Use of headspace solid-phase microextraction for the analysis and characterisation of volatile compounds in rumen contents : a thesis presented in partial fulfillment of the requirements for the degree of Masterate of Science in Chemistry at Massey University

Appendix 2&3 removed due to copyright restrictions. Please consult print copy in Library.Volatile fatty acids (VFAs), alkyl phenols and indolic compounds are produced by rumen microbes during the fermentation of forages in ruminants. In this study, ruminal fluid obtained from sheep was examined by headspace solid-phase microextraction (SPME) sampling followed by GC-MS analysis. This technique provides a non-invasive, clean and selective method to characterize the volatiles in ruminal fluid from an in vitro fermentation system. The factors which can influence the extraction efficiency were studied and include the SPME fibre, sample volume, pH of sample matrix (rumen fluid) and extraction time by the fibre in the headspace. The optimum experimental conditions for the analytes in question included: polyacrylate fibre to perform the headspace SPME above 20 mL of rumen fluid in a 68 mL vial for 5 min, followed by immediate GC-MS analysis. The pH of the rumen fluid sample greatly influenced VFA extraction efficiency. Quantitative analysis of p-cresol, m-cresol, indole and skatolc with SPME were compared with steam distillation simultaneous extraction. This comparison showed that the HS-SPME method was semi-quantitative. The optimum in vitro system (16 mL of rumen fluid and 4 mL of artificial saliva in a 68 mL vial incubated at 39°C) was utilised to study production of indole, skatolc and p-cresol from the anaerobic fermentation of tryptophan and tyrosine. Spirulina is an abundant source of dietary protein. Therefore, ¹³C labelled spirulina was used to study the metabolism of protein and formation of analytes derived from ruminal metabolism of protein. A series of labelled end products, including toluene, acetic acid, propanoic acid, iso-butyric acid, n-butyric acid, iso-valeric acid, n-valeric acid, p-cresol, indole, skatole, dimethyldisulfide and dimethyltrisulfide were detected by GC-MS. This result indicates that these compounds are the products of ruminal metabolism of spirulina. When applied to the in vitro rumen system the headspace SPME technique provides a fast approach to study metabolism of target compounds and allows the researcher to follow proposed pathways with labelled substrate

Subgraph Frequency Distribution Estimation using Graph Neural Networks

Small subgraphs (graphlets) are important features to describe fundamental units of a large network. The calculation of the subgraph frequency distributions has a wide application in multiple domains including biology and engineering. Unfortunately due to the inherent complexity of this task, most of the existing methods are computationally intensive and inefficient. In this work, we propose GNNS, a novel representational learning framework that utilizes graph neural networks to sample subgraphs efficiently for estimating their frequency distribution. Our framework includes an inference model and a generative model that learns hierarchical embeddings of nodes, subgraphs, and graph types. With the learned model and embeddings, subgraphs are sampled in a highly scalable and parallel way and the frequency distribution estimation is then performed based on these sampled subgraphs. Eventually, our methods achieve comparable accuracy and a significant speedup by three orders of magnitude compared to existing methods.Comment: accepted by KDD 2022 Workshop on Deep Learning on Graph

AVSegFormer: Audio-Visual Segmentation with Transformer

The combination of audio and vision has long been a topic of interest in the multi-modal community. Recently, a new audio-visual segmentation (AVS) task has been introduced, aiming to locate and segment the sounding objects in a given video. This task demands audio-driven pixel-level scene understanding for the first time, posing significant challenges. In this paper, we propose AVSegFormer, a novel framework for AVS tasks that leverages the transformer architecture. Specifically, we introduce audio queries and learnable queries into the transformer decoder, enabling the network to selectively attend to interested visual features. Besides, we present an audio-visual mixer, which can dynamically adjust visual features by amplifying relevant and suppressing irrelevant spatial channels. Additionally, we devise an intermediate mask loss to enhance the supervision of the decoder, encouraging the network to produce more accurate intermediate predictions. Extensive experiments demonstrate that AVSegFormer achieves state-of-the-art results on the AVS benchmark. The code is available at https://github.com/vvvb-github/AVSegFormer.Comment: 9 pages, 7 figure

