Spatiospectral image processing workflow considerations for advanced MR spectroscopy of the brain.

Magnetic resonance spectroscopy (MRS) is one of the few non-invasive imaging modalities capable of making neurochemical and metabolic measurements in vivo. Traditionally, the clinical utility of MRS has been narrow. The most common use has been the "single-voxel spectroscopy" variant to discern the presence of a lactate peak in the spectra in one location in the brain, typically to evaluate for ischemia in neonates. Thus, the reduction of rich spectral data to a binary variable has not classically necessitated much signal processing. However, scanners have become more powerful and MRS sequences more advanced, increasing data complexity and adding 2 to 3 spatial dimensions in addition to the spectral one. The result is a spatially- and spectrally-variant MRS image ripe for image processing innovation. Despite this potential, the logistics for robustly accessing and manipulating MRS data across different scanners, data formats, and software standards remain unclear. Thus, as research into MRS advances, there is a clear need to better characterize its image processing considerations to facilitate innovation from scientists and engineers. Building on established neuroimaging standards, we describe a framework for manipulating these images that generalizes to the voxel, spectral, and metabolite level across space and multiple imaging sites while integrating with LCModel, a widely used quantitative MRS peak-fitting platform. In doing so, we provide examples to demonstrate the advantages of such a workflow in relation to recent publications and with new data. Overall, we hope our characterizations will lower the barrier of entry to MRS processing for neuroimaging researchers.

Pitfalls in measurements of R1 relaxation rates of protein backbone 15N nuclei.

The dynamics of the backbone and side-chains of protein are routinely studied by interpreting experimentally determined 15N spin relaxation rates. R1(15N), the longitudinal relaxation rate, reports on fast motions and encodes, together with the transverse relaxation R2, structural information about the shape of the molecule and the orientation of the amide bond vectors in the internal diffusion frame. Determining error-free 15N longitudinal relaxation rates remains a challenge for small, disordered, and medium-sized proteins. Here, we show that mono-exponential fitting is sufficient, with no statistical preference for bi-exponential fitting up to 800 MHz. A detailed comparison of the TROSY and HSQC techniques at medium and high fields showed no statistically significant differences. The least error-prone DD/CSA interference removal technique is the selective inversion of amide signals while avoiding water resonance. The exchange of amide with solvent deuterons appears to affect the rate R1 of solvent-exposed amides in all fields tested and in each DD/CSA interference removal technique in a statistically significant manner. In summary, the most accurate R1(15N) rates in proteins are achieved by selective amide inversion, without the addition of D2O. Importantly, at high magnetic fields stronger than 800 MHz, when non-mono-exponential decay is involved, it is advisable to consider elimination of the shortest delays (typically up to 0.32 s) or bi-exponential fitting.

Constructing neural networks with pre-specified dynamics.

A main goal in neuroscience is to understand the computations carried out by neural populations that give animals their cognitive skills. Neural network models allow to formulate explicit hypotheses regarding the algorithms instantiated in the dynamics of a neural population, its firing statistics, and the underlying connectivity. Neural networks can be defined by a small set of parameters, carefully chosen to procure specific capabilities, or by a large set of free parameters, fitted with optimization algorithms that minimize a given loss function. In this work we alternatively propose a method to make a detailed adjustment of the network dynamics and firing statistic to better answer questions that link dynamics, structure, and function. Our algorithm-termed generalised Firing-to-Parameter (gFTP)-provides a way to construct binary recurrent neural networks whose dynamics strictly follows a user pre-specified transition graph that details the transitions between population firing states triggered by stimulus presentations. Our main contribution is a procedure that detects when a transition graph is not realisable in terms of a neural network, and makes the necessary modifications in order to obtain a new transition graph that is realisable and preserves all the information encoded in the transitions of the original graph. With a realisable transition graph, gFTP assigns values to the network firing states associated with each node in the graph, and finds the synaptic weight matrices by solving a set of linear separation problems. We test gFTP performance by constructing networks with random dynamics, continuous attractor-like dynamics that encode position in 2-dimensional space, and discrete attractor dynamics. We then show how gFTP can be employed as a tool to explore the link between structure, function, and the algorithms instantiated in the network dynamics.

