Exploring the Structural and Functional Diversity among FGF Signals: A Comparative Study of Human, Mouse, and Xenopus FGF Ligands in Embryonic Development and Cancer Pathogenesis.

Fibroblast growth factors (FGFs) encode a large family of growth factor proteins that activate several intracellular signaling pathways to control diverse physiological functions. The human genome encodes 22 FGFs that share a high sequence and structural homology with those of other vertebrates. FGFs orchestrate diverse biological functions by regulating cellular differentiation, proliferation, and migration. Dysregulated FGF signaling may contribute to several pathological conditions, including cancer. Notably, FGFs exhibit wide functional diversity among different vertebrates spatiotemporally. A comparative study of FGF receptor ligands and their diverse roles in vertebrates ranging from embryonic development to pathological conditions may expand our understanding of FGF. Moreover, targeting diverse FGF signals requires knowledge regarding their structural and functional heterogeneity among vertebrates. This study summarizes the current understanding of human FGF signals and correlates them with those in mouse and Xenopus models, thereby facilitating the identification of therapeutic targets for various human disorders.

Bmp4 Synexpression Gene, Sizzled, Transcription Is Collectively Modulated by Smad1 and Ventx1.1/Ventx2.1 in Early Xenopus Embryos.

Sizzled (Szl) is a secreted frizzled protein, having a sequence homology with the extracellular cysteine-rich domain (CRD) of the Wnt receptor, 'Frizzled'. Contrary to the other secreted frizzled like proteins (Sfrps), szl belongs to the bone morphogenetic protein 4 (Bmp4) synexpression group and is tightly coexpressed with Bmp4. What is not known is how the szl transcription achieves its Bmp4 synexpression pattern. To address the molecular details of szl transcription control, we cloned a promoter of size 1566 base pairs for szl (bps) from the Xenopus laevis genomic DNA. Luciferase and eGFP reporter gene results of this szl promoter (-1566 bp) in its activation and repression patterns by Bmp4/Smad1 and a dominant negative Bmp4 receptor (DNBR) were similar to those of the endogenous szl expression. Reporter gene assays and site-directed mutagenesis of the szl promoter mapped an active Bmp4/Smad1 response element (BRE) and a cis-acting element, which competitively share a direct binding site for Ventx1.1 and Ventx2.1 (a Ventx response element, VRE). Smad1 and ventx2.1 alone increased szl promoter activity; in addition, the binding of each protein component was enhanced with their coexpression. Interestingly, Ventx1.1 repressed this reporter gene activity; however, Ventx1.1 and Ventx2.1 together positively regulated the szl promoter activity. From our analysis, Ventx2.1 binding was enhanced by Ventx1.1, but Ventx1.1 inhibitory binding was inhibited by co-injection of Ventx2.1 for the VRE site. The inhibitory Ventx1.1 co-injection decreased Smad1 binding on the szl promoter. In a triple combination of overexpressed Smad1/Ventx1.1/Ventx2.1, the reduced binding of Smad1 from Ventx1.1 was recovered to that of the Smad1/Ventx2 combination. Collectively, this study provides evidence of Bmp4/Smad1 signaling for a primary immediate early response and its two oppositely behaving target transcription factors, Ventx1.1 and Ventx2.1, for a secondary response, as they together upregulate the szl promoter's activity to achieve szl expression in a Bmp4 synexpression manner.

Smad2 and Smad3 differentially modulate chordin transcription via direct binding on the distal elements in gastrula Xenopus embryos.

