Search

Abstract Background Persons with asthma may experience excessive airway narrowing due to exercise or exposure to cold air, worsening their daily functionality. Exercise has several benefits for asthma control, but it may induce airway narrowing in some persons with asthma. When combined with cold temperatures, it introduces another layer of challenges. Therefore, managing this interaction is crucial to increase the quality of life in individuals with asthma. The purpose of this study was to develop a reliable experimental protocol to assess the effects of exercise and cold air on airway narrowing in adults with asthma in a controlled and safe environment. Methods This study was a randomized cross-over study in adults with and without asthma. Participants underwent a protocol involving a 10-min seated rest, followed by a 10-min cycling on a stationary bike in different temperatures of 0, 10, or 20 $$^{\circ }$$ ∘ C. The sequence of room temperatures was randomized, and there was a 30-min interval for recovery between each temperature transition. In each temperature, to measure lung function and respiratory symptoms, oscillometry and a questionnaire were used at 0 min (baseline), after 10 min of sitting and before starting biking (pre-exercise), and after 10 min of biking (post-exercise). At each room temperature, the changes in airway mechanics and asthma symptoms among baseline, pre-exercise, and post-exercise were compared with one-way repeated measures ANOVA or Friedman Rank Test. Within each arm, cardiac and thoraco-abdominal motion respiration signals were also measured continuously using electrodes and calibrated respiratory inductance plethysmographs, respectively. Results A total of 23 persons with asthma (11 females, age: 56.3 ± 10.9 years, BMI: 27.4 ± 5.7 kg/m2) and 6 healthy subjects (3 females, age: 61.8 ± 9.1 years, BMI: 28.5 ± 3.1 kg/m2) were enrolled in the study. Cold temperature of 0 $$^{\circ }$$ ∘ C induced airway narrowing in those with and without asthma after 10 and 20 min, respectively. Exercise intervention had significant changes in airway narrowing in participants with asthma in the range of 10–20 $$^{\circ }$$ ∘ C. Our results showed that in asthma, changes in subjective respiratory symptoms were due to both cold temperatures of 0 and 10 $$^{\circ }$$ ∘ C and exercise in the 0–20 $$^{\circ }$$ ∘ C range. Respiratory symptoms were not noticed among the healthy participants. Conclusion In conclusion, our findings suggest that exposure to cold temperatures of 0 $$^{\circ }$$ ∘ C could serve as a reliable method in the experimental protocol for inducing airway narrowing in asthma. The impact of exercise on airway narrowing was more variable among participants. Understanding these triggers in the experimental protocol is essential for the successful management of asthma in future studies.

Objective: To investigate the potential of voice analysis as a prescreening or monitoring tool for type 2 diabetes mellitus (T2DM) by examining the differences in voice recordings between nondiabetic and T2DM individuals. Patients and Methods: Total 267 participants diagnosed as nondiabetic (79 women and 113 men) or T2DM (18 women and 57 men) on the basis of American Diabetes Association guidelines were recruited in India between August 30, 2021 and June 30, 2022. Using a smartphone application, participants recorded a fixed phrase up to 6 times daily for 2 weeks, resulting in 18,465 recordings. Fourteen acoustic features were extracted from each recording to analyze differences between nondiabetic and T2DM individuals and create a prediction methodology for T2DM status. Results: Significant differences were found between voice recordings of nondiabetic and T2DM men and women, both in the entire dataset and in an age-matched and body mass index (BMI [calculated as the weight in kilograms divided by the height in meters squared])-matched sample. The highest predictive accuracy was achieved by pitch (P

Chronic pain is a pathological state defined as daily pain sensation over three consecutive months. It affects up to 30% of the general population. Although significant research efforts have been made in the past 30 years, only a few and relatively low effective molecules have emerged to treat chronic pain, with a considerable translational failure rate. Most preclinical models have focused on sensory neurotransmission, with particular emphasis on the dorsal horn of the spinal cord as the first relay of nociceptive information. Beyond impaired nociceptive transmission, chronic pain is also accompanied by numerous comorbidities, such as anxiety–depressive disorders, anhedonia and motor and cognitive deficits gathered under the term “pain matrix”. The emergence of cutting-edge techniques assessing specific neuronal circuits allow in-depth studies of the connections between “pain matrix” circuits and behavioural outputs. Pain behaviours are assessed not only by reflex-induced responses but also by various or more complex behaviours in order to obtain the most complete picture of an animal’s pain state. This review summarises the latest findings on pain modulation by brain component of the pain matrix and proposes new opportunities to unravel the mechanisms of chronic pain.

Summary: In neuropathic pain, recent evidence has highlighted a sex-dependent role of the P2X4 receptor in spinal microglia in the development of tactile allodynia following nerve injury. Here, using internalization-defective P2X4mCherryIN knockin mice (P2X4KI), we demonstrate that increased cell surface expression of P2X4 induces hypersensitivity to mechanical stimulations and hyperexcitability in spinal cord neurons of both male and female naive mice. During neuropathy, both wild-type (WT) and P2X4KI mice of both sexes develop tactile allodynia accompanied by spinal neuron hyperexcitability. These responses are selectively associated with P2X4, as they are absent in global P2X4KO or myeloid-specific P2X4KO mice. We show that P2X4 is de novo expressed in reactive microglia in neuropathic WT and P2X4KI mice of both sexes and that tactile allodynia is relieved by pharmacological blockade of P2X4 or TrkB. These results show that the upregulation of P2X4 in microglia is crucial for neuropathic pain, regardless of sex.

Abstract RNA-binding proteins (RBPs) are key players regulating RNA processing and are associated with disorders ranging from cancer to neurodegeneration. Here, we present a proteomics workflow for large-scale identification of RBPs and their RNA-binding regions in the mammalian brain identifying 526 RBPs. Analysing brain tissue from males of the Huntington’s disease (HD) R6/2 mouse model uncovered differential RNA-binding of the alternative splicing regulator RBM5. Combining several omics workflows, we show that RBM5 binds differentially to transcripts enriched in pathways of neurodegeneration in R6/2 brain tissue. We further find these transcripts to undergo changes in splicing and demonstrate that RBM5 directly regulates these changes in human neurons derived from embryonic stem cells. Finally, we reveal that RBM5 interacts differently with several known huntingtin interactors and components of huntingtin aggregates. Collectively, we demonstrate the applicability of our method for capturing RNA interactor dynamics in the contexts of tissue and disease.

Objective: To investigate the use of a mathematical model of glucose homeostasis, fit to continuous glucose monitor data, as a metric of dysfunctional glycemic control. Patients and Methods: Three hundred eighty four participants recruited from 2 studies between October 2020 and June 2022 were equipped with a continuous glucose monitor, and interstitial glucose data were automatically collected for 2 weeks. The participants were assessed by a physician and diagnosed as being diabetic, prediabetic, or healthy according to the American Diabetes Association guidelines. A mathematical model of glucose homeostasis was fitted to the glucose data, and model parameter values were obtained. The participants were classified into the following 2 groups on the basis of their glucose homeostasis parameters: effective and impaired. Finally, glycemic variability metrics were compared with glucose homeostasis classification. Results: The homeostasis classification resulted in a specificity, sensitivity of individuals with prediabetes, and sensitivity of individuals with type 2 diabetes (T2D) of 0.78, 0.86, and 1.00, respectively, for women and 0.71, 0.86, and 1.00, respectively, for men. This sensitivity was similar to that of glycated hemoglobin A1c measurement (a sensitivity of 0.89 for women and 0.90 for men for prediabetes and a sensitivity of 1.00 for T2D) and superior to that of the oral glucose tolerance test (a sensitivity of 0.18 for women and 0.24 for men for prediabetes and a sensitivity of 0.75 for women and 0.86 for men for T2D). Overall, the individuals classified as impaired had increased glucose variability metrics than the individuals classified as effective (P

