[Simulation model of tumor-treating fields].

Tumor-treating fields (TTFields) is a novel treatment modality for malignant solid tumors, often employing electric field simulations to analyze the distribution of electric fields on the tumor under different parameters of TTFields. Due to the present difficulties and high costs associated with reproducing or implementing the simulation model construction techniques, this study used readily available open-source software tools to construct a highly accurate, easily implementable finite element simulation model for TTFields. The accuracy of the model is at a level of 1 mm 3. Using this simulation model, the study carried out analyses of different factors, such as tissue electrical parameters and electrode configurations. The results show that factors influncing the distribution of the internal electric field of the tumor include changes in scalp and skull conductivity (with a maximum variation of 21.0% in the treatment field of the tumor), changes in tumor conductivity (with a maximum variation of 157.8% in the treatment field of the tumor), and different electrode positions and combinations (with a maximum variation of 74.2% in the treatment field of the tumor). In summary, the results of this study validate the feasibility and effectiveness of the proposed modeling method, which can provide an important reference for future simulation analyses of TTFields and clinical applications.

Association between the gut microbiota, inflammatory factors, and colorectal cancer: evidence from Mendelian randomization analysis.

Background: Colorectal cancer (CRC) is one of the most common malignant tumors primarily affecting individuals over the age of 50 years. Recent studies have suggested that the dysbiosis of the gut microbiota, a community of microorganisms in the human gut, is closely associated with the occurrence and development of CRC. Additionally, inflammatory factors (IFs) have also been reported to play a significant role in the development of CRC. However, the causal relationships between the gut microbiota, IFs, and CRC remain unclear. Methods: In this study, we performed Mendelian randomization (MR) analysis using publicly available genome-wide association study (GWAS) data to explore the causal relationship between the gut microbiota, IFs, and CRC. The gut microbiota GWAS data were obtained from the MiBioGen study, while the IFs GWAS data were derived from the comprehensive analysis of three independent cohorts. Causal relationship analysis was conducted using appropriate instrumental variables (IVs) and statistical models. Results: MR analysis of the gut microbiota and CRC revealed a negative correlation between the Lachnospiraceae species in the gut and CRC risk, while a positive correlation was observed between Porphyromonadaceae species, Lachnospiraceae UCG010 genus, Lachnospira genus, and Sellimonas genus in the gut, and CRC risk. Additionally, we observed a causal relationship between IL-10 and CRC risk. These findings suggest that the dysbiosis of the gut microbiota might be associated with an increased risk of CRC and that specific bacterial groups may play a crucial role in the occurrence and development of CRC. Conclusion: Using MR analysis, this study revealed the causal relationships between the gut microbiota, IFs, and CRC. The negative correlation between the Lachnospiraceae species in the gut and CRC risk, as well as the causal relationship between IL-10 and CRC, provide important clues for the potential roles of gut microbiota regulation and inflammatory factor control in the prevention and treatment of CRC.

Integrated analysis of disulfidptosis-related immune genes signature to boost the efficacy of prognostic prediction in gastric cancer.

