Miracle-dz/UniFAR-FTUs huggingface dataset:
Pasting and Dough Rheological Properties of Ackee (Blighia sapida) Aril Flour: A Contribution to the Search for Wheat Flour Substitutes

Wheat is one of the most widely used cereals in the world. However, studies consider wheat flour doughs to be of low nutritional quality, as there is now greater public awareness of celiac disease and gluten intolerance. Therefore, consumers are demanding healthier and more varied food products. Consequently, wheat flour is being replaced fully or partially by flours from other sources with higher quality. Hence, the main objective of this work was to report the effect of blending wheat flour with ackee aril flour, until the total replacement of wheat flour, on pasting and dough rheological properties. Five different levels of blending were analyzed: wheat to ackee aril flour mass ratios of 100 : 0, 75 : 25, 50 : 50, 25 : 75, and 0 : 100. Pasting properties (pasting temperature, peak viscosity, ease of cooking, swelling power, final viscosity at 50 °C, and thixotropy) were analyzed; and steady-state shear measurements were used to obtain consistency coefficients (K) and flow behavior indexes (n) after data was fitted to the Power Law and Herschel-Bulkley models. The gradual addition of the ackee aril flour fraction produced an increase in ash, fat, protein, and fiber content; while water and carbohydrate content showed the opposite behavior in the obtained composite flour. Consequently, the partial or full replacement of wheat flour changed the rheological properties of the produced doughs, as well as the quality of the final product. These changes were mostly related to the protein and carbohydrate content of the ackee aril flour fraction. In general, doughs showed a pseudoplastic behavior with thixotropy whose viscosity decreased as the addition of ackee aril flour was increased. Pasting properties of blends involving 25 %-75 % ackee aril flour demonstrate the feasibility of including these flours in products subjected to high processing temperatures such as canned products or even to produce chips and pasta.
Regulation and mechanism of YAP/TAZ in the mechanical microenvironment of stem cells

Stem cells receive cues from their physical and mechanical microenvironment via mechanosensing and mechanotransduction. These cues affect proliferation, self-renewal and differentiation into specific cell fates. A growing body of evidence suggests that yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) mechanotransduction is key for driving stem cell behavior and regeneration via the Hippo and other signaling pathways. YAP/TAZ receive a range of physical cues, including extracellular matrix stiffness, cell geometry, flow shear stress and mechanical forces in the cytoskeleton, and translate them into cell-specific transcriptional programs. However, the mechanism by which mechanical signals regulate YAP/TAZ activity in stem cells is not fully understand. The present review summarizes the current knowledge of the mechanisms involved in YAP/TAZ regulation on the physical and mechanical microenvironment, as well as its potential effects on stem cell differentiation.
Autogenous Mineralized Dentin versus Xenograft granules in Ridge Preservation for Delayed Implantation in Postextraction Sites: A Randomized controlled clinical trial with an 18 months follow-up.

OBJECTIVES To test primary stability of delayed implants placed in post-extraction ridges preserved with autogenous mineralized dentin matrix (MDM) versus xenograft granules. Clinical, histological and pain experience outcomes were further assessed. MATERIAL AND METHODS From March 2018 to July 2020, patients requiring ridge preservation in preparation for delayed implant placement in post-extraction sites were included. Participants were randomly allocated to either the test (MDM) or control group (xenograft granules) prior to ridge preservation. Visual analogue scale and analgesic consumption were measured every day for a week. Six months after preservation trephine cores were harvested for histomorphometry prior to implant placement. Implants were then placed and implant stability was measured immediately as well as two months after placement. Marginal bone loss, and presence of mucositis/peri-implantitis were registered up to 18 months after prosthetic loading. RESULTS Fifty-two patients (66 implants) completed the study. MDM and xenograft groups presented similar primary (77.1 ± 6.9 vs. 77.0 vs. 5.9) and secondary (81.8 ± 5.1 vs. 80.1 ± 3.8) implant stabilities. The percentage of newly formed bone in MDM (47.3%) was significantly higher than xenograft (34.9%) (p<0.001), and the proportion of residual graft was significantly lower (12.2% in MDM and 22.1% in xenograft) (p<0.001). No significant differences were found as far as clinical, radiographic and patient-related outcomes. CONCLUSIONS Implants placed in sites preserved with MDM had similar primary stability in comparison to xenograft granules. MDM showed a significantly higher quantity of newly formed bone and lower amount of residual graft in histomorphometry results and equal clinical and patient-related outcomes.
Surface Electromyography-Based Recognition, Synthesis, and Perception of Prosodic Subvocal Speech.

Purpose This study aimed to evaluate a novel communication system designed to translate surface electromyographic (sEMG) signals from articulatory muscles into speech using a personalized, digital voice. The system was evaluated for word recognition, prosodic classification, and listener perception of synthesized speech. Method sEMG signals were recorded from the face and neck as speakers with (n = 4) and without (n = 4) laryngectomy subvocally recited (silently mouthed) a speech corpus comprising 750 phrases (150 phrases with variable phrase-level stress). Corpus tokens were then translated into speech via personalized voice synthesis (n = 8 synthetic voices) and compared against phrases produced by each speaker when using their typical mode of communication (n = 4 natural voices, n = 4 electrolaryngeal [EL] voices). Naïve listeners (n = 12) evaluated synthetic, natural, and EL speech for acceptability and intelligibility in a visual sort-and-rate task, as well as phrasal stress discriminability via a classification mechanism. Results Recorded sEMG signals were processed to translate sEMG muscle activity into lexical content and categorize variations in phrase-level stress, achieving a mean accuracy of 96.3% (SD = 3.10%) and 91.2% (SD = 4.46%), respectively. Synthetic speech was significantly higher in acceptability and intelligibility than EL speech, also leading to greater phrasal stress classification accuracy, whereas natural speech was rated as the most acceptable and intelligible, with the greatest phrasal stress classification accuracy. Conclusion This proof-of-concept study establishes the feasibility of using subvocal sEMG-based alternative communication not only for lexical recognition but also for prosodic communication in healthy individuals, as well as those living with vocal impairments and residual articulatory function. Supplemental Material https://doi.org/10.23641/asha.14558481.
An automated computational image analysis pipeline for histological grading of cardiac allograft rejection

Abstract Aim Allograft rejection is a serious concern in heart transplant medicine. Though endomyocardial biopsy with histological grading is the diagnostic standard for rejection, poor inter-pathologist agreement creates significant clinical uncertainty. The aim of this investigation is to demonstrate that cellular rejection grades generated via computational histological analysis are on-par with those provided by expert pathologists Methods and results The study cohort consisted of 2472 endomyocardial biopsy slides originating from three major US transplant centres. The ‘Computer-Assisted Cardiac Histologic Evaluation (CACHE)-Grader’ pipeline was trained using an interpretable, biologically inspired, ‘hand-crafted’ feature extraction approach. From a menu of 154 quantitative histological features relating the density and orientation of lymphocytes, myocytes, and stroma, a model was developed to reproduce the 4-grade clinical standard for cellular rejection diagnosis. CACHE-grader interpretations were compared with independent pathologists and the ‘grade of record’, testing for non-inferiority (δ = 6%). Study pathologists achieved a 60.7% agreement [95% confidence interval (CI): 55.2–66.0%] with the grade of record, and pair-wise agreement among all human graders was 61.5% (95% CI: 57.0–65.8%). The CACHE-Grader met the threshold for non-inferiority, achieving a 65.9% agreement (95% CI: 63.4–68.3%) with the grade of record and a 62.6% agreement (95% CI: 60.3–64.8%) with all human graders. The CACHE-Grader demonstrated nearly identical performance in internal and external validation sets (66.1% vs. 65.8%), resilience to inter-centre variations in tissue processing/digitization, and superior sensitivity for high-grade rejection (74.4% vs. 39.5%, P < 0.001). Conclusion These results show that the CACHE-grader pipeline, derived using intuitive morphological features, can provide expert-quality rejection grading, performing within the range of inter-grader variability seen among human pathologists.
Personalized fracture risk assessment: where are we at?

ABSTRACT Introduction: Osteoporotic fracture imposes a significant health care burden globally. Personalized assessment of fracture risk can potentially guide treatment decisions. Over the past decade, a number of risk prediction models, including the Garvan Fracture Risk Calculator (Garvan) and FRAX®, have been developed and implemented in clinical practice. Areas covered: This article reviews recent development and validation results concerning the prognostic performance of the two tools. The main areas of review are the need for personalized fracture risk prediction, purposes of risk prediction, predictive performance in terms of discrimination and calibration, concordance between the Garvan and FRAX tools, genetic profiling for improving predictive performance, and treatment thresholds. In some validation studies, FRAX tended to underestimate fracture by as high as 50%. Studies have shown that the predicted risk from the Garvan tool is highly concordant with clinical decision. Expert opinion: Although there are some discrepancy in fracture risk prediction between Garvan and FRAX, both tools are valid and can aid patients and doctors communicate about risk and make informed decision. The ideal of personalized risk assessment for osteoporosis patients will be realized through the incorporation of genetic profiling into existing fracture risk assessment tools.
Evidence for Beneficial Associations between Isoenergetic Macronutrient Exchanges and Serum non-HDL Cholesterol, a Measure of All Circulating Atherogenic, apoB-Containing Lipoproteins

1Department of Nutritional Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, United Kingdom; 2Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading, Berkshire, United Kingdom; and 3Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Sciences, University of Reading, Reading, Berkshire, United Kingdom
Individuals with autism spectrum disorder have altered visual encoding capacity

Perceptual anomalies in individuals with autism spectrum disorder (ASD) have been attributed to an imbalance in weighting incoming sensory evidence with prior knowledge when interpreting sensory information. Here, we show that sensory encoding and how it adapts to changing stimulus statistics during feedback also characteristically differs between neurotypical and ASD groups. In a visual orientation estimation task, we extracted the accuracy of sensory encoding from psychophysical data by using an information theoretic measure. Initially, sensory representations in both groups reflected the statistics of visual orientations in natural scenes, but encoding capacity was overall lower in the ASD group. Exposure to an artificial (i.e., uniform) distribution of visual orientations coupled with performance feedback altered the sensory representations of the neurotypical group toward the novel experimental statistics, while also increasing their total encoding capacity. In contrast, neither total encoding capacity nor its allocation significantly changed in the ASD group. Across both groups, the degree of adaptation was correlated with participants’ initial encoding capacity. These findings highlight substantial deficits in sensory encoding—independent from and potentially in addition to deficits in decoding—in individuals with ASD.
Achieving Breastfeeding Equity and Justice in Black Communities: Past, Present, and Future.

Background: Breastfeeding is protective of maternal and infant health across the life course. Increasing breastfeeding rates in Black communities is an important public health strategy to address maternal and infant mortality and morbidity. Methods: Data trends for the past 10 years suggest that Black-led community efforts; local, state, and national initiatives; and maternity care practices that are supportive of breastfeeding have been effective in improving and increasing breastfeeding rates among Black women. Results: Yet breastfeeding disparities and inequities in Black communities persist. Systemic and structural barriers, such as racism, bias, and inequitable access to lactation resources and support continue to be issues in the United States. Conclusion: Going forward, significant investments are needed to decolonize breastfeeding research and clinical practice. Public health and policy priorities need to center on listening to Black women, and funding Black, Indigenous, and People of Color (BIPOC) organizations and researchers conducting innovative projects and research.
Systematic literature review and network Meta-analysis of sulodexide and other drugs in chronic venous disease

Objective To assess the clinical efficacy of sulodexide, including a comparison with venoactive drugs (VAD) (micronized purified flavonoid fraction, MPFF; hydroxy-ethyl-rutosides, HR; calcium dobesilate;Ruscus extract combined with hesperidin methyl chalcone and vitamin C, Ruscus+HMC+VitC; horse chestnut seed extract, HCSE) and pentoxifylline in patients with chronic venous disease. Methods We performed a literature search in MEDLINE, Embase, and Cochrane Library for randomized controlled trials (RCTs) and observational studies. Proportion of patients with complete venous ulcer healing was the primary outcome and lower leg volume, foot volume, ankle circumference and symptoms were the secondary outcomes. Bayesian network meta-analysis (NMA) was perfomed with random effects models using only RCTs. A meta-analysis of observational studies was performed for sulodexide because no RCT could be included in NMA for symptoms or signs. Results Forty-five RCTs and eighteen observational studies were identified. Sulodexide was included only in a single NMA for the proportion of patients with complete ulcer healing and it showed to have the highest probability of being the best treatment (48%) compared with pentoxifylline (37%) and MPFF (16%). MPFF was the most effective treatment in reducing lower leg volume, CIVIQ-20 score and pain VAS scale while calcium dobesilate and Ruscus+HMC+VitC were the most effective in reducing foot volume and ankle circumference respectively. Meta-analyses of observational studies for sulodexide showed that it improves significantly the scoring of pain, feeling of swelling, heaviness and parasthesiae measured by Likert scales. Conclusions Sulodexide is at least as effective as pentoxifylline and more effective than MPFF in improving the rate of ulcer healing in patients with CVD. VADs are effective in improving venous symptoms and signs, as was also shown by sulodexide in the meta-analysis of observational studies. The relative effectiveness of sulodexide and VADs needs to be evaluated by an RCT in order to better inform clinical practice.
Use of FMF algorithm for prediction of preeclampsia in high risk pregnancies: a single center longitudinal study

ABSTRACT OBJECTIVE: This study aimed to assess the accuracy of The Fetal Medicine Foundation (FMF) screening algorithm for the prediction of preeclampsia. METHODS: Out of 138 women with high-risk pregnancies prospectively followed, 30 developed preeclampsia. The clinical examination and biochemical measurements were performed at first, second, early and late third trimester. RESULTS: A lower PAPP-A levels were found in the first trimester, while sFlt/PlGF was increased in the second and early third trimester in preeclampsia (p>0.05). FMF algorithm presented higher specificity (>70%), but had a drawback of lower sensitivity (35–77%). CONCLUSION: FMF algorithm had modest performance in the prediction of preeclampsia for high-risk pregnancies.
‘They say we are money minded’ exploring experiences of formal private for-profit health providers towards contribution to pro-poor access in post conflict Northern Uganda

ABSTRACT Background: The perception within literature and populace is that the private for-profit sector is for the rich only, and this characteristic results in behaviours that hinder advancement of Universal health coverage (UHC) goals. The context of Northern Uganda presents an opportunity for understanding how the private sector continues to thrive in settings with high poverty levels and history of conflict. Objective: The study aimed at understanding access mechanisms employed by the formal private for-profit providers (FPFPs) to enable pro-poor access to health services in post conflict Northern Uganda. Methods: Data collection was conducted in Gulu municipality in 2015 using Organisational survey of 45 registered formal private for-profit providers (FPFPs),10 life histories, and 13 key informant interviews. Descriptive statistics were generated for the quantitative findings whereas qualitative findings were analysed thematically. Results: FPFPs pragmatically employed various access mechanisms and these included fee exemptions and provision of free services, fee reductions, use of loan books, breaking down doses and partial payments. Most mechanisms were preceded by managers’ subjective identification of the poor, while operationalisation heavily depended on the managers’ availability and trust between the provider and the customer. For a few FPFPs, partnerships with Non-governmental organisations (NGOs) and government enabled provision of free, albeit mainly preventive services, including immunisation, consultations, screening for blood pressure and family planning. Challenges such as quality issues, information asymmetry and standardisation of charges arose during implementation of the mechanisms. Conclusion: The identification of the poor by the FPFPs was subjective and unsystematic. FPFPs implemented various innovations to ensure pro-poor access to health services. However, they face a continuous dilemma of balancing the profit maximization and altruism objectives. Implementation of some pro-poor mechanisms raises concerns included those related to quality and standardisation of pricing.
Cross-Subject Zero Calibration Driver’s Drowsiness Detection: Exploring Spatiotemporal Image Encoding of EEG Signals for Convolutional Neural Network Classification

