Giant placental chorioangioma presenting as severe polyhydramnios: a case report

Chorioangiomas are the most common non-trophoblastic, benign, vascular tumour of the hemochorial placenta. Small chorioangiomas are usually symptomless, and of no clinical significance while giant ones more than 4 cm in diameter may be complicated by polyhydramnios, foetal cardiomegaly, hydrops fetalis, and foetal growth restriction. We present a case of a 32-year-old primigravida referred to us at 30 weeks of gestation with large placental chorioangioma causing polyhydramnios which was treated by amnioreduction twice over 1 month. On referral the tumour size was about 56 mm size with severe polyhydramnios with amniotic fluid index of 57 cm, with breathlessness and pain abdomen. After relevant investigations and informed consent, she was taken up for caesarean section. 2 litres of clear liquor drained. She delivered a live female baby weighing 1.2 kg with Apgar score of 7 and 8. Patient stood the operation well. Gross and microscopic examination of the placenta confirmed the diagnosis of chorioangioma. Chorioangioma should be considered as differential diagnosis in cases of hydrops fetalis or polyhydramnios. Doppler ultrasound is the method of choice to detect chorioangioma and its vascularity. Giant chorioangiomas complicating pregnancy can be managed conservatively with close surveillance, foetal monitoring and timely intervention to prevent maternal and foetal morbidity and mortality.

Rhizosphere dynamics of inoculated cyanobacteria and their growth-promoting role in rice crop

Nitrogen fixing cyanobacteria are the predominant flora in waterlogged paddy fields which contribute significantly towards nitrogen budgeting in these ecosystems. Their establishment and role in plant growth promotion and soil microbial activity is poorly known. Under greenhouse conditions, pots were inoculated with one of a set of twenty cyanobacterial strains isolated from the rhizosphere of diverse rice and wheat varieties. Several strains established in the soil and persisted up to the harvest stage in soil and roots, significantly enhancing soil microbial biomass carbon, available nitrogen, and related soil microbiological parameters, and increased grain yields and grain weight. This can help in selecting promising strains for developing carrier-based inoculants to promote the growth of crop and soil microflora, leading to enhanced soil fertility and crop yields

EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy

Traversing terrain with good traction is crucial for achieving fast off-road navigation. Instead of manually designing costs based on terrain features, existing methods learn terrain properties directly from data via self-supervision, but challenges remain to properly quantify and mitigate risks due to uncertainties in learned models. This work efficiently quantifies both aleatoric and epistemic uncertainties by learning discrete traction distributions and probability densities of the traction predictor's latent features. Leveraging evidential deep learning, we parameterize Dirichlet distributions with the network outputs and propose a novel uncertainty-aware squared Earth Mover's distance loss with a closed-form expression that improves learning accuracy and navigation performance. The proposed risk-aware planner simulates state trajectories with the worst-case expected traction to handle aleatoric uncertainty, and penalizes trajectories moving through terrain with high epistemic uncertainty. Our approach is extensively validated in simulation and on wheeled and quadruped robots, showing improved navigation performance compared to methods that assume no slip, assume the expected traction, or optimize for the worst-case expected cost.Comment: Under review. Journal extension for arXiv:2210.00153. Project website: https://xiaoyi-cai.github.io/evora

An efficient algorithm for systematic analysis of nucleotide strings suitable for siRNA design

<p>Abstract</p> <p>Background</p> <p>The "off-target" silencing effect hinders the development of siRNA-based therapeutic and research applications. Existing solutions for finding possible locations of siRNA seats within a large database of genes are either too slow, miss a portion of the targets, or are simply not designed to handle a very large number of queries. We propose a new approach that reduces the computational time as compared to existing techniques.</p> <p>Findings</p> <p>The proposed method employs tree-based storage in a form of a modified truncated suffix tree to sort all possible short string substrings within given set of strings (i.e. transcriptome). Using the new algorithm, we pre-computed a list of the best siRNA locations within each human gene ("siRNA seats"). siRNAs designed to reside within siRNA seats are less likely to hybridize off-target. These siRNA seats could be used as an input for the traditional "set-of-rules" type of siRNA designing software. The list of siRNA seats is available through a publicly available database located at <url>http://web.cos.gmu.edu/~gmanyam/siRNA_db/search.php</url></p> <p>Conclusions</p> <p>In attempt to perform top-down prediction of the human siRNA with minimized off-target hybridization, we developed an efficient algorithm that employs suffix tree based storage of the substrings. Applications of this approach are not limited to optimal siRNA design, but can also be useful for other tasks involving selection of the characteristic strings specific to individual genes. These strings could then be used as siRNA seats, as specific probes for gene expression studies by oligonucleotide-based microarrays, for the design of molecular beacon probes for Real-Time PCR and, generally, any type of PCR primers.</p

