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Etmopteridae (lantern sharks) is the most species-rich family of sharks, comprising more than 50 species.
Many species are described from few individuals, and re-collection of specimens is often hindered by the remoteness of their sampling sites.
For taxonomic studies, comparative morphological analysis of type specimens housed in natural history collections has been the main source of evidence.
In contrast, DNA sequence information has rarely been used.
Most lantern shark collection specimens, including the types, were formalin fixed before long-term storage in ethanol solutions.
The DNA damage caused by both fixation and preservation of specimens has excluded these specimens from DNA sequence-based phylogenetic analyses so far.
However, recent advances in the field of ancient DNA have allowed recovery of wet-collection specimen DNA sequence data.
Here we analyse archival mitochondrial DNA sequences, obtained using ancient DNA approaches, of two wet-collection lantern shark paratype specimens, namely Etmopterus litvinovi and E. pycnolepis, for which the type series represent the only known individuals.
Target capture of mitochondrial markers from single-stranded DNA libraries allows for phylogenetic placement of both species.
Our results suggest synonymy of E. benchleyi with E. litvinovi but support the species status of E. pycnolepis. This revised taxonomy is helpful for future conservation and management efforts, as our results indicate a larger distribution range of E. litvinovi. This study further demonstrates the importance of wet-collection type specimens as genetic resource for taxonomic research.
The degree of detrimental effects inflicted on mankind by the COVID-19 pandemic increased the need to develop ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable) POCT (point of care testing) to overcome the current and any future pandemics. Much effort in research and development is currently advancing the progress to overcome the diagnostic pressure built up by emerging new pathogens. LAMP (loop-mediated isothermal amplification) is a well-researched isothermal technique for specific nucleic acid amplification which can be combined with a highly sensitive immunochromatographic readout via lateral flow assays (LFA). Here we discuss LAMP-LFA robustness, sensitivity, and specificity for SARS-CoV-2 N-gene detection in cDNA and clinical swab-extracted RNA samples. The LFA readout is designed to produce highly specific results by incorporation of biotin and FITC labels to 11-dUTP and LF (loop forming forward) primer, respectively. The LAMP-LFA assay was established using cDNA for N-gene with an accuracy of 95.65%. To validate the study, 82 SARS-CoV-2-positive RNA samples were tested. Reverse transcriptase (RT)-LAMP-LFA was positive for the RNA samples with an accuracy of 81.66%; SARS-CoV-2 viral RNA was detected by RT-LAMP-LFA for as low as CT-33. Our method reduced the detection time to 15 min and indicates therefore that RT-LAMP in combination with LFA represents a promising nucleic acid biosensing POCT platform that combines with smartphone based semi-quantitative data analysis.
This study focuses on three key aspects: (a) crude throat swab samples in a viral transport medium (VTM) as templates for RT-LAMP reactions; (b) a biotinylated DNA probe with enhanced specificity for LFA readouts; and (c) a digital semi-quantification of LFA readouts. Throat swab samples from SARS-CoV-2 positive and negative patients were used in their crude (no cleaning or pre-treatment) forms for the RT-LAMP reaction. The samples were heat-inactivated but not treated for any kind of nucleic acid extraction or purification. The RT-LAMP (20 min processing time) product was read out by an LFA approach using two labels: FITC and biotin. FITC was enzymatically incorporated into the RT-LAMP amplicon with the LF-LAMP primer, and biotin was introduced using biotinylated DNA probes, specifically for the amplicon region after RT-LAMP amplification. This assay setup with biotinylated DNA probe-based LFA readouts of the RT-LAMP amplicon was 98.11% sensitive and 96.15% specific. The LFA result was further analysed by a smartphone-based IVD device, wherein the T-line intensity was recorded. The LFA T-line intensity was then correlated with the qRT-PCR Ct value of the positive swab samples. A digital semi-quantification of RT-LAMP-LFA was reported with a correlation coefficient of R2 = 0.702. The overall RT-LAMP-LFA assay time was recorded to be 35 min with a LoD of three RNA copies/µL (Ct-33). With these three advancements, the nucleic acid testing-point of care technique (NAT-POCT) is exemplified as a versatile biosensor platform with great potential and applicability for the detection of pathogens without the need for sample storage, transportation, or pre-processing.
Functional characterization of ROS-responsive genes, ANAC085 and ATR7, in Arabidopsis thaliana
(2023)
Chromatographic separation of the extract of the roots of Dorstenia kameruniana (family Moraceae) led to the isolation of three new benzylbenzofuran derivatives, 2-(p-hydroxybenzyl)benzofuran-6-ol (1), 2-(p-hydroxybenzyl)-7-methoxybenzofuran-6-ol (2) and 2-(p-hydroxy)-3-(3-methylbut-2-en-1-yl)benzyl)benzofuran-6-ol (3) (named dorsmerunin A, B and C, respectively), along with the known furanocoumarin, bergapten (4). The twigs of Dorstenia kameruniana also produced compounds 1-4 as well as the known chalcone licoagrochalcone A (5). The structures were elucidated by NMR spectroscopy and mass spectrometry. The isolated compounds displayed cytotoxicity against the sensitive CCRF-CEM and multidrug-resistant CEM/ADR5000 leukemia cells, where compounds 4 and 5 had the highest activities (IC50 values of 7.17 mu M and 5.16 mu M, respectively) against CCRF-CEM leukemia cells. Compound 5 also showed cytotoxicity against 7 sensitive or drug-resistant solid tumor cell lines (breast carcinoma, colon carcinoma, glioblastoma), with IC50 below 50 mu M, whilst 4 showed selective activity.
A new isoflavone, 4′-prenyloxyvigvexin A (1) and a new pterocarpan, (6aR,11aR)-3,8-dimethoxybitucarpin B (2) were isolated from the leaves of Lonchocarpus bussei and the stem bark of Lonchocarpus eriocalyx, respectively. The extract of L. bussei also gave four known isoflavones, maximaisoflavone H, 7,2′-dimethoxy-3′,4′-methylenedioxyisoflavone, 6,7,3′-trimethoxy-4′,5′-methylenedioxyisoflavone, durmillone; a chalcone, 4-hydroxylonchocarpin; a geranylated phenylpropanol, colenemol; and two known pterocarpans, (6aR,11aR)-maackiain and (6aR,11aR)-edunol. (6aR,11aR)-Edunol was also isolated from the stem bark of L. eriocalyx. The structures of the isolated compounds were elucidated by spectroscopy. The cytotoxicity of the compounds was tested by resazurin assay using drug-sensitive and multidrug-resistant cancer cell lines. Significant antiproliferative effects with IC50 values below 10 μM were observed for the isoflavones 6,7,3′-trimethoxy-4′,5′-methylenedioxyisoflavone and durmillone against leukemia CCRF-CEM cells; for the chalcone, 4-hydroxylonchocarpin and durmillone against its resistant counterpart CEM/ADR5000 cells; as well as for durmillone against the resistant breast adenocarcinoma MDA-MB231/BCRP cells and resistant gliobastoma U87MG.ΔEGFR cells.
The central rift of the Red Sea has 25 brine pools with different physical and geochemical characteristics. Atlantis II (ATIID), Discovery Deeps (DD) and Chain Deep (CD) are characterized by high salinity, temperature and metal content. Several studies reported microbial communities in these brine pools, but few studies addressed the brine pool sediments. Therefore, sediment cores were collected from ATIID, DD, CD brine pools and an adjacent brine-influenced site. Sixteen different lithologic sediment sections were subjected to shotgun DNA pyrosequencing to generate 1.47 billion base pairs (1.47 x 10(9) bp). We generated sediment-specific reads and attempted to annotate all reads. We report the phylogenetic and biochemical uniqueness of the deepest ATIID sulfur-rich brine pool sediments. In contrary to all other sediment sections, bacteria dominate the deepest ATIID sulfur-rich brine pool sediments. This decrease in virus-to-bacteria ratio in selected sections and depth coincided with an overrepresentation of mobile genetic elements. Skewing in the composition of viruses-to-mobile genetic elements may uniquely contribute to the distinct microbial consortium in sediments in proximity to hydrothermally active vents of the Red Sea and possibly in their surroundings, through differential horizontal gene transfer.
Aging is a highly controlled biological process characterized by a progressive deterioration of various cellular activities. One of several hallmarks of aging describes a link to transcriptional alteration, suggesting that it may impact the steady-state mRNA levels. We analyzed the mRNA steady-state levels of polyCAG-encoding transgenes and endogenous genes under the control of well-characterized promoters for intestinal (vha-6), muscular (unc-54, unc-15) and pan-neuronal (rgef-1, unc-119) expression in the nematode Caenorhabditis elegans. We find that there is not a uniform change in transcriptional profile in aging, but rather a tissue-specific difference in the mRNA levels of these genes. While levels of mRNA in the intestine (vha-6) and muscular (unc-54, unc-15) cells decline with age, pan-neuronal tissue shows more stable mRNA expression (rgef-1, unc-119) which even slightly increases with the age of the animals. Our data on the variations in the mRNA abundance from exemplary cases of endogenous and transgenic gene expression contribute to the emerging evidence for tissue-specific variations in the aging process.
