Copy Number Gain in Androgen Receptors Predicts the Poor Prognosis in Japanese Castration-resistant Prostate Cancer.

BACKGROUND/AIM: The prognostic significance of androgen receptor amplification (AR amp) in cell-free DNA (cfDNA) was studied in Japanese patients with castration-resistant prostate cancer (CRPC). PATIENTS AND METHODS: A total of 120 serum samples were obtained from 38 patients with CRPC. Serum cfDNA was purified and the AR copy number was determined. Factors associated with progression-free survival (PFS) and overall survival (OS) were statistically investigated. RESULTS: The number of patients administered enzalutamide (Enza)/abiraterone (Abi)/docetaxel (DTX) was 33/25/11, respectively. The median PSA was 16.5 ng/ml. Thirty patients (79%) had bone metastases and three patients (7.9%) had lung metastases. The median follow-up was 655 days. The median initial AR copy number was 1.27 (1.10-11.50); an AR copy number of 1.27 or higher was defined as an AR-amp. Regarding PFS, the presence of AR-amp, Gleason score (GS), and ALP were significant factors in univariate analysis. In multivariate analysis, AR amplification was an independent prognostic factor (hazard ratio=7.7, p=0.0035). For OS, PSA and AR-amp were significant factors. In multivariate analysis, AR-amp (hazard ratio=4.65, p=0.0188) was the only independent prognostic factor. CONCLUSION: AR-amp was associated with high nadir PSA and low iPSA/PSA ratio. AR-amp was significantly associated with poor prognosis in Japanese patients with CRPC.

Preoperative PI-RADS v2.1 Scoring System Improves Risk Classification in Patients Undergoing Radical Prostatectomy.

BACKGROUND/AIM: The purpose of this study was to examine the prognostic value of Prostate imaging-reporting and data system (PI-RADS) v2.1 scoring system in patients who underwent radical prostatectomy (RP). PATIENTS AND METHODS: Clinical data of 294 patients who received RP between 2006 and 2018 were reviewed and multiple parameters including PI-RADS v2.1 score were employed to identify predictive factors for biochemical recurrence (BCR). Tumor volume was calculated from prostatectomy specimens. RESULTS: Median age at operation and initial PSA level were 67 years old and 7.68 ng/ml, respectively. 44.9 and 24.8% of patients were diagnosed with PI-RADS score 4 and 5 prior to biopsies, respectively. BCR was observed in 17% of patients and median observation period was 63.43 months. After multivariate analysis, PI-RADS v2.1 score 5 [hazard ratio (HR)=2.24, p=0.0124] was an independent predictive factor of BCR in addition to clinical T stage (≥2c) (HR=2.32, p=0.0093) and biopsy Gleason score (≥8) (HR=2.81, p=0.0007). Furthermore, PI-RADS score 5 significantly stratified the prognosis in D'Amico intermediate- and high-risk groups (p=0.0174 and p=0.0013, respectively). We established novel risk classifications including PI-RADS v2.1 score and found that prognostic capabilities were improved as compared to the D'Amico classification. CONCLUSION: The PI-RADS v2.1 score exhibited significant prognostic value in patients with localized prostate cancer following RP. Risk classifications based on PI-RADS v2.1 score might provide better ability for predicting oncological outcomes as compared to the D'Amico classification system.

OutcropHyBNet: Hybrid Backbone Networks with Data Augmentation for Accurate Stratum Semantic Segmentation of Monocular Outcrop Images in Carbon Capture and Storage Applications.

The rapid advancement of climate change and global warming have widespread impacts on society, including ecosystems, water security, food production, health, and infrastructure. To achieve significant global emission reductions, approximately 74% is expected to come from cutting carbon dioxide (CO2) emissions in energy supply and demand. Carbon Capture and Storage (CCS) has attained global recognition as a preeminent approach for the mitigation of atmospheric carbon dioxide levels, primarily by means of capturing and storing CO2 emissions originating from fossil fuel systems. Currently, geological models for storage location determination in CCS rely on limited sampling data from borehole surveys, which poses accuracy challenges. To tackle this challenge, our research project focuses on analyzing exposed rock formations, known as outcrops, with the goal of identifying the most effective backbone networks for classifying various strata types in outcrop images. We leverage deep learning-based outcrop semantic segmentation techniques using hybrid backbone networks, named OutcropHyBNet, to achieve accurate and efficient lithological classification, while considering texture features and without compromising computational efficiency. We conducted accuracy comparisons using publicly available benchmark datasets, as well as an original dataset expanded through random sampling of 13 outcrop images obtained using a stationary camera, installed on the ground. Additionally, we evaluated the efficacy of data augmentation through image synthesis using Only Adversarial Supervision for Semantic Image Synthesis (OASIS). Evaluation experiments on two public benchmark datasets revealed insights into the classification characteristics of different classes. The results demonstrate the superiority of Convolutional Neural Networks (CNNs), specifically DeepLabv3, and Vision Transformers (ViTs), particularly SegFormer, under specific conditions. These findings contribute to advancing accurate lithological classification in geological studies using deep learning methodologies. In the evaluation experiments conducted on ground-level images obtained using a stationary camera and aerial images captured using a drone, we successfully demonstrated the superior performance of SegFormer across all categories.

Clinical utility of the prognostic nutritional index in patients with metastatic hormone-sensitive prostate cancer: A retrospective, multicenter, cohort study.

BACKGROUND: The prognostic nutritional index (PNI) based on the serum albumin level and the lymphocyte count has been investigated as a prognostic factor in patients with malignant tumors. However, it has been poorly studied in prostate cancer (PCa), and little is known about its clinical utility. METHODS: Clinical data of 353 patients with de novo, metastatic, hormone-sensitive PCa (mHSPC) who received androgen deprivation therapy (ADT) were obtained from multiple institutions between 2000 and 2019. The impacts of the pretreatment PNI level on treatment response and survival, together with clinical parameters, were examined. The Mann-Whitney U test, Cox proportional hazards models, and Kaplan-Meier methods were used to evaluate significance. RESULTS: The median age and initial prostate-specific antigen level were 73 and 266.18 ng/mL, respectively. Patients with a low PNI had shorter progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS) (p < 0.0001). On multivariate analysis, low PNI was an independent prognostic factor for OS (p = 0.0027, HR = 1.65), as well as advanced age (p = 0.049, HR = 1.38), the International Society of Urological Pathology (ISUP) grade group (GG) 5 (p = 0.0027, HR = 1.69), and elevated lactate dehydrogenase (LDH) (p < 0.0001, HR = 2.08). A propensity score-matching analysis showed that the PNI level remained a significant prognostic biomarker for PFS (p = 0.0263), CSS (p = 0.0006), and OS (p = 0.0015). Furthermore, a novel risk classification using PNI, LDH, and the ISUP GG was established to stratify patients' prognosis. An increase in the number of risk factors was significantly correlated with poor outcomes. CONCLUSIONS: A low pretreatment PNI might be an effective biomarker of poor treatment response and survival in patients with mHSPC undergoing ADT.

Machine-learning predicts time-series prognosis factors in metastatic prostate cancer patients treated with androgen deprivation therapy.

Machine learning technology is expected to support diagnosis and prognosis prediction in medicine. We used machine learning to construct a new prognostic prediction model for prostate cancer patients based on longitudinal data obtained from age at diagnosis, peripheral blood and urine tests of 340 prostate cancer patients. Random survival forest (RSF) and survival tree were used for machine learning. In the time-series prognostic prediction model for metastatic prostate cancer patients, the RSF model showed better prediction accuracy than the conventional Cox proportional hazards model for almost all time periods of progression-free survival (PFS), overall survival (OS) and cancer-specific survival (CSS). Based on the RSF model, we created a clinically applicable prognostic prediction model using survival trees for OS and CSS by combining the values of lactate dehydrogenase (LDH) before starting treatment and alkaline phosphatase (ALP) at 120 days after treatment. Machine learning provides useful information for predicting the prognosis of metastatic prostate cancer prior to treatment intervention by considering the nonlinear and combined impacts of multiple features. The addition of data after the start of treatment would allow for more precise prognostic risk assessment of patients and would be beneficial for subsequent treatment selection.

Design of Surfactant Tails for Effective Surface Tension Reduction and Micellization in Water and/or Supercritical CO2.

The interfacial properties and water-in-CO2 (W/CO2) microemulsion (µE) formation with double- and novel triple-tail surfactants bearing trimethylsilyl (TMS) groups in the tails are investigated. Comparisons of these properties are made with those for analogous hydrocarbon (HC) and fluorocarbon (FC) tail surfactants. Surface tension measurements allowed for critical micelle concentrations (CMC) and surface tensions at the CMC (γCMC) to be determined, resulting in the following trend in surface activity FC > TMS > HC. Addition of a third surfactant tail gave rise to increased surface activity, and very low γCMC values were recorded for the double/triple-tail TMS and HC surfactants. Comparing effective tail group densities (ρlayer) of the respective surfactants allowed for an understanding of how γCMC is affected by both the number of surfactant tails and the chemistry of the tails. These results highlight the important role of tail group chemical structure on ρlayer for double-tail surfactants. For triple-tail surfactants, however, the degree to which ρlayer is affected by tail group architecture is harder to discern due to formation of highly dense layers. Stable W/CO2 µEs were formed by both the double- and the triple-tail TMS surfactants. High-pressure small-angle neutron scattering (HP-SANS) has been used to characterize the nanostructures of W/CO2 µEs formed by the double- and triple-tail surfactants, and at constant pressure and temperature, the aqueous cores of the microemulsions were found to swell with increasing water-to-surfactant ratio (W0). A maximum W0 value of 25 was recorded for the triple-tail TMS surfactant, which is very rare for nonfluorinated surfactants. These data therefore highlight important parameters required to design fluorine-free environmentally responsible surfactants for stabilizing W/CO2 µEs.

Testosterone Reduction of ≥ 480 ng/dL Predicts Favorable Prognosis of Japanese Men With Advanced Prostate Cancer Treated With Androgen-Deprivation Therapy.

INTRODUCTION: Reductions in testosterone concentration play a significant role in the treatment of prostate cancer. We studied the role of testosterone as a prognostic marker for advanced prostate cancer (stage C or higher) treated with primary androgen-deprivation therapy (ADT). PATIENTS AND METHODS: A total of 348 patients were treated using ADT as first-line therapy for prostate cancer at Chiba University Hospital between 1999 and 2016. Of these, 222 patients with advanced prostate cancer (stage C or higher) were enrolled onto this study. The prognostic values of serum testosterone level and other clinical factors were evaluated in association with prostate-specific antigen (PSA), progression-free survival during first-line therapy, and overall survival. RESULTS: Median age was 73 years. PSA at baseline was 86 ng/mL. Gleason scores of ≤ 6, 7, 8, and ≥ 9 were seen in 2.3%, 19.4%, 21.2%, and 41.9%, respectively. Mean follow-up was 60.5 months. Median testosterone at baseline was 482 ng/dL and nadir testosterone was 13 ng/dL. No variable associated with testosterone predicted progression-free survival. With regard to overall survival, multivariate analysis identified nadir testosterone ≤ 20 ng/dL (hazard ratio = 0.44, P = .026) and testosterone reduction ≥ 480 ng/dL (hazard ratio = 0.35, P = .030) as independent prognostic factors. With regard to progression-free survival, multivariate analysis identified nadir PSA ≤ 0.1 ng/mL (hazard ratio = 3.07, P < .001), presence of lymph node metastasis (hazard ratio = 1.67, P = .017), and time to nadir PSA (hazard ratio = 0.30, P < .001) as independent prognostic factors. CONCLUSION: Our data suggested both nadir testosterone (< 20 ng/dL; P = .026) and testosterone reduction (≥ 480 ng/dL; P = .030) to be key prognostic factors for primary ADT in advanced prostate cancer in Japanese men.

Chylothorax associated with child abuse.

We report a case of right chylothorax associated with physical abuse in a 10-month-old boy who presented with respiratory decompensation. Chylothorax was improved by thoracic drainage and nutrition management, such as fasting followed by medium-chain triglyceride milk. Chest computed tomography on admission showed bilateral old rib fractures. Accordingly, physical abuse was suspected. Chylothorax of unknown cause in infancy, especially in those with coexisting rib fractures, must be scrutinized for child abuse.

ATP transport in saccular cerebral aneurysms at arterial bends.

ATP acts as an extracellular signaling molecule in purinergic signaling that regulates vascular tone. ATP binds purinergic P2 nucleotide receptors on endothelial cells. Understanding the mass transport of ATP to endothelial cells by blood flow is thus important to predict functional changes in aneurysmal walls. While some clinical observations indicate a difference of wall pathology between ruptured and unruptured aneurysms, no study has focused on the mass transport in aneurysms. We investigated the characteristics of ATP concentration at aneurysmal wall using a numerical model of ATP transport in aneurysms formed at arterial bends. The magnitude of ATP concentration at the aneurysmal wall was significantly smaller than that at the arterial wall. In particular, significantly low concentration was predicted at the proximal side of the aneurysmal sac. A strong correlation was revealed between the inflow flux at the aneurysmal neck and the resultant concentration at the aneurysmal wall.

The importance of parent artery geometry in intra-aneurysmal hemodynamics.

We show the importance of arterial geometry in intra-aneurysmal hemodynamics. Using a new geometric parameterized saccular aneurysm model including parameters for parent artery shape and the configuration of the aneurysm in the parent artery, we performed a parametric computational fluid dynamics study. We examined lateral saccular aneurysm models with different aneurysm shapes (i.e., the ratio of aneurysm height to aneurysm neck diameter) and different configurations (i.e., the torsion angle of the aneurysm to the upstream part of the parent artery). The aneurysm lateral to the curve of the parent artery had significantly higher wall shear stress than the aneurysm inside or outside the curve of the artery, even with the same shape of the aneurysm. Our findings suggest the important role played by the configuration of the aneurysm relative to the parent artery in intra-aneurysmal hemodynamics.

Inflow into saccular cerebral aneurysms at arterial bends.

To identify shortcomings in the design of conventional endovascular devices, we investigated the inflow features of untreated aneurysms at a variety of arterial bends using computational fluid dynamics. As a preliminary study, we analyzed the steady-state inflow for aneurysms created at U-shaped, twisted, and S-shaped arteries. Both the inflow pattern and inflow flux were strongly influenced by the shape of the artery and the configuration angle of the aneurysm to the artery. We revealed that the secondary flow generated in the parent artery is the dominant factor affecting the inflow. Our results suggest that the arterial geometry and secondary flow should be considered in the design of endovascular devices.