Long-term impact of self-compassion training with core stability exercise on patients with nonspecific chronic low back pain: A randomized controlled trial.

OBJECTIVE: To compare the long-term effectiveness of self-compassion therapy (SCT) combined with core stability exercise (CSE) versus CSE alone in managing nonspecific chronic low back pain (NCLBP). METHODS: The combined group received SCT and CSE, while the exercise group only received CSE. Treatment was administered once weekly for four weeks, followed by one year of follow-up. The primary outcomes were changes in functional limitations (measured by Roland and Morris Disability Questionnaire scores[RMDQ]) and self-reported back pain (measured by the Numeric Pain Rating Scale[NRS]) at 52 weeks, with assessments also conducted at 2, 4, and 16 weeks. RESULTS: 52 (83.9%) completed the follow-up assessments and were included in the analysis (42 women [80.8%]; mean [SD] age,35.3 [10.0] years). In the combined group, the baseline mean (SD) RMDQ score was 9.3 (4.1),5.7 (5.8) at 2 weeks, 3.8 (3.4) at 4 weeks, 3.8 (3.7) at 16 weeks, and 2.4 (2.7) at 52 weeks. For the exercise group, the RMDQ scores were 8.2 (3.3) at baseline, 6.2 (4.2) at 2 weeks, 5.5 (4.7) at 4 weeks, 4.4 (4.5) at 16 weeks, and 5.2 (5.6) at 52 weeks. The estimated mean difference between the groups at 52 weeks was -3.356 points (95% CI, -5.835 to -0.878; P = 0.009), favoring the combined group. NRS scores showed similar changes. CONCLUSION: The addition of self-compassion therapy enhances the long-term efficacy of core stability training for NCLBP (Preregistered at chictr.org.cn:ChiCTR2100042810).

Integrated profiling identifies ferredoxin 1 as an immune-related biomarker of malignant phenotype in glioma.

Background: Glioma, a highly resistant and recurrent type of central nervous system tumor, poses a significant challenge in terms of effective drug treatments and its associated mortality rates. Despite the discovery of Ferredoxin 1 (FDX1) as a crucial participant in cuproptosis, an innovative mechanism of cellular demise, its precise implications for glioma prognosis and tumor immune infiltration remain inadequately elucidated. Methods: To analyze pan-cancer data, we employed multiple public databases. Gene expression evaluation was performed using tissue microarray (TMA) and single-cell sequencing data. Furthermore, four different approaches were employed to assess the prognostic importance of FDX1 in glioma. We conducted the analysis of differential expression genes (DEGs) and Gene Set Enrichment Analysis (GSEA) to identify immune-related predictive signaling pathways. Somatic mutations were assessed using Tumor Mutation Burden (TMB) and waterfall plots. Immune cell infiltration was evaluated with five different algorithms. Furthermore, we performed in vitro investigations to evaluate the biological roles of FDX1 in glioma. Results: Glioma samples exhibited upregulation of FDX1, which in turn predicted poor prognosis and was positively associated with unfavorable clinicopathological characteristics. Notably, the top four enriched signaling pathways were immune-related, and the discovery revealed a connection between the expression of FDX1 and the frequency of mutations or the TMB. The FDX1_high group exhibited heightened infiltration of immune cells, and there existed a direct association between the expression of FDX1 and the regulation of immune checkpoint. In vitro experiments demonstrated that FDX1 knockdown reduced proliferation, migration, invasion and transition from G2 to M phase in glioma cells. Conclusion: In glioma, FDX1 demonstrated a positive association with the advancement of malignancy and changes in the infiltration of immune cells.

Single-cell and whole-transcriptome sequencing of lymph node metastasis-related gene signature: A large-scale pan-cancer cohort, machine learning and experimental study.

