Background Exposure to trauma reminders has been considered imperative in psychotherapy for posttraumatic stress disorder (PTSD). No treatment benefits all patients, however. We tested Interpersonal Psychotherapy, which has demonstrated antidepressant efficacy and showed promise in pilot PTSD research, as a non-exposure-based, non-cognitive behavioral PTSD treatment. Methods A randomized, fourteen-week trial compared Interpersonal Psychotherapy; Prolonged Exposure, an exposure-based exemplar; and Relaxation Therapy, an active control psychotherapy. Subjects were 110 unmedicated patients having DSM-IV chronic PTSD and Clinician-Administered PTSD Scale (CAPS) score >50. Randomization stratified for comorbid major depression. We hypothesized Interpersonal Psychotherapy would be no more than minimally inferior (CAPS difference <12.5 points) to Prolonged Exposure. Results All therapies had large within-group pre/post effect sizes (d=1.32–1.88). Response rates (>30% CAPS improvement) were: Interpersonal Psychotherapy 63%, Prolonged Exposure 47%, Relaxation Therapy 38% (n.s.). Interpersonal psychotherapy and Prolonged Exposure CAPS outcome differed by 5.5 points (n.s.); the null hypothesis of more than minimal Interpersonal Psychotherapy inferiority was rejected (p=0.035). Patients with comorbid major depression dropped out from Prolonged Exposure nine times more than non-depressed Prolonged Exposure patients. Interpersonal Psychotherapy and Prolonged Exposure improved quality of life and social functioning more than Relaxation Therapy. Conclusions This first controlled study of individual Interpersonal Psychotherapy for PTSD demonstrated non-inferiority to the “gold standard” PTSD treatment. Interpersonal Psychotherapy had (non-significantly) lower attrition and higher response rates than Prolonged Exposure. Contradicting a widespread clinical belief, PTSD treatment may not require cognitive behavioral exposure to trauma reminders. Moreover, as differential therapeutics, patients with comorbid major depression may fare better in Interpersonal Psychotherapy than Prolonged Exposure.

Abscisic acid (ABA) is a hormone that modulates a variety of agronomically important growth and developmental processes and various stresses responses, but its signal transduction pathways remain poorly understood. ROP10, a member of ROP small GTPases in Arabidopsis (Arabidopsis thaliana), is a plasma membrane-associated protein specifically involved in negative regulation of ABA responses. To dissect the ROP10-mediated ABA signaling, we carried out transcriptome analysis using the Arabidopsis full-genome chip. Our analysis revealed a total of 262 and 125 genes that were, respectively, up-and downregulated ($2-fold cutoff) by 1 mM ABA in wild type (Wassilewskija [Ws]); 42 up-regulated and 38 down-regulated genes have not been identified in other studies. Consistent with the nonpleiotropic phenotypes of rop10-1, only three genes were altered in rop10-1 in the absence of ABA treatment. In response to 1 mM ABA, 341 and 127 genes were, respectively, activated and repressed in rop10-1. Interestingly, a particular subset of 21 genes that were not altered by 1 mM ABA in Ws but only activated in rop10-1 was identified. Reverse transcription-polymerase chain reaction analysis revealed the existence of three distinct categories of ABA dose-response patterns. One novel category is characterized by their ABA unresponsiveness in Ws and activation in rop10-1 at 1 mM but not 10 and 100 mM of ABA. This indicates that ROP10 gates the expression of genes that are specific to low concentrations of ABA. Furthermore, almost all of these 21 genes are known to be highly induced by various biotic and abiotic stresses. Consequently, we found that rop10-1 enhanced the sensitivity of seed germination inhibition to mannitol and sodium chloride. Our results suggest that ROP10 negatively regulates ABA responses by specifically and differentially modulating the ABA sensitivity of a subset of genes including protein kinases and zinc-finger family proteins.Abscisic acid (ABA) is a hormone that modulates a variety of agronomically important growth and developmental processes (such as the synthesis of seed storage proteins and lipids, and the control of seed maturation, dormancy, and germination) and responses to various stresses, including drought, salt, and cold (for a recent comprehensive review, see Finkelstein et al., 2002). Despite significant progress in the understanding of ABA biosynthesis (Xiong and Zhu, 2003), ABA perception and signal transduction pathways remain poorly defined (Finkelstein et al., 2002;Himmelbach et al., 2003). Since it was compiled three years ago that nearly 50 genes in Arabidopsis (Arabidopsis thaliana) alone can directly or indirectly affect ABA responses (Finkelstein et al., 2002), novel candidate ABA signaling genes have been identified through either forward or reverse genetic approaches. Together, these include genes encoding intracellular signaling proteins, such as heterotrimeric and monomeric GTP-binding proteins; G-protein-coupled receptors; (receptor-like) protein kinases and protein phosphatases; transc...

Capillary evaporation in nanoscale conduits is an efficient heat/mass transfer strategy that has been widely utilized by both nature and mankind. Despite its broad impact, the ultimate transport limits of capillary evaporation in nanoscale conduits, governed by the evaporation/condensation kinetics at the liquid-vapor interface, have remained poorly understood. Here we report experimental study of the kinetic limits of water capillary evaporation in two dimensional nanochannels using a novel hybrid channel design. Our results show that the kinetic-limited evaporation fluxes break down the limits predicated by the classical Hertz-Knudsen equation by an order of magnitude, reaching values up to 37.5 mm/s with corresponding heat fluxes up to 8500 W/cm. The measured evaporation flux increases with decreasing channel height and relative humidity but decreases as the channel temperature decreases. Our findings have implications for further understanding evaporation at the nanoscale and developing capillary evaporation-based technologies for both energy- and bio-related applications.

