Theoretical Insights on the Charge State and Bifunctional OER/ORR Electrocatalyst Activity in 4d-Transition-Metal-Doped g‑C₃N₄ Monolayers

Exploring efficient and stable electrocatalysts for the bifunctional oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) is vital to developing renewable energy technologies. However, due to the substantial and intricate design space associated with these bifunctional OER/ORR electrocatalysts, their development presents a formidable challenge, resulting in their cost-prohibitive nature in both experimental and computational studies. Herein, using the defect physics method, we systematically investigate the formation energies and bifunctional overpotential (ηBi) of 4d-transition-metal (4d-TM, 4d-TM = Zr, Nb, Mo, Ru, Rh, Pd, and Ag)-doped monolayer supercell g-C3N4 (4d-TM@C54N72) based on the density functional theory (DFT) calculations. Under N-rich and C-rich conditions, we find that the formation energies of RhN@C54N71 (Rh occupation N) and PdN@C54N71 (Pd occupation N) are smaller than that of other 4d-TMN@C54N71 (4d-TM occupation N site); for the 4d-TMint@C54N72 (4d-TM interstitial site occupation), the lowest-formation energy defects are Pdint@C54N72. These results indicate that they have better stabilities. Interestingly, for these formation energy lower systems, Pd0int@C54N72 (ηBi = 1.00 V) and Rh1+N@C54N71 (ηBi = 0.73 V) have ultralow overpotential and can be great candidates for bifunctional OER/ORR electrocatalysts. We find the reason is that adjusting the charge states of 4d-TM@C54N72 can tune the interaction strength between the oxygenated intermediates and the 4d-TM@C54N72, which plays a crucial role in the activity of reactions. Additionally, the data obtained through machine learning (ML) application suggest that the electronegativity (Nm) and bond length of 4d-TM and coordination atoms (dTM‑OOH) are primary descriptors characterizing the OER and ORR activities, respectively. The charged defect tuning of the bifunctional OER/ORR activity for 4d-TM@C54N72 would enable electrocatalytic performance optimization and the development of potential electrocatalysts for renewable energy applications

Investigations on the p‑Type Formation Mechanisms of Group II and VII Elements and N‑Doped β‑Bi₂O₃

In this work, the feasibility of p- and n-type doping modifications in intrinsic n-type β-Bi2O3 via Group VII (F, Cl, Br, I) and Group II (Be, Mg, Ca, Sr) elements as well as N have been systematically investigated using first-principles hybrid functional calculations. Notably, the p-type modification mechanism in N-doped β-Bi2O3 has been extensively, carefully, and comparably explored and analyzed, in contrast to the famous N-doped ZnO case. It is found that the enhancement of the n-type conductivity in β-Bi2O3 by Group VII element doping is easily achieved, and F is the best n-type dopant candidate. However, achieving the transition from an unintentional n-type to a p-type semiconductor in β-Bi2O3 is very difficult via Group II element doping because of the stronger compensation effect from the intrinsic donor O1 vacancy defect and unintentional H interstitial (donor) as well as the self-compensation effects from the doping itself under thermal equilibrium growth conditions. Fortunately, it should be easier to dope and achieve the p-type conductivity in β-Bi2O3 using NO2 rather than these source gases, including N2, N2O, NO, and NH3 or Group II element doping under O-poor conditions. The substitutional defect NO2 is the most possible candidate for the p-type modification. However, because of the charge compensation effect, nonequilibrium conditions such as annealing under high temperatures may be essential in obtaining long-lasting p-type conductivity for β-Bi2O3. Understanding the different element doping effects on the p- or n-type conductivity in β-Bi2O3 can further facilitate relevant experimental preparation and application studies

The up-regulation of K17 expression in IL-22-induced keratinocytes.

<p>(<b>A</b>) The real-time PCR analysis of K17 mRNA levels. Data are expressed as 2^−ΔΔCT relative to untreated HaCaT cells. (<b>B</b>) The ELISA analysis of K17 expression. (<b>C</b>) The Western blot analysis of K17 protein expression. (<b>D</b>) Immunofluorescence was performed on HaCaT cells to measure K17 expression. DAPI staining for nuclei is in blue. The scale bars represent 30 µm. The blank group is untreated HaCaT cells. Results represent means±SEM from three independent experiments. *P<0.05 was considered significant for the IL-22 treated group versus blank.</p

The synergism of IL-22, IL-17A and IFN-γ in inducing K17 expression.

