LINC00606 promotes glioblastoma progression through sponge miR-486-3p and interaction with ATP11B.

BACKGROUND: LncRNAs regulate tumorigenesis and development in a variety of cancers. We substantiate for the first time that LINC00606 is considerably expressed in glioblastoma (GBM) patient specimens and is linked with adverse prognosis. This suggests that LINC00606 may have the potential to regulate glioma genesis and progression, and that the biological functions and molecular mechanisms of LINC00606 in GBM remain largely unknown. METHODS: The expression of LINC00606 and ATP11B in glioma and normal brain tissues was evaluated by qPCR, and the biological functions of the LINC00606/miR-486-3p/TCF12/ATP11B axis in GBM were verified through a series of in vitro and in vivo experiments. The molecular mechanism of LINC00606 was elucidated by immunoblotting, FISH, RNA pulldown, CHIP-qPCR, and a dual-luciferase reporter assay. RESULTS: We demonstrated that LINC00606 promotes glioma cell proliferation, clonal expansion and migration, while reducing apoptosis levels. Mechanistically, on the one hand, LINC00606 can sponge miR-486-3p; the target gene TCF12 of miR-486-3p affects the transcriptional initiation of LINC00606, PTEN and KLLN. On the other hand, it can also regulate the PI3K/AKT signaling pathway to mediate glioma cell proliferation, migration and apoptosis by binding to ATP11B protein. CONCLUSIONS: Overall, the LINC00606/miR-486-3p/TCF12/ATP11B axis is involved in the regulation of GBM progression and plays a role in tumor regulation at transcriptional and post-transcriptional levels primarily through LINC00606 sponging miR-486-3p and targeted binding to ATP11B. Therefore, our research on the regulatory network LINC00606 could be a novel therapeutic strategy for the treatment of GBM.

Mesoporous MOFs with ROS scavenging capacity for the alleviation of inflammation through inhibiting stimulator of interferon genes to promote diabetic wound healing.

Excessive production of reactive oxygen species (ROS) and inflammation are the key problems that impede diabetic wound healing. In particular, dressings with ROS scavenging capacity play a crucial role in the process of chronic wound healing. Herein, Zr-based large-pore mesoporous metal-organic frameworks (mesoMOFs) were successfully developed for the construction of spatially organized cascade bioreactors. Natural superoxide dismutase (SOD) and an artificial enzyme were spatially organized in these hierarchical mesoMOFs, forming a cascade antioxidant defense system, and presenting efficient intracellular and extracellular ROS scavenging performance. In vivo experiments demonstrated that the SOD@HMUiO-MnTCPP nanoparticles (S@M@H NPs) significantly accelerated diabetic wound healing. Transcriptomic and western blot results further indicated that the nanocomposite could inhibit fibroblast senescence and ferroptosis as well as the stimulator of interferon genes (STING) signaling pathway activation in macrophages mediated by mitochondrial oxidative stress through ROS elimination. Thus, the biomimetic multi-enzyme cascade catalytic system with spatial ordering demonstrated a high potential for diabetic wound healing, where senescence, ferroptosis, and STING signaling pathways may be potential targets.

Effects of Different Varieties on Physicochemical Properties, Browning Characteristics, and Quality Attributes of Mume fructus (Wumei).

The dried Mume fructus (MF) is a special food and herbal medicine with a long history of processing and application. The browning index (BI) of Prunus mume (PM) is pivotal in determining the medicinal value and edible quality of MF. Exploring the BI of PM holds significant importance for both the selection of PM varieties and understanding the formation mechanism of high-quality MF. This study systematically analyzed the physicochemical properties, BI, and quality indicators of four PM varieties (Qingzhu Mei, Yesheng Mei, Nangao Mei, and Zhaoshui Mei) after processing into MF. The results showed significant differences in eight physicochemical indicators among the four PM varieties (p < 0.05). Notably, Qingzhu Mei exhibited the highest titratable acid content, Nangao Mei had the most prominent soluble solid and soluble sugar content, and Zhaoshui Mei showed outstanding performance in reducing sugar, soluble protein, and free amino acids. Regarding drying characteristics, Yesheng Mei and Nangao Mei required a shorter drying time. In terms of BI, Nangao Mei exhibited the greatest degree of browning and its color appearance was darker. When considering quality evaluation, Nangao Mei excelled in rehydration ability and extract content, while Zhaoshui Mei demonstrated outstanding levels of total phenols, total flavonoids, and total antioxidant capacity. Overall, the evaluation suggested that the Nangao Mei variety was more suitable for MF processing. These research results provide a valuable theoretical foundation for understanding the BI of PM varieties and serve as a reference for the selection of PM varieties as raw materials for processing MF.

