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Infectious disease models are widely used by epidemiologists to improve the understanding of transmission dynamics and disease natural history, and to predict the possible effects of interventions. As the complexity of such models increases, however, it becomes increasingly challenging to robustly calibrate them to empirical data. History matching with emulation is a calibration method that has been successfully applied to such models, but has not been widely used in epidemiology partly due to the lack of available software. To address this issue, we developed a new, user-friendly R package hmer to simply and efficiently perform history matching with emulation. In this paper, we demonstrate the first use of hmer for calibrating a complex deterministic model for the country-level implementation of tuberculosis vaccines to 115 low-and middle-income countries. The model was fit to 9–13 target measures, by varying 19–22 input parameters. Overall, 105 countries were successfully calibrated. Among the remaining countries, hmer visualisation tools, combined with derivative emulation methods, provided strong evidence that the models were misspecified and could not be calibrated to the target ranges. This work shows that hmer can be used to simply and rapidly calibrate a complex model to data from over 100 countries, making it a useful addition to the epidemiologist’s calibration tool-kit.

Supplementary Figure Legends, Figure S1 Dicer- and Drosha-dependent diRNAs are essential for HR repair, Figure S2 Dicer or Drosha is required for the recruitment of MMSET and Tip60 to the DSB, Figure S3 Chemically synthesized oligo-RNAs restored the accumulation of MMSET, Tip60, H4K20me2, 3 and H4K16 Ac at the DSB, Figure S4 Chemically synthesized oligo-RNAs rescued the accumulation of AGO2 at the DSB in Dicer- or Drosha-depleted U2OS cells, Figure S5 Phosphorylation of MMSET at serine 102 site and Tip60 at Tyrosine 44 site enhance the interaction of AGO2 with MMSET and Tip60 after IR (5Gy) exposure, Figure S6 diRNAs bind to AGO2/MMSET/Tip60 complex. A-C, DR-GFP/U2OS cells transfected with indicated siRNA for two days were further transfected with infected with pCBA-β vector expressing I-SecI for another one day, Figure S7 Chemically synthesized oligo-RNAs rescued the accumulation of Rad51 and BRCA1 at the DSB, Figure S8 MMST or Tip60 is essential for chromatin relaxation and the recruitment of Rad51 and BRCA1 to the DSB, Figure S9 Dicer or Drosha has no effect on DNA end resection, Supplementary Materials and Methods

Supplementary Figure from Loss of H3K27 Trimethylation Promotes Radiotherapy Resistance in Medulloblastoma and Induces an Actionable Vulnerability to BET Inhibition

Supplementary Data from Loss of H3K27 Trimethylation Promotes Radiotherapy Resistance in Medulloblastoma and Induces an Actionable Vulnerability to BET Inhibition

Medulloblastoma has been categorized into four subgroups based on genetic, epigenetic, and transcriptional profiling. Radiation is used for treating medulloblastoma regardless of the subgroup. A better understanding of the molecular pathways determining radiotherapy response could help improve medulloblastoma treatment. Here, we investigated the role of the EZH2 (enhancer of zeste 2 polycomb repressive complex 2 subunit)-dependent histone H3K27 trimethylation in radiotherapy response in medulloblastoma. The tumors in 47.2% of patients with group 3 and 4 medulloblastoma displayed H3K27me3 deficiency. Loss of H3K27me3 was associated with a radioresistant phenotype, high relapse rates, and poor overall survival. In H3K27me3-deficient medulloblastoma cells, an epigenetic switch from H3K27me3 to H3K27ac occurred at specific genomic loci, altering the transcriptional profile. The resulting upregulation of EPHA2 stimulated excessive activation of the prosurvival AKT signaling pathway, leading to radiotherapy resistance. Bromodomain and extraterminal motif (BET) inhibition overcame radiation resistance in H3K27me3-deficient medulloblastoma cells by suppressing H3K27ac levels, blunting EPHA2 overexpression, and mitigating excessive AKT signaling. In addition, BET inhibition sensitized medulloblastoma cells to radiation by enhancing the apoptotic response through suppression of Bcl-xL and upregulation of Bim. This work demonstrates a novel mechanism of radiation resistance in medulloblastoma and identifies an epigenetic marker predictive of radiotherapy response. On the basis of these findings, we propose an epigenetically guided treatment approach targeting radiotherapy resistance in patients with medulloblastoma.Significance:This study demonstrates a novel epigenetic mechanism of radiation resistance in medulloblastoma and identifies a therapeutic approach to improve outcomes in these patients.

Recent reports have demonstrated that DNA double-strand break (DSB)–induced small RNAs (diRNA) play an important role in the DNA damage response (DDR). However, the molecular mechanism by which diRNAs regulate the DDR remains unclear. Here, we report that Dicer- and Drosha-dependent diRNAs function as guiding molecules to promote the recruitment of the methyltransferase MMSET (WHSC1) and the acetyltransferase Tip60 (KAT5) to the DSB, where local levels of histone H4 di- and tri-methylation at lysine 20 (H4K20me2, 3) and H4 acetylation at lysine 16 (H4K16Ac) were enhanced. These histone modification events resulted in an open, flexible chromatin configuration, as indicated by the increased release of histones γH2AX, H2AX, and H3 from damaged chromatin. Furthermore, we found that diRNA-associated AGO2 interacted with MMSET and Tip60 and that the diRNA binding and catalytic activities of AGO2 were dispensable for the interaction but required for the recruitment of MMSET and Tip60 to DSBs. Consequently, diRNA-mediated chromatin remodeling promoted DSB repair by enhancing the recruitment of Rad51 and BRCA1 to the DSB site. Taken together, our findings reveal an unexpected direct role for diRNAs in regulating chromatin remodeling to facilitate DSB repair, revealing a new layer of DDR regulation involving specialized RNA molecules. Cancer Res; 76(7); 1904–15. ©2016 AACR.

Figure S4. DSB repair in cycling cells depends on Brca1 and NBS1 but not RAP80

Supplemental Figure legends

Figure S5. RAP80 suppresses excessive DSB processing

Figure S1. PARP1 and ATM inhibition attenuates Brca1 recruitment in the DSB surrounding regions but not directly at the DSB

