Selenium protects against cadmium-induced cardiac injury by attenuating programmed cell death via PI3K/AKT/PTEN signaling.

Cadmium (Cd) is an environmental pollutant that has an enormous influence on agricultural production, but selenium (Se) can alleviate its toxicity. The present study aimed to illustrate the effects of Se on Cd-induced heart injury. All 40 rabbits were randomly divided into four groups: control group, Se [0.5 mg kg-1 ·body weight (BW)] group, Cd (1 mg kg-1 ·BW) group, and Se + Cd group. After 30 days of feeding, morphological changes, the levels of oxidative stress and myocardial enzyme, the content of cardiac troponin T, programmed cell death (pyroptosis, autophagy and apoptosis), and PI3K/AKT/PTEN transduction capacity were observed. The results showed that Cd destroyed the physiological balance of trace elements and caused myocardial damage, increased the cardiac oxidative damage and led to programmed cell death. Coadministration of Se prominently ameliorated histological lesions and improved cardiac function of hearts in Cd-induced rabbits. Furthermore, Se exerted detoxification and oxidation resistance, maintained trace element homeostasis, and alleviated the changes of mRNA and protein levels of pyroptosis-, autophagy- and apoptosis-controlling factors and PI3K/AKT/PTEN signal molecules caused by Cd. In conclusion, Se might protect against Cd-induced pyroptosis, autophagy and apoptosis by interfering with PI3K/AKT/PTEN signaling in heart.

Selenium triggers Nrf2-AMPK crosstalk to alleviate cadmium-induced autophagy in rabbit cerebrum.

Cadmium (Cd) is a toxic heavy metal that accumulates in the brain and causes a series of histopathological changes. Selenium (Se) exerts a crucial function in protecting damage caused by toxic heavy metals, but its potential mechanism is rarely studied. The main purpose of this study is to explore the protective effects of Se on Cd-induced oxidative stress and autophagy in rabbit cerebrum. Forty rabbits were randomly divided into four groups and treated as follows: Control group, Cd (1 mg/kg⋅BW) group, Se (0.5 mg/kg⋅BW) group and Cd (1 mg/kg⋅BW)+Se (0.5 mg/kg⋅BW) group, with 30 days feeding management. Our results suggested that Se treatment significantly suppressed the Cd-induced degenerative changes including cell necrosis, vacuolization, and atrophic neurons. In addition, Se decreased the contents of MDA and H2O2 and increased the activities of CAT, SOD, GST, GSH and GSH-Px, alleviating the imbalance of the redox system induced by Cd. Furthermore, Cd caused the up-regulation of the mRNA levels of autophagy-related genes (ATG3, ATG5, ATG7, ATG12 and p62), AMPK (Prkaa1, Prkaa2, Prkab1, Prkab2, Prkag2, Prkag3) and Nrf2 (Nrf2, HO-1 and NQO1) signaling pathway, and the expression levels of LC3II/LC3I, p-AMPK/AMPK, Beclin-1, Nrf2 and HO-1 proteins, which were alleviated by Se, indicated that Se inhibited Cd-induced autophagy and Nrf2 signaling pathway activation. In conclusion, our study found that Se antagonized Cd-induced oxidative stress and autophagy in the brain by generating crosstalk between AMPK and Nrf2 signaling pathway.

A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT.

Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based model for automatic COVID-19 diagnosis on chest CT is helpful to counter the outbreak of SARS-CoV-2. A weakly-supervised deep learning framework was developed using 3D CT volumes for COVID-19 classification and lesion localization. For each patient, the lung region was segmented using a pre-trained UNet; then the segmented 3D lung region was fed into a 3D deep neural network to predict the probability of COVID-19 infectious; the COVID-19 lesions are localized by combining the activation regions in the classification network and the unsupervised connected components. 499 CT volumes were used for training and 131 CT volumes were used for testing. Our algorithm obtained 0.959 ROC AUC and 0.976 PR AUC. When using a probability threshold of 0.5 to classify COVID-positive and COVID-negative, the algorithm obtained an accuracy of 0.901, a positive predictive value of 0.840 and a very high negative predictive value of 0.982. The algorithm took only 1.93 seconds to process a single patient's CT volume using a dedicated GPU. Our weakly-supervised deep learning model can accurately predict the COVID-19 infectious probability and discover lesion regions in chest CT without the need for annotating the lesions for training. The easily-trained and high-performance deep learning algorithm provides a fast way to identify COVID-19 patients, which is beneficial to control the outbreak of SARS-CoV-2. The developed deep learning software is available at https://github.com/sydney0zq/covid-19-detection.

Molybdenum Induces Mitochondrial Oxidative Damage in Kidney of Goats.

The purpose of this study was to evaluate the effects of excessive molybdenum (Mo) on renal function and oxidative stress in goats. Twenty-seven healthy goats were randomly allotted in three groups and were fed deionized water to which sodium molybdate [(NH4)6Mo7O24·4H2O] was added at different doses of 0, 15, and 45 mg Mo/(kg·BW) for 50 days, respectively. The results indicated that white blood cell (WBC) counts were significantly increased (P < 0.05), while red blood cell (RBC) counts, hemoglobin (HGB), and mean corpuscular hemoglobin concentration (MCH) were tended to decrease with the increasing of the experimental period in high-Mo group compared with the control group. Besides, blood urea nitrogen (BUN) and creatinine (CREA) contents in serum were increased (P < 0.05) in both groups supplemented with molybdenum. Meanwhile, contents of copper (Cu) from the both experimental groups were significantly decreased (P < 0.05), while contents of zinc (Zn) and iron (Fe) were increased (P < 0.05) in serum. The contents of Cu were significantly increased (P < 0.05), while the contents of zinc (Zn) and iron (Fe) did not obviously change (P > 0.05) in the kidney. In addition, the activities of total antioxidant capacity (T-AOC), superoxide dismutase (SOD), and catalase (CAT) significantly decreased (P < 0.05) in the mitochondria, whereas malondialdehyde (MDA) and nitric oxide synthase (NOS) expression significantly increased (P < 0.05). Collectively, these results indicated that excess Mo exposure could induce secondary Cu deficiency and oxidative stress in the kidney, which finally undermine the renal function of goats.