Individualized prediction of anxiety and depressive symptoms using gray matter volume in a non-clinical population.

Machine learning is an emerging tool in clinical psychology and neuroscience for the individualized prediction of psychiatric symptoms. However, its application in non-clinical populations is still in its infancy. Given the widespread morphological changes observed in psychiatric disorders, our study applies five supervised machine learning regression algorithms-ridge regression, support vector regression, partial least squares regression, least absolute shrinkage and selection operator regression, and Elastic-Net regression-to predict anxiety and depressive symptom scores. We base these predictions on the whole-brain gray matter volume in a large non-clinical sample (n = 425). Our results demonstrate that machine learning algorithms can effectively predict individual variability in anxiety and depressive symptoms, as measured by the Mood and Anxiety Symptoms Questionnaire. The most discriminative features contributing to the prediction models were primarily located in the prefrontal-parietal, temporal, visual, and sub-cortical regions (e.g. amygdala, hippocampus, and putamen). These regions showed distinct patterns for anxious arousal and high positive affect in three of the five models (partial least squares regression, support vector regression, and ridge regression). Importantly, these predictions were consistent across genders and robust to demographic variability (e.g. age, parental education, etc.). Our findings offer critical insights into the distinct brain morphological patterns underlying specific components of anxiety and depressive symptoms, supporting the existing tripartite theory from a neuroimaging perspective.

A flexible electrode Array for genetic transfection of different layers of the retina by electroporation.

Electroporation (in which the permeability of a cell membrane is increased transiently by exposure to an appropriate electric field) has exhibited great potential of becoming an alternative to adeno-associated virus (AAV)-based retina gene delivery. Electroporation eliminates the safety concerns of employing exogenous viruses and exceeds the limit of AAV cargo size. Unfortunately, several concerns (e.g., relatively high electroporation voltage, poor surgical operability and a lack of spatial selectivity of retina tissue) have prevented electroporation from being approved for clinical application (or even clinical trials). In this study, a flexible micro-electrode array for retina electroporation (FERE) was developed for retina electroporation. A suitably shaped flexible substrate and well-placed micro-electrodes were designed to adapt to the retina curvature and generate an evenly distributed electric field on the retina with a significantly reduced electroporation voltage of 5 V. The FERE provided (for the first time) a capability of controlled gene delivery to the different structural layers of retina tissue by precise control of the distribution of the electrical field. After ensuring the surgical operability of the FERE on rabbit eyeballs, the FERE was verified to be capable of transfecting different layers of retina tissue with satisfactory efficiency and minimum damage. Our method bridges the technical gap between laboratory validation and clinical use of retina electroporation.

Reactivity of the ventromedial prefrontal cortex, but not the amygdala, to negative emotion faces predicts greed personality trait.

This study explored whether amygdala reactivity predicted the greed personality trait (GPT) using both task-based and resting-state functional connectivity analyses (ntotal = 452). In Cohort 1 (n = 83), task-based functional magnetic resonance imaging (t-fMRI) results from a region-of-interest (ROI) analysis revealed no direct correlation between amygdala reactivity to fearful and angry faces and GPT. Instead, whole-brain analyses revealed GPT to robustly negatively vary with activations in the right ventromedial prefrontal cortex (vmPFC), supramarginal gyrus, and angular gyrus in the contrast of fearful + angry faces > shapes. Moreover, task-based psychophysiological interaction (PPI) analyses showed that the high GPT group showed weaker functional connectivity of the vmPFC seed with a top-down control network and visual pathways when processing fearful or angry faces compared to their lower GPT counterparts. In Cohort 2, resting-state functional connectivity (rs-FC) analyses indicated stronger connectivity between the vmPFC seed and the top-down control network and visual pathways in individuals with higher GPT. Comparing the two cohorts, bilateral amygdala seeds showed weaker associations with the top-down control network in the high group via PPI analyses in Cohort 1. Yet, they exhibited distinct rs-FC patterns in Cohort 2 (e.g., positive associations of GPT with the left amygdala-top-down network FC but negative associations with the right amygdala-visual pathway FC). The study underscores the role of the vmPFC and its functional connectivity in understanding GPT, rather than amygdala reactivity.

