A novel compound heterozygous variant of ECEL1 induced joint dysfunction and cartilage degradation: a case report and literature review

BackgroundDistal arthrogryposis type 5D (DA5D) represents a subtype of distal arthrogryposis (DA) characterized by congenital joint contractures in the distal extremities. DA5D is inherited in a rare autosomal recessive manner and is associated with the ECEL1 gene. In this report, we describe a case of an infant with bilateral knee contractures and ptosis, caused by a novel compound heterozygous mutation of ECEL1.Case presentationWe conducted DNA extraction, whole-exome sequencing analysis, and mutation analysis of ECEL1 to obtain genetic data on the patient. We subsequently analyzed the patient’s clinical and genetic data. The proband was a 6 months-old male infant who presented with significant bilateral knee contracture disorders and bilateral ptosis. MRI demonstrated cartilage degradation in knee joint. Whole-exome sequencing of the patient’s DNA revealed a compound heterozygous mutation of c.2152-15C>A and c.110_155del in ECEL1. Analysis with the MutationTaster application indicated that c.110_155del was pathogenic (probability = 1), causing frameshift mutations affecting 151 amino acids (p.F37Cfs*151). The truncated protein lost the substructure of a transmembranous site based on the predicted protein crystal structure AF-O95672-F1. The variant of c.2152-15C>A of ECEL1 was also predicted to be disease-causing (probability = 0.98) as it impaired the methylation of ECEL1 serving as an H3K27me3 modification site, which led to the dysfunction of the second topological domain. Therefore, we concluded that the compound heterozygous mutation caused the pathogenic phenotype of this proband.ConclusionThe present case highlights the usefulness of molecular genetic screening in diagnosing unexpected joint disorder. Identification of novel mutations in the ECEL1 gene broadens the mutation spectrum of this gene and adds to the genotype-phenotype map of DA5D. Furthermore, rapid whole-exome sequencing analysis enabled timely diagnosis of this rare disease, facilitating appropriate treatment and scheduled follow-up to improve clinical outcomes

Phenotypic Pattern-Based Assay for Dynamically Monitoring Host Cellular Responses to Salmonella Infections

The interaction between mammalian host cells and bacteria is a dynamic process, and the underlying pathologic mechanisms are poorly characterized. Limited information describing the host-bacterial interaction is based mainly on studies using label-based endpoint assays that detect changes in cell behavior at a given time point, yielding incomplete information. In this paper, a novel, label-free, real-time cell-detection system based on electronic impedance sensor technology was adapted to dynamically monitor the entire process of intestinal epithelial cells response to Salmonella infection. Changes in cell morphology and attachment were quantitatively and continuously recorded following infection. The resulting impedance-based time-dependent cell response profiles (TCRPs) were compared to standard assays and showed good correlation and sensitivity. Biochemical assays further suggested that TCRPs were correlated with cytoskeleton-associated morphological dynamics, which can be largely attenuated by inhibitions of actin and microtubule polymerization. Collectively, our data indicate that cell-electrode impedance measurements not only provide a novel, real-time, label-free method for investigating bacterial infection but also help advance our understanding of host responses in a more physiological and continuous manner that is beyond the scope of current endpoint assays

3D dictionary learning based iterative cone beam CT reconstruction

Purpose: This work is to develop a 3D dictionary learning based cone beam CT (CBCT) reconstruction algorithm on graphic processing units (GPU) to improve the quality of sparse-view CBCT reconstruction with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3 × 3 × 3 was trained from a large number of blocks extracted from a high quality volume image. On the basis, we utilized cholesky decomposition based orthogonal matching pursuit algorithm to find the sparse representation of each block. To accelerate the time-consuming sparse coding in the 3D case, we implemented the sparse coding in a parallel fashion by taking advantage of the tremendous computational power of GPU. Conjugate gradient least square algorithm was adopted to minimize the data fidelity term. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with tight frame (TF) by performing reconstructions on a subset data of 121 projections. Results: Compared to TF based CBCT reconstruction that shows good overall performance, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, remove more streaking artifacts and also induce less blocky artifacts. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppress the noise, and hence to achieve high quality reconstruction under the case of sparse view. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential clinical application.-------------------------------Cite this article as: Bai T, Yan H, Shi F, Jia X, Lou Y, Xu Q, Jiang S, Mou X. 3D dictionary learning based iterative cone beam CT reconstruction. Int J Cancer Ther Oncol 2014; 2(2):020240. DOI: 10.14319/ijcto.0202.4

Hsf transcription factor gene family in peanut (Arachis hypogaea L.): genome-wide characterization and expression analysis under drought and salt stresses

