Affinity Chromatography Method for Determination of Binding of Drugs to Melanin and Evaluation of Side Effect Potential of Antipsychotic Agents

The extrapyramidal side effect parameters of typical and atypical antypsychotics were correlated with affinity chromatographic data determined on the melanin-based column. The chromatographic study was performed according to the hypothesis that extrapyramidal symptoms (EPS) as side effects of the use of antipsychotic drugs at clinically effective doses are correlated to the affinity of these drugs to neuromelanin. For that aim the polymerization product of L-DOPA (melanin) was immobilized onto aminopropyl silica and the binding efficiency of melanin towards antipsychotics has been determined. The results indicate that melanin based-column can be used to evaluate the risk of EPS of drug candidates to antipsychotic drug therapy

Friedewald formula may be used to calculate non-HDL-C from LDL-C and TG

BackgroundThe Friedewald formula (FF) was originally designed 50 years ago and has been in use to this day despite better methods for estimating LDL cholesterol (LDL-C). Its success was mainly due to its simplicity. Nowadays most laboratories determine or can determine LDL-C by the direct method. The SCORE2 tables, recommended by the European Society of Cardiology, are based on non-HDL cholesterol (non-HDL-C). To calculate its value, one needs to know the values of total cholesterol (TC) and HDL-C. The presented idea is to use the FF to calculate non-HDL-C based on the values of LDL-C and TG instead of TC and HDL-C.Methods and findingsBased on database of 26,914 laboratory results, covering the complete lipid panel, the error regarding non-HDL-C values calculated in both ways (recommended and proposed) was determined. The average error in the LDL-C value calculated with the FF compared to the LDL-C value measured in the laboratory is 9.77%, while for non-HDL-C the error between the calculated and laboratory-determined value amounts to 8.88%. The proposed transformation of the FF also yields a much lower percentage of error calculations. Both LDL-C and non-HDL-C (calculated) in our material are strongly correlated with LDL-C and non-HDL-C (measured) values of r = 0.965 (p < 0.000) and r = 0.962 (p < 0.000), respectively.ConclusionNon-HDL-C may be calculated based on the values of LDL-C and TG (without the need to determine the levels of TC and HDL-C). The proposed calculation may greatly reduce the cost of testing, given the price of a complete lipid profile

Clinical data analysis with the use of artificial neural networks (ANN) and principal component analysis (PCA) of patients with endometrial carcinoma

AimSatisfactory performance of modern data processing methods, namely principal component analysis (PCA) and artificial neural network (ANN) analysis, has been demonstrated in the prediction of the results of surgical treatment for endometrial carcinoma.Materials/MethodsThe data from 121 patients treated and observed in one oncology unit was retrospectively evaluated. 26 subject and treatment variables were determined for each patient. A matrix of 121×26 data points was subjected to PCA and ANN processing.ResultsThe properly trained ANN was used to predict whether patients belonged to the group of those who survived, or to the group of those who did not survive, a 5-year period. It was found that the prognostic capability of the ANN, regarding the tested set of patients, was very high. Additionally, using the principal component analysis (PCA) method, two principal components, PC1 and PC2 were extracted and accounted, cumulatively, for 23% of the variance in the data analyzed. An apparent clustering of the variables and a clear cut clustering of the patients was observed, which has been interpreted in terms of similarity, or dissimilarity, of the variables and of the patients.ConclusionsIt has been concluded that ANN analysis offers a promising alternative to established methods for the statistical analysis of multivariate data in cancer patients. Also, PCA has been recommended as a new and promising alternative to classical regression analysis of multivariate clinical data. By means of PCA, practically useful systematic information may be extracted from large sets of data, which is otherwise hardly interpretable in comprehensive physical terms. Such information can be of value for general prognosis and for making appropriate adjustments in treatment

Clinical data analysis using artificial neural networks (ANN) and principal component analysis (PCA) of patients with breast cancer after mastectomy

BackgroundExploitation of the several types of information on patient, disease and treatment variables ranging from sociological to genetic ones by means of chemometric analysis was considered and evaluated.AimPerformance of modern data processing methods, namely principal component analysis (PCA) and artificial neural network (ANN) analysis, is demonstrated for predictions of the recurrence of breast cancer in patients treated previously with mastectomy.Materials/MethodsThe data on 718 patients were retrospectively evaluated. 11 subject and treatment variables were determined for each patient. A matrix of 718×11 data points was subjected to PCA and ANN processing. The properly trained ANN was used to predict the patients with recurrence and without recurrence within a 10-year period after mastectomy.ResultsIt was found that the prognostic potency of the trained and validated ANN was reasonably high. Additionally, using the principal component analysis (PCA) method two principal components, PC1 and PC2, were extracted from the input data. They accounted cumulatively for 37.5% of the variance of the data analyzed. An apparent clustering of the variables and patients was observed – these have been interpreted in terms of their similarities and dissimilarities.ConclusionsIt has been concluded that ANN analysis offers a promising implementation to established methods of statistical analysis of multivariable data on cancer patients. On the other hand, PCA has been recommended as an alternative to classical regression analysis of multivariable clinical data. By means of ANN and PCA practically useful systematic information may be extracted from large sets of data, which can be of value for prognosis and appropriate adjustment of the treatment of breast cancer

