A neural signature of the vividness of prospective thought is modulated by temporal proximity during intertemporal decision making.

Why do people discount future rewards? Multiple theories in psychology argue that one reason is that future events are imagined less vividly than immediate events, thereby diminishing their perceived value. Here we provide neuroscientific evidence for this proposal. First, we construct a neural signature of the vividness of prospective thought, using an fMRI dataset where the vividness of imagined future events is orthogonal to their valence by design. Then, we apply this neural signature in two additional fMRI datasets, each using a different delay-discounting task, to show that neural measures of vividness decline as rewards are delayed farther into the future.

An fMRI-Based Brain Marker of Individual Differences in Delay Discounting.

Individual differences in delay discounting-how much we discount future compared to immediate rewards-are associated with general life outcomes, psychopathology, and obesity. Here, we use machine learning on fMRI activity during an intertemporal choice task to develop a functional brain marker of these individual differences in human adults. Training and cross-validating the marker in one dataset (Study 1, N = 110 male adults) resulted in a significant prediction-outcome correlation (r = 0.49), generalized to predict individual differences in a completely independent dataset (Study 2: N = 145 male and female adults, r = 0.45), and predicted discounting several weeks later. Out-of-sample responses of the functional brain marker, but not discounting behavior itself, differed significantly between overweight and lean individuals in both studies, and predicted fasting-state blood levels of insulin, c-peptide, and leptin in Study 1. Significant predictive weights of the marker were found in cingulate, insula, and frontoparietal areas, among others, suggesting an interplay among regions associated with valuation, conflict processing, and cognitive control. This new functional brain marker is a step toward a generalizable brain model of individual differences in delay discounting. Future studies can evaluate it as a potential transdiagnostic marker of altered decision-making in different clinical and developmental populations.SIGNIFICANCE STATEMENT People differ substantially in how much they prefer smaller sooner rewards or larger later rewards such as spending money now versus saving it for retirement. These individual differences are generally stable over time and have been related to differences in mental and bodily health. What is their neurobiological basis? We applied machine learning to brain-imaging data to identify a novel brain activity pattern that accurately predicts how much people prefer sooner versus later rewards, and which can be used as a new brain-based measure of intertemporal decision-making in future studies. The resulting functional brain marker also predicts overweight and metabolism-related blood markers, providing new insight into the possible links between metabolism and the cognitive and brain processes involved in intertemporal decision-making.

Evaluation of medications used for opioid use disorder in emergency departments: A cross-sectional analysis of the 2020 National Hospital Ambulatory Medical Care Survey.

INTRODUCTION: Opioid use disorder (OUD) is a significant health issue impacting millions in the United States (US). Medications used for OUD (MOUD) (e.g., buprenorphine, methadone, naltrexone) and medications for overdose and symptom management (e.g., naloxone, clonidine) have been shown to be safe and effective tools in clinical management. MOUD therapy in Emergency Departments (EDs) improves patient outcomes and enhances engagement with formal addiction treatment; however, provider factors and institutional barriers have created hurdles to ED-based MOUD treatment and heterogeneity in ED based OUD care. We used a nationally representative dataset, the National Hospital Ambulatory Medical Care Survey (NHAMCS) to characterize MOUD prescribing practices across patient demographics, geographic regions, payers, providers, and comorbidities in EDs. METHODS: NHAMCS is a survey conducted by the US Census Bureau assessing utilization of ambulatory healthcare services nationally. Survey staff compile encounter records from a nationally representative sample of EDs. We conducted a cross-sectional study using this data to assess visits in 2020 among patients aged 18-64 presenting with an opioid overdose or OUD. We estimated the proportion of patients who had any MOUD, clonidine, or naloxone treatment and 95% confidence intervals (CI). We modeled the association between patient demographic, location, comorbidities, and provider characteristics with receipt of MOUD treatment as unadjusted odds ratios (OR) and 95% CI. RESULTS: There was a weighted frequency of 469,434 patients who were discharged from EDs after being seen for OUD or overdose. Naloxone, clonidine, and buprenorphine were the most frequent treatments administered and/or prescribed for OUDs or overdose. Overall, 54,123 (11.5%, 95%CI 0-128,977) patients who were discharged from the ED for OUDs or overdose received at least one type of MOUD. Hispanic race, (OR 17.9, 95%CI 1.33-241.90) and Western region (OR43.77, 95%CI 2.97-645.27) were associated with increased odds of receiving MOUDs, while arrival by ambulance was associated with decreased odds of receiving MOUDs (OR0.01, 95%CI 0.001-0.19). Being seen by an APP or physician assistant was associated with MOUD treatment (OR 16.68, 95%CI: 1.41-152.33; OR: 13.84, 95%CI: 3.58-53.51, respectively). CONCLUSION: Our study findings suggest that MOUD and other medications for opioid overdose are infrequently used in the ED setting. This finding was especially notable in race, geographic region, mode of arrival, and those seen by APP, underscoring the need for further study into the root causes of these disparities. Our study provides a foundational understanding of MOUD patterns, guiding future research as the landscape of OUD treatment continues to shift.

