Predicting histologic grades for pancreatic neuroendocrine tumors by radiologic image-based artificial intelligence: a systematic review and meta-analysis.

Background: Accurate detection of the histological grade of pancreatic neuroendocrine tumors (PNETs) is important for patients' prognoses and treatment. Here, we investigated the performance of radiological image-based artificial intelligence (AI) models in predicting histological grades using meta-analysis. Method: A systematic literature search was performed for studies published before September 2023. Study characteristics and diagnostic measures were extracted. Estimates were pooled using random-effects meta-analysis. Evaluation of risk of bias was performed by the QUADAS-2 tool. Results: A total of 26 studies were included, 20 of which met the meta-analysis criteria. We found that the AI-based models had high area under the curve (AUC) values and showed moderate predictive value. The pooled distinguishing abilities between different grades of PNETs were 0.89 [0.84-0.90]. By performing subgroup analysis, we found that the radiomics feature-only models had a predictive value of 0.90 [0.87-0.92] with I2 = 89.91%, while the pooled AUC value of the combined group was 0.81 [0.77-0.84] with I2 = 41.54%. The validation group had a pooled AUC of 0.84 [0.81-0.87] without heterogenicity, whereas the validation-free group had high heterogenicity (I2 = 91.65%, P=0.000). The machine learning group had a pooled AUC of 0.83 [0.80-0.86] with I2 = 82.28%. Conclusion: AI can be considered as a potential tool to detect histological PNETs grades. Sample diversity, lack of external validation, imaging modalities, inconsistent radiomics feature extraction across platforms, different modeling algorithms and software choices were sources of heterogeneity. Standardized imaging, transparent statistical methodologies for feature selection and model development are still needed in the future to achieve the transformation of radiomics results into clinical applications. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022341852.

Co-sensitization of Copper Indium Gallium Disulfide and Indium Sulfide on Zinc Oxide Nanostructures: Effect of Morphology in Electrochemical Carbon Dioxide Reduction.

Recent advances in nanoparticle materials can facilitate the electro-reduction of carbon dioxide (CO2) to form valuable products with high selectivity. Copper (Cu)-based electrodes are promising candidates to drive efficient and selective CO2 reduction. However, the application of Cu-based chalcopyrite semiconductors in the electrocatalytic reduction of CO2 is still limited. This study demonstrated that novel zinc oxide (ZnO)/copper indium gallium sulfide (CIGS)/indium sulfide (InS) heterojunction electrodes could be used in effective CO2 reduction for formic acid production. It has been determined that Faradaic efficiencies for formic acid production using ZnO nanowire (NW) and nanoflower (NF) structures vary due to structural and morphological differences. A ZnO NW/CIGS/InS heterojunction electrode resulted in the highest efficiency of 77.2% and 0.35 mA cm-2 of current density at a -0.24 V (vs. reversible hydrogen electrode) bias potential. Adding a ZTO intermediate layer by the spray pyrolysis method decreased the yield of formic acid and increased the yield of H2. Our work offers a new heterojunction electrode for efficient formic acid production via cost-effective and scalable CO2 reduction.

Barriers and facilitators to medical help-seeking in rural patients with mental illness: A qualitative meta-synthesis.

PURPOSE: Numerous barriers hinder individuals with mental illness from seeking medical assistance in rural regions, yet a comprehensive understanding of these challenges remains elusive. This meta-synthesis aims to understand the barriers and facilitators in medical help-seeking among rural individuals with mental illness. METHODS: We systematically searched seven databases (PubMed, CINAHL, Medline(OVID), PsycINFO(OVID), Cochrane, Embase, and ProQuest) to May 2023 and included the studies if they reported the barriers or/and facilitators to seek health care in rural patients with mental illness. Conduct hand search and citation search on Google Scholar for literature supplements. Thematic analysis was employed. RESULTS: The study included 27 articles reporting on the barriers and facilitators to seeking medical help in this population from 2007-2023. We ultimately identified themes at 3 levels: the individual with mental illness, the external environment and the health service system. CONCLUSIONS: We must design more effective strategies to improve mental health care access for rural patients, considering cultural nuances and health service utilization patterns. This requires a multi-level approach, tailored to the unique needs of diverse populations.

