Browsing by Author "Aqsa Fayyaz"

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    GC-MS analysis of methanolic extracts of Alcea Setosa (leaves and flowers)
    (UMT Lahore, 2019) Aqsa Fayyaz
    Plants are the traditional sources for many chemicals used as pharmaceutical biochemical in many countries. Alcea setosa is an ornamental plant which belongs to flowering plant family Malvaceae and commonly known as bristly hollyhock. The flowers and leaves of Alcea setosa are used in treatment of many diseases such as inflammation, stomach ailment and breathing illness. The major aim of study was to investigate the bioactive compounds of Alcea setosa flowers and leaves by GC-MS analysis. The chemical composition of the Methanolic extract of Alcea setosa parts was done by standard protocol using the equipment Clarus 500 Perkin – elmer (Auto system XL) Gas Chromatograph- Mass Spectroscopy. GC-MS analysis of the flower extract revealed the existence of seven compounds after matching the mass spectra with NIST library. While eleven compounds were identified from leaves extract. The major compounds present in flower Methanolic extract were 2-O-(2,2dimethylpropyl) 1-O-(4-methylpentyl) oxalate, 2-ethylhexyl nonyl sulfite, 2,3epoxyhexanol and N-(5-chloro-2-hydroxyphenyl) dodecanamide. The vital compounds present in leave extract were Spathulenol, Octacosane, Hexanedioic Acid, Dioctyl Ester and Heneicosanoic Acid, Methyl Ester. The components of extracts of Alcea setosa could be responsible for many medicinal and antimicrobial activities.
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    Life stressors, interpersonal difficulties, sleep quality and eating problems in hostelite and day scholar university students
    (UMT, Lahore, 2025) Maila Sadiq; Aqsa Fayyaz; Musa Kaleem
    The research was conducted to find out the association of life stressors, interpersonal difficulties, sleep quality and eating habits among hostilite and day scholars in university students. The study used a cross-sectional correlational and 300 university students aged from 19-25 years old were selected through convenience sampling. Four scales were used to collect data; Eating Problem Scale (Naeem et al., 2022), Sleep Quality Scale Yi, Shin, and Shin (2006), Interpersonal Difficulties Scale (Saleem et al., 2014) and Life Stressors Scale (Naeem & Saleem, 2024), and a demographic form was given to participants. Descriptive statistics, correlation analysis, regression analysis, t-tests, and ANOVA were used to examine association between the study variables in the data analysis, which was conducted using SPSS Version 25. The results indicated that there was a significant association between life stressors, interpersonal difficulties, sleep quality and eating problems. Correlation analysis showed that eating problems are positively correlated with negative sleep quality, interpersonal difficulties and life stressors, whereas, positive sleep quality is negatively correlated with life stressors, whereas negative sleep quality is positively associated with interpersonal difficulties and life stressors. Furthermore, Regression analysis suggested that interpersonal difficulties and life stressors are strongly predicting the eating problems in university students. It is also indicated that positive sleep quality also significantly predicting eating problems, whereas, negative sleep quality and other demographics did not have any impact on eating problems.