Sulfur dioxide-triggered visualization tool for auxiliary diagnosis of alcohol-induced "anti-inflammatory and pro-inflammatory" development process.

Inflammation is the most common disease in humans. Alcohol has been part of human culture throughout history. To avoid alcohol prompting inflammation to develop into a more serious disease, it is important for human health to explore the effects of alcohol on the development of inflammation.Endogenous sulfur dioxide (SO2) is considered an important regulator of the development of inflammation and is involved in the entire development process of inflammation. Taken together, it is of great significance to explore the impact of alcohol on the development process of inflammation through changes in SO2 concentration in the inflammatory microenvironment. Herein, we report the development of a molecular tool (Nu-SO2) with rapid (5 s) response to the important inflammatory modulator sulfur dioxide (SO2) for the diagnosis of inflammation, assessment of therapeutic effects, and evaluation of the development process of alcohol-induced inflammation. The rationality of Nu-SO2 was confirmed through molecular docking calculations, density functional theory (DFT) theoretical calculations, DNA/RNA titration experiments and co-localization experiments. Furthermore, Nu-SO2 was effectively applied for specific response and highly sensitive visualization imaging of SO2 in solution, cells and mice. Importantly, Nu-SO2 was successfully used to diagnose lipopolysaccharide-induced inflammation in cells and mice and evaluate the efficacy of dexamethasone in treating inflammation. More significantly, based on the excellent performance of Nu-SO2 in dynamically reporting the further development of inflammation in mice triggered by alcohol, we successfully elucidated the "anti-inflammatory and pro-inflammatory" trend in the development of inflammation caused by alcohol stimulation. Thus, this work not only advances the research on the relationship between alcohol, inflammation and SO2, but also provides a new non-invasive assessment method for the development mechanism of inflammation induced by external stimuli and the precise diagnosis and treatment of drug efficacy evaluation.

Cancer on motors: How kinesins drive prostate cancer progression?

Prostate cancer causes numerous male deaths annually. Although great progress has been made in the diagnosis and treatment of prostate cancer during the past several decades, much about this disease remains unknown, especially its pathobiology. The kinesin superfamily is a pivotal group of motor proteins, that contains a microtubule-based motor domain and features an adenosine triphosphatase activity and motility characteristics. Large-scale sequencing analyses based on clinical samples and animal models have shown that several members of the kinesin family are dysregulated in prostate cancer. Abnormal expression of kinesins could be linked to uncontrolled cell growth, inhibited apoptosis and increased metastasis ability. Additionally, kinesins may be implicated in chemotherapy resistance and escape immunologic cytotoxicity, which creates a barrier to cancer treatment. Here we cover the recent advances in understanding how kinesins may drive prostate cancer progression and how targeting their function may be a therapeutic strategy. A better understanding of kinesins in prostate cancer tumorigenesis may be pivotal for improving disease outcomes in prostate cancer patients.

Co-transcriptional R-loops-mediated epigenetic regulation drives growth retardation and docetaxel chemosensitivity enhancement in advanced prostate cancer.

R-loops are prevalent three-stranded nucleic acid structures, comprising a DNA-RNA hybrid and a displaced single-stranded DNA, that frequently form during transcription and may be attributed to genomic stability and gene expression regulation. It was recently discovered that RNA modification contributes to maintain the stability of R-loops such as N6-methyladenosine (m6A). Yet, m6A-modified R-loops in regulating gene transcription remains poorly understood. Here, we demonstrated that insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs) recognize R-loops in an m6A-dependent way. Consequently, IGF2BPs overexpression leads to increased overall R-loop levels, cell migration inhibition, and cell growth retardation in prostate cancer (PCa) via precluding the binding of DNA methyltransferase 1(DNMT1) to semaphorin 3 F (SEMA3F) promoters. Moreover, the K homology (KH) domains of IGF2BPs are required for their recognition of m6A-containing R-loops and are required for tumor suppressor functions. Overexpression of SEMA3F markedly enhanced docetaxel chemosensitivity in prostate cancer via regulating Hippo pathway. Our findings point to a distinct R-loop resolution pathway mediated by IGF2BPs, emphasizing the functional importance of IGF2BPs as epigenetic R-loop readers in transcriptional genetic regulation and cancer biology.The manuscript summarizes the new role of N6-methyladenosine in epigenetic regulation, we introduce the distinct R-loop resolution mediated by IGF2BP proteins in an m6A-dependent way, which probably lead to the growth retardation and docetaxel chemotherapy resistance in prostate cancer. Moreover, our findings first emphasized the functional importance of IGF2BPs as epigenetic R-loop readers in transcriptional genetic regulation and cancer biology. In addition, our research provides a novel RBM15/IGF2BPs/DNMT1 trans-omics regulation m6A axis, indicating the new crosstalk between RNA m6A methylation and DNA methylation in prostate cancer.