Mucosal Healing in Ulcerative Colitis: A Comprehensive Review

Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by periods of remission and periods of relapse. Patients often present with symptoms such as rectal bleeding, diarrhea and weight loss, and may require hospitalization and even colectomy. Long-term complications of UC include decreased quality of life and productivity and an increased risk of colorectal cancer. Mucosal healing (MH) has gained progressive importance in the management of UC patients. In this article, we review the endoscopic findings that define both mucosal injury and MH, and the strengths and limitations of the scoring systems currently available in clinical practice. The basic mechanisms behind colonic injury and MH are covered, highlighting the pathways through which different drugs exert their effect towards reducing inflammation and promoting epithelial repair. A comprehensive review of the evidence for approved drugs for UC to achieve and maintain MH is provided, including a section on the pharmacokinetics of anti-tumor necrosis factor (TNF)-alpha drugs. Currently approved drugs with proven efficacy in achieving MH in UC include salicylates, corticosteroids (induction only), calcineurin inhibitors (induction only), thiopurines, vedolizumab and anti-TNF alpha drugs (infliximab, adalimumab, and golimumab). MH is of crucial relevance in the outcomes of UC, resulting in lower incidences of clinical relapse, the need for hospitalization and surgery, as well as reduced rates of dysplasia and colorectal cancer. Finally, we present recent evidence towards the need for a more strict definition of complete MH as the preferred endpoint for UC patients, using a combination of both endoscopic and histological findings.info:eu-repo/semantics/publishedVersio

A Network-Based Approach to Prioritize Results from Genome-Wide Association Studies

Genome-wide association studies (GWAS) are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI), a network-based method that combines GWAS data with human protein-protein interaction data (PPI). NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call ‘trait prioritized sub-networks.’ As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn’s disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn’s disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses

The Role of Proteasome Beta Subunits in Gastrin-Mediated Transcription of Plasminogen Activator Inhibitor-2 and Regenerating Protein1

The hormone gastrin physiologically regulates gastric acid secretion and also contributes to maintaining gastric epithelial architecture by regulating expression of genes such as plasminogen activator inhibitor 2 (PAI-2) and regenerating protein 1(Reg1). Here we examine the role of proteasome subunit PSMB1 in the transcriptional regulation of PAI-2 and Reg1 by gastrin, and its subcellular distribution during gastrin stimulation. We used the gastric cancer cell line AGS, permanently transfected with the CCK2 receptor (AGS-GR) to study gastrin stimulated expression of PAI-2 and Reg1 reporter constructs when PSMB1 was knocked down by siRNA. Binding of PSMB1 to the PAI-2 and Reg1 promoters was assessed by chromatin immunoprecipitation (ChIP) assay. Subcellular distribution of PSMB1 was determined by immunocytochemistry and Western Blot. Gastrin robustly increased expression of PAI-2 and Reg1 in AGS-GR cells, but when PSMB1 was knocked down the responses were dramatically reduced. In ChIP assays, following immunoprecipitation of chromatin with a PSMB1 antibody there was a substantial enrichment of DNA from the gastrin responsive regions of the PAI-2 and Reg1 promoters compared with chromatin precipitated with control IgG. In AGS-GR cells stimulated with gastrin there was a significant increase in the ratio of nuclear:cytoplasmic PSMB1 over the same timescale as recruitment of PSMB1 to the PAI-2 and Reg1 promoters seen in ChIP assays. We conclude that PSMB1 is part of the transcriptional machinery required for gastrin stimulated expression of PAI-2 and Reg1, and that its change in subcellular distribution in response to gastrin is consistent with this role