Identification of discriminative neuroimaging markers for patients on hemodialysis with insomnia: a fractional amplitude of low frequency fluctuation-based machine learning analysis.

BACKGROUND AND OBJECTIVE: Insomnia is one of the common problems encountered in the hemodialysis (HD) population, but the mechanisms remain unclear. we aimed to (1) detect the spontaneous brain activity pattern in HD patients with insomnia (HDWI) by using fractional fractional amplitude of low frequency fluctuation (fALFF) method and (2) further identify brain regions showing altered fALFF as neural markers to discriminate HDWI patients from those on hemodialysis but without insomnia (HDWoI) and healthy controls (HCs). METHOD: We compared fALFF differences among HDWI subjects (28), HDWoI subjects (28) and HCs (28), and extracted altered fALFF features for the subsequent discriminative analysis. Then, we constructed a support vector machine (SVM) classifier to identify distinct neuroimaging markers for HDWI. RESULTS: Compared with HCs, both HDWI and HDWoI patients exhibited significantly decreased fALFF in the bilateral calcarine (CAL), right middle occipital gyrus (MOG), left precentral gyrus (PreCG), bilateral postcentral gyrus (PoCG) and bilateral temporal middle gyrus (TMG), whereas increased fALFF in the bilateral cerebellum and right insula. Conversely, increased fALFF in the bilateral CAL/right MOG and decreased fALFF in the right cerebellum was observed in HDWI patients when compared with HDWoI patients. Moreover, the SVM classification achieved a good performance [accuracy = 82.14%, area under the curve (AUC) = 0.8202], and the consensus brain regions with the highest contributions to classification were located in the right MOG and right cerebellum. CONCLUSION: Our result highlights that HDWI patients had abnormal neural activities in the right MOG and right cerebellum, which might be potential neural markers for distinguishing HDWI patients from non-insomniacs, providing further support for the pathological mechanism of HDWI.

Modified biochar improves the storage capacity and adsorption affinity of organic phosphorus in soil.

The loss of soil organic phosphorus can easily cause water eutrophication. In order to effectively reduce the loss of soil organic phosphorus, this manuscript investigated the adsorption of soil organic phosphorus by lanthanum modified biochar (BC), traditional adsorbent gypsum (GY) and zeolite (ZE) by taking phytic acid as the representative. The adsorption isotherm model and kinetic models were used to fit the phosphorus absorption characteristics of the adsorbents. The effects of initial pH and temperature on the adsorption capacity were discussed, and the adsorption mechanism of each adsorbent was explained by means of FTIR and XRD. The results showed that the adsorption capacity of phytate phosphorus followed the trend of BCTS > GYTS > ZETS > TS (soil), and the maximum phosphorus adsorption capacity obtained from Langmuir isotherm for treatment with BCTS was 2.836 mg g-1, and the treatment had the strongest affinity for phytate phosphorus and also the ability to store phosphorus. The adsorption process fits well with Langmuir isotherm equation and pseudo-second-order kinetic equation, and the adsorption behavior of phytate phosphorus was mainly controlled by the chemisorption of monolayer. When the concentration of phytate phosphorus was 100 mg L-1, percentage of modified biochar added to the soil was 3% and the pH was 6, the adsorption capacity reached the maximum, and the maximum adsorption capacity was 2.000 mg g-1. The results of FTIR and XRD characterization showed that complexation was the main adsorption mechanism. In this study, the combination of modified biochar and soil phytate phosphorus can provide a good theoretical basis for reducing the loss of soil organic phosphorus.