Socio-economic predictors of uptake of malaria interventions among pregnant women and mothers of under 5 children in Oyo State, Nigeria: a cross-sectional study.

Introduction: socio-economic status (SES), especially for women, influence access to care. This study aimed to determine the relationship between SES and uptake of malaria intervention by pregnant women and non-pregnant mothers of children under 5 years old in Ibadan, Oyo state, Nigeria. Methods: this cross-sectional study was conducted at Adeoyo teaching hospital located in Ibadan, Nigeria. The hospital-based study population included consenting mothers. Data were collected using an interviewer-administered modified validated demographic health survey questionnaire. The statistical analysis involved both descriptive (mean, count, frequency) and inferential statistics (Chi-square, logistic regression). Level of statistical significance was set at 0.05. Results: mean age of the study´s total of 1373 respondents was 29 years (SD: 5.2). Of these, 60% (818) were pregnant. The non-pregnant mothers of children under five years old showed a significantly increased odds (OR: 7.55, 95% CI: 3.81, 14.93) for the uptake of malaria intervention. Within the low SES category, women aged 35 years and above were significantly less likely to utilize malaria intervention (OR=0.08; 95% CI: 0.01-0.46; p=0.005) compared to those younger. In the middle SES, women who have one or two children were 3.51 times more likely than women with three or more children to utilize malaria intervention (OR=3.51; 95% CI: 1.67-7.37; p=0.001). Conclusion: the findings provide evidence that age, maternal grouping, and parity within the SES category can significantly impact on uptake of malaria interventions. There is a need for strategies to boost the SES of women because they play significant roles in the wellbeing of members of the home.

Statistical Sequential Experimentation: Preliminary Mixed Factorial Design, I-Optimal Mixture Design Then Finally Novel Design Space Expansion for Optimization of Tazarotene Cubosomes.

Objective: This study aims to illustrate the potential of sequential experimentation for statistically scientific based optimization of Tazarotene (TAZA) cubosomes. Methods: Hot melt emulsification method was used for cubosomes preparation. A preliminary (3.2) mixed factorial design (MFD) was conducted to choose suitable types of stabilizer and surfactant that maximize entrapment efficiency (EE) and minimize particle size (PS). These chosen stabilizer and surfactant were to be used in the statistical design proposed for optimization of TAZA cubosomes (I-optimal mixture design) (IOMD). Glyceryl monooleate (GMO), stabilizer and surfactant amounts were the three mixture components (MixCs) studied in that design. Responses (EE, PS and drug percent released after 24 hours (Q24h)) were statistically analyzed. Numerical optimization using desirability function based on different responses' importance was used to find an IOMD-optimized formulation (IOMD-OF) with the predetermined characters. Then, a novel statistical methodology of design space expansion was adopted to enhance Q24h. Suitable models to express EE, PS and Q24h were elucidated over the expanded mixture design (EMD) space. Validity of derived models was verified via prediction intervals and percent deviations of actual values from predicted ones for all the EMD design points. EMD was then navigated to find EMD-OF. Results: Analysis of MFD showed that Pluronic-F68 and polyvinyl alcohol were the best stabilizer and surfactant to be used. First stage optimization after IOMD analysis led to a formulation with unsatisfactory Q24h of 58.8%. After design space expansion adoption, re-analysis and re-optimization, a satisfactory EMD-OF having EE of 82.1%, PS of 273.0 nm and Q24h of 68.8% was found. Conclusion: Statistical sequential experimentation with the novel design space expansion approach proved to be a successful paradigm for enhancing TAZA cubosomes optimization. Thus, this paradigm is expected to have promising future applications in various pharmaceutical formulations optimization.

KAP-COVIDGLOBAL: a multinational survey of the levels and determinants of public knowledge, attitudes and practices towards COVID-19.

