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In sensory systems of the brain, mechanisms exist to extract distinct features from stimuli to generate a variety of behavioural repertoires. These often correspond to different cell types at various stages in sensory processing. In the mammalian olfactory system, complex information processing starts in the olfactory bulb, whose output is conveyed by mitral and tufted cells (MCs and TCs). Despite many differences between them, and despite the crucial position they occupy in the information hierarchy, Cre-driver lines that distinguish them do not yet exist. Here, we sought to identify genes that are differentially expressed between MCs and TCs of the mouse, with an ultimate goal to generate a cell-type specific Cre-driver line, starting from a transcriptome analysis using a large and publicly available single-cell RNA-seq dataset (Zeisel et al., 2018). Many genes were differentially expressed, but only a few showed consistent expressions in MCs and at the specificity required. After further validating these putative markers using in-situ hybridization, two genes, namely Pkib and Lbdh2, remained as promising candidates. Using CRISPR/Cas9-mediated gene editing, we generated Cre-driver lines and analysed the resulting recombination patterns. This indicated that our new inducible Cre-driver line, Lbhd2-CreERT2, can be used to genetically label MCs in a tamoxifen dose-dependent manner, both in male and female mice, as assessed by soma locations, projection patterns and sensory-evoked responses in vivo. Hence this is a promising tool for investigating cell-type specific contributions to olfactory processing and demonstrates the power of publicly accessible data in accelerating science. SIGNIFICANCE STATEMENT: In the brain, distinct cell types play unique roles. It is therefore important to have tools for studying unique cell types specifically. For the sense of smell in mammals, information is processed first by circuits of the olfactory bulb, where two types of cells, mitral cells and tufted cells, output different information. We generated a transgenic mouse line that enables mitral cells to be specifically labelled or manipulated. This was achieved by looking for genes that are specific to mitral cells using a large and public gene expression dataset, and creating a transgenic mouse using the gene editing technique, CRISPR/Cas9. This will allow scientists to better investigate parallel information processing underlying the sense of smell.

An unexpected new Metapenaeus shrimp species has arrived to the coastal water of Alexandria City, Egypt. Morphological and molecular studies were conducted for its identification. The results revealed that it is the Indo-West Pacific species, Metapenaeus affinis (H. Milne Edwards, 1837), which is considered as a new addition to the already present local penaeidae species; Metapenaeus monoceros (Fabricius, 1798) and Metapenaeus stebbingi (Nobili, 1904). Large numbers of Metapenaeus affinis were observed and collected by the Egyptian fishermen from the coastal waters of Alexandria City, Egypt, during the study period (2020–2021), which indicates its establishment in the area. A recommendation was presented for further studies regarding the suggested ways of introduction and the prediction for future new species appearance. Such phenomenon requires international efforts to deal with the non-indigenous species’ entries that are recently intensified on the global and regional level.

Africa is a continent that incubates huge inland freshwater reservoirs, representing 27% of total world liquid freshwater, and bounded by marine blue belt. This topography makes Africa harboring diverse freshwater and marine fishery resources. However, fisheries in Africa are still facing big challenges that can be resolved by molecular genetic tools. The present review demonstrated how DNA barcoding approaches expand in African fisheries to solve the problems of fish species identifications, evolutions, population differentiations and biogeographic distributions. Additionally, the limited DNA metabarcoding applications in screening African fish gut microbiome and fish diseases were discussed. Also, we highlighted future perspectives in molecular barcoding applications in African fisheries and a concept for establishing of Africa fish gene bank.

Sea cucumber (bêche-de-mer, Echinodermata: Holothuroidea) is one of the top internationally traded seafood varieties. Besides its direct nutritional benefits, it is continuously used in the traditional medicine in different areas and cultures in the world. This world-wide interest triggered various issues related to stocks´ declining and risks of species extinction. For these reasons, the current study was designed to provide molecular tools for accurate discrimination between two sea cucumber species that prevail the Mediterranean of these echinoderms in Egypt, that are Holothuria polii and H. sanctori. The power of three gene markers, i.e., 16S rDNA, 28S rDNA, and Histone H3 in achieving accurate DNA-based identification, as well as elucidating clear phylogenetic and genetic diversity differences between those two species was assessed. Among the three genes, 16S rDNA showed the highest potentials as genetic and phylogenetic species discrimination marker. Both 28S rDNA and H3 exhibited the least number of holothuroid reference sequences in the GenBank database. For genetic diversity within each species population, 16S rDNA exhibited the best potentials, followed by H3. 28S rDNA showed no genetic polymorphism at all. Moreover, the collective data of both H3 and 16S rDNA suggested a possible role of asexual reproduction behavior in H. sanctori in the reduction of genetic diversity, as a possible response to overfishing. Hence, the current research can recommend the simultaneous application of both 16S rDNA and H3 as accurate markers for genetic discrimination among H. polii, H. sanctori and other different holothuroid species.

