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Gram-negative bacteria have a cell envelope that comprises an outer membrane (OM), a peptidoglycan (PG) layer and an inner membrane (IM)1. The OM and PG are load-bearing, selectively permeable structures that are stabilized by cooperative interactions between IM and OM proteins2,3. In Escherichia coli, Braun's lipoprotein (Lpp) forms the only covalent tether between the OM and PG and is crucial for cell envelope stability4; however, most other Gram-negative bacteria lack Lpp so it has been assumed that alternative mechanisms of OM stabilization are present5. We used a glycoproteomic analysis of PG to show that β-barrel OM proteins are covalently attached to PG in several Gram-negative species, including Coxiella burnetii, Agrobacterium tumefaciens and Legionella pneumophila. In C. burnetii, we found that four different types of covalent attachments occur between OM proteins and PG, with tethering of the β-barrel OM protein BbpA becoming most abundant in the stationary phase and tethering of the lipoprotein LimB similar throughout the cell cycle. Using a genetic approach, we demonstrate that the cell cycle-dependent tethering of BbpA is partly dependent on a developmentally regulated L,D-transpeptidase (Ldt). We use our findings to propose a model of Gram-negative cell envelope stabilization that includes cell cycle control and an expanded role for Ldts in covalently attaching surface proteins to PG.

Portal hypertension represents a dysfunctional hemodynamic alteration within the portal venous system, usually due to cirrhosis. These altered hemodynamics play a direct role in the development of acute, life-threatening variceal hemorrhage and mark an important pathophysiologic step in the development of other sudden and life-threatening complications such as type 1 hepatorenal syndrome and spontaneous bacterial peritonitis. Many life-saving interventions in these patients are aimed at reducing portal venous pressure. The contribution of portal hypertension to the development of variceal hemorrhage, type 1 hepatorenal syndrome (known also by the name HRS-AKI), and spontaneous bacterial peritonitis in cirrhotic patients is discussed. This article reviews the pathophysiology and incidence of life-threatening complications of cirrhotic portal hypertension, with a discussion of management options and treatment costs.

Background: Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer’s disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM. Objective: In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and controls. Methods: By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons. Results: Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus. Conclusion: This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset.

We derive expressions for the survey-window convolved galaxy power spectrum in real space for a full sky and deep redshift survey, but taking into account the geometrical lightcone effect. We investigate the impact of using the standard mean redshift approximation as a function of survey depth, and show that this assumption can lead to both an overall amplitude suppression and scale-dependent error when compared to the `true' spectrum. However, we also show that by using a carefully chosen `effective fixed-time', one can find a range of scales where the approximation to the full model is highly accurate, but only on a more restricted set of scales. We validate the theory by constructing dark matter and galaxy lightcone mock surveys from a large $N$-body simulation with a high cadence of snapshots. We do this by solving the light cone equation exactly for every particle, where the particle worldlines are obtained in a piecewise fashion with cubic interpolation between neighbouring snapshots. We find excellent agreement between our measurements and the theory ($\sim \pm 5\%$) over scales $(0.004 h{\rm Mpc}^{-1} \leq k \leq 0.54 h {\rm Mpc}^{-1})$ and for a variety of magnitude limits. Finally, we look to see how accurately we can measure the turnover scale of the galaxy power spectrum $k_0$. Using the lightcone mocks we show that one can detect the turnover scale with a probability $P \geq 95\%$ in an all-sky catalogue limited to an apparent magnitude $m_{\rm lim}\sim 21$. We also show that the detection significance would remain high for surveys with $m_{\rm lim}\sim22$ and $20\%$ sky coverage., 31 + 11 pages, 12 figures. Closely matches version published in JCAP -- 2022JCAP...08..019P

Background: The introduction of daratumumab into the treatment of multiple myeloma has improved outcomes in patients; however, community oncologists often dose more frequently than the US FDA-approved label. Materials and methods: Integra analyzed its database to elucidate daratumumab treatment patterns and the impact of increased utilization on the cost of care for multiple myeloma. Results: Following week 24, 671 (65%) of 1037 patients remained on daratumumab-containing regimens, with 330 patients continuing more frequent treatments than the expected once-every-4-weeks dosing described in the standard dosing schedule. Patients received an average of 14% more daratumumab doses than the FDA-approved label indicates, increasing the 1-year daratumumab costs by an estimated US$31,353. Conclusion: Daratumumab is utilized more frequently than the FDA-recommended dosing, leading to higher multiple myeloma treatment costs.

We explore an alternative method to the usual shear correlation function approach for the estimation of aperture mass statistics in weak lensing survey data. Our approach builds on the direct estimator method. In this paper, we extend our analysis to statistics of arbitrary order and to the multiscale aperture mass statistics. We show that there always exists a linear order algorithm to retrieve any of these generalised aperture mass statistics from shape catalogs when the direct estimator approach is adopted. We validate our approach through application to a large number of Gaussian mock lensing surveys where the true answer is known and we do this up to 10th order statistics. We then apply our estimators to an ensemble of real-world mock catalogs obtained from N-body simulations - the SLICS mocks, and show that one can expect to retrieve detections of higher order clustering up to fourth order in a KiDS-1000 like survey. We expect that these methods will be of most utility for future wide-field surveys like Euclid and the Rubin Telescope., 13 pages + 11 pages appendix, 10 figures. Matches version published in MNRAS

The concentrations of 3,4-dihydroxybenzoic acid, caffeic acid, catechin, chlorogenic acid, epicatechin, gallic acid, p-coumaric acid, quercetin, rutin, ferulic acid, and the major metals in graviola (Annona muricata), atemoya (A. squamosa x A. cherimola), fruta do conde (A. squamosa), biriba (Rollinia mucosa), and the North American pawpaw (Asimina triloba) were determined by UPLC-ESI (−)-MS/MS. It enabled the identification and quantification of phenolic compounds. Catechin was only found in atemoya, at a concentration of 38.6 μg/g-dw. Only 3,4-dihydroxybenzoic acid was found in the fruit pulps of all five fruits analyzed. Atemoya stands out for not only having catechin but also for having much more epicatechin (239 μg/g-dw) than the other fruits. At the same time, graviola had more p-coumaric acid (62.6 μg/g-dw), and the North American pawpaw had more chlorogenic acid (48.1 μg/g-dw) than the other fruits. Metals were determined by ICP equipped with axially viewed plasma. All five fruit pulps had relatively high levels of potassium, with concentrations ranging from 7640 to 15,000 μg/g-dw, with pawpaw being the lowest and atemoya being the highest. The concentrations of other metals ranged from Ca 547 to 1110, Na 14.3 to 123, P 1210 to 1690, Mg 472 to 980, Mn 1.86 to 5.27, and Zn 5.55 to 7.32 μg/g-dw. All five fruits in the Annonaceae family that were analyzed in this study have several phenolic compounds in them and were good sources of potassium, calcium, phosphorus, and magnesium.

e13507 Background: In August 2019 IC partnered with University of Pittsburg Medical Center (UPMC) on a QI aimed at improving outcomes in stages 3 and 4 NSCLC. This report details the findings, interventions, and results in the stage 4 cohort to date. Guidelines advocate broad molecular profiling and completion of biomarker testing prior to initiation of initial therapy (KF Mileham,2022). However, real world data has shown a high rate of treatment initiation without biomarker testing due to low rate of testing and, if tested, treatment prior to results reporting (H West,2021; J Nicholas, 2021) in this disease state having a 5-year survival of only 7% (N Howlander). Based on analysis of the US Oncology Network it was found that only 46% of patients (pts) with metastatic NSCLC received testing for PD-L1, EGFR, ALK, ROS1, and BRAF-V600E (J Nicholas, 2021). Methods: By querying the UPMC and IC databases, 847 patients (pts) with ND NSCLC-4 were identified who received an initial line of therapy, excluding squamous carcinoma pts unless documented never-smokers, during 1/1/2017- 12/31/2021. Date of EGFR test ordered, date of test result report to electronic health record, and date of treatment initiation were captured. Also included were test orders for the NCCN recommended biomarker panel of PD-L1, ALK, ROS1, BRAF, RET, MET, and NTRK. The data were evaluated in three time periods for the QI: Phase 1 of 1339 days (1/1/2017-8/31/2020) for baseline, Phase 2 of 122 days (9/1/2020-12/31/20) post physician leadership intervention, and Phase 3 of 272 days (1/1/2021-9/30/2021) performance measurement period. Baseline and on-going measurement of testing metrics was performed with physician leadership intervention for identified gaps in care. Additionally, surveys were implemented to assess caregiver perceptions. The use of chart curation and software-based monitoring tools powered by IC enabled providers to understand current levels of testing and track performance over time. Results: Median age was 68 (range 36 - 89) and 49% male. As shown in Data Table, EGFR testing at baseline was 94% and increased to 96%. Testing of the entire biomarker panel noted above increased from 52% baseline to 76% at this point in Phase 3. While only 72% had treatment initiated after EGFR result at baseline, this improved to 88% during Phase 3. Conclusions: This QI led to improvement in rates of broad biomarker testing and initiation of treatment only after results were made available in this NSCLC-4 population. While this initiative was not designed to evaluate outcomes, one would expect outcome improvement over baseline with higher guideline adherence.[Table: see text]

We present a joint likelihood analysis of the real-space power spectrum and bispectrum measured from a variety of halo and galaxy mock catalogs. A novel aspect of this work is the inclusion of nonlinear triangle configurations for the bispectrum, made possible by a complete next-to-leading order ("one-loop") description of galaxy bias, as is already common practice for the power spectrum. Based on the goodness-of-fit and the unbiasedness of the parameter posteriors, we accomplish a stringent validation of this model compared to the leading order ("tree-level") bispectrum. Using measurement uncertainties that correspond to an effective survey volume of $6\,(\mathrm{Gpc}/h)^3$, we determine that the one-loop corrections roughly double the applicable range of scales, from $\sim 0.17\,h/\mathrm{Mpc}$ (tree-level) to $\sim 0.3\,h/\mathrm{Mpc}$. This converts into a $1.5 - 2$x improvement on constraints of the linear bias parameter at fixed cosmology, and a $1.5 - 2.4$x shrinkage of uncertainties on the amplitude of fluctuations $A_s$, which clearly demonstrates the benefit of extracting information from nonlinear scales despite having to marginalize over a larger number of bias parameters. Besides, our precise measurements of galaxy bias parameters up to fourth order allow for thorough comparisons to coevolution relations, showing excellent agreement for all contributions generated by the nonlocal action of gravity. Using these relations in the likelihood analysis does not compromise the model validity and is crucial for obtaining the quoted improvements on $A_s$. We also analyzed the impact of higher-derivative and scale-dependent stochastic terms, finding that for a subset of our tracers the former can boost the performance of the tree-level model with constraints on $A_s$ that are only slightly degraded compared to the one-loop model., Comment: 33 pages, 13 figures, supporting Mathematica notebook available at https://doi.org/10.5281/zenodo.4529886, Python package for Delaunay binning correction available at https://github.com/aegge/BispTools

This paper provides a perspective on historical background, innovation and applications of Artificial Intelligence (AI) and Machine Learning (ML), data successes and systems challenges, national security interests, and mission opportunities for system problems. AI and ML today are used interchangeably, or together as AI/ML, and are ubiquitous among many industries and applications. The recent explosion, based on a confluence of new ML algorithms, large data sets, and fast and cheap computing, has demonstrated impressive results in classification and regression and used for prediction, and decision-making. Yet, AI/ML today lacks a precise definition, and as a technical discipline, it has grown beyond its origins in computer science. Even though there are impressive feats, primarily of ML, there still is much work needed in order to see the systems benefits of AI, such as perception, reasoning, planning, acting, learning, communicating, and abstraction. Recent national security interests in AI/ML have focused on problems including multidomain operations (MDO), and this has renewed the focus on a systems view of AI/ML. This paper will address the solutions for systems from an AI/ML perspective and that these solutions will draw from methods in AI and ML, as well as computational methods in control, estimation, communication, and information theory, as in the early days of cybernetics. Along with the focus on developing technology, this paper will also address the challenges of integrating these AI/ML systems for warfare.