Pollination syndromes and their predictive power regarding actual plant-animal interactions have been controversially discussed in the past. We investigate pollination syndromes in Balsaminaceae, utilizing quantitative respectively categorical data sets of flower morphometry, signal and reward traits for 86 species to test for the effect of different types of data on the test patterns retrieved. Cluster Analyses of the floral traits are used in combination with independent pollinator observations. Based on quantitative data we retrieve seven clusters, six of them corresponding to plausible pollination syndromes and one additional, well-supported cluster comprising highly divergent floral architectures. This latter cluster represents a non-syndrome of flowers not segregated by the specific data set here used. Conversely, using categorical data we obtained only a rudimentary resolution of pollination syndromes, in line with several earlier studies. The results underscore that the use of functional, exactly quanitified trait data has the power to retrieve pollination syndromes circumscribed by the specific data used. Data quality can, however, not be replaced by sheer data volume. With this caveat, it is possible to identify pollination syndromes from large datasets and to reliably extrapolate them for taxa for which direct observations are unavailable.
Stress inoculation facilitates active avoidance learning of the semi-precocial rodent Octodon degus
(2010)
A growing body of evidence highlights the impact of the early social environment for the adequate development of brain and behavior in animals and humans. Disturbances of this environment were found to be both maladaptive and adaptive to emotional and cognitive function. Using the semi-precocial, biparental rodent Octodon degus, we aimed to examine (i) the impact of age (juvenile/adult), sex (male/female), and (ii) "motivation" to solve the task (by applying increasing foot-shock-intensities) on two-way active avoidance (TWA) learning in socially reared degus, and (iii) whether early life stress inoculation by 1 h daily parental separation during the first three weeks of life has maladaptive or adaptive consequences on cognitive function as measured by TWA learning. Our results showed that (i) juvenile degus, unlike altricial rats of the same age, can successfully learn the TWA task comparable to adults, and (ii) that learning performance improves with increasing "task motivation", irrespective of age and sex. Furthermore, we revealed that (iii) stress inoculation improves avoidance learning, particularly in juvenile males, quantitatively and qualitatively depending on "task motivation". In conclusion, the present study describes for the first time associative learning in O. degus and its modulation by early life stress experience as an animal model to study the underlying mechanisms of learning and memory in the stressed and unstressed brain. Although, stress is commonly viewed as being maladaptive, our data indicate that early life stress inoculation triggers developmental cascades of adaptive functioning, which may improve cognitive and emotional processing of stressors later in life.
Indoor mesocosm experiments were conducted to test for potential climate change effects on the spring succession of Baltic Sea plankton. Two different temperature (Delta 0 A degrees C and Delta 6 A degrees C) and three light scenarios (62, 57 and 49 % of the natural surface light intensity on sunny days), mimicking increasing cloudiness as predicted for warmer winters in the Baltic Sea region, were simulated. By combining experimental and modeling approaches, we were able to test for a potential dietary mismatch between phytoplankton and zooplankton. Two general predator-prey models, one representing the community as a tri-trophic food chain and one as a 5-guild food web were applied to test for the consequences of different temperature sensitivities of heterotrophic components of the plankton. During the experiments, we observed reduced time-lags between the peaks of phytoplankton and protozoan biomass in response to warming. Microzooplankton peak biomass was reached by 2.5 day A degrees C-1 earlier and occurred almost synchronously with biomass peaks of phytoplankton in the warm mesocosms (Delta 6 A degrees C). The peak magnitudes of microzooplankton biomass remained unaffected by temperature, and growth rates of microzooplankton were higher at Delta 6 A degrees C (mu(a dagger 0 A degrees C) = 0.12 day(-1) and mu(a dagger 6 A degrees C) = 0.25 day(-1)). Furthermore, warming induced a shift in microzooplankton phenology leading to a faster species turnover and a shorter window of microzooplankton occurrence. Moderate differences in the light levels had no significant effect on the time-lags between autotrophic and heterotrophic biomass and on the timing, biomass maxima and growth rate of microzooplankton biomass. Both models predicted reduced time-lags between the biomass peaks of phytoplankton and its predators (both microzooplankton and copepods) with warming. The reduction of time-lags increased with increasing Q(10) values of copepods and protozoans in the tritrophic food chain. Indirect trophic effects modified this pattern in the 5-guild food web. Our study shows that instead of a mismatch, warming might lead to a stronger match between protist grazers and their prey altering in turn the transfer of matter and energy toward higher trophic levels.
This article documents the addition of 283 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Agalinis acuta; Ambrosia artemisiifolia; Berula erecta; Casuarius casuarius; Cercospora zeae-maydis; Chorthippus parallelus; Conyza canadensis; Cotesia sesamiae; Epinephelus acanthistius; Ficedula hypoleuca; Grindelia hirsutula; Guadua angustifolia; Leucadendron rubrum; Maritrema novaezealandensis; Meretrix meretrix; Nilaparvata lugens; Oxyeleotris marmoratus; Phoxinus neogaeus; Pristomyrmex punctatus; Pseudobagrus brevicorpus; Seiridium cardinale; Stenopsyche marmorata; Tetranychus evansi and Xerus inauris. These loci were cross-tested on the following species: Agalinis decemloba; Agalinis tenella; Agalinis obtusifolia; Agalinis setacea; Agalinis skinneriana; Cercospora zeina; Cercospora kikuchii; Cercospora sorghi; Mycosphaerella graminicola; Setosphaeria turcica; Magnaporthe oryzae; Cotesia flavipes; Cotesia marginiventris; Grindelia Xpaludosa; Grindelia chiloensis; Grindelia fastigiata; Grindelia lanceolata; Grindelia squarrosa; Leucadendron coniferum; Leucadendron salicifolium; Leucadendron tinctum; Leucadendron meridianum; Laodelphax striatellus; Sogatella furcifera; Phoxinus eos; Phoxinus rigidus; Phoxinus brevispinosus; Phoxinus bicolor; Tetranychus urticae; Tetranychus turkestani; Tetranychus ludeni; Tetranychus neocaledonicus; Tetranychus amicus; Amphitetranychus viennensis; Eotetranychus rubiphilus; Eotetranychus tiliarium; Oligonychus perseae; Panonychus citri; Bryobia rubrioculus; Schizonobia bundi; Petrobia harti; Xerus princeps; Spermophilus tridecemlineatus and Sciurus carolinensis.
Komplexe Systeme reichen von "harten", physikalischen, wie Klimaphysik, Turbulenz in Fluiden oder Plasmen bis zu so genannten "weichen", wie man sie in der Biologie, der Physik weicher Materie, Soziologie oder Ökonomie findet. Die Ausbildung von Verständnis zu einem solchen System beinhaltet eine Beschreibung in Form von Statistiken und schlussendlich mathematischen Gleichungen. Moderne Datenanalyse stellt eine große Menge von Werkzeugen zur Analyse von Komplexität auf verschiedenen Beschreibungsebenen bereit. In diesem Kurs werden statistische Methoden mit einem Schwerpunkt auf dynamischen Systemen diskutiert und eingeübt. Auf der methodischen Seite werden lineare und nichtlineare Ansätze behandelt, inklusive der Standard-Werkzeuge der deskriptiven und schlussfolgernden Statistik, Wavelet Analyse, Nichtparametrische Regression und der Schätzung nichtlinearer Maße wie fraktaler Dimensionen, Entropien und Komplexitätsmaßen. Auf der Modellierungsseite werden deterministische und stochastische Systeme, Chaos, Skalierung und das Entstehen von Komplexität durch Wechselwirkung diskutiert - sowohl für diskrete als auch für ausgedehnte Systeme. Die beiden Ansätze werden durch Systemanalyse jeweils passender Beispiele vereint.
Komplexe Systeme reichen von "harten", physikalischen, wie Klimaphysik, Turbulenz in Fluiden oder Plasmen bis zu so genannten "weichen", wie man sie in der Biologie, der Physik weicher Materie, Soziologie oder Ökonomie findet. Die Ausbildung von Verständnis zu einem solchen System beinhaltet eine Beschreibung in Form von Statistiken und schlussendlich mathematischen Gleichungen. Moderne Datenanalyse stellt eine große Menge von Werkzeugen zur Analyse von Komplexität auf verschiedenen Beschreibungsebenen bereit. In diesem Kurs werden statistische Methoden mit einem Schwerpunkt auf dynamischen Systemen diskutiert und eingeübt. Auf der methodischen Seite werden lineare und nichtlineare Ansätze behandelt, inklusive der Standard-Werkzeuge der deskriptiven und schlussfolgernden Statistik, Wavelet Analyse, Nichtparametrische Regression und der Schätzung nichtlinearer Maße wie fraktaler Dimensionen, Entropien und Komplexitätsmaßen. Auf der Modellierungsseite werden deterministische und stochastische Systeme, Chaos, Skalierung und das Entstehen von Komplexität durch Wechselwirkung diskutiert - sowohl für diskrete als auch für ausgedehnte Systeme. Die beiden Ansätze werden durch Systemanalyse jeweils passender Beispiele vereint.