Recurring outbreaks of crown-of-thorns starfish (COTS) severely damage healthy corals in the Western Pacific Ocean. To determine the source of outbreaking COTS larvae and their dispersal routes across the Western Pacific, complete mitochondrial genomes were sequenced from 243 individuals collected in 11 reef regions. Our results indicate that Pacific COTS comprise two major clades, an East-Central Pacific clade (ECP-C) and a Pan-Pacific clade (PP-C). The ECP-C consists of COTS from French Polynesia (FP), Fiji, Vanuatu and the Great Barrier Reef (GBR), and does not appear prone to outbreaks. In contrast, the PP-C, which repeatedly spawns outbreaks, is a large clade comprising COTS from FP, Fiji, Vanuatu, GBR, Papua New Guinea, Vietnam, the Philippines, Japan, Micronesia, and the Marshall Islands. Given the nature of Pacific Ocean currents, the vast area encompassing FP, Fiji, Vanuatu, and the GBR likely supplies larvae for repeated outbreaks, exacerbated by anthropogenic environmental changes, such as eutrophication.

Despite being one of the world’s leading countries in coral reef conservation and management, very little data exist for coral reef-associated species in the island nation of Palau, hampering managers’ ability to more effectively protect coral reef ecosystems. Here we examine populations of the vermetid Ceraesignum maximum, a common species on coral reefs, with short or absent pelagic larval stage, in order to elucidate patterns of gene flow within Palauan reefs. We collected specimens (n = 582) from 20 sites across Palau. Cytochrome oxidase subunit I analyses show private haplotypes at all sites examined, with a clear separation between outer and inner reef locations, and a unique population within isolated Nikko Bay. Oceanographic isolation between the waters of Nikko Bay, inner and outer reefs may contribute to our observed genetic differentiation. Our results indicate past demographic expansion of C. maximum across the region and also indicate that multiple sites of both inner and outer reef locations would need to be protected to conserve this species’ genetic diversity, including unique Nikko Bay. These results demonstrate the utility of C. maximum as a good species to investigate gene flow across small scales (

For optimized deployment of deep neural networks in embedded devices, hardware approximations offer acceptable trade-offs between computational resources, power consumption, and network accuracy. In this paper, we propose a novel approximation technique with variable error range, targeting various architectures that adopt bit-decomposition of the Multiply and Accumulate (MAC) operation, especially emerging in-memory computing based architectures. Through our experiments with state-of-the-art neural networks for image classification using CIFAR10 and ImageNet, we demonstrate that this approximation technique achieves 2x power efficiency compared to the base architecture, with an accuracy loss of less than 3%.

We examined genetic diversity and connectivity of two indigenous Mediterranean goatfish species (Mullus barbatus and M. surmuletus), and a Lessepsian migrant species (Upeneus moluccensis), across the Nile Delta outflow using two mitochondrial DNA markers (COI and cyt b). Genetic diversity was high for the two Mediterranean species but relatively lower for the migrant species, suggesting founder effects after invasion from the Red Sea. Confirmation of this hypothesis, however, would require comparison with populations of origin in the Red Sea and the Indo-West Pacific. AMOVA and network analyses revealed no genetic partitioning for all species, indicating the Nile outflow does not currently, and may not have historically, posed a significant barrier to larval dispersal in these goatfish despite a present-day temperature and salinity gradient along the Mediterranean coastline of Egypt.

Efficient low-power accelerators for Convolutional Neural Networks (CNNs) largely benefit from quantization and approximation, which are typically applied layer-wise for efficient hardware implementation. In this work, we present a novel strategy for efficient combination of these concepts at a deeper level, which is at each channel or kernel. We first apply layer-wise, low bit-width, linear quantization and truncation-based approximate multipliers to the CNN computation. Then, based on a state-of-the-art resiliency analysis, we are able to apply a kernel-wise approximation and quantization scheme with negligible accuracy losses, without further retraining. Our proposed strategy is implemented in a specialized framework for fast design space exploration. This optimization leads to a boost in estimated power savings of up to 34% in residual CNN architectures for image classification, compared to the base quantized architecture.

