Role of low-proportion, hydrophobic dissolved organic matter components in inhibiting methylmercury uptake by phytoplankton.

Uptake of methylmercury (MeHg), a potent neurotoxin, by phytoplankton is a major concern due to its role as the primary pathway for MeHg entry into aquatic food webs, thereby posing a significant risk to human health. While it is widely believed that the MeHg uptake by plankton is negatively correlated with the concentrations of dissolved organic matter (DOM) in the water, ongoing debates continue regarding the specific components of DOM that exerts the dominant influence on this process. In this study, we employed a widely-used resin fractionation approach to separate and classify DOM derived from algae (AOM) and natural rivers (NOM) into distinct components: strongly hydrophobic, weakly hydrophobic, and hydrophilic fractions. We conduct a comparative analysis of different DOM components using a combination of spectroscopy and mass spectrometry techniques, aiming to identify their impact on MeHg uptake by Microcystis elabens, a prevalent alga in freshwater environments. We found that the hydrophobic components had exhibited more pronounced spectral characteristics associated with the protein structures while protein-like compounds between hydrophobic and hydrophilic components displayed significant variations in both distributions and the values of m/z (mass-to-charge ratio) of the molecules. Regardless of DOM sources, the low-proportion hydrophobic components usually dominated inhibition of MeHg uptake by Microcystis elabens. Results inferred from the correlation analysis suggest that the uptake of MeHg by the phytoplankton was most strongly and negatively correlated with the presence of protein-like components. Our findings underscore the importance of considering the diverse impacts of different DOM fractions on inhibition of phytoplankton MeHg uptake. This information should be considered in future assessments and modeling endeavors aimed at understanding and predicting risks associated with aquatic Hg contamination.

Redundancy effect of initial enactment encoding and subsequent testing on memory enhancement: Insights from an electrophysiological study.

Testing is more beneficial for memory retention than restudying the same content. However, the effect of the initial encoding method on the testing effect remains unclear. In this study, a classical testing effect paradigm was employed, along with event-related potentials (ERP), to investigate the electrophysiological processes underlying the effect of enactment encoding on the testing effect. Participants were randomly assigned to the Self-Performed Test (SPT) or Verbalized Test (VT) groups. Both groups underwent three stages: an initial encoding phase, an initial test phase (comprising a source memory task and a restudy task), and a final test phase. During the initial encoding phase, the SPT group encoded action phrases through enactment, while the VT group encoded information through reading. During the initial test phase, the SPT group exhibited superior recognition performance in item memory compared with the VT group. Both groups exhibited significant parietal old/new effects in the source memory task, with only the SPT group displaying parietal positivity during the restudy task. During the final test phase, the behavioral testing effect was exclusively observed in the VT group. Furthermore, the VT group displayed a more pronounced parietal positivity in the test condition compared to the restudy condition, while the parietal positivity between the two conditions was comparable in the SPT group. In summary, the absence of a final behavioral testing effect in the SPT group may be attributed to both enactment and testing primarily enhancing memory performance through recollection-based retrieval, as indicated by the parietal positivity. Consequently, the initial enactment encoding method leaves limited scope for further improvements through subsequent testing. These findings suggest that initial enactment encoding, and subsequent testing may be redundant in improving episodic memory performance.

Magnetically actuated sonodynamic nanorobot collectives for potentiated ovarian cancer therapy.

Ovarian cancer presents a substantial challenge due to its high mortality and recurrence rates among gynecological tumors. Existing clinical chemotherapy treatments are notably limited by drug resistance and systemic toxic side effects caused by off target drugs. Sonodynamic therapy (SDT) has emerged as a promising approach in cancer treatment, motivating researchers to explore synergistic combinations with other therapies for enhanced efficacy. In this study, we developed magnetic sonodynamic nanorobot (Fe3O4@SiO2-Ce6, FSC) by applying a SiO2 coating onto Fe3O4 nanoparticle, followed by coupling with the sonosensitizer Ce6. The magnetic FSC nanorobot collectives could gather at fixed point and actively move to target site regulated by magnetic field. In vitro experiments revealed that the magnetic FSC nanorobot collectives enabled directional navigation to the tumor cell area under guidance. Furthermore, under low-intensity ultrasonic stimulation, FSC nanorobot collectives mediated sonodynamic therapy exhibited remarkable anti-tumor performance. These findings suggest that magnetically actuated sonodynamic nanorobot collectives hold promising potential for application in target cancer therapy.

