Chiang Mai Journal of Science

     The increasing demand for biopolymers in the food industry has increased interest in using alternative resources. Kefiran, which is produced by microorganisms found in kefir grains, is a versatile exopolysaccharide (EPS) that can form gel, an important biopolymer for the food manufacturing. In this study, kefiran extracted by using an EPS isolation method was characterized by rheological analysis according to power law model and determination of functional properties and texture profile analysis. The effects on apparent viscosity (η_a) and flow properties of kefiran concentrations ranging from 1.1 to 3.1% (w/v) were investigated. The results indicated that kefiran solutions at low concentrations exhibited behavior close to Newtonian, whereas at higher concentrations, they showed pseudoplastic (shear-thinning) behavior. This shear-thinning behavior is attributed to hydrogen bonding between hydroxyl groups and water molecules, which contributes to the formation of an entangled polymer network. The results showed that isolated kefiran at a high degree of purity (93.0%) was able to possess good texture profile properties and with a high degree of water holding capacity (WHC) (90.3%), and bloom strength value (53.0 g). Kefiran had a gelling temperature of 14 °C. This study confirms that extracted polysaccharide can be especially used as a gelling agent in fermented dairy products and can also be successfully used as a texture improver biopolymer in food systems.

     Prostate cancer antigen 3 (PCA3) screening has the potential to detect prostate cancer early and assess the efficacy of surgery or radiation therapy. Nanotechnology integration in biosensor development enables effective targeted biomarker detection. Diagnosis of prostate cancer via PCA3 biomarker detection is promising to be much more efficient than with the prostatic-specific antigens currently used. In this study, we developed a GO/PCA3 marker on a surface acoustic wave (SAW) biosensor. The GO-modified SAW biosensor was prepared by conjugating GO onto L-Cysteine on the SAW chip surface. Afterward, the PCA3 capture probe was immobilized on the GO surface, and characterization was performed with XRD, SEM, AFM, and FTIR techniques. This result confirmed the successful deposition of GO, increasing the number of binding sites for interaction between GO and PCA3 capture probe through enhanced sensor surface area. The effects of EDC-NHS activation time, capture probe concentration, and incubation time were optimized. The sensor has a wide linear response that extends from 1.00 fM to 1.00 μM of PCA3 target, and the limit of detection (LOD) is 0.27 nM. These characteristics make the SAW device a promising candidate for various clinical and rapid detection applications.

     This study aims to investigate water quality and pollution source identification in the Xilin River Basin using Environmental Science and Engineering terminology. The study employs Water Quality Index (WQI), Principal Component Analysis (PCA), Factor Analysis (FA), Absolute Principal Component Scores Multiple Linear Regression (APCS-MLR), and Positive Matrix Factorization (PMF). WQI results indicate values of 96.55, 138.36, and 115.47 during normal season (NS), wet season (WS), and dry season (DS) respectively, with NS showing better water quality compared to WS and DS. PCA and FA identified four key factors explaining 80.08% to 83.55% of the total variance. APCS-MLR modeling results indicate that agricultural and livestock farming pollution sources (ALS), as well as industrial wastewater and urban domestic pollution sources (IUS), are the primary contributors to river water pollution. PMF simulations reveal slight variations in pollution sources across each season. Comparing the R2 values of APCS-MLR and PMF simulations, with averages of 0.80 and 0.67 respectively, indicates that APCS-MLR demonstrates higher stability and better simulation results.