Identification of methotrexate as a heterochromatin-promoting drug.

Heterochromatin is a tightly packed form of DNA involved in gene silencing, chromosome segregation, and protection of genome stability. Heterochromatin is becoming more recognized in tumor suppression and may thus serve as a potential target for cancer therapy. However, to date there are no drugs that are well established to specifically promote heterochromatin formation. Here, we describe a screening method using Drosophila to identify small molecule compounds that promote heterochromatin formation, with the purpose of developing epigenetic cancer therapeutics. We took advantage of a Drosophila strain with a variegated eye color phenotype that is sensitive to heterochromatin levels, and screened a library of 97 FDA approved oncology drugs. This screen identified methotrexate as the most potent small molecule drug, among the 97 oncology drugs screened, in promoting heterochromatin formation. Interestingly, methotrexate has been identified as a JAK/STAT inhibitor in a functional screen, causing reduced phosphorylation of STAT proteins. These findings are in line with our previous observation that unphosphorylated STAT (uSTAT) promotes heterochromatin formation in both Drosophila and human cells and suppresses tumor growth in mouse xenografts. Thus, Drosophila with variegated eye color phenotypes could be an effective tool for screening heterochromatin-promoting compounds that could be candidates as cancer therapeutics

Polar Mapper: a computational tool for integrated visualization of protein interaction networks and mRNA expression data

Polar Mapper is a computational application for exposing the architecture of protein interaction networks. It facilitates the system-level analysis of mRNA expression data in the context of the underlying protein interaction network. Preliminary analysis of a human protein interaction network and comparison of yeast oxidative stress and heat shock gene expression responses are addressed as case studies

Computer Vision Datasets and Models Exhibit Cultural and Linguistic Diversity in Perception

Computer vision often treats human perception as homogeneous: an implicit assumption that visual stimuli are perceived similarly by everyone. This assumption is reflected in the way researchers collect datasets and train vision models. By contrast, literature in cross-cultural psychology and linguistics has provided evidence that people from different cultural backgrounds observe vastly different concepts even when viewing the same visual stimuli. In this paper, we study how these differences manifest themselves in vision-language datasets and models, using language as a proxy for culture. By comparing textual descriptions generated across 7 languages for the same images, we find significant differences in the semantic content and linguistic expression. When datasets are multilingual as opposed to monolingual, descriptions have higher semantic coverage on average, where coverage is measured using scene graphs, model embeddings, and linguistic taxonomies. For example, multilingual descriptions have on average 29.9% more objects, 24.5% more relations, and 46.0% more attributes than a set of monolingual captions. When prompted to describe images in different languages, popular models (e.g. LLaVA) inherit this bias and describe different parts of the image. Moreover, finetuning models on captions from one language performs best on corresponding test data from that language, while finetuning on multilingual data performs consistently well across all test data compositions. Our work points towards the need to account for and embrace the diversity of human perception in the computer vision community

Cassini in situ observations of long duration magnetic reconnection in Saturn’s magnetotail

Magnetic reconnection is a fundamental process in solar system and astrophysical plasmas, through which stored magnetic energy associated with current sheets is converted into thermal, kinetic and wave energy1, 2, 3, 4. Magnetic reconnection is also thought to be a key process involved in shedding internally produced plasma from the giant magnetospheres at Jupiter and Saturn through topological reconfiguration of the magnetic field5, 6. The region where magnetic fields reconnect is known as the diffusion region and in this letter we report on the first encounter of the Cassini spacecraft with a diffusion region in Saturn’s magnetotail. The data also show evidence of magnetic reconnection over a period of 19?h revealing that reconnection can, in fact, act for prolonged intervals in a rapidly rotating magnetosphere. We show that reconnection can be a significant pathway for internal plasma loss at Saturn6. This counters the view of reconnection as a transient method of internal plasma loss at Saturn5, 7. These results, although directly relating to the magnetosphere of Saturn, have applications in the understanding of other rapidly rotating magnetospheres, including that of Jupiter and other astrophysical bodies

