Miracle-dz/UniFAR-FTUs huggingface dataset:
Early-life stress alters chromatin modifications in VTA to prime stress sensitivity

Early-life stress increases sensitivity to subsequent stress, which has been observed among humans, other animals, at the level of cellular activity, and at the level of gene expression. However, the molecular mechanisms underlying such long-lasting sensitivity are poorly understood. We tested the hypothesis that persistent changes in transcription and transcriptional potential were maintained at the level of the epigenome, through changes in chromatin. We used a combination of bottom-up mass spectrometry, viral-mediated epigenome-editing, behavioral quantification, and RNA-sequencing in a mouse model of early-life stress, focusing on the ventral tegmental area (VTA), a brain region critically implicated in motivation, reward learning, stress response, and mood and drug disorders. We find that early-life stress in mice alters histone dynamics in VTA and that a majority of these modifications are associated with an open chromatin state that would predict active, primed, or poised gene expression, including enriched histone-3 lysine-4 methylation and the H3K4 monomethylase Setd7. Mimicking ELS through over-expression of Setd7 and enrichment of H3K4me1 in VTA recapitulates ELS-induced behavioral and transcriptional hypersensitivity to future stress. These findings enrich our understanding of the epigenetic mechanisms linking early-life environmental experiences to long-term alterations in stress reactivity within the brain’s reward circuitry, with implications for understanding and potentially treating mood and anxiety disorders in humans.
Comparing different methods of human breast milk fortification using measured v. assumed macronutrient composition to target reference growth: a randomised controlled trial

Abstract The variable content of human breast milk suggests that its routine fortification may result in sub-optimal nutritional intakes and growth. In a pragmatic trial, we randomised infants born below 30 weeks of gestation to either the intervention (Igp) of fortifying milk on measured composition according to birth weight criteria and postmenstrual age (PMA) or our routine practice (RPgp) of fortifying on assumed milk composition to target 3·8–4·4 g protein/kg per d and 545–629 kJ/kg per d. Milk composition was measured using the MIRIS® Human Milk Analyser. Percentage fat mass (%FM) was measured using PEA POD (COSMED). The effects of macronutrient intakes and clinical variables on growth were assessed using mixed model analysis. Mean measured protein content (1·6 g/100 ml) was higher than the assumed value (1·4 g/100 ml), often leading to lower amounts of fortifier added to the milk of intervention infants. At discharge (Igp v. RPgp), total protein (3·2 (sd 0·3) v. 3·4 (sd 0·4) g; P=0·067) and energy (456 (sd 39) v. 481 (sd 48) kJ; P=0·079) intakes from all nutrition sources, weight gain velocity (11·4 (sd 1·4) v. 12·1 (sd 1·6) g/kg per d; P=0·135) and %FM (13·7 (sd 3·6) v.13·6 (sd 3·5) %; P=0·984) did not significantly differ between groups. A protein intake >3·4 g/kg per d reduced %FM by 2 %. Nutrition and growth was not improved by targeting milk fortification according to birth weight criteria and PMA using measured milk composition, compared with routine practice. Targeting fortification on measured composition is labour intensive, requiring frequent milk sampling and precision measuring equipment, perhaps reasons for its limited practice. Guidance around safe upper levels of milk fortification is needed.
Decoding the Cognitive map: Learning place cells and remapping

Hippocampal place cells are known for their spatially selective firing and are believed to encode an animal’s location while forming part of a cognitive map of space. These cells exhibit marked tuning curve and rate changes when an animal’s environment is sufficiently manipulated, in a process known as remapping. Place cells are accompanied by many other spatially tuned cells such as border cells and grid cells, but how these cells interact during navigation and remapping is unknown. In this work, we build a normative place cell model wherein a neural network is tasked with accurate position reconstruction and path integration. Motivated by the notion of a cognitive map, the network’s position is estimated directly from its learned representations. To obtain a position estimate, we propose a non-trainable decoding scheme applied to network output units, inspired by the localized firing patterns of place cells. We find that output units learn place-like spatial representations, while upstream recurrent units become boundary-tuned. When the network is trained to perform the same task in multiple simulated environments, its place-like units learn to remap like biological place cells, displaying global, geometric and rate remapping. These remapping abilities appear to be supported by rate changes in upstream units. While the model does not learn grid-like units, its place cell centers form clusters organized in a hexagonal lattice in open fields. When we decode the center locations of CA1 place fields in mice, we find a similar clustering tendency. This suggests a potential mechanism for the interaction between place cells, border cells, and grid cells. Our model provides a normative framework for learning spatial representations previously reserved for biological place cells, providing new insight into place cell field formation and remapping.
Variability in temperature, precipitation and river discharge in the Baltic States

The climate change impact on water resources is observed in all the Baltic States. These processes became more evident in the last decades. Although the territory of the Baltic States (Lithuania, Latvia, Estonia) is not large (175 000 km2), the climatic differences are quite considerable. We performed a regionalization of the territory of the Baltic States depending on the conditions of river runoff formation which can be defined according to percentages of the river feeding sources (precipitation, snowmelt, groundwater). Longterm series of temperature (40 stations), precipitation (59 stations) and river discharge (77 stations) were used to compose ten regional series. This paper addresses: (1) variability in long-term regional series of temperature, precipitation and river discharge over a long period (1922–2007); (2) changes in regional series, comparing the periods 1991–2007 and 1931–1960 with the reference period (1961–1990), and (3) the impact of temperature and precipitation changes on regional river discharge.
Perceptual awareness of near-threshold tones scales gradually with auditory cortex activity and pupil dilation

Perceptual awareness covaries with negative-going responses in sensory cortex, but the derived concept of perceptual awareness negativity has been criticized a.o. because of its presence for undetected stimuli. To evaluate this objection, we combined magnetoencephalography, electroencephalography, and pupillometry to study the roles of sustained attention and response criterion on the auditory awareness negativity. Participants first detected distractor sounds and denied hearing task-irrelevant near-threshold tones, which evoked neither awareness negativity nor pupil dilation. These same tones evoked responses when task-relevant, stronger for hit but also present for miss trials. To explore if response criterion could explain the presence of responses for miss trials, participants rated their perception on a six-point scale. Decreasing perception ratings were associated with gradually reduced evoked responses, consistent with signal detection theory. These results support the concept of an awareness negativity that is modulated by attention, but does not exhibit a non-linear threshold mechanism.
Dissociable roles of the mPFC-to-VTA Pathway in the control of iImpulsive Action and Risk-Related Decision-Making in Roman High- And Low-Avoidance Rats

Impulsivity is a multidimensional trait associated with various psychiatric disorders including drug abuse. Impulsivity facets, such as impulsive action and risk-related decision-making (RDM), have been associated with reduced frontocortical activity and alterations in dopamine function in the ventral tegmental area (VTA). However, despite direct projections from the medial prefrontal cortex (mPFC) to the VTA, the specific role of the mPFC-to-VTA pathway in the control of impulsive behaviors remains unexplored. Here, we used Positron Emission Tomography with [18F]-Fluorodeoxyglucose to evaluate brain metabolic activity in Roman High-(RHA) and Low-avoidance (RLA) rats, which exhibit innate differences in impulsivity. Notably, we used a viral-based intersectional chemogenetic strategy to isolate, for the first time, the role of the mPFC-to-VTA pathway in controlling impulsive behaviors. We selectively activated the mPFC-to-VTA pathway in RHAs and inhibited it in RLAs, and assessed the effects on impulsive action and RDM in the rat gambling task. Our results showed that RHA rats displayed higher impulsive action, less optimal decision-making, and lower cortical activity than RLA rats at baseline. Chemogenetic activation of the mPFC-to-VTA pathway reduced impulsive action in RHAs, whereas chemogenetic inhibition had the opposite effect in RLAs. However, these manipulations did not affect RDM. Thus, by specifically and bidirectionally targeting the mPFC-to-VTA pathway in a phenotype-dependent way, we were able to revert innate patterns of impulsive action, but not RDM. Our findings suggest a dissociable role of the mPFC-to-VTA pathway in impulsive action and RDM, highlighting its potential as a target for investigating impulsivity-related disorders.
Emotional language processing in autism spectrum disorders: a systematic review

