Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes.

BACKGROUND AND OBJECTIVES: Musculoskeletal (MSK) complaints comprise more than 20% of all visits to health care providers each year. Despite required experiences in MSK care, family physicians report low confidence in diagnosing and treating MSK conditions. The purpose of this study was to analyze the effects of early and longitudinal exposure to MSK education on residents confidence in and likelihood of performing MSK physical exams and injections in future practice. METHODS: From 2017 to 2019, residents completed an annual survey assessing confidence in, frequency of, and future intentions to perform exams and injections for MSK conditions. We compared responses between family medicine residents who completed a 176-hour longitudinal sports medicine (LSM) curriculum distributed over all 3 years of residency and a comparable cohort of family medicine residents who completed a 188-hour concentrated MSK curriculum primarily in the final year of residency. We made comparisons using the Fisher exact test for categorical variables and an independent samples t test for numeric variables. RESULTS: We analyzed the 98 total responses from 50 residents. The proportion of residents reporting high ratings of their residency MSK education (26% to 60%), performing >5 injections (38% to 73%), reporting confidence in performing injections (12% to 40%), and indicating likelihood to perform MSK injections in the future (52% to 65%) were all greater in the LSM versus concentrated MSK curriculum cohorts (P<.05 for all). CONCLUSIONS: Early and longitudinal exposure to MSK care and sports medicine in family medicine residency led to both an increase in MSK injections during residency training and a greater desire to perform these injections in postresidency practice.

Continuous-time birth-death-shift (BDS) processes are frequently used in stochastic modeling, with many applications in ecology and epidemiology. In particular, such processes can model evolutionary dynamics of transposable elements-important genetic markers in molecular epidemiology. Estimation of the effects of individual covariates on the birth, death, and shift rates of the process can be accomplished by analyzing patient data, but inferring these rates in a discretely and unevenly observed setting presents computational challenges. We propose a multi-type branching process approximation to BDS processes and develop a corresponding expectation maximization algorithm, where we use spectral techniques to reduce calculation of expected sufficient statistics to low-dimensional integration. These techniques yield an efficient and robust optimization routine for inferring the rates of the BDS process, and apply broadly to multi-type branching processes whose rates can depend on many covariates. After rigorously testing our methodology in simulation studies, we apply our method to study intrapatient time evolution of IS6110 transposable element, a genetic marker frequently used during estimation of epidemiological clusters of Mycobacterium tuberculosis infections.

Objective The purpose of this study was to analyze the effect of the coronavirus disease 2019 (COVID-19) on injury prevalence in National Collegiate Athletic Association (NCAA) varsity athletes following mandatory state-issued stay-at-home orders in March 2020. A secondary objective was to evaluate the relationship between COVID-19 infection and injury prevalence. Methods The respondents were recruited during pre-participation evaluations held at a Division I university in California in the summer of 2021, as well as via emails shared by athletic trainers at the institution. Data was collected using the Qualtrics Survey Platform (Qualtrics, Provo, UT). For all questions regarding the effects of the COVID-19 pandemic, the participants were asked to compare March 2020-March 2021 (post-pandemic) to March 2019-March 2020 (pre-pandemic). Injury was defined as a physical complaint or condition sustained by an athlete during participation in training or competition that resulted in at least one missed day of practice or competition. The study participants were also asked to disclose their history of laboratory-confirmed COVID-19 infection. Results One hundred forty-six respondents completed the survey, with a 72.3% response rate. Of the respondents, 33.6% (n=49) reported sustaining at least one injury in the year preceding the pandemic, whereas 45.2% (n=66) of respondents reported sustaining at least one injury within the first year of the pandemic, a 34.5% relative increase in injuries (RR=1.35; 95% CI=1.01, 1.80). There was no significant difference in the number of upper body (RR=1.64; 95% CI=0.8, 3.34; p=0.177) versus lower body (RR=1.31; 95% CI=0.94, 1.82; p=0.11) injuries before and after the pandemic onset. Thirty-two respondents reported a history of COVID-19 infection. The athletes who reported a prior COVID-19 diagnosis were no more likely than the athletes with no prior COVID-19 diagnosis to obtain an injury from March 2020 to February 2021 (p=0.85). Conclusion This study indicates that the COVID-19 pandemic and stay-at-home orders were associated with a greater risk of injury in this cohort of collegiate athletes. Interestingly, a history of laboratory-confirmed COVID-19 infection was not associated with increased risk of injury.

