Short-Chain Fatty Acids Are Antineoplastic Agents

Human diet contains a mixture of saturated and unsaturated fatty acids. These are either long, medium or short chain fatty acids. As commonly believed, all fatty acids are not detrimental to human health. In addition to energy reserves, long chain fatty acids are known as acylating agents for many biomolecules such as cholesterol, terpenoids as well as steroid hormones. They are also involved in acylation of polyphenols such as flavonoids making them palatable for better absorption and biological activities. Polyunsaturated fatty acids (PUFAs) are known for their numerous beneficial health effects including cancer and inflammation. PUFA, particularly ω3 fatty acids, have attracted attention as anticancer agents and particularly for colorectal cancer. PUFAs exhibit immunomodulatory activities controlling inflammosome and are used as adjuvants together with standard anticancer drugs. A reciprocal interaction of short chain fatty acids with PUFAs has been suggested for their anticancer activities. Thus, in colon cancer cells, sodium butyrate (NaB) interacts with docosahexaenoic acid inducing cell differentiation or catalyze apoptosis. These results encouraged us to investigate NaB, a C4 acid, as an adjuvant to standard proteasome inhibitors. Our results show that NaB sensitizes colon cancer cell lines for treatment with proteasome inhibitors

Probing the Nature of Pakistan’s Money Supply

Historic development of monetary economics encompasses two different school of thoughts on functioning of central banks in management of money supply and the level of economic activities, indirectly. “Monetarists” argue that “Money supply is exogenously determined” while “Post Keynesians” claim endogenously determined nature of money supply. In order to explore the real scenario of endogenous nature of money supply, there is a dire need of empirical studies covering different economies at different stages of development. the present study was planned to examine nature of money supply in Pakistan. study period covered a span ranging from 1995 to 2019 and Semi-annual data is used for analysis. Three hypothesis are tested in this study. i.e. accomodationists view, structuralists view and liquidity preference view. variables of the study comprised of monetary base, bank credit, money multiplier, M2 money supply and money income. Co-integration and error correction mechanism (ECM) were applied for determining long run relationships and short run deviations. results revealed that structuralists and liquidity preference view both hold true in case of Pakistan. Liquidity preference view holds true completely; whereas structuralists view was partially supported by the results of our study. &nbsp

Water deficit-induced regulation of growth, gas exchange, chlorophyll fluorescence, inorganic nutrient accumulation and antioxidative defense mechanism in mungbean [Vigna radiata (L.) Wilczek]

The study was conducted to appraise the influence of water deficit conditions on growth, yield, gas exchange characteristics, and antioxidative defense system in two mungbean [Vigna radiata (L.) Wilczek) lines, 97001 and 97012. The plants of both lines were grown for 30 days under normal natural conditions, after which time two drought regimes [control (well-watering and 60% field capacity)] were applied. Data for various attributes were recorded after 30 days of drought application while at maturity, yield attributes were recorded. Water deficit conditions caused a considerable reduction in growth attributes, net CO2 assimilation rate, stomatal conductance, electron transport ratio, total phenolics, leaf Ca2+ and yield attributes. Imposition of water deficit conditions significantly increased leaf tocopherol contents and activity of catalase in both mungbean lines. Both lines showed a considerable variation in growth attributes, the line 97001 being better in performance compared with 97012 under water deficit conditions

The impact of arterial input function determination variations on prostate dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic modeling: a multicenter data analysis challenge, part II

This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate Ktrans (volume transfer rate constant), ve (extravascular, extracellular volume fraction), kep (efflux rate constant), and τi (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T1 values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for Ktrans, ve, kep, and τi, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in Ktrans and ve (wCV = 0.50 and 0.10, respectively), but had smaller effects on kep and τi (wCV = 0.39 and 0.22, respectively). kep is less sensitive to AIF variation than Ktrans, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τi parameter may have advantages over the conventional PK parameters in a longitudinal study

