Stepwise reduction and approximation method for performance analysis of generalized stochastic petri nets

This thesis delves into the performance analysis of generalized stochastic Petri net (GSPN) model by using an approximation method: the Stepwise Reduction and Approximation (SRA) Method. The key point is that we are able to analyze a subnet in isolation by keeping its token flow direction and its sub-throughput equivalent with all the possible tokens entering into the subnet. The thesis first defines various kinds of potentially reducible subnets, subnet selection rules, approximation subnet construction rules, and reduction evaluation rules. Then corresponding to the possible subnets, the approximation method is used stepwisely until the interested measures are found with the global state space reduced. Two GSPN model examples from the literature are analyzed by using the proposed method. The approximation errors are given and discussed. Finally, the conclusions are drawn and future research is discussed

Making the Best of Both Worlds: A Domain-Oriented Transformer for Unsupervised Domain Adaptation

Extensive studies on Unsupervised Domain Adaptation (UDA) have propelled the deployment of deep learning from limited experimental datasets into real-world unconstrained domains. Most UDA approaches align features within a common embedding space and apply a shared classifier for target prediction. However, since a perfectly aligned feature space may not exist when the domain discrepancy is large, these methods suffer from two limitations. First, the coercive domain alignment deteriorates target domain discriminability due to lacking target label supervision. Second, the source-supervised classifier is inevitably biased to source data, thus it may underperform in target domain. To alleviate these issues, we propose to simultaneously conduct feature alignment in two individual spaces focusing on different domains, and create for each space a domain-oriented classifier tailored specifically for that domain. Specifically, we design a Domain-Oriented Transformer (DOT) that has two individual classification tokens to learn different domain-oriented representations, and two classifiers to preserve domain-wise discriminability. Theoretical guaranteed contrastive-based alignment and the source-guided pseudo-label refinement strategy are utilized to explore both domain-invariant and specific information. Comprehensive experiments validate that our method achieves state-of-the-art on several benchmarks.Comment: Accepted at ACMMM 202

Metagenomic Insights Into a Cellulose-Rich Niche Reveal Microbial Cooperation in Cellulose Degradation

BackgroundCellulose is the most abundant organic polymer mainly produced by plants in nature. It is insoluble and highly resistant to enzymatic hydrolysis. Cellulolytic microorganisms that are capable of producing a battery of related enzymes play an important role in recycling cellulose-rich plant biomass. Effective cellulose degradation by multiple synergic microorganisms has been observed within a defined microbial consortium in the lab culture. Metagenomic analysis may enable us to understand how microbes cooperate in cellulose degradation in a more complex microbial free-living ecosystem in nature.ResultsHere we investigated a typical cellulose-rich and alkaline niche where constituent microbes survive through inter-genera cooperation in cellulose utilization. The niche has been generated in an ancient paper-making plant, which has served as an isolated habitat for over 7 centuries. Combined amplicon-based sequencing of 16S rRNA genes and metagenomic sequencing, our analyses showed a microbial composition with 6 dominant genera including Cloacibacterium, Paludibacter, Exiguobacterium, Acetivibrio, Tolumonas, and Clostridium in this cellulose-rich niche; the composition is distinct from other cellulose-rich niches including a modern paper mill, bamboo soil, wild giant panda guts, and termite hindguts. In total, 11,676 genes of 96 glucoside hydrolase (GH) families, as well as 1,744 genes of carbohydrate transporters were identified, and modeling analysis of two representative genes suggested that these glucoside hydrolases likely evolved to adapt to alkaline environments. Further reconstruction of the microbial draft genomes by binning the assembled contigs predicted a mutualistic interaction between the dominant microbes regarding the cellulolytic process in the niche, with Paludibacter and Clostridium acting as helpers that produce endoglucanases, and Cloacibacterium, Exiguobacterium, Acetivibrio, and Tolumonas being beneficiaries that cross-feed on the cellodextrins by oligosaccharide uptake.ConclusionThe analysis of the key genes involved in cellulose degradation and reconstruction of the microbial draft genomes by binning the assembled contigs predicted a mutualistic interaction based on public goods regarding the cellulolytic process in the niche, suggesting that in the studied microbial consortium, free-living bacteria likely survive on each other by acquisition and exchange of metabolites. Knowledge gained from this study will facilitate the design of complex microbial communities with a better performance in industrial bioprocesses

Physiological responses to drought in three provenances of Discorea nipponica Makino

