Immunosuppression and Viral Infections

Immunosuppression is commonly used for prevention of graft rejection in solid organ transplantation (SOT) and prevention of graft versus host disease in hematopoietic allogeneic stem cell transplant (ASCT). In ASCT, immunosuppression is used to control GVHD and can be tapered off within 6–12 months after transplantation. SOT recipients require lifelong immunosuppression to prevent graft rejection, making them susceptible to serious viral infections including EBV PTLD. EBV PTLD occurs within the first 6 months following ASCT prior to effective reconstitution of cytotoxic T lymphocytes (CTL). Our understanding on EBV-related PTLD is mostly extrapolated from SOT-associated PTLD. Features of conditioning and use of serotherapy remain important in development of EBV PTLD. Other viral infections that occur early post-transplant include CMV, HHV6, BK, and adenovirus, and usually correspond to degree of immunosuppression post-transplant. These infections are associated with significant morbidity and mortality. However, the current literature lacks information on outcomes of viral infections related to immunosuppression. Alternative donor ASCT are now more common, and patients are more susceptible to multiple viral infectious complications at the peak of immunosuppression and require monitoring for viral infections in these immunosuppressed patients

Clinical and Pathological Review of Post Transplant Lymphoproliferative Disorders

Posttransplant lymphoproliferative disorder (PTLD) is a rare but potentially serious complication following transplantation with an overall incidence of PTLD of 1–5% in solid organ transplant (SOT) recipients and 1% in hematopoietic stem cell transplant (HSCT) recipients. The clinical and pathological spectrum of PTLD is broad; however, most cases of PTLD occur within the first year after transplantation and are associated with EBV. Clinical features that independently predict rates of response and survival have not been systematically studied for PTLD. Patients whose PTLD expressed CD20 or EBV have shorter intervals to PTLD onset, whereas late-onset cases of PTLD are typically EBV negative. Phenotypic characterization of PTLD reveals potential reliance on EBV or NF-kappaB signaling instead of B-cell receptor signaling, which links PTLD to other subgroups of EBV-related lymphomas, highlighting new potential treatment approaches. PTLD can be a life-threatening post-HSCT complication due to the impact of the patient’s underlying disease (malignant or nonmalignant) as well as the type and intensity of the conditioning regimen. EBV-negative PTLD is more often a delayed phenomenon post-HSCT compared to EBV-positive PTLD. Further investigations are needed to better understand the role of EBV in the pathogenesis of different forms of PTLD in the immunosuppressed patients

Composite Scores for Transplant Center Evaluation: A New Individualized Empirical Null Method

Risk-adjusted quality measures are used to evaluate healthcare providers while controlling for factors beyond their control. Existing healthcare provider profiling approaches typically assume that the risk adjustment is perfect and the between-provider variation in quality measures is entirely due to the quality of care. However, in practice, even with very good models for risk adjustment, some between-provider variation will be due to incomplete risk adjustment, which should be recognized in assessing and monitoring providers. Otherwise, conventional methods disproportionately identify larger providers as outliers, even though their provider effects need not be "extreme.'' Motivated by efforts to evaluate the quality of care provided by transplant centers, we develop a composite evaluation score based on a novel individualized empirical null method, which robustly accounts for overdispersion due to unobserved risk factors, models the marginal variance of standardized scores as a function of the effective center size, and only requires the use of publicly-available center-level statistics. The evaluations of United States kidney transplant centers based on the proposed composite score are substantially different from those based on conventional methods. Simulations show that the proposed empirical null approach more accurately classifies centers in terms of quality of care, compared to existing methods