1530 Background: In a prior analysis, we identified 525 pts with newly diagnosed NSCLC 4 harboring AOD in the ICD. Of these, 141 were treated prior to the reporting of AOD with chemotherapy (C), immune checkpoint inhibitor (ICI), or both. This report details the clinical outcomes of these 141 compared to the 384 treated after AOD reported. Methods: Real world data (RWD) were obtained from a curated ICD for pts with NSCLC 4 diagnosed 1/1/2018-12/31/2020 with cutoff of data 3/31/2021. Pts with EGFR, ALK, ROS1, BRAF, MET, RET, HER2, and NTRK were included if their treatment record were captured. Also included were demographics, ECOG score, date of first report of AOD and dates of initiations of first and any second line of therapy and date of apparent death (AD). Outcome measures were time to next treatment or apparent death (TTNT) and apparent survival (AS) (ICD model does not allow date of death per HIPAA de-identified Expert Determination). Descriptive statistics were used with Kaplan-Meier (K-M) estimates and Hazard Ratios (HR) by Cox regression. 3 cohorts were defined: Group (Gr) A with 384 pts treated after AOD reported and used as the comparator; the 141 pts treated before AOD with C, ICI or both were divided into Gr B (n = 51) who subsequently switched to TKI within 35 days and Gr C (n = 90) who did not switch. Results: As shown in data table, AS was significantly worse in Gr B and Gr C, TTNT was significantly worse in Gr C and with worsening trend in Gr B. Two potential confounders were identified: higher ECOG scores might indicate more urgency to assign treatment, but pts with ECOG ≥ 2 were similar in all 3 groups; also, difference in proportion of EGFRm by Group (Gr A 62%, Gr B 57%, and Gr C 29%), but separating cohorts by EGFR mutation status did not alter results. Conclusions: While subject to the limitations of a retrospective observational RWD study, this study strongly suggests outcomes are significantly compromised in pts harboring AOD but who are treated initially with C, ICI or both, even in pts quickly switched to TKI. Since a prospective clinical trial is not ethically feasible, these findings may stimulate review of current guidelines, fuel optimization of universal testing in NSCLC 4, and encourage utilization of liquid or ultra-fast NGS with their rapid turnaround times in order to improve survival in this setting. [Table: see text]

e13510 Background: Broad molecular profile-based initiation of Tx in newly diagnosed NSCLC 4 (KF Mileham, Cancer Med, 2022) is advocated by NCCN guidelines. Despite this, Tx is often started prior to, and without knowledge of, an actionable oncogenic driver (AOD), and often without subsequent switch to appropriate tyrosine kinase inhibitor (TKI). In this study we sought to assess the impact of TAT of genomic testing on Tx in patients harboring a potentially actionable EGFR mutation. Methods: By interrogating the IC curated database, we identified 2,357 newly diagnosed NSCLC 4 patients (pts) who started an initial line of therapy (LOT 1) between 1/1/2019 and 12/31/2021. Squamous carcinoma pts were excluded unless documented to be never smokers or st Tx start. From this, we calculated TAT and whether Tx was initiated after genomic results. In addition, we captured whether testing was in-house or by reference lab (RL). We looked at the RLs that comprise of the top 85% of NGS test sources, where the testing source was known. We removed records where test order dates and results dates were the same date, where test order dates or results dates were unknown, and where TAT > 90 days. EGFR Effective Testing Rate (EETR) is defined as EGFR result prior to line 1 Tx start. Results: Median age was 70 (range 40 - 89) and 50% male. Pts with TAT of ≤7 days had an 82% EETR vs. Pts with TAT of >29 days had a 61% EETR. Overall, RLs had a median TAT of 19 days with a 72% EETR, whereas in-house labs had a median TAT of 15 days with a EETR of 80%. Conclusions: When providers and patients can obtain test results within 21 days of test order there is a higher likelihood of waiting for the test result to start Tx. Many community oncology practices are contemplating implementing in-house testing solutions to improve rates of testing and turnaround time of testing. This may prove to be an effective strategy given the better TAT for in-house testing. When there is faster TAT, patients and providers wait to start initial Tx. Getting patients on appropriate therapy based on their biomarker status can improve overall survival.[Table: see text]

The power spectrum of the nonlinearly evolved large-scale mass distribution recovers only a minority of the information available on the mass fluctuation amplitude. We investigate the recovery of this information in 2D "slabs" of the mass distribution averaged over $\approx100$~$h^{-1}$Mpc along the line of sight, as might be obtained from photometric redshift surveys. We demonstrate a Hamiltonian Monte Carlo (HMC) method to reconstruct the non-Gaussian mass distribution in slabs, under the assumption that the projected field is a point-transformed Gaussian random field, Poisson-sampled by galaxies. When applied to the \textit{Quijote} $N$-body suite at $z=0.5$ and at a transverse resolution of 2~$h^{-1}$Mpc, the method recovers $\sim 30$ times more information than the 2D power spectrum in the well-sampled limit, recovering the Gaussian limit on information. At a more realistic galaxy sampling density of $0.01$~$h^3$Mpc$^{-3}$, shot noise reduces the information gain to a factor of 5 improvement over the power spectrum at resolutions of 4~$h^{-1}$Mpc or smaller., Comment: 13 pages, 11 figures. Matches published version

