Rejection Threshold Research Articles

Donor-derived Cell-free DNA Evaluation in Pediatric Heart Transplant Recipients: A Single-center 12-mo Experience.

Endomyocardial biopsy (EMB) is considered the gold-standard method to diagnose rejection after heart transplantation. However, the many disadvantages and potential complications of this test restrict its routine application, particularly in pediatric patients. Donor-derived cell-free DNA (dd-cfDNA), released by the transplanted heart as result of cellular injury, is emerging as a biomarker of tissue damage involved in ischemia/reperfusion injury and posttransplant rejection. In the present study, we systematically evaluated dd-cfDNA levels in pediatric heart transplant patients coming for follow-up visits to our clinic for 12 mo, with the aim of determining whether dd-cfDNA monitoring could be efficiently applied and integrated into the posttransplant management of rejection in pediatric recipients. Twenty-nine patients were enrolled, and cfDNA was obtained from 158 blood samples collected during posttransplant follow-up. dd-cfDNA% was determined with a droplet-digital polymerase chain reaction assay. EMB scores, donor-specific antibody measurements, and distress marker quantification were correlated with dd-cfDNA, together with echocardiogram information. The percentage of dd-cfDNA increased when EMBs scored positive for rejection (P = 0.0002) and donor-specific antibodies were present (P = 0.0010). N-terminal pro-B-type natriuretic peptide and high-sensitive troponin I elevation were significantly associated with dd-cfDNA release (P = 0.02 and P < 0.0001, respectively), as were reduced isovolumetric relaxation time (P = 0.0031), signs of heart failure (P = 0.0018), and treatment for rejection (P = 0.0017). By determining a positive threshold for rejection at 0.55%, the test had a negative predictive value maximized at 100%. Collectively, results indicate that dd-cfDNA monitoring has a high negative prognostic value, suggesting that in heart transplanted children with dd-cfDNA levels of <0.55% threshold, protocol EMBs may be postponed.

Physicochemical Characterization of Carao Honey Flour (Cassia grandis) and Its Effects on the Sensory Attributes in a Cookie

Carao honey is a potential functional ingredient that can generate added value to food products enriched by reducing waste. In many countries, carao has been utilized for therapeutic purposes since this type of plant extract can inhibit the growth against the most common dermatophytes, a pathogenic fungus that grows on the skin, mucous membranes, hair, nails, feathers, and other body surfaces, causing ringworm and related diseases. The physicochemical characteristics of the cookies were also investigated, which included aW, proximate analysis, hardness, and color. A sensory study was carried out to determine the rejection threshold, acceptability, purchase intent, and general taste of 90 consumers. The gluten-free cookies were prepared with carao honey as a partial substitute for rice flour in different percentages (0%, 2.5%, 5%, and 10%). The carao honey proximate composition, rheological properties, and pasting properties were analyzed. It was emphasized that incorporating carao honey into cookies improves the ingredient’s sustainability. The impact of carao on the physicochemical and sensory properties of cookies was evident in color, flavor, and smell. According to the results, only samples with 2.5% carao were accepted regarding flavor and smell. Overall, liking scores, age, and flavor were the most significant predictors of purchase intent. The information given to panelists did not significantly (p &lt; 0.05) influence liking scores only for cookies. According to physicochemical analysis, carao honey flour was high in carbohydrates (88%). The incorporation of carao produced cookies with darker colors and a softer texture. The study demonstrated that carao flour could be included to produce sensorial accepted cookies at a 2.5% addition level as an alternative in the food industry that benefits from environmental sustainability and, at the nutritional level, improves the availability of nutrients, mainly sugars and proteins.

FPGA implementation and measurement of cusp-flattop hybrid filter shaping method for nuclear instruments

