Red Clover Research Articles

Biochanin A Attenuates Psoriasiform Inflammation by Regulating Nrf2/HO-1 Pathway Activation and Attenuating Inflammatory Signalling.

Psoriasis is a long-term inflammatory skin condition marked by an overabundance of keratinocytes and the release of pro-inflammatory cytokines in the outer layer of skin. For the comprehensive management of intermediate to advanced psoriasis, innovative biological treatments have been developed. Products for the superficial therapy of mild to moderate psoriasis are still necessary, though. Trifolium pratense contains the isoflavone biochanin A (BCA), which exhibits antiviral, antioxidant, anti-carcinogenic, and anti-inflammatory properties, and helps protect the integrity and function of the endothelium. Although investigations have not shown that BCA is effective in treating psoriasis, it has been shown to slow down the breakdown of the skin barrier by regulating keratinocyte growth. We sought to clarify the basic mechanisms behind BCA's impact on psoriasis in vitro and in vivo using experimental research via regulating Nrf2/HO-1 signaling pathway. By subjecting human primary keratinocytes to psoriasis-related cytokines, psoriasis-like keratinocytes were produced. The CCK8 test was used in this investigation to assess cell viability. BCA reduced keratinocyte growth and inflammatory cascade stimulation produced by TNF-α and IL-6, according to in vitro investigations conducted on HaCaT cells. The in vivo findings showed that six days of BCA therapy significantly decreased the skin, hematological indicators, levels of NO, TBARS, histopathological, and pro-inflammatory factors of COX-2, iNOS, NF-κB pathway. It additionally influenced the protein content of pro-inflammatory cytokines such as IL-17, IL-23, IL-1β in the epidermis along with IL-6, TNF-α among the epidermis and serum. In addition, in contrast to the IMQ group, BCA improved the skin's level of Nrf2/HO-1 protein, anti-inflammatory cytokine IL-10, and antioxidant indicators like SOD, CAT, GST, GSH, GR, and Vit-C. Ultimately, our research shows that BCA was effective in treating psoriasis in pre-clinical animal models by activating the Nrf2/HO-1 pathway, leading to an increase in antioxidant and anti-inflammatory markers.

Genome-wide analysis of the R2R3-MYB gene family and identification of candidate genes that regulate isoflavone biosynthesis in red clover (Trifolium pratense)

Red clover (Trifolium pratense) is a perennial legume with high feeding and medicinal value attributed to its abundant isoflavone content. Previous studies reported that R2R3-MYB transcription factors are involved in the biosynthesis of isoflavones; however, their specific role in red clover remains poorly understood. Through comprehensive genome-wide and transcriptome analyses, a total of 138 TpR2R3-MYB genes were identified and classified into 30 distinct subgroups within a phylogenetic tree. Importantly, six of these subgroups showed associations with isoflavone biosynthesis in red clover. The majority of segmental duplication events (Ka/Ks < 1) indicated that the TpR2R3-MYB gene underwent strong purifying selection during evolution. The qRT-PCR analysis demonstrated high expression levels of TpMYB79 and TpMYB53 in Minshan red clover at full flowering stage, consistent with the trend for isoflavone content determination, suggesting that TpMYB79 and TpMYB53 might be important regulators of isoflavone biosynthesis in red clover. Additionally, we observed nucleus and vacuole membrane localization of TpMYB53 and TpMYB79, with TpMYB53 primarily exerting transcriptional activation through its C-terminal activation motifs while TpMYB79 exhibited no transcriptional activity. These findings provided a foundation for the study of the biological function of R2R3-MYB transcription factors in red clover.

