The phylogenetic relationships of Ig light chain (IGL) genes are difficult to resolve, because these genes are short and evolve relatively fast. Here, we classify the IGL sequences from 12 tetrapod ...species into three distinct groups (κ, λ, and σ isotypes) using conserved amino acid residues, recombination signal sequences, and genomic organization of IGL genes as cladistic markers. From the distribution of the markers we conclude that the earliest extant tetrapods, the amphibians, possess three IGL isotypes: κ, λ, and σ. Of these, two (κ and λ) are also found in reptiles and some mammals. The λ isotype is found in all tetrapods tested to date, whereas the κ isotype seems to have been lost at least in some birds and in the microbat. Conservation of the cladistic molecular markers suggests that they are associated with functional specialization of the three IGL isotypes. The genomic maps of IGL loci reveal multiple gene rearrangements that occurred in the evolution of tetrapod species. These rearrangements have resulted in interspecific variation of the genomic lengths of the IGL loci and the number and order of IGL constituent genes, but the overall organization of the IGL loci has not changed.
In Germany, warm water Recirculating Aquaculture Systems (RAS) are generally integrated with biogas plants. The process sludge produced in aquaculture could be utilized to generate energy. This study ...investigates the potential of process sludge from commercial African catfish ( Clarias gariepinus ) warm water RAS, alongside associated plant production residues (whole plants and pruning residues) for energy generation through anaerobic digestion. Biogas tests, including batch, semi-Continuous Stirred Tank Reactor (CSTR), and Upflow Anaerobic Sludge Blanket Reactor (UASB) were conducted. In batch, methane yields were 229 L(N) / kg VS from the sludge and 173–184 L(N) / kg VS from the various plant substrates (cucumber, paprika, and tomato plants). During CSTR operation, mono-fermentation of sludge produced a methane yield of 265 L(N) / kg VS. Co-fermentation with 25% cucumber residues, based on VS , increased this value to 381 L(N) / kg VS. Mono-fermentation of sludge in the UASB reactor yielded a maximum of 329 L(N) /kg VS. The relatively low TS content and unfavorable C/N ratio in C. gariepinus sludge, along with the low energy density and occasional high sulfur content in the investigated plant substrates, present challenges for CSTR biogas production. These challenges can be partially mitigated through substrate combination. For mono-fermentation of African catfish RAS sludge, the UASB reactor is recommended. Improved solids separation, extraction, and concentration techniques at aquaculture operations are essential for the efficient utilization of aquaculture sludge, especially from African catfish, in biogas plants.
Analysis of gene expression is one of the major ways to better understand plant reactions to changes in environmental conditions. The comparison of many different factors influencing plant growth ...challenges the gene expression analysis for specific gene-targeted experiments, especially with regard to the choice of suitable reference genes. The aim of this study is to compare expression results obtained by Northern blot, semi-quantitative PCR and RT-qPCR, and to identify a reliable set of reference genes for oilseed rape (Brassica napus L.) suitable for comparing gene expression under complex experimental conditions. We investigated the influence of several factors such as sulfur deficiency, different time points during the day, varying light conditions, and their interaction on gene expression in oilseed rape plants. The expression of selected reference genes was indeed influenced under these conditions in different ways. Therefore, a recently developed algorithm, called GrayNorm, was applied to validate a set of reference genes for normalizing results obtained by Northern blot analysis. After careful comparison of the three methods mentioned above, Northern blot analysis seems to be a reliable and cost-effective alternative for gene expression analysis under a complex growth regime. For using this method in a quantitative way a number of references was validated revealing that for our experiment a set of three references provides an appropriate normalization. Semi-quantitative PCR was prone to many handling errors and difficult to control while RT-qPCR was very sensitive to expression fluctuations of the reference genes.
Sex
-
lethal
(
Sxl
) functions as the switch gene for sex-determination in
Drosophila melanogaster
by engaging a regulatory cascade. Thus far the origin and evolution of both the regulatory system ...and SXL protein’s sex-determination function have remained largely unknown. In this study, we explore systematically the
Sxl
homologs in a wide range of insects, including the 12 sequenced
Drosophila
species, medfly, blowflies, housefly,
Megaselia scalaris
, mosquitoes, butterfly, beetle, honeybee, ant, and aphid. We find that both the male-specific and embryo-specific exons exist in all
Drosophila
species. The homologous male-specific exon is also present in
Scaptodrosophila lebanonensis
, but it does not have in-frame stop codons, suggesting the exon’s functional divergence between
Drosophila
and
Scaptodrosophila
after acquiring it in their common ancestor. Two motifs closely related to the exons’ functions, the SXL binding site poly(U) and the transcription-activating motif TAGteam, surprisingly exhibit broader phylogenetic distributions than the exons. Some previously unknown motifs that are restricted to or more abundant in
Drosophila
and
S. lebanonensis
than in other insects are also identified. Finally, phylogenetic analysis suggests that the SXL’s novel sex-determination function in
Drosophila
is more likely attributed to the changes in the N- and C-termini rather than in the RNA-binding region. Thus, our results provide a clearer picture of the phylogeny of the
Sxl
’s
cis
-regulatory elements and protein sequence changes, and so lead to a better understanding of the origin of sex-determination in
Drosophila
and also raise some new questions regarding the evolution of
Sxl
.
Plano-convex microlens arrays of organic-inorganic polymers with tailored optical properties are presented. The fine-tuning of each microlens within an array is achieved by confining inkjet printed ...drops of the polymeric ink onto pre-patterned substrates. The lens optical properties are thus freely specified, and high numerical apertures from 0.45 to 0.9 and focal lengths between 10 μm and 100 μm are demonstrated, confirming theoretical predictions. Combining nanoimprint lithography approaches and inkjet printing enables using the same material for the microlenses and their substrates, improving the optical performances. Microlens arrays with desired specifications are printed reaching yields up to 100% and high lens reproducibility with standard deviations of the apparent contact angle under 1° and of the numerical apertures and focal lengths under 6%. Microlens arrays involving lenses with different characteristics, e.g. multi focal length, and thus focal planes separated by only few microns are printed with the same reproducibility.
The modular synthesis of a novel pseudopeptide scaffold based on a bis(thiourea)hydrazide motif is reported. This compound class is designed to display "amphifinity", i.e. association with a peptide ...strand on one but not the other face of the scaffold, and hence could potentially inhibit β-sheet aggregation.
To enable automatic disassembly of different product types with uncertain condition and degree of wear in remanufacturing, agile production systems that can adapt dynamically to changing requirements ...are needed. Machine learning algorithms can be employed due to their generalization capabilities of learning from various types and variants of products. However, in reality, datasets with a diversity of samples that can be used to train models are difficult to obtain in the initial period. This may cause bad performances when the system tries to adapt to new unseen input data in the future. In order to generate large datasets for different learning purposes, in our project, we present a Blender add-on named MotorFactory to generate customized mesh models of various motor instances. MotorFactory allows to create mesh models which, complemented with additional add-ons, can be further used to create synthetic RGB images, depth images, normal images, segmentation ground truth masks and 3D point cloud datasets with point-wise semantic labels. The created synthetic datasets may be used for various tasks including motor type classification, object detection for decentralized material transfer tasks, part segmentation for disassembly and handling tasks, or even reinforcement learning-based robotics control or view-planning.
Types of maltreatment often co-occur and it is unclear how maltreatment patterns impact on comorbidity in depressed patients.
We analysed associations of maltreatment patterns with a broad range of ...comorbidities assessed with diagnostic interviews in 311 treatment-seeking depressed outpatients.
Latent class analyses identified a “no maltreatment class” (39%), a “mild to moderate abuse and neglect class” (34%), a “severe abuse and neglect class” (14%) and a “severe neglect class” (13%). We found a dose-response association for the first three classes with comorbid disorders, a general psychopathology factor and an interpersonal insecurity factor. Patients in the “severe abuse and neglect” class had increased odds ratios (OR) of suffering from an anxiety disorder (OR 3.58), PTSD (OR 7.09), Borderline personality disorder (OR 7.97) and suicidality (OR 10.04) compared to those without child maltreatment. Patients in the “severe neglect” class did not have a higher risk for comorbidity than those in the “no maltreatment” class.
Class sizes in the “severe abuse and neglect” and the “severe neglect” classes were small and findings should be replicated with other clinical and population samples.
A higher severity rather than the constellation of types of child abuse and neglect was associated with more comorbid disorders. An exception were patients reporting solely severe emotional and physical neglect who had a similar risk for comorbidity as patients without a history of child maltreatment. This may be associated with distinct learning experiences and may inform treatment decisions.
•Four pattern of child maltreatment were identified in adult depressed outpatients.•These distinct patterns were differentially associated with comorbid disorders.•A dose-response relation was found for two groups which included abuse and neglect.•Emotional and physical neglect alone were not associated with more comorbidity.
One of the reasons that the deployment of network intrusion detection methods falls short is the lack of realistic labeled datasets, which makes it challenging to develop and compare techniques. It ...is caused by the large amounts of effort that it takes for a cyber expert to classify network connections. This has raised the need for methods that learn from both labeled and unlabeled data which observations are best to present to the human expert. Hence, Active Learning (AL) methods are of interest.
In this paper, we propose a new hybrid AL method called Jasmine. Firstly, it uses the uncertainty score and anomaly score to determine how suitable each observation is for querying, i.e., how likely it is to enhance classification. Secondly, Jasmine introduces dynamic updating. This allows the model to adjust the balance between querying uncertain, anomalous and randomly selected observations. To this end, Jasmine is able to learn the best query strategy during the labeling process. This is in contrast to the other AL methods in cybersecurity that all have static, predetermined query functions. We show that dynamic updating, and therefore Jasmine, is able to consistently obtain good and more robust results than querying only uncertainties, only anomalies or a fixed combination of the two.
•Jasmine is a novel hybrid Active Learning method for network intrusion detection.•Jasmine queries uncertain, anomalous and randomly selected observations.•Jasmine can dynamically adjust and optimize the balance between these query types.•Jasmine is the first Active Learning method with dynamic updating.•Jasmine performs better than existing static Active Learning methods.
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