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Impact of elateriospermum tapos supplementation on leptin and hypothalamic signaling in female offspring of high-fat diet-induced obese
No full textPurpose: The central nervous system plays a crucial role in regulating food intake and energy expenditure to maintain energy homeostasis in the body. With rising obesity rates, alternative therapeutic strategies, including herbal-based interventions, are gaining attention. Elateriospermum tapos a plant that rich in flavonoids, has shown potential supporting weight reduction. This study aimed to evaluate the effects of E. tapos seed and shell supplementation on the hypothalamic feeding pathway in obese female rats and their offspring. Methods: Thirty adult female Sprague-Dawley rats were used in this study. Obesity was induced in 24 rats via high-fat diet (HFD) for five weeks. Six rats were maintained on a normal diet as the control group (DCG). The obese rats were then divided into four groups: negative control (DNG, HFD only), positive control (DPG, HFD + orlistat 200 mg/kg), treatment 1 (DTX1, HFD + E. tapos seed 200 mg/kg), and treatment 2 (DTX2, HFD + E. tapos shell 200 mg/kg). Treatments were administered daily for six weeks before mating. On postnatal day 21 (PND21), blood and hypothalamus samples were collected from female rats and their female offspring. Plasma leptin levels were measured using ELISA, and expression of leptin receptor (Obr), proopiomelanocortin (POMC), and neuropeptide Y (NPY) in the hypothalamus was assessed by western blotting. Results: DTX2 and offspring (OTX2) groups showed significantly (P< 0.05) lower levels of leptin. Western blot results indicate Obr, POMC and NPY protein significantly (P< 0.05) higher expression in DNG and ONG compared to the other groups. Conclusion: In conclusion, the E. tapos shell significantly reduced maternal obesity in female offspring at PND21 compared to its seed
Investigating the kinetics of tannin removal in Sorghum [Sorghum bicolor (L.) Moench] grains through a soaking process
No full textSorghum (Sorghum bicolor (L.) Moench) grains contain tannins that significantly affect their nutritional value and potential utilizations in food product development. This study aims to investigate the kinetics of tannin removal during the soaking process and to optimize the operating condition. To achieve the goals, sorghum grains were subjected to various soaking durations, temperatures, and soaking solution concentrations. The soaking process employed potassium hydroxide and calcium hydroxide solutions at concentrations ranging from 0.05% to 0.15%; soaking temperatures were varied at 30°C, 40°C, and 50°C. Soaking was performed for 8 hours, with samples withdrawn every hour. The dissolved tannin was analyzed for its concentration, and the data were fitted to first-order rate equation kinetic models to determine the rate constants associated with tannin reduction. This study provides valuable insights into the soaking kinetics of sorghum grains, highlighting the potential for improving sorghum-based products’ nutritional quality through optimized soaking treatments. From the investigation results, the type and concentration of the solvent, as well as the soaking temperature, affected the tannins removal rate from sorghum grains. The highest dissolution rate and constant (k) were obtained during soaking in 0.15% calcium hydroxide solution at 50°C, with values of 0.436 ppm. min⁻¹ and 0.00616 min⁻¹, respectively. The average percentage error of the first-order reaction kinetics model was below 0.2%, which suggested its high suitability for application in the soaking process of sorghum grains using an alkaline solvent. The findings can guide food processors in developing more efficient methods for tannin reduction, enhancing the utilization of sorghum as both a staple food and food ingredient
Comparative analysis of microbial diversity in various kombucha starter cultures in Malaysia using the random amplified polymorphic DNA (RAPD) approach
No full textKombucha is sweetened black tea fermented with symbiotic culture of bacteria and yeasts (SCOBY) and has been widely consumed for its purported health benefits. The microbial consortium in kombucha is dominated by yeasts such as Brettanomyces sp. and Zygosaccharomyces sp., as well as acetic acid bacteria (AAB), Komagataeibacter sp. and Acetobacter sp. However, the source of SCOBY and substrates used may affect the microbial diversity as well as the biochemical, and flavour of the kombucha. Identifying the microbial population is important as the use of undefined starter cultures may lead to variable metabolite production and increase the risk of food pathogen contamination which can pose harm to human health. This study aims to isolate the microbes from kombucha in Malaysia for the future development of a new starter culture with specific species for the safe consumption of kombucha. Briefly, a total of 100 colonies were isolated from nine kombucha starter cultures with selective culture plates. Differences in colony morphology were observed based on their colours, surface texture, elevation, and margin. Their phenotypic morphology and genetic diversity were screened using microscopic examination, coupled with a catalase test and random amplified polymorphic DNA (RAPD), respectively. Based on the data, 51% of the isolates showed yeasts morphology under microscopic examination, while the rest were bacteria. Additionally, 55.79% of the isolates showed distinct banding profile patterns in the RAPD assessments. In conclusion, the data of this study shows that there is a diverse microbial consortium in different starter cultures of kombucha from Malaysia, mainly predominated by Gram-negative AAB and Gram-positive yeasts. Identification at the species level is to be conducted in the future. By understanding the microbiota diversity in kombucha, it contributes to the development and production of a safe functional drink
