Landau-Kleffner Syndrome (LKS) is a subtype of epileptic encephalopathy with spike-wave activation during sleep (EESWAS), characterized by acquired aphasia associated with the emergence of epileptiform abnormalities.

A cross-sectional descriptive study was conducted in a tertiary hospital, involving one group of children with LKS and another with EESWAS. The aim was to compare the clinical, neurophysiological, and neuropsychological aspects of both groups.

Seven patients with LKS and seven patients with EE-SWAS were analyzed; the samples were homogeneous in terms of sex, etiology, and type of electroencephalographic pattern. The mean ages of onset were 3.6 years in the LKS group, debuting with language and behavioral regression in 100% (five patients with expressive language impairment only), and 4 years in the EE-SWAS group, debuting with epilepsy in 100%, followed by behavioral regression. In 57% of the LKS group, evolving epilepsy was observed with predominantly posterior epileptic abnormalities during wakefulness. The mean duration of continuous spike-and-wave activity during sleep (SWAS) was longer in the LKS group (3.7 vs 1.8 years). Corticosteroids was the most effective treatment, with 86% of patients in both groups showing improvement. On a neuropsychological level, cognitive impairment was observed in 71% of the LKS group versus 43% in the EE-SWAS group; attention difficulties were present in all EE-SWAS patients and 85% of LKS patients.

EE-SWAS is characterized by cognitive-behavioral regression, with corticosteroids being the treatment of choice. LKS is a subtype of epilepsy within this group, with distinct features such as initial language impairment, posterior electroencephalogram (EEG) activity, and a longer duration of SWAS.

The advancement of artificial intelligence (AI), particularly generative AI, has significantly transformed the field of medicine, impacting healthcare delivery, medical education, and research. While the opportunities are substantial, the implementation of AI also raises important ethical and technical challenges, including risks related to data bias, the potential erosion of clinical skills, and concerns about information privacy.

AI has demonstrated great potential in optimizing both clinical and educational processes. However, its operation based on probabilistic prediction is inherently prone to errors and biases. Healthcare professionals must be aware of these limitations and advocate for a transparent, responsible, and safe integration of AI, while maintaining full ethical and legal responsibility for clinical decisions. It is essential to safeguard traditional clinical competencies and prioritize the use of AI in automating low-value, repetitive tasks. In biomedical research, transparency and independent validation are crucial to ensure the reproducibility of findings. Similarly, in medical education, structured training in AI is vital to enable professionals to apply these tools safely and effectively in clinical practice.

Generative AI offers a transformative potential for medicine, but its adoption must be guided by rigorous ethical standards. Comprehensive training, risk mitigation, and the preservation of core clinical skills are essential pillars for its responsible implementation. This transformation must be led by the medical profession to ensure a patient-centered approach to care.

microRNA-494 (miRNA-494) plays a key role in neuroinflammation following cerebral ischemia. We aimed to assess miRNA-494 levels as a biomarker for predicting acute ischemic stroke (AIS) severity and outcomes.

miRNA-494 levels in peripheral lymphocytes were measured using reverse transcription-quantitative polymerase chain reaction. Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to identify variables for multivariate logistic regression analysis. Univariate and multivariate logistic regression were conducted to assess the association between miRNA-494 levels and both AIS outcomes and stroke severity on admission. The primary outcome was defined as an excellent prognosis (modified Rankin Scale score of 0 or 1). The secondary outcome was milder stroke severity at admission (National Institutes of Health Stroke Scale score <15).

High miRNA-494 expression in patients aged <65 years predicted excellent AIS outcomes (odds ratio (OR) = 2.800 [1.120–7.002], p = 0.028, n = 105). In these patients, miRNA-494 levels predicted excellent outcomes for those who did not receive recanalization therapy (continuous: OR = 8.938 [2.123–62.910], p = 0.010; categorical: OR = 5.200 [1.480–20.773], p = 0.013). Elevated miRNA-494 levels were also linked to milder stroke severity (continuous: OR = 2.586 [1.024–6.533], p = 0.044; categorical variables: OR = 3.514 [1.501–8.230], p = 0.004, n = 205).

