Biofilm-associated infections, which are able to resist antibiotics, pose a significant challenge in clinical treatments. Such infections have been linked to various medical conditions, including chronic wounds and implant-associated infections, making them a major public-health concern. Early-detection of biofilm formation offers significant advantages in mitigating adverse effects caused by biofilms. In this work, we aim to explore the feasibility of employing a novel wireless sensor for tracking both early-stage and matured-biofilms formed by the medically relevant bacteria Staphylococcus aureus and Pseudomonas aeruginosa. The sensor utilizes electrochemical reduction of an AgCl layer bridging two silver legs made by inkjet-printing, forming a part of near-field-communication tag antenna. The antenna is interfaced with a carbon cloth designed to promote the growth of microorganisms, thereby serving as an electron source for reduction of the resistive AgCl into a highly-conductive Ag bridge. The AgCl-Ag transformation significantly alters the impedance of the antenna, facilitating wireless identification of an endpoint caused by microbial growth. To the best of our knowledge, this study for the first time presents the evidence showcasing that electrons released through the actions of bacteria can be harnessed to convert AgCl to Ag, thus enabling the wireless, battery-less, and chip-less early-detection of biofilm formation.

Bacterial infections can affect the skin, lungs, blood, and brain, and are among the leading causes of mortality globally. Early infection detection is critical in diagnosis and treatment but is a time- and work-consuming process taking several days, creating a hitherto unmet need to develop simple, rapid, and accurate methods for bacterial detection at the point of care. The most frequent type of bacterial infection is infection of the urinary tract. Here, we present a wireless-enabled, portable, potentiometric sensor for E. coli. E. coli was chosen as a model bacterium since it is the most common cause of urinary tract infections. The sensing principle is based on reduction of Prussian blue by the metabolic activity of the bacteria, detected by monitoring the potential of the sensor, transferring the sensor signal via Bluetooth, and recording the output on a laptop or a mobile phone. In sensing of bacteria in an artificial urine medium, E. coli was detected in similar to 4 h (237 +/- 19 min; n = 4) and in less than 0.5 h (21 +/- 7 min, n = 3) using initial E. coli concentrations of similar to 10(3) and 10(5) cells mL(-1), respectively, which is under or on the limit for classification of a urinary tract infection. Detection of E. coli was also demonstrated in authentic urine samples with bacteria concentration as low as 10(4) cells mL(-1), with a similar response recorded between urine samples collected from different volunteers as well as from morning and afternoon urine samples.

To maximize the potential of 5G infrastructure in healthcare, simple integration of biosensors with wireless tag antennas would be beneficial. This work introduces novel glucose-to-resistor transduction, which enables simple, wireless biosensor design. The biosensor was realized on a near-field communication tag antenna, where a sensing bioanode generated electrical current and electroreduced a nonconducting antenna material into an excellent conductor. For this, a part of the antenna was replaced by a Ag nanoparticle layer oxidized to high-resistance AgCl. The bioanode was based on Au nanoparticle-wired glucose dehydrogenase (GDH). The exposure of the cathode-bioanode to glucose solution resulted in GDH-catalyzed oxidation of glucose at the bioanode with a concomitant reduction of AgCl to highly conducting Ag on the cathode. The AgCl-to-Ag conversion strongly affected the impedance of the antenna circuit, allowing wireless detection of glucose. Mimicking the final application, the proposed wireless biosensor was ultimately evaluated through the measurement of glucose in whole blood, showing good agreement with the values obtained with a commercially available glucometer. This work, for the first time, demonstrates that making a part of the antenna from the AgCl layer allows achieving simple, chip-less, and battery-less wireless sensing of enzyme-catalyzed reduction reaction. 