A Nationwide Emergency Department Data Analysis to Predict Beers List Medications Use Among Older Adults.

BACKGROUND: The use of potentially inappropriate medications (PIMs) is considered an important quality indicator for older adults seen in the ambulatory care setting. STUDY OBJECTIVES: To evaluate the pattern of potentially inappropriate medication (PIMs) use as specified in the Beers Criteria, for older adults during emergency department (ED) visits in the United States. METHODS: Using data from the National Hospital Ambulatory Care Survey (NHAMCS) we identified older adults (age 65 or older) discharged home from an ED visit in 2019. We defined PIMs as those with an 'avoid' recommendation under the American Geriatrics Society (AGS) 2019 Beers Criteria in older adults. Logistic regression models were used to assess demographic, clinical, and hospital factors associated with the use of any PIMs upon ED discharge. RESULTS: Overall, 5.9% of visits by older adults discharged from the ED included administration or prescriptions for PIMs. Among those who received any PIMs, 25.5% received benzodiazepines, 42.5 % received anticholinergics, 1.4% received nonbenzodiazepine hypnotics, and 0.5% received barbiturates. A multivariable model showed statistically significant associations for age 65 to 74 (OR 1.91, 95% CI 1.39-2.62 vs. age >=75), dementia (OR 0.45, 95% CI 0.21-0.95), lower immediacy (OR 2.45, 95% CI 1.56-3.84 vs. higher immediacy), and Northeastern rural region (OR 0.34, 95% CI 0.21-0.55 vs. Midwestern rural). CONCLUSION: We found that younger age and lower immediacy were associated with increased prescriptions of PIMs for older adults seen, while dementia and Northeastern rural region was associated with reduced use of PIMs seen and discharged from EDs in United States.

Bispectral EEG (BSEEG) Algorithm Captures High Mortality Risk Among 1,077 Patients: Its Relationship to Delirium Motor Subtype.

OBJECTIVE: Delirium is dangerous and a predictor of poor patient outcomes. We have previously reported the utility of the bispectral EEG (BSEEG) with a novel algorithm for the detection of delirium and prediction of patient outcomes including mortality. The present study employed a normalized BSEEG (nBSEEG) score to integrate the previous cohorts to combine their data to investigate the prediction of patient outcomes. We also aimed to test if the BSEEG method can be applicable regardless of age, and independent of delirium motor subtypes. METHODS: We calculated nBSEEG score from raw BSEEG data in each cohort and classified patients into BSEEG-positive and BSEEG-negative groups. We used log-rank test and Cox proportional hazards models to predict 90-day and 1-year outcomes for the BSEEG-positive and -negative groups in all subjects and motor subgroups. RESULTS: A total of 1,077 subjects, the BSEEG-positive group showed significantly higher 90-day (hazard ratio 1.33 [95% CI 1.16-1.52] and 1-year (hazard ratio 1.22 [95% CI 1.06-1.40] mortality rates than the negative group after adjustment for covariates such as age, sex, CCI, and delirium status. Among patients with different motor subtypes of delirium, the hypoactive group showed significantly higher 90-day (hazard ratio 1.41 [95% CI 1.12-1.76] and 1-year mortality rates (hazard ratio 1.32 [95% CI 1.05-1.67], which remained significant after adjustment for the same covariates. CONCLUSION: We found that the BSEEG method is capable of capturing patients at high mortality risk.

