材料科学最新文献

In the recent years, the number of Point-Of-Care-Tests (POCTs) available for clinical diagnostic has steadily increased. POCTs provide a near-patient testing with the potential to generate a result quickly so that appropriate treatment can be implemented, leading to improved clinical outcomes compared to traditional laboratory testing. Technological advances, such as miniaturization of sensors and improved instrumentation, have revolutionized POCTs, enabling the development of smaller and more accurate devices. In this context, it has also gained increasing importance the screening of various analytes simultaneously to increase specificity and improve the characterization of the disease. This study is aimed at developing and characterizing a photonic integrated circuit for multiple markers detection, which represents the functional core towards a full developed POCT device for clinical pathology applications. The photonic sensor, based on microring resonators (MRRs), is functionalized by immobilizing specific antibodies on a copolymer layer deposited on the MRR's surfaces. Surface chemical techniques were employed to analyse the surface chemical characteristics while fluorescence microscopy was involved to analyse the resulting bioreceptor surface density. The photonic sensor is characterized for the parallel detection of two biomarkers, the C-Reactive Protein (CRP) and the Creatine-Kinase-MB (CK-MB). The analyte-antibody binding curves were obtained both in buffer and in filtered un-diluted artificial saliva showing promising results both in terms of sensitivity, with limit of detection (LOD) of 103 pM for CRP and 140 pM for CK-MB, and in terms of specificity. These encouraging results let the assembly of a highly sensitive POC device for molecular diagnostics.

Gas-chromatography hyphenated with low-resolution mass spectrometry is a very flexible tool for the cost-effective identification and quantification of volatile compounds in complex matrices. In some analytical fields, criteria for the agreement between retention time and mass spectra of the analyte in calibrators and samples are defined based on the general understanding of the performance of these parameters. However, since this harmonisation is not based on experimental performance observed for specific GC-MS conditions and analyte it leads to false identifications. This research proposes a novel and robust tool for defining statistically sound criteria for the identification of compounds by GC-MS and LC-MS using experimental data. The Monte Carlo Method (MCM) simulation of the correlated abundance of characteristic ions of analyte mass spectrum allows simulating the abundance ratio difference of the analyte in a calibrator and sample used for statistically sound identifications. The Cholesky decomposition of the covariance matrix of ion abundances for MCM simulations allows the reliable use of many ion abundance ratios in identifications. The developed methodology was implemented in a user-friendly Excel spreadsheet and applied to the identification of tear gas agents in tear gas sprays. Criteria defined by SANTE for identifying pesticide residues in foodstuffs were compared with the developed tool. The cross-validation of computational and SANTE tools allowed concluding that the statistical control of retention time and mass spectra performs according to the defined confidence level. On the other hand, the SANTE criteria can produce up to 92 % false identifications for being too strict considering signal dispersion.

Ginseng may improve the myelosuppression and intestinal microbiota disorder induced by cyclophosphamide (CY); however, the effect of ginseng components on hematopoietic stem cell (HSC) damage remains largely unexplored. The present study aimed to assess the protective effect of ginseng extract (GE), total ginsenosides (TG) and total polysaccharides (TP) from ginseng on the intestinal microflora and HSCs of model mice. In the present study, a mouse model of HSC damage induced by CY was constructed, intestinal microflora of fecal samples were sequenced using the 16S ribosomal RNA (rRNA) sequencing techniques, the differentially expressed genes (DEGs) of HSCs were analyzed using high‑throughput RNA‑sequencing, cell apoptosis and erythroid differentiation were detected using flow cytometry and the blood cell parameters were analyzed using a hematology analyzer. Analysis of the 16S rRNA in fecal samples showed that GE, TG and TP improved an imbalanced intestinal microflora, where the relative abundance of Lactobacillus intestinalis had a positive correlation with ginsenosides content. Specifically, TP significantly increased the expression of low‑abundance microflora. Transcriptomic analysis results revealed 2,250, 3,432 and 261 DEGs in the GE, TG and TP groups compared with those in the Model group, respectively. In the expression analysis of DEGs, both TG and GE were found to markedly increase the expression levels of Klf4, Hhex, Pbx1, Kmt2a, Mecom, Zc3h12a, Zbtb16, Lilr4b, Flt3 and Klf13. Furthermore, TG inhibited the apoptosis of HSCs by increasing the expression levels of Bcl2 and Mcl1, whilst decreasing the expression of Bax. By contrast, GE inhibited the apoptosis of HSCs by reducing the expression of Bax and Bad. Regarding erythroid differentiation and blood cell parameters, GE was found to significantly increase the expression of TER‑119. In addition, GE and TG improved all blood cell parameters, including the count of white blood cells, neutrophils (NEUT), lymphocytes (LYMPH), red blood cells (RBC), hemoglobin (HGB) and reticulocyte and platelets (PLT), whereas TP could only improve the counts of LYMPH, RBC, HGB and PLT. The improvement effect of GE and TG on WBC, NEUT and Ret was superior to TP. In conclusion, TG may protect the hematopoiesis function of HSCs in a CY‑induced mouse model of HSC damage, followed by GE. However, TP did not appear to improve HSC damage. Ginsenosides may therefore be considered essential ingredients in GE when protecting HSCs against damage. GE and TG exerted their protective effects on HSCs by inhibiting the apoptosis of HSCs whilst improving the imbalance of intestinal microflora.