D-Mag: a laboratory for studying plasma physics and diagnostics in strong magnetic fields

We have set up a diagnostic magnet (D-Mag) laboratory for a wide range of applications in plasma physics. It consists of a superconducting magnet for field strengths of up to 5.9 T. The main purpose is to provide an experimental environment for the development of plasma diagnostics for nuclear fusion studies and the investigation of dusty plasmas in strong magnetic fields. We describe in the article the setup and operation of the D-Mag. Some applications are presented for the development of plasma diagnostics, such as neutral pressure gauges and Langmuir probes that have to be operated in strong magnetic fields. Among the examples is the test of the long-pulse capability and stability of the diagnostic pressure gauge (DPG) for the ITER device.Comment: Superconducting Magnet - laboratory for diagnostic development and tests in strong and variable magnetic fields of up to 6 Tesl

Development of a clinical prediction rule to diagnose Pneumocystis jirovecii pneumonia in the World Health Organization’s algorithm for seriously ill HIV-infected patients

Background: The World Health Organization (WHO) algorithm for the diagnosis of tuberculosis in seriously ill HIV-infected patients recommends that treatment for Pneumocystis jirovecii pneumonia (PJP) should be considered without giving clear guidance on selecting patients for empiric PJP therapy. PJP is a common cause of hospitalisation in HIV-infected patients in resource-poor settings where diagnostic facilities are limited.Methods: We developed clinical prediction rules for PJP in a prospective cohort of HIVinfected inpatients with WHO danger signs and cough of any duration. The reference standard for PJP was > 1000 copies/mL of P. jirovecii DNA on real-time sputum polymerase chain reaction (PCR). Four potentially predictive variables were selected for regression models: dyspnoea, chest X-ray, haemoglobin and oxygen saturation. Respiratory rate was explored as a replacement for oxygen saturation as pulse oximetry is not always available in resource-poor settings.Results: We enrolled 500 participants. After imputation for missing values, there were 56 PJP outcome events. Dyspnoea was not independently associated with PJP. Oxygen saturation and respiratory rate were inversely correlated. Two clinical prediction rules were developed: chest X-ray possible/likely PJP, haemoglobin ≥ 9 g/dL and either oxygen saturation < 94% or respiratory rate. The area under the receiver operating characteristic curve of the clinical prediction rule models was 0.761 (95% CI 0.683–0.840) for the respiratory rate model and 0.797 (95% CI 0.725–0.868) for the oxygen saturation model. Both models had zero probability for PJP for scores of zero, and positive likelihood ratios exceeded 10 for high scores.Conclusion: We developed simple clinical prediction rules for PJP, which, if externally validated, could assist decision-making in the WHO seriously ill algorithm

States for phase estimation in quantum interferometry

Ramsey interferometry allows the estimation of the phase $\phi$ of rotation of the pseudospin vector of an ensemble of two-state quantum systems. For $\phi$ small, the noise-to-signal ratio scales as the spin-squeezing parameter $\xi$, with $\xi<1$ possible for an entangled ensemble. However states with minimum $\xi$ are not optimal for single-shot measurements of an arbitrary phase. We define a phase-squeezing parameter, $\zeta$, which is an appropriate figure-of-merit for this case. We show that (unlike the states that minimize $\xi$), the states that minimize $\zeta$ can be created by evolving an unentangled state (coherent spin state) by the well-known 2-axis counter-twisting Hamiltonian. We analyse these and other states (for example the maximally entangled state, analogous to the optical "NOON" state $|\psi> = (|N,0>+|0,N>)/\sqrt{2}$) using several different properties, including $\xi$, $\zeta$, the coefficients in the pseudo angular momentum basis (in the three primary directions) and the angular Wigner function $W(\theta,\phi)$. Finally we discuss the experimental options for creating phase squeezed states and doing single-shot phase estimation.Comment: 8 pages and 5 figure