Metagenomics of high-altitude groundwater reveal different health risks associated with antibiotic-resistant pathogens and bacterial resistome in the latitudinal gradient.

Groundwater on the Tibetan Plateau is a critical water resource to people in Asia. However, its prevalence of antibiotic-resistant pathogens (ARPs), bacterial resistome and their driving factors remain unknown. Using metagenomics analysis, a hotspot of antibiotic-resistance genes (ARGs) and last-resort ARGs (LARGs) with a total of 639 subtypes was identified in the groundwater. Importantly, 164 metagenome-assembled genomes (MAGs) which possessed both ARGs and virulence factors (VFs) were assigned as potential ARPs, with the most abundant species being Acinetobacter johnsonii and Acinetobacter pittii. A total of 157 potential ARPs, involving Escherichia coli, were predicted as "natural" ARGs supercarriers. Thirty-six ARPs dominated by the genus Acinetobacter and Pseudomonas were found to harbour LARGs. Co-localizations of the ARG-mobile genetic elements (MGEs) showed that MGEs were significantly associated with ARGs in the ARPs, which suggests ARPs play a prominent role in ARG dissemination. Notably, latitudinal gradient is a driving factor in the occurrence of ARGs and ARPs. The average abundances of ARGs and ARP decreased as the latitude increased, with the highest abundance occurring in the region between 28.6◦N and 29.5◦N. MetaCompare further revealed health risks associated with the resistome decreased as the latitudes increased. These findings indicated different health risks associated with ARPs and bacterial resistome in latitudinal gradient groundwater. They raise the concerns of mitigating ARPs risk in groundwater on the Tibetan Plateau.

CRISPR/Cas9-based engineered Escherichia coli biosensor for sensitive and specific detection of Cd(II) in drinking water.

Cadmium (Cd) is a ubiquitous pollutant that poses a potential threat to human health. Monitoring Cd(II) in drinking water has significant implications for preventing potential threats of Cd(II) to human. However, the weak signal output and response to nontarget interference limit the detection of Cd(II) using bacterial biosensors. In this study, to enable sensitive and specific detection of Cd(II) in water, a stable whole-cell biosensor, K12-PMP-luxCDABE-△cysI, was constructed in a dual-promoter mode by fusing the mercury promoter Pmer, regulatory gene merR(m), and luciferase gene luxCDABE into the E.coli chromosome based on CRISPR/Cas9 gene editing technology. By knocking out the cadmium-resistance-gene cysI, the sensitivity of the biosensor to Cd(II) was further enhanced. The constructed E. coli biosensor K12-PMP-luxCDABE-△cysI exhibited good nonlinear responses to 0.005-2 mg/L Cd(II). Notably, among the three constructed E. coli biosensor, it exhibited the strongest fluorescence intensity, with the limit of detection meeting the allowable limit for Cd(II) in drinking water. Simultaneously, it could specifically detect Cd(II). Nontarget metal ions, such as Zn(II), Hg(II), and Pb(II), did not affect its performance. Furthermore, it exhibited superior performance in detecting Cd(II) in real drinking water samples by avoiding background interference, and showed excellent stability with the relative standard deviation under 5%. Thus, K12-PMP-luxCDABE-△cysI holds promise as a potential tool for the detection of Cd(II) in drinking water.

[Associations between puberty timing and cardiovascular metabolic risk factors among primary and secondary students].

