Poly(vinyl alcohol) (PVA)/pullulan (PULL) blend nanofibres were prepared from their aqueous solutions by electrospinning method. Polymer solutions with different concentrations and blend ratios were used to investigate the effect of polymer concentrations and blend ratios on the morphologies and properties of PVA/PULL nanofibres. At a fixed blend ratio, the total polymer concentrations were also adjusted to find suitable electrospinning condition for preparing uniform and bead-free nanofibres. The as-prepared nanofibres were characterized by scanning electron microscopy (SEM), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), X-ray diffraction (XRD), and Fourier transform infrared (FTIR) spectroscopy. Their mechanical properties were also studied by measuring their tensile strength. The results showed that polymer concentrations and blend ratios have direct influence on the morphologies and properties of PVA/PULL nanofibres. 12 wt.% total polymer concentration and higher PVA contents have been found to be favourable for obtaining uniform and bead free PVA/PULL blend nanofibres with improved mechanical and thermal properties.

This research was carried out to systematize and assess the appropriateness of farmer's indigenous knowledge and their adaptive capacity with floods. The research aimed at providing scientific foundation for proposing solutions to conserve and enhance the effectiveness of valuable indigenous knowledge in reducing vulnerability of people living in flooded areas. The results showed that local people are using several effective indigenous knowledge for coping with floods. However, the valuable indigenous knowledge has not recorded yet, nor documented in written materials for sharing to young generation and communities. Besides, some indigenous practices are not suitable in practice which required reevaluation for current flood adaptation strategies. The research suggested some solutions to conserve the most valuable indigenous knowledge for pro-active adaptation of local people in changing climate.

We analyzed the antioxidant and anti-wrinkle effects of Pinus rigida Mill. (pitch pine) to evaluate its use as a cosmetic material. 3-[4,5-Dimethylthiazol-2-yl]-2,5-diphenyl-tetrazoliumbromide assay was performed to evaluate the toxicity of the sample. To evaluate the antiwrinkle activity of P. rigida Mill., the amount of type I procollagen and TIMP-1 synthesized was measured, and Western blot analysis and RT-PCR were performed to determine the expression levels of wrinkle-related proteins and genes. To investigate the inhibitory effect of ROS of P. rigida Mill, we conducted experiments to induce oxidative damage by UVB radiation using zebrafish embryos. Cytotoxicity to EtOAc extract (PRE) was measured using the human dermal fibroblast cell line CCD-986sk, and cytotoxicity was not observed below the concentration of 20 μg/mL. PRE has been shown to increase type I procollagen synthesis and promote the expression of its regulator, TIMP-1. In addition, P. rigida Mill. reduced the expression of MMP-1, -2, and -3 in CCD-986sk cells stimulated with UVB among the matrix metalloproteinases found in the dermal layers, which cause collagen reduction. After treatment with P. rigida Mill. extract at various concentrations, fluorescence spectra of ROS levels in the zebrafish embryos induced by UVB showed that fluorescence intensity decreased in a concentration-dependent manner compared with the intensity of the positive control group. Based on these findings, it is considered that P. rigida Mill. has value as a cosmetic material for antioxidant and anti-wrinkle benefits.

Therapy-induced neuroendocrine prostate cancer (NEPC) is an extremely aggressive variant of castration-resistant prostate cancer (CRPC) that is increasing in incidence with the widespread use of second generation of androgen receptor (AR)-pathway inhibitors (APIs) such as Enzalutamide (ENZ) and Abiraterone. This aggressive variant arises from CRPC-Adenocarcinomas (CRPC-Adeno) via a reversible trans-differentiation process, referred to as neuroendocrine differentiation (NED) wherein cells undergo a lineage switch and exhibit neuroendocrine (NE) features, characterized by expression of neuronal markers such as enolase 2 (ENO2), chromogranin A (CHGA) and synaptophysin (SYP). Currently, histopathological assessment combined with immunohistochemical detection in PCa tissues/serum levels of neuronal markers including SYP, NSE, CHGA and CD56 is used to monitor NED in CRPC patients. However, these markers are not sufficiently specific, highlighting the urgent need of novel molecular markers to assess emergence of NED in CRPC patients. We demonstrated that progression of CRPC-Adeno to CRPC-NE states is associated with a characteristic set of miRNA alterations. Here we validate a ‘novel miRNA classifier’ to robustly stratify CRPC-NE tumors from CRPC-Adenocarcinomas in independent clinical cohorts and deduce the optimal miRNA genes required for NEPC diagnosis. Methods: Human FFPE sections from CRPC-Adeno and CRPC-NE patients were microdissected, RNA were extracted and small RNA sequencing was performed using an Illumina NextSeq 500 platform. Sequencing data were analyzed and machine learning algorithms were applied (random forest machine learning technique with leave-pair-out cross validation (LPOCV)). The performance of classifier was measured using receiver operating characteristic (ROC) analysis with area under the curve (AUC) as the primary evaluation metric. Results: Unsupervised analysis of sequencing data by principal component analyses (PCA) revealed distinct clustering of the CRPC-NE tumors from CRPC-Adenocarcinomas based on miRNA profiles suggesting that miRNA profiles can be used to stratify these tumor types. We applied the ‘43-miRNA classifier data’ we deduced earlier to these validation cohorts. Our analyses showed that a set of 5 miRNAs of the classifier are important in distinguishing between CRPC-Adeno vs CRPC-NE with an AUC=0.8318. Conclusions: A ‘5- miRNA’ classifier was validated to be of significance in two independent validation cohorts employing clinical samples from two independent sites. We propose this miRNA classifier as an important tool for diagnosing NED in CRPC patients. Citation Format: Sharanjot Saini, Amritha Sreekumar, Jin Tae Lee, Nikhil Patel, Ashok Sharma. A microRNA classifier for predicting neuroendocrine differentiation in castration-resistant prostate cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1481.

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