In his first description of Autism Spectrum Disorders (ASD), Kanner emphasized emotional impairments by characterizing children with ASD as indifferent to other people, self-absorbed, emotionally cold, distanced, and retracted. Thereafter, emotional impairments became regarded as part of the social impairments of ASD, and research mostly focused on understanding how individuals with ASD recognize visual expressions of emotions from faces and body postures. However, it still remains unclear how emotions are processed outside of the visual domain. This systematic review aims to fill this gap by focusing on impairments of emotional language processing in ASD. We systematically searched PubMed for papers published between 1990 and 2013 using standardized search terms. Studies show that people with ASD are able to correctly classify emotional language stimuli as emotionally positive or negative. However, processing of emotional language stimuli in ASD is associated with atypical patterns of attention and memory performance, as well as abnormal physiological and neural activity. Particularly, younger children with ASD have difficulties in acquiring and developing emotional concepts, and avoid using these in discourse. These emotional language impairments were not consistently associated with age, IQ, or level of development of language skills. We discuss how emotional language impairments fit with existing cognitive theories of ASD, such as central coherence, executive dysfunction, and weak Theory of Mind. We conclude that emotional impairments in ASD may be broader than just a mere consequence of social impairments, and should receive more attention in future research.
Increased perceptual reliability reduces membrane potential variability in cortical neurons

Uncertainty is omnipresent. While humans and other animals take uncertainty into account during decision making, it remains unclear how it is represented in cortex. To investigate the effect of stimulus reliability on uncertainty representation in cortical neurons, we analyzed single unit activity data recorded in mouse PPC, while animals performed a multisensory change detection task. We further used simulation-based inference (SBI) to infer membrane potential statistics underlying the spiking activity. Our analysis shows that stimulus changes increase spiking rate while decreasing its variability. The inferred membrane potential statistics suggest that PPC neurons decrease their membrane potential variability in response to task relevant stimuli. Furthermore, more perceptually reliable stimuli lead to a larger decrease in membrane potential variability than less reliable ones. These findings suggest that individual cortical neurons track uncertainty, providing Bayesian benefits for downstream computations.
Approximate nearest neighbor fields in video

We introduce RIANN (Ring Intersection Approximate Nearest Neighbor search), an algorithm for matching patches of a video to a set of reference patches in real-time. For each query, RIANN finds potential matches by intersecting rings around key points in appearance space. Its search complexity is reversely correlated to the amount of temporal change, making it a good fit for videos, where typically most patches change slowly with time. Experiments show that RIANN is up to two orders of magnitude faster than previous ANN methods, and is the only solution that operates in real-time. We further demonstrate how RIANN can be used for real-time video processing and provide examples for a range of real-time video applications, including colorization, denoising, and several artistic effects.
Prognosis of aortic valve sclerosis in cardiovascular mortality of patients seen at the cardiology institute of Rio Grande do Sul.

OBJECTIVE To evaluate the prognostic effect of aortic valve sclerosis on all-cause and cardiovascular mortality of patients seen at the Cardiology Institute of the Brazilian state of Rio Grande do Sul from 1996 to 2000. METHODS A historical cohort study using information from both the database of the Echocardiography Laboratory of the Cardiology Hospital and the Death Registry of Rio Grande do Sul Health Department. The evaluation was carried out from 1996 to 2000. Study endpoints were all-cause and cardiovascular mortality. RESULTS A total of 8585 patients were analyzed, 2154 (25%) of whom had aortic valve sclerosis. Mean follow-up was 41+/-6 months, and all-cause and cardiovascular deaths were 299 (3.5%) and 95 (1.1%), respectively. The group of patients with aortic valve sclerosis had more segmental cardiomyopathy, ventricular dysfunction, ventricular enlargement, and ventricular hypertrophy; yet, they did not show higher risk for all-cause or cardiovascular mortality in the multivariate analysis. CONCLUSION The presence of aortic valve sclerosis was not associated with increased risk for all-cause and cardiovascular mortality in the population studied.
Proton MR spectroscopy and MRI-volumetry in mild traumatic brain injury.

