Neutrophil extracellular traps (NETs), the product of NETosis, is found to localize pathogens and crystals in immune response. Recent studies have found that excessive NETs lead to disease conditions such as diabetes and its complications like diabetic retinopathy (DR). However, the correlation between NETs and high glucose or DR remains unclear. Here, we found NETs level was significantly increased in the serum of diabetic patients, especially in proliferation diabetic retinopathy (PDR) patients. High glucose dramatically increased NETs production in diabetic individuals with time prolonging. The activation of NADPH oxidase was involved in the NETs process which is triggered by high glucose. Moreover, we verified the infiltration of neutrophils in the eyes and adhesion to vascular endothelial cells in diabetic rat models. NETs formation was observed in the vitreous bodies and retinas of diabetic individuals, which indicates NETs may play a role in the pathogenesis of diabetic retinopathy. Furthermore, anti-VEGF therapy downregulates NETs production indicating that NADPH oxidase-derived ROS may be another signaling pathway involved in anti-VEGF therapy.

Inspired by natural creatures, the development of a device that collects water from fog represents an important research direction.

A computational auditory nerve (AN) model was developed for use in modeling psychophysical experiments with normal and impaired human listeners. In this phenomenological model, many physiologically vulnerable response properties associated with the cochlear amplifier are represented by a single nonlinear control mechanism, including the effects of level-dependent tuning, compression, level-dependent phase, suppression, and fast nonlinear dynamics on the responses of high, medium, and low spontaneous-rate (SR) AN fibers. Several model versions are described that can be used to evaluate the relative effects of these nonlinear properties.

The present results suggest that miR-155 expression is decreased in active BD but not in VKH patients. Downregulated miR-155 may be involved in BD pathogenesis by targeting TAB2.

Hypoxia inducible factor-1α (HIF-1α) up-regulates the expression of programmed death ligand-1 (PD-L1) in some extracranial malignancies. However, whether it could increase PD-L1 expression in intracranial tumor is still unknown. Here, we explored the relationship between HIF-1α and PD-L1 expression in glioma, and investigated their clinical significance. In glioma patients, HIF-1α and PD-L1 were overexpressed in high grade glioma tissues and were significantly associated with poor survival. In glioma cells, PD-L1 expression was induced under hypoxia condition, and the enhanced PD-L1 expression was abrogated by either HIF-1α knock-down or HIF-1α inhibitor treatment. Furthermore, ChIP-qPCR analysis showed the direct binding of HIF-1α to PD-L1 proximal promoter region, providing evidence that HIF-1α up-regulates PD-L1 in glioma. In glioma murine model, the combination treatment with HIF-1α inhibitor and anti-PD-L1 antibody caused a more pronounced suppressive effect on tumor growth compared to either monotherapy. Immunologically, the combination treatment improved both dendritic cell (DC) and CD8+ T cell activation. Overall, our results demonstrated that positive correlation between PD-L1 and HIF-1α in glioma, and provide an alternative strategy, inhibiting HIF-1α, as combination therapies with immunotherapies to advance glioma treatment.

In this paper we document our experiences with developing speech recognition for medical transcription -a system that automatically transcribes doctor-patient conversations. Towards this goal, we built a system along two different methodological lines -a Connectionist Temporal Classification (CTC) phoneme based model and a Listen Attend and Spell (LAS) grapheme based model. To train these models we used a corpus of anonymized conversations representing approximately 14,000 hours of speech. Because of noisy transcripts and alignments in the corpus, a significant amount of effort was invested in data cleaning issues. We describe a two-stage strategy we followed for segmenting the data. The data cleanup and development of a matched language model was essential to the success of the CTC based models. The LAS based models, however were found to be resilient to alignment and transcript noise and did not require the use of language models. CTC models were able to achieve a word error rate of 20.1%, and the LAS models were able to achieve 18.3%. Our analysis shows that both models perform well on important medical utterances and therefore can be practical for transcribing medical conversations.

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Purpose To investigate the dynamic changes of hyperreflective foci (HF) in diabetic macular edema (DME) patients during the intravitreal Conbercept treatment in China. Methods DME Patients receiving intravitreal Conbercept (IVC) injections during the year 2016–2017 were retrospectively investigated. Thirteen patients (26 eyes) were recruited in this study. They received IVC once a month for 3 consecutive months. The number and location of HFs, the best-corrected visual acuity (BCVA) and central macular thickness (CMT) at each visit were analyzed and compared. Results After the first injection, BCVA (LogMAR) was increased from 0.75 ± 0.48 to 0.43 ± 0.24 ( p < 0.05), CMT improved from 575.9 ± 191.9 to 388.2 ± 198.5 μm ( p = 0.014). However, the BCVA and CMT had no statistical difference after the second and third injection as compared with those after the first injection respectively. The baseline number of HFs was 5.39 ± 4.24, 5.15 ± 5.17 and 0.88 ± 1.90 in the inner retinal, outer retinal and subretinal layer respectively. The number of HFs in these three retinal layers decreased significantly after the first injection ( p = 0.0045, p < 0.0001 and p = 0.0045, respectively). However, after the second injection, only the number of HFs in the inner retinal layer experienced a further decrease. After the third injection, no statistically significant HFs changes was observed in each retinal layers. Correlation analysis showed that there was a positive significant correlation between the baseline number of HFs in the inner retina, outer retina, subretina and final BCVA (r = 0.571, p = 0.002; r = 0.464, p = 0.017; r = 0.405, p = 0.04 respectively). There was also a significant positive correlation between outer retinal HFs reduction, total retinal HFs reduction and increase of BCVA (r = 0.40, p = 0.043 and r = 0.393, p = 0.04 respectively). There were no severe ocular adverse reactions or systemic adverse events. Conclusions Conbercept is effective and safe in the treatment of DME. HFs can act as a biomarker of poor final visual outcome.