Abnormal salience attribution is implicated in heroin addiction. Previously, combining functional magnetic resonance imaging (fMRI) and a drug cue-reactivity task, we demonstrated abnormal patterns of subjective response and brain reactivity in heroin-dependent individuals. However, whether the changes in cue-induced brain response were related to relapse was unknown. In a prospective study, we recruited 49 heroin-dependent patients under methadone maintenance treatment, a gold standard treatment (average daily dose 41.8 ± 16.0 mg), and 20 healthy subjects to perform the heroin cue-reactivity task during fMRI. The patients' subjective craving was evaluated. They participated in a follow-up assessment for 3 months, during which heroin use was assessed and relapse was confirmed by self-reported relapse or urine toxicology. Differences between relapsers and non-relapsers were analyzed with respect to the results from heroin-cue responses. Compared with healthy subjects, relapsers and non-relapsers commonly demonstrated significantly increased brain responses during the processing of heroin cues in the mesolimbic system, prefrontal regions and visuospatial-attention regions. However, compared with non-relapsers, relapsers demonstrated significantly greater cue-induced craving and the brain response mainly in the bilateral nucleus accumbens/subcallosal cortex and cerebellum. Although the cue-induced heroin craving was low in absolute measures, the change in craving positively correlated with the activation of the nucleus accumbens/subcallosal cortex among the patients. These findings suggest that in treatment-seeking heroin-dependent individuals, greater cue-induced craving and greater specific regional activations might be related to reward/craving and memory retrieval processes. These responses may predict relapse and represent important targets for the development of new treatment for heroin addiction.

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We present the analysis of seven microlensing planetary events with planet/host mass ratios q < 10−4: KMT-2017-BLG-1194, KMT-2017-BLG-0428, KMT-2019-BLG-1806, KMT-2017-BLG-1003, KMT-2019-BLG-1367, OGLE-2017-BLG-1806, and KMT-2016-BLG-1105. They were identified by applying the Korea Microlensing Telescope Network (KMTNet) AnomalyFinder algorithm to 2016–2019 KMTNet events. A Bayesian analysis indicates that all the lens systems consist of a cold super-Earth orbiting an M or K dwarf. Together with 17 previously published and three that will be published elsewhere, AnomalyFinder has found a total of 27 planets that have solutions with q < 10−4 from 2016–2019 KMTNet events, which lays the foundation for the first statistical analysis of the planetary mass-ratio function based on KMTNet data. By reviewing the 27 planets, we find that the missing planetary caustics problem in the KMTNet planetary sample has been solved by AnomalyFinder. We also find a desert of high-magnification planetary signals (A ≳ 65), and a follow-up project for KMTNet high-magnification events could detect at least two more q < 10−4 planets per year and form an independent statistical sample.