Abstract Background Benefit of early awake prone positioning for COVID-19 patients hospitalised in medical wards and who need oxygen therapy remains to be demonstrated. The question was considered at the time of COVID-19 pandemic to avoid overloading the intensive care units. We aimed to determine whether prone position plus usual care could reduce the rate of non-invasive ventilation (NIV) or intubation or death as compared to usual care alone. Methods In this multicentre randomised clinical trial, 268 patients were randomly assigned to awake prone position plus usual care (N = 135) or usual care alone (N = 132). The primary outcome was the proportion of patients who underwent NIV or intubation or died within 28 days. Main secondary outcomes included the rates of NIV, of intubation or death, within 28 days. Results Median time spent each day in the prone position within 72 h of randomisation was 90 min (IQR 30–133). The proportion of NIV or intubation or death within 28 days was 14.1% (19/135) in the prone position group and 12.9% (17/132) in the usual care group [odds ratio adjusted for stratification (aOR) 0.43; 95% confidence interval (CI) 0.14–1.35]. The probability of intubation, or intubation or death (secondary outcomes) was lower in the prone position group than in the usual care group (aOR 0.11; 95% CI 0.01–0.89 and aOR 0.09; 95% CI 0.01–0.76, respectively) in the whole study population and in the prespecified subgroup of patients with SpO2 ≥ 95% on inclusion (aOR 0.11; 95% CI 0.01–0.90, and aOR 0.09; 95% CI 0.03–0.27, respectively). Conclusions Awake prone position plus usual care in COVID-19 patients in medical wards did not decrease the composite outcome of need for NIV or intubation or death. Trial registration ClinicalTrials.gov Identifier: NCT04363463 . Registered 27 April 2020.

Abstract Among therapeutic proteins, cytokines and growth factors have great potential for regenerative medicine applications. However, these molecules have encountered limited clinical success due to low effectiveness and major safety concerns, highlighting the need to develop better approaches that increase efficacy and safety. Promising approaches leverage how the extracellular matrix (ECM) controls the activity of these molecules during tissue healing. Using a protein motif screening strategy, we discovered that amphiregulin possesses an exceptionally strong binding motif for ECM components. We used this motif to confer the pro-regenerative therapeutics platelet-derived growth factor-BB (PDGF-BB) and interleukin-1 receptor antagonist (IL-1Ra) a very high affinity to the ECM. In mouse models, the approach considerably extended tissue retention of the engineered therapeutics and reduced leakage in the circulation. Prolonged retention and minimal systemic diffusion of engineered PDGF-BB abolished the tumour growth-promoting adverse effect that was observed with wild-type PDGF-BB. Moreover, engineered PDGF-BB was substantially more effective at promoting diabetic wound healing and regeneration after volumetric muscle loss, compared to wild-type PDGF-BB. Finally, while local or systemic delivery of wild-type IL-1Ra showed minor effects, intramyocardial delivery of engineered IL-1Ra enhanced cardiac repair after myocardial infarction by limiting cardiomyocyte death and fibrosis. This engineering strategy highlights the key importance of exploiting interactions between ECM and therapeutic proteins for developing effective and safer regenerative therapies.

Research on pain often relies on animals, and there is always a need for more precise and more ethical tools. Here, authors present a light-activatable molecule that induces pain in freely moving animal models in a reversible, non-invasive, and spatiotemporally defined way.

