A model of human neural networks reveals NPTX2 pathology in ALS and FTLD.

Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms2-5 that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors6. Single-cell transcriptomics and comparison to independent neural stem cells7 showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids8. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3' untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity.

Ncs2* mediates in vivo virulence of pathogenic yeast through sulphur modification of cytoplasmic transfer RNA.

Fungal pathogens threaten ecosystems and human health. Understanding the molecular basis of their virulence is key to develop new treatment strategies. Here, we characterize NCS2*, a point mutation identified in a clinical baker's yeast isolate. Ncs2 is essential for 2-thiolation of tRNA and the NCS2* mutation leads to increased thiolation at body temperature. NCS2* yeast exhibits enhanced fitness when grown at elevated temperatures or when exposed to oxidative stress, inhibition of nutrient signalling, and cell-wall stress. Importantly, Ncs2* alters the interaction and stability of the thiolase complex likely mediated by nucleotide binding. The absence of 2-thiolation abrogates the in vivo virulence of pathogenic baker's yeast in infected mice. Finally, hypomodification triggers changes in colony morphology and hyphae formation in the common commensal pathogen Candida albicans resulting in decreased virulence in a human cell culture model. These findings demonstrate that 2-thiolation of tRNA acts as a key mediator of fungal virulence and reveal new mechanistic insights into the function of the highly conserved tRNA-thiolase complex.

Dynamic 23S rRNA modification ho5C2501 benefits Escherichia coli under oxidative stress.

Post-transcriptional modifications are added to ribosomal RNAs (rRNAs) to govern ribosome biogenesis and to fine-tune protein biosynthesis. In Escherichia coli and related bacteria, RlhA uniquely catalyzes formation of a 5-hydroxycytidine (ho5C) at position 2501 of 23S rRNA. However, the molecular and biological functions as well as the regulation of ho5C2501 modification remain unclear. We measured growth curves with the modification-deficient ΔrlhA strain and quantified the extent of the modification during different conditions by mass spectrometry and reverse transcription. The levels of ho5C2501 in E. coli ribosomes turned out to be highly dynamic and growth phase-dependent, with the most effective hydroxylation yields observed in the stationary phase. We demonstrated a direct effect of ho5C2501 on translation efficiencies in vitro and in vivo. High ho5C2501 levels reduced protein biosynthesis which however turned out to be beneficial for E. coli for adapting to oxidative stress. This functional advantage was small under optimal conditions or during heat or cold shock, but becomes pronounced in the presence of hydrogen peroxide. Taken together, these data provided first functional insights into the role of this unique 23S rRNA modification for ribosome functions and bacterial growth under oxidative stress.

Association of enlarged extra-axial spaces and subdural hemorrhage in preterm infants at term-equivalent age.

To determine the incidence of enlarged extra-axial space (EES) and its association with subdural hemorrhage (SDH) in a regional cohort of preterm infants. As part of a prospective cohort study of 395 preterm infants, brain magnetic resonance imaging (MRI) was collected on each infant at term-equivalent age. Six preterm infants showed evidence of SDH. We reviewed the MRIs to identify the incidence of EES in these 6 infants and the cohort broadly. We then completed a retrospective chart review of the 6 infants to identify any concerns for non-accidental trauma (NAT) since the MRI was obtained. The incidence of SDH in the cohort was 1.6%. The incidence of EES was 48.1% including all 6 infants with SDH. The incidence of SDH in infants with EES was 3.2%. The retrospective chart review of the 6 infants did not yield any evidence of NAT. The incidence of EES and SDH in our cohort was significantly higher than similar cohorts of term infants, demonstrating an increased risk in preterm infants. The incidence of SDH in infants with EES was greater than in the total cohort, suggesting that it is a risk factor for asymptomatic SDH in preterm infants.

Performing Quality Control on Magnetic Resonance Imaging Liver Fat/Iron Quantification Studies: A Critical Requirement.