We explore an alternative method to the usual shear correlation function approach for the estimation of aperture mass statistics in weak lensing survey data. Our approach builds on the direct estimator method of Schneider (1998). In this paper, to test and validate the methodology, we focus on the aperture mass dispersion. After computing the signal and noise for a weighted set of measured ellipticites we show how the direct estimator can be made into a linear order algorithm that enables a fast and efficient computation. We then investigate the applicability of the direct estimator approach in the presence of a real survey mask with holes and chip gaps. For this we use a large ensemble of full ray-tracing mock simulations. By using various weighting schemes for combining information from different apertures we find that inverse variance weighting the individual aperture estimates with an aperture completeness greater than 70 per cent coverage yields an answer that is in close agreement with the standard correlation function approach. We then apply this approach to the CFHTLenS as pilot scheme and find that our method recovers to high accuracy the Kilbinger (2013) result for the variance of both the E and B mode signal, after we correct the catalogue for the shear bias in the lensfit algorithm for pairs closer than 9". We then explore the cosmological information content of the direct estimator using the Fisher information approach. We show that there is a only modest loss in cosmological information from the rejection of apertures that are of low completeness. This method unlocks the door to fast and efficient methods for recovering higher order aperture mass statistics in linear order operations., Comment: 26 pages, 15 figures. Submitted to MNRAS, comments welcome. v2: updated MNRAS template

Head motion is a major confounding factor in neuroimaging studies. While numerous studies have investigated how motion impacts estimates of functional connectivity, the effects of motion on structural connectivity measured using diffusion MRI have not received the same level of attention, despite the fact that, like functional MRI, diffusion MRI relies on elaborate preprocessing pipelines that require multiple choices at each step. Here, we report a comprehensive analysis of how these choices influence motion-related contamination of structural connectivity estimates. Using a healthy adult sample (N = 252), we evaluated 240 different preprocessing pipelines, devised using plausible combinations of different choices related to explicit head motion correction, tractography propagation algorithms, track seeding methods, track termination constraints, quantitative metrics derived for each connectome edge, and parcellations. We found that an approach to motion correction that includes outlier replacement and within-slice volume correction led to a dramatic reduction in cross-subject correlations between head motion and structural connectivity strength, and that motion contamination is more severe when quantifying connectivity strength using mean tract fractional anisotropy rather than streamline count. We also show that the choice of preprocessing strategy can significantly influence subsequent inferences about network organization, with the location of network hubs varying considerably depending on the specific preprocessing steps applied. Our findings indicate that the impact of motion on structural connectivity can be successfully mitigated using recent motion-correction algorithms that include outlier replacement and within-slice motion correction.HighlightsWe assess how motion affects structural connectivity in 240 preprocessing pipelinesMotion contamination of structural connectivity depends on preprocessing choicesAdvanced motion correction tools reduce motion confoundsFA edge weighting is more susceptible to motion effects than streamline count

Online social networks provide users with unprecedented opportunities to engage with diverse opinions. At the same time, they enable confirmation bias on large scales by empowering individuals to self-select narratives they want to be exposed to. A precise understanding of such tradeoffs is still largely missing. We introduce a social learning model where most participants in a network update their beliefs unbiasedly based on new information, while a minority of participants reject information that is incongruent with their preexisting beliefs. This simple mechanism generates permanent opinion polarization and cascade dynamics, and accounts for the aforementioned tradeoff between confirmation bias and social connectivity through analytic results. We investigate the model’s predictions empirically using US county-level data on the impact of Internet access on the formation of beliefs about global warming. We conclude by discussing policy implications of our model, highlighting the downsides of debunking and suggesting alternative strategies to contrast misinformation.

The diffusion tensor model for diffusion MRI has been used extensively to study asymmetry in the human brain white matter. However, given the limitations of the tensor model, the nature of any underlying asymmetries remains uncertain, particularly in crossing fibre regions. Here, we provide a more robust characterisation of human brain white matter asymmetries based on fibre-specific diffusion MRI metrics and a whole-brain data-driven approach. We used high-quality diffusion MRI data (n = 100) from the Human Connectome Project, the spherical deconvolution model for fibre orientation distribution estimation, and the Fixel-Based Analysis framework to utilise crossing fibre information in registration, data smoothing and statistical inference. We found many significant asymmetries, widespread throughout the brain white matter, with both left>right and right>left dominances observed in different pathways. No influences of sex, age, or handedness on asymmetry were found. We also report on the relative contributions of microstructural and morphological white matter properties toward the asymmetry findings. Our findings should provide important information to future studies focussing on how these asymmetries are affected by disease, development/ageing, or how they correlate to functional/cognitive measures.

