Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation.

Sequence-based machine-learning models trained on genomics data improve genetic variant interpretation by providing functional predictions describing their impact on the cis-regulatory code. However, current tools do not predict RNA-seq expression profiles because of modeling challenges. Here, we introduce Borzoi, a model that learns to predict cell-type-specific and tissue-specific RNA-seq coverage from DNA sequence.

How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities.

The cell is arguably the most fundamental unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determining the root causes of disease. Recent advances in artificial intelligence (AI), combined with the ability to generate large-scale experimental data, present novel opportunities to model cells.

Angular Momentum Fine Structure in InP/ZnSe Quantum Dots.

There is a large experimental and theoretical literature on the angular momentum fine structure of the lowest energy exciton in InP-based quantum dots. This literature is highly contradictory, and no clear picture of the fine structure accounting for all these results is available. This paper presents a quantitative analysis of recently published luminescence anisotropy results and presents an analysis of the different proposed fine structure models that compares radiative lifetimes calculated from those models with experimental values.

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

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 '. May these essays encourage readers to find their own creative spark in medicine.

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.

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.

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.

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

A recent Letter in this Journal (Langhals and Schlücker, . , 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.

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.

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.

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 EC values remained in sub-nM range.

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.

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.

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.

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.

Radiative dynamics and delayed emission in pure and doped InP/ZnSe/ZnS quantum dots.

We have used time-correlated single photon counting to elucidate the radiative dynamics of InP/ZnSe/ZnS core/shell/shell quantum dots (QDs) that differ in the amount and distribution of excess indium. Stoichiometric QDs having an In:P atom ratio very near unity exhibit simple luminescence kinetics. The photoluminescence (PL) rises with the 40 ps instrument response function and exhibits a decay that is close to a single exponential with a time constant that decreases from 32 to 28 ns with increasing shell thickness.

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.

Effective gene expression prediction from sequence by integrating long-range interactions.

How noncoding DNA determines gene expression in different cell types is a major unsolved problem, and critical downstream applications in human genetics depend on improved solutions. Here, we report substantially improved gene expression prediction accuracy from DNA sequences through the use of a deep learning architecture, called Enformer, that is able to integrate information from long-range interactions (up to 100 kb away) in the genome. This improvement yielded more accurate variant effect predictions on gene expression for both natural genetic variants and saturation mutagenesis measured by massively parallel reporter assays.