BACKGROUND: Gastric cancer (GC) remains a malignant tumor with high morbidity and mortality, accounting for approximately 1,080,000 diagnosed cases and 770,000 deaths worldwide annually. Disulfidptosis, characterized by the stress-induced abnormal accumulation of disulfide, is a recently identified form of programmed cell death. Substantial studies have demonstrated the significant influence of immune clearance on tumor progression. Therefore, we aimed to explore the intrinsic correlations between disulfidptosis and immune-related genes (IRGs) in GC, as well as the potential value of disulfidptosis-related immune genes (DRIGs) as biomarkers. METHODS: This study incorporated the single-cell RNA sequencing (scRNA-seq) dataset GSE183904 and transcriptome RNA sequencing of GC from the TCGA database. Disulfidptosis-related genes (DRGs) and IRGs were derived from the representative literature on both cell disulfidptosis and immunity. The expression and distribution of DRGs were investigated at the single-cell level in different GC cell types. Pearson correlation analysis was used to identify the IRGs closely related to disulfidptosis. The prognostic signature of DRIGs was established using Cox and LASSO analyses. We then analyzed and evaluated the differences in long-term prognosis, Gene Set Enrichment Analysis (GSEA), immune infiltration, mutation profile, CD274 expression, and response to chemotherapeutic drugs between the two groups. A tissue array containing 63 paired GC specimens was used to verify the expression of 4 DRIGs and disulfidptosis regulator SLC7A11 through immunohistochemistry staining. RESULTS: The scRNA-seq analysis found that SLC7A11, SLC3A2, RPN1 and NCKAP1 were enriched in specific cell types and closely related to immune infiltration. Four DIRGs (GLA, HIF-1α, VPS35 and CDC37) were successfully identified to establish a signature to potently predict the survival time of GC patients. Patients with high risk scores generally experienced worse prognoses and exhibited greater resistant to classical chemotherapy drugs. Furthermore, the expression of GLA, HIF-1α, VPS35, CDC37 and SLC7A11 were elevated in GC tissues. A high expression of GLA, HIF-1α, VPS35 or CDC37 was associated with more advanced clinical stage of GC and increased SLC7A11 expression. CONCLUSION: Current study first highlights the potential value of DRIGs as biomarkers in GC. We successfully constructed a robust model incorporating four DRIGs to accurately predict the survival time and clinicopathological characteristics of GC patients.

Acidic Gas Determination Using Indium Tin Oxide-Based Gas Sensors.

This work has presented gas sensors based on indium tin oxide (ITO) for the detection of SO2 and NO2. The ITO gas-sensing material was deposited by radio frequency (RF) magnetron sputtering. The properties of gas sensing could be improved by increasing the ratio of SnO2. The response characteristics of the gas sensor for detecting different concentrations of NO2 and SO2 were investigated. In the detection of NO2, the sensitivity was significantly improved by increasing the SnO2 ratio in ITO by 5%, and the response and recovery time were reduced significantly. However, the sensitivity of the sensor decreased with increasing SO2 concentration. From X-ray photoelectron spectroscopy (XPS) analysis, the gas-sensitive response mechanisms were different in the atmosphere of NO2 and SO2. The NO2 was adsorbed by ITO via physisorption but the SO2 had a chemical reaction with the ITO surface. The gas selectivity, temperature dependence, and environmental humidity of ITO-based gas sensors were systematically analyzed. The high detection sensitivity for acidic gas of the prepared sensor presented great potential for acid rain monitoring.

Comprehensive integration of single-cell RNA and transcriptome RNA sequencing to establish a pyroptosis-related signature for improving prognostic prediction of gastric cancer.

Cell pyroptosis, a Gasdermin-dependent programmed cell death characterized by inflammasome, plays a complex and dynamic role in Gastric cancer (GC), a serious threat to human health. Therefore, the value of pyroptosis-related genes (PRGs) as prognostic biomarkers and therapeutic indicators for patients needs to be exploited in GC. This study integrates single-cell RNA sequencing (scRNA-seq) dataset GSE183904 with GC transcriptome data from the TCGA database, focusing on the expression and distribution of PRGs in GC at the single-cell level. The prognostic signature of PRGs was established by using Cox and LASSO analyses. The differences in long-term prognosis, immune infiltration, mutation profile, CD274 and response to chemotherapeutic drugs between the two groups were analyzed and evaluated. A tissue array was used to verify the expression of six PRGs, CD274, CD163 and FoxP3. C12orf75, VCAN, RGS2, MKNK2, SOCS3 and TNFAIP2 were successfully screened out to establish a signature to potently predict the survival time of GC patients. A webserver (https://pumc.shinyapps.io/GastricCancer/) for prognostic prediction in GC patients was developed based on this signature. High-risk score patients typically had worse prognoses, resistance to classical chemotherapy, and a more immunosuppressive tumor microenvironment. VCAN, TNFAIP2 and SOCS3 were greatly elevated in the GC while RGS2 and MKNK2 were decreased in the tumor samples. Further, VCAN was positively related to the infiltrations of Tregs and M2 TAMs in GC TME and the CD274 in tumor cells. In summary, a potent pyroptosis-related signature was established to accurately forecast the survival time and treatment responsiveness of GC patients.

Safety and efficacy of radiotherapy combined with chemotherapy for recurrent metastatic renal pelvic and ureteral carcinoma.

