Chlordecone (CLD), also named Kepone, is a synthetic organochlorine pesticide. As one of the common persistent organic pollutants (POPs) in nature, CLD has a profound impact on the environment and human health. The study aims to investigate the reproductive toxicity effects of CLD on male Caenorhabditis elegans and on progeny. L1-stage male nematodes were exposed to the control group (M9 solution) and four dose groups (0.02, 0.2, 2, and 20 μg/L). After exposure for 48 h, the male nematodes were picked to mating experiment and progeny experiment that the number of progeny and the time of observation in male parent and in F1 generation were counted; the number of germ cells and the number of sperm in the meiotic division of male nematodes were counted by staining with dimercaptophenyl hydrazine (DAPI), and the nematode gland area was observed under the bright field of the microscope. In male nematodes, the results showed that a number of progeny were 351.20 ± 31.40, 321.60 ± 24.70, 307.30 ± 19.30, 240.10 ± 27.60, and 227.90 ± 22.70 (P < 0.05); the generation times were 55.80 ± 1.95 h, 56.40 ± 1.60 h, 56.70 ± 0.92 h, 60.80 ± 0.95 h, and 69.60 ± 1.97 h (P < 0.05); relative areas of gonad were (99.80 ± 6.27)%, (93.00 ± 1.70)%, (85.00 ± 1.70)%, (70.70 ± 9.81)%, and (60.00 ± 5.23)% (P < 0.05); DAPI staining results showed the number of germ cells in meiosis area were 191.00 ± 10.97, 181.10 ± 15.56, 177.00 ± 9.20, 147.50 ± 10.56, and 139.30 ± 23.79 (P < 0.05); the sperm numbers were 335.60 ± 21.31, 308.60 ± 19.60, 306.00 ± 11.23, 260.10 ± 27.41, and 255.00 ± 3.72 (P < 0.05). In the F1 generation, the progeny numbers were 328.10 ± 22.28, 167.50 ± 15.30, 150.00 ± 13.65, 131.30 ± 18.40, and 130.20 ± 16.17 (P < 0.05); the generation times were 55.50 ± 2.36, 71.10 ± 0.97, 70.90 ± 0.52, 74.10 ± 2.07, and 73.90 ± 1.35 h (P < 0.05). The groups are grouped in order as M9 solution, 0.02, 0.2, 2, and 20 μg/L. The results revealed that CLD caused decrease in progeny number, relative area of gonad, number of germ cells, and sperm number and prolonged the generation time in the male nematode. In offspring grown up without CLD, the effect of CLD on generation time and sperm number can still be observed on offspring. In conclusion, CLD induces male nematode reproductive toxicity and causes defects in offspring.

South Asia is susceptible to drought due to high variation in monthly precipitation. The drought indices deriving from remote sensing data have been used to monitor drought events. To secure agricultural land in South Asia, timely and effective drought monitoring is very important. In this study, TRMM data was utilized along with remote sensing techniques for reliable drought monitoring. The Drought Severity Index (DSI), Temperature Vegetation Drought Index (TVDI), NDVI, and Normalized Vegetation Supply Water Index (NVSWI) are more helpful in describing the drought events in South Asia due to the dryness and low vegetation. To categorize drought-affected areas, the spatial maps of TRMM were used to confirm MODIS-derived TVDI, DSI, and NVSWI. The DSI, TVDI, NVSWI, and Normalized Monthly Precipitation Anomaly Percentage (NAP) indices with an integrated use of MODIS-derived ET/PET and NDVI were selected as a tool for monitoring drought in South Asia. The seasonal DSI, TVDI, NVSWI, NAP, and NDVI values confirmed that South Asia suffered an extreme drought in 2001, which continued up to 2003. The correlation was generated among DSI, NAP, NVWSI, NDVI, TVDI, and TCI on a seasonal basis. The significantly positive correlation values of DSI, TVDI, and NVSWI were in DJF, MAM, and SON seasons, which were described as good drought monitoring indices during these seasons. During summer, the distribution values of drought indicated that more droughts occurred in the southwest regions as compared to the northeast region of South Asia. From 2001 to 2017, the change trend of drought was characterized; the difference of drought trend was obviously indicated among different regions. In South Asia, generally, the frequency of drought showed declining trends from 2001 to 2017. It was verified that these drought indices are a comprehensive drought monitoring indicator and would reduce drought risk in South Asia.

