An AI recognition method for children's clinical operative pain by skin potential (SP) signal.

Objective And Rationale: Children's clinical pain phenotypes are complex, and there is a lack of objective biological diagnostic markers and cognitive patterns. Detecting physiological signals through wearable devices simplifies disease diagnosis and holds the potential for remote medical applications.

Method And Results: This research established a pain recognition model based on AI skin potential (SP) signal analysis.

Exogenous melatonin enhances heat tolerance in buckwheat seedlings by modulating physiological response mechanisms.

Melatonin (MT) serves as a potent antioxidant in plant organisms, bolstering their resilience to temperature stress. In this study, the impact of MT on various buckwheat varieties under high-temperature stress conditions (40 °C) was investigated. Specifically, five buckwheat seedling varieties, comprising three sweet buckwheat variants (Fagopyrum esculentum) and two bitter buckwheat types (Fagopyrum tataricum), were subjected to foliar sprays of melatonin at concentrations of 50, 100 and 200 μM, with water at 25 °C employed as a control.

Task-state skin potential abnormalities can distinguish major depressive disorder and bipolar depression from healthy controls.

Early detection of bipolar depression (BPD) and major depressive disorder (MDD) has been challenging due to the lack of reliable and easily measurable biological markers. This study aimed to investigate the accuracy of discriminating patients with mood disorders from healthy controls based on task state skin potential characteristics and their correlation with individual indicators of oxidative stress. A total of 77 patients with BPD, 53 patients with MDD, and 79 healthy controls were recruited.

Children's Pain Identification Based on Skin Potential Signal.

Pain management is a crucial concern in medicine, particularly in the case of children who may struggle to effectively communicate their pain. Despite the longstanding reliance on various assessment scales by medical professionals, these tools have shown limitations and subjectivity. In this paper, we present a pain assessment scheme based on skin potential signals, aiming to convert subjective pain into objective indicators for pain identification using machine learning methods.

Mycorrhizas enhance drought tolerance of citrus by altering root fatty acid compositions and their saturation levels.

Arbuscular mycorrhizas (AMs) have the ability to enhance drought tolerance of citrus, but the underlying mechanisms have not been clearly elucidated. Considering the strong association of cell membrane fatty acid (FA) unsaturation with plant drought tolerance, the present study hypothesized that AM fungi (AMF) modulated the composition and unsaturation of FAs to enhance drought tolerance of host plants. Drought-sensitive citrus rootstocks, trifoliate orange (Poncirus trifoliata) seedlings, were inoculated with AMF (Funneliformis mosseae) for 3 months and were subsequently exposed to drought stress (DS) for 8 weeks.

Construction of the Syngonium podophyllum-Pseudomonas sp. XNN8 Symbiotic Purification System and Investigation of Its Capability of Remediating Uranium Wastewater.

The endophyte Pseudomonas sp. XNN8 was separated from Typha orientalis which can secrete indole-3-acetic acid and 1-aminocyclopropane-1-carboxylate deaminase and siderophores and has strong resistance to uranium it was then colonized in the Syngonium podophyllum; and the S. podophyllum-Pseudomonas sp.

An artificially constructed Syngonium podophyllum-Aspergillus niger combinate system for removal of uranium from wastewater.

Aspergillus niger was inoculated to the roots of five plants, and the Syngonium podophyllum-A. niger combinate system (SPANCS) was found to be the most effective in removing uranium from hydroponic liquid with initial uranium concentration of 5 mg L(-1). Furthermore, the hydroponic experiments on the removal of uranium from the hydroponic liquids with initial uranium concentrations of 0.