In the field of nuclear technology applications, digital multi-channel pulse amplitude analysis technology plays an indispensable role in information acquisition due to its high precision and sensitivity. However, the challenge of pulse pileup can compromise the accuracy of measurement results in this technology. While conventional filter shaping and pulse pileup processing methods can extract nuclear pulse feature information under mild pileup conditions, severe pileup can notably degrade spectral counting rate and resolution. This paper introduces a designed two-channel pulse pileup rejection method, termed the cusp-flattop hybrid filter forming algorithm, leveraging the unique features of cusp, such as high forming speed and minimal interference from pulse pileup. The two channels simultaneously process the collected signals and utilize their differences for data filtering and rejection. This approach enhances information content, improves data processing quality, and boosts the signal-to-noise ratio. Compared to three methods—three trapezoidal filter shaping algorithms, the triangle trapezoidal pulse shaping algorithm, and the pulse width discrimination algorithm—our proposed method refines the shaping threshold of pulse pileup rejection. It accurately distinguishes and extracts effective pulse amplitudes even under severe pileup conditions, generating energy spectrum results while accounting for counting rate and resolution. Building on this, we construct a digital multichannel pulse amplitude analysis system based on FPGA (Field Programmable Gate Array) and use a national standard alloy sample, YSBS41346, for testing. The system can generate energy spectrum correctly, consistent with the actual sample content. We evaluate the system's performance by comparing the peak counting rate and resolution of the energy spectrum generated by the cusp-flattop hybrid filter forming algorithm and the trapezoidal forming algorithm. A high peak counting rate represents the maximum nuclear pulse data captured by the system, while low resolution indicates more valid data after pileup rejection. Through testing, the peak counting rate reaches 12843cps, with a resolution of 6.68%, marking a significant improvement over the trapezoidal pulse forming algorithm. The system demonstrates satisfactory performance and operational effectiveness, aligning with the design objectives and presenting innovative and practical applications.

PallorMetrics: Software for Automatically Quantifying Optic Disc Pallor in Fundus Photographs, and Associations With Peripapillary RNFL Thickness.

We sough to develop an automatic method of quantifying optic disc pallor in fundus photographs and determine associations with peripapillary retinal nerve fiber layer (pRNFL) thickness. We used deep learning to segment the optic disc, fovea, and vessels in fundus photographs, and measured pallor. We assessed the relationship between pallor and pRNFL thickness derived from optical coherence tomography scans in 118 participants. Separately, we used images diagnosed by clinical inspection as pale (n = 45) and assessed how measurements compared with healthy controls (n = 46). We also developed automatic rejection thresholds and tested the software for robustness to camera type, image format, and resolution. We developed software that automatically quantified disc pallor across several zones in fundus photographs. Pallor was associated with pRNFL thickness globally (β = -9.81; standard error [SE] = 3.16; P < 0.05), in the temporal inferior zone (β = -29.78; SE = 8.32; P < 0.01), with the nasal/temporal ratio (β = 0.88; SE = 0.34; P < 0.05), and in the whole disc (β = -8.22; SE = 2.92; P < 0.05). Furthermore, pallor was significantly higher in the patient group. Last, we demonstrate the analysis to be robust to camera type, image format, and resolution. We developed software that automatically locates and quantifies disc pallor in fundus photographs and found associations between pallor measurements and pRNFL thickness. We think our method will be useful for the identification, monitoring, and progression of diseases characterized by disc pallor and optic atrophy, including glaucoma, compression, and potentially in neurodegenerative disorders.

Added sugar in coffee beverages: A study with a sample of Brazilian consumers of sweetened and unsweetened coffee

AbstractThis study aimed to determine the compromised acceptance threshold (CAT) and the hedonic rejection threshold (HRT) for consumers of sweetened coffee to propose a strategy to reduce the sucrose addition by studying the behavior of consumers of sweetened and unsweetened coffee. From the sample that showed the highest acceptance (control sample, with 12% added sucrose), it was possible to reduce the sucrose addition by up to 18% without compromising acceptance (CAT = 9.76%) and by up to 52% without promoting the rejection of the beverage (HRT = 5.61%). Consumers who were reducing the sucrose addition exhibited a reduction in CAT (6.54%). Consumers of sweetened and unsweetened coffee had different perceptions regarding the sweetened beverage, thus, research involving coffee consumption should be segmented between these two groups. As a strategy, we suggest that the reduction of sucrose should be gradual and associated with information about its health benefits.Practical ApplicationsThe results are relevant for those interested in understanding the habits of consumers of sweetened and unsweetened coffee and providing an estimate of the tolerance of consumers of sweetened beverages when reducing the sucrose content in coffee beverages. Considering the volume and regularity of coffee consumption by Brazilian consumers, these findings can contribute to the development of a strategy to reduce sugar consumption. This information also supports the production sector in developing ready‐to‐drink beverages, prepared by industries and coffee shops or available in vending machines, indicating that the concentration of added sugar provided can be reduced, as long as a sufficient amount is maintained not to impair the acceptance of the beverage. Additionally, the data are important for sensory analysis researchers, enabling them to better adapt coffee beverage tasting conditions to consumer expectations and, thus, obtain more reliable results.

