Structural determinants of the dominant conformational epitopes of phospholipase A2 receptor in primary membranous nephropathy.

Anti-phospholipase A2 receptor autoantibody (PLA2R-Ab) plays a critical role in the pathogenesis of primary membranous nephropathy (PMN), an autoimmune kidney disease characterized by immune deposits in the glomerular subepithelial spaces and proteinuria. However, the mechanism of how PLA2R-Abs interact with the conformational epitope(s) of PLA2R has remained elusive. PLA2R is a single transmembrane helix receptor containing ten extracellular domains that begin with a CysR domain followed by a FnII and eight CTLD domains. Here, we examined the interactions of PLA2R-Ab with the full PLA2R protein, N-terminal domain truncations, and C-terminal domain deletions under either denaturing or physiological conditions. Our data demonstrate that the PLA2R-Abs against the dominant epitope (the N-terminal CysR-CTLD1 triple domain) possess weak cross-reactivities to the C-terminal domains beyond CTLD1. Moreover, both the CysR and CTLD1 domains are required to form a conformational epitope for PLA2R-Ab interaction, with FnII serving as a linker domain. Upon close examination, we also observed that patients with newly diagnosed PMN carry two populations of PLA2R-Abs in sera that react to the denatured CysR-CTLD3 (the PLA2R-Ab1) and denatured CysR-CTLD1 (the PLA2R-Ab2) domain complexes on Western blots, respectively. Furthermore, the PLA2R-Ab1 appeared at an earlier time point than PLA2R-Ab2 in patients, whereas the increased levels of PLA2R-Ab2 coincided with the worsening of proteinuria. In summary, our data support that an integrated folding of the three PLA2R N-terminal domains, CysR, FnII, and CTLD1, is a prerequisite to forming the PLA2R conformational epitope and that the dominant epitope-reactive PLA2R-Ab2 plays a critical role in PMN clinical progression.

Rapid Approximate Subset-Based Spectra Prediction for Electron Ionization-Mass Spectrometry.

Mass spectrometry is a vital tool in the analytical chemist's toolkit, commonly used to identify the presence of known compounds and elucidate unknown chemical structures. All of these applications rely on having previously measured spectra for known substances. Computational methods for predicting mass spectra from chemical structures can be used to augment existing spectral databases with predicted spectra from previously unmeasured molecules. In this paper, we present a method for prediction of electron ionization-mass spectra (EI-MS) of small molecules that combines physically plausible substructure enumeration and deep learning, which we term rapid approximate subset-based spectra prediction (RASSP). The first of our two models, FormulaNet, produces a probability distribution over chemical subformulae to achieve a state-of-the-art forward prediction accuracy of 92.9% weighted (Stein) dot product and database lookup recall (within top 10 ranked spectra) of 98.0% when evaluated against the NIST 2017 Mass Spectral Library. The second model, SubsetNet, produces a probability distribution over vertex subsets of the original molecule graph to achieve similar forward prediction accuracy and superior generalization in the high-resolution, low-data regime. Spectra predicted by our best model improve upon the previous state-of-the-art spectral database lookup error rate by a factor of 2.9×, reducing the lookup error (top 10) from 5.7 to 2.0%. Both models can train on and predict spectral data at arbitrary resolution. Source code and predicted EI-MS spectra for 73.2M small molecules from PubChem will be made freely accessible online.

Type I interferon responses in rhesus macaques prevent SIV infection and slow disease progression.

Inflammation in HIV infection is predictive of non-AIDS morbidity and death, higher set point plasma virus load and virus acquisition; thus, therapeutic agents are in development to reduce its causes and consequences. However, inflammation may simultaneously confer both detrimental and beneficial effects. This dichotomy is particularly applicable to type I interferons (IFN-I) which, while contributing to innate control of infection, also provide target cells for the virus during acute infection, impair CD4 T-cell recovery, and are associated with disease progression. Here we manipulated IFN-I signalling in rhesus macaques (Macaca mulatta) during simian immunodeficiency virus (SIV) transmission and acute infection with two complementary in vivo interventions. We show that blockade of the IFN-I receptor caused reduced antiviral gene expression, increased SIV reservoir size and accelerated CD4 T-cell depletion with progression to AIDS despite decreased T-cell activation. In contrast, IFN-α2a administration initially upregulated expression of antiviral genes and prevented systemic infection. However, continued IFN-α2a treatment induced IFN-I desensitization and decreased antiviral gene expression, enabling infection with increased SIV reservoir size and accelerated CD4 T-cell loss. Thus, the timing of IFN-induced innate responses in acute SIV infection profoundly affects overall disease course and outweighs the detrimental consequences of increased immune activation. Yet, the clinical consequences of manipulation of IFN signalling are difficult to predict in vivo and therapeutic interventions in human studies should be approached with caution.