Increased miRNA-494 expression in lymphocytes predicts excellent outcomes in patients aged <65 years with AIS. Higher miRNA-494 levels are associated with milder stroke on admission.

While there is a growing body of evidence indicating a potential connection between Parkinson’s disease and diabetes mellitus, there is a lack of focus on investigating how diabetes correlates with the severity of both motor and non-motor symptoms in Parkinson’s disease.

This study examined and contrasted both motor and non-motor symptoms in patients diagnosed with Parkinson’s disease, stratified by the presence or absence of diabetes.

A total of 40 Parkinson’s disease patients, divided into two groups (with and without diabetes), were assessed using various scales, including the Movement Disorders Society – Unified Parkinson’s Disease Rating Scale, Scales for Outcomes in Parkinson’s Disease - Autonomic Dysfunction and Non-Motor Symptoms, Beck Depression Inventory, Montreal Cognitive Assessment, and Parkinson’s Disease Questionnaire-39. Demographic and clinical characteristics were also recorded. Statistical analyses included t-tests, Mann-Whitney U tests, and Fisher’s exact test.

Significant differences were observed in the motor sub-score of postural instability and gait disturbance symptoms, autonomic total scores, urinary function domain, depression scores, and quality of life in the mobility and emotional domains between the Parkinson’s disease non-diabetes, and Parkinson’s disease - diabetes groups.

Our study unveiled differences in motor and Non-Motor Symptoms among patients with Parkinson’s disease and diabetes, underscoring the influence of diabetes on manifestations of the disease.

Functional magnetic resonance imaging (fMRI) studies examining emotional memory encoding often use event-related designs with stimuli in the form of words or pictures. Prior research has suggested differential hemispheric specialization for these stimulus types, yet no meta-analysis has directly compared the neural systems involved in each.

A meta-analysis was conducted using peer-reviewed, event-related fMRI studies. The Activation Likelihood Estimation (ALE) method was applied via GingerALE software to compare brain activations associated with the encoding of affective visual stimuli presented as either words or photographs. Three contrasts were assessed: pictures > neutral + control, words > neutral + control, and overlap between both.

Picture stimuli elicited bilateral activation in the medial parahippocampus, while word stimuli produced left-lateralized activation in the lateral parahippocampus. The overlap analysis identified a shared region in the parahippocampal amygdala. All three contrasts revealed significant activations in key medial temporal lobe (MTL) regions involved in emotional memory, including the hippocampus and amygdala.

Both stimulus types engaged medial temporal networks specialized in emotional memory encoding. Word stimuli selectively activated regions lateralized to the left hemisphere, whereas picture stimuli produced bilateral activation with a leftward bias. This study provides the first meta-analytic evidence of a medial-lateral differentiation in the parahippocampal gyrus based on emotional stimulus type.

To evaluate the impact of intensive gait training on gross motor function using the pediatric exoskeleton ATLAS 2030, as well as to determine the post-intervention maintenance of effects in children with cerebral palsy (CP).

A non-randomized controlled prospective study. Thirteen children with CP participated. A program of four weekly sessions lasting 65 minutes each was implemented over six weeks. Gross motor function was assessed using the 88 items Gross Motor Function Measure (GMFM-88); physical exercise endurance was measured with the Six-Minute Walk Test (6MWT) using the device; the number of steps walked in each session and mode of use was recorded to evaluate adaptation to the activity. Three evaluations were conducted: before treatment, at the end of treatment (6 weeks), and a follow-up evaluation at 12 weeks.

The total GMFM-88 score showed significant changes at the end of the intervention (p < 0.001), which persisted at follow-up (p < 0.001). The number of steps in automatic and active modes increased significantly after the intervention (p < 0.001) and were maintained at follow-up (p = 0.001). Lastly, the 6MWT improved significantly after the intervention, with a reduction observed at follow-up (p < 0.001).

Six weeks of intensive training with ATLAS 2030 positively impacts the gross motor function of children with CP, with benefits increasing six weeks after treatment completion. Physical endurance and adaptation to the activity improve with continued use. These results support the potential of ATLAS 2030 as an intensive therapeutic strategy for this population.

No: NCT07066956. https://clinicaltrials.gov/search?cond=NCT07066956.