Kinetic model-informed deep learning for multiplexed PET image separation.

BACKGROUND: Multiplexed positron emission tomography (mPET) imaging can measure physiological and pathological information from different tracers simultaneously in a single scan. Separation of the multiplexed PET signals within a single PET scan is challenging due to the fact that each tracer gives rise to indistinguishable 511 keV photon pairs, and thus no unique energy information for differentiating the source of each photon pair. METHODS: Recently, many applications of deep learning for mPET image separation have been concentrated on pure data-driven methods, e.g., training a neural network to separate mPET images into single-tracer dynamic/static images. These methods use over-parameterized networks with only a very weak inductive prior. In this work, we improve the inductive prior of the deep network by incorporating a general kinetic model based on spectral analysis. The model is incorporated, along with deep networks, into an unrolled image-space version of an iterative fully 4D PET reconstruction algorithm. RESULTS: The performance of the proposed method was evaluated on a simulated brain image dataset for dual-tracer [ 18 F]FDG+[ 11 C]MET PET image separation. The results demonstrate that the proposed method can achieve separation performance comparable to that obtained with single-tracer imaging. In addition, the proposed method outperformed the model-based separation methods (the conventional voxel-wise multi-tracer compartment modeling method (v-MTCM) and the image-space dual-tracer version of the fully 4D PET image reconstruction algorithm (IS-F4D)), as well as a pure data-driven separation [using a convolutional encoder-decoder (CED)], with fewer training examples. CONCLUSIONS: This work proposes a kinetic model-informed unrolled deep learning method for mPET image separation. In simulation studies, the method proved able to outperform both the conventional v-MTCM method and a pure data-driven CED with less training data.

Unveiling the Mechanism and Kinetics of Pollutant Attenuation by Free Radicals Triggered from Goethite in Water Distribution Systems.

Investigating the fate of persistent organic pollutants in water distribution systems (WDSs) is of great significance for preventing human health risks. The role of iron corrosion scales in the migration and transformation of organics in such systems remains unclear. Herein, we determined that hydroxyl (•OH), chlorine, and chlorine oxide radicals are generated by Fenton-like reactions due to the coexistence of oxygen vacancy-related Fe(II) on goethite (a major constituent of iron corrosion scales) and hypochlorous acid (HClO, the main reactive chlorine species of residual chlorine at pH ∼ 7.0). •OH contributed mostly to the decomposition of atrazine (ATZ, model compound) more than other radicals, producing a series of relatively low-toxicity small molecular intermediates. A simplified kinetic model consisting of mass transfer of ATZ and HClO, •OH generation, and ATZ oxidation by •OH on the goethite surface was developed to simulate iron corrosion scale-triggered residual chlorine oxidation of organic compounds in a WDS. The model was validated by comparing the fitting results to the experimental data. Moreover, the model was comprehensively applicable to cases in which various inorganic ions (Ca2+, Na+, HCO3-, and SO42-) and natural organic matter were present. With further optimization, the model may be employed to predict the migration and accumulation of persistent organic pollutants under real environmental conditions in the WDSs.

Indirect photodegradation of typical pyrrolizidine alkaloids in water induced by triplet states of dissolved organic matter.

The occurrence of pyrrolizidine alkaloids (PAs) in the aquatic environment has received growing attention due to their persistent mutagenicity and carcinogenicity. In this study, the photooxidation processes of four representative PAs (senecionine, senecionine N-oxide, europine, and heliotrine) in the presence of dissolved organic matter (DOM) were investigated. The excited triplet DOM (3DOM*) was demonstrated to play a dominant role in the phototransformation of PAs. The observed degradation rates of PAs largely depended on the DOM concentration. Alkaline conditions and the presence of HCO3-/CO32- were conducive to the photodegradation. Based on kinetic modeling, the second-order reaction rate constants of PAs with 3DOM* were predicted to be (1.7∼5.3)×108 M-1 s-1, nearly two orders of magnitude higher than those with singlet oxygen (1O2). The monoester structure and electron-withdrawing substituent (e.g., -O atom) substantially affected the one-electron oxidation potential of PAs, which dictates the reaction rates of PAs with 3DOM*. Finally, a tentative degradation pathway of PAs was proposed, involving the formation of an N-centered radical cation through one-electron transfer, which then likely deprotonated and further oxidized to more persistent and toxic phototransformation products with an added oxygen atom into the pyrrole ring.