Transforming growth factor (TGF)ß/activin superfamily regulates diverse biological processes including germ layer specification and axis patterning in vertebrates. TGFß/activin leads to phosphorylation of Smad2 and Smad3, followed by regulation of their target genes. Activin treatment also induces the essential organizer gene chordin (chrd). The involvement of Smad2/3 in chrd expression has been unclear as to whether Smad2/3 involvement is direct or indirect and whether any cis-acting response elements for Smad2/3 are present in the proximal or distal regions of its promoter. In the present study, we isolated the -2250 bps portion of the chrd promoter, showing that it contained Smad2/3 direct binding sites at its distal portion, separate from the proximal locations of other organizer genes, goosecoid and cerberus. The pattern of transcription activation for the promoter (-2250 bps) was indistinguishable from that of the endogenous chrd in gastrula Xenopus embryos. Reporter gene assays and site-directed mutagenesis analysis of the chrd promoter mapped two active activin/Smad response elements (ARE1 and ARE2) for Smad2 and Smad3. For a differential chrd induction, Smad2 acted on both ARE1 and ARE2, but Smad3 was only active for ARE2. Collectively, the results demonstrate that the distal region of chrd promoter contains the direct binding cis-acting elements for Smad2 and Smad3, which differentially modulate chrd transcription in gastrula Xenopus embryos.

Automatic, Qualitative Scoring of the Clock Drawing Test (CDT) Based on U-Net, CNN and Mobile Sensor Data.

The Clock Drawing Test (CDT) is a rapid, inexpensive, and popular screening tool for cognitive functions. In spite of its qualitative capabilities in diagnosis of neurological diseases, the assessment of the CDT has depended on quantitative methods as well as manual paper based methods. Furthermore, due to the impact of the advancement of mobile smart devices imbedding several sensors and deep learning algorithms, the necessity of a standardized, qualitative, and automatic scoring system for CDT has been increased. This study presents a mobile phone application, mCDT, for the CDT and suggests a novel, automatic and qualitative scoring method using mobile sensor data and deep learning algorithms: CNN, a convolutional network, U-Net, a convolutional network for biomedical image segmentation, and the MNIST (Modified National Institute of Standards and Technology) database. To obtain DeepC, a trained model for segmenting a contour image from a hand drawn clock image, U-Net was trained with 159 CDT hand-drawn images at 128 × 128 resolution, obtained via mCDT. To construct DeepH, a trained model for segmenting the hands in a clock image, U-Net was trained with the same 159 CDT 128 × 128 resolution images. For obtaining DeepN, a trained model for classifying the digit images from a hand drawn clock image, CNN was trained with the MNIST database. Using DeepC, DeepH and DeepN with the sensor data, parameters of contour (0-3 points), numbers (0-4 points), hands (0-5 points), and the center (0-1 points) were scored for a total of 13 points. From 219 subjects, performance testing was completed with images and sensor data obtained via mCDT. For an objective performance analysis, all the images were scored and crosschecked by two clinical experts in CDT scaling. Performance test analysis derived a sensitivity, specificity, accuracy and precision for the contour parameter of 89.33, 92.68, 89.95 and 98.15%, for the hands parameter of 80.21, 95.93, 89.04 and 93.90%, for the numbers parameter of 83.87, 95.31, 87.21 and 97.74%, and for the center parameter of 98.42, 86.21, 96.80 and 97.91%, respectively. From these results, the mCDT application and its scoring system provide utility in differentiating dementia disease subtypes, being valuable in clinical practice and for studies in the field.

Automatic, Qualitative Scoring of the Interlocking Pentagon Drawing Test (PDT) based on U-Net and Mobile Sensor Data.

