Conserved methylation signatures associate with the tumor immune microenvironment and immunotherapy response.

BACKGROUND: Aberrant DNA methylation is a major characteristic of cancer genomes. It remains unclear which biological processes determine epigenetic reprogramming and how these processes influence the variants in the cancer methylome, which can further impact cancer phenotypes. METHODS: We performed pairwise permutations of 381,900 loci in 569 paired DNA methylation profiles of cancer tissue and matched normal tissue from The Cancer Genome Atlas (TCGA) and defined conserved differentially methylated positions (DMPs) based on the resulting null distribution. Then, we derived independent methylation signatures from 2,465 cancer-only methylation profiles from the TCGA and 241 cell line-based methylation profiles from the Genomics of Drug Sensitivity in Cancer (GDSC) cohort using nonnegative matrix factorization (NMF). We correlated DNA methylation signatures with various clinical and biological features, including age, survival, cancer stage, tumor immune microenvironment factors, and immunotherapy response. We inferred the determinant genes of these methylation signatures by integrating genomic and transcriptomic data and evaluated the impact of these signatures on cancer phenotypes in independent bulk and single-cell RNA/methylome cohorts. RESULTS: We identified 7,364 differentially methylated positions (2,969 Hyper-DMPs and 4,395 Hypo-DMPs) in nine cancer types from the TCGA. We subsequently retrieved three highly conserved, independent methylation signatures (Hyper-MS1, Hypo-MS1, and Hypo-MS4) from cancer tissues and cell lines based on these Hyper and Hypo-DMPs. Our data suggested that Hypo-MS4 activity predicts poor survival and is associated with immunotherapy response and distant tumor metastasis, and Hypo-MS4 activity is related to TP53 mutation and FOXA1 binding specificity. In addition, we demonstrated a correlation between the activities of Hypo-MS4 in cancer cells and the fractions of regulatory CD4 + T cells with the expression levels of immunological genes in the tumor immune microenvironment. CONCLUSIONS: Our findings demonstrated that the methylation signatures of distinct biological processes are associated with immune activity in the cancer microenvironment and predict immunotherapy response.

A CT-based radiomics nomogram for predicting histologic grade and outcome in chondrosarcoma.

OBJECTIVE: The preoperative identification of tumor grade in chondrosarcoma (CS) is crucial for devising effective treatment strategies and predicting outcomes. The study aims to build and validate a CT-based radiomics nomogram (RN) for the preoperative identification of tumor grade in CS, and to evaluate the correlation between the RN-predicted tumor grade and postoperative outcome. METHODS: A total of 196 patients (139 in the training cohort and 57 in the external validation cohort) were derived from three different centers. A clinical model, radiomics signature (RS) and RN (which combines significant clinical factors and RS) were developed and validated to assess their ability to distinguish low-grade from high-grade CS with area under the curve (AUC). Additionally, Kaplan-Meier survival analysis was applied to examine the association between RN-predicted tumor grade and recurrence-free survival (RFS) of CS. The predictive accuracy of the RN was evaluated using Harrell's concordance index (C-index), hazard ratio (HR) and AUC. RESULTS: Size, endosteal scalloping and active periostitis were selected to build the clinical model. Three radiomics features, based on CT images, were selected to construct the RS. Both the RN (AUC, 0.842) and RS (AUC, 0.835) were superior to the clinical model (AUC, 0.776) in the validation set (P = 0.003, 0.040, respectively). A correlation between Nomogram score (Nomo-score, derived from RN) and RFS was observed through Kaplan-Meier survival analysis in the training and test cohorts (log-rank P < 0.050). Patients with high Nomo-score tumors were 2.669 times more likely to suffer recurrence than those with low Nomo-score tumors (HR, 2.669, P < 0.001). CONCLUSIONS: The CT-based RN performed well in predicting both the histologic grade and outcome of CS.

Antisolvent precipitation for the synergistic preparation of ultrafine particles of nobiletin under ultrasonication-homogenization and evaluation of the inhibitory effects of α-glucosidase and porcine pancreatic lipase in vitro.

To further enhance the application of nobiletin (an important active ingredient in Citrus fruits), we used ultrasonic homogenization-assisted antisolvent precipitation to create ultrafine particles of nobiletin (UPN). DMSO was used as the solvent, and deionized water was used as the antisolvent. When ultrasonication (670 W) and homogenization (16000 r/min) were synergistic, the solution concentration was 57 mg/mL, and the minimum particle size of UPN was 521.02 nm. The UPN samples outperformed the RN samples in terms of the inhibition of porcine pancreatic lipase, which was inhibited (by 500 mg/mL) by 68.41 % in the raw sample, 90.34 % in the ultrafine sample, and 83.59 % in the positive control, according to the data. Fourier transform infrared spectroscopy analysis revealed no chemical changes in the samples before or after preparation. However, the crystallinity of the processed ultrafine nobiletin particles decreased. Thus, this work offers significant relevance for applications in the realm of food chemistry and indirectly illustrates the expanded application potential of nobiletin.

The dysfunction of CD8+ T cells triggered by endometriotic stromal cells promotes the immune survival of endometriosis.

Endometriosis is defined as an oestrogen-dependent and inflammatory gynaecological disease of which the pathogenesis remains unclear. This study aimed to investigate the cellular heterogeneity and reveal the effect of CD8+ T cells on the progress of endometriosis. Three ovarian endometriosis patients were collected, and single-cell RNA sequencing (scRNA-seq) progressed and delineated the cellular landscape of endometriosis containing five cell clusters. The endometrial cells (EMCs) were the major component, of which the mesenchymal cells were preponderant and characterized with increased inflammation and oestrogen synthesis in endometriosis. The proportion of T cells, mainly CD8+ T cells rather than CD4+, was reduced in endometriotic lesions, and the cytokines and cytotoxicity of ectopic T cells were depressed. CD8+ T cells depressed the proliferation of ESCs through inhibiting CDK1/CCNB1 pathway to arrest the cell cycle and triggered inflammation through activating STAT1 pathway. Correspondingly, the coculture with ESCs resulted in the dysfunction of CD8+ T cells through upregulating STAT1/PDCD1 pathway and glycolysis-promoted metabolism reprogramming. The endometriotic lesions were larger in nude mouse models with T-cell deficiency than the normal mouse models. The inhibition of T cells via CD90.2 or CD8A antibody increased the endometriotic lesions in mouse models, and the supplement of T cells to nude mouse models diminished the lesion sizes. In conclusion, this study revealed the global cellular variation of endometriosis among which the cellular count and physiology of EMCs and T cells were significantly changed. The depressed cytotoxicity and aberrant metabolism of CD8+ T cells were induced by ESCs with the activation of STAT1/PDCD1 pathway resulting in immune survival to promote endometriosis.

Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues.

Expression quantitative trait loci (eQTLs) are used to inform the mechanisms of transcriptional regulation in eukaryotic cells. However, the specificity of genome-wide eQTL identification is limited by stringent control for false discoveries. Here, we described a method based on the non-homogeneous Poisson process to identify 125 489 regions with highly frequent, multiple eQTL associations, or 'eQTL-hotspots', from the public database of 59 human tissues or cell types. We stratified the eQTL-hotspots into two classes with their distinct sequence and epigenomic characteristics. Based on these classifications, we developed a machine-learning model, E-SpotFinder, for augmented discovery of tissue- or cell-type-specific eQTL-hotspots. We applied this model to 36 tissues or cell types. Using augmented eQTL-hotspots, we recovered 655 402 eSNPs and reconstructed a comprehensive regulatory network of 2 725 380 cis-interactions among eQTL-hotspots. We further identified 52 012 modules representing transcriptional programs with unique functional backgrounds. In summary, our study provided a framework of epigenome-augmented eQTL analysis and thereby constructed comprehensive genome-wide networks of cis-regulations across diverse human tissues or cell types.

CDSKNNXMBD: a novel clustering framework for large-scale single-cell data based on a stable graph structure.

