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Fungal endophyte Penicillium janthinellum LK5 improves growth of ABA-deficient tomato under salinity
Khan, Abdul Latif,Waqas, Muhammad,Khan, Abdur Rahim,Hussain, Javid,Kang, Sang-Mo,Gilani, Syed Abdullah,Hamayun, Muhammad,Shin, Jae-Ho,Kamran, Muhammad,Al-Harrasi, Ahmed,Yun, Byung-Wook,Adnan, Muhammad Springer-Verlag 2013 World journal of microbiology & biotechnology Vol.29 No.11
Adnan Khan,판정훈,조성하,이소정,김영준,황용자 한국식품영양과학회 2017 Journal of medicinal food Vol.20 No.8
This study aimed to identify the changes in the metabolomics profile of liver damage caused by alcohol consumption and verify beneficial effect of Prunus mume Sieb. et Zucc extract (PME) in protection of alcohol-induced injury by attenuating the level of identified metabolites. Mice were treated with PME and saline or untreated once daily for 5 days, followed by alcohol injection. The plasma samples were analyzed using liquid chromatography–mass spectrometry-based high-resolution metabolomics followed by a multivariate statistical analysis using MetaboAnalyst 3.0 to obtain significantly expressed metabolites, using a false discovery rate threshold of q = 0.05. Metabolites were annotated using Metlin database and mapped through Kyoto Encyclopedia of Genes and Genomes (KEGG). Among 4999 total features, 101 features were significant among alcohol- and PME-treated mice groups. All the samples cluster showed a clear separation in the heat map, and the scores plot of orthogonal partial least squares-discriminant analysis (OPLS-DA) model discriminated the three groups. Phosphatidylcholine, Saikosaponin BK1, Ganoderiol I, and N-2-[4-(3,3-dimethylallyloxy) phenyl] ethylcinnamide were among the significant compounds with a low intensity in alcohol group compared to PME group, suggesting that these compounds have a relation in the development of PME's protective effect. The study confirms the hepatoprotective, antioxidant, and anti-inflammatory effects of PME against alcohol-induced liver steatosis, inflammation, and apoptosis.
Khan, Adnan,Choi, Soo An,Na, Jinhyuk,Pamungkas, Aryo Dimas,Jung, Keum Ji,Jee, Sun Ha,Park, Youngja H. American Chemical Society 2019 Journal of proteome research Vol.18 No.4
<P>This study aimed to apply high-resolution metabolomics to detect compounds that may contribute significantly to prostate cancer (PCa) development. The test population’s sera for evaluating the metabolic differences consisted of healthy control (<I>n</I> = 96) and PCa (<I>n</I> = 50) groups. PCa patients were further divided into two groups based on whether their PSA level was >4 (<I>n</I> = 25) or <4 (<I>n</I> = 25). Univariate analysis was performed with the false discovery rate (FDR) at <I>q</I> = 0.05 to determine significantly different metabolites. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) clearly distinguished healthy subjects from PCa groups, while no significant difference was observed in PCa patients with PSA level < 4 or > 4. Mummichog, in combination with the KEGG and MetaboAnalyst, showed that tryptophan metabolism along the kynurenine pathway was most significantly enriched, with −log (<I>p</I>) < 0.05. <SMALL>L</SMALL>-Tryptophan, kynurenine, anthranilate, isophenoxazine, glutaryl-CoA, (<I>S</I>)-3-hydroxybutanoyl-CoA, acetoacetyl-CoA, and acetyl-CoA were upregulated in correlation with the PSA level of PCa patients; in contrast, indoxyl, indolelactate, and indole-3-ethanol, involved in the alternative pathway, were downregulated in the PCa patients. Validation and quantification of potential metabolites by MS/MS further confirmed the disruption of tryptophan, kynurenine, and anthranilate, suggesting that the metabolites of this pathway are potential biomarkers in patients with PCa.</P> [FIG OMISSION]</BR>
Khan, Adnan,Choi, Yoonjeong,Back, Joung Hwan,Lee, Sunmi,Jee, Sun Ha,Park, Youngja H. Elsevier 2020 clinical and experimental Vol.104 No.-
<P><B>Abstract</B></P> <P><B>Background</B></P> <P>Identifying changes in serum metabolites before the occurrence of acute myocardial infarction (AMI) is an important approach for finding novel biomarkers of AMI.</P> <P><B>Methods</B></P> <P>In this prospective cohort study, serum samples obtained from patients at risk of AMI (<I>n</I> = 112) and non-risk controls (<I>n</I> = 89) were tested using high-resolution metabolomics (HRM). Partial least-squares discriminant analysis (PLS-DA), along with univariate analysis using a false discovery rate (FDR) of <I>q</I> = 0.05 were performed to discriminate metabolic profiles and to determine significantly different metabolites between healthy control and AMI risk groups.</P> <P><B>Results</B></P> <P>PLS-DA significantly separated the AMI risk sera from control sera. The metabolites associated with amino acid biosynthesis, 2-oxocarboxylic acid, tryptophan, and amino sugar and nucleotide sugar metabolism pathways were mainly elevated in patients at risk of AMI. Further validation and quantification by MS/MS showed that tryptophan, carnitine, L-homocysteine sulfinic acid (L-HCSA), and cysteic acid (CA) were upregulated, while L-cysteine and L-cysteine sulfinic acid (L-CSA) were downregulated, specifically among AMI risk sera. Additionally, these discriminant metabolic profiles were not related to hypertension, smoking or alcoholism.</P> <P><B>Conclusion</B></P> <P>In conclusion, detecting upregulated L-HCSA and CA along with carnitine among patients at risk for AMI could serve as promising non-invasive biomarkers for early AMI detection.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Subjects at risk for Acute Myocardial Infarction (AMI) have a significantly different serum metabolome compared with healthy subjects. </LI> <LI> The differential metabolome of AMI risk sera were not related to hypertension, smoking, alcohol consumption or age. </LI> <LI> Upregulated L-homocysteine sulfinic acid (L-HCSA) and cysteic acid (CA) along with carnitine can help detecting the subjects who are at risk of developing AMI. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
Analysis of 3D Building Construction Applications in Augmented Reality
Khan, Humera Mehfooz,Waseemullah, Waseemullah,Bhutto, Muhammad Aslam,Khan, Shariq Mahmood,Baig, Mirza Adnan International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.10
Construction industry is considered as one of the oldest industries in the world since human came into being and the need of their own space is realized. All this led to make the world a space of many beautiful constructive ventures. As per the requirements of today's world, every industry is recognizing the need for use and adoption of modern as well as innovative technologies due to their benefits and timely production. Now construction industry has also started adopting the use of modern and innovative technologies during their projects but still the rate of adoption is so slow. From design to completion, construction projects take a lot to manage for which technology based solutions have continuously been proposed. These include Computer Aided Design (CAD), building information modeling (BIM) and cloud computing have been proved to be much successful until now. The construction projects are high budgeted, and direly require timely and successful completion with quality, resource and other constraints. So, the researchers observe the need of more clear and technology based communication between the construction projects and its constructors and other stakeholders is required before and during the construction to take timely precautions for expected issues. This study has analyzed the use of Augmented Reality (AR) technology adopting GammaAR, and ARki applications in construction industry. It has been found that both applications are light-weighted, upgradable, provide offline availability and collaborative environment as well as fulfil most of the requirements of the construction industry except the cost. These applications also support different screen size for better visualization and deep understanding. Both applications are analyzed, based on construction's application requirements, usability of AR and ratings of applications user collected from application's platform. The purpose of this research is to provide a detail insight of construction applications which are using AR to facilitate both the future developers and consumers.
Hamayun Khan,Abdul Kabir Khalil,Adnan Khan,Khalid Saeed Ibrahim,Nauman Ali 한국화학공학회 2016 Korean Journal of Chemical Engineering Vol.33 No.10
Three different chitosan conjugated magnetic nanoparticles (CCMN) of Co, Ni and Fe were prepared using co-precipitation method. The prepared CCMN were characterized by scanning electron microscopy (SEM), Xray diffraction (XRD) and Fourier transform infra-red (FT-IR) spectroscopic techniques. The SEM results showed a smooth surface morphology with almost uniform particle size and irregular shape structure for all CCMN. The XRD study revealed the crystalline structure in case of Co-CCMN and Ni-CCMN, while amorphous nature of Fe-CCMN was observed. The particle size of the prepared CCMN was found to be <95 nm, as confirmed from SEM and XRD analyses. Similarly, FT-IR analysis showed the incorporation and conjugation of Co, Ni and Fe magnetic nanoparticles into the chitosan polymer matrix. The point of zero charge (PZC) was found to be 7.41 for Co-CCMN and Ni-CCMN and 7.70 for Fe-CCMN. The photocatalytic activity of the prepared CCMN was investigated under UV light irradiation (254 nm and 15 W) in the aqueous medium using bromophenol blue (BPB). The photocatalytic process was monitored by UV-visible spectrophotometer for different irradiation times (0 to 10 h). The results showed that all the prepared CCMN displayed good to excellent photocatalytic property where the highest degradation was exhibited by Fe-CCMN (94.5%), followed by Co-CCMN (85.1%) and Ni-CCMN (83.0%). The prepared catalysts were recycled and reused, maintaining good photocatalytic activity for four consecutive batches.