Prevalence of sexual dysfunction in Chinese patients with schizophrenia: a systematic review and meta-analysis.

Background: There may be a higher risk of sexual dysfunction in the schizophrenia population. China has made significant contributions to the global community of patients with schizophrenia. Currently, there is no estimation of the prevalence of sexual dysfunction in Chinese patients with schizophrenia. Aim: We conducted a meta-analysis to pool the evaluated prevalence of sexual dysfunction in Chinese patients with schizophrenia. Methods: We systematically searched PubMed, Web of Science, Embase, PsycINFO, China National Knowledge Infrastructure, China Science and Technology Journal Database, Wanfang Medical Network, and Huayi Academic Literature Database from inception to September 2023. Meta-analysis was conducted with R version 4.3.1. Outcomes: To examine the pooled prevalence of sexual dysfunctions among Chinese patients with schizophrenia. Results: In our meta-analysis, we included 16 studies with 5417 participants, among whom 1727 experienced sexual dysfunction. The results of the meta-analysis reveal that the prevalence of sexual dysfunction in Chinese patients with schizophrenia is 50.43% (95% CI, 37.86%-62.95%). Subgroup analysis results indicate that various factors-including the specific type of dysfunction, duration of illness, assessment tools, mean ages, study region, gender, research setting, marital status, publication years, and type of antipsychotics-all have a particular impact on the occurrence rate of sexual dysfunction in Chinese patients with schizophrenia. Female patients had a slightly higher prevalence of sexual dysfunction than male patients (65.22% vs 54.84%). Clinical Implications: The findings of this study can be used in high-quality nursing care for the schizophrenia population, particularly for the care of specific sexual dysfunction nursing. Strengths and Limitations: This meta-analysis is the first to evaluate the prevalence of sexual dysfunction in China among patients with schizophrenia. The limited number of studies is the most important limitation. Conclusions: The pooled prevalence of sexual dysfunction in Chinese patients with schizophrenia is relatively high, and the prevention and intervention of individual sexual dysfunctions in schizophrenia are advised.

LINC00909 up-regulates pluripotency factors and promotes cancer stemness and metastasis in pancreatic ductal adenocarcinoma by targeting SMAD4.

BACKGROUND: Pancreatic cancer stem cells are crucial for tumorigenesis and cancer metastasis. Presently, long non-coding RNAs were found to be associated with Pancreatic Ductal Adenocarcinoma stemness characteristics but the underlying mechanism is largely known. Here, we aim to explore the function of LINC00909 in regulating pancreatic cancer stemness and cancer metastasis. METHODS: The expression level and clinical characteristics of LINC00909 were verified in 80-paired normal pancreas and Pancreatic Ductal Adenocarcinoma tissues from Guangdong Provincial People's Hospital cohort by in situ hybridization. RNA sequencing of PANC-1 cells with empty vector or vector encoding LINC00909 was experimented for subsequent bioinformatics analysis. The effect of LINC00909 in cancer stemness and metastasis was examined by in vitro and in vivo experiments. The interaction between LINC00909 with SMAD4 and the pluripotency factors were studied. RESULTS: LINC00909 was generally upregulated in pancreatic cancer tissues and was associated with inferior clinicopathologic features and outcome. Over-expression of LINC00909 enhanced the expression of pluripotency factors and cancer stem cells phenotype, while knock-down of LINC00909 decreased the expression of pluripotency factors and cancer stem cells phenotype. Moreover, LINC00909 inversely regulated SMAD4 expression, knock-down of SMAD4 rescued the effect of LINC00909-deletion inhibition on pluripotency factors and cancer stem cells phenotype. These indicated the effect of LINC00909 on pluripotency factors and CSC phenotype was dependent on SMAD4 and MAPK/JNK signaling pathway, another downstream pathway of SMAD4 was also activated by LINC00909. Specifically, LINC00909 was localized in the cytoplasm in pancreatic cancer cells and decreased the stability the SMAD4 mRNA. Finally, we found over-expression of LINC00909 not only accelerated tumor growth in subcutaneous mice models, but also facilitated tumorigenicity and spleen metastasis in orthotopic mice models. CONCLUSION: We demonstrate LINC00909 inhibits SMAD4 expression at the post-transcriptional level, which up-regulates the expression of pluripotency factors and activates the MAPK/JNK signaling pathway, leading to enrichment of cancer stem cells and cancer metastasis in pancreatic cancer.

