Antibacterial and antibiofilm efficacy of Solanum lasiocarpum root extract synthesized silver/silver chloride nanoparticles against Staphylococcus haemolyticus associated with bovine mastitis.

Staphylococcus haemolyticus is a cause of bovine mastitis, leading to inflammation in the mammary gland. This bacterial infection adversely affects animal health, reducing milk quality and yield. Its emergence has been widely reported, representing a significant economic loss for dairy farms. Interestingly, S. haemolyticus exhibits higher levels of antimicrobial resistance than other coagulase-negative Staphylococci. In this study, we synthesized silver/silver chloride nanoparticles (Ag/AgCl-NPs) using Solanum lasiocarpum root extract and evaluated their antibacterial and antibiofilm activities against S. haemolyticus. The formation of the Ag/AgCl-NPs was confirmed using UV-visible spectroscopy, which revealed maximum absorption at 419 nm. X-ray diffraction (XRD) analysis demonstrated the crystalline nature of the Ag/AgCl-NPs, exhibiting a face-centered cubic lattice. Fourier transform infrared (FT-IR) spectroscopy elucidated the functional groups potentially involved in the Ag/AgCl-NPs synthesis. Transmission electron microscopy (TEM) analysis revealed that the average particle size of the Ag/AgCl-NPs was 10 nm. Antimicrobial activity results indicated that the minimum inhibitory concentration (MIC) and maximum bactericidal concentration (MBC) of the Ag/AgCl-NPs treatment were 7.82-15.63 µg/mL towards S. haemolyticus. Morphological changes in bacterial cells treated with the Ag/AgCl-NPs were observed under scanning electron microscopy (SEM). The Ag/AgCl-NPs reduced both the biomass of biofilm formation and preformed biofilm by approximately 20.24-94.66 % and 13.67-88.48 %. Bacterial viability within biofilm formation and preformed biofilm was reduced by approximately 21.56-77.54 % and 18.9-71.48 %, respectively. This study provides evidence of the potential of the synthesized Ag/AgCl-NPs as an antibacterial and antibiofilm agent against S. haemolyticus.

Dual-Responsive Carbon Quantum Dots for the Simultaneous Detection of Cytosine and 5-Methylcytosine Interpreted by a Machine Learning-Assisted Smartphone.

DNA methylation is an epigenetic alteration that results in 5-methylcytosine (5-mC) through the addition of a methyl group to the fifth carbon of a cytosine (C) residue. The methylation level, the ratio of 5-mC to C, in urine might be related to the whole-body epigenetic status and the occurrence of common cancers. To date, never before have any nanomaterials been developed to simultaneously determine C and 5-mC in urine samples. Herein, a dual-responsive fluorescent sensor for the urinary detection of C and 5-mC has been developed. This assay relied on changes in the optical properties of nitrogen-doped carbon quantum dots (CQDs) prepared by microwave-assisted pyrolysis. In the presence of C, the blue-shifted fluorescence intensity of the CQDs increased. However, fluorescence quenching was observed upon the addition of 5-mC. This was primarily due to photoinduced electron transfer as confirmed by the density functional theory calculation. In urine samples, our sensitive fluorescent sensor had detection limits for C and 5-mC of 43.4 and 74.4 µM, respectively, and achieved satisfactory recoveries ranging from 103.5 to 115.8%. The simultaneous detection of C and 5-mC leads to effective methylation level detection, achieving recoveries in the range of 104.6-109.5%. Besides, a machine learning-enabled smartphone was also developed, which can be effectively applied to the determination of methylation levels (0-100%). These results demonstrate a simple but very effective approach for detecting the methylation level in urine, which could have significant implications for predicting the clinical prognosis.

Nanoscale carbon dot-embedded metal-organic framework for turn-on fluorescence detection of water in organic solvents.

An easy-to-use, highly selective, and real-time organic solvent quality assessment is desirable to detect water contamination in organic solvents. Herein, a one-step procedure using ultrasound irradiation was used for encapsulating nanoscale carbon dots (CDs) into metal-organic framework-199 (HKUST-1) to form CDs@HKUST-1 composite. The CDs@HKUST-1 exhibited very weak fluorescence due to photo-induced electron transfer (PET) from the CDs to the Cu2+ centers, acting as a fluorescent sensor in its off-state. The designed material can detect and discriminate water from other organic solvents, driven by turn-on fluorescence. This highly sensitive sensing platform could be applied for the detection of water in ethanol, acetonitrile, and acetone with wide linear detection ranges of 0-70% v/v, 2-12% v/v, and 10-50% v/v and limits of detection of 0.70% v/v, 0.59% v/v, and 1.08% v/v, respectively. The detection mechanism is attributed to the interruption of the PET process due to the release of fluorescent CDs after treatment with water. A smartphone-based quantitative test was successfully developed to monitor the water content in organic solvents utilizing CDs@HKUST-1 and a phone color processing application, thus making it possible to develop an on-site, real time and easy-to-use sensor for water detection.

