Investigations of D-glycero-D-ido-octulose (D-g-D-i-oct) metabolism and transketolases in the resurrection plant <em>Craterostigma plantagineum</em>

Eight-carbon monosaccharides (C8H16O8) occur naturally in a number of higher plants (e.g. avocado and sedum species), but they did not get much attention in research compared to common sugars (e.g. glucose, fructose and sucrose). D-glycero-D-ido-2-octulose (D-g-D-i-oct), an eight carbon monosaccharide has been reported as a rare but abundant monosaccharide in leaves of the resurrection plant Craterostigma plantagineum. When C. plantagineum plants encounter dehydration, D-g-D-i-oct is converted to sucrose that plays a fundamental role in regulating osmotic potential and protecting membranes as well as macro-molecules in resurrection plants. Previous studies suggested that the metabolism of D-g-D-i-oct involves transketolase and the exchange reaction of an alternative Calvin cycle may be responsible for the synthesis of D-g-D-i-oct phosphate. However, the metabolic pathways and the properties of the octulose molecule have not been well investigated. Three different isoforms of transketolase of C. plantagineum and their functions are not clearly characterized. Thus, some questions need to be answered: whether the exchange reaction exists in C. plantagineum and whether the three different isoforms of transketolase in C. plantagineum have the same function, as well as how the three different isoforms are regulated in C. plantagineum? In this study I focused on the carbohydrate status in relation to desiccation tolerance, developmental stage and selected environmental factors to explore the function of D-g-D-i-oct in C. plantagineum. The transketolases in C. plantagineum were extracted and the recombinant transketolase 3, 7 and 10 were purified. All proteins were tested in the enzymatic assays to determine the reaction products. In addition, the inhibitor of transketolase oxythiamine, was used in the rehydration of leaves of C. plantagineum to determine the activity of transketolase and in the enzymatic assays of recombinant transketolases. Besides, the relationship between D-g-D-i-oct and phosphate was studied. From the results, it is concluded that desiccation tolerance is regulated by senescence and this reflects the strategy of resurrection plants to adapt to a complex environment. The differences in expression patterns of senescence-related genes and carbohydrate status of senescent and vigorous C. plantagineum plants indicate that resurrection plants or their organs will be prepared in different ways for possible dehydration stress in a developmental-stage specific manner. By analyzing the levels of sucrose, it is found that sucrose synthesis is more inclined to be regulated by water stress than by senescence in C. plantagineum. Light is an important factor for D-g-D-i-oct synthesis. The D-g-D-i-oct level is strictly controlled in C. plantagienum and D-g-D-i-oct was consumed to defend reactive oxygen species (ROS) produced by paraquat. D-g-D-i-oct is also localized in the cytosol and could be exported from leaves. Relative to common sugars present in C. plantagineum leaves, the substantial accumulation of D-g-D-i-oct may propose that D-g-D-i-oct is not primarily a sensing molecule but has a “structural” role. The excellent hydroxyl scavenging ability of D-g-D-i-oct implies that D-g-D-i-oct may be important for ROS scavenging which could further explain the substantial accumulation. Our study suggests that the three isoforms of C. plantagineum transketolase may exert different functions. The tkt3 plays a role in the photosynthesis and the pentose phosphate pathway. The tkt7 and tkt10 isoforms of transketolase, which show distinct specificity in function and evolution catalyze the formation of D-g-D-i-oct-8-phosphate using glucose-6-phosphate and fructose-6-phosphate as substrate. The activity of transketolase was inhibited by the analogue of thiamine diphosphate, oxythiamine. The transketolase of E. coli could perform the same reactions as tkt7and tkt10. This may indicate that the D-g-D-i-oct and its metabolism might commonly exist in organisms. Although the phosphatase that hydrolyzes D-g-D-i-oct phosphate to produce D-g-D-i-oct could not be identified and characterized so far, the influence of phosphate on D-g-D-i-oct metabolism indicates that the phosphatase exists and is activated by a lack of phosphate and attenuated by an excess of phosphate

Presbycusis-Related Tinnitus and Cognitive Impairment: Gender Differences and Common Mechanisms

