Electroacupuncture improves apoptosis of nucleus pulposus cells via the IL-22/JAK2-STAT3 signaling pathway in a rat model of cervical intervertebral disk degeneration.

BACKGROUND: Cervical spondylosis (CS) is a prevalent disorder that can have a major negative impact on quality of life. Traditional conservative treatment has limited efficacy, and electroacupuncture (EA) is a novel treatment option. We investigated the application and molecular mechanism of EA treatment in a rat model of cervical intervertebral disk degeneration (CIDD). METHODS: The CIDD rat model was established, following which rats in the electroacupuncture (EA) group received EA. For overexpression of IL-22 or inhibition of JAK2-STAT3 signaling, the rats were injected intraperitoneally with recombinant IL-22 protein (p-IL-22) or the JAK2-STAT3 (Janus kinase 2-signal transducer and activator of transcription protein 3) inhibitor AG490 after model establishment. Rat nucleus pulposus (NP) cells were isolated and cultured. Cell counting kit-8 and flow cytometry were used to analyze the viability and apoptosis of the NP cells. Expression of IL-22, JAK2 and STAT3 was determined using RT-qPCR. Expression of IL-22/JAK2-STAT3 pathway and apoptosis related proteins was detected by Western blotting (WB). RESULTS: EA protected the NP tissues of CIDD rats by regulating the IL-22/JAK2-STAT3 pathway. Overexpression of IL-22 significantly promoted the expression of tumor necrosis factor (TNF)-α, IL-6, IL-1ß, matrix metalloproteinase (MMP)3 and MMP13 compared with the EA group. WB demonstrated that the expression of IL-22, p-JAK2, p-STAT3, caspase-3 and Bax in NP cells of the EA group was significantly reduced and Bcl-2 elevated compared with the model group. EA regulated cytokines and MMP through activation of IL-22/JAK2-STAT3 signaling in CIDD rat NP cells. CONCLUSION: We demonstrated that EA affected apoptosis by regulating the IL-22/JAK2-STAT3 pathway in NP cells and reducing inflammatory factors in the CIDD rat model. The results extend our knowledge of the mechanisms of action underlying the effects of EA as a potential treatment approach for CS in clinical practice.

Characteristics of Fe/C catalysts based on pyrolysis of ferric citrate and its peroxymonosulfate activation performance to degrade sulfadiazine in water.

Advanced oxidation techniques based on peroxysulfate activation have been paid much attention owing to their excellent performance in degrading stubborn pollutants in water. In response to the current situation that requires more raw materials and higher costs and involves more complicated processes for the preparation of Fe/C catalysts to activate persulfates, novel catalysts (Fe/C-700, Fe/C-800, Fe/C-900 and Fe/C-1000) were prepared by a high-temperature carbonization method at different pyrolysis temperatures (700, 800, 900 and 1000 °C) using inexpensive and environmentally friendly ferric citrate as raw material. Fe/C catalysts were characterized using SEM, EDS, XRD, XPS, and VSM and were screened for the activation of peroxymonosulfate (PMS) to degrade sulfadiazine (SDZ) in water, where Fe/C-900 exhibited higher efficiency. Thus, its activation performance for PMS to degrade SDZ was comprehensively investigated and the mechanisms of activation degradation were analyzed. The results showed that the degradation rate of 98.7% can be achieved to 10 mg L-1 SDZ by 0.1 g L-1 Fe/C-900 and 0.5 mmol L-1 PMS within 60 min. A wide range of solution pH, low catalyst dosage and good recycling performance were found in the Fe/C-900 application and the amount of iron ions dissolved at the end of the reaction was low (0.350 mg L-1). It was shown that both free radical and non-free radical pathways existed in the reaction system, where 1O2, SO4-˙ and O2-˙ played dominant roles in the degradation process of SDZ. The results could provide new ideas for the preparation of Fe/C catalysts and their heterogeneous activation for PMS to degrade stubborn organic pollutants in water.

A Vacancy-Engineering Ferroelectric Nanomedicine for Cuproptosis/Apoptosis Co-Activated Immunotherapy.

Low efficacy of immunotherapy due to the poor immunogenicity of most tumors and their insufficient infiltration by immune cells highlights the importance of inducing immunogenic cell death and activating immune system for achieving better treatment outcomes. Herein, ferroelectric Bi2CuO4 nanoparticles with rich copper vacancies (named BCO-VCu) are rationally designed and engineered for ferroelectricity-enhanced apoptosis, cuproptosis, and the subsequently evoked immunotherapy. In this structure, the suppressed recombination of the electron-hole pairs by the vacancies and the band bending by the ferroelectric polarization lead to high catalytic activity, triggering reactive oxygen species bursts and inducing apoptosis. The cell fragments produced by apoptosis serve as antigens to activate T cells. Moreover, due to the generated charge by the ferroelectric catalysis, this nanomedicine can act as "a smart switch" to open the cell membrane, promote nanomaterial endocytosis, and shut down the Cu+ outflow pathway to evoke cuproptosis, and thus a strong immune response is triggered by the reduced content of adenosine triphosphate. Ribonucleic acid transcription tests reveal the pathways related to immune response activation. Thus, this study firstly demonstrates a feasible strategy for enhancing the efficacy of immunotherapy using single ferroelectric semiconductor-induced apoptosis and cuproptosis.

Identification of the prognostic value of LACTB2 and its correlation with immune infiltrates in ovarian cancer by integrated bioinformatics analyses.

Ovarian cancer (OC) is one of the most common reproductive tumors in women, whereas current treatment options are limited. ß-lactamase-like-protein 2 (LACTB2) has been observed to be associated with various cancers, but its function in OC is unknown. Therefore, we evaluate the prognostic value and the underlying function of LACTB2 in OC. In this study, high expression of LACTB2 was observed in OC compared with normal controls. Kaplan-Meier Plotter analysis revealed that overexpressed LACTB2 is strongly correlated with poor prognosis. We conducted GO/KEGG analysis to investigate the potential biological function of LACTB2 in OC. GESA analysis showed that LACTB2 was closely related to immune-related pathways. Subsequently, we explored the relationship between LACTB2 and 24 types of immune cells in OC. The results suggested that LACTB2 was positively associated with multiple tumor-infiltrating immune cells. Importantly, LACTB2 may modulate immune cell infiltration in OC to influence prognosis. In conclusion, LACTB2 can be used as a promising prognostic biomarker and immunotherapy target for OC.

Generation of human vascularized and chambered cardiac organoids for cardiac disease modelling and drug evaluation.

Human induced pluripotent stem cell (hiPSC)-derived cardiac organoids (COs) have shown great potential in modelling human heart development and cardiovascular diseases, a leading cause of global death. However, several limitations such as low reproducibility, limited vascularization and difficulty in formation of cardiac chamber were yet to be overcome. We established a new method for robust generation of COs, via combination of methodologies of hiPSC-derived vascular spheres and directly differentiated cardiomyocytes from hiPSCs, and investigated the potential application of human COs in cardiac injury modelling and drug evaluation. The human COs we built displayed a vascularized and chamber-like structure, and hence were named vaschamcardioids (vcCOs). These vcCOs exhibited approximately 90% spontaneous beating ratio. Single-cell transcriptomics identified a total of six cell types in the vcCOs, including cardiomyocytes, cardiac precursor cells, endothelial cells, fibroblasts, etc. We successfully recaptured the processes of cardiac injury and fibrosis in vivo on vcCOs, and showed that the FDA-approved medication captopril significantly attenuated cardiac injury-induced fibrosis and functional disorders. In addition, the human vcCOs exhibited an obvious drug toxicity reaction to doxorubicin in a dose-dependent manner. We developed a three-step method for robust generation of chamber-like and vascularized complex vcCOs, and our data suggested that vcCOs might become a useful model for understanding pathophysiological mechanisms of cardiovascular diseases, developing intervention strategies and screening drugs.

