Paederia Foetida Linn (Rubiaceae): Chemical Diversity, Phytopharmacological Potential, Quantitative Analysis and Clinical Approaches.

The discovery of novel counteractive pharmaceuticals, which have recently generated much interest, has played a significant role in the development of drugs derived from herbal medicines or botanical sources. Paederia foetida (P. foetida) is one such example of a role in both traditional and traditional medicine.

CRISPR/Cas technology: fueling the future of Biofuel production with sugarcane.

The objective of present review is to provide a scientific overview of sugarcane as a potential feedstock for biofuel and use of genome editing approach for improvement of industrial and agronomical traits in sugarcane. Sugarcane, a perennial tropical grass with a high biomass index, is a promising feedstock for bioethanol production, and its bagasse, rich in lignocellulosic material, serves as an ideal feedstock for producing second-generation bioethanol. To improve the conversion of sugarcane biomass into biofuels, developing varieties with improved biomass degradability and high biomass and sucrose content is essential.

Enhancing Sugarcane Seedling Resilience to Water Stress through Exogenous Abscisic Acid: A Study on Antioxidant Enzymes and Phytohormone Dynamics.

Exogenous hormones play a crucial role in regulating plant growth, development, and stress tolerance. However, the effects of exogenous abscisic acid (ABA) on sugarcane seedlings under water stress remain poorly understood. Here, in this study, a pot experiment was conducted on sugarcane seedlings 4 weeks after transplanting, employing three treatments: control (normal growth), drought (water stress), and drought + ABA (foliar application of 100 μM ABA before water stress).

A systematic review on deep learning-based automated cancer diagnosis models.

Deep learning is gaining importance due to its wide range of applications. Many researchers have utilized deep learning (DL) models for the automated diagnosis of cancer patients. This paper provides a systematic review of DL models for automated diagnosis of cancer patients.

Regulation of an endophytic nitrogen-fixing bacteria GXS16 promoting drought tolerance in sugarcane.

Background: Drought limits crop growth and is an important issue in commercial sugarcane (Saccharum officinarum) production. Drought tolerance in sugarcane induced by endophytic nitrogen-fixing bacteria is a complex biological process that ranges from altered gene expression and cellular metabolism to changes in growth and productivity.

Results: In this study, changes in physiological features and transcriptome related to drought tolerance in sugarcane conferred by the Burkholderia endophytic nitrogen-fixing bacterial strain GXS16 were investigated.

Flowering in sugarcane-insights from the grasses.

Flowering is a crucial phase for angiosperms to continue their species propagation and is highly regulated. In the current review, flowering in sugarcane and the associated mechanisms are elaborately presented. In sugarcane, flowering has two effects, wherein it is a beneficial factor from the breeder's perspective and crucial for crop improvement, but commercially, it depletes the sucrose reserves from the stalks; hence, less value is assigned.

Strategies of pretreatment of feedstocks for optimized bioethanol production: distinct and integrated approaches.

Bioethanol is recognized as a valuable substitute for renewable energy sources to meet the fuel and energy demand of the nation, considered an environmentally friendly resource obtained from agricultural residues such as sugarcane bagasse, rice straw, husk, wheat straw and corn stover. The energy demand is sustained using lignocellulosic biomass to produce bioethanol. Lignocellulosic biomass (LCBs) is the point of attention in replacing the dependence on fossil fuels.

Infestation of Rice by Gall Midge Influences Density and Diversity of and in the Host Plant Microbiome.

The virulence of phytophagous insects is predominantly determined by their ability to evade or suppress host defense for their survival. The rice gall midge (GM, ), a monophagous pest of rice, elicits a host defense similar to the one elicited upon pathogen attack. This could be due to the GM feeding behaviour, wherein the GM endosymbionts are transferred to the host plant oral secretions, and as a result, the host mounts an appropriate defense response(s) (.

COVID-19 Public Opinion: A Twitter Healthcare Data Processing Using Machine Learning Methodologies.

The COVID-19 pandemic has shattered the whole world, and due to this, millions of people have posted their sentiments toward the pandemic on different social media platforms. This resulted in a huge information flow on social media and attracted many research studies aimed at extracting useful information to understand the sentiments. This paper analyses data imported from the Twitter API for the healthcare sector, emphasizing sub-domains, such as vaccines, post-COVID-19 health issues and healthcare service providers.

Target association rule mining to explore novel paediatric illness patterns in emergency settings.

Background And Aims: To assess the hospitalized sick children admitted to the pediatric emergency department (ED) and to find new patterns of clinical and laboratory attributes using association rule mining (ARM).

Methods: In this observational study, 158 children with median (IQR) age 11 months and a PRISM III score of 5 (2-9) were enrolled. Hotspot data mining method was applied to assess clinical attributes, lab investigations and pre-defined outcome parameters of children and their association in sick hospitalized children aged 1 month to 12 years.

A Novel Framework for Abnormal Risk Classification over Fetal Nuchal Translucency Using Adaptive Stochastic Gradient Descent Algorithm.

