Automatic anal sphincter integrity detection from ultrasound images via convolutional neural networks.

BACKGROUND: The anal sphincter complex comprises the anal sphincter and the U-shaped deep and superficial puborectalis muscle. As an important supporting structure of the posterior pelvic floor, together with its surrounding tissues and muscles, the anal sphincter complex maintains the normal physiological functions of defecation and continence. OBJECTIVE: The plane required for diagnosing anal sphincter injury and the diagnosis of anal sphincter integrity through pelvic floor ultrasound are highly dependent on sonographers' experience. We developed a deep learning (DL) tool for the automatic diagnosis of anal sphincter integrity via pelvic floor ultrasound. METHODS: A 2D detection network was trained to detect the bounding box of the anal sphincter. The pelvic floor ultrasound image and its corresponding oval mask were input into a 2D classification network to determine the integrity of the anal sphincter. The average precision (AP) and intersection over union (IoU) were used to evaluate the performance of anal sphincter detection. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the classification model. RESULTS: The Pearson correlation coefficients (r values) of the topmost and bottommost layers detected by the CNN and sonographers were 0.932 and 0.978, respectively. The best DL model yielded the highest area under the curve (AUC) of 0.808 (95% CI: 0.698-0.921) in the test cohort. The results from the CNN agreed well with the diagnostic results of experienced sonographers. CONCLUSIONS: We proposed, for the first time, a CNN to obtain the plane required for diagnosing anal sphincter injury on the basis of pelvic floor ultrasound and for preliminarily diagnosing anal sphincter injury.

LSD1 inhibition by tranylcypromine hydrochloride reduces alkali burn-induced corneal neovascularization and ferroptosis by suppressing HIF-1α pathway.

Background: Corneal neovascularization (CNV) is a sight-threatening condition that necessitates epigenetic control. The role of lysine-specific demethylase 1 (LSD1) in CNV remains unclear, despite its established significance in tumor angiogenesis regulation. Methods: An alkali burn-induced CNV mouse model was used in vivo. The effects of LSD1 inhibitor tranylcypromine hydrochloride (TCP) were examined through slit lamp, histological staining, and immunofluorescence. The expression of malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione (GSH) levels were assessed in corneal tissues. Oxidative stress and ferrous ion expression during CNV were determined using 4-HNE, GPX4, and FerroOrange staining. In vitro, a hypoxia-reoxygenation (H/R) model was established using human umbilical vein endothelial cells (HUVECs) to study LSD1 or hypoxia-inducible factor (HIF-1α) knockdown and lentiviral overexpression of HIF-1α. The effects on HUVECs migration, invasion, and angiogenesis were evaluated through cell scratching assay, transwell migration assay and tube formation assay. The role of ferroptosis was investigated using ROS staining, FerroOrange staining, and key ferroptosis proteins. Further, The JAK2/STAT3 pathway's involvement in CNV regulation was explored through in vivo experiments with subconjunctival injection of AG490. Results: The results showed a substantial correlation between corneal damage and LSD1 levels. In addition, HIF-1α expression was also elevated after alkali burns, and subconjunctival injection of TCP reduced corneal inflammation and neovascularization. Corneal alkali burns increased ROS levels and reduced antioxidative stress indicators, accompanied by elevated ferrous ion levels, which were reversed by TCP injection. In vitro, TCP or siRNAs inhibited H/R-induced ferroptosis and angiogenesis in HUVECs by affecting specific protein expressions and MDA, SOD, and GSH levels. HIF-1α levels, associated with ROS production, ferroptosis, and angiogenesis, increased during H/R, but were reversed by TCP or siRNA administration. HIF-1α overexpression counteracted the effects of LSD1 inhibition. Additionally, AG490 injection effectively reduced HIF-1α and VEGFA expression in the CNV model. Discussion: These findings suggest that LSD1 inhibition via the HIF-1α-driven pathway prevents angiogenesis, oxidative stress, and ferroptosis in corneal alkali burn-induced CNV, highlighting LSD1 as a potential therapeutic target.

Ultrasonographic features of female urethral caruncle: a retrospective study of 20 patients.

Female urethral caruncle is the most common urethral mass in postmenopausal women, yet there is a lack of studies on its imaging. The aim of this study was to provide a summary of the clinical and ultrasound features as well as the precise location of female urethral caruncle. This study reviewed the clinical and ultrasonographic records of 20 consecutive women with pathologically confirmed urethral caruncle. Data on patient demographics, symptoms, and transperineal and transrectal ultrasound imaging features, including location, shape, margin, size, blood flow, and inner echo of the caruncle, were extracted. Each patient presented with only one mass at the urethral meatus. Most caruncles were located on the posterior lip (75%) of the urethra, presenting as oval (80%), mixed-echoic (50%), or hypo-echoic (40%) nodules with abundant linear (40%) or dendritic (60%) blood flow. The average distance between the bladder neck and the cranial end of the masses was 28 mm. Hyper-echogenic spots, cystic echo areas, and macrocalcifications were detected in thirteen caruncles (70%). This study shows that transperineal combined with transrectal ultrasound can be used to assess female urethral caruncle, and its relative location to the urethra can be accurately described, which is helpful for surgeons making preoperative localization and conversations.

Comparative genomic and metabolomic analysis reveals the potential of a newly isolated Enterococcus faecium B6 involved in lipogenic effects.

Evidence has indicated that Enterococcus plays a vital role in non-alcoholic fatty liver disease (NAFLD) development. However, the microbial genetic basis and metabolic potential in the disease are yet unknown. We previously isolated a bacteria Enterococcus faecium B6 (E. faecium B6) from children with NAFLD for the first time. Here, we aim to systematically investigate the potential of strain B6 in lipogenic effects. The lipogenic effects of strain B6 were explored in vitro and in vivo. The genomic and functional characterizations were investigated by whole-genome sequencing and comparative genomic analysis. Moreover, the metabolite profiles were unraveled by an untargeted metabolomic analysis. We demonstrated that strain B6 could effectively induce lipogenic effects in the liver of mice. Strain B6 contained a circular chromosome and two circular plasmids and posed various functions. Compared to the other two probiotic strains of E. faecium, strain B6 exhibited unique functions in pathways of ABC transporters, phosphotransferase system, and amino sugar and nucleotide sugar metabolism. Moreover, strain B6 produced several metabolites, mainly enriched in the protein digestion and absorption pathway. The unique potential of strain B6 in lipogenic effects was probably associated with glycolysis, fatty acid synthesis, and glutamine and choline transport. This study pioneeringly revealed the metabolic characteristics and specific detrimental traits of strain B6. The findings provided new insights into the underlying mechanisms of E. faecium in lipogenic effects, and laid essential foundations for further understanding of E. faecium-related disease.

A Deep Learning Model for Automatically Quantifying the Anterior Segment in Ultrasound Biomicroscopy Images of Implantable Collamer Lens Candidates.

OBJECTIVE: This study aimed to develop and evaluate a deep learning-based model that could automatically measure anterior segment (AS) parameters on preoperative ultrasound biomicroscopy (UBM) images of implantable Collamer lens (ICL) surgery candidates. METHODS: A total of 1164 panoramic UBM images were preoperatively obtained from 321 patients who received ICL surgery in the Eye Center of Renmin Hospital of Wuhan University (Wuhan, China) to develop an imaging database. First, the UNet++ network was utilized to segment AS tissues automatically, such as corneal lens and iris. In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks (ALs) of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA), and sulcus-to-sulcus distance (STS). Based on the results of the latter two processes, PD, ACD, ATA, and STS can be measured. Meanwhile, an external dataset of 294 images from Huangshi Aier Eye Hospital was employed to further assess the model's performance in other center. Lastly, a subset of 100 random images from the external test set was chosen to compare the performance of the model with senior experts. RESULTS: Whether in the internal test dataset or external test dataset, using manual labeling as the reference standard, the models achieved a mean Dice coefficient exceeding 0.880. Additionally, the intra-class correlation coefficients (ICCs) of ALs' coordinates were all greater than 0.947, and the percentage of Euclidean distance distribution of ALs within 250 µm was over 95.24%.While the ICCs for PD, ACD, ATA, and STS were greater than 0.957, furthermore, the average relative error (ARE) of PD, ACD, ATA, and STS were below 2.41%. In terms of human versus machine performance, the ICCs between the measurements performed by the model and those by senior experts were all greater than 0.931. CONCLUSION: A deep learning-based model could measure AS parameters using UBM images of ICL candidates, and exhibited a performance similar to that of a senior ophthalmologist.

