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IntroductionCognitive models of depression highlight the role of inhibitory control - the cognitive control ability which supports our goal directed behavior – as key and even causal feature of the disorder. According to these models, deficits in inhibitory control prevent the exclusion of irrelevant negative information, leading to rumination and sustained negative mood which result in depressive episodes. However, the scientific evidence linking deficits in inhibitory control to depression is thus far mixed. Moreover, although one’s inhibitory control ability may fluctuate, it is often assessed using a single-time measurement in the lab.ObjectivesHere we aimed to assess the association between intra-individual fluctuations in inhibitory control measured in ecological settings, daily mood states, and depressive symptoms.MethodsN=106 participants (Mean age: 38 ± 10 years; range: 19-62 years; 68% female) reported their depressive symptoms (using the PHQ-9 scale) and completed a mobile version of the Go-NoGo inhibition task at baseline. They then completed a 5-day ecological-momentary-assessment (EMA) protocol, in which they reported their current mood (using the IMS-12 scale) and performed a shortened version of the Go-NoGo task twice/day using a mobile application. Depressive symptoms were assessed again following the 5-day EMA. Hierarchical-linear-modeling (HLM) was applied to examine the association between momentary IC and mood, with post-EMA depressive symptoms as a moderator. Inhibitory control was included as a time-varying predictor for mood in the 1st step, and depressive symptoms post-EMA and their interaction with inhibition were included in the 2nd step.ResultsAt baseline, there were no correlations between depressive symptoms and inhibitory control (rp = .035, n.s). However, individuals with elevated depressive symptoms demonstrated worse and more variable inhibition performance over time (rp = .29, p = .002), as captured in the EMA measures. In addition, participants with more variable inhibitory control performance over time also reported more depressive symptoms at the end of the 5-day period (rp = .27, p = .006). Finally, post-EMA depressive symptoms moderated the association between momentary inhibitory control and daily mood, such that reduced inhibition was associated with more negative mood only for those with lower, but not with higher, depressive symptoms (Figure 1).Image:ConclusionsVariable, rather than mere reduced inhibitory control is related to depressive symptoms. Moreover, the role of inhibition in modulating mood differs in non-depressed vs. depressed individuals. These findings contribute to our understanding of inhibition and mood in real life and help account for some of the discrepant findings related to cognitive control models of depression. Future investigations should examine the validity of these outcomes in other, clinical samples.Disclosure of InterestNone Declared

Thermokarst lakes, formed by permafrost thaw in the Arctic, are hotspots for methane (CH.sub.4) and carbon dioxide (CO.sub.2) emissions and are expected to double permafrost carbon emissions by the end of the century. While the implications of ongoing permafrost thaw on CH.sub.4 dynamics in these lakes have been modeled, here we provide empirical data on CH.sub.4 production dynamics as lakes evolve from young recently formed lakes to older lakes that have been present for hundreds of years. Sediment cores (up to 4 m long) were collected from the centers and thermokarst margins of a new thermokarst lake (Big Trail Lake (BTL), 70 years old) and from an older thermokarst lake (Goldstream Lake (GSL), â¼ 900 years old) from the same interior Alaskan watershed. The highest CH.sub.4 production rates were observed in the uppermost sediments near the sediment-water interface at the thermokarst margins of both lakes, with a steep decrease with sediment depth into the talik. BTL exhibited elevated CH.sub.4 production rates, correlated with higher carbon lability for thermal-induced reactions measured by Rock-Eval analyses, suggesting its potential use as a proxy for organic carbon breakdown by methanogenesis. In contrast, GSL displayed lower CH.sub.4 production rates, likely due to a longer period of organic carbon degradation and reduced carbon lability. The integrated sediment-column CH.sub.4 production rates were similar (around 7 to 10 mol m.sup.-2 yr.sup.-1 ), primarily due to the thinner talik at BTL. Our data support the predictions that the formation and expansion of thermokarst lakes over the next centuries will increase CH.sub.4 production in newly thawed Yedoma permafrost sediments, while CH.sub.4 production will decrease as taliks mature and labile organic carbon is used up.

