Empirical analysis of lead neurotoxicity mode of action and its application in health risk assessment.

The mode of action (MOA) framework is proposed to inform a biological link between chemical exposures and adverse health effects. Despite a significant increase in knowledge and awareness, the application of MOA in human health risk assessment (RA) remains limited. This study aims to discuss the adoption of MOA for health RA within a regulatory context, taking our previously proposed but not yet validated MOA for lead neurotoxicity as an example. We first conducted a quantitative weight of evidence (qWOE) assessment, which revealed that the MOA has a moderate confidence. Then, targeted bioassays were performed within an in vitro blood-brain barrier (BBB) model to quantitatively validate the scientific validity of key events (KEs) in terms of essentiality and concordance of empirical support (dose/temporal concordance), which increases confidence in utilizing the MOA for RA. Building upon the quantitative validation data, we further conducted benchmark dose (BMD) analysis to map dose-response relationships for the critical toxicity pathways, and the lower limit of BMD at a 5% response (BMDL5) was identified as the point of departure (POD) value for adverse health effects. Notably, perturbation of the Aryl Hydrocarbon Receptor (AHR) signaling pathway exhibited the lowest POD value, measured at 0.0062 µM. Considering bioavailability, we further calculated a provisional health-based guidance value (HBGV) for children's lead intake, determining it to be 2.56 µg/day. Finally, the health risk associated with the HBGV was assessed using the hazard quotient (HQ) approach, which indicated that the HBGV established in this study is a relative safe reference value for lead intake. In summary, our study described the procedure for utilizing MOA in health RA and set an example for MOA-based human health risk regulation.

Shallow groundwater table fluctuations promote the accumulation and loss of phosphorus from surface soil to deeper soil in croplands around plateau lakes in Southwest China.

The continuous excessive application of phosphorus (P) fertilizers in intensive agricultural production leads to a large accumulation of P in surface soils, increasing the risk of soil P loss by runoff and leaching. However, there are few studies on the accumulation and loss of P from surface soil to deep soil profiles driven by shallow groundwater table (SGT) fluctuations. This study used the intensive cropland around 7 plateau lakes in Yunnan Province as an example and conducted in situ monitoring of P storage in the soil profile and SGT during the rainy season (RS) and dry season (DS) as well as simulation experiments on soil P loss. The aim was to study the spatiotemporal variation in P accumulation in the soil profile of cropland driven by SGT fluctuations in the RS and DS and estimate the P loss in the soil profile driven by SGT fluctuations. The results showed that fluctuations in the SGT promoted P accumulation from the surface soil to deeper soil. The proportions of P stored in various forms in the 30-60 cm and 60-100 cm soil layers in the RS were greater than those in the DS, while the average proportion in the 0-30 cm soil layer in the DS was as high as 48%. Compared with those in the DS, the maximum decreases in the proportion of P stored as TP and Olsen-P in the 0-100 cm soil layer in the RS were 16% and 58%, respectively, due to the rise in the SGT (SGT <30 cm), while the soil TP storage decreased by only 1% when the SGT was maintained at 60-100 cm. The critical thresholds for soil Olsen-P and TP gradually decreased with increasing soil depth, and the risk of P loss in deeper soil increased. The loss of soil P was increased by fluctuations in the SGT. Based on the cropland area around the 7 plateau lakes, P storage, and SGT fluctuations, the average loss intensity and loss amount of TP in the 0-100 cm soil layer around the 7 plateau lakes were estimated to be 25 kg/ha and 56 t, respectively. Therefore, reducing exogenous P inputs, improving soil endogenous P utilization efficiency and maintaining deep soil P retention are the basic strategies for preventing and controlling P accumulation and loss in deep soil caused by SGT fluctuations.

Neonatal DEX exposure leads to hyperanxious and depressive-like behaviors as well as a persistent reduction of BDNF expression in developmental stages.