Neuroanatomical and functional substrates of the hypomanic personality trait and its prediction on aggression

Hypomanic personality manifests a close link with several psychiatric disorders and its abnormality is a risk indicator for developing bipolar disorders. We systematically investigated the potential neuroanatomical and functional substrates underlying hypomanic personality trait (HPT) and its sub-dimensions (i.e., Social Vitality, Mood Volatility, and Excitement) combined with structural and functional imaging data as well as their corresponding brain networks in a large non-clinical sample across two studies (n = 464). Behaviorally, HPT, specifically Mood Volatility and Excitement, was positively associated with aggressive behaviors in both studies. Structurally, sex-specific morphological characteristics were further observed in the motor and top-down control networks especially for Mood Volatility, although HPT was generally positively associated with grey matter volumes (GMVs) in the prefrontal, temporal, visual, and limbic systems. Functionally, brain activations related to immediate or delayed losses were found to predict individual variability in HPT, specifically Social Vitality and Excitement, on the motor and prefrontal-parietal cortices. Topologically, connectome-based prediction model analysis further revealed the predictive role of individual-level morphological and resting-state functional connectivity on HPT and its sub-dimensions, although it did not reveal any links with general brain topological properties. GMVs in the temporal, limbic (e.g., amygdala), and visual cortices mediated the effects of HPT on behavioral aggression. These findings suggest that the imbalance between motor and control circuits may be critical for HPT and provide novel insights into the neuroanatomical, functional, and topological mechanisms underlying the specific temperament and its impacts on aggression. (AU)

Pan-cancer analysis of NFE2L2 mutations identifies a subset of lung cancers with distinct genomic and improved immunotherapy outcomes.

BACKGROUND: Mutations in the KEAP1-NFE2L2 signaling pathway were linked to increased tumorigenesis and aggressiveness. Interestingly, not all hotspot mutations on NFE2L2 were damaging; some even were activating. However, there was conflicting evidence about the association between NFE2L2 mutation and Nrf2-activating mutation and responsiveness to immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and other multiple cancers. METHODS: The study with the largest sample size (n = 49,533) explored the landscape of NFE2L2 mutations and their impact response/resistance to ICIs using public cohorts. In addition, the in-house WXPH cohort was used to validate the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC. RESULTS: In two pan-cancer cohorts, Nrf2-activating mutation was associated with higher TMB value compared to wild-type. We identified a significant association between Nrf2-activating mutation and shorter overall survival in pan-cancer patients and NSCLC patients but not in those undergoing ICIs treatment. Similar findings were obtained in cancer patients carrying the NFE2L2 mutation. Furthermore, in NSCLC and other cancer cohorts, patients with NFE2L2 mutation demonstrated more objective responses to ICIs than patients with wild type. Our in-house WXPH cohort further confirmed the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC. Lastly, decreased inflammatory signaling pathways and immune-depleted immunological microenvironments were enriched in Nrf2-activating mutation patients with NSCLC. CONCLUSIONS: Our study found that patients with Nrf2-activating mutation had improved immunotherapy outcomes than patients with wild type in NSCLC and other tumor cohorts, implying that Nrf2-activating mutation defined a distinct subset of pan-cancers and might have implications as a biomarker for guiding ICI treatment, especially NSCLC.

Chitosan-stabilized iron-copper nanoparticles for efficient removal of nitrate.

