AI inspired EEG-based spatial feature selection method using multivariate empirical mode decomposition for emotion classification.

Classification of human emotions based on electroencephalography (EEG) is a very popular topic nowadays in the provision of human health care and well-being. Fast and effective emotion recognition can play an important role in understanding a patient's emotions and in monitoring stress levels in real-time. Due to the noisy and non-linear nature of the EEG signal, it is still difficult to understand emotions and can generate large feature vectors. In this article, we have proposed an efficient spatial feature extraction and feature selection method with a short processing time. The raw EEG signal is first divided into a smaller set of eigenmode functions called (IMF) using the empirical model-based decomposition proposed in our work, known as intensive multivariate empirical mode decomposition (iMEMD). The Spatio-temporal analysis is performed with Complex Continuous Wavelet Transform (CCWT) to collect all the information in the time and frequency domains. The multiple model extraction method uses three deep neural networks (DNNs) to extract features and dissect them together to have a combined feature vector. To overcome the computational curse, we propose a method of differential entropy and mutual information, which further reduces feature size by selecting high-quality features and pooling the k-means results to produce less dimensional qualitative feature vectors. The system seems complex, but once the network is trained with this model, real-time application testing and validation with good classification performance is fast. The proposed method for selecting attributes for benchmarking is validated with two publicly available data sets, SEED, and DEAP. This method is less expensive to calculate than more modern sentiment recognition methods, provides real-time sentiment analysis, and offers good classification accuracy.

An Innovative Multi-Model Neural Network Approach for Feature Selection in Emotion Recognition Using Deep Feature Clustering.

Emotional awareness perception is a largely growing field that allows for more natural interactions between people and machines. Electroencephalography (EEG) has emerged as a convenient way to measure and track a user's emotional state. The non-linear characteristic of the EEG signal produces a high-dimensional feature vector resulting in high computational cost. In this paper, characteristics of multiple neural networks are combined using Deep Feature Clustering (DFC) to select high-quality attributes as opposed to traditional feature selection methods. The DFC method shortens the training time on the network by omitting unusable attributes. First, Empirical Mode Decomposition (EMD) is applied as a series of frequencies to decompose the raw EEG signal. The spatiotemporal component of the decomposed EEG signal is expressed as a two-dimensional spectrogram before the feature extraction process using Analytic Wavelet Transform (AWT). Four pre-trained Deep Neural Networks (DNN) are used to extract deep features. Dimensional reduction and feature selection are achieved utilising the differential entropy-based EEG channel selection and the DFC technique, which calculates a range of vocabularies using k-means clustering. The histogram characteristic is then determined from a series of visual vocabulary items. The classification performance of the SEED, DEAP and MAHNOB datasets combined with the capabilities of DFC show that the proposed method improves the performance of emotion recognition in short processing time and is more competitive than the latest emotion recognition methods.

Bisphenol A analogues bisphenol B, bisphenol F, and bisphenol S induce oxidative stress, disrupt daily sperm production, and damage DNA in rat spermatozoa: a comparative in vitro and in vivo study.

Bisphenol A (BPA) is a well-known endocrine-disrupting chemical with estrogenic activity. The widespread exposure of individuals to BPA is suspected to affect a variety of physiological functions, including reproduction, development, and metabolism. Here we report the mechanisms by which BPA and three of its analogues bisphenol B (BPB), bisphenol F (BPF), and bisphenol S (BPS) cause generation of reactive oxygen species (ROS), sperm DNA damage, and oxidative stress in both in vivo and in vitro rat models. Sperm were incubated with different concentrations (1, 10, and 100 µg/L) of BPA and its analogues BPB, BPF, and BPS for 2 h. BPA and its analogues were observed to increase DNA fragmentation, formation of ROS, and affected levels of superoxide dismutase at higher concentration groups. In an in vivo experiment, rats were exposed to different concentrations (5, 25, and 50 mg/kg/day) of BPA, BPB, BPF, and BPS for 28 days. In the higher dose (50 mg/kg/day) treated groups of BPA and its analogues BPB, BPF, and BPS, DNA damage was observed while the motility of sperm was not affected.

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach.

