Sabine Pass: The Confederacy\u27s Thermopylae

Texans triumph Confederates avoid a single casualty On September 8, 1863, a group of less than 50 Irish-Confederate dock workers from Houston successfully defended Sabine Pass, Texas, from a much larger, better-equipped Union invasion force. For this action Lieutenant Dick Dowlin...

Born to Battle: Grant and Forrest: Shiloh, Vicksburg and Chattanooga: The Campaigns That Doomed the Confederacy

Analyzing Civil War Leadership Both Ulysses Grant and Nathan Bedford Forrest left indelible legacies during the American Civil War. Both men came from humble beginnings, although Forrest earned a fortune in slaves and cotton and Grant attended the United States Military Academy at West ...

Phenex: Ontological Annotation of Phenotypic Diversity

Phenex is a platform-independent desktop application designed to facilitate efficient and consistent annotation of phenotypic variation using Entity-Quality syntax, drawing on terms from community ontologies for anatomical entities, phenotypic qualities, and taxonomic names. Despite the centrality of the phenotype to so much of biology, traditions for communicating information about phenotypes are idiosyncratic to different disciplines. Phenotypes seem to elude standardized descriptions due to the variety of traits that compose them and the difficulty of capturing the complex forms and subtle differences among organisms that we can readily observe. Consequently, phenotypes are refractory to attempts at data integration that would allow computational analyses across studies and study systems. Phenex addresses this problem by allowing scientists to employ standard ontologies and syntax to link computable phenotype annotations to evolutionary character matrices, as well as to link taxa and specimens to ontological identifiers. Ontologies have become a foundational technology for establishing shared semantics, and, more generally, for capturing and computing with biological knowledge

Regenerating zebrafish scales express a subset of evolutionary conserved genes involved in human skeletal disease

BACKGROUND: Scales are mineralised exoskeletal structures that are part of the dermal skeleton. Scales have been mostly lost during evolution of terrestrial vertebrates whilst bony fish have retained a mineralised dermal skeleton in the form of fin rays and scales. Each scale is a mineralised collagen plate that is decorated with both matrix-building and resorbing cells. When removed, an ontogenetic scale is quickly replaced following differentiation of the scale pocket-lining cells that regenerate a scale. Processes promoting de novo matrix formation and mineralisation initiated during scale regeneration are poorly understood. Therefore, we performed transcriptomic analysis to determine gene networks and their pathways involved in dermal scale regeneration. RESULTS: We defined the transcriptomic profiles of ontogenetic and regenerating scales of zebrafish and identified 604 differentially expressed genes (DEGs). These were enriched for extracellular matrix, ossification, and cell adhesion pathways, but not in enamel or dentin formation processes indicating that scales are reminiscent to bone. Hypergeometric tests involving monogenetic skeletal disorders showed that DEGs were strongly enriched for human orthologues that are mutated in low bone mass and abnormal bone mineralisation diseases (P< 2× 10(−3)). The DEGs were also enriched for human orthologues associated with polygenetic skeletal traits, including height (P< 6× 10(−4)), and estimated bone mineral density (eBMD, P< 2× 10(−5)). Zebrafish mutants of two human orthologues that were robustly associated with height (COL11A2, P=6× 10(−24)) or eBMD (SPP1, P=6× 10(−20)) showed both exo- and endo- skeletal abnormalities as predicted by our genetic association analyses; col11a2(Y228X/Y228X) mutants showed exoskeletal and endoskeletal features consistent with abnormal growth, whereas spp1(P160X/P160X) mutants predominantly showed mineralisation defects. CONCLUSION: We show that scales have a strong osteogenic expression profile comparable to other elements of the dermal skeleton, enriched in genes that favour collagen matrix growth. Despite the many differences between scale and endoskeletal developmental processes, we also show that zebrafish scales express an evolutionarily conserved sub-population of genes that are relevant to human skeletal disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-01209-8

Puerto Rican Karst - A Vital Resource

The limestone region of Puerto Rico covers about 27.5 percent of the island\u27s surface and is subdivided into the northern, southern, and dispersed limestone areas. All limestone areas have karst features. The karst belt is that part of the northern limestone with the most spectacular surficial karst landforms. It covers 142,544 ha or 65 percent of the northern limestone. The karst belt is the focus of this publication, although reference is made to all limestone regions. The northern limestone contains Puerto Rico\u27s most extensive freshwater aquifer, largest continuous expanse of mature forest, and largest coastal wetland, estuary, and underground cave systems. The karst belt is extremely diverse, and its multiple landforms, concentrated in such a small area, make it unique in the world. Puerto Rico\u27s karst forests whether dry, moist, or wet share common physiognomic and structural characteristics. Karst forests contain the largest reported number of tree species per unit area in Puerto Rico. Both fauna and flora are rich in taxa; and many rare, threatened, endangered, and migratory species find refuge in the karst belt. Almost all fossil records of Puerto Rico\u27s extinct flora and fauna come from the karst belt

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level