RESUMEN

Background: The rapid and accurate acquisition of prostate cancer pathological tissue is critical to prostate cancer research but has traditionally proven challenging. However, the gradual application of three-dimensional (3D) modeling in medical practice has overcome many of the related limitations. This cohort study aimed to compare the difference between a 3D stereotaxic sampling method and traditional cognitive sampling method to clarify the factors affecting sampling. Methods: An analysis of 111 men who received radical prostatectomy for prostate cancer at The First Affiliated Hospital of Soochow University between November 2020 and April 2022 was conducted. The positive rate of the cognitive sampling method and the 3D stereotaxic sampling method and their respective influencing factors, such as age, body mass index (BMI), prostate-specific antigen (PSA), PSA density (PSAD), International Society of Urological Pathology (ISUP) grade, tumor volume, number of positive needles from perineal puncture, clinical T stage, and tumor image location, were compared and analyzed, and a cohort study was conducted. Results: Among the 111 patients, there were 57 cases of cognitive sampling and 54 cases of 3D stereotaxic sampling. In this study, the positive rate of cognitive sampling was 29.82% (17/57,), and the positive rate of 3D stereotaxic sampling was 61.11% (33/54), with the positive rate of 3D stereotaxic sampling being significantly higher than that of cognitive sampling (P=0.001). In cognitive sampling, tumor volume [odds ratio (OR) =1.10; 95% confidence interval (CI): 1.02-1.20], number of positive biopsy cores (OR =1.30; 95% CI: 1.06-1.60), Prostate Imaging Report and Data System (PI-RADS) score (OR =5.54; 95% CI: 1.60-19.12), and clinical T stage (OR =2.36; 95% CI: 1.31-4.25) were identified as influencing factors; in 3D stereotaxic sampling, these influencing factors were eliminated, with ORs of 1.22 (95% CI: 0.78-1.90), 0.88 (95% CI: 0.72-1.09), 1.09 (95% CI: 0.62-1.92), and 1.51 (95% CI: 0.86-2.65), respectively, representing a statistically significant difference (P<0.05). Conclusions: The 3D stereotaxic sampling method can accurately obtain the required prostate cancer tissue from the prostate in vitro within a short time, and the factors affecting the positive rate of sampling can be eliminated.

RESUMEN

Postharvest fruits, especially climacteric fruits, are prone to ethylene ripening, browning and aging, microbial growth accelerated decay and other problems in natural environment. Herein, a carboxylated cellulose nanofibers/phytic acid­titanium dioxide nanoparticles (CPT) biodegradable coating with "photocatalytic antibacterial barrier" structure，was developed by homogeneous dispersion of phytic acid(PA) complexed titanium dioxide nanoparticles (TNPs) in carboxylated cellulose nanofibers(CCNF). The CPT coating achieves effective dispersion and efficient utilization of TNPs through the complexation of PA. The coating ethylene clearance rate of CPT up to 70.89 %. Meanwhile, the coating exhibits excellent antibacterial (99.67 %), UV resistance, gas barrier. It was found that the CPT coating delays fruit ripening caused by ethylene, which effectively maintaining the quality of respiratory climacteric fruits and non- climacteric fruits, extending the shelf life of perishable fruit by up to 9 days. In particular, the coating is virtually biodegradable in soil after 21 days, which offers the possibility of replacing non-biodegradable multifunctional coatings in food packaging.

RESUMEN

Redundant manipulators, as mechanical equipments imitating human arms, have been applied to various areas in recent years from the perspective of control. Different from pure control technologies, the motion capability of a human arm is achieved by a complex and efficient neural system, with the cerebellum playing a pivotal role. Motivated by this fact, we design a cerebellum model based on an echo state network (ESN) for the learning and control of redundant manipulators. In addition, to simulate the skillful control ability of the cerebellum over movements of human arms, the proposed model is constructed at the joint velocity level. Furthermore, to improve the accuracy and applicability, we propose an ESN-based Kalman-filter-incorporated and cerebellum-inspired (KFICI) scheme for the learning and control of redundant manipulators with Kalman filter incorporated. The proposed scheme enables a redundant manipulator to track the desired trajectory at the velocity level and tolerate noises. Finally, simulations and experiments based on a physical redundant manipulator are performed to verify the effectiveness of the proposed control scheme.

