Search

Intrahepatic cholangiocarcinoma (iCCA) is an aggressive liver malignancy with limited treatment options and a dismal prognosis. The tumor immune microenvironment (TIME) is crucial for iCCA progression, yet its comprehensive characterization remains incomplete. This study utilized mass cytometry by time of flight (CyTOF) to comprehensively analyze immune cell populations in fresh iCCA tumor samples and adjacent peritumor liver tissues. Notably, NK cell percentages significantly decreased in iCCA lesions compared to peritumor liver tissues. Conversely, an enrichment of immunosuppressive CD39+Foxp3+CD4+ regulatory T cells (CD39+T-regs) and exhausted-like CD8+ T cells (with pronounced CD39 and PD-1 expression) within TIME was identified and confirmed by multiplex immunofluorescence staining in an independent patient cohort (n = 140). Crucially, tumor-infiltrating CD39+T-regs and CD39+PD-1+CD8+ T cells emerged as independent prognostic indicators associated with an unfavorable prognosis in iCCA. These findings unveil the intricate immune landscape within iCCA, offering valuable insights for disease management and novel cancer immunotherapies.

Hypertriglyceridemia (HTG) is a common cardiovascular risk factor characterized by elevated triglyceride (TG) levels. Researchers have assessed the genetic factors that influence HTG in studies focused predominantly on individuals of European ancestry. However, relatively little is known about the contribution of genetic variation of HTG in people of African ancestry (AA), potentially constraining research and treatment opportunities. Our objective was to characterize genetic profiles among individuals of AA with mild-to-moderate HTG and severe HTG versus those with normal TGs by leveraging whole-genome sequencing data and longitudinal electronic health records available in the All of Us program. We compared the enrichment of functional variants within five canonical TG metabolism genes, an AA-specific polygenic risk score for TGs, and frequencies of 145 known potentially causal TG variants between HTG patients and normal TG among a cohort of AA patients (N = 15,373). Those with mild-to-moderate HTG (N = 342) and severe HTG (N ≤ 20) were more likely to carry APOA5 p.S19W (odds ratio = 1.94, 95% confidence interval = [1.48–2.54], P = 1.63 × 10−6 and OR = 3.65, 95% confidence interval: [1.22–10.93], P = 0.02, respectively) than those with normal TG. They were also more likely to have an elevated (top 10%) polygenic risk score, elevated carriage of potentially causal variant alleles, and carry any genetic risk factor. Alternative definitions of HTG yielded comparable results. In conclusion, individuals of AA with HTG were enriched for genetic risk factors compared to individuals with normal TGs.

Abstract Tumor mutational burden (TMB) and T‐cell receptor (TCR) might predict the response to immunotherapy in patients with non–small cell lung cancer (NSCLC). However, the predictive value of the combination of TMB and TCR was not clear. Targeted DNA and TCR sequencing were performed on tumor biopsy specimens. We combined TMB and TCR diversity into a TMB‐and‐TCR (TMR) score using logistic regression. In total, 38 patients with advanced NSCLC were divided into a discovery set (n = 17) and validation set (n = 21). A higher TMR score was associated with better response and longer progression‐free survival to immunotherapy in both the discovery set and validation set. The performance of TMR score was confirmed in the two external validation cohorts of 225 NSCLC patients and 306 NSCLC patients. Tumors with higher TMR scores were more likely to combine with LRP1B gene mutation (p = 0.027) and top 1% CDR3 sequences (p = 0.001). Furthermore, LRP1B allele frequency was negatively correlated with the top 1% CDR3 sequences (r = –0.55, p = 0.033) and positively correlated with tumor shrinkage (r = 0.68, p = 0.007). The TMR score could serve as a potential predictive biomarker for the response to immunotherapy in advanced NSCLC.

Abstract The Kevlar fibers were irradiated at up to 2500 kGy using a 10 MeV electron accelerator. The effects of radiation on the Kevlar fibers were evaluated in detail. The [...]

Abstract Candidalysin, a cytolytic peptide toxin secreted by the human fungal pathogen Candida albicans, is critical for fungal pathogenesis. Yet, its intracellular targets have not been extensively mapped. Here, we performed a high-throughput enhanced yeast two-hybrid (HT-eY2H) screen to map the interactome of all eight Ece1 peptides with their direct human protein targets and identified a list of potential interacting proteins, some of which were shared between the peptides. CCNH, a regulatory subunit of the CDK-activating kinase (CAK) complex involved in DNA damage repair, was identified as one of the host targets of candidalysin. Mechanistic studies revealed that candidalysin triggers a significantly increased double-strand DNA breaks (DSBs), as evidenced by the formation of γ-H2AX foci and colocalization of CCNH and γ-H2AX. Importantly, candidalysin binds directly to CCNH to activate CAK to inhibit DNA damage repair pathway. Loss of CCNH alleviates DSBs formation under candidalysin treatment. Depletion of candidalysin-encoding gene fails to induce DSBs and stimulates CCNH upregulation in a murine model of oropharyngeal candidiasis. Collectively, our study reveals that a secreted fungal toxin acts to hijack the canonical DNA damage repair pathway by targeting CCNH and to promote fungal infection.

Abstract Drug repurposing represents an attractive alternative to the costly and time-consuming process of new drug development, particularly for serious, widespread conditions with limited effective treatments, such as Alzheimer’s disease (AD). Emerging generative artificial intelligence (GAI) technologies like ChatGPT offer the promise of expediting the review and summary of scientific knowledge. To examine the feasibility of using GAI for identifying drug repurposing candidates, we iteratively tasked ChatGPT with proposing the twenty most promising drugs for repurposing in AD, and tested the top ten for risk of incident AD in exposed and unexposed individuals over age 65 in two large clinical datasets: (1) Vanderbilt University Medical Center and (2) the All of Us Research Program. Among the candidates suggested by ChatGPT, metformin, simvastatin, and losartan were associated with lower AD risk in meta-analysis. These findings suggest GAI technologies can assimilate scientific insights from an extensive Internet-based search space, helping to prioritize drug repurposing candidates and facilitate the treatment of diseases.

Rheumatoid arthritis (RA) is an autoimmune disease with a complex etiology. Monocyte-derived macrophages (MDMs) infiltration are associated with RA severity. We have reported the deletion of G-protein-coupled receptor kinase 2 (GRK2) reprograms macrophages toward an anti-inflammatory phenotype by recovering G-protein-coupled receptor signaling. However, as more GRK2-interacting proteins were discovered, the GRK2 interactome mechanisms in RA have been understudied. Thus, in the collagen-induced arthritis mouse model, we performed genetic GRK2 deletion using GRK2f/fLyz2-Cre+/− mice. Synovial inflammation and M1 polarization were improved in GRK2f/fLyz2-Cre+/− mice. Supporting experiments with RNA-seq and dual-luciferase reporter assays identified peroxisome proliferator-activated receptor γ (PPARγ) as a new GRK2-interacting protein. We further confirmed that fms-related tyrosine kinase 1 (Flt-1), which promoted macrophage migration to induce angiogenesis, was inhibited by GRK2-PPARγ signaling. Mechanistically, excess GRK2 membrane recruitment in CIA MDMs reduced the activation of PPARγ ligand-binding domain and enhanced Flt-1 transcription. Furthermore, the treatment of mice with GRK2 activity inhibitor resulted in significantly diminished CIA pathology, Flt-1+ macrophages induced-synovial inflammation, and angiogenesis. Altogether, we anticipate to facilitate the elucidation of previously unappreciated details of GRK2-specific intracellular signaling. Targeting GRK2 activity is a viable strategy to inhibit MDMs infiltration, affording a distinct way to control joint inflammation and angiogenesis of RA.

Osteoarthritis (OA) is a chronic degenerative joint disease whose main characteristic is the destruction of articular cartilage, causing pain and disability in patients and seriously affecting their quality of life. OA can be induced by a variety of causes, and pathological changes in articular cartilage are considered to be one of the key driving factors for the occurrence of OA. High mobility group box-1 protein (HMGB1), as a non-histone protein in eukaryotic cells, can participate in regulating the inflammation and apoptosis process of OA chondrocytes, thus leading to the occurrence of OA. This article reviews the research on the mechanism of HMGB1 in OA chondrocytes, with a view to providing new ideas for the clinical prevention and treatment of OA.

Background/Aim. High-grade glioma (HGG) is an interstitial cell-derived primary tumor of the nervous system. The current guidelines for the diagnosis and treatment of glioma recommend the maximum safe range of tumor resection for treatment methods. Adjuvant concurrent chemoradiotherapy is recommended after surgery, followed by six cycles of single-drug chemotherapy, temozolomide. Evaluation of the early efficacy of concurrent chemoradio-therapy after HGG surgery, especially for patients with a high risk of recurrence, is a crucial step in enhancing the treatment efficiency for patients diagnosed with HGG. In this study, we investigated the clinical utility of magnetic resonance (MR) spectroscopy (MRS) in assessing the early curing impact of concurrent chemoradiotherapy following HGG surgery. Methods. A total of 50 patients with incomplete resection or suspected residual postoperative HGG, treated in the radiotherapy department of our hospital between January 2016 and June 2021, were selected for routine concurrent chemoradiotherapy. Conventional MR imaging and MRS were performed one week prior to treatment and one month after treatment to assess changes in specific brain metabolites. All 50 patients were followed up for 6 to 12 months. Based on the follow-up results, the patients were divided into two groups: the tumor recurrence group and the tumor suppression group. One month after the end of the treatment, the differences in levels of brain metabolites between the two groups were analyzed using MRS. Results. The levels of N-acetylaspartate (NAA) and creatine (Cr) increased after radiotherapy, while choline (Cho) peak value, and Cho/Cr, NAA/Cr, and Cho/NAA ratios decreased compared to pre-treatment levels. There were statistically significant differences in the NAA peak value, and Cho/Cr, and Cho/NAA ratios in the tumor enhancement area before and after treatment (p < 0.05). There were also statistically significant differences in Cho/Cr ratio in the peritumoral edema area before and after treatment (p < 0.05). Conclusion. After concurrent chemoradiotherapy, MRS can be used to detect early metabolic changes in the tumor enhancement and peritumoral edema areas of HGG.

Abstract Background The alpine meadow is one of the most important ecosystems in the Qinghai-Tibet Plateau (QTP), and critically sensitive to climate change and human activities. Thus, it is crucial to precisely reveal the current state and predict future trends in the carbon budget of the alpine meadow ecosystem. The objective of this study was to explore the applicability of the Biome-BGC model (BBGC) in the Qinghai Lake Basin (QLB), identify the key parameters affecting the variation of net ecosystem exchange (NEE), and further predict the future trends in carbon budget in the QLB. Results The alpine meadow mainly acted as carbon sink during the growing season. For the eco-physiological factors, the YEL (Yearday to end litterfall), YSNG (Yearday to start new growth), CLEC (Canopy light extinction coefficient), FRC:LC (New fine root C: new leaf C), SLA (Canopy average specific leaf area), C:Nleaf (C:N of leaves), and FLNR (Fraction of leaf N in Rubisco) were confirmed to be the top seven parameters affecting carbon budget of the alpine meadow. For the meteorological factors, the sensitivity of NEE to precipitation was greater than that to vapor pressure deficit (VPD), and it was greater to radiation than to air temperature. Moreover, the combined effect of two different meteorological factors on NEE was higher than the individual effect of each one. In the future, warming and wetting would enhance the carbon sink capacity of the alpine meadow during the growing season, but extreme warming (over 3.84 ℃) would reduce NEE (about 2.9%) in the SSP5-8.5 scenario. Conclusion Overall, the alpine meadow ecosystem in the QLB generally performs as a carbon sink at present and in the future. It is of great significance for the achievement of the goal of carbon neutrality and the management of alpine ecosystems.

The concept of probabilistic interval preference ordering sets (PIPOSs) provides a scientific and intuitive framework for solving real-life multi-criteria group decision-making problems. In some areas such as investment decision-making and supplier selection, PIPOSs have a wider application space, and the development of similarity and distance measures based on PIPOSs holds great significance. Similarity measure is a basic and prominent tool for dealing with imperfect and ambiguous information in fuzzy sets, but it can also be used to deal with uncertain information in preference ordering. These metrics play an important role in the actual decision-making process, as they effectively quantify the degree of similarity between two PIPOSs, and further allow for the prioritization of different scenarios. In this article, we sort out the definitions and arithmetic rules of PIPOSs, and creatively propose several new similarity measures based on PIPOSs. Then, we propose a group decision-making method based on similarity measures and conduct a comparative study with three existing similarity measures to illustrate its advantages over existing metrics. Finally, we confirm its validity through numerical illustrations in the case study, and also conduct a comparative assessment to verify the scientific validity and effectiveness of the newly introduced measure against the existing metrics.