OBJECTIVE: To explore the relationship between puberty timing and cardiovascular metabolic risk factors among primary and secondary students with different genders in Beijing. METHODS: Using the method of stratified cluster sampling by urban and rural areas and school sections, 3 067 students from 16 primary and secondary schools in Fangshan District of Beijing were selected in October 2012, with questionnaire survey, physical examination and serum laboratory testing. In this study, we controlled for confounding factors such as school segments, current residence of the family, birth weight, feeding method, only child, highest educational level of parents, and monthly family income, and then the associations between cardiovascular metabolic risk factors and puberty timing among the primary and secondary students was analyzed by multivariate Logistic analysis. To ensure the reliability of the data, this study adopted strict quality control. RESULTS: A total of 3 067 primary and middle school students aged 7 to 16 years were included in this study, including 1 575 boys and 1 492 girls. The prevalence of premature puberty was 14.73% among the boys and 12.89% among the girls, respectively. The prevalence of delayed puberty was 9.49% among the boys and 10.99% among the girls, respectively. The detection rates of central obesity, hypertension, hyperglycemia, and dyslipidemia among the primary and secondary students were 35.87%, 19.95%, 2.54% and 26.31%, respectively. The detection rates of 1 risk factor clustering, 2 risk factors clustering and more than 3 risk factors clustering were 29.21%, 16.17% and 9.36%, respectively. The difference in the detection rate of cardiovascular and metabolic risk factors in different youth stages was insignificant (P>0.05), the detection rate of risk factor aggregation of 0 was lower than that of the timely group and delayed group, and the detection rate of risk factors aggregation of 2 was higher than that of the timely group (P < 0.05).After adjusting the effects of learning stage, region, birth weight, feeding patterns, one-child, family income and the parents' educational levels, multivariate Logistic regression analysis showed that, compared with the on-time puberty group, the risk of 1 risk factor clustering, 2 risk factors clustering and more than 3 risk factors clustering increased by 1.94 times (95% CI=1.29-2.91), 2.97 times (95% CI=1.89-4.67) and 2.02 times (95% CI= 1.13-3.63) among the girls; It had not been found that the relationship between puberty timing and cardiovascular risk factor clustering among the boys (P>0.05). CONCLUSION: Premature puberty is an independent risk factor for the clustering of cardiometabolic risk factors in girls, and primary prevention strategies should be implemented to reduce the burden of cardiovascular metabolic diseases in the population.

A mica filter enables bacterial enrichment from large volumes of natural water for sensitive monitoring of pathogens by nanopore sequencing.

Nanopore sequencing is extremely promising for the high-throughput detection of pathogenic bacteria in natural water; these bacteria may be transmitted to humans and cause waterborne infectious diseases. However, the concentration of pathogenic bacteria in natural water is too low to be detected directly by nanopore sequencing. Herein, we developed a mica filter to enrich over 85% of bacteria from > 10 L of natural water in 100 min, which led to a 102-fold improvement in the assay limits of the MinION sequencer for assessing pathogenic bacteria. Correspondingly, the sequencing time of S. Typhi detection at a concentration as low as 105 CFU/L was reduced from traditional 48 h to 3 h. The bacterial adsorption followed pseudo-first-order kinetics and the successful adsorption of bacteria to the mica filter was confirmed by scanning electron microscopy and Fourier infrared spectroscopy et al. The mica filter remained applicable to a range of water samples whose quality parameters were within the EPA standard limits for freshwater water. The mica filter is thus an effective tool for the sensitive and rapid monitoring of pathogenic bacteria by nanopore sequencing, which can provide timely alerts for waterborne transmission events.

Emergence of colistin-resistant Stenotrophomonas maltophilia with high virulence in natural aquatic environments.

The presence of Stenotrophomonas maltophilia in aquatic environments poses great health risks to immunocompromised individuals because of its multidrug resistance and resultant high mortality. However, a significant gap exists in the isolation and understanding of colistin-resistant S. maltophilia in aquatic environments. In this study, nine colistin-resistant S. maltophilia strains isolated from natural lakes were explored, and their phylogenetic relationship, biofilm formation, virulence, and antibiotic resistance profiles and underlying genetic determinants were assessed. After genome analysis, besides known multi-locus sequence typing (MLST) of ST532, new assigned ST965 and ST966 which phylogenetically clustered into soil isolates were found firstly. All the isolates exhibited resistance to multiple antibiotics, including aminoglycosides, beta-lactams, tetracyclines, and even colistin, with the highest minimum inhibitory concentration (MIC) against colistin reaching 640 mg/L. Comparative genomic analysis revealed aph(3')-Iic, blaL1, tetT, phoP, mcr-3, arnA, pmrE, and efflux pump genes as the genetic determinants underlying this multidrug resistance. Notably, the biofilm-forming capacities of the newly discovered ST965 and ST966 isolates were significant stronger than those of the known ST532 isolates (p < 0.01), resulting in the death of over 50 % of the Galleria mellonella population within 1 day of injection. The ST965 isolates demonstrated the highest virulence against G. mellonella, followed by the ST966 isolates and ST532 isolates which was phylogenetically clustered with clinical isolates, indicating that the novel S. maltophilia strains of ST965 and ST966 may pose considerable health risks to humans. Our findings provide insights into colistin-resistant S. maltophilia in aquatic environments and raise concerns about the health risks posed by the newly assigned sequence types of colistin-resistant S. maltophilia with potential high virulence in natural aquatic environments.

