Insights From Supply Chain Disruptions in the COVID-19 Era

The COVID-19 pandemic has created a devastating impact on supply chains. Especially, transportation disruptions, the slowdown in manufacturing, supply-demand imbalances, operational inefficiency in last-mile, and deficiencies in dealing with the crisis can be seen as main headings. This chapter aims to reveal the problems and learn lessons in these areas where significant risks are faced. During the COVID era, the need for resilient supply chains that are not affected by instantaneous changes has come to the fore. Accordingly, the second aim of the chapter is to offer solutions toward the short, medium, and long terms of the first-mile, production, and last-mile processes as enhancing the responsiveness of supply chains by the elements of supply chain resilience. This study is prepared as a review article in an exploratory approach through the supply chain literature and current practical examples. As a result of the study, digital-intensive business models, collaborative network design, and sustainability are highlighted as the main concepts to reach more resilient networks.

An Approach to Information Management as a Subsidy of Global Health Actions

In the information age, it is urgent to work in a collaborative network, as well as the identification of researchers in specific areas in the globalized world. In this time, half of the world's population does not have access to essential health services, and more than one billion are threatened by neglected diseases. Information management helps in the identifying, extracting, and treating. In Brazil, the Lattes platform is the main curriculum repository for scientists and professionals in the different areas of scientific knowledge. After processing, 105 specialists were identified. Scientific articles published on Dengue, Zika virus, and Chikungunya are 11,743. The computational tool ScriptLattes proved to be efficient to extract, identify, and recover data from the curricula present in the Lattes database, contributing to the management of scientific knowledge in public health. Thus, Dengue, Zika, and Chikungunya infection data extracted from the platform generate information to assist in the knowledge management and decision makers for public health.

Protocol for a diagnostic accuracy study to develop diagnosis algorithm for biliary atresia using MMP-7 (DIABA-7 study): a study recruiting from Chinese Biliary Atresia Collaborative Network

IntroductionBiliary atresia is a severe liver disease in neonates, and the prognosis partially depends on the age at which infants undergo the Kasai procedure. Matrix metalloproteinase-7 (MMP-7) was confirmed to have significant value in the diagnosis of biliary atresia. However, so far, the reference range and its cut-off value for diagnosing biliary atresia have not been established yet.Methods and analysisDIagnosis Algorithm for Biliary Atresia (DIABA-7) is a prospective diagnostic test. Cholestatic infants and normal controls within 150 days of age are recruiting from the Chinese Biliary Atresia Collaborative Network. The serum samples and dried blood spot (DBS) samples are obtained to detect MMP-7 concentrations using an ELISA kit. The reference standard is the intraoperative exploration and subsequent histological examination of liver biopsies. Lambda-Mu-Sigma (LMS) method is used to calculate the normal range of serum MMP-7 of each age group. Receiver operating characteristics (ROC) curves are constructed to calculate the best cut-off point and area under the curve for the index test. The sensitivity, specificity, positive predictive value and negative predictive value are used to show the diagnostic accuracy. Pearson correlation coefficient test is applied to assess the correlation of serum MMP-7 and DBS MMP-7.Ethics and disseminationThis study was reviewed and approved by the Ethics Committee of Children’s Hospital of Fudan University (Number 2020–296). Dissemination will be guided by investigators and patients. The aim is to publish the study results in a high-quality peer-reviewed journal and present the findings at international academic meetings.Trial registration numberChiCTR2000032983.