We implemented a mobile phone application of the pentagon drawing test (PDT), called mPDT, with a novel, automatic, and qualitative scoring method for the application based on U-Net (a convolutional network for biomedical image segmentation) coupled with mobile sensor data obtained with the mPDT. For the scoring protocol, the U-Net was trained with 199 PDT hand-drawn images of 512ⅹ512 resolution obtained via the mPDT in order to generate a trained model, Deep5, for segmenting a drawn right or left pentagon. The U-Net was also trained with 199 images of 512ⅹ512 resolution to attain the trained model, DeepLock, for segmenting an interlocking figure. Here, the epochs were iterated until the accuracy was greater than 98% and saturated. The mobile senor data primarily consisted of x and y coordinates, timestamps, and touch-events of all the samples with a 20 ms sampling period. The velocities were then calculated using the primary sensor data. With Deep5, DeepLock, and the sensor data, four parameters were extracted. These included the number of angles (0-4 points), distance/intersection between the two drawn figures (0-4 points), closure/opening of the drawn figure contours (0-2 points), and tremors detected (0-1 points). The parameters gave a scaling of 11 points in total. The performance evaluation for the mPDT included 230 images from subjects and their associated sensor data. The results of the performance test indicated, respectively, a sensitivity, specificity, accuracy, and precision of 97.53%, 92.62%, 94.35%, and 87.78% for the number of angles parameter; 93.10%, 97.90%, 96.09%, and 96.43% for the distance/intersection parameter; 94.03%, 90.63%, 92.61%, and 93.33% for the closure/opening parameter; and 100.00%, 100.00%, 100.00%, and 100.00% for the detected tremor parameter. These results suggest that the mPDT is very robust in differentiating dementia disease subtypes and is able to contribute to clinical practice and field studies.

Dysregulation of the causative genes for hereditary parkinsonism in the midbrain in Parkinson's disease.

BACKGROUND AND OBJECTIVES: Many hereditary movement disorders with complex phenotypes without a locus symbol prefix for familial PD present as parkinsonism; however, the dysregulation of genes associated with these phenotypes in the SNpc of PD patients has not been systematically studied. METHODS: Gene set enrichment analyses were performed using 10 previously published genome-wide expression datasets obtained by laser-captured microdissection of pigmented neurons in the SNpc. A custom-curated gene set for hereditary parkinsonism consisting of causative genes (n = 78) related to disorders with a parkinsonism phenotype, but not necessarily idiopathic or monogenic PD, was constructed from the Online Mendelian Inheritance in Man database. RESULTS: In 9 of the 10 gene expression data sets, gene set enrichment analysis showed that the disease-causing genes for hereditary parkinsonism were downregulated in the SNpc in PD patients compared to controls (nominal P values <0.05 in five studies). Among the 63 leading edge subset genes representing downregulated genes in PD, 79.4% were genes without a locus symbol prefix for familial PD. A meta-gene set enrichment analysis performed with a random-effect model showed an association between the gene set for hereditary parkinsonism and PD with a negative normalized enrichment score value (-1.40; 95% CI: -1.52∼-1.28; P < 6.2E-05). CONCLUSION: Disease-causing genes with a parkinsonism phenotype are downregulated in the SNpc in PD. Our study highlights the importance of genes associated with hereditary movement disorders with parkinsonism in understanding the pathogenesis of PD. © 2017 International Parkinson and Movement Disorder Society.

Draft Genome of Toxocara canis, a Pathogen Responsible for Visceral Larva Migrans.

This study aimed at constructing a draft genome of the adult female worm Toxocara canis using next-generation sequencing (NGS) and de novo assembly, as well as to find new genes after annotation using functional genomics tools. Using an NGS machine, we produced DNA read data of T. canis. The de novo assembly of the read data was performed using SOAPdenovo. RNA read data were assembled using Trinity. Structural annotation, homology search, functional annotation, classification of protein domains, and KEGG pathway analysis were carried out. Besides them, recently developed tools such as MAKER, PASA, Evidence Modeler, and Blast2GO were used. The scaffold DNA was obtained, the N50 was 108,950 bp, and the overall length was 341,776,187 bp. The N50 of the transcriptome was 940 bp, and its length was 53,046,952 bp. The GC content of the entire genome was 39.3%. The total number of genes was 20,178, and the total number of protein sequences was 22,358. Of the 22,358 protein sequences, 4,992 were newly observed in T. canis. Following proteins previously unknown were found: E3 ubiquitin-protein ligase cbl-b and antigen T-cell receptor, zeta chain for T-cell and B-cell regulation; endoprotease bli-4 for cuticle metabolism; mucin 12Ea and polymorphic mucin variant C6/1/40r2.1 for mucin production; tropomodulin-family protein and ryanodine receptor calcium release channels for muscle movement. We were able to find new hypothetical polypeptides sequences unique to T. canis, and the findings of this study are capable of serving as a basis for extending our biological understanding of T. canis.