BACKGROUND: Lymph node metastasis (LNM) is an independent prognostic factor in numerous types of cancer. Therefore, a LNM-related gene-based nomogram may precisely predict survival and drug sensitivity, and reveal the mechanism underlying LNM. MATERIALS AND METHODS: Gene sequencing profiles of pan-cancer data (33 cancer types) were acquired from The Cancer Genome Atlas UCSC Xena database. Patients were classified into primary (N = 10,071) and testing (N = 5,036) cohorts. The lymph node score (LNscore) was established via single-cell RNA sequencing, whole-transcriptome sequencing, machine learning, and Cox regression analyses. A novel prognosis model, formulated by incorporating the LNscore and clinical characteristics, was evaluated using the concordance index, calibration curve, and decision curve analysis. Moreover, patients were assigned into high- and low-risk groups according to the median LNscore. We investigated these two groups for survival prognosis, functional enrichment, immune infiltration, and drug sensitivity. In addition, we silenced and overexpressed insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2). We also analyzed the behavior of breast cancer (BRCA) cells regarding lymphatic metastasis and lymphangiogenesis in vitro. IGF2BP2 stimulated the proliferation of BRCA cells via 5-Ethynyl-2'-deoxyuridine and Cell Counting Kit-8 experiments. RESULTS: A LNM-related set of 12 genes was identified and utilized to determine the LNscore. The concordance-index of both cohorts in the LNscore-based model was >0.7. The immune landscape revealed that the sensitivity to immunotherapy might be better in the high-risk group versus the low-risk group. In addition, we discovered that IGF2BP2 was overexpressed in BRCA tissues and significantly associated with poor survival. Functional analysis indicated that IGF2BP2 promoted BRCA cell migration and proliferation. Additionally, IGF2BP2 accelerated lymphatic metastasis and lymphangiogenesis in vivo. CONCLUSIONS: A novel LNscore-based model was established via comprehensive analysis of LNM-related genes. This model can accurately predict patient survival and drug sensitivity, and reveal the mechanism of LNM in the pan-cancer setting.

A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study.

BACKGROUND: Axillary lymph nodes (ALN) status serves as a crucial prognostic indicator in breast cancer (BC). The aim of this study was to construct a radiogenomic multimodal model, based on machine learning and whole-transcriptome sequencing (WTS), to accurately evaluate the risk of ALN metastasis (ALNM), drug therapeutic response and avoid unnecessary axillary surgery in BC patients. METHODS: In this study, conducted a retrospective analysis of 1078 BC patients from The Cancer Genome Atlas (TCGA), The Cancer Imaging Archive (TCIA), and Foshan cohort. These patients were divided into the TCIA cohort ( N =103), TCIA validation cohort ( N =51), Duke cohort ( N =138), Foshan cohort ( N =106), and TCGA cohort ( N =680). Radiological features were extracted from BC radiological images and differentially expressed gene expression was calibrated using technology. A support vector machine model was employed to screen radiological and genetic features, and a multimodal model was established based on radiogenomic and clinical pathological features to predict ALNM. The accuracy of the model predictions was assessed using the area under the curve (AUC) and the clinical benefit was measured using decision curve analysis. Risk stratification analysis of BC patients was performed by gene set enrichment analysis, differential comparison of immune checkpoint gene expression, and drug sensitivity testing. RESULTS: For the prediction of ALNM, rad-score was able to significantly differentiate between ALN- and ALN+ patients in both the Duke and Foshan cohorts ( P <0.05). Similarly, the gene-score was able to significantly differentiate between ALN- and ALN+ patients in the TCGA cohort ( P <0.05). The radiogenomic multimodal nomogram demonstrated satisfactory performance in the TCIA cohort (AUC 0.82, 95% CI: 0.74-0.91) and the TCIA validation cohort (AUC 0.77, 95% CI: 0.63-0.91). In the risk sub-stratification analysis, there were significant differences in gene pathway enrichment between high and low-risk groups ( P <0.05). Additionally, different risk groups may exhibit varying treatment responses ( P <0.05). CONCLUSION: Overall, the radiogenomic multimodal model employs multimodal data, including radiological images, genetic, and clinicopathological typing. The radiogenomic multimodal nomogram can precisely predict ALNM and drug therapeutic response in BC patients.

