Small polar hits against <i>S. aureus</i>:Screening, initial hit optimization and metabolomic studies

The global prevalence of antibacterial resistance requires new antibacterial drugs with novel chemical scaffolds and modes of action. It is also vital to design compounds with optimal physicochemical properties to permeate the bacterial cell envelope. We described an approach of combining and integrating whole cell screening and metabolomics into early antibacterial drug discovery using a library of small polar compounds. Whole cell screening of a diverse library of small polar compounds against Staphylococcus aureus gave compound 2. Hit expansion was carried out to determine structure–activity relationships. A selection of compounds from this series, together with other screened active compounds, was subjected to an initial metabolomics study to provide a metabolic fingerprint of the mode of action. It was found that compound 2 and its analogues have a different mode of action from some of the known antibacterial compounds tested. This early study highlighted the potential of whole cell screening and metabolomics in early antibacterial drug discovery. Future works will require improving potency and performing orthogonal studies to confirm the modes of action

Space-to-Ground Interactions While Conducting Scientific Fieldwork Under Mars Mission Constraints

The Biologic Analog Science Associated with Lava Terrains (BASALT) project is a 4-year program dedicated to iteratively designing, implementing, and evaluating concepts of operations (ConOps) and supporting capabilities to enable and enhance scientific exploration for future human Mars missions. BASALT incorporates three field deployments during which real (non-simulated) biological and geochemical field science is conducted at two high-fidelity Mars analog locations under simulated Mars mission conditions, including communication de-lays and data transmission limitations. BASALTs primary science objective is to investigate how the redox conditions of altered basaltic environments affect the development of microbial communities in these Mars-relevant settings. Field sites include the active East Rift Zone on the Big Island of Hawaii, reminiscent of early Mars when basaltic volcanism and interaction with water were widespread, and the dormant eastern Snake River Plain in Idaho, similar to present-day Mars where basaltic volcanism is rare and most evidence for volcano-driven hydrothermal activity is relict. BASALTs primary science operations objective is to investigate exploration ConOps and capabilities that facilitate scientific return during human-robotic exploration under Mars mission constraints. Each field deployment consists of ten extravehicular activities (EVAs) on the volcanic flows in which two extravehicular and two intravehicular (IV) crew-members conduct the science while communicating across time delay and under bandwidth constraints with an Earth-based Mission Support Center (MSC) comprised of expert scientists and operators. Communication latencies of 5 and 15-minute one-way light time and low (0.512 Mb/s uplink, 1.54 Mb/s down-link) and high (5.0 Mb/s uplink, 10.0 Mb/s downlink) bandwidth conditions are being evaluated. EVA crewmembers communicate with the MSC via voice and text messaging and provide scientific instrument data, still imagery, video streams, and GPS tracking information. The MSC reviews this data across delay and provides recommendations for presampling and sampling tasks. The scientists used dynamic leaderboards (priority rank-ing lists), to track and rank candidate samples relative to one another and against the science objectives for the current EVA and the overall mission. Updates to the dynamic leaderboards are relayed regularly to the IV crewmembers to provide scientific feedback from Earth and to help minimize crew idle time (time spent waiting for Earth input during which no productive tasks are performed). EVA timelines are strategically designed to enable continuous (delayed) feedback from an Earth-based science team while simultaneously minimizing crew idle time. Such timelines are operationally advantageous, reducing transport costs by eliminating the need for crews to return to the same locations on multiple EVAs while still providing opportunities for recommendations from science experts on Earth, and scientifically advantageous by minimizing the potential for cross-contamination across sites. This paper will highlight the space-to-ground interaction results from the three BASALT field deployments, including planned versus actual EVA time-line data, ground assimilation times (the amount of time available to the MSC to provide input to the crew), and idle time. Furthermore, we describe how these results vary under the different communication latency and bandwidth conditions. Together, these data will provide a basis for guiding and prioritizing capability development for future human exploration missions

Intra-EVA Space-to-Ground Interactions when Conducting Scientific Fieldwork Under Simulated Mars Mission Constraints

