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Background Preoperative malnourishment has been consistently associated with poor outcomes after radical cystectomy and other major abdominal surgeries. Most enhanced recovery after surgery (ERAS) studies have examined preoperative nutrition and its relationship to outcomes after gastrointestinal surgery. Although numerous studies have demonstrated the benefits of using an ERAS protocol, this study in unique in comparing 2 ERAS protocols, with and without a nutrition component. Methods A formalized preoperative nutrition protocol (PNP) recommending use of preoperative immunonutrition and carbohydrate drink was introduced in June 2018. A total of 78 consecutive patients who drank both beverages were compared with 92 historical controls. Multivariable logistic regression analyses were sequentially performed to determine if preoperative nutrition was associated with binary outcome variables (30-day complication, infectious complication, and readmission within 30 days). Results The preoperative nutrition group and control group were statistically similar in distribution of age, sex, American Society of Anesthesiologists physical status classification, clinical stage, and body mass index. Return of bowel function was found to occur earlier in the preoperative nutrition group than in the control group (3.12 vs 3.74 days; relative risk, 0.82; CI, 0.73-0.93; P = .0029). Complications within 30 days were similar in both groups (63.6% vs 55.4%; P = 0.36). Infectious complications (42.9% vs 37%; P = .53) and readmission within 30 days (22.1% vs 15.2%; P = .34) were also similar in both groups. Conclusions Use of a PNP including immunonutrition and carbohydrate drink may be associated with earlier return of bowel function after radical cystectomy.

Summary A clearer understanding of the tumor immune microenvironment (TIME) in metastatic clear cell renal cell carcinoma (ccRCC) may help to inform precision treatment strategies. We sought to identify clinically meaningful TIME signatures in ccRCC. We studied tumors from 39 patients with metastatic ccRCC using quantitative multiplexed immunofluorescence and relevant immune marker panels. Cell densities were analyzed in three regions of interest (ROIs): tumor core, tumor–stroma interface and stroma. Patients were stratified into low- and high-marker density groups using median values as thresholds. Log-rank and Cox regression analyses while controlling for clinical variables were used to compare survival outcomes to patterns of immune cell distributions. There were significant associations with increased macrophage (CD68+CD163+CD206+) density and poor outcomes across multiple ROIs in primary and metastatic tumors. In primary tumors, T-bet+ T helper type 1 (Th1) cell density was highest at the tumor–stromal interface (P = 0·0021), and increased co-expression of CD3 and T-bet was associated with improved overall survival (P = 0·015) and survival after immunotherapy (P = 0·014). In metastatic tumor samples, decreased forkhead box protein 3 (FoxP3)+ T regulatory cell density correlated with improved survival after immunotherapy (P = 0·016). Increased macrophage markers and decreased Th1 T cell markers within the TIME correlated with poor overall survival and treatment outcomes. Immune markers such as FoxP3 showed consistent levels across the TIME, whereas others, such as T-bet, demonstrated significant variance across the distinct ROIs. These findings suggest that TIME profiling outside the tumor core may identify clinically relevant associations for patients with metastatic ccRCC.

The Citrus tristeza virus (CTV) is one of the most economically devastating citrus diseases worldwide. The spread of CTV in eastern Spain was studied by Gottwald et al. with the goal of determining the spatio-temporal mechanisms of spread. Since the subjects in this study are individual trees, it is natural to think of infections as Bernoulli trials. This approach is difficult however, due to the spatial and temporal dependence of the observations. Consequently, a system of ordinary differential equations (ODE) was used to model the probabilities of infection as well as the spatial and temporal dependence. Given the parameters in the ODE, the probabilities of infection are treated as conditionally independent. Using the conditional independence we then specify the joint likelihood function as a Poisson binomial distribution. For the purpose of model selection and hypothesis testing we, employed accumulated prediction error (APE) which has connections to both Bayesian and frequentist frameworks. We demonstrated the robustness of our method in accounting for spatio-temporal dependencies in the data by accurately predicting the spatial distribution of the disease through Join Counts.

Introduction Mycophenolate mofetil (MMF) dose/kg can influence clinical outcomes of allogeneic hematopoietic cell transplantation (HCT) including acute graft-versus-host disease (GVHD) (Harnicar BBMT 2015; Bejanyan BBMT 2018). When used for GVHD prophylaxis in conjunction with post-transplant cyclophosphamide (PTCy), MMF is generally dosed at 15 mg/kg three times daily (capped at a maximum of 3 g/day) and combined with either tacrolimus or sirolimus. Thus, many adults receive the maximum dose and a variable dose/kg of MMF. Objectives We sought to investigate the impact of MMF dose/kg on clinical outcomes of HCT in the setting of PTCy-based GVHD prophylaxis, where the effect of MMF dose/kg is unknown. Methods Included are 112 consecutive adult patients with hematologic malignancies who received myeloablative (n=70) or reduced intensity (n=42) HCT at the Moffitt Cancer Center between 2012-2018 with T-cell replete peripheral blood stem cells (n=94) or bone marrow (n=18). GVHD prophylaxis consisted of PTCy/MMF and either tacrolimus (n=57) or sirolimus (n=55). MMF dose relative to patient actual body weight (mg/kg/day), was stratified by tertiles into low ( 40 mg/kg/day, n=36). Results The median age at transplant was 57.8 (range: 21-75) years. Median follow-up was 12 months (range: 0.3-39). Donors were haploidentical related (n=74), mismatched unrelated (n=26), and matched related/unrelated (n=12). MMF dose groups had similar characteristics, except the low dose group having a higher proportion of males (p Conclusion In patients receiving PTCy based GVHD prophylaxis, MMF dose/kg had no significant effect on GVHD. However, lower MMF dose/kg was associated with worse DFS. This study suggests that

