纤维素酶液体深层发酵条件的研究

选用青霉菌（Pemicillumsp）用于纤维素酶液体深层发酵条件和生产工艺的研究。研究了纤维素酶二级和三级液体培养的条件。确定了种子液和发酵液的配方、产酶活力FPA167单位／毫升、β-葡聚糖酶活力20万单位／毫升。为纤维素酶三级液体深层发酵的工业生产提供了工艺路线和参数。     

Repeated invasions into the twilight zone: evolutionary origins of a novel assemblage of fishes from deep Caribbean reefs

Mesophotic and deeper reefs of the tropics are poorly known and underexplored ecosystems worldwide. Collectively referred to as the ‘twilight zone’, depths below ~30–50 m are home to many species of reef fishes that are absent from shallower depths, including many undescribed and endemic species. We currently lack even a basic understanding of the diversity and evolutionary origins of fishes on tropical mesophotic reefs. Recent submersible collections in the Caribbean have provided new specimens that are enabling phylogenetic reconstructions that incorporate deep‐reef representatives of tropical fish genera. Here, we investigate evolutionary depth transitions in the family Gobiidae (gobies), the most diverse group of tropical marine fishes. Using divergence‐time estimation coupled with stochastic character mapping to infer the timing of shallow‐to‐deep habitat transitions in gobies, we demonstrate at least four transitions from shallow to mesophotic depths. Habitat transitions occurred in two broad time periods (Miocene, Pliocene–Pleistocene), and may have been linked to the availability of underutilized niches, as well as the evolution of morphological/behavioural adaptations for life on deep reefs. Further, our analysis shows that at least three evolutionary lineages that invaded deep habitats subsequently underwent speciation, reflecting another unique mode of radiation within the Gobiidae. Lastly, we synthesize depth distributions for 95 species of Caribbean gobies, which reveal major bathymetric faunal breaks at the boundary between euphotic and mesophotic reefs. Ultimately, our study is the first rigorous investigation into the origin of Caribbean deep‐reef fishes and provides a framework for future studies that utilize rare, deep‐reef specimens.     

A synthesis of genetic connectivity in deep‐sea fauna and implications for marine reserve design

With anthropogenic impacts rapidly advancing into deeper waters, there is growing interest in establishing deep‐sea marine protected areas (MPAs) or reserves. Reserve design depends on estimates of connectivity and scales of dispersal for the taxa of interest. Deep‐sea taxa are hypothesized to disperse greater distances than shallow‐water taxa, which implies that reserves would need to be larger in size and networks could be more widely spaced; however, this paradigm has not been tested. We compiled population genetic studies of deep‐sea fauna and estimated dispersal distances for 51 studies using a method based on isolation‐by‐distance slopes. Estimates of dispersal distance ranged from 0.24 km to 2028 km with a geometric mean of 33.2 km and differed in relation to taxonomic and life‐history factors as well as several study parameters. Dispersal distances were generally greater for fishes than invertebrates with the Mollusca being the least dispersive sampled phylum. Species that are pelagic as adults were more dispersive than those with sessile or sedentary lifestyles. Benthic species from soft‐substrate habitats were generally less dispersive than species from hard substrate, demersal or pelagic habitats. As expected, species with pelagic and/or feeding (planktotrophic) larvae were more dispersive than other larval types. Many of these comparisons were confounded by taxonomic or other life‐history differences (e.g. fishes being more dispersive than invertebrates) making any simple interpretation difficult. Our results provide the first rough estimate of the range of dispersal distances in the deep sea and allow comparisons to shallow‐water assemblages. Overall, dispersal distances were greater for deeper taxa, although the differences were not large (0.3–0.6 orders of magnitude between means), and imbalanced sampling of shallow and deep taxa complicates any simple interpretation. Our analyses suggest the scales of dispersal and connectivity for reserve design in the deep sea might be comparable to or slightly larger than those in shallow water. Deep‐sea reserve design will need to consider the enormous variety of taxa, life histories, hydrodynamics, spatial configuration of habitats and patterns of species distributions. The many caveats of our analyses provide a strong impetus for substantial future efforts to assess connectivity of deep‐sea species from a variety of habitats, taxonomic groups and depth zones.     

Is the lack of respiratory gating prejudicial for left breast TomoDirect treatments?

Background and purposeTomoDirect (TD) can only operate in free-breathing. The purpose of this study is to compare TD with breath-hold 3D conformal radiotherapy (3DCRT) and intensity modulated radiotherapy (IMRT) techniques for left breast treatments, and to determine if the lack of respiratory gating is a handicap for cardiac sparing.Materials and methods15 patients treated for left breast had two computed tomography simulation, in free breathing (FB) and in deep-inspiration breath-hold (DIBH). Four treatments were planned: TD-FB, 3DCRT-FB, 3DCRT-DIBH and IMRT-DIBH. Dose to PTV, heart, lungs, right breast and patient were compared.ResultsA slightly lower cardiac mean dose is found for 3DCRT-DIBH than for TD-FB group (1.99 Gy Vs 2.89 Gy, p = 0.0462), while no statistical difference is found for heart V₂₀. TD-FB plans show the best PTV dose homogeneity (0.053, p < 0.001) and the lowest left lung mean dose (5.16 Gy, p < 0.001). No major differences are found for the other organs.ConclusionsTomoDirect and breath-hold 3DCRT are complementary techniques for left breast treatments: for a minority of patients, respiratory gating is mandatory to lower cardiac dose; for the remaining majority of patients, TomoDirect achieves better PTV homogeneity and reduced left lung dose, with cardiac dose equivalent to 3DCRT-DIBH.     

Morphological investigation of the deep pineal of the rat

Summary The results presented here reveal that in adult Sprague-Dawley and Wistar rats the pineal gland represents a complex rather than a single organ. Regularly one can distinguish (i) pineal tissue in the intercommissural region as a deep pineal, (ii) a superficial pineal, which represents the major part of the pineal complex, and (iii) nearly always a parenchymal stalk of variable length. The volume of the deep pineal with the adjacent parenchymal stalk exhibits great interindividual variation. It amounts to 127±39×10⁵ m³ (mean ±standard deviation). The histological appearance of the deep and superficial pineal tissue is fairly similar. The intrinsic cells of the deep and superficial pineal differ in nuances only. Karyometry reveals that the nuclear volumes of the intrinsic cells of the deep pineal are very variable ranging from 90–450 m³, with a mean value of 207 m³. The changes over a period of 24 h reach statistical significance.Supported by the Deutsche Forschungsgemeinschaft (Grant Vo 135/4) within the Schwerpunktprogramm NeuroendokrinologieThis paper is an abridged version of a thesis submitted for obtaining the degree of Dr. med., Fachbereich Medizin, University of Mainz     

Effect of urea placement on leaching losses of nitrogen from flooded rice soils

In an effort to provide an explanation for the reported variability in fertilizer N efficiency from deepplaced urea on flooded rice, a set of controlled experiments was conducted to evaluate the effect of water percolation on fertilizer loss and plant uptake from¹⁵N labeled urea supergranules. Three soils of different texture (silt loam-clay) were subjected to various percolation rates (0–20 mm/day) while planted to rice which was harvested after approximately 40 days.The results indicate that moderate to high percolation through silt loam soil will lead to significant fertilizer N losses and drastically decrease the fertilizer uptake by plants. The permeability of the clay soil was too low for any leaching to take place. It is therefore concluded that deep placement of urea supergranules not be recommended in soils where percolation rates may exceed 5 mm/day, particularly if the cation exchange capacity of the soil is low. This experiment points to the need of evaluating and reporting the percolation rates in soils where experiments with supergranular urea are conducted.Contribution from the Agro-Economic Division of the International Fertilizer Development Center (IFDC), Muscle Shoals, Alabama 35660.     

Deep placement: A method of nitrogen fertilizer application compatible with algal nitrogen fixation in wetland rice soils

Summary The effect of different methods of nitrogen fertilizer application on the algal flora and biological nitrogen fixation (Acetylene-reducing activity) in a wetland rice soil was studied in pot and field experiments. Broadcast application of urea inhibited nitrogen fixation and favored the growth of green algae. In contrast, deep placement of urea supergranules (1–2 g urea granules) did not suppress the growth of N₂-fixing blue-green algae and permitted acetylene-reducing activity on the soil surface to continue virtually uninhibited.     

An extremely thermophilic Methanococcus from a deep sea hydrothermal vent and its plasmid

An extremely thermophilic methanogen was isolated from a hydrothermal vent core sample from Guaymas Basin, Gulf of California, at a depth of 2003 m. The isolate, designated strain AG86, was a coccoid autotroph using H₂-CO₂ as energy and carbon source with a growth temperature range of 48 to 92°C, optimum, 85°C. AG86 required NaCl and Mg²⁺ and trace amounts of selenite and tungstate. Vitamins were not required. However, yeast extract, Casamino acids and Trypticase stimulated growth significantly. When grown in the presence of these stimulants and at the optimal growth temperature and pH 6.5, the minimum doubling time was 20 min. Cells were fragile and readily lysed by detergents. The mol% G+C was 33%. These results and partial 16S rRNA sequencing indicated that AG86 belonged to the genus Methanococcus and closely resembled Methanococcus jannaschii. Tests for extrachromosomal DNA revealed a plasmid in AG86 and two plasmids in M. jannaschii. Different patterns were obtained from restriction endonuclease digestion of the three plasmids, and no homology was observed with DNA-DNA hybridization.Abbreviations CCC DNA covalently close circular DNA - DM defined marine medium - G+C Guanine plus cytosine - MPN most probable number     

Comparison of different deep learning architectures for synthetic CT generation from MR images

PurposeAmong the different available methods for synthetic CT generation from MR images for the task of MR-guided radiation planning, the deep learning algorithms have and do outperform their conventional counterparts. In this study, we investigated the performance of some most popular deep learning architectures including eCNN, U-Net, GAN, V-Net, and Res-Net for the task of sCT generation. As a baseline, an atlas-based method is implemented to which the results of the deep learning-based model are compared.MethodsA dataset consisting of 20 co-registered MR-CT pairs of the male pelvis is applied to assess the different sCT production methods' performance. The mean error (ME), mean absolute error (MAE), Pearson correlation coefficient (PCC), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR) metrics were computed between the estimated sCT and the ground truth (reference) CT images.ResultsThe visual inspection revealed that the sCTs produced by eCNN, V-Net, and ResNet, unlike the other methods, were less noisy and greatly resemble the ground truth CT image. In the whole pelvis region, the eCNN yielded the lowest MAE (26.03 ± 8.85 HU) and ME (0.82 ± 7.06 HU), and the highest PCC metrics were yielded by the eCNN (0.93 ± 0.05) and ResNet (0.91 ± 0.02) methods. The ResNet model had the highest PSNR of 29.38 ± 1.75 among all models. In terms of the Dice similarity coefficient, the eCNN method revealed superior performance in major tissue identification (air, bone, and soft tissue).ConclusionsAll in all, the eCNN and ResNet deep learning methods revealed acceptable performance with clinically tolerable quantification errors.