Cuproptosis: Mechanism, role, and advances in urological malignancies.

Prostate, bladder, and kidney cancers are the most common malignancies of the urinary system. Chemotherapeutic drugs are generally used as adjuvant treatment in the middle, late, or recurrence stages after surgery for urologic cancers. However, traditional chemotherapy is plagued by problems such as poor efficacy, severe side effects, and complications. Copper-containing nanomedicines are promising novel cancer treatment modalities that can potentially overcome these disadvantages. Copper homeostasis and cuproptosis play crucial roles in the development, adaptability, and therapeutic sensitivity of urological malignancies. Cuproptosis refers to the direct binding of copper ions to lipoylated components of the tricarboxylic acid cycle, leading to protein oligomerization, loss of iron-sulfur proteins, proteotoxic stress, and cell death. This review focuses on copper homeostasis and cuproptosis as well as recent findings on copper and cuproptosis in urological malignancies. Furthermore, we highlight the potential therapeutic applications of copper- and cuproptosis-targeted therapies to better understand cuproptosis-based drugs for the treatment of urological tumors in the future.

Birt-Hogg-Dubé syndrome in an overall view: Focus on the clinicopathological prospects in renal tumors.

Birt-Hogg-Dubé syndrome (BHD) represents a rare autosomal dominant tumor predisposition syndrome characterized by skin lesions, lung cysts, and renal tumors. The predominant histological subtypes of BHD-related renal tumors include hybrid oncocytoma-chromophobe tumors, oncocytomas, and chromophobe renal cell carcinomas, all exhibiting eosinophilic/oncocytic features. Immunohistochemistry staining for KIT (CD117) and CK7 exhibits variability in these tumor types. Germline mutations in FLCN have been consistently identified. Generally, patients with BHD demonstrate a favorable prognosis with minimal metastatic potential. Nonetheless, the comprehensive elucidation of pathological characteristics of BHD remains incomplete, particularly in BHD-associated renal tumors that deviate from the previously identified subtypes, thereby complicating the differential diagnosis. In this review, we provide a comprehensive overview of BHD encompassing epidemiology, clinical manifestations, genetic and molecular pathogenesis, as well as clinical diagnostic modalities. Emphasis is placed on clinicopathological features, specifically focusing on BHD-associated renal tumors. Collectively, this review aims to present the latest insights into BHD which benefits in the early detection, therapeutic decision-making, and prognosis prediction in BHD cases, and deepen the understanding of sporadic renal tumors.

Development trends and knowledge framework in the application of magnetic resonance imaging in prostate cancer: a bibliometric analysis from 1984 to 2022.

Background: Prostate cancer (PCa) is the most common tumor of the male genitourinary system. With the development of imaging technology, the role of magnetic resonance imaging (MRI) in the management of PCa is increasing. The present study summarizes research on the application of MRI in the field of PCa using bibliometric analysis and predicts future research hotspots. Methods: Articles regarding the application of MRI in PCa between January 1, 1984 and June 30, 2022 were selected from the Web of Science Core Collection (WoSCC) on November 6, 2022. Microsoft Excel 2016 and the Bibliometrix Biblioshiny R-package software were used for data analysis and bibliometric indicator extraction. CiteSpace (version 6.1.R3) was used to visualize literature feature clustering, including co-occurrence analysis of countries, institutions, authors, references, and burst keywords analysis. Results: A total of 10,230 articles were included in the study. Turkbey was the most prolific author. The USA was the most productive country and had strong partnerships with other countries. The most productive institution was Memorial Sloan Kettering Cancer Center. Journal of Magnetic Resonance Imaging and Radiology were the most productive and highest impact factor (IF) journals in the field, respectively. Timeline views showed that "#1 multiparametric magnetic resonance imaging", "#4 pi-rads", and "#8 psma" were currently the latest research hotspots. Keywords burst analysis showed that "machine learning", "psa density", "multi parametric mri", "deep learning", and "artificial intelligence" were the most frequently used keywords in the past 3 years. Conclusions: MRI has a wide range of applications in PCa. The USA is the leading country in this field, with a concentration of highly productive and high-level institutions. Meanwhile, it can be projected that "deep learning", "radiomics", and "artificial intelligence" will be research hotspots in the future.

Association of long-term exposure to ambient PM2.5 and its constituents with gut microbiota: Evidence from a China cohort.

Accumulating animal experiments and epidemiological studies have found that exposure to fine particulate matter (PM2.5) is associated with altered gut microbiota (GM). However, it is unclear what kind of role the PM2.5 constituents play in the PM2.5-GM association. Therefore, this study aimed to investigate the association of long-term exposure to PM2.5 and its constituents (PMcons) with GM. This study included 1583 participants from a cohort in Southwest China. Satellite remote sensing and chemical transport modelling were used to determine the yearly average concentrations of PMcons. GM data were derived from 16 s sequencing based on stool samples. Generalized propensity score weighting regression and Bayesian Kernel Machine Regression (BKMR) were used to estimate the individual and joint association of exposure to PMcons with the Shannon index. The weighted correlation analysis was used to estimate the association of PMcons with the composition of GM. The result showed that an interquartile range increase of 3-year average black carbon (BC), ammonium, nitrate, organic matter (OM), sulfate, and soil particles (SOIL) were negatively associated with Shannon index with mean difference (95 % confidence interval) being -0.144 (-0.208, -0.080), -0.141 (-0.205, -0.078), -0.126 (-0.184, -0.068), -0.117 (-0.172, -0.062), -0.153 (-0.221, -0.085), and - 0.153 (-0.222, -0.085). BKMR indicated joint exposure to PMcons was associated with decreased Shannon index, and BC had the largest posterior inclusion probability (0.578). Weighted correlation analyses indicated PMcons were associated with decreased Bacteroidetes (r = -0.204, P < 0.001 for PM2.5) and increased Proteobacteria (r = 0.273, P < 0.001 for PM2.5). These results revealed that long-term exposure to PMcons was associated with GM. BC was the most important constituent in the association, indicating that the source of BC should be controlled to mitigate the negative effects of PM2.5 on GM.

Efficient and selective removal of Hg(II) from water using recyclable hierarchical MoS2/Fe3O4 nanocomposites.

Developing practical and cost-effective adsorbents with satisfactory mercury (Hg) remediation capability is indispensable for aquatic environment safety and public health. Herein, a recyclable hierarchical MoS2/Fe3O4 nanocomposite (by in-situ growth of MoS2 nanosheets on the surface of Fe3O4 nanospheres) is presented for the selective removal of Hg(II) from aquatic samples. It exhibited high adsorption capacity (∼1923.5 mg g -1), fast kinetics (k2 ∼ 0.56 mg g -1 min-1), broad working pH range (2-11), excellent selectivity (Kd > 1.0 × 107 mL g -1), and great reusability (removal efficiency > 90% after 20 cycles). In particular, removal efficiencies of up to ∼97% for different Hg(II) concentrations (10-1000 µg L -1) in natural water and industrial effluents confirmed the practicability of MoS2/Fe3O4. The possible mechanism for effective Hg(II) removal was discussed by a series of characterization analyses, which was attributed to the alteration of the MoS2 structure and the surface coordination of Hg-S. The accessibility of surface sulfur sites and the diffusion of Hg(II) in the solid-liquid system were enhanced due to the advantage of the expanded interlayer spacing (0.96 nm) and the hierarchical structure. This study suggests that MoS2/Fe3O4 is a promising material for Hg(II) removal in actual scenarios and provides a feasible approach by rationally constructing hierarchical structures to promote the practical applications of MoS2 in sustainable water treatments.

Superhydrophobic lignin-based multifunctional polyurethane foam with SiO2 nanoparticles for efficient oil adsorption and separation.

Superhydrophobic polyurethane foam is one of the most promising materials for oil-water separation. However, there are only limited studies prepared matrix superhydrophobic foams as adsorbents. In this paper, SiO2 modified by 1H, 1H, 2H, 2H-perfluorododecyl trichlorosilane (F-SiO2) was added into the lignin-based foam matrix by a one-step foaming technique. The average diameter of F-SiO2 was about 480 nm with an water contact angle (WCA) of 160.3°. The lignin-based polyurethane foam with F-SiO2 had a superhydrophobic water contact angle of 151.3°. There is no obvious change in contact angle after 100 cycles of compression or after cutting and abrasion. Scanning electron microscopy (SEM) analysis showed that F-SiO2 was distributed both on the surface and inside of the foam. The efficiency for oil-water separation reached 99 %. Under the light intensity of 1 kW/m2, the surface temperature of the lignin-based foam rose to 77.6 °C. In addition, the foam exhibited self-cleaning properties and degraded within 2 h in an alcoholic alkali solution. Thus, in this study, we developed a novel matrix superhydrophobic lignin-based polyurethane foam with an excellent promise to be used as oil water separation adsorbents in industrial wastewater treatment and oil spill clean-up processes.

Radiomics models based on multi-sequence MRI for preoperative evaluation of MUC4 status in pancreatic ductal adenocarcinoma: a preliminary study.

Background: Mucin 4 (MUC4) overexpression promotes tumorigenesis and increases the aggressiveness of pancreatic ductal adenocarcinoma (PDAC). To date, no study has reported the association between radiomics and MUC4 expression in PDAC. Thus, we aimed to explore the utility of radiomics based on multi-sequence magnetic resonance imaging (MRI) to predict the status of MUC4 expression in PDAC preoperatively. Methods: This retrospective study included 52 patients with PDAC who underwent MRI. The patients were divided into two groups based on MUC4 expression status. Two feature sets were extracted from the arterial and portal phases (PPs) of dynamic contrast-enhanced MRI (DCE-MRI). Univariate analysis, minimum redundancy maximum relevance (MRMR), and principal component analysis (PCA) were performed for the feature selection of each dataset, and features with a cumulative variance of 90% were selected to develop radiomics models. Clinical characteristics were gathered to develop a clinical model. The selected radiomics features and clinical characteristics were modeled by multivariable logistic regression. The combined model integrated radiomics features from different selected data sets and clinical characteristics. The classification metrics were applied to assess the discriminatory power of the models. Results: There were 22 PDACs with a high expression of MUC4 and 30 PDACs with a low expression of MUC4. The area under the receiver operating characteristic (ROC) curve (AUC) values of the arterial phase (AP) model, the PP model, and the combined model were 0.732 (0.591-0.872), 0.709 (0.569-0.849), and 0.861 (0.760-0.961), respectively. The AUC of the clinical model was 0.666 (0.600-0.682). The combined model that was constructed outperformed the AP, the PP, and the clinical models (P<0.05, although no statistical significance was observed in the combined model vs. AP model). Conclusions: Radiomics models based on multi-sequence MRI have the potential to predict MUC4 expression levels in PDAC.

Radiomics Model Based on MR Images to Discriminate Pancreatic Ductal Adenocarcinoma and Mass-Forming Chronic Pancreatitis Lesions.

BACKGROUND: It is difficult to identify pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP) lesions through conventional CT or MR examination. As an innovative image analysis method, radiomics may possess potential clinical value in identifying PDAC and MFCP. To develop and validate radiomics models derived from multiparametric MRI to distinguish pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP) lesions. METHODS: This retrospective study included 119 patients from two independent institutions. Patients from one institution were used as the training cohort (51 patients with PDAC and 13 patients with MFCP), and patients from the other institution were used as the testing cohort (45 patients with PDAC and 10 patients with MFCP). All the patients had pathologically confirmed results, and preoperative MRI was performed. Four feature sets were extracted from T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and the artery (A) and portal (P) phases of dynamic contrast-enhanced MRI, and the corresponding radiomics models were established. Several clinical characteristics were used to discriminate PDAC and MFCP lesions, and clinical model was established. The results of radiologists' evaluation were compared with pathology and radiomics models. Univariate analysis and the least absolute shrinkage and selection operator algorithm were performed for feature selection, and a support vector machine was used for classification. The receiver operating characteristic (ROC) curve was applied to assess the model discrimination. RESULTS: The areas under the ROC curves (AUCs) for the T1WI, T2WI, A and, P and clinical models were 0.893, 0.911, 0.958, 0.997 and 0.516 in the primary cohort, and 0.882, 0.902, 0.920, 0.962 and 0.649 in the validation cohort, respectively. All radiomics models performed better than clinical model and radiologists' evaluation both in the training and testing cohorts by comparing the AUC of various models, all P<0.050. Good calibration was achieved. CONCLUSIONS: The radiomics models based on multiparametric MRI have the potential ability to classify PDAC and MFCP lesions.

Synergistic effects of carbon nanoparticle-Cr-Pb in PM2.5 cause cell cycle arrest via upregulating a novel lncRNA NONHSAT074301.2 in human bronchial epithelial cells.

Inhalation of carcinogenic PM2.5 particles is a severe threat to all the people in both developing and developed nations. However, which components of PM2.5 and how they perturb human cells to cause various diseases are still not understood. Here, employing a reductionism approach, we revealed that one of the crucial toxic and pathogenic mechanisms of PM2.5 was the blocking of human bronchial cell cycle through upregulation of a novel long non-coding RNA NONHSAT074301.2 by carbon particles with payloads of Cr(VI) and Pb2+. We also discovered that NONHSAT074301.2 is a key regulatory molecule controlling cell cycle arrest at G2/M phase. This work highlights cellular function and molecular signaling events investigations using a 16-membered combinational model PM2.5 library which contain carbon particles carrying four toxic pollutants in all possible combinations at environmental relevant concentrations. This work demonstrates a very powerful methodology to elucidate mechanisms at molecular level and help unlock the "black box" of PM2.5-induced toxicities.

