Motivated by the COVID-19 pandemic, this paper explores the supply chain viability of medical equipment, an industry whose supply chain was put under a crucial test during the pandemic. This paper ...includes an empirical network-level analysis of supplier reachability under Random Failure Experiments (RFE) and Intelligent Attack Experiments (IAE). Specifically, this study investigates the effect of RFE and IAE across multiple tiers and scales. The global supply chain data was mined and analysed from about 45,000 firms with about 115,000 intertwined relationships spanning across 10 tiers of the backward supply chain of medical equipment. This complex supply chain network was analysed at four scales, namely: firm, country-industry, industry, and country. A notable contribution of this study is the application of a supply chain tier optimisation tool to identify the lowest tier of the supply chain that can provide adequate resolution for the study of the supply chain pattern. We also developed data-driven-tools to identify the thresholds for breakdown and fragmentation of the medical equipment supply chain when faced with random failures or different intelligent attack scenarios. The novel network analysis tools utilised in the study can be applied to the study of supply chain reachability and viability in other industries.
Summary Background First-line chemotherapy for patients with cisplatin-ineligible locally advanced or metastatic urothelial carcinoma is associated with short response duration, poor survival, and ...high toxicity. This study assessed atezolizumab (anti-programmed death-ligand 1 PD-L1) as treatment for metastatic urothelial cancer in cisplatin-ineligible patients. Methods For this single-arm, multicentre, phase 2 study, in 47 academic medical centres and community oncology practices in seven countries in North America and Europe, we recruited previously untreated patients with locally advanced or metastatic urothelial cancer who were cisplatin ineligible. Patients were given 1200 mg intravenous atezolizumab every 21 days until progression. The primary endpoint was independently confirmed objective response rate per Response Evaluation Criteria in Solid Tumors version 1.1 (central review), assessed in prespecified subgroups based on PD-L1 expression and in all patients. All participants who received one or more doses of atezolizumab were included in the primary and safety analyses. This study was registered with ClinicalTrials.gov , number NCT02108652. Findings Between June 9, 2014, and March 30, 2015, we enrolled 123 patients, of whom 119 received one or more doses of atezolizumab. At 17·2 months' median follow-up, the objective response rate was 23% (95% CI 16 to 31), the complete response rate was 9% (n=11), and 19 of 27 responses were ongoing. Median response duration was not reached. Responses occurred across all PD-L1 and poor prognostic factor subgroups. Median progression-free survival was 2·7 months (2·1 to 4·2). Median overall survival was 15·9 months (10·4 to not estimable). Tumour mutation load was associated with response. Treatment-related adverse events that occurred in 10% or more of patients were fatigue (36 30% patients), diarrhoea (14 12% patients), and pruritus (13 11% patients). One treatment-related death (sepsis) occurred. Nine (8%) patients had an adverse event leading to treatment discontinuation. Immune-mediated events occurred in 14 (12%) patients. Interpretation Atezolizumab showed encouraging durable response rates, survival, and tolerability, supporting its therapeutic use in untreated metastatic urothelial cancer. Funding F Hoffmann-La Roche, Genentech.
Cancer immunotherapies, such as atezolizumab, are proving to be a valuable therapeutic strategy across indications, including non-small cell lung cancer (NSCLC) and urothelial cancer (UC). Here, we ...describe a diagnostic assay that measures programmed-death ligand 1 (PD-L1) expression, via immunohistochemistry, to identify patients who will derive the most benefit from treatment with atezolizumab, a humanized monoclonal anti-PD-L1 antibody. We describe the performance of the VENTANA PD-L1 (SP142) Assay in terms of specificity, sensitivity, and the ability to stain both tumor cells (TC) and tumor-infiltrating immune cells (IC), in NSCLC and UC tissues. The reader precision, repeatability and intermediate precision, interlaboratory reproducibility, and the effectiveness of pathologist training on the assessment of PD-L1 staining on both TC and IC were evaluated. We detail the analytical validation of the VENTANA PD-L1 (SP142) Assay for PD-L1 expression in NSCLC and UC tissues and show that the assay reliably evaluated staining on both TC and IC across multiple expression levels/clinical cut-offs. The reader precision showed high overall agreement when compared with consensus scores. In addition, pathologists met the predefined training criteria (≥85.0% overall percent agreement) for the assessment of PD-L1 expression in NSCLC and UC tissues with an average overall percent agreement ≥95.0%. The assay evaluates PD-L1 staining on both cell types and is robust and precise. In addition, it can help to identify those patients who may benefit the most from treatment with atezolizumab, although treatment benefit has been demonstrated in an all-comer NSCLC and UC patient population.