BACKGROUND: Accurate and efficient cell grouping is essential for analyzing single-cell transcriptome sequencing (scRNA-seq) data. However, the existing clustering techniques often struggle to provide timely and accurate cell type groupings when dealing with datasets with large-scale or imbalanced cell types. Therefore, there is a need for improved methods that can handle the increasing size of scRNA-seq datasets while maintaining high accuracy and efficiency. METHODS: We propose CDSKNNXMBD (Community Detection based on a Stable K-Nearest Neighbor Graph Structure), a novel single-cell clustering framework integrating partition clustering algorithm and community detection algorithm, which achieves accurate and fast cell type grouping by finding a stable graph structure. RESULTS: We evaluated the effectiveness of our approach by analyzing 15 tissues from the human fetal atlas. Compared to existing methods, CDSKNN effectively counteracts the high imbalance in single-cell data, enabling effective clustering. Furthermore, we conducted comparisons across multiple single-cell datasets from different studies and sequencing techniques. CDSKNN is of high applicability and robustness, and capable of balancing the complexities of across diverse types of data. Most importantly, CDSKNN exhibits higher operational efficiency on datasets at the million-cell scale, requiring an average of only 6.33 min for clustering 1.46 million single cells, saving 33.3% to 99% of running time compared to those of existing methods. CONCLUSIONS: The CDSKNN is a flexible, resilient, and promising clustering tool that is particularly suitable for clustering imbalanced data and demonstrates high efficiency on large-scale scRNA-seq datasets.

Ct-based intratumoral and peritumoral radiomics for predicting prognosis in osteosarcoma: A multicenter study.

PURPOSE: To evaluate the performance of CT-based intratumoral, peritumoral and combined radiomics signatures in predicting prognosis in patients with osteosarcoma. METHODS: The data of 202 patients (training cohort:102, testing cohort:100) with osteosarcoma admitted to the two hospitals from August 2008 to February 2022 were retrospectively analyzed. Progression free survival (PFS) and overall survival (OS) were used as the end points. The radiomics features were extracted from CT images, three radiomics signatures（RSintratumoral, RSperitumoral, RScombined）were constructed based on intratumoral, peritumoral and combined radiomics features, respectively, and the radiomics score (Rad-score) were calculated. Kaplan-Meier survival analysis was used to evaluate the relationship between the Rad-score with PFS and OS, the Harrell's concordance index (C-index) was used to evaluate the predictive performance of the radiomics signatures. RESULTS: Finally, 8, 6, and 21 features were selected for the establishment of RSintratumoral, RSperitumoral, and RScombined, respectively. Kaplan-Meier survival analysis confirmed that the Rad-scores of the three RSs were significantly correlated with the PFS and OS of patients with osteosarcoma. Among the three radiomics signatures, RScombined had better predictive performance, the C-index of PSF prediction was 0.833 in the training cohort and 0.814 in the testing cohort, the C-index of OS prediction was 0.796 in the training cohort and 0.764 in the testing cohort. CONCLUSIONS: CT-based intratumoral, peritumoral and combined radiomics signatures can predict the prognosis of patients with osteosarcoma, which may assist in individualized treatment and improving the prognosis of osteosarcoma patients.

Whole-genome shotgun sequencing unravels the influence of environmental microbial co-infections on the treatment efficacy for severe pediatric infectious diseases.

Background: The microbiome plays a pivotal role in mediating immune deviation during the development of early-life viral infections. Recurrent infections in children are considered a risk factor for disease development. This study delves into the metagenomics of the microbiome in children suffering from severe infections, seeking to identify potential sources of these infections. Aims: The aim of this study was to identify the specific microorganisms and factors that significantly influence the treatment duration in patients suffering from severe infections. We sought to understand how these microbial communities and other variables may affect the treatment duration and the use of antibiotics of these patients with severe infections. Method: Whole-genome shotgun sequencing was conducted on samples collected from children aged 0-14 years with severe infections, admitted to the Pediatrics Department of Xiamen First Hospital. The Kraken2 algorithm was used for taxonomic identification from sequence reads, and linear mixed models were employed to identify significant microorganisms influencing treatment duration. Colwellia, Cryptococcus, and Citrobacter were found to significantly correlate with the duration of clinical treatment. Further analysis using propensity score matching (PSM) and rank-sum test identified clinical indicators significantly associated with the presence of these microorganisms. Results: Using a linear mixed model after removed the outliers, we identified that the abundance of Colwellia, Cryptococcus, and Citrobacter significantly influences the treatment duration. The presence of these microorganisms is associated with a longer treatment duration for patients. Furthermore, these microorganisms were found to impact various clinical measures. Notably, an increase in hospitalization durations and medication costs was observed in patients with these microorganisms. In patients with Colwellia, Cryptococcus, and Citrobacter, we discover significant differences in platelets levels. We also find that in patients with Cryptococcus, white blood cells, hemoglobin, and neutrophils levels are lower. Conclusion: These findings suggest that Colwellia, Cryptococcus, and Citrobacter, particularly Cryptococcus, could potentially contribute to the severity of infections observed in this cohort, possibly as co-infections. These microorganisms warrant further investigation into their pathogenic roles and mechanisms of action, as their presence in combination with disease-causing organisms may have a synergistic effect on disease severity. Understanding the interplay between these microorganisms and pathogenic agents could provide valuable insights into the complex nature of severe pediatric infections and guide the development of targeted therapeutic strategies.

Prenatal EGCG consumption impacts hepatic glycogen synthesis and lipid metabolism in adult mice.

In this study, the impact of prenatal exposure to Epigallocatechin gallate (EGCG) on the liver of adult offspring mice was investigated. While EGCG is known for its health benefits, its effects of prenatal exposure on the liver remain unclear. Pregnant C57BL/6 J mice were exposed to 1 mg/kg of EGCG for 16 days to assess hepatotoxicity effects of adult offspring. Transcriptomics and metabolomics were employed to elucidate the hepatotoxicity mechanisms. The findings revealed that prenatal EGCG exposure led to a decrease in liver somatic index, enhanced inflammatory responses and disrupted liver function through increased glycogen accumulation in adult mice. The integrated omics analysis revealed significant alterations in key pathways involved in liver glucose lipid metabolism, such as gluconeogenesis, dysregulation of insulin signaling, and induction of liver inflammation. Furthermore, the study found a negative correlation between the promoter methylation levels of Ppara and their mRNA levels, suggesting that EGCG could reduce hepatic lipid content through epigenetic modifications. The findings suggest that prenatal EGCG exposure can have detrimental impacts on the liver among adult individuals and emphasize the need for a comprehensive evaluation of the potential risks associated with EGCG consumption during pregnancy.

Intratumoral and peritumoral CT radiomics in predicting prognosis in patients with chondrosarcoma: a multicenter study.

OBJECTIVE: To evaluate the efficacy of the CT-based intratumoral, peritumoral, and combined radiomics signatures in predicting progression-free survival (PFS) of patients with chondrosarcoma (CS). METHODS: In this study, patients diagnosed with CS between January 2009 and January 2022 were retrospectively screened, and 214 patients with CS from two centers were respectively enrolled into the training cohorts (institution 1, n = 113) and test cohorts (institution 2, n = 101). The intratumoral and peritumoral radiomics features were extracted from CT images. The intratumoral, peritumoral, and combined radiomics signatures were constructed respectively, and their radiomics scores (Rad-score) were calculated. The performance of intratumoral, peritumoral, and combined radiomics signatures in PFS prediction in patients with CS was evaluated by C-index, time-dependent area under the receiver operating characteristics curve (time-AUC), and time-dependent C-index (time C-index). RESULTS: Eleven, 7, and 16 features were used to construct the intratumoral, peritumoral, and combined radiomics signatures, respectively. The combined radiomics signature showed the best prediction ability in the training cohort (C-index, 0.835; 95%; confidence interval [CI], 0.764-0.905) and the test cohort (C-index, 0.800; 95% CI, 0.681-0.920). Time-AUC and time C-index showed that the combined signature outperformed the intratumoral and peritumoral radiomics signatures in the prediction of PFS. CONCLUSION: The CT-based combined signature incorporating intratumoral and peritumoral radiomics features can predict PFS in patients with CS, which might assist clinicians in selecting individualized surveillance and treatment plans for CS patients. CRITICAL RELEVANCE STATEMENT: Develop and validate CT-based intratumoral, peritumoral, and combined radiomics signatures to evaluate the efficacy in predicting prognosis of patients with CS. KEY POINTS: • Reliable prognostic models for preoperative chondrosarcoma are lacking. • Combined radiomics signature incorporating intratumoral and peritumoral features can predict progression-free survival in patients with chondrosarcoma. • Combined radiomics signature may facilitate individualized stratification and management of patients with chondrosarcoma.