A prognostic signature based on snoRNA predicts the overall survival of lower-grade glioma patients.

Introduction: Small nucleolar RNAs (snoRNAs) are a group of non-coding RNAs enriched in the nucleus which direct post-transcriptional modifications of rRNAs, snRNAs and other molecules. Recent studies have suggested that snoRNAs have a significant role in tumor oncogenesis and can be served as prognostic markers for predicting the overall survival of tumor patients. Methods: We screened 122 survival-related snoRNAs from public databases and eventually selected 7 snoRNAs that were most relevant to the prognosis of lower-grade glioma (LGG) patients for the establishment of the 7-snoRNA prognostic signature. Further, we combined clinical characteristics related to the prognosis of glioma patients and the 7-snoRNA prognostic signature to construct a nomogram. Results: The prognostic model displayed greater predictive power in both validation set and stratification analysis. Results of enrichment analysis revealed that these snoRNAs mainly participated in the post-transcriptional process such as RNA splicing, metabolism and modifications. In addition, 7-snoRNA prognostic signature were positively correlated with immune scores and expression levels of multiple immune checkpoint molecules, which can be used as potential biomarkers for immunotherapy prediction. From the results of bioinformatics analysis, we inferred that SNORD88C has a major role in the development of glioma, and then performed in vitro experiments to validate it. The results revealed that SNORD88C could promote the proliferation, invasion and migration of glioma cells. Discussion: We established a 7-snoRNA prognostic signature and nomogram that can be applied to evaluate the survival of LGG patients with good sensitivity and specificity. In addition, SNORD88C could promote the proliferation, migration and invasion of glioma cells and is involved in a variety of biological processes related to DNA and RNA.

The research landscape of immunology research in spinal cord injury from 2012 to 2022.

Background: Spinal cord injury (SCI) is defined as traumatic damage to the spinal cord, affecting over three million patients worldwide, and there is still no treatment for the injured spinal cord itself. In recent years, immunology research on SCI has been published in various journals. Methods: To systematically analyze the research hotspots and dynamic scientific developments of immunology research in SCI, we conducted a bibliometric and knowledge map analysis to help researchers gain a global perspective in this research field. Results: The bibliometric study we completed included 1788 English-language papers published in 553 journals by 8861 authors from 1901 institutions in 66 countries/regions. Based on the references and keyword analysis, researchers in the past 10 years have mainly focused on the research directions of "monocyte chemoattractor protein 1," "nitric oxide," "pain," and "nitric oxide synthase" related to immunological research in SCI. However, with the development of other new directions such as "extracellular vesicles" (2019-2022), "Regenerative medicine" (2019-2022), "stromal cells" (2018-2022), "motor recovery" (2019-2022), and "glial activation" (2019-2022). Researchers prefer to study the application of regenerative strategies in SCI, the mechanism of extracellular vesicles in the development of SCI, the activation of spinal glial cells in SCI, and the pathways of motor recovery. This bibliometric analysis of immunology research in SCI summarizes the current status of this research field. The relationship between extracellular vesicles, regenerative medicine, stromal cells, motor recovery, and glial activation is currently a major research frontier. Further research and cooperation worldwide need to be enhanced. Conclusion: We believe that our research can help researchers quickly grasp the current hotspot of immunology research in SCI and determine a new direction for future research.

NFYB increases chemosensitivity in glioblastoma by promoting HDAC5-mediated transcriptional inhibition of SHMT2.

Temozolomide (TMZ) is a commonly used chemotherapeutic agent for glioblastoma (GBM), but acquired drug resistance prevents its therapeutic efficacy. We investigated potential mechanisms underlying TMZ resistance and glycolysis in GBM cells through regulation by nuclear transcription factor Y subunit ß (NFYB) of the oncogene serine hydroxymethyltransferase 2 (SHMT2). GBM U251 cells were transfected with NFYB-, SHMT2-, and the potential NFYB target histone deacetylase 5 (HDAC5)-related vectors. Glucose uptake and lactate production were measured with detection kits. CCK-8/colony formation, scratch, Transwell, and flow cytometry assays were performed to detect cell proliferation, migration, invasion, and apoptosis, respectively. The binding of NFYB to the HDAC5 promoter and the regulation of NFYB on HDAC5 promoter activity were detected with chromatin immunoprecipitation and dual-luciferase reporter assays, respectively. NFYB and HDAC5 were poorly expressed and SHMT2 was expressed at high levels in GBM U251 cells. NFYB overexpression or SHMT2 knockdown decreased glucose uptake, lactate production, proliferation, migration, and invasion and increased apoptosis and TMZ sensitivity of the cells. NFYB activated HDAC5 to inhibit SHMT2 expression. SHMT2 overexpression nullified the inhibitory effects of NFYB overexpression on glycolysis and TMZ resistance. Thus, NFYB may reduce tumorigenicity and TMZ resistance of GBM through effects on the HDAC5/SHMT2 axis.

TUBA1C is a potential new prognostic biomarker and promotes bladder urothelial carcinoma progression by regulating the cell cycle.

BACKGROUND: TUBA1C is an α-tubulin isoform involved in mitosis, and its dysregulation has been implicated in tumor progression. There is still no clear understanding of its role in bladder urothelial carcinoma (BLCA). METHODS: This study examined the differential expression of TUBA1C and its prognostic significance in bladder cancer based on data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and also assessed the correlation of TUBA1C expression level with immune cell infiltration and immune checkpoint gene expression levels and the half-inhibitory concentration (IC50) of different chemotherapeutic agents. Immunotherapy response was estimated using the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. We detected TUBA1C expression in BLCA cells using PCR and Western blotting. Functional assays, including CCK-8, colony formation, transwell, apoptosis and cell cycle assays, were also performed to assess the oncogenic role of TUBA1C in BLCA. RESULT: In three independent public cohorts, TUBA1C was significantly upregulated in bladder tumor tissues, and high TUBA1C expression in bladder cancer was associated with a poorer outcome than low expression. TUBA1C was an independent prognostic risk factor for bladder cancer, and numerous immune checkpoint genes and infiltrating immune cells were associated with TUBA1C. TIDE analysis revealed that TUBA1C showed great potential for predicting the immunotherapy response in bladder cancer patients. In addition, drug sensitivity analysis revealed that high TUBA1C expression indicated sensitivity to multiple chemotherapeutic agents. Functional assays revealed that silencing TUBA1C significantly inhibited the proliferation, migration and invasion of BLCA cells and induced apoptosis and cell cycle arrest. CONCLUSION: The overexpression of TUBA1C in bladder cancer predicts a poor prognosis and may also be a potential immunotherapeutic target. As a prognostic marker, TUBA1C influences tumor progression by regulating the cell cycle.

Potential impact of time trend of whole grain intake on burden of major cancers in China.

Numerous studies have revealed associations between high intake of whole grains and reduced risk of various cancers. Yet, in recent decades, the traditional Chinese diets have been challenged by reduction in whole grains and increase in refined grains. To assess the impact of this dietary transition on cancer prevention, we analyzed the time trend of whole grain intake using nationally representative sampling data of over 15 thousand individuals from the China Health and Nutrition Survey. We applied the comparative risk assessment method to estimate the population attributable fraction of cancers due to insufficient whole grain intake from 1997 to 2011 and projected the trend of whole grain intake and the associated burden of cancers to 2035. We found a significant decrease of approximately 59% of whole grain intake in the Chinese population from 1997 to 2011. Compared with 1997, insufficient intake of whole grains was responsible for 9940 more cases of breast cancer, 12,903 more cases of colorectal cancer and 434 more cases of pancreatic cancer in 2011. Our projections suggest that if every Chinese would consume 125 g whole grain per day as recommended by the latest Chinese Dietary Guidelines, 0.63% bladder cancer, 8.98% breast cancer, 15.85% colorectal cancer, 3.86% esophageal cancer, 2.52% liver cancer and 2.22% pancreatic cancer (totaling 186,659 incident cases) could theoretically be averted by 2035. Even if everyone maintained the 2011 whole grain intake level, an estimated 8.38% of cancer events could still be prevented by 2035.

