EHD1 impaired decidualization of endometrial stromal cells in recurrent implantation failure: role of SENP1 in modulating progesterone receptor signalling†

Recurrent implantation failure (RIF) patients exhibit poor endometrial receptivity and abnormal decidualization with reduced effectiveness and exposure to progesterone, which is an intractable clinical problem. However, the associated molecular mechanisms remain elusive. We found that EH domain containing 1 (EHD1) expression was abnormally elevated in RIF and linked to aberrant endometrial decidualization. Here we show that EHD1 overexpressed in human endometrial stromal cells significantly inhibited progesterone receptor (PGR) transcriptional activity and the responsiveness to progesterone. No significant changes were observed in PGR mRNA levels, while a significant decrease in progesterone receptor B (PRB) protein level. Indeed, EHD1 binds to the PRB protein, with the K388 site crucial for this interaction. Overexpression of EHD1 promotes the SUMOylation and ubiquitination of PRB, leading to the degradation of the PRB protein. Supplementation with the de-SUMOylated protease SENP1 ameliorated EHD1-repressed PRB transcriptional activity. To establish a functional link between EHD1 and the PGR signalling pathway, sg-EHD1 were utilized to suppress EHD1 expression in HESCs from RIF patients. A significant increase in the expression of prolactin and insulin-like growth factor-binding protein 1 was detected by interfering with the EHD1. In conclusion, we demonstrated that abnormally high expression of EHD1 in endometrial stromal cells attenuated the activity of PRB associated with progesterone resistance in a subset of women with RIF.

Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study

BACKGROUND

Ovarian cancer is the most lethal gynecological malignancy. Timely diagnosis of ovarian cancer is difficult due to the lack of effective biomarkers. Laboratory tests are widely applied in clinical practice, and some have shown diagnostic and prognostic relevance to ovarian cancer. We aimed to systematically evaluate the value of routine laboratory tests on the prediction of ovarian cancer, and develop a robust and generalisable ensemble artificial intelligence (AI) model to assist in identifying patients with ovarian cancer.

METHODS

In this multicentre, retrospective cohort study, we collected 98 laboratory tests and clinical features of women with or without ovarian cancer admitted to three hospitals in China during Jan 1, 2012 and April 4, 2021. A multi-criteria decision making-based classification fusion (MCF) risk prediction framework was used to make a model that combined estimations from 20 AI classification models to reach an integrated prediction tool developed for ovarian cancer diagnosis. It was evaluated on an internal validation set (3007 individuals) and two external validation sets (5641 and 2344 individuals). The primary outcome was the prediction accuracy of the model in identifying ovarian cancer.

FINDINGS

Based on 52 features (51 laboratory tests and age), the MCF achieved an area under the receiver-operating characteristic curve (AUC) of 0·949 (95% CI 0·948-0·950) in the internal validation set, and AUCs of 0·882 (0·880-0·885) and 0·884 (0·882-0·887) in the two external validation sets. The model showed higher AUC and sensitivity compared with CA125 and HE4 in identifying ovarian cancer, especially in patients with early-stage ovarian cancer. The MCF also yielded acceptable prediction accuracy with the exclusion of highly ranked laboratory tests that indicate ovarian cancer, such as CA125 and other tumour markers, and outperformed state-of-the-art models in ovarian cancer prediction. The MCF was wrapped as an ovarian cancer prediction tool, and made publicly available to provide estimated probability of ovarian cancer with input laboratory test values.

INTERPRETATION

The MCF model consistently achieved satisfactory performance in ovarian cancer prediction when using laboratory tests from the three validation sets. This model offers a low-cost, easily accessible, and accurate diagnostic tool for ovarian cancer. The included laboratory tests, not only CA125 which was the highest ranked laboratory test in importance of diagnostic assistance, contributed to the characterisation of patients with ovarian cancer.

FUNDING

Ministry of Science and Technology of China; National Natural Science Foundation of China; Natural Science Foundation of Guangdong Province, China; and Science and Technology Project of Guangzhou, China.

TRANSLATION

For the Chinese translation of the abstract see Supplementary Materials section.

Multiparametric MR-based feature fusion radiomics combined with ADC maps-based tumor proliferative burden in distinguishing TNBC versus non-TNBC

Objective.To investigate the incremental value of quantitative stratified apparent diffusion coefficient (ADC) defined tumor habitats for differentiating triple negative breast cancer (TNBC) from non-TNBC on multiparametric MRI (mpMRI) based feature-fusion radiomics (RFF) model.Approach.466 breast cancer patients (54 TNBC, 412 non-TNBC) who underwent routine breast MRIs in our hospital were retrospectively analyzed. Radiomics features were extracted from whole tumor on T2WI, diffusion-weighted imaging, ADC maps and the 2nd phase of dynamic contrast-enhanced MRI. Four models including the RFFmodel (fused features from all MRI sequences), RADCmodel (ADC radiomics feature), StratifiedADCmodel (tumor habitas defined on stratified ADC parameters) and combinational RFF-StratifiedADCmodel were constructed to distinguish TNBC versus non-TNBC. All cases were randomly divided into a training (n= 337) and test set (n= 129). The four competing models were validated using the area under the curve (AUC), sensitivity, specificity and accuracy.Main results.Both the RFFand StratifiedADCmodels demonstrated good performance in distinguishing TNBC from non-TNBC, with best AUCs of 0.818 and 0.773 in the training and test sets. StratifiedADCmodel revealed significant different tumor habitats (necrosis/cysts habitat, chaotic habitat or proliferative tumor core) between TNBC and non-TNBC with its top three discriminative parameters (p <0.05). The integrated RFF-StratifiedADCmodel demonstrated superior accuracy over the other three models, with higher AUCs of 0.832 and 0.784 in the training and test set, respectively (p <0.05).Significance.The RFF-StratifiedADCmodel through integrating various tumor habitats' information from whole-tumor ADC maps-based StratifiedADCmodel and radiomics information from mpMRI-based RFFmodel, exhibits tremendous promise for identifying TNBC.

A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI

PURPOSE

To explore a subregion-based RadioFusionOmics (RFO) model for discrimination between adult-type grade 4 astrocytoma and glioblastoma according to the 2021 WHO CNS5 classification.

METHODS

329 patients (40 grade 4 astrocytomas and 289 glioblastomas) with histologic diagnosis was retrospectively collected from our local institution and The Cancer Imaging Archive (TCIA). The volumes of interests (VOIs) were obtained from four multiparametric MRI sequences (T1WI, T1WI + C, T2WI, T2-FLAIR) using (1) manual segmentation of the non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE), and (2) K-means clustering of four habitats (H1: high T1WI + C, high T2-FLAIR; (2) H2: high T1WI + C, low T2-FLAIR; (3) H3: low T1WI + C, high T2-FLAIR; and (4) H4: low T1WI + C, low T2-FLAIR). The optimal VOI and best MRI sequence combination were determined. The performance of the RFO model was evaluated using the area under the precision-recall curve (AUPRC) and the best signatures were identified.

RESULTS

The two best VOIs were manual VOI3 (putative peritumoral edema) and clustering H34 (low T1WI + C, high T2-FLAIR (H3) combined with low T1WI + C and low T2-FLAIR (H4)). Features fused from four MRI sequences ([Formula: see text]) outperformed those from either a single sequence or other sequence combinations. The RFO model that was trained using fused features [Formula: see text] achieved the AUPRC of 0.972 (VOI3) and 0.976 (H34) in the primary cohort (p = 0.905), and 0.971 (VOI3) and 0.974 (H34) in the testing cohort (p = 0.402).

CONCLUSION

The performance of subregions defined by clustering was comparable to that of subregions that were manually defined. Fusion of features from the edematous subregions of multiple MRI sequences by the RFO model resulted in differentiation between grade 4 astrocytoma and glioblastoma.

Discriminative fusion of moments-aligned latent representation of multimodality medical data

Fusion of multimodal medical data provides multifaceted, disease-relevant information for diagnosis or prognosis prediction modeling. Traditional fusion strategies such as feature concatenation often fail to learn hidden complementary and discriminative manifestations from high-dimensional multimodal data. To this end, we proposed a methodology for the integration of multimodality medical data by matching their moments in a latent space, where the hidden, shared information of multimodal data is gradually learned by optimization with multiple feature collinearity and correlation constrains. We first obtained the multimodal hidden representations by learning mappings between the original domain and shared latent space. Within this shared space, we utilized several relational regularizations, including data attribute preservation, feature collinearity and feature-task correlation, to encourage learning of the underlying associations inherent in multimodal data. The fused multimodal latent features were finally fed to a logistic regression classifier for diagnostic prediction. Extensive evaluations on three independent clinical datasets have demonstrated the effectiveness of the proposed method in fusing multimodal data for medical prediction modeling.

NUSAP1 regulates mouse oocyte meiotic maturation

The correct assembly of the spindle apparatus directly regulates the precise separation of chromosomes in mouse oocytes, which is crucial for obtaining high-quality oocytes capable of successful fertilization. The localization, assembly, migration, and disassembly of the spindle are regulated by a series of spindle-associated proteins, which exhibit unique expression level variations and specific localization in oocytes. Proteomic analysis revealed that among many representative spindle-associated proteins, the expression level of nucleolar and spindle-associated protein 1 (NUSAP1) significantly increased after meiotic resumption, with a magnitude of change higher than that of other proteins. However, the role of NUSAP1 during oocyte meiosis maturation has not been reported. Here, we report that NUSAP1 is distributed within the cell nucleus during the germinal vesicle (GV) oocytes with non-surrounded nucleolus stage and is not enriched in the nucleus during the GV-surrounded nucleolus stage. Interestingly, NUSAP1 forms distinct granular aggregates near the spindle poles during the prophase of the first meiotic division (Pro-MI), metaphase I, and anaphase I/telophase I stages. Nusap1 depletion leads to chromosome misalignment, increased aneuploidy, and abnormal spindle assembly, particularly a decrease in spindle pole width. Correspondingly, RNA-seq analysis revealed significant suppression of the "establishment of spindle orientation" signaling pathway. Additionally, the attenuation of F-actin in NUSAP1-deficient oocytes may affect the asymmetric division process. Gene ontology analysis of NUSAP1 interactomes, identified through mass spectrometry here, revealed significant enrichment for RNA binding. As an RNA-binding protein, NUSAP1 is likely involved in the regulation of messenger RNA homeostasis by influencing the dynamics of processing (P)-body components. Overall, our results demonstrate the critical importance of precise regulation of NUSAP1 expression levels and protein localization for maintaining mouse oocyte meiosis.

Elucidating the role of nicotinamide N-methyltransferase-p53 axis in the progression of chronic kidney disease

Background

Chronic kidney disease (CKD) is a significant global health issue characterized by progressive loss of kidney function. Renal interstitial fibrosis (TIF) is a common feature of CKD, but current treatments are seldom effective in reversing TIF. Nicotinamide N-methyltransferase (NNMT) has been found to increase in kidneys with TIF, but its role in renal fibrosis is unclear.

Methods

Using mice with unilateral ureteral obstruction (UUO) and cultured renal interstitial fibroblast cells (NRK-49F) stimulated with transforming growth factor-β1 (TGF-β1), we investigated the function of NNMT in vivo and in vitro.

Results

We performed single-cell transcriptome sequencing (scRNA-seq) on the kidneys of mice and found that NNMT increased mainly in fibroblasts of UUO mice compared to sham mice. Additionally, NNMT was positively correlated with the expression of renal fibrosis-related genes after UUO injury. Knocking down NNMT expression reduced fibroblast activation and was accompanied by an increase in DNA methylation of p53 and a decrease in its phosphorylation.

Conclusions

Our findings suggest that chronic kidney injury leads to an accumulation of NNMT, which might decrease p53 methylation, and increase the expression and activity of p53. We propose that NNMT promotes fibroblast activation and renal fibrosis, making NNMT a novel target for preventing and treating renal fibrosis.

Maternal and embryonic signals cause functional differentiation of luminal epithelial cells and receptivity establishment

Embryo implantation requires temporospatial maternal-embryonic dialog. Using single-cell RNA sequencing for the uterus from 2.5 to 4.5 days post-coitum (DPC) and bulk sequencing for the corresponding embryos of 3.5 and 4.0 DPC pregnant mice, we found that estrogen-responsive luminal epithelial cells (EECs) functionally differentiated into adhesive epithelial cells (AECs) and supporting epithelial cells (SECs), promoted by progesterone. Along with maternal signals, embryonic Pdgfa and Efna3/4 signaling activated AECs and SECs, respectively, enhancing the attachment of embryos to the endometrium and furthering embryo development. This differentiation process was largely conserved between humans and mice. Notably, the developmental defects of SOX9-positive human endometrial epithelial cells (similar to mouse EEC) were related to thin endometrium, whereas functional defects of SEC-similar unciliated epithelial cells were related to recurrent implantation failure (RIF). Our findings provide insights into endometrial luminal epithelial cell development directed by maternal and embryonic signaling, which is crucial for endometrial receptivity.

Decreased HAT1 expression in granulosa cells disturbs oocyte meiosis during mouse ovarian aging

BACKGROUND

With advanced maternal age, abnormalities during oocyte meiosis increase significantly. Aneuploidy is an important reason for the reduction in the quality of aged oocytes. However, the molecular mechanism of aneuploidy in aged oocytes is far from understood. Histone acetyltransferase 1 (HAT1) has been reported to be essential for mammalian development and genome stability, and involved in multiple organ aging. Whether HAT1 is involved in ovarian aging and the detailed mechanisms remain to be elucidated.

METHODS

The level of HAT1 in aged mice ovaries was detected by immunohistochemical and immunoblotting. To explore the function of HAT1 in the process of mouse oocyte maturation, we used Anacardic Acid (AA) and small interfering RNAs (siRNA) to culture cumulus-oocyte complexes (COCs) from ICR female mice in vitro and gathered statistics of germinal vesicle breakdown (GVBD), the first polar body extrusion (PBE), meiotic defects, aneuploidy, 2-cell embryos formation, and blastocyst formation rate. Moreover, the human granulosa cell (GC)-like line KGN cells were used to investigate the mechanisms of HAT1 in this progress.

RESULTS

HAT1 was highly expressed in ovarian granulosa cells (GCs) from young mice and the expression of HAT1 was significantly decreased in aged GCs. AA and siRNAs mediated inhibition of HAT1 in GCs decreased the PBE rate, and increased meiotic defects and aneuploidy in oocytes. Further studies showed that HAT1 could acetylate Forkhead box transcription factor O1 (FoxO1), leading to the translocation of FoxO1 into the nucleus. Resultantly, the translocation of acetylated FoxO1 increased the expression of amphiregulin (AREG) in GCs, which plays a significant role in oocyte meiosis.

CONCLUSION

The present study suggests that decreased expression of HAT1 in GCs is a potential reason corresponding to oocyte age-related meiotic defects and provides a potential therapeutic target for clinical intervention to reduce aneuploid oocytes.

Decreased LONP1 expression contributes to DNA damage and meiotic defects in oocytes

Meiotic defects in oocytes are the primary reason for decreased female fertility with advanced maternal age. In this study, we revealed that decreased expression of ATP-dependent Lon peptidase 1 (LONP1) in aged oocytes and oocyte-specific depletion of LONP1 disrupt oocyte meiotic progression accompanying with mitochondrial dysfunction. In addition, LONP1 downregulation increased oocyte DNA damage. Moreover, we demonstrated that splicing factor proline and glutamine rich directly interacts with LONP1 and mediate the effect of LONP1 depletion on meiotic progression in oocytes. In summary, our data suggest that decreased expression of LONP1 is involved in advanced maternal age-related meiosis defects and that LONP1 represents a new therapeutic target to improve aged oocyte quality.

Granulosa cell mevalonate pathway abnormalities contribute to oocyte meiotic defects and aneuploidy

With aging, abnormalities during oocyte meiosis become more prevalent. However, the mechanisms of aging-related oocyte aneuploidy are not fully understood. Here we performed Hi-C and SMART-seq of oocytes from young and old mice and reveal decreases in chromosome condensation and disrupted meiosis-associated gene expression in metaphase I oocytes from aged mice. Further transcriptomic analysis showed that meiotic maturation in young oocytes was correlated with robust increases in mevalonate (MVA) pathway gene expression in oocyte-surrounding granulosa cells (GCs), which was largely downregulated in aged GCs. Inhibition of MVA metabolism in GCs by statins resulted in marked meiotic defects and aneuploidy in young cumulus-oocyte complexes. Correspondingly, supplementation with the MVA isoprenoid geranylgeraniol ameliorated oocyte meiotic defects and aneuploidy in aged mice. Mechanically, we showed that geranylgeraniol activated LHR/EGF signaling in aged GCs and enhanced the meiosis-associated gene expression in oocytes. Collectively, we demonstrate that the MVA pathway in GCs is a critical regulator of meiotic maturation and euploidy in oocytes, and age-associated MVA pathway abnormalities contribute to oocyte meiotic defects and aneuploidy.

