Global analysis of the eukaryotic pathways and networks regulated by Salmonella typhimurium in mouse intestinal infection in vivo

<p>Abstract</p> <p>Background</p> <p>Acute enteritis caused by <it>Salmonella </it>is a public health concern. <it>Salmonella </it>infection is also known to increase the risk of inflammatory bowel diseases and cancer. Therefore, it is important to understand how <it>Salmonella </it>works in targeting eukaryotic pathways in intestinal infection. However, the global physiological function of <it>Salmonella </it>typhimurium in intestinal mucosa <it>in vivo </it>is unclear. In this study, a whole genome approach combined with bioinformatics assays was used to investigate the <it>in vivo </it>genetic responses of the mouse colon to <it>Salmonella</it>. We focused on the intestinal responses in the early stage (8 hours) and late stage (4 days) after <it>Salmonella </it>infection.</p> <p>Results</p> <p>Of the 28,000 genes represented on the array, our analysis of mRNA expression in mouse colon mucosa showed that a total of 856 genes were expressed differentially at 8 hours post-infection. At 4 days post-infection, a total of 7558 genes were expressed differentially. 23 differentially expressed genes from the microarray data was further examined by real-time PCR. Ingenuity Pathways Analysis identified that the most significant pathway associated with the differentially expressed genes in 8 hours post-infection is oxidative phosphorylation, which targets the mitochondria. At the late stage of infection, a series of pathways associated with immune and inflammatory response, proliferation, and apoptosis were identified, whereas the oxidative phosphorylation was shut off. Histology analysis confirmed the biological role of <it>Salmonella</it>, which induced a physiological state of inflammation and proliferation in the colon mucosa through the regulation of multiple signaling pathways. Most of the metabolism-related pathways were targeted by down-regulated genes, and a general repression process of metabolic pathways was observed. Network analysis supported IFN-γ and TNF-α function as mediators of the immune/inflammatory response for host defense against pathogen.</p> <p>Conclusion</p> <p>Our study provides novel genome-wide transcriptional profiling data on the mouse colon mucosa's response to the <it>Salmonella typhimurium </it>infection. Building the pathways and networks of interactions between these genes help us to understand the complex interplay in the mice colon during <it>Salmonella </it>infection, and further provide new insights into the molecular cascade, which is mobilized to combat <it>Salmonella</it>-associated colon infection <it>in vivo</it>.</p

Routing Optimization with Generalized Consistency Requirements

The consistent vehicle routing problem (ConVRP) aims to design synchronized routes on multiple days to serve a group of customers while minimizing the total travel cost. It stipulates that customers should be visited at roughly the same time (time consistency) by several familiar drivers (driver consistency). This paper generalizes the ConVRP for any level of driver consistency and additionally addresses route consistency, which means that each driver can traverse at most a certain proportion of different arcs of routes on planning days, which guarantees route familiarity. To solve this problem, we develop two set partitioning-based formulations, one based on routes and the other based on schedules. We investigate valid lower bounds on the linear relaxations of both of the formulations that are used to derive a subset of columns (routes and schedules); within the subset are columns of an optimal solution for each formulation. We then solve the reduced problem of either one of the formulations to achieve an optimal solution. Numerical results show that our exact method can effectively solve most of the medium-sized ConVRP instances in the literature and can also solve some newly generated instances involving up to 50 customers. Our exact solutions explore some managerial findings with respect to the adoption of consistency measures in practice. First, maintaining reasonably high levels of consistency requirements does not necessarily always lead to a substantial increase in cost. Second, a high level of time consistency can potentially be guaranteed by adopting a high level of driver consistency. Third, maintaining high levels of time consistency and driver consistency may lead to lower levels of route consistency

DCELANM-Net:Medical Image Segmentation based on Dual Channel Efficient Layer Aggregation Network with Learner

The DCELANM-Net structure, which this article offers, is a model that ingeniously combines a Dual Channel Efficient Layer Aggregation Network (DCELAN) and a Micro Masked Autoencoder (Micro-MAE). On the one hand, for the DCELAN, the features are more effectively fitted by deepening the network structure; the deeper network can successfully learn and fuse the features, which can more accurately locate the local feature information; and the utilization of each layer of channels is more effectively improved by widening the network structure and residual connections. We adopted Micro-MAE as the learner of the model. In addition to being straightforward in its methodology, it also offers a self-supervised learning method, which has the benefit of being incredibly scaleable for the model

Cardiac Response to Chronic Intermittent Hypoxia with a Transition from Adaptation to Maladaptation: The Role of Hydrogen Peroxide

Obstructive sleep apnea (OSA) is a highly prevalent respiratory disorder of sleep, and associated with chronic intermittent hypoxia (CIH). Experimental evidence indicates that CIH is a unique physiological state with potentially “adaptive” and “maladaptive” consequences for cardio-respiratory homeostasis. CIH is also a critical element accounting for most of cardiovascular complications of OSA. Cardiac response to CIH is time-dependent, showing a transition from cardiac compensative (such as hypertrophy) to decompensating changes (such as failure). CIH-provoked mild and transient oxidative stress can induce adaptation, but severe and persistent oxidative stress may provoke maladaptation. Hydrogen peroxide as one of major reactive oxygen species plays an important role in the transition of adaptive to maladaptive response to OSA-associated CIH. This may account for the fact that although oxidative stress has been recognized as a driver of cardiac disease progression, clinical interventions with antioxidants have had little or no impact on heart disease and progression. Here we focus on the role of hydrogen peroxide in CIH and OSA, trying to outline the potential of antioxidative therapy in preventing CIH-induced cardiac damage

Regularly Truncated M-estimators for Learning with Noisy Labels

The sample selection approach is very popular in learning with noisy labels. As deep networks learn pattern first, prior methods built on sample selection share a similar training procedure: the small-loss examples can be regarded as clean examples and used for helping generalization, while the large-loss examples are treated as mislabeled ones and excluded from network parameter updates. However, such a procedure is arguably debatable from two folds: (a) it does not consider the bad influence of noisy labels in selected small-loss examples; (b) it does not make good use of the discarded large-loss examples, which may be clean or have meaningful information for generalization. In this paper, we propose regularly truncated M-estimators (RTME) to address the above two issues simultaneously. Specifically, RTME can alternately switch modes between truncated M-estimators and original M-estimators. The former can adaptively select small-losses examples without knowing the noise rate and reduce the side-effects of noisy labels in them. The latter makes the possibly clean examples but with large losses involved to help generalization. Theoretically, we demonstrate that our strategies are label-noise-tolerant. Empirically, comprehensive experimental results show that our method can outperform multiple baselines and is robust to broad noise types and levels.Comment: 16 pages, 11 tables, 9 figure

Cold hardiness of Phauda flammans (Lepidoptera: Zygaenidae) larvae

This study aimed to determine the cold hardiness of Phauda flammans (Lepidoptera: Zygaenidae) larvae. Supercooling points of the 1st–6th instar larvae of P. flammans ranged from –7.7 to –13.0 °C. The lethal temperatures were –8 °C for 1st, –5 °C for 2nd, and –7 °C for 3rd–6th instars. Lethal times at the instar-specific lethal temperatures were 12 h for 1st, 14 h for 2nd, 15 h for 3rd, 17 h for 4th, and 18 h for 5th–6th instars. The times required for all larvae to die in an incubator at 5 °C were 30 d for 1st, 3rd, 4th, and 5th instars, and 25 d for 2nd and 6th instars. The findings suggest that P. flammans is a chill-intolerant species, and larvae will die if the air temperature decreases to –5 to –8 °C for 12–18 h or to 5 °C for 25–30 d. Such conditions are, however, unlikely to occur in southern China

How tyramine β-hydroxylase controls the production of octopamine, modulating the mobility of beetles

Biogenic amines perform many kinds of important physiological functions in the central nervous system (CNS) of insects, acting as neuromodulators, neurotransmitters, and neurohormones. The five most abundant types of biogenic amines in invertebrates are dopamine, histamine, serotonin, tyramine, and octopamine (OA). However, in beetles, an important group of model and pest insects, the role of tyramine beta-hydroxylase (T beta H) in the OA biosynthesis pathway and the regulation of behavior remains unknown so far. We therefore investigated the molecular characterization and spatiotemporal expression profiles of T beta H in red flour beetles (Triboliun castaneum). Most importantly, we detected the production of OA and measured the crawling speed of beetles after dsTcT beta H injection. We concluded that TcT beta H controls the biosynthesis amount of OA in the CNS, and this in turn modulates the mobility of the beetles. Our new results provided basic information about the key genes in the OA biosynthesis pathway of the beetles, and expanded our knowledge on the physiological functions of OA in insects

The Role of Deubiquitinases in DNA Double-Strand Break Repair

DNA double-strand break (DSB) is a type of the most critical DNA lesions, and if not repaired promptly, it can result in cell death or a wide variety of genetic alterations including genome instability, large- or small-scale deletions, chromosome loss, loss of heterozygosity, and translocations. DSBs are repaired by double-strand break repair (DSBR), including nonhomologous end-joining (NHEJ) and homologous recombination (HR) pathway, and defects in these pathways cause genome instability and promote tumorigenesis. Accumulating evidence has demonstrated that the superfamily of deubiquitinases (DUBs) can regulate the action and stability of DNA repair enzymes involving in DSBR via modifying ubiquitination levels, a reversible posttranslational modification pathway. In this review, we will discuss ubiquitination/deubiquitination modification involving in DSBR genes, the role of DUBs in DSBR and corresponding mechanisms, and the potential effects of this modification on human diseases