Stress-related psychopathology is highly prevalent among elderly individuals and is associated with detrimental effects on mood, appetite and cognition. Conversely, under certain circumstances repeated mild-to-moderate stressors have been shown to enhance cognitive performance in rodents and exert stress-inoculating effects in humans. As most stress-related favorable outcomes have been reported in adolescence and young-adulthood, this apparent disparity could result from fundamental differences in how aging organisms respond to stress. Furthermore, given prominent age-related alterations in sex hormones, the effect of chronic stress in aging females remains a highly relevant yet little studied issue. In the present study, female C57BL/6 mice aged 3 (young-adult) and 20-23 (old) months were subjected to 8 weeks of chronic unpredictable stress (CUS). Behavioral outcomes were measured during the last 3 weeks of the CUS protocol, followed by brain dissection for histological and molecular end points. We found that in young-adult female mice, CUS resulted in decreased anxiety-like behavior and enhanced cognitive performance, whereas in old female mice it led to weight loss, dysregulated locomotion and memory impairment. These phenotypes were paralleled by differential changes in the expression of hypothalamic insulin and melanocortin-4 receptors and were consistent with an age-dependent reduction in the dynamic range of stress-related changes in the hippocampal transcriptome. Supported by an integrated microRNA (miRNA)-mRNA expression analysis, the present study proposes that, when confronted with ongoing stress, neuroprotective mechanisms involving the upregulation of neurogenesis, Wnt signaling and miR-375 can be harnessed more effectively during young-adulthood. Conversely, we suggest that aging alters the pattern of immune activation elicited by stress. Ultimately, interventions that modulate these processes could reduce the burden of stress-related psychopathology in late life.

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depression. However, the link between inhibition of serotonin reuptake and remission from depression remains controversial: in spite of the rapid onset of serotonin reuptake inhibition, remission from depression takes several weeks, presumably reflecting synaptogenesis/neurogenesis and neuronal rewiring. We compared genome-wide expression profiles of human lymphoblastoid cell lines from unrelated individuals following treatment with 1 μ M paroxetine for 21 days with untreated control cells and examined which genes and microRNAs (miRNAs) showed the most profound and consistent expression changes. ITGB3 , coding for integrin beta-3, showed the most consistent altered expression (1.92-fold increase, P =7.5 × 10 −8 ) following chronic paroxetine exposure. Using genome-wide miRNA arrays, we observed a corresponding decrease in the expression of two miRNAs, miR-221 and miR-222, both predicted to target ITGB3 . ITGB3 is crucial for the activity of the serotonin transporter (SERT), the drug target of SSRIs. Moreover, it is presumably required for the neuronal guidance activity of CHL1 , whose expression was formerly identified as a tentative SSRI response biomarker. Further genes whose expression was significantly modulated by chronic paroxetine are also implicated in neurogenesis. Surprisingly, the expression of SERT or serotonin receptors was not modified. Our findings implicate ITGB3 in the mode of action of SSRI antidepressants and provide a novel link between CHL1 and the SERT. Our observations suggest that SSRIs may relieve depression primarily by promoting neuronal synaptogenesis/neurogenesis rather than by modulating serotonin neurotransmission per se .

Earlier in the day, pro-[Ouattara] fighters ambushed a police station in the Adjame district of Abidjan, though it was unclear whether anyone was killed. Adjame resident Idrissa Ouedraogo said commandos loyal to Mr Ouattara went around the neighbourhood and warned people to stay inside just minutes before the morning attack. Police loyal to sitting president Laurent Gbagbo were later seen fleeing the scene, he said.