The effect of powdery mildew on the cell structure and cell wall composition of red clover

The effect of powdery mildew on the cell structure and cell wall composition of red clover

Animal performance over 16 years after implementing a lucerne grazing system on Bog Roy Station - a case study

In 2023, the animal performance data for Bog Roy station show 151 t weaned lamb is being produced from 4272 ewes plus 9.0 t from hogget lambs. The ability to mate merino hoggets has resulted from increased feed supply that means mixed age ewes are now consistently averaging 65.6±1.17 kg/hd at mating (2019-2023). This has enabled an emphasis on two-tooth weight at mating, which has also increased 0.74±0.14 kg/hd/yr (R2 = 0.64) from 52 kg/hd in 2012 to 61 kg/hd in 2023. Consequently, scanning is consistently ~167±1.59% for the mixed age ewes (2012-2023) and increased from 113% (2008) to 154% (2023) in the two-tooths. Lamb wastage for the mixed age ewes has decreased 0.70±0.08%/yr (R2 = 0.88) to 15% in 2023 and, although more variable (R2 = 0.13), the wastage in two-tooths has also reduced from 32% (2014) to 21% (2023). Lamb wastage is negatively related to two-tooth weight at set-stocking, so feeding young stock is a priority. Since 2016, pre-weaning merino lamb growth rates have averaged 286±4.39 g/hd/d with weaning now at 79.3±2.56 days. This consistency coincided with the addition of 210 ha of feed under pivot irrigation that was initially sown in red and white clover and is now in lucerne/grass mixes. The additional feed has meant wool production has remained constant throughout the 15 years of pasture development. Cow numbers have been used to buffer the changes in pasture supply as the dryland and pivot development occurred. These have now increased to their highest level since the development began. The major change in farm income has resulted from the earlier sale of more lambs at a higher average price because they are heavier due to the extra feed. This unique long-term dataset of on-farm performance provides a commercial example of transformational change that has resulted from changes in the farm system, driven by direct feeding of dryland lucerne and irrigation development focused on growing young stock in this 420 mm rainfall environment.

Investigating Flavonoids by HPTLC Analysis Using Aluminium Chloride as Derivatization Reagent

This is the first study to report on high performance thin layer chromatography (HPTLC) generated spectrophotometric data to systematically capture flavonoid compounds using optimized derivatization with either AlCl3 or NaNO2-AlCl3-NaOH as visualisation reagents. While the traditional AlCl3 colorimetric method using UV–Vis analysis provides valuable insights into the presence of flavonoids and allows derivation of the total flavonoid content (TFC) of a sample, HPTLC fingerprints obtained after spraying with AlCl3 or NaNO2-AlCl3-NaOH enable the visualization of the various flavonoids present in a sample based on their respective absorption shifts, thus complementing the traditional TFC assay. In this study, 40 different flavonoids representing different classes (flavonols, flavanolols, flavan-3-ol, flavones, flavanones, and isoflavonoids) were analysed. Upon derivatization with AlCl3 most of the investigated flavonoids recorded bathochromic shifts, yielding characteristic λmax values between 370 and 420 nm, while spraying with NaNO2-AlCl3-NaOH triggered hyperchromic shifts, and thus an increase in absorbance intensity in flavonoids with particular substitution patterns. A few non-flavonoid components with structural similarities to flavonoids (e.g., rosmarinic acid, gallic acid, aspirin, salicylic acid) served as the negative control in this study to determine whether the derivatization reagents allowed exclusive detection of flavonoids. The method was then applied to the analysis of flavonoid containing supplements as well as red clover honey to demonstrate the method’s application in the analysis of natural products.

Plant responses to urban gradients: Extinction, plasticity, adaptation

Abstract Biodiversity‐oriented urban management and planning require information on the drivers of wildlife composition and ecosystem function within cities. Urban landscapes impose environmental gradients along which species may be filtered away, or respond by showing adaptive variation in functional trait values. Such trait variation may in turn be due to a species' phenotypic plasticity, or a consequence of microevolution leading to local adaptation. This study investigates three possible plant responses to urban environmental gradients, with different evolutionary consequences: extinction, plasticity and adaptation. We assessed whether individual functional traits (LMA—leaf mass per area, plant height and flower length), population performance traits (seed mass and germination rate), as well as species frequency in the plant community, responded to gradients in mowing frequency, soil fertility and structure, temperature and surrounding mean building height, among four herbaceous plant species present in the metropolitan area of Strasbourg. Using a common garden experiment, we tested whether the observed trait variation was hereditary, and may thus constitute evidence for local adaptation. Our results detected the three types of expected responses. Plantago lanceolata is plastic to urban gradients, and Trifolium pratense showed both plastic and hereditary responses. Dactylis glomerata and Medicago lupulina showed all three responses: they both declined under increasing mowing frequency, were plastic to surrounding mean building height, and showed hereditary responses to different urban gradients. Urban management and planning therefore impact on the evolutionary capabilities of plants in cities. In the case of management this is highlighted by the detected trends in species' traits and frequency in response to mowing. The consequences of urban planning are evidenced by mean building height eliciting most often plastic and adaptive responses. Synthesis. Herbaceous plants often change their morphology in response to urban conditions: grass cutting, altered soils, warmer temperatures and being surrounded by tightly packed buildings. These changes are sometimes hereditary, which suggests that city management and planning affect the ability of plants to survive and evolve in urban environments.

Rhizobial variation, more than plant variation, mediates plant symbiotic and fitness responses to herbicide stress.

Symbiotic mutualisms provide critical ecosystem services throughout the world. Anthropogenic stressors, however, may disrupt mutualistic interactions and impact ecosystem health. The plant-rhizobia symbiosis promotes plant growth and contributes to the nitrogen (N) cycle. While off-target herbicide exposure is recognized as a significant stressor impacting wild plants, we lack knowledge about how it affects the symbiotic relationship between plants and rhizobia. Moreover, we do not know whether the impact of herbicide exposure on symbiotic traits or plant fitness might be ameliorated by plant or rhizobial genetic variation. To address these gaps, we conducted a greenhouse study where we grew 17 full-sibling genetic families of red clover (Trifolium pratense) either alone (uninoculated) or in symbiosis with one of two genetic strains of rhizobia (Rhizobium leguminosarum) and exposed them to a concentration of the herbicide dicamba that simulated "drift" (i.e., off-target atmospheric movement) or a control solution. We recorded responses in immediate vegetative injury, key features of the plant-rhizobia mutualism (nodule number, nodule size, and N fixation), mutualism outcomes, and plant fitness (biomass). In general, we found that rhizobial variation more than plant variation determined outcomes of mutualism and plant fitness in response to herbicide exposure. Herbicide damage response depended on plant family, but also whether plants were inoculated with rhizobia and if so, with which strain. Rhizobial strain variation determined nodule number and size, but this was herbicide treatment-dependent. In contrast, strain and herbicide treatment independently impacted symbiotic N fixation. And while herbicide exposure significantly reduced plant fitness, this effect depended on inoculation state. Furthermore, the differential fitness benefits that the two rhizobial strains provided plants seemed to diminish under herbicidal conditions. Altogether, these findings suggest that exposure to low levels of herbicide impact key components of the plant-rhizobia mutualism as well as plant fitness, but genetic variation in the partners determines the magnitude and/or direction of these effects. In particular, our results highlight a strong role of rhizobial strain identity in driving both symbiotic and plant growth responses to herbicide stress.

