Sensitivity and stability improvement on slippery surface-aggregated substrate for trace heavy metals detection using NELIBS.

The sensitive and stable detection of trace heavy metals in liquid is crucial given its profound impact on various aspects of human life. Currently, nanoparticle-enhanced laser-induced breakdown spectroscopy (NELIBS) with dried droplet method (DDM) is widely applied for heavy metals detection. Nevertheless, the coffee ring effect (CRE) in DDM affects the stability, accuracy, and sensitivity of NELIBS. Here, we developed a slippery surface-aggregated substrate (SS substrate) to suppress the CRE and enrich analytes, and form a plasmonic platform for NELIBS detection. The SS substrate was prepared by infiltrating perfluorinated lubricant into the pores of PTFE membrane. The droplet, with targeted elements and gold nanoparticles, was dried on the SS substate to form the plasmonic platform for NELIBS analysis. Then, trace heavy metal elements copper (Cu) and manganese (Mn) were analyzed by NELIBS. The results of Cu (RSD = 5.60%, LoD = 3.72 µg/L) and Mn (RSD = 7.42%, LoD = 6.37 µg/L), illustrated the CRE suppression and analytes enrichment by the SS substrate. The results verified the realization of stable, accurate and sensitive NELIBS detection. And the LoDs succeeded to reach the standard limit of China (GB/T 14848-2017). Furthermore, the results for groundwater detection (relative error: 5.92% (Cu) and 4.74% (Mn)), comparing NELIBS and inductively coupled plasma mass spectrometry (ICP-MS), validated the feasibility of the SS substrate in practical applications. In summary, the SS substrate exhibits immense potential for practical application such as water quality detection and supervision.

Phonon Pseudoangular Momentum in α-MoO3.

In recent studies, it has been discovered that phonons can carry angular momentum, leading to a series of investigations into systems with three-fold rotation symmetry. However, for systems with two-fold screw rotational symmetry, such as α-MoO3, there has been no relevant discussion. In this paper, we investigated the pseudoangular momentum of phonons in crystals with two-fold screw rotational symmetry. Taking α-MoO3 as an example, we explain the selection rules in circularly polarized Raman experiments resulting from pseudoangular momentum conservation, providing important guidance for experiments. This study of pseudoangular momentum in α-MoO3 opens up a new degree of freedom for its potential applications, expanding into new application domains.

Associations of schizophrenia with the activities of the HPA and HPG axes and their interactions characterized by hair-based biomarkers.

BACKGROUND: Past studies on schizophrenia (SCZ) and the stress-sensitive neuroendocrine systems have mostly focused on a single system and traditionally utilized acute biomarkers (e.g., biomarkers from blood, urine and saliva) that poorly match the chronic course of schizophrenia in time span. Using eight biomarkers in hair, this study aimed to explore the functional characteristics of SCZ patients in the hypothalamic-pituitary-adrenocortical (HPA) and hypothalamic-pituitary-gonadal (HPG) axes and the interaction between the two axes. METHODS: Hair samples were taken from 137 SCZ patients and 73 controls. The SCZ patients were diagnosed by their attending physician according to the Diagnostic and Statistical Manual of Mental Disorders IV and were clinically stable after treatment. Gender, age, BMI, frequency of hair washing, marital status, education level, family history of mental illness and clozapine dosage were concurrently collected as covariates. The 10-item perceived stress scale (PSS-10) and the social readjustment rating scale were used to assess chronic stress status in SCZ patients. Eight hair biomarkers, cortisol, cortisone, dehydroepiandrosterone (DHEA), testosterone, progesterone, cortisol/cortisone, cortisol/DHEA and cortisol/testosterone, were measured by high performance liquid chromatography tandem mass spectrometer. Among them, cortisol, cortisone, DHEA and cortisol/DHEA reflected the functional activity of the HPA axis, and testosterone and progesterone reflected the functional activity of the HPG axis, and cortisol/cortisone reflected the activity of 11ß-hydroxysteroid dehydrogenase types 2 (11ß-HSD 2), and cortisol/testosterone reflected the HPA-HPG interaction. RESULTS: SCZ patients showed significantly higher cortisone and cortisol/testosterone than controls (p<0.001, η²p=0.180 and p=0.015, η²p=0.031), lower testosterone (p=0.009, η²p=0.034), progesterone (p<0.001, η²p=0.069) and cortisol/cortisone (p=0.001, η²p=0.054). There were significant intergroup differences in male and female progesterone (p=0.003, η²p=0.088 and p=0.030, η²p=0.049) and female testosterone (p=0.028, η²p=0.051). In SCZ patients, cortisol, cortisol/cortisone, cortisol/DHEA and cortisol/testosterone were positively associated with PSS-10 score (ps<0.05, 0.212

Quantifying the impact of upscaled parameters on radionuclide transport in three-dimensional fracture-matrix systems.

Assessing the long-term safety of geological repositories for high-level radioactive waste is critically dependent on understanding radionuclide transport in multi-scale fractured rocks. This study explores the influence of upscaled parameters on radionuclide movement within a three-dimensional fracture-matrix system using a discrete fracture-matrix (DFM) model. The developed numerical simulation workflow includes creating a random discrete fracture network, meshing of the fractures and matrix, assigning upscaled parameters, and conducting finite element simulations. We simulated the spatiotemporal evolution of radionuclide concentrations in the fractures and matrix over a century, revealing significant spatial heterogeneity driven by a heterogeneous seepage field. Employing geostatistics-based upscaling methods, we predicted the effective ranges of crucial solute transport parameters at the field scale. The matrix diffusion coefficient, matrix distribution coefficient, and longitudinal dispersivity were upscaled by factors of 2.0-3.0, 2.5-4.0, and 10-104, respectively, based on laboratory-scale measurements. Incorporating these upscaled parameters into the DFM model, we analyzed their impact on radionuclide transport. Our findings demonstrate that an upscaled matrix diffusion coefficient and matrix distribution coefficient result in a delayed transport of radionuclides in fractures by enhancing mass transfer between the fractures and rock matrix, while an upscaled longitudinal dispersivity accelerates transport by advancing the positions of concentration peaks. Sensitivity analysis revealed that the matrix distribution coefficient is the most impactful, followed by dispersivity and matrix diffusion coefficient. These insights are important for minimizing parameter uncertainties and enhancing the accuracy of predictions concerning radionuclide transport in multi-scale fractured rocks.

HSFA3 functions as a positive regulator of HSFA2a to enhance thermotolerance in perennial ryegrass.

Perennial ryegrass (Lolium perenne) is a widely used cool season turfgrass with outstanding turf quality and grazing tolerance. High temperature is the key factor restricting the distribution of perennial ryegrass in temperate and sub-tropic regions. In this study, we found that one HEAT SHCOK TRANSCRIPTION FACOTR (HSF) class A gene from perennial ryegrass, LpHSFA3, was highly induced by heat stress. LpHSFA3 is localized in nucleus and functions as a transcription factor. Ectopic overexpression of LpHSFA3 in Arabidopsis improved thermotolerance and rescued heat sensitive deficiency of athsfa3 mutant. Overexpression of LpHSFA3 in perennial ryegrass enhanced heat tolerance and increased survival rate in summer season as evidenced by decreased EL and MDA, increased number of green leaves and total chlorophyll content. LpHSFA3 binds to the HSE region in LpHSFA2a promoter to constitutively activate the expression of LpHSFA2a and downstream heat stress responsive genes. Ectopic overexpression of LpHSFA2a consequently rescued thermal sensitivity of athsfa3 mutant and enhanced thermotolerance of athsfa2 mutant. Perennial ryegrass protoplasts with overexpression of LpHSFA3 and LpHSFA2a exhibited induction of similar subsets of heat responsive genes. These results indicated that transcription factor LpHSFA3 functions as positive regulator of LpHSFA2a to improve thermotolerance of perennial ryegrass, providing further evidence to understand the regulatory networks of plant heat stress response.

[Advances of studies on culture and product functions of Euglena gracilis].

