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Metabolomic Profiling of Dongxiang Crazy Rice Below Salinity Demonstrates the Significant Part of Healthy proteins in Grain Salt Stress.
Metaproteomics, the study of the collective protein composition of multi-organism systems, provides deep insights into the biodiversity of microbial communities and the complex functional interplay between microbes and their hosts or environment. Thus, metaproteomics has become an indispensable tool in various fields such as microbiology and related medical applications. The computational challenges in the analysis of corresponding datasets differ from those of pure-culture proteomics, e.g., due to the higher complexity of the samples and the larger reference databases demanding specific computing pipelines. Corresponding data analyses usually consist of numerous manual steps that must be closely synchronized. With MetaProteomeAnalyzer and Prophane, we have established two open-source software solutions specifically developed and optimized for metaproteomics. Among other features, peptide-spectrum matching is improved by combining different search engines and, compared to similar tools, metaproteome annotation benefits from the most comprehensive set of available databases (such as NCBI, UniProt, EggNOG, PFAM, and CAZy). The workflow described in this protocol combines both tools and leads the user through the entire data analysis process, including protein database creation, database search, protein grouping and annotation, and results visualization. To the best of our knowledge, this protocol presents the most comprehensive, detailed and flexible guide to metaproteomics data analysis to date. While beginners are provided with robust, easy-to-use, state-of-the-art data analysis in a reasonable time (a few hours, depending on, among other factors, the protein database size and the number of identified peptides and inferred proteins), advanced users benefit from the flexibility and adaptability of the workflow.One of the prominent challenges in precision medicine is to select the most appropriate treatment strategy for each patient based on the personalized information. The availability of massive data about drugs and cell lines facilitates the possibility of proposing efficient computational models for predicting anticancer drug response. In this study, we propose ADRML, a model for Anticancer Drug Response Prediction using Manifold Learning to systematically integrate the cell line information with the drug information to make accurate predictions about drug therapeutic. The proposed model maps the drug response matrix into the lower-rank spaces that lead to obtaining new perspectives about cell lines and drugs. The drug response for a new cell line-drug pair is computed using the low-rank features. The evaluation of ADRML performance on various types of cell lines and drug information, in addition to the comparisons with previously proposed methods, shows that ADRML provides accurate and robust predictions. Further investigations about the association between drug response and pathway activity scores reveal that the predicted drug responses can shed light on the underlying drug mechanism. Also, the case studies suggest that the predictions of ADRML about novel cell line-drug pairs are validated by reliable pieces of evidence from the literature. Consequently, the evaluations verify that ADRML can be used in accurately predicting and imputing the anticancer drug response.The oasis villages of the Tarim Basin served as hubs along the ancient Silk Road, and they played an important role in facilitating communication between the imperial centers of Asia. These villages were supported by an irrigated form of cereal farming that was specifically adapted to these early oasis settlements. In this manuscript, we present the results from new archaeobotanical analyses, radiocarbon dating, and organic carbon isotopic studies directly from carbonized seeds at the Wupaer site (1500-400 BC) in the Kashgar Oasis of the western Tarim Basin. Our results showed that early farming in the oasis relied on a mixed wheat and barley system, but after 1200 BC was intensified through more elaborate irrigation, the introduction of more water-demanding legumes, and possibly a greater reliance on free-threshing wheat. These crops and the knowledge of irrigated farming likely dispersed into the Tarim Basin through the mountains from southern Central Asia. Improved agricultural productivity in the Tarim Basin may also have led to demographic and socio-political shifts and fed into the increased exchange that is colloquially referred to as the Silk Road.Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to manually label training data. These constraints make it difficult to develop systems for automatic analysis, like detecting disease or other lesions. In this respect, this article presents HyperKvasir, the largest image and video dataset of the gastrointestinal tract available today. The data is collected during real gastro- and colonoscopy examinations at Bærum Hospital in Norway and partly labeled by experienced gastrointestinal endoscopists. The dataset contains 110,079 images and 374 videos, and represents anatomical landmarks as well as pathological and normal findings. The total number of images and video frames together is around 1 million. Initial experiments demonstrate the potential benefits of artificial intelligence-based computer-assisted diagnosis systems. The HyperKvasir dataset can play a valuable role in developing better algorithms and computer-assisted examination systems not only for gastro- and colonoscopy, but also for other fields in medicine.Early cow-calf separation prevents much of cows' natural maternal behaviour. Early separation is thought to prevent the development of a cow-calf bond. To assess this bond, we measured motivation of dairy cows to reunite with their calf. To vary the degree of bonding, some cows were allowed continued contact with their calf and others were separated from their calf soon after birth, following standard practice on most farms. Among cows allowed continued contact, some were able to suckle their calf and others were prevented from suckling (by covering the cow's udder with an udder net). Cows were habituated to the weighted-gate apparatus before calving by daily training with the (un-weighted) gate. After calving, cow willingness to use the gate was assessed by determining if she would push open the gate to access to her own calf. Testing occurred once daily, with weight on the gate gradually increased. After passing through the gate, the dam's calf-directed behaviour was recorded. Suckled cows pushed a greater maximum weight (45.8 ± 7.8 kg) than separated cows (21.6 ± 6.7 kg) and non-suckled cows (24.3 ± 4.5 kg), with no differences between separated and non-suckled cows. Once reunited, latency to make nose contact and duration of licking did not differ between treatments. We conclude that motivation for calf contact is greater for cows that are suckled.We compared the somatostatin analog radioligand, DOTANOC, with FDG, to determine whether there was increased detection of active or sub-clinical lesions in pulmonary tuberculosis (TB) with DOTANOC. Three groups were recruited (1) active pulmonary TB; (2) IGRA-positive household TB contacts; (3) pneumonia (non-TB). DOTANOC PET/MRI followed by FDG PET/MRI was performed in active TB and pneumonia groups. TB contacts underwent FDG PET/MRI, then DOTANOC PET/MRI if abnormalities were detected. Quantitative and qualitative analyses were performed for total lung and individual lesions. Eight active TB participants, three TB contacts and three pneumonia patients had paired PET/MRI scans. In the active TB group, median SUVmax[FDG] for parenchymal lesions was 7.69 (range 3.00-15.88); median SUVmax[DOTANOC] was 2.59 (1.48-6.40). Regions of tracer uptake were fairly similar for both radioligands, albeit more diffusely distributed in the FDG scans. In TB contacts, two PET/MRIs had parenchymal lesions detected with FDG (SUVmax 5.50 and 1.82), with corresponding DOTANOC uptake less then  1. FDG and DOTANOC uptake was similar in pneumonia patients (SUVmax[FDG] 4.17-6.18; SUVmax[DOTANOC] 2.92-4.78). DOTANOC can detect pulmonary TB lesions, but FDG is more sensitive for both active and sub-clinical lesions. FDG remains the preferred ligand for clinical studies, although DOTANOC may provide additional value for pathogenesis studies.Staphylococcus epidermidis (S. epidermidis) is one of the primary pathogens in postoperative endophthalmitis, which is a devastating complication of cataract surgery and often results in irreversible visual loss and even blindness. Meanwhile, it is the most frequently isolated commensal bacterium in the healthy conjunctiva. In this study, we investigated the differentially expressed genes (DEGs) of S. epidermidis isolated from the patients with postoperative endophthalmitis and the healthy conjunctiva to predict their functions and pathways by Illumina high-throughput RNA sequencing. Using genome-wide transcriptional analysis, 281 genes (142 upregulated and 139 downregulated genes) were found to be differentially expressed (fold change ≥ 2, p ≤ 0.05) in the strains from endophthalmitis. Ten randomly selected DEGs were further validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). GO enrichment analysis suggested that more DEGs were associated with the thioredoxin system and iron ion metabolism. KEGG pathway analysis revealed that more DEGs were associated with the pathways of the two-component system and pyruvate metabolism. Moreover, the gene SE1634 code for staphylococcal toxin was significantly upregulated in S. epidermidis strains of the endophthalmitis, which might be directly responsible for the pathogenesis of endophthalmitis. this website In conclusion, this research is helpful for further investigations on genes or pathways related with the pathogenesis and therapeutic targets of S. epidermidis endophthalmitis.Flavonols play key roles in many plant defense mechanisms, consequently they are frequently investigated as stress sensitive factors in relation to several oxidative processes. It is well known that grapevine (Vitis vinifera L.) can synthesize various flavonol glycosides in the leaves, however, very little information is available regarding their distribution along the cane at different leaf levels. In this work, taking into consideration of leaf position, the main flavonol glycosides of a red grapevine cultivar (Cabernet Sauvignon) were profiled and quantified by HPLC-DAD analysis. It was found that amount of four flavonol glycosides, namely, quercetin-3-O-galactoside, quercetin-3-O-glucoside, kaempferol-3-O-glucoside and kaempferol-3-O-glucuronide decreased towards the shoot tip. Since leaf age also decreases towards the shoot tip, the obtained results suggest that these compounds continuously formed by leaf aging, resulting in their accumulation in the older leaves. In contrast, quercetin-3-O-glucuronide (predominant form) and quercetin-3-O-rutinoside were not accumulated significantly by aging. We also pointed out that grapevine boosted the flavonol biosynthesis in September, and flavonol profile differed significantly in the two seasons. Our results contribute to the better understanding of the role of flavonols in the antioxidant defense system of grapevine.
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