The Dust in M31

We have analysed Herschel observations of M31, using the PPMAP procedure. The resolution of PPMAP images is sufficient (31 pc on M31) that we can analyse far-IR dust emission on the scale of Giant Molecular Clouds. By comparing PPMAP estimates of the far-IR emission optical depth at 300 microns (tau_300), and the near-IR extinction optical depth at 1.1 microns (tau_1.1) obtained from the reddening of RGB stars, we show that the ratio R_OBS.tau = tau_1.1/tau_300 falls in the range 500 to 1500. Such low values are incompatible with many commonly used theoretical dust models, which predict values of R_MODEL.kappa = kappa_1.1/kappa_300 (where kappa is the dust opacity coefficient) in the range 2500 to 4000. That is, unless a large fraction, at least 60%, of the dust emitting at 300 microns is in such compact sources that they are unlikely to intercept the lines of sight to a distributed population like RGB stars. This is not a new result: variants obtained using different observations and/or different wavelengths have already been reported by other studies. We present two analytic arguments for why it is unlikely that at least 60% of the emitting dust is in sufficiently compact sources. Therefore it may be necessary to explore the possibility that the discrepancy between observed values of R_OBS.tau and theoretical values of R_MODEL.kappa is due to limitations in existing dust models. PPMAP also allows us to derive optical-depth weighted mean values for the emissivity index, beta = - dln(kappa_lambda)/dln(lambda), and the dust temperature, T, denoted betabar and Tbar. We show that, in M31, R_OBS.tau is anti-correlated with betabar according to R_OBS.tau = 2042(+/-24)-557(+/-10)betabar. If confirmed, this provides a challenging constraint on the nature of interstellar dust in M31.Comment: 17 pages, 8 figures, 3 table

Long-term monitoring of wildlife populations for protected area management in Southeast Asia

Long-term monitoring of biodiversity in protected areas (PAs) is critical to assess threats, link conservation action to species outcomes, and facilitate improved management. Yet, rigorous longitudinal monitoring within PAs is rare. In Southeast Asia (SEA), there is a paucity of long-term wildlife monitoring within PAs, and many threatened species lack population estimates from anywhere in their range, making global assessments difficult. Here, we present new abundance estimates and population trends for 11 species between 2010 and 2020, and spatial distributions for 7 species, based on long-term line transect distance sampling surveys in Keo Seima Wildlife Sanctuary in Cambodia. These represent the first robust population estimates for four threatened species from anywhere in their range and are among the first long-term wildlife population trend analyses from the entire SEA region. Our study revealed that arboreal primates and green peafowl (Pavo muticus) generally had either stable or increasing population trends, whereas ungulates and semiarboreal primates generally had declining trends. These results suggest that ground-based threats, such as snares and domestic dogs, are having serious negative effects on terrestrial species. These findings have important conservation implications for PAs across SEA that face similar threats yet lack reliable monitoring data

Experimentally assessing the effect of search effort on snare detectability

Reducing threats to biodiversity is the key objective of ranger patrols in protected areas. However, efforts can be hampered by rangers' inability to detect threats, and poor understanding of threat abundance and distribution in a landscape. Snares are particularly problematic due to their cryptic nature and limited selectivity with respect to captured animals' species, sex, or age. Using an experimental approach, we investigated the effect of search effort, habitat, season, and team on rangers' detection of snares in a tropical forest landscape. We provide an effort-detection curve, and use our findings to make preliminary predictions about snare detection under different scenarios of patrol effort. Results suggest that the overall probability of a searcher detecting any given snare in a 0.25/km2 area, assuming 60 min (or approximately 2 km) of search effort is 20% (95% CI ± 15–25%), with no significant effect of season, habitat or team. Our models suggested this would increase by approximately 10% with an additional 30mins/1 km of search effort. Our preliminary predictions of the effectiveness of different patrolling scenarios show that detection opportunities are maximised at low effort levels by deploying multiple teams to a single area, but at high effort levels deploying single teams becomes more efficient. Our results suggest that snare detectability in tropical forest landscapes is likely to be low, and may not improve dramatically with increased search effort. Given this, managers need to consider whether intensive snare-removal efforts are the best use of limited resources; the answer will depend on their underlying objectives

