Microscopic derivation of multi-channel Hubbard models for ultracold nonreactive molecules in an optical lattice

Recent experimental advances in the cooling and manipulation of bialkali dimer molecules have enabled the production of gases of ultracold molecules that are not chemically reactive. It has been presumed in the literature that in the absence of an electric field the low-energy scattering of such nonreactive molecules (NRMs) will be similar to atoms, in which a single $s$-wave scattering length governs the collisional physics. However, in Ref. [1], it was argued that the short-range collisional physics of NRMs is much more complex than for atoms, and that this leads to a many-body description in terms of a multi-channel Hubbard model. In this work, we show that this multi-channel Hubbard model description of NRMs in an optical lattice is robust against the approximations employed in Ref. [1] to estimate its parameters. We do so via an exact, albeit formal, derivation of a multi-channel resonance model for two NRMs from an ab initio description of the molecules in terms of their constituent atoms. We discuss the regularization of this two-body multi-channel resonance model in the presence of a harmonic trap, and how its solutions form the basis for the many-body model of Ref. [1]. We also generalize the derivation of the effective lattice model to include multiple internal states (e.g., rotational or hyperfine). We end with an outlook to future research.Comment: 19 pages, 4 figure

Public Health Surveillance Using Electronic Health Records: Rising Potential to Advance Public Health

Background: Public health surveillance has traditionally relied on manual processes including paper-based reporting by clinicians. The introduction of electronic laboratory reporting increased the efficiency and completeness of infectious disease surveillance but clinical and risk factor data are often still collected manually. The use of electronic health records (EHR) has significant promise to enrich surveillance by collecting these data automatically and by expanding surveillance to chronic diseases (e.g., diabetes, hypertension, obesity). However, the extent of the use of EHRs for public surveillance is not well studied. Evidence Acquisition: The peer-reviewed medical literature was searched for descriptions of the use of EHRs for public health surveillance. Evidence Synthesis: This literature is very limited. The largest body of work describes the experience of the Electronic Medical Record Support for Public Health system (ESPnet) currently being used in Massachusetts, Ohio, and Texas. It shows both the potential and challenges of using EHRs for surveillance. Discussion: Routine incorporation of EHR data into surveillance provides a unique opportunity to expand the breadth, quality, and efficiency of surveillance efforts. However, more research is needed to document the potential benefits and limitations of EHRs. Implications: Surveillance practitioners should work with health systems and EHR vendors to explore the use of EHRs. Policymakers should increase financial support for EHR-based surveillance by building requirements into Meaningful Use and other initiatives. In addition, clinical medicine and public health should work together to develop meaningful surveillance measures that can simultaneously improve the care of individuals and populations

Novel population pharmacokinetic approach to explain the differences between cystic fibrosis patients and healthy volunteers via protein binding

The pharmacokinetics in patients with cystic fibrosis (CF) has long been thought to differ considerably from that in healthy volunteers. For highly protein bound beta -lactams, profound pharmacokinetic differences were observed between comparatively morbid patients with CF and healthy volunteers. These differences could be explained by body weight and body composition for beta -lactams with low protein binding. This study aimed to develop a novel population modeling approach to describe the pharmacokinetic differences between both subject groups by estimating protein binding. Eight patients with CF (lean body mass [LBM]: 39.8 +/- 5.4kg) and six healthy volunteers (LBM: 53.1 +/- 9.5kg) received 1027.5 mg cefotiam intravenously. Plasma concentrations and amounts in urine were simultaneously modelled. Unscaled total clearance and volume of distribution were 3% smaller in patients with CF compared to those in healthy volunteers. After allometric scaling by LBM to account for body size and composition, the remaining pharmacokinetic differences were explained by estimating the unbound fraction of cefotiam in plasma. The latter was fixed to 50% in male and estimated as 54.5% in female healthy volunteers as well as 56.3% in male and 74.4% in female patients with CF. This novel approach holds promise for characterizing the pharmacokinetics in special patient populations with altered protein binding

The New York State Cardiac Registries History, Contributions, Limitations, and Lessons for Future Efforts to Assess and Publicly Report Healthcare Outcomes

