Comparison of 2-wall versus 3-wall orbital decompression against dysthyroid optic neuropathy in visual function: A retrospective study in a Chinese population.

ABSTRACT: To compare visual function of 2-wall (medial and lateral) versus 3-wall (medial, lateral, and inferior) orbital decompression in patients with dysthyroid optic neuropathy (DON).A total of 52 eyes of 37 patients underwent orbital decompression for DON between 2013 and 2019 were retrospectively reviewed. Two- or 3-wall decompression was performed in 31 eyes of 23 patients and 21 eyes of 14 patients, respectively. We examined best-corrected visual acuity (BCVA), visual field mean deviation (MD) and pattern standard deviation (PSD), pattern-reversed visual evoked potential (PVEP) for P100 latency and amplitude at 60 and 15 arcmin stimulation checkerboard size, as well as proptosis using Hertel exophthalmometry.Whether 2-wall or 3-wall decompression, all parameters of visual function were improved after surgery (all P < .05). The improvement in BCVA, MD, and PSD was not statistically significant between groups (all P > .05). Proptosis reduction was higher after 3-wall decompression (P = .011). Mean increase in P100 amplitude after 3-wall decompression was statistically higher than that of after 2-wall decompression at 60 and 15 arcmin (P = .045 and .020, respectively), while the mean decrease in P100 latency was similar between the groups (P = .821 and .655, respectively). Six patients (66.67%) had persistent postoperative diplopia and 1 patient (20%) had new-onset diplopia in 3-wall decompression group, which were higher than in 2-wall decompression group (46.15% persistent postoperative diplopia and no new-onset diplopia).Both 2-wall and 3-wall decompression can effectively improve visual function of patients with DON. Three-wall decompression provides better improvement in P100 amplitude and proptosis, however new-onset diplopia is more common with this surgical technique.

Nitric Oxide-Driven Nanomotor for Deep Tissue Penetration and Multidrug Resistance Reversal in Cancer Therapy.

Poor permeation of therapeutic agents and multidrug resistance (MDR) in solid tumors are the two major challenges that lead to the failure of the current chemotherapy methods. Herein, a zero-waste doxorubicin-loaded heparin/folic acid/l-arginine (HFLA-DOX) nanomotor with motion ability and sustained release of nitric oxide (NO) to achieve deep drug penetration and effective reversal of MDR in cancer chemotherapy is designed. The targeted recognition, penetration of blood vessels, intercellular penetration, special intracellular distribution (escaping from lysosomes and accumulating in Golgi and nucleus), 3D multicellular tumor spheroids (3D MTSs) penetration, degradation of tumor extracellular matrix (ECM), and reversal of MDR based on the synergistic effects of the motion ability and sustained NO release performance of the NO-driven nanomotors are investigated in detail. Correspondingly, a new chemotherapy mode called recognition-penetration-reversal-elimination is proposed, whose effectiveness is verified by in vitro cellular experiments and in vivo animal tumor model, which can not only provide effective solutions to these challenges encountered in cancer chemotherapy, but also apply to other therapy methods for the special deep-tissue penetration ability of a therapeutic agent.

Dynamic early warning of regional atmospheric environmental carrying capacity.

Economic development cannot exceed the maximum amount that the environment can support. Therefore, atmospheric environmental policy should be formulated based on the scientific assessment of regional atmospheric environmental carrying capacity. The establishment of an early warning model of atmospheric environmental carrying capacity can dynamically analyse regional atmospheric environmental carrying capacity, which contributes to discerning the change trend of the regional atmospheric environmental carrying capacity and the risk issue of the regional atmospheric environment. Additionally, it can provide theoretical reference for the formulation of relevant binding and restrictive policies. In this study, according to the daily monitoring data of atmospheric pollutants, we established a dynamic early warning model of regional atmospheric environmental carrying capacity based on the cloud model and Markov chain. The research results show that this model has an excellent early warning capability. Moreover, many regions in China have exceeded the atmospheric environmental carrying capacity, especially in North China and Central China. By 2020, North China and Central China for prediction of region with non-overloading are only 9.09% and 12.50%, respectively. China's regional atmospheric environmental carrying capacity is gradually improving. It is predicted that by 2024, regions with non-overloading in North China and Central China will reach 40.91% and 37.50%, respectively. From the overall aspect, there is currently no risk of serious overload in any region.

Spatial agglomeration of new energy industries on the performance of regional pollution control through spatial econometric analysis.

With the increasing prominence of China's energy security and environmental pollution issues, improving environmental control performance is significant for China to achieve a sustainable economy and environment. In this study, the impact of the spatial agglomeration of the new energy industry on the regional pollution control performance was considered in a spatial econometric model. From the two perspectives of technology patents and employees, the impact of the spatial agglomeration of the new energy industry was explored using the spatial panel data model. The research results show the existence of spatial correlation of the pollution control performance among regions. Moreover, the spatial agglomeration of relevant technology patents can have a negative effect and the spatial agglomeration of employees a positive effect on the improvement in regional pollution control performance. Then, policy recommendations to improve the regional pollution control performance are proposed based on the research results: establishing a regional environmental joint governance system, improving the diffusion mode of new energy technology patents, and quickly constructing a new energy industrial park.

Development of novel affinity reagents for detecting protein tyrosine phosphorylation based on superbinder SH2 domain in tumor cells.

Tyrosine phosphorylation, as a hallmark in cellular signal transduction, is important for a diverse array of cellular processes, such as proliferation, metabolism, motility, and survival. Aberrant tyrosine phosphorylation plays a causal role in many diseases, especially the cancer. Detecting protein phosphorylation status in the cancer cells or tissues is vital for assessing the pathological phase, discovering the cancer biomarkers, and identifying the drug targets. However, the common biochemical detection methods remain through anti-pTyr antibodies, which are known to have limited sensitivity, poor reproducibility and high cost. Recent studies have proved that superbinder SH2 domain is a good replacement of anti-pTyr antibodies for the specific enrichment of pTyr peptides in phosphoproteomics analysis. In this work, we exploited a series of affinity reagents based on superbinder SH2 derived from Src protein for detecting the pTyr-containing proteins to replace anti-pY antibodies in immunoblotting and immunofluorescence techniques. The excellent performance of HRP-sSH2 and EGFP-sSH2 was verified by the analysis of several different tumor cell samples and was compared with most commonly used commercial antibodies. EGFP-sSH2-(Arg)9 might be applied as the probe for direct fluorescence imaging in live cells via efficiently penetrating cell membranes and specifically binding with pTyr proteins. In summary, we have developed three novel, convenient, sensitive, and cost-effective affinity reagents that would have wide applications in protein tyrosine phosphorylation analysis for the tumor research and clinical diagnosis.