On curve fitting between topological indices and Gibb's energy for semiconducting carbon nitrides network.

Quantitative structure relationships linked to a chemical structure that shed light on its properties and chemical reactions are called topological indices. This structure is upset by the addition of silicon (Si) doping, which changes the electrical and optical characteristics. In this article, we examine the connection between a chemical structure's Gibbs energy (GE) and K-Banhatti indices. In this article, we compute the K-Banhatti indices and then show the correlation between the indices and Gibb's energy of the molecule using curve fitting. Through the curve fitting, we see that there is a strong correlation between indices and Gibb's energy of a molecule. We use the polynomial curve fitting approach to see the correlation between indices and Gibb's energy.

Effect of glass compression plate on EBT-XD film dosimetry for pretreatment quality assurance of stereotactic body radiotherapy.

Background: EBT-XD film specially designed for high dose verifications such as stereotactic treatments. The dose response of the film can be affected by several factors, the curly nature of the film being one of them. In this study this curly nature of the film was investigated for stereotactic body radiotherapy (SBRT) plan verifications. Materials and methods: For this study, 18 SBRT (11 prostate, 3 spines, and 4 lungs) cases were enrolled. For all the cases, VMAT plans were created in the Monaco treatment planning system and plan was delivered in Elekta Versa HD linear accelerator and delivered fluence was captured by EBT-XD films. All films were scanned with and without a compression plate. All the films were analyzed using the single-channel film method using the red channel. Results: A significant difference in the gamma passing rates (GPR) for the films scanned with and without the compression plate was observed. The maximum percentage differences in GPR between using and not using a compression plate were 12.7% for 1% 1 mm, 8.1% for 2% 2 mm, 7.5% for 3% 2 mm, and 5% for 3% 3mm criteria. Similarly, the mean %difference in GPR was 5.8% for 1% 1 mm, 2.4% for 2% 2 mm, 1.6% for 3% 2 mm and 0.96% for 3% 3 mm criteria. Conclusion: The results suggest that placing a compression plate over the film during scanning provided a great advantage in achieving a more accurate gamma passing rate irrespective of gamma criteria.

A Novel Time-Frequency Parameterization Method for Oscillations in Specific Frequency Bands and Its Application on OPM-MEG.

Time-frequency parameterization for oscillations in specific frequency bands reflects the dynamic changes in the brain. It is related to cognitive behavior and diseases and has received significant attention in neuroscience. However, many studies do not consider the impact of the aperiodic noise and neural activity, including their time-varying fluctuations. Some studies are limited by the low resolution of the time-frequency spectrum and parameter-solved operation. Therefore, this paper proposes super-resolution time-frequency periodic parameterization of (transient) oscillation (STPPTO). STPPTO obtains a super-resolution time-frequency spectrum with Superlet transform. Then, the time-frequency representation of oscillations is obtained by removing the aperiodic component fitted in a time-resolved way. Finally, the definition of transient events is used to parameterize oscillations. The performance of this method is validated on simulated data and its reliability is demonstrated on magnetoencephalography. We show how it can be used to explore and analyze oscillatory activity under rhythmic stimulation.

Physics-Based Artificial Neural Network Assisting in Extracting Transient Properties of Extrinsically Triggering Photoconductive Semiconductor Switches.

In this paper, a physics-based ANN assisting method for extracting transient properties of extrinsically triggering photoconductive semiconductor switches (ET-PCSSs) is proposed. It exploits the nonlinear mapping of ANN between transient current (input) and doping concentration (output). According to the basic laws of photoelectric device operating, two types of ANN models are constructed by gaussian and polynomial fitting. The mean absolute error (MAE) of forecasting transient photocurrent can be less than 10 A under low triggering optical powers, which verifies the feasibility of ANN assisting TCAD applied to PCSSs. The results are comparable to computation by Mixed-Mode simulation, yet even thousands of seconds of CPU runtime cost are saved in every period. To improve the robustness of the Poly-ANN predictor, Bayesian optimization (BO) is implemented for minimizing the curl deviation of photocurrent-time curves.

Facial growth dynamics dictate optimal facemask fitting during the first year of life.