Multifunctional fluorescent Eu-MOF probe for tetracycline antibiotics and dihydrogen phosphate sensing and visualizing latent fingerprints.

The contamination of tetracycline antibiotics and dihydrogen phosphate (H2PO4 -) in food and the environment is one of the major concerns for human health. Herein, a water-stable carboxyl-functionalized europium metal-organic framework (Eu-MOF) was prepared and demonstrated, for the first time, as a dual-responsive fluorescent sensor of tetracycline antibiotics (oxytetracycline (OTC), tetracycline (TC), and doxycycline (DOX)) and H2PO4 - via fluorescent turn-on and turn-off, respectively. Eu-MOF presents a sensitive and selective detection of OTC with a rapid response time (1 min) and good anti-interference ability. The limits of detection (LODs) of 78 nm, 225 nm, and 201 nM were achieved for OTC, TC, and DOX, respectively. Coordination and hydrogen bonding led to energy and electron transfer from the TC to the MOF, contributing to the fluorescent enhancement mechanism. Moreover, Eu-MOF can effectively detect H2PO4 - via fluorescence turn-off with a LOD of 0.70 µM. The interactions between H2PO4 - and MOF interrupt the energy transfer from ligand to MOF, leading to fluorescence quenching. In addition, Eu-MOF was successfully applied to determine OTC and H2PO4 - in real samples, obtaining satisfactory recoveries and RSDs. More fascinating, Eu-MOF could be utilized to develop latent fingerprints on various surfaces, providing well-defined fluorescent fingerprint details in which the sweat pores can be seen with the naked eye.

Human sensor-inspired supervised machine learning of smartphone-based paper microfluidic analysis for bacterial species classification.

Bacteria identification has predominantly been conducted using specific bioreceptors such as antibodies or nucleic acid sequences. This approach may be inappropriate for environmental monitoring when the user does not know the target bacterial species and for screening complex water samples with many unknown bacterial species. In this work, we investigate the supervised machine learning of the bacteria-particle aggregation pattern induced by the peptide sets identified from the biofilm-bacteria interface. Each peptide is covalently conjugated to polystyrene particles and loaded together with bacterial suspensions onto paper microfluidic chips. Each peptide interacts with bacterial species to a different extent, leading to varying sizes of particle aggregation. This aggregation changes the surface tension and viscosity of the liquid flowing through the paper pores, altering the flow velocity at different extents. A smartphone camera captures this flow velocity without being affected by ambient and environmental conditions, towards a low-cost, rapid, and field-ready assay. A collection of such flow velocity data generates a unique fingerprinting profile for each bacterial species. Support vector machine is utilized to classify the species. At optimized conditions, the training model can predict the species at 93.3% accuracy out of five bacteria: Escherichia coli, Staphylococcus aureus, Salmonella Typhimurium, Enterococcus faecium, and Pseudomonas aeruginosa. Flow rates are monitored for less than 6 s and the sample-to-answer assay time is less than 10 min. The demonstrated method can open a new way of analyzing complex biological and environmental samples in a biomimetic manner with machine learning classification.

Sonochemical synthesis of microscale Zn(ii)-MOF with dual Lewis basic sites for fluorescent turn-on detection of Al3+ and methanol with low detection limits.

The effects of synthetic methods, modulator types, the content of the modulator, and reaction time on the size and morphology of a microscale Zn-MOF containing dual Lewis basic amino and carbonyl groups, namely [Zn(NH2-bdc)(4,4'-bpy)] {NH2-H2bdc = 2-amino-1,4-benzenedicarboxylic acid and 4,4'-bpy = 4,4'-bipyridine}, were systemically investigated. Uniform octahedral microparticles of Zn-MOF with an average size of 1.7 µm were obtained within an hour at ambient temperature under ultrasound irradiation using sodium acetate as a modulating agent. Interestingly, Zn-MOF has been demonstrated for the dual-functional fluorescent detection of Al3+ and methanol based on a fluorescent turn-on strategy. Very low detection limits (LODs) for Al3+ and methanol were achieved using microcrystalline Zn-MOF and reached 30 nM and 0.7% (v/v), respectively. In comparison to the larger size of the polycrystalline Zn-MOF, the microparticles obtained from the ultrasonic route exhibited an improvement in the detection sensitivity. The dual uncoordinated Lewis basic sites play an important role in the sensitivity and selectivity of the detection. Additionally, the fluorogenic change in the sensing process can be observed by the naked eye under UV-light, allowing preliminary on-field screening.