OBJECTIVE: The adherence to public health recommendations to control COVID-19 spread is influenced by public knowledge, attitudes and practices (KAP). We performed this cross-sectional study to assess the levels and determinants of public KAP towards COVID-19 in a large, multinational sample. DESIGN: Cross-sectional study (survey). SETTING: The questionnaire was distributed to potential respondents via online platforms. PARTICIPANTS: 71 890 individuals from 22 countries. METHODS: We formulated a four-section questionnaire in English, followed by validation and translation into seven languages. The questionnaire was distributed (May to June 2020) and each participant received a score for each KAP section. RESULTS: Overall, the participants had fair knowledge (mean score: 19.24±3.59) and attitudes (3.72±2.31) and good practices (12.12±1.83) regarding COVID-19. About 92% reported moderate to high compliance with national lockdown. However, significant gaps were observed: only 68.2% knew that infected individuals may be asymptomatic; 45.4% believed that antibiotics are an effective treatment; and 55.4% stated that a vaccine has been developed (at the time of data collection). 71.9% believed or were uncertain that COVID-19 is a global conspiracy; 36.8% and 51% were afraid of contacting doctors and Chinese people, respectively. Further, 66.4% reported the pandemic had moderate to high negative effects on their mental health. Female gender, higher education and urban residents had significantly (p≤0.001) higher knowledge and practice scores. Further, we observed significant correlations between all KAP scores. CONCLUSIONS: Although the public have fair/good knowledge and practices regarding COVID-19, significant gaps should be addressed. Future awareness efforts should target less advantaged groups and future studies should develop new strategies to tackle COVID-19 negative mental health effects.

Sustained ocular delivery of Dorzolamide-HCl via proniosomal gel formulation: in-vitro characterization, statistical optimization, and in-vivo pharmacodynamic evaluation in rabbits.

Glaucoma is the second cause of blindness worldwide. Frequent administration of traditional topical dosage forms may lead to patient incompliance and failure of treatment. Our study aims to formulate proniosomal gel formulations that sustain the release of the water-soluble anti-glaucoma drug Dorzolamide-HCl (Dorz). Proniosomal gel formulations were prepared using coacervation phase separation method according to a 52 full factorial design. The effects of Cholesterol and surfactant (Span 40) amounts (independent variables) on the percentage entrapment efficiency (EE%), particle size (PS), and the percent of drug released after 8 h (Q8h) (dependent variables (DVs)) were investigated. An optimized formulation (OF) was chosen based on maximizing EE% and Q8h and minimizing PS. An intraocular pressure (IOP) pharmacodynamic study was performed in rabbits to evaluate the in-vivo performance of the OF-gel compared to the marketed Trusopt® eye drops. The results showed that the independent variables studied significantly affected EE%, PS, and Q8h. OF was the one containing 60 mg Cholesterol and 540 mg Span 40. It had desirability of 0.885 and its actually measured DVs deviated from the predicted ones by a maximum of 4.8%. The in-vivo pharmacodynamic study showed that OF could result in higher reduction in IOP, significantly sustain that reduction in IOP and increase Dorz bioavailability compared to Trusopt® eye drops. Thus the OF-gel is very promising for being used in glaucoma treatment.

Image segmentation and particles classification using texture analysis method

Introduction: Ingredients of oily fish include a large amount of polyunsaturated fatty acids, which are important elements in various metabolic processes of humans, and have also been used to prevent diseases. However, in an attempt to reduce cost, recent developments are starting a replace the ingredients of fish oil with products of microalgae, that also produce polyunsaturated fatty acids. To do so, it is important to closely monitor morphological changes in algae cells and monitor their age in order to achieve the best results. This paper aims to describe an advanced vision-based system to automatically detect, classify, and track the organic cells using a recently developed SOPAT-System (Smart On-line Particle Analysis Technology), a photo-optical image acquisition device combined with innovative image analysis software. Methods The proposed method includes image de-noising, binarization and Enhancement, as well as object recognition, localization and classification based on the analysis of particles’ size and texture. Results The methods allowed for correctly computing cell’s size for each particle separately. By computing an area histogram for the input images (1h, 18h, and 42h), the variation could be observed showing a clear increase in cell. Conclusion The proposed method allows for algae particles to be correctly identified with accuracies up to 99% and classified correctly with accuracies up to 100%.