Comparative assessment of leaf photosynthetic capacity datasets for estimating terrestrial gross primary productivity.

The maximum Rubisco carboxylation rate normalized to 25 °C (Vcmax25) is a key parameter in terrestrial biosphere models for simulating carbon cycling. Recently, global distributions of Vcmax25 have been derived through various methods and different data, including field measurements, ecological optimality theory (EOT), leaf chlorophyll content (LCC), and solar-induced chlorophyll fluorescence (SIF). However, direct validation poses challenges due to high uncertainty arising from limited ground-based observations. This study conducted an indirect evaluation of four Vcmax25 datasets by assessing the accuracy of gross primary productivity (GPP) simulated using the Biosphere-atmosphere Exchange Process Simulator (BEPS) at both site and global scales. Results indicate that, compared to utilizing Vcmax25 fixed by plant functional types (PFT) derived from field measurements, incorporating Vcmax25 derived from SIF and LCC (SIF + LCC), or solely LCC, into BEPS significantly reduces simulated errors in the annual total GPP, with a 23.2 %-25.1 % decrease in the average absolute bias across 196 FLUXNET2015 sites. Daily GPP for evergreen needleleaf forests, deciduous broadleaf forests, shrublands, grasslands, and croplands shows a 7.8 %-27.6 % decrease in absolute bias, primarily attributed to reduced simulation errors during off-peak seasons of vegetation growth. Conversely, the annual total GPP error simulated using EOT-derived Vcmax25 increases slightly (2.2 %) compared to that simulated using PFT-fixed Vcmax25. This is primarily due to a significant overestimation in evergreen broadleaf forests and underestimation in croplands, despite slight increased accuracy for other PFTs. The global annual GPP simulated using Vcmax25 with seasonal variations (i.e., LCC Vcmax25 and SIF + LCC Vcmax25) yields a 4.3 %-7.3 % decrease compared to that simulated using PFT-fixed Vcmax25. Compared to FLUXCOM and GOSIF GPP products, the GPP simulated based on SIF + LCC Vcmax25 and LCC Vcmax25 demonstrates better consistency (R2 = 0.91-0.93, RMSE = 314.2-376.6 g C m-2 yr-1). This study underscores the importance of accurately characterizing the spatiotemporal variations in Vcmax25 for the accurate simulation of global vegetation productivity.

Correlation Between Anterior Chamber Angle Status and Limbal Stem Cell Deficiency in Primary Angle-Closure Glaucoma.

PURPOSE: To investigate the correlation between the opening and closing states of anterior chamber angle (ACA) and the density of limbal epithelial basal cells (LEBCs) in subjects with primary angle-closure glaucoma (PACG). DESIGN: Cross-sectional observational study. METHODS: A total of 54 eyes of 29 patients diagnosed with PACG were included in the study. Fifty-four eyes from normal subjects were included as control. Automatic evaluation system for ultrasound biomicroscopy images of anterior chamber angle was used to assist ophthalmologists in identifying the opening or closing state of ACA, and the in vivo confocal microscopy (IVCM) was used to evaluate the density of LEBCs in different directions. RESULTS: (1) The average density of LEBCs in the superior, inferior, nasal, and temporal limbus of the eyes in the PACG group was lower than that in the control group, and this pattern did not align with the density distribution observed in the control group. (2) In the early, moderate and advanced PACG, the density of LEBCs corresponding to the closed angle was lower than that in the control group (P < .05). Compared with the density of LEBCs corresponding to the closed angle and the open angle, the closed angle of PACG in the early, moderate and advanced stages was less than that in the open angle (P < .05 in the early and moderate stages; advanced stage P > .05). (3) The basal cell density was processed by dimensionless analysis. In the data calculated by averaging and minimizing, both closed angle dimensionless values were smaller than the open angle (P < .05). (4) Comparative analysis was conducted among the normal, open-angle, and closed-angle conditions in the superior, inferior, nasal, and temporal limbus. In the early stage of PACG, significant differences were observed in 4 limbal regions (P < .05), while in the moderate PACG stage, this difference was noted in 3 limbal regions (P < .05). In advanced PACG, 2 limbal regions exhibited significant differences (P < .05). These findings suggest that during the early PACG stage, angle closure is the predominant influencing factor on LEBCs density, while in the advanced stage, the decrease in density is attributed to a combination of angle closure and the natural progression of the disease. CONCLUSIONS: There is a significant correlation between anterior chamber angle status and LEBCs. Advanced PACG and angle closure should be highly suspected of the occurrence of limbal stem cell deficiency (LSCD).

