5-(Dimethyl­ammonio)naphthalene-1-sulfonate dihydrate

There are two formula units in the asymmetric unit of the title compound, C12H13NO3S·2H2O. In the crystal structure, mol­ecules are linked by inter­molecular O—H⋯O, N—H⋯O and weak C—H⋯O hydrogen bonds, forming a three-dimensional network

[N,N,N′,N′-Tetra­kis(benzimidazol-2-yl­meth­yl)ethane-1,2-diamine]copper(II) sulfate monohydrate

In the title compound, [Cu(C34H32N10)]SO4·H2O, the CuII ion is coordinated by six N atoms of a hexa­dentate N,N,N′,N′-tetra­kis(benzimidazol-2-ylmeth­yl)ethane-1,2-diamine (EDTB) ligand, in a distorted octa­hedral environment. In the crystal structure, inter­molecular N—H⋯O and weak C—H⋯O hydrogen bonds connect the cations, anions and water mol­ecules into a three-dimensional network. The O atoms of the anion are disordered over two sites with refined occupancies of 0.711 (2) and 0.289 (2)

8-Chloro-4-cyclo­hexyl-2H-1,4-benzoxazin-3(4H)-one

In the crystal structure of title compound, C14H16ClNO2, the cyclo­hexyl ring is in a chair conformation. The molecules are connected into centrosymmetric dimers via weak C—H⋯O hydrogen bonds

Dichlorido[tris­(benzimidazol-2-ylmeth­yl)amine]­indium(III) chloride ethanol solvate dihydrate

In the title complex, [InCl2(C24H21N7)]Cl·C2H5OH·2H2O, the InIII ion is coordinated by four N atoms from the tris­(benz­imidazol-2-ylmeth­yl)amine (NTB) ligand and two Cl atoms in a distorted octa­hedral environment. In the crystal structure, inter­molecular N—H⋯O, O—H⋯O, O—H⋯Cl and weak C—H⋯Cl hydrogen bonds connect the cations, anions and solvent mol­ecules into a three-dimensional network. The ethanol solvent mol­ecule is disordered over two sites with refined occupancies of 0.54 (2) and 0.46 (2)

Genes and Small RNA Transcripts Exhibit Dosage-Dependent Expression Pattern in Maize Copy-Number Alterations

Copy-number alterations are widespread in animal and plant genomes, but their immediate impact on gene expression is still unclear. In animals, copy-number alterations usually exhibit dosage effects, except for sex chromosomes which tend to be dosage compensated. In plants, genes within small duplications (\u3c100 kb) often exhibit dosage-dependent expression, whereas large duplications (\u3e50 Mb) are more often dosage compensated. However, little or nothing is known about expression in moderately-sized (1–50 Mb) segmental duplications, and about the response of small RNAs to dosage change. Here, we compared maize (Zea mays) plants with two, three, and four doses of a 14.6-Mb segment of chromosome 1 that contains ∼300 genes. Plants containing the duplicated segment exhibit dosage-dependent effects on ear length and flowering time. Transcriptome analyses using GeneChip and RNA-sequencing methods indicate that most expressed genes and unique small RNAs within the duplicated segments exhibit dosage-dependent transcript levels. We conclude that dosage effect is the predominant regulatory response for both genes and unique small RNA transcripts in the segmental dosage series we tested. To our knowledge this is the first analysis of small RNA expression in plant gene dosage variants. Because segmental duplications comprise a significant proportion of eukaryotic genomes, these findings provide important new insight into the regulation of genes and small RNAs in response to dosage changes

Ethyl 2-[(Z)-2-benzyl­hydrazin-1-yl­idene]-2-bromo­acetate

In the title compound, C11H13BrN2O2, the dihedral angle between the phenyl ring and the almost planar (r.m.s. deviation = 0.011 Å) C—C(Br)=N—N(H)— fragment is 74.94 (16)°. In the crystal, mol­ecules are linked by N—H⋯O hydrogen bonds, which generate C(6) chains propagating in [010]. Weak aromatic π–π stacking [centroid–centroid separation = 3.784 (3) Å] may also help to consolidate the packing

CTooth+: A Large-scale Dental Cone Beam Computed Tomography Dataset and Benchmark for Tooth Volume Segmentation

Accurate tooth volume segmentation is a prerequisite for computer-aided dental analysis. Deep learning-based tooth segmentation methods have achieved satisfying performances but require a large quantity of tooth data with ground truth. The dental data publicly available is limited meaning the existing methods can not be reproduced, evaluated and applied in clinical practice. In this paper, we establish a 3D dental CBCT dataset CTooth+, with 22 fully annotated volumes and 146 unlabeled volumes. We further evaluate several state-of-the-art tooth volume segmentation strategies based on fully-supervised learning, semi-supervised learning and active learning, and define the performance principles. This work provides a new benchmark for the tooth volume segmentation task, and the experiment can serve as the baseline for future AI-based dental imaging research and clinical application development