Chitosan-stabilized iron-copper nanomaterials (CS-nZVI/Cu) were successfully prepared and applied to the nitrate removal. Batch experiments were conducted to examine the effects of experimental parameters on nitrate removal, including Cu loading, CS-nZVI/Cu dosages, initial nitrate concentrations, and initial pHs. From the experimental date, it was concluded that CS-nZVI/Cu has a high nitrate removal efficiency, which can be more than 97%, respectively, at Cu loading = 5%, dosages of CS-nZVI/Cu = 3 g/L, initial nitrate concentrations of 30~120 mg/L, and initial pH values = 2~9. Additionally, the kinetic data for CS-nZVI/Cu were found to fit well with the first-order kinetic model with a rate constant of 0.15 (mg∙L)1-n/min, where n=1. The Langmuir model showed a good fit for NO3- removal, indicating that monolayer chemisorption occurred. The SEM and TEM analyses showed that the addition of chitosan resulted in improved dispersion of the CS-nZVI/Cu. The CS-nZVI/Cu nanomaterials have a more complete elliptical shape and are between 50 and 100 nm in size. The XRD analysis showed that the chitosan encapsulation reduced the oxidation of the iron component and the main product was Fe3O4. The FT-IR analysis showed that the immobilization of chitosan and the iron was accomplished by the ligand interaction. The nitrogen adsorption-desorption isotherm results showed that the CS-nZVI/Cu specific surface area and pore volume decreased significantly after the reaction. Adsorption, oxidation, and reduction are possible mechanisms for nitrate removal by CS-nZVI/Cu. The XPS analysis investigated the contribution of nZVI and Cu in the removal mechanism. Adding copper accelerates the reaction time and rate. In addition, nZVI played a vital role in reducing nitrate to N2. Based on these results, it looks like CS-nZVI/Cu could be a satisfactory material for nitrate removal.

Neuroanatomical and functional substrates of the hypomanic personality trait and its prediction on aggression.

Hypomanic personality manifests a close link with several psychiatric disorders and its abnormality is a risk indicator for developing bipolar disorders. We systematically investigated the potential neuroanatomical and functional substrates underlying hypomanic personality trait (HPT) and its sub-dimensions (i.e., Social Vitality, Mood Volatility, and Excitement) combined with structural and functional imaging data as well as their corresponding brain networks in a large non-clinical sample across two studies (n = 464). Behaviorally, HPT, specifically Mood Volatility and Excitement, was positively associated with aggressive behaviors in both studies. Structurally, sex-specific morphological characteristics were further observed in the motor and top-down control networks especially for Mood Volatility, although HPT was generally positively associated with grey matter volumes (GMVs) in the prefrontal, temporal, visual, and limbic systems. Functionally, brain activations related to immediate or delayed losses were found to predict individual variability in HPT, specifically Social Vitality and Excitement, on the motor and prefrontal-parietal cortices. Topologically, connectome-based prediction model analysis further revealed the predictive role of individual-level morphological and resting-state functional connectivity on HPT and its sub-dimensions, although it did not reveal any links with general brain topological properties. GMVs in the temporal, limbic (e.g., amygdala), and visual cortices mediated the effects of HPT on behavioral aggression. These findings suggest that the imbalance between motor and control circuits may be critical for HPT and provide novel insights into the neuroanatomical, functional, and topological mechanisms underlying the specific temperament and its impacts on aggression.

Development of green finance, tourism, and corporate access to bank loans in China.

The fundamental purpose of this study is to conduct an inquiry into the efficacy of China's green credit strategy, and that is the core focus of the investigation. As part of this study, we investigate whether or not businesses that increase the environmental transparency of their operations to the outside world and green innovation within their operations are rewarded with more favorable bank loan terms as a direct result of receiving green credit. Specifically, we look at whether or not these businesses are awarded green credit. Our hypothesis is put to the test by using difference-in-differences (DID) model and the data that was collected from a sample of 1086 publicly traded Chinese manufacturers over the years 2012 to 2017. According to the data, businesses that improve the quality of their environmental disclosures do not receive an increase in their access to corporate finance. On the other hand, businesses that introduce new environmentally friendly (tourism) breakthroughs do receive an increase in their access to corporate finance. Our research demonstrates that the root of the problem is corporate greenwashing, a practice that is common in regions with low environmental disclosure standards and makes it more difficult for businesses to obtain new loans. This practice is popular in areas where environmental disclosure standards are lax. This is the most basic explanation for why the phenomena occur in the first place. Our findings contribute to the literature on themes including green credit policy, corporate green innovation, environmental transparency, and green financing and tourism, all of which are useful to corporations, governments, and financial institutions.