Enhancing saltiness perception in bone broth: the additive effect of oil and optimization of sodium-reduction formula for consumer acceptability.

Excessive NaCl intake in liquid and semi-solid food (e.g. soup, hot pot base, sauce) poses a high risk to human health, and reducing NaCl intake is a major concern for global health. Using the generalized Labeled Magnitude Scale (gLMS) method, the study verified the possibility of sodium reduction through oil addition. The compromised acceptance threshold (CAT) and hedonic rejection threshold (HRT) were determined. The gLMS results showed that the saltiness intensity of samples containing 0.36% NaCl and 2.29% sunflower seed oil was significantly higher than that of samples containing only 0.36% NaCl (P < 0.05). CAT and HRT results indicated that by adding 3.59% sunflower oil, the NaCl content could be reduced to a minimum of 0.14% without causing sensory rejection in bone broth samples. The quantitative descriptive analysis method was used to determine the effects of NaCl and oil concentrations on the sensory attributes of bone broth samples. Furthermore, it was used to analyze the consumer acceptability drivers in combination with the hedonic scale to optimize the formulation of reduced-salt bone broth products. Notably, sample E (0.36% NaCl, 2.29% fat) not only had a significant salt reduction effect with a 20% decrease in NaCl, but also had improved overall acceptability. This study provides theoretical guidance for designing salt-reduction cuisine within the catering and food industries, including bone broth and hot pot bases. © 2024 Society of Chemical Industry.

Identification of lentils (Lens culinaris Medik) from Eglouvi (Lefkada, Greece) based on rare earth elements profile combined with chemometrics

An analytical approach has been developed to verify the authenticity of premium lentils originating from Eglouvi, Lefkada, Greece. The method relies on the digestion of samples followed by the analysis of their rare earth elements (REEs) content. Lentils originating from Eglouvi exhibit higher content in most REEs compared to lentils from other regions as well as distinct Sc/Y and Sc/Yb concentration ratios. Principal component analysis effectively segregates “Eglouvi” lentils into a distinct cluster. Soft Independent Modelling of Class Analogy (SIMCA) successfully models “Eglouvi” lentils. Significant enhancement in model specificity was achieved upon inclusion of Sc/Y and Sc/Yb concentration ratios as additional variables. The model is capable of detecting adulteration in blends of Eglouvi lentils, with a minimum rejection threshold of 4.6% w/w for Greek lentil adulterants and 6.0% w/w for imported lentil adulterants.

Uncertainty-aware single-cell annotation with a hierarchical reject option.

Automatic cell type annotation methods assign cell type labels to new datasets by extracting relationships from a reference RNA-seq dataset. However, due to the limited resolution of gene expression features, there is always uncertainty present in the label assignment. To enhance the reliability and robustness of annotation, most machine learning methods address this uncertainty by providing a full reject option, i.e. when the predicted confidence score of a cell type label falls below a user-defined threshold, no label is assigned and no prediction is made. As a better alternative, some methods deploy hierarchical models and consider a so-called partial rejection by returning internal nodes of the hierarchy as label assignment. However, because a detailed experimental analysis of various rejection approaches is missing in the literature, there is currently no consensus on best practices. We evaluate three annotation approaches (i) full rejection, (ii) partial rejection, and (iii) no rejection for both flat and hierarchical probabilistic classifiers. Our findings indicate that hierarchical classifiers are superior when rejection is applied, with partial rejection being the preferred rejection approach, as it preserves a significant amount of label information. For optimal rejection implementation, the rejection threshold should be determined through careful examination of a method's rejection behavior. Without rejection, flat and hierarchical annotation perform equally well, as long as the cell type hierarchy accurately captures transcriptomic relationships. Code is freely available at https://github.com/Latheuni/Hierarchical_reject and https://doi.org/10.5281/zenodo.10697468.

