ANTIMICROBIAL POTENTIAL OF HERBAL AND CHEMICAL NEONATAL EYE DROPS

Objective: The present study focuses on exploring the antimicrobial potential of chemical (Tobastar and natamycin) and herbal eye drops (Itone) which are specifically preferred against neonatal eye infections.Methods: Well diffusion method (for testing the antimicrobial potential of selected eye drops against different bacterial and fungal strains), minimum inhibitory concentration (MIC) (broth dilution method) for detecting the MIC effective against various strains taken into consideration.Results: The results indicated that Itone and Tobastar are effective against bacterial strains, thus highlighting the importance of these two eye drops against bacterial infections, whereas natamycin is effective against fungal infection.Conclusion: It may be concluded that the herbal eye drop (Itone) and the chemical eye drop (Tobastar) are effective against bacterial infections. The components such as neem, tulsi, kapur, and honey in herbal composition possess good antibacterial activity confirming the great potential of bioactive compounds and are useful for the growth inhibition of the carcinogenic bacterium. The alkaloids, flavonoids and saponins are based on antibiotic principles and are actually the defensive mechanisms of the plant against pathogens and chemical eye drop, that is, natamycin is effective against fungal infections, which may be due to the presence of polyene antifungal agent which works against fungal infections. There is a need to optimize the blending of the different herbal and chemical components to form a single effective antimicrobial formulation (more of herbal component and less chemical components) against neonatal infections

Complete genome sequence of an isolate of leek yellow stripe virus from garlic in India

Not AvailableThe complete genome sequence of leek yellow stripe virus (LYSV) isolate AC-50 from garlic in India was determined and the predicted amino acid (aa) sequence was analyzed. The LYSV RNA genome is 10,131 nucleotides (nt) long excluding the poly(A) tail (KP168261) and has a large open reading frame (ORF) encoding a putative polyprotein of 3152 aa with conserved motifs typical of members of the genus Potyvirus in the family Potyviridae. The pretty interesting Potyviridae ORF (PIPO) coding region was identified in the P3 coding region. LYSV isolate AC-50 shares maximum nt and aa sequence identity of 79.9% and 87.2% with a LYSV isolate from Australia (HQ258895) at the full genome and polyprotein level, respectively, and clusters with clade II isolates from China, Mexico, Australia, Brazil and Spain. The P1 coding region of isolate AC-50 was highly variable with an identity range of 48.9- 70.9% with other LYSV isolates and a deletion of 204 nt compared to Japanese and Australian isolates. The ratio of nonsynonymous (dN) and synonymous (dS) polymorphic sites suggested that purifying selection dominates in the evolution of LYSV and the mean dN/dS ratio was highest for P1, confirming that this coding region is under less evolutionary constraints

Multi-Object Tracking in Heterogeneous environments (MOTHe) for animal video recordings

Aerial imagery and video recordings of animals are used for many areas of research such as animal behaviour, behavioural neuroscience and field biology. Many automated methods are being developed to extract data from such high-resolution videos. Most of the available tools are developed for videos taken under idealised laboratory conditions. Therefore, the task of animal detection and tracking for videos taken in natural settings remains challenging due to heterogeneous environments. Methods that are useful for field conditions are often difficult to implement and thus remain inaccessible to empirical researchers. To address this gap, we present an open-source package called Multi-Object Tracking in Heterogeneous environments (MOTHe), a Python-based application that uses a basic convolutional neural network for object detection. MOTHe offers a graphical interface to automate the various steps related to animal tracking such as training data generation, animal detection in complex backgrounds and visually tracking animals in the videos. Users can also generate training data and train a new model which can be used for object detection tasks for a completely new dataset. MOTHe doesn’t require any sophisticated infrastructure and can be run on basic desktop computing units. We demonstrate MOTHe on six video clips in varying background conditions. These videos are from two species in their natural habitat—wasp colonies on their nests (up to 12 individuals per colony) and antelope herds in four different habitats (up to 156 individuals in a herd). Using MOTHe, we are able to detect and track individuals in all these videos. MOTHe is available as an open-source GitHub repository with a detailed user guide and demonstrations at: https://github.com/tee-lab/MOTHe-GUI

Examining a theoretical model of eco-anxiety on consumers' intentions towards green products

Given the current levels of pollution and global warming concerns, consumers started to be more and more involved with environmental issues, becoming more anxious regarding the state of natural resource depletion. Thus, this research aims to examine the concept of eco-anxiety among consumers who are aware of the repercussions of the current environmental complexities, analysing how or to what extent it affects them, bearing in mind that individuals may tend to escape from stressful environmental issues. A conceptual model will be tested using data from consumers of two countries representing very different regions and socioeconomic contexts: India and Italy. An online self-administered questionnaire was distributed in India and Italy between February and March 2022. Employing partial least squares structural equation modelling (PLS-SEM), a sample of 557 individuals was collected (316 from India; 241 from Italy). The study examined the measurement model to assess validity and reliability, as well as the structural model to test the hypotheses. The results indicate that consumers of India and Italy tend to avoid thinking about environmental crises trying to normalise their plight. As observed, eco-anxiety positively influences emotional dissonance, and escapism is positively related to this construct, but intentions to buy green products are found to be insignificant. Practical implications were drawn for policymakers and practitioners, indicating different orientations according to the region

Strategies to increase the demand for childhood vaccination in lowand middle-income countries : a systematic review and meta-analysis

Objective To investigate which strategies to increase demand for vaccination are effective in increasing child vaccine coverage in low- and middle-income countries. Methods We searched MEDLINE, EMBASE, Cochrane library, POPLINE, ECONLIT, CINAHL, LILACS, BDSP, Web of Science and Scopus databases for relevant studies, published in English, French, German, Hindi, Portuguese and Spanish up to 25 March 2014. We included studies of interventions intended to increase demand for routine childhood vaccination. Studies were eligible if conducted in low- and middle-income countries and employing a randomized controlled trial, non-randomized controlled trial, controlled before-and-after or interrupted time series design. We estimated risk of bias using Cochrane collaboration guidelines and performed random-effects meta-analysis. Findings We identified 11 studies comprising four randomized controlled trials, six cluster randomized controlled trials and one controlled before-and-after study published in English between 1996 and 2013. Participants were generally parents of young children exposed to an eligible intervention. Six studies demonstrated low risk of bias and five studies had moderate to high risk of bias. We conducted a pooled analysis considering all 11 studies, with data from 11 512 participants. Demand-side interventions were associated with significantly higher receipt of vaccines, relative risk (RR): 1.30, (95% confidence interval, CI: 1.17–1.44). Subgroup analyses also demonstrated significant effects of seven education and knowledge translation studies, RR: 1.40 (95% CI: 1.20–1.63) and of four studies which used incentives, RR: 1.28 (95% CI: 1.12–1.45). Conclusion Demand-side interventions lead to significant gains in child vaccination coverage in low- and middle-income countries. Educational approaches and use of incentives were both effective strategies