"Blue-free" orange ZnO-related light-emitting diode based on a natural interface layer of Ga2O3 and ZnGa2O4.

To fabricate a ZnO-related light-emitting diode (LED) with zero emission at blue wavelengths ("blue-free"), an ingenious strategy is employed. Specifically, for the first time to the best of our knowledge, a natural oxide interface layer, possessing remarkable visible emission potential, is introduced into the Au/i-ZnO/n-GaN metal-insulator-semiconductor (MIS) structure. The unique Au/i-ZnO/interface layer/n-GaN structure successfully eliminated the harmful blue emissions (400-500 nm) from the ZnO film, and the remarkable orange electroluminescence is mainly attributed to the impact ionization process of the natural interface layer at high electric field. It is worth mentioning that the device achieved ultra-low color temperature (2101 K) and excellent color rendering index (92.8) under electrical injection, indicating that the device could fulfill the requirements of electronic display systems and general illumination, and might even play unexpected roles in special lighting domains. The results obtained provide a novel and effective strategy for the design and preparation of ZnO-related LEDs.

Classification related to immunogenic cell death predicts prognosis, immune microenvironment characteristics, and response to immunotherapy in lower-grade gliomas.

Background: Immunogenic cell death (ICD) is a form of cell death that elicits immune responses against the antigens found in dead or dying tumor cells. Growing evidence implies that ICD plays a significant role in triggering antitumor immunity. The prognosis for glioma remains poor despite many biomarkers being reported, and identifying ICD-related biomarkers is imminent for better-personalized management in patients with lower-grade glioma (LGG). Materials and methods: We identified ICD-related differentially expressed genes (DEGs) by comparing gene expression profiles obtained across Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) cohorts. On the foundation of ICD-related DEGs, two ICD-related clusters were identified through consensus clustering. Then, survival analysis, functional enrichment analysis, somatic mutation analysis, and immune characteristics analysis were performed in the two ICD-related subtypes. Additionally, we developed and validated a risk assessment signature for LGG patients. Finally, we selected one gene (EIF2AK3) from the above risk model for experimental validation. Results: 32 ICD-related DEGs were screened, dividing the LGG samples from the TCGA database into two distinct subtypes. The ICD-high subgroup showed worse overall survival (OS), greater immune infiltration, more active immune response process, and higher expression levels of HLA genes than the ICD-low subgroup. Additionally, nine ICD-related DEGs were identified to build the prognostic signature, which was highly correlated with the tumor-immune microenvironment and could unambiguously be taken as an independent prognostic factor and further verified in an external dataset. The experimental results indicated that EIF2AK3 expression was higher in tumors than paracancerous tissues, and high-expression EIF2AK3 was enriched in WHO III and IV gliomas by qPCR and IHC, and Knockdown of EIF2AK3 suppressed cell viability and mobility in glioma cells. Conclusion: We established novel ICD-related subtypes and risk signature for LGG, which may be beneficial to improving clinical outcome prediction and guiding individualized immunotherapy.

[Modeling the noninvasive bi-level positive airway pressure ventilation therapy system and simulated application].

Without artificial airway though oral, nasal or airway incision, the bi-level positive airway pressure (Bi-PAP) has been widely employed for respiratory patients. In an effort to investigate the therapeutic effects and measures for the respiratory patients under the noninvasive Bi-PAP ventilation, a therapy system model was designed for virtual ventilation experiments. In this system model, it includes a sub-model of noninvasive Bi-PAP respirator, a sub-model of respiratory patient, and a sub-model of the breath circuit and mask. And based on the Matlab Simulink, a simulation platform for the noninvasive Bi-PAP therapy system was developed to conduct the virtual experiments in simulated respiratory patient with no spontaneous breathing (NSB), chronic obstructive pulmonary disease (COPD) and acute respiratory distress syndrome (ARDS). The simulated outputs such as the respiratory flows, pressures, volumes, etc, were collected and compared to the outputs which were obtained in the physical experiments with the active servo lung. By statistically analyzed with SPSS, the results demonstrated that there was no significant difference ( P > 0.1) and was in high similarity ( R > 0.7) between the data collected in simulations and physical experiments. The therapy system model of noninvasive Bi-PAP is probably applied for simulating the practical clinical experiment, and maybe conveniently applied to study the technology of noninvasive Bi-PAP for clinicians.