Cluster-based Adversarial Decision Boundary for domain-adaptive open set recognition

Domain adaptation has achieved significant progress recently by adapting models trained on a source domain to an unlabeled target domain. Open Set Domain adaptation (OSDA) has drawn much attention nowadays, where the target domain contains some exclusive categories other than the source domain’s known classes. With no label in the target data, existing OSDA methods often suffer from negative transfer. Conventional methods for unknown class rejection require an empirical setting of the confidence threshold, which lacks flexibility since the model confidence may vary during the training process, and our motivation is to omit the effort of setting the rejection threshold manually. Based on the idea that latent features of the same class should be in the same cluster to address this issue, we propose a domain adaptive open set recognition framework: Cluster-based Adversarial Decision Boundary (CADB). Specifically, we design an end-to-end unknown class rejection model consisting of three components: known class prototype estimation under the cluster assumption; known class similarity score estimation; and adaptive unknown class rejection threshold generation with adversarial feature suppression. These three components work as one entity to give a similarity score for each sample. Those samples that are less similar to the cluster prototype compared with the counterfactual features are rejected as the unknown class. Extensive evaluations are conducted to verify the effectiveness and robustness of the proposed boundary generation procedure.

An Open Set Recognition for SAR Targets Based on Encoding-Conditional Decoding Network with Reject Threshold Adaptation

An Open Set Recognition for SAR Targets Based on Encoding-Conditional Decoding Network with Reject Threshold Adaptation

Recognition and rejection of foreign eggs of different colors in Barn Swallows

Brood parasitic birds lay eggs in the nests of other birds, and the parasitized hosts can reduce the cost of raising unrelated offspring through the recognition of parasitic eggs. Hosts can adopt vision-based cognitive mechanisms to recognize foreign eggs by comparing the colors of foreign and host eggs. However, there is currently no uniform conclusion as to whether this comparison involves the single or multiple threshold decision rules. In this study, we tested both hypotheses by adding model eggs of different colors to the nests of Barn Swallows (Hirundo rustica) of two geographical populations breeding in Hainan and Heilongjiang Provinces in China. Results showed that Barn Swallows rejected more white model eggs (moderate mimetic to their own eggs) and blue model eggs (highly non-mimetic eggs with shorter reflectance spectrum) than red model eggs (highly non-mimetic eggs with longer reflectance spectrum). There was no difference in the rejection rate of model eggs between the two populations of Barn Swallows, and clutch size was not a factor affecting egg recognition. Our results are consistent with the single rejection threshold model. This study provides strong experimental evidence that the color of model eggs can has an important effect on egg recognition in Barn Swallows, opening up new avenues to uncover the evolution of cuckoo egg mimicry and explore the cognitive mechanisms underlying the visual recognition of foreign eggs by hosts.

Development of an Adaptive Artifact Subspace Reconstruction Based on Hebbian/Anti-Hebbian Learning Networks for Enhancing BCI Performance.

Brain-computer interface (BCI) actively translates the brain signals into executable actions by establishing direct communication between the human brain and external devices. Recording brain activity through electroencephalography (EEG) is generally contaminated with both physiological and nonphysiological artifacts, which significantly hinders the BCI performance. Artifact subspace reconstruction (ASR) is a well-known statistical technique that automatically removes artifact components by determining the rejection threshold based on the initial reference EEG segment in multichannel EEG recordings. In real-world applications, the fixed threshold may limit the efficacy of the artifact correction, especially when the quality of the reference data is poor. This study proposes an adaptive online ASR technique by integrating the Hebbian/anti-Hebbian neural networks into the ASR algorithm, namely, principle subspace projection ASR (PSP-ASR) and principal subspace whitening ASR (PSW-ASR) that segmentwise self-organize the artifact subspace by updating the synaptic weights according to the Hebbian and anti-Hebbian learning rules. The effectiveness of the proposed algorithm is compared to the conventional ASR approaches on benchmark EEG dataset and three BCI frameworks, including steady-state visual evoked potential (SSVEP), rapid serial visual presentation (RSVP), and motor imagery (MI) by evaluating the root-mean-square error (RMSE), the signal-to-noise ratio (SNR), the Pearson correlation, and classification accuracy. The results demonstrated that the PSW-ASR algorithm effectively removed the EEG artifacts and retained the activity-specific brain signals compared to the PSP-ASR, standard ASR (Init-ASR), and moving-window ASR (MW-ASR) methods, thereby enhancing the SSVEP, RSVP, and MI BCI performances. Finally, our empirical results from the PSW-ASR algorithm suggested the choice of an aggressive cutoff range of c = 1-10 for activity-specific BCI applications and a moderate range of for the benchmark dataset and general BCI applications.

Physico-Chemical and Sensory Assessment of Local and Imported Catfish Fillets

In this study, twenty fresh African catfish (Clarias gariepinus) and silver catfish (Bagrus bayad) fillets as well as twenty frozen pangasius catfish (Pangasianodon hypophthalmus) fillets were collected from Egyptian local markets and retailers during 2021. Pangasius catfish fillets can be divided into two grades: white basa fillets (grade I, white colour) and red basa fillets (grade II, pale pink to red colour). This study aimed to assess the physical (colour and shear force), chemical (pH, TVB-N and TBARS) and sensory parameters of catfish fillet samples. The sensory attributes of raw catfish fillets were measured using a 9-point hedonic scale and these attributes include colour and appearance, odor, texture, and overall acceptability. The results of the proximate composition showed that the African catfish and silver catfish fillets had significantly lower moisture (76.12-76.94) and higher crude protein (17.19-17.24) and fat levels (3.35-4.12) compared to the frozen Pangasius catfish fillets. The total volatile basic nitrogen (TVB-N) ranged from 6.83 to 16.38 mg/100g, thiobarbituric acid-reactive substances (TBARS) values ranged from 0.35 to 1.01 mg malonaldehyde/kg and pH ranged from 6.43 to 7.35. The TVB-N and TBARS values of examined catfish fillets were within acceptable limits. The African catfish fillets were darker and characterized by higher redness (a*) and lower yellowness (b*) values as well as higher shear force values (9.52 kgf/m3), while white basa fillet was the lowest darkness, less saturated with the red pigment (a*) and more saturated with the yellow component (b*) as well as lower shear values (2.17 kgf/m3) among the examined catfish fillets. African catfish and silver catfish fillets showed significantly higher sensory scores than the Pangasius catfish fillets. All the organoleptic properties of raw catfish fillets were above the rejection threshold score (≤4.0) In conclusion, catfish fillets were of superior quality and acceptable for human consumption.

Host learning selects for the coevolution of greater egg mimicry and narrower antiparasitic egg-rejection thresholds.

Egg rejection is an effective and widespread antiparasitic defense to eliminate foreign eggs from the nests of hosts of brood parasitic birds. Several lines of observational and critical experimental evidence support a role for learning by hosts in the recognition of parasitic versus own eggs; specifically, individual hosts that have had prior or current experience with brood parasitism are more likely to reject foreign eggs. Here we confirm experimentally the role of prior experience in altering subsequent egg-rejection decisions in the American robin Turdus migratorius, a free-living host species of an obligate brood parasite, the brown-headed cowbird Molothrus ater. We then model the coevolutionary trajectory of both the extent of mimicry of host eggs by parasitic eggs and the host's egg rejection thresholds in response to an increasing role of learning in egg recognition. Critically, with more learning, we see the evolution of both narrower (more discriminating) rejection thresholds in hosts and greater egg mimicry in parasites. Increasing host clutch size (number of eggs/nest) and increasing parasite load (parasitism rate) also have narrowing effects on the egg-rejection threshold. Together, these results suggest that learning from prior experience with egg rejection may play an important role in the coevolution of egg-mimetic lineages of brood parasites and the refined egg rejection defenses of hosts.

Incorporation of jaggery in beetroot jam enhances its antioxidant properties with acceptable sensory and physicochemical profile

With the growing consumer interest in incorporating healthier foods in diet, the market for functional foods is increasing. The present study focused on developing beetroot jam (BJ) using jaggery (non-centrifugal sugar) as a sweetener. Formulation of BJ was carried out by partial replacement of sugar with jaggery and evaluated for sensory attributes (odor, color, spreadability, taste, acid attribute and overall acceptance) using compromised acceptance threshold (CAT) and the hedonic rejection threshold (HRT). The incorporation of jaggery in BJ shifted the acceptances of tatse (CATt = 82.56%), color (CATc = 78.82%), odor (CATo = 73.16%), acid attribute (CATac = 65.01%), overall acceptance (CAToc = 65.61%), and spreadabality (CATs=50.94%). This depreciation, however, did not result in sensory rejection of the jam odor, color, and taste. On the other hand, a sensory rejection started to occur for spreadability, acid attribute, and overall acceptance at jaggery concentrations of 66.92%, 88.1%, and 77.49%, respectively. Physicochemical characterization of BJ for parameters such as color, texture, and rheological properties was carried out. Thermal behaviour of BJ was studied using differential scanning calorimetry (DSC), whereas chemical characterization was performed using Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). Assessment of nutraceutical and nutritional properties of BJ revealed that an increase in jaggery proportion resulted in an increase in total phenolic content (TPC) and total flavonoid content (TFC), where BJ100 showed the highest TPC and TFC of 2.58 mg GAE/g and 1.08 mg QE/g, respectively. The increase in the polyphenols in BJ correlated positively with the antioxidant activities evaluated through DPPH, FRAP, and ABTS assays. Lastly, the proximate analysis of BJ was carried out for protein, fat, carbohydrates, sugar, and fibre content.