Evaluating the performance of machine learning methods for risk estimation of delirium in patients hospitalized from the emergency department.

INTRODUCTION: Delirium is a cerebral dysfunction seen commonly in the acute care setting. It is associated with increased mortality and morbidity and is frequently missed in the emergency department (ED) and inpatient care by clinical gestalt alone. Identifying those at risk of delirium may help prioritize screening and interventions in the hospital setting. OBJECTIVE: Our objective was to leverage electronic health records to identify a clinically valuable risk estimation model for prevalent delirium in patients being transferred from the ED to inpatient units. METHODS: This was a retrospective cohort study to develop and validate a risk model to detect delirium using patient data available from prior visits and ED encounter. Electronic health records were extracted for patients hospitalized from the ED between January 1, 2014, and December 31, 2020. Eligible patients were aged 65 or older, admitted to an inpatient unit from the emergency department, and had at least one DOSS assessment or CAM-ICU recorded within 72 h of hospitalization. Six machine learning models were developed to estimate the risk of delirium using clinical variables including demographic features, physiological measurements, medications administered, lab results, and diagnoses. RESULTS: A total of 28,531 patients met the inclusion criteria with 8057 (28.4%) having a positive delirium screening within the outcome observation period. Machine learning models were compared using the area under the receiver operating curve (AUC). The gradient boosted machine achieved the best performance with an AUC of 0.839 (95% CI, 0.837-0.841). At a 90% sensitivity threshold, this model achieved a specificity of 53.5% (95% CI 53.0%-54.0%) a positive predictive value of 43.5% (95% CI 43.2%-43.9%), and a negative predictive value of 93.1% (95% CI 93.1%-93.2%). A random forest model and L1-penalized logistic regression also demonstrated notable performance with AUCs of 0.837 (95% CI, 0.835-0.838) and 0.831 (95% CI, 0.830-0.833) respectively. CONCLUSION: This study demonstrated the use of machine learning algorithms to identify a combination of variables that enables an estimation of risk of positive delirium screens early in hospitalization to develop prevention or management protocols.

Noninvasive Ventilation for Acute Respiratory Failure in Pediatric Patients: A Systematic Review and Meta-Analysis.

OBJECTIVE: To perform a systematic review and meta-analysis of randomized controlled trials (RCTs) on the use of noninvasive ventilation (NIV) for acute respiratory failure (ARF) in pediatric patients. DATA SOURCES: We searched PubMed, EMBASE, the Cochrane Central Register of Clinical Trials, and Clinicaltrials.gov with a last update on July 31, 2022. STUDY SELECTION: We included RCTs comparing NIV with any comparator (standard oxygen therapy and high-flow nasal cannula [HFNC]) in pediatric patients with ARF. We excluded studies performed on neonates and on chronic respiratory failure patients. DATA EXTRACTION: Baseline characteristics, intubation rate, mortality, and hospital and ICU length of stays were extracted by trained investigators. DATA SYNTHESIS: We identified 15 RCTs (2,679 patients) for the final analyses. The intubation rate was 109 of 945 (11.5%) in the NIV group, and 158 of 1,086 (14.5%) in the control group (risk ratio, 0.791; 95% CI, 0.629-0.996; p = 0.046; I2 = 0%; number needed to treat = 31). Findings were strengthened after removing studies with intervention duration shorter than an hour and after excluding studies with cross-over as rescue treatment. There was no difference in mortality, and ICU and hospital length of stays. CONCLUSIONS: In pediatric patients, NIV applied for ARF might reduce the intubation rate compared with standard oxygen therapy or HFNC. No difference in mortality was observed.