TSAF-Net: a rotated two-stage Cnaphalocrocis medinalis damage detection method based on anchor-free arbitrary-oriented proposal network.

BACKGROUND: Cnaphalocrocis medinalis (C.medinalis) is an agricultural pest with recurrent outbreaks. The investigation into automated pest and disease detection technology holds significant value for in-field surveys. Current generic detection methods are inadequate due to arbitrary orientations and a wide range of aspect ratios in damage symptoms. To tackle these issues, we put forward a rotated two-stage detection method for in-field C.medinalis surveys. This method relies on an anchor-free rotated region proposal network (AF-R2PN), bypassing the need for hyper-parameter optimization induced by predefined anchor boxes. An in-field C.medinalis dataset is constructed during on-site pest surveys to validate the effectiveness of our method. RESULTS: The experimental results show that our method can accomplish 80% average precision (AP), surpassing the corresponding horizontal detector by 2.3%. The visualization results of our work showcase its exceptional localization capability over generic detection methods, facilitating inspection by plant protectors. Meanwhile, our proposed method outperforms other state-of-the-art rotated detection algorithms. The AF-R2PN module can generate superior arbitrary-oriented proposals even with a decreased number of proposals, balancing inference speed and detection performance among other rotated two-stage methods. CONCLUSION: The proposed method exhibits superiority in detecting C. medinalis damage under complex field conditions. It provides greater practical applicability during in-field surveys, enhancing their efficiency and coverage. The findings hold significance for pest and disease monitoring, providing important technical support for agricultural production. © 2024 Society of Chemical Industry.

Matching actions to needs: shifting policy responses to the changing health needs of Chinese children and adolescents.

China is home to the second largest population of children and adolescents in the world. Yet demographic shifts mean that the government must manage the challenge of fewer children with the needs of an ageing population, while considering the delicate tension between economic growth and environmental sustainability. We mapped the health problems and risks of contemporary school-aged children and adolescents in China against current national health policies. We involved multidisciplinary experts, including young people, with the aim of identifying actionable strategies and specific recommendations to promote child and adolescent health and wellbeing. Notwithstanding major improvements in their health over the past few decades, contemporary Chinese children and adolescents face distinct social challenges, including high academic pressures and youth unemployment, and new health concerns including obesity, mental health issues, and sexually transmitted infections. Inequality by gender, geography, and ethnicity remains a feature of health risks and outcomes. We identified a mismatch between current health determinants, risks and outcomes, and government policies. To promote the health of children and adolescents in China, we recommend a set of strategies that target government-led initiatives across the health, education, and community sectors, which aim to build supportive and responsive families, safe communities, and engaging and respectful learning environments. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Carbonaceous particulate matter promotes the horizontal transfer of antibiotic resistance genes.

There is growing concern about the transfer of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in airborne particulate matter. In this study, we investigated the effects of various types of carbonaceous particulate matter (CPM) on the transfer of ARGs in vitro. The results showed that CPM promoted the transfer of ARGs, which was related to the concentration and particle size. Compared with the control group, the transfer frequency was 95.5, 74.7, 65.4, 14.7, and 3.8 times higher in G (graphene), CB (carbon black), NGP (nanographite powder), GP1.6 (graphite powder 1.6 micron), and GP45 (graphite powder 45 micron) groups, respectively. Moreover, the transfer frequency gradually increased with the increase in CPM concentration, while there was a negative relationship between the CPM particle size and conjugative transfer frequency. In addition, the results showed that CPM could promote the transfer of ARGs by increasing ROS, as well as activating the SOS response and expression of conjugative transfer-related genes (trbBp, trfAp, korA, kroB, and trbA). These findings are indicative of the potential risk of CPM for the transfer of ARGs in the environment, enriching our understanding of environmental pollution and further raising awareness of environmental protection.

Comparative analysis of chlorine-resistant bacteria after chlorination and chloramination in drinking water treatment plants.