Over 30% of patients with major depression do not respond well to first-line treatment with selective serotonin reuptake inhibitors (SSRIs). Using genome-wide expression profiling of human lymphoblastoid cell lines (LCLs) was identified as a tentative SSRI sensitivity biomarker. This study reports on miRNAs implicated in SSRI sensitivity of LCLs. Eighty LCLs were screened from healthy adult female individuals for growth inhibition by paroxetine. Eight LCLs exhibiting high or low sensitivities to paroxetine were chosen for genome-wide expression profiling with miRNA microarrays. The miRNA miR-151-3p had 6.7-fold higher basal expression in paroxetine-sensitive LCLs. This corresponds with lower expression of , a target of miR-151-3p. The additional miRNAs miR-212, miR-132, miR-30b*, let-7b and let-7c also differed by >1.5-fold (p < 0.05) between the two LCL groups. The potential value of these miRNAs as tentative SSRI response biomarkers awaits validation with lymphocyte samples of major depression patients. Original submitted 28 March 2012; Revision submitted 21 May 2012

Carriers of carbapenem-resistant Enterobacteriaceae (CRE) are often readmitted, exposing patients to CRE cross-transmission. OBJECTIVE To identify predictors of persistent CRE carriage upon readmission, directing a risk prediction score. Retrospective cohort study. University-affiliated general hospital. A cohort of 168 CRE carriers with 474 readmissions. The primary and secondary outcomes were CRE carriage status at readmission and length of CRE carriage. Predictors of persistent CRE carriage upon readmission were analyzed using a generalized estimating equations (GEE) multivariable model. Readmissions were randomly divided into derivation and validation sets. A CRE readmission score was derived to predict persistent CRE carriage in 3 risk groups: high, intermediate, and low. The discriminatory ability of the model and the score were expressed as C statistics. CRE carrier status persisted for 1 year in 33% of CRE carriers. Positive CRE status was detected in 202 of 474 readmissions (42.6%). The following 4 variables were associated with persistent CRE carriage at readmission: readmission within 1 month (odds ratio [OR], 6.95; 95% confidence interval [CI], 2.79-17.30), positive CRE status on preceding admission (OR, 5.46; 95% CI, 3.06-9.75), low Norton score (OR, 3.07; 95% CI, 1.26-7.47), and diabetes mellitus (OR, 1.84; 95% CI, 0.98-3.44). The C statistics were 0.791 and 0.789 for the derivation set (n=322) model and score, respectively, and the C statistic was 0.861 for the validation set of the score (n=152). The rates of CRE carriage at readmissions (validation set) for the groups with low, intermediate, and high scores were 8.6%, 38.9%, and 77.6%, respectively. CRE carrier state commonly persists upon readmission, and this risk can be estimated to guide screening policy and infection control measures.

Major depression disorder (MDD) is the most widespread mental disorder. Selective serotonin reuptake inhibitors (SSRIs) are used as first-line MDD treatment but are effective in <70% of patients. Thus, biomarkers for the early identification of treatment-resistant (TR) MDD patients are needed for prioritizing them for alternative therapeutics. SSRI-induced inhibition of the growth of peripheral blood mononuclear cells (PBMCs) is mediated via their target, the serotonin transporter (SERT). Here, we examined whether antidepressant drug-induced inhibition of the growth of PBMCs differed between MDD patients and healthy controls. PBMCs from well-characterized 33 treatment-sensitive (TS) and 33 TR MDD patients, and 24 healthy volunteers were studied. Dose-dependent inhibition of PBMCs growth was observed for both the non-SSRI antidepressant mirtazapine and the SSRI antidepressant paroxetine. Significantly lower sensitivities to 20 μ m paroxetine were observed in MDD compared with control PBMCs prior to treatment onset (13% and 46%, respectively; P< 0.05). Following antidepressant drug treatment for 4 or 7 weeks, the ex vivo paroxetine sensitivity increased to control levels in PBMCs from TS but not from TR MDD patients. This suggests that the low ex vivo paroxetine sensitivity phenotype reflects a state marker of depression. A significantly lower expression of integrin beta-3 ( ITGB3 ), a co-factor of the SERT, was observed in the PBMCs of MDD patients prior to treatment onset compared with healthy controls, and may explain their lower paroxetine sensitivity. Further studies with larger cohorts are required for clarifying the potential of reduced PBMCs paroxetine sensitivity and lower ITGB3 expression as MDD biomarkers.

