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An experiment was carried out to evaluate how interactions between forage to concentrate ratio and dietary crude protein level may alter nitrogen efficiency and UT-B expression in growing Baluchi male lambs. Four Baluchi male lambs [30 ± 2 kg BW] were used in a 4 x 4 latin square design with 28-d periods and a 2 x 2 factorial arrangement of dietary treatments. The treatments fed forage: concentrate [FC; DM basis] ratios of 45:55 low concentrate (LC) or 25:75 high concentrate (HC) with dietary levels of CP of 14 low protein (LP) or 18% high protein (HP) [CP, DM basis]. Dry matter intake increased as dietary concentrate level increased. Treatments, dietary CP content and F: C ratio had significant effect on CP intake. Increasing dietary N content of the diet increased dry matter (DM), crude protein (CP) and organic matter (OM) digestibility. Forage to concentrate ratio had a significant effect on neutral detergent fiber (NDF) and OM digestibility. Treatments had significant effect on the CP, NDF and OM digestibility. There were an interaction between dietary CP content and F: C ratio on the ruminal pH, NH3-N concentration, individual volatile fatty acids (VFA) concentration, acetate: propionate ratio and BUN concentration. Except ruminal pH, all ruminal fermentation and blood metabolite factors were affected by both dietary CP content and F: C ratio in trial. Treatments had significant influence on the NI (g/d) and urinary N excretion (g/d) (% of N intake). Also, both dietary CP content and F: C ratio had significant effect on NI. The lambs consume high crude protein treatments tended to have greater urinary N excretion (g/d) than those consume low crude protein treatments. The F: C ratio had a significant effect on urinary N excretion (g/d). Approximately 6.56 times more UT-B was expressed by the rumen ventral sac for lambs on the treatments contain 18% crude protein relative to those on the treatments contain 14% crude protein. In conclusion this study shows that changes in characteristic of the diet produce significant changes in UT-B urea transporter expression within the ovine rumen. Changing urea entry into the GIT via dietary regulation of UT-B could serve as important mechanism to maintenance of nitrogen balance and increase nitrogen efficiency in Baluchi growing lambs. Our findings suggest that the dietary regulation of urea transporters plays a major role in altering urea entry into the gastrointestinal tract. [ABSTRACT FROM AUTHOR]

Background and Objectives Alloimmunization with the prevalence rate of 60% is a common problem in chronically transfused patients. This problem has been reported to be less common in transfused hospital-based patients, amounting to 1-2 percent. Alloimmunization can lead to some difficulty varying from delay in the provision of similar blood types to delayed hemolytic transfusion reactions. The aim of this study was to analyze alloimmunization against RBCs among non-chronically transfused patients in Namazi Hospital in Shiraz. Materials and Methods Retrospective analysis of 3487 non-chronically transfused patients was conducted with antibody screening test and identification of patients' alloantibodies with the panel cell test. For patients with alloantibody, the data for sex, age, and history of transfusion and surgery were collected. Finally, the data were analyzed by SPSS software v. 15 using chi-square (CI= 95%). Results Twenty-eight out of 3487 patients had alloantibody (prevalence rate of 0.8%). The most common clinically significant alloantibodies found were anti-K (23%), anti- E (15%) and anti-C (11%). The most common clinically significant alloantibodies identified in males and females were anti-K and anti-C, respectively. Conclusions Alloantibody prevalence rate did not show any correlation with age and sex and was more common in patients with surgery history and transfusion record. Important factors contributing to the higher prevalence of the above alloantibodies are the higher prevalence of the related antigens in the population, higher antigenicity power, and the lack of crossmatch and grouping for the antigens before blood transfusion. [ABSTRACT FROM AUTHOR]

The fish finger produced from mince and surimi of common carp (Cyprinus carpio L., 1758) as well as the changes in chemical, microbial and sensory quality of the during product process were examined. The moisture content in the fish fingers produced from mince (FFm) and surimi (FFs) was reduced from 76.65 to 66.10 % and from 83.76 to 70.08 %, respectively (p<0.05). The Ash and fat content increased signiicantly in both kinds of fish finger. The increase in the protein content was only signiicant in ish inger produced by surimi. The protein content in surimi-based ish inger increased from 10.85% to 12.09%. There was also a signiicant decrease in TBC, TC and E. coli during the production process of both ish ingers (p<0.05). There were no signiicant difference in sensory parameters of odor, taste and texture, but the difference in color and general acceptability of both groups was significant (p<0.05). The Overall mean score of sensory evaluation of ish ingers produced from surimi was higher than ish ingers produced from mince. [ABSTRACT FROM AUTHOR]

Introduction: Cardiovascular disease is a major factor in the deterioration of the health and the death of hemodialysis patients. Previous studies have mainly shown a decreased level of heat shock protein 27 (HSP27) in patients with cardiovascular disease. We conducted this study to investigate whether HSP27 correlates with common carotid intima-media thickness (CCIMT) and if it has a potential to be a biomarker for cardiovascular disease. Materials and Methods: In this cross-sectional study, the correlation between HSP27 serum concentration and CCIMT was investigated in 42 hemodialysis patients. An enzyme-linked immunosorbent assay method was used to measure HSP27 level in the plasma of the patients, and a high-resolution B-mode ultrasonography was applied to measure CCIMT. Results: There was an inverse significant correlation between serum concentration of HSP27 and CCIMT only in patients that had hypertension as their only cardiovascular risk factor (r = - 0.61, P = .02). Conclusions: According to our results and the fact that HSP27 has been shown to be expressed in atherosclerotic plaques of both experimental animals and humans, we suggest that circulatory HSP27 concentration has a potential of being used as a marker for cardiovascular events. [ABSTRACT FROM AUTHOR]

Introduction: Nowadays artificially assisted reproductive techniques are used to cure infertility. These methods are highly expensive, time-consuming and have low success rates which are usually around 20-40%. One of the best alternate methods for infertility treatment that can be considered is adoption that often decreases the treatment costs and the psychological impact within an infertile couple. Materials and Methods: A cross-sectional study was performed between October 2009-2010 on 200 infertile couples who had been referred to Infertility Center of Shahid Sadoughi University of Medical Sciences. Information gathered through face-to-face interview and questionnaires. The data analyzed through a SPSS software program using ANOVA test. Results: There was a significant statistical relationship between adoption acceptance value scores and marriage duration of a couple (p=0.002 in men, p=0.004 in women) and presence of adoption backgrounds in male relatives (p=0.004). There was no statistically significant relationship between age, gender, education level, and onus of infertility, the number of previous referrals for an infertility solution and presence of adoption backgrounds in female relatives. Conclusion: Adoption as an alternative option to infertility treatment need to be more considered as a medical, social and cultural issue. [ABSTRACT FROM AUTHOR]

Objective: Granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA) are chronic life-threatening vasculitides requiring substantial immunotherapy. Adult trials identified rituximab (RTX) as an alternative to cyclophosphamide (CYC) for remission-induction of GPA/MPA. Disease rarity has limited feasibility of similar trials in pediatrics. We aim to evaluate the relative efficacy and toxicity of CYC and RTX for childhood GPA/MPA through registry-based comparative evaluation., Methods: From A Registry of Childhood Vasculitis we identified GPA/MPA patients who received induction with RTX or CYC. Pediatric vasculitis activity score (PVAS) and pediatric vasculitis damage index (pVDI) evaluated disease activity and damage. Descriptive statistics summarized patient characteristics. RTX/CYC comparisons used logistic regression for primary outcomes of post-induction remission (PVAS=0) or low disease activity (PVAS<2). Hospital admission for adverse events and pVDI were compared using logistic regression and ordinal regression, respectively., Results: Among 104 patients, 43% received RTX, 46% CYC, 11% both. Treatment groups did not significantly differ for diagnosis PVAS and onset age. There was no difference in remission between groups (63% overall; OR 1.07, 95% CI: 0.45, 2.52). Hospitalizations occurred in 22% of RTX patients versus 10% on CYC (OR 2.27, 95% CI: 0.73, 7.05). The median 12-month pVDI was one in both groups (OR 0.98, 95% CI 0.43, 2.22)., Conclusion: This is the first study comparing CYC and RTX for induction in pediatric GPA/MPA. No significant differences were shown in rates of remission, severe adverse events, or organ damage. Limitations included lack of standardized treatment regimens, retrospectivity, and lack of longitudinal adverse drug-related event data., (This article is protected by copyright. All rights reserved.)

Objective: This study describes the development, validation, and integration of a detector response model that accounts for the combined effects of x-ray crosstalk, charge sharing, and pulse pileup in photon-counting detectors., Approach: The x-ray photon transport was simulated using Geant4, followed by analytical charge sharing simulation in MATLAB. The analytical simulation models charge clouds with Gaussian-distributed charge densities, which are projected on a 3x3 pixel neighborhood of interaction location to compute detected counts. For pulse pileup, a prior analytical method for redistribution of energy-binned counts was implemented for delta pulses. The x-ray photon transport and charge sharing components were validated using experimental data acquired on the CdTe-based Pixirad-1/Pixie-III detector using monoenergetic beams at 26, 33, 37, and 50 keV. The pulse pileup implementation was verified with a comparable Monte Carlo simulation. The model output without pulse pileup was used to generate spatio-energetic response matrices for efficient simulation of scanner-specific photon-counting CT (PCCT) images with DukeSim, with pulse pileup modeled as a post-processing step on simulated projections. For analysis, images for the Gammex multi-energy phantom and the XCAT chest phantom were simulated at 120 kV, both with and without pulse pileup for a range of doses (27-1344 mAs). The XCAT images were evaluated qualitatively at 120 mAs, while images for the Gammex phantom were evaluated quantitatively for all doses using measurements of attenuation coefficients and Calcium concentrations., Main Results: Reasonable agreement was observed between simulated and experimental spectra with Mean Absolute Percentage Error Values (MAPE) between 10%-31% across all incident energies and detector modes. The increased pulse pileup from increased dose affected attenuation coefficients and calcium concentrations, with an effect on calcium quantification as high as MAPE of 28%., Significance: The presented approach demonstrates the viability of the model for enabling VITs to assess and optimize the clinical performance of PCCT., (© 2024 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Background: Awareness of paediatric-specific predictors of damage in Childhood-lupus is needed to inform mitigation measures., Objectives: To ascertain how clinical and demographic variables correlate with damage accrual and identify predictors of damage., Methods: Analysis included UK JSLE Cohort Study participants. Univariable and multivariable Prentice-Williams-Peterson models investigated how demographic and clinical factors influenced hazards of new damage. Analyses were performed across the entire cohort, in patients with minimal disease activity marked by a time-adjusted average SLEDAI-2K score (AMS)≤2, low activity (AMS ≤ 4), moderate-high activity (AMS > 4) and those with no corticosteroids., Results: Within the entire cohort (n = 430), factors associated with damage included: any methylprednisolone (Hazard Ratio, HR 2.20, [CI 1.33-3.62]), time-adjusted mean Physicians Global Assessment (PGA) (HR 2.87, [CI 1.48-5.56]) and AMS score (HR 1.13, [CI 1.03-1.24], all p< 0.05). Within the low activity subgroup, any methylprednisolone (HR 2.61, [CI 1.04-6.53]) and time-adjusted mean PGA (HR 3.41, [CI 1.52-7.76]) were associated with damage (both p< 0.05). Within the moderate-high activity subgroup, any methylprednisolone (HR 2.29, [CI 1.31-4.00]), time-adjusted mean PGA (HR 2.66, [CI 1.20-5.87]) and AMS score (HR 1.15, [CI 1.03-1.29]), were predictive of damage (all p< 0.05). Baseline organ damage was predictive of subsequent damage accrual in the minimal activity (HR 1.33, CI [1.78-8.08]) and no corticosteroids subgroups (HR 3.64, CI [1.83-7.24], both p< 0.005)., Conclusion: Disease activity levels (AMS/PGA) and proxy indicators (methylprednisolone exposure, baseline damage) were found to be key predictors of damage accrual. This highlights the importance of practical strategies, to reduce disease activity and long-term treatment toxicity, such as treat-to-target., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Objectives: We report the safety, tolerability and efficacy of tofacitinib in patients with juvenile idiopathic arthritis (JIA) in an ongoing long-term extension (LTE) study., Methods: Patients (2-<18 years) with JIA who completed phase 1/3 index studies or discontinued for reasons excluding treatment-related serious adverse events (AEs) entered the LTE study and received tofacitinib 5 mg two times per day or equivalent weight-based doses. Safety outcomes included AEs, serious AEs and AEs of special interest. Efficacy outcomes included improvement since tofacitinib initiation per the JIA-American College of Rheumatology (ACR)70/90 criteria, JIA flare rate and disease activity measured by Juvenile Arthritis Disease Activity Score (JADAS)27, with inactive disease corresponding to JADAS ≤1.0., Results: Of 225 patients with JIA (median (range) duration of treatment, 41.6 (1-103) months), 201 (89.3%) had AEs; 34 (15.1%) had serious AEs. 10 patients developed serious infections; three had herpes zoster. Two patients newly developed uveitis. Among patients with polyarticular course JIA, JIA-ACR70/90 response rates were 60.0% (78 of 130) and 33.6% (47 of 140), respectively, at month 1, and generally improved over time. JIA flare events generally occurred in <5% of patients through to month 48. Observed mean (SE) JADAS27 was 22.0 (0.6) at baseline, 6.2 (0.7) at month 1 and 2.8 (0.5) at month 48, with inactive disease in 28.8% (36 of 125) of patients at month 1 and 46.8% (29 of 82) at month 48., Conclusions: In this interim analysis of LTE study data in patients with JIA, safety findings were consistent with the known profile of tofacitinib, and efficacy was maintained up to month 48., Trial Registration Number: NCT01500551., Competing Interests: Competing interests: HIB has received research grants from Bristol Myers Squibb, Novartis and Pfizer; is an employee of Cincinnati Children’s Hospital Medical Center; has received consulting fees or other remuneration from AbbVie, AstraZeneca/MedImmune, Bayer, Biocon, Boehringer Ingelheim, Bristol Myers Squibb, Cerecor, Eli Lilly, EMD Serono, Janssen, Novartis, Pfizer, Roche, R-Pharm and Sobi; and is a member of speaker bureaus for Novartis and Pfizer. JDA has received honorarium from Novartis. JFB has received research grants from AbbVie, Bristol Myers Squibb, Janssen, Pfizer and Roche. ALB is a member of speaker bureaus for AbbVie, Novartis and Roche. RC has received consulting fees or other remuneration from AbbVie, Bristol Myers Squibb, Eli Lilly, GSK, Novartis, Pfizer, Roche and Sanofi. GS has received consulting fees or other remuneration from Novartis and Sobi and research support from IpiNovyx. CN has received research grants from AbbVie, AstraZeneca, Bristol Myers Squibb, Eli Lilly, GSK, Pfizer and UCB. MV-DM is an employee of Clínica de Investigacion en Reumatologia y Obesidad, SC. HP, CC, CWh, KeK and SL are employees and stockholders of Pfizer. AW was an employee and stockholder of Pfizer at the time of this analysis. AM has received consulting fees or other remuneration from Aurinia, Bristol Myers Squibb, Eli Lilly, EMD Serono, Janssen and Pfizer. DL’s institution, the Cincinnati Children’s Hospital Medical Center, has received research grants from Bristol Myers Squibb, Janssen, Novartis, Pfizer, Roche and UBC; and has received consulting fees or other remuneration from AstraZeneca, Boehringer Ingelheim, GSK, Roche, Novartis, Pfizer, Takeda and UBC. DL is also a data safety and monitoring board member or chairperson for the National Institutes of Health and the Canadian Arthritis Society. NR has received honoraria for consultancies or speaker bureaus from Ablynx, AstraZeneca/MedImmune, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, EMD Serono, F Hoffmann-La Roche, GS, Janssen, MSD, Novartis, Pfizer, R-Pharm, Sanofi, Servier, Sinergie and Sobi. The IRCCS Istituto Giannina Gaslini, where NR works as a full-time public employee, has received contributions from Bristol Myers Squibb, Eli Lilly, F Hoffmann-La Roche, GS, Janssen, Novartis, Pfizer and Sobi; this funding has been reinvested for the research activities of the hospital in a fully independent manner, without any commitment with third parties. EA-A, GC, WDLP, LJ, ÖK, KaK, RR-C, JCRR, LW-W, JEW and CWo have declared no conflicts., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ on behalf of EULAR.)

The rapid advancement in the field of medical imaging presents a challenge in keeping up to date with the necessary objective evaluations and optimizations for safe and effective use in clinical settings. These evaluations are traditionally done using clinical imaging trials, which while effective, pose several limitations including high costs, ethical considerations for repetitive experiments, time constraints, and lack of ground truth. To tackle these issues, virtual trials (aka in silico trials) have emerged as a promising alternative, using computational models of human subjects and imaging devices, and observer models/analysis to carry out experiments. To facilitate the widespread use of virtual trials within the medical imaging research community, a major need is to establish a common consensus framework that all can use. Based on the ongoing efforts of an AAPM Task Group (TG387), this article provides a comprehensive overview of the requirements for establishing virtual imaging trial frameworks, paving the way toward their widespread use within the medical imaging research community. These requirements include credibility, reproducibility, and accessibility. Credibility assessment involves verification, validation, uncertainty quantification, and sensitivity analysis, ensuring the accuracy and realism of computational models. A proper credibility assessment requires a clear context of use and the questions that the study is intended to objectively answer. For reproducibility and accessibility, this article highlights the need for detailed documentation, user-friendly software packages, and standard input/output formats. Challenges in data and software sharing, including proprietary data and inconsistent file formats, are discussed. Recommended solutions to enhance accessibility include containerized environments and data-sharing hubs, along with following standards such as CDISC (Clinical Data Interchange Standards Consortium). By addressing challenges associated with credibility, reproducibility, and accessibility, virtual imaging trials can be positioned as a powerful and inclusive resource, advancing medical imaging innovation and regulatory science., (© 2024 American Association of Physicists in Medicine.)

Background: Papillary fibroelastoma (PFE) is an uncommon benign cardiac tumor, typically arising from valvular structures. Nonvalvular PFEs are exceedingly rare and may present with diverse symptoms., Case Presentation: We present a case of a 46-year-old woman with positional vertigo and exertional dyspnea. Transthoracic echocardiography revealed a mobile oval-shaped mass in the left ventricle. Cardiac magnetic resonance imaging suggested a large papillary fibroelastoma. The tumor was successfully resected, and histopathological examination confirmed the diagnosis., Conclusion: This case highlights the importance of thorough imaging and surgical intervention in managing large, nonvalvular PFEs, which, although rare, can lead to significant complications., Competing Interests: Conflict of interest: The authors declare no conflict of interest., (© 2024 Saudi Heart Association.)