This paper explores two methodologies for drowsiness detection using EEG signals in a sustained-attention driving task considering pre-event time windows, and focusing on cross-subject zero calibration. Driving accidents are a major cause of injuries and deaths on the road. A considerable portion of those are due to fatigue and drowsiness. Advanced driver assistance systems that could detect mental states which are associated with hazardous situations, such as drowsiness, are of critical importance. EEG signals are used widely for brain-computer interfaces, as well as mental state recognition. However, these systems are still difficult to design due to very low signal-to-noise ratios and cross-subject disparities, requiring individual calibration cycles. To tackle this research domain, here, we explore drowsiness detection based on EEG signals’ spatiotemporal image encoding representations in the form of either recurrence plots or gramian angular fields for deep convolutional neural network (CNN) classification. Results comparing both techniques using a public dataset of 27 subjects show a superior balanced accuracy of up to 75.87% for leave-one-out cross-validation, using both techniques, against works in the literature, demonstrating the possibility to pursue cross-subject zero calibration design.
FDDH: Fast Discriminative Discrete Hashing for Large-Scale Cross-Modal Retrieval

Cross-modal hashing, favored for its effectiveness and efficiency, has received wide attention to facilitating efficient retrieval across different modalities. Nevertheless, most existing methods do not sufficiently exploit the discriminative power of semantic information when learning the hash codes while often involving time-consuming training procedure for handling the large-scale dataset. To tackle these issues, we formulate the learning of similarity-preserving hash codes in terms of orthogonally rotating the semantic data, so as to minimize the quantization loss of mapping such data to hamming space and propose an efficient fast discriminative discrete hashing (FDDH) approach for large-scale cross-modal retrieval. More specifically, FDDH introduces an orthogonal basis to regress the targeted hash codes of training examples to their corresponding semantic labels and utilizes the $\varepsilon $ -dragging technique to provide provable large semantic margins. Accordingly, the discriminative power of semantic information can be explicitly captured and maximized. Moreover, an orthogonal transformation scheme is further proposed to map the nonlinear embedding data into the semantic subspace, which can well guarantee the semantic consistency between the data feature and its semantic representation. Consequently, an efficient closed-form solution is derived for discriminative hash code learning, which is very computationally efficient. In addition, an effective and stable online learning strategy is presented for optimizing modality-specific projection functions, featuring adaptivity to different training sizes and streaming data. The proposed FDDH approach theoretically approximates the bi-Lipschitz continuity, runs sufficiently fast, and also significantly improves the retrieval performance over the state-of-the-art methods. The source code is released at https://github.com/starxliu/FDDH.
Comparative protein structure network analysis on 3CLpro from SARS‐CoV‐1 and SARS‐CoV‐2

The main protease Mpro, 3CLpro is an important target from coronaviruses. In spite of having 96% sequence identity among Mpros from SARS‐CoV‐1 and SARS‐CoV‐2; the inhibitors used to block the activity of SARS‐CoV‐1 Mpro so far, were found to have differential inhibitory effect on Mpro of SARS‐CoV‐2. The possible reason could be due to the difference of few amino acids among the peptidases. Since, overall 3‐D crystallographic structure of Mpro from SARS‐CoV‐1 and SARS‐CoV‐2 is quite similar and mapping a subtle structural variation is seemingly impossible. Hence, we have attempted to study a structural comparison of SARS‐CoV‐1 and SARS‐CoV‐2 Mpro in apo and inhibitor bound states using protein structure network (PSN) based approach at contacts level. The comparative PSNs analysis of apo Mpros from SARS‐CoV‐1 and SARS‐CoV‐2 uncovers small but significant local changes occurring near the active site region and distributed throughout the structure. Additionally, we have shown how inhibitor binding perturbs the PSG and the communication pathways in Mpros. Moreover, we have also investigated the network connectivity on the quaternary structure of Mpro and identified critical residue pairs for complex formation using three centrality measurement parameters along with the modularity analysis. Taken together, these results on the comparative PSN provide an insight into conformational changes that may be used as an additional guidance towards specific drug development.