Enhanced Stability of Iridium Nanocatalysts via Exsolution for the CO2 Reforming of Methane.

The reforming reactions of greenhouse gases require catalysts with high reactivity, coking resistance, and structural stability for efficient and durable use. Among the possible strategies, exsolution has been shown to demonstrate the requirements needed to produce appropriate catalysts for the dry reforming of methane, the conversion of which strongly depends on the choice of active species, its interaction with the support, and the catalyst size and dispersion properties. Here, we exploit the exsolution approach, known to produce stable and highly active nanoparticle-supported catalysts, to develop iridium-nanoparticle-decorated perovskites and apply them as catalysts for the dry reforming of methane. By studying the effect of several parameters, we tune the degree of exsolution, and consequently the catalytic activity, thereby identifying the most efficient sample, 0.5 atomic % Ir-BaTiO3, which showed 82% and 86% conversion of CO2 and CH4, respectively. By comparison with standard impregnated catalysts (e.g., Ir/Al2O3), we benchmark the activity and stability of our exsolved systems. We find almost identical conversion and syngas rates of formation but observe no carbon deposition for the exsolved samples after catalytic testing; such deposition was significant for the traditionally prepared impregnated Ir/Al2O3, with almost 30 mgC/gsample measured, compared to 0 mgC/gsample detected for the exsolved system. These findings highlight the possibility of achieving in a single step the mutual interaction of the parameters enhancing the catalytic efficiency, leading to a promising pathway for the design of catalysts for reforming reactions.

Long COVID Is Not a Functional Neurologic Disorder.

Long COVID is a common sequela of SARS-CoV-2 infection. Data from numerous scientific studies indicate that long COVID involves a complex interaction between pathophysiological processes. Long COVID may involve the development of new diagnosable health conditions and exacerbation of pre-existing health conditions. However, despite this rapidly accumulating body of evidence regarding the pathobiology of long COVID, psychogenic and functional interpretations of the illness presentation continue to be endorsed by some healthcare professionals, creating confusion and inappropriate diagnostic and therapeutic pathways for people living with long COVID. The purpose of this perspective is to present a clinical and scientific rationale for why long COVID should not be considered as a functional neurologic disorder. It will begin by discussing the parallel historical development of pathobiological and psychosomatic/sociogenic diagnostic constructs arising from a common root in neurasthenia, which has resulted in the collective understandings of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and functional neurologic disorder (FND), respectively. We will also review the case definition criteria for FND and the distinguishing clinical and neuroimaging findings in FND vs. long COVID. We conclude that considering long COVID as FND is inappropriate based on differentiating pathophysiologic mechanisms and distinguishing clinical findings.

Synergistic growth of nickel and platinum nanoparticles via exsolution and surface reaction.

Bimetallic catalysts combining precious and earth-abundant metals in well designed nanoparticle architectures can enable cost efficient and stable heterogeneous catalysis. Here, we present an interaction-driven in-situ approach to engineer finely dispersed Ni decorated Pt nanoparticles (1-6 nm) on perovskite nanofibres via reduction at high temperatures (600-800 oC). Deposition of Pt (0.5 wt%) enhances the reducibility of the perovskite support and promotes the nucleation of Ni cations via metal-support interaction, thereafter the Ni species react with Pt forming alloy nanoparticles, with the combined processes yielding smaller nanoparticles that either of the contributing processes. Tuneable uniform Pt-Ni nanoparticles are produced on the perovskite surface, yielding reactivity and stability surpassing 1 wt.% Pt/γ-Al2O3 catalysts for CO oxidation. This approach heralds the possibility of in-situ fabrication of supported bimetallic nanoparticles with engineered compositional distributions and performance.

Performance of GPT-4 on the American College of Radiology In-training Examination: Evaluating Accuracy, Model Drift, and Fine-tuning.

