Correlation Between Lifestyle Patterns and Cognitive Function Among Community-Dwelling Older Chinese Adults in the Pre-Dementia Stages: A Latent Class Analysis.

Lifestyle activity engagement is a modifiable factor for cognitive decline. We aimed to identify lifestyle patterns (LPs) among community-dwelling older adults in the pre-dementia stages and to explore the links between LPs, cognitive function, and individual characteristics. 702 older Chinese adults were recruited. Three LPs were identified by latent class analysis: active aging lifestyle pattern (AALP), leisure lifestyle pattern (LLP), and work-centered lifestyle pattern (WLP). AALP refers to participation in various activities that are meaningful to individuals and benefit their well-being. LLP is the pattern of activities aimed at recreation. WLP refers to the LP where individuals are most likely to engage in work-related activities. However, only AALP is protected against mild cognitive impairment (MCI). Multinomial logistic regression models revealed the differences in individual characteristics among participants with different LPs, indicating the importance of tailored intervention strategies. As a protective factor against MCI, AALP should be highlighted in community-based care.

Study protocol for a prediction model for mild cognitive impairment in older adults with diabetes mellitus and construction of a nurse-led screening system: a prospective observational study.

INTRODUCTION: With an increasing number of older adults in China, the number of people with cognitive impairment is also increasing. To decrease the risk of dementia, it is necessary to timely detect mild cognitive impairment (MCI), which is the preliminary stage of dementia. The prevalence of MCI is relatively high among older adults with diabetes mellitus (DM); however, no effective screening strategy has been designed for this population. This study will construct a nurse-led screening system to detect MCI in community-dwelling older adults with DM in a timely manner. METHODS AND ANALYSIS: A total of 642 participants with DM will be recruited (n=449 for development, n=193 for validation). The participants will be divided into MCI and none-MCI groups. The candidate predictors will include demographic variables, lifestyle factors, history of diseases, physical examinations, laboratory tests and neuropsychological tests. Univariate analysis, least absolute shrinkage and selection operator regression screening, and multivariate logistic regression analysis will be conducted to identify the outcome indicators. Based on the multivariate logistic regression equation, we will develop a traditional model as a comparison criterion for the machine learning models. The Hosmer-Lemeshow goodness-of-fit test and calibration curve will be used to evaluate the calibration. Sensitivity, specificity, area under the curves and clinical decision curve analysis will be performed for all models. We will report the sensitivity, specificity, area under the curve and decision curve analysis of the validation dataset. A prediction model with better performance will be adopted to form the nurse-led screening system. ETHICS AND DISSEMINATION: This prospective study has received institutional approval of the Medical Ethics Committee of Qidong Hospital of TCM (QDSZYY-LL-20220621). Study results will be disseminated through conference presentations, Chinese Clinical Trial Registry and publication. TRIAL REGISTRATION NUMBER: ChiCTR2200062855.

Use of municipal solid waste incineration (MSWI) bottom ash as a permeable subgrade material: An experimental and mechanism study.

As a traditional method of waste treatment, municipal solid waste incineration (MSWI) has become one of the main methods of urban waste treatment. However, as a byproduct of MSWI, a large amount of MSWI bottom ash is not reused in current practice. This study innovatively posits MSWI bottom ash as an eco-friendly adsorbent rather than a pollutant, exploring its potential application as a permeable subgrade material. The results reveal that MSWI bottom ash exhibits promising properties to serve as a permeable subgrade material to achieve the permeability and improve the sustainability for subgrade. Due to the arrangement of its particles, it shows excellent performance in shear strength and permeability, which are comparable to or surpass those of sandy soils. The average pore width of 14.200 nm allows heavy metal substances to be encapsulated within the matrix, significantly reducing their leachability, thereby aligning with environmental friendliness standards. Its adsorption capacity is about 6.60 mg/g, and the adsorption capacity per volume is 3.66 times and 2.04 times that of fly ash and clay, respectively. The mechanism analysis shows that the adsorption process is monolayer heterogeneous adsorption. This paper presents a novel perspective on reusing MSWI bottom ash and provides evidence supporting its effective utilization as a permeable subgrade material, offering substantial environmental benefits through enhanced adsorption ability.Implications: Municipal solid waste incineration (MSWI) is a common method for municipal solid waste treatment, while the MSWI bottom ash is often not reused. This paper explored the explores the feasibility of using MSWI bottom ash as a permeable road base material. The results show that the particle arrangement enables excellent shear strength and permeability, comparable to sandy soil. It meets safety requirements for the leaching of heavy metals and acts as an adsorbent for pollutants leaching from permeable pavements. Furthermore, the mechanisms underlying these behaviors of MSWI were confirmed by microstructural and mineralogical analyses. These indicate that MSWI bottom ash has great potential as a permeable road base material. This paper provides a clear understanding of the physical, mechanical and environmental properties of MSWI bottom ash, which can promote its reuse in practice.

