Temporal cascade model for analyzing spread in evolving networks

Current approaches for modeling propagation in networks (e.g., of diseases, computer viruses, rumors) cannot adequately capture temporal properties such as order/duration of evolving connections or dynamic likelihoods of propagation along connections. Temporal models on evolving networks are crucial in applications that need to analyze dynamic spread. For example, a disease spreading virus has varying transmissibility based on interactions between individuals occurring with different frequency, proximity, and venue population density. Similarly, propagation of information having a limited active period, such as rumors, depends on the temporal dynamics of social interactions. To capture such behaviors, we first develop the Temporal Independent Cascade (T-IC) model with a spread function that efficiently utilizes a hypergraph-based sampling strategy and dynamic propagation probabilities. We prove this function to be submodular, with guarantees of approximation quality. This enables scalable analysis on highly granular temporal networks where other models struggle, such as when the spread across connections exhibits arbitrary temporally evolving patterns. We then introduce the notion of ‘reverse spread’ using the proposed T-IC processes, and develop novel solutions to identify both sentinel/detector nodes and highly susceptible nodes. Extensive analysis on real-world datasets shows that the proposed approach significantly outperforms the alternatives in modeling both if and how spread occurs, by considering evolving network topology alongside granular contact/interaction information. Our approach has numerous applications, such as virus/rumor/influence tracking. Utilizing T-IC, we explore vital challenges of monitoring the impact of various intervention strategies over real spatio-temporal contact networks where we show our approach to be highly effective

Wearable technology for one health: Charting the course of dermal biosensing

Over the last decade, a significant paradigm shift has been observed towards leveraging less invasive biological fluids—such as skin interstitial fluid (ISF), sweat, tears, and saliva—for health monitoring. This evolution seeks to transcend traditional, invasive blood-based methods, offering a more accessible approach to health monitoring for non-specialized personnel. Skin ISF, with its profound resemblance to blood, emerges as a pivotal medium for the real-time, minimally invasive tracking of a broad spectrum of biomarkers, thus becoming an invaluable asset for correlating with blood-based data. Our exploration delves deeply into the development of wearable molecular biosensors, spotlighting dermal sensors for their pivotal roles across both clinical and everyday health monitoring scenarios and underscoring their contributions to the holistic One Health initiative. In bringing forward the myriad challenges that permeate this field, we also project future directions, notably the potential of skin ISF as a promising candidate for continuous health tracking. Moreover, this paper aims to catalyse further exploration and innovation by presenting a curated selection of seminal technological advancements. Amidst the saturated landscape of analytical literature on translational challenges, our approach distinctly seeks to highlight recent developments. In attracting a wider spectrum of research groups to this versatile domain, we endeavour to broaden the collective understanding of its trajectory and potential, mapping the evolution of wearable biosensor technology. This strategy not only illuminates the transformative impact of wearable biosensors in reshaping health diagnostics and personalized medicine but also fosters increased participation and progress within the field. Distinct from recent manuscripts in this domain, our review serves as a distillation of key concepts, elucidating pivotal papers that mark the latest advancements in wearable sensors. Through presenting a curated collection of landmark studies and offering our perspectives on the challenges and forward paths, this paper seeks to guide new entrants in the area. We delineate a division between wearable epidermal and subdermal sensors—focusing on the latter as the future frontier—thereby establishing a unique discourse within the ongoing narrative on wearable sensing technologies

HIV gp120 Induces, NF-κB Dependent, HIV Replication that Requires Procaspase 8

HIV envelope glycoprotein gp120 causes cellular activation resulting in anergy, apoptosis, proinflammatory cytokine production, and through an unknown mechanism, enhanced HIV replication.We describe that the signals which promote apoptosis are also responsible for the enhanced HIV replication. Specifically, we demonstrate that the caspase 8 cleavage fragment Caspase8p43, activates p50/p65 Nuclear Factor kappaB (NF-kappaB), in a manner which is inhibited by dominant negative IkappaBalpha. This caspase 8 dependent NF-kappaB activation occurs following stimulation with gp120, TNF, or CD3/CD28 crosslinking, but these treatments do not activate NF-kappaB in cells deficient in caspase 8. The Casp8p43 cleavage fragment also transactivates the HIV LTR through NF-kappaB, and the absence of caspase 8 following HIV infection greatly inhibits HIV replication.Gp120 induced caspase 8 dependent NF-kappaB activation is a novel pathway of HIV replication which increases understanding of the biology of T-cell death, as well as having implications for understanding treatment and prevention of HIV infection

Conceptualizing Creativity and Strategy in the Work of Professional Songwriters

Drawing upon interviews conducted as part of the Sodajerker on Songwriting podcast this paper explores professional songwriting as musical labor. It explores how songwriters conceptualize creativity and what strategies they employ for the delivery of original songs. It argues that individuals evince a faith in their own autonomy in the face of the demands of form and industry, expressing intuitive concepts of inspiration and practical insights into the nature of their work as work. The paper suggests that achieving and maintaining success is affirmed in a conjunction of value that is both economic and aesthetic, personal and public

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease