Designing connected nature reserve networks using a graph theory approach

Habitat fragmentation has been cited as one of the critical reasons for biodiversity loss. Establishing connected nature reserve networks is an effective way to reduce habit fragmentation. However, the resources devoted to nature reserves have always been scarce. Therefore it is important to allocate our scarce resources in an optimal way. The optimal design of a reserve network which is effective both ecologically and economically has become an important research topic in the reserve design literature. The problem of optimal selection of a subset from a larger group of potential habitat sites is solved using either heuristic or formal optimization methods. The heuristic methods, although flexible and computationally fast, can not guarantee the solution is optimal therefore may lead to scarce resources being used in an ineffective way. The formal optimization methods, on the other hand, guarantees the solution is optimal, but it has been argued that it would be difficult to model site selection process using optimization models, especially when spatial attributes of the reserve have to be taken into account. This paper presents a linear integer programming model for the design of a minimal connected reserve network using a graph theory approach. A connected tree is determined corresponding to a connected reserve. Computational performance of the model is tested using datasets randomly generated by the software GAMS. Results show that the model can solve a connected reserve design problem which includes 100 potential sites and 30 species in a reasonable period of time. As an empirical application, the model is applied to the protection of endangered and threatened bird species in the Cache River basin area in Illinois, US. Two connected reserve networks are determined for 13 bird species.     

Pool‐less processing to streamline downstream purification of monoclonal antibodies

With cell culture titers and productivity increasing in the last few years, pressure has been placed on downstream purification to look at alternative strategies to meet the demand of biotech products with high dose requirements. Even when the upstream process is not continuous (perfusion based), adopting a more productive and/or continuous downstream process can be of significant advantage. Due to the recent trend in exploring continuous processing options for biomolecules, several enabling technologies have been assessed at Biogen. In this paper, we evaluate the capability of one of these technologies to streamline and improve our downstream mAb purification platform. Current conventional downstream polishing steps at Biogen are operated in flow‐through mode to achieve higher loadings while maintaining good selectivity. As titers increase, this would result in larger columns and larger intermediate product pool holding tanks. A semicontinuous downstream process linking the second and third chromatography steps in tandem can reduce/eliminate intermediate holding tanks, reduce overall processing time, and combine unit operations to reduce validation burdens. A pool‐less processing technology utilizing inline adjustment functionality was evaluated to address facility fit challenges for three high titer mAbs. Two different configurations of polishing steps were examined: (i) anion exchange and hydrophobic interaction and (ii) anion exchange and mixed mode chromatography. Initial laboratory scale proof of concept studies showed comparable performance between the batch purification process and the pool‐less process configuration.     

Differentiated free-living and sediment-attached bacterial community structure inside and outside denitrification hotspots in the river–groundwater interface

This study assessed the functional significance of attached and free-living bacterial communities involved in the process of denitrification in a shallow aquifer of a riparian zone (Garonne River, SW France). Denitrification enzyme activity (DEA), bacterial density (BD) and bacterial community composition (BCC) were measured in two aquifer compartments: the groundwater and the sandy fraction of the sediment deposit. Samples were collected in wells located inside (IHD) and outside (OHD) identified hotspots of denitrification. Despite high BD values (up to 1.14 × 10¹² cells m⁻³), DEA was not detected in the water compartment (< 0.32 mg N–N₂O m⁻³ d⁻¹). The sandy fraction showed detectable DEA (up to 1,389 mg N–N₂O m⁻³ d⁻¹) and, consistent with BD pattern, higher DEA values were measured in IHD zones than in OHD zones. The BCC assessed by 16S rDNA polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) partly supported this result: attached and free-living communities were significantly different (< 30% similarity) but patterns of BCC did not cluster according to IHD and OHD zones. Targeting the denitrifying communities by means of a culture enrichment step prior to 16S rDNA PCR-DGGE showed that the free-living and sediment attached communities differed. Most sequences obtained from DGGE profiles of denitrifying communities were affiliated to Proteobacteria and showed low genetic distance with taxa that have already been detected in aquifers (e.g., Azoarcus sp., Acidovorax sp. and Pseudomonas spp.). This study confirms that in the aquifer the sediment-attached fraction exhibits different functions (DEA) from free-living communities and suggests that this functional difference is related to the communities’ structure.     

Polishing approach with fully connected flow‐through purification for therapeutic monoclonal antibody

The biopharmaceutical industry is evolving toward process intensification that can offer increased productivity and improved economics without sacrificing process robustness. A semi‐continuous downstream process linking purification/polishing unit operations in series can reduce or eliminate intermediate holding tanks and reduce overall processing time. Accordingly, we have developed a therapeutic monoclonal antibody polishing template comprised of a connected flow‐through polishing technologies that include activated carbon, cation exchange, and anion‐exchange chromatography. In this report, we evaluated fully‐connected pool‐less polishing with three flow‐through technologies, operating as a single skid to streamline and improve an mAb purification platform. Laboratory‐scale pool‐less processing was achieved without utilizing in‐line pH adjustment and conductivity dilution based on the previously optimized single process parameter. Two connected flow‐through configurations of polishing steps were evaluated: a two‐step process using anion exchange and cation exchange and a three step process using activated carbon, anion exchange and cation exchange chromatography. Laboratory‐scale proof of concept studies showed comparable performance between the batch purification process and the pool‐less process configuration. Three step polishing highly intensified the processes and provided higher process loading and achieved bulk drug specification with higher impurity clearance (>95%) and high overall mAb yield (>95%).     

Designing connected nature reserve networks using a graph theory approach

Habitat fragmentation has been cited as one of the critical reasons for biodiversity loss. Establishing connected nature reserve networks is an effective way to reduce habit fragmentation. However, the resources devoted to nature reserves have always been scarce. Therefore it is important to allocate our scarce resources in an optimal way. The optimal design of a reserve network which is effective both ecologically and economically has become an important research topic in the reserve design literature. The problem of optimal selection of a subset from a larger group of potential habitat sites is solved using either heuristic or formal optimization methods. The heuristic methods, although flexible and computationally fast, can not guarantee the solution is optimal therefore may lead to scarce resources being used in an ineffective way. The formal optimization methods, on the other hand, guarantees the solution is optimal, but it has been argued that it would be difficult to model site selection process using optimization models, especially when spatial attributes of the reserve have to be taken into account. This paper presents a linear integer programming model for the design of a minimal connected reserve network using a graph theory approach. A connected tree is determined corresponding to a connected reserve. Computational performance of the model is tested using datasets randomly generated by the software GAMS. Results show that the model can solve a connected reserve design problem which includes 100 potential sites and 30 species in a reasonable period of time. As an empirical application, the model is applied to the protection of endangered and threatened bird species in the Cache River basin area in Illinois, US. Two connected reserve networks are determined for 13 bird species.     

Experimental design for gene expression microarrays

We examine experimental design issues arising with gene expression microarray technology. Microarray experiments have multiple sources of variation, and experimental plans should ensure that effects of interest are not confounded with ancillary effects. A commonly used design is shown to violate this principle and to be generally inefficient. We explore the connection between microarray designs and classical block design and use a family of ANOVA models as a guide to choosing a design. We combine principles of good design and A-optimality to give a general set of recommendations for design with microarrays. These recommendations are illustrated in detail for one kind of experimental objective, where we also give the results of a computer search for good designs.