Purpose: The pathways underlying basal-like breast cancer are poorly understood, and as yet, there is no approved targeted therapy
for this disease. We investigated the role of mitogen-activated ...protein kinase kinase (MEK) and phosphatidylinositol 3-kinase
(PI3K) inhibitors as targeted therapies for basal-like breast cancer.
Experimental Design: We used pharmacogenomic analysis of a large panel of breast cancer cell lines with detailed accompanying molecular information
to identify molecular predictors of response to a potent and selective inhibitor of MEK and also to define molecular mechanisms
underlying combined MEK and PI3K targeting in basal-like breast cancer. Hypotheses were confirmed by testing in multiple tumor
xenograft models.
Results: We found that basal-like breast cancer models have an activated RAS-like transcriptional program and show greater sensitivity
to a selective inhibitor of MEK compared with models representative of other breast cancer subtypes. We also showed that loss
of PTEN is a negative predictor of response to MEK inhibition, that treatment with a selective MEK inhibitor caused up-regulation
of PI3K pathway signaling, and that dual blockade of both PI3K and MEK/extracellular signal–regulated kinase signaling synergized
to potently impair the growth of basal-like breast cancer models in vitro and in vivo .
Conclusions: Our studies suggest that single-agent MEK inhibition is a promising therapeutic modality for basal-like breast cancers with
intact PTEN, and also provide a basis for rational combination of MEK and PI3K inhibitors in basal-like cancers with both
intact and deleted PTEN.
Evidence on the harms and benefits of social media use is mixed, in part because the effects of social media on well-being depend on a variety of individual difference moderators. Here, we explored ...potential neural moderators of the link between time spent on social media and subsequent negative affect. We specifically focused on the strength of correlation among brain regions within the frontoparietal system, previously associated with the top-down cognitive control of attention and emotion. Participants (N = 54) underwent a resting state functional magnetic resonance imaging scan. Participants then completed 28 days of ecological momentary assessment and answered questions about social media use and negative affect, twice a day. Participants who spent more than their typical amount of time on social media since the previous time point reported feeling more negative at the present moment. This within-person temporal association between social media use and negative affect was mainly driven by individuals with lower resting state functional connectivity within the frontoparietal system. By contrast, time spent on social media did not predict subsequent affect for individuals with higher frontoparietal functional connectivity. Our results highlight the moderating role of individual functional neural connectivity in the relationship between social media and affect.
Together, data from brain scanners and smartphones have sufficient coverage of biology, psychology, and environment to articulate between-person differences in the interplay within and across ...biological, psychological, and environmental systems thought to underlie psychopathology. An important next step is to develop frameworks that combine these two modalities in ways that leverage their coverage across layers of human experience to have maximum impact on our understanding and treatment of psychopathology. We review literature published in the last 3 years highlighting how scanners and smartphones have been combined to date, outline and discuss the strengths and weaknesses of existing approaches, and sketch a network science framework heretofore underrepresented in work combining scanners and smartphones that can push forward our understanding of health and disease.
Modifying behaviors, such as alcohol consumption, is difficult. Creating psychological distance between unhealthy triggers and one's present experience can encourage change. Using two multisite, ...randomized experiments, we examine whether theory-driven strategies to create psychological distance-mindfulness and perspective-taking-can change drinking behaviors among young adults without alcohol dependence via a 28-day smartphone intervention (Study 1, N = 108 participants, 5492 observations; Study 2, N = 218 participants, 9994 observations). Study 2 presents a close replication with a fully remote delivery during the COVID-19 pandemic. During weeks when they received twice-a-day intervention reminders, individuals in the distancing interventions reported drinking less frequently than on control weeks-directionally in Study 1, and significantly in Study 2. Intervention reminders reduced drinking frequency but did not impact amount. We find that smartphone-based mindfulness and perspective-taking interventions, aimed to create psychological distance, can change behavior. This approach requires repeated reminders, which can be delivered via smartphones.
A holistic understanding of the naturalistic dynamics among physical activity, sleep, emotions, and purpose in life as part of a system reflecting wellness is key to promoting well-being. The main ...aim of this study was to examine the day-to-day dynamics within this wellness system.
Using self-reported emotions (happiness, sadness, anger, anxiousness) and physical activity periods collected twice per day, and daily reports of sleep and purpose in life via smartphone experience sampling, more than 28 days as college students ( n = 226 young adults; mean standard deviation = 20.2 1.7 years) went about their daily lives, we examined day-to-day temporal and contemporaneous dynamics using multilevel vector autoregressive models that consider the network of wellness together.
Network analyses revealed that higher physical activity on a given day predicted an increase of happiness the next day. Higher sleep quality on a given night predicted a decrease in negative emotions the next day, and higher purpose in life predicted decreased negative emotions up to 2 days later. Nodes with the highest centrality were sadness, anxiety, and happiness in the temporal network and purpose in life, anxiety, and anger in the contemporaneous network.
Although the effects of sleep and physical activity on emotions and purpose in life may be shorter term, a sense of purpose in life is a critical component of wellness that can have slightly longer effects, bleeding into the next few days. High-arousal emotions and purpose in life are central to motivating people into action, which can lead to behavior change.
Genealogical networks (i.e. family trees) are of growing interest, with the largest known data sets now including well over one billion individuals. Interest in family history also supports an 8.5 ...billion dollar industry whose size is projected to double within 7 years FutureWise report HC-1137. Yet little mathematical attention has been paid to the complex network properties of genealogical networks, especially at large scales. The structure of genealogical networks is of particular interest due to the practice of forming unions, e.g. marriages, that are typically well outside one’s immediate family. In most other networks, including other social networks, no equivalent restriction exists on the distance at which relationships form. To study the effect this has on genealogical networks we use persistent homology to identify and compare the structure of 101 genealogical and 31 other social networks. Specifically, we introduce the notion of a network’s persistence curve, which encodes the network’s set of persistence intervals. We find that the persistence curves of genealogical networks have a distinct structure when compared to other social networks. This difference in structure also extends to subnetworks of genealogical and social networks suggesting that, even with incomplete data, persistent homology can be used to meaningfully analyze genealogical networks. Here we also describe how concepts from genealogical networks, such as common ancestor cycles, are represented using persistent homology. We expect that persistent homology tools will become increasingly important in genealogical exploration as popular interest in ancestry research continues to expand.
Networks, which represent agents and interactions between them, arise in myriad applications throughout the sciences, engineering, and even the humanities. To understand large-scale structure in a ...network, a common task is to cluster a network’s nodes into sets called “communities,” such that there are dense connections within communities but sparse connections between them. A popular and statistically principled method to perform such clustering is to use a family of generative models known as stochastic block models (SBMs). In this paper, we show that maximum-likelihood estimation in an SBM is a network analog of a well-known continuum surface-tension problem that arises from an application in metallurgy. To illustrate the utility of this relationship, we implement network analogs of three surface-tension algorithms, with which we successfully recover planted community structure in synthetic networks and which yield fascinating insights on empirical networks that we construct from hyperspectral videos.
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