An insight into the anticancer potentials of lignan arctiin: A comprehensive review of molecular mechanisms.

Natural products are being developed as possible treatment options due to the rising prevalence of cancer and the harmful side effects of synthetic medications. Arctiin is a naturally occurring lignan found in numerous plants and exhibits different pharmacological activities, along with cancer. To elucidate the anticancer properties and underlying mechanisms of action, a comprehensive search of various electronic databases was conducted using appropriate keywords to identify relevant publications. The findings suggest that arctiin exhibits anticancer properties against tumor formation and various cancers such as cervical, myeloma, prostate, endothelial, gastric, and colon cancers in several preclinical pharmacological investigations. This naturally occurring compound exerts its anticancer effect through different cellular mechanisms, including mitochondrial dysfunction, cell cycle at different phases (G2/M), inhibition of cell proliferation, apoptotic cell death, and cytotoxic effects, as well as inhibition of migration and invasion of various malignant cells. Moreover, the study also revealed that, among the various cellular pathways, arctiin was shown to be more potent in terms of the PI3K/AKT and JAK/STAT signaling pathways. However, pharmacokinetic investigation indicated the compound's poor oral bioavailability. Because of these findings, arctiin might be considered a promising chemotherapeutic drug candidate.

A gold standard dataset and evaluation of methods for lineage abundance estimation from wastewater.

During the SARS-CoV-2 pandemic, genome-based wastewater surveillance sequencing has been a powerful tool for public health to monitor circulating and emerging viral variants. As a medium, wastewater is very complex because of its mixed matrix nature, which makes the deconvolution of wastewater samples more difficult. Here we introduce a gold standard dataset constructed from synthetic viral control mixtures of known composition, spiked into a wastewater RNA matrix and sequenced on the Oxford Nanopore Technologies platform. We compare the performance of eight of the most commonly used deconvolution tools in identifying SARS-CoV-2 variants present in these mixtures. The software evaluated was primarily chosen for its relevance to the CDC wastewater surveillance reporting protocol, which until recently employed a pipeline that incorporates results from four deconvolution methods: Freyja, kallisto, Kraken 2/Bracken, and LCS. We also tested Lollipop, a deconvolution method used by the Swiss SARS-CoV-2 Sequencing Consortium, and three additional methods not used in the C-WAP pipeline: lineagespot, Alcov, and VaQuERo. We found that the commonly used software Freyja outperformed the other CDC pipeline tools in correct identification of lineages present in the control mixtures, and that the VaQuERo method was similarly accurate, with minor differences in the ability of the two methods to avoid false negatives and suppress false positives. Our results also provide insight into the effect of the tiling primer scheme and wastewater RNA extract matrix on viral sequencing and data deconvolution outcomes.

Whole-genome sequencing of Klebsiella pneumoniae isolated from clinical specimens in Chattogram, Bangladesh.

The emergence of multidrug-resistant Klebsiella pneumoniae (Kpn) is a global concern due to the increasing rate of mortality and hospital cost burden in the affected population. This study reports the whole-genome sequences of nine multidrug-resistant Kpn from a hospital in Chattogram city of Bangladesh.

More Is Faster: Why Population Size Matters in Biological Search.

Many biological scenarios have multiple cooperating searchers, and the timing of the initial first contact between any one of those searchers and its target is critically important. However, we are unaware of biological models that predict how long it takes for the first of many searchers to discover a target. We present a novel mathematical model that predicts initial first contact times between searchers and targets distributed at random in a volume. We compare this model with the extreme first passage time approach in physics that assumes an infinite number of searchers all initially positioned at the same location. We explore how the number of searchers, the distribution of searchers and targets, and the initial distances between searchers and targets affect initial first contact times. Given a constant density of uniformly distributed searchers and targets, the initial first contact time decreases linearly with both search volume and the number of searchers. However, given only a single target and searchers placed at the same starting location, the relationship between the initial first contact time and the number of searchers shifts from a linear decrease to a logarithmic decrease as the number of searchers grows very large. More generally, we show that initial first contact times can be dramatically faster than the average first contact times and that the initial first contact times decrease with the number of searchers, while the average search times are independent of the number of searchers. We suggest that this is an underappreciated phenomenon in biology and other collective search problems.