Much attention has been paid to the recognition of human emotions with the help of electroencephalogram (EEG) signals based on machine learning technology. Recognizing emotions is a challenging task due to the non-linear property of the EEG signal. This paper presents an advanced signal processing method using the deep neural network (DNN) for emotion recognition based on EEG signals. The spectral and temporal components of the raw EEG signal are first retained in the 2D Spectrogram before the extraction of features. The pre-trained AlexNet model is used to extract the raw features from the 2D Spectrogram for each channel. To reduce the feature dimensionality, spatial, and temporal based, bag of deep features (BoDF) model is proposed. A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. Lastly, the emotion of each subject is represented using the histogram of the vocabulary set collected from the raw-feature of a single channel. Features extracted from the proposed BoDF model have considerably smaller dimensions. The proposed model achieves better classification accuracy compared to the recently reported work when validated on SJTU SEED and DEAP data sets. For optimal classification performance, we use a support vector machine (SVM) and k-nearest neighbor (k-NN) to classify the extracted features for the different emotional states of the two data sets. The BoDF model achieves 93.8% accuracy in the SEED data set and 77.4% accuracy in the DEAP data set, which is more accurate compared to other state-of-the-art methods of human emotion recognition.

Mechanisms of Cr(VI) resistance by endophytic Sphingomonas sp. LK11 and its Cr(VI) phytotoxic mitigating effects in soybean (Glycine max L.).

Chromium Cr(VI) is highly toxic and leads to impaired phenotypic plasticity of economically important crops. The current study assessed an endophytic-bacteria assisted metal bio-remediation strategy to understand stress-alleviating mechanisms in Glycine max L (soybean) plants inoculated with Sphingomonas sp. LK11 under severe Cr(VI) toxicity. The screening analysis showed that high Cr concentrations (5.0 mM) slightly suppressed LK11 growth and metal uptake by LK11 cells, while significantly enhancing indole-3-acetic acid (IAA) production. Endophytic LK11 significantly upregulated its antioxidant system compared to control by enhancing reduced glutathione (GSH), catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) activities to counteract Cr-induced oxidative stress. Cr toxicity induced cell morphological alteration, as shown by SEM-EDX analysis and triggered significant lipid peroxidation. The interaction between LK11 and soybean in Cr-contaminated soil significantly increased plant growth attributes and down-regulated the synthesis of endogenous defense-related phytohormones, salicylic acid and abscisic acid, by 20% and 37%, respectively, and reduced Cr translocation to the roots, shoot, and leaves. Additionally, Cr-induced oxidative stress was significantly reduced in LK11-inoculated soybean, regulating metal responsive reduced GSH and enzymatic antioxidant CAT. Current findings indicate that LK11 may be a suitable candidate for the bioremediation of Cr-contaminated soil and stimulation of host physiological homeostasis.

The Potential Use of Vetiveria zizanioides for the Phytoremediation of Antimony, Arsenic and Their Co-Contamination.

Antimony (Sb) and arsenic (As) contaminations are the well reported and alarming issues of various contaminated smelting and mining sites all over the world, especially in China. The present hydroponic study was to assess the capacity of Vetiveria zizanioides for Sb, As and their interactive accumulations. The novelty of the present research is this that the potential of V. zizanioides for Sb and As alone and their interactive accumulation are unaddressed. This is the first report about the interactive co-accumulation of Sb and As in V. zizanioides. Highest applied Sb and As contaminations significantly inhibited the plant growth. Applied Sb and As alone significantly increased their concentrations in the roots/shoot of V. zizanioides. While co-contamination of Sb and As steadily increased their concentrations, in the plant. The co-contamination of Sb and As revealed a positive correlation between the two, as they supplemented the uptake and accumulation of each other. The overall translocation (TF) and bioaccumulation factors (BF) of Sb in V. zizanioides, were 0.75 and 4. While the TF and BF of As in V. zizanioides, were 0.86 and 10. V. zizanioides proved as an effective choice for the phytoremediation and ecosystem restoration of Sb and As contaminated areas.

Multiple-Drug Resistant Shiga Toxin-Producing E. coli in Raw Milk of Dairy Bovine.

