Photophysics of Silicon Phthalocyanines in Aqueous Media

Phthalocyanines have been used as photodynamic therapy (PDT) agents because of their uniquely favorable optical properties and high photostability. They have been shown to be highly successful for the treatment of cancer through efficient singlet‐oxygen (¹O₂) production. However, due to their hydrophobic properties, the considerations of solubility and cellular location have made understanding their photophysics in vitro and in vivo difficult. Indeed, many quantitative assessments of PDT reagents are undertaken in purely organic solvents, presenting challenges for interpreting observations during practical application in vivo. With steady‐state and time‐resolved laser spectroscopy, we show that for axial ligated silicon phthalocyanines in aqueous media, both the water:lipophile ratio and the pH have drastic effects on their photophysics, and ultimately dictate their functionality as PDT drugs. We suggest that considering the presented photophysics for PDT drugs in aqueous solutions leads to guidelines for a next generation of even more potent PDT agents.     

Comparison of Yield,Chemical Composition and Antimicrobial Activity of Distichochlamys citrea Rhizome Essential Oils Obtained by Different Extraction Methods

Moscow University Chemistry Bulletin - Hydrodistillation (HD), steam distillation (SD) and microwave-assisted hydrodistillation (MAHD) extraction methods were assessed for their effects on yield,...     

AQP4 Attenuated TRAF6/NFκB Activation in Acrylamide-Induced Neurotoxicity

Acrylamide (ACR) is present in high-temperature-processed high-carbohydrate foods, cigarette smoke, and industrial pollution. Chronic exposure to ACR may induce neurotoxicity from reactive oxygen species (ROS); however, the mechanisms underlying ACR-induced neurotoxicity remain unclear. We studied 28-day subacute ACR toxicity by repeatedly feeding ACR (0, 15, or 30 mg/kg) to rats. We conducted RNA sequencing and Western blot analyses to identify differences in mRNA expression in the blood and in protein expression in the brain tissues, respectively, of the rats. AQP4 transient transfection was performed to identify potential associations with protein regulation. The rats treated with 30 mg/kg ACR exhibited hind-limb muscle weakness. Matrix metalloproteinase (MMP9) expression was higher in the ACR-treated group than in the control group. ACR induced MMP-9 and AQP4 protein expression in the brain tissues of the rats, which subsequently presented with neurotoxicity. In the in vitro study, Neuro-2a cells were transiently transfected with AQP4, which inhibited MMP-9 and TNF receptor-associated factor 6 (TRAF6) expression, and inhibited ACR induced expression of TRAF6, IκBα, and nuclear factor κB (NFκB). Using a combination of in vivo and in vitro experiments, this study revealed that depressive symptoms associated with ACR-induced neurotoxicity are associated with downregulation of AQP4 and induction of the TRAF6 pathway.     

Directed triple systems

Directed triple systems are an example of block designs on directed graphs. A block design on a directed graph can be defined as follows. Let G be a directed graph of k vertices which contain no loops. Let S be a set of υ elements. A collection of k-subsets of S with an assignment of the elements of each k-subset to the vertices of G is called a block design on G of order υ if the following is satisfied. Any ordered pair of elements of S is assigned λ times to an edge of G.For example, if S = {a, b, c, d, e} and

and bae; cad; abc; dbe; acd; bce; adb; cde; aed; bec; is a collection of 3-subsets so written that in each subset the first element is assigned to the vertex 1, the second to 2, and the third to 3, then the collection is a block design on G with λ = 1.In this paper, it is shown that for the graph

if λ = 1, then the graph exists for all υ such that ν ? 2 mod 3.     

Cyclic orbifolds of lattice vertex operator algebras having group-like fusions

Letters in Mathematical Physics - Let L be an even (positive definite) lattice and $$gin O(L)$$. In this article, we prove that the orbifold vertex operator algebra $$V_{L}^{{hat{g}}}$$ has...     

Tomographic probability representation for quantum fermion fields

Tomographic probability representation is introduced for fermion fields. The states of the fermions are mapped onto the probability distribution of discrete random variables (spin projections). The operators acting on the fermion states are described by fermionic tomographic symbols. The product of the operators acting on the fermion states is mapped onto the star-product of the fermionic symbols. The kernel of the star-product is obtained. The antisymmetry of the fermion states is formulated as a specific symmetry property of the tomographic joint probability distribution associated with the states.     

Optical design of high performance con-focal microscopy with digital micro-mirror and stray light filters

This research proposes a newly developed stray light filter in order to eliminate stray light, which otherwise might severely reduce the performance of the con-focal microscopy presented in this research. First, an optical design for con-focal microscopy with a digital micro-mirror device (DMD) is illustrated; second, a newly developed stray light filter is presented, which functions to eliminate possible stray light and ghost images without any sacrifice of luminance. It indicates that not only can the optical system be much simplified but also that its resolution could be one step higher, because the system employs neither a pinhole nor a CCD camera lens. Experimental results are shown in the paper, demonstrating an increase in contrast of up to 60%.     

Planar Hall effect in biosensor with a tilted angle of the cross-junction

A typical planar Hall effect (PHE) sensor junction consists of two Hall bars that the bars appear normal to each other and the junction can have the required four terminals for current and voltage measurements. We are now introducing a tilted angle of the cross-junction and studying the role of the PHE therein. The results show that although there is a tilted angle of the cross-junction, the PHE voltage is remained constant. The result is interpreted by assuming the sensor material with the behavior of a basic single domain structure under the external magnetic field reversals. The calculations of the model are found to be in good concurrence with the experimental results.     

Multiplex metal-detection based assay (MMDA) for COVID-19 diagnosis and identification of disease severity biomarkers

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases.

A MMDA platform is developed by using metal-tagged antibodies as reporting probes combined with machine learning algorithms, as a general strategy for highly multiplexed biofluid assay.