Introduction Ginger ( Zingiber officinale ) has been one of the most commonly consumed herbal medicines for a long time to treat several common diseases. Antibacterial activity, antioxidant properties and many bioactive compounds in ginger have been identified previously, which could be used as an alternative method to treat many infectious diseases. Methods The current study evaluates ginger’s biochemical profile using qualitative and quantitative analysis and its bioactive potentials using antioxidant and antimicrobial assays against Streptococcus mutans and selective oral microbes. HPLC analysis was performed for the quantitative analysis. DPPH and disc diffusion assays were used for antioxidant and antimicrobial activities. The antimicrobial activity was checked against Streptococcus mutans, Enterococcus faecalis, Staphylococcus spp., and Lactobacillus spp. All solvents were removed by rotary evaporation before testing the dried extracts. Results The observed IC 50 value showed that distilled water extract exhibited the highest antioxidant activity (43.9), followed by ethanol extract (52.4), and the lowest activity was observed in n -butanol extract (91.2) and n -hexane (90.6). Different plant extracts have shown significant antibacterial activity ( p = 0.001) against each bacterium. The highest antibacterial activity against tested bacteria was observed in n -hexane, chloroform and ethanol extracts. In comparison, the ethyl acetate, n -butanol and water extracts showed low antibacterial activity. Conclusion This study emphasizes that Zingiber officinale ( Z. officinale ) against Gram-positive bacteria is an effective antimicrobial herb. Furthermore, it can be used as a potential natural source of antioxidants. Further studies on the toxicity analysis of ginger are recommended.

The proliferation of user-generated content on social media has made opinion mining an arduous job. As a microblogging platform, Twitter is being used to collect views about products, trends, and politics. Sentiment analysis is a technique used to analyze the attitude, emotions and opinions of different people towards anything, and it can be carried out on tweets to analyze public opinion on news, policies, social movements, and personalities. By employing Machine Learning models, opinion mining can be performed without reading tweets manually. Their results could assist governments and businesses in rolling out policies, products, and events. Seven Machine Learning models are implemented for emotion recognition by classifying tweets as happy or unhappy. With an in-depth comparative performance analysis, it was observed that proposed voting classifier(LR-SGD) with TF-IDF produces the most optimal result with 79% accuracy and 81% F1 score. To further validate stability of the proposed approach on two more datasets, one binary and other multi-class dataset and achieved robust results.

This study mathematically correlates incidence of cotton leaf curl virus (CLCuV), environmental factors (i.e., rainfall, humidity and temperature), and silverleaf whitefly population in agricultural system of Pakistan. It has been concluded that the disease is directly linked with rainfall and humidity. The third most influential factor in defining CLCuV incidence is the vector population, which is also strictly dependent upon monthly mean temperature of Pakistan. Developed mathematical interrelation is capable of predicting disease incidence of future months. Therefore, it will help agriculturists to control disease in agricultural areas of Pakistan. It is strongly advised on the basis of current research that vector population controlling practices should be immediately applied after detecting small elevations in mean monthly temperature.

The current investigation analyzes metabolites of Acetobacter aceti to explore chemical compounds responsible for the induction of vitamins in barley seeds. A bioactivity guided assay of bacterial extracts and chromatographic analyses of barley produce revealed 13 chemical compounds, which were subjected to principal component analysis (PCA). PCA determined four chemical compounds (i.e., quinolinic acid, pyridoxic acid, p-aminobenzoate, and α-oxobutanoic acid) highly associated with increased quantities of vitamins. Further experimentations confirmed that quinolinic acid and p-aminobenzoate were the most efficient vitamin inducers. The results indicated chloroform/ethanol (4:1) as the best solvent system for the extraction of active compounds from crude metabolites of A. aceti. Significant quantities of mevalonic acid were detected in the extracted fraction, indicating the possible induction of the isoprenoid pathway. Altogether, the current investigation broadens the frontiers in plant-microbe interaction.

The aim of present research was to investigate the relationship among religiosity, psychological distress and mental wellbeing. The current study was conducted on a purposive sample of undergraduates and graduates taken from University of Sargodha, Mianwali sub-campus and Chashma city (n = 100). The sample comprised of male (n = 50) and female (n = 50). In order to measure religiosity, psychological distress and mental wellbeing, English version of Centrality of Religiosity Scale (Huber & Huber, 2012), Kessler Psychological Distress Scale (Kessler et al., 2002), and The Warwick-Edinburgh Mental Well-being Scale (Tennant, Hiller, & Platt, 2007) were used respectively. Linear regression analysis portrayed that religiosity is significant positive predictor of mental wellbeing while religiosity appeared as a non-significant correlate of psychological distress. Data analysis also revealed that mental well-being is significant negative predictor of Psychological distress. Moreover, the analysis revealed that the mean scores for the females significantly higher on religiosity and psychological distress. While non-significant gender differences were found in mental wellbeing.

Acetobacter aceti was successfully used to induce transcriptional analysis, plant biochemical profile and nutritional contents in barley. Association of barley and microbial strain AC8 was reported best combination among other eight microbial strains of Bacillus in this study. AC8 microbial strain was identified as A. aceti from Fungal Culture Bank, Institute of Agricultural Science, University of the Punjab, Lahore, Pakistan. Different strains of A. aceti i.e., AC1, AC2, AC3… AC8 were analyzed as plant inducers and AC8 was screened out as best inducer in barley. It induced highest quantities of plant biochemical (i.e., phytosterols, phenolics, alkaloids and terpenoids) in barley. Current study revealed that among eight microbial strains AC8 had maximum potential to increase ascorbic acid, panthothenic acid, pyridoxine, thiamine and riboflavin in barley than other microbial strains. AC8 screened out among other microbial strains on the basis of its high vitamins induction potential. AC3 plus AC6 were reported second in the recorded list although other strains had a chronological reduction in vitamins as AC2>AC7>AC4>AC5 and AC1. Further evaluation of AC8 was done to check its efficiency for biochemicals, nutritional and isozyme contents induction in barley. Statistical analysis was performed using ANOVA and DMRT through DSAASTAT.

The present study examined the impact of perceived social support and gender on creativity level in a sample of university undergraduates. The present study was conducted on undergraduates taken from University of Sargodha through random sampling (N = 177; M.A/M.Sc, II, and IV). Sample was comprised of boys (n = 74) and girls (n = 103). Urdu translated Interpersonal Support Evaluation List (Yousaf & Ghayas, 2003) was used to measure perceived social support; while, creativity was assessed through Urdu translated Torrance Test of Creative Thinking (Shaheen, 2010). Analyses portrayed that perceived social support was significant and positive predictor of creativity. Gender difference was not found in perceived social support. Analysis revealed that girls were significantly high on creativity as compared to boys. The t-test analysis revealed that girl's scores were significantly high on fluency, abstractness of title, resistance to premature closure, abstractness of title, originality and fantasy than boys. While, boys scored high on internal visualization as compared to girls.Non-significant gender difference were found in elaboration, movement or action, storytelling articulateness, humor, expressiveness of title, colorfulness of imagery, unusual visualization, synthesis of lines, extending or breaking boundaries, synthesis of incomplete figure, richness of imagery. Limitation and suggestions for future studies have been discussed.

Background: Hepatitis C virus (HCV) is the major cause of liver cirrhosis, chronic liver disease, and hepatocellular carcinoma. More than 10 million individuals are living with HCV infection in Pakistan. Due to unawareness, very little information is known about HCV genotype occurrence in Punjab, the largest province of Pakistan. Identification of HCV genotype is very important for HCV treatment because different genotypes of HCV respond differently to antiviral therapy.Objective: The purpose of this research was to determine the distribution frequency of different HCV genotypes in the Punjab province and to demonstrate the distribution pattern of HCV genotypes in different age groups and sexes.Materials and Methods: In this study, we performed HCV genotyping of 3692 samples collected from different sites of the Punjab province, Pakistan. Among 3692 samples, 1755 (47.5%) were males and 1937 (52.4%) were females.Results: A total of 3692 samples were subjected to HCV genotyping and 2977 (81%) patients were genotyped successfully, whereas 715 (19%) patients were found to be HCV not detected. Our study demonstrated that among typeable genotypes, 3a constituted 2582 (69.9%) patients followed by 1a (n = 280) 7.5%, 1b (n = 64) 1.7%, 2a (n = 6) 0.16%, genotype 4 (n = 10) 0.27%, 3+4 (n = 2) 0.56%, 1a+2a (n = 11) 0.29%, 1b+2a (n = 1) 0.02%, 1a+1b (n = 1) 0.02%, and 1a+1b+3 (n = 1) 0.02% patients. HCV genotype distribution was evaluated gender wise and in different age groups like 0-12, 13-18, 19-59, and >60 years. All the HCV genotypes were equally distributed among men and women. The most affected age group was 19-59 years as compared to other age groups. Conclusion:The most frequently distributed HCV genotype in Punjab was found to be genotype 3a followed by genotype 1a, and only 0.94% of infected patients had a mixed genotype infection. Genotype 1a was found to be increasing significantly in the studied population. With these results, it can be assumed that genotype 3a may be replaced by genotype 1a with the passage of time. If this happens, this situation will be challenging in terms of antiviral therapy.