CRISPR/Cas9-Facilitated Chromosome Engineering to Model Human Chromosomal Alterations

Rodents, particularly the mouse, have been used extensively for genetic modeling and analysis of human chromosomal alterations based on the syntenic conservations between the human and rodent genomes. In this article, we will discuss the emergence of CRISPR/Cas9-facilitated chromosome engineering techniques, which may open up a new avenue to study human diseases associated with chromosomal abnormalities, such as Down syndrome and cancer

Final state rescattering as a contribution to B→ργB \to \rho \gamma

We provide a new estimate of the long-distance component to the radiative transition $B \to \rho \gamma$. Our mechanism involves the soft-scattering of on-shell hadronic products of nonleptonic $B$ decay, as in the chain $B \to \rho\rho \to \rho\gamma$. We employ a phenomenological fit to scattering data to estimate the effect. The specific intermediate states considered here modify the $B \to \rho \gamma$ decay rate at roughly the $5 \to 8$ level, although the underlying effect has the potential to be larger. Contrary to other mechanisms of long distance physics which have been discussed in the literature, this yields a non-negligible modification of the $B^0 \to \rho^0 \gamma$ channel and hence will provide an uncertainty in the extraction of $V_{td}$. This mechanism also affects the isospin relation between the rates for $B^- \to \rho^-\gamma$ and $B^0 \to \rho^0 \gamma$ and may generate CP asymmetries at experimentally observable levels.Comment: 15 pages, RevTex, 3 figure

Myocyte-Specific Overexpressing HDAC4 Promotes Myocardial Ischemia/Reperfusion Injury

Background: Histone deacetylases (HDACs) play a critical role in modulating myocardial protection and cardiomyocyte survivals. However, Specific HDAC isoforms in mediating myocardial ischemia/reperfusion injury remain currently unknown. We used cardiomyocyte-specific overexpression of active HDAC4 to determine the functional role of activated HDAC4 in regulating myocardial ischemia and reperfusion in isovolumetric perfused hearts. Methods: In this study, we created myocyte-specific active HDAC4 transgenic mice to examine the functional role of active HDAC4 in mediating myocardial I/R injury. Ventricular function was determined in the isovolumetric heart, and infarct size was determined using tetrazolium chloride staining. Results: Myocyte-specific overexpressing activated HDAC4 in mice promoted myocardial I/R injury, as indicated by the increases in infarct size and reduction of ventricular functional recovery following I/R injury. Notably, active HDAC4 overexpression led to an increase in LC-3 and active caspase 3 and decrease in SOD-1 in myocardium. Delivery of chemical HDAC inhibitor attenuated the detrimental effects of active HDAC4 on I/R injury, revealing the pivotal role of active HDAC4 in response to myocardial I/R injury. Conclusions: Taken together, these findings are the first to define that activated HDAC4 as a crucial regulator for myocardial ischemia and reperfusion injury

Functional Multipotency of Stem Cells: A Conceptual Review of Neurotrophic Factor-Based Evidence and Its Role in Translational Research

We here propose an updated concept of stem cells (SCs), with an emphasis on neural stem cells (NSCs). The conventional view, which has touched principally on the essential property of lineage multipotency (e.g., the ability of NSCs to differentiate into all neural cells), should be broadened to include the emerging recognition of biofunctional multipotency of SCs to mediate systemic homeostasis, evidenced in NSCs in particular by the secretion of neurotrophic factors. Under this new conceptual context and taking the NSC as a leading example, one may begin to appreciate and seek the “logic” behind the wide range of molecular tactics the NSC appears to serve at successive developmental stages as it integrates into and prepares, modifies, and guides the surrounding CNS micro- and macro-environment towards the formation and self-maintenance of a functioning adult nervous system. We suggest that embracing this view of the “multipotency” of the SCs is pivotal for correctly, efficiently, and optimally exploiting stem cell biology for therapeutic applications, including reconstitution of a dysfunctional CNS

A Deep Learning Approach for Predicting Antidepressant Response in Major Depression Using Clinical and Genetic Biomarkers

In the wake of recent advances in scientific research, personalized medicine using deep learning techniques represents a new paradigm. In this work, our goal was to establish deep learning models which distinguish responders from non-responders, and also to predict possible antidepressant treatment outcomes in major depressive disorder (MDD). To uncover relationships between the responsiveness of antidepressant treatment and biomarkers, we developed a deep learning prediction approach resulting from the analysis of genetic and clinical factors such as single nucleotide polymorphisms (SNPs), age, sex, baseline Hamilton Rating Scale for Depression score, depressive episodes, marital status, and suicide attempt status of MDD patients. The cohort consisted of 455 patients who were treated with selective serotonin reuptake inhibitors (treatment-response rate = 61.0%; remission rate = 33.0%). By using the SNP dataset that was original to a genome-wide association study, we selected 10 SNPs (including ABCA13 rs4917029, BNIP3 rs9419139, CACNA1E rs704329, EXOC4 rs6978272, GRIN2B rs7954376, LHFPL3 rs4352778, NELL1 rs2139423, NUAK1 rs2956406, PREX1 rs4810894, and SLIT3 rs139863958) which were associated with antidepressant treatment response. Furthermore, we pinpointed 10 SNPs (including ARNTL rs11022778, CAMK1D rs2724812, GABRB3 rs12904459, GRM8 rs35864549, NAALADL2 rs9878985, NCALD rs483986, PLA2G4A rs12046378, PROK2 rs73103153, RBFOX1 rs17134927, and ZNF536 rs77554113) in relation to remission. Then, we employed multilayer feedforward neural networks (MFNNs) containing 1–3 hidden layers and compared MFNN models with logistic regression models. Our analysis results revealed that the MFNN model with 2 hidden layers (area under the receiver operating characteristic curve (AUC) = 0.8228 ± 0.0571; sensitivity = 0.7546 ± 0.0619; specificity = 0.6922 ± 0.0765) performed maximally among predictive models to infer the complex relationship between antidepressant treatment response and biomarkers. In addition, the MFNN model with 3 hidden layers (AUC = 0.8060 ± 0.0722; sensitivity = 0.7732 ± 0.0583; specificity = 0.6623 ± 0.0853) achieved best among predictive models to predict remission. Our study indicates that the deep MFNN framework may provide a suitable method to establish a tool for distinguishing treatment responders from non-responders prior to antidepressant therapy

Direct Observation of an Interface Dipole between Two Metallic Oxides Caused by Localized Oxygen Vacancies

Oxygen vacancies are increasingly recognized to play a role in phenomena observed at transition-metal oxide interfaces. Here we report a study of SrRuO3/La0.7Sr0.3MnO3 (SRO/LSMO) interfaces using a combination of quantitative aberration-corrected scanning transmission electron microscopy, electron energy loss spectroscopy, and density-functional calculations. Cation displacements are observed at the interface, indicative of a dipole-like electric field even though both materials are nominally metallic. The observed displacements are reproduced by theory if O vacancies are present in the near-interface LSMO layers. The results suggest that atomic-scale structural mapping can serve as a quantitative indicator of the presence of O vacancies at interfaces

SENP1 regulates IFN-γ−STAT1 signaling through STAT3−SOCS3 negative feedback loop

Interferon-γ (IFN-γ) triggers macrophage for inflammation response by activating the intracellular JAK−STAT1 signaling. Suppressor of cytokine signaling 1 (SOCS1) and protein tyrosine phosphatases can negatively modulate IFN-γ signaling. Here, we identify a novel negative feedback loop mediated by STAT3−SOCS3, which is tightly controlled by SENP1 via de-SUMOylation of protein tyrosine phosphatase 1B (PTP1B), in IFN-γ signaling. SENP1-deficient macrophages show defects in IFN-γ signaling and M1 macrophage activation. PTP1B in SENP1-deficient macrophages is highly SUMOylated, which reduces PTP1B-induced de-phosphorylation of STAT3. Activated STAT3 then suppresses STAT1 activation via SOCS3 induction in SENP1-deficient macrophages. Accordingly, SENP1-deficient macrophages show reduced ability to resist Listeria monocytogenes infection. These results reveal a crucial role of SENP1-controlled STAT1 and STAT3 balance in macrophage polarization

Discovering novel systemic biomarkers in photos of the external eye

External eye photos were recently shown to reveal signs of diabetic retinal disease and elevated HbA1c. In this paper, we evaluate if external eye photos contain information about additional systemic medical conditions. We developed a deep learning system (DLS) that takes external eye photos as input and predicts multiple systemic parameters, such as those related to the liver (albumin, AST); kidney (eGFR estimated using the race-free 2021 CKD-EPI creatinine equation, the urine ACR); bone & mineral (calcium); thyroid (TSH); and blood count (Hgb, WBC, platelets). Development leveraged 151,237 images from 49,015 patients with diabetes undergoing diabetic eye screening in 11 sites across Los Angeles county, CA. Evaluation focused on 9 pre-specified systemic parameters and leveraged 3 validation sets (A, B, C) spanning 28,869 patients with and without diabetes undergoing eye screening in 3 independent sites in Los Angeles County, CA, and the greater Atlanta area, GA. We compared against baseline models incorporating available clinicodemographic variables (e.g. age, sex, race/ethnicity, years with diabetes). Relative to the baseline, the DLS achieved statistically significant superior performance at detecting AST>36, calcium=300, and WBC<4 on validation set A (a patient population similar to the development sets), where the AUC of DLS exceeded that of the baseline by 5.2-19.4%. On validation sets B and C, with substantial patient population differences compared to the development sets, the DLS outperformed the baseline for ACR>=300 and Hgb<11 by 7.3-13.2%. Our findings provide further evidence that external eye photos contain important biomarkers of systemic health spanning multiple organ systems. Further work is needed to investigate whether and how these biomarkers can be translated into clinical impact

Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese

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