Propylparaben Induces Reproductive Toxicity in Human Extravillous Trophoblast Cells via Apoptosis and Cell Cycle Pathways.

Parabens (PBs), especially propylparaben, commonly used in consumer products, pose environmental and health concerns. This study explored propylparaben's cytotoxicity on HTR-8/SVneo human trophoblast cells, revealing significant dose-dependent cytotoxic effects, particularly post 48-h exposure. Elevated propylparaben levels triggered apoptosis, evidenced by increased Bax and activated Caspase-3, and induced the G0/G1 cell cycle arrest. Concurrently, an increase in reactive oxygen species and reduced mitochondrial membrane potential indicated oxidative stress and mitochondrial dysfunction. Although N-acetylcysteine (NAC) treatment reduced oxidative stress, cell invasiveness persisted, suggesting propylparaben might affect cell migration through nonoxidative mechanisms. Integrated transcriptome analysis through RNA sequencing revealed 3488 differentially expressed genes affected by propylparaben, highlighting changes in pathways like apoptosis and cell cycle regulation and identifying seven hub genes as potential biomarkers for pregnancy-related complications. This study comprehensively demonstrates the cytotoxic effects of propylparaben on human trophoblast cells, notably through apoptosis induction and cell cycle disruption, thereby providing crucial insights into its potential risks for reproductive health.

Common and differential EEG microstate of major depressive disorder patients with and without response to rTMS treatment.

OBJECTIVE: Repetitive transcranial magnetic stimulation (rTMS) has recently emerged as a novel treatment option for patients with major depressive disorder (MDD), but clinical observations reveal variability in patient's responses to rTMS. Therefore, it is clinically significant to investigate the baseline neuroimaging differences between patients with (Responder) and without (NonResponder) response to rTMS treatment and predict rTMS treatment outcomes based on baseline neuroimaging data. METHOD: Baseline resting-state EEG data and Beck Depression Inventory (BDI) were collected from 74 rTMS Responder, 43 NonResponder, and 47 matched healthy controls (HC). EEG microstate analysis was applied to analyze common and differential microstate characteristics of Responder and NonResponder. In addition, the microstate temporal parameters were sent to four machine learning models to classify Responder from NonResponder. RESULT: There exists some common and differential EEG microstate characteristics for Responder and NonResponder. Specifically, compared to the HC group, both Responder and NonResponder exhibited a significant increase in the occurrence of microstate A. Only Responder showed an increase in the coverage of microstate A, occurrence of microstate D, transition probability (TP) from A to D, D to A, and C to A, and a decrease in the duration of microstates B and E, TP from A to B and C to B compared to HC. Only NonResponder exhibited a significant decrease in the duration of microstate D, TP from C to D, and an increase in the occurrence of microstate E, TP from C to E compared to HC. The primary differences between the Responder and NonResponder are that Responder had higher parameters for microstate D, TP from other microstates to D, and lower parameters for microstate E, TP from other microstates to E compared to NonResponder. Baseline parameters of microstate D showed significant correlation with Beck Depression Inventory (BDI) reduction rate. Additionally, these microstate features were sent to four machine learning models to predict rTMS treatment response and classification results indicate that an excellent predicting performance (accuracy = 97.35 %, precision = 96.31 %, recall = 100 %, F1 score = 98.06 %) was obtained when using AdaBoost model. These results suggest that baseline resting-state EEG microstate parameters could serve as robust indicators for predicting the effectiveness of rTMS treatment. CONCLUSION: This study reveals significant baseline EEG microstate differences between rTMS Responder, NonResponder, and healthy controls. Microstates D and E in baseline EEG can serve as potential biomarkers for predicting rTMS treatment outcomes in MDD patients. These findings may aid in identifying patients likely to respond to rTMS, optimizing treatment plans and reducing trial-and-error approaches in therapy selection.

Graphene-Based Virus Enrichment Protocol Increases the Detection Sensitivity of Human Norovirus in Strawberry and Oyster Samples.