Genome-wide quantification of RNA flow across subcellular compartments reveals determinants of the mammalian transcript life cycle.

Dissecting the regulatory mechanisms controlling mammalian transcripts from production to degradation requires quantitative measurements of mRNA flow across the cell. We developed subcellular TimeLapse-seq to measure the rates at which RNAs are released from chromatin, exported from the nucleus, loaded onto polysomes, and degraded within the nucleus and cytoplasm in human and mouse cells. These rates varied substantially, yet transcripts from genes with related functions or targeted by the same transcription factors and RNA-binding proteins flowed across subcellular compartments with similar kinetics. Verifying these associations uncovered a link between DDX3X and nuclear export. For hundreds of RNA metabolism genes, most transcripts with retained introns were degraded by the nuclear exosome, while the remaining molecules were exported with stable cytoplasmic lifespans. Transcripts residing on chromatin for longer had extended poly(A) tails, whereas the reverse was observed for cytoplasmic mRNAs. Finally, machine learning identified molecular features that predicted the diverse life cycles of mRNAs.

Heparosan biosynthesis in recombinant Bacillus megaterium: Influence of N-acetylglucosamine supplementation and kinetic modeling.

Heparosan, an unsulfated polysaccharide, plays a pivotal role as a primary precursor in the biosynthesis of heparin-an influential anticoagulant with diverse therapeutic applications. To enhance heparosan production, the utilization of metabolic engineering in nonpathogenic microbial strains is emerging as a secure and promising strategy. In the investigation of heparosan production by recombinant Bacillus megaterium, a kinetic modeling approach was employed to explore the impact of initial substrate concentration and the supplementation of precursor sugars. The adapted logistic model was utilized to thoroughly analyze three vital parameters: the B. megaterium growth dynamics, sucrose utilization, and heparosan formation. It was noted that at an initial sucrose concentration of 30 g L-1 (S1), it caused an inhibitory effect on both cell growth and substrate utilization. Intriguingly, the inclusion of N-acetylglucosamine (S2) resulted in a significant 1.6-fold enhancement in heparosan concentration. In addressing the complexities of the dual substrate system involving S1 and S2, a multi-substrate kinetic models, specifically the double Andrew's model was employed. This approach not only delved into the intricacies of dual substrate kinetics but also effectively described the relationships among the primary state variables. Consequently, these models not only provide a nuanced understanding of the system's behavior but also serve as a roadmap for optimizing the design and management of the heparosan production method.

Utilizing an Integrated Flow Cathode-Membrane Filtration System for Effective and Continuous Electrochemical Hydrodechlorination.

Pd-based electrodes are recognized to facilitate effective electrochemical hydrodechlorination (EHDC) as a result of their superior capacity for atomic hydrogen (H*) generation. However, challenges such as electrode stability, feasibility of treating complex matrices, and high cost associated with electrode synthesis hinder the application of Pd-based electrodes for EHDC. In this work, we investigated the feasibility of degrading 2,4-dichlorophenol (2,4-DCP) by EHDC employing Pd-loaded activated carbon particles, prepared via a simple wet-impregnation method, as a flow cathode (FC) suspension. Compared to other Pd-based EHDC studies, a much lower Pd loading (0.02-0.08 mg cm-2) was used. Because of the excellent mass transfer in the FC system, almost 100% 2,4-DCP was hydrodechlorinated to phenol within 1 h. The FC system also showed excellent performance in treating complex water matrices (including hardness ion-containing wastewater and various other chlorinated organics such as 2,4-dichlorobenzoic acid and trichloroacetic acid) with a relatively low energy consumption (0.26-1.56 kW h m-3 mg-1 of 2,4-DCP compared to 0.32-7.61 kW h m-3 mg-1 of 2,4-DCP reported by other studies). The FC synthesized here was stable over 36 h of continuous operation, indicating its potential suitability for real-world applications. Employing experimental investigations and mathematical modeling, we further show that hydrodechlorination of 2,4-DCP occurs via interaction with H*, with no role of direct electron transfer and/or HO•-mediated processes in the removal of 2,4-DCP.

Challenges and opportunities in bioprocessing of gellan gum: A review.

