Microbial production of keratinase from Bacillus velezensis strain MAMA: A novel enzyme for eco-friendly degradation of keratin waste.

Keratin waste has become an increasingly serious environmental and health hazard. Keratin waste is mainly composed of keratin protein, which is one of the most difficult polymers to break down in nature and is resistant to many physical, chemical, and biological agents. With physical and chemical methods being environment damaging and costly, microbial degradation of keratin using keratinase enzyme is of great significance as it is both environment friendly and cost-effective. The aim of this study was to extract and purify keratinase from bacterial species isolated from the soil. Among the organisms, an isolate of Bacillus velezensis, coded as MAMA could break down chicken feathers within 72 hours (h). The isolated strain produced significant levels of keratinase in mineral salt medium by supplying chicken feathers as the sole source of nitrogen and carbon. Feather deterioration was observed with the naked eye, and enzyme activity was evaluated using a spectrophotometric assay. Sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and zymography results revealed that the keratinase protein produced by Bacillus velezensis had a molecular weight between 40 and 55 kilodalton (kDa).

Comparative study on efficiency of surface enhanced coal fly ash and raw coal fly ash for the removal of hazardous dyes in wastewater: optimization through response surface methodology.

Crystal violet (CV) dye, because of its non-biodegradability and harmful effects, poses a significant challenge for wastewater treatment. This study addresses the efficiency of easily accessible coal fly ash (CFA)-based adsorbents such as raw coal fly ash (RCFA) and surface enhanced coal fly ash (SECFA), in removing CV dye from waste effluents. Various analytical techniques such as FTIR, XRD, SEM, TEM, BET, zeta sizer and zeta potential were employed for the characterization of the adsorbents and dye-loaded samples. BET revealed that RCFA possesses a surface area of 19.370 m2 g-1 and SECFA of 27.391 m2 g-1, exhibiting pore volumes of 0.1365 cm3 g-1 and 0.1919 cm3 g-1 respectively. Zeta-sizer and potential analysis showed the static charges of RCFA as -27.3 mV and SECFA as -28.2 mV, with average particle sizes of 346.6 and 315.3 nm, respectively. Langmuir and Freundlich adsorption isotherms were also employed for adsorption studies. Employing central composite design (CCD) of response surface methodology (RSM), the maximum CV removal was 81.52% for RCFA and 97.52% for SECFA, providing one minute contact time, 0.0125 g adsorbent dose and 10 ppm dye concentration. From the thermodynamic studies, all the negative values of ΔG° showed that all the adsorption processes of both adsorbents were spontaneous in nature.

Starch exploration in Nelumbo nucifera and Trapa natans: Understanding physicochemical and functional variations for future perspectives.

The current research emphasis on identifying unconventional starch sources with varied properties to broaden industrial applications. The focus of this research is on the search for alternative sources of starch with different properties in order to expand their potential use in the industrial sector. Starch was extracted from Trapa natans and Nelumbo nucifera and analyzed for their physicochemical and functional properties. They had similar protein (0.35 %) and ash contents, but the nitrogen-free extract was slightly higher in Nelumbo starch (87.58 %) than in Trapa starch (85.09 %). The amylose and amylopectin contents were 23.89 % and 76.11 % in Trapa starch and 15.70 % and 84.30 % in Nelumbo starch, respectively. Fourier-transform infrared spectroscopy identified both as polysaccharides. The characteristic absorption bands assigned to the stretching of OH groups (3324 cm-1; 3280 cm-1), the asymmetric and symmetric stretching of aliphatic chain groups (2925 cm-1; 2854 cm-1), the bending vibration of CHO groups (1149 cm-1; 1144 cm-1) were present in both the starch samples, with the exception of CH3 which could not be detected in Trapa natans starch. X-ray diffraction confirmed hexagonal and orthorhombic crystal structures in Nelumbo nucifera and Trapa natans starch. Scanning electron microscopy revealed a smooth oval and a rough cuboidal shape for lotus and chestnut starch, respectively. Rheological analysis showed that both starch solutions exhibited gel behavior, with Trapa showing stronger gel behavior after the crossover point. These results suggest potential applications in various industries, including the food industry and beyond.

Improved dehydrogenation performance of LiAlH4 doped with BaMnO3.

