Epidemiological modeling of COVID-19 data with Advanced statistical inference based on Type-II progressive censoring.

This research proposes the Kavya-Manoharan Unit Exponentiated Half Logistic (KM-UEHL) distribution as a novel tool for epidemiological modeling of COVID-19 data. Specifically designed to analyze data constrained to the unit interval, the KM-UEHL distribution builds upon the unit exponentiated half logistic model, making it suitable for various data from COVID-19. The paper emphasizes the KM-UEHL distribution's adaptability by examining its density and hazard rate functions. Its effectiveness is demonstrated in handling the diverse nature of COVID-19 data through these functions. Key characteristics like moments, quantile functions, stress-strength reliability, and entropy measures are also comprehensively investigated. Furthermore, the KM-UEHL distribution is employed for forecasting future COVID-19 data under a progressive Type-II censoring scheme, which acknowledges the time-dependent nature of data collection during outbreaks. The paper presents various methods for constructing prediction intervals for future-order statistics, including maximum likelihood estimation, Bayesian inference (both point and interval estimates), and upper-order statistics approaches. The Metropolis-Hastings and Gibbs sampling procedures are combined to create the Markov chain Monte Carlo simulations because it is mathematically difficult to acquire closed-form solutions for the posterior density function in the Bayesian framework. The theoretical developments are validated with numerical simulations, and the practical applicability of the KM-UEHL distribution is showcased using real-world COVID-19 datasets.

Different estimation techniques and data analysis for constant-partially accelerated life tests for power half-logistic distribution.

Partial accelerated life tests (PALTs) are employed when the results of accelerated life testing cannot be extended to usage circumstances. This work discusses the challenge of different estimating strategies in constant PALT with complete data. The lifetime distribution of the test item is assumed to follow the power half-logistic distribution. Several classical and Bayesian estimation techniques are presented to estimate the distribution parameters and the acceleration factor of the power half-logistic distribution. These techniques include Anderson-Darling, maximum likelihood, Cramér von-Mises, ordinary least squares, weighted least squares, maximum product of spacing and Bayesian. Additionally, the Bayesian credible intervals and approximate confidence intervals are constructed. A simulation study is provided to compare the outcomes of various estimation methods that have been provided based on mean squared error, absolute average bias, length of intervals, and coverage probabilities. This study shows that the maximum product of spacing estimation is the most effective strategy among the options in most circumstances when adopting the minimum values for MSE and average bias. In the majority of situations, Bayesian method outperforms other methods when taking into account both MSE and average bias values. When comparing approximation confidence intervals to Bayesian credible intervals, the latter have a higher coverage probability and smaller average length. Two authentic data sets are examined for illustrative purposes. Examining the two real data sets shows that the value methods are workable and applicable to certain engineering-related problems.

Precision enhancement in variance estimation for complex environmental populations using adaptive cluster sampling.

Estimating dispersion in populations that are extremely rare, hidden, geographically clustered, and hard to access is a well-known challenge. Conventional sampling approaches tend to overestimate the variance, even though it should be genuinely reduced. In this environment, adaptive cluster sampling is considered to be the most efficient sampling technique as it provides generally a lower variance than the other conventional probability sampling designs for the assessment of rare and geographically gathered population parameters like mean, total, variance, etc. The use of auxiliary data is very common to obtain the precise estimates of the estimators by taking advantage of the correlation between the survey variable and the auxiliary data. In this article, we introduced a generalized estimator for estimating the variance of populations that are rare, hidden, geographically clustered and hard-to-reached. The proposed estimator leverages both actual and transformed auxiliary data through adaptive cluster sampling. The expressions of approximate bias and mean square error of the proposed estimator are derived up to the first-order approximation using Taylor expansion. Some special cases are also obtained using the known parameters associated with the auxiliary variable. The proposed class of estimators is compared with available estimators using simulation and real data applications.

Estimation methods based on ranked set sampling for the power logarithmic distribution.

The sample strategy employed in statistical parameter estimation issues has a major impact on the accuracy of the parameter estimates. Ranked set sampling (RSS) is a highly helpful technique for gathering data when it is difficult or impossible to quantify the units in a population. A bounded power logarithmic distribution (PLD) has been proposed recently, and it may be used to describe many real-world bounded data sets. In the current work, the three parameters of the PLD are estimated using the RSS technique. A number of conventional estimators using maximum likelihood, minimum spacing absolute log-distance, minimum spacing square distance, Anderson-Darling, minimum spacing absolute distance, maximum product of spacings, least squares, Cramer-von-Mises, minimum spacing square log distance, and minimum spacing Linex distance are investigated. The different estimates via RSS are compared with their simple random sampling (SRS) counterparts. We found that the maximum product spacing estimate appears to be the best option based on our simulation results for the SRS and RSS data sets. Estimates generated from SRS data sets are less efficient than those derived from RSS data sets. The usefulness of the RSS estimators is also investigated by means of a real data example.

Application of gelatin-based zinc oxide nanoparticles bionanocomposite coatings to control Listeria monocytogenes in Talaga cheese and camel meat during refrigerated storage.

Listeria monocytogenes is a concerning foodborne pathogen incriminated in soft cheese and meat-related outbreaks, highlighting the significance of applying alternative techniques to control its growth in food. In the current study, eco-friendly zinc oxide nanoparticles (ZnO-NPs) were synthesized using Rosmarinus officinalis, Punica granatum, and Origanum marjoram extracts individually. The antimicrobial efficacy of the prepared ZnO-NPs against L. monocytogenes was assessed using the agar well diffusion technique. Data indicated that ZnO-NPs prepared using Origanum marjoram were the most effective; therefore, they were used for the preparation of gelatin-based bionanocomposite coatings. Furthermore, the antimicrobial efficacy of the prepared gelatin-based bionanocomposite coatings containing eco-friendly ZnO-NPs was evaluated against L. monocytogenes in Talaga cheese (an Egyptian soft cheese) and camel meat during refrigerated storage at 4 ± 1 oC. Talaga cheese and camel meat were inoculated with L. monocytogenes, then coated with gelatin (G), gelatin with ZnO-NPs 1% (G/ZnO-NPs 1%), and gelatin with ZnO-NPs 2% (G/ZnO-NPs 2%). Microbiological examination showed that the G/ZnO-NPs 2% coating reduced L. monocytogenes count in the coated Talaga cheese and camel meat by 2.76 ± 0.19 and 2.36 ± 0.51 log CFU/g, respectively, by the end of the storage period. Moreover, G/ZnO-NPs coatings controlled pH changes, reduced water losses, and improved the sensory characteristics of Talaga cheese and camel meat, thereby extending their shelf life. The obtained results from this study indicate that the application of gelatin/ZnO-NPs 2% bionanocomposite coating could be used in the food industry to control L. monocytogenes growth, improve quality, and extend the shelf life of Talaga cheese and camel meat.

The Role of Musculoskeletal Training During Return to Performance Following Relative Energy Deficiency in Sport.

BACKGROUND: Relative energy deficiency in sport (REDs) is a condition that is associated with negative health and performance outcomes in athletes. Insufficient energy intake relative to exercise energy expenditure, resulting in low energy availability, is the underlying cause, which triggers numerous adverse physiological consequences including several associated with musculoskeletal (MSK) health and neuromuscular performance. PURPOSE: This commentary aims to (1) discuss the health and performance implications of REDs on the skeletal and neuromuscular systems and (2) examine the role that MSK training (ie, strength and plyometric training) during treatment and return to performance following REDs might have on health and performance in athletes, with practical guidelines provided. CONCLUSIONS: REDs is associated with decreases in markers of bone health, lean body mass, maximal and explosive strength, and muscle work capacity. Restoration of optimal energy availability, mainly through an increase in energy intake, is the primary goal during the initial treatment of REDs with a return to performance managed by a multidisciplinary team of specialists. MSK training is an effective nonpharmacological component of treatment for REDs, which offers multiple long-term health and performance benefits, assuming the energy needs of athletes are met as part of their recovery. Supervised, prescribed, and gradually progressive MSK training should include a combination of resistance training and high-impact plyometric-based exercise to promote MSK adaptations, with an initial focus on achieving movement competency. Progressing MSK training exercises to higher intensities will have the greatest effects on bone health and strength performance in the long term.

Effect of thyme, ginger, and their nano-particles on growth performance, carcass characteristics, meat quality and intestinal bacteriology of broiler chickens.

This study was conducted to evaluate the effects of thyme, ginger, and their nano-particles, as alternatives to antibiotic growth promotors (AGP), on productive performance, carcass traits, meat quality and gut health of broiler chickens. A total of 270 one-day-old broiler chicks were randomly distributed into 6 groups, each consisting of 3 replicates (n = 15 chicks/replicate). The birds in group 1 were fed the control diet which contained neither antibiotic growth promotors nor phytogenic feed additives (PFA). Birds in group 2 were fed diets containing 0.05% of AGP (Bacitracin methylene disalicylate). Chicks in group 3 and 4 were fed diets supplemented with 1.0% of thyme and ginger, respectively, whereas birds in group 5 and 6 were offered diets including 0.10% of nano-thyme and nano-ginger, respectively. The experiment lasted for 35 days. It was found that thyme and ginger with their nano-products, like the antibiotic, improved the body weight, weight gain and feed conversion rate of birds. The effect of ginger and nano-ginger on body weight and weight gain was greater than other treatments. During the overall feeding period, the feed cost of production was the highest in antibiotic group, but was the lowest in ginger and nano-ginger treatments. There was no effect of dietary treatments on carcass yield or organs weight except bursa of Fabricius and abdominal fat. Thyme, ginger and their nano-composites increased the weight of bursa and reduced the abdominal fat amount. The phytogenic additives and their nano-particles improved the colour, water holding capacity, and flavor of meat. Moreover, these additives reduced the total intestinal bacterial count as well as the total aerobic mesophilic count of meat. The effect of PFA and their nano-particles on the bacterial count was similar to that of antibiotic. In conclusion, thyme and ginger with their nano- particles can be considered as promising agents in feeding of broilers to improve the growth performance, gut health and meat quality. Moreover, these additives can be used as alternatives to AGP to overcome its health hazards and the high cost. The nanotechnology of herbal plants enables them to be added in smaller amounts in poultry diets with producing the same effect of raw ingredients, and this could be due to the higher bioavailability.

Rapid and sensitive in situ detection of heavy metals in fish using enhanced Raman spectroscopy.

Heavy metals have been widely applied in industry, agriculture, and other fields because of their outstanding physics and chemistry properties. They are non-degradable even at low concentrations, causing irreversible harm to the human and other organisms. Therefore, it is of great significance to develop high accuracy and sensitivity as well as stable techniques for their detection. Raman scattering spectroscopy and atomic absorption spectrophotometer (AAS) were used parallelly to detect heavy metal ions such as Hg, Cd, and Pb of different concentrations in fish samples. The concentration of the heavy metals is varied from 5 ppb to 5 ppm. Despite the satisfactory recoveries of AAS, their drawbacks are imperative for an alternative technique. In Raman scattering spectroscopy, the intensities and areas of the characteristic peaks are increased with increasing the concentration of the heavy metals. For Hg concentration ≥ 1 ppm, a slight shift is observed in the peak position. The obtained values of peak intensity and peak area are modeled according to Elvoich, Pseudo-first order, Pseudo-second order, and asymptotic1 exponential model. The best modeling was obtained using the Elovich model followed by the asymptotic1 exponential model. The introduced Raman spectroscopy-based approach for on-site detection of trace heavy metal pollution in fish samples is rapid, low-cost, and simple to implement, increasing its visibility in food safety and industrial applications.

A probe of new molecularly imprinted solid-phase extraction coupled with HPLC-DAD and atomic absorption spectrophotometry for quantification of tetracycline HCl, metronidazole and bismuth subcitrate in combination with their official impurities: Application in dosage form and human plasma.

The integration of molecular imprinting technique with chromatographic one has a great impact on the assay's selectivity and sensitivity. Herein, a molecularly imprinted solid-phase extraction associated with high performance liquid chromatography (MISPE-HPLC) was employed for simultaneous determination of the co-formulated drugs; tetracycline hydrochloride (TET) and metronidazole (MET), in plasma and in their anti-H-pylori drug for the first time. Two sorts of molecularly imprinted polymers (MIPs) were fabricated using TET and MET as the template molecules, while ethylene glycol dimethacrylate and methacrylic acid were used as a cross-linker and a monomer, respectively. The synthesized MIPs were identified using different techniques. The adsorption-desorption capability of each template was investigated towards its corresponding MIP. The extraction conditions of MISPE was optimized with respect to TET/MIP and MET/MIP sorbent. Bismuth subcitrate (BSC), the third co-formulated drug was analyzed in spiked human plasma using an atomic absorption spectrometric (AAS) method. The performance of the developed methods was assured as per ICH guidelines for analyzing the studied drugs in their pharmaceutical dosage form along with two of their official impurities. In addition, bioanalytical method validation was conducted where linearity was achieved at 2.0-40.0 µg mL-1, 2.0-40.0 µg mL-1 and 5.0-80.0 µg mL-1 for TET, MET and BSC, respectively.

