Imaging assessment of conjunctival goblet cells in dry eye disease.

Dry eye disease (DED) is a widespread, multifactorial, and chronic disorder of the ocular surface with disruption of tear film homeostasis as its core trait. Conjunctival goblet cells (CGCs) are specialised secretory cells found in the conjunctival epithelium that participate in tear film formation by secreting mucin. Changes in both the structure and function of CGCs are hallmarks of DED, and imaging assessment of CGCs is important for the diagnosis, classification, and severity evaluation of DED. Existing imaging methods include conjunctival biopsy, conjunctival impression cytology and in vivo confocal microscopy, which can be used to assess the morphology, distribution, and density of the CGCs. Recently, moxifloxacin-based fluorescence microscopy has emerged as a novel technique that enables efficient, non-invasive and in vivo imaging of CGCs. This article presents a comprehensive overview of both the structure and function of CGCs and their alterations in the context of DED, as well as current methods of CGCs imaging assessment. Additionally, potential directions for the visual evaluation of CGCs are discussed.

Classification of Vogt-Koyanagi-Harada disease using feature selection and classification based on wide-field swept-source optical coherence tomography angiography.

Background: Vogt-Koyanagi-Harada (VKH) disease is a common and easily blinded uveitis entity, with choroid being the main involved site. Classification of VKH disease and its different stages is crucial because they differ in clinical manifestations and therapeutic interventions. Wide-field swept-source optical coherence tomography angiography (WSS-OCTA) provides the advantages of non-invasiveness, large-field-of-view, high resolution, and ease of measuring and calculating choroid, offering the potential feasibility of simplified VKH classification assessment based on WSS-OCTA. Methods: 15 healthy controls (HC), 13 acute-phase and 17 convalescent-phase VKH patients were included, undertaken WSS-OCTA examination with a scanning field of 15 × 9 mm2. 20 WSS-OCTA parameters were then extracted from WSS-OCTA images. To classify HC and VKH patients in acute and convalescent phases, two 2-class VKH datasets (HC and VKH) and two 3-class VKH datasets (HC, acute-phase VKH, and convalescent-phase VKH) were established by the WSS-OCTA parameters alone or in combination with best-corrected visual acuity (logMAR BCVA) and intraocular pressure (IOP), respectively. A new feature selection and classification method that combines an equilibrium optimizer and a support vector machine (called SVM-EO) was adopted to select classification-sensitive parameters among the massive datasets and to achieve outstanding classification performance. The interpretability of the VKH classification models was demonstrated based on SHapley Additive exPlanations (SHAP). Results: Based on pure WSS-OCTA parameters, we achieved classification accuracies of 91.61% ± 12.17% and 86.69% ± 8.30% for 2- and 3-class VKH classification tasks. By combining the WSS-OCTA parameters and logMAR BCVA, we achieved better classification performance of 98.82% ± 2.63% and 96.16% ± 5.88%, respectively. Through SHAP analysis, we found that logMAR BCVA and vascular perfusion density (VPD) calculated from the whole field of view region in the choriocapillaris (whole FOV CC-VPD) were the most important features for VKH classification in our models. Conclusion: We achieved excellent VKH classification performance based on a non-invasive WSS-OCTA examination, which provides the possibility for future clinical VKH classification with high sensitivity and specificity.

Automatic vessel crossing and bifurcation detection based on multi-attention network vessel segmentation and directed graph search.

Analysis of the vascular tree is the basic premise to automatically diagnose retinal biomarkers associated with ophthalmic and systemic diseases, among which accurate identification of intersection and bifurcation points is quite challenging but important for disentangling complex vascular network and tracking vessel morphology. In this paper, we present a novel directed graph search-based multi-attentive neural network approach to automatically segment the vascular network and separate intersections and bifurcations from color fundus images. Our approach uses multi-dimensional attention to adaptively integrate local features and their global dependencies while learning to focus on target structures at different scales to generate binary vascular maps. A directed graphical representation of the vascular network is constructed to represent the topology and spatial connectivity of the vascular structures. Using local geometric information including color difference, diameter, and angle, the complex vascular tree is decomposed into multiple sub-trees to finally classify and label vascular feature points. The proposed method has been tested on the DRIVE dataset and the IOSTAR dataset containing 40 images and 30 images, respectively, with 0.863 and 0.764 F1-score of detection points and average accuracy of 0.914 and 0.854 for classification points. These results demonstrate the superiority of our proposed method outperforming state-of-the-art methods in feature point detection and classification.

Superhydrophobic fluorinated microspheres for fluorous affinity chromatography.

Fluorous affinity chromatography has received growing attention in separation and purification of fluoro compounds, but the wettability of the fluorinated stationary phases is seldom noticed. Here, we construct a series of micro-sized fluorine-containing microspheres by solvothermal precipitation polymerization. The fluorinated microspheres could be obtained with narrow size distribution at even high monomer loading of 15 wt%. Through alternating fluoro monomer, both the particle size and the wettability of the microsphere array could be tuned. Among them, the poly(divinylbenzene -dodecafluoroheptyl methacrylate), P(DVB-DFHMA), microsphere (6.1 µm) arrays displays superhydrophobicity with 153.2° water contact angle. The P(DVB-DFHMA) fluorinated microspheres (7.58% fluorine content) can be packed into steel-less columns as stationary phase for high-performance liquid chromatography. The retention mechanism of the fluorinated column is proven to be the specific fluorine-fluorine interaction. Compared to the commercial C18 silica column, the fluorinated column can completely separate fluorine-containing compounds under high water content mobile phase, including small fluoro molecules and fluoro macromolecules, at much lower back pressure by fluorous affinity.

Portable boom-type ultrahigh-resolution OCT with an integrated imaging probe for supine position retinal imaging.

To expand the clinical applications and improve the ease of use of ultrahigh-resolution optical coherence tomography (UHR-OCT), we developed a portable boom-type ophthalmic UHR-OCT operating in supine position that can be used for pediatric subjects, bedridden patients and perioperative conditions. By integrating the OCT sample arm probe with real-time iris display and automatic focusing electric lens for easy alignment, coupling the probe on a self-locking multi-directional manipulator to reduce motion artifacts and operator fatigue, and installing the OCT module on a moveable cart for system mobility, our customized portable boom-type UHR-OCT enables non-contact, high-resolution and high-stability retinal examinations to be performed on subjects in supine position. The spectral-domain UHR-OCT operates at a wavelength of 845 nm with 130 nm FWHM (full width at half maximum) bandwidth, achieving an axial resolution of ≈2.3µm in tissue with an A-line acquisition rate up to 128 kHz. A high-definition two-dimensional (2D) raster protocol was used for high-quality cross-sectional imaging while a cube volume three-dimensional (3D) scan was used for three-dimensional imaging and en-face reconstruction, resolving major layer structures of the retina. The feasibility of the system was demonstrated by performing supine position 2D/3D retinal imaging on healthy human subjects, sedated infants, and non-sedated awake neonates.

Anticancer nanomedicines harnessing tumor microenvironmental components.

INTRODUCTION: Small-molecular drugs are extensively used in cancer therapy, while they have issues of nonspecific distribution and consequent side effects. Nanomedicines that incorporate chemotherapeutic drugs have been developed to enhance the therapeutic efficacy of these drugs and reduce their side effects. One of the promising strategies is to prepare nanomedicines by harnessing the unique tumor microenvironment (TME). AREAS COVERED: The TME contains numerous cell types that specifically express specific antibodies on the surface. The physicochemical environment is characterized with a low pH, hypoxia, and a high redox potential resulting from tumor-specific metabolism. Therefore, intelligent nanomedicines designed based on the characteristics of the tumor microenvironment can be divided into two groups: the first group which is rapidly responsive to extracellular chemical/biological factors in the TME and the second one which actively and/or specifically targets cellular components in the TME. EXPERT OPINION: In this paper, we review recent progress of nanomedicines by harnessing the TME and illustrate the principles and advantages of different strategies for designing nanomedicines, which are of great significance for exploring novel nanomedicines or translating current nanomedicines into clinical practice. We will discuss the challenges and prospects of preparing nanomedicines to utilize or alter the TME for achieving effective, safe anticancer treatment.

Balanced detection spectral-domain optical coherence tomography with a single line-scan camera.

This paper describes a balanced detection spectral-domain optical coherence tomography (BD-SD-OCT) system for suppressing autocorrelation (AC) artifacts and increasing the signal-to-noise ratio (SNR). The system employed three optical fiber couplers to generate two phase-opposed interference spectra that were acquired by a single line-scan camera simultaneously. When compared with conventional unbalanced detection SD-OCT systems, the developed BD-SD-OCT system improved the SNR by 5.4-6 dB and suppressed the AC term by 5-10 dB. The imaging quality of the BD-SD-OCT system was evaluated by in vivo imaging of human nail folds and retinas.

Bimetallic-MOF-Derived Amorphous Zinc/Cobalt-Iron-Based Hollow Nanowall Arrays via Ion Exchange for Highly Efficient Oxygen Evolution.

Oxygen evolution reaction (OER) is critical for optimizing renewable energy systems, including metal-air batteries and water electrolysis. One major challenge for OER is to develop durable and cost-effective electrocatalysts with high catalytic performance. Herein, a controllable ion-exchange method to synthesize amorphous zinc/cobalt-iron hydroxide-based hollow nanowall arrays (A-Zn/Co-Fe HNAs) derived from bimetallic metal-organic frameworks (MOFs) on carbon cloth is reported. The amorphous characteristic enables the presented materials with more electrocatalytic sites and short diffusion paths for rapid access to the electrolyte, achieving efficient charge transfer for OER. The optimized nanostructure of A-Zn/Co-Fe HNAs via tuning the amount of iron sulfate in the reaction solution delivers a low overpotential of 226 mV to reach a current density of 10 mA cm-2 with a small Tafel slope of 37.81 mV dec-1 while exhibiting high durability at varied current densities over 80 h. The remarkable electrochemical performance can be attributed to the synergistic effect from chemical elements of Zn, Co-Fe, and a robust hollow structure. This simple method of fabricating bimetallic-MOF-derived amorphous Zn/Co-Fe HNAs on carbon cloth can be applied as a practical platform for other OER electrocatalysts.

A novel multiple subdivision-based algorithm for quantitative assessment of retinal vascular tortuosity.

Vascular tortuosity as an indicator of retinal vascular morphological changes can be quantitatively analyzed and used as a biomarker for the early diagnosis of relevant disease such as diabetes. While various methods have been proposed to evaluate retinal vascular tortuosity, the main obstacle limiting their clinical application is the poor consistency compared with the experts' evaluation. In this research, we proposed to apply a multiple subdivision-based algorithm for the vessel segment vascular tortuosity analysis combining with a learning curve function of vessel curvature inflection point number, emphasizing the human assessment nature focusing not only global but also on local vascular features. Our algorithm achieved high correlation coefficients of 0.931 for arteries and 0.925 for veins compared with clinical grading of extracted retinal vessels. For the prognostic performance against experts' prediction in retinal fundus images from diabetic patients, the area under the receiver operating characteristic curve reached 0.968, indicating a good consistency with experts' predication in full retinal vascular network evaluation.

Inflammatory responses associated with hyposaline stress in gill epithelial cells of the spotted scat Scatophagus argus.

The molecular processes of immune responses in mucosal tissues such as fish gills under environmental stress are poorly understood. In the present study, pro-inflammatory response under hyposaline stress and its regulation by cortisol/corticosteroid receptors (CRs) in gill epithelial cells of the spotted scat Scatophagus argus were analyzed. The fish were transferred to freshwater for 6 days (144 h) of acclimation. Following freshwater exposure, the cortisol concentration increased transiently before returning to the control level over time. mRNA expression of pro-inflammatory cytokines (TNF-a, IL-1b and IL-6) was stimulated by cortisol through CR signals at early stages of acclimation, but hyposaline stress inhibited their levels by the end of the experimental period. The transcriptional profile of anti-inflammatory cytokine IL-10 was quite different from these pro-inflammatory cytokines, and its value fluctuated within a narrow range during the experimental period. Full-length cDNAs of mineralocorticoid receptor (MR) and glucocorticoid receptor 1 (GR1) (different kinds of CRs) were cloned from the gills. Our results showed that MR and GR displayed mutually antagonistic effects during hyposaline stress. MR responded quickly at early stages, and its expression decreased with the drop of cortisol concentration. By contrast, GR expression was maintained at high levels after the acclimation of freshwater exposure. The tight coordination of GR and MR helps to shape the effects of stress on the immune system, which in turn, regulates the stress response. Our results confirm the interaction between endocrine and cytokine messengers and a clear difference in the sensitivity of GR and MR during the hyposaline challenge in gill epithelial cells of the spotted scat Scatophagus argus.

Transcriptional analysis of renal dopamine-mediated Na+ homeostasis response to environmental salinity stress in Scatophagus argus.

BACKGROUND: To control the osmotic pressure in the body, physiological adjustments to salinity fluctuations require the fish to regulate body fluid homeostasis in relation to environmental change via osmoregulation. Previous studies related to osmoregulation were focused primarily on the gill; however, little is known about another organ involved in osmoregulation, the kidney. The salinity adaptation of marine fish involves complex physiological traits, metabolic pathways and molecular and gene networks in osmoregulatory organs. To further explore of the salinity adaptation of marine fish with regard to the role of the kidney, the euryhaline fish Scatophagus argus was employed in the present study. Renal expression profiles of S. argus at different salinity levels were characterized using RNA-sequencing, and an integrated approach of combining molecular tools with physiological and biochemical techniques was utilized to reveal renal osmoregulatory mechanisms in vivo and in vitro. RESULTS: S. argus renal transcriptomes from the hyposaline stress (0‰, freshwater [FW]), hypersaline stress (50‰, hypersaline water [HW]) and control groups (25‰) were compared to elucidate potential osmoregulatory mechanisms. In total, 19,012 and 36,253 differentially expressed genes (DEGs) were obtained from the FW and HW groups, respectively. Based on the functional classification of DEGs, the renal dopamine system-induced Na+ transport was demonstrated to play a fundamental role in osmoregulation. In addition, for the first time in fish, many candidate genes associated with the dopamine system were identified. Furthermore, changes in environmental salinity affected renal dopamine release/reuptake by regulating the expression of genes related to dopamine reuptake (dat and nkaα1), vesicular traffic-mediated dopamine release (pink1, lrrk2, ace and apn), DAT phosphorylation (CaMKIIα and pkcß) and internalization (akt1). The associated transcriptional regulation ensured appropriate extracellular dopamine abundance in the S. argus kidney, and fluctuations in extracellular dopamine produced a direct influence on Na+/K+-ATPase (NKA) expression and activity, which is associated with Na+ homeostasis. CONCLUSIONS: These transcriptomic data provided insight into the molecular basis of renal osmoregulation in S. argus. Significantly, the results of this study revealed the mechanism of renal dopamine system-induced Na+ transport is essential in fish osmoregulation.

School bus routing problem in the stochastic and time-dependent transportation network.

Accidents, bad weathers, traffic congestions, etc. led to the uncertainties of travel times in real-life road networks, which greatly affected the quality of individual's life and the reliability of transportation system. This paper addressed the school bus routing problem in such a stochastic and time-dependent road environment. Firstly, the problem was set based on a single-school configuration, and the students were picked up at their homes, which was in line with the current situation of school bus systems in China. Thus, it could be regarded as an independent problem of school bus route generation in random dynamic networks, which could be solved as a variant of extended Vehicle Routing Problem. However, due to the fluctuation and uncertainty of link travel times, the arrival time at each stop including the destination was varying. Therefore, the selection of optimal path connecting the current service node with the next one was treated as a sub-problem in this study, where the reliability of travel times in the stochastic and time-varying network was highly concerned by such time-rigid commuters. To this end, a Robust Optimal Schedule Times model with a hard time windows constraint was built to generate a most cost-reliable route for school buses. By the use of Robust Optimization method, it was intended to minimize the worst-case total cost which combined the cost of earlier schedule delays with the disutility of travel times. It was also proved that the proposed model could be converted into solving a conventional problem in deterministic dynamic networks for a reduction of computation complexity, which provided the potential of applying to the practical problems. Finally, the validity of the proposed model and its performance evaluation was analyzed through a small-scale computational instance, where all the link travel times in the simulated network were attributed to both time-varying and stochastic. Then, a mathematical programming solver was used to find the exact optimal solution. The results indicated that the model was valid, and the necessity of considering the stochastic and time-dependent nature of transportation networks was also confirmed in the case study.

A framework for spatial interaction analysis based on large-scale mobile phone data.

The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning. This study aimed to analyze the spatial interaction based on the large-scale mobile phone data. The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics. A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement. The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association. A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application. The spatial interaction patterns and the representative features proved the rationality of the proposed framework.