Heat shock transcription factors (Hsfs) play important roles in plant developmental regulations and various stress responses. In present study, 46 Hsf genes in peanut (AhHsf) were identified and analyzed. The 46 AhHsf genes were classed into three groups (A, B, and C) and 14 subgroups (A1-A9, B1-B4, and C1) together with their Arabidopsis homologs according to phylogenetic analyses, and 46 AhHsf genes unequally located on 17 chromosomes. Gene structure and protein motif analysis revealed that members from the same subgroup possessed similar exon/intron and motif organization, further supporting the results of phylogenetic analyses. Gene duplication events were found in peanut Hsf gene family via syntenic analysis, which were important in Hsf gene family expansion in peanut. The expression of AhHsf genes were detected in different tissues using published data, implying that AhHsf genes may differ in function. In addition, several AhHsf genes (AhHsf5, AhHsf11, AhHsf20, AhHsf24, AhHsf30, AhHsf35) were induced by drought and salt stresses. Furthermore, the stress-induced member AhHsf20 was found to be located in nucleus. Notably, overexpression of AhHsf20 was able to enhance salt tolerance. These results from this study may provide valuable information for further functional analysis of peanut Hsf genes

Rif1 Maintains Telomere Length Homeostasis of ESCs by Mediating Heterochromatin Silencing

SummaryTelomere length homeostasis is essential for genomic stability and unlimited self-renewal of embryonic stem cells (ESCs). We show that telomere-associated protein Rif1 is required to maintain telomere length homeostasis by negatively regulating Zscan4 expression, a critical factor for telomere elongation by recombination. Depletion of Rif1 results in terminal hyperrecombination, telomere length heterogeneity, and chromosomal fusions. Reduction of Zscan4 by shRNA significantly rescues telomere recombination defects of Rif1-depleted ESCs and associated embryonic lethality. Further, Rif1 negatively modulates Zscan4 expression by maintaining H3K9me3 levels at subtelomeric regions. Mechanistically, Rif1 interacts and stabilizes H3K9 methylation complex. Thus, Rif1 regulates telomere length homeostasis of ESCs by mediating heterochromatic silencing

Prevalence of JC Virus in Chinese Patients with Colorectal Cancer

BACKGROUND: JCV is a DNA polyomavirus very well adapted to humans. Although JCV DNA has been detected in colorectal cancers (CRC), the association between JCV and CRC remains controversial. In China, the presence of JCV infection in CRC patients has not been reported. Here, we investigated JCV infection and viral DNA load in Chinese CRC patients and to determine whether the JCV DNA in peripheral blood (PB) can be used as a diagnostic marker for JCV-related CRC. METHODOLOGY/PRINCIPAL FINDINGS: Tumor tissues, non-cancerous tumor-adjacent tissues and PB samples were collected from 137 CRC patients. In addition, 80 normal colorectal tissue samples from patients without CRC and PB samples from 100 healthy volunteers were also harvested as controls. JCV DNA was detected by nested PCR and glass slide-based dot blotting. Viral DNA load of positive samples were determined by quantitative real-time PCR. JCV DNA was detected in 40.9% (56/137) of CRC tissues at a viral load of 49.1 to 10.3×10(4) copies/µg DNA. Thirty-four (24.5%) non-cancerous colorectal tissues (192.9 to 4.4×10(3) copies/µg DNA) and 25 (18.2%) PB samples (81.3 to 4.9×10(3) copies/µg DNA) from CRC patients were positive for JCV. Tumor tissues had higher levels of JCV than non-cancerous tissues (P = 0.003) or PB samples (P<0.001). No correlation between the presence of JCV and demographic or medical characteristics was observed. The JCV prevalence in PB samples was significantly associated with the JCV status in tissue samples (P<0.001). Eleven (13.8%) normal colorectal tissues and seven (7.0%) PB samples from healthy donors were positive for JCV. CONCLUSIONS/SIGNIFICANCE: JCV infection is frequently present in colorectal tumor tissues of CRC patients. Although the association between JCV presence in PB samples and JCV status in tissue samples was identified in this study, whether PB JCV detection can serve as a marker for JCV status of CRC requires further study

Methylprednisolone as Adjunct to Endovascular Thrombectomy for Large-Vessel Occlusion Stroke

Importance It is uncertain whether intravenous methylprednisolone improves outcomes for patients with acute ischemic stroke due to large-vessel occlusion (LVO) undergoing endovascular thrombectomy. Objective To assess the efficacy and adverse events of adjunctive intravenous low-dose methylprednisolone to endovascular thrombectomy for acute ischemic stroke secondary to LVO. Design, Setting, and Participants This investigator-initiated, randomized, double-blind, placebo-controlled trial was implemented at 82 hospitals in China, enrolling 1680 patients with stroke and proximal intracranial LVO presenting within 24 hours of time last known to be well. Recruitment took place between February 9, 2022, and June 30, 2023, with a final follow-up on September 30, 2023.InterventionsEligible patients were randomly assigned to intravenous methylprednisolone (n = 839) at 2 mg/kg/d or placebo (n = 841) for 3 days adjunctive to endovascular thrombectomy. Main Outcomes and Measures The primary efficacy outcome was disability level at 90 days as measured by the overall distribution of the modified Rankin Scale scores (range, 0 [no symptoms] to 6 [death]). The primary safety outcomes included mortality at 90 days and the incidence of symptomatic intracranial hemorrhage within 48 hours. Results Among 1680 patients randomized (median age, 69 years; 727 female [43.3%]), 1673 (99.6%) completed the trial. The median 90-day modified Rankin Scale score was 3 (IQR, 1-5) in the methylprednisolone group vs 3 (IQR, 1-6) in the placebo group (adjusted generalized odds ratio for a lower level of disability, 1.10 [95% CI, 0.96-1.25]; P = .17). In the methylprednisolone group, there was a lower mortality rate (23.2% vs 28.5%; adjusted risk ratio, 0.84 [95% CI, 0.71-0.98]; P = .03) and a lower rate of symptomatic intracranial hemorrhage (8.6% vs 11.7%; adjusted risk ratio, 0.74 [95% CI, 0.55-0.99]; P = .04) compared with placebo. Conclusions and Relevance Among patients with acute ischemic stroke due to LVO undergoing endovascular thrombectomy, adjunctive methylprednisolone added to endovascular thrombectomy did not significantly improve the degree of overall disability.Trial RegistrationChiCTR.org.cn Identifier: ChiCTR210005172

Genome-Wide Identification and Characterization of the OPR Gene Family in Wheat (<i>Triticum aestivum</i> L.)

The 12-oxo-phytodienoic acid reductases (OPRs), which belong to the old yellow enzyme (OYE) family, are flavin mononucleotide (FMN)-dependent oxidoreductases with critical functions in plants. Despite the clear characteristics of growth and development, as well as the defense responses in Arabidopsis, tomato, rice, and maize, the potential roles of OPRs in wheat are not fully understood. Here, forty-eight putative OPR genes were found and classified into five subfamilies, with 6 in sub. I, 4 in sub. II, 33 in sub. III, 3 in sub. IV, and 2 in sub. V. Similar gene structures and conserved protein motifs of TaOPRs in wheat were identified in the same subfamilies. An analysis of cis-acting elements in promoters revealed that the functions of OPRs in wheat were mostly related to growth, development, hormones, biotic, and abiotic stresses. A total of 14 wheat OPR genes were identified as tandem duplicated genes, while 37 OPR genes were segmentally duplicated genes. The expression patterns of TaOPRs were tissue- and stress-specific, and the expression of TaOPRs could be regulated or induced by phytohormones and various stresses. Therefore, there were multiple wheat OPR genes, classified into five subfamilies, with functional diversification and specific expression patterns, and to our knowledge, this was the first study to systematically investigate the wheat OPR gene family. The findings not only provide a scientific foundation for the comprehensive understanding of the wheat OPR gene family, but could also be helpful for screening more candidate genes and breeding new varieties of wheat, with a high yield and stress resistance

Predicting central lymph node metastasis in patients with papillary thyroid carcinoma based on ultrasound radiomic and morphological features analysis

Abstract Objectives To build a combined model based on the ultrasound radiomic and morphological features, and evaluate its diagnostic performance for preoperative prediction of central lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC). Method A total of 295 eligible patients, who underwent preoperative ultrasound scan and were pathologically diagnosed with unifocal PTC were included at our hospital from October 2019 to July 2022. According to ultrasound scanners, patients were divided into the training set (115 with CLNM; 97 without CLNM) and validation set (45 with CLNM; 38 without CLNM). Ultrasound radiomic, morphological, and combined models were constructed using multivariate logistic regression. The diagnostic performance was assessed by the area under the curve (AUC) of the receiver operating characteristic curve, accuracy, sensitivity, and specificity. Results A combined model was built based on the morphology, boundary, length diameter, and radiomic score. The AUC was 0.960 (95% CI, 0.924–0.982) and 0.966 (95% CI, 0.901–0.993) in the training and validation set, respectively. Calibration curves showed good consistency between prediction and observation, and DCA demonstrated the clinical benefit of the combined model. Conclusion Based on ultrasound radiomic and morphological features, the combined model showed a good performance in predicting CLNM of patients with PTC preoperatively

3D dictionary learning based iterative cone beam CT reconstruction

Purpose: This work is to develop a 3D dictionary learning based cone beam CT (CBCT) reconstruction algorithm on graphic processing units (GPU) to improve the quality of sparse-view CBCT reconstruction with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3 × 3 × 3 was trained from a large number of blocks extracted from a high quality volume image. On the basis, we utilized cholesky decomposition based orthogonal matching pursuit algorithm to find the sparse representation of each block. To accelerate the time-consuming sparse coding in the 3D case, we implemented the sparse coding in a parallel fashion by taking advantage of the tremendous computational power of GPU. Conjugate gradient least square algorithm was adopted to minimize the data fidelity term. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with tight frame (TF) by performing reconstructions on a subset data of 121 projections. Results: Compared to TF based CBCT reconstruction that shows good overall performance, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, remove more streaking artifacts and also induce less blocky artifacts. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppress the noise, and hence to achieve high quality reconstruction under the case of sparse view. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential clinical application.-------------------------------Cite this article as: Bai T, Yan H, Shi F, Jia X, Lou Y, Xu Q, Jiang S, Mou X. 3D dictionary learning based iterative cone beam CT reconstruction. Int J Cancer Ther Oncol 2014; 2(2):020240. DOI: 10.14319/ijcto.0202.40</p