Komplexe Systeme reichen von "harten", physikalischen, wie Klimaphysik, Turbulenz in Fluiden oder Plasmen bis zu so genannten "weichen", wie man sie in der Biologie, der Physik weicher Materie, Soziologie oder Ökonomie findet. Die Ausbildung von Verständnis zu einem solchen System beinhaltet eine Beschreibung in Form von Statistiken und schlussendlich mathematischen Gleichungen. Moderne Datenanalyse stellt eine große Menge von Werkzeugen zur Analyse von Komplexität auf verschiedenen Beschreibungsebenen bereit. In diesem Kurs werden statistische Methoden mit einem Schwerpunkt auf dynamischen Systemen diskutiert und eingeübt. Auf der methodischen Seite werden lineare und nichtlineare Ansätze behandelt, inklusive der Standard-Werkzeuge der deskriptiven und schlussfolgernden Statistik, Wavelet Analyse, Nichtparametrische Regression und der Schätzung nichtlinearer Maße wie fraktaler Dimensionen, Entropien und Komplexitätsmaßen. Auf der Modellierungsseite werden deterministische und stochastische Systeme, Chaos, Skalierung und das Entstehen von Komplexität durch Wechselwirkung diskutiert - sowohl für diskrete als auch für ausgedehnte Systeme. Die beiden Ansätze werden durch Systemanalyse jeweils passender Beispiele vereint.
Komplexe Systeme reichen von "harten", physikalischen, wie Klimaphysik, Turbulenz in Fluiden oder Plasmen bis zu so genannten "weichen", wie man sie in der Biologie, der Physik weicher Materie, Soziologie oder Ökonomie findet. Die Ausbildung von Verständnis zu einem solchen System beinhaltet eine Beschreibung in Form von Statistiken und schlussendlich mathematischen Gleichungen. Moderne Datenanalyse stellt eine große Menge von Werkzeugen zur Analyse von Komplexität auf verschiedenen Beschreibungsebenen bereit. In diesem Kurs werden statistische Methoden mit einem Schwerpunkt auf dynamischen Systemen diskutiert und eingeübt. Auf der methodischen Seite werden lineare und nichtlineare Ansätze behandelt, inklusive der Standard-Werkzeuge der deskriptiven und schlussfolgernden Statistik, Wavelet Analyse, Nichtparametrische Regression und der Schätzung nichtlinearer Maße wie fraktaler Dimensionen, Entropien und Komplexitätsmaßen. Auf der Modellierungsseite werden deterministische und stochastische Systeme, Chaos, Skalierung und das Entstehen von Komplexität durch Wechselwirkung diskutiert - sowohl für diskrete als auch für ausgedehnte Systeme. Die beiden Ansätze werden durch Systemanalyse jeweils passender Beispiele vereint.
Komplexe Systeme reichen von "harten", physikalischen, wie Klimaphysik, Turbulenz in Fluiden oder Plasmen bis zu so genannten "weichen", wie man sie in der Biologie, der Physik weicher Materie, Soziologie oder Ökonomie findet. Die Ausbildung von Verständnis zu einem solchen System beinhaltet eine Beschreibung in Form von Statistiken und schlussendlich mathematischen Gleichungen. Moderne Datenanalyse stellt eine große Menge von Werkzeugen zur Analyse von Komplexität auf verschiedenen Beschreibungsebenen bereit. In diesem Kurs werden statistische Methoden mit einem Schwerpunkt auf dynamischen Systemen diskutiert und eingeübt. Auf der methodischen Seite werden lineare und nichtlineare Ansätze behandelt, inklusive der Standard-Werkzeuge der deskriptiven und schlussfolgernden Statistik, Wavelet Analyse, Nichtparametrische Regression und der Schätzung nichtlinearer Maße wie fraktaler Dimensionen, Entropien und Komplexitätsmaßen. Auf der Modellierungsseite werden deterministische und stochastische Systeme, Chaos, Skalierung und das Entstehen von Komplexität durch Wechselwirkung diskutiert - sowohl für diskrete als auch für ausgedehnte Systeme. Die beiden Ansätze werden durch Systemanalyse jeweils passender Beispiele vereint.