Anthracene–Naphthalenediimide Compact Electron Donor/Acceptor Dyads: Electronic Coupling, Electron Transfer, and Intersystem Crossing

We attached different electron donors of phenyl, anthryl, and alkylamino moieties, to electron acceptor naphthalenediimide (NDI) to construct compact electron donor/acceptor dyads. The purpose is to study the effect of electron coupling (the magnitude is the matrix element, VDA) on the photophysical properties of UV–vis absorption, fluorescence emission, especially spin–orbit charge transfer intersystem crossing. We found that the magnitude of VDA depends on the electron donating strength of the aryl moieties (VDA = 0.22–0.55 eV), as well as the molecular conformation, based on steady state and time-resolved transient absorption spectroscopies. We also found that electron coupling does not show the add-up (or synergetic) effect. Solvent polarity-dependent intersystem crossing (ISC) was observed for the dyad/triads and singlet oxygen quantum yield decreases in polar solvents. Femtosecond transient absorption results indicate that the charge separation (CS) for 9-An-NDI-NH occurs on time scale of 0.83 ps (in toluene) or 0.71 ps (in acetonitrile). The charge recombination (CR) process (50 ps in toluene) produces triplet state with ΦISC = 19%. The triplet state lifetime is up to 22 μs. This result indicates that orthogonal geometry for a compact electron donor/acceptor does not lead to efficient ISC via CR. Other factors such as the energy gap between the CS state and triplet state also determine the ISC efficiency

ASNV disappeared with Vmax in right SCA and OA improved after CEA in patient 1.

<p>A, INV can be seen at the pupil margin from 9 to 11 o’clock in the right eye before CEA. B, INV in the right eye disappeared at 10 days after CEA. C, TCD examination showed lower Vmax in right SCA and OA comparing to the left side before CEA in the right ICA. D, TCD examination showed improved Vmax in right SCA and OA comparing to the left side at 10 days after CEA in the right ICA.</p

Image_1_Identifying Gut Microbiota Associated With Colorectal Cancer Using a Zero-Inflated Lognormal Model.TIF

Colorectal cancer (CRC) is the third most common cancer worldwide. Its incidence is still increasing, and the mortality rate is high. New therapeutic and prognostic strategies are urgently needed. It became increasingly recognized that the gut microbiota composition differs significantly between healthy people and CRC patients. Thus, identifying the difference between gut microbiota of the healthy people and CRC patients is fundamental to understand these microbes' functional roles in the development of CRC. We studied the microbial community structure of a CRC metagenomic dataset of 156 patients and healthy controls, and analyzed the diversity, differentially abundant bacteria, and co-occurrence networks. We applied a modified zero-inflated lognormal (ZIL) model for estimating the relative abundance. We found that the abundance of genera: Anaerostipes, Bilophila, Catenibacterium, Coprococcus, Desulfovibrio, Flavonifractor, Porphyromonas, Pseudoflavonifractor, and Weissella was significantly different between the healthy and CRC groups. We also found that bacteria such as Streptococcus, Parvimonas, Collinsella, and Citrobacter were uniquely co-occurring within the CRC patients. In addition, we found that the microbial diversity of healthy controls is significantly higher than that of the CRC patients, which indicated a significant negative correlation between gut microbiota diversity and the stage of CRC. Collectively, our results strengthened the view that individual microbes as well as the overall structure of gut microbiota were co-evolving with CRC.</p

BOIMPY-Based NIR-II Fluorophore with High Brightness and Long Absorption beyond 1000 nm for In Vivo Bioimaging: Synergistic Steric Regulation Strategy

Fluorescence imaging in the second near-infrared (NIR-II, 1000–1700 nm) region holds great promise for in vivo bioimaging. However, it is challenging to develop a brilliant donor–acceptor–donor (D–A–D) type NIR-II fluorophore with maximal absorption beyond 1000 nm in aqueous solution. Herein, we report a bright D–A–D type BOIMPY-based NIR-II dye (NK1143) with peak absorption/emission at 1005/1143 nm for in vivo bioimaging. Co-assembly of NK1143, SC12 (intermolecular steric hindrance modulator), and DSPE-PEG2000 effectively inhibits H-aggregation of NK1143 in aqueous solution and enhances the brightness simultaneously up to 53-fold by leveraging synergistic steric regulation strategy. Notably, this strategy allows for deep optical penetration of 8 mm and high-resolution blood vessels imaging in vivo, displaying high signal-to-background ratio of 7.8/1 under 980 nm excitation. More importantly, the BOIMPY-based nanoprobe can passively target and clearly visualize broad types of tumor xenografts, further improving intraoperative NIR-II fluorescence-guided resection of tiny metastases of less than 1 mm. This work provides an effective strategy for the development of BOIMPY-based NIR-II organic fluorophores with broad applications

Characteristics of the study population.

<p><b>Abbreviations:</b> M, male; F, female; DR, diabetic retinopathy; PDR, proliferative diabetic retinopathy;</p><p>Characteristics of the study population.</p

Polymorphisms in the <i>HTRA1</i> gene lesion: Distribution and Genotypes in neovascular Age-Related Macular Degeneration (nAMD), Polypoidal Choroidal Vasculopathy, and Controls in the northern Chinese Population.

*<p><i>p</i>-Value <0.05 is considered to be statistically significant and they are shown in bold.</p>**<p>OR(95%CI): Odds ratios are given for the risk allele compared with the wildtype allele.</p

Soil chemical properties in different soil depths across the 0‒5.2 m soil profiles in the N0 and N600 treatments.

Soil clay content (a), pH (b), soil organic carbon (c) and nitrate content (d) in different soil depths across the 0‒5.2 m soil profiles in the N0 and N600 treatments. N0 and N600 represent fertilizer N input rates of 0 and 600 kg N ha-1 year-1, respectively. Relative errors were less than 0.05 for all the measured parameters (n = 2).</p

Postmenstrual and chronological age at treatment, by birth weight and gestational age (prethreshold).

<p>* Statistically significant differences at p<0.05</p><p>Postmenstrual and chronological age at treatment, by birth weight and gestational age (prethreshold).</p

S1 Data -

(XLSX)</p