Presbycusis-related tinnitus and cognitive impairment are common in the elderly and generate a massive burden on family and society. Except for age, the study explored the gender differences in the prevalence of the three diseases. We found that women have an advantage in maintaining better cognitive and auditory functions. Recent studies suggest the complex links among the three diseases. Peripheral hearing loss can affect sound coding and neural plasticity, which will lead to cognitive impairment and tinnitus. The deficits of the central nervous system, especially central auditory structures, can, in turn, cause the presbycusis. The interaction among three diseases indicated that comprehensive assessment, intervention and treatment in consideration of hearing loss, tinnitus and cognitive impairment are important to decay aging

Optical limiting using Laguerre-Gaussian beams

We demonstrate optical limiting using the self-lensing effect of a higher-order Laguerre-Gaussian beam in a thin dye-doped polymer sample, which we find is consistent with our model using Gaussian decomposition. The peak phase shift in the sample required for limiting is smaller than for a fundamental Gaussian beam with the added flexibility that the nonlinear medium can be placed either in front of or behind the beam focus.Comment: 3 pages, 4 figure

WGCN: Graph Convolutional Networks with Weighted Structural Features

Graph structural information such as topologies or connectivities provides valuable guidance for graph convolutional networks (GCNs) to learn nodes' representations. Existing GCN models that capture nodes' structural information weight in- and out-neighbors equally or differentiate in- and out-neighbors globally without considering nodes' local topologies. We observe that in- and out-neighbors contribute differently for nodes with different local topologies. To explore the directional structural information for different nodes, we propose a GCN model with weighted structural features, named WGCN. WGCN first captures nodes' structural fingerprints via a direction and degree aware Random Walk with Restart algorithm, where the walk is guided by both edge direction and nodes' in- and out-degrees. Then, the interactions between nodes' structural fingerprints are used as the weighted node structural features. To further capture nodes' high-order dependencies and graph geometry, WGCN embeds graphs into a latent space to obtain nodes' latent neighbors and geometrical relationships. Based on nodes' geometrical relationships in the latent space, WGCN differentiates latent, in-, and out-neighbors with an attention-based geometrical aggregation. Experiments on transductive node classification tasks show that WGCN outperforms the baseline models consistently by up to 17.07% in terms of accuracy on five benchmark datasets

Ask Question First for Enhancing Lifelong Language Learning

Lifelong language learning aims to stream learning NLP tasks while retaining knowledge of previous tasks. Previous works based on the language model and following data-free constraint approaches have explored formatting all data as "begin token (\textit{B}) + context (\textit{C}) + question (\textit{Q}) + answer (\textit{A})" for different tasks. However, they still suffer from catastrophic forgetting and are exacerbated when the previous task's pseudo data is insufficient for the following reasons: (1) The model has difficulty generating task-corresponding pseudo data, and (2) \textit{A} is prone to error when \textit{A} and \textit{C} are separated by \textit{Q} because the information of the \textit{C} is diminished before generating \textit{A}. Therefore, we propose the Ask Question First and Replay Question (AQF-RQ), including a novel data format "\textit{BQCA}" and a new training task to train pseudo questions of previous tasks. Experimental results demonstrate that AQF-RQ makes it easier for the model to generate more pseudo data that match corresponding tasks, and is more robust to both sufficient and insufficient pseudo-data when the task boundary is both clear and unclear. AQF-RQ can achieve only 0.36\% lower performance than multi-task learning.Comment: This paper has been accepted for publication at COLING 202

Magnesia-stabilised zirconia solid electrolyte assisted electrochemical investigation of iron ions in the SiO2-CaO-MgO-Al2O3 molten slag at 1723 K

Production of metallic iron through molten oxide electrolysis using inert electrodes is an alternative route for fast ironmaking without CO2 emissions. The fact that many inorganic oxides melt at ultrahigh temperatures (>1500 K) challenges conventional electro-analytical techniques used in aqueous, organic and molten salt electrolytes. However, in order to design a feasible and effective electrolytic process, it is necessary to best understand the electrochemical properties of iron ions in molten oxide electrolytes. In this work, a magnesia-stabilised zirconia (MSZ) tube with a closed end was used to construct an integrated three-electrode cell with the “MSZ | Pt | O2 (air)” assembly functioning as the solid electrolyte, the reference electrode and also the counter electrode. Electrochemical reduction of iron ions was systematically investigated on an iridium (Ir) wire working electrode in the SiO2-CaO-MgO-Al2O3 molten slag at 1723 K by cyclic voltammetry (CV), square wave voltammetry (SWV), chronopotentiometry (CP) and potentiostatic electrolysis (PE). The results show that the electro-reduction of the Fe2+ ion to Fe on the Ir electrode in the molten slag follows a single two-electron transfer step, and the rate of the process is diffusion controlled. The peak current on the obtained CVs is proportional to the concentration of the Fe2+ ion in the molten slag and the square root of scan rate. The diffusion coefficient of Fe2+ ions in the molten slag containing 5 wt% FeO at 1723 K was derived to be (3.43 ± 0.06)×10-6 cm2 s-1 from CP analysis. However, a couple of following processes, i.e. alloy formation on the Ir electrode surface and interdiffusion were found to affect the kinetics of iron deposition. An ECC mechanism is proposed to account for the CV observations. The findings from this work confirm that zirconia-based solid electrolytes can play an important role in electrochemical fundamental research in high temperature molten slag electrolytes

Determination of erlotinib in rabbit plasma by liquid chromatography mass spectrometry

A sensitive and selective liquid chromatography mass spectrometry (LC–MS) method for determination of erlotinib in rabbit plasma was developed. After addition of midazolam as internal standard (IS), protein precipitation by acetonitrile was used as sample preparation. Chromatographic separation was achieved on a Zorbax SB-C18 (2.1 × 150 mm, 5 μm) column with acetonitrile-0.1 % formic acid as mobile phase with gradient elution. Electrospray ionization (ESI) source was applied and operated in positive ion mode; multiple reaction monitoring (MRM) mode was used to quantification using target fragment ions m/z 394→336 for erlotinib and m/z 326→291 for the IS. Calibration plots were linear over the range of 5-2000 ng/mL for erlotinib in plasma. Lower limit of quantification (LLOQ) for erlotinib was 5 ng/mL. Mean recovery of erlotinib from plasma was in the range 84.5-95.7 %. CV of intra-day and interday precision were both less than 12 %. This method is simple and sensitive enough to be used in pharmacokinetic research for determination of erlotinib in rabbit plasma.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Determination of erlotinib in rabbit plasma by liquid chromatography mass spectrometry

A sensitive and selective liquid chromatography mass spectrometry (LC–MS) method for determination of erlotinib in rabbit plasma was developed. After addition of midazolam as internal standard (IS), protein precipitation by acetonitrile was used as sample preparation. Chromatographic separation was achieved on a Zorbax SB-C18 (2.1 × 150 mm, 5 μm) column with acetonitrile-0.1 % formic acid as mobile phase with gradient elution. Electrospray ionization (ESI) source was applied and operated in positive ion mode; multiple reaction monitoring (MRM) mode was used to quantification using target fragment ions m/z 394→336 for erlotinib and m/z 326→291 for the IS. Calibration plots were linear over the range of 5-2000 ng/mL for erlotinib in plasma. Lower limit of quantification (LLOQ) for erlotinib was 5 ng/mL. Mean recovery of erlotinib from plasma was in the range 84.5-95.7 %. CV of intra-day and interday precision were both less than 12 %. This method is simple and sensitive enough to be used in pharmacokinetic research for determination of erlotinib in rabbit plasma.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Enhanced Fairness Testing via Generating Effective Initial Individual Discriminatory Instances

Fairness testing aims at mitigating unintended discrimination in the decision-making process of data-driven AI systems. Individual discrimination may occur when an AI model makes different decisions for two distinct individuals who are distinguishable solely according to protected attributes, such as age and race. Such instances reveal biased AI behaviour, and are called Individual Discriminatory Instances (IDIs). In this paper, we propose an approach for the selection of the initial seeds to generate IDIs for fairness testing. Previous studies mainly used random initial seeds to this end. However this phase is crucial, as these seeds are the basis of the follow-up IDIs generation. We dubbed our proposed seed selection approach I&D. It generates a large number of initial IDIs exhibiting a great diversity, aiming at improving the overall performance of fairness testing. Our empirical study reveal that I&D is able to produce a larger number of IDIs with respect to four state-of-the-art seed generation approaches, generating 1.68X more IDIs on average. Moreover, we compare the use of I&D to train machine learning models and find that using I&D reduces the number of remaining IDIs by 29% when compared to the state-of-the-art, thus indicating that I&D is effective for improving model fairnessComment: 19 pages, 7 figure