Identification of cuproptosis-related subtypes and the development of a prognostic model in glioma.

Introduction: A copper-dependent cell death, cuproptosis, involves copper binding with lipoylated tricarboxylic acid (TCA) cycle components. In cuproptosis, ferredoxin 1 (FDX1) and lipoylation act as key regulators. The mechanism of cuproptosis differs from the current knowledge of cell death, which may invigorate investigations into copper's potential as a cancer treatment. An extremely dismal prognosis is associated with gliomas, the most prevalent primary intracranial tumor. In patients with glioma, conventional therapies, such as surgery and chemotherapy, have shown limited improvement. A variety of cell death modes have been confirmed to be operative in glioma oncogenesis and participate in the tumor microenvironment (TME), implicated in glioma development and progression. In this study, we aimed to explore whether cuproptosis influences glioma oncogenesis. Methods: Gene expression profiles related to cuproptosis were comprehensively evaluated by comparing adjacent tissues from glioma tissues in The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) database. Gene expression, prognostic, clinical, and pathological data of lower-grade gliomas (LGG) and glioblastoma were retrieved from TCGA and Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) databases. The datasets were managed by "Combat" algorithm to eliminate batch effects and then combined. A consensus clustering algorithm based on the Partitioning Around Medoid (PAM) algorithm was used to classified 725 patients with LGG and glioblastoma multiforme (GBM) into two cuproptosis subtypes. According to the differentially expressed genes in the two cuproptosis subtypes, 725 patients were divided into 2 gene subtypes. Additionally, a scoring system that associated with TME was constructed to predict patient survival and patient immunotherapy outcomes. Furthermore, we constructed a prognostic CRG-score and nomogram system to predict the prognosis of glioma patients. 95 tissue specimens from 83 glioma patients undergoing surgical treatment were collected, including adjacent tissues. Using immunohistochemistry and RT-qPCR, we verified cuproptosis-related genes expression and CRG-score predictive ability in these clinical samples. Results: Our results revealed extensive regulatory mechanisms of cuproptosis-related genes in the cell cycle, TME, clinicopathological characteristics, and prognosis of glioma. We also developed a prognostic model based on cuproptosis. Through the verifications of database and clinical samples, we believe that cuproptosis affects the prognosis of glioma and potentially provides novel glioma research approaches. Conclusion: We suggest that cuproptosis has potential importance in treating gliomas and could be utilized in new glioma research efforts.

High expression of ABCF1 is an independent predictor of poor prognosis in bladder cancer.

ABCF1, a member of the ATP-binding cassette (ABC) transporter family, is involved in the malignant progression of tumors. However, the role of ABCF1 in bladder cancer is poorly understood. In our study, we explored the differential expression of ABCF1 in bladder cancer and normal bladder tissues based on bioinformatic analysis and immunohistochemical results. GSEA was performed to ascertain the potential related signaling pathways of ABCF1. The relationship between ABCF1 expression and bladder cancer progression was analyzed using the GSE13507 dataset. In addition, the differential expression of ABCF1 in the cell lines was verified by quantitative real-time polymerase chain reaction (qRT‒PCR) and Western blotting. ABCF1 was upregulated in bladder cancer, and the high expression of ABCF1 was closely related to sex (P = 0.00056), grade (P = 0.00049), T stage (P = 0.00007), and N stage (P = 0.0076). High expression of ABCF1 was correlated with poor overall survival in bladder cancer patients (P < 0.001). In addition, univariate and multivariate Cox regression analyses showed that high ABCF1 expression was an independent factor for poor prognosis in bladder cancer patients. Therefore, ABCF1 expression is closely related to the progression of bladder cancer and can be used as a potential indicator of poor prognosis and a therapeutic target for bladder cancer.

