Rare variants in NR2F2 cause congenital heart defects in humans.

Congenital heart defects (CHDs) are the most common birth defect worldwide and are a leading cause of neonatal mortality. Nonsyndromic atrioventricular septal defects (AVSDs) are an important subtype of CHDs for which the genetic architecture is poorly understood. We performed exome sequencing in 13 parent-offspring trios and 112 unrelated individuals with nonsyndromic AVSDs and identified five rare missense variants (two of which arose de novo) in the highly conserved gene NR2F2, a very significant enrichment (p = 7.7 × 10(-7)) compared to 5,194 control subjects. We identified three additional CHD-affected families with other variants in NR2F2 including a de novo balanced chromosomal translocation, a de novo substitution disrupting a splice donor site, and a 3 bp duplication that cosegregated in a multiplex family. NR2F2 encodes a pleiotropic developmental transcription factor, and decreased dosage of NR2F2 in mice has been shown to result in abnormal development of atrioventricular septa. Via luciferase assays, we showed that all six coding sequence variants observed in individuals significantly alter the activity of NR2F2 on target promoters.

FRA2A is a CGG repeat expansion associated with silencing of AFF3.

Folate-sensitive fragile sites (FSFS) are a rare cytogenetically visible subset of dynamic mutations. Of the eight molecularly characterized FSFS, four are associated with intellectual disability (ID). Cytogenetic expression results from CGG tri-nucleotide-repeat expansion mutation associated with local CpG hypermethylation and transcriptional silencing. The best studied is the FRAXA site in the FMR1 gene, where large expansions cause fragile X syndrome, the most common inherited ID syndrome. Here we studied three families with FRA2A expression at 2q11 associated with a wide spectrum of neurodevelopmental phenotypes. We identified a polymorphic CGG repeat in a conserved, brain-active alternative promoter of the AFF3 gene, an autosomal homolog of the X-linked AFF2/FMR2 gene: Expansion of the AFF2 CGG repeat causes FRAXE ID. We found that FRA2A-expressing individuals have mosaic expansions of the AFF3 CGG repeat in the range of several hundred repeat units. Moreover, bisulfite sequencing and pyrosequencing both suggest AFF3 promoter hypermethylation. cSNP-analysis demonstrates monoallelic expression of the AFF3 gene in FRA2A carriers thus predicting that FRA2A expression results in functional haploinsufficiency for AFF3 at least in a subset of tissues. By whole-mount in situ hybridization the mouse AFF3 ortholog shows strong regional expression in the developing brain, somites and limb buds in 9.5-12.5dpc mouse embryos. Our data suggest that there may be an association between FRA2A and a delay in the acquisition of motor and language skills in the families studied here. However, additional cases are required to firmly establish a causal relationship.

Genome-wide DNA methylation analysis of patients with imprinting disorders identifies differentially methylated regions associated with novel candidate imprinted genes.

BACKGROUND: Genomic imprinting is allelic restriction of gene expression potential depending on parent of origin, maintained by epigenetic mechanisms including parent of origin-specific DNA methylation. Among approximately 70 known imprinted genes are some causing disorders affecting growth, metabolism and cancer predisposition. Some imprinting disorder patients have hypomethylation of several imprinted loci (HIL) throughout the genome and may have atypically severe clinical features. Here we used array analysis in HIL patients to define patterns of aberrant methylation throughout the genome. DESIGN: We developed a novel informatic pipeline capable of small sample number analysis, and profiled 10 HIL patients with two clinical presentations (Beckwith-Wiedemann syndrome and neonatal diabetes) using the Illumina Infinium Human Methylation450 BeadChip array to identify candidate imprinted regions. We used robust statistical criteria to quantify DNA methylation. RESULTS: We detected hypomethylation at known imprinted loci, and 25 further candidate imprinted regions (nine shared between patient groups) including one in the Down syndrome critical region (WRB) and another previously associated with bipolar disorder (PPIEL). Targeted analysis of three candidate regions (NHP2L1, WRB and PPIEL) showed allelic expression, methylation patterns consistent with allelic maternal methylation and frequent hypomethylation among an additional cohort of HIL patients, including six with Silver-Russell syndrome presentations and one with pseudohypoparathyroidism 1B. CONCLUSIONS: This study identified novel candidate imprinted genes, revealed remarkable epigenetic convergence among clinically divergent patients, and highlights the potential of epigenomic profiling to expand our understanding of the normal methylome and its disruption in human disease.

RBFOX2 protein domains and cellular activities.

RBFOX2 (RNA-binding protein, Fox-1 homologue 2)/RBM9 (RNA-binding-motif protein 9)/RTA (repressor of tamoxifen action)/HNRBP2 (hexaribonucleotide-binding protein 2) encodes an RNA-binding protein involved in tissue specific alternative splicing regulation and steroid receptors transcriptional activity. Its ability to regulate specific splicing profiles depending on context has been related to different expression levels of the RBFOX2 protein itself and that of other splicing regulatory proteins involved in the shared modulation of specific genes splicing. However, this cannot be the sole explanation as to why RBFOX2 plays a widespread role in numerous cellular mechanisms from development to cell survival dependent on cell/tissue type. RBFOX2 isoforms with altered protein domains exist. In the present article, we describe the main RBFOX2 protein domains, their importance in the context of splicing and transcriptional regulation and we propose that RBFOX2 isoform distribution may play a fundamental role in RBFOX2-specific cellular effects.

BRCA1 EXON 11, a CERES (composite regulatory element of splicing) element involved in splice regulation.

Unclassified variants (UV) of BRCA1 can affect normal pre-mRNA splicing. Here, we investigate the UV c.693G>A, a "silent" change in BRCA1 exon 11, which we have found induces aberrant splicing in patient carriers and in vitro. Using a minigene assay, we show that the UV c.693G>A has a strong effect on the splicing isoform ratio of BRCA1. Systematic site-directed mutagenesis of the area surrounding the nucleotide position c.693G>A induced variable changes in the level of exon 11 inclusion/exclusion in the mRNA, pointing to the presence of a complex regulatory element with overlapping enhancer and silencer functions. Accordingly, protein binding analysis in the region detected several splicing regulatory factors involved, including SRSF1, SRSF6 and SRSF9, suggesting that this sequence represents a composite regulatory element of splicing (CERES).

Integrating Image Analysis and Machine Learning for Moisture Prediction and Appearance Quality Evaluation: A Case Study of Kiwifruit Drying Pretreatment.

The appearance of dried fruit clearly influences the consumer's perception of the quality of the product but is a subtle and nuanced characteristic that is difficult to quantitatively measure, especially online. This paper describes a method that combines several simple strategies to assess a suitable surrogate for the elusive quality using imaging, combined with multivariate statistics and machine learning. With such a convenient tool, this study also shows how one can vary the pretreatments and drying conditions to optimize the resultant product quality. Specifically, an image batch processing method was developed to extract color (hue, saturation, and value) and morphological (area, perimeter, and compactness) features. The accuracy of this method was verified using data from a case study experiment on the pretreatment of hot-air-dried kiwifruit slices. Based on the extracted image features, partial least squares and random forest models were developed to satisfactorily predict the moisture ratio (MR) during drying process. The MR of kiwifruit slices during drying could be accurately predicted from changes in appearance without using any weighing device. This study also explored determining the optimal drying strategy based on appearance quality using principal component analysis. Optimal drying was achieved at 60 °C with 4 mm thick slices under ultrasonic pretreatment. For the 70 °C, 6 mm sample groups, citric acid showed decent performance.

Lateral entorhinal cortex is necessary for associative but not nonassociative recognition memory.

The lateral entorhinal cortex (LEC) provides one of the two major input pathways to the hippocampus and has been suggested to process the nonspatial contextual details of episodic memory. Combined with spatial information from the medial entorhinal cortex it is hypothesised that this contextual information is used to form an integrated spatially selective, context-specific response in the hippocampus that underlies episodic memory. Recently, we reported that the LEC is required for recognition of objects that have been experienced in a specific context (Wilson et al. (2013) Hippocampus 23:352-366). Here, we sought to extend this work to assess the role of the LEC in recognition of all associative combinations of objects, places and contexts within an episode. Unlike controls, rats with excitotoxic lesions of the LEC showed no evidence of recognizing familiar combinations of object in place, place in context, or object in place and context. However, LEC lesioned rats showed normal recognition of objects and places independently from each other (nonassociative recognition). Together with our previous findings, these data suggest that the LEC is critical for associative recognition memory and may bind together information relating to objects, places, and contexts needed for episodic memory formation.

