Increasing Higher Alcohols and Acetates in Low-Alcohol Beer by Proteases.

The market of non-alcoholic and low-alcohol beer has grown continuously thanks to the advocacy for healthy and responsible drinking. Non-alcoholic and low-alcohol products usually possess less higher alcohols and acetates and more aldehyde off-flavors due to the manufacturing processes. The employment of non-conventional yeasts partially mitigates this problem. In this study, we used proteases to optimize the wort amino acid profile for better aroma production during yeast fermentation. The design of experiments was applied to increase the leucine molar fraction, aiming to boost 3-methylbutan-1-ol and 3-methylbutyl acetate (banana-like aromas). This led to an increase from 7% to 11% leucine in wort after protease treatment. The aroma output in the subsequent fermentation, however, was yeast-dependent. An 87% increase of 3-methylbutan-1-ol and a 64% increase of 3-methylbutyl acetate were observed when Saccharomycodes ludwigii was used. When Pichia kluyveri was employed, higher alcohols and esters from valine and isoleucine were increased: 58% more of 2-methylpropyl acetate, 67% more of 2-methylbutan-1-ol, and 24% more of 2-methylbutyl acetate were observed. Conversely, 3-methylbutan-1-ol decreased by 58% and 3-methylbutyl acetate largely remained the same. Apart from these, the amounts of aldehyde intermediates were increased to a varying extent. The impact of such increases in aromas and off-flavors on the perception of low-alcohol beer remains to be evaluated by sensory analysis in future studies.

Packing a punch: understanding how flavours are produced in lager fermentations.

Beer is one of the most popular beverages in the world and it has an irreplaceable place in culture. Although invented later than ale, lager beers dominate the current market. Many factors relating to the appearance (colour, clarity and foam stability) and sensory characters (flavour, taste and aroma) of beer, and other psychological determinants affect consumers' perception of the product and defines its drinkability. This review takes a wholistic approach to scrutinise flavour generation in the brewing process, focusing particularly on the contribution of the raw ingredients and the yeasts to the final flavour profiles of lager beers. In addition, we examine current developments to improve lager beer flavour profiles for the modern consumers.

Alkaline surface treatment and time-resolved reading of mn-doped nanocrystal signal transducer for enhanced bioassay sensitivity.

Recently, Mn-doped semiconductor nanocrystals (NCs) with high brightness, long lifetimes, and low-energy excitation are emerging for time-resolved luminescence biosensing/imaging. Following our previous work on Mn-doped NCs, in this work we developed poly(styrene-co-maleic anhydride) (PSMA)-encapsulated Mn-doped AgZnInS/ZnS NCs as signal transducers for immunoassay of capsular polysaccharide (CPS), a surface antigen and also a biomarker of Burkholderia pseudomallei which causes a fatal disease called melioidosis. To enhance the assay sensitivity, a surface treatment for PSMA-encapsulated NCs (NC-probes) was performed to promote the presence of carboxyl groups that help conjugate more anti-CPS antibodies to the surface of NC-probes and thus enhance bioassay signals. Meanwhile, time-resolved reading on the luminescence of NC-probes was adopted to minimize the assay background autofluorescence. Both strategies essentially enhance the assay signal-to-background ratio (or equivalently the assay sensitivity) by increasing the signal and decreasing the background, respectively. Through performing and comparing immunoassays with different NC-probes (with and without surface treatment) and different signal reading methods (time-resolved reading and non-time-resolved reading), it was proven that the immunoassay adopting surface-treated NC-probes and time-resolved reading achieved a lower limit-of-detection (LOD) than the ones adopting non-surface-treated NC-probes or non-time-resolved reading. Moreover, the achieved LOD is comparable to the LOD of immunoassay using enzyme horseradish peroxidase as a signal transducer.

Sex Differences in Coronary Artery Disease Characteristics Among Patients With Type 2 Myocardial Infarction.

Background: Type 2 myocardial infarction (MI) results from coronary supply and demand imbalance and has a poor prognosis. It is crucial to identify potential sex-based differences in the prevalence and nature of coronary artery disease (CAD) within this population. Objectives: The purpose of this study was to evaluate sex-based disease differences in type 2 MI among patients evaluated with coronary computed tomography angiography and fractional flow reserve. Methods: In a single-center, prospective study, patients with strictly adjudicated type 2 MI underwent coronary computed tomography angiography with fractional flow reserve. Results: Among 50 study participants enrolled, 50% were women. A similar mix of MI precipitants was present in both sexes. ST-segment depression was more common in women (64% vs 32%), while men were more likely to have T wave inversion (68% vs 36%). Women and men had comparable coronary artery calcium scores (median: 152 [Q1, Q3: 45, 762] vs 234 [Q1, Q3: 56, 422]). Prevalence of any CAD (84% vs 100%), obstructive CAD (24% vs 28%), and hemodynamically significant focal stenosis (20% vs 32%) were similar between sexes. Total plaque volume was similar between sexes, but women had significantly lower levels of low-attenuation plaque (median: 3 [Q1, Q3: 1, 7] vs 9 [Q1, Q3: 3, 14]). Conclusions: Among patients with type 2 MI, prevalence of any CAD and obstructive CAD did not differ according to sex. Total plaque volume was similar between sexes, but women had a lower volume of low-attenuation plaque (DEFINing the PrEvalence and Characteristics of Coronary Artery Disease Among Patients With TYPE 2 Myocardial Infarction Using CT-FFR [DEFINE TYPE2MI]; NCT04864119).

The Societal Cost of Schizophrenia: An Updated Systematic Review of Cost-of-Illness Studies.

BACKGROUND: Schizophrenia imposes a substantial economic burden on society. This updated systematic review aims to collate the latest societal cost of schizophrenia across countries by reviewing recent cost-of-illness (COI) studies. METHODS: An electronic search was conducted across several databases (MEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Health Management Information Consortium, and System for Information on Grey Literature) to identify COI studies published from 2016 to 2022. Two independent reviewers selected studies for inclusion. The cost components and estimates reported by included studies were descriptively summarised. All costs were converted to US dollars (2022 values). Study quality was assessed using a checklist adapted from Larg & Moss. RESULTS: Twenty-four studies were included (5 from the update review and 19 from the original review), of which only two were conducted for low- and middle-income countries (LMICs). Widespread methodological heterogeneity among included studies was observed. The annual societal cost per person varied from US$819 in Nigeria to US$94,587 in Norway. Productivity losses accounted for 32-83% of the overall societal cost, whilst direct healthcare cost made up 11-87%. The reporting quality of included studies varied. CONCLUSION: This review highlights the substantial economic burden of schizophrenia and a lack of COI studies for LMICs. Recommendations on future research, and good practices on improving the methodological and reporting quality of COI research for schizophrenia are provided.

Novel combination of imipridones and histone deacetylase inhibitors demonstrate cytotoxic effect through integrated stress response in pediatric solid tumors.

There is a demonstrated need for new chemotherapy options in pediatric oncology, as pediatric solid tumors continue to plateau at 60% with event-free survival. Imipridones, a novel class of small molecules, represent a potential new therapeutic option, with promising pre-clinical data and emerging clinical trial data in adult malignancies. ONC201, ONC206, and ONC212 are imipridones showing pro-apoptotic anti-cancer response. Using cell viability assays, and protein immunoblotting, we were able to demonstrate single-agent efficacy of all 3 imipridones inducing cell death in pediatric solid tumor cell lines, including osteosarcoma, malignant peripheral nerve sheath tumors, Ewing sarcoma (EWS), and neuroblastoma. ONC201 displayed IC50 values for non-H3K27M-mutated EWS cell lines ranging from 0.86 µM (SK-N-MC) to 2.76 µM (RD-ES), which were comparable to the range of IC50 values for H3K27M-mutated DIPG cells lines (range 1.06 to 1.56 µM). ONC212 demonstrated the highest potency in single-agent cell killing, followed by ONC206, and ONC201. Additionally, pediatric solid tumor cells were treated with single-agent therapy with histone deacetylase inhibitors (HDACi) vorinostat, entinostat, and panobinostat, showing cell killing with all 3 HDACi drugs, with panobinostat showing the greatest potency. We demonstrate that dual-agent therapy with combinations of imipridones and HDACi lead to synergistic cell killing and apoptosis in all pediatric solid tumor cell lines tested, with ONC212 and panobinostat combinations demonstrating maximal potency. The imipridones induced the integrated stress response with ATF4 and TRAIL receptor upregulation, as well as reduced expression of ClpX. Hyperacetylation of H3K27 was associated with synergistic killing of tumor cells following exposure to imipridone plus HDAC inhibitor therapies. Our results introduce a novel class of small molecules to treat pediatric solid tumors in a precision medicine framework. Use of impridones in pediatric oncology is novel and shows promising pre-clinical efficacy in pediatric solid tumors, including in combination with HDAC inhibitors.

Coronary Computed Tomographic Angiography With Fractional Flow Reserve in Patients With Type 2 Myocardial Infarction.

