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68Ga-satoreotide trizoxetan is a novel somatostatin receptor antagonist associated with high sensitivity and reproducibility in neuroendocrine tumour (NET) detection and localisation. However, the optimal peptide mass and radioactivity ranges for 68Ga-satoreotide trizoxetan have not yet been established. We therefore aimed to determine its optimal dosing regimen in patients with metastatic gastroenteropancreatic NETs in a prospective, randomised, 2×3 factorial, multicentre, phase II study. Methods: Patients received 68Ga-satoreotide trizoxetan at a peptide mass of 5-20 µg on day 1 of the study and of 30-45 µg on day 16-22, at one of three gallium-68 radioactivity ranges (40-80, 100-140, or 160-200 MBq). Whole-body PET/CT imaging was performed 50-70 minutes after each injection. The primary endpoint was the detection rate of NET lesions imaged by 68Ga-satoreotide trizoxetan relative to contrast-enhanced CT (CECT) (for each of the six peptide mass/radioactivity range combinations). Results: Twenty-four patients were evaluated in the per-protocol analysis. The median number of lesions detected by 68Ga-satoreotide trizoxetan PET/CT or PET only was at least twice as high as the number of lesions detected by CECT across the six studied peptide mass dose/radioactivity range combinations. There were no differences between the two peptide mass ranges and between the three radioactivity ranges in the number of identified lesions. However, a trend towards a lower relative lesion count was noted in the liver for the 40-80 MBq range. No relationship was observed between the radioactivity range per patient's body weight (MBq/kg) and the number of lesions detected by 68Ga-satoreotide trizoxetan. Median diagnostic sensitivity of 68Ga-satoreotide trizoxetan PET/CT, based on the number of lesions per patient, ranged from 85% to 87% across the different peptide mass and radioactivity ranges. Almost all reported adverse events were mild and self-limiting. Conclusion: A radioactivity of 100-200 MBq with a peptide mass up to 50 μg were confirmed as the optimal dosing regimen for 68Ga-satoreotide trizoxetan to be used in future phase III studies.

Significance: In humans, imbalances in the reduction-oxidation (redox) status of cells are associated with many pathological states. In addition, many therapeutics and prophylactics used as interventions for diverse pathologies either directly modulate oxidant levels or otherwise influence endogenous cellular redox systems. Recent Advances: The cellular machineries that maintain redox homeostasis or that function within antioxidant defense systems rely heavily on the regulated reactivities of sulfur atoms either within or derived from the amino acids cysteine and methionine. Recent advances have substantially advanced our understanding of the complex and essential chemistry of biological sulfur-containing molecules. Critical Issues: The redox machineries that maintain cellular homeostasis under diverse stresses can consume large amounts of energy to generate reducing power and/or large amounts of sulfur-containing nutrients to replenish or sustain intracellular stores. By understanding the metabolic pathways underlying these responses, one can better predict how to protect cells from specific stresses. Future Directions: Here, we summarize the current state of knowledge about the impacts of different stresses on cellular metabolism of sulfur-containing molecules. This analysis suggests that there remains more to be learned about how cells use sulfur chemistry to respond to stresses, which could in turn lead to advances in therapeutic interventions for some exposures or conditions.