AIM: The aim of this study is to prevent mask leak during ventilation in infant emergencies, appropriate facemask fitting is essential. Therefore, we investigated facial profiles during the first year of life and their correlation with the correct sizing of masks. METHODS: This is a post hoc subgroup analysis of 32 healthy term infants, based on a prospective observational study performed from September 2018 to December 2019 in Tuebingen, Germany. In 3-monthly intervals, facial aspects were measured based on anatomical landmarks in three-dimensional frontal photographs to describe their changes across the first year of life. All infants were awake and breathing spontaneously; none required any anaesthesia. RESULTS: In 130 3D images, mean distance between nasion and gnathion was 54 mm (3.3) measured at birth and 70 mm (3.5) at age 12 months. Gompertz models showed relevant growth-related changes in the facial profile in vertical but not horizontal direction. Vertical growth occurred mainly in the first 6 months. Boys and girls differed by an average of about 2 mm (boys >girls). CONCLUSION: Based on our findings, it should now be verified whether the 50 mm facemasks are suitable for infants from birth to 2 months of age, respectively, the 60 mm version for infants aged three to 12 months.

Modelling glioblastoma resistance to temozolomide. A mathematical model to simulate cellular adaptation in vitro.

Drug resistance is one of the biggest challenges in the fight against cancer. In particular, in the case of glioblastoma, the most lethal brain tumour, resistance to temozolomide (the standard of care drug for chemotherapy in this tumour) is one of the main reasons behind treatment failure and hence responsible for the poor prognosis of patients diagnosed with this disease. In this work, we combine the power of three-dimensional in vitro experiments of treated glioblastoma spheroids with mathematical models of tumour evolution and adaptation. We use a novel approach based on internal variables for modelling the acquisition of resistance to temozolomide that was observed in experiments for a group of treated spheroids. These internal variables describe the cell's phenotypic state, which depends on the history of drug exposure and affects cell behaviour. We use model selection to determine the most parsimonious model and calibrate it to reproduce the experimental data, obtaining a high level of agreement between the in vitro and in silico outcomes. A sensitivity analysis is carried out to investigate the impact of each model parameter in the predictions. More importantly, we show how the model is useful for answering biological questions, such as what is the intrinsic adaptation mechanism, or for separating the sensitive and resistant populations. We conclude that the proposed in silico framework, in combination with experiments, can be useful to improve our understanding of the mechanisms behind drug resistance in glioblastoma and to eventually set some guidelines for the design of new treatment schemes.

Prosthetic management of an epulis fissuratum with simple conditioning tissue: A case report.

INTRODUCTION AND IMPORTANCE: Epulis fissuratum is an oral hyperplasic lesion related to an overextended and ill-fitting denture. The treatment of this lesion can be conservative or surgical associated to a good prosthetic management. CASE PRESENTATION: The aim of this article is to present a case report about treatment of an epulis fissuratum with simple conditioning tissue, using provisional removable complete dentures. CLINICAL DISCUSSION: The early management of the epulis fissuratum with conditioning tissue, associated to a good oral hygiene and a correct prosthetic rehabilitation provides satisfactory clinical results and avoids surgical treatment. CONCLUSION: Conditioning tissue technique is a useful conservative approach for the treatment of the epulis fissuratum at an early stage.

Automatic reorientation to generate short-axis myocardial PET images.

BACKGROUND: Accurately redirecting reconstructed Positron emission tomography (PET) images into short-axis (SA) images shows great significance for subsequent clinical diagnosis. We developed a system for automatic redirection and quantitative analysis of myocardial PET images. METHODS: A total of 128 patients were enrolled for 18 F-FDG PET/CT myocardial metabolic images (MMIs), including 3 image classifications: without defects, with defects, and excess uptake. The automatic reorientation system includes five modules: regional division, myocardial segmentation, ellipsoid fitting, image rotation and quantitative analysis. First, the left ventricular geometry-based canny edge detection (LVG-CED) was developed and compared with the other 5 common region segmentation algorithms, the optimized partitioning was determined based on partition success rate. Then, 9 myocardial segmentation methods and 4 ellipsoid fitting methods were combined to derive 36 cross combinations for diagnostic performance in terms of Pearson correlation coefficient (PCC), Kendall correlation coefficient (KCC), Spearman correlation coefficient (SCC), and determination coefficient. Finally, the deflection angles were computed by ellipsoid fitting and the SA images were derived by affine transformation. Furthermore, the polar maps were used for quantitative analysis of SA images, and the redirection effects of 3 different image classifications were analyzed using correlation coefficients. RESULTS: On the dataset, LVG-CED outperformed other methods in the regional division module with a 100% success rate. In 36 cross combinations, PSO-FCM and LLS-SVD performed the best in terms of correlation coefficient. The linear results indicate that our algorithm (LVG-CED, PSO-FCM, and LLS-SVD) has good consistency with the reference manual method. In quantitative analysis, the similarities between our method and the reference manual method were higher than 96% at 17 segments. Moreover, our method demonstrated excellent performance in all 3 image classifications. CONCLUSION: Our algorithm system could realize accurate automatic reorientation and quantitative analysis of PET MMIs, which is also effective for images suffering from interference.

