Cadmium phytotoxicity: issues, progress, environmental concerns and future perspectives

Cadmium, a high toxicity element, is a potential threat to plant and human health, and a dangerous pollutant in the environment. Uptake and accumulation by crops represent the main entry pathway for potentially health-threatening toxic metals into human and animal food. Crops and other plants take up Cd from the soil or water and may distribute it in their roots and shoots. Soil and/or water are usually contaminated with Cd through natural sources, industrial effluent, and anthropogenic activities. In this review, the sources of Cd contamination, evaluation of the phytotoxic effects on plants, and mode of action of Cd toxicity, were summarized. Plant defensive strategies upon excess Cd are also considered in this review. Cd-induced effects include oxidative stress, disintegration of the photosynthetic apparatus, reduction in gas exchange parameters, nutrient imbalance, and subcellular organelle degradation. In addition, Cd severely impairs biomolecules such as DNA, protein, and lipids. Although plants are sessile in nature, they are equipped with certain mechanisms to cope with unfavorable conditions. These mechanisms include synthesis of metal-helating proteins, expression of enzymatic and non-enzymatic antioxidants, organic acids, and plant root–mycorrhiza association. The built-in system of plant tolerance to Cd can be further enhanced by the application of exogenous organic and inorganic metal sources. This review will broaden the knowledge about the Cd accumulation in plants and the responses to metal exposure, as well as our understanding of metal tolerance and overcoming this serious issue for sustainable agriculture and human health worldwide. Highlights Cd accumulation has harmful effects in an organism. Cd has been listed 7th out of 275 compounds in the priority list of hazardous materials. Cd remains in the soil for 15–1100 years. Plants usually imply certain strategies to overcome Cd toxicity. Plants built-in systems can be enhanced to overwhelmed this problem.Cadmium, a high toxicity element, is a potential threat to plant and human health, and a dangerous pollutant in the environment. Uptake and accumulation by crops represent the main entry pathway for potentially health-threatening toxic metals into human and animal food. Crops and other plants take up Cd from the soil or water and may distribute it in their roots and shoots. Soil and/or water are usually contaminated with Cd through natural sources, industrial effluent, and anthropogenic activities. In this review, the sources of Cd contamination, evaluation of the phytotoxic effects on plants, and mode of action of Cd toxicity, were summarized. Plant defensive strategies upon excess Cd are also considered in this review. Cd-induced effects include oxidative stress, disintegration of the photosynthetic apparatus, reduction in gas exchange parameters, nutrient imbalance, and subcellular organelle degradation. In addition, Cd severely impairs biomolecules such as DNA, protein, and lipids. Although plants are sessile in nature, they are equipped with certain mechanisms to cope with unfavorable conditions. These mechanisms include synthesis of metal-helating proteins, expression of enzymatic and non-enzymatic antioxidants, organic acids, and plant root–mycorrhiza association. The built-in system of plant tolerance to Cd can be further enhanced by the application of exogenous organic and inorganic metal sources. This review will broaden the knowledge about the Cd accumulation in plants and the responses to metal exposure, as well as our understanding of metal tolerance and overcoming this serious issue for sustainable agriculture and human health worldwide. Highlights Cd accumulation has harmful effects in an organism. Cd has been listed 7th out of 275 compounds in the priority list of hazardous materials. Cd remains in the soil for 15–1100 years. Plants usually imply certain strategies to overcome Cd toxicity. Plants built-in systems can be enhanced to overwhelmed this problem

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB

Prediction of gestational age using urinary metabolites in term and preterm pregnancies.

Assessment of gestational age (GA) is key to provide optimal care during pregnancy. However, its accurate determination remains challenging in low- and middle-income countries, where access to obstetric ultrasound is limited. Hence, there is an urgent need to develop clinical approaches that allow accurate and inexpensive estimations of GA. We investigated the ability of urinary metabolites to predict GA at time of collection in a diverse multi-site cohort of healthy and pathological pregnancies (n = 99) using a broad-spectrum liquid chromatography coupled with mass spectrometry (LC-MS) platform. Our approach detected a myriad of steroid hormones and their derivatives including estrogens, progesterones, corticosteroids, and androgens which were associated with pregnancy progression. We developed a restricted model that predicted GA with high accuracy using three metabolites (rho = 0.87, RMSE = 1.58 weeks) that was validated in an independent cohort (n = 20). The predictions were more robust in pregnancies that went to term in comparison to pregnancies that ended prematurely. Overall, we demonstrated the feasibility of implementing urine metabolomics analysis in large-scale multi-site studies and report a predictive model of GA with a potential clinical value