Figure S3. MCF7 cells accumulate in G1 following serum starvation

Background: Despite advances in surgery and pharmacotherapy, there remains significant residual ischemic risk after coronary artery bypass grafting surgery. Methods: In REDUCE-IT (Reduction of Cardiovascular Events With Icosapent Ethyl–Intervention Trial), a multicenter, placebo-controlled, double-blind trial, statin-treated patients with controlled low-density lipoprotein cholesterol and mild to moderate hypertriglyceridemia were randomized to 4 g daily of icosapent ethyl or placebo. They experienced a 25% reduction in risk of a primary efficacy end point (composite of cardiovascular death, myocardial infarction, stroke, coronary revascularization, or hospitalization for unstable angina) and a 26% reduction in risk of a key secondary efficacy end point (composite of cardiovascular death, myocardial infarction, or stroke) when compared with placebo. The current analysis reports on the subgroup of patients from the trial with a history of coronary artery bypass grafting. Results: Of the 8179 patients randomized in REDUCE-IT, a total of 1837 (22.5%) had a history of coronary artery bypass grafting, with 897 patients randomized to icosapent ethyl and 940 to placebo. Baseline characteristics were similar between treatment groups. Randomization to icosapent ethyl was associated with a significant reduction in the primary end point (hazard ratio [HR], 0.76 [95% CI, 0.63–0.92]; P =0.004), in the key secondary end point (HR, 0.69 [95% CI, 0.56–0.87]; P =0.001), and in total (first plus subsequent or recurrent) ischemic events (rate ratio, 0.64 [95% CI, 0.50–0.81]; P =0.0002) compared with placebo. This yielded an absolute risk reduction of 6.2% (95% CI, 2.3%–10.2%) in first events, with a number needed to treat of 16 (95% CI, 10–44) during a median follow-up time of 4.8 years. Safety findings were similar to the overall study: beyond an increased rate of atrial fibrillation/flutter requiring hospitalization for at least 24 hours (5.0% vs 3.1%; P =0.03) and a nonsignificant increase in bleeding, occurrences of adverse events were comparable between groups. Conclusions: In REDUCE-IT patients with a history of coronary artery bypass grafting, treatment with icosapent ethyl was associated with significant reductions in first and recurrent ischemic events. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01492361.

Introduction For cancer survivors, insomnia is a frequent and distressing concern. Cognitive behavioral therapy for insomnia (CBT-I) is an effective treatment, yet in-person care can be difficult for cancer survivors to access for a variety of socioeconomic, medical and logistical reasons. In a pilot randomized clinical trial, four, weekly sessions of virtually-delivered, synchronous CBT-I were feasible, acceptable, and seemingly efficacious for reducing insomnia among cancer survivors (vs. an enhanced usual care control). The aim of this secondary analysis was to characterize daily patterns in sleep diary metrics during the intervention phase. Methods Adults who had completed treatment for any non-metastatic cancer and had chronic insomnia (DSM-5 criteria and Insomnia Severity Index score Results Among 20 cancer survivors who received CBT-I (mean age 51.2 ± 17.1 years, 90% female), model fit indices indicated that across sleep metrics, linear growth models provided a better fit to the data than either quadratic or cubic growth models. Significant linear improvement was observed for SQ (B = 0.02, t = 3.60, p < 0.001), SE (B = 0.16, t = 2.01, p = 0.046), and SOL (B = -0.41, t = -2.47, p = 0.01), but not TIB, TST, or WASO (ts < 1.12, ps > 0.26). Conclusion Findings elucidate how sleep may be expected to change over the course CBT-I, in particular for the growing population of cancer survivors seeking virtual care for insomnia. The strengths, limitations, and potential modifications to optimize the intervention across sleep metrics will be discussed. Support (if any) This work was conducted with support from the American Cancer Society (Massachusetts General Hospital Institutional Research Grant, PI: Hall).

STUDY OBJECTIVES: Although subjective-objective sleep discrepancy has long been observed in patients with insomnia, the profiles of this discrepancy are poorly understood. Further, sleep discrepancy in insomnia with sleep comorbidities remains underexplored. We sought to better characterize sleep discrepancy among patient groups with and without insomnia and comorbid conditions such as obstructive sleep apnea (OSA). METHODS: Using data from the Sleep Heart Health Study, we conducted a secondary analysis describing (1) the profile of self-reported and objective sleep measures in patients with insomnia (IS group; n = 73) and comorbid OSA (IS + OSA group; n = 143), compared with individuals with OSA only (OSA group; n = 296) and normal sleep control patients (NSC group; n = 126); (2) the comparative magnitude of sleep misperception between these 4 groups; and (3) the self-reported quality of life (QOL) in the 4 groups. RESULTS: Subjective-objective sleep discrepancy existed in all 4 groups, including the NSC group. Controlling for age, sex, mental health conditions, sleep apnea severity, and objectively measured sleep time, the presence of self-reported insomnia had the strongest association with sleep discrepancy. In patients with insomnia, sleep onset latency was overestimated (7.8 ± 36.8 min in the IS group; P < .001 when compared to the NSC and OSA groups), with the largest differences seen in the comorbid IS + OSA group (15.0 ± 56.8 min). Insomnia conferred the most negative impact on QOL, with the combined IS + OSA group reporting the lowest QOL. CONCLUSIONS: Self-reported insomnia is associated with sleep discrepancy and negative QOL. Those with comorbid OSA reported the greatest sleep discrepancy and the lowest QOL. Future research is warranted to further understand individual profiles of misperception and insomnia phenotypes. CITATION: Ma Y, Goldstein MR, Davis RB, Yeh GY. Profile of subjective-objective sleep discrepancy in patients with insomnia and sleep apnea. J Clin Sleep Med. 2021;17(11):2155–2163.

Objective Diabetes is a known risk factor for severe coronavirus disease 2019 (COVID-19). We conducted this study to determine if there is a correlation between hemoglobin A1C (HbA1C) level and poor outcomes in hospitalized patients with diabetes and COVID-19. Methods This is a retrospective, single-center, observational study of patients with diabetes (defined by an HbA1C level of ≥6.5% or known medical history of diabetes) who had a confirmed case of COVID-19 and required hospitalization. All patients were admitted to our institution between March 3, 2020, and May 5, 2020. HbA1C results for each patient were divided into quartiles: 5.1% to 6.7% (32-50 mmol/mol), 6.8% to 7.5% (51-58 mmol/mol), 7.6% to 8.9% (60-74 mmol/mol), and >9% (>75 mmol/mol). The primary outcome was in-hospital mortality. Secondary outcomes included admission to an intensive care unit, invasive mechanical ventilation, acute kidney injury, acute thrombosis, and length of hospital stay. Results A total of 506 patients were included. The number of deaths within quartiles 1 through 4 were 30 (25%), 37 (27%), 34 (27%), and 24 (19%), respectively. There was no statistical difference in the primary or secondary outcomes among the quartiles, except that acute kidney injury was less frequent in quartile 4. Conclusion There was no significant association between HbA1C level and adverse clinical outcomes in patients with diabetes who are hospitalized with COVID-19. HbA1C levels should not be used for risk stratification in these patients.

STUDY OBJECTIVES: Prior studies have suggested a benefit of yoga for alleviating sleep disturbance; however, many studies have had methodological limitations. This trial study aimed to extend that literature by including an active sleep hygiene comparison. METHODS: Participants aged 25–59 years with a primary complaint of sleep onset insomnia lasting at least 6 months were block randomized to an 8-week Kundalini yoga or sleep hygiene intervention, both consisting of initial 60-minute instruction and weekly check-ins. Daily sleep diaries and questionnaires were collected at baseline, throughout the intervention, and at 6-month follow-up. Data were analyzed using linear mixed models (n = 20 in each group). RESULTS: Participant ratings of the interventions did not significantly differ. Sleep hygiene improved several diary and questionnaire outcomes, however, yoga resulted in even greater improvements corresponding to medium-to-large between-group effect sizes. Total sleep time increased progressively across yoga treatment (d = 0.95, P = .002), concurrent with increased sleep efficiency (d = 1.36, P < .001) and decreased sleep onset latency (d = −1.16, P < .001), but without changes in pre-sleep arousal (d =−0.30, P = .59). Remission rates were also higher for yoga compared to sleep hygiene, with ≥ 80% of yoga participants reporting average sleep onset latency < 30 minutes and sleep efficiency > 80% at 6-month follow-up. For over 50% of yoga participants, the insomnia severity index decreased by at least 8 points at end of treatment and follow-up. CONCLUSIONS: Yoga, taught in a self-care framework with minimal instructor burden, was associated with self-reported improvements above and beyond an active sleep hygiene comparison, sustained at 6-month follow-up. Follow-up studies are needed to assess actigraphy and polysomnography outcomes, as well as possible mechanisms of change. Clinical Trial Registration: Registry: ClinicalTrials.gov; Name: Yoga as a Treatment for Insomnia; URL: https://clinicaltrials.gov/ct2/show/NCT00033865; Identifier: NCT00033865. CITATION: Khalsa SBS, Goldstein MR. Treatment of chronic primary sleep onset insomnia with Kundalini yoga: a randomized controlled trial with active sleep hygiene comparison. J Clin Sleep Med. 2021;17(9):1841–1852.

What is the function of immature vocalizing in early learning environments? Previous work on infants in the US indicates that prelinguistic vocalizations elicit caregiver speech which is simplified in its linguistic structure. However, there is strong cross-cultural variation in the extent to which children’s vocalizations elicit responses from caregivers. While reports indicate that children in several non-Western communities may hear less adult speech which is tailored for their learning, the extent to which children’s vocalizations elicit changes in their immediate caregivers’ speech structure is presently unknown. Here we compare Tseltal Mayan and US caregivers’ verbal responses to their children’s vocalizations. Similar to findings from US dyads, we found that children in a subsistence farming community regulate the statistical structure of caregivers’ speech simply by vocalizing. Following the _interaction burst hypothesis_, where clusters of child-adult contingent response alternations facilitate learning from limited input, we reveal a stable source of information facilitating language learning within ongoing interaction.

The expression of Bruton tyrosine kinase (BTK) in B cells and innate immune cells provides essential downstream signaling for BCR, Fc receptors, and other innate immune cell pathways. The topical covalent BTK inhibitor PRN473 has shown durable, reversible BTK occupancy with rapid on-rate and slow off-rate binding kinetics and long residence time, resulting in prolonged, localized efficacy with low systemic exposure in vivo. Mechanisms of PRN473 include inhibition of IgE (FcεR)–mediated activation of mast cells and basophils, IgG (FcγR)–mediated activation of monocytes, and neutrophil migration. In vivo, oral PRN473 was efficacious and well tolerated in the treatment of canine pemphigus foliaceus. In this study, we evaluated in vitro selectivity and functionality, in vivo skin Ab inflammatory responses, and systemic pharmacology with topically administered PRN473. Significant dose-dependent inhibition of IgG-mediated passive Arthus reaction in rats was observed with topical PRN473 and was maintained when given 16 h prior to challenge, reinforcing extended activity with once-daily administration. Similarly, topical PRN473 resulted in significant dose-dependent inhibition of the mouse passive cutaneous anaphylaxis IgE-mediated reaction. Multiday treatment with topical PRN473 in rodents resulted in low-to-no systemic accumulation, suggesting that efficacy was mainly due to localized exposure. Reduced skin Ab inflammatory activity was also confirmed with oral PRN473. These preclinical studies provide a strong biologic basis for targeting innate immune cell responses locally in the skin, with rapid onset of action following once-daily topical PRN473 administration and minimal systemic exposure. Dose-dependent inhibition in these preclinical models of immune-mediated skin diseases support future clinical studies.

The autonomic system plays an important role in regulating blood pressure (BP). BP is elevated at night when individuals remain awake and continues to be elevated during either the night or the day if wakefulness persists. There is a close relationship between the high frequency (HF) of the variability of the RR interval (RRI), an index of parasympathetic predominance, and delta power during slow-wave sleep bouts. In addition, there is an HF rebound once sleep is permitted following sleep deprivation. Furthermore, this is the case for acute total sleep deprivation, as well as for models of chronic sleep restriction. Evidence indicates that sleep is important for autonomic homeostasis. It has long been recognized that physiological stress induces sympathetic activation. However, the simple fact that humans can voluntarily, and sometimes even with great pleasure, deprive themselves of sleep, has led us to overlook the role that deficient sleep plays as a physiological stressor. Physiological and epidemiological data have shown that short sleep is a risk factor for a broad range of morbidity and all-cause mortality. Understanding the role sleep plays in autonomic regulation can open new opportunities for the development of sleep interventions to improve cardiovascular health.

To describe an experience using a protocol using de novo belatacept (DNB) based maintenance immunosuppression in the setting of lymphocyte depletion. A retrospective, observational study was performed on 37 kidney transplant recipients treated with the DNB protocol, which was defined as belatacept initiated within 7 days after a kidney transplant with steroids and mycophenolate with anti-thymocyte globulin (ATG) induction without concomitant calcineurin inhibitors (CNIs). Patients who received a deceased donor kidney meeting one or more of the following criteria: anticipated cold ischemia time (CIT) greater than 24 h, donation after cardiac death, donor acute kidney injury, and a Kidney Donor Profile Index (KDPI) 85% during the study period were included. Patient survival at 1 year was 97.3% and graft survival was 94.6%. Delayed graft function (DGF) occurred in 40.54% of the patients. Two patients experienced a Banff 1B acute cellular rejection. BK viremia was detected in 32.4% of patients. The mean estimated glomerular filtration rate (eGFR) calculated with the use of modification of diet in renal disease (MDRD) equation at 1 year in the study group was 54.7 ml/min/1.73 m

In power systems modelling, optimization methods based on certain objective function(s) are widely used to provide solutions for decision makers. For complex high-dimensional problems, such as network hosting capacity evaluation of intermittent renewables, simplifications are often used which can lead to the ‘optimal’ solution being suboptimal or nonoptimal. Even where the optimization problem is resolved, it would still be valuable to introduce some diversity to the solution for long-term planning purposes. This paper introduces a general framework for solving optimization for power systems that treats an optimization problem as a history match problem which is resolved via statistical emulation and uncertainty quantification. Emulation constructs fast statistical approximations to the complex computer simulation model in order to identify appropriate choices of candidate solutions for given objective function(s). Uncertainty quantification is adopted to capture multiple sources of uncertainty attached to each candidate solution and is conducted via Bayes linear analysis. It is demonstrated through a hosting capacity case study involving variable wind generation and active network management. The proposed method effectively identified not only the maximum connectable capacities but also a diverse set of near-optimal solutions, and so provided flexible guides for using the existing network to maximize the benefits of renewable generation.

