Research progress on deep learning in magnetic resonance imaging–based diagnosis and treatment of prostate cancer: a review on the current status and perspectives

Multiparametric magnetic resonance imaging (mpMRI) has emerged as a first-line screening and diagnostic tool for prostate cancer, aiding in treatment selection and noninvasive radiotherapy guidance. However, the manual interpretation of MRI data is challenging and time-consuming, which may impact sensitivity and specificity. With recent technological advances, artificial intelligence (AI) in the form of computer-aided diagnosis (CAD) based on MRI data has been applied to prostate cancer diagnosis and treatment. Among AI techniques, deep learning involving convolutional neural networks contributes to detection, segmentation, scoring, grading, and prognostic evaluation of prostate cancer. CAD systems have automatic operation, rapid processing, and accuracy, incorporating multiple sequences of multiparametric MRI data of the prostate gland into the deep learning model. Thus, they have become a research direction of great interest, especially in smart healthcare. This review highlights the current progress of deep learning technology in MRI-based diagnosis and treatment of prostate cancer. The key elements of deep learning-based MRI image processing in CAD systems and radiotherapy of prostate cancer are briefly described, making it understandable not only for radiologists but also for general physicians without specialized imaging interpretation training. Deep learning technology enables lesion identification, detection, and segmentation, grading and scoring of prostate cancer, and prediction of postoperative recurrence and prognostic outcomes. The diagnostic accuracy of deep learning can be improved by optimizing models and algorithms, expanding medical database resources, and combining multi-omics data and comprehensive analysis of various morphological data. Deep learning has the potential to become the key diagnostic method in prostate cancer diagnosis and treatment in the future

Unleashing novel horizons in advanced prostate cancer treatment: investigating the potential of prostate specific membrane antigen-targeted nanomedicine-based combination therapy

Prostate cancer (PCa) is a prevalent malignancy with increasing incidence in middle-aged and older men. Despite various treatment options, advanced metastatic PCa remains challenging with poor prognosis and limited effective therapies. Nanomedicine, with its targeted drug delivery capabilities, has emerged as a promising approach to enhance treatment efficacy and reduce adverse effects. Prostate-specific membrane antigen (PSMA) stands as one of the most distinctive and highly selective biomarkers for PCa, exhibiting robust expression in PCa cells. In this review, we explore the applications of PSMA-targeted nanomedicines in advanced PCa management. Our primary objective is to bridge the gap between cutting-edge nanomedicine research and clinical practice, making it accessible to the medical community. We discuss mainstream treatment strategies for advanced PCa, including chemotherapy, radiotherapy, and immunotherapy, in the context of PSMA-targeted nanomedicines. Additionally, we elucidate novel treatment concepts such as photodynamic and photothermal therapies, along with nano-theragnostics. We present the content in a clear and accessible manner, appealing to general physicians, including those with limited backgrounds in biochemistry and bioengineering. The review emphasizes the potential benefits of PSMA-targeted nanomedicines in enhancing treatment efficiency and improving patient outcomes. While the use of PSMA-targeted nano-drug delivery has demonstrated promising results, further investigation is required to comprehend the precise mechanisms of action, pharmacotoxicity, and long-term outcomes. By meticulous optimization of the combination of nanomedicines and PSMA ligands, a novel horizon of PSMA-targeted nanomedicine-based combination therapy could bring renewed hope for patients with advanced PCa

Prognostic value of microRNA-20b expression level in patients with prostate cancer

Background. miR-20b is a member of the miR-106a-363 gene cluster located in the mammalian X chromosome, the larger miR-17 family, and the miR-17- 92 and miR-106b-25 gene clusters. Previous studies have indicated that miR-20b may function as oncogene or tumor suppressor in different types of cancers. The present study analyzed the association between miR-20b and clinicopathological characteristics of patients with prostate cancer. Methods. A total of 127 pairs of prostate cancer tissue samples and adjacent prostate tissue samples were collected from April 2013 to March 2018. The associations between miR-20b expression levels and clinicopathological factors were assessed using the χ 2‑test. Survival was estimated using the Kaplan-Meier method, and the differences in survival according to miR-20b expression were compared using the log-rank test. Prognostic values of miR-20b expression and clinical outcomes were evaluated by Cox regression analysis. Results. The relative expression of miR-20b in prostate cancer tissues was significantly higher than that in adjacent noncancerous prostate tissues (P<0.001). miR-20b expression was observed to be significantly associated with Gleason score (P<0.001), lymph node metastasis (P<0.001), and TNM stage (P=0.002). The log-rank test indicated that patients with increased miR- 20b expression experienced poor overall survival (P=0.037). Multivariate Cox regression analysis showed that miR-20b expression level (HR=2.181, 95% CI: 1.772-9.021, P=0.016) was an independent factor in predicting the overall survival of prostate cancer patients. Conclusion. The present study demonstrated that tissue miR-20b expression level could be a promising biomarker of prognosis in prostate cancer

A New Trajectory Tracking Control Method for Fully Electrically Driven Quadruped Robot

To improve the accuracy of tracking the trunk center-of-mass (CoM) trajectory and foot-end trajectory in a fully electrically driven quadruped robot, an efficient and practical new trajectory tracking control method is designed. The proposed trajectory tracking method is mainly divided into trunk balance controller (TBC) and swing leg controller (SLC). In TBC, a quadruped robot dynamics model is developed to find the optimal foot-end force that follows the trunk CoM trajectory based on the model predictive control (MPC) principle. In SLC, the Bessel curve is planned as the desired trajectory at the foot-end, while the desired trajectory is tracked by a virtual spring-damping element driving the foot-end, meanwhile, the radial basis function neural network (RBFNN) is applied for supervisory control to improve the control performance for the system. The experimental results show that the control method can modify the robot’s foot-end trajectory tracking effect, so that the stability error can be eliminated and the robustness of the controller can be improved, meanwhile, the linear and circular trajectory for CoM can be tracked accurately and quickly

Table_1_Assessment of biochemical outcomes in patients with primary aldosteronism after adrenalectomy based on CT scan diagnosis of unilateral adenoma without adrenal vein sampling.doc

PurposeThe purpose of this study was to assess the surgical outcomes of patients with primary aldosteronism when surgery was based only on CT finding of unilateral adenoma without adrenal vein sampling (AVS).MethodsThis is a retrospective review of the records of patients who had undergone retroperitoneal laparoscopic adrenalectomy for primary aldosteronism based on CT scan finding of unilateral adenoma and had a follow-up of at least 6–12 months from January 2012 to December 2020 in a single center; decision for adrenalectomy was based on CT scan, and AVS was not used. The clinical and biochemical outcomes were accessed using the standardized primary aldosteronism surgical outcome (PASO) criteria. Patient’s demographics and preoperative factors were analyzed to assess for independent predictor of surgical success.ResultsAccording to the PASO criteria, 172 patients finally enrolled in the training dataset, and 20 patients enrolled in the validation dataset. In the training dataset, complete clinical success was achieved in 71 patients (41.3%), partial success in 87 (50.6%), and absent success in 14 (8.1%). Biochemical outcomes showed that 151 patients (87.8%) were completely cured, 14 patients (8.1%) got a partial biochemical success, and an absent biochemical success was found in seven patients (4.1%). Multivariate logistic regression analysis showed that age, body mass index (BMI), tumor size, mean arterial pressure (MAP), and serum potassium were the most independent factors for incomplete biochemical success. Based on the results of statistical analysis, our study constructed a nomogram prognostic evaluation model for patients after unilateral primary aldosterone surgery.ConclusionsLaparoscopic adrenalectomy for patients with primary aldosteronism base on CT scan finding of a unilateral adenoma without AVS had a high rate of complete biochemical cure at 12 months. Risk factors for incomplete biochemical success include age, BMI, tumor size, MAP, and serum potassium. Our study constructed a nomogram prognostic evaluation model for patients after unilateral primary aldosterone surgery. The nomogram accurately and reliably predicted the incomplete biochemical success.</p

Chimeric antigen receptor-modified T cells therapy in prostate cancer: A comprehensive review on the current state and prospects

Recent immunotherapy research has focused on chimeric antigen receptor-modified T cells (CAR-Ts). CAR-T therapies have been clinically applied to manage hematologic malignancies with satisfactory effectiveness. However, the application of CAR-T immunotherapy in solid tumors remains challenging. Even so, current CAR-T immunotherapies for prostate cancer (PCa) have shown some promise, giving hope to patients with advanced metastatic PCa. This review aimed to elucidate different types of prostate tumor-associated antigen targets, such as prostate-specific membrane antigen and prostate stem cell antigen, and their effects. The current status of the corresponding targets in clinical research through their applications was also discussed. To improve the efficacy of CAR-T immunotherapy, we addressed the possible applications of multimodal immunotherapy, chemotherapy, and CAR-T combined therapies. The obstacles of solid tumors were concisely elaborated. Further studies should aim to discover novel potential targets and establish new models by overcoming the inherent barriers of solid tumors, such as tumor heterogeneity and the immunosuppressive nature of the tumor microenvironment

An artificial tongue fluorescent sensor array for identification and quantitation of various heavy metal ions

Herein, a small-molecule fluorescent sensor array for rapid identification of seven heavy metal ions was designed and synthesized, with its sensing mechanism mimicking that of a tongue. The photoinduced electron transfer and intramolecular charge transfer mechanism result in combinatorial interactions between sensor array and heavy metal ions, which lead to diversified fluorescence wavelength shifts and emission intensity changes. Upon principle component analysis (PCA), this result renders clear identification of each heavy metal ion on a 3D spatial dispersion graph. Further exploration provides a concentration-dependent pattern, allowing both qualitative and quantitative measurements of heavy metal ions. On the basis of this information, a &quot;safe-zone&quot; concept was proposed, which provides rapid exclusion of versatile hazardous species from clean water samples based on toxicity characteristic leaching procedure standards. This type of small-molecule fluorescent sensor array could open a new avenue for multiple heavy metal ion detection and simplified water quality analysis.close0

Redefining Molecular Amphipathicity in Reversing the “Coffee-Ring Effect”: Implications for Single Base Mutation Detection

The “coffee ring effect” is a natural phenomenon wherein sessile drops leave ring-shaped structures on the solid surfaces upon drying. It drives a nonuniform deposition of suspended compounds on the substrates, which adversely affects many processes, including surface-assisted biosensing and molecular self-assembly. In this study, we describe how the coffee ring effect can be eliminated by controlling the amphipathicity of the suspended compounds, for example, DNA modified with hydrophobic dye. Specifically, nuclease digestion of the hydrophilic DNA end converts the dye-labeled molecule into an amphipathic molecule (one with comparably weighted hydrophobic and hydrophilic ends) and reverses the coffee ring effect and results in a uniform disk-shaped feature deposition of the dye. The amphipathic product decreases the surface tension of the sessile drops and induces the Marangoni flow, which drives the uniform distribution of the amphipathic dye-labeled product in the drops. As a proof of concept, this strategy was used in a novel enzymatic amplification method for biosensing to eliminate the coffee ring effect on a nitrocellulose membrane and increase assay reliability and sensitivity. Importantly, the reported strategy for eliminating the coffee ring effect can be extended to other sessile drop systems for potentially improving assay reliability and sensitivity