Dioscorea nipponica Makino is an optimal candidate to develop the diosgenin industry in North China. Given the large fluctuations in soil water availability induced by global climate change, information on drought tolerance of this species is urgently needed. Thus, seedlings of three provenances, selected from Manghe, Pangquangou nd Luyashan Nature Reserves in Shanxi Province, were exposed to 70%-85%, 55%-60%, 40%-45% and 20%-35% of water holding capacity, representing normal-watered, light drought stress, moderate drought stress and severe drought stress, respectively. Thirteen indices concerning plant water status, photosynthesis, antioxidants and osmotic regulation were recorded. Principal Component Analysis was applied to identify indices with a high contribution to drought tolerance, fulfilled by the average of subordinate function values (Xij) of drought tolerance index (Xij). We found that rhizome-propagated seedlings of D. nipponica Makino could survive eighty days of severe drought. The drought tolerance of this species is achieved mainly through physiological responses including decreased photosynthesis, increased activity of antioxidant enzymes, and accumulation of osmotic regulating compounds. The means of drought tolerance index for the provenances Manghe, Pangquangou and Luyashan were 0.29, 0.68 and 0.50, respectively. Pangquangou provenance showed higher drought tolerance than the other two, indicating that it might be a good candidate for cross breeding to combat the increasing drought climate in Shanxi Province

Isolation and identification of pathogens of Morchella sextelata bacterial disease

Morel mushroom (Morchella spp.) is a rare edible and medicinal fungus distributed worldwide. It is highly desired by the majority of consumers. Bacterial diseases have been commonly observed during artificial cultivation of Morchella sextelata. Bacterial pathogens spread rapidly and cause a wide range of infections, severely affecting the yield and quality of M. sextelata. In this study, two strains of bacterial pathogens, named M-B and M-5, were isolated, cultured, and purified from the tissues of the infected M. sextelata. Koch’s postulates were used to determine the pathogenicity of bacteria affecting M. sextelata, and the pathogens were identified through morphological observation, physiological and biochemical analyses, and 16S rRNA gene sequence analysis. Subsequently, the effect of temperature on the growth of pathogenic bacteria, the inhibitory effect of the bacteria on M. sextelata on plates, and the changes in mycelial morphology of M. sextelata mycelium were analyzed when M. sextelata mycelium was double-cultured with pathogenic bacteria on plates. The results revealed that M-B was Pseudomonas chlororaphis subsp. aureofaciens and M-5 was Bacillus subtilis. Strain M-B started to multiply at 10–15°C, and strain M-5 started at 15–20°C. On the plates, the pathogenic bacteria also produced significant inhibition of M. sextelata mycelium, and the observation of mycelial morphology under the scanning electron microscopy revealed that the inhibited mycelium underwent obvious drying and crumpling, and the healthy mycelium were more plump. Thus, this study clarified the pathogens, optimal growth environment, and characteristics of M. sextelata bacterial diseases, thereby providing valuable basic data for the disease prevention and control of Morchella production

Anti-PD-L1/TGF-βR fusion protein (SHR-1701) overcomes disrupted lymphocyte recovery-induced resistance to PD-1/PD-L1 inhibitors in lung cancer

Background Second-generation programmed cell death-protein 1/programmed death-ligand 1 (PD-1/PD-L1) inhibitors, such as bintrafusp alfa (M7824), SHR-1701, and YM101, have been developed to simultaneously block PD-1/PD-L1 and transforming growth factor-beta/transforming growth factor-beta receptor (TGF-β/TGF-βR). Consequently, it is necessary to identify predictive factors of lung cancer patients who are not only resistant to PD-1/PD-L1 inhibitors but also sensitive to bifunctional drugs. The purpose of this study was to search for such predictors. Methods Multivariable Cox regression was used to study the association between the clinical outcome of treatment with PD-1/PD-L1 inhibitors and lymphocyte recovery after lymphopenia in lung cancer patients. Murine CMT167 lung cancer cells were engineered to express the firefly luciferase gene and implanted orthotopically in the lung of syngeneic mice. Bioluminescence imaging, flow cytometry, and immunohistochemistry were employed to determine response to immunotherapy and function of tumor-infiltrating immune cells. Results For lung cancer patients treated with anti-PD-1/PD-L1 antibodies, poor lymphocyte recovery was associated with a shorter progression-free survival (PFS; P < 0.001), an accumulation of regulatory T cells (Tregs), and an elimination of CD8+ T cells in the peripheral blood. Levels of CD8+ T cells and Treg cells were also imbalanced in the tumors and peripheral immune organs of mice with poor lymphocyte recovery after chemotherapy. Moreover, these mice failed to respond to anti-PD-1 antibodies but remained sensitive to the anti-PD-L1/TGF-βR fusion protein (SHR-1701). Consistently, SHR-1701 but not anti-PD-1 antibodies, markedly enhanced IFN-γ production and Ki-67 expression in peripheral CD8+ T cells from patients with impaired lymphocyte recovery. Conclusions Lung cancer patients with poor lymphocyte recovery and suffering from persistent lymphopenia after previous chemotherapy are resistant to anti-PD-1/PD-L1 antibodies but might be sensitive to second-generation agents such as SHR-1701.publishedVersio