Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.
Episodic memory function has been shown to depend critically on the hippocampus. This region is made up of a number of subfields, which differ in both cytoarchitectural features and functional roles in the mature brain. Recent neuroimaging work in children and adolescents has suggested that these regions may undergo different developmental trajectories-a fact that has important implications for how we think about learning and memory processes in these populations. Despite the growing research interest in hippocampal structure and function at the subfield level in healthy young adults, comparatively fewer studies have been carried out looking at subfield development. One barrier to studying these questions has been that manual segmentation of hippocampal subfields-considered by many to be the best available approach for defining these regions-is laborious and can be infeasible for large cross-sectional or longitudinal studies of cognitive development. Moreover, manual segmentation requires some subjectivity and is not impervious to bias or error. In a developmental sample of individuals spanning 6-30 years, we assessed the degree to which two semi-automated segmentation approaches-one approach based on Automated Segmentation of Hippocampal Subfields (ASHS) and another utilizing Advanced Normalization Tools (ANTs)-approximated manual subfield delineation on each individual by a single expert rater. Our main question was whether performance varied as a function of age group. Across several quantitative metrics, we found negligible differences in subfield validity across the child, adolescent, and adult age groups, suggesting that these methods can be reliably applied to developmental studies. We conclude that ASHS outperforms ANTs overall and is thus preferable for analyses carried out in individual subject space. However, we underscore that ANTs is also acceptable and may be well-suited for analyses requiring normalization to a single group template (e.g., voxelwise analyses across a wide age range). Previous work has supported the use of such methods in healthy young adults, as well as several special populations such as older adults and those suffering from mild cognitive impairment. Our results extend these previous findings to show that ASHS and ANTs can also be used in pediatric populations as young as six.
As the human lifespan has increased due to developments in medical technology, the number of patients with neurological diseases has rapidly increased. Therefore, studies on effective treatments for neurological diseases are becoming increasingly important. To perform these studies, it is essential to obtain a large number of patient-derived neural cells. The purpose of the present study was to establish a technology that allows the high-efficiency generation of genetically stable, direct-conversion-derived neural stem cells (dcNSCs) through the expression of a new combination of reprogramming factors, including a proto-oncogene. Specifically, human c-MYC proto-oncogene and the human SOX2 gene were overexpressed in a precisely controlled manner in various human somatic cells. As a result, the direct conversion into multipotent dcNSCs occurred only when the cells were treated with an MOI of 1 of hc-MYC proto-oncogene and hSOX2 retrovirus. When MOIs of 5 or 10 were utilized, distinct results were obtained. In addition, the pluripotency was bypassed during this process. Notably, as the MOI used to treat the cells increased, expression of the p53 tumor suppressor gene, which is typically a reprogramming hurdle, increased proportionately. Interestingly, p53 was genetically stable in dcNSCs generated through direct conversion into a low p53 expression state. In the present study, generation of genetically stable dcNSCs using direct conversion was optimized by precisely controlling the overexpression of a proto-oncogene. This method could be utilized in future studies, such as in vitro drug screening using generated dcNSCs. In addition, this method could be effectively utilized in studies on direct conversion into other types of target cells.
Early in gestation, wounds in fetal skin heal by regeneration, in which microRNAs play key roles. Seq-915_x4024 is a novel microRNA candidate confirmed by deep sequencing and mirTools 2.0. It is highly expressed in fetal keratinocytes during early gestation. Using an in vitro wound-healing assay, Transwell cell migration assay, and MTS proliferation assay, we demonstrated that keratinocytes overexpressing seq-915_x4024 exhibited higher proliferative activity and the ability to promote fibroblast migration and fibroblast proliferation. These characteristics of keratinocytes are the same biological behaviors as those of fetal keratinocytes, which contribute to skin regeneration. In addition, seq-915_x4024 suppressed the expression of the pro-inflammatory markers TNF-α, IL-6, and IL-8 and the pro-inflammatory chemokines CXCL1 and CXCL5. We also demonstrated that seq-915_x4024 regulates TGF-β isoforms and the extracellular matrix. Moreover, using an in vivo wound-healing model, we demonstrated that overexpression of seq-915_x4024 in keratinocytes suppresses inflammatory cell infiltration and scar formation. Using bioinformatics analyses, luciferase reporter assays, and western blotting, we further demonstrated that Sar1A, Smad2, TNF-α, and IL-8 are direct targets of seq-915_x4024. Furthermore, the expression of phosphorylated Smad2 and Smad3 was reduced by seq-915_x4024. Seq-915_x4024 could be used as an anti-fibrotic factor for the treatment of wound healing.
