PAKISTAN SCIENCE BULLETIN Volume 2, Issue 1

There has been an increase in human studies of exposure to endocrine-disrupting chemicals (EDCs). In this follow-up to a previous study, we analyzed new data to determine whether or not there was substantial human evidence linking the exposures and outcomes of the prior study. Perfluoroalkyl chemicals have been linked to an increased risk of childhood and adult obesity, impaired glucose tolerance, gestational diabetes, low birth weight, poor sperm quality, polycystic ovary syndrome, endometriosis, and breast cancer. There is substantial evidence supporting these associations. Children exposed prenatally to bisphenol A, organophosphate insecticides, and polybrominated flame retardants are more likely to develop cognitive impairments and attention-deficit hyperactivity disorder. Although a comprehensive evaluation of the frequency and intensity of these exposure-result links is required, a growing body of evidence suggests that immediate action be taken to reduce exposure to environmental toxicants (EDCs).
Our environment has become contaminated enormously with different industrial chemicals that could disturb the natural mechanism of hormones like their secretion, transport etc., in our body. These industrial effluents are called as endocrine disruptors (EDs) and they mainly affect through polluted water and food. These chemicals (EDs) have the ability to stay in the environment for years and to travel vast distances due to their long half-life. Plastics, fungicides, pesticides, medications, plasticizers, lubricants, and so on are only few examples of the wide range of potential environmental contaminants (EDs). Due to the complexity of the situation, it is difficult to understand the precise mechanism of action of these EDs, which cause disruptions in hormone production or epigenetic pathways as well as in thyroid receptors (TRs), oestrogen receptors (ER), androgen receptors (AR) and aryl hydrocarbon receptors (AhR). The research advancements in this area is mandatory to get more information about EDs, their potential and their mode of action and removal of these chemicals from environment.
Keywords: Endocrine Disrupting Chemicals EDCs, toxicity mechanism, mixture interaction.

Urooba Gulshan¹, Yousaf Khan¹, Rafia Masood¹, Areeba Raza¹, Sumera Latif^1
1Department of Chemistry, COMSATS University Islamabad, 45550, Islamabad Pakistan
Corresponding Author: Yousaf Khan, yousaf7n@gmail.com

01-20

To recognize, evaluate, assort, document respiratory and gastrointestinal medicinal plants used within Tehsil Balakot. A list of conventional healers of Balakot was arranged and information was obtained through questionnaires and interviews. Subsequently sample of different species were collected from preferred areas and deposited in the Herbarium of Govt. Post graduate college Mansehra. Results shows that 42 different medicinal species belong to 33 several families are being used for the treatment of various digestive and respiratory disorders. The commonly used plants parts were leaves and roots. The traditional dosage forms were liquid, powder, granules, decoction and juice. People of the tehsil Balakot have belief that plants have influential role in the cure of respiratory and digestive diseases and they used therapeutic plants as ancients to indulgence of special disorders. Our research showed significance of traditional medicines in this area as source of medicament for pharmacist in future.
Keywords: Medicinal plants, Herbal, Ethno botany, Respiratory diseases, Gastrointestinal diseases, Tehsil Balakot.

Danish Ali¹, Dr. Abbas Hussain Shah², Dr. Zayad Tariq, Warda tu Nisa¹

¹Department of Dental Akbar institute of Medical Sciences and Nursing College Mansehra.
²Botany Government Post Graduate College Mandian Abbottabad
⁴Khyber Medical University Peshawar.
*Corresponding author: danibotanist@gmail.com.

21-35

There are hundreds and thousands of compounds of marine natural product that are used for medicinal use from the present decades. These compounds are used for therapy of different infectious diseases like HIV, cancer, tumor, and analgesic. These compounds are synthesized and modified and make them useable for the treatment of different diseases and having numerous characteristics in medical field extracted from marine organism. These compounds of marine organisms are further modified with high specificity for the discovery of new drugs in present and near future.
Keywords: Marine Alkaloid, Medicinal Importance, Drug Discovery, Anti-Carcinogenic, Plants Microbes

Yousaf Khan^a* Abdul Sattar^a, Syed Amin ullah^a, Zia Ur Rehman Panizai^b, Madeeha Bibi^c, Saif Ud Din Panizai ^d
aDepartment of Chemistry, COMSATS University Islamabad, 45550, Islamabad Pakistan.
^bDepartment of Chemistry, University of Baluchistan Quetta, Pakistan. ^cDepartment of Chemistry, Hazara University Mansehra, Pakistan.
^dDepartment of Bio-Chemistry, Abasyn University Islamabad, Pakistan.

Email Address: Corresponding Author: yousaf7n@gmail.com.

36-50

One of the most difficult problems in the medical field nowadays is the prediction of heart disease. Approximately in the current period, one person dies from heart disease every minute. In the sphere of healthcare, the process must be automated to reduce risks and notify the patient well in advance because predicting cardiac illness is a challenging task. In this study, the UCI machine learning repository’s heart disease data-set is used.
In the current project, five well-known machine learning algorithms—decision tree, Random forest, Support Vector Machine, logistic regression, and k-neighbor —are being evaluated for accuracy by using machine learning, which learns from natural events and data and uses biological variables like cholesterol, blood pressure, sex, and age as evaluating data. Finding the most accurate way to predict cardiac illnesses is the study’s main objective.
The performance of five well-known machine learning algorithms is thus analyzed in this work to give a comparison study. In comparison to other ML algorithms used, the testing results demonstrate that the support vector machine approach has the highest accuracy of 85%.
Keywords— Decision tree, Support vector machine, linear regression, decision tree, naïve bayes, supervised, unsupervised, reinforced.

Muhammad Abrar¹, Muhammad Sadique^2
1Department of Computer Science GPGC Mansehra, Pakistan
²Department of Computer Science GPGC Mansehra, Pakistan

51-75