International trends in prescribing extended wear soft contact lenses (2000-2023): An update.

PURPOSE: Extended wear has long been considered as the ultimate contact lens modality in terms of user convenience. The purpose of this work is to update earlier surveys by describing international trends in extended wear soft lens fitting between 2000 and 2023, inclusive. METHOD: An annual contact lens prescribing survey was sent to eye care practitioners in up to 71 countries between 2000 and 2023, inclusive. Data relating to 282,142 soft contact lens fits undertaken in 20 countries returning reliable longitudinal data were analysed in respect of extended wear soft lens fitting. RESULTS: Over the duration of the work there was a very small decrease in the prescribing of extended wear soft lenses (p < 0.0001). More detailed inspection shows that prescribing of these lenses steadily increased from 5.8 % of all soft lens fits in 2000 to 11.6 % in 2007, then steadily decreased to 5.2 % in 2023. Of all soft contact lenses prescribed to males, 9.2 % were fitted for extended wear, compared with 6.7 % for females (p < 0.0001). The mean age of extended wear soft lens wearers at fitting was 34.7 ± 14.7 years, compared to 31.1. ± 14.10 years for daily soft lens wearers (p < 0.0001). Analysis of 1,948 recent extended wear soft lens fits (2019-2023, inclusive), in terms of material type, revealed that, on average, 86 % and 14 % of extended wear soft lenses were fitted using silicone hydrogel and hydrogel materials, respectively. CONCLUSION: A modest increase in extended wear soft lens prescribing from 2000 to 2007 corresponded with the introduction of high oxygen transmissibility silicone hydrogel lenses. However, prescribing of this lens type declined thereafter, probably due to ongoing concerns over their increased rate of microbial keratitis, resulting in a prescribing rate in 2023 (5.2%) that was little different to that observed in 2000 (5.8%).

On physical analysis of topological indices for iron disulfide network via curve fitting model.

In this study, we conduct a comprehensive physical analysis of topological indices for the Iron Disulfide (FeS 2 ) network using a curve-fitting model. Iron Disulfide is a cubic compound. In metamorphic rock, sedimentary rock, and quartz veins, it is typically found in combination with other sulfides or oxides. The numerical properties of molecular structures are referred to as topological indices. There are several different kinds of topological indices, including those that are based on distance, degree, or counting, among other factors. The real process of creating a topological index involves turning a chemical structure into a numerical value. In this paper, we calculate the iron disulfide network topological indices using the degrees of vertices in a chemical network of Iron Disulfide (FeS 2 ). Thereafter, we discovered the physical parameters of FeS 2 production, such as heat of formation. We then fitted curves between the thermodynamic properties and several indices. Several techniques based on rationality, linearity, and nonlinearity were used to fit curves in MATLAB. These quantitative results imply that a variety of thermodynamic characteristics of semiconducting materials may be accurately predicted by topological indices. These findings have significant ramifications as they provide the groundwork for the application of topological indices in semiconducting network design and optimization, which might result in more effective and economical material creation.

Mathematical modelling of genipin-bovine serum albumin interaction using fluorescence intensity measurements.

The interaction between genipin and a model protein bovine serum albumin (BSA), with and without the addition of acetic acid, has been studied experimentally and by modelling. The number of amino groups available to react was determined to be 5.6 % of the total number of amino acid building blocks on BSA. Fluorescence intensity was used to record the progress of the reaction over the 24 h, while the modelling study focused on capturing the kinetic profiles of the reaction. The experiments revealed a slow start to the BSA and genipin interaction, that subsequently accelerated in an S-shaped curve which the modelling study linked with the existence of the feedback cycle for both reactive amino groups and genipin. At BSA concentrations ≥30 mg/mL the reaction was accelerated in the presence of acid, while below 30 mg/mL the acidified conditions delayed the onset of the reaction. Contrary to the reaction mechanisms previously proposed, a degree of breakdown of the fluorescent links in the products formed was denoted both experimentally and in a modelling study. This indicated the reversibility of the processes forming fluorescent product/s and suggested feasibility of the successful release of the protein following prospective encapsulation within the genipin-crosslinked hydrogel structure.

Biophysical essentials - A full stack open-source software framework for conserved and advanced analysis of patch-clamp recordings.

BACKGROUND AND OBJECTIVES: Patch-Clamp recordings allow for in depth electrophysiological characterization of single cells, their general biophysical properties as well as characteristics of voltage- and ligand-gated ionic currents. Different acquisition modes, such as whole-cell patch-clamp recordings in the current or voltage clamp configuration, capacitance measurements or single channel recordings from cultured cells as well as acute brain slices are routinely performed for these purposes. Nevertheless, multipurpose transparent and adaptable software tools to perform reproducible state-of-the-art analysis of multiple experiment types and to manage larger sets of experimental data are currently unavailable. METHODS: Biophysical Essentials (BPE) was developed as an open-source full stack python software for transparent and reproducible analysis of electrophysiological recordings. For validation, BPE results were compared with manually analyzed single-cell patch-clamp data acquired from a human in vitro nociceptor-model and mouse dorsal root ganglia neurons. RESULTS: While initially designed to improve time consuming and repetitive analysis steps, BPE was further optimized as a technical software solution for entire workflow processing including data acquisition, data preprocessing, normalization and visualization and of single recordings up to stacked calculations and statistics of multiple experiments. BPE can operate with different file formats from different amplifier systems and producers. An in-process database logs all analysis steps reproducible review and serves as a central storage point for recordings. Statistical testing as well as advanced analysis functions like Boltzmann-fitting and dimensional reduction methods further support the researchers' needs in projects involving electrophysiology techniques. CONCLUSIONS: BPE extends beyond available patch-clamp specific, open source - and commercial analysis tools in particular because of reproducible and sharable analysis workflows. BPE enables full analysis from raw data acquisition to publication ready result visualizations - all within one single program. Thereby, BPE significantly enhances transparency in the analytical process of patch-clamp data analysis. BPEs function scope is completely accessible through an easy-to-use graphical user interface eliminating the need for programing language proficiency as required by many community patch-clamp analysis frameworks and algorithms.

HeartMate 3 for Heart Failure with Preserved Ejection Fraction: In Vitro Hemodynamic Evaluation and Anatomical Fitting.

Heart failure with preserved ejection fraction (HFpEF) constitutes approximately 50% of heart failure (HF) cases, and encompasses different phenotypes. Among these, most patients with HFpEF exhibit structural heart changes, often with smaller left ventricular cavities, which pose challenges for utilizing ventricular assist devices (VADs). A left atrial to aortic (LA-Ao) VAD configuration could address these challenges, potentially enhancing patient quality of life by lowering elevated mean left atrial pressure (MLAP). This study assessed the anatomical compatibility and left atrial unloading capacity using a simulated VAD-supported HFpEF patient. A HeartMate3-supported HFpEF patient in an LA-Ao configuration was simulated using a cardiovascular simulator. Hemodynamic parameters were recorded during rest and exercise at seven pump flow rates. Computed tomography scans of 14 HFpEF (NYHA II-III) and six heart failure with reduced ejection fraction patients were analysed for anatomical comparisons. HFpEF models were independently assessed for virtual anatomical fit with the HM3 in the LA-Ao configuration. Baseline MLAP was reduced from 15 to 11 mmHg with the addition of 1 L/min HM3 support in the rest condition. In an exercise simulation, 6 L/min of HM3 support was required to reduce the MLAP from 29 to 16 mmHg. The HM3 successfully accommodated six HFpEF patients without causing interference with other cardiac structures, whereas it caused impingement ranging from 4 to 14 mm in the remaining patients. This study demonstrated that the HM3 in an LA-Ao configuration may be suitable for unloading the left atrium and relieving pulmonary congestion in some HFpEF patients where size-related limitations can be addressed through pre-surgical anatomical fit analysis.