INTRODUCTION: Raw milk may contain pathogenic microorganisms harmful to humans, e.g., multidrug-resistant Escherichia coli non-O157:H7, which can cause severe colitis, hemolytic uremia, and meningitis in children. No studies are available on the prevalence of Shiga toxin-producing E. coli (STEC O157:H7) in sick or healthy dairy animals in the Khyber Pakhtunkhwa Province of Pakistan. AIM: This study aimed to isolate, characterize, and detect antibiotic resistance in STEC non-O157:H7 from unpasteurized milk of dairy bovines in this province. MATERIALS AND METHODS: We collected raw milk samples (n = 800) from dairy farms, street vendors, and milk shops from different parts of the Khyber Pakhtunkhwa Province. E. coli was isolated from these samples followed by latex agglutination tests for serotyping. The detection of STEC was conducted phenotypically and confirmed by the detection of virulence genes genotypically. An antibiogram of STEC isolates was performed against 12 antibiotics using the disc diffusion method. RESULTS: A total of 321 (40.12%) samples were found to be positive for E. coli in this study. These samples were processed for the presence of four virulence genes (Stx1, Stx2, ehxA, eae). Forty samples (5.0%) were STEC-positive. Of these, 38%, 25%, 19%, and 18% were positive for Stx1, Stx2, ehxA, and eae, respectively. Genotypically, we found that 1.37% of STEC isolates produced extended-spectrum beta-lactamase (ESBL) and contained the blaCTX M gene. Resistance to various antibiotics ranged from 18% to 77%. CONCLUSION: This study highlights the risk of virulent and multidrug-resistant STEC non-O157:H7 in raw milk and the need for proper quality surveillance and assurance plans to mitigate the potential public health threat.

Biological Control of Hyalomma Ticks in Cattle by Fungal Isolates.

Ticks pose a major threat to cattle health and production in Pakistan because they transmit pathogens of diseases like Babesiosis and Theileriosis. Hyalomma spp., found across Africa, Asia, and Europe, are especially problematic. This study explored biocontrol of Hyalomma spp. using spore-free fungal culture filtrates collected from dairy farm soil in Kohat, Pakistan. Three fungal species of the genera Alternaria, Aspergillus, and Penicillium were isolated, and their filtrates were tested against tick adults and larvae. Filtrate concentrations were prepared at different strengths. Data were taken after the exposure of adults and larvae ticks to various concentrations of the fungal filtrates. Results indicated that at 100% concentration, all fungal filtrates induced 100% mortality in adults and larvae. Decreasing filtrate concentration lowered tick mortality. The lowest concentration caused the least mortality. The effect was time- and dose-dependent. In conclusion, spore-free fungal culture filtrates can provide biocontrol of Hyalomma spp. in a time- and concentration-dependent manner. Further research should explore the active compounds causing mortality and optimal application methods. The process outlined here provides a natural biocontrol alternative to chemical pesticides to reduce tick infestations and associated cattle diseases in Pakistan.

Formulation of Polymers-Based Methotrexate Patches and Investigation of the Effect of Various Penetration Enhancers: In Vitro, Ex Vivo and In Vivo Characterization.

The present study aimed to prepare methotrexate-loaded transdermal patches with different blends of hydrophobic and hydrophilic polymers (Eudragit S-100 and hydroxypropyl methylcellulose) at different concentrations. The polymers employed in transdermal patches formulations served as controlled agent. Transdermal patches were prepared using the solvent casting technique. The suitable physicochemical properties were obtained from the formulation F5 (HPMC and Eudragit S-100 (5:1). Various penetration enhancers were employed in different concentrations to investigate their potential for enhancing the drug permeation profile from optimized formulations. A preformulation study was conducted to investigate drug-excipient compatibilities (ATR-FTIR) and the study showed greater compatibility between drug, polymers and excipients. The prepared patches containing different penetration enhancers at different concentrations were subjected for evaluating different physicochemical parameters and in vitro drug release studies. The obtained data were added to various kinetic models, then formulated patch formulations were investigated for ex vivo permeation studies, in vivo studies and skin drug retention studies. The prepared patches showed elastic, smooth and clear nature with good thickness, drug content, % moisture uptake and weight uniformity. The prepared transdermal patches showed % drug content ranging from 91.43 ± 2.90 to 98.37 ± 0.56, % swelling index from 36.98 ± 0.19 to 75.32 ± 1.21, folding endurance from 61 ± 3.14 to 78 ± 1.54 and tensile strength from 8.54 ± 0.18 to 12.87 ± 0.50. The formulation F5, containing a greater amount of hydrophilic polymers (HPMC), showed increased drug release and permeation and drug retention when compared to other formulated transdermal patch formulations (F1-F9). No significant change was observed during a stability study for a period of 60 days. The rabbit skin samples were subjected to ATR-FTIR studies, which revealed that polymers and penetration enhancers have affected skin proteins (ceramides and keratins). The pharmacokinetic profiling of optimized formulation (F5) as well as formulations with optimized concentrations of penetration enhancers revealed Cmax ranged 167.80 ng/mL to 178.07 ± 2.75 ng/mL, Tmax was 8 h to 10 h, and t1/2 was 15.9 ± 2.11 to 21.49 ± 1.16. From the in vivo studies, it was revealed that the formulation F5-OA-10% exhibited greater skin drug retention as compared to other formulations. These results depicted that prepared methotrexate transdermal patches containing different blends of hydrophobic and hydrophilic polymers along with different penetration enhancers could be safely used for the management of psoriasis. The formulated transdermal patches exhibited sustained release of drug with good permeations and retention profile. Hence, these formulated transdermal patches can effectively be used for the management of psoriasis.