Cdx1 and Gsc distinctly regulate the transcription of BMP4 target gene ventx3.2 by directly binding to the proximal promoter region in Xenopus gastrulae.

A comprehensive regulatory network of transcription factors controls the dorsoventral patterning of the body axis in developing vertebrate embryos. Bone morphogenetic protein signaling is essential for activating the Ventx family of homeodomain transcription factors, which regulates embryonic patterning and germ layer identity during Xenopus gastrulation. Although Ventx1.1 and Ventx2.1 of the Xenopus Ventx family have been extensively investigated, Ventx3.2 remains largely understudied. Therefore, this study aimed to investigate the transcriptional regulation of ventx3.2 during the embryonic development of Xenopus. We used goosecoid (Gsc) genome-wide chromatin immunoprecipitation-sequencing data to isolate and replicate the promoter region of ventx3.2. Serial deletion and site-directed mutagenesis were used to identify the cis-acting elements for Gsc and caudal type homeobox 1 (Cdx1) within the ventx3.2 promoter. Cdx1 and Gsc differentially regulated ventx3.2 transcription in this study. Additionally, positive cis-acting and negative response elements were observed for Cdx1 and Gsc, respectively, within the 5' flanking region of the ventx3.2 promoter. This result was corroborated by mapping the active Cdx1 response element (CRE) and Gsc response element (GRE). Moreover, a point mutation within the CRE and GRE completely abolished the activator and repressive activities of Cdx1 and Gsc, respectively. Furthermore, the chromatin immunoprecipitation-polymerase chain reaction confirmed the direct binding of Cdx1 and Gsc to the CRE and GRE, respectively. Inhibition of Cdx1 and Gsc activities at their respective functional regions, namely, the ventral marginal zone and dorsal marginal zone, reversed their effects on ventx3.2 transcription. These results indicate that Cdx1 and Gsc modulate ventx3.2 transcription in the ventral marginal zone and dorsal marginal zone by directly binding to the promoter region during Xenopus gastrulation.

Sizzled (Frzb3) physically interacts with noncanonical Wnt ligands to inhibit gastrulation cell movement.

The coordinated movement of germ layer progenitor cells reaches its peak at the dorsal side, where the Bmp signaling gradient is low, and minimum at the ventral side, where the Bmp gradient is high. This dynamic cell movement is regulated by the interplay of various signaling pathways. The noncanonical Wnt signaling cascade serves as a pivotal regulator of convergence and extension cell movement, facilitated by the activation of small GTPases such as Rho, Rab, and Rac. However, the underlying cause of limited cell movement at the ventral side remains elusive. To explore the functional role of a key regulator in constraining gastrulation cell movement at the ventral side, we investigated the Bmp4-direct target gene, sizzled (szl), to assess its potential role in inhibiting noncanonical Wnt signaling. In our current study, we demonstrated that ectopic expression of szl led to gastrulation defects in a dose-dependent manner without altering cell fate specification. Overexpression of szl resulted in decreased elongation of Activin-treated animal cap and Keller explants. Furthermore, our immunoprecipitation assay unveiled the physical interaction of Szl with noncanonical Wnt ligand proteins (Wnt5 and Wnt11). Additionally, the activation of small GTPases involved in Wnt signaling mediation (RhoA and Rac1) was diminished upon szl overexpression. In summary, our findings suggest that Bmp4 signaling negatively modulates cell movement from the ventral side of the embryo by inducing szl expression during early Xenopus gastrulation.

