PAX9 and MSX1 are transcription factors that play essential roles in craniofacial and limb development. In humans, mutations in both genes are associated with nonsyndromic and syndromic oligodontia, respectively. We screened one family with nonsyndromic oligodontia for mutations in PAX9 and MSX1. Single stranded conformational polymorphism (SSCP) analysis and sequencing revealed a novel heterozygous C139T transition in PAX9 in the affected members of the family. There were no mutations detected in the entire coding sequence of MSX1. The C139T mutation, predicted to result in the substitution of an arginine by a tryptophan (R47W) in the N-terminal subdomain, affected conserved residues in the PAX9 paired domain. To elucidate the pathogenic mechanism producing oligodontia phenotype caused by this mutation, we analyzed the binding of wild-type and mutant PAX9 paired domain protein to double-stranded DNA targets. The R47W mutation dramatically reduced DNA binding suggesting that the mutant protein with consequent haploinsufficiency results in a clinical phenotype.

Our research aimed to look into the clinical traits and genetic mutations in sporadic non-syndromic anodontia and to gain insight into the role of mutations of PAX9, MSX1, AXIN2 and EDA in anodontia phenotypes, especially for the PAX9.Material and Methods:The female proband and her family members from the ethnic Han families underwent complete oral examinations and received a retrospective review. Venous blood samples were obtained to screen variants in the PAX9, MSX1, AXIN2, and EDA genes. A case-control study was performed on 50 subjects with sporadic tooth agenesis (cases) and 100 healthy controls, which genotyped a PAX9 gene polymorphism (rs4904210). Results:Intra-oral and panoramic radiographs revealed that the female proband had anodontia denoted by the complete absence of teeth in both the primary and secondary dentitions, while all her family members maintained normal dentitions. Detected in the female proband were variants of the PAX9 and AXIN2 including A240P (rs4904210) of the PAX9, c.148C>T (rs2240308), c.1365A>G (rs9915936) and c.1386C>T (rs1133683) of the AXIN2. The same variants were present in her unaffected younger brother. The PAX9 variations were in a different state in her parents. Mutations in the MSX1 and EDA genes were not identified. No significant diferences were found in the allele and genotype frequencies of the PAX9 polymorphism between the controls and the subjects with sporadic tooth agenesis. Conclusions:These results suggest that the association of A240P with sporadic tooth agenesis still remains obscure, especially for different populations. The genotype/phenotype correlation in congenital anodontia should be verified.

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Low-light environments have posed a formidable challenge for robust unmanned aerial vehicle (UAV) tracking even with state-of-the-art (SOTA) trackers since the potential image features are hard to extract under adverse light conditions. Besides, due to the low visibility, accurate online selection of the object also becomes extremely difficult for human monitors to initialize UAV tracking in ground control stations. To solve these problems, this work proposes a novel enhancer, i.e., HighlightNet, to light up potential objects for both human operators and UAV trackers. By employing Transformer, HighlightNet can adjust enhancement parameters according to global features and is thus adaptive for the illumination variation. Pixel-level range mask is introduced to make HighlightNet more focused on the enhancement of the tracking object and regions without light sources. Furthermore, a soft truncation mechanism is built to prevent background noise from being mistaken for crucial features. Evaluations on image enhancement benchmarks demonstrate HighlightNet has advantages in facilitating human perception. Experiments on the public UAVDark135 benchmark show that HightlightNet is more suitable for UAV tracking tasks than other state-of-theart (SOTA) low-light enhancers. In addition, real-world tests on a typical UAV platform verify HightlightNet's practicability and efficiency in nighttime aerial tracking-related applications. The code and demo videos are available at https://github. com/vision4robotics/HighlightNet.