Due to its high gravimetric capacity of hydrogen (10.5 wt%), LiAlH4 has been regarded as a promising material for solid-state hydrogen storage material for onboard usage. However, high decomposition temperature, poor kinetics and irreversibility retard its application. To counter this problem, various weight percentages of BaMnO3 are introduced into the LiAlH4 system as an additive in this work. As a result, the starting hydrogen release of LiAlH4 was reduced to 109-115 °C and the second desorption temperature occurred at around 134-158 °C, much lower than pure LiAlH4. The isothermal desorption kinetics also proved that faster desorption kinetics can be observed at 90 °C for 80 min. About 2.00-2.60 wt% of H2 could be desorbed by the composite, whereas only <1.00 wt% of H2 was desorbed by undoped LiAlH4. Additionally, adding BaMnO3 reduced the activation energies by 30 kJ/mol for the first stages and 34 kJ/mol for the second stages. Based on the X-ray diffraction result, the active species formed of MnO2 and Ba or Ba-containing materials are believed to be responsible for the noticeable enhancement in the desorption properties of LiAlH4.

Advanced stability analysis of a fractional delay differential system with stochastic phenomena using spectral collocation method.

In recent years, there has been a growing interest in incorporating fractional calculus into stochastic delay systems due to its ability to model complex phenomena with uncertainties and memory effects. The fractional stochastic delay differential equations are conventional in modeling such complex dynamical systems around various applied fields. The present study addresses a novel spectral approach to demonstrate the stability behavior and numerical solution of the systems characterized by stochasticity along with fractional derivatives and time delay. By bridging the gap between fractional calculus, stochastic processes, and spectral analysis, this work contributes to the field of fractional dynamics and enriches the toolbox of analytical tools available for investigating the stability of systems with delays and uncertainties. To illustrate the practical implications and validate the theoretical findings of our approach, some numerical simulations are presented.

A novel approach towards web browser using the concept of a complex spherical fuzzy soft information.

The modern technology is the practical application of scientific knowledge, whether in industry or daily life, for goals or purposes. More quickly than any other technological advancement in human history, digital technologies have advanced. The technology sector is expanding and provides both new educational opportunities and innovative, exciting products. Right now, one of the most widely used and fascinating technologies is the web browser. This article introduced the novel concepts of complex spherical fuzzy soft relations (CSFSRs) by using the Cartesian Product (CP) of two complex spherical fuzzy soft sets (CSFSSs). Additionally, examples are used to clarify various types of relations. Because it discusses all levels of membership, abstinence, and non-membership with multidimensional variables, the CSFSRs have a detailed structure. The CSFSR-based modelling tools developed in this research, which primarily rely on the score function, can be used to choose the best Web browser. The transaction could be as easy as users sharing records via a functional web browser. Finally, the advantages of this suggested structure are illustrated by contrasting it with alternative structures.

Investigation of the accuracy of a portable109Cd XRF system for the measurement of iron in skin.

We have previously reported the design of a portable109Cd x-ray fluorescence (XRF) system to measure iron levels in the skin of patients with either iron overload disease, such as thalassemia, or iron deficiency disease, such as anemia. In phantom studies, the system was found to have a detection limit of 1.35µg Fe per g of tissue for a dose of 1.1 mSv. However, the system must provide accurate as well as precise measurements of iron levels in the skin in order to be suitable for human studies. The accuracy of the system has been explored using several methods. First, the iron concentrations of ten pigskin samples were assessed using both the portable XRF system and ICP-MS, and the results were compared. Overall, it was found that XRF and ICP-MS reported average values for iron in skin that were comparable to within uncertainties. The mean difference between the two methodologies was not significant, 2.5 ± 4.6µg Fe per g. On this basis, the system could be considered accurate. However, ICP-MS measurements reported a wider range of values than XRF, with two individual samples having ICP-MS results that were significantly elevated (p < 0.05) compared to XRF. SynchrotronµXRF maps of iron levels in pigskin were acquired on the BioXAS beam line of the Canadian Light Source. TheµXRF maps indicated two important features in the distribution of iron in pigskin. First, there were small areas of high iron concentration in the pigskin samples, that were predominantly located in the dermis and hypodermis at depths greater than 0.5 mm. Monte Carlo modelling using the EGS 5 code determined that if these iron 'hot spots' were located towards the back of the skin at depths greater than 0.5 mm, they would not be observed by XRF, but would be measured by ICP-MS. These results support a hypothesis that iron levels in the two samples that reported significantly elevated ICP-MS results compared to XRF may have had small blood vessels at the back of the skin. Second, the synchrotronµXRF maps also showed a narrow (approximately 100µm thick) layer of elevated iron at the surface of the skin. Monte Carlo models determined that, as expected, the XRF system was most sensitive to these skin layers. However, the simulations found that the XRF system, when calibrated against homogenous water-based phantoms, was found to accurately measure average iron levels in the skin of normal pigs despite the greater sensitivity to the surface layer. The Monte Carlo results further indicated that with highly elevated skin surface iron levels, the XRF system would not provide a good estimate of average skin iron levels. The XRF estimate could, with correction factors, provide a good estimate of the iron levels in the surface layers of skin. There is limited data on iron distribution in skin, especially under conditions of disease. If iron levels are elevated at the skin surface by diseases including thalassemia and hemochromatosis, this XRF device may prove to be an accurate clinical tool. However, further data are required on skin iron distributions in healthy and iron overload disease before this system can be verified to provide accurate measurements.

