Neopterin has been considered as an important marker of cellular inflammation. The primary objective of the current study was to determine the role of neopterin in cardiovascular disease and its association with other well known cardiac markers. The study was composed of total 200 subjects (100 confirmed coronary artery disease (CAD) patients, 50 recently diagnosed, and 50 managed CAD patients) both men and women and 100 healthy control individuals of matching age and weight. Serum neopterin analysis was done using commercial available ELISA kits. Other cardiac markers viz. troponin, creatine kinase (CK), CK MB isoenzyme (CKMB), lactate dehydrogenase (LDH), fibrinogen, C-reactive protein (CRP), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) estimation was done by standard routine biochemical methods. Neopterin level was found to be remarkably enhanced by 150% and 513% in the recently diagnosed and managed CAD patients, respectively. CK level also showed a significant rise by 62% in the managed patients. However, recently diagnosed patients did not show any significant change. Moreover, cross correlation study showed statistically significant (P < 0.01) change in neopterin and CK levels between recently and managed patients. In the other studied CAD markers such as CKMB, fibrinogen and LDH also showed a significant increase in both categories of patients. CRP level was also found to be significantly enhanced by 357% (P < 0.01) and 341% (P < 0.05) in recently diagnosed and managed patients respectively. Because of cost effectiveness, easy and quick analysis of neopterin in the serum sample, we propose neopterin as the prognostic as well as diagnostic biomarker of CAD before other markers could be tested especially in Saudi population.
Most of the studies related to the use of unconventional methods of therapy by cancer patients have been carried out in the developed countries. This study was conducted to ascertain the frequency, type, and duration of use of unconventional methods of therapy by cancer patients in Pakistan. We also wanted to identify individuals who are most likely to use these methods and to compare the findings with those reported from the developed countries. Between 1 April and 30 May 1994, all patients with histologically proven cancer who visited the oncology unit were interviewed. A printed questionnaire with questions and options was used as an interview guide. Informed consent was obtained. One hundred and ninety-one patients were interviewed, on average, for 25 minutes each. Use of unconventional methods of therapy by cancer patients was widespread (54.5% of all patients). The majority (83.7%) were influenced by family members to use these methods. Traditional herbal medicines (70.2%) and homeopathy (64.4%) were the most commonly employed methods. Thirty-six percent of the users employed these methods before receiving any conventional therapy. Only 15% used these methods after conventional therapeutic options had been exhausted. Patients generally perceived these methods as useful, non-toxic and inexpensive. Age, marital status, socio-economic background, education level and status of underlying neoplasm did not influence the frequency of use of unconventional methods. The use, however, was influenced by gender, family size, and type of underlying malignancy. Patients aware of their diagnosis were less likely to use these methods. This study suggests that use of unconventional methods by cancer patients in Pakistan is widespread. Unlike western countries, these methods are often employed before receiving any conventional therapy. This probably results in a significant delay which can be expected to adversely influence the subsequent disease management and survival. Public education, reduction of cost and easy availability of conventional therapy may be helpful in reducing the use of methods which otherwise may have no proven value.
A few methods and tools are available for the quantitative measurement of the brain volume targeting mainly brain volume loss. However, several factors, such as the clinical conditions, the time of the day, the type of MRI machine, the brain volume artifacts, the pseudoatrophy, and the variations among the protocols, produce extreme variations leading to misdiagnosis of brain atrophy. While brain white matter loss is a characteristic lesion during neurodegeneration, the main objective of this study was to create a computational tool for high precision measuring structural brain changes using the fractal dimension (FD) definition. The validation of the BrainFD software is based on T1-weighted MRI images from the Open Access Series of Imaging Studies (OASIS)-3 brain database, where each participant has multiple MRI scan sessions. The software is based on the Python and JAVA programming languages with the main functionality of the FD calculation using the box-counting algorithm, for different subjects on the same brain regions, with high accuracy and resolution, offering the ability to compare brain data regions from different subjects and on multiple sessions, creating different imaging profiles based on the Clinical Dementia Rating (CDR) scores of the participants. Two experiments were executed. The first was a cross-sectional study where the data were separated into two CDR classes. In the second experiment, a model on multiple heterogeneous data was trained, and the FD calculation for each participant of the OASIS-3 database through multiple sessions was evaluated. The results suggest that the FD variation efficiently describes the structural complexity of the brain and the related cognitive decline. Additionally, the FD efficiently discriminates the two classes achieving 100% accuracy. It is shown that this classification outperforms the currently existing methods in terms of accuracy and the size of the dataset. Therefore, the FD calculation for identifying intracranial brain volume loss could be applied as a potential low-cost personalized imaging biomarker. Furthermore, the possibilities measuring different brain areas and subregions could give robust evidence of the slightest variations to imaging data obtained from repetitive measurements to Physicians and Radiologists.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.