PERSPECTIVES FOR THE USE OF PLANT RAW MATERIALS OF THE CLOVER MEADOW (TRIFOLIUM PRATENSE L.) IN PHARMACY

Background. The creation and registration of original medicines based on plant raw materials are becoming promising areas in pharmaceutical practice. Clover meadow (Trifolium pratense L.) has been used in folk medicine for a long time, due to the content of many biologically active substances with Therapeutic properties. It grows over large areas; extracts are easy to obtain from plant raw materials and have a certain economic attractiveness. In this regard, compounds extracted from meadow clover can be considered as potential precursors for the development of new promising pharmaceuticals. Aim. Carrying out a narrative review on the Perspectives of the use of biologically active substances extracted from the plant raw materials of meadow clover in pharmaceutical practice. Material and methods. The scientific publications of the PubMed biomedical research database are analyzed. Results. Meadow clover (Trifolium pratense L.) is a widespread perennial herbaceous plant belonging to the pharmacopoeia group. Extracts obtained from plant raw materials have a wide range of biological activity. The largest proportion of them are isoflavones, flavonoids, saponins, clovamides and phenolic acids. Isoflavones have a phytoestrogenic effect, and in this regard, they are successfully used in the treatment of diseases of the reproductive system. In addition, their anti-inflammatory, reparative properties have been proven; they can be used for the prevention and recovery of metabolic disorders. Flavonoids, saponins, clovamides and phenolic acids have antioxidant and antiplatelet effects. Conclusion. Among biologically active substances extracted from meadow clover, the greatest use in pharmacological practice was noted for isoflavones. At the same time, there are a few other potentially effective compounds with known medicinal properties. Their further study is required in order to create new original medicines

GWAS for Drought Resilience Traits in Red Clover (Trifolium pratense L.)

Red clover (Trifolium pratense L.) is a well-appreciated grassland crop in temperate climates but suffers from increasingly frequent and severe drought periods. Molecular markers for drought resilience (DR) would benefit breeding initiatives for red clover, as would a better understanding of the genes involved in DR. Two previous studies, as follows, have: (1) identified phenotypic DR traits in a diverse set of red clover accessions; and (2) produced genotypic data using a pooled genotyping-by-sequencing (GBS) approach in the same collection. In the present study, we performed genome-wide association studies (GWAS) for DR using the available phenotypic and genotypic data. Single nucleotide polymorphism (SNP) calling was performed using GBS data and the following two red clover genome assemblies: the recent HEN-17 assembly and the Milvus assembly. SNP positions with significant associations were used to delineate flanking regions in both genome assemblies, while functional annotations were retrieved from Medicago truncatula orthologs. GWAS revealed 19 significant SNPs in the HEN-17-derived SNP set, explaining between 5.3 and 23.2% of the phenotypic variation per SNP–trait combination for DR traits. Among the genes in the SNP-flanking regions, we identified candidate genes related to cell wall structuring, genes encoding sugar-modifying proteins, an ureide permease gene, and other genes linked to stress metabolism pathways. GWAS revealed 29 SNPs in the Milvus-derived SNP set that explained substantially more phenotypic variation for DR traits, between 5.3 and 42.3% per SNP–trait combination. Candidate genes included a DEAD-box ATP-dependent RNA helicase gene, a P-loop nucleoside triphosphate hydrolase gene, a Myb/SANT-like DNA-binding domain protein, and an ubiquitin–protein ligase gene. Most accessions in this study are genetically more closely related to the Milvus genotype than to HEN-17, possibly explaining how the Milvus-derived SNP set yielded more robust associations. The Milvus-derived SNP set pinpointed 10 genomic regions that explained more than 25% of the phenotypic variation for DR traits. A possible next step could be the implementation of these SNP markers in practical breeding programs, which would help to improve DR in red clover. Candidate genes could be further characterized in future research to unravel drought stress resilience in red clover in more detail.

Comparison of Single-Trait and Multi-Trait GBLUP Models for Genomic Prediction in Red Clover

Red clover (Trifolium pratense) is a perennial forage legume wildly used in temperate regions, including northern Europe. Its breeders are under increasing pressure to obtain rapid genetic gains to meet the high demand for improved forage yield and quality. One solution to increase genetic gain by reducing time and increasing accuracy is genomic selection. Thus, efficient genomic prediction (GP) models need to be developed, which are unbiased to traits and harvest time points. This study aimed to develop and evaluate single-trait (ST) and multi-trait (MT) models that simultaneously target more than one trait or cut. The target traits were dry matter yield, crude protein content, net energy for lactation, and neutral detergent fiber. The MT models either combined dry matter yield with one forage quality trait, all traits at one cut, or one trait across all cuts. The results show an increase with MT models where the traits had a genetic correlation of 0.5 or above. This study indicates that non-additive genetic effects have significant but varying effects on the predictive ability and reliability of the models. The key conclusion of this study was that these non-additive genetic effects could be better described by incorporating genetically correlated traits or cuts.

