Mutations in WNT10B Are Identified in Individuals with Oligodontia

Supplemental Data Supplemental Data include six figures and three tables and can be found with this article online at http://dx.doi.org/10.1016/j.ajhg.2016.05.012. Supplemental Data Document S1. Figures S1–S6 and Tables S1–S3 Download Document S2. Article plus Supplemental Data Download Web Resources Allen Brain Atlas, http://www.brain-map.org/ Eurexpress, http://www.eurexpress.org/ee/ ExAC Browser, http://exac.broadinstitute.org/ GEO Profiles, http://www.ncbi.nlm.nih.gov/geoprofiles HGMD, http://www.biobase-international.com/product/hgmd MutationTaster, http://www.mutationtaster.org/ OMIM, http://www.omim.org RefSeq, http://www.ncbi.nlm.nih.gov/refseq/ Tooth agenesis is one of the most common developmental anomalies in humans. Oligodontia, a severe form of tooth agenesis, is genetically and phenotypically a heterogeneous condition. Although significant efforts have been made, the genetic etiology of dental agenesis remains largely unknown. In the present study, we performed whole-exome sequencing to identify the causative mutations in Chinese families in whom oligodontia segregates with dominant inheritance. We detected a heterozygous missense mutation (c.632G>A [p.Arg211Gln]) in WNT10B in all affected family members. By Sanger sequencing a cohort of 145 unrelated individuals with non-syndromic oligodontia, we identified three additional mutations (c.569C>G [p.Pro190Arg], c.786G>A [p.Trp262∗], and c.851T>G [p.Phe284Cys]). Interestingly, analysis of genotype-phenotype correlations revealed that mutations in WNT10B affect the development of permanent dentition, particularly the lateral incisors. Furthermore, a functional assay demonstrated that each of these mutants could not normally enhance the canonical Wnt signaling in HEPG2 epithelial cells, in which activity of the TOPFlash luciferase reporter was measured. Notably, these mutant WNT10B ligands could not efficiently induce endothelial differentiation of dental pulp stem cells. Our findings provide the identification of autosomal-dominant WNT10B mutations in individuals with oligodontia, which increases the spectrum of congenital tooth agenesis and suggests attenuated Wnt signaling in endothelial differentiation of dental pulp stem cells

Continuous theta burst stimulation over right cerebellum for speech impairment in Parkinson’s disease: study protocol for a randomized, sham-controlled, clinical trial

BackgroundSpeech impairment is a common symptom of Parkinson’s disease (PD) that worsens with disease progression and affects communication and quality of life. Current pharmacological and surgical treatments for PD have inconsistent effects on speech impairment. The cerebellum is an essential part of sensorimotor network that regulates speech production and becomes dysfunctional in PD. Continuous theta-burst stimulation (cTBS) is a non-invasive brain stimulation technique that can modulate the cerebellum and its connections with other brain regions.ObjectiveTo investigate whether cTBS over the right cerebellum coupled with speech-language therapy (SLT) can improve speech impairment in PD.MethodsIn this randomized controlled trial (RCT), 40 patients with PD will be recruited and assigned to either an experimental group (EG) or a control group (CG). Both groups will receive 10 sessions of standard SLT. The EG will receive real cTBS over the right cerebellum, while the CG will receive sham stimulation. Blinded assessors will evaluate the treatment outcome at three time points: pre-intervention, post-intervention, and at a 12-week follow-up. The primary outcome measures are voice/speech quality and neurobehavioral parameters of auditory-vocal integration. The secondary outcome measures are cognitive function, quality of life, and functional connectivity determined by resting-state functional magnetic resonance imaging (fMRI).SignificanceThis trial will provide evidence for the efficacy and safety of cerebellar cTBS for the treatment of speech impairment in PD and shed light on the neural mechanism of this intervention. It will also have implications for other speech impairment attributed to cerebellar dysfunctions.Clinical trial registrationwww.chictr.org.cn, identifier ChiCTR2100050543

Wolbachia Infections in Anopheles gambiae Cells: Transcriptomic Characterization of a Novel Host-Symbiont Interaction

The endosymbiotic bacterium Wolbachia is being investigated as a potential control agent in several important vector insect species. Recent studies have shown that Wolbachia can protect the insect host against a wide variety of pathogens, resulting in reduced transmission of parasites and viruses. It has been proposed that compromised vector competence of Wolbachia-infected insects is due to up-regulation of the host innate immune system or metabolic competition. Anopheles mosquitoes, which transmit human malaria parasites, have never been found to harbor Wolbachia in nature. While transient somatic infections can be established in Anopheles, no stable artificially-transinfected Anopheles line has been developed despite numerous attempts. However, cultured Anopheles cells can be stably infected with multiple Wolbachia strains such as wAlbB from Aedes albopictus, wRi from Drosophila simulans and wMelPop from Drosophila melanogaster. Infected cell lines provide an amenable system to investigate Wolbachia-Anopheles interactions in the absence of an infected mosquito strain. We used Affymetrix GeneChip microarrays to investigate the effect of wAlbB and wRi infection on the transcriptome of cultured Anopheles Sua5B cells, and for a subset of genes used quantitative PCR to validate results in somatically-infected Anopheles mosquitoes. Wolbachia infection had a dramatic strain-specific effect on gene expression in this cell line, with almost 700 genes in total regulated representing a diverse array of functional classes. Very strikingly, infection resulted in a significant down-regulation of many immune, stress and detoxification-related transcripts. This is in stark contrast to the induction of immune genes observed in other insect hosts. We also identified genes that may be potentially involved in Wolbachia-induced reproductive and pathogenic phenotypes. Somatically-infected mosquitoes had similar responses to cultured cells. The data show that Wolbachia has a profound and unique effect on Anopheles gene expression in cultured cells, and has important implications for mechanistic understanding of Wolbachia-induced phenotypes and potential novel strategies to control malaria

