The cardiorespiratory system of miniature frogs.

Anurans of the genus Brachycephalus are among the smallest vertebrates in the world, due to an extreme process of miniaturization. As an example of this process, Brachycephalus species show loss of fingers, loss of the eardrum and middle ear, bone fusions, and the presence of paravertebral plates and parotic plaque. However, no studies addressing the consequences of miniaturization on internal organs, such as the lungs and heart, are currently available. Thus, this study aimed to investigate if overall small body size has affected the cardiorespiratory system. We investigated, via dissections, individuals of four Brachycephaloidea species: Brachycephalus rotenbergae, B. pitanga, Eleutherodactylus johnstonei, and Ischnocnema parva. We observed that B. rotenbergae and B. pitanga present a reduction of the atrial septum and absence of the carotid body. On the other hand, despite being a member of the sister genus to Brachycephalus (both genera belong to the Brachycephalidae), individuals of Ischnocnema present a heart with a complete septum and carotid body; this is also observed in E. johnstonei (Eleutherodactylidae). We observed that B. rotenbergae and B. pitanga have thin skin with a one to two cell thick germ layer, and their lungs likely exhibit lower blood supply when compared to individuals of the E. johnstonei and I. parva species. Based on the observed structures, we suggest that in species of Brachycephalus, respiration is performed mainly through the skin, and their lungs may have a reduced respiratory function.

Two-step estimators of high-dimensional correlation matrices.

We investigate block diagonal and hierarchical nested stochastic multivariate Gaussian models by studying their sample cross-correlation matrix on high dimensions. By performing numerical simulations, we compare a filtered sample cross-correlation with the population cross-correlation matrices by using several rotationally invariant estimators (RIEs) and hierarchical clustering estimators (HCEs) under several loss functions. We show that at large but finite sample size, sample cross-correlations filtered by RIE estimators are often outperformed by HCE estimators for several of the loss functions. We also show that for block models and for hierarchically nested block models, the best determination of the filtered sample cross-correlation is achieved by introducing two-step estimators combining state-of-the-art nonlinear shrinkage models with hierarchical clustering estimators.

Implementing youth participatory action research at a continuation high school.

OBJECTIVE: To describe the process of implementing a Youth Participatory Action Research (YPAR) project at a continuation high school (CHS) and share the results of a youth-designed research project that explores barriers to high school completion. DATA SOURCES AND STUDY SETTING: YPAR was implemented across three cohorts at a CHS in the central coast of California from 2019 to 2022. Student survey respondents were enrolled CHS students between March and April 2021. STUDY DESIGN: A modified YPAR curriculum integrating research methodology and social justice topics was used to guide student-led research that resulted in a cross-sectional survey. DATA COLLECTION: Field notes maintained by the first author documented the process of implementing YPAR including the curriculum, conversations, and research decisions and procedures. A student-designed survey disseminated to all enrolled students resulted in 76 (66%) participant responses. The survey included 18 close-ended questions and three narrative responses. PRINCIPAL FINDINGS: This study details how YPAR methodologies can be translated to a high school credit recovery program. For example, student cohorts were needed to maintain continuity over time. A student-designed survey revealed that 72% of student respondents reported taking care of family members and illuminated high rates of depression symptoms. CONCLUSIONS: This study offers a detailed description of how we implemented YPAR at a credit recovery program and provides student-driven perspectives on educational reform and evaluation. This project addresses the implementation and challenges of using YPAR to engage youth in transformational resistance to rapidly study and improve CHS' policy and practice.

LSTM-GARCH Hybrid Model for the Prediction of Volatility in Cryptocurrency Portfolios.

In the present work, the volatility of the leading cryptocurrencies is predicted through generalised autoregressive conditional heteroskedasticity (GARCH) models, multilayer perceptron (MLP), long short-term memory (LSTM), and hybrid models of the type LSTM and GARCH, where parameters of the GARCH family are included as features of LSTM models. The study period covered the scenario of the World Health Organization pandemic declaration around March 2020 at hourly frequency. We have found that the different variants of deep neural network models outperform those of the GARCH family in the sense of the hetorerocedastic error, and absolute and squared error (HSE). Under the sharpe ratio, the volatility forecasting of a uniform portfolio at long horizons systematically outperforms the stablecoin Tether, which is considered here as the risk-free asset. Also, including transaction volume helps reduce the value at risk or loss probability for the uniform portfolio. Moreover, in a minimum variance portfolio, it is observed that before the pandemic declaration, a large proportion of the capital was allocated to bitcoin (BTC). In contrast, after March 2020, the portfolio is more diversified with short positions for BTC. Moreover, the MLP models give the best predictive results, although not statistically different in accuracy compared to the LSTM and LSTM-GARCH versions under the Diebold-Mariano test. In sum, MLP models outperform most stylised financial models and are less computationally expensive than more complex neural networks. Therefore, simple learning models are suggested in highly non-linear time series volatility forecasts as it is the cryptocurrency market.

Delayed sleep phase disorder during the COVID-19 pandemic and its health implications.

Circadian rhythm sleep disorders are alterations that are characterized by a shift in the sleep-wake cycle relative to day and night, such as the delayed sleep phase disorder (DSPD), which is a retard of at least 2 hours in the sleep start. Typically, the patient falls asleep after 2 a.m. and wakes up after 10 a.m. and with symptom of sleep onset insomnia. The prevalence of DSPD in young adults is 0.48%, increasing to 3.3% in adolescents. Interestingly, patients with COVID-19 infection report anxiety due to the intensive care unit lockdown and constant exposure to bright light. In addition, post-COVID patients have an increased risk of developing DSPD. For example, in adolescent post-COVID patients, the prevalence of DSPD increases to 63.3%. Patients with DSPD also have alterations in metabolic health, poor school performance, cognitive impairment, and a higher risk of developing other diseases. The objective of the present review is therefore to describe the characteristics of DSPD during the COVID-19 pandemic and to outline its possible implications for physical health (eg, metabolism) and mental health (eg, anxiety or depression).

The economic costs of insomnia comorbid with depression and anxiety disorders: an observational study at a sleep clinic in Mexico.

Significant advances documenting the costs associated with insomnia have been achieved. However, those related to insomnia associated with mood disorders remain understudied, even though insomnia is more severe in the presence of comorbid conditions such as depression and anxiety. The aim of this study was to determine the direct and indirect costs of insomnia associated with depression and anxiety disorders (DAD) from the perspective of the patient in a private healthcare system. This was an observational study of chronic insomnia associated with DAD at a private Sleep Disorders Clinic in Mexico City between 2019 and 2020. Patients were followed for up to one year. Healthcare resource utilization data were collected through clinical records. Direct and indirect costs associated with insomnia treatment were estimated through micro-costing. The estimated economic burden was projected to 5 years adjusting for inflation and discounting future costs. A deterministic sensitivity analysis was performed. The median cost of the first year of insomnia treatment associated with DAD was US$3537.57 per patient. The work productivity loss represented the highest economic burden (63.84%) followed by direct medical costs (28.32%), and the direct non-medical costs (7.85%). The estimated annual economic burden for patients treated in the private healthcare system in Mexico was US$293 million. The costs of insomnia associated with DAD at a private clinic in México were found to be high. The burden of the costs faced by these patients is substantial relative to the median income of the population. The economic costs at an individual and societal levels are substantial. Supplementary Information: The online version contains supplementary material available at 10.1007/s41105-022-00412-6.

Alteration in tyrosine phosphorylation of cardiac proteome and EGFR pathway contribute to hypertrophic cardiomyopathy.

Alterations of serine/threonine phosphorylation of the cardiac proteome are a hallmark of heart failure. However, the contribution of tyrosine phosphorylation (pTyr) to the pathogenesis of cardiac hypertrophy remains unclear. We use global mapping to discover and quantify site-specific pTyr in two cardiac hypertrophic mouse models, i.e., cardiac overexpression of ErbB2 (TgErbB2) and α myosin heavy chain R403Q (R403Q-αMyHC Tg), compared to control hearts. From this, there are significant phosphoproteomic alterations in TgErbB2 mice in right ventricular cardiomyopathy, hypertrophic cardiomyopathy (HCM), and dilated cardiomyopathy (DCM) pathways. On the other hand, R403Q-αMyHC Tg mice indicated that the EGFR1 pathway is central for cardiac hypertrophy, along with angiopoietin, ErbB, growth hormone, and chemokine signaling pathways activation. Surprisingly, most myofilament proteins have downregulation of pTyr rather than upregulation. Kinase-substrate enrichment analysis (KSEA) shows a marked downregulation of MAPK pathway activity downstream of k-Ras in TgErbB2 mice and activation of EGFR, focal adhesion, PDGFR, and actin cytoskeleton pathways. In vivo ErbB2 inhibition by AG-825 decreases cardiomyocyte disarray. Serine/threonine and tyrosine phosphoproteome confirm the above-described pathways and the effectiveness of AG-825 Treatment. Thus, altered pTyr may play a regulatory role in cardiac hypertrophic models.

