Fragment Merging Using a Graph Database Samples Different Catalogue Space than Similarity Search.

Fragment merging is a promising approach to progressing fragments directly to on-scale potency: each designed compound incorporates the structural motifs of overlapping fragments in a way that ensures compounds recapitulate multiple high-quality interactions. Searching commercial catalogues provides one useful way to quickly and cheaply identify such merges and circumvents the challenge of synthetic accessibility, provided they can be readily identified. Here, we demonstrate that the Fragment Network, a graph database that provides a novel way to explore the chemical space surrounding fragment hits, is well-suited to this challenge. We use an iteration of the database containing >120 million catalogue compounds to find fragment merges for four crystallographic screening campaigns and contrast the results with a traditional fingerprint-based similarity search. The two approaches identify complementary sets of merges that recapitulate the observed fragment-protein interactions but lie in different regions of chemical space. We further show our methodology is an effective route to achieving on-scale potency by retrospective analyses for two different targets; in analyses of public COVID Moonshot and Mycobacterium tuberculosis EthR inhibitors, potential inhibitors with micromolar IC50 values were identified. This work demonstrates the use of the Fragment Network to increase the yield of fragment merges beyond that of a classical catalogue search.

Temporal trends and determinants of COVID-19 vaccine series initiation after recent pregnancy.

During the rapid deployment of COVID-19 vaccines in 2021, safety concerns may have led some pregnant individuals to postpone vaccination until after giving birth. This study aimed to describe temporal patterns and factors associated with COVID-19 vaccine series initiation after recent pregnancy in Ontario, Canada. Using the provincial birth registry linked with the COVID-19 vaccine database, we identified all individuals who gave birth between January 1 and December 31, 2021, and had not yet been vaccinated by the end of pregnancy, and followed them to June 30, 2022 (follow-up ranged from 6 to 18 months). We used cumulative incidence curves to describe COVID-19 vaccine initiation after pregnancy and assessed associations with sociodemographic, pregnancy-related, and health behavioral factors using Cox proportional hazards regression to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CI). Among 137,198 individuals who gave birth in 2021, 87,376 (63.7%) remained unvaccinated at the end of pregnancy; of these, 65.0% initiated COVID-19 vaccination by June 30, 2022. Lower maternal age (<25 vs. 30-34 y aHR: 0.73, 95%CI: 0.70-0.77), smoking during pregnancy (vs. nonsmoking aHR: 0.68, 95%CI: 0.65-0.72), lower neighborhood income (lowest quintile vs. highest aHR: 0.79, 95%CI: 0.76-0.83), higher material deprivation (highest quintile vs. lowest aHR: 0.74, 95%CI: 0.70-0.79), and exclusive breastfeeding (vs. other feeding aHR: 0.81, 95%CI: 0.79-0.84) were associated with lower likelihood of vaccine initiation. Among unvaccinated individuals who gave birth in 2021, COVID-19 vaccine initiation after pregnancy reached 65% by June 30, 2022, suggesting persistent issues with vaccine hesitancy and/or access to vaccination in this population.

Molecular Epidemiology of SARS-CoV-2 during Five COVID-19 Waves and the Significance of Low-Frequency Lineages.

SARS-CoV-2 lineages and variants of concern (VOC) have gained more efficient transmission and immune evasion properties with time. We describe the circulation of VOCs in South Africa and the potential role of low-frequency lineages on the emergence of future lineages. Whole genome sequencing was performed on SARS-CoV-2 samples from South Africa. Sequences were analysed with Nextstrain pangolin tools and Stanford University Coronavirus Antiviral & Resistance Database. In 2020, 24 lineages were detected, with B.1 (3%; 8/278), B.1.1 (16%; 45/278), B.1.1.348 (3%; 8/278), B.1.1.52 (5%; 13/278), C.1 (13%; 37/278) and C.2 (2%; 6/278) circulating during the first wave. Beta emerged late in 2020, dominating the second wave of infection. B.1 and B.1.1 continued to circulate at low frequencies in 2021 and B.1.1 re-emerged in 2022. Beta was outcompeted by Delta in 2021, which was thereafter outcompeted by Omicron sub-lineages during the 4th and 5th waves in 2022. Several significant mutations identified in VOCs were also detected in low-frequency lineages, including S68F (E protein); I82T (M protein); P13L, R203K and G204R/K (N protein); R126S (ORF3a); P323L (RdRp); and N501Y, E484K, D614G, H655Y and N679K (S protein). Low-frequency variants, together with VOCs circulating, may lead to convergence and the emergence of future lineages that may increase transmissibility, infectivity and escape vaccine-induced or natural host immunity.

Evidence-driven spatiotemporal COVID-19 hospitalization prediction with Ising dynamics.

In this work, we aim to accurately predict the number of hospitalizations during the COVID-19 pandemic by developing a spatiotemporal prediction model. We propose HOIST, an Ising dynamics-based deep learning model for spatiotemporal COVID-19 hospitalization prediction. By drawing the analogy between locations and lattice sites in statistical mechanics, we use the Ising dynamics to guide the model to extract and utilize spatial relationships across locations and model the complex influence of granular information from real-world clinical evidence. By leveraging rich linked databases, including insurance claims, census information, and hospital resource usage data across the U.S., we evaluate the HOIST model on the large-scale spatiotemporal COVID-19 hospitalization prediction task for 2299 counties in the U.S. In the 4-week hospitalization prediction task, HOIST achieves 368.7 mean absolute error, 0.6 [Formula: see text] and 0.89 concordance correlation coefficient score on average. Our detailed number needed to treat (NNT) and cost analysis suggest that future COVID-19 vaccination efforts may be most impactful in rural areas. This model may serve as a resource for future county and state-level vaccination efforts.

Mapping emerging technologies in aged care: results from an in-depth online research.

BACKGROUND: Emerging Technologies (ETs) have recently acquired great relevance in elderly care. The exceptional experience with SARS-CoV-2 pandemic has emphasized the usefulness of ETs in the assistance and remote monitoring of older adults. Technological devices have also contributed to the preservation of social interactions, thus reducing isolation and loneliness. The general purpose of this work is to provide a comprehensive and updated overview of the technologies currently employed in elderly care. This objective was achieved firstly, by mapping and classifying the ETs currently available on the market and, secondly, by assessing the impact of such ETs on elderly care, exploring the ethical values promoted, as well as potential ethical threats. METHODS: An in-depth search was carried out on Google search engine, by using specific keywords (e.g. technology, monitoring techniques, ambient intelligence; elderly, older adults; care and assistance). Three hundred and twenty-eight technologies were originally identified. Then, based on a predetermined set of inclusion-exclusion criteria, two hundreds and twenty-two technologies were selected. RESULTS: A comprehensive database was elaborated, where the two hundred and twenty-two ETs selected were classified as follows: category; developmental stage; companies and/or partners; functions; location of development; time of development; impact on elderly care; target; website. From an in-depth qualitative analysis, some ethically-related contents and themes emerged, namely: questions related to safety, independence and active aging, connectedness, empowerment and dignity, cost and efficiency. Although not reported by developers, a close analysis of website contents highlights that positive values are often associated with potential risks, notably privacy threats, deception, dehumanization of care. CONCLUSIONS: Research findings may ultimately lead to a better understanding of the impact of ETs on elderly people.

Use of eco-mapping in health services research: a scoping review protocol.

INTRODUCTION: People with complex health and social needs often require care from different providers and services. Identifying their existing sources of support could assist with addressing potential gaps and opportunities for enhanced service delivery. Eco-mapping is an approach used to visually capture people's social relationships and their linkages to the larger social systems. As it is an emerging and promising approach in the health services field, a scoping review on eco-mapping is warranted. This scoping review aims to synthesise the empirical literature that has focused on the application of eco-mapping by describing characteristics, populations, methodological approaches and other features of eco-mapping in health services research. METHODS AND ANALYSIS: This scoping review will follow the Joanna Briggs Institute methodology. From the date of database construction to 16 January 2023, the following databases in English will be searched: Ovid Medline, Ovid Embase, CINAHL Ultimate (EBSCOhost), Emcare (Ovid), Cochrane Central Register of Controlled Trials (Ovid) and Cochrane Database of Systematic Reviews (Ovid) Study/Source of Evidence selection. The inclusion criteria consist of empirical literature that uses eco-mapping or a related tool in the context of health services research. Two researchers will independently screen references against inclusion and exclusion criteria using Covidence software. Once screened, the data will be extracted and organised according to the following research questions: (1) What research questions and phenomena of interest do researchers address when using eco-mapping? (2) What are the characteristics of studies that use eco-mapping in health services research? (3) What are the methodological considerations for eco-mapping in health services research? ETHICS AND DISSEMINATION: This scoping review does not require ethical approval. The findings will be disseminated through publications, conference presentations and stakeholder meetings. TRIAL REGISTRATION NUMBER: https://doi.org/10.17605/OSF.IO/GAWYN.

Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs against them: An in silico approach.

Monkeypox virus (mpox virus) outbreak has rapidly spread to 82 non-endemic countries. Although it primarily causes skin lesions, secondary complications and high mortality (1-10%) in vulnerable populations have made it an emerging threat. Since there is no specific vaccine/antiviral, it is desirable to repurpose existing drugs against mpox virus. With little knowledge about the lifecycle of mpox virus, identifying potential inhibitors is a challenge. Nevertheless, the available genomes of mpox virus in public databases represent a goldmine of untapped possibilities to identify druggable targets for the structure-based identification of inhibitors. Leveraging this resource, we combined genomics and subtractive proteomics to identify highly druggable core proteins of mpox virus. This was followed by virtual screening to identify inhibitors with affinities for multiple targets. 125 publicly available genomes of mpox virus were mined to identify 69 highly conserved proteins. These proteins were then curated manually. These curated proteins were funnelled through a subtractive proteomics pipeline to identify 4 highly druggable, non-host homologous targets namely; A20R, I7L, Top1B and VETFS. High-throughput virtual screening of 5893 highly curated approved/investigational drugs led to the identification of common as well as unique potential inhibitors with high binding affinities. The common inhibitors, i.e., batefenterol, burixafor and eluxadoline were further validated by molecular dynamics simulation to identify their best potential binding modes. The affinity of these inhibitors suggests their repurposing potential. This work can encourage further experimental validation for possible therapeutic management of mpox.

Analyzing the role of ACE2, AR, MX1 and TMPRSS2 genetic markers for COVID-19 severity.

BACKGROUND: The use of molecular biomarkers for COVID-19 remains unconclusive. The application of a molecular biomarker in combination with clinical ones that could help classifying aggressive patients in first steps of the disease could help clinician and sanitary system a better management of the disease. Here we characterize the role of ACE2, AR, MX1, ERG, ETV5 and TMPRSS2 for trying a better classification of COVID-19 through knowledge of the disease mechanisms. METHODS: A total of 329 blood samples were genotyped in ACE2, MX1 and TMPRSS2. RNA analyses were also performed from 258 available samples using quantitative polymerase chain reaction for genes: ERG, ETV5, AR, MX1, ACE2, and TMPRSS2. Moreover, in silico analysis variant effect predictor, ClinVar, IPA, DAVID, GTEx, STRING and miRDB database was also performed. Clinical and demographic data were recruited from all participants following WHO classification criteria. RESULTS: We confirm the use of ferritin (p < 0.001), D-dimer (p < 0.010), CRP (p < 0.001) and LDH (p < 0.001) as markers for distinguishing mild and severe cohorts. Expression studies showed that MX1 and AR are significantly higher expressed in mild vs severe patients (p < 0.05). ACE2 and TMPRSS2 are involved in the same molecular process of membrane fusion (p = 4.4 × 10-3), acting as proteases (p = 0.047). CONCLUSIONS: In addition to the key role of TMPSRSS2, we reported for the first time that higher expression levels of AR are related with a decreased risk of severe COVID-19 disease in females. Moreover, functional analysis demonstrates that ACE2, MX1 and TMPRSS2 are relevant markers in this disease.

Increased risk of new-onset diabetes in patients with COVID-19: a systematic review and meta-analysis.

Background: There is growing evidence that patients with COVID-19 are at increased risk of new-onset diabetes. The limited preliminary studies do not provide strong evidence. To assess the association of the SARS-CoV-2 virus with new-onset diabetes and to characterize the population. Methods: Search PubMed, Embase, Cochrane Library, and Web of Science electronic databases for a limited period from December 2019 to July 2022. Two independent reviewers conducted a thorough review of eligible articles and extracted relevant information. Pooled proportions, risk ratios (RR), and 95% confidence intervals (95% CI) indicated the incidence and risk ratios of events. Results: The incidence of new-onset diabetes and hyperglycemia in patients with COVID-19 was 5% (P < 0.001) (3 and 30% for new-onset diabetes and hyperglycemia, respectively), with age, ethnicity, time of diagnosis, and study type all having an impact on the incidence (P < 0.05). New-onset diabetes and hyperglycemia were 1.75 times higher in COVID-19 patients than in non-COVID-19 patients. In new-onset diabetes and hyperglycemia population, the percentage of men is 60% (40% for women), with a mortality rate of 17%. The proportion of new-onset diabetes and hyperglycemia after infection with COVID-19 was 25% in men and 14% in women. Conclusions: The incidence and relative risk of new-onset diabetes and hyperglycemia are elevated after COVID-19 infection, especially in the early COVID-19 and male populations. Systemic review registration: PROSPERO registration no.: CRD42022382989 https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=382989.

Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets.

Background: Sepsis is a dysfunctional host response to infection. The syndrome leads to millions of deaths annually (19.7% of all deaths in 2017) and is the cause of most deaths from severe Covid infections. High throughput sequencing or 'omics' experiments in molecular and clinical sepsis research have been widely utilized to identify new diagnostics and therapies. Transcriptomics, quantifying gene expression, has dominated these studies, due to the efficiency of measuring gene expression in tissues and the technical accuracy of technologies like RNA-Seq. Objective: Most of these studies seek to uncover novel mechanistic insights into sepsis pathogenesis and diagnostic gene signatures by identifying genes differentially expressed between two or more relevant conditions. However, little effort has been made, to date, to aggregate this knowledge from such studies. In this study we sought to build a compendium of previously described gene sets that combines knowledge gained from sepsis-associated studies. This would enable the identification of genes most associated with sepsis pathogenesis, and the description of the molecular pathways commonly associated with sepsis. Methods: PubMed was searched for studies using transcriptomics to characterize acute infection/sepsis and severe sepsis (i.e., sepsis combined with organ failure). Several studies were identified that used transcriptomics to identify differentially expressed (DE) genes, predictive/prognostic signatures, and underlying molecular responses and pathways. The molecules included in each gene set were collected, in addition to the relevant study metadata (e.g., patient groups used for comparison, sample collection time point, tissue type, etc.). Results: After performing extensive literature curation of 74 sepsis-related publications involving transcriptomics, 103 unique gene sets (comprising 20,899 unique genes) from thousands of patients were collated together with associated metadata. Frequently described genes included in gene sets as well as the molecular mechanisms they were involved in were identified. These mechanisms included neutrophil degranulation, generation of second messenger molecules, IL-4 and -13 signaling, and IL-10 signaling among many others. The database, which we named SeptiSearch, is made available in a web application created using the Shiny framework in R, (available at https://septisearch.ca). Conclusions: SeptiSearch provides members of the sepsis community the bioinformatic tools needed to leverage and explore the gene sets contained in the database. This will allow the gene sets to be further scrutinized and analyzed for their enrichment in user-submitted gene expression data and used for validation of in-house gene sets/signatures.

Bibliometric analysis of the classic cited papers in the American Journal of Surgery: Citation recapitulates surgical history.