Caesarean delivery and neonatal mortality: evidence from selected slums in and around Dhaka city, Bangladesh- A prospective cohort study.

BACKGROUND: This study examined the neonatal mortality for newborn of women who delivered by caesarean section or vaginally using a prospective cohort. METHODS: A total of 6,989 live births registered from 2016 to 2018, were followed for neonatal survival from the selected slums of Dhaka (North and South) and Gazipur city corporations, where icddr,b maintained the Health and Demographic Surveillance System (HDSS). Neonatal mortality was compared by maternal and newborn characteristics and mode of delivery using z-test. Logistic regression model performed for neonatal mortality by mode of delivery controlling selected covariates and reported adjusted odd ratios (aOR) with 95% confidence interval (CI). RESULTS: Out of 6,989 live births registered, 27.7% were caesarean and the rest were vaginal delivery; of these births, 265 neonatal deaths occurred during the follow-up. The neonatal mortality rate was 2.7 times higher (46 vs. 17 per 1,000 births) for vaginal than caesarean delivered. Until 3rd day of life, the mortality rate was very high for both vaginal and caesarean delivered newborn; however, the rate was 24.8 for vaginal and 6.3 per 1,000 live births for caesarean delivered on the 1st day of life. After adjusting the covariates, the odds of neonatal mortality were higher for vaginal than caesarean delivered (aOR: 2.63; 95% CI: 1.82, 3.85). Additionally, the odds were higher for adolescent than elderly adult mother (aOR: 1.60; 95% CI: 1.03, 2.48), for multiple than singleton birth (aOR: 5.40; 95% CI: 2.82, 10.33), for very/moderate (aOR: 5.13; 95% CI: 3.68, 7.15), and late preterm birth (aOR: 1.48; 95% CI: 1.05, 2.08) than term birth; while the odds were lower for girl than boy (aOR: 0.74; 95% CI: 0.58, 0.96), and for 5th wealth quintile than 1st quintile (aOR: 0.59, 95% CI: 0.38, 0.91). CONCLUSION: Our study found that caesarean delivered babies had significantly lower neonatal mortality than vaginal delivered. Therefore, a comprehensive delivery and postnatal care for vaginal births needed a special attention for the slum mothers to ensure the reduction of neonatal mortality.

Isolation, characterization and pharmacological potentials of methanol extract of Cassia fistula leaves: Evidenced from mice model along with molecular docking analysis.

The purpose of the current investigation was to conduct a detailed analysis of the chemical components and medicinal properties of the methanolic crude extract derived from the leaves of Cassia fistula. This analysis was carried out using both experimental (in vivo) and computational (in silico) methods. Eleven chemicals were chromatographically isolated using GC-MS/MS, which utilizes a library of NIST and Wiley 2020 versions. FTIR analysis of the extract was performed to identify the functional group of the compounds. The glucose-lowering capacity, analgesic, and anti-diarrheal activities of methanolic crude extract were analyzed utilizing a well-known oral glucose tolerance test, tail immersion method, writhing assay, and castor oil-induced diarrheal mice methods, respectively. After 60 min, 120 min, and 180 min of loading the drugs, a significant reduction of blood glucose levels was examined (p < 0.05) in all the extracts of this plant (200 mg/kg, 400 mg/kg and 600 mg/kg) utilized in this research at a time-dependent manner. Similarly, all the crude extracts showed significant (p < 0.05) effects against pain centrally and peripherally compared to the standard drug morphine (2 mg/kg bw) and diclofenac sodium (50 mg/kg bw). Moreover, the methanol extract (400 mg/kg bw) manifested anti-diarrheal efficacy by inhibiting 72.0 % of the diarrheal episode in mice compared to the standard drug loperamide (inhibition = 80.0%). The results of the computational investigations corroborated existing in-vivo findings. Greater or close to equivalent binding affinity to the active binding sites of kappa opioid receptor, glucose transporter 3 (GLUT 3), and cyclooxygenase 2 was indicative of the potential anti-diarrheal, hypoglycemic, and analgesic characteristics of the isolated compounds (COX-2). Moreover, anticancer and antimicrobial potentiality was also found impressive through evaluation of binding affinity with epidermal growth factor receptor (EGFR) and dihydrofolate reductase (DHFR) receptors. Results from this study indicated that C. fistula might be a beneficial natural resource for treating diarrhea, hyperglycemia, and pain. However, additional research is required to conduct a comprehensive phytochemical screening and establish precise action mechanisms of the crude extract or the plant-derived compounds.

