Nirsevimab for Prevention of RSV in Healthy Late-Preterm and Term Infants.

BACKGROUND: Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infection and hospitalization in infants. Nirsevimab is a monoclonal antibody to the RSV fusion protein that has an extended half-life. The efficacy and safety of nirsevimab in healthy late-preterm and term infants are uncertain. METHODS: We randomly assigned, in a 2:1 ratio, infants who had been born at a gestational age of at least 35 weeks to receive a single intramuscular injection of nirsevimab or placebo before the start of an RSV season. The primary efficacy end point was medically attended RSV-associated lower respiratory tract infection through 150 days after the injection. The secondary efficacy end point was hospitalization for RSV-associated lower respiratory tract infection through 150 days after the injection. RESULTS: A total of 1490 infants underwent randomization: 994 were assigned to the nirsevimab group and 496 to the placebo group. Medically attended RSV-associated lower respiratory tract infection occurred in 12 infants (1.2%) in the nirsevimab group and in 25 infants (5.0%) in the placebo group; these findings correspond to an efficacy of 74.5% (95% confidence interval [CI], 49.6 to 87.1; P<0.001) for nirsevimab. Hospitalization for RSV-associated lower respiratory tract infection occurred in 6 infants (0.6%) in the nirsevimab group and in 8 infants (1.6%) in the placebo group (efficacy, 62.1%; 95% CI, -8.6 to 86.8; P = 0.07). Among infants with data available to day 361, antidrug antibodies after baseline were detected in 58 of 951 (6.1%) in the nirsevimab group and in 5 of 473 (1.1%) in the placebo group. Serious adverse events were reported in 67 of 987 infants (6.8%) who received nirsevimab and in 36 of 491 infants (7.3%) who received placebo. CONCLUSIONS: A single injection of nirsevimab administered before the RSV season protected healthy late-preterm and term infants from medically attended RSV-associated lower respiratory tract infection. (Funded by MedImmune/AstraZeneca and Sanofi; MELODY ClinicalTrials.gov number, NCT03979313.).

A riboswitch separated from its ribosome-binding site still regulates translation.

Riboswitches regulate downstream gene expression by binding cellular metabolites. Regulation of translation initiation by riboswitches is posited to occur by metabolite-mediated sequestration of the Shine-Dalgarno sequence (SDS), causing bypass by the ribosome. Recently, we solved a co-crystal structure of a prequeuosine1-sensing riboswitch from Carnobacterium antarcticum that binds two metabolites in a single pocket. The structure revealed that the second nucleotide within the gene-regulatory SDS, G34, engages in a crystal contact, obscuring the molecular basis of gene regulation. Here, we report a co-crystal structure wherein C10 pairs with G34. However, molecular dynamics simulations reveal quick dissolution of the pair, which fails to reform. Functional and chemical probing assays inside live bacterial cells corroborate the dispensability of the C10-G34 pair in gene regulation, leading to the hypothesis that the compact pseudoknot fold is sufficient for translation attenuation. Remarkably, the C. antarcticum aptamer retained significant gene-regulatory activity when uncoupled from the SDS using unstructured spacers up to 10 nucleotides away from the riboswitch-akin to steric-blocking employed by sRNAs. Accordingly, our work reveals that the RNA fold regulates translation without SDS sequestration, expanding known riboswitch-mediated gene-regulatory mechanisms. The results infer that riboswitches exist wherein the SDS is not embedded inside a stable fold.

Structure and function analysis of a type III preQ1-I riboswitch from Escherichia coli reveals direct metabolite sensing by the Shine-Dalgarno sequence.