BACKGROUND AND PURPOSE More than 85% of brain traumas are classified as "mild"; MR imaging findings are minimal if any and do not correspond to clinical symptoms. Our goal, therefore, was to quantify the global decline of the neuronal marker N-acetylaspartate (NAA), as well as gray (GM) and white matter (WM) atrophy after mild traumatic brain injury (mTBI). MATERIALS AND METHODS Twenty patients (11 male, 9 female; age range, 19-57 years; median, 35 years) with mTBI (Glasgow Coma Scale score 13-15 with loss of consciousness for at least 30 seconds) and 19 age- and sex-matched control subjects were studied. Seven patients were studied within 9 days of TBI; the other 13 ranged from 1.2 months to 31.5 years (average and median of 4.6 and 1.7 years, respectively) after injury. Whole-brain NAA (WBNAA) concentration was obtained in all subjects with nonlocalizing proton MR spectroscopy. Brain volume and GM and WM fractions were segmented from T1-weighted MR imaging and normalized to the total intracranial volume, suitable for intersubject comparisons. The data were analyzed with least squares regression. RESULTS Patients with mTBI exhibited, on average, a 12% WBNAA deficit that increased with age, compared with the control subjects (p<.05). Adjusted for age effects, patients also suffered both global atrophy (-1.09%/year; P=.029) and GM atrophy (-0.89%/year; P=.042). Patients with and without visible MR imaging pathology, typically punctate foci of suspected shearing injury, were indistinguishable in both atrophy and WBNAA. CONCLUSION WBNAA detected neuronal/axonal injury beyond the minimal focal MR-visible lesions in mTBI. Combined with GM atrophy, the findings may provide further, noninvasive insight into the nature and progression of mTBI.
Sulforaphane, a Dietary Component of Broccoli/Broccoli Sprouts, Inhibits Breast Cancer Stem Cells

Purpose: The existence of cancer stem cells (CSCs) in breast cancer has profound implications for cancer prevention. In this study, we evaluated sulforaphane, a natural compound derived from broccoli/broccoli sprouts, for its efficacy to inhibit breast CSCs and its potential mechanism. Experimental Design: Aldefluor assay and mammosphere formation assay were used to evaluate the effect of sulforaphane on breast CSCs in vitro. A nonobese diabetic/severe combined immunodeficient xenograft model was used to determine whether sulforaphane could target breast CSCs in vivo, as assessed by Aldefluor assay, and tumor growth upon cell reimplantation in secondary mice. The potential mechanism was investigated using Western blotting analysis and β-catenin reporter assay. Results: Sulforaphane (1-5 μmol/L) decreased aldehyde dehydrogenase–positive cell population by 65% to 80% in human breast cancer cells (P < 0.01) and reduced the size and number of primary mammospheres by 8- to 125-fold and 45% to 75% (P < 0.01), respectively. Daily injection with 50 mg/kg sulforaphane for 2 weeks reduced aldehyde dehydrogenase–positive cells by >50% in nonobese diabetic/severe combined immunodeficient xenograft tumors (P = 0.003). Sulforaphane eliminated breast CSCs in vivo, thereby abrogating tumor growth after the reimplantation of primary tumor cells into the secondary mice (P < 0.01). Western blotting analysis and β-catenin reporter assay showed that sulforaphane downregulated the Wnt/β-catenin self-renewal pathway. Conclusions: Sulforaphane inhibits breast CSCs and downregulates the Wnt/β-catenin self-renewal pathway. These findings support the use of sulforaphane for the chemoprevention of breast cancer stem cells and warrant further clinical evaluation. Clin Cancer Res; 16(9); 2580–90. ©2010 AACR.
Multinational evidence-based recommendations on how to investigate and follow-up undifferentiated peripheral inflammatory arthritis: integrating systematic literature research and expert opinion of a broad international panel of rheumatologists in the 3E Initiative