Maternal circadian disruption before pregnancy impairs the ovarian function of female offspring in mice

Circadian disturbance brought on by shift employment, nighttime light pollution, and other factors is quite prevalent in contemporary culture. However, the effect of maternal circadian disruption before pregnancy on the reproduction of offspring in mice requires further research. Herein, we exposed female ICR mice to constant light to establish a model of preconceptional circadian disruption and then checked the ovarian function of female offspring (named the CLE group below). Our results revealed obesity, abnormal lipid metabolism and earlier puberty onset in the CLE group. Additionally, impaired ovarian follicle development, oocyte quality and preimplantation embryo development were shown in the CLE group. Moreover, the expression levels of Gnrh1 in the hypothalamus and Cyp17a1, Bmper, Bdnf and Lyve1 in ovaries, as well as circadian clock genes, including Clock, Cry1, Nr1d2 and Per2, were significantly downregulated in the CLE group. Mechanistically, immune responses, including the interleukin-17 (IL-17) signalling pathway, cytokine-cytokine receptor interaction and the chemokine signalling pathway, were altered in the CLE group, which may be responsible for the damaged ovarian function.

Machine learning based multi-label classification of single or mixed-composition urinary stones in in vivo spectral CT

BACKGROUND

Urinary stones comprise both single and mixed compositions. Knowledge of the stone composition helps the urologists choose appropriate medical interventions for patients. The parameters from the spectral computerized tomography (CT) analysis have potential values for identification of the urinary stone compositions.

PURPOSE

The present study aims to identify the compositions of urinary stones in vivo using parameters from spectral CT and machine learning, based on multi-label classification modeling.

METHODS

This retrospective study collected 252 urinary stone samples with single/mixed compositions (including carbapatite [CP], calcium oxalate monohydrate [COM], calcium oxalate dehydrate [COD], uric acid [UA], and struvite [STR]), which were confirmed by ex vivo infrared spectroscopy. Parameters were extracted from an energy spectrum analysis (ESA) of the spectral CT, including the effective atomic number (Z_eff ), Z_eff histogram, CT values at a given x-ray energy level, and material densities. These ESA parameters were utilized for composition analysis via a multi-label classification fusion framework, where 250 multi-label models were built and the classification decisions from the top performance models were integrated by a multi-criterion weighted fusion (MCWF) approach in order to reach a consensus prediction. An example-based metric A c c e x a m $Ac{c_{exam}}$ and label-based metric A c c l a b e l $Ac{c_{label}}$ were used for global and label-wise accuracy evaluations, respectively. The top-ranked parameters associated with discriminating the stone composition were also identified.

RESULTS

The multi-label classification fusion framework achieved an overall A c c e x a m $Ac{c_{exam}}$ of 81.2%, with A c c l a b e l $Ac{c_{label}}$ of 86.7% (CP), 90.6% (COM), 80.6% (COD), 95.0% (UA), and 94.4% (STR) for each composition on the independent testing cohort 1, and A c c e x a m $Ac{c_{exam}}$ of 76.4% with A c c l a b e l $Ac{c_{label}}$ of 80.5% (CP), 88.7% (COM), 74.9% (COD), 94.4% (UA), and 98.5% (STR) on the independent testing cohort 2.

CONCLUSION

The parameters extracted from the ESA on spectral CT can be utilized to characterize single or mixed stone compositions via multi-label classification modeling. The generalization capability of the proposed methodology still requires further verification.

Academic achievement is more closely associated with student-peer relationships than with student-parent relationships or student-teacher relationships

Introduction

Personal relationships have long been a concern in education. Most studies indicate that good personal relationships are generally positively correlated with academic performance. However, few studies have compared how different types of personal relationships correlate with academic performance, and the conclusions of existing studies are inconsistent. Based on a large sample, the current study compared how the three closest types of personal relationships among students (with parents, teachers, and their peers) compared with their academic performance.

Methods

Cluster sampling was used to issue questionnaires to students in Qingdao City, Shandong Province, China in 2018 (Study 1) and in 2019 (Study 2). The actual sample size included 28168 students in Study 1 and 29869 students in Study 2 (both studies, Grades 4 and 8), thus totaling 58037 students. All students completed a personal relationship questionnaire and several academic tests.

Results

The results showed that: (1) the quality of personal relationships significantly and positively correlated with academic performance; (2) Among the three types of relationships tested, the quality of student-peer relationships was the most closely associated with academic achievement.

Discussion

This study gives insights into future research directions in this field and also reminds educators to pay attention to the personal relationships among their students, especially peer relationships.

FHL1 mediates HOXA10 deacetylation via SIRT2 to enhance blastocyst-epithelial adhesion

Recurrent implantation failure (RIF) is a rather thorny problem in the clinical practice of assisted reproductive technology. Due to the complex aetiology of RIF, its pathogenesis is far from fully understood, and there is no effective treatment available. Here, We explored the regulatory mechanism of the four half-domains of LIM domain 1 (FHL1), which is significantly downregulated in the endometrium of RIF patients, in blastocyst-epithelial adhesion. Indeed, FHL1 expression was dramatically increased in normal female mid-secretory endometrial epithelial cells and was abnormally reduced in RIF patients. Furthermore, FHL1 overexpression promoted blastocyst-epithelial adhesion, and interfering with FHL1 expression in the mouse uterus significantly inhibited embryo implantation. Mechanistically, FHL1 did not regulate HOXA10 mRNA expression but increased HOXA10 protein stability and activated HOXA10, thereby promoting its regulation of downstream gene expression and the β3 integrin/FAK pathway. Meanwhile, FHL1 regulates HOXA10 function by increasing HOXA10 deacetylation through enhanced binding of HOXA10 and SIRT2. SIRT2-specific inhibitors can significantly inhibit this effect. In the endometrial epithelial cells of RIF patients, the correlation between FHL1 and HOXA10 and its downstream target genes has also been verified. Finally, our data indicated FHL1 is a regulatory molecule that promotes blastocyst-epithelial adhesion. Altogether, downstream dysfunction due to aberrant FHL1 expression is an important molecular basis for embryo implantation failure in patients with RIF and to provide new potential therapeutic targets.

Mechanisms of Xiong-Pi-Fang in treating coronary heart disease associated with depression: A systematic pharmacology strategy and in vivo pharmacological validation

BACKGROUND

Coronary heart disease (CHD) and depression are very common and often co-existing disorders. Xiong-Pi-Fang (XPF), a therapeutic classical traditional Chinese medicine (TCM) formula, has shown satisfactory efficacy in treating CHD associated with depression. However, its mechanism of action is still unknown.

PURPOSE

To employ a systematic pharmacology approach for identifying the action mechanisms of XPF in treating CHD associated with depression.

METHODS

We used a systematic pharmacology approach to identify the potential active mechanisms of XPF in treating CHD with depression. Potential active compounds in XPF and the diseases targets were screened using relevant databases to build corresponding pathways, following the experiments that were conducted to confirm whether the presumptive results of systemic pharmacology were correct.

RESULTS

Network pharmacology predicted 42 key targets and 20 signaling pathways involved in XPF-mediated treatment, with IL-6/JAK2/STAT3/HIF-1α/VEGF-A pathway significantly affected. The common influences were hypothalamic-pituitary-adrenal axis (HPA axis) and glucocorticoid signaling, validated through chronic unexpected mild stress (CUMS) with isoprenaline (ISO) for inducing CHD within the depression model in rats. In addition, XPF intake reduced depressive-like behaviors and improved ECG ischemic changes. Furthermore, XPF exerted some anti-inflammatory effects by inhibiting the interleukin-6 (IL-6) induced phosphorylation of janus kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3), ultimately downregulating hypoxia-inducible factor 1-α (HIF-1α) and vascular endothelial growth factor-A (VEGF-A) activation. The dysfunctional HPA axis feedback loop was also regulated, which enhanced the glucocorticoid receptor (GR) expression. In contrast, it improved glucocorticoid resistance by reducing the mineralocorticoid receptor expression.

