A patient safety knowledge graph supporting vaccine product development.

BACKGROUND: Knowledge graphs are well-suited for modeling complex, unstructured, and multi-source data and facilitating their analysis. During the COVID-19 pandemic, adverse event data were integrated into a knowledge graph to support vaccine safety surveillance and nimbly respond to urgent health authority questions. Here, we provide details of this post-marketing safety system using public data sources. In addition to challenges with varied data representations, adverse event reporting on the COVID-19 vaccines generated an unprecedented volume of data; an order of magnitude larger than adverse events for all previous vaccines. The Patient Safety Knowledge Graph (PSKG) is a robust data store to accommodate the volume of adverse event data and harmonize primary surveillance data sources. METHODS: We designed a semantic model to represent key safety concepts. We built an extract-transform-load (ETL) data pipeline to parse and import primary public data sources; align key elements such as vaccine names; integrated the Medical Dictionary for Regulatory Activities (MedDRA); and applied quality metrics. PSKG is deployed in a Neo4J graph database, and made available via a web interface and Application Programming Interfaces (APIs). RESULTS: We import and align adverse event data and vaccine exposure data from 250 countries on a weekly basis, producing a graph with 4,340,980 nodes and 30,544,475 edges as of July 1, 2022. PSKG is used for ad-hoc analyses and periodic reporting for several widely available COVID-19 vaccines. Analysis code using the knowledge graph is 80% shorter than an equivalent implementation written entirely in Python, and runs over 200 times faster. CONCLUSIONS: Organizing safety data into a concise model of nodes, properties, and edge relationships has greatly simplified analysis code by removing complex parsing and transformation algorithms from individual analyses and instead managing these centrally. The adoption of the knowledge graph transformed how the team answers key scientific and medical questions. Whereas previously an analysis would involve aggregating and transforming primary datasets from scratch to answer a specific question, the team can now iterate easily and respond as quickly as requests evolve (e.g., "Produce vaccine-X safety profile for adverse event-Y by country instead of age-range").

Alpha-Lipoic acid alleviates imidacloprid-induced neuro-behavioral deficits in rats via Nrf2/HO-1 pathway.

Imidacloprid (IMI), a widely used pesticide in agriculture and a potential food contaminant, poses significant health concerns. This study sought to comprehensively evaluate its neurotoxic effects while investigating the potential protective role of alpha-lipoic acid (ALA), a naturally occurring dietary antioxidant renowned for its capacity to combat oxidative stress, support cardiovascular health, and maintain optimal nerve function. In this study, 28 rats were divided evenly into four groups and administered oral treatments of corn oil, IMI, IMI + ALA, and ALA, respectively. The results of the study indicated that rats exposed to IMI exhibited significant neurobehavioral impairments, decreased levels of antioxidant enzymes and acetylcholinesterase activity, reduced expression of HO-1 and Nrf2, and increased levels of pro-inflammatory cytokines like IL-6 and TNF-α in their hippocampal tissues. Furthermore, histopathological analysis of the brain tissues, specifically cortex and hippocampus, from the IMI-treated group revealed varying degrees of neuronal degeneration. In contrast, rats co-administered ALA alongside IMI showed noticeable improvements in all the assessed toxicological parameters. This study underscores the vital significance of ALA as a potential therapeutic adjunct in mitigating the adverse neurobehavioral consequences of insecticide exposure. By harnessing the Nrf2/HO-1 pathway, ALA demonstrates its ability to shield against IMI-induced neurotoxicity, offering a promising avenue for enhancing public health and safety. As a result, our findings advocate for the incorporation of ALA as a daily dietary supplement to fortify resilience against oxidative stress-related neurobehavioral deficits linked to pesticide exposure, thereby advancing our understanding of neuroprotection strategies in the face of environmental challenges.

Probing the Dark Sector with Nuclear Transition Photons.

Here we present world-leading sensitivity to light (<170 MeV) dark matter (DM) using beam-dump experiments. Dark sector particles produced during pion decay at accelerator beam dumps can be detected via scattering in neutrino detectors. The decay of nuclei excited by the inelastic scattering of DM is an unexploited channel which has significantly better sensitivity than similar searches using the elastic scattering channel. We show that this channel is a powerful probe of DM by demonstrating sensitivity to the thermal relic abundance benchmark in a scalar DM dark-photon portal model. This is achieved through the use of existing data, obtained by the KARMEN experiment over two decades ago, which allow us to set world-leading constraints on this model over a wide mass range. With experimental improvements planned for the future, this technique will be able to probe the thermal relic benchmark for fermionic DM across a wide mass range.

Oxymatrine and insulin resistance: Focusing on mechanistic intricacies involve in diabetes associated cardiomyopathy via SIRT1/AMPK and TGF-ß signaling pathway.

Cardiomyopathy (CDM) and related morbidity and mortality are increasing at an alarming rate, in large part because of the increase in the number of diabetes mellitus cases. The clinical consequence associated with CDM is heart failure (HF) and is considerably worse for patients with diabetes mellitus, as compared to nondiabetics. Diabetic cardiomyopathy (DCM) is characterized by structural and functional malfunctioning of the heart, which includes diastolic dysfunction followed by systolic dysfunction, myocyte hypertrophy, cardiac dysfunctional remodeling, and myocardial fibrosis. Indeed, many reports in the literature indicate that various signaling pathways, such as the AMP-activated protein kinase (AMPK), silent information regulator 1 (SIRT1), PI3K/Akt, and TGF-ß/smad pathways, are involved in diabetes-related cardiomyopathy, which increases the risk of functional and structural abnormalities of the heart. Therefore, targeting these pathways augments the prevention as well as treatment of patients with DCM. Alternative pharmacotherapy, such as that using natural compounds, has been shown to have promising therapeutic effects. Thus, this article reviews the potential role of the quinazoline alkaloid, oxymatrine obtained from the Sophora flavescensin CDM associated with diabetes mellitus. Numerous studies have given a therapeutic glimpse of the role of oxymatrine in the multiple secondary complications related to diabetes, such as retinopathy, nephropathy, stroke, and cardiovascular complications via reductions in oxidative stress, inflammation, and metabolic dysregulation, which might be due to targeting signaling pathways, such as AMPK, SIRT1, PI3K/Akt, and TGF-ß pathways. Thus, these pathways are considered central regulators of diabetes and its secondary complications, and targeting these pathways with oxymatrine might provide a therapeutic tool for the diagnosis and treatment of diabetes-associated cardiomyopathy.

Solutions to the MiniBooNE Anomaly from New Physics in Charged Meson Decays.

We point out that production of new bosons by charged meson decays can greatly enhance the sensitivity of beam-focused accelerator-based experiments to new physics signals. This enhancement arises since the charged mesons are focused and their three-body decays do not suffer from helicity suppression in the same way as their usual two-body decays. As a realistic application, we attempt to explain the MiniBooNE low energy excess utilizing this overlooked mechanism, uniquely realizing dark-sector interpretations as plausible solutions to the excess. As proof of the principle, we consider two well-motivated classes of dark-sector models, models of vector-portal dark matter and models of long-lived (pseudo)scalar. We argue that the model parameter values to accommodate the excess are consistent with existing limits and that they can be tested at current and future accelerator-based neutrino experiments.

Inside the diabetic brain: Insulin resistance and molecular mechanism associated with cognitive impairment and its possible therapeutic strategies.

Type 2 diabetes mellitus (T2DM) the most prevalent metabolic disease that has evolved into a major public health issue. Concerning about its secondary complications, a growing body of evidence links T2DM to cognitive impairment and neurodegenerative disorders. The underlying pathology behind this secondary complication disease is yet to be fully known. Nonetheless, they are likely to be associated with poor insulin signaling as a result of insulin resistance. We have combed through a rising body of literature on insulin signaling in the normal and diabetic brains along with various factors like insulin resistance, hyperglycemia, obesity, oxidative stress, neuroinflammation and Aß plaques which can act independently or synergistically to link T2DM with cognitive impairments. Finally, we explored several pharmacological and non-pharmacological methods in the hopes of accelerating the rational development of medications for cognitive impairment in T2DM by better understanding these shared pathways.

Similarity and consistency assessment of three major online drug-drug interaction resources.

AIMS: The aim of this study was to explore the level of agreement on drug-drug interaction (DDI) information listed in three major online drug information resources (DIRs) in terms of: (1) interacting drug pairs; (2) severity rating; (3) evidence rating; and (4) clinical management recommendations. METHODS: We extracted information from the British National Formulary (BNF), Thesaurus and Micromedex. Following drug name normalisation, we estimated the overlap of the DIRs in terms of DDI. We annotated clinical management recommendations either manually, where possible, or through application of a machine learning algorithm. RESULTS: The DIRs contained 51 481 (BNF), 38 037 (Thesaurus) and 65 446 (Micromedex) drug pairs involved in DDIs. The number of common DDIs across the three DIRs was 6970 (13.54% of BNF, 18.32% of Thesaurus and 10.65% of Micromedex). Micromedex and Thesaurus overall showed higher levels of similarity in their severity ratings, while the BNF agreed more with Micromedex on the critical severity ratings and with Thesaurus on the least significant ones. Evidence rating agreement between BNF and Micromedex was generally poor. Variation in clinical management recommendations was also identified, with some categories (i.e., Monitor and Adjust dose) showing higher levels of agreement compared to others (i.e., Use with caution, Wash-out, Modify administration). CONCLUSIONS: There is considerable variation in the DDIs included in the examined DIRs, together with variability in categorisation of severity and clinical advice given. DDIs labelled as critical were more likely to appear in multiple DIRs. Such variability in information could have deleterious consequences for patient safety, and there is a need for harmonisation and standardisation.

Axionlike Particles at Future Neutrino Experiments: Closing the Cosmological Triangle.

Axionlike particles (ALPs) provide a promising direction in the search for new physics, while a wide range of models incorporate ALPs. We point out that future neutrino experiments, such as DUNE, possess competitive sensitivity to ALP signals. The high-intensity proton beam impinging on a target can not only produce copious amounts of neutrinos, but also cascade photons that are created from charged particle showers stopping in the target. Therefore, ALPs interacting with photons can be produced (often energetically) with high intensity via the Primakoff effect and then leave their signatures at the near detector through the inverse Primakoff scattering or decays to a photon pair. Moreover, the high-capability near detectors allow for discrimination between ALP signals and potential backgrounds, improving the signal sensitivity further. We demonstrate that a DUNE-like detector can explore a wide range of parameter space in ALP-photon coupling g_{aγ} vs ALP mass m_{a}, including some regions unconstrained by existing bounds; the "cosmological triangle" will be fully explored and the sensitivity limits would reach up to m_{a}∼3-4 GeV and down to g_{aγ}∼10^{-8} GeV^{-1}.

Inverse Primakoff Scattering as a Probe of Solar Axions at Liquid Xenon Direct Detection Experiments.

We show that XENON1T and future liquid xenon (LXe) direct detection experiments are sensitive to axions through the standard g_{aγ}aFF[over ˜] operators due to inverse-Primakoff scattering. This previously neglected channel significantly improves the sensitivity to the axion-photon coupling, with a reach extending to g_{aγ}∼10^{-10} GeV^{-1} for axion masses up to a keV, thereby extending into the region of heavier QCD axion models. This result modifies the couplings required to explain the XENON1T excess in terms of solar axions, opening a large region of g_{aγ}-m_{a} parameter space that is not ruled out by the CAST helioscope experiment and reducing the tension with the astrophysical constraints. We explore the sensitivity to solar axions for future generations of LXe detectors that can exceed future helioscope experiments, such as IAXO, for a large region of parameter space.

Explaining the XENON1T Excess with Luminous Dark Matter.

We show that the excess in electron recoil events seen by the XENON1T experiment can be explained by a relatively low-mass luminous dark matter candidate. The dark matter scatters inelastically in the detector (or the surrounding rock) to produce a heavier dark state with a ∼2-3 keV mass splitting. This heavier state then decays within the detector, producing a peak in the electron recoil spectrum that is a good fit to the observed excess. We comment on the ability of future direct detection experiments to differentiate this model from other "beyond the standard model" scenarios and from possible tritium backgrounds, including the use of diurnal modulation, multichannel signals, etc., as possible distinguishing features of this scenario.

Dark Matter Signals from Timing Spectra at Neutrino Experiments.

We propose a novel strategy to search for new physics in timing spectra at low-energy neutrino experiments using a pulsed beam, envisioning the situation in which a new particle comes from the decay of its heavier partner with a finite particle width. The timing distribution of events induced by the dark matter (DM) candidate particle scattering at the detector may populate in a relatively narrow range, forming a "resonancelike" shape. Because of this structural feature, the signal may be isolated from the backgrounds, in particular when the backgrounds are uniformly distributed in energy and time. For proof of the principle, we investigate the discovery potential for DM from the decay of a dark photon in the ongoing COHERENT experiment and show the exciting prospects for exploring the associated parameter space with this experiment. We analyze the existing CsI detector data with a timing cut and an energy cut, and we find, for the first time, an excess in the timing distribution that can be explained by such DM. We compare the sensitivity to the kinetic mixing parameter (ε) for current and future COHERENT experiments with the projected limits from LDMX and DUNE.

New Directions for Axion Searches via Scattering at Reactor Neutrino Experiments.

Searches for pseudoscalar axionlike-particles (ALPs) typically rely on their decay in beam dumps or their conversion into photons in haloscopes and helioscopes. We point out a new experimental direction for ALP probes via their production by the intense gamma ray flux available from megawatt-scale nuclear reactors at neutrino experiments through Primakoff-like or Compton-like channels. Low-threshold detectors in close proximity to the core will have visibility to ALP decays and inverse Primakoff and Compton scattering, providing sensitivity to the ALP-photon and ALP-electron couplings. We find that the sensitivity to these couplings at the ongoing MINER and various other reactor based neutrino experiments, e.g., CONNIE, CONUS, ν-cleus, etc., exceeds existing limits set by laboratory experiments and, for the ALP-electron coupling, we forecast the world's best laboratory-based constraints over a large portion of the sub-MeV ALP mass range.

Dual Roles for Ikaros in Regulation of Macrophage Chromatin State and Inflammatory Gene Expression.

Macrophage activation by bacterial LPS leads to induction of a complex inflammatory gene program dependent on numerous transcription factor families. The transcription factor Ikaros has been shown to play a critical role in lymphoid cell development and differentiation; however, its function in myeloid cells and innate immune responses is less appreciated. Using comprehensive genomic analysis of Ikaros-dependent transcription, DNA binding, and chromatin accessibility, we describe unexpected dual repressor and activator functions for Ikaros in the LPS response of murine macrophages. Consistent with the described function of Ikaros as transcriptional repressor, Ikzf1-/- macrophages showed enhanced induction for select responses. In contrast, we observed a dramatic defect in expression of many delayed LPS response genes, and chromatin immunoprecipitation sequencing analyses support a key role for Ikaros in sustained NF-κB chromatin binding. Decreased Ikaros expression in Ikzf1+/- mice and human cells dampens these Ikaros-enhanced inflammatory responses, highlighting the importance of quantitative control of Ikaros protein level for its activator function. In the absence of Ikaros, a constitutively open chromatin state was coincident with dysregulation of LPS-induced chromatin remodeling, gene expression, and cytokine responses. Together, our data suggest a central role for Ikaros in coordinating the complex macrophage transcriptional program in response to pathogen challenge.

Searching for Beyond the Standard Model Physics with COHERENT Energy and Timing Data.

We search for beyond the standard model physics by combining COHERENT Collaboration energy and timing data. Focusing on light, ≲GeV mediators, we find the data favor a ∼10-1000 MeV mediator, as compared to the standard model best fit at the ≲2σ level. The best-fit coupling range is g∼10^{-5}-10^{-3}. The timing data provide statistical information on the neutrino flavor distributions that is not attainable from the nuclear recoil energies alone. This result accounts for uncertainty in the effective size of the neutron distribution, and highlights the power of including uncertainties on experimental backgrounds, nuclear structure, and beyond the standard model physics.

Proteome and Secretome Analysis Reveals Differential Post-transcriptional Regulation of Toll-like Receptor Responses.

The innate immune system is the organism's first line of defense against pathogens. Pattern recognition receptors (PRRs) are responsible for sensing the presence of pathogen-associated molecules. The prototypic PRRs, the membrane-bound receptors of the Toll-like receptor (TLR) family, recognize pathogen-associated molecular patterns (PAMPs) and initiate an innate immune response through signaling pathways that depend on the adaptor molecules MyD88 and TRIF. Deciphering the differences in the complex signaling events that lead to pathogen recognition and initiation of the correct response remains challenging. Here we report the discovery of temporal changes in the protein signaling components involved in innate immunity. Using an integrated strategy combining unbiased proteomics, transcriptomics and macrophage stimulations with three different PAMPs, we identified differences in signaling between individual TLRs and revealed specifics of pathway regulation at the protein level.

A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.

The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI.

Unveiling the interplay of AMPK/SIRT1/PGC-1α axis in brain health: Promising targets against aging and NDDs.

The escalating prevalence of neurodegenerative diseases (NDDs) within an aging global population presents a pressing challenge. The multifaceted pathophysiological mechanisms underlying these disorders, including oxidative stress, mitochondrial dysfunction, and neuroinflammation, remain complex and elusive. Among these, the AMPK/SIRT1/PGC-1α pathway emerges as a pivotal network implicated in neuroprotection against these destructive processes. This review sheds light on the potential therapeutic implications of targeting this axis, specifically emphasizing the promising role of flavonoids in mitigating NDD-related complications. Expanding beyond conventional pharmacological approaches, the exploration of non-pharmacological interventions such as exercise and calorie restriction (CR), coupled with the investigation of natural compounds, offers a beacon of hope. By strategically elucidating the intricate connections within these pathways, this review aims to pave the ways for novel multi-target agents and interventions, fostering a renewed optimism in the quest to combat and manage the debilitating impacts of NDDs on global health and well-being.

iPREDICT: proof-of-concept study to develop a predictive model of changes in asthma control.

BACKGROUND: The individualized PREdiction of DIsease Control using digital sensor Technology (iPREDICT) program was developed for asthma management using digital technology. Devices were integrated into daily lives of patients to establish a predictive model of asthma control by measuring changes from baseline health status with minimal device burden. OBJECTIVES: To establish baseline disease characteristics of the study participants, detect changes from baseline associated with asthma events, and evaluate algorithms capable of identifying triggers and predicting asthma control changes from baseline data. Patient experience and compliance with the devices were also explored. DESIGN: This was a multicenter, observational, 24-week, proof-of-concept study conducted in the United States. METHODS: Patients (⩾12 years) with severe, uncontrolled asthma engaged with a spirometer, vital sign monitor, sleep monitor, connected inhaler devices, and two mobile applications with embedded patient-reported outcome (PRO) questionnaires. Prospective data were linked to data from electronic health records and transmitted to a secure platform to develop predictive algorithms. The primary endpoint was an asthma event: symptom worsening logged by patients (PRO); peak expiratory flow (PEF) < 65% or forced expiratory volume in 1 s < 80%; increased short-acting ß2-agonist (SABA) use (>8 puffs/24 h or >4 puffs/day/48 h). For each endpoint, predictive models were constructed at population, subgroup, and individual levels. RESULTS: Overall, 108 patients were selected: 66 (61.1%) completed and 42 (38.9%) were excluded for failure to respond/missing data. Predictive accuracy depended on endpoint selection. Population-level models achieved low accuracy in predicting endpoints such as PEF < 65%. Subgroups related to specific allergies, asthma triggers, asthma types, and exacerbation treatments demonstrated high accuracy, with the most accurate, predictive endpoint being >4 SABA puffs/day/48 h. Individual models, constructed for patients with high endpoint overlap, exhibited significant predictive accuracy, especially for PEF < 65% and >4 SABA puffs/day/48 h. CONCLUSION: This multidimensional dataset enabled population-, subgroup-, and individual-level analyses, providing proof-of-concept evidence for development of predictive models of fluctuating asthma control.

iPREDICT: Characterization of Asthma Triggers and Selection of Digital Technology to Predict Changes in Disease Control.

Purpose: The iPREDICT program aimed to develop an integrated digital health solution capable of continuous data streaming, predicting changes in asthma control, and enabling early intervention. Patients and Methods: As part of the iPREDICT program, asthma triggers were characterized by surveying 221 patients (aged ≥18 years) with self-reported asthma for a risk-benefit analysis of parameters predictive of changes in disease control. Seventeen healthy volunteers (age 25-65 years) tested 13 devices to measure these parameters and assessed their usability attributes. Results: Patients identified irritants such as chemicals, allergens, weather changes, and physical activity as triggers that were the most relevant to deteriorating asthma control. Device testing in healthy volunteers revealed variable data formats/units and quality issues, such as missing data and low signal-to-noise ratio. Based on user preference and data capture validity, a spirometer, vital sign monitor, and sleep monitor formed the iPREDICT integrated system for continuous data streaming to develop a personalized/predictive algorithm for asthma control. Conclusion: These findings emphasize the need to systematically compare devices based on several parameters, including usability and data quality, to develop integrated digital technology programs for asthma care.

Supersymmetric model for dark matter and baryogenesis motivated by the recent CDMS result.

We discuss a supersymmetric model for cogenesis of dark and baryonic matter where the dark matter (DM) has mass in the 8-10 GeV range as indicated by several direct detection searches, including most recently the CDMS experiment with the desired cross section. The DM candidate is a real scalar field. Two key distinguishing features of the model are the following: (i) in contrast with the conventional weakly interacting massive particle dark matter scenarios where thermal freeze-out is responsible for the observed relic density, our model uses nonthermal production of dark matter after reheating of the Universe caused by moduli decay at temperatures below the QCD phase transition, a feature which alleviates the relic overabundance problem caused by small annihilation cross section of light DM particles and (ii) baryogenesis occurs also at similar low temperatures from the decay of TeV scale mediator particles arising from moduli decay. A possible test of this model is the existence of colored particles with TeV masses accessible at the LHC.