El presente trabajo consiste en un estudio de la obra Carnes tolendas. Retrato escénico de una travesti, protagonizada por la galardonada actriz y escritora argentina Camila Sosa Villada y dirigida por María Palacios. Desde la perspectiva de los estudios teatrales, analizaremos la posibilidad de la obra de producir escenas de igualdad en términos de Jacques Rancière (2010; 2012). Para ello observamos cómo el espectáculo se inscribe en la crisis del personaje (Ryngaert, 2013) en virtud de que la construcción de la puesta está atravesada por múltiples textualidades que son identificadas y reconstruidas. Se profundiza en la descripción y análisis de la construcción de voces (Jolly y Moreira da Silva, 2013) y corporalidades (Fischer-Lichte, 2011) que escenifican distintos materiales, entre ellos textos dramáticos, canciones, relatos biográficos y aperturas al diálogo con la audiencia. En escena, Sosa Villada convoca numerosos cuerpos: cuerpos de varones violentos del universo familiar y policial, cuerpos de mujeres frágiles, cuerpos rotos y gastados de mujeres lorqueanas, su propio cuerpo travesti y hasta su antiguo cuerpo. La escena construye y deconstruye representaciones de cuerpos y voces en la lógica rapsoda que cose fragmentos en el teatro contemporáneo. La dramaturgia escénica abre la posibilidad de que el público experimente una puesta en escena que da voz a una historia invisibilizada y se deslumbre con las capacidades poéticas de la intérprete.

Summary: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has had a tremendous impact worldwide. Mapping virus-host interactions is critical to understand disease progression. MicroRNAs (miRNAs) are important RNA regulators, but their interaction with SARS-CoV-2 RNA was not experimentally investigated. Here, using Argonaute (AGO) cross-linking immunoprecipitation combined with RNA proximity ligation (CLEAR-CLIP), we provide unbiased mapping of SARS-CoV-2/miRNA interactions. We identified six main regions on the viral RNA bound primarily by one specific miRNA. Targeted mutagenesis and AGO1-3 knockdown demonstrated that these interactions are not critical for virus production. Moreover, we identified perturbed regulation of cellular miRNA interactions during infection, including non-compensated viral sequestration of the miR-15 family. Transcriptome analysis further showed that mRNAs targeted by this miRNA family are derepressed. This work delineates the interphase between miRNA regulation and SARS-CoV-2 infection and further contributes to deciphering the full molecular interactome of this virus.

This work addresses the dynamic modeling of a negative stiffness absorber consisting of an assembly of curved beams. Design rules are derived from the orders of magnitude of stiffness and elastic energy stored by the negative stiffness elements. Although static and dynamic performances are widely documented using equivalent spring–mass system equations of motion, this paper presents a modeling approach based on beam dynamics to predict the behavior by incorporating the generation of negative stiffness with prestressed Euler beams. The static behavior is first recalled to feed the dynamic beam model with realistic orders of magnitude. The latter is derived from the beam balance instead of the spring–mass system and aims at solving the beam problem, which encompasses more realistic phenomena compared to introducing the equivalent stiffness in the spring–mass equation of motion. The consistency of the beam modeling is confirmed by comparison with available models in the literature and finite element simulations. A mock-up is built in which beam-type components are 3D-printed. Axial loading is introduced on the curved beams to evaluate its influence on the response of the isolator, and the observed softening trend complies with the theoretical predictions.

Abstract Background Congenital heart diseases are the major cause of death in newborns, but the genetic etiology of this developmental disorder is not fully known. The conventional approach to identify the disease-causing genes focuses on screening genes that display heart-specific expression during development. However, this approach would have discounted genes that are expressed widely in other tissues but may play critical roles in heart development. Results We report an efficient pipeline of genome-wide gene discovery based on the identification of a cardiac-specific cis-regulatory element signature that points to candidate genes involved in heart development and congenital heart disease. With this pipeline, we retrieve 76% of the known cardiac developmental genes and predict 35 novel genes that previously had no known connectivity to heart development. Functional validation of these novel cardiac genes by RNAi-mediated knockdown of the conserved orthologs in Drosophila cardiac tissue reveals that disrupting the activity of 71% of these genes leads to adult mortality. Among these genes, RpL14, RpS24, and Rpn8 are associated with heart phenotypes. Conclusions Our pipeline has enabled the discovery of novel genes with roles in heart development. This workflow, which relies on screening for non-coding cis-regulatory signatures, is amenable for identifying developmental and disease genes for an organ without constraining to genes that are expressed exclusively in the organ of interest.

Context. Over the past 40 years, helioseismology has been enormously successful in the study of the solar interior. A shortcoming has been the lack of a convincing detection of the solar g modes, which are oscillations driven by gravity and are hidden in the deepest part of the solar body – its hydrogen-burning core. The detection of g modes is expected to dramatically improve our ability to model this core, the rotational characteristics of which have, until now, remained unknown. Aims. We present the identification of very low frequency g modes in the asymptotic regime and two important parameters that have long been waited for: the core rotation rate, and the asymptotic equidistant period spacing of these g modes. Methods. The GOLF instrument on board the SOHO space observatory has provided two decades of full-disk helioseismic data. The search for g modes in GOLF measurements has been extremely difficult because of solar and instrumental noise. In the present study, the p modes of the GOLF signal are analyzed differently: we search for possible collective frequency modulations that are produced by periodic changes in the deep solar structure. Such modulations provide access to only very low frequency g modes, thus allowing statistical methods to take advantage of their asymptotic properties. Results. For oscillatory periods in the range between 9 and nearly 48 h, almost 100 g modes of spherical harmonic degree 1 and more than 100 g modes of degree 2 are predicted. They are not observed individually, but when combined, they unambiguously provide their asymptotic period equidistance and rotational splittings, in excellent agreement with the requirements of the asymptotic approximations. When the period equidistance has been measured, all of the individual frequencies of each mode can be determined. Previously, p-mode helioseismology allowed the g-mode period equidistance parameter P0 to be bracketed inside a narrow range, between approximately 34 and 35 min. Here, P0 is measured to be 34 min 01 s, with a 1 s uncertainty. The previously unknown g-mode splittings have now been measured from a non-synodic reference with very high accuracy, and they imply a mean weighted rotation of 1277 ± 10 nHz (9-day period) of their kernels, resulting in a rapid rotation frequency of 1644 ± 23 nHz (period of one week) of the solar core itself, which is a factor 3.8 ± 0.1 faster than the rotation of the radiative envelope. Conclusions. The g modes are known to be the keys to a better understanding of the structure and dynamics of the solar core. Their detection with these precise parameters will certainly stimulate a new era of research in this field.

The mathematical modelling of biological systems has historically followed one of two approaches: comprehensive and minimal. In comprehensive models, the involved biological pathways are modelled independently, then brought together as an ensemble of equations that represents the system being studied, most often in the form of a large system of coupled differential equations. This approach often contains a very large number of tuneable parameters (> 100) where each describes some physical or biochemical subproperty. As a result, such models scale very poorly when assimilation of real world data is needed. Furthermore, condensing model results into simple indicators is challenging, an important difficulty in scenarios where medical diagnosis is required. In this paper, we develop a minimal model of glucose homeostasis with the potential to yield diagnostics for pre-diabetes. We model glucose homeostasis as a closed control system containing a self-feedback mechanism that describes the collective effects of the physiological components involved. The model is analyzed as a planar dynamical system, then tested and verified using data collected with continuous glucose monitors (CGMs) from healthy individuals in four separate studies. We show that, although the model has only a small number (3) of tunable parameters, their distributions are consistent across subjects and studies both for hyperglycemic and for hypoglycemic episodes.

Introduction COVID-19 is responsible of severe hypoxaemia and acute respiratory distress syndrome (ARDS). Prone positioning improves oxygenation and survival in sedated mechanically patients with ARDS not related to COVID-19. Awake prone positioning is a simple and safe technique which improves oxygenation in non-intubated COVID-19 patients. We hypothesised that early prone positioning in COVID-19 patients breathing spontaneously in medical wards could decrease the rates of intubation or need for noninvasive ventilation or death.Methods and analysis PROVID-19 is an investigator-initiated, prospective, multicentre randomised, controlled, superiority trial comparing awake prone positioning to standard of care in hypoxaemic COVID-19 patients in 20 medical wards in France and Monaco. Patients are randomised to receive either awake prone position plus usual care or usual care alone with stratification on centres, body mass index and severity of hypoxaemia.The study objective is to compare the rate of treatment failure defined as a composite endpoint comprising the need for non-invasive ventilation (at two pressure levels) or for intubation or death, between the intervention group (awake prone position plus usual care) and the usual care (usual care alone) group at 28 days.Ethics and dissemination The protocol and amendments have been approved by the ethics committees (Comité de protection des personnes Ouest VI, France, no 1279 HPS2 and Comité Consultatif d’Ethique en matière de Recherche Biomédicale, Monaco, no 2020.8894 AP/jv), and patients are included after written informed consent. The results will be submitted for publication in peer-reviewed journals.Trial registration number NCT04363463.

This research examines whether the mere presence of asking about gender pronouns (e.g., she/her, he/him, they/them, and ze/zir) in a survey enhances participants’ attitudes and satisfaction of answering the questions. A large sample (N = 1,511) of heterosexual, cisgender, and LGBTQIA+ participants across the United States (US) were surveyed an online “personality test” (as a deception), with the real purpose of examining whether asking a pronoun question enhanced their perceptions of the survey. Three demographic groups were included: (i) heterosexual–cisgender (n = 503), (ii) gay–cisgender (n = 509), and (iii) genderqueer (trans, non-conforming, other, n = 499). Half of each group were randomly given either a survey that included a gender pronoun question (test) or not (control), and then all rated their perceptions of the survey questions. For participants who identified as heterosexual or gay, no major differences were found between survey conditions. However, participants who identified as genderqueer experienced significant increases of satisfaction, comfort level, and perceived relevance of the questions when given a survey that asked their gender pronouns versus the survey that did not. These findings have implications for any surveys that ask about personal demographics, and suggest that any form of written communication should include clarity about gender pronouns.

Abstract Background Few studies have evaluated muscle strength in COVID-19 ICU survivors. We aimed to report the incidence of limb and respiratory muscle weakness in COVID-19 ICU survivors. Method We performed a cross sectional study in two ICU tertiary Hospital Settings. COVID-19 ICU survivors were screened and respiratory and limb muscle strength were measured at the time of extubation. An ICU mobility scale was performed at ICU discharge and walking capacity was self-evaluated by patients 30 days after weaning from mechanical ventilation. Results Twenty-three patients were included. Sixteen (69%) had limb muscle weakness and 6 (26%) had overlap limb and respiratory muscle weakness. Amount of physiotherapy was not associated with muscle strength. 44% of patients with limb weakness were unable to walk 100 m 30 days after weaning. Conclusion The large majority of COVID-19 ICU survivors developed ICU acquired limb muscle weakness. 44% of patients with limb weakness still had severely limited function one-month post weaning.

BackgroundIt has been suggested that Bayesian dosing apps can assist in the therapeutic drug monitoring of patients receiving vancomycin. Unfortunately, Bayesian dosing tools are often unaffordable to resource-limited hospitals. Our aim was to improve vancomycin dosing in adults. We created a free and open-source dose adjustment app, VancoCalc, which uses Bayesian inference to aid clinicians in dosing and monitoring of vancomycin. ObjectiveThe aim of this paper is to describe the design, development, usability, and evaluation of a free open-source Bayesian vancomycin dosing app, VancoCalc. MethodsThe app build and model fitting process were described. Previously published pharmacokinetic models were used as priors. The ability of the app to predict vancomycin concentrations was performed using a small data set comprising of 52 patients, aged 18 years and over, who received at least 1 dose of intravenous vancomycin and had at least 2 vancomycin concentrations drawn between July 2018 and January 2021 at Lakeridge Health Corporation Ontario, Canada. With these estimated and actual concentrations, median prediction error (bias), median absolute error (accuracy), and root mean square error (precision) were calculated to evaluate the accuracy of the Bayesian estimated pharmacokinetic parameters. ResultsA total of 52 unique patients’ initial vancomycin concentrations were used to predict subsequent concentration; 104 total vancomycin concentrations were assessed. The median prediction error was –0.600 ug/mL (IQR –3.06, 2.95), the median absolute error was 3.05 ug/mL (IQR 1.44, 4.50), and the root mean square error was 5.34. ConclusionsWe described a free, open-source Bayesian vancomycin dosing calculator based on revisions of currently available calculators. Based on this small retrospective preliminary sample of patients, the app offers reasonable accuracy and bias, which may be used in everyday practice. By offering this free, open-source app, further prospective validation could be implemented in the near future.