RESUMEN

Purpose To develop and validate a machine learning multimodality model based on preoperative MRI, surgical whole-slide imaging (WSI), and clinical variables for predicting prostate cancer (PCa) biochemical recurrence (BCR) following radical prostatectomy (RP). Materials and Methods In this retrospective study (September 2015 to April 2021), 363 male patients with PCa who underwent RP were divided into training (n = 254; median age, 69 years [IQR, 64-74 years]) and testing (n = 109; median age, 70 years [IQR, 65-75 years]) sets at a ratio of 7:3. The primary end point was biochemical recurrence-free survival. The least absolute shrinkage and selection operator Cox algorithm was applied to select independent clinical variables and construct the clinical signature. The radiomics signature and pathomics signature were constructed using preoperative MRI and surgical WSI data, respectively. A multimodality model was constructed by combining the radiomics signature, pathomics signature, and clinical signature. Using Harrell concordance index (C index), the predictive performance of the multimodality model for BCR was assessed and compared with all single-modality models, including the radiomics signature, pathomics signature, and clinical signature. Results Both radiomics and pathomics signatures achieved good performance for BCR prediction (C index: 0.742 and 0.730, respectively) on the testing cohort. The multimodality model exhibited the best predictive performance, with a C index of 0.860 on the testing set, which was significantly higher than all single-modality models (all P ≤ .01). Conclusion The multimodality model effectively predicted BCR following RP in patients with PCa and may therefore provide an emerging and accurate tool to assist postoperative individualized treatment. Keywords: MR Imaging, Urinary, Pelvis, Comparative Studies Supplemental material is available for this article. © RSNA, 2024.

Asunto(s)

Imagen por Resonancia Magnética , Recurrencia Local de Neoplasia , Prostatectomía , Neoplasias de la Próstata , Humanos , Masculino , Neoplasias de la Próstata/diagnóstico por imagen , Neoplasias de la Próstata/cirugía , Neoplasias de la Próstata/sangre , Anciano , Estudios Retrospectivos , Recurrencia Local de Neoplasia/diagnóstico por imagen , Recurrencia Local de Neoplasia/sangre , Persona de Mediana Edad , Prostatectomía/métodos , Imagen por Resonancia Magnética/métodos , Aprendizaje Automático , Valor Predictivo de las Pruebas , Imagen Multimodal/métodos , Antígeno Prostático Específico/sangre , Imágenes de Resonancia Magnética Multiparamétrica/métodos

RESUMEN

OBJECTIVE: To clarify the composition of lesions in different magnetic resonance imaging (MRI) partitions of positive surgical margins (PSM) after laparoscopic radical prostatectomy, explore the influence of lesion location on PSM, and construct a clinical prediction model to predict the risk of PSM. MATERIALS AND METHODS: This retrospective cohort study included 309 patients who underwent laparoscopic radical prostatectomy from 2018 to 2021 in our center was performed. 129 patients who met the same criteria from January to September 2022 were external validation cohorts. RESULTS: The incidence of PSM in transition zone (TZ) lesions was higher than that in peripheral zone (PZ) lesions. The incidence of PSM in the middle PZ was lower than that in other regions. Prostate specific antigen (PSA), clinical T-stage, the number of positive cores, international society of urological pathology (ISUP) grade (biopsy), MRI lesion location, extracapsular extension, seminal vesicle invasion (SVI), pseudo-capsule invasion (PCI), long diameter of lesions, lesion volume, lesion volume ratio, PSA density were related to PSM. MRI lesion location and PCI were independent risk factors for PSM. Least absolute shrinkage and selection operator (LASSO) regression was used to construct a clinical prediction model for PSM, including five variables: the number of positive cores, SVI, MRI lesion location, long diameter of lesions, and PSA. CONCLUSION: The positive rate of surgical margin in middle PZ was significantly lower than that in other regions, and MRI lesion location was an independent risk factor for PSM.

