Directional TV algorithm for image reconstruction from sparse-view projections in EPR imaging.

OBJECTIVE: Electron paramagnetic resonance (EPR) imaging is an advanced in vivo oxygen imaging modality. The main drawback of EPR imaging is the long scanning time. Sparse-view projections collection is an effective fast scanning pattern. However, the commonly-used filtered backprojection (FBP) algorithm is not competent to accurately reconstruct images from sparse-view projections because of the severe streak artifacts. The aim of this work is to develop an advanced algorithm for sparse reconstruction of 3D EPR imaging. METHODS: The optimization based algorithms including the total variation (TV) algorithm have proven to be effective in sparse reconstruction in EPR imaging. To further improve the reconstruction accuracy, we propose the directional TV (DTV) model and derive its Chambolle-Pock (CP) solving algorithm. RESULTS: After the algorithm correctness validation on simulation data, we explore the sparse reconstruction capability of the DTV algorithm via a simulated six-sphere phantom and two real bottle phantoms filled with OX063 trityl solution and scanned by an EPR imager with a magnetic field strength of 250G. CONCLUSION: Both the simulated and real data experiments show that the DTV algorithm is superior to the existing FBP and TV-type algorithms and a deep learning based method according to visual inspection and quantitative evaluations in sparse reconstruction of EPR imaging. SIGNIFICANCE: These insights gained in this work may be used in the development of fast EPR imaging workflow of practical significance.

Directional TV algorithm for fast EPR imaging.

Precise radiation guided by oxygen images has demonstrated superiority over the traditional radiation methods. Electron paramagnetic resonance (EPR) imaging has proven to be the most advanced oxygen imaging modality. However, the main drawback of EPR imaging is the long scan time. For each projection, we usually need to collect the projection many times and then average them to achieve high signal-to-noise ratio (SNR). One approach to fast scan is to reduce the repeating time for each projection. While the projections would be noisy and thus the traditional commonly-use filtered backprojection (FBP) algorithm would not be capable of accurately reconstructing images. Optimization-based iterative algorithms may accurately reconstruct images from noisy projections for they may incorporate prior information into optimization models. Based on the total variation (TV) algorithms for EPR imaging, in this work, we propose a directional TV (DTV) algorithm to further improve the reconstruction accuracy. We construct the DTV constrained, data divergence minimization (DTVcDM) model, derive its Chambolle-Pock (CP) solving algorithm, validate the correctness of the whole algorithm, and perform evaluations via simulated and real data. The experimental results show that the DTV algorithm outperforms the existing TV and FBP algorithms in fast EPR imaging. Compared to the standard FBP algorithm, the proposed algorithm may achieve 10 times of acceleration.

A dense and U-shaped transformer with dual-domain multi-loss function for sparse-view CT reconstruction.

OBJECTIVE: CT image reconstruction from sparse-view projections is an important imaging configuration for low-dose CT, as it can reduce radiation dose. However, the CT images reconstructed from sparse-view projections by traditional analytic algorithms suffer from severe sparse artifacts. Therefore, it is of great value to develop advanced methods to suppress these artifacts. In this work, we aim to use a deep learning (DL)-based method to suppress sparse artifacts. METHODS: Inspired by the good performance of DenseNet and Transformer architecture in computer vision tasks, we propose a Dense U-shaped Transformer (D-U-Transformer) to suppress sparse artifacts. This architecture exploits the advantages of densely connected convolutions in capturing local context and Transformer in modelling long-range dependencies, and applies channel attention to fusion features. Moreover, we design a dual-domain multi-loss function with learned weights for the optimization of the model to further improve image quality. RESULTS: Experimental results of our proposed D-U-Transformer yield performance improvements on the well-known Mayo Clinic LDCT dataset over several representative DL-based models in terms of artifact suppression and image feature preservation. Extensive internal ablation experiments demonstrate the effectiveness of the components in the proposed model for sparse-view computed tomography (SVCT) reconstruction. SIGNIFICANCE: The proposed method can effectively suppress sparse artifacts and achieve high-precision SVCT reconstruction, thus promoting clinical CT scanning towards low-dose radiation and high-quality imaging. The findings of this work can be applied to denoising and artifact removal tasks in CT and other medical images.