Color Night Light Remote Sensing Images Generation Using Dual-Transformation.

Traditional night light images are black and white with a low resolution, which has largely limited their applications in areas such as high-accuracy urban electricity consumption estimation. For this reason, this study proposes a fusion algorithm based on a dual-transformation (wavelet transform and IHS (Intensity Hue Saturation) color space transform), is proposed to generate color night light remote sensing images (color-NLRSIs). In the dual-transformation, the red and green bands of Landsat multi-spectral images and "NPP-VIIRS-like" night light remote sensing images are merged. The three bands of the multi-band image are converted into independent components by the IHS modulated wavelet transformed algorithm, which represents the main effective information of the original image. With the color space transformation of the original image to the IHS color space, the components I, H, and S of Landsat multi-spectral images are obtained, and the histogram is optimally matched, and then it is combined with a two-dimensional discrete wavelet transform. Finally, it is inverted into RGB (red, green, and blue) color images. The experimental results demonstrate the following: (1) Compared with the traditional single-fusion algorithm, the dual-transformation has the best comprehensive performance effect on the spatial resolution, detail contrast, and color information before and after fusion, so the fusion image quality is the best; (2) The fused color-NLRSIs can visualize the information of the features covered by lights at night, and the resolution of the image has been improved from 500 m to 40 m, which can more accurately analyze the light of small-scale area and the ground features covered; (3) The fused color-NLRSIs are improved in terms of their MEAN (mean value), STD (standard deviation), EN (entropy), and AG (average gradient) so that the images have better advantages in terms of detail texture, spectral characteristics, and clarity of the images. In summary, the dual-transformation algorithm has the best overall performance and the highest quality of fused color-NLRSIs.

Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model.

Introduction: The rapid progress and poor prognosis of the exercise of esophageal squamous cell carcinoma (ESCA) bring great challenges to the treatment. Hypoxia in the tumor microenvironment has become a key factor in the pathogenesis of tumors. However, due to the lack of clear therapeutic targets, hypoxia targeted therapy of ESCA is still in the exploratory stage. Methods: To bridge this critical gap, we mined a large number of gene expression profiles and clinical data on ESCA from public databases. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed. We next delved into the relationship between hypoxia and apoptotic cell interactions. Meanwhile, using LASAS-Cox regression, we designed a robust prognostic risk score, which was subsequently validated in the GSE53625 cohort. In addition, we performed a comprehensive analysis of immune cell infiltration and tumor microenvironment using cutting-edge computational tools. Results: Hypoxia-related genes were identified and classified by WGCNA. Functional enrichment analysis further elucidated the mechanism by which hypoxia affected the ESCA landscape. The results of the interaction analysis of hypoxia and apoptotic cells revealed their important roles in driving tumor progression. The validation results of the prognostic risk score model in the GSE53625 cohort obtained a good area under the receiver operating characteristic (ROC) curve, and the risk score was independently verified as a significant predictor of ESCA outcome. The results of immune cell infiltration and tumor microenvironment analysis reveal the profound impact of immune cell dynamics on tumor evolution. Conclusion: Overall, our study presents a pioneering hypoxiacentered gene signature for prognostication in ESCA, providing valuable prognostic insights that could potentially revolutionize patient stratification and therapeutic management in clinical practice.

Stretchable Sponge-Based Electrochemical Biosensor for Real-Time Sensing of Cells in Three-Dimensional Culture.

For the study of cell biology, real-time information on cell physiological processes will be more accurate and closer to the in vivo condition in a three-dimensional (3D) culture system. Although most reported 3D cell culture scaffolds can better mimic the in vivo dynamic microenvironment, the real-time analysis technique is deficient or lacking. Herein, a stretchable and conductive 3D scaffold is developed to construct an electrochemical biosensor for real-time monitoring of cell release in 3D culture under stimulation of drug stimulant and mechanical force. In our design, the polyurethane sponge (PU) dipped with conductive carbon ink (CC/PU) was used as a conductive scaffold, and gold nanoparticles (nano-Au) were electrodeposited on the CC/PU (nano-Au CC/PU) to improve the electrochemical sensing performance. The prepared nano-Au CC/PU scaffold exhibits a good electrocatalytic ability to H2O2 with a linear range from 20 nM to 43 µM. Due to the great biocompatibility, HeLa cells can be cultured directly on the nano-Au CC/PU and the in situ and real-time tracking of H2O2 secretion from cells was achieved. The results demonstrate that both the drug stimulant and mechanical force can rapidly activate the release of reactive oxygen species. This study indicates that the stretchable 3D sensing scaffold has good potential for cell biology research in an in vivo-like microenvironment and can be extensively used in the fields of tissue engineering, drug screening, and pathological research.

Enhanced adsorption of phenol from aqueous solution by KOH combined Fe-Zn bimetallic oxide co-pyrolysis biochar: Fabrication, performance, and mechanism.

In this study, impregnation combined with KOH activation with different mixing methods was used to prepare magnetic biochar. The effects of synthetic method on biochar physicochemical properties and adsorption performance were explored. The results showed that treatment of a Fe-Zn oxide with KOH activation provided excellent adsorption properties with adsorption capacity of 458.90 mg/g due to well-developed microporous structure and rich-in O-containing functional groups as well as exposed oxidizing functional groups (Fe2O3 and FeOOH). Langmuir-Freundlich and pseudo-second-order models accurately fit phenol adsorption. Neutral conditions (pH = 6) and lower ionic strengths were beneficial to phenol removal. Additionally, the predominant adsorption processes were physisorption and chemisorption. Correlation analyses and characterization data confirmed that pore filling, π-π interactions and surface complexation were the dominant driving forces for phenol adsorption. This research provides an environmentally friendly method for utilizing agricultural wastes for the removal of a variety of pollutions from aquatic environment.

Development and evaluation of the MiCheck® Prostate test for clinically significant prostate cancer.

BACKGROUND: There is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant prostate cancer (CSCaP). We have previously reported the development of the MiCheck® Test for clinically significant prostate cancer. Here, we report MiCheck's further development and incorporation of the Roche Cobas standard clinical chemistry analyzer. OBJECTIVES: To further develop and adapt the MiCheck® Prostate test so it can be performed using a standard clinical chemistry analyzer and characterize its performance using the MiCheck-01 clinical trial sample set. DESIGN, SETTINGS, AND PARTICIPANTS: About 358 patient samples from the MiCheck-01 US clinical trial were used for the development of the MiCheck® Prostate test. These consisted of 46 controls, 137 non-CaP, 62 non-CSCaP, and 113 CSCaP. METHODS: Serum analyte concentrations for cellular growth factors were determined using custom-made Luminex-based R&D Systems multi-analyte kits. Analytes that can also be measured using standard chemistry analyzers were examined for their ability to contribute to an algorithm with high sensitivity for the detection of clinically significant prostate cancer. Samples were then re-measured using a Roche Cobas analyzer for development of the final algorithm. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Logistic regression modeling with Monte Carlo cross-validation was used to identify Human Epidydimal Protein 4 (HE4) as an analyte able to significantly improve the algorithm specificity at 95% sensitivity. A final model was developed using analyte measurements from the Cobas analzyer. RESULTS: The MiCheck® logistic regression model was developed and consisted of PSA, %free PSA, DRE, and HE4. The model differentiated clinically significant cancer from no cancer or not-clinically significant cancer with AUC of 0.85, sensitivity of 95%, and specificity of 50%. Applying the MiCheck® test to all evaluable 358 patients from the MiCheck-01 study demonstrated that up to 50% of unnecessary biopsies could be avoided while delaying diagnosis of only 5.3% of Gleason Score (GS) ≥3+4 cancers, 1.8% of GS≥4+3 cancers and no cancers of GS 8 to 10. CONCLUSIONS: The MiCheck® Prostate test identifies clinically significant prostate cancer with high sensitivity and negative predictive value (NPV). It can be performed in a clinical laboratory using a Roche Cobas clinical chemistry analyzer. The MiCheck® Prostate test could assist in reducing unnecessary prostate biopsies with a marginal number of patients experiencing a delayed diagnosis.