Sixteen Years since the Convention on the Rights of Persons with Disabilities: What Have We Learned since Then?

Persons with disabilities have historically been subjected to discrimination and exclusion, placing them in dangerous situations of social vulnerability. The Convention on the Rights of Persons with Disabilities, passed on the 13th of December 2006, was an important legislative landmark for valuing the rights of this population group. This study involved a bibliometric analysis of 1024 research articles published in Scopus on the social, workplace, educational, and financial inclusion of persons with disabilities since the Convention. The results show an increase in scientific production, and there is also a great deal of multi-disciplinarity, which has led to important breakthroughs for the all-encompassing inclusion of this section of the population. The most productive journals, authors, institutions, and countries, as well as the international cooperation networks, are presented here. The review concludes by setting out the main themes and trends in the research.

A Method for Rapid and Reliable Molecular Detection of Drought-Response Genes in Sorghum bicolor (L.) Moench Roots.

Drought is a major environmental stress that limits growth and productivity in agricultural ecosystems limiting crop yield worldwide. Breeding crops for enhanced drought tolerance is a priority to preserve food security on the increasing world population. Recent work in Arabidopsis has shown that vascular brassinosteroid receptor BRL3 (Brassinosteroid insensitive like-3) transcriptionally controls the production of osmoprotectant metabolites that confer drought resistance without penalizing growth, offering new and exciting possibilities for biotechnological improvement of drought-resistant crops. In cereals, understanding transcriptional responses to drought is an essential step for the production of gene-edited drought-resistant cereals. In this chapter, we present a method to analyze the transcriptional responses to drought in Sorghum bicolor (L.) Moench, our cereal of choice. Among the genes we tested, we found that drought marker gene SbDHN1 has a 1000-fold increase only after 1 day of drought, bringing possibilities for the development of molecular sensors for testing drought. Overall, this analysis is useful to set up conditions of high-throughput transcriptomic analysis of drought stressed plants before drought phenotype is observed.

Parasomnias in patients with addictions-a systematic review.

Parasomnias are involuntary behaviors or subjective experiences during sleep. Our objective was to review existing information on the presence of parasomnias in patients with addictions or during treatment for addictions. Information about parasomnias related to rapid-eye-movement (REM) and non-REM sleep in patients with addictions, while using substances or in abstinence, was reviewed. A systematic search of published articles reporting parasomnias as a consequence of drug use or abuse was conducted in the PubMed and SciELO databases. The search for the studies was performed in three phases: (1) by title, (2) by abstract, and (3) by complete text. The search was performed independently by two researchers, who then compared their results from each screening phase. Seventeen articles were found. The consumption of alcohol was reported in association with arousal disorders, such as sexsomnia and sleep-related eating disorder; and REM sleep behavior disorder was reported during alcohol withdrawal. Cocaine abuse was associated with REM sleep behavior disorder with drug consumption dream content. Overall, we found that several types of parasomnias were very frequent in patients with addictions. To avoid accidents in bedroom, legal problems, and improve evolution and prognosis; must be mandatory to include security measures related to sleep period; avoid pharmacological therapy described as potential trigger factor; improve sleep hygiene; and give pharmacological and behavioral treatments for patients with these comorbid sleep disorders.

What Drives Bitcoin? An Approach from Continuous Local Transfer Entropy and Deep Learning Classification Models.

Bitcoin has attracted attention from different market participants due to unpredictable price patterns. Sometimes, the price has exhibited big jumps. Bitcoin prices have also had extreme, unexpected crashes. We test the predictive power of a wide range of determinants on bitcoins' price direction under the continuous transfer entropy approach as a feature selection criterion. Accordingly, the statistically significant assets in the sense of permutation test on the nearest neighbour estimation of local transfer entropy are used as features or explanatory variables in a deep learning classification model to predict the price direction of bitcoin. The proposed variable selection do not find significative the explanatory power of NASDAQ and Tesla. Under different scenarios and metrics, the best results are obtained using the significant drivers during the pandemic as validation. In the test, the accuracy increased in the post-pandemic scenario of July 2020 to January 2021 without drivers. In other words, our results indicate that in times of high volatility, Bitcoin seems to self-regulate and does not need additional drivers to improve the accuracy of the price direction.

Measuring information flux between social media and stock prices with Transfer Entropy.

Transfer Entropy was applied to analyze the correlations and flow of information between 200,500 tweets and 23 of the largest capitalized companies during 6 years along the period 2013-2018. The set of tweets were obtained applying a text mining algorithm and classified according to daily date and company mentioned. We proposed the construction of a Sentiment Index applying a Natural Processing Language algorithm and structuring the sentiment polarity for each data set. Bootstrapped Simulations of Transfer Entropy were performed between stock prices and Sentiment Indexes. The results of the Transfer Entropy simulations show a clear information flux between general public opinion and companies' stock prices. There is a considerable amount of information flowing from general opinion to stock prices, even between different Sentiment Indexes. Our results suggest a deep relationship between general public opinion and stock prices. This is important for trading strategies and the information release policies for each company.

Evolutionary advantage of a dissociative search mechanism in DNA mismatch repair.

Protein complexes involved in DNA mismatch repair diffuse along dsDNA as sliding clamps in order to locate a hemimethylated incision site. They have been observed to use a dissociative mechanism, in which two proteins, while continuously remaining attached to the DNA, sometimes associate into a single complex sliding on the DNA and sometimes dissociate into two independently sliding proteins. Here, we study the probability that these complexes locate a given target site via a semi-analytic, Monte Carlo calculation that tracks the association and dissociation of the sliding complexes. We compare such probabilities to those obtained using a nondissociative diffusive scan in the space of physically realistic diffusion constants, hemimethylated site distances, and total search times to determine the regions in which dissociative searching is more or less efficient than nondissociative searching. We conclude that the dissociative search mechanism is advantageous in the majority of the physically realistic parameter space, suggesting that the dissociative search mechanism confers an evolutionary advantage.

Multistage allocation problem for Mexican pension funds.

The problem of multistage allocation is solved using the Target Date Fund (TDF) strategy subject to a set of restrictions which model the latest regulatory framework of the Mexican pension system. The investment trajectory or glide-path for a representative set of 14 assets of heterogeneous characteristics is studied during a 161 quarters long horizon. The expected returns are estimated by the GARCH(1,1), EGARCH(1,1), GJR-GARCH(1,1) models, and a stationary block bootstrap model is used as a benchmark for comparison. A fixed historical covariance matrix and a multi-period estimation of DCC-GARCH(1,1) are also considered as inputs of the objective function. Forecasts are evaluated through their asymmetric dependencies as quantified by the transfer entropy measure. In general, we find very similar glide-paths so that the overall structure of the investment is maintained and does not rely on the particular forecasting model. However, the GARCH(1,1) under a fixed historical covariance matrix exhibits the highest Sharpe ratio and in this sense represents the best trade-off between wealth and risk. As expected, the initial stages of the obtained glide-paths are initially dominated by risky assets and gradually transition into bonds towards the end oof the trajectory. Overall, the methodology proposed here is computationally efficient and displays the desired properties of a TDF strategy in realistic settings.

Strategies for the prevention of carpal tunnel syndrome in the workplace: A systematic review.

Carpal Tunnel Syndrome (CTS) is one of the most frequently occurring musculoskeletal disorders of the upper limbs. Strategies for preventing CTS in the workplace include interventions such as ergonomics, education, exercise, physical therapy, and occupational health. The purpose of this study was to provide a general overview based on the review of scientific literature regarding strategies used for preventing CTS in working populations. From September to October 2018, the MEDLINE, PUBMED, EMBASE and SCOPUS (1990 to December 2017) databases were searched for evidence. The risk of bias assessment in the selected papers was evaluated using the criteria recommended by The Cochrane Handbook and the methodological quality of the included studies was evaluated using Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields. A total of 11 studies were included in the present review. A total of 1,061 subjects participated in the studies. The quality of the included studies was limited in three studies, appropriate in three studies, good in three studies, and strong in two studies. The overall results suggest a mixed level of evidence of the effect of applying strategies for preventing CTS in the workplace. The bias assessment was primarily due to incomplete result data, selective reporting of results, and blinding. In this review, interventions focused on the modification or change of accessories (keyboard, mouse, wrist rest, and the overall workstation), education in ergonomics, exercise, and physical therapies, among others, were analyzed. The findings of this review show different possibilities when choosing an intervention strategy for the workplace. However, it was challenging to analyze each of the papers owing to the heterogeneity of the studies included.

Network Analysis of Multivariate Transfer Entropy of Cryptocurrencies in Times of Turbulence.

We investigate the effects of the recent financial turbulence of 2020 on the market of cryptocurrencies taking into account the hourly price and volume of transactions from December 2019 to April 2020. The data were subdivided into time frames and analyzed the directed network generated by the estimation of the multivariate transfer entropy. The approach followed here is based on a greedy algorithm and multiple hypothesis testing. Then, we explored the clustering coefficient and the degree distributions of nodes for each subperiod. It is found the clustering coefficient increases dramatically in March and coincides with the most severe fall of the recent worldwide stock markets crash. Further, the log-likelihood in all cases bent over a power law distribution, with a higher estimated power during the period of major financial contraction. Our results suggest the financial turbulence induce a higher flow of information on the cryptocurrency market in the sense of a higher clustering coefficient and complexity of the network. Hence, the complex properties of the multivariate transfer entropy network may provide early warning signals of increasing systematic risk in turbulence times of the cryptocurrency markets.

Cardiac up-regulation of NBCe1 emerges as a beneficial consequence of voluntary wheel running in mice.

Physical training stimulates the development of physiologic cardiac hypertrophy (CH), being a key event in this process the inhibition of the Na+/H+ exchanger. However, the role of the sodium bicarbonate cotransporter (NBC) has not been explored yet under this circumstance. C57/Bl6 mice were allowed to voluntary exercise (wheel running) for five weeks. Cardiac mass was evaluated by echocardiography and histomorphometry detecting that training promoted the development of physiological CH (heart weight/tibia length ratio, mg/mm: 6.54 ± 0.20 vs 8.81 ± 0.24; interstitial collagen content, %: 3.14 ± 0.63 vs. 1.57 ± 0.27; and cross-sectional area of cardiomyocytes, µm2: 200.6 ± 8.92 vs. 281.9 ± 24.05; sedentary (Sed) and exercised (Ex) mice, respectively). The activity of the electrogenic isoform of the cardiac NBC (NBCe1) was estimated by recording intracellular pH under high potassium concentration and by measuring action potential duration (APD). NBCe1 activity was significantly increased in isolated cardiomyocytes of trained mice. Additionally, the APD was shorter and the alkalization due to high extracellular potassium-induced depolarization was greater in this group, indicating that the NBCe1 was hyperactive. These results are online with the observed myocardial up-regulation of the NBCe1 (Western Blot, %: 100 ± 13.86 vs. 202 ± 29.98; Sed vs. Ex, n = 6 each group). In addition, we detected a reduction in H2O2 production in the myocardium of trained mice. These results support that voluntary training induces the development of physiologic CH with up-regulation of the cardiac NBCe1 in mice. Furthermore, the improvement in the antioxidant capacity contributes to the beneficial cardiovascular consequences of physical training.

Exogenous Nitric Oxide Delays Plant Regeneration from Protoplast and Protonema Development in Physcomitrella patens.

Nitric oxide (NO) has been recognized as a major player in the regulation of plant physiology and development. NO regulates cell cycle progression and cell elongation in flowering plants and green algae, although the information about NO function in non-vascular plants is scarce. Here, we analyze the effect of exogenous NO on Physcomitrella patens protonema growth. We find that increasing concentrations of the NO donor sodium nitroprusside (SNP) inhibit protonema relative growth rate and cell length. To further comprehend the effect of NO on moss development, we analyze the effect of SNP 5 and 10 µM on protoplast regeneration and, furthermore, protonema formation compared with untreated plants (control). Isolated protoplasts were left to regenerate for 24 h before starting the SNP treatments that lasted five days. The results show that SNP restrains the protoplast regeneration process and the formation of new protonema cells. When SNP treatments started five days after protoplast isolation, a decrease in cell number per protonema filament was observed, indicating an inhibition of cell cycle progression. Our results show that in non-vascular plants, NO negatively regulates plant regeneration, cell cycle and cell elongation.

The physiology of plant responses to drought.

Drought alone causes more annual loss in crop yield than all pathogens combined. To adapt to moisture gradients in soil, plants alter their physiology, modify root growth and architecture, and close stomata on their aboveground segments. These tissue-specific responses modify the flux of cellular signals, resulting in early flowering or stunted growth and, often, reduced yield. Physiological and molecular analyses of the model plant Arabidopsis thaliana have identified phytohormone signaling as key for regulating the response to drought or water insufficiency. Here we discuss how engineering hormone signaling in specific cells and cellular domains can facilitate improved plant responses to drought. We explore current knowledge and future questions central to the quest to produce high-yield, drought-resistant crops.