Comparison of ribonucleic acid (RNA) molecules is important for revealing their evolutionary relationships, predicting their functions and predicting their structures. Many methods have been developed for comparing RNAs using either sequence or three-dimensional (3D) structure (backbone geometry) information. Sequences and 3D structures contain non-overlapping sets of information that both determine RNA functions. When comparing RNA 3D structures, both types of information need to be taken into account. However, few methods compare RNA structures using both sequence and 3D structure information. Recently, we have developed a new method based on elastic shape analysis (ESA) that compares RNA molecules by combining both sequence and 3D structure information. ESA treats RNA structures as 3D curves with sequence information encoded on additional coordinates so that the alignment can be performed in the joint sequence-structure space. The similarity between two RNA molecules is quantified by a formal distance, geodesic distance. In this study, we implement a web server for the method, called RASS, to make it publicly available to research community. The web server is located at http://cloud.stat.fsu.edu/RASS/.

Despite many years of research, comparing multiple protein structures simultaneously (multiple structure comparison) is still a challenging problem. Most of the previous studies have focused on similarities among subsets of residues (or atoms) from a group of proteins (local structure alignment) by minimizing some similarity scores based on root mean square deviation (RMSD) of the aligned residues. In this paper, we designed a novel mathematical and statistical framework for multiple global structure comparison (MGSC). Under this framework, a formal geodesic distance is defined for any pair of protein structures and a mean structure can be estimated for a group of protein structures. The multiple structure comparison is then conveniently performed by comparing each individual structure with the mean structure. The formal distance facilitates consistent and accurate clustering of protein structures. An efficient clustering algorithm was designed based on the developed method. Probability models can be built for groups of protein structures and used in hypothesis testing. A robust outlier detection algorithm was designed to illustrate the potential applications of the framework.

In recent years, RNAs have been found to have diverse functions beyond being a messenger in gene transcription. The functions of non-coding RNAs are determined by their structures. Structure comparison/alignment of RNAs provides an effective means to predict their functions. Despite many previous studies on RNA structure alignment, it is still a challenging problem to predict the function of RNA molecules based on their structure information. In this study, we developed a new RNA structure alignment method based on elastic shape analysis (ESA). ESA treats RNA structures as three dimensional curves and performs flexible alignment between two RNA molecules by bending and stretching one of the molecules to match the other. The amount of bending and stretching is quantified by a formal distance, geodesic distance. Based on ESA, a rigorous mathematical framework can be built for RNA structure comparison. Means and covariances can be computed and probability distributions can be constructed for a group of RNA structures. We further applied the method to predict functions of RNA molecules. Our method achieved good performance when tested on benchmark datasets.

The functions of RNAs, like proteins, are determined by their structures, which, in turn, are determined by their sequences. Comparison/alignment of RNA molecules provides an effective means to predict their functions and understand their evolutionary relationships. For RNA sequence alignment, most methods developed for protein and DNA sequence alignment can be directly applied. RNA 3-dimensional structure alignment, on the other hand, tends to be more difficult than protein structure alignment due to the lack of regular secondary structures as observed in proteins. Most of the existing RNA 3D structure alignment methods use only the backbone geometry and ignore the sequence information. Using both the sequence and backbone geometry information in RNA alignment may not only produce more accurate classification, but also deepen our understanding of the sequence-structure-function relationship of RNA molecules. In this study, we developed a new RNA alignment method based on elastic shape analysis (ESA). ESA treats RNA structures as three dimensional curves with sequence information encoded on additional dimensions so that the alignment can be performed in the joint sequence-structure space. The similarity between two RNA molecules is quantified by a formal distance, geodesic distance. Based on ESA, a rigorous mathematical framework can be built for RNA structure comparison. Means and covariances of full structures can be defined and computed, and probability distributions on spaces of such structures can be constructed for a group of RNAs. Our method was further applied to predict functions of RNA molecules and showed superior performance compared with previous methods when tested on benchmark datasets. The programs are available at http://stat.fsu.edu/ ∼jinfeng/ESA.html.