Mapping philanthropic support of science.

While philanthropic support for science has increased in the past decade, there is limited quantitative knowledge about the patterns that characterize it and the mechanisms that drive its distribution. Here, we map philanthropic funding to universities and research institutions based on IRS tax forms from 685,397 non-profit organizations. We identify nearly one million grants supporting institutions involved in science and higher education, finding that in volume and scope, philanthropy is a significant source of funds, reaching an amount that rivals some of the key federal agencies like the NSF and NIH. Our analysis also reveals that philanthropic funders tend to focus locally, indicating that criteria beyond research excellence play an important role in funding decisions, and that funding relationships are stable, i.e. once a grant-giving relationship begins, it tends to continue in time. Finally, we show that the bipartite funder-recipient network displays a highly overrepresented motif indicating that funders who share one recipient also share other recipients and we show that this motif contains predictive power for future funding relationships. We discuss the policy implications of our findings on inequality in science, scientific progress, and the role of quantitative approaches to philanthropy.

Modelling HDV kinetics under the entry inhibitor bulevirtide suggests the existence of two HDV-infected cell populations.

Background & Aims: Bulevirtide (BLV) was approved for the treatment of compensated chronic hepatitis D virus (HDV) infection in Europe in 2020. However, research into the effects of the entry inhibitor BLV on HDV-host dynamics is in its infancy. Methods: Eighteen patients with HDV under nucleos(t)ide analogue treatment for hepatitis B, with compensated cirrhosis and clinically significant portal hypertension, received BLV 2 mg/day. HDV RNA, alanine aminotransferase (ALT), and hepatitis B surface antigen (HBsAg) were measured at baseline, weeks 4, 8 and every 8 weeks thereafter. A mathematical model was developed to account for HDV, HBsAg and ALT dynamics during BLV treatment. Results: Median baseline HDV RNA, HBsAg, and ALT were 4.9 log IU/ml [IQR: 4.4-5.8], 3.7 log IU/ml [IQR: 3.4-3.9] and 106 U/L [IQR: 81-142], respectively. During therapy, patients fit into four main HDV kinetic patterns: monophasic (n = 2), biphasic (n = 10), flat-partial response (n = 4), and non-responder (n = 2). ALT normalization was achieved in 14 (78%) patients at a median of 8 weeks (range: 4-16). HBsAg remained at pre-treatment levels. Assuming that BLV completely (∼100%) blocks HDV entry, modeling indicated that two HDV-infected cell populations exist: fast HDV clearing (median t1/2 = 13 days) and slow HDV clearing (median t1/2 = 44 days), where the slow HDV-clearing population consisted of ∼1% of total HDV-infected cells, which could explain why most patients exhibited a non-monophasic pattern of HDV decline. Moreover, modeling explained ALT normalization without a change in HBsAg based on a non-cytolytic loss of HDV from infected cells, resulting in HDV-free HBsAg-producing cells that release ALT upon death at a substantially lower rate compared to HDV-infected cells. Conclusion: The entry inhibitor BLV provides a unique opportunity to understand HDV, HBsAg, ALT, and host dynamics. Impact and implications: Mathematical modeling of hepatitis D virus (HDV) treatment with the entry inhibitor bulevirtide (BLV) provides a novel window into the dynamics of HDV RNA and alanine aminotransferase. Kinetic data from patients treated with BLV monotherapy can be explained by hepatocyte populations with different basal HDV clearance rates and non-cytolytic clearance of infected cells. While further studies are needed to test and refine the kinetic characterization described here, this study provides a new perspective on viral dynamics, which could inform evolving treatment strategies for HDV.

Hepatitis D Virus and HBsAg Dynamics in the era of new Antiviral Treatments.

PURPOSE OF REVIEW: Hepatitis D virus (HDV) infection is the most severe form of chronic viral hepatitis, with no FDA-approved therapy. Progress in the development of effective HDV treatments is accelerating. This review highlights how mathematical modeling is improving understanding of HDV-HBsAg-host dynamics during antiviral therapy and generating insights into the efficacy and modes of action (MOA) of new antiviral agents. RECENT FINDINGS: Clinical trials with pegylated-interferon-λ, bulevertide, nucleic acid polymers, and/or lonafarnib against various steps of the HDV-life cycle have revealed new viral-kinetic patterns that were not observed under standard treatment with pegylated-interferon-α. Modeling indicated that the half-lives of circulating HDV and HBsAg are ~ 1.7 d and ~ 1.3 d, respectively, estimated the relative response of HDV and HBsAg during different antiviral therapies, and provided insights into the efficacy and MOA of drugs in development for treating HDV, which can inform response-guided therapy to individualize treatment duration. Mathematical modeling of HDV and HBsAg kinetics provides a window into the HDV virus lifecycle, HDV-HBsAg-host dynamics during antiviral therapy, and the MOA of new drugs for HDV.

Philanthropy in art: locality, donor retention, and prestige.

A significant portion of funding for art comes from foundations, representing a key revenue stream for most art organizations. Little is known, however, about the quantitative patterns that govern art funding, limiting the fundraising efficiency of organizations in need of resources, as well as optimal funding allocation of donors. To address these shortcomings, here we relied on the IRS e-file dataset to identify $36B in grants from 46,643 foundations to 48,766 art recipients between 2010 and 2019, allowing us to quantify donor-recipient relationships in art. We find that philanthropic giving is broadly distributed, following a stable power-law distribution, indicating that some funders give considerably and predictably more than others. Giving is highly localized, with 60% of grants and funds going to recipients in the donor's state. Furthermore, donors often support multiple local organizations that offer distinct artforms, rather than advancing a particular subarea within art. Donor retention is strong, with nearly 70% of relationships continuing the next year. Finally, we explored the role of institutional prestige in foundation giving, finding that funding does correlate with prestige, with notable exceptions. Our results present the largest and most comprehensive data-driven exploration of giving by foundations to art to date, unveiling multiple insights that could benefit both donors and recipients.

Hepatitis delta virus RNA decline post-inoculation in human NTCP transgenic mice is biphasic.

Chronic infection with hepatitis B and delta viruses (HDV) is the most serious form of viral hepatitis due to more severe manifestations of an accelerated progression to liver fibrosis, cirrhosis, and hepatocellular carcinoma. We characterized early HDV kinetics post-inoculation and incorporated mathematical modeling to provide insights into host-HDV dynamics. We analyzed HDV RNA serum viremia in 192 immunocompetent (C57BL/6) and immunodeficient (NRG) mice that did or did not transgenically express the HDV receptor-human sodium taurocholate co-transporting polypeptide (hNTCP). Kinetic analysis indicates an unanticipated biphasic decline consisting of a sharp first-phase and slower second-phase decline regardless of immunocompetence. HDV decline after re-inoculation again followed a biphasic decline; however, a steeper second-phase HDV decline was observed in NRG-hNTCP mice compared to NRG mice. HDV-entry inhibitor bulevirtide administration and HDV re-inoculation indicated that viral entry and receptor saturation are not major contributors to clearance, respectively. The biphasic kinetics can be mathematically modeled by assuming the existence of a non-specific-binding compartment with a constant on/off-rate and the steeper second-phase decline by a loss of bound virus that cannot be returned as free virus to circulation. The model predicts that free HDV is cleared with a half-life of 35 minutes (standard error, SE: 6.3), binds to non-specific cells with a rate of 0.05 per hour (SE: 0.01), and returns as free virus with a rate of 0.11 per hour (SE: 0.02). Characterizing early HDV-host kinetics elucidates how quickly HDV is either cleared or bound depending on the immunological background and hNTCP presence. IMPORTANCE The persistence phase of HDV infection has been studied in some animal models; however, the early kinetics of HDV in vivo is incompletely understood. In this study, we characterize an unexpectedly HDV biphasic decline post-inoculation in immunocompetent and immunodeficient mouse models and use mathematical modeling to provide insights into HDV-host dynamics.

Rapid monophasic HBsAg decline during nucleic-acid polymer-based therapy predicts functional cure.

BACKGROUND AND AIMS: Analyzing the interplay among serum HBV DNA, HBsAg, anti-HBs, and alanine aminotransferase (ALT) during nucleic-acid polymer (NAP)-based therapy for chronic hepatitis B provides a unique opportunity to identify kinetic patterns associated with functional cure. METHODS: All participants with HBeAg-negative chronic HBV infection in the REP 401 study (NCT02565719) first received 24 weeks of tenofovir-disoproxil-fumarate (TDF) monotherapy. The early triple therapy group (n = 20) next received 48 weeks of TDF+pegylated interferon-α2a (pegIFN)+NAPs. In contrast, the delayed triple therapy group (n = 20) next received 24 weeks of TDF+pegIFN before 48 weeks of triple therapy. Three participants discontinued treatment and were excluded. Functional cure (HBsAg and HBV DNA not detectable with normal ALT) was assessed at 48 weeks post-treatment. Different kinetic phases were defined by at least a 2-fold change in slope. A single-phase decline was categorized as monophasic, and 2-phase declines were categorized as biphasic. RESULTS: Fourteen (35%) participants achieved a functional cure. HBV DNA remained below or near undetectable for all participants by the end of TDF monotherapy and during subsequent combination therapies. Three HBsAg kinetic patterns were found in both the early and delayed groups, nonresponders (n = 4 and n = 4), monophasic (n = 11 and n = 11), and biphasic (n = 4 and n = 3), respectively. All participants who achieved a functional cure had a monophasic HBsAg kinetic pattern during triple therapy. Among participants with a monophasic HBsAg decline, those who had a functional cure had a shorter median time to HBsAg loss of 21 (interquartile range=11) weeks compared with those who did not achieve functional cure [median: 27 (7) weeks] (p = 0.012). CONCLUSIONS: Functional cure was associated with a rapid monophasic HBsAg decline during NAP-based therapy. A nonmonophasic HBsAg kinetic pattern had a 100% negative predictive value (NPV) for a functional cure.

Hepatitis delta virus RNA decline post inoculation in human NTCP transgenic mice is biphasic.

Background and Aims: Chronic infection with hepatitis B and hepatitis delta viruses (HDV) is considered the most serious form of viral hepatitis due to more severe manifestations of and accelerated progression to liver fibrosis, cirrhosis, and hepatocellular carcinoma. There is no FDA-approved treatment for HDV and current interferon-alpha treatment is suboptimal. We characterized early HDV kinetics post inoculation and incorporated mathematical modeling to provide insights into host-HDV dynamics. Methods: We analyzed HDV RNA serum viremia in 192 immunocompetent (C57BL/6) and immunodeficient (NRG) mice that did or did not transgenically express the HDV receptor - human sodium taurocholate co-transporting peptide (hNTCP). Results: Kinetic analysis indicates an unanticipated biphasic decline consisting of a sharp first-phase and slower second-phase decline regardless of immunocompetence. HDV decline after re-inoculation again followed a biphasic decline; however, a steeper second-phase HDV decline was observed in NRG-hNTCP mice compared to NRG mice. HDV-entry inhibitor bulevirtide administration and HDV re-inoculation indicated that viral entry and receptor saturation are not major contributors to clearance, respectively. The biphasic kinetics can be mathematically modeled by assuming the existence of a non-specific binding compartment with a constant on/off-rate and the steeper second-phase decline by a loss of bound virus that cannot be returned as free virus to circulation. The model predicts that free HDV is cleared with a half-life of 18 minutes (standard error, SE: 2.4), binds to non-specific cells with a rate of 0.06 hour -1 (SE: 0.03), and returns as free virus with a rate of 0.23 hour -1 (SE: 0.03). Conclusions: Understanding early HDV-host kinetics will inform pre-clinical therapeutic kinetic studies on how the efficacy of anti-HDV therapeutics can be affected by early kinetics of viral decline. LAY SUMMARY: The persistence phase of HDV infection has been studied in some animal models, however, the early kinetics of HDV in vivo is incompletely understood. In this study, we characterize an unexpectedly HDV biphasic decline post inoculation in immunocompetent and immunodeficient mouse models and use mathematical modeling to provide insights into HDV-host dynamics. Understanding the kinetics of viral clearance in the blood can aid pre-clinical development and testing models for anti-HDV therapeutics.

Modeling hepatitis C virus kinetics during liver transplantation reveals the role of the liver in virus clearance.

