Power spectral density and similarity analysis of COVID-19 mortality waves across countries.

Background: During the COVID-19 pandemic, the Johns Hopkins University Center for Systems Science and Engineering (CSSE) established a comprehensive database detailing daily mortality rates across countries. This dataset revealed fluctuating global mortality trends attributable to COVID-19; however, the specific differences and similarities in mortality patterns between countries remain insufficiently explored. Consequently, this study employs Fourier and similarity analyses to examine these patterns within the frequency domain, thereby offering novel insights into the dynamics of COVID-19 mortality waves across different nations. Methods: We employed the Fast Fourier transform to calculate the power spectral density (PSD) of COVID-19 mortality waves in 199 countries from January 22, 2020, to March 9, 2023. Moreover, we performed a cosine similarity analysis of these PSD patterns among all the countries. Results: We identified two dominant peaks in the grand averaged PSD: one at a frequency of 1.15 waves per year (i.e., one wave every 10.4 months) and another at 2.7 waves per year (i.e., one wave every 4.4 months). We also found a cosine similarity index distribution with a skewness of -0.54 and a global median of cosine similarity index of 0.84, thus revealing a remarkable similarity in the dominant peaks of the COVID-19 mortality waves. Conclusion: These findings could be helpful for planetary health if a future pandemic of a similar scale occurs so that effective confinement measures or other actions could be planned during these two identified periods.

Digestivamente: Mobile application for patients with irritable bowel syndrome / Digestivamente: Aplicación móvil para pacientes con Síndrome de Intestino Irritable.

Irritable Bowel Syndrome (IBS) is a chronic functional gastrointestinal disorder that represents a significant public health problem due to the impact it produces on quality of life. Recommended treatments include cognitive-behavioral therapy to address psychological factors that may exacerbate symptoms. The use of technology and particularly mobile applications has grown significantly in recent years. In Argentina, no applications have been developed for IBS. Digestivamente is a mobile application, based on cognitive-behavioral therapy developed in this country. It aims to register the psychological factors of patients with IBS, in the context of a psychotherapeutic treatment. This work describes the application and its functionalities. The use of the application is expected to allow greater adherence to treatment and an improvement in the symptoms of these patients.

El Síndrome de Intestino Irritable (SII) es un trastorno gastrointestinal funcional crónico que representa un problema en salud pública debido al impacto que produce en la calidad de vida. Los tratamientos recomendados incluyen a la terapia cognitivo-conductual para el abordaje de aquellos factores psicológicos que exacerban los síntomas. El uso de la tecnología y particularmente de aplicaciones móviles ha crecido de manera significativa durante los últimos años. En Argentina no se han desarrollado aplicaciones para SII. Digestivamente es una aplicación móvil, basada en la terapia cognitivo-conductual desarrollada en este país. Tiene por objetivo el registro de los factores psicológicos de los pacientes con SII en el contexto de un tratamiento psicoterapéutico. En el presente trabajo se describe la aplicación y sus funcionalidades. Se espera que la utilización de la aplicación permita mayor adherencia al tratamiento y una mejoría en la sintomatología de estos pacientes.

Modeling Post-Scratching Locomotion with Two Rhythm Generators and a Shared Pattern Formation.

This study aimed to present a model of post-scratching locomotion with two intermixed central pattern generator (CPG) networks, one for scratching and another for locomotion. We hypothesized that the rhythm generator layers for each CPG are different, with the condition that both CPGs share their supraspinal circuits and their motor outputs at the level of their pattern formation networks. We show that the model reproduces the post-scratching locomotion latency of 6.2 ± 3.5 s, and the mean cycle durations for scratching and post-scratching locomotion of 0.3 ± 0.09 s and 1.7 ± 0.6 s, respectively, which were observed in a previous experimental study. Our findings show how the transition of two rhythmic movements could be mediated by information exchanged between their CPG circuits through routes converging in a common pattern formation layer. This integrated organization may provide flexible and effective connectivity despite the rigidity of the anatomical connections in the spinal cord circuitry.

Tapirus bairdii-Associated Fecal Microbiome from a Critical Conservation Area: Calakmul, México.

Baird's tapir (Tapirus bairdii) is the largest native terrestrial mammal in the Neotropics, which is endangered primarily as a consequence of habitat loss and overhunting. Baird's tapir is predominantly nocturnal and exists at low densities which complicates field studies. Baird's tapir is a large-bodied herbivore that plays a key role in maintaining healthy tropical forests through seed dispersal in its feces. Studies of gut microbiome are essential and valuable to assess the health status of the host and the interaction with the environment. In this study, we collected fresh fecal samples of T. bairdii to analyze its gut microbiome during the rainy and dry seasons in the Calakmul region, which is a critical rainforest conservation area in Mexico. The results of a high-throughput 16S rDNA gene sequencing approach suggest that the fecal microbiome of Baird's tapir has no significant differences in composition among seasons. The most common phyla were Firmicutes, Bacteroidetes, Proteobacteria, Kiritimatiellaeota, and Spirochaetes. This study suggests that the stability of the fecal microbiome is related to similar feeding strategies throughout the year, and emphasizes the value of tapir in seed dispersal (and associated microbes) to the well-conserved forests of the Greater Calakmul region as biodiversity hotspots for conservation.

Digital signal processing by virtual instrumentation of a MEMS magnetic field sensor for biomedical applications.

We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing. The virtual instrument includes an algorithm to implement different configurations of infinite impulse response (IIR) filters. The PCB contains a precision instrumentation amplifier, a demodulator, a low-pass filter (LPF) and a buffer with operational amplifier. The proposed prototype is used for real-time non-invasive monitoring of magnetic flux density in the thoracic cage of rats. The response of the rat respiratory magnetogram displays a similar behavior as the rat electromyogram (EMG).

Respiratory magnetogram detected with a MEMS device.

Magnetic fields generated by the brain or the heart are very useful in clinical diagnostics. Therefore, magnetic signals produced by other organs are also of considerable interest. Here we show first evidence that thoracic muscles can produce a strong magnetic flux density during respiratory activity, that we name respiratory magnetogram. We used a small magnetometer based on microelectromechanical systems (MEMS), which was positioned inside the open thoracic cage of anaesthetized and ventilated rats. With this new MEMS sensor of about 20 nT resolution, we recorded a strong and rhythmic respiratory magnetogram of about 600 nT.