Brain-derived neurotrophic factor (BDNF), which regulates the neuronal survival, differentiation and synaptic plasticity, has been proved to play a critical role in the pathology and treatment of several psychiatric disorders including depression. Dexamethaone (DEX) is indicated for a number of conditions in perinatal medicine, however, the long-term impact of early-life DEX exposure on BDNF expression in hippocampus remains unknown. Here we found that neonatal DEX(ND) exposure leads to insignificant change of BDNF expression levels in the adulthood, albeit increased hyperanxious and depressive-like behaviors. However, the bdnf mRNA and BDNF protein levels were significantly reduced in all the hippocampal subregions during the developmental stages, including the perinatal period and puberty. We conclude that early life DEX exposure leads to a persistent disturbance of BDNF signaling during the developmental stages, which might be associated with the life-long impairment of hippocampal function.

N1 and LNC Reveal the Differential Electrophysiological Signatures of Functional and Hedonic Images Processing.

In the process of creative sentence or phrase utilization, novel and appropriate evaluations cause the different brain responses observed in event-related potentials: the N400 reflects the novelty evaluation, whereas a late negative component marks appropriate processing. Do we have similar brain reactions in image perception when we rapidly browse pictures of objects with different novelty, functional/appropriate, and hedonic value? To explore this question, participants were presented with four novel object images with high or low functional and hedonic properties, as well as the ordinary product images, with the instruction to attentively observe and understand each image. We found a clear dissociation between processing of novelty and functional value: novelty objects produced negative deflections in the N2-N400 time window relative to the ordinary object images, whereas images with high functional value elicited a larger N2 and late negative waves (LNC) resembling the late component found for the appropriate phrases. Object images with high hedonic value, however, were associated with earlier aesthetic preference reflected in smaller N1 amplitudes, but failed to elicit a LNC effect. We therefore conclude that the processing of novelty, functional, and hedonic value are dissociation, and the perception of hedonic value is earlier (N1) than the novelty processing (N400) and the verification of functional value (LNC).

Co-exposure of petrochemical workers to noise and mixture of benzene, toluene, ethylbenzene, xylene, and styrene: Impact on mild renal impairment and interaction.

Epidemiological evidence concerning effects of simultaneous exposure to noise and benzene, toluene, ethylbenzene, xylene, and styrene (BTEXS) on renal function remains uncertain. In 2020, a cross-sectional study was conducted among 1160 petrochemical workers in southern China to investigate effects of their co-exposure on estimated glomerular filtration rate (eGFR) and mild renal impairment (MRI). Noise levels were assessed using cumulative noise exposure (CNE). Urinary biomarkers for BTEXS were quantified. We found the majority of workers had exposure levels to noise and BTEXS below China's occupational exposure limits. CNE, trans, trans-muconic acid (tt-MA), and the sum of mandelic acid and phenylglyoxylic acid (PGMA) were linearly associated with decreased eGFR and increased MRI risk. We observed U-shaped associations for both N-acetyl-S-phenyl-L-cysteine (SPMA) and o-methylhippuric acid (2-MHA) with MRI. In further assessing the joint effect of BTEXS (ß, -0.164 [95% CI, -0.296 to -0.033]) per quartile increase in all BTEXS metabolites on eGFR using quantile g-computation models, we found SPMA, tt-MA, 2-MHA, and PGMA played pivotal roles. Additionally, the risk of MRI associated with tt-MA was more pronounced in workers with lower CNE levels (P = 0.004). Multiplicative interaction analysis revealed antagonisms of CNE and PGMA on MRI risk (P = 0.034). Thus, our findings reveal negative dose-effect associations between noise and BTEXS mixture exposure and renal function in petrochemical workers. With the exception of toluene, benzene, xylene, ethylbenzene, and styrene are all concerning pollutants for renal dysfunction. Effects of benzene, ethylbenzene, and styrene exposure on renal dysfunction were more pronounced in workers with lower CNE.

8-OHdG mediates the association of co-exposure to fifty-five typical endocrine-disrupting chemicals with renal function: a cross-section investigation in Southern Chinese adults.

