The genome and transcriptome of Japanese flounder provide insights into flatfish asymmetry

Flatfish have the most extreme asymmetric body morphology of vertebrates. During metamorphosis, one eye migrates to the contralateral side of the skull, and this migration is accompanied by extensive craniofacial transformations and simultaneous development of lopsided body pigmentation(1-5). The evolution of this developmental and physiological innovation remains enigmatic. Comparative genomics of two flatfish and transcriptomic analyses during metamorphosis point to a role for thyroid hormone and retinoic acid signaling, as well as phototransduction pathways. We demonstrate that retinoic acid is critical in establishing asymmetric pigmentation and, via cross-talk with thyroid hormones, in modulating eye migration. The unexpected expression of the visual opsins from the phototransduction pathway in the skin translates illumination differences and generates retinoic acid gradients that underlie the generation of asymmetry. Identifying the genetic underpinning of this unique developmental process answers long-standing questions about the evolutionary origin of asymmetry, but it also provides insight into the mechanisms that control body shape in vertebrates.National Natural Science Foundation of China [31130057, 31461163005, 31530078, 31472269, 31472262, 31472273]; State 863 High Technology R&D Project of China [2012AA092203, 2012AA10A408, 2012AA10A403-2]; Education and Research of Guangdong Province [2013B090800017]; Taishan Scholar Climb Project Fund of Shandong of China; Taishan Scholar Project Fund of Shandong of China for Young Scientists; Shanghai Universities First-class Disciplines Project of Fisheries; Program for Professor of Special Appointment (Eastern Scholar) at the Shanghai Institutions of Higher Learning; Shanghai Municipal Science, Special Project on the Integration of Industryinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/publishedVersio

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Online Parameter Estimation of the Ni-MH Batteries Based on Statistical Methods

Based on the application of the power batteries, this paper uses a statistical method to estimate the internal resistance and open-circuit voltage of Ni-MH battery. Battery status is monitored and simulated by battery pack test bench. Through using ideal battery model and fitting the data of measured voltage and current, the battery internal resistance and open-circuit voltage are estimated. The average relative error between battery statistic internal resistance and pulse internal resistance is less than 15% in different state of charge. Relative error is influenced by dispersion and symmetry of charge or discharge current. Average of absolute error in open-circuit voltage is about 5% respectively. The results show that it is feasible and accurate to estimate the parameters of Ni-MH battery by using statistical method