Pan-cancer analysis implicates novel insights of lactate metabolism into immunotherapy response prediction and survival prognostication.

BACKGROUND: Immunotherapy has emerged as a potent clinical approach for cancer treatment, but only subsets of cancer patients can benefit from it. Targeting lactate metabolism (LM) in tumor cells as a method to potentiate anti-tumor immune responses represents a promising therapeutic strategy. METHODS: Public single-cell RNA-Seq (scRNA-seq) cohorts collected from patients who received immunotherapy were systematically gathered and scrutinized to delineate the association between LM and the immunotherapy response. A novel LM-related signature (LM.SIG) was formulated through an extensive examination of 40 pan-cancer scRNA-seq cohorts. Then, multiple machine learning (ML) algorithms were employed to validate the capacity of LM.SIG for immunotherapy response prediction and survival prognostication based on 8 immunotherapy transcriptomic cohorts and 30 The Cancer Genome Atlas (TCGA) pan-cancer datasets. Moreover, potential targets for immunotherapy were identified based on 17 CRISPR datasets and validated via in vivo and in vitro experiments. RESULTS: The assessment of LM was confirmed to possess a substantial relationship with immunotherapy resistance in 2 immunotherapy scRNA-seq cohorts. Based on large-scale pan-cancer data, there exists a notably adverse correlation between LM.SIG and anti-tumor immunity as well as imbalance infiltration of immune cells, whereas a positive association was observed between LM.SIG and pro-tumorigenic signaling. Utilizing this signature, the ML model predicted immunotherapy response and prognosis with an AUC of 0.73/0.80 in validation sets and 0.70/0.87 in testing sets respectively. Notably, LM.SIG exhibited superior predictive performance across various cancers compared to published signatures. Subsequently, CRISPR screening identified LDHA as a pan-cancer biomarker for estimating immunotherapy response and survival probability which was further validated using immunohistochemistry (IHC) and spatial transcriptomics (ST) datasets. Furthermore, experiments demonstrated that LDHA deficiency in pancreatic cancer elevated the CD8+ T cell antitumor immunity and improved macrophage antitumoral polarization, which in turn enhanced the efficacy of immunotherapy. CONCLUSIONS: We unveiled the tight correlation between LM and resistance to immunotherapy and further established the pan-cancer LM.SIG, holds the potential to emerge as a competitive instrument for the selection of patients suitable for immunotherapy.

Verapamil Attenuates the Severity of Tendinopathy by Mitigating Mitochondrial Dysfunction through the Activation of the Nrf2/HO-1 Pathway.

Tendinopathy is a prevalent condition in orthopedics patients, exerting a profound impact on tendon functionality. However, its underlying mechanism remains elusive and the efficacy of pharmacological interventions continues to be suboptimal. Verapamil is a clinically used medicine with anti-inflammation and antioxidant functions. This investigation aimed to elucidate the impact of verapamil in tendinopathy and the underlying mechanisms through which verapamil ameliorates the severity of tendinopathy. In in vitro experiments, primary tenocytes were exposed to interleukin-1 beta (IL-1ß) along with verapamil at a concentration of 5 µM. In addition, an in vivo rat tendinopathy model was induced through the localized injection of collagenase into the Achilles tendons of rats, and verapamil was injected into these tendons at a concentration of 5 µM. The in vitro findings highlighted the remarkable ability of verapamil to attenuate extracellular matrix degradation and apoptosis triggered by inflammation in tenocytes stimulated by IL-1ß. Furthermore, verapamil was observed to significantly suppress the inflammation-related MAPK/NFκB pathway. Subsequent investigations revealed that verapamil exerts a remediating effect on mitochondrial dysfunction, which was achieved through activation of the Nrf2/HO-1 pathway. Nevertheless, the protective effect of verapamil was nullified with the utilization of the Nrf2 inhibitor ML385. In summary, the in vivo and in vitro results indicate that the administration of verapamil profoundly mitigates the severity of tendinopathy through suppression of inflammation and activation of the Nrf2/HO-1 pathway. These findings suggest that verapamil is a promising therapeutic agent for the treatment of tendinopathy, deserving further and expanded research.

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.

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.

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.

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.

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.

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.

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.

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.

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.