Individual typical endocrine-disrupting chemicals (EDCs), including organophosphate triesters (OPEs), parabens, triclosan (TCS), bisphenols, benzophenones (BPs), phthalates (PAEs), and synthetic phenolic antioxidants (SPAs), are associated with renal dysfunction. However, the combined effects and underlying mechanisms of mixed EDC exposure on renal function remain unclear. Two hundred ninety-nine adult participants were enrolled in the cross-sectional survey conducted in Guangzhou, China. Urinary levels of 7 OPEs, 6 parabens, TCS, 14 bisphenols, 8 BPs, 15 PAEs, 4 SPAs, and 8-hydroxy-2'-deoxyguanosine (8-OHdG) were determined, and estimated glomerular filtration rate (eGFR) was served as the outcome index. We found elevated levels of diphenyl phosphate (DPP), bisphenol A (BPA), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), and mono-butyl phthalate (MBP) showed dose-responsive associations with eGFR decline, However, nonlinear associations were observed for bis(2-butoxyethyl) hydrogen phosphate (BBOEP), TCS, 4-hydroxybenzophenone (HBP), mono-n-pentyl phthalate (MnPP), and mono-benzyl phthalate (MBzP). The quantile-based g-computation model demonstrated that a quartile increase in the EDC mixture corresponded to a 0.383-SD decrease (95% CI - 0.658 ~ - 0.108, P = 0.007) in eGFR. Notably, BPA was identified as the primary contributor to this effect. Moreover, 8-OHdG mediated the eGFR decline associated with EDC mixtures with a mediation proportion of 25.49%. A sex-modified effect was also observed (P = 0.004), indicating that exposure to the mixture of EDC was linked to more pronounced renal dysfunction in females. Our novel findings suggest that exposure to a typical mixture of EDCs is associated with renal dysfunction in the general adult population of Southern China. Furthermore, 8-OHdG may play a role in the pathogenesis of EDC mixture-related renal dysfunction.

Prediction of phosphorus concentrations in shallow groundwater in intensive agricultural regions based on machine learning.

Excessive accumulation of phosphorus in soil profiles has become the main source of phosphorus in groundwater due to the application of phosphorus fertilizers in intensive agricultural regions (IARs). Elevated phosphorus concentrations in groundwater have become a global phenomenon, which places enormous pressure on the safe use of water resources and the safety of the aquatic environment. Currently, the prediction of pollutant concentrations in groundwater mainly focuses on nitrate nitrogen, while research on phosphorus prediction is limited. Taking the IARs approximately 8 plateau lakes in the Yunnan-Guizhou Plateau as an example, 570 shallow groundwater samples and 28 predictor variables were collected and measured, and a machine learning approach was used to predict phosphorus concentrations in groundwater. The performance of three machine learning algorithms and different sets of variables for predicting phosphorus concentrations in shallow groundwater was evaluated. The results showed that after all variables were introduced into the model, the R2, RMSE and MAE of support vector machine (SVM), random forest (RF) and neural network (NN) were 0.52-0.60, 0.101-0.108 and 0.074-0.081, respectively. Among them, the SVM model had the best prediction effect. The clay content and water-soluble phosphorus in soil and soluble organic carbon in groundwater had a high contribution to the prediction accuracy of the model. The prediction accuracy of the model with reduced number of variables showed that when the number of variables was equal to 6, the RF model had R2, RMSE and MAE values of 0.53, 0.108 and 0.074, respectively, and the number of variables increased again; there were small changes in R2, RMSE and MAE. Compared with the SVM and NN models, the RF model can achieve higher accuracy by inputting fewer variables.

Effects of coexposure to noise and mixture of toluene, ethylbenzene, xylene, and styrene (TEXS) on hearing loss in petrochemical workers of southern China.