Human noroviruses (HuNoVs), the most prevalent viral contaminant in food, account for a substantial proportion of nonbacterial gastroenteritis cases. Extensive work has been focused on the diagnosis of HuNoVs in clinical samples, whereas the availability of sensitive detection methods for their detection in food is lacking. Here, we developed a virus enrichment approach utilizing graphene-based nanocomposites (CTAB-rGO-Fe3O4) that does not rely on large instruments and is suitable for on-site food pretreatment. The recovery efficiency of the developed virus enrichment procedure for serially diluted GII.4 norovirus ranged from 10.06 to 72.67% in strawberries and from 2.66 to 79.65% in oysters. Furthermore, we developed a real-time recombinase polymerase amplification (real-time RPA) assay, which can detect as low as 1.22 genome copies µL-1 of recombinant plasmid standard and has no cross-reactivity with genomes of astrovirus, rotavirus, adenovirus, and MS2 bacteriophage. Notably, the combined virus enrichment and real-time RPA detection assay enhanced the detection limits to 2.84 and 37.5 genome copies g-1 in strawberries and oysters, respectively, compared to those of qPCR. Our strategy, the graphene-based virus enrichment method combined with real-time RPA, presents a promising tool for sensitively detecting HuNoVs in food samples.

Enzyme-armed nanocleaner provides superior detoxification against organophosphorus compounds via a dual-action mechanism.

By inhibiting acetylcholinesterase (AChE) activity, organophosphate compounds (OPs) can quickly cause severe injury to the nervous system and death, making it extremely difficult to rescue victims after OP exposure. However, it is quite challenging to construct scavengers that neutralize and eliminate these harmful chemical agents promptly in the blood circulation system. Herein, we report an enzyme-armed biomimetic nanoparticle that enables a 'targeted binding and catalytic degradation' action mechanism designed for highly efficient in vivo detoxification (denoted as 'Nanocleaner'). Specifically, the resulting Nanocleaner is fabricated with polymeric cores camouflaged with a modified red blood cell membrane (RBC membrane) that is inserted with the organophosphorus hydrolase (OPH) enzyme. In such a subtle construct, Nanocleaner inherits abundant acetylcholinesterase (AChE) on the surface of the RBC membrane, which can specifically lure and neutralize OPs through biological binding. The OPH enzyme on the membrane surface breaks down toxicants catalytically. The in vitro protective effects of Nanocleaner against methyl paraoxon (MPO)-induced inhibition of AChE activity were validated using both preincubation and competitive regimens. Furthermore, we selected the PC12 neuroendocrine cell line as an experimental model and confirmed the cytoprotective effects of Nanocleaner against MPO. In mice challenged with a lethal dose of MPO, Nanocleaner significantly reduces clinical signs of intoxication, rescues AChE activity and promotes the survival rate of mice challenged with lethal MPO. Overall, these results suggest considerable promise of enzyme-armed Nanocleaner for the highly efficient removal of OPs for clinical treatment.

CRISPR/Cas13a analysis based on NASBA amplification for norovirus detection.

Human norovirus (HuNoV) is a leading cause of foodborne diseases worldwide, making rapid and accurate detection crucial for prevention and control. In recent years, the CRISPR/Cas13a system, known for its single-base resolution in RNA recognition and unique collateral cleavage activity, is particularly suitable for sensitive and rapid RNA detection. However, isothermal amplification-based CRISPR/Cas13 assays often require an external transcription step, complicating the detection process. In our study, an efficient diagnostic technique based on the NASBA/Cas13a system was established to identify conserved regions at the ORF1-ORF2 junction of norovirus. The RNA amplification techniques [Nucleic Acid Sequence-Based Amplification (NASBA)] integrates reverse transcription and transcription steps, enabling sensitive, accurate, and rapid enrichment of low-abundance RNA. Furthermore, the CRISPR/Cas13a system provides secondary precise recognition of the amplified products, generating a fluorescence signal through its activated accessory collateral cleavage activity. We optimized the reaction kinetics parameters of Cas13a and achieved a detection limit as low as 51pM. The conditions for the cascade reaction involving CRISPR analysis and RNA amplification were optimized. Finally, we validated the reliability and accuracy of the NASBA/Cas13a method by detecting norovirus in shellfish, achieving results comparable to qRT-PCR in a shorter time and detecting viral loads as low as 10 copies/µL.

Functional poly(e-caprolactone)/SerMA hybrid dressings with dimethyloxalylglycine-releasing property improve cutaneous wound healing.

Medical dressings with multifunctional properties, including potent regeneration capability and good biocompatibility, are increasingly needed in clinical practice. In this study, we reported a novel hybrid wound dressing (PCL/SerMA/DMOG) that combines electrospun PCL membranes with DMOG-loaded methacrylated sericin (SerMA) hydrogel. In such a design, DMOG molecules are released from the hybrid dressing in a sustained mannerin vitro. A series ofin vitroassays demonstrated that DMOG-loaded hybrid dressing has multiple biological functions, including promotion of human umbilical vein endothelial cells proliferation and migration,in vitrovascularization, and the generation of intracellular NO. When applied to the cutaneous wound, the PCL/SerMA/DMOG dressing significantly accelerated wound closure and tissue regeneration by promoting angiogenesis in the wound area, collagen deposition, and cell proliferation within the wound bed. These results highlight the potential clinical application of PCL/SerMA/DMOG hybrid dressings as promising alternatives for accelerating wound healing via improved biocompatibility and angiogenesis amelioration.

Insights into preeclampsia: a bioinformatics approach to deciphering genetic and immune contributions.

Background: Preeclampsia (PE) is a global pregnancy concern, characterized by hypertension with an unclear etiology. This study employs Mendelian randomization (MR) and single-cell RNA sequencing (scRNA-seq) to clarify its genetic and molecular roots, offering insights into diagnosis and treatment avenues. Methods: We integrated PE-specific genome-wide association study (GWAS) data, expression and protein quantitative trait loci (eQTL and pQTL) data, and single-cell data from peripheral blood mononuclear cells (PBMCs). We identified highly variable genes using single-cell information and employed MR to determine potential causality. We also combined pQTL and GWAS data, discerned genes positively associated with PE through scRNA-seq, and leveraged the Enrichr platform to unearth drug-gene interactions. Results: Our scRNA-seq pinpointed notable cell type distribution variances, especially in T helper cells (Th cells), between PE and control groups. We unveiled 591 highly variable genes and 6 directly PE-associated genes. Although MR revealed correlations with PE risk, pQTL analysis was inconclusive due to data constraints. Using DSigDB, 93 potential therapeutic agents, like Retinoic acid targeting core genes (IFITM3, NINJ1, COTL1, CD69, and YWHAZ), emerged as prospective multi-target treatments. Conclusion: Utilizing MR and scRNA-seq, this study underscores significant cellular disparities, particularly in Th cells, and identifies crucial genes related to PE. Despite some limitations, these genes have been revealed in PE's underlying mechanism. Potential therapeutic agents, such as Retinoic acid, suggest promising treatment pathways.

Investigating cortical complexity and connectivity in rats with schizophrenia.

Background: The above studies indicate that the SCZ animal model has abnormal gamma oscillations and abnormal functional coupling ability of brain regions at the cortical level. However, few researchers have focused on the correlation between brain complexity and connectivity at the cortical level. In order to provide a more accurate representation of brain activity, we studied the complexity of electrocorticogram (ECoG) signals and the information interaction between brain regions in schizophrenic rats, and explored the correlation between brain complexity and connectivity. Methods: We collected ECoG signal from SCZ rats. The frequency domain and time domain functional connectivity of SCZ rats were evaluated by magnitude square coherence and mutual information (MI). Permutation entropy (PE) and permutation Lempel-Ziv complexity (PLZC) were used to analyze the complexity of ECoG, and the relationship between them was evaluated. In addition, in order to further understand the causal structure of directional information flow among brain regions, we used phase transfer entropy (PTE) to analyze the effective connectivity of the brain. Results: Firstly, in the high gamma band, the complexity of brain regions in SCZ rats is higher than that in normal rats, and the neuronal activity is irregularity. Secondly, the information integration ability of SCZ rats decreased and the communication of brain network information was hindered at the cortical level. Finally, compared with normal rats, the causal relationship between brain regions of SCZ rats was closer, but the information interaction center was not clear. Conclusion: The above findings suggest that at the cortical level, complexity and connectivity are valid biomarkers for identifying SCZ. This bridges the gap between peak potentials and EEG. This may help to understand the pathophysiological mechanisms at the cortical level in schizophrenics.

