Storylines of family medicine XI: professional identity formation-nurturing one's own story.

Storylines of Family Medicine is a 12-part series of thematically linked mini-essays with accompanying illustrations that explore the many dimensions of family medicine, as interpreted by individual family physicians and medical educators in the USA and elsewhere around the world. In 'XI: professional identity formation-nurturing one's own story', authors address the following themes: 'The social construction of professional identity', 'On becoming a family physician', 'What's on the test?-professionalism for family physicians', 'The ugly doc-ling', 'Teachers-the essence of who we are', 'Family medicine research-it starts in the clinic', 'Socially accountability in medical education', 'Personal philosophy and how to find it' and 'Teaching and learning with Storylines of Family Medicine'. May these essays encourage readers to find their own creative spark in medicine.

An encyclopedia of enhancer-gene regulatory interactions in the human genome.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and largescale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 elementgene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancerpromoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Spectral widths and Stokes shifts in InP-based quantum dots.

InP-based quantum dots (QDs) have Stokes shifts and photoluminescence (PL) line widths that are larger than in II-VI semiconductor QDs with comparable exciton energies. The mechanisms responsible for these spectral characteristics are investigated in this paper. Upon comparing different semiconductors, we find the Stokes shift decreases in the following order: InP > CdTe > CdSe. We also find that the Stokes shift decreases with core size and decreases upon deposition of a ZnSe shell. We suggest that the Stokes shift is largely due to different absorption and luminescent states in the angular momentum fine structure. The energy difference between the fine structure levels, and hence the Stokes shifts, are controlled by the electron-hole exchange interaction. Luminescence polarization results are reported and are consistent with this assignment. Spectral widths are controlled by the extent of homogeneous and inhomogeneous broadening. We report PL and PL excitation (PLE) spectra that facilitate assessing the roles of homogeneous and different inhomogeneous broadening mechanisms in the spectra of zinc-treated InP and InP/ZnSe/ZnS particles. There are two distinct types of inhomogeneous broadening: size inhomogeneity and core-shell interface inhomogeneity. The latter results in a distribution of core-shell band offsets and is caused by interfacial dipoles associated with In-Se or P-Zn bonding. Quantitative modeling of the spectra shows that the offset inhomogeneity is comparable to but somewhat smaller than the size inhomogeneity. The combination of these two types of inhomogeneity also explains several aspects of reversible hole trapping dynamics involving localized In3+/VZn2- impurity states in the ZnSe shells.

Medications for opioid use disorder in rural primary care practices: Patient and provider experiences.

INTRODUCTION: The opioid epidemic has exacted a significant toll in rural areas, yet adoption of medications for opioid use disorder (MOUD) lags. The Rural Access to Medication Assisted Treatment in Pennsylvania (RAMP) Project facilitated adoption of MOUD in rural primary care clinics. The purpose of this study was to gain a better understanding of the barriers and facilitators operating at multiple levels to access or provide MOUD in rural Pennsylvania. METHODS: In total, the study conducted 35 semi-structured interviews with MOUD patients and MOUD providers participating in RAMP. Qualitative analysis incorporated both deductive and inductive approaches. The study team coded interviews and performed thematic analysis. Using a modified social-ecological framework, themes from the qualitative interviews are organized in five nested levels: individual, interpersonal, health care setting, community, and public policy. RESULTS: Patients and providers agreed on many barriers (e.g., lack of providers, lack of transportation, insufficient rapport and trust in patient-provider relationship, and cost, etc.); however, their interpretation of the barrier, or indicated solution, diverged in meaningful ways. Patients described their experiences in broad terms pointing to the social determinants of health, as they highlighted their lives outside of the therapeutic encounter in the clinic. Providers focused on their professional roles, responsibilities, and operations within the primary care setting. CONCLUSIONS: Providers may want to discuss barriers to treatment related to social determinants of health with patients, and pursue partnerships with organizations that seek to address those barriers. The findings from these interviews point to potential opportunities to enhance patient experience, increase access to and optimize processes for MOUD in rural areas, and reduce stigma against people with opioid use disorder (OUD) in the wider community.

Individual cell types in C. elegans age differently and activate distinct cell-protective responses.

Aging is characterized by a global decline in physiological function. However, by constructing a complete single-cell gene expression atlas, we find that Caenorhabditis elegans aging is not random in nature but instead is characterized by coordinated changes in functionally related metabolic, proteostasis, and stress-response genes in a cell-type-specific fashion, with downregulation of energy metabolism being the only nearly universal change. Similarly, the rates at which cells age differ significantly between cell types. In some cell types, aging is characterized by an increase in cell-to-cell variance, whereas in others, variance actually decreases. Remarkably, multiple resilience-enhancing transcription factors known to extend lifespan are activated across many cell types with age; we discovered new longevity candidates, such as GEI-3, among these. Together, our findings suggest that cells do not age passively but instead react strongly, and individualistically, to events that occur during aging. This atlas can be queried through a public interface.

Strategies to recruit rural primary care providers to implement a medication for opioid use disorder (MOUD) focused integrated care model.

Background: Access to providers and programs that provide medications for opioid use disorder (MOUD) remains a systemic barrier for patients with opioid use disorder (OUD), particularly if they live in rural areas. The Rural Access to Medication Assisted Treatment (MAT) in Pennsylvania Project (Project RAMP) addressed this problem with a multisystem partnership that recruited, trained, and supported rural primary care providers to provide MOUD and implement an integrated care model (ICM) for patients with OUD. Given the demonstrated efficacy of Project RAMP, this article summarizes our recruitment strategies, including feasibility concerns for further expansion into other regions. Methods: The approach for recruiting implementation sites included two phases: partner outreach and site identification. Once recruited, the Systems Transformation Framework guided planning and implementation activities. Recruitment and implementation activities were assessed with implementation trackers and evaluated by providers via key informant interviews (KIIs). Results: Project RAMP recruited 26 primary care practices from 13 counties, including nine health systems and two private practice groups-exceeding the original target of 24 sites. There was a median of 49 days from first contact to project onboarding. A total of 108 primary care practices spanning 22 health systems declined participation. Findings from the KIIs highlighted the value of engaging PCPs by connecting to a shared vision (i.e., improving the quality of patient care) as well as addressing perceived participation barriers (e.g., offering concierge technical assistance to address lack of training or resources). Conclusion: Findings highlight how successful recruitment activities should leverage the support of health system leadership. Findings also emphasize that aiding recruitment and engagement efforts successfully addressed prescribers' perceived barriers to providing MOUD as well as facilitating better communication among administrators, PCPs, behavioral health professionals, care managers, and patients.Plain Language Summary: Opioid use disorder (OUD) is one of the leading causes of preventable illness and death. The standard of care for OUD is the provision of medications for opioid use disorder (MOUD) and the application of an integrative integrated care model (ICM) where behavioral health is blended with specialized medical services. Unfortunately, access to providers and healthcare facilities that provide MOUD or apply an ICM remains a systemic barrier for patients with OUD, particularly if they live in rural areas. Although there is no one-size-fits-all approach to implementing MOUD in primary care, findings from Project The Rural Access to Medication Assisted Treatment (MAT) in Pennsylvania Project (Project RAMP) highlight strategies that may improve future MOUD and ICM implementation efforts in similar rural contexts. Specifically, future efforts to increase MOUD capacity by recruiting new providers should be prepared to leverage health system leadership, address provider barriers via training and expert consultation, and facilitate connections to local behavioral health providers. This approach may be helpful to others recruiting health systems and primary care practices to implement new care models to use MOUD in treating patients with OUD.

Rewriting regulatory DNA to dissect and reprogram gene expression.

Regulatory DNA sequences within enhancers and promoters bind transcription factors to encode cell type-specific patterns of gene expression. However, the regulatory effects and programmability of such DNA sequences remain difficult to map or predict because we have lacked scalable methods to precisely edit regulatory DNA and quantify the effects in an endogenous genomic context. Here we present an approach to measure the quantitative effects of hundreds of designed DNA sequence variants on gene expression, by combining pooled CRISPR prime editing with RNA fluorescence in situ hybridization and cell sorting (Variant-FlowFISH). We apply this method to mutagenize and rewrite regulatory DNA sequences in an enhancer and the promoter of PPIF in two immune cell lines. Of 672 variant-cell type pairs, we identify 497 that affect PPIF expression. These variants appear to act through a variety of mechanisms including disruption or optimization of existing transcription factor binding sites, as well as creation of de novo sites. Disrupting a single endogenous transcription factor binding site often led to large changes in expression (up to -40% in the enhancer, and -50% in the promoter). The same variant often had different effects across cell types and states, demonstrating a highly tunable regulatory landscape. We use these data to benchmark performance of sequence-based predictive models of gene regulation, and find that certain types of variants are not accurately predicted by existing models. Finally, we computationally design 185 small sequence variants (≤10 bp) and optimize them for specific effects on expression in silico. 84% of these rationally designed edits showed the intended direction of effect, and some had dramatic effects on expression (-100% to +202%). Variant-FlowFISH thus provides a powerful tool to map the effects of variants and transcription factor binding sites on gene expression, test and improve computational models of gene regulation, and reprogram regulatory DNA.

Comment on "Dependence of the Fluorescent Lifetime τ on the Concentration at High Dilution".

A recent Letter in this Journal (Langhals and Schlücker, J. Phys. Chem. Lett. 202213, 7568-7573) reported a dependence of the fluorescence lifetime of a dye on concentration and attributed it to "electromagnetic interactions with distant resonating structures" on a length scale of more than 100 nm. We show that their results can be explained as a straightforward result of absorption and re-emission of the fluorescence ("radiative energy transport"), which lengthens the apparent lifetime at higher concentrations. This effect has been well-documented in the literature many times. We show that simulations of the fluorescence decays accounting for radiative transport can reproduce the authors' results without postulating any new electromagnetic mechanism.

The genetic and biochemical determinants of mRNA degradation rates in mammals.

BACKGROUND: Degradation rate is a fundamental aspect of mRNA metabolism, and the factors governing it remain poorly characterized. Understanding the genetic and biochemical determinants of mRNA half-life would enable more precise identification of variants that perturb gene expression through post-transcriptional gene regulatory mechanisms. RESULTS: We establish a compendium of 39 human and 27 mouse transcriptome-wide mRNA decay rate datasets. A meta-analysis of these data identified a prevalence of technical noise and measurement bias, induced partially by the underlying experimental strategy. Correcting for these biases allowed us to derive more precise, consensus measurements of half-life which exhibit enhanced consistency between species. We trained substantially improved statistical models based upon genetic and biochemical features to better predict half-life and characterize the factors molding it. Our state-of-the-art model, Saluki, is a hybrid convolutional and recurrent deep neural network which relies only upon an mRNA sequence annotated with coding frame and splice sites to predict half-life (r=0.77). The key novel principle learned by Saluki is that the spatial positioning of splice sites, codons, and RNA-binding motifs within an mRNA is strongly associated with mRNA half-life. Saluki predicts the impact of RNA sequences and genetic mutations therein on mRNA stability, in agreement with functional measurements derived from massively parallel reporter assays. CONCLUSIONS: Our work produces a more robust ground truth for transcriptome-wide mRNA half-lives in mammalian cells. Using these revised measurements, we trained Saluki, a model that is over 50% more accurate in predicting half-life from sequence than existing models. Saluki succinctly captures many of the known determinants of mRNA half-life and can be rapidly deployed to predict the functional consequences of arbitrary mutations in the transcriptome.