Delirium, confusion, or altered mental status as a risk for abnormal head CT in older adults in the emergency department: A systematic review and meta-analysis.

BACKGROUND: Altered mental status (including delirium) is a common presentations among older adults to the emergency department (ED). We aimed to report the association between altered mental status in older ED patients and acute abnormal findings on head computed tomogram (CT). METHODS: A systematic review was conducted using Ovid Medline, Embase, Clinicaltrials.gov, Web of Science, and Cochrane Central from conception to April 8th, 2021. We included citations if they described patients aged 65 years or older who received head imaging at the time of ED assessment, and reported whether patients had delirium, confusion, or altered mental status. Screening, data extraction, and bias assessment were performed in duplicate. We estimated the odds ratios (OR) for abnormal neuroimaging in patients with altered mental status. RESULTS: The search strategy identified 3031 unique citations, of which two studies reporting on 909 patients with delirium, confusion or altered mental status were included. No identified study formally assessed for delirium. The OR for abnormal head CT findings in patients with delirium, confusion or altered mental status was 0.35 (95% CI 0.031 to 3.97) compared to patients without delirium, confusion or altered mental status. CONCLUSION: We did not find a statistically significant association between delirium, confusion or altered mental status and abnormal head CT findings in older ED patients.

Comparison of diagnosis-based risk adjustment methods for episode-based costs to apply in efficiency measurement.

BACKGROUND: The recent rising health spending intrigued efficiency and cost-based performance measures. However, mortality risk adjustment methods are still under consideration in cost estimation, though methods specific to cost estimate have been developed. Therefore, we aimed to compare the performance of diagnosis-based risk adjustment methods based on the episode-based cost to utilize in efficiency measurement. METHODS: We used the Health Insurance Review and Assessment Service-National Patient Sample as the data source. A separate linear regression model was constructed within each Major Diagnostic Category (MDC). Individual models included explanatory (demographics, insurance type, institutional type, Adjacent Diagnosis Related Group [ADRG], diagnosis-based risk adjustment methods) and response variables (episode-based costs). The following risk adjustment methods were used: Refined Diagnosis Related Group (RDRG), Charlson Comorbidity Index (CCI), National Health Insurance Service Hierarchical Condition Categories (NHIS-HCC), and Department of Health and Human Service-HCC (HHS-HCC). The model accuracy was compared using R-squared (R2), mean absolute error, and predictive ratio. For external validity, we used the 2017 dataset. RESULTS: The model including RDRG improved the mean adjusted R2 from 40.8% to 45.8% compared to the adjacent DRG. RDRG was inferior to both HCCs (RDRG adjusted R2 45.8%, NHIS-HCC adjusted R2 46.3%, HHS-HCC adjusted R2 45.9%) but superior to CCI (adjusted R2 42.7%). Model performance varied depending on the MDC groups. While both HCCs had the highest explanatory power in 12 MDCs, including MDC P (Newborns), RDRG showed the highest adjusted R2 in 6 MDCs, such as MDC O (pregnancy, childbirth, and puerperium). The overall mean absolute errors were the lowest in the model with RDRG ($1,099). The predictive ratios showed similar patterns among the models regardless of the  subgroups according to age, sex, insurance type, institutional type, and the upper and lower 10th percentiles of actual costs. External validity also showed a similar pattern in the model performance. CONCLUSIONS: Our research showed that either NHIS-HCC or HHS-HCC can be useful in adjusting comorbidities for episode-based costs in the process of efficiency measurement.

Insensitive Effects of Inflammatory Cytokines on the Reference Genes of Synovial Fluid Resident-Mesenchymal Stem Cells Derived from Rheumatoid Arthritis Patients.

Mesenchymal stem cells derived from rheumatoid arthritis patients (RA-MSCs) provide an understanding of a variety of cellular and immunological responses within the inflammatory milieu. Sustained exposure of MSCs to inflammatory cytokines is likely to exert an influence on genetic variations, including reference genes (RGs). The sensitive effect of cytokines on the reference genes of RA-SF-MSCs may be a variation factor affecting patient-derived MSCs as well as the accuracy and reliability of data. Here, we comparatively evaluated the stability levels of nine RG candidates, namely GAPDH, ACTB, B2M, EEF1A1, TBP, RPLP0, PPIA, YWHAZ, and HPRT1, to find the most stable ones. Alteration of the RG expression was evaluated in MSCs derived from the SF of healthy donors (H-SF-MSCs) and in RA-SF-MSCs using the geNorm and NormFinder software programs. The results showed that TBP, PPIA, and YWHAZ were the most stable RGs for the normalization of H-SF-MSCs and RA-SF-MSCs using RT-qPCR, whereas ACTB, the most commonly used RG, was less stable and performed poorly. Additionally, the sensitivity of RG expression upon exposure to proinflammatory cytokines (TNF-α and IL-1ß) was evaluated. RG stability was sensitive in the H-SF-MSCs exposed to TNF-α and IL-1ß but insensitive in the RA-SF-MSCs. Furthermore, the normalization of IDO expression using ACTB falsely diminished the magnitude of biological significance, which was further confirmed with a functional analysis and an IDO activity assay. In conclusion, the results suggest that TBP, PPIA, and YWHAZ can be used in SF-MSCs, regardless of their exposure to inflammatory cytokines.

The Ventral and Dorsal Default Mode Networks Are Dissociably Modulated by the Vividness and Valence of Imagined Events.

Recent work has shown that the brain's default mode network (DMN) is active when people imagine the future. Here, we test in human participants (both sexes) whether future imagination can be decomposed into two dissociable psychological processes linked to different subcomponents of the DMN. While measuring brain activity with fMRI as subjects imagine future events, we manipulate the vividness of these events to modulate the demands for event construction, and we manipulate the valence of these events to modulate the demands for event evaluation. We found that one subcomponent of the DMN, the ventral DMN or medial temporal lobe (MTL) subsystem, responds to the vividness but not the valence of imagined events. In contrast, another subcomponent, the dorsal or core DMN, responds to the valence but not the vividness of imagined events. This separate modifiability of different subcomponents of the DMN by vividness and valence provides strong evidence for a neurocognitive dissociation between (1) the construction of novel, imagined events from individual components from memory and (2) the evaluation of these constructed events as desirable or undesirable.

Dynamic Representation of the Subjective Value of Information.

To improve future decisions, people should seek information based on the value of information (VOI), which depends on the current evidence and the reward structure of the upcoming decision. When additional evidence is supplied, people should update the VOI to adjust subsequent information seeking, but the neurocognitive mechanisms of this updating process remain unknown. We used a modified beads task to examine how the VOI is represented and updated in the human brain of both sexes. We theoretically derived, and empirically verified, a normative prediction that the VOI depends on decision evidence and is biased by reward asymmetry. Using fMRI, we found that the subjective VOI is represented in the right dorsolateral prefrontal cortex (DLPFC). Critically, this VOI representation was updated when additional evidence was supplied, showing that the DLPFC dynamically tracks the up-to-date VOI over time. These results provide new insights into how humans adaptively seek information in the service of decision-making.SIGNIFICANCE STATEMENT For adaptive decision-making, people should seek information based on what they currently know and the extent to which additional information could improve the decision outcome, formalized as the VOI. Doing so requires dynamic updating of VOI according to outcome values and newly arriving evidence. We formalize these principles using a normative model and show that information seeking in people adheres to them. Using fMRI, we show that the underlying subjective VOI is represented in the dorsolateral prefrontal cortex and, critically, that it is updated in real time according to newly arriving evidence. Our results reveal the computational and neural dynamics through which evidence and values are combined to inform constantly evolving information-seeking decisions.

Comparison of the efficacy and safety of LBAL, a candidate adalimumab biosimilar, and adalimumab reference product in patients with active rheumatoid arthritis inadequately responding to methotrexate: a 52-week phase III randomised study.