Water immersion behavior of CNF/GNP reinforced green epoxy hybrid nanocomposites
No full textEnvironmental challenges have prompted the development of sustainable materials such as nanocomposites. However, these composites exhibit inadequate water resistance, leading to suboptimal performance. This study investigates the impact of water absorption on the properties of green epoxy nanocomposites reinforced with low loading of cellulose nanofibrils (CNF) and graphene nanoplatelets (GNP) at (0.1, 0.25, and 0.5) wt%. After 15 days of water immersion, contact angle tests showed that CNF increased hydrophilicity 80.26°, while GNP improved water resistance 90.04°. The presence of nanoparticles was confirmed by XRD and Raman spectra. Micrographs from FESEM confirmed the role of CNF in making nanocomposite hydrophilic due to water molecule penetration through capillary flow due to hydrolytic breakdown. Mechanical tests indicated a 46.6 % increase in hardness for water-absorbed hybrid nanocomposites, with GNP enhancing impact resistance, tensile strength ranging from 400 to 600 MPa and flexural strength between 600 and 800 MPa. Thermally, the composites offer conductivity values of 10–30 W/m·K, supporting efficient heat dissipation, and maintain structural integrity at temperatures up to 300 °C due to the synergistic effects of CNF and GNP. The GNP enhances interfacial bonding with the epoxy matrix through π–π stacking and van der Waals forces. Its high aspect ratio and 2D structure improve stress transfer, load distribution, and crack resistance. Additionally, GNP forms continuous thermal pathways, boosting thermal conductivity and heat dissipation. This study emphasizes that filler dispersion and component interaction play vital roles in defining density performance and water absorption and highlights the role of filler type and dispersion in controlling moisture behavior, offering the potential for moisture-resistant composites in electronics applications
Exploring the effective parameters on the photocatalytic activity of TiO2 nanoparticles
No full textThe growing challenge of environmental pollution has driven intense research into advanced materials for pollutant degradation. Among them, titanium dioxide (TiO2) nanoparticles stand out for their efficiency in the photocatalytic degradation of organic pollutants, offering a promising solution for environmental remediation. In this study, TiO2 nanoparticles were synthesized and characterized to measure their structural, morphological, and optical properties, which directly influence their photocatalytic degradation of methylene blue (MB), a model organic dye. TiO2 nanoparticles were synthesized via the sol-gel method, enabling fine-tuned control over their crystallization and purity, and subsequently characterized using UV–Vis spectroscopy, field emission scanning electron microscopy (FESEM), Raman spectroscopy, Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD) and a particle size analyzer. The photocatalytic activity was evaluated by measuring the degradation rate of MB under UV light irradiation. One hour of sonication was employed after the optimization study to enhance the dispersion of the nanoparticles, resulting in a more uniform size and shape for further characterization. Raman spectroscopy confirmed the presence of both anatase and rutile phases, with peaks at 386 cm−1 and 516 cm−1 indicating anatase, while the rutile phase was identified by peaks at 451 cm−1 and 615 cm−1. Fourier Transform Infrared (FTIR) spectroscopy confirmed characteristic bond formations at 1643 cm−1 (Ti-OH) and 3338 cm−1(O–H). The degradation analysis was performed via UV–Vis spectrophotometer, which demonstrated a decrease in absorbance at λmax of 662 nm within 240 min. Additionally, UV–Vis spectroscopy was employed to determine the band gap energy of TiO2, calculated to be approximately 3.19 eV. Morphological analysis using FESEM revealed flake-like structures with an average size distribution of 52 nm, consistent with the nanoscale distribution observed using the particle analyzer and UV–Vis spectroscopy. In summary, this study successfully synthesized TiO2 nanoparticles with a mixed crystalline phase, achieving about 96.6 % photocatalytic efficiency for MB degradation, highlighting their potential for environmental treatment applications
UPM raikan ibu bapa hantar anak belajar
No full textIbu bapa pelajar baharu Universiti Putra Malaysia (UPM) mengucapkan terima kasih kepada pihak pengurusan Masjid UPM yang menyediakan kemudahan istirahat sempena majlis pendaftaran pelajar baharu bagi sesi akademik 2024/2025 yang berlangsung dari 4 hingga 6 Oktober
Lumpuh separuh badan, tidak halang Clarissa lanjut pengajian
