Buenos Aires Institute of Technology

In a world where social interaction presents challenges for children with Autism Spectrum Disorder (ASD), robots are stepping in as allies in emotional learning. This study examined how affective interactions with a humanoid robot elicited physiological responses in children with ASD, using electrodermal activity (EDA) and heart rate variability (HRV) as key indicators of emotional arousal. The objectives were to identify emotionally salient moments during human-robot interaction, assess whether certain individual characteristics - such as age or ASD severity - modulate autonomic responses, and evaluate the usefulness of wearable devices for real-time monitoring. Thirteen children participated in structured sessions involving a range of social, cognitive, and motor tasks alongside the robot Pepper. The results showed that the hugging phase (HS2) often generated greater autonomic reactivity in children, especially among younger children and those with higher levels of restlessness or a higher level of ASD. Children with level 2 ASD displayed higher sympathetic activation compared to level 1 participants, who showed more HRV stability. Age also played a role, as younger children demonstrated lower autonomic regulation. These findings highlight the relevance of physiological monitoring in detecting emotional dysregulation and tailoring robot-assisted therapy. Future developments will explore adaptive systems capable of adjusting interventions in real time to better support each child's unique needs.

RationaleDiaphragm neurostimulation-assisted ventilation (DNAV) can improve cardiopulmonary function during passive mechanical ventilation. However, this technique requires a reliable method to monitor and titrate diaphragmatic loading to avoid both insufficient and excessive diaphragmatic stimulation.ObjectiveTo establish whether the reduction in airway pressure-time product (ΔPTPaw) obtained during diaphragm neurostimulation in assist control volume-controlled mode accurately quantifies the magnitude of respiratory muscle effort elicited by neurostimulation.MethodsThis was a secondary analysis of the STIMULUS trial. Diaphragm neurostimulation was titrated across four levels targeting progressive occlusion pressures of 0, − 5, − 10, and − 15 cm H₂O at two PEEP levels. At each level, airway, esophageal, and gastric pressures were recorded to compute transdiaphragmatic pressure-time product (PTPdi), respiratory muscles pressure-time product (PTPmus), and ΔPTPaw, defined as the difference in airway pressure-time product between non-stimulated and stimulated breaths. Linear mixed-effects models, Bland–Altman analyses, and receiver operating characteristic (ROC) curves were used to assess agreement and discriminative ability.Measurements and main resultsTwelve patients contributed 494 high-quality respiratory cycles (63% of recorded cycles). Valid Pdi data were available in nine patients. Increasing neurostimulation was associated with higher PTPdi and PTPmus and a corresponding reduction in PTPaw. ΔPTPaw was correlated with both PTPdi (R² = 0.82) and PTPmus (R² = 0.92), with good agreement observed (limits: − 4 to 44 cm H₂O·s/min for PTPdi, and − 5 to 39 cm H₂O·s/min for PTPmus). ΔPTPaw demonstrated excellent discrimination for inadequate (area under receiver operating characteristic curve, AUROC ≥ 0.94) and excessive (AUROC ≥ 0.86) diaphragmatic effort.ConclusionsΔPTPaw is a reliable, non-invasive surrogate for monitoring diaphragm loading during DNAV under assist-controlled volume-controlled mode and may guide neurostimulation titration in mechanically ventilated patients.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13054-025-05810-z.

BackgroundThe oscillatory nature of slow waves during non‐rapid eye movement (NREM) sleep has recently been proposed as crucial for the glymphatic system, facilitating the clearance of metabolic waste from the brain. While aging‐related reductions in slow wave quantity and amplitude are well‐documented and linked to this cleansing function, we propose that the rhythmic dynamics in which slow waves occur may also play a critical role.MethodThus, we introduce a novel classification of slow waves based on their temporal dynamics, categorizing them into isolated waves and oscillation trains. Using overnight EEG recordings from young and elderly adults, we compared the proportions of these wave types. Additionally, we analyzed train composition, including the proportion of slow waves that initiate a train (lead waves) and the lengths of the oscillation trains (number of consecutive slow waves initiated by one lead wave).ResultOur results revealed that elderly adults exhibited a higher prevalence of isolated waves and a lower proportion of oscillation trains. Moreover, while elderly adults showed a higher proportion of lead waves, their oscillation trains were significantly shorter compared to those of young adults.ConclusionWe propose that natural aging may result in a less oscillatory brain state, characterized by a diminished ability to produce sustained, periodic oscillations. This diminished rhythmicity could impair cerebrospinal fluid pulsation, potentially reducing the brain's ability to efficiently clear pathogenic substances during sleep. Given the established link between impaired glymphatic clearance and neurodegenerative diseases such as Alzheimer's, this diminished capacity to sustain slow wave trains may contribute to age‐related decline in neurological functioning.