Asunto(s)

Laparoscopía , Imagen por Resonancia Magnética , Márgenes de Escisión , Prostatectomía , Neoplasias de la Próstata , Humanos , Masculino , Prostatectomía/métodos , Laparoscopía/métodos , Neoplasias de la Próstata/cirugía , Neoplasias de la Próstata/patología , Neoplasias de la Próstata/diagnóstico por imagen , Estudios Retrospectivos , Imagen por Resonancia Magnética/métodos , Persona de Mediana Edad , Anciano , Antígeno Prostático Específico/sangre , Factores de Riesgo , Medición de Riesgo/métodos , Clasificación del Tumor , Estadificación de Neoplasias

RESUMEN

BACKGROUND: The high-mobility group A1 gene (HMGA1) plays a major role in the development of malignant cancers. However, the mechanisms underlying the correlation between HMGA1 expression level and patients' overall survival rate in various malignant cancers is unclear. METHODS: We used The Cancer Genome Atlas (TCGA) database (https://genome-cancer.ucsc.edu/) to search for mRNA expression levels of HMGA1 in tumor patients and grouped them by receiver operating characteristic (ROC) curve. This divided patients into a high expression cohort and low expression cohort, and Kaplan-Meier analysis revealed the overall survival of the cancer patients. We also used real-time quantitative PCR (qPCR) to detect the expression of HMGA1, CBX7, E-cadherin, and ß-catenin gene was detected by normalized to the expression of ß-actin in colorectal cancer cell lines. RESULTS: High expression group correlated with worse survival prognosis statistically significant (P<0.05), and scatter plots showed HMGA1 high expression in the different cancers (lung cancers; lung adenocarcinoma and lung squamous cell carcinoma; stomach and colorectal cancers; liver and pancreatic cancer; kidney papillary cell carcinoma; kidney clear cell carcinoma, brain lower grade glioma; adrenocortical cancer; acute myeloid leukemia; and sarcoma; head and neck squamous cell carcinoma, cholangio and bladder urothelial cancers). Further, we also found that the mRNA expressions of HMGA1, CBX7, E-cadherin, and ß-catenin genes significantly in colorectal cancer cell lines (P value: 0.0005), consistent with the results of HMGA1 in TCGA database. CONCLUSIONS: HMGA1 is highly expressed in various cancers than normal tissues, and high expression levels of HMGA1 correlated with a worse prognosis. The gene expressions and the TCGA data clearly supports that targeting HMGA1 in the management of cancers increases the survival rate of cancer patients.

RESUMEN

The aberrant expression of long noncoding RNAs (lncRNAs) is implicated in cancer development and progression. However, the clinical significance and mechanism by which NONHSAT062994 regulates colorectal cancer (CRC) is unknown. We here reported that NONHSAT062994 was significantly downregulated in human CRC tissues and cell lines. Moreover, its expression was inversely correlated with tumor size and overall survival (OS) time in CRC patients. In CRC cells, the overexpression and knockdown of NONHSAT062994 inhibited and enhanced CRC cell growth, respectively, in vitro and in vivo. Mechanistically, NONHSAT062994 functioned as a tumor suppressor to inhibit CRC cell growth by inactivating Akt signaling. Notably, the NONHSAT062994 expression status was negatively correlated with the Akt downstream targets c-Myc and Cyclin D1 in clinical CRC samples. The current findings suggest that NONHSAT062994 plays a critical role in the development of CRC by regulating Akt signaling, and identified a candidate prognostic biomarker or potential therapeutic target for CRC patients.