Unveiling the potent effect of vitamin D: harnessing Nrf2/HO-1 signaling pathways as molecular targets to alleviate urban particulate matter-induced asthma inflammation.

BACKGROUND: Asthma is the most common allergic disease characterized by an inflammatory response in the airways. Mechanismly, urban particulate matter (PM) is the most widely air pollutant associated with increased asthma morbidity and airway inflammation. Current research found that vitamin D is an essential vitamin with anti-inflammatory, antioxidant and other medical efficacy. Inadequate or deficient vitamin D often leads to the pathogenesis and stability of asthma. NGF exacerbates airway inflammation in asthma by promoting smooth muscle cell proliferation and inducing the Th2 immune response. Activation of the Nrf2/HO-1 signaling pathway can exert a protective effect on the inflammatory response in bronchial asthma. However, the specific mechanism of this pathway in PM-involved asthmatic airway smooth muscle cells remains unclear. METHODS: Mice were sensitized and challenged with Ovalbumin (OVA) to establish an asthma model. They were then exposed to either PM, vitamin D or a combination of both, and inflammatory responses were observed. Including, acetylcholine stimulation at different concentrations measured airway hyperresponsiveness in mice. Bronchoalveolar lavage fluid (BALF) and serum were collected for TNF-α, IL-1ß, IL-6, and Nerve growth factor (NGF) analysis. Additionally, lung tissues underwent histopathological examination to observe alveolar structure and inflammatory cell infiltration. Specific ELISA kits were utilized to determine the levels of the inflammatory factors TNF-α, IL-1ß, IL-6, and Nerve growth factor (NGF). Nrf2/HO-1 signaling pathways were examined by western blot analysis. Meanwhile, we constructed a cell system with low HO-1 expression by lentiviral transfection of airway smooth muscle cells. The changes of Nrf2, HO-1, and NGF were observed after the treatment of OVA, PM, and Vit D were given. RESULTS: The in vivo results showed that vitamin D significantly alleviated pathological changes in lung tissue of PM-exposed mice models. Mechanismly, vitamin D decreased substantial inflammatory cell infiltration in lung tissue, as well as the number of inflammatory cells in BALF. Furthermore, vitamin D reduced the heightened inflammatory factors including of TNF-α, IL-1ß, IL-6, and NGF caused by PM exposure, and triggered the activity of nucleus Nrf2 and HO-1 in PM-exposed asthmatic mice. Notably, knockdown HO-1 weakens the Vitamin D- mediated inhibition to pollution toxicity in asthma. Importantly, in vitro experiments on OVA-stimulated mice airway smooth muscle cells, the results showed that OVA and PM, respectively, reduced Nrf2/HO-1 and increased NGF's expression, while vitamin D reversed the process. And in the HO-1 knockdown cell line of Lenti-si-HO-1 ASMCs, OVA and PM reduced Nrf2's expression, while HO-1 and NGF's expression were unchanged. CONCLUSIONS: The above results demastrate that vitamin D downregulated the inflammatory response and the expression of NGF by regulating the Nrf2/HO-1 signaling pathways in airway smooth muscle cells, thereby showing potent anti-inflammatory activity in asthma.

Verteporfin regulates corneal neovascularization through inhibition of YAP protein activation.