Chlorine-resistant bacteria (CRB) in drinking water treatment plants (DWTPs) jeopardize water quality and pose a potential risk to human health. However, the specific response of CRB to chlorination and chloramination remains uncharacterized. Therefore, we analyzed 16 S rRNA sequencing data from water samples before and after chlorination and chloramination taken between January and December 2020. Proteobacteria and Firmicutes dominated all finished water samples. After chloramination, Acinetobacter, Pseudomonas, Methylobacterium, Ralstonia, and Sphingomonas were the dominant CRB, whereas Ralstonia, Bacillus, Acinetobacter, Pseudomonas, and Enterococcus were prevalent after chlorination. Over 75% of the CRB e.g. Acinetobacter, Pseudomonas, Bacillus, and Enterococcus were shared between the chlorination and chloramination, involving potentially pathogens, such as Acinetobacter baumannii and Pseudomonas aeruginosa. Notably, certain genera such as Faecalibacterium, Geobacter, and Megasphaera were enriched as strong CRB after chloramination, whereas Vogesella, Flavobacterium, Thalassolituus, Pseudoalteromonas, and others were enriched after chlorination according to LEfSe analysis. The shared CRB correlated with temperature, pH, and turbidity, displaying a seasonal pattern with varying sensitivity to chlorination and chloramination in cold and warm seasons. These findings enhance our knowledge of the drinking water microbiome and microbial health risks, thus enabling better infectious disease control through enhanced disinfection strategies in DWTPs.

Promoting mental health in children and adolescents through digital technology: a systematic review and meta-analysis.

Background: The increasing prevalence of mental health issues among children and adolescents has prompted a growing number of researchers and practitioners to explore digital technology interventions, which offer convenience, diversity, and proven effectiveness in addressing such problems. However, the existing literature reveals a significant gap in comprehensive reviews that consolidate findings and discuss the potential of digital technologies in enhancing mental health. Methods: To clarify the latest research progress on digital technology to promote mental health in the past decade (2013-2023), we conducted two studies: a systematic review and meta-analysis. The systematic review is based on 59 empirical studies identified from three screening phases, with basic information, types of technologies, types of mental health issues as key points of analysis for synthesis and comparison. The meta-analysis is conducted with 10 qualified experimental studies to determine the overall effect size of digital technology interventions and possible moderating factors. Results: The results revealed that (1) there is an upward trend in relevant research, comprising mostly experimental and quasi-experimental designs; (2) the common mental health issues include depression, anxiety, bullying, lack of social emotional competence, and mental issues related to COVID-19; (3) among the various technological interventions, mobile applications (apps) have been used most frequently in the diagnosis and treatment of mental issues, followed by virtual reality, serious games, and telemedicine services; and (4) the meta-analysis results indicated that digital technology interventions have a moderate and significant effect size (g = 0.43) for promoting mental health. Conclusion: Based on these findings, this study provides guidance for future practice and research on the promotion of adolescent mental health through digital technology. Systematic review registration: https://inplasy.com/inplasy-2023-12-0004/, doi: 10.37766/inplasy2023.12.0004.

Two new bibenzyl methylglucosides as SIRT3 activators obtained through microbial transformation.

Microbial transformation of dihydroresveratrol (DHRSV) using Beauveria bassiana has produced two new methylglucosylated derivatives of DHRSV (1 and 2), whose structures were characterized as 4'-O-(4″-O-methyl-ß-D-glucopyranosyl)-dihydroresveratrol (4'-O-MG DHRSV, 1) and 3-O-(4″-O-methyl-ß-D-glucopyranosyl)-dihydroresveratrol (3-O-MG DHRSV, 2) on the basis of spectroscopic methods. They showed moderate SIRT3 agonistic activity, and compound 2 exhibited the best deacetylation of 406.63% at 10 µM. The activity of 2 increased by 3.12-fold compared with that of DHRSV, since 2 performed better in molecular docking assay (GScore -8.445).

Full-Length Transcriptome Sequencing Analysis and Characterization of WRKY Transcription Factors Responsive to Cadmium Stress in Arabis paniculata.

Arabis paniculata is a newly discovered hyperaccumulator known for its ability to accumulate multiple metals. WRKY proteins play a significant role in plant responses to various stresses, including cadmium (Cd) stress. However, there is limited research on the molecular biology of Arabis paniculata, especially regarding the WRKY family. In this study, we conducted third-generation sequencing for functional annotation and structural analysis of Arabis paniculata. We obtained 41,196 high-quality isoforms from the full-length transcriptome, with an average length of 1043 bp. A total of 26,670 genes were predicted against NR, Swissprot, KOG, and KEGG databases. Functional comparison using the KOG database revealed excellent annotation in 25 functional categories, with general function prediction (1822 items) being the most predominant. MISA analysis identified 12,593 SSR loci, with single nucleotide repeats being the largest category (44.83% of the total). Moreover, our predictions provide insights into 20,022 coding sequences (CDS), 811 transcription factors, and 17,963 LncRNAs. In total, 34 WRKY gene sequences were identified in Arabis paniculata. Bioinformatics analysis revealed diverse numbers of amino acids in these WRKYs (113 to 545 aa), and a conserved WRKYGQK sequence within the N-terminus of the WRKY protein. Furthermore, all WRKYs were found to be localized in the nucleus. Phylogenetic analysis classified the WRKY genes into three categories: I (14 members), II (17 members), and III (3 members). Category II was subsequently divided into four sub-categories: II-a (8 members), II-b (1 member), II-c (1 member), and II-d (7 members). Our quantitative real-time polymerase chain reaction (qRT-PCR) experiments revealed that ApWRKY23 and ApWRKY34 exhibited the highest expression levels at the 24-h time point, suggesting their potential role as the candidate genes for Cd stress response. These findings contribute to our understanding of the genomic information of Arabis paniculata and provide a basis for the analysis of its genetic diversity. Additionally, this study paves the way for a comprehensive exploration of the molecular mechanisms underlying the WRKY genes in Arabis paniculata under Cd stress conditions.

Feature Refinement Method Based on the Two-Stage Detection Framework for Similar Pest Detection in the Field.

Efficient pest identification and control is critical for ensuring food safety. Therefore, automatic detection of pests has high practical value for Integrated Pest Management (IPM). However, complex field environments and the similarity in appearance among pests can pose a significant challenge to the accurate identification of pests. In this paper, a feature refinement method designed for similar pest detection in the field based on the two-stage detection framework is proposed. Firstly, we designed a context feature enhancement module to enhance the feature expression ability of the network for different pests. Secondly, the adaptive feature fusion network was proposed to avoid the suboptimal problem of feature selection on a single scale. Finally, we designed a novel task separation network with different fusion features constructed for the classification task and the localization task. Our method was evaluated on the proposed dataset of similar pests named SimilarPest5 and achieved a mean average precision (mAP) of 72.7%, which was better than other advanced object detection methods.

Landscape of antibiotic resistance genes and bacterial communities in groundwater on the Tibetan Plateau, and distinguishing their difference with low-altitude counterparts.

Groundwater is a vital source of drinking water for Tibetans. Antibiotic resistance genes (ARGs) and bacterial communities in groundwater on the Tibetan Plateau remain unclear. Furthermore, the characterization of their differences between high-altitude and low-altitude groundwater is still unrevealed. Herein, 32 groundwater samples were collected on the plateau, and intra- and extracellular ARGs (iARGs and eARGs), and bacterial communities were characterised through qPCR assays to 19 ARGs and 16S rRNA sequencing. It showed top four abundant intra- and extracellular last-resort ARGs (LARGs) were blaOXA-48, mcr-1, vanA, and vanB, whereas dominant common ARGs (CARGs) were tetA and ermB, respectively. CARGs had higher abundances than LARGs, and iARGs were more frequently detected than eARGs. Proteobacteria, an invasive resident phylum, and Firmicutes dominated eDNA release. Network analysis revealed all observed LARGs co-occurred with pathogenic and non-pathogenic bacteria. Community diversity was significantly associated with longitude and elevation, while nitrate correlated with ARGs. Comparative analysis demonstrated eARG frequencies and abundances were higher at high altitudes than at low altitudes. Additionally, Acinetobacter and Pseudomonas specifically dominated at high altitudes. This study reveals the widespread prevalence of ARGs, particularly LARGs, in groundwater on the less-disturbed Tibetan Plateau and underlines the potential risks associated with the LARG-carrying bacteria. ENVIRONMENTAL IMPLICATION: Antibiotic resistance genes (ARGs), which are defined as emerging environmental contaminants, are becoming a global concern due to their ability to confer antibiotic resistance to pathogens. Our findings highlight the prevalence of ARGs, particularly LARGs, in groundwater on the Tibetan Plateau, and the possibility that naturally-occurring pathogenic and non-pathogenic bacteria carry multiple LARGs. In addition, we further reveal differences in the distribution of ARGs and bacterial community between high-altitude and low-altitude groundwater. Collectively, our findings offer an important insight into the potential public risks related to groundwater on the Tibetan Plateau.

The TabHLH094-TaMYC8 complex mediates the cadmium response in wheat.

In wheat, TaMYC8 is a negative regulator of cadmium (Cd)-responsive ethylene signaling. In this study, we functionally characterized TabHLH094, a basic helix-loop-helix (bHLH) transcription factor (TF) that inhibits the transcriptional activity of TaMYC8. The TabHLH094 protein was found in the nucleus of tobacco epidermal cells and exhibited transcriptional activation activity. Real-time quantitative PCR (RT-qPCR) indicated that TabHLH094 exhibited root-specific, Cd-responsive expression in wheat seedlings. Overexpression of TabHLH094 enhanced the tolerance of wheat seedlings to Cd exposure. The protein-protein interaction between TabHLH094 and TaMYC8 was verified by glutathione S-transferase (GST) pulldown, coimmunoprecipitation (Co-IP), yeast two-hybrid (Y2H), and bimolecular fluorescence complementation (BiFC) analyses. TabHLH094 was found to reduce the ability of TaMYC8 to bind to the TaERF6 promoter. Furthermore, TabHLH094 could also reduce aminocyclopropanecarboxylate oxidase (ACO) and ACC synthase (ACS) activities, both of which are necessary for ethylene biosynthesis. Taken together, these results indicate that TabHLH094 mediates Cd tolerance by regulating the transcriptional activity of TaMYC8 and decreasing ethylene production. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01404-1.

Predicting the Efficacy of Neoadjuvant Chemotherapy for Pancreatic Cancer Using Deep Learning of Contrast-Enhanced Ultrasound Videos.

Contrast-enhanced ultrasound (CEUS) is a promising imaging modality in predicting the efficacy of neoadjuvant chemotherapy for pancreatic cancer, a tumor with high mortality. In this study, we proposed a deep-learning-based strategy for analyzing CEUS videos to predict the prognosis of pancreatic cancer neoadjuvant chemotherapy. Pre-trained convolutional neural network (CNN) models were used for binary classification of the chemotherapy as effective or ineffective, with CEUS videos collected before chemotherapy as the model input, and with the efficacy after chemotherapy as the reference standard. We proposed two deep learning models. The first CNN model used videos of ultrasound (US) and CEUS (US+CEUS), while the second CNN model only used videos of selected regions of interest (ROIs) within CEUS (CEUS-ROI). A total of 38 patients with strict restriction of clinical factors were enrolled, with 76 original CEUS videos collected. After data augmentation, 760 and 720 videos were included for the two CNN models, respectively. Seventy-six-fold and 72-fold cross-validations were performed to validate the classification performance of the two CNN models. The areas under the curve were 0.892 and 0.908 for the two models. The accuracy, recall, precision and F1 score were 0.829, 0.759, 0.786, and 0.772 for the first model. Those were 0.864, 0.930, 0.866, and 0.897 for the second model. A total of 38.2% and 40.3% of the original videos could be clearly distinguished by the deep learning models when the naked eye made an inaccurate classification. This study is the first to demonstrate the feasibility and potential of deep learning models based on pre-chemotherapy CEUS videos in predicting the efficacy of neoadjuvant chemotherapy for pancreas cancer.

Spatial and temporal analysis of the seasonal dynamics of antibiotic resistance gene occurrence in recreational marine water.

People who engage in water sports in recreational marine water may be at high risk of exposure to hazardous antibiotic-resistant bacteria (ARB). However, information on the contribution of specific sources to ARB contamination in recreational marine water is still lacking. Here, we carried out monthly analyses of antibiotic resistance genes (ARGs), pathogenic bacteria and 16S rRNA sequencing data at the First Bathing Beach in Qingdao. The sampling sites were divided into four areas: swimming area, intermediate area, polluted area, and sewage outlet. Correlations between ARGs and bacterial communities among sampling sites were explored by spatial and temporal analysis. We found that all of 21 important ARG types were detected in the swimming area, with aadA (1.3 × 106 ± 2.7 × 106 genomic copies/L) and sul2 (4.3 × 105 ± 5.9 × 105 genomic copies/L) at the highest concentration. Most ARGs were detected at highest frequency and concentration in the sewage outlet and decreased from there to the swimming area. ARG correlation between these two areas was positive only in the cold season, suggesting that sewage was the main source of ARG pollution in the swimming area during that period. The ARGs ermA(1) and vanA were detected at highest frequency and concentration in the swimming area and were significantly correlated with the intestinal pathogen Enterococcus, which was more abundant here than in the surrounding areas during the warm season. Co-occurrence analysis of bacterial genera and ARGs showed that six genera were commonly correlated with ARGs in all sampling areas in the cold season, while none were found in the warm season. Our findings indicate that ARG pollution in the swimming area was also driven by sources other than sewage, especially in the warm season, which is the peak tourist season in Qingdao. These results provide a valuable basis for the implementation of effective strategies to control ARG risks in recreational waters.

CMRD-Net: a deep learning-based Cnaphalocrocis medinalis damage symptom rotated detection framework for in-field survey.

The damage symptoms of Cnaphalocrocis medinalis (C.medinalis) is an important evaluation index for pest prevention and control. However, due to various shapes, arbitrary-oriented directions and heavy overlaps of C.medinalis damage symptoms under complex field conditions, generic object detection methods based on horizontal bounding box cannot achieve satisfactory results. To address this problem, we develop a Cnaphalocrocis medinalis damage symptom rotated detection framework called CMRD-Net. It mainly consists of a Horizontal-to-Rotated region proposal network (H2R-RPN) and a Rotated-to-Rotated region convolutional neural network (R2R-RCNN). First, the H2R-RPN is utilized to extract rotated region proposals, combined with adaptive positive sample selection that solves the hard definition of positive samples caused by oriented instances. Second, the R2R-RCNN performs feature alignment based on rotated proposals, and exploits oriented-aligned features to detect the damage symptoms. The experimental results on our constructed dataset show that our proposed method outperforms those state-of-the-art rotated object detection algorithms achieving 73.7% average precision (AP). Additionally, the results demonstrate that our method is more suitable than horizontal detection methods for in-field survey of C.medinalis.

Effects of gender diversity on college students' collaborative learning: From individual gender to gender pairing.

This study investigated the effects of gender and gender pairing on behaviors and social interaction during collaborative learning in a blended learning environment. Three types of pairing (all-female, all-male, and mixed) were considered in an empirical study with 44 undergraduate students. The results revealed that, first, female students were more likely to perform well in listening, talking, and integrating during class, and in the quality of posts after class, whereas male students tended to engage more in irrelevant behavior in collaboration. Second, same-gender groups were more active in collaborative discussion, but all-male groups performed worst in quality of posts after class. Third, both male and female students were more active in same-gender groups than in mixed groups. Finally, same-gender groups tended to have greater interpersonal connectedness than mixed-gender groups. The paper ends with a list of practical implications for facilitating effective collaborative learning in co-educational college classrooms.

The role of pre-class and in-class behaviors in predicting learning performance and experience in flipped classrooms.

The flipped classroom is a well-recognized instructional approach that improves learning performance and experience through two sequential phases: pre-class preparation and in-class collaboration. Despite the large differences between the two phases, few studies have explored their separate effects on flipped learning. This study conducted a hierarchical linear regression to investigate how the two sequential phases and their featured behaviors can predict learning performance and experience in a flipped classroom at the undergraduate level. The results indicated that students' pre-class discussion positively predicted their assignment scores to a moderate degree, while the in-class collaboration was negatively correlated with test scores. However, the two phases had a limited impact on students' flipped learning experience. The results also highlight the influence of students' initial interest and prior achievement on their flipped learning experience. The findings can extend our understanding of the flipped classroom approach and inform its design and implementation in higher education contexts.