Searching for Dark Matter with a Superconducting Qubit

Detection mechanisms for low mass bosonic dark matter candidates, such the axion or hidden photon, leverage potential interactions with electromagnetic fields, whereby the dark matter (of unknown mass) on rare occasion converts into a single photon. Current dark matter searches operating at microwave frequencies use a resonant cavity to coherently accumulate the field sourced by the dark matter and a near standard quantum limited (SQL) linear amplifier to read out the cavity signal. To further increase sensitivity to the dark matter signal, sub-SQL detection techniques are required. Here we report the development of a novel microwave photon counting technique and a new exclusion limit on hidden photon dark matter. We operate a superconducting qubit to make repeated quantum non-demolition measurements of cavity photons and apply a hidden Markov model analysis to reduce the noise to 15.7 dB below the quantum limit, with overall detector performance limited by a residual background of real photons. With the present device, we perform a hidden photon search and constrain the kinetic mixing angle to $\epsilon \leq 1.68 \times 10^{-15}$ in a band around 6.011 GHz (24.86 $\mu$eV) with an integration time of 8.33 s. This demonstrated noise reduction technique enables future dark matter searches to be sped up by a factor of 1300. By coupling a qubit to an arbitrary quantum sensor, more general sub-SQL metrology is possible with the techniques presented in this work.Comment: 15 pages, 14 figures, 2 table. Dark matter exclusion analysis modified to include experimental systematics. Discussion of background calibration and detector compatibility with tunable cavity added to conclusion. Future optimizations and integration into axion search sections moved to Supplemental Material. References update

Hypoxia and HIF-1α promote lytic de novo KSHV infection

The impact of different stress conditions on the oncogenic Kaposi's sarcoma-associated herpesvirus (KSHV) primary infection that can occur in vivo remains largely unknown. We hypothesized that KSHV can establish a latency or lytic cycle following de novo infection, depending on the conditions of the cellular environment. Previous studies showed that hypoxia is a natural stress condition that promotes lytic reactivation and contributes to KSHV pathogenesis, but its effect on de novo KSHV infection is unknown. To test the effect of hypoxia on KSHV infection, we infected cells under normoxia and hypoxia, performed a comparative analysis of viral gene expression and viral replication, and tested chromatinization of the KSHV genome during infection. We found that hypoxia induces viral lytic gene expression and viral replication following de novo infection in several biologically relevant cell types, in which the virus normally establishes latency under normoxia. We also found that hypoxia reduces the level of repressive heterochromatin and promotes the formation of a transcriptionally permissive chromatin on the incoming viral DNA during infection. We demonstrate that silencing hypoxia-inducible factor-1 alpha (HIF-1 alpha) during hypoxia abrogates lytic KSHV infection, while the overexpression of HIF-1 alpha under normoxia is sufficient to drive lytic KSHV infection. Also, we determined that the DNA-binding domain and the N-terminal but not the C-terminal transactivation domain of HIF-1 alpha are required for HIF-1 alpha-induced lytic gene expression. Altogether, our data indicate that HIF-1 alpha accumulation, which can be induced by hypoxia, prevents the establishment of latency and promotes lytic KSHV infection following primary infection

Applying Large Language Models for Causal Structure Learning in Non Small Cell Lung Cancer

Causal discovery is becoming a key part in medical AI research. These methods can enhance healthcare by identifying causal links between biomarkers, demographics, treatments and outcomes. They can aid medical professionals in choosing more impactful treatments and strategies. In parallel, Large Language Models (LLMs) have shown great potential in identifying patterns and generating insights from text data. In this paper we investigate applying LLMs to the problem of determining the directionality of edges in causal discovery. Specifically, we test our approach on a deidentified set of Non Small Cell Lung Cancer(NSCLC) patients that have both electronic health record and genomic panel data. Graphs are validated using Bayesian Dirichlet estimators using tabular data. Our result shows that LLMs can accurately predict the directionality of edges in causal graphs, outperforming existing state-of-the-art methods. These findings suggests that LLMs can play a significant role in advancing causal discovery and help us better understand complex systems

Multimode photon blockade

Interactions are essential for the creation of correlated quantum many-body states. While two-body interactions underlie most natural phenomena, three- and four-body interactions are important for the physics of nuclei [1], exotic few-body states in ultracold quantum gases [2], the fractional quantum Hall effect [3], quantum error correction [4], and holography [5, 6]. Recently, a number of artificial quantum systems have emerged as simulators for many-body physics, featuring the ability to engineer strong interactions. However, the interactions in these systems have largely been limited to the two-body paradigm, and require building up multi-body interactions by combining two-body forces. Here, we demonstrate a pure N-body interaction between microwave photons stored in an arbitrary number of electromagnetic modes of a multimode cavity. The system is dressed such that there is collectively no interaction until a target total photon number is reached across multiple distinct modes, at which point they interact strongly. The microwave cavity features 9 modes with photon lifetimes of $\sim 2$ ms coupled to a superconducting transmon circuit, forming a multimode circuit QED system with single photon cooperativities of $\sim10^9$. We generate multimode interactions by using cavity photon number resolved drives on the transmon circuit to blockade any multiphoton state with a chosen total photon number distributed across the target modes. We harness the interaction for state preparation, preparing Fock states of increasing photon number via quantum optimal control pulses acting only on the cavity modes. We demonstrate multimode interactions by generating entanglement purely with uniform cavity drives and multimode photon blockade, and characterize the resulting two- and three-mode W states using a new protocol for multimode Wigner tomography.Comment: 5 pages of main text with 5 figures. 11 pages of supplementary information with 10 figure

Nanowired three-dimensional cardiac patches

Engineered cardiac patches for treating damaged heart tissues after a heart attack are normally produced by seeding heart cells within three-dimensional porous biomaterial scaffolds1, 2, 3. These biomaterials, which are usually made of either biological polymers such as alginate4 or synthetic polymers such as poly(lactic acid) (PLA)5, help cells organize into functioning tissues, but poor conductivity of these materials limits the ability of the patch to contract strongly as a unit6. Here, we show that incorporating gold nanowires within alginate scaffolds can bridge the electrically resistant pore walls of alginate and improve electrical communication between adjacent cardiac cells. Tissues grown on these composite matrices were thicker and better aligned than those grown on pristine alginate and when electrically stimulated, the cells in these tissues contracted synchronously. Furthermore, higher levels of the proteins involved in muscle contraction and electrical coupling are detected in the composite matrices. It is expected that the integration of conducting nanowires within three-dimensional scaffolds may improve the therapeutic value of current cardiac patches.National Institutes of Health (U.S.) (NIH, grant GM073626)National Institutes of Health (U.S.) (NIH, grant DE13023)National Institutes of Health (U.S.) (NIH, grant DE016516)American Heart Association (Postdoctoral Fellowship)National Institutes of Health (U.S.) (Ruth L. Kirschstein National Research Service Award (no. F32GM096546)

A Design Space Exploration of Creative Concepts for Care Robots: Questioning the Differentiation of Social and Physical Assistance

In an interdisciplinary project, creative concepts for care robotics were developed. To explore the design space that these open up, we discussed them along the common differentiation of physical (effective) and social-emotional assistance. Trying to rate concepts on these dimensions frequently raised questions regarding the relation between the social-emotional and the physical, and highlighted gaps and a lack of conceptual clarity. We here present our design concepts, report on our discussion, and summarize our insights; in particular we suggest that the social and the physical dimension of care technologies should always be thought of and designed as interrelated

Randomized compiling for scalable quantum computing on a noisy superconducting quantum processor

The successful implementation of algorithms on quantum processors relies on the accurate control of quantum bits (qubits) to perform logic gate operations. In this era of noisy intermediate-scale quantum (NISQ) computing, systematic miscalibrations, drift, and crosstalk in the control of qubits can lead to a coherent form of error which has no classical analog. Coherent errors severely limit the performance of quantum algorithms in an unpredictable manner, and mitigating their impact is necessary for realizing reliable quantum computations. Moreover, the average error rates measured by randomized benchmarking and related protocols are not sensitive to the full impact of coherent errors, and therefore do not reliably predict the global performance of quantum algorithms, leaving us unprepared to validate the accuracy of future large-scale quantum computations. Randomized compiling is a protocol designed to overcome these performance limitations by converting coherent errors into stochastic noise, dramatically reducing unpredictable errors in quantum algorithms and enabling accurate predictions of algorithmic performance from error rates measured via cycle benchmarking. In this work, we demonstrate significant performance gains under randomized compiling for the four-qubit quantum Fourier transform algorithm and for random circuits of variable depth on a superconducting quantum processor. Additionally, we accurately predict algorithm performance using experimentally-measured error rates. Our results demonstrate that randomized compiling can be utilized to maximally-leverage and predict the capabilities of modern-day noisy quantum processors, paving the way forward for scalable quantum computing