Induced pluripotent stem cells (iPSC) were derived from human dermal fibroblasts (HDF) of two siblings with small fiber neuropathy (SFN) potentially based on the same variation in SCN10A but exhibiting diverse disease phenotypes. HDF were reprogrammed using a non-integrating mRNA approach and showed robust expression of pluripotency markers. iPSC displayed no chromosomal aberrations and were differentiated into all three germ-layers. These two cell lines with a familial genetic background may provide a useful in vitro tool to investigate the underlying mechanisms leading to different phenotypes caused by the same variation.
Adolescence is frequently described as a developmental period characterized by increased sensitivity to rewards. However, previous research on age-related changes in the neural response to gains and losses have produced mixed results, with only some studies reporting potentiated neural responses during adolescence. The current study examined the ERP responses to gains and losses during a simple monetary reward (i.e., Doors) task in a large and longitudinal sample of 248 adolescent females assessed at two time points, separated by two years. At baseline, when the sample was 8- to 14-years-old, age related to larger (i.e., more positive) ERP responses to both gains and losses; moreover, age-related effects were stronger in relation to gains than losses. Overall, the amplitude of the ERP response to gains, but not losses, significantly increased from baseline to follow-up; however, this effect was moderated by age, such that reward-related ERPs only increased longitudinally among the younger participants. At the follow-up assessment, ERP responses to gains and losses were equally related to age. Collectively, these within- and between-subjects findings suggest a relatively specific developmental increase in reward-related neural activity during late childhood and early adolescence.
Hand-foot-mouth disease (HFMD) is a serious public health problem with increasing cases and substantial financial burden in China, especially in Wuhan city. Hence, there is an urgent need to construct a model to predict the incidence of HFMD that could make the prevention and control of this disease more effective.The incidence data of HFMD of Wuhan city from January 2009 to December 2016 were used to fit a combined model with seasonal autoregressive integrated moving average (SARIMA) model and support vector regression (SVR) model. Then, the SARIMA-SVR hybrid model was constructed. Subsequently, the fitted SARIMA-SVR hybrid model was applied to obtain the fitted HFMD incidence from 2009 to 2016. Finally, the fitted SARIMA-SVR hybrid model was used to forecast the incidence of HFMD of the year 2017. To assess the validity of the model, the mean square error (MSE) and mean absolute percentage error (MAPE) between the actual values and predicted values of HFMD incidence (2017) were calculated.From 2009 to 2017, a total of 107636 HFMD cases were reported in Wuhan City, Hubei Province, and the male-to-female ratio is 1.60:1. The age group of 0 to 5 years old accounts for 95.06% of all reported cases and scattered children made up the large proportion (accounted for 56.65%). There were 2 epidemic peaks, from April to July and September to December, respectively, with an emphasis on the former. High-prevalence areas mainly emerge in Dongxihu District, Jiangxia District, and Hongshan District. SARIMA (1,0,1)(0,0,2)[12] is the optimal model given with a minimum Akaike information criterion (AIC) (700.71), then SVR model was constructed by using the optimum parameter (C = 100000, =0.00001, =0.01). The forecasted incidences of single SARIMA model and SARIMA-SVR hybrid model from January to December 2017 match the actual data well. The single SARIMA model shows poor performance with large MSE and MAPE values in comparison to SARIMA-SVR hybrid model.The SARIMA-SVR hybrid model in this study showed that accurate forecasting of the HFMD incidence is possible. It is a potential decision supportive tool for controlling HFMD in Wuhan, China.
Transcriptome profiling of osteosarcoma (OS) by next generation sequencing technology (NGS) has been broadly performed by previous researches, which uncovers a large number protein-coding driver genes, facilitates our understanding of the molecular mechanisms of OS formation, progression and metastasis. Recently, more and more researchers realize the importance of long non-coding RNAs (lncRNAs) on the development of OS. However, few studies focus on discovering driver lncRNAs.Here we collected somatic copy number alterations (SCNAs) and gene expression profiles of 84 samples from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) project. The RNA sequencing data detected 13,903 expressed lncRNAs, 157 of which were previously reported to be associated with cancer based on the annotations from Lnc2Cancer database.By analyzing the SNP array data, several significant SCNAs were detected, such as the amplifications on chromosomes 1q, 4q, 17p, 17q, and 19q, and deletions on 1q, 3q, 9p, 10q, and 15q. With the SCNA and gene expression profiles, we identified 167 driver genes by integrative analysis, including 162 novel driver lncRNAs, 2 lncRNAs reported to be associated with OS, and another 3 associated with other cancers. Furthermore, functional characterization and survival analysis revealed that RP11-241F15.10 may function as a tumor suppressor in OS, and loss of function may contribute to activation of Wnt signaling pathway.This study not only facilitates our understanding of the oncogenic or tumor-suppressor role of lncRNAs in OS, but also provides potential therapies for the patients with OS with metastasis or relapse.