RATIONALE AND OBJECTIVES: In our study, we evaluate GPT-4's performance on the American College of Radiology (ACR) 2022 Diagnostic Radiology In-Training Examination (DXIT). We perform multiple experiments across time points to assess for model drift, as well as after fine-tuning to assess for differences in accuracy. MATERIALS AND METHODS: Questions were sequentially input into GPT-4 with a standardized prompt. Each answer was recorded and overall accuracy was calculated, as was logic-adjusted accuracy, and accuracy on image-based questions. This experiment was repeated several months later to assess for model drift, then again after the performance of fine-tuning to assess for changes in GPT's performance. RESULTS: GPT-4 achieved 58.5% overall accuracy, lower than the PGY-3 average (61.9%) but higher than the PGY-2 average (52.8%). Adjusted accuracy was 52.8%. GPT-4 showed significantly higher (p = 0.012) confidence for correct answers (87.1%) compared to incorrect (84.0%). Performance on image-based questions was significantly poorer (p < 0.001) at 45.4% compared to text-only questions (80.0%), with adjusted accuracy for image-based questions of 36.4%. When the questions were repeated, GPT-4 chose a different answer 25.5% of the time and there was no change in accuracy. Fine-tuning did not improve accuracy. CONCLUSION: GPT-4 performed between PGY-2 and PGY-3 levels on the 2022 DXIT, significantly poorer on image-based questions, and with large variability in answer choices across time points. Exploratory experiments in fine-tuning did not improve performance. This study underscores the potential and risks of using minimally-prompted general AI models in interpreting radiologic images as a diagnostic tool. Implementers of general AI radiology systems should exercise caution given the possibility of spurious yet confident responses.

Pretreatment Spatially Aware Magnetic Resonance Imaging Radiomics Can Predict Distant Brain Metastases (DBMs) After Stereotactic Radiosurgery/Radiation Therapy (SRS/SRT).

Purpose: Stereotactic radiosurgery/radiation therapy (SRS/SRT) increasingly has been used to treat brain metastases. However, the development of distant brain metastases (DBMs) in the untreated brain remains a serious complication. We sought to develop a spatially aware radiomic signature to model the time-to-DBM development in a cohort of patients leveraging pretreatment magnetic resonance imaging (MRI) and radiation therapy treatment planning data including radiation dose distribution maps. Methods and Materials: We retrospectively analyzed a cohort of 105 patients with brain metastases treated by SRS/SRT with pretreatment multiparametric MRI (T1, T1 postcontrast, T2, fluid-attenuated inversion recovery). Three-dimensional radiomic features were extracted from each MRI sequence within 5 isodose regions of interest (ROIs) identified via radiation dose distribution maps and gross target volume (GTV) contours. Clinical features including patient performance status, number of lesions treated, tumor volume, and tumor stage were collected to serve as a baseline for comparison. Cox proportional hazards (CPH) modeling and Kaplan-Meier analysis were used to model time-to-DBM development. Results: CPH models trained using radiomic features achieved a mean concordance index (c-index) of 0.63 (standard deviation [SD], 0.08) compared with a c-index of 0.49 (SD, 0.09) for CPH models trained using clinical factors. A CPH model trained using both radiomic and clinical features achieved a c-index of 0.69 (SD, 0.08). The identified radiomic signature was able to stratify patients into distinct risk groups with statistically significant differences (P = .00007) in time-to-DBM development as measured by log-rank test. Clinical features were unable to do the same. Radiomic features from the peritumoral 50% to 75% isodose ROI and GTV region were most predictive of DBM development. Conclusions: Our results suggest that radiomic features extracted from pretreatment MRI and multiple isodose ROIs can model time-to-DBM development in patients receiving SRS/SRT for brain metastases, outperforming clinical feature baselines. Notably, we believe we are the first to leverage SRS/SRT dose maps for ROI identification and subsequent radiomic analysis of peritumoral and untargeted brain regions using multiparametric MRI. We observed that the peritumoral environment may be implicated in DBM development for SRS/SRT-treated brain metastases. Our preliminary results might enable the identification of patients with predisposition to DBM development and prompt subsequent changes in disease management.

Automated Detection of Cervical Spinal Stenosis and Cord Compression via Vision Transformer and Rules-Based Classification.

BACKGROUND AND PURPOSE: Cervical spinal cord compression, defined as spinal cord deformity and severe narrowing of the spinal canal in the cervical region, can lead to severe clinical consequences, including intractable pain, sensory disturbance, paralysis, and even death, and may require emergent intervention to prevent negative outcomes. Despite the critical nature of cord compression, no automated tool is available to alert clinical radiologists to the presence of such findings. This study aims to demonstrate the ability of a vision transformer (ViT) model for the accurate detection of cervical cord compression. MATERIALS AND METHODS: A clinically diverse cohort of 142 cervical spine MRIs was identified, 34% of which were normal or had mild stenosis, 31% with moderate stenosis, and 35% with cord compression. Utilizing gradient-echo images, slices were labeled as no cord compression/mild stenosis, moderate stenosis, or severe stenosis/cord compression. Segmentation of the spinal canal was performed and confirmed by neuroradiology faculty. A pretrained ViT model was fine-tuned to predict section-level severity by using a train:validation:test split of 60:20:20. Each examination was assigned an overall severity based on the highest level of section severity, with an examination labeled as positive for cord compression if ≥1 section was predicted in the severe category. Additionally, 2 convolutional neural network (CNN) models (ResNet50, DenseNet121) were tested in the same manner. RESULTS: The ViT model outperformed both CNN models at the section level, achieving section-level accuracy of 82%, compared with 72% and 78% for ResNet and DenseNet121, respectively. ViT patient-level classification achieved accuracy of 93%, sensitivity of 0.90, positive predictive value of 0.90, specificity of 0.95, and negative predictive value of 0.95. Receiver operating characteristic area under the curve was greater for ViT than either CNN. CONCLUSIONS: This classification approach using a ViT model and rules-based classification accurately detects the presence of cervical spinal cord compression at the patient level. In this study, the ViT model outperformed both conventional CNN approaches at the section and patient levels. If implemented into the clinical setting, such a tool may streamline neuroradiology workflow, improving efficiency and consistency.

Effect of Cobalt-60 Treatment Dose Rate on Arteriovenous Malformation Obliteration After Stereotactic Radiosurgery With Gamma Knife.

BACKGROUND AND OBJECTIVES: Stereotactic radiosurgery (SRS) marginal dose is associated with successful obliteration of cerebral arteriovenous malformations (AVM). SRS dose rate-how old the cobalt-60 sources are-is known to influence outcomes for some neurological conditions and benign tumors. The objective of this study was to determine the association between cobalt-60 treatment dose rate and cerebral AVM obliteration in patients treated with SRS. METHODS: We performed a retrospective cohort study of 361 patients undergoing 411 AVM-directed SRS treatments between 2005 and 2019 at a single institution. Lesion characteristics, SRS details, obliteration dates, and post-treatment toxicities were recorded. Univariate and multivariate regression analyses of AVM outcomes regarding SRS dose rate (range 1.3-3.7 Gy, mean = 2.4 Gy, median = 2.5 Gy) were performed. RESULTS: At 10 years post-SRS, 68% of AVMs were obliterated on follow-up imaging. Dose rates >2.9 Gy/min were found to be significantly associated with AVM obliteration compared with those <2.1 Gy/min ( P = .034). AVM size, biologically effective dose, and SRS marginal dose were also associated with obliteration, with obliteration more likely for smaller lesions, higher biologically effective dose, and higher marginal dose. Higher dose rates were not associated with the development of post-SRS radiological or symptomatic edema, although larger AVM volume was associated with both types of edema. CONCLUSION: Patients with cerebral AVMs treated with higher SRS dose rates (from newer cobalt-60 sources) experience higher incidences of obliteration without a significant change in the risk of post-treatment edema.

Genomic Surveillance Reveals the Rapid Expansion of the XBB Lineage among Circulating SARS-CoV-2 Omicron Lineages in Southeastern Wisconsin, USA.

SARS-CoV-2 caused a life-threatening COVID-19 pandemic outbreak worldwide. The Southeastern Region of Wisconsin, USA (SERW) includes large urban Milwaukee and six suburban counties, namely Kenosha, Ozaukee, Racine, Walworth, Washington and Waukesha. Due to the lack of detailed SARS-CoV-2 genomic surveillance in the suburban populations of the SERW, whole-genome sequencing was employed to investigate circulating SARS-CoV-2 lineages and characterize dominant XBB lineages among this SERW population from November 2021 to April 2023. For an unbiased data analysis, we combined our 6709 SARS-CoV-2 sequences with 1520 sequences from the same geographical region submitted by other laboratories. Our study shows that SARS-CoV-2 genomes were distributed into 357 lineages/sublineages belonging to 13 clades, of which 88.8% were from Omicron. We document dominant sublineages XBB.1.5 and surging XBB.1.16 and XBB.1.9.1 with a few additional functional mutations in Spike, which are known to contribute to higher viral reproduction, enhanced transmission and immune evasion. Mutational profile assessment of XBB.1.5 Spike identifies 38 defining mutations with high prevalence occurring in 49.8-99.6% of the sequences studied, of which 32 mutations were in three functional domains. Phylogenetic and genetic relatedness between XBB.1.5 sequences reveal potential virus transmission occurring within households and within and between Southeastern Wisconsin counties. A comprehensive phylogeny of XBB.1.5 with global sub-dataset sequences confirms the wide spread of genetically similar SARS-CoV-2 strains within the same geographical area. Altogether, this study identified proportions of circulating Omicron variants and genetic characterization of XBB.1.5 in the SERW population, which helped state and national public health agencies to make compelling mitigation efforts to reduce COVID-19 transmission in the communities and monitor emerging lineages for their impact on diagnostics, treatments and vaccines.

Comparison of an ID NOW COVID-19 Assay Used at the Point of Care to Laboratory-Based Nucleic Acid Amplification Tests.

The emergence of a novel coronavirus, namely, SARS-CoV-2, necessitated the use of rapid, accurate diagnostics to quickly diagnose COVID-19. This need has increased with the emergence of new variants and continued waves of COVID-19 cases. The ID NOW COVID-19 assay is a rapid nucleic acid amplification test (NAAT) that is used by hospitals, urgent care facilities, medical clinics, and public health laboratories for rapid molecular SARS-CoV-2 testing at the point of care. The District of Columbia Department of Forensic Sciences Public Health Laboratory Division (DC DFS PHL) implemented ID NOW COVID-19 testing in nontraditional laboratory settings, including a mobile testing unit, health clinic, and emergency department, to assist with rapid identification and isolation for populations at high risk of SARS-CoV-2 transmission in the District of Columbia. The DC DFS PHL provided these nontraditional laboratories with safety risk assessment, assay training, competency assessment, and quality control monitoring as parts of a comprehensive quality management system (QMS). We assessed the accuracy of the ID NOW COVID-19 assay when operated in the context of these trainings and systems. This was done by comparing results from 9,518 paired tests, and strong agreement (κ = 0.88, OPA = 98.3%) was found between the ID NOW COVID-19 assay and laboratory-based NAATs. These findings indicate that the ID NOW COVID-19 assay can be used to detect SARS-CoV-2 in nontraditional laboratory settings when used within the context of a comprehensive QMS.

High Daytime Temperature Responsive MicroRNA Profiles in Developing Grains of Rice Varieties with Contrasting Chalkiness.

High temperature impairs starch biosynthesis in developing rice grains and thereby increases chalkiness, affecting the grain quality. Genome encoded microRNAs (miRNAs) fine-tune target transcript abundances in a spatio-temporal specific manner, and this mode of gene regulation is critical for a myriad of developmental processes as well as stress responses. However, the role of miRNAs in maintaining rice grain quality/chalkiness during high daytime temperature (HDT) stress is relatively unknown. To uncover the role of miRNAs in this process, we used five contrasting rice genotypes (low chalky lines Cyp, Ben, and KB and high chalky lines LaGrue and NB) and compared the miRNA profiles in the R6 stage caryopsis samples from plants subjected to prolonged HDT (from the onset of fertilization through R6 stage of caryopsis development). Our small RNA analysis has identified approximately 744 miRNAs that can be grouped into 291 families. Of these, 186 miRNAs belonging to 103 families are differentially regulated under HDT. Only two miRNAs, Osa-miR444f and Osa-miR1866-5p, were upregulated in all genotypes, implying that the regulations greatly varied between the genotypes. Furthermore, not even a single miRNA was commonly up/down regulated specifically in the three tolerant genotypes. However, three miRNAs (Osa-miR1866-3p, Osa-miR5150-3p and canH-miR9774a,b-3p) were commonly upregulated and onemiRNA (Osa-miR393b-5p) was commonly downregulated specifically in the sensitive genotypes (LaGrue and NB). These observations suggest that few similarities exist within the low chalky or high chalky genotypes, possibly due to high genetic variation. Among the five genotypes used, Cypress and LaGrue are genetically closely related, but exhibit contrasting chalkiness under HDT, and thus, a comparison between them is most relevant. This comparison revealed a general tendency for Cypress to display miRNA regulations that could decrease chalkiness under HDT compared with LaGrue. This study suggests that miRNAs could play an important role in maintaining grain quality in HDT-stressed rice.

Cobalt containing glass fibres and their synergistic effect on the HIF-1 pathway for wound healing applications.

Introduction and Methods: Chronic wounds are a major healthcare problem, but their healing may be improved by developing biomaterials which can stimulate angiogenesis, e.g. by activating the Hypoxia Inducible Factor (HIF) pathway. Here, novel glass fibres were produced by laser spinning. The hypothesis was that silicate glass fibres that deliver cobalt ions will activate the HIF pathway and promote the expression of angiogenic genes. The glass composition was designed to biodegrade and release ions, but not form a hydroxyapatite layer in body fluid. Results and Discussion: Dissolution studies demonstrated that hydroxyapatite did not form. When keratinocyte cells were exposed to conditioned media from the cobalt-containing glass fibres, significantly higher amounts of HIF-1α and Vascular Endothelial Growth Factor (VEGF) were measured compared to when the cells were exposed to media with equivalent amounts of cobalt chloride. This was attributed to a synergistic effect of the combination of cobalt and other therapeutic ions released from the glass. The effect was also much greater than the sum of HIF-1α and VEGF expression when the cells were cultured with cobalt ions and with dissolution products from the Co-free glass, and was proven to not be due to a rise in pH. The ability of the glass fibres to activate the HIF-1 pathway and promote VEGF expression shows the potential for their use in chronic wound dressings.

Real-time insight into the multistage mechanism of nanoparticle exsolution from a perovskite host surface.

In exsolution, nanoparticles form by emerging from oxide hosts by application of redox driving forces, leading to transformative advances in stability, activity, and efficiency over deposition techniques, and resulting in a wide range of new opportunities for catalytic, energy and net-zero-related technologies. However, the mechanism of exsolved nanoparticle nucleation and perovskite structural evolution, has, to date, remained unclear. Herein, we shed light on this elusive process by following in real time Ir nanoparticle emergence from a SrTiO3 host oxide lattice, using in situ high-resolution electron microscopy in combination with computational simulations and machine learning analytics. We show that nucleation occurs via atom clustering, in tandem with host evolution, revealing the participation of surface defects and host lattice restructuring in trapping Ir atoms to initiate nanoparticle formation and growth. These insights provide a theoretical platform and practical recommendations to further the development of highly functional and broadly applicable exsolvable materials.

Computational and experimental studies of the wide bandgap semiconductors NH4TiOF3 and (NH4)2TiOF4.

As the topotactic synthetic precursor of the ubiquitous functional semiconductor anatase TiO2, ammonium fluoroxotitanates, such as NH4TiOF3 and (NH4)2TiOF4, have received lots of research interest as synthetic precursors. However, few of the existing studies focus on their properties and possible applications on their own. To fill this gap, both NH4TiOF3 and (NH4)2TiOF4 were studied in this work experimentally by material characterization and computationally via DFT calculations. Electronic structures of both materials from experimental and computational perspectives were mutually supportive. Based on these, immobilised NH4TiOF3 was preliminarily tested as a UV photocatalyst for dye degradation. Reasonable photocatalytic activities were observed.

Determining the optical properties of solar cells using low cost scanners.

This paper investigates the use of consumer flatbed scanners for the use of monitoring solar cell precursors. Two types of scanners are investigated a contact image scanner and scanners with more conventional optical setups. The contact image sensor is found to be more suitable as it does not require additional flat field calibration. The scanners' ability to monitor variation in sample texture was investigated by monitoring the reflection of multi-crystalline and mono-crystalline textured wafers. For a baseline, a comparison was made to a high-end tool used in industry. Both good qualitative agreement and statistical correlation were achieved between the scanner and industry tool for the isotropic multi-crystalline wafers.

A cohort study measuring SARS-CoV-2 seroconversion and serial viral testing in university students.

BACKGROUND: To improve understanding of the antibody response to SARS-CoV-2 infection, we examined seroprevalence, incidence of infection, and seroconversion among a cohort of young adults living on university campuses during the fall of 2020. METHODS: At the beginning (semester start) and end (semester end) of an 11-week period, serum collected from 107 students was tested using the qualitative Abbott Architect SARS-CoV-2 IgG and AdviseDx SARS-CoV-2 IgG II assays. Results were matched to interim weekly surveillance viral testing and symptom data. RESULTS: With the SARS-CoV-2 IgG assay, 15 (14.0%) students were seropositive at semester start; 29 (27.1%) students were seropositive at semester end; 10 (9.3%) were seropositive at both times. With the AdviseDx SARS-CoV-2 IgG II assay, 17 (16.3%) students were seropositive at semester start, 37 (35.6%) were seropositive at semester end, and 16 (15.3%) were seropositive at both times. Overall, 23 students (21.5%) had positive viral tests during the semester. Infection was identified by serial testing in a large majority of individuals who seroconverted using both assays. Those seropositive at semester end more frequently reported symptomatic infections (56.5%) than asymptomatic infections (30.4%). CONCLUSION: Differences between antibody targets were observed, with more declines in antibody index values below the threshold of positivity with the anti-nucleocapsid assay compared to the anti-spike assay. Serology testing, combined with serial viral testing, can detect seroconversions, and help understand the potential correlates of protection provided by antibodies to SARS-CoV-2.