IGF2BP3 overexpression predicts poor prognosis and correlates with immune infiltration in bladder cancer.

BACKGROUND: IGF2BP3 expression is associated with poor prognosis in cancers of multiple tissue origins. However, the precise mechanism of its co-carcinogenic action in bladder cancer is unknown. METHODS: We aimed to demonstrate the relationship between IGF2BP3 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. We next validated IGF2BP3 expression in the Gene Expression Omnibus (GEO) database (GSE3167). Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic values of IGF2BP3. Cox and logistic regression were used to explore the factors affecting the prognosis. Protein-protein interactions (PPIs) network was constructed by STRING. Enrichment analyses were performed to infer involved pathways and functional categories of IGF2BP3 using the cluster Profiler package. We applied single-sample gene set enrichment analysis (ssGSEA) algorithm and TIMER database to evaluate the expression level of immune genes. RESULTS: Pan-cancer analyses reveal that IGF2BP3 was higher in most cancer types, including bladder cancer, and the same results were found in GSE3167. The area under the ROC curve of IGF2BP3 was 0.736, which indicated that IGF2BP3 may be a potential diagnostic biomarker. High IGF2BP3 expression was associated with poorer overall survival (OS) (P = 0.015). For validation, we collected 95 bladder cancer samples and found that IGF2BP3 expression was higher in bladder cancer tissues than that in non-tumor bladder tissues by immunohistochemistry staining. We found a positive correlation between the expression level of IGF2BP3 and the clinical stage of bladder cancer. Immunocyte infiltration analysis showed that high IGF2BP3 expression was correlated with regulating the infiltration level of immune cell, including neutrophil cells and macrophages. IGF2BP3 promotes migration and invasion of bladder cancer cells, while IGF2BP3 inhibition had the opposite effects. Higher IGF2BP3 expression was closely associated with advanced TNM stage. CONCLUSION: IGF2BP3 overexpression was related to disease progression and poor prognosis, as well as infiltration of immune cells in bladder cancer. IGF2BP3 can be a promising independent prognostic biomarker and potential treatment target for bladder cancer.

miR-33b in human cancer: Mechanistic and clinical perspectives.

The microRNAs (miRNAs), an extensive class of small noncoding RNAs (∼22 nucleotides), have been shown to have critical functions in various biological processes during development. miR-33b (or hsa-miR-33b) is down-regulated in cancer of multiple systems. Notably, at least 27 protein-coding genes can be targeted by miR-33b. miR-33b regulates the cell cycle, cell proliferation, various metabolism pathways, epithelial-mesenchymal transition (EMT), cancer cell invasion and migration, etc. In prostate cancer, Cullin 4B (CUL4B) can be recruited to the promoter to inhibit the expression of miR-33b. In gastric cancer, the hypermethylation of the CpG island regulated the expression of miR-33b. Besides, miR-33b could be negatively regulated by 7 competing-endogenous RNAs (ceRNAs), which are all long non-coding RNAs (lncRNAs). There are at least 4 signaling pathways, including NF-κB, MAP8, Notch1, and Wnt/ß-catenin signaling pathways, which could be regulated partially by miR-33b. Additionally, low expression of miR-33b was associated with clinicopathology and prognosis in cancer patients. In addition, the aberrant expression of miR-33b was connected with the resistance of cancer cells to 5 anticancer drugs (cisplatin, docetaxel, bortezomib, paclitaxel, and daunorubicin). Importantly, our work systematically summarizes the aberrant expression of miR-33b in various neoplastic diseases and the effect of its downregulation on the biological behavior of cancer cells. Furthermore, this review focuses on recent advances in understanding the molecular regulation mechanisms of miR-33b. Moreso, the relationship between the miR-33b expression levels and the clinicopathological data and prognosis of tumor patients was summarized for the first time. Overall, we suggest that the current studies of miR-33b are insufficient but provide potential hints and direction for future miR-33b-related research.

