Impact of rhizobacterial inoculation in plant growth medium to mitigate lead stress in Tomato (Solanum lycopersicum L.).

This study investigates the effects of lead stress on tomato plants and explores the potential role of plant growth-promoting rhizobacteria (PGPR) to alleviate this stress. The experiment was conducted in pots, introducing varying lead levels (0, 100, 200, 300, 400, and 500 mg kg⁻¹) using lead nitrate. For rhizobacterial inoculation, pre-characterized LTPGP strains S5 Pseudomonas fluorescens A506 and S10 Pseudomonas fluorescens LMG 2189 were used.

A Cross-Sectional Serological Study to Assess the Prevalence and Risk Factors of Anaplasmosis in Dromedary Camels in Punjab, Pakistan.

Anaplasmosis is an infectious disease transmitted by ticks and caused by obligate intracellular pathogen of belonging to genus Infections of one-humped camels () and llamas () have been reported previously. The aim of this study was to investigate the seroprevalence and risk factors of anti- spp. antibodies in of the Punjab, Pakistan.

Allium chromosome evolution and DNA sequence localization.

Background: Molecular cytogenetics, utilizing DNA probes, serves as a critical tool for mapping genes to the physical structures of chromosomes.

Methods: In this study, we examined three Allium species: A. cepa L.

Comparative Study of Essential Oils Extracted From Miller Seeds Using Hydrodistillation, Steam Distillation, and Superheated Steam Distillation.

Miller is a highly valued aromatic and nutritious plant. The unique compositions of its essential oil make it more valuable in the flavor, fragrance, and medicinal industries. However, the potential of superheated steam distillation for obtaining essential oils from its seeds has not been explored in detail.

Impact of electro-acupuncture on EAAT2 and NMDAR-2B expression in goats with visceral hypersensitivity.

Objective: This study evaluates the effect of electro-acupuncture (EA) on visceral hypersensitivity (VH) and the expression of N-methyl-D-aspartate receptor-2B (NMDAR-2B) and glutamate transporter EAAT2 in goats.

Methods: Twenty-four goats were divided into four groups: saline, 2, 4, 6-Trinitrobenzenesulfonic acid (TNBS), TNBS + EA, and sham EA. EA was administered at Zusanli (ST36) with 60 Hz and 1-3 mA on specified days.

Clinical and genetic characterization of a progressive RBL2-associated neurodevelopmental disorder.

Retinoblastoma (RB) proteins are highly conserved transcriptional regulators that play important roles during development by regulating cell-cycle gene expression. RBL2 dysfunction has been linked to a severe neurodevelopmental disorder. However, to date, clinical features have only been described in six individuals carrying five biallelic predicted loss of function (pLOF) variants.

Ultra-Sensitive Abscisic Acid Detection Using Gold and 4-Mercaptopyridine Perovskite-Engineered Robust Nanofibers (GLAMPER-NFs) under Surface-Enhanced Raman Spectroscopy.

This study explores the development and application of gold and 4-mercaptopyridine (MPY) perovskite-engineered robust nanofibers (GLAMPER-NFs) for the ultrasensitive detection of Abscisic acid (ABA) under Raman spectroscopy, a crucial plant hormone. The GLAMPER-NFs composite material, consisting of MAPbCl nanofibers integrated with MPY-coated gold nanostructures, demonstrates exceptional performance in surface-enhanced Raman scattering (SERS)-based sensing. The study elucidates the material structure and properties through comprehensive characterization using scanning electron microscopy (SEM), UV-vis spectroscopy, fluorescence spectroscopy, Fourier transform infrared, and Raman spectroscopy.

Smart agriculture: utilizing machine learning and deep learning for drought stress identification in crops.

Plant stress reduction research has advanced significantly with the use of Artificial Intelligence (AI) techniques, such as machine learning and deep learning. This is a significant step toward sustainable agriculture. Innovative insights into the physiological responses of plants mostly crops to drought stress have been revealed through the use of complex algorithms like gradient boosting, support vector machines (SVM), recurrent neural network (RNN), and long short-term memory (LSTM), combined with a thorough examination of the TYRKC and RBR-E3 domains in stress-associated signaling proteins across a range of crop species.

Performance evaluation of irrigation outlets with physical model study in Indus basin irrigation system of Pakistan.

The efficiency of water distribution at primary, secondary, and tertiary levels in the Indus Basin Irrigation System (IBIS) has historically suffered due to poor design, suboptimal operation, and water scarcity. To address these issues, the system has been designed with ungated irrigation outlets to ensure equitable water allocation at secondary and tertiary levels. This research evaluates the hydraulic performance of three irrigation outlets: adjustable proportional module (APM), adjustable orifice semi-module (AOSM), and open flume (OF) using a physical model study.

Preparation and Characterization of Essential oil from Lavandula spica Plant and its Antimicrobial Activity against Pseudomonas aeruginosa and Staphylococcus aureus.

The biological properties of herbs and essential oils (EOs), such as their antibacterial, analgesic, anti-inflammatory, antioxidant, and anticancer characteristics, make them widely used in a variety of fields. This research aims to assess the antibacterial efficacy of lavender oil against Staphylococcus aureus (S. aureus) and Pseudomonas aeruginosa (P.

Computational Identification of Milk Trait Regulation Through Transcription Factor Cooperation in Murciano-Granadina Goats.

