Defect engineering on electrocatalysts for sustainable nitrate reduction to ammonia: Fundamentals and regulations

Electrocatalytic nitrate (NO3 -) reduction to ammonia (NH3) is a "two birds-one stone" method that targets remediation of NO3 --containing sewage and production of valuable NH3. The exploitation of advanced catalysts with high activity, selectivity, and durability is a key issue for the efficient catalytic performance. Among various strategies for catalyst design, defect engineering has gained increasing attention due to its ability to modulate the electronic properties of electrocatalysts and optimize the adsorption energy of reactive species, thereby enhancing the catalytic performance. Despite previous progress, there remains a lack of mechanistic insights into the regulation of catalyst defects for NO3 - reduction. Herein, this review presents insightful understanding of defect engineering for NO3 - reduction, covering its background, definition, classification, construction, and underlying mechanisms. Moreover, the relationships between regulation of catalyst defects and their catalytic activities are illustrated by investigating the properties of electrocatalysts through the analysis of electronic band structure, charge density distribution, and controllable adsorption energy. Furthermore, challenges and perspectives for future development of defects in NO3RR are also discussed, which can help researchers to better understand the defect engineering in catalysts, and also inspire scientists entering into this promising field.

Endoscopic ultrasound-based application system for predicting endoscopic resection-related outcomes and diagnosing subepithelial lesions: Multicenter prospective study

OBJECTIVES

Subepithelial lesions (SELs) are associated with various endoscopic resection (ER) outcomes and diagnostic challenges. We aimed to establish a tool for predicting ER-related outcomes and diagnosing SELs and to investigate the predictive value of endoscopic ultrasound (EUS).

METHODS

Phase 1 (system development) was performed in a retrospective cohort (n = 837) who underwent EUS before ER for SELs at eight hospitals. Prediction models for five key outcomes were developed using logistic regression. Models with satisfactory internal validation performance were included in a mobile application system, SEL endoscopic resection predictor (SELERP). In Phase 2, the models were externally validated in a prospective cohort of 200 patients.

RESULTS

An SELERP was developed using EUS characteristics, which included 10 models for five key outcomes: post-ER ulcer management, short procedure time, long hospital stay, high medication costs, and diagnosis of SELs. In Phase 1, 10 models were derived and validated (C-statistics, 0.67-0.99; calibration-in-the-large, -0.14-0.10; calibration slopes, 0.92-1.08). In Phase 2, the derived risk prediction models showed convincing discrimination (C-statistics, 0.64-0.73) and calibration (calibration-in-the-large, -0.02-0.05; calibration slopes, 1.01-1.09) in the prospective cohort. The sensitivities and specificities of the five diagnostic models were 68.3-95.7% and 64.1-83.3%, respectively.

CONCLUSION

We developed and prospectively validated an application system for the prediction of ER outcomes and diagnosis of SELs, which could aid clinical decision-making and facilitate patient-physician consultation. EUS features significantly contributed to the prediction.

TRIAL REGISTRATION

Chinese Clinical Trial Registry, http://www.chictr.org.cn (ChiCTR2000040118).

Graded diagnosis of Helicobacter pylori infection using hyperspectral images of gastric juice

Helicobacter pylori is a potential underlying cause of many diseases. Although the Carbon 13 breath test is considered the gold standard for detection, it is high cost and low public accessibility in certain areas limit its widespread use. In this study, we sought to use machine learning and deep learning algorithm models to classify and diagnose H. pylori infection status. We used hyperspectral imaging system to gather gastric juice images and then retrieved spectral feature information between 400 and 1000 nm. Two different data processing methods were employed, resulting in the establishment of one-dimensional (1D) and two-dimensional (2D) datasets. In the binary classification task, the random forest model achieved a prediction accuracy of 83.27% when learning features from 1D data, with a specificity of 84.56% and a sensitivity of 92.31%. In the ternary classification task, the ResNet model learned from 2D data and achieved a classification accuracy of 91.48%.

Intracavitary Spraying of Nanoregulator-Encased Hydrogel Modulates Cholesterol Metabolism of Glioma-Supportive Macrophage for Postoperative Glioblastoma Immunotherapy

Glioblastoma multiforme (GBM) is notoriously resistant to immunotherapy due to its intricate immunosuppressive tumor microenvironment (TME). Dysregulated cholesterol metabolism is implicated in the TME and promotes tumor progression. Here, it is found that cholesterol levels in GBM tissues are abnormally high, and glioma-supportive macrophages (GSMs), an essential "cholesterol factory", demonstrate aberrantly hyperactive cholesterol metabolism and efflux, providing cholesterol to fuel GBM growth and induce CD8+ T cells exhaustion. Bioinformatics analysis confirms that high 7-dehydrocholesterol reductase (DHCR7) level in GBM tissues associates with increased cholesterol biosynthesis, suppressed tumoricidal immune response, and poor patient survival, and DHCR7 expression level is significantly elevated in GSMs. Therefore, an intracavitary sprayable nanoregulator (NR)-encased hydrogel system to modulate cholesterol metabolism of GSMs is reported. The degradable NR-mediated ablation of DHCR7 in GSMs effectively suppresses cholesterol supply and activates T-cell immunity. Moreover, the combination of Toll-like receptor 7/8 (TLR7/8) agonists significantly promotes GSM polarization to antitumor phenotypes and ameliorates the TME. Treatment with the hybrid system exhibits superior antitumor effects in the orthotopic GBM model and postsurgical recurrence model. Altogether, the findings unravel the role of GSMs DHCR7/cholesterol signaling in the regulation of TME, presenting a potential treatment strategy that warrants further clinical trials.

