A Study of Water-Soluble Inhibitory Compounds (Algicides) Produced by Fresh-Water Algae

A complex system of growth inhibitors was observed in the green algae (Volvocaceae). Inhibitors were found in the culture filtrates of some genera which limit their own growth (autoinhibitors) while others in the family produce substances which check the growth of other genera (heteroinhibitors). These inhibitors were destroyed by autoclaving. It was decided that Pandorina morum, which produced the strongest inhibitor and Volvox tertius, the most sensitive to the inhibitor would make an excellent model system for a study of the chemical and physical properties of these naturally occurring algicides. The algicide could be removed from actively growing cultures about the 12th day after inoculation and maximum inhibition was recorded for the next 18 days. The substance could be diluted several times with the retention of at least partial activity. The inhibitor was relatively stable to high temperatures, moved slowly through a dialysis membrane and possessed anti-bacterial properties in that it inhibited the growth of Staphylococcus aureus. The material was relatively stable when exposed to acid, although exposure to a pH of 2.0 for 30 minutes did destroy most of the activity. The substance was soluble in benzene and chloroform. All attempts to degrade or destroy the inhibitor with the common proteolytic enzymes (trypsin, chymotrypsin and pronase) proved unsuccessful, suggesting the substance is not proteinaceous in nature. In experiments with G-25 and G-50 Sephadex, the inhibitor was retained on the column, indicating a molecular weight of less than 5000. The Clark type oxygen electrode revealed that the inhibitor greatly reduced photosynthetic rates in Volvox. A 65% reduction in the rate of photosynthesis was observed after several minutes exposure to medium in which Pandorina morum had been growing. Respiration rates were apparently unaffected

Covering problems in edge- and node-weighted graphs

This paper discusses the graph covering problem in which a set of edges in an edge- and node-weighted graph is chosen to satisfy some covering constraints while minimizing the sum of the weights. In this problem, because of the large integrality gap of a natural linear programming (LP) relaxation, LP rounding algorithms based on the relaxation yield poor performance. Here we propose a stronger LP relaxation for the graph covering problem. The proposed relaxation is applied to designing primal-dual algorithms for two fundamental graph covering problems: the prize-collecting edge dominating set problem and the multicut problem in trees. Our algorithms are an exact polynomial-time algorithm for the former problem, and a 2-approximation algorithm for the latter problem, respectively. These results match the currently known best results for purely edge-weighted graphs.Comment: To appear in SWAT 201

Glycan shield of the ebolavirus envelope glycoprotein GP

The envelope glycoprotein GP of the ebolaviruses is essential for host cell entry and the primary target of the host antibody response. GP is heavily glycosylated with up to 17 N-linked sites, numerous O-linked glycans in its disordered mucin-like domain (MLD), and three predicted C-linked mannosylation sites. Glycosylation is important for host cell attachment, GP stability and fusion activity, and shielding from neutralization by serum antibodies. Here, we use glycoproteomics to profile the site-specific glycosylation patterns of ebolavirus GP. We detect up to 16 unique O-linked glycosylation sites in the MLD, and two O-linked sites in the receptor-binding GP1 subunit. Multiple O-linked glycans are observed within N-linked glycosylation sequons, suggesting crosstalk between the two types of modifications. We confirmed C-mannosylation of W288 in full-length trimeric GP. We find complex glycosylation at the majority of N-linked sites, while the conserved sites N257 and especially N563 are enriched in unprocessed glycans, suggesting a role in host-cell attachment via DC-SIGN/L-SIGN. Our findings illustrate how N-, O-, and C-linked glycans together build the heterogeneous glycan shield of GP, guiding future immunological studies and functional interpretation of ebolavirus GP-antibody interactions

Mining Mini-Halos with MeerKAT I. Calibration and Imaging

Radio mini-halos are clouds of diffuse, low surface brightness synchrotron emission that surround the Brightest Cluster Galaxy (BCG) in massive cool-core galaxy clusters. In this paper, we use third generation calibration (3GC), also called direction-dependent (DD) calibration, and point source subtraction on MeerKAT extragalactic continuum data. We calibrate and image archival MeerKAT L-band observations of a sample of five galaxy clusters (ACO 1413, ACO 1795, ACO 3444, MACS J1115.8+0129, MACS J2140.2-2339). We use the CARACal pipeline for direction-independent (DI) calibration, DDFacet and killMS for 3GC, followed by visibility-plane point source subtraction to image the underlying mini-halo without bias from any embedded sources. Our 3GC process shows a drastic improvement in artefact removal, to the extent that the local noise around severely affected sources was halved and ultimately resulted in a 7\% improvement in global image noise. Thereafter, using these spectrally deconvolved Stokes I continuum images, we directly measure for four mini-halos the flux density, radio power, size and in-band integrated spectra. Further to that, we show the in-band spectral index maps of the mini-halo (with point sources). We present a new mini-halo detection hosted by MACS J2140.2-2339, having flux density $S_{\rm 1.28\,GHz} = 2.61 \pm 0.31$ mJy, average diameter 296 kpc and $\alpha^{\rm 1.5\,GHz}_{\rm 1\,GHz} = 1.21 \pm 0.36$. We also found a $\sim$100 kpc southern extension to the ACO 3444 mini-halo which was not detected in previous VLA L-band observations. Our description of MeerKAT wide-field, wide-band data reduction will be instructive for conducting further mini-halo science.Comment: 16 pages. 10 figure