Importance: Clinical imaging trials are crucial for definitive evaluation of medical innovations, but the process is inefficient, expensive, and ethically-constrained. Virtual imaging trial (VIT) approach address these limitations by emulating the components of a clinical trial. An in silico rendition of the National Lung Screening Trial (NCLS) via Virtual Lung Screening Trial (VLST) demonstrates the promise of VITs to expedite clinical trials, reduce risks to subjects, and facilitate the optimal use of imaging technologies in clinical settings., Objectives: To demonstrate that a virtual imaging trial platform can accurately emulate a major clinical trial, specifically the National Lung Screening Trial (NLST) that compared computed tomography (CT) and chest x-ray (CXR) imaging for lung cancer screening., Design Setting and Participants: A diverse virtual patient population of 294 subjects was created from human models (XCAT) emulating the characteristics of cases on NLST, with two types of simulated lung nodules. The cohort was assessed using simulated CT and CXR systems to generate images that reflect the NLST imaging technologies. Deep learning models trained for lesion detection in CXR and CT served as virtual readers., Main Outcomes and Measures: The primary outcome was the difference in the Receiver Operating Characteristic Area Under the Curve (AUC) for CT and CXR modalities. Lesion-level AUC was aggregated to report patient-level AUC., Results: The study analyzed 294 CT and CXR simulated images from 294 virtual patients, with a lesion-level AUC of 0.81 (95% CI: 0.79-0.84) for CT and 0.56 (95% CI: 0.54-0.58) for CXR. At the patient level, CT demonstrated an AUC of 0.84 (95% CI: 0.80-0.89), compared to 0.52 (95% CI: 0.45-0.58) for CXR. Subgroup analyses on CT results indicated superior detection of homogeneous lesions (lesion-level AUC 0.97) than heterogeneous lesions (lesion-level AUC 0.72). Performance was particularly high for identifying larger nodules (AUC of 0.98 for nodules > 8 mm). The VLST results closely mirrored the NLST, particularly in size-based detection trends, with CT achieving high AUCs for nodules ≥ 8 mm and similar challenges in detecting smaller nodules., Conclusion and Relevance: The VIT results closely replicated those of the earlier NLST, underscoring its potential to replicate real clinical imaging trials. Integration of virtual trials may aid in the evaluation and improvement of imaging-based diagnosis.

Purpose: Photon-counting computed tomography (PCCT) has the potential to provide superior image quality to energy-integrating CT (EICT). We objectively compare PCCT to EICT for liver lesion detection., Approach: Fifty anthropomorphic, computational phantoms with inserted liver lesions were generated. Contrast-enhanced scans of each phantom were simulated at the portal venous phase. The acquisitions were done using DukeSim, a validated CT simulation platform. Scans were simulated at two dose levels ( CTDI vol 1.5 to 6.0 mGy) modeling PCCT (NAEOTOM Alpha, Siemens, Erlangen, Germany) and EICT (SOMATOM Flash, Siemens). Images were reconstructed with varying levels of kernel sharpness (soft, medium, sharp). To provide a quantitative estimate of image quality, the modulation transfer function (MTF), frequency at 50% of the MTF ( f 50 ), noise magnitude, contrast-to-noise ratio (CNR, per lesion), and detectability index ( d ' , per lesion) were measured., Results: Across all studied conditions, the best detection performance, measured by d ' , was for PCCT images with the highest dose level and softest kernel. With soft kernel reconstruction, PCCT demonstrated improved lesion CNR and d ' compared with EICT, with a mean increase in CNR of 35.0% ( p < 0.001 ) and 21% ( p < 0.001 ) and a mean increase in d ' of 41.0% ( p < 0.001 ) and 23.3% ( p = 0.007 ) for the 1.5 and 6.0 mGy acquisitions, respectively. The improvements were greatest for larger phantoms, low-contrast lesions, and low-dose scans., Conclusions: PCCT demonstrated objective improvement in liver lesion detection and image quality metrics compared with EICT. These advances may lead to earlier and more accurate liver lesion detection, thus improving patient care., (© 2024 Society of Photo-Optical Instrumentation Engineers (SPIE).)

Background: Dynamic chest radiography (DCR) is a recently developed functional x-ray imaging technique that detects pulmonary ventilation impairment as a decrease in changes in lung density during respiration. However, the diagnostic performance of DCR is uncertain owing to an insufficient number of clinical cases. One solution is virtual imaging trials (VITs), which is an emerging alternative method for efficiently evaluating medical imaging technology via computer simulation techniques., Purpose: This study aimed to estimate the typical threshold thickness of residual normal tissue below which the presence of emphysema may be detected by DCR via VITs using virtual patients with different physiques and a user-defined ground truth., Methods: Twenty extended cardiac-torso (XCAT) phantoms that exhibited changes in lung density during respiration were generated to simulate virtual patients. To simulate a locally collapsed lung, an air sphere was inserted into each lung regions in the phantom. The XCAT phantom was virtually projected using an x-ray simulator. The respiratory changes in pixel value (ΔPV) were measured on the projected air spheres (simulated lesions) to calculate the percentage of decrease (ΔPV%) relative to ΔPV exp-ins in the absence of an air sphere. The relationship between the amount of residual normal tissue and ΔPV% was fitted to a cubic approximation curve (hereafter, performance curve), and the threshold at which the ΔPV% began to decrease (normal-tissue thre ) was determined. The goodness of fit for each performance curve was evaluated according to the coefficient of determination (R 2 ) and the 95% confidence interval derived from the standard errors between the measured and theoretical values corresponding to each performance curve. The ΔPV% was also visualized as a color scaling to validate the results of the VITs in both virtual and clinical patients., Results: For each lung region in all body sizes, the ΔPV% decreased as the amount of residual normal tissue decreased and could be defined as a function of the amount of residual normal tissue in front of and behind the simulated lesions with high R 2 values. Meanwhile, the difference between the measured and theoretical values corresponding to each performance curve was only partially included in the 95% confidence interval. The normal-tissue thre values were 146.0, 179.5, and 170.9 mm for the upper, middle, and lower lungs, respectively, which were demonstrated in virtual patients and one real patient, where the value of the residual normal tissue was less than that of normal-tissue thre ; any reduction in the residual normal tissue was reflected as a reduced ΔPV and depicted as a reduced color intensity., Conclusions: The performance of DCR-based pulmonary impairment assessment depends on the amount of residual normal tissue in front of and behind the lesion rather than on the lesion size. The performance curve can be defined as a function of the amount of residual normal tissue in each lung region with a specific threshold of normal tissue remaining where lesions become detectable, shown as a decrease in ΔPV. The results of VITs are expected to accelerate future clinical trials for DCR-based pulmonary function assessment., (© 2024 The Author(s). Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Computed Tomography (CT) quantification is affected by the variability in image acquisition and rendition. This paper aimed to reduce this variability by harmonizing the images utilizing physics-based deep neural networks (DNNs)., Methods: An adversarial generative network was trained on virtual CT images acquired under various imaging conditions using a virtual imaging platform with 40 computational patient models. These models featured anthropomorphic lungs with different levels of pulmonary diseases, including nodules and emphysema. Imaging was conducted using a validated CT simulator at two dose levels and varying reconstruction kernels. The trained model was tested on an independent virtual test dataset and two clinical datasets., Results: On the virtual test set, the harmonizer improved the structural similarity index from 79.3 ±16.4% to 95.8 ±1.7%, normalized mean squared error from 16.7 ±9.7% to 9.2 ±1.7%, and peak signal-to-noise ratio from 27.7 ±3.7 dB to 32.2 ±1.6 dB. Moreover, the harmonized images yielded more precise quantification of emphysema-based imaging biomarkers for lung attenuation, LAA -950 from 5.6 ±8.7% to 0.23 ±0.16%, Perc 15 from 43.4 ±45.4 HU to 20.0 ±7.5 HU, and Lung Mass from 0.3 ±0.3 g to 0.1 ±0.2 g. In clinical data, the harmonizer reduced biomarker variability by an average of 70%. For lung nodules, harmonized images improved the detectability index by 6.5-fold and DNN-based precision by 6%., Conclusion: The proposed harmonizer significantly enhances image quality and quantification accuracy in CT imaging., Significance: The study demonstrated the potential utility of image harmonization for consistent CT image quality and reliable quantification, which is crucial for clinical applications and patient management.