Dual-Channel Prototype Network for Few-Shot Pathology Image Classification.

In the field of pathology, the scarcity of certain diseases and the difficulty of annotating images hinder the development of large, high-quality datasets, which in turn affects the advancement of deep learning-assisted diagnostics. Few-shot learning has demonstrated unique advantages in modeling tasks with limited data, yet explorations of this method in the field of pathology remain in the early stages. To address this issue, we present a dual-channel prototype network (DCPN), a novel few-shot learning approach for efficiently classifying pathology images with limited data. The DCPN leverages self-supervised learning to extend the pyramid vision transformer (PVT) to few-shot classification tasks and combines it with a convolutional neural network to construct a dual-channel network for extracting multi-scale, high-precision pathological features, thereby substantially enhancing the generalizability of prototype representations. Additionally, we design a soft voting classifier based on multi-scale features to further augment the discriminative power of the model in complex pathology image classification tasks. We constructed three few-shot classification tasks with varying degrees of domain shift using three publicly available pathological datasets-CRCTP, NCTCRC, and LC25000-to emulate real-world clinical scenarios. The results demonstrated that the DCPN outperformed the prototypical network across all metrics, achieving the highest accuracies in same-domain tasks-70.86% for 1-shot, 82.57% for 5-shot, and 85.2% for 10-shot setups-corresponding to improvements of 5.51%, 5.72%, and 6.81%, respectively, over the prototypical network. Notably, in the same-domain 10-shot setting, the accuracy of the DCPN (85.2%) surpassed that of the PVT-based supervised learning model (85.15%), confirming its potential to diagnose rare diseases within few-shot learning frameworks.

Mechanical enhancement and high linearity health monitoring of composite materials based on CNTs/PSF/PI film sensor with ultra-low SWCNTs doping content.

A new type of embedded composite material health monitoring nano-sensor is designed to ensure that the unique material advantages of nanofillers can be maximized. The carbon nanotubes (CNTs)/polysulfone (PSF)/polyimide (PI) thin film sensor in this paper is obtained by the self-assembly of a PSF/PI asymmetric porous membrane which is prepared by a phase inversion method through vacuum filtration of SWCNTs. It is a new structure for a practical CNT sensor that can take into account both 'composite health monitoring and damage warning' and 'composite mechanical enhancement'. The new structure of the CNTs/PSF/PI film sensor is divided into two parts. The upper part consists of small-aperture finger-like holes filled with SWCNTs (the SWCNT content is 0.0127 mg cm-2). The lower part consists of large-aperture cavities conducive to resin infiltration, which enhance the interface bonding force between the sensor and the composite material. This unique structure allows the CNTs/PSF/PI film sensor to change the influence of the embedded sensor from 'introducing defects' to 'local enhancement', and the mechanical strength of the enhanced specimen can reach up to 1.68 times that of the original specimen, and the service interval can reach 2.01 times that of the original specimen. In addition, the CNTs/PSF/PI film sensor also has good sensitivity (GF = 2.54) and extremely high linearity (R2 = 0.9995), and has excellent follow-up and interface bonding ability. It can also maintain excellent fatigue resistance and stability over 46 500 vibration cycles, which provides new research ideas and research methods for the field of composite-life monitoring sensors.

Phosphoserine aminotransferase deficiency diagnosed by whole-exome sequencing and LC-MS/MS reanalysis: A case report and review of literature.

BACKGROUND: Phosphoserine aminotransferase deficiency (PSATD) is an autosomal recessive disorder associated with hypertonia, psychomotor retardation, and acquired microcephaly. Patients with PSATD have low concentrations of serine in plasma and cerebrospinal fluid. METHODS: We reported a 2-year-old female child with developmental delay, dyskinesia, and microcephaly. LC-MS/MS was used to detect amino acid concentration in the blood and whole-exome sequencing (WES) was used to identify the variants. PolyPhen-2 web server and PyMol were used to predict the pathogenicity and changes in the 3D model molecular structure of protein caused by variants. RESULTS: WES demonstrated compound heterozygous variants in PSAT1, which is associated with PSATD, with a paternal likely pathogenic variant (c.235G>A, Gly79Arg) and a maternal likely pathogenic variant (c.43G>C, Ala15Pro). Reduced serine concentration in LC-MS/MS further confirmed the diagnosis of PSATD in this patient. CONCLUSIONS: Our findings demonstrate the importance of WES combined with LC-MS/MS reanalysis in the diagnosis of genetic diseases and expand the PSAT1 variant spectrum in PSATD. Moreover, we summarize all the cases caused by PSAT1 variants in the literature. This case provides a vital reference for the diagnosis of future cases.

Immobilisation remediation of arsenic-contaminated soils with promising CaAl-layered double hydroxide and bioavailability, bioaccessibility, and speciation-based health risk assessment.

Arsenic (As)-contaminated soil poses great health risk to human mostly through inadvertent oral exposure. We investigated CaAl-layered double hydroxide (CaAl-LDH), a promising immobilising agent, for the remediation of As-contaminated Chinese soils. The effects on specific soil properties and As fractionation were analyzed, and changes in the health risk of soil As were accurately assessed by means of advanced in vivo mice model and in vitro PBET-SHIME model. Results showed that the application of CaAl-LDH significantly increased soil pH and concentration of Fe and Al oxides, and effectively converted active As fractions into the most stable residual fraction, guaranteeing long-term remediation stability. Based on in vivo test, As relative bioavailability was significantly reduced by 37.75%. Based on in vitro test, As bioaccessibility in small intestinal and colon phases was significantly reduced by 25.65% and 28.57%, respectively. Furthermore, As metabolism (reduction and methylation) by the gut microbiota inhabiting colon was clearly observed. After immobilisation with CaAl-LDH, the concentration of bioaccessible As(Ⅴ) in the colon fluid was significantly reduced by 61.91%, and organic As (least toxic MMA(V) and DMA(V)) became the main species, which further reduced the health risk of soil As. In summary, CaAl-LDH proved to be a feasible option for immobilisation remediation of As-contaminated soils, and considerable progress was made in relevant health risk assessment.

Exposure to tris (1,3-dichloro-2-propyl) phosphate affects the embryonic cardiac development of Oryzias melastigma.

Tris (1,3-dichloro-2-propyl) phosphate (TDCPP) is a growing concern and may be a potential risk to marine environmental health due to its widespread usage and distribution. However, the toxic effects of TDCPP on cardiac development in marine fish have not been reported. In this study, Oryzias melastigma embryos were exposed to TDCPP at doses of 0, 0.04, 0.4, 4 and 40 µg/L from early embryogenesis to 10 days postfertilization (dpf). Then, the heart rate and sinus venosus-bulbus arteriosus (SV-BA) distance of the exposed embryos were measured at 5, 6, 8 and 10 dpf. Furthermore, alterations in the mRNA levels of the genes encoding cyclooxygenase-2 (COX-2), bone morphogenetic protein 4 (BMP4), fibroblast growth factor 8 (FGF8), and GATA-binding protein 4 (GATA4) were evaluated at 5, 6, 8 and 10 dpf. We found that the heart rate significantly increased in all TDCPP exposure groups at 10 dpf. The SV-BA distance significantly decreased in all TDCPP exposure groups at all developmental stages (except for the 0.4 µg/L group at 5 dpf and the 4 µg/L group at 10 dpf). The mRNA expression of COX-2 was downregulated at 5 dpf, BMP4 was downregulated at 5 and 6 dpf, FGF8 was downregulated at 5, 6 and 8 dpf, GATA4 was downregulated at 8 dpf, and GATA4 was upregulated at 10 dpf. These results indicate that the changes in heart rate and SV-BA distance might be accompanied by disturbances in the four genes involved in cardiac development. Our findings will help to illustrate the possible cardiac toxic effects of marine fish exposed to TDCPP.

Single exposure to anesthesia/surgery in neonatal mice induces cognitive impairment in young adult mice.

