Although widespread antibiotic resistance has been mostly attributed to the selective pressure generated by overuse and misuse of antibiotics, recent growing evidence suggests that chemicals other than antibiotics, such as certain metals, can also select and stimulate antibiotic resistance via both co-resistance and cross-resistance mechanisms. For instance, tetL, merE, and oprD genes are resistant to both antibiotics and metals. However, the potential de novo resistance induced by heavy metals at environmentally-relevant low concentrations (much below theminimum inhibitory concentrations [MICs], also referred as sub-inhibitory) has hardly been explored. This study investigated and revealed that heavy metals, namely Cu(II), Ag(I), Cr(VI), and Zn(II), at environmentally-relevant and sub-inhibitory concentrations, promoted conjugative transfer of antibiotic resistance genes (ARGs) between E. coli strains. The mechanisms of this phenomenon were further explored, which involved intracellular reactive oxygen species (ROS) formation, SOS response, increased cell membrane permeability, and altered expression of conjugation-relevant genes. These findings suggest that sub-inhibitory levels of heavy metals that widely present in various environments contribute to the resistance phenomena via facilitating horizontal transfer of ARGs. This study provides evidence from multiple aspects implicating the ecological effect of low levels of heavy metals on antibiotic resistance dissemination and highlights the urgency of strengthening efficacious policy and technology to control metal pollutants in the environments.

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Endothelin receptor B subtype 2 (EDNRB2) is a seven-transmembrane G-protein coupled receptor. In this study, we investigated EDNRB2 gene as a candidate gene for duck spot plumage pattern according to studies of chicken and Japanese quail. The entire coding region was cloned by the reverse transcription polymerase chain reaction (RT-PCR). Sequence analysis showed that duck EDNRB2 cDNA contained a 1311bp open reading frame and encoded a putative protein of 436 amino acids residues. The transcript shared 89%-90% identity with the counterparts in other avian species. A phylogenetic tree based on amino acid sequences showed that duck EDNRB2 was evolutionary conserved in avian clade. The entire coding region of EDNRB2 were sequenced in 20 spot and 20 non-spot ducks, and 13 SNPs were identified. Two of them (c.940G>A and c.995G>A) were non-synonymous substitutions, and were genotyped in 647 ducks representing non-spot and spot phenotypes. The c.995G>A mutation, which results in the amino acid substitution of Arg332His, was completely associated with the spot phenotype: all 152 spot ducks were carriers of the AA genotype and the other 495 individuals with non-spot phenotype were carriers of GA or GG genotype, respectively. Segregation in 17 GA×GG and 22 GA×GA testing combinations confirmed this association since the segregation ratios and genotypes of the offspring were in agreement with the hypothesis. In order to investigate the underlying mechanism of the spot phenotype, MITF gene was used as cell type marker of melanocyte progenitor cells while TYR and TYRP1 gene were used as cell type markers of mature melanocytes. Transcripts of MITF, TYR and TYRP1 gene with expected size were identified in all pigmented skin tissues while PCR products were not obtained from non-pigmented skin tissues. It was inferred that melanocytes are absent in non-pigmented skin tissues of spot ducks.

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Forty-three high school students participated in an online reading task to generate a critical question on a controversial topic. Participants’ concurrent verbal reports of strategy use (i.e., information location, meaning making, source evaluation, self-monitoring) and their reading outcome (i.e., the generated question) were evaluated with scoring rubrics. Path analysis indicated that strategic meaning making coordinated with self-monitoring and source evaluation positively influenced the quality of the generated questions, whereas information-locating strategies alone contributed little to the participants’ question generation. Further, source evaluation played a positive role when readers monitored and regulated their strategies for information location and meaning making. The findings on the interplay of metacognitive, critical, and intertextual strategies in online reading are discussed with regard to research and practice.

Alzheimer’s disease is the most common neurodegenerative disease and is characterized by the accumulation of amyloid-beta peptides leading to the formation of plaques and tau protein tangles in brain. These neuropathological features precede cognitive impairment and Alzheimer’s dementia by many years. To better understand and predict the course of disease from early-stage asymptomatic to late-stage dementia, it is critical to study the patterns of progression of multiple markers. In particular, we aim to predict the likely future course of progression for individuals given only a single observation of their markers. Improved individual-level prediction may lead to improved clinical care and clinical trials. We propose a two-stage approach to modeling and predicting measures of cognition, function, brain imaging, fluid biomarkers, and diagnosis of individuals using multiple domains simultaneously. In the first stage, joint (or multivariate) mixed-effects models are used to simultaneously model multiple markers over time. In the second stage, random forests are used to predict categorical diagnoses (cognitively normal, mild cognitive impairment, or dementia) from predictions of continuous markers based on the first-stage model. The combination of the two models allows one to leverage their key strengths in order to obtain improved accuracy. We characterize the predictive accuracy of this two-stage approach using data from the Alzheimer’s Disease Neuroimaging Initiative. The two-stage approach using a single joint mixed-effects model for all continuous outcomes yields better diagnostic classification accuracy compared to using separate univariate mixed-effects models for each of the continuous outcomes. Overall prediction accuracy above 80% was achieved over a period of 2.5 years. The results further indicate that overall accuracy is improved when markers from multiple assessment domains, such as cognition, function, and brain imaging, are used in the prediction algorithm as compared to the use of markers from a single domain only.

Perovskite nanocrystals are a new type of fluorescent material with the advantages of facile preparation process, bright tunable color with high quantum yield. They are ideal candidates for optoelectronic devices such as light-emitting diode (LED) and display. However, for practical applications of iodine-based perovskite nanocrystals, the photostability remains a great challenge because of their sensitivity to environmental factors such as oxygen, humidity etc. In this paper, we improve the photostability of CsPbI 3 by introducing the polymethyl methacrylate (PMMA) as a matrix to form flexible perovskite/PMMA composite films. The composite films maintain good photoluminescence quantum yield for 25 d in air and 4 d in water. Furthermore, these films are flexible and can sustain multiple bending and folding while maintaining their photoluminescence properties. This photostability against mechanical deformation allows for the development of flexible devices. As an example, flexible white light-emitting diodes (WLED) were produced with chromaticity coordination (0.31, 0.32), color temperature 6735 K and good stability over time.