Objective: Different methods can be used to condition imaging systems for clinical use. The purpose of this study was to assess how these methods complement one another in evaluating a system for clinical integration of an emerging technology, photon-counting computed tomography (PCCT), for thoracic imaging., Methods: Four methods were used to assess a clinical PCCT system (NAEOTOM Alpha; Siemens Healthineers, Forchheim, Germany) across 3 reconstruction kernels (Br40f, Br48f, and Br56f). First, a phantom evaluation was performed using a computed tomography quality control phantom to characterize noise magnitude, spatial resolution, and detectability. Second, clinical images acquired using conventional and PCCT systems were used for a multi-institutional reader study where readers from 2 institutions were asked to rank their preference of images. Third, the clinical images were assessed in terms of in vivo image quality characterization of global noise index and detectability. Fourth, a virtual imaging trial was conducted using a validated simulation platform (DukeSim) that models PCCT and a virtual patient model (XCAT) with embedded lung lesions imaged under differing conditions of respiratory phase and positional displacement. Using known ground truth of the patient model, images were evaluated for quantitative biomarkers of lung intensity histograms and lesion morphology metrics., Results: For the physical phantom study, the Br56f kernel was shown to have the highest resolution despite having the highest noise and lowest detectability. Readers across both institutions preferred the Br56f kernel (71% first rank) with a high interclass correlation (0.990). In vivo assessments found superior detectability for PCCT compared with conventional computed tomography but higher noise and reduced detectability with increased kernel sharpness. For the virtual imaging trial, Br40f was shown to have the best performance for histogram measures, whereas Br56f was shown to have the most precise and accurate morphology metrics., Conclusion: The 4 evaluation methods each have their strengths and limitations and bring complementary insight to the evaluation of PCCT. Although no method offers a complete answer, concordant findings between methods offer affirmatory confidence in a decision, whereas discordant ones offer insight for added perspective. Aggregating our findings, we concluded the Br56f kernel best for high-resolution tasks and Br40f for contrast-dependent tasks., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Photon-counting computed tomography (PCCT) has recently emerged into clinical use; however, its optimum imaging protocols and added benefits remains unknown in terms of providing more accurate lung density quantification compared to energy-integrating computed tomography (EICT) scanners., Purpose: To systematically assess the performance of a clinical PCCT scanner for lung density quantifications and compare it against EICT., Methods: This cross-sectional study involved a retrospective analysis of subjects scanned (August-December 2021) using a clinical PCCT system. The influence of altering reconstruction parameters was studied (reconstruction kernel, pixel size, slice thickness). A virtual CT dataset of anthropomorphic virtual subjects was acquired to demonstrate the correspondence of findings to clinical dataset, and to perform systematic imaging experiments, not possible using human subjects. The virtual subjects were imaged using a validated, scanner-specific CT simulator of a PCCT and two EICT (defined as EICT A and B) scanners. The images were evaluated using mean absolute error (MAE) of lung and emphysema density against their corresponding ground truth., Results: Clinical and virtual PCCT datasets showed similar trends, with sharper kernels and smaller voxel sizes increasing percentage of low-attenuation areas below -950 HU (LAA-950) by up to 15.7 ± 6.9% and 11.8 ± 5.5%, respectively. Under the conditions studied, higher doses, thinner slices, smaller pixel sizes, iterative reconstructions, and quantitative kernels with medium sharpness resulted in lower lung MAE values. While using these settings for PCCT, changes in the dose level (13 to 1.3 mGy), slice thickness (0.4 to 1.5 mm), pixel size (0.49 to 0.98 mm), reconstruction technique (70 keV-VMI to wFBP), and kernel (Qr48 to Qr60) increased lung MAE by 15.3 ± 2.0, 1.4 ± 0.6, 2.2 ± 0.3, 4.2 ± 0.8, and 9.1 ± 1.6 HU, respectively. At the optimum settings identified per scanner, PCCT images exhibited lower lung and emphysema MAE than those of EICT scanners (by 2.6 ± 1.0 and 9.6 ± 3.4 HU, compared to EICT A, and by 4.8 ± 0.8 and 7.4 ± 2.3 HU, compared to EICT B). The accuracy of lung density measurements was correlated with subjects' mean lung density (p < 0.05), measured by PCCT at optimum setting under the conditions studied., Conclusion: Photon-counting CT demonstrated superior performance in density quantifications, with its influences of imaging parameters in line with energy-integrating CT scanners. The technology offers improvement in lung quantifications, thus demonstrating potential toward more objective assessment of respiratory conditions., (© 2024 American Association of Physicists in Medicine.)

Background: The accuracy of morphological radiomic features (MRFs) can be affected by various acquisition settings and imaging conditions. To ensure that clinically irrelevant changes do not reduce sensitivity to capture the radiomics changes between successive acquisitions, it is essential to determine the optimal imaging systems and protocols to use., Purpose: The main goal of our study was to optimize CT protocols and minimize the minimum detectable difference (MDD) in successive acquisitions of MRFs., Method: MDDs were derived based on the previous research involving 15 realizations of nodule models at two different sizes. Our study involved simulations of two consecutive acquisitions using 297 different imaging conditions, representing variations in scanners' reconstruction kernels, dose levels, and slice thicknesses. Parametric polynomial models were developed to establish correlations between imaging system characteristics, lesion size, and MDDs. Additionally, polynomial models were used to model the correlation of the imaging system parameters. Optimization problems were formulated for each MRF to minimize the approximated function. Feature importance was determined for each MRF through permutation feature analysis. The proposed method was compared to the recommended guidelines by the quantitative imaging biomarkers alliance (QIBA)., Results: The feature importance analysis showed that lesion size is the most influential parameter to estimate the MDDs in most of the MRFs. Our study revealed that thinner slices and higher doses had a measurable impact on reducing the MDDs. Higher spatial resolution and lower noise magnitude were identified as the most suitable or noninferior acquisition settings. Compared to QIBA, the proposed protocol selection guideline demonstrated a reduced coefficient of variation, with values decreasing from 1.49 to 1.11 for large lesions and from 1.68 to 1.12 for small lesions., Conclusion: The protocol optimization framework provides means to assess and optimize protocols to minimize the MDD to increase the sensitivity of the measurements in lung cancer screening., (© 2024 Society of Photo-Optical Instrumentation Engineers (SPIE).)

Background: As a leading cause of death, worldwide, cardiovascular disease is of great clinical importance. Among cardiovascular diseases, coronary artery disease (CAD) is a key contributor, and it is the attributed cause of death for 10% of all deaths annually. The prevalence of CAD is commensurate with the rise in new medical imaging technologies intended to aid in its diagnosis and treatment. The necessary clinical trials required to validate and optimize these technologies require a large cohort of carefully controlled patients, considerable time to complete, and can be prohibitively expensive. A safer, faster, less expensive alternative is using virtual imaging trials (VITs), utilizing virtual patients or phantoms combined with accurate computer models of imaging devices., Purpose: In this work, we develop realistic, physiologically-informed models for coronary plaques for application in cardiac imaging VITs., Methods: Histology images of plaques at micron-level resolution were used to train a deep convolutional generative adversarial network (DC-GAN) to create a library of anatomically variable plaque models with clinical anatomical realism. The stability of each plaque was evaluated by finite element analysis (FEA) in which plaque components and vessels were meshed as volumes, modeled as specialized tissues, and subjected to the range of normal coronary blood pressures. To demonstrate the utility of the plaque models, we combined them with the whole-body XCAT computational phantom to perform initial simulations comparing standard energy-integrating detector (EID) CT with photon-counting detector (PCD) CT., Results: Our results show the network is capable of generating realistic, anatomically variable plaques. Our simulation results provide an initial demonstration of the utility of the generated plaque models as targets to compare different imaging devices., Conclusions: Vast, realistic, and variable CAD pathologies can be generated to incorporate into computational phantoms for VITs. There they can serve as a known truth from which to optimize and evaluate cardiac imaging technologies quantitatively., (© 2024 American Association of Physicists in Medicine.)

Pulmonary emphysema is a progressive lung disease that requires accurate evaluation for optimal management. This task, possible using quantitative CT, is particularly challenging as scanner and patient attributes change over time, negatively impacting the CT-derived quantitative measures. Efforts to minimize such variations have been limited by the absence of ground truth in clinical data, thus necessitating reliance on clinical surrogates, which may not have one-to-one correspondence to CT-based findings. This study aimed to develop the first suite of human models with emphysema at multiple time points, enabling longitudinal assessment of disease progression with access to ground truth. A total of 14 virtual subjects were modeled across three time points. Each human model was virtually imaged using a validated imaging simulator (DukeSim), modeling an energy-integrating CT scanner. The models were scanned at two dose levels and reconstructed with two reconstruction kernels, slice thicknesses, and pixel sizes. The developed longitudinal models were further utilized to demonstrate utility in algorithm testing and development. Two previously developed image processing algorithms (CT-HARMONICA, EmphysemaSeg) were evaluated. The results demonstrated the efficacy of both algorithms in improving the accuracy and precision of longitudinal quantifications, from 6.1±6.3% to 1.1±1.1% and 1.6±2.2% across years 0-5. Further investigation in EmphysemaSeg identified that baseline emphysema severity, defined as >5% emphysema at year 0, contributed to its reduced performance. This finding highlights the value of virtual imaging trials in enhancing the explainability of algorithms. Overall, the developed longitudinal human models enabled ground-truth based assessment of image processing algorithms for lung quantifications.

Objectives: To assess perceptual benefits provided by the improved spatial resolution and noise performance of deep silicon photon-counting CT (Si-PCCT) over conventional energy-integrating CT (ECT) using polychromatic images for various clinical tasks and anatomical regions., Materials and Methods: Anthropomorphic, computational models were developed for lungs, liver, inner ear, and head-and-neck (H&N) anatomies. These regions included specific abnormalities such as lesions in the lungs and liver, and calcified plaques in the carotid arteries. The anatomical models were imaged using a scanner-specific CT simulation platform (DukeSim) modeling a Si-PCCT prototype and a conventional ECT system at matched dose levels. The simulated polychromatic projections were reconstructed with matched in-plane resolutions using manufacturer-specific software. The reconstructed pairs of images were scored by radiologists to gauge the task-specific perceptual benefits provided by Si-PCCT compared to ECT based on visualization of anatomical and image quality features. The scores were standardized as z-scores for minimizing inter-observer variability and compared between the systems for evidence of statistically significant improvement (one-sided Wilcoxon rank-sum test with a significance level of 0.05) in perceptual performance for Si-PCCT., Results: Si-PCCT offered favorable image quality and improved visualization capabilities, leading to mean improvements in task-specific perceptual performance over ECT for most tasks. The improvements for Si-PCCT were statistically significant for the visualization of lung lesion (0.08 ± 0.89 vs. 0.90 ± 0.48), liver lesion (-0.64 ± 0.37 vs. 0.95 ± 0.55), and soft tissue structures (-0.47 ± 0.90 vs. 0.33 ± 1.24) and cochlea (-0.47 ± 0.80 vs. 0.38 ± 0.62) in inner ear., Conclusions: Si-PCCT exhibited mean improvements in task-specific perceptual performance over ECT for most clinical tasks considered in this study, with statistically significant improvement for 6/20 tasks. The perceptual performance of Si-PCCT is expected to improve further with availability of spectral information and reconstruction kernels optimized for high resolution provided by smaller pixel size of Si-PCCT. The outcomes of this study indicate the positive potential of Si-PCCT for benefiting routine clinical practice through improved image quality and visualization capabilities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ((E. Abadi and P. Segars)). The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Current employee of Canon Medical Research USA. (S Sharma). Current employee of Amazon. (D. Pal). Retiree of GE Healthcare. (J. Hsieh). Relationships with the following entities unrelated to the present publication: GE Healthcare, Siemens Healthineers, Imalogix, 12Sigma, Sun Nuclear, Nanox, Metis Health Analytics, Cambridge University Press, and Wiley. (E. Samei).]., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Image quality of photon-counting and energy integrating CT scanners changes with object size, dose to the object, and kernel selection., Purpose: To comprehensively compare task-generic image quality of photon-counting CT (PCCT) and energy integrating CT (EICT) systems as a function of phantom size, dose, and reconstruction kernel., Methods: A size-variant phantom (Mercury Phantom 3.0) was used to characterize the image quality of PCCT and EICT systems as a function of object size. The phantom contained five cylinders attached by slanted tapered sections. Each cylinder contained two sections: one uniform for noise, and the other with inserts for spatial resolution and contrast measurements. The phantom was scanned on Siemens' SOMATOM Force and NAEOTOM Alpha at 1.18 and 7.51 mGy without tube current modulation. CTDI vol was matched across two systems by setting the required tube currents, else, all other acquisition settings were fixed. CT sinograms were reconstructed using FBP and iterative (ADMIRE2 - Force; QIR2 - Alpha) algorithms with Body regular (Br) kernels. Noise Power Spectrum (NPS), Task Transfer Function (TTF), contrast-to-noise ratio (CNR), and detectability index (d') for a task of identifying 2-mm disk were evaluated based on AAPM TG-233 metrology using imQuest, an open-source software package. Averaged noise frequency (f av ) and 50% cut-off frequency for TTF (f 50 ) were used as scalar metrics to quantify noise texture and spatial resolution, respectively. The difference between image quality metrics' measurements was calculated as IQ PCCT - IQ EICT ., Results: From Br40 (soft) to Br64 (sharp), f 50 for air insert increased from 0.35 mm -1  ± 0.04 (standard deviation) to 0.76 mm -1  ± 0.17, 0.34 mm -1  ± 0.04 to 0.77 mm -1  ± 0.17, 0.37 mm -1  ± 0.02 to 0.95 mm -1  ± 0.17 for PCCT-T3D-QIR2, PCCT-70keV-QIR2, and EICT-ADMIRE2, respectively, when averaged over all sizes and dose levels. Similarly, from Br40 to Br64, noise magnitude increased from 10.86 HU ± 7.12 to 38.61 HU ± 18.84, 10.94 HU ± 7.08 to 38.82 HU ± 18.70, 13.74 HU ± 11.02 to 52.11 HU ± 26.22 for PCCT-T3D-QIR2, PCCT-70keV-QIR2, and EICT-ADMIRE2, respectively. The difference in f av was consistent across all sizes and dose levels. PCCT-70keV-VMI showed better consistency in contrast measurements for iodine and bone inserts than PCCT-T3D and EICT; however, PCCT-T3D had higher contrast for both inserts. From Br40 to Br64, considering all sizes and dose levels, CNR for iodine insert decreased from 52.30 ± 46.44 to 12.18 ± 10.07, 40.42 ± 33.42 to 9.48 ± 7.16, 39.94 ± 37.60 to 7.84 ± 6.67 for PCCT-T3D-QIR2, PCCT-70keV-QIR2, and EICT-ADMIRE2, respectively., Conclusions: Both PCCT image types, T3D and 70-keV-VMI exhibited similar or better noise, contrast, CNR than EICT when comparing kernels with similar names. For 512 × 512 matrix, PCCT's sharp kernels had lower resolution than EICT's sharp kernels. For all image quality metrics, except extreme low, every dose condition had a similar set of IQ-matching kernels. It suggests that considering patient size and dose level to determine IQ-matching kernel pairs across PCCT and EICT systems may not be imperative while translating protocols, except when the signal to the detector is extremely low., (© 2023 American Association of Physicists in Medicine.)

Parametric response mapping (PRM) is a voxel-based quantitative CT imaging biomarker that measures the severity of chronic obstructive pulmonary disease (COPD) by analyzing both inspiratory and expiratory CT scans. Although PRM-derived measurements have been shown to predict disease severity and phenotyping, their quantitative accuracy is impacted by the variability of scanner settings and patient conditions. The aim of this study was to evaluate the variability of PRM-based measurements due to the changes in the scanner types and configurations. We developed 10 human chest models with emphysema and air-trapping at end-inspiration and end-expiration states. These models were virtually imaged using a scanner-specific CT simulator (DukeSim) to create CT images at different acquisition settings for energy-integrating and photon-counting CT systems. The CT images were used to estimate PRM maps. The quantified measurements were compared with ground truth values to evaluate the deviations in the measurements. Results showed that PRM measurements varied with scanner type and configurations. The emphysema volume was overestimated by 3 ± 9.5 % (mean ± standard deviation) of the lung volume, and the functional small airway disease (fSAD) volume was underestimated by 7.5±19 % of the lung volume. PRM measurements were more accurate and precise when the acquired settings were photon-counting CT, higher dose, smoother kernel, and larger pixel size. This study demonstrates the development and utility of virtual imaging tools for systematic assessment of a quantitative biomarker accuracy.

Background: Incorporation of bentonite into the diets of ruminants can be helpful to maximize their performance. Modifying the structure of bentonite to nano and nanocomposite has improved their chemical stability and physicochemical properties, enhancing adsorption, absorption, and cation exchange capacity. Aims: This study aimed to assess the effect of magnetic bentonite nanocomposite (MBNC) on in vivo and in vitro fermentation process patterns, nutrient digestibility, and growth performance of Baluchi male lambs., Methods: Effects of control (basal diet), natural bentonite (NB) (10 g/kg dry matter (DM)), processed bentonite (PB) (5 and 10 g/kg DM basal diet), and MBNC (5 and 10 g/kg DM basal diet) on gas production (GP), and the fermentation process were determined using in vitro GP technique. For the in vivo experiment, 20 Baluchi male lambs were used with 4 experimental treatments: control, NB (5 g/kg DM), PB (5 g/kg DM), and MBNC (5 g/kg DM) and 5 replications in a completely randomized design for 60 consecutive days., Results: The potential for GP and its fractional rates were significantly decreased and increased in MBNC, respectively (P<0.01). The lowest cumulative GP, and CH 4 yield were observed in MBNC (P<0.05). In vitro , DM and organic matter (OM) digestibility and all fermentation parameters increased with the addition of two levels of MBNC to the culture medium (P<0.01). Except for feed conversion ratio (FCR), other growth performance parameters increased with the addition of MBNC to the diet (P<0.01). The ruminal pH, total volatile fatty acids (TVFA), acetate, and propionate significantly increased when MBNC incorporated to the diet (P<0.01). The NH 3 -N (P<0.001) was significantly decreased in MBNC. The bentonite supplementation decreased acetate to propionate (P=0.001) compared to the control., Conclusion: Adding MBNC at the 5 g/kg diet DM level can be used as a useful supplement to optimize rumen fermentation pattern, reduce methane production, and increase lamb performance., Competing Interests: The authors declare that there was no conflict of interest.

Objective. Virtual imaging trials enable efficient assessment and optimization of medical image devices and techniques via simulation rather than physical studies. These studies require realistic, detailed ground-truth models or phantoms of the relevant anatomy or physiology. Anatomical structures within computational phantoms are typically based on medical imaging data; however, for small and intricate structures (e.g. trabecular bone), it is not reasonable to use existing clinical data as the spatial resolution of the scans is insufficient. In this study, we develop a mathematical method to generate arbitrary-resolution bone structures within virtual patient models (XCAT phantoms) to model the appearance of CT-imaged trabecular bone. Approach . Given surface definitions of a bone, an algorithm was implemented to generate stochastic bicontinuous microstructures to form a network to define the trabecular bone structure with geometric and topological properties indicative of the bone. For an example adult male XCAT phantom (50th percentile in height and weight), the method was used to generate the trabecular structure of 46 chest bones. The produced models were validated in comparison with published properties of bones. The utility of the method was demonstrated with pilot CT and photon-counting CT simulations performed using the accurate DukeSim CT simulator on the XCAT phantom containing the detailed bone models. Main results . The method successfully generated the inner trabecular structure for the different bones of the chest, having quantiative measures similar to published values. The pilot simulations showed the ability of photon-counting CT to better resolve the trabecular detail emphasizing the necessity for high-resolution bone models. Significance. As demonstrated, the developed tools have great potential to provide ground truth simulations to access the ability of existing and emerging CT imaging technology to provide quantitative information about bone structures., (© 2023 Institute of Physics and Engineering in Medicine.)

ISG15 deficiency is a rare disease caused by autosomal recessive variants in the ISG15 gene, which encodes the ISG15 protein. The ISG15 protein plays a dual role in both the type I and II interferon (IFN) immune pathways. Extracellularly, the ISG15 protein is essential for IFN-γ-dependent anti-mycobacterial immunity, while intracellularly, ISG15 is necessary for USP18-mediated downregulation of IFN-α/β signalling. Due to this dual role, ISG15 deficiency can present with various clinical phenotypes, ranging from susceptibility to mycobacterial infection to autoinflammation characterised by necrotising skin lesions, intracerebral calcification, and pulmonary involvement. In this report, we describe novel variants found in two different families that result in complete ISG15 deficiency and severe skin ulceration. Whole exome sequencing identified a heterozygous missense p.Q16X ISG15 variant and a heterozygous multigene 1p36.33 deletion in the proband from the first family. In the second family, a homozygous total ISG15 gene deletion was detected in two siblings. We also conducted further analysis, including characterisation of cytokine dysregulation, interferon-stimulated gene expression, and p-STAT1 activation in lymphocytes and lesional tissue. Finally, we demonstrate the complete and rapid resolution of clinical symptoms associated with ISG15 deficiency in one sibling from the second family following treatment with the Janus kinase (JAK) inhibitor baricitinib., Competing Interests: PB has received institutional grants from: Novartis, SOBI, Roche, Chemocentryx, and Novimmune; consultancy fees from Roche, Novartis and SOBI; and speaker fees from UCB. DE has received institutional grants from Lilly, Sobi, Roche and Pfizer. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Burleigh, Moraitis, Al Masroori, Al-Abadi, Hong, Omoyinmi, Titheradge, Stals, Jones, Gait, Jayarajan, Di, Sebire, Solman, Ogboli, Welch, Sudarsanam, Wacogne, Price-Kuehne, Jensen, Brogan and Eleftheriou.)