Euglena gracilis is a unicellular eukaryote between animal and plant cells, which is widely distributed in nature. E. gracilis has both plant and animal characteristics, and can grow photoautotrophically, heterotrophically and mixotrophically. E. gracilis also features on abundant and various cellular composition. Recently, extensive researches on unique cellular components of E. gracilis have revealed its application in the field of medicine, food, and feedstuff, in terms of improving immunity, fighting inflammation, and lowering uric acid levels. The application prospects of paramylon in biomedical area were also discovered. As food ingredients, food additives, feedstuffs and cosmetic ingredients, E. gracilis has been certified domestically and overseas. A series of products have been developed overseas, especially in Japan. However, the research and development of E. gracilis are still in its infancy in China, and there is huge space for development. At present, the research and potential application of cultivation and product functions of E. gracilis have been rarely reviewed. This review systematically examines both the domestic and abroad research of cultivation and production of E. gracilis, as well as the biological activity of E. gracilis powder and paramylon. The existing problems in the application, exploitation, and possible development direction of E. gracilis in the future are prospected. This review might be useful for establishing and optimizing large-scale and efficient heterotrophic technology, as well as developing related products of E. gracilis with specific functions.

Porous durian shell biochar modified by KMnO4 (Mn-DSB) as a highly selective adsorbent for Be(II).

The mining of uranium-beryllium ores has resulted in substantial beryllium (Be) contamination. In this study, agricultural waste durian shells were utilized as raw materials to prepare biochar, which was further modified to enhance its adsorption capacity (Mn-DSB). The results effectively demonstrated Mn loading onto the DSB surface. Batch experiments were conducted to identify the optimal adsorption conditions of Mn-DSB for beryllium. At a temperature of 35 °C and pH 6, beryllium's maximum adsorption capacity (Qe) was 42.08 mg·g-1. The materials' internal structure was analyzed before and after adsorption via multiple techniques. Mn-DSB manifested potent selectivity towards beryllium in multicomponent mixed solutions, binary systems, and uranium-beryllium wastewater, as the beryllium removal rate exceeded 90%. The study investigated the recyclability of Mn-DSB and found that after five reuse cycles, the adsorption and desorption efficiencies were 90% and 85%, respectively. The strong ligand complexation (N-H, CO32-, -OH) and ion exchange mechanisms (with Mn7+ ions) of Mn-DSB explained its high adsorption capacity. Therefore, this study demonstrates the potential of Mn-DSB for treating uranium-beryllium tailing wastewater.

The Effect of Health Literacy on Disease Management Self-Efficacy in Chronic Disease Patients: The Mediating Effects of Social Support and the Moderating Effects of Illness Perception.

Purpose: To test a hypothetical pathway model to estimate the links between health literacy, social support, illness perception, and disease management self-efficacy. Methods: This cross-sectional study, conducted from June to October 2022, involved the recruitment of 210 patients with chronic diseases at two primary care facilities. Participants completed the Health Literacy Management Scale, Self-Efficacy for Managing Chronic Disease 6-Item Scale, Social Support Rating Scale and Brief Illness Perception Questionnaire. We used the PROCESS macro for R to determine the hypothetical pathway model. Results: The direct effect of health literacy on self-efficacy was significant (ß=0.1792, 95% CI: 0.0940-0.2644), and social support played a partial mediating role between health literacy and self-efficacy (ES=0.0761, 95% CI: 0.0398-0.1204). Illness perception moderated the relationship between social support and self-efficacy (ß=-0.0153, 95% CI: -0.0268- -0.0039). Conclusion: Proposed a conceptual model including the mediating effect of social support and the moderating effect of illness perception, which helps to clarify the underlying mechanisms between health literacy and self-efficacy.

Identification of hub genes significantly linked to temporal lobe epilepsy and apoptosis via bioinformatics analysis.