A novel weighted family of probability distributions with applications to world natural gas, oil, and gold reserves.

Recent innovations have focused on the creation of new families that extend well-known distributions while providing a huge amount of practical flexibility for data modeling. Weighted distributions offer an effective approach for addressing model building and data interpretation problems. The main objective of this work is to provide a novel family based on a weighted generator called the length-biased truncated Lomax-generated (LBTLo-G) family. Discussions are held about the characteristics of the LBTLo-G family, including expressions for the probability density function, moments, and incomplete moments. In addition, different measures of uncertainty are determined. We provide four new sub-distributions and investigated their functionalities. Subsequently, a statistical analysis is given. The LBTLo-G family's parameter estimation is carried out using the maximum likelihood technique on the basis of full and censored samples. Simulation research is conducted to determine the parameters of the LBTLo Weibull (LBTLoW) distribution. Four genuine data sets are considered to illustrate the fitting behavior of the LBTLoW distribution. In each case, the application outcomes demonstrate that the LBTLoW distribution can, in fact, fit the data more accurately than other rival distributions.

Application of multivariate chemometrics tools for spectrophotometric determination of naphazoline HCl, pheniramine maleate and three official impurities in their eye drops.

This work is concerned with exploiting the power of chemometrics in the assay and purity determination of naphazoline HCl (NZ) and pheniramine maleate (PN) in their combined eye drops. Partial least squares (PLS) and artificial neural network (ANN) were the chosen models for that purpose where three selected official impurities, namely; NZ impurity B and PN impurities A and B, were successfully determined. The quantitative determinations of studied components were assessed by percentage recoveries, standard errors of prediction as well as root mean square errors of prediction. The developed models were constructed in the ranges of 5.0-13.0 µg mL-1 for NZ, 10.0-60.0 µg mL-1 for PN, 1.0-5.0 µg mL-1 for NZ impurity B and 2.0-14.0 µg mL-1 for two PN impurities. The proposed models could determine NZ and PN with respective detection limits of 0.447 and 1.750 µg mL-1 for PLS, and 0.494 and 2.093 µg mL-1 for ANN. The two established models were compared favorably with official methods where no significant difference observed.

Molecular imprinted polymer-based potentiometric approach for the assay of the co-formulated tetracycline HCl, metronidazole and bismuth subcitrate in capsules and spiked human plasma.

BACKGROUND: An anti-H-pylori co-formulated mixture of tetracycline HCl (TET), metronidazole (MET), and bismuth subcitrate (BSC) is recently available. Only two chromatographic and spectrophotometric methods are reported for determining those drugs simultaneously where the effect of impurities that could be present as well as the biological fluids matrix influence do not be taken into consideration. There is a need to develop an easy-to-use potentiometric technique for analysis of TET, MET, and BSC in their co-formulated capsules, in presence of some official impurities and in spiked human plasma. RESULTS: Three carbon paste electrodes (CPEs) were fabricated for this purpose. Being a solid contact ion-selective electrode, CPE suffers from the creation of a water layer affecting its stability and reproducibility. Besides, it has a common problem in differentiation between two drugs carrying the same charge (positively charged TET and MET). Water layer formation was prevented through inserting polyaniline nanoparticles (≈10.0 nm diameter) between solid contact and ion-sensing membrane in the three proposed sensors. TET and MET interference was overcome by synthesizing a corresponding molecular imprinted polymer (MIP) for each drug. The synthesized MIPs were inserted in equivalent sensing membranes and characterized using several techniques. The suggested MIPs have a noticeable enhanced sensitivity in potentiometric determination. The obtained LODs were 5.88 × 10-8, 5.19 × 10-7, and 1.73 × 10-6 M for TET, MET and BSC proposed CPEs, respectively, with corresponding slopes of 57.37, 56.20, and -57.40 mV decade-1. SIGNIFICANCE: The proposed potentiometric method makes the detection of the three cited drugs simple, fast, and feasible. This approach is the first for determining three drugs potentiometrically in one combined formulation. The obtained results were compared favorably with previously reported potentiometric methods.

Degradation and energy performance evaluation of mono-crystalline photovoltaic modules in Egypt.