The phytochemical composition of Kuzbass medicinal plants studied by spectrophotometry and chromatography

Flavonoids are plant polyphenols that exhibit biological activity with antibacterial, antiviral, antioxidant, anti-inflammatory, antimutagenic, and anticarcinogenic effects. The medicinal plants of Kuzbass have high contents of flavonoids and other polyphenolic compounds. Therefore, they can be used in medicinal preparations to prevent or treat serious diseases. We studied the following plants collected in Kuzbass: common thyme (Thymus vulgaris Linn., leaves and stems), woolly burdock (Arctium tomentosum Mill., roots), alfalfa (Medicago sativa L., leaves and stems), common lungwort (Pulmonaria officinalis L., leaves and stems), common yarrow (Achillea millefolium L., leaves and stems), red clover (Trifolium pratense L., leaves and stems), common ginseng (Panax ginseng, roots), sweetvetch (Hedysarum neglectum Ledeb., roots), and cow parsnip (Heracleum sibiricum L., inflorescences, leaves, and stems). To extract flavonoids, we used ethanol at concentrations of 40, 55, 60, 70, and 75%. Spectrophotometry was used to determine total flavonoids, while high-performance liquid chromatography was employed to study the qualitative and quantitative composition of the extracts. The highest yield of flavonoids was found in H. sibiricum leaves (at all concentrations except 70%), followed by the 55% and 70% ethanol extracts of T. vulgaris leaves and stems, as well as the 75% ethanol extract of A. millefolium leaves and stems. Thus, these plants have the greatest potential in being used in medicines. High-performance liquid chromatography showed the highest contents of polyphenolic compounds in the samples of P. officinalis, A. millefolium, T. vulgaris, and T. pratense. Our results can be used in further research to produce new medicinal preparations based on the medicinal plants of Kuzbass.

Optimizing polyphenol extraction and UPLC-MS/MS analysis from red clover (Trifolium pratense L.) species using response surface methodology

Polyphenols were extracted from red clover (Trifolium pratense L.) plants following conventional extraction. The combined factors of ethanol concentration (60–80%), extraction time (15–45 min) and extraction temperature (40–80°C) were evaluated. Central composite design software was used to conduct Response Surface Methodology (RSM) modelling and optimize the polyphenol yield from the red clover. Total phenolic content, antioxidant activity and ultra-performance liquid chromatography mass-spectrometry (UPLC-MS/MS) analysis were used to quantify polyphenols. The RSM model identified ethanolic composition having greatest influence (p < 0.05) on the polyphenol yield with extraction yields increasing with percentage ethanol. The optimal extraction conditions were identified as 80% ethanol for 45 minutes at 40°C. When compared with an exhaustive polyphenol extraction method (70% ethanol for 21 h at room temperature), the optimal extraction resulted in a 25.6% increase in TPC yield. UPLC-MS/MS was performed to quantify the individual polyphenols present within the sample, in which biochanin A and formononetin were present in abundance. The outcomes of this modelling and optimization study demonstrate that polyphenols from red clover can be extracted efficiently with minimal environmental and energy cost and thus had the capability to serve as a source of valuable nutraceutical and pharmaceutical products.

Contribution of mycorrhizal symbiosis and root strategy to red clover aboveground biomass under nitrogen addition and phosphorus distribution.

