Pathways for the Oxidation of Sarin in Urban Atmospheres

Terrorists have threatened and carried out chemicalhiological agent attacks on targets in major cities. The nerve agent sarin figured prominently in one well-publicized incident. Vapors disseminating from open containers in a Tokyo subway caused thousands of casualties. High-resolution tracer transport modeling of agent dispersion is at hand and will be enhanced by data on reactions with components of the urban atmosphere. As a sample of the level of complexity currently attainable, we elaborate the mechanisms by which sarin can decompose in polluted air. A release scenario is outlined involving the passage of a gas-phase agent through a city locale in the daytime. The atmospheric chemistry database on related organophosphorus pesticides is mined for rate and product information. The hydroxyl,radical and fine-mode particles are identified as major reactants. A review of urban air chernistry/rnicrophysics generates concentration tables for major oxidant and aerosol types in both clean and dirty environments. Organic structure-reactivity relationships yield an upper limit of 10-1' cm3 molecule-' S-* for hydrogen abstraction by hydroxyl. The associated midday loss time scale could be as little as one hour. Product distributions are difficult to define but may include nontoxic organic oxygenates, inorganic phosphorus acids, sarin-like aldehydes, and nitrates preserving cholinergic capabilities. Agent molecules will contact aerosol surfaces in on the order of minutes, with hydrolysis and side-chain oxidation as likely reaction channels

Evaluation of Three Automated Genome Annotations for Halorhabdus utahensis

Genome annotations are accumulating rapidly and depend heavily on automated annotation systems. Many genome centers offer annotation systems but no one has compared their output in a systematic way to determine accuracy and inherent errors. Errors in the annotations are routinely deposited in databases such as NCBI and used to validate subsequent annotation errors. We submitted the genome sequence of halophilic archaeon Halorhabdus utahensis to be analyzed by three genome annotation services. We have examined the output from each service in a variety of ways in order to compare the methodology and effectiveness of the annotations, as well as to explore the genes, pathways, and physiology of the previously unannotated genome. The annotation services differ considerably in gene calls, features, and ease of use. We had to manually identify the origin of replication and the species-specific consensus ribosome-binding site. Additionally, we conducted laboratory experiments to test H. utahensis growth and enzyme activity. Current annotation practices need to improve in order to more accurately reflect a genome's biological potential. We make specific recommendations that could improve the quality of microbial annotation projects

Changes in time spent on unpaid labor since the woman’s cervical cancer diagnosis stratified by higher SES (A) and lower SES (B).

Changes in time spent on unpaid labor since the woman’s cervical cancer diagnosis stratified by higher SES (A) and lower SES (B).</p

STROBE statement—Checklist of items that should be included in reports of <i>cross-sectional studies</i>.

STROBE statement—Checklist of items that should be included in reports of cross-sectional studies.</p

Indirect costs that women paid out-of-pocket for in the past month by SES.

Indirect costs that women paid out-of-pocket for in the past month by SES.</p

Inclusivity in global research checklist.

There is limited research on how a cervical cancer diagnosis financially impacts women and their families in Uganda. This analysis aimed to describe the economic impact of cervical cancer treatment, including how it differs by socio-economic status (SES) in Uganda. We conducted a cross-sectional study from September 19, 2022 to January 17, 2023. Women were recruited from the Uganda Cancer Institute and Jinja Regional Referral Hospital, and were eligible if they were ≥ of 18 years and being treated for cervical cancer. Participants completed a survey that included questions about their out-of-pocket costs, unpaid labor, and family’s economic situation. A wealth index was constructed to determine their SES. Descriptive statistics were reported. Of the 338 participants, 183 were from the lower SES. Women from the lower SES were significantly more likely to be older, have ≤ primary school education, and have a more advanced stage of cervical cancer. Over 90% of participants in both groups reported paying out-of-pocket for cervical cancer. Only 15 participants stopped treatment because they could not afford it. Women of a lower SES were significantly more likely to report borrowing money (higher SES n = 47, 30.5%; lower SES n = 84, 46.4%; p-value = 0.004) and selling possessions (higher SES n = 47, 30.5%; lower SES n = 90, 49.7%; p-value = 0.006) to pay for care. Both SES groups reported a decrease in the amount of time that they spent caring for their children since their cervical cancer diagnosis (higher SES n = 34, 31.2%; lower SES n = 36, 29.8%). Regardless of their SES, women in Uganda incur out-of-pocket costs related to their cervical cancer treatment. However, there are inequities as women from the lower SES groups were more likely to borrow funds to afford treatment. Alternative payment models and further economic support could help alleviate the financial burden of cervical cancer care in Uganda.</div

Participant demographic information by socio-economic status.

Participant demographic information by socio-economic status.</p

Comparison of putative glycoside hydrolase start sites.

<p>Examination of an individual gene displays tendencies of the annotation services. RAST identifies GTG as the start codon for the gene, while IMG and JCVI select two ATG codons at different locations. Predicted start codon affects gene length.</p

Glycolysis/gluconeogenesis pathway.

<p>Diagram based on RAST's KEGG pathway map displays present and absent enzymes for <i>H. utahensis</i>. Green boxes indicate that the enzyme was predicted by RAST and displayed in the KEGG map. Yellow boxes designate enzymes that were called by RAST but had not been added to the KEGG map. Red boxes mark enzymes that were listed as absent and could not be located in the <i>H. utahensis</i> genome.</p

<i>H. utahensis</i> primary contig and ORC/Cdc6 genes.

<p>Circular display of the largest contig of the <i>H. utahensis</i> genome sequence. The contig begins at the top and wraps clockwise. The red bars illustrate the location of ORC/Cdc6 orthologs. The ORC/Cdc6 gene numbered 3 lies near the origin of replication, at 2,327,225 base pairs.</p