The Influence of Temperature on the Photoelectric Properties of GeSe Nanowires.

Using physical vapor deposition (PVD) technology, GeSe nanowires were successfully fabricated by heating GeSe powder at temperatures of 500 °C, 530 °C, 560 °C, 590 °C, and 620 °C. The microstructure, crystal morphology, and chemical composition of the resulting materials were thoroughly analyzed employing methods like Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), plus Raman Spectroscopy. Through a series of photoelectric performance tests, it was discovered that the GeSe nanowires prepared at 560 °C exhibited superior properties. These nanowires not only possessed high crystalline quality but also featured uniform diameters, demonstrating excellent consistency. Under illumination at 780 nm, the GeSe nanowires prepared at this temperature showed higher dark current, photocurrent, and photoresponsivity compared to samples prepared at other temperatures. These results indicate that GeSe nanomaterials hold substantial potential in the field of photodetection. Particularly in the visible light spectrum, GeSe nanomaterials exhibit outstanding light absorption capabilities and photoresponse.

Enantioseparation of amino acid and mandelic acid enantiomers using Josiphos-metal complexes as chiral extractants.

The development of new and efficient chiral extractants has always been the research hotspot and difficulty in the field of chiral extraction. Josiphos, a famous ferrocene derivative catalyst, is employed as a chiral extractant in enantioseparation of amino acid and mandelic acid enantiomers. The influences of metal ions, organic solvents, pH of the aqueous solution, extractant concentrations, and extraction temperature on enantioselectivities are systematically studied. The result reveals that Josiphos-Pd has good capabilities to enantioseparate 4-nitro-phenylalanine (Nphe), 3-chloro-phenylglycine (Cpheg), and mandelic acid (MA) with separation factors (α) of 3.30, 2.65, and 2.18, respectively. The pH of the aqueous phase and Josiphos-Pd concentration affect the extraction significantly, whereas extraction temperature shows little influence. After optimizing by response surface method, the mathematical models for extractions are established. And the highest experimental performance factors (pf) for Nphe, Cpheg, and MA are 0.1843, 0.1335, and 0.08884, respectively.

Enantioseparation of amino acid and mandelic acid enantiomers using Garphos derivatives as chiral extractants.

In this paper, Garphos with different substituents were employed as chiral extractants to enantioseparate racemic amino acid and mandelic acid. The influences of metal precursors, pH of aqueous solution, Garphos-metal concentration, extraction temperature, and substituent effect on extraction were investigated. The results indicated that the substituent groups significantly affected the π-π interaction between extractant and substrate. And the separation factors (α) for Garphos could be remarkably improved by regulating substituent groups. Garphos-II-Pd, Garphos-VI-Pd, Garphos-III-Pd, Garphos-I-Cu, Garphos-VI-Cu, and Garphos-V-Pd were the most efficient extractants for phenylalanine (Phe), homophenylalanine (Hphe), 4-nitrophenylalanine (Nphe), 3-chlorophenylglycine (Cpheg), mandelic acid (MA), and 2-chlormandelic acid (CMA) with α values of 2.40, 2.37, 5.37, 1.59, 5.98, and 3.69, respectively. This work provided an important reference for the design of efficient chiral extractants in future work.

Automatic identification of meibomian gland dysfunction with meibography images using deep learning.

BACKGROUND: Artificial intelligence is developing rapidly, bringing increasing numbers of intelligent products into daily life. However, it has little progress in dry eye, which is a common disease and associated with meibomian gland dysfunction (MGD). Noninvasive infrared meibography, known as an effective diagnostic tool of MGD, allows for objective observation of meibomian glands. Thus, we discuss a deep learning method to measure and assess meibomian glands of meibography. METHODS: We used Mask R-CNN deep learning (DL) framework. A total of 1878 meibography images were collected and manually annotated by two licensed eyelid specialists with two classes: conjunctiva and meibomian glands. The annotated pictures were used to establish a DL model. An independent test dataset that contained 58 images was used to compare the accuracy and efficiency of the deep learning model with specialists. RESULTS: The DL model calculated the ratio of meibomian gland loss with precise values by achieving high accuracy in the identification of conjunctiva (validation loss < 0.35, mAP > 0.976) and meibomian glands (validation loss < 1.0, mAP > 0.92). The comparison between specialists' annotation and the DL model evaluation showed that there is little difference between the gold standard and the model. Each image takes 480 ms for the model to evaluate, almost 21 times faster than specialists. CONCLUSIONS: The DL model can improve the accuracy of meibography image evaluation, help specialists to grade the meibomian glands and save their time to some extent.

Inhibition of EZH2 alleviates angiogenesis in a model of corneal neovascularization by blocking FoxO3a-mediated oxidative stress.

Enhancer of zeste homolog 2 (EZH2), a well-known methyltransferase, mediates histone H3 lysine 27 trimethylation (H3K27me3) and plays a vital role in ophthalmological disease. However, its role in corneal neovascularization (CoNV) remains unclear. In vitro and in vivo models were assessed in hypoxia-stimulated angiogenesis and in a mouse model of alkali burn-induced CoNV. Human umbilical vein endothelial cells (HUVECs) were cultured under hypoxic conditions and different reoxygenation times to identify the molecular mechanisms involved in this process. In this study, we found that EZH2 was positively related to corneal alkali burn-induced injury. Inhibition of EZH2 with 3-Deazaneplanocin A (DZNeP) alleviated corneal injury, including oxidative stress and neovascularization in vivo. Similarly, inhibition of EZH2 with either DZNeP or small interfering RNA (siRNA) exerted an inhibitory effect on hypoxia/reoxygenation (H/R)-induced oxidative stress and angiogenesis in HUVECs. Moreover, our study revealed that ablation of reactive oxygen species (ROS) with N-acetyl-cysteine suppressed angiogenesis in HUVECs exposed to H/R stimulation. Furthermore, Forkhead-box protein O3a (FoxO3a), which was positively associated with ROS production and angiogenesis, was elevated during H/R. This effect could be reversed through the suppression of the transcription activity of EZH2 with DZNeP or siRNA. In addition, the PI3K/Akt pathway, which is the upstream of FoxO3a, was activated in both DZNeP-treated mice and EZH2-inhibited HUVECs. Collectively, our results demonstrated that the inhibition of EZH2 alleviated corneal angiogenesis by inhibiting FoxO3a-dependent ROS production through the PI3K/Akt signaling pathway. These findings indicate that EZH2 may be a valuable therapeutic target for CoNV.

Automated and real-time validation of gastroesophageal varices under esophagogastroduodenoscopy using a deep convolutional neural network: a multicenter retrospective study (with video).

BACKGROUND AND AIMS: Rupture of gastroesophageal varices is the most common fatal adverse event of cirrhosis. EGD is considered the criterion standard for diagnosis and risk stratification of gastroesophageal variceal bleeding. The aim of this study was to train and validate a real-time deep convolutional neural network (DCNN) system, named ENDOANGEL, for diagnosing gastroesophageal varices and predicting the risk of rupture. METHODS: After training with 8566 images of endoscopic gastroesophageal varices from 3021 patients and 6152 images of normal esophagus/stomach from 3168 patients, ENDOANGEL was also tested with independent images and videos. It was also compared with endoscopists in several aspects. RESULTS: ENDOANGEL, in contrast with endoscopists, displayed higher accuracy of 97.00% and 92.00% in terms of detecting esophageal varices (EVs) and gastric varices (GVs) in an image contest (97.00% vs 93.94% , P < .01; 92.00% vs 84.43%, P < .05). It also surpassed endoscopists for red color signs of EVs and red spots of GVs (84.21% vs 73.45%, P < .01; 85.26% vs 77.52%, P < .05). Moreover, ENDOANGEL achieved comparable performance in the determination of size, form, color, and bleeding signs. ENDOANGEL also had good performance in making treatment suggestions. With regard to predicting risk factors in multicenter videos, ENDOANGEL showed great stability. CONCLUSIONS: Our data suggest that DCNNs were precise in detecting both EVs and GVs and performed excellently in uncovering the endoscopic risk factors of gastroesophageal variceal bleeding. Thus, the application of DCNNs will assist endoscopists in evaluating gastroesophageal varices more objectively and precisely. (Clinical trial registration number: ChiCTR1900023970.).

