A transcription factor-mediated regulatory network controls fungal pathogen colonization of insect body cavities.

Successful host tissue colonization is crucial for fungal pathogens to cause mycosis and complete the infection cycle, in which fungal cells undergo a series of morphological transition-included cellular events to combat with hosts. However, many transcription factors (TFs) and their mediated networks regulating fungal pathogen colonization of host tissue are not well characterized. Here, a TF (BbHCR1)-mediated regulatory network was identified in an insect pathogenic fungus, Beauveria bassiana, that controlled insect hemocoel colonization. BbHCR1 was highly expressed in fungal cells after reaching insect hemocoel and controlled the yeast (in vivo blastospores)-to-hyphal morphological switch, evasion of immune defense response, and fungal virulence. Comparative analysis of RNA sequencing and chromatin immunoprecipitation sequencing identified a core set of BbHCR1 target genes during hemocoel colonization, in which abaA and brlA were targeted to limit the rapid switch from blastospores to hyphae and fungal virulence. Two targets encoding hypothetical proteins, HP1 and HP2, were activated and repressed by BbHCR1, respectively, which acted as a virulence factor and repressor, respectively, suggesting that BbHCR1 activated virulence factors but repressed virulence repressors during the colonization of insect hemocoel. BbHCR1 tuned the expression of two dominant hemocoel colonization-involved metabolite biosynthetic gene clusters, which linked its regulatory role in evasion of immune response. Those functions of BbHCR1 were found to be collaboratively regulated by Fus3- and Hog1-MAP kinases via phosphorylation. These findings have drawn a regulatory network in which Fus3- and Hog1-MAP kinases phosphorylate BbHCR1, which in turn controls the colonization of insect body cavities by regulating fungal morphological transition and virulence-implicated genes.IMPORTANCEFungal pathogens adopt a series of tactics for successful colonization in host tissues, which include morphological transition and the generation of toxic and immunosuppressive molecules. However, many transcription factors (TFs) and their linked pathways that regulate tissue colonization are not well characterized. Here, we identified a TF (BbHCR1)-mediated regulatory network that controls the insect fungal pathogen, Beauveria bassiana, colonization of insect hemocoel. During these processes, BbHCR1 targeted the fungal central development pathway for the control of yeast (blastospores)-to-hyphae morphological transition, activated virulence factors, repressed virulence repressors, and tuned the expression of two dominant hemocoel colonization-involved immunosuppressive and immunostimulatory metabolite biosynthetic gene clusters. The BbHCR1 regulatory function was governed by Fus3- and Hog1-MAP kinases. These findings led to a new regulatory network composed of Fus3- and Hog1-MAP kinases and BbHCR1 that control insect body cavity colonization by regulating fungal morphological transition and virulence-implicated genes.

Comparative in vitro toxicological effects of water-soluble and insoluble components of atmospheric PM2.5 on human lung cells.

Fine particulates in city air significantly impact human health, but the hazardous compositional mechanisms are still unclear. Besides the toxicity of environmental PM2.5 to in vitro human lung epithelial cells (A549), the independent cytotoxicity of PM2.5-bound water-soluble (WS-PM2.5) and water-insoluble (WIS-PM2.5) fractions were also compared by cell viability, oxidative stress (reactive oxygen species, ROS), and inflammatory injury (IL-6 and TNF-α). The cytotoxicity of PM2.5 varied significantly by sampling season and place, with degrees greater in winter and spring than in summer and autumn, related to corresponding trend of air PM2.5 level, and also higher in industrial than urban site, although their PM2.5 pollution levels were comparable. The PM2.5 bound metals (Ni, Cr, Fe, and Mn) may contribute to cellular injury. Both WS-PM2.5 and WIS-PM2.5 posed significant cytotoxicity, that WS-PM2.5 was more harmful than WIS-PM2.5 in terms of decreasing cell viability and increasing inflammatory cytokines production. In particular, industrial samples were usually more toxic than urban samples, and those from summer were generally less toxic than other seasons. Hence, in order to mitigate the health risks of PM2.5 pollution, the crucial targets might be components of heavy metals and soluble fractions, and sources in industrial areas, especially during the cold seasons.