BACKGROUND: Type 2 myocardial infarction (T2MI) related to a supply/demand imbalance of coronary blood flow is common and associated with poor prognosis. Coronary artery disease (CAD) may predispose some individuals to T2MI and contribute to its high rate of recurrent cardiovascular events. Little is known about the presence and extent of CAD in this population. OBJECTIVES: The goal of this study was to evaluate the presence and characteristics of CAD among patients with T2MI. METHODS: In this prospective study, consecutive eligible individuals with Fourth Universal Definition of Myocardial Infarction criteria for T2MI were enrolled. Participants underwent coronary computed tomography angiography (CTA), fractional flow reserve derived with coronary CTA (FFRCT), and plaque volume analyses. RESULTS: Among 50 participants, 25 (50%) were female, and the mean age was 68.0 ± 11.4 years. Atherosclerotic risk factors were common. Coronary CTA revealed coronary plaque in 46 participants (92%). A moderate or greater stenosis (≥50%) was identified in 42% of participants, and obstructive disease (≥50% left main stenosis or ≥70% stenosis in any other epicardial coronary artery) was present in 26%. Prevalence of obstructive CAD did not differ according to T2MI cause (P = 0.54). A hemodynamically significant focal stenosis identified by FFRCT was present in 13 participants (26%). Among participants with a stenosis ≥50% (n = 21), FFRCT excluded lesion-specific hemodynamically significant stenosis in 8 cases (38%). CONCLUSIONS: Among individuals with adjudicated T2MI, CAD was prevalent, but the majority of patients had nonobstructive CAD. Mediators of ischemia are likely multifactorial in this population. (Defining the Prevalence and Characteristics of Coronary Artery Disease Among Patients with Type 2 Myocardial Infarction using CT-FFR [DEFINE TYPE 2 MI]; NCT04864119).

Performance of a deep learning-based CT image denoising method: Generalizability over dose, reconstruction kernel, and slice thickness.

PURPOSE: Deep learning (DL) is rapidly finding applications in low-dose CT image denoising. While having the potential to improve the image quality (IQ) over the filtered back projection method (FBP) and produce images quickly, performance generalizability of the data-driven DL methods is not fully understood yet. The main purpose of this work is to investigate the performance generalizability of a low-dose CT image denoising neural network in data acquired under different scan conditions, particularly relating to these three parameters: reconstruction kernel, slice thickness, and dose (noise) level. A secondary goal is to identify any underlying data property associated with the CT scan settings that might help predict the generalizability of the denoising network. METHODS: We select the residual encoder-decoder convolutional neural network (REDCNN) as an example of a low-dose CT image denoising technique in this work. To study how the network generalizes on the three imaging parameters, we grouped the CT volumes in the Low-Dose Grand Challenge (LDGC) data into three pairs of training datasets according to their imaging parameters, changing only one parameter in each pair. We trained REDCNN with them to obtain six denoising models. We test each denoising model on datasets of matching and mismatching parameters with respect to its training sets regarding dose, reconstruction kernel, and slice thickness, respectively, to evaluate the denoising performance changes. Denoising performances are evaluated on patient scans, simulated phantom scans, and physical phantom scans using IQ metrics including mean-squared error (MSE), contrast-dependent modulation transfer function (MTF), pixel-level noise power spectrum (pNPS), and low-contrast lesion detectability (LCD). RESULTS: REDCNN had larger MSE when the testing data were different from the training data in reconstruction kernel, but no significant MSE difference when varying slice thickness in the testing data. REDCNN trained with quarter-dose data had slightly worse MSE in denoising higher-dose images than that trained with mixed-dose data (17%-80%). The MTF tests showed that REDCNN trained with the two reconstruction kernels and slice thicknesses yielded images of similar image resolution. However, REDCNN trained with mixed-dose data preserved the low-contrast resolution better compared to REDCNN trained with quarter-dose data. In the pNPS test, it was found that REDCNN trained with smooth-kernel data could not remove high-frequency noise in the test data of sharp kernel, possibly because the lack of high-frequency noise in the smooth-kernel data limited the ability of the trained model in removing high-frequency noise. Finally, in the LCD test, REDCNN improved the lesion detectability over the original FBP images regardless of whether the training and testing data had matching reconstruction kernels. CONCLUSIONS: REDCNN is observed to be poorly generalizable between reconstruction kernels, more robust in denoising data of arbitrary dose levels when trained with mixed-dose data, and not highly sensitive to slice thickness. It is known that reconstruction kernel affects the in-plane pNPS shape of a CT image, whereas slice thickness and dose level do not, so it is possible that the generalizability performance of this CT image denoising network highly correlates to the pNPS similarity between the testing and training data.

Molecular Targets for Novel Therapeutics in Pediatric Fusion-Positive Non-CNS Solid Tumors.

Chromosomal fusions encoding novel molecular drivers have been identified in several solid tumors, and in recent years the identification of such pathogenetic events in tumor specimens has become clinically actionable. Pediatric sarcomas and other rare tumors that occur in children as well as adults are a group of heterogeneous tumors often with driver gene fusions for which some therapeutics have already been developed and approved, and others where there is opportunity for progress and innovation to impact on patient outcomes. We review the chromosomal rearrangements that represent oncogenic events in pediatric solid tumors outside of the central nervous system (CNS), such as Ewing Sarcoma, Rhabdomyosarcoma, Fibrolamellar Hepatocellular Carcinoma, and Renal Cell Carcinoma, among others. Various therapeutics such as CDK4/6, FGFR, ALK, VEGF, EGFR, PDGFR, NTRK, PARP, mTOR, BRAF, IGF1R, HDAC inhibitors are being explored among other novel therapeutic strategies such as ONC201/TIC10.

Efficient Regularized Field Map Estimation in 3D MRI.

Magnetic field inhomogeneity estimation is important in some types of magnetic resonance imaging (MRI), including field-corrected reconstruction for fast MRI with long readout times, and chemical shift based water-fat imaging. Regularized field map estimation methods that account for phase wrapping and noise involve nonconvex cost functions that require iterative algorithms. Most existing minimization techniques were computationally or memory intensive for 3D datasets, and are designed for single-coil MRI. This paper considers 3D MRI with optional consideration of coil sensitivity, and addresses the multi-echo field map estimation and water-fat imaging problem. Our efficient algorithm uses a preconditioned nonlinear conjugate gradient method based on an incomplete Cholesky factorization of the Hessian of the cost function, along with a monotonic line search. Numerical experiments show the computational advantage of the proposed algorithm over state-of-the-art methods with similar memory requirements.

Efficient Dynamic Parallel MRI Reconstruction for the Low-Rank Plus Sparse Model.

The low-rank plus sparse (L+S) decomposition model enables the reconstruction of under-sampled dynamic parallel magnetic resonance imaging (MRI) data. Solving for the low-rank and the sparse components involves non-smooth composite convex optimization, and algorithms for this problem can be categorized into proximal gradient methods and variable splitting methods. This paper investigates new efficient algorithms for both schemes. While current proximal gradient techniques for the L+S model involve the classical iterative soft thresholding algorithm (ISTA), this paper considers two accelerated alternatives, one based on the fast iterative shrinkage-thresholding algorithm (FISTA), and the other with the recent proximal optimized gradient method (POGM). In the augmented Lagrangian (AL) framework, we propose an efficient variable splitting scheme based on the form of the data acquisition operator, leading to simpler computation than the conjugate gradient (CG) approach required by existing AL methods. Numerical results suggest faster convergence of the efficient implementations for both frameworks, with POGM providing the fastest convergence overall and the practical benefit of being free of algorithm tuning parameters.

Numerical methods for polyline-to-point-cloud registration with applications to patient-specific stent reconstruction.

We present novel numerical methods for polyline-to-point-cloud registration and their application to patient-specific modeling of deployed coronary artery stents from image data. Patient-specific coronary stent reconstruction is an important challenge in computational hemodynamics and relevant to the design and improvement of the prostheses. It is an invaluable tool in large-scale clinical trials that computationally investigate the effect of new generations of stents on hemodynamics and eventually tissue remodeling. Given a point cloud of strut positions, which can be extracted from images, our stent reconstruction method aims at finding a geometrical transformation that aligns a model of the undeployed stent to the point cloud. Mathematically, we describe the undeployed stent as a polyline, which is a piecewise linear object defined by its vertices and edges. We formulate the nonlinear registration as an optimization problem whose objective function consists of a similarity measure, quantifying the distance between the polyline and the point cloud, and a regularization functional, penalizing undesired transformations. Using projections of points onto the polyline structure, we derive novel distance measures. Our formulation supports most commonly used transformation models including very flexible nonlinear deformations. We also propose 2 regularization approaches ensuring the smoothness of the estimated nonlinear transformation. We demonstrate the potential of our methods using an academic 2D example and a real-life 3D bioabsorbable stent reconstruction problem. Our results show that the registration problem can be solved to sufficient accuracy within seconds using only a few number of Gauss-Newton iterations.

Rhodium-catalyzed 1,3-acyloxy migration and subsequent intramolecular [4+2] cycloaddition of vinylallene and unactivated alkyne.

A Rh-catalyzed 1,3-acyloxy migration of propargyl ester followed by intramolecular [4+2] cycloaddition of vinylallene and unactivated alkyne was developed. This tandem reaction provides access to bicyclic compounds containing a highly functionalized isotoluene or cyclohexenone structural motif, while only aromatic compounds were observed in related transition metal-catalyzed cycloadditions.