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Within the framework of the valorization of natural resources, a characterization of the biochemical composition of the edible parts of Adansonia Digitata is applied. The antibacterial effect against bacteria is also realized and compared to some synthetic antibiotics.

The biochemical characterization is carried out according to the norms of the French Association of Normalization, methods of Association of Official Analytical Chemists (AOAC International) and gas chromatography (GC). The antibacterial activity is tested by disk diffusion on a solid medium. Parametric tests are used to compare the differences between groups and heat maps to show the expression of the mean inhibitions according to the studied parameters. Multivariate logistic modeling is applied to study the effect of extracts and antibiotics on bacteria.

Biochemical characterization showed a variable importance of proteins, fibers and total sugars, with the presence of highly desired fatty acids such as palmitic, oleic, stearic, linoleic and a-linolenic acids. This gives the tested parts important energy values, especially in the seeds very rich in fatty acids. Methanol proved to be a better extraction solvent than dichloromethane. Antibacterial activity showed that pulp and leaves extracted with methanol had quite similar inhibitory activities against Enterococcus faecalis ATCC29212 and that this effect was better than some antibiotics. Multivariate analysis showed that the leaves had a similar effect to antibiotics, and a significant effect against Staphylococcus aureus ATCC29213.

This important activity and the attractive nutritional value of this plant could justify its extensive use in the traditional pharmacopoeia.

This review aims to provide synoptic documentation on acclaimed anecdotal plant-based remedies used by Latin America and the Caribbean (LAC) communities to manage COVID-19. The theoretical approaches that form the basis for using the anecdotally claimed phytotherapies were reviewed against current scientific evidence.

In this paper plant-based remedies for managing COVID-19 were searched on social and print media to identify testimonies of people from different communities in LAC countries. Information was extracted, evaluated and reviewed against current scientific evidence based on a literature search from databases such as Journal Storage (JSTOR), Excerpta Medica Database (EMBASE), SpringerLink, Scopus, ScienceDirect, PubMed, Google Scholar and Medline to explore the scientific basis for anecdotal claims.

A total of 23 medicinal plants belonging to 15 families were identified as phytotherapies used in managing COVID-19 in LAC communities.

The plant-based remedies contained valuable phytochemicals scientifically reported for their anti-inflammatory, antiviral, antioxidant and anticancer effects. Anecdotal information helps researchers investigate disease patterns, management and new drug discoveries. The identified acclaimed plant-based remedies are potential candidates for pharmacological evaluations for possible drug discovery for future pandemics.

The purpose of the study was to develop a powder shampoo with antioxidant attributes.

Dry shampoo compositions were formulated containing alpha olefin sulfonate (AOS), sodium cocoyl isethionate (SCI), microcrystalline cellulose, mannitol, carboxymethyl cellulose, maltodextrin and sodium benzoate with or without extract of Cinnamomum zeylanicum bark. Cinnamon extract was chosen for this study owing to its ubiquitously known antioxidant attributes. The formulations were tested for detergency action and antioxidant potential in vitro.

Cinnamomum zeylanicum extract exhibited noticeable antioxidant activity in vitro. The authors observed that addition of the bark extract to the shampoo formulation was associated with remarkable increase in total phenolic content, total antioxidant activity and radical scavenging activity without any effect on detergency action.

This preliminary study provides a powder shampoo formulation which exhibits antioxidant attributes as a result of incorporation of cinnamon bark extract. Clinical efficacy of the formulation remains to be tested.

Owing to the powder format of the shampoo, the formulation can be manufactured with ease and economically. Functionalizing the formulation with enhancement of antioxidant activity by incorporation of cinnamon bark extract may be associated with beneficial clinical outcomes, which remains to be tested.

The proposed formulation may be stored and sold in eco-friendly packing material, thus could pave the way for reducing the burden of plastic consumption by the shampoo industry.

The present work demonstrates that incorporation of cinnamon bark extract to a powder shampoo formulation, containing AOS and SCI as principle surfactants, significantly enhances its antioxidant attributes.

This study aims to explore the traditional plant dyeing of Xinjiang Atlas silk fabrics, providing references for the comprehensive utilization of plant dyes in intangible cultural heritage.

The focus of this study is on dyeing experiments of Atlas silk fabrics using safflower extracts, constrained by regional resources. Safflower dry flowers grown in Xinjiang were selected, rinsed with pure water and rubbed. Yellow pigments were removed by adding edible white vinegar. Red pigments from safflower were extracted using an alkaline solution prepared with Populus euphratica ash, a special product of Xinjiang. The extraction rate was analyzed under varying material-to-liquor ratios, pH values, times and temperatures. Direct dyeing process experiments were conducted to obtain different colorimetric L, a, b and K/S values for comparison. Samples with good color development were selected to test the impact of dyeing immersions on color development, and their color fastness, UV protection and antibacterial effects were verified.

The dyeing experiments on silk fabrics confirmed their UV protection capabilities and antibacterial properties, demonstrating effectiveness against E. coli and Staphylococcus aureus. As a major producer of safflower, Xinjiang underscores the significance of safflower as an essential plant dyes on the Silk Road. This study reveals its market potential and suitability for use in the plant dyeing process of Atlas silk, producing vibrant red and pink colors.

The experiments indicated that after removing yellow pigments, the highest extraction rate of red pigment from safflower was achieved at a pH value of 10–11, a temperature of 30°C and an extraction time of 40 min. The best bright red color effect with strong color fastness was obtained with a material-to-liquor ratio of 1:20, a temperature of 40°C and three immersions. The best light pink color effect with strong color fastness was a material-to-liquor ratio of 1:80, a temperature of 30°C and two immersions.

In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

This study aims to evaluate the effect of Piper betle leaf extract towards the acute-lethal toxicity, LC50 of red Nile tilapia juveniles (Oreochromis niloticus).

Ten red Nile tilapia juveniles per tank (in triplicate) were used as an experimental fish for the LC50 bioassay. Five different concentrations of P. betle extract; 80 ppm, 90 ppm, 100 ppm, 110 ppm and 120 ppm, were tested on the red Nile tilapia juveniles and one tank was acting as a control. The progress of the LC50 and lethal time of fish mortality were observed and recorded within the random interval of 96 h. The value for LC50 was determined as 100 ppm of P. betle leaf extract. Higher number of fish mortalities was observed when concentration higher than 100 ppm was tested on to the red Nile tilapia juveniles.

Data obtained shows that the P. betle concentration of 120 ppm accelerated the fish mortality period.

However, adaption of P. betle extract occurred after 50 h, as there was no fish mortality observed within the time.

The purpose of this paper is to investigate the health and medicinal importance of bush tea (Athrixia phylicoides DC) and special tea (Monsonia burkeana Planch. ex Harv), two of Southern African indigenous herbal teas.

The two herbal teas, A. phylicoides and M. burkeana were extracted individually and in combined ratios for analysis. The phenolic content was determined and the different phenolic compounds were identified using thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC). The anti-diabetic activity of the teas was determined by evaluating the inhibition of both α-amylase and α-glucosidase in vitro. The anti-proliferative activity was measured on human cervical cancer (HeLa) cell line using the MTT (3-(4,5-dimethylthiazol-2-yl)2,5-diphenyltetrazolium) assay.

Gallic acid, chlorogenic acid and quercetin were identified to be present in significant quantities by TLC. The HPLC quantified the presence of catechin (1.567 mg/g) and chlorogenic acid (1.862 mg/g) in special tea while chlorogenic acid (1.288 mg/g) was present in bush tea. Bush tea and special tea expressed significant levels of phenolic content and high antioxidant activities. Special tea (S100) expressed high inhibition of α-amylase, α-glucosidase and HeLa cell line proliferation when compared to bush tea (B100).

Both bush tea and special tea could provide an alternative for treatment and management of both diabetes and cervical cancer. However, future studies are needed to investigate their synergistic effect with a wide range of other commercial herbal teas.

The establishment of partnerships between companies, government and universities aims to enhance innovation and the technological development of institutions. The biotechnology sector has grown in recent years mainly driven by its cooperative business model. Compared to other countries, this sector is slowly advancing in Brazil, with delays in science, technology and innovation, especially in the private sector. This paper aims to examine, through social network analysis, the collaborative networks between institutions that filed patents in biotechnology – medicinal preparations from plants – whose inventions had Brazil as the priority country.