Introduction Parathyroid adenoma (PA) and parathyroid hyperplasia (PH) are common causes of primary hyperparathyroidism (PHPT) for which the only definitive treatment is surgical removal. Surgery is often preceded by imaging for localization, including by ultrasound (US), Sestamibi scan (MIBI), positron emission tomography/computer tomography (PET/CT), and four-dimensional computed tomography (4D-CT). While it is common for parathyroid pathology to not be visualized on imaging, non-visualization is more typical of adenomas and hyperplasia of smaller size. Clinical Case A 65-year-old male without history of kidney dysfunction or family history of parathyroid disease was referred to surgery for parathyroidectomy to manage longstanding PHPT. Serology showed a parathyroid hormone (PTH) level of 581 pg/mL (reference range: 12-65 pg/mL) and calcium of 11.8 mg/dL (reference range: 8.6-10.5 mg/dL). Preoperative parathyroid localization US revealed a large well-defined 1.5 cm PA. The patient underwent parathyroidectomy, which detected a large right inferior parathyroid gland, confirmed with pathology to be an atypical parathyroid adenoma weighing 1800 mg. Postoperative PTH level was 550 pg/mL and calcium was 12.6 mg/dL. MIBI did not display any definite parathyroid adenoma or ectopic parathyroid tissue. Further evaluation with PET/CT did not demonstrate any evidence of metabolically active residual or ectopic parathyroid adenoma or metastatic disease, and repeat US showed did not reveal evidence of any abnormal parathyroid tissue. Ultimately, 4D-CT detected a multiglandular parathyroid with a 1.8×1.4×3.0 cm right superior adenoma weighing approximately 3931 mg, 1.2×0.8×2.1cm left superior adenoma weighing approximately 1048 mg, and a 0.3×0.4×0.4cm left superior adenoma weighing approximately 25 mg. The patient underwent re-exploration parathyroidectomy with removal of the right superior adenoma weighing 3105 mg and left superior adenoma weighing 1100 mg. The remaining left inferior gland was biopsied and the majority of it was implanted into the arm. Repeat serology one week post-operatively showed improvement of PTH level to 5 pg/mL and of calcium to 8.9 mg/dL and serology one year post-operatively showed a PTH level of 82 pg/mL and a calcium of 9.4 mg/dL. Conclusion We present a patient with massive four-gland PH who initially presented with findings more typical of PA, but ultimately had additional hyperplasic glands that were identified after removal of the adenomatous gland. These glands were unusually large to be seen in PH and yet still be undetected on multiple imaging modalities; no previously reported non-ectopic hyperplastic glands of this size have been documented that were not detected on US or MIBI. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.

Decreased sea ice concentration due to climate change has dramatically increased shipping traffic on the Northern Sea Route (NSR). In recent years, NSR has become a shipping route of economic importance, with traffic equivalent to 1-2 days of traffic through the Suez Canal. Yet either sea ice or recent sanctions on Russia could close or shorten its use. Here we use results of 16 climate realizations and shipping routes to estimate the value of an NSR transit, and thus the cost when it is closed due to sea ice or sanctions on Russia. Either way, the closure of the NSR is expensive, with the costs borne by the global community through higher shipping costs, higher emissions, and loss of time. Using conservative estimates, costs throughout the system could be as high as $3.3 billion, with possible overall losses as high as $10 billion. Collectively, we show how the intersection of climate change and geopolitics causes heretofore unregistered effects. Ultimately, sanctions are as expensive as sea ice. These estimates can be used by future researchers to assess possible future cost savings as climate change continues to affect global transportation.

Summary When performing classic uncertainty reduction according to dynamic data, a large number of reservoir simulations need to be evaluated at high computational cost. As an alternative, we construct Bayesian emulators that mimic the dominant behavior of the reservoir simulator, and which are several orders of magnitude faster to evaluate. We combine these emulators within an iterative procedure that involves substantial but appropriate dimensional reduction of the output space (which represents the reservoir physical behavior, such as production data), enabling a more effective and efficient uncertainty reduction on the input space (representing uncertain reservoir parameters) than traditional methods, and with a more comprehensive understanding of the associated uncertainties. This study uses the emulation-based Bayesian history-matching (BHM) uncertainty analysis for the uncertainty reduction of complex models, which is designed to address problems with a high number of both input and output parameters. We detail how to efficiently choose sets of outputs that are suitable for emulation and that are highly informative to reduce the input-parameter space and investigate different classes of outputs and objective functions. We use output emulators and implausibility analysis iteratively to perform uncertainty reduction in the input-parameter space, and we discuss the strengths and weaknesses of certain popular classes of objective functions in this context. We demonstrate our approach through an application to a benchmark synthetic model (built using public data from a Brazilian offshore field) in an early stage of development using 4 years of historical data and four producers. This study investigates traditional simulation outputs (e.g., production data) and also novel classes of outputs, such as misfit indices and summaries of outputs. We show that despite there being a large number (2,136) of possible outputs, only very few (16) were sufficient to represent the available information; these informative outputs were used using fast and efficient emulators at each iteration (or wave) of the history match to perform the uncertainty-reduction procedure successfully. Using this small set of outputs, we were able to substantially reduce the input space by removing 99.8% of the original volume. We found that a small set of physically meaningful individual production outputs were the most informative at early waves, which once emulated, resulted in the highest uncertainty reduction in the input-parameter space, while more complex but popular objective functions that combine several outputs were only modestly useful at later waves. The latter point is because objective functions such as misfit indices have complex surfaces that can lead to low-quality emulators and hence result in noninformative outputs. We present an iterative emulator-based Bayesian uncertainty-reduction process in which all possible input-parameter configurations that lead to statistically acceptable matches between the simulated and observed data are identified. This methodology presents four central characteristics: incorporation of a powerful dimension reduction on the output space, resulting in significantly increased efficiency; effective reduction of the input space; computational efficiency, and provision of a better understanding of the complex geometry of the input and output spaces.

Complex systems are often modelled by intricate and intensive computer simulators. This makes their behaviour difficult to study, and so a statistical representation of the simulator is often used, known as an emulator, to enable users to explore the space more thoroughly. These have the disadvantage that they do not allow one to learn about the simulator’s behaviour beyond its role as a function from input to output variables. We take a new approach, by involving the internal processes modelled within the simulator in our emulator. We introduce a new technique, intermediate variable emulation, which enables a simulator to be understood in terms of the processes it models. This leads to advantages in simulator improvement and in calibration, as the simulator can be scrutinised in more detail and the physical processes can be used to refine the input space. The intermediate variable emulator also allows one to represent more complicated relationships within the simulator, as we show with a simple example. We demonstrate the method using a simulator of the ocean carbon cycle. Using an intermediate variable emulator we are able to discover unrealistic behaviour in the simulator that would not be noticeable using a standard input to output emulator, and reduce the input space accordingly. We also learn about the sub-processes that drive the output, and about the input variables driving each sub-process.

