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Home > A Study on the Synthesis and Biological Evaluation of Some 3, 6-Disubstituted-1, 2, 4-Triazolo[3, 4-B]-1, 3, 4-Thiadiazoles and 2, 5-Disubstituted-1, 3, 4-Oxadiazoles

A Study on the Synthesis and Biological Evaluation of Some 3, 6-Disubstituted-1, 2, 4-Triazolo[3, 4-B]-1, 3, 4-Thiadiazoles and 2, 5-Disubstituted-1, 3, 4-Oxadiazoles

Thesis Info

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External Link

Author

Khan, Mahmood-Ul-Hassan

Program

PhD

Institute

Quaid-I-Azam University

City

Islamabad

Province

Islamabad.

Country

Pakistan

Thesis Completing Year

2011

Thesis Completion Status

Completed

Subject

Chemistry

Language

English

Link

http://prr.hec.gov.pk/jspui/handle/123456789/701

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676725423605

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The 1,2,4-triazolo[3,4-b]-1,3,4-thiadiazoles and 1,3,4-oxadiazoles are prominent biological agents used as a cure against a number of human ailments. The present work deals with the synthesis of 3,6-disubstituted-1,2,4-triazolo[3,4-b]-1,3,4- thiadiazoles and 2,5-disubstituted-1,3,4-oxadiazoles bearing adamantyl and aryl moieties. The synthesis of 3,6-disubstituted-1,2,4-triazolo[3,4-b]-1,3,4-thiadiazoles was carried out starting from aryl carboxylic acids. On the other hand, 2,5-disubstituted-1,3,4-oxadiazoles were synthesized using two distinct routes starting from either aryl carboxylic acids or aryl nitriles. The structures of the synthesized compounds were confirmed by IR, 1 H- and 13 C-NMR, EIMS and XRD analysis. The target compounds were screened for their antitumor, antiviral, antibacterial and antifungal potential. Among the tested compounds, 3-(2-methylphenyl)-6-adamantyl- 1,2,4-triazolo[3,4-b]-1,3,4-thiadiazole (4a) and 3-(2-fluorophenyl)-6-adamantyl-1,2,4- triazolo[3,4-b]-1,3,4-thiadiazole (4d) exhibited prominent antiproliferative activity against human CD4 + T-cells containing an integrated HTLV-1 genome (MT-4) with CC 50 of 45 μM and 47 μM, respectively. These compounds were also found to be active against human acute T-lymphoblastic leukemia (CCRF-CEM) cell lines with CC 50 of 40 μM each. 3-(3-Methylphenyl)-6-adamantylmethyl-1,2,4-triazolo[3,4-b]- 1,3,4-thiadiazole (4n) showed moderate inhibition of HIV-1 and HIV-2 with EC 50 of >10.90 μg/mL, but no selectivity could be witnessed. Similarly, 3-(3-methylphenyl)- 6-adamantylmethyl-1,2,4-triazolo[3,4-b]-1,3,4-thiadiazole (5n) was found to be potent exhibiting moderate inhibition of HIV-1 and HIV-2 with EC 50 of >10.86 μg/mL. Furthermore, oxadiazole (9a) and 2-adamantyl-5-(2-(2-methylphenyl)-1,3-thiazol-4-yl)-1,3,4- 2-adamantyl-5-(2-(2-bromophenyl)-1,3-thiazol-4-yl)-1,3,4- oxadiazole (9j) showed significant inhibition of HIV-1 and HIV-2 with EC 50 of >10.50 μg/mL and >10.90 μg/mL, respectively. However, antibacterial and antifungal activities of all the compounds were found to be non-significant at non-toxic concentrations.
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مواد کی اہمیت، مواد کی اقسام، مواد کی فراہمی کے ذرائع

