Soil bacterial communities associated with marbled fruit in Citrus reticulata Blanco 'Orah'.

Citrus reticulata Blanco 'Orah' is grown throughout southern China and provides enormous economic value. However, the agricultural industry has suffered substantial losses during recent years due to marbled fruit disease. The present study focuses on the soil bacterial communities associated with marbled fruit in 'Orah'. The agronomic traits and microbiomes of plants with normal and marbled fruit from three different orchards were compared. No significant differences were found in agronomic traits between the groups, except for higher fruit yields and higher quality of fruits in normal fruit group. Additionally, a total of 2,106,050 16S rRNA gene sequences were generated via the NovoSeq 6000. The alpha diversity index (including the Shannon and Simpson indices), Bray-Curtis similarity, and principal component analyses indicated no significant differences in microbiome diversity between normal and marbled fruit groups. For the healthy 'Orah', the most abundant associated phyla were Bacteroidetes, Firmicutes, and Proteobacteria. In comparison, Burkholderiaceae and Acidobacteria were the most abundant taxa with the marbled fruit group. In addition, the family Xanthomonadaceae and the genus Candidatus Nitrosotalea were prevalent with this group. Analysis using the Kyoto Encyclopedia of Genes and Genomes pathways showed that several pathways related to metabolism significantly differed between the groups. Thus, the present study provides valuable information regarding soil bacterial communities associated with marbled fruit in 'Orah'.

Preventive therapeutic effect of Lactobacillus-fermented black wolfberry juice on sodium dextran sulfate-induced ulcerative colitis in mice.

In this study, male mice were treated with fermented and unfermented Lactobacillus plantarum, Lactobacillus bulgaricus, and Lactobacillus rhamnosus black wolfberry juice (10 mL/kg/day) for 40 days, and their prophylactic effects on ulcerative colitis (UC) induced by dextran sodium sulfate were investigated. The intervention of black wolfberry juice reduced the levels of pro-inflammatory cytokines and increased the content of anti-inflammatory cytokines in the serum and colon. In addition, the pathological changes in colon tissue were alleviated, the expression of Bcl-2 protein in the colon was enhanced, and the intestinal microbiota of the mice was regulated, with an increase in Bacteroidetes and a decrease in Helicobacter. These results suggested that black wolfberry juice had an anti-UC function and Lactobacillus fermentation enhanced the anti-inflammatory effect of black wolfberry juice by modulating the intestinal microbiota.

Nonintrusive Monitoring of Mental Fatigue Status Using Epidermal Electronic Systems and Machine-Learning Algorithms.

Mental fatigue, characterized by subjective feelings of "tiredness" and "lack of energy", can degrade individual performance in a variety of situations, for example, in motor vehicle driving or while performing surgery. Thus, a method for nonintrusive monitoring of mental fatigue status is urgently needed. Recent research shows that physiological signal-based fatigue-classification methods using wearable electronics can be sufficiently accurate; by contrast, rigid, bulky devices constrain the behavior of those wearing them, potentially interfering with test signals. Recently, wearable electronics, such as epidermal electronics systems (EES) and electronic tattoos (E-tattoos), have been developed to meet the requirements for the comfortable measurement of various physiological signals. However, comfortable, effective, and nonintrusive monitoring of mental fatigue levels remains to be fulfilled. In this work, an EES is established to simultaneously detect multiple physiological signals in a comfortable and nonintrusive way. Machine-learning algorithms are employed to determine the mental fatigue levels and a predictive accuracy of up to 89% is achieved based on six different kinds of physiological features using decision tree algorithms. Furthermore, EES with the trained predictive model are applied to monitor in situ human mental fatigue levels when doing several routine research jobs, as well as the effect of relaxation methods in relieving fatigue.

Precise Engineering of Conductive Pathway by Frictional Direct-Writing for Ultrasensitive Flexible Strain Sensors.

Highly sensitive strain sensors that can detect small strain are in high demand in the fields of displays, robotics, fatigue detection, body monitoring, in vitro diagnostics, and advanced therapies. However, resistive-type sensors that are composed of electrically conductive sensing films coupled with flexible substrates suffer from the limits that their gauge factors (GFs) at small strains (e.g., 0.1-1%) are not high. Herein, through frictional direct-writing of graphite rod on the composite paper substrates, we produced strain sensors with extremely high gauge factor at small strains. The sensors exhibited a gauge factor of 9720 at a small strain of 0.9%, minimum strain detection up to 0.05%, strain resolution of 0.05%, response time of 40 ms, and high stability (>5000 bending-unbending cycles). Compared with the literature results so far, our sensors hold the highest GF value at small strains. Such high sensitivities are due to the precise control of narrow two-dimensional percolative conductive pathway, which means the content of conductive graphite sheets is close to the conductive percolation threshold. The strain sensors have a rapid response to microdeformation changes and can monitor various structural changes, including human motion, through facilitative and effective installation of device designs.