OBJECTIVE: Nonalcoholic fatty liver and iron overload can lead to cirrhosis requiring early detection. Magnetic resonance (MR) imaging utilizing chemical shift-encoded sequences and multi-Time of Echo single-voxel spectroscopy (SVS) are frequently used for assessment. The purpose of this study was to assess various quality factors of technical acceptability and any deficiencies in technologist performance in these fat/iron MR quantification studies. METHODS: Institutional review board waived retrospective quality improvement review of 87 fat/iron MR studies performed over a 6-month period was evaluated. Technical acceptability/unacceptability for chemical shift-encoded sequences (q-Dixon and IDEAL-IQ) included data handling errors (missing maps), liver field coverage, fat/water swap, motion, or other artifacts. Similarly, data handling (missing table/spectroscopy), curve-fit, fat- and water-peak separation, and water-peak sharpness were evaluated for SVS technical acceptability. RESULTS: Data handling errors were found in 11% (10/87) of studies with missing maps or entire sequence (SVS or q-Dixon). Twenty-seven percent (23/86) of the q-Dixon/IDEAL-IQ were technically unacceptable (incomplete liver-field [39%], other artifacts [35%], significant/severe motion [18%], global fat/water swap [4%], and multiple reasons [4%]). Twenty-eight percent (21/75) of SVS sequences were unacceptable (water-peak broadness [67%], poor curve-fit [19%] overlapping fat and water peaks [5%], and multiple reasons [9%]). CONCLUSIONS: A high rate of preventable errors in fat/iron MR quantification studies indicates the need for routine quality control and evaluation of technologist performance and technical deficiencies that may exist within a radiology practice. Potential solutions such as instituting a checklist for technologists during each acquisition procedure and routine auditing may be required.

World Health Organization MPOWER for tobacco control in India: a 6-year retrospective analysis.

Background: Prevalence and practices of tobacco usage in India are diverse and incongruent and Government of India has enacted various laws to overcome this burden. To make tobacco control measures effective and powerful, WHO introduced MPOWER in 2004 and India was one of the first countries that implemented the MPOWER. Objective: This study is aimed to quantify the implementation of MPOWER tobacco control policies in India. Material and Methods: In this retrospective analysis, data was gathered from the WHO MPOWER of India from 2015 to 2021. This analysis was based on the checklist which was designed previously by Iranian and international tobacco control specialists in their study on tobacco control. Results: In the present comparative analysis, India was categorized by scores and these were acquired from each indicator for each activity and 2021 year got the highest scores as compared to the previous year scores i.e. 27 in 2015. In context to individual indicators, noticeable increase in scores has been seen in both health warning on cigarette packages and adult daily smoking prevalence, whereas no progress was observed in smoking related policies. Conclusion: Although MPOWER programmes are widely accepted by the Indian government, but still substantial improvement in fewer sections is required.

Diagnostic accuracy and performance of artificial intelligence in measuring left atrial volumes and function on multiphasic CT in patients with atrial fibrillation.

OBJECTIVES: To evaluate the effectiveness of a novel artificial intelligence (AI) algorithm for fully automated measurement of left atrial (LA) volumes and function using cardiac CT in patients with atrial fibrillation. METHODS: We included 79 patients (mean age 63 ± 12 years; 35 with atrial fibrillation (AF) and 44 controls) between 2017 and 2020 in this retrospective study. Images were analyzed by a trained AI algorithm and an expert radiologist. Left atrial volumes were obtained at cardiac end-systole, end-diastole, and pre-atrial contraction, which were then used to obtain LA function indices. Intraclass correlation coefficient (ICC) analysis of the LA volumes and function parameters was performed and receiver operating characteristic (ROC) curve analysis was used to compare the ability to detect AF patients. RESULTS: The AI was significantly faster than manual measurement of LA volumes (4 s vs 10.8 min, respectively). Agreement between the manual and automated methods was good to excellent overall, and there was stronger agreement in AF patients (all ICCs ≥ 0.877; p < 0.001) than controls (all ICCs ≥ 0.799; p < 0.001). The AI comparably estimated LA volumes in AF patients (all within 1.3 mL of the manual measurement), but overestimated volumes by clinically negligible amounts in controls (all by ≤ 4.2 mL). The AI's ability to distinguish AF patients from controls using the LA volume index was similar to the expert's (AUC 0.81 vs 0.82, respectively; p = 0.62). CONCLUSION: The novel AI algorithm efficiently performed fully automated multiphasic CT-based quantification of left atrial volume and function with similar accuracy as compared to manual quantification. Novel CT-based AI algorithm efficiently quantifies left atrial volumes and function with similar accuracy as manual quantification in controls and atrial fibrillation patients. KEY POINTS: • There was good-to-excellent agreement between manual and automated methods for left atrial volume quantification. • The AI comparably estimated LA volumes in AF patients, but overestimated volumes by clinically negligible amounts in controls. • The AI's ability to distinguish AF patients from controls was similar to the manual methods.