Soil nutrients exhibit heterogeneity in their spatial distribution, presenting challenges to plant acquisition. Notably, phosphorus (P) heterogeneity is a characteristic feature of soil, necessitating the development of adaptive strategies by plants to cope with this phenomenon. To address this, fully crossed three-factor experiments were conducted using red clover within rhizoboxes. Positions of P in three conditions, included P even distribution (even P), P close distribution (close P), and P far distribution (far P). Concurrently, N addition was two amounts(0 and 20mg kg- 1), both with and without AMF inoculation. The findings indicated a decrease in aboveground biomass attributable to uneven P distribution, whereas N and AMF demonstrated the potential to affect aboveground biomass. In a structural equation model, AMF primarily increased aboveground biomass by enhancing nodule number and specific leaf area (SLA). In contrast, N addition improved aboveground biomass through increased nodule number or direct effects. Subsequently, a random forest model indicated that under the far P treatment, fine root length emerged as the primary factor affecting aboveground biomass, followed by thickest root length. Conversely, in the even P treatment, the thickest root length was of paramount importance. In summary, when confronted with uneven P distribution, clover plants adopted various root foraging strategies. AMF played a pivotal role in elevating nodule number, and SLA.

Molecular insights into genistein-NSAID hybrids—synthesis, characterisation and DFT study

AbstractGenistein (GEN) is one of the pharmaceutically valuable phenolic compounds, which belongs to the isoflavone group of flavonoids and is a natural phytohormone found mainly in soybeans and red clover. It affects estrogen receptors, functioning as a selective estrogen receptor modulator (SERM) with anti-inflammatory and antioxidant activity. The presence of reactive phenolic groups in genistein provides an opportunity to expand its structure by introducing components responsible for anti-inflammatory properties. Such an innovative combination of a compound with anticancer and antioxidant potential with an anti-inflammatory compound (NSAID) may lead to interesting new derivatives with dual mechanisms of biological action. The synthesis and characterisation of genistein-NSAID hybrid compounds (ibuprofen, ketoprofen, naproxen, flurbiprofen) was conducted, together with a comprehensive structural and quantum chemistry DFT (density functional theory) computational analysis allowing the description of 1H-NMR and 13C-NMR spectroscopic properties of the starting compounds and the resulting hybrids. The study resulted in the formation of seven hybrid GEN-NSAID derivatives. In the case of ibuprofen, ketoprofen and flurbiprofen, a mixture of isomeric hybrid GEN-4’-NSAID and GEN-7-NSAID derivatives was obtained, whereas, for naproxen, only GEN-4’-NSAID was formed. The structural characteristics of the resulting compounds were determined using MS, IR, 1H-NMR and 13C-NMR spectroscopic methods. The most accurate DFT computational methods for predicting 1H-NMR and 13C-NMR spectra were also established with statistical parameters to assess their accuracy.

Machine learning reveals dynamic controls of soil nitrous oxide emissions from diverse long-term cropping systems.

Soil nitrous oxide (N2O) emissions exhibit high variability in intensively managed cropping systems, which challenges our ability to understand their complex interactions with controlling factors. We leveraged 17 years (2003-2019) of measurements at the Kellogg Biological Station Long-Term Ecological Research (LTER)/Long-Term Agroecosystem Research (LTAR) site to better understand the controls of N2O emissions in four corn-soybean-winter wheat rotations employing conventional, no-till, reduced input, and biologically based/organic inputs. We used a random forest machine learning model to predict daily N2O fluxes, trained separately for each system with 70% of observations, using variables such as crop species, daily air temperature, cumulative 2-day precipitation, water-filled pore space, and soil nitrate and ammonium concentrations. The model explained 29%-42% of daily N2O flux variability in the test data, with greater predictability for the corn phase in each system. The long-term rotations showed different controlling factors and threshold conditions influencing N2O emissions. In the conventional system, the model identified ammonium (>15 kg N ha-1) and daily air temperature (>23°C) as the most influential variables; in the no-till system, climate variables such as precipitation and air temperature were important variables. In low-input and organic systems, where red clover (Trifolium repens L.; before corn) and cereal rye (Secale cereale L.; before soybean) cover crops were integrated, nitrate was the predominant predictor of N2O emissions, followed by precipitation and air temperature. In low-input and biologically based systems, red clover residues increased soil nitrogen availability to influence N2O emissions. Long-term data facilitated machine learning for predicting N2O emissions in response to differential controls and threshold responses to management, environmental, and biogeochemical drivers.

