Preoperative Exercise during Neoadjuvant Therapy for Pancreatic Cancer: A Pilot Study

Exercise improves cancer treatment outcomes including health-related quality of life and physical functioning. Patients with pancreatic cancer are generally older adults, and frailty and cachexia are prevalent. Chemotherapy and chemoradiation are increasingly administered prior to pancreatic cancer surgery, and sarcopenia has been shown to accompany these therapies. Preoperative exercise may improve health, well-being, and perioperative outcomes among patients undergoing preoperative therapy for pancreatic cancer. The purpose of this pilot study was to determine the feasibility of exercise in this context. Feasibility was defined as patients completing, on average, 60% of recommended weekly exercise minutes. Twenty patients (M=64 years old, SD=9.9; 42% female) enrolled in a home-based exercise program during preoperative therapy (chemotherapy and/or chemoradiation and preoperative “rest”, M=21.2 weeks total, SD=16.4). Exercise recommendations included moderate-intensity walking for 20-30 minutes/day on ≥3 days/week and moderate-intensity resistance exercises for 30-45 minutes/day on ≥2 days/week. Exercise recommendations (120 minutes of moderate-intensity activity/week) were based on American College of Sports Medicine and American Cancer Society recommendations (150 minutes of moderate-intensity activity/week), but reduced due to patients’ older age and concurrent preoperative therapy. Resistance exercises targeted upper body, lower body, and abdominal muscles, and patients were instructed to perform 3 sets of 8-12 repetitions of multiple exercises for each region during each session. Patients received Yamax Digiwalker pedometers, graded resistance tube sets, and booklets and DVDs with instructions and safety tips. Research staff provided detailed instructions and resistance exercise demonstrations at enrollment and monitored and encouraged adherence with biweekly phone calls. Patients recorded minutes of walking and resistance exercise in daily logs. On average, patients reported 73.9 minutes of walking (\u3e100% of recommendation, SD=72.4) and 43.1 minutes of resistance exercise per week (71.8% of recommendation, SD=39.0). Patients reported the most walking during chemoradiation (M=94.7 minutes/week, SD=104.3), followed by preoperative “rest” (M=77.4 minutes/week, SD=80.4), and chemotherapy (M=70.8 minutes/week, SD=75.2). Patients reported the most resistance exercise during the preoperative “rest” period (M=51.6 minutes/week, SD=52.3), followed by chemoradiation (M=38.0 minutes/week, SD=36.8), and chemotherapy (M=31.1 minutes/week, SD=38.1). Walking and resistance exercise are feasible for patients undergoing preoperative therapy for pancreatic cancer. Varying levels of fatigue and treatment-related side effects may affect exercise during different treatment phases

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

The nonperturbative functional renormalization group and its applications

The renormalization group plays an essential role in many areas of physics, both conceptually and as a practical tool to determine the long-distance low-energy properties of many systems on the one hand and on the other hand search for viable ultraviolet completions in fundamental physics. It provides us with a natural framework to study theoretical models where degrees of freedom are correlated over long distances and that may exhibit very distinct behavior on different energy scales. The nonperturbative functional renormalization-group (FRG) approach is a modern implementation of Wilson's RG, which allows one to set up nonperturbative approximation schemes that go beyond the standard perturbative RG approaches. The FRG is based on an exact functional flow equation of a coarse-grained effective action (or Gibbs free energy in the language of statistical mechanics). We review the main approximation schemes that are commonly used to solve this flow equation and discuss applications in equilibrium and out-of-equilibrium statistical physics, quantum many-particle systems, high-energy physics and quantum gravity.Comment: v2) Review article, 93 pages + bibliography, 35 figure