Miracle-dz/UniFAR-FTUs huggingface dataset:
Feedback and therapist effects in the context of treatment outcome and treatment length

Abstract Objective: This study estimates feedback and therapist effects and tests the predictive value of therapists’ and patient attitudes toward psychometric feedback for treatment outcome and length. Methods: Data of 349 outpatients and 44 therapists in private practices were used. Separate multilevel analyses were conducted to estimate predictors and feedback and therapist effects. Results: Around 5.88% of the variability in treatment outcome and 8.89% in treatment length were attributed to therapists. There was no relationship between the average effectiveness of therapists and the average length of their treatments. Initial impairment, early alliance, number of diagnoses, feedback as well as therapists’ and patients’ attitudes toward feedback were significant predictors of treatment outcome. Treatments tended to be longer for patients with a higher number of approved sessions by the insurance company, with higher levels of interpersonal distress at intake, and for those who developed negatively (negative feedback) over the course of their treatment. Conclusions: Therapist effects on treatment outcome and treatment length in routine care seem to be relevant predictors in the context of feedback studies. Therapists’ attitudes toward and use of feedback as well as patients’ attitudes toward feedback should be further investigated in future research on psychometric feedback.
Low Carbamoyl Phosphate Pools May Drive Lactobacillus plantarum CO2-Dependent Growth Phenotype

Lactobacillus plantarum is often found in nutrient-rich habitats with elevated levels of inorganic carbon (IC), and IC-dependent growth is commonly encountered in natural isolates of this species. High CO2-requiring (HCR) prototrophs are unable to grow under conditions of low IC unless arginine and pyrimidines are provided. Prototrophy is restored under high IC conditions, that is in 4% CO2-enriched air or bicarbonate-supplemented medium. Bicarbonate is required for the synthesis of carbamoyl phosphate (CP), a precursor of both arginine and pyrimidine biosynthesis. We hypothesize that at low IC levels, intracellular CP pools limit growth through the limitation of arginine and nucleotide supplies. HCR mutants obtained in the laboratory can be classified into 3 functional groups: mutants with impaired CP synthesis, increased CP consumption or increased CP requirements relative to wild type. This classification provides a framework for investigating the origin of the HCR phenotype in natural environmental isolates of Lactobacillus species, and to investigate the hypothesis that a low level of carbamoyl phosphate is a major determinant of the CO2-dependent growth phenotype often observed in L. plantarum isolates.
Automatic detection and size quantification of infarcts by myocardial perfusion SPECT: clinical validation by delayed-enhancement MRI.

UNLABELLED We aimed to validate the accuracy of a new automated myocardial perfusion SPECT quantification based on normal limits for detection and sizing of infarcts, using delayed-enhancement MRI (DE-MRI) as a gold standard. METHODS Eighty-two immediate (201)Tl rest scans and 26 (201)Tl delayed redistribution scans were compared with resting DE-MRI scans acquired within 24 h of SPECT acquisition. The immediate (201)Tl scans were considered for validation of infarct detection and the delayed (201)Tl scans were considered for infarct sizing. A simplified quantification scheme was used in which defect extent (EXT) and total perfusion deficit (TPD) parameters were derived automatically from SPECT images by comparison with sex-matched normal limits and applying a 3.0 average deviation criterion. The total extent of hyperenhancement expressed as the percentage of the left ventricle was derived from DE-MRI images by visual definition of myocardial contours and defects. DE-MRI and SPECT images were fused in 3 dimensions for visual comparison. Phantom data were also quantified using the same EXT and TPD measures for defects ranging from 5% to 70% of the myocardium. RESULTS The area under the receiver-operator-characteristic curve for the detection of infarct on immediate rest scans was 0.91 +/- 0.03 for EXT and 0.90 +/- 0.03 for TPD (P = not significant). The sensitivity and specificity for the detection of infarct by EXT on immediate (201)Tl rest scan were 87% and 91%, respectively, with the optimal defect size threshold of 4%. Six of 7 cases with DE-MRI defects < 5% were detected by SPECT. Infarct sizes obtained from DE-MRI correlated well with EXT (slope = 0.94, offset = 3.8%; r = 0.84) and TPD (slope = 0.75, offset = 4.2%; r = 0.85) obtained from delayed SPECT (201)Tl scans. Excellent correlation was observed between the SPECT quantification and the physical defect size for the phantom data. The actual size of the defect was better estimated by EXT (slope = 1.00, offset 1.33%; r = 0.99) than by TPD (slope = 0.79, offset = 1.9%; r = 0.99). CONCLUSION Automated quantification of the EXT on myocardial perfusion SPECT images can reliably detect infarcts and measure infarct sizes.
A Novel and Divergent Role of Granzyme A and B in Resistance to Helminth Infection