High arsenic pollution of the eutrophic Lake Taihu and its relationship with iron, manganese, and dissolved organic matter: High-resolution synchronous analysis.

Arsenic (As) is a metalloid that can accumulate in eutrophic lakes and cause adverse health effects to people worldwide. However, the seasonal process and dynamic mechanism for As mobilization in eutrophic lake remains effectively unknown. Here we innovatively used the planar optodes (PO), high-resolution dialysis (HR-Peeper) combined with fluorescence excitation-emission matrix coupled with parallel factor (EEM-PARAFAC) analysis technologies. We synchronously investigate monthly O2, As, iron (Fe), manganese (Mn), and naturally occurring dissolved organic matter (DOM) changes in sediments of Lake Taihu at high resolution in field conditions. We find high As contamination from sediments with 61.88-327.07 µg m-2 d-1 release As fluxes during the algal bloom seasons from May to October 2021. Our results show that an increase in DOM, mainly for humic-like components, resulting in high electron transfer capacity (ETC), promoted the reductive dissolution of Fe and Mn oxides to release As. Partial least square-path modeling (PLS-PM) and random forest modeling analysis identified that Mn oxide reductive dissolution directly accelerated sediments As contamination, which is the crucial factor. Understanding crucial factor controlling As release is especially essential in areas of eutrophic lakes developing effective strategies to manage As-rich eutrophic lake sediments worldwide.

Contrasting effects of a traditional material of polyaluminum chloride and an emerging material of lanthanum carbonate capping on sediment internal phosphorus immobilization.

Polyaluminum chloride (PAC) is a traditional material used for immobilizing sediment internal phosphorus (P) in field-scale experiment. Lanthanum carbonate (LC) is an emerging material which have been used in immobilizing sediment internal P in laboratory. To promote LC in practice, the premise is that it does have advantages over traditional material when used. Herein, a 90-day incubation experiment was conducted comparing the effectiveness and mechanism of LC and PAC capping in controlling sediment internal P. The results of isotherm experiment and XPS analysis indicated that the adsorption mechanism of P onto LC and PAC involved ligand exchange and formation of inner-sphere La/Al-O-P complexes. The incubation experiment revealed that PAC capping was more effective in reducing pore water soluble reactive phosphorus (SRP), exhibiting a reduction of up to 81.32 % but showed a decrease trend. However, LC capping resulted in a reduction of pore water SRP up to 52.84 % and maintained stability. On average, LC and PAC capping reduced SRP flux by 0.27 and 0.32 µg·m-2d-1, respectively relative to the control sediment. Moreover, LC capping facilitated the formation of Fe(III)/Mn(IV) oxyhydroxides, leading to an increased P adsorption, whereas PAC capping facilitated the reduction of Fe(III)/Mn(IV) minerals with P release. Additionally, LC capping resulted in the reduction of a higher ratio of mobile P/TP to stable P forms than PAC capping, as compared to the control. In contrast to PAC capping which converted mobile P to stable NaOH-rP, LC capping transformed mobile P and NaOH-rP into more stable HCl-P and ResP. Both LC and PAC capping caused variations in sediment bacterial communities. Nevertheless, PAC capping heightened the risk of Co, Ni, Cu, and Pb releases in sediment compared to LC capping. In summary, this study suggested that LC capping surpassed PAC capping in immobilizing sediment internal P.

Simultaneous immobilization of sediment internal phosphorus, arsenic and tungsten by lanthanum carbonate capping.