Estimating hunting prevalence and wild meat reliance in Cambodia’s Eastern Plains

Hunting is a primary driver of biodiversity loss across South-east Asia. Within Cambodia, the use of wire snares to capture wildlife is a severe threat in protected areas but there have been few studies of the behaviour of hunters from local communities. Here, we combine the unmatched count technique with direct questioning to estimate the prevalence of hunting behaviours and wildlife consumption amongst 705 households living within Keo Seima Wildlife Sanctuary, Cambodia. We assessed respondents’ knowledge of rules, and their perceptions of patrols responsible for enforcing rules. Estimates of hunting behaviour were variable: results from the unmatched count technique were inconclusive, and direct questioning revealed 9% of households hunted, and 20% set snares around farms to prevent wildlife eating crops. Hunting with domestic dogs was the method most commonly used to catch wildlife (87% of households owned dogs). Wild meat was consumed by 84% of households, and was most frequently bought or caught, but also gifted. We detected a high awareness of conservation rules, but low awareness of punishments and penalties, with wildlife depletion, rather than the risk of being caught by patrols, causing the greatest reduction in hunting. Our findings demonstrate the challenges associated with reliably estimating rule-breaking behaviour and highlight the need to incorporate careful triangulation into study design

COVID-19: combining antiviral and anti-inflammatory treatments

Both coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome (SARS) are characterised by an overexuberant inflammatory response and, for SARS, viral load is not correlated with the worsening of symptoms. In our previous Correspondence to The Lancet, we described how BenevolentAI's proprietary artificial intelligence (AI)-derived knowledge graph, queried by a suite of algorithms, enabled identification of a target and a potential therapeutic against SARS coronavirus 2 (SARS-CoV-2; the causative organism in COVID-19). We identified a group of approved drugs that could inhibit clathrin-mediated endocytosis and thereby inhibit viral infection of cells (appendix). The drug targets are members of the numb-associated kinase (NAK) family—including AAK1 and GAK—the inhibition of which has been shown to reduce viral infection in vitro. Baricitinib was identified as a NAK inhibitor, with a particularly high affinity for AAK1, a pivotal regulator of clathrin-mediated endocytosis. We suggested that this drug could be of use in countering SARS-CoV-2 infections, subject to appropriate clinical testing. To take this work further in a short timescale, a necessity when dealing with a new human pathogen, we re-examined the affinity and selectivity of all the approved drugs in our knowledge graph to identify those with both antiviral and anti-inflammatory properties. Such drugs are predicted to be of particular importance in the treatment of severe cases of COVID-19, when the host inflammatory response becomes a major cause of lung damage and subsequent mortality. Comparison of the properties of the three best candidates are shown in the table. Baricitinib, fedratinib, and ruxolitinib are potent and selective JAK inhibitors approved for indications such as rheumatoid arthritis and myelofibrosis. All three are powerful anti-inflammatories that, as JAK–STAT signalling inhibitors, are likely to be effective against the consequences of the elevated levels of cytokines (including interferon-γ) typically observed in people with COVID-19·2 Although the three candidates have similar JAK inhibitor potencies, a high affinity for AAK1 suggests baricitinib is the best of the group, especially given its once-daily oral dosing and acceptable side-effect profile.The most significant side-effect seen over 4214 patient-years in the clinical trial programmes used for European Medicines Agency registration was a small increase in upper respiratory tract infections (similar to that observed with methotrexate), but the incidence of serious infections (eg, herpes zoster) over 52 weeks' dosing was small (3·2 per 100 patient-years), and similar to placebo.7 Use of this agent in patients with COVID-19 over 7–14 days, for example, suggests side-effects would be trivial.</p

Baricitinib as potential treatment for 2019-nCoV acute respiratory disease

Given the scale and rapid spread of the 2019 novel coronavirus (2019-nCoV) acute respiratory disease, there is an immediate need for medicines that can help before a vaccine can be produced. Results of rapid sequencing of 2019-nCoV, coupled with molecular modelling based on the genomes of related virus proteins,1 have suggested a few compounds that are likely to be effective, including the anti-HIV lopinavir plus ritonavir combination...</p