Enhanced Optic Nerve Expansion and Altered Ultrastructure of Elastic Fibers Induced by Lysyl Oxidase Inhibition in a Mouse Model of Marfan Syndrome.

Two major constituents of exfoliation material, fibrillin-1 and lysyl oxidase-like 1 (encoded by FBN1 and LOXL1), are implicated in exfoliation glaucoma, yet their individual contributions to ocular phenotype are minor. To test the hypothesis that a combination of FBN1 mutation and LOXL1 deficiency exacerbates ocular phenotypes, the pan-lysyl oxidase inhibitor ß-aminopropionitrile (BAPN) was used to treat adult wild-type (WT) mice and mice heterozygous for a missense mutation in Fbn1 (Fbn1C1041G/+) for 8 weeks and their eyes were examined. Although intraocular pressure did not change and exfoliation material was not detected in the eyes, BAPN treatment worsened optic nerve and axon expansion in Fbn1C1041G/+ mice, an early sign of axonal damage in rodent models of glaucoma. Disruption of elastic fibers was detected only in Fbn1C1041G/+ mice, which increased with BAPN treatment, as shown by histologic and immunohistochemical staining of the optic nerve pia mater. Transmission electron microscopy showed that Fbn1C1041G/+ mice had fewer microfibrils, smaller elastin cores, and a lower density of elastic fibers compared with WT mice in control groups. BAPN treatment led to elastin core expansion in both WT and Fbn1C1041G/+ mice, but an increase in the density of elastic fiber was confined to Fbn1C1041G/+ mice. LOX inhibition had a stronger effect on optic nerve and elastic fiber parameters in the context of Fbn1 mutation, indicating the Marfan mouse model with LOX inhibition warrants further investigation for exfoliation glaucoma pathogenesis.

Study on the correlation between serum indole-3-propionic acid levels and the progression and prognosis of acute ischemic stroke.

OBJECTIVE: This study aimed to explore the correlation between the serum level of indole-3-propionic acid (IPA) and the progression and prognosis of acute cerebral infarction (ACI). METHODS: This study enrolled 197 patients with ACI, and 53 participants from a community-based stroke screening program during the same period were included as the control group. The patients with ACI were divided into quartiles of serum IPA. A logistic regression model was used for comparison. Receiver operating characteristic (ROC) curves were drawn to evaluate the predictive value of the IPA. RESULTS: Compared with the healthy control group, the ACI group had lower serum IPA (P < 0.05). The serum IPA was an independent factor for acute ischemic stroke (OR=0.992, 95% CI: 0.984-0.999, P=0.035). The serum IPA was lower in patients with progressive stroke or poor prognosis than in patients with stable stroke or good prognosis (P < 0.05). Patients with ACI with low serum IPA are prone to progression and poor prognosis. The best cutoff value for predicting progression was 193.62 pg/mL (sensitivity, 67.5%; specificity 83.7%), and that for poor prognosis was 193.77 pg/mL (sensitivity, 71.1%; specificity, 72.5%). CONCLUSION: The serum level of IPA was an independent predictor of ACI and had certain clinical value for predicting stroke progression and prognosis in patients with ACI.

External validation of the iScore, ASTRAL score, DRAGON score, and THRIVE score and development of a nomogram to predict outcome in patients with large vessel occlusion-acute ischemic stroke.

OBJECTIVE: This study aimed to validate the iScore, ASTRAL score, DRAGON score, and THRIVE score for assessing large vessel occlusion-acute ischemic stroke (AIS-LVO) and establish a predictive model for AIS-LVO patients that has better performance to guide clinical practice. METHODS: We retrospectively included 439 patients with AIS-LVO and collected baseline data from all of them. External validation of the iScore, ASTRAL score, DRAGON score, and THRIVE score was performed. All variables were compared between groups via univariate analysis, and the results are expressed as ORs and 95 % CIs. Independent variables with P < 0.25 were included in the multivariate logistic analysis, and statistically significant differences (P < 0.05) were identified as risk factors for prognosis in AIS-LVO patients. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive value of our model. RESULTS: Our external validation resulted in an iScore under the curve (AUC) of 0.8475, an ASTRAL AUC of 0.8324, a DRAGON AUC of 0.8196, and a THRIVE AUC of 0.8039. In our research, multivariate Cox regression revealed 8 independent predictors. We used a nomogram to visualize the results of the data analysis. The AUC for the training cohort was 0.8855 (95 % CI, 0.8487-0.9222), and that in the validation cohort was 0.8992 (95 % CI, 0.8496-0. 9488). CONCLUSIONS: In this study, we verified that the above scores have excellent efficacy in predicting the prognosis of AIS-LVO patients. The nomogram we developed was able to predict the prognosis of AIS-LVO more accurately and may contribute to personalized clinical decision-making and treatment for future clinical work.

The Effect of Diabetes Management Shared Care Clinic on Glycated Hemoglobin A1c Compliance and Self-Management Abilities in Patients with Type 2 Diabetes Mellitus.

Objective: We aim to evaluate the impact of diabetes management shared care clinic (DMSCC) on glycated hemoglobin A1c (HbA1c) compliance and self-management abilities in patients with type 2 diabetes mellitus (T2DM). Methods: This study was a prospective cohort study of patients with T2DM participating in the DMSCC. At baseline and after management, the HbA1c levels were measured, the HbA1c compliance rate were calculated, and the Summary of Diabetes Self-Care Activities-6 (SDSCA-6), Diabetes Empowerment Scale-DAWN Short Form (DES-DSF), and Problem Areas in Diabetes Scale-Five-item Short Form (PAID-5) were completed. These pre- and post-management data were compared. Results: A total of 124 eligible patients were enrolled. After the diabetes management of DMSCC, the average HbA1c decreased and the HbA1c compliance rate increased significantly (P < 0.01). SDSCA-6 showed significant improvement in physical activity, glycemic monitoring, smoking (P < 0.01), and taking medication (P < 0.05). DES-DSF suggested a greater willingness to try to effectively treat diabetes (P < 0.05). PAID-5 indicated significant improvement in diabetes-related emotional distress. Conclusion: DMSCC can help patients with T2DM reduce HbA1c, increase HbA1c compliance, improve diabetes self-management behaviors, empowerment, and diabetes-related emotional distress and serve as an effective exploration and practice of diabetes self-management education and support.

Machine Learning-Based Clinical Prediction Models for Acute Ischemic Stroke Based on Serum Xanthine Oxidase Levels.

OBJECTIVE: Early prediction of the onset, progression and prognosis of acute ischemic stroke (AIS) is helpful for treatment decision-making and proactive management. Although several biomarkers have been found to predict the progression and prognosis of AIS, these biomarkers have not been widely used in routine clinical practice. Xanthine oxidase (XO) is a form of xanthine oxidoreductase (XOR), which is widespread in various organs of the human body and plays an important role in redox reactions and ischemia‒reperfusion injury. Our previous studies have shown that serum XO levels on admission have certain clinical predictive value for AIS. The purpose of this study was to utilize serum XO levels and clinical data to establish machine learning models for predicting the onset, progression, and prognosis of AIS. METHODS: We enrolled 328 consecutive patients with AIS and 107 healthy controls from October 2020 to September 2021. Serum XO levels and stroke-related clinical data were collected. We established 5 machine learning models-the logistic regression (LR), support vector machine (SVM), decision tree, random forest, and K-nearest neighbor (KNN) models-to predict the onset, progression, and prognosis of AIS. The area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, negative predictive value, and positive predictive value were used to evaluate the predictive performance of each model. RESULTS: Among the 5 machine learning models predicting AIS onset, the AUROC values of 4 prediction models were over 0.7, while that of the KNN model was lower (AUROC = 0.6708, 95% CI 0.576-0.765). The LR model showed the best AUROC value (AUROC = 0.9586, 95% CI 0.927-0.991). Although the 5 machine learning models showed relatively poor predictive value for the progression of AIS (all AUROCs <0.7), the LR model still showed the highest AUROC value (AUROC = 0.6543, 95% CI 0.453-0.856). We compared the value of 5 machine learning models in predicting the prognosis of AIS, and the LR model showed the best predictive value (AUROC = 0.8124, 95% CI 0.715-0.910). CONCLUSIONS: The tested machine learning models based on serum levels of XO could predict the onset and prognosis of AIS. Among the 5 machine learning models, we found that the LR model showed the best predictive performance. Machine learning algorithms improve accuracy in the early diagnosis of AIS and can be used to make treatment decisions.

Dapagliflozin ameliorates diabetes-induced spermatogenic dysfunction by modulating the adenosine metabolism along the gut microbiota-testis axis.

Male infertility is one of the most common complications of diabetes mellitus (DM). Dapagliflozin is widely used to manage the type II DM. This study aimed to assess the dapagliflozin's effects on the spermatogenesis by administering either dapagliflozin (Dapa) or vehicle (db) to male db/db mice, and using littermate male db/m mice as the control (Con). We further performed the integrative analyses of the cecal shotgun metagenomics, cecal/plasmatic/testicular metabolomics, and testicular proteomics. We found that dapagliflozin treatment significantly alleviated the diabetes-induced spermatogenic dysfunction by improving sperm quality, including the sperm concentration and sperm motility. The overall microbial composition was reshaped in Dapa mice and 13 species (such as Lachnospiraceae bacterium 3-1) were regarded as potential beneficial bacteria. Metabolites exhibited modified profiles, in which adenosine, cAMP, and 2'-deoxyinosine being notably altered in the cecum, plasma, and testis, respectively. Testicular protein expression patterns were similar between the Dapa and Con mice. In vivo results indicated that when compared with db group, dapagliflozin treatment alleviated apoptosis and oxidative stress in testis tissues by down-regulating 2'-deoxyinosine. This was further validated by in vitro experiments using GC-2 cells. Our findings support the potential use of dapagliflozin to prevent the diabetes-induced impaired sperm quality and to treat diabetic male infertility.

A lung disease diagnosis algorithm based on 2D spectral features of ultrasound RF signals.

Lung diseases are commonly diagnosed based on clinical pathological indications criteria and radiological imaging tools (e.g., X-rays and CT). During a pandemic like COVID-19, the use of ultrasound imaging devices has broadened for emergency examinations by taking their unique advantages such as portability, real-time detection, easy operation and no radiation. This provides a rapid, safe, and cost-effective imaging modality for screening lung diseases. However, the current pulmonary ultrasound diagnosis mainly relies on the subjective assessments of sonographers, which has high requirements for the operator's professional ability and clinical experience. In this study, we proposed an objective and quantifiable algorithm for the diagnosis of lung diseases that utilizes two-dimensional (2D) spectral features of ultrasound radiofrequency (RF) signals. The ultrasound data samples consisted of a set of RF signal frames, which were collected by professional sonographers. In each case, a region of interest of uniform size was delineated along the pleural line. The standard deviation curve of the 2D spatial spectrum was calculated and smoothed. A linear fit was applied to the high-frequency segment of the processed data curve, and the slope of the fitted line was defined as the frequency spectrum standard deviation slope (FSSDS). Based on the current data, the method exhibited a superior diagnostic sensitivity of 98% and an accuracy of 91% for the identification of lung diseases. The area under the curve obtained by the current method exceeded the results obtained that interpreted by professional sonographers, which indicated that the current method could provide strong support for the clinical ultrasound diagnosis of lung diseases.

Gut Microbiota-Tryptophan Metabolism-GLP-1 Axis Participates in ß-Cell Regeneration Induced by Dapagliflozin.

Sodium-glucose cotransporter 2 inhibitors, efficacious antidiabetic agents that have cardiovascular and renal benefits, can promote pancreatic ß-cell regeneration in type 2 diabetic mice. However, the underlying mechanism remains unclear. In this study, we aimed to use multiomics to identify the mediators involved in ß-cell regeneration induced by dapagliflozin. We showed that dapagliflozin lowered blood glucose level, upregulated plasma insulin level, and increased islet area in db/db mice. Dapagliflozin reshaped gut microbiota and modulated microbiotic and plasmatic metabolites related to tryptophan metabolism, especially l-tryptophan, in the diabetic mice. Notably, l-tryptophan upregulated the mRNA level of glucagon-like peptide 1 (GLP-1) production-related gene (Gcg and Pcsk1) expression and promoted GLP-1 secretion in cultured mouse intestinal L cells, and it increased the supernatant insulin level in primary human islets, which was eliminated by GPR142 antagonist. Transplant of fecal microbiota from dapagliflozin-treated mice, supplementation of l-tryptophan, or treatment with dapagliflozin upregulated l-tryptophan, GLP-1, and insulin or C-peptide levels and promoted ß-cell regeneration in db/db mice. Addition of exendin 9-39, a GLP-1 receptor (GLP-1R) antagonist, or pancreatic Glp1r knockout diminished these beneficial effects. In summary, treatment with dapagliflozin in type 2 diabetic mice promotes ß-cell regeneration by upregulating GLP-1 production, which is mediated via gut microbiota and tryptophan metabolism.

Candida albicans accelerates atherosclerosis by activating intestinal hypoxia-inducible factor2α signaling.

The gut microbiota is closely linked to atherosclerosis. However, the role of intestinal fungi, essential members of the complex microbial community, in atherosclerosis is poorly understood. Herein, we show that gut fungi dysbiosis is implicated in patients with dyslipidemia, characterized by higher levels of Candida albicans (C. albicans), which are positively correlated with plasma total cholesterol and low-density lipoprotein-cholesterol (LDL-C) levels. Furthermore, C. albicans colonization aggravates atherosclerosis progression in a mouse model of the disease. Through gain- and loss-of-function studies, we show that an intestinal hypoxia-inducible factor 2α (HIF-2α)-ceramide pathway mediates the effect of C. albicans. Mechanistically, formyl-methionine, a metabolite of C. albicans, activates intestinal HIF-2α signaling, which drives increased ceramide synthesis to accelerate atherosclerosis. Administration of the HIF-2α selective antagonist PT2385 alleviates atherosclerosis in mice by reducing ceramide levels. Our findings identify a role for intestinal fungi in atherosclerosis progression and highlight the intestinal HIF-2α-ceramide pathway as a target for atherosclerosis treatment.

Single-cell RNA-seq identified novel genes involved in primordial follicle formation.

Introduction: The number of primordial follicles (PFs) in mammals determines the ovarian reserve, and impairment of primordial follicle formation (PFF) will cause premature ovarian insufficiency (POI). Methods: By analyzing public single-cell RNA sequencing performed during PFF on mice and human ovaries, we identified novel functional genes and novel ligand-receptor interaction during PFF. Based on immunofluorescence and in vitro ovarian culture, we confirmed mechanisms of genes and ligand-receptor interaction in PFF. We also applied whole exome sequencing (WES) in 93 cases with POI and whole genome sequencing (WGS) in 465 controls. Variants in POI patients were further investigated by in silico analysis and functional verification. Results: We revealed ANXA7 (annexin A7) and GTF2F1 (general transcription factor IIF subunit 1) in germ cells to be novel potentially genes in promoting PFF. Ligand Mdk (midkine) in germ cells and its receptor Sdc1 (syndecan 1) in granulosa cells are novel interaction crucial for PFF. Based on immunofluorescence, we confirmed significant up-regulation of ANXA7 in PFs compared with germline cysts, and uniform expression of GTF2F1, MDK and SDC1 during PFF, in 25 weeks human fetal ovary. In vitro investigation indicated that Anxa7 and Gtf2f1 are vital for mice PFF by regulating Jak/Stat3 and Jnk signaling pathways, respectively. Ligand-receptor (Mdk-Sdc1) are crucial for PFF by regulating Pi3k-akt signaling pathway. Two heterozygous variants in GTF2F1, and one heterozygous variants in SDC1 were identified in cases, but no variant were identified in controls. The protein level of GTF2F1 or SDC1 in POI cases are significantly lower than that of controls, indicating the pathogenic effects of the two genes on ovarian function were dosage dependent. Discussion: Our study identified novel genes and novel ligand-receptor interaction during PFF, and further expanding the genetic architecture of POI.

CXADR promote epithelial-mesenchymal transition in endometriosis by modulating AKT/GSK-3ß signaling.

Endometriosis is a benign high prevalent disease exhibiting malignant features. However, the underlying pathogenesis and key molecules of endometriosis remain unclear. By integrating and analysis of existing expression profile datasets, we identified coxsackie and adenovirus receptor (CXADR), as a novel key gene in endometriosis. Based on the results of immunohistochemistry (IHC), we confirmed significant down-regulation of CXADR in ectopic endometrial tissues obtained from women with endometriosis compared with healthy controls. Further in vitro investigation indicated that CXADR regulated the stability and function of the phosphatases and AKT inhibitors PHLPP2 (pleckstrin homology domain and leucine-rich repeat protein phosphatase 2) and PTEN (phosphatase and tensin homolog). Loss of CXADR led to phosphorylation of AKT and glycogen synthase kinase-3ß (GSK-3ß), which resulted in stabilization of an epithelial-mesenchymal transition (EMT) factor, SNAIL1 (snail family transcriptional repressor 1). Therefore, EMT processs was induced, and the proliferation, migration and invasion of Ishikawa cells were enhanced. Over-expression of CXADR showed opposite effects. These findings suggest a previously undefined role of AKT/GSK-3ß signaling axis in regulating EMT and reveal the involvement of a CXADR-induced EMT, in pathogenic progression of endometriosis.