Visual Feedback Gain Modulates the Activation of Task-Related Networks and the Suppression of Non-Task Networks During Precise Grasping.

Visual feedback gain is a crucial factor influencing the performance of precision grasping tasks, involving multiple brain regions of the visual motor system during task execution. However, the dynamic changes in brain network during this process remain unclear. The aim of this study is to investigate the impact of changes in visual feedback gain during precision grasping on brain network dynamics. Sixteen participants performed precision grip tasks at 15% of MVC under low (0.1°), medium (1°), and high (3°) visual feedback gain conditions, with simultaneous recording of EEG and right-hand precision grip data during the tasks. Utilizing electroencephalogram (EEG) microstate analysis, multiple parameters (Duration, Occurrence, Coverage, Transition probability(TP)) were extracted to assess changes in brain network dynamics. Precision grip accuracy and stability were evaluated using root mean square error(RMSE) and coefficient of variation(CV) of grip force. Compared to low visual feedback gain, under medium/high gain, the Duration, Occurrence, and Coverage of microstates B and D increase, while those of microstates A and C decrease. The Transition probability from microstates A, C, and D to B all increase. Additionally, RMSE and CV of grip force decrease. Occurrence and Coverage of microstates B and C are negatively correlated with RMSE and CV. These findings suggest that visual feedback gain affects the brain network dynamics during precision grasping; moderate increase in visual feedback gain can enhance the accuracy and stability of grip force, whereby the increased Occurrence and Coverage of microstates B and C contribute to improved performance in precision grasping. Our results play a crucial role in better understanding the impact of visual feedback gain on the motor control of precision grasping.

CLICK-FLISA Based on Metal-Organic Frameworks for Simultaneous Detection of Fumonisin B1 (FB1) and Zearalenone (ZEN) in Maize.

Mycotoxins are secondary products produced primarily by fungi and are pathogens of animals and cereals, not only affecting agriculture and the food industry but also causing great economic losses. The development of rapid and sensitive methods for the detection of mycotoxins in food is of great significance for livelihood issues. This study employed an amino-functionalized zirconium luminescent metal-organic framework (LOF) (i.e., UiO-66-NH2). Click chemistry was utilized to assemble UiO-66-NH2 in a controlled manner, generating LOF assemblies to serve as probes for fluorescence-linked immunoassays. The proposed fluoroimmunoassay method for Zearalenone (ZEN) and Fumonisin B1 (FB1) detection based on the UiO-66-NH2 assembled probe (CLICK-FLISA) afforded a linear response range of 1-20 µmol/L for ZEN, 20 µmol/L for FB1, and a very low detection limit (0.048-0.065 µmol/L for ZEN; 0.048-0.065 µmol/L for FB1). These satisfying results demonstrate promising applications for on-site quick testing in practical sample analysis. Moreover, the amino functionalization may also serve as a modification strategy to design luminescent sensors for other food contaminants.

A colorimetric/electrochemical microfluidic biosensor using target-triggered DNA hydrogels for organophosphorus detection.

Organophosphorus compounds are widely distributed and highly toxic to the environment and living organisms. The current detection of organophosphorus compounds is based on a single-mode method, which makes it challenging to achieve good portability, accuracy, and sensitivity simultaneously. This study designed a multifunctional microfluidic chip to develop a dual-mode biosensor employing a DNA hydrogel as a carrier and aptamers as recognition probes for the colorimetric/electrochemical detection of malathion, an organophosphorus compound. The biosensor balanced portability and stability by combining a microfluidic chip and target-triggered DNA hydrogel-sensing technologies. Moreover, the biosensor based on target-triggered DNA hydrogel modified microfluidic developed in this study exhibited a dual-mode response to malathion, providing both colorimetric and electrochemical signals. The colorimetric mode enables rapid visualization and qualitative detection and, when combined with a smartphone, allows on-site quantitative analysis with a detection limit of 56 nM. The electrochemical mode offers a broad linear range (0.01-3000 µM) and high sensitivity (a limit of detection of 5 nM). The two modes could validate each other and improve the accuracy of detection. The colorimetric/electrochemical dual-mode biosensor based on target-triggered DNA hydrogel modified microfluidic chip offers a portable, simple, accurate, and sensitive strategy for detecting harmful environmental and food substances.

