Acupressure to Reduce Treatment-Related Symptoms for Children With Cancer and Recipients of Hematopoietic Stem Cell Transplant: Protocol for a Randomized Controlled Trial.

BackgroundWe describe the study design and protocol of a pragmatic randomized controlled trial (RCT) Acupressure for Children in Treatment for a Childhood Cancer (ACT-CC).ObjectiveTo describe the feasibility and effectiveness of an acupressure intervention to decrease treatment-related symptoms in children in treatment for cancer or recipients of a chemotherapy-based hematopoietic stem cell transplant (HSCT).DesignTwo-armed RCTs with enrollment of 5 to 30 study days.SettingTwo pediatric teaching hospitals.PatientsEighty-five children receiving cancer treatment or a chemotherapy-based HSCT each with 1 parent or caregiver.InterventionPatients are randomized 1:1 to receive either usual care plus daily professional acupressure and caregiver delivered acupressure versus usual care alone for symptom management. Participants receive up to 20 professional treatments.Main outcomeA composite nausea/vomiting measure for the child.Secondary outcomesChild's nausea, vomiting, pain, fatigue, depression, anxiety, and positive affect.Parent outcomesDepression, anxiety, posttraumatic stress symptoms, caregiver self-efficacy, and positive affect. Feasibility of delivering the semistandardized intervention will be described. Linear mixed models will be used to compare outcomes between arms in children and parents, allowing for variability in diagnosis, treatment, and age.DiscussionTrial results could help childhood cancer and HSCT treatment centers decide about the regular inclusion of trained acupressure providers to support symptom management

Time-Course Analysis of Cyanobacterium Transcriptome: Detecting Oscillatory Genes

The microarray technique allows the simultaneous measurements of the expression levels of thousands of mRNAs. By mining these data one can identify the dynamics of the gene expression time series. The detection of genes that are periodically expressed is an important step that allows us to study the regulatory mechanisms associated with the circadian cycle. The problem of finding periodicity in biological time series poses many challenges. Such challenge occurs due to the fact that the observed time series usually exhibit non-idealities, such as noise, short length, outliers and unevenly sampled time points. Consequently, the method for finding periodicity should preferably be robust against such anomalies in the data. In this paper, we propose a general and robust procedure for identifying genes with a periodic signature at a given significance level. This identification method is based on autoregressive models and the information theory. By using simulated data we show that the suggested method is capable of identifying rhythmic profiles even in the presence of noise and when the number of data points is small. By recourse of our analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis

Changes in Mood States and Biomarkers During Peginterferon and Ribavirin Treatment of Chronic Hepatitis C

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74953/1/j.1572-0241.2008.02106.x.pd

Differences in COVID-19 Outcomes Among Patients With Type 1 Diabetes: First vs Later Surges

Background Outcomes of the novel coronavirus SARS-CoV-2 (COVID-19) have improved throughout the pandemic. However, whether outcomes of COVID-19 in the type 1 diabetes (T1D) population improved over time is unknown. Therefore, we aim to investigate differences in COVID-19 outcomes for patients with T1D in the US. Method We analyzed data collected via a registry of patients with T1D and COVID-19 from 56 sites between April 2020 and January 2021. First, we grouped cases into First Surge (04/09/2020 - 07/31/2020, n=188) and Late Surge (08/01/2020 - 01/31/2021, n=410). Then, we compared outcomes between both groups using descriptive statistics and logistic regression models. Results Adverse outcomes were more frequent during the first surge including Diabetic Ketoacidosis (32% versus 15%, p<0.001), severe hypoglycemia (4% versus 1%, p=0.04) and hospitalization (52% versus 22%, p<0.001). The First surge cases were older (28 +/- 18.8 years versus 18.8 +/- 11.1 years, p<0.001), had higher hemoglobin A1c (HbA1c) levels (Median (IQR): 9.3 (4.0) versus 8.4(2.8), <0.001) and use public insurance (n(%): 107 (57) versus 154 (38), p <0.001). There were five times increased odds of hospitalization for adults (OR 5.01 (2.11,12.63) in the first surge compared to the late surge. Conclusion COVID-19 cases among patients with T1D reported during the first surge had a higher proportion of adverse outcomes than those presented in a later surge

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them