Liver iron quantification in children and young adults: comparison of a volumetric multi-echo 3-D Dixon sequence with conventional 2-D T2* relaxometry.

BACKGROUND: Magnetic resonance imaging (MRI)-based liver iron quantification is the standard of care to guide chelation therapy in children at risk of hemochromatosis. T2* relaxometry is the most widely used technique but requires third-party software for post-processing. Vendor-provided three-dimensional (3-D) multi-echo Dixon techniques are now available that allow inline/automated post-processing. OBJECTIVE: The purpose of our study was to evaluate the diagnostic accuracy of a volumetric multi-echo Dixon technique using conventional T2* relaxometry as the reference standard in a pediatric and young adult population. MATERIALS AND METHODS: In this retrospective study, we queried the radiology information system to identify all MRIs performed for liver iron quantification from July 2015 to January 2020. All patients had undergone T2* relaxometry on a 1.5-tesla (T) scanner for liver iron concentration (LIC) estimation. In addition, a 3-D multi-echo Dixon was performed using Siemens Healthineers LiverLab (Erlangen, Germany). Two readers independently estimated liver R2* and T2* on the multi-echo Dixon by drawing free-hand regions of interest on the scanner-generated R2* and T2* maps. Conventional T2*-relaxometry-based LIC was the reference standard. We estimated interobserver agreement by concordance correlation coefficient (CCC). We used Bland-Altman analysis and Pearson correlation coefficient (r) to compare LIC by the two methods. RESULTS: Fifty-four MRIs on 38 patients (22 females) were available for analysis. Mean patient age was 11.8 years (standard deviation [SD] 5.3 years). Reference standard LIC ranged 1.1-21.1 (median 6.8) mg/g dry weight of liver. The concordance between readers for T2* estimation using 3-D multi-echo Dixon was substantial (CCC 0.99, confidence interval 0.99-1.00). Bland-Altman plot showed that all observations were clustered around the zero bias line if the LIC average was ≤8 mg/g, and r was very strong (reader 1 r=0.93, reader 2 r=0.92, both P-values <0.001). With increasing LIC, there was a pattern of poor agreement on the Bland-Altman plot, with observations crossing the lower limits of agreement, and r was very weak (reader 1 r=0.05, P-value 0.84; reader 2 r=0.17, P-value 0.44). CONCLUSION: Vendor-based 3-D multi-echo Dixon allows for excellent interobserver correlation in liver T2* estimation. LIC estimated by this method has a very strong correlation with conventional T2* relaxometry if liver iron overload is mild-moderate (LIC ≤8 mg/g).

Automated detection of lung nodules and coronary artery calcium using artificial intelligence on low-dose CT scans for lung cancer screening: accuracy and prognostic value.

BACKGROUND: Artificial intelligence (AI) in diagnostic radiology is undergoing rapid development. Its potential utility to improve diagnostic performance for cardiopulmonary events is widely recognized, but the accuracy and precision have yet to be demonstrated in the context of current screening modalities. Here, we present findings on the performance of an AI convolutional neural network (CNN) prototype (AI-RAD Companion, Siemens Healthineers) that automatically detects pulmonary nodules and quantifies coronary artery calcium volume (CACV) on low-dose chest CT (LDCT), and compare results to expert radiologists. We also correlate AI findings with adverse cardiopulmonary outcomes in a retrospective cohort of 117 patients who underwent LDCT. METHODS: A total of 117 patients were enrolled in this study. Two CNNs were used to identify lung nodules and CACV on LDCT scans. All subjects were used for lung nodule analysis, and 96 subjects met the criteria for coronary artery calcium volume analysis. Interobserver concordance was measured using ICC and Cohen's kappa. Multivariate logistic regression and partial least squares regression were used for outcomes analysis. RESULTS: Agreement of the AI findings with experts was excellent (CACV ICC = 0.904, lung nodules Cohen's kappa = 0.846) with high sensitivity and specificity (CACV: sensitivity = .929, specificity = .960; lung nodules: sensitivity = 1, specificity = 0.708). The AI findings improved the prediction of major cardiopulmonary outcomes at 1-year follow-up including major adverse cardiac events and lung cancer (AUCMACE = 0.911, AUCLung Cancer = 0.942). CONCLUSION: We conclude the AI prototype rapidly and accurately identifies significant risk factors for cardiopulmonary disease on standard screening low-dose chest CT. This information can be used to improve diagnostic ability, facilitate intervention, improve morbidity and mortality, and decrease healthcare costs. There is also potential application in countries with limited numbers of cardiothoracic radiologists.