Effects of red and blue light on red clover (Trifolium pratense L.) growth and secondary metabolism

Effects of red and blue light on red clover (Trifolium pratense L.) growth and secondary metabolism

Investigating the Anticancer Potential of Biochanin A in KB Oral Cancer Cells Through the NFκB Pathway.

Squamous cell carcinoma (SCC) is a malignancy primarily affecting squamous cells. Its development is linked to multiple risk factors, such as alcohol and tobacco consumption, human papillomavirus (HPV) infection, and Epstein-Barr Virus (EBV) infection. Biochanin A (BCA), a phytoestrogen extracted from red clover, has been extensively researched for its therapeutic properties. It spans antioxidant activity, anti-inflammatory effects, neuroprotection, cardioprotection, and anticancer potential in different bodily systems. However, its impact on oral cancer remains unexplored. Therefore, this investigation aims to assess the potential anticancer effects of BCA, specifically on KB oral cancer cells. This study utilized KB cells to evaluate the impact of BCA on various cellular parameters, including cell viability, apoptosis, intracellular ROS production, mitochondrial membrane potential, and cell migration. BCA treatment induced several notable effects on KB cells, including reduced cell viability, altered morphology suggestive of apoptosis, heightened oxidative stress, and alterations in mitochondrial membrane potential. Moreover, BCA treatment demonstrated an inhibitory effect on cell migration. The study further investigated the impact of BCA on antioxidant enzyme activities and lipid peroxidation, revealing decreased antioxidant enzyme activities and increased lipid peroxidation across different BCA concentrations (IC50 and IC90). Immunocytochemistry and qRT-PCR analyses unveiled that BCA treatment at varying doses (IC50 and IC90) downregulated the expression of nuclear factor-κB (NF-κB) subunits p50 and p65, pivotal players in cancer progression. In summary, this study sheds light on the promising potential of BCA as an anticancer therapeutic agent for treating oral cancer. Its demonstrated ability to induce apoptosis, perturb cellular functions, and modulate gene expression within cancer cells underscores its significance. Nonetheless, further research, particularly following animal studies, is imperative to comprehensively grasp the breadth of BCA's effects and its viability for clinical applications.

Bioactive Compounds from Natural Products as RHOA/ROCK and VEGFR1 Inhibitors: An In-silico Approach for Developing Therapeutics for ALI/ARDS

