Identification of novel TMEM231 gene splice variants and pathological findings in a fetus with Meckel Syndrome

Background: Meckel Syndrome (MKS, OMIM #249000) is a rare and fatal autosomal recessive ciliopathy with high clinical and genetic heterogeneity. MKS shows complex allelism with other related ciliopathies such as Joubert Syndrome (JBTS, OMIM #213300). In MKS, the formation and function of the primary cilium is defective, resulting in a multisystem disorder including occipital encephalocele, polycystic kidneys, postaxial polydactyly, liver fibrosis, central nervous system malformations and genital anomalies. This study aimed to analyze the genotype of MKS patients and investigate the correlation between genotype and phenotype.Methods: A nonconsanguineous couple who conceived four times with a fetus affected by multiorgan dysfunction and intrauterine fetal death was studied. Whole exome sequencing (WES) was performed in the proband to identify the potentially pathogenic variant. Sanger sequencing was performed in family members. In silico tools were used to analyse the pathogenicity of the identified variants. cDNA TA-cloning sequencing was performed to validate the effects of intronic variants on mRNA splicing. Quantitative real-time PCR was performed to investigate the effect of the variants on gene expression. Immunofluorescence was performed to observe pathological changes of the primary cilium in kidney tissue from the proband.Results: Two splice site variants of TMEM231 (NM_001077418.2, c.583-1G>C and c.583-2_588delinsTCCTCCC) were identified in the proband, and the two variants have not been previously reported. The parents were confirmed as carriers. The two variants were predicted to be pathogenic by in silico tools and were classified as pathogenic/likely pathogenic variants according to the American College of Medical Genetics and Genomics guideline. cDNA TA cloning analysis showed that both splice site variants caused a deletion of exon 5. RT-PCR revealed that the expression of TMEM231 was significantly decreased and immunofluorescence showed that the primary cilium was almost absent in the proband’s kidney tissue.Conclusion: We reported the clinical, genetic, molecular and histochemical characterisation of a family affected by MKS. Our findings not only extended the mutation spectrum of the TMEM231 gene, but also revealed for the first time the pathological aetiology of primary cilia in humans and provide a basis for genetic counselling of the parents to their offspring

Controlled Growth of Carbon Spheres Through the Mg-Reduction Route

Hollow spheres, hollow capsules and solid spheres of carbon were selectively synthesized by Mg-reduction of hexachlorobutadiene at appropriate reaction conditions. X-ray powder diffraction and Raman spectra reveal that the as-prepared materials have a well-ordered structure. A possible formation mechanism has been proposed

Research on the Upgrading Path of Regional Equipment Manufacturing Industry

Constructing the upgrading path of regional equipment manufacturing industry based on innovation network is of great significance for solving the transformation and upgrading problems of regional equipment manufacturing industry in China, further catching up with the development level of equipment manufacturing industry in developed countries, and alleviating the regional gap. Based on literature analysis and industrial upgrading theory, this paper puts forward the basic principles and general ideas of upgrading path design of regional equipment manufacturing industry, focusing on designing industrial upgrading path based on key common technologies, industrial upgrading path based on industrial chain optimization and industrial upgrading path based on innovation platform, and finally puts forward corresponding countermeasures and suggestions

Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks

With success of Deep Belief Networks (DBNs) in computer vision, DBN has attracted great attention in hyperspectral classification. Many deep learning based algorithms have been focused on deep feature extraction for classification improvement. Multi-features, such as texture feature, are widely utilized in classification process to enhance classification accuracy greatly. In this paper, a novel hyperspectral classification framework based on an optimal DBN and a novel texture feature enhancement (TFE) is proposed. Through band grouping, sample band selection and guided filtering, the texture features of hyperspectral data are improved. After TFE, the optimal DBN is employed on the hyperspectral reconstructed data for feature extraction and classification. Experimental results demonstrate that the proposed classification framework outperforms some state-of-the-art classification algorithms, and it can achieve outstanding hyperspectral classification performance. Furthermore, our proposed TFE method can play a significant role in improving classification accuracy

Metabolomics Reveals Changes in Metabolite Profiles among Pre-Diapause, Diapause and Post-Diapause Larvae of Sitodiplosis mosellana (Diptera: Cecidomyiidae)

Sitodiplosis mosellana, a notorious pest of wheat worldwide, copes with temperature extremes during harsh summers and winters by entering obligatory diapause as larvae. However, the metabolic adaptive mechanism underlying this process is largely unknown. In this study, we performed a comparative metabolomics analysis on S. mosellana larvae at four programmed developmental stages, i.e., pre-diapause, diapause, low temperature quiescence and post-diapause development. In total, we identified 54 differential metabolites based on pairwise comparisons of the four groups. Of these metabolites, 37 decreased in response to diapause, including 4 TCA cycle intermediates (malic acid, citric acid, fumaric acid, α-ketoglutaric acid), 2 saturated fatty acids (palmitic acid, stearic acid) and most amino acids. In contrast, nine metabolites, including trehalose, glycerol, mannitol, proline, alanine, oleic acid and linoleic acid were significantly higher in both the diapause and quiescent stages than the other two stages. In addition to two of them (trehalose, proline), glutamine was also significantly highest in the cold quiescence stage. These elevated metabolites could function as cryoprotectants and/or energy reserves. These findings suggest that the reduced TCA cycle activity and elevated biosynthesis of functional metabolites are most likely responsible for maintaining low metabolic activity and cold tolerance during diapause, which is crucial for the survival and post-diapause development of this pest

Metabolomics Reveals Changes in Metabolite Profiles among Pre-Diapause, Diapause and Post-Diapause Larvae of <i>Sitodiplosis mosellana</i> (Diptera: Cecidomyiidae)

Sitodiplosis mosellana, a notorious pest of wheat worldwide, copes with temperature extremes during harsh summers and winters by entering obligatory diapause as larvae. However, the metabolic adaptive mechanism underlying this process is largely unknown. In this study, we performed a comparative metabolomics analysis on S. mosellana larvae at four programmed developmental stages, i.e., pre-diapause, diapause, low temperature quiescence and post-diapause development. In total, we identified 54 differential metabolites based on pairwise comparisons of the four groups. Of these metabolites, 37 decreased in response to diapause, including 4 TCA cycle intermediates (malic acid, citric acid, fumaric acid, α-ketoglutaric acid), 2 saturated fatty acids (palmitic acid, stearic acid) and most amino acids. In contrast, nine metabolites, including trehalose, glycerol, mannitol, proline, alanine, oleic acid and linoleic acid were significantly higher in both the diapause and quiescent stages than the other two stages. In addition to two of them (trehalose, proline), glutamine was also significantly highest in the cold quiescence stage. These elevated metabolites could function as cryoprotectants and/or energy reserves. These findings suggest that the reduced TCA cycle activity and elevated biosynthesis of functional metabolites are most likely responsible for maintaining low metabolic activity and cold tolerance during diapause, which is crucial for the survival and post-diapause development of this pest

Hyperspectral and LiDAR Data Fusion Classification Using Superpixel Segmentation-Based Local Pixel Neighborhood Preserving Embedding

A new method of superpixel segmentation-based local pixel neighborhood preserving embedding (SSLPNPE) is proposed for the fusion of hyperspectral and light detection and ranging (LiDAR) data based on the extinction profiles (EPs), superpixel segmentation and local pixel neighborhood preserving embedding (LPNPE). A new workflow is proposed to calibrate the Goddard&rsquo;s LiDAR, hyperspectral and thermal (G-LiHT) data, which allows our method to be applied to actual data. Specifically, EP features are extracted from both sources. Then, the derived features of each source are fused by the SSLPNPE. Using the labeled samples, the final label assignment is produced by a classifier. For the open standard experimental data and the actual data, experimental results prove that the proposed method is fast and effective in hyperspectral and LiDAR data fusion

Table_1_Effect of plantation age on plant and soil C:N:P stoichiometry in Kentucky bluegrass pastures.DOCX

Plant and soil C:N:P stoichiometry reflects the element content and energy flow, which are important for biogeochemical cycling in ecosystems. Although plantation age has been verified to affect leaf C:N:P stoichiometry in alfalfa plants, its effect on plant and soil C:N:P stoichiometry in grass remains poorly documented. A 10-year field experiment of Kentucky bluegrass (Poa pratensis) was used to test how plantation age affect plant and soil C:N:P stoichiometry in a perennial rhizomatous grass pasture. This study demonstrated that leaf C:N, C:P, and N:P ratios exhibited a rapid increasing trend from 2 to 6 years of age, whereas leaf C:N showed a slight decreasing trend, and leaf C:P and N:P maintained stability from 6 to 9 years of age. Stem C:N and N:P were not different among plantation ages, while stem C:P increased from 2 to 4 years of plantation age and then maintained stability from 4 to 9 years of plantation age. Root N:P showed an increasing trend from 2 to 6 years of plantation age and relative stability from 6 to 9 years of plantation age, whereas root C:N and C:P showed decreasing trends from 2 to 9 years of plantation age. Although soil C:P did not differ among nine plantation ages, soil C:N and N:P remained relatively stable from 2 to 6 years of plantation age. However, soil C:N showed a decreasing trend, while soil N:P showed an increasing trend after 6 years of plantation age. The results from an ecological stoichiometric homeostasis analysis further showed that N in the leaf, stem, and root and P in the stem had strict homeostasis, whereas P in the leaf and root showed plastic and weakly homeostatic status, respectively. These results present a pattern concerning the plantation age in relation to plant and soil C:N:P stoichiometry in a perennial grass and provide useful information for N and P management in Kentucky bluegrass pastures.</p