Data_Sheet_1_Multi-pinhole collimator design in different numbers of projections for brain SPECT.docx

PurposeHigh resolution and sensitivity brain SPECT is promising for the accurate diagnosis of Alzheimer's disease (AD) and Parkinson's disease (PD). Multi-pinhole (MPH) collimators with a good performance in imaging small field-of-view (FOV) could be better used for brain SPECT. In this study, we aim to evaluate the impact of varying the number of pinholes and the number of projections on the performance of MPH brain SPECT.MethodsThe system design was based on a commercial clinical dual-head SPECT/CT scanner, with target spatial resolutions of 12 mm and 8 mm for AD and PD SPECT, respectively. In total, 1–25 pinholes were modeled for 64, 32, 16, 8, 4, and 2 projections. The 3D NURBS-based HUman Brain (NHUB) phantom was used in the analytical simulation to model 99mTc-HMPAO and 99mTc-TRODAT distributions. The 2D Derenzo hot-rod phantom and star phantom were used in Monte Carlo simulations to evaluate the spatial resolution and angular sampling performance of MPH. The influence of different detector positions was also evaluated for 2, 4, and 6 angular views. The projections were reconstructed using the 3D MPH ML-EM method. Normalized mean square error, coefficient of variation, and image profiles were evaluated.ResultsAlong with the decrease in the number of projections, more pinholes are required to achieve the optimum performance. For 32 projections, 9- and 7-pinhole collimators provide the best normalized mean square error (NMSE) to the coefficient of variation (COV) trade-off for 99mTc-HMPAO and 99mTc-TRODAT, respectively. Detector positions substantially affect the image quality for MPH SPECT for 2 and 4 angular views. The smallest rod size for the Derenzo hot-rod phantom, which could be resolved, is 7.9 mm for the MPH general purpose collimator (MPGP) with more than 16 projections and 6.4 mm for MPH high-resolution collimator (MPHR) with more than 8 projections.ConclusionThe number of pinholes affects the performance of the MPH collimator, especially when the projection views become fewer. More pinholes are required for fewer projections to provide better angular sampling in MPH for complex activity distributions. Detector positions affect the image quality of MPH SPECT for 2 and 4 angular views, where L-mode acquisition is slightly superior to H-mode. MPH collimators exhibited improved spatial resolution and angular sampling compared with both LEHR and single pinhole collimators.</p

Bismuth(III) Triflate Catalyzed Three-Component Reactions of Indoles, Ketones, and α‑Bromoacetaldehyde Acetals Enable Indole-to-Carbazole Transformation

A three-component reaction of indoles, α-bromoacetaldehyde acetals, and ketones was developed by using bismuth­(III) triflate as the catalyst to realize a straightforward approach for synthesizing carbazole derivatives. The reaction was established mechanistically through the autotandem catalysis of Bi­(OTf)₃ in the following two steps: (i) Friedel–Crafts-type alkylation of indole with α-bromoacetaldehyde acetal, which produced a tryptaldehyde-type intermediate and (ii) [4 + 2] annulation of this intermediate with the ketone component

Machine learning-based prediction of in-hospital mortality in patients with pneumonic chronic obstructive pulmonary disease exacerbations

While linear regression and LASSO models have been established for predicting in-hospital mortality, there is currently no validated clinical prediction algorithm to predict in-hospital mortality for patients with chronic obstructive pulmonary disease (COPD) exacerbations using machine learning. Thus, we will evaluate the BAP-65 and CURB-65, and construct a novel prediction model using the random forest (RF) technique. A dataset of 1,418 patients with COPD exacerbations was collected. Age, gender, mental status, vital signs, and laboratory results were all taken into account for predictors. The categorical outcome variable was hospital-based mortality of people over 65 years. The dataset was divided randomly into a training dataset (70%) and a testing dataset (30%). We trained three prediction models, BAP-65, CURB-65, and the RF model, estimated the area under the receiver operating characteristic curve (AUROC) for the entire dataset. We also conducted a comparison of the AUROC values using the Delong test. A total of 658 individuals with COPD acute exacerbations were enrolled. Our analysis using the receiver operating characteristic curve demonstrated that the RF model exhibited excellent performance, with an AUROC of 0.80 (95% confidence interval: 0.75-0.84). In comparison, the BAP-65 prediction model yielded an AUROC of 0.72 (0.68-0.75), while the CURB-65 prediction model achieved an AUROC of 0.69 (0.67-0.73). The RF model demonstrated superior predictive capabilities than the BAP-65 and CURB-65 models in predicting in-hospital mortality. The results further highlighted significant factors for predicting in-hospital mortality, including blood eosinophil count, systolic blood pressure, and prior history of asthma.</p

Experimental Study on a Superstable Nano-TiO₂ Deep Eutectic Solvent Nanofluid for Solar Energy Harvesting

Nanofluids have emerged as an important working fluid for various heat transfer and thermal energy transportation demands thanks to its promising thermal conductivity. While, poor static stability brought by segregation of nanoparticle heavily hinders its wide practical utilization. In this work, a novel “one-pot one-step” strategy was realized to generate a superior stable nanofluid which can stand uneventfully for at least 2 months without observation of any sedimentation with tetrabutyl titanate as a TiO2 precursor in glycerol/chlorine chloride deep eutectic solvents. Mechanism study reveals that the good stability of this nanofluid is mainly attributed to in situ formation protocol for which the inherent aggregation of TiO2 can be theoretically avoided. Meanwhile, thermophysical properties, such as viscosity, thermal conductivity, and rheological behavior, were comprehensively studied, which indicates that the obtained nanofluids exhibit a non-Newtonian shear thinning fluid behavior with a thermal conductivity enhancement ratio up to 9.0%. More importantly, photothermal conversion efficiency of the nanofluid could reach 51.2%, and the efficiency enhancement is 181.9% over the pristine deep eutectic solvents. This work paves a novel avenue for fabricating nanofluids with super static stability and gives a supplementary idea for “one-step” nanofluids preparation process

Microscopic and Spectroscopic Insights into Uranium Phosphate Mineral Precipitated by <i>Bacillus Mucilaginosus</i>

In this paper, we used spectroscopic and microscopic techniques to investigate the interaction mechanism between uranium and <i>Bacillus mucilaginosus</i>. According to scanning electron microscope couple with energy dispersive X-ray detector analysis, the lamellar uranium phosphate precipitation was only observed on the living <i>B. mucilaginosus</i> and the resting <i>B. mucilaginosus</i>. The Fourier transform infrared spectroscopy spectrum also indicated the important role of phosphate groups in forming U­(VI)-phosphates precipitation. The X-ray diffraction analysis identified the phase of U­(VI)-phosphate precipitation as H₃OUO₂PO₄·3H₂O. Batch experiment showed that biominerilization amount could be up to 195.84 mg/g when exposing living <i>B. mucilaginosus</i> to U­(VI) aqueous solution at pH 5.0 for 1 h. The precipitate was further evidenced by extended X-ray absorption fine structure spectra based on the presence of U–P shell, which demonstrated that hydrogen uranyl phosphate became the main products on the living <i>B. mucilaginosus</i> with prolonged reacting time. After ashing and hydrothermal process, the precipitated U­(VI) on <i>B. mucilaginosus</i> could be converted into UO₂ and K­(UO₂)­(PO₄)·3H₂O. Our findings have significant implications in elucidating the potential role of bacteria in the migration of uranium in geological environment