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Mpox (formerly known as monkeypox) virus and some related poxviruses including smallpox virus pose a significant threat to public health, and effective prevention and treatment strategies are needed. This study utilized a reverse vaccinology approach to retrieve conserved epitopes for monkeypox virus and construct a vaccine that could provide cross-protection against related viruses with similar antigenic properties. The selected virulent proteins of monkeypox virus, MPXVgp165, and Virion core protein P4a, were subjected to epitope mapping for vaccine construction. Two vaccines were constructed using selected T cell epitopes and B cell epitopes with PADRE and human beta-defensins adjuvants conjugated in the vaccine sequence. Both constructs were found to be highly antigenic, non-allergenic, nontoxic, and soluble, suggesting their potential to generate an adequate immune response and be safe for humans. Vaccine construct 1 was selected for molecular dynamic simulation studies. The simulation studies revealed that the TLR8-vaccine complex was more stable than the TLR3-vaccine complex. The lower RMSD and RMSF values of the TLR8 bound vaccine compared to the TLR3 bound vaccine suggested better stability and consistency of hydrogen bonds. The Rg values of the vaccine chain bound to TLR8 indicated overall stability, whereas the vaccine chain bound to TLR3 showed deviations throughout the simulation. These results suggest that the constructed vaccine could be a potential preventive measure against monkeypox and related viruses however, further experimental validation is required to confirm these findings.

Guavas (Psidium guajava) are regarded as one of the most perishable commodities, primarily owing to their climacteric characteristics and heightened metabolic processes, resulting in a faster rate of softening. Edible coating is a natural ingredient that is employed as an alternative to extend the shelf life of fruits while also providing bioactive and functional compounds. Aloe vera gel is predominantly used for this purpose due to its widespread availability. Various concentrations of aloe vera-based coating formulation (25%, 50%, 75%, and 100%) were applied on fresh whole guava by dipping method. The guava was stored at a refrigerated condition (4°C) and weight loss, color, firmness, vitamin C, total phenol, and pH change were observed in this research. A significant effect of aloe vera coating was found over the storage period. Aloe vera treatment lowered the weight loss, and retarded the texture and color compared to the control sample throughout the 28 days of storage. Vitamin C and total phenol content remined high at 141.4 mg/100g and 219.6 mg GAE/100g respectively in a 100% aloe vera coated sample after 28 days of storage compared to the control. Among 25%, 50%, 75%, and 100% aloe vera coated sample, 100% aloe vera was found to be the best coating material to prevent physical changes in fresh guava.

The raising concern of drug resistance, having substantial impacts on public health, has instigated the search of new natural compounds with substantial medicinal activity. In order to find out a natural solution, the current study has utilized prodigiosin, a linear tripyrrole red pigment, as an active ingredient to control bacterial proliferation and prevent cellular oxidation caused by ROS (Reactive Oxygen Species). A prodigiosin-producing bacterium BRL41 was isolated from the ancient Barhind soil of BCSIR Rajshahi Laboratories, Bangladesh, and its morphological and biochemical characteristics were investigated. Whole genome sequencing data of the isolate revealed its identity as Serratia sp. and conferred the presence of prodigiosin gene cluster in the bacterial genome. "Prodigiosin NRPS", among the 10 analyzed gene clusters, showed 100% similarity with query sequences where pigC, pigH, pigI, and pigJ were identified as fundamental genes for prodigiosin biosynthesis. Some other prominent clusters for synthesis of ririwpeptides, yersinopine, trichrysobactin were also found in the chromosome of BRL41, whilst the rest displayed less similarity with query sequences. Except some first-generation beta-lactam resistance genes, no virulence and resistance genes were found in the genome of BRL41. Structural illumination of the extracted red pigment by spectrophotometric scanning, Thin-Layer Chromatography (TLC), Fourier Transform Infrared Spectroscopy (FTIR), and change of color at different pH solutions verified the identity of the isolated compound as prodigiosin. Serratia sp. BRL41 attained its maximum productivity 564.74 units/cell at temperature 30˚C and pH 7.5 in two-fold diluted nutrient broth medium. The compound exhibited promising antibacterial activity against Gram-positive and Gram-negative bacteria with MIC (Minimum Inhibitory Concentration) and MBC (Minimum Bactericidal Concentration) values ranged from 3.9 to15.62 μg/mL and 7.81 to 31.25 μg/mL respectively. At concentration 500 μg/mL, except in Salmonella enterica ATCC-10708, prodigiosin significantly diminished biofilm formed by Listeria monocytogens ATCC-3193, Pseudomonas aeruginosa ATCC-9027, Escherichia coli (environmental isolate), Staphylococcus aureus (environmental isolate). Cellular glutathione level (GSH) was elevated upon application of 250 and 500 μg/mL pigment where 125 μg/mL failed to show any free radical scavenging activity. Additionally, release of cellular components in growth media of both Gram-positive and Gram-negative bacteria were facilitated by the extract that might be associated with cell membrane destabilization. Therefore, the overall findings of antimicrobial, antibiofilm and antioxidant activities suggest that in time to come prodigiosin might be a potential natural source to treat various diseases and infections.

Human T-lymphotropic virus (HTLV), a group of retroviruses belonging to the oncovirus family, has long been associated with various inflammatory and immunosuppressive disorders. At present, there is no approved vaccine capable of effectively combating all the highly pathogenic strains of HTLV that makes this group of viruses a potential threat to human health. To combat the devastating impact of any potential future outbreak caused by this virus group, our study employed a reverse vaccinology approach to design a novel polyvalent vaccine targeting the highly virulent subtypes of HTLV. Moreover, we comprehensively analyzed the molecular interactions between the designed vaccine and corresponding Toll-like receptors (TLRs), providing valuable insights for future research on preventing and managing HTLV-related diseases and any possible outbreaks. The vaccine was designed by focusing on the envelope glycoprotein gp62, a crucial protein involved in the infectious process and immune mechanisms of HTLV inside the human body. Epitope mapping identified T cell and B cell epitopes with low binding energies, ensuring their immunogenicity and safety. Linkers and adjuvants were incorporated to enhance the vaccine's stability, antigenicity, and immunogenicity. Initially, two vaccine constructs were formulated, and among them, vaccine construct-2 exhibited superior solubility and structural stability. Molecular docking analyses also revealed strong binding affinity between the vaccine construct-2 and both targeted TLR2 and TLR4. Molecular dynamics simulations demonstrated enhanced stability, compactness, and consistent hydrogen bonding within TLR-vaccine complexes, suggesting a strong binding affinity. The stability of the complexes was further corroborated by contact, free energy, structure, and MM-PBSA analyses. Consequently, our research proposes a vaccine targeting multiple HTLV subtypes, offering valuable insights into the molecular interactions between the vaccine and TLRs. These findings should contribute to developing effective preventive and treatment approaches against HTLV-related diseases and preventing possible outbreaks. However, future research should focus on in-depth validation through experimental studies to confirm the interactions identified in silico and to evaluate the vaccine's efficacy in relevant animal models and, eventually, in clinical trials.

The increasing incidence of prostate cancer (PCa) indicates an urgent need for the development of new effective drug therapy. There are limited options to treat the PCa, this study tried to determine a new therapy option for this acute cancer. Androgen-independent PCa cell lines PC3 and DU145 were treated with different melatonin concentrations (0.1~3.5 mM) for 1~3 days and assessed cell migration, cell invasion, cycle arrest in G0/G1 phase as well as apoptosis. We utilized RNA-seq technology to analyze the transcriptional misregulation pathways in DU145 prostate cancer cell line with melatonin (0.5 mM) treatment. Data revealed 20031 genes were up and down-regulated, there were 271 genes that differentially expressed: 97 up-regulated (P

BackgroundNon-alcoholic fatty liver disease (NAFLD) is a spectrum of disease ranging from simple steatosis, non-alcoholic steatohepatitis (NASH), through to advanced fibrosis and cirrhosis. We assessed the prevalence, spectrum, and determinants of NAFLD among adults in urban and rural North India.MethodsA representative sample of adults aged 30-60 years were recruited from urban Delhi and rural Ballabhgarh during 2017-2019. Participants underwent abdominal ultrasonography (USG) and vibration controlled transient elastography (VCTE) with FibroScan to assess fatty liver and fibrosis, respectively. We estimated the age- and sex-standardised prevalence of NAFLD and its spectrum. The factors associated with 'ultrasound-diagnosed NAFLD' were identified using multivariate logistic regression.ResultsA total of 828 urban (mean ± SD age: 45.5 ± 8.0 years; women: 52.7%) and 832 rural (mean ± SD age: 45.1 ± 7.9 years; women: 62.4%) participants were recruited. The age- and sex-standardized prevalence of ultrasound-diagnosed NAFLD was 65.7% (95%CI: 60.3-71.2) in the urban and 61.1% (55.8-66.5) in the rural areas, respectively. The prevalence of NAFLD with elevated alanine transaminase (≥40IU/L) was 23.2% (19.8-26.6), and 22.5% (19.0-26.0) and any fibrosis by liver stiffness measurement on transient elastography (≥6.9 kPa) was 16.5% (13.8-19.8) and 5.2% (3.8-6.7) in urban and rural participants, respectively. In both urban and rural areas, diabetes, central obesity and insulin resistance were significantly associated with NAFLD.ConclusionNAFLD prevalence was high among rural and urban North Indian adults, including fibrosis or raised hepatic enzymes. The strong association of metabolic determinants confirms its linkage with metabolic syndrome.

The Recency, Frequency, and Monetary model, also known as the RFM model, is a popular and widely used business model for determining beneficial client segments and analyzing profit. It is also recommended and frequently used in superstores to identify customer segments and increase profit margins. Later, the Length, Recency, Frequency, and Monetary model, also known as the LRFM model, was introduced as an improved version of the RFM model to identify more relevant and exact consumer groups for profit maximization. Superstores have a varying number of different products. In RFM and LRFM models, the relationship between profit and purchased quantity has never been investigated. Therefore, this paper proposed an efficient customer segmentation model, namely LRFMV (Length, Recency, Frequency, Monetary and Volume) and studied the profit-quantity relationship. A new dimension V (volume) has been added to the existing LRFM model to show a direct profit-quantity relationship in customer segmentation. The V stands for volume, which is derived by calculating the average number of products purchased by a frequent superstore client in a single day. The data obtained from feature extraction of the LRMFV model is then clustered by using conventional K-means, K-Medoids, and Mini Batch K-means methods. The results obtained from the three algorithms are compared, and the K-means algorithm is chosen for the superstore dataset of the proposed LRFMV model. All clusters created using these three algorithms are evaluated in the LRFMV model, and a close relationship between profit and volume is observed. A clear profit-quantity relationship of items has yet not been seen in any prior study on the RFM and LRFM models. Grouping customers aiming at profit maximization existed previously, but there was no clear and direct depiction of profit and quantity of sold items. This study applied unsupervised machine learning to investigate the patterns, trends, and correlations between volume and profit. The traits of all the clusters are analyzed by the Customer-Classification Matrix. The LRFMV values, larger or less than the overall average for each cluster, are identified as their traits. The performance of the proposed LRFMV model is compared with the legacy RFM and LRFM customer segmentation models. The outcome shows that the LRFMV model creates precise customer segments with the same number of customers while maintaining a greater profit. Author summary Why was this study done? Superstore business has been booming in the last decades. In the FY-2017, retail revenue of the top 250 superstores was 4,530,059 million USD which achieved 5.7% economic growth [1]. The Length, Recency, Frequency, and Monetary model, also known as the LRFM model, was introduced as an improved version of the RFM model to identify more relevant and exact consumer groups for profit maximization. However, there exists a substantial association between the purchase quantity and revenue generation that had been overlooked in earlier models. In this research, we introduced the LRFMV model, an improved version of existing business models for superstores, to further assess how much revenue boost and marketing strategy can be developed for the superstore industry and contribute to both technical sectors and the business world. In this research, we searched for a new way to utilize the segmentation model based on the scoring procedure and encountered how a business based matrix can employ them to have a substantial influence on the existing collaborative business and technology sector. What did the researchers do and find? We proposed an efficient customer segmentation model, LRFMV and tried to observe the profit-quantity relationship. A new dimension V (volume) has been added to the existing LRFM model in order to show a direct profit-quantity relationship. Here, the V stands for volume, which was derived by calculating the average number of products purchased by a frequent superstore client in a single day. To get the final average as volume in a specified time frame, the previously found average amount was divided by total days in a limited period of time of visitation of that customer. Quantity of purchased goods refers to the average amount of procured product by repeatedly going customers. Superstores have a varying number of different products with the record of being bought in different quantities multiple times on the same day by a specific customer. In RFM and LRFM models, the relationship between profit and purchased quantity and how they can contribute to an effective customer behavioral analysis was not investigated and evaluated. What do these findings mean? It is visible that a large volume of purchased products positively influences the profit maximization of a superstore. The establishment of the proposed model will assist superstores in generating more profit and performing comprehensive business analysis by helping to find the most profitable group of customers.

The Recency, Frequency, and Monetary model, also known as the RFM model, is a popular and widely used business model for determining beneficial client segments and analyzing profit. It is also recommended and frequently used in superstores to identify customer segments and increase profit margins. Later, the Length, Recency, Frequency, and Monetary model, also known as the LRFM model, was introduced as an improved version of the RFM model to identify more relevant and exact consumer groups for profit maximization. Superstores have a varying number of different products. In RFM and LRFM models, the relationship between profit and purchased quantity has never been investigated. Therefore, this paper proposed an efficient customer segmentation model, namely LRFMV (Length, Recency, Frequency, Monetary and Volume) and studied the profit-quantity relationship. A new dimension V (volume) has been added to the existing LRFM model to show a direct profit-quantity relationship in customer segmentation. The V stands for volume, which is derived by calculating the average number of products purchased by a frequent superstore client in a single day. The data obtained from feature extraction of the LRMFV model is then clustered by using conventional K-means, K-Medoids, and Mini Batch K-means methods. The results obtained from the three algorithms are compared, and the K-means algorithm is chosen for the superstore dataset of the proposed LRFMV model. All clusters created using these three algorithms are evaluated in the LRFMV model, and a close relationship between profit and volume is observed. A clear profit-quantity relationship of items has yet not been seen in any prior study on the RFM and LRFM models. Grouping customers aiming at profit maximization existed previously, but there was no clear and direct depiction of profit and quantity of sold items. This study applied unsupervised machine learning to investigate the patterns, trends, and correlations between volume and profit. The traits of all the clusters are analyzed by the Customer-Classification Matrix. The LRFMV values, larger or less than the overall average for each cluster, are identified as their traits. The performance of the proposed LRFMV model is compared with the legacy RFM and LRFM customer segmentation models. The outcome shows that the LRFMV model creates precise customer segments with the same number of customers while maintaining a greater profit.