Xbra modulates the activity of linker region phosphorylated Smad1 during Xenopus development.

The Bmp/Smad1 pathway plays a crucial role in developmental processes and tissue homeostasis. Mitogen-activated protein kinase (Mapk)/Erk mediated phosphorylation of Smad1 in the linker region leads to Smad1 degradation, cytoplasmic retention and inhibition of Bmp/Smad1 signaling. While Fgf/Erk pathway has been documented to inhibit Bmp/Smad1 signaling, several studies also suggests the cooperative interaction between these two pathways in different context. However, the precise role and molecular pathway of this collaborative interaction remain obscure. Here, we identified Xbra induced by Fgf/Erk signaling as a factor in a protective mechanism for Smad1. Xbra physically interacted with the linker region phosphorylated Smad1 to make Xbra/Smad1/Smad4 trimeric complex, leading to Smad1 nuclear localization and protecting it from ubiquitin-mediated proteasomal degradation. This interaction of Xbra/Smad1/Smad4 led to sustained nuclear localization of Smad1 and the upregulation of lateral mesoderm genes, while concurrently suppression of neural and blood forming genes. Taken together, the results suggests Xbra-dependent cooperative interplays between Fgf/Erk and Bmp/Smad1 signaling during lateral mesoderm specification in Xenopus embryos.

Gut microbiota-based machine-learning signature for the diagnosis of alcohol-associated and metabolic dysfunction-associated steatotic liver disease.

Alcoholic-associated liver disease (ALD) and metabolic dysfunction-associated steatotic liver disease (MASLD) show a high prevalence rate worldwide. As gut microbiota represents current state of ALD and MASLD via gut-liver axis, typical characteristics of gut microbiota can be used as a potential diagnostic marker in ALD and MASLD. Machine learning (ML) algorithms improve diagnostic performance in various diseases. Using gut microbiota-based ML algorithms, we evaluated the diagnostic index for ALD and MASLD. Fecal 16S rRNA sequencing data of 263 ALD (control, elevated liver enzyme [ELE], cirrhosis, and hepatocellular carcinoma [HCC]) and 201 MASLD (control and ELE) subjects were collected. For external validation, 126 ALD and 84 MASLD subjects were recruited. Four supervised ML algorithms (support vector machine, random forest, multilevel perceptron, and convolutional neural network) were used for classification with 20, 40, 60, and 80 features, in which three nonsupervised ML algorithms (independent component analysis, principal component analysis, linear discriminant analysis, and random projection) were used for feature reduction. A total of 52 combinations of ML algorithms for each pair of subgroups were performed with 60 hyperparameter variations and Stratified ShuffleSplit tenfold cross validation. The ML models of the convolutional neural network combined with principal component analysis achieved areas under the receiver operating characteristic curve (AUCs) > 0.90. In ALD, the diagnostic AUC values of the ML strategy (vs. control) were 0.94, 0.97, and 0.96 for ELE, cirrhosis, and liver cancer, respectively. The AUC value (vs. control) for MASLD (ELE) was 0.93. In the external validation, the AUC values of ALD and MASLD (vs control) were > 0.90 and 0.88, respectively. The gut microbiota-based ML strategy can be used for the diagnosis of ALD and MASLD.ClinicalTrials.gov NCT04339725.

Machine Learning Model for Mild Cognitive Impairment Stage Based on Gait and MRI Images.

In patients with mild cognitive impairment (MCI), a lower level of cognitive function is associated with a higher likelihood of progression to dementia. In addition, gait disturbances and structural changes on brain MRI scans reflect cognitive levels. Therefore, we aimed to classify MCI based on cognitive level using gait parameters and brain MRI data. Eighty patients diagnosed with MCI from three dementia centres in Gangwon-do, Korea, were recruited for this study. We defined MCI as a Clinical Dementia Rating global score of ≥0.5, with a memory domain score of ≥0.5. Patients were classified as early-stage or late-stage MCI based on their mini-mental status examination (MMSE) z-scores. We trained a machine learning model using gait and MRI data parameters. The convolutional neural network (CNN) resulted in the best classifier performance in separating late-stage MCI from early-stage MCI; its performance was maximised when feature patterns that included multimodal features (GAIT + white matter dataset) were used. The single support time was the strongest predictor. Machine learning that incorporated gait and white matter parameters achieved the highest accuracy in distinguishing between late-stage MCI and early-stage MCI.

A computational method for detecting copy number variations using scale-space filtering.

BACKGROUND: As next-generation sequencing technology made rapid and cost-effective sequencing available, the importance of computational approaches in finding and analyzing copy number variations (CNVs) has been amplified. Furthermore, most genome projects need to accurately analyze sequences with fairly low-coverage read data. It is urgently needed to develop a method to detect the exact types and locations of CNVs from low coverage read data. RESULTS: Here, we propose a new CNV detection method, CNV_SS, which uses scale-space filtering. The scale-space filtering is evaluated by applying to the read coverage data the Gaussian convolution for various scales according to a given scaling parameter. Next, by differentiating twice and finding zero-crossing points, inflection points of scale-space filtered read coverage data are calculated per scale. Then, the types and the exact locations of CNVs are obtained by analyzing the finger print map, the contours of zero-crossing points for various scales. CONCLUSIONS: The performance of CNV_SS showed that FNR and FPR stay in the range of 1.27% to 2.43% and 1.14% to 2.44%, respectively, even at a relatively low coverage (0.5x ≤C ≤2x). CNV_SS gave also much more effective results than the conventional methods in the evaluation of FNR, at 3.82% at least and 76.97% at most even when the coverage level of read data is low. CNV_SS source code is freely available from http://dblab.hallym.ac.kr/CNV SS/.

Two Homeobox Transcription Factors, Goosecoid and Ventx1.1, Oppositely Regulate Chordin Transcription in Xenopus Gastrula Embryos.

The reciprocal inhibition between two signaling centers, the Spemann organizer (dorsal mesoderm) and ventral region (mesoderm and ectoderm), collectively regulate the overall development of vertebrate embryos. Each center expresses key homeobox transcription factors (TFs) that directly control target gene transcription. Goosecoid (Gsc) is an organizer (dorsal mesoderm)-specific TF known to induce dorsal fate and inhibit ventral/ectodermal specification. Ventx1.1 (downstream of Bmp signaling) induces the epidermal lineage and inhibits dorsal organizer-specific genes from the ventral region. Chordin (Chrd) is an organizer-specific secreted Bmp antagonist whose expression is primarily activated by Gsc. Alternatively, chrd expression is repressed by Bmp/Ventx1.1 in the ventral/epidermal region. However, the regulatory mechanisms underlying the transcription mediated by Gsc and Ventx1.1 remain elusive. Here, we found that the chrd promoter contained two cis-acting response elements that responded negatively to Ventx1.1 and positively to Gsc. In the ventral/ectodermal region, Ventx1.1 was directly bound to the Ventx1.1 response element (VRE) and inhibited chrd transcription. In the organizer region, Gsc was bound to the Gsc response elements (GRE) to activate chrd transcription. The Gsc-mediated positive response on the chrd promoter completely depended on another adjacent Wnt response cis-acting element (WRE), which was the TCF7 (also known as Tcf1) binding element. Site-directed mutagenesis of VRE, GRE, or WRE completely abolished the repressive or activator activity of Ventx1.1 and Gsc, respectively. The ChIP-PCR results confirmed the direct binding of Ventx1.1 and Gsc/Tcf7 to VRE and GRE/WRE, respectively. These results demonstrated that chrd expression is oppositely modulated by homeobox TFs, Ventx1.1, and Gsc/Tcf7 during the embryonic patterning of Xenopus gastrula.