MiR-155-5p improves the insulin sensitivity of trophoblasts by targeting CEBPB in gestational diabetes mellitus.

INTRODUCTION: Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication featuring impaired insulin sensitivity. MiR-155-5p is associated with various metabolic diseases. However, its specific role in GDM remains unclear. CCAAT enhancer binding protein beta (CEBPB), a critical role in regulating glucolipid metabolism, has been identified as a potential target of miR-155-5p. This study aims to investigate the impact of miR-155-5p and CEBPB on insulin sensitivity of trophoblasts in GDM. METHODS: Placental tissues were obtained from GDM and normal pregnant women; miR-155-5p expression was then evaluated by RT‒qPCR and CEBPB expression by western blot and immunohistochemical staining. To investigate the impact of miR-155-5p on insulin sensitivity and CEBPB expression, HTR-8/SVneo cells were transfected with either miR-155-5p mimic or inhibitor under basal and insulin-stimulated conditions. Cellular glucose uptake consumption was quantified using a glucose assay kit. Furthermore, the targeting relationship between miR-155-5p and CEBPB was validated using a dual luciferase reporter assay. RESULTS: Reduced miR-155-5p expression and elevated CEBPB expression were observed in GDM placentas and high glucose treated HTR8/SVneo cells. The overexpression of miR-155-5p significantly enhanced insulin signaling and glucose uptake in trophoblasts. Conversely, inhibiting miR-155-5p induced the opposite effects. Additionally, CEBPB was directly targeted and negatively regulated by miR-155-5p in HTR8/SVneo cells. Silencing CEBPB effectively restored the inhibitory effect of miR-155-5p downregulation on insulin sensitivity in trophoblasts. DISCUSSION: These findings suggest that miR-155-5p could enhance insulin sensitivity in trophoblasts by targeting CEBPB, highlighting the potential of miR-155-5p as a therapeutic target for improving the intrauterine hyperglycemic environment in GDM.

Analysis, validation, and discussion of key genes in placenta of patients with gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) is a common complication during pregnancy, which can have harmful health consequences for both the mother and the fetus. Given the placenta's crucial role as an endocrine organ during pregnancy, exploring and validating key genes in the placenta hold significant potential in the realm of GDM prevention and treatment. In this study, differentially expressed genes (DEGs) were identified from two databases, GSE70493 and PRJNA646212, and verified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in placenta tissues. DEGs expression was detected in normal or high-glucose-treated HTR8/SVneo cells. We also investigated the relationship between DEGs and glucose levels in GDM patients. By selecting the intersection of the two databases, we screened 20 DEGs, which were validated in GDM patients. We observed an up-regulation of SLAMF, ALDH1A2, and CHI3L2, and a down-regulation of HLA-E, MYH11, HLA-DRB5, ITGAX, GZMB, NAIP, TMEM74B, RANBP3L, PAEP, WT-1, and CEP170. We conducted further investigations into the expression of DEGs in HTR8/SVneo cells exposed to high glucose, revealing a significant upregulation in the expression of SERPINA3, while the expressions of HLA-E, BCL6, NAIP, PAEP, MUC16, WT-1, and CEP170 were decreased. Moreover, some DEGs were confirmed to have a positive or negative correlation with blood glucose levels of GDM patients through correlation analysis. The identified DEGs are anticipated to exert potential implications in the prevention and management of GDM, thereby offering potential benefits for improving pregnancy outcomes and long-term prognosis of fetuses among individuals affected by GDM.

Long-term outcomes of offspring from multiple gestations: a two-sample Mendelian randomization study on multi-system diseases using UK Biobank and FinnGen databases.