Gellan gum (GG) - the microbial exopolysaccharide is increasingly being adopted into drug development, tissue engineering, and food and pharmaceutical products. In spite of the commercial importance and expanding application horizon of GG, little attention has been directed toward the exploration of novel microbial cultures, development of advanced screening protocols, strain engineering, and robust upstream or downstream processes. This comprehensive review not only attempts to summarize the existing knowledge pool on GG bioprocess but also critically assesses their inherent challenges. The process optimization design augmented with advanced machine learning modeling tools, widely adopted in other microbial bioprocesses, should be extended to GG. The unification of mechanistic insight into data-driven modeling would help to formulate optimal feeding and process control strategies.

Carbon monoxide inhibition on acidogenic glucose fermentation and aceticlastic methanogenesis.

Syngas and CO-rich off-gases are key chemical platforms to produce biofuels and bioproducts. From the perspective of optimizing and up-scaling CO co-digestion with organic waste streams, this study aims at assessing and quantifying the inhibitory effects of CO on acidogenic glucose fermentation and aceticlastic methanogenesis. Mesophilic cultures were fed in two sets of batch assays, respectively, with glucose and acetate while being exposed to dissolved CO in equilibrium with partial pressures in the range of 0.25-1.00 atm. Cumulative methane production and microbial monitoring revealed that aceticlastic methanogenic archaea were significantly inhibited (2-20 % of the methane production of CO non-exposed cultures). The acidogenic glucose degrading community was also inhibited by CO, although, thanks to its functional redundancy, shifted its metabolism towards propionate production. Future work should assess the sensitivity of hereby estimated CO inhibition parameters, e.g., on the simulation output of a continuous syngas co-digestion process with organic substrates.

PEMPS: a phylogenetic software tool to model the evolution of metabolic pathways.

BACKGROUND: Metabolic pathways support the enzyme flux that converts input chemicals into energy and cellular building blocks. With a constant rate of input, steady-state flux is achieved when metabolite concentrations and reaction rates remain constant over time. Individual genes undergo mutation, while selection acts on higher level functions of the pathway, such as steady-state flux where applicable. Modeling the evolution of metabolic pathways through mechanistic sets of ordinary differential equations is a piece of the genotype-phenotype map model for interpreting genetic variation and inter-specific differences. Such models can generate distinct compensatory changes and adaptive changes from directional selection, indicating single nucleotide polymorphisms and fixed differences that could affect phenotype. If used for inference, this would ultimately enable detection of selection on metabolic pathways as well as inference of ancestral states for metabolic pathway function. RESULTS: A software tool for simulating the evolution of metabolic pathways based upon underlying biochemistry, phylogenetics, and evolutionary considerations is presented. The Python program, Phylogenetic Evolution of Metabolic Pathway Simulator (PEMPS), implements a mutation-selection framework to simulate the evolution of the pathway over a phylogeny by interfacing with COPASI to calculate the steady-state flux of the metabolic network, introducing mutations as alterations in parameter values according to a model, and calculating a fitness score and corresponding probability of fixation based on the change in steady-state flux value(s). Results from simulations are consistent with a priori expectations of fixation probabilities and systematic change in model parameters. CONCLUSIONS: The PEMPS program simulates the evolution of a metabolic pathway with a mutation-selection modeling framework based on criteria like steady-state flux that is designed to work with SBML-formatted kinetic models, and Newick-formatted phylogenetic trees. The Python software is run on the Linux command line and is available at https://github.com/nmccloskey/PEMPS .

Bacterial cellulose microfilament biochar-architectured chitosan/polyethyleneimine beads for enhanced tetracycline and metronidazole adsorption.

This study investigates the potential applications of incorporating 2D bacterial cellulose microfibers (BCM) biochar into chitosan/polyethyleneimine beads as a semi-natural sorbent for the efficient removal of tetracycline (TET) and metronidazole (MET) antibiotics. Batch adsorption experiments and characterization techniques evaluate removal performance and synthesized adsorbent properties. The adsorbent eliminated 99.13 % and 90 % of TET and MET at a 10 mg.L-1 concentration with optimal pH values of 8 and 6, respectively, for 90 min. Under optimum conditions and a 400 mg.L-1 concentration, MET and TET have possessed the maximum adsorption capacities of 691.325 and 960.778 mg.g-1, respectively. According to the isothermal analysis, the adsorption of TET fundamentally follows the Temkin (R2 = 0.997), Redlich-Peterson (R2 = 0.996), and Langmuir (R2 = 0.996) models. In contrast, the MET adsorption can be described by the Langmuir (R2 = 0.997), and Toth (R2 = 0.991) models. The pseudo-second-order (R2 = 0.998, 0.992) and Avrami (R2 = 0.999, 0.999) kinetic models were well-fitted with the kinetic results for MET and TET respectively. Diffusion models recommend that pore, liquid-film, and intraparticle diffusion govern the rate of the adsorption process. The developed semi-natural sorbent demonstrated exceptional adsorption capacity over eleven cycles due to its porous bead structure, making it a potential candidate for wastewater remediation.

Evaluating Possible Formation Mechanisms of Criegee Intermediates during the Heterogeneous Autoxidation of Squalene.

Organic molecules in the environment oxidatively degrade by a variety of free radical, microbial, and biogeochemical pathways. A significant pathway is heterogeneous autoxidation, in which degradation occurs via a network of carbon and oxygen centered free radicals. Recently, we found evidence for a new heterogeneous autoxidation mechanism of squalene that is initiated by hydroxyl (OH) radical addition to a carbon-carbon double bond and apparently propagated through pathways involving Criegee Intermediates (CI) produced from ß-hydroxy peroxy radicals (ß-OH-RO2•). It remains unclear, however, exactly how CI are formed from ß-OH-RO2•, which could occur by a unimolecular or bimolecular pathway. Combining kinetic models and multiphase OH oxidation measurements of squalene, we evaluate the kinetic viability of three mechanistic scenarios. Scenario 1 assumes that CI are formed by the unimolecular bond scission of ß-OH-RO2•, whereas Scenarios 2 and 3 test bimolecular pathways of ß-OH-RO2• to yield CI. Scenario 1 best replicates the entire experimental data set, which includes effective uptake coefficients vs [OH] as well as the formation kinetics of the major products (i.e., aldehydes and secondary ozonides). Although the unimolecular pathway appears to be kinetically viable, future high-level theory is needed to fully explain the mechanistic relationship between CI and ß-OH-RO2• in the condensed phase.

Reaction-Kinetic Modeling of Photorespiration Using Modelbase.

Plant science has become more and more complex. With the introduction of new experimental techniques and technologies, it is now possible to explore the fine details of plant metabolism. Besides steady-state measurements often applied in gas-exchange or metabolomic analyses, new approaches, e.g., based on 13C labeling, are now available to understand the changes in metabolic concentrations under fluctuating environmental conditions in the field or laboratory. To explore those transient phenomena of metabolite concentrations, kinetic models are a valuable tool. In this chapter, we describe ways to implement and build kinetic models of plant metabolism with the Python software package modelbase. As an example, we use a part of the photorespiratory pathway. Moreover, we show additional functionalities of modelbase that help to explore kinetic models and thus can reveal information about a biological system that is not easily accessible to experiments. In addition, we will point to extra information on the mathematical background of kinetic models to give an impetus for further self-study.

Drying kinetics and energy efficiency of soot ash of smelting silicon manganese alloys under microwave heating.

When smelting silicon manganese alloy in an industrial electric furnace, it will produce smoke and dust waste gas, which can be utilized again back to the furnace and improve the utilization rate of raw materials after a particular trapping device and collection treatment. However, at higher moisture levels, they are prone to explode. Effects of various initial masses, initial moisture contents, and microwave output powers on the soot ash of smelting silicon manganese alloy were studies. The findings indicate that the microwave drying rate increases with all three variables. The time for complete microwave drying is directly proportional to the sample's initial moisture content and the sample's initial mass, and the time for complete microwave drying is inversely proportional to the microwave output power. The results demonstrate that the Modified Page model can accurately describe the microwave drying process. The experimental data were fitted experimentally by drying kinetic models. Microscopic characterization of soot ash from refining silico­manganese alloys before and after drying was carried out using FTIR and SEM. Through FTIR characterization, the peak value of the -OH absorption peak decreases upon drying, and SEM results in no agglomeration caused by microwave drying and better dispersion of the soot ash of the dried smelted silica­manganese alloys, all of which proved that microwaves could effectively remove water. It was discovered that the diffusion coefficient increased gradually with increasing power when it was computed using Fick's second law. The diffusion coefficient increases and then decreases as the moisture content increases. The diffusion coefficient decreases as the initial mass increases. Activation energy of microwave drying of soot ash from the refining of silicomanganese alloys was calculated to be -1.4467 W/g. Its purpose is to offer a detailed guide for the industrial drying of soot ash from silicomanganese alloy refinement using microwave drying technology.