Comprehensive machine learning-based preoperative blood features predict the prognosis for ovarian cancer.

PURPOSE: Significant advancements in improving ovarian cancer (OC) outcomes have been limited over the past decade. To predict prognosis and improve outcomes of OC, we plan to develop and validate a robust prognosis signature based on blood features. METHODS: We screened age and 33 blood features from 331 OC patients. Using ten machine learning algorithms, 88 combinations were generated, from which one was selected to construct a blood risk score (BRS) according to the highest C-index in the test dataset. RESULTS: Stepcox (both) and Enet (alpha = 0.7) performed the best in the test dataset with a C-index of 0.711. Meanwhile, the low RBS group possessed observably prolonged survival in this model. Compared to traditional prognostic-related features such as age, stage, grade, and CA125, our combined model had the highest AUC values at 3, 5, and 7 years. According to the results of the model, BRS can provide accurate predictions of OC prognosis. BRS was also capable of identifying various prognostic stratifications in different stages and grades. Importantly, developing the nomogram may improve performance by combining BRS and stage. CONCLUSION: This study provides a valuable combined machine-learning model that can be used for predicting the individualized prognosis of OC patients.

Multitask prediction models for serous ovarian cancer by preoperative CT image assessments based on radiomics.

Objective: High-grade serous ovarian cancer (HGSOC) has the highest mortality rate among female reproductive system tumors. Accurate preoperative assessment is crucial for treatment planning. This study aims to develop multitask prediction models for HGSOC using radiomics analysis based on preoperative CT images. Methods: This study enrolled 112 patients diagnosed with HGSOC. Laboratory findings, including serum levels of CA125, HE-4, and NLR, were collected. Radiomic features were extracted from manually delineated ROI on CT images by two radiologists. Classification models were developed using selected optimal feature sets to predict R0 resection, lymph node invasion, and distant metastasis status. Model evaluation was conducted by quantifying receiver operating curves (ROC), calculating the area under the curve (AUC), De Long's test. Results: The radiomics models applied to CT images demonstrated superior performance in the testing set compared to the clinical models. The area under the curve (AUC) values for the combined model in predicting R0 resection were 0.913 and 0.881 in the training and testing datasets, respectively. De Long's test indicated significant differences between the combined and clinical models in the testing set (p = 0.003). For predicting lymph node invasion, the AUCs of the combined model were 0.868 and 0.800 in the training and testing datasets, respectively. The results also revealed significant differences between the combined and clinical models in the testing set (p = 0.002). The combined model for predicting distant metastasis achieved AUCs of 0.872 and 0.796 in the training and test datasets, respectively. The combined model displayed excellent agreement between observed and predicted results in predicting R0 resection, while the radiomics model demonstrated better calibration than both the clinical model and combined model in predicting lymph node invasion and distant metastasis. The decision curve analysis (DCA) for predicting R0 resection favored the combined model over both the clinical and radiomics models, whereas for predicting lymph node invasion and distant metastasis, DCA favored the radiomics model over both the clinical model and combined model. Conclusion: The identified radiomics signature holds potential value in preoperatively evaluating the R0, lymph node invasion and distant metastasis in patients with HGSC. The radiomics nomogram demonstrated the incremental value of clinical predictors for surgical outcome and metastasis estimation.

Anoikis-related signature predicts prognosis and characterizes immune landscape of ovarian cancer.