Degradation reduces the capability of solar photovoltaic (PV) production over time. Studies on PV module degradation are typically based on time-consuming and labor-intensive accelerated or field experiments. Understanding the modes and methodologies of degradation is critical to certifying PV module lifetimes of 25 years. Both technological and environmental conditions affect the PV module degradation rate. This paper investigates the degradation of 24 mono-crystalline silicon PV modules mounted on the rooftop of Egypt's electronics research institute (ERI) after 25 years of outdoor operation. Degradation rates were determined using the module's performance ratio, temperature losses, and energy yield. Visual inspection, I-V characteristic measurement, and degradation rate have all been calculated as part of the PV evaluation process. The results demonstrate that the modules' maximum power ([Formula: see text]) has decreased in an average manner by 23.3% over time. The degradation rates of short-circuit current ([Formula: see text]) and maximum current ([Formula: see text]) are 12.16% and 7.2%, respectively. The open-circuit voltage ([Formula: see text]), maximum voltage ([Formula: see text]), and fill factor ([Formula: see text]) degradation rates are 2.28%, 12.16%, and 15.3%, respectively. The overall performance ratio obtained for the PV system is 85.9%. After a long time of operation in outdoor conditions, the single diode model's five parameters are used for parameter identification of each module to study the effect of aging on PV module performance.

Inference and quantile regression for the unit-exponentiated Lomax distribution.

In probability theory and statistics, it is customary to employ unit distributions to explain practical variables having values between zero and one. This study suggests a brand-new distribution for modelling data on the unit interval called the unit-exponentiated Lomax (UEL) distribution. The statistical aspects of the UEL distribution are shown. The parameters corresponding to the proposed distribution are estimated using widely recognized estimation techniques, such as Bayesian, maximum product of spacing, and maximum likelihood. The effectiveness of the various estimators is assessed through a simulated scenario. Using mock jurors and food spending data sets, the UEL regression model is demonstrated as an alternative to unit-Weibull regression, beta regression, and the original linear regression models. Using Covid-19 data, the novel model outperforms certain other unit distributions according to different comparison criteria.

Assessment of Knowledge and Perception of Sodium-Glucose Co-transporter 2 (SGLT-2) Inhibitors prescription Among Physicians in Saudi Arabia.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors are a new class of medications that have been proven to improve both glycemic control and cardio-renal outcomes. The knowledge, attitude, and perception toward their prescriptions in Jazan, Saudi Arabia, are still unknown. OBJECTIVE: The study aimed to measure the level of knowledge and attitude toward sodium-glucose cotransporter 2 inhibitors prescription among physicians in the Jazan region, Saudi Arabia. METHODS: Data analysis was performed using Statistical Package for the Social Sciences, SPSS 23rd version. Frequency and percentages were used to display categorical variables. Minimum, maximum, mean, and standard deviation were used to test numerical variables. Independent t-test and ANOVA test were both utilized to test the factors associated with knowledge and attitude toward the use of SGLT-2 inhibitors. RESULTS: A total of 65 participants were included in the study. 26.2% had a low knowledge level, 30.8% had a moderate knowledge level, and 43.1% had a high knowledge level of sodium-glucose cotransporter 2 inhibitors. 9.2% had a low attitude level, 43.1% had a moderate attitude level, and 47.7% had a high attitude level toward sodium-glucose cotransporter 2 inhibitors. Age, professional status, years of experience, and specialty were significantly associated with attitude but not with the knowledge of sodium-glucose cotransporter 2 inhibitors prescription. CONCLUSION: While the study cohort scored high in the knowledge and attitude domains of the survey, a large proportion failed to answer very essential questions in type 2 diabetes management. An educational awareness program needs to be carried out to strengthen the physicians' knowledge of SGLT2 inhibitors prescription.

Molecular Identification, Pathogenesis, and Life Cycle of Sarcocystis cruzi from Cattle (Bos taurus) in New Valley Governorate, Egypt.