OBJECTIVES: To evaluate the similarities between LBAL (adalimumab biosimilar candidate) and the adalimumab reference product (ADL) in terms of efficacy and safety, including immunogenicity, in patients with active rheumatoid arthritis despite methotrexate treatment. METHODS: This phase III, multicentre, randomised, double-blind, parallel-group, 56-week study was conducted in Japan and Korea. During the first 24 weeks, patients subcutaneously received 40 mg of LBAL or ADL every two weeks (LBAL and ADL groups). During the subsequent 28 weeks, the LBAL group patients and half of the ADL group patients received LBAL (L-L and A-L arms). The remaining ADL group patients continued to receive ADL (A-A arm). The primary efficacy endpoint was the change from baseline in disease activity score 28-erythrocyte sedimentation rate (DAS28-ESR) at Week 24. American College of Rheumatology (ACR) response rates, adverse events (AEs), and anti-drug antibody (ADA) were also assessed. RESULTS: In total, 383 patients were randomised. The least squares (LS) mean changes from baseline in DAS28-ESR at Week 24 were -2.45 and -2.53 in the LBAL (n=191) and ADL (n=190) groups, respectively. The 95% confidence interval (CI; -0.139, 0.304) of the difference (0.08) was within the pre-specified equivalence margin (-0.6, 0.6). Up to Week 52, the decreases in DAS28-ESR were maintained in all three arms. No notable differences in ACR20/50/70 were observed. The AE and ADA incidences were comparable between the arms. CONCLUSIONS: LBAL was equivalent in efficacy and comparable in safety, including immunogenicity, to ADL. Switching from ADL to LBAL did not impact on efficacy and safety.

An Exploration Into Patients' Experiences That Make Them Feel Safe During Hospitalization: A Qualitative Study.

BACKGROUND: Patient safety is a crucial indicator of health care quality. It is necessary to check the subjective perception of patient safety from the patient's point of view as a consumer of healthcare services. To identify patients' experiences of safety and the themes that constitute the patients' feeling of safety during hospitalization. METHODS: A qualitative study, comprising five focus group discussions (seven people each), was conducted in South Korea between May and July 2018. Patients who were hospitalized for at least three days within one year were included. Researchers analyzed the transcribed script, and a content analysis was performed to describe patients' hospitalized experiences of safety. RESULTS: A total of 35 patients with an average age of 45.4 years participated in the study, and had experience of hospitalization for up to 32 days. The findings revealed four core themes and 14 sub-themes. Patients wanted to take initiative in controlling his/her reception of information and wanted healthcare providers to make the patient feel safe. Patients felt safe when hospitals provided unstinted and generous support. Also, public sentiment about national healthcare and safety made an effect on patient safety sentiment. CONCLUSION: Patients felt safe during hospitalization not only because of the explanation, attitude, and professionalism of the healthcare providers but also because of the support, system, and procedure of the medical institution. Healthcare providers and medical institutions should strive to narrow the gap in patient safety awareness factors through activities with patients. Furthermore, the government and society should make an effort to create a safe medical environment and social atmosphere.

Understanding Physicians' and Nurses' Adaption of National-Leading Patient Safety Culture Policy: A Qualitative Study in Tertiary and General Hospitals in Korea.

BACKGROUND: In Korea, the safety culture is led by national policy. How the policy ensures a patient safety culture needs to be investigated. This study aimed to examine the way in which physicians and nurses regard, understand, or interpret the patient safety-related policy in the hospital setting. METHODS: In this qualitative study, we conducted four focus group interviews (FGIs) with 25 physicians and nurses from tertiary and general hospitals in South Korea. FGIs data were analyzed using thematic analysis, which was conducted in an inductive and interpretative way. RESULTS: Three themes were identified. The healthcare providers recognized its benefits in the forms of knowledge, information and training at least although the policy implemented by the law forcibly and temporarily. The second theme was about the interaction of the policy and the Korean context of healthcare, which makes a "turning point" in the safety culture. The final theme was about some strains and conflicts resulting from patient safety policy. CONCLUSION: To provide a patient safety culture, it is necessary to develop a plan to improve the voluntary participation of healthcare professionals and their commitment to safety. Hospitals should provide more resources and support for healthcare professionals.