BackgroundWith increasing life expectancy, aging‐related neurocognitive challenges are becoming more prevalent worldwide. A continuum of severity, from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and Alzheimer's disease dementia (ADD), is measurable through cognitive and neuroimaging assessments. However, these approaches are costly, subject to scheduling delays, and reliant on specialized personnel or resources, which are scarce in many regions. Automated speech and language analysis (ASLA) offers an affordable, scalable solution for detecting neurocognitive compromise in underserved areas. Yet, no prior study has employed ASLA to predict neuropsychological and brain measures across this continuum in Spanish‐speaking Latinos. Our study addresses this gap.MethodWe recruited 150 Chilean individuals with diverse cognitive profiles: 17 healthy controls, 55 with SCD, 57 with MCI, and 21 with ADD. Participants completed 1‐minute phonemic and semantic fluency tasks, alongside cognitive (Addenbrooke's Cognitive Examination‐III [ACE‐III], Montreal Cognitive Assessment [MoCA]) and executive function (INECO Frontal Screening [IFS]) tests and MRI scans. Machine learning models were trained with word‐property and speech‐timing features from fluency responses (both separate and combined), derived via the TELL app, to predict cognitive test outcomes, total gray matter (GM) and white matter volumes, hippocampal GM volume, and a mask encompassing ADD‐sensitive regions. The best regressors were selected based on the 95% confidence intervals of R2 scores. Pearson's partial correlations between actual and predicted values were computed, controlling for age, sex, and education (and MoCA scores for brain‐related measures). Analyses were repeated for each fluency task, their combination, and their average.ResultsSignificant partial Pearson correlations were obtained for ACE‐III (r = .55, p < .001), MoCA (r = .39, p < .001), and IFS (r = .31, p = .001) scores, as well as for normalized GM volume (r = .34, p = .006). All results correspond to word‐property features, with combined fluency tasks.ConclusionA fully automated, multivariate pipeline captures cognitive and MRI measures of brain health based on brief fluency tasks. Unlike gold‐standard tests, this approach is examiner‐independent, objective, time‐efficient, and affordable. This approach represents a scalable resource to favor equity in the global fight against dementia and cognitive decline.

We study photonic meta-atoms in media with a zero-nonlinearity wavelength (ZNW). We show that the Raman self-frequency shift experienced by these bound compounds, formed by an intense soliton and a trapped weak pulse, is strongly dependent on the actual position of the ZNW. Moreover, the amount of trapped energy is shown to depend on the position of the ZNW, causing these two-color compounds to be unstable whenever the ZNW lies close to the weak pulse wavelength. Finally, simulation results obtained with the photon-conserving Generalized Nonlinear Schrödinger Equation (pcGNLSE) are shown to differ significantly from those obtained with the conventional GNLSE. Most strikingly, whenever the ZNW lies in between the soliton and weak pulse wavelengths, the pcGNLSE predicts that no stable compounds can be formed, contrary to the GNLSE.

Eyewitness misidentifications are a major cause of wrongful convictions. While most research has focused on the role of sleep in memory encoding and consolidation, recent findings suggest that non-REM sleep may also enhance retrieval processes by restoring executive and monitoring functions. Here, we investigated whether a short nap before retrieval could improve performance in forensic memory tasks. Participants watched an aversive video of a robbery and, after 24 h, either took a 60-minute nap (Sleep group) or stayed awake (Wake group) before completing a series of memory tasks, including face recognition (target-present and target-absent lineups), free recall, context recognition, and temporal order. A nap prior to retrieval selectively reduced false identifications in target-absent lineups, increasing correct rejections without affecting performance in target-present trials. Temporal order memory also improved in the Sleep group, whereas no significant differences were observed in free recall or context recognition. Confidence-accuracy calibration was stronger in the Sleep group, particularly when the perpetrator was absent. These findings suggest that a brief nap prior to memory retrieval may improve the accuracy of eyewitness decisions by enhancing metacognitive monitoring and temporal discrimination, offering a simple, non-invasive intervention to reduce errors in forensic settings.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-20471-2.

The star K2-19 hosts a pair of Neptunian planets deep inside the 3:2 resonance. They induce strong transit-timing variations with two incommensurate frequencies. Previous photodynamical modeling of 3.3 years of transit and radial velocity data produced mass estimates of $32.4± 1.7,M_⊕$ and $10.8± 0.6,M_⊕$ for planets b and c, respectively, and corresponding eccentricity estimates of $0.20± 0.03$ and $0.21± 0.03$. These high eccentricities raise questions about the formation origin of the system, and this motivated us to extend the observing baseline in an attempt to better constrain their values. We present a photodynamical analysis of 10 years of transit data that confirms the previous mass estimates ($30.8± 1.3,M_⊕$ and $11.1± 0.4,M_⊕$), but reduces the median eccentricities to $0.04± 0.02$ and $0.07± 0.02$ for b and c, respectively. These values are more consistent with standard formation models, but still involve nonzero free eccentricity. The previously reported high eccentricities appear to be due to a single transit for which measurements taken at twilight mimicked ingress. This resulted in a 12-minute error in the midtransit time. The data that covered 1.3 and 5 so-called super and resonant periods were used to match a Fourier analysis of the transit-timing variation signal with simple analytic expressions for the frequencies and amplitudes to obtain planet mass estimates within 2% of the median photodynamical values, regardless of the eccentricities. Theoretical details of the analysis are presented in a companion paper. Additionally, we identified a possible planet candidate situated exterior to the b–c pair. Finally, in contrast to a previous study, our internal structure modeling of K2-19,b yields a metal mass fraction that is consistent with core accretion.

A few years ago, the 2-hydroxy-4´-methoxy dibenzoylmethane (DBM11) molecule was synthesized and studied as a replacement for avobenzone (AVB, butyl methoxydibenzoylmethane) because of the latter's instability under UVA radiation. These studies, conducted in absolute ethanol with an estimated UV irradiance of 8,56 mW/cm2, demonstrated almost zero decomposition of DBM11. Thus, it is a promising candidate for use as a UVA chemical filter. However, further studies must be conducted to verify its photostability once formulated into an emulsion and to establish its toxicological profile. The first aim of this work was to scale up the synthesis of DBM11 to allow its formulation into an emulsion, which is required for the evaluation of its photostability under standardized UV irradiation conditions (close to ISO 24443), as required for sunscreen testing in the cosmetic industry. Additionally, invitro phototoxicity assessments were conducted, with slight modifications to improve reproducibility, in accordance with OECD guidelines. These results demonstrate that DBM11 exhibits promising photostability and a favourable toxicological profile, making it a potential candidate for use as a UVA filter.

The control of glutamate concentration in the synaptic gap is crucial for neuronal communication, preventing excitotoxicity from excessive receptor activation. There are specific transporters in the brain that are responsible for maintaining glutamate homeostasis. The glutamate transporter GLT-1 is mainly localized in astrocytes, and its expression is particularly abundant in the hippocampus. This study explored the role of GLT-1 in memory phases using contextual fear conditioning (CFC) and inhibitory avoidance (IA) tasks. Dihydrokainic acid (DHK), a selective GLT-1 inhibitor, was injected into the dorsal hippocampus of female rats at different times around aversive learning. DHK administration 2 h after weak CFC or IA training sessions improved long-term memory (LTM) formation. However, DHK administration around strong training sessions did not affect consolidation in either task. Moreover, the DHK application 15 min before test sessions impaired short-term memory (STM) and LTM expression in both tasks. In contrast, the antibiotic ceftriaxone (CFT), which increases GLT-1 expression, did not affect the expression of aversive memories. This study highlights the critical role of hippocampal astrocytic glutamate uptake in the formation and expression of aversive memories.