Ultrasound-assisted extraction of phenolics from Sargassum carpophyllum - A kinetics study.

The species of the brown macroalgal genus Sargassum are distributed globally and contain many bioactive compounds. In this study, ultrasound-assisted extraction (UAE) was applied to obtain phenolic compounds with strong antioxidant activity from Sargassum carpophyllum collected along the coastline of Weizhou Island in the South China Sea. The influence of different variables such as the solid-liquid ratio (1:5-1:30 g · mL-1), ultrasonic power (160-280 W), duty circle ratio (DCR, 1/3-1/1), and ethanol concentration (30% to ~90%) were studied using a single factor design. The extraction kinetics were investigated using the Peleg model and second-order kinetics model, and the second-order model described the extraction procedure better than the Peleg model. Total phenol content (TPC) values of 3.316, 2.964, 2.741, and 3.665 mg phloroglucinol (PHG) · g-1 algae were achieved at a higher solid-liquid ratio (1:30 g · mL-1), higher ultrasonic power (280 W), a higher DCR (1/1), and a moderate ethanol concentration (50%), respectively. However, a slightly different result was observed in the extract obtained, with total phenol contents (TPCextract) of 52.99, 65.00, 46.22, and 55.10 mg PHG · g-1 extract and DPPH radical scavenging activity (IC50) of 0.096, 0.066, 0.131, and 0.136 mg extract · mL-1 observed at 50% ethanol, 1:5 g m· mL-1, 2/3 DCR, and 200 W respectively. All variables studied influenced the extraction kinetics by altering the extraction rate and the TPC at equilibrium. As for the bioactivities in the extract, a larger solid-liquid ratio and greater ultrasonic power may not contribute because of their ability to extract non-phenolic components simultaneously, leading to reduced overall bioactivities. The results of the present study provide essential information for future UAE process design and optimization for extracting phenolics from S. carpophyllum through mathematical modeling and could be regarded as important reference for obtaining value-added products from other macroalgae species.

Full kinetic modeling analysis of [18F]fluorocholine Positron Emission Tomography (PET) at initial diagnosis of high-grade glioma.

PURPOSE: The main objective was to characterize the tracer uptake kinetics of [18F]fluoromethylcholine ([18F]F-CHO) in high-grade gliomas (HGG) through a full PET kinetic modeling approach. Secondarily, we aimed to explore the relationship between the PET uptake measures and the HGG molecular features. MATERIALS AND METHODS: Twenty-four patients with a suspected diagnosis of HGG were prospectively included. They underwent a dynamic brain [18F]F-CHO-PET/CT, from which a tumoral time-activity curve was extracted. The plasma input function was obtained through arterial blood sampling with metabolite correction. These data were fitted to 1- and 2-tissue-compartment models, the best of which was selected through the Akaike information criterion. We assessed the correlation between the kinetic parameters and the conventional static PET metrics (SUVmax, SUVmean and tumor-to-background ratio TBR). We explored the association between the [18F]F-CHO-PET quantitative parameters and relevant molecular biomarkers in HGG. RESULTS: Tumoral time-activity curves in all patients showed a rapid rise of [18F]F-CHO uptake followed by a plateau-like shape. Best fits were obtained with near-irreversible 2-tissue-compartment models. The perfusion-transport constant K1 and the net influx rate Ki showed strong correlation with SUVmax (r = 0.808-0.861), SUVmean (r = 0.794-0.851) and TBR (r = 0.643-0.784), p < 0.002. HGG was confirmed in 21 patients, of which those with methylation of the O-6-methylguanine-DNA methyltransferase (MGMT) gene promoter showed higher mean Ki (p = 0.020), K1 (p = 0.025) and TBR (p = 0.001) than the unmethylated ones. CONCLUSION: [18F]F-CHO uptake kinetics in HGG is best explained by a 2-tissue-compartment model. The conventional static [18F]F-CHO-PET measures have been validated against the perfusion-transport constant (K1) and the net influx rate (Ki) derived from kinetic modeling. A relationship between [18F]F-CHO uptake rate and MGMT methylation is suggested but needs further confirmation.

Dual-time-point dynamic 68Ga-PSMA-11 PET/CT for parametric imaging generation in prostate cancer.

PURPOSE: To investigate the optimal dual-time-point (DTP) approaches using dynamic 68Ga-PSMA-11 PET/CT imaging to generate parametric images for prostate cancer patients. METHODS: Fifteen patients with prostate cancer were intravenously administered 68Ga-PSMA-11 of 181.9 ± 47.2 MBq, followed by an immediate 60 min dynamic PET/CT scan. List-mode data were reconstructed into 25 timeframes (6 × 10 s, 8 × 30 s, and 11 × 300 s) and corrected for motion and partial volume effect. DTP parametric images were generated using different interval time points of 5 min and 10 min, with a minimum of 30 min time interval. Net influx rates (Ki) were calculated through the fitting of a single irreversible two-tissue compartmental model. Intraclass correlation coefficient (ICC) values between DTP protocols and 60 min Ki were obtained. Lesion-to-background ratios (LBRs) of Ki and standardized uptake value (SUV) images in each DTP protocol were determined. RESULTS: The DTP protocol of 5-10 min with a 40-45 min interval showed the highest ICC of 0.988 compared with the 60 min Ki, whereas the ICC values for the intervals of 0-5 min with 55-60 min and 0-10 min with 50-60 min were 0.941. The LBRs of the 60 min Ki, 5-10 min with 40-45 min Ki, 0-5 min with 55-60 min Ki, 0-10 min with 50-60 min Ki, SUVmean, and SUVmax images were 29.53 ± 27.33, 13.05 ± 15.28, 45.15 ± 53.11, 45.52 ± 70.31, 19.77 ± 23.43, and 25.06 ± 30.07, respectively. CONCLUSION: The 0-5 min with 55-60 min DTP parametric imaging exhibits a comparable Ki to 60 min parametric imaging and remarkable image quality and contrast than SUV imaging, enhancing prostate cancer diagnosis while maintaining time efficiency.

Assessment of cerebral drug occupancy in humans using a single PET-scan: A [11C]UCB-J PET study.

PURPOSE: Here, we evaluate a PET displacement model with a Single-step and Numerical solution in healthy individuals using the synaptic vesicle glycoprotein (SV2A) PET-tracer [11C]UCB-J and the anti-seizure medication levetiracetam (LEV). We aimed to (1) validate the displacement model by comparing the brain LEV-SV2A occupancy from a single PET scan with the occupancy derived from two PET scans and the Lassen plot and (2) determine the plasma LEV concentration-SV2A occupancy curve in healthy individuals. METHODS: Eleven healthy individuals (five females, mean age 35.5 [range: 25-47] years) underwent two 120-min [11C]UCB-J PET scans where an LEV dose (5-30 mg/kg) was administered intravenously halfway through the first PET scan to partially displace radioligand binding to SV2A. Five individuals were scanned twice on the same day; the remaining six were scanned once on two separate days, receiving two identical LEV doses. Arterial blood samples were acquired to determine the arterial input function and plasma LEV concentrations. Using the displacement model, the SV2A-LEV target engagement was calculated and compared with the Lassen plot method. The resulting data were fitted with a single-site binding model. RESULTS: SV2A occupancies and VND estimates derived from the displacement model were not significantly different from the Lassen plot (p = 0.55 and 0.13, respectively). The coefficient of variation was 14.6% vs. 17.3% for the Numerical and the Single-step solution in Bland-Altman comparisons with the Lassen plot. The average half maximal inhibitory concentration (IC50), as estimated from the area under the curve of the plasma LEV concentration, was 12.5 µg/mL (95% CI: 5-25) for the Single-Step solution, 11.8 µg/mL (95% CI: 4-25) for the Numerical solution, and 6.3 µg/mL (95% CI: 0.08-21) for the Lassen plot. Constraining Emax to 100% did not significantly improve model fits. CONCLUSION: Plasma LEV concentration vs. SV2A occupancy can be determined in humans using a single PET scan displacement model. The average concentration of the three computed IC50 values ranges between 6.3 and 12.5 µg/mL. The next step is to use the displacement model to evaluate LEV occupancy and corresponding plasma concentrations in relation to treatment efficacy. CLINICAL TRIAL REGISTRATION: NCT05450822. Retrospectively registered 5 July 2022 https://clinicaltrials.gov/ct2/results? term=NCT05450822&Search=Search.

Ultrasound-Assisted Extraction of Bioactive Compounds from Broccoli By-Products.

The objective of this work was to gain insight into the operating conditions that affect the efficiency of ultrasound-assisted extraction (UAE) parameters to achieve the best recovery of bioactive compounds from broccoli leaf and floret byproducts. Therefore, total phenolic content (TPC) and the main sulfur bioactive compounds (sulforaphane (SFN) and glucosinolates (GLSs)) were assayed. Distilled water was used as solvent. For each byproduct type, solid/liquid ratio (1:25 and 2:25 g/mL), temperature (25, 40, and 55 °C), and extraction time (2.5, 5, 7.5, 10, 15, and 20 min) were the studied variables to optimize the UAE process by using a kinetic and a cubic regression model. TPC was 12.5-fold higher in broccoli leaves than in florets, while SFN was from 2.5- to 4.5-fold higher in florets regarding the leaf's extracts obtained from the same plants, their precursors (GLS) being in similar amounts for both plant tissues. The most efficient extraction conditions were at 25 °C, ratio 2:25, and during 15 or 20 min according to the target phytochemical to extract. In conclusion, the type of plant tissue and used ratio significantly influenced the extraction of bioactive compounds, the most efficient UAE parameters being those with lower energy consumption.

Design, Optimization, and Modeling Study of Ultrasound-Assisted Extraction of Bioactive Compounds from Purple-Fleshed Sweet Potatoes.

This study focuses on optimizing the ultrasound-assisted extraction (UAE) of bioactive compounds from purple-fleshed sweet potatoes (PFSP) for potential use as natural colorants. Factors such as time, temperature, and solid-to-liquid ratio were varied using a Box-Behnken Design. The optimal conditions were determined as 75 min, 70 °C, and a 1:15 m/v solid-to-liquid ratio, resulting in 18.372 mg/100 g total anthocyanin (TA) and 151.160 mg GAE/100 g total phenolic content (TPC). The validation yielded 18.822 mg/100 g for total anthocyanin and 162.174 mg GAE/100 g for total phenolic content, showing a 7% difference from predictions. UAE significantly increased TA extraction by 81% and TPC by 93% compared with the conventional method, with a notable reduction in process time from 24 h to 75 min. Additionally, three kinetic models were tested to compare extraction mechanisms, confirming the efficiency of UAE for PFSP bioactive compound recovery. This study proposes the UAE technique as a highly effective means of extracting bioactive compounds from PFSP, offering promising applications across multiple industries.

Bone turnover prediction in patients with chronic kidney disease (CKD) undergoing hemodialysis using shortened dynamic 18F-NaF PET/CT Ki-Patlak.

This study investigated whether Ki-Patlak derived from a shortened scan time for dynamic 18F-NaF PET/CT in chronic kidney disease (CKD) patients undergoing hemodialysis can provide predictive accuracy comparable to that obtained from a longer scan. Twenty-seven patients on chronic hemodialysis, involving a total of 42 scans between December 2021 and August 2023 were recruited. Dynamic 18F-NaF PET/CT scans, lasting 60-90 min, were immediately acquired post-injection, covering the mid-twelfth thoracic vertebra to the pelvis region. Ki-Patlak analysis was performed on bone time-activity curves at 15, 30, 45, 60, and 90 min in the lumbar spine (L1-L4) and both anterior iliac crests. Spearman's rank correlation (rs) and interclass correlation coefficient were used to assess the correlation and agreement of Ki-Patlak between shortened and standard scan times. Bone-specific alkaline phosphatase (BsAP) and tartrate-resistant acid phosphatase isoform 5b (TRAP5b) were tested for their correlation with individual Ki-Patlak. Strong correlations and good agreement were observed between Ki-Patlak values from shortened 30-min scans and longer 60-90-min scans in both lumbar spine (rs = 0.858, p < 0.001) and anterior iliac crest regions (rs = 0.850, p < 0.001). The correlation between BsAP and Ki-Patlak in the anterior iliac crests was weak and statistically insignificant. This finding suggests that a proposed shortened dynamic 18F-NaF PET/CT scan is effective in assessing bone metabolic flux in CKD patients undergoing hemodialysis, offering a non-invasive alternative approach for bone turnover prediction.