances of the interactions within the TME is vital for the advancement of targeted cancer therapies. Consequently, a thorough understanding of the alterations of TME and the identification of upstream regulatory targets have emerged as a research priority. NF-κB transcription factors, central to inflammation and innate immunity, are increasingly recognized for their significant role in cancer onset and progression. This review emphasizes the crucial influence of the NF-κB signaling pathway within the TME, underscoring its roles in the development and advancement of cancer. By examining the interactions between NF-κB and various components of the TME, targeting the NF-κB pathway appears as a promising cancer treatment approach.

Background: The incidence of breast cancer remains high and severely affects human health. However, given the heterogeneity of tumor cells, identifying additional characteristics of breast cancer cells is essential for accurate treatment.

Purpose: This study aimed to analyze the relevant characteristics of matrix genes in breast cancer through the multigroup data of a breast cancer multi-database.

Methods: The related characteristics of matrix genes in breast cancer were analyzed using multigroup data from the breast cancer multi database in the Cancer Genome Atlas, and the differential genes of breast cancer matrix genes were identified using the elastic net penalty logic regression method. The risk characteristics of matrix genes in breast cancer were determined, and matrix gene expression in different breast cancer cells was evaluated using real-time fluorescent quantitative polymerase chain reaction (PCR). A consensus clustering algorithm was used to identify the biological characteristics of the population based on the matrix molecular subtypes in breast cancer, followed by gene mutation, immune correlation, pathway, and ligand-receptor analyses.

Results: This study reveals the genetic characteristics of cell matrix related to breast cancer. It is found that 18.1% of stromal genes are related to the prognosis of breast cancer, and these genes are mostly concentrated in the biological processes related to metabolism and cytokines in protein. Five different matrix-related molecular subtypes were identified by using the algorithm, and it was found that the five molecular subtypes were obviously different in prognosis, immune infiltration, gene mutation and drug-making gene analysis.

Conclusions: This study involved analyzing the characteristics of cell-matrix genes in breast cancer, guiding the precise prevention and treatment of the disease.

Introduction: The proteome profile of the female Tenualosa ilisha (Hamilton, 1822), a species of great ecological and economic importance, across various age groups was investigated to comprehend the functional dynamics of the serum proteome for conservation and aquaculture, as well as sustain the population.

Methods: Advanced liquid chromatography-tandem mass spectrometry LC-MS/MS-based proteomic data were analysed and submitted to the ProteomeXchange Consortium via PRIDE (PRoteomics IDEntifications database). Bioinformatics analysis of serum proteome have been done and it showed different proteins associated with GO Gene Ontology () terms, and the genes associated with enriched KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways (such as phagosome, mTOR, Apelin signalling pathways, herpes simplex virus) implicated in immune responses.

Results: The expression levels of important immunological proteins, such as those involved in cellular defence and inflammatory responses, were significantly different age-dependently. In this study, we annotated 952, 494, 415, and 282 proteins in year classes IV, III, II, and I Hilsa, respectively, and analysed their Protein-Protein Interaction (PPI) networks based on their functional characteristics. From year classes I to IV, new proteins appeared and were more than three-fold. Notably, class I hilsa displayed a lower abundance of proteins than class IV hilsa.

Discussion: This is the first study, to the best of our knowledge, to report the analysis of the serum proteome of hilsa at different developmental stages, and the results can help improve the understanding of the mechanisms underlying the different changes in protein enrichment during migration in hilsa. This analysis also offers crucial insights into the immune system for hilsa conservation and management.

Introduction: ER aminopeptidase 1 (ERAP1) is a polymorphic intracellular aminopeptidase with key roles in antigen presentation and adaptive immune responses. ERAP1 allotype 10 is highly protective toward developing some forms of autoimmunity and displays unusual functional properties, including very low activity versus some substrates.

Methods: To understand the molecular mechanisms that underlie the biology of allotype 10, we studied its enzymatic and biophysical properties focusing on its unique polymorphisms V349M and Q725R.

Results: Compared to ancestral allotype 1, allotype 10 is much less effective in trimming small substrates but presents allosteric kinetics that ameliorate activity differences at high substrate concentrations. Furthermore, it is inhibited by a transition-state analogue via a non-competitive mechanism and is much less responsive to an allosteric small-molecule modulator. It also presents opposite enthalpy, entropy, and heat capacity of activation compared to allotype 1, and its catalytic rate is highly dependent on viscosity. Polymorphisms V349M and Q725R significantly contribute to the lower enzymatic activity of allotype 10 for small substrates, especially at high substrate concentrations, influence the cooperation between the regulatory and active sites, and regulate viscosity dependence, likely by limiting product release.

Conclusions: Overall, our results suggest that allotype 10 is not just an inactive variant of ERAP1 but rather carries distinct enzymatic properties that largely stem from changes at positions 349 and 725. These changes affect kinetic and thermodynamic parameters that likely control rate-limiting steps in the catalytic cycle, resulting in an enzyme optimized for sparing small substrates and contributing to the homeostasis of antigenic epitopes in the ER.