Identity of the reversible hole traps in InP/ZnSe core/shell quantum dots.

Density functional theory calculations are combined with time-resolved photoluminescence experiments to identify the species responsible for the reversible trapping of holes following photoexcitation of InP/ZnSe/ZnS core/shell/shell quantum dots (QDs) having excess indium in the shell [P. Cavanaugh et al., J. Chem. Phys. 155, 244705 (2021)]. Several possible assignments are considered, and a substitutional indium adjacent to a zinc vacancy, In3+/VZn 2-, is found to be the most likely. This assignment is consistent with the observation that trapping occurs only when the QD has excess indium and is supported by experiments showing that the addition of zinc oleate or acetate decreases the extent of trapping, presumably by filling some of the vacancy traps. We also show that the addition of alkyl carboxylic acids causes increased trapping, presumably by the creation of additional zinc vacancies. The calculations show that either a single In2+ ion or an In2+-In3+ dimer is much too easily oxidized to form the reversible traps observed experimentally, while In3+ is far too difficult to oxidize. Additional experimental data on InP/ZnSe/ZnS QDs synthesized in the absence of chloride demonstrates that the reversible traps are not associated with Cl-. However, a zinc vacancy adjacent to a substitutional indium is calculated to have its highest occupied orbitals about 1 eV above the top of the valence band of bulk ZnSe, in the appropriate energy range to act as reversible traps for quantum confined holes in the InP valence band. The associated orbitals are predominantly composed of p orbitals on the Se atoms adjacent to the Zn vacancy.

scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks.

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC) shows great promise for studying cellular heterogeneity in epigenetic landscapes, but there remain important challenges in the analysis of scATAC data due to the inherent high dimensionality and sparsity. Here we introduce scBasset, a sequence-based convolutional neural network method to model scATAC data. We show that by leveraging the DNA sequence information underlying accessibility peaks and the expressiveness of a neural network model, scBasset achieves state-of-the-art performance across a variety of tasks on scATAC and single-cell multiome datasets, including cell clustering, scATAC profile denoising, data integration across assays and transcription factor activity inference.

Discovery of Insulin Receptor Partial Agonists MK-5160 and MK-1092 as Novel Basal Insulins with Potential to Improve Therapeutic Index.

We have identified a series of novel insulin receptor partial agonists (IRPAs) with a potential to mitigate the risk of hypoglycemia associated with the use of insulin as an antidiabetic treatment. These molecules were designed as dimers of native insulin connected via chemical linkers of variable lengths with optional capping groups at the N-terminals of insulin chains. Depending on the structure, the maximal activation level (%Max) varied in the range of ∼20-70% of native insulin, and EC50 values remained in sub-nM range. Studies in minipig and dog demonstrated that IRPAs had sufficient efficacy to normalize plasma glucose levels in diabetes, while providing reduction of hypoglycemia risk. IRPAs had a prolonged duration of action, potentially making them suitable for once-daily dosing. Two lead compounds with %Max values of 30 and 40% relative to native insulin were selected for follow up studies in the clinic.

Functionally selective signaling and broad metabolic benefits by novel insulin receptor partial agonists.

Insulin analogs have been developed to treat diabetes with focus primarily on improving the time action profile without affecting ligand-receptor interaction or functional selectivity. As a result, inherent liabilities (e.g. hypoglycemia) of injectable insulin continue to limit the true therapeutic potential of related agents. Insulin dimers were synthesized to investigate whether partial agonism of the insulin receptor (IR) tyrosine kinase is achievable, and to explore the potential for tissue-selective systemic insulin pharmacology. The insulin dimers induced distinct IR conformational changes compared to native monomeric insulin and substrate phosphorylation assays demonstrated partial agonism. Structurally distinct dimers with differences in conjugation sites and linkers were prepared to deliver desirable IR partial agonist (IRPA). Systemic infusions of a B29-B29 dimer in vivo revealed sharp differences compared to native insulin. Suppression of hepatic glucose production and lipolysis were like that attained with regular insulin, albeit with a distinctly shallower dose-response. In contrast, there was highly attenuated stimulation of glucose uptake into muscle. Mechanistic studies indicated that IRPAs exploit tissue differences in receptor density and have additional distinctions pertaining to drug clearance and distribution. The hepato-adipose selective action of IRPAs is a potentially safer approach for treatment of diabetes.