Semantic Retrieval of Remote Sensing Images Based on the Bag-of-Words Association Mapping Method.

With the increasing demand for remote sensing image applications, extracting the required images from a huge set of remote sensing images has become a hot topic. The previous retrieval methods cannot guarantee the efficiency, accuracy, and interpretability in the retrieval process. Therefore, we propose a bag-of-words association mapping method that can explain the semantic derivation process of remote sensing images. The method constructs associations between low-level features and high-level semantics through visual feature word packets. An improved FP-Growth method is proposed to achieve the construction of strong association rules to semantics. A feedback mechanism is established to improve the accuracy of subsequent retrievals by reducing the semantic probability of incorrect retrieval results. The public datasets AID and NWPU-RESISC45 were used to validate these experiments. The experimental results show that the average accuracies of the two datasets reach 87.5% and 90.8%, which are 22.5% and 20.3% higher than VGG16, and 17.6% and 15.6% higher than ResNet18, respectively. The experimental results were able to validate the effectiveness of our proposed method.

Biotransformation and Gut Microbiota-Mediated Bioactivity of Flavonols.

Consumption of fruits and vegetables has been associated with a reduced risk of multiple diseases, such as metabolic disorders. Flavonols are the most ubiquitous flavonoids in fruits and vegetables. However, dietary flavonols exhibit a general low oral bioavailability for their extensive biotransformation mediated by phase II enzymes in enterocytes and liver as well as by microbiota in the gut lumen. In this context, flavonols have brought attention to a paradox between low bioavailability and health-promoting effects. Flavonols are often transformed prior to absorption, which could change their biological activity. Compared to their parent compounds, the corresponding metabolites of flavonols in vivo might exhibit similar or higher intrinsic bioactivities, or perhaps a decreased efficacious effectiveness. Indeed, a growing body of evidence from biological function studies of metabolites supports the positive and significant contribution of in vivo metabolic processes, particularly conversion mediated by gut microbiota, to the health-promoting benefits of flavonols. As such, further understanding of the metabolic fate of flavonols and biological activities of their metabolites as well as the possible impact of microbiota-mediated conversion on the bioactivity is of great significance to guide a rational diet with flavonol-rich fruits and vegetables and/or flavonol-containing functional foods.

Pharmacokinetics and Biodistribution of 89Zr-Miltuximab and Its Antibody Fragments as Glypican-1 Targeting Immuno-PET Agents in Glioblastoma.