Osteosarcoma malignancy exhibits significant heterogeneity, comprising both osteosarcoma stem cells (OSCs) and non‑OSCs. OSCs demonstrate increased resistance to chemotherapy due to their distinctive cellular and molecular characteristics. Alterations in mitochondrial morphology and homeostasis may enhance chemoresistance by modulating metabolic and regulatory processes. However, the relationship between mitochondrial homeostasis and chemoresistance in OSCs remains to be elucidated. The present study employed high‑resolution microscopy to perform multi‑layered image reconstructions for a quantitative analysis of mitochondrial morphology. The results indicated that OSCs exhibited larger mitochondria in comparison with non‑OSCs. Furthermore, treatment of OSCs with cisplatin (CIS) or doxorubicin (DOX) resulted in preserved mitochondrial morphological stability, which was not observed in non‑OSCs. This finding suggested a potential association between mitochondrial homeostasis and chemoresistance. Further analysis indicated that dynamin‑related protein 1 (DRP1) might play a pivotal role in maintaining the stability of mitochondrial homeostasis in OSCs. Depletion of DRP1 resulted in the disruption of mitochondrial stability when OSCs were treated with CIS or DOX. Additionally, knocking out DRP1 in OSCs led to a reduction in chemoresistance. These findings unveil a novel mechanism underlying chemoresistance in osteosarcoma and suggest that targeting DRP1 could be a promising therapeutic strategy to overcome chemoresistance in OSCs. This provided valuable insights for enhancing treatment outcomes among patients with osteosarcoma.

Adults with attention-deficit/hyperactivity disorder (ADHD) experience impairing levels of inattention and/or hyperactivity-impulsivity, while individuals without ADHD experience these symptoms to a lesser extent. Yet, ADHD self-report scales so far hardly captured continuous distributions across the general population. In addition, they focused on weaknesses and ignored strengths. To address these shortcomings, we present here the Strengths and Weaknesses of ADHD and Normal-Behavior Scale Self-Report (SWAN-DE-SB). The normal distribution of the data collected and the scale's internal consistency, and factorial and convergent validity were assessed using data from a general population sample. Its clinical utility was evaluated by comparing scores from a clinical sample and a sample of individuals without ADHD and by calculating optimal cut-off values for specificity and sensitivity. The SWAN-DE-SB demonstrated normal distribution of the data collected, high internal consistency, and factorial and convergent validity. It reliably discriminated individuals with and without ADHD, with high specificity and sensitivity. It should therefore be considered a psychometrically convincing measure to assess strengths and weaknesses of ADHD symptoms and normal behavior in clinical and general population samples.

Operant conditioning and social learning theories suggest that positive cannabis use-related outcomes are a primary contributor to maintained use and risk for dependence. However, currently there does not exist a reliable, validated measure of positive cannabis-related outcomes. This study sought to develop and psychometrically evaluate the Positive Outcomes of Cannabis Use Scale (POCUS). We collected three samples, college students (N = 883), community adults (N = 214), and college students (N = 615), of predominantly White adults in the United States who completed an online survey. Exploratory and confirmatory factor analyses evaluated scale structure and identified four factors: social enhancement, mood enhancement, cognitive enhancement, and sexual enhancement. Positive outcomes were positively associated with recent use, controlling for expectancies and negative outcomes. Positive outcomes were also differentiated from positive expectancies and more influential in predicting typical use frequency. Findings indicate that the POCUS is psychometrically sound and clinically useful for measuring positive cannabis use-related outcomes among predominantly White adults in the United States.

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) shows great promise in clinical application for its high specificity, high sensitivity and wide linear range for the determination of small molecules. However, its application in clinical laboratory is hampered by matrix effect of clinical samples which could greatly affect quantification accuracy and the difficulty to be automated for the traditional sample preparation procedures. Thus, new techniques which could achieve selective enrichment to minimize matrix effect and automatic sample preparation of mass spectrometry are needed. We developed an immunologic mass spectrometry (iMS) method to overcome matrix effect and its clinical application was demonstrated for automatic analysis of testosterone (T), progesterone (P) and estradiol (E2) in human serum simultaneously. Firstly, three monoclonal antibodies were coupled to magnetic beads for selective enrichment of target hormones from serum. The immunomagnetic beads were separated, washed and eluted automatically for LC-MS/MS analysis. Analytical performance of the iMS method was validated and compared with traditional LC-MS/MS and chemiluminescence immunoassay (CLIA). Hormone levels were measured for 160 pregnancy women at different gestational weeks. Results showed that target hormones could be selectively captured with absolute recoveries of 93.9%-110.8 %. Relative responses for high, medium and low concentrations of the hormones between serum and methanol solution were 98.0%-109.7 %, 92.2%-105.3 % and 91.7%-96.0 % for T, P and E2, respectively. Calibration curves prepared in methanol solution, BSA solution and blank serum showed good consistency for the iMS method. The automated iMS method could overcome matrix effect of LC-MS/MS and cross-reaction of CLIA. Matrix effect of the iMS method was negligible as high specificity of target hormone enrichment before LC-MS/MS analysis. Matrix-matched calibration standards were no longer necessary for accurate quantification, which was of great benefit for the clinical application of mass spetrometry.

A comprehensive understanding of chemical composition of cultural heritage materials usually requires several complementary analytical techniques. Given the fragility and value of artworks, minimizing or avoiding sampling and performing in situ analysis under ambient light is an important goal. This article outlines a novel prototype designed to merge LIBS, laser-induced fluorescence spectroscopy (LIF), Raman spectroscopy using a single pulsed laser, and reflectance spectroscopy in a multi-spectroscopic characterization system for cultural heritage analysis (SYSPECTRAL). The aim is to analyze cultural heritage materials in their original place, obtaining both elemental and molecular information at such same point that is not always insured with several separated experimental settings. The SYSPECTRAL system focuses on compactness, mobility, and ease of operation. Software designed for the prototype controls multi-spectroscopic measurements, allows for image capture, precise localization, and data acquisition. Reflectance spectra examined the material and colors at the surface, and the LIBS-LIF-Raman package examines the stratigraphic structure of a multi-layered painted sample.

For industrial production and disease diagnosis, real-time detection of low concentrations of NH₃ is crucial, necessitating a gas-sensitive sensor compatible with integrated processes and exhibiting excellent performance. Herein, we employed wet etching and rapid in-situ polymerization on silicon nanowire substrates to grow polyaniline fibers, thereby fabricating NH₃ gas sensors with p-p heterojunction and three-dimensional network structures. Characterization and gas sensing performance testing were conducted. The results demonstrate the outstanding NH₃ detection capabilities of the sensor, providing stable responses down to concentrations as low as 1 ppb, which indicates its LOD is one to two orders of magnitude lower than current similar products. It also exhibits verified selectivity and long-term reliability. The excellent sensing performance is attributed to the high surface area from the silicon nanowire structure and efficient synergy of p-p heterojunction. Additionally, the influence of doping types of the substrates and annealing process were explored. This work serves as a reference for the design of silicon-based gas sensors with high sensitivity, low detection limits, and extended operational lifetimes, suitable for deployment in commercial integrated monitoring systems.

Soil pollution is predominantly attributed to the presence of heavy metal elements and organic compounds; However, current detection methodologies are restricted to the identification of only one of these two sources at a time. A novel analytical approach, known as nanoliter spray enhanced microwave plasma ionization mass spectrometry (Nano-Spray-EMPI-MS), has been developed to facilitate the simultaneous detection of both heavy metals and organic pollutants in soil samples. This technique is characterized by its requirement for minimal sample volumes, thereby allowing for efficient and rapid analysis. The research concentrated on the simultaneous analysis of five heavy metals (Pb, Zn, Cu, Cr, and Ni) and three major phthalates (PAEs), specifically DEHP, DBP, and DMP. The detection and quantification limits for the heavy metals were established to be between 0.16-0.57 and 0.53-1.88 μg L^-1, respectively, while the limits for the PAEs ranged from 0.02 to 0.05 and 0.07-0.16 μg L^-1. Validation of the method's efficacy in soil detection demonstrated recovery rates of 90.9 %-105.7 % for heavy metals and 89.4 %-97.2 % for PAEs. The application of this method analyzing soil samples collected from an area adjacent to a lead-acid battery industrial park in China revealed varying levels of contamination by both heavy metals and PAEs. Notably, Lead contamination was found to be the most pronounced, with a peak concentration of 862.5 mg kg^-1 and a correspondingly high pollution index. These findings are significant for evaluating local ecological risks, pinpointing sources of pollution, and formulating effective pollution management strategies in the region.