Leveraging a gene signature associated with disulfidptosis identified by machine learning to forecast clinical outcomes, immunological heterogeneities, and potential therapeutic targets within lower-grade glioma.

Background: Disulfidptosis, a newly defined type of programmed cell death, has emerged as a significant regulatory process in the development and advancement of malignant tumors, such as lower-grade glioma (LGG). Nevertheless, the precise biological mechanisms behind disulfidptosis in LGG are yet to be revealed, considering the limited research conducted in this field. Methods: We obtained LGG data from the TCGA and CGGA databases and performed comprehensive weighted co-expression network analysis, single-sample gene set enrichment analysis, and transcriptome differential expression analyses. We discovered nine genes associated with disulfidptosis by employing machine learning methods like Cox regression, LASSO regression, and SVM-RFE. These were later used to build a predictive model for patients with LGG. To confirm the expression level, functional role, and impact on disulfidptosis of ABI3, the pivotal gene of the model, validation experiments were carried out in vitro. Results: The developed prognostic model successfully categorized LGG patients into two distinct risk groups: high and low. There was a noticeable difference in the time the groups survived, which was statistically significant. The model's predictive accuracy was substantiated through two independent external validation cohorts. Additional evaluations of the immune microenvironment and the potential for immunotherapy indicated that this risk classification could function as a practical roadmap for LGG treatment using immune-based therapies. Cellular experiments demonstrated that suppressing the crucial ABI3 gene in the predictive model significantly reduced the migratory and invasive abilities of both SHG44 and U251 cell lines while also triggering cytoskeletal retraction and increased cell pseudopodia. Conclusion: The research suggests that the prognostic pattern relying on genes linked to disulfidptosis can provide valuable insights into the clinical outcomes, tumor characteristics, and immune alterations in patients with LGG. This could pave the way for early interventions and suggests that ABI3 might be a potential therapeutic target for disulfidptosis.

Effect of Laser Irradiation and Tensile Stress on Microstructure and Magnetic Properties of Fe-Based Amorphous Alloys.

The effect of laser irradiation and tensile stress on the microstructure and soft magnetic properties of the FeSiBNbCu nanocrystalline alloy prepared using a continuous laser has been investigated. The experimental results indicate that a decreased laser scanning speed provides more thermal energy to induce nanocrystals and encourage grain growth. When the scanning speed is excessively high, the crystallization process will cease due to a lack of energy to drive diffusion phase transitions. Nevertheless, the introduction of tensile stress could significantly promote crystallization in FeSiBNbCu alloy samples irradiated at these high laser scanning speeds. This phenomenon can be attributed to the augmentation of compressive thermal stress at the interface between the laser-treated track and the untreated region. This heightened compressive stress promotes the diffusivity of atoms, and, as a result, the transformation from amorphous to crystalline states can be enhanced. As the applied tensile stress increases, both grain size and crystalline volume fraction exhibit a proportional augmentation. Consequently, these changes manifest in the soft magnetic properties. The crystalline volume fraction can reach 62%, and the coercivity is 2.9 A/m at the optimized scanning speed; these values correspond to 54% and 3.3 A/m under specific tensile stress loading.

The role of lncRNA just proximal to XIST (JPX) in human disease phenotypes and RNA methylation: The novel biomarker and therapeutic target potential.

Increasing evidence suggests that long non-coding RNAs (lncRNAs) are closely related to the initialization and development of human diseases. lncRNA just proximal to XIST (JPX), as a newly identified lncRNA, has been reported to be aberrantly expressed and associated with pathophysiological traits in numerous diseases, particularly cancers. More importantly, JPX has been proven to play important roles in various biological functions, including cell proliferation, migration, invasion, apoptosis, chemoresistance, and differentiation. In addition, we discuss the diverse molecular mechanisms and correlation with RNA methylation of JPX in several cancers. In this Review, we summarize current studies on JPX's roles in diseases and its potential application as a biomarker for both diagnoses and prognoses and a therapeutic target in human diseases.