High-throughput biochemical profiling reveals functional adaptation of a bacterial Argonaute.

Argonautes are nucleic acid-guided proteins that perform numerous cellular functions across all domains of life. Little is known about how distinct evolutionary pressures have shaped each Argonaute's biophysical properties. We applied high-throughput biochemistry to characterize how Thermus thermophilus Argonaute (TtAgo), a DNA-guided DNA endonuclease, finds, binds, and cleaves its targets. We found that TtAgo uses biophysical adaptations similar to those of eukaryotic Argonautes for rapid association but requires more extensive complementarity to achieve high-affinity target binding. Using these data, we constructed models for TtAgo association rates and equilibrium binding affinities that estimate the nucleic acid- and protein-mediated components of the target interaction energies. Finally, we showed that TtAgo cleavage rates vary widely based on the DNA guide, suggesting that only a subset of guides cleaves targets on physiologically relevant timescales.

Organization of the human intestine at single-cell resolution.

The intestine is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota and affects overall health1. The intesting has a length of over nine metres, along which there are differences in structure and function2. The localization of individual cell types, cell type development trajectories and detailed cell transcriptional programs probably drive these differences in function. Here, to better understand these differences, we evaluated the organization of single cells using multiplexed imaging and single-nucleus RNA and open chromatin assays across eight different intestinal sites from nine donors. Through systematic analyses, we find cell compositions that differ substantially across regions of the intestine and demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighbourhoods and communities, highlighting distinct immunological niches that are present in the intestine. We also map gene regulatory differences in these cells that are suggestive of a regulatory differentiation cascade, and associate intestinal disease heritability with specific cell types. These results describe the complexity of the cell composition, regulation and organization for this organ, and serve as an important reference map for understanding human biology and disease.

High-Throughput Analysis Reveals Rules for Target RNA Binding and Cleavage by AGO2.

Argonaute proteins loaded with microRNAs (miRNAs) or small interfering RNAs (siRNAs) form the RNA-induced silencing complex (RISC), which represses target RNA expression. Predicting the biological targets, specificity, and efficiency of both miRNAs and siRNAs has been hamstrung by an incomplete understanding of the sequence determinants of RISC binding and cleavage. We applied high-throughput methods to measure the association kinetics, equilibrium binding energies, and single-turnover cleavage rates of mouse AGO2 RISC. We find that RISC readily tolerates insertions of up to 7 nt in its target opposite the central region of the guide. Our data uncover specific guide:target mismatches that enhance the rate of target cleavage, suggesting novel siRNA design strategies. Using these data, we derive quantitative models for RISC binding and target cleavage and show that our in vitro measurements and models predict knockdown in an engineered cellular system.

A Quantitative and Predictive Model for RNA Binding by Human Pumilio Proteins.

High-throughput methodologies have enabled routine generation of RNA target sets and sequence motifs for RNA-binding proteins (RBPs). Nevertheless, quantitative approaches are needed to capture the landscape of RNA-RBP interactions responsible for cellular regulation. We have used the RNA-MaP platform to directly measure equilibrium binding for thousands of designed RNAs and to construct a predictive model for RNA recognition by the human Pumilio proteins PUM1 and PUM2. Despite prior findings of linear sequence motifs, our measurements revealed widespread residue flipping and instances of positional coupling. Application of our thermodynamic model to published in vivo crosslinking data reveals quantitative agreement between predicted affinities and in vivo occupancies. Our analyses suggest a thermodynamically driven, continuous Pumilio-binding landscape that is negligibly affected by RNA structure or kinetic factors, such as displacement by ribosomes. This work provides a quantitative foundation for dissecting the cellular behavior of RBPs and cellular features that impact their occupancies.

Alloantibodies after simultaneous liver-kidney transplant: A story of primary nonfunction, retransplantation, and antibody-mediated rejection.

