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opencc-by-4.0Dec 2023View details →

Data for: Engineering A-type Dye-decolorizing Peroxidases by Modification of a Conserved Glutamate Residue

Dye-decolorizing peroxidases (DyPs) are recently identified microbial enzymes that have been used in several Biotechnology applications from wastewater treatment to lignin valorization. However, their properties and mechanism of action still have many open questions. Their heme-containing active site is buried by three conserved flexible loops with a putative role in modulating substrate access and enzyme catalysis. Here, we investigated the role of a conserved glutamate residue in stabilizing interactions in loop 2 of A-type DyPs. First, we did site saturation mutagenesis of this residue, replacing it with all possible amino acids in bacterial DyPs from Bacillus subtilis (BsDyP) and from Kitasatospora aureofaciens (KaDyP1), the latter being characterized here for the first time. We screened the resulting libraries of variants for activity towards ABTS and identified variants with increased catalytic efficiency. The selected variants were purified and characterized for activity and stability. We furthermore used Molecular Dynamics simulations to rationalize the increased catalytic efficiency and found that the main reason is the electron channeling becoming easier from surface-exposed tryptophans. Based on our findings, we also propose that this glutamate could work as a pH switch in the wild-type enzyme, preventing intracellular damage.

openJan 2024View details →

Assessing microbiome population dynamics using wild-type isogenic standardized hybrid (WISH)-tags

Microbiomes feature recurrent compositional structures under given environmental conditions. However, these patterns may conceal diverse underlying population dynamics that require intra-strain resolution. Here, we developed a genomic tagging system, termed wild-type isogenic standardized hybrid (WISH)-tags, that can be combined with quantitative PCR and next-generation sequencing for microbial strain enumeration. We experimentally validated the performance of 62 tags and showed they can be differentiated with high precision. WISH-tags were introduced into model and non-model bacterial members of the mouse and plant microbiota. Intra-strain priority effects were tested using one species of isogenic barcoded bacteria in the murine gut and the Arabidopsis phyllosphere, both with and without microbiota context. We observed colonization resistance against late arriving strains of Salmonella typhimurium in the mouse gut, whereas the phyllosphere accommodated Sphingomonas latecomers in a proportional manner to their presence at the late inoculation timepoint. This demonstrates that WISH-tags are a resource for deciphering population dynamics underlying microbiome assembly across biological systems.

opencc-by-4.0Jan 2024View details →

annual maps of gloabl forest management types from 2001-2020

This dataset provided the annual global fine composition of forests from a management perspective. Based on multi-data sources such as MOD13Q1, human footprint, and DEM, we extracted variables such as vegetation growth characteristics, local texture information, human activities, and terrain property. Using machine learning and change detection methods,  annual global maps of forest management types with a spatial resolution of 250 m were generated for the detailed composition of forests from 2001 to 2020 from a forest management perspective. Forest management types were defined into six categories: natural regeneration forests (both unmanaged and managed), plantation forests (rotation >15 years and ≤15 years), oil palm plantations, and agroforestry. Point-scale validation results indicated an overall accuracy ranging from 75.55% to 96.26%. The annual forest management type data holds significant importance in understanding the fine composition of forests. <div>1:unmanaged naturally regenerated forest</div> <div>2:managed naturally regenerated forest</div> <div>3:planted forest with rotation >15 years </div> <div>4:planted forest with rotation≤15 years</div> <div>5:oil palm plantation</div> <div>6:agroforestry</div> <div>7:Others</div> A research article about this dataset, please cite: Hongtao Xu,Bin He, Lanlan Guo, Xing Yan, Jinwei Dong, Wenping Yuan, Xingming Hao, Aifeng Lv, Xiangqi He, Tiewei Li. Changes in the Fine Composition of Global Forests from 2001 to 2020. J Remote Sens. 2024;4:0119.DOI:<a href="https://doi.org/10.34133/remotesensing.0119">10.34133/remotesensing.0119</a>

Figure 20 in New records for the Indian cuckoo wasp fauna (Hymenoptera: Chrysididae) with description of two new species and remarks on types of Smith and Cameron

Figure 20. Stilbum princeps (Gray, 1832), holotype ♀. A. Habitus, postero-lateral view. B. Illustration of the type from Griffith and Pidgeon (1832). C. Habitus, lateral view. D. Head, frontal view. E. Head and mesosoma, dorsal view. F. Metasoma, dorsal view. Scale bar: 5 mm.

Figure 1 in New records for the Indian cuckoo wasp fauna (Hymenoptera: Chrysididae) with description of two new species and remarks on types of Smith and Cameron

Figure 1. Chrysis parviocula sp. n., holotype, ♀. A. Habitus, lateral view. B. Head, frontal view. C. Head and pronotum, dorsal view. D. Mesosoma, dorsal view. E. Metasoma, dorsal view. F. Habitus, posterior view. Scale bar: 1 mm.

