Antibiotic resistance in urban green spaces mirrors the pattern of industrial distribution

Urban green spaces are closely related to the activities and health of urban residents. Turf grass and soil are two major interfaces between the environmental and human microbiome, which represent potential pathways for the spread of antibiotic resistance genes (ARGs) from environmental to human microbiome through skin-surface contact. However, the information regarding the prevalence of ARGs in urban green spaces and drivers in shaping their distribution patterns remain unclear. Here, we profiled a wide spectrum of ARGs in grass phyllosphere and soils from 40 urban parks across Greater Melbourne, Australia, using high throughput quantitative PCR. A total of 217 and 218 unique ARGs and MGEs were detected in grass phyllosphere and soils, respectively, conferring resistance to almost all major classes of antibiotics commonly used in human and animals. The plant microbiome contained a core resistome, which occupied > 84% of the total abundance of ARGs. In contrast, no core resistome was identified in the soil microbiome. The difference between plant and soil resistome composition was attributed to the difference in bacterial community structure and intensity of environmental and anthropogenic influence. Most importantly, the abundance of ARGs in urban green spaces was significantly positively related to industrial factors including total number of business, number of manufacturing, and number of electricity, gas, water and waste services in the region. Structural equation models further revealed that industrial distribution was a major factor shaping the ARG profiles in urban green spaces after accounting for multiple drivers. These findings have important implications for mitigation of the potential risks posed by ARGs to urban residents

Improve Affective Learning with EEG Approach

With the development of computer science, cognitive science and psychology, a new paradigm, affective learning, has emerged into e-learning domain. Although scientists and researchers have achieved fruitful outcomes in exploring the ways of detecting and understanding learners affect, e.g. eyes motion, facial expression etc., it sounds still necessary to deepen the recognition of learners affect in learning procedure with innovative methodologies. Our research focused on using bio-signals based methodology to explore learner's affect and the study was primarily made on Electroencephalography (EEG). After the EEG signals were collected from EEG equipment, we tidied the EEG data with signal processing algorithms and then extracted some features. We applied k-Nearest-Neighbor classifier and Naive Bayes classifier to these features to find out a combination, which may mostly contribute to reflect learners' affect, for example, Attention. In the classification algorithm, we presented a different way of using the Self-Assessment Manikin (SAM) model to classify and analyze learners attention, although the SAM was normally used for classifying emotions, for example, happiness etc. For the purpose of evaluating our findings, we also developed an affective learning prototype based on university e-learning web site. A real time EEG feedback window and an attention report were integrated into the system. The result of the experiment was encouraging and further discussion was also included in this paper

Comparative transcriptome analysis reveals the involvement of an MYB transcriptional activator, SmMYB108, in anther dehiscence in eggplant

Male sterility is a highly attractive agronomic trait as it effectively prevents self-fertilization and facilitates the production of high-quality hybrid seeds in plants. Timely release of mature pollen following anther dehiscence is essential for stamen development in flowering plants. Although several theories have been proposed regarding this, the specific mechanism of anther development in eggplant remains elusive. In this study, we selected an R2R3-MYB transcription factor gene, SmMYB108, that encodes a protein localized primarily in the nucleus by comparing the transcriptomics of different floral bud developmental stages of the eggplant fertile line, F142. Quantitative reverse transcription polymerase chain reaction revealed that SmMYB108 was preferentially expressed in flowers, and its expression increased significantly on the day of flowering. Overexpression of SmMYB108 in tobacco caused anther dehiscence. In addition, we found that SmMYB108 primarily functions as a transcriptional activator via C-terminal activation (amino acid 262–317). Yeast one-hybrid and dual-luciferase reporter assays revealed that genes (SmMYB21, SmARF6, and SmARF8) related to anther development targeted the SmMYB108 promoter. Overall, our results provide insights into the molecular mechanisms involved in the regulation of anther development by SmMYB108

Dual hydrophobic modifications toward anion exchange membranes with both high ion conductivity and excellent dimensional stability

Abstract(#br)Anion exchange membrane (AEMs) as a kind of important functional material are widely used in many fields including fuel cell, electrodialysis and water treatment. However, synthetic AEMs generally suffer a pernicious trade-off: high ion-conductive AEMs lack dimensional stability and vice versa. Herein we demonstrate a versatile strategy to prepare the AEMs with both high ion conductivity and excellent dimensional stability ( i.e. , low swelling ratio) via hydrophobic crosslinking and introducing hydrophobic chains. The hydrophobic length of crosslinkers has great influence on construction of highly efficient ion channels in the AEMs. Amazingly, the hydrophilic poly (phenylene oxide) (PPO) AEM crosslinked by 1,8-diaminooctane has the highest hydroxide conductivity that is further improved to 157.2 mS cm −1 (10% increases) with a low swelling ratio of 12.9% at 80 °C by introducing hydrophobic PPO backbone. This AEM not only overcomes the trade-off between the ion conductivity and the dimensional stability of crosslinked AEMs, but also breaks the upper bound between the ion conductivity and the water uptake. The newly developed strategy of hydrophobic dual-modifications promises to be an effective approach to develop the high-performance AEMs

The Protective Effects of Bushen Daozhuo Granule on Chronic Non-bacterial Prostatitis

