sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

Background: Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. Results: This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. Conclusions: The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMapComment: 3 pages, 1 table, 1 eps figur

Single-cell landscape in mammary epithelium reveals bipotent-like cells associated with breast cancer risk and outcome

Adult stem-cells may serve as the cell-of-origin for cancer, yet their unbiased identification in single cell RNA sequencing data is challenging due to the high dropout rate. In the case of breast, the existence of a bipotent stem-like state is also controversial. Here we apply a marker-free algorithm to scRNA-Seq data from the human mammary epithelium, revealing a high-potency cell-state enriched for an independent mammary stem-cell expression module. We validate this stem-like state in independent scRNA-Seq data. Our algorithm further predicts that the stem-like state is bipotent, a prediction we are able to validate using FACS sorted bulk expression data. The bipotent stem-like state correlates with clinical outcome in basal breast cancer and is characterized by overexpression of YBX1 and ENO1, two modulators of basal breast cancer risk. This study illustrates the power of a marker-free computational framework to identify a novel bipotent stem-like state in the mammary epithelium

SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification.

BACKGROUND: Black-box skepticism is one of the main hindrances impeding deep-learning-based automatic sleep scoring from being used in clinical environments. METHODS: Towards interpretability, this work proposes a sequence-to-sequence sleep staging model, namely SleepTransformer. It is based on the transformer backbone and offers interpretability of the models decisions at both the epoch and sequence level. We further propose a simple yet efficient method to quantify uncertainty in the models decisions. The method, which is based on entropy, can serve as a metric for deferring low-confidence epochs to a human expert for further inspection. RESULTS: Making sense of the transformers self-attention scores for interpretability, at the epoch level, the attention scores are encoded as a heat map to highlight sleep-relevant features captured from the input EEG signal. At the sequence level, the attention scores are visualized as the influence of different neighboring epochs in an input sequence (i.e. the context) to recognition of a target epoch, mimicking the way manual scoring is done by human experts. CONCLUSION: Additionally, we demonstrate that SleepTransformer performs on par with existing methods on two databases of different sizes. SIGNIFICANCE: Equipped with interpretability and the ability of uncertainty quantification, SleepTransformer holds promise for being integrated into clinical settings

A simple and robust method for connecting small-molecule drugs using gene-expression signatures

Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties. The Connectivity Map was a novel concept and innovative tool first introduced by Lamb et al to connect small molecules, genes, and diseases using genomic signatures [Lamb et al (2006), Science 313, 1929-1935]. However, the Connectivity Map had some limitations, particularly there was no effective safeguard against false connections if the observed connections were considered on an individual-by-individual basis. Further when several connections to the same small-molecule compound were viewed as a set, the implicit null hypothesis tested was not the most relevant one for the discovery of real connections. Here we propose a simple and robust method for constructing the reference gene-expression profiles and a new connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with the two example gene-signatures (HDAC inhibitors and Estrogens) used by Lamb et al and also a new gene signature of immunosuppressive drugs. Our testing with this new method shows that it achieves a higher level of specificity and sensitivity than the original method. For example, our method successfully identified raloxifene and tamoxifen as having significant anti-estrogen effects, while Lamb et al's Connectivity Map failed to identify these. With these properties our new method has potential use in drug development for the recognition of pharmacological and toxicological properties in new drug candidates.Comment: 8 pages, 2 figures, and 2 tables; supplementary data supplied as a ZIP fil

AtPAP2 modulates the import of the small subunit of Rubisco into chloroplasts

published_or_final_versio

Natural killer cells attenuate cytomegalovirus-induced hearing loss in mice

<div><p>Congenital cytomegalovirus (CMV) infection is the most common non-hereditary cause of sensorineural hearing loss (SNHL) yet the mechanisms of hearing loss remain obscure. Natural Killer (NK) cells play a critical role in regulating murine CMV infection via NK cell recognition of the Ly49H cell surface receptor of the viral-encoded m157 ligand expressed at the infected cell surface. This Ly49H NK receptor/m157 ligand interaction has been found to mediate host resistance to CMV in the spleen, and lung, but is much less effective in the liver, so it is not known if this interaction is important in the context of SNHL. Using a murine model for CMV-induced labyrinthitis, we have demonstrated that the Ly49H/m157 interaction mediates host resistance in the temporal bone. BALB/c mice, which lack functional Ly49H, inoculated with mCMV at post-natal day 3 developed profound hearing loss and significant outer hair cell loss by 28 days of life. In contrast, C57BL/6 mice, competent for the Ly49H/m157 interaction, had minimal hearing loss and attenuated outer hair cell loss with the same mCMV dose. Administration of Ly49H blocking antibody or inoculation with a mCMV viral strain deleted for the m157 gene rendered the previously resistant C57BL/6 mouse strain susceptible to hearing loss to a similar extent as the BALB/c mouse strain indicating a direct role of the Ly49H/m157 interaction in mCMV-dependent hearing loss. Additionally, NK cell recruitment to sites of infection was evident in the temporal bone of inoculated susceptible mouse strains. These results demonstrate participation of NK cells in protection from CMV-induced labyrinthitis and SNHL in mice.</p></div

Social support and sense of loneliness in solitary older adults

Older people are vulnerable to loneliness and isolation. Solitary seniors are more likely to suffer the feelings of loneliness with inadequate social networks. Based on a face-to-face questionnaire survey with 151 community-dwelling solitary seniors, the present study examined the associations between social support and the sense of loneliness among solitary older adults in Hong Kong. The results showed that poor mental health status, financial inadequacy and weak social support networks were significantly associated with the sense of loneliness of solitary older adults, with social support being the most prominent risk factor. Frequent contacts with siblings, relatives or friends were found to be important sources of social support to combat loneliness. Policy and service implications are discussed

Characterization and Comparison of 2 Distinct Epidemic Community-Associated Methicillin-Resistant Staphylococcus aureus Clones of ST59 Lineage.

Sequence type (ST) 59 is an epidemic lineage of community-associated (CA) methicillin-resistant Staphylococcus aureus (MRSA) isolates. Taiwanese CA-MRSA isolates belong to ST59 and can be grouped into 2 distinct clones, a virulent Taiwan clone and a commensal Asian-Pacific clone. The Taiwan clone carries the Panton-Valentine leukocidin (PVL) genes and the staphylococcal chromosomal cassette mec (SCCmec) VT, and is frequently isolated from patients with severe disease. The Asian-Pacific clone is PVL-negative, carries SCCmec IV, and a frequent colonizer of healthy children. Isolates of both clones were characterized by their ability to adhere to respiratory A549 cells, cytotoxicity to human neutrophils, and nasal colonization of a murine and murine sepsis models. Genome variation was determined by polymerase chain reaction of selected virulence factors and by multi-strain whole genome microarray. Additionally, the expression of selected factors was compared between the 2 clones. The Taiwan clone showed a much higher cytotoxicity to the human neutrophils and caused more severe septic infections with a high mortality rate in the murine model. The clones were indistinguishable in their adhesion to A549 cells and persistence of murine nasal colonization. The microarray data revealed that the Taiwan clone had lost the ø3-prophage that integrates into the β-hemolysin gene and includes staphylokinase- and enterotoxin P-encoding genes, but had retained the genes for human immune evasion, scn and chps. Production of the virulence factors did not differ significantly in the 2 clonal groups, although more α-toxin was expressed in Taiwan clone isolates from pneumonia patients. In conclusion, the Taiwan CA-MRSA clone was distinguished by enhanced virulence in both humans and an animal infection model. The evolutionary acquisition of PVL, the higher expression of α-toxin, and possibly the loss of a large portion of the β-hemolysin-converting prophage likely contribute to its higher pathogenic potential than the Asian-Pacific clone

Measuring Phases of Employment Decision-Making and the Need for Vocational Services as a Social Determinant of the Health of Employed People Living with HIV

(1) Background: Secure employment has been recognized as a social determinant of health for people living with HIV (PLHIV), but limited research has been conducted to understand the employment needs and vocational decision-making process of those who are employed. The purpose of this study is to examine the applicability of the client-focused considering-work model to assess the employment outcomes and employment decision-making phases of a sample of employed PLHIV. (2) Methods: This study analyzed data of 244 employed PLHIV who completed National Working Positive Coalition’s Employment Needs Survey which included a 20-item Considering Work Scale- Employed version (CWS-Employed) and a single-item Classification of Employment Status Scale (CESS). Factor analysis was used to evaluate the CWS-Employed. Chi-square tests of homogeneity of proportions were conducted to assess the domain-specific needs of individuals in each phase of employment decision-making. (3) Results: Our findings revealed high rates of insecure employment and diverse vocational service needs among research participants. Additionally, the CWS-Employed accurately predicted 71% of the self-reported classification of phases of employment decision-making. (4) Conclusions: When investigating the role of employment as a social determinant of health, more research is needed to better understand the vocational needs and outcomes of PLHIV who are working. Improving the measurement of the phases of employment decision-making is needed to better identify appropriate vocational interventions that can lead to improved employment and related health outcomes for this population