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

Revealing Facts and Avoiding Biases: A Review of Several Common Problems in Statistical Analyses of Epidemiological Data

This paper reviews common challenges encountered in statistical analyses of epidemiological data for epidemiologists. We focus on the application of linear regression, multivariate logistic regression, and log-linear modeling to epidemiological data. Specific topics include: a) deletion of outliers, b) heteroscedasticity in linear regression, c) limitations of principal component analysis in dimension reduction, d) hazard ratio vs. odds ratio in a rate comparison analysis, e) log-linear models with multiple response data, and f) ordinal logistic vs. multinomial logistic models. As a general rule, a thorough examination of a model’s assumptions against both current data and prior research should precede its use in estimating effects

Optimal UAV Formation Tracking Control with Dynamic Leading Velocity and Network-Induced Delays

With the rapid development of UAV technology, the research of optimal UAV formation tracking has been extensively studied. However, the high maneuverability and dynamic network topology of UAVs make formation tracking control much more difficult. In this paper, considering the highly dynamic features of uncertain time-varying leader velocity and network-induced delays, the optimal formation control algorithms for both near-equilibrium and general dynamic control cases are developed. First, the discrete-time error dynamics of UAV leader–follower models are analyzed. Next, a linear quadratic optimization problem is formulated with the objective of minimizing the errors between the desired and actual states consisting of velocity and position information of the follower. The optimal formation tracking problem of near-equilibrium cases is addressed by using a backward recursion method, and then the results are further extended to the general dynamic case where the leader moves at an uncertain time-varying velocity. Additionally, angle deviations are investigated, and it is proved that the similar state dynamics to the general case can be derived and the principle of control strategy design can be maintained. By using actual real-world data, numerical experiments verify the effectiveness of the proposed optimal UAV formation-tracking algorithm in both near-equilibrium and dynamic control cases in the presence of network-induced delays

Pancreatic index: A prognostic factor of upfront surgery for body or tail pancreatic ductal adenocarcinoma with vascular involvement—A retrospective study

Abstract Background The pancreatic index (PI) is a useful preoperative imaging predictor for pancreatic ductal adenocarcinoma (PDAC). In this retrospective study, we determined the predictive effect of PI to distinguish patients of pancreatic body/tail cancer (PBTC) with vascular involvement who can benefit from upfront surgery. Method All patients who received distal pancreatectomy for PDAC from 2016 to 2020 at the Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiaotong University School of Medicine were considered for the study. A total of 429 patients with PBTC were assessed in relation to the value of PI. Fifty‐five patients were eventually included and divided into low PI group and 29 patients in the normal PI group. Results The median overall survival (mOS) was significantly shorter in the low PI group (13.1 vs. 30.0 months, p = 0.002) in this study, and PI ≥ 0.78 (OR = 0.552, 95% CI: 0.301–0.904, p = 0.020) was an independent influencing factor confirmed by multivariate analysis. Subgroup analysis showed that PI was an independent prognostic factor for LA‐PBTC (OR = 0.272, 95% CI: 0.077–0.969, p = 0.045). As for BR PBTC, PI (OR = 0.519, 95% CI: 0.285–0.947, p = 0.033) combined with carbohydrate antigen 125 (CA125) (OR = 2.806, 95% CI: 1.206–6.526, p = 0.017) and chemotherapy (OR = 0.327, 95% CI: 0.140–0.763, p = 0.010) were independent factors. Conclusion This study suggests that the PI can be used as a predictive factor to optimize the surgical indication for PBTC with vascular involvement. Preoperative patients with normal PI and CA125 can achieve a long‐term prognosis comparable to that of resectable PBTC patients

Microscopy imaging and modeling study on the mechanical properties of the primary flight feather shaft of the bean goose, Anser fabalis

Avian flight feathers have the unique advantages of lightweight and high strength, which play a key role in their flight capacity. In this article, the rachis of the bean goose's primary flight feather was used as the research object. Its compressive properties were analyzed and the 3D microscale was observed by 3D microscope system with a super wide depth of field. The distribution of mechanical properties, section variation of fiber and internal microstructure of rachis were obtained by micro-CT technique. Based on these results, a 3D reconstructed model was established for structure mechanical simulation. The simulation results were close basically to the compressive strength of the actual sample. These results show that the synergistic effect of cortex and medulla can improve mechanical resistance of the rachis. Therefore, the best position (N3) of the primary flight feather shaft can be applied to the bionic design of thin wall structures for energy absorption. This research can provide some guidance for the application of lightweight structural design. Research Highlights: The internal structure of bean goose feather shaft was observed by micro-CT. The experimental method has a deeper understanding of the compressive properties of rachis fiber orientation. Under the synergistic effect of cortex and medulla, the compressive performance of rachis is better