Acute Respiratory Distress Syndrome (ARDS) is a dangerous lung condition characterised by non-cardiogenic pulmonary edoema caused by various factors, including inflammation and hypoxia. It is a more severe and evolved form of Acute Lung Injury (ALI) and requires the patient to be on mechanical ventilation for survival. Several medicinal plants, herbs, oils, and natural extracts have been studied for their anti-inflammatory properties and their targeted action on respiratory disorders. The target of the current study is to elaborate on the target-specific action of bioactive compounds from natural products by Molecular Docking and study their drug-likeness along with their other important pharmacokinetic properties. Bioactive compounds (total 71) from Zingiber officinale (ginger), Trifolium pratense (red clover), Curcuma longa (turmeric), Melaleuca alternifolia (tea tree), Ocimum tenuiflorum (Tulsi), Chlorophytum borivilianum (Safed Musli), Cinnamomum cassia (cinnamon), Elettaria cardamomum (cardamom), and Glycine max (soybean) were selected to be investigated and were screened against RhoA and VEGFR1. The ADMET properties and drug-likeness of the bioactive compounds were studied using Molinspiration and ADMETlab 2.0. Docking studies revealed that Hecogenin (-8.4 and -10.3 kcal/mol), Neotigogenin (-7.7 and -9.8 kcal/mol), and Neohecogenin (-7.6 and -9.7 kcal/mol) produced the best docking results, showing the lowest binding energies for RhoA and VEGFR1, respectively. These energies were found to be comparable to the standard ligands Fasudil (-7.3 kcal/mol for RhoA) and Pazopanib (-8.0 kcal/mol for VEGFR1) for the selected targets. Moreover, Stigmasterol (-7.6 kcal/mol) and Genistein (-8.4 kcal/mol) showed a good binding affinity with RhoA and VEGFR1, respectively. The ADME properties of these molecules were also studied. Thus, the best-docked ligands mentioned above can be used as potential novel compounds against these two targets to develop therapeutics against ARDS. Further in-vitro and in-vivo experiments are required to cement these claims and prepare next-generation natural therapeutics for ARDS.

Low N2O emissions induced by root-derived residues compared to aboveground residues of red clover or grass mixed into soil

The default The Intergovernmental Panel on Climate Change (IPCC) guidelines assume a constant N2O emission factor (EFN2O) for both belowground crop residues (BGR) and aboveground residues (AGR), and that ∼70 % of total N2O emissions following renewal of temporary grasslands come from BGR. However, empirical evidence is lacking, which motivated this study. BGR-free and BGR-rich clay loam collected in grass or red clover leys were incubated alone or mixed with AGR and different doses of nitrate over 107 days. The average EFN2O of BGR was around 18 % of that of AGR, and remained low even when soil nitrate concentration was very high, whereas EFN2O of AGR varied largely and rocketed even with a small increase in soil nitrate. The decomposition of the carbon present in crop residues was critical for N2O emissions. Lower EFN2O of BGR relative to AGR were related to slower C decomposition, which was not predicted by the biochemical characteristics. It is also likely that BGR were less conducive than AGR to develop into hotspots for N2O emission because of the roots’ finer distribution and closer contact with soil particles. Differences in EFN2O among AGR were mostly linked to the availability of N, either derived from residue mineralization or present in the soil. In conclusion, N2O accountings based on present IPCC default methodology likely overestimate the contribution by crops’ BGR.

RGB‐based indices for estimating cover crop biomass, nitrogen content, and carbon:nitrogen ratio

AbstractPlant cover and biochemical composition are essential parameters for evaluating cover crop management. Destructive sampling or estimates with aerial imagery require substantial labor, time, expertise, or instrumentation cost. Using low‐cost consumer and mobile phone cameras to estimate plant canopy coverage and biochemical composition could broaden the use of high‐throughput technologies in research and crop management. Here, we estimated canopy development, tissue nitrogen, and biomass of medium red clover (Trifolium pratense L.), a perennial forage legume and common cover crop, using red‐green‐blue (RGB) indices collected with standard settings in non‐standardized field conditions. Pixels were classified as plant or background using combinations of four RGB indices with both unsupervised machine learning and preset thresholds. The excess green minus red (ExGR) index with a preset threshold of zero was the best index and threshold combination. It correctly identified pixels as plant or background 86.25% of the time. This combination also provided accurate estimates of crop growth and quality: Canopy coverage correlated with red clover biomass (R2 = 0.554, root mean square error [RMSE] = 219.29 kg ha−1), and ExGR index values of vegetation pixels were highly correlated with clover nitrogen content (R2 = 0.573, RMSE = 3.5 g kg−1) and carbon:nitrogen ratio (R2 = 0.574, RMSE = 1.29 g g−1). Data collection were simple to implement and stable across imaging conditions. Pending testing across different sensors, sites, and crop species, this method contributes to a growing and open set of decision support tools for agricultural research and management.