In each sensory system of the brain, mechanisms exist to extract distinct features from stimuli to generate a variety of behavioural repertoires. These often correspond to different cell types at some stage in sensory processing. In the mammalian olfactory system, complex information processing starts in the olfactory bulb, whose output is conveyed by mitral and tufted cells (MCs and TCs). Despite many differences between them, and despite the crucial position they occupy in the information hierarchy, little is known how these two types of projection neurons differ at the mRNA level. Here, we sought to identify genes that are differentially expressed between MCs and TCs, with an ultimate goal to generate a cell-type specific Cre-driver line, starting from a transcriptome analysis using a large and publicly available single-cell RNA-seq dataset (Zeisel et al., 2018). Despite many genes showing differential expressions, we identified only a few that were abundantly and consistently expressed only in MCs. After further validating these putative markers usingin-situhybridization, two genes, namelyPkibandLbdh2, remained as promising candidates. Using CRISPR/Cas9-mediated gene editing, we generated Cre-driver lines and analysed the resulting recombination patterns. This analysis indicated that our new inducible Cre-driver line,Lbhd2-CreERT2, can be used to genetically label MCs in a tamoxifen dose-dependent manner, as assessed by soma locations, projection patterns and sensory-evoked responses. Hence this line is a promising tool for future investigations of cell-type specific contributions to olfactory processing and demonstrates the power of publicly accessible data in accelerating science.

In the last couple of years, the goal of deploying Deep Neural Networks (DNNs) in the embedded domain has led to the development of several dedicated DNN Hardware Accelerators (HWAs), many of which rely on a Dot-Product Engine (DPE)-based architecture. A DPE is a hardware block that receives two input vectors of the same size and produces one scalar value. Nevertheless, when the actual input vector does not match the DPEs native input-size, the DPE becomes underutilized. This is particularly observed for Convolutional Neural Networks (CNNs). In this article, we introduce kernel linearization, a technique to mitigate the underutilization of DPE-based HWA for DNNs. To demonstrate the benefits of this method, we implemented AEXelerator, a DPE-based HWA prototyped on FPGA and validated using automotive relevant DNNs. Our evaluation shows that our architecture achieves a high DPE utilization even in the presence of large vector-size mismatches.

Our knowledge of the ecology and habitat of juveniles of many sea cucumber species is limited, due to their cryptic habitats and differing color and shape from adults. In the present study, a juvenile specimen of the sea cucumber Thelenota anax H. L. Clark, 1921, collected from 30 m at Rukan Reef, Okinawa, Japan, is described. We confirmed specific identity using cytochrome oxidase subunit I (COI) sequences. We show that the pseudotable ossicles in Thelenota are table ossicles, and document synallactid-like ossicles not previously recorded in the Stichopodidae.

Recently, tilapia have become increasingly important in aquaculture and fisheries worldwide. They are one of the major protein sources in many African countries and are helping to combat malnutrition. Therefore, maintenance and conservation genetics of wild populations of tilapia are of great significance. In this study, we report the population genetic structure and genetic diversity of the redbelly tilapia (Coptodon zillii) in three different Egyptian aquatic environments: brackish (Lake Idku), marine (Al-Max Bay), and freshwater (Lake Nasser). The habitat differences, environmental factors, and harvesting pressures are the main characteristics of the sampling sites. Three mitochondrial DNA markers (COI: cytochrome oxidase subunit I; the D-loop; CYTB: cytochrome b) were used to assess population structure differences among the three populations. The population at Lake Nasser presented the highest genetic diversity (Hd = 0.8116, H = 6), and the marine population of Al-Max Bay the lowest (Hd = 0.2391, H = 4) of the combined sequences. In addition, the phylogenetic haplotype network showed private haplotypes in each environmental habitat. Results presented here will be useful in aquaculture to introduce the appropriate broodstock for future aquaculture strategies of C. zillii. In addition, evidence of population structure may contribute to the management of tilapia fisheries in Egyptian waters.

In recent years, an increasing number of different JEDEC memory standards, like DDR4/5, LPDDR4/5, GDDR6, Wide I/O2, HBM2, and NVDIMM-P have been specified, which differ significantly from the previous ones like DDR3 and LPDDR3. Since each new standard comes with significant changes in the DRAM protocol compared to the previous ones, the developers of memory controllers and memory simulation models regularly face challenges implementing and verifying these new standards. In order to keep pace with these frequent changes of the requirements and the large variety of variants a robust validation methodology must be established. The JEDEC standards describe the complex memory protocol, i.e., DRAM commands and their timing dependencies, by using a mixture of state machine diagrams, tables, and timing diagrams. However, there exists no unique formal description of the JEDEC standards which could be used for a fast simulation-based validation. In this paper, for the first time, we present a comprehensive and formal mathematical model based on Petri Nets that contains the DRAM states, transitions, and timings. Furthermore, we present a Domain Specific Language (DSL) for describing the memory functionality and timing dependencies of a JEDEC standard in just a few lines of code. From this DSL description an executable Petri Net is generated automatically, which is used for the fast simulation-based validation of memory controllers and DRAM simulation models.