The study of technological cooperation using patent documents is a reliable approach as they serve as good indicators of the interactions between organizations that focus on innovation and development of new product. Social network analysis of cooperation networks helps to understand the connections between patent assignees, and how they establish relationships.

Results show that public universities are the institutions that most deposit patents, as well as those that co-operate the most, especially Universidade of Campinas. The study also reveals the critical role of Research Support Agencies in stimulating research and technological development, which result in new technologies.

The study applied the social network analysis to provide an overview of the interactions among Brazilian institutions with the purpose of helping in decision-making and inciting public policies to leverage the biotechnology sector.

This study aims to analyze the use of discourse to solve issues related to coordination between advocacy coalitions in processes of gradual and transformative institutional change related to public policies.

Theoretical background is based on the advocacy coalition framework (ACF), new discursive institutionalism and critical discourse analysis theories. The research examines shorthand notes of public hearings held in the Brazilian Chamber of Deputies and the Federal Senate between 1999 and 2012, carrying out a case study on Belo Monte hydroelectric power plant. The speech extracts were categorized according to the modes of operation of ideology and typical strategies of symbolic construction proposed by Thompson (1995).

The results suggest that the discourse can be an instrument of internal coordination and between coalitions that share beliefs about a policy, as in the case of Belo Monte. Potentially existing coalitions define their identities and set positions on controversial issues, aligning interests and expectations. In the case studied, the modes of operation of ideology verified as instruments of the coalitions were dissimulation, reification, fragmentation, unification and legitimation.

The paper represents a unique analysis of the modes of operation of ideology (Thompson, 1999) in the case of Belo Monte. In addition, the paper aims to contribute to the New Discursive Institutionalism and to the ACF when it uses the critical discourse analysis to articulate a method to analyze the use of the Discourse by the coalitions. In fact, such an approach integrating the ACF, the New Discursive Institutionalism and the critical discourse analysis is something original. Finally, it also addresses a gap in ACF: issues related to advocacy coalition coordination.

Attentive readers linked to organizations working on infrastructure and environmental policies can benefit from the results by envisaging the deliberate manipulation of typical symbolic construction strategies and general modes of operation of ideology.

The study sheds light on the daily and behind-the-scenes disputes among stakeholders who are interested in a certain public policy. It may draw attention to the access and professional use of the shorthand notes of the hearings held at the National Congress.

This paper aims to fill a gap pointed out by Jenkins-Smith et al. (2014) regarding problems of coordination of advocacy coalitions. In addition, it innovates by using critical discourse analysis as a methodological reference in ACF empirical studies. In addition, this work continues a trajectory of two other previously published studies dealing with the same phenomenon: a theoretical essay and a case study.

Plant cultivation holds a pivotal role in agriculture, necessitating precise disease identification for the overall health of plants. This research conducts a comprehensive comparative analysis between two prominent deep learning algorithms, convolutional neural network (CNN) and DenseNet121, with the goal of enhancing disease identification in tomato plant leaves.

The dataset employed in this investigation is a fusion of primary data and publicly available data, covering 13 distinct disease labels and a total of 18,815 images for model training. The data pre-processing workflow prioritized activities such as normalizing pixel dimensions, implementing data augmentation and achieving dataset balance, which were subsequently followed by the modeling and testing phases.

Experimental findings elucidated the superior performance of the DenseNet121 model over the CNN model in disease classification on tomato leaves. The DenseNet121 model attained a training accuracy of 98.27%, a validation accuracy of 87.47% and average recall, precision and F1-score metrics of 87, 88 and 87%, respectively. The ultimate aim was to implement the optimal classifier for a mobile application, namely Tanamin.id, and, therefore, DenseNet121 was the preferred choice.

The integration of private and public data significantly contributes to determining the optimal method. The CNN method achieves a training accuracy of 90.41% and a validation accuracy of 83.33%, whereas the DenseNet121 method excels with a training accuracy of 98.27% and a validation accuracy of 87.47%. The DenseNet121 architecture, comprising 121 layers, a global average pooling (GAP) layer and a dropout layer, showcases its effectiveness. Leveraging categorical_crossentropy as the loss function and utilizing the stochastic gradien descent (SGD) Optimizer with a learning rate of 0.001 guides the course of the training process. The experimental results unequivocally demonstrate the superior performance of DenseNet121 over CNN.