A radiomics model of liver CT to predict risk of hepatic encephalopathy secondary to hepatitis B related cirrhosis.

PURPOSE: To build a radiomics model of liver contrast-enhanced computed tomography (CT) to predict hepatic encephalopathy secondary to Hepatitis B related cirrhosis. MATERIALS AND METHODS: This study consisted of 304 consecutive patients with first-diagnosed hepatitis B related cirrhosis. 212 and 92 patients were randomly computer-generated into training and testing cohorts, among which 38 and 21 patients endured HE, respectively. 356 radiomics features of liver were extracted from portal venous-phase CT data, and 3 clinical features were collected from medical record. After data were standardized by Z-score, we used least absolute shrinkage and selection operator to choose useful radiomics features. Ultimately, three predictive models including a radiomics model, a clinical model and an integrated model of radiomics and clinical features were built by analysis of R-software. Predictive performance was tested by multivariable logistic regression, and evaluated by area under receiver-operating characteristic curve (AUC), and accuracy. RESULTS: 19 radiomics features of liver CT were selected. The selected radiomics features and 3 relevant clinical features were applied to develop a radiomics model, a clinical model, and an integrated model of both radiomics and clinical features. The integrated model showed better performance than the radiomics model or clinical model to predict HE (AUC = 0.94 vs. 0.91 or 0.76, and 0.87 vs. 0.86 or 0.73; accuracy = 0.93 vs. 0.89 or 0.83, and 0.83 vs. 0.84 or 0.77) in the training and testing cohorts, respectively. CONCLUSION: The integrated model of radiomics and clinical features could well predict HE secondary to hepatitis B related cirrhosis.

Magnetic resonance imaging for preoperative staging of pancreatic cancer based on the 8th edition of AJCC guidelines.

BACKGROUND: Preoperative staging of pancreatic cancer determines the choice of treatment. Magnetic resonance imaging (MRI) plays an important role in preoperative staging of pancreatic cancer. The American Joint Committee on Cancer (AJCC) TNM staging system was revised to its 8th version in 2016, there has been no report correlating the 8th edition of the AJCC TNM staging with preoperative MRI examinations and pathological findings. The purpose of our study is to determine the staging accuracy and evaluate the resectability by using MRI about pancreatic cancer compared with intraoperative or pathological findings according to the 8th edition of the AJCC TNM staging system. METHODS: One hundred thirty-two patients with a pathological diagnosis of pancreatic cancer who underwent preoperative MRI were identified. The clinical data, MRI findings and pathological findings were analyzed. Preoperative MRI staging and resectability evaluation were compared with pathological findings. The accuracy of MRI for preoperative T and N staging was evaluated, and the sensitivity, specificity and accuracy of MRI in evaluating the resectability were assessed. All the staging and resectability assessments were according to the 8th edition of the AJCC TNM staging system. RESULTS: Analysis showed that the accuracy of MRI for evaluation of the T and N stages was 82.6% (109/132) and 74.2% (98/132), respectively. The sensitivity and specificity of MRI in assessing the resectability were 94.2% and 71.4%, respectively. Integrating the 8th edition of the AJCC TNM stage, no significant differences were identified between the preoperative MRI and pathological results for the staging of pancreatic cancer (P=0.805). CONCLUSIONS: MRI is highly accurate for T staging and moderately accurate for N staging. MRI provides important preoperative evaluation of the stage and resectability of pancreatic cancer based on the 8th edition of the AJCC TNM staging system.

Lifestyle and lifetime occupational exposures may not play a role in the pathogenesis of Modic changes on the lumbar spine MR images.