Sex, obesity, diabetes, and exposure to particulate matter among patients with severe asthma: Scientific insights from a comparative analysis of open clinical data sources during a five-day hackathon.

This special communication describes activities, products, and lessons learned from a recent hackathon that was funded by the National Center for Advancing Translational Sciences via the Biomedical Data Translator program ('Translator'). Specifically, Translator team members self-organized and worked together to conceptualize and execute, over a five-day period, a multi-institutional clinical research study that aimed to examine, using open clinical data sources, relationships between sex, obesity, diabetes, and exposure to airborne fine particulate matter among patients with severe asthma. The goal was to develop a proof of concept that this new model of collaboration and data sharing could effectively produce meaningful scientific results and generate new scientific hypotheses. Three Translator Clinical Knowledge Sources, each of which provides open access (via Application Programming Interfaces) to data derived from the electronic health record systems of major academic institutions, served as the source of study data. Jupyter Python notebooks, shared in GitHub repositories, were used to call the knowledge sources and analyze and integrate the results. The results replicated established or suspected relationships between sex, obesity, diabetes, exposure to airborne fine particulate matter, and severe asthma. In addition, the results demonstrated specific differences across the three Translator Clinical Knowledge Sources, suggesting cohort- and/or environment-specific factors related to the services themselves or the catchment area from which each service derives patient data. Collectively, this special communication demonstrates the power and utility of intense, team-oriented hackathons and offers general technical, organizational, and scientific lessons learned.

Optimal seed solver: optimizing seed selection in read mapping.

MOTIVATION: Optimizing seed selection is an important problem in read mapping. The number of non-overlapping seeds a mapper selects determines the sensitivity of the mapper while the total frequency of all selected seeds determines the speed of the mapper. Modern seed-and-extend mappers usually select seeds with either an equal and fixed-length scheme or with an inflexible placement scheme, both of which limit the ability of the mapper in selecting less frequent seeds to speed up the mapping process. Therefore, it is crucial to develop a new algorithm that can adjust both the individual seed length and the seed placement, as well as derive less frequent seeds. RESULTS: We present the Optimal Seed Solver (OSS), a dynamic programming algorithm that discovers the least frequently-occurring set of x seeds in an L-base-pair read in [Formula: see text] operations on average and in [Formula: see text] operations in the worst case, while generating a maximum of [Formula: see text] seed frequency database lookups. We compare OSS against four state-of-the-art seed selection schemes and observe that OSS provides a 3-fold reduction in average seed frequency over the best previous seed selection optimizations. AVAILABILITY AND IMPLEMENTATION: We provide an implementation of the Optimal Seed Solver in C++ at: https://github.com/CMU-SAFARI/Optimal-Seed-Solver CONTACT: hxin@cmu.edu, calkan@cs.bilkent.edu.tr or onur@cmu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pain Management of Patients with Substance Abuse in the Ambulatory Setting.

PURPOSE OF REVIEW: Abuse of illicit substances and prescription opioids is a growing problem that presents challenges for pain management in the inpatient and outpatient setting. With future patient care models shifting toward shorter hospital stays and more same-day surgeries, it is crucial that clinicians learn to manage this patient population and strike a balance between the overtreatment of pain that can subsequently worsen tolerance and addiction, and the undertreatment of pain that can lead to pseudoaddiction. RECENT FINDINGS: Through recognition of maladaptive behaviors, use of screening programs, and pain contracts, physicians in the outpatient setting can improve their oversight and shepherding of these patients. In the inpatient setting, regularly scheduled rather than PRN opioids are recommended for chronic opioid users, and good communication with the patient's outpatient prescriber of pain medications is essential. For surgical patients on chronic opioid therapy, making a multimodal plan in advance of the day of surgery that may incorporate NSAIDs, tricyclics, gabapentinoids, anticonvulsants, opioid tapering, and regional anesthesia can help alleviate high postoperative pain control requirements. In conjunction with such medication management, setting realistic expectations for pain control with preoperative counseling may be highly beneficial. For postoperative pain refractory to other strategies, the use of inpatient low-dose ketamine infusions is a novel approach that is gaining popularity, but this does require monitoring by a dedicated pain service.