We conducted a secondary analysis of the Mindfulness Sleep Therapy study, a randomized controlled trial testing Mindfulness-Based Therapy for Insomnia (MBTI) against a sleep hygiene education and exercise program (SHEEP). We investigated whether the interventions led to changes in sleep macroarchitecture (N2, N3 and REM), and microarchitecture (sleep fragmentation, slow wave activity, spectral band power) measured by ambulatory polysomnography (PSG).48 MBTI and 46 SHEEP participants provided usable PSG and subjective sleep quality data both pre- and post intervention. The interventions consisted of 8 weekly 2-hour group sessions, and daily practice. PSG data were staged according to the American Academy of Sleep Medicine criteria by 2 technicians blind to time point and condition. Repeated-measures ANOVA and permutation analysis were used to test for differences over time and between the interventions.Self-reported sleep quality improved in both study groups. We observed significant increases in N2 in MBTI but not SHEEP (p = .045), and significant increases in N3 in SHEEP but not MBTI (p = .012). No significant differences over time or between group were observed in N1, REM, or sleep fragmentation. Higher frequency non-REM EEG power decreased in SHEEP but not MBTI. Slow wave activity and slow wave activity dissipation did not differ over time or between groups. Among all variables, significant time by group interactions were observed in only N3 and non-REM alpha power.MBTI and sleep hygiene education had different effects on sleep macro and microarchitecture, suggesting that the underlying mechanisms of mindfulness training in improving sleep quality may differ from traditional interventions.

Introduction Acromegaly is a clinical disorder that occurs from autonomous production of growth hormone (GH). Diabetic ketoacidosis (DKA) is an uncommon and late complication of acromegaly. Acromegaly presenting in DKA prognosticates glycemic management with insulin-based regimens. Cessation of insulin therapy, however, can be achieved in patients with acromegaly after proper medical and/or surgical interventions. Our case highlights a unique outcome in a patient with newly-diagnosed acromegaly that initially presented in DKA with very high insulin requirements and was ultimately de-escalated off all anti-hyperglycemic therapy with significant glycemic improvement prior to any treatment for acromegaly. Clinical Case A 32 year-old male with a past medical history of colorectal cancer and no known history of diabetes presented to the emergency department for evaluation of generalized weakness, epigastric pain, nausea, and vomiting and was admitted for DKA. Hemoglobin A1c was 11.6% (reference range < 5.7%), confirming the diagnosis of newly-diagnosed diabetes. C-peptide was 1.4 ng/mL (reference range 0.5-3.3 ng/mL) and anti-glutamic acid decarboxylase, anti-islet cell, and anti-zinc transporter 8 antibodies were all negative. He was initiated on intravenous insulin infusion, with rates achieving > 200 units of insulin per day. Given severe insulin resistance in conjunction with acromegalic features on physical exam and a unique history of colorectal cancer at a young age without any family history, evaluation for acromegaly was initiated. Human GH level was 68.60 ng/mL (reference range 0.05-3.00 ng/mL) and insulin-like growth factor-1 (IGF-1) level was 1,036 ng/mL (reference range 82-242 ng/mL). MRI brain revealed a hypoenhancing 1.3 cm lesion enlarging the left lateral pituitary gland. Diagnosis of acromegaly due to a GH-secreting macroadenoma was established. The patient was discharged on a high-dose insulin regimen in addition to metformin therapy with de-escalation off of all anti-glycemic therapy within a few weeks of diagnosis; at his 3 month follow-up visit, his repeat hemoglobin A1c was 6.1 with repeat GH level of 28.8 ng/mL and IGF-1 level of 1602 ng/mL, despite not yet undergoing any treatment for the underlying condition. Conclusion DKA as an initial presentation of acromegaly has been previously reported in literature, however, not with a concomitant history of colon cancer. Moreover, no previous cases of acromegaly have reported glycemic normalization off of anti-hyperglycemic therapy prior to any treatment for acromegaly. Our case highlights that evaluation for secondary causes, including acromegaly, should be considered in patients with severe insulin resistance and emphasizes the dramatic range of insulin requirements that patients with acromegaly may have. Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

Introduction Mind-body interventions (MBIs) continue to receive widespread interest for improving sleep disturbances. This study investigated the feasibility of using an automated electronic survey system in REDCap in the context of a fully remote clinical trial study to produce detailed measures of participant adherence, daily sleep quality, and associations with physiological outcomes captured by wearable devices. Methods Eighteen healthy participants (age 18-30 yrs, 12 female) were randomized to one of three 8-week long interventions: slow-paced breathing (SPB, N=5, 24.6 ± 2.1 years, 4 female), mindfulness (M, N=6, 23.7 ± 3.7 years, 4 female), or yogic breathing (SPB+M, N=7, 24.3 ± 3.1 years). Participants completed two weeks of daily sleep logs along with the Pittsburgh Sleep Quality Index (PSQI) prior to a virtual laboratory visit, which consisted of a 60-min intervention-specific training, including a 20-min guided practice, and subsequent tasks including experimental stress induction. Participants were then instructed to repeat their assigned intervention practice daily, selecting either the same or a similar guided audio as their initial training. After an initial video check-in appointment, participants received regular visual feedback of their data and completed weekly check-ins with the study team to improve adherence. At the end of the intervention period, participants again completed daily sleep logs and the PSQI, in addition to other outcome measures and a virtual laboratory visit. Data were analyzed using linear mixed models. Results Sleep log adherence was over 90% in all three groups. The groups were successfully distinguishable based on HRV-derived breathing and mindfulness ratings. For the SBP+M group only, there was a trend of reduced sleep onset latency (SOL, p=.093) and a significant increase in sleep efficiency (SE, p=.025). There were no significant changes in PSQI or other sleep log measures. More detailed analysis of timecourse across these measures is ongoing. Conclusion These findings support feasibility for a fully remote, semi-automated clinical trial study assessing component-specific effects of these MBIs on sleep in generally healthy young adults. Research evaluating MBIs for sleep in both clinical and nonclinical populations would benefit from similar study designs to examine intervention-specific components while increasing both scalability and quality control. Support (If Any) Pilot Research Grant, Osher Center for Integrative Medicine of Harvard Medical School and Brigham & Women’s Hospital; National Institutes of Health (5T32HL007901-22)

Persistent HPV infection is causative for the majority of cervical cancer cases; however, current guidelines do not require HPV testing for newly diagnosed cervical cancer. Using an institutional cohort of 88 patients with cervical cancer treated uniformly with standard-of-care chemoradiation treatment (CRT) with prospectively collected clinical outcome data, we observed that patients with cervical tumors containing HPV genotypes other than HPV 16 have worse survival outcomes after CRT compared with patients with HPV 16+ tumors, consistent with previously published studies. Using RNA sequencing analysis, we quantified viral transcription efficiency and found higher levels of E6 and the alternative transcript E6*I in cervical tumors with HPV genotypes other than HPV 16. These findings were validated using whole transcriptome data from The Cancer Genome Atlas (n = 304). For the first time to our knowledge, transcript expression level of HPV E6*I was identified as a predictive biomarker of CRT outcome in our complete institutional data set (n = 88) and within the HPV 16+ subset (n = 36). In vitro characterization of HPV E6*I and E6 overexpression revealed that both induce CRT resistance through distinct mechanisms dependent upon p53-p21. Our findings suggest that high expression of E6*I and E6 may represent novel biomarkers of CRT efficacy, and these patients may benefit from alternative treatment strategies.