SUMMARY Energetic nutrients are oxidized to sustain high intra-cellular NADPH/NADP+ ratios. NADPH-dependent reduction of thioredoxin-1 (Trx1) disulfide and glutathione disulfide by thioredoxin reductase-1 (TrxR1) and glutathione reductase (Gsr), respectively, fuels antioxidant systems and deoxyribonucleotide synthesis. Mouse livers lacking both TrxR1 and Gsr sustain these essential activities using an NADPH-independent methionine-consuming pathway; however, it remains unclear how this reducing power is distributed. Here, we show that liver-specific co-disruption of the genes encoding Trx1, TrxR1, and Gsr (triple-null) causes dramatic hepatocyte hyperproliferation. Thus, even in the absence of Trx1, methionine-fueled glutathione production supports hepatocyte S phase deoxyribonucleotide production. Also, Trx1 in the absence of TrxR1 provides a survival advantage to cells under hyperglycemic stress, suggesting that glutathione, likely via glutaredoxins, can reduce Trx1 disulfide in vivo. In triple-null livers like in many cancers, deoxyribonucleotide synthesis places a critical yet relatively low-volume demand on these reductase systems, thereby favoring high hepatocyte turnover over sustained hepatocyte integrity., In Brief All cells require cytosolic disulfide-reducing power fueled by intracellular NADPH or, in mammals, alternatively generated by catabolism of the essential amino acid methionine. Prigge et al. show that liver homeostasis under cytosolic disulfide reductase paucity involves noncanonical trafficking of reducing power and a hyperproliferation-based organ survival strategy.

Quantitative imaging biomarkers could speed the development of new treatments for unmet medical needs and improve routine clinical care. However, it is not clear how the various regulatory and nonregulatory (eg, reimbursement) processes (often referred to as pathways) relate, nor is it clear which data need to be collected to support these different pathways most efficiently, given the time- and cost-intensive nature of doing so. The purpose of this article is to describe current thinking regarding these pathways emerging from diverse stakeholders interested and active in the definition, validation, and qualification of quantitative imaging biomarkers and to propose processes to facilitate the development and use of quantitative imaging biomarkers. A flexible framework is described that may be adapted for each imaging application, providing mechanisms that can be used to develop, assess, and evaluate relevant biomarkers. From this framework, processes can be mapped that would be applicable to both imaging product development and to quantitative imaging biomarker development aimed at increasing the effectiveness and availability of quantitative imaging.http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100800/-/DC1.RSNA, 2011

A three step protocol for protein S-nitrosothiol conversion to fluorescent mixed disulfides with purified proteins, referred to as the thiosulfonate switch, is explored which involves: (1) thiol blocking at pH 4.0 using S-phenylsulfonylcysteine (SPSC); (2) trapping of protein S-nitrosothiols as their S-phenylsulfonylcysteines employing sodium benzenesulfinate; and (3) tagging the protein thiosulfonate with a fluorescent rhodamine based probe bearing a reactive thiol (Rhod-SH), which forms a mixed disulfide between the probe and the formerly S-nitrosated cysteine residue. S-Nitrosated bovine serum albumin and the S-nitrosated C-terminally truncated form of AdhR-SH (alcohol dehydrogenase regulator) designated as AdhR*-SNO were selectively labelled by the thiosulfonate switch both individually and in protein mixtures containing free thiols. This protocol features the facile reaction of thiols with S-phenylsulfonylcysteines forming mixed disulfides at mild acidic pH (pH = 4.0) in both the initial blocking step as well as in the conversion of protein-S-sulfonylcysteines to form stable fluorescent disulfides. Labelling was monitored by TOF-MS and gel electrophoresis. Proteolysis and peptide analysis of the resulting digest identified the cysteine residues containing mixed disulfides bearing the fluorescent probe, Rhod-SH.

Objectives To evaluate if the mean smallest detectable change (SDC) of multiple time intervals using the Bland & Altman (B&A) levels of agreement (LoA) method is an appropriate surrogate for the generalisability analysis method for estimating the overall SDC of radiological progression in rheumatoid arthritis (RA) trials. Secondly, to compare the SDC based on 95% LoA with the SDC based on 80% LoA, and to investigate the association between SDC and baseline damage and progression. Methods Fifteen datasets from randomised controlled trials in RA were scored by 13 experienced readers as pairs according to the modified Sharp/van der Heijde method. The SDC using the 95% and 80% LoA and the generalisability methods was calculated. Results 21 295 radiographic time points from 7643 patients were included. The mean (range) SDC for the LoA and the generalisability methods was 3.1 (2.3–4.3) and 3.2 (2.3–4.6) units, respectively. The mean±SD difference between the two methods was −0.13±0.28. The mean SDC including all intervals (n=31) was 3.0±0.7 for 95% LoA and 2.0±0.4 for 80% LoA. No relationship was observed between baseline damage and the SDC, whereas the SDC increased with increasing radiological progression. Conclusions The mean of the interval SDCs obtained by the simple LoA method is a valid surrogate for the SDC obtained by complex generalisability methods. The SDC depends on the level of radiographic progression rather than on the level of absolute damage. In addition, the use of an SDC based on 80% rather than on 95% LoA is proposed.

Objective The aim of this study is to provide data on the adjudication rate for a predetermined threshold of difference in change score between two readers in randomized controlled trials (RCTs). Methods Fifteen datasets from RCTs in RA were scored by 13 experienced readers as pairs according to the modified Sharp-van der Heijde method. The theoretical adjudication rates for thresholds of between 3 and 20 units were calculated. We investigated the influence of the number of time points within the same session, the length of the interval and disease duration on the adjudication rates. Results A total of 21,295 time points from 7643 patients from 15 databases were included in the analysis. The adjudication rate was inversely related to the threshold. Higher adjudication rates were observed with a higher number of time points, longer time intervals and in early versus established RA. The adjudication rates ranged from 0% to 22% depending on the scenario. Conclusion With trained and experienced readers, the adjudication rate in RA RCTs is low even with very conservative adjudication thresholds.

SummaryImaging of hip in osteoarthritis (OA) has seen considerable progress in the past decade, with the introduction of new techniques that may be more sensitive to structural disease changes. The purpose of this expert opinion, consensus driven recommendation is to provide detail on how to apply hip imaging in disease modifying clinical trials. It includes information on acquisition methods/techniques (including guidance on positioning for radiography, sequence/protocol recommendations/hardware for magnetic resonance imaging (MRI)); commonly encountered problems (including positioning, hardware and coil failures, artifacts associated with various MRI sequences); quality assurance/control procedures; measurement methods; measurement performance (reliability, responsiveness, and validity); recommendations for trials; and research recommendations.

y Institute of Bone and Joint Research, Kolling Institute, University of Sydney, Sydney, NSW, Australia z Rheumatology Department, Royal North Shore Hospital, University of Sydney, Sydney, NSW, Australia x Department of Medicine, Division of Rheumatology and Immunology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA k School of Public health and Preventive Medicine, Monash University, Alfred Hospital, Melbourne 3004, Australia ¶ Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA, USA # Department of Radiology, Hospital do Corac~ ao (HCor) and Teleimagem, S~ ao Paulo, SP, Brazil yy Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Brazil zz Institute of Anatomy, Paracelsus Medical University Salzburg & Nuremberg, Salzburg, Austria xx Chondrometrics GmbH, Ainring, Germany kk Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA ¶¶ Department of Radiology and Biomedical Imaging, UCSF, San Francisco, USA ## Osteoarthritis Research Unit, University of Montreal Hospital Research Centre (CRCHUM), Montreal, Quebec, Canada yyy BioClinica, Newtown, PA, USA zzz Department of Radiology, Penn State University, Hershey, PA, USA xxx Department of Orthopaedic Surgery, Penn State University, Hershey, PA, USA kkk Department of Radiology, The American British Cowdray Medical Center, Mexico City, Mexico ¶¶¶ Spire Sciences, Inc., Boca Raton, Florida, USA ### Department of Radiology, University of Erlangen-Nuremberg, Erlangen, Germany yyyy Qmetrics Technologies, Rochester, NY, USA zzzz Department of Radiology, Stanford University, Stanford, CA, USA xxxx Department of Bioengineering, Stanford University, Stanford, CA, USA kkkk Department of Orthopaedic Surgery, Stanford University, Stanford, CA, USA