Dual-targeting nanotherapeutics antagonize hyperinsulinemia-promoted tumor growth via activating cell autophagy.

Hyperinsulinemia, a concomitant symptom in type 2 diabetes mellitus (T2DM) promotes the migration, invasion and proliferation of tumors by inhibiting autophagy. Therefore, it is necessary to search for antitumor drugs that can effectively antagonize hyperinsulinemia by promoting autophagy. In this study, dual-targeting modified selenium nanoparticles (u/A-SeNPs) were proposed as a biocompatible tumor chemotherapeutic drug to antagonize high insulin. The modification of chitosan (CS) and grafting targeted peptides (uPA/ACPP) allowed SeNPs to exert better selectivity and higher antitumor activity. The nanotherapeutics entered tumor cells through receptor-mediated endocytosis and produced excessive ROS. Meanwhile, u/A-SeNPs significantly increased the level of autophagy in tumor cells, as detected by monodansylcadaverine (MDC) and mRFP-GFP-LC3. U/A-SeNPs cause mitochondrial fragmentation to induce the cell apoptosis via the synergistic action of overproduced ROS and activated autophagy. In conclusion, this study proposes a feasible method for the synthesis of dual-targeting nanomedicines, and it also provides a new strategy for the application of Se-based nanotherapeutics in tumor therapy under hyperinsulinemia conditions.

Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress.

Video tracking based biological early warning system achieved a great progress with advanced computer vision and machine learning methods. Ability of video tracking of multiple biological organisms has been largely improved in recent years. Video based behavioral monitoring has become a common tool for acquiring quantified behavioral data for aquatic risk assessment. Investigation of behavioral responses under chemical and environmental stress has been boosted by rapidly developed machine learning and artificial intelligence. In this paper, we introduce the fundamental of video tracking and present the pioneer works in precise tracking of a group of individuals in 2D and 3D space. Technical and practical issues suffered in video tracking are explained. Subsequently, the toxic analysis based on fish behavioral data is summarized. Frequently used computational methods and machine learning are explained with their applications in aquatic toxicity detection and abnormal pattern analysis. Finally, advantages of recent developed deep learning approach in toxic prediction are presented.

Implementation of Fractal Dimension and Self-Organizing Map to Detect Toxic Effects of Toluene on Movement Tracks of Daphnia magna.

Movement behaviors of an indicator species, Daphnia magna, in response to contaminants have been implemented to monitor environmental disturbances. Complexity in movement tracks of Daphnia magna was characterized by use of fractal dimension and self-organizing map. The individual movement tracks of D. magna were continuously recorded for 24 hours before and after treatments with toluene at the concentration of 10 mg/L, respectively. The general complexity in movement tracks (10 minutes) was characterized by fractal dimension. Results showed that average fractal dimension of movement tracks was decreased from 1.62 to 1.22 after treatments. The instantaneous movement parameters of movement segments in 5 s were input into the self-organizing map to investigate the swimming pattern changes under stresses of toluene. Abnormal behaviors of D. magna are more frequently observed after treatments than before treatments. Computational methods in ecological informatics could be utilized to obtain the useful information in behavioral data of D. magna and would be further applied as an in situ monitoring tool in water environment.

Effect doses for protection of human health predicted from physicochemical properties of metals/metalloids.

Effect doses (EDs) of metals/metalloids, usually obtained from toxicological experiments are required for developing environmental quality criteria/standards for use in assessment of hazard or risks. However, because in vivo tests are time-consuming, costly and sometimes impossible to conduct, among more than 60 metals/metalloids, there are sufficient data for development of EDs for only approximately 25 metals/metalloids. Hence, it was deemed a challenge to derive EDs for additional metals by use of alternative methods. This study found significant relationships between EDs and physicochemical parameters for twenty-five metals/metalloids. Elements were divided into three classes and then three individual empirical models were developed based on the most relevant parameters for each class. These parameters included log-ßn, ΔE0 and Xm2r, respectively (R2 = 0.988, 0.839, 0.871, P < 0.01). Those models can satisfactorily predict EDs for another 25 metals/metalloids. Here, these alternative models for deriving thresholds of toxicity that could be used to perform preliminarily, screen-level health assessments for metals are presented.

Inhalation toxicity of indoor air pollutants in Drosophila melanogaster using integrated transcriptomics and computational behavior analyses.

We conducted an inhalation toxicity test on the alternative animal model, Drosophila melanogaster, to investigate potential hazards of indoor air pollution. The inhalation toxicity of toluene and formaldehyde was investigated using comprehensive transcriptomics and computational behavior analyses. The ingenuity pathway analysis (IPA) based on microarray data suggests the involvement of pathways related to immune response, stress response, and metabolism in formaldehyde and toluene exposure based on hub molecules. We conducted a toxicity test using mutants of the representative genes in these pathways to explore the toxicological consequences of alterations of these pathways. Furthermore, extensive computational behavior analysis showed that exposure to either toluene or formaldehyde reduced most of the behavioral parameters of both wild-type and mutants. Interestingly, behavioral alteration caused by toluene or formaldehyde exposure was most severe in the p38b mutant, suggesting that the defects in the p38 pathway underlie behavioral alteration. Overall, the results indicate that exposure to toluene and formaldehyde via inhalation causes severe toxicity in Drosophila, by inducing significant alterations in gene expression and behavior, suggesting that Drosophila can be used as a potential alternative model in inhalation toxicity screening.

Selenadiazole derivatives antagonize hyperglycemia-induced drug resistance in breast cancer cells by activation of AMPK pathways.

Hyperglycemia is an important factor for chemoresistance of breast cancer patients with diabetes. In the present study, a novel selenadiazole derivative has been evaluated and found to be able to antagonize the doxorubicin (DOX) resistance of MCF-7 cells under simulated diabetes conditions. Hyperglycemia promotes the proliferation, invasion and migration of MCF-7 cells through activation of ERK and AKT pathways, which could be inhibited by the synthetic selenadiazole derivative. The antitumor effects of the selenadiazole derivative were attributed to its ability to activate AMPK pathways. Furthermore, the high lipophilicity (log P = 1.9) of the synthetic selenadiazole derivative facilitated its uptake by cancer cells and subsequently potentiated the cellular uptake of DOX, leading to a strong enhancment of the antiproliferative activity of DOX on MCF-7 cells by induction of apoptosis. The apoptosis was initiated by the ROS overproduction induced by the cooperation of the selenadiazole derivative and DOX. The excessive ROS then caused damage to DNA, which upregulated the expression of proapoptosis Bcl-2 family proteins and led to fragmentation of mitochondria, which finally caused apoptosis of the cancer cells. Taken together, this study provides a rational strategy for using selenadiazole derivatives to overcome hyperglycemia-induced drug resistance in breast cancer by activation of AMPK-mediated pathways.

Comparative study of species sensitivity distributions based on non-parametric kernel density estimation for some transition metals.

Transition metals in the fourth period of the periodic table of the elements are widely widespread in aquatic environments. They could often occur at certain concentrations to cause adverse effects on aquatic life and human health. Generally, parametric models are mostly used to construct species sensitivity distributions (SSDs), which result in comparison for water quality criteria (WQC) of elements in the same period or group of the periodic table might be inaccurate and the results could be biased. To address this inadequacy, the non-parametric kernel density estimation (NPKDE) with its optimal bandwidths and testing methods were developed for establishing SSDs. The NPKDE was better fit, more robustness and better predicted than conventional normal and logistic parametric density estimations for constructing SSDs and deriving acute HC5 and WQC for transition metals in the fourth period of the periodic table. The decreasing sequence of HC5 values for the transition metals in the fourth period was Ti > Mn > V > Ni > Zn > Cu > Fe > Co > Cr(VI), which were not proportional to atomic number in the periodic table, and for different metals the relatively sensitive species were also different. The results indicated that except for physical and chemical properties there are other factors affecting toxicity mechanisms of transition metals. The proposed method enriched the methodological foundation for WQC. Meanwhile, it also provided a relatively innovative, accurate approach for the WQC derivation and risk assessment of the same group and period metals in aquatic environments to support protection of aquatic organisms.

Analysis of the Time-Concentration-Mortality Response of Nilaparvata lugens (Hemiptera: Delphacidae) to Paichongding.