Novel insights from a multiomics dissection of the Hayflick limit.

The process wherein dividing cells exhaust proliferative capacity and enter into replicative senescence has become a prominent model for cellular aging in vitro. Despite decades of study, this cellular state is not fully understood in culture and even much less so during aging. Here, we revisit Leonard Hayflick's original observation of replicative senescence in WI-38 human lung fibroblasts equipped with a battery of modern techniques including RNA-seq, single-cell RNA-seq, proteomics, metabolomics, and ATAC-seq. We find evidence that the transition to a senescent state manifests early, increases gradually, and corresponds to a concomitant global increase in DNA accessibility in nucleolar and lamin associated domains. Furthermore, we demonstrate that senescent WI-38 cells acquire a striking resemblance to myofibroblasts in a process similar to the epithelial to mesenchymal transition (EMT) that is regulated by t YAP1/TEAD1 and TGF-ß2. Lastly, we show that verteporfin inhibition of YAP1/TEAD1 activity in aged WI-38 cells robustly attenuates this gene expression program.

Biexciton and trion dynamics in InP/ZnSe/ZnS quantum dots.

Transient absorption (TA) and time-resolved photoluminescence (PL) spectroscopies have been used to elucidate the hole tunneling and Auger dynamics in biexcitons and negative trions in high-quality InP/ZnSe/ZnS quantum dots (QDs). In a previous paper [Nguyen et al., J. Phys. Chem. C 125, 15405-15414 (2021)], we showed that under high-intensity photoexcitation, two types of biexcitons are formed: those having two conduction band electrons and two valence band holes (designated as an XX state) and those having two conduction band electrons, one valence band hole, and an additional trapped hole (designated as an XT state). In the present paper, we show that both types of biexcitons can undergo Auger processes, with those of the XT state being a factor of four to five slower than those of the XX state. In addition, the trapped holes can undergo tunneling into the valence band, converting an XT state to an XX state. The relative amplitudes of the fast (XX) and slow (XT) components are different in the TA and PL kinetics, and these differences can be quantitatively understood in terms of oscillator strengths and electron-hole overlap integrals of each state. XT to XX hole tunneling rates are obtained from the comparison of the XT state lifetimes with those of the negative trions. This comparison shows that the tunneling times decrease with decreasing core size and shell thickness. These times are about 2 ns for the thinnest shell red-emitting QDs and decrease to 330 ps for QDs that luminesce in the yellow.

Effects of using an abdominal simulator to develop palpatory competencies in 3rd year medical students.

BACKGROUND: Medical school faculty are hard pressed to provide clerkship students with sufficient opportunity to develop and practice their capacity to perform a competent clinical examination, including the palpatory examination of the abdomen. We evaluated the impact of training with an abdominal simulator, AbSim, designed to monitor the depth, location, and thoroughness of their palpation and to provide concurrent and summative feedback regarding their performance. METHODS: All third-year medical students were given the opportunity to develop their palpatory skills with the AbSim simulator during the family medicine rotation. The performance of those who studied with the simulator was measured by its sensors, before and after a training session that included visual feedback regarding the depth and coverage of the student's manual pressure. Additionally, all students reported their confidence in their evolving abdominal palpation skills at the beginning and end of the rotation. RESULTS: 119 (86.9%) of 137 students filled out the initial questionnaire, and 73 (61.3%) studied with the abdominal simulator. The training produced a highly significant improvement in their overall performance (4 measures, p's < 0.001). Pre-training performance (depth calibration and thoroughness of coverage) was not related to the number of months of previous clinical rotations nor to previous internal medicine or surgery rotations. There was little relation between students' confidence in their abdominal examination skills and objective measures of their palpatory performance; however, students who chose the training started with less confidence, and became more confident after training. CONCLUSIONS: Guided abdominal simulator practice increased medical students' capacity to perform an abdominal examination with more appropriate depth and thoroughness of palpation. Interpretation of changes in confidence are uncertain, because confidence was unrelated to objectively measured performance. However, students with low initial confidence in their abdominal examination seemed to be more likely to choose to study with the abdominal simulator.

Provider and Patient-panel Characteristics Associated With Initial Adoption and Sustained Prescribing of Medication for Opioid Use Disorder.

OBJECTIVES: Limited information is available regarding provider- and patient panel-level factors associated with primary care provider (PCP) adoption/prescribing of medication for opioid use disorder (MOUD). METHODS: We assessed a retrospective cohort from 2015 to 2018 within the Pennsylvania Medicaid Program. Participants included PCPs who were Medicaid providers, with no history of MOUD provision, and who treated ≥10 Medicaid enrollees annually. We assessed initial MOUD adoption, defined as an index buprenorphine/buprenorphine-naloxone or oral/extended release naltrexone fill and sustained prescribing, defined as ≥1 MOUD prescription(s) for 3 consecutive quarters from the PCP. Independent variables included provider- and patient panel-level characteristics. RESULTS: We identified 113 rural and 782 urban PCPs who engaged in initial adoption and 36 rural and 288 urban PCPs who engaged in sustained prescribing. Rural/urban PCPs who issued increasingly larger numbers of antidepressant and antipsychotic medication prescriptions had greater odds of initial adoption and sustained prescribing (P < 0.05) compared to those that did not prescribe these medications. Further, each additional patient out of 100 with opioid use disorder diagnosed before MOUD adoption increased the adjusted odds for initial adoption 2% to 4% (95% confidence interval [CI] = 1.01-1.08) and sustained prescribing by 4% to 7% (95% CI = 1.01-1.08). New Medicaid providers in rural areas were 2.52 (95% CI = 1.04-6.11) and in urban areas were 2.66 (95% CI = 1.94, 3.64) more likely to engage in initial MOUD adoption compared to established PCPs. CONCLUSIONS: MOUD prescribing adoption was concentrated among PCPs prescribing mental health medications, caring for those with OUD, and new Medicaid providers. These results should be leveraged to test/implement interventions targeting MOUD adoption among PCPs.

Health Plans Struggle to Report on Depression Quality Measures That Require Clinical Data.

OBJECTIVE: Depression quality measures aligned with evidence-based practices require that health care organizations use standardized tools for tracking and monitoring patient-reported symptoms and functioning over time. This study describes challenges and opportunities for reporting 5 HEDIS measures which use electronic clinical data to assess adolescent and perinatal depression care quality. METHODS: Two learning collaboratives were convened with 10 health plans from 5 states to support reporting of the depression measures. We conducted content analysis of notes from collaborative meetings and individual calls with health plans to identify key challenges and strategies for reporting. RESULTS: Health plans used various strategies to collect the clinical data needed to report the measures, including setting up direct data exchange with providers and data aggregators and leveraging data captured in health information exchanges and case management records. Health plans noted several challenges to reporting and performance improvement: 1) lack of access to clinical data sources where the results of patient-reported tools were documented; 2) unavailability of the results of patient-reported tools in usable data fields; 3) lack of routine depression screening and ongoing assessment occurring in provider practices. CONCLUSIONS: Our findings demonstrate ongoing challenges in collecting and using patient-reported clinical data for health plan quality measurement. Systems to track and improve outcomes for individuals with depression will require significant investments and policy support at the point of care and across the healthcare system.