Background Although the coronavirus disease 2019 (COVID-19) pandemic had pervasive effects on the lives of individuals, its influence on the mental health of collegiate athletes remains unknown. This study aimed to assess changes in mental health and substance use in National Collegiate Athlete Association (NCAA) Division I athletes in Southern California during the COVID-19 pandemic. Methodology An online survey was created using the Qualtrics software (Qualtrics, Provo, Utah). NCAA Division I athletes in Southern California completed preseason surveys querying indices of mental health, substance use, and injury in the year before the COVID-19 pandemic (March 2019 to March 2020) and during the pandemic (March 2020 to March 2021). The athletes filled out the survey from June 2021 to September 2021. Participants were asked how likely they were to agree with the following statements: I have felt physically prepared for athletic competitions, I have been satisfied with my mental health, and I have had adequate sleep. Participants were also asked to compare their substance use between the two time periods. Sociodemographic information regarding participants age, gender, sports team, as well as year in sport and school was also collected. Group comparison analyses were performed using Fishers exact test. Correlations between mental health measures and other variables were examined using Spearmans correlation coefficients. Results A total of 189 athletes completed the survey (out of the 259 surveys that were started). Females were significantly less likely to feel satisfied with mental health (p < 0.01) and physically prepared for sport (p < 0.01). Across all respondents, satisfaction with mental health was positively correlated with adequate sleep (p < 0.01) and physical preparedness for sport (p < 0.01) and negatively correlated with injury (p < 0.05). There was no significant correlation between mental health status and history of COVID-19 infection (p = 0.84). The vast majority of athletes reported no significant change in substance use pre- to post-pandemic, with no differences according to sex. Conclusions The COVID-19 pandemic had a differential impact on the mental health of female versus male NCAA athletes. Mental health was correlated with sleep, physical preparedness, and being injury-free but not with a history of COVID-19 infection. Despite reports indicating increased substance use in the general population, athletes in this group reported no change in licit and illicit substance use.

Single-cell lineage tracking strategies enabled by recent experimental technologies have produced significant insights into cell fate decisions, but lack the quantitative framework necessary for rigorous statistical analysis of mechanistic models describing cell division and differentiation. In this paper, we develop such a framework with corresponding moment-based parameter estimation techniques for continuous-time, multi-type branching processes. Such processes provide a probabilistic model of how cells divide and differentiate, and we apply our method to study hematopoiesis, the mechanism of blood cell production. We derive closed-form expressions for higher moments in a general class of such models. These analytical results allow us to efficiently estimate parameters of much richer statistical models of hematopoiesis than those used in previous statistical studies. To our knowledge, the method provides the first rate inference procedure for fitting such models to time series data generated from cellular barcoding experiments. After validating the methodology in simulation studies, we apply our estimator to hematopoietic lineage tracking data from rhesus macaques. Our analysis provides a more complete understanding of cell fate decisions during hematopoiesis in nonhuman primates, which may be more relevant to human biology and clinical strategies than previous findings from murine studies. For example, in addition to previously estimated hematopoietic stem cell self-renewal rate, we are able to estimate fate decision probabilities and to compare structurally distinct models of hematopoiesis using cross validation. These estimates of fate decision probabilities and our model selection results should help biologists compare competing hypotheses about how progenitor cells differentiate. The methodology is transferrable to a large class of stochastic compartmental and multi-type branching models, commonly used in studies of cancer progression, epidemiology and many other fields.

