We report an investigation of normal-incidence GeSn-based p-i-n photodetectors (PDs) with a Ge0.94Sn0.06 active layer grown using sputter epitaxy on a Ge(100) substrate. A low dark current density of 0.24 A/cm2 was obtained at a reverse bias of 1 V. A high optical responsivity of the Ge0.94Sn0.06/Ge p-i-n PDs at zero bias was achieved, with an optical response wavelength extending to 1985 nm. The temperature-dependent optical-response measurement was performed, and a clear redshift absorption edge was observed. This work presents an approach for developing efficient and cost-effective GeSn-based infrared devices.

Objective In this study, we focused on the interaction between SARS-CoV-2 and host Type I Interferon (IFN) response, so as to identify whether IFN effects could be influenced by the products of SARS-CoV-2. Methods All the structural and non-structural proteins of SARS-CoV-2 were transfected and overexpressed in the bronchial epithelial cell line BEAS-2B respectively, and typical antiviral IFN-stimulated gene (ISG) ISG15 expression was detected by qRT-PCR. RNA-seq based transcriptome analysis was performed between control and Spike (S) protein-overexpressed BEAS-2B cells. The expression of ACE2 and IFN effector JAK-STAT signaling activation were detected in control and S protein-overexpressed BEAS-2B cells by qRT-PCR or/and Western blot respectively. The interaction between S protein with STAT1 and STAT2, and the association between JAK1 with downstream STAT1 and STAT2 were measured in BEAS-2B cells by co-immunoprecipitation (co-IP). Results S protein could activate IFN effects and downstream ISGs expression. By transcriptome analysis, overexpression of S protein induced a set of genes expression, including series of ISGs and the SARS-CoV-2 receptor ACE2. Mechanistically, S protein enhanced the association between the upstream JAK1 and downstream STAT1 and STAT2, so as to promote STAT1 and STAT2 phosphorylation and ACE2 expression. Conclusion SARS-CoV-2 S protein enhances ACE2 expression via facilitating IFN effects, which may help its infection.

Hepatic apoptosis and the initiated liver inflammation play the initial roles in inflammation-induced hepatocarcinogenesis. Molecular mechanisms underlying the regulation of hepatocyte apoptosis and their roles in hepatocarcinogenesis have attracted much attention. A set of microRNAs (miRNAs) have been determined to be dysregulated in hepatocellular carcinoma (HCC) and participated in cancer progression, however, the roles of these dysregulated miRNAs in carcinogenesis are still poorly understood. We previously analyzed the dysregulated miRNAs in HCC using high-throughput sequencing, and found that miR-199a/b-3p was abundantly expressed in human normal liver while markedly decreased in HCC, which promotes HCC progression. Whether miR-199a/b-3p participates in HCC carcinogenesis is still unknown up to now. Hence, we focused on the role and mechanism of miR-199a/b-3p in hepatocarcinogenesis in this study. Hepatic miR-199a/b-3p was determined to be expressed by miR-199a-2 gene in mice, and we constructed miR-199a-2 knockout and hepatocyte-specific miR-199a-2 knockout mice. Diethylnitrosamine (DEN)-induced hepatocarcinogenesis were markedly increased by hepatocyte-specific miR-199a-3p knockout, which is mediated by the enhanced hepatocyte apoptosis and hepatic injury by DEN administration. In acetaminophen (APAP)-induced acute hepatic injury model, hepatocyte-specific miR-199a-3p knockout also aggravated hepatic apoptosis. By proteomic screening and reporter gene validation, we identified and verified that hepatic programed cell death 4 (PDCD4), which promotes apoptosis, was directly targeted by miR-199a-3p. Furthermore, we confirmed that miR-199a-3p-suppressed hepatocyte apoptosis and hepatic injury by targeting and suppressing PDCD4. Thus, hepatic miR-199a-3p inhibits hepatocyte apoptosis and hepatocarcinogenesis, and decreased miR-199a-3p in hepatocytes may aggravate hepatic injury and HCC development.

The aim of the study is to investigate the diffusion characteristics of Alzheimer’s disease (AD) patients using an ultra-high b-values apparent diffusion coefficient (ADC_uh) and diffusion kurtosis imaging (DKI). A total of 31 AD patients and 20 healthy controls (HC) who underwent both MRI examination and clinical assessment were included in this study. Diffusion weighted imaging (DWI) was acquired with 14 b-values in the range of 0 and 5000 s/mm2. Diffusivity was analyzed in selected regions, including the amygdala (AMY), hippocampus (HIP), thalamus (THA), caudate (CAU), globus pallidus (GPA), lateral ventricles (LVe), white matter (WM) of the frontal lobe (FL), WM of the temporal lobe (TL), WM of the parietal lobe (PL) and centrum semiovale (CS). The mean, median, skewness and kurtosis of the conventional apparent diffusion coefficient (ADC), DKI (including two variables, Dapp and Kapp) and ADC_uh values were calculated for these selected regions. Compared to the HC group, the ADC values of AD group were significantly higher in the right HIP and right PL (WM), while the ADC_uh values of the AD group increased significantly in the WM of the bilateral TL and right CS. In the AD group, the Kapp values in the bilateral LVe, bilateral PL/left TL (WM) and right CS were lower than those in the HC group, while the Dapp value of the right PL (WM) increased. The ADC_uh value of the right TL was negatively correlated with MMSE (mean, r=-0.420, p=0.019). The ADC value and Dapp value have the same regions correlated with MMSE. Compared with the ADC_uh, combining ADC_uh and ADC parameters will result in a higher AUC (0.894, 95%CI=0.803-0.984, p=0.022). Comparing to ADC or DKI, ADC_uh has no significant difference in the detectability of AD, but ADC_uh can better reflect characteristic alternation in unconventional brain regions of AD patients.

Full waveform airborne Light Detection And Ranging(LiDAR) data contains abundant information which may overcome some deficiencies of discrete LiDAR point cloud data provided by conventional LiDAR systems. Processing full waveform data to extract more information than coordinate values alone is of great significance for potential applications. The Levenberg–Marquardt (LM) algorithm is a traditional method used to estimate parameters of a Gaussian model when Gaussian decomposition of full waveform LiDAR data is performed. This paper employs the generalized Gaussian mixture function to fit a waveform, and proposes using the grouping LM algorithm to optimize the parameters of the function. It is shown that the grouping LM algorithm overcomes the common drawbacks which arise from the conventional LM for parameter optimization, such as the final results being influenced by the initial parameters, possible algorithm interruption caused by non-numerical elements that occurred in the Jacobian matrix, etc. The precision of the point cloud generated by the grouping LM is evaluated by comparing it with those provided by the LiDAR system and those generated by the conventional LM. Results from both simulation and real data show that the proposed algorithm can generate a higher-quality point cloud, in terms of point density and precision, and can extract other information, such as echo location, pulse width, etc., more precisely as well.

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Aim: To explore the association between the atherosclerosis and diabetic retinopathy (DR) in Chinese patients with type 2 diabetes mellitus (T2DM). Methods: This hospital-based cross-sectional study included 949 patients (700 males and 249 females) with T2DM. The atherosclerotic parameters were assessed using the cardioankle vascular index (CAVI), ankle-brachial index (ABI), and carotid plaque. DR was assessed and graded using digital retinal photography and fundus fluorescein angiography as either nonproliferative DR (NPDR) or proliferative DR (PDR). Multiple logistic regression analysis was performed to identify the associations between the atherosclerotic parameters and DR status. Results: The prevalence of DR was 23.6% in total patients, including 167 (17.6%) patients with NPDR and 57 (6.0%) patients with PDR. Patients with NPDR and PDR were more likely to have higher prevalence of increased CAVI, increased ABI, and carotid plaque than those without DR. In multivariable adjusted logistic regression analysis, patients with NPDR showed an odds ratio (OR) of 2.59 [95% confidence interval (CI), 1.61-4.19] for increased CAVI, 1.99 (0.62-6.34) for increased ABI, and 1.75 (1.13-2.71) for carotid plaque. Patients with PDR showed an OR of 7.83 (3.52-17.41) for increased CAVI, 10.65 (3.33-34.04) for increased ABI, and 11.40 (2.67-48.63) for carotid plaque. Conclusion: Both NPDR and PDR were independently associated with increased CAVI and presence of carotid plaque in Chinese patients with T2DM.