Post pandemic strategic planning of food catering production and distribution networks: A regional case study

Due to the Covid19 outbreak, the food catering industry faces disruption of demand traits and great uncertainty about the future development of market segmentation. The need for a re-design of production and logistic networks faces the lack of knowledge about cost drivers, rendering the application of mathematical optimization models challenging. In this paper, a cost components analysis is carried out to quantify each cost item's impact on the full meal cost. Cost analysis aims to formalize the relationship between meal cost and parameters such as productivity, meal conservation regime, customer typology, portioning method, and customer-plant distance. The cost parameters are adjusted through empirically driven correction factors to include operational and management complexities that would otherwise be neglected. The obtained parameters feed a total cost minimization model for a productive and distributive catering network. The location-allocation model chooses the production capacity to activate in each production plant for every meal-type and achieves the customer-production plant pairing. The framework is applied in an Italian regional case study to compare the BAU scenario to two different To-Be scenarios. The As-Is scenario considers four different production facilities serving the pre-pandemic demand of 2019, while the To-Be scenarios are based upon a demand forecast enforcing a more resilient network. The analysis shows how re-designing production and distribution networks enables meeting uncertain demand while keeping FMCs under control within a regional environment

Economic and environmental optimization of packaging containers choice in Food Catering Supply Chain

Disposable containers are widely employed throughout food supply chains (FSCs) to transport, sell, or store perishable products. These containers are made of several materials, like plastic and cardboard. Albeit the widespread use of such containers, not all the materials are suitable for food contact, and a barrier layer between perishable products and the container is needed. Moreover, a high percentage of waste along the FSC consists of primary and secondary packages. Food Catering Supply Chain (FCSC), made of multi-stage logistic networks, represents a challenging scenario for minimizing packaging disposal. Chosen for reducing waste, reusable plastic containers (RPCs) are gaining ground within the food supply chain network. We propose a multi-objective optimization model to improve the business as usual (BAU) of FCSC, quantifying saving in terms of cost and environmental impact due to the employment of RPCs. The model virtualizes the logistic and operational costs as well as the transportation and disposal impact of reusable and recyclable plastic containers. This paper evaluates the use of RPCs by comparing the performances of as-is and to-be scenarios derived from an industrial case study. The analyzed network comprises perishable product suppliers, RPC poolers, cross-docking facilities, customers, and collectors. The results show the reduction of environmental impacts and logistic, handling, and operational costs in the proposed FCSC topology. A new network configuration and insights for future research investigations are presented

Sustainability assessment of transport operations in local Food Supply Chain networks

As food supply chains represent a hotspot of climate change, a rapid transition toward more sustainable processes and operations is expected. Whilst research provides decision-support models to optimize food ecosystems, the application of these techniques in practice is often discouraged by a lack of knowledge and visibility on the hidden food networks’ performance and impacts. This paper overviews a case study on a regional fruit and vegetable supply chain characterized by broad fragmentation of supplies, a wide number of actors involved, multiple stages, and limited visibility on the routes traveled by a generic food order. This work analyzes the perishable flows from the growers to the retailer under the lens of environmental externalities in order to promote sustainable supply chain management strategies. Logistic flows throughout the stages are tracked and mapped to aid integrated decision-making, resulting in food miles and transport externalities assessment. A multi-scenario what-if analysis is illustrated to compare and assess transportation costs, food miles, and carbon footprint resulting from more integrated supply chain decisions and configurations. The To-Be scenario results in significant savings in terms of carbon emissions, traveling, and transportation costs. Moreover, the reduction of transported volumes reflects how multiple supply chain stages compel double/triple-handling of food and avoidable travelin

Localization of Magic-F1 Transgene, Involved in Muscular Hypertrophy, during Early Myogenesis

We recently showed that Magic-F1 (Met-activating genetically improved chimeric factor 1), a human recombinant protein derived from hepatocyte growth factor/scatter factor (HGF/SF) induces muscle cell hypertrophy but not progenitor cell proliferation, both in vitro and in vivo. Here, we examined the temporal and spatial expression pattern of Magic-F1 in comparison with Pax3 (paired box gene 3) transcription factor during embryogenesis. Ranging from 9.5 to 17.5 dpc (days post coitum) mouse embryos were analyzed by in situ hybridization using whole mounts during early stages of development (9.5–10.5–11.5 dpc) and cryostat sections for later stages (11.5–13.5–15.5–17.5 dpc). We found that Magic-F1 is expressed in developing organs and tissues of mesenchymal origin, where Pax3 signal appears to be downregulated respect to the wt embryos. These data suggest that Magic-F1 could be responsible of muscular hypertrophy, cooperating with Pax3 signal pathway in skeletal muscle precursor cells

Muscle hypertrophy and vascularization induction using human recombinant proteins

Met-Activating Genetically Improved Chimeric Factor-1 (Magic-F1) is an engineered protein that contains two human Met-binding domains. Previous experiments in both homozygous and hemizygous transgenic mice demonstrated that the skeletal muscle specific expression of Magic-F1 can induce a constitutive muscular hypertrophy, increasing the vessel number in fast twitch fibers, also improving running performance and accelerating muscle regeneration after injury [1]. We also found that Magic-F1 could be responsible of muscular hypertrophy inteacting with Pax3 signal pathway in skeletal muscle precursor cells [2]. In order to evaluate the therapeutic potential of Magic-F1, we tested its effect on multipotent and pluripotent stem cells [3]. Murine mesoangioblasts (adult vessel-associated stem cells) expressing Magic-F1 were able to differentiate spontaneously forming myotubes. In addition, in Magic-F1 inducible murine embryonic stem cells subjected to myogenic differentiation, the presence of recombinant protein resulted in improved myogenic commitment. Finally, the microarray analysis of Magic-F1+/+ satellite cells evidenced transcriptomic changes in genes involved in the control of muscle growth, development and vascularisation [4]. Taken together our results candidate Magic-F1 as a potent myogenic inducer, able to affect positively the vascular network, increasing vessel number in fast twitch fibers and modulating the gene expression profile in myogenic progenitors

Localization of Magic-F1 Transgene, Involved in Muscular Hypertrophy, during Early Myogenesis

We recently showed that Magic-F1 (Met-activating genetically improved chimeric factor 1), a human recombinant protein derived from hepatocyte growth factor/scatter factor (HGF/SF) induces muscle cell hypertrophy but not progenitor cell proliferation, both in vitro and in vivo. Here, we examined the temporal and spatial expression pattern of Magic-F1 in comparison with Pax3 (paired box gene 3) transcription factor during embryogenesis. Ranging from 9.5 to 17.5 dpc (days post coitum) mouse embryos were analyzed by in situ hybridization using whole mounts during early stages of development (9.5-10.5-11.5 dpc) and cryostat sections for later stages (11.5-13.5-15.5-17.5 dpc). We found that Magic-F1 is expressed in developing organs and tissues of mesenchymal origin, where Pax3 signal appears to be downregulated respect to the wt embryos. These data suggest that Magic-F1 could be responsible of muscular hypertrophy, cooperating with Pax3 signal pathway in skeletal muscle precursor cells

Development of a small molecule that corrects misfolding and increases secretion of Z α1 -antitrypsin.

Severe α1 -antitrypsin deficiency results from the Z allele (Glu342Lys) that causes the accumulation of homopolymers of mutant α1 -antitrypsin within the endoplasmic reticulum of hepatocytes in association with liver disease. We have used a DNA-encoded chemical library to undertake a high-throughput screen to identify small molecules that bind to, and stabilise Z α1 -antitrypsin. The lead compound blocks Z α1 -antitrypsin polymerisation in vitro, reduces intracellular polymerisation and increases the secretion of Z α1 -antitrypsin threefold in an iPSC model of disease. Crystallographic and biophysical analyses demonstrate that GSK716 and related molecules bind to a cryptic binding pocket, negate the local effects of the Z mutation and stabilise the bound state against progression along the polymerisation pathway. Oral dosing of transgenic mice at 100 mg/kg three times a day for 20 days increased the secretion of Z α1 -antitrypsin into the plasma by sevenfold. There was no observable clearance of hepatic inclusions with respect to controls over the same time period. This study provides proof of principle that "mutation ameliorating" small molecules can block the aberrant polymerisation that underlies Z α1 -antitrypsin deficiency

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and objectives: It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19-related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population. Methods: Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score > 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ2 test, and the risk excess was quantified by risk ratios (RRs). Results: The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p < 0.001), RR = 2.19 for ICU admission (p < 0.001), and RR = 2.43 for death (p < 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04). Discussion: Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon