PHLDA3 exerts an antitumor function in prostate cancer by down-regulating Wnt/ß-catenin pathway via inhibition of Akt.

Pleckstrin homology-like domain family A, member 3 (PHLDA3) is a novel tumor-related protein that mediates carcinogenesis of multiple cancers. However, the relevance of PHLDA3 in prostate cancer has not been explored. The purpose of this work was to illustrate the possible roles and mechanisms of PHLDA3 in prostate cancer. Our data showed strikingly lower abundance of PHLDA3 in prostate cancer, and that low levels of PHLDA3 in prostate cancer patients was associated with reduced survival. PHLDA3 was also weakly expressed in prostate cancer cells, and demethylation treatment dramatically up-regulated the expression level of PHLDA3. Up-regulation of PHLDA3 restrained proliferation, induced G1 cell cycle arrest, suppressed epithelial-mesenchymal transition of prostate cancer cells. In addition, up-regulation of PHLDA3 increased the sensitivity of prostate cancer cells to docetaxel In-depth research into the mechanism elucidated that PHLDA3 overexpression decreased the phosphorylation of Akt and suppressed the activation of Wnt/ß-catenin signaling. Overexpression of constitutively active Akt strikingly abolished PHLDA3-mediated inactivation of Wnt/ß-catenin pathway. A xenograft assay revealed that prostate cancer cells with PHLDA3 overexpression displayed reduced tumorigenicity in vivo. Collectively, these data document that PHLDA3 exerts an outstanding cancer-inhibiting role in prostate cancer by down-regulating Wnt/ß-catenin pathway via the inhibition of Akt. This work highlights PHLDA3 as a novel anticancer target for prostate cancer.

Optical biomarker analysis for renal cell carcinoma obtained from preoperative and postoperative patients using ATR-FTIR spectroscopy.

Renal cell carcinoma (RCC) is the most common malignant tumor in the urinary system, accounting for 80 % to 90 % for all renal malignancies. Traditional diagnostic methods like magnetic resonance imaging (MRI) and computed tomography (CT) lack the sensitivity and specificity as they lack specific biomarkers. These limitations impede effective monitoring of tumor recurrence. This study aims to employ Attenuated Total Reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy, an optical technology sensitive to molecular groups, to analyze the potential optical biomarkers in urine and plasma samples from RCC patients pre- and post-surgery. The results reveal distinctive spectral information from both plasma and urine samples. Post-surgery urine spectra exhibit complexity compared to plasma, showing reduced content at 1072 cm-1, 1347 cm-1 and 1654 cm-1 bands, while increased content at 1112 cm-1, 1143 cm-1, 1447 cm-1, 3334 cm-1 and 3420 cm-1 bands. Utilizing machine learning models such as eXtreme Gradient Boosting (XGBoost), support vector machine (SVM), partial least squares (PLS), and artificial neural network (ANN), the study evaluated plasma and urine samples pre- and post-surgery. Remarkably, the XGBoost method excelled in distinguishing between tumor conditions and recovery, achieving an impressive AUC value of 0.99. These results underscore the potential of ATR-FTIR technology in identifying RCC optical biomarkers, with XGBoost showing promise as a valuable screening tool for RCC recurrence diagnosis.

Case reports of robot-assisted laparoscopic radical nephrectomy and inferior vena cava tumor thrombectomy: A retrospective analysis.

ABSTRACT: Renal cell carcinoma is one common type of urologic cancers. It has tendencies to invade into the inferior vena cava (IVC) and usually requires an open surgery procedure. High rates of operative complications and mortality are usually associated with an open surgery procedure. The recently emerged robot-assisted laparoscopic radical nephrectomy (RAL-RN) and IVC tumor thrombectomy have shown to reduce operative related complications in patients with renal cell carcinoma.This case series study aimed to summarize technical utilization, perioperative outcomes, and efficacies of RAL-RN and IVC tumor thrombectomy in our hospital. A retrospective analysis was performed on clinical data from 20 patients who underwent RAL-RN and IVC tumor thrombectomy from January 2017 to December 2019 in our department.Patients had a median age of 59 years (interquartile range [IQR], 46-68). Four patients had renal neoplasm on left side and 16 on right side. Nineteen patients underwent RAL-RN (level 0: n = 2) or RAL-RN with IVC thrombectomy (n = 17) (level I: n = 3; level II: n = 12; and level III: n = 3) and 1 patient was converted into an open surgery. The median operative time was 328 minutes (IQR, 221-453). The estimated median blood loss was 500 mL (IQR, 200-1200). The median size of removed renal carcinoma was 67 cm2 (IQR, 40-91); the length of IVC tumor thrombus was 5 cm (IQR, 3-7). The postsurgery hospital length of stay was 6 days (IQR, 5-7). The complications included intestinal obstruction (n = 1), lymphatic fistula (n = 1), heart failure (n = 1), and low hemoglobin level (n = 1). The outcomes for patients after 16 months (IQR, 11-21) follow-up were tumor-free (n = 10), tumor progression (n = 4), loss of contact (n = 1), and death (n = 5).We concluded that RAL-RN and IVC thrombectomy renders good safety profiles including minimal invasiveness, low estimated median blood loss, short hospitalization, low morbidity, and quick renal function recovery. The long-term efficacy needs a further investigation.

Fuzzy [Formula: see text] output-feedback control for the discrete-time system with channel fadings, sector nonlinearities, and randomly occurring interval delays and nonlinearities.

In this paper, the fuzzy [Formula: see text] output-feedback control problem is investigated for a class of discrete-time T-S fuzzy systems with channel fadings, sector nonlinearities, randomly occurring interval delays (ROIDs) and randomly occurring nonlinearities (RONs). A series of variables of the randomly occurring phenomena obeying the Bernoulli distribution is used to govern ROIDs and RONs. Meanwhile, the measurement outputs are subject to the sector nonlinearities (i.e. the sensor saturations) and we assume the system output is [Formula: see text], [Formula: see text]. The Lth-order Rice model is utilized to describe the phenomenon of channel fadings by setting different values of the channel coefficients. The aim of this work is to deal with the problem of designing a full-order dynamic fuzzy [Formula: see text] output-feedback controller such that the fuzzy closed-loop system is exponentially mean-square stable and the [Formula: see text] performance constraint is satisfied, by means of a combination of Lyapunov stability theory and stochastic analysis along with LMI methods. The proposed fuzzy controller parameters are derived by solving a convex optimization problem via the semidefinite programming technique. Finally, a numerical simulation is given to illustrate the feasibility and effectiveness of the proposed design technique.