Objective: Several monogenic autoinflammatory disorders and primary immunodeficiencies can present early in life with features that may be mistaken for Behçet's disease (BD). We aimed to develop a genetic analysis workflow to identify rare monogenic BD-like diseases and establish the contribution of HLA haplotype in a cohort of patients from the UK., Methods: Patients with clinically suspected BD were recruited from four BD specialist care centres in the UK. All participants underwent whole exome sequencing (WES), and genetic analysis thereafter by 1. examining genes known to cause monogenic immunodeficiency, autoinflammation or vasculitis by virtual panel application; 2. scrutiny of variants prioritised by Exomiser using Human Phenotype Ontology (HPO); 3. identification of copy number variants using ExomeDepth; and 4. HLA-typing using OptiType., Results: Thirty-one patients were recruited: median age 15 (4-52), and median disease onset age 5 (0-20). Nine/31 (29%) patients had monogenic disease mimicking BD: 5 cases of Haploinsufficiency of A20 with novel TNFAIP3 variants (p.T76I, p.M112Tfs*8, p.S548Dfs*128, p.C657Vfs*14, p.E661Nfs*36); 1 case of ISG15 deficiency with a novel nonsense variant (ISG15:p.Q16X) and 1p36.33 microdeletion; 1 case of Common variable immune deficiency (TNFRSF13B:p.A181E); and 2 cases of TNF receptor associated periodic syndrome (TNFRSF1A:p.R92Q). Of the remaining 22 patients, 8 (36%) were HLA-B*51 positive., Conclusion: We describe a novel genetic workflow for BD, which can efficiently detect known and potentially novel monogenic forms of BD, whilst additionally providing HLA-typing. Our results highlight the importance of genetic testing before BD diagnosis, since this has impact on choice of therapy, prognosis, and genetic counselling., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Background: High tube current generates a high flux of x-rays to photon counting detectors (PCDs) that can potentially result in the piling up of pulses formed by concurrent photons, which can cause count loss and energy resolution degradation., Purpose: To evaluate the performance of clinical photon-counting CT (PCCT) systems in high flux, potentially influenced by pulse pileup effects, in terms of task-generic image quality metrics., Methods: A clinical phantom was scanned on a commercial PCCT scanner (NAEOTOM Alpha, Siemens) at 120 kV under fourteen different tube current levels (40-1000 mA) with a rotation time of 0.25 s and a pitch of 1. The dose levels corresponded to CTDI vol (32 cm phantom) of 0.79-19.8 mGy. CT sinograms were reconstructed using QIR-off mode (noniterative reconstruction algorithm), Br44 kernel, and a voxel size of 0.4102 × 0.4102 × 3 mm 3 $0.4102 \times 0.4102 \times 3{\mathrm{\ mm}}^3$ . imQuest, an open-source MATLAB-based software package was used to calculate noise power spectrum (NPS), task transfer function (TTF), contrast-to-noise ratio (CNR), and CT number according to AAPM Task Group 233 metrology., Results: The 50% cut-off frequency of TTF (f 50 ) remained mostly constant across all higher tube currents for all inserts, namely polyethylene, bone, air, and acrylic. Using the lowest two data points (40 and 80 mA), the expected relationship between noise magnitude and tube current was determined to be noise ∝ $ \propto \ $ mA -0.47 . The measured noise magnitude were up to 11.1% higher than the expected value at the highest tube current. The average frequency of NPS (f av ) decreased from 0.32 to 0.29 mm -1 as tube current increased from 40 to 1000 mA. No considerable effects were observed in CT number measurement of any insert; however, CT numbers for air and bone changed almost monotonically as tube current increased. Absolute CNR increased monotonically for all inserts; however, the difference between measured and expected CNRs were approximately -6% to 12% across all tube currents., Conclusions: Increasing tube currents did not affect the spatial resolution, but slightly affected the CT number and noise measurements of the clinical PCCT system. However, the effects were only considerable at clinically irrelevant tube currents used on a small 20-cm phantom. In general clinical practices, automatic exposure control techniques are used to decrease the variation of flux on the detector, which alleviates the chances of detector saturation due to high count rates. The observed effects could be due to pulse pileup, signal-dependent filtration of the system, or nonlinearities in the reconstruction algorithm. In conclusion, either the deadtime of the detector used in the photon-counting CT system is shorter such that count losses due to pulse pileup are negligible, or pulse pileup has inconsiderable effects on the image quality of clinical photon-counting CT systems in routine clinical practice due to possible corrections applied on the system., (© 2023 American Association of Physicists in Medicine.)

Background: The accuracy and variability of quantification in computed tomography angiography (CTA) are affected by the interplay of imaging parameters and patient attributes. The assessment of these combined effects has been an open engineering challenge., Purpose: In this study, we developed a framework that optimizes imaging parameters for accurate and consistent coronary stenosis quantification in cardiac CTA while accounting for patient-specific variables., Methods: The framework utilizes a task-specific image quality index, the estimability index ( e ' ), approximated by a surrogate estimability polynomial function (EPF) capable of finding the optimal protocol that (1) maximizes image quality with an upper bound for desired radiation dose or (2) minimizes the dose level with a lower bound of acceptable image quality. The optimization process was formulated with the decision variables being subject to a set of constraints. The methodology was verified using CTA data from a prior clinical trial (prospective multi-center imaging study for evaluation of chest pain) by assessing the concordance of its prediction with the trial results. Further, the framework was used to derive an optimum protocol for each case based on the patient attributes, gauging how much improvement would have been possible if the derived optimized protocol would have been deployed., Results: The framework produced results consistent with imaging physics principles with approximated EPFs of 97% accuracy. The feature importance evaluation demonstrated a close match with earlier studies. The verification study found e ' scores closely predicting the cardiologist scores to within 95% in terms of the area under the receiver operating characteristic curve and predicting potential for either an average of fourfold increase in e ' within a targeted dose or a reduction in radiation dose by an average of 57% without reducing the image quality., Conclusions: The protocol optimization framework provides means to assess and optimize CTA in terms of either image quality or radiation dose objectives with its results predicting prior clinical trial findings., (© 2023 Society of Photo-Optical Instrumentation Engineers (SPIE).)