Riboswitches are small noncoding RNAs found primarily in the 5' leader regions of bacterial messenger RNAs where they regulate expression of downstream genes in response to binding one or more cellular metabolites. Such noncoding RNAs are often regulated at the translation level, which is thought to be mediated by the accessibility of the Shine-Dalgarno sequence (SDS) ribosome-binding site. Three classes (I-III) of prequeuosine1 (preQ1)-sensing riboswitches are known that control translation. Class I is divided into three subtypes (types I-III) that have diverse mechanisms of sensing preQ1, which is involved in queuosine biosynthesis. To provide insight into translation control, we determined a 2.30 Å-resolution cocrystal structure of a class I type III preQ1-sensing riboswitch identified in Escherichia coli (Eco) by bioinformatic searches. The Eco riboswitch structure differs from previous preQ1 riboswitch structures because it has the smallest naturally occurring aptamer and the SDS directly contacts the preQ1 metabolite. We validated structural observations using surface plasmon resonance and in vivo gene-expression assays, which showed strong switching in live E. coli. Our results demonstrate that the Eco riboswitch is relatively sensitive to mutations that disrupt noncanonical interactions that form the pseudoknot. In contrast to type II preQ1 riboswitches, a kinetic analysis showed that the type III Eco riboswitch strongly prefers preQ1 over the chemically similar metabolic precursor preQ0. Our results reveal the importance of noncanonical interactions in riboswitch-driven gene regulation and the versatility of the class I preQ1 riboswitch pseudoknot as a metabolite-sensing platform that supports SDS sequestration.

Comparative assessment of radiation therapy-induced vasculitis using [18F]FDG-PET/CT in patients with non-small cell lung cancer treated with proton versus photon radiotherapy.

PURPOSE: To assess radiation therapy (RT)-induced vasculitis in patients with non-small cell lung cancer (NSCLC) by examining changes in the uptake of 18F-fluoro-D-deoxyglucose ([18F]FDG) by positron emission tomography/computed tomography (PET/CT) images of the ascending aorta (AA), descending aorta (DA), and aortic arch (AoA) before and after proton and photon RT. METHOD: Thirty-five consecutive locally advanced NSCLC patients were definitively treated with proton (n = 27) or photon (n = 8) RT and concurrent chemotherapy. The patients were prospectively enrolled to undergo [18F]FDG-PET/CT imaging before and 3 months after RT. An adaptive contrast-oriented thresholding algorithm was applied to generate mean standardized uptake values (SUVmean) for regions of interest (ROIs) 3 mm outside and 3 mm inside the outer perimeter of the AA, DA, and AoA. These ROIs were employed to exclusively select the aortic wall and remove the influence of blood pool activity. SUVmeans before and after RT were compared using two-tailed paired t-tests. RESULTS: RT treatments were associated with increased SUVmeans in the AA, DA, and AoA-1.9%, 0.3%, and 1.3% for proton and 15.8%, 9.5%, and 15.5% for photon, respectively. There was a statistically significant difference in the ∆SUVmean (post-RT SUVmean - pre-RT SUVmean) in patients treated with photon RT when compared to ∆SUVmean in patients treated with proton RT in the AA (p = 0.043) and AoA (p = 0.015). There was an average increase in SUVmean that was related to dose for photon patients (across structures), but that was not seen for proton patients, although the increase was not statistically significant. CONCLUSION: Our results suggest that patients treated with photon RT for NSCLC may exhibit significantly more RT-induced inflammation (measured as ∆SUVmean) in the AA and AoA when compared to patients who received proton RT. Knowledge gained from further analyses in larger cohorts could aid in treatment planning and help prevent the significant morbidity and mortality associated with RT-induced vascular complications. TRIAL REGISTRATION: NCT02135679.

An analysis of iris pattern as a risk factor for skin cancer development in immunosuppressed renal transplant recipients.

INTRODUCTION: Renal transplant recipients are at increased risk of keratinocyte skin cancers with a tendency to have multiple, aggressive and difficult to treat tumours. The eye and the skin share the same embryological ectoderm. Iris pattern has recently been reported as a predictive risk factor for skin cancer in non-immunosuppressed Southern European (Grigore et al., J Eur Acad Dermatol Venereol, 2018, 1662) and Irish populations (Ridge et al., J Eur Acad Dermatol Venereol, 2022, e542). AIMS: To analyse if an individual's iris pattern is an independent risk factor for the development of keratinocyte skin cancers in renal transplant recipients. METHODS: Iris patterns of 110 renal transplant recipients were evaluated using the Simionescu visual three-step technique (iris periphery, colarette and iris freckling [Simionescu et al., Ann Res Rev Biol, 2014, 2525]). Established risk factors for skin cancer in transplant patients were recorded as confounding factors. RESULTS: Observational cross-sectional study including 110 renal transplant population. Thirty-one participants had skin cancer. In the skin cancer group, iris periphery was blue/grey in 74.3% (p = 0.053, OR 2.5), the colarette was light brown in 57.1% (p < 0.0043) and iris freckles were present in 55%(p = 0.044). Dark brown and blue colarettes were observed in controls. Binary Logistic Regression analysis showed light brown colarette is a significant independent risk factor for skin cancer (OR 4.54, p < 0.02, CI 1.56-10.57). CONCLUSION: Within this renal transplant population a blue iris periphery, light brown colarette and presence of freckling confers an independent risk for keratinocyte skin cancer. Iris pattern is a useful tool for identification of transplant patients at risk of keratinocyte skin cancer and an easy-to-use technique for risk evaluation in this cohort. This is the first study looking at iris pattern and keratinocyte skin cancer risk in renal transplant population.

RNA target highlights in CASP15: Evaluation of predicted models by structure providers.

The first RNA category of the Critical Assessment of Techniques for Structure Prediction competition was only made possible because of the scientists who provided experimental structures to challenge the predictors. In this article, these scientists offer a unique and valuable analysis of both the successes and areas for improvement in the predicted models. All 10 RNA-only targets yielded predictions topologically similar to experimentally determined structures. For one target, experimentalists were able to phase their x-ray diffraction data by molecular replacement, showing a potential application of structure predictions for RNA structural biologists. Recommended areas for improvement include: enhancing the accuracy in local interaction predictions and increased consideration of the experimental conditions such as multimerization, structure determination method, and time along folding pathways. The prediction of RNA-protein complexes remains the most significant challenge. Finally, given the intrinsic flexibility of many RNAs, we propose the consideration of ensemble models.

Single-Dose Nirsevimab for Prevention of RSV in Preterm Infants.

BACKGROUND: Respiratory syncytial virus (RSV) is the most common cause of lower respiratory tract infection in infants, and a need exists for prevention of RSV in healthy infants. Nirsevimab is a monoclonal antibody with an extended half-life that is being developed to protect infants for an entire RSV season with a single intramuscular dose. METHODS: In this trial conducted in both northern and southern hemispheres, we evaluated nirsevimab for the prevention of RSV-associated lower respiratory tract infection in healthy infants who had been born preterm (29 weeks 0 days to 34 weeks 6 days of gestation). We randomly assigned the infants in a 2:1 ratio to receive nirsevimab, at a dose of 50 mg in a single intramuscular injection, or placebo at the start of an RSV season. The primary end point was medically attended RSV-associated lower respiratory tract infection through 150 days after administration of the dose. The secondary efficacy end point was hospitalization for RSV-associated lower respiratory tract infection through 150 days after administration of the dose. RESULTS: From November 2016 through November 2017, a total of 1453 infants were randomly assigned to receive nirsevimab (969 infants) or placebo (484 infants) at the start of the RSV season. The incidence of medically attended RSV-associated lower respiratory tract infection was 70.1% lower (95% confidence interval [CI], 52.3 to 81.2) with nirsevimab prophylaxis than with placebo (2.6% [25 infants] vs. 9.5% [46 infants]; P<0.001) and the incidence of hospitalization for RSV-associated lower respiratory tract infection was 78.4% lower (95% CI, 51.9 to 90.3) with nirsevimab than with placebo (0.8% [8 infants] vs. 4.1% [20 infants]; P<0.001). These differences were consistent throughout the 150-day period after the dose was administered and across geographic locations and RSV subtypes. Adverse events were similar in the two trial groups, with no notable hypersensitivity reactions. CONCLUSIONS: A single injection of nirsevimab resulted in fewer medically attended RSV-associated lower respiratory tract infections and hospitalizations than placebo throughout the RSV season in healthy preterm infants. (Funded by AstraZeneca and Sanofi Pasteur; ClinicalTrials.gov number, NCT02878330.).

Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record?