In this study, lanthanum carbonate (LC) was selected as a capping agent to examine its effectiveness in immobilizing sediment internal phosphorus (P), arsenic (As) and tungsten (W). With a 180-day incubation experiment, it was determined that LC capping efficiently reduced the concentrations of soluble reactive P (SRP), soluble As and soluble W in pore water, with the highest reduction rate of 83.39%, 56.21% and 68.52%, respectively. The primary mechanisms involved in the adsorption of P, As and W by LC were precipitation reactions and ligand exchange. Additionally, P, As and W were immobilized by LC capping through the transformation of fractions from mobile and less stable forms to more stable forms. Furthermore, LC capping led to an increase in the Eh value, which promoted the oxidation of soluble Fe (Ⅱ) and soluble Mn. The significantly positive correlation and synchronized variations observed between SRP, soluble As, soluble W, and soluble Fe (II) indicated that the effects of LC on Fe redox played a crucial role in immobilizing sediment internal P, As and W. However, the oxidation of Mn, promoted by LC, played a more significant role in immobilizing sediment internal As than P and W. These effects resulted in LC capping achieving the highest reduction of SRP, soluble As and soluble W flux at 145.22, 22.19, and 0.58 µg m-2d-1. It is of note that LC capping did not lead to an elevated release hazard of Co, Ni, Cu, and Pb, barring Cd. Besides, LC capping did not modify the entire microbial communities in the sediment, but altered the proportional representation of specific microorganisms. Generally, LC has potential as a capping agent capable of simultaneously immobilizing sediment internal P, As and W.

Degradation of algae promotes the release of arsenic from sediments under high-sulfate conditions.

Sulfate concentrations in eutrophic waters continue to increase; however, the transformations of arsenic (As) in sediments under these conditions are unclear. In this study, we constructed a series of microcosms to investigate the effect of algal degradation on As transformations in sediments with high sulfate concentrations. The results showed that both the elevated sulfate levels and algal degradation enhanced the release of As from sediments to the overlying water, and degradation of algal in the presence of elevated sulfate levels could further contribute to As release. Sulfate competed with arsenate for adsorption in the sediments, leading to As desorption, while algal degradation created a strongly anaerobic environment, leading to the loss of the redox layer in the surface sediments. With high sulfate, algal degradation enhanced sulfate reduction, and sulfur caused the formation of thioarsenates, which may cause re-dissolution of the arsenides, enhancing As mobility by changing the As speciation. The results of sedimentary As speciation analysis indicated that elevated sulfur levels and algal degradation led to a shift of As from Fe2O3/oxyhydroxide-bound state to specifically adsorbed state at the sediment water interface. This study indicated that algal degradation increases the risk of As pollution in sulfate-enriched eutrophic waters.

Deep Learning-Based Model for Automatic Assessment of Anterior Angle Chamber in Ultrasound Biomicroscopy.

OBJECTIVE: The goal of the work described here was to develop and assess a deep learning-based model that could automatically segment anterior chamber angle (ACA) tissues; classify iris curvature (I-Curv), iris root insertion (IRI), and angle closure (AC); automatically locate scleral spur; and measure ACA parameters in ultrasound biomicroscopy (UBM) images. METHODS: A total of 11,006 UBM images were obtained from 1538 patients with primary angle-closure glaucoma who were admitted to the Eye Center of Renmin Hospital of Wuhan University (Wuhan, China) to develop an imaging database. The UNet++ network was used to segment ACA tissues automatically. In addition, two support vector machine (SVM) algorithms were developed to classify I-Curv and AC, and a logistic regression (LR) algorithm was developed to classify IRI. Meanwhile, an algorithm was developed to automatically locate the scleral spur and measure ACA parameters. An external data set of 1,658 images from Huangshi Aier Eye Hospital was used to evaluate the performance of the model under different conditions. An additional 439 images were collected to compare the performance of the model with experts. RESULTS: The model achieved accuracies of 95.2%, 88.9% and 85.6% in classification of AC, I-Curv and IRI, respectively. Compared with ophthalmologists, the model achieved an accuracy of 0.765 in classifying AC, I-Curv and IRI, indicating that its high accuracy was as high as that of the ophthalmologists (p > 0.05). The average relative errors (AREs) of ACA parameters were smaller than 15% in the internal data sets. Intraclass correlation coefficients (ICCs) of all the angle-related parameters were greater than 0.911. ICC values of all iris thickness parameters were greater than 0.884. The accurate measurement of ACA parameters partly depended on accurate localization of the scleral spur (p < 0.001). CONCLUSION: The model could effectively and accurately evaluate the ACA automatically based on fully automated analysis of UBM images, and it can potentially be a promising tool to assist ophthalmologists. The present study suggested that the deep learning model can be extensively applied to the evaluation of ACA and AC-related biometric risk factors, and it may broaden the application of UBM imaging in the clinical research of primary angle-closure glaucoma.

Dark respiration explains nocturnal stomatal conductance in rice regardless of drought and nutrient stress.

The ecological mechanism underlying nocturnal stomatal conductance (gsn ) in C3 and C4 plants remains elusive. In this study, we proposed a 'coordinated leaf trait' hypothesis to explain gsn in rice plants. We conducted an open-field experiment by applying drought, nutrient stress and the combined drought-nutrient stress. We found that gsn was neither strongly reduced by drought nor consistently increased by nutrient stress. With the aforementioned multiple abiotic stressors considered as random effects, gsn exhibited a strong positive correlation with dark respiration (Rn ). Notably, gsn primed early morning (5:00-7:00) photosynthesis through faster stomatal response time. This photosynthesis priming effect diminished after mid-morning (9:00). Leaves were cooled by gsn -derived transpiration. However, our results clearly suggest that evaporative cooling did not reduce dark respiration cost. Our results indicate that gsn is more closely related to carbon respiration and assimilation than water and nutrient availability, and that dark respiration can explain considerable variation of gsn .

Synthesis of carboxymethyl cellulose-g-poly (acrylic acid-co-acrylamide)/polyvinyl alcohol sponge as a fast absorbent composite and its application in coral sand soil.

To improve the rapid absorption capacity of coral sand soil for rainfall, a composite of carboxymethyl cellulose-g-poly (acrylic acid-co-acrylamide)/polyvinyl alcohol sponge (CMC-g-P(AA-co-AM)/PVA) was designed and synthesized by coupling CMC-g-P(AA-co-AM) granules with a PVA sponge. The results showed that the rapid water absorption of CMC-g-P (AA-co-AM)/PVA in distilled water in 1 h was 26.45 g/g, twice that of CMC-g-P(AA-co-AM) and the PVA sponge, which is suitable for short-term rainfall. In addition, the cation had a slight influence on the water absorption capacity of CMC-g-P (AA-co-AM)/PVA, which were 29.5 and 18.9 g/g in 0.9 wt% NaCl and CaCl2 solutions, respectively, indicating the great adaptability of CMC-g-P (AA-co-AM)/PVA to high­calcium coral sand. With the addition of 2 wt% CMC-g-P (AA-co-AM)/PVA, the water interception ratio of the coral sand increased from 13.8 % to 23.7 %, and 54.6 % of the total interception water remained after 15-day evaporation. Moreover, pot experiments demonstrated that 2 wt% CMC-g-P(AA-co-AM)/PVA in coral sand enhanced plant development under water scarcity, suggesting that CMC-g-P (AA-co-AM)/PVA is a promising soil amendment for coral sand soils.

Evaluation of a computer-aided diagnostic model for corneal diseases by analyzing in vivo confocal microscopy images.