Many harmful factors existing simultaneously with noise are reported to induce hearing impairment, such as organic solvents. However, the existing hearing safety limits and current risk assessment for hearing loss rely on single noise exposure. It is urgent to clarify the combined effect of noise and other harmful factors on hearing loss. Petrochemical workers are always exposed to noise and organic solvents, mainly benzene, toluene, ethylbenzene, xylene, and styrene (BTEXS), while the combined effect of their coexposure on hearing remains unclear. Herein we conducted a cross-sectional survey, measuring pure-tone audiometry of 1496 petrochemical workers in southern China. Participants exposed to BTEXS were 569, 524, 156, 452, and 177 respectively. Individual cumulative noise exposure (CNE) levels and BTEXS exposure were assessed. The average CNE was 93.27 ± 4.92 dB(A)·years, and the concentrations of BTEXS were far below the occupational exposure limits of China. Logistic regression analyses showed that CNE was consistently positively associated with hearing loss (HL) and high-frequency hearing loss (HFHL) but not related to speech-frequency hearing loss (SFHL). Compared with participants in the lowest quartile of CNE, those in the highest quartile showed an OR of 5.229 (95% CI: 3.179, 8.598) for HFHL. Two-pollutant model analysis indicated that TEXS exposure was positively associated with HL (OR 1.679, 95%CI 1.086, 2.597), SFHL (OR 2.440, 95%CI 1.255, 4.744), and HFHL (OR 1.475, 95%CI 1.077, 2.020). However, no interactions were observed between CNE and TEXS coexposure on hearing loss. In our study, covariates including smoking and drinking status, body mass index (BMI), ear protection and personal protective equipment, and use of earphone/headphone were adjusted. In conclusion, coexposure to noise and low-level TEXS could induce more severe damage on hearing function than exposure to each alone, especially SFHL. Therefore, petrochemical workers simultaneously exposed to noise and TEXS, even at low-level, should be included in hearing protection programs.

[Identification of Nitrate Source and Transformation Process in Shallow Groundwater Around Dianchi Lake].

Elucidating the main sources and transformation process of nitrate for the prevention and control of groundwater nitrogen pollution and the development and utilization of groundwater resources has great significance. To explore the current situation and source of nitrate pollution in shallow groundwater around the Dianchi Lake, 73 shallow groundwater samples were collected in the rainy season in 2020(October) and dry season in 2021(April). Using the hydrochemistry and nitrogen and oxygen isotopes(δ15N-NO3- and δ18O-NO3-), the spatial distribution, source, and transformation process of nitrate in shallow groundwater were identified. The contribution of nitrogen from different sources to nitrate in shallow groundwater was quantitatively evaluated using the isotope mixing model(SIAR). The results showed that in nearly 40.5% of sampling points in the shallow groundwater in the dry season, ρ(NO3--N) exceeded the 20 mg·L-1 specified in the Class Ⅲ water quality standard for groundwater(GB/T 14848), and in more than 47.2% of sampling points in the rainy season, ρ (NO3--N) exceeded 20 mg·L-1. The analysis results of nitrogen and oxygen isotopes and SIAR model showed that soil organic nitrogen, chemical fertilizer nitrogen, and manure and sewage nitrogen were the main sources of nitrate in shallow groundwater; these nitrogen sources contributed 13.9%, 11.8%, and 66.5% to nitrate in shallow groundwater in the dry season and 33.7%, 31.1%, and 25.9% in the rainy season, respectively. However, the contribution rate of atmospheric nitrogen deposition was only 8.5%, which contributed little to the source of nitrate in shallow groundwater in the study area. Nitrification was the leading process of nitrate transformation in shallow groundwater in the dry season, denitrification was the dominant process in the rainy season, and denitrification was more noticeable in the rainy season than that in the dry season.

Relational integration predicted numerical inductive reasoning: ERP Evidence from the N400 and LNC.

As relational integration performance can be used to predict reasoning ability, the present study aimed to provide electrophysiological evidence for numerical inductive reasoning. Number series with two levels of relational complexity were utilized, including simple and hierarchical problems (such as "15-16-17" versus "15-16-18"). Two tasks were adopted: a relational integration task that required to determine whether the numerical relations were changed across numbers; a number series task that required to determine whether a hidden rule was acquired (Experiment 1) or to predict the subsequent number (Experiment 2), whose phases were divided as rule searching, rule discovery, and rule following. The event-related potential (ERP) results of both experiments indicated that, in contrast to simple problems, hierarchical problems triggered enhanced N400 and late negative component (LNC), reflecting numerical fact retrieval, and generalizing novel hypotheses about the hidden rules by integrating adjacent numerical relations, respectively; relational integration showed similar N400 and LNC activation patterns to rule discovery (Experiment 1) or rule searching (Experiment 2). Additionally, the N400 and LNC elicited by relational integration showed strong positive correlations and even were able to predict the ones triggered by rule discovery (Experiment 1) or rule searching (Experiment 2). Therefore, the results supported the role of relational integration in numerical inductive reasoning and thereby in intelligence.