Figure 7 in New records for the Indian cuckoo wasp fauna (Hymenoptera: Chrysididae) with description of two new species and remarks on types of Smith and Cameron

Figure 7. Elampus kashmirensis (Nurse, 1902), lectotype J. A. Habitus, dorsal view. B. Habitus, lateral view. C. Head, frontal view. D. Mesosoma, dorsal view. E. Metasoma, lateral view. F. Third metasomal tergum, posterior view. Scale bars: 1 mm.

opencc-by-4.0Feb 2024View details →

Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021)

The dataset contains maps of the main classes of agricultural land use (dominant crop types and other land use types) in Germany, which are produced annually at the Thünen Institute beginning with the year 2017 on the basis of satellite data. The maps cover the entire open landscape, i.e., the agriculturally used area (UAA) and e.g., uncultivated areas. The map was derived from time series of Sentinel-1, Sentinel-2, Landsat 8 and additional environmental data. Map production is based on the methods described in <a href="https://doi.org/10.1016/j.rse.2021.112831">Blickensdörfer et al. (2022)</a>. All optical satellite data were managed, pre-processed and structured in an analysis-ready data (ARD) cube using the open-source software <a href="https://force-eo.readthedocs.io/en/latest/">FORCE </a>- Framework for Operational Radiometric Correction for Environmental monitoring (Frantz, D., 2019), in which SAR and environmental data were integrated. The map extent covers all areas in Germany that are defined in the respective year as cropland, grassland, small woody features, heathland, peatland or unvegetated areas according to ATKIS Basis-DLM (Geobasisdaten: © GeoBasis-DE / BKG, 2020).  Version v201: Post-processing of the maps included a sieve filter as well as a ruleset for the reduction of non-plausible areas using the Basis-DLM and the digital terrain model of Germany (Geobasisdaten: © GeoBasis-DE / BKG, 2015). Version v202: Additional post-processing was performed to detect and mask additional non-plausible areas that were not adequately covered by the first post-processing (e.g., areas with sparse vegetation, montane forests) based on the &bdquo;Ökosystematlas Deutschland“ (© Statistisches Bundesamt, Deutschland, 2024). As a consequence, the current version includes a new class “Small woody features on other land”. Furthermore, the class "permanent grassland" was refined. Each pixel that was classified as "cultivated grassland" in at least five years (between 2017 and 2022) was translated to "permanent grassland" in the annual maps. The maps are available as cloud optimized GeoTiffs, which makes downloading the full dataset optional. All data can directly be accessed in QGIS, R, Python or any supported software of your choice using the provided URL to the datasets (right click on the respective data set --> “copy link address”). By doing so the entire map area or only the regions of interest can be accessed. QGIS legend files for data visualization can be downloaded separately. Class-specific accuracies for each year are provided in the respective tables. We provide this dataset "as is" without any warranty regarding the accuracy or completeness and exclude all liability.    References: Blickensdörfer, L., Schwieder, M., Pflugmacher, D., Nendel, C., Erasmi, S., & Hostert, P. (2022). Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany. Remote Sensing of Environment, 269, 112831. BKG, Bundesamt für Kartographie und Geodäsie (2015). Digitales Geländemodell Gitterweite 10 m. DGM10. https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/dgm10.pdf (last accessed: 28. April 2022). BKG, Bundesamt für Kartographie und Geodäsie (2020). Digitales Basis-Landschaftsmodell. https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/basis-dlm.pdf (last accessed: 28. April 2022). Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, 1124. Statistisches Bundesamt, Deutschland (2024). Ökosystematlas Deutschland https://oekosystematlas-ugr.destatis.de/ (last accessed: 08.02.2024). ___________________________________________________________________________ National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021) © 2024 by Schwieder, Marcel; Tetteh, Gideon Okpoti; Blickensdörfer, Lukas; Gocht, Alexander; Erasmi, Stefan;  licensed under CC BY 4.0.  Funding was provided by the German Federal Ministry of Food and Agriculture as part of the joint project “Monitoring der biologischen Vielfalt in Agrarlandschaften” (<a href="https://www.agrarmonitoring-monvia.de/en/">MonViA</a>, Monitoring of biodiversity in agricultural landscapes). The study was financially supported by the European Environment Agency and the European Union’s Horizon Europe Research and Innovation programme under Grant Agreement No 101060423 (LAMASUS).

FIGURE 1 in Discovery of the primary aphid (Hemiptera: Aphidomorpha) and scale insect (Hemiptera: Coccomorpha) type specimens from the collection of Theodor Hartig (1805-1880)

FIGURE 1. Theodor Hartig's Sternorrhyncha collection after Burckhardt's (2008) removal of the Psylloidea.

FIGURE 12 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 12. Distribution map based on label information attached to the type specimens in NHMW. Identifications are nominal species as identified by Attems (1951), all here considered to be Lithobius iranicus Attems, 1951, except for L. inquiriendus.