BACKGROUND CONTEXT: Modic changes (MCs) have long been suspected as a pathologic cause of back pain. Although much attention has been focused on clinical perspectives, the etiology of MCs remains unclear. Although some studies have reported that sex, body mass index (BMI), cigarette smoking, and physical loading may associate with MCs, the observed associations are inconsistent among studies. PURPOSE: To investigate associations between MCs and lifestyle and lifetime occupational exposures using a general population sample. STUDY DESIGN: Cross-sectional study. PATIENT SAMPLE: The study was an extension of the Hangzhou Lumbar Spine Study, a population-based study of mainland Chinese focusing on lumbar degenerative changes. A total of 644 randomly selected subjects from a typical community in Hangzhou, Eastern China participated. OUTCOME MEASURES: The presence and type of MCs in the lumbosacral spine were evaluated on sagittal magnetic resonance images. Demographics, lifestyle factors, and occupational exposures were measured using a structured interview. METHODS: Univariate and multivariate logistic regressions were used to examine the associations of MCs with various environmental exposures. RESULTS: Among the 644 subjects (52.6±13.9 years; range 20-88 years) included in this study, 44.7% had MCs. In univariate regression analyses, the presence of MCs was associated with greater age, higher BMI, greater cigarette smoking, regular exercise, and absence of daily vehicle vibration. Modic changes were not univariately associated with sex or alcohol consumption. In addition, all occupational loading measurements were associated with the occurrence of MCs in univariate analyses, except work time spent in vehicles and work-related back injuries. However, in multivariate regression analyses, no statistically significant associations between the occurrence of MCs and lifestyle or lifetime occupational exposures were observed after adjusting for age, sex, and BMI. CONCLUSIONS: Age is an important determinant of MCs, with BMI and sex also playing a role. Lifestyle and occupational factors appear to have minor effects, if any, on the pathogenesis of MCs in the lumbar spine.

Prediction of axillary lymph node metastases in breast cancer patients based on pathologic information of the primary tumor.

BACKGROUND: Axillary lymph nodes (ALN) are the most commonly involved site of disease in breast cancer that has spread outside the primary lesion. Although sentinel node biopsy is a reliable way to manage ALN, there are still no good methods of predicting ALN status before surgery. Since morbidity in breast cancer surgery is predominantly related to ALN dissection, predictive models for lymph node involvement may provide a way to alert the surgeon in subgroups of patients. MATERIAL AND METHODS: A total of 1325 invasive breast cancer patients were analyzed using tumor biological parameters that included age, tumor size, grade, estrogen receptor, progesterone receptor, lymphovascular invasion, and HER2, to test their ability to predict ALN involvement. A support vector machine (SVM) was used as a classification model. The SVM is a machine-learning system developed using statistical learning theories to classify data points into 2 classes. Notably, SVM models have been applied in bioinformatics. RESULTS: The SVM model correctly predicted ALN metastases in 74.7% of patients using tumor biological parameters. The predictive ability of luminal A, luminal B, triple negative, and HER2 subtypes using subgroup analysis showed no difference, and this predictive performance was inferior, with only 60% accuracy. CONCLUSIONS: With an SVM model based on clinical pathologic parameters obtained in the primary tumor, it is possible to predict ALN status in order to alert the surgeon about breast cancer counseling and in decision-making for ALN management.

Interleukin-27 and interleukin-12 augment activation of distinct cord blood natural killer cells responses via STAT3 pathways.

BACKGROUND/PURPOSE: Umbilical cord blood is rich in primitive natural killer (NK) cells, which are activated by interleukin (IL)-12. It was previously reported that a novel IL-12 family cytokine, IL-27 comprised of EBI3 and p28, was elevated in maternal serum during normal pregnancy. Thus, we compared the immune regulatory functions of IL-27 and IL-12 on mononuclear cells derived from cord blood and adult peripheral blood. METHODS: After stimulation with IL-27, IL-12, and IL-27 combined with IL-12, the cytotoxicity against BJAB lymphoma cells by blood mononuclear cells was performed. Then immunofluorescence staining, reverse transcriptase-polymerase chain reaction and Western blotting were used to detect the effects of IL-27 and IL-12 in isolated NK cells. RESULTS: IL-27, IL-12, and IL-27 combined with IL-12 enhanced the cytotoxicity of adult peripheral blood cells and cord blood cells, but the proliferation of distinct subpopulations of cells was not evident. Similar results were also obtained with purified cord blood NK cells. Interestingly, distinct from IL-12, IL-27 could induce aggregation and morphological changes of umbilical cord blood cells. Finally, IL-27 combined with IL-12 could stimulate increased IL-27 receptor (gp130 and WSX-1) transcripts in purified cord blood NK cells. However, the activation of signal transducer and activator of transcription 3 (STAT3) in NK cells was only detected in the presence of IL-27, but not IL-12 alone. CONCLUSION: From previous results, we summarize our current understanding of the augmentation of distinct regulation of NK cells by IL-27 and IL-12.