Moderate and Large Deviations for the Smoothed Estimate of Sample Quantiles

We derive the moderate and large deviations principle for the smoothed sample quantile from a sequence of independent and identically distributed samples of size

Moderate and Large Deviations for the Smoothed Estimate of Sample Quantiles

We derive the moderate and large deviations principle for the smoothed sample quantile from a sequence of independent and identically distributed samples of size n

Handwritten Font Classification Method Based on Ghost Imaging

With the rapid development of the economy， financial services such as bills are also increasing day by day. Among them， the important information in the bill business， such as personal vouchers， checks， and other bills， requires manual reading and input of a large amount of digital information. In order to avoid the waste of human and financial resources， related researchers classify and recognize handwritten fonts based on the neural network classification idea of ​​deep learning. When the method based on deep learning is used for feature extraction of handwritten fonts， there is often a lack of detailed information such as edges and textures， which leads to the problem of low recognition accuracy. Aiming at the problem that the features of handwritten digits or letters are difficult to effectively extract， the recognition efficiency was not high and even caused recognition errors， a new automatic recognition method of handwritten digits or letters was proposed by combining the principle of ghost imaging and the classification network based on deep learning. This method utilizes the principle of ghost imaging. It can save the imaging process in the traditional image recognition method， and jumping out of the inherent thinking that identifying objects is identifying images， and can quickly classify the image of handwritten digits and letters only by the total light intensity value transmitted by handwritten digits or letters without extracting and identifying features of handwritten digits or letters. The automatic recognition of handwritten digits or letters based on ghost imaging solves the critical problem of needing to extract digits or letter images features in traditional handwritten font recognition methods， and can greatly improve the recognition efficiency of handwritten digits or letters. Firstly， a ghost imaging detection system is built using commonly used optical instruments such as lasers， digital micromirror arrays， and single-pixel detectors. The laser in the built detection system is used to generate a pseudothermal light source， and the digital micromirror array is used to obtain the Hadamard speckle sequence with a resolution of 32×32 irradiating the target object at different times. And realizing the irradiation of 17 239 handwritten images of handwritten digits and letters. Secondly， the single-pixel detector is used to collect data on the total light intensity value transmitted by the handwritten digits and letters. The data collection process is very fast and does not cause huge time costs. The value of the bucket detector after the collection is converted into a one-dimensional vector， and use the one-dimensional vector corresponds to the handwritten font as the input of network training. Finally， the network framework is built based on the advantages of the convolutional neural network in image classification and is used to solve the problems in the training process. The network degradation problem is added to the residual block structure， which can directly pass shallow information to deeper layers by skipping one or several layers through skip connections. In order to solve the problem of overfitting， the Dropout layer is added to it， and the robustness of the network to the loss of specific neuron connections is improved by reducing the weight. The experimental results show that： for handwritten digits， compared with the fully connected network， the precision， recall rate and F1 value of the convolutional neural network model are increased by 86.50%/97.25%， 86.40%/98.03%， 86.31%/97.60%； for handwritten letters， the precision， recall， and F1 value of the convolutional neural network under full sampling are 91.87%， 90%， and 90.23%， respectively. At the same time， in the case of undersampling and non-undersampling， the ten types of digits from 0 to 9 under the two models of convolutional neural network and fully connected neural network and randomly selected l， v， y， z， m， n， o， r， s， and h ten types of letters are compared and analyzed. The experimental results show that the accuracy rate of each type of digit and letter of the convolutional neural network is higher than that of the fully connected network under the same conditions. The accuracy of each type of digit and letter under the two models further verifies that as the sampling rate increases， the recognition accuracy also increases. By comparing the evaluation indicators of the convolutional neural network and the fully connected network architecture， the effectiveness and rationality of the proposed method are further illustrated. The classification and recognition results of handwritten letters verified by experiments further illustrate the versatility of the constructed convolutional neural network. It provides the possibility for the wide application of handwritten fonts in real life. The research on the classification and the recognition of handwritten fonts based on ghost imaging can effectively solve the bottleneck problem of low recognition efficiency of existing font recognition methods

A Novel Lactobacilli-Based Teat Disinfectant for Improving Bacterial Communities in the Milks of Cow Teats with Subclinical Mastitis

Teat disinfection pre- and post-milking is important for the overall health and hygiene of dairy cows. The objective of this study was to evaluate the efficacy of a novel probiotic lactobacilli-based teat disinfectant based on changes in somatic cell count (SCC) and profiling of the bacterial community. A total of 69 raw milk samples were obtained from eleven Holstein-Friesian dairy cows over 12 days of teat dipping in China. Single molecule, real-time sequencing technology (SMRT) was employed to profile changes in the bacterial community during the cleaning protocol and to compare the efficacy of probiotic lactic acid bacteria (LAB) and commercial teat disinfectants. The SCC gradually decreased following the cleaning protocol and the SCC of the LAB group was slightly lower than that of the commercial disinfectant (CD) group. Our SMRT sequencing results indicate that raw milk from both the LAB and CD groups contained diverse microbial populations that changed over the course of the cleaning protocol. The relative abundances of some species were significantly changed during the cleaning process, which may explain the observed bacterial community differences. Collectively, these results suggest that the LAB disinfectant could reduce mastitis-associated bacteria and improve the microbial environment of the cow teat. It could be used as an alternative to chemical pre- and post-milking teat disinfectants to maintain healthy teats and udders. In addition, the Pacific Biosciences SMRT sequencing with the full-length 16S ribosomal RNA gene was shown to be a powerful tool for monitoring changes in the bacterial population during the cleaning protocol