Ovarian cancer (OV) is the most lethal gynecological malignancy worldwide, with high recurrence rates. Anoikis, a newly-acknowledged form of programmed cell death, plays an essential role in cancer progression, though studies focused on prognostic patterns of anoikis in OV are still lacking. We filtered 32 potential anoikis-related genes (ARGs) among the 6406 differentially expressed genes (DEGs) between the 180 normal controls and 376 TCGA-OV samples. Through the LASSO-Cox analysis, a 2-gene prognostic signature, namely AKT2, and DAPK1, was finally distinguished. We then demonstrated the promising prognostic value of the signature through the K-M survival analysis and time-dependent ROC curves (p-value < 0.05). Moreover, based on the signature and clinical features, we constructed and validated a nomogram model for 1-year, 3-year, and 5-year overall survival, with reliable prognostic values in both TCGA-OV training cohort (p-value < 0.001) and ICGC-OV validation cohort (p-value = 0.030). We evaluated the tumor immune landscape through the CIBERSORT algorithm, which indicated the upregulation of resting Myeloid Dendritic Cells (DCs), memory B cells, and naïve B cells and high expression of key immune checkpoint molecules (CD274 and PDCD1LG2) in the high-risk group. Interestingly, the high-risk group exhibited better sensitivity toward immunotherapy and less sensitivity toward chemotherapies, including Cisplatin and Bleomycin. Especially, based on the IHC of tissue microarrays among 125 OV patients at our institution, we reported that aberrant upregulation of DAPK1 was related to poor prognosis. Conclusively, the anoikis-related signature was a promising tool to evaluate prognosis and predict therapy responses, thus assisting decision-making in the realm of OV precision medicine.

Employing Piezoelectric Mg2+-Doped Hydroxyapatite to Target Death Receptor-Mediated Necroptosis: A Strategy for Amplifying Immune Activation.

Although immunogenic cell death (ICD) inducers evidently enhance the effectiveness of immunotherapy, their potential is increasingly restricted by the development of apoptosis resistance in tumor cells, poor immunogenicity, and low T-cell immune responsiveness. In this study, for the first time, piezoelectrically catalyzed Mg2+-doped hydroxyapatite (Mg-HAP) nanoparticles, which are coated with a mesoporous silica layer and loaded with ONC201 as an agonist to specifically target the death receptor DR5 on tumor cells, ultimately developing an Mg-HAP@MS/ONC201 nanoparticle (MHMO NP) system, are engineered. Owing to its excellent piezoelectric properties, MHMO facilitates the release of a significant amount of reactive oxygen species and Ca2+ within tumor cells, effectively promoting the upregulation of DR5 expression and inducing tumor cell necroptosis to ultimately overcome apoptosis resistance. Concurrently, Mg2+ released in the tumor microenvironment promotes CD8+ T receptor activation in response to the antitumor immune reaction induced by ICD. Using RNA-seq analysis, it is elucidated that MHMO can activate the NF-κB pathway under piezoelectric catalysis, thus inducing M1-type macrophage polarization. In summary, a dual-targeting therapy system that targets both tumor cells and the tumor microenvironment under piezoelectric catalysis is designed. This system holds substantial potential for advancements in tumor immunotherapy.

Dynamic Traffic Data in Machine-Learning Air Quality Mapping Improves Environmental Justice Assessment.

Air pollution poses a critical public health threat around many megacities but in an uneven manner. Conventional models are limited to depict the highly spatial- and time-varying patterns of ambient pollutant exposures at the community scale for megacities. Here, we developed a machine-learning approach that leverages the dynamic traffic profiles to continuously estimate community-level year-long air pollutant concentrations in Los Angeles, U.S. We found the introduction of real-world dynamic traffic data significantly improved the spatial fidelity of nitrogen dioxide (NO2), maximum daily 8-h average ozone (MDA8 O3), and fine particulate matter (PM2.5) simulations by 47%, 4%, and 15%, respectively. We successfully captured PM2.5 levels exceeding limits due to heavy traffic activities and providing an "out-of-limit map" tool to identify exposure disparities within highly polluted communities. In contrast, the model without real-world dynamic traffic data lacks the ability to capture the traffic-induced exposure disparities and significantly underestimate residents' exposure to PM2.5. The underestimations are more severe for disadvantaged communities such as black and low-income groups, showing the significance of incorporating real-time traffic data in exposure disparity assessment.

Chicoric Acid Effectively Mitigated Dextran Sulfate Sodium (DSS)-Induced Colitis in BALB/c Mice by Modulating the Gut Microbiota and Fecal Metabolites.

Chicoric acid (CA) has been reported to exhibit biological activities; it remains unclear, however, whether CA could regulate colitis via modulation of the gut microbiota and metabolites. This study aimed to assess CA's impact on dextran sulfate sodium (DSS)-induced colitis, the gut microbiota, and metabolites. Mice were induced with 2.5% DSS to develop colitis over a 7-day period. CA was administered intragastrically one week prior to DSS treatment and continued for 14 days. The microbial composition in the stool was determined using 16S rRNA sequencing, while non-targeted metabolomics was employed to analyze the metabolic profiles of each mouse group. The results show that CA effectively alleviated colitis, as evidenced by an increased colon length, lowered disease activity index (DAI) and histological scores, and decreased tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) expression levels. CA intervention restored the structure of gut microbiota. Specifically, it decreased the abundance of Bacteroidetes and Cyanobacteria at the phylum level and Bacteroides, Rosiarcus, and unclassified Xanthobacteraceae at the genus level, and increased the abundance of unclassified Lachnospiraceae at the genus level. Metabolomic analysis revealed that CA supplementation reversed the up-regulation of asymmetric dimethylarginine, N-glycolylneuraminic acid, and N-acetylneuraminic acid, as well as the down-regulation of phloroglucinol, thiamine, 4-methyl-5-thiazoleethanol, lithocholic acid, and oxymatrine induced by DSS. Our current research provides scientific evidence for developing CA into an anti-colitis functional food ingredient. Further clinical trials are warranted to elucidate the efficacy and mechanism of CA in treating human inflammatory bowel disease (IBD).

Revealing the Mutually Enhanced Mechanism of Necroptosis and Immunotherapy Induced by Defect Engineering and Piezoelectric Effect.

Owing to low immunogenicity-induced immune escape and short-term circulating immune responses, the efficiency of immunotherapy is unsatisfactory. Therefore, triggering immunogenic cell death and establishing a long-term, mutually reinforced treatment modality are urgent challenges. In this study, ultrathin CaBi2 Nb2 O9 nanosheets with tunable oxygen vacancies (abbreviated as CBNO-OV1) are prepared for synergistic necroptosis and immunotherapy. The optimized vacancy concentration significantly improves the piezoelectric effect under ultrasound irradiation, thereby considerably improving the generation of reactive oxygen species (ROS). Density functional theory shows that oxygen vacancies can improve the efficiency of electron hole separation by suppressing their recombination, thus resulting in enhanced piezocatalytic activity. Moreover, the piezoelectric effect improves the permeability of tumor cell membranes, thus resulting in Ca2+ influx. Additionally, CBNO-OV1 also releases a portion of Ca2+ , which induces necroptosis assisted by explosive ROS. Ribonucleic acid transcription tests suggest the mechanisms associated with immune response activation and necroptosis. More importantly, necroptosis can trigger a significant immune response in vivo, thus activating macrophage M1 polarization through the NF-kappa B pathway and promoting T-cell differentiation.Tumor Necrosis Factor-α differentiated from macrophages conversely promotes necroptosis, thus realizing a mutually enhanced effect. This study demonstrates the feasibility of mutually reinforced necroptosis and immunotherapy for amplifying tumor efficacy.

A "One Arrow Three Eagle" Strategy to Improve CM-272 Primed Bladder Cancer Immunotherapy.

Immunotherapy using an immune-checkpoint blockade has significantly improved its therapeutic effects. CM-272, which is a novel epigenetic inhibitor of G9a, induces immunogenic cell death (ICD) for recovering the sensitivity to anti-PD-1 antibodies; however, the efficacy of CM-272 is greatly limited by promoting the transcription activity of HIF-1α to form a hypoxic environment. Here, a Fe3+ -based nanoscale metal-organic framework (MIL-53) is used to load CM-272 (ultra-high loading rate of 56.4%) for realizing an MIL-53@CM-272 nanoplatform. After entering bladder cancer cells, Fe3+ not only promotes the decomposition of H2 O2 into O2 for O2 -compensated sonodynamic therapy but reduces the high level of glutathione in the tumor microenvironment (TME) for enhancing reactive oxygen species, including ferroptosis and apoptosis. MIL-53 carriers can be degraded in response to the TME, accelerating the release of CM-272, which helps achieve the maximum effectiveness in an O2 -sufficient TME by attenuating drug resistance. Furthermore, MIL-53@CM-272 enhances dendritic cell maturation and synergistically combines it with an anti-programmed cell death protein 1 antibody during the study of immune-related pathways in the transcriptomes of bladder cancer cells using RNA-seq. This study presents the first instance of amalgamating nanomedicine with CM-272, inducing apoptosis, ferroptosis, and ICD to achieve the "one arrow three eagle" effect.

CSGALNACT2 restricts ovarian cancer migration and invasion by modulating MAPK/ERK pathway through DUSP1.

PURPOSE: Ovarian cancer is one of the leading causes of cancer-related death among women. CSGALNACT2 is a vital Golgi transferase and is related to a variety of human diseases. However, its expression pattern and function in ovarian cancer remain uncertain. METHODS: The Cancer Genome Atlas and GEPIA databases were used to assess the expression of CSGALNACT2 in ovarian cancer patients. RNA-seq, qRT-PCR, and IHC were used to verify the expression of CSGALNACT2 in ovarian cancer tissues. Then, in vivo and in vitro experiments were conducted to evaluate the role of CSGALNACT2 in the progression of ovarian cancer. RNA-seq and GSEA were used to reveal the potential biological function and oncogenic pathways of CSGALNACT2. RESULTS: We demonstrated that the mRNA expression and protein level of CSGALNACT2 were significantly downregulated in ovarian cancer and ovarian cancer metastatic tissues. CSGALNACT2 can significantly inhibit the migration, invasion, and clonogenic growth of ovarian cancer in vitro and is progressively lost during ovarian cancer progression in vivo. CSGALNACT2 suppresses ovarian cancer migration and invasion via DUSP1 modulation of the MAPK/ERK pathway through RNA-seq, KEGG analysis, and Western blotting. Moreover, CSGALNACT2 expression was correlated with immune cell infiltration and had prognostic value in different immune cell-enriched or decreased ovarian cancer. In addition, patients with CSGALNACT2 downregulation are less likely to benefit from immunotherapy. CONCLUSION: As an ovarian cancer suppressor gene, CSGALNACT2 inhibits the development of ovarian cancer, and it might be used as a prognostic biomarker in patients with ovarian cancer.

Clinical significance and immune infiltration analyses of a novel coagulation-related signature in ovarian cancer.