Prognostic significance of glucose-lipid metabolic index in pancreatic cancer patients with diabetes mellitus.

BACKGROUND: The incidence of pancreatic cancer (PC) is higher in diabetic patients due to disturbances in glucose and lipid metabolism caused by insulin resistance (IR). However, the effect of diabetes as well as IR on the prognosis of PC patients remains inconclusive. Our study aims to assess the impact of IR on the prognosis of PC patients with diabetes. METHODS: We conducted a retrospective analysis of 172 PC patients with diabetes in our institute from 2015 to 2021. Prognostic assessment was performed using univariate/multifactorial analysis and survival analysis. The predictive efficacy of metabolic indices was compared using receiver operator characteristic (ROC) curve analysis. RESULTS: One hundred twenty-one of 172 patients died during follow-up, with a median follow-up of 477 days and a median overall survival (OS) of 270 days. Survival analysis showed a significant difference in OS by IR related parameters, which were triglyceride-glucose index (TyG), triglyceride-glucose index-body mass index (TyG-BMI), and triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-c). The ROC curve indicated that TyG, TyG-BMI, and TG/HDL-c had prognostic efficacy for PC with diabetes. We next optimized TyG-BMI and obtained a new parameter, namely glucose-lipid metabolism index (GLMI), and the patients were classified into GLMI low group and high group based on the calculated cutoff value. The GLMI high group had higher TyG, TyG-BMI, TyG/HDL-c, BMI, TG, total cholesterol (TC), TC/HDL-c, fasting plasma glucose, CA199, and more advanced tumor stage compared to low group. Univariate and multivariate analyses showed that GLMI was an independent prognostic factor. Furthermore, the patients of GLMI high group had worse OS compared to low group and the ROC curves showed GLMI had better predictive ability than TyG and TyG-BMI. CONCLUSIONS: IR is associated with the outcome of PC patients with diabetes and higher level of IR indicates worse prognosis. GLMI has a good predictive value for PC with diabetes.

NINJ1 regulates ferroptosis via xCT antiporter interaction and CoA modulation.

Ninjurin-1 (NINJ1), initially identified as a stress-induced protein in neurons, recently emerged as a key mediator of plasma membrane rupture during apoptosis, necrosis, and pyroptosis. However, its involvement in ferroptosis remains unknown. Here, we demonstrate that NINJ1 also plays a crucial role in ferroptosis, but through a distinct mechanism. NINJ1 knockdown significantly protected cancer cells against ferroptosis induced by xCT inhibitors but no other classes of ferroptosis-inducing compounds (FINs). Glycine, known to inhibit canonical NINJ1-mediated membrane rupture in other cell deaths, had no impact on ferroptosis. A compound screen revealed that NINJ1-mediated ferroptosis protection can be abolished by pantothenate kinase inhibitor (PANKi), buthionine sulfoximine (BSO), and diethylmaleate (DEM). These results suggest that this ferroptosis protection is mediated via Coenzyme A (CoA) and glutathione (GSH), both of which were found to be elevated upon NINJ1 knockdown. Furthermore, we discovered that NINJ1 interacts with the xCT antiporter, which is responsible for cystine uptake for the biosynthesis of CoA and GSH. The removal of NINJ1 increased xCT levels and stability, enhanced cystine uptake, and contributed to elevated CoA and GSH levels, collectively contributing to ferroptosis protection. These findings reveal that NINJ1 regulates ferroptosis via a non-canonical mechanism, distinct from other regulated cell deaths.

FLNB overexpression promotes tumor progression and associates with immune suppression, evasion and stemness in pancreatic cancer.