Gender dynamics in modern agricultural value chains

Presented by Aneela Afzal (Arid Agriculture University), as part of the Annual Scientific Conference hosted by the University of Canberra and co-sponsored by the University of Canberra, the Australian Centre for International Agricultural Research (ACIAR) and CGIAR Collaborative Platform for Gender Research, Canberra, Australia, April 2-4, 2019

An Assessment and Control of AFM₁ in Milk and Main Dairy Products in Lahore, Pakistan

The main objective of this study is to investigate the presence of Aflatoxin M1 (AFM1) in local and processed milk and main dairy products available in Lahore. Total 60 milk samples and 120 samples of dairy products including butter (n = 30), cheese (n = 30), cream (n = 30), and yogurt (n = 30) were collected. Milk samples were collected from 3 different sources i.e. unprocessed milk from local milk shop (n = 20) and a local dairy farm (n = 20), and processed milk sample from a commercial shop (n = 20) while samples of each dairy product were also different i.e. processed (n = 15) and unprocessed (n = 15). Milk samples were analyzed using kit method while dairy product samples were analyzed by high performance liquid chromatography (HPLC) technique equipped with fluorescence detector (HPLC-FLD) followed by immunoaffinity column clean up. In second phase of the study, efficacy of three different toxin binders was compared and analyzed. The results showed that AFM1 was detected in 16.7% of processed butter samples, 33.3% of processed cheese samples, 13.3% of local cream samples and 26.6% of processed yogurt samples and these samples exceeds European Union (EU) permissible limits of 0.05 ppb with mean concentration 0.090 ± 0.180 μg/kg and 0.000 ± 0.000 μg/kg for processed and local butter samples, 0.350 ± 0.606 μg/kg and 0.000 ± 0.000 μg/kg for processed and local cheese samples, 0.000 ± 0.000 μg/kg and 0.542 ± 1.085 μg/kg for processed and local cream samples and 0.552 ± 1.001 μg/kg and 0.000 ± 0.000 μg/kg for processed and local yogurt samples, respectively. Moreover, milk samples showed highest AFM1 (62%) in local unprocessed dairy farm followed by samples from local milk shop (51%) and commercial dairy farm (31%). In addition, therapeutic efficacy of three different types of toxin binders showed that the toxin binder which had yeast wall (75%) and algae (25%) is the best to control AFM1 under field conditions. Overall, results of this study are valuable for dairy farmers on one hand and law enforcement authorities on the other to comprehend and control AFM1 problem in milk and main dairy products

Congenital hypothyroidism in neonates

Context: Congenital hypothyroidism (CH) is one of the most common preventable causes of mental retardation in children and it occurs in approximately 1:2,000-1:4,000 newborns. Aims and Objectives: The aim of this study is to determine the frequency of CH in neonates. Settings and Design: This cross-sectional study was conducted in neonatal units of the Department of Pediatrics Unit-I, King Edward Medical University/Mayo Hospital, Lahore and Lady Willington Hospital Lahore in 6 months (January-June 2011). Materials and Methods: Sample was collected by non-probability purposive sampling. After consent, 550 newborn were registered for the study. Demographic data and relevant history was recorded. After aseptic measures, 2-3 ml venous blood analyzed for thyroid-stimulating hormone (TSH) level by immunoradiometric assay. Treatment was started according to the individual merit as per protocol. Statistical Analysis Used: Data was analyzed by SPSS 17 and Chi-square test was applied to find out the association of CH with different variables. Results: The study population consisted of 550 newborns. Among 550 newborns, 4 (0.8%) newborns had elevated TSH level. CH had statistically significant association with mother′s hypothyroidism (P value 0.000) and mother′s drug intake during the pregnancy period (P value 0.013). Conclusion: CH is 0.8% in neonates. It has statistically significant association with mother′s hypothyroidism and mother′s drug intake during pregnancy

Early Prediction of Breast Cancer Therapy Response using Multiresolution Fractal Analysis of DCE-MRI Parametric Maps

