Gastrin-releasing peptide receptor-based targeting using bombesin analogues is superior to metabolism-based targeting using choline for in vivo imaging of human prostate cancer xenografts

Purpose: Prostate cancer (PC) is a major health problem. Overexpression of the gastrin-releasing peptide receptor (GRPR) in PC, but not in the hyperplastic prostate, provides a promising target for staging and monitoring of PC. Based on the assumption that cancer cells have increased metabolic activity, metabolism-based tracers are also being used for PC imaging. We compared GRPR-based targeting using the68Ga-labelled bombesin analogue AMBA with metabolism-based tar

Влияние фосфатных связующих на физико-механические свойства периклазохромитовых огнеупоров

У данній статті наведено та порівняно фізико-механічні властивості периклазо-хромітових матеріалів в залежності від різних типів фосфатних зв’язуючих та введення різних домішок. Визначено, що найбільш раціональним є введення триполіфосфату натрію.In given clause are resulted and the physycal-mechanical properties periclase-cgromite of materials are compared depending on different of types phosphate binding and introduction of the various additives. Is determined, that most rational is the introduction treepolyphosphate sodume

Dual-Phase PET-CT to Differentiate [F-18]Fluoromethylcholine Uptake in Reactive and Malignant Lymph Nodes in Patients with Prostate Cancer

PURPOSE: To investigate whether time-trends of enhanced [(18)F]Fluoromethylcholine ([(18)F]FCH) in lymph nodes (LN) of prostate cancer (PCa) patients can help to discriminate reactive from malignant ones, and whether single time point standardized uptake value (SUV) measurements also suffice. PROCEDURES: 25 PCa patients with inguinal (presumed benign) and enlarged pelvic LN (presumed malignant) showing enhanced [(18)F]FCH uptake at dual-phase PET-CT were analyzed. Associations between LN status (benign versus malignant) and SUV(max) and SUV(meanA50), determined at 2 min (early) and 30 min (late) post injection, were assessed. We considered two time-trends of [(18)F]FCH uptake: type A (SUV early > SUV late) and type B (SUV late ≥ SUV early). Histopathology and/or follow-up were used to confirm the assumption that LN with type A pattern are benign, and LN with type B pattern malignant. RESULTS: Analysis of 54 nodes showed that LN status, time-trends, and 'late' (30 min p.i.) SUV(max) and SUV(meanA50) parameters were strongly associated (P<0.0001). SUV(max) relative difference was the best LN status predictor. All but one inguinal LN showed a decreasing [(18)F]FCH uptake over time (pattern A), while 95% of the pelvic nodes presented a stable or increasing uptake (pattern B) type. CONCLUSIONS: Time-trends of enhanced [(18)F]FCH uptake can help to characterize lymph nodes in prostate cancer patients. Single time-point SUV measurements, 30 min p.i., may be a reasonable alternative for predicting benign versus malignant status of lymph nodes, but this remains to be validated in non-enlarged pelvic lymph nodes

Nociceptors: a phylogenetic view

The ability to react to environmental change is crucial for the survival of an organism and an essential prerequisite is the capacity to detect and respond to aversive stimuli. The importance of having an inbuilt “detect and protect” system is illustrated by the fact that most animals have dedicated sensory afferents which respond to noxious stimuli called nociceptors. Should injury occur there is often sensitization, whereby increased nociceptor sensitivity and/or plasticity of nociceptor-related neural circuits acts as a protection mechanism for the afflicted body part. Studying nociception and nociceptors in different model organisms has demonstrated that there are similarities from invertebrates right through to humans. The development of technology to genetically manipulate organisms, especially mice, has led to an understanding of some of the key molecular players in nociceptor function. This review will focus on what is known about nociceptors throughout the Animalia kingdom and what similarities exist across phyla; especially at the molecular level of ion channels

Heterogeneous treatment effects of therapeutic-dose heparin in patients hospitalized for COVID-19

Importance Randomized clinical trials (RCTs) of therapeutic-dose heparin in patients hospitalized with COVID-19 produced conflicting results, possibly due to heterogeneity of treatment effect (HTE) across individuals. Better understanding of HTE could facilitate individualized clinical decision-making. Objective To evaluate HTE of therapeutic-dose heparin for patients hospitalized for COVID-19 and to compare approaches to assessing HTE. Design, Setting, and Participants Exploratory analysis of a multiplatform adaptive RCT of therapeutic-dose heparin vs usual care pharmacologic thromboprophylaxis in 3320 patients hospitalized for COVID-19 enrolled in North America, South America, Europe, Asia, and Australia between April 2020 and January 2021. Heterogeneity of treatment effect was assessed 3 ways: using (1) conventional subgroup analyses of baseline characteristics, (2) a multivariable outcome prediction model (risk-based approach), and (3) a multivariable causal forest model (effect-based approach). Analyses primarily used bayesian statistics, consistent with the original trial. Exposures Participants were randomized to therapeutic-dose heparin or usual care pharmacologic thromboprophylaxis. Main Outcomes and Measures Organ support–free days, assigning a value of −1 to those who died in the hospital and the number of days free of cardiovascular or respiratory organ support up to day 21 for those who survived to hospital discharge; and hospital survival. Results Baseline demographic characteristics were similar between patients randomized to therapeutic-dose heparin or usual care (median age, 60 years; 38% female; 32% known non-White race; 45% Hispanic). In the overall multiplatform RCT population, therapeutic-dose heparin was not associated with an increase in organ support–free days (median value for the posterior distribution of the OR, 1.05; 95% credible interval, 0.91-1.22). In conventional subgroup analyses, the effect of therapeutic-dose heparin on organ support–free days differed between patients requiring organ support at baseline or not (median OR, 0.85 vs 1.30; posterior probability of difference in OR, 99.8%), between females and males (median OR, 0.87 vs 1.16; posterior probability of difference in OR, 96.4%), and between patients with lower body mass index (BMI 90% for all comparisons). In risk-based analysis, patients at lowest risk of poor outcome had the highest propensity for benefit from heparin (lowest risk decile: posterior probability of OR >1, 92%) while those at highest risk were most likely to be harmed (highest risk decile: posterior probability of OR <1, 87%). In effect-based analysis, a subset of patients identified at high risk of harm (P = .05 for difference in treatment effect) tended to have high BMI and were more likely to require organ support at baseline. Conclusions and Relevance Among patients hospitalized for COVID-19, the effect of therapeutic-dose heparin was heterogeneous. In all 3 approaches to assessing HTE, heparin was more likely to be beneficial in those who were less severely ill at presentation or had lower BMI and more likely to be harmful in sicker patients and those with higher BMI. The findings illustrate the importance of considering HTE in the design and analysis of RCTs. Trial Registration ClinicalTrials.gov Identifiers: NCT02735707, NCT04505774, NCT04359277, NCT0437258

Methodology to determine product dimensions based on user anthropometric data

The determination of product dimensions is usually a complicated task developed during the design process. Typically, product dimensions are developed using wrong percentiles and wrong anthropometric data, i.e., designers use data from other populations. This chapter proposes a method for dimensioning products based on user–product interactions and the user’s anthropometric dimensions. The methodology includes 7 steps: (1) determine the objective of the product, (2) identify the interactions user–product, (3) assign a name to the product dimensions, (4) identify the user dimensions to design the product, (5) determine the percentiles and Z-scores for each product dimension, (6) calculate the percentiles, (7) determine the dimensions of the product. In order to exemplify the proposed method, two examples were developed using the methodology. The first was related with the design of a conventional bench, and the second was related with design of an adjustable school desk. After applying the proposed method, both products were successfully dimensioned