Many molecular epidemiology studies have reported an association between the combined effects of glutathione S-transferase M1 (GSTM1) and glutathione S-transferase T1 (GSTT1) polymorphisms on breast cancer risk. However, the results have been controversial.A meta-analysis was performed to clarify this issue.Meta-analysis of observational studies in epidemiology guidelines was used. Pooled the crude odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a random-effects model or fixed-effects model. Several subgroup analyses were conducted by ethnicity, source of control, matching, and menopausal status. In addition, we also performed sensitivity analysis and publication bias. Moreover, a false-positive report probability (FPRP) test was applied to assess positive results.A significantly increased breast cancer risk was observed in overall population (GSTM1 null/GSTT1 present [- +] vs GSTM1 present/GSTT1 present [+ +]: OR = 1.19, 95% CI: 1.03-1.36, GSTM1 null/GSTT1 null [- -] vs + +: OR = 1.63, 95% CI: 1.29-2.06, (- +) + GSTM1 present/GSTT1 null (+ -) vs + +: OR = 1.17, 95% CI: 1.05-1.31, (- +) + (+ -) + (- -) vs + +: OR = 1.27, 95% CI: 1.12-1.44, and - - vs (- +) + (+ -) + (+ +): OR = 1.39, 95% CI: 1.17-1.66) and several subgroup analyses, such as Caucasians, Indians, postmenopausal women, and so on. However, positive results were only considered noteworthy in overall population (- - vs + +: FPRP = 0.150 and (- +) + (+ -) + (- -) vs + +: FPRP = 0.162). Moreover, no significant association was observed when we used the trim and fill method to adjust the pooled data from all populations. Further, none of positive results of sensitivity analysis were considered noteworthy (FPRP >0.2).These positive findings should be interpreted with caution and indicate that an increased breast cancer risk may most likely result from false-positive results, rather than from true associations or biological factors on the combined effects of GSTM1 and GSTT1. Future studies should be based on sample sizes well-powered and attention needs to be paid to study design to further identify this issue.
This study aimed to identify modules associated with breast cancer (BC) development by constructing a gene co-expression network, and mining hub genes that may serve as markers of invasive breast cancer (IBC).We downloaded 2 gene expression datasets from the Gene Expression Omnibus (GEO) database, and used weighted gene co-expression network analysis (WGCNA) to dynamically study the changes of co-expression genes in normal breast tissues, ductal carcinoma in situ (DCIS) tissues, and IBC tissues. Modules that highly correlated with BC development were carried out functional enrichment analysis for annotation, visualization, and integration discovery. The hub genes detected by WGCNA were also confirmed using the Oncomine dataset.We detected 17 transcriptional modules in total and 4 - namely tan, greenyellow, turquoise, and brown - were highly correlated with BC development. The functions of these 4 modules mainly concerned cell migration (tan module, P = 3.03 × 10), the cell cycle (greenyellow module, P = 3.08 × 10), cell-cell adhesion (turquoise module, P = .002), and the extracellular exosome (brown module, P = 1.38 × 10). WGCNA also mined the hub genes, which were highly correlated with the genes in the same module and with BC development. The Oncomine database confirmed that the expressions levels of 6 hub genes were significantly higher in BC tissues than in normal tissues, with fold changes larger than 2 (all P < .05). Apart from the 2 well-known genes EPCAM and MELK, during the development of BC, KRT8, KRT19, KPNA2, and ECT2 also play key roles, and may be used as new targets for the detection or treatment of BC.In summary, our study demonstrated that hub genes such as EPCAM and MELK are highly correlated with breast cancer development. However, KRT8, KRT19, KPNA2, and ECT2 may also have potential as diagnostic and prognostic biomarkers of IBC.
Machado-Joseph disease (MJD) is a spinocerebellar ataxia, and osteoporosis is a multifactor disease that may affect patients with neurologic conditions. The frequency of osteoporosis among MJD patients, however, has not been studied. The purpose of this study is to evaluate bone mineral density (BMD) and identify correlations between clinical factors and frequency of vertebral fractures in patients with MJD.
Welcome to the SPARC SAWG Resources search. From here you can search through a compilation of resources used by SPARC SAWG and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that SPARC SAWG has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on SPARC SAWG then you can log in from here to get additional features in SPARC SAWG such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into SPARC SAWG you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the facets that you can filter your papers by.
From here we'll present any options for the literature, such as exporting your current results.
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
Year:
Count: