Destemming fresh chilli fruit (Capsicum) in large productivity is necessary, especially in the Mekong Delta region. Several studies have been done to solve this problem with high applicability, but a certain percentage of the output consisted of cracked fruits, thus reducing the quality of the system. The manual sorting results in high costs and low quality, so it is necessary that automatic grading is performed after destemming. This research focused on developing a method to identify and classify cracked chilli fruits caused by the destemming process. The convolution neural network (CNN) model was built and trained to identify cracks; then, appropriate control signals were sent to the actuator for classification. Image processing operations are supported by the OpenCV library, while the TensorFlow data structure is used as a database and the Keras application programming interface supports the construction and training of neural network models. Experiments were carried out in both the static and working conditions, which, respectively, achieved an accurate identification rate of 97 and 95.3%. In addition, a success rate of 93% was found even when the chilli body is wrinkled due to drying after storage time at 120 hours. Practical results demonstrate that the reliability of the model was useful and acceptable.

In a previous study, a fresh chili destemming system has been proposed, and the TCS3200 color sensor was used as low-cost equipment in the arrangement section of the system. However, the working and installing parameters have not yet been investigated in detail. This study focused on investigating the optimal working conditions of TCS3200 on the fresh chili destemming system. The study included three experiments including the effect of the red and green color channels, the effect of the height between the sensor and fruits, and the effect of the running velocity on the received signal level of the sensor. A total of 260 ripen fruits were chosen to test. The results showed that the red channel generated a stronger signal than the green one. The optimal height from the sensor to the fruits was obtained at 25 mm, and the maximum conveyor velocity is limited to 100 mm/s. This study helps to determine the optimal operating parameters and enhance the working ability of a low-cost sensor. However, the high-speed pushing actuating mechanism should be developed in further works.

This study compared the therapeutic effects of engineered exosomes derived from RAW264.7 cells overexpressing hsa-let-7i-5p (engineered exosomes) to exosomes from human placenta-derived mesenchymal stem cells (hpMSC exosomes) against sepsis-induced acute lung injury. Adult male C57BL/6 mice were divided into lipopolysaccharide (LPS), LPS plus engineered exosome (LEExo), or LPS plus hpMSC exosome (LMExo) groups, alongside control groups. The results showed that lung injury scores (based on pathohistological characteristics) and the levels of lung function alterations, tissue edema, and leukocyte infiltration in LEExo and LMExo groups were comparable and significantly lower than in the LPS group (all p < 0.05). Furthermore, the levels of inflammation (nuclear factor-κB activation, cytokine upregulation), macrophage activation (hypoxia-inducible factor-1α activation, M1 phase polarization), oxidation, and apoptosis were diminished in LEExo and LMExo groups compared to the LPS group (all p < 0.05). Inhibition of hsa-let-7i-5p attenuated the therapeutic effects of both engineered and hpMSC exosomes. These findings underscore the potent therapeutic capacity of engineered exosomes enriched with hsa-let-7i-5p and their potential as an alternative to hpMSC exosomes for sepsis treatment. Continued research into the mechanisms of action and optimization of engineered exosomes could pave the way for their future clinical application.

Background: Aspiration pneumonia (AP), which can be caused by gastric content inhalation into the lower airways, causes acute lung injury (ALI) through complex mechanisms, including inflammation, oxidative stress, and apoptosis. Here, we evaluated the efficacy of exosomes derived from human placental mesenchymal stem cells (hpMSCs) in mitigating ALI in a murine model of AP. We also investigated the role of hsa-let-7i-5p, the most abundant miRNA in hpMSC-derived exosomes, in this respect.Methods: Adult male C57BL/6 mouse AP models were administered hpMSC-derived exosomes (APExo group) or phosphate-buffered saline (AP group) intra-tracheally. After 48 h, the mice were euthanized and evaluated. The effects of hsa-let-7i-5p were assessed by specific inhibition or overexpression.Results: Compared with the APExo group, the AP group exhibited significantly greater ALI, as evidenced by histological damage, increased lung injury scores, impaired lung function, increased leukocyte infiltration, and elevated tissue edema (all P < 0.05). The untreated AP group also showed more inflammation, characterized by nuclear factor-κB upregulation, macrophage M1 polarization, and cytokine level elevation (tumor necrosis factor-α, interleukin-1β, and interleukin-6), as well as increased oxidation and activation of the apoptosis pathway (all P < 0.05). Notably, the therapeutic effects of hpMSC-derived exosomes were compromised by specific inhibition of hsa-let-7i-5p. Furthermore, engineered exosomes derived from genetically modified RAW264.7 overexpressing hsa-let-7i-5p demonstrated therapeutic effects against AP similar to those obtained with hpMSC-derived exosomes.Conclusions: In a murine AP model, intra-tracheal administration of hpMSC-derived exosomes has ALI-mitigating effects, involving inflammation, oxidation, and apoptosis modulation, with hsa-let-7i-5p playing a pivotal mediating role.