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BACKGROUND Social media has emerged as an effective tool to mitigate preventable and costly health issues with social network interventions (SNIs), but a precision public health approach is still lacking to improve health equity and account for population disparities. OBJECTIVE This study aimed to (1) develop an SNI framework for precision public health using control systems engineering to improve the delivery of digital educational interventions for health behavior change and (2) validate the SNI framework to increase organ donation awareness in California, taking into account underlying population disparities. METHODS This study developed and tested an SNI framework that uses publicly available data at the ZIP Code Tabulation Area (ZCTA) level to uncover demographic environments using clustering analysis, which is then used to guide digital health interventions using the Meta business platform. The SNI delivered 5 tailored organ donation–related educational contents through Facebook to 4 distinct demographic environments uncovered in California with and without an Adaptive Content Tuning (ACT) mechanism, a novel application of the Proportional Integral Derivative (PID) method, in a cluster randomized trial (CRT) over a 3-month period. The daily number of impressions (ie, exposure to educational content) and clicks (ie, engagement) were measured as a surrogate marker of awareness. A stratified analysis per demographic environment was conducted. RESULTS Four main clusters with distinctive sociodemographic characteristics were identified for the state of California. The ACT mechanism significantly increased the overall click rate per 1000 impressions (β=.2187; PPP=.053). Cluster 1 is mainly composed of a population that is more likely to be rural, White, and have a higher rate of Medicare beneficiaries, while cluster 4 is more likely to be urban, Hispanic, and African American, with a high employment rate without high income and a higher proportion of Medicaid beneficiaries. CONCLUSIONS The proposed SNI framework, with its ACT mechanism, learns and delivers, in real time, for each distinct subpopulation, the most tailored educational content and establishes a new standard for precision public health to design novel health interventions with the use of social media, automation, and machine learning in a form that is efficient and equitable. CLINICALTRIAL ClinicalTrials.gov NTC04850287; https://clinicaltrials.gov/ct2/show/NCT04850287

UNSTRUCTURED This is the author(s)’ responses to peer review reports related to MS ID30777

Heart failure (HF) is a major health care burden increasing in prevalence over time. Effective, evidence-based interventions for HF prevention and management are needed to improve patient longevity, symptom control, and quality of life. Dietary Approaches to Stop Hypertension (DASH) diet interventions can have a positive impact for HF patients. However, the absence of a consensus for comprehensive dietary guidelines and for pragmatic evidence limits the ability of health care providers to implement clinical recommendations. The refinement of medical nutrition therapy through precision nutrition approaches has the potential to reduce the burden of HF, improve clinical care, and meet the needs of diverse patients. The aim of this review is to summarize current evidence related to HF dietary recommendations including DASH diet nutritional interventions and to develop initial recommendations for DASH diet implementation in outpatient HF management. Articles involving human studies were obtained using the following search terms: Dietary Approaches to Stop Hypertension (DASH diet), diet pattern, diet, metabolism, and heart failure. Only full-text articles written in English were included in this review. As DASH nutritional interventions have been proposed, limitations of these studies are the small sample size and non-randomization of interventions, leading to less reliable evidence. Randomized controlled interventions are needed to offer definitive evidence related to the use of the DASH diet in HF management.

Nanomechanical resonators have applications in a wide variety of technologies ranging from biochemical sensors to mobile communications, quantum computing, inertial sensing, and precision navigation. The quality factor of the mechanical resonance is critical for many applications. Until recently, mechanical quality factors rarely exceeded a million. In the past few years however, new methods have been developed to exceed this boundary. These methods involve careful engineering of the structure of the nanomechanical resonator, including the use of acoustic bandgaps and nested structures to suppress dissipation into the substrate, and the use of dissipation dilution and strain engineering to increase the mechanical frequency and suppress intrinsic dissipation. Together, they have allowed quality factors to reach values near a billion at room temperature, resulting in exceptionally low dissipation. This review aims to provide a pedagogical introduction to these new methods, primarily targeted to readers who are new to the field, together with an overview of the existing state-of-the-art, what may be possible in the future, and a perspective on the future applications of these extreme-high quality resonators., 22 pages, 11 figures