Pancreatic cancer (PC) is an immunosuppressive cancer. Immune-based therapies that enhance or recruit antitumor immune cells into the tumor microenvironment (TME) remain promising strategies for PC treatment. Consequently, a deeper understanding of the molecular mechanisms involved in PC immune suppression is critical for developing immune-based therapies to improve survival rates. In this study, weighted gene co-expression network analysis (WGCNA) was used to identify Filamin B (FLNB) correlated with the infiltration of CD8+ T cells and tumor-associated macrophages (TAMs). The clinical significance and potential biological function of FLNB were evaluated using bioinformatic analysis. The oncogenic role of FLNB in PC was determined using in vitro and in vivo studies. We further analyzed possible associations between FLNB expression and tumor immunity using CIBERSORT, single sample gene set enrichment analysis, and ESTIMATE algorithms. We found FLNB was overexpressed in PC tissues and was correlated with poorer overall survival, tumor recurrence, larger tumor size, and higher histologic grade. Moreover, FLNB overexpression was associated with the mutation status and expression of driver genes, especially for KRAS and SMAD4. Functional enrichment analysis identified the role of FLNB in the regulation of cell cycle, focal adhesion, vascular formation, and immune regulation. Knockdown of FLNB expression inhibited cancer cell proliferation and migration in-vitro and suppressed tumor growth in-vivo. Furthermore, FLNB overexpression caused high infiltration of Treg cells, Th2 cells, and TAMs, but reduced infiltration of CD8+ T cells and Th1/Th2. Collectively, our findings suggest FLNB promotes PC progression and may be a novel biomarker for PC.

Ultra-Thin and Broadband P-Band Metamaterial Absorber Based on Carbonyl Iron Powder Composites.

The field of P-band (0.3-1 GHz) absorption has witnessed rapid development in metamaterial absorbers due to their exceptional designability and the absence of restrictions imposed by the one-fourth wavelength rule. In this study, we combined carbonyl iron powder (CIP) composites with a periodic structure composed of metal capacitive patterns and employed a genetic algorithm (GA) to optimize the electromagnetic parameters of the CIP substrate. By selecting the appropriate shape and material for the units of pattern based on transmission line theory, as well as regulating relevant structural parameters, we successfully designed an ultra-thin broadband metamaterial absorber for the P-band. Experimental results demonstrate that within the range of 0.3-0.85 GHz, the reflection loss of our absorber remains below -5 dB, with a maximum value of -9.54 dB occurring at 0.45 GHz. Remarkably, this absorber possesses a thickness equivalent to only 1/293 of its working wavelength. Then, we conducted analyses on electric field distribution, magnetic field distribution, and energy loss density. Our findings suggest that high-performance absorption in metamaterials can be attributed to λ/4 resonant or coupling effects between structural units or diffraction phenomena. This absorber offers several advantages, including broad low-frequency absorption capability, ultra-thin profile, and convenient fabrication process, thus providing valuable theoretical insights for designing metamaterial structures.

Preexisting renal graft dysfunction as a major risk factor for SARS-CoV-2 Omicron variant pneumonia: A postinfection cross-sectional study of 312 immunosuppressed renal transplant recipients.

OBJECTIVES: SARS-CoV-2 pneumonia poses significant challenges to health systems worldwide, particularly, in severe and critical cases. Immunosuppressed renal transplant recipients appear to be at a particularly high risk for severe or critical COVID-19 illness. However, few studies elucidated the risk factors of SARS-CoV-2 pneumonia in renal transplant recipients with COVID-19. METHODS: A postinfection cross-sectional survey was conducted in 312 renal transplant recipients and 503 age- and sex-matched controls to explore risk factors for SARS-CoV-2 pneumonia in immunosuppressed renal transplant recipients. RESULTS: The results showed that renal transplant recipients had a much higher incidence of SARS-CoV-2 pneumonia (48.1%) after infection with the SARS-CoV-2 Omicron variant than controls (5.6%). The multivariate binary logistic regression analysis identified older age, lower creatinine clearance before infection, and higher dose of prednisone before infection as risk factors for SARS-CoV-2 pneumonia in renal transplant recipients. Preexisting renal dysfunction was a major risk factor for SARS-CoV-2 pneumonia, with an odds ratio of 3.27 (1.01-10.61). CONCLUSIONS: Preexisting renal graft dysfunction was a major risk factor for SARS-CoV-2 Omicron variant pneumonia. It is suggested that high-risk renal transplant recipients should undergo computed tomography scanning within 14 days after infection with SARS-CoV-2.

Decoupled electrolysis for hydrogen production and hydrazine oxidation via high-capacity and stable pre-protonated vanadium hexacyanoferrate.

Decoupled electrolysis for hydrogen production with the aid of a redox mediator enables two half-reactions operating at different rates, time, and spaces, which offers great flexibility in operation. Herein, a pre-protonated vanadium hexacyanoferrate (p-VHCF) redox mediator is synthesized. It offers a high reversible specific capacity up to 128 mAh g-1 and long cycling performance of 6000 cycles with capacity retention about 100% at a current density of 10 A g-1 due to the enhanced hydrogen bonding network. By using this mediator, a membrane-free water electrolytic cell is built to achieve decoupled hydrogen and oxygen production. More importantly, a decoupled electrolysis system for hydrogen production and hydrazine oxidation is constructed, which realizes not only separate hydrogen generation but electricity generation through the p-VHCF-N2H4 liquid battery. Therefore, this work enables the flexible energy conversion and storage with hydrogen production driven by solar cell at day-time and electricity output at night-time.

Identification and validation of stemness-based and ferroptosis-related molecular clusters in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with an extremely poor prognosis. Cancer stem cells (CSCs) are considered to be responsible for the poor survival, recurrence and therapy resistance of PDAC. Ferroptosis plays a crucial role in the sustain and survival of CSCs. Here, we employed a rigorous evaluation of multiple datasets to identify a novel stemness-based and ferroptosis-related genes (SFRGs) signature to access the potential prognostic application. This work we retrieved RNA-sequencing and clinical annotation data from the TCGA, ICGC, GTEx and GEO database, and acquired 26 stem cell gene sets and 259 ferroptosis genes from StemChecker database and FerrDb database, respectively. Based on consensus clustering and ssGSEA analysis, we identified two expression patterns of CSCs traits (C1 and C2). Then, WGCNA analysis was implemented to screen out hub module genes correlated with stemness. Furthermore, differential expression analysis, Pearson correlation analysis, and the Least absolute shrinkage and selection operator (LASSO) and Cox regression were performed to identify the SFRGs and to construct model. In addition, the differences in prognosis, tumor microenvironment (TME) components and therapy responses were evaluated between two risk groups. Finally, we verified the most influential marker ARNTL2 experimentally by western blot, qRT-PCR, sphere formation assay, mitoscreen assay, intracellular iron concentration determination and MDA determination assays. In conclusion, we developed a stemness-based and ferroptosis-related prognostic model, which could help predict overall survival for PDAC patients. Targeting ferroptosis may be a promising therapeutic strategy to inhibit PDAC progression by suppressing CSCs.

Genome-wide CRISPR/Cas9 screening for drug resistance in tumors.

Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated nuclease 9 (Cas9) screening is a simple screening method for locating loci under specific conditions, and it has been utilized in tumor drug resistance research for finding potential drug resistance-associated genes. This screening strategy has significant implications for further treatment of malignancies with acquired drug resistance. In recent years, studies involving genome-wide CRISPR/Cas9 screening have gradually increased. Here we review the recent application of genome-wide CRISPR/Cas9 screening for drug resistance, involving mitogen-activated protein kinase (MAPK) pathway inhibitors, poly (ADP-ribose) polymerase inhibitors (PARPi), alkylating agents, mitotic inhibitors, antimetabolites, immune checkpoint inhibitors (ICIs), and cyclin-dependent kinase inhibitors (CDKI). We summarize drug resistance pathways such as the KEAP1/Nrf2 pathway MAPK pathway, and NF-κB pathway. Also, we analyze the limitations and conditions for the application of genome-wide CRISPR/Cas9 screening techniques.

A hierarchical prognostic model for Co-diabetes pancreatic adenocarcinoma.

Background: Co-diabetes pancreatic adenocarcinoma has a poorer prognosis than pancreatic adenocarcinoma without diabetes. This study aimed to develop a reliable prognostic model for patients with co-diabetes pancreatic adenocarcinoma. Method: Overall, 169 patients with co-diabetes pancreatic adenocarcinoma were included in our study. First, the independent risk factors affecting the prognosis of patients with co-diabetes pancreatic adenocarcinoma were determined by univariate and multivariate Cox regression analyses. Based on these identified risk factors, we developed a nomogram and evaluated its predictive ability using the concordance index, receiver operating characteristic curve, calibration plot, decision curve, and net reclassification index. Results: In this study, prealbumin, transferrin, carcinoembryonic antigen, distant metastasis, tumor differentiation neutrophil count, lymphocyte count and fasting blood glucose were confirmed as significant prognostic factors. Based on these predictors, a new nomogram was developed. Compared with the American Joint Committee on Cancer 8 staging system and other models, the nomogram achieved a higher concordance index in the training (0.795) and validation (0.729) queues. The area under the nomogram's curve for predicting patient survival at 0.5, 1, and 1.5 years in the training queue was >0.8. Patients were risk-stratified using the nomogram, and Kaplan-Meier survival curves of subgroups were plotted. The Kaplan-Meier curve also showed better separation than the American Joint Committee on Cancer 8 staging system, indicating that our model has a better risk hierarchical ability. Conclusions: Compared to the American Joint Committee on Cancer 8 staging system and other predictive models, our model showed better predictive ability for patients with co-diabetes pancreatic adenocarcinoma. Our model will help in patients' risk stratification and improves their prognosis.

Association Between Interleukin-6 Gene Polymorphism and Severity of Coronary Artery Disease in Patients with Diabetes.

Introduction: Previous studies have identified diabetes as a risk factor for coronary heart disease. This study determined the correlation between the IL-6 gene -572 G/C polymorphism and the incidence and severity of coronary heart disease in patients with diabetes. Methods: One hundred four patients with diabetes who were admitted to our hospital from January 2019 to December 2020 were retrospectively enrolled in the current study. These patients were divided into a diabetes only group (group A, 27 patients) and a diabetes complicated by coronary heart disease group (group B, 77 patients). Seventy patients in the latter group were further divided into low, medium, and high Syntax score groups based on coronary angiography results. A correlation analysis between IL-6, blood lipids, and the IL-6 -572 G/C gene levels was performed. Results: The serum IL-6 level in patients with the IL-6-572G/C-GG genotype was higher than patients with the GC and CC genotypes. In patients with diabetes, the presence of the IL-6-572G/C-GG and GC genotypes was associated with a significantly increased risk of developing coronary heart disease. Patients with the IL-6-572G/C-GG genotype and diabetes were shown to have more severe coronary artery lesions compared to patients with the CC genotype. Moreover, the G allele of the IL-6-572G/C gene was linked to a higher risk of coronary heart disease and more severe coronary artery lesions in patients with diabetes compared to the C allele. Conclusion: The IL-6-572G/C gene polymorphism is associated with the incidence and severity of coronary heart disease in patients with diabetes.

Establishment of a Seven-Gene Signature Associated with CD8+ T Cells through the Utilization of Both Single-Cell and Bulk RNA-Sequencing Techniques in Clear Cell Renal Cell Carcinoma.

Tumor immune microenvironment constituents, such as CD8+ T cells, have emerged as crucial focal points for cancer immunotherapy. Given the absence of reliable biomarkers for clear cell renal cell carcinoma (ccRCC), we aimed to ascertain a molecular signature that could potentially be linked to CD8+ T cells. The differentially expressed genes (DEGs) linked to CD8+ T cells were identified through an analysis of single-cell RNA sequencing (scRNA-seq) data obtained from the Gene Expression Omnibus (GEO) database. Subsequently, immune-associated genes were obtained from the InnateDB and ImmPort datasets and were cross-referenced with CD8+ T-cell-associated DEGs to generate a series of DEGs linked to immune response and CD8+ T cells. Patients with ccRCC from the Cancer Genome Atlas (TCGA) were randomly allocated into testing and training groups. A gene signature was established by conducting LASSO-Cox analysis and subsequently confirmed using both the testing and complete groups. The efficacy of this signature in evaluating immunotherapy response was assessed on the IMvigor210 cohort. Finally, we employed various techniques, including CIBERSORT, ESTIMATE, ssGSEA, and qRT-PCR, to examine the immunological characteristics, drug responses, and expression of the signature genes in ccRCC. Our findings revealed 206 DEGs linked to immune response and CD8+ T cells, among which 65 genes were correlated with overall survival (OS) in ccRCC. A risk assessment was created utilizing a set of seven genes: RARRES2, SOCS3, TNFSF14, XCL1, GRN, CLDN4, and RBP7. The group with a lower risk showed increased expression of CD274 (PD-L1), suggesting a more favorable response to anti-PD-L1 treatment. The seven-gene signature demonstrated accurate prognostic prediction for ccRCC and holds potential as a clinical reference for treatment decisions.