The primary objective of mobile phone technology is to achieve communication with any person at any place and time. In the modern era, it is impossible to ignore the usefulness of mobile phone technology in cases of emergency as many lives have been saved. However, the biological effects they may have on humans and other animals have been largely ignored and not been evaluated comprehensively. One of the reasons for this is the speedy uncontrollable growth of this technology which has surpassed our researching ability. Initiated with the first generation, the mobile telephony currently reaches to its fifth generation without being screened extensively for any biological effects that they may have on humans or on other animals. Mounting evidences suggest possible non-thermal biological effects of radiofrequency electromagnetic radiation (RF-EMR) on brain and behavior. Behavioral studies have particularly concentrated on the effects of RF-EMR on learning, memory, anxiety, and locomotion. The literature analysis on behavioral effects of RF-EMR demonstrates complex picture with conflicting observations. Nonetheless, numerous reports suggest a possible behavioral effect of RF-EMR. The scientific findings about this issue are presented in the current review. The possible neural and molecular mechanisms for the behavioral effects have been proposed in the light of available evidences from the literature.

Arsenic exposure by groundwater contamination is a menace which threatens more than 26 million individuals of West Bengal. Interestingly, with similar levels of arsenic exposure, only 15–20% of the population show arsenic-induced skin lesions, the hallmarks of chronic arsenic toxicity, but the rest do not. In this study, our aim was to identify whether microRNAs (miRNA) have any role to play in causing such arsenic susceptibility. Global plasma miRNA profiling was done in 12 arsenic-exposed individuals with skin lesions and 12 exposed individuals without skin lesions. Two hundred two miRNAs were found to be differentially regulated between the two study groups. Results were validated by quantitative real-time PCR in 30 exposed subjects from each of the groups, which showed that among others miR-21, miR-23a, miR-27a, miR-122, miR-124, miR-126, miR-619, and miR-3613 were significantly upregulated and miR-1282 and miR-4530 were downregulated in the skin lesion group compared with the no skin lesion group. Bioinformatic analyses predicted that these altered miRNAs have targets in 7 different biochemical pathways, including glycerophospholipid metabolism, colorectal cancer, glycosphingolipid biosynthesis, T cell receptor signaling, and neurotrophin signaling pathways; glycerophospholipid metabolism pathway being the most enriched pathway. Association study show that these microRNAs contribute significantly to the increased prevalence of other non-dermatological health effects like conjunctival irritations of the eyes and respiratory distress in the study subjects. To our knowledge, this is the first study of its kind involving miRNA expressions contributing to arsenic susceptibility in the exposed population of West Bengal.

Urban water supply networks are susceptible to intentional, accidental chemical, and biological pollution, which pose a threat to the health of consumers. In recent years, drinking-water pollution incidents have occurred frequently, seriously endangering social stability and security. The real-time monitoring for water quality can be effectively implemented by placing sensors in the water supply network. However, locating the source of pollution through the data detection obtained by water quality sensors is a challenging problem. The difficulty lies in the limited number of sensors, large number of water supply network nodes, and dynamic user demand for water, which leads the pollution source localization problem to an uncertainty, large-scale, and dynamic optimization problem. In this paper, we mainly study the dynamics of the pollution source localization problem. Previous studies of pollution source localization assume that hydraulic inputs (e.g., water demand of consumers) are known. However, because of the inherent variability of urban water demand, the problem is essentially a fluctuating dynamic problem of consumer’s water demand. In this paper, the water demand is considered to be stochastic in nature and can be described using Gaussian model or autoregressive model. On this basis, an optimization algorithm is proposed based on these two dynamic water demand change models to locate the pollution source. The objective of the proposed algorithm is to find the locations and concentrations of pollution sources that meet the minimum between the analogue and detection values of the sensor. Simulation experiments were conducted using two different sizes of urban water supply network data, and the experimental results were compared with those of the standard genetic algorithm.

Monomethylmercury (MeHg) is one of the most toxic and the most commonly occurring organomercury compound and the wetlands are one of the main areas of generation of this Hg form. Concretely, it is in the macrophyte root system where better conditions are given for its generation. However, the knowledge of absorption and subsequent distribution of mercury (Hg) and monomethylmercury in aquatic plants is still limited. Mercury mining district such as Almadén (Ciudad Real, Spain) is a natural laboratory where different rivers flow and the species Typha domingensis Pers. is a common macrophyte which grows in their riverbanks. The aim of the present work is to apply a recently developed method specially designed to analyze Hg species in plant tissues to the different fractions of T. domingensis under real field conditions and to study the accumulation and distribution of Hg species (inorganic Hg and MeHg) within the plant. The results proved that whatever Hg species has preference to be accumulated in the belowground fractions and demonstrated a high efficiency in the accumulation of MeHg.

Heavy metal contamination, one of the greatest global problems, not only endangers humans and animals but also negatively affects plants. New trends, the production and industrial applications of metals in nanoforms, lead to release of large amounts of nanoparticles into the environment. However, the influence of nanoparticles on living organisms is not well understood. Cadmium is a heavy metal not essential for plants, and to its phytotoxicity also contributes its chemical similarity to zinc. It has been recorded that zinc at low concentrations reduces the toxicity of cadmium, but our results with ZnO nanoparticles did not proved it. In contrast, ZnO nanoparticles significantly increased the negative effect of cadmium, which was reflected mainly in changes in the content of photosynthetic pigments.

This study investigates the removal of selected pharmaceuticals, as recalcitrant organic compounds, from synthetic wastewater using an electro-membrane bioreactor (eMBR). Diclofenac (DCF), carbamazepine (CBZ), and amoxicillin (AMX) were selected as representative drugs from three different therapeutic groups such as anti-inflammatory, anti-epileptic, and antibiotic, respectively. An environmentally relevant concentration (10 μg/L) of each compound was spiked into the synthetic wastewater, and then, the impact of appending electric field on the control of membrane fouling and the removal of conventional contaminants and pharmaceutical micropollutants were assessed. A conventional membrane bioreactor (MBR) was operated as a control test. A reduction of membrane fouling was observed in the eMBR with a 44% decrease of the fouling rate and a reduction of membrane fouling precursors. Humic substances (UV₂₅₄), ammonia nitrogen (NH₄-N), and orthophosphate (PO₄-P) showed in eMBR removal efficiencies up to 90.68 ± 4.37, 72.10 ± 13.06, and 100%, respectively, higher than those observed in the MBR. A reduction of DCF, CBZ, and AMX equal to 75.25 ± 8.79, 73.84 ± 9.24, and 72.12 ± 10.11%, respectively, was found in the eMBR due to the enhanced effects brought by electrochemical processes, such as electrocoagulation, electrophoresis, and electrooxidation.

Nanomaterials (NMs) commercially used for various activities mostly end up in landfills. Reduced biogas productions reported in landfill reactors create a need for more comprehensive research on these greatly-diverse microbial pools. In order to evaluate the impact of one of the most widely-used NMs, namely nano-zinc oxide (nano-ZnO), simulated bioreactor and conventional landfills were operated using real municipal solid waste (MSW) for 300 days with addition nano-ZnO. Leachate samples were taken at different phases and analyzed by 16S rRNA gene amplicon sequencing. The bacterial communities were distinctly characterized by Cloacamonaceae (phylum WWE1), Rhodocyclaceae (phylum Proteobacteria), Porphyromonadaceae (phylum Bacteroidetes), and Synergistaceae (phylum Synergistetes). The bacterial community in the bioreactors shifted at the end of the operation and was dominated by Rhodocyclaceae. There was not a major change in the bacterial community in the conventional reactors. The methanogenic archaeal diversity highly differed between the bioreactors and conventional reactors. The dominance of Methanomicrobiaceae was observed in the bioreactors during the peak methane-production period; however, their prominence shifted to WSA2 in the nano-ZnO-added bioreactor and to Methanocorpusculaceae in the control bioreactor towards the end. Methanocorpusculaceae was the most abundant family in both conventional control and nano-ZnO-containing reactors.