The role of operational research in green freight transportation

Recent years have witnessed an increased awareness of the negative external impacts of freight transportation. The field of Operational Research (OR) has, particularly in the recent years, continued to contribute to alleviating the negative impacts through the use of various optimization models and solution techniques. This paper presents the basic principles behind and an overview of the existing body of recent research on ‘greening’ freight transportation using OR-based planning techniques. The particular focus is on studies that have been described for two heavily used modes for transporting freight across the globe, namely road (including urban and electric vehicles) and maritime transportation, although other modes are also briefly discussed

An Optimization Approach to the Ordering Phase of an Attended Home Delivery Service

Attended Home Delivery (AHD) systems are used whenever a supplying company offers online shopping services that require that customers must be present when their deliveries arrive. Therefore, the supplying company and the customer must both agree on a time window, which ideally is rather short, during which delivery is guaranteed. Typically, a capacitated Vehicle Routing Problem with Time Windows forms the underlying optimization problem of the AHD system. In this work, we consider an AHD system that runs the online grocery shopping service of an international grocery retailer. The ordering phase, during which customers place their orders through the web service, is the computationally most challenging part of the AHD system. The delivery schedule must be built dynamically as new orders are placed. We propose a solution approach that allows to (non-stochastically) determine which delivery time windows can be offered to potential customers. We split the computations of the ordering phase into four key steps. For performing these basic steps we suggest both a heuristic approach and a hybrid approach employing mixed-integer linear programs. In an experimental evaluation we demonstrate the efficiency of our approaches

VarFish - Collaborative and comprehensive variant analysis for diagnosis and research

VarFish is a user-friendly web application for the quality control, filtering, prioritization, analysis, and user-based annotation of panel and exome variant data for rare disease genetics. It is capable of processing variant call files with single or multiple samples. The variants are automatically annotated with population frequencies, molecular impact, and presence in databases such as ClinVar. Further, it provides support for pathogenicity scores including CADD, MutationTaster, and phenotypic similarity scores. Users can filter variants based on these annotations and presumed inheritance pattern and sort the results by these scores. Filtered variants are listed with their annotations and many useful link-outs to genome browsers, other gene/variant data portals, and external tools for variant assessment. VarFish allows user to create their own annotations including support for variant assessment following ACMG-AMP guidelines. In close collaboration with medical practitioners, VarFish was designed for variant analysis and prioritization in diagnostic and research settings as described in the software’s extensive manual. The user interface has been optimized for supporting these protocols. Users can install VarFish on their own in-house servers where it provides additional lab notebook features for collaborative analysis and allows re-analysis of cases, e.g., after update of genotype or phenotype databases

Variable pulmonary manifestations in Chitayat syndrome: Six additional affected individuals

Hand hyperphalangism leading to shortened index fingers with ulnar deviation, hallux valgus, mild facial dysmorphism and respiratory compromise requiring assisted ventilation are the key features of Chitayat syndrome. This condition results from the recurrent heterozygous missense variant NM_006494.2:c.266A>G; p.(Tyr89Cys) in ERF on chromosome 19q13.2, encoding the ETS2 repressor factor (ERF) protein. The pathomechanism of Chitayat syndrome is unknown. To date, seven individuals with Chitayat syndrome and the recurrent pathogenic ERF variant have been reported in the literature. Here, we describe six additional individuals, among them only one presenting with a history of assisted ventilation, and the remaining presenting with variable pulmonary phenotypes, including one individual without any obvious pulmonary manifestations. Our findings widen the phenotype spectrum caused by the recurrent pathogenic variant in ERF, underline Chitayat syndrome as a cause of isolated skeletal malformations and therefore contribute to the improvement of diagnostic strategies in individuals with hand hyperphalangism

Genetic Diagnostics in Routine Osteological Assessment of Adult Low Bone Mass Disorders

Context Many different inherited and acquired conditions can result in premature bone fragility / low bone mass disorders (LBMD). Objective We aimed at elucidating the impact of genetic testing on differential diagnosis of adult LBMD and at defining clinical criteria for predicting monogenic forms. Methods Four clinical centers broadly recruited a cohort of 394 unrelated adult women before menopause and men younger than 55 years with a bone mineral density (BMD) Z-score 2), and a high normal BMI. In contrast, mutation frequencies did not correlate with age, prevalent vertebral fractures, BMD, or biochemical parameters. In individuals without monogenic disease-causing rare variants, common variants predisposing for low BMD, e.g. in LRP5, were overrepresented. Conclusion The overlapping spectra of monogenic adult LBMD can be easily disentangled by genetic testing and the proposed clinical criteria can help to maximize the diagnostic yield