Background: Epilepsy stands as an intricate disorder of the central nervous system, subject to the influence of diverse risk factors and a significant genetic predisposition. Within the pathogenesis of temporal lobe epilepsy (TLE), the apoptosis of neurons and glial cells in the brain assumes pivotal importance. The identification of differentially expressed apoptosis-related genes (DEARGs) emerges as a critical imperative, providing essential guidance for informed treatment decisions. Methods: We obtained datasets related to epilepsy, specifically GSE168375 and GSE186334. Utilizing differential expression analysis, we identified a set of 249 genes exhibiting significant variations. Subsequently, through an intersection with apoptosis-related genes, we pinpointed 16 genes designated as differentially expressed apoptosis-related genes (DEARGs). These DEARGs underwent a comprehensive array of analyses, including enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, prediction of miRNA and transcription factors, and molecular docking analysis. Results: In the epilepsy datasets examined, we successfully identified 16 differentially expressed apoptosis-related genes (DEARGs). Subsequent validation in the external dataset GSE140393 revealed the diagnostic potential of five biomarkers (CD38, FAIM2, IL1B, PAWR, S100A8) with remarkable accuracy, exhibiting an impressive area under curve (AUC) (The overall AUC of the model constructed by the five key genes was 0.916, and the validation set was 0.722). Furthermore, a statistically significant variance (p < 0.05) was observed in T cell CD4 naive and eosinophil cells across different diagnostic groups. Exploring interaction networks uncovered intricate connections, including gene-miRNA interactions (164 interactions involving 148 miRNAs), gene-transcription factor (TF) interactions (22 interactions with 20 TFs), and gene-drug small molecule interactions (15 interactions involving 15 drugs). Notably, IL1B and S100A8 demonstrated interactions with specific drugs. Conclusion: In the realm of TLE, we have successfully pinpointed noteworthy differentially expressed apoptosis-related genes (DEARGs), including CD38, FAIM2, IL1B, PAWR, and S100A8. A comprehensive understanding of the implications associated with these identified genes not only opens avenues for advancing our comprehension of the underlying pathophysiology but also bears considerable potential in guiding the development of innovative diagnostic methodologies and therapeutic interventions for the effective management of epilepsy in the future.

Genome-wide identification of DREB1 transcription factors in perennial ryegrass and functional profiling of LpDREB1H2 in response to cold stress.

Perennial ryegrass (Lolium perenne L.) is an outstanding turfgrass and forage cultivated in temperate regions worldwide. However, poor tolerance to extreme cold, heat, or drought limits wide extension and cultivation. DEHYDRATION-RESPONSIVE ELEMENT BINDING FACTOR1s (DREB1s) play a vital role in enhancing plant tolerance to abiotic stress, specifically for low-temperature stress. In this study, a total of 24 LpDREB1 family members were identified from the released genome of perennial ryegrass. Phylogenetic analysis showed that the LpDREB1 genes are divided into 7 groups that have close relationships with rice homologues. Conserved motif analysis revealed that members within the same group have similar conserved motif compositions. All LpDREB1s lack introns, and the promoter sequences of LpDREB1 genes contain multiple cis-acting elements associated with stress response, phytohormone signal transduction and plant growth and development. The majority of LpDREB1 genes were upregulated by drought, submergence, heat and cold stress treatments, including LpDREB1H2. Further investigation showed that LpDREB1H2 is localized in the nucleus. Overexpression of LpDREB1H2 in Arabidopsis induced the expression of cold-responsive (COR) genes, increased the levels of osmotic adjusting substances, and enhanced antioxidant enzyme activities, thus improving the cold tolerance of Arabidopsis. This study lays a foundation for further understanding the function of LpDREB1 genes in perennial ryegrass and provides insights for plant stress tolerance breeding.

Artificial neural networks prediction and optimization based on four light regions for light utilization from Synechocystis sp. PCC 6803.

Light is crucial in microalgae growth. However, dividing the microalgae growth region into light and dark regions has limitations. In this study, the light response of Synechocystis sp. PCC 6803 was investigated to define four light regions (FLRs): light compensation region, light limitation region, light saturation region, and photoinhibition region. The proportions of cells' residence time in the FLRs and the number of times cells (NTC) passed through the FLRs in photobioreactors were calculated by using MATLAB. Based on the FLRs and NTC passed through the FLRs, a growth model was established by using artificial neural network (ANN).The ANN model had a validation R2 value of 0.97, which was 76.36% higher than the model based on light-dark regions. The high accuracy of the ANN model was further verified through dynamic adjustment of light intensity experiments.This study confirmed the importance of the FLRs for studying microalgae growth dynamics.

Gas-phase synthesis of Ti2CCl2 enables an efficient catalyst for lithium-sulfur batteries.

