Use of Artificial Intelligence in Stem Cell Research – Legal, Social and Health Concerns

Artificial intelligence (AI)  is an evolving discipline with a combination of computer science and engineering. This innovative invention from its launch has shown latent applications in various fields such as robotics, agriculture, home automation, healthcare, banking, and transportation. Due to technological developments AI and its applications have helped scientific researchers to enhance the precision and the quality of the output of  a products or process. Recently  AI  has been used in the field of stem cell research. Stem cells are unique cells with an ability to reproduce continuously. This ability of the stem cells and products and process derived from it have promising abilities to cure incurable diseases. But since it is a natural process or a stimulated process it is difficult to determine the quality and the output of the cells.  Stem cells  have concerns in predictability and identification of the quality stem cells for research or extraction purposes. Albiet its promising abilities concerns were raised regarding its accurate predictable use. The researcher in this article has tried to Map the plausible legal, social and ethical issues in including Artificial intelligence to the field of stem cells and the existing National and international policy approach to resolve the conundrums

Neurochemical Changes in the Mouse Hippocampus Underlying the Antidepressant Effect of Genetic Deletion of P2X7 Receptors.

Recent investigations have revealed that the genetic deletion of P2X7 receptors (P2rx7) results in an antidepressant phenotype in mice. However, the link between the deficiency of P2rx7 and changes in behavior has not yet been explored. In the present study, we studied the effect of genetic deletion of P2rx7 on neurochemical changes in the hippocampus that might underlie the antidepressant phenotype. P2X7 receptor deficient mice (P2rx7-/-) displayed decreased immobility in the tail suspension test (TST) and an attenuated anhedonia response in the sucrose preference test (SPT) following bacterial endotoxin (LPS) challenge. The attenuated anhedonia was reproduced through systemic treatments with P2rx7 antagonists. The activation of P2rx7 resulted in the concentration-dependent release of [3H]glutamate in P2rx7+/+ but not P2rx7-/- mice, and the NR2B subunit mRNA and protein was upregulated in the hippocampus of P2rx7-/- mice. The brain-derived neurotrophic factor (BDNF) expression was higher in saline but not LPS-treated P2rx7-/- mice; the P2rx7 antagonist Brilliant blue G elevated and the P2rx7 agonist benzoylbenzoyl ATP (BzATP) reduced BDNF level. This effect was dependent on the activation of NMDA and non-NMDA receptors but not on Group I metabotropic glutamate receptors (mGluR1,5). An increased 5-bromo-2-deoxyuridine (BrdU) incorporation was also observed in the dentate gyrus derived from P2rx7-/- mice. Basal level of 5-HT was increased, whereas the 5HIAA/5-HT ratio was lower in the hippocampus of P2rx7-/- mice, which accompanied the increased uptake of [3H]5-HT and an elevated number of [3H]citalopram binding sites. The LPS-induced elevation of 5-HT level was absent in P2rx7-/- mice. In conclusion there are several potential mechanisms for the antidepressant phenotype of P2rx7-/- mice, such as the absence of P2rx7-mediated glutamate release, elevated basal BDNF production, enhanced neurogenesis and increased 5-HT bioavailability in the hippocampus

Superhydrophobic paper in the development of disposable labware and lab-on-paper devices

Traditionally in superhydrophobic surfaces history, the focus has frequently settled on the use of complex processing methodologies using nonbiodegradable and costly materials. In light of recent events on lab-on-paper emergence, there are now some efforts for the production of superhydrophobic paper but still with little development and confined to the fabrication of flat devices. This work gives a new look at the range of possible applications of bioinspired superhydrophobic paper-based substrates, obtained using a straightforward surface modification with poly(hydroxybutyrate). As an end-of-proof of the possibility to create lab-on-chip portable devices, the patterning of superhydrophobic paper with different wettable shapes is shown with low-cost approaches. Furthermore, we suggest the use of superhydrophobic paper as an extremely low-cost material to design essential nonplanar lab apparatus, including reservoirs for liquid storage and manipulation, funnels, tips for pipettes, or accordion-shaped substrates for liquid transport or mixing. Such devices take the advantage of the self-cleaning and extremely water resistance properties of the surfaces as well as the actions that may be done with paper such as cut, glue, write, fold, warp, or burn. The obtained substrates showed lower propensity to adsorb proteins than the original paper, kept superhydrophobic character upon ethylene oxide sterilization and are disposable, suggesting that the developing devices could be especially adequate for use in contact with biological and hazardous materials

Implications of z>∼12z>{\sim}12 JWST galaxies for galaxy formation at high redshift

Using a semi-analytic galaxy-formation model, we study analogues of 8 recently discovered JWST galaxies at $z>{\sim}12$. We select analogues from a cosmological simulation with a $(311{\rm cMpc})^3$ volume and an effective particle number of $10^{12}$ enabling resolution of every atomic-cooling galaxy at $z{\le}20$. We vary model parameters to reproduce the observed UV luminosity function of $5{<}z{<}13$, aiming for a statistically representative high-redshift galaxy mock catalogue. Using the forward-modelled JWST photometry, we identify analogues from this catalogue and study their properties as well as possible evolutionary paths and local environments. We find faint JWST galaxies ($M_{\rm UV}>{\sim}-19.5$) remain consistent with standard galaxy-formation model and that our fiducial catalogue includes large samples of their analogues. The properties of these analogues broadly agree with conventional SED fitting results, except for having systematically lower redshifts due to the evolving UV luminosity function, and for having higher specific star formation rates as a result of burstier histories in our model. On the other hand, only a handful of bright galaxy analogues can be identified for observed $z{\sim}12$ galaxies. Moreover, in order to reproduce $z>{\sim}16$ JWST galaxy candidates, boosted star-forming efficiencies and reduced feedback regulation are necessary relative to models of lower-redshift populations. This suggests star formation in the first galaxies could differ significantly from their lower-redshift counterparts. We also find that these candidates are subject to low-redshift contamination, which is present in our fiducial results as both the dusty or quiescent galaxies at $z{\sim}5$.Comment: 10 pages, 11 figures, submitted to MNRAS, comments welcome

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

REVERSAL OF CLONIDINE-INDUCED HYPOTHERMIA BY DECAFFEINATED TEA/COFFEE EXTRACT, AND THEIR FRACTIONS IN MICE

Objective: To study the effect of decaffeinated tea extract (DTE) and decaffeinated coffee extract (DCE) and their respective fractions viz: chloroform fractions (DTCf and DCCf), ethyl acetate fractions (DTEa and DCEa), diethyl ether fractions (DTDe and DCDe) and acetone-water fractions (DTAw and DCAw) against clonidine-induced hypothermia in mice. Methods: Clonidine (0.1 mg/kg, i. p.) administered to a group of mice pretreated 30 min before with the dose of DTE or DCE or their respective fractions. Rectal temperature was measured at the time of clonidine administration and thereafter at every 30 min up to 2 h test period. Results: DTE 200 DTE 300 has significantly inhibited clonidine-induced hypothermia. Among the fractions tested, DTE fraction-DTEa 100 and 200 and DCE fractions DCDe 200 and DCAw 200 significantly (p&lt;0.0001) reversed clonidine-induced hypothermia; the effect of DTEa was found to be more sustained. Conclusion: Both, the decaffeinated tea and coffee contain ingredients that reverse clonidine-induced hypothermia, but they are required to do so in very large doses which are not achievable with normally administered doses of decaffeinated tea or coffee

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment