The Impact of FBN1-α5ß1 Axis in Fibro/Adipogenic Progenitor Cells (FAPCD9-) on Intramuscular Fat Content in Pigs.

Intramuscular fat (IMF) plays a crucial role in enhancing meat quality, enriching meat flavor, and overall improving palatability. In this study, Single-cell RNA sequencing was employed to analyze the longissimus dorsi (LD) obtained from Guangdong small-ear spotted pigs (GDSS, with high IMF) and Yorkshire pigs (YK, with low IMF). GDSS had significantly more Fibro/Adipogenic Progenitor (FAPs), in which the CD9 negative FAPs (FAPCD9-) having adipogenic potential, as demonstrated by in vitro assays using cells originated from mouse muscle. On the other hand, Yorkshire had more fibro-inflammatory progenitors (FIPs, marked with FAPCD9+), presenting higher expression of the FBN1-Integrin α5ß1. FBN1-Integrin α5ß1 could inhibit insulin signaling in FAPCD9-, suppressing adipogenic differentiation. Our results demonstrated that fat-type pigs possess a greater number of FAPCD9-, which are the exclusive cells in muscle capable of differentiating into adipocytes. Moreover, lean-type pigs exhibit higher expression of FBN1-Integrin α5ß1 axis, which inhibits adipocyte differentiation. These results appropriately explain the observed higher IMF content in fat-type pigs.

Starter molds and multi-enzyme catalysis in koji fermentation of soy sauce brewing: A review.

Soy sauce is a traditional fermented food produced from soybean and wheat under the action of microorganisms. The soy sauce brewing process mainly involves two steps, namely koji fermentation and moromi fermentation. In the koji fermentation process, enzymes from starter molds, such as protease, aminopeptidase, carboxypeptidase, l-glutaminase, amylase, and cellulase, hydrolyze the protein and starch in the raw ingredients to produce short-chain substances. However, the enzymatic reactions may be diminished after being subjected to moromi fermentation due to its high NaCl concentration. These enzymatically hydrolyzed products are further metabolized by lactic acid bacteria and yeasts during the moromi fermentation process into organic acids and aromatic compounds, giving soy sauce a unique flavor. Thus, the starter molds, such as Aspergillus oryzae, Aspergillus sojae, and Aspergillus niger, and their secreted enzymes play crucial roles in soy sauce brewing. This review comprehensively covers the characteristics of the starter molds mainly used in soy sauce brewing, the enzymes produced by starter molds, and the roles of enzymes in the degradation of raw material. We also enumerate current problems in the production of soy sauce, aiming to offer some directions for the improvement of soy sauce taste.

Autokinesis Reveals a Threshold for Perception of Visual Motion.

In natural viewing conditions, the brain can optimally integrate retinal and extraretinal signals to maintain a stable visual perception. These mechanisms, however, may fail in circumstances where extraction of a motion signal is less viable such as impoverished visual scenes. This can result in a phenomenon known as autokinesis in which one may experience apparent motion of a small visual stimulus in an otherwise completely dark environment. In this study, we examined the effect of autokinesis on visual perception of motion in human observers. We used a novel method with optical tracking in which the visual motion was reported manually by the observer. Experiment results show at lower speeds of motion, the perceived direction of motion was more aligned with the effect of autokinesis, whereas in the light or at higher speeds in the dark, it was more aligned with the actual direction of motion. These findings have important implications for understanding how the stability of visual representation in the brain can affect accurate perception of motion signals.

Visualizing Nanoscale Interlayer Magnetic Interactions and Unconventional Low-Frequency Behaviors in Ferromagnetic Multishelled Structures.

Precise manipulation of van der Waals forces within 2D atomic layers allows for exact control over electron-phonon coupling, leading to the exceptional quantum properties. However, applying this technique to diverse structures such as 3D materials is challenging. Therefore, investigating new hierarchical structures and different interlayer forces is crucial for overcoming these limitations and discovering novel physical properties. In this work, a multishelled ferromagnetic material with controllable shell numbers is developed. By strategically regulating the magnetic interactions between these shells, the magnetic properties of each shell are fine-tuned. This approach reveals distinctive magnetic characteristics including regulated magnetic domain configurations and enhanced effective fields. The nanoscale magnetic interactions between the shells are observed and analyzed, which shed light on the modified magnetic properties of each shell, enhancing the understanding and control of ferromagnetic materials. The distinctive magnetic interaction significantly boosts electromagnetic absorption at low-frequency frequencies used by fifth-generation wireless devices, outperforming ferromagnetic materials without multilayer structures by several folds. The application of magnetic interactions in materials science reveals thrilling prospects for technological and electronic innovation.

Insight into deep learning for glioma IDH medical image analysis: A systematic review.

BACKGROUND: Deep learning techniques explain the enormous potential of medical image analysis, particularly in digital pathology. Concurrently, molecular markers have gained increasing significance over the past decade in the context of glioma patients, providing novel insights into diagnosis and more personalized treatment options. Deep learning combined with imaging and molecular analysis enables more accurate prognostication of patients, more accurate treatment plan proposals, and accurate biomarker (IDH) prediction for gliomas. This systematic study examines the development of deep learning techniques for IDH prediction using histopathology images, spanning the period from 2019 to 2023. METHOD: The study adhered to the PRISMA reporting requirements, and databases including PubMed, Google Scholar, Google Search, and preprint repositories (such as arXiv) were systematically queried for pertinent literature spanning the period from 2019 to the 30th of 2023. Search phrases related to deep learning, digital pathology, glioma, and IDH were collaboratively utilized. RESULTS: Fifteen papers meeting the inclusion criteria were included in the analysis. These criteria specifically encompassed studies utilizing deep learning for the analysis of hematoxylin and eosin images to determine the IDH status in patients with gliomas. CONCLUSIONS: When predicting the status of IDH, the classifier built on digital pathological images demonstrates exceptional performance. The study's predictive effectiveness is enhanced with the utilization of the appropriate deep learning model. However, external verification is necessary to showcase their resilience and universality. Larger sample sizes and multicenter samples are necessary for more comprehensive research to evaluate performance and confirm clinical advantages.

Multi-omics analysis-based macrophage differentiation-associated papillary thyroid cancer patient classifier.

BACKGROUND: The reclassification of Papillary Thyroid Carcinoma (PTC) is an area of research that warrants attention. The connection between thyroid cancer, inflammation, and immune responses necessitates considering the mechanisms of differential prognosis of thyroid tumors from an immunological perspective. Given the high adaptability of macrophages to environmental stimuli, focusing on the differentiation characteristics of macrophages might offer a novel approach to address the issues related to PTC subtyping. METHODS: Single-cell RNA sequencing data of medullary cells infiltrated by papillary thyroid carcinoma obtained from public databases was subjected to dimensionality reduction clustering analysis. The RunUMAP and FindAllMarkers functions were utilized to identify the gene expression matrix of different clusters. Cell differentiation trajectory analysis was conducted using the Monocle R package. A complex regulatory network for the classification of Immune status and Macrophage differentiation-associated Papillary Thyroid Cancer Classification (IMPTCC) was constructed through quantitative multi-omics analysis. Immunohistochemistry (IHC) staining was utilized for pathological histology validation. RESULTS: Through the integration of single-cell RNA and bulk sequencing data combined with multi-omics analysis, we identified crucial transcription factors, immune cells/immune functions, and signaling pathways. Based on this, regulatory networks for three IMPTCC clusters were established. CONCLUSION: Based on the co-expression network analysis results, we identified three subtypes of IMPTCC: Immune-Suppressive Macrophage differentiation-associated Papillary Thyroid Carcinoma Classification (ISMPTCC), Immune-Neutral Macrophage differentiation-associated Papillary Thyroid Carcinoma Classification (INMPTCC), and Immune-Activated Macrophage differentiation-associated Papillary Thyroid Carcinoma Classification (IAMPTCC). Each subtype exhibits distinct metabolic, immune, and regulatory characteristics corresponding to different states of macrophage differentiation.

Corrigendum to "3D-printed tri-element-doped hydroxyapatite/ polycaprolactone composite scaffolds with antibacterial potential for osteosarcoma therapy and bone regeneration" [Bioact. Mater. 31 (January 2024) 18-37].

[This corrects the article DOI: 10.1016/j.bioactmat.2023.07.004.].

Prognosis and immunotherapy response prediction based on M2 macrophage-related genes in colon cancer.

BACKGROUND: M2 macrophage were revealed to play a crucial role in immune evasion and immunotherapies. This study aims to explore the potential significance of M2 macrophage-related genes in colon adenocarcinoma (COAD) by analysizing the transcriptome data in a comprehensive way. METHODS: We collected RNA-sequencing (RNA-seq) data of COAD from The Cancer Genome Atlas (TCGA) and Gene Expression Ominibus (GEO) databases. We calculated the immune infiltration scores of every sample using CIBERSORT algorithm. Through weighted gene co-expression network analysis (WGCNA), we picked out M2 macrophage-related genes. With these genes we screened out prognosis related genes which were utilized to construct a signature to assess the prognosis of patients. To extend the potential application of the signature, we also calculated the correlations with immune infiltration. Finally, we applied techniques such as quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunoblotting (Western Blotting) to validate the RNF32 gene in cellular in vitro assays. RESULTS: Seven M2 macrophage-related genes signature was constructed, which was an excellent prognostic predictor in two independent groups. The high-risk group showed lower immune infiltration and poorer response to immunotherapies than those of the low-risk group. The cell vitro experiments showed that the expression level of RNF32 was upregulated in colon cancer cell lines compared with normal cell lines. Moreover, we found that RNF32 may promote the proliferation, migration and invasion of cancer cells in vitro by inhibiting apoptosis. CONCLUSION: A novel M2 macrophage-related gene signature affects the prognosis and immune characteristics of colon cancer.

Clinical prediction models for cervical lymph node metastasis of papillary thyroid carcinoma.

PURPOSE: Accurate preoperative diagnosis of lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) remains an unsolved problem. This study aimed to construct a nomogram and scoring system for predicting LNM based on the clinical characteristics of patients with PTC. METHODS: 1400 patients with PTC who underwent thyroidectomy and lymph node dissection at the First Affiliated Hospital of Sun Yat-sen University were retrospectively enrolled and randomly divided into training and internal testing sets. Furthermore, 692 patients with PTC from three other medical centers were collected as external testing sets. Least absolute shrinkage and selection operator (LASSO) was used to screen the predictors, and a nomogram was constructed. In addition, a scoring system was constructed using 10-fold cross-validation. The performances of the two models were verified among datasets and compared with preoperative ultrasound (US). RESULTS: Six independent predictors were included in the multivariate logistic model: age, sex, US diagnosis of LNM, tumor diameter, location, and thyroid peroxidase antibody level. The areas under the receiver operating characteristic curve (AUROC) (95% confidence interval) of this nomogram in the training, internal testing, and three external testing sets were 0.816 (0.791-0.840), 0.782 (0.727-0.837), 0.759 (0.699-0.819), 0.749 (0.667-0.831), and 0.777 (0.726-0.828), respectively. The AUROC of the scoring system were 0.810 (0.785-0.835), 0.772 (0.718-0.826), 0.736 (0.675-0.798), 0.717 (0.635-0.799) and 0.756 (0.704-0.808), respectively. The prediction performances were both significantly superior to those of preoperative US (P < 0.001). CONCLUSION: The nomogram and scoring system performed well in different datasets and significantly improved the preoperative prediction of LNM than US alone.

Predictive Panel for Immunotherapy in Low-Grade Glioma.

BACKGROUND: The main treatment of low-grade glioma (LGG) is still surgical resection followed by radiotherapy and/or chemotherapy, which has certain limitations, including side effects and drug resistance. Immunotherapy is a promising treatment for LGG, but it is generally hindered by the tumor microenvironment with the limited expression of tumor antigens. METHODS: We integrated RNA sequencing data sets and clinical information and conducted consistent cluster analysis to explore the most suitable patients for immune checkpoint therapy. Gene set enrichment analysis, UMAP analysis, mutation correlation analysis, TIMER analysis, and TIDE analysis were used to identify the immune characteristics of 3 immune subtypes and the feasibility of 5 antigens as immune checkpoint markers. RESULTS: We analyzed the isolation and mutation of homologous recombination repair genes (HRR) of the 3 immune subtypes, and the HRR genes of the 3 subtypes were obviously segregated. Among them, the IS2 subtype has a large number of HRR gene mutations, which increases the immunogenicity of tumors-this is consistent with the results of tumor mutation load analysis of 3 immune subtypes. Then we evaluated the immune cell infiltration of immune subtypes and found that IS2 and IS3 subtypes were rich in immune cells. It is worth noting that there are many Treg cells and NK cells in the IS1 subtype. In addition, when analyzing the immune checkpoint gene expression of the 3 subtypes, we found that they were upregulated most in IS2 subtypes compared with other subtypes. Then when we further confirmed the role of immune-related genes in LGG; through TIDE analysis and TISIDB analysis, we obtained 5 markers that can predict the efficacy of ICB in patients with LGG. In addition, we confirmed that they were associated with poor prognosis through survival analysis. CONCLUSIONS: We obtained 3 reliable immune subtypes, and patients with the IS2 subtype are suitable for immunotherapy, in which NAMPT, SLC11A1, TNC, VIM, and SPP1 are predictive panel markers for ICB in the LGG group. Our findings provide a rationale for immunotherapy selection and prediction of patient prognosis in LGG patients.

Serum levels of PDGF-CC as a potential biomarker for the diagnosis of Kawasaki disease.

BACKGROUND: Kawasaki disease (KD) is an acute systemic vasculitis of unknown etiology that predominantly affects children, and no specific diagnostic biomarkers for KD are available. Platelet-derived growth factor CC (PDGF-CC) is a peptide with angiogenic properties that has been amply demonstrated to play a critical role in the cardiovascular system. This study aimed to investigate the serum expression of PDGF-CC in children with KD and to evaluate the ability of PDGF-CC to diagnose KD. METHODS: A total of 96 subjects, including 59 KD patients, 17 febrile controls (FC), and 20 healthy controls (HC), were enrolled. Serum levels of PDGF-CC were measured via enzyme-linked immunosorbent assay. The associations between PDGF-CC and clinical laboratory parameters were investigated by correlation analysis. The diagnostic performance was assessed by receiver operating characteristic (ROC) curve analysis. RESULTS: Serum PDGF-CC levels in the KD group were significantly higher than in the FC and HC groups. Serum PDGF-CC levels in the KD group were positively correlated with white blood cell counts, percentage of neutrophils, IL-2, IL-12p70, TNF-α, and IL-1ß levels, and negatively correlated with the percentage of lymphocytes. In the analysis of ROC curves, the area under the curve was 0.796 (95% confidence interval 0.688-0.880; P < 0.0001) for PDGF-CC and increased to 0.900 (95% confidence interval 0.808-0.957; P < 0.0001) in combination with white blood cell counts and C-reactive protein. CONCLUSIONS: PDGF-CC is a potential biomarker for KD diagnosis, and the combination with white blood cell counts and C-reactive protein can further improve diagnostic performance.

BHLHE40 Inhibits Ferroptosis in Pancreatic Cancer Cells via Upregulating SREBF1.

Pancreatic cancer (PCa) is one of the most fatal human malignancies. The enhanced infiltration of stromal tissue into the PCa tumor microenvironment limits the identification of key tumor-specific transcription factors and epigenomic abnormalities in malignant epithelial cells. Integrated transcriptome and epigenetic multiomics analyses of the paired PCa organoids indicate that the basic helix-loop-helix transcription factor 40 (BHLHE40) is significantly upregulated in tumor samples. Increased chromatin accessibility at the promoter region and enhanced mTOR pathway activity contribute to the elevated expression of BHLHE40. Integrated analysis of chromatin immunoprecipitation-seq, RNA-seq, and high-throughput chromosome conformation capture data, together with chromosome conformation capture assays, indicate that BHLHE40 not only regulates sterol regulatory element-binding factor 1 (SREBF1) transcription as a classic transcription factor but also links the enhancer and promoter regions of SREBF1. It is found that the BHLHE40-SREBF1-stearoyl-CoA desaturase axis protects PCa cells from ferroptosis, resulting in the reduced accumulation of lipid peroxidation. Moreover, fatostatin, an SREBF1 inhibitor, significantly suppresses the growth of PCa tumors with high expressions of BHLHE40. This study highlights the important roles of BHLHE40-mediated lipid peroxidation in inducing ferroptosis in PCa cells and provides a novel mechanism underlying SREBF1 overexpression in PCa.

Advances in 3D Printing of Highly Bioadaptive Bone Tissue Engineering Scaffolds.

The number of patients with bone defects caused by trauma, bone tumors, and osteoporosis has increased considerably. The repair of irregular, recurring, and large bone defects poses a great challenge to clinicians. Bone tissue engineering is emerging as an appropriate strategy to replace autologous bone grafting in the repair of critically sized bone defects. However, the suitability of bone tissue engineering scaffolds in terms of structure, mechanics, degradation, and the microenvironment is inadequate. Three-dimensional (3D) printing is an advanced additive-manufacturing technology widely used for bone repair. 3D printing constructs personalized structurally adapted scaffolds based on 3D models reconstructed from CT images. The contradiction between the mechanics and degradation is resolved by altering the stacking structure. The local microenvironment of the implant is improved by designing an internal pore structure and a spatiotemporal factor release system. Therefore, there has been a boom in the 3D printing of personalized bone repair scaffolds. In this review, successful research on the preparation of highly bioadaptive bone tissue engineering scaffolds using 3D printing is presented. The mechanisms of structural, mechanical, degradation, and microenvironmental adaptations of bone prostheses and their interactions were elucidated to provide a feasible strategy for constructing highly bioadaptive bone tissue engineering scaffolds.

3D-printed tri-element-doped hydroxyapatite/ polycaprolactone composite scaffolds with antibacterial potential for osteosarcoma therapy and bone regeneration.

The resection of malignant osteosarcoma often results in large segmental bone defects, and the residual cells can facilitate recurrence. Consequently, the treatment of osteosarcoma is a major challenge in clinical practice. The ideal goal of treatment for osteosarcoma is to eliminate it thoroughly, and repair the resultant bone defects as well as avoid bacterial infections. Herein, we fabricated a selenium/strontium/zinc-doped hydroxyapatite (Se/Sr/Zn-HA) powder by hydrothermal method, and then employed it with polycaprolactone (PCL) as ink to construct composite scaffolds through 3D printing, and finally introduced them in bone defect repair induced by malignant osteosarcoma. The resultant composite scaffolds integrated multiple functions involving anti-tumor, osteogenic, and antibacterial potentials, mainly attributed to the anti-tumor effects of SeO32-, osteogenic effects of Sr2+ and Zn2+, and antibacterial effects of SeO32- and Zn2+. In vitro studies confirmed that Se/Sr/Zn-HA leaching solution could induce apoptosis of osteosarcoma cells, differentiation of MSCs, and proliferation of MC3T3-E1 while showing excellent antibacterial properties. In vivo tests demonstrated that Se/Sr/Zn-HA could significantly suppress tumors after 8 days of injection, and the Se/Sr/Zn-HA-PCLs scaffold repaired femoral defects effectively after 3 months of implantation. Summarily, the Se/Sr/Zn-HA-PCLs composite scaffolds developed in this study were effective for tumor treatment, bone defect repair, and post-operative anti-infection, which provided a great potential to be a facile therapeutic material for osteosarcoma resection.

Exceptionally Bifunctional ORR/OER Performance via Synergistic Atom-Cluster Interaction.

The single-atom sites (SAs) have achieved enhanced performance toward oxygen reduction reaction (ORR) with the effective utilization of the active sites. However, the excess adsorption of the intermediates and the limited stability hinders performance improvement. Metal clusters with promising stability and weak adsorption can be used as potential substitutions, but the lack of active sites is considered undesirable for catalytic reactions. Herein, a framework of Fe nanoclusters combined with SAs on One dimensional (1D) carbon nanotubes (Fe3 C-NCNTs 90 min CC-1 ) is synthesized to confirm the synergistic atom-cluster interaction. The composite exhibits strong polarization and electron redistribution between nanocluster and SAs. The electron redistribution will significantly boost the electron transport and the desorption of the intermediates, which is confirmed by off-axis holography and DFT calculation. The electrocatalytic performance is significantly enhanced as the half-wave potential of ORR increased 75 mV and the potential of OER increased 133 mV compared with the sample without nanoclusters. Furthermore, such a bifunctional catalyst endows homemade Zn-air batteries (ZABs) with high power density and long-term stability. This work paves a facile route to design bifunctional ORR/OER electrocatalysts consisting of 0D composite structures.

Engineering Phase to Reinforce Dielectric Polarization in Nickel Sulfide Heterostructure for Electromagnetic Wave Absorption.

Engineering phase transition in micro-nanomaterials to optimize the dielectric properties and further enhance the electromagnetic microwave absorption (EMA) performance is highly desirable. However, the severe synthesis conditions restrict the design of EMA materials featuring controllable phases, which hinders the tunability of effective absorption bandwidth (EAB) and leads to an unclear loss mechanism. Herein, a seed phase decomposition-controlled strategy is proposed to induct nickel sulfide (NiSx ) absorbers with controllable phases and hollow sphere nature. Transmission electron microscopy holography and theoretical calculations evidence that the reconstruction of atoms in phase transition induces numerous heterogeneous interfaces and lattice defects/sulfur vacancies to cause varied work functions and local electronic redistribution, which contributes to reinforced dielectric polarization. As a result, the optimized NiS2 /NiS heterostructure enables enhanced EM attenuation capability with a wide EAB of 5.04 GHz at only 1.6 mm, compared to that of NiS2 and NiS. Moreover, the correlation between EAB and NiS phase content is demonstrated as the "volcano" feature. This study on the concept of phase transition of micro-nanomaterials can offer a novel approach to constructing highly efficient absorbers for EMA and other functionalities.

High CTCF expression mediated by FGD5-AS1/miR-19a-3p axis is associated with immunosuppression and pancreatic cancer progression.

The most common reason for cancer-related death globally is predicted to be pancreatic cancer (PC), one of the deadliest cancers. The CCCTC-binding factor (CTCF) regulates the three-dimensional structure of chromatin, was reported to be highly regulated in various malignancies. However, the underlying biological functions and possible pathways via which CTCF promotes PC progression remain unclear. Herein, we examined the CTCF function in PC and discovered that CTCF expression in PC tissues was significantly raised compared to neighboring healthy tissues. Additionally, Kaplan-Meier survival analysis demonstrated a strong connection between elevated CTCF expression and poor patient prognosis. A study of the ROC curve (receiver operating characteristic) revealed an AUC value for CTCF of 0.968. Subsequent correlation analysis exhibited a strong relationship between immunosuppression and CTCF expression in PC. CTCF knockdown significantly inhibited the malignant biological process of PC in vitro and in vivo, suggesting that CTCF may be a potential PC treatment target. We also identified the FGD5 antisense RNA 1 (FGD5-AS1)/miR-19a-3p axis as a possible upstream mechanism for CTCF overexpression. In conclusion, our data suggest that ceRNA-mediated CTCF overexpression contributes to the suppression of anti-tumor immune responses in PC and could be a predictive biomarker and potential PC treatment target.

ATF3-induced activation of NF-κB pathway results in acquired PARP inhibitor resistance in pancreatic adenocarcinoma.

PURPOSE: Olaparib, an inhibitor of poly-(adenosine diphosphate-ribose) polymerase (PARP), has been shown to have anticancer benefits in patients with pancreatic cancer who have a germline mutation in BRCA1/2. However, resistance acquired on long-term exposure to olaparib significantly impedes clinical efficacy. METHODS: In this study, the chromatin accessibility and differentially expressed transcripts of parental and olaparib-resistant pancreatic cancer cell lines were assessed using the Assay for Transposase Accessible Chromatin with sequencing (ATAC-seq) and mRNA-seq. Detection of downstream genes regulated by transcription factors using ChIP (Chromatin immunoprecipitation assay). RESULTS: According to pathway enrichment analysis, differentially expressed genes in olaparib-resistant cells were remarkably enriched in the NF-κB signaling pathway. With ATAC-seq, we identified chromatin regions with higher accessibility in olaparib-resistant cells and predicted a series of important transcription factors. Among them, activating transcription factor 3 (ATF3) was significantly highly expressed. Functional experiments verified that inhibition of ATF3 suppressed the NF-κB pathway significantly and restored olaparib sensitivity in olaparib-resistant cells. CONCLUSION: Experiments in vitro and in vivo indicate ATF3 enhances olaparib resistance through the NF-κB signaling pathway, suggesting that ATF3 could be employed as an olaparib sensitivity and prognostic indicator in patients with pancreatic cancer.

SNHG17 alters anaerobic glycolysis by resetting phosphorylation modification of PGK1 to foster pro-tumor macrophage formation in pancreatic ductal adenocarcinoma.

BACKGROUND: Within the tumor immune microenvironment (TME), tumor-associated macrophages (TAMs) are crucial in modulating polarization states to influence cancer development through metabolic reprogramming. While long non-coding RNAs (lncRNAs) have been shown to play a pivotal role in the progression of various cancers, the underlying mechanisms by which lncRNAs alter M2 polarization through macrophage metabolism remodeling remain unelucidated. METHODS: RNA sequencing was used to screen for differentially expressed lncRNAs in TAMs and normal tissue-resident macrophages (NTRMs) isolated from pancreatic ductal adenocarcinoma (PDAC) tissues, whilst RT-qPCR and FISH were employed to detect the expression level of SNHG17. Moreover, a series of in vivo and in vitro experiments were conducted to assess the functions of SNHG17 from TAMs in the polarization and glycolysis of M2-like macrophages and in the proliferation and metastasis of pancreatic cancer cells (PCs). Furthermore, Western blotting, RNA pull-down, mass spectrometry, RIP, and dual-luciferase assays were utilized to explore the underlying mechanism through which SNHG17 induces pro-tumor macrophage formation. RESULTS: SNHG17 was substantially enriched in TAMs and was positively correlated with a worse prognosis in PDAC. Meanwhile, functional assays determined that SNHG17 promoted the malignant progression of PCs by enhancing M2 macrophage polarization and anaerobic glycolysis. Mechanistically, SNHG17 could sponge miR-628-5p to release PGK1 mRNA and concurrently interact with the PGK1 protein, activating the pro-tumorigenic function of PGK1 by enhancing phosphorylation at the T168A site of PGK1 through ERK1/2 recruitment. Lastly, SNHG17 knockdown could reverse the polarization status of macrophages in PDAC. CONCLUSIONS: The present study illustrated the essential role of SNHG17 and its molecular mechanism in TAMs derived from PDAC, indicating that SNHG17 might be a viable target for PDAC immunotherapy.

Prediction of Coronary Artery Lesions in Patients With Recurrent Kawasaki Disease.

BACKGROUND: A subset of patients with Kawasaki disease (KD) will suffer recurrence. However, there is still a lack of accurate prediction models for coronary artery lesions (CAL) in recurrent KD patients. It is necessary to establish a new nomogram model for predicting CAL in patients with recurrent KD. METHODS: Data from patients with recurrent KD between 2015 and 2021 were retrospectively reviewed. After splitting the patients into training and validation cohorts, the least absolute shrinkage and selection operator was used to select the predictors of CAL and multivariate logistic regression was used to construct a nomogram based on the selected predictors. The application of area under the receiver operating characteristic curve (AUC), calibration curves, Hosmer-Lemeshow test, Brier score and decision curve analysis were used to assess the model performance. RESULTS: A total of 159 recurrent KD patients were enrolled, 66 (41.5%) of whom had CAL. Hemoglobin levels, CAL at the first episode, and intravenous immunoglobulin resistance at recurrence were identified by the least absolute shrinkage and selection operator regression analysis as significant predictors. The model incorporating these predictors showed good discrimination (AUC, 0.777) and calibration capacities (Hosmer-Lemeshow P value, 0.418; Brier score, 0.190) in the training cohort. Application of the model to the validation cohort yielded an AUC of 0.741, a Hosmer-Lemeshow P value of 0.623 and a Brier score of 0.190. The decision curve analysis demonstrated that the nomogram model was clinically useful. CONCLUSIONS: The proposed nomogram model could help clinicians assess the risk of CAL in patients with recurrent KD.