PURPOSE: To retrospectively investigate the safety and efficacy of radiotherapy combined with chemotherapy for recurrent metastatic renal pelvic and ureteral carcinoma. METHODS: 109 patients were enrolled in this study, including 44 patients in the radiochemotherapy group and 65 patients in the chemotherapy group. Propensity score matching (PSM) was used to balance the baseline characteristics of the two groups by 1:1 matching. Kaplan-Meier method was used to calculate PFS and OS. Cox regression model was used for multivariate analysis. The side effects were evaluated by CTCAE v5.0 RESULTS: The median follow-up time was 14.5 months. Multivariate analysis showed that radiotherapy was a good independent prognostic factor for OS (HR: 0.327, 95% CI 0.157-0.680, P = 0.003). After matching, there were 40 patients in both groups, and the median PFS and OS in the radiochemotherapy group were longer than those in the chemotherapy group (PFS: 10.4 vs. 6.7 months, P = 0.035; OS: 43.5 vs. 18.8 months, P < 0.001). In addition, in the radiochemotherapy group, patients treated with radiotherapy before first-line chemotherapy failure had a longer PFS than those treated with radiotherapy after chemotherapy failure (median PFS: 15.7 vs. 6 months, P = 0.003). There was no significant difference in the incidence of grade 3-4 toxicities between the two groups (52.3% vs. 50.8%, P = 0.878). CONCLUSION: For patients with recurrent metastatic renal pelvic and ureteral carcinoma, radiotherapy combined with chemotherapy is well tolerable and expected to bring long-term survival benefits, and the benefits of early interventional radiotherapy may be more obvious.

Integration of Multiparameter MRI into Conventional Pretreatment Risk Factors to Predict Positive Surgical Margins After Radical Prostatectomy.

INTRODUCTION/BACKGROUND: Positive surgical margins (PSMs) after radical prostatectomy (RP) can increase the risk of biochemical recurrence in prostate cancer (PCa) patients. However, the prediction of the likelihood of PSMs in patients undergoing similar surgical procedures remains a challenge. We aim to develop a predictive model for PSMs in patients undergoing non-nerve-sparing RP. PATIENTS AND METHODS: In this retrospective study, we analyzed data from PCa patients who underwent minimally invasive non-nerve-sparing RP at our hospital between June 2017 and June 2021. We identified independent risk factors associated with PSMs using clinical and MRI-based parameters in univariate and multivariate logistic regression analyzes. These factors were then used to develop a nomogram for predicting the probability of PSMs. The predictive performance was validated using calibration and receiver operating characteristic curve, area under the curve ,and decision curve analysis. RESULTS: Multivariate analyzes revealed prostate-specific antigen density, tumor size, tumor location at the apex, tumor contact length, extracapsular extension (ECE) level, and apparent diffusion coefficient value as independent risk factors. A nomogram was developed and validated with high accuracy (C-index = 0.78). Furthermore, we found that 44.2% of patients diagnosed with organ-confined disease had ECE after surgery, and 29.1% of patients with Gleason scores ≤7 had higher pathological scores. Interestingly, the tumor burden calculated from PCa biopsy cores was overestimated when compared to postoperative PCa specimens. CONCLUSION: We developed a reliable nomogram for predicting the risk of PSMs in PCa patients undergoing non-nerve-sparing RP. The study highlights the importance of incorporating these parameters in personalized surgical management.

Breaking barriers: Stereotactic ablative proton and photon radiation therapy for renal cell carcinoma with extensive metastases: A case report.