Concept of the Ambulatory Pain Physician.

PURPOSE OF REVIEW: Given the growing number of ambulatory surgeries being performed and the variability in postoperative pain requirements, early discharge, and inconsistent follow-up, ambulatory surgery presents a unique challenge for this patient population and warrants the presence of an ambulatory pain specialist to evaluate a patient preoperatively and postoperatively to optimize patient safety and satisfaction. This article explores the crucial role that a dedicated pain physician would have in the ambulatory surgery setting. RECENT FINDINGS: The prevalence of chronic pain, opioid use, and substance abuse is growing in this country, while ambulatory and same-day surgery have also experienced considerable growth. Inevitably, more patients with challenging chronic pain or substance abuse are having ambulatory surgery. Increased BMI, advanced age, more comorbidities warranting a higher ASA physical status classification, and longer surgeries are now all components of ambulatory surgery that contribute to increased risk too. Certain surgeries including breast surgery, inguinal hernia repair, and thoracotomy are at higher risk for the conversion of acute to chronic pain, and an ambulatory pain specialist would be beneficial for added focus on these patients. Multimodal pain control with non-opioids and regional anesthesia adjuvants are beneficial, while emphasis on a patient's functional capacity may be more useful than quantifying the severity of pain. Despite the best efforts of patients' primary care providers or surgeons, patients often are discharged with more chronic opioid therapy than they presented with, and an ambulatory pain specialist can help manage the complications and prevent further escalation of this opioid epidemic. An onsite anesthesiologist with interest in pain management in each ambulatory surgery center administering anesthesia and available onsite to deal with immediate preoperative, intraoperative, and recovery room would be ideal to curb and manage complication from uncontrolled pain and related pain issues.

Pain Control in the Presence of Drug Addiction.

Drug addiction is present in a significant proportion of the population in the USA and worldwide. Drug addiction can occur with the abuse of many types of substances including cocaine, marijuana, stimulants, alcohol, opioids, and tranquilizers. There is a high likelihood that clinicians will encounter patients with substance abuse disorders on a regular basis with the prevalence of the use of illicit substances and the high rate of abuse of prescription drugs. The use of abuse deterrent formulations of prescription opioid agents, pill counts, and urine drug abuse screenings are all useful strategies. Optimum pain management of patients with addiction in the outpatient and inpatient setting is essential to minimize pain states. Careful selection of medications and appropriate oversight, including drug agreements, can reduce drug-induced impairments, including sleep deficits and diminished physical, social, and sexual functioning. This review, therefore, discusses the prevalence of illicit and prescription drug addiction, the challenges of achieving optimum pain control, and the therapeutic approaches to be considered in this challenging population. More research is warranted to develop improved therapies and routes of treatments for optimum pain relief and to prevent the development of central sensitization, chronic pain, and impaired physical and social functioning in patients with drug addiction.

Modeling, Production, and Testing of an Echogenic Needle for Ultrasound-Guided Nerve Blocks.

We have designed, produced, and tested an echogenic needle based on a sawtooth pattern where the height of the tooth was 1.25 times the wavelength of the ultrasound transducer. A numeric solution to the time-independent wave equation (Helmholtz equation) was used to create a model of backscattering from a needle. A 21-gauge stainless steel prototype was manufactured and tested in a water bath. Backscattering from the needle was compared to theoretical predications from our model. Based on these results, an 18-gauge prototype needle was fabricated from stainless steel and tested in a pig cadaver. This needle was compared to a commercial 18-gauge echogenic needle (Pajunk Medical Systems, Tucker, GA) by measuring the brightness of the needle relative to the background of sonograms of a needle in a pig cadaver. The backscattering from the 21-gauge prototype needle reproduced the qualitative predictions of our model. At 30° and 45° of insonation, our prototype performed equivalently to the Pajunk needle. At 60°, our prototype was significantly brighter than the Pajunk needle (P = .017). In conclusion, we chose a model for the design of an echogenic needle and modeled it on the basis of a solution to the Helmholtz equation. A prototype needle was tested in a water bath and compared to the model prediction. After verification of our model, we designed an 18-gauge needle, which performed better than an existing echogenic needle (Pajunk) at 60° of insonation. Our needle will require further testing in human trials.