In 1988, the New York State Health Commissioner was confronted with hospital-level data demonstrating very large, multiple-year, interhospital variations in short-term mortality and complications for cardiac surgery. The concern with the extent to which these differences were due to variations in patients' pre-surgical severity of illness versus hospitals' quality of care led to the development of clinical registries for cardiac surgery in 1989 and for percutaneous coronary interventions in 1992 in New York. In 1990, the Department of Health released hospitals' risk-adjusted cardiac surgery mortality rates for the first time, and shortly thereafter, similar data were released for hospitals and physicians for percutaneous coronary interventions, cardiac valve surgery, and pediatric cardiac surgery (only hospital data). This practice is still ongoing. The purpose of this communication is to relate the history of this initiative, including changes or purported changes that have occurred since the public release of cardiac data. These changes include decreases in risk-adjusted mortality, cessation of cardiac surgery in New York by low-volume and high-mortality surgeons, out-of-state referral or avoidance of cardiac surgery/angioplasty for high-risk patients, alteration of contracting choices by insurance companies, and modifications in market share of cardiac hospitals. Evidence related to these impacts is reviewed and critiqued. This communication also includes a summary of numerous studies that used New York's cardiac registries to examine a variety of policy issues regarding the choice and use of cardiac procedures, the comparative effectiveness of competing treatment options, and the examination of the relationship among processes, structures, and outcomes of cardiac care

Lattice-Model Parameters for Ultracold Nonreactive Molecules: Chaotic Scattering and Its Limitations

We calculate the parameters of the recently derived many-channel Hubbard model that is predicted to describe ultracold nonreactive molecules in an optical lattice, going beyond the approximations used by Doçaj et al. [A. Doçaj et al., Phys. Rev. Lett. 116, 135301 (2016)]. Although those approximations are expected to capture the qualitative structure of the model parameters, finer details and quantitative values are less certain. To set expectations for experiments, whose results depend on the model parameters, we describe the approximations’ regime of validity and the likelihood that experiments will be in this regime, discuss the impact that the failure of these approximations would have on the predicted model, and develop theories going beyond these approximations. Not only is it necessary to know the model parameters in order to describe experiments, but the connection that we elucidate between these parameters and the underlying assumptions that are used to derive them will allow molecule experiments to probe new physics. For example, transition state theory, which is used across chemistry and chemical physics, plays a key role in our determination of lattice parameters, thus connecting its physical assumptions to highly accurate experimental investigation

Evaluation of atrial fibrillation using wearable device signals and home blood pressure data in the Michigan Predictive Activity & Clinical Trajectories in Health (MIPACT) Study: A Subgroup Analysis (MIPACT-AFib)

BackgroundThe rising adoption of wearable technology increases the potential to identify arrhythmias. However, specificity of these notifications is poorly defined and may cause anxiety and unnecessary resource utilization. Herein, we report results of a follow-up screening protocol for incident atrial fibrillation/flutter (AF) within a large observational digital health study.MethodsThe MIPACT Study enrolled 6,765 adult patients who were provided an Apple Watch and blood pressure (BP) monitors. From March to July 2019, participants were asked to contact the study team for any irregular heart rate (HR) notification. They were assessed using structured questionnaires and asked to provide 6 Apple Watch EKGs. Those with arrhythmias or non-diagnostic EKGs were sent 7-day monitors. The EHR was reviewed after 3 years to determine if participants developed arrhythmias.Results86 participants received notifications and met inclusion criteria. Mean age was 50.5 (SD 16.9) years, and 46 (53.3%) were female. Of 76 participants assessed by the study team, 32 (42.1%) reported anxiety surrounding notifications. Of 59 participants who sent at least 1 EKG, 52 (88.1%) were in sinus rhythm, 3 (5.1%) AF, 2 (3.4%) indeterminate, and 2 (3.4%) sinus bradycardia. Cardiac monitor demonstrated AF in 2 of 3 participants with AF on Apple Watch EKGs. 2 contacted their PCPs and were diagnosed with AF. In total, 5 cases of AF were diagnosed with 1 additional case identified during EHR review.ConclusionWearable devices produce alarms that can frequently be anxiety provoking. Research is needed to determine the implications of these alarms and appropriate follow-up