Prevalence, antibiotic resistance pattern for bacteriuria from patients with urinary tract infections.

Background and Aims: Antibiotic resistance presents a significant global public health challenge, particularly for urinary tract infections (UTIs), and is notably severe in developing countries. Surveillance of the antimicrobial susceptibility patterns of UTI-causing bacteria is crucial for effective treatment selection. This study aimed to analyze these patterns in bacteria isolated from the urine samples of patients at Mughda Medical College Hospital, Dhaka, Bangladesh. Methods: A retrospective study (January 2019 to December 2020) at Mugdha Medical College and Hospital, Dhaka, examined clinical and laboratory data from patients with positive urine cultures (≥105 CFU/mL). The study classified patients into four age groups: children (1-<18 years), young adults (18-<33 years), middle-aged adults (33-50 years), and old adults (>50 years). The standard Kirby-Bauer method was used to assess antibiotic sensitivity to 28 common antibiotics. Results: Among 243 positive urine cultures in both community- and hospital-acquired UTIs, Escherichia coli was the most common uropathogen (65.84%), followed by Klebsiella spp. (12.34%), Enterococcus spp. (8.23%), and other types of bacteria. Conclusion: Old adults are particularly vulnerable to UTIs, with E. coli being the predominant causative agent in the study region. The observed antimicrobial resistance patterns underscore the necessity of judicious antibiotic selection to effectively treat UTIs across different age groups.

Community engagement and social participation in dengue prevention: A cross-sectional study in Dhaka City.

Background: Dengue is a major public health concern in Bangladesh. This study aimed to assess the perceptions and practices of community members in Dhaka regarding community engagement and social participation for dengue prevention. Methods: A cross-sectional online survey was conducted in Dhaka City from May 2022 to December 2022. The respondents were randomly selected. The association between community participation and prevention practices was tested using the χ 2 test. Results: The findings of this study indicate that the majority of participants (92%) believed that community effort would be relied upon in the event of a dengue outbreak. Environmental cleaning campaigns were the preferred approach, and religious leaders viewed them positively. This study also revealed significant variations in knowledge levels, with those involved in community efforts and mass gatherings demonstrating greater knowledge. This study sheds light on the demographic factors that influence dengue knowledge and provides valuable insights into the development of targeted public health interventions. Conclusion: The study revealed negative perceptions and limited participation in dengue prevention among participants, with the majority demonstrating a poor understanding of preventive measures. While some showed positive attitudes towards community engagement, significant disparities existed in participation, highlighting the need for targeted educational campaigns and enhanced community mobilization efforts. Moreover, the importance of multisectoral collaboration is emphasized, underscoring the need for coordinated efforts among health departments, NGOs, religious institutions, and community leaders to effectively combat dengue transmission. Recommendations include ongoing educational initiatives, targeted interventions to promote community involvement, and fostering collaboration across sectors to strengthen dengue prevention efforts and to safeguard public health.

Bioactivities of morroniside: A comprehensive review of pharmacological properties and molecular mechanisms.

Morroniside (MOR) is an iridoid glycoside and the main active principle of the medicinal plant, Cornus officinalis Sieb. This phytochemical is associated with numerous health benefits due to its antioxidant properties. The primary objective of the present study was to assess the pharmacological effects and underlying mechanisms of MOR, utilizing published data obtained from literature databases. Data collection involved accessing various sources, including PubMed/Medline, Scopus, Science Direct, Google Scholar, Web of Science, and SpringerLink. Our findings demonstrate that MOR can be utilized for the treatment of several diseases and disorders, as numerous studies have revealed its significant therapeutic activities. These activities encompass anti-inflammatory, antidiabetic, lipid-lowering capability, anticancer, trichogenic, hepatoprotective, gastroprotective, osteoprotective, renoprotective, and cardioprotective effects. MOR has also shown promising benefits against various neurological ailments, including Alzheimer's disease, Parkinson's disease, spinal cord injury, cerebral ischemia, and neuropathic pain. Considering these therapeutic features, MOR holds promise as a lead compound for the treatment of various ailments and disorders. However, further comprehensive preclinical and clinical trials are required to establish MOR as an effective and reliable therapeutic agent.

Pharmacological Activities of Plant-Derived Fraxin with Molecular Mechanisms: A Comprehensive Review.

Fruits and vegetables serve not only as sources of nutrition but also as medicinal agents for the treatment of diverse diseases and maladies. These dietary components are significant resources of phytochemicals that demonstrate therapeutic properties against many illnesses. Fraxin is a naturally occurring coumarin glycoside mainly present in various species of Fraxinus genera, having a multitude of therapeutic uses against various diseases and disorders. This study focuses to investigate the pharmacological activities, botanical sources, and biopharmaceutical profile of the phytochemical fraxin based on different preclinical and non-clinical studies to show the scientific evidence and to evaluate the underlying molecular mechanisms of the therapeutic effects against various ailments. For this, data was searched and collected (as of February 15, 2024) in a variety of credible electronic databases, including PubMed/Medline, Scopus, Springer Link, ScienceDirect, Wiley Online, Web of Science, and Google Scholar. The findings demonstrated favorable outcomes in relation to a range of diseases or medical conditions, including inflammation, neurodegenerative disorders such as cerebral ischemia-reperfusion (I/R) and depression, viral infection, as well as diabetic nephropathy. The phytochemical also showed protective effects such as osteoprotective, renoprotective, pulmoprotective, hepatoprotective, and gastroprotective effects due to its antioxidant capacity. Fraxin has a great capability to diminish oxidative stress-related damage in different organs by stimulating the antioxidant enzymes, downregulating nuclear factor kappa B and NLRP3, and triggering the Nrf2/ARE signaling pathways. Fraxin exhibited poor oral bioavailability because of reduced absorption and a wide distribution into tissues of different organs. However, extensive research is required to decipher the biopharmaceutical profiles, and clinical studies are necessary to establish the efficacy of the natural compound as a reliable therapeutic agent.

A systematic review of potential productivity, egg quality, and animal welfare implications of extended lay cycles in commercial laying hens in Canada.

Lay cycle lengths in the Canadian egg industry are currently 50 to 52 wk (68-70 wk of age). In light of increased productivity in commercial laying hens over the last few decades, the much longer lay cycle lengths already implemented in other countries, extending lay cycle lengths in Canada, should be considered with careful attention to potential environmental, economic, and animal welfare implications. However, there is a lack of information in the public domain that provides robust evidence of performance levels and potential trade-offs to support comprehensive consideration of the desirability of extending lay cycles beyond current Canadian norms. Hence, a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was undertaken. Data collection focused primarily on information related to feed-, flock management-, and hen genetics/physiology-related interventions that were studied in literature to support extension of lay cycles (review objective 1), and compiling and analyzing productivity, egg quality, and animal welfare outcomes reported at 70 wk of age or beyond (review objective 2). Several feed-related interventions such as high-protein diets, and probiotics supplements, and flock management interventions such split-feeding were found to potentially improve productivity, and especially egg quality, outcomes in the late laying phase. More studies with bigger flock sizes and in commercial lay facilities need to be undertaken before any of these interventions can be definitively recommended for commercial egg production. Under objective 2, productivity was found to be at acceptable levels well beyond 70 wk of age. Performance on most egg quality traits and animal welfare indicators were also at acceptable levels past 70 wk of age but increased variability was observed beyond ∼80 wk of age. There were also inconclusive indications on how hens in caged housing and white laying hens fare relative to hens in noncaged housing and brown-type layers during the late laying phase. Economic data were limited but suggested that lay cycle lengths beyond 90 wk might not generated net economic benefits.

Cholera toxin and O-specific polysaccharide immune responses after oral cholera vaccination with Dukoral in different age groups of Bangladeshi participants.

