In this study we propose a simple and sensitive colorimetric aptasensor for the quantitative analysis of abrin by using catalytic AuNPs for the first time. AuNPs possess the peroxidase-like activity ...that can catalyse 3,3,5,5-tetramethylbenzidine (TMB) in the presence of H2O2, leading to color change of the solution. It is interesting to find that the peroxidase-like activity of AuNPs can be improved by surface activation with a target-specific aptamer. However, with a target molecule, the aptamer is desorbed from the AuNPs surface, resulting in a decrease of the catalytic abilities of AuNPs. The color change of the solution is relevant to the target concentration, and this can be judged by the naked eye and monitored by using a UV-vis spectrometer. The linear range for the current analytical system was from 0.2 nM to 17.5 nM. The corresponding limit of detection (LOD) was 0.05 nM. Some other proteins such as thrombin (Th), glucose oxidase (GOx), and bovine serum albumin (BSA) all had a negligible effect on the determination of abrin. Furthermore, several practical samples spiked with abrin were analyzed using the proposed method with excellent recoveries. This aptamer-based colorimetric biosensor is superior to other conventional methods owing to its simplicity, low cost, and high sensitivity.
A novel fluorometric assay for acetylcholinesterase and its inhibitor detection based on the in situ formation of fluorescent copper nanoparticles is proposed.
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•A novel fluorescent ...assay for AChE and its inhibitor detection has been developed.•This novel assay is based on the fluorescent copper nanoparticles.•This assay shows high sensitivity and selectivity for AChE activity detection.
The poly(thymine) (poly T) can effectively template the in situ formation of copper nanoparticles (CuNPs) within several minutes under ambient conditions, offering great potential as fluorescence probe for biochemical analysis without complicated modifications. However, the exploration of poly T-templated CuNPs (poly T-CuNPs) for biochemical applications is still at its very early stage. Herein, a novel fluorescent assay has been developed for acetylcholinesterase (AChE) and its inhibitor detection based on poly T-CuNPs. In the absence of AChE, the high affinity between Cu2+ and thymine leads to the formation of fluorescent CuNPs. In the presence of AChE, the fluorescence of poly T-CuNPs is quenched based on the reaction between Cu2+ and thiocholine generating from the hydrolysis of ATCh by AChE. This detection assay is simple without the requirement for complex labeling of probe DNA and the multiple preparation procedure of fluorescent compounds. The detection assay is highly sensitive for sensing AChE in the concentration ranging from 0.11 to 2.78mUmL−1 with a detection limit of 0.05mUmL−1 and is feasible for screening AChE inhibitor. This method paves a new way for exploring the biosensing applications of the poly T-CuNPs.
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It’s almost hardly to realize the large-scale practical application of fuel cells if the costly noble metal-based electrocatalysts for oxygen reduction reaction (ORR) cannot be ...replaced by other efficient, stable, and low-cost non-precious metal or even metal-free ORR electrocatalysts. Herein, we report the novel design and synthesis of N and S dual-doped hierarchical micro/mesoporous carbon (NS-MC) foams via high temperature treatment of polyaniline coated sulfur sphere composite without any side products. The highlight of our method lies in its environmental concept of green synthesis and simplicity for no use of toxic gas (NH3 or H2S) or templates (SiO2 or MgO). The main focus of this research is to develop a high-performance metal-free ORR electrocatalyst as well as to gain insight into the synergistic effects originating from multiple-element doping on ORR performance. It is found that much graphitic-N and thiophene-S binding configurations formed for NS-MC foams at 1000°C, which shows excellent electrocatalytic activity (high onset potential (0.051V vs. Ag/AgCl (sat.KCl)), large diffusion-limiting current density (5.61mAcm−2 at 1600rpm) and kinetic current density (22.22mAcm−2 at −0.25V)), high selectivity towards methanol and long durability compared to commercial Pt/C with a nearly four-electron transfer passway when they are employed as metal-free catalyst for ORR. Besides, the desired NS-MC1000 shows a strong amperometric response towards ethanol indicating its potential application as an anode metal-free electrocatalyst in the alkaline direct ethanol fuel cell.
Extracellular vesicles (EVs) are important for cell-to-cell communication in animals. EVs also play important roles in plant-microbe interactions, but the underlying mechanisms remain elusive. Here, ...proteomic analyses of EVs from the soybean (Glycine max) root rot pathogen Phytophthora sojae identify the tetraspanin family proteins PsTET1 and PsTET3, which are recognized by Nicotiana benthamiana to trigger plant immune responses. Both proteins are required for the full virulence of P. sojae. The large extracellular loop (EC2) of PsTET3 is the key region recognized by N. benthamiana and soybean cells in a plant receptor-like kinase NbSERK3a/b dependent manner. TET proteins from oomycete and fungal plant pathogens are recognized by N. benthamiana thus inducing immune responses, whereas plant-derived TET proteins are not due to the sequence divergence of sixteen amino acids at the C-terminal of EC2. This feature allows plants to distinguish self and non-self EVs to trigger active defense responses against pathogenic eukaryotes.
Lung cancer is a common comorbidity of heart failure (HF). The early identification of the risk factors for lung cancer in patients with HF is crucial to early diagnosis and prognosis. Furthermore, ...oxidative stress and immune responses are the two critical biological processes shared by HF and lung cancer. Therefore, our study aimed to select the core genes in HF and then investigate the potential mechanisms underlying HF and lung cancer, including oxidative stress and immune responses through the selected genes.
Differentially expressed genes (DEGs) were analyzed for HF using datasets extracted from the Gene Expression Omnibus database. Functional enrichment analysis was subsequently performed. Next, weighted gene co-expression network analysis was performed to select the core gene modules. Support vector machine models, the random forest method, and the least absolute shrinkage and selection operator (LASSO) algorithm were applied to construct a multigene signature. The diagnostic values of the signature genes were measured using receiver operating characteristic curves. Functional analysis of the signature genes and immune landscape was performed using single-sample gene set enrichment analysis. Finally, the oxidative stress-related genes in these signature genes were identified and validated
in lung cancer cell lines.
The DEGs in the GSE57338 dataset were screened, and this dataset was then clustered into six modules using weighted gene co-expression network analysis; MEblue was significantly associated with HF (cor =
0.72, p < 0.001). Signature genes including extracellular matrix protein 2 (ECM2), methyltransferase-like 7B (METTL7B), meiosis-specific nuclear structural 1 (MNS1), and secreted frizzled-related protein 4 (SFRP4) were selected using support vector machine models, the LASSO algorithm, and the random forest method. The respective areas under the curve of the receiver operating characteristic curves of ECM2, METTL7B, MNS1, and SFRP4 were 0.939, 0.854, 0.941, and 0.926, respectively. Single-sample gene set enrichment analysis revealed significant differences in the immune landscape of the patients with HF and healthy subjects. Functional analysis also suggested that these signature genes may be involved in oxidative stress. In particular, METTL7B was highly expressed in lung cancer cell lines. Meanwhile, the correlation between METTL7B and oxidative stress was further verified using flow cytometry.
We identified that ECM2, METTL7B, MNS1, and SFRP4 exhibit remarkable diagnostic performance in patients with HF. Of note, METTL7B may be involved in the co-occurrence of HF and lung cancer by affecting the oxidative stress immune responses.
Electrochemical reduction and electrodeposition are two effective methods for the preparation of new nanomaterials for electrochemical sensing. In this work, the reduced graphene oxide‐nickel ...nanoparticles composite (RGO‐NiNPs) was synthesized using both methods mentioned above. The fabrication process was simple and easily performed. Then, the RGO‐NiNPs composite was characterized by SEM, EDS, and XRD. Furthermore, for the strong catalytic ability of the high‐valent oxyhydroxide species (NiOOH) formed in alkaline media, the composite was used as the matrix for nonenzymatic detection of glucose. Comparing with NiNPs modified glassy carbon electrode (NiNPs/GCE), the RGO‐NiNPs/GCE showed better sensitivity and stability. A low detection limit of 0.1 µM with a wide linear range from 2 µM to 2.1 mM (R=0.996) was obtained.