<p>HaCaT were treated with IL-22(25 ng/ml), IL-17A (100 U/ml) and IFN-γ (100 U/ml) alone or in combination. (<b>A</b>) The real-time PCR analysis of K17 mRNA levels after 24 h; Data are expressed as 2^−ΔΔCT relative to untreated HaCaT cells. (<b>B</b>) The Western blot analysis of K17 protein expression. The blank group is untreated HaCaT cells. Results represent means±SEM from three independent experiments. *P<0.05 was considered significant.</p

The activation of STAT3 and ERK1/2 signaling pathways in IL-22-treated HaCaT cells.

<p>HaCaT cells were treated with IL-22 and the expression of STAT3, ERK1/2, phospho-STAT3 or phospho-ERK1/2 was tested with corresponding antibodies. (<b>A</b>) The Western blot analysis of the activation of phospho-STAT3 and phospho-ERK1/2 in IL-22-treated HaCaT cells. (<b>B</b>) Immunofluorescence staining of phospho-STAT3 and phospho-ERK1/2 in IL-22-treated-HaCaT cells at different time points. Note that stronger signals were observed in the cultures at 15 min, 30 min or 60 min following IL-22 treatment. DAPI staining for nuclei is in blue. The scale bars represent 30 µm. The blank group is untreated HaCaT cells.</p

Selection of Aptamers for Hydrophobic Drug Docetaxel To Improve Its Solubility

With the development of combinatorial chemistry and high-throughput screening, the number of hydrophobic drug candidates continues to increase. However, the low solubility of hydrophobic drugs could induce erratic absorption patterns and affect the drug efficacy. Aptamers are artificially selected highly water-soluble oligonucleotides that bind to ions, small molecules, proteins, living cells, and even tissues. Herein, to increase the solubility of hydrophobic drug, we screened the aptamer by exploiting DNA library immobilization selection strategy and microfluidic technology. The highly water-soluble aptamer might influence the dissolving capacity of its target. To demonstrate the concept, docetaxel (DOC), a second-generation taxoid cytotoxic with significant antitumor agent activity, was chosen as the model. It is generally known that the clinical application of docetaxel is limited greatly owing to its poor water solubility and serious side effects. After seven rounds of selection, two docetaxel-specific aptamers DOC6–5 and DOC7–38, were successfully obtained, and their apparent dissociation constants (<i>K</i>_d) were at nanomolar level. Then these two 100 mer ssDNA aptamers against docetaxel were truncated to 22 mer ones by utilizing the recognition domain. Moreover, the shorter aptamer exhibited higher binding affinity than 100 mer ssDNA aptamers. By adding the optimized aptamer, the solubility of docetaxel was increased from ∼14 μM to ∼145 μM, and the cytotoxicity of docetaxel did not reduce in the presence of aptamer. Therefore, the aptamer was used as a solubilizer to improve the solubility of hydrophobic drug (docetaxel) in aqueous phase. This strategy may also be extended to other hydrophobic drugs. Meanwhile, this work could also provide a useful tool for tumor targeting therapy by combining with cell target ligands

Deep-Learning-Enhanced Diffusion Imaging Assay for Resolving Local-Density Effects on Membrane Receptors

G-protein-coupled receptor (GPCR) density at the cell surface is thought to regulate receptor function. Spatially resolved measurements of local-density effects on GPCRs are needed but technically limited by density heterogeneity and mobility of membrane receptors. We now develop a deep-learning (DL)-enhanced diffusion imaging assay that can measure local-density effects on ligand–receptor interactions in the plasma membrane of live cells. In this method, the DL algorithm allows the transformation of 100 ms exposure images to density maps that report receptor numbers over any specified region with ∼95% accuracy by 1 s exposure images as ground truth. With the density maps, a diffusion assay is further established for spatially resolved measurements of receptor diffusion coefficient as well as to express relationships between receptor diffusivity and local density. By this assay, we scrutinize local-density effects on chemokine receptor CXCR4 interactions with various ligands, which reveals that an agonist prefers to act with CXCR4 at low density while an inverse agonist dominates at high density. This work suggests a new insight into density-dependent receptor regulation as well as provides an unprecedented assay that can be applicable to a wide variety of receptors in live cells

Rational Design of Tetrahedral Derivatives as Efficient Light-Emitting Materials Based on “Super Atom” Perspective

Traditional semiconductor quantum dots of groups II–VI are key ingredients of next-generation display technology. Yet, the majority of them contain toxic heavy-metal elements, thus calling for alternative light-emitting materials. Herein, we have explored three novel categories of multicomponent compounds, namely, tetragonal II-III2-VI4 porous ternary compounds, cubic I2-II3-VI4 ternary compounds, and cubic I-II-III3-V4 quaternary compounds. This is achieved by judicious introduction of a “super atom” perspective and concurrently varying the solid-state lattice packing of involved super atoms or the population of surrounding counter cations. Based on first-principles calculations of 392 candidate materials with designed crystal structures, 53 highly stable materials have been screened. Strikingly, 34 of them are direct-bandgap semiconductors with emitting wavelengths covering the near-infrared and visible-light regions. This work provides a comprehensive database of highly efficient light-emitting materials, which may be of interest for a broad field of optoelectronic applications

Deep-Learning-Enhanced Diffusion Imaging Assay for Resolving Local-Density Effects on Membrane Receptors

G-protein-coupled receptor (GPCR) density at the cell surface is thought to regulate receptor function. Spatially resolved measurements of local-density effects on GPCRs are needed but technically limited by density heterogeneity and mobility of membrane receptors. We now develop a deep-learning (DL)-enhanced diffusion imaging assay that can measure local-density effects on ligand–receptor interactions in the plasma membrane of live cells. In this method, the DL algorithm allows the transformation of 100 ms exposure images to density maps that report receptor numbers over any specified region with ∼95% accuracy by 1 s exposure images as ground truth. With the density maps, a diffusion assay is further established for spatially resolved measurements of receptor diffusion coefficient as well as to express relationships between receptor diffusivity and local density. By this assay, we scrutinize local-density effects on chemokine receptor CXCR4 interactions with various ligands, which reveals that an agonist prefers to act with CXCR4 at low density while an inverse agonist dominates at high density. This work suggests a new insight into density-dependent receptor regulation as well as provides an unprecedented assay that can be applicable to a wide variety of receptors in live cells

Carrier-Free Immunotherapeutic Nano-Booster with Dual Synergistic Effects Based on Glutaminase Inhibition Combined with Photodynamic Therapy

The immunotherapeutic effect elicited by photodynamic therapy (PDT) is attenuated by tumor defense mechanisms associated with glutamine metabolism, including the metabolic regulation of redox homeostasis and the limitation of the immunosuppressive tumor microenvironment (ITM). Herein, a carrier-free immunotherapeutic nanobooster C9SN with dual synergistic effects was constructed by the self-assembly of glutaminase (GLS) inhibitor compound 968 (C968) and photosensitizer Chlorin e6. C968-mediated GSH deprivation through inhibiting glutamine metabolism prevented PDT-generated reactive oxygen species from being annihilated by GSH, amplifying intracellular oxidative stress, which caused severe cell death and also enhanced the immunogenic cell death (ICD) effect. In addition, genome-wide analysis was carried out using RNA-sequencing to evaluate the changes in cell transcriptome induced by amplifying oxidative stress. Thereafter, neoantigens generated by the enhanced ICD effect promoted the maturation of dendritic cells, thereby recruiting and activating cytotoxic T lymphocytes (CTLs). Meanwhile, C9SN remodeled the ITM by blocking glutamine metabolism to polarize M2-type tumor-associated macrophages (TAMs) into M1-type TAMs, which further recruited and activated the CTLs. Ultimately, this immunotherapeutic nanobooster suppressed primary and distant tumors. This “kill two birds with one stone” strategy would shed light on enhancing tumor immunogenicity and alleviating tumor immunosuppression to improve the immunotherapeutic effect of PDT