Sarcocystis cruzi was identified by molecular methods from an intermediate host, cattle (Bos taurus), in El-Kharga, New Valley Governorate, Egypt, and its life cycle and pathogenicity were studied in the final host, dogs (Canis familiaris). 600 slaughtered cattle aged 6-8 years (480/120 males/females) were included. In addition, three laboratory-bred, coccidian-free puppies aged 2-3 months were fed infected bovine muscles to locate the definitive host and analyze sporogony. 18S rRNA-specific gene primers were used for DNA amplification from esophageal muscles. These polymerase chain reaction (PCR) amplicons were subjected to restriction fragment length polymorphism (RFLP) and molecular sequence analysis. Infection was detected in 78.8% (473/600; 95% CI, 75.56-82.11%). Histopathological examination of esophageal muscles showed oval- to spherical-shaped cysts, 96.7 µm wide by 326.9 µm long; cysts in cardiac muscles were ovoid and smaller. Infected puppies began shedding sporocysts in feces 7 days post-inoculation and showed distorted organ architecture, severe cellular damage, and inflammatory lesions in liver, kidney, esophagus, and stomach. Three oocysts with different shapes and sizes were identified. Partial 18S rRNA gene sequences of isolated New Valley sarcocysts were identical to S. cruzi isolated from different areas, verifying their genetic relatedness. Our analysis suggests that S. cruzi is the most prevalent in slaughtered cattle in New Valley Governorate, Egypt.

Evaluating the role of polysaccharide extracted from Pleurotus columbinus on cisplatin-induced oxidative renal injury.

This research aimed to examine the antioxidant polysaccharide activity (PsPc-3) derived from Pleurotus columbinus (P. columbinus) on oxidative renal injury (ORI) induced by cisplatin (CP). The principal components of crude polysaccharide were assessed. We studied the preventive impact of polysaccharide on cisplatin-induced renal damage in this study. For 21 days, we employed the CP-induced ORI rat model and divided the rats into four groups: control, CP alone, polysaccharide post CP (100 mg/kg) orally, and CP + polysaccharide (pre and post). The chemical characterization of the polysaccharide fraction PsPc-3 stated that protein was not present. PsPc-3 contained 7.2% uronic acid as assessed as 0% sulfate. PsPc-3 hydrolysate structured of Galacturonic:Glucose:Xylose and their molar proportions were 1:4:5, respectively. The average molecular weight (Mw) and molecular mass (Mn) per molecule of PsPc-3 were 5.49 × 104 g/mol and Mn of 4.95 × 104 g/mol respectively. DPPH radical scavenging activity was demonstrated by the polysaccharide of 65.21-95.51% at 10 mg/ml with IC50 less than 10 mg/ml. CP increased serum urea to 92.0 mg/dl and creatinine up to 1.0 mg/dl, with a concurrent decrease in the levels of total protein to 4.0 mg/dl. Besides, Also, CP-induced ORI raised levels of malondialdehyde (MDA), alkaline phosphatase (ALP), and renal hormones (renin and aldosterone), with a decline in antioxidants compared to control rats. In addition, in the presence of CP, interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-alpha) levels increased. PsPc-3 decreased these changes dramatically. PsPc-3 improves pathological renal damage caused by CP and decreases tubular apoptosis measured by DNA ladder formation and cleaved caspase- 3. These findings showed that PsPc-3 isolated from P. columbinus protects and inhibits tubular apoptosis in cisplatin-induced ORI. Furthermore, PsPc-3 has no influence on the anticancer efficacy of CP in rats. Thus, PsPc-3 derived from P. columbinus might provide a novel therapy method for cisplatin-induced nephrotoxicity.

LC-MS/MS and GC-MS based phytochemical perspectives and antimicrobial effects of endophytic fungus Chaetomium ovatoascomatis isolated from Euphorbia milii.

The antimicrobial activity of endophytic fungi isolated from Euphorbia milii was evaluated against Gram-positive, Gram-negative bacteria, unicellular yeast, and filamentous fungi. Chaetomium ovatoascomatis NRC was identified morphologically and genetically as the most active strain. The total ethyl acetate extract of C. ovatoascomatis NRC demonstrated significant antimicrobial activity against Gram-negative; Escherichia coli, Salmonella enteric, and fungi; Aspergillus niger with MIC of 62.5 ug/ml. Whereas n-hexane fraction demonstrated broader activity against Gram-positive; Bacillus subtilis, Lactobacillus cereus, Gram-negative; Escherichia coli and Salmonella enteric, fungi; Candida albicans and F. solani. LC-MS/MS analysis of ethyl acetate strain extract and GC-MS analysis of the n-hexane fraction were used to identify the metabolites of the strain extract. LC-MS/MS determined three major metabolites with potential antimicrobial activities including grevilline B, aflatoxin G2 and apigenin. GC-MS analysis of n-hexane fraction tentatively identified 30 compounds, where 9,12-octadecadienoic acid methyl ester was the major compound.