The Murciano-Granadina goat (MUG) is a renowned dairy breed, known for its adaptability and resilience, as well as for its exceptional milk traits characterized by high protein and fat content, along with low somatic cell counts. These traits are governed by complex biological processes, crucial in shaping phenotypic diversity. Thus, it is imperative to explore the factors regulating milk production and lactation for this breed.

Development and biochemical characterization of freeze-dried guava powder fortified with Lactobacillus plantarum.

Guava (Psidium guajava L.) is one of the most nutrient-dense fruits, which is native to tropical and subtropical regions of the world. The processing of value-added products from guava has not been carried out on a scale similar to some other fruits, which offers an opportunity to fully exploit the potential of this fruit, such as guava-based nutraceutical food products.

Exploration of underutilized chayote fractions following drying and extraction.

Valorizing neglected crop byproducts through eco-friendly techniques has gained attention as underutilized crops offer new sources of bioactive components. This study examined the chemical composition, phytochemicals, and antioxidant activities in six fractions of the underutilized chayote (Sechium edule). Each fraction was microwave-dried and extracted with ultrasound assistance.

UV/visible absorption maxima prediction of water-soluble organic compounds and generation of library of new organic compounds.

In this study, UV/visible absorption maxima of organic compounds are predicted with the help of machine learning (ML). Four ML models are evaluated, the gradient boosting model has performed best. We also analyzed feature importance.

Validation of SSR markers for identification of high-yielding and Phytophthora Capsici root rot resistant chilli genotypes.

The study was designed to validate the previously reported 34 SSR markers using 78 chilli genotypes to detect significant trait specific markers as well as superior genotypes resistant to Phytophthora capsici root rot (PcRR). In this context, the identification of germplasm with higher yield per plant (YPP) leads to hype in stress tolerance index (STI) in genotypes, Chakwal3 (11.98), Greenfire (10.

Exploration of BRCA1 and BRCA2 mutations in gastric cancer patients through next generation sequencing: implications for diagnosis and therapy.

Objectives: The study aims to characterize BRCA1/2 mutations in Pakistani gastric cancer (GC) patients, identifying unique pathogenic variants and evaluating their potential as diagnostic biomarkers, while also exploring therapeutic avenues for personalized treatment strategies.

Methodology: In this study, we investigated the role of Breast Cancer gene 1 (BRCA1) and Breast Cancer gene 2 (BRCA2) mutations in Pakistani GC patients and their functional implications using Next-Generation Sequencing (NGS).

Results: Through NGS, we identified a total of 19 mutations in BRCA1 and 11 mutations in BRCA2, all with high mutation quality scores.

Harnessing hybrid deep learning approach for personalized retrieval in e-learning.

The current worldwide pandemic has significantly increased the need for online learning platforms, hence presenting difficulty in choosing appropriate course materials from the vast online educational resources due to user knowledge frameworks variations. This paper presents a novel course recommendation system called the Deep Learning-based Course Recommendation System (DLCRS). The DLCRS combines a hybrid Sequential GRU+adam optimizer with collaborative filtering techniques to offer accurate and learner-centric course suggestions.

Foliar application of silver (Ag-NPs) and copper (Cu-NPs) nanoparticles enhances phenotypic traits and oil quality in Brassica napus L.

Nanotechnology represents a burgeoning field of science that enables advanced research across various domains. In recent years, there has been a notable increase in the utilization of silver nanoparticles (AgNPs) for diverse agricultural and industrial applications. Similarly, copper nanoparticles (CuNPs) have significant attention in agriculture due to their cost-effectiveness and practicality.

CRISPR applications in microbial World: Assessing the opportunities and challenges.

Genome editing has emerged during the past few decades in the scientific research area to manipulate genetic composition, obtain desired traits, and deal with biological challenges by exploring genetic traits and their sequences at a level of precision. The discovery of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) as a genome editing tool has offered a much better understanding of cellular and molecular mechanisms. This technology emerges as one of the most promising candidates for genome editing, offering several advantages over other techniques such as high accuracy and specificity.

Comparative efficiency of Geotrichum candidum microcapsules prepared with alginate and in combination with other polymers: In vitro evaluation.

Microencapsulation is utilized to protect probiotics, such as Geotrichum candidum, ensuring their survival, stability, and targeted release. The encapsulation efficiency depends on factors such as the type and concentration of the polymers and the encapsulation method. In this study, G.

Accelerated discovery of polymer donors for organic solar cells through machine learning: From library creation to performance forecasting.

The design of novel polymer donors for organic solar cells has been a major research focus for decades, but discovering unique materials remains challenging due to the high cost of experimentation. In this study, machine learning models are employed to predict power conversion efficiency (PCE), Mordred descriptors are used for model training. Among the four machine learning models evaluated, the gradient boosting regressor emerged as the best-performing model.

Exploring the impact of Joule heating and Brownian motion on assisting and opposing flows in Eyring-Prandtl fluid.

Motivation And Objectives: The basic aim of this investigation is to explore the energy transfer impact on Eyring-Prandtl fluid, a topic that has not been previously examined, thereby paving the way for future researchers. The present literature is crucial for advancing thermal management in engineering applications. This study aims to numerically investigate the thermophoretic effects and Brownian motion of non-Newtonian nanofluid relying on Eyring-Prandtl fluid model across the stretching sheet.