MXenes have aroused intensive enthusiasm because of their exotic properties and promising applications. However, to date, they are usually synthesized by etching technologies. Developing synthetic technologies provides more opportunities for innovation and may extend unexplored applications. Here, we report a bottom-up gas-phase synthesis of Cl-terminated MXene (Ti2CCl2). The gas-phase synthesis endows Ti2CCl2 with unique surface chemistry, high phase purity, and excellent metallic conductivity, which can be used to accelerate polysulfide conversion kinetics and dramatically prolong the cyclability of Li-S batteries. In-depth mechanistic analysis deciphers the origin of the formation of Ti2CCl2 and offers a paradigm for tuning MXene chemical vapor deposition. In brief, the gas-phase synthesis transforms the synthesis of MXenes and unlocks the hardly achieved potentials of MXenes.

Staging classification of omicron variant SARS-CoV-2 infection based on dual-spectrometer LIBS (DS-LIBS) combined with machine learning.

Effective differentiation of the infection stages of omicron can provide significant assistance in transmission control and treatment strategies. The combination of LIBS serum detection and machine learning methods, as a novel disease auxiliary diagnostic approach, has a high potential for rapid and accurate staging classification of Omicron infection. However, conventional single-spectrometer LIBS serum detection methods focus on detecting the spectra of major elements, while trace elements are more closely related to the progression of COVID-19. Here, we proposed a rapid analytical method with dual-spectrometer LIBS (DS-LIBS) assisted with machine learning to classify different infection stages of omicron. The DS-LIBS, including a broadband spectrometer and a narrowband spectrometer, enables synchronous collection of major and trace elemental spectra in serum, respectively. By employing the RF machine learning models, the classification accuracy using the spectra data collected from DS-LIBS can reach 0.92, compared to 0.84 and 0.73 when using spectra data collected from single-spectrometer LIBS. This significant improvement in classification accuracy highlights the efficacy of the DS-LIBS approach. Then, the performance of four different models, SVM, RF, IGBT, and ETree, is compared. ETree demonstrates the best, with cross-validation and test set accuracies of 0.94 and 0.93, respectively. Additionally, it achieves classification accuracies of 1.00, 0.92, 0.92, and 0.89 for the four stages B1-acute, B1-post, B2, and B3. Overall, the results demonstrate that DS-LIBS combined with the ETree machine learning model enables effective staging classification of omicron infection.

Development of PMA-qPCR assay to accurately and reproducible quantify viable bacteria of Paenibacillus polymyxa.

Paenibacillus polymyxa is an important biocontrol bacterium. The combination of propidium monoazide (PMA) and quantitative polymerase chain reactionq (qPCR) has proven effective in quantifying live bacteria from various microorganisms. The objective was to create a PMA-qPCR assay to precisely and consistently measure the number of living bacteria of biocontrol P. polymyxa. The primers were designed for the spo0A gene of P. polymyxa HY96-2. The optimal conditions for treating the target strain with PMA were a PMA concentration of 15 µg/mL, an incubation time of 5 min, and an exposure time of 10 min. The PMA-qPCR method had a limit of quantification (LOQ) of 1.0 × 103 CFU/mL for measuring the amount of viable P. polymyxa bacteria. The PMA-qPCR method is more sensitive than the qPCR method in detecting viable bacteria in the mixtures of viable and dead bacteria. The accuracy and reproducibility of quantifying viable P. polymyxa bacteria using the PMA-qPCR method were higher compared to the plate count method.

Visualization of laser-induced breakdown spectroscopy data of mouse organs based on the feature extraction method.

At present, there is no comprehensive and systematic research on laser-induced breakdown spectroscopy (LIBS) data visualization. In particular, the LIBS spectra of biological samples have large noise and weak signals, which seriously affect the feature visualization. Here, three commonly used sample visualization methods were compared, and a new method was applied for tissue sample visualization. We used the LIBS mapping technique to obtain LIBS spectra of different organ slice samples from mice. LIBS spectral distribution was visualized after extracting the region of interest. The three spectral visualization methods are compared, and the performance of visualization algorithms is quantitatively analyzed. The potential of heat-diffusion for the affinity-based transition embedding (PHATE) method highlights the details of the LIBS spectral distribution while maintaining the overall structure of the data. The correlation coefficient between dimensionality reduction data and raw data is 0.97, and the average distance between samples of different categories is 0.64, which are superior to those of traditional principal component analysis (PCA), multidimensional scaling (MDS), and t-distributed stochastic neighbor embedding (t-SNE). The results show that the PHATE method can serve as a very promising LIBS spectral visualization tool.

Drying Acoustically Levitated Droplets as Signal-Amplifying Platforms for Ultrasensitive and Multimode Laser Sensing.

Ultrasensitive sensing to trace atomic and molecular analytes has gained interest for its intimate relation to industrial sectors and human lives. One of the keys to ultrasensitive sensing for many analytical techniques lies in enriching trace analytes onto well-designed substrates. However, the coffee ring effect, nonuniform distribution of analytes onto substrates, in the droplet drying process hinders the ultrasensitive and stable sensing onto the substrates. Here, we propose a substrate-free strategy to suppress the coffee ring effect, enrich analytes, and self-assemble a signal-amplifying (SA) platform for multimode laser sensing. The strategy involves acoustically levitating and drying a droplet, mixed with analytes and core-shell Au@SiO2 nanoparticles, to self-assemble an SA platform. The SA platform with a plasmonic nanostructure can dramatically enrich analytes, enabling enormous spectroscopic signal amplification. Specifically, the SA platform can promote atomic detection (cadmium and chromium) to the 10-3 mg/L level by nanoparticle-enhanced laser-induced breakdown spectroscopy and can promote molecule detection (rhodamine 6G) to the 10-11 mol/L level by surface-enhanced Raman scattering. All in all, the SA platform, self-assembled by acoustic levitation, can intrinsically suppress the coffee ring effect and enrich trace analytes, enabling ultrasensitive multimode laser sensing.

Heterogeneity of resilience and the curvilinear relationship between childhood trauma and resilience among people with schizophrenia.

Background: As a group with a high incidence of childhood trauma, the differential characteristics of resilience in schizophrenia and its relationship with childhood trauma are still unclear. Methods: A total of 626 individuals diagnosed with schizophrenia were selected from four psychiatric hospitals in northern China. Childhood trauma and resilience were measured using the Childhood Trauma Questionnaire-short form (CTQ-SF) and Connor-Davidson Resilience Scale (CD-RISC), respectively. Latent profile analysis (LPA) was used to identify the potential classes of resilience. A generalized additive mixed model (GAMM) and restricted cubic spline (RCS) was used to explore and determine the shape of the relationship between childhood trauma and resilience. Results: Model fits of LPA showed three heterogeneous classes of resilience: moderate resilience levels (n = 312; 49.06%); high resilience levels (n = 171; 26.89%) and low resilience levels (n = 153; 24.06%). Resilience scores fluctuated depending on amount of exposure to childhood trauma. The GAMM results verified the non-linear relationship between resilience and childhood trauma, with an estimated degree of freedom higher than 1 (4.573) and p = 0.003. RCS fitted for ordinary least square (OLS) regression models determined a smooth continuous cubic curve of resilience across childhood trauma levels, and the two turning points of the curve line were 41.04 and 54.74 for childhood trauma. Discussion: Our findings confirm the people-specific differences in the level of resilience in schizophrenia and describe the cubic curvilinear relationship between childhood trauma and resilience, which provides data support for mechanistic research and intervention in related fields.

Novel CuMgAlTi-LDH Photocatalyst for Efficient Degradation of Microplastics under Visible Light Irradiation.

Microplastics (MPs) in the water system could easily enter the human body and pose a potential threat, so finding a green and effective solution remains a great challenge. At present, the advanced oxidation technology represented by photocatalysis has been proven to be effective in the removal of organic pollutants, making it a feasible method to solve the problem of MP pollution. In this study, the photocatalytic degradation of typical MP polystyrene (PS) and polyethylene (PE) by a new quaternary layered double hydroxide composite photomaterial CuMgAlTi-R400 was tested under visible light irradiation. After 300 h of visible light irradiation, the average particle size of PS decreased by 54.2% compared with the initial average particle size. The smaller the particle size, the higher the degradation efficiency. The degradation pathway and mechanism of MPs were also studied by GC-MS, which showed that PS and PE produced hydroxyl and carbonyl intermediates in the process of photodegradation. This study demonstrated a green, economical, and effective strategy for the control of MPs in water.