Patients with advanced renal cancer (RCC) often have limited success with systemic therapy due to tumor heterogeneity. However, stereotactic ablative radiotherapy (SABR) has been shown to have a beneficial therapeutic effect for oligometastatic disease when used early. Despite this, current guidelines recommend the use of tyrosine kinase inhibitors (TKIs) as the first-line therapeutic agent for patients with recurrent or metastatic kidney cancer. Additionally, there is limited data on the combination of systemic treatment and SABR for extensive metastatic RCC due to concerns about high toxicity. Proton therapy offers a promising treatment option as it emits energy at a specific depth, generating high target doses while minimizing damage to normal tissue. This allows for precise treatment of various tumor lesions. In this case report, we describe a high-risk 65-year-old male with extensive pleural and thoracic lymph node metastases and 2 bone metastases of clear cell renal cancer. While the targeted therapy and immunotherapy effectively treated the bone metastases, it was not effective in treating the chest metastases, including the pleural and lymph node metastases. Thus, the patient received full-coverage radiotherapy with photon for primary renal tumor and intensity-modulated proton therapy (IMPT) for thoracic metastases. The patient showed no evidence of disease for 1 year after the initial radiotherapy, and no severe SABR-related adverse effects were observed until now. The combination of targeted therapy and immunotherapy with full-coverage radiotherapy may be a promising treatment option for selected patients with extensive metastatic renal cancer, especially as proton therapy allows for more precise control of the beam and minimal damage to normal tissue. This case has motivated us to investigate the potential advantages of administering proton therapy concurrently with systemic therapy in the management of metastatic renal cell carcinoma patients.

Dose-Intensified Postoperative Radiation Therapy for Prostate Cancer: Long-Term Results From the PKUFH Randomized Phase 3 Trial.

PURPOSE: In the randomized, single-center, PKUFH phase 3 trial, dose-intensified (72 Gy) radiation therapy was compared with conventional (66 Gy) radiation therapy. In a previous study, we found no significant difference in biochemical progression-free survival (bPFS) between the 2 cohorts at 4 years. In the current analysis, we provide 7-year outcomes. METHODS AND MATERIALS: Patients with stage pT3-4, positive surgical margins, or a prostate-specific antigen increase ≥0.2 ng/mL after radical prostatectomy were randomly assigned 1:1 to receive either 72 Gy in 36 fractions or 66 Gy in 33 fractions. All the patients underwent image guided intensity modulated radiation therapy. The primary endpoint was bPFS. Secondary endpoints were distant metastasis-free survival (DMFS), cancer-specific survival (CSS), and overall survival (OS) as estimated using the Kaplan-Meier method. RESULTS: Between September 2011 and November 2016, 144 patients were enrolled with 73 and 71 in the 72- and 66-Gy cohorts, respectively. At a median follow-up of 89.5 months (range, 73-97 months), there was no difference in 7-year bPFS between the 72- and 66-Gy cohorts (70.3% vs 61.2%; hazard ratio [HR], 0.73; 95% CI, 0.41-1.29; P = .274). However, in patients with a higher Gleason score (8-10), the 72-Gy cohort had statistically significant improvement in 7-year bPFS compared with the 66-Gy cohort (66.5% vs 30.2%; HR, 0.37; 95% CI, 0.17-0.82; P = .012). In addition, in patients with multiple positive surgical margins, the 72-Gy cohort had statistically significant improvement in 7-year bPFS compared with single positive surgical margin (82.5% vs 57.5%; HR, 0.36; 95% CI, 0.13-0.99; P = .037). The 7-year DMFS (88.4% vs 84.9%; HR, 0.93; 95% CI, 0.39-2.23; P = .867), CSS (94.1% vs 95.5%; HR, 1.19; 95% CI, 0.42-3.39; P = .745), and OS (92.8% vs 94.1%; HR, 1.29; 95% CI, 0.51-3.24; P = .594) had no statistical differences between the 72- and 66-Gy cohorts. CONCLUSIONS: The current 7-year bPFS results confirmed our previous findings that dose escalation (72 Gy) demonstrated no improvement in 7-year bPFS, DMFS, CSS, or OS compared with the 66-Gy regimen. However, patients with a higher Gleason score (8-10) or multiple positive surgical margins might benefit from the 72-Gy regimen, but this requires further prospective research.

Biomarkers for Prostate Cancer: From Diagnosis to Treatment.

Prostate cancer (PCa) is a widespread malignancy with global significance, which substantially affects cancer-related mortality. Its spectrum varies widely, from slow-progressing cases to aggressive or even lethal forms. Effective patient stratification into risk groups is crucial to therapeutic decisions and clinical trials. This review examines a wide range of diagnostic and prognostic biomarkers, several of which are integrated into clinical guidelines, such as the PHI, the 4K score, PCA3, Decipher, and Prolaris. It also explores the emergence of novel biomarkers supported by robust preclinical evidence, including urinary miRNAs and isoprostanes. Genetic alterations frequently identified in PCa, including BRCA1/BRCA2, ETS gene fusions, and AR changes, are also discussed, offering insights into risk assessment and precision treatment strategies. By evaluating the latest developments and applications of PCa biomarkers, this review contributes to an enhanced understanding of their role in disease management.