Objective To develop evidence-based recommendations on how to investigate and follow-up undifferentiated peripheral inflammatory arthritis (UPIA). Methods 697 rheumatologists from 17 countries participated in the 3E (Evidence, Expertise, Exchange) Initiative of 2008–9 consisting of three separate rounds of discussions and modified Delphi votes. In the first round 10 clinical questions were selected. A bibliographic team systematically searched Medline, Embase, the Cochrane Library and ACR/EULAR 2007–2008 meeting abstracts. Relevant articles were reviewed for quality assessment, data extraction and synthesis. In the second round each country elaborated a set of national recommendations. Finally, multinational recommendations were formulated and agreement among the participants and the potential impact on their clinical practice was assessed. Results A total of 39 756 references were identified, of which 250 were systematically reviewed. Ten multinational key recommendations about the investigation and follow-up of UPIA were formulated. One recommendation addressed differential diagnosis and investigations prior to establishing the operational diagnosis of UPIA, seven recommendations related to the diagnostic and prognostic value of clinical and laboratory assessments in established UPIA (history and physical examination, acute phase reactants, autoantibodies, radiographs, MRI and ultrasound, genetic markers and synovial biopsy), one recommendation highlighted predictors of persistence (chronicity) and the final recommendation addressed monitoring of clinical disease activity in UPIA. Conclusions Ten recommendations on how to investigate and follow-up UPIA in the clinical setting were developed. They are evidence-based and supported by a large panel of rheumatologists, thus enhancing their validity and practical use.
JACKSTRAWS: Picking Command and Control Connections from Bot Traffic

A distinguishing characteristic of bots is their ability to establish a command and control (C&C) channel. The typical approach to build detection models for C&C traffic and to identify C&C endpoints (IP addresses and domains of C&C servers) is to execute a bot in a controlled environment and monitor its outgoing network connections. Using the bot traffic, one can then craft signatures that match C&C connections or blacklist the IP addresses or domains that the packets are sent to. Unfortunately, this process is not as easy as it seems. For example, bots often open a large number of additional connections to legitimate sites (to perform click fraud or query for the current time), and bots can deliberately produce "noise" - bogus connections that make the analysis more difficult. Thus, before one can build a model for C&C traffic or blacklist IP addresses and domains, one first has to pick the C&C connections among all the network traffic that a bot produces. In this paper, we present JACKSTRAWS, a system that accurately identifies C&C connections. To this end, we leverage host-based information that provides insights into which data is sent over each network connection as well as the ways in which a bot processes the information that it receives. More precisely, we associate with each network connection a behavior graph that captures the system calls that lead to this connection, as well as the system calls that operate on data that is returned. By using machine learning techniques and a training set of graphs that are associated with known C&C connections, we automatically extract and generalize graph templates that capture the core of different types of C&C activity. Later, we use these C&C templates to match against behavior graphs produced by other bots. Our results show that JACKSTRAWS can accurately detect C&C connections, even for novel bot families that were not used for template generation.
MODEL-ENSEMBLE TRUST-REGION POLICY OPTI-

Model-free reinforcement learning (RL) methods are succeeding in a growing number of tasks, aided by recent advances in deep learning. They tend to suffer from high sample complexity, however, which hinders their use in real-world domains. Alternatively, model-based reinforcement learning promises to reduce sample complexity, but tends to require careful tuning and to date have succeeded mainly in restrictive domains where simple models are sufficient for learning. In this paper, we analyze the behavior of vanilla model-based reinforcement learning methods when deep neural networks are used to learn both the model and the policy, and show that the learned policy tends to exploit regions where insufficient data is available for the model to be learned, causing instability in training. To overcome this issue, we propose to use an ensemble of models to maintain the model uncertainty and regularize the learning process. We further show that the use of likelihood ratio derivatives yields much more stable learning. Altogether, our approach Model-Ensemble Trust-Region Policy Optimization (ME-TRPO) significantly reduces the sample complexity compared to model-free deep RL methods on challenging continuous control benchmark tasks1.