Perinatal Risk and Protective Factors in the Development of Diffuse White Matter Abnormality on Term-Equivalent Age Magnetic Resonance Imaging in Infants Born Very Preterm.

OBJECTIVE: To identify perinatal clinical diseases and treatments that are associated with the development of objectively diagnosed diffuse white matter abnormality (DWMA) on structural magnetic resonance imaging (MRI) at term-equivalent age in infants born very preterm. STUDY DESIGN: A prospective cohort of 392 infants born very preterm (≤32 weeks of gestational age) was enrolled from 5 level III/IV neonatal intensive care units between September 2016 and November 2019. MRIs of the brain were collected at 39 to 45 weeks of postmenstrual age to evaluate DWMA volume. A predefined list of pertinent maternal characteristics, pregnancy/delivery data, and neonatal intensive care unit data were collected for enrolled patients to identify antecedents of objectively diagnosed DWMA. RESULTS: Of the 392 infants in the cohort, 377 (96%) had high-quality MRI data. Their mean (SD) gestational age was 29.3 (2.5) weeks. In multivariable linear regression analyses, pneumothorax (P = .027), severe bronchopulmonary dysplasia (BPD) (P = .009), severe retinopathy of prematurity (P < .001), and male sex (P = .041) were associated with increasing volume of DWMA. The following factors were associated with decreased risk of DWMA: postnatal dexamethasone therapy for severe BPD (P = .004), duration of caffeine therapy for severe BPD (P = .009), and exclusive maternal milk diet at neonatal intensive care unit discharge (P = .049). CONCLUSIONS: Severe retinopathy of prematurity and BPD exhibited the strongest adverse association with development of DWMA. We also identified treatments and nutritional factors that appear protective against the development of DWMA that also have implications for the clinical care of infants born very preterm.

Matching tRNA modifications in humans to their known and predicted enzymes.

tRNA are post-transcriptionally modified by chemical modifications that affect all aspects of tRNA biology. An increasing number of mutations underlying human genetic diseases map to genes encoding for tRNA modification enzymes. However, our knowledge on human tRNA-modification genes remains fragmentary and the most comprehensive RNA modification database currently contains information on approximately 20% of human cytosolic tRNAs, primarily based on biochemical studies. Recent high-throughput methods such as DM-tRNA-seq now allow annotation of a majority of tRNAs for six specific base modifications. Furthermore, we identified large gaps in knowledge when we predicted all cytosolic and mitochondrial human tRNA modification genes. Only 48% of the candidate cytosolic tRNA modification enzymes have been experimentally validated in mammals (either directly or in a heterologous system). Approximately 23% of the modification genes (cytosolic and mitochondrial combined) remain unknown. We discuss these 'unidentified enzymes' cases in detail and propose candidates whenever possible. Finally, tissue-specific expression analysis shows that modification genes are highly expressed in proliferative tissues like testis and transformed cells, but scarcely in differentiated tissues, with the exception of the cerebellum. Our work provides a comprehensive up to date compilation of human tRNA modifications and their enzymes that can be used as a resource for further studies.

A DICOM Framework for Machine Learning and Processing Pipelines Against Real-time Radiology Images.