Multi-stage multi-criteria group decision making method based on hierarchical criteria interaction and trust rejection threshold under uncertain preference information

In the face of complex and changeable group decision-making problems, making satisfactory decisions is always difficult, which is deeply affected by information such as different stages, criteria, experts and alternatives. Thus, this study aims to develop an effective multi-stage multi-criteria group decision making (MSMCGDM) method to solve the multi-stage group decision making problems with various information. Firstly, through the introduction of trust rejection threshold, a Cross Calibration method is proposed to calculate experts' weights, considering the social influence of experts in the same stage as well as different stages. Then, based on the extend DEMATEL and Shapley approaches, the DE-Shapley method is constructed to obtain criteria weights considering the hierarchical criteria interaction according to the evaluation information on criteria. Furthermore, inspired by the adjacency matrix, the relationship matrix on alternatives and the concept of alternative sets are proposed to consider the acceptability of alternatives in different stages. Afterwards, elastic mechanism in proposed framework is put forward to deal with the unexpected situations when implementing the optimal alternative set. Finally, two scenarios on snowmelt flood are presented to demonstrate the application of the proposed method, sensitive analysis and comparative analyses are conducted to highlight the advantages of our proposed method.

Rejection thresholds for sweetness reduction in a model drink predict dietary sugar intake

Links between individual sweetness perception and sugar intake have been previously explored, with highly contrasting results. The current study aims to test individual-based rejection thresholds (RjTs) to ascending and descending sucrose concentrations in a model drink, and to evaluate potential links between these measures and sugar intake behaviour in real life. Sixty-three participants (final N = 43 [f = 29]; 20 ± 5 years) each undertook three sensory testing sessions and completed a 4-day weighed food records. Each individual was tested for their Sweet Liker status, detection thresholds to sucrose, RjTs to 5 descending and 5 ascending sucrose concentrations in an orange-flavoured drink, as well as sugar intake in daily diet and from sweetened beverages. The results demonstrate that RjTs can be estimated an individual level. With each participant completing 4 replications of the RjT task, data from over 88% of participants produced a reasonable individual-based psychometric function. Intriguingly, descending, but not ascending, RjTs were positively correlated with sweet liking (r = 0.43, p < 0.01), and acted as a significant predictor of both overall dietary sugar intakes (R2 = 0.10, F(4,38) = 2.23, p = 0.050) and sugar intakes from sweetened beverages (R2 = 0.21, F(4,38) = 3.73, p = 0.012). While sweet likers (SL) and dislikers (SD) had comparable ascending RjTs (acceptance for sugar addition), they differed substantially in terms of descending RjTs (p = 0.002; acceptance for sugar reduction), with SL rejecting samples having > 47% sugar reduction (47 g/L), whereas SD rejecting samples with > 68% reduction (28 g/L). Overall, these findings suggest that descending RjTs is a useful measure for detecting a sensory-diet relationship, and should be considered to better inform sugar reduction targets and facilitate policies on product reformulation.

Information on sodium reduction modifies how much sodium chloride level can be reduced without affecting the sensory acceptance of salty crackers