BACKGROUND Higher-than-expected heart failure (HF) readmissions affect half of US hospitals every year. The Hospital Reduction Readmission Program has reduced risk-adjusted readmissions, but it has also produced unintended consequences. Shared care models have been advocated for HF care, but the association of shared care networks with HF readmissions has never been investigated. OBJECTIVE This study aims to evaluate the association of shared care networks with 30-day HF excessive readmission rates using a longitudinal observational study. METHODS We curated publicly available data on hospital discharges and HF excessive readmission ratios from hospitals in California between 2012 and 2017. Shared care areas were delineated as data-driven units of care coordination emerging from discharge networks. The localization index, the proportion of patients who reside in the same shared care area in which they are admitted, was calculated by year. Generalized estimating equations were used to evaluate the association between the localization index and the excessive readmission ratio of hospitals controlling for race/ethnicity and socioeconomic factors. RESULTS A total of 300 hospitals in California in a 6-year period were included. The HF excessive readmission ratio was negatively associated with the adjusted localization index (β=–.0474, 95% CI –0.082 to –0.013). The percentage of Black residents within the shared care areas was the only statistically significant covariate (β=.4128, 95% CI 0.302 to 0.524). CONCLUSIONS Higher-than-expected HF readmissions were associated with shared care networks. Control mechanisms such as the Hospital Reduction Readmission Program may need to characterize and reward shared care to guide hospitals toward a more organized HF care system.

STRUCTURED ABSTRACTObjectivesThis study aimed to evaluate the impact of shared care networks on heart failure readmission rates.BackgroundHigher-than-expected heart failure (HF) readmissions affect half of US hospitals every year. The Hospital Reduction Readmission Program (HRRP) has reduced risk-adjusted readmissions, but it has also produced unintended consequences. Shared care models have been advocated for HF care, but the association of shared care networks with HF readmissions has never been investigated.MethodsWe curated publicly available data on hospital discharges and HF excessive readmission ratios (ERRs) from hospitals in California between 2012 and 2017. Shared Care Areas (SCAs) were delineated as data-driven units of care coordination emerging from discharge networks. The localization index (LI), the proportion of patients who reside in the same SCA in which they are admitted, were calculated by year. Generalized estimating equations (GEE) were used to evaluate the association between the LI and the ERR of hospitals controlling for race/ethnicity and socioeconomics factors.ResultsA total of 300 hospitals in California in a 6-yr period were included. The HF excessive readmission ratio (ERR) was negatively associated with the localization index (beta: -0.0474; 95% CI: -0.082 to -0.013). The percentage of Black residents within the SCAs was the only statistically significant covariate (beta: 0.4128; 95% CI: 0.302 to 0.524).ConclusionsHigher-than-expected HF readmissions were associated with shared care networks. Control mechanisms such as the HRRP may need to characterize and reward shared care to guide hospitals towards a more organized HF care system.

Nanomechanical circuits for transverse acoustic waves promise to enable new approaches to computing, precision biochemical sensing and many other applications. However, progress is hampered by the lack of precise control of the coupling between nanomechanical elements. Here, we demonstrate virtual-phonon coupling between transverse mechanical elements, exploiting tunnelling through a zero-mode acoustic barrier. This allows the construction of large-scale nanomechanical circuits on a silicon chip, for which we develop a new scalable fabrication technique. As example applications, we build mode-selective acoustic mirrors with controllable reflectivity and demonstrate acoustic spatial mode filtering. Our work paves the way towards applications such as fully nanomechanical computer processors and distributed nanomechanical sensors, and to explore the rich landscape of nonlinear nanomechanical dynamics., 9 pages, 6 figures

Background: Only a small proportion of patients with Heart Failure with Reduced Ejection Fraction (HFrEF) receive optimal Guideline-Directed Medical Therapy (GDMT) despite being eligible based on their clinical profile. The GDMT underuse leads to an important gap in clinical outcomes. In light of this gap, we integrated telemonitoring with a protocol for therapy optimization. We hypothesize that GDMT assisted by telemonitoring can improve the proportion of patients receiving optimal GDMT Objective: The aim of this study is to assess the value of telemonitoring in the optimization of GDMT. Methods: In a randomized controlled trial control patients will receive standard of care for GDMT, whereas the intervention group will receive GDMT assisted by telemonitoring. Patient eligibility includes HFrEF (LVEF≤ 40%), ACC/AHA stage C while receiving ≥ 1 GDMT medication at Conclusions: This trial implements and tests the value of GDMT assisted by telemonitoring. Our approach combines telemonitoring in a structured titration program for therapy optimization. Findings may have implications for achieving GDMT adherence in clinical practice.