Systematic analysis of the cuprotosis in tumor microenvironment and prognosis of gastric cancer.

Cuprotosis is a new programmed cell death related to cancer. However, the characteristics of cuprotosis in gastric cancer (GC) remain unknown. Ten cuprotosis molecules from 1544 GC patients were used to identify three GC molecular genotypes. Cluster A was characterized by the best clinical outcome and was significantly enriched in metabolic signaling pathways. Cluster B exhibited elevated immune activation, high immune stroma scores and was significantly enriched in tumor immune signaling pathways. Cluster C was characterized by severe immunosuppression and poor response to immunotherapy. Notably, the citrate cycle, cell cycle, and p53 signaling pathways were enriched in the differentially expressed genes among the three subtypes, which were critical signaling pathways for cell death. We also developed a cuprotosis signature risk score that could accurately predict the survival, immunity, and subtype of GC. This study presents a systematic analysis of cuprotosis molecules and provides new immunotherapeutic targets for GC patients.

An antigen processing and presentation signature for prognostic evaluation and immunotherapy selection in advanced gastric cancer.

Objective: The aim of the study was to propose a signature based on genes associated with antigen processing and presentation (APscore) to predict prognosis and response to immune checkpoint inhibitors (ICIs) in advanced gastric cancer (aGC). Background: How antigen presentation-related genes affected the immunotherapy response and whether they could predict the clinical outcomes of the immune checkpoint inhibitor (ICI) in aGC remain largely unknown. Methods: In this study, an aGC cohort (Kim cohort, RNAseq, N=45) treated by ICIs, and 467 aGC patients from seven cohorts were conducted to investigate the value of the APscore predicting the prognosis and response to ICIs. Subsequently, the associations of the APscore with the tumor microenvironment (TME), molecular characteristics, clinical features, and somatic mutation variants in aGC were assessed. The area under the receiver operating characteristic curve (AUROC) of the APscore was analyzed to estimate response to ICIs. Cox regression or Log-rank test was used to estimate the prognosis of aGC patients. Results: The APscore constructed by principal component analysis algorithms was an effective predictive biomarker of the response to ICIs in the Kim cohort and 467 aGC patients (Kim: AUC =0.85, 95% CI: 0.69-1.00; 467 aGC: AUC =0.69, 95% CI: 0.63-0.74). The APscore also was a prognostic biomarker in 467 aGC patients (HR=1.73, 95% CI: 1.21-2.46). Inhibitory immunity, decreased TMB and low stromal scores were observed in the high APscore group, while activation of immunity, increased TMB, and high stromal scores were observed in the low APscore group. Next, we evaluated the value of several central genes in predicting the prognosis and response to ICIs in aGC patients, and verified them using immunogenic, transcriptomic, genomic, and multi-omics methods. Lastly, a predictive model built successfully discriminated patients with vs. without immunotherapy response and predicted the survival of aGC patients. Conclusions: The APscore was a new biomarker for identifying high-risk aGC patients and patients with responses to ICIs. Exploration of the APscore and hub genes in multi-omics GC data may guide treatment decisions.

Can Linear Conjugated Polymers Form Stable Helical Structures on the Carbon Nanotubes?

The formation mechanism of ordered helical structures of conjugated polymers wrapping onto single-walled carbon nanotubes (SWCNTs) has been full of controversy in recent decades. A formation mechanism is proposed for the linear conjugated polymers wrapping around SWCNTs that the formation of helical structures is dependent on the orientation competition between backbone segments and side groups via transmission electron microscopy observations and molecular dynamics simulations. Results show that the conjugated polymers cannot always form stable helical structures, even if they have the capability to form a stable helix. In fact, only part of polymer segments presents a stable helix on the SWCNTs for the internal rotation in polymer deformations. Furthermore, a design framework is proposed to choose specific conjugated homopolymers and copolymers which can form helical structures on the SWCNTs.