Glioblastoma (GBM) is the most aggressive form of primary brain cancer, accounting for about 85% of all primary central nervous system (CNS) tumors. With standard treatment strategies like surgery, radiation, and chemotherapy, the median survival time of patients with GBM is only 12-15 months from diagnosis. The poor prognosis of GBM is due to a very high tumor recurrence rate following initial treatment, indicating a dire need for improved diagnostic and therapeutic alternatives for this disease. Antibody-based immunotheranostics holds great promise in treating GBM, combining the theranostic applications of radioisotopes and target-specificity of antibodies. In this study, we developed and validated antibody-based positron emission tomography (PET) tracers targeting the heparan sulfate proteoglycan, glypican-1 (GPC-1), for noninvasive detection of disease using diagnostic molecular imaging. GPC-1 is overexpressed in multiple solid tumor types, including GBM, and is a promising biomarker for novel immunotheranostics. Here, we investigate zirconium-89 (89Zr)-conjugated Miltuximab (a clinical stage anti-GPC-1 monoclonal antibody developed by GlyTherix, Ltd.) and engineered fragments for their potential as immuno-PET tracers to detect GPC-1positive GBM tumors in preclinical models. We explore the effects of molecular size, avidity, and Fc-domain on the pharmacokinetics and biodistribution in vivo, by comparing in parallel the full-length antibody (Miltuximab), Fab'2, Fab, and single-chain variable fragment (scFv) formats. High radiolabeling efficiency (>95%) was demonstrated by all the formats and the stability post-radiolabeling was higher for larger constructs of Miltuximab and the Fab. Receptor-mediated internalization of all 89Zr-labeled formats was observed in a human GBM cell line in vitro, while full-length Miltuximab demonstrated the highest tumor retention (5.7 ± 0.94% ID/g, day-9 postinjection (p.i.)) and overall better tumor-to-background ratios than the smaller Fc-less formats. Results from in vivo PET image quantification and ex vivo scintillation counting were highly correlated. Altogether, 89Zr-DFO-Miltuximab appears to be an effective immuno-PET imaging agent for detecting GPC-1positive tumors such as GBM and the current results support utility of the Fc containing whole mAb format over smaller antibody fragments for this target.

Accurate ab initio based global adiabatic potential energy surfaces for the 13A'', 13A' and 21A' states of SiH2.

Three accurate global adiabatic potential energy surfaces for the 13A'', 13A' and 21A' states of SiH2 are constructed by fitting numerous ab initio energies calculated at the aug-cc-pV(Q+d)Z and aug-cc-pV(5+d)Z basis sets based on the multi-reference configuration interaction level with Davidson correction. It is worth noting that the potential energy surface of the 13A'' state is established for the first time. The topographic features of these novel potential energy surfaces are investigated in detail and are very consistent with those obtained in the available literature. Moreover, the integral cross-sections of the corresponding reaction are calculated for the first time using a quasi-classical trajectory method and time-dependent wave packet method, indicating that the 13A'' state makes a major contribution to the reaction of Si(3P) + H2(X1Σ+g) (v = 0, j = 0) → H(2S) + SiH(X2Π) at high collision energies. These new potential energy surfaces provide a reliable foundation for investigation of the dynamics and a component for constructing larger silicon-/hydrogen-containing systems.

An accurate many-body expansion potential energy surface for AlH2 (22A') and quantum dynamics in Al(3P) + H2 (v0 = 0-3, j0 = 0, 2, 4, 6) collisions.

An accurate potential energy surface is constructed for the excited state of AlH2 by fitting extensive ab initio points calculated at the multi-reference configuration interaction level based on aug-cc-pV(Q+d)Z and aug-cc-pV(5+d)Z basis sets. All the calculated energies are corrected via the many-body expansion method and extrapolated to the complete basis set limit. The various topographic features of the new potential energy surface are investigated to demonstrate the correct behavior of Al(3P) + H2(X1Σg+) and AlH(a3Π) + H(2S) dissociation limits. By employing the time-dependent wave packet approach, the integral scattering cross-sections obtained from the Coriolis coupling calculation and the centrifugal sudden approximation, respectively, are compared in detail and show that the former has a higher effect on the reaction. Moreover, the thermal rate constants for Al(3P) + H2 (v0 = 0-3, j0 = 0, 2, 4, 6) in the temperature range of 0-5000 K are calculated, thereby providing insights into the influence of ro-vibrational quantum numbers on the thermal rate constants.

Assessing the activity of antibodies conjugated to upconversion nanoparticles for immunolabeling.

Surface modification and functionalization is typically required to engineer upconversion nanoparticles (UCNPs) for biosensing and bioimaging applications. Nevertheless, despite various antibody conjugation methods having been applied to UCNPs, no consensus has been reached on the best choice, as the results from individual studies are largely unable to be compared due to inadequate assessment of the properties of the conjugated products. Here, we introduce a systematic approach to quantitatively evaluate the biological activity of antibody-conjugated UCNPs. We determine that the optimal antibody conjugation efficiency to our colominic acid polysaccharide-coated UCNPs via 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide/N-hydroxy succinimide (EDC/NHS) coupling is approximately 70%, corresponding to 16 antibodies per nanoparticle of 63 nm hydrodynamic diameter, with on average 12 of the 16 antibodies maintaining their affinity to the target antigens. The binding ability of the antibody-conjugated UCNPs to the antigen was well preserved, as verified by enzyme-linked immunosorbent assay (ELISA), flow cytometry, and cellular imaging. This is the first study to quantitate the active antibody binding capacity of polysaccharide coated UCNP nanoparticles, offering a practical guideline for benchmarking functionalised UCNPs in future studies.

Bio-based arginine surface-modified ammonium polyphosphate: an efficient intumescent flame retardant for epoxy resin.

In this work, ammonium polyphosphate (APP) was surface-modified by bio-based arginine (Arg) for the first time to enhance its flame retardance for fire-safety epoxy resin (EP). The structure of Arg modified APP (Arg-APP) was characterized by Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), 1H nuclear magnetic resonance (1H-NMR), and scanning electron microscopy (SEM). The results illustrated that Arg was attached on the surface of APP through a cation exchange reaction. With Arg acting as the efficient carbon source, the char-forming ability of Arg-APP was significantly improved as illustrated by thermogravimetric analysis (TGA). The flame retardance of EP/APP and EP/Arg-APP composites was evaluated using the limit oxygen index (LOI), vertical burning tests (UL-94), and cone calorimeter tests (CCT). The results showed that at the same weight loading (15 wt%), Arg-APP had better flame retardance and smoke suppression performance compared with pristine APP, which can be attributed to Arg-APP constituting an integrated intumescent flame retardant (IFR) and facilitating formation of char residues with significantly expanded structures and higher carbonization degrees. When the weight loading of Arg-APP reached 25 wt%, the EP/Arg-APP composite could achieve an LOI value as high as 34.7%, pass V-0 requirements in UL-94 tests, and decrease the peak heat release rate and total smoke production by 83.5% and 61.1% compared with neat EP in CCT, respectively, indicating the superior flame retardance performance of Arg-APP. Finally, the effects of the flame retardant additives on the mechanical properties of EP were evaluated by the differential scanning calorimetry (DSC) tests and tensile-strain tests. At the same additive weight loading (15 wt%), the EP/Arg-APP composite showed higher glass-transition temperature and better tensile-strain properties compared with EP/APP composite, which can be attributed to the Arg shell structure improving the compatibility between APP and the organic substrate. In conclusion, this work presents a convenient and environmentally friendly method to improve the practical performance of APP.

An accurate many-body expansion potential energy surface for SiH2 (11 A') using a switching function formalism.

An accurate many-body expansion potential energy surface for the ground state of SiH2 is reported. To warrant the correct behavior at the Si (1D) + H2 (X1Σ+g) dissociation channels involving silicon in the first excited Si (1D) and ground Si (3P) states, a switching function formalism has been utilized. A great deal of ab initio points based on aug-cc-pV(Q+d)Z and aug-cc-pV(5+d)Z basis sets are utilized at the multi-reference configuration interaction level using the full-valence-complete-active-space wave function as the reference. Subsequently the calculated energies are corrected via a many-body expansion method to extrapolate to the complete basis set limit. The topographic features of the novel many-body expansion global potential energy surface are studied in detail, showing a good agreement with the theoretical and experimental results in the literature. Moreover, the integral cross-section of the Si (1D) + H2 (X1Σ+g) → H (2S) + SiH (X2Π) reaction has been calculated using the time-dependent wave packet method, which provides support for the reliability of the title potential energy surface. This work can serve as the foundation for the study of Si (1D) + H2 (X1Σ+g) reaction kinetics, and for the construction of the larger multibody expansion potential energy surface of silicon/hydrogen containing systems.