BACKGROUND: Assisted reproductive technologies (ART) have increased the incidence of multiple births, which can have a negative impact on maternal and offspring health. The study aimed to investigate the association between genetically predicted multiple birth and the risk of 42 common diseases of the nervous, psychiatric, cardiovascular, respiratory, digestive, and endocrine systems. METHODS: The study utilized two-sample Mendelian randomization (MR) analysis to explore the potential causal relationship between genetically predicted multiple birth and the genetically predicted risk of diseases. The study used the FinnGen and UK Biobank datasets for analysis. RESULTS: The study found no significant causal relationship between multiple birth and psychiatric disorders. However, the lower limits of the 95% confidence intervals for bipolar affective disorder and anxiety disorders were not robust, indicating a need for further investigation. The study found that multiple birth may be a strong risk factor for infantile cerebral palsy, and caution is necessary in both natural and ART multiple births. The study revealed a potential causal relationship between multiple birth and coronary heart disease, ischemic heart disease, and deep vein thrombosis, which may be related to abnormal intrauterine environments in multiple pregnancies. Surprisingly, multiple birth appears to have a protective effect against some respiratory diseases, such as chronic obstructive pulmonary disease and asthma. CONCLUSIONS: The study highlights the need for caution regarding the risk of infantile cerebral palsy, cardiovascular diseases, and psychiatric disorders in multiple birth. Our study can lead to the development of preventive strategies and improved clinical management for affected infants.

CGP-Uformer: A low-dose CT image denoising Uformer based on channel graph perception.

BACKGROUND: An effective method for achieving low-dose CT is to keep the number of projection angles constant while reducing radiation dose at each angle. However, this leads to high-intensity noise in the reconstructed image, adversely affecting subsequent image processing, analysis, and diagnosis. OBJECTIVE: This paper proposes a novel Channel Graph Perception based U-shaped Transformer (CGP-Uformer) network, aiming to achieve high-performance denoising of low-dose CT images. METHODS: The network consists of convolutional feed-forward Transformer (ConvF-Transformer) blocks, a channel graph perception block (CGPB), and spatial cross-attention (SC-Attention) blocks. The ConvF-Transformer blocks enhance the ability of feature representation and information transmission through the CNN-based feed-forward network. The CGPB introduces Graph Convolutional Network (GCN) for Channel-to-Channel feature extraction, promoting the propagation of information across distinct channels and enabling inter-channel information interchange. The SC-Attention blocks reduce the semantic difference in feature fusion between the encoder and decoder by computing spatial cross-attention. RESULTS: By applying CGP-Uformer to process the 2016 NIH AAPM-Mayo LDCT challenge dataset, experiments show that the peak signal-to-noise ratio value is 35.56 and the structural similarity value is 0.9221. CONCLUSIONS: Compared to the other four representative denoising networks currently, this new network demonstrates superior denoising performance and better preservation of image details.

Mating-induced prolactin surge is not required for subsequent neurogenesis in male mice.

Parenting involves major behavioral transitions that are supported by coordinated neuroendocrine and physiological changes to promote the onset of novel offspring-directed behaviors. In comparison to maternal care, however, the mechanisms underlying the transition to paternal care are less understood. Male laboratory mice are predominantly infanticidal as virgins but show paternal responses 2 weeks after mating. Interestingly, males show a mating-induced surge of prolactin, which we hypothesized may be involved in initiating this behavioral transition. During pregnancy, prolactin stimulates olfactory bulb neurogenesis, which is essential for maternal behavior. Mating induces olfactory bulb neurogenesis in males, but it is unknown whether this is driven by prolactin or is important for subsequent paternal care. New olfactory neurons are generated from cells in the subventricular zone (SVZ) and take about 2 weeks to migrate to the olfactory bulb, which may account for the delayed behavioral change in mated males. We investigated whether mating increases cell proliferation at the SVZ. Males were either mated, exposed to receptive female cues, or left alone (control) and injected with Bromodeoxyuridine (BrdU, a marker of cell division). Contrary to our hypothesis, we found that mating decreased cell proliferation in the caudal lateral portion of the SVZ. Next, we tested whether prolactin itself mediates cell proliferation in the SVZ and/or new cell survival in the olfactory bulb by administering bromocriptine (prolactin inhibitor), vehicle, or bromocriptine + prolactin prior to mating. While suppressing prolactin had no effect on cell proliferation in the SVZ, administering exogenous prolactin resulted in significantly higher BrdU-labeled cells in mated but not virgin male mice. No effects of prolactin were observed on new olfactory cell survival. Taken together, prolactin may have context-dependent effects on new cell division in the SVZ, while other unknown mechanisms may be driving the effects on new olfactory cell survival following mating.

DHA supplementation and pregnancy complications.