CONCLUSIONS

Suppressing IL-6 release and maintaining the HPA feedback loop balance could be the primary mechanism of XPF against CHD with depression. The significance of the IL-6 and HPA axis identified indicates their potential as essential targets for CHD therapy with depression.

Dietary choline, via gut microbe- generated trimethylamine-N- oxide, aggravates chronic kidney disease-induced cardiac dysfunction by inhibiting hypoxia-induced factor 1α

Chronic kidney disease (CKD) is a global public health problem that shortens lifespan primarily by increasing the risk of cardiovascular diseases. Trimethylamine-N-oxide (TMAO), a gut microbiota-derived toxin produced by metabolizing high-choline or carnitine foods, is associated with cardiovascular events in patients with CKD. Although the deleterious effect of TMAO on CKD-induced cardiac injury has been confirmed by various researches, the mechanisms remain unclear. Here, we tested the hypothesis that TMAO aggravates CKD-induced cardiac injury and explores the potential mechanism. CD1 mice underwent 5/6 nephrectomy to induce CKD, and then fed with a diet supplemented with choline (1.2% total) for 8 weeks. Serum TMAO levels were elevated in CKD mice compared with SHAM group, and higher TMAO levels were found in choline-supplemented CKD mice compared with CKD group. Dietary choline aggravated CKD-induced cardiac dysfunction, and reducing TMAO levels via medicinal charcoal tablets improved cardiac dysfunction. RNA-seq analysis revealed that dietary choline affected cardiac angiogenesis in CKD mice. Reduced cardiac capillary density and expressions of angiogenesis-related genes were observed in choline-treated CKD mice. Furthermore, dietary choline inhibited cardiac Hif-1α protein level in CKD mice, and Hif-1α stabilizer FG-4592 could improve cardiac angiogenesis and dysfunction in CKD mice on a high-choline diet. In conclusion, these data indicate that dietary choline, via gut microbe-generated TMAO, inhibits cardiac angiogenesis by reducing Hif-1α protein level, ultimately aggravates cardiac dysfunction in CKD mice.

MEKK4-mediated Phosphorylation of HOXA10 at Threonine 362 facilitates embryo adhesion to the endometrial epithelium

Embryo adhesion is a very important step in the embryo implantation process. Homeobox A10 (HOXA10), a key transcriptional factor of endometrial receptivity, is indispensable for embryo adhesion. However, how to control the activation status of HOXA10 remains elusive. Here, we found that Mitogen-activated protein kinase kinase kinase 4 (MEKK4) was associated with HOXA10 and directly phosphorylated HOXA10 at threonine 362. This MEKK4-mediated phosphorylation enhanced HOXA10-mediated transcriptional responses and adhesion between the embryo and endometrial epithelium. Specific deletion or kinase inactivation of MEKK4 in endometrial epithelial cells attenuates adhesion between embryo and epithelium. Therefore, the identification of MEKK4 as a novel physiological positive regulator of HOXA10 activation provides mechanistic insights to improve embryo implantation success. Moreover, when Thr362 was mutated to alanine (T362A) to mimic its dephosphorylation, the protein stability and transcriptional regulation of HOXA10 were decreased. In addition, HOXA10 -promoted embryo adhesion was weakened after the mutation of Thr362, suggesting that the phosphorylation of HOXA10 at this site may be a new indicator for evaluating endometrial receptivity and judging the ‘implantation window’.

Multi-Omics-Guided Discovery of Omicsynins Produced by Streptomyces sp. 1647: Pseudo-Tetrapeptides Active Against Influenza A Viruses and Coronavirus HCoV-229E

Many microorganisms have mechanisms that protect cells against attack from viruses. The fermentation components of Streptomyces sp. 1647 exhibit potent anti-influenza A virus (IAV) activity. This strain was isolated from soil in southern China in the 1970s, but the chemical nature of its antiviral substance(s) has remained unknown until now. We used an integrated multi-omics strategy to identify the antiviral agents from this streptomycete. The antibiotics and Secondary Metabolite Analysis Shell (antiSMASH) analysis of its genome sequence revealed 38 biosynthetic gene clusters (BGCs) for secondary metabolites, and the target BGCs possibly responsible for the production of antiviral components were narrowed down to three BGCs by bioactivity-guided comparative transcriptomics analysis. Through bioinformatics analysis and genetic manipulation of the regulators and a biosynthetic gene, cluster 36 was identified as the BGC responsible for the biosynthesis of the antiviral compounds. Bioactivity-based molecular networking analysis of mass spectrometric data from different recombinant strains illustrated that the antiviral compounds were a class of structural analogues. Finally, 18 pseudo-tetrapeptides with an internal ureido linkage, omicsynins A1-A6, B1-B6, and C1-C6, were identified and/or isolated from fermentation broth. Among them, 11 compounds (omicsynins A1, A2, A6, B1-B3, B5, B6, C1, C2, and C6) are new compounds. Omicsynins B1-B4 exhibited potent antiviral activity against IAV with the 50% inhibitory concentration (IC₅₀) of approximately 1 µmol∙L^-1 and a selectivity index (SI) ranging from 100 to 300. Omicsynins B1-B4 also showed significant antiviral activity against human coronavirus HCoV-229E. By integrating multi-omics data, we discovered a number of novel antiviral pseudo-tetrapeptides produced by Streptomyces sp. 1647, indicating that the secondary metabolites of microorganisms are a valuable source of novel antivirals.

[A discrimination model for differentiation of renal cell carcinoma from renal angiomyolipoma without visible fat: based on hierarchical fusion framework of multi-classifier]

OBJECTIVE

To investigate the capabilities of classification models based on hierarchical fusion framework of multi-classifier using a random projection strategy for differentiation of renal cell carcinoma (RCC) from small renal angiomyolipoma (< 4 cm) without visible fat (AMLwvf).

METHODS

We retrospectively collected the clinical data from 163 patients with pathologically proven small renal mass, including 118 with RCC and 45 with AMLwvf.Target region of interest (ROI) delineation was performed on an unenhanced phase (UP) CT image slice displaying the largest lesion area.The radiomics features were used to establish a hierarchical fusion method.On the projection-based level, the homogeneous classifiers were fused, and the fusion results were further fused at the classifier-based level to construct a multi-classifier fusion system based on random projection for differentiation of AMLwvf and RCC.The discriminative capability of this model was quantitatively evaluated using 5-fold cross validation and 4 evaluation indexes[specificity, sensitivity, accuracy and area under ROC curve (AUC)].We quantitatively compared this multi-classifier fusion framework against different classification models using a single classifier and several multi-classifier ensemble models.

RESULTS

When the projection number was set at 10, the proposed hierarchical fusion differentiation framework achieved the best results on all the evaluation measurements.At the optimal projection number of 10, the specificity, sensitivity, average accuracy and AUC of the multi-classifier ensemble classification system for differentiation between AMLwvf and RCC were 0.853, 0.693, 0.809 and 0.870, respectively.

CONCLUSION

The proposed model constructed based on a multi-classifier fusion system using random projection shows better performance to differentiate RCC from AMLwvf than the AMLwvf and RCC discrimination models based on a single classification algorithm and the currently available benchmark ensemble methods.

A novel lncRNA lncSAMD11-1: 1 interacts with PIP4K2A to promote endometrial decidualization by stabilizing FoxO1 nuclear localization

Decidualization is essential for a successful pregnancy and determines embryo implantation and pregnancy maintenance. Abnormal decidualization is one of the main causes of recurrent implantation failure (RIF). Studies have shown that large amounts of long noncoding RNAs (lncRNAs) are abnormally expressed in endometrial samples from patients with RIF. However, the functional contributions of lncRNAs to decidualization in RIF have not been explored. In this study, we found that lncSAMD11-1:1 was significantly declined in the endometria of patients with RIF. The knockdown of lncSAMD11-1:1 in human endometrial stromal cells (hESCs) restrained decidualization and embryo implantation in vitro, while the overexpression of lncSAMD11-1:1 facilitated hESC decidualization and embryo implantation in vitro and ameliorated decidualization in RIF patients. Mechanistically, lncSAMD11-1:1 and phosphatidylinositol-5-phosphate 4-kinase type 2 alpha (PIP4K2A) translocated out of nucleus and bound to each other during decidualization, thereby inhibiting the phosphorylation of AKT and promoting FoxO1 nuclear localization. These data suggest that lncSAMD11-1:1 might be a critical novel lncRNA functionally required for human decidualization, and the dysregulation of lncSAMD11-1:1 in the endometrium may be a new predisposing factor of RIF.