Oxidative stress in cerebrovascular disease and associated diseases.

Cellular aging is the most severe risk factor for neurodegenerative disease. Simultaneously, oxidative stress (OS) is a critical factor in the aging process, resulting from an imbalance between reactive oxygen and nitrogen species and the antioxidant defense system. Emerging evidence indicates that OS is a common cause of several age-related brain pathologies, including cerebrovascular diseases. Elevated OS disrupts endothelial functional ability by diminishing the bioavailability of nitric oxide (a vascular dilator), induces atherosclerosis, and impairs vasculature, which are all common characteristics of cerebrovascular disease. In this review, we summarize evidence supporting an active role of OS in cerebrovascular disease progression, focusing primarily on stroke pathogenesis. We briefly discuss hypertension, diabetes, heart disease, and genetic factors that are often linked to OS and are considered associated factors influencing stroke pathology. Finally, we discuss the current pharmaceutics/therapeutics available for treating several cerebrovascular diseases.

Relationship of Neural Correlates of Gait Characteristics and Cognitive Dysfunction in Patients with Mild Cognitive Impairment.

Background: Some patients with mild cognitive impairment (MCI) experience gait disturbances. However, there are few reports on the relationship between gait disturbance and cognitive function in patients with MCI. Therefore, we investigated the neural correlates of gait characteristics related to cognitive dysfunction. Methods: Eighty patients diagnosed with MCI from three dementia centers in Gangwon-do, Korea, were recruited for this study. We defined MCI as a Clinical Dementia Rating global score of 0.5 or higher, with a memory domain score of 0.5 or greater. The patients were classified as having either higher or lower MMSE and the groups were based on their Mini Mental Status Examination z-scores. Multiple logistic regression analysis was performed to examine the association between the gait characteristics and cognitive impairment. Analyses included variables such as age, sex, years of education, number of comorbidities, body mass index, and height. Results: Gait velocity, step count, step length, heel-to-heel base support, swing and stance phase duration, and support time were associated with cognitive function. A decrease in gray matter volume in the right pericalcarine area was associated with gait characteristics related to cognitive dysfunction. An increase in the curvature of gray matter in the right entorhinal, right lateral orbitofrontal, right cuneus, and right and left pars opercularis areas was also associated with gait characteristics related to cognitive dysfunction. Conclusion: Since gait impairment is an important factor in determining activities of daily living in patients with mild cognitive impairment, the evaluation of gait and cognitive functions in patients with mild cognitive impairment is important.

The Organizer and Its Signaling in Embryonic Development.

Germ layer specification and axis formation are crucial events in embryonic development. The Spemann organizer regulates the early developmental processes by multiple regulatory mechanisms. This review focuses on the responsive signaling in organizer formation and how the organizer orchestrates the germ layer specification in vertebrates. Accumulated evidence indicates that the organizer influences embryonic development by dual signaling. Two parallel processes, the migration of the organizer's cells, followed by the transcriptional activation/deactivation of target genes, and the diffusion of secreting molecules, collectively direct the early development. Finally, we take an in-depth look at active signaling that originates from the organizer and involves germ layer specification and patterning.

Functional Roles of FGF Signaling in Early Development of Vertebrate Embryos.

Fibroblast growth factors (FGFs) comprise a large family of growth factors, regulating diverse biological processes including cell proliferation, migration, and differentiation. Each FGF binds to a set of FGF receptors to initiate certain intracellular signaling molecules. Accumulated evidence suggests that in early development and adult state of vertebrates, FGFs also play exclusive and context dependent roles. Although FGFs have been the focus of research for therapeutic approaches in cancer, cardiovascular disease, and metabolic syndrome, in this review, we mainly focused on their role in germ layer specification and axis patterning during early vertebrate embryogenesis. We discussed the functional roles of FGFs and their interacting partners as part of the gene regulatory network for germ layer specification, dorsal-ventral (DV), and anterior-posterior (AP) patterning. Finally, we briefly reviewed the regulatory molecules and pharmacological agents discovered that may allow modulation of FGF signaling in research.