No full textSERDANG, 5 Oktober- Fizikal cacat dan kehidupan seharian bergantung kepada kerusi roda tidak menghalang atlet memanah Para Sukma XXI Sarawak 2024 memulakan pengajian sebagai pelajar Bachelor Pentadbiran Perniagaan dengan Kepujian di Universiti Putra Malaysia (UPM)
Does frontline employee friendliness during service delivery still matter in the current era? Revisiting its dimensionality effects on brand outcome
No full textRecently, digitalization has caused service providers to focus on service delivery excellence to build robust brands. Hence, the purpose of this study is to revisit the effects of four dimensions of frontline employee friendliness on brand identification and repurchase intent. This study utilized a structured online questionnaire from a sample of full-service restaurant customers in Malaysia. The results indicate that the behaviours of approachable, humorous, conversational and informal influence repeat purchase intention. However, only dimensions of conversational and humorous behaviours influence brand identification. Further findings also demonstrate that brand identification plays several important mediating roles in predicting repurchase intent. This study advances brand management literature by being the pioneer among scholars in separately examining the impacts of a four-factor model of frontline employee friendliness on brand outcome. This study provides novel insights into the mediating roles of brand identification on the link between each behaviour of frontline employee friendliness and repat purchase intention. This research is one of the few studies that enriches stimulus–organism–response (SOR) theory to explain consecutive relationships and underlying mechanisms among factors investigated. This study also provides additional insights in guiding service providers to leverage effective practices and management of frontline employee friendliness to achieve impactful performance on branding and business profitability
A hybrid chromaticity-morphological machine learning model to overcome the limit of detecting newcastle disease in experimentally infected chicken within 36 h
No full textThe nexus between animal and human health is crucial in upholding global health. Humans are at risk of food security due to fatal infections associated with the Newcastle disease virus (NDV), resulting in severe disease outbreaks. This work reports on the early detection of experimentally NDV-infected chickens to prevent such catastrophic events. Image processing techniques were employed to extract the chromaticity and morphological features of the chicken comb and standing posture. The changes in these features across different stages of symptom severity, indicated by the post-infection period in hours, were examined through statistical and Spearman coefficient correlation analysis. Various hybrid chromaticity-morphology machine learning (HCMML) classifier models, including Logistic Regression, Support Vector Machine (SVM) with different kernels, K-Nearest Neighbour (KNN), Decision Tree, and Artificial Neural Network (ANN), were trained using selected feature variables and different variation of datasets to detect infected chickens. The statistical analysis on individual features demonstrates the necessity of HCMML models to predict infected chicken with a reasonably high accuracy. Based on the coefficient correlation analysis, the chromaticity features demonstrate a higher correlation to the chickens with NDV infection than the morphological features. These findings highlight the importance of extracting chromaticity features in predicting infected chicken, especially at the early phase of infection. Based on the HCMML models result, SVM with Polynomial kernel achieved a test accuracy of 82·39 % with 79·00 % validation accuracy at 36 h post-infection after feature optimization and > 95·00 % test accuracy after 96 h post-infection. This work demonstrates a promising methodology in developing machine learning algorithm using hybrid chromaticity-morphological features for early detection of virus-infected chickens, contributing to the goal of a sustainable and healthier planet
Effect of parental support on learning engagement in mathematics online learning environment: the mediating role of online self-regulated learning strategies
Get PDFThis study examines the effects of parental support on learning engagement and the mediating roles of self-regulated learning (SRL) in mathematics online learning environments. A sample of 112 undergraduate students from the mathematics departments of two public universities in Malaysia participated in the study. We analyzed the data using descriptive analysis and partial least squares structural equation modeling (PLS-SEM), and the study findings indicate that parental support significantly predicts online self-regulated learning (OSRL). In addition, OSRL is a significant predictor of students’ engagement. The results also suggest that OSRL fully mediates the relationship between parental support and learning engagement. However, parental support had no significant effect on learning engagement. This study highlights the importance of considering parental support and fostering OSRL strategies to promote learning engagement among mathematics higher learning institution students