[Shallow Groundwater Around Plateau Lakes: Spatiotemporal Distribution of Nitrogen and Its Driving Factors].

Shallow groundwater around plateau lakes is one of the important sources of production and potable water. Shallow groundwater NO3--N pollution driven by factors such as surface nitrogen input load, rainfall, and irrigation is serious and threatens the water quality of plateau lakes. In order to identify the characteristics of nitrogen pollution and its driving factors in shallow groundwater, 463 shallow groundwater samples were collected from wells in farmland and residential areas around eight plateau lakes of Yunnan in the rainy and dry seasons in 2020 and 2021. The results showed that the average values of ρ(TN), ρ(NO3--N), ρ(ON), and ρ(NH4+-N) in shallow groundwater were 24.35, 15.15, 8.41, and 0.79 mg·L-1, respectively. Nearly 32% of the shallow groundwater samples around the eight lakes failed to meet the groundwater Class Ⅲ water quality requirements (GB/T 14848) of 20 mg·L-1 for NO3--N. Among them, the NO3--N concentration in the shallow groundwater around Erhai Lake, Qiluhu Lake, and Dianchi Lake had the highest rate of exceeding the standard, followed by that around Xingyunhu Lake, Yangzonghai Lake, Yilonghu Lake, Fuxianhu Lake, and Chenghai Lake as the smallest. Land use and seasonal changes affected the concentration and composition of various forms of nitrogen in shallow groundwater. The concentration of various forms of nitrogen in shallow groundwater in the farmland area was higher than that in the residential area. The nitrogen concentration in shallow groundwater in farmland was higher than that in residential areas. Except for NH4+-N, the concentration of various forms of nitrogen in shallow groundwater in the rainy season was higher than that in the dry season. NO3--N was the main nitrogen form in shallow groundwater; the fraction of TN was 57%-68%, and the fraction of ON was 27%-38%. The EC, DO, ORP, and T in shallow groundwater were the key factors reflecting or affecting the concentration of various forms of nitrogen in shallow groundwater, whereas soil factors had a weak impact on the concentration of various forms of nitrogen in shallow groundwater.

[Shallow Groundwater Around Plateau Lakes: Spatiotemporal Distribution of Phosphorus and Its Driving Factors].

The extensive application of phosphorus fertilizers to croplands and the aggregation of towns and villages around plateau lakes has resulted in the continuous accumulation of phosphorus in the soil profile and the discharge of phosphorus pollutants, which causes phosphorus pollution in shallow groundwater around the lakes. The phosphorus entering the lake with shallow underground runoff in the region around the lake also affects the water quality safety of plateau lakes. The spatiotemporal differences in phosphorus concentrations in 452 shallow groundwater samples and the driving factors were analyzed by monitoring wells in croplands and residential areas around the eight lakes in Yunnan province during the rainy and dry seasons from 2019 to 2021. The results showed that seasonal changes and land use influenced phosphorus concentrations and their composition in shallow groundwater. The concentration of phosphorus in shallow groundwater in the rainy season was higher than that in the dry season, and it was also greater in cropland than that in residential areas. DTP was the dominant form of TP, accounting for 75%-81%, and DIP was the dominant form of DTP, accounting for 74%-80%. Nearly 30% of the samples around the eight lakes had TP concentrations exceeding the surface water Class Ⅲ standard (GB 3838); the exceeded rates of phosphorus in groundwater around the Erhai Lake (52%), Qiluhu Lake (45%), Xingyun Lake (42%), and Dianchi Lake (29%) were far higher than those of Yangzonghai Lake (16%), Fuxianhu Lake (13%), Chenghai Lake (6%), and Yilonghu Lake (5%). The key driving factors of phosphorus concentrations in shallow groundwater were water-soluble phosphorus (WEP), water content (MWC), soil organic matter (SOM), total nitrogen (TN), pH in the soil profile, and pH and groundwater level in the shallow groundwater (P<0.05). The increases in WEP, SOM, TN, and MWC in the soil and pH in groundwater significantly increased the concentrations of DIP and DTP in shallow groundwater, whereas the decrease in groundwater level significantly reduced the concentrations of DTP and DIP in the groundwater.