Extracts of Bauhinia Championii Alleviate Acute Neuronal Injury After Ischemic Reperfusion by Improving Endoplasmic Reticulum Stress-Mediated Neuronal Apoptosis.

OBJECTIVE: Cerebral ischemia/reperfusion (I/R) is a potential factor for lethal injury, and currently lacks effective remedies. Bauhinia championii extracts (BCEs) have been reported to exhibit anti-oxidative and anti-hypoxia properties. The current work aimed to study whether BCE could alleviate neuronal injury caused by I/R. METHODS: To investigate the protective effects of BCE, oxygen-glucose deprivation/reperfusion (OGD/R) was applied to the HT22 cell line in vitro and to a cerebral I/R mouse model in vivo. RESULTS: Under OGD/R, the survival of HT22 cells was significantly prolonged after treatment with BCE. In vivo, BCE significantly reduced the infarct area and decreased neuronal apoptosis caused by I/R. It was further found that OGD/R could trigger endoplasmic reticulum (ER) stress and induce ER stress-mediated neuronal apoptosis in vivo and in vitro, while BCE could effectively alleviate ER stress and neuronal apoptosis. CONCLUSION: These results suggested that BCE exhibits neuroprotective effects by reducing ER stress-mediated apoptosis after cerebral I/R injury. BCE may therefore be an effective therapeutic regimen against cerebral I/R damage.

Tunable and Transferable Diamond Membranes for Integrated Quantum Technologies.

Color centers in diamond are widely explored as qubits in quantum technologies. However, challenges remain in the effective and efficient integration of these diamond-hosted qubits in device heterostructures. Here, nanoscale-thick uniform diamond membranes are synthesized via "smart-cut" and isotopically (12C) purified overgrowth. These membranes have tunable thicknesses (demonstrated 50 to 250 nm), are deterministically transferable, have bilaterally atomically flat surfaces (Rq ≤ 0.3 nm), and bulk-diamond-like crystallinity. Color centers are synthesized via both implantation and in situ overgrowth incorporation. Within 110-nm-thick membranes, individual germanium-vacancy (GeV-) centers exhibit stable photoluminescence at 5.4 K and average optical transition line widths as low as 125 MHz. The room temperature spin coherence of individual nitrogen-vacancy (NV-) centers shows Ramsey spin dephasing times (T2*) and Hahn echo times (T2) as long as 150 and 400 µs, respectively. This platform enables the straightforward integration of diamond membranes that host coherent color centers into quantum technologies.

Analyses of prevalence and molecular typing of Salmonella in the goose production chain.

This study investigated the prevalence of Salmonella and the molecular typing of all isolates in a goose production chain including hatchery, farm, slaughterhouse, and market. A total of 350 Salmonella isolates was detected from 1,030 samples, and 13 serotypes were recovered. The highest Salmonella contamination frequency was observed at the hatchery, which 51.8% (188/363) of samples were Salmonella positive. S. Potsdam and S. Typhimurium were the 2 most common serotypes. S. Potsdam was most frequently found in the hatchery, while S. Typhimurium was widely distributed in the goose production chain. In general, the antibiotic resistance of Salmonella isolates is low, which isolates from the market is comparatively higher than from other production links indicating a possibility of Salmonella cross-contamination in the market. By the multilocus sequence typing (MLST) analysis, 7 different ST types were identified. ST2039 was the most common ST type, which was mostly found from S. Potsdam isolates in hatchery indicating that S. Potsdam might have been long existed in hatchery. The pulsed-field gel electrophoresis (PFGE) analysis of S. Potsdam indicated that S. Potsdam could be transmitted along the production chain. The PFGE analysis of S. Typhimurium showed that PFGE pattern 29 (PF29) was distributed in hatchery, and also in farm and from humans indicating the risk of S. Typhimurium transmitting to humans by the food supply chain. Our study provided the evidence of Salmonella cross-contamination in the slaughterhouse and the retail market of goose production chain, and specific serotypes existed for a long time at a particular production link. The spread of Salmonella along the production chain, might cause harm to humans through cross-contamination. Further studies would be needed to control the Salmonella contamination in hatchery and prevent the transmission of the pathogen during the goose production.