With the outbreak of novel coronavirus in 2019, most universities changed from traditional offline teaching to online teaching, which brought about a large amount of problems, including teachers’ physical and mental problems. Because of teaching on the computer screen for a long period of time, the teacher lacks communication and can act casually. With long-term accumulation, the problem of teachers’ job burnout has become increasingly serious. The main purpose of this study was to examine the influence of professional identity on job burnout during the period of the novel coronavirus. At the same time, this study also discussed the moderating effect of job satisfaction on professional identity and job burnout, and its relationship between job satisfaction and job burnout. During the peak period of the COVID-19 epidemic, we conducted an online survey—483 Chinese university teachers with online teaching experience completed the Teacher Professional Identity Scale, Job Satisfaction Scale, and Job Burnout Scale. The results of this study found professional identity and job satisfaction of university teachers to be significantly negative predictors of job burnout, with job satisfaction playing a moderating role between professional identity and job burnout. This study also confirmed that professional identity and job satisfaction are important factors affecting job burnout of university teachers. Therefore, this study proposed that schools should adopt more effective strategies to improve university teachers’ professional identity and job satisfaction in order to reduce the practical problems of job burnout, ensure the effectiveness of online teaching, and maintain the sustainable development during the epidemic.

In linear regression with functional predictors and scalar responses, it may be advantageous, particularly if the function is thought to contain features at many scales, to restrict the coefficient function to the span of a wavelet basis, thereby converting the problem into one of variable selection. If the coefficient function is sparsely represented in the wavelet domain, we may employ the well-known LASSO to select a relatively small number of nonzero wavelet coefficients. This is a natural approach to take but to date, the properties of such an estimator have not been studied. In this paper we describe the wavelet-based LASSO approach to regressing scalars on functions and investigate both its asymptotic convergence and its finite-sample performance through both simulation and real-data application. We compare the performance of this approach with existing methods and find that the wavelet-based LASSO performs relatively well, particularly when the true coefficient function is spiky. Source code to implement the method and data sets used in the study are provided as supplemental materials available online.

These authors contributed equally to this work. SUMMARYSulfur is required for the biosynthesis of cysteine, methionine and numerous other metabolites, and thus is critical for cellular metabolism and various growth and developmental processes. Plants are able to sense their physiological state with respect to sulfur availability, but the sensor remains to be identified. Here we report the isolation and characterization of two novel allelic mutants of Arabidopsis thaliana, sel1-15 and sel1-16, which show increased expression of a sulfur deficiency-activated gene b-glucosidase 28 (BGLU28). The mutants, which represent two different missense alleles of SULTR1;2, which encodes a high-affinity sulfate transporter, are defective in sulfate transport and as a result have a lower cellular sulfate level. However, when treated with a very high dose of sulfate, sel1-15 and sel1-16 accumulated similar amounts of internal sulfate and its metabolite glutathione (GSH) to wild-type, but showed higher expression of BGLU28 and other sulfur deficiency-activated genes than wild-type. Reduced sensitivity to inhibition of gene expression was also observed in the sel1 mutants when fed with the sulfate metabolites Cys and GSH. In addition, a SULTR1;2 knockout allele also exhibits reduced inhibition in response to sulfate, Cys and GSH, consistent with the phenotype of sel1-15 and sel1-16. Taken together, the genetic evidence suggests that, in addition to its known function as a high-affinity sulfate transporter, SULTR1;2 may have a regulatory role in response to sulfur nutrient status. The possibility that SULTR1;2 may function as a sensor of sulfur status or a component of a sulfur sensory mechanism is discussed.

Background and Scope Psychiatric science remains descriptive, with a categorical nosology intended to enhance inter-observer reliability. Increased awareness of the mismatch between categorical classifications and the complexity of biological systems drives the search for novel frameworks including discovery science in Big Data. In this review, we provide an overview of incipient approaches, primarily focused on classically categorical diagnoses such as schizophrenia (SZ), autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), but also reference convincing, if focal, advances in cancer biology, to describe the challenges of Big Data and discovery science, and outline approaches being formulated to overcome existing obstacles. Findings A paradigm shift from categorical diagnoses to a domain/structure-based nosology and from linear causal chains to complex causal network models of brain-behavior relationship is ongoing. This (r)evolution involves appreciating the complexity, dimensionality and heterogeneity of neuropsychiatric data collected from multiple sources (“broad” data) along with data obtained at multiple levels of analysis, ranging from genes to molecules, cells, circuits and behaviors (“deep” data). Both of these types of Big Data landscapes require the use and development of robust and powerful informatics and statistical approaches. Thus, we describe Big Data analysis pipelines and the promise and potential limitations in using Big Data approaches to study psychiatric disorders. Conclusion We highlight key resources available for psychopathological studies and call for the application and development of Big Data approaches to dissect the causes and mechanisms of neuropsychiatric disorders and identify corresponding biomarkers for early diagnosis.

Current homogeneous bioscaffolds could hardly recapture the regenerative microenvironment of extracellular matrix. Inspired by the peculiar nature of dura matter, we developed an extracellular matrix–mimicking scaffold with biomimetic heterogeneous features so as to fit the multiple needs in dura mater repairing. The inner surface endowed with anisotropic topology and optimized chemical cues could orchestrate the elongation and bipolarization of fibroblasts and preserve the quiescent phenotype of fibroblasts indicated by down-regulated α–smooth muscle actin expression. The outer surface could suppress the fibrotic activity of myofibroblasts via increased microfiber density. Furthermore, integrin β1 and Yes-associated protein molecule signaling activities triggered by topological and chemical cues were verified, providing evidence for a potential mechanism. The capability of the scaffold in simultaneously promoting dura regeneration and inhibiting epidural fibrosis was further verified in a rabbit laminectomy model. Hence, the so-produced heterogeneous fibrous scaffold could reproduce the microstructure and function of natural dura.