Industrial robots are being widely applied to machining operations, and are gradually becoming competitive with traditional CNC machining centers. Obtaining accurate stiffness values of robotic ...joints is the foundation for deflections compensation in case of large cutting forces. A number of factors influence the accuracy of joint stiffness identification, especially robotic posture. This paper proposes a robust and accurate method for selecting suitable postures in the joint stiffness identification. The identification process of the joint stiffness matrix is presented, an index considering both the dexterity and the condition number of the observation matrix is then developed, and the procedure for postures selection based on it is provided. The results of simulations and experiments show that the proposed method is more robust and accurate than classical method.
A controllable silver nanoparticle aggregate system has been synthesized by adding different amounts of ethanol to cetyltrimethylammonium bromide (CTAB) capped silver nanoparticles (Ag-nps), which ...could be used as highly efficient surface-enhanced Raman scattering (SERS) active substrates. This ethanol-induced aggregation can be attributed to preferential dissolution of CTAB into ethanol, which leads a partial removal of the protective CTAB layer on Ag-nps. The optical and morphological properties of these aggregates under various volumes of ethanol were explored via UV−vis spectroscopy and atomic force microscopy. Two common probe molecules, Rhodamine 6G (R6G) and 4-aminothiophenol (4-ATP) were used for testing the SERS activity on these substrates at very low concentrations. It was found that the SERS enhancement ability is dependent on the ethanol volume used. The SERS enhancement factors of 4-ATP were estimated to be as large as 8.1 × 108 for b2 vibration modes and 6.8 × 106 for a1 vibration modes. Good stability of the substrates was demonstrated by measuring the Raman activity with time. The optimized SERS-active substrate with the largest enhancement ability shown in this study could be used to detect double-strand DNA. The great advantage for this SERS-based DNA detection is that a dye label is not needed. It showed the potential of this Ag-nps aggregate system as a convenient and powerful SERS-active substrate for DNA detection.
Abstract
Background
Among all types of mental disorders, individuals with schizophrenia exhibit the highest frequency of aggressive behavior. This disrupts the healthcare environment and poses ...threats to family life and social harmony. Present approaches fail to identify individuals with schizophrenia who are predisposed to aggressive behavior. In this study, we aimed to construct a risk prediction model for aggressive behavior in stable patients with schizophrenia, which may facilitate early identification of patients who are predisposed to aggression by assessing relevant factors, enabling the management of high-risk groups to mitigate and prevent aggressive behavior.
Methods
A convenience sample of stable inpatients with schizophrenia were selected from Daqing Municipal Third Hospital and Chifeng Municipal Anding Hospital from March 2021 to July 2023. A total of 429 patients with stable schizophrenia who met the inclusion criteria were included. A survey was conducted with them using a questionnaire consisting of general information questionnaire, Positive and Negative Symptom Scale, Childhood Trauma Questionnaire-Short Form, Connor-Davidson Resilience Scale and Self-esteem Scale. Patients enrolled in this study were divided into aggressive and non-aggressive groups based on whether there was at least one obvious and recorded personal attack episode (including obvious wounding and self-injurious behavior) following diagnosis. Binary Logistic regression was used to determine the influencing factors, and R software was used to establish a nomogram model for predicting the risk of aggressive behavior. Bootstrap method was used for internal validation of the model, and the validation group was used for external validation. C statistic and calibration curve were used to evaluate the prediction performance of the model.
Results
The model variables included Age, Duration of disease, Positive symptom, Childhood Trauma, Self-esteem and Resilience. The AUROC of the model was 0.790 (95% CI:0.729–0.851), the best cutoff value was 0.308; the sensitivity was 70.0%; the specificity was 81.4%; The C statistics of internal and external validation were 0.759 (95%CI:0.725–0.814) and 0.819 (95%CI:0.733–0.904), respectively; calibration curve and Brier score showed good fit.
Conclusions
The prediction model has a good degree of discrimination and calibration, which can intuitively and easily screen the high risk of aggressive behavior in stable patients with schizophrenia, and provide references for early screening and intervention.
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