Foxd4l1.1 Negatively Regulates Chordin Transcription in Neuroectoderm of Xenopus Gastrula.

Inhibition of the bone morphogenetic proteins (BMPs) is the primary step toward neuroectoderm formation in vertebrates. In this process, the Spemann organizer of the dorsal mesoderm plays a decisive role by secreting several extracellular BMP inhibitors such as Chordin (Chrd). Chrd physically interacts with BMP proteins and inhibits BMP signaling, which triggers the expression of neural-specific transcription factors (TFs), including Foxd4l1.1. Thus, Chrd induces in a BMP-inhibited manner and promotes neuroectoderm formation. However, the regulatory feedback mechanism of Foxd4l1.1 on mesodermal genes expression during germ-layer specification has not been fully elucidated. In this study, we investigated the regulatory mechanism of Foxd4l1.1 on chrd (a mesodermal gene). We demonstrate that Foxd4l1.1 inhibits chrd expression during neuroectoderm formation in two ways: First, Foxd4l1.1 directly binds to FRE (Foxd4l1.1 response elements) within the chrd promoter region to inhibit transcription. Second, Foxd4l1.1 physically interacts with Smad2 and Smad3, and this interaction blocks Smad2 and Smad3 binding to activin response elements (AREs) within the chrd promoter. Site-directed mutagenesis of FRE within the chrd(-2250) promoter completely abolished repressor activity of the Foxd4l1.1. RT-PCR and reporter gene assay results indicate that Foxd4l1.1 strongly inhibits mesoderm- and ectoderm-specific marker genes to maintain neural fate. Altogether, these results suggest that Foxd4l1.1 negatively regulates chrd transcription by dual mechanism. Thus, our study demonstrates the existence of precise reciprocal regulation of chrd transcription during neuroectoderm and mesoderm germ-layer specification in Xenopus embryos.

Alteration of the corpus callosum in patients with Alzheimer's disease: Deep learning-based assessment.

BACKGROUND: Several studies have reported changes in the corpus callosum (CC) in Alzheimer's disease. However, the involved region differed according to the study population and study group. Using deep learning technology, we ensured accurate analysis of the CC in Alzheimer's disease. METHODS: We used the Open Access Series of Imaging Studies (OASIS) dataset to investigate changes in the CC. The individuals were divided into three groups using the Clinical Dementia Rating (CDR); 94 normal controls (NC) were not demented (NC group, CDR = 0), 56 individuals had very mild dementia (VMD group, CDR = 0.5), and 17 individuals were defined as having mild and moderate dementia (MD group, CDR = 1 or 2). Deep learning technology using a convolutional neural network organized in a U-net architecture was used to segment the CC in the midsagittal plane. Total CC length and regional magnetic resonance imaging (MRI) measurements of the CC were made. RESULTS: The total CC length was negatively associated with cognitive function. (beta = -0.139, p = 0.022) Among MRI measurements of the CC, the height of the anterior third (beta = 0.038, p <0.0001) and width of the body (beta = 0.077, p = 0.001) and the height (beta = 0.065, p = 0.001) and area of the splenium (beta = 0.059, p = 0.027) were associated with cognitive function. To distinguish MD from NC and VMD, the receiver operating characteristic analyses of these MRI measurements showed areas under the curves of 0.65-0.74. (total CC length = 0.705, height of the anterior third = 0.735, width of the body = 0.714, height of the splenium = 0.703, area of the splenium = 0.649). CONCLUSIONS: Among MRI measurements, total CC length, the height of the anterior third and width of the body, and the height and area of the splenium were associated with cognitive decline. They had fair diagnostic validity in distinguishing MD from NC and VMD.