Real-time execution of machine learning (ML) pipelines on radiology images is difficult due to limited computing resources in clinical environments, whereas running them in research clusters requires efficient data transfer capabilities. We developed Niffler, an open-source Digital Imaging and Communications in Medicine (DICOM) framework that enables ML and processing pipelines in research clusters by efficiently retrieving images from the hospitals' PACS and extracting the metadata from the images. We deployed Niffler at our institution (Emory Healthcare, the largest healthcare network in the state of Georgia) and retrieved data from 715 scanners spanning 12 sites, up to 350 GB/day continuously in real-time as a DICOM data stream over the past 2 years. We also used Niffler to retrieve images bulk on-demand based on user-provided filters to facilitate several research projects. This paper presents the architecture and three such use cases of Niffler. First, we executed an IVC filter detection and segmentation pipeline on abdominal radiographs in real-time, which was able to classify 989 test images with an accuracy of 96.0%. Second, we applied the Niffler Metadata Extractor to understand the operational efficiency of individual MRI systems based on calculated metrics. We benchmarked the accuracy of the calculated exam time windows by comparing Niffler against the Clinical Data Warehouse (CDW). Niffler accurately identified the scanners' examination timeframes and idling times, whereas CDW falsely depicted several exam overlaps due to human errors. Third, with metadata extracted from the images by Niffler, we identified scanners with misconfigured time and reconfigured five scanners. Our evaluations highlight how Niffler enables real-time ML and processing pipelines in a research cluster.

A Software Tool for Lyophilization Primary Drying Process Development and Scale-up Including Process Heterogeneity, I: Laboratory-Scale Model Testing.

Freeze-drying is a deceptively complex operation requiring sophisticated design of a robust and efficient process that includes understanding and planning for heterogeneity across the batch and shifts in parameters due to vial or lyophilizer changes. A software tool has been designed to assist in process development and scale-up based on a model that includes consideration of the process heterogeneity. Two drug formulations were used to test the ability of the new tool to develop a freeze-drying cycle and correctly predict product temperatures and drying times. Model inputs were determined experimentally, and the primary drying heterogeneous freeze-drying model was used to design drying cycles that provided data to verify the accuracy of model-predicted product temperature and primary drying time. When model inputs were accurate, model-predicted primary drying times were within 0.1 to 15.9% of experimentally measured values, and product temperature accuracy was between 0.2 and 1.2°C for three vial locations, center, inner edge, and outer edge. However, for some drying cycles, differences in vial heat transfer coefficients due to changes in shelf and product temperature as well as altered product resistance due to product temperature-dependent microcollapse increased inaccuracy (up to 28.6% difference in primary drying time and 5.1°C difference in product temperature). This highlights the need for careful determination of experimental conditions used to calculate model inputs. In future efforts, full characterization of location- and shelf temperature-dependentKv as well as location- and product temperature-dependentRp will enhance the accuracy of the predictions by the model within the user-friendly software.

Recommended Best Practices for Lyophilization Validation-2021 Part I: Process Design and Modeling.

This work describes lyophilization process validation and consists of two parts. Part I focuses on the process design and is described in the current paper, while part II is devoted to process qualification and continued process verification. The intent of these articles is to provide readers with recent updates on lyophilization validation in the light of community-based combined opinion on the process and reflect the industrial prospective. In this paper, the design space approach for process design is described in details, and examples from practice are provided. The approach shows the relationship between the process inputs; it is based on first principles and gives a thorough scientific understanding of process and product. The lyophilization process modeling and scale-up are also presented showing the impact of facility, equipment, and vial heat transfer coefficient. The case studies demonstrating the effect of batch sizes, fill volume, and dose strength to show the importance of modeling as well as the effect of controlled nucleation on product resistance are discussed.

Recommended Best Practices for Lyophilization Validation 2021 Part II: Process Qualification and Continued Process Verification.

This work describes the lyophilization process validation and consists of two parts. Part one (Part I: Process Design and Modeling) focuses on the process design and is described in the previous paper, while the current paper is devoted to process qualification and continued process verification. The goal of the study is to show the cutting edge of lyophilization validation based on the integrated community-based opinion and the industrial perspective. This study presents best practices for batch size determination and includes the effect of batch size on drying time, process parameters selection strategies, and batch size overage to compensate for losses during production. It also includes sampling strategies to demonstrate batch uniformity as well as the use of statistical models to ensure adequate sampling. Based on the LyoHUB member organizations survey, the best practices in determining the number of PPQ runs are developed including the bracketing approach with minimum and maximum loads. Standard practice around CQA and CPP selection is outlined and shows the advantages of using control charts and run charts for process trending and quality control. The case studies demonstrating the validation strategy for monoclonal antibody and the impact of the loading process on the lyophilization cycle and product quality as well as the special case of lyophilization for dual-chamber cartridge system are chosen to illustrate the process validation. The standard practices in the validation of the lyophilization process, special lyophilization processes, and their impact on the validation strategy are discussed.