Effects of micro-nano plastics on the environmental biogeochemical cycle of nitrogen: A comprehensive review.

Micro-nano plastics (MNPs; size <5 mm), ubiquitous and emerging pollutants, accumulated in the natural environment through various sources, and are likely to interact with nutrients, thereby influencing their biogeochemical cycle. Increasing scientific evidences reveal that MNPs can affect nitrogen (N) cycle processes by affecting biotopes and organisms in the environmental matrix and MNPs biofilms, thus plays a crucial role in nitrous oxide (N2O) and ammonia (NH3) emission. Yet, the mechanism and key processes behind this have not been systematically reviewed in natural environments. In this review, we systematically summarize the effects of MNPs on N transformation in terrestrial, aquatic, and atmospheric ecosystems. The effects of MNPs properties on N content, composition, and function of the microbial community, enzyme activity, gene abundance and plant N uptake in different environmental conditions has been briefly discussed. The review highlights the significant potential of MNPs to alter the properties of the environmental matrix, microbes and plant or animal physiology, resulting in changes in N uptake and metabolic efficiency in plants, thereby inhibiting organic nitrogen (ON) formation and reducing N bioavailability, or altering NH3 emissions from animal sources. The faster the decomposition of plastics, the more intense the perturbation of MNPs to organisms in the natural ecosystem. Findings of this provide a more comprehensive analysis and research directions to the environmentalists, policy makers, water resources planners & managers, biologists, and biotechnologists to do integrate approaches to reach the practical engineering solutions which will further diminish the long-term ecological and climatic risks.

Tetracycline and sulfadiazine toxicity in human liver cells Huh-7.

As typical antibiotics, tetracycline (TC) and sulfadiazine (SDZ) enter the human body through the food chain. Therefore, it is necessary to understand their individual and combined toxicity. In this study, the effects of TC, SDZ, and their mixture on cell viability, cell membrane damage, liver cell damage, and oxidative damage were evaluated in in vitro assays with human liver cells Huh-7. The results showed cytotoxicity of TC, SDZ, and their mixture, which induced oxidative stress and caused membrane and cell damage. The effect of antibiotics on Huh-7 cells increased with increasing concentration, except for lactate dehydrogenase (LDH) activity that commonly showed a threshold concentration response and cell viability, which commonly showed a biphasic trend, suggesting the possibility of hormetic responses where proper doses are included. The toxicity of TC was commonly higher than that of SDZ when applied at the same concentration. These findings shed light on the individual and joint effects of these major antibiotics on liver cells, providing a scientific basis for the evaluation of antibiotic toxicity and associated risks.

Infant crying predicts real-time fluctuations in maternal mental health in ecologically valid home settings.

Exposure to infant crying is a well-established predictor of mothers' mental health. However, this association may reflect many potential mechanisms. Capturing dynamic fluctuations in mothers' states simultaneously with caregiving experiences is necessary to identify the real-time processes influencing mental health. In this study, we leveraged ecological momentary assessments (EMAs) and infant-worn audio recorders to capture variability in mothers' mental health symptoms and their exposure to infant crying over one week in a racially and socio-economically diverse urban North-American sample (N = 53). We use multilevel modeling to characterize within- and between-person effects of crying on maternal negative affect and symptoms of depression and anxiety. Within participants, when infants cried more than average in the 10 min, 1 hr, and 8 hr prior to an EMA report, mothers' negative affect subsequently increased, controlling for mean levels of infant crying. In contrast to findings from laboratory studies, in everyday settings crying exposure did not immediately increase feelings of depression. Only when crying was above average for 8 hr prior to EMA did mothers report increases in subsequent depression symptoms, suggesting that the effects of crying on maternal mental health take hours to unfold in ecologically valid home settings. Between participants, mothers of infants who cried more on average did not report higher negative affect or symptoms of depression or anxiety. Overall, our findings reveal that crying exposure dynamically influences maternal negative affect and depression but not anxiety in ecologically valid real-world settings. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Validating a model to detect infant crying from naturalistic audio.

Human infant crying evolved as a signal to elicit parental care and actively influences caregiving behaviors as well as infant-caregiver interactions. Automated cry detection algorithms have become more popular in recent decades, and while some models exist, they have not been evaluated thoroughly on daylong naturalistic audio recordings. Here, we validate a novel deep learning cry detection model by testing it in assessment scenarios important to developmental researchers. We also evaluate the deep learning model's performance relative to LENA's cry classifier, one of the most commonly used commercial software systems for quantifying child crying. Broadly, we found that both deep learning and LENA model outputs showed convergent validity with human annotations of infant crying. However, the deep learning model had substantially higher accuracy metrics (recall, F1, kappa) and stronger correlations with human annotations at all timescales tested (24 h, 1 h, and 5 min) relative to LENA. On average, LENA underestimated infant crying by 50 min every 24 h relative to human annotations and the deep learning model. Additionally, daily infant crying times detected by both automated models were lower than parent-report estimates in the literature. We provide recommendations and solutions for leveraging automated algorithms to detect infant crying in the home and make our training data and model code open source and publicly available.

INFANT CRYING DETECTION IN REAL-WORLD ENVIRONMENTS.

Most existing cry detection models have been tested with data collected in controlled settings. Thus, the extent to which they generalize to noisy and lived environments is unclear. In this paper, we evaluate several established machine learning approaches including a model leveraging both deep spectrum and acoustic features. This model was able to recognize crying events with F1 score 0.613 (Precision: 0.672, Recall: 0.552), showing improved external validity over existing methods at cry detection in everyday real-world settings. As part of our evaluation, we collect and annotate a novel dataset of infant crying compiled from over 780 hours of labeled real-world audio data, captured via recorders worn by infants in their homes, which we make publicly available. Our findings confirm that a cry detection model trained on in-lab data underperforms when presented with real-world data (in-lab test F1: 0.656, real-world test F1: 0.236), highlighting the value of our new dataset and model.

Relationships between soil respiration and hyperspectral vegetation indexes and crop characteristics under different warming and straw application modes.

Examining the relationship between seasonal variations in soil respiration and abiotic factors and vegetation indexes is crucial for modeling soil respiration using upscaled remote sensing satellite data. A field experiment including control (CK), warming (WA), straw application (SA), and warming and straw application (WASA) treatments was performed in a winter wheat-soybean rotation cropland on the north shore of the lower reaches of the Yangtze River. Soil respiration, abiotic factors, crop hyperspectral vegetation indexes, leaf area index (LAI), and chlorophyll content (represented as the SPAD value) were measured during the 2018-2020 rotation growing seasons. The results indicated that the mean annual soil respiration was 2.27 ± 0.04, 3.08 ± 0.06, 3.64 ± 0.08, and 3.95 ± 0.20 µmol m-2 s-1 in the CK, WA, SA, and WASA plots, respectively, during the 2-year experimental period. Soil respiration was significantly (P < 0.05) correlated with soil temperature, soil moisture, hyperspectral vegetation indexes, LAI, and SPAD value in all plots. Models that included temperature, moisture, hyperspectral vegetation indexes, LAI, and SPAD value explained 50.5-74.7% of the seasonal variation in soil respiration in the CK, WA, SA, and WASA plots during the 2-year experimental period. A model including the seasonal mean NDVI, DVI, EVI, PRI, and LAI explained 72.4% of the interseasonal and intertreatment variations in seasonal mean soil respiration in the different plots across the four different crop-growing seasons. Our study indicated the potential applicability of hyperspectral vegetation indexes, LAI, and SPAD value to the estimation of soil respiration at a regional scale.

Degradation of phenanthrene and fluoranthene in a slurry bioreactor using free and Ca-alginate-immobilized Sphingomonas pseudosanguinis and Pseudomonas stutzeri bacteria.

Biodegradation studies of three- and four-ring polycyclic aromatic hydrocarbons (PAHs) (phenanthrene [PHE] and fluoranthene [FLU]) were conducted using free and Ca-alginate-immobilized Sphingomonas pseudosanguinis strain J1-q (S1) and Pseudomonas stutzeri strain (S2) in bench-scale sediment slurry reactors. In this study, the effects of sodium alginate (SA) dosage on the characteristics of immobilized bacterial beads were investigated. The results indicated a 3% alginate concentration was optimal for immobilizing bacteria for PHE and FLU degradation. Scanning electron microscopy (SEM) images of the immobilized beads showed the presence of honeycomb structures and abundant interstices in the beads, which provided adequate space for microorganism adhesion and proliferation. The biodegradation of PHE and FLU using both free and immobilized bacteria fit a first-order reaction model well. The degradation efficiencies of PHE and FLU using immobilized bacteria were higher than those of free bacteria in sediment slurry reactors. The removal percentages of PHE and FLU using immobilized indigenous bacteria strain S1 after 42 d were 63.16% and 56.94%, respectively, which were higher than the removal percentages of exogenous strain S2.

Automated Detection of Infant Holding Using Wearable Sensing: Implications for Developmental Science And Intervention.

Physical contact is critical for children's physical and emotional growth and well-being. Previous studies of physical contact are limited to relatively short periods of direct observation and self-report methods. These methods limit researchers' understanding of the natural variation in physical contact across families, and its specific impacts on child development. In this study we develop a mobile sensing platform that can provide objective, unobtrusive, and continuous measurements of physical contact in naturalistic home interactions. Using commercially available motion detectors, our model reaches an accuracy of 0.870 (std: 0.059) for a second-by-second binary classification of holding. In addition, we detail five assessment scenarios applicable to the development of activity recognition models for social science research, where required accuracy may vary as a function of the intended use. Finally, we propose a grand vision for leveraging mobile sensors to access high-density markers of multiple determinants of early parent-child interactions, with implications for basic science and intervention.

Effect of Tenax addition amount and desorption time on desorption behaviour for bioavailability prediction of polycyclic aromatic hydrocarbons.

In this work, Tenax consecutive extractions of polycyclic aromatic hydrocarbons (PAHs) were conducted in two spiked sediments to investigate the influence of different Tenax addition amounts and desorption times on the rapidly desorbing fraction of PAHs, and to determine a reliable method for estimating PAHs bioavailability. The results indicated that a large Tenax addition amount has a positive effect on the desorption of PAHs from sediments. The desorption amounts of target PAHs compounds (3-ring phenanthrene and 4-ring fluoranthene) increased as the Tenax: sediment ratios increased from 0.25 to 2 in two spiked sediments. The highest desorption percentages of phenanthrene and fluoranthene were 48.91% and 34.70% for Jialing industrial park sediment, and 43.36% and 33.24% for Huanghuayuan bridge sediment, respectively. The results of desorption kinetics were suitably fitted with first order three-compartment model to estimate the rapidly desorbing fraction, Moreover, the Tenax: sediment ratio of 1 and desorption time of 24 h were found to be suitable for the desorption of phenanthrene and fluoranthene from sediments. The PAHs in sediments were biodegraded well by the bacterial strain J1-q. Comparing the maximum biodegraded amount of target PAHs in 30 days and the desorbed fraction over 400 h, the results showed that Tenax had better correlation with the high molecular weight fluoranthene than with the low molecular weight phenanthrene.