Notes

Immunomodulatory aftereffect of psoriasis-derived skin mesenchymal stem cellular material on TH1/TH17 cellular material.
Analgesic efficacy of intravenous dexamethasone has not been well defined after caesarean delivery. We performed a systematic review and meta-analysis to evaluate the impact of peri-operative dexamethasone administration on postoperative pain after caesarean delivery.

We investigated the impact of perioperative intravenous dexamethasone on postoperative pain after caesarean delivery. The two primary outcomes of interest were early (4 to 6 h) resting pain scores and time to first rescue analgesia.

A systematic review and meta-analysis of randomised controlled trials (RCTs).

PubMed, EMBASE, Scopus and the Cochrane central registers of controlled trials were searched to identify RCTs from inception to April 2021.

Prospective RCTs comparing the role of intravenous dexamethasone with non-active control were eligible for inclusion. Exclusion criteria included trials comparing various doses of dexamethasone without any control treatment arm, dexamethasone with other active drugs and trials comparing differin postoperative pain scores at rest and a longer time to first rescue analgesia, along with a small but statistically significantly reduced opioid consumption after caesarean delivery compared with nonactive control.
Peri-operative intravenous dexamethasone was associated with a significant decrease in postoperative pain scores at rest and a longer time to first rescue analgesia, along with a small but statistically significantly reduced opioid consumption after caesarean delivery compared with nonactive control.Hepatocellular carcinoma (HCC) remains the second leading cause of cancer related deaths worldwide. Understanding about the molecular biology of HCC and development of targeted therapies are still the main focuses of this type of disease. Here, by connecting the expression levels of FOX proteins with their associated clinical characteristics using TCGA LIHC dataset, we found that 27/40 FOX proteins were highly expressed in HCC tumors compared to normal liver tissues and their expression levels were tightly associated with HCC tumor stage, tumor grade and overall survival. Our experimental results also confirmed that FOXH1 indeed played an oncogenic role in HCC development by promoting cell growth and cell migration/invasion. HOIPIN-8 cell line Mechanistic dissection demonstrated that FOXH1-induced cell growth and cell migration/invasion relied on mTOR signaling because inhibition of mTOR signaling by rapamycin could attenuate FOXH1-mediated phenotypic alterations of HCC cells. The results from orthotopic mouse model also validated that FOXH1 promoted HA22T tumor growth via triggering mTOR activation. Overall, this study not only comprehensively examines the clinical values of FOX proteins in HCC but also provides experimental evidence to support the role of FOXH1 in HCC development, building rationale to develop more effective therapies to treat HCC patients.Mucins are components of the mucus layer overlying the intestinal epithelial cells, which maintains physiological homeostasis. Altered mucin expression is associated with disease progression. Expression of MUC4 decreases in colorectal cancer (CRC); however, its functional role and implications in the intestinal pathology in CRC are not studied well. Therefore, we generated a genetically engineered Muc4 knockout (Muc4-/-) CRC mouse model by crossing with Muc4-/- and Apcflox/flox mice in the presence of colon-specific inducible Cre. We observed that deficiency of Muc4 results in an increased number of macroscopic tumors in the colon and rectal region and leads to poor survival. Further, the absence of Muc4 was associated with goblet cell dysfunction where the expression of intestinal homeostasis molecules (Muc2 and Fam3D) was downregulated. Next, we also observed that loss of Muc4 showed reduced thickness of mucus layer, leading to infiltration of bacteria, reduction in anti-microbial peptides, and upregulation of pro-inflammatory cytokines. Further, Apc gene mutation results in activation of the Wnt/β-catenin signaling pathway that corroborated with an increased nuclear accumulation of β-catenin and activation of its target genes cyclin D1 and c-Myc in Muc4-/- mice was observed. We conclude that the presence of Muc4 is essential for intestinal homeostasis, reduces tumor burden, and improves overall survival.
Sodium homeostasis is disrupted in many cardiovascular diseases, which makes non-invasive sodium storage assessment desirable. In this regard, sodium MRI has shown its potential to reveal differences in sodium content between healthy and diseased tissues as well as treatment-related changes of sodium content. When different tissues are affected disparately, simultaneous assessment of these compartments is expected to provide better information about sodium distribution, reduce examination time, and improve clinical efficiency.

The objectives were (1) to investigate sodium storage levels in calf and pectoral muscle in healthy controls and patients and quantify changes following medical treatment and (2) to demonstrate homogeneous disruption in skeletal muscle sodium storage in patients with primary hyperaldosteronism (PHA).