Prediction of the antimicrobial activity of quaternary ammonium salts against Staphylococcus aureus using artificial neural networks

The study of the quantitative structure–activity relationship (QSAR) on antibacterial activity in a series of new imidazole derivatives against Staphylococcus aureus was conducted using artificial neural networks (ANNs). Antibacterial activity against S. aureus was associated with a number of physicochemical and structural parameters of the examined imidazole derivatives. The designed regression and classification models were useful in determining the antibacterial properties of quaternary ammonium salts against S. aureus. The developed models of artificial neural networks were characterized by high predictability (93.57% accuracy of classification, regression model: training data R = 0.92, test data R = 0.92, validation data R = 0.91). ANNs are considered to be a useful tool in supporting the design of synthesis and further biological experiments in the logical search for new antimicrobial substances. Data analysis using ANNs enables the optimization and reduction of labor costs by narrowing the compound synthesis to achieve the desired properties

A principal component analysis of patients, disease and treatment variables: a new prognostic tool in breast cancer after mastectomy

PurposeTo demonstrate unique information potential of a powerful multivariate data processing method, principal component analysis (PCA), in detecting complex interrelationships between diverse patient, disease and treatment variables and in prognostication of therapy's outcome and response of patients after mastectomy.Patients and MethodsOne hundred-forty-two patients with breast cancer were retrospectively evaluated. The patients were selected from a group of 201 patients who had been treated and observed in the same oncology ward. The selection was based on availability of complete set of information describing each patient. The set consisted of 60 specific data. A matrix of 142 × 60 data points was subjected to PCA using a professional, statistical software (commercially available) and a personal computer.ResultsTwo principal components, PC1 and PC2, were extracted. They accounted for 26% of total data variance. Projections of 60 variables and 142 patients were made on a plane determined by PC1 and PC2. A clear clustering of the variables and of the patients was observed. It was discussed in terms of similarity (dissimilarity) of the variables and the patients, respectively. A strikingly clear separation was demonstrated to exist between the group of patients living over 7 years after mastectomy and the group of deceased patients.ConclusionPCA offers a new promising alternative of statistical analysis of multivariable data on cancer patients. Using the PCA, potentially useful information on both the factors affecting treatment outcome and general prognosis, may be extracted from large data sets

Optimization of Distillation Conditions for Improved Recovery of Phthalides from Celery (Apium graveolens L.) Seeds

The essential oil of celery (Apium graveolens) is characterized by exceptionally high content of alkylphthalides. The mentioned compounds exhibit a number of biological effects (including hypotensive, lipid-lowering, neuroprotective, and cytotoxic) and are also responsible for distinctive aroma of the plant. In the current work, parameters of conventional hydrodistillation (HD) and simultaneous distillation-extraction (SDE) were optimized to obtain phthalide-enriched fractions of celery seeds. A positive correlation was shown between hydrodistillation time and improved essential oil and phthalide yields. The 6-h HD of comminuted seeds yielded essential oil (2.9%) with a higher total phthalide content (51%), as compared to the samples collected after 1.5-3.0 h, which gave 2.4-2.7% of oil containing 24.6-39.2% of total phthalides. The oil contained sedanenolide (36.7%), 3-n-butylphthalide (13.1%), and sedanolide (1.1%). A further increase in the total phthalide content was achieved by omitting the size reduction step prior to hydrodistillation (68.8%) and utilization of the salting-out effect (84.3%). Enzyme pretreatment had a negligible effect on essential oil and phthalide yields. The change of distillation mode from HD to SDE significantly increased the oil yield of whole seeds (from 2.8 to 5.8% for 6 h processing) while maintaining its high phthalide content (62.5%), which translated to an increase in the total phthalide yield from 19.4 to 36.0 g/kg

Original articleAnalysis of selected risk factors of coronary artery disease in a healthy population aged 35-55 years

Background: This report comprises an analysis of results of examinations performed as a part of a cardiovascular disease prevention programme funded by the National Health Fund. Aim: To determine the relationship between body mass index (BMI) and blood pressure, blood glucose and lipid metabolism abnormalities in an ethnically homogeneous population of males and females aged 35 to 55 years with sense of full health without prior diagnosis of cardiovascular disease or diabetes. Methods: The study was carried out in the population of a 175,000-resident city during 9 months, involving 1080 subjects (696 females and 384 males) aged 35 to 55 years (mean age – 47.2±5.4). The following variables were assessed: systolic and diastolic blood pressure, body weight and height, BMI, fasting blood glucose, total cholesterol, triglycerides and HDL cholesterol levels. Results: The studied male population had significantly higher blood pressure, blood glucose, total cholesterol, triglycerides and lower HDL cholesterol levels compared to age-matched females. The female population was found to have a more prominent relationship between increased BMI and blood pressure, blood glucose and serum cholesterol levels than males. Significant differences in favour of females regarding systolic blood pressure, blood glucose and serum cholesterol failed to be present in the obese women subgroup (no statistically significant differences were found compared to obese males). In females aged 45 to 55 years, significantly higher body weight, blood pressure as well as blood glucose, cholesterol and triglyceride levels were observed than in younger women (35-45 years old). Conclusions: Overweight and obesity are associated with increase of arterial blood pressure, lipid metabolism disturbances and elevation of blood glucose. The relationship between BMI and studied risk factors was influenced by age and gender. Menopause is associated with increasing body weight and unfavourable evolution of studied risk factors.Wstęp: Praca stanowi analizę wyników badań uzyskanych w ramach programu profilaktyki chorób układu krążenia finansowanego przez Narodowy Fundusz Zdrowia. Cel: Określenie zależności między wskaźnikiem masy ciała (ang. body mass index, BMI) a wartościami ciśnienia tętniczego krwi, glikemią i zaburzeniami lipidowymi występującymi w jednolitej etnicznie populacji kobiet i mężczyzn od 35. do 55. roku życia, z poczuciem pełnego zdrowia, u których dotychczas nie rozpoznano chorób układu krążenia i cukrzycy. Metodyka: Badanie przeprowadzono w populacji 175-tysięcznego miasta w ciągu 9 mies., obejmując analizą 1080 osób (696 kobiet i 384 mężczyzn) w wieku 35–55 lat (średnia wieku 47,2±5,4). Oceniono pomiary wartości skurczowej i rozkurczowej ciśnienia tętniczego krwi, masę i wysokość ciała, BMI, stężenie glukozy na czczo, cholesterolu całkowitego, trójglicerydów i frakcji HDL cholesterolu. Wyniki: W badanej populacji mężczyzn stwierdzono znamiennie wyższe wartości ciśnienia tętniczego, stężenia glukozy, cholesterolu całkowitego, trójglicerydów i niższe stężenia frakcji HDL cholesterolu w porównaniu z populacją kobiet w tym samym przedziale wiekowym. W populacji kobiet obserwowano bardziej wyraźną niż w grupie mężczyzn zależność między wzrostem wskaźnika BMI a wartościami ciśnienia tętniczego krwi, stężeniem glukozy i cholesterolu w surowicy. Znamienne, korzystne dla płci żeńskiej, różnice w wartościach skurczowego ciśnienia tętniczego krwi, stężenia glukozy i cholesterolu w surowicy krwi nie były widoczne w podgrupie kobiet otyłych (brak istotnych statystycznie różnic w porównaniu z podgrupą otyłych mężczyzn). Wśród kobiet w wieku 45–55 lat obserwowano znamiennie wyższe wartości masy ciała, ciśnienia tętniczego krwi oraz stężenia glukozy, cholesterolu i trójglicerydów w porównaniu z kobietami młodszymi (35–45 lat). Wnioski: Nadwaga i otyłość łączą się ze wzrostem wartości ciśnienia tętniczego krwi, z zaburzeniami lipidowymi i wzrostem stężenia glukozy w surowicy krwi. Związek między wskaźnikiem BMI a badanymi czynnikami ryzyka zależy od wieku i płci badanych osób. Okres menopauzy wiąże się ze wzrostem masy ciała i niekorzystnymi zmianami ocenianych czynników ryzyka

Coping Styles and Alcohol Dependence among Homeless People.

BACKGROUND AND OBJECTIVES:The ways in which homeless individuals cope with stress may differ from those relied upon by the members of the general population and these differences may either be the result or the cause of their living conditions. The aim of the study was to determine the preferred coping style among the homeless and its relationship with alcohol dependence. METHODS:The study included 78 homeless individuals and involved the collection of demographic, sociological, psychological and medical data from each participant. Coping styles relied upon when dealing with stressful situations were assessed using a Polish adaptation of the Coping Inventory for Stressful Situations. Alcohol dependence was assessed using the Michigan Alcoholism Screening Test (MAST) and a quantitative analysis of alcohol consumption. RESULTS:Men accounted for 91.93% of the study population. Nearly 75% of the subjects met the alcohol dependence criterion. Significant relationships were observed between the individual's age, preferred coping style and alcohol consumption level. As an individual's age increased, the use of emotion-oriented coping styles decreased, while an increase in alcohol consumption was associated with a more frequent use of emotion- and avoidance-oriented strategies. CONCLUSIONS:The findings of this study, similarly to those of many other studies of homeless individuals but investigating other areas (e.g. epidemiology of tuberculosis and traumatic injuries), are an exaggerated representation of associations observed in the general population. The results describe a group of people living on the margins of the society, often suffering from extremely advanced alcoholism, with clear evident psychodegradation. The presence of specific ways of coping with stress related to excessive alcohol consumption in this group of individuals may interfere with active participation in support programmes provided for the homeless and may further exacerbate their problems