BACKGROUND: We performed a bibliometric analysis of the American Journal of Surgery (AJS) to identify, characterize and place within a historical context, its published classic cited papers (CCPs). METHODS: Bibliometric data from papers published in the AJS between January 1, 1945, and December 31, 2021 was extracted from the Web of Science database. Analysis was performed utilizing Bibliometrix and VOSViewer software. RESULTS: 27,070 papers were published in the AJS over the study period. There were 16 CCPs, including 5 Top CCPs, identified. Review of the Top CCPs reveals that they are based on careful clinical observations, innovation and generally build on prior published work. Top CCPs usually are specific to a particular diagnosis or a commonly performed procedure, as such papers frequently present a scoring or classification system, or important details related to new operative approaches or techniques. CONCLUSIONS: Bibliometric study of the AJS has allowed for identification, characterization and appreciation of many of the key changes that have occurred in the discipline throughout the history of modern surgery.

Changes in vaccine administration trends across the life-course during the COVID-19 pandemic in the United States: a claims database study.

BACKGROUND: This study provides an updated and expanded analysis of the impact of the COVID-19 pandemic on routine vaccinations across the life-course in the United States. RESEARCH DESIGN AND METHODS: Routine wellness visits and vaccination rates were calculated using structured claims data for each month during the impact period (January 2020 to August 2022) and compared to the respective baseline period (January 2018 to December 2019). Monthly rates were aggregated as annual accumulated and cumulative percent changes. RESULTS: The complete monthly rate interactive dataset can be viewed at https://vaccinationtrends.com. The greatest decrease in annual accumulated administration rates in the 0-2 and 4-6 years age groups was for the measles, mumps, and rubella vaccine; for adolescents and older adults, it was for human papillomavirus and pneumococcal vaccines, respectively. Routine in-person wellness visit rates recovered faster and more completely than vaccination rates in all age groups, indicating potential missed opportunities to administer vaccines during visits. CONCLUSIONS: This updated analysis reveals that the negative impact of the COVID-19 pandemic on routine vaccination continued through 2021 and into 2022. Proactive efforts to reverse this decline are needed to increase individual- and population-level vaccination coverage and avoid the associated preventable morbidity, mortality, and health care costs.

Severity of the Omicron SARS-CoV-2 variant compared with the previous lineages: A systematic review.

The Omicron variant was first detected in October 2021, which evolved from the original SARS-CoV-2 strain and was found to possess many mutations. Immune evasion was one of the notable consequences of these mutations. Despite Omicron exhibiting increased transmissibility, the rates of hospitalizations and deaths among patients infected with this variant were substantially lower when compared to other strains. However, concluding that the Omicron variant is less severe than other variants of SARS-CoV-2 requires consideration of multiple factors, including the vaccination status of infected patients as well as any previous infections with other variants. This review compiled data about any reported indicators of severity in Omicron-infected patients, including studies comparing Omicron with other variants while adjusting for confounders. A comprehensive search was conducted using different databases to target any studies about Omicron. In total, 62 studies met our inclusion criteria and were included in this study. Many studies reported a significantly reduced risk of hospitalization, ICU admission, need for oxygenation/ventilation, and death in Omicron-infected patients compared to patients infected with other variants, such as Delta. Some studies, however, reported comparable severity in Omicron infected patients as to other variants emphasizing a substantial risk for severe illness. Furthermore, the COVID-19 vaccines were less effective against Omicron relative to previous lineages, except after receiving the booster dose. One study recommended vaccination during pregnancy, which may help prevent future cases of severe SARS-CoV-2 pneumonia in neonates and young infants due to the transfer of humoral response from the mother.

Digital dashboards visualizing public health data: a systematic review.

Introduction: Public health is not only threatened by diseases, pandemics, or epidemics. It is also challenged by deficits in the communication of health information. The current COVID-19 pandemic demonstrates that impressively. One way to deliver scientific data such as epidemiological findings and forecasts on disease spread are dashboards. Considering the current relevance of dashboards for public risk and crisis communication, this systematic review examines the state of research on dashboards in the context of public health risks and diseases. Method: Nine electronic databases where searched for peer-reviewed journal articles and conference proceedings. Included articles (n = 65) were screened and assessed by three independent reviewers. Through a methodological informed differentiation between descriptive studies and user studies, the review also assessed the quality of included user studies (n = 18) by use of the Mixed Methods Appraisal Tool (MMAT). Results: 65 articles were assessed in regards to the public health issues addressed by the respective dashboards, as well as the data sources, functions and information visualizations employed by the different dashboards. Furthermore, the literature review sheds light on public health challenges and objectives and analyzes the extent to which user needs play a role in the development and evaluation of a dashboard. Overall, the literature review shows that studies that do not only describe the construction of a specific dashboard, but also evaluate its content in terms of different risk communication models or constructs (e.g., risk perception or health literacy) are comparatively rare. Furthermore, while some of the studies evaluate usability and corresponding metrics from the perspective of potential users, many of the studies are limited to a purely functionalistic evaluation of the dashboard by the respective development teams. Conclusion: The results suggest that applied research on public health intervention tools like dashboards would gain in complexity through a theory-based integration of user-specific risk information needs. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=200178, identifier: CRD42020200178.

Identifying and Validating Pediatric Hospitalizations for MIS-C Through Administrative Data.

BACKGROUND: Individual children's hospitals care for a small number of patients with multisystem inflammatory syndrome in children (MIS-C). Administrative databases offer an opportunity to conduct generalizable research; however, identifying patients with MIS-C is challenging. METHODS: We developed and validated algorithms to identify MIS-C hospitalizations in administrative databases. We developed 10 approaches using diagnostic codes and medication billing data and applied them to the Pediatric Health Information System from January 2020 to August 2021. We reviewed medical records at 7 geographically diverse hospitals to compare potential cases of MIS-C identified by algorithms to each participating hospital's list of patients with MIS-C (used for public health reporting). RESULTS: The sites had 245 hospitalizations for MIS-C in 2020 and 358 additional MIS-C hospitalizations through August 2021. One algorithm for the identification of cases in 2020 had a sensitivity of 82%, a low false positive rate of 22%, and a positive predictive value (PPV) of 78%. For hospitalizations in 2021, the sensitivity of the MIS-C diagnosis code was 98% with 84% PPV. CONCLUSION: We developed high-sensitivity algorithms to use for epidemiologic research and high-PPV algorithms for comparative effectiveness research. Accurate algorithms to identify MIS-C hospitalizations can facilitate important research for understanding this novel entity as it evolves during new waves.

Predictive values of procalcitonin for coinfections in patients with COVID-19: a systematic review and meta-analysis.

OBJECTIVES: To assess the ability of procalcitonin (PCT)-a promising marker for coinfections-to predict coinfections in patients with COVID-19. METHODS: In this systematic review and meta-analysis, PubMed, Embase, Web of Science, Cochrane, the China National Knowledge Infrastructure (CNKI), and Wanfang were searched to identify eligible studies (up to August 30, 2021). Articles that reported the predictive value of PCT for coinfections in patients with COVID-19 were included. Individual and pooled sensitivities and specificities were reported, and I2 was used to test heterogeneity. This study was prospectively registered on the International Prospective Register of Systematic Reviews (PROSPERO) database (registration number: CRD42021283344). RESULTS: Five studies involving a total of 2775 patients reported the predictive value of PCT for coinfections in patients with COVID-19. The sensitivity, specificity, and area under the curve of PCT in predicting coinfections in the pooled studies were 0.60 (95% CI 0.35-0.81, I2 = 88.85), 0.71 (95% CI 0.58-0.81, I2 = 87.82), and 0.72(95% CI 0.68-0.76) respectively. CONCLUSIONS: Although PCT has limited predictive value for coinfections in patients with COVID-19, lower PCT levels seem to indicate a decreased probability of having a coinfection.

Safety outcomes associated with the moderna COVID-19 vaccine (mRNA-1273): a literature review.

INTRODUCTION: Current safety data from Phase 3 clinical trials have concluded that apart from transient local and systemic reactions, no safety concerns were identified for the Moderna COVID-19 vaccine (mRNA-1273). However, Phase 3 studies are insufficient to detect rare adverse events (AEs). A literature search of the two major electronic databases, Embase and PubMed, was performed to enable the identification and characterization of all relevant articles from December 2020 to November 2022. AREAS COVERED: This narrative review summarizes the key safety outcomes associated with the mRNA-1273 vaccine to inform healthcare decisions and increase public awareness of mRNA-1273 vaccine safety. The primary adverse events (AEs) reported within a diverse population, receiving the mRNA-1273 vaccine, were; localized injection site pain, fatigue, headache, myalgia, and chills. In addition, the mRNA-1273 vaccine was also associated with; less than a 1-day change in the menstrual cycle, a 10-fold higher risk of myocarditis and pericarditis within young males aged 18-29 years and increased levels of anti-polyethylene glycol (PEG) antibodies. EXPERT OPINION: The transient nature of commonly observed AEs and the rare occurrence of severe events within mRNA-1273 recipients show no significant safety concerns which should prevent vaccination. However, large-scale epidemiological studies with longer follow-up periods are required to surveillance rare safety outcomes.

The significance of the library's physical space: how COVID-19 impacted a consumer health service.

Background: During the beginning of the COVID-19 pandemic, many consumer health libraries were forced to close their doors to patrons. At the Health Information Center in Knoxville, Tennessee, the physical space closed, while health information services continued to be provided via phone and email. To examine the impact of lack of access to a physical library for consumer health information, researchers analyzed the number of health information requests pre-COVID-19 pandemic compared to during the initial phase of the pandemic. Case Presentation: Data from an internal database was collected and analyzed. Researchers divided the data into three time periods: March 2018 to February 2019 (Phase 1), March 2019 to February 2020 (Phase 2), and March 2020 to February 2021 (Phase 3). Data was de-identified and duplicate entries were removed. The type of interaction and request topics were reviewed in each phase. Conclusion: In Phase 1, there were 535 walk-ins to request health information and 555 walk-ins in Phase 2. In Phase 3, there were 40 walk-ins. The number of requests through phone and email varied but remained steady. There was a 61.56% decrease in requests between Phase 1 and Phase 3 while there was a 66.27% decrease between Phase 2 and Phase 3 due to the lack of walk-in requests. The number of phone and email requests did not increase despite the closure of the physical library space to the public. Access to the physical space plays a significant role in providing health information requests to patients and family members.

Association between the COVID-19 pandemic and first cancer treatment modality: a population-based cohort study.

BACKGROUND: Physicians were directed to prioritize using nonsurgical cancer treatment at the beginning of the COVID-19 pandemic. We sought to quantify the impact of this policy on the modality of first cancer treatment (surgery, chemotherapy, radiotherapy or no treatment). METHODS: In this population-based study using Ontario data from linked administrative databases, we identified adults diagnosed with cancer from January 2016 to November 2020 and their first cancer treatment received within 1 year postdiagnosis. Segmented Poisson regressions were applied to each modality to estimate the change in mean 1-year recipient volume per thousand patients (rate) at the start of the pandemic (the week of Mar. 15, 2020) and change in the weekly trend in rate during the pandemic (Mar. 15, 2020, to Nov. 7, 2020) relative to before the pandemic (Jan. 3, 2016, to Mar. 14, 2020). RESULTS: We included 321 535 people diagnosed with cancer. During the first week of the COVID-19 pandemic, the mean rate of receiving upfront surgery over the next year declined by 9% (rate ratio 0.91, 95% confidence interval [CI] 0.88-0.95), and chemotherapy and radiotherapy rates rose by 30% (rate ratio 1.30, 95% CI 1.23-1.36) and 13% (rate ratio 1.13, 95% CI 1.07-1.19), respectively. Subsequently, the 1-year rate of upfront surgery increased at 0.4% for each week (rate ratio 1.004, 95% CI 1.002-1.006), and chemotherapy and radiotherapy rates decreased by 0.9% (rate ratio 0.991, 95% CI 0.989-0.994) and 0.4% (rate ratio 0.996, 95% CI 0.994-0.998), respectively, per week. Rates of each modality resumed to prepandemic levels at 24-31 weeks into the pandemic. INTERPRETATION: An immediate and sustained increase in use of nonsurgical therapy as the first cancer treatment occurred during the first 8 months of the COVID-19 pandemic in Ontario. Further research is needed to understand the consequences.

Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022.

The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.