Objective Mindfulness-based interventions (MBI) have been shown to reduce subjective symptoms of insomnia but the effects on objective measures remain unclear. The purpose of this study was to examine sleep EEG microarchitecture patterns from a randomized controlled trial of Mindfulness-Based Stress Reduction (MBSR) and Mindfulness-Based Therapy for Insomnia (MBTI). Methods Sleep EEG spectral analysis was conducted on 36 participants with chronic insomnia (>6 months) randomized to 8-week MBSR, MBTI, or self-monitoring control (SM). Overnight polysomnography with 6-channel EEG was conducted at baseline, post-treatment, and 6-month follow-up. Spectral power averaged from channels C3/C4 across NREM epochs (excluding N1) was examined for within-group changes and relationships with self-report measures. Results Increases in absolute NREM beta (16–25 Hz) power were observed from baseline to post-treatment (p = .02, d = 0.53) and maintained at 6-month follow-up (p = .01, d = 0.57) in the combined MBI groups, and additionally in the gamma (25–40 Hz) range at follow-up for the MBTI group only. No significant changes in these frequency bands were observed for SM. Following mindfulness intervention, NREM beta was positively associated with Five-Facet Mindfulness (FFM) score (rho = 0.37, p = .091) and negatively associated with Insomnia Severity Index (rho = −0.43, p = .047). Conclusion These results in people with insomnia corroborate prior reports of increased high-frequency sleep EEG power associated with mindfulness training. This change in beta EEG pattern merits further evaluation as a potential marker of the effects of mindfulness meditation on sleep, especially given the paradoxical findings in the context of insomnia. Clinical Trial Registration clinicaltrials.gov , NCT00768781 .

We study multi-frequency quasiperiodic Schrodinger operators on $${\mathbb {Z}}$$ . We prove that for a large real analytic potential satisfying certain restrictions the spectrum consists of a single interval. The result is a consequence of a criterion for the spectrum to contain an interval at a given location that we establish non-perturbatively in the regime of positive Lyapunov exponent.

History matching (HM) is an inverse problem where uncertainties in attributes are reduced by comparison with observed dynamic data. Typically, normalized misfit summarizes dissimilarities between observed and simulation data. Especially for long-time series, objective functions (OFs) aggregate multiple events and tendencies relevant to field performance in a single indicator (e.g. water rate and breakthrough time). To capture the attributes influencing the reservoir behavior, we evaluate the assimilation of data series through additional OFs, obtained from splitting time-series data. In this study, two additional OF groups supplement the time-series misfits: Breakthrough Deviation (BD) indicating dissimilarities in water breakthrough time; Productivity Deviation (PD), representing mismatches of the well potential, mainly impacting the transition from history to forecast conditions. The Productivity Deviation (PD) is adapted from previous studies. Instead of simulating the last time of the historical period under forecast conditions, we propose keeping it under historical data. The change is the historical data used as target condition to the simulator: Bottom Hole Pressure (BHP) in place of liquid production and water injection rates; with this, we estimate a mismatch in well productivity, while avoiding the influence of other boundary conditions in the evaluation. Two applications (1 & 2), assimilating different OF quantities, highlight the influence of the additional groups. Application 1 only computes time-series misfit (64 OFs) whereas Application 2 includes the BD and PD (counting 128 OFs). The iterative HM method presents flexibility regarding OFs assimilated and incorporation of uncertain attributes. UNISIM-I-H case allows us to evaluate the HM considering history and forecast data. We examine differences between the 450 scenarios resulting of data assimilation for each application through four perspectives. Application 2 resulted in scenarios with better predictability of the field behavior and smoother transitions between field history and forecast periods. Field cumulative oil production of Application 2 is also forecasted closer to the reference data when compared to Application 1; all forecast periods (1, 5 and 19 years) emphasize this impact. Some wells presented breakthrough time closer to the reference for Application 2. The challenging achievement of exact BD matches leads to the third advantage of the additional indicators. These OFs supply supplementary information to the diagnosis of scenarios, identifying unnoticed problems in the traditional approach. Finally, even with an overall better performance, some of the well OFs presented poorer matches for Application 2. To explain this, we analyzed the relationship between attributes and the OFs used to update the attributes. In conclusion, the improved forecast of the simulation scenarios indicates that superior performance of the HM process is possible by splitting the available dynamic data in relevant additional OFs. This study presents a case application with 11 years of field history, in which additional OFs, derived from dynamic data, add value to the reservoir characterization. They allow the influence of uncertain attributes to be captured for relevant events in reservoir performance. We also show how the increased quantity of OFs assimilated makes the HM harder for some OFs.

BACKGROUND & AIMS We evaluated treatment withdrawal, long-term outcomes, and safety of budesonide oral suspension (BOS) 2.0 mg twice daily in patients with eosinophilic esophagitis who completed a 12-week induction study. METHODS Induction full responders (≤6 eosinophils per high-power field [eos/hpf] and ≥30% reduction in the Dysphagia Symptom Questionnaire score) to BOS 2.0 mg twice daily (ORBIT1/SHP621-301/NCT02605837) were randomized to continue BOS (BOS-BOS) or withdraw to placebo (BOS-PBO) for 36 weeks (ORBIT2/SHP621-302/NCT02736409). Induction partial responders and nonresponders, and patients who received induction placebo, received BOS for 36 weeks. The primary end point was the proportion of BOS-BOS and BOS-PBO patients who relapsed (≥15 eos/hpf and ≥4 days of dysphagia [Dysphagia Symptom Questionnaire] over 2 weeks) by week 36. The key secondary end point was the proportion of induction partial responders and nonresponders who fully responded after 52 weeks of total BOS therapy. Other secondary end points included the proportion of induction full responders with histologic responses (≤1, ≤6

Meningiomas are among the most common tumors of the adult central nervous system (CNS). They are classified by the World Health Organization into three pathologic grades with increasing severity: grade I are benign with favorable treatment outcomes and low recurrence rates while grade III display malignant behavior and poor progression-free survival. Previous studies have shown that inactivation of NF-2 is the most common genetic event in high-grade meningioma; however, there is dearth of molecular data to distinguish grade II (AM-II) from the even more aggressive grade III (AM-III). As part of a routine diagnostic workup, 19 AM-II and 5 AM-III were submitted for targeted sequencing on a panel of twenty-four genes relevant to CNS tumors. The data generated during the course of clinical care was collected and re-analyzed with the aim of identifying molecular features to distinguish AM-II and AM-III. Our cases contained several well-characterized, potentially actionable mutations, but we did not find any novel, recurrent sequence variants. Copy number variations were common in both AM-II and AM-III; chr22q loss was the most prevalent followed in decreasing frequency by losses of chr1p, chr14q, and chr10. In particular, chr10 loss was noted in 4 of 5 AM-III cases but none of the AM-II cases. This suggests that chr10 loss may serve as a diagnostic and perhaps a prognostic marker to differentiate AM-II from AM-III. If confirmed in larger studies, our finding could further aid the classification of meningioma.