BackgroundNepal has one of the highest rates of maternal mortality in the South Asia region, partly due to the underutilization of maternal health services and the high number of adolescent pregnancies. This study explores married Nepali adolescent girls' healthcare-seeking behaviour throughout their pregnancies, during their delivery and postpartum.MethodsWe conducted a prospective qualitative study in Banke district, Nepal. In-depth interviews were conducted with 27 married adolescent girls before and after delivery. In addition, a focus group discussion was conducted with community health works and key-informant interviews were conducted with family members of adolescent girls, representatives from the government and health care providers. We applied the Social-Ecological Model (SEM) as a framework to guide thematic content analysis and presentation of our qualitative data.ResultsSeveral factors in the SEM influenced maternal health care-seeking behaviour of adolescents. At the individual level, girls' perceptions, their lack of knowledge about maternal and reproductive health, certain traditional practices, their sole dependency on their husbands and mothers-in-laws and their low decision-making autonomy towards their own health care negatively influenced their utilization of skilled maternal health services. Mothers-in-law and other family members played a critical role in either encouraging or discouraging the use of skilled maternal health services. At the health systems level, lack of adolescent-friendly maternal health services, difficulties in accessing quality maternal health services, and the fixed operating hours of public health facilities restricted their ability to obtain services. The existence of the Safe Motherhood Programme, knowledge sharing platforms such as "women's groups" and the active role of Female Community Health Volunteers (FCHVs) positively influenced utilization of skilled maternal health services among these girls.ConclusionInfluences on married adolescent girls' use of skilled maternal health services in Banke District, Nepal were multi-factoral. Ensuring easy access and availability of adolescent-friendly maternal health services are important to encourage adolescent girls to use skilled maternal health services. Moreover, interventions are needed to improve adolescent girls' knowledge of maternal health, keep them in school, involve family members (mainly mothers-in-law) in health interventions, as well as overcome negative traditional beliefs within the community that discourage care-seeking for skilled maternal health services.

In the Point-Centred Quarter Method (PCQM), the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1) and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nearest plants, respectively) show discrepancy. This study attempts to review PCQM estimators in order to find the most accurate equation form. We tested the accuracy of different PCQM equations using Monte Carlo Simulations in simulated (having 'random', 'aggregated' and 'regular' spatial patterns) plant populations and empirical ones.PCQM requires at least 50 sample points to ensure a desired level of accuracy. PCQM with a corrected estimator is more accurate than with a previously published estimator. The published PCQM versions (PCQM1, PCQM2 and PCQM3) show significant differences in accuracy of density estimation, i.e. the higher order PCQM provides higher accuracy. However, the corrected PCQM versions show no significant differences among them as tested in various spatial patterns except in plant assemblages with a strong repulsion (plant competition). If N is number of sample points and R is distance, the corrected estimator of PCQM1 is 4(4N - 1)/(π ∑ R2) but not 12N/(π ∑ R2), of PCQM2 is 4(8N - 1)/(π ∑ R2) but not 28N/(π ∑ R2) and of PCQM3 is 4(12N - 1)/(π ∑ R2) but not 44N/(π ∑ R2) as published.If the spatial pattern of a plant association is random, PCQM1 with a corrected equation estimator and over 50 sample points would be sufficient to provide accurate density estimation. PCQM using just the nearest tree in each quadrant is therefore sufficient, which facilitates sampling of trees, particularly in areas with just a few hundred trees per hectare. PCQM3 provides the best density estimations for all types of plant assemblages including the repulsion process. Since in practice, the spatial pattern of a plant association remains unknown before starting a vegetation survey, for field applications the use of PCQM3 along with the corrected estimator is recommended. However, for sparse plant populations, where the use of PCQM3 may pose practical limitations, the PCQM2 or PCQM1 would be applied. During application of PCQM in the field, care should be taken to summarize the distance data based on 'the inverse summation of squared distances' but not 'the summation of inverse squared distances' as erroneously published.