FCNet: Stereo 3D Object Detection with Feature Correlation Networks.

Deep-learning techniques have significantly improved object detection performance, especially with binocular images in 3D scenarios. To supervise the depth information in stereo 3D object detection, reconstructing the 3D dense depth of LiDAR point clouds causes higher computational costs and lower inference speed. After exploring the intrinsic relationship between the implicit depth information and semantic texture features of the binocular images, we propose an efficient and accurate 3D object detection algorithm, FCNet, in stereo images. First, we construct a multi-scale cost-volume containing implicit depth information using the normalized dot-product by generating multi-scale feature maps from the input stereo images. Secondly, the variant attention model enhances its global and local description, and the sparse region monitors the depth loss deep regression. Thirdly, for balancing the channel information preservation of the re-fused left-right feature maps and computational burden, a reweighting strategy is employed to enhance the feature correlation in merging the last-layer features of binocular images. Extensive experiment results on the challenging KITTI benchmark demonstrate that the proposed algorithm achieves better performance, including a lower computational cost and higher inference speed in 3D object detection.

A COVID-19 Patient Discharged According to Strict Discharge Standards: Viral Negativity in Both Nasopharynx and Feces.

Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) currently has spread all over the world. However, the dynamic characteristics of SARS-CoV-2 infections have not previously been described in detail. Here, we report a cured patient in West China Hospital, and describe the dynamic detection of SARS-CoV-2-RNA in different specimens and viral specific IgM and IgG antibodies in blood. The findings suggest that the fecal SARS-CoV-2-RNA negativity may be considered as a new standard for de isolation. Serum IgM and IgG antibodies detection were helpful for early diagnosis of SARS-CoV-2 infection and judgment of patients in recovery stage, respectively.

Metformin ameliorates sepsis-induced brain injury by inhibiting apoptosis, oxidative stress and neuroinflammation via the PI3K/Akt signaling pathway.

Sepsis-induced brain injuries increase mortality, morbidity, cognitive impairment and lack of effective therapeutic treatment. Previous studies have suggested that metformin provides neuroprotective effects against ischemia, brain trauma and other brain damage, but whether metformin protects a septic brain remains unknown. Thus, the aim of this study is to investigate the possible effects and the mechanism of metformin against septic brain damage using the cecal ligation and puncture (CLP) model. Mice were randomly divided into five groups: the Sham group, CLP group, CLP+ Met group, CLP+ vehicle group and CLP+ Met+ LY group. The survival percentage and brain water content were examined, and the Morris water maze was conducted to determine the protective effect of metformin. Neuronal apoptosis in the cerebral cortex, striatum and hippocampus was examined using TUNEL assay and immunohistochemistry, and western blot was applied to measure the expression of p-Akt. The results indicate that metformin can increase survival percentage, decrease brain edema, preserve the blood-brain barrier (BBB) and improve cognitive function. Metformin also reduced the neuronal apoptosis induced by sepsis and increased the phosphorylation of Akt. However, the protective effect of metformin can be reversed by LY294002, a PI3K inhibitor. In summary, our results demonstrate that metformin can exert a neuroprotective effect by activating the PI3K/Akt signaling pathway.

Expression of NLRC4 in children with septicaemia and mechanisms of NLRC4 in in vitro cytokine secretion.

Septicaemia, a systemic bacterial infection, frequently leads to morbidity and mortality in children. The NOD-like receptor (NLR) family, CARD domain containing 4 (NLRC4) is involved in the control of infections. The aim of the present study was to detect the expression of NLRC4 in the blood samples of children with septicaemia, in addition to investigating the importance of NLRC4 in cytokine production, and the signaling pathways that regulate NLRC4 expression in lipopolysaccharide (LPS)-stimulated macrophages. It was determined that when compared with the control, the mRNA and protein expression levels of NLRC4 were significantly increased in the blood samples of children with septicaemia, as demonstrated by the reverse transcription­quantitative polymerase chain reaction and western blot analysis. The results from the western blotting indicated that treatment with LPS induced NLRC4 expression in a time­ and dose­dependent manner in RAW264.7 cells. A knockdown of NLRC4 by siRNA transfection enhanced the effect of LPS on interleukin (IL)­1ß and IL­18 production, as determined by enzyme­linked immunosorbent assay. Inhibitors of extracellular regulated protein kinases, c­Jun N­terminal kinases and p38 were used in the present study to block the mitogen­activated protein kinase (MAPK) signaling pathway, and it was determined that LPS­induced NLRC4 expression was reversed by the suppression of the MAPK signaling pathway. To the best of our knowledge, this is the first report regarding the expression of NLRC4 in children with septicaemia. Furthermore, a novel molecular mechanism for NLRC4 regulation in LPS­induced RAW264.7 macrophage cells has been elucidated. The data in the present study supports the hypothesis that LPS activates the MAPK pathway in macrophages, thus resulting in the upregulation of NLRC4; however, NLRC4 inhibits IL­1ß and IL­18 production, contributing to the anti-inflammatory response.

A secure steganography for privacy protection in healthcare system.

Private data in healthcare system require confidentiality protection while transmitting. Steganography is the art of concealing data into a cover media for conveying messages confidentially. In this paper, we propose a steganographic method which can provide private data in medical system with very secure protection. In our method, a cover image is first mapped into a 1D pixels sequence by Hilbert filling curve and then divided into non-overlapping embedding units with three consecutive pixels. We use adaptive pixel pair match (APPM) method to embed digits in the pixel value differences (PVD) of the three pixels and the base of embedded digits is dependent on the differences among the three pixels. By solving an optimization problem, minimal distortion of the pixel ternaries caused by data embedding can be obtained. The experimental results show our method is more suitable to privacy protection of healthcare system than prior steganographic works.

[A study on the screening of high-risk population of schistosomiasis using a quick inquiry discriminant method during the years of disasters].

OBJECTIVE: To seek a rapid, simple, but effective inquiry method for screening high risk population challenged by schistosomiasis. METHODS: Two embankment collapsed villages were selected in schistosomiasis epidemic area in Dongting Lake. Information on water exposure was collected through a retrospective study. Data was analyzed by stepwise discriminant analysis. RESULTS: A Fisher's function was established by stepwise discriminant analysis which including 5 variables out of 18. Two hundred and forty-six individuals were discriminated by the function with accuracy, sensitivity and specificity of predicting their current infection status with the results of 87.4%, 84.1% and 89.0% respectively. CONCLUSION: The inquiry method might serve as simple, rapid, economic and effective tool for diagnosis in screening high risk population challenged by schistosomiasis in lake communities.