Medulloblastoma has been categorized into four subgroups based on genetic, epigenetic, and transcriptional profiling. Radiation is used for treating medulloblastoma regardless of the subgroup. A better understanding of the molecular pathways determining radiotherapy response could help improve medulloblastoma treatment. Here, we investigated the role of the EZH2 (enhancer of zeste 2 polycomb repressive complex 2 subunit)-dependent histone H3K27 trimethylation in radiotherapy response in medulloblastoma. The tumors in 47.2% of patients with group 3 and 4 medulloblastoma displayed H3K27me3 deficiency. Loss of H3K27me3 was associated with a radioresistant phenotype, high relapse rates, and poor overall survival. In H3K27me3-deficient medulloblastoma cells, an epigenetic switch from H3K27me3 to H3K27ac occurred at specific genomic loci, altering the transcriptional profile. The resulting upregulation of EPHA2 stimulated excessive activation of the prosurvival AKT signaling pathway, leading to radiotherapy resistance. Bromodomain and extraterminal motif (BET) inhibition overcame radiation resistance in H3K27me3-deficient medulloblastoma cells by suppressing H3K27ac levels, blunting EPHA2 overexpression, and mitigating excessive AKT signaling. In addition, BET inhibition sensitized medulloblastoma cells to radiation by enhancing the apoptotic response through suppression of Bcl-xL and upregulation of Bim. This work demonstrates a novel mechanism of radiation resistance in medulloblastoma and identifies an epigenetic marker predictive of radiotherapy response. On the basis of these findings, we propose an epigenetically guided treatment approach targeting radiotherapy resistance in patients with medulloblastoma. Significance: This study demonstrates a novel epigenetic mechanism of radiation resistance in medulloblastoma and identifies a therapeutic approach to improve outcomes in these patients.

Introduction Wearable devices and mind-body interventions (MBIs) continue to receive widespread interest as tools for improving sleep. This study investigated the feasibility of using an automated electronic survey system and wearable heart rate (HR) monitor in the context of a fully remote clinical trial study to produce detailed measures of participant adherence, daily sleep quality, and associations with physiological outcomes captured by wearable devices. Methods Eighteen healthy participants (age 18-30yrs, 12 female) were randomized to one of three 8-week long interventions: slow-paced breathing (SPB, N=5, 24.6 ± 2.1 years, 4 female), mindfulness (M, N=6, 23.7 ± 3.7 years, 4 female), or yogic breathing (SPB+M, N=7, 24.3 ± 3.1 years). Participants completed two weeks of daily sleep logs prior to a virtual laboratory visit, consisting of a 60-min intervention-specific training with 20-min guided practice, and subsequent tasks including experimental stress induction. Participants started a 24-hour HR recording using a Polar H10 chest strap on the night prior. Then, participants were instructed to repeat their assigned intervention practice daily, using a guided audio similar to their initial training, while concurrently recording HR data and completing a detailed practice log. HR interbeat interval data were examined with spectral analysis using full spectrograms for inspection of timecourse and frequency-specific patterns in both the nocturnal recordings and daily practice sessions. Results Participants completed an average of 75% of daily practice sessions across the 8-week intervention period (SPB: 77%, M: 65%, SPB+M: 77%). An automated procedure was developed to analyze and visualize the timecourse of HRV-derived breathing patterns in the 754 completed practice sessions and 36 nocturnal recordings. The three groups were then successfully distinguishable based on breathing rates and mindfulness questionnaires. Nocturnal HR recordings demonstrated visually identifiable patterns of interindividual variability and intraindividual consistency. Statistical analysis is ongoing to further characterize these patterns. Conclusion These findings support feasibility for a fully remote, semi-automated clinical trial study assessing component-specific effects of these MBIs on sleep, including detailed spectral analysis of high-quality HR data. Future studies would benefit from examining scalability of this type of study design with wearable physiology in both clinical and nonclinical populations. Support (If Any) Pilot Research Grant, Osher Center for Integrative Medicine of Harvard Medical School and Brigham & Women’s Hospital; National Institutes of Health (5T32HL007901-22)

Objective: Compare two distinct psychosocial stress-management workshops.Participants: Undergraduate and graduate students (n = 69 for analysis, completed April 2017).Methods: Participants were ran...

Contains fulltext : 229013.pdf (Publisher’s version ) (Closed access) OBJECTIVES: The Kidney Disease: Improving Global Outcomes urine output criteria for acute kidney injury lack specificity for identifying patients at risk of adverse renal outcomes. The objective was to develop a model that analyses hourly urine output values in real time to identify those at risk of developing severe oliguria. DESIGN: This was a retrospective cohort study utilizing prospectively collected data. SETTING: A cardiac ICU in the United Kingdom. PATIENTS: Patients undergoing cardiac surgery between January 2013 and November 2017. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: Patients were randomly assigned to development (n = 981) and validation (n = 2,389) datasets. A patient-specific, dynamic Bayesian model was developed to predict future urine output on an hourly basis. Model discrimination and calibration for predicting severe oliguria (< 0.3 mL/kg/hr for 6 hr) occurring within the next 12 hours were tested in the validation dataset at multiple time points. Patients with a high risk of severe oliguria (p > 0.8) were identified and their outcomes were compared with those for low-risk patients and for patients who met the Kidney Disease: Improving Global Outcomes urine output criterion for acute kidney injury. Model discrimination was excellent at all time points (area under the curve > 0.9 for all). Calibration of the model's predictions was also excellent. After adjustment using multivariable logistic regression, patients in the high-risk group were more likely to require renal replacement therapy (odds ratio, 10.4; 95% CI, 5.9-18.1), suffer prolonged hospital stay (odds ratio, 4.4; 95% CI, 3.0-6.4), and die in hospital (odds ratio, 6.4; 95% CI, 2.8-14.0) (p < 0.001 for all). Outcomes for those identified as high risk by the model were significantly worse than for patients who met the Kidney Disease: Improving Global Outcomes urine output criterion. CONCLUSIONS: This novel, patient-specific model identifies patients at increased risk of severe oliguria. Classification according to model predictions outperformed the Kidney Disease: Improving Global Outcomes urine output criterion. As the new model identifies patients at risk before severe oliguria develops it could potentially facilitate intervention to improve patient outcomes.