Regulation of iron metabolism and ferroptosis in cancer stem cells.

The ability of cancer stem cells (CSCs) to self-renew, differentiate, and generate new tumors is a significant contributor to drug resistance, relapse, and metastasis. Therefore, the targeting of CSCs for treatment is particularly important. Recent studies have demonstrated that CSCs are more susceptible to ferroptosis than non-CSCs, indicating that this could be an effective strategy for treating tumors. Ferroptosis is a type of programmed cell death that results from the accumulation of lipid peroxides caused by intracellular iron-mediated processes. CSCs exhibit different molecular characteristics related to iron and lipid metabolism. This study reviews the alterations in iron metabolism, lipid peroxidation, and lipid peroxide scavenging in CSCs, their impact on ferroptosis, and the regulatory mechanisms underlying iron metabolism and ferroptosis. Potential treatment strategies and novel compounds targeting CSC by inducing ferroptosis are also discussed.

Mueller transform matrix neural network for underwater polarimetric dehazing imaging.

Polarization dehazing imaging has been used to restore images degraded by scattering media, particularly in turbid water environments. While learning-based approaches have shown promise in improving the performance of underwater polarimetric dehazing, most current networks rely heavily on data-driven techniques without consideration of physics principles or real physical processes. This work proposes, what we believe to be, a novel Mueller transform matrix network (MTM-Net) for underwater polarimetric image recovery that considers the physical dehazing model adopting the Mueller matrix method, significantly improving the recovery performance. The network is trained with a loss function that combines content and pixel losses to facilitate detail recovery, and is sped up with the inverse residuals and channel attention structure without decreasing image recovery quality. A series of ablation experiment results and comparative tests confirm the performance of this method with a better recovery effect than other methods. These results provide deeper understanding of underwater polarimetric dehazing imaging and further expand the functionality of polarimetric dehazing method.

The predictive values of monocyte-lymphocyte ratio in postoperative acute kidney injury and prognosis of patients with Stanford type A aortic dissection.

Objectives: Postoperative acute kidney injury (pAKI) is a serious complication of Stanford type A aortic dissection (TAAD) surgery, which is significantly associated with the inflammatory response. This study aimed to explore the relationship between blood count-derived inflammatory markers (BCDIMs) and pAKI and to construct a predictive model for pAKI. Methods: Patients who underwent TAAD surgery were obtained from our center and the Medical Information Mart for Intensive Care (MIMIC)-IV database. The differences in preoperative BCDIMs and clinical outcomes of patients with and without pAKI were analyzed. Logistic regression was used to construct predictive models based on preoperative BCDIMs or white cell counts (WCCs). The performance of the BCDIMs and WCCs models was evaluated and compared using the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), Hosmer-Lemeshow test, calibration plot, net reclassification index (NRI), integrated discrimination improvement index (IDI), and decision curve analysis (DCA). The Kaplan-Meier curves were applied to compare the survival rate between different groups. Results: The overall incidence of pAKI in patients who underwent TAAD surgery from our center was 48.63% (124/255). The presence of pAKI was associated with longer ventilation time, higher incidence of cerebral complications and postoperative hepatic dysfunction, and higher in-hospital mortality. The results of the logistic regression indicated that the monocyte-lymphocyte ratio (MLR) was an independent risk factor for pAKI. The BCDIMs model had good discriminating ability, predictive ability, and clinical utility. In addition, the performance of the BCDIMs model was significantly better than that of the WCCs model. Analysis of data from the MIMIC-IV database validated that MLR was an independent risk factor for pAKI and had predictive value for pAKI. Finally, data from the MIMIC-IV database demonstrated that patients with a high MLR had a significantly poor 28-day survival rate when compared to patients with a low MLR. Conclusion: Our study suggested that the MLR is an independent risk factor for pAKI. A predictive model based on BCDIMs had good discriminating ability, predictive ability, and clinical utility. Moreover, the performance of the BCDIMs model was significantly better than that of the WCCs model. Finally, a high MLR was significantly associated with poor short-term survival of patients who underwent TAAD surgery.