BACKGROUND: In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as ​​reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to identify informative patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients. METHODS: We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern. RESULTS: With these analyses, we identified mapping issues faced in seven out of 15 sites. We also identified nuances in data collection and variable definition for the various sites. Temporal trend analyses may support the use of laboratory test result missingness patterns in identifying severe COVID-19 patients. Lastly, using missingness patterns, we determined relationships between various labs that reflect clinical behaviors. CONCLUSION: In this work, we use computational approaches to relate missingness patterns to hospital treatment capacity and highlight the heterogeneity of looking at COVID-19 over time and at multiple sites, where there might be different phases, policies, etc. Changes in missingness could suggest a change in a patient's condition, and patterns of missingness among laboratory measurements could potentially identify clinical outcomes. This allows sites to consider missing data as informative to analyses and help researchers identify which sites are better poised to study particular questions.

Improving integrated depression and non-communicable disease care in Malawi through engaged leadership and supportive implementation climate.

BACKGROUND: Low- and middle-income countries often lack access to mental health services, leading to calls for integration within other primary care systems. In sub-Saharan Africa, integration of depression treatment in non-communicable disease (NCD) settings is feasible, acceptable, and effective. However, leadership and implementation climate challenges often hinder effective integration and quality of services. The aim of this study was to identify discrete leadership strategies that facilitate overcoming barriers to the integration of depression care in NCD clinics in Malawi and to understand how clinic leadership shapes the implementation climate. METHODS: We conducted 39 in-depth interviews with the District Medical Officer, the NCD coordinator, one NCD provider, and the research assistant from each of the ten Malawian NCD clinics (note one District Medical Officer served two clinics). Based on semi-structured interview guides, participants were asked their perspectives on the impact of leadership and implementation climate on overcoming barriers to integrating depression care into existing NCD services. Thematic analysis used both inductive and deductive approaches to identify emerging themes and compare among participant type. RESULTS: The results revealed how engaged leadership can fuel a positive implementation climate where clinics had heightened capacity to overcome implementation barriers. Effective leaders were approachable and engaged in daily operations of the clinic and problem-solving. They held direct involvement with and mentorship during the intervention, providing assistance in patient screening and consultation with treatment plans. Different levels of leadership utilized their respective standings and power dynamics to influence provider attitudes and perceptions surrounding the intervention. Leaders acted by informing providers about the intervention source and educating them on the importance of mental healthcare, as it was often undervalued. Lastly, they prioritized teamwork and collective ownership for the intervention, increasing provider responsibility. CONCLUSION: Training that prioritizes leadership visibility and open communication will facilitate ongoing Malawi Ministry of Health efforts to scale up evidence-based depression treatment within NCD clinics. This proves useful where extensive and external monitoring may be limited. Ultimately, these results can inform successful strategies to close implementation gaps to achieve integration of mental health services in low-resource settings through improved leadership and implementation climate. TRIAL REGISTRATION: These findings are reported from ClinicalTrials.gov, NCT03711786. Registered on 18/10/2018. https://clinicaltrials.gov/ct2/show/NCT03711786 .

Generate Analysis-Ready Data for Real-world Evidence: Tutorial for Harnessing Electronic Health Records With Advanced Informatic Technologies.

Although randomized controlled trials (RCTs) are the gold standard for establishing the efficacy and safety of a medical treatment, real-world evidence (RWE) generated from real-world data has been vital in postapproval monitoring and is being promoted for the regulatory process of experimental therapies. An emerging source of real-world data is electronic health records (EHRs), which contain detailed information on patient care in both structured (eg, diagnosis codes) and unstructured (eg, clinical notes and images) forms. Despite the granularity of the data available in EHRs, the critical variables required to reliably assess the relationship between a treatment and clinical outcome are challenging to extract. To address this fundamental challenge and accelerate the reliable use of EHRs for RWE, we introduce an integrated data curation and modeling pipeline consisting of 4 modules that leverage recent advances in natural language processing, computational phenotyping, and causal modeling techniques with noisy data. Module 1 consists of techniques for data harmonization. We use natural language processing to recognize clinical variables from RCT design documents and map the extracted variables to EHR features with description matching and knowledge networks. Module 2 then develops techniques for cohort construction using advanced phenotyping algorithms to both identify patients with diseases of interest and define the treatment arms. Module 3 introduces methods for variable curation, including a list of existing tools to extract baseline variables from different sources (eg, codified, free text, and medical imaging) and end points of various types (eg, death, binary, temporal, and numerical). Finally, module 4 presents validation and robust modeling methods, and we propose a strategy to create gold-standard labels for EHR variables of interest to validate data curation quality and perform subsequent causal modeling for RWE. In addition to the workflow proposed in our pipeline, we also develop a reporting guideline for RWE that covers the necessary information to facilitate transparent reporting and reproducibility of results. Moreover, our pipeline is highly data driven, enhancing study data with a rich variety of publicly available information and knowledge sources. We also showcase our pipeline and provide guidance on the deployment of relevant tools by revisiting the emulation of the Clinical Outcomes of Surgical Therapy Study Group Trial on laparoscopy-assisted colectomy versus open colectomy in patients with early-stage colon cancer. We also draw on existing literature on EHR emulation of RCTs together with our own studies with the Mass General Brigham EHR.

Expected 10-anonymity of HyperLogLog sketches for federated queries of clinical data repositories.

MOTIVATION: The rapid growth in of electronic medical records provide immense potential to researchers, but are often silo-ed at separate hospitals. As a result, federated networks have arisen, which allow simultaneously querying medical databases at a group of connected institutions. The most basic such query is the aggregate count-e.g. How many patients have diabetes? However, depending on the protocol used to estimate that total, there is always a tradeoff in the accuracy of the estimate against the risk of leaking confidential data. Prior work has shown that it is possible to empirically control that tradeoff by using the HyperLogLog (HLL) probabilistic sketch. RESULTS: In this article, we prove complementary theoretical bounds on the k-anonymity privacy risk of using HLL sketches, as well as exhibit code to efficiently compute those bounds. AVAILABILITY AND IMPLEMENTATION: https://github.com/tzyRachel/K-anonymity-Expectation.

Synthesis and Functionalization of Challenging meso-Substituted Aryl Bis-pocket Porphyrins Accessed via Suzuki-Miyaura Cross-Coupling.

Herein we report an investigation into the synthesis, metalation, and functionalization of bis-pocket porphyrins using the Suzuki-Miyaura cross-coupling reaction. Steric limitations to accessing bis-pocket porphyrins were overcome by using this Pd-catalyzed C-C-bond-forming strategy to introduce steric bulk after macrocyclization: 2,6-dibromo-4-trimethylsilybenzaldehyde was condensed with pyrrole, and a variety of boronic acids were coupled to the resulting porphyrin in up to 95% yield. Furthermore, we show that these porphyrins can be metalated with a variety of metals and sulfonated to create water-soluble bis-pocket porphyrins.

Polycyclic aliphatic hydrocarbons: is tetrahedrane present in UIR spectra?

The smallest Platonic hydrocarbon, tetrahedrane, has been subject to frequent theoretical and experimental study for 50 years, but its infrared spectrum and synthetic pathway remain a mystery. The recent partial attribution of the ultraviolet extinction bump observed in the interstellar medium (ISM) of the Milky Way galaxy to hydrogenated T-carbon, a larger tetrahedral cluster formed from tetrahedrane and C4 monomers, has brought renewed interest to the molecule. Similarly, as a polycyclic hydrocarbon, tetrahedrane is similar in structure to the molecules proposed to be responsible for the so-called unidentified infrared bands (UIRs) observed in all kinds of astronomical environments. Furthermore, tetrahedrane's ν2 and ν7 fundamental vibrational frequencies, with values of 3210.6 cm-1 (3.11 µm) and 752.5 cm-1 (13.29 µm) as computed in the present quantum chemical study, have substantial intensities of 59 and 183 km mol-1, respectively. These come tantalizingly close to, but potentially distinct from, the 3.3 and 13.2 µm regions of the infrared spectrum typically included in the UIRs. As such, tetrahedrane or related clusters of these polycyclic aliphatic hydrocarbons may have a role to play in both of these sets of observations and could even help to explain the relation between them. Regardless, if tetrahedrane is present in the ISM, the highly-accurate theoretical data reported herein should help to aid in its identification and may assist in guiding future synthetic experiments as well.

SurvMaximin: Robust federated approach to transporting survival risk prediction models.

OBJECTIVE: For multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and high-dimensional features, we propose the SurvMaximin algorithm to estimate Cox model feature coefficients for a target population by borrowing summary information from a set of health care centers without sharing patient-level information. MATERIALS AND METHODS: For each of the centers from which we want to borrow information to improve the prediction performance for the target population, a penalized Cox model is fitted to estimate feature coefficients for the center. Using estimated feature coefficients and the covariance matrix of the target population, we then obtain a SurvMaximin estimated set of feature coefficients for the target population. The target population can be an entire cohort comprised of all centers, corresponding to federated learning, or a single center, corresponding to transfer learning. RESULTS: Simulation studies and a real-world international electronic health records application study, with 15 participating health care centers across three countries (France, Germany, and the U.S.), show that the proposed SurvMaximin algorithm achieves comparable or higher accuracy compared with the estimator using only the information of the target site and other existing methods. The SurvMaximin estimator is robust to variations in sample sizes and estimated feature coefficients between centers, which amounts to significantly improved estimates for target sites with fewer observations. CONCLUSIONS: The SurvMaximin method is well suited for both federated and transfer learning in the high-dimensional survival analysis setting. SurvMaximin only requires a one-time summary information exchange from participating centers. Estimated regression vectors can be very heterogeneous. SurvMaximin provides robust Cox feature coefficient estimates without outcome information in the target population and is privacy-preserving.

Analysis of a preQ1-I riboswitch in effector-free and bound states reveals a metabolite-programmed nucleobase-stacking spine that controls gene regulation.

Riboswitches are structured RNA motifs that recognize metabolites to alter the conformations of downstream sequences, leading to gene regulation. To investigate this molecular framework, we determined crystal structures of a preQ1-I riboswitch in effector-free and bound states at 2.00 Å and 2.65 Å-resolution. Both pseudoknots exhibited the elusive L2 loop, which displayed distinct conformations. Conversely, the Shine-Dalgarno sequence (SDS) in the S2 helix of each structure remained unbroken. The expectation that the effector-free state should expose the SDS prompted us to conduct solution experiments to delineate environmental changes to specific nucleobases in response to preQ1. We then used nudged elastic band computational methods to derive conformational-change pathways linking the crystallographically-determined effector-free and bound-state structures. Pathways featured: (i) unstacking and unpairing of L2 and S2 nucleobases without preQ1-exposing the SDS for translation and (ii) stacking and pairing L2 and S2 nucleobases with preQ1-sequestering the SDS. Our results reveal how preQ1 binding reorganizes L2 into a nucleobase-stacking spine that sequesters the SDS, linking effector recognition to biological function. The generality of stacking spines as conduits for effector-dependent, interdomain communication is discussed in light of their existence in adenine riboswitches, as well as the turnip yellow mosaic virus ribosome sensor.

Distinguishing Admissions Specifically for COVID-19 From Incidental SARS-CoV-2 Admissions: National Retrospective Electronic Health Record Study.

BACKGROUND: Admissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. Electronic health record (EHR)-based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. Although the need to improve classification of COVID-19 versus incidental SARS-CoV-2 is well understood, the magnitude of the problems has only been characterized in small, single-center studies. Furthermore, there have been no peer-reviewed studies evaluating methods for improving classification. OBJECTIVE: The aims of this study are to, first, quantify the frequency of incidental hospitalizations over the first 15 months of the pandemic in multiple hospital systems in the United States and, second, to apply electronic phenotyping techniques to automatically improve COVID-19 hospitalization classification. METHODS: From a retrospective EHR-based cohort in 4 US health care systems in Massachusetts, Pennsylvania, and Illinois, a random sample of 1123 SARS-CoV-2 PCR-positive patients hospitalized from March 2020 to August 2021 was manually chart-reviewed and classified as "admitted with COVID-19" (incidental) versus specifically admitted for COVID-19 ("for COVID-19"). EHR-based phenotyping was used to find feature sets to filter out incidental admissions. RESULTS: EHR-based phenotyped feature sets filtered out incidental admissions, which occurred in an average of 26% of hospitalizations (although this varied widely over time, from 0% to 75%). The top site-specific feature sets had 79%-99% specificity with 62%-75% sensitivity, while the best-performing across-site feature sets had 71%-94% specificity with 69%-81% sensitivity. CONCLUSIONS: A large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.

Glucose Increases STAT3 Activation, Promoting Sustained XRCC1 Expression and Increasing DNA Repair.

Dysregulation of DNA repair is a hallmark of cancer, though few cancer-specific mechanisms that drive the overexpression of DNA repair proteins are known. We previously identified STAT3 as a novel transcriptional regulator of X-ray cross-complementing group 1 (XRCC1), an essential scaffold protein in base excision repair in triple-negative breast cancers. We also identified an inducible response to IL-6 and epidermal growth factor stimulation in the non-tumorigenic embryonic kidney cell line HEK293T. As IL-6 and EGF signaling are growth and inflammatory-inducible responses, we examined if glucose challenge can increase STAT3 activation, promoting adaptive changes in XRCC1 expression in different cell types. Acute high glucose exposure promoted XRCC1 expression through STAT3 activation, increasing the repair of methyl methanesulfonate-induced DNA damage in HEK293T cells and the osteosarcoma cell line U2OS. Sustained exposure to high glucose promoted the overexpression of XRCC1, which can be reversed upon glucose restriction and down-regulation of STAT3 activation. Thus, we have identified a novel link between XRCC1 expression and STAT3 activation following exogenous exposures, which could play a critical role in dictating a cancer cell's response to DNA-damaging agents.

HyperMinHash: MinHash in LogLog space.

In this extended abstract, we describe and analyze a lossy compression of MinHash from buckets of size O(logn) to buckets of size O(loglogn) by encoding using floating-point notation. This new compressed sketch, which we call HyperMinHash, as we build off a HyperLogLog scaffold, can be used as a drop-in replacement of MinHash. Unlike comparable Jaccard index fingerprinting algorithms in sub-logarithmic space (such as b-bit MinHash), HyperMinHash retains MinHash's features of streaming updates, unions, and cardinality estimation. For an additive approximation error ϵ on a Jaccard index t, given a random oracle, HyperMinHash needs O(ϵ-2(loglogn+log1ϵ)) space. HyperMinHash allows estimating Jaccard indices of 0.01 for set cardinalities on the order of 1019 with relative error of around 10% using 2MiB of memory; MinHash can only estimate Jaccard indices for cardinalities of 1010 with the same memory consumption.

Functional diversification accompanies gene family expansion of MED2 homologs in Candida albicans.

Gene duplication facilitates functional diversification and provides greater phenotypic flexibility to an organism. Expanded gene families arise through repeated gene duplication but the extent of functional divergence that accompanies each paralogous gene is generally unexplored because of the difficulty in isolating the effects of single family members. The telomere-associated (TLO) gene family is a remarkable example of gene family expansion, with 14 members in the more pathogenic Candida albicans relative to two TLO genes in the closely-related species C. dubliniensis. TLO genes encode interchangeable Med2 subunits of the major transcriptional regulatory complex Mediator. To identify biological functions associated with each C. albicans TLO, expression of individual family members was regulated using a Tet-ON system and the strains were assessed across a range of phenotypes involved in growth and virulence traits. All TLOs affected multiple phenotypes and a single phenotype was often affected by multiple TLOs, including simple phenotypes such as cell aggregation and complex phenotypes such as virulence in a Galleria mellonella model of infection. No phenotype was regulated by all TLOs, suggesting neofunctionalization or subfunctionalization of ancestral properties among different family members. Importantly, regulation of three phenotypes could be mapped to individual polymorphic sites among the TLO genes, including an indel correlated with two phenotypes, growth in sucrose and macrophage killing. Different selective pressures have operated on the TLO sequence, with the 5' conserved Med2 domain experiencing purifying selection and the gene/clade-specific 3' end undergoing extensive positive selection that may contribute to the impact of individual TLOs on phenotypic variability. Therefore, expansion of the TLO gene family has conferred unique regulatory properties to each paralog such that it influences a range of phenotypes. We posit that the genetic diversity associated with this expansion contributed to C. albicans success as a commensal and opportunistic pathogen.

What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask.

Coincident with the tsunami of COVID-19-related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field.