Rupture Risk of Small Unruptured Intracranial Aneurysms in Japanese Adults.

Background and Purpose- Therapeutic decision making for small unruptured intracranial aneurysms (<10 mm) is difficult. We aimed to develop a rupture risk model for small intracranial aneurysms in Japanese adults, including clinical, morphological, and hemodynamic parameters. Methods- We analyzed 338 small unruptured aneurysms; 35 ruptured during the observation period, and 303 remained stable. Clinical, morphological, and hemodynamic parameters were considered. Computational fluid dynamics was used to calculate hemodynamic parameters based on computed tomography images of all aneurysms in their unruptured state. Differences between the ruptured and unruptured groups were tested by the Mann-Whitney U or Fisher exact tests. Multivariate logistic regression was applied to obtain a rupture risk model. Its predictive ability was investigated by receiver operating characteristic analysis. Results- The risk model revealed that rupture may be more likely to in younger patients (odds ratio [OR], 0.92 for each age increase of 1 year [95% CI, 0.88-0.96] P<0.001) with multiple aneurysms (OR, 2.58 [95% CI, 1.07-6.19] P=0.03), located at a bifurcation (OR, 5.45 [95% CI, 1.87-15.85] P=0.002), with a bleb (OR, 4.09 [95% CI, 1.42-11.79] P=0.009), larger length (OR, 1.91 for each increase of 1 mm [95% CI, 1.42-2.57] P<0.001), and lower pressure loss coefficient (OR, 0.33 for each decrease of 1 unit [95% CI, 0.14-0.77] P=0.01). The sensitivity, specificity, and area under the curve were 0.800, 0.752, and 0.826 (95% CI, 0.739-0.914) respectively. Conclusions- Younger age, presence of multiple aneurysms, location at a bifurcation, presence of a bleb, larger length, and lower pressure loss coefficient were identified as risk factors for rupture of small intracranial aneurysms. The risk model should be validated in further studies.

Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling.

Purpose To compare two technical approaches for determination of coronary computed tomography (CT) angiography-derived fractional flow reserve (FFR)-FFR derived from coronary CT angiography based on computational fluid dynamics (hereafter, FFRCFD) and FFR derived from coronary CT angiography based on machine learning algorithm (hereafter, FFRML)-against coronary CT angiography and quantitative coronary angiography (QCA). Materials and Methods A total of 85 patients (mean age, 62 years ± 11 [standard deviation]; 62% men) who had undergone coronary CT angiography followed by invasive FFR were included in this single-center retrospective study. FFR values were derived on-site from coronary CT angiography data sets by using both FFRCFD and FFRML. The performance of both techniques for detecting lesion-specific ischemia was compared against visual stenosis grading at coronary CT angiography, QCA, and invasive FFR as the reference standard. Results On a per-lesion and per-patient level, FFRML showed a sensitivity of 79% and 90% and a specificity of 94% and 95%, respectively, for detecting lesion-specific ischemia. Meanwhile, FFRCFD resulted in a sensitivity of 79% and 89% and a specificity of 93% and 93%, respectively, on a per-lesion and per-patient basis (P = .86 and P = .92). On a per-lesion level, the area under the receiver operating characteristics curve (AUC) of 0.89 for FFRML and 0.89 for FFRCFD showed significantly higher discriminatory power for detecting lesion-specific ischemia compared with that of coronary CT angiography (AUC, 0.61) and QCA (AUC, 0.69) (all P < .0001). Also, on a per-patient level, FFRML (AUC, 0.91) and FFRCFD (AUC, 0.91) performed significantly better than did coronary CT angiography (AUC, 0.65) and QCA (AUC, 0.68) (all P < .0001). Processing time for FFRML was significantly shorter compared with that of FFRCFD (40.5 minutes ± 6.3 vs 43.4 minutes ± 7.1; P = .042). Conclusion The FFRML algorithm performs equally in detecting lesion-specific ischemia when compared with the FFRCFD approach. Both methods outperform accuracy of coronary CT angiography and QCA in the detection of flow-limiting stenosis.

Impact of Natural Variations in Freeze-Drying Parameters on Product Temperature History: Application of Quasi Steady-State Heat and Mass Transfer and Simple Statistics.

Inter- and intra-batch variability in heat and mass transfer during the drying phase of lyophilization is well recognized. Heat transfer variability between individual vials in the same batch arise from both different positions in the vial array and from variations in the bottom contour of the vials, both effects contributing roughly equally to variations in the effective heat transfer coefficient of the vials, Kv. Both effects can be measured in the laboratory, and variations in average Kv values as a function of vial position in the array for lab and production can be calculated by use of the simple steady-state heat and mass transfer theory. Typically, in the laboratory dryer, vials on the edge of the array, "edge vials," run 2-4°C warmer than "center vials," but differences between laboratory and manufacturing temperatures are modest. The variability in mass transfer can be assigned to major variations in ice nucleation temperature (both intra-batch and inter-batch), including major differences between laboratory and manufacturing. The net effect of all random variations, for each class of vial, can be evaluated by a simple statistical model-propagation of error, which then allows prediction of the distribution in product temperatures and drying times, and therefore prediction of percent of vials dry and percent of vials collapsed and proximity to the edge of failure for a given process. Good agreement between theoretical and experimentally determined maximum temperatures in primary drying and percent collapsed product demonstrates the calculations have useful accuracy.

Comparative Evaluation of Different Bone Markers in Peri-implant Crevicular Fluid of Immediate Loaded and Nonloaded Dental Implants.

AIM: The present study was conducted to determine different bone markers in immediate loaded and nonloaded dental implants. MATERIALS AND METHODS: It comprised of 60 patients (males-30, females-30) which were divided into two groups of 30 each. Group I received immediate loaded dental implants, and group II received non-loaded dental implants. Modified bleeding on probing index, peri-implant sulcus depth was assessed in both groups at 1 month, 2 months, 3 months and 4 months. The crevicular fluid was obtained to determine bone markers levels such as transforming growth factor-alpha (TGF-a), osteocalcin (OCN), osteopontin (OPN), parathyroid hormone (PTH) and osteoprotegerin (OPG). RESULTS: Both groups revealed non-significant difference in modified bleeding on probing index and peri-implant sulcus depth (p > 0.05). Bone markers found to be elevated more in group I as compared to group II. However, the difference was non- significant (p > 0.05). CONCLUSION: Transforming growth factor alpha (TGF-a), OCN, OPN, OPG and PTH and parathyroid hormone (PTH) levels were higher in immediate loaded dental implants as compared to nonloaded dental implants. CLINICAL SIGNIFICANCE: Immediate loaded dental implants showed an increase in expression of bone markers such as TNF-a, OCN, OPN, PTH and OPG which may be useful in deciding future of immediate loaded dental implants.

Multiresolution imaging using golden angle stack-of-stars and compressed sensing for dynamic MR urography.

PURPOSE: To develop a novel multiresolution MRI methodology for accurate estimation of glomerular filtration rate (GFR) in vivo. MATERIALS AND METHODS: A three-dimensional golden-angle radial stack-of-stars (SoS) trajectory was used for data acquisition on a 3 Tesla MRI scanner. Multiresolution reconstruction and analysis was performed using arterial input function reconstructed at 1-s. temporal resolution and renal dynamic data reconstructed using compressed sensing (CS) with 4-s temporal resolution. The method was first validated using simulations and the clinical utility of the technique was evaluated by comparing the GFR estimates from the proposed method to the estimated GFR (eGFR) obtained from serum creatinine for 10 subjects. RESULTS: The 4-s temporal resolution CS images minimized streaking artifacts and noise while the 1-s temporal resolution AIF minimized errors in GFR estimates. A paired t-test showed that there was no statistically significant difference between MRI based total GFR values and serum creatinine based eGFR estimates (P = 0.92). CONCLUSION: We have demonstrated the feasibility of multiresolution MRI using a golden angle radial stack-of-stars scheme to accurately estimate GFR as well as produce diagnostic quality dynamic images in vivo. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:303-311.