Analysis of plethysmographic waveform changes induced by beach chair positioning under general anesthesia.

During shoulder surgery, patients typically are placed in the beach chair position. In rare cases, this positioning has resulted in devastating outcomes of postoperative cerebral ischemia (Cullen and Kirby in APSF Newsl 22(2):25-27, 2007; Munis in APSF Newsl 22(4):82-83, 2008). This study presents a method to noninvasively and continuously hemodynamically monitor patients during beach chair positioning by using the photoplethysmograph signal recorded from a commercial pulse oximeter. Twenty-nine adults undergoing shoulder surgery were monitored before and after beach chair positioning with electrocardiogram, intermittent blood pressure, end tidal carbon dioxide, and photoplethysmograph via Nellcor finger pulse oximeter. Fast Fourier transform (FFT) was used to perform frequency-domain analysis on the photoplethysmograph (PPG) signal for data segments taken 80-120 s before and after beach chair positioning. The amplitude density of respiration-associated PPG oscillations was quantified measuring the height of the FFT peak at respiratory frequency. Results were reported as (median, interquartile range) and statistical analysis was performed using Wilcoxon sign rank test. Data were also collected when vasoactive drugs phenylephrine and ephedrine were used to maintain acceptable mean arterial pressure during a case. With beach chair positioning, all subjects who did not receive vasoactive drugs showed an increase in the FFT amplitude density of respiration-associated PPG oscillations (p < 0.0001) without change in pulse-associated PPG oscillations. The PPG was more accurate at monitoring the change to beach chair position than blood pressure or heart rate. With vasoactive drugs, pulse-associated PPG oscillations decreased only with phenylephrine while respiration-associated oscillations did not change. Frequency domain analysis of the PPG signal may be a better tool than traditional noninvasive hemodynamic parameters at monitoring patients during beach chair position surgery.

The Interplay Between Human Leukocyte Antigen Antibody Profile and COVID-19 Vaccination in Waitlisted Renal Transplant Patients.

CONTEXT.­: Mass COVID-19 vaccination is mandated in vulnerable populations in our renal transplant waitlist cohort. However, the anti-human leukocyte antigen (anti-HLA) profile after COVID-19 vaccination is controversial, and the side effects are yet to be discerned. OBJECTIVE.­: To evaluate the status of HLA antibodies in waitlist renal transplant patients before and 3 weeks after each vaccination and if comorbidities are associated with the HLA antibody profile. DESIGN.­: A total of 59 waitlisted kidney transplant patients were included in this study. The anti-HLA antibodies were analyzed before and 6 months after their last COVID-19 vaccination. The mean fluorescence intensity change in the anti-HLA antibody levels was used to classify patients into 3 groups: high inducers, low inducers, and noninducers. RESULTS.­: There were significant HLA antibody profile changes after COVID-19 vaccination, showing 21 antibodies generated against HLA class I antigens and 7 against HLA class II antigens to their baseline. Compared with the noninducers, the high and low inducers showed a higher prevalence of COVID-19 infection, COVID-19 vaccine type, and background hypertension history. CONCLUSIONS.­: Our data suggest that COVID-19 vaccination propagates anti-HLA class I and II antibodies for waitlisted renal transplant patients. The clinical significance of these antibodies needs further study. Furthermore, comorbidities, such as history of COVID-19 infection and hypertension, supplemented this effect. Anti-HLA antibody monitoring may be warranted in vaccinated, waitlisted renal transplant patients with COVID-19 vaccinations, and a history of COVID-19 infection or hypertension.

Evaluating the efficacy of combination and single-agent immunotherapies in real-world patterns of disease progression and survival of metastatic melanoma patients.

The objective of this study is to describe survival outcomes in patients with metastatic melanoma in a real-world setting receiving combination and single-agent immunotherapy outside the clinical trial context. We conducted a retrospective single-institution study of patients with metastatic melanoma in a real-world setting. Survival was calculated using log-rank test. Contingency tables were analyzed using Fisher's Exact test. CD8 + T-cell densities were measured using quantitative immunofluorescence and analyzed using Mann-Whitney U test. The median overall survival (OS) for 132 patients was 45.3 months. Brain metastasis did not confer a higher risk of death relative to liver and/or bone disease (39.53 versus 30.00 months, respectively; P  = 0.687). Anti-PD-1 monotherapy was the most common first-line treatment, received by 49.2% of patients. There was no significant difference in OS between patients receiving single-agent anti-PD-1 and combination anti-PD-1 plus CTLA-4 (39.4 months versus undefined; P  = 0.643). Patients treated with combination therapy were more likely to be alive without progression at the last follow-up than those who received monotherapy (70.4% versus 49.2%; P  = 0.0408). Median OS was 21.8 months after initiation of second-line therapy after anti-PD-1 monotherapy. CD8+ T-cell densities were higher in patients who achieved disease control on first-line immunotherapy ( P  = 0.013). In a real-world setting, patients with metastatic melanoma have excellent survival rates, and treatment benefit can be achieved even after progression on first-line therapy. Combination immunotherapy may produce more favorable long-term outcomes in a real-world setting. High pretreatment CD8+ T-cell infiltration correlates with immunotherapy efficacy.

Colonic Perforation Secondary to COVID-19 Induced Hemorrhagic Colitis in a Patient Heterozygous for Factor V Leiden.

Up to 17.6% of COVID-19 positive patients present with gastrointestinal symptoms and bowel wall abnormalities have been described in up to 31% of COVID-19 positive patients. Here, we present a case of a 40-year-old male diagnosed with COVID-19 complicated by hemorrhagic colitis leading to colonic perforation. CT scan of abdomen and pelvis demonstrated markedly distended descending and sigmoid colon with poorly defined wall, pneumatosis, and pneumoperitoneum. The patient was taken for emergent exploratory laparotomy for extended left hemicolectomy, partial omentectomy, transverse colostomy creation, abdominal washout, repair of small bowel, and appendectomy. The patient was brought back for repeat exploratory laparotomy with ICG perfusion assessment. Patient was found to be heterozygous for factor V Leiden mutation and was never vaccinated for COVID-19. Our case demonstrates a novel use for indocyanine green (ICG) to assess perfusion and underscores the importance of completing a thorough hypercoagulable evaluation following COVID-19 induced thrombotic event.

The predictive and prognostic value of peripheral blood antigen-specific memory B cells in phospholipase A2 receptor-associated membranous nephropathy.

Background: Phospholipase A2 receptor-associated membranous nephropathy (PLA2R-MN) is an anti-PLA2R antibody (PLA2R-Ab) mediated autoimmune kidney disease. Although antibody titer correlates closely with disease activity, whether it can provide longer-term predictions on disease course and progression is unclear. Rituximab, a B-cell depletion therapy, has become the first-line treatment option for PLA2R-MN; however, the response to Rituximab varies among patients. Methods: We developed a flow cytometry-based test that detects and quantifies PLA2R antigen-specific memory B cells (PLA2R-MBCs) in peripheral blood, the primary source for PLA2R-Ab production upon disease relapse. We applied the test to 159 blood samples collected from 28 patients with PLA2R-MN (at diagnosis, during and after immunosuppressive treatment, immunological remission, and relapse) to evaluate the relationship between circulating PLA2R-MBC levels and disease activity. Results: The level of PLA2R-MBCs in healthy controls (n=56) is less than or equal to 1.5% of the total MBC compartment. High circulating PLA2R-MBC levels were detected in two patients post-Rituximab despite achieving immunologic and proteinuric remission, as well as in two patients with negative serum autoantibody but increasing proteinuria. Elimination of these cells with Rituximab improved clinical outcomes. Moreover, five patients exhibited elevated PLA2R-MBC levels before disease relapse, followed by a rapid decline to baseline when relapse became clinically evident. COVID-19 vaccination or SARS-CoV-2 infection significantly affected the dynamics of circulating PLA2R-MBCs. Conclusions: This study suggests that monitoring PLA2R-MBC levels in patients with PLA2R-MN may help refine and individualize immunosuppressive therapy and predict disease course and progression. The technology and findings may also have broader applications in the clinical management of other autoimmune diseases.

hACE2-Induced Allosteric Activation in SARS-CoV versus SARS-CoV-2 Spike Assemblies Revealed by Structural Dynamics.

