Frizzled-8 integrates Wnt-11 and transforming growth factor-β signaling in prostate cancer

Wnt-11 promotes cancer cell migration and invasion independently of β-catenin but the receptors involved remain unknown. Here, we provide evidence that FZD8 is a major Wnt-11 receptor in prostate cancer that integrates Wnt-11 and TGF-β signals to promote EMT. FZD8 mRNA is upregulated in multiple prostate cancer datasets and in metastatic cancer cell lines in vitro and in vivo. Analysis of patient samples reveals increased levels of FZD8 in cancer, correlating with Wnt-11. FZD8 co-localizes and co-immunoprecipitates with Wnt-11 and potentiates Wnt-11 activation of ATF2-dependent transcription. FZD8 silencing reduces prostate cancer cell migration, invasion, three-dimensional (3D) organotypic cell growth, expression of EMT-related genes, and TGF-β/Smad-dependent signaling. Mechanistically, FZD8 forms a TGF-β-regulated complex with TGF-β receptors that is mediated by the extracellular domains of FZD8 and TGFBR1. Targeting FZD8 may therefore inhibit aberrant activation of both Wnt and TGF-β signals in prostate cancer

The effects of exposure to images of others’ suffering and vulnerability on altruistic, trust-based, and reciprocated economic decision-making

In this paper we explored the effects of exposure to images of the suffering and vulnerability of others on altruistic, trust-based, and reciprocated incentivized economic decisions, accounting for differences in participants’ dispositional empathy and reported in-group trust for their recipient(s). This was done using a pictorial priming task, framed as a memory test, and a triadic economic game design. Using the largest experimental sample to date to explore this issue, our integrated analysis of two online experiments (total N = 519), found statistically consistent evidence that exposure to images of suffering and vulnerability (vs. neutral images) increased altruistic in-group giving as measured by the “triple dictator game”, and that the manipulation was significantly more effective in those who reported lower trust for their recipients. The experimental manipulation also significantly increased altruistic giving in the standard “dictator game” and trust-based giving in the “investment game”, but only in those who were lower in in-group trust and also high in affective or cognitive empathy. Complementary qualitative evidence revealed the strongest motivations associated with increased giving in the experimental condition were greater assumed reciprocation and a lower aversion to risk. However, no consistent effects of the experimental manipulation on participants’ reciprocated decisions were observed. These findings suggest that, as well as altruistic decision-making in the “triple dictator game”, collaboratively witnessing the suffering of others may heighten trust-based in-group giving in the “investment game” for some people, but the effects are heterogeneous and sensitive to context

Heart versus Head: Differential Bodily Feedback Causally Alters Economic Decision-making

Metaphorically, altruistic acts, such as monetary donations, are said to be driven by the heart, whereas sound financial investments are guided by reason, embodied by the head. In a unique experiment, we tested the effects of these bodily metaphors using biofeedback and an incentivized economic decision-making paradigm. Participants played a repeated investment game with a simulated partner, alternating between tactical investor and altruistic investee. When making decisions, participants received counterbalanced visual feedback from their own or a simulated partner’s heart or head, as well as no feedback. As investor, participants transferred a greater proportion of their endowments when exposed to visual feedback from their own head than to feedback from their own heart or no feedback at all. These effects were not observed when the source of the feedback was the simulated partner. As investee, heart feedback predicted greater altruistic returns than head or no feedback, but this effect did not differ based on source (own vs partner). Consistent with a dual-process framework, we suggest that people may be encouraged to invest more or be more altruistic when receiving bodily feedback from conceptually diametric sources

Urban aerosol number size distributions

International audienceAerosol number size