Development and Assessment of an Artificial Intelligence-Based Tool for Ptosis Measurement in Adult Myasthenia Gravis Patients Using Selfie Video Clips Recorded on Smartphones

Introduction: Myasthenia gravis (MG) is a rare autoimmune disease characterized by muscle weakness and fatigue. Ptosis (eyelid drooping) occurs due to fatigue of the muscles for eyelid elevation and is one symptom widely used by patients and healthcare providers to track progression of the disease. Margin reflex distance 1 (MRD1) is an accepted clinical measure of ptosis and is typically assessed using a hand-held ruler. In this work, we develop an AI model that enables automated measurement of MRD1 in self-recorded video clips collected using patient smartphones. Methods: A 3-month prospective observational study collected a dataset of video clips from patients with MG. Study participants were asked to perform an eyelid fatigability exercise to elicit ptosis while filming “selfie” videos on their smartphones. These images were collected in nonclinical settings, with no in-person training. The dataset was annotated by non-clinicians for (1) eye landmarks to establish ground truth MRD1 and (2) the quality of the video frames. The ground truth MRD1 (in millimeters, mm) was calculated from eye landmark annotations in the video frames using a standard conversion factor, the horizontal visible iris diameter of the human eye. To develop the model, we trained a neural network for eye landmark detection consisting of a ResNet50 backbone plus two dense layers of 78 dimensions on publicly available datasets. Only the ResNet50 backbone was used, discarding the last two layers. The embeddings from the ResNet50 were used as features for a support vector regressor (SVR) using a linear kernel, for regression to MRD1, in mm. The SVR was trained on data collected remotely from MG patients in the prospective study, split into training and development folds. The model’s performance for MRD1 estimation was evaluated on a separate test fold from the study dataset. Results: On the full test fold (N = 664 images), the correlation between the ground truth and predicted MRD1 values was strong (r = 0.732). The mean absolute error was 0.822 mm; the mean of differences was −0.256 mm; and 95% limits of agreement (LOA) were −0.214–1.768 mm. Model performance showed no improvement when test data were gated to exclude “poor” quality images. Conclusions: On data generated under highly challenging real-world conditions from a variety of different smartphone devices, the model predicts MRD1 with a strong correlation (r = 0.732) between ground truth and predicted MRD1

Allogeneic Hematopoietic Cell Transplantation Provides Effective Salvage Despite Refractory Disease or Failed Prior Autologous Transplant in Angioimmunoblastic T-Cell Lymphoma: A CIBMTR Analysis

Background: There is a paucity of data on the role of allogeneic hematopoietic cell transplantation (allo-HCT) in patients with angioimmunoblastic T-cell lymphoma (AITL). Using the CIBMTR registry, we report here the outcomes of AITL patients undergoing an allo-HCT. Methods: We evaluated 249 adult AITL patients who received their first allo-HCT during 2000–2016. Results: The median patient age was 56 years (range = 21–77). Majority of the patients were Caucasians (86%), with a male predominance (60%). Graft-versus-host disease (GVHD) prophylaxis was predominantly calcineurin inhibitor-based approaches while the most common graft source was peripheral blood (97%). Median follow-up of survivors was 49 months (range = 4–170 months). The cumulative incidence of grade 2–4 and grade 3–4 acute GVHD at day 180 were 36% (95% CI = 30–42) and 12 (95% CI = 8–17), respectively. The cumulative incidence of chronic GVHD at 1 year was 49% (95%CI 43–56). The 1-year non-relapse mortality (NRM) was 19% (95% CI = 14–24), while the 4-year relapse/progression, progression-free survival (PFS), and overall survival (OS) were 21% (95% CI = 16–27), 49% (95% CI = 42–56), and 56% (95% CI = 49–63), respectively. On multivariate analysis, chemoresistant status at the time of allo-HCT was associated with a significantly higher risk for therapy failure (inverse of PFS) (RR = 1.73 95% CI = 1.08–2.77), while KPS \u3c 90% was associated with a significantly higher risk of mortality (inverse of OS) (RR = 3.46 95% CI = 1.75–6.87). Conclusion: Our analysis shows that allo-HCT provides durable disease control even in AITL patients who failed a prior auto-HCT and in those subjects with refractory disease at the time of allografting