Atomic Force Microscopy (AFM) force measurements are a powerful tool for the nano-scale characterization of surface properties. However, the analysis of force measurements requires several processing steps. One is locating different type of events e.g., contact point, adhesions and indentations. At present, there is a lack of algorithms that can automate this process in a reliable way for different types of samples. Moreover, because of their stochastic nature, the acquisition and analysis of a high number of force measurements is typically required. This can result in these experiments becoming an overwhelming task if their analysis is not automated. Here, we propose a Machine Learning approach, the use of one-dimensional convolutional neural networks, to locate specific events within AFM force measurements. Specifically, we focus on locating the contact point, a critical step for the accurate quantification of mechanical properties as well as long-range interactions. We validate this approach on force measurements obtained both on hard and soft surfaces. This approach, which could be easily used to also locate other events e.g., indentations and adhesions, has the potential to significantly facilitate and automate the analysis of AFM force measurements and, therefore, the use of this technique by a wider community.

HYPOTHESIS: Among other functions, mucins hydrate and protect biological interfaces from mechanical challenges. Mucins also attract interest as biocompatible coatings with excellent lubrication performance. Therefore, it is of high interest to understand the structural response of mucin films to mechanical challenges. We hypothesized that this could be done with Neutron Reflectometry using a novel sample environment where mechanical confinement is achieved by inflating a membrane against the films.

EXPERIMENTS: Oral MUC5B mucin films were investigated by Force Microscopy/Spectroscopy and Neutron Reflectometry both at solid-liquid interfaces and under mechanical confinement.

FINDINGS: NR indicated that MUC5B films were almost completely compressed and dehydrated when confined at 1 bar. This was supported by Force Microscopy/Spectroscopy investigations. Force Spectroscopy also indicated that MUC5B films could withstand mechanical confinement by means of steric interactions for pressures lower than ∼ 0.5 bar i.e., mucins could protect interfaces from mechanical challenges of this magnitude while keeping them hydrated. To investigate mucin films under these pressures by means of the employed sample environment for NR, further technological developments are needed. The most critical would be identifying or developing more flexible membranes that would still meet certain requirements like chemical homogeneity and very low roughness.

HYPOTHESIS: Salivary pellicles i.e., thin films formed upon selective adsorption of saliva, protect oral surfaces against chemical and mechanical insults. Pellicles are also excellent aqueous lubricants. It is generally accepted that reconstituted pellicles have a two-layer structure, where the outer layer is mainly composed of MUC5B mucins. We hypothesized that by comparing the effect of ionic strength on reconstituted pellicles and MUC5B films we could gain further insight into the pellicle structure.

EXPERIMENTS: Salivary pellicles and MUC5B films reconstituted on solid surfaces were investigated at different ionic strengths by Force Spectroscopy, Quartz Crystal Microbalance with Dissipation, Null Ellipsometry and Neutron Reflectometry.

FINDINGS: Our results support the two-layer structure for reconstituted salivary pellicles. The outer layer swelled when ionic strength decreased, indicating a weak polyelectrolyte behavior. While initially the MUC5B films exhibited a similar tendency, this was followed by a drastic collapse indicating an interaction between exposed hydrophobic domains. This suggests that mucins in the pellicle outer layer form complexes with other salivary components that prevent this interaction. Lowering ionic strength below physiological values also led to a partial removal of the pellicle inner layer. Overall, our results highlight the importance that the interactions of mucins with other pellicle components play on their structure.

Continuous and automated bacteria detection is pivotal for a myriad of biomedical, food safety and envi-ronmental applications. This work presents the fabrication of a prototype of a passive (battery-free) radio frequency sensor for wireless detection of bacteria. The sensing mechanism is based on the bacterial-induced (proteases and peptidases) degradation of glutaraldehyde (GTA) cross-linked gelatin-caprylic acid (CA) composite film. Proteolytic degradation of the film resulted in a decrease of its resistivity, a quan-tity that could be wirelessly monitored by coupling the film to a radio-frequency antenna (an inductor-capacitor resonator) and monitoring the frequency for which the transferred power between this antenna and another antenna connected to a Vector Network Analyzer (VNA) was maximized. We experimen-tally proved this concept by monitoring E.coli bacteria in aqueous medium and detected at 18.0 +/- 2.8 h, 23.5 +/- 0.7 h, 27.0 +/- 2.8 h, 40.5 +/- 3.5 h, 45.5 +/- 0.7 h for the initial E.coli concentration of 3.2 +/- 10(8) , 6.8 +/- 10(7) , 2.3 +/- 10(6) , 4.3 +/- 10(5) , and 3.6 +/- 10(4) CFU/mL, respectively. Further, the E.coli induced degrada-tion of the composite film was investigated by evaluating the thickness of the film by optical microscopy as well as morphology by scanning electron microscopy techniques.

Surfactants are important components of oral care products. Sodium dodecyl sulfate (SDS) is the most common because of its foaming properties, taste and low cost. However, the use of ionic surfactants, especially SDS, is related to several oral mucosa conditions. Thus, there is a high interest in using non-ionic and amphoteric surfactants as they are less irritant. To better understand the performance of these surfactants in oral care products, we investigated their interaction with salivary pellicles i.e., the proteinaceous films that cover surfaces exposed to saliva. Specifically, we focused on pentaethylene glycol monododecyl ether (C12E5) and cocamidopropyl betaine (CAPB) as model nonionic and amphoteric surfactants respectively, and investigated their interaction with reconstituted salivary pellicles with various surface techniques: Quartz Crystal Microbalance with Dissipation, Ellipsometry, Force Spectroscopy and Neutron Reflectometry. Both C12E5 and CAPB were gentler on pellicles than SDS, removing a lower amount. However, their interaction with pellicles differed. Our work indicates that CAPB would mainly interact with the mucin components of pellicles, leading to collapse and dehydration. In contrast, exposure to C12E5 had a minimal effect on the pellicles, mainly resulting in the replacement/solubilisation of some of the components anchoring pellicles to their substrate.

Scanning probe microscopies allow investigating surfaces at the nanoscale, in real space and with unparalleled signal-to-noise ratio. However, these microscopies are not used as much as it would be expected considering their potential. The main limitations preventing a broader use are the need of experienced users, the difficulty in data analysis and the time-consuming nature of experiments that require continuous user supervision. In this work, we addressed the latter and developed an algorithm that controlled the operation of an Atomic Force Microscope (AFM) that, without the need of user intervention, allowed acquiring multiple high-resolution images of different molecules. We used DNA on mica as a model sample to test our control algorithm, which made use of two deep learning techniques that so far have not been used for real time SPM automation. One was an object detector, YOLOv3, which provided the location of molecules in the captured images. The second was a Siamese network that could identify the same molecule in different images. This allowed both performing a series of images on selected molecules while incrementing the resolution, as well as keeping track of molecules already imaged at high resolution, avoiding loops where the same molecule would be imaged an unlimited number of times. Overall, our implementation of deep learning techniques brings SPM a step closer to full autonomous operation.

For a better understanding of the effect of drugs and their interaction with cells and tissues, there is a need for in vitro and ex vivo model systems which enables studying these events. There are several in vitro methods available to evaluate the antioxidant activity; however, these methods do not factor in the complex in vivo physiology. Here we present an intestinal tissue modified oxygen electrode, used for the detection of the antioxidant effect of orally administered drugs in the presence of H₂O₂. Antioxidants are essential in the defense against oxidative stress, more specifically against reactive oxygen species such as H₂O_2. Due to the presence of native catalase in the intestine, with the tissue-based biosensor we were able to detect H₂O₂ in the range between 50 and 500 µM. The reproducibility of the sensor based on the calculated relative standard deviations was 15 ± 6%. We found that the O₂ production by catalase from H₂O₂ was reduced in the presence of a well-known antioxidant, quinol. This indirectly detected antioxidant activity was also observed in the case of orally administered drugs with a reported anti-inflammatory effect such as mesalazine and paracetamol, while no antioxidant activity was recorded with aspirin and metformin.