Background Mitochondrial dysfunction is associated with poor allograft prognosis. Mitochondrial-related gene expression (GE) in endomyocardial biopsies (EMBs) could be useful as a nonimmune functional marker of rejection. We hypothesize that acute cardiac allograft rejection is associated with decreased mitochondrial-related GE in EMBs. Methods We collected 64 routines or clinically indicated EMB from 47 patients after heart transplant. The EMBs were subjected to mRNA sequencing. We conducted weighted gene coexpression network analysis to construct module-derived eigengenes. The modules were assessed by gene ontology enrichment and hub gene analysis. Modules were correlated with the EMBs following the International Society of Heart and Lung Transplantation histology-based criteria and a classification based on GE alone; we also correlated with clinical parameters. Results The modules enriched with mitochondria-related and immune-response genes showed the strongest correlation to the clinical traits. Compared with the no-rejection samples, rejection samples had a decreased activity of mitochondrial-related genes and an increased activity of immune-response genes. Biologic processes and hub genes in the mitochondria-related modules were primarily involved with energy generation, substrate metabolism, and regulation of oxidative stress. Compared with International Society of Heart and Lung Transplantation criteria, GE-based classification had stronger correlation to the weighted gene coexpression network analysis-derived functional modules. The brain natriuretic peptide level, ImmuKnow, and Allomap scores had negative relationships with the expression of mitochondria-related modules and positive relationships with immune-response modules. Conclusions During acute cardiac allograft rejection, there was a decreased activity of mitochondrial-related genes, related to an increased activity of immune-response genes, and depressed allograft function manifested by brain natriuretic peptide elevation. This suggests a rejection-associated mitochondrial impairment.

A Health Service Area (HSA) is a group of geographic regions served by similar health care facilities. The delineation of HSAs plays a pivotal role in the characterization of health care services available in an area, enabling better planning and regulation of health care services. Though Dartmouth HSAs have been the standard delineation for decades, previous work has recently shown an improved HSA delineation using a network-based approach, in which HSAs are the communities extracted by the Louvain algorithm in hospital-patient discharge networks. Given the known heterogeneity of communities extracted by different community detection algorithms, a comparative analysis of community detection algorithms for optimal HSA delineation is lacking. In this work, we compared HSA delineations produced by community detection algorithms using a large-scale dataset containing different types of hospital-patient discharges spanning a 7-year period in the USA. Our results replicated the heterogeneity among community detection algorithms found in previous works, the improved HSA delineation obtained by a network-based, and suggested that Infomap may be a more suitable community detection for HSA delineation since it finds a high number of HSAs with high localization index and a low network conductance.

Micro and nanomechanical systems play an important role in modern science and technology. They are indispensable for precision sensing, navigation and communication. Over the past decade, the rapid advances in nano-fabrication and measurement science have enabled quantum control of mechanical devices by integrating them to optical and microwave cavities, in the growing field of quantum optomechanics. However, experiments in quantum optomechanics at room temperature still face significant challenges. Perhaps the most demanding condition to perform experiments of this nature is reducing noise level due to coupling of the device to its environment through mechanical vibrations, phonons. In this thesis, we engineer micromechanical devices that confine mechanical excitations, decoupling them from their environment. The engineered design of these resonators combines a built-in suspended phononic low pass filter with a trampoline design made of top quality SiC single crystal. Results with quality factors Q~4x10^8 show the efficiency of these resonators. This is the largest Q for a system of its kind with such a large mesoscopic mode size ~0.5 mm^2 and resonance frequency f~220 kHz. The ultra-high Q mechanical resonators we developed can be used for quantum optomechanics experiments at room temperature. Similar to electrons, phonons propagate through material and are characterized by their dispersion relation. By engineering the properties of the material it is possible to confine and guide phonons through phononic channels. The importance of guided phonons relies on the fact that guided signals are the back-bone of all communication systems. The existing platforms for mechanical channels rely on the inclusion of phononic crystals for phonon confinement. However, phononic crystals base their functionality on acoustic interference, limiting its scalability. In this thesis, we designed, fabricated and characterized the basic components for a phononic circuitry platform based on highly stressed silicon nitride membranes on Si. These phononic waveguides share a similar mathematical framework with to photonic waveguides. Our phononic waveguides are single mode for a range of frequencies. In this region, the guided mode experiences low dissipation. We also show that there is a cut-off frequency at which the excitations cannot propagate, completely analogous to the photonic case. This phononic ``wires'' could in principle be used as the fundamental element for mechanics based communication networks. In the last chapter of this thesis, we propose a magnetomechanical system, where the mechanical system couples through the momentum to an electromagnetic field. By coupling the momentum to an electromagnetic field, it is possible to perform non-demolition measurement protocols that allow us to measure directly the position of the oscillator. By enhancing the coupling between the mechanics and the electromagnetic field we predict that the ground state of the two systems get entangled. We designed a system that can achieve coupling rates as large as a significant fraction of the mechanical resonance frequency. With such extremely large coupling rates, it is possible to explore the "ultra strong coupling regime" (USC). The USC has not previously been observed in mechanical systems.