We assessed sodium storage levels (relative sodium signal intensity, rSSI) in the calf and pectoral muscles of eight patients with PHA prior and after treatment and 12 age- and sex-mancreases 23Na-MRI's clinical feasibility as an innovative technique to monitor sodium storage.During bone formation, mesenchymal progenitor cells mature into bone-forming osteoblasts after undergoing several stages of differentiation. Impaired bone formation is a predominant finding in glucocorticoid (GC)-induced osteoporosis (GIO). Osteoblasts at different stages of maturation can be affected by excessive endogenous or therapeutic GCs. Sex-determining region Y-box 2 (SOX2) is normally expressed in immature osteoblasts, but its overexpression can suppress osteoblast differentiation. This study aimed to evaluate whether GC affects SOX2 expression in osteoblasts, and whether SOX2 contributes to GC-induced inhibition of osteoblast differentiation. Treatment with GCs such as dexamethasone (Dex) or hydrocortisone enhanced SOX2 expression. Silencing SOX2 improved inhibition of GC-induced osteoblast differentiation, whereas SOX2 overexpression decreased mineralized nodule formation and RUNX2 and Osterix expression in MC3T3-E1 cells. On the contrary, when C3H10T1/2 uncommitted mesenchymal stem cells were subjected to SOX2 overexpression, RUNX2 expression increased. As a mechanism of Dex-induced SOX2 upregulation in preosteoblasts, we found that the STAT3 pathway or GC receptor (GR) is involved, using a GR antagonist, STAT3 regulators, and chromatin immunoprecipitation assays. Moreover, mice treated with Dex for 4 weeks showed a notable increase in SOX2 expression in the bones and an increased ratio of procollagen type 1 N-terminal propeptide to osteocalcin in the plasma than in control mice. This study demonstrated that GC enhances SOX2 expression in vitro in osteoblast and in vivo in the mice bone, which affects bone-forming activity differently depending on the differentiation stage of osteoblast-lineage cells. Our results provide new insights into prevention and treatment against impaired bone formation in GIO.Proper detection and accurate characterization of Non-Small Cell Lung Cancer (NSCLC) are an open challenge in the imaging field. Biomedical imaging is fundamental in lung cancer assessment and offers the possibility of calculating predictive biomarkers impacting patients' management. Within this context, radiomics, which consists of extracting quantitative features from digital images, shows encouraging results for clinical applications, but the sub-optimal standardization of the procedure and the lack of definitive results are still a concern in the field. For these reasons, this work proposes the design and development of LuCIFEx, a fully-automated pipeline for non-invasive in-vivo characterization of NSCLC, aiming to speed up the analysis process and enable an early diagnosis of the tumor.LuCIFEx pipeline relies on routinely acquired [18F]FDG-PET/CT images for the automatic segmentation of the cancer lesion, allowing the computation of accurate radiomic features, then employed for cancer characterization through Machine Learning algorithms. The proposed multi-stage segmentation process can identify the lesion with a mean accuracy of 94.2±5.0%. Finally, the proposed data analysis pipeline demonstrates the potential of PET/CT features for the automatic recognition of lung metastases and NSCLC histological subtypes, while highlighting the main current limitations of the radiomic approach.Although the development of computer-aided algorithms for sleep staging is integrated into automatic detection of sleep disorders, most supervised deep learning based models might suffer from insufficient labeled data. While the adoption of semi-supervised learning (SSL) can mitigate the issue, the SSL models are still limited to the lack of discriminative feature extraction for diverse obstructive sleep apnea (OSA) severity. This model deterioration might be exacerbated during the domain adaptation. Such exploration on the alleviation of domain-shift of SSL model between different OSA conditions has attracted more and more attentions from the clinic. In this work, a co-attention meta sleep staging network (CMS2-net) is proposed to simultaneously deal with two issues the inter-class disparity problem and the intra-class selection problem. Within CMS2-net, a co-attention module and a triple-classifier are designed to explicitly refine the coarse feature representations by identifying the class boundary inconsistency. Moreover, the mutual information with meta contrastive variance is introduced to supervise the gradient stream from a multiscale view. The performance of the proposed framework is demonstrated on both public and local datasets. Furthermore, our approach achieves the state-of-the-art SSL results on both datasets.Susceptibility weighted imaging (SWI) is a routine magnetic resonance imaging (MRI) sequence that combines the magnitude and high-pass filtered phase images to qualitatively enhance the image contrasts related to tissue susceptibility. Tremendous amounts of the high-pass filtered phase data with low signal to noise ratio and incomplete background field removal have thus been collected under default clinical settings. Since SWI cannot quantitatively estimate the susceptibility, it is thus non-trivial to derive quantitative susceptibility mapping (QSM) directly from these redundant phase data, which effectively promotes the mining of the SWI data collected previously and even provides potentials for synchronous imaging of both SWI and QSM based on single SWI scanning in future. To this end, a novel deep learning based SWI-to-QSM-Net (S2Q-Net) is proposed for QSM reconstruction from SWI high-pass filtered phase data. S2Q-Net firstly estimates the edge maps of QSM to integrate edge prior into features, which benefits the network to reconstruct QSM with realistic and clear tissue boundaries. Furthermore, a novel Second-order Cross Dense Block is proposed in S2Q-Net, which can capture rich inter-region interactions to provide rich non-local phase information related to local tissue susceptibility. Experimental results on both simulated and in-vivo datasets demonstrate its superiority over all the compared QSM reconstruction methods, including conventional methods and the state-of-the-art DL-based algorithms. Our results suggest the potentials of S2Q-Net to reconstruct promising QSM from the high-pass filtered phase obtained in clinical SWI sequences.
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