Using three major criteria to evaluate aromaticity of five-member C-containing rings and their Si-, N-, and P-substituted aromatic heterocyclics

In this paper, we used bond-length equalization, aromatic stabilization energies (ASE) and nucleus-independent chemical shifts (NICS), calculated with (density functional theory) B3LYP levels at the 6-311+G^** basis set, to evaluate the aromaticity of a set of 38 five-member planar π-electron aromatic systems: sila-, aza- and phospha- derivatives and their parent systems. The result revealed statistically significant correlations among the above three criteria, and the order of aromaticity of the whole set was: Aza- derivatives rings > Phospha- derivatives rings > Sila- derivatives rings > Carbon-containing rings; NICS(0.6) and NICS(0.8) had the same results in evaluating the order of aromaticity in our case.     

活性位高度暴露的钴/氮/碳电催化剂的构建及氧还原性能研究

金属/氮/碳催化剂（M/N/C，M=Fe、Co等）是最有发展前景的非贵金属电催化剂之一，其性能依赖于催化剂表面的活性物种密度.通过常规的热解含氮前驱物与金属盐的方法制得的催化剂往往存在金属活性物种被包埋而不能有效利用的缺点.考虑到石墨相氮化碳（g-C₃N₄）富含类吡啶氮和亚纳米孔腔结构，将g-C₃N₄包覆在高导电性碳纳米笼（hCNC）表面，进而利用表层g-C₃N₄的配位和限域作用锚定大量Co²⁺离子，获得的Co/g-C₃N₄/hCNC复合物经热解后形成了活性位高度暴露、导电性好、孔结构丰富的Co/N/C催化剂.800℃热解得到的最优化催化剂在碱性介质中展现出优异氧还原活性，其起始电位（0.97 V）与商业Pt/C催化剂相当，且抗甲醇干扰性能和稳定性优异.此项研究提供了一种构建具有高度暴露活性位的M/N/C催化剂的有效策略.     

A new quantum group associated with a ‘nonstandard’ braid group representation

A new quantum group is derived from a nonstandard braid group representation by employing the Faddeev-Reshetikhin-Takhtajan constructive method. The classical limit is not a Lie superalgebra, despite relations like x ²–y ²=0. We classify all finite-dimensional irreducible representations of the new Hopf algebra and find only one- and two-dimensional ones.     

Assay development and high-throughput screening of caspases in microfluidic format

Caspase proteases are familiar targets in drug discovery. A common format for screening to identify caspase inhibitors employs fluorogenic or colorimetric tetra-peptide substrates in 96, 384, or 1536 -well microtiter plates. The primary motivation for increasing the number of wells per plate is to reduce the reagent cost per test and increase the throughput of HTS operations. There are significant challenges, however, to moving into or beyond the 1536-well format, such as submicroliter liquid handling, liquid evaporation, increased surface area-to-volume ratios, and the potential for artifacts and interference from small air-borne particles such as lint. Therefore, HTS scientists remain keenly interested in technologies that offer alternatives to the ever-shrinking microtiter plate well. Microfluidic assay technology represents an attractive option that, in theory, consumes only subnanoliter volumes of reagents per test. We have successfully employed a microfluidic assay technology in fluorogenic screening assays for several caspase isoforms utilizing the Caliper Technologies Labchip platform. Caspase-3 is used as a representative case to describe microfluidic assay development and initial high-throughput screening results. In addition, microfluidic screening and plate-based screening are compared in terms of reagent consumption, data quality, and ease of operation.     

Two N,N′‐diaryl‐2,2,2‐trichloroethane‐1,1‐diamines: hydrogen‐bonded supramolecular structures in one and two dimensions

The molecules of 2,2,2‐trichloro‐N,N′‐diphenylethane‐1,1‐diamine, C₁₄H₁₃Cl₃N₂, are linked into (040) sheets by a combination of C—H...Cl and C—H...π(arene) hydrogen bonds. In 2,2,2‐trichloro‐N,N′‐bis(4‐methylphenyl)ethane‐1,1‐diamine, C₁₆H₁₇Cl₃N₂, the molecules are linked into C(7) chains by two independent C—H...Cl hydrogen bonds and one Cl...Cl contact.     

Detecting the Critical States of Type 2 Diabetes Mellitus Based on Degree Matrix Network Entropy by Cross-Tissue Analysis

Type 2 diabetes mellitus (T2DM) is a metabolic disease caused by multiple etiologies, the development of which can be divided into three states: normal state, critical state/pre-disease state, and disease state. To avoid irreversible development, it is important to detect the early warning signals before the onset of T2DM. However, detecting critical states of complex diseases based on high-throughput and strongly noisy data remains a challenging task. In this study, we developed a new method, i.e., degree matrix network entropy (DMNE), to detect the critical states of T2DM based on a sample-specific network (SSN). By applying the method to the datasets of three different tissues for experiments involving T2DM in rats, the critical states were detected, and the dynamic network biomarkers (DNBs) were successfully identified. Specifically, for liver and muscle, the critical transitions occur at 4 and 16 weeks. For adipose, the critical transition is at 8 weeks. In addition, we found some “dark genes” that did not exhibit differential expression but displayed sensitivity in terms of their DMNE score, which is closely related to the progression of T2DM. The information uncovered in our study not only provides further evidence regarding the molecular mechanisms of T2DM but may also assist in the development of strategies to prevent this disease.     

Nano-Based Co-Delivery System for Treatment of Rheumatoid Arthritis

A systemic autoimmune condition known as rheumatoid arthritis (RA) has a significant impact on patients’ quality of life. Given the complexity of RA’s biology, no single treatment can totally block the disease’s progression. The combined use of co-delivery regimens integrating various diverse mechanisms has been widely acknowledged as a way to make up for the drawbacks of single therapy. These days, co-delivery systems have been frequently utilized for co-treatment, getting over drug limitations, imaging of inflammatory areas, and inducing reactions. Various small molecules, nucleic acid drugs, and enzyme-like agents intended for co-delivery are frequently capable of producing the ability to require positive outcomes. In addition, the excellent response effect of phototherapeutic agents has led to their frequent use for delivery together with chemotherapeutics. In this review, we discuss different types of nano-based co-delivery systems and their advantages, limitations, and future directions. In addition, we review the prospects and predicted challenges for the combining of phototherapeutic agents with conventional drugs, hoping to provide some theoretical support for future in-depth studies of nano-based co-delivery systems and phototherapeutic agents.     

Functionalized Ultrasmall Iron Oxide Nanoparticles for T1-Weighted Magnetic Resonance Imaging of Tumor Hypoxia

Hypoxia is a common biological condition in many malignant solid tumors that plays an imperative role in regulating tumor growth and impacting the treatment’s therapeutic effect. Therefore, the hypoxia assessment is of great significance in predicting tumor development and evaluating its prognosis. Among the plenty of existing tumor diagnosis techniques, magnetic resonance imaging (MRI) offers certain distinctive features, such as being free of ionizing radiation and providing images with a high spatial resolution. In this study, we develop a fluorescent traceable and hypoxia-sensitive T₁-weighted MRI probe (Fe₃O₄-Met-Cy5.5) via conjugating notable hypoxia-sensitive metronidazole moiety and Cy5.5 dye with ultrasmall iron oxide (Fe₃O₄) nanoparticles. The results of in vitro and in vivo experiments show that Fe₃O₄-Met-Cy5.5 has excellent performance in relaxivity, biocompatibility, and hypoxia specificity. More importantly, the obvious signal enhancement in hypoxic areas indicates that the probe has great feasibility for sensing tumor hypoxia via T₁-weighted MRI. These promising results may unlock the potential of Fe₃O₄ nanoparticles as T₁-weighted contrast agents for the development of clinical hypoxia probes.     

Establishment and Application of a Predictive Growth Kinetic Model of Salmonella with the Appearance of Two Other Dominant Background Bacteria in Fresh Pork

To better guide microbial risk management and control, growth kinetic models of Salmonella with the coexistence of two other dominant background bacteria in pork were constructed. Sterilized pork cutlets were inoculated with a cocktail of Salmonella Derby (S. Derby), Pseudomonas aeruginosa (P. aeruginosa), and Escherichia coli (E. coli), and incubated at various temperatures (4–37 °C). The predictive growth models were developed based on the observed growth data. By comparing R² of primary models, Baranyi models were preferred to fit the growth curves of S. Derby and P. aeruginosa, while the Huang model was preferred for E. coli (all R² ≥ 0.997). The secondary Ratkowsky square root model can well describe the relationship between temperature and μ_max (all R² ≥ 0.97) or Lag (all R² ≥ 0.98). Growth models were validated by the actual test values, with B_f and A_f close to 1, and MSE around 0.001. The time for S. Derby to reach a pathogenic dose (10⁵ CFU/g) at each temperature in pork was predicted accordingly and found to be earlier than the time when the pork began to be judged nearly fresh according to the sensory indicators. Therefore, the predictive microbiology model can be applied to more accurately predict the shelf life of pork to secure its quality and safety.