Detection limits for blood on four fabric types using infrared diffuse reflection spectroscopy in mid- and near-infrared spectral windows.

Detection limits (DL) for blood on four fabric types were estimated for calibrations derived using partial least squares regression applied to infrared (IR) diffuse reflection spectra. Samples were prepared by dip-coating acrylic, cotton, nylon, and polyester fabrics from solutions of diluted rat blood. While DLs often appear in terms of dilution factor in the forensic community, mass percentage, coverage (mass per unit area), or film thickness are often more relevant when comparing experimental methods. These alternate DL units are related to one another and presented here. The best IR diffuse reflection DLs for blood on acrylic and cotton fabrics were in the mid-IR spectral window corresponding to the protein Amide I/II absorption bands. These DLs were dilution by a factor of 2300 (0.019% w/w blood solids) for acrylic and a factor of 610 (0.055% w/w blood solids) for cotton. The best DL for blood on polyester was found in the mid-IR spectral window corresponding to the protein Amide A absorption band at dilution by a factor of 900 (0.034% w/w blood solids). Because of the similarity between the IR spectra of blood solids and nylon fabrics, no satisfactory IR DLs were determined for the calibration of blood on nylon. We compare our values to DLs reported for blood detection using the standard luminol method. The most commonly reported luminol DLs are of the order of 1000-fold dilution, which we estimate are a factor of 2-7 lower than our reported IR DLs on a coverage basis.

Improved parameterization of interatomic potentials for rare gas dimers with density-based energy decomposition analysis.

We examine interatomic interactions for rare gas dimers using the density-based energy decomposition analysis (DEDA) in conjunction with computational results from CCSD(T) at the complete basis set (CBS) limit. The unique DEDA capability of separating frozen density interactions from density relaxation contributions is employed to yield clean interaction components, and the results are found to be consistent with the typical physical picture that density relaxations play a very minimal role in rare gas interactions. Equipped with each interaction component as reference, we develop a new three-term molecular mechanical force field to describe rare gas dimers: a smeared charge multipole model for electrostatics with charge penetration effects, a B3LYP-D3 dispersion term for asymptotically correct long-range attractions that is screened at short-range, and a Born-Mayer exponential function for the repulsion. The resulted force field not only reproduces rare gas interaction energies calculated at the CCSD(T)/CBS level, but also yields each interaction component (electrostatic or van der Waals) which agrees very well with its corresponding reference value.

Covalent Organic Frameworks-Based Electrochemical Sensors for Food Safety Analysis.

Food safety is a key issue in promoting human health and sustaining life. Food analysis is essential to prevent food components or contaminants causing foodborne-related illnesses to consumers. Electrochemical sensors have become a desirable method for food safety analysis due to their simple, accurate and rapid response. The low sensitivity and poor selectivity of electrochemical sensors working in complex food sample matrices can be overcome by coupling them with covalent organic frameworks (COFs). COFs are a kind of novel porous organic polymer formed by light elements, such as C, H, N and B, via covalent bonds. This review focuses on the recent progress in COF-based electrochemical sensors for food safety analysis. Firstly, the synthesis methods of COFs are summarized. Then, a discussion of the strategies is given to improve the electrochemistry performance of COFs. There follows a summary of the recently developed COF-based electrochemical sensors for the determination of food contaminants, including bisphenols, antibiotics, pesticides, heavy metal ions, fungal toxin and bacterium. Finally, the challenges and the future directions in this field are discussed.

Screening and expression verification of key genes in cutaneous squamous cell carcinoma.

Background: Cutaneous squamous cell carcinoma (cSCC), a common skin malignancy, often occurs at exposed sites, and patients' appearance after surgical resection can be affected. This study sought to screen the key genes of cSCC via a bioinformatics analysis and explore the clinical significance and possible potential mechanisms of these genes in cSCC. Methods: We screened differentially expressed genes (DEGs) between cSCC and normal skin tissues from the Gene Expression Omnibus database, performed functional enrichment and protein interaction network analyses, and used Cytoscape software to identify the key genes. The expression of the genes was proved by immunohistochemistry. Results: A total of 164 DEGs were screened, and the functional enrichment analysis showed that the DEGs were significantly enriched in deoxyribonucleic acid replication and the cell-cycle pathway. By constructing a protein-to-protein interaction network, kinesin family member 11 (KIF11), aurora kinase A (AURKA), minichromosome maintenance complex component 2 (MCM2), minichromosome maintenance 10 replication initiation factor (MCM10), and denticleless E3 ubiquitin protein ligase homolog (DTL) were identified as 5 key genes with the highest connectivity. The expression of KIF11, AURKA, and MCM2 were investigated by immunohistochemistry. Compared to the normal skin tissues, the positive rates of the KIF11 and MCM2 proteins in the cSCC tissues were 70.0% and 90.0%, respectively, and the difference was statistically significant (P<0.05). The positive rates of AURKA protein expression in the cSCC and normal skin tissues were 13.9% and 0%, respectively, but the difference was not statistically significant. There was no correlation between the above-mentioned 3 key genes. Conclusions: KIF11 and MCM2 were highly expressed in cSCC, and may be involved in tumorigenesis, and represent novel targets for the clinical diagnosis and treatment of cSCC.

Detection Limits for Blood on Fabrics Using Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectroscopy and Derivative Processing.

Attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) was used to detect blood stains based on signature protein absorption in the mid-IR region, where intensity changes in the spectrum can be related to blood concentration. Partial least squares regression (PLSR) was applied for multivariate calibrations of IR spectra of blood dilutions on four types of fabric (acrylic, nylon, polyester, and cotton). Gap derivatives (GDs) were applied as a preprocessing technique to optimize the performance of calibration models. We report a much improved IR detection limit (DL) for blood on cotton (2700× in dilution factor units) and the first IR DL reported for blood on nylon (250×). Due to sample heterogeneity caused by fabric hydrophobicity, acrylic fabric produced variable ATR FT-IR spectra that caused poor DLs in concentration units compared to previous work. Polyester showed a similar problem at low blood concentrations that lead to a relatively poor DL as well. However, the increased surface sensitivity and decreased penetration depth of ATR FT-IR make it an excellent choice for detection of small quantities of blood on the front surface of all fabrics tested (0.0010 µg for cotton, 0.0077 µg for nylon, 0.011 µg for acrylic, and 0.0066 µg for polyester).