In most maternity hospitals, an ultrasound scan in the mid-trimester is now a standard element of antenatal care. More fetal abnormalities are being detected in scans as technology advances and ability improves. Fetal anomalies are developmental abnormalities in a fetus that arise during pregnancy, birth defects and congenital abnormalities are related terms.

Protective effect of D-(-)-quinic acid as food supplement in modulating AMP-activated protein kinase signalling pathway activation in HFD induced obesity.

Background: Dietary quinic acid given as the nutritional supplement, which may leads to tryptophan and nicotinamide production in the intestinal tract and NAD precursor which can prevent from the negative consequences of high fat diet (HFD) consumption.

Objective: The present study was designed to assess in vivo and in vitro effect of D-(-)-Quinic acid in high-fat diet induced hyperlipidemia in mice.

Material And Methods: Thirty six albino mice were randomly divided in six groups and each group had six mice.

VCNet: Hybrid Deep Learning Model for Detection and Classification of Lung Carcinoma Using Chest Radiographs.

Detection of malignant lung nodules from Computed Tomography (CT) images is a significant task for radiologists. But, it is time-consuming in nature. Despite numerous breakthroughs in studies on the application of deep learning models for the identification of lung cancer, researchers and doctors still face challenges when trying to deploy the model in clinical settings to achieve improved accuracy and sensitivity on huge datasets.

Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images.

Breast cancer is the most menacing cancer among all types of cancer in women around the globe. Early diagnosis is the only way to increase the treatment options which then decreases the death rate and increases the chance of survival in patients. However, it is a challenging task to differentiate abnormal breast tissues from normal tissues because of their structure and unclear boundaries.

A Neural Network and Optimization Based Lung Cancer Detection System in CT Images.

One of the most common causes of death from cancer for both women and men is lung cancer. Lung nodules are critical for the screening of cancer and early recognition permits treatment and enhances the rate of rehabilitation in patients. Although a lot of work is being done in this area, an increase in accuracy is still required to swell patient persistence rate.

Diagnosis of Lumbar Spondylolisthesis Using a Pruned CNN Model.

Convolutional neural network (CNN) models have made tremendous progress in the medical domain in recent years. The application of the CNN model is restricted due to a huge number of redundant and unnecessary parameters. In this paper, the weight and unit pruning strategy are used to reduce the complexity of the CNN model so that it can be used on small devices for the diagnosis of lumbar spondylolisthesis.

Diagnosis of Lumbar Spondylolisthesis Using Optimized Pretrained CNN Models.

Spondylolisthesis refers to the slippage of one vertebral body over the adjacent one. It is a chronic condition that requires early detection to prevent unpleasant surgery. The paper presents an optimized deep learning model for detecting spondylolisthesis in X-ray radiographs.

Colonization with non-mycorrhizal culturable endophytic fungi enhances orchid growth and indole acetic acid production.

Background: Symbiotic associations of endophytic fungi have been proved by possessing an ability to produce hormones and metabolites for their host plant. Members of the Orchidaceae are obligate mycorrhizal species but a non-mycorrhizal association needs more investigation for their ability to promote plant growth and produce plant growth hormones. In the present study, endophytic fungi were isolated from the roots of Dendrobium longicornu Lindl.

Bioaccumulation of arsenic(V) from wastewater by live and dead Spirogyra sp.

Contaminated water with arsenic causes a negative impact on socioeconomic status in the concerned area. Existing methods are not much adequate, efficient, and appropriate. Bioremediation of heavy metals with microalgae seems to be a promising and holistic approach to counter the pre-existing associated with heavy metal toxicity.

In vitro mature embryo culture protocol of einkorn ( ssp. ) and bread ( L.) wheat under boron stress.

Mature embryos of einkorn ( ssp. ) and bread ( L.) wheat were used for callus induction on media containing four different doses (0, 1, 2 and 4 mg L) of 2,4-D and dicamba supplemented with five different boron concentrations (0, 6.

Potential of live Spirogyra sp. in the bioaccumulation of copper and nickel ions: A study on suitability and sustainability.

Aim: Various industrial and municipal wastes are the major sources of heavy metal contamination in water causing significant environmental issues. Bioremediation is an effective and affordable solution for the removal of metals and metal pollutants from industrial wastewater. This study aimed to assess the efficacy of live and dead Spirogyra sp.

Advances in biotechnology of Gaertn. syn. L.: a nutraceuticals-rich fruit tree with multifaceted ethnomedicinal uses.

Gaertn. syn. L.

Biological Nanofactories: Using Living Forms for Metal Nanoparticle Synthesis.

Metal nanoparticles are nanosized entities with dimensions of 1-100 nm that are increasingly in demand due to applications in diverse fields like electronics, sensing, environmental remediation, oil recovery and drug delivery. Metal nanoparticles possess large surface energy and properties different from bulk materials due to their small size, large surface area with free dangling bonds and higher reactivity. High cost and pernicious effects associated with the chemical and physical methods of nanoparticle synthesis are gradually paving the way for biological methods due to their eco-friendly nature.