Shift in social media app usage during covid-19 lockdown and clinical anxiety symptoms: Machine learning-based ecological momentary assessment study

Background: Anxiety symptoms during public health crises are associated with adverse psychiatric outcomes and impaired health decision-making. The interaction between real-time social media use patterns and clinical anxiety during infectious disease outbreaks is underexplored. Objective: We aimed to evaluate the usage pattern of 2 types of social media apps (communication and social networking) among patients in outpatient psychiatric treatment during the COVID-19 surge and lockdown in Madrid, Spain and their short-term anxiety symptoms (7-item General Anxiety Disorder scale) at clinical follow-up. Methods: The individual-level shifts in median social media usage behavior from February 1 through May 3, 2020 were summarized using repeated measures analysis of variance that accounted for the fixed effects of the lockdown (prelockdown versus postlockdown), group (clinical anxiety group versus nonclinical anxiety group), the interaction of lockdown and group, and random effects of users. A machine learning–based approach that combined a hidden Markov model and logistic regression was applied to predict clinical anxiety (n=44) and nonclinical anxiety (n=51), based on longitudinal time-series data that comprised communication and social networking app usage (in seconds) as well as anxiety-associated clinical survey variables, including the presence of an essential worker in the household, worries about life instability, changes in social interaction frequency during the lockdown, cohabitation status, and health status. Results: Individual-level analysis of daily social media usage showed that the increase in communication app usage from prelockdown to lockdown period was significantly smaller in the clinical anxiety group than that in the nonclinical anxiety group (F1,72=3.84, P=.05). The machine learning model achieved a mean accuracy of 62.30% (SD 16%) and area under the receiver operating curve 0.70 (SD 0.19) in 10-fold cross-validation in identifying the clinical anxiety group. Conclusions: Patients who reported severe anxiety symptoms were less active in communication apps after the mandated lockdown and more engaged in social networking apps in the overall period, which suggested that there was a different pattern of digital social behavior for adapting to the crisis. Predictive modeling using digital biomarkers—passive-sensing of shifts in category-based social media app usage during the lockdown—can identify individuals at risk for psychiatric sequelae.JR was supported by the American Psychiatric Association 2021 Junior Psychiatrist Research Colloquium (NIDA R-13 grant). ES received funding from the European Union Horizon 2020 research and innovation program (Marie Sklodowska-Curie grant 813533). AA is supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (RTI2018-099655-B-I00), the Comunidad de Madrid (Y2018/TCS-4705 PRACTICO-CM), and the BBVA Foundation (Deep-DARWiN grant)

Modeling the Influence of Vitamin D Deficiency on Cigarette Smoke-Induced Emphysema

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. While the primary risk factor for COPD is cigarette smoke exposure, vitamin D deficiency has been epidemiologically implicated as a factor in the progressive development of COPD-associated emphysema. Because of difficulties inherent to studies involving multiple risk factors in the progression of COPD in humans, we developed a murine model in which to study the separate and combined effects of vitamin D deficiency and cigarette smoke exposure. During a 16-week period, mice were exposed to one of four conditions, control diet breathing room air (CD-NS), control diet with cigarette smoke exposure (CD-CSE), vitamin D deficient diet breathing room air (VDD-NS) or vitamin D deficient diet with cigarette smoke exposure (VDD-CSE). At the end of the exposure period, the lungs were examined by a pathologist and separately by morphometric analysis. In parallel experiments, mice were anesthetized for pulmonary function testing followed by sacrifice and analysis. Emphysema (determined by an increase in alveolar mean linear intercept length) was more severe in the VDD-CSE mice compared to control animals and animals exposed to VDD or CSE alone. The VDD-CSE and the CD-CSE mice had increased total lung capacity and increased static lung compliance. There was also a significant increase in the matrix metalloproteinase-9: tissue inhibitor of metalloproteinases-1 (TIMP-1) ratio in VDD-CSE mice compared with all controls. Alpha-1 antitrypsin (A1AT) expression was reduced in VDD-CSE mice as well. In summary, vitamin D deficiency, when combined with cigarette smoke exposure, seemed to accelerate the appearance of emphysemas, perhaps by virtue of an increased protease-antiprotease ratio in the combined VDD-CSE animals. These results support the value of our mouse model in the study of COPD

Regulation of BRCA1 stability through the tandem UBX domains of isoleucyl-tRNA synthetase 1

