Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of chitosan on physicochemical and rheological attributes of bread

The aim of this study was to develop fiber-enriched functional bread containing selected concentration of chitosan (0.1%, 0.5%, 1%, 1.5%, and 2% w/w). Dynamic rheology of bread dough established that viscous moduli were lower than elastic moduli. Until 1% chitosan concentration, dough extensibility increased. Avrami nonlinear regression equation was selected as a convenient mathematical tool to model bread crumb staling kinetics. Scanning electron microscopy, Fourier-transform infrared, differential scanning calorimetry, and extensibility tests were used to examine the changes of the structure of control dough and chitosan containing dough. Specific volume of bread was inversely proportional to firmness of bread. Firmness is directly proportional function of storage time and chitosan quantity. Sensory evaluation revealed that 1% chitosan can be used as potential functional ingredient to prevent chronic diseases like obesity, type 2 diabetes, constipation, and colon cancer.
Long-term treatment effect in cerebrotendinous xanthomatosis depends on age at treatment start

Objective To evaluate the effect of chenodeoxycholic acid treatment on disease progression in cerebrotendinous xanthomatosis (CTX). Methods In this retrospective cohort study, we report the clinical long-term follow-up characteristics of 56 Dutch patients with CTX. Age at diagnosis was correlated with clinical characteristics and with the course of modified Rankin Scale (mRS) and Expanded Disability Status Scale (EDSS) scores at follow-up. Results Median follow-up time was 8 years (6 months–31.5 years). Patients diagnosed and treated before the age of 24 years had a significantly better outcome at follow-up. When considering only patients with a good treatment adherence (n = 43), neurologic symptoms, if present, disappeared in all patients who were diagnosed before the age of 24 and treated since. Furthermore, treatment prevented the development of new neurologic symptoms during follow-up. In contrast, 61% of the patients diagnosed and treated after the age of 24 showed deterioration of the neurologic symptoms, with parkinsonism as a treatment-resistant feature. There was an improvement or stabilization in favor of patients diagnosed and treated before the age of 24 compared to those treated after the age of 24: 100% vs 58% for mRS scores and 100% vs 50% for EDSS scores, respectively. Conclusions Treatment start at an early age can reverse and even prevent the development of neurologic symptoms in CTX. This study emphasizes the importance of early diagnosis in CTX and provides a rationale to include CTX in newborn screening programs.
On the Curved Geometry of Accelerated Optimization

In this work we propose a differential geometric motivation for Nesterov's accelerated gradient method (AGM) for strongly-convex problems. By considering the optimization procedure as occurring on a Riemannian manifold with a natural structure, The AGM method can be seen as the proximal point method applied in this curved space. This viewpoint can also be extended to the continuous time case, where the accelerated gradient method arises from the natural block-implicit Euler discretization of an ODE on the manifold. We provide an analysis of the convergence rate of this ODE for quadratic objectives.
Approaching the adiabatic timescale with machine learning

Significance Engineering the fast evolution of a quantum system between states is a key problem to be solved in the development of quantum technologies, such as quantum computing. We experimentally demonstrate a general approach using a machine-learning algorithm that develops a model of the system, based on previous performance, to create further educated guesses on how to improve. Applied to a system similar to moving a cup of liquid between two locations (while blindfolded), the algorithm reaches a speed faster than that of previous approaches, dealing well with the complex dynamics and experimental imperfections present with its empirical approach. The resulting fast dynamics open the door to understanding how quantum mechanical systems reach equilibrium while the method provides a tool for taming complex quantum systems. The control and manipulation of quantum systems without excitation are challenging, due to the complexities in fully modeling such systems accurately and the difficulties in controlling these inherently fragile systems experimentally. For example, while protocols to decompress Bose–Einstein condensates (BECs) faster than the adiabatic timescale (without excitation or loss) have been well developed theoretically, experimental implementations of these protocols have yet to reach speeds faster than the adiabatic timescale. In this work, we experimentally demonstrate an alternative approach based on a machine-learning algorithm which makes progress toward this goal. The algorithm is given control of the coupled decompression and transport of a metastable helium condensate, with its performance determined after each experimental iteration by measuring the excitations of the resultant BEC. After each iteration the algorithm adjusts its internal model of the system to create an improved control output for the next iteration. Given sufficient control over the decompression, the algorithm converges to a solution that sets the current speed record in relation to the adiabatic timescale, beating out other experimental realizations based on theoretical approaches. This method presents a feasible approach for implementing fast-state preparations or transformations in other quantum systems, without requiring a solution to a theoretical model of the system. Implications for fundamental physics and cooling are discussed.
Head models of healthy and depressed adults for simulating the electric fields of non-invasive electric brain

During the past decade, it became clear that the electric field elicited by non-invasive brain stimulation (NIBS) techniques such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS) are substantially influenced by variations in individual head and brain anatomy. In addition to structural variations in the healthy, several psychiatric disorders are characterized by anatomical alterations that are likely to further constrain the intracerebral effects of NIBS. Here, we present high-resolution realistic head models derived from structural magnetic resonance imaging data of 19 healthy adults and 19 patients diagnosed with major depressive disorder (MDD). By using a freely available software package for modelling the electric fields induced by different NIBS protocols, we show that our head models are well-suited for assessing inter-individual and between-group variability in the magnitude and focality of tDCS-induced electric fields for two protocols targeting the left dorsolateral prefrontal cortex.
Rare copy number variants in the genome of Chinese female children and adolescents with Turner syndrome

Turner syndrome (TS) is a congenital disease caused by complete or partial loss of one X chromosome. Low bone mineral status is a major phenotypic characteristic of TS that can not be fully explained by X chromosome loss, suggesting other autosomal-linked mutations may also exist. Therefore, the present study aimed to detect potential genetic mutations in TS through examination of copy number variation (CNV). Seventeen patients with TS and 15 healthy volunteer girls were recruited. Array-based comparative genomic hybridization (a-CGH) was performed on whole blood genomic DNA (gDMA) from the 17 TS patients and 15 healthy volunteer girls to identify potential CNVs. The abnormal CNV of one identified gene (CARD11) was verified by quantitative PCR. All cases diagnosed had TS based on genotype examination and physical characteristics, including short stature and premature ovarian failure. Three rare CNVs, located individually at 7p22.3, 7p22.2, and Xp22.33, where six genes (TTYH3, AMZ1, GNA12, BC038729, CARD11, and SHOX (stature homeobox)) are located, were found in TS patients. Quantitative PCR confirmed the CNV of CARD11 in the genome of TS patients. Our results indicate that CARD11 gene is one of the mutated genes involved in TS disease. However, this CNV is rare and its contribution to TS phenotype requires further study.
sTLR4/sMD-2 complex alleviates LPS-induced acute lung injury by inhibiting pro-inflammatory cytokines and chemokine CXCL1 expression

Activation of Toll-like receptor 4 (TLR4) and its accessory proteins myeloid differentiation protein 2 (MD-2) can trigger immune and inflammatory activities, and contribute to developing chronic inflammatory diseases. The formation of the TLR4/MD-2 complex after binding to lipopolysaccharide (LPS) leads to the activation of downstream signaling pathway. The present study was designed to reveal the effect of the soluble form of the extracellular TLR4 domain and MD-2 (sTLR4/sMD-2) complex lacking the intracellular and transmembrane domains on various aspects of LPS-induced inflammation in vivo and in vitro. It was demonstrated that the sTLR4/sMD-2 complex inhibited the LPS-induced production of tumor necrosis factor-α, interleukin-8 and C-X-C motif chemokine ligand 1 (CXCL1) in THP-1 cells. In addition, it was revealed that the sTLR4/sMD-2 complex significantly reduced LPS-induced acute lung injury (ALI) with a reduction of total cells and neutrophil count, pro-inflammatory cytokines and chemokine CXCL1 in bronchoalveolar lavage fluid. Moreover, the sTLR4/sMD-2 complex inhibited the number of inflammatory cells in the lung of treated animals. These novel mechanisms emphasized the important role of sTLR4/sMD-2 complex in ALI and suggested sTLR4/sMD-2 complex could provide an anti-inflammatory strategy for treating inflammatory diseases.
CD226 regulates natural killer cell antitumor responses via phosphorylation-mediated inactivation of transcription factor FOXO1