Perioperative Enteral Immunonutrition Support for the Immune Function and Intestinal Mucosal Barrier in Gastric Cancer Patients Undergoing Gastrectomy: A Prospective Randomized Controlled Study.

OBJECTIVE: The impact of perioperative immunonutrition on patients undergoing radical gastrectomy remains undetermined. This study aimed to assess the influence of enteral immunonutrition support on postoperative immune function and intestinal mucosal barrier function following radical gastrectomy, contrasting findings with a control group to furnish evidence for perioperative enteral nutrition support. METHODS: In this prospective randomized trial, 65 patients who underwent radical gastrectomy between June 2022 and June 2023 were included. Participants were allocated to either the study group (receiving enteral immunonutrition) or the control group (not receiving enteral immunonutrition). We compared postoperative rehabilitation and complications between the groups, analyzed the intestinal mucosal barrier function markers on the 3rd and 7th postoperative days, and delved deeper into peripheral blood cell immunity, inflammation, and nutritional indicators. RESULTS: The cohort consisted of 30 patients in the study group and 35 in the control group, with no significant differences in demographic attributes between the two groups. On the 3rd postoperative day, the diamine oxidase, D-lactic acid, and endotoxin levels in the study group were significantly lower than those in the control group (p = 0.029, p = 0.044, and p = 0.010, respectively). By the 7th postoperative day, these levels continued to be significantly diminished in the study group (p = 0.013, p = 0.033, and p = 0.004, respectively). The times to first flatus (p = 0.012) and first bowel movement (p = 0.012) were significantly shorter in the study group. Moreover, postoperative complications in the study group were fewer than in the control group (p = 0.039). On the 7th postoperative day, the study group had lower peripheral white blood cell (WBC) levels (p = 0.020) and neutrophil-lymphocyte ratios (NLR) (p = 0.031), but displayed elevated albumin levels (p = 0.006). One month post-surgery, the CD4+T and CD8+T counts were significantly greater in the study group (p = 0.003 and p = 0.012, respectively). Correlation analyses indicated that NLR and complications were associated with endotoxin levels. CONCLUSION: Administering perioperative enteral immunonutrition enhances postoperative immune and intestinal mucosal barrier functions in patients undergoing radical gastrectomy. This effect leads to diminished inflammatory responses, a decreased rate of postoperative complications, and accelerated patient recovery.

Extracting laboratory test information from paper-based reports.

BACKGROUND: In the healthcare domain today, despite the substantial adoption of electronic health information systems, a significant proportion of medical reports still exist in paper-based formats. As a result, there is a significant demand for the digitization of information from these paper-based reports. However, the digitization of paper-based laboratory reports into a structured data format can be challenging due to their non-standard layouts, which includes various data types such as text, numeric values, reference ranges, and units. Therefore, it is crucial to develop a highly scalable and lightweight technique that can effectively identify and extract information from laboratory test reports and convert them into a structured data format for downstream tasks. METHODS: We developed an end-to-end Natural Language Processing (NLP)-based pipeline for extracting information from paper-based laboratory test reports. Our pipeline consists of two main modules: an optical character recognition (OCR) module and an information extraction (IE) module. The OCR module is applied to locate and identify text from scanned laboratory test reports using state-of-the-art OCR algorithms. The IE module is then used to extract meaningful information from the OCR results to form digitalized tables of the test reports. The IE module consists of five sub-modules, which are time detection, headline position, line normalization, Named Entity Recognition (NER) with a Conditional Random Fields (CRF)-based method, and step detection for multi-column. Finally, we evaluated the performance of the proposed pipeline on 153 laboratory test reports collected from Peking University First Hospital (PKU1). RESULTS: In the OCR module, we evaluate the accuracy of text detection and recognition results at three different levels and achieved an averaged accuracy of 0.93. In the IE module, we extracted four laboratory test entities, including test item name, test result, test unit, and reference value range. The overall F1 score is 0.86 on the 153 laboratory test reports collected from PKU1. With a single CPU, the average inference time of each report is only 0.78 s. CONCLUSION: In this study, we developed a practical lightweight pipeline to digitalize and extract information from paper-based laboratory test reports in diverse types and with different layouts that can be adopted in real clinical environments with the lowest possible computing resources requirements. The high evaluation performance on the real-world hospital dataset validated the feasibility of the proposed pipeline.