While the liver, specifically hepatocytes, are widely accepted as the main source of hepatitis C virus (HCV) production, the role of the liver/hepatocytes in clearance of circulating HCV remains unknown. Frequent HCV kinetic data were recorded and mathematically modeled from five liver transplant patients throughout the anhepatic (absence of liver) phase and for 4 hr post-reperfusion. During the anhepatic phase, HCV remained at pre-anhepatic levels (n = 3) or declined (n = 2) with t1/2~1 hr. Immediately post-reperfusion, virus declined in a biphasic manner in four patients consisting of a rapid decline (t1/2 = 5 min) followed by a slower decline (t1/2 = 67 min). Consistent with the majority of patients in the anhepatic phase, when we monitored HCV clearance at 37°C from culture medium in the absence/presence of chronically infected hepatoma cells that were inhibited from secreting HCV, the HCV t1/2 in cell culture was longer in the absence of chronically HCV-infected cells. The results suggest that the liver plays a major role in the clearance of circulating HCV and that hepatocytes may be involved.

Efficient network immunization under limited knowledge.

Targeted immunization of centralized nodes in large-scale networks has attracted significant attention. However, in real-world scenarios, knowledge and observations of the network may be limited, thereby precluding a full assessment of the optimal nodes to immunize (or quarantine) in order to avoid epidemic spreading such as that of the current coronavirus disease (COVID-19) epidemic. Here, we study a novel immunization strategy where only n nodes are observed at a time and the most central among these n nodes is immunized. This process can globally immunize a network. We find that even for small n (≈10) there is significant improvement in the immunization (quarantine), which is very close to the levels of immunization with full knowledge. We develop an analytical framework for our method and determine the critical percolation threshold p c and the size of the giant component P ∞ for networks with arbitrary degree distributions P(k). In the limit of n → ∞ we recover prior work on targeted immunization, whereas for n = 1 we recover the known case of random immunization. Between these two extremes, we observe that, as n increases, p c increases quickly towards its optimal value under targeted immunization with complete information. In particular, we find a new general scaling relationship between |p c (∞) - p c (n)| and n as |p c (∞) - p c (n)| ∼ n -1exp(-αn). For scale-free (SF) networks, where P(k) ∼ k -γ, 2 < γ < 3, we find that p c has a transition from zero to nonzero when n increases from n = 1 to O(log N) (where N is the size of the network). Thus, for SF networks, having knowledge of ≈log N nodes and immunizing the most optimal among them can dramatically reduce epidemic spreading. We also demonstrate our limited knowledge immunization strategy on several real-world networks and confirm that in these real networks, p c increases significantly even for small n.

Optimal resilience of modular interacting networks.

Coupling between networks is widely prevalent in real systems and has dramatic effects on their resilience and functional properties. However, current theoretical models tend to assume homogeneous coupling where all the various subcomponents interact with one another, whereas real-world systems tend to have various different coupling patterns. We develop two frameworks to explore the resilience of such modular networks, including specific deterministic coupling patterns and coupling patterns where specific subnetworks are connected randomly. We find both analytically and numerically that the location of the percolation phase transition varies nonmonotonically with the fraction of interconnected nodes when the total number of interconnecting links remains fixed. Furthermore, there exists an optimal fraction [Formula: see text] of interconnected nodes where the system becomes optimally resilient and is able to withstand more damage. Our results suggest that, although the exact location of the optimal [Formula: see text] varies based on the coupling patterns, for all coupling patterns, there exists such an optimal point. Our findings provide a deeper understanding of network resilience and show how networks can be optimized based on their specific coupling patterns.

Multiple metastable network states in urban traffic.

While abrupt regime shifts between different metastable states have occurred in natural systems from many areas including ecology, biology, and climate, evidence for this phenomenon in transportation systems has been rarely observed so far. This limitation might be rooted in the fact that we lack methods to identify and analyze possible multiple states that could emerge at scales of the entire traffic network. Here, using percolation approaches, we observe such a metastable regime in traffic systems. In particular, we find multiple metastable network states, corresponding to varying levels of traffic performance, which recur over different days. Based on high-resolution global positioning system (GPS) datasets of urban traffic in the megacities of Beijing and Shanghai (each with over 50,000 road segments), we find evidence supporting the existence of tipping points separating three regimes: a global functional regime and a metastable hysteresis-like regime, followed by a global collapsed regime. We can determine the intrinsic critical points where the metastable hysteresis-like regime begins and ends and show that these critical points are very similar across different days. Our findings provide a better understanding of traffic resilience patterns and could be useful for designing early warning signals for traffic resilience management and, potentially, other complex systems.

Modelling hepatitis D virus RNA and HBsAg dynamics during nucleic acid polymer monotherapy suggest rapid turnover of HBsAg.

Hepatitis D virus (HDV) requires hepatitis B surface antigen (HBsAg) for its assembly and release. Current HBV treatments are only marginally effective against HDV because they fail to inhibit HBsAg production/secretion. However, monotherapy with the nucleic acid polymer REP 2139-Ca is accompanied by rapid declines in both HBsAg and HDV RNA. We used mathematical modeling to estimate HDV-HBsAg-host parameters and to elucidate the mode of action and efficacy of REP 2139-Ca against HDV in 12 treatment-naive HBV/HDV co-infected patients. The model accurately reproduced the observed decline of HBsAg and HDV, which was simultaneous. Median serum HBsAg half-life (t1/2) was estimated as 1.3 [0.9-1.8] days corresponding to a pretreatment production and clearance of ~108 [107.7-108.3] IU/day. The HDV-infected cell loss was estimated to be 0.052 [0.035-0.074] days-1 corresponding to an infected cell t1/2 = 13.3 days. The efficacy of blocking HBsAg and HDV production were 98.2 [94.5-99.9]% and 99.7 [96.0-99.8]%, respectively. In conclusion, both HBsAg production and HDV replication are effectively inhibited by REP 2139-Ca. Modeling HBsAg kinetics during REP 2139-Ca monotherapy indicates a short HBsAg half-life (1.3 days) suggesting a rapid turnover of HBsAg in HBV/HDV co-infection.

Interconnections between networks acting like an external field in a first-order percolation transition.

Many interdependent, real-world infrastructures involve interconnections between different communities or cities. Here we show how the effects of such interconnections can be described as an external field for interdependent networks experiencing a first-order percolation transition. We find that the critical exponents γ and δ, related to the external field, can also be defined for first-order transitions but that they have different values than those found for second-order transitions. Surprisingly, we find that both sets of different exponents (for first and second order) can even be found within a single model of interdependent networks, depending on the dependency coupling strength. Nevertheless, in both cases both sets satisfy Widom's identity, δ-1=γ/ß, which further supports the validity of their definitions. Furthermore, we find that both Erdos-Rényi and scale-free networks have the same values of the exponents in the first-order regime, implying that these models are in the same universality class. In addition, we find that in k-core percolation the values of the critical exponents related to the field are the same as for interdependent networks, suggesting that these systems also belong to the same universality class.

Modeling Challenges of Ebola Virus-Host Dynamics during Infection and Treatment.

Mathematical modeling of Ebola virus (EBOV)-host dynamics during infection and treatment in vivo is in its infancy due to few studies with frequent viral kinetic data, lack of approved antiviral therapies, and limited insight into the timing of EBOV infection of cells and tissues throughout the body. Current in-host mathematical models simplify EBOV infection by assuming a single homogeneous compartment of infection. In particular, a recent modeling study assumed the liver as the largest solid organ targeted by EBOV infection and predicted that nearly all cells become refractory to infection within seven days of initial infection without antiviral treatment. We compared our observations of EBOV kinetics in multiple anatomic compartments and hepatocellular injury in a critically ill patient with Ebola virus disease (EVD) with this model's predictions. We also explored the model's predictions, with and without antiviral therapy, by recapitulating the model using published inputs and assumptions. Our findings highlight the challenges of modeling EBOV-host dynamics and therapeutic efficacy and emphasize the need for iterative interdisciplinary efforts to refine mathematical models that might advance understanding of EVD pathogenesis and treatment.

Predictability of real temporal networks.

Links in most real networks often change over time. Such temporality of links encodes the ordering and causality of interactions between nodes and has a profound effect on network dynamics and function. Empirical evidence has shown that the temporal nature of links in many real-world networks is not random. Nonetheless, it is challenging to predict temporal link patterns while considering the entanglement between topological and temporal link patterns. Here, we propose an entropy-rate-based framework, based on combined topological-temporal regularities, for quantifying the predictability of any temporal network. We apply our framework on various model networks, demonstrating that it indeed captures the intrinsic topological-temporal regularities whereas previous methods considered only temporal aspects. We also apply our framework on 18 real networks of different types and determine their predictability. Interestingly, we find that, for most real temporal networks, despite the greater complexity of predictability brought by the increase in dimension, the combined topological-temporal predictability is higher than the temporal predictability. Our results demonstrate the necessity for incorporating both temporal and topological aspects of networks in order to improve predictions of dynamical processes.