The Biologic Analog Science Associated with Lava Terrains (BASALT) project is a four-year program dedicated to iteratively designing, implementing, and evaluating concepts of operations (ConOps) and supporting capabilities to enable and enhance scientific exploration for future human Mars missions. The BASALT project has incorporated three field deployments during which real (non-simulated) biological and geochemical field science have been conducted at two high-fidelity Mars analog locations under simulated Mars mission conditions, including communication delays and data transmission limitations. BASALT's primary Science objective has been to extract basaltic samples for the purpose of investigating how microbial communities and habitability correlate with the physical and geochemical characteristics of chemically altered basalt environments. Field sites include the active East Rift Zone on the Big Island of Hawai'i, reminiscent of early Mars when basaltic volcanism and interaction with water were widespread, and the dormant eastern Snake River Plain in Idaho, similar to present-day Mars where basaltic volcanism is rare and most evidence for volcano-driven hydrothermal activity is relict. BASALT's primary Science Operations objective has been to investigate exploration ConOps and capabilities that facilitate scientific return during human-robotic exploration under Mars mission constraints. Each field deployment has consisted of ten extravehicular activities (EVAs) on the volcanic flows in which crews of two extravehicular and two intravehicular crewmembers conducted the field science while communicating across time delay and under bandwidth constraints with an Earth-based Mission Support Center (MSC) comprised of expert scientists and operators. Communication latencies of 5 and 15 min one-way light time and low (0.512 Mb/s uplink, 1.54 Mb/s downlink) and high (5.0 Mb/s uplink, 10.0 Mb/s downlink) bandwidth conditions were evaluated. EVA crewmembers communicated with the MSC via voice and text messaging. They also provided scientific instrument data, still imagery, video streams from chest-mounted cameras, GPS location tracking information. The MSC monitored and reviewed incoming data from the field across delay and provided recommendations for pre-sampling and sampling tasks based on their collective expertise. The scientists used dynamic priority ranking lists, referred to as dynamic leaderboards, to track and rank candidate samples relative to one another and against the science objectives for the current EVA and the overall mission. Updates to the dynamic leaderboards throughout the EVA were relayed regularly to the IV crewmembers. The use of these leaderboards enabled the crew to track the dynamic nature of the MSC recommendations and helped minimize crew idle time (defined as time spent waiting for input from Earth during which no other productive tasks are being performed). EVA timelines were strategically designed to enable continuous (delayed) feedback from an Earth-based Science Team while simultaneously minimizing crew idle time. Such timelines are operationally advantageous, reducing transport costs by eliminating the need for crews to return to the same locations on multiple EVAs while still providing opportunities for recommendations from science experts on Earth, and scientifically advantageous by minimizing the potential for cross-contamination across sites. This paper will highlight the space-to-ground interaction results from the three BASALT field deployments, including planned versus actual EVA timeline data, ground assimilation times (defined as the amount of time available to the MSC to provide input to the crew), and idle time. Furthermore, we describe how these results vary under the different communication latency and bandwidth conditions. Together, these data will provide a basis for guiding and prioritizing capability development for future human exploration missions

A hybrid double-dot in silicon

We report electrical measurements of a single arsenic dopant atom in the tunnel-barrier of a silicon SET. As well as performing electrical characterization of the individual dopant, we study series electrical transport through the dopant and SET. We measure the triple points of this hybrid double dot, using simulations to support our results, and show that we can tune the electrostatic coupling between the two sub-systems.Comment: 11 pages, 6 figure

24-Hour Rhythms of DNA Methylation and Their Relation with Rhythms of RNA Expression in the Human Dorsolateral Prefrontal Cortex

Circadian rhythms modulate the biology of many human tissues, including brain tissues, and are driven by a near 24-hour transcriptional feedback loop. These rhythms are paralleled by 24-hour rhythms of large portions of the transcriptome. The role of dynamic DNA methylation in influencing these rhythms is uncertain. While recent work in Neurospora suggests that dynamic site-specific circadian rhythms of DNA methylation may play a role in modulating the fungal molecular clock, such rhythms and their relationship to RNA expression have not, to our knowledge, been elucidated in mammalian tissues, including human brain tissues. We hypothesized that 24-hour rhythms of DNA methylation exist in the human brain, and play a role in driving 24-hour rhythms of RNA expression. We analyzed DNA methylation levels in post-mortem human dorsolateral prefrontal cortex samples from 738 subjects. We assessed for 24-hour rhythmicity of 420,132 DNA methylation sites throughout the genome by considering methylation levels as a function of clock time of death and parameterizing these data using cosine functions. We determined global statistical significance by permutation. We then related rhythms of DNA methylation with rhythms of RNA expression determined by RNA sequencing. We found evidence of significant 24-hour rhythmicity of DNA methylation. Regions near transcription start sites were enriched for high-amplitude rhythmic DNA methylation sites, which were in turn time locked to 24-hour rhythms of RNA expression of nearby genes, with the nadir of methylation preceding peak transcript expression by 1–3 hours. Weak ante-mortem rest-activity rhythms were associated with lower amplitude DNA methylation rhythms as were older age and the presence of Alzheimer's disease. These findings support the hypothesis that 24-hour rhythms of DNA methylation, particularly near transcription start sites, may play a role in driving 24-hour rhythms of gene expression in the human dorsolateral prefrontal cortex, and may be affected by age and Alzheimer's disease

Synergistic drug combinations from electronic health records and gene expression.

ObjectiveUsing electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding.MethodWe applied Group Lasso INTERaction NETwork (glinternet), an overlap group lasso penalty on a logistic regression model, with pairwise interactions to identify variables and interacting drug pairs associated with reduced 5-year mortality using EHRs of 9945 breast cancer patients. We identified differentially expressed genes from 14 case-control human breast cancer gene expression datasets and integrated them with drug-protein networks. Drugs in the network were scored according to their association with breast cancer individually or in pairs. Lastly, we determined whether synergistic drug pairs found in the EHRs were enriched among synergistic drug pairs from gene-expression data using a method similar to gene set enrichment analysis.ResultsFrom EHRs, we discovered 3 drug-class pairs associated with lower mortality: anti-inflammatories and hormone antagonists, anti-inflammatories and lipid modifiers, and lipid modifiers and obstructive airway drugs. The first 2 pairs were also enriched among pairs discovered using gene expression data and are supported by molecular interactions in drug-protein networks and preclinical and epidemiologic evidence.ConclusionsThis is a proof-of-concept study demonstrating that a combination of complementary data sources, such as EHRs and gene expression, can corroborate discoveries and provide mechanistic insight into drug synergism for repurposing

Neighbourhood, Route and Workplace-Related Environmental Characteristics Predict Adults' Mode of Travel to Work

Commuting provides opportunities for regular physical activity which can reduce the risk of chronic disease. Commuters' mode of travel may be shaped by their environment, but understanding of which specific environmental characteristics are most important and might form targets for intervention is limited. This study investigated associations between mode choice and a range of objectively assessed environmental characteristics.Participants in the Commuting and Health in Cambridge study reported where they lived and worked, their usual mode of travel to work and a variety of socio-demographic characteristics. Using geographic information system (GIS) software, 30 exposure variables were produced capturing characteristics of areas around participants' homes and workplaces and their shortest modelled routes to work. Associations between usual mode of travel to work and personal and environmental characteristics were investigated using multinomial logistic regression.Of the 1124 respondents, 50% reported cycling or walking as their usual mode of travel to work. In adjusted analyses, home-work distance was strongly associated with mode choice, particularly for walking. Lower odds of walking or cycling rather than driving were associated with a less frequent bus service (highest versus lowest tertile: walking OR 0.61 [95% CI 0.20–1.85]; cycling OR 0.43 [95% CI 0.23–0.83]), low street connectivity (OR 0.22, [0.07–0.67]; OR 0.48 [0.26–0.90]) and free car parking at work (OR 0.24 [0.10–0.59]; OR 0.55 [0.32–0.95]). Participants were less likely to cycle if they had access to fewer destinations (leisure facilities, shops and schools) close to work (OR 0.36 [0.21–0.62]) and a railway station further from home (OR 0.53 [0.30–0.93]). Covariates strongly predicted travel mode (pseudo r-squared 0.74).Potentially modifiable environmental characteristics, including workplace car parking, street connectivity and access to public transport, are associated with travel mode choice, and could be addressed as part of transport policy and infrastructural interventions to promote active commuting