Open-fitting hearing aids: a comparative analysis between open behind-the-ear and open completely-in-the-canal instant-fit devices.

PURPOSE: Our study aims to assess the open-fitting capabilities and vent properties of traditional open-fitting behind-the-ear (open BTE) hearing aids to instant-fit open-fitting completely-in-the-canal (open CIC) systems. METHODS: The study analysed data from 40 patients grouped in two groups based on the used hearing aids. Free field pure tone and speech audiometry were performed to obtain the free-field pure tone average and free-field word recognition score (WRS). The matrix sentence test was employed to evaluate the auditory performance and functional outcomes of patients. The Satisfaction with Amplification in Daily Life (SADL) and the Abbreviated Profile of Hearing Aid Benefit (APHAB) questionnaire were used to assess the personal satisfaction and benefit provided by the hearing aid. Real ear measurements were conducted to objectively evaluate the Real-Ear Unaided Gain (REUG) and Real-Ear Occluded Gain (REOG) of the two groups. For this purpose, six frequency bands (band 1 from 125 to 200 Hz, band 2 from 250 to 400 Hz, band 3 from 500 to 800 Hz, band 4 from 1000 to 1600 Hz, band 5 from 2000 to 3150 Hz, and band 6 from 4000 to 6300 Hz) were defined and compared. RESULTS: Free-field WRS exhibited a significant difference (p-value = 0.004) between open BTE and open CIC, with better results for the open BTE. Matrix test speech reception threshold scores did not differ significantly between groups. No statistical significant difference were observed between APHAB and SADL total scores. Correlation tests revealed a negative correlation between SRT and APHAB scores in the open BTE group, not seen in the open CIC. No statistically significant difference was observed for all bands of REUG values, demonstrating comparability in terms of acoustic resonance of the external auditory canal. Comparing the REOG recorded in the two groups a significant difference was observed for bands 2 through 6. While the average REOG values for bands 5 and 6 were higher in patients with traditional open BTE aids, in contrast, for bands 2, 3, and 4, the REOG values for the open CIC group were higher and statistically significant compared to patients wearing traditional open-fitting BTE hearing aids. CONCLUSION: Patients with open CIC seem to perform worse in quiet environments compared to noisy ones, as indicated by the free field WRS score. However, the absence of differences in functional performance assessed with the matrix sentence test, and in the psychosocial aspects, makes these devices a good solution for individuals who reject hearing aids due to aesthetic concerns. The differences in terms of real ear measurements, while statistically significant, do not negatively impact overall performance.

Relative increase in production ratio of small dense low-density lipoprotein in acute coronary syndrome with high coronary plaque burden: an ex-vivo analysis.

The absolute value of small dense low-density lipoprotein (sd-LDL) including small LDL (s-LDL) and very small LDL (vs-LDL) has been shown to be associated with increased incidence of atherosclerosis. However, the impact of short-timeframe increases in sd-LDL on arteriosclerosis has not yet been elucidated. Therefore, we investigated the clinical roles of ex-vivo induced sd-LDL in acute coronary syndrome (ACS) using a novel method. This is a prospective, single-blind, and observational study that screened patients who underwent coronary angiography (CAG) for the treatment of ACS or investigation of heart-failure etiology between June 2020 and April 2022 (n = 247). After excluding patients with known diabetes mellitus and advanced renal disease, the patients were further divided into the ACS (n = 34) and control (non-obstructive coronary artery, n = 34) groups. The proportion of sd-LDL (s-LDL + vs-LDL) in total lipoproteins was observed before and after 2-h incubation at 37 ℃ (to approximate physiologic conditions) using 3% polyacrylamide gel electrophoresis. The coronary plaque burden was quantified upon CAG in the ACS group. There were no significant differences between the ACS and control groups in terms of clinical coronary risk factors. The baseline of large, medium, small, and very small LDL were comparable between the two groups. Following a 2-h incubation period, significant increases were observed in the ratios of s-LDL and vs-LDL in both the ACS and control groups (ACS, p = 0.01*; control, p = 0.01*). Notably, the magnitude of increase in sd-LDL was more pronounced in the ACS group compared to the control group, with s-LDL showing a significant difference (p = 0.03*) and vs-LDL showing a tread toward significance (p = 0.08). In addition, in both groups, there was a decrease in IDL and L-LDL, while M-LDL remained unchanged. The plaque burden index and rate of short-timeframe changes in both s-LDL (p = 0.01*) and vs-LDL (p = 0.04*) before and after incubation were significantly correlated in the ACS group. The enhanced production rate of sd-LDL induced under short-term physiologic culture in an ex-vivo model was greater in patients with ACS than in the control group. The increase in sd-LDL is positively correlated with coronary plaque burden. Short-timeframe changes in sd-LDL may serve as markers for the severity of coronary artery disease.

Test-Retest Reliability of EEG Aperiodic Components in Resting and Mental Task States.

Aperiodic activity is derived from the electroencephalography (EEG) power spectrum and reflects changes in the slope and shifts of the broadband spectrum. Studies have shown inconsistent test-retest reliability of the aperiodic components. This study systematically measured how the test-retest reliability of the aperiodic components was affected by data duration (1, 2, 3, 4, and 5 min), states (resting with eyes closed, resting with eyes open, performing mental arithmetic, recalling the events of the day, and mentally singing songs), and methods (the Fitting Oscillations and One-Over-F (FOOOF) and Linear Mixed-Effects Regression (LMER)) at both short (90-min) and long (one-month) intervals. The results showed that aperiodic components had fair, good, or excellent test-retest reliability (ranging from 0.53 to 0.91) at both short and long intervals. It is recommended that better reliability of the aperiodic components be obtained using data durations longer than 3 min, the resting state with eyes closed, the mental arithmetic task state, and the LMER method.

In vitro fermentation potential of gut endogenous protein losses of growing pigs.

Fermentation of dietary and endogenous protein in the hindgut is generally considered detrimental to the health of pigs. We investigated the in vitro fermentation potential of porcine endogenous protein in ileal digesta and colonic mucus, using a N-free buffer with an excess of fermentable carbohydrates. Urea, whey protein isolate (WPI, positive control), WPI hydrolysate (WPIH), and combinations of the latter two were used to validate the assay. A new biphasic model, including a linear end simulation, fitted to the gas production data over a 48-h period identified the time point when substrate fermentation ended. A higher degree of hydrolysis of WPI resulted in a higher maximum gas production rate (Rmax, P < 0.01). Differences in Rmax and the time required to reach Rmax were observed among ileal digesta samples, with Rmax increasing with the insoluble protein content, and the highest Rmax occurring with colonic mucus samples (P < 0.05). The endogenous proteins entering the large intestine of pigs can ferment more rapidly compared to highly soluble and digestible protein sources, with Rmax positively correlated with decreasing solubility of endogenous nitrogenous components.

Protein fermentation in the hindgut of pigs can impact their health, affecting factors like growth rates and feed efficiency. Besides dietary protein, up to 50% of the protein entering the large intestine of growing pigs may be of endogenous origin. Therefore, we explored the fermentation potential of endogenous proteins compared to a well-known protein source, whey protein isolate (WPI). In developing and validating an in vitro gas production technique, we employed urea, WPI, WPI hydrolysate, and various combinations as substrates. The study introduces a new biphasic model for in vitro gas production, offering a detailed analysis of the fermentation process over a 48-h period. Our results revealed that porcine endogenous proteins can undergo rapid fermentation because the maximum gas production rate was higher compared to WPI. This insight is crucial for understanding the dynamics of protein fermentation in pigs. Additionally, we explored the solubility and molecular size of proteins, providing a comprehensive understanding of their fermentation characteristics. We found that endogenous proteins were less soluble compared to WPI but contained more smaller peptides. Unraveling the complexities of protein fermentation in pigs contributes to improvement of feed formulation for optimal gut health.