Significance CD226 is an important activating receptor involved in mediating natural killer (NK) cell responses against tumors, but how CD226 exerts control over NK cell function is not fully understood. CD226 belongs to the poliovirus receptor (PVR)-nectin family that includes TIGIT and CD96, with TIGIT garnering much attention as a key checkpoint in T cell and NK cell antitumor responses and as an immunotherapy target. Thus, it is imperative to determine how CD226 counteracts the actions of TIGIT and CD96 with which it competes for binding to its ligands such as CD155 (PVR). We demonstrate that CD226 engagement of CD155 is required for phosphorylation of transcription factor FOXO1, resulting in inactivation of its negative regulatory control over NK cell effector function. Natural killer (NK) cell recognition of tumor cells is mediated through activating receptors such as CD226, with suppression of effector functions often controlled by negative regulatory transcription factors such as FOXO1. Here we show that CD226 regulation of NK cell cytotoxicity is facilitated through inactivation of FOXO1. Gene-expression analysis of NK cells isolated from syngeneic tumors grown in wild-type or CD226-deficient mice revealed dysregulated expression of FOXO1-regulated genes in the absence of CD226. In vitro cytotoxicity and stimulation assays demonstrated that CD226 is required for optimal killing of tumor target cells, with engagement of its ligand CD155 resulting in phosphorylation of FOXO1. CD226 deficiency or anti-CD226 antibody blockade impaired cytotoxicity with concomitant compromised inactivation of FOXO1. Furthermore, inhibitors of FOXO1 phosphorylation abrogated CD226-mediated signaling and effector responses. These results define a pathway by which CD226 exerts control of NK cell responses against tumors.
Experimental Comparison of Hardware-Amenable Spike Detection Algorithms for iBMIs

This paper presents an experiment based comparison of absolute threshold (AT) and non-linear energy operator (NEO) spike detection algorithms in intra-cortical Brain Machine Interfaces (iBMIs). Results show an average increase in decoding performance of ≈5% in monkey A across 28 sessions recorded over 6 days and ≈2% in monkey B across 35 sessions recorded over 8 days when using NEO over AT. To the best of our knowledge, this is the first ever reported comparison of spike detection algorithms in an iBMI experimental framework involving two monkeys. Based on the improvements observed in an experimental setting backed by previously reported improvements in simulation studies, we advocate switching from state of the art spike detection technique - AT to NEO.
In-Out-Test: A New Paradigm for Sorting the Wheat from the Chaff in Prodromal Alzheimer’s Disease

Background: Assessment of hippocampal amnesia is helpful to distinguish between normal cognition and mild cognitive impairment (MCI), but not for identifying converters to dementia. Here biomarkers are useful but novel neuropsychological approaches are needed in their absence. The In-out-test assesses episodic memory using a new paradigm hypothesized to avoid reliance on executive function, which may compensate for damaged memory networks. Objective: To assess the validity of the In-out-test in identifying prodromal Alzheimer’s disease (PAD) in a clinical setting, by comparing this to the Free and Cued Selective Reminding Test (FCSRT) and cerebrospinal fluid biomarkers. Methods: A cross-sectional study of 32 cognitively healthy, 32 MCI, and 30 progressive dementia subjects. All participants were given both the In-out-test and the FCSRT; 40 of them also received a lumbar puncture. Results: Internal consistency was demonstrated using Cronbach Alpha (r = 0.81) and Inter-rater reliability with Kappa (k = 0.94). Intraclass correlation (ICC) for test-retest reliability: r = 0.57 (p = 0.57). ICC between the In-out-test and FCSRT r = 0.87 (p = 0.001). ICC between the In-out-test and Aβ42 and P-tau/Aβ42 for controls: 0.73 and 0.75, respectively; P-tau for MCI: 0.77 and total sample: 0.70; Aβ42 for dementia: 0.71. All ICC measures between FCSRT and biomarkers were ≤0.264. AD diagnosis: In-out-test k = 0.71; FCSRT k = 0.49. PAD diagnosis (N = 35): In-out-test k = 0.69; FCSRT k = 0.44. Conclusions: The In-out-test detected prodromal AD with a higher degree of accuracy than a conventional hippocampal-based memory test. These results suggest that this new paradigm could be of value in clinical settings, predicting which patients with MCI will go on to develop AD.
Hard Decisions Shape the Neural Coding of Preferences