Introduction: In patients with Hereditary Angioedema (HAE) related to primary C1 inhibitor deficiency (C1INH), the defective clearance of immune complexes and apoptotic materials along with impairment of normal humoral response potentially leads to autoimmunity. Few studies report evidence on autoimmune diseases in C1INH-HAE, but no large population studies focus on rare connective tissue diseases (RCTDs). We aim at evaluating for the first time prevalence and distribution of RCTDs - Systemic Lupus Erytematosus (SLE), primary Sjogren Syndrome (SjS), primary antiphospholipid syndrome (APS), Systemic Sclerosis (SSc), and mixed connective tissue diseases (MCTD) in a large Italian cohort of C1INH-HAE patients.

Methods: A multicenter observational study includes C1INH-HAE patients from ITACA Centers throughout Italy (time frame Sept 2023-March 2024). Inclusion criteria are i. a defined diagnosis of type I or type II C1INH-HAE; ii. age ≥15 years (puberty already occurred); iii. enrollment in the ITACA Registry. The diagnosis of SLE, primary SjS, primary APS, SSc, and MCTD are made in accordance with international classification criteria.

Results: Data are collected from a total of 855 C1INH-HAE patients referring to 15 ITACA Centers. Patients with concomitant RCTDs were 18/855 (2.1%) with F:M ratio 3.5 and a prevalent type I C1INH-HAE diagnosis (87.2%). A diagnosis of SLE results in 44.5% of cases (n=8) while the remaining diagnoses are primary SjS (22.2%, n=4), primary APS (16.6%, n=3), SSc (11.2%, n=2), and a single case of MCTD (5.5%). The female gender is prevalent in all the RCTDs. Patients on long term prophylaxis (LTP) are significantly prevalent in RCTDs group than in the whole C1INH-HAE population (p<0.01).

Conclusions: A relevant prevalence of RCTDs is documented in C1INH-HAE patients, mainly SLE. Patients with RCTDs are on LTP in a significant proportion supporting the idea of a bidirectional link between C1INH-HAE and autoimmunity.

Introduction: Respiratory syncytial virus (RSV) causes acute respiratory tract infection (ARTI) and reinfects adults throughout life, posing a risk for hospitalization in older adults (>60 years) with frailty and comorbidities.

Methods: To investigate serum and mucosal antibodies for protection against RSV infections, baseline serum samples were compared for RSV-pre- and -post-fusion (F) binding, and RSV-A2 neutralizing IgG antibodies between symptomatic RSV-ARTI (N = 30), non-RSV (RSV negative) ARTI (N = 386), and no ARTI (N = 338). Mucosal RSV-pre-F IgA and IgG levels, as well as serum RSV-G IgG antibodies, were analyzed to determine their association with protection from symptomatic RSV-ARTI in a subset study.

Results: Using a receiver operating characteristic (ROC) analysis, we established thresholds of 1.4- to 1.6-fold change (FC) for RSV-pre-F and -post-F, and RSV-A2 neutralizing IgG antibodies, respectively, enabling the identification of asymptomatic RSV cases with high sensitivity and specificity (>80% and >90%, respectively). As a result, serum RSV-pre-F, RSV-G IgG, and mucosal pre-F binding IgA antibodies showed correlations with protection against symptomatic RSV infection. RSV-pre-F IgG antibodies were correlated with protection from RSV infections irrespective of the symptoms.

Discussion: This study provides insights into antibody-mediated protection for symptomatic RSV infection in a community-dwelling older-adult population and establishes a threshold to identify asymptomatic RSV infection using a data-driven approach.

Artificial intelligence (AI) has meant a turning point in data analysis, allowing predictions of unseen outcomes with precedented levels of accuracy. In multiple sclerosis (MS), a chronic inflammatory-demyelinating condition of the central nervous system with a complex pathogenesis and potentially devastating consequences, AI-based models have shown promising preliminary results, especially when using neuroimaging data as model input or predictor variables. The application of AI-based methodologies to serum/blood and CSF biomarkers has been less explored, according to the literature, despite its great potential. In this review, we aimed to investigate and summarise the recent advances in AI methods applied to body fluid biomarkers in MS, highlighting the key features of the most representative studies, while illustrating their limitations and future directions.

In recent decades, nanotechnology has significantly advanced drug delivery systems, particularly in targeting subcellular organelles, thus opening new avenues for disease treatment. Mitochondria, critical for cellular energy and health, when dysfunctional, contribute to cancer, neurodegenerative diseases, and metabolic disorders. This has propelled the development of nanomedicines aimed at precise mitochondrial targeting to modulate their function, marking a research hotspot. This review delves into the recent advancements in mitochondrial-targeted nanotherapeutics, with a comprehensive focus on targeting strategies, nanocarrier designs, and their therapeutic applications. It emphasizes nanotechnology's role in enhancing drug delivery by overcoming biological barriers and optimizing drug design for specific mitochondrial targeting. Strategies exploiting mitochondrial membrane potential differences and specific targeting ligands improve the delivery and mitochondrial accumulation of nanomedicines. The use of diverse nanocarriers, including liposomes, polymer nanoparticles, and inorganic nanoparticles, tailored for effective mitochondrial targeting, shows promise in anti-tumor and neurodegenerative treatments. The review addresses the challenges and future directions in mitochondrial targeting nanotherapy, highlighting the need for precision, reduced toxicity, and clinical validation. Mitochondrial targeting nanotherapy stands at the forefront of therapeutic strategies, offering innovative treatment perspectives. Ongoing innovation and research are crucial for developing more precise and effective treatment modalities.