Combined intermittent and sustained hypoxia is a novel and deleterious cardio-metabolic phenotype

STUDY OBJECTIVES

Chronic obstructive pulmonary disease and obstructive sleep apnea overlap syndrome is associated with excess mortality, and outcomes are related to the degree of hypoxemia. People at high altitudes are susceptible to periodic breathing, and hypoxia at altitude is associated with cardio-metabolic dysfunction. Hypoxemia in these scenarios may be described as superimposed sustained hypoxia (SH) plus intermittent hypoxia (IH), or overlap hypoxia (OH), the effects of which have not been investigated. We aimed to characterize the cardio-metabolic consequences of OH in mice.

METHODS

C57BL/6J mice were subjected to either SH (FiO2 = 0.10), IH (FiO2 = 0.21 for 12 h, and FiO2 oscillating between 0.21 and 0.06, 60 times/hour, for 12 h), OH (FiO2 = 0.13 for 12 h, and FiO2 oscillating between 0.13 and 0.06, 60 times/hour, for 12 h), or room air (RA), n = 8/group. Blood pressure and intraperitoneal glucose tolerance test were measured serially, and right ventricular systolic pressure (RVSP) was assessed.

RESULTS

Systolic blood pressure transiently increased in IH and OH relative to SH and RA. RVSP did not increase in IH, but increased in SH and OH by 52% (p < .001) and 20% (p = .001). Glucose disposal worsened in IH and improved in SH, with no change in OH. Serum low- and very-low-density lipoproteins increased in OH and SH, but not in IH. Hepatic oxidative stress increased in all hypoxic groups, with the highest increase in OH.

CONCLUSIONS

OH may represent a unique and deleterious cardio-metabolic stimulus, causing systemic and pulmonary hypertension, and without protective metabolic effects characteristic of SH.

Mechanisms of Lian-Gui-Ning-Xin-Tang in the treatment of arrhythmia: Integrated pharmacology and in vivo pharmacological assessment

BACKGROUND

Lian-Gui-Ning-Xin-Tang (LGNXT), a classical traditional Chinese medicine (TCM) formula, has been widely used in clinical practice and has shown satisfactory efficacy in the treatment of arrhythmias. However, its mechanism of action in the treatment of arrhythmias is still unknown. Moreover, the complex chemical composition and therapeutic targets of LGNXT pose a challenge in pharmacological research.

PURPOSE

To analyze the active compounds and action mechanisms of LGNXT for the treatment of arrhythmias.

METHODS

Here, we used an integrated pharmacology approach to identify the potential active compounds and mechanisms of action of LGNXT in treating arrhythmias. Potential active compounds in LGNXT were identified using ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF/MS) and the potential related targets of these compounds were predicted using an integrated in silico approach. The obtained targets were mapped onto relevant databases to identify their corresponding pathways, following the experiments that were conducted to confirm whether the presumptive results of systemic pharmacology were correct.

RESULTS

Eighty-three components were identified in herbal materials and in animal plasma using UPLC-Q-TOF/MS and were considered the potential active components of LGNXT. Thirty key targets and 57 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified as possible targets and pathways involved in LGNXT-mediated treatment using network pharmacology, with the cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA)/Ca2+ system pathway being the most significantly affected. This finding was validated using an adrenaline (Adr)-induced rat model of arrhythmias. Pretreatment with LGNXT delayed the occurrence, shortened the duration, and reduced the severity of arrhythmias. LGNXT exerted antiarrhythmic effects by inhibiting cAMP, PKA, CACNA1C, and RyR2.

CONCLUSIONS

The findings of this study revealed that preventing intracellular Ca2+ overload and maintaining intracellular Ca2+ homeostasis may be the primary mechanisms of LGNXT in alleviating arrhythmias. Thus, we suggest that the β-adrenergic receptor (AR)/cAMP/PKA/Ca2+ system signaling hub may constitute a promising molecular target for the development of novel antiarrhythmic therapeutic interventions. Additionally, we believe that the approach of investigation of the biological effects of a multi-herbal formula by the combination of metabolomics and network pharmacology, as used in this study, could serve as a systematic model for TCM research.

Radiomics combined with clinical characteristics predicted the progression-free survival time in first-line targeted therapy for advanced non-small cell lung cancer with EGFR mutation

Objective

This study was to explore the most appropriate radiomics modeling method to predict the progression-free survival of EGFR-TKI treatment in advanced non-small cell lung cancer with EGFR mutations. Different machine learning methods may vary considerably and the selection of a proper model is essential for accurate treatment outcome prediction. Our study were established 176 discrimination models constructed with 22 feature selection methods and 8 classifiers. The predictive performance of each model were evaluated using the AUC, ACC, sensitivity and specificity, where the optimal model was identified.

Results

There were totally 107 radiomics features and 7 clinical features obtained from each patient. After feature selection, the top-ten most relevant features were fed to train 176 models. Significant performance variations were observed in the established models, with the best performance achieved by the logistic regression model using gini-index feature selection (AUC = 0.797, ACC = 0.722, sensitivity = 0.758, specificity = 0.693). The median R-score was 0.518 (IQR, 0.023–0.987), and the patients were divided into high-risk and low-risk groups based on this cut-off value. The KM survival curves of the two groups demonstrated evident stratification results (p = 0.000).

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-022-06019-x.

[The incidence of myopia and myopic progression from 2019 to 2020 in school-age children in Zhuozhou]

Objective: To analyze the changes in refractive status and prevalence of myopia in 6-to 14-year-old children at 2 time points in Zhuozhou, Hebei Province. Methods: In the current cohort study, the visual acuity and refractive status of primary and secondary school students aged 6 to 14 years were examined from June to August 2019 and reexamined from June to August 2020. A total of 30 412 subjects with examination data were enrolled, including 15 861 males (52.2%) and 14 551 females (47.8%), with an average age of (10.0±2.7) years. The participants underwent autorefraction without cycloplegia and a naked eye visual acuity test with a standard logarithmic visual acuity chart. Myopia was screened by the standard of equivalent spherical refraction less than -0.75 diopter (D). The categorical data were analyzed by the Chi-square or Fisher's exact test. Clopper-Pearson was used to estimate the 95% confidence intervals for the incidence of myopia. Results: After the 1-year interval, the change of equivalent spherical refraction was(-0.67±1.11) D and(-0.76±1.11) D, respectively, in male and female participants, and their visual acuity decreased by 0.11±0.19 and 0.12±0.21, respectively. There were significant inter-group differences in the annual change of spherical power in different age groups (χ²=276.23, P<0.001). The naked eye visual acuity reduction was greatest in the 10-year-old students. The incidence of myopia was 42.2% (95% confidence intervals of 41.47% to 42.93%) during the 1-year follow-up period. The incidence of myopia was highest at the age of 14 (52.0% in males and 54.2% in females) and lowest at the age of 6 (31.0% in males and 33.1% in females). Conclusions: The 1-year follow-up revealed an obvious myopic shift in the refractive status of school students in Zhuozhou, with their naked eye visual acuity decreased. The incidence of myopia was higher in females than that in males.

Calpain7 negatively regulates human endometrial stromal cell decidualization in EMs by promoting FoxO1 nuclear exclusion via hydrolyzing AKT1

Endometrial receptivity damage caused by impaired decidualization may be one of the mechanisms of infertility in endometriosis (EMs). Our previous study demonstrated that Calpain-7 (CAPN7) is abnormally overexpressed in EMs. Whether CAPN7 affects the regulation of decidualization and by what mechanism CAPN7 regulates decidualization remains to be determined. In this study, we found CAPN7 expression decreased during human endometrial stromal cell (HESC) decidualization in vitro. CAPN7 negatively regulated decidualization in vitro and in vivo. We also identified one conserved potential PEST sequence in the AKT1 protein and found that CAPN7 was able to hydrolyse AKT1 and enhance AKT1's phosphorylation. Correspondingly, CAPN7 notably promoted the phosphorylation of Forkhead Box O1 (FoxO1), the downstream of AKT1 protein, at Ser319, leading to increased FoxO1 exclusion from nuclei and attenuated FoxO1 transcriptional activity in decidualized HESC. In addition, we detected endometrium CAPN7, p-AKT1 and p-FoxO1 expressions were increased in EMs. These data demonstrate that CAPN7 negatively regulates HESC decidualization in EMs probably by promoting FoxO1's phosphorylation and FoxO1 nuclear exclusion via hydrolyzing AKT1. The dysregulation of CAPN7 may be a novel cause of EMs.

