Early auditory deprivation has serious neurodevelopmental and cognitive repercussions largely derived from impoverished and delayed language acquisition. These conditions may be associated with early changes in brain connectivity. Vibrotactile stimulation is a sensory substitution method that allows perception and discrimination of sound and even speech. To clarify the efficacy of this approach, a vibrotactile oddball task with 700 and 900 Hz pure-tones as stimuli [counterbalanced as target (T: 20% of the total) and non-target (NT: 80%)] with simultaneous EEG recording was performed by 14 profoundly deaf and 14 normal-hearing (NH) subjects, before and after a short training period (5 one-hour sessions; in 2.5-3 weeks). A small device worn on the right index finger delivered sound-wave stimuli. The training included discrimination of pure tone frequency and duration, and more complex natural sounds. A significant P300 amplitude increase and behavioral improvement were observed in both deaf and normal subjects, with no between-group differences. However, a P3 with larger scalp distribution over parietal cortical areas and lateralized to the right was observed in the profoundly deaf. A graph theory analysis showed that brief training significantly increased fronto-central brain connectivity in deaf subjects, but not in NH subjects. Together, ERP tools and graph methods depicted the different functional brain dynamic in deaf and NH individuals, underlying the temporary engagement of the cognitive resources demanded by the task. Our findings showed that the index-fingertip somatosensory mechanoreceptors can discriminate sounds. Further studies are necessary to clarify brain connectivity dynamics associated with the performance of vibrotactile language-related discrimination tasks and the effect of lengthier training programs.

One of the fields of applied mathematics is related to model analysis. Biomedical systems are suitable candidates for this field because of their importance in life sciences including therapeutics. Here we deal with the analysis of a model recently proposed by Espinoza-Valdez et al. (2010) for the kidney vasculature developed via angiogenesis. The graph theory allows one to model quantitatively a vascular arterial tree of the kidney in sense that (1) the vertex represents a vessels bifurcation, whereas (2) each edge stands for a vessel including physiological parameters. The analytical model is based on the two processes of sprouting and splitting angiogeneses, the concentration of the vascular endothelial growth factor (VEGF), and the experimental data measurements of the rat kidneys. The fractal dimension depends on the probability of sprouting angiogenesis in the development of the arterial vascular tree of the kidney, that is, of the distribution of blood vessels in the morphology generated by the analytical model. The fractal dimension might determine whether a suitable renal vascular structure is capable of performing physiological functions under appropriate conditions. The analysis can describe the complex structures of the development vasculature in kidney.

Let P be a set of $n\ge 3$ points in general position in the plane. The edge disjointness graph $D\left(P\right)$ of P is the graph whose vertices are the $\left(\genfrac{}{}{0pt}{}{n}{2}\right)$ closed straight line segments with endpoints in P, two of which are adjacent in $D\left(P\right)$ if and only if they are disjoint. In this paper we show that the connectivity of $D\left(P\right)$ is at most $\frac{7n^2}{18}+\Theta \left(n\right)$, and that this upper bound is asymptotically tight. The proof is based on the analysis of the connectivity of $D\left(Q_n\right)$, where $Q_n$ denotes an n-point set that is almost 3-symmetric.

One of the most common and severe complications of diabetes mellitus is diabetic foot, making early detection a public health priority. Infrared thermography is a promising noninvasive technique for identifying abnormal thermal patterns associated with inflammation, neuropathy, angiopathy, and tissue damage. This technique involves acquiring infrared radiation emitted by the skin and processing it to generate thermal maps that reflect underlying physiological changes. However, the reliability of thermographic assessments depends on strict technical conditions, including sensor performance, environmental control, and reproducible measurements. Despite its advantages, the clinical adoption of thermography is limited by the absence of standardized acquisition protocols and the influence of external and physiological factors on temperature measurements. Addressing these challenges is essential to ensure the accurate interpretation and validation of results. Recent advances, such as the incorporation of artificial intelligence algorithms and the development of portable, low-cost devices, offer new opportunities to enhance thermography’s applicability in clinical settings and home monitoring.

La pandemia por el COVID-19 tomó al mundo por sorpresa. EnMéxico, al igual que en muchas partes del mundo,millones de estudiantes cambiaron alaprendizajeen línea de un día para otro. En este documento se presentan los resultados de una encuesta aplicadaa estudiantesuniversitarios con la finalidad de entender tanto su adaptación como el involucramiento en las tecnologías parala educación en línea. Participaron 1297alumnos de diversas partes de la República mexicana. Los principales resultados indican que, la actitud de los usuariosde cara al futurohacia las tecnologías, su uso y aprendizaje, se ve influidapor la sustentabilidad percibida como resultado de innovación en contraste con su preservación. Otrosresultados muestran que, aun cuando la adaptacióna la tecnologíaha sido favorable,los estudiantesextrañan el salón de clase.