Unveiling Enhanced PEC Water Oxidation: Morphology Tuning and Interfacial Phase Change in α-Fe2O3@K-OMS-2 Branched Core-Shell Nanoarrays.

A simple fabrication method that involves two steps of hydrothermal reaction has been demonstrated for the growth of α-Fe2O3@K-OMS-2 branched core-shell nanoarrays. Different reactant concentrations in the shell-forming step led to different morphologies in the resultant composites, denoted as 0.25 OC, 0.5 OC, and 1.0 OC. Both 0.25 OC and 0.5 OC formed perfect branched core-shell structures, with 0.5 OC possessing longer branches, which were observed by SEM and TEM. The core K-OMS-2 and shell α-Fe2O3 were confirmed by grazing incidence X-ray diffraction (GIXRD), EDS mapping, and atomic alignment from high-resolution STEM images. Further investigation with high-resolution HAADF-STEM, EELS, and XPS indicated the existence of an ultrathin layer of Mn3O4 sandwiched at the interface. All composite materials offered greatly enhanced photocurrent density at 1.23 VRHE, compared to the pristine Fe2O3 photoanode (0.33 mA/cm2), and sample 0.5 OC showed the highest photocurrent density of 2.81 mA/cm2. Photoelectrochemical (PEC) performance was evaluated for the samples by conducting linear sweep voltammetry (LSV), applied bias photo-to-current efficiency (ABPE), electrochemical impedance spectroscopy (EIS), incident-photo-to-current efficiency (IPCE), transient photocurrent responses, and stability tests. The charge separation and transfer efficiencies, together with the electrochemically active surface area, were also investigated. The significant enhancement in sample 0.5 OC is ascribed to the synergetic effect brought by the longer branches in the core-shell structure, the conductive K-OMS-2 core, and the formation of the Mn3O4 thin layer formed between the core and shell.

Lipophilic AIEgens as the "Trojan Horse" with Discrepant Efficacy in Tracking and Treatment of Mycobacterial Infection.

The highly contagious tuberculosis is a leading infectious killer, which urgently requires effective diagnosis and treatment methods. To address these issues, three lipophilic aggregation-induced emission (AIE) photosensitizers (TTMN, TTTMN, and MeOTTMN) are selected to evaluate their labeling and antimicrobial properties in vitro and in vivo. These three lipophilic AIEgens preserve low cytotoxicity and achieve real-time and non-invasive visualization of the process of mycobacteria infection in vitro and in vivo. More importantly, these AIEgens can be triggered by white light to produce reactive oxygen species (ROS), which is a highly efficient antibacterial reagent. Among these AIEgens, the TTMN photosensitizer has an outstanding antibacterial efficacy over the clinical first-line drug rifampicin at the same therapeutic concentration. Interestingly, this study also finds that TTMN can increase the expression of pro-inflammatory cytokines in the early stage of infection after light irradiation, indicating an additional pro-inflammatory role of TTMN. This work provides some feasibility basis for developing AIEgens-based agents for effectively destroying mycobacterium.

Development and validation of a deep learning model for multicategory pneumonia classification on chest computed tomography: a multicenter and multireader study.

Background: Accurate diagnosis of pneumonia is vital for effective disease management and mortality reduction, but it can be easily confused with other conditions on chest computed tomography (CT) due to an overlap in imaging features. We aimed to develop and validate a deep learning (DL) model based on chest CT for accurate classification of viral pneumonia (VP), bacterial pneumonia (BP), fungal pneumonia (FP), pulmonary tuberculosis (PTB), and no pneumonia (NP) conditions. Methods: In total, 1,776 cases from five hospitals in different regions were retrospectively collected from September 2019 to June 2023. All cases were enrolled according to inclusion and exclusion criteria, and ultimately 1,611 cases were used to develop the DL model with 5-fold cross-validation, with 165 cases being used as the external test set. Five radiologists blindly reviewed the images from the internal and external test sets first without and then with DL model assistance. Precision, recall, F1-score, weighted F1-average, and area under the curve (AUC) were used to evaluate the model performance. Results: The F1-scores of the DL model on the internal and external test sets were, respectively, 0.947 [95% confidence interval (CI): 0.936-0.958] and 0.933 (95% CI: 0.916-0.950) for VP, 0.511 (95% CI: 0.487-0.536) and 0.591 (95% CI: 0.557-0.624) for BP, 0.842 (95% CI: 0.824-0.860) and 0.848 (95% CI: 0.824-0.873) for FP, 0.843 (95% CI: 0.826-0.861) and 0.795 (95% CI: 0.767-0.822) for PTB, and 0.975 (95% CI: 0.968-0.983) and 0.976 (95% CI: 0.965-0.986) for NP, with a weighted F1-average of 0.883 (95% CI: 0.867-0.898) and 0.846 (95% CI: 0.822-0.871), respectively. The model performed well and showed comparable performance in both the internal and external test sets. The F1-score of the DL model was higher than that of radiologists, and with DL model assistance, radiologists achieved a higher F1-score. On the external test set, the F1-score of the DL model (F1-score 0.848; 95% CI: 0.824-0.873) was higher than that of the radiologists (F1-score 0.541; 95% CI: 0.507-0.575) as was its precision for the other three pneumonia conditions (all P values <0.001). With DL model assistance, the F1-score for FP (F1-score 0.541; 95% CI: 0.507-0.575) was higher than that achieved without assistance (F1-score 0.778; 95% CI: 0.750-0.807) as was its precision for the other three pneumonia conditions (all P values <0.001). Conclusions: The DL approach can effectively classify pneumonia and can help improve radiologists' performance, supporting the full integration of DL results into the routine workflow of clinicians.

Seeing is believing: Efficiency evaluation of multifunctional ionic-dependent AIEgens for tuberculosis.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a significant public health threat with high rates of infection and mortality. Rapid and reliable theranostics of TB are essential to control transmission and shorten treatment duration. In this study, we report two cationic aggregation-inducing emission luminogens (AIEgens) named TTVP and TTPy, which have different functional charged moieties, to investigate their potential for simultaneous tracing and photodynamic therapy in TB infection. TTVP and TTPy exhibit intrinsic positive charges, excellent water solubility, and near-infrared (NIR) emission. Based on ionic-function relationships, TTVP, with more positive charges, demonstrates a stronger binding affinity to Mycobacterium marinum (M.m), (a close genetic relative of Mtb), compared to TTPy. Both TTVP and TTPy exhibit high efficiency in generating reactive oxygen species (ROS) when exposed to white light irradiation, enabling effective photodynamic killing of M.m in vitro. Additionally, we achieved long-term, real-time, noninvasive, continuous tracing, and evaluated therapeutic performance in vivo. Notably, TTVP outperformed TTPy in intracellular killing of M.m, suggesting a possible correlation between the labeling and photodynamic killing abilities of AIEgens. These findings provide valuable insights and a design basis for cationic AIEgens in TB research, offering potential advancements in TB theranostics.

Highly Mesoporous MoO3 Catalysts for Electrophilic Aromatic Substitution.

Herein, a straightforward synthesis method for highly mesoporous molybdenum oxide has been demonstrated via use of inverse micelles and molybdenum-oxo cluster formation. The synthesized catalyst is stable, crystalline, and MoO3 phase pure, as confirmed through thermogravimetric analysis, X-ray diffraction, and X-ray photoelectron spectroscopy. Further results from electron paramagnetic resonance, Raman spectroscopy, and UV-vis spectroscopy confirm the MoO3 phase purity. Chemisorption studies reveal that the synthesized material is 65 times more active than its commercial parts. The quantitative value of ammonia chemisorption for the synthesized catalyst is 1270 µmol/g, whereas the commercial catalyst only gives 22 µmol/g. These materials were tested for electrophilic substitution reactions since they are excellent solid acid. Electrophilic substitution of benzyl alcohol with toluene gives a >99% conversion with ∼80% of selectivity toward the methyl diphenylmethane product. The turnover number and turnover frequency values were calculated to be as high as 115 and 38, respectively. A substrate scope study shows that the reaction has preference toward electron-donating groups, whereas electron-withdrawing groups block the reaction. Based on the obtained results, a mechanism has been proposed.