SARS-CoV and SARS-CoV-2 cell entry begins when spike glycoprotein (S) docks with the human ACE2 (hACE2) receptor. While the two coronaviruses share a common receptor and architecture of S, they exhibit differences in interactions with hACE2 as well as differences in proteolytic processing of S that trigger the fusion machine. Understanding how those differences impact S activation is key to understand its function and viral pathogenesis. Here, we investigate hACE2-induced activation in SARS-CoV and SARS-CoV-2 S using hydrogen/deuterium-exchange mass spectrometry (HDX-MS). HDX-MS revealed differences in dynamics in unbound S, including open/closed conformational switching and D614G-induced S stability. Upon hACE2 binding, notable differences in transduction of allosteric changes were observed extending from the receptor binding domain to regions proximal to proteolytic cleavage sites and the fusion peptide. Furthermore, we report that dimeric hACE2, the native oligomeric form of the receptor, does not lead to any more pronounced structural effect in S compared to saturated monomeric hACE2 binding. These experiments provide mechanistic insights into receptor-induced activation of Sarbecovirus spike proteins.

Geographic and Temporal Trends in COVID-Associated Acute Kidney Injury in the National COVID Cohort Collaborative.

BACKGROUND: AKI is associated with mortality in patients hospitalized with coronavirus disease 2019 (COVID-19); however, its incidence, geographic distribution, and temporal trends since the start of the pandemic are understudied. METHODS: Electronic health record data were obtained from 53 health systems in the United States in the National COVID Cohort Collaborative. We selected hospitalized adults diagnosed with COVID-19 between March 6, 2020, and January 6, 2022. AKI was determined with serum creatinine and diagnosis codes. Time was divided into 16-week periods (P1-6) and geographical regions into Northeast, Midwest, South, and West. Multivariable models were used to analyze the risk factors for AKI or mortality. RESULTS: Of a total cohort of 336,473, 129,176 (38%) patients had AKI. Fifty-six thousand three hundred and twenty-two (17%) lacked a diagnosis code but had AKI based on the change in serum creatinine. Similar to patients coded for AKI, these patients had higher mortality compared with those without AKI. The incidence of AKI was highest in P1 (47%; 23,097/48,947), lower in P2 (37%; 12,102/32,513), and relatively stable thereafter. Compared with the Midwest, the Northeast, South, and West had higher adjusted odds of AKI in P1. Subsequently, the South and West regions continued to have the highest relative AKI odds. In multivariable models, AKI defined by either serum creatinine or diagnostic code and the severity of AKI was associated with mortality. CONCLUSIONS: The incidence and distribution of COVID-19-associated AKI changed since the first wave of the pandemic in the United States. PODCAST: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_08_08_CJN0000000000000192.mp3.

Prophages Present in Acinetobacter pittii Influence Bacterial Virulence, Antibiotic Resistance, and Genomic Rearrangements.

Introduction: Antibiotic resistance and virulence are common among bacterial populations, posing a global clinical challenge. The bacterial species Acinetobacter pittii, an infectious agent in clinical environments, has shown increasing rates of antibiotic resistance. Viruses that integrate as prophages into A. pittii could be a potential cause of this pathogenicity, as they often contain antibiotic resistance or virulence factor gene sequences. Methods: In this study, we analyzed 25 A. pittii strains for potential prophages. Using virulence factor databases, we identified many common and virulent prophages in A. pittii. Results: The analysis also included a specific catalogue of the virulence factors and antibiotic resistance genes contributed by A. pittii prophages. Finally, our results illustrate multiple similarities between A. pittii and its bacterial relatives with regard to prophage integration sites and prevalence. Discussion: These findings provide a broader insight into prophage behavior that can be applied to future studies on similar species in the Acinetobacter calcoaceticus-baumannii complex.