Background: Chronic non-bacterial prostatitis (CNP), one of the most common chronic diseases in urology, leads to pain in the prostate and dysuria, critically affecting the physical or mental health of patients. However, there are no standard treatment approaches for the treatment of CNP in the clinic. Although the clinical application of Bushen Daozhuo granule (BSDZG) offers hope to CNP patients in China, the mechanisms of BSDZG in treating CNP are still not entirely clear. Hence, we aimed to investigate the novel therapeutic mechanisms of BSDZG on CNP.Methods: In this study, we first assayed the prostate index of rats and then determined the anti-inflammatory and anti-apoptotic effects of BSDZG on CNP in vivo and in vitro by employing ELISA kits and TUNEL staining. Next, we investigated whether the anti-inflammatory and anti-apoptotic mechanisms of BSDZG on prostate protein-induced rats and lipopolysaccharide (LPS) induced RWPE-1 cells were related to the AKT, p38 MAPK, and NF-κB pathways with the help of Western blot. Finally, the influence of BSDZG on the interaction between the p38 MAPK and NF-κB pathway in LPS-induced RWPE-1 cells was explored by adopting dehydrocorydaline (DHC, p38 MAPK activator) with the help of ELISA kits and Western blot.Results:In vivo, BSDZG effectively reduced the prostate index. In vivo and in vitro, BSDZG dramatically declined the level of two pro-inflammatory cytokines, TNF-α and IL-1β, as well as the apoptosis rate. Moreover, in vivo and in vitro, BSDZG memorably upregulated the expression level of p-AKT, and substantially downregulated the expression level of p-p38 MAPK and NF-κB2. The activation of p38 MAPK significantly reversed the moderation effects of BSDZG on the level of TNF-α and IL-1β, as well as the expression level of p-p38 MAPK and NF-κB2 in vitro.Conclusion: To sum up, the in vivo and in vitro therapeutic mechanisms of BSDZG on CNP were reflected as the anti-inflammation and anti-apoptosis that was formed by inhibiting the level of pro-inflammatory cytokines, TNF-α and IL-1β, to regulate the AKT, p38 MAPK, and NF-κB pathways, and the anti-inflammatory effect of BSDZG was realized by suppressing the p38 MAPK pathway to inhibit the downstream NF-κB pathway

The clinical characteristics of Chinese elderly patients with different durations of type 2 diabetes mellitus

AimsTo explore the clinical characteristics among elderly (aged ≥60 years) patients with type 2 diabetes (T2DM) of different durations.MethodsClinical characteristics were investigated in 3840 elderly T2DM patients according to their different durations of diabetes (< 1 year, 1~5 years, 5~10 years, and ≥ 10 years). Kruskal-Wallis and Dunn tests were used to assess the differences among groups for continuous variables. The chi-square and post hoc tests were carried out for dichotomous variables. The logistic regression was adopted to investigate the relationships between various durations of diabetes and the control rates of achieving the control targets for T2DM as well as diabetic vascular complications.ResultsThere were 972, 896, 875 and 1097 patients with a duration of diabetes of <1, 1~5, 5~10 and ≥10 years, respectively. In logistic regression models adjusted for age, sex, education, BMI, smoking and family history of diabetes, elderly T2DM patients with a duration of diabetes of ≥10 years were more likely to reach the comprehensive control targets for TC (ORTC = 1.36, 95% CI =1.14-1.63), LDL-C (ORLDL-C = 1.39, 95% CI =1.17-1.66), TG (ORTG = 1.76, 95% CI =1.46-2.12) and BMI (ORBMI = 1.82, 95% CI =1.52-2.18). Elderly T2DM patients with a duration of diabetes of 1~5 years were more likely to achieve the HbA1c control target (ORHbA1c = 1.92, 95% CI = 1.59-2.31) than elderly T2DM patients with a duration of diabetes of <1 year. Furthermore, in elderly T2DM patients with a duration of diabetes of 5~10 years or ≥ 10 years, the duration of diabetes was positively associated with diabetic macrovascular complications (coronary heart disease and peripheral artery disease). In elderly T2DM patients with a duration of diabetes of over 10 years, the duration of diabetes was associated with diabetes kidney disease (all P < 0.05).ConclusionsIt is worth noting that the clinical characteristics of elderly patients with type 2 diabetes in different durations of diabetes are different

MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

According to the World Health Organization, the number of mental disorder patients, especially depression patients, has grown rapidly and become a leading contributor to the global burden of disease. However, the present common practice of depression diagnosis is based on interviews and clinical scales carried out by doctors, which is not only labor-consuming but also time-consuming. One important reason is due to the lack of physiological indicators for mental disorders. With the rising of tools such as data mining and artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. However, good quality physiological data for mental disorder patients are hard to acquire. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and audio data from clinically depressed patients and matching normal controls. All our patients were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications. The 128-electrodes EEG signals of 53 subjects were recorded as both in resting state and under stimulation; the 3-electrode EEG signals of 55 subjects were recorded in resting state; the audio data of 52 subjects were recorded during interviewing, reading, and picture description. We encourage other researchers in the field to use it for testing their methods of mental-disorder analysis