FIGURE 8 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 8. Sternites of ultimate leg-bearing segment and intermediate segment in females, ventral view. A–B. Lithobius iranicus Attems, 1951. A. Lectotype, NHMW MY3963. B. NHMW MY5700. C. Lithobius rhiknus Attems, 1951 syn. nov., syntype, NHMW MY3942. D. Lithobius inquiriendus Attems, 1951, syntype, NHMW MY10386.

FIGURE 1. Lithobius iranicus Attems, 1951 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 1. Lithobius iranicus Attems, 1951, ♀ lectotype NHMW MY3963. A. Habitus, dorsal view. B. Cephalic plate and T1, dorsal view. C. Forcipular segment, ventral view. D. Ocelli and Tömösváry's organ, lateral view. Abbreviation: TO = Tömösváry's organ.

FIGURE 4. Lithobius iranicus Attems, 1951 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 4. Lithobius iranicus Attems, 1951, ♂, new specimen NHMW MY10387. A. Close-up of coxosternal margin showing teeth and porodont. B. TT9-13, dorsal view. C. Posterior segments, ventral view. Abbreviation: Po = porodont.

FIGURE 11 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 11. Maximum Likelihood tree based on all molecular data (28S-16S-COI). Above nodes: bootstrap values>50%, black dot for 100% support.

FIGURE 3. Lithobius iranicus Attems, 1951 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 3. Lithobius iranicus Attems, 1951, ♂, new specimen NHMW MY10387. A. Habitus, dorsal view. B. Cephalic plate and T1, dorsal view. C. Ocelli, lateral view. D. Forcipular segment, ventral view.

FIGURE 9 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 9. Sternites of ultimate leg-bearing segment and first genital segment in males, ventral view. A–C. Lithobius iranicus Attems, 1951. A. Paralectotype, NHMW MY3964. B. NHMW MY5701. C. NHMW MY5700. D–E. Lithobius inaequidens Attems, 1951 syn. nov. D. Syntype, NHMW MY3962. E. Syntype, NHMW MY10385. F. Lithobius rhiknus Attems, 1951 syn. nov., syntype, NHMW MY4044.

FIGURE 5 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 5. Paired sulci on ultimate legs of males, dorsal view. A–B. Lithobius iranicus Attems, 1951. A. Paralectotype NHMW MY10383. B. NHMW MY10387. C. Lithobius rhiknus Attems, 1951 syn. nov., leg 13, syntype NHMW MY4044. D. Lithobius inaequidens Attems, 1951 syn. nov., NHMW MY3962. Arrows pointing to sulci.

FIGURE 6 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 6. Close-up of coxosternal teeth. A–F. Lithobius iranicus Attems, 1951. A. Paralectotype ♂, NHMW MY10383. B. Paralectotype ♂, NHMW MY10384. C. Paralectotype ♂, NHMW MY3964. D. Non-type ♂ NHMW MY5701. E. Non-type ♀, NHMW MY5700. F. Non-type ♂, NHMW MY5700. G–H. Lithobius inaequidens Attems, 1951 syn. nov. G. Syntype ♂, NHMW MY3962. H. Syntype ♂, NHMW MY10385. I. Lithobius inquiriendus Attems, 1951, syntype ♀, NHMW MY10386. J. Lithobius rhiknus Attems, 1951 syn. nov., syntype ♀, NHMW MY3942.

FIGURE 7 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951

FIGURE 7. Ocellar field in lateral view. A. Lithobius iranicus Attems, 1951, paralectotype ♂, NHMW MY3964. B. Lithobius inaequidens Attems, 1951 syn. nov., syntype ♂, NHMW MY3962. C. Lithobius inaequidens Attems, 1951 syn. nov., syntype ♂, NHMW MY10385. D. Lithobius iranicus Attems, 1951, syntype ♂, NHMW MY10383. E. Lithobius rhiknus Attems, 1951 syn. nov., syntype ♂, NHMW MY4044. Abbreviation: TO = Tömösváry's organ.

openMar 2024View details →

Acoustic feedback tendency in hearing aids for different types and couplings in relation to insertion gain

To make signals audible again for hearing impaired people, hearing aids pick up the sounds with a microphone amplify them and play them back in the ear canal. Parts of the amplified output signal return to the microphone by an acoustic pathway. Depending on the selected amplification, this can result in 'critical feedback', which limits the maximum possible amplification of hearing aids.  The Insertion-Gain-Related Feedback Path (IFP) was introduced to characterize the acoustic feedback path. It describes the frequency-dependent gain that a hearing aid can provide until a critical feedback condition becomes possible. In addition to the feedback signal, the IFP also takes the Real Ear Unaided Gain (REUG), the Microphone Location Effect (MLE) and the hearing aid transmission to the eardrum into account. Technical measurements were used in this work, including the use of hearing aid dummies and probe microphones. This was used to determine the IFPs in 28 test subjects' ears. This data is freely available.