In Communication Theory, intermedia agenda-setting refers to the influence that different news sources may have on each other, and how this subsequently affects the breadth of information that is presented to the public. Several studies have attempted to quantify the impact of intermedia agenda-setting in specific countries or contexts, but a large-scale, data-driven investigation is still lacking. Here, we operationalise intermedia agenda-setting by putting forward a methodology to infer networks of influence between different news sources on a given topic, and apply it on a large dataset of news articles published by globally and locally prominent news organisations in 2016. We find influence to be significantly topic-dependent, with the same news sources acting as agenda-setters (i.e., central nodes) with respect to certain topics and as followers (i.e., peripheral nodes) with respect to others. At the same time, we find that the influence networks associated with most topics exhibit small world properties, which we find to play a significant role towards the overall diversity of sentiment expressed about the topic by the news sources in the network. In particular, we find clustering and density of influence networks to act as competing forces in this respect, with the former increasing and the latter reducing diversity., 21 pages, 9 figures

This paper delineates some boundary conditions for the effectiveness of ad creativity on brand responses. By taking a closer look at the divergence factor—the core of creativity, we conceptually define two types of divergence (brand divergence and execution divergence) and empirically test their interactions on brand processing and responses. Incorporating an important factor in ad-viewing situation (consumer involvement), we predict different interaction patterns for the two types of divergence. With one pretest and one 2 × 2 × 2 between-subjects experiment, we find that under particular type of consumer involvement, more divergence of certain type could be effective or distracting, depending on the stage of processing. These findings have potential implications for brand managers to create and implement ads with appropriate combinations of brand and execution divergence.

ObjectiveThe US Veterans Health Administration’s Disaster Emergency Medical Personnel System (DEMPS) is a team of employee disaster response volunteers who provide clinical and non-clinical staffing assistance when local systems are overwhelmed. This study evaluated attitudes and recommendations of the DEMPS program to understand the impact of multi-modal training on volunteer perceptions.MethodsDEMPS volunteers completed an electronic survey in 2012 (n=2120). Three training modes were evaluated: online, field exercise, and face-to-face. Measures included: “Training Satisfaction,” “Attitudes about Training,” “Continued Engagement in DEMPS.” Data were analyzed using χ2and logistic regression. Open-ended questions were evaluated in a manner consistent with grounded theory methodology.ResultsMost respondents participated in DEMPS training (80%). Volunteers with multi-modal training who completed all 3 modes (14%) were significantly more likely to have positive attitudes about training, plan to continue as volunteers, and would recommend DEMPS to others (P-valueConclusionsA blended learning environment using multi-modal training methods, could enhance satisfaction and attitudes and possibly encourage continued engagement in DEMPS or similar programs. DEMPS training program modifications in 2015 expanded this blended learning approach through new interactive online learning opportunities. (Disaster Med Public Health Preparedness. 2018;12:744-751)

BACKGROUND Since the FDA's initial indication for the use of daratumumab in relapsed/refractory multiple myeloma (RRMM) in November 2015, usage has been expanded by subsequent approvals in newly diagnosed, transplant-ineligible MM patients, and more recently in newly diagnosed transplant-eligible patients. Real World Data (RWD) has been published demonstrating daratumumab's efficacy in RRMM settings[1]and its utility of split dosing for the initial dose[2]. However, no study has been published to examine the real-world dosing patterns of daratumumab compared to the FDA standard dosing schedule. While there are minimal variations in the approved dosing schedule of daratumumab, generally accepted dosing is weekly in week 1 through week 8, q 2 Wks in week 9 through week 24, and q 4 Wks after week 24, all at the standard 16 mg/kg dosage[3]. In its approved dosing schedule, adjustments are made in the frequency of administration, but not in the standard weight-based dosing. METHODS Utilizing the Integra Connect database which contains 17 community oncology network accounts and over 1,900 providers in US, we collected all MM patients treated with daratumumab between January 1, 2016 and March 31, 2020. We then excluded any patient whose first line of therapy (LOT) was ambiguous, in order to correctly identify the daratumumab-containing LOTs. We also excluded LOT 1 daratumumab transplant induction due to the wide variation in daratumumab dosing schedules in clinical trials in the transplant eligible patient[4]. LOTs were determined based on International Myeloma Working Group guidelines[5]. Data were collected on the date of each individual daratumumab administration, counting initial split dose, if utilized, as 1 dose. The duration of daratumumab and number of doses administered were calculated and corrected for any time on treatment breaks. The study was conducted per individual patient by LOT cohorts, and for the entire cohort of patients. We utilized the standard dose schedule for daratumumab noted above to establish the expected doses of daratumumab and calculated the compliance dose ratio (ratio of actual doses to expected doses per time on therapy) to evaluate how closely real-world treatment adhered to the standard dosing schedule. RESULTS 1037 MM patients were included with at least 6 doses of daratumumab administration and without stem cell transplant or uncertain LOT. Across all LOTs, the mean duration of daratumumab treatment was 5.6 months with a median duration of 9.8 months. After week twenty-four, 671 (65%) patients remained on daratumumab-containing regimens, with 330 patients continuing q 1 Wk or q 2 Wks dosing, whereas the standard would employ a switch to q 4 Wks dosing (Figure 1). Overall compliance dose ratio was consistently above 100%, implying a significant proportion of patients were receiving more frequent dosing than expected under the standard dosing schedule (Figure 2). We carefully evaluated patients in various LOTs and combination therapies. Drug combination was not found to exert a significant impact on the daratumumab dosing pattern. Compliance dose ratio of daratumumab is slightly higher in RRMM compared to the dose ratio in LOT 1 newly diagnosed MM, but even LOT 1 has a ratio greater than 1 (Figure 3). It should be noted that this increased compliance dose ratio is present in all LOT cohorts despite 25% of patients being started on doses less frequent than weekly (Figure 1). CONCLUSIONS In real-world community oncology practices, daratumumab is utilized in a more frequent dosing schedule than the FDA approved standard dosing. With standard dosing there are 23 daratumumab doses in the first 52 weeks. The compliance dose ratio found in our RWD implies 27.3 doses in the first year for the entire cohort and 26.9 and 28.3 doses in LOTs 2 and 3 respectively. Thus, significantly increased drug and administrative costs are incurred over those anticipated in respect to daratumumab dosing utilization. This study is limited to the EMR and administrative claims data of those individuals who are being treated in a community oncology setting. Residual confounding and bias may exist due to entry error and unobserved patient characteristics. References [1] Gergely Varga, et al; Blood 2018; 132:3257 [2] Rifkin R, et al; Clin Ther. 2019;41(5):866-881 [3] DARZALEX® [Prescribing Information] [4] Abdallah N, et al. Ther Adv Hematol. 2019 Dec 23 [5] Rajkumar SV, et al Blood. 2015;126(7):921-922 Disclosures Smith: Integra Connect: Current Employment; Sanofi: Research Funding. Xue:Sanofi: Research Funding; Integra Connect: Current Employment. Marks:Sanofi: Research Funding. Scott:Integra Connect: Current Employment; Sanofi: Research Funding. Blanc:Sanofi: Research Funding. Nagovski:Sanofi: Research Funding. Lambert:Sanofi: Research Funding; Integra Connect: Current Employment. Varughese:Integra Connect: Current Employment; Sanofi: Research Funding.

Endpoint-to-endpoint fibre bundle connectivity estimated using spherical deconvolution & streamlines tractography in diffusion MRI may be excessive in the presence of pathologies that involve truncation of axons within the white matter. Here we propose a simple modification to an existing method that directly quantifies and corrects for this over-estimation.

“Tractography” refers to the process of digitally reconstructing the spatial trajectories of elongated thin structures based on a continuous field of local orientation data; most commonly in reference to white matter axons within the central nervous system based on a diffusion Magnetic Resonance Imaging (MRI) model. This technology provides a unique capacity to investigate the long-distance connectional structure of such biology both in vivo and noninvasively. This chapter describes the basic principles behind the near-ubiquitous “streamlines” approach to tractography (which has remained relatively unchanged for 20 years) as well as some modern advancements to such, with a particular emphasis on the quantitative capabilities of this technology.