N6-methyladenosine-modified CircPSMA7 enhances bladder cancer malignancy through the miR-128-3p/MAPK1 axis.

Several studies have indicated that circular RNAs (circRNAs) play vital roles in the progression of various diseases, including bladder cancer (BCa). However, the underlying mechanisms by which circRNAs drive BCa malignancy remain unclear. In this study, we identified a novel circRNA, circPSMA7 (circbaseID:has_circ_0003456), showing increased expression in BCa cell lines and tissues, by integrating the reported information with circRNA-seq and qRT-PCR. We revealed that circPSMA7 is associated with a higher tumor grade and stage in BCa. M6A modification was identified in circPSMA7, and IGF2BP3 recognized this modification and stabilized circPSMA7, subsequently increasing the circPSMA7 expression. In vitro and in vivo experiments showed that circPSMA7 promoted BCa proliferation and metastasis by regulating the cell cycle and EMT processes. CircPSMA7 acted as a sponge for miR-128-3p, which showed antitumor effects in BCa cell lines, increasing the expression of MAPK1. The tumor proliferation and metastasis suppression induced by silencing circPSMA7 could be partly reversed by miR-128-3p inhibition. Thus, the METTL3/IGF2BP3/circPSMA7/miR-128-3p/MAPK1 axis plays a critical role in BCa progression. Furthermore, circPSMA7 may be a potential diagnostic biomarker and novel therapeutic target for patients with BCa.

A Class of Activatable NIR-II Photoacoustic Dyes for High-Contrast Bioimaging.

Photoacoustic (PA) imaging is emerging as one of the important non-invasive imaging techniques in biomedical research. Small molecule- second near-infrared window (NIR-II) PA dyes combined with imaging data can provide comprehensive and in-depth in vivo physiological and pathological information. However, the NIR-II PA dyes usually exhibit "always-on" properties due to the lack of a readily optically tunable group, which hinders the further applications in vivo. Herein, a novel class of dyes GX have been designed and synthesized as an activatable NIR-II PA platform, in which the absorption/emission wavelength of GX-5 extends up to 1082/1360 nm. Importantly, the GX dyes have a strong tissue penetration depth and high-resolution for the mouse vasculature structures in NIR-II PA 3D imaging and high signal-to-noise ratio in NIR-II fluorescence (FL) imaging. Furthermore, to demonstrate the applicability of GX dyes, the first NIR-II PA probe GX-5-CO activated by carbon monoxide (CO) was engineered and employed to reveal the enhancement of the CO levels in the hypertensive mice by high-contrast NIR-II PA and FL imaging. We expect that many derivatives of GX dyes will be developed to afford versatile NIR-II PA platforms for designing a wide variety activatable NIR-II PA probes as biomedical tools.

Spillover effects of urban form on urban land use efficiency: evidence from a comparison between the Yangtze and Yellow Rivers of China.

The contradiction between the basin's economic importance and its role as an ecological barrier impedes efficient urban land use. This study aims to propose an integrated approach to compare the urban land use of two representative basin areas of the Yangtze River Economic Belt and the Yellow River Basin and to investigate the impact of urban form on urban land use efficiency. Urban form was characterized by landscape indexes including Patch Density, Largest Patch Index, Edge Density, Patch Cohesion Index, and Agglomeration Index based on FRAGSTATS 4.0 software, and urban land use efficiency was measured by using Slack-Based Model-Undesirable, considering urban land becomes an emission source. Furthermore, spatial econometric models were adopted to explore direct effects and spatial spillover effects of urban form on urban land use efficiency. From 2000 to 2018, changes in urban form in both Yangtze River Economic Belt and Yellow River Basin showed increased fragmentation, enhanced heterogeneity, and more complex patch shapes. The high values of urban land use efficiency were concentrated in lower reaches of the Yangtze and Yellow Rivers. Spatial econometric models suggested that between different basins and various sized cities, the impact of urban form on urban land use efficiency had a spatial spillover effect and regional heterogeneity. Results indicated that input factors such as capital and labor should be more concentrated in metropolitan areas and urban agglomerations, thus promoting higher land use efficiency.

Urban expansion patterns and their driving forces analysis: a comparison between Chengdu-Chongqing and Middle Reaches of Yangtze River urban agglomerations.

Urban agglomerations have emerged as the primary drivers of high-quality economic growth in China. While recent studies have examined the urban expansion patterns of individual cities, a comparative study of the urban expansion patterns of urban agglomerations at two different scales is required for a more comprehensive understanding. Thus, in this study, we conduct a two-scale comparative analysis of urban expansion patterns and their driving factors of the two largest urban agglomerations in western and central China, i.e., Chengdu-Chongqing urban agglomeration (CCUA) and the Middle Reaches of Yangtze River urban agglomerations (MRYRUA) at both the urban agglomeration and city levels. We investigate the urban expansion patterns of CCUA and MRYRUA between 2000 and 2020 using various models, including the urban expansion rate, fractal dimension, modified compactness, and gravity-center method. Then we use multiple linear regression analysis and geographically weighted regression (GWR) to explore the magnitude and geographical differentiation of influences for economic, demographic, industrial structure, environmental conditions, and neighborhood factors on urban expansion patterns. Our findings indicate that CCUA experienced significantly faster urban growth compared to MRYRUA. There is an excessive concentration of resources to megacities within the CCUA, whereas there is a lack of sufficient collaboration among the three provinces within the MRYRUA. Additionally, we identify significant differences in the impacts of driving forces of CCUA and MRYRUA, as well as spatial heterogeneity and regional aggregation in the variation of their strength. Our two-scale comparative study of urban expansion patterns will not only provide essential reference points for CCUA and MRYRUA but also serve as valuable insights for other urban agglomerations in China, enabling them to promote sustainable urban management and foster integrated regional development.

Sentiment Analysis on Online Videos by Time-Sync Comments.

Video highlights are welcomed by audiences, and are composed of interesting or meaningful shots, such as funny shots. However, video shots of highlights are currently edited manually by video editors, which is inconvenient and consumes an enormous amount of time. A way to help video editors locate video highlights more efficiently is essential. Since interesting or meaningful highlights in videos usually imply strong sentiments, a sentiment analysis model is proposed to automatically recognize sentiments of video highlights by time-sync comments. As the comments are synchronized with video playback time, the model detects sentiment information in time series of user comments. Moreover, in the model, a sentimental intensity calculation method is designed to compute sentiments of shots quantitatively. The experiments show that our approach improves the F1 score by 12.8% and overlapped number by 8.0% compared with the best existing method in extracting sentiments of highlights and obtaining sentimental intensities, which provides assistance for video editors in editing video highlights efficiently.

Research hotspots of prostate cancer at the international conferences on urology in 2022. / 2022å¹´æ³Œå°¿å¤–ç§‘å›½é™ ä¼šè®®å‰åˆ—è ºç™Œç›¸å ³ç ”ç©¶çƒ­ç‚¹.

The American Urological Association (AUA), European Association of Urology (EUA) and International Urological Society (SIU) annual meetings were held in 2022. Studies on prostate cancer reported in the meetings mainly focus on the advances of diagnostic biomarkers (such as α-2, 3-1inked sialylation of terminal N-glycan on free PSA density, SelectMDx) and imaging techniques [such as multiparametric magnetic resonance imaging, prostate specific membrane antigen(PSMA)-PET/CT], the new method for prostate biopsy, the new treatments of prostate cancer including [177Lu] Ludotadipep and DROP-IN PSMA probe, and the prognosis assessment of prostate cancer (such as AR-V7). This article provides an overview on the research hotspots of three international academic meetings.

A robust activatable two-photon fluorescent probe for endogenous formaldehyde biomarker visualization diagnosis and evaluation of diabetes mellitus.

Diabetes mellitus and its complications are one of the largest healthcare burdens in the world and are increasing every year. However, the lack of effective biomarkers and non-invasive real-time monitoring tools remains a great challenge for the early diagnosis of diabetes mellitus. Endogenous formaldehyde (FA) represents a key reactive carbonyl species in biological systems, and altered metabolism and functions of FA have been closely related to the pathogenesis and maintenance of diabetes. Among various noninvasive biomedical imaging techniques, the identification-responsive fluorescence (FL) imaging could greatly benefit the comprehensive multi-scale assessment of some diseases such as diabetes. Herein, we have designed a robust activatable two-photon probe DM-FA for the first highly selective monitoring of fluctuations in FA levels during diabetes mellitus. Through the density functional theory (DFT) theoretical calculations, we elucidated the rationality of the activatable fluorescent probe DM-FA turning on the FL before and after the reaction with FA. In addition, DM-FA has excellent high selectivity, high growth factor and good photostability in the process of recognizing FA. Due to the brilliant two-photon and one-photon FL imaging capabilities of DM-FA, it has been successfully used to visualize of exogenous and endogenous FA in cells and mice. Remarkably, as a powerful FL imaging visualization tool, DM-FA was introduced for the first time to visually diagnose and explore diabetes through the fluctuation of FA content. The successful application of DM-FA in two-photon and one-photon FL imaging experiments found elevated FA levels in high glucose-stimulated diabetic cell models. We successfully visualized upregulation of FA levels in diabetic mice and decreased of FA levels in diabetic mice scavenged by NaHSO3 from multiple perspectives using multiple imaging modalities. This work may provide a novel strategy for the initial diagnosis of diabetes mellitus and the evaluation of the efficacy of drug therapy for treating diabetes mellitus, which will likely have a positive impact on clinical medicine.

Real-time monitoring norepinephrine exocytosis by high K+via an endoplasmic reticulum-targeting fluorescent probe.

Norepinephrine (NE), a neurotransmitter, has multiple functions in the neural system and peripheral organs. Abnormal levels of NE may lead to numerous neuro-degenerative and psychiatric disorders, such as Parkinson's disease, depression and Alzheimer's disease. Moreover, studies have indicated that an increase in NE may induce endoplasmic reticulum (ER) stress and cell apoptosis via oxidative stress. Therefore, developing a measure to monitor NE levels in the ER appears to be particularly important. The fluorescence imaging technique has become an ideal tool for detecting various biological molecules in situ, with the advantages of high selectivity, nondestructive testing, and real-time dynamic monitoring. However, there are currently no activatable ER fluorescent probes that can be used to monitor NE levels in the ER. Herein, a robust ER-targetable fluorescence probe (ER-NE) for detecting NE in the ER was constructed for the first time. With the excellent properties of high selectivity, low cytotoxicity and good biocompatibility for NE detection, ER-NE successfully achieved the detection of endogenous and exogenous NE under physiological conditions. More importantly, a probe was further applied to monitor NE exocytosis stimulated by continuous incubation with high K+. We expect that the probe may serve as a powerful tool for detecting NE and provide a potential new diagnostic method for related neurodegenerative diseases.

HMGB1, angel or devil, in ischemic stroke.

INTRODUCTION: High-mobility group box 1 protein (HMGB1) is extensively involved in causing ischemic stroke, pathological damage of ischemic brain injury, and neural tissue repair after ischemic brain injury. However, the precise role of HMGB1 in ischemic stroke remains to be elucidated. METHODS: Comprehensive literature search and narrative review to summarize the current field of HMGB1 in cerebral ischemic based on the basic structure, structural modification, and functional roles of HMGB1 described in the literature. RESULTS: Studies have exhibited the crucial roles of HMGB1 in cell death, immunity and inflammation, thrombosis, and remodeling and repair. HMGB1 released after cerebral infarction is extensively involved in the pathological injury process in the early stage of cerebral infarction, whereas it is involved in the promotion of brain tissue repair and remodeling in the late stage of cerebral infarction. HMGB1 plays a neurotrophic role in acute white matter stroke, whereas it causes sustained activation of inflammation and plays a damaging role in chronic white matter ischemia. CONCLUSIONS: HMGB1 plays a complex role in cerebral infarction, which is related to not only the modification of HMGB1 and bound receptors but also different stages and subtypes of cerebral infarction. future studies on HMGB1 should investigate the spatial and temporal dynamics of HMGB1 after cerebral infarction. Moreover, future studies on HMGB1 should attempt to integrate different stages and infarct subtypes of cerebral infarction.

Improvement Pathways for Urban Land Use Efficiency in the Beijing-Tianjin-Hebei Urban Agglomeration at the County Level: A Context-Dependent DEA Based on the Closest Target.

One of the most effective ways to achieve sustainable land use and the regional coordinated development of urban agglomerations lies in improving the urban land use efficiency (ULUE) of both large, medium, and small cities and small towns. However, in previous studies, less attention has been paid to pathways for potential improvement, especially at the county level. The main purpose of this paper is to examine potential improvement paths for the ULUE at the county level in urban agglomerations, while attempting to provide more practical targets for improvement and formulate more reasonable improvement steps for inefficient counties. Therefore, a total of 197 counties in the Beijing-Tianjin-Hebei urban agglomeration (BTHUA) in 2018 were taken as examples to build a context-dependent data envelopment analysis (DEA) model based on the closest target. In addition, by utilizing methods such as the significant difference test and system clustering analysis, the shortest path and steps to achieve efficiency were identified for inefficient counties, and the characteristics of improvement paths at different levels were summarized. Furthermore, improvement pathways were compared for two dimensions: administrative type and region. The results showed that the causes of polarization for ULUE at different levels were mainly reflected in more complex targets to be improved in the middle- and low-level counties than at high levels. Improving environmental and social benefits was essential to achieving efficiency in most inefficient counties, especially at the middle and low levels. The improvement paths for inefficient counties between different administrative types, as well as the prefecture-level cities, were heterogeneous. The results of this study can provide a policy and planning basis for improving urban land use. This study is of practical significance in accelerating the development of urbanization and the promotion of regional coordination and sustainable development.

Maximize Eco-Economic Benefits with Minimum Land Resources Input: Evaluation and Evolution of Land Use Eco-Efficiency of Agglomerations in Middle Reaches of Yangtze River, China.

Increasing land-use eco-efficiency can alleviate human-land conflict in urban areas as well as improve regional urbanization quality to achieve sustainable development. As the central urban agglomeration in China, the Middle Reaches of Yangtze River (MRYR) has experienced rapid urbanization and huge land-use change during 2000 to 2020, which poses great threats to its ecological environment. This study adopted the Super-Slack-Based Data Envelopment Analysis (Super SBM-DEA) model to evaluate the eco-efficiency of land use in MRYR. The result shows that the average eco-efficiency value of land use is above 0.77 for each year, indicating that the general efficiency is at a middle level. The trend of the evolution of the eco-efficiency can be summarized as a "U-shape" style curve. The variance between the four urban agglomerations of the MRYR changed over time. Not all capital cities or cities with higher GDP per capita obtain higher eco-efficiency in this study. Policy intervention, population and land use, technique, and environmental pollution are influencing factors of land-use eco-efficiency. Based on slacks analysis, this study proposed the optimization of the land-use structure to improve eco-efficiency from four aspects of land-use structure, investment and labor, ecosystem services value (ESV) and environment pollution, and industry structure.

Multiscale ecosystem service synergies/trade-offs and their driving mechanisms in the Han River Basin, China: implications for watershed management.

The synergies and trade-offs between ecosystem services (ESs) and their driving mechanisms are hot topics in ecology and geography research. In recent years, the Han River Basin (HRB) has been continuously impacted by high-intensity urban sprawl and the Middle Route of the South-to-North Water Diversion Project, which have posed severe threats to the ecology and regional stability along the route. It is thus critical to study the ES synergies/trade-offs and their driving mechanisms. Based on the InVEST model and the value coefficient method, four vital types of ESs in the HRB, i.e., carbon sequestration (CS), food supply (FS), net primary productivity (NPP), and water yield (WY), were evaluated at town, county, and sub-watershed scales. Then, the Pearson correlation analysis was adopted to quantify the interrelationship among different ESs. Finally, the ordinary least squares (OLS) and geographical detector model (GDM) were applied to reveal the driving mechanisms of the ES synergies/trade-offs. The results showed that (1) apart from NPP, which increased at a rate of 7.54 gC·m-2·a-1 during 2000-2018, the other three types of ESs in the HRB deteriorated, with WY almost halving. (2) While CS, FS, and WY tended to exhibit high synergistic relationships, NPP showed mostly trade-off relationships, and the evaluation scale did not affect those main relationships. (3) Precipitation is the strongest driving force for the ES synergies/trade-offs in the HRB, and natural factors are generally more influential than socioeconomic factors on the ES synergies/trade-offs. This study warns of the deteriorating ecological condition of the HRB and provides empirical evidence for the synergistic enhancement of regional ESs and the optimization of ecological management policies.

Chinese diabetes datasets for data-driven machine learning.

Data of the diabetes mellitus patients is essential in the study of diabetes management, especially when employing the data-driven machine learning methods into the management. To promote and facilitate the research in diabetes management, we have developed the ShanghaiT1DM and ShanghaiT2DM Datasets and made them publicly available for research purposes. This paper describes the datasets, which was acquired on Type 1 (n = 12) and Type 2 (n = 100) diabetic patients in Shanghai, China. The acquisition has been made in real-life conditions. The datasets contain the clinical characteristics, laboratory measurements and medications of the patients. Moreover, the continuous glucose monitoring readings with 3 to 14 days as a period together with the daily dietary information are also provided. The datasets can contribute to the development of data-driven algorithms/models and diabetes monitoring/managing technologies.

A Biocompatible Probe for the Detection of Neutrophil Elastase Free from the Interference of Structural Changes and Its Application to Ratiometric Photoacoustic Imaging In Vivo.

Neutrophil elastase (NE) plays a key role in chronic inflammation and acute responses to infection and injury. Effective disease interventions thus call for precise identification of NE to aid the clinical treatment of such diseases. However, the detection process suffers from the interference of structural changes of NE. Herein, we introduce a molecular probe with high biocompatibility to overcome the interference, which was achieved by combining theoretical calculations and experimental studies, that permits highly specific and sensitive detection of NE in cells and in vivo. The upregulated NE accumulation was specifically measured in inflammation by ratiometric photoacoustic and near-infrared fluorescence imaging, providing a new method for developing more specific fluorogenic probes for other enzymes.

A prospective multi-center randomized comparative trial evaluating outcomes of transrectal ultrasound (TRUS)-guided 12-core systematic biopsy, mpMRI-targeted 12-core biopsy, and artificial intelligence ultrasound of prostate (AIUSP) 6-core targeted biopsy for prostate cancer diagnosis.

BACKGROUND: Artificial intelligence ultrasound of prostate (AIUSP)-targeted biopsy has been used for prostate cancer (PCa) diagnosis. The objective of this prospective multi-center head-to-head clinical randomized comparative trail (RCT) is to compare PCa detection rate in the TRUS-guided 12-core standard systematic biopsy (TRUS-SB) group and cognitive fused mpMRI-guided 12-core biopsy (mpMRI) group against AIUSP group. METHODS: Four hundred patients were randomized to three arms and underwent biopsies by TRUS-SB (n = 133), mpMRI (n = 134), and AIUSP (n = 133) between January 2015 and December 2017. In TRUS-SB group, a standard 12-core systematic biopsy was performed. In mpMRI group, mpMRI-suspicious lesions (PI-RADS 3-5) were targeted by 2-core biopsy followed by a 10-core systematic biopsy. Otherwise, 12-core systematic biopsy was performed. In AIUSP group, a 6-core targeted biopsy was performed. The primary endpoint was PCa detection rate. RESULTS: AIUSP detected the highest rate of PCa (66/133, 49.6%) compared to TRUS-SB (46/133, 34.6%, p = 0.036) and mpMRI (48/134, 35.8%, p = 0.052). Compared to TRUS-SB (35/133, 26.3%) and mpMRI (31/134, 23.1%) groups, clinically significant PCa (csPCa) detection rate was 32.3% (43/133) in AIUSP group. Overall biopsy core positive rate in the TRUS-SB group (11.0%, 176/1598) and in the mpMRI group (12.7%, 204/1608) was significantly lower than that in the AIUSP group (22.7%, 181/798, p < 0.001). CONCLUSIONS: AIUSP detected the highest rate of overall and significant PCa compared to TRUS-SB and mpMRI, and could be used as an alternative to systematic biopsy in the future. REGISTRATION: This trial was registered in ISRCTN (ISRCTN18033113).

In vivo confocal microscopy of sub-basal corneal nerves and corneal densitometry after three kinds of refractive procedures for high myopia.

PURPOSE: To observe corneal nerve fibers and densitometry after small incision lenticule extraction (SMILE), femtosecond laser-assisted laser in situ keratomileusis (FS-LASIK) and laser-assisted subepithelial keratomileusis (LASEK) for high myopia. METHODS: This is a prospective, cross-sectional research study. Patients with high myopia (equivalent spherical lens: -6.00 and -11.00D) who underwent laser corneal refractive surgery were divided into three groups: SMILE, FS-LASIK and LASEK. Scheimpflug imaging of corneal nerves in five areas was observed by confocal microscopy before and 6, 12 months after surgery. Corneal densitometry was measured by Pentacam anterior segment analysis system. RESULTS: Overall, 59 patients were enrolled. The nerve density in the central area did not recover to the preoperative level in three groups until 12 months. The density and length of corneal nerves in central and lower area were better in the SMILE group 6 months postoperatively (p = 0.01), while nerve density did not differ significantly among three groups 12 months postoperatively (p = 0.18). Nerve fibers in central and temporal region were wider in LASEK than that in other two groups at 6- and 12-month follow-up. Corneal densitometry in the central 6 mm diameter was significantly higher in the LASEK group compared with other two groups 6 months postoperatively (p = 0.04). Twelve months postoperatively, corneal densitometry in range of all zone was lower in SMILE than in FS-LASIK and LASEK (p = 0.01, 0.03, 0.04). CONCLUSIONS: Compared with FS-LASIK and LASEK, SMILE-treated eyes with high myopia had certain advantages in nerve density, length and nerve connection way and had better corneal transparency after operation.

A Dual-Stage Attention Model for Tool Wear Prediction in Dry Milling Operation.

The intelligent monitoring of tool wear status and wear prediction are important factors affecting the intelligent development of the modern machinery industry. Many scholars have used deep learning methods to achieve certain results in tool wear prediction. However, due to the instability and variability of the signal data, some neural network models may have gradient decay between layers. Most methods mainly focus on feature selection of the input data but ignore the influence degree of different features to tool wear. In order to solve these problems, this paper proposes a dual-stage attention model for tool wear prediction. A CNN-BiGRU-attention network model is designed, which introduces the self-attention to extract deep features and embody more important features. The IndyLSTM is used to construct a stable network to solve the gradient decay problem between layers. Moreover, the attention mechanism is added to the network to obtain the important information of output sequence, which can improve the accuracy of the prediction. Experimental study is carried out for tool wear prediction in a dry milling operation to demonstrate the viability of this method. Through the experimental comparison and analysis with regression prediction evaluation indexes, it proves the proposed method can effectively characterize the degree of tool wear, reduce the prediction errors, and achieve good prediction results.