BACKGROUND: The effects of a solitary neonatal exposure to anesthesia plus surgery (anesthesia/surgery) on cognitive function and the underlying mechanism in developing brains remains largely undetermined. We, therefore, set out to investigate the impact of single exposure to anesthesia/surgery in neonatal mice. METHODS: Six-day-old male and female mice received abdominal surgery under 3% sevoflurane plus 50% oxygen for 2 h. The new object recognition (NOR) and Morris water maze (MWM) were used to evaluate cognitive function in young adult mice. Western blot, ELISA and RT-PCR were used to measure levels of NR2B and IL-6 in medial prefrontal cortex and IL-6 in blood of the mice. We employed NR2B siRNA and IL-6 antibody in the interaction studies. RESULTS: The anesthesia/surgery decreased the ratio of novel time to novel plus familiar time in NOR and the number of platform crossings, but not escape latency, in MWM compared to sham condition. The mice in anesthesia/surgery group had increased NR2B expression in medial prefrontal cortex, and IL-6 amounts in blood and medial prefrontal cortex. Local injection of NR2B siRNA in medial prefrontal cortex alleviated the anesthesia/surgery-induced cognitive impairment. IL-6 antibody mitigated the anesthesia/surgery-induced upregulation of NR2B and cognitive impairment in young adult mice. CONCLUSIONS: These results suggest that a single neonatal exposure to anesthesia/surgery causes impairment of memory, but not learning, in young adult mice through IL-6-regulated increases in NR2B concentrations in medial prefrontal cortex, highlighting the need for further research on the underlying mechanisms of anesthesia/surgery's impact on cognitive function in developing brains.

Influences of coexisting aged polystyrene microplastics on the ecological and health risks of cadmium in soils: A leachability and oral bioaccessibility based study.

Whether coexisting microplastics (MPs) affect the ecological and health risks of cadmium (Cd) in soils is a cutting-edge scientific issue. In this study, four typical Chinese soils were prepared as artificially Cd-contaminated soils with/without aged polystyrene (PS). TCLP and in vitro PBET model were used to determine the leachability (ecological risk) and oral bioaccessibility (human health risk) of soil Cd. The mechanisms by which MPs influence soil Cd were discussed from direct and indirect perspectives. Results showed that there was no significant difference in the leachability of soil Cd with/without aged PS. Additionally, aged PS led to a significant decrease in the bioaccessibility of soil Cd in gastric phase, but not in small intestinal phase. The increase in surface roughness and the new characteristic peaks (e.g., Si-O-Si) of aged PS directly accounted for the change in Cd bioaccessibility. The change in organic matter content indirectly accounted for the exceptional increase in Cd bioaccessibility of black soil with aged PS in small intestinal phase. Furthermore, the changes in cation exchange capacity and Cd mobility factor caused by aged PS explained the change in Cd leachability. These results contribute to a deeper understanding about environmental and public health in complicated emerging scenarios.

Bioinspired Multifunctional Self-Sensing Actuated Gradient Hydrogel for Soft-Hard Robot Remote Interaction.

The development of bioinspired gradient hydrogels with self-sensing actuated capabilities for remote interaction with soft-hard robots remains a challenging endeavor. Here, we propose a novel multifunctional self-sensing actuated gradient hydrogel that combines ultrafast actuation and high sensitivity for remote interaction with robotic hand. The gradient network structure, achieved through a wettability difference method involving the rapid precipitation of MoO2 nanosheets, introduces hydrophilic disparities between two sides within hydrogel. This distinctive approach bestows the hydrogel with ultrafast thermo-responsive actuation (21° s-1) and enhanced photothermal efficiency (increase by 3.7 °C s-1 under 808 nm near-infrared). Moreover, the local cross-linking of sodium alginate with Ca2+ endows the hydrogel with programmable deformability and information display capabilities. Additionally, the hydrogel exhibits high sensitivity (gauge factor 3.94 within a wide strain range of 600%), fast response times (140 ms) and good cycling stability. Leveraging these exceptional properties, we incorporate the hydrogel into various soft actuators, including soft gripper, artificial iris, and bioinspired jellyfish, as well as wearable electronics capable of precise human motion and physiological signal detection. Furthermore, through the synergistic combination of remarkable actuation and sensitivity, we realize a self-sensing touch bioinspired tongue. Notably, by employing quantitative analysis of actuation-sensing, we realize remote interaction between soft-hard robot via the Internet of Things. The multifunctional self-sensing actuated gradient hydrogel presented in this study provides a new insight for advanced somatosensory materials, self-feedback intelligent soft robots and human-machine interactions.