Simultaneous liver-kidney transplant (SLKT) in the presence of antihuman leukocyte antigen (HLA) donor-specific antibodies (DSA) is a well-accepted practice. Herein, we describe the evolution of alloantibodies in a patient who received an SLKT. The pre-SLKT serum sample showed multiple strong DSA. As expected, all DSA cleared in a sample collected 4 days after the SLKT. Because of the primary nonfunction of the liver in the SLKT, the patient had a second liver transplant 4 days later. An abrupt increase in DSA levels against the kidney was detected 10 days after the second liver transplant. These DSA were refractory to treatment, and the transplanted kidney was lost due to antibody-mediated rejection (AMR). A detailed study of the HLA epitopes recognized by DSA and, after normalization with third-party alloantibodies to address the effect of multiple transfusions and liver allograft neutralization, showed that the elimination of these antibodies depended on the HLA antigens expressed by the transplanted liver cells. The return of DSA after removal of the first transplanted liver was associated with AMR in the transplanted kidney.

Demonstration of protein cooperativity mediated by RNA structure using the human protein PUM2.

Posttranslational gene regulation requires a complex network of RNA-protein interactions. Cooperativity, which tunes response sensitivities, originates from protein-protein interactions in many systems. For RNA-binding proteins, cooperativity can also be mediated through RNA structure. RNA structural cooperativity (RSC) arises when binding of one protein induces a redistribution of RNA conformational states that enhance access (positive cooperativity) or block access (negative cooperativity) to additional binding sites. As RSC does not require direct protein-protein interactions, it allows cooperativity to be tuned for individual RNAs, via alterations in sequence that alter structural stability. Given the potential importance of this mechanism of control and our desire to quantitatively dissect features that underlie physiological regulation, we developed a statistical mechanical framework for RSC and tested this model by performing equilibrium binding measurements of the human PUF family protein PUM2. Using 68 RNAs that contain two to five PUM2-binding sites and RNA structures of varying stabilities, we observed a range of structure-dependent cooperative behaviors. To test our ability to account for this cooperativity with known physical constants, we used PUM2 affinity and nearest-neighbor RNA secondary structure predictions. Our model gave qualitative agreement for our disparate set of 68 RNAs across two temperatures, but quantitative deviations arise from overestimation of RNA structural stability. Our results demonstrate cooperativity mediated by RNA structure and underscore the power of quantitative stepwise experimental evaluation of mechanisms and computational tools.

Increased access to liver transplantation for patients with acute on chronic liver failure after implementation of Share 35 Rule: An analysis from the UNOS database.

INTRODUCTION AND OBJECTIVES: Acute on chronic liver failure (ACLF), leads to high mortality. These patients are at risk of being delisted for liver transplantation (LT). Emerging data shows 1y post-transplant survival of 80-92%. The Share 35 (S35) policy was implemented to prioritize patients with MELD ≥35 on the LT waitlist. Our aim was to compare the LT outcomes of ACLF patients as a result of S35. MATERIALS AND METHODS: Data from the UNOS scientific registry were used to classify ACLF patients using the NACSELD criteria. For the analyses, data were divided into two eras; 2 years before S35 (Era 1) and 2 years after S35 (Era 2). Waitlist status was classified into categories: Transplanted, Death or Too Sick to Transplant and Still Waiting/Other. LT cumulative incidence between the populations in the eras was calculated using Fine and Gray's method. A proportional hazards model was used to investigate the era effect on cumulative incidence of LT. RESULTS: 46,861 patients were reviewed, of which 817 had ACLF. 366 patients (mean MELD: 37.1) were identified in Era 1 and 451 patients (mean MELD: 37.3) in Era 2. We found that ACLF patients were more likely to receive a liver transplant in Era 2 (p=0.0074). In both eras, transplanted patients had a significantly higher survival than those who were not transplanted (p<0.0001). CONCLUSIONS: Our study shows that S35 improved LT rate for ACLF suggesting that there should be broader recognition of ACLF and early transplantation should be pursued.

High fat diet causes distinct aberrations in the testicular proteome.