AbstractThe information present on packages of low‐sodium food can affect the different segment consumers' sensory and affective perceptions. The objective of the study was to investigate to which extent the package information on the reduction of sodium can reduce acceptance (compromised acceptance threshold—CAT) or cause rejection (hedonic rejection threshold—HRT) in different segments of salty crackers consumers. Consumers were segmented into little, medium, and great health concerns (GHC) using the Health Consciousness Scale, but only the two last groups were studied. Three trials were conducted: blind trial, with no information about the product; trial “Love your life!,” with package bringing information about sodium reduction, traffic light alerts and additional information “Love your life!”; and the trial “Great flavor,” with package similar to the previous trial, but with the additional information “Great flavor.” The hedonic thresholds were determined for each trial and for the medium and great health concern segments. Package information on the sodium reduction had no influence on CAT and HRT values for consumers expressing medium health concerns. However, the additional sentence “Great flavor” negatively influenced the CAT values of this segment. For consumers expressing GHC, the presence of the package allowed a more significant sodium chloride reduction without affecting the cracker sensory acceptance. For this segment, the package with the additional sentence “Great flavor” had the most significant favorable influence on the results. Therefore, for most of the population, food industries need not be afraid to report on the reduction of sodium on food labels.Practical applicationsHedonic threshold values are very useful for industries that intend to reduce the sodium CAT and without HRT of their products. In addition, the results of this study can help industries in the process of package development for low‐sodium products, allowing a more significant reduction of this ingredient without compromising the product's sensory acceptance or without resulting in rejection. Furthermore, it was demonstrated that there is adequate communication, regardless of whether the consumer segment has medium or GHC.

Analysis of Artifactual Components Rejection Threshold towards Enhanced Characterization of Neural Activity in Post-Stroke Survivor.

Research advancement has spurred the usage of electroencephalography (EEG)-based neural oscillatory rhythms as a biomarker to complement clinical rehabilitation strategies for the recovery of motor functions in stroke survivors. However, the inevitable contamination of EEG signals with artifacts from various sources limits its utilization and effectiveness. Thus, the integration of Independent Component Analysis (ICA) and Independent Component Label (ICLabel) has been widely employed to separate neural activity from artifacts. A crucial step in the ICLabel preprocessing pipeline is the artifactual ICs rejection threshold (TH) parameter, which determines the overall signal's quality. For instance, selecting a high TH will cause many ICs to be rejected, thereby leading to signal over-cleaning, and choosing a low TH may result in under-cleaning of the signal. Toward determining the optimal TH parameter, this study investigates the effect of six different TH groups (NO-TH and TH1-TH6) on EEG signals recorded from post-stroke patients who performed four distinct motor imagery (MI) tasks including wrist and grasping movements. Utilizing the EEG-beta band signal at the brain's sensorimotor cortex, the performance of the TH groups was evaluated using three notable EEG quantifiers. Overall, the obtained result shows that the considered THs will significantly alter neural oscillatory patterns. Comparing the performance of the TH-groups, TH-3 with a confidence level of 60% showed consistently stronger signal desynchronization and lateralization. The correlation result shows that most of the electrode pairs with high correlation values are replicable across all the MI tasks. It also revealed that brain activity correlates linearly with distance, and a strong correlation between electrode pairs is independent of the different brain cortices. The study outcome may facilitate adequate therapeutic intervention for stroke rehab.Clinical Relevance: This study indicated that optimal selection of the ICLabel artifactual rejection threshold is essential for EEG enhancement for adequate signal characterization. Thus, a TH-values with a confidence level between 50% - 70% would be suggested for artifactual ICs rejection in MI-EEG.

Change in fat skatole and indole content in lambs switched from a concentrate-based diet indoors to alfalfa grazing for various durations before slaughter

Meat from lambs fattened on alfalfa is at risk of excessive pastoral flavours due to high levels of in-fat volatile indolic compounds (especially, skatole). Skatole has also been identified as a potential marker of interest for authenticating pasture-fed lamb meat. Here, we investigated the change in skatole and indole concentrations in kidney fat from lambs switched from an indoor-fed concentrate based diet to outdoor alfalfa grazing for various durations (0, 21, 42, 63 days) before slaughter. The study used a total of 219 lambs over 3 consecutive years. Kidney-fat skatole and indole concentrations increased from as early as 21 days on alfalfa, and then reached a plateau. Similarly, the proportion of lambs that had a kidney fat-skatole concentration above 0.15 μg/g liquid fat, a value that has been established as a sensory rejection threshold for pork, increased significantly from as early as 21 days on alfalfa and then reached a plateau. This value was reached or exceeded in a significant proportion of lambs fattened on alfalfa pastures (45.1%). However, skatole was not detected in kidney fat from 20 out of 164 alfalfa-fattened lambs (i.e., 12.2%) but was detected in 15 out of 55 concentrate-fed lambs (i.e., 27.3%). We thus conclude that while skatole content in kidney fat can inform on dietary changes made shortly before slaughter, it does not have the discrimination power needed to reliably authenticate pasture-fed lamb meat, let alone duration of finishing on pasture.