Champion Solution for the WSDM2023 Toloka VQA Challenge

In this report, we present our champion solution to the WSDM2023 Toloka Visual Question Answering (VQA) Challenge. Different from the common VQA and visual grounding (VG) tasks, this challenge involves a more complex scenario, i.e. inferring and locating the object implicitly specified by the given interrogative question. For this task, we leverage ViT-Adapter, a pre-training-free adapter network, to adapt multi-modal pre-trained Uni-Perceiver for better cross-modal localization. Our method ranks first on the leaderboard, achieving 77.5 and 76.347 IoU on public and private test sets, respectively. It shows that ViT-Adapter is also an effective paradigm for adapting the unified perception model to vision-language downstream tasks. Code and models will be released at https://github.com/czczup/ViT-Adapter/tree/main/wsdm2023.Comment: Technical report in WSDM Cup 202

BRAD, the genetics and genomics database for Brassica plants

<p>Abstract</p> <p>Background</p> <p>Brassica species include both vegetable and oilseed crops, which are very important to the daily life of common human beings. Meanwhile, the Brassica species represent an excellent system for studying numerous aspects of plant biology, specifically for the analysis of genome evolution following polyploidy, so it is also very important for scientific research. Now, the genome of <it>Brassica rapa </it>has already been assembled, it is the time to do deep mining of the genome data.</p> <p>Description</p> <p>BRAD, the Brassica database, is a web-based resource focusing on genome scale genetic and genomic data for important Brassica crops. BRAD was built based on the first whole genome sequence and on further data analysis of the Brassica A genome species, <it>Brassica rapa </it>(Chiifu-401-42). It provides datasets, such as the complete genome sequence of <it>B. rapa</it>, which was <it>de novo </it>assembled from Illumina GA II short reads and from BAC clone sequences, predicted genes and associated annotations, non coding RNAs, transposable elements (TE), <it>B. rapa </it>genes' orthologous to those in <it>A. thaliana</it>, as well as genetic markers and linkage maps. BRAD offers useful searching and data mining tools, including search across annotation datasets, search for syntenic or non-syntenic orthologs, and to search the flanking regions of a certain target, as well as the tools of BLAST and Gbrowse. BRAD allows users to enter almost any kind of information, such as a <it>B. rapa </it>or <it>A. thaliana </it>gene ID, physical position or genetic marker.</p> <p>Conclusion</p> <p>BRAD, a new database which focuses on the genetics and genomics of the Brassica plants has been developed, it aims at helping scientists and breeders to fully and efficiently use the information of genome data of Brassica plants. BRAD will be continuously updated and can be accessed through <url>http://brassicadb.org</url>.</p

Optogenetic control of GGGGCC repeat-containing RNA phase transition

The GGGGCC (G4C2) hexanucleotide repeat expansion in the C9ORF72 gene is a major cause of both hereditary amyotrophic lateral sclerosis and familial frontotemporal dementia. Recent studies have shown that G4C2 hexanucleotide repeat-containing RNA transcripts ((G4C2)n RNA) could go through liquid-liquid phase separation to form RNA foci, which may elicit neurodegeneration. However, the direct causality between these abnormal RNA foci and neuronal toxicity remains to be demonstrated. Here we introduce an optogenetic control system that can induce the assembly and phase separation of (G4C2)n RNA foci with blue light illumination in human cells, by fusing a specific (G4C2)n RNA binding protein as the linker domain to Cry2, a protein that oligomerizes in response to blue light. Our results demonstrate that a higher number of G4C2 repeats have the potential to be induced into more RNA foci in the cells. Both spontaneous and induced RNA foci display liquid-like properties according to FRAP measurements. Computational simulation shows strong consistency with the experimental results and supports the effect of our system to promote the propensity of (G4C2)n RNA towards phase separation. This system can thus be used to investigate whether (G4C2)n RNA foci would disrupt normal cellular processes and lead to pathological phenotypes relevant to repeat expansion disorders

AVSegFormer: Audio-Visual Segmentation with Transformer

Audio-visual segmentation (AVS) aims to locate and segment the sounding objects in a given video, which demands audio-driven pixel-level scene understanding. The existing methods cannot fully process the fine-grained correlations between audio and visual cues across various situations dynamically. They also face challenges in adapting to complex scenarios, such as evolving audio, the coexistence of multiple objects, and more. In this paper, we propose AVSegFormer, a novel framework for AVS that leverages the transformer architecture. Specifically, It comprises a dense audio-visual mixer, which can dynamically adjust interested visual features, and a sparse audio-visual decoder, which implicitly separates audio sources and automatically matches optimal visual features. Combining both components provides a more robust bidirectional conditional multi-modal representation, improving the segmentation performance in different scenarios. Extensive experiments demonstrate that AVSegFormer achieves state-of-the-art results on the AVS benchmark. The code is available at https://github.com/vvvb-github/AVSegFormer