Corneal neovascularization (CNV) is a vision-threatening disease that is becoming a growing public health concern. While Yes-associated protein (YAP) plays a critical role in neovascular disease and allow for the sprouting angiogenesis. Verteporfin (VP) is a classical inhibitor of the YAP-TEAD complex, which is used for clinical treatment of neovascular macular degeneration through photodynamic therapy. The purpose of this study is to explore the effect of verteporfin (VP) on the inhibition of CNV and its potential mechanism. Rat CNV model were established by suturing in the central cornea and randomly divided into three groups (control, CNV and VP group). Neovascularization was observed by slit lamp to extend along the corneal limbus to the suture line. RNA-sequencing was used to reveal the related pathways on the CNV and the results revealed the vasculature development process and genes related with angiogenesis in CNV. In CNV group, we detected the nuclear translocation of YAP and the expression of CD31 in corneal neovascular endothelial cells through immunofluorescence. After the application of VP, the proliferation, migration and the tube formation of HUVECs were significantly inhibited. Furthermore, VP showed the CNV inhibition by tail vein injection without photoactivation. Then we found that the expression of phosphorylated YAP significantly decreased, and its downstream target protein connective tissue growth factor (CTGF) increased in the CNV group, while the expression was just opposite in other groups. Besides, both the expression of vascular endothelial growth factor receptor 2 (VEGFR2) and cofilin significantly increased in CNV group, and decreased after VP treatment. Therefore, we conclude that Verteporfin could significantly inhibited the CNV without photoactivation by regulating the activation of YAP.

Facile Fabrication of Flexible and High-Performing Thermoelectrics by Direct Laser Printing on Plastic Foil.

The emerging fields of wearables and the Internet of Things introduce the need for electronics and power sources with unconventional form factors: large area, customizable shape, and flexibility. Thermoelectric (TE) generators can power those systems by converting abundant waste heat into electricity, whereas the versatility of additive manufacturing suits heterogeneous form factors. Here, additive manufacturing of high-performing flexible TEs is proposed. Maskless and large-area patterning of Bi2Te3-based films is performed by laser powder bed fusion directly on plastic foil. Mechanical interlocking allows simultaneous patterning, sintering, and attachment of the films to the substrate without using organic binders that jeopardize the final performance. Material waste could be minimized by recycling the unexposed powder. The particular microstructure of the laser-printed material renders the-otherwise brittle-Bi2Te3 films highly flexible despite their high thickness. The films survive 500 extreme-bending cycles to a 0.76 mm radius. Power factors above 1500 µW m-1K-2 and a record-low sheet resistance for flexible TEs of 0.4 Ω sq-1 are achieved, leading to unprecedented potential for power generation. This versatile fabrication route enables innovative implementations, such as cuttable arrays adapting to specific applications in self-powered sensing, and energy harvesting from unusual scenarios like human skin and curved hot surfaces.

Multi-band all-silicon TM-pass polarizer based on one-dimensional photonic crystals nanohole array.

We propose an on-chip transverse magnetic (TM)-pass polarizer utilizing one-dimensional photonic crystals for multi-band operation. The TE0 modes in the 1550/2000nm wave band are suppressed by carefully selecting the pitch lengths of the nanoholes, leveraging the bandgap of the nanohole array. Conversely, the TM0 modes remain almost unaffected. The TM-pass polarizer employs a single-etched design on a standard 220 nm SOI platform and has a compact length of ∼ 17.9 µm. The simulated bandwidths (BWs) for polarization extinction ratios (PERs) > 20 dB and > 25 dB are about 210 nm and 195 nm for the 1550 nm wave band, and 265 nm and 240 nm for the 2000nm wave band. Moreover, the insertion losses (ILs) are ∼ 0.5/0.3 dB at wavelengths of 1550/2000nm, respectively. For the fabricated device, the measured BWs for PER > 20 dB and > 25 dB are evaluated to be larger than 100 nm for both 1550/2000nm wave bands. The measured ILs are 1/0.8 dB at wavelengths of 1550/2000nm. This straightforward and compatible design opens possibilities for the development of practical multi-band silicon photonic integrated circuits.

The transcription factor Zeb1 controls homeostasis and function of type 1 conventional dendritic cells.