CREBBP mutations in individuals without Rubinstein-Taybi syndrome phenotype

Item does not contain fulltextMutations in CREBBP cause Rubinstein-Taybi syndrome. By using exome sequencing, and by using Sanger in one patient, CREBBP mutations were detected in 11 patients who did not, or only in a very limited manner, resemble Rubinstein-Taybi syndrome. The combined facial signs typical for Rubinstein-Taybi syndrome were absent, none had broad thumbs, and three had only somewhat broad halluces. All had apparent developmental delay (being the reason for molecular analysis); five had short stature and seven had microcephaly. The facial characteristics were variable; main characteristics were short palpebral fissures, telecanthi, depressed nasal ridge, short nose, anteverted nares, short columella, and long philtrum. Six patients had autistic behavior, and two had self-injurious behavior. Other symptoms were recurrent upper airway infections (n = 5), feeding problems (n = 7) and impaired hearing (n = 7). Major malformations occurred infrequently. All patients had a de novo missense mutation in the last part of exon 30 or beginning of exon 31 of CREBBP, between base pairs 5,128 and 5,614 (codons 1,710 and 1,872). No missense or truncating mutations in this region have been described to be associated with the classical Rubinstein-Taybi syndrome phenotype. No functional studies have (yet) been performed, but we hypothesize that the mutations disturb protein-protein interactions by altering zinc finger function. We conclude that patients with missense mutations in this specific CREBBP region show a phenotype that differs substantially from that in patients with Rubinstein-Taybi syndrome, and may prove to constitute one (or more) separate entities. (c) 2016 Wiley Periodicals, Inc

TGDS pathogenic variants cause Catel-Manzke syndrome without hyperphalangy

Catel-Manzke syndrome, also known as micrognathia-digital-syndrome, is a rare autosomal recessive disorder characterized by the combination of the two cardinal features Pierre-Robin sequence and bilateral hyperphalangy leading to ulnar clinodactyly (ulnar curvature of the phalanges) and radial deviation (radial angulation at the metacarpophalangeal joint) of the index finge

Independent Recruitment of a Flavin-Dependent Monooxygenase for Safe Accumulation of Sequestered Pyrrolizidine Alkaloids in Grasshoppers and Moths

Several insect lineages have developed diverse strategies to sequester toxic pyrrolizidine alkaloids from food-plants for their own defense. Here, we show that in two highly divergent insect taxa, the hemimetabolous grasshoppers and the holometabolous butterflies, an almost identical strategy evolved independently for safe accumulation of pyrrolizidine alkaloids. This strategy involves a pyrrolizidine alkaloid N-oxygenase that transfers the pyrrolizidine alkaloids to their respective N-oxide, enabling the insects to avoid high concentrations of toxic pyrrolizidine alkaloids in the hemolymph. We have identified a pyrrolizidine alkaloid N-oxygenase, which is a flavin-dependent monooxygenase, of the grasshopper Zonocerus variegatus. After heterologous expression in E. coli, this enzyme shows high specificity for pyrrolizidine alkaloids of various structural types and for the tropane alkaloid atropine as substrates, a property that has been described previously for a pyrrolizidine alkaloid N-oxygenase of the arctiid moth Grammia geneura. Phylogenetic analyses of insect flavin-dependent monooxygenase sequences suggest that independent gene duplication events preceded the establishment of this specific enzyme in the lineages of the grasshoppers and of arctiid moths. Two further flavin-dependent monooxygenase sequences have been identified from Z. variegatus sharing amino acid identities of approximately 78% to the pyrrolizidine alkaloid N-oxygenase. After heterologous expression, both enzymes are also able to catalyze the N-oxygenation of pyrrolizidine alkaloids, albeit with a 400-fold lower specific activity. With respect to the high sequence identity between the three Z. variegatus sequences this ability to N-oxygenize pyrrolizidine alkaloids is interpreted as a relict of a former bifunctional ancestor gene of which one of the gene copies optimized this activity for the specific adaptation to pyrrolizidine alkaloid containing food plants

PEDIA: prioritization of exome data by image analysis

Purpose Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. Methods Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. Results The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20–89% and the top 10 accuracy rate by more than 5–99% for the disease-causing gene. Conclusion Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis