A scheme for determining vehicle routes based on Arc-based service network design

In freight transportation, less-than-truckload carriers often need to assign each vehicle a cyclic route so that drivers can come back home after a certain period of time. However, the Node-Arc model for service network design addresses decisions on each arc and does not determine routes directly, although the vehicle balancing constraint ensures that the number of outgoing vehicles equals the number of incoming vehicles at each node. How to transform the optimized service network into a set of vehicle routes remains an important problem that has not yet been studied. In this paper, we propose a three-phase scheme to address this problem. In the first stage, we present an algorithm based on the depth-first search to find all of the different cyclic routes in a service network design solution. In the second stage, we propose to prune poor cyclic routes using real-life constraints so that a collection of acceptable vehicle routes can be obtained before route assignment. Some of the pruning can also be done in the first stage to speed up the proposed algorithm. In the third stage, we formulate the problem of selecting a set of cyclic routes to cover the entire network as a weighted set covering problem. The resulting model is formulated as an integer program and solved with IBM ILOG CPLEX solver. Experimental results on benchmark instances for service network design indicate the effectiveness of the proposed scheme which gives high-quality solutions in an efficient way

Dynamic fleet scheduling with uncertain demand and customer flexibility

We develop a dynamic fleet scheduling model that demonstrates how a carrier can improve fleet utilization. The fleet scheduling model presented by Lee et al. (Eur J Oper Res 218(1):261-269, 2012) minimizes (1) a carrier's fleet size and (2) the penalty associated with the alternative delivery times selected. The model is static since requests are collected over time and processed together. In this paper we present a stochastic, dynamic version of the fleet reduction model. As demand is revealed throughout an order horizon, decisions are made in stages by sampling anticipated demand to avoid recourse penalties in later stages. Based on computational experiments we find the following:1. Modeling stochasticity improves the quality of solutions relative to the analogous model that does not include stochasticity. Counter-intuitively, an order lead-time distribution in which most loads are requested early can negatively impact optimal solution costs.2. The stochastic model produces good results without requiring prohibitively large numbers of demand scenarios.3. Consignees that place orders early in the order horizon are more often assigned their requested delivery times than those who place orders late.open

Colonization by B. infantis EVC001 modulates enteric inflammation in exclusively breastfed infants

BackgroundInfant gut dysbiosis, often associated with low abundance of bifidobacteria, is linked to impaired immune development and inflammation-a risk factor for increased incidence of several childhood diseases. We investigated the impact of B. infantis EVC001 colonization on enteric inflammation in a subset of exclusively breastfed term infants from a larger clinical study.MethodsStool samples (n = 120) were collected from infants randomly selected to receive either 1.8 × 1010 CFU B. infantis EVC001 daily for 21 days (EVC001) or breast milk alone (controls), starting at day 7 postnatal. The fecal microbiome was analyzed using 16S ribosomal RNA, proinflammatory cytokines using multiplexed immunoassay, and fecal calprotectin using ELISA at three time points: days 6 (Baseline), 40, and 60 postnatal.ResultsFecal calprotectin concentration negatively correlated with Bifidobacterium abundance (P < 0.0001; ρ = -0.72), and proinflammatory cytokines correlated with Clostridiaceae and Enterobacteriaceae, yet negatively correlated with Bifidobacteriaceae abundance. Proinflammatory cytokines were significantly lower in EVC001-fed infants on days 40 and 60 postnatally compared to baseline and compared to control infants.ConclusionOur findings indicate that gut dysbiosis (absence of B. infantis) is associated with increased intestinal inflammation. Early addition of EVC001 to diet represents a novel strategy to prevent enteric inflammation during a critical developmental phase

Maternal fucosyltransferase 2 status affects the gut bifidobacterial communities of breastfed infants

BACKGROUND: Individuals with inactive alleles of the fucosyltransferase 2 gene (FUT2; termed the ‘secretor’ gene) are common in many populations. Some members of the genus Bifidobacterium, common infant gut commensals, are known to consume 2′-fucosylated glycans found in the breast milk of secretor mothers. We investigated the effects of maternal secretor status on the developing infant microbiota with a special emphasis on bifidobacterial species abundance. RESULTS: On average, bifidobacteria were established earlier and more often in infants fed by secretor mothers than in infants fed by non-secretor mothers. In secretor-fed infants, the relative abundance of the Bifidobacterium longum group was most strongly correlated with high percentages of the order Bifidobacteriales. Conversely, in non-secretor-fed infants, Bifidobacterium breve was positively correlated with Bifidobacteriales, while the B. longum group was negatively correlated. A higher percentage of bifidobacteria isolated from secretor-fed infants consumed 2′-fucosyllactose. Infant feces with high levels of bifidobacteria had lower milk oligosaccharide levels in the feces and higher amounts of lactate. Furthermore, feces containing different bifidobacterial species possessed differing amounts of oligosaccharides, suggesting differential consumption in situ. CONCLUSIONS: Infants fed by non-secretor mothers are delayed in the establishment of a bifidobacteria-laden microbiota. This delay may be due to difficulties in the infant acquiring a species of bifidobacteria able to consume the specific milk oligosaccharides delivered by the mother. This work provides mechanistic insight into how milk glycans enrich specific beneficial bacterial populations in infants and reveals clues for enhancing enrichment of bifidobacterial populations in at risk populations - such as premature infants. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-015-0071-z) contains supplementary material, which is available to authorized users

Multiple Dynamics in Tumor Microenvironment Under Radiotherapy.

The tumor microenvironment (TME) is an evolutionally low-level and embryonically featured tissue comprising heterogenic populations of malignant and stromal cells as well as noncellular components. Under radiotherapy (RT), the major modality for the treatment of malignant diseases [1], TME shows an adaptive response in multiple aspects that affect the efficacy of RT. With the potential clinical benefits, interests in RT combined with immunotherapy (IT) are intensified with a large scale of clinical trials underway for an array of cancer types. A better understanding of the multiple molecular aspects, especially the cross talks of RT-mediated energy reprogramming and immunoregulation in the irradiated TME (ITME), will be necessary for further enhancing the benefit of RT-IT modality. Coming studies should further reveal more mechanistic insights of radiation-induced instant or permanent consequence in tumor and stromal cells. Results from these studies will help to identify critical molecular pathways including cancer stem cell repopulation, metabolic rewiring, and specific communication between radioresistant cancer cells and the infiltrated immune active lymphocytes. In this chapter, we will focus on the following aspects: radiation-repopulated cancer stem cells (CSCs), hypoxia and re-oxygenation, reprogramming metabolism, and radiation-induced immune regulation, in which we summarize the current literature to illustrate an integrated image of the ITME. We hope that the contents in this chapter will be informative for physicians and translational researchers in cancer radiotherapy or immunotherapy