Real-Time, Selective Detection of Heavy Metal Ions in Water Using 2d Nanomaterials-based Field-effect Transistors

Excessive intake of heavy metals damages the central nervous system and causes brain and blood disorders in mammals. Heavy metal contamination is commonly associated with exposure to mercury, lead, arsenic, and cadmium (arsenic is a metalloid, but classified as a heavy metal). Traditional methods to detect heavy metal ions include graphite furnace atomic absorption spectroscopy (GFAAS), inductively-coupled plasma optical emission spectroscopy (ICP-OES), and inductively-coupled plasma mass spectroscopy (ICP-MS). Recently, many new methods have been proposed to detect heavy metal ions, including atomic absorption spectrometry, fluorescent sensors, colorimetric sensors, electrochemical sensors, X-ray absorption fine structure spectroscopy, ultrasensitive dynamic light scatting assays, and ion selective electrodes. Although significant progress has been made, there are still some critical issues to be addressed, e.g., lack of portability, the need for well-trained personnel, highly expensive and complex instruments, long response time (tens of minutes or even longer), and the possibility of introducing additional contamination. Therefore, it is highly desirable to develop a real-time, low-cost, portable, user-friendly analytical platform for rapid inline analysis of mercury, lead and other heavy metal ions. This dissertation research aims to investigate field-effect transistor (FET) sensors based on two-dimensional (2D) nanomaterials with specific probe-functionalized gold (Au) nanoparticles (NPs). The fundamental mechanism of the FET platform is to use a 2D nanomaterial as the conducting channel to transport charge carriers (electrons or holes). Upon the capture of target analytes, the charge carrier concentration and/or mobility changes correspondingly with a signal of current change within the channel. As a result, the FET characteristic changes upon the introduction of the heavy metal ion solution, varies with the metal concentration, and takes only a few seconds to respond. Control experiments are performed to verify the selectivity of the 2D nanomaterial/Au NP hybrid sensor to specific targets. The rapid, selective, sensitive, and stable detection performance indicates the promise of 2D nanomaterial/Au NP hybrid sensors for heavy metal ion detection in an aqueous solution. This research is accomplished through several steps: First, various heavy metal ion contaminants, their damage, and the conventional detection methods are reviewed; Second, the FET-based plaform and its working mechanism are explored; Third, the understanding of various 2D nanomaterials, their unique properties pertinent to electronic sensing, and their selection to realize real-time, selective, and sensitive detection of heavy metal ions is carried out; Finally, improvement of stability, sensitivity and lifetime of FET sensors is investigated. In this thesis work, sensitive and selective FET-based 2D nanomaterial/Au NP hybrid sensors for Pb2+, Hg2+, As(III), and As(V) have been demonstrated. The 2D nanomaterials include reduced graphene oxide (rGO), molybdenum disulfide (MoS2), and black phosphorus (BP). The hybrid structure consists of a nanomaterial film, homogeneously dispersed Au NPs, and specific probes. The detection is enabled by recording the electrical conductance of the device through monitoring the change in the drain current of the 2D nanomaterial sheets. The platform offers a promising route for real-time (1-2 seconds), high-performance and low-cost detection of heavy metal ions. The lower detection limit can reach the order of µg/L (parts-per-billion or ppb). The sensor also shows high selectivity against other co-existing metal ions. To improve the sensitivity of the nanomaterial-based electronic sensor, theoretical analysis on the sensing mechanism has been carried out, together with experimental validation. Theoretical analysis indicates that sensitivity-related factors are semiconducting properties of nanomaterials (e.g., carrier mobility, band gap), number of probes, and adsorption capacity of Au NPs. Experimental results suggest that a higher sensitivity for sensors can be realized by forming hybrid structures with thinner 2D conducting materials with a larger band gap and a higher carrier mobility, increasing the areal density of anchoring sites on the sensor surface, and enhancing the adsorption of detection probes. Investigation into the stability of the nanomaterial-based electronic sensor includes the binding strength between the nanomaterial and electrodes, stability of the nanomaterials in ambient environment and water, the detachment of Au NPs, the lifetime and diffusion of probes, and the overall stability of the sensor platform. Subsequently, strategies to improve the stability of the nanomaterial-based FET sensor have been proposed. Finally, the FET sensor has been used for the accurate prediction of arsenic ions in lake water and integrated into a practical flowing water system for continuous detection of lead ions. The rapid, selective, sensitive, and stable detection performance of the FET sensor for various heavy metal ions in water suggests a promising future for in-situ detection of contamination events. The thesis study provides a scientific foundation to engineer FET sensors with enhanced performance. An attempt has been made to practically develop the FET platform into standalone sensors and to integrate the sensor into flowing water equipment for heavy metal ion detection. The thesis results thus contribute to the future application of FET sensors for monitoring water contamination and mitigating the public health risk

The durability of basalt-fiber-reinforced cement mortar under exposure to unilateral salt freezing cycles

Basalt fiber and cement-based materials have been widely applied in engineering structures. In this context, the durability of basalt-fiber-reinforced ordinary silicate mortar was systematically studied under exposure to unilateral salt freezing. The mechanical durability, chloride ion diffusion characteristics, and microscopic pore characteristics of cement mortar with basalt fiber content levels in the range of 0 kg/m3–1.5 kg/m3 were tested under exposure to 0–40 freeze–thaw cycles. The relationships of changes in the internal pore structure with mass loss, mechanical damage, and the physical properties of the material were also analyzed under exposure to salt freezing cycles. The results demonstrated that even a small amount of basalt fiber could significantly improve the mechanical properties of cement mortar under unilateral salt freezing and its resistance to salt freezing erosion. In particular, cement mortar with 1.2 kg/m3 basalt fiber content exhibited good durability of compressive and flexural strength, while the specimens with no basalt fibers exhibited a relatively large degree of internal porosity under exposure to unilateral salt freezing. Our work provides concrete evidence for changes in the porosity of mortar under exposure to unilateral salt freezing, with these changes showing an exponential relationship with mortar mass loss and a strong linear correlation with changes in the compressive strength, flexural strength, and chloride ion diffusion coefficient of the material

Cardiac mesenchymal stem cells promote fibrosis and remodeling in heart failure: Role of PDGF signaling

Heart failure (HF) is characterized by progressive fibrosis. Both fibroblasts and mesenchymal stem cells (MSCs) can differentiate into pro-fibrotic myofibroblasts. MSCs secrete and express platelet-derived growth factor (PDGF) and its receptors. We hypothesized that PDGF signaling in cardiac MSCs (cMSCs) promotes their myofibroblast differentiation and aggravates post-myocardial infarction left ventricular remodeling and fibrosis. We show that cMSCs from failing hearts post-myocardial infarction exhibit an altered phenotype. Inhibition of PDGF signaling in vitro inhibited cMSC-myofibroblast differentiation, whereas in vivo inhibition during established ischemic HF alleviated left ventricular remodeling and function, and decreased myocardial fibrosis, hypertrophy, and inflammation. Modulating cMSC PDGF receptor expression may thus represent a novel approach to limit pathologic cardiac fibrosis in HF

Biogeography and Virulence of Staphylococcus aureus

Staphylococcus aureus is commonly carried asymptomatically in the human anterior nares and occasionally enters the bloodstream to cause invasive disease. Much of the global diversity of S. aureus remains uncharacterised, and is not clear how disease propensity varies between strains, and between host populations.We compared 147 isolates recovered from five kindergartens in Chengdu, China, with 51 isolates contemporaneously recovered from cases of pediatric infection from the main hospital serving this community. The samples were characterised by MLST, the presence/absence of PVL, and antibiotic resistance profiling.Genotype frequencies within individual kindergartens differ, but the sample recovered from cases of disease shows a general enrichment of certain MLST genotypes and PVL positive isolates. Genotypes under-represented in the disease sample tend to correspond to a single sequence cluster, and this cluster is more common in China than in other parts of the world.Virulence propensity likely reflects a synergy between variation in the core genome (MLST) and accessory genome (PVL). By combining evidence form biogeography and virulence we demonstrate the existence of a "native" clade in West China which has lowered virulence, possibility due to acquired host immunity

Individual risk and prognostic value prediction by machine learning for distant metastasis in pulmonary sarcomatoid carcinoma: a large cohort study based on the SEER database and the Chinese population

BackgroundThis study aimed to develop diagnostic and prognostic models for patients with pulmonary sarcomatoid carcinoma (PSC) and distant metastasis (DM).MethodsPatients from the Surveillance, Epidemiology, and End Results (SEER) database were divided into a training set and internal test set at a ratio of 7 to 3, while those from the Chinese hospital were assigned to the external test set, to develop the diagnostic model for DM. Univariate logistic regression was employed in the training set to screen for DM-related risk factors, which were included into six machine learning (ML) models. Furthermore, patients from the SEER database were randomly divided into a training set and validation set at a ratio of 7 to 3 to develop the prognostic model which predicts survival of patients PSC with DM. Univariate and multivariate Cox regression analyses have also been performed in the training set to identify independent factors, and a prognostic nomogram for cancer-specific survival (CSS) for PSC patients with DM.ResultsFor the diagnostic model for DM, 589 patients with PSC in the training set, 255 patients in the internal and 94 patients in the external test set were eventually enrolled. The extreme gradient boosting (XGB) algorithm performed best on the external test set with an area under the curve (AUC) of 0.821. For the prognostic model, 270 PSC patients with DM in the training and 117 patients in the test set were enrolled. The nomogram displayed precise accuracy with AUC of 0.803 for 3-month CSS and 0.869 for 6-month CSS in the test set.ConclusionThe ML model accurately identified individuals at high risk for DM who needed more careful follow-up, including appropriate preventative therapeutic strategies. The prognostic nomogram accurately predicted CSS in PSC patients with DM

New fusion transcripts identified in normal karyotype acute myeloid leukemia

Genetic aberrations contribute to acute myeloid leukemia (AML). However, half of AML cases do not contain the well-known aberrations detectable mostly by cytogenetic analysis, and these cases are classified as normal karyotype AML. Different outcomes of normal karyotype AML suggest that this subgroup of AML could be genetically heterogeneous. But lack of genetic markers makes it difficult to further study this subgroup of AML. Using paired-end RNAseq method, we performed a transcriptome analysis in 45 AML cases including 29 normal karyotype AML, 8 abnormal karyotype AML and 8 AML without karyotype informaiton. Our study identified 134 fusion transcripts, all of which were formed between the partner genes adjacent in the same chromosome and distributed at different frequencies in the AML cases. Seven fusions are exclusively present in normal karyotype AML, and the rest fusions are shared between the normal karyotype AML and abnormal karyotype AML. CIITA, a master regulator of MHC class II gene expression and truncated in B-cell lymphoma and Hodgkin disease, is found to fuse with DEXI in 48% of normal karyotype AML cases. The fusion transcripts formed between adjacent genes highlight the possibility that certain such fusions could be involved in oncological process in AML, and provide a new source to identify genetic markers for normal karyotype AML

Inhibiting decoherence via ancilla processes

General conditions are derived for preventing the decoherence of a single two-state quantum system (qubit) in a thermal bath. The employed auxiliary systems required for this purpose are merely assumed to be weak for the general condition while various examples such as extra qubits and extra classical fields are studied for applications in quantum information processing. The general condition is confirmed with well known approaches towards inhibiting decoherence. A novel approach for decoherence-free quantum memories and quantum operations is presented by placing the qubit into the center of a sphere with extra qubits on its surface.Comment: pages 8, Revtex

Printability and Applicability of 3D Printing System Loaded with Chlorogenic Acid Hydrogel

Three-dimensional food printing (3DFP) is an efficient way of food processing in line with the future lifestyle. As a delivery system, hydrogel has become a research hotspot because of its remarkable characteristics such as directed delivery. The purpose of this study was to explore the effects of 3DFP on the structure, physical properties and functions of hydrogels containing methylcellulose (MC), chlorogenic acid (CA) and hyaluronic acid (HA) for the purpose of revealing the printability and applicability of hydrogels in 3DFP processing. Texture properties, rheological properties, microstructure, embedding rate and digestive properties of the 3D printed products were measured. The results showed that the best CA-loaded hydrogel system for 3DFP processing consisted of MC, HA and CA at a mass ratio of 8:0.5:0.5. Its printed product showed the smallest width deviation (13.40%), the highest hardness, the maximum elasticity, and the minimum adhesiveness, had compact structure and uniform porosity, was not easy to collapse, and had good supportability and the best printing moldability. 3DFP well optimized the physical structure of hydrogel without changing its chemical properties. The embedding rate of CA was 22.09 percentage points higher than that before 3D printing. In simulated gastrointestinal digestion test, the release rate of CA from the printed product was significantly higher than that of the unprinted samples, showing a good sustained release effect, and the in vitro release of CA was fitted to the Ritger-Peppas model. These results showed that the hydrogel system had good printability and applicability, and 3DFP could significantly improve the targeted release of CA loaded in hydrogel

Downregulation of TLX induces TET3 expression and inhibits glioblastoma stem cell self-renewal and tumorigenesis

International audienceGlioblastomas have been proposed to be maintained by highly tumorigenic glioblastoma stem cells (GSCs) that are resistant to current therapy. Therefore, targeting GSCs is critical for developing effective therapies for glioblastoma. In this study, we identify the regulatory cascade of the nuclear receptor TLX and the DNA hydroxylase Ten eleven translocation 3 (TET3) as a target for human GSCs. We show that knockdown of TLX expression inhibits human GSC tumorigenicity in mice. Treatment of human GSC-grafted mice with viral vector-delivered TLX shRNA or nanovector-delivered TLX siRNA inhibits tumour development and prolongs survival. Moreover, we identify TET3 as a potent tumour suppressor downstream of TLX to regulate the growth and self-renewal in GSCs. This study identifies the TLX-TET3 axis as a potential therapeutic target for glioblastoma