High quality micro- and nano-mechanical resonators are widely used in sensing, communications and timing, and have future applications in quantum technologies and fundamental studies of quantum physics. Crystalline thin-films are particularly attractive for such resonators due to their prospects for high quality, intrinsic stress and yield strength, and low dissipation. However, when grown on a silicon substrate, interfacial defects arising from lattice mismatch with the substrate have been postulated to introduce additional dissipation. Here, we develop a new backside etching process for single crystal silicon carbide microresonators that allows us to quantitatively verify this prediction. By engineering the geometry of the resonators and removing the defective interfacial layer, we achieve quality factors exceeding a million in silicon carbide trampoline resonators at room temperature, a factor of five higher than without the removal of the interfacial defect layer. We predict that similar devices fabricated from ultrahigh purity silicon carbide and leveraging its high yield strength, could enable room temperature quality factors as high as $6\times10^9$, Comment: 9 pages 5 figures

We demonstrate a single-mode phononic waveguide that enables robust propagation of mechanical waves. The waveguide is a highly-stressed silicon nitride membrane that supports the propagation of out-of-plane modes. In direct analogy to rectangular microwave waveguides, there exists a band of frequencies over which only the fundamental mode is allowed to propagate, while multiple modes are supported at higher frequencies. We directly image the mode profiles using optical heterodyne vibration measurement, showing good agreement with theory. In the single-mode frequency band, we show low-loss propagation ($\sim1$~dB/cm) for a $\sim5$~MHz mechanical wave. This design is well suited for phononic circuits interconnecting elements such as non-linear resonators or optomechanical devices for signal processing, sensing or quantum technologies., Comment: 6 pages, 5 figures

Purpose Primary graft dysfunction (PGD) in heart transplantation (HTx) patients is the leading cause of death within the first 30 days of HTx. Ischemic time >4 hours has been associated with a significant increase in mortality at 30 days post-transplant and up to 6 years post-transplant. The optimal immunosuppression regimen including induction therapy to prevent allograft failure is unclear. Induction therapy may have a protective effect against ischemia-reperfusion injury, a main mechanism of allograft injury after HTx. We sought to evaluate the effect of induction therapy in heart transplant recipients with longer ischemic times in both early and long-term graft failure. Methods This retrospective cohort study used the United Network for Organ Sharing (UNOS) and included adult (>21yr) heart transplant patients from Jun 30, 2004 to Mar 2015. The effect of induction therapy, either basiliximab (IL-2Rab) or ATG/ALG/thymoglobulin, on all-cause early and late graft failure was estimated by a logistic regression adjusted for the covariates ischemic time, age, African American race, serum creatinine >2.5, HLA mismatch > 4, and acute rejection episodes. The Inverse Probability Treatment Weighting (IPTW) was used to control for imbalanced propensity of receiving induction given the covariates. Results At 30 days, induction was shown to reduce graft failure OR 0.69 (95% CI, 0.57-0.82) in all comers with no additional benefit for patients with prolonged ischemic time OR 1.08 (95% CI 0.87-1.36). Induction had no effect on long term graft failure up to 5.6 years OR 0.96 (95% CI 0.88 -1.04), except in patients with prolonged ischemic time OR 0.88 (95%CI 0.79-0.98). Conclusion Our results suggest that induction therapy may be protective against graft failure at 30 days, and late graft failure up to five years in a subset of patients with prolonged ischemic times.

Introduction The optimal management of advanced heart failure patients partially depends on the shared care between community HF units (i.e., primary care and general cardiologists), specialized HF units (i.e., interventional cardiology), and tertiary hubs of advanced HF care (i.e., mechanical circulatory support and transplant). Currently, we lack a methodology to uncover the underlying areas of shared care. In this sense, we started to unveiling the underlying shared care areas in California using network science and large-scale data sets. Methods We modeled the shared care network using 37,324,861 discharges from 478 General Acute Care Hospitals to 2,709 patient home Zip Codes in California between 2016 and 2017. In the shared care network, nodes are Zip codes and links between two Zip Codes are given by the sum of the individual contribution of each facility, which is the product between the total number of discharges of that facility, the proportion of its discharges to both Zip Codes. Finally, Shared Care Areas (SCA) were extracted by applying a community detection algorithm called Infomap. For each SCA, we calculated the percentiles (25th, 50th, and 95th) for the population size using the Census data, the rate of heart transplants per 100,000 using data from the United Network for Organ Sharing (UNOS) as well as the rate of combinations of HF prescriptions per 100,000 involving specific Angiotensin converting enzyme (ACE) inhibitors, Beta-blockers (BB), Angiotensin II receptor blockers (ARB), Mineralocorticoid Receptor Antagonists (MRA), and angiotensin receptor-neprilysin inhibitor (ARNI) using Medicare Advantage Part D claims. Results We uncovered 44 SCAs as shown in the Figure. The population size (172,078, and 436,609, and 2,881,420), the rates of heart transplants (9, 10 and 19), as well as the rates of ARNI+BB+MRA (0, .26, and 1.29), ACE+ARB+BB (236, 276, and 449), ACE+MRA (100, 128, and 266), ARB+BB (773, 1034, and 1830), ACE+ARB (626, 780, and 1390) and ACE+BB (1108, 1267, and 1949) significantly varied among SCAs. Conclusions In the era where models of shared care are necessary for the optimal management of advanced heart failure patients, we still lack an automated methodology to unveil these areas. Here, we attempted to establish the foundations of how SCA can be uncovered using network science and large-scale data sets of patient discharges, census, heart transplantations, and prescription claims.

Objectives Most national-level data regarding lesbian, gay, bisexual, transgender, queer/questioning, intersex, and allies (LGBTQIA) immunizations are limited. The primary objective of this study was to identify factors that influence behaviors, attitudes, and perceptions toward the uptake of the influenza vaccine within the Hispanic LGBTQIA community. Methods This was a prospective survey that assessed vaccine acceptability and practices regarding the influenza vaccine within the LGBTQIA community. Collection of data occurred through the use of social media platforms from July 2016 to May 2018. A total of 126 participants (mean age 32.03 ± 11.68 years) completed a 15-minute, 26-item, English/Spanish survey. A number of outcome measures assessed perceptions of vaccine effectiveness and safety. In addition, perceived severity of influenza symptoms and perceived susceptibility to contract influenza was assessed. Results A logistic regression model assessed the impact of several factors on influenza vaccine uptake. Perceived susceptibility of contracting influenza from the vaccine (P = 0.015) and perceived ease of receiving the influenza vaccine (P = 0.005) were the strongest predictors of vaccine uptake. Results showed no association between disclosure of sexual orientation and influenza immunization uptake (χ2 = 3.55; P = 0.17). Exploratory analyses revealed that non-Hispanic patients were more likely to perceive that their health care providers were aware of their sexual orientation compared with Hispanic patients (χ2 = 8.66; P = 0.013). Conclusion Several factors emerged as predictors of influenza vaccine uptake in the LGBTQIA population. Further studies are needed to explore additional factors such as disclosure of sexual orientation and variation of uptake based on vaccine type (STD vs. non-STD vaccines).

The AUTHIC project is part of assistive technologies and it aims to develop tools which aid children with autism spectrum disorder (ASD) to understand and interpret facial expressions associated with an emotion, through interactive games supervised by a therapist. Since research is translational, health sciences findings in understanding emotion and the universality of facial expression support the multimedia applications development designed by user-centered methodologies and gamification. Learning routines enable training of ASD children to identify emotions in an interactive and entertaining way.

Resumen El uso de biomasa lignocelulosica como fuente de energia renovable se ha convertido progresivamente en un tema fundamental. Grandes esfuerzos se estan realizando enfocados en la identificacion y caracterizacion de biomasa adecuada que pueda ser utilizada para el reemplazo de combustibles fosiles convencionales. El principal objetivo del presente estudio es determinar la correlacion que existe entre los parametros del No. Kappa y el contenido de lignina en la paja de trigo y hacer un analisis quimico de la paja de trigo que queda como residuo agricola del cultivo de Trigo en el Valle de Mexicali, Mexico; todo esto para su futuro uso como biocombustible de siguiente generacion. Se realizaron los analisis de Humedad, cenizas, Proteina cruda, carbono organico, extraibles en hexano, extraibles en acetona, extraibles en agua, No. Kappa, lignina, hemicelulosa y celulosa. Las muestras de paja de trigo fueron posteriormente caracterizadas por Espectroscopia de infrarrojo por transformadas de Fourier para la asociacion del contenido de lignina con los resultados reportados. Un factor de correlacion de 0.239 entre el No. Kappa y el contenido de lignina se determino en base a manejo de datos para diferentes tipos de muestras de paja de trigo con la finalidad de poder determinar el contenido de lignina por un metodo de analisis mas sencillo y rapido para estudios posteriores de delignificacion de la paja del trigo.