The Microbiome in Systemic Sclerosis: Pathophysiology and Therapeutic Potential.

Systemic sclerosis (SSc), also known as scleroderma, is an autoimmune disease with unknown etiology characterized by multi-organ fibrosis. Despite substantial investigation on SSc-related cellular and molecular mechanisms, effective therapies are still lacking. The skin, lungs, and gut are the most affected organs in SSc, which act as physical barriers and constantly communicate with colonized microbiota. Recent reports have documented a unique microbiome signature, which may be the pathogenic trigger or driver of SSc. Since gut microbiota influences the efficacy and toxicity of oral drugs, evaluating drug-microbiota interactions has become an area of interest in disease treatment. The existing evidence highlights the potential of the microbial challenge as a novel therapeutic option in SSc. In this review, we have summarized the current knowledge about molecular mechanisms of SSc and highlighted the underlying role of the microbiome in SSc pathogenesis. We have also discussed the latest therapeutic interventions using microbiomes in SSc, including drug-microbiota interactions and animal disease models. This review aims to elucidate the pathophysiological connection and therapeutic potential of the microbiome in SSc. Insights into the microbiome will significantly improve our understanding of etiopathogenesis and developing therapeutics for SSc.

Subjective value, not a gridlike code, describes neural activity in ventromedial prefrontal cortex during value-based decision-making.

Across many studies, ventromedial prefrontal cortex (vmPFC) activity has been found to correlate with subjective value during value-based decision-making. Recently, however, vmPFC has also been shown to reflect a hexagonal gridlike code during navigation through physical and conceptual space, and such gridlike codes have been proposed to enable value-based choices between novel options. Here, we first show that, in theory, a hexagonal gridlike code can in some cases mimic vmPFC activity previously attributed to subjective value, raising the possibility that the subjective value correlates previously observed in vmPFC may have actually been a misconstrued gridlike signal. We then compare the two accounts empirically, using fMRI data from a large number of subjects performing an intertemporal choice task. We find clear and unambiguous evidence that subjective value is a better description of vmPFC activity in this task than a hexagonal gridlike code. In fact, we find no significant evidence at all for a hexagonal gridlike code in vmPFC activity during intertemporal choice. This result limits the generality of gridlike modulation as description of vmPFC activity. We suggest that vmPFC may flexibly switch representational schemes so as to encode the most relevant information for the current task.

Diurnal variations of brown fat thermogenesis and fat oxidation in humans.

BACKGROUND/OBJECTIVES: Disturbed circadian rhythm is associated with an increased risk of obesity and metabolic disorders. Brown adipose tissue (BAT) is a site of nonshivering thermogenesis (NST) and plays a role in regulating whole-body energy expenditure (EE), substrate metabolism, and body fatness. In this study, we examined diurnal variations of NST in healthy humans by focusing on their relation to BAT activity. METHODS: Forty-four healthy men underwent 18F-fluoro-2-deoxy-D-glucose positron emission tomography and were divided into Low-BAT and High-BAT groups. In STUDY 1, EE, diet-induced thermogenesis (DIT), and fat oxidation (FO) were measured using a whole-room indirect calorimeter at 27 °C. In STUDY 2, EE, FO, and skin temperature in the region close to BAT depots (Tscv) and in the control region (Tc) were measured at 27 °C and after 90 min cold exposure at 19 °C in the morning and in the evening. RESULTS: In STUDY 1, DIT and FO after breakfast was higher in the High-BAT group than in the Low-BAT group (P < 0.05), whereas those after dinner were comparable in the two groups. FO in the High-BAT group was higher after breakfast than after dinner (P < 0.01). In STUDY 2, cold-induced increases in EE (CIT), FO, and Tscv relative to Tc in the morning were higher in the High-BAT group than in the Low-BAT group (P < 0.05), whereas those after dinner were comparable in the two groups. CIT in the High-BAT group tended to be higher in the morning than in the evening (P = 0.056). CONCLUSION: BAT-associated NST and FO were evident in the morning, but not in the evening, suggesting that the activity of human BAT is higher in the morning than in the evening, and thus may be involved in the association of an eating habit of breakfast skipping with obesity and related metabolic disorders.

The regional diversity of gut microbiome along the GI tract of male C57BL/6 mice.

BACKGROUND: The proliferation and survival of microbial organisms including intestinal microbes are determined by their surrounding environments. Contrary to popular myth, the nutritional and chemical compositions, water contents, O2 contents, temperatures, and pH in the gastrointestinal (GI) tract of a human are very different in a location-specific manner, implying heterogeneity of the microbial composition in a location-specific manner. RESULTS: We first investigated the environmental conditions at 6 different locations along the GI tract and feces of ten weeks' old male SPF C57BL/6 mice. As previously known, the pH and water contents of the GI contents at the different locations of the GI tract were very different from each other in a location-specific manner, and none of which were not even similar to those of feces. After confirming the heterogeneous nature of the GI contents in specific locations and feces, we thoroughly analyzed the composition of the microbiome of the GI contents and feces. 16S rDNA-based metagenome sequencing on the GI contents and feces showed the presence of 13 different phyla. The abundance of Firmicutes gradually decreased from the stomach to feces while the abundance of Bacteroidetes gradually increased. The taxonomic α-diversities measured by ACE (Abundance-based Coverage Estimator) richness, Shannon diversity, and Fisher's alpha all indicated that the diversities of gut microbiome at colon and cecum were much higher than that of feces. The diversities of microbiome compositions were lowest in jejunum and ileum while highest in cecum and colon. Interestingly, the diversities of the fecal microbiome were lower than those of the cecum and colon. Beta diversity analyses by NMDS plots, PCA, and unsupervised hierarchical clustering all showed that the microbiome compositions were very diverse in a location-specific manner. Direct comparison of the fecal microbiome with the microbiome of the whole GI tracts by α-and ß-diversities showed that the fecal microbiome did not represent the microbiome of the whole GI tract. CONCLUSION: The fecal microbiome is different from the whole microbiome of the GI tract, contrary to a baseline assumption of contemporary microbiome research work.

Appropriate Number of Adjuvant Chemotherapy Cycles for Patients with Stage 2 or 3 Gastric Cancer After Curative Gastrectomy: A Multicenter Cohort Study.

BACKGROUND: Few studies have presented evidence pertaining to the adequate minimum number of adjuvant chemotherapy (AC) cycles required to achieve an oncologic benefit for gastric cancer. METHODS: From January 2012 to December 2013, data from patients who underwent curative radical gastrectomy and consequently received AC for pathologic stage 2 or 3 gastric cancer at 27 institutions in South Korea were analyzed. RESULTS: The study enrolled 925 patients, 661 patients (71.5%) who completed 8 cycles of AC and 264 patients (28.5%) who did not. Compared with the mean disease-free survival (DFS) of the patients who completed 8 AC cycles (69.3 months), the mean DFS of patients who completed 6 AC cycles (72.4 months; p = 0.531) and those who completed 7 AC cycles (63.7 months; p = 0.184) did not differ significantly. However, the mean DFS of the patients who completed 5 AC cycles (48.2 months; p = 0.016) and those who completed 1-4 AC cycles (62.9 months; p = 0.036) was significantly lower than the DFS of those who completed 8 AC cycles. In the multivariate Cox proportional hazards analysis, the mean DFS was significantly affected by advanced stage, large tumor size, positive vascular invasion, and number of completed AC cycles (1-5 cycles: hazard ratio 1.45; 95% confidence interval 1.01-2.08; p = 0.041). CONCLUSION: The current multicenter observational cohort study showed that the mean DFS for 6 or 7 AC cycles was similar to that for 8 AC cycles as an adjuvant treatment for gastric cancer.