Vaccination is important to prevent cholera. There are limited data comparing anti-O-specific polysaccharide (OSP) and anti-cholera toxin-specific immune responses following oral whole-cell with cholera toxin B-subunit (WC-rBS) vaccine (Dukoral, Valneva) administration in different age groups. An understanding of the differences is relevant because young children are less well protected by oral cholera vaccines than older children and adults. We compared responses in 50 adults and 49 children (ages 2 to <18) who were administered two doses of WC-rBS at a standard 14-day interval. All age groups had significant IgA and IgG plasma-blast responses to the OSP and cholera toxin B-subunit (CtxB) antigens that peaked 7 days after vaccination. However, in adults and older children (ages 5 to <18), antibody responses directed at the OSP antigen were largely IgA and IgG, with a minimal IgM response, while younger children (ages 2 to <5) mounted significant increases in IgM with minimal increases in IgA and IgG antibody responses 30 days after vaccination. In adults, anti-OSP and CtxB memory B-cell responses were detected after completion of the vaccination series, while children only mounted CtxB-specific IgG memory B-cell responses and no OSP-memory B-cell responses. In summary, children and adults living in a cholera endemic area mounted different responses to the WC-rBS vaccine, which may be a result of more prior exposure to Vibrio cholerae in older participants. The absence of class-switched antibody responses and memory B-cell responses to OSP may explain why protection wanes more rapidly after vaccination in young children compared to older vaccinees.IMPORTANCEVaccination is an important strategy to prevent cholera. Though immune responses targeting the OSP of V. cholerae are believed to mediate protection against cholera, there are limited data on anti-OSP responses after vaccination in different age groups, which is important as young children are not well protected by current oral cholera vaccines. In this study, we found that adults mounted memory B-cell responses to OSP, which were not seen in children. Adults and older children mounted class-switched (IgG and IgA) serum antibody responses to OSP, which were not seen in young children who had only IgM responses to OSP. The lack of class-switched antibody responses and memory B-cell responses to OSP in younger participants may be due to lack of prior exposure to V. cholerae and could explain why protection wanes more rapidly after vaccination in young children.

Machine learning based recommendation of agricultural and horticultural crop farming in India under the regime of NPK, soil pH and three climatic variables.

Machine learning (ML) can make use of agricultural data related to crop yield under varying soil nutrient levels, and climatic fluctuations to suggest appropriate crops or supplementary nutrients to achieve the highest possible production. The aim of this study was to evaluate the efficacy of five distinct ML models for a dataset sourced from the Kaggle repository to generate practical recommendations for crop selection or determination of required nutrient(s) in a given site. The datasets contain information on NPK, soil pH, and three climatic variables: temperature, rainfall, and humidity. The models namely Support vector machine, XGBoost, Random forest, KNN, and Decision Tree were trained using yields of individual data sets of 11 agricultural and 10 horticultural crops, as well as combined yield of both agri-horticultural crops. The results strongly suggest to evaluate individual data sets separately for each crop category rather than using combined the data sets of both categories for better predictions. Comparing the five ML models, the XGBoost demonstrated the highest level of accuracy. The precision rates of XGBoost for recommending agricultural crops, horticultural crops, and a combination of both were 99.09 % (AUC 1.0), 99.3 % (AUC 1.0), and 98.51 % (AUC 0.99), respectively. This non-intrusive method for generating crop recommendations in diverse environmental conditions holds the potential to provide valuable insights for the development of a user-friendly AI cloud-based interface. Such an interface would enable rapid decision-making for optimal fertilizer applications and the selection of suitable crops for cultivation at specific sites.

Preterm birth and neonatal mortality in selected slums in and around Dhaka City of Bangladesh: A cohort study.

BACKGROUND: Although under-five mortality has declined appreciably in Bangladesh over the last few decades, neonatal mortality still remains high. The objective of the study is to assess the level and determinants of preterm birth and the contribution of preterm birth to neonatal mortality. METHODS: Data for this study came from selected slums in and around Dhaka city, where; since 2015, icddr,b has been maintaining the Health and Demographic Surveillance System (HDSS). The HDSS data were collected by female Field Workers by visiting each household every three months; however, during the visit, data on the Last Menstrual Period (LMP) were also collected by asking each eligible woman to ascertain the date of conception. Gestational age was estimated in complete weeks by subtracting LMP from the date of the pregnancy outcome. In this study, 6,989 livebirths were recorded by HDSS during 2016-2018, and these births were followed for neonatal survival; both bivariate and multivariate analyses were performed. RESULTS: Out of total births, 21.7% were born preterm (before 37 weeks of gestation), and sub-categories were: 2.19% for very preterm (28 to 31 weeks), 3.81% for moderate preterm (32 to 33 weeks), and 15.71% for late preterm (34 to 36 weeks). The study revealed that preterm babies contributed to 39.6% of neonatal deaths; however, the probability of death was very high on the 1st day of birth (0.124 for very preterm, 0.048 for moderate preterm, 0.024 for late preterm, and 0.013 for term birth), and continued until the 3rd day. In the regression analysis, compared to the term neonates, the odds of neonatal mortality were 8.66 (CI: 5.63, 13.32, p<0.01), 4.13 (CI: 2.69, 6.34, p<0.01) and 1.48 (CI: 1.05, 2.08, p<0.05) respectively for very, moderate, and late preterm birth categories. The population attributable fraction for neonatal mortality was 23%, and sub-categories were 14% for very preterm, 10% for moderate preterm, and 6% for late preterm. CONCLUSIONS: Although urban slums are in proximity to many health facilities, a substantial proportion of preterm births contribute to neonatal deaths. So, pregnant women should be targeted, to ensure timely care during pregnancy, delivery, and post-partum periods to improve the survival of new-borns in general and preterm birth in particular.

Serosurveillance among urban slum and non-slum populations immunized with COVID-19 vaccines in Bangladesh.

Using two rounds of serosurveillance, we aimed to observe the COVID-19 vaccination status and the dynamics of antibody responses to different vaccines among urban slum and non-slum populations of Bangladesh. Adults (>18 years) and children (10-17 years) were enrolled in March and October 2022. Data including COVID-19 vaccine types and dosage uptake were collected. SARS-CoV-2 spike (S)-specific antibodies were measured in blood. The proportion of vaccinated children was significantly lower among slum than non-slum populations. Two doses of vaccines showed an increase in the level of anti-S-antibodies up to 2 months, followed by reduced levels at 2-6 months and a resurgence at 6-12 months. Children showed significantly higher anti-S-antibodies after two doses of the Pfizer-BioNTech vaccine than adults; however, after 6 months, the level of antibodies declined in younger children (10 - < 12 years). In a mixed vaccine approach, mRNA vaccines contributed to the highest antibody response whether given as the first two doses or as the third dose. Our findings emphasized the need for increasing the coverage of COVID-19 vaccination among slum children and booster dosing among all children. The use of mRNA vaccines in the mixed vaccination approach was found to be useful in boosting the antibody response to SARS-CoV-2.

Assessing deep convolutional neural network models and their comparative performance for automated medicinal plant identification from leaf images.

Medicinal plants have got notable attention in recent years in the field of pharmaceutical and drug research. The high demand of herbal medicine in the rural areas of developing countries and drug industries necessitates correct identification of the medicinal plant species which is challenging in absence of expert taxonomic knowledge. Against this backdrop, we attempted to assess the performance of seven advanced deep learning algorithms in the automated identification of the plants from their leaf images and to suggest the best model from a comparative study of the models. We meticulously trained VGG16, VGG19, DenseNet201, ResNet50V2, Xception, InceptionResNetV2, and InceptionV3 deep neural network models. This training utilized a dataset comprising 5878 images encompassing 30 medicinal species distributed among 20 families. Our approach involved two avenues: the utilization of public data (PI) and a blend of public and field data (PFI), the latter featuring intricate backgrounds. Our study elucidates the robustness of these models in accurately identifying and classifying both interfamily and interspecies variations. Despite variations in accuracy across diverse families and species, the models demonstrated adeptness in these classifications. Comparing the models, we unearthed a crucial insight: the Normalized leverage factor (γω) for DenseNet201 stands at 0.19, elevating it to the pinnacle position for PI with a remarkable 99.64 % accuracy and 98.31 % precision. In the PFI scenario, the same model achieves a γω of 0.15 with a commendable 97 % accuracy. These findings serve as a guiding beacon for shaping future application tools designed to automate medicinal plant identification at the user level.