Abstract Disclosure: E. Jaffe: None. I. Ayalon-Dangur: Grant Recipient; Self; Boehringer Ingelheim. A. Grossman: None. H. Hendel: None. Y. Oved: None. A. Shaked: None. I. Shimon: None. B. Basharim: None. M. Abo Molhem: None. R. McNeil: None. R. Abuhasira: None. T. Shitrit: None. L. Azulay Gitter: None. R. El Saleh: None. T. Shochat: None. N. Eliakim-Raz: None. Background: Type 2 diabetes mellitus (T2DM) is a major cause of morbidity and mortality. Current guidelines recommend the use of glucagon-like peptide-1 receptor agonists (GLP-1RA) and sodium-glucose cotransporter-2 inhibitors (SGLT2i) in patients with T2DM with or at high risk for cardiovascular disease to reduce mortality. Despite the established benefit, many studies found low treatment rates with these medications in eligible patients. The aim of our study is to examine the effectiveness of a clinical decision support (CDS) algorithm that was developed in our institution, in improving the recommendation rate of SGLT2i and GLP-1RA upon discharge from hospitalization in internal medicine wards. Methods: Our algorithm was developed to automatically recommend SGLT2i and GLP-1RA for T2DM patients based on current guidelines. Data was collected from electronic medical records of all T2DM patients ≥18 years old who were eligible for SGLT2i or GLP-1RA and hospitalized for any reason in one of five internal medicine wards in Beilinson Hospital. The primary outcome was to evaluate the rate of physician recommendation of SGLT2i or GLP-1RA at hospital discharge for eligible patients pre-algorithm implementation (January 2021-December 2021) versus post-algorithm implementation (April 2023-September 2023). Results: A total of 1318 patients were included in the pre-algorithm group and 970 were included in the post-algorithm group. Median age was 75 and 73 years in the pre- and post-algorithm groups, respectively. In the pre-algorithm group, 62% were males vs 60% in the post-algorithm group. Median length of hospitalization was three days and four days in the pre- and post-algorithm groups, respectively. The rate of SGLT2i and GLP-1RA recommendation for eligible patients was 8.50% (112 of 1318 patients) in the pre-algorithm group and 22.68% (220 of 970 patients) in the post-algorithm group. The odds ratio of the recommendation rate in the post vs pre-algorithm group was 3.151, 95% confidence interval 2.467– 4.025, p<0.0001. Conclusion: The results of this study demonstrate the benefit of an algorithm as part of a CDS system to improve recommendation rates of SGLT2i and GLP-1RA for eligible patients upon discharge from hospitalization. Future studies should assess the impact of the algorithm on prescription rates, patient adherence, and long-term outcomes. Presentation: 6/2/2024

The Veterans Health Administration (VHA) is plagued by abnormally high no-show and cancellation rates that reduce the productivity and efficiency of its medical outpatient clinics. We address this issue by developing a dynamic scheduling system that utilizes mobile computing via geo-location data to estimate the likelihood of a patient arriving on time for a scheduled appointment. These likelihoods are used to update the clinic’s schedule in real time. When a patient’s arrival probability falls below a given threshold, the patient’s appointment is canceled. This appointment is immediately reassigned to another patient drawn from a pool of patients who are actively seeking an appointment. The replacement patients are prioritized using their arrival probability. Real-world data were not available for this study, so synthetic patient data were generated to test the feasibility of the design. The method for predicting the arrival probability was verified on a real set of taxicab data. This study demonstrates that dynamic scheduling using geo-location data can reduce the number of unused appointments with minimal risk of double booking resulting from incorrect predictions. We acknowledge that there could be privacy concerns with regards to government possession of one’s location and offer strategies for alleviating these concerns in our conclusion.