Micro-/nanostructures for surface-enhanced Raman spectroscopy: Recent advances and perspectives.

Surface-enhanced Raman spectroscopy (SERS) has great potential for the analysis of molecules adsorbed on metals with rough surfaces or substrates with micro-/nanostructures. Plasmonic coupling between metal nanoparticles and the morphology of the rough metal surface can produce "hot spots" that enhance Raman scattering by adsorbed molecules, typically at micro- to nanomolar concentrations, although high enhancement factors can also facilitate single-molecule detection. This phenomenon is widely applicable for chemical analysis and sensing in various fields. In this review, the latest research progress on SERS micro-/nanosensors is evaluated, and the sensors are classified according to their individual functions. Furthermore, the design principles and working mechanisms of reported SERS-active micro-/nanostructured substrates are analyzed, and the design features adopted to overcome the difficulties associated with precision detection are explored. Finally, challenges and directions for future development in this field are discussed. This review serves as a design guide for novel SERS-active substrates.

Transient paper-based electrochemical biosensor Fabricated by superadditive Cu-TCPP(Fe)/Mxene for Multipathway non-invasive, highly sensitive detection of Bodily metabolites.

Current advances in non-invasive fluid diagnostics highlight unique benefits for monitoring metabolic diseases. However, the low concentrations and complex compositions of biomarkers in fluids such as sweat, urine, and saliva impose stringent demands on the sensitivity and stability of detection technologies. Here, we developed a high-sensitivity, low-cost instantaneous electrochemical sensor based on the superadditive effect mechanism of Cu-TCPP(Fe)/Mxene (MMs Paper-ECL Sensor), which has been successfully applied for the simultaneous real-time detection of glucose and uric acid. Strong interfacial interactions between Mxene and Cu-TCPP(Fe) were revealed through precise simulation calculations and multi-dimensional characterization analysis, significantly enhancing the sensor's electrocatalytic performance and reaction kinetics. Experimentally, this exceptional electrocatalytic activity was demonstrated in its unprecedented high sensitivity and wide linear detection range for glucose and uric acid, with a non-invasive linear range from 0.001 nM to 5 mM, 0.025 nM-5 mM, detection limits as low as 1.88 aM and 5.80 pM, and stability extending up to 100 days. This represents not only a breakthrough in sensitivity and stability but also provides an effective, low-cost solution that overcomes the limitations of existing electronic devices, enabling multi-channel simultaneous detection. The universality of this sensor holds vast potential for application in the field of non-invasive fluid diagnostics.

A smartphone-based fluorescent biosensor with metal-organic framework biocomposites and cotton swabs for the rapid determination of tetrodotoxin in seafood.

BACKGROUND: Tetrodotoxin (TTX) is a potent neurovirulent marine biotoxin that is present in puffer fish and certain marine animals. It is capable of causing severe neurotoxic symptoms and even death when consumed through contaminated seafood. Due to its high toxicity, developing an effective assay for TTX determination in seafood has significant benefits for food safety and human health. Currently, it remains challenging to achieve on-site determination of TTX in seafood. To facilitate mass on-site assays, more affordable technologies utilizing accessible equipment that require no skilled personnel are needed. RESULTS: A smartphone-based portable fluorescent biosensor is proposed for TTX determination by using metal-organic framework (MOF) biocomposites and cotton swabs. Oriented antibody (Ab)-decorated and fluorescent quantum dot (QD)-loaded MOF biocomposites (QD@MOF*Ab) are rapidly synthesized for binding targets and fluorescent responses by utilizing the tunability of zinc-based MOF. Moreover, facile Ab-immobilized household cotton swabs are utilized as TTX capture tools. TTX forms sandwich immune complexes with QD@MOF*Ab probes, achieving signal amplification. These probes are excited by a portable device to generate bright fluorescent signals, which can be detected by the naked eye, and TTX quantitative results are obtained using a smartphone. When observed with the naked eye, the limit of detection (LOD) is 0.4 ng/mL, while intelligent quantitation presents an LOD of 0.13 ng/mL at logarithmic concentrations of 0.2-400 ng/mL. SIGNIFICANCE: This biosensor is convenient to use, and an easy-to-operate analysis is completed within 15 min, thus demonstrating excellent performance in terms of detection speed and portability. Furthermore, it successfully determines TTX contents in puffer fish and clam samples, demonstrating its potential for monitoring seafood. Herein, this work provides a favorable rapid sensing platform that is easily portable.

Construction and validation of a deep learning prognostic model based on digital pathology images of stage III colorectal cancer.

BACKGROUND: TNM staging is the main reference standard for prognostic prediction of colorectal cancer (CRC), but the prognosis heterogeneity of patients with the same stage is still large. This study aimed to classify the tumor microenvironment of patients with stage III CRC and quantify the classified tumor tissues based on deep learning to explore the prognostic value of the developed tumor risk signature (TRS). METHODS: A tissue classification model was developed to identify nine tissues (adipose, background, debris, lymphocytes, mucus, smooth muscle, normal mucosa, stroma, and tumor) in whole-slide images (WSIs) of stage III CRC patients. This model was used to extract tumor tissues from WSIs of 265 stage III CRC patients from The Cancer Genome Atlas and 70 stage III CRC patients from the Sixth Affiliated Hospital of Sun Yat-sen University. We used three different deep learning models for tumor feature extraction and applied a Cox model to establish the TRS. Survival analysis was conducted to explore the prognostic performance of TRS. RESULTS: The tissue classification model achieved 94.4 % accuracy in identifying nine tissue types. The TRS showed a Harrell's concordance index of 0.736, 0.716, and 0.711 in the internal training, internal validation, and external validation sets. Survival analysis showed that TRS had significant predictive ability (hazard ratio: 3.632, p = 0.03) for prognostic prediction. CONCLUSION: The TRS is an independent and significant prognostic factor for PFS of stage III CRC patients and it contributes to risk stratification of patients with different clinical stages.

Synthetic biology for the food industry: advances and challenges.

As global environmental pollution increases, climate change worsens, and population growth continues, the challenges of securing a safe, nutritious, and sustainable food supply have become enormous. This has led to new requirements for future food supply methods and functions. The use of synthetic biology technology to create cell factories suitable for food industry production and renewable raw material conversion into: important food components, functional food additives, and nutritional chemicals, represents an important method of solving the problems faced by the food industry. Here, we review the recent progress and applications of synthetic biology in the food industry, including alternatives to: traditional (artificial pigments, meat, starch, and milk), functional (sweeteners, sugar substitutes, nutrients, flavoring agents), and green (green fiber, degradable packing materials, green packaging materials and food traceability) foods. Furthermore, we discuss the future prospects of synthetic biology-based applications in the food industry. Thus, this review may serve as a reference for research on synthetic biology in the: food safety, food nutrition, public health, and health-related fields.

Carboxyl-functionalized two-dimensional MXene-Au nanocomposites were prepared as SERS substrates for the detection of melamine in dairy products.

