Search Results (121)

Plant growth-promoting rhizobacteria (PGPR) are beneficial soil microorganisms that enhance plant growth and stress tolerance through various mechanisms, including phytohormone production, EPS production, phosphate solubilization, and extracellular enzyme production. These bacteria establish endosymbiotic relationships with plants, improving nutrient availability and overall crop productivity. Despite extensive research on PGPR isolation, their practical application in agricultural fields has faced challenges due to environmental stresses and limited survival during storage. To address these limitations, the present study aimed to isolate salt-tolerant bacterial strains and formulate them with organic carriers to enhance their stability and effectiveness under saline conditions. The isolated bacterial strains exhibited high salt tolerance, surviving NaCl concentrations of up to 850 millimolar. These strains demonstrated basic key plant growth-promoting traits, including phosphate solubilization, auxin production, and nitrogen fixation. The application of carrier-based formulations with both strains, Bacillus wiedmannii (RR2) and Bacillus paramobilis (RR3), improved physiological and biochemical parameters in wheat plants subjected to salinity stress. The treated plants, when subjected to salinity stress, showed notable increases in chlorophyll a (73.3% by Peat + RR3), chlorophyll b (41.1% by Compost + RR3), carotenoids (51.1% by Peat + RR3), relative water content (77.7% by Compost + RR2), proline (75.8% by compost + RR3), and total sugar content (12.4% by peat + RR2), as compared to the stressed control. Plant yield parameters such as stem length (35.1% by Peat + RR3), spike length (22.5% by Peat + RR2), number of spikes (67.6% by Peat + RR3), and grain weight (39.8% by Peat + RR3) were also enhanced and compared to the stressed control. These results demonstrate the potential of the selected salt-tolerant PGPR strains (ST-strains) to mitigate salinity stress and improve wheat yield under natural field conditions. The study highlights the significance of carrier-based PGPR applications as an effective and sustainable approach for enhancing crop productivity in saline-affected soils. Full article

Rice (Oryza sativa) is a globally important crop that plays a central role in maintaining food security. This scientific review examines the critical role of genetic disease resistance in protecting rice yields, dissecting at the molecular level how rice plants detect and respond to pathogen attacks while evaluating modern approaches to developing improved resistant varieties. The analysis covers single-gene-mediated and multi-gene resistance systems, detailing how on one hand specific resistance proteins, defense signaling components, and clustered loci work together to provide comprehensive protection against a wide range of pathogens and yet their production is severely impacted by pathogens such as Xanthomonas oryzae (bacterial blight) and Magnaporthe oryzae (rice blast). The discussion extends to breakthrough breeding technologies currently revolutionizing rice improvement programs, including DNA marker-assisted selection for accelerating traditional breeding, gene conversion methods for introducing new resistance traits, and precision genome editing tools such as CRISPR/Cas9 for enabling targeted genetic modifications. By integrating advances in molecular biology and genomics, these approaches offer sustainable solutions to safeguard rice yields against evolving pathogens. Full article

The growing need to reduce methane emissions from ruminants while enhancing feed utilization has driven the development of innovative in vitro measurement techniques. This review examines the Gas Endeavour (GES), an automated volumetric apparatus that quantifies both total gas and methane production in real time during rumen fermentation. Utilizing the principles of liquid displacement and buoyancy, the GES integrates a thermostatically controlled water bath, specialized gas flow cells, and an alkaline CO₂ absorption unit to deliver precise kinetic data on fermentation. Compared to conventional methods—which often rely on manual measurements and post-incubation gas chromatography—the GES provides continuous monitoring and immediate data acquisition, reducing labour and potential errors. This review discusses the system’s design, operational challenges such as controlling headspace pressure and ensuring consistent inoculum preparation, and its applications in both animal nutrition and biomethane potential assessments. The findings suggest that, with further standardization and protocol refinement, the GES could significantly advance research aimed at optimizing feed digestibility and mitigating methane emissions in ruminant production systems. Full article

Insulin resistance (IR) is a significant factor in the development and progression of metabolic-related diseases like dyslipidemia, T2DM, hypertension, nonalcoholic fatty liver disease, cardiovascular and cerebrovascular disorders, and cancer. The pathogenesis of IR depends on multiple factors, including age, genetic predisposition, obesity, oxidative stress, among others. Abnormalities in the insulin-signaling cascade lead to IR in the host, including insulin receptor abnormalities, internal environment disturbances, and metabolic alterations in the muscle, liver, and cellular organelles. The complex and multifaceted characteristics of insulin signaling and insulin resistance envisage their thorough and comprehensive understanding at the cellular and molecular level. Therapeutic strategies for IR include exercise, dietary interventions, and pharmacotherapy. However, there are still gaps to be addressed, and more precise biomarkers for associated chronic diseases and lifestyle interventions are needed. Understanding these pathways is essential for developing effective treatments for IR, reducing healthcare costs, and improving quality of patient life. Full article

The study of bubble growth and collapse is of great significance in the context of sustainability due to its influence on numerous energy-related processes and technologies. Understanding the dynamics of bubble behavior is vital for optimising heat transfer efficiency, which has an energetic role in improving the performance of sustainable systems such as nuclear reactors, thermal inkjet printing, and nucleate boiling. Indeed, researchers can progress strategies to enhance the efficiency of these technologies by analysing the parameters influencing bubble growth and collapse, which can lead to reduced energy consumption and environmental impact. Although several theoretical models and experimental investigations have been achieved in the past to inspect bubble growth and collapse, a thorough review and critical assessment of the studies conducted have not yet been achieved. This review aims to provide a comprehensive understanding of the relationship between bubble dynamics and sustainability, highlighting the potential for further research and development in this area. Specifically, the scope and limitations of past research on bubble growth and collapse is conducted to fill this gap in the open literature. The review covers both numerical and experimental studies of bubble growth and collapse in a wide set of innovative industrial applications including nuclear reactors, thermal inkjet printing, nucleate boiling, hydrodynamic erosion, and ultrasonic and medicinal therapy. The current review also attempts to illustrate and evaluate the numerical methods used and underlines the most relevant results from the studies that were looked at in order to provide researchers with a clear picture of the growth and collapse of bubbles in different applications. The results give a precise understanding of the dynamics of bubble growth and collapse and the related temperature change and cumulative heat transmission from the thermal boundary layer. Additionally, it has been demonstrated that simulation-based models can effectively predict transport coefficients. However, the review observes a number of limitations of the past research on bubble growth and collapse. Due to numerical instability, very little work with respect to dynamic modelling has been carried out on the mechanisms of bubble collapse. Accordingly, a number of recommendations are made for the improvement of heat transmission during bubble growth and collapse. Specifically, future criteria for the highest heat transmission will demand more precise experimental and numerical approaches. Full article

The diet of Apis mellifera L. is a crucial factor for managing its colonies particularly during dearth periods. Numerous diets have been developed; however, their global implementation faces challenges due to diverse climatic conditions and some other factors. To address this issue, three previously evaluated diets (selected from seven) were tested to assess their effects on A. mellifera using key health biomarkers (immune function, stress response) and performance metrics (foraging activity, honey quality, and social interactions). The experiment was conducted using 12 colonies, including three replications, in The Islamia University of Bahawalpur, Pakistan, from June to September 2023. The results revealed that all the tested parameters were significantly affected by diets. Highest phenol-oxidase activity was recorded in T1 (28.7 U/mg). Heat shock protein (HSP) bands showed that T1 had the fewest (Hsp70), while T0 had more bands (Hsp40, Hsp60, and Hsp70), indicating stress differences. In foraging activity, average number of outgoing bees were highest in T1 (81.8) and lowest in T0 (31.2) and similar trend was followed for returning bees, i.e., T1 (81.8) and T0 (31.2). For pollen-carrying bees, the highest bees were counted in T1 (34.9), and the lowest in T0 (4.10). Honey quality was also significantly affected by diets, pH was highest in T1 (3.85), while moisture was highest in T0 (19.44%). Diastase activity, ash content, and electrical conductivity were best in T1 (13.74 units/g, 0.17%, 0.94 mS/cm, respectively). Mineral content was highest in T1 (406.54 mg/kg), and fructose content also peaked in T1 (396.21 mg/kg). Antioxidant contents, total phenolic content, flavonoid content, and ORAC value were highest in T1 (60.50 mg GAE/100 g, 44.41 mg QE/100 g, 10,237.30 µmol TE/g), while T0 consistently showed the lowest values across all parameters. In social interaction experiments, trophallaxis events were most frequent in T1 (7.38), and T1 also exhibited the longest trophallaxis time (5.51 s). The number of bees per trophallaxis event and antennation frequency followed a similar trend, with the highest recorded in T1 (5.16 bees/event, 10.1 antennation frequency) and the lowest in T0 (2.94 bees/event, 4.18 antennation frequency). Therefore, diet-1 (Watermelon juice 20 mL + Fenugreek powder 2 g + Chickpea flour 20 g + Lupin flour 20 g + Mung bean flour 20 g + Yeast 10 g + Powdered sugar 40 g + vegetable oil 10 mL) is recommended as a suitable substitute for managing A. mellifera colonies during dearth periods. Full article

Background/Objectives: Metallic NPs have been explored for various therapeutic uses owing to utilitarian physicochemical characteristics such as antibacterial, anti-inflammatory, and healing properties. The objective of this study is to evaluate the therapeutic potential of novel silver carbonate nanostructures in promoting wound healing and their antibacterial activity against Pseudomonas chengduensis and Staphylococcus aureus. Methods: In this work, we prepared Ag₂CO₃ nanoparticles through a two-step methodology that was expected to improve the material’s biomedical performance and biocompatibility. The characterization and assessment of synthesized NPs biocompatibility were conducted using hemolysis assays on the blood of a healthy male human. Further, we performed molecular docking analysis to confirm interactions of silver NPs with biological molecules. Results: In detail, the synthesized NPs showed <5% hemolysis activity at various concentrations, confirming their therapeutic applicability. Additionally, the NPs had good metabolic activities; they raised the T3/T4 hormone content and acted effectively on Insulin-like Growth Factor 1 (IGF-1) in diabetic models. They also facilitated the rate of repair by having the diabetic wounds reach 100% re-epithelialization by day 13, unlike the control group, which reached the same level only by day 16. The synthesized Ag₂CO₃ NPs exhibited high antimicrobial potential against both Pseudomonas chengduensis and Staphylococcus aureus, hence being a potential material that can be used for infection control in biomedical tissue engineering applications. Conclusions: These findings concluded that novel synthesis methods lead to the formation of NPs with higher therapeutic prospects; however, studies of their metaphysical and endocrinological effects are necessary. Full article

In recent decades, the use of pesticides has become fundamental to agricultural growth. However, the persistent and toxic nature of pesticides has led to significant concerns regarding their ecological and human health consequences. Therefore, for a better understanding of pesticide contamination and its potential risks, here we assessed the levels of five emerging pesticides—acetochlor, imidacloprid, MCPA, atrazine, and allethrin—in soil samples from ponds used for irrigation and in drinking water samples from nearby areas in Lahore, Pakistan. Our findings revealed that 100% of the samples were contaminated, posing substantial ecological and human health risks. Based on the toxic units (TU_sum), all the soil samples showed higher toxic pressure, exceeding acute and chronic toxicity thresholds for earthworms, while 100% of water samples posed chronic toxicity risks to crustaceans and 10% to algae. Pollution index (PI) analysis further classified 100% of the soil samples and 10% of the water samples as highly polluted. These findings show high-pesticide residues in both soil and water and highlight immediate risk assessment and mitigation measures to protect non-target organisms. This preliminary information can be used to adopt risk assessment monitoring programmes and help higher authorities in making policies and guidelines to mitigate the escalating risk for ecology and humans. Full article

Brain tumour disease develops due to abnormal cell proliferation. The early identification of brain tumours is vital for their effective treatment. Most currently available examination methods are laborious, require extensive manual instructions, and produce subpar findings. The EfficientNet-B0 architecture was used to diagnose brain tumours using magnetic resonance imaging (MRI). The fine-tuned EffeceintNet B0 model was proposed for the Internet of Medical Things (IoMT) environment. The fine-tuned EfficientNet-B0 architecture was employed to classify four different stages of brain tumours from the MRI images. The fine-tuned model showed 99% accuracy in the detection of four different classes of brain tumour detection (glioma, no tumour, meningioma, and pituitary). The proposed model performed very well in the detection of the pituitary class with a precision of 0.95, recall of 0.98, and F1 score of 0.96. The proposed model also performed very well in the detection of the no-tumour class with values of 0.99, 0.90, and 0.94 for precision, recall, and the F1 score, respectively. The precision, recall, and F1 scores for Glioma and Meningioma classes were also high. The proposed solution has several implications for enhancing clinical investigations of brain tumours. Full article

Climate change has emerged as one of the most significant challenges in modern agriculture, with potential implications for global food security. The impact of changing climatic conditions on crop yield, particularly for staple crops like wheat, has raised concerns about future food production. By integrating historical climate data, GCM (CMIP3) projections, and wheat-yield records, our analysis aims to provide significant insights into how climate change may affect wheat output. This research uses advanced machine learning models to explore the intricate relationship between climate change and wheat-yield prediction. Machine learning models used include multiple linear regression (MLR), boosted tree, random forest, ensemble models, and several types of ANNs: ANN (multi-layer perceptron), ANN (probabilistic neural network), ANN (generalized feed-forward), and ANN (linear regression). The model was evaluated and validated against yield and weather data from three Punjab, Pakistan, regions (1991–2021). The calibrated yield response model used downscaled global climate model (GCM) outputs for the SRA2, B1, and A1B average collective CO₂ emissions scenarios to anticipate yield changes through 2052. Results showed that maximum temperature (R = 0.116) was the primary climate factor affecting wheat yield in Punjab, preceding the $T_{min}$ (R = 0.114), while rainfall had a negligible impact (R = 0.000). The ensemble model (R = 0.988, nRMSE= 8.0%, MAE = 0.090) demonstrated outstanding yield performance, outperforming Random Forest Regression (R = 0.909, nRMSE = 18%, MAE = 0.182), ANN(MLP) (R = 0.902, MAE = 0.238, nRMSE = 17.0%), and boosting tree (R = 0.902, nRMSE = 20%, MAE = 0.198). ANN(PNN) performed inadequately. The ensemble model and RF showed better yield results with $R^2$ = 0.953, 0.791. The expected yield is 5.5% lower than the greatest average yield reported at the site in 2052. The study predicts that site-specific wheat output will experience a significant loss due to climate change. This decrease, which is anticipated to be 5.5% lower than the highest yield ever recorded, points to a potential future loss in wheat output that might worsen food insecurity. Additionally, our findings highlighted that ensemble approaches leveraging multiple model strengths could offer more accurate and reliable predictions under varying climate scenarios. This suggests a significant potential for integrating machine learning in developing climate-resilient agricultural practices, paving the way for future sustainable food security solutions. Full article

Background: Type 2 diabetes mellitus (T2DM) is becoming a major global health concern, especially in developing nations. The high prevalence of obesity and related diabetes cases are attributed to rapid economic progress, physical inactivity, the consumption of high-calorie foods, and changing lifestyles. Objectives: We investigated the roles of pro-inflammatory chemokines CCL1, 2, 4, and 5 in T2DM with varying levels of obesity in the Asir region of Saudi Arabia. Materials and Methods: In total, 170 confirmed T2DM subjects and a normal control group were enrolled. Demographic data, serum levels of CCL-1, 2, 4, and 5, and biochemical indices were assessed in the subjects and control groups by standard procedures. Results: T2DM subjects were divided into four groups: A (normal body weight), B (overweight), C (obese), and D (highly obese). We observed that male and female control subjects had similar mean serum concentrations of pro-inflammatory chemokines CCL-1, 2, 4, and 5. T2DM subjects in all the four groups showed significantly higher levels of all the four chemokines compared to the controls, regardless of gender. In T2DM subjects with obesity and severe obesity, the rise was most significant. There was a progressive rise in the concentrations of CCL-1, 2, and 4 in T2DM subjects with increasing BMI. Serum CCL5 levels increased significantly in all T2DM subject groups. The increase in CCL5 was more predominant in normal-weight people, compared to overweight and obese T2DM subjects. Conclusions: Male and female control subjects had similar serum levels of pro-inflammatory chemokines CCL-1, 2, 4, and 5. The progressive rise in blood concentrations of three pro-inflammatory chemokines CCL-1, 2, and 4 in T2DM subjects with increasing BMI supports the idea that dyslipidemia and obesity contribute to chronic inflammation and insulin resistance. Serum CCL5 levels increased significantly in all T2DM subject groups. The selective and more pronounced increase in CCL5 in the T2DM group with normal BMI, compared to subjects with varying degrees of obesity, was rather surprising. Further research is needed to determine if CCL5 underexpression in overweight and obese T2DM subjects is due to some unexplained counterbalancing processes. Full article

In this study, a new species of the subgenus Pullus belonging to the Scymnus genus from Pakistan, Scymnus (Pullus) cardi sp. nov., was described and illustrated, with information on its distribution, host plants, and prey. Additionally, the completed mitochondrial genome (mitogenome) of the new species using high-throughput sequencing technology was obtained. The genome contains the typical 37 genes (13 protein-coding genes, two ribosomal RNAs, and 22 transfer RNAs) and a non-coding control region, and is arranged in the same order as that of the putative ancestor of beetles. The AT content of the mitogenome is approximately 85.1%, with AT skew and GC skew of 0.05 and −0.43, respectively. The calculated values of relative synonymous codon usage (RSCU) determine that the codon UUA (L) has the highest frequency. Furthermore, we explored the phylogenetic relationship among 59 representatives of the Coccinellidae using Bayesian inference and maximum likelihood methods, the results of which strongly support the monophyly of Coccinellinae. The phylogenetic results positioned Scymnus (Pullus) cardi in a well-supported clade with Scymnus (Pullus) loewii and Scymnus (Pullus) rubricaudus within the genus Scymnus and the tribe Scymnini. The mitochondrial sequence of S. (P.) cardi will contribute to the mitochondrial genome database and provide helpful information for the identification and phylogeny of Coccinellidae. Full article

Due to its high pollutant rejection and low energy usage, the spiral wound module of reverse osmosis (RO) process is the most commonly used technology utilised in wastewater treatment. For a spiral wound module, the presence of a feed spacer is important as a key solution to mitigate the concentration polarisation phenomenon, due to disorderly fluid flow, and to improve the mass transfer coefficient. Undoubtedly, improvements in the spiral wound module design, mainly in the symmetrical shape of the feed spacer, can have a significant impact on the cost and probable use of these modules. Despite the wide interest in appraising the impact of feed spacer geometry and orientation on the performance of a spiral wound module for RO process-based water desalination, the hydrodynamics of feed spacers (pressure drop and mass transfer coefficient) and the associated influences of feed spacer design (the height of the feed spacer, the angle of the filaments, and the porosity) on the removal of pollutants from wastewater have not yet been addressed. The current investigation aims to fill this gap by studying the hydrodynamics and design parameters of the selected parallelogram feed spacer type ultrafiltration (UF−3) for the removal of dimethylphenol from wastewater. Using model-based simulation, the impacts of UF−3 feed spacer design parameters, including the height, angle between the filaments (orientation), and porosity on the pressure drop, friction factor, axial flow fluid velocity, mass transfer coefficient, water flux, dimethylphenol rejection, recovery rate, and specific energy consumption are detailed in this study. The study intends to demonstrate the optimum design features of UF−3 feed spacer that should be considered to assure the highest elimination of dimethylphenol from wastewater in addition to the lowest specific energy consumption. Full article

This study carefully assesses the capability of supervised machine learning classification algorithms in identifying land cover (LC) in the context of the Jhelum River basin in Kashmir. Sentinel 2 and Landsat 8 high-resolution data from two satellite sources were used. Through preprocessing techniques, we removed any potential noise inherent to satellite imagery and assured data consistency. The study then utilized and compared the skills of the supervised algorithms random forest (RF) and support vector machine (SVM). A hybrid approach, amalgamating classifications from both methods, was also tested for potential synergistic enhancements in accuracy. Using a stratified random sampling approach for validation, the SVM algorithm emerged with a commendable accuracy rate of 82.5%. Using simulations from 2000 to 2015, the soil and water assessment tool (SWAT) model was used to further explore the hydrological effects of LC alterations. Between 2009 and 2019, there were discernible changes in the land cover, with a greater emphasis on ranges, forests, and agricultural plains. When these changes were combined with the results of the hydrologic simulation, a resultant fall in average annual runoff—from above 700 mm to below 600 mm—was seen. With runoff values possibly ranging between 547 mm and 747 mm, the statistics emphasize the direct effects of urban communities encroaching upon forest, agricultural, and barren lands. This study concludes by highlighting the crucial role that technical pipelines play in enhancing LC classifications and by providing suggestions for future water resource estimation and hydrological impact evaluations. Full article

Fluoride (F⁻) pollution in potable groundwater (GW) is a serious environmental concern in Pakistan with substantial human health hazard reports. The research on F⁻ pollution in GW resources in Sindh Province is still incomplete. To explore the realistic conditions, the present research aimed to investigate the GW quality of community tube wells concerning F⁻ contamination in Tharparkar, Sindh, Pakistan. A total of 53 samples were collected and examined for F⁻, along with other physicochemical parameters. The F⁻ values observed varied from 0.2–4.2 mg/L, with a mean value of 1.63 mg/L. Among the 53 samples, 46% had F⁻ levels that were higher than the World Health Organization’s (WHO) recommended limit (1.5 mg/L). The water type of the studied region was Ca-HCO₃ type, which can be attributed to fresh recharged water. The interaction of rock–water contact controls the hydrochemistry of GW. The GW resources of the research zone were highly saturated with fluorite minerals. Human health risk calculation outcomes exposed that 21 samples showed high HQ values for children and 7 samples showed high values for adults in the research zone. Children are at high risk in the study area from drinking F⁻-contaminated GW. WQI results showed that 31 samples were not suitable for drinking. Full article