Efficacy of Rotundic Acid and Its Derivatives as Promising Natural Anticancer Triterpenoids: A Literature-Based Study.

Rotundic acid (RA) is a naturally occurring pentacyclic triterpene with a multitude of pharmacological activities. The primary emphasis of this study is on summarizing the anticancer properties with the underlying mechanisms of RA and its derivatives, as well as the pharmacokinetic features. Data was collected (up to date as of November 10, 2023) from various reliable and authentic literatures by searching in different academic search engines, including PubMed, Springer Link, Scopus, Wiley Online, Web of Science, ScienceDirect, and Google Scholar. The findings imply that RA and its synthetic derivatives possess promising anti-cancer properties against breast, colorectal, liver, and cervical cancers in various preclinical pharmacological test systems. The results also indicate that RA and its derivatives demonstrated anticancer effects via a number of cellular mechanisms, including apoptotic cell death, inhibition of oxidative stress, anti-inflammatory effect, cytotoxicity, cell cycle arrest, anti-proliferative effect, anti-angiogenic effect, and inhibition of cancer cell migration and invasion. It has been proposed that RA and its derived compounds have the capability to serve as a hopeful chemotherapeutic agent, so further extensive clinical research is necessary.

Exploring Cinnamoyl-Substituted Mannopyranosides: Synthesis, Evaluation of Antimicrobial Properties, and Molecular Docking Studies Targeting H5N1 Influenza A Virus.

The pursuit of innovative combinations for the development of novel antimicrobial and antiviral medications has garnered worldwide interest among scientists in recent times. Monosaccharides and their glycosides, such as methyl α-d-mannopyranoside derivatives, play a significant role in the potential treatment of viral respiratory pathologies. This study was undertaken to investigate and assess the synthesis and spectral characterization of methyl α-d-mannopyranoside derivatives 2-6, incorporating various aliphatic and aromatic groups. The investigation encompassed comprehensive in vitro antimicrobial screening, examination of physicochemical properties, molecular docking analysis, molecular dynamics simulations, and pharmacokinetic predictions. A unimolar one-step cinnamoylation reaction was employed under controlled conditions to produce methyl 6-O-cinnamoyl-α-d-mannopyranoside 2, demonstrating selectivity at the C-6 position. This represented a pivotal step in the development of potential antimicrobial derivatives based on methyl α-d-mannopyranoside. Subsequently, four additional methyl 6-O-cinnamoyl-α-d-mannopyranoside derivatives were synthesized with reasonably high yields. The chemical structures of these novel analogs were confirmed through a thorough analysis of their physicochemical properties, elemental composition, and spectroscopic data. In vitro antimicrobial assays were conducted against six bacterial strains and two fungal strains, revealing promising antifungal properties of these methyl α-d-mannopyranoside derivatives in comparison to their antibacterial activity. Moreover, cytotoxicity testing revealed that the compounds are less toxic. Further supporting these findings, molecular docking studies were performed against the H5N1 influenza A virus, indicating significant binding affinities and nonbonding interactions with the target protein 6VMZ. Notably, compounds 4 (-7.2) and 6 (-7.0) exhibited the highest binding affinities. Additionally, a 100 ns molecular dynamics simulation was conducted to assess the stability of the complex formed between the receptor 6VMZ and methyl α-d-mannopyranoside derivatives under in silico physiological conditions. The results revealed a stable conformation and binding pattern within the stimulating environment. In silico pharmacokinetic and toxicity assessments of the synthesized molecules were performed using Osiris software (version 2.9.1). Compounds 4 and 6 demonstrated favorable computational and pharmacological activities, albeit with a low drug score, possibly attributed to their higher molecular weight and irritancy. In conclusion, this study showcases the synthesis and evaluation of methyl α-d-mannopyranoside derivatives as promising candidates for antimicrobial and antifungal agents. Molecular docking and dynamics simulations, along with pharmacological predictions, contribute to our understanding of their potential therapeutic utility, although further research may be warranted to address certain pharmacological aspects.

Synthesis, characterization and thermoluminescence properties of LiCaPO4 phosphor for ionizing radiation dosimetry.

Many minerals and compounds show thermoluminescence (TL) properties but only a few of them can meet the requirements of an ideal dosimeter. Several phosphate materials have been studied for low-dose dosimetryin recent times. Among the various phosphates, ABPO4-type material shows interesting TL properties. In this study, an ABPO4-type (A = Lithium, B=Calcium) phosphor is synthesized using a modified solid-state diffusion method. Temperature is maintained below 800 °C in every step of phosphor preparation to obtain the pure phase of Lithium calcium phosphate (LiCaPO4). The purpose of this work is to synthesize LiCaPO4 using a simple method, examine its structural and luminescence properties in order to gain a deeper understanding of its TL characteristics. The general TL properties, such as TL glow curve, dose linearity, sensitivity, and fading, are investigated. Additionally, this study aims to determine various kinetic parameters through Glow Curve Deconvolution (GCD) method using the Origin Lab software together with the Chen model. XRD analysis confirmed the phase purity of the phosphor with a rhombohedral structure. Lattice parameters, unit cell volume, grain size, dislocated density, and microstrain were also calculated from XRD data. Raman analysis and Fourier Transform Infrared analysis were used to collect information about molecular bonds, vibrations, identity, and structure of the phosphor. To investigate TL properties and associated kinetic parameters, the phosphor was irradiated with 6.0 MV (photon energy) and 6.0 MeV (electron energy) from a linear accelerator for doses ranging from 0.5 Gy to 6.0 Gy. For both photon and electron energy, TL glow curves have two identical peaks near 200 °C and 240 °C.The TL glow curves for 0.5 Gy-6 Gy are deconvoluted, then fitted with the appropriate model and then calculated the kinetic parameters. Kinetic parameters such as geometric factor (µg), order of kinetics, activation energy (E), and frequency factor (s) are obtained from Chen's peak shape method. The dose against the TL intensity curve shows that the response is almost linear in the investigated dose range. For photon and electron energy, the phosphor is found to be the most sensitive at 2.0 Gy and 4.0 Gy, respectively. The phosphor shows a low fading and after 28 days of exposure, it shows a signal loss of better than 3%. The studied TL properties suggest the suitability of LiCaPO4 in radiation dosimetry and associated fields.

Assessment of the hypoglycemic and anti-hemostasis effects of Paederia foetida (L.) in controlling diabetes and thrombophilia combining in vivo and computational analysis.

Paederia foetida is valued for its folk medicinal properties. This research aimed to assess the acute toxicity, hypoglycemic and anti-hemostasis properties of the methanolic extract of P. foetida leaves (PFLE). Acute toxicity of PFLE was performed on a mice model. Hypoglycemic and anti-hemostasis properties of PFLE were investigated on normal and streptozotocin-induced mice models. Deep learning, molecular docking, density functional theory, and molecular simulation techniques were employed to understand the underlying mechanisms through in silico study. Oral administration of PFLE at a dosage of 300 µg/kg body weight (BW) showed no signs of toxicity. Treatment with PFLE (300 µg/kg/BW) for 14 days resulted in a hypoglycemic condition and a 30.47% increase in body weight. Additionally, PFLE mixed with blood exhibited a 44.6% anti-hemostasis effect. Deep learning predicted the inhibitory concentration (pIC50, nM) of Cleomiscosins against SGLT2 and FXa to be 7.478 and 6.017, respectively. Molecular docking analysis revealed strong binding interactions of Cleomiscosins with crucial residues of the target proteins, exhibiting binding energies of -8.2 kcal/mol and -7.1 kcal/mol, respectively. ADME/Tox predictions indicated favorable pharmacokinetic properties of Cleomiscosins, and DFT calculations of frontier molecular orbitals analyzed the stability and reactivity of these compounds. Molecular simulation dynamics, principal component analysis and MM-PBSA calculation demonstrated the stable, compact, and rigid nature of the protein-ligand complexes. The methanolic PFLE exhibited significant hypoglycemic and anti-hemostasis properties. Cleomiscosin may have inhibitory properties for the development of novel drugs to manage diabetes and thrombophilia in the near future.