Study on Low-Temperature Emission Performance of Scandate Cathode with Micro-Blade-Type Arrays

In order to meet the requirements of high-frequency vacuum electronic devices with small size, high current density, and low working temperature, a kind of porous tungsten scandate cathode with micro-blade-type arrays was developed. The micro-blade-type arrays were fabricated by laser engraving technology. Subsequently, the cathode was prepared by a vacuum copper removal process and impregnated with active substances at high temperature. Experimental results show that the cathode exhibits excellent low-temperature electron emission performance and that the maximum pulse electron emission current density reaches 81.18 A/cm2 at 800 &deg;C. The cathode also shows apparent combined thermal-field emission characteristics. Further analysis shows that a high electric field strength plays an important role in the electron emission of the scandate cathode. By virtue of the electric field enhancement effect formed by the fabricated micro-blade-type arrays on the cathode surface, the prepared cathode achieves high electron emission capacity

Effect of Experimental Periodontal Ligament Pain on Gingival Somatosensory Sensitivity

Aims: To use a randomized, blinded, crossover design to evaluate the possible heterotopic effects of experimental periodontal ligament pain on adjacent gingival somatosensory sensitivity. Methods: A total of 12 healthy volunteers (8 female, 4 male; mean age standard error in means (SEM): 28 1 years) participated in two randomized experimental quantitative sensory testing (QST) sessions, one in which capsaicin (experimental) was injected into the periodontal ligament and one in which isotonic saline (control) was injected. A total of 13 standardized QST measures were obtained on the buccal attached gingiva of a maxillary central incisor before, immediately after, and 30 minutes after injection of 30 mu L of 5% capsaicin or isotonic saline into the periodontal ligament of the same incisor. The injection-evoked pain was evaluated on a 0-10 numeric rating scale (NRS). QST data were analyzed with two-way repeated measurement analysis of variance. Results: Capsaicin injected into the periodontal ligament evoked moderate levels of pain (mean peak NRS SEM: capsaicin: 5.5.7; control: 0.6 0.5 [P .050). Conclusion: Capsaicin injected into the periodontal ligament caused gain of heterotopic somatosensory sensitivity toward warmth and painful heat stimuli as well as reduction in mechanical sensitivity of the gingiva adjacent to the injected tooth. These findings may have implications for interpretation of somatosensory functions in patients with chronic intraoral pain, where gingival somatosensory profiles similar to those detected after capsaicin injection in the present study may be interpreted as signs of nerve damage

Lipid Metabolism Traits Mediate the Effect of Psoriasis on Myocardial Infarction Risk: A Two-Step Mendelian Randomization Study

Mendelian randomization (MR) analysis was performed to explore the effect of psoriasis on lipid metabolism traits and myocardial infarction (MI) risk and to analyze the proportion of the mediatory effect of lipid metabolism traits. Publicly accessible summary-level data for psoriasis, lipid metabolism traits, and MI were provided by the genome-wide association studies (GWASs) of the FinnGen Biobank, UK Biobank, and CARDIoGRAMplusC4D, respectively. A two-sample MR was carried out to evaluate the association of psoriasis with lipid metabolism traits and MI. Furthermore, the current research focused on determining if the impact of psoriasis on MI is mediated by lipid metabolism traits. The outcomes of the random effect inverse-variance-weighted (IVW) technique indicated a substantial link between genetically predicted psoriasis and a higher risk of low-density lipoprotein (LDL) cholesterol (OR: 1.006, 95% CI: 1.005–1.007, p = 0.024), apolipoprotein B (OR: 1.018, 95% CI: 1.010–1.026, p = 0.015), lipoprotein A (OR: 1.006, 95% CI: 1.002–1.010, p = 0.039), and MI (OR: 1.066, 95% CI: 1.014–1.121, p = 0.012). The percentages of the mediatory effect of LDL cholesterol, apolipoprotein B, and lipoprotein A under psoriasis conditions on MI risk was 7.4%, 10.2%, and 4.1%, respectively. Psoriasis was causally linked to an elevated risk of lipid metabolism levels and MI. This study further demonstrated that LDL cholesterol, apolipoprotein B, and lipoprotein A mediated the effect of psoriasis on MI risk. And timely lipid-lowering treatment should be given to MI patients