Respiratory Muscle Durability Fresh Engineering for quick Assessment
Anti-PD-1 immunotherapy has recently shown tremendous success for the treatment of several aggressive cancers. However, variability and unpredictability in treatment outcome have been observed, and are thought to be driven by patient-specific biology and interactions of the patient's immune system with the tumor. Here we develop an integrative systems biology and machine learning approach, built around clinical data, to predict patient response to anti-PD-1 immunotherapy and to improve the response rate. Using this approach, we determine biomarkers of patient response and identify potential mechanisms of drug resistance. We develop systems biology informed neural networks (SBINN) to calculate patient-specific kinetic parameter values and to predict clinical outcome. selleck chemicals llc We show how transfer learning can be leveraged with simulated clinical data to significantly improve the response prediction accuracy of the SBINN. Further, we identify novel drug combinations and optimize the treatment protocol for triple combination therapy consisting of IL-6 inhibition, recombinant IL-12, and anti-PD-1 immunotherapy in order to maximize patient response. We also find unexpected differences in protein expression levels between response phenotypes which complement recent clinical findings. Our approach has the potential to aid in the development of targeted experiments for patient drug screening as well as identify novel therapeutic targets.
A detailed characterization of patients with COVID-19 living with obesity has not yet been undertaken. We aimed to describe and compare the demographics, medical conditions, and outcomes of COVID-19 patients living with obesity (PLWO) to those of patients living without obesity.
We conducted a cohort study based on outpatient/inpatient care and claims data from January to June 2020 from Spain, the UK, and the US. We used six databases standardized to the OMOP common data model. We defined two non-mutually exclusive cohorts of patients diagnosed and/or hospitalized with COVID-19; patients were followed from index date to 30 days or death. We report the frequency of demographics, prior medical conditions, and 30-days outcomes (hospitalization, events, and death) by obesity status.
We included 627 044 (Spain 122 058, UK 2336, and US 502 650) diagnosed and 160 013 (Spain 18 197, US 141 816) hospitalized patients with COVID-19. The prevalence of obesity was higher among patients hospitalized (39.9%, 95%CI 39tive strategies of COVID-19 infection and complications and generating hypotheses for causal inference studies.
COVID-19-related school closures may increase the prevalence of childhood obesity, which has aroused public concerns. We aimed to analyze the weight and height changes in Chinese preschool children during the COVID-19-related school closures period.
A total of 124,603 children from multi-city kindergartens in China were included in this study. We evaluated the prevalence of overweight and obese in preschool children experienced school closures, and compared the changes in BMI, weight, and height of preschool children among COVID-19 school closures period, the same period last year and the same period the year before last.
After the school closures, childhood obesity prevalence increased, whereas overweight prevalence decreased. During school closures, the average increase in height was about 1 cm less as compared with the same period last year and the year before last, but no noteworthy difference in the weight change was observed among the three periods.
During COVID-19 school closures, children's height increase seemed to be more affected than weight change. Innovative, robust, and highly adaptable strategies should be taken to increase physical activity, reduce sedentary time and promote healthy diets, to minimize the adverse impact of school closures.
During COVID-19 school closures, children's height increase seemed to be more affected than weight change. Innovative, robust, and highly adaptable strategies should be taken to increase physical activity, reduce sedentary time and promote healthy diets, to minimize the adverse impact of school closures.
In adults, cardiovascular risk factors are known to be associated with brain health. We hypothesized that these associations are already present at school-age. We examined the associations of adverse body fat measures and cardiovascular risk factors with brain structure, including volumetric measures and white matter microstructure, in 10-year-old children.
We performed a cross-sectional analysis in a population-based prospective cohort study in Rotterdam, the Netherlands. Analyses were based on 3098 children aged 10 years with neuroimaging data and at least one measurement of body fat and cardiovascular risk factors. Body fat measures included body mass index (BMI), fat mass index and android fat mass percentage obtained by Dual-energy X-ray absorptiometry. Cardiovascular risk factors included blood pressure, and serum glucose, insulin and lipids blood concentrations. Structural neuroimaging, including global and regional brain volumes, was quantified by magnetic resonance imaging. DTI was used to assesseasures, but not other cardiovascular risk factors, were associated with structural neuroimaging outcomes in school-aged children. Prospective studies are needed to assess causality, direction and long-term consequences of the associations.
Fecal microbiome disturbances are linked to different human diseases. In the case of obesity, gut microbiota seems to play a role in the development of low-grade inflammation. The purpose of the present study was to identify specific bacterial families and genera associated with an increased obesity-related inflammatory status, which would allow to build a regression model for the prediction of the inflammatory status of obese and overweight subjects based on fecal microorganisms.
A total of 361 volunteers from the Obekit trial (65 normal-weight, 110 overweight, and 186 obese) were classified according to four variables waist/hip ratio (≥0.86 for women and ≥1.00 for men), leptin/adiponectin ratio (LAR, ≥3.0 for women and ≥1.4 for men), and plasma C-reactive protein (≥2 mg/L) and TNF levels (≥0.85 pg/mL). An inflammation score was designed to classify individuals in low (those subjects who did exceed the threshold value in 0 or 1 variable) or high inflammatory index (those subjects who did exceed the threshold value in 2 or more variables).