Review on Frontal Polymerization Behavior for Thermosetting Resins: Materials, Modeling and Application.

The traditional curing methods for thermosetting resins are energy-inefficient and environmentally unfriendly. Frontal polymerization (FP) is a self-sustaining process relying on the exothermic heat of polymerization. During FP, the external energy input (such as UV light input or heating) is only required at the initial stage to trigger a localized reaction front. FP is regarded as the rapid and energy-efficient manufacturing of polymers. The precise control of FP is essential for several manufacturing technologies, such as 3D printing, depending on the materials and the coupling of thermal transfer and polymerization. In this review, recent progress on the materials, modeling, and application of FP for thermosetting resins are presented. First, the effects of resin formulations and mixed fillers on FP behavior are discussed. Then, the basic mathematical model and reaction-thermal transfer model of FP are introduced. After that, recent developments in FP-based manufacturing applications are introduced in detail. Finally, this review outlines a roadmap for future research in this field.

Assembly mechanisms of microbial communities in plastisphere related to species taxonomic types and habitat niches.

A lot of plastic floats are presented in the kelp cultivation zone, enabling us to effectively evaluate the differences between surface water (SW) and plastic-attached (PA) microbial communities. In this study, we explored the microbial communities (both bacteria and protists) in SW and PA niches during the kelp cultivation activities. Effects of habitat niches on the diversity and composition of microbial communities were found. Beta partitioning and core taxa analyses showed species turnover and local species pool governed the microbial community assembly, and they contributed more to bacteria and protists, respectively. Based on the results of null model, bacterial communities presented a more deterministic and homogeneous assembly compared to protistan communities. Moreover, microbial communities in PA niche had higher species turnover and homogenizing assembly compared to the SW niche. The results of this study supplemented the theory of microbial community assembly and expanded our understanding of protists in plastisphere.

Differential response of Hg-methylating and MeHg-demethylating microbiomes to dissolved organic matter components in eutrophic lake water.

Methylmercury (MeHg) production in aquatic ecosystems is a global concern because of its neurotoxic effect. Dissolved organic matter (DOM) plays a crucial role in biogeochemical cycling of Hg. However, owing to its complex composition, the effects of DOM on net MeHg production have not been fully understood. Here, the Hg isotope tracer technique combined with different DOM treatments was employed to explore the influences of DOM with divergent compositions on Hg methylation/demethylation and its microbial mechanisms in eutrophic lake waters. Our results showed that algae-derived DOM treatments enhanced MeHg concentrations by 1.42-1.53 times compared with terrestrial-derived DOM. Algae-derived DOM had largely increased the methylation rate constants by approximately 1-2 orders of magnitude compared to terrestrial-derived DOM, but its effects on demethylation rate constants were less pronounced, resulting in the enhancement of net MeHg formation. The abundance of hgcA and merB genes suggested that Hg-methylating and MeHg-demethylating microbiomes responded differently to DOM treatments. Specific DOM components (e.g., aromatic proteins and soluble microbial byproducts) were positively correlated with both methylation rate constants and the abundance of Hg-methylating microbiomes. Our results highlight that the DOM composition influences the Hg methylation and MeHg demethylation differently and should be incorporated into future Hg risk assessments in aquatic ecosystems.

Strain Sensors Made of MXene, CNTs, and TPU/PSF Asymmetric Structure Films with Large Tensile Recovery and Applied in Human Health Monitoring.