BackgroundIn December 2019, the COVID-19 outbreak started in China and rapidly spread around the world. Many studies have been conducted to understand the clinical characteristics of COVID-19, and recently postinfection sequelae of this disease have begun to be investigated. However, there is little consensus on the longitudinal changes of lasting physical or psychological symptoms from prior COVID-19 infection. ObjectiveThis study aims to investigate and analyze public social media data from Reddit to understand the longitudinal impact of COVID-19 symptoms before and after recovery from COVID-19. MethodsWe collected 22,890 Reddit posts that were generated by 14,401 authors from March 14 to December 16, 2020. Using active learning and intensive manual inspection, 292 (2.03%) active authors, who were infected by COVID-19 and frequently reported disease progress on Reddit, along with their 2213 (9.67%) longitudinal posts, were identified. Machine learning tools to extract biomedical information were applied to identify COVID-19 symptoms mentioned in the Reddit posts. We then examined longitudinal changes in individual physiological and psychological characteristics before and after recovery from COVID-19 infection. ResultsIn total, 58 physiological and 3 psychological symptoms were identified in social media before and after recovery from COVID-19 infection. From the analyses, we found that symptoms of patients with COVID-19 lasted 2.5 months. On average, symptoms appeared around a month before recovery and remained for 1.5 months after recovery. Well-known COVID-19 symptoms, such as fever, cough, and chest congestion, appeared relatively earlier in patient journeys and were frequently observed before recovery from COVID-19. Meanwhile, mental discomfort or distress, such as brain fog or stress, fatigue, and manifestations on toes or fingers, were frequently mentioned after recovery and remained as intermediate- and longer-term sequelae. ConclusionsIn this study, we showed the dynamic changes in COVID-19 symptoms during the infection and recovery phases of the disease. Our findings suggest the feasibility of using social media data for investigating disease states and understanding the evolution of the physiological and psychological characteristics of COVID-19 infection over time.

Abstract According to medical guidelines, the distinction between “healthy” and “unhealthy” patients is commonly based on single, discrete values taken at an isolated point in time (e.g., blood pressure or core temperature). Perhaps a more robust and insightful diagnosis can be obtained by studying the functional interdependence of such indicators and the homeostasis that controls them. This requires quasi-continuous measurements and a procedure to map the data onto a parsimonious control model with a degree of universality. The current research illustrates this approach using glucose homeostasis as a target. Data were obtained from 41 healthy subjects wearing over-the-counter glucose monitors, and projected onto a simple proportional–integral (PI) controller, widely used in engineering applications. The indicators quantifying the control function are clustered for the great majority of subjects, while a few outliers exhibit less responsive homeostasis. Practical implications for healthcare and education are further discussed.

Digital therapeutics is a newly described concept in healthcare which is proposed to change patient behavior and treat medical conditions using a variety of digital technologies. However, the term is rarely defined with criteria that make it distinct from simply digitizedversions of traditional therapeutics. Our objective is to describe a more valuable characteristic of digital therapeutics, which is distinct from traditional medicine or therapy: that is, the utilization of artificial intelligence and machine learning systems to monitor and predict individual patient symptom data in an adaptive clinical feedback loop via digital biomarkers to provide a precision medicine approach to healthcare. Artificial intelligence platforms can learn and predict effective interventions for individuals using a multitude of personal variables to provide a customized and more tailored therapy regimen. Digital therapeutics coupled with artificial intelligence and machine learning also allows more effective clinical observations and management at the population level for various health conditions and cohorts. This vital differentiation of digital therapeutics compared to other forms of therapeutics enables a more personalized form of healthcare that actively adapts to patients’ individual clinical needs, goals, and lifestyles. Importantly, these characteristics are what needs to be emphasized to patients, physicians, and policy makers to advance the entire field of digital healthcare.

The current study was a replication and comparison of our previous research which examined the comprehension accuracy of popular intelligent virtual assistants, including Amazon Alexa, Google Assistant, and Apple Siri for recognizing the generic and brand names of the top 50 most dispensed medications in the United States. Using the exact same voice recordings from 2019, audio clips of 46 participants were played back to each device in 2021. Google Assistant achieved the highest comprehension accuracy for both brand medication names (86.0%) and generic medication names (84.3%), followed by Apple Siri (brand names = 78.4%, generic names = 75.0%), and the lowest accuracy by Amazon Alexa (brand names 64.2%, generic names = 66.7%). These findings represent the same trend of results as our previous research, but reveal significant increases of ~10–24% in performance for Amazon Alexa and Apple Siri over the past 2 years. This indicates that the artificial intelligence software algorithms have improved to better recognize the speech characteristics of complex medication names, which has important implications for telemedicine and digital healthcare services.

Many naturally occurring elastomers are intrinsically disordered proteins (IDPs) built up of repeating units, and they can demonstrate two types of thermoresponsive phase behavior. Systems characterized by lower critical solution temperatures (LCSTs) undergo phase separation above the LCST, whereas systems characterized by upper critical solution temperatures (UCSTs) undergo phase separation below the UCST. There is congruence between thermoresponsive coil–globule transitions and phase behavior, whereby the theta temperatures above or below which the IDPs transition from coils to globules serve as useful proxies for the LCST/UCST values. This implies that one can design sequences with desired values for the theta temperature with either increasing or decreasing radii of gyration above the theta temperature. Here, we show that the Monte Carlo simulations performed in the so-called intrinsic solvation (IS) limit version of the temperature dependent self-Assembly of Biomolecules Studied by an Implicit, Novel, and Tunable Hamiltonian (ABSINTH) implicit solvation model yield a useful heuristic for discriminating between sequences with known LCST and UCST phase behavior. Accordingly, we use this heuristic in a supervised approach, integrate it with a genetic algorithm, combine this with IS limit simulations, and demonstrate that novel sequences can be designed with LCST phase behavior. These calculations are aided by direct estimates of temperature dependent free energies of solvation for model compounds that are derived using the polarizable atomic multipole optimized energetics for biomolecular applications forcefield. To demonstrate the validity of our designs, we calculate coil–globule transition profiles using the full ABSINTH model and combine these with Gaussian cluster theory calculations to establish the LCST phase behavior of designed IDPs.

Protein interaction is critical molecular regulatory activity underlining cellular functions and precise cell fate choices. Using TWIST1 BioID-proximity-labeling and network propagation analyses, we discovered and characterized a TWIST-chromatin regulatory module (TWIST1-CRM) in the neural crest cells (NCC). Combinatorial perturbation of core members of TWIST1-CRM: TWIST1, CHD7, CHD8, and WHSC1 in cell models and mouse embryos revealed that loss of the function of the regulatory module resulted in abnormal differentiation of NCCs and compromised craniofacial tissue patterning. Following NCC delamination, low level of TWIST1-CRM activity is instrumental to stabilize the early NCC signatures and migratory potential by repressing the neural stem cell programs. High level of TWIST1 module activity at later phases commits the cells to the ectomesenchyme. Our study further revealed the functional interdependency of TWIST1 and potential neurocristopathy factors in NCC development.