Background We aimed to evaluate the clinical outcomes of molecular glioblastoma (mGBM) as compared to histological GBM (hGBM) and to determine the prognostic impact of TERT mutation, EGFR amplification, and CDKN2A/B deletion on isocitrate dehydrogenase (IDH)-wildtype GBM. Methods IDH-wildtype GBM patients treated with radiation therapy (RT) between 2012 and 2019 were retrospectively analyzed. mGBM was defined as grade II-III IDH-wildtype astrocytoma without histological features of GBM but with one of the following molecular alterations: TERT mutation, EGFR amplification, or combination of whole chromosome 7 gain and whole chromosome 10 loss. Overall survival (OS) and progression-free survival (PFS) were calculated from RT and analyzed using the Kaplan–Meier method. Multivariable analysis (MVA) was performed using Cox regression to identify independent predictors of OS and PFS. Results Of the 367 eligible patients, the median follow-up was 11.7 months. mGBM and hGBM did not have significantly different OS (median: 16.6 vs 13.5 months, respectively, P = .16), nor PFS (median: 11.7 vs 7.3 months, respectively, P = .08). However, mGBM was associated with better OS (hazard ratio [HR] 0.50, 95% CI 0.29–0.88) and PFS (HR 0.43, 95% CI 0.26–0.72) than hGBM after adjusting for known prognostic factors on MVA. CDKN2A/B deletion was associated with worse OS (HR 1.57, 95% CI 1.003–2.46) and PFS (HR 1.57, 95% CI 1.04–2.36) on MVA, but TERT mutation and EGFR amplification were not. Conclusion Criteria for mGBM may require further refinement and validation. CDKN2A/B deletion, but not TERT mutation or EGFR amplification, may be an independent prognostic biomarker for IDH-wildtype GBM patients.

Summary Model discrepancy specifies unavoidable differences between a physical system and its corresponding computer model. Incomplete information, simplifications and lack of knowledge about the physical state originate model discrepancy. Misevaluation of model discrepancy exposes decision-makers to overconfident and biased forecasts, a risky situation. We describe a methodology to account for one type of model discrepancy in the Bayesian History Matching for Uncertainty Reduction (BHMUR), an approach that combines reservoir simulation and emulation techniques to find all reservoir scenarios consistent with observed data and uncertainties in the problem. Our methodology is an alternative and more rigorous tool to account for the model discrepancy caused by errors in target data while performing uncertainty analysis. Target data used in historical period contain observational errors that propagate through the simulator, causing one type of model discrepancy. We follow a systematic procedure for uncertainty reduction previously presented by the authors, expanding the step dedicated to the model discrepancy. Our methodology: (1) obtains a training set by evaluating model discrepancy in multiple scenarios of the search space, an expensive simulation-based process; (2) characterises the model discrepancy across the entire search space via Bayesian emulators; and (3) integrates the model discrepancy in the BHMUR via bias and covariance structures. The methodology is demonstrated in a case study: 27 valid emulators for model discrepancy were constructed and integrated into the implausibility analysis and uncertainty reduction process. Two perspectives showed the impact of this type of model discrepancy. Firstly, neglecting model discrepancy resulted in all the search space being implausible –an indicator to review the problem characterisation and uncertainties; by contrast, when considering the model discrepancy, the non-implausible region consists of 8% of the search space. Secondly, we demonstrated the uncertainty reduction in the historical and forecasting periods. A key finding is that the error in target data results in a substantial model discrepancy over many other simulation outputs, being both time and location dependent. We advance the applicability of BHMUR by proposing a statistically consistent tool to account for one type of model discrepancy in the uncertainty quantification process. We showed that errors in target data cause model discrepancy with a complex structure. Appropriate consideration of model discrepancy is vital to (a) identify the whole class of solutions consistent with historical data and uncertainties in the problem, (b) appropriately represent the physical system; (c) avoid making decisions based on over-confident and biased information while enabling more reliable production forecast.

Implementation of proxy models, such as emulators might reduce the computational time required in a variety of reservoir simulation studies. By definition, an emulator uses reservoir properties as input parameters in a statistical model constructed from simulator outputs. However, incorporation of petrophysical properties distributions in all model grid-blocks implies too many input parameters for direct emulation. Currently, most employments of emulation only consider single-value parameterization of reservoir properties. In this work, we propose a methodology to consider spatially-distributed properties, such as porosity and permeability, in reservoir emulation technique. First, we present the process of finding a procedure to deal with geostatistical realizations in the emulator and then implement it in a risk quantification application. Construction of an emulator in a probabilistic approach involved: selection of a base model, definition of uncertain inputs, selection of outputs to be emulated, sampling inputs to generate scenarios, simulation of scenarios, and building the emulator. As an application, we used emulators to generate risk curves at the final production time of a synthetic reservoir model. By implementing the proposed procedure, we showed that emulators can provide reliable results during risk analysis in oilfield development. Furthermore, with emulators it is possible to generate risk curves that reproduce simulations results at a lower computational cost. It can be expected that parameterization of petrophysical properties will boost the applicability of the reservoir emulation technique. For instance, emulators can significantly reduce both the time and computational resources demanded in various reservoir studies for high heterogeneity and complex reservoir models such as found in the Brazilian pre-salt area.

Background: There are limited treatment options available for patients with advanced pancreatic ductal adenocarcinoma (PDAC). We conducted a phase II study evaluating the efficacy and safety of capecitabine/oxaliplatin (CAPOX) in patients with locally advanced and metastatic PDAC treated in the first and second lines. Methods: Forty subjects with advanced PDAC and ECOG performance status ≥2 were enrolled. Treatment consisted of capecitabine 2,000 mg/m 2 orally in two divided doses daily for 14 days and oxaliplatin 130 mg/m 2 intravenously day 1 every 21 days. The primary endpoint was response rate (RR); secondary endpoints included safety analysis, progression free survival (PFS) and overall survival (OS). Results: The overall RR was 12.5% (N=3); the disease control rate was 67% (N=16). Due to the protocol definition for eligibility of response evaluation, only 60% (N=24) were evaluable for the primary endpoint. Median progression free survival (mPFS) was 3.8 months (95% CI: 1.3, 6.2); median OS (mOS) was 7.4 months (95% CI: 4.8, 12.2). The most common grade 3/4 toxicities included: fatigue (19%), nausea (17%), and diarrhea (14%). Conclusions: CAPOX is an active regimen in patients with advanced PDAC and is associated with acceptable toxicity. Careful consideration should be given to response endpoints and outcome measures when studying this characteristically ill population.