Avulsion fractures of the pediatric knee

Although avulsion fractures of the pediatric knee are uncommon, they are important injuries to recognize because they are frequently associated with adjacent soft-tissue and osteocartilaginous abnormalities. Related injuries, which include entrapment of soft-tissue structures, intra-articular fracture extension, and intra-articular loose bodies, can complicate or alter therapy. The most commonly affected soft-tissue structures include the cruciate ligaments, collateral ligaments and supporting tendons, and extensor mechanism and retinacula. The purpose of this pictorial essay is to review avulsion fractures of the pediatric knee and to highlight associated injuries.     

Gender medicine: Lessons from COVID-19 and other medical conditions for designing health policy

Gender-specific differences in the prevalence, incidence, comorbidities, prognosis, severity, risk factors, drug-related aspects and outcomes of various medical conditions are well documented. We present a literature review on the extent to which research in this field has developed over the years, and reveal gaps in gender-sensitive awareness between the clinical portrayal and the translation into gender-specific treatment regimens, guidelines and into gender-oriented preventive strategies and health policies. Subsequently, through the lens of gender, we describe these domains in detail for four selected medical conditions: Asthma, obesity and overweight, chronic kidney disease and coronavirus disease 2019. As some of the key gender differences become more apparent during adolescence, we focus on this developmental stage. Finally, we propose a model which is based on three influential issues: (1) Investigating gender-specific medical profiles of related health conditions, rather than a single disease; (2) The dynamics of gender disparities across developmental stages; and (3) An integrative approach which takes into account additional risk factors (ethnicity, socio-demographic variables, minorities, lifestyle habits etc.). Increasing the awareness of gender-specific medicine in daily practice and in tailored guidelines, already among adolescents, may reduce inequities, facilitate the prediction of future trends and properly address the characteristics and needs of certain subpopulations within each gender.     

Feasibility Study of Automated Overnight Closed-Loop Glucose Control Under MD-Logic Artificial Pancreas in Patients with Type 1 Diabetes: The DREAM Project

Abstract Background: Artificial pancreas systems may offer a potential major impact on the normalization of metabolic control and preventing hypoglycemic events. This study aims to establish near-normal overnight glucose control and reduce the risk of nocturnal hypoglycemia using the MD-Logic Artificial Pancreas (MDLAP), an algorithm that was developed by our research group. This inpatient feasibility study is the first step towards implementing an overnight closed-loop MDLAP system at the patient's home. Subjects and Methods: Seven patients with type 1 diabetes (three adolescents and four adults; mean±SD age, 20.6±4.7 years; duration of diabetes, 9.6±2.6 years; body mass index, 24.3±3.9 kg/m(2); and glycated hemoglobin, 7.8±0.8%) participated in a total of 14 closed-loop overnight sessions. Each participant underwent two closed-loop inpatient sessions starting at dinner alone and at dinner following exercise. The closed-loop inpatient sessions were compared with data derived from nights spent at home with an open-loop system in a similar scenario to the study protocol. Results: The mean percentage of time spent in the near normal glucose range of 63-140?mg/dL was 83±16%, and the median (interquartile range) was 85% (78-92%) for the overnight closed-loop sessions compared with 34±31% and 27% (6-57%) in the homecare open-loop setting, respectively. During the overnight closed-loop sessions at dinner alone 92±9% of the sensor values ranged within target range, compared with 73±19% for the sessions following exercise (P=0.03). No hypoglycemic (<63?mg/dL) events occurred during the closed-loop sessions. Conclusion: Closed-loop insulin delivery under MDLAP is a feasible and safe solution to control overnight glycemia.     

Individual changes in T lymphocyte parameters of old human subjects

Parameters of peripheral blood T lymphocytes were determined repeatedly (twice, 2-4 weeks apart), in ten old (78 + 5) and compared to nine young (31 + 5) human subjects. Assays included percentage of total, helper, and suppressor, T lymphocytes, and the reaction to PHA stimulation for 24, 48, 72, and 96 h, as assessed by levels of proliferation and IL-2 production. A lower response to PHA was observed in the old as compared to the young, with no significant changes in T cell subsets. A marked variability was noted between the results of the first and second determinations of the response to PHA in each individual. The lack of correlation between the two determinations was more prominent in the old. Unresponsiveness to PHA throughout the incubation period, was noted in two old subjects, but, in only one of the two determinations. This transient unresponsiveness was not accompanied by any changes in their clinical state. Thus, establishments of the immune status of the aged should be based on at least two repeated determinations.     

Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates

Patterns of sequencing coverage along a bacterial genome—summarized by a peak-to-trough ratio (PTR)—have been shown to accurately reflect microbial growth rates, revealing a new facet of microbial dynamics and host–microbe interactions. Here, we introduce Compute PTR (CoPTR): a tool for computing PTRs from complete reference genomes and assemblies. Using simulations and data from growth experiments in simple and complex communities, we show that CoPTR is more accurate than the current state of the art while also providing more PTR estimates overall. We further develop a theory formalizing a biological interpretation for PTRs. Using a reference database of 2935 species, we applied CoPTR to a case-control study of 1304 metagenomic samples from 106 individuals with inflammatory bowel disease. We show that growth rates are personalized, are only loosely correlated with relative abundances, and are associated with disease status. We conclude by showing how PTRs can be combined with relative abundances and metabolomics to investigate their effect on the microbiome.

Dynamic changes in the human microbiome play a fundamental role in our health. Understanding how and why these changes occur can help uncover mechanisms of disease. In line with this goal, the Integrative Human Microbiome Project and others have generated longitudinal data sets from disease cohorts in which the microbiome has been observed to play a role (Buffie et al. 2015; DiGiulio et al. 2015; Lloyd-Price et al. 2019; Serrano et al. 2019; Zhou et al. 2019). Yet, investigating microbiome dynamics is challenging. On one hand, a promising line of investigation uses time-series or dynamical systems–based models to investigate community dynamics (Stein et al. 2013; Bucci et al. 2016; Gibbons et al. 2017; Gibson and Gerber 2018; Shenhav et al. 2019; Joseph et al. 2020). On the other hand, the resolution of such methods is limited by sampling frequency, which is often limited by physiological constraints on sample collection for DNA sequencing. Furthermore, although such methods accurately infer changes in abundance, they do not directly assess growth rates per sample.Korem et al. (2015) introduced a complementary approach to investigate microbiome dynamics. They showed that sequencing coverage of a given species in a metagenomic sample reflects its growth rate. They summarized growth rates by a metric called the peak-to-trough ratio (PTR): the ratio of sequencing coverage near the replication origin and near the replication terminus. Thus, PTRs provide a snapshot of growth at the time of sampling, and their resolution is not limited by sampling frequency.Their original method—PTRC—estimates PTRs using reads mapped to complete reference genomes. It has been used as a gold standard to evaluate other methods (Brown et al. 2016; Emiola and Oh 2018; Gao and Li 2018). However, most species lack complete reference genomes, reducing PTRC''s utility to researchers in the field. Therefore, follow-up work has focused on estimating PTRs from draft assemblies: short sections of contiguous sequences (contigs) in which the order of contigs along the genome is unknown. These approaches rely on reordering binned read counts or contigs by estimating their distance to the replication origin. Although less accurate than PTRC, they allow PTRs to be estimated for a larger number of species. iRep (Brown et al. 2016) sorts binned read counts along a 5-kb sliding window and then fits a log-linear model to the sorted bins to estimate a PTR. GRiD (Emiola and Oh 2018) sorts the contigs themselves by sequencing coverage. It fits a curve to the log sequencing coverage of the sorted contigs using Tukey''s biweight function. DEMIC (Gao and Li 2018) also sorts contigs. However, it uses sequencing coverage across multiple samples to infer a contig''s distance from the replication origin. Specifically, DEMIC performs a principal component analysis on the log contig coverage across samples. The investigators show that the scores along the first principal component correlate with distance from the replication origin. Ma et al. (2021) provide theoretical criteria for when such an approach is optimal. Finally, other estimators have focused on PTR estimation for specific strains (Emiola et al. 2020) or on estimation using circular statistics (Suzuki and Yamada 2020).Nonetheless, using PTRs has several limitations. From a theoretical perspective, it is not clear what PTRs estimate and how they should be interpreted. Bremer and Churchward (1977) showed that under exponential growth, PTRs measure the ratio of chromosome replication time to generation time, but this is not established under arbitrary models of dynamics. From a practical perspective, estimating PTRs at scale requires running multiple tools across multiple computational environments—a cumbersome task.In the present work, we seek to address these issues. Our contributions are threefold. First, we provide theory that shows PTRs measure the rate of DNA synthesis and generation time, regardless of the underlying dynamic model. Second, we derive two estimators for PTRs—one for complete reference genomes and one for draft assemblies. Third, we combine our estimators in an easy-to-use tool called Compute PTR (CoPTR). CoPTR provides extensive documentation, a tutorial, and precomputed reference databases for its users. We show that CoPTR is more accurate than the current state of the art and conclude with a large-scale application to a data set of 1304 metagenomic samples from a study of inflammatory bowel disease (IBD).