Ovarian cancer (OV) is the most lethal gynecological malignancies worldwide. The coagulation cascade could induce tumor cell infiltration and contribute to OV progression. However, coagulation-related gene (CRG) signature for OV prognosis hasn't been determined yet. In this study, we evaluated the prognostic value of coagulation scores through receiver operating characteristics (ROC) analysis and K-M curves, among OV patients at our institution. Based on the transcriptome data of TCGA-OV cohort, we stratified two coagulation-related subtypes with distinct differences in prognosis and tumor immune microenvironment (p < 0.05). Moreover, from the 6406 differentially-expressed genes (DEGs) between the GTEx (n = 180) and TCGA-OV cohorts (n = 376), we identified 138 potential CRGs. Through LASSO-Cox algorithm, we finally distinguished a 3-gene signature (SERPINA10, CD38, and ZBTB16), with promising prognostic ability in both TCGA (p < 0.001) and ICGC cohorts (p = 0.040). Stepwise, we constructed a nomogram based on the clinical features and coagulation-related signature for overall survival prediction, with the C-index of 0.6761, which was evaluated by calibration curves. Especially, based on tissue microarrays analysis, Quantitative real-time fluorescence PCR (qRT-PCR), and Western Blot, we found that aberrant upregulation of CRGs was related to poor prognosis in OV at both mRNA and protein level (p < 0.05). Collectively, the coagulation-related signature was a robust prognostic biomarker, which could provide therapeutic benefits for chemotherapy/immunotherapy and assist clinical decision in OV patients.

EDARADD promotes colon cancer progression by suppressing E3 ligase Trim21-mediated ubiquitination and degradation of Snail.

Tumor cell migration, specifically epithelial-mesenchymal transition (EMT), serves as a key contributor to treatment failure in colon cancer patients. However, the limited comprehension of its genetic and biological aspects presents challenges for its investigation. EDAR-associated death domain (EDARADD), an important TNFR superfamily member, is elevated in colon cancer. However, it remains unclear about the exact role of EDARADD in the progression of colon cancer metastasis. In this study, we initially demonstrated that both protein and mRNA levels of EDDARADD are elevated in colon cancer tissues and cells, associated with reduced overall survival. Furthermore, functional experiments demonstrated that EDARADD promotes colon cancer cell proliferation and participates in EMT both in vitro and vivo. Mechanistically, Co-IP verified EDARADD could stabilize Snail1 by interacting with E3 ubiquitin ligase Trim21 to inhibit ubiquitination of Snail1. Interestingly, RNA-seq and ubiquitination assay revealed EDARADD's dual downregulation of Trim21 expression at the translational level via Cul1-mediated ubiquitin degradation, and at the transcriptional level through PPARa regulation. Moreover, EDARADD activates NF-κB signaling and experiences feedback transcriptional regulation by p65. In conclusion, this study highlights the signal pathway of EDARADD-PPARa-Trim21-Snail1-EMT and a feedback regulation of NF-κB signaling on EDARADD, which indicated EDARADD as an emerging therapeutic target for colon cancer.

Phenomic and transcriptomic analyses reveal the sequential synthesis of Fe3O4 nanoparticles in Acidithiobacillus ferrooxidans BYM.

IMPORTANCE: As the most important non-magnetotactic magnetosome-producing bacteria, Acidithiobacillus ferrooxidans only requires very mild conditions to produce Fe3O4 nanoparticles, thus conferring greater flexibility and potential application in biomagnetic nanoparticle production. However, the available information cannot explain the mechanism of Fe3O4 nanoparticle formation in A. ferrooxidans. In this study, we applied phenomic and transcriptomic analyses to reveal this mechanism. We found that different treatment condition factors notably affect the phenomic data of Fe3O4 nanoparticle in A. ferrooxidans. Using transcriptomic analyses, the gene network controlling/regulating Fe3O4 nanoparticle biogenesis in A. ferrooxidans was proposed, excavating the candidate hub genes for Fe3O4 nanoparticle formation in A. ferrooxidans. Based on this information, a sequential model for Fe3O4 nanoparticle synthesis in A. ferrooxidans was hypothesized. It lays the groundwork for further clarifying the feature of Fe3O4 nanoparticle synthesis.

A Novel pyroptosis-related signature for predicting prognosis and evaluating tumor immune microenvironment in ovarian cancer.

Ovarian cancer (OV) is the most fatal gynecological malignant tumor worldwide, with high recurrence rates and great heterogeneity. Pyroptosis is a newly-acknowledged inflammatory form of cell death with an essential role in cancer progression, though studies focusing on prognostic patterns of pyroptosis in OV are still lacking. Our research filtered 106 potential pyroptosis-related genes (PRGs) among the 6406 differentially expressed genes (DEGs) between the 376 TCGA-OV samples and 180 normal controls. Through the LASSO-Cox analysis, the 6-gene prognostic signature, namely CITED2, EXOC6B, MIA2, NRAS, SETBP1, and TRPV46, was finally distinguished. Then, the K-M survival analysis and time-dependent ROC curves demonstrated the promising prognostic value of the 6-gene signature (p-value < 0.0001). Furthermore, based on the signature and corresponding clinical features, we constructed and validated a nomogram model for 1-year, 2-year, and 3-year OV survival, with reliable prognostic values in TCGA-OV (p-value < 0.001) and ICGC-OV cohort (p-value = 0.040). Pathway analysis enriched several critical pathways in cancer, refer to the pyroptosis-related signature, while the m6A analysis indicated greater m6A level in high-risk group. We assessed tumor immune microenvironment through the CIBERSORT algorithm, which demonstrated the upregulation of M1 Macrophages and activated DCs and high expression of key immune checkpoint molecules (CTLA4, PDCD1LG2, and HAVCR2) in high-risk group. Interestingly, the high-risk group exhibited poor sensitivity towards immunotherapy and better sensitivity towards chemotherapies, including Vinblastine, Docetaxel, and Sorafenib. Briefly, the pyroptosis-related signature was a promising tool to predict prognosis and evaluate immune responses, in order to assist decision-making for OV patients in the realm of precision medicine.

Beyond Extracellular Vesicles: Hybrid Membrane Nanovesicles as Emerging Advanced Tools for Biomedical Applications.

Extracellular vesicles (EVs), involved in essential physiological and pathological processes of the organism, have emerged as powerful tools for disease treatment owing to their unique natural biological characteristics and artificially acquired advantages. However, the limited targeting ability, insufficient production yield, and low drug-loading capability of natural simplex EVs have greatly hindered their development in clinical translation. Therefore, the establishment of multifunctional hybrid membrane nanovesicles (HMNVs) with favorable adaptability and flexibility has become the key to expanding the practical application of EVs. This timely review summarizes the current progress of HMNVs for biomedical applications. Different HMNVs preparation strategies including physical, chemical, and chimera approaches are first discussed. This review then individually describes the diverse types of HMNVs based on homologous or heterologous cell membrane substances, a fusion of cell membrane and liposome, as well as a fusion of cell membrane and bacterial membrane. Subsequently, a specific emphasis is placed on the highlight of biological applications of the HMNVs toward various diseases with representative examples. Finally, ongoing challenges and prospects of the currently developed HMNVs in clinical translational applications are briefly presented. This review will not only stimulate broad interest among researchers from diverse disciplines but also provide valuable insights for the development of promising nanoplatforms in precision medicine.

Forecasting the progression of human civilization on the Kardashev Scale through 2060 with a machine learning approach.

Energy has been propelling the development of human civilization for millennia. Humanity presently stands at Type 0.7276 on the Kardashev Scale, which was proposed to quantify the relationship between energy consumption and the development of civilizations. However, current predictions of human civilization remain underdeveloped and energy consumption models are oversimplified. In order to improve the precision of the prediction, we use machine learning models random forest and autoregressive integrated moving average to simulate and predict energy consumption on a global scale and the position of humanity on the Kardashev Scale through 2060. The result suggests that global energy consumption is expected to reach ~ 887 EJ in 2060, and humanity will become a Type 0.7449 civilization. Additionally, the potential energy segmentation changes before 2060 and the influence of the advent of nuclear fusion are discussed. We conclude that if energy strategies and technologies remain in the present course, it may take human civilization millennia to become a Type 1 civilization. The machine learning tool we develop significantly improves the previous projection of the Kardashev Scale, which is critical in the context of civilization development.