Correction: Identifying COVID-19 Outbreaks From Contact-Tracing Interview Forms for Public Health Departments: Development of a Natural Language Processing Pipeline.

[This corrects the article DOI: 10.2196/36119.].

Identifying COVID-19 Outbreaks From Contact-Tracing Interview Forms for Public Health Departments: Development of a Natural Language Processing Pipeline.

BACKGROUND: In Wisconsin, COVID-19 case interview forms contain free-text fields that need to be mined to identify potential outbreaks for targeted policy making. We developed an automated pipeline to ingest the free text into a pretrained neural language model to identify businesses and facilities as outbreaks. OBJECTIVE: We aimed to examine the precision and recall of our natural language processing pipeline against existing outbreaks and potentially new clusters. METHODS: Data on cases of COVID-19 were extracted from the Wisconsin Electronic Disease Surveillance System (WEDSS) for Dane County between July 1, 2020, and June 30, 2021. Features from the case interview forms were fed into a Bidirectional Encoder Representations from Transformers (BERT) model that was fine-tuned for named entity recognition (NER). We also developed a novel location-mapping tool to provide addresses for relevant NER. Precision and recall were measured against manually verified outbreaks and valid addresses in WEDSS. RESULTS: There were 46,798 cases of COVID-19, with 4,183,273 total BERT tokens and 15,051 unique tokens. The recall and precision of the NER tool were 0.67 (95% CI 0.66-0.68) and 0.55 (95% CI 0.54-0.57), respectively. For the location-mapping tool, the recall and precision were 0.93 (95% CI 0.92-0.95) and 0.93 (95% CI 0.92-0.95), respectively. Across monthly intervals, the NER tool identified more potential clusters than were verified in WEDSS. CONCLUSIONS: We developed a novel pipeline of tools that identified existing outbreaks and novel clusters with associated addresses. Our pipeline ingests data from a statewide database and may be deployed to assist local health departments for targeted interventions.

EPR-ENDOR characterization of (17O, 1H, 2H) water in manganese catalase and its relevance to the oxygen-evolving complex of photosystem II.

The synthesis of efficient water-oxidation catalysts demands insight into the only known, naturally occurring water-oxidation catalyst, the oxygen-evolving complex (OEC) of photosystem II (PSII). Understanding the water oxidation mechanism requires knowledge of where and when substrate water binds to the OEC. Mn catalase in its Mn(III)-Mn(IV) state is a protein model of the OEC's S(2) state. From (17)O-labeled water exchanged into the di-µ-oxo di-Mn(III,IV) coordination sphere of Mn catalase, CW Q-band ENDOR spectroscopy revealed two distinctly different (17)O signals incorporated in distinctly different time regimes. First, a signal appearing after 2 h of (17)O exchange was detected with a 13.0 MHz hyperfine coupling. From similarity in the time scale of isotope incorporation and in the (17)O µ-oxo hyperfine coupling of the di-µ-oxo di-Mn(III,IV) bipyridine model (Usov, O. M.; Grigoryants, V. M.; Tagore, R.; Brudvig, G. W.; Scholes, C. P. J. Am. Chem. Soc. 2007, 129, 11886-11887), this signal was assigned to µ-oxo oxygen. EPR line broadening was obvious from this (17)O µ-oxo species. Earlier exchange proceeded on the minute or faster time scale into a non-µ-oxo position, from which (17)O ENDOR showed a smaller 3.8 MHz hyperfine coupling and possible quadrupole splittings, indicating a terminal water of Mn(III). Exchangeable proton/deuteron hyperfine couplings, consistent with terminal water ligation to Mn(III), also appeared. Q-band CW ENDOR from the S(2) state of the OEC was obtained following multihour (17)O exchange, which showed a (17)O hyperfine signal with a 11 MHz hyperfine coupling, tentatively assigned as µ-oxo-(17)O by resemblance to the µ-oxo signals from Mn catalase and the di-µ-oxo di-Mn(III,IV) bipyridine model.

Chloride regulation of enzyme turnover: application to the role of chloride in photosystem II.

Chloride-dependent α-amylases, angiotensin-converting enzyme (ACE), and photosystem II (PSII) are activated by bound chloride. Chloride-binding sites in these enzymes contain a positively charged Arg or Lys residue crucial for chloride binding. In α-amylases and ACE, removal of chloride from the binding site triggers formation of a salt bridge between the positively charged Arg or Lys residue involved in chloride binding and a nearby carboxylate residue. The mechanism for chloride activation in ACE and chloride-dependent α-amylases is 2-fold: (i) correctly positioning catalytic residues or other residues involved in stabilizing the enzyme-substrate complex and (ii) fine-tuning of the pKa of a catalytic residue. By using examples of how chloride activates α-amylases and ACE, we can gain insight into the potential mechanisms by which chloride functions in PSII. Recent structural evidence from cyanobacterial PSII indicates that there is at least one chloride-binding site in the vicinity of the oxygen-evolving complex (OEC). Here we propose that, in the absence of chloride, a salt bridge between D2:K317 and D1:D61 (and/or D1:E333) is formed. This can cause a conformational shift of D1:D61 and lower the pKa of this residue, making it an inefficient proton acceptor during the S-state cycle. Movement of the D1:E333 ligand and the adjacent D1:H332 ligand due to chloride removal could also explain the observed change in the magnetic properties of the manganese cluster in the OEC upon chloride depletion.

Substrate water binding and oxidation in photosystem II.

This mini review presents a general introduction to photosystem II with an emphasis on the oxygen evolving complex. An attempt is made to summarise what is currently known about substrate interaction in the oxygen evolving complex of photosystem II in terms of the nature of the substrate, the timing and the location of its binding. As the nature of substrate water binding has a direct bearing on the mechanism of O-O bond formation in PSII, a discussion of O-O bond formation follows the summary of current opinion in substrate interaction.