Screening of various Brassica species for phytoremediation of heavy metals-contaminated soil of Lakki Marwat, Pakistan.

Natural resources, especially agrarian soils, have been much contaminated with various pollutants including heavy metals since industrial revolution, so it is pertinent to utilize green technology, the so-called phytoremediation technology for reclamation of heavy metal-contaminated soils. A pot experiment was conducted to screen four different species (Brassica juncea, Brassica napus, Brassica rapa, Brassica campestris) of Brassicaceae family for the remediation of HMs contaminated soil of Lakki Marwat city, Pakistan, irrigated with municipal wastewater. Plants were analyzed for various morpho-physiological, biochemical, and phytoextraction factors like bioaccumulation (BAF) and translocation factor (TF). Results showed maximum morpho-physiological responses including seed germination, chlorophyll content, root fresh and dry weights, and shoot fresh and dry weights in B. juncea followed by B. napus, B. campestris, and B. rapa. Plant biochemical analyses of antioxidant enzymes including superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) also exhibited maximum activity in B. juncea followed by B. napus, B. campestris, and B. rapa, respectively, in both control and contaminated soils. Conversely, plant oxidative stress markers including malondialdehyde (MDA) and hydrogen peroxide (H2O2) showed maximum contents in B. rapa followed by B. campestris, B. napus, and B. juncea in both soils. Plant bioconcentration factors i.e. BAF and TF measured for all species in both soils confirmed that B. juncea accumulated maximum heavy metals. Similarly, enhanced phytoextraction capacity was noticed for all Brassica species in decreasing order i.e. B. napus > B. campestris > B. rapa. Hence, all the results confirmed that B. juncea excelled and can be recommended for phytoremediation purpose in soils of study area.

Assessment of Geographical Distribution of Emerging Zoonotic Toxoplasma gondii Infection in Women Patients Using Geographical Information System (GIS) in Various Regions of Khyber Pakhtunkhwa (KP) Province, Pakistan.

Toxoplasmosis is a zoonotic parasitic disease caused by T. gondii, an obligate intracellular apcomplexan zoonotic parasite that is geographically worldwide in distribution. The parasite infects humans and all warm-blooded animals and is highly prevalent in various geographical regions of the world, including Pakistan. The current study addressee prevalence of Toxoplasma infection in women in various geographical regions, mapping of endemic division and t district of Khyber Pakhtunkhwa province through geographical information system (GIS) in order to locate endemic regions, monitor seasonal and annual increase in prevalence of infection in women patients. Setting: Tertiary hospitals and basic health care centers located in 7 divisions and 24 districts of Khyber Pakhtunkhwa (KP) province of Pakistan. During the current study, 3586 women patients from 7 divisions and 24 districts were clinically examined and screened for prevalence of T. gondii infection. Participants were screened for Toxoplasma infection using ICT and latex agglutination test (LAT) as initial screening assay, while iELISA (IgM, IgG) was used as confirmatory assay. Mapping of the studied region was developed by using ArcGIS 10.5. Spatial analyst tools were applied by using Kriging/Co-kriging techniques, followed by IDW (Inverse Distance Weight) techniques. Overall prevalence of T. gondii infection was found in 881 (24.56%) patients. A significant (<0.05) variation was found in prevalence of infection in different divisions and districts of the province. Prevalence of infection was significantly (<0.05) high 129 (30.07%) in Kohat Division, followed by 177 (29.06%), 80 (27.87%), 287 (26.72%), 81 (21.21%), 47 (21.07%), and 80 (13.71%) cases in Hazara Division, D.I Khan Division, Malakand Division, Mardan Division, Bannu Division, and Peshawar Division. Among various districts, a significant variation (<0.05) was found in prevalence of infection. Prevalence of infection was significantly (<0.05) high 49 (44.95%) in district Karak, while low (16 (10.81%) in district Nowshera. No significant (>0.05) seasonal and annual variation was found in prevalence of Toxoplasma infection. LAT, ICT and ELISA assays were evaluated for prevalence of infection, which significantly (<0.05) detected T. gondii antibodies. LAT, ICT and ELISA assays significantly (<0.05) detected infection, while no significant (>0.05) difference was found between positivity of LAT and ICT assays. A significant difference (<0.05) was found in positivity of Toxoplasma-specific (IgM), (IgG) and (IgM, IgG) immunoglobulin by ICT and ELISA assay. The current study provides comprehensive information about geographical distribution, seasonal and annual variation of Toxoplasmosis infection in various regions of Khyber Pakhtunkhwa province of Pakistan. Infection of T. gondii in women shows an alarming situation of disease transmission from infected animals in the studied region, which is not only a serious and potential threat for adverse pregnancy outcomes, but also cause socioeconomic burden and challenges for various public and animal health organizations in Pakistan and across the country.

Seroprevalence of COVID-19 IgG antibodies among healthcare workers of Pakistan: a cross-sectional study assessing exposure to COVID-19 and identification of high-risk subgroups.

OBJECTIVE: In this study, we aimed to find the seroprevalence of healthcare workers (HCWs) of Pakistan involved in the treatment and care of patients with COVID-19. SETTING: This was a cross-sectional study and total of 15 000 HCWs involved in providing services and care to the patients with COVID-19 were randomly selected from all over Pakistan. PARTICIPANTS: Informed consent was taken from all participants and were included according to inclusion and exclusion criteria. All testing was done on serum samples for the qualitative detection of SARS-CoV-2 IgG antibodies using Abbott Chemiluminescent microparticle immunoassay. An index of 1.4 was used as a cut-off to mark reactive and non-reactive cases. SPSS V.23.0 was used for data analysis. OUTCOME: Immune status of the study population depicting seroprevalence among HCWs. RESULTS: Out of all the candidates, majority of the HCWs were men (61.9%) and were doctors (62.4%). The mean age of participants was 32.8 years (SD 8.7) and majority were asymptomatic (51.8%). In this study, 33% of the HCWs were reactive for SARS-CoV-2 IgG antibody. Around 44% of the reactive cases were asymptomatic. The symptoms more significantly associated with seropositivity were: fever (OR 1.31; 95% CI 1.16 to 1.48), headache (OR 2.43; 95% CI 2.16 to 2.73), cough and shortness of breath (OR 2.10; 95% CI 1.91 to 2.31), loss of sense of smell or taste (OR 3.70; 95% CI 3.29 to 4.17) (p<0.001). Factors which showed significant association with the presence of antibodies were professional category (absolute risk (AR) 0.09; OR 1.46; 95% CI 1.36 to 1.56), availability of protective masks (AR 0.02; OR 0.90; 95% CI 0.84 to 0.96), safety goggles (AR 0.02; OR 0.90; 95% CI 0.84 to 0.97) and living arrangements (AR 0.03; OR 1.12; 95% CI 1.04 to 1.20) (p<0.05). CONCLUSION: Our study showed a high seropositivity of HCWs dealing with patients with COVID-19 in Pakistan revealing significant association with professional category, nature of work place and precautions taken while performing duties.

Compost mixed fruits and vegetable waste biochar with ACC deaminase rhizobacteria can minimize lead stress in mint plants.

High lead (Pb) concentration in soils is becoming a severe threat to human health. It also deteriorates plants, growth, yield and quality of food. Although the use of plant growth-promoting rhizobacteria (PGPR), biochar and compost can be effective environment-friendly amendments for decreasing Pb stress in crop plants, the impacts of their simultaneous co-application has not been well documented. Thus current study was carried, was conducted to investigate the role of rhizobacteria and compost mixed biochar (CB) under Pb stress on selected soil properties and agronomic parameters in mint (Mentha piperita L.) plants. To this end, six treatments were studied: Alcaligenes faecalis, Bacillus amyloliquefaciens, CB, PGPR1 + CB, PGPR2 + CB and control. Results showed that the application A. faecalis + CB significantly decreased soil pH and EC over control. However, OM, nitrogen, phosphorus and potassium concentration were significantly improved in the soil where A. faecalis + CB was applied over control. The A. faecalis + CB treatment significantly improved mint plant root dry weight (58%), leaves dry weight (32%), chlorophyll (37%), and N (46%), P (39%) and K (63%) leave concentration, while also decreasing the leaves Pb uptake by 13.5% when compared to the unamended control. In conclusion, A. faecalis + CB has a greater potential to improve overall soil quality, fertility and mint plant productivity under high Pb soil concentration compared to the sole application of CB and A. faecalis.

Effect of Cadmium-Tolerant Rhizobacteria on Growth Attributes and Chlorophyll Contents of Bitter Gourd under Cadmium Toxicity.

Cadmium (Cd) is one of the heavy metals that negatively affects the growth of plants. High solubilization in water leads Cd to enter into plants quite easily, thus decreasing seed germination, photosynthesis, and transpiration. It also shows an antagonistic effect with many of the plants' nutrients like Mn, Ca, K, Mg and Fe. Nowadays, inoculation of plants with ACC deaminase (ACCD) rhizobacteria to mitigate Cd's adverse effects has drawn the attention of environmental microbiologists. The rhizobacteria secrete organic compounds that can immobilize Cd in soil. Therefore, this study was accomplished to investigate the effect of ACCD plant growth promoting rhizobacteria (PGPR) on the bitter gourd under Cd stress. There were six treatments consisting of two ACCD PGPR (Stenotrophomonas maltophilia and Agrobacterium fabrum) strains and inorganic fertilizers at two levels of Cd, i.e., 2 (Cd2) and 5 mg kg-1 soil (Cd5). The results showed A. fabrum with the recommended NPK fertilizer (RNPKF) significantly increased the vine length (48 and 55%), fresh weight (24 and 22%), and contents of chlorophyll a (79 and 50%), chlorophyll b (30 and 33%) and total chlorophyll (61 and 36%), over control at the two Cd levels i.e., Cd2 and Cd5, respectively. In conclusion, the recommended NPK fertilizer + A. fabrum combination is a very effective treatment with which to immobilize Cd in soil for the improvement of bitter gourd growth.

Alleviation of lead-induced physiological, metabolic, and ultramorphological changes in leaves of upland cotton through glutathione.

Plants face changes in leaves under lead (Pb) toxicity. Reduced glutathione (GSH) has several functions in plant metabolism, but its role in alleviating Pb toxicity in cotton leaves is still unknown. In the present study, cotton seedlings (28 days old) were exposed to 500 µM Pb and 50 µM GSH, both alone and in combination, for a period of 10 days, in the Hoagland solution under controlled growth conditions. Results revealed Pb-induced changes in cotton's leaf morphology, photosynthesis, and oxidative metabolism. However, exogenous application of GSH restored leaf growth. GSH triggered build up of chlorophyll a, chlorophyll b, and carotenoid contents and boosted fluorescence ratios (F v/F m and F v/F 0). Moreover, GSH reduced the malondialdehyde (MDA), hydrogen peroxide (H2O2), and Pb contents in cotton leaves. Results further revealed that total soluble protein contents were decreased under Pb toxicity; however, exogenously applied GSH improved these contents in cotton leaves. Activities of antioxidant enzymes (catalase (CAT), superoxide dismutase (SOD), peroxidase (POD), glutathione reductase (GR), and ascorbate peroxidase (APX)) were also increased by GSH application under Pb toxicity. Microscopic analysis showed that excess Pb shattered thylakoid membranes in chloroplasts. However, GSH stabilized ultrastructure of Pb-stressed cotton leaves. These findings suggested that exogenously applied GSH lessened the adverse effects of Pb and improved cotton's tolerance to oxidative stress.