Hard decisions between equally valued alternatives can result in preference changes, meaning that subsequent valuations for chosen items increase and decrease for rejected items. Previous research suggests that this phenomenon is a consequence of cognitive dissonance reduction after the decision, induced by the mismatch between initial preferences and decision outcomes. In contrast, this functional magnetic resonance imaging and eye-tracking study with male and female human participants found that preferences are already updated online during the process of decision-making. Preference changes were predicted from activity in left dorsolateral prefrontal cortex and precuneus while making hard decisions. Fixation durations during this phase predicted both choice outcomes and subsequent preference changes. These preference adjustments became behaviorally relevant only for choices that were remembered and were in turn associated with hippocampus activity. Our results suggest that preferences evolve dynamically as decisions arise, potentially as a mechanism to prevent stalemate situations in underdetermined decision scenarios. SIGNIFICANCE STATEMENT Most theories of decision-making assume that we always choose the best option available, based on a set of stable preferences. However, what happens for hard decisions when the available options are preferred equally? We show that in such stalemate situations, decision-makers adjust their preferences dynamically during the process of decision-making, and these preference adjustments are predicted by a left prefrontal-parietal network. We also show that eye movements during decision-making are predictive of the magnitude of the upcoming value change. Our results suggest that preferences are dynamic, adjusted every time a hard decision is made, prompting a re-evaluation of existing frameworks of decision-making.
A well-controlled BioID design for endogenous bait proteins

The CRISPR/Cas9 revolution is profoundly changing the way life sciences technologies are used. Many assays now rely on engineered clonal cell lines to eliminate overexpression of bait proteins. Control cell lines are typically non-engineered cells or engineered clones implying a considerable risk for artefacts because of clonal variation. Genome engineering can also transform BioID, a proximity labelling method that relies on fusing a bait protein to a promiscuous biotin ligase, BirA*, resulting in the tagging of vicinal proteins. We here propose an innovative design to enable BioID for endogenous proteins wherein we introduce a T2A-BirA* module at the C-terminus of endogenous p53 by genome engineering, leading to bi-cistronic expression of both p53 and BirA* under control of the endogenous promoter. By targeting a Cas9-cytidine deaminase base editor to the T2A auto-cleavage site, we can efficiently derive an isogenic population expressing a functional p53-BirA* fusion protein. Using quantitative proteomics we show significant benefits over classical ectopic expression of p53-BirA*, and we provide a first well-controlled view on the proximal proteins of endogenous p53 in colon carcinoma cells. This novel application for base editors expands the CRISPR/Cas9 toolbox and can be a valuable addition for synthetic biology.
Mindfulness Training & Assessment and Intelligence

Three key attentional mechanisms, attentional orienting (curiosity, openness and acceptance), engaging attention and sustaining-monitoring attention are the core skills on-target in any mindfulness-based program. Mindfulness skills are inherently related to top-down processes, such as awareness and reflection as well as bottom-up processes, such as emotional reappraisal, thus they can improve one’s cognitive and emotional regulation. Practitioners become more responsive, calm, and focused while experiencing less stress and distractions. Furthermore, mindfulness has been proven to foster stress resilience and create a great sense of interconnectedness so that it diminishes one’s possible involvement in impulsive behaviors. In addition, these techniques have multiple applications in modern medicine, working environments and school psychology, supported by ICTs to enhance practioners’ health status. Research can be focused on practioners’ mindfulness skills training and assessment through smartphones as a cost-effective and usable, every day treatment.
Application of human pluripotent stem cells and pluripotent stem cell-derived cellular models for assessing drug toxicity