Designing flexible wearable sensors with a wide sensing range, high sensitivity, and high stability is a vulnerable research direction with a futuristic field to study. In this paper, Ti3C2Tx MXene/carbon nanotube (CNT)/thermoplastic polyurethane (TPU)/polysulfone (PSF) composite films with excellent sensor performance were obtained by self-assembly of conductive fillers in TPU/PSF porous films with an asymmetric structure through vacuum filtration, and the porous films were prepared by the phase inversion method. The composite films consist of the upper part with finger-like "cavities" filled by MXene/CNTs, which reduces the microcracks in the conductive network during the tensile process, and the lower part has smaller apertures of a relatively dense resin cortex assisting the recovery process. The exclusive layer structure of the MXene/CNTs/TPU/PSF film sensor, with a thickness of 46.95 µm, contains 0.0339 mg/cm2 single-walled carbon nanotubes (SWNTs) and 0.348 mg/cm2 MXene only, providing functional range (0-80.7%), high sensitivity (up to 1265.18), and excellent stability and durability (stable sensing under 2300 fatigue tests, viable to the initial resistance), endurably cycled under large strains with serious damage to the conductive network. Finally, the MXene/CNTs/TPU/PSF film sensor is usable for monitoring pulse, swallow, tiptoe, and various joint bends in real time and distributing effective electrical signals. This paper implies that the MXene/CNTs/TPU/PSF film sensor has broad prospects in pragmatic applications.

PB-LNet: a model for predicting pathological subtypes of pulmonary nodules on CT images.

OBJECTIVE: To investigate the correlation between CT imaging features and pathological subtypes of pulmonary nodules and construct a prediction model using deep learning. METHODS: We collected information of patients with pulmonary nodules treated by surgery and the reference standard for diagnosis was post-operative pathology. After using elastic distortion for data augmentation, the CT images were divided into a training set, a validation set and a test set in a ratio of 6:2:2. We used PB-LNet to analyze the nodules in pre-operative CT and predict their pathological subtypes. Accuracy was used as the model evaluation index and Class Activation Map was applied to interpreting the results. Comparative experiments with other models were carried out to achieve the best results. Finally, images from the test set without data augmentation were analyzed to judge the clinical utility. RESULTS: Four hundred seventy-seven patients were included and the nodules were divided into six groups: benign lesions, precursor glandular lesions, minimally invasive adenocarcinoma, invasive adenocarcinoma Grade 1, Grade 2 and Grade 3. The accuracy of the test set was 0.84. Class Activation Map confirmed that PB-LNet classified the nodules mainly based on the lungs in CT images, which is in line with the actual situation in clinical practice. In comparative experiments, PB-LNet obtained the highest accuracy. Finally, 96 images from the test set without data augmentation were analyzed and the accuracy was 0.89. CONCLUSIONS: In classifying CT images of lung nodules into six categories based on pathological subtypes, PB-LNet demonstrates satisfactory accuracy without the need of delineating nodules, while the results are interpretable. A high level of accuracy was also obtained when validating on real data, therefore demonstrates its usefulness in clinical practice.

Learning how to detect: A deep reinforcement learning method for whole-slide melanoma histopathology images.

Cutaneous melanoma represents one of the most life-threatening malignancies. Histopathological image analysis serves as a vital tool for early melanoma detection. Deep neural network (DNN) models are frequently employed to aid pathologists in enhancing the efficiency and accuracy of diagnoses. However, due to the paucity of well-annotated, high-resolution, whole-slide histopathology image (WSI) datasets, WSIs are typically fragmented into numerous patches during the model training and testing stages. This process disregards the inherent interconnectedness among patches, potentially impeding the models' performance. Additionally, the presence of excess, non-contributing patches extends processing times and introduces substantial computational burdens. To mitigate these issues, we draw inspiration from the clinical decision-making processes of dermatopathologists to propose an innovative, weakly supervised deep reinforcement learning framework, titled Fast medical decision-making in melanoma histopathology images (FastMDP-RL). This framework expedites model inference by reducing the number of irrelevant patches identified within WSIs. FastMDP-RL integrates two DNN-based agents: the search agent (SeAgent) and the decision agent (DeAgent). The SeAgent initiates actions, steered by the image features observed in the current viewing field at various magnifications. Simultaneously, the DeAgent provides labeling probabilities for each patch. We utilize multi-instance learning (MIL) to construct a teacher-guided model (MILTG), serving a dual purpose: rewarding the SeAgent and guiding the DeAgent. Our evaluations were conducted using two melanoma datasets: the publicly accessible TCIA-CM dataset and the proprietary MELSC dataset. Our experimental findings affirm FastMDP-RL's ability to expedite inference and accurately predict WSIs, even in the absence of pixel-level annotations. Moreover, our research investigates the WSI-based interactive environment, encompassing the design of agents, state and reward functions, and feature extractors suitable for melanoma tissue images. This investigation offers valuable insights and references for researchers engaged in related studies. The code is available at: https://github.com/titizheng/FastMDP-RL.

