Dual-functional metal-organic framework for chemisorption and colorimetric monitoring of cyanogen chloride.

Given the growing concern over the deployment of toxic chemicals in warfare, the rapid and accurate removal and detection of cyanogen chloride (CK) as a blood agent has become increasingly critical. However, conventional physisorbents and chemisorbents used in military respirators are insufficient for the effective removal of CK. In this study, we demonstrate the chemisorption and sensing abilities of Co2(m-DOBDC) (m-DOBDC4- = 4,6-dioxo-1,3-benzenedicarboxylate) for CK via electrophilic aromatic substitution (EAS) in humid environments. Unlike the chemisorption in triethylenediamine (TEDA) impregnated carbon materials, which generates by-products through hydrolysis, the electron-rich C5 sites in m-DOBDC4- ligands give rise to cyano substitution with CK. This leads to the formation of stable C-C bonds and chloride ions (Cl-) coordinating with open Co2+ sites. Such a mechanism prevents the generation of toxic by-products like cyanic acid and hydrochloric acid. Breakthrough experiments conducted in a packed-bed system conclusively demonstrated the superior CK removal capacity of Co2(m-DOBDC) (1662 min/g), compared to TEDA-impregnated activated carbon (323 min/g) under humid conditions. Considering that MOF-74 series, isostructural with Co2(m-DOBDC), barely adsorb CK under similar conditions, this finding marks a significant advancement in developing novel sorbents for CK removal. Moreover, this chemisorption not only exhibited rapid and highly efficient CK removal but also enabled colorimetric monitoring via the distinctive color change induced by the coordination of Cl- acting as σ donors. These findings facilitate the development of adsorption and sensing equipment to protect military personnel from toxic chemical threats.

Detection of Micrometer-Sized Virus Aerosols by Using a Real-Time Bioaerosol Monitoring System.

This study investigates a real-time handheld bioaerosol monitoring system for the detection of biological particles using UV-LED and light-induced fluorescence technology. Biological particles produce both scattering and fluorescence signals simultaneously, which can help distinguish them from general particles. The detected scattering, fluorescence, and simultaneous signals are then converted into photon signals and categorized based on predetermined criteria. A reliable biological particle generator was required to validate the performance of the system. This study explores the use of an M13 bacteriophage as a virus simulant of biological agents and employs a customized inkjet aerosol generator to produce M13 bacteriophage aerosols of a specific size by controlling the concentration of M13. We confirmed that micro-sized, narrowly dispersed M13 aerosols were efficiently generated. Additionally, we confirmed the performance of this real-time handheld bioaerosol monitoring system by detecting viruses.

Ultralight and Ultrathin Electrospun Membranes with Enhanced Air Permeability for Chemical and Biological Protection.

With the growing interest in chemical and biological warfare agents (CWAs/BWAs), the focus has shifted toward aerosol protection using protective clothing. However, compared to air-permeable membranes, those with water vapor permeability have been investigated more extensively. Filtering membranes without air permeability have limited practical usage in personal protective suits and masks. In this study, polyacrylonitrile membranes with tightly attached activated carbon and doped copper(II) oxide were prepared via electrospinning. The nanofibers with uniformly controlled diameters and smooth morphologies enable water/air breathability and protection against aerosol (100 nm polystyrene nanobeads similar to SARS-CoV-2) penetration. The uniformly distributed and tightly attached activated carbon and doped copper(II) oxide particles enhance the sorptive performance of the membranes by blocking gaseous CWAs, including soman, nerve chemical agents, and BWAs. Such dual-purpose membranes can be implemented in protective equipment owing to their high performance and easy processing.

Learning Curve Analysis of Single-Site Robot-Assisted Hysterectomy.

We aim to analyze the surgical outcomes and learning curve of single-site robot-assisted hysterectomy. This was a retrospective cohort study from a single academic medical center. A total of 123 patients who underwent single-site robotic surgery for gynecologic disease were enrolled. Gynecologic surgeries were performed by a single surgeon using single-site robot-assisted hysterectomy. The median age of enrolled patients was 49 years (range: 30-74 years). The median operation time was 131 min (range: 59-502 min) and the median docking time was 3 min (range: 1-10 min). In addition, the median console time was 76 min (range: 29-465 min). The cumulative sum (CUSUM) graph for total operation time indicated an initial decrease at case 41, generating 3 distinct performance phases: learning (n = 41 initial cases), competence (n = 54 middle cases), and mastery (n = 28 final cases). There was one case conversion to open surgery due to the difficulty in securing the field of view because of a 16-cm bulky mass protruding from the left pelvic wall. No patients required a transfusion and two complications including vaginal cuff dehiscence were identified. The single-site robot-assisted hysterectomy is a safe and feasible procedure. The learning curve consisted of 41 cases to significantly decrease the total operation time.

Long-term effects of the mean hemoglobin A1c levels after percutaneous coronary intervention in patients with diabetes.

BACKGROUND/AIMS: The clinical benefit of strict blood glucose-lowering therapy for patients with coronary artery disease (CAD) is still debated. We aimed to evaluate the long-term outcomes of patients with diabetes who underwent percutaneous coronary intervention (PCI), according to the mean hemoglobin A1c (HbA1c) level after PCI. METHODS: We evaluated 675 diabetes patients with CAD treated with PCI. We categorized the study population into three groups based on the mean observed HbA1c levels during the follow-up duration, as follows: aggressive control (AC) group (HbA1c level < 6.5%, n = 148), moderate control (MC) group (HbA1c level ≥ 6.5% and < 7.0%, n = 138), and uncontrolled (UC) group (HbA1c level ≥ 7.0%, n = 389). The primary endpoint was major adverse cardiovascular and cerebrovascular events (MACCEs), defined as cardiac death, myocardial infarction, repeat target vessel revascularization, and stroke. RESULTS: The mean HbA1c level of the AC group was significantly lower than that of the MC and UC groups (6.04% ± 0.36% vs. 6.74% ± 0.14% vs. 8.39% ± 1.20%, p < 0.001). The incidence of MACCEs was significantly lower in the AC group than in the MC and UC groups (16.0% vs. 24.3% vs. 26.3%, p = 0.010), mostly driven by the incidence of stroke (4.4% vs. 14.0% vs. 11.4%, p = 0.013). Multivariate Cox regression analysis showed that only the AC group was associated with a reduced rate of MACCEs (hazard ratio, 0.499; 95% confidence interval, 0.316 to 0.786; p = 0.004) compared with the UC group. CONCLUSION: Our study showed that intensive glycemic control (HbA1c level < 6.5%) is associated with improved clinical outcomes after PCI in patients with diabetes.