Paichongding is an adicyclicnitromethylene neonicotinoid insecticide with a cis-configuration. Bioassay of paichongding was conducted against Nilaparvata lugens Stål under a laboratory condition. Mortality of N. lugens was analyzed by time-concentration-mortality (TCM) regressions based on the complementary log-log (CLL) model. The conditional mortalities of test individuals increased with the exposure time after treatments with different concentrations, showing that the speed of insecticidal action is concentration dependent. Meanwhile, the conditional mortalities of N. lugens increased as the concentrations of paichongding increased for all developmental stages from instars I-II to macropterous females. Correspondingly, LC(50) and LC90 values to N. lugens gradually decreased with the developmental stages, in which instars I-II were the most sensitive to paichongding, with LC(50) values of 6.31, 0.45, 0.09, and 0.03 mg/liter for 24, 48, 72, and 96 h after treatments, respectively, while macropterous females were the least sensitive among all developmental stages, with LC(50) values of 309.03, 11.48, 1.35, and 0.19 mg/liter at 24, 48, 72, and 96 h after the treatments, respectively. The time-concentration-mortality modeling was mathematically and biologically robust to evaluate the effects of paichongding on N. lugens. The results suggest that paichongding would be an effective alternative pesticide for controlling N. lugens considering its potent effects.

Non-parametric kernel density estimation of species sensitivity distributions in developing water quality criteria of metals.

Due to use of different parametric models for establishing species sensitivity distributions (SSDs), comparison of water quality criteria (WQC) for metals of the same group or period in the periodic table is uncertain and results can be biased. To address this inadequacy, a new probabilistic model, based on non-parametric kernel density estimation was developed and optimal bandwidths and testing methods are proposed. Zinc (Zn), cadmium (Cd), and mercury (Hg) of group IIB of the periodic table are widespread in aquatic environments, mostly at small concentrations, but can exert detrimental effects on aquatic life and human health. With these metals as target compounds, the non-parametric kernel density estimation method and several conventional parametric density estimation methods were used to derive acute WQC of metals for protection of aquatic species in China that were compared and contrasted with WQC for other jurisdictions. HC5 values for protection of different types of species were derived for three metals by use of non-parametric kernel density estimation. The newly developed probabilistic model was superior to conventional parametric density estimations for constructing SSDs and for deriving WQC for these metals. HC5 values for the three metals were inversely proportional to atomic number, which means that the heavier atoms were more potent toxicants. The proposed method provides a novel alternative approach for developing SSDs that could have wide application prospects in deriving WQC and use in assessment of risks to ecosystems.

Rational design of selenadiazole derivatives to antagonize hyperglycemia-induced drug resistance in cancer cells.

Hyperglycemia is an important factor for chemoresistance of hepatocellular carcinoma patients with diabetes to therapeutics. In the present study, a series of selenadiazole derivatives have been rationally designed, synthesized, and found be able to antagonize drug resistance in HepG2 cells to doxorubicin (DOX) under simulated diabetes conditions. Hyperglycemia could promote the cell proliferation through upregulation of ERK and AKT phosphorylation. However, the synthetic selenadiazole derivatives effectively potentiated the cellular uptake of DOX and enhanced the antiproliferative activity of DOX on HepG2 cells by induction of apoptosis, via regulation of ROS-mediated AMPK activation, inhibition of mTORC1, and an increase in DNA damage. The selenadiazole derivatives that possess an increased lipophilicity could enhance the cellular uptake and anticancer efficacy of DOX. Taken together, this study provides a rational design strategy of selenadiazole derivatives to overcome hyperglycemia-induced drug resistance.

Two new species of Stenochironomus Kieffer (Diptera, Chironomidae) from Zhejiang, China.

Two new species of Stenochironomus Kieffer (Diptera: Chironomidae: Chironominae), Stenochironomusbrevissimus sp. n. and Stenochironomuslinanensis sp. n., are described from China and the male imagines are illustrated. Stenochironomusbrevissimus sp. n. can be separated from the so far known species by having very short and small, spatulate superior volsella with two long setae, whereas Stenochironomuslinanensis sp. n. is easily separated from the other species of Stenochironomus by the following characters: wings transparent, body yellow, superior volsella finger-like, with nine long setae, elongated inferior volsella with four long setae and one well developed terminal spine; tergite IX with 10-15 long setae medially. A key to the males of Stenochironomus occurring in China is given.

Setting water quality criteria in China: approaches for developing species sensitivity distributions for metals and metalloids.

Both nonparametric and parametric approaches were used to construct SSDs for use in ecological risk assessments. Based on toxicity to representative aquatic species and typical water contaminants of metals and metalloids in China, nonparametric methods based on the bootstrap were statistically superior to the parametric curve-fitting approaches. Knowing what the SSDs for each targeted species are might help in selecting efficient indicator species to use for water quality monitoring. The species evaluated herein showed sensitivity variations to different chemical treatments that were used in constructing the SSDs. For example, D. magna was more sensitive than most species to most chemical treatments, whereas D. rerio was sensitive to Hg and Pb but was tolerant to Zn. HC5 values, derived for the pollutants in this study for protecting Chinese species, differed from those published by the USEPA. Such differences may result from differences in geographical conditions and biota between China and the United States. Thus, the degree of protection desired for aquatic organisms should be formulated to fit local conditions. For approach selection, we recommend all approaches be considered and the most suitable approaches chosen. The selection should be based on the practical information needs of the researcher (viz., species composition, species sensitivity, and geological characteristics of aquatic habitats), since risk assessments usually are focused on certain substances, species, or monitoring sites. We used Tai Lake as a typical freshwater lake in China to assess the risk of metals and metalloids to the aquatic species. We calculated hazard quotients for the metals and metalloids that were found in the water of this lake. Results indicated the decreasing ecological risk of these contaminants in the following order: Hg

Predicting criteria continuous concentrations of 34 metals or metalloids by use of quantitative ion character-activity relationships-species sensitivity distributions (QICAR-SSD) model.

Criteria continuous concentrations (CCCs) are useful for describing chronic exposure to pollutants and setting water quality standards to protect aquatic life. However, because of financial, practical, or ethical restrictions on toxicity testing, few data are available to derive CCCs. In this study, CCCs for 34 metals or metalloids were derived using quantitative ion character-activity relationships-species sensitivity distributions (QICAR-SSD) and the final acute-chronic ratio (FACR) method. The results showed that chronic toxic potencies were correlated with several physico-chemical properties among eight species chosen, where the softness index was the most predictive characteristic. Predicted CCCs for most of the metals, except for Lead and Iron, were within a range of 10-fold of values recommended by the U.S. EPA. The QICAR-SSD model was superior to the FACR method for prediction of data-poor metals. This would have significance for predicting toxic potencies and criteria thresholds of more metals or metalloids.

[Ecological risk assessment of bisphenol A in Chinese freshwaters].

Bisphenol A (BPA) has many toxic effects on aquatic organisms, of which the most obvious effect is the estrogenic effect. The data collected in the study were divided into two parts, based on the response of the tested organisms to the estrogenic effects of BPA and their exposed time, and the risk of BPA to Chinese aquatic water was assessed by using quotient method, quotient exponent and probability method, safety threshold value method and joint probability risk assessment, respectively. Similar results were derived from the above four methods. Aquatic organisms were more sensitive to the estrogenic effects of BPA than other toxic effects. The results of risk assessment from safety threshold value method were more accurate and confident than the other three methods. Using the chronic data of BPA's estrogenic effect on tested organisms as the endpoint for risk assessment in safety threshold value method, it was found that in 64.70% of the Chinese freshwaters more than 5% of aquatic organisms were affected by the estrogenic toxicity of BPA, and the maximum allowable concentration of BPA was 15.72 ng x L(-1). Using the acute data of such effects as endpoint in safety threshold value method, in about 20.43% volume of the Chinese freshwaters more than 5% of aquatic organisms were affected by the estrogenic toxicity of BPA, and the maximum allowable concentration was 2.24 x 10(2) ng x L(-1).

A new online monitoring and management system for accidental pollution events developed for the regional water basin in Ningbo, China.

Due to urgency of the accidental pollution events (APE) on one side and the variability in water quality data on the other side, a new online monitoring and management system (OMMS) was developed for the purpose of sustainable water quality management and human health protection as well. The Biological Early Warning System (BEWS) based on the behavioral responses (behavior strength) of medaka (Oryzias latipes) were built in combination with the physico-chemical factor monitoring system (PFMS) in OMMS. OMMS included a monitoring center and six monitoring stations. Communication between the center and the peripheral stations was conducted by the General Packet Radio Service (GPRS) network transmission complemented by a dial-up connection for use when GPRS was unavailable. OMMS could monitor water quality continuously for at least 30 days. Once APEs occurred, OMMS would promptly notify the administrator to make some follow up decisions based on the Emergency Treatment of APE. Meanwhile, complex behavioral data were analyzed by Self-Organizing Map to properly classify behavior response data before and after contamination. By utilizing BEWS, PFMS and the modern data transmission in combination, OMMS was efficient in monitoring the water quality more realistically.