Impaired epithelial barrier function disrupts immune homeostasis and increases inflammation in intestines, leading to many intestinal diseases. Cathelicidin peptides suppress intestinal inflammation and improve intestinal epithelial barrier function independently of their antimicrobial activity. In this study, we investigated the effects of Cathelicidin-WA (CWA) on intestinal epithelial barrier function, as well as the underlying mechanism, by using enterohemorrhagic Escherichia coli (EHEC)-infected mice and intestinal epithelial cells. The results showed that CWA attenuated EHEC-induced clinical symptoms and intestinal colitis, as did enrofloxacin (Enro). CWA decreased IL-6 production in the serum, jejunum, and colon of EHEC-infected mice. Additionally, CWA alleviated the EHEC-induced disruption of mucin-2 and goblet cells in the intestine. Interestingly, CWA increased the mucus layer thickness, which was associated with increasing expression of trefoil factor 3, in the jejunum of EHEC-infected mice. CWA increased the expression of tight junction proteins in the jejunum of EHEC-infected mice. Using intestinal epithelial cells and a Rac1 inhibitor in vitro, we demonstrated that the CWA-mediated increases in the tight junction proteins might depend on the Rac1 pathway. Furthermore, CWA improved the microbiota and short-chain fatty acid concentrations in the cecum of EHEC-infected mice. Although Enro and CWA had similar effects on intestinal inflammation, CWA was superior to Enro with regard to improving intestinal epithelial barrier and microbiota in the intestine. In conclusion, CWA attenuated EHEC-induced inflammation, intestinal epithelial barrier damage, and microbiota disruption in the intestine of mice, suggesting that CWA may be an effective therapy for many intestinal diseases.

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It is imperative to accurately predict the remaining useful life (RUL) of lithium-ion batteries to ensure the reliability and safety of related industries and facilities. In view of the noise sequence embedded in the measured aging data of lithium-ion batteries and the strong nonlinear characteristics of the aging process, this study proposes a method for predicting lithium-ion batteries’ RUL based on the wavelet threshold denoising and transformer model. To specify, firstly, the wavelet threshold denoising method is adopted to preprocess the measured discharging capacity data of lithium-ion batteries to eliminate some noise signals. Second, based on the denoised data, the transformer model output’s full connection layer is applied to replace the decoder layer for establishing the RUL prediction model of lithium-ion batteries. Finally, the discharging capacity of each charging–discharging cycle is predicted iteratively, and then the RUL of lithium-ion batteries can be calculated eventually. Two groups of lithium-ion batteries’ aging data from the Center for Advanced Life Cycle Engineering (CALCE) at the University of Maryland and the laboratory at Anqing Normal University (AQNU) are employed to verify the proposed method, individually. The experimental results demonstrate that this method can overcome the impacts of data measurement noise, effectively predict the RUL of lithium-ion batteries, and present a sound generalization ability and high accuracy.

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The status and drivers of soil-available nutrients in plant-recovered soils are not fully understood, limiting our ability to explore the role of soil-available nutrients in soil geochemical cycling and ecosystem sustainability. Here, we combined the spatial distribution of soil-available nutrients and chemical and aggregate properties from six soil types (subalpine meadow soil, meadow soil, dark brown soil, brown soil, yellow-brown soil, and cinnamon soil) and three horizons (a leaching horizon, sediment horizon, and parent material horizon) to study the status and drivers of soil-available nutrients. Our findings reveal that the soil-available nitrogen (AN) ranged from 72.33 to 169.67 mg/kg, the soil-available phosphorus (AP) ranged from 1.77 to 75.90 mg/kg, and the soil-available potassium (AK) ranged from 46.43 to 88.55 mg/kg in the six soil types. The subalpine meadow soil and the dark brown soil had the highest soil AN, with means of 169.67 and 139.35 mg/kg, respectively. The brown soil had the highest soil AP, with a mean of 75.9 mg/kg, and the dark brown soil and the brown soil had the highest soil AK, with means of 83.49 and 88.55 mg/kg, respectively. The results show that the soil types and soil depths had a significant impact on the status of AN, AP, and AK (p < 0.05). Moreover, a higher cation exchange capacity (CEC), the macro-aggregate contents (with 2–1 mm and 1–0.5 mm particle sizes) of the non-water-stable aggregates, and the macro-aggregate content and stability (2–1 mm particle size and geometric mean diameter (GMD) of the water-stable aggregates were deemed to facilitate soil-available nitrogen because of the positive correlations (p < 0.05). Lower exchangeable cations (ECs) and the micro-aggregate content (≤0.1 mm particle size) of the water-stable aggregates and higher soil cations helped in the accumulation of soil-available phosphorus and soil-available potassium, respectively. Moreover, the regulation of the soil chemical and aggregate properties was found to vary with soil type and horizon in a correlation analysis. Together, our results provide insights into the importance of chemical and aggregate properties in regulating soil nutrient availability across soil types, as well as providing strong support for the inclusion of soil resource utilization in regional forest restoration and management.

Population aging in Singapore has encouraged the development of ambient smart communities to support healthy aging. Poor understanding of the living activities that address both clinical and biological concerns may plague efficient aging service designs and community health programs. We have designed a new computational workflow to identify important living activities for older adults in Singapore. We investigated innovatively three pillars of human life aspects: activities, clinical health, and biological health to identify living activities that are significantly associated with both clinical health and biological health. Cross-sectional data analyses were performed on 1356 community-living Chinese older adults of 65–80 years old in the Singapore Longitudinal Aging Study II (SLASII) cohort. 7 out of 29 living activities were found significantly associated with clinically healthy aging and showed improved prediction accuracy towards health status in machining learning schemes. Furthermore, biological age has been computed by screening and modeling 66 biomarkers. 15 out of the 29 living activities were found significantly associated with biologically healthy aging. Checking the overlapping living activities, we have found that physical exercise and cognitive-simulating activities are the most important activities for healthy aging: such as jogging regularly and reading, writing, and doing puzzles often. We regroup participants into active and non-active groups according to these two activities. The Keplan-Meier survival analysis showed statistically significant differences in survival time between the active and non-active groups (p &lt; 0.001) in an 8-year longitudinal study. The workflow, results and biomarkers may provide references for future health program design improvement.

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