We aimed to determine whether multiresolution fractal analysis of voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps can provide early prediction of breast cancer response to neoadjuvant chemotherapy (NACT). In total, 55 patients underwent 4 DCE-MRI examinations before, during, and after NACT. The shutter-speed model was used to analyze the DCE-MRI data and generate parametric maps within the tumor region of interest. The proposed multiresolution fractal method and the more conventional methods of single-resolution fractal, gray-level co-occurrence matrix, and run-length matrix were used to extract features from the parametric maps. Only the data obtained before and after the first NACT cycle were used to evaluate early prediction of response. With a training (N = 40) and testing (N = 15) data set, support vector machine was used to assess the predictive abilities of the features in classification of pathologic complete response versus non-pathologic complete response. Generally the multiresolution fractal features from individual maps and the concatenated features from all parametric maps showed better predictive performances than conventional features, with receiver operating curve area under the curve (AUC) values of 0.91 (all parameters) and 0.80 (Ktrans), in the training and testing sets, respectively. The differences in AUC were statistically significant (P < .05) for several parametric maps. Thus, multiresolution analysis that decomposes the texture at various spatial-frequency scales may more accurately capture changes in tumor vascular heterogeneity as measured by DCE-MRI, and therefore provide better early prediction of NACT response

DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response

This study investigates the effectiveness of hundreds of texture features extracted from voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps for early prediction of breast cancer response to neoadjuvant chemotherapy (NAC). In total, 38 patients with breast cancer underwent DCE-MRI before (baseline) and after the first of the 6–8 NAC cycles. Quantitative pharmacokinetic (PK) parameters and semiquantitative metrics were estimated from DCE-MRI time-course data. The residual cancer burden (RCB) index value was computed based on pathological analysis of surgical specimens after NAC completion. In total, 1043 texture features were extracted from each of the 13 parametric maps of quantitative PK or semiquantitative metric, and their capabilities for early prediction of RCB were examined by correlating feature changes between the 2 MRI studies with RCB. There were 1069 pairs of feature–map combinations that showed effectiveness for response prediction with 4 correlation coefficients >0.7. The 3-dimensional gray-level cooccurrence matrix was the most effective feature extraction method for therapy response prediction, and, in general, the statistical features describing texture heterogeneity were the most effective features. Quantitative PK parameters, particularly those estimated with the shutter-speed model, were more likely to generate effective features for prediction response compared with the semiquantitative metrics. The best feature–map pair could predict pathologic complete response with 100% sensitivity and 100% specificity using our cohort. In conclusion, breast tumor heterogeneity in microvasculature as measured by texture features of voxel-based DCE-MRI parametric maps could be a useful biomarker for early prediction of NAC response

Evaluation of Soft Tissue Sarcoma Response to Preoperative Chemoradiotherapy Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging

This study aims to assess the utility of quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) parameters in comparison with imaging tumor size for early prediction and evaluation of soft tissue sarcoma response to preoperative chemoradiotherapy. In total, 20 patients with intermediate- to high-grade soft tissue sarcomas received either a phase I trial regimen of sorafenib + chemoradiotherapy (n = 8) or chemoradiotherapy only (n = 12), and underwent DCE-MRI at baseline, after 2 weeks of treatment with sorafenib or after the first chemotherapy cycle, and after therapy completion. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed using the Shutter-Speed model. After only 2 weeks of treatment with sorafenib or after 1 chemotherapy cycle, Ktrans (rate constant for plasma/interstitium contrast agent transfer) and its percent change were good early predictors of optimal versus suboptimal pathological response with univariate logistic regression C statistics values of 0.90 and 0.80, respectively, whereas RECIST LD percent change was only a fair predictor (C = 0.72). Post-therapy Ktrans, ve (extravascular and extracellular volume fraction), and kep (intravasation rate constant), not RECIST LD, were excellent (C > 0.90) markers of therapy response. Several DCE-MRI parameters before, during, and after therapy showed significant (P < .05) correlations with percent necrosis of resected tumor specimens. In conclusion, absolute values and percent changes of quantitative DCE-MRI parameters provide better early prediction and evaluation of the pathological response of soft tissue sarcoma to preoperative chemoradiotherapy than the conventional measurement of imaging tumor size change