Functionalized Single Crystal Perovskite Materials for SERS and Their Potential Detection Applications.

Recent advances in detection and diagnostic tools have improved understanding and identification of plant physiological and biochemical processes. Effective and safe Surface Enhanced Raman Spectroscopy (SERS) can find objects quickly and accurately. Raman enhancement amplifies the signal by 1014-1015 to accurately quantify plant metabolites at the molecular level. This paper shows how to use functionalized perovskite substrates for SERS. These perovskite substrates have lots of surface area, intense Raman scattering, and high sensitivity and specificity. These properties eliminate sample matrix component interference. This study identified research gaps on perovskite substrates' effectiveness, precision, and efficiency in biological metabolite detection compared to conventional substrates. This article details the synthesis and use of functionalized perovskites for plant metabolites measurement. It analyzes their pros and cons in this context. The manuscript analyzes perovskite-based SERS substrates, including single-crystalline perovskites with enhanced optoelectronic properties. This manuscript aims to identify this study gap by comprehensively reviewing the literature and using it to investigate plant metabolite detection in future studies.

A novel simulation-based analysis of a stochastic HIV model with the time delay using high order spectral collocation technique.

The economic impact of Human Immunodeficiency Virus (HIV) goes beyond individual levels and it has a significant influence on communities and nations worldwide. Studying the transmission patterns in HIV dynamics is crucial for understanding the tracking behavior and informing policymakers about the possible control of this viral infection. Various approaches have been adopted to explore how the virus interacts with the immune system. Models involving differential equations with delays have become prevalent across various scientific and technical domains over the past few decades. In this study, we present a novel mathematical model comprising a system of delay differential equations to describe the dynamics of intramural HIV infection. The model characterizes three distinct cell sub-populations and the HIV virus. By incorporating time delay between the viral entry into target cells and the subsequent production of new virions, our model provides a comprehensive understanding of the infection process. Our study focuses on investigating the stability of two crucial equilibrium states the infection-free and endemic equilibriums. To analyze the infection-free equilibrium, we utilize the LaSalle invariance principle. Further, we prove that if reproduction is less than unity, the disease free equilibrium is locally and globally asymptotically stable. To ensure numerical accuracy and preservation of essential properties from the continuous mathematical model, we use a spectral scheme having a higher-order accuracy. This scheme effectively captures the underlying dynamics and enables efficient numerical simulations.

The effect of turmeric and black pepper powder incorporated in breakfast on postprandial glycemia, appetite, palatability, and gastrointestinal well-being in normal-weight adults.

Culinary herbs and spices are primarily known as flavor enhancers, research suggests that black pepper (Piper nigrum) and turmeric (Curcuma longa) have now been proven to prevent many non-communicable chronic diseases such as diabetes. Bioactive components of black pepper and turmeric ameliorate glucose metabolism and appetite regulation. The present research was designed to investigate the impact of turmeric and black pepper on blood glycemia, gastrointestinal well-being, appetite, and palatability. In a randomized crossover study, four iso-caloric experimental meals each having 50 g of available carbohydrates were subjected to healthy human participants (N = 20). Turmeric and black pepper were incorporated in the breakfast meal, 1 g black pepper (BP), 1 g turmeric (TR), and combination of the (BP + TR) was added in the breakfast. Standard questionnaires were used to evaluate palatability, subjective appetite, and gastrointestinal well-being. Blood glycemia, subjective gastrointestinal well-being, and appetite were measured at 0, 30, 60, 120, and 180 min. Experimental meals BP and BP + TR resulted in lower blood glycemia (p < .05) significantly compared to control meal. A decrease in perceived eating ability and hunger, and an increase in satiety after BP + TR and BP meal was observed. No significant changes were observed after consuming test meals on gastrointestinal well-being. Compared to control and BP + TR meals, BP and TR meals had considerably lower palatability. Results showed that compared to the control intake of starchy meals supplemented with black pepper and turmeric reduced postprandial glycemia, hunger, and perceived eating ability without affecting gastrointestinal well-being.

Numerical simulation of a fractional stochastic delay differential equations using spectral scheme: a comprehensive stability analysis.

The fractional stochastic delay differential equation (FSDDE) is a powerful mathematical tool for modeling complex systems that exhibit both fractional order dynamics and stochasticity with time delays. The purpose of this study is to explore the stability analysis of a system of FSDDEs. Our study emphasizes the interaction between fractional calculus, stochasticity, and time delays in understanding the stability of such systems. Analyzing the moments of the system's solutions, we investigate stochasticity's influence on FSDDS. The article provides practical insight into solving FSDDS efficiently using various numerical techniques. Additionally, this research focuses both on asymptotic as well as Lyapunov stability of FSDDS. The local stability conditions are clearly presented and also the effects of a fractional orders with delay on the stability properties are examine. Through a comprehensive test of a stability criteria, practical examples and numerical simulations we demonstrate the complexity and challenges concern with the analyzing FSDDEs.

A fuel gas waste heat recovery-based multigeneration plant integrated with a LNG cold energy process, a water desalination unit, and a CO2 separation process.

Development of the multigeneration plants based on the simultaneous production of water and energy can solve many of the current problems of these two major fields. In addition, the integration of fossil power plants with waste heat recovery processes in order to prevent the release of pollutants in the environment can simultaneously cover the environmental and thermodynamic improvements. Besides, the addition of a carbon dioxide (CO2) capturing cycles with such plants is a key issue towards a sustainable environment. Accordingly, a novel waste heat recovery-based multigeneration plant integrated with a carbon dioxide separation/liquefaction cycle is proposed and investigated under multi-variable assessments (energy/exergy, financial, and environmental). The offered multigeneration system is able to generate various beneficial outputs (electricity, liquefied CO2 (L-CO2), natural gas (NG), and freshwater). In the offered system, the liquified natural gas (LNG) cold energy is used to carry out condensation processes, which is a relatively new idea. Based on the results, the outputs rates of net power, NG, L-CO2, and water were determined to be approximately 42.72 MW and 18.01E+03, 612 and 3.56E+03 kmol/h, respectively. Moreover, the multigeneration plant was efficient about 32.08% and 87.72%, respectively, in terms of energy and exergy. Economic estimates indicated that the unit product costs of electricity and liquefied carbon dioxide production, respectively, were around 0.0466 USD per kWh and 0.0728 USD per kg-CO2. Finally, the total released CO2 was about 0.034 kg per kWh. According to a comprehensive comparison, the offered multigeneration plant can provide superior environmental, thermodynamic, and economic performances compared to similar plants. Moreover, there was no need to purchase electricity from the grid.

Advancing COVID-19 stochastic modeling: a comprehensive examination integrating vaccination classes through higher-order spectral scheme analysis.

This research article presents a comprehensive analysis aimed at enhancing the stochastic modeling of COVID-19 dynamics by incorporating vaccination classes through a higher-order spectral scheme. The ongoing COVID-19 pandemic has underscored the critical need for accurate and adaptable modeling techniques to inform public health interventions. In this study, we introduce a novel approach that integrates various vaccination classes into a stochastic model to provide a more nuanced understanding of disease transmission dynamics. We employ a higher-order spectral scheme to capture complex interactions between different population groups, vaccination statuses, and disease parameters. Our analysis not only enhances the predictive accuracy of COVID-19 modeling but also facilitates the exploration of various vaccination strategies and their impact on disease control. The findings of this study hold significant implications for optimizing vaccination campaigns and guiding policy decisions in the ongoing battle against the COVID-19 pandemic.

Activation of GPBAR1 attenuates vascular inflammation and atherosclerosis in a mouse model of NAFLD-related cardiovascular disease.

While patients with nonalcoholic fatty liver disease (NAFLD) are at increased risk to develop clinically meaningful cardiovascular diseases (CVD), there are no approved drug designed to target the liver and CVD component of NAFLD. GPBAR1, also known as TGR5, is a G protein coupled receptor for secondary bile acids. In this study we have investigated the effect of GPBAR1 activation by BAR501, a selective GPBAR1 agonist, in Apolipoprotein E deficient (ApoE-/-) mice fed a high fat diet and fructose (Western diet), a validated model of NAFLD-associated atherosclerosis. Using aortic samples from patients who underwent surgery for abdominal aneurism, and ex vivo experiments with endothelial cells and human macrophages, we were able to co-localize the expression of GPBAR1 in CD14+ and PECAM1+ cells. Similar findings were observed in the aortic plaques from ApoE-/- mice. Treating ApoE-/- mice with BAR501, 30 mg/kg for 14 weeks, attenuated the body weight gain while ameliorated the insulin sensitivity by increasing the plasma concentrations of GLP-1 and FGF15. Activation of GPBAR1 reduced the aorta thickness and severity of atherosclerotic lesions and decreased the amount of plaques macrophages. Treating ApoE-/- mice reshaped the aortic transcriptome promoting the expression of anti-inflammatory genes, including IL-10, as also confirmed by tSNE analysis of spleen-derived macrophages. Feeding ApoE-/- mice with BAR501 redirected the bile acid synthesis and the composition of the intestinal microbiota. In conclusion, GPBAR1 agonism attenuates systemic inflammation and improve metabolic profile in a genetic/dietetic model of atherosclerosis. BAR501 might be of utility in the treatment for NAFLD-related CVD.

From Pixels to Pathology: Employing Computer Vision to Decode Chest Diseases in Medical Images.

Radiology has been a pioneer in the healthcare industry's digital transformation, incorporating digital imaging systems like picture archiving and communication system (PACS) and teleradiology over the past thirty years. This shift has reshaped radiology services, positioning the field at a crucial junction for potential evolution into an integrated diagnostic service through artificial intelligence and machine learning. These technologies offer advanced tools for radiology's transformation. The radiology community has advanced computer-aided diagnosis (CAD) tools using machine learning techniques, notably deep learning convolutional neural networks (CNNs), for medical image pattern recognition. However, the integration of CAD tools into clinical practice has been hindered by challenges in workflow integration, unclear business models, and limited clinical benefits, despite development dating back to the 1990s. This comprehensive review focuses on detecting chest-related diseases through techniques like chest X-rays (CXRs), magnetic resonance imaging (MRI), nuclear medicine, and computed tomography (CT) scans. It examines the utilization of computer-aided programs by researchers for disease detection, addressing key areas: the role of computer-aided programs in disease detection advancement, recent developments in MRI, CXR, radioactive tracers, and CT scans for chest disease identification, research gaps for more effective development, and the incorporation of machine learning programs into diagnostic tools.

Nanotechnologies for environmental remediation and their ecotoxicological impacts.

Environmental nanoremediation is an emerging technology that aims to rapidly and efficiently remove contaminants from the polluted sites using engineered nanomaterials (ENMs). Inorganic nanoparticles which are generally metallic, silica-based, carbon-based, or polymeric in nature serve to remediate through chemical reactions, filtration, or adsorption. Their greater surface area per unit mass and high reactivity enable them to treat groundwater, wastewater, oilfields, and toxic industrial contaminants. Despite the growing interest in nanotechnological solutions for bioremediation, the environmental and human hazard associated with their use is raising concerns globally. Nanoremediation techniques when compared to conventional remediation solutions show increased effectivity in terms of cost and time; however, the main challenge is the ability of ENMs to remove contaminants from different environmental mediums by safeguarding the ecosystem. ENMs improving the accretion of the pollutant and increasing their bioavailability should be rectified along with the vigilant management of their transfer to the upper levels of the food chain which subsequently causes biomagnification. The ecosystem-centered approach will help monitor the ecotoxicological impacts of nanoremediation considering the safety, sustainability, and proper disposal of ENMs. The environment and human health risk assessment of each novel engineered nanomaterial along with the regulation of life cycle assessment (LCA) tools of ENMs for nanoremediation can help investigate the possible environmental hazard. This review focuses on the currently available nanotechnological methods used for environmental remediation and their potential toxicological impacts on the ecosystem.

Salmonella meningitis in a young child from Pakistan: a case report.