Lateral entorhinal cortex is critical for novel object-context recognition.

Episodic memory incorporates information about specific events or occasions including spatial locations and the contextual features of the environment in which the event took place. It has been modeled in rats using spontaneous exploration of novel configurations of objects, their locations, and the contexts in which they are presented. While we have a detailed understanding of how spatial location is processed in the brain relatively little is known about where the nonspatial contextual components of episodic memory are processed. Initial experiments measured c-fos expression during an object-context recognition (OCR) task to examine which networks within the brain process contextual features of an event. Increased c-fos expression was found in the lateral entorhinal cortex (LEC; a major hippocampal afferent) during OCR relative to control conditions. In a subsequent experiment it was demonstrated that rats with lesions of LEC were unable to recognize object-context associations yet showed normal object recognition and normal context recognition. These data suggest that contextual features of the environment are integrated with object identity in LEC and demonstrate that recognition of such object-context associations requires the LEC. This is consistent with the suggestion that contextual features of an event are processed in LEC and that this information is combined with spatial information from medial entorhinal cortex to form episodic memory in the hippocampus.

Updating of action-outcome associations is prevented by inactivation of the posterior pedunculopontine tegmental nucleus.

The pedunculopontine tegmental nucleus (PPTg) is in a pivotal position between the basal ganglia and brainstem: it is able to influence and regulate all levels of basal ganglia and corticostriatal activity as well as being a key component of brainstem reticular and motor control circuitry. Consistent with its anatomical position, the PPTg has previously been shown to process rapid, salient sensory input, is a target for Parkinson's disease treatments and has been implicated in associative learning. We explicitly investigated the role of the posterior pPPTg (pPPTg) in action-outcome processes, where actions are performed with the goal-directed aim of obtaining an anticipated outcome. We assessed rats' sensitivity to degradation of the contingency between actions (lever pressing) and outcomes (food reward) during either inactivation of pPPTg by microinjection of the GABA agonist muscimol or control infusions of saline. In response to the degradation of contingency between lever press and food reward, saline treated rats rapidly reduced rates of lever pressing whereas muscimol treated rats (pPPTg inactivation) maintained previous lever pressing rates. In contrast, when the contingency between lever press and food reward was unchanged saline and muscimol treated rats maintained their previous rates of lever pressing. This shows that the pPPTg is critically required for updating associations between actions and outcomes, but not in the continued performance of previously learned associations. These results are consistent with a role for the PPTg in 'higher-order' associative learning and are the first to demonstrate a brainstem role in action-outcome learning.

Mutation of ALMS1, a large gene with a tandem repeat encoding 47 amino acids, causes Alström syndrome.

Alström syndrome (OMIM 203800) is an autosomal recessive disease, characterized by cone-rod retinal dystrophy, cardiomyopathy and type 2 diabetes mellitus, that has been mapped to chromosome 2p13 (refs 1-5). We have studied an individual with Alström syndrome carrying a familial balanced reciprocal chromosome translocation (46, XY,t(2;11)(p13;q21)mat) involving the previously implicated critical region. We postulated that this individual was a compound heterozygote, carrying one copy of a gene disrupted by the translocation and the other copy disrupted by an intragenic mutation. We mapped the 2p13 breakpoint on the maternal allele to a genomic fragment of 1.7 kb which contains exon 4 and the start of exon 5 of a newly discovered gene (ALMS1); we detected a frameshift mutation in the paternal copy of the gene. The 12.9-kb transcript of ALMS1 encodes a protein of 4,169 amino acids whose function is unknown. The protein contains a large tandem-repeat domain comprising 34 imperfect repetitions of 47 amino acids. We have detected six different mutations (two nonsense and four frameshift mutations causing premature stop codons) in seven families, confirming that ALMS1 is the gene underlying Alström syndrome. We believe that ALMS1 is the first human disease gene characterized by autosomal recessive inheritance to be identified as a result of a balanced reciprocal translocation.

Application of Three-Dimensional Digital Photogrammetry to Quantify the Surface Roughness of Milk Powder.

The surface appearance of milk powders is a crucial quality property since the roughness of the milk powder determines its functional properties, and especially the purchaser perception of the milk powder. Unfortunately, powder produced from similar spray dryers, or even the same dryer but in different seasons, produces powder with a wide variety of surface roughness. To date, professional panelists are used to quantify this subtle visual metric, which is time-consuming and subjective. Consequently, developing a fast, robust, and repeatable surface appearance classification method is essential. This study proposes a three-dimensional digital photogrammetry technique for quantifying the surface roughness of milk powders. A contour slice analysis and frequency analysis of the deviations were performed on the three-dimensional models to classify the surface roughness of milk powder samples. The result shows that the contours for smooth-surface samples are more circular than those for rough-surface samples, and the smooth-surface samples had a low standard deviation; thus, milk powder samples with the smoother surface have lower Q (the energy of the signal) values. Lastly, the performance of the nonlinear support vector machine (SVM) model demonstrated that the technique proposed in this study is a practicable alternative technique for classifying the surface roughness of milk powders.

The importance of outlier rejection and significant explanatory variable selection for pinot noir wine soft sensor development.

Sensory attributes are essential factors in determining the quality of wines. However, it can be challenging for consumers, even experts, to differentiate and quantify wines' sensory attributes for quality control. Soft sensors based on rapid chemical analysis offer a potential solution to overcome this challenge. However, the current limitation in developing soft sensors for wines is the need for a significant number of input parameters, at least 12, necessitating costly and time-consuming analyses. While such a comprehensive approach provides high accuracy in sensory quality mapping, the expensive and time-consuming studies required do not lend themselves to the industry's routine quality control activities. In this work, Box plots, Tucker-1 plots, and Principal Component Analysis (PCA) score plots were used to deal with output data (sensory attributes) to improve the model quality. More importantly, this work has identified that the number of analyses required to fully quantify by regression models and qualify by classification models can be significantly reduced. Based on regression models, only four key chemical parameters (total flavanols, total tannins, A520nmHCl, and pH) were required to accurately predict 35 sensory attributes of a wine with R2 values above 0.6 simultaneously. In addition, for classification models to accurately predict 35 sensory attributes of a wine at once with prediction accuracy above 70%, only four key chemical parameters (A280nmHCl, A520nmHCl, chemical age and pH) were required. These models with reduced chemical parameters complement each other in sensory quality mapping and provide acceptable accuracy. The application of the soft sensor based on these reduced sets of key chemical parameters translated to a potential reduction in analytical cost and labour cost of 56% for the regression model and 83% for the classification model, respectively, making these models suitable for routine quality control use.

The Application of Artificial Intelligence and Big Data in the Food Industry.

Over the past few decades, the food industry has undergone revolutionary changes due to the impacts of globalization, technological advancements, and ever-evolving consumer demands. Artificial intelligence (AI) and big data have become pivotal in strengthening food safety, production, and marketing. With the continuous evolution of AI technology and big data analytics, the food industry is poised to embrace further changes and developmental opportunities. An increasing number of food enterprises will leverage AI and big data to enhance product quality, meet consumer needs, and propel the industry toward a more intelligent and sustainable future. This review delves into the applications of AI and big data in the food sector, examining their impacts on production, quality, safety, risk management, and consumer insights. Furthermore, the advent of Industry 4.0 applied to the food industry has brought to the fore technologies such as smart agriculture, robotic farming, drones, 3D printing, and digital twins; the food industry also faces challenges in smart production and sustainable development going forward. This review articulates the current state of AI and big data applications in the food industry, analyses the challenges encountered, and discusses viable solutions. Lastly, it outlines the future development trends in the food industry.

BRCA1 exon 11 alternative splicing, multiple functions and the association with cancer.

BRCA1 (breast cancer early-onset 1) alternative splicing levels are regulated in a cell-cycle- and cell-type-specific manner, with splice variants being present in different proportions in tumour cell lines as well as in normal mammary epithelial cells. The importance of this difference in the pathogenesis of breast cancer has yet to be determined. Developing an understanding of the impact of BRCA1 isoform ratio changes on cell phenotype will be of value in breast cancer and may offer therapeutic options. In the present paper, we describe the splicing isoforms of BRCA1 exon 11, their possible role in cancer biology and the importance of maintaining a balanced ratio.

Assessing and Quantifying the Surface Texture of Milk Powder Using Image Processing.

Milk powders produced from similar spray dryers have different visual appearances, while the surface appearance of the powder is a key quality attribute because the smoothness of the milk powder also affects flowability and handling properties. Traditionally quantifying this nuanced visual metric was undertaken using sensory panelists, which is both subjective and time consuming. Therefore, it is advantageous to develop an on-line quick and robust appearance assessment tool. The aim of this work is to develop a classification model which can classify the milk powder samples into different surface smoothness groups. This work proposes a strategy for quantifying the relative roughness of commercial milk powder from 3D images. Photogrammetry equipment together with the software RealityCapture were used to build 3D models of milk powder samples, and a surface normal analysis which compares the area of the triangle formed by the 3 adjacent surface normals or compares the angle between the adjacent surface normals was used to quantify the surface smoothness of the milk powder samples. It was found that the area of the triangle of the smooth-surface milk powder cone is smaller than the area of the triangle of the rough-surface milk powder cone, and the angle between the adjacent surface normals of the rough-surface milk powder cone is larger than the angle between the adjacent surface normals of the smooth-surface milk powder cone, which proved that the proposed area metrics and angle metrics can be used as tools to quantify the smoothness of milk powder samples. Finally, the result of the support vector machine (SVM) classifier proved that image processing can be used as a preliminary tool for classifying milk powder into different surface texture groups.

Defining cardiac cell populations and relative cellular composition of the early fetal human heart.

While the adult human heart is primarily composed of cardiomyocytes, fibroblasts, endothelial and smooth muscle cells, the cellular composition during early development remains largely unknown. Reliable identification of fetal cardiac cell types using protein markers is critical to understand cardiac development and delineate the cellular composition of the developing human heart. This is the first study to use immunohistochemistry (IHC), flow cytometry and RT-PCR analyses to investigate the expression and specificity of commonly used cardiac cell markers in the early human fetal heart (8-12 post-conception weeks). The expression of previously reported protein markers for the detection of cardiomyocytes (Myosin Heavy Chain (MHC) and cardiac troponin I (cTnI), fibroblasts (DDR2, THY1, Vimentin), endothelial cells (CD31) and smooth muscle cells (α-SMA) were assessed. Two distinct populations of cTnI positive cells were identified through flow cytometry, with MHC positive cardiomyocytes showing high cTnI expression (cTnIHigh) while MHC negative non-myocytes showed lower cTnI expression (cTnILow). cTnI expression in non-myocytes was further confirmed by IHC and RT-PCR analyses, suggesting troponins are not cardiomyocyte-specific and may play distinct roles in non-muscle cells during early development. Vimentin (VIM) was expressed in cultured ventricular fibroblast populations and flow cytometry revealed VIMHigh and VIMLow cell populations in the fetal heart. MHC positive cardiomyocytes were VIMLow whilst CD31 positive endothelial cells were VIMHigh. Using markers investigated within this study, we characterised fetal human cardiac populations and estimate that 75-80% of fetal cardiac cells are cardiomyocytes and are MHC+/cTnIHigh/VIMLow, whilst non-myocytes comprise 20-25% of total cells and are MHC-/cTnILow/VIMHigh, with CD31+ endothelial cells comprising ~9% of this population. These findings show distinct differences from those reported for adult heart.

Induction of a disintegrin and metalloprotease 33 during embryonic lung development and the influence of IL-13 or maternal allergy.