Experimental Parity-Time Symmetric Quantum Walks for Centrality Ranking on Directed Graphs.

Using quantum walks (QWs) to rank the centrality of nodes in networks, represented by graphs, is advantageous compared to certain widely used classical algorithms. However, it is challenging to implement a directed graph via QW, since it corresponds to a non-Hermitian Hamiltonian and thus cannot be accomplished by conventional QW. Here we report the realizations of centrality rankings of a three-, a four-, and a nine-vertex directed graph with parity-time (PT) symmetric quantum walks by using high-dimensional photonic quantum states, multiple concatenated interferometers, and dimension dependent loss to achieve these. We demonstrate the advantage of the QW approach experimentally by breaking the vertex rank degeneracy in a four-vertex graph. Furthermore, we extend our experiment from single-photon to two-photon Fock states as inputs and realize the centrality ranking of a nine-vertex graph. Our work shows that a PT symmetric multiphoton quantum walk paves the way for realizing advanced algorithms.

Efficient delivery of HBV NLS siRNAs into HepG2.2.15 cells for HBV inhibition through novel recombinant preS1­tP proteins.

Hepatitis B virus (HBV) infection and related liver complications remain severe public health problems worldwide. Previous investigations have shown that small interfering (si)RNAs can offer an effective strategy for the treatment of chronic hepatitis B. The present study aimed to develop a novel siRNA­delivering system of therapeutic HBV nuclear localization sequence (NLS) siRNAs using the recombinant preS1­truncated protamine (tP) proteins. The preS1 region of the LHB was used in place of scFv to construct the recombinant preS1­tP proteins, which were applied to deliver siRNAs targeting the HBV NLS to inhibit HBV replication and infection in HepG2.2.15 cells overexpressing sodium taurocholate cotransporting polypeptide (NTCP). The results revealed that HepG2.2.15 cells with stable NTCP expression (HepG2.2.15­NTCP cells) transfected with the recombinant lentivirus showed increased expression of NTCP genes. The HBV NLS siRNAs significantly suppressed HBV mRNA content and levels of HBsAg and HBeAg in the HepG2.2.15­NTCP cells. Recombinant preS1­tP proteins tagged with His and glutathione S­transferase were found to enter into HepG2.2.15­NTCP cells and bind with DNA. The HBV NLS siRNAs were delivered into HepG2.2.15­NTCP cells by recombinant preS1­tP proteins, which resulted in decreased expression of HBV mRNA, HBsAg and HBeAg, HBV DNA and covalently closed circular DNA in the HepG2.2.15­NTCP cells. Therefore, the recombinant preS1­tP proteins successfully delivered NLS siRNAs into HepG2.2.15 cells and repressed HBV infection and replication.

Melatonin Mitigates Kainic Acid-Induced Neuronal Tau Hyperphosphorylation and Memory Deficits through Alleviating ER Stress.

Kainic acid (KA) exposure causes neuronal degeneration featured by Alzheimer-like tau hyperphosphorylation and memory deficits. Melatonin (Mel) is known to protect hippocampal neurons against KA-induced damage. However, the underlying mechanisms remain elusive. In the current study, we investigated the protective effect of melatonin on KA-induced tau hyperphosphorylation by focusing on endoplasmic reticulum (ER) stress-mediated signaling pathways. By using primary hippocampal neurons and mouse brain, we showed that KA treatment specifically induced ER stress and activated GSK-3ß and CDK5, two major kinases responsible for tau phosphorylation. Inhibition of ER stress efficiently inactivated GSK-3ß and CDK5. Mechanistically, we found that KA-induced ER stress significantly activated calpain, a calcium-dependent protease. Inhibition of ER stress or calpain leads to the reduction in KA-induced GSK-3ß and CDK5 activities and tau phosphorylation. Moreover, GSK-3ß or CDK5 inhibition failed to downregulate ER stress efficiently, suggesting that ER stress functions upstream of GSK-3ß or CDK5. Notably, our results revealed that melatonin acts against KA-induced neuronal degeneration and tau hyperphosphorylation via easing ER stress, further highlighting the protective role of melatonin in the KA-induced neuronal defects.