Diet has important effects on normal physiology and the potential deleterious effects of high fat diets and obesity on male reproductive health are being increasingly described. We conducted a histological review of the effects of chronic high fat (HF) diet (using a mouse model fed a 45% fat diet for 21 weeks) with a discovery proteomic study to assess for changes in the abundance of proteins in the testis. Mice on a HF diet became obese and developed glucose intolerance. Using mass spectrometry, we identify 102 proteins affected in the testis of obese mice. These included structural proteins important for the blood testis barrier (filamin A, FLNA), proteins involved in oxidative stress responses (spermatogenesis associated 20, SPATA-20) and lipid homoeostasis (sterol regulatory element-binding protein 2, SREBP2 and apolipoprotein A1, APOA1). In addition, an important regulator protein paraspeckle component 1, PSPC-1, which interacts with the androgen receptor was significantly downregulated. Proteomic data was validated using both Western blotting and immunostaining which confirmed and localised protein expression in both mouse and human testis using biopsy specimens. This study focused mainly on the abnormalities that occurred at the protein level and as a result, we have identified several candidate proteins and conducted pathway analysis around the effects of HF diet on the testis providing novel insights not previously described. Some of the identified targets could be targeted therapeutically and future work is directed in this area.

Clinicians' Overestimation of Their Geographic Service Area.

In this study, we evaluated family physicians' ability to estimate the service area of their patient panel-a critical first step in contextual population-based primary care. We surveyed 14 clinicians and administrators from 6 practices. Participants circled their estimated service area on county maps that were compared with the actual service area containing 70% of the practice's patients. Accuracy was ascertained from overlap and the amount of estimated census tracts that were not part of the actual service area. Average overlap was 75%, but participants overestimated their service area by an average of 166 square miles. Service area overestimation impedes implementation of targeted community interventions by practices.

Loneliness in Primary Care Patients: A Prevalence Study.

PURPOSE: Loneliness has important health consequences. Little is known, however, about loneliness in primary care patient populations. This study describes the prevalence of loneliness in patients presenting for primary care and associations with self-reported demographic factors, health care utilization, and health-related quality of life. METHODS: We conducted cross-sectional surveys of adults presenting for routine care to outpatient primary care practices in 2 diverse practice-based research networks. The 3-item University of California, Los Angeles Loneliness Scale was utilized to determine loneliness. RESULTS: The prevalence of loneliness was 20% (246/1,235). Loneliness prevalence was inversely associated with age (P <.01) and less likely in those who were married (P <.01) or employed (P <.01). Loneliness was more common in those with lower health status (P <.01), including when adjusting for employment and relationship status (odds ratio [OR] = 1.05; 95% CI, 1.03-1.07). Primary care visits (OR = 1.07; 95% CI, 1.03-1.10), urgent care/emergency department visits (OR = 1.24; 95% CI, 1.12-1.38), and hospitalizations (OR = 1.15; 95% CI, 1.01-1.31) were associated with loneliness status. There was no significant difference in rates of loneliness between sexes (P = .08), racial categories (P = .57), or rural and urban respondents (P = .42). CONCLUSIONS: Our findings demonstrate that loneliness is common in primary care patients and is associated with adverse health consequences including poorer health status and greater health care utilization. Further work is needed to understand the value of screening for and using interventions to treat loneliness in primary care.

Geographic Characteristics of Loneliness in Primary Care.

Loneliness is associated with poor health outcomes, and there is growing attention on loneliness as a social determinant of health. Our study sought to determine the associations between community factors and loneliness. The Three-Item Loneliness Scale and zip codes of residence were collected in primary care practices in Colorado and Virginia. Living in zip codes with higher unemployment, poor access to health care, lower income, higher proportions of blacks, and poor transportation was associated with higher mean loneliness scores. Future studies that examine interventions addressing loneliness may be more effective if they consider social context and community characteristics.

Hospitalizations for Cardiovascular Disease After Liver Transplantation in the United States.