BACKGROUND: Asthma pathogenesis involves gene and environmental interactions. A disintegrin and metalloprotease 33 (ADAM33)/Adam33 is a susceptibility gene for asthma and bronchial hyperresponsiveness in human beings and mice. ADAM33 is almost exclusively expressed in mesenchymal cells, including mesenchymal progenitors in developing lungs. OBJECTIVE: Because maternal allergy is a risk factor for asthma, we hypothesized that an allergic environment affects ADAM33/Adam33 expression during human and mouse lung development. METHODS: Human embryonic/fetal lung (HEL) tissues were collected from first-trimester terminations of pregnancy. These were processed immediately or used for explant culture +/- IL-13. MF1 mice or ovalbumin-sensitized A/J mice (Bronchial hyperresponsivness (Bhr)1/Adam33 locus-positive) were time-mated and challenged with ovalbumin (A/J mice only) during pregnancy. Lungs were harvested at different times during gestation and post partum. ADAM33/Adam33 expression was analyzed by using reverse transcriptase quantitative polymerase chain reaction and Western blotting. RESULTS: ADAM33 mRNA was detectable in HELs in the pseudoglandular stage of development and showed a significant increase from 7 to 9 weeks postconception. IL-13 significantly suppressed ADAM33 mRNA in HEL explants. In developing murine lungs, Adam33 mRNA and protein expression increased significantly in the early pseudoglandular stage and showed another large increase post partum. In A/J mice, maternal allergy significantly suppressed Adam33 mRNA in lungs of newborn pups, whereas processed Adam33 protein increased and several smaller isoforms were detected. CONCLUSION: Adam33/Adam33 shows 2 significant increments in expression during lung morphogenesis, suggesting important developmental regulation. The ability of maternal allergy or exogenous IL-13 to suppress Adam33/ADAM33 mRNA but enhance Adam33 processing suggests a gene-environment interaction that may be relevant for asthma pathogenesis.

Lateral entorhinal cortex lesions impair both egocentric and allocentric object-place associations.

During navigation, landmark processing is critical either for generating an allocentric-based cognitive map or in facilitating egocentric-based strategies. Increasing evidence from manipulation and single-unit recording studies has highlighted the role of the entorhinal cortex in processing landmarks. In particular, the lateral (LEC) and medial (MEC) sub-regions of the entorhinal cortex have been shown to attend to proximal and distal landmarks, respectively. Recent studies have identified a further dissociation in cue processing between the LEC and MEC based on spatial frames of reference. Neurons in the LEC preferentially encode egocentric cues while those in the MEC encode allocentric cues. In this study, we assessed the impact of disrupting the LEC on landmark-based spatial memory in both egocentric and allocentric reference frames. Animals that received excitotoxic lesions of the LEC were significantly impaired, relative to controls, on both egocentric and allocentric versions of an object-place association task. Notably, LEC lesioned animals performed at chance on the egocentric version but above chance on the allocentric version. There was no significant difference in performance between the two groups on an object recognition and spatial T-maze task. Taken together, these results indicate that the LEC plays a role in feature integration more broadly and in specifically processing spatial information within an egocentric reference frame.

Effects of Morphology on the Bulk Density of Instant Whole Milk Powder.

The chemical and physical properties of instant whole milk powder (IWMP), such as morphology, protein content, and particle size, can affect its functionality and performance. Bulk density, which directly determines the packing cost and transportation cost of milk powder, is one of the most important functional properties of IWMP, and it is mainly affected by physical properties, e.g., morphology and particle size. This work quantified the relationship between morphology and bulk density of IWMP and developed a predictive model of bulk density for IWMP. To obtain milk powder samples with different particle size fractions, IWMP samples of four different brands were sieved into three different particle size range groups, before using the simplex-centroid design (SCD) method to remix the milk powder samples. The bulk densities of these remixed milk powder samples were then measured by tap testing, and the particles' shape factors were extracted by light microscopy and image processing. The number of variables was decreased by principal component analysis and partial least squares models and artificial neural network models were built to predict the bulk density of IWMP. It was found that different brands of IWMP have different morphology, and the bulk density trends versus the shape factor changes were similar for the different particle size range groups. Finally, prediction models for bulk density were developed by using the shape factors and particle size range fractions of the IWMP samples. The good results of these models proved that predicting the bulk density of IWMP by using shape factors and particle size range fractions is achievable and could be used as a model for online model-based process monitoring.