ABSTRACT Introduction: Human pluripotent stem cells (hPSCs) are capable of differentiating into all types of cells in the body and so provide suitable toxicology screening systems even for hard-to-obtain human tissues. Since hPSCs can also be generated from differentiated cells and current gene editing technologies allow targeted genome modifications, hPSCs can be applied for drug toxicity screening both in normal and disease-specific models. Targeted hPSC differentiation is still a challenge but cardiac, neuronal or liver cells, and complex cellular models are already available for practical applications. Areas covered: The authors review new gene-editing and cell-biology technologies to generate sensitive toxicity screening systems based on hPSCs. Then the authors present the use of undifferentiated hPSCs for examining embryonic toxicity and discuss drug screening possibilities in hPSC-derived models. The authors focus on the application of human cardiomyocytes, hepatocytes, and neural cultures in toxicity testing, and discuss the recent possibilities for drug screening in a ‘body-on-a-chip’ model system. Expert opinion: hPSCs and their genetically engineered derivatives provide new possibilities to investigate drug toxicity in human tissues. The key issues in this regard are still the selection and generation of proper model systems, and the interpretation of the results in understanding in vivo drug effects.
Understanding Protein Networks Using Vester's Sensitivity Model

Magnesium-based biomaterials belong to the third generation of biomaterials that are also bioactive. These smart materials combine bioactivity and biodegradability, and elicit specific cellular responses at the molecular level. In fact, osteoinductive properties have been observed in mesenchymal stem cells in the presence of Magnesium. The mechanistic understanding of the physiological effects however, remains a difficult task as Mg is involved in a multitude of biological reactions. The study of protein interactions may shed light on the molecular processes in Mg-stimulated cells, therefore, suitable data mining tools are required to analyze the large amount data generated via proteomics. Protein compositions over time between two conditions (human mesenchymal stem cells cultured with and without Mg degradation products) were analyzed using Vester's Sensitivity Model. Proteins whose dynamics significantly change from one setup to the other were classified into four categories: passive, active, critical, and buffering according to their regulatory activity. In this work, we demonstrated the use of Vester's Sensitivity Model as an appropriate data mining tool. Protein network analyses highlighted the primary role of Mg-based implant degradation on cell metabolism without deleterious effect on cell viability. Furthermore, key proteins involved in calcium-dependant cellular activities were emphasized leading to further studies.
Screening and verification of genes associated with leaf angle and leaf orientation value in inbred maize lines

Leaf angle and leaf orientation value are important traits affecting planting density and photosynthetic efficiency. To identify the genes involved in controlling leaf angle and leaf orientation value, we utilized 1.49×106 single nucleotide polymorphism (SNP) markers obtained after sequencing 80 backbone inbred maize lines in Jilin Province, based on phenotype data from two years, and analyzed these two traits in a genome-wide association study (GWAS). A total of 33 SNPs were significantly associated (P<0.000001) with the two target traits. Twenty-two SNPs were significantly associated with leaf angle and distributed on chromosomes 1, 3, 4, 5, 6, 7, 8, and 9, explaining 21.62% of the phenotypic variation. Eleven SNPs were significantly associated with leaf orientation value and distributed on chromosomes 1, 3, 4, 5, 6, 7, and 9, explaining 29.63% of the phenotypic variation. Within the mean linkage disequilibrium (LD) distance of 9.7 kb for the significant SNP locus, 22 leaf angle candidate genes were detected, and 3 of these candidate genes harbored significant SNPs, with phenotype contribution rates greater than 10%. Two candidate genes at distances less than 100 bp from significant SNPs showed phenotype contribution rates greater than 8%. Seven leaf orientation value candidate genes were detected: 3 of these candidate genes harbored significant SNPs, with phenotype contribution rates greater than 10%. Eight inbred maize lines with significant differences in leaf angle and leaf orientation value were selected to test candidate gene expression levels from 182 recombinant inbred lines (RILs). The 5 leaf angle candidate genes and 3 leaf orientation value candidate genes were verified using quantitative real-time PCR (qRT-PCR). The results showed significant differences in the expression levels of the above eight genes between inbred maize lines with significant differences in leaf angle and leaf orientation value.