Docosahexaenoic acid (DHA) supplementation is recommended for women during pregnancy because of its neurological, visual, and cognitive effects. Previous studies have suggested that DHA supplementation during pregnancy may prevent and treat certain pregnancy complications. However, there are contradictions in the current related studies, and the specific mechanism by which DHA acts remains unclear. This review summarizes the research on the relationship between DHA intake during pregnancy and preeclampsia, gestational diabetes mellitus, preterm birth, intrauterine growth restriction, and postpartum depression. Furthermore, we explore the impact of DHA intake during pregnancy on the prediction, prevention, and treatment of pregnancy complications as well as its impact on offspring neurodevelopment. Our results suggest that there is limited and controversial evidence for the protective effect of DHA intake on pregnancy complications, with the exception of preterm birth and gestational diabetes mellitus. However, additional DHA supplementation may improve long-term neurodevelopmental outcomes in the offspring of women with pregnancy complications.

The role of chemerin in the regulation of cGAS-STING pathway in gestational diabetes mellitus placenta.

Recent studies already confirmed that placenta mitochondrial dysfunction is associated with the progression of gestational diabetes mellitus (GDM). Besides, a possible relationship between adipokine chemerin and disulfide-bond A oxidoreductase-like protein (DsbA-L) had been revealed, whereas the potential interaction remains unclear. In addition, very little is still known about the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway and its mechanisms of action in the context of GDM. The present study aims to investigate the underlying mechanism of cGAS-STING pathway and its regulatory relationship with chemerin in GDM. A total of 50 participants, including 25 cases of GDM patients and 25 pregnant women with normal glucose tolerance, were enrolled, and their placenta tissues at term labor were collected. Besides, an insulin resistance cell model was established on the human trophoblastic cell line to explore the molecular mechanism of chemerin on cGAS-STING pathway. Results showed that there were mitochondrial pathological changes in GDM placenta, accompanied by the decreased expression of DsbA-L, increased level of chemerin, and the activation of cGAS-STING pathway. In the insulin resistant cell model, overexpression of chemerin upregulated protein expression of DsbA-L, and recombinant chemerin presented time-dependent inhibition on the cGAS-STING pathway, but this effect was not dependent on DsbA-L. In conclusion, elevated chemerin is probably a protective mechanism, which may be a potential therapeutic strategy for GDM.

Role of melatonin receptor 1B gene polymorphism and its effect on the regulation of glucose transport in gestational diabetes mellitus.

Melatonin receptor 1B (MT2, encoded by the MTNR1B gene), a high-affinity receptor for melatonin, is associated with glucose homeostasis including glucose uptake and transport. The rs10830963 variant in the MTNR1B gene is linked to glucose metabolism disorders including gestational diabetes mellitus (GDM); however, the relationship between MT2-mediated melatonin signaling and a high birth weight of GDM infants from maternal glucose abnormality remains poorly understood. This article aims to investigate the relationship between rs10830963 variants and GDM development, as well as the effects of MT2 receptor on glucose uptake and transport in trophoblasts. TaqMan-MGB (minor groove binder) probe quantitative real-time polymerase chain reaction (qPCR) assays were used for rs10930963 genotyping. MT2 expression in the placenta of GDM and normal pregnant women was detected by immunofluorescence, western blot, and qPCR. The relationship between MT2 and glucose transporters (GLUTs) or peroxisome proliferator-activated receptor γ (PPARγ) was established by western blot, and glucose consumption of trophoblasts was measured by a glucose assay kit. The results showed that the genotype and allele frequencies of rs10830963 were significantly different between GDM and normal pregnant women (P<0.05). The fasting, 1-h and 2-h plasma glucose levels of G-allele carriers were significantly higher than those of C-allele carriers (P<0.05). Besides, the protein and messenger RNA (mRNA) expression of MT2 in the placenta of GDM was significantly higher than that of normal pregnant women (P<0.05). Melatonin could stimulate glucose uptake and GLUT4 and PPARγ protein expression in trophoblasts, which could be attenuated by MT2 receptor knockdown. In conclusion, the rs10830963 variant was associated with an increased risk of GDM. The MT2 receptor is essential for melatonin to raise glucose uptake and transport, which may be mediated by PPARγ.

Low-dose asprin use during pregnancy may be a potential risk for postpartum hemorrhage and increased blood loss: a systematic review and meta-analysis.

OBJECTIVE: The association between aspirin use during pregnancy and the risk of postpartum hemorrhage remains unclear. This study aimed to explore the incidence of postpartum hemorrhage and the amount of postpartum blood loss among women who used aspirin during pregnancy. DATA SOURCES: From inception to October 2022, this study searched the following databases: MEDLINE, Web of Science, Embase, and the Cochrane Central Register of Controlled Trials. STUDY ELIGIBILITY CRITERIA: Studies comparing pregnancy outcomes that covered the incidence of postpartum hemorrhage or the amount of postpartum blood loss in pregnancies with aspirin vs placebo (or no aspirin) were included. METHODS: Reviewers separately ascertained studies, obtained data, and gauged study quality. The meta-analysis was conducted using a random effects model owing to the probable heterogeneity of the included studies. The rates of postpartum hemorrhage or the mean amounts of postpartum blood loss were compared, and the odds ratios or mean differences with 95% confidence intervals were estimated. Of note, 2 parts performed both a pooled analysis of randomized controlled trials and cohort studies and a separate analysis of randomized controlled trials. RESULTS: Overall, 21 studies with 373,926 women were included in the postpartum hemorrhage part, and 7 studies with 10,163 women were included in the postpartum blood loss part. The results suggested that aspirin (dose 60-150mg a day) use during pregnancy was associated with an increased incidence of postpartum hemorrhage (odds ratio, 1.20; 95% confidence interval, 1.07-1.34). When only randomized controlled trials were retained, the results remained significant (odds ratio, 1.12; 95% confidence interval, 1.00-1.25). In the second part, higher total blood loss after delivery was obtained (mean difference, 12.85 mL; 95% confidence interval, 3.28-22.42), and the result was unaltered when cohort studies were eliminated (mean difference, 13.72 mL; 95% confidence interval, 4.63-22.81). The conclusions are more likely to be obtained in developed countries. CONCLUSION: Low-dose aspirin use during pregnancy is a potential risk of postpartum hemorrhage and does slightly increase the amount of postpartum blood loss. Without denying the combined value of aspirin, our conclusions raised an alarm for clinicians about postpartum hemorrhage in women using aspirin during pregnancy.

miR-17-5p Promotes Glucose Uptake of HTR8/SVneo Trophoblast Cells by Inhibiting TXNIP/NLRP3 Inflammasome Pathway.

Introduction: Gestational diabetes mellitus (GDM) is one of the common metabolic disorders of pregnancy and results in poor pregnancy outcomes for both mother and fetus. MiR-17-5p is considered as the strongest predictor of metabolic syndrome status, but the relationship between GDM and miR-17-5p remains unclear. TXNIP, which leads to activation of NLRP3, is considered as a potential target of miR-17-5p, and the miR-17-5p/TXNIP/NLRP3 axis has been shown to play a major role in the occurrence and development of many metabolic diseases but has not been validated in GDM. Methods: MiR-17-5p was detected by RT-qPCR. The expression of TXNIP and NLRP3 in placenta was detected by immunofluorescence, RT-qPCR and Western blot. To explore the effect of miR-17-5p on TXNIP and NLRP3 and glucose uptake of HTR8/SVneo cells, miR-17-5p mimic and miR-17-5p inhibitor were transfected to achieve overexpression and inhibition. The interaction between miR-17-5p and TXNIP was confirmed by dual-luciferase reporter assay. Besides, glucose consumption of trophoblast cells was detected by glucose assay kit. Results: MiR-17-5p expression was down-regulated, while the expression of TXNIP and NLRP3 was up-regulated in GDM placental tissues. MiR-17-5p targeted TXNIP and inhibited its expression. MiR-17-5p also regulated NLRP3 expression and glucose uptake of HTR8/SVneo cells, which could be reversed by overexpression of TXNIP, suggesting that miR-17-5p improved glucose uptake of HTR8/SVneo cells by TXNIP/NLRP3 axis. The results were consistent with the above findings in high-glucose treated HTR8/SVneo cells. Conclusion: Our results suggested that miR-17-5p ameliorates the glucose uptake of HTR8/SVneo cells by TXNIP/NLRP3 axis, which may provide a new idea for offspring health of GDM patients.