Angle-resolved conical emission spectra from filamentation in a solid with an Airy pattern and a Gaussian laser beam.

Filamentation dynamics in fused silica are investigated using an Airy pattern and a Gaussian laser beam. The angle-resolved conical emission spectra are measured and compared with the predictions of several models. Our experimental observations are consistent with the X-waves model in both cases. This indicates that both laser beams spontaneously evolve into nonlinear X-waves and suggests a universal evolution of filaments in fused silica, regardless of the initial laser beam profile.

Gold nanoparticle-based enzyme-linked antibody-aptamer sandwich assay for detection of Salmonella Typhimurium.

Enzyme-linked immunosorbent assay (ELISA) provides a convenient means for the detection of Salmonella enterica serovar Typhimurium (STM), which is important for rapid diagnosis of foodborne pathogens. However, conventional ELISA is limited by antibody-antigen immunoreactions and suffers from poor sensitivity and tedious sample pretreatment. Therefore, development of novel ELISA remains challenging. Herein, we designed a comprehensive strategy for rapid, sensitive, and quantitative detection of STM with high specificity by gold nanoparticle-based enzyme-linked antibody-aptamer sandwich (nano-ELAAS) method. STM was captured and preconcentrated from samples with aptamer-modified magnetic particles, followed by binding with detector antibodies. Then nanoprobes carrying a large amount of reporter antibodies and horseradish peroxidase molecules were used for colorimetric signal amplification. Under the optimized reaction conditions, the nano-ELAAS assay had a quantitative detection range from 1 × 10(3) to 1 × 10(8) CFU mL(-1), a limit of detection of 1 × 10(3) CFU mL(-1), and a selectivity of >10-fold for STM in samples containing other bacteria at higher concentration with an assay time less than 3 h. In addition, the developed nanoprobes were improved in terms of detection range and/or sensitivity when compared with two commercial enzyme-labeled antibody signal reporters. Finally, the nano-ELAAS method was demonstrated to work well in milk samples, a common source of STM contamination.

Ghrelin protects human umbilical vein endothelial cells against high glucose-induced apoptosis via mTOR/P70S6K signaling pathway.

Ghrelin exhibits its biological effect through binding to the growth hormone secretagogue 1a receptor (GHS-R1a). Recently, it has been reported that ghrelin has an anti-apoptotic effect in several cell types. However, the molecule mechanisms underlying the anti-apoptotic effect of ghrelin remain poorly understood. In this study, we investigated the intracellular mechanisms responsible for anti-apoptotic effect of ghrelin on human umbilical vein endothelial cells (HUVEC). Treatment of HUVEC with ghrelin inhibited high glucose-induced cell apoptosis. Ghrelin stimulated the rapid phosphorylation of mammalian target of rapamycin (mTOR), P70S6K and S6. The GHS-R1a-specific antagonist [D-Lys3]-GHRP-6 abolished the anti-apoptotic effect and inhibited the activation of mTOR, P70S6K, S6 induced by ghrelin. Pretreatment of cells with specific inhibitor of mTOR blocked the anti-apoptotic effect of ghrelin. In addition, ghrelin protected HUVECs against high glucose induced apoptosis by increasing Bcl-2/Bax ratio. Taken together, our results demonstrate that ghrelin produces a protective effect on HUVECs through activating GHS-R1a and mTOR/P70S6K signaling pathway mediates the effect of ghrelin. These observations suggest that ghrelin may act as a survival factor in preventing HUVECs apoptosis caused by high glucose.