Possible origin of memory in earthquakes: Real catalogs and an epidemic-type aftershock sequence model.

Earthquakes are one of the most devastating natural disasters that plague society. Skilled, reliable earthquake forecasting remains the ultimate goal for seismologists. Using the detrended fluctuation analysis (DFA) and conditional probability (CP) methods, we find that memory exists not only in interoccurrence seismic records but also in released energy as well as in the series of the number of events per unit time. Analysis of a standard epidemic-type aftershock sequences (ETAS) earthquake model indicates that the empirically observed earthquake memory can be reproduced only for a narrow range of the model's parameters. This finding therefore provides tight constraints on the model's parameters and can serve as a testbed for existing earthquake forecasting models. Furthermore, we show that by implementing DFA and CP results, the ETAS model can significantly improve the short-term forecasting rate for the real (Italian) earthquake catalog.

Correction: Modeling suggests that microliter volumes of contaminated blood caused an outbreak of hepatitis C during computerized tomography.

[This corrects the article DOI: 10.1371/journal.pone.0210173.].

Modeling suggests that microliter volumes of contaminated blood caused an outbreak of hepatitis C during computerized tomography.

BACKGROUND & AIMS: Acute hepatitis C (AHC) is not frequently identified because patients are usually asymptomatic, although may be recognized after iatrogenic exposures such as needle stick injuries, medical injection, and acupuncture. We describe an outbreak of AHC among 12 patients who received IV saline flush from a single multi-dose vial after intravenous contrast administration for a computerized tomography (CT) scan. The last patient to receive IV contrast with saline flush from a multi-dose vial at the clinic on the previous day was known to have chronic HCV genotype 1b (termed potential source, PS). Here we sought to confirm (via genetic analysis) the source of infection and to predict the minimal contaminating level of IV saline flush needed to transmit infectious virus to all patients. METHODS: In order to confirm the source of infection, we sequenced the HCV E1E2 region in 7 CT patients, in PS, and in 2 control samples from unrelated patients also infected with HCV genotype 1b. A transmission probabilistic model was developed to predict the contamination volume of blood that would have been sufficient to transmit infectious virus to all patients. RESULTS: Viral sequencing showed close clustering of the cases with the PS. The transmission probabilistic model predicted that contamination of the multi-dose saline vial with 0.6-8.7 microliters of blood would have been sufficient to transmit infectious virus to all patients. CONCLUSION: Analysis of this unique cohort provides a new understanding of HCV transmission with respect to contaminating volumes and viral titers.

Modeling of patient virus titers suggests that availability of a vaccine could reduce hepatitis C virus transmission among injecting drug users.

The major route of hepatitis C virus (HCV) transmission in the United States is injection drug use. We hypothesized that if an HCV vaccine were available, vaccination could affect HCV transmission among people who inject drugs by reducing HCV titers after viral exposure without necessarily achieving sterilizing immunity. To investigate this possibility, we developed a mathematical model to determine transmission probabilities relative to the HCV RNA titers of needle/syringe-sharing donors. We simulated sharing of two types of syringes fitted with needles that retain either large or small amounts of fluid after expulsion. Using previously published viral kinetics data from both naïve subjects infected with HCV and reinfected individuals who had previously cleared an HCV infection, we estimated transmission risk between pairs of serodiscordant injecting drug users, accounting for syringe type, rinsing, and sharing frequency. We calculated that the risk of HCV transmission through syringe sharing increased ~10-fold as viral titers (log10 IU/ml) increased ~25-fold. Cumulative analyses showed that, assuming sharing episodes every 7 days, the mean transmission risk over the first 6 months was >90% between two people sharing syringes when one had an HCV RNA titer >5 log10 IU/ml. For those with preexisting immunity that rapidly controlled HCV, the cumulative risk decreased to 1 to 25% depending on HCV titer and syringe type. Our modeling approach demonstrates that, even with transient viral replication after exposure during injection drug use, HCV transmission among people sharing syringes could be reduced through vaccination if an HCV vaccine were available.