Extensively chaotic motion in electrostatically driven nanowires and applications.

We carry out a detailed bifurcation analysis for a common class of electrostatically driven nanowires in a multiphysics model. A finding is that the nanoscale system can exhibit distinct chaotic states: chaos with symmetry breaking and extensive chaos possessing the full symmetry of the system. Potential applications such as nanoscale random number generator and controlling extensive chaos to achieve desirable performance are articulated.

How does typicality of category members affect the deductive reasoning? An ERP study.

The typicality effect describes a phenomenon whereby a typical item is easier to be judged as a member of a category than are atypical items. This effect has been intensively studied in the context of category verification tasks. The present study further investigated the typicality effect using our newly developed category-based deductive reasoning task. Subjects were required to judge whether an incoming stimulus had the properties described in the premise presented before. The stimuli were either typical or atypical members of four target semantic categories or were non-target stimuli. According to the ERP results, three phases were needed to determine whether the object has the property associated with the category in the premise. First, significant amplitude differences were seen between typical and atypical items at N1, which suggested that attention processing was influenced by the expectation in this up-to-down (deductive) process. The premise automatically induced the expectation of the prototype of one concept, i.e. the expectation for the prototype of birds was induced when the premise was "Birds possess the property C". Typical items (e.g., sparrow) were more similar to the prototype; hence, they were easier to be matched with the prototype induced by the premise than were atypical items (e.g., ostrich). Additionally, there was a dissociation between typical and atypical items at P2, which suggested that the participants' early detection of an item's category membership was influenced by the typicality. Thirdly, N400 effect is related to the process of semantic processes and determining whether the object has the property associated with the category in the premise. N400 mean amplitudes during the 300-500 ms epoch were significantly greater for non-target members than for target members, while words of lower typicality (atypical) evoked greater N400 amplitudes during the 350-450 ms epoch than did words of higher typicality (typical).

Controlled generation of intrinsic localized modes in microelectromechanical cantilever arrays.

We propose a scheme to induce intrinsic localized modes (ILMs) at an arbitrary site in microelectromechanical cantilever arrays. The idea is to locate the particular cantilever beam in the array that one wishes to drive to an oscillating state with significantly higher amplitude than the average and then apply small adjustments to the electrical signal that drives the whole array system. Our scheme is thus a global closed-loop control strategy. We argue that the dynamical mechanism on which our global driving scheme relies is spatiotemporal chaos and we develop a detailed analysis based on the standard averaging method in nonlinear dynamics to understand the working of our control scheme. We also develop a Markov model to characterize the transient time required for inducing ILMs.

How types of prior knowledge and task properties impact the category-based induction: diverging evidence from the P2, N400, and LPC effects.

Category-based induction task was combined with ERP to unravel whether prior knowledge and property interact when inferring on genes or diseases. Larger P2 amplitudes for near taxonomic/causal distances relative to far ones, as well as larger LPC for taxonomic relation relative to thematic relation, are found in both gene and disease tasks. However, smaller N400 is found for taxonomic relation in gene task and thematic relation in disease task, respectively, and larger LPC at 700-850 ms for near taxonomic distance in the gene task and near causal distance in the disease task. These results suggested that the category-based inductive reasoning is context-sensitive, and there may be four stages of category-based inductive reasoning: the early automatic comparison of features/relations (P2), features/relations generalization process (N400), the extraction of common relationship/rule (LPC at 550-700 ms), the inference generation (LPC at 700-850 ms).

Task relevance effect on number/shape conflict detection in the number-matching task: An ERP study.

It is debatable whether the task relevance effect on a conflict occurs in the detection or in the inhibition underlying sequential matching. To explore this issue, three types of number pairs, identical (e.g., 12, 12), conserved (e.g., 12, ), and non-conserved (e.g., 12, 15) pairs, were displayed to be judged as perceptually (identical shape condition) or quantitatively (identical value condition) the same. Both error rates and RTs for the three types of number pairs showed different patterns to detect perceptual mismatch in the identical shape condition and number inequivalence in the identical value conditions. The event-related potential (ERP) results showed that increased N200 and N400 as well as decreased P300 were triggered by the conserved and non-conserved pairs in contrast to identical pairs in the identical shape condition and by the non-conserved pairs relative to the conserved and identical pairs in the identical value condition. These results showed that task-relevant mismatches were attended to and detected in both conditions. Therefore, for the task-relevance effect on a conflict, attention is selectively directed to task-relevant features rather than inhibiting task-irrelevant conflict.

N400/frontal negativity reveals the controlled processes of taxonomic and thematic relationships in semantic priming for artifacts.

Recent studies show that taxonomic and thematic relationships are functionally and neurologically dissociated; however, there remain some discrepancies due to inconsistencies in definitions, task properties, and concept domains. This issue was further explored via the semantic priming paradigm with a long SOA of 600 ms while controlling for perceptual or functional features of artifacts involved across taxonomic and thematic relationships. Six conditions were compared: perceptual relationship (axe-helve), functional relationship (axe-wood), perceptual classification (axe-hammer), functional classification (axe-saw), unrelated condition (axe-skates), and nonword (axe-derf) conditions. Behavioral priming effects are found for all related conditions relative to unrelated conditions except for perceptual relationships, whereas semantic priming effects (smaller N400 amplitude) are found for functional relationships and perceptual classification relative to unrelated conditions but not for perceptual relationships and functional classification, indicating perceptual features are less important than functional features for artifacts. Furthermore, the frontal negativity elicited by functional relationships is smaller than all other related conditions at 400-550 ms, while it is only smaller than functional classification at 550-650 ms. These results indicate that, besides different features, taxonomic and thematic relationships are dissociated to organize object knowledge, which is primarily fuelled by feature processing, with taxonomic, or thematic, relationships further embedded with such sensory, or functional, features.

Targeting epidermal growth factor-overexpressing triple-negative breast cancer by natural killer cells expressing a specific chimeric antigen receptor.

OBJECTIVES: Traditional cancer therapy and regular immunotherapy are ineffective for treating triple-negative breast cancer (TNBC) patients. Recently, chimeric antigen receptor-engineered natural killer cells (CAR NK) have been applied to target several hormone receptors on different cancer cells to improve the efficacy of immunotherapy. Furthermore, epidermal growth factor receptor (EGFR) is a potential therapeutic target for TNBC. Here, we demonstrated that EGFR-specific CAR NK cells (EGFR-CAR NK cells) could be potentially used to treat patients with TNBC exhibiting enhanced EGFR expression. MATERIALS AND METHODS: We investigated the cytotoxic effects of EGFR-CAR NK cells against TNBC cells in vitro and in vivo. The two types of EGFR-CAR NK cells were generated by transducing lentiviral vectors containing DNA sequences encoding the single-chain variable fragment (scFv) regions of the two anti-EGFR antibodies. The cytotoxic and anti-tumor effects of the two cell types were examined by performing cytokine release and cytotoxicity assays in vitro, and tumor growth assays in breast cancer cell line-derived xenograft (CLDX) and patient-derived xenograft (PDX) mouse models. RESULTS: Both EGFR-CAR NK cell types were activated by TNBC cells exhibiting upregulated EGFR expression and specifically triggered the lysis of the TNBC cells in vitro. Furthermore, the two EGFR-CAR NK cell types inhibited CLDX and PDX tumors in mice. CONCLUSIONS: This study suggested that treatment with EGFR-CAR NK cells could be a promising strategy for TNBC patients.

Scaling of noisy fluctuations in complex networks and applications to network prediction.

We study the collective dynamics of oscillator-network systems in the presence of noise. By focusing on the time-averaged fluctuation of dynamical variable of interest about the mean field, we discover a scaling law relating the average fluctuation to the node degree. The scaling law is quite robust as it holds for a variety of network topologies and node dynamics. Analyses and numerical support for different types of networks and node dynamics are provided. We also point out an immediate application of the scaling law: predicting complex networks based on time series only, and we articulate how this can be done.