Cardiovascular disease (CVD) is a leading cause of post-liver transplant death, and variable care patterns may affect outcomes. We aimed to describe epidemiology and outcomes of inpatient CVD care across US hospitals. Using a merged data set from the 2002-2011 Nationwide Inpatient Sample and the American Hospital Association Annual Survey, we evaluated liver transplant patients admitted primarily with myocardial infarction (MI), stroke (cerebrovascular accident [CVA]), congestive heart failure (CHF), dysrhythmias, cardiac arrest (CA), or malignant hypertension. Patient-level data include demographics, Charlson comorbidity index, and CVD diagnoses. Facility-level variables included ownership status, payer-mix, hospital resources, teaching status, and physician/nursing-to-bed ratios. We used generalized estimating equations to evaluate patient- and hospital-level factors associated with mortality. There were 4763 hospitalizations that occurred in 153 facilities (transplant hospitals, n = 80). CVD hospitalizations increased overall by 115% over the decade (P < 0.01). CVA and MI declined over time (both P < 0.05), but CHF and dysrhythmia grew significantly (both P < 0.03); a total of 19% of hospitalizations were for multiple CVD diagnoses. Transplant hospitals had lower comorbidity patients (P < 0.001) and greater resource intensity including presence of cardiac intensive care unit, interventional radiology, operating rooms, teaching status, and nursing density (all P < 0.01). Transplant and nontransplant hospitals had similar unadjusted mortality (overall, 3.9%, P = 0.55; by diagnosis, all P > 0.07). Transplant hospitals had significantly longer overall length of stay, higher total costs, and more high-cost hospitalizations (all P < 0.05). After risk adjustment, transplant hospitals were associated with higher mortality and high-cost hospitalizations. In conclusion, CVD after liver transplant is evolving and responsible for growing rates of inpatient care. Transplant hospitals are associated with poor outcomes, even after risk adjustment for patient and hospital characteristics, which may be attributable to selective referral of certain patient phenotypes but could also be related to differences in quality of care. Further study is warranted.

Glucose homeostasis after simultaneous pancreas and kidney transplantation: a comparison of subjects with C-peptide-positive non-type 1 diabetes mellitus and type 1 diabetes mellitus.

BACKGROUND: While simultaneous pancreas kidney transplant (SPKTx) is a therapeutic option for patients with type 1 diabetes (T1DM) and renal failure, few centers offer SPKTx to "select" non-T1DM patients. To address concerns that existing insulin resistance may limit the benefits of the pancreas allograft among non-T1DM, we compared several indices of glucose homeostasis, in "select" non-T1DM and T1DM patients who received SPKTx. METHODS: Criteria for "select" non-T1DM included the following: positive C-peptide, BMI <30 kg/m(2) , treatment with oral agents before insulin initiation, and insulin at <1 unit/kg/d. We compared several indices of glucose homeostasis within 1 yr post-SPKTx among seven "select" patients with non-T1DM and nine patients with T1DM with similar age, BMI, and immunosuppression. Measurements of insulin resistance included the following: homeostatic model, insulin sensitivity index, and insulin-glucose ratio; insulin secretion measures included the following: corrected insulin response. RESULTS: Non-T1DM had similar pre-transplant metabolic (fasting glucose, HbA1c, blood pressure, and lipid) parameters to the T1DM cohort. There were no significant differences in the various measures of insulin resistance and secretion between T1DM and "select" non-T1DM patients. CONCLUSION: Our results suggest SPKTx should be considered in the therapeutic armamentarium among carefully select non-T1DM with features of minimal insulin resistance; however, a larger cohort with longer follow-up is needed to confirm our results.

When Do Primary Care Physicians Retire? Implications for Workforce Projections.

PURPOSE: Retirement of primary care physicians is a matter of increasing concern in light of physician shortages. The joint purposes of this investigation were to identify the ages when the majority of primary care physicians retire and to compare this with the retirement ages of practitioners in other specialties. METHODS: This descriptive study was based on AMA Physician Masterfile data from the most recent 5 years (2010-2014). We also compared 2008 Masterfile data with data from the National Plan and Provider Enumeration System to calculate an adjustment for upward bias in retirement ages when using the Masterfile alone. The main analysis defined retirement as leaving clinical practice. The primary outcome was construction of a retirement curve. Secondary outcomes involved comparisons of retirement interquartile ranges (IQRs) by sex and practice location across specialties. RESULTS: The 2014 Masterfile included 77,987 clinically active primary care physicians between ages 55 and 80 years. The median age of retirement from clinical activity of all primary care physicians who retired in the period from 2010 to 2014 was 64.9 years, (IQR, 61.4-68.3); the median age of retirement from any activity was 66.1 years (IQR, 62.6-69.5). However measured, retirement ages were generally similar across primary care specialties. Females had a median retirement about 1 year earlier than males. There were no substantive differences in retirement ages between rural and urban primary care physicians. CONCLUSIONS: Primary care physicians in our data tended to retire in their mid-60s. Relatively small differences across sex, practice location, and time suggest that changes in the composition of the primary care workforce will not have a remarkable impact on overall retirement rates in the near future.

Solo and Small Practices: A Vital, Diverse Part of Primary Care.

PURPOSE: Solo and small practices are facing growing pressure to consolidate. Our objectives were to determine (1) the percentage of family physicians in solo and small practices, and (2) the characteristics of and services provided by these practices. METHODS: A total of 10,888 family physicians seeking certification through the American Board of Family Medicine in 2013 completed a demographic survey. Their practices were split into categories by size: solo, small (2 to 5 providers), medium (6 to 20 providers), and large (more than 20 providers). We also determined the rurality of the county where the physicians practiced. We developed 2 logistic regression models: one assessed predictors of practicing in a solo or small practice, while the other was restricted to solo and small practices and assessed predictors of practicing in a solo practice. RESULTS: More than one-half of respondents worked in solo or small practices. Small practices were the largest group (36%) and were the most likely to be located in a rural setting (20%). The likelihood of having a care coordinator and medical home certification increased with practice size. Physicians were more likely to be practicing in small or solo practices (vs medium-sized or large ones) if they were African American or Hispanic, had been working for more than 30 years, and worked in rural areas. Physicians were more likely to be practicing in small practices (vs solo ones) if they worked in highly rural areas. CONCLUSIONS: Family physicians in solo and small practices comprised the majority among all family physicians seeking board certification and were more likely to work in rural geographies. Extension programs and community health teams have the potential to support transformation within these practices.

Estimating the residency expansion required to avoid projected primary care physician shortages by 2035.

PURPOSE: The purpose of this study was to calculate the projected primary care physician shortage, determine the amount and composition of residency growth needed, and estimate the impact of retirement age and panel size changes. METHODS: We used the 2010 National Ambulatory Medical Care Survey to calculate utilization of ambulatory primary care services and the US Census Bureau to project demographic changes. To determine the baseline number of primary care physicians and the number retiring at 66 years, we used the 2014 American Medical Association Masterfile. Using specialty board and American Osteopathic Association figures, we estimated the annual production of primary care residents. To calculate shortages, we subtracted the accumulated primary care physician production from the accumulated number of primary care physicians needed for each year from 2015 to 2035. RESULTS: More than 44,000 primary care physicians will be needed by 2035. Current primary care production rates will be unable to meet demand, resulting in a shortage in excess of 33,000 primary care physicians. Given current production, an additional 1,700 primary care residency slots will be necessary by 2035. A 10% reduction in the ratio of population per primary care physician would require more than 3,000 additional slots by 2035, whereas changing the expected retirement age from 66 years to 64 years would require more than 2,400 additional slots. CONCLUSIONS: To eliminate projected shortages in 2035, primary care residency production must increase by 21% compared with current production. Delivery models that shift toward smaller ratios of population to primary care physicians may substantially increase the shortage.

Cost, utilization, and quality of care: an evaluation of illinois' medicaid primary care case management program.

PURPOSE: In 2006, Illinois established Illinois Health Connect (IHC), a primary care case management program for Medicaid that offered enhanced fee-for-service, capitation payments, performance incentives, and practice support. Illinois also implemented a complementary disease management program, Your Healthcare Plus (YHP). This external evaluation explored outcomes associated with these programs. METHODS: We analyzed Medicaid claims and enrollment data from 2004 to 2010, covering both pre- and post-implementation. The base year was 2006, and 2006-2010 eligibility criteria were applied to 2004-2005 data to allow comparison. We studied costs and utilization trends, overall and by service and setting. We studied quality by incorporating Healthcare Effectiveness Data and Information Set (HEDIS) measures and IHC performance payment criteria. RESULTS: Illinois Medicaid expanded considerably between 2006 (2,095,699 full-year equivalents) and 2010 (2,692,123). Annual savings were 6.5% for IHC and 8.6% for YHP by the fourth year, with cumulative Medicaid savings of $1.46 billion. Per-beneficiary annual costs fell in Illinois over this period compared to those in states with similar Medicaid programs. Quality improved for nearly all metrics under IHC, and most prevention measures more than doubled in frequency. Medicaid inpatient costs fell by 30.3%, and outpatient costs rose by 24.9% to 45.7% across programs. Avoidable hospitalizations fell by 16.8% for YHP, and bed-days fell by 15.6% for IHC. Emergency department visits declined by 5% by 2010. CONCLUSIONS: The Illinois Medicaid IHC and YHP programs were associated with substantial savings, reductions in inpatient and emergency care, and improvements in quality measures. This experience is not typical of other states implementing some, but not all, of these same policies. Although specific features of the Illinois reforms may have accounted for its better outcomes, the limited evaluation design calls for caution in making causal inferences.

Examining Linguistic Differences in Electronic Health Records for Diverse Patients With Diabetes: Natural Language Processing Analysis.

Background: Individuals from minoritized racial and ethnic backgrounds experience pernicious and pervasive health disparities that have emerged, in part, from clinician bias. Objective: We used a natural language processing approach to examine whether linguistic markers in electronic health record (EHR) notes differ based on the race and ethnicity of the patient. To validate this methodological approach, we also assessed the extent to which clinicians perceive linguistic markers to be indicative of bias. Methods: In this cross-sectional study, we extracted EHR notes for patients who were aged 18 years or older; had more than 5 years of diabetes diagnosis codes; and received care between 2006 and 2014 from family physicians, general internists, or endocrinologists practicing in an urban, academic network of clinics. The race and ethnicity of patients were defined as White non-Hispanic, Black non-Hispanic, or Hispanic or Latino. We hypothesized that Sentiment Analysis and Social Cognition Engine (SEANCE) components (ie, negative adjectives, positive adjectives, joy words, fear and disgust words, politics words, respect words, trust verbs, and well-being words) and mean word count would be indicators of bias if racial differences emerged. We performed linear mixed effects analyses to examine the relationship between the outcomes of interest (the SEANCE components and word count) and patient race and ethnicity, controlling for patient age. To validate this approach, we asked clinicians to indicate the extent to which they thought variation in the use of SEANCE language domains for different racial and ethnic groups was reflective of bias in EHR notes. Results: We examined EHR notes (n=12,905) of Black non-Hispanic, White non-Hispanic, and Hispanic or Latino patients (n=1562), who were seen by 281 physicians. A total of 27 clinicians participated in the validation study. In terms of bias, participants rated negative adjectives as 8.63 (SD 2.06), fear and disgust words as 8.11 (SD 2.15), and positive adjectives as 7.93 (SD 2.46) on a scale of 1 to 10, with 10 being extremely indicative of bias. Notes for Black non-Hispanic patients contained significantly more negative adjectives (coefficient 0.07, SE 0.02) and significantly more fear and disgust words (coefficient 0.007, SE 0.002) than those for White non-Hispanic patients. The notes for Hispanic or Latino patients included significantly fewer positive adjectives (coefficient -0.02, SE 0.007), trust verbs (coefficient -0.009, SE 0.004), and joy words (coefficient -0.03, SE 0.01) than those for White non-Hispanic patients. Conclusions: This approach may enable physicians and researchers to identify and mitigate bias in medical interactions, with the goal of reducing health disparities stemming from bias.