A Machine Learning Approach for Identifying Novel Cell Type–Specific Transcriptional Regulators of Myogenesis

Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA–based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type–specific developmental gene expression patterns

Pure Piezoelectricity Generation by a Flexible Nanogenerator Based on Lead Zirconate Titanate Nanofibers

Lead zirconate titanate (PbZr0.52Ti0.48O3, PZT) alloys have been extensively studied to be used for piezoelectric nanogenerators to harvest energy from mechanical motions. In this study, PZT nanofiber-based nanogenerators were fabricated to test their true piezoelectric performance without the triboelectric effect. Aligned PZT nanofibers were fabricated by a sol–gel electrospinning process. The thickness, area, and orientation of the PZT textile made by electrospinning a PZT solution onto multipair metal wires or metal mesh were controlled to form a composite textile. After the calcination, the PZT textile mixed with polydimethylsiloxane was placed between two flexible indium-doped tin oxide–polyethylene naphthalate substrates. The performance parameters of the nanogenerators were investigated under the bending motion, which excludes the triboelectric effect. An assembled nanogenerator of an area of 8 cm2 and a thickness of 80 μm could generate an electrical output voltage of 1.1 V and a current of 1.4 μA under the bending strain. The piezoelectric voltage depended on the thickness of the PZT textile, whereas the piezoelectric current depended on both the thickness and the area of the PZT textile. The electrical performance of the device was significantly affected by the orientation of the PZT fiber and the bending direction. The output voltage and the output current were strain-dependent, whereas the total integrated charge was independent of the strain rate. The properties of the flexible nanogenerator could be quantified to verify the pure piezoelectric performance of the device

Impact of 9/11-Induced Adverse Experiences on the Mental Health of Latino Americans and the Role of Religious Service Attendance

Much research has documented the mental health consequences of the terrorist attacks of September 11, 2001; however, little is known about how the 9/11 attacks affect the mental health of Latino Americans. This study uses a nationally representative sample of Latino Americans (N = 2,346) from the National Latino and Asian American Study (NLAAS) to examine the relationships between 9/11-induced negative life experiences and mental disorders. The former includes losing a job, reducing family income, feeling less safe and secure, discrimination, loss of optimism, and inability to cope with things. For the latter, mental disorders may exhibit as psychological distress, depressive disorder, and anxiety disorder. This study also evaluates the moderating role of religious service attendance in these relationships. Results indicated that the negative life experiences resulting from the 9/11 terrorist attacks were predictive of psychological distress, depressive disorder, and anxiety disorder. In addition, religious service attendance exhibited the buffering effect of the 9/11-related experiences on distress and depressive disorder, but not on anxiety disorder. Findings highlight the potential role of religious service attendance in mitigating the adverse mental health effects of stressors among Latinos Americans especially in the aftermath of a disaster