A role for the ATP-dependent DNA ligase lig E of Neisseria gonorrhoeae in biofilm formation.

BACKGROUND: The ATP-dependent DNA ligase Lig E is present as an accessory DNA ligase in numerous proteobacterial genomes, including many disease-causing species. Here we have constructed a genomic Lig E knock-out in the obligate human pathogen Neisseria gonorrhoeae and characterised its growth and infection phenotype. RESULTS: This demonstrates that N. gonorrhoeae Lig E is a non-essential gene and its deletion does not cause defects in replication or survival of DNA-damaging stressors. Knock-out strains were partially defective in biofilm formation on an artificial surface as well as adhesion to epithelial cells. In addition to in vivo characterisation, we have recombinantly expressed and assayed N. gonorrhoeae Lig E and determined the crystal structure of the enzyme-adenylate engaged with DNA substrate in an open non-catalytic conformation. CONCLUSIONS: These findings, coupled with the predicted extracellular/ periplasmic location of Lig E indicates a role in extracellular DNA joining as well as providing insight into the binding dynamics of these minimal DNA ligases.

Characterization and Exploration of Placket-Burman-Designed Porous Calcium Carbonate (Vaterite) Microparticles.

The objective of the research was to identify significant variables that impact the porosity-related properties of CaCO3 particles. The Placket-Burman design was employed to screen multiple variables, including pH, molar concentrations of calcium chloride and sodium carbonate, temperature, concentration of Gelucire 44/14, Cremophor RH40, Solutol HS15, Labrasol, mixing rate, reaction time, and order of addition. The response variables were surface area, pore radius, and pore volume. Influential methodologies such as XRD, FTIR, Raman spectroscopy, and TGA were utilized to validate the precipitate type. The BET surface area ranged from 1.5 to 16.14 m2/g, while the pore radius varied from 2.62 to 6.68 nm, and the pore volume exhibited a range of 2.43 to 37.97 cc/gm. Vaterite structures with spherical mesoporous characteristics were observed at high pH, whereas calcite formations occurred at low pH. The order of addition impacted the surface area but did not affect the pore volume. To maximize the surface area, a lower reaction time and molar concentrations of sodium carbonate were found to be advantageous. The pore radius was influenced by the pH, surfactants, and reaction conditions. The sediments were categorized based on the percentage of vaterite formation. The instrumental techniques effectively characterized the precipitates and provided a valuable complementary analysis.

Biopolymer-Capped Pyrazinamide-Loaded Colloidosomes: In Vitro Characterization and Bioavailability Studies.

This study aimed to prepare colloidosome particles loaded with pyrazinamide (PZA). These drug-loaded colloidosomes were prepared using an in situ gelation technique using a central composite design with a shell made of calcium carbonate (CaCO3) particles. Optimal amounts of 150 mg of CaCO3, sodium alginate (2%), and 400 mg of poly(3-hydroxybutyrate-co-3-hydroxy valerate) (PHBV) concentration resulted in the maximum drug loading and efficient release profile. Field emission scanning electron microscopy results showed spherical porous particles with a good coating of the PHBV polymer. Additionally, Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), thermogravimetric and differential thermal analysis (TGA-DTA), and X-ray diffraction (XRD) analysis showed good compatibility between the drug and excipients. The pharmacokinetic studies demonstrated that the drug-loaded colloidosomes resulted in 4.26 times higher plasma drug concentrations with Cmax values of 32.386 ± 2.744 mcg/mL (PZA solution) and 115.868 ± 53.581 mcg/mL (PZA-loaded colloidosomes) and AUC0-t values of 61.24 mcg-h/mL (PZA solution) and 260.9 mcg-h/mL (PZA-loaded colloidosomes), indicating that colloidosomes have the potential to be effective drug carriers for delivering PZA to the target site.

Sentinel Surveillance System Implementation and Evaluation for SARS-CoV-2 Genomic Data, Washington, USA, 2020-2021.

Genomic data provides useful information for public health practice, particularly when combined with epidemiologic data. However, sampling bias is a concern because inferences from nonrandom data can be misleading. In March 2021, the Washington State Department of Health, USA, partnered with submitting and sequencing laboratories to establish sentinel surveillance for SARS-CoV-2 genomic data. We analyzed available genomic and epidemiologic data during presentinel and sentinel periods to assess representativeness and timeliness of availability. Genomic data during the presentinel period was largely unrepresentative of all COVID-19 cases. Data available during the sentinel period improved representativeness for age, death from COVID-19, outbreak association, long-term care facility-affiliated status, and geographic coverage; timeliness of data availability and captured viral diversity also improved. Hospitalized cases were underrepresented, indicating a need to increase inpatient sampling. Our analysis emphasizes the need to understand and quantify sampling bias in phylogenetic studies and continue evaluation and improvement of public health surveillance systems.

Associations Between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants and Risk of Coronavirus Disease 2019 (COVID-19) Hospitalization Among Confirmed Cases in Washington State: A Retrospective Cohort Study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with 7 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. METHODS: Our study includes individuals with positive SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) in the Washington Disease Reporting System with available viral genome data, from 1 December 2020 to 14 January 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. RESULTS: In total, 58 848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95% confidence interval [CI] 2.40-4.26), Beta (HR 2.85, 95% CI 1.56-5.23), Delta (HR 2.28 95% CI 1.56-3.34), or Alpha (HR 1.64, 95% CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95% CI .56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSIONS: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.

Associations between SARS-CoV-2 variants and risk of COVID-19 hospitalization among confirmed cases in Washington State: a retrospective cohort study.

BACKGROUND: The COVID-19 pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with seven SARS-CoV-2 variants. METHODS: Our study includes individuals with positive SARS-CoV-2 RT-PCR in the Washington Disease Reporting System with available viral genome data, from December 1, 2020 to January 14, 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. FINDINGS: 58,848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95%CI 2.40-4.26), Beta (HR 2.85, 95%CI 1.56-5.23), Delta (HR 2.28 95%CI 1.56-3.34) or Alpha (HR 1.64, 95%CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95%CI 0.56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSION: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance. SUMMARY: Hospitalization risk following infection with SARS-CoV-2 variant remains unclear. We find a higher hospitalization risk in cases infected with Alpha, Beta, Gamma, and Delta, but not Omicron, with vaccination lowering risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.

A Rapid Method for the Detection of Diarrhetic Shellfish Toxins and Azaspiracid Shellfish Toxins in Washington State Shellfish by Liquid Chromatography Tandem Mass Spectrometry.

BACKGROUND: Diarrhetic shellfish toxins (DSTs) in domestic shellfish and azaspiracids (AZAs) in imported products are emerging seafood safety issues in the United States. In addition to causing gastrointestinal illnesses, some of these toxins are also carcinogenic and genotoxic. Efficient analytical strategies are needed for their monitoring in U.S. domestic and imported shellfish. OBJECTIVE: In the US, DSTs and AZAs are the only lipophilic shellfish toxins addressed in regulations. Streamlining of existing methods for several classes of lipophilic toxins, based on liquid chromatography coupled with triple quadrupole mass spectrometry, was pursued. METHOD: The resulting simplified LC-MS/MS method is focused on the separation and detection of just the AZAs and total DSTs using a C18 Hypersil gold column. Filter vials are used to expedite and simplify sample handling. RESULTS: The method has a run time of 7.25 min. LOQs for the AZAs and DSTs in shellfish were 0.3-0.4 µg/kg. Recoveries (AZAs and total DSTs) for three spiking levels in three matrixes ranged from 68 to 129%. Trueness was established using certified reference materials. Method equivalence was established using shellfish provided blind by the Washington State Department of Health Public Health Laboratory (WA DOH PHL). Data obtained from these samples agreed well with data from another LC-MS/MS method used in harvest control by WA DOH PHL (R = 0.999; P < 0.0001). CONCLUSIONS: The LC-MS/MS method described offers more rapid sample handling and has excellent sensitivity, linearity, and repeatability.

Visual Dialog.

We introduce the task of Visual Dialog, which requires an AI agent to hold a meaningful dialog with humans in natural, conversational language about visual content. Specifically, given an image, a dialog history, and a question about the image, the agent has to ground the question in image, infer context from history, and answer the question accurately. Visual Dialog is disentangled enough from a specific downstream task so as to serve as a general test of machine intelligence, while being sufficiently grounded in vision to allow objective evaluation of individual responses and benchmark progress. We develop a novel two-person real-time chat data-collection protocol to curate a large-scale Visual Dialog dataset (VisDial). VisDial v0.9 has been released and consists of dialog question-answer pairs from 10-round, human-human dialogs grounded in images from the COCO dataset.