Type 1 conventional dendritic cells (cDC1) are the most efficient cross-presenting cells that induce protective cytotoxic T cell response. However, the regulation of their homeostasis and function is incompletely understood. Here we observe a selective reduction of splenic cDC1 accompanied by excessive cell death in mice with Zeb1 deficiency in dendritic cells, rendering the mice more resistant to Listeria infection. Additionally, cDC1 from other sources of Zeb1-deficient mice display impaired cross-presentation of exogenous antigens, compromising antitumor CD8+ T cell responses. Mechanistically, Zeb1 represses the expression of microRNA-96/182 that target Cybb mRNA of NADPH oxidase Nox2, and consequently facilitates reactive-oxygen-species-dependent rupture of phagosomal membrane to allow antigen export to the cytosol. Cybb re-expression in Zeb1-deficient cDC1 fully restores the defective cross-presentation while microRNA-96/182 overexpression in Zeb1-sufficient cDC1 inhibits cross-presentation. Therefore, our results identify a Zeb1-microRNA-96/182-Cybb pathway that controls cross-presentation in cDC1 and uncover an essential role of Zeb1 in cDC1 homeostasis.

Unsupervised Learning Based on Meibography Enables Subtyping of Dry Eye Disease and Reveals Ocular Surface Features.

Purpose: This study aimed to establish an image-based classification that can reveal the clinical characteristics of patients with dry eye using unsupervised learning methods. Methods: In this study, we analyzed 82,236 meibography images from 20,559 subjects. Using the SimCLR neural network, the images were categorized. Data for each patient were averaged and subjected to mini-batch k-means clustering, and validated through consensus clustering. Statistical metrics determined optimal category numbers. Using a UNet model, images were segmented to identify meibomian gland (MG) areas. Clinical features were assessed, including tear breakup time (BUT), tear meniscus height (TMH), and gland atrophy. A thorough ocular surface evaluation was conducted on 280 cooperative patients. Results: SimCLR neural network achieved clustering patients with dry eye into six image-based subtypes. Patients in different subtypes harbored significantly different noninvasive BUT, significantly correlated with TMH. Subtypes 1 and 5 had the most severe MG atrophy. Subtype 2 had the highest corneal fluorescent staining (CFS). Subtype 4 had the lowest TMH, whereas subtype 5 had the highest. Subtypes 3 and 6 had the largest MG areas, and the upper MG areas of a person's bilateral eyes were highly correlated. Image-based subtypes are related to meibum quality, CFS, and morphological characteristics of MG. Conclusions: In this study, we developed an unsupervised neural network model to cluster patients with dry eye into image-based subtypes using meibography images. We annotated these subtypes with functional and morphological clinical characteristics.

The Use of Iron-Doped Anatase TiO2 Nanofibers for Enhanced Photocatalytic Fenton-like Reaction to Degrade Tylosin.

The removal of antibiotics from wastewater to prevent their environmental accumulation is significant for human health and ecosystems. Herein, iron (Fe)-atom-doped anatase TiO2 nanofibers (Fe-TNs) were manufactured for the photocatalytic Fenton-like decomposition of tylosin (TYL) under LED illumination. Compared with the pristine TiO2 nanofibers (TNs), the optimized Fe-TNs exhibited improved visible-light-driven photocatalytic Fenton-like activity with a TYL degradation efficiency of 98.5% within 4 h. The effective TYL degradation could be attributed to the expanded optical light absorption and accelerated separation and migration of photogenerated electrons and holes after the introduction of Fe. The photogenerated electrons were highly conducive to the generation of active SO4•- radicals as they facilitated Fe(III)/Fe(II) cycles, and to oxidizing TYL. Moreover, the holes could be involved in TYL degradation. Thus, a significant enhancement in TYL degradation could be achieved. This research verifies the use of iron-doped anatase nanofibers as an effective method to synthesize novel photocatalytic Fenton-like catalysts through surface engineering for wastewater remediation.

High-speed mid-infrared graphene electro-optical modulator based on suspended germanium slot waveguides.

The mid-infrared (MIR) region is attracting increasing interest for on-chip synchronous detection and free-space optical (FSO) communications. For such applications, a high-performance electro-optical modulator is a crucial component. In this regard, we propose and investigate a graphene-based electro-absorption modulator (EAM) and microring modulator (MRM) using the suspended germanium waveguide platform. The modulators are designed for the second atmospheric window (8 to 12 µm). The incorporation of double-layer graphene on the suspended slot waveguide structure allows for the significant enhancement of light-graphene interaction, theoretically achieving a 3-dB bandwidth as high as 78 GHz. The EAM shows a calculated modulation depth of 0.022-0.045 dB/µm for the whole operation wavelength range. The MRM exhibits a calculated extinction ratio as high as 68.9 dB and a modulation efficiency of 0.59 V·cm around 9 µm. These modulators hold promise for constructing high-speed FSO communication and on-chip spectroscopic detection systems in the MIR atmospheric window.

Efficacy of corneal curvature on the accuracy of 8 intraocular lens power calculation formulas in 302 highly myopic eyes.

PURPOSE: To investigate the effect of corneal curvature (K) on the accuracy of 8 intraocular lens formulas in highly myopic eyes. SETTING: Eye Hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, China. DESIGN: Retrospective consecutive case series. METHODS: 302 eyes (302 patients) were analyzed in subgroups based on the K value. The mean refractive error, mean absolute error (MAE), median absolute error (MedAE), root-mean-square absolute prediction error (RMSAE) and proportions of eyes within ±0.25 diopter (D), ±0.50 D, ±0.75 D, ±1.00 D were statistical analyzed. RESULTS: Emmetropia Verifying Optical (EVO) 2.0, Kane, and Radial Basis Function (RBF) 3.0 had the lower MAE (≤0.28) and RMSAE (≤0.348) and highest percentage of eyes within ±0.50 D (≥83.58%) in the flat (K ≤ 43 D) and steep K (K > 45 D) groups. Hoffer QST had the lowest MedAE (0.19), RMSAE (0.351) and the highest percentage of eyes within ±0.50 D (82.98%) in the normal K group (43 < K ≤ 45 D). When axial length (AL) ≤28 mm, all formulas showed close RMSAE values (0.322 to 0.373) in flat K group. When AL >28 mm, RBF 3.0 achieved the lowest MAE (≤0.24), MedAE (≤0.17) and RMSAE (≤0.337) across all subgroups. CONCLUSIONS: EVO 2.0, Kane, and RBF 3.0 were the most accurate in highly myopic eyes with a flat or steep K. Hoffer QST is recommended for long eyes with normal K values. RBF 3.0 showed the highest accuracy when AL >28 mm, independent of corneal curvature.

Gut microbiome interacts with pregnancy hormone metabolites in gestational diabetes mellitus.

Introduction: Change in the composition of intestinal microbiota is associated with metabolic disorders such as gestational diabetes mellitus (GDM). Methods: To understand how the microbiota impacts the development of gestational diabetes mellitus, we profiled the intestinal microbiome of 54 pregnant women, including 27 GDM subjects, by employing 16S rRNA gene sequencing. Additionally, we conducted targeted metabolomics assays to validate the identified pathways with overrepresented metabolites. Results: We evaluated the patterns of changing abundances of operational taxonomic units (OTU) between GDM and the healthy counterparts over three timepoints. Based on the significant OTUs, we inferred 132 significantly altered metabolic pathways in GDM. And identified two overrepresented metabolites of pregnancy hormone, butyrate and mevalonate, as potential intermediary metabolites of intestinal microbiota in GDM. Finally, we validated the impacts of the intestinal microbiota on GDM by demonstrating consistent changes of the serum levels of progesterone, estradiol, butyrate, and mevalonate in an independent cohort. Discussion: Our findings confirm that alterations in the microbiota play a role in the development of GDM by impacting the metabolism of pregnancy hormones. This provides a novel perspective on the pathogenesis of GDM and introduces potential biomarkers that can be used for early diagnosis and prevention of the disease.