Secukinumab-Induced Alopecia Areata Successfully Treated with Tofacitinib in a Patient with Palmoplantar Pustulosis.

Secukinumab, a monoclonal antibody targeting interleukin-17 (IL-17), has exhibited encouraging results in the therapeutic management of palmoplantar pustulosis (PPP). The development of alopecia areata (AA) is closely related to IL-17, and IL-17A inhibitors were considered as a potential treatment modality. Therefore, the development of AA during secukinumab treatment for PPP is a rare adverse event that has been rarely reported worldwide. Here we report a 35-year-old female patient with PPP who developed AA after completing the induction period of secukinumab treatment. Discontinuing secukinumab and initiating treatment with tofacitinib resulted in a significant improvement in both PPP and AA. The emergence of AA in this patient can be attributed to paradoxical skin reactions associated with IL-17 inhibitors. Tofacitinib appears to alleviate biologic-induced AA during PPP syndrome treatment.

Tumour-associated macrophages in gastric cancer: From function and mechanism to application.

BACKGROUND: Gastric cancer (GC) is a malignant tumour, with high morbidity and mortality rates worldwide. The occurrence and development of GC is a complex process involving genetic changes in tumour cells and the influence of the surrounding tumour microenvironment (TME). Accumulative evidence shows that tumour-associated macrophages (TAMs) play a vital role in GC, acting as plentiful and active infiltrating inflammatory cells in the TME. MAIN BODY: In this review, the different functions and mechanisms of TAMs in GC progression, including the conversion of phenotypic subtypes; promotion of tumour proliferation, invasion and migration; induction of chemoresistance; promotion of angiogenesis; modulation of immunosuppression; reprogramming of metabolism; and interaction with the microbial community are summarised. Although the role of TAMs in GC remains controversial in clinical settings, clarifying their significance in the treatment selection and prognostic prediction of GC could support optimising TAM-centred clinicaltherapy. CONCLUSION: In summary, we reviewed the the phenotypic polarisation, function and molecular mechanism of TAMs and their potential applications in the treatment selection and prognostic prediction of GC.

Hypoxia-based classification and prognostic signature for clinical management of hepatocellular carcinoma.

OBJECTIVE: Intratumoral hypoxia is an essential feature of hepatocellular carcinoma (HCC). Herein, we investigated the hypoxia-based heterogeneity and relevant clinical implication in HCC. METHODS: Three HCC cohorts: TCGA-LIHC, LICA-FR, and LIRI-JP were retrospectively gathered. Consensus clustering analysis was utilized for hypoxia-based classification based upon transcriptome of hypoxia genes. Through LASSO algorithm, a hypoxia-relevant prognostic signature was built. Immunotherapeutic response was inferred through analyzing immune checkpoints, T cell inflamed score, TIDE score, and TMB score. RNF145 expression was measured in normoxic or hypoxic HCC cells. In RNF145-knockout cells, CCK-8, TUNEL, and scratch tests were implemented. RESULTS: HCC patients were classified into two hypoxia subtypes, with more advanced stages and poorer prognosis in cluster2 than cluster1. The heterogeneity in tumor infiltrating immune cells and genetic mutation was found between subtypes. The hypoxia-relevant prognostic model was proposed, composed of ANLN, CBX2, DLGAP5, FBLN2, FTCD, HMOX1, IGLV1-44, IL33, LCAT, LPCAT1, MKI67, PFN2, RNF145, S100A9, and SPP1). It was predicted that high-risk patients presented worse prognosis with an independent and reliable manner. Based upon high expression of immune checkpoints (CD209, CTLA4, HAVCR2, SIRPA, TNFRSF18, TNFRSF4, and TNFRSF9), high T cell inflamed score, low TIDE score and high TMB score, high-risk patients might respond to immunotherapy. Experimental validation showed that RNF145 was upregulated in hypoxic HCC cells, RNF145 knockdown attenuated proliferation and migration, but aggravated apoptosis in HCC cells. CONCLUSION: Altogether, the hypoxia-based classification and prognostic signature might be useful for prognostication and guiding treatment of HCC.

A Fast Magnetic Flux Density Measurement Method With Skip-Echo Acquired Turbo Spin Echo (SATE).

The measurements of magnetic flux density ( Bz) needed in magnetic resonance electrical impedance tomography (MREIT) and magnetic resonance current density imaging (MRCDI) techniques often utilize spin echo (SE)-based sequences for data acquisition. The low imaging speed of SE-based methods significantly hampers the clinical applications of MREIT and MRCDI. Here, we propose a new sequence for substantially accelerating the acquisition of Bz measurements. A skip-echo acquired turbo spin echo (SATE) imaging sequence based on the conventional turbo spin echo (TSE) technique was proposed by adding a skip-echo module in front of the TSE acquisition module. The skip-echo module consisted of a series of refocusing pulses without acquisition. In SATE, amplitude-modulated crusher gradients were used to remove the stimulated echo pathways, and the radiofrequency (RF) pulse shape was specially selected to preserve more signals. In efficiency evaluation experiments performed on a spherical gel phantom, we demonstrated that SATE had improved measurement efficiency compared to the conventional TSE sequence via skipping one echo before acquiring signals. The accuracy of the Bz measurements by SATE was validated against those by the multi-echo injection current nonlinear encoding (ME-ICNE) method, while SATE was able to accelerate the data acquisition up to 10-fold. Volumetric coverage of Bz maps obtained in the phantom, pork, and human calf illustrated that SATE can reliably measure volumetric Bz distributions within clinically acceptable time. The proposed SATE sequence provides a fast and effective approach for volumetric coverage of Bz measurements, greatly facilitating the clinical applications of MREIT and MRCDI techniques.

Crafting a Personalized Prognostic Model for Malignant Prostate Cancer Patients Using Risk Gene Signatures Discovered through TCGA-PRAD Mining, Machine Learning, and Single-Cell RNA-Sequencing.

BACKGROUND: Prostate cancer is a significant clinical issue, particularly for high Gleason score (GS) malignancy patients. Our study aimed to engineer and validate a risk model based on the profiles of high-GS PCa patients for early identification and the prediction of prognosis. METHODS: We conducted differential gene expression analysis on patient samples from The Cancer Genome Atlas (TCGA) and enriched our understanding of gene functions. Using the least absolute selection and shrinkage operator (LASSO) regression, we established a risk model and validated it using an independent dataset from the International Cancer Genome Consortium (ICGC). Clinical variables were incorporated into a nomogram to predict overall survival (OS), and machine learning was used to explore the risk factor characteristics' impact on PCa prognosis. Our prognostic model was confirmed using various databases, including single-cell RNA-sequencing datasets (scRNA-seq), the Cancer Cell Line Encyclopedia (CCLE), PCa cell lines, and tumor tissues. RESULTS: We identified 83 differentially expressed genes (DEGs). Furthermore, WASIR1, KRTAP5-1, TLX1, KIF4A, and IQGAP3 were determined to be significant risk factors for OS and progression-free survival (PFS). Based on these five risk factors, we developed a risk model and nomogram for predicting OS and PFS, with a C-index of 0.823 (95% CI, 0.766-0.881) and a 10-year area under the curve (AUC) value of 0.788 (95% CI, 0.633-0.943). Additionally, the 3-year AUC was 0.759 when validating using ICGC. KRTAP5-1 and WASIR1 were found to be the most influential prognosis factors when using the optimized machine learning model. Finally, the established model was interrelated with immune cell infiltration, and the signals were found to be differentially expressed in PCa cells when using scRNA-seq datasets and tissues. CONCLUSIONS: We engineered an original and novel prognostic model based on five gene signatures through TCGA and machine learning, providing new insights into the risk of scarification and survival prediction for PCa patients in clinical practice.