Mechanistic insights into inositol-mediated rumen function promotion and metabolic alteration using in vitro and in vivo models.

Inositol is a bioactive factor that is widely found in nature; however, there are few studies on its use in ruminant nutrition. This study investigated the effects of different inositol doses and fermentation times on rumen fermentation and microbial diversity, as well as the levels of rumen and blood metabolites in sheep. Rumen fermentation parameters, microbial diversity, and metabolites after different inositol doses were determined in vitro. According to the in vitro results, six small-tailed Han sheep fitted with permanent rumen fistulas were used in a 3 × 3 Latin square feeding experiment where inositol was injected into the rumen twice a day and rumen fluid and blood samples were collected. The in vitro results showed that inositol could increase in vitro dry matter digestibility, in vitro crude protein digestibility, NH3-N, acetic acid, propionic acid, and rumen microbial diversity and affect rumen metabolic pathways (p < 0.05). The feeding experiment results showed that inositol increased the blood concentration of high-density lipoprotein and IgG, IgM, and IL-4 levels. The rumen microbial composition was significantly affected (p < 0.05). Differential metabolites in the rumen were mainly involved in ABC transporters, biotin metabolism, and phenylalanine metabolism, whereas those in the blood were mainly involved in arginine biosynthesis and glutathione and tyrosine metabolism. In conclusion, inositol improves rumen function, affects rumen microorganisms and rumen and blood metabolites and may reduce inflammation, improving animal health.

Internet-of-Things-Enabled Data Fusion Method for Sleep Healthcare Applications.

The Internet of Medical Things (IoMT) aims to exploit the Internet-of-Things (IoT) techniques to provide better medical treatment scheme for patients with smart, automatic, timely, and emotion-aware clinical services. One of the IoMT instances is applying IoT techniques to sleep-aware smartphones or wearable devices' applications to provide better sleep healthcare services. As we all know, sleep is vital to our daily health. What is more, studies have shown a strong relationship between sleep difficulties and various diseases such as COVID-19. Therefore, leveraging IoT techniques to develop a longer lifetime sleep healthcare IoMT system, with a tradeoff between data transferring/processing speed and battery energy efficiency, to provide longer time services for bad sleep condition persons, especially the COVID-19 patients or survivors, is a meaningful research topic. In this study, we propose an IoT-enabled sleep data fusion networks (SDFN) module with a star topology Bluetooth network to fuse data of sleep-aware applications. A machine learning model is built to detect sleep events through an audio signal. We design two data reprocessing mechanisms running on our IoT devices to alleviate the data jam problem and save the IoT devices' battery energy. The experiments manifest that the presented module and mechanisms can save the energy of the system and alleviate the data jam problem of the device.

Applications and developments of on-chip biochemical sensors based on optofluidic photonic crystal cavities.

Photonic crystal (PC) cavities, which possess the advantages of compactness, flexible design, and suitability for integration in a lab-on-a-chip system, are able to distinguish slight variations in refractive index with only a small amount of analyte. Combined with the newly proposed optofluidic technology, PC-cavity devices stimulate an emerging class of miniaturized and label-free biochemical sensors. In this review, an overview of optofluidic PC cavities based biochemical sensors is presented. First, the basic properties of the PC, as well as the sensing principle of the PC cavity, are discussed. Second, the applications of the sensors in detecting gas, liquid, and biomolecule concentrations are reviewed, with a focus on their structures, sensing principles, sensing properties, advantages, and disadvantages. Finally, the current challenges and future development directions of optofluidic PC-cavity-based biochemical sensors are discussed.

Photonic crystal fiber modal interferometer with Pd/WO3 coating for real-time monitoring of dissolved hydrogen concentration in transformer oil.

A highly-sensitive and temperature-robust photonic crystal fiber (PCF) modal interferometer coated with Pd/WO3 film was fabricated and studied, aiming for real-time monitoring of dissolved hydrogen concentration in transformer oil. The sensor probe was fabricated by splicing two segments of a single mode fiber (SMF) with both ends of the PCF. Since the collapse of air holes in the PCF in the interfaces between SMF and PCF, a SMF-PCF-SMF interferometer structure was formed. The Pd/WO3 film was fabricated by sol-gel method and coated on the surface of the PCF by dip-coating method. When the Pd/WO3 film is exposed to hydrogen, both the length and cladding refractive index of the PCF would be changed, resulting in the resonant wavelength shift of the interferometer. Experimental results showed that the hydrogen measurement sensitivity of the proposed sensor can reach 0.109 pm/(µl/l) in the transformer oil, with the measurement range of 0-10 000 µl/l and response time less than 33 min. Besides, the proposed sensor was temperature-insensitive without any compensation process, easy to fabricate without any tapering, polishing, or etching process, low cost and quickly response without any oil-gas separation device. All these performances satisfy the actual need of real-time monitoring of dissolved hydrogen concentration in the transformer oil.