In the present study, we address the limitations of conventional surface-enhanced Raman scattering (SERS) techniques for sensitive and stable detection of melamine in food products, especially dairy. To overcome these challenges, we developed a novel SERS-active substrate by incorporating gold nanoparticles (AuNPs) onto carboxyl-functionalized two-dimensional (2D) MXene material doped with nitrides, specifically Au-Ti2N-COOH. Our strategy leverages the unique physicochemical properties of MXene, a class of atomically thin, 2D transition metal carbides/nitrides, with tunable surface functionalities. By modifying the MXene surface with AuNPs and introducing carboxyl groups (-COOH), we successfully enhanced the interaction between the substrate and melamine molecules. The carboxyl groups form hydrogen bonds with the amino groups on the melamine's triazine ring, facilitating the adsorption of melamine molecules within the 'hotspot' regions responsible for SERS signal amplification. A series of characterization methods were used to confirm the successful synthesis of Au-Ti2N-COOH composites.Using Au-Ti2N-COOH as the SERS substrate, we detected melamine in spiked dairy product samples with significantly enhanced sensitivity and stability compared to nitride-doped MXene alone. The detection limit in liquid milk stands at 3.7008 µg kg-1, with spike recovery rates ranging from 99.84% to 107.55% and an approximate RSD of 5%. This work demonstrates the effectiveness of our approach in designing a label-free, rapid, and robust SERS platform for the accurate quantitation of melamine contamination in food, thereby mitigating health risks associated with melamine adulteration.

Rapid detection of melamine by DNA Walker mediated SERS sensing technique based on signal amplification function.

A new method is proposed for detecting typical melamine dopants in food using surface-enhanced Raman scattering (SERS) biosensing technology. Melamine specific aptamer was used as the identification probe, and gold magnets (AuNPs@MNPs) and small gold nanoparticles (AuNPs@MBA) were used as the basis for Raman detection. The Raman signal of the detection system can directly detect melamine quantitatively. Under optimized conditions, the detection of melamine was carried out in the low concentration range of 0.001-500 mg/kg, the enhancement factor (EF) was 2.3 × 107, and the detection limit was 0.001 mg/kg. The method is sensitive and rapid, and can be used for the rapid detection of melamine in the field environment.

Influencing factors of corticomuscular coherence in stroke patients.

Stroke, also known as cerebrovascular accident, is an acute cerebrovascular disease with a high incidence, disability rate, and mortality. It can disrupt the interaction between the cerebral cortex and external muscles. Corticomuscular coherence (CMC) is a common and useful method for studying how the cerebral cortex controls muscle activity. CMC can expose functional connections between the cortex and muscle, reflecting the information flow in the motor system. Afferent feedback related to CMC can reveal these functional connections. This paper aims to investigate the factors influencing CMC in stroke patients and provide a comprehensive summary and analysis of the current research in this area. This paper begins by discussing the impact of stroke and the significance of CMC in stroke patients. It then proceeds to elaborate on the mechanism of CMC and its defining formula. Next, the impacts of various factors on CMC in stroke patients were discussed individually. Lastly, this paper addresses current challenges and future prospects for CMC.

Different metal (Mn, Fe, Co, Ni, and Zr) decorated Cu/CeO2 catalysts for efficient CO oxidation in a rich CO2/H2 atmosphere.

In this work, CuM/CeO2 (M = Mn, Fe, Co, Ni, and Zr) catalysts with a low Cu content of 1 wt% were purposely designed and prepared using the co-impregnation method. The samples were characterized using various techniques (TG-DTA, XRD, N2-adsorption/desorption measurements, H2-TPR, XPS and Raman spectroscopy) and CO preferential oxidation (CO-Prox) under H2/CO2-rich conditions was performed. The results have shown that enhanced catalytic performance was achieved upon the introduction of Mn, Co and Ni, and little impact was observed with Zr doping, but Fe showed a negative effect, as compared with the Cu/CeO2 catalyst. Characterization data revealed that the M doping strongly changed the surface composition, revealing the decreased Cu/Ce ratios on the surface, which could be accounted for by the formation of more M/Cu-O-Ce solid solution, or strong Cu-M interactions. When Mn was used, the obtained CuMn/CeO2 catalyst revealed the highest concentration of the oxygen vacancies and Ce3+ ions, which could be correlated well with its superior catalytic performance. Compared with the Cu/CeO2 catalyst, the CO conversion rate increased by 24.7% at a low temperature of 90 °C over the CuMn/CeO2 catalyst. At 130 °C, the maximum CO conversion was 94.7% and the CO2 selectivity was 78.9%. Conversely, the Fe doped Cu/CeO2 catalyst demonstrated the poorest catalytic activity, which was due to the blockage effect of Fe species on Cu showing a high Fe/Cu ratio of 1.9 on the surface.