Birth-death processes track the size of a univariate population, but many biological systems involve interaction between populations, necessitating models for two or more populations simultaneously. A lack of efficient methods for evaluating finite-time transition probabilities of bivariate processes, however, has restricted statistical inference in these models. Researchers rely on computationally expensive methods such as matrix exponentiation or Monte Carlo approximation, restricting likelihood-based inference to small systems, or indirect methods such as approximate Bayesian computation. In this paper, we introduce the birth/birth-death process, a tractable bivariate extension of the birth-death process, where rates are allowed to be nonlinear. We develop an efficient algorithm to calculate its transition probabilities using a continued fraction representation of their Laplace transforms. Next, we identify several exemplary models arising in molecular epidemiology, macro-parasite evolution, and infectious disease modeling that fall within this class, and demonstrate advantages of our proposed method over existing approaches to inference in these models. Notably, the ubiquitous stochastic susceptible-infectious-removed (SIR) model falls within this class, and we emphasize that computable transition probabilities newly enable direct inference of parameters in the SIR model. We also propose a very fast method for approximating the transition probabilities under the SIR model via a novel branching process simplification, and compare it to the continued fraction representation method with application to the 17th century plague in Eyam. Although the two methods produce similar maximum a posteriori estimates, the branching process approximation fails to capture the correlation structure in the joint posterior distribution.

The University of California San Diego (UCSD) School of Medicine (SOM) is transitioning its third-year primary care curriculum from a year-long longitudinal primary care course to a three-week clerkship in Family Medicine (FM). Additionally, there is a lack of FM physicians in the US, and limited information on what factors affect students’ decisions to enter FM. The aim of this pilot study is to analyze the effects of introducing sub-specialty tracks within an FM clerkship on student attitudes towards FM. A limiting factor for students within FM clerkships is that often they are not exposed to the full spectrum of FM. The aim of the tracks is to demonstrate that there are many FM clinicians practicing what may be considered more specialized aspects of primary care, including sports, sexual and reproductive health, and lifestyle and integrative medicine. There is a pre-existing family medicine clerkship for fourth-year medical students (FPM 426), which will serve as the pilot program. Three subspecialty tracks (sports medicine, sexual and reproductive health, and lifestyle and integrative medicine) will be introduced. Students will be assigned a track based on interest. A student will not be assigned a track if they did not express interest or if there was insufficient space to accommodate. Students not assigned a track will serve as the control group for this study. At the end of the clerkship, students will be emailed an anonymous survey to complete, and time will be provided during the course to complete the survey. The post-clerkship survey will collect data on students’ experience of the clerkship and perceptions of FM. We hypothesize that students placed in the subspecialty tracks will report a better experience during their clerkship and an expanded understanding of the scope of practice of family physicians. Comparisons will be made between students within tracks and those not in a track, who will serve as the control.

Precise genetic modifications in model animals are essential for biomedical research. Here, we report a programmable "base editing" system to induce precise base conversion with high efficiency in zebrafish. Using cytidine deaminase fused to Cas9 nickase, up to 28% of site-specific single-base mutations are achieved in multiple gene loci. In addition, an engineered Cas9-VQR variant with 5'-NGA PAM specificities is used to induce base conversion in zebrafish. This shows that Cas9 variants can be used to expand the utility of this technology. Collectively, the targeted base editing system represents a strategy for precise and effective genome editing in zebrafish.The use of base editing enables precise genetic modifications in model animals. Here the authors show high efficient single-base editing in zebrafish using modified Cas9 and its VQR variant with an altered PAM specificity.

Devoid of all known canonical actin-binding proteins, the prevalent parasite Giardia lamblia uses an alternative mechanism for cytokinesis. Unique aspects of this mechanism can potentially be leveraged for therapeutic development. Here, live-cell imaging methods were developed for Giardia to establish division kinetics and the core division machinery. Surprisingly, Giardia cytokinesis occurred with a median time that is ∼60 times faster than mammalian cells. In contrast to cells that use a contractile ring, actin was not concentrated in the furrow and was not directly required for furrow progression. Live-cell imaging and morpholino depletion of axonemal Paralyzed Flagella 16 indicated that flagella-based forces initiated daughter cell separation and provided a source for membrane tension. Inhibition of membrane partitioning blocked furrow progression, indicating a requirement for membrane trafficking to support furrow advancement. Rab11 was found to load onto the intracytoplasmic axonemes late in mitosis and to accumulate near the ends of nascent axonemes. These developing axonemes were positioned to coordinate trafficking into the furrow and mark the center of the cell in lieu of a midbody/phragmoplast. We show that flagella motility, Rab11, and actin coordination are necessary for proper abscission. Organisms representing three of the five eukaryotic supergroups lack myosin II of the actomyosin contractile ring. These results support an emerging view that flagella play a central role in cell division among protists that lack myosin II and additionally implicate the broad use of membrane tension as a mechanism to drive abscission.