Impacts of autochthonous dissolved organic matter on the accumulation of methylmercury by phytoplankton and zooplankton in a eutrophic coastal ecosystem.

The bioaccumulation of methylmercury (MeHg) within the pelagic food webs is a crucial determinant of the MeHg concentration in the organisms at higher trophic levels. Dissolved organic matter (DOM) is recognized for its influence on mercury (Hg) cycling in the aquatic environment because of its role in providing metabolic substrate for heterotrophic organism and serving as a strong ligand for MeHg. However, the impact of DOM on MeHg bioaccumulation in pelagic food chains remain controversial. Here, we explored MeHg bioaccumulation within a pelagic food web in China, in the eutrophic Bohai Sea and adjacent seas, covering a range of DOM concentrations and compositions. Our findings show that elevated concentrations of dissolved organic carbon (DOC) and phytoplankton biomass may contribute to a reduction in MeHg uptake by phytoplankton. Moreover, we observe that a higher level of autochthonous DOM in the water may result in more significant MeHg biomagnification in zooplankton. This can be explained by alterations in the structure of pelagic food webs and/or an increase in the direct consumption of DOM and particulate organic matter (POM) containing MeHg. Our study offers direct field monitoring evidence of dual roles played by DOM in regulating MeHg transfers from water to phytoplankton and zooplankton in coastal pelagic food webs. A thorough understanding of the intricate interactions is essential for a more comprehensive evaluation of ecological risks associated with MeHg exposure in coastal ecosystems.

Shear Thickening Fluid and Its Application in Impact Protection: A Review.

Shear thickening fluid (STF) is a dense colloidal suspension of nanoparticles in a carrier fluid in which the viscosity increases dramatically with a rise in shear rate. Due to the excellent energy absorption and energy dissipation of STF, there is a desire to employ STFs in a variety of impact applications. In this study, a comprehensive review on STFs' applications is presented. First, several common shear thickening mechanisms are discussed in this paper. The applications of different STF impregnated fabric composites and the STF's contributions on improving the impact, ballistic and stab resistance performance have also been presented. Moreover, recent developments of STF's applications, including dampers and shock absorbers, are included in this review. In addition, some novel applications (acoustic structure, STF-TENG and electrospun nonwoven mats) based on STF are summarized, to suggest the challenges of future research and propose some more deterministic research directions, e.g., potential trends for applications of STF.

Subtle Pathophysiological Changes in Working Memory-Related Potentials and Intrinsic Theta Power in Community-Dwelling Older Adults With Subjective Cognitive Decline.

Background and Objectives: Individuals with subjective cognitive decline (SCD) who perform normally on objective cognitive tests may have an increased risk of pathological cognitive decline and progression to Alzheimer's disease (AD) and related dementia (ADRD). Working memory is widely regarded as an early sign of pathological cognitive decline. We tested the hypothesis that older adults with SCD already exhibit aberrant neurocognitive processing underlying working memory. Research Design and Methods: Electroencephalography (EEG) was recorded during a delayed match-to-sample (DMS) task and an eyes-closed resting condition in cognitively healthy community-dwelling older adults who were assigned to the SCD or Control group. Results: The SCD and Control groups showed comparable performance on the neuropsychological tests and DMS task. The SCD group showed an enhanced right frontal target-related P300 effect during working memory retrieval and higher frontal theta power during rest. Higher theta power was associated with worse working memory performance and greater left frontal nontarget-related positivity across all older adults. Discussion and Implications: Our findings suggest that older people with SCD have subtle pathophysiological changes in working memory-related potentials and intrinsic theta power, which has important implications for predicting risks and early interventions in older adults in the preclinical stage of ADRD.