BACKGROUND: Salmonella meningitis is a rare but serious complication of Salmonella infection, primarily affecting infants, children, and immunocompromised individuals. CASE PRESENTATION: We present a case of a two-and-a-half-year-old Asian boy who developed Salmonella meningitis along with pneumonia and respiratory failure. Initially, he experienced symptoms of loose motions, fever, and irritability, which progressed to neck stiffness and brisk reflexes. Cerebrospinal fluid (CSF) analysis confirmed Salmonella typhi in the CSF. Due to the worsening condition, the patient was admitted to the intensive care unit, intubated, and switched to meropenem as the antibiotic of choice after an initial empiric therapy with ceftriaxone and vancomycin. With appropriate treatment, the patient showed significant improvement, including resolution of fever and respiratory symptoms. CONCLUSION: Management of Salmonella meningitis is often challenging primarily because of the fact that the empiric therapy for meningitis may not always provide coverage to the multi-drug resistant Salmonella species found in South Asia. Prompt administration of appropriate antibiotics based on sensitivity testing is crucial for successful management. This case emphasizes the importance of early recognition and effective management of this uncommon yet severe complication of Salmonella infection.

Spatial spillover impact of determinants on child mortality in Pakistan: evidence from Spatial Durbin Model.

BACKGROUND: Child mortality is a major challenge to public health in Pakistan and other developing countries. Reduction of the child mortality rate would improve public health and enhance human well-being and prosperity. This study recognizes the spatial clusters of child mortality across districts of Pakistan and identifies the direct and spatial spillover effects of determinants on the Child Mortality Rate (CMR). METHOD: Data of the multiple indicators cluster survey (MICS) conducted by the United Nations International Children's Emergency Fund (UNICEF) was used to study the CMR. We used spatial univariate autocorrelation to test the spatial dependence between contiguous districts concerning CMR. We also applied the Spatial Durbin Model (SDM) to measure the spatial spillover effects of factors on CMR. RESULTS: The study results showed 31% significant spatial association across the districts and identified a cluster of hot spots characterized by the high-high CMR in the districts of Punjab province. The empirical analysis of the SDM confirmed that the direct and spatial spillover effect of the poorest wealth quintile and MPI vulnerability on CMR is positive whereas access to postnatal care to the newly born child and improved drinking water has negatively (directly and indirectly) determined the CMR in Pakistan. CONCLUSION: The instant results concluded that spatial dependence and significant spatial spillover effects concerning CMR exist across districts. Prioritization of the hot spot districts characterized by higher CMR can significantly reduce the CMR with improvement in financial statuses of households from the poorest quintile and MPI vulnerability as well as improvement in accessibility to postnatal care services and safe drinking water.

Melatonin and strigolactone mitigate chromium toxicity through modulation of ascorbate-glutathione pathway and gene expression in tomato.

Chromium (Cr) is considered one of the most hazardous metal contaminant reducing crop production and putting human health at risk. Phytohormones are known to regulate chromium stress, however, the function of melatonin and strigolactones in Chromium stress tolerance in tomato is rarely investigated. Here we investigated the potential role of melatonin (ML) and strigolactone (SL) on mitigating Chromium toxicity in tomato. With exposure to 300 µM Cr stress a remarkable decline in growth (63.01%), biomass yield (50.25)%, Pigment content (24.32%), photosynthesis, gas exchange and Physico-biochemical attributes of tomato was observed. Cr treatment also resulted in oxidative stress closely associated with higher H2O2 generation (215.66%), Lipid peroxidation (50.29%), electrolyte leakage (440.01%) and accumulation of osmolytes like proline and glycine betine. Moreover, Cr toxicity up-regulated the transcriptional expression profiles of antioxidant, stress related and metal transporter genes and down-regulated the genes related to photosynthesis. The application of ML and SL alleviated the Cr induced phytotoxic effects on photosynthetic pigments, gas exchange parameters and restored growth of tomato plants. ML and SL supplementation induced plant defense system via enhanced regulation of antioxidant enzymes, ascorbate and glutathione pool and transcriptional regulation of several genes. The coordinated regulation of antioxidant and glyoxalase systems expressively suppressed the oxidative stress. Hence, ML and SL application might be considered as an effective approach for minimizing Cr uptake and its detrimental effects in tomato plants grown in contaminated soils. The study may also provide new insights into the role of transcriptional regulation in the protection against heavy metal toxicity.