A multi-omics study to investigate the progression of the Correa pathway in gastric mucosa in the context of cirrhosis

BACKGROUND

Patients with liver cirrhosis (LC) are prone to gastric mucosa damage. We investigated the alterations of gastric mucosa in LC patients and their possible mechanisms through multi-omics.

RESULTS

We observed significant gastric mucosa microbial dysbiosis in LC subjects. Gastric mucosal microbiomes of LC patients contained a higher relative abundance of Streptococcus, Neisseria, Prevotella, Veillonella, and Porphyromonas, as well as a decreased abundance in Helicobacter and Achromobacter, than control subjects. The LC patients had higher levels of bile acids (BAs) and long-chain acylcarnitines (long-chain ACs) in serum. The gastric mucosal microbiomes were associated with serum levels of BAs and long-chain ACs. Transcriptome analyses of gastric mucosa revealed an upregulation of endothelial cell specific molecule 1, serpin family E member 1, mucin 2, caudal type homeobox 2, retinol binding protein 2, and defensin alpha 5 in LC group. Besides, the bile secretion signaling pathway was significantly upregulated in the LC group.

CONCLUSIONS

The alterations in the gastric mucosal microbiome and transcriptome of LC patients were identified. The impaired energy metabolism in gastric mucosal cells and bile acids might aggravate the inflammation of gastric mucosa and even exacerbate the Correa's cascade process. The gastric mucosal cells might reduce bile acid toxicity by bile acid efflux and detoxification.

TRIAL REGISTRATION

ChiCTR2100051070.

Surficial nano-deposition locoregionally yielding bactericidal super CAR-macrophages expedites periprosthetic osseointegration

Tracking and eradicating Staphylococcus aureus in the periprosthetic microenvironment are critical for preventing periprosthetic joint infection (PJI), yet effective strategies remain elusive. Here, we report an implant nanoparticle coating that locoregionally yields bactericidal super chimeric antigen receptor macrophages (CAR-MΦs) to prevent PJI. We demonstrate that the plasmid-laden nanoparticle from the coating can introduce S. aureus-targeted CAR genes and caspase-11 short hairpin RNA (CASP11 shRNA) into macrophage nuclei to generate super CAR-MΦs in mouse models. CASP11 shRNA allowed mitochondria to be recruited around phagosomes containing phagocytosed bacteria to deliver mitochondria-generated bactericidal reactive oxygen species. These super CAR-MΦs targeted and eradicated S. aureus and conferred robust bactericidal immunologic activity at the bone-implant interface. Furthermore, the coating biodegradability precisely matched the bone regeneration process, achieving satisfactory osteogenesis. Overall, our work establishes a locoregional treatment strategy for priming macrophage-specific bactericidal immunity with broad application in patients suffering from multidrug-resistant bacterial infection.

[Femtosecond laser-assisted minimally invasive lamellar keratoplasty for advanced keratoconus]

Objective: To evaluate the initial safety and efficacy of femtosecond laser-assisted minimally invasive lamellar keratoplasty (FL-MILK) for advanced keratoconus. Methods: It was a case series study. Patients with advanced keratoconus who underwent FL-MILK between August 2017 and April 2020 at Shandong Eye Hospital were prospectively included. The femtosecond laser was used to create an intrastromal pocket in the recipient cornea and a lamellar cornea in the donor. The lamellar cornea was then gently inserted into the intrastromal pocket through the incision and flattened. Clinical measurements included best-corrected visual acuity, 3-mm anterior corneal mean keratometry, anterior and posterior central corneal elevation, central corneal thickness, corneal biomechanics, and endothelial cell density. The follow-up was conducted at 1 month, 12 months, and 24 months after the operation. Results: There were 33 patients (35 eyes) in the study. Twenty-six patients were male and 7 patients were female. The mean age was (20.34±5.24) years old. All patients completed 12 months of follow-up, and 25 patients (27 eyes) completed 24 months of follow-up. No epithelial ingrowth, infection, or allogeneic rejection was observed. Compared with the preoperative data, the anterior central corneal elevation significantly decreased (P<0.001), the mean keratometry significantly decreased (P<0.05), and the central corneal thickness significantly increased (P<0.001). The corneal biomechanical strength was significantly improved, with the deformation amplitude ratio at 2.0 mm decreasing from 1.39±0.14 preoperatively to 1.21±0.10 at 24 months postoperatively (P<0.001) and the stiffness parameter at the first applanation increasing from 41.49±11.47 preoperatively to 88.41±18.17 at 24 months postoperatively (P<0.001). There were no significant changes in the mean best-corrected visual acuity, posterior corneal elevation, mean spherical equivalent, and endothelial cell density (all P>0.05). Conclusions: FL-MILK may be a feasible option for advanced keratoconus. This procedure may provide a new resolution for keratoconus.