A gas sensor array was developed and evaluated using four high-frequency quartz crystal microbalance devices (with a 30 MHz resonant frequency in fundamental mode). The QCM devices were coated with ethyl cellulose (EC), polymethylmethacrylate (PMMA), Apiezon L (ApL), and Apiezon T (ApT) sensing films, and deposited by the ultrasonic atomization method. The objective of this research was to propose a non-invasive technique for acetone biomarker detection, which is associated with diabetes mellitus disease. The gas sensor array was exposed to methanol, ethanol, isopropanol, and acetone biomarkers in four different concentrations, corresponding to 1, 5, 10, and 15 µL, at temperature of 22 °C and relative humidity of 20%. These samples were used because human breath contains them and they are used for disease detection. Moreover, the gas sensor responses were analyzed using principal component analysis and discriminant analysis, achieving the classification of the acetone biomarker with a 100% membership percentage when its concentration varies from 327 to 4908 ppm, and its identification from methanol, ethanol, and isopropanol.

Organ failure constitutes a significant global concern requiring urgent attention. While organ transplantation offers prospective treatment, it remains suboptimal. The scarcity of donor organs and the need for lifelong immunosuppressive treatments highlight the necessity for innovative approaches in regenerative medicine. In response, tissue engineering has emerged as a promising alternative, particularly through advancements in three-dimensional (3D) and four-dimensional (4D) printing technologies. These approaches enable the fabrication of complex, patient-specific constructs for regenerating tissues such as skin, bone, cartilage, and vascularized organs. This review systematically examines 3D printing techniques, commonly used biomaterials (e.g., hydrogels, bio-inks, and polymers), and their applications in dermal, cardiovascular, bone, and neural regeneration. In addition to discussing 3D technology, an introduction to 4D bioprinting is provided, enabling advanced biomedical applications and establishing itself as an innovative tool that enhances the classic approach to 3D bioprinting in the context of regenerative medicine. Finally, key challenges and ethical considerations are discussed to provide a comprehensive perspective on the current state and future of printed scaffolds in regenerative medicine.

This work proposes a feasible, reproducible, and low-cost modified method to manufacture chitosan, chitosan/IgG-protein-loaded, and trimethylated chitosan nanoparticles, using microfluidics combined with the microemulsion technique, which differs from the traditional batch process of chitosan-based nanoparticles. The synthesis process consists of generating microreactors of chitosan-based polymer in a poly-dimethylsiloxane ψ-shaped microfluidic device and then crosslinking with sodium tripolyphosphate outside the cell. Transmission electron microscopy demonstrates an improvement in size control and distribution of the solid-shape chitosan nanoparticles (~80 nm) compared to the batch synthesis. Regarding chitosan/IgG-protein-loaded nanoparticles, these presented a core-shell morphology having a diameter of close to 15 nm. Raman and X-ray photoelectron spectroscopies confirmed the ionic crosslinking between the amino groups of chitosan and the phosphate groups of sodium tripolyphosphate in the fabricated samples and the total encapsulation of IgG protein during the fabrication of chitosan/IgG-loaded nanoparticles. Then, an ionic crosslinking and nucleation-diffusion process of chitosan-sodium tripolyphosphate was carried out during the nanoparticle formation, with and without IgG protein loading. The use of N-trimethyl chloride chitosan nanoparticles in vitro on human-keratinocyte-derived cell line HaCaT did not show side effects independently of its concentration from 1 to 10 μg/mL. Therefore, the proposed materials could be used as potential carrier-delivery systems.

This paper presents a new approach to reduce the measurement time by the prediction of the steady-state using the transient response to ethanol for quartz crystal microbalance gas sensors coated with ethyl cellulose. The experimentally measured response curves were successively fitted using a mathematical model based on the sum of two exponentials with different time constants. The parameters of the model were determined, and the time constants and the magnitude of the steady-state response were analyzed. Even though the time constants did not stabilize well, the parameter corresponding to the magnitude of the steady-state response quickly converged and stabilized after 37 s. Moreover, this calculated parameter was highly correlated with the measured values of the steady-state response, which was measured at five times the longest time constant (83 s) of the model. Therefore, the steady-state response could be predicted with a 55% reduction in the measurement (detection) time.

The discrimination improvement of an array of four highly sensitive 30 MHz gas quartz crystal microbalance (QCM) sensors was performed and compared to a similar system based on a 12-MHz QCM. The sensing polymeric films were ethyl cellulose (EC), poly-methyl methacrylate (PMMA), Apiezon L (ApL), and Apiezon T (ApT) and they were coated over the AT-cut QCM devices by the drop casting technique. All the sensors had almost the same film thickness (0.2 μm). The fabricated QCM sensor arrays were exposed to three different concentrations, corresponding to 5, 10, and 15 μL, of ethanol, ethyl acetate, and heptane vapors. The steady state sensor responses were measured in a static system at a temperature of 20 °C and relative humidity of 22%. Our results showed that the 30-MHz sensors have a higher sensitivity than 12-MHz ones (around 5.73 times), independently of the sensing film and measured sample. On the other hand, principal component analysis and discriminant analysis were performed using the raw data of the responses. An improvement of the classification percentage between 12 MHz and 30 MHz sensors was found. However, it was not sufficient, especially for low concentrations. Furthermore, using partition coefficient and discriminant analysis (DA), an improvement of 100% classification of the three samples was achieved for the case of the 30-MHz sensor array.