Aminoacyl-tRNA synthetases possess unique domains. In this study the structure of the vertebrate IARS1 and EARS1 complex reveals that vertebrate IARS1 protects the DNA repair factor BRCA1 from proteolytic degradation via its UBX-fold domain. Aminoacyl-tRNA synthetases (ARSs) have evolved to acquire various additional domains. These domains allow ARSs to communicate with other cellular proteins in order to promote non-translational functions. Vertebrate cytoplasmic isoleucyl-tRNA synthetases (IARS1s) have an uncharacterized unique domain, UNE-I. Here, we present the crystal structure of the chicken IARS1 UNE-I complexed with glutamyl-tRNA synthetase 1 (EARS1). UNE-I consists of tandem ubiquitin regulatory X (UBX) domains that interact with a distinct hairpin loop on EARS1 and protect its neighboring proteins in the multi-synthetase complex from degradation. Phosphomimetic mutation of the two serine residues in the hairpin loop releases IARS1 from the complex. IARS1 interacts with BRCA1 in the nucleus, regulates its stability by inhibiting ubiquitylation via the UBX domains, and controls DNA repair function

Molecular engineering of atomically dispersed Fe-N4 and Cu-N4 dual-sites in carbon nitride nanotubes for rechargeable zinc-air batteries

Metal-nitrogen-carbon (M-N-C) electrocatalysts have emerged as promising oxygen electrocatalysts with the excessive catalytically active M-Nx sites. However, M-Nx sites are not easy to be preserved at elevated temperature of pyrolysis step. Here, we show that a supercritical fluid with a fast reaction kinetics allows us to synthesize a high-purity carbon nitride nanotube filled with the iron and copper phthalocyanine nanorods as a bifunctional oxygen electrocatalyst. The well-preserved Fe-N4 and Cu-N4 sites inside of carbon nitride nanotubes are clearly observed by the systematic analysis. In addition, we investigate the synergistic effect of atomically dispersed Fe-N4 and Cu-N4 dual-atom catalysts inside the carbon nitride nanotube. The prepared sample exhibits the half-wave potential of 0.94 V for oxygen reduction reaction and the potential of 1.65 V at 10 mA cm-2 for oxygen evolution reaction. Further, we fabricate rechargeable zinc-air batteries with the dual-atomic catalyst, which show better bi-functional activities than the mixture of Pt/C and IrO2 under high depth of discharge (DOD) of -32.6% (12 h per cycle) for the zinc-air batteries. Finally, the in-situ X-ray absorption spectroscopy analysis during ORR and OER reactions revealed the catalytic origin of the FCN4-CNNT, providing a new insight into the development of efficient oxygen electrocatalysts

A natural language processing approach reveals first-person pronoun usage and non-fluency as markers of therapeutic alliance in psychotherapy

Summary: It remains elusive what language markers derived from psychotherapy sessions are indicative of therapeutic alliance, limiting our capacity to assess and provide feedback on the trusting quality of the patient-clinician relationship. To address this critical knowledge gap, we leveraged feature extraction methods from natural language processing (NLP), a subfield of artificial intelligence, to quantify pronoun and non-fluency language markers that are relevant for communicative and emotional aspects of therapeutic relationships. From twenty-eight transcripts of non-manualized psychotherapy sessions recorded in outpatient clinics, we identified therapists’ first-person pronoun usage frequency and patients’ speech transition marking relaxed interaction style as potential metrics of alliance. Behavioral data from patients who played an economic game that measures social exchange (i.e. trust game) suggested that therapists’ first-person pronoun usage may influence alliance ratings through their diminished trusting behavior toward therapists. Together, this work supports that communicative language features in patient-therapist dialogues could be markers of alliance

Functional selectivity of insulin receptor revealed by aptamer-trapped receptor structures

Activation of insulin receptor (IR) initiates a cascade of conformational changes and autophosphorylation events. Herein, we determined three structures of IR trapped by aptamers using cryo-electron microscopy. The A62 agonist aptamer selectively activates metabolic signaling. In the absence of insulin, the two A62 aptamer agonists of IR adopt an insulin-accessible arrowhead conformation by mimicking site-1/site-2' insulin coordination. Insulin binding at one site triggers conformational changes in one protomer, but this movement is blocked in the other protomer by A62 at the opposite site. A62 binding captures two unique conformations of IR with a similar stalk arrangement, which underlie Tyr1150 mono-phosphorylation (m-pY1150) and selective activation for metabolic signaling. The A43 aptamer, a positive allosteric modulator, binds at the opposite side of the insulin-binding module, and stabilizes the single insulin-bound IR structure that brings two FnIII-3 regions into closer proximity for full activation. Our results suggest that spatial proximity of the two FnIII-3 ends is important for m-pY1150, but multi-phosphorylation of IR requires additional conformational rearrangement of intracellular domains mediated by coordination between extracellular and transmembrane domains. DNA aptamers can activate insulin receptor as selective agonists or positive allosteric modulators. Here, authors determine structures of the insulin receptor bound to aptamers and provide a basis for the selective activation or allosteric regulation of insulin receptor.11Ysciescopu