Rationale and Objectives: Deep silicon-based photon-counting CT (Si-PCCT) is an emerging detector technology that provides improved spatial resolution by virtue of its reduced pixel sizes. This article reports the outcomes of the first simulation study evaluating the impact of this advantage over energy-integrating CT (ECT) for estimation of morphological radiomics features in lung lesions., Materials and Methods: A dynamic nutrient-access-based stochastic model was utilized to generate three distinct morphologies for lung lesions. The lesions were inserted into the lung parenchyma of an anthropomorphic phantom (XCAT - 50 th percentile BMI) at 50, 70, and 90 mm from isocenter. The phantom was virtually imaged with an imaging simulator (DukeSim) modeling a Si-PCCT and a conventional ECT system using varying imaging conditions (dose, reconstruction kernel, and pixel size). The imaged lesions were segmented using a commercial segmentation tool (AutoContour, Advantage Workstation Server 3.2, GE Healthcare) followed by extraction of morphological radiomics features using an open-source radiomics package (pyradiomics). The estimation errors for both systems were computed as percent differences from corresponding feature values estimated for the ground-truth lesions., Results: Compared to ECT, the mean estimation error was lower for Si-PCCT (independent features: 35.9% vs. 54.0%, all features: 54.5% vs. 68.1%) with statistically significant reductions in errors for 8/14 features. For both systems, the estimation accuracy was minimally affected by dose and distance from the isocenter while reconstruction kernel and pixel size were observed to have a relatively stronger effect., Conclusion: For all lesions and imaging conditions considered, Si-PCCT exhibited improved estimation accuracy for morphological radiomics features over a conventional ECT system, demonstrating the potential of this technology for improved quantitative imaging., (Copyright © 2022 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Objectives: Application of 'treat-to-target' (T2T) in childhood-onset systemic lupus erythematosus (cSLE) may improve care and health outcomes. This initiative aimed to harmonise existing evidence and expert opinion regarding T2T for cSLE., Methods: An international T2T Task Force was formed of specialists in paediatric rheumatology, paediatric nephrology, adult rheumatology, patient and parent representatives. A steering committee formulated a set of draft overarching principles and points-to-consider, based on evidence from systematic literature review. Two on-line preconsensus meeting Delphi surveys explored healthcare professionals' views on these provisional overarching principles and points-to-consider. A virtual consensus meeting employed a modified nominal group technique to discuss, modify and vote on each overarching principle/point-to-consider. Agreement of >80% of Task Force members was considered consensus., Results: The Task Force agreed on four overarching principles and fourteen points-to-consider. It was agreed that both treatment targets and therapeutic strategies should be subject to shared decision making with the patient/caregivers, with full remission the preferred target, and low disease activity acceptable where remission cannot be achieved. Important elements of the points-to-consider included: aiming for prevention of flare and organ damage; glucocorticoid sparing; proactively addressing factors that impact health-related quality of life (fatigue, pain, mental health, educational challenges, medication side effects); and aiming for maintenance of the target over the long-term. An extensive research agenda was also formulated., Conclusions: These international, consensus agreed overarching principles and points-to-consider for T2T in cSLE lay the foundation for future T2T approaches in cSLE, endorsed by the Paediatric Rheumatology European Society., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: CT scan has notable potential to quantify the severity and progression of emphysema in patients. Such quantification should ideally reflect the true attributes and pathologic conditions of subjects, not scanner parameters. To achieve such an objective, the effects of the scanner conditions need to be understood so the influence can be mitigated., Research Question: How do CT scan imaging parameters affect the accuracy of emphysema-based quantifications and biomarkers?, Study Design and Methods: Twenty anthropomorphic digital phantoms were developed with diverse anatomic attributes and emphysema abnormalities informed by a real COPD cohort. The phantoms were input to a validated CT scan simulator (DukeSim), modeling a commercial scanner (Siemens Flash). Virtual images were acquired under various clinical conditions of dose levels, tube current modulations (TCM), and reconstruction techniques and kernels. The images were analyzed to evaluate the effects of imaging parameters on the accuracy of density-based quantifications (percent of lung voxels with HU < -950 [LAA-950] and 15 th percentile of lung histogram HU [Perc15]) across varied subjects. Paired t tests were performed to explore statistical differences between any two imaging conditions., Results: The most accurate imaging condition corresponded to the highest acquired dose (100 mAs) and iterative reconstruction (SAFIRE) with the smooth kernel of I31, where the measurement errors (difference between measurement and ground truth) were 35 ± 3 Hounsfield Units (HU), -4% ± 5%, and 26 ± 10 HU (average ± SD), for the mean lung HU, LAA-950, and Perc15, respectively. Without TCM and at the I31 kernel, increase of dose (20 to 100 mAs) improved the lung mean absolute error (MAE) by 4.2 ± 2.3 HU (average ± SD). TCM did not contribute to a systematic improvement of lung MAE., Interpretation: The results highlight that although CT scan quantification is possible, its reliability is impacted by the choice of imaging parameters. The developed virtual imaging trial platform in this study enables comprehensive evaluation of CT scan methods in reliable quantifications, an effort that cannot be readily made with patient images or simplistic physical phantoms., (Copyright © 2022 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Objectives: Juvenile-onset systemic lupus erythematosus (jSLE) affects 15-20% of lupus patients. Clinical heterogeneity between racial groups, age groups and individual patients suggests variable pathophysiology. This study aimed to identify highly penetrant damaging mutations in genes associated with SLE/SLE-like disease in a large national cohort (UK JSLE Cohort Study) and compare demographic, clinical and laboratory features in patient sub-cohorts with 'genetic' SLE vs remaining SLE patients., Methods: Based on a sequencing panel designed in 2018, target enrichment and next-generation sequencing were performed in 348 patients to identify damaging gene variants. Findings were integrated with demographic, clinical and treatment related datasets., Results: Damaging gene variants were identified in ∼3.5% of jSLE patients. When compared with the remaining cohort, 'genetic' SLE affected younger children and more Black African/Caribbean patients. 'Genetic' SLE patients exhibited less organ involvement and damage, and neuropsychiatric involvement developed over time. Less aggressive first line treatment was chosen in 'genetic' SLE patients, but more second and third line agents were used. 'Genetic' SLE associated with anti-dsDNA antibody positivity at diagnosis and reduced ANA, anti-LA and anti-Sm antibody positivity at last visit., Conclusion: Approximately 3.5% of jSLE patients present damaging gene variants associated with younger age at onset, and distinct clinical features. As less commonly observed after treatment induction, in 'genetic' SLE, autoantibody positivity may be the result of tissue damage and explain reduced immune complex-mediated renal and haematological involvement. Routine sequencing could allow for patient stratification, risk assessment and target-directed treatment, thereby increasing efficacy and reducing toxicity., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Chronic obstructive pulmonary disease (COPD) is one of the top three causes of death worldwide, characterized by emphysema and bronchitis. Airway measurements reflect the severity of bronchitis and other airway-related diseases. Airway structures can be objectively evaluated with quantitative computed tomography (CT). The accuracy of such quantifications is limited by the spatial resolution and image noise characteristics of the imaging system and can be potentially improved with the emerging photon-counting CT (PCCT) technology. This study evaluated the quantitative performance of PCCT against energy-integrating CT (EICT) systems for airway measurements, and further identified optimum CT imaging parameters for such quantifications. The study was performed using a novel virtual imaging framework by developing the first library of virtual patients with bronchitis. These virtual patients were developed based on CT images of confirmed COPD patients with varied bronchitis severity. The human models were virtually imaged at 6.3 and 12.6 mGy dose levels using a scanner-specific simulator (DukeSim), synthesizing clinical PCCT and EICT scanners (NAEOTOM Alpha, FLASH, Siemens). The projections were reconstructed with two algorithms and kernels at different matrix sizes and slice thicknesses. The CT images were used to quantify clinically relevant airway measurements ("Pi10" and "WA%") and compared against their ground truth values. Compared to EICT, PCCT provided more accurate Pi10 and WA% measurements by 63.1% and 68.2%, respectively. For both technologies, sharper kernels and larger matrix sizes led to more reliable bronchitis quantifications. This study highlights the potential advantages of PCCT against EICT in characterizing bronchitis utilizing a virtual imaging platform.

Photon-counting CT (PCCT) is an emerging imaging technology with potential improvements in quantification and rendition of micro-structures due to its smaller detector sizes. The aim of this study was to assess the performance of a new PCCT scanner (NAEOTOM Alpha, Siemens) in quantifying clinically relevant bone imaging biomarkers for characterization of common bone diseases. We evaluated the ability of PCCT in quantifying microarchitecture in bones compared to conventional energy-integrating CT. The quantifications were done through virtual imaging trials, using a 50 percentile BMI male virtual patient, with a detailed model of trabecular bone with varied bone densities in the lumbar spine. The virtual patient was imaged using a validated CT simulator (DukeSim) at CTDI vol of 20 and 40 mGy for three scan modes: ultra-high-resolution PCCT (UHR-PCCT), high-resolution PCCT (HR-PCCT), and a conventional energy-integrating CT (EICT) (FORCE, Siemens). Further, each scan mode was reconstructed with varying parameters to evaluate their effect on quantification. Bone mineral density (BMD), trabecular volume to total bone volume (BV/TV), and radiomics texture features were calculated in each vertebra. The most accurate BMD measurements relative to the ground truth were UHR-PCCT images (error: 3.3% ± 1.5%), compared to HR-PCCT (error: 5.3% ± 2.0%) and EICT (error: 7.1% ± 2.0%). UHR-PCCT images outperformed EICT and HR-PCCT. In BV/TV quantifications, UHR-PCCT (errors of 29.7% ± 11.8%) outperformed HR-PCCT (error: 80.6% ± 31.4%) and EICT (error: 67.3% ± 64.3). UHR-PCCT and HR-PCCT texture features were sensitive to anatomical changes using the sharpest kernel. Conversely, the texture radiomics showed no clear trend to reflect the progression of the disease in EICT. This study demonstrated the potential utility of PCCT technology in improved performance of bone quantifications leading to more accurate characterization of bone diseases.

The rendition of medical images influences the accuracy and precision of quantifications. Image variations or biases make measuring imaging biomarkers challenging. The objective of this paper is to reduce the variability of computed tomography (CT) quantifications for radiomics and biomarkers using physics-based deep neural networks (DNNs). With the proposed framework, it is possible to harmonize the different renditions of a single CT scan (with variations in reconstruction kernel and dose) into an image that is in close agreement with the ground truth. To this end, a generative adversarial network (GAN) model was developed where the generator is informed by the scanner's modulation transfer function (MTF). To train the network, a virtual imaging trial (VIT) platform was used to acquire CT images, from a set of forty computational models (XCAT) serving as the patient model. Phantoms with varying levels of pulmonary disease, such as lung nodules and emphysema, were used. We scanned the patient models with a validated CT simulator (DukeSim) modeling a commercial CT scanner at 20 and 100 mAs dose levels and then reconstructed the images by twelve kernels representing smooth to sharp kernels. An evaluation of the harmonized virtual images was conducted in four different ways: 1) visual quality of the images, 2) bias and variation in density-based biomarkers, 3) bias and variation in morphological-based biomarkers, and 4) Noise Power Spectrum (NPS) and lung histogram. The trained model harmonized the test set images with a structural similarity index of 0.95±0.1, a normalized mean squared error of 10.2±1.5%, and a peak signal-to-noise ratio of 31.8±1.5 dB. Moreover, emphysema-based imaging biomarkers of LAA-950 (-1.5±1.8), Perc15 (13.65±9.3), and Lung mass (0.1±0.3) had more precise quantifications.

Respiratory X-ray imaging enhanced by phase contrast has shown improved airway visualization in animal models. Limitations in current X-ray technology have nevertheless hindered clinical translation, leaving the potential clinical impact an open question. Here, we explore phase-contrast chest radiography in a realistic in silico framework. Specifically, we use preprocessed virtual patients to generate in silico chest radiographs by Fresnel-diffraction simulations of X-ray wave propagation. Following a reader study conducted with clinical radiologists, we predict that phase-contrast edge enhancement will have a negligible impact on improving solitary pulmonary nodule detection (6 to 20 mm). However, edge enhancement of bronchial walls visualizes small airways (< 2 mm), which are invisible in conventional radiography. Our results show that phase-contrast chest radiography could play a future role in observing small-airway obstruction (e.g., relevant for asthma or early-stage chronic obstructive pulmonary disease), which cannot be directly visualized using current clinical methods, thereby motivating the experimental development needed for clinical translation. Finally, we discuss quantitative requirements on distances and X-ray source/detector specifications for clinical implementation of phase-contrast chest radiography.

Background: Quantitative analysis of computed tomography (CT) images traditionally utilizes real patient data that can pose challenges with replicability, efficiency, and radiation exposure. Instead, virtual imaging trials (VITs) can overcome these hurdles through computer simulations of models of patients and imaging systems. DukeSim is a scanner-specific CT imaging simulator that has previously been validated with simple cylindrical phantoms, but not with anthropomorphic conditions and clinically relevant measurements., Purpose: To validate a scanner-specific CT simulator (DukeSim) for the assessment of lung imaging biomarkers under clinically relevant conditions across multiple scanners using an anthropomorphic chest phantom, and to demonstrate the utility of virtual trials by studying the effects or radiation dose and reconstruction kernels on the lung imaging quantifications., Methods: An anthropomorphic chest phantom with customized tube inserts was imaged with two commercial scanners (Siemens Force and Siemens Flash) at 28 dose and reconstruction conditions. A computational version of the chest phantom was used with a scanner-specific CT simulator (DukeSim) to simulate virtual images corresponding to the settings of the real acquisitions. Lung imaging biomarkers were computed from both real and simulated CT images and quantitatively compared across all imaging conditions. The VIT framework was further utilized to investigate the effects of radiation dose (20-300 mAs) and reconstruction settings (Qr32f, Qr40f, and Qr69f reconstruction kernels using ADMIRE strength 3) on the accuracy of lung imaging biomarkers, compared against the ground-truth values modeled in the computational chest phantom., Results: The simulated CT images matched closely the real images for both scanners and all imaging conditions qualitatively and quantitatively, with the average biomarker percent error of 3.51% (range 0.002%-18.91%). The VIT study showed that sharper reconstruction kernels had lower accuracy with errors in mean lung HU of 84-94 HU, lung volume of 797-3785 cm 3 , and lung mass of -800 to 1751 g. Lower tube currents had the lower accuracy with errors in mean lung HU of 6-84 HU, lung volume of 66-3785 cm 3 , and lung mass of 170-1751 g. Other imaging biomarkers were consistent under the studied reconstruction settings and tube currents., Conclusion: We comprehensively evaluated the realism of DukeSim in an anthropomorphic setup across a diverse range of imaging conditions. This study paves the way toward utilizing VITs more reliably for conducting medical imaging experiments that are not practical using actual patient images., (© 2022 American Association of Physicists in Medicine.)

Objective: To devise a patient-informed time series model that predicts liver contrast enhancement, by integrating clinical data and pharmacokinetics models, and to assess its feasibility to improve enhancement consistency in contrast-enhanced liver CT scans., Methods: The study included 1577 Chest/Abdomen/Pelvis CT scans, with 70-30% training/validation-testing split. A Gaussian function was used to approximate the early arterial, late arterial, and the portal venous phases of the contrast perfusion curve of each patient using their respective bolus tracking and diagnostic scan data. Machine learning models were built to predict the Gaussian parameters of each patient using the patient attributes (weight, height, age, sex, BMI). Pearson's coefficient, mean absolute error, and root mean squared error were used to assess the prediction accuracy., Results: The integration of the pharmacokinetics model with a two-layered neural network achieved the highest prediction accuracy on the test data (R 2  = 0.61), significantly exceeding the performance of the pharmacokinetics model alone (R 2  = 0.11). Applying the model demonstrated that adjusting the contrast administration directed by the model may reduce clinical enhancement inconsistency by up to 40 %., Conclusions: A new model using a Gaussian function and supervised machine learning can be used to build liver parenchyma contrast enhancement prediction model. The model can have utility in clinical settings to optimize and improve consistency in contrast-enhanced liver imaging., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

In this study, a magnetic solid-phase extraction method was developed based on multi-wall carbon nanotubes decorated by magnetic nanoparticles (Fe 3 O 4 ) and cadmium sulfide nanoparticles (Fe 3 O 4 @MWCNT-CdS) for trace extraction of cefixime and tetracycline antibiotics from urine and drug company wastewater. The adsorbent features were characterized by Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscope (FESEM), and energy dispersive X-ray analysis (EDX). Various effective parameters on the sorption and desorption cycle, such as sorption time, the mass of adsorbent, pH, salt addition, and material ratio, were investigated and optimized. The data were evaluated using isotherm models, and experimental data were well-fitted to both Langmuir (R 2 = 0.975) and Freundlich (R 2 = 0.985) models. Moreover, kinetic of reaction was agreement with pseudo-second-order (R 2 = 0.999) as compared pseudo-first-order (R 2 = 0.760). The maximum adsorption capacity for tetracycline and cefixime was achieved at 116.27 and 105.26 mg·g -1 , respectively. Hence, the prepared adsorbent can be used as an alternative material for enhanced determination of pharmaceutical substances in biological fluids., Competing Interests: The authors declare no conflict of interest.

Fewer studies in recent years have been conducted on the nutritional potential and fermentation quality of silage prepared from pomegranate leaves (PL). So, we investigated the nutritional-fermentation quality of PL before and after ensiling with or without yogurt containing mainly lactic acid-producing bacteria (Lactobacillus bulgaricus and Streptococcus thermophiles) and molasses (at two levels of 2 and 4% of dry matter) in the polyethylene microsilos for 60 days. A range of dry matter (29.1-39.1%), crude protein (3.85-4.83%), ash (5.33-8.60%), and non-fiber carbohydrates (53.2%-58.6%) contents were observed among the treatments. A significant increase in calcium, potassium, magnesium, manganese, iron, and zinc was observed in PL after ensiling compared to before ensiling (p < 0.05). The PL ensiled with 4% yogurt exhibited the highest ammonia nitrogen, lactic and acetic acids, but the lowest butyric acid among the ensiled PL (p < 0.05). The ensiling of PL without additive (control) significantly decreased potential gas production, dry matter digestibility, organic matter digestibility, total volatile fatty acids, metabolizable energy, net energy for lactation, base-buffering capacity, titratable alkalinity, and acid-base buffering capacity compared to before ensiling (p < 0.05). According to the present results, the nutritional value of PL before ensiling was higher than after ensiling. The addition of yogurt and molasses to PL at the ensiling process especially at 4% of dry matter, improved the fermentation and nutritional characteristics. In general, the addition of yogurt or molasses as two cheap and available additives is recommended to improve the digestive-fermentation parameters of PL in silo and ruminal environments., (© 2022. The Author(s).)

Objectives: To assess the achievability and effect of attaining low disease activity (LDA) or remission in childhood-onset SLE (cSLE)., Methods: Attainment of three adult-SLE derived definitions of LDA (LLDAS, LA, Toronto-LDA), and four definitions of remission (clinical-SLEDAI-defined remission on/off treatment, pBILAG-defined remission on/off treatment) was assessed in UK JSLE Cohort Study patients longitudinally. Prentice-Williams-Petersen gap recurrent event models assessed the impact of LDA/remission attainment on severe flare/new damage., Results: LLDAS, LA and Toronto-LDA targets were reached in 67%, 73% and 32% of patients, after a median of 18, 15 or 17 months, respectively. Cumulatively, LLDAS, LA and Toronto-LDA was attained for a median of 23%, 31% and 19% of total follow-up-time, respectively. Remission on-treatment was more common (61% cSLEDAI-defined, 42% pBILAG-defined) than remission off-treatment (31% cSLEDAI-defined, 21% pBILAG-defined). Attainment of all target states, and disease duration (>1 year), significantly reduced the hazard of severe flare (P < 0.001). As cumulative time in each target increased, hazard of severe flare progressively reduced. LLDAS attainment reduced the hazard of severe flare more than LA or Toronto-LDA (P < 0.001). Attainment of LLDAS and all remission definitions led to a statistically comparable reduction in the hazards of severe flare (P > 0.05). Attainment of all targets reduced the hazards of new damage (P < 0.05)., Conclusions: This is the first study demonstrating that adult-SLE-derived definitions of LDA/remission are achievable in cSLE, significantly reducing risk of severe flare/new damage. Of the LDA definitions, LLDAS performed best, leading to a statistically comparable reduction in the hazards of severe flare to attainment of clinical remission., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Background: We report a three-year-old girl with a potentially unique phenotype of perinatal onset and neurovascular features who was found to have PAMI syndrome. We also compare her case to those previously reported and review the differences between the PSTPIP1-associated inflammatory diseases (PAID) phenotypes and genotypes., Case Presentation: The patient was found to have a heterozygous pathogenic variant in PSTPIP1 (c.748G > A p.E250K). This variant was shown to be absent in both parents and therefore de novo in the patient. A literature review was carried out through multiple databases using the terms PSTPIP1, PAID, PAPA syndrome and PAMI syndrome. This information was collected and used to form comparisons between the current literature and our reported case., Conclusions: Our case contributes to the literature on PAMI syndrome whilst providing an example of a potentially unique clinical phenotype, giving insight into the pre-symptomatic phase of the condition. We highlight the importance of considering PAMI syndrome in the differential for early onset unexplained inflammation. In addition, we explore the possibility that perinatal neurovascular events could be an early feature of PAMI syndrome., (© 2022. The Author(s).)

Ion mobility spectrometers (IMS) are widely used in the security industry as well as in analytical measurements. Nevertheless, the IMS input is dynamic in nature because the sampling input can vary over time. Similar to most instruments, IMS is unable to respond immediately to variations in the input sample. Therefore, the measurements are made under transient conditions, which may affect the results. This work investigates the dynamic response of an IMS to different inputs, including steps, pulsed, exponential, and Gaussian functions. A theoretical model was developed based on two phenomena: the accumulation or dilution of a sample in the ionization region and the adsorption or desorption inside the injection port. Both processes have a charging/discharging nature. Thus, a mathematical expression was derived that takes into account two RC circuits in series. Fitting the output signal of the experimental data to the expression obtained from the model gave reasonable time constants of 2-4 s and 15-20 s for the dilution and the desorption processes, respectively. The model performance was evaluated by comparing the output with the experimental results, which were in excellent correlation. IMS was also found to behave in a manner similar to a second-order instrument, in which the output is related to the input via a second-order differential equation. These results are applicable to GC-IMS and IMS-based detectors.