A comparison of South African national HIV incidence estimates: A critical appraisal of different methods

BACKGROUND: The interpretation of HIV prevalence trends is increasingly difficult as antiretroviral treatment programs expand. Reliable HIV incidence estimates are critical to monitoring transmission trends and guiding an effective national response to the epidemic. Methods and FINDINGS: We used a range of methods to estimate HIV incidence in South Africa: (i) an incidence testing algorithm applying the Limiting-Antigen Avidity Assay (LAg-Avidity EIA) in combination with antiretroviral drug and HIV viral load testing; (ii) a modelling technique based on the synthetic cohort principle; and (iii) two dynamic mathematical models, the EPP/Spectrum model package and the Thembisa model. Overall, the different incidence estimation methods were in broad agreement on HIV incidence estimates among persons aged 15-49 years in 2012. The assay-based method produced slightly higher estimates of incidence, 1.72% (95% CI 1.38 - 2.06), compared with the mathematical models, 1.47% (95% CI 1.23 - 1.72) in Thembisa and 1.52% (95% CI 1.43 - 1.62) in EPP/Spectrum, and slightly lower estimates of incidence compared to the synthetic cohort, 1.9% (95% CI 0.8 - 3.1) over the period from 2008 to 2012. Among youth aged 15-24 years, a declining trend in HIV incidence was estimated by all three mathematical estimation methods. CONCLUSIONS: The multi-method comparison showed similar levels and trends in HIV incidence and validated the estimates provided by the assay-based incidence testing algorithm. Our results confirm that South Africa is the country with the largest number of new HIV infections in the world, with about 1 000 new infections occurring each day among adults aged 15-49 years in 2012

A MeerKAT view on galaxy clusters: a radio-optical study of Abell 1300 and MACS J1931.8--2634

In this paper we present results from a radio-optical study of the galaxy populations of the galaxy clusters Abell 1300 and MACS J1931.8$-$2634, a merger and a relaxed system respectively both located at $z \sim 0.3$, aimed at finding evidence of merger-induced radio emission. Radio observations are taken at 1.28 GHz with the MeerKAT interferometer during its early-stage commissioning phase, and combined with archive optical data. We generated catalogues containing 107 and 162 radio sources in the A$~$1300 and MACS J1931.8--2634 cluster fields respectively, above a 0.2 mJy threshold and within a 30~arcmin radius from the cluster centre (corresponding to 8.1 and 8.8 Mpc respectively). By cross-correlating the radio and optical catalogues, and including spectroscopic information, 9 and 6 sources were found to be cluster members and used to construct the radio luminosity functions respectively for both clusters. The comparison of the radio source catalogues between the two cluster fields leads to a marginal difference, with a $2\sigma$ statistical significance. We derived the radio luminosity function at 1.28 GHz in both clusters, in the power range $22.81 < \rm {log~P_{1.28~GHz}~(W/Hz)} < 25.95$, and obtained that in A 1300 the radio luminosity function averaged over the full radio power interval is only $3.3 \pm 1.9$ times higher than the MACS J1931.8--2634 one, suggesting no statistical difference in their probability to host nuclear radio emission. We conclude that, at least for the two clusters studied here, the role of cluster mergers in affecting the statistical properties of the radio galaxy population is negligible.Comment: 18 pages, 8 figures, MNRAS accepte

ChatGPT and Bard Responses to Polarizing Questions

Recent developments in natural language processing have demonstrated the potential of large language models (LLMs) to improve a range of educational and learning outcomes. Of recent chatbots based on LLMs, ChatGPT and Bard have made it clear that artificial intelligence (AI) technology will have significant implications on the way we obtain and search for information. However, these tools sometimes produce text that is convincing, but often incorrect, known as hallucinations. As such, their use can distort scientific facts and spread misinformation. To counter polarizing responses on these tools, it is critical to provide an overview of such responses so stakeholders can determine which topics tend to produce more contentious responses -- key to developing targeted regulatory policy and interventions. In addition, there currently exists no annotated dataset of ChatGPT and Bard responses around possibly polarizing topics, central to the above aims. We address the indicated issues through the following contribution: Focusing on highly polarizing topics in the US, we created and described a dataset of ChatGPT and Bard responses. Broadly, our results indicated a left-leaning bias for both ChatGPT and Bard, with Bard more likely to provide responses around polarizing topics. Bard seemed to have fewer guardrails around controversial topics, and appeared more willing to provide comprehensive, and somewhat human-like responses. Bard may thus be more likely abused by malicious actors. Stakeholders may utilize our findings to mitigate misinformative and/or polarizing responses from LLM