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Introduction: The prognostic significance of steroid receptors in bladder cancer remains controversial. This study was designed to determine the expression status of androgen receptor (AR), estrogen receptors (ERα and Erß), and its potential role in predicting survival in patients with nonmuscle invasive bladder cancer (NMIBC). Methods: Sixty patients of NMIBC were screened and 57 (41 males and 16 females) were included in our study. The tissue microarray slides were evaluated by pathologists blinded to the clinical information. Association of distribution of steroid receptors with stage, grade, progression, and recurrence was seen. Results: The mean age of the population was 60.9 ± 9.3 years. Pathologically, majority of the patients were Ta (Ta: T1 stage 61.4% vs. 38.6%). Nine (15.8%) of the tumors stained positive for AR while one (1.8%) tumor stained positive for ERα and 36 (63.2%) tumors stained for ERß. A higher proportion of male NMIBC stained positive for AR (19.5% vs. 6.2%, P = 0.420) while ERß positivity was higher in females (58.5% vs. and 75%,P = 0.247). AR-negative tumors showed higher recurrence (20/48%-42%) as compared to AR-positive tumors (2/9%-22%). ERß-positive tumors showed higher recurrence (15/36%-42% vs. 7/21%-33%, P = 0.179). Progression-free survival (PFS) was found to be significantly lower for ERß-negative group (log-rank test P = 0.035). Conclusion: AR and ERß positivity is found in NMIBC patients while ERα shows minimal staining in NMIBC patients. Although it did not reach a statistical significance, a higher proportion of AR-negative and ERß-positive tumors recurred as compared to AR-positive and ERß-negative patients. PFS was significantly lower in ERß-negative group. Further exploratory studies on larger sample sizes are required to validate these findings in NMIBC patients.
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Aim: Cancer is a significant public health concern, and National Cancer Control Programs (NCCPs) are crucial for reducing its burden. However, assessing the progress of NCCPs is challenging due to the complexity of cancer control outcomes and the various factors that influence them. Composite indicators can provide a comprehensive and accurate assessment of NCCP progress. Materials and Methods: The dataset was compiled for 144 countries and comprised eight composite indices and two high-level comparative indicators (mortality-to-cancer incidence ratio [MIR] and 5-year cancer prevalence-to-incidence ratio [PCIR]) representing NCCP outcomes. Two large databases and six annual composite index reports were consulted. Linear regression analysis and Pearson correlation coefficients were used to establish a relationship between indicators and NCCP outcomes. A multiple regression machine learning model was generated to further improve the accuracy of NCCP outcome prediction. Results: High-income countries had the highest cancer incidence, whereas low-income countries had the highest MIR. Linear regression analysis indicated a negative trend between all composite indicators and MIR, whereas a positive trend was observed with PCIR. The Human Development Index and the Legatum Prosperity Index had the highest adjusted R 2 values for MIR (0.74 and 0.73) and PCIR (0.86 and 0.81), respectively. Multiple linear regression modeling was performed, and the results indicated a low mean squared error score (-0.02) and a high R 2 score (0.86), suggesting that the model accurately predicts NCCP outcomes. Conclusions: Overall, composite indicators can be an effective tool for evaluating NCCP, and the results of this study can aid in the development and keeping track of NCCP progress for better cancer control.
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Predicting ionic conductivity is crucial for developing efficient electrolytes for energy storage and conversion and other electrochemical applications. An accurate estimate of ionic conductivity requires understanding complex ion-ion and ion-solvent interactions governing the charge transport at the molecular level. Molecular simulations can provide key insights into the spatial and temporal behavior of electrolyte constituents. However, such insights depend on the ability of force fields to describe the underlying phenomena. In this work, molecular dynamics simulations were leveraged to delineate the impact of force field parameters on ionic conductivity predictions of potassium hydroxide (KOH) in ethylene glycol (EG). Four different force fields were used to represent the K+ ion. Diffusion-based Nernst-Einstein and correlation-based Einstein approaches were implemented to estimate the ionic conductivity, and the predicted values were compared with experimental measurements. The physical aspects, including ion-aggregation, charge distribution, cluster correlation, and cluster dynamics, were also examined. A force field was identified that provides reasonably accurate Einstein conductivity values and a physically coherent representation of the electrolyte at the molecular level.
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Copper sulfide nanostructures have evolved as one of the most technologically important materials for energy conversion and storage owing to their economic and non-toxic nature and superior performances. This paper presents a direct, scalable synthetic route aided by a single source molecular precursor (SSP) approach to access copper sulfide nanomaterials. Two SSPs, CuX(dmpymSH)(PPh3)2 (where X = Cl or I), were synthesized in quantitative yields and thermolyzed under appropriate conditions to afford the nanostructures. The analysis of the nanostructures through pXRD, EDS and XPS suggested that phase pure digenite (Cu9S5) and djurleite (Cu31S16) nanostructures were isolated from -Cl and -I substituted SSPs, respectively. The morphologies of the as-synthesized nanomaterials were investigated using electron microscopy techniques (SEM and TEM). DRS studies on pristine materials revealed blue shifted optical band gaps, which were found to be optimum for photoelectrochemical application. A prototype photoelectrochemical cell fabricated using the pristine nanostructures exhibited a stable photo-switching property, which presents these materials as suitable economic and environmentally friendly photon absorber materials.