Globally Accurate Potential Energy Surface for BH2+2(13A') Using the Switching Function Formalism.

A great number of ab initio energy points are calculated using the aug-cc-pV(Q,5)Z basis sets at the multireference configuration interaction level and extrapolated to the complete basis set limit. An exact three-dimensional potential energy surface of the ground-state BH2+ is obtained. A switching function is developed to model the transition of B+(3P) to B+(1S) to guarantee the reliable behavior at B+(3P) + H2(X1∑g+) and BH+(X2∑+) + H(2S) dissociation limits. The various topographic features of the new global potential energy surface are discussed in detail, showing a good agreement with the previous results from the theory. The quasi-classical trajectory method is utilized to calculate the integral cross sections of the B+(3P) + H2(X1∑g+) (v = 0, j = 0) → BH+(X2∑+) + H(2S) reaction, which can provide another support for reliability of the title potential energy surface.

Upconversion nanoparticle-assisted single-molecule assay for detecting circulating antigens of aggressive prostate cancer.

Sensitive and quantitative detection of molecular biomarkers is crucial for the early diagnosis of diseases like metabolic syndrome and cancer. Here we present a single-molecule sandwich immunoassay by imaging the number of single nanoparticles to diagnose aggressive prostate cancer. Our assay employed the photo-stable upconversion nanoparticles (UCNPs) as labels to detect the four types of circulating antigens in blood circulation, including glypican-1 (GPC-1), leptin, osteopontin (OPN), and vascular endothelial growth factor (VEGF), as their serum concentrations indicate aggressive prostate cancer. Under a wide-field microscope, a single UCNP doped with thousands of lanthanide ions can emit sufficiently bright anti-Stokes' luminescence to become quantitatively detectable. By counting every single streptavidin-functionalized UCNP which specifically labeled on each sandwich immune complex across multiple fields of views, we achieved the Limit of Detection (LOD) of 0.0123 ng/ml, 0.2711 ng/ml, 0.1238 ng/ml, and 0.0158 ng/ml for GPC-1, leptin, OPN and VEGF, respectively. The serum circulating level of GPC-1, leptin, OPN, and VEGF in a mixture of 10 healthy normal human serum was 25.17 ng/ml, 18.04 ng/ml, 11.34 ng/ml, and 1.55 ng/ml, which was within the assay dynamic detection range for each analyte. Moreover, a 20% increase of GPC-1 and OPN was observed by spiking the normal human serum with recombinant antigens to confirm the accuracy of the assay. We observed no cross-reactivity among the four biomarker analytes, which eliminates the false positives and enhances the detection accuracy. The developed single upconversion nanoparticle-assisted single-molecule assay suggests its potential in clinical usage for prostate cancer detection by monitoring tiny concentration differences in a panel of serum biomarkers.

Effect of long-term ageing on graphene oxide: structure and thermal decomposition.

After long-term ageing, the structure of graphene oxide prepared by the modified Hummers method changed. Because of the desorption of oxygen-containing functional groups, the C/O ratio of graphene oxide increased from 1.96 to 2.76. However, the average interlayer distance decreased from 0.660 to 0.567 nm. The content of -CH- and -CH2- decreased; however, the type of oxygen-containing functional groups did not change. Moreover, I D/I G increased from 0.87 to 0.92, indicating that the defect density decreased because of desorbing oxygen functional groups after ageing. When the temperature exceeded 60°C, CO2 produced by decomposing graphene oxide was detected. The thermal decomposition changed after ageing. The decomposition peak temperature decreased from 216°C to 195°C. The CO2 amount produced remained almost unchanged; however, the amount of CO, SO2 and H2O decreased. After ageing, the apparent activation energy of graphene oxide decreased from 150 to 134 kJ mol-1.