The mitochondrial protease LONP1 maintains oocyte development and survival by suppressing nuclear translocation of AIFM1 in mammals

Background

Oogenesis is a fundamental process of human reproduction, and mitochondria play crucial roles in oocyte competence. Mitochondrial ATP-dependent Lon protease 1 (LONP1) functions as a critical protein in maintaining mitochondrial and cellular homeostasis in somatic cells. However, the essential role of LONP1 in maintaining mammalian oogenesis is far from elucidated.

Methods

Using conditional oocyte Lonp1-knockout mice, RNA sequencing (RNA-seq) and coimmunoprecipitation/liquid chromatography–mass spectrometry (Co-IP/LC–MS) technology, we analysed the functions of LONP1 in mammalian oogenesis.

Findings

Conditional knockout of Lonp1 in mouse oocytes in both the primordial and growing follicle stages impairs follicular development and causes progressive oocyte death, ovarian reserve loss, and infertility. LONP1 directly interacts with apoptosis inducing factor mitochondria-associated 1 (AIFM1), and LONP1 ablation leads to the translocation of AIFM1 from the cytoplasm to the nucleus, causing apoptosis in mouse oocytes. In addition, women with pathogenic variants of LONP1 lack large antral follicles (>10 mm) in the ovaries, are infertile and present premature ovarian insufficiency.

Interpretation

We demonstrated the function of LONP1 in regulating oocyte development and survival, and in-depth analysis of LONP1 will be crucial for elucidating the mechanisms underlying premature ovarian insufficiency.

Funding

This work was supported by grants from the National Key Research and Development Program of China (2018YFC1004701), the National Nature Science Foundation of China (82001629, 81871128, 81571391, 81401166, 82030040), the Jiangsu Province Social Development Project (BE2018602), the Jiangsu Provincial Medical Youth Talent (QNRC2016006), the Youth Program of the Natural Science Foundation of Jiangsu Province (BK20200116) and Jiangsu Province Postdoctoral Research Funding (2021K277B).

A Multiparametric MR-Based RadioFusionOmics Model with Robust Capabilities of Differentiating Glioblastoma Multiforme from Solitary Brain Metastasis

Simple Summary

Glioblastoma multiforme (GBM) and solitary brain metastasis (SBM) are common brain tumors in adults. The two tumors often pose a diagnostic dilemma owing to their similar features on conventional magnetic resonance imaging (MRI). Ability to discriminate the two tumors is critical as it informs clinical treatment strategies. This pilot study attempts to employ the machine learning technique to identify GBM and SBM by fusing radiomics features of multiple MRI sequences and multiple models. A multiparametric MR-based RadioFusionOmics (RFO) model was developed and has demonstrated promising prediction accuracy for the identifications of GBM and SBM.

Abstract

This study aimed to evaluate the diagnostic potential of a novel RFO model in differentiating GBM and SBM with multiparametric MR sequences collected from 244 (131 GBM and 113 SBM) patients. Three basic volume of interests (VOIs) were delineated on the conventional axial MR images (T₁WI, T₂WI, T₂_FLAIR, and CE_T₁WI), including volumetric non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE). Using the RFO model, radiomics features extracted from different multiparametric MRI sequence(s) and VOI(s) were fused and the best sequence and VOI, or possible combinations, were determined. A multi-disciplinary team (MDT)-like fusion was performed to integrate predictions from the high-performing models for the final discrimination of GBM vs. SBM. Image features extracted from the volumetric ET (VOI_ET) had dominant predictive performances over features from other VOI combinations. Fusion of VOI_ET features from the T₁WI and T₂_FLAIR sequences via the RFO model achieved a discrimination accuracy of AUC = 0.925, accuracy = 0.855, sensitivity = 0.856, and specificity = 0.853, on the independent testing cohort 1, and AUC = 0.859, accuracy = 0.836, sensitivity = 0.708, and specificity = 0.919 on the independent testing cohort 2, which significantly outperformed three experienced radiologists (p = 0.03, 0.01, 0.02, and 0.01, and p = 0.02, 0.01, 0.45, and 0.02, respectively) and the MDT-decision result of three experienced experts (p = 0.03, 0.02, 0.03, and 0.02, and p = 0.03, 0.02, 0.44, and 0.03, respectively).

Fuhrman nuclear grade prediction of clear cell renal cell carcinoma: influence of volume of interest delineation strategies on machine learning-based dynamic enhanced CT radiomics analysis

OBJECTIVE

To investigate the influence of different volume of interest (VOI) delineation strategies on machine learning-based predictive models for discrimination between low and high nuclear grade clear cell renal cell carcinoma (ccRCC) on dynamic contrast-enhanced CT.

METHODS

This study retrospectively collected 177 patients with pathologically proven ccRCC (124 low-grade; 53 high-grade). Tumor VOI was manually segmented, followed by artificially introducing uncertainties as: (i) contour-focused VOI, (ii) margin erosion of 2 or 4 mm, and (iii) margin dilation (2, 4, or 6 mm) inclusive of perirenal fat, peritumoral renal parenchyma, or both. Radiomics features were extracted from four-phase CT images (unenhanced phase (UP), corticomedullary phase (CMP), nephrographic phase (NP), excretory phase (EP)). Different combinations of four-phasic features for each VOI delineation strategy were used to build 176 classification models. The best VOI delineation strategy and superior CT phase were identified and the top-ranked features were analyzed.

RESULTS

Features extracted from UP and EP outperformed features from other single/combined phase(s). Shape features and first-order statistics features exhibited superior discrimination. The best performance (ACC 81%, SEN 67%, SPE 87%, AUC 0.87) was achieved with radiomics features extracted from UP and EP based on contour-focused VOI.

CONCLUSION

Shape and first-order features extracted from UP + EP images are better feature representations. Contour-focused VOI erosion by 2 mm or dilation by 4 mm within peritumor renal parenchyma exerts limited impact on discriminative performance. It provides a reference for segmentation tolerance in radiomics-based modeling for ccRCC nuclear grading.

KEY POINTS

• Lesion delineation uncertainties are tolerated within a VOI erosion range of 2 mm or dilation range of 4 mm within peritumor renal parenchyma for radiomics-based ccRCC nuclear grading. • Radiomics features extracted from unenhanced phase and excretory phase are superior to other single/combined phase(s) at differentiating high vs low nuclear grade ccRCC. • Shape features and first-order statistics features showed superior discriminative capability compared to texture features.

Hepatocyte HIF-1 and Intermittent Hypoxia Independently Impact Liver Fibrosis in Murine NAFLD

Obstructive sleep apnea (OSA) is associated with insulin resistance, lipid dysregulation, and hepatic steatosis and fibrosis in nonalcoholic fatty liver disease (NAFLD). We have previously shown that hepatocyte hypoxia inducible factor-1 (HIF-1) mediates the development of liver fibrosis in a mouse model of NAFLD. We hypothesized that intermittent hypoxia (IH) modeling OSA would worsen hepatic steatosis and fibrosis in murine NAFLD, via HIF-1. Mice with hepatocyte-specific deletion of Hif1a (Hif1a^-/-hep) and wild-type (Hif1a^F/F) controls were fed a high trans-fat diet to induce NAFLD with steatohepatitis. Half from each group were exposed to IH, and the other half to intermittent air. Glucose tolerance test was performed prior to sacrifice. Liver collagen and triglycerides were determined. Mitochondrial efficiency was assessed in fresh liver tissue at sacrifice. Hepatic malondialdehyde concentration and pro-inflammatory cytokine levels were assessed, and genes of collagen and fatty acid metabolism were queried. Hif1a^-/-hep mice gained less weight than Hif1a^F/F mice (-2.3 grams, p=0.029). There was also a genotype-independent effect of IH on body weight, with less weight gain in IH (p=0.003). Fasting glucose, HOMA-IR, and glucose tolerance test were all improved in Hif1a^-/-hep mice. Liver collagen was increased in IH (p=0.033), and reduced in Hif1a^-/-hep mice (p<0.001), without any significant exposure/genotype interaction. Liver TNF-α and IL-1β were significantly increased in IH, and decreased in Hif1a^-/-hep. We conclude that HIF-1 signaling worsens the metabolic profile and hastens NAFLD progression, and that IH may worsen liver fibrosis. These effects are plausibly mediated by hepatic inflammatory stress.

Fusapyrone A, a γ-pyrone derived from a desert Fusarium sp

In this work, we isolated and characterized fusapyrone A (1), a new γ-pyrone derivative, along with six previously described compounds from the rice fermentation of Fusarium sp. CPCC 401218, a fungus collected from the desert. The structure of 1 was characterized using various spectroscopic analyses, such as MS, IR, 1D, and 2D NMR. The absolute configuration of 1 was determined through the use of ¹³C NMR chemical shifts, electronic circular dichroism (ECD) and optical rotation (OR) calculations. Compound 1 was found to have weak antiproliferative activity for Hela cells, with an IC₅₀ of 50.6 μM.[Formula: see text].

Rectum Protection by Rectal Gel Injection in Cervical Cancer Brachytherapy: A Dosimetric Study via Deformable Surface Dose Accumulation and Machine-Learning-Based Discriminative Modeling

Purpose

This retrospective study aimed to evaluate the dosimetric effects of a rectal insertion of Kushen Ningjiao on rectal protection using deformable dose accumulation and machine learning–based discriminative modelling.

Materials and Methods

Sixty-two patients with cervical cancer enrolled in a clinical trial, who received a Kushen Ningjiao injection of 20 g into their rectum for rectal protection via high–dose rate brachytherapy (HDR-BT, 6 Gy/f), were studied. The cumulative equivalent 2-Gy fractional rectal surface dose was deformably summed using an in-house-developed topography-preserved point-matching deformable image registration method. The cumulative three-dimensional (3D) dose was flattened and mapped to a two-dimensional (2D) plane to obtain the rectal surface dose map (RSDM). For analysis, the rectal dose (RD) was further subdivided as follows: whole, anterior, and posterior 3D-RD and 2D-RSDM. The dose–volume parameters (DVPs) were extracted from the 3D-RD, while the dose geometric parameters (DGPs) and textures were extracted from the 2D-RSDM. These features were fed into 192 classification models (built with 8 classifiers and 24 feature selection methods) for discriminating the dose distributions between pre-Kushen Ningjiao and pro-Kushen Ningjiao.

Results

The rectal insertion of Kushen Ningjiao dialated the rectum in the ambilateral direction, with the rectal column increased from pre-KN 15 cm³ to post-KN 18 cm³ (P < 0.001). The characteristics of DGPs accounted for the largest portions of the top-ranked features. The top-ranked dosimetric features extracted from the posterior rectum were more reliable indicators of the dosimetric effects/changes introduced by the rectal insertion of Kushen Ningjiao. A significant dosimetric impact was found on the dose–volume parameters D_1.0cc–D_2.5cc extracted on the posterior rectal wall.

Conclusions

The rectal insertion of Kushen Ningjiao incurs significant dosimetric changes on the posterior rectal wall. Whether this effect is eventually translated into clinical gains requires further long-term follow-up and more clinical data for confirmation.

ATF3 deficiency impairs the proliferative-secretory phase transition and decidualization in RIF patients

Decidualization is a complex process involving cellular proliferation and differentiation of the endometrial stroma and is required to establish and support pregnancy. Dysregulated decidualization has been reported to be a critical cause of recurrent implantation failure (RIF). In this study, we found that Activating transcription factor 3 (ATF3) expression was significantly downregulated in the endometrium of RIF patients. Knockdown of ATF3 in human endometrium stromal cells (hESCs) hampers decidualization, while overexpression could trigger the expression of decidual marker genes, and ameliorate the decidualization of hESCs from RIF patients. Mechanistically, ATF3 promotes decidualization by upregulating FOXO1 via suppressing miR-135b expression. In addition, the endometrium of RIF patients was hyperproliferative, while overexpression of ATF3 inhibited the proliferation of hESCs through CDKN1A. These data demonstrate the critical roles of endometrial ATF3 in regulating decidualization and proliferation, and dysregulation of ATF3 in the endometrium may be a novel cause of RIF and therefore represent a potential therapeutic target for RIF.

Prediction of Microvascular Invasion in Hepatocellular Carcinoma With a Multi-Disciplinary Team-Like Radiomics Fusion Model on Dynamic Contrast-Enhanced Computed Tomography

Objective

To investigate microvascular invasion (MVI) of HCC through a noninvasive multi-disciplinary team (MDT)-like radiomics fusion model on dynamic contrast enhanced (DCE) computed tomography (CT).

Methods

This retrospective study included 111 patients with pathologically proven hepatocellular carcinoma, which comprised 57 MVI-positive and 54 MVI-negative patients. Target volume of interest (VOI) was delineated on four DCE CT phases. The volume of tumor core (V_tc) and seven peripheral tumor regions (V_pt, with varying distances of 2, 4, 6, 8, 10, 12, and 14 mm to tumor margin) were obtained. Radiomics features extracted from different combinations of phase(s) and VOI(s) were cross-validated by 150 classification models. The best phase and VOI (or combinations) were determined. The top predictive models were ranked and screened by cross-validation on the training/validation set. The model fusion, a procedure analogous to multidisciplinary consultation, was performed on the top-3 models to generate a final model, which was validated on an independent testing set.

Results

Image features extracted from V_tc+V_pt(12mm) in the portal venous phase (PVP) showed dominant predictive performances. The top ranked features from V_tc+V_pt(12mm) in PVP included one gray level size zone matrix (GLSZM)-based feature and four first-order based features. Model fusion outperformed a single model in MVI prediction. The weighted fusion method achieved the best predictive performance with an AUC of 0.81, accuracy of 78.3%, sensitivity of 81.8%, and specificity of 75% on the independent testing set.

Conclusion

Image features extracted from the PVP with V_tc+V_pt(12mm) are the most reliable features indicative of MVI. The MDT-like radiomics fusion model is a promising tool to generate accurate and reproducible results in MVI status prediction in HCC.

Multiphase Contrast-Enhanced CT-Based Machine Learning Models to Predict the Fuhrman Nuclear Grade of Clear Cell Renal Cell Carcinoma

Objective

To investigate the predictive performance of different machine learning models for the discrimination of low and high nuclear grade clear cell renal cell carcinoma (ccRCC) by using multiphase computed tomography (CT)-based radiomic features.

Materials and Methods

A total of 137 consecutive patients with pathologically proven ccRCC (including 96 low-grade [grade 1 or 2] and 41 high-grade [grade 3 or 4] ccRCC) from January 2011 to January 2019 were enrolled in this retrospective study. Target region of interest (ROI) delineation followed by texture extraction was performed on a representative slice with the largest section of the tumor on the four-phase (unenhanced phase [UP], corticomedullary phase [CMP], nephrographic phase [NP] and excretory phase [EP]) CT images. Fifteen concatenations of the four-phase features were fed into 176 classification models (built with 8 classifiers and 22 feature selection methods), the classification performances of the 2640 resultant discriminative models were compared, and the top-ranked features were analyzed.

Results

Image features extracted from the unenhanced phase (UP) CT images demonstrated a dominant classification performance over features from the other three phases. The discriminative model "Bagging + CMIM" achieved the highest classification AUC of 0.75. The top-ranked features from the UP included one shape-based feature and five first-order statistical features.

Conclusion

Image features extracted from the UP are more effective than other CT phases in differentiating low and high nuclear grade ccRCC based on machine learning-based classification modeling.

Nicotinamide Supplementation Attenuates Renal Interstitial Fibrosis via Boosting the Activity of Sirtuins

Background

Progressive tubulointerstitial fibrosis (TIF) is the final common pathway leading to ESRD. There is an urgent need to develop effective approaches slowing the progression of TIF. Previous studies showed that systemic supplementation of nicotinamide (NAM) increases renal NAD⁺ and reverses ischemic-reperfusion induced acute renal injury. However, the role and mechanism of NAM in TIF has been unclear.

Methods

In vivo, we injected NAM (0.25 mg/g) 3 days before unilateral ureter obstruction (UUO) till day 7 post-operation. In vitro, mouse primary proximal tubular epithelial cells (PTCs), rat renal NRK-49F cells, and human renal proximal tubular epithelial cell (HK-2) were pretreated with the indicated concentration of NAM 1 h before incubation with transform growth factor-β1 (TGF-β1) or aristolochic acid (AA) for 24 or 48 h. To evaluate the role of sirtuins (SIRTs), PTCs were pretreated with EX527 or resveratrol 30 min before incubation with NAM and TGF-β1.

Results

In the present study, we demonstrated that NAM supplementation prevented UUO-induced TIF, and AA-induced renal injury. NAM also decreased the expression of pro-fibrotic proteins and pro-inflammatory cytokines (IL-6 and TNF-α) and attenuated interstitial inflammation. In vitro experiment showed that, NAM inhibited AA-induced G2/M arrest of HK-2 cells by downregulating the expression of cyclin G1, a target gene of p53. In addition, NAM inhibited TGF-β1-induced fibroblast proliferation and activation shown as downregulated expression of collagen I, fibronectin, PCNA, cyclin D1, IL-6, and TNF-α. NAM decreased the acetylation of Smad3 and p53. EX527, an inhibitor of SIRT1, reversed the effect of NAM on TGF-β1-induced matrix protein production. However, resveratrol, a SIRT1 activator, did not further boost the protective effect of NAM on reducing matrix protein production.

Conclusions

Taken together, these data indicate that NAM supplementation could inhibit TIF at least partially by boosting the activity of sirtuins.

MicroRNA-181a promotes follicular granulosa cell apoptosis via sphingosine-1-phosphate receptor 1 expression downregulation†

Oxidative stress induces granulosa cell (GC) apoptosis and subsequent follicular atresia. Since our previous studies indicate that microRNA-181a (miR-181a) expression is increased in GCs undergoing apoptosis, the present study was designed to define the relationship between exposure to oxidative stressors in GCs and changes in miR-181a expression and function. To achieve this, we employed an H2O2-induced in vitro model and a 3-nitropropionic acid-induced in vivo model of ovarian oxidative stress. We demonstrated that in vitro miR-181a overexpression promoted GC apoptosis in a dose-dependent manner; sphingosine-1-phosphate (S1P) significantly reversed both H2O2-induced and miR-181a-induced apoptosis in GCs. Moreover, we identified sphingosine-1-phosphate receptor 1 (S1PR1), a critical receptor of S1P, as a novel target of miR-181a in GCs. MicroRNA-181a induced GC apoptosis by repressing S1PR1 expression in vitro. Importantly, increased miR-181a expression and decreased S1PR1 expression were detected in the in vivo ovarian oxidative stress model by Western blot analysis and immunohistochemistry. Furthermore, we found similar expression patterns of miR-181a and S1PR1 in GCs from patients with premature ovarian insufficiency. In conclusion, our results suggest that miR-181a directly suppresses expression of S1PR1, which has critical roles in mediating oxidative stress-induced GC apoptosis both in vitro and in vivo.

Pattern Recognition Receptors and Liver Failure

Liver failure is a clinical syndrome with many causes, a complicated pathogenesis, diverse clinical manifestations, and very high mortality. No effective treatment is yet available. Main pathological processes of liver failure include direct damage to parenchymal and nonparenchymal liver cells that might be caused by viruses or drugs, immune-mediated indirect damage, inflammation, and ischemia-hypoxia injury that further strengthen liver damage and lead to endotoxemia. Among these causes, viral or bacterial components (called pathogen-associated and damage-associated molecular patterns) are released during tissue damage and cell death and may be recognized by pattern recognition receptors (PRRs) to induce secretion of inflammatory cytokines and chemokines and activate immune cells. This process is an important mechanism that underlies the progression of liver failure. Research concerning the roles of PRR signaling pathways in liver failure is expected to result in development of immunomodulatory drugs to target specific disease stages, immune cells, and signal transduction molecules. This article briefly introduces the research status of six main PRRs (Toll-like receptors, nucleotide-binding oligomerization domain-like receptors, retinoic-acid-inducible gene I-like receptors, cytosolic DNA sensors, C-type lectin receptors, and inflammasomes) in acute liver failure and acute-on-chronic liver failure and explores further research directions.

miR-21 reverses impaired decidualization through modulation of KLF12 and NR4A1 expression in human endometrial stromal cells†

Impaired decidualization has been considered a major cause of infertility in adenomyosis. However, the mechanism remains poorly understood. Recent studies suggest that microRNAs (miRNA) play a crucial role in embryo implantation. The aim of the present study was to identify the role of miR-21 in human endometrial stromal cell (hESC) decidualization in vitro. To explore the roles of miR-21 in decidualization, we detected the expression of miR-21 in the endometrium of fertile control and adenomyosis patients, and analyzed the effects of miR-21 on the biological behaviors of hESC decidualization. The results demonstrated that miR-21 was downregulated in the endometrium of adenomyosis patients compared with the control endometrium. miR-21 effectively promoted the expression of the 8Br-cAMP plus medroxyprogesterone acetate (MPA)-induced hESC decidualization marker genes PRL and IGFBP-1 and morphological transformation through the modulation of KLF12 and NR4A1 expression; conversely, inhibition of miR-21 expression compromised hESC decidualization in vitro. In addition, Luciferase reporter, western blotting, and quantitative real-time PCR (qRT-PCR) assays confirmed that miR-21 interacted with the 3' untranslated region of the transcription factor KLF12 and downregulated KLF12 at the transcriptional and translational levels. KLF12 overexpression abolished miR-21-enhanced 8Br-cAMP plus MPA-induced decidualization. Taken together, these results illustrate that miR-21 promotes endometrial decidualization by inhibiting KLF12, and miR-21 overexpression reverses the poor decidual response of hESCs in patients with adenomyosis in vitro.

MiR-512-3p regulates malignant tumor behavior and multi-drug resistance in breast cancer cells via targeting Livin

Breast cancer (BCa) is one of the most lethal malignancies of female reproductive organs. Increasing evidence has revealed that miRNAs participate in both tumorigenesis and multi-drug resistance. MiR-512-3p, a small non-coding RNA (miRNA), was previously found to be upregulated in breast cancer cells. In this study, we first verified that miR-512-3p expression forced a significant reorganization of the tumor architecture, affecting important cellular processes involved in cell-cell contact, cell adhesion and cell motility. Accordingly, induction of miR-512-3p expression significantly enhanced chemosensitivity and decreased metastatic potential in BCa cells. Our study demonstrated that miR-512-3p directly targets the 3'UTR of Livin, thereby decreasing its expression in MCF-7 cells. MiR-512-3p overexpression significantly inhibited breast cancer cell growth and metastasis. Both miR-512-3p overexpression and Livin knockdown significantly increased the chemosensitivity of cancer cells. Epirubicin (EPB), gemcitabine (GCB) and docetaxel (TXT) had antitumor effects in vitro against human breast cancer cell lines, and miR-512-3p overexpression increased tumor sensitivity to these drugs. In addition, miR-512-3p overexpression significantly inhibited tumor growth in vivo. Collectively, our data suggest that miR-512-3p is a significant regulator of tumorigenesis and drug resistance in breast cancer and provides evidence that miR-512-3p may represent a promising target for breast cancer therapy.

Genome-wide identification and characterization of R2R3-MYB genes in Medicago truncatula

MYB is a large family of plant transcription factors. Its function has been identified in several plants, while there are few reports in Medicago truncatula. In this study, we used RNA-seq data to analyze and identify R2R3-MYB genes in the genome of Medicago truncatula. Phylogenetic analysis classified 150 MtMYB genes into 21 subfamilies with homologs. Out of the 150 MtMYB genes, 139 were distributed among 8 chromosomes, with tandem duplications (TD) and segment duplications (SD). Microarray data were used for functional analysis of the MtMYB genes during growth and developmental processes providing evidence for a role in tissues differentiation, seed development processes, and especially the nodulation process. Furthermore, we investigated the expression of MtMYB genes in response to abiotic stresses using RNA-seq data, which confirmed the critical roles in signal transduction and regulation processes under abiotic stress. We used quantitative real-time PCR (qRT-PCR) to validate expression profiles. The expression pattern of M. truncatula MYB genes under different abiotic stress conditions suggest that some may play a major role in cross-talk among different signal transduction pathways in response to abiotic stresses. Our study will serve as a foundation for future research into the molecular function of M. truncatula R2R3-MYB genes.