N-acetylcysteine Protects against Apoptosis through Modulation of Group I Metabotropic Glutamate Receptor Activity

The activation of group I metabotropic glutamate receptor (group I mGlus) has been shown to produce neuroprotective or neurotoxic effects. In this study, we investigated the effects of N-acetylcysteine (NAC), a precursor of the antioxidant glutathione, on group I mGlus activation in apoptosis of glial C6 and MN9D cell lines, and a rat model of Parkinson's disease (PD). We demonstrated that NAC protected against apoptosis through modulation of group I mGlus activity. In glial C6 cells, NAC promoted phosphorylation of ERK induced by (s)-3,5- dihydroxy-phenylglycine (DHPG), an agonist of group I mGlus. NAC enhanced the group I mGlus-mediated protection from staurosporine (STS)-induced apoptosis following DHPG treatment. Moreover, in rotenone-treated MN9D cells and PD rat model, NAC protected against group I mGlus-induced toxicity by compromising the decrease in phosphorylation of ERK, phosphorylation or expression level of TH. Furthermore, the results showed that NAC prohibited the level of ROS and oxidation of cellular GSH/GSSG (Eh) accompanied by activated group I mGlus in the experimental models. Our results suggest that NAC might act as a regulator of group I mGlus-mediated activities in both neuroprotection and neurotoxicity via reducing the oxidative stress, eventually to protect cell survival. The study also suggests that NAC might be a potential therapeutics targeting for group I mGlus activation in the treatment of PD

Broadband NIR photon upconversion generates NIR persistent luminescence for bioimaging

Upconversion persistent luminescence (UCPL) phosphors that can be directly charged by near-infrared (NIR) light have gained considerable attention due to their promising applications ranging from photonics to biomedicine. However, current lanthanide-based UCPL phosphors show small absorption cross-sections and low upconversion charging efficiency. The development of UCPL phosphors faces challenges of lacking flexible upconversion charging pathways and poor design flexibility. Herein, we discovered a new lattice defect-mediated broadband photon upconversion process and the accompanied NIR-to-NIR UCPL in Cr-doped zinc gallate nanoparticles. The zinc gallate nanoparticles can be directly activated by broadband NIR light in the 700-1000 nm range to produce persistent luminescence at about 700 nm, which is also readily enhanced by rationally tailoring the lattice defects in the phosphors. This proposed UCPL phosphors achieved a signal-to-background ratio of over 200 in bioimaging by efficiently avoiding interference from autofluorescence and light scattering. Our findings reported the lattice defect-mediated photon upconversion for the first time, which significantly expanded the horizons for the flexible design of NIR-to-NIR UCPL phosphors toward broad applications

Enhanced terahertz sensitivity for glucose detection with a hydrogel platform embedded with Au nanoparticles

We presented a strategy for enhancing the sensitivity of terahertz glucose sensing with a hydrogel platform pre-embedded with Au nanoparticles. Physiological-level glucose solutions ranging from 0 to 0.8 mg/mL were measured and the extracted absorption coefficients can be clearly distinguished compared to traditional terahertz time domain spectroscopy performed directly on aqueous solutions. Further, Isotherm models were applied to successfully describe the relationship between the absorption coefficient and the glucose concentration (R2 = 0.9977). Finally, the origin of the sensitivity enhancement was investigated and verified to be the pH change induced by the catalysis of Au nanoparticles to glucose oxidation

Weight-based Channel-model Matrix Framework provides a reasonable solution for EEG-based cross-dataset emotion recognition

Cross-dataset emotion recognition as an extremely challenging task in the field of EEG-based affective computing is influenced by many factors, which makes the universal models yield unsatisfactory results. Facing the situation that lacks EEG information decoding research, we first analyzed the impact of different EEG information(individual, session, emotion and trial) for emotion recognition by sample space visualization, sample aggregation phenomena quantification, and energy pattern analysis on five public datasets. Based on these phenomena and patterns, we provided the processing methods and interpretable work of various EEG differences. Through the analysis of emotional feature distribution patterns, the Individual Emotional Feature Distribution Difference(IEFDD) was found, which was also considered as the main factor of the stability for emotion recognition. After analyzing the limitations of traditional modeling approach suffering from IEFDD, the Weight-based Channel-model Matrix Framework(WCMF) was proposed. To reasonably characterize emotional feature distribution patterns, four weight extraction methods were designed, and the optimal was the correction T-test(CT) weight extraction method. Finally, the performance of WCMF was validated on cross-dataset tasks in two kinds of experiments that simulated different practical scenarios, and the results showed that WCMF had more stable and better emotion recognition ability.Comment: 18 pages, 12 figures, 8 table

N-phosphorylation of amino acids by trimetaphosphate in aqueous solution-learning from prebiotic synthesis

Inspired by a reactivity study between sodium trimetaphosphate (P(3)m) and amino acids in prebiotic chemistry, a one-step reaction with efficient purification procedure in aqueous media has been developed for the synthesis of N-phosphono-amino acids (NPAA). P(3)m was used to phosphorylate amino acids to NPAA with yields of 60 similar to 91%. The by-products, inorganic polyphosphates, were recycled to regenerate the phosphorylation reagent P(3)m.Ministry of Science and Technology [2006DFA43030]; Chinese National Natural Science Foundation [20572061, 20732004

Tunable van Hove singularity without structural instability in Kagome metal CsTi3_3Bi5_5

In Kagome metal CsV$_3$Sb$_5$, multiple intertwined orders are accompanied by both electronic and structural instabilities. These exotic orders have attracted much recent attention, but their origins remain elusive. The newly discovered CsTi$_3$Bi$_5$ is a Ti-based Kagome metal to parallel CsV$_3$Sb$_5$. Here, we report angle-resolved photoemission experiments and first-principles calculations on pristine and Cs-doped CsTi$_3$Bi$_5$ samples. Our results reveal that the van Hove singularity (vHS) in CsTi$_3$Bi$_5$ can be tuned in a large energy range without structural instability, different from that in CsV$_3$Sb$_5$. As such, CsTi$_3$Bi$_5$ provides a complementary platform to disentangle and investigate the electronic instability with a tunable vHS in Kagome metals

Improving Performance of All-Polymer Solar Cells Through Backbone Engineering of Both Donors and Acceptors

All-polymer solar cells (APSCs), composed of semiconducting donor and acceptor polymers, have attracted considerable attention due to their unique advantages compared to polymer-fullerene-based devices in terms of enhanced light absorption and morphological stability. To improve the performance of APSCs, the morphology of the active layer must be optimized. By employing a random copolymerization strategy to control the regularity of the backbone of the donor polymers (PTAZ-TPDx) and acceptor polymers (PNDI-Tx) the morphology can be systematically optimized by tuning the polymer packing and crystallinity. To minimize effects of molecular weight, both donor and acceptor polymers have number-average molecular weights in narrow ranges. Experimental and coarse-grained modeling results disclose that systematic backbone engineering greatly affects the polymer crystallinity and ultimately the phase separation and morphology of the all-polymer blends. Decreasing the backbone regularity of either the donor or the acceptor polymer reduces the local crystallinity of the individual phase in blend films, affording reduced short-circuit current densities and fill factors. This two-dimensional crystallinity optimization strategy locates a PCE maximum at highest crystallinity for both donor and acceptor polymers. Overall, this study demonstrates that proper control of both donor and acceptor polymer crystallinity simultaneously is essential to optimize APSC performance