Stock Price Movement Prediction Using Sentiment Analysis and CandleStick Chart Representation

Determining the price movement of stocks is a challenging problem to solve because of factors such as industry performance, economic variables, investor sentiment, company news, company performance, and social media sentiment. People can predict the price movement of stocks by applying machine learning algorithms on information contained in historical data, stock candlestick-chart data, and social-media data. However, it is hard to predict stock movement based on a single classifier. In this study, we proposed a multichannel collaborative network by incorporating candlestick-chart and social-media data for stock trend predictions. We first extracted the social media sentiment features using the Natural Language Toolkit and sentiment analysis data from Twitter. We then transformed the stock’s historical time series data into a candlestick chart to elucidate patterns in the stock’s movement. Finally, we integrated the stock’s sentiment features and its candlestick chart to predict the stock price movement over 4-, 6-, 8-, and 10-day time periods. Our collaborative network consisted of two branches: the first branch contained a one-dimensional convolutional neural network (CNN) performing sentiment classification. The second branch included a two-dimensional (2D) CNN performing image classifications based on 2D candlestick chart data. We evaluated our model for five high-demand stocks (Apple, Tesla, IBM, Amazon, and Google) and determined that our collaborative network achieved promising results and compared favorably against single-network models using either sentiment data or candlestick charts alone. The proposed method obtained the most favorable performance with 75.38% accuracy for Apple stock. We also found that the stock price prediction achieved more favorable performance over longer periods of time compared with shorter periods of time.

Impact Measurement of a Collaborative Pathology Network and Its Digital Support

The possibility to access healthcare fairly and equally among all the patients can be enhanced with the development of collaborative networks. To achieve their goals and exchange relevant information, they must be combined with a proper digital support. Several works dealing with this aspect can be found in literature; however, works defining a general methodological approach to design a digital solution for a collaborative network were not found. In addition to this, to assess the impact of a pathology network and its digital support, and ensure quality improvement as well as proper clinical outcomes, a suitable panel of key performance indicators (KPIs) should be designed. This paper describes a methodology to design a digital support of a collaborative pathology network, together with a set of KPIs to assess the impact of the pathology network and its digital solution. This approach was specifically applied for the Italian Rare Cancer Network in the context of the project “Italian Rare Cancer Network: Process monitoring and System Impact Assessment”.

Evaluation of Early Treatment Response Utilizing the MAS-ALL18 Adapted Management Guideline in Four "Mexico in Alliance with St. Jude" (MAS) Member Hospitals