Granzyme (gzm) A and B, proteases of NK cells and T killer cells, mediate cell death, but also cleave extracellular matrices, inactivate intracellular pathogens, and induce cytokines. Moreover, macrophages, Th2 cells, regulatory T cells, mast cells, and B cells can express gzms. We recently reported gzm induction in human filarial infection. In this study, we show that in rodent filarial infection with Litomosoides sigmodontis, worm loads were significantly reduced in gzmA×B and gzmB knockout mice during the whole course of infection, but enhanced only early in gzmA knockout compared with wild-type mice. GzmA/B deficiency was associated with a defense-promoting Th2 cytokine and Ab shift, enhanced early inflammatory gene expression, and a trend of reduced alternatively activated macrophage induction, whereas gzmA deficiency was linked with reduced inflammation and a trend toward increased alternatively activated macrophages. This suggests a novel and divergent role for gzms in helminth infection, with gzmA contributing to resistance and gzmB promoting susceptibility.
Occurrence of classes I and II integrons in Enterobacteriaceae collected from Zagazig University Hospitals, Egypt

Integrons are genetic units characterized by the ability to capture and incorporate gene cassettes, thus can contribute to the emergence and transfer of antibiotic resistance. The objectives of this study were: (1) to investigate the presence and distribution of class I and class II integrons and the characteristics of the gene cassettes they carry in Enterobacteriaceae isolated from nosocomial infections at Zagzig University Hospital in Egypt, (2) to determine their impact on resistance, and (3) to identify risk factors for the existence of integrons. Relevant samples and full clinical history were collected from 118 inpatients. Samples were processed; isolated microbes were identified and tested for antibiotic susceptibilities. Integrons were detected by polymerase chain reaction (PCR) and were characterized into class I or II by restriction fragment length polymorphism (RFLP). Integron-positive isolates were subjected to another PCR to detect gene cassette, followed by gene cassette sequencing. Risk factors were analyzed by logistic regression analysis. Seventy-six Enterobacteriaceae isolates were recognized, 41 of them (53.9%) were integron-positive; 39 strains carried class I and 2 strains carried class II integrons. Integrons had gene cassettes encoding different combinations and types of resistance determinants. Interestingly, blaOXA129 gene was found and ereA gene was carried on class I integrons. The same determinants were carried within isolates of the same species as well as isolates of different species. The presence of integrons was significantly associated with multidrug resistance (MDR). No risk factors were associated for integron carriage. We conclude that integrons carrying gene cassettes encoding antibiotic resistance are significantly present among Enterobacteriaceae causing nosocomial infection in our hospital. Risk factors for acquisition remain to be identified.
Performance characteristics and exhaust gas analysis of a diesel engine using biodiesel fuel blends

ABSTRACT This study details an investigation of the performance and emission characteristics of a Ford XLD 418 compression ignition engine fuelled by various biodiesel/standard agricultural diesel blends. Blend ratios of 10, 50 and 75% were tested and compared with baseline tests performed using pure diesel fuel in the same engine and under the same nominal test conditions. All experiments were carried out in a controlled laboratory environment in accordance with the British Standard, International Organization for Standardization (BS ISO) 15550 standard for compression ignition engines. Numerous full engine performance tests and emission analyses were carried out for each blend, and it is concluded that the engine mechanical performance became marginally worse with increased fuel blend ratio levels. In terms of exhaust gas analysis, emission gas levels for NOx showed a definitive increase, whereas others such as CO and HC generally decreased. CO2 did not show a conclusive trend when regarded in the context of the variation associated with the baseline pure diesel tests, although the literature supports that it increases marginally.
Dendritic Cell Therapies in Transplantation Revisited: Deletion of Recipient DCs Deters the Effect of Therapeutic DCs

A critical goal in transplantation is the achievement of donor‐specific tolerance, minimizing the use of immunosuppressants. Dendritic cells (DCs) are antigen (Ag) presenting cells (APCs) with capability to promote immunity or tolerance. The immune‐regulatory properties of DCs have been exploited for generation of tolerogenic/immunosuppressive (IS) DCs that, when transfer systemically, prolong allograft survival in murine models. Surprisingly, the in vivo mechanisms of therapies based on (donor‐ or recipient‐derived) ISDCs in transplantation remain unknown, given that previous studies investigated their effects in vitro, or ex vivo after transplantation. Since once injected, ISDCs are short‐lived and transfer Ag to recipient APCs, we assessed the role of recipient DCs by depleting them at the time of ISDC‐therapy in a mouse model of cardiac transplantation. The results indicate that, contrary to the accepted paradigm, systemically administered ISDCs reduce the alloresponse and prolong allograft survival, not by themselves, but through conventional DCs (cDCs) of the recipient. These findings raise doubts on the advantages of the currently used ISDC‐therapies, since the immune‐regulatory properties of the injected ISDC do not seem to be functionally relevant in vivo, and the quiescent/pro‐tolerogenic status of cDCs may be compromised in patients with end‐stage diseases that require transplantation.
A Superprocess with Upper Confidence Bounds for Cooperative Spectrum Sharing

Cooperative Spectrum Sharing (CSS) is an appealing approach for primary users (PUs) to share spectrum with secondary users (SUs) because it increases the transmission range or rate of the PUs. Most previous works are focused on developing complex algorithms which may not be fast enough for real-time variations such as channel availability and/or assume perfect information about the network. Instead, we develop a learning mechanism for a PU to enable CSS in a strongly incomplete information scenario with low computational overhead. Our mechanism is based on a Markovian variant of multi-armed bandits (MABs) called superprocess, enhanced with the concept of Upper Confidence Bound (UCB) from stochastic MABs. By means of Monte-Carlo evaluations we show that, despite its low computational overhead, it converges to a low regret solution outperforming baseline approaches such as epsilon-greedy. This algorithm can be extended to include more sophisticated features while maintaining its desirable properties such as low computational overhead and fast speed of convergence.
Working Memory and the Suppression of Reflexive Saccades

Conscious behavioral intentions can frequently fail under conditions of attentional depletion. In attempting to trace the cognitive origin of this effect, we hypothesized that failures of action controlspecifically, oculomotor movementcan result from the imposition of fronto-executive load. To evaluate this prediction, participants performed an antisaccade task while simultaneously completing a working-memory task that is known to make variable demands on prefrontal processes (n-back task, see Jonides et al., 1997). The results of two experiments are reported. As expected, antisaccade error rates were increased in accordance with the fronto-executive demands of the n-back task (Experiment 1). In addition, the debilitating effects of working-memory load were restricted to the inhibitory component of the antisaccade task (Experiment 2). These findings corroborate the view that working memory operations play a critical role in the suppression of prepotent behavioral responses.
Chemokine-driven lymphocyte infiltration: an early intratumoural event determining long-term survival in resectable hepatocellular carcinoma

Objective Hepatocellular carcinoma (HCC) is a heterogeneous disease with poor prognosis and limited methods for predicting patient survival. The nature of the immune cells that infiltrate tumours is known to impact clinical outcome. However, the molecular events that regulate this infiltration require further understanding. Here the ability of immune genes expressed in the tumour microenvironment to predict disease progression was investigated. Methods Using quantitative PCR, the expression of 14 immune genes in resected tumour tissues from 57 Singaporean patients was analysed. The nearest-template prediction method was used to derive and test a prognostic signature from this training cohort. The signature was then validated in an independent cohort of 98 patients from Hong Kong and Zurich. Intratumoural components expressing these critical immune genes were identified by in situ labelling. Regulation of these genes was analysed in vitro using the HCC cell line SNU-182. Results The identified 14 immune-gene signature predicts patient survival in both the training cohort (p=0.0004 and HR=5.2) and the validation cohort (p=0.0051 and HR=2.5) irrespective of patient ethnicity and disease aetiology. Importantly, it predicts the survival of patients with early disease (stages I and II), for whom classical clinical parameters provide limited information. The lack of predictive power in late disease stages III and IV emphasises that a protective immune microenvironment has to be established early in order to impact disease progression significantly. This signature includes the chemokine genes CXCL10, CCL5 and CCL2, whose expression correlates with markers of T helper 1 (Th1), CD8+ T and natural killer (NK) cells. Inflammatory cytokines (tumour necrosis factor α, interferon γ) and Toll-like receptor 3 ligands stimulate intratumoural production of these chemokines which drive tumour infiltration by T and NK cells, leading to enhanced cancer cell death. Conclusion A 14 immune-gene signature, which identifies molecular cues driving tumour infiltration by lymphocytes, accurately predicts survival of patients with HCC especially in early disease.
KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research.

A database (DB) describing the relationships between species and their metabolites would be useful for metabolomics research, because it targets systematic analysis of enormous numbers of organic compounds with known or unknown structures in metabolomics. We constructed an extensive species-metabolite DB for plants, the KNApSAcK Core DB, which contains 101,500 species-metabolite relationships encompassing 20,741 species and 50,048 metabolites. We also developed a search engine within the KNApSAcK Core DB for use in metabolomics research, making it possible to search for metabolites based on an accurate mass, molecular formula, metabolite name or mass spectra in several ionization modes. We also have developed databases for retrieving metabolites related to plants used for a range of purposes. In our multifaceted plant usage DB, medicinal/edible plants are related to the geographic zones (GZs) where the plants are used, their biological activities, and formulae of Japanese and Indonesian traditional medicines (Kampo and Jamu, respectively). These data are connected to the species-metabolites relationship DB within the KNApSAcK Core DB, keyed via the species names. All databases can be accessed via the website http://kanaya.naist. jp/KNApSAcK_Family/. KNApSAcK WorldMap DB comprises 41,548 GZ-plant pair entries, including 222 GZs and 15,240 medicinal/edible plants. The KAMPO DB consists of 336 formulae encompassing 278 medicinal plants; the JAMU DB consists of 5,310 formulae encompassing 550 medicinal plants. The Biological Activity DB consists of 2,418 biological activities and 33,706 pairwise relationships between medicinal plants and their biological activities. Current statistics of the binary relationships between individual databases were characterized by the degree distribution analysis, leading to a prediction of at least 1,060,000 metabolites within all plants. In the future, the study of metabolomics will need to take this huge number of metabolites into consideration.
Shear Capacity of Stud-Groove Connector in Glulam-concrete Composite Structure

A timber-concrete composite structure (TCC) is economically and environmentally friendly. One of the key design points of this kind of structure is to ensure the reliability of the shear connectors. The objective of this paper is to study the mechanical property of stud-groove-type connectors and to provide shear capacity equations for stud-groove connectors in timber-concrete composite structures. Based on the Johansen Yield Theory (European Yield Model), some mechanical models and capacity equations for stud-groove-type connectors in timber-concrete structures were studied. Push-out specimens with different parameters (stud diameter, stud length, groove width, and groove depth) were tested to obtain the shear capacity and slip modulus. The experimental strengths were used to validate equations given in the paper. The shear capacity and slip modulus of stud-groove-type connectors was in direct proportion to the diameter of studs and the dimension of the groove. Comparison between the theoretical and the experimental shear strength results showed reasonable agreement. The highlight of this study on shear capacity equations could significantly reduce the push-out tests before investigating the other properties of TCC.
Information on the go: A case study of Europeana mobile users

According to estimates the mobile device will soon be the main platform for searching the web, and yet our knowledge of how mobile consumers use information, and how that differs from desktops/laptops users, is imperfect. The paper sets out to correct this through an analysis of the logs of a major cultural website, Europeana. The behavior of nearly 70,000 mobile users was examined over a period of more than a year and compared with that for PC users of the same site and for the same period. The analyses conducted include: size and growth of use, time patterns of use; geographical location of users, digital collections used; comparative information-seeking behavior using dashboard metrics, clustering of users according to their information seeking, and user satisfaction. The main findings were that mobile users were the fastest-growing group and will rise rapidly to a million by December 2012 and that their visits were very different in the aggregate from those arising from fixed platforms. Mobile visits could be described as being information “lite”: typically shorter, less interactive, and less content viewed per visit. Use took a social rather than office pattern, with mobile use peaking at nights and weekends. The variation between different mobile devices was large, with information seeking on the iPad similar to that for PCs and laptops and that for smartphones very different indeed. The research further confirms that informationseeking behavior is platform-specific and the latest platforms are changing it all again. Websites will have to adapt.
Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms

Location check-ins contain both geographical and semantic information about the visited venues, in the form of tags (e.g., “restaurant”). Such data might reveal some personal information about users beyond what they actually want to disclose, hence their privacy is threatened. In this paper, we study users’ motivations behind location check-ins, and we quantify the effect of a privacy-preserving technique (i.e., generalization) on the perceived utility of check-ins. By means of a targeted user study on Foursquare (N = 77), we show that the motivation behind Foursquare check-ins is a mediator of the loss of utility caused by generalization. Using these findings, we propose a machine learning method for determining the motivation behind each check-in, and we design a motivation-based predictive model for utility. Our results show that the model accurately predicts the loss of utility caused by semantic and geographical generalization; this model enables the design of utility-aware, privacy-enhancing mechanisms in location-based social networks.
A Rescorla-Wagner drift-diffusion model of conditioning and timing

Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this article we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 10 experimental phenomena and show that it can provide an adequate account for 8, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSC-TD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used. Author Summary How does the time of events affect the way we learn about associations between these events? Computational models have made great contributions to our understanding of associative learning, but they usually do not perform very well when time is taken into account. Models of timing have reached high levels of accuracy in describing timed behaviour, but they usually do not have much to say about associations. A unified approach would involve combining associative learning and timing models into a single framework. This article takes just this approach. It combines the influential Rescorla-Wagner associative model with a timing model based on the Drift-Diffusion process, and shows how the resultant model can account for a number of learning and timing phenomena. The article also compares the new model to others that are similar in scope.