Structural dynamics reveal isolate-specific differences at neutralization epitopes on HIV Env.

The envelope glycoprotein (Env) is the sole target for neutralizing antibodies against HIV and the most rapidly evolving, variable part of the virus. High-resolution structures of Env trimers captured in the pre-fusion, closed conformation have revealed a high degree of structural similarity across diverse isolates. Biophysical data, however, indicate that Env is highly dynamic, and the level of dynamics and conformational sampling is believed to vary dramatically between HIV isolates. Dynamic differences likely influence neutralization sensitivity, receptor activation, and overall trimer stability. Here, using hydrogen/deuterium-exchange mass spectrometry (HDX-MS), we have mapped local dynamics across native-like Env SOSIP trimers from diverse isolates. We show that significant differences in epitope order are observed across most sites targeted by broadly neutralizing antibodies. We also observe isolate-dependent conformational switching that occurs over a broad range of timescales. Lastly, we report that hyper-stabilizing mutations that dampen dynamics in some isolates have little effect on others.

Harmonizing units and values of quantitative data elements in a very large nationally pooled electronic health record (EHR) dataset.

OBJECTIVE: The goals of this study were to harmonize data from electronic health records (EHRs) into common units, and impute units that were missing. MATERIALS AND METHODS: The National COVID Cohort Collaborative (N3C) table of laboratory measurement data-over 3.1 billion patient records and over 19 000 unique measurement concepts in the Observational Medical Outcomes Partnership (OMOP) common-data-model format from 55 data partners. We grouped ontologically similar OMOP concepts together for 52 variables relevant to COVID-19 research, and developed a unit-harmonization pipeline comprised of (1) selecting a canonical unit for each measurement variable, (2) arriving at a formula for conversion, (3) obtaining clinical review of each formula, (4) applying the formula to convert data values in each unit into the target canonical unit, and (5) removing any harmonized value that fell outside of accepted value ranges for the variable. For data with missing units for all the results within a lab test for a data partner, we compared values with pooled values of all data partners, using the Kolmogorov-Smirnov test. RESULTS: Of the concepts without missing values, we harmonized 88.1% of the values, and imputed units for 78.2% of records where units were absent (41% of contributors' records lacked units). DISCUSSION: The harmonization and inference methods developed herein can serve as a resource for initiatives aiming to extract insight from heterogeneous EHR collections. Unique properties of centralized data are harnessed to enable unit inference. CONCLUSION: The pipeline we developed for the pooled N3C data enables use of measurements that would otherwise be unavailable for analysis.

COVID-19-associated AKI in hospitalized US patients: incidence, temporal trends, geographical distribution, risk factors and mortality.

Background: Acute kidney injury (AKI) is associated with mortality in patients hospitalized with COVID-19, however, its incidence, geographic distribution, and temporal trends since the start of the pandemic are understudied. Methods: Electronic health record data were obtained from 53 health systems in the United States (US) in the National COVID Cohort Collaborative (N3C). We selected hospitalized adults diagnosed with COVID-19 between March 6th, 2020, and January 6th, 2022. AKI was determined with serum creatinine (SCr) and diagnosis codes. Time were divided into 16-weeks (P1-6) periods and geographical regions into Northeast, Midwest, South, and West. Multivariable models were used to analyze the risk factors for AKI or mortality. Results: Out of a total cohort of 306,061, 126,478 (41.0 %) patients had AKI. Among these, 17.9% lacked a diagnosis code but had AKI based on the change in SCr. Similar to patients coded for AKI, these patients had higher mortality compared to those without AKI. The incidence of AKI was highest in P1 (49.3%), reduced in P2 (40.6%), and relatively stable thereafter. Compared to the Midwest, the Northeast, South, and West had higher adjusted AKI incidence in P1, subsequently, the South and West regions continued to have the highest relative incidence. In multivariable models, AKI defined by either SCr or diagnostic code, and the severity of AKI was associated with mortality. Conclusions: Uncoded cases of COVID-19-associated AKI are common and associated with mortality. The incidence and distribution of COVID-19-associated AKI have changed since the first wave of the pandemic in the US.