Introduction: Acute lymphoblastic leukemia (ALL) represents approximately 50% of all childhood cancers in Latin America. Mexico is not the exception. The impact of ALL survival on overall childhood cancer survival is significant. According to government data, five-year survival is about 52%. Mexico in Alliance with St. Jude (MAS) is a multi-site, intersectoral collaboration. The collaborative network has explored and reported on factors associated with this suboptimal outcome and have identified challenges with ALL risk group classification as a leading cause. For example, as many as 82% of children diagnosed with ALL in Mexico receive high-risk treatment and the tendency for higher-risk group assignment often occurs in response to limited access to cytogenetic testing and minimal residual disease (MRD) testing. This leads to higher intensity treatment and may explain the high rate of treatment-related death (TRD) (12%) documented during the induction but also subsequently. In our previous case series, only 75% of patients were alive at the end of the first year of treatment. These findings, led MAS to develop a consensus-derived standardized diagnosis and treatment schema (MAS-ALL18), which takes into account clinical, cytogenetic, and MRD results. Diagnostic testing is performed in a centralized laboratory. Although centred on delivery of standard of care, this experience represents is the first prospective multi-site cooperative group effort in Mexico. We report on early treatment (first 90 days) clinical and implementation outcomes utilizing the MAS-ALL18 adapted management guideline (AMG) in four member hospitals of the MAS collaboration network. Results: From June 2019 to June 2020, 137 patients received treatment utilizing the MAS-ALL18 AMG in four publicly funded hospitals in Mexico. B-cell ALL represented 91.9% of the cases, 20.4% of patients were older than 9 years of age, 25.5% had a white blood cell count greater than 50,000 at diagnosis and 58.3% were male. Complete remission at the end of the induction was achieved in 90.6% of patients. TRD during the induction phase was 8%. MRD at Day 15 in 123 patients with B-cell ALL, 84.5% of them had MRD <1% and 7.3% had MRD ≥5%. MRD at Day 29 was assessed for the 10 patients diagnosed with T-cell ALL, 4 patients had MRD <0.01%, 2 had 0.02%, and 4 died during the induction phase. MRD was also assessed during consolidation (at Day 84) in 99 patients, 94.9% had MRD <0.01% and 5 patients MRD ≥0.01%, from which 3 had MRD at day 15 >1% and none registered an MRD result <0.5%. Utilizing the MAS-ALL18 risk group stratification, 50% of patients were assigned to a favorable risk group at the end of the consolidation. In 34 patients, the risk group was reclassified following the standardized algorithm; 30 reclassification events happened at the end of the induction and four at the end of the consolidation. Only two events were reassigned to a lower risk group, while the rest of the reclassifications were conducted to assign patients to a higher risk group due to unfavorable cytogenetics or an inadequate early response to treatment. High-risk treatment was ultimately assigned to 30% of patients using the MAS-ALL18 risk classification schema. Conclusion: It is feasible to implement a standardized multi-site adapted management guideline for ALL risk group stratification and treatment allocation in Mexico in the context of a collaborative network. TRD remains high during the induction phase, nevertheless, this number shows an improvement (8%) compared to the 2015 data report (12%). The ALL risk group classification is transitioning from a rigid scheme that placed 80% of patients in a high-risk group to a dynamic classification system that considers cytogenetic testing and MRD conducted in a centralized and externally validated laboratory that serves as reference for all the participating hospitals. The standardized MAS-ALL18 approach allowed us to classify 50% of patients in a favorable risk group during and at the end of the induction phase, which implies receiving a lower intensity treatment with a high probability of cure and a lower risk of TRD. The implementation of MAS-ALL18 risk classification scheme reduced the number of children requiring high-risk treatment in the participating hospitals. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Multiparametric Flow Cytometry Evaluation of CD200L/CD200R- LSC/NK Synapse Including Leukemia Stem Cell (LSC) Fraction As a Potential Therapeutic Target and Marker of NK Cell Exhaustion in Pediatric AML-Conect-AML French Collaborative Network

BACKGROUND: NK cells play a crucial role in the immune surveillance of malignant hemopathies. They undergo fine regulation by the microenvironment and by integrating activating and inhibiting signals trough several receptor/ligand couple interactions, hereafter referred to as "NK synapse". The ligands are expressed by a variety of cell types in the hematopoietic niche, including most immature leukemic stem cells CD34+CD38-. High expression of inhibiting ligands on AML (acute myeloid leukemia) blasts was associated with adverse clinical outcome . This observation highlights the relevance of identifying new ligand/receptor (L/R) pairs that could be targeted to prevent inhibiting interactions at the NK synapse. Relevant interactions to be blocked would display both ligand and receptor expressions on the leukemic cells and NK cells respectively. PATIENTS AND METHODS: 23 pediatric AML patients from the pediatric MyeChild01 protocol including in CONECT-AML French national collaborative network project diagnosed between 2018 and 2019 were included in this study. Reference bone marrows used were regenerative (4) or healthy bone marrows (5) . Multicolour flowcytometry protocole used fresh EDTA bone marrow at AML diagnosis and immunostaining with fluorochrome-coupled antibodies using 14 colour panel of L/R couples (Figure 1). Data was acquired on the FORTESSA Becton Dickinson with the Diva software and analysis using script R-PCA and FlowJo . RESULTS: We studied 5 inhibiting NK synapses (iinhibitory ligand/receptor pairs) . Four out of five inhibiting synapses (TIGIT/CD155; PD1-1/PD-L1; CD94/HLA-E and KIR2DL/HLA-A-B-C), showed not significant expression of ligand associated with the corresponding receptor expression. The CD200/CD200R synapse was the only one in which high ligand expression in blasts was significantly associated with high receptor expression on NK cells (Figure 2). This synapse could thus be of interest to develop targeting therapies for CD200-positive pediatric AML, with the strong advantage that patient eligibility could be easily identified at diagnosis. We then realized a principal component analysis, using the R software (PCA), integrating the MFIs of the 5 inhibiting NK synapses and 6 activating NK synapses (Figure 1) for the pediatric AML cohort (ID #1 to #23 ) together with reference bone marrows (healthy donors (n=5; ID #24 to #28) and regenerative bone marrows (n=4; ID #29 to #32)) . The CD200/CD200R synapse was identified as the main variable, explaining the distribution of patients and healthy donors as both CD200 and CD200R expressions happened to be among the most contributive to PCA axes. Interestingly, healthy donors clustered together, close to regenerative bone marrows. Pediatric AML patients distributed heterogeneously (Figure 3). In parallel, we evaluated whether CD200 expression on bulk leukemia blasts including most immature CD34+CD38- LSC was associated with exhaustion markers on NK cells. We found that patients with high and intermediate expression of CD200 on blasts (MFI > 3 rd quartile and comprised between 2 nd and 3 rd quartile, respectively) displayed strong PD-1 and TIGIT expressions on NK cells. Reciprocally, patients with low CD200 expression (MFI< 2 nd quartile) displayed a moderate PD-1 expression on NK cells, and TIGIT expression was more heterogeneous among individuals (Figure 4). CONCLUSIONS: Here, we identified CD200 expression in AML blasts including LSC as a marker that could be associated with NK cell exhaustion. at diagnosis. A PCA strategy allowed to observe that this marker differentiated pediatric AML patients NK synapse profiles from healthy donors and regenerative bone marrows sugesting a potential deregulation of bone marrow niche including NK-LSC escape. This suggests that CD200 expression assessment on blasts at diagnosis could be a tool to evaluate NK cell antitumor potential. Indeed, direct NK cell assessment by flow cytometry can be challenging because of blast invasion in the bone marrow. Nevertheless, it remains to be elucidated whether this clustering and exhaustion markers on NK cells correlated with patient clinical outcomes and MRD kinetics including CD34+CD38- LSC flow frequency evaluation that should be useful in most clinical trials to overcome chemoresistance of LSC. These results should be confirmed in a prospectively larger cohort of patients in future clinical trials. Figure 1 Figure 1. Disclosures Renard: Jazz Pharmaceuticals: Research Funding.

Teamwork makes the net-work: participant-governed networks and athletics sustainability collaboration

Purpose Athletic departments play an important role in sustainability-based collaborative processes due to their boundary spanning connections with both internal and external university stakeholders. As a result, athletic department representatives have become prominent members of university participant-governed network structures. The purpose of this study is to examine the role of dedicated “athletics green teams” as a unique form of control and coordination by considering how green team interactions support and augment the collaborative network of actors who are responsible for executing athletics sustainability practices on university campuses. Design/methodology/approach A sociocentric analysis is used to explore the network of a green team at a large American university. The analysis focuses on examining the size, composition and structure of relations involving green team members that facilitated various forms of information transmission and strategic action(s). Findings The results highlight how the presence of the athletic department in the green team provides heterophilous and multiplex relations across the collaborative network and how the green team itself provides a unique forum for planning and coordination, which is critical for providing more sophisticated, advanced structures for sustainability. Practical implications The findings of this study should reassure practitioners involved in convening green teams that such shared governance structures add value to athletics sustainability collaborative processes. In addition, subtle changes to the network governance structures has the potential to streamline the contribution of athletic departments to university sustainability initiatives and help project a more cohesive “Athletics” sustainability message that transmits across the collaborative network. Originality/value The outcomes of dedicated athletics green teams have been explored from a largely qualitative perspective. However, this study applies a novel relational approach to understand the shared governance value-added within a largely intra-organizational collaborative network.