Association of maternal prenatal copper concentration with gestational duration and preterm birth : a multicountry meta-analysis

BACKGROUND: Copper (Cu), an essential trace mineral regulating multiple actions of inflammation and oxidative stress, has been implicated in risk for preterm birth (PTB). OBJECTIVES: This study aimed to determine the association of maternal Cu concentration during pregnancy with PTB risk and gestational duration in a large multicohort study including diverse populations. METHODS: Maternal plasma or serum samples of 10,449 singleton live births were obtained from 18 geographically diverse study cohorts. Maternal Cu concentrations were determined using inductively coupled plasma mass spectrometry. The associations of maternal Cu with PTB and gestational duration were analyzed using logistic and linear regressions for each cohort. The estimates were then combined using meta-analysis. Associations between maternal Cu and acute-phase reactants (APRs) and infection status were analyzed in 1239 samples from the Malawi cohort. RESULTS: The maternal prenatal Cu concentration in our study samples followed normal distribution with mean of 1.92 μg/mL and standard deviation of 0.43 μg/mL, and Cu concentrations increased with gestational age up to 20 wk. The random-effect meta-analysis across 18 cohorts revealed that 1 μg/mL increase in maternal Cu concentration was associated with higher risk of PTB with odds ratio of 1.30 (95% confidence interval [CI]: 1.08, 1.57) and shorter gestational duration of 1.64 d (95% CI: 0.56, 2.73). In the Malawi cohort, higher maternal Cu concentration, concentrations of multiple APRs, and infections (malaria and HIV) were correlated and associated with greater risk of PTB and shorter gestational duration. CONCLUSIONS: Our study supports robust negative association between maternal Cu and gestational duration and positive association with risk for PTB. Cu concentration was strongly correlated with APRs and infection status suggesting its potential role in inflammation, a pathway implicated in the mechanisms of PTB. Therefore, maternal Cu could be used as potential marker of integrated inflammatory pathways during pregnancy and risk for PTB.Peer reviewe

Association of maternal prenatal copper concentration with gestational duration and preterm birth: a multicountry meta-analysis

Background Copper (Cu), an essential trace mineral regulating multiple actions of inflammation and oxidative stress, has been implicated in risk for preterm birth (PTB). Objectives This study aimed to determine the association of maternal Cu concentration during pregnancy with PTB risk and gestational duration in a large multicohort study including diverse populations. Methods Maternal plasma or serum samples of 10,449 singleton live births were obtained from 18 geographically diverse study cohorts. Maternal Cu concentrations were determined using inductively coupled plasma mass spectrometry. The associations of maternal Cu with PTB and gestational duration were analyzed using logistic and linear regressions for each cohort. The estimates were then combined using meta-analysis. Associations between maternal Cu and acute-phase reactants (APRs) and infection status were analyzed in 1239 samples from the Malawi cohort. Results The maternal prenatal Cu concentration in our study samples followed normal distribution with mean of 1.92 μg/mL and standard deviation of 0.43 μg/mL, and Cu concentrations increased with gestational age up to 20 wk. The random-effect meta-analysis across 18 cohorts revealed that 1 μg/mL increase in maternal Cu concentration was associated with higher risk of PTB with odds ratio of 1.30 (95% confidence interval [CI]: 1.08, 1.57) and shorter gestational duration of 1.64 d (95% CI: 0.56, 2.73). In the Malawi cohort, higher maternal Cu concentration, concentrations of multiple APRs, and infections (malaria and HIV) were correlated and associated with greater risk of PTB and shorter gestational duration. Conclusions Our study supports robust negative association between maternal Cu and gestational duration and positive association with risk for PTB. Cu concentration was strongly correlated with APRs and infection status suggesting its potential role in inflammation, a pathway implicated in the mechanisms of PTB. Therefore, maternal Cu could be used as potential marker of integrated inflammatory pathways during pregnancy and risk for PTB

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Profitability Analysis of Selected Farms in the Batinah Region of Oman

The agricultural sector of Oman represents less than 2% of the total GDP and uses 88% of the fresh water. Several decision makers are questioning whether the agricultural activity in the Sultanate of Oman can be sustained and if so what type of crops should be encouraged. More than 53% of the agricultural cropped area is situated in the Batinah coastal area where farming is exclusively based on groundwater pumping. A sample of 49 market-oriented farms from the Batinah region was surveyed during 2006. Four types of farms were considered. Results showed that the most profitable farms are mixing fodder crops and vegetables with a net margin of 1,412 RO/ha/year. The less profitable farms are based on tree crops and vegetables with a net margin of 847 RO/ha/year. For vegetables the most profitable crop is tomato with an average net margin of 2,580 RO/ha/year with a standard deviation of 2,043 RO/ha/year and the least profitable crop is cabbage with 113 RO/ha/ year with a standard deviation of 182 RO/ha/year. The net margin of crops grown under drip irrigation is higher than that for crops under furrow irrigation, with a difference of 548 RO/ha/year. Farms equipped with such modern irrigation systems tend to irrigate almost the same area in winter as in summer, while farms under furrow irrigation crop less than one percent of their cropped area during summer compared to winter. Consequently and contrary to expectations, modern irrigation systems tend to increase, rather than reduce, groundwater pumping given the financial incentives for farmers to grow summer vegetables instead of only winter vegetables. Even so, the net water use efficiency is greater for vegetable production under drip irrigation than it is for fodder production. The figures show that, on average, farming in the Batinah is financially profitable for the types of farm considered in this study. However, profitability varies widely between different farms and crops. The reasons for these differences are technical, as observed in the big differences in yield among crops, and economic because the prices received by farmers differ significantly

Automatic Vehicle Number Plate Recognition Approach Using Color Detection Technique

An Automatic Vehicle Number Plate Recognition System (AVNPR) is a key research area in image processing. Various techniques are developed and tested by researchers to improve the detection and recognition rate of AVNPR system but faced problems due to issues such as variation in format, lighting conditions, scales, and colors of number plates in different countries or states or even provinces of a country. Douglas Peucker Algorithm for shape approximation has been used in this research to detect the rectangular contours and the most prominent rectangular contour is extracted as a number plate (NP) and the connected component analysis is used to segment the characters followed by optical character recognition (OCR) to recognize the number plate characters. A custom dataset of 210 vehicle images with different colors at various distances and lighting conditions was used for the proposed method captured on my smart phone Galaxy J7 Model SM-j700F at roads and parking. The dataset contains various types of vehicles (i.e. Trucks, motorcars, mini-buses, tractors, pick-ups etc). The proposed method shows an average result of 95.5%. The novelty used in this method is that it works for different colors simultaneously because in Pakistan, several colors are used for vehicle NPs. Full Tex

Automatic Vehicle Number Plate Recognition Approach Using Color Detection Technique

An Automatic Vehicle Number Plate Recognition System (AVNPR) is a key research area in image processing. Various techniques are developed and tested by researchers to improve the detection and recognition rate of AVNPR system but faced problems due to issues such as variation in format, lighting conditions, scales, and colors of number plates in different countries or states or even provinces of a country. Douglas Peucker Algorithm for shape approximation has been used in this research to detect the rectangular contours and the most prominent rectangular contour is extracted as a number plate (NP) and the connected component analysis is used to segment the characters followed by optical character recognition (OCR) to recognize the number plate characters. A custom dataset of 210 vehicle images with different colors at various distances and lighting conditions was used for the proposed method captured on my smart phone Galaxy J7 Model SM-j700F at roads and parking. The dataset contains various types of vehicles (i.e. Trucks, motorcars, mini-buses, tractors, pick-ups etc). The proposed method shows an average result of 95.5%. The novelty used in this method is that it works for different colors simultaneously because in Pakistan, several colors are used for vehicle NPs. Full Tex

Evaluation of Warm Season Turfgrass under Different Irrigation Regimes in Arid Region

Turfgrasses play a very important role in enhancing quality of life in modern urban living. Water quantity is the most important challenge worldwide in establishing and maintaining quality turf. The present study was aimed to test the performance of three warm season turfgrasses under four water levels for plantation in arid zones. Pits (48) measuring 1m length x 1m width x 0.6 m depth were planted with four replications of Common Bermuda grass (Cynodon dactylon), Tifway Bermuda grass (Cynodon dactylon x transvaalensis) and Seashore Paspalum grass (Paspalum vaginatum) in complete randomized design (CRD). Irrigation was done daily with 15 l/plot during the first 4 weeks (establishment period) and four irrigation levels (5, 10, and 15, 20 l/lot) were maintained in the following 8 weeks (treatment period). Physical parameters (canopy temperatures, ambient temperature, leaf area, shoot production and relative water content) were measured once in two week as well as the visual quality (shoot color, shoot density and shoot uniformity) was assessed, however, chlorophyll analysis was done in the end of the study. It was found that temperature has significant effect on performance of turfgrasses. Canopy temperature was higher than ambient temperature in the three turfgrasses but it has different level in each variety. Five liter of water per day per square meter gave acceptable turf quality when ambient temperature ranged from 20 to 33�C. Seashore paspalum performed best followed by Tifway Bermuda grass and common Bermuda grass respectively