Cohesion in the discourse of people with post-stroke aphasia.

Aphasic discourse has been investigated through two major approaches: a micro-linguistic approach and a macro one, but the separate analysis of the micro and macro aspects of aphasic discourse has led to a noticeable gap between them. Cohesion analysis is one of the possible ways that can directly connect these two aspects. However, few studies have investigated cohesion in aphasic discourse in an integrated manner. The present study employs a mixed-methods approach to examine whether and how patients with fluent and non-fluent stroke-induced aphasia differ from normal individuals in the cohesion of their discourse, aiming to provide a more comprehensive understanding of this issue. We compared the use of cohesive devices in the discourse of 7 non-fluent aphasics (4 males, mean age = 70.9) and 9 fluent aphasics (4 males, mean age = 70.7) against 16 non-aphasic controls (NACs) (8 males, mean age = 71.0). Transcripts were analysed and conclusions were drawn based on the combination of quantitative and qualitative observations. As predicted, discourse by aphasic participants is less cohesive than that by non-aphasic participants and the three groups' discourse differs from each other in the distribution of cohesion categories, with non-fluent aphasics having more trouble in using grammatical cohesive devices while fluent aphasics more severely affected in constructing lexical cohesion. Results suggest that cohesion in post-stroke aphasic discourse may vary between different aphasia types and thus can be rather complicated. Additional work involving more aphasia types and more dimensions of discourse cohesion is needed to provide further insight into this question.

A deep learning method for delineating early gastric cancer resection margin under chromoendoscopy and white light endoscopy.

BACKGROUND: Accurate delineation of cancer margins is critical for endoscopic curative resection. This study aimed to train and validate real-time fully convolutional networks for delineating the resection margin of early gastric cancer (EGC) under indigo carmine chromoendoscopy (CE) or white light endoscopy (WLE), and evaluated its performance and that of magnifying endoscopy with narrow-band imaging (ME-NBI). METHODS: We collected CE and WLE images of EGC lesions to train fully convolutional networks ENDOANGEL. ENDOANGEL was tested both on stationary images and endoscopic submucosal dissection (ESD) videos. The accuracy and reliability of ENDOANGEL and NBI-dependent delineation were further evaluated by a novel endoscopy-pathology point-to-point marking. RESULTS: ENDOANGEL had an accuracy of 85.7% in the CE images and 88.9% in the WLE images under an overlap ratio threshold of 0.60 in comparison with the manual markers labeled by the experts. In the ESD videos, the resection margins predicted by ENDOANGEL covered all areas of high-grade intraepithelial neoplasia and cancers. The minimum distance between the margins predicted by ENDOANGEL and the histological cancer boundary was 3.44 ± 1.45 mm which outperformed the resection margin based on ME-NBI. CONCLUSIONS: ENDOANGEL has the potential to assist endoscopists in delineating the resection extent of EGC under CE or WLE during ESD.

miR-212 downregulation contributes to the protective effect of exercise against non-alcoholic fatty liver via targeting FGF-21.

Non-alcoholic fatty liver disease (NAFLD) is associated with obesity and lifestyle, while exercise is beneficial for NAFLD. Dysregulated microRNAs (miRs) control the pathogenesis of NAFLD. However, whether exercise could prevent NAFLD via targeting microRNA is unknown. In this study, normal or high-fat diet (HF) mice were either subjected to a 16-week running program or kept sedentary. Exercise attenuated liver steatosis in HF mice. MicroRNA array and qRT-PCR demonstrated that miR-212 was overexpressed in HF liver, while reduced by exercise. Next, we investigated the role of miR-212 in lipogenesis using HepG2 cells with/without long-chain fatty acid treatment (± FFA). FFA increased miR-212 in HepG2 cells. Moreover, miR-212 promoted lipogenesis in HepG2 cells (± FFA). Fibroblast growth factor (FGF)-21, a key regulator for lipid metabolism, was negatively regulated by miR-212 at protein level in HepG2 cells. Meanwhile, FFA downregulated FGF-21 both at mRNA and protein levels in HepG2 cells. Also, FGF-21 protein level was reduced in HF liver, while reversed by exercise in vivo. Furthermore, siRNA-FGF-21 abolished the lipogenesis-reducing effect of miR-212 inhibitor in HepG2 cells (± FFA), validating FGF-21 as a target gene of miR-212. These data link the benefit of exercise and miR-212 downregulation in preventing NAFLD via targeting FGF-21.

MiR-221 Promotes Capan-2 Pancreatic Ductal Adenocarcinoma Cells Proliferation by Targeting PTEN-Akt.

BACKGROUND/AIMS: MicroRNAs (miRNAs, miRs) have emerged as critical regulators of cancer cell proliferation. The effect of miR-221 on cancer cell growth could be significantly changeable in different cell lines. Although miR-221 was reported to promote the cell growth of pancreatic ductal adenocarcinoma (PDAC) cells, its role in Capan-2 cell line is largely unknown. METHODS: Capan-2 cells were transfected with miR-221 mimics, inhibitors, or negative controls. Cell Counting Kit-8 was used to determine cell viability. EdU staining and cell cycle analysis were used to measure cell proliferation. Western blotting was used to detect the expression levels of PTEN and phospho-Akt. The PI3K-Akt pathway activator SC-79 and inhibitor LY294002 were used to perform the rescue experiment in determining cell proliferation. RESULTS: Overexpressing miR-221 significantly increased cell vitality and promoted cell proliferation and G1-to-S phase transition of the cell cycle in Capan-2 cells, while inhibition of miR-221 decreased that. The protein level of PTEN in Capan-2 cells was downregulated by overexpressing miR-221, while upregulated by inhibiting miR-221. Consistently, enhanced phosphorylation of AktSer473 was observed in miR-221 overexpressed Capan-2 cells, and the opposite result was found in miR-221 inhibited cells. LY294002 restored the pro-proliferation effect of miR-221 on Capan-2 cells, while SC-79 had no additional effect on cell proliferation in Capan-2 cells transfected with miR-221 mimics. CONCLUSION: Our study indicates that miR-221 is an oncogenic miRNA which promotes Capan-2 cells proliferation by targeting PTEN-Akt pathway.

Risk Factors for Dry Eye Syndrome: A Retrospective Case-Control Study.

PURPOSE: To investigate the independent risk factors of dry eye syndrome (DES) in Chinese. METHODS: A hospital-based age- and sex-matched population was enrolled with a case-control ratio of 1:2, with 789 DES case patients and 1119 healthy family members. Both groups underwent standard ophthalmologic examinations, including slit-lamp evaluation of the anterior segment, measurement of tear film breakup time, Schirmer test, and corneal fluorescein staining. Data on demographic characteristics and lifestyle habits were collected using a questionnaire. Dry eye syndrome risk factors were identified by univariate and multivariate logistic regression analyses. RESULTS: The following independent risk factors showed significant association with DES: diabetes (odds ratio [OR], 1.408; 95% confidence interval [CI], 1.031 to 1.924), hepatitis C (OR, 3.326; 95% CI, 1.632 to 6.776); connective tissue disease (OR, 2.157; 95% CI, 1.679 to 2.771), benign prostatic hyperplasia (OR, 3.892; 95% CI, 2.476 to 6.116), rosacea (OR, 3.747; 95% CI, 1.972 to 7.120), posttraumatic stress disorder (OR, 1.449; 95% CI, 1.043 to 2.013), hematopoietic stem cell transplantation (OR, 7.269; 95% CI, 2.312 to 22.849), head and neck radiotherapy (OR, 8.776; 95% CI, 3.096 to 24.873), postmenopausal estrogen therapy (OR, 1.912; 95% CI, 1.160 to 3.151), antihistamines (OR, 2.040; 95% CI, 1.516 to 2.746), antidepressants (OR, 1.982; 95% CI, 1.077 to 3.647), contact lenses (OR, 2.366; 95% CI, 1.266 to 4.423), and video display terminal exposure for more than 6 h/d (OR, 2.275; 95% CI, 1.451 to 3.568). Potentially protective factors against DES were vitamin supplements (OR, 0.716; 95% CI, 0.528 to 0.972) and Ω-3 fatty acid-rich diet (OR, 0.514; 95% CI, 0.332 to 0.796). CONCLUSION: Several known risk factors of DES are applicable to Chinese, and some distinctive dietary factors may be protective in this population.

Prevalence of infectious keratitis in Central China.

BACKGROUND: The baseline data pertaining to the national epidemiological survey of infectious keratitis remain scarce in China, and currently there is no corneal blindness control strategy developed by the nation. METHODS: Geographically defined cluster sampling was used to randomly select a cross-section of residents from representative urban and rural populations in Hubei Province. Participants were selected from village registers, followed by door-to-door household visits. The assessment items included a structured interview, visual acuity testing, external eye examination, and anterior segment examination using slit lamp. Causes and sequelae of corneal disease were identified according to uniform customized protocol. RESULTS: The prevalence of presenting corneal diseases was 0.8% (211/26 305), while the prevalence of infectious keratitis was 0.148% (39/26 305). The prevalences of viral, bacterial, and fungal keratitis were 0.065, 0.068, and 0.015%, respectively. There were no significant differences found between the prevalences of viral (accounting for 43.6%) and bacterial (accounting for 46.2%) corneal ulcers. cases of Acanthamoeba keratitis were not found. Infectious keratitis was the leading cause of corneal blindness (85.7%), and the prevalence of blindness in at least one eye resulting from infected corneas was 0.091% (95% CI: 0.067-0.127%). CONCLUSIONS: Viral and bacterial mechanisms constitute the most important risk factors for infectious corneal ulcers in Central China. To reduce the rate and severity of infectious keratitis, he public health care policy should be focused on designing cost-effective strategies and operational programs for the prevention and prompt treatment of infectious corneal ulcers.

Sensing Based on Plasmon-Induced Transparency in H-Shaped Graphene-Based Metamaterials.

Graphene can support surface plasmon polaritons (SPPs) in the terahertz band, and graphene SPP sensors are widely used in the field of terahertz micro- and nano-optical devices. In this paper, we propose an H-shaped graphene metasurface and investigate the plasmon-induced transparency (PIT) phenomenon in the proposed structure using the finite-difference time-domain (FDTD) method. Our results show that the Fermi energy levels, as well as certain shape parameters, can effectively modulate the PIT phenomenon in the proposed structure. Interestingly, changing some of these shape parameters can excite two dips into three. In terms of sensing performance, the maximum values of sensitivity and figure of merit (FOM) are 1.4028 THz/RIU and 17.97, respectively. These results offer valuable guidance for the use of terahertz optical graphene SPP sensors.

Investigating the Causal Relationship Between Sleep Behaviors and Primary Open-Angle Glaucoma: A Bidirectional Two-Sample Mendelian Randomization Study.

Background: Although previous studies of sleep-related behaviors in relation to primary open-angle glaucoma (POAG) have been noted, the causal relationship remains unclear. The purpose of our present study was to investigate the relationships of genetically predicted sleep traits with POAG using a two-sample bidirectional Mendelian randomization (MR) method. Methods: Summary-level data collected from publicly available genome-wide association studies (GWAS) of European decent were applied for the bidirectional MR analysis. After quality control steps, independent single-nucleotide polymorphisms for eight sleep behaviors and POAG were selected as the genetic instruments. The inverse-variance weighted (IVW) approach was adopted as the primary method, which was complemented by a series of sensitivity analyses to assess the robustness of the results by estimating heterogeneity and pleiotropy. Multivariable MR (MVMR) was used to assess the direct effect of sleep traits on POAG, after adjusting for several confounding factors. Results: Our investigation revealed a positive correlation between genetically predicted ease of getting up in the morning and sleep duration and POAG using the IVW method (odds ratio (OR)=1.78, 95% confidence interval (CI):1.29-2.46, P = 4.33× 10-4; OR = 1.66, 95% CI:1.18-2.34, P = 3.38×10-3, respectively). Other supplementary MR methods also confirmed similar results. Moreover, the MVMR results also revealed that the adverse effects of these two sleep traits on POAG persisted after adjusting for body mass index, smoking, drinking, and education (all P < 0.05). Conversely, the relationships between genetic liability of POAG and different sleep behaviors were not statistically significant in the reverse-direction MR estimate (all P > 0.05). Conclusion: Our study demonstrated that genetic prediction of getting up easily in the morning or sleep duration were associated with a higher risk of POAG, but not vice versa, in a European population. Further validation and clinical interventions are required to offer potential strategies to prevent and manage POAG.

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.

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).

Inhibiting PRMT1 protects against CoNV by regulating macrophages through the FGF2/PI3K/Akt pathway.

Corneal neovascularization (CoNV) is predominantly initiated by inflammatory processes, resulting in aberrant vascular proliferation and consequent visual impairment. Existing therapeutic interventions for CoNV demonstrate limited efficacy and potential for adverse reactions. Protein arginine methyltransferase 1 (PRMT1) is associated with the regulation of inflammation and M2 macrophage polarization. Nevertheless, the precise mechanism by which PRMT1 operates in CoNV remains uncertain. This study explored the impact of PRMT1 inhibition in a murine model of CoNV induced by alkali burn. Our findings indicated a direct relationship between PRMT1 levels and corneal damage. Moreover, our observations indicated an increase in fibroblast growth factor 2 (FGF2) expression in CoNV, which was reduced after treatment with a PRMT1 inhibitor. The inhibition of PRMT1 alleviated both corneal injury and CoNV, as evidenced by decreased corneal opacity and neovascularization. Immunofluorescence analysis and evaluation of inflammatory factor expression demonstrated that PRMT1 inhibition attenuated M2 macrophage polarization, a phenomenon that was reversed by the administration of recombinant FGF2 protein. These results were confirmed through experimentation on Human Umbilical Vein Endothelial Cells (HUVECs) and Mouse leukemia cells of monocyte macrophage cells (RAW264.7). Furthermore, it was established that FGF2 played a role in PI3K/Akt signal transduction, a critical regulatory pathway for M2 macrophage polarization. Importantly, the activity of this pathway was found to be suppressed by PRMT1 inhibitors. Mechanistically, PRMT1 was shown to promote M2 macrophage polarization, thereby contributing to CoNV, through the FGF2/PI3K/Akt pathway. Therefore, targeting PRMT1 may offer a promising therapeutic approach.

HMW-GSs 1Dx3+1Dy12 contribute to a suitable wheat gluten strength that confers superior Chinese steamed bread quality.

The aim of this study was to clarify the effects of the high-molecular-weight glutenin subunits (HMW-GSs) 1Dx3+1Dy12 (3+12) and 1Dx4+1Dy12 (4+12) at the Glu-D1 locus on gluten and Chinese steamed bread (CSB) quality. The grain protein content and composition, gluten content and gluten index, farinograph properties, and CSB quality were investigated using four wheat near-isogenic lines (NILs) carrying HMW-GSs 1Dx2+1Dy12 (2+12), 3+12, 4+12 and 1Dx5+1Dy10 (5+10), respectively. The unextractable polymeric protein (UPP) and glutenin macropolymer (GMP) content, gluten index, dough development time, stability time, and farinograph quality number of four NILs all ranked as 5+10 > 3+12 > 2+12/4+12, such as the gluten index ranked as 5+10(44.88%) > 3+12(40.07%) > 2+12(37.46%)/4+12(35.85%); however, their contributions to the quality of CSB were ranked as 3+12 > 5+10 > 2+12/4+12, such as the specific volume ranked as 3+12(2.64 mL/g) > 5+10(2.49 mL/g) > 2+12(2.36 mL/g)/4+12(2.35 mL/g), which indicated that a suitable gluten strength (3+12) was crucial to making high-quality CSB. In addition, subunits 4+12 had a similar quality performance to low-quality subunits 2+12. All these findings suggested that, except for the acknowledged high-quality subunits 5+10, the introduction of 3+12 at the Glu-D1 locus is an efficient way for quality improvement of gluten as well as CSB.

Deep learning for multi-type infectious keratitis diagnosis: A nationwide, cross-sectional, multicenter study.

The main cause of corneal blindness worldwide is keratitis, especially the infectious form caused by bacteria, fungi, viruses, and Acanthamoeba. The key to effective management of infectious keratitis hinges on prompt and precise diagnosis. Nevertheless, the current gold standard, such as cultures of corneal scrapings, remains time-consuming and frequently yields false-negative results. Here, using 23,055 slit-lamp images collected from 12 clinical centers nationwide, this study constructed a clinically feasible deep learning system, DeepIK, that could emulate the diagnostic process of a human expert to identify and differentiate bacterial, fungal, viral, amebic, and noninfectious keratitis. DeepIK exhibited remarkable performance in internal, external, and prospective datasets (all areas under the receiver operating characteristic curves > 0.96) and outperformed three other state-of-the-art algorithms (DenseNet121, InceptionResNetV2, and Swin-Transformer). Our study indicates that DeepIK possesses the capability to assist ophthalmologists in accurately and swiftly identifying various infectious keratitis types from slit-lamp images, thereby facilitating timely and targeted treatment.

Identification of the immune-associated characteristics and predictive biomarkers of keratoconus based on single-cell RNA-sequencing and bulk RNA-sequencing.

Background: Whether keratoconus (KC) is an inflammatory disease is currently debated. Hence, we aimed to investigate the immune-related features of KC based on single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) data. Methods: scRNA-seq data were obtained from the Genome Sequence Archive (GSA), bulk RNA-seq data were obtained from the Gene Expression Omnibus (GEO), and immune-associated genes(IAGs) were obtained from the ImmPort database. Cell clusters of KC were annotated, and different cell clusters were then selected. The IAG score of each cell was calculated using the AUCell package. Three bulk RNA-seq datasets were merged and used to identify the differentially expressed genes (DEGs), biological functions, and immune characteristics. Weighted gene coexpression network analysis (WGCNA) was used to select the IAG score-related hub genes. Based on scRNA-seq and bulk RNA-seq analyses, three machine learning algorithms, including random forest (RF), support vector machine (SVM), and least absolute shrinkage and selection operator (LASSO) regression analysis, were used to identify potential prognostic markers for KC. A predictive nomogram was developed based on prognostic markers. Results: Six cell clusters were identified in KC, and decreased corneal stromal cell-5 (CSC-5) and increased CSC-6 were found in KC. CSC and immune cell clusters had the highest IAG scores. The bulk RNA-seq analysis identified 1362 DEGs (553 upregulated and 809 downregulated) in KC. We found different immune cell populations and differentially expressed cytokines in KC. More than three key IAG score-related modules and 367 genes were identified. By integrating the scRNA-seq and bulk RNA-seq analyses, 250 IAGs were selected and then incorporated into three machine learning models, and 10 IAGs (CEP112, FYN, IFITM1, IGFBP5, LPIN2, MAP1B, RNASE1, RUNX3, SMIM10, and SRGN) were identified as potential prognostic genes that were significantly associated with cytokine and matrix metalloproteinase(MMP)1-14 expression. Finally, a predictive nomogram was constructed and validated. Conclusion: Taken together, our results identified CSCs and immune cell clusters that may play a key role during KC progression by regulating immunological features and maintaining cell stability.