موضوع3:مواد کی اہمیت، مواد کی اقسام، مواد کی فراہمی کے ذرائع
مواد کیا ہے؟
مواد عربی لفظ "مادہ" کی جمع ہے۔ اس کے معنی رسالہ، سامان اوراسبا ب کے ہیں۔علمی اصطلاح میں مواد سے مراد وہ اسباب ہیں جو محقق تحقیق کے دوران استعمال میں لاتا ہے۔مواد کا متبادل لفظ موازنہ ہے یہ بھی عربی کا لفظ ہے جس کے لغوی معنی ضروری چیزیں یا سامان ،میٹریل کے ہیں۔Contentاور ڈیٹا کے انگریزی الفاظ بھی مواد کے متبادل کے طورپر مستعمل ہیں۔لفظ میٹیریل بالعموم مادی اشیاء کے لیے ڈیٹا، اعداد و شمار ، Contentاور نفس مضمون کے لیے استعمال ہوتا ہے۔
مواد کی اہمیت:
تحقیق کسی بھی شعبے میں ہو مواد کے بغیر ممکن ہی نہیں بلکہ کئی ایک ماہرین کا مانناہے کہ تحقیق کی گاڑی مواد کے ایندھن کے بغیر چل ہی نہیں سکتی اور مواد ہی محقق کے غور و فکر کی بنیاد ہوتا ہے۔ پروفیسر عبدالستار دلوی کے مطابق:
’’خالص مواد کی شکل خام مال کی طرح ہوتی ہے۔ اسی خام ما ل سے تجزیہ ، درجہ بندی اور تحقیق کے ذریعہ نتائج اور عام اصول وضع کیے جاتے ہیں۔‘‘
مواد کی فراہمی تحقیق میں کافی اہمیت کی حامل ہے۔ اس کا سارا بار ایک ریسرچ اسکالر کو خود ہی اٹھانا پڑتا ہے۔ خلیق انجم نے اپنے ایک مضمون ’ادبی تحقیق اور حقائق‘ میں لکھا ہے:
"ایک محقق کو سب سے پہلے یہ معلوم کرنا ہوگا کہ موضوع سے متعلق کیا مواد ہے؟ کہاں ہے؟ اور کیسے فراہم کیا جاسکتا ہے؟"
مواد کی فراہمی کے سلسلے میں محقق کو شہد کی مکھی سے تعبیر کیا گیا ہے کہ جس طرح شہد کی مکھیاں مختلف پھولوں کارس چوس کر شہد بناتی ہیں ،اسی طرح ایک محقق کو بھی مختلف ماخذوں کو حاصل کر کے اپنی تحقیق کو بہترین بنانا پڑے گا تب جاکر وہ تحقیق...

PENDIDIKAN AGAMA ISLAM (PAI) MULTIKULTURAL PERSPEKTIF PEMBELAJARAN INTEGRATIF

Tulisan ini mengkaji tentang PAI multikultural sebagai model pembelajaran integratif yang memadukan antara ilmu pengetahuan dan agama. Dari aspek konten, multikulturalisme mengkaji keragaman bangsa, suku, warna kulit, bahasa, agama dan keragaman lain yang terbentang dalam realitas sosial kehidupan manusia sebagai ayat-ayat Allah yang bersifat kauniyah. Sedangkan PAI mempelajari normativitas ajaran Islam dan dimensi historis yang banyak termuat dalam al-Qur’an sebagai ayat-ayat Allah yang bersifat qauliyah. Pembelajaran kedua bidang keilmuan tersebut sama-sama sebagai proses pencarian kebenaran yang merujuk kepada Allah sebagai episentrum kebenaran Hakiki dan sumber ilmu pengetahuan. Dari konsep pembelajaran integratif yang dikemukakan pemikir Islam dan Barat, PAI multikultural berada pada pola relasi antardispliner, yaitu integrasi antara ilmu umum dan ilmu agama. PAI multikultural sebagai pembelajaran integratif tergambar pada aspek: tujuan, materi, metode, media dan sumber belajar dan penilaian yang saling terintegrasi dalam membentuk kompetensi beragama peserta didik secara integral, yaitu: keterpaduan antara unsur duniawi dan ukhrawi, antara dimensi spritual dan intelektual, antara ranah personal dan sosial dalam konteks membangun harmoni kehidupan warga sekolah, masyarakat dan bangsa Indonesia yang pluralistik dari segala aspeknya.

Predicting Financial Distress Using Machine Learning Techniques in Services Sector of Pakistan

Financial distress is an active research area particularly for business community of Pakistan due to economic conditions, electricity shortage and political situation. Banks are also taking keen interest in this area after the global financial crisis of year 2008. Therefore, the question that how financial distress can be predicted accurately has been widely debated by many scholars by using traditional statistical models. However, earlier research has not adequately addressed the issue of predicting financial distress. Adding to that the rate of financial distress is also getting harder to estimate by using traditional statistical models, because firms are becoming more complex and creating refined plans to hide their real financial situation. To prevent this condition latest prediction models are adopted by many countries which can give early indication of firm?s financial distress with highly accurate results. In this regard, prediction of financial distress by Neural Network Model is not much explored in Pakistan for foreseeing the financial health of firms. This paper addresses this issue and uses Neural Network Model to predict financial distress of firms in Pakistan by selecting suitable independent variables. The sample of 22 private sector conventional banks listed at Pakistan Stock Exchange is selected. The time series financial statements of these banks are selected for 15 years (2001 to 2015).Selected sample time frame is (pre-crisis 2001-2007), (crisis 2008) and (post-crisis 2009-2015). To test first hypothesis,4 Altman''s ratios from revised Altman''s Z-Score Model are calculated from these financial statements of selected banks. This study used three layered Neural Network Model consisting of input layer, hidden layer and output layer. The 4 independent explanatory variables/ input are 4 Altman''s ratios and 1 dependent variable/output is probable financial distress. After determining the Neural Network architecture, cross-validation re-sampling procedure is used to train, validate, and test a Neural Network by using commerciallyavailable MATLAB software. The best and most appropriate Neural Networks model, constructed by combining input variables of 4 Altman''s ratios, resulted in the R value of 0.99 that shows a relatively high accuracy given the error ratio in the input variables. These results confirmed the second hypothesis. By testing third hypothesis, distressed and non distressed banks are correctly classified with reference to Altman?s ratio