Trends in psychotherapy process research: Samples, measures, researchers, and classic publications.

Psychotherapy studies published in the Journal of Counseling Psychology (JCP) and the Journal of Consulting and Clinical Psychology (JCCP) between 1978 and 1992 were examined. Differences were found between the 2 journals. JCP published mostly process, outcome, and analog research, whereas JCCP published mostly outcome research. Most process and process-outcome studies across journals were of individual, brief therapy. Across the years, more diversity was evident in samples used in process research in terms of student status, gender, and race of clients and therapists. Three content areas were prominent in the process measures and classic studies: therapist techniques, therapist influence, and facilitative conditions. Lists are provided of the frequently used measures, most productive authors, and classic studies in process research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An output formation consensus control for leader–follower networked multi-agent systems under communication constraints and switching topologies

In this paper, the formation consensus problem for a class of leader–follower networked multi-agent systems under communication constraints and switching topologies is investigated. A networked predictive control scheme is proposed to achieve stability and output formation consensus with the switching topology, capable of compensating for data loss and time delays in the network. By equating the whole closed-loop networked multi-agent system with the proposed control scheme to the corresponding switched system, the sufficient and necessary condition of output formation consensus and stability for agents is given. Finally, using three-degree-of-freedom air-bearing spacecraft simulators as the control objects, the proposed scheme is demonstrated to be able to actively compensate for the communication constraints through numerical simulations, and it is also verified to have a good control performance by further realizing the formation task of the simulators through practical experiments.     

Experimental study of diffusion-based extraction from a cell suspension

A recently proposed application of microfluidics is the post-thaw processing of biological cells. Numerical simulations suggest that diffusion-based extraction of the cryoprotective agent dimethyl sulfoxide (DMSO) from blood cells is viable and more efficient than centrifugation, the conventional method of DMSO removal. In order to validate the theoretical model used in these simulations, a prototype was built and the flow of two parallel streams, a suspension of Jurkat cells containing DMSO and a wash stream that contained neither cells nor DMSO, was characterized experimentally. DMSO transport in a rectangular channel (depth 500 μm, width 25 mm and overall length 125 mm) was studied as a function of three dimensionless parameters: depth ratio of the streams, cell volume fraction in the cell solution, and the Peclet number (Pe) based on channel depth, average flow rate and the diffusion coefficient for DMSO in water. In our studies, values of Pe ranged from O(10³) to O(10⁴). Laminar flow was ensured by keeping the Reynolds number between O(1) and O(10). Experimental results based on visual and quantitative data demonstrate conclusively that a microfluidic device can effectively remove DMSO from liquid and cell laden streams without compromising cell recovery. Also, flow conditions in the microfluidic device appear to have no adverse effect on cell viability at the outlet. Further, the results demonstrate that we can predict the amount of DMSO removed from a given device with the theoretical model mentioned previously.     

Towards the Search for Potential Biomarkers in Osteosarcoma: State-of-the-Art and Translational Expectations

Osteosarcoma represents a rare cause of cancer in the general population, accounting for <1% of malignant neoplasms globally. Nonetheless, it represents the main cause of malignant bone neoplasm in children, adolescents and young adults under 20 years of age. It also presents another peak of incidence in people over 50 years of age and is associated with rheumatic diseases. Numerous environmental risk factors, such as bone diseases, genetics and a history of previous neoplasms, have been widely described in the literature, which allows monitoring a certain group of patients. Diagnosis requires numerous imaging tests that make it possible to stratify both the local involvement of the disease and its distant spread, which ominously determines the prognosis. Thanks to various clinical trials, the usefulness of different chemotherapy regimens, radiotherapy and surgical techniques with radical intent has now been demonstrated; these represent improvements in both prognosis and therapeutic approaches. Osteosarcoma patients should be evaluated in reference centres by multidisciplinary committees with extensive experience in proper management. Although numerous genetic and rheumatological diseases and risk factors have been described, the use of serological, genetic or other biomarkers has been limited in clinical practice compared to other neoplasms. This limits both the initial follow-up of these patients and screening in populations at risk. In addition, we cannot forget that the diagnosis is mainly based on the direct biopsy of the lesion and imaging tests, which illustrates the need to study new diagnostic alternatives. Therefore, the purpose of this study is to review the natural history of the disease and describe the main biomarkers, explaining their clinical uses, prognosis and limitations.     

Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature

Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups—healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.     

A single pass algorithm for clustering evolving data streams based on swarm intelligence

Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics, and an offline phase that generates the clusters by using the summary data. In this article we propose a data stream clustering method based on a multi-agent system that uses a decentralized bottom-up self-organizing strategy to group similar data points. Data points are associated with agents and deployed onto a 2D space, to work simultaneously by applying a heuristic strategy based on a bio-inspired model, known as flocking model. Agents move onto the space for a fixed time and, when they encounter other agents into a predefined visibility range, they can decide to form a flock if they are similar. Flocks can join to form swarms of similar groups. This strategy allows to merge the two phases of density-based approaches and thus to avoid the computing demanding offline cluster computation, since a swarm represents a cluster. Experimental results show that the bio-inspired approach can obtain very good results on real and synthetic data sets.     

IL-33 and IL-37: A Possible Axis in Skin and Allergic Diseases

Interleukin (IL)-37 and IL-33 are among the latest cytokines identified, playing a role in several inflammatory conditions, spanning from systemic conditions to tumors to localized diseases. As newly discovered interleukins, their role is still scarcely understood, but their potential role as therapeutic targets or disease activity markers suggests the need to reorganize the current data for a better interpretation. The aim of this review is to collect and organize data produced by several studies to create a complete picture. The research was conducted on the PubMed database, and the resulting articles were sorted by title, abstract, English language, and content. Several studies have been assessed, mostly related to atopic dermatitis and immunologic pathways. Collective data demonstrates a pro-inflammatory role of IL-33 and an anti-inflammatory one for IL-37, possibly related to each other in an IL-33/IL-37 axis. Although further studies are needed to assess the safety and plausibility of targeting these two interleukins for patients affected by skin conditions, the early results indicate that both IL-33 and IL-37 represent markers of disease activity.     

Murine Animal Models in Osteogenesis Imperfecta: The Quest for Improving the Quality of Life

Osteogenesis imperfecta is a rare genetic disorder characterized by bone fragility, due to alterations in the type I collagen molecule. It is a very heterogeneous disease, both genetically and phenotypically, with a high variability of clinical phenotypes, ranging from mild to severe forms, the most extreme cases being perinatal lethal. There is no curative treatment for OI, and so great efforts are being made in order to develop effective therapies. In these attempts, the in vivo preclinical studies are of paramount importance; therefore, serious analysis is required to choose the right murine OI model able to emulate as closely as possible the disease of the target OI population. In this review, we summarize the features of OI murine models that have been used for preclinical studies until today, together with recently developed new murine models. The bone parameters that are usually evaluated in order to determine the relevance of new developing therapies are exposed, and finally, current and innovative therapeutic strategies attempts considered in murine OI models, along with their mechanism of action, are reviewed. This review aims to summarize the in vivo studies developed in murine models available in the field of OI to date, in order to help the scientific community choose the most accurate OI murine model when developing new therapeutic strategies capable of improving the quality of life.     

Spanish Melon Landraces: Revealing Useful Diversity by Genomic,Morphological, and Metabolomic Analysis

Spain is a secondary centre of the diversification of the melon (Cucumis melo L.), with high diversity represented in highly appreciated landraces belonging to the Flexuosus and Ibericus groups. A collection of 47 accessions of Flexuosus, Chate, Piel de Sapo, Tendral, Amarillo, Blanco, and Rochet was analysed using a genotyping-by-sequencing (GBS) approach. A total of 66,971 quality SNPs were identified. Genetic analysis differentiated Ibericus accessions and exotic materials (Ameri, Momordica, Kachri, and Agrestis), while Flexuous accessions shared ancestry between them. Within the Ibericus group, no clear genomic distinction could be identified for the different landraces evaluated, with accessions of different landraces showing high genetic similarity. The morphological characterization confirmed that the external colour and fruit shape had been used as recognition patterns for Spanish melon landraces, but variability within a landrace exists. Differences were found in the sugars and acid and volatile profiles of the materials. Flexuosus and Chate melons at the immature commercial stage accumulated malic acid and low levels of hexoses, while Ibericus melons accumulated high contents of sucrose and citric acid. Specific trends could be identified in the Ibericus landraces. Tendral accumulated low levels of sugars and citric acid and high of malic acid, maintaining higher firmness, Rochet reached higher levels of sugars, and Amarillo tended to lower malic acid contents. Interestingly, high variability was found within landraces for the acidic profile, offering possibilities to alter taste tinges. The main volatile organic compounds (VOCs) in Flexuosus and Chate were aldehydes and alcohols, with clear differences between both groups. In the Ibericus landraces, general trends for VOC accumulation could be identified, but, again, a high level of variation exists. This situation highlights the necessity to develop depuration programs to promote on-farm in situ conservation and, at the same time, offers opportunities to establish new breeding program targets and to take advantage of these sources of variation.     

Potential for identification of wild night-flying moths by remote infrared microscopy

There are hundreds of thousands of moth species with crucial ecological roles that are often obscured by their nocturnal lifestyles. The pigmentation and appearance of moths are dominated by cryptic diffuse shades of brown. In this study, 82 specimens representing 26 moth species were analysed using infrared polarimetric hyperspectral imaging in the range of 0.95–2.5 µm. Contrary to previous studies, we demonstrate that since infrared light does not resolve the surface roughness, wings appear glossy and specular at longer wavelengths. Such properties provide unique reflectance spectra between species. The reflectance of the majority of our species could be explained by comprehensive models, and a complete parametrization of the spectral, polarimetric and angular optical properties was reduced to just 11 parameters with physical units. These parameters are complementary and, compared with the within-species variation, were significantly distinct between species. Counterintuitively to the aperture-limited resolution criterion, we could deduce microscopic features along the surface from their infrared properties. These features were confirmed by electron microscopy. Finally, we show how our findings could greatly enhance opportunities for remote identification of free-flying moth species, and we hypothesize that such flat specular wing targets could be expected to be sensed over considerable distances.