Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge.

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS-CoV-2 ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. We found that (1) the quality of submitted ligand models and surrounding atoms varied, as judged by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics, and contact scores, and (2) a composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

Heat Inactivation of Nipah Virus for Downstream Single-Cell RNA Sequencing Does Not Interfere with Sample Quality.

Single-cell RNA sequencing (scRNA-seq) technologies are instrumental to improving our understanding of virus-host interactions in cell culture infection studies and complex biological systems because they allow separating the transcriptional signatures of infected versus non-infected bystander cells. A drawback of using biosafety level (BSL) 4 pathogens is that protocols are typically developed without consideration of virus inactivation during the procedure. To ensure complete inactivation of virus-containing samples for downstream analyses, an adaptation of the workflow is needed. Focusing on a commercially available microfluidic partitioning scRNA-seq platform to prepare samples for scRNA-seq, we tested various chemical and physical components of the platform for their ability to inactivate Nipah virus (NiV), a BSL-4 pathogen that belongs to the group of nonsegmented negative-sense RNA viruses. The only step of the standard protocol that led to NiV inactivation was a 5 min incubation at 85 °C. To comply with the more stringent biosafety requirements for BSL-4-derived samples, we included an additional heat step after cDNA synthesis. This step alone was sufficient to inactivate NiV-containing samples, adding to the necessary inactivation redundancy. Importantly, the additional heat step did not affect sample quality or downstream scRNA-seq results.

AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination.

Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

The bad and the good of trends in model building and refinement for sparse-data regions: pernicious forms of overfitting versus good new tools and predictions.

Model building and refinement, and the validation of their correctness, are very effective and reliable at local resolutions better than about 2.5 Šfor both crystallography and cryo-EM. However, at local resolutions worse than 2.5 Šboth the procedures and their validation break down and do not ensure reliably correct models. This is because in the broad density at lower resolution, critical features such as protein backbone carbonyl O atoms are not just less accurate but are not seen at all, and so peptide orientations are frequently wrongly fitted by 90-180°. This puts both backbone and side chains into the wrong local energy minimum, and they are then worsened rather than improved by further refinement into a valid but incorrect rotamer or Ramachandran region. On the positive side, new tools are being developed to locate this type of pernicious error in PDB depositions, such as CaBLAM, EMRinger, Pperp diagnosis of ribose puckers, and peptide flips in PDB-REDO, while interactive modeling in Coot or ISOLDE can help to fix many of them. Another positive trend is that artificial intelligence predictions such as those made by AlphaFold2 contribute additional evidence from large multiple sequence alignments, and in high-confidence parts they provide quite good starting models for loops, termini or whole domains with otherwise ambiguous density.

Estimating County Level Health Indicators Using Spatial Microsimulation.

Given the importance of understanding health outcomes at fine spatial scales, iterative proportional fitting (IPF), a form of small area estimation, was applied to a fixed number of health-related variables (obesity, overweight, diabetes) taken from regionalized 2019 survey responses (n = 5474) from the Idaho Behavioral Risk Factor Surveillance System (BRFSS). Using associated county-level American Community Survey (ACS) census data, a set of constraints, which included age categorization, race, sex, and education level, were used to create county-level weighting matrices for each variable, for each of the seven (7) Idaho public health districts. Using an optimized modeling construction technique, we identified significant constraints and grouping splits for each variable/region, resulting in estimates that were internally and externally validated. Externally validated model results for the most populated counties showed correlations ranging from .79 to .85, with p values all below .05. Estimates indicated higher levels of obesity and overweight individuals for midsouth and southwestern Idaho counties, with a cluster of higher diabetes estimates in the center of the state (Gooding, Lincoln, Minidoka, and Jerome counties). Alternative external sources for health outcomes aligned extremely well with our estimates, with wider confidence intervals in more rural counties with sparse populations.

Associations between AI-Assisted Tumor Amphiregulin and Epiregulin IHC and Outcomes from Anti-EGFR Therapy in the Routine Management of Metastatic Colorectal Cancer.

PURPOSE: High tumor production of the EGFR ligands, amphiregulin (AREG) and epiregulin (EREG), predicted benefit from anti-EGFR therapy for metastatic colorectal cancer (mCRC) in a retrospective analysis of clinical trial data. Here, AREG/EREG IHC was analyzed in a cohort of patients who received anti-EGFR therapy as part of routine care, including key clinical contexts not investigated in the previous analysis. EXPERIMENTAL DESIGN: Patients who received panitumumab or cetuximab ± chemotherapy for treatment of RAS wild-type mCRC at eight UK cancer centers were eligible. Archival formalin-fixed paraffin-embedded tumor tissue was analyzed for AREG and EREG IHC in six regional laboratories using previously developed artificial intelligence technologies. Primary endpoints were progression-free survival (PFS) and overall survival (OS). RESULTS: A total of 494 of 541 patients (91.3%) had adequate tissue for analysis. A total of 45 were excluded after central extended RAS testing, leaving 449 patients in the primary analysis population. After adjustment for additional prognostic factors, high AREG/EREG expression (n = 360; 80.2%) was associated with significantly prolonged PFS [median: 8.5 vs. 4.4 months; HR, 0.73; 95% confidence interval (CI), 0.56-0.95; P = 0.02] and OS [median: 16.4 vs. 8.9 months; HR, 0.66 95% CI, 0.50-0.86; P = 0.002]. The significant OS benefit was maintained among patients with right primary tumor location (PTL), those receiving cetuximab or panitumumab, those with an oxaliplatin- or irinotecan-based chemotherapy backbone, and those with tumor tissue obtained by biopsy or surgical resection. CONCLUSIONS: High tumor AREG/EREG expression was associated with superior survival outcomes from anti-EGFR therapy in mCRC, including in right PTL disease. AREG/EREG IHC assessment could aid therapeutic decisions in routine practice. See related commentary by Randon and Pietrantonio, p. 4021.

Recalled Exposure to COVID-19 Public Education Campaign Advertisements Predicts COVID-19 Vaccine Confidence.

This study examined the relationship between recalled exposure to the We Can Do This COVID-19 Public Education Campaign (the Campaign) and COVID-19 vaccine confidence (the likelihood of vaccination or vaccine uptake) in the general population, including vaccine-hesitant adults (the "Movable Middle"). Analyses used three waves of a triannual, nationally representative panel survey of adults in the U.S. fielded from January to November 2021 (n = 3,446). Proportional odds regression results demonstrated a positive, statistically significant relationship between past 4-month Campaign recall and vaccine confidence, controlling for lagged reports of Campaign recall and vaccine confidence; concurrent and lagged fictional campaign recall; survey wave; and sociodemographics. Results indicated that as one moves from no Campaign recall to infrequent recall, there is a 29% increase in the odds of being in a higher vaccine confidence category. Findings offer evidence of the impact of a COVID-19 public education campaign on increasing vaccine confidence.

The Initial Relationship Between the United States Department of Health and Human Services' Digital COVID-19 Public Education Campaign and Vaccine Uptake: Campaign Effectiveness Evaluation.

BACKGROUND: Over 1 million people in the United States have died of COVID-19. In response to this public health crisis, the US Department of Health and Human Services launched the We Can Do This public education campaign in April 2021 to increase vaccine confidence. The campaign uses a mix of digital, television, print, radio, and out-of-home channels to reach target audiences. However, the impact of this campaign on vaccine uptake has not yet been assessed. OBJECTIVE: We aimed to address this gap by assessing the association between the We Can Do This COVID-19 public education campaign's digital impressions and the likelihood of first-dose COVID-19 vaccination among US adults. METHODS: A nationally representative sample of 3642 adults recruited from a US probability panel was surveyed over 3 waves (wave 1: January to February 2021; wave 2: May to June 2021; and wave 3: September to November 2021) regarding COVID-19 vaccination, vaccine confidence, and sociodemographics. Survey data were merged with weekly paid digital campaign impressions delivered to each respondent's media market (designated market area [DMA]) during that period. The unit of analysis was the survey respondent-broadcast week, with respondents nested by DMA. Data were analyzed using a multilevel logit model with varying intercepts by DMA and time-fixed effects. RESULTS: The We Can Do This digital campaign was successful in encouraging first-dose COVID-19 vaccination. The findings were robust to multiple modeling specifications, with the independent effect of the change in the campaign's digital dose remaining practically unchanged across all models. Increases in DMA-level paid digital campaign impressions in a given week from -30,000 to 30,000 increased the likelihood of first-dose COVID-19 vaccination by 125%. CONCLUSIONS: Results from this study provide initial evidence of the We Can Do This campaign's digital impact on vaccine uptake. The size and length of the Department of Health and Human Services We Can Do This public education campaign make it uniquely situated to examine the impact of a digital campaign on COVID-19 vaccination, which may help inform future vaccine communication efforts and broader public education efforts. These findings suggest that campaign digital dose is positively associated with COVID-19 vaccination uptake among US adults; future research assessing campaign impact on reduced COVID-19-attributed morbidity and mortality and other benefits is recommended. This study indicates that digital channels have played an important role in the COVID-19 pandemic response. Digital outreach may be integral in addressing future pandemics and could even play a role in addressing nonpandemic public health crises.

Accelerating crystal structure determination with iterative AlphaFold prediction.

Experimental structure determination can be accelerated with artificial intelligence (AI)-based structure-prediction methods such as AlphaFold. Here, an automatic procedure requiring only sequence information and crystallographic data is presented that uses AlphaFold predictions to produce an electron-density map and a structural model. Iterating through cycles of structure prediction is a key element of this procedure: a predicted model rebuilt in one cycle is used as a template for prediction in the next cycle. This procedure was applied to X-ray data for 215 structures released by the Protein Data Bank in a recent six-month period. In 87% of cases our procedure yielded a model with at least 50% of Cα atoms matching those in the deposited models within 2 Å. Predictions from the iterative template-guided prediction procedure were more accurate than those obtained without templates. It is concluded that AlphaFold predictions obtained based on sequence information alone are usually accurate enough to solve the crystallographic phase problem with molecular replacement, and a general strategy for macromolecular structure determination that includes AI-based prediction both as a starting point and as a method of model optimization is suggested.

Personalizing neoadjuvant chemotherapy for locally advanced colon cancer: protocols for the international phase III FOxTROT2 and FOxTROT3 randomized controlled trials.

AIM: FOxTROT1 established a new standard of care for managing locally advanced colon cancer (CC) with neoadjuvant chemotherapy (NAC). Six weeks of neoadjuvant oxaliplatin and fluoropyrimidine (OxFp) chemotherapy was associated with greater 2-year disease-free survival (DFS) when compared with proceeding straight to surgery (STS). There is now a need to refine the use of NAC and identify those most likely to benefit. FOxTROT2 will aim to investigate NAC in older adults and those with frailty. FOxTROT3 will aim to assess whether intensified triplet NAC provides additional benefits over OxFp. METHOD: FOxTROT2 and FOxTROT3 are international, open-label, phase III randomized controlled trials. Eligible patients will be identified by the multidisciplinary team. Patient age, frailty and comorbidities will be considered to guide trial entry. Participants will be randomized 2:1 to the intervention or control arm: 6 weeks of dose-adapted neoadjuvant OxFp versus STS in FOxTROT2 and 6 weeks of neoadjuvant modified oxaliplatin, 5-fluorouracil and irinotecan versus OxFp in FOxTROT3. The primary endpoint in FOxTROT2 is 3-year DFS. In FOxTROT3, tumour regression grade and 3-year DFS are co-primary endpoints. DISCUSSION: FOxTROT2 and FOxTROT3 will establish the FOxTROT platform, a key part of our long-term strategy to develop neoadjuvant treatments for CC. FOxTROT2 will investigate NAC in a population under-represented in FOxTROT1 and wider research. FOxTROT3 will assess whether it is possible to induce greater early tumour responses and whether this translates to superior long-term outcomes. Looking ahead, the FOxTROT platform will facilitate further trial comparisons and extensive translational research to optimize the use of NAC in CC.

Hepatitis of unknown aetiology in children - epidemiological overview of cases reported in Europe, 1 January to 16 June 2022.

Following the report of an excess in paediatric cases of severe acute hepatitis of unknown aetiology by the United Kingdom (UK) on 5 April 2022, 427 cases were reported from 20 countries in the World Health Organization European Region to the European Surveillance System TESSy from 1 January 2022 to 16 June 2022. Here, we analysed demographic, epidemiological, clinical and microbiological data available in TESSy. Of the reported cases, 77.3% were 5 years or younger and 53.5% had a positive test for adenovirus, 10.4% had a positive RT-PCR for SARS-CoV-2 and 10.3% were coinfected with both pathogens. Cases with adenovirus infections were significantly more likely to be admitted to intensive care or high-dependency units (OR = 2.11; 95% CI: 1.18-3.74) and transplanted (OR = 3.36; 95% CI: 1.19-9.55) than cases with a negative test result for adenovirus, but this was no longer observed when looking at this association separately between the UK and other countries. Aetiological studies are needed to ascertain if adenovirus plays a role in this possible emergence of hepatitis cases in children and, if confirmed, the mechanisms that could be involved.

Impact of meningococcal ACWY conjugate vaccines on pharyngeal carriage in adolescents: evidence for herd protection from the UK MenACWY programme.

OBJECTIVE: Serogroup W and Y invasive meningococcal disease increased globally from 2000 onwards. Responding to a rapid increase in serogroup W clonal complex 11 (W:cc11) invasive meningococcal disease, the UK replaced an adolescent booster dose of meningococcal C conjugate vaccine with quadrivalent MenACWY conjugate vaccine in 2015. By 2018, the vaccine coverage in the eligible school cohorts aged 14 to 19 years was 84%. We assessed the impact of the MenACWY vaccination programme on meningococcal carriage. METHODS: An observational study of culture-defined oropharyngeal meningococcal carriage prevalence before and after the start of the MenACWY vaccination programme in UK school students, aged 15 to 19 years, using two cross-sectional studies: 2014 to 2015 "UKMenCar4" and 2018 "Be on the TEAM" (ISRCTN75858406). RESULTS: A total of 10 625 participants preimplementation and 13 438 postimplementation were included. Carriage of genogroups C, W, and Y (combined) decreased from 2.03 to 0.71% (OR 0.34 [95% CI 0.27-0.44], p < 0.001). Carriage of genogroup B meningococci did not change (1.26% vs 1.23% [95% CI 0.77-1.22], p = 0.80) and genogroup C remained rare (n = 7/10 625 vs 17/13 438, p = 0.135). The proportion of serogroup positive isolates (i.e. those expressing capsule) decreased for genogroup W by 53.8% (95% CI -5.0 - 79.8, p = 0.016) and for genogroup Y by 30.1% (95% CI 8.946·3, p = 0.0025). DISCUSSION: The UK MenACWY vaccination programme reduced carriage acquisition of genogroup and serogroup Y and W meningococci and sustained low levels of genogroup C carriage. These data support the use of quadrivalent MenACWY conjugate vaccine for indirect (herd) protection.

The importance of residue-level filtering and the Top2018 best-parts dataset of high-quality protein residues.

We have curated a high-quality, "best-parts" reference dataset of about 3 million protein residues in about 15,000 PDB-format coordinate files, each containing only residues with good electron density support for a physically acceptable model conformation. The resulting prefiltered data typically contain the entire core of each chain, in quite long continuous fragments. Each reference file is a single protein chain, and the total set of files were selected for low redundancy, high resolution, good MolProbity score, and other chain-level criteria. Then each residue was critically tested for adequate local map quality to firmly support its conformation, which must also be free of serious clashes or covalent-geometry outliers. The resulting Top2018 prefiltered datasets have been released on the Zenodo online web service and are freely available for all uses under a Creative Commons license. Currently, one dataset is residue filtered on main chain plus Cß atoms, and a second dataset is full-residue filtered; each is available at four different sequence-identity levels. Here, we illustrate both statistics and examples that show the beneficial consequences of residue-level filtering. That process is necessary because even the best of structures contain a few highly disordered local regions with poor density and low-confidence conformations that should not be included in reference data. Therefore, the open distribution of these very large, prefiltered reference datasets constitutes a notable advance for structural bioinformatics and the fields that depend upon it.

Atraumatic Medullary Osteonecrosis of the Tibia and Femur Treated With Intraosseous Orthobiologics.

Osteonecrosis (ON) is a painful condition involving bony cell death with resultant architectural collapse. This report discusses the case of a 50-year-old Caucasian female who presented to an outpatient musculoskeletal clinic with severe chronic left knee pain. She had a history of ulcerative colitis and resultant chronic corticosteroid exposure with subsequent development of knee ON. She was treated with an intraosseous autologous bone marrow concentrate (BMC), demineralized bone matrix (DBM), and platelet-rich plasma (PRP) injection. At 11 months post-injection, she demonstrated a significant improvement in pain scores, mobility, activity, and decreased narcotic use. Intraosseous orthobiologic injection for the treatment of knee ON is a promising procedure with a reasonable safety profile that warrants further study as an alternative to surgical intervention.

Artificial Intelligence-Assisted Amphiregulin and Epiregulin IHC Predicts Panitumumab Benefit in RAS Wild-Type Metastatic Colorectal Cancer.

PURPOSE: High tumor mRNA levels of the EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are associated with anti-EGFR agent response in metastatic colorectal cancer (mCRC). However, ligand RNA assays have not been adopted into routine practice due to issues with analytic precision and practicality. We investigated whether AREG/EREG IHC could predict benefit from the anti-EGFR agent panitumumab. EXPERIMENTAL DESIGN: Artificial intelligence algorithms were developed to assess AREG/EREG IHC in 274 patients from the PICCOLO trial of irinotecan with or without panitumumab (Ir vs. IrPan) in RAS wild-type mCRC. The primary endpoint was progression-free survival (PFS). Secondary endpoints were RECIST response rate (RR) and overall survival (OS). Models were repeated adjusting separately for BRAF mutation status and primary tumor location (PTL). RESULTS: High ligand expression was associated with significant PFS benefit from IrPan compared with Ir [8.0 vs. 3.2 months; HR, 0.54; 95% confidence interval (CI), 0.37-0.79; P = 0.001]; whereas low ligand expression was not (3.4 vs. 4.4 months; HR, 1.05; 95% CI, 0.74-1.49; P = 0.78). The ligand-treatment interaction was significant (P interaction = 0.02) and remained significant after adjustment for BRAF-mutation status and PTL. Likewise, RECIST RR was significantly improved in patients with high ligand expression (IrPan vs. Ir: 48% vs. 6%; P < 0.0001) but not those with low ligand expression (25% vs. 14%; P = 0.10; P interaction = 0.01). The effect on OS was similar but not statistically significant. CONCLUSIONS: AREG/EREG IHC identified patients who benefitted from the addition of panitumumab to irinotecan chemotherapy. IHC is a practicable assay that may be of use in routine practice.

Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge.

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.

Improving SARS-CoV-2 structures: Peer review by early coordinate release.

This work builds upon the record-breaking speed and generous immediate release of new experimental three-dimensional structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins and complexes, which are crucial to downstream vaccine and drug development. We have surveyed those structures to catch the occasional errors that could be significant for those important uses and for which we were able to provide demonstrably higher-accuracy corrections. This process relied on new validation and correction methods such as CaBLAM and ISOLDE, which are not yet in routine use. We found such important and correctable problems in seven early SARS-CoV-2 structures. Two of the structures were soon superseded by new higher-resolution data, confirming our proposed changes. For the other five, we emailed the depositors a documented and illustrated report and encouraged them to make the model corrections themselves and use the new option at the worldwide Protein Data Bank for depositors to re-version their coordinates without changing the Protein Data Bank code. This quickly and easily makes the better-accuracy coordinates available to anyone who examines or downloads their structure, even before formal publication. The changes have involved sequence misalignments, incorrect RNA conformations near a bound inhibitor, incorrect metal ligands, and cis-trans or peptide flips that prevent good contact at interaction sites. These improvements have propagated into nearly all related structures done afterward. This process constitutes a new form of highly rigorous peer review, which is actually faster and more strict than standard publication review because it has access to coordinates and maps; journal peer review would also be strengthened by such access.

Identification of a Male-Produced Volatile Pheromone for Phymatodes dimidiatus (Coleoptera: Cerambycidae) and Seasonal Flight Phenology of Four Phymatodes Species Endemic to the North American Intermountain West.

Research over the last 15 yr has shown widespread pheromone parsimony within the coleopteran family Cerambycidae, with a number of highly conserved pheromone motifs, often shared within and across subfamilies, tribes, and genera. Our goals were to increase our understanding of the evolution of volatile pheromones within the Cerambycidae, their role in reproductive isolation and to identify pheromones for use in the development of lures for monitoring cerambycids. Over 3 yr, we tested 12 compounds known to be cerambycid pheromones as possible attractants at sites across Idaho. This study focused on species within the cerambycine genus Phymatodes (Tribe: Callidiini). We also collected and analyzed headspace volatiles of captured Phymatodes dimidiatus (Kirby). Our results demonstrate that (R)-2-methylbutan-1-ol is a male-produced volatile pheromone for P. dimidiatus. These results are consistent with prior research suggesting that (R)-2-methylbutan-1-ol and (R)-3-hydroxyhexan-2-one, individually or in a blend of both compounds, commonly serve as pheromones for Phymatodes spp. We captured Phymatodes starting in mid-May, continuing through mid-August. Our data indicate that flight periods of Phymatodes spp. in Idaho overlap. These species may be utilizing various mechanisms to ensure reproductive isolation, such as the production of different volatile pheromones, minor components, and/or proportions of components, utilizing different host species and/or host volatiles, differing daily activity periods, and/or occupying different heights in the tree canopy. Our results contribute to the basic understanding of the chemical and behavioral ecology of the Cerambycidae and can be applied to the development of pheromone lures for monitoring of economically important or endangered species.

New tools in MolProbity validation: CaBLAM for CryoEM backbone, UnDowser to rethink "waters," and NGL Viewer to recapture online 3D graphics.

The MolProbity web service provides macromolecular model validation to help correct local errors, for the structural biology community worldwide. Here we highlight new validation features, and also describe how we are fighting back against outside developments which compromise that mission. Our new tool called UnDowser analyzes the properties and context of clashing HOH "waters" to diagnose what they might actually represent; a dozen distinct scenarios are illustrated and described. We now treat alternate conformations more thoroughly, and switching to the Neo4j database (graphical rather than relational) enables cleaner, more comprehensive, and much larger reference datasets. A problematic outside change is that refinement software now increasingly restrains traditional validation criteria (geometry, clashes, rotamers, and even Ramachandran) in order to supplement the sparser experimental data at 3-4 Å resolutions typical of modern cryoEM. But unfortunately the broad density allows model optimization without fixing underlying problems, which means these structures often score much better on validation than they really are. CaBLAM, our tool designed for evaluating peptide orientations at lower resolutions, was described in the previous Tools issue, and here we demonstrate its effectiveness in diagnosing local errors even when other validation outliers have been artificially removed. Sophisticated hacking of the MolProbity server has required continual monitoring and various security measures short of restricting user access. The deprecation of Java applets now prevents KiNG interactive online display of outliers on the 3D model during a MolProbity run, but that important functionality has now been recaptured with a modified version of the Javascript NGL Viewer.