Objective: In order to automatically and rapidly recognize the layers of corneal images using in vivo confocal microscopy (IVCM) and classify them into normal and abnormal images, a computer-aided diagnostic model was developed and tested based on deep learning to reduce physicians' workload. Methods: A total of 19,612 corneal images were retrospectively collected from 423 patients who underwent IVCM between January 2021 and August 2022 from Renmin Hospital of Wuhan University (Wuhan, China) and Zhongnan Hospital of Wuhan University (Wuhan, China). Images were then reviewed and categorized by three corneal specialists before training and testing the models, including the layer recognition model (epithelium, bowman's membrane, stroma, and endothelium) and diagnostic model, to identify the layers of corneal images and distinguish normal images from abnormal images. Totally, 580 database-independent IVCM images were used in a human-machine competition to assess the speed and accuracy of image recognition by 4 ophthalmologists and artificial intelligence (AI). To evaluate the efficacy of the model, 8 trainees were employed to recognize these 580 images both with and without model assistance, and the results of the two evaluations were analyzed to explore the effects of model assistance. Results: The accuracy of the model reached 0.914, 0.957, 0.967, and 0.950 for the recognition of 4 layers of epithelium, bowman's membrane, stroma, and endothelium in the internal test dataset, respectively, and it was 0.961, 0.932, 0.945, and 0.959 for the recognition of normal/abnormal images at each layer, respectively. In the external test dataset, the accuracy of the recognition of corneal layers was 0.960, 0.965, 0.966, and 0.964, respectively, and the accuracy of normal/abnormal image recognition was 0.983, 0.972, 0.940, and 0.982, respectively. In the human-machine competition, the model achieved an accuracy of 0.929, which was similar to that of specialists and higher than that of senior physicians, and the recognition speed was 237 times faster than that of specialists. With model assistance, the accuracy of trainees increased from 0.712 to 0.886. Conclusion: A computer-aided diagnostic model was developed for IVCM images based on deep learning, which rapidly recognized the layers of corneal images and classified them as normal and abnormal. This model can increase the efficacy of clinical diagnosis and assist physicians in training and learning for clinical purposes.

A combined study on Vallisneria spiralis and lanthanum modified bentonite to immobilize arsenic in sediments.

Submerged plants and lanthanum-modified bentonite (LMB) have important applications for the remediation of contaminated sediments; however, their combined effect on arsenic (As) removal has not been comprehensively evaluated. In this study, the physicochemical properties and changes in soluble As in sediments treated with LMB, Vallisneria spiralis (V. spiralis), and LMB + V. spiralis were observed at three time points (days 15, 35, and 66), and the changes in microbial and As species in sediments on day 66 were analyzed. LMB + V. spiralis treatment was the most effective for As removal. On day 66, the average concentrations of soluble As at a depth of 0-100 mm decreased by 12.71%, 48.81%, and 59.73% following treatment with LMB, V. spiralis, and LMB + V. spiralis, respectively. Further analysis showed that LMB is more effective at removing As(V) than V. spiralis, while V. spiralis is more effective at removing As(III), and the combination of LMB + V. spiralis is more effective for removing both As(III) and As(V) than individual LMB and V. spiralis treatments. LMB + V. spiralis enhanced the transformation of mobile As to Fe2O3/oxyhydroxide-bound As in sediments and the activity of As-oxidizing microorganisms. LMB promoted the growth of V. spiralis and enhanced the removal of As. This study indicates that this combination is an effective method for removing mobile As from sediments, and could effectively inhibit the release of As from sediments to overlying water.

Thermochemical Recycling of Oily Sludge by Catalytic Pyrolysis: A Review.

The main methods of treating oily sludge at home and abroad and the current research status of oily sludge pyrolysis technology are briefly described, and four commonly used catalysts are introduced: metals, metal compounds, molecular sieves, metal-supported molecular sieves, and biomass catalysts for oily sludge. The influence of pyrolysis, the pyrolysis mechanism, and the product composition of oily sludge with the addition of different catalysts are also discussed. Finally, the development direction of preparing new catalysts and the mixed use of multiple catalysts is proposed as a theory to provide for the efficient and reasonable utilization of oily sludge.

A Deep Learning Model for Screening Multiple Abnormal Findings in Ophthalmic Ultrasonography (With Video).

Purpose: The purpose of this study was to construct a deep learning system for rapidly and accurately screening retinal detachment (RD), vitreous detachment (VD), and vitreous hemorrhage (VH) in ophthalmic ultrasound in real time. Methods: We used a deep convolutional neural network to develop a deep learning system to screen multiple abnormal findings in ophthalmic ultrasonography with 3580 images for classification and 941 images for segmentation. Sixty-two videos were used as the test dataset in real time. External data containing 598 images were also used for validation. Another 155 images were collected to compare the performance of the model to experts. In addition, a study was conducted to assess the effect of the model in improving lesions recognition of the trainees. Results: The model achieved 0.94, 0.90, 0.92, 0.94, and 0.91 accuracy in recognizing normal, VD, VH, RD, and other lesions. Compared with the ophthalmologists, the modal achieved a 0.73 accuracy in classifying RD, VD, and VH, which has a better performance than most experts (P < 0.05). In the videos, the model had a 0.81 accuracy. With the model assistant, the accuracy of the trainees improved from 0.84 to 0.94. Conclusions: The model could serve as a screening tool to rapidly identify patients with RD, VD, and VH. In addition, it also has potential to be a good tool to assist training. Translational Relevance: We developed a deep learning model to make the ultrasound work more accurately and efficiently.

The effects of lipid-lowering therapy on coronary plaque regression: a systematic review and meta-analysis.

To assess the influence of lipid-lowering therapy on coronary plaque volume, and to identify the LDL and HDL targets for plaque regression to provide a comprehensive overview. The databases searched (from inception to 15 July 2020) to identify prospective studies investigating the impact of lipid-lowering therapy on coronary plaque volume and including quantitative measurement of plaque volume by intravascular ultrasound after treatment. Thirty-one studies that included 4997 patients were selected in the final analysis. Patients had significantly lower TAV (SMD: 0.123 mm3; 95% CI 0.059, 0.187; P = 0.000) and PAV (SMD: 0.123%; 95% CI 0.035, 0.212; P = 0.006) at follow-up. According to the subgroup analyses, TAV was significantly reduced in the LDL < 80 mg/dL and HDL > 45 mg/dL group (SMD: 0.163 mm3; 95% CI 0.092, 0.234; P = 0.000), and PAV was significantly reduced in the LDL < 90 mg/dL and HDL > 45 mg/dL group (SMD: 0.186%; 95% CI 0.081, 0.291; P = 0.001).Thirty-one studies that included 4997 patients were selected in the final analysis. Patients had significantly lower TAV (SMD: 0.123 mm3; 95% CI 0.059, 0.187; P = 0.000) and PAV (SMD: 0.123%; 95% CI 0.035, 0.212; P = 0.006) at follow-up. According to the subgroup analyses, TAV was significantly reduced in the LDL < 80 mg/dL and HDL > 45 mg/dL group (SMD: 0.163 mm3; 95% CI 0.092, 0.234; P = 0.000), and PAV was significantly reduced in the LDL < 90 mg/dL and HDL > 45 mg/dL group (SMD: 0.186%; 95% CI 0.081, 0.291; P = 0.001). Our meta-analysis suggests that not only should LDL be reduced to a target level of < 80 mg/dL, but HDL should be increased to a target level of > 45 mg/dL to regress coronary plaques.Trial Registration PROSPERO identifier: CRD42019146170.

Spatiotemporal evolvement and factors influencing natural and synthetic EDCs and the microbial community at different groundwater depths in the Chaobai watershed: A long-term field study on a river receiving reclaimed water.

In this long-term field study, to restore a dried river ecosystem, reclaimed water was used as a supplementary water source. The main aim of this study was to investigate the accumulation and migration potential of EDCs in groundwater during long-term utilization of reclaimed water and the changes in microbial community during the removal of EDCs. A long-term field study was conducted in order to ascertain the temporal and spatial distribution of four selected endocrine-disrupting chemicals (EDCs) in an underground aquifer in the Chaobai watershed, where reclaimed water is the primary water source. Anew, the microbial community structure at different groundwater depths, along with related environmental factors were also determined. Based on the results obtained from this long-term study, it was found that the EDCs in the surface water of the Chaobai river have entered a depth of 80 m in the groundwater aquifers, within a distance of 360 m from the river. The vertical profiles of the concentrations of bisphenol A (BPA), 4-nonylphenol (NP), estrone (E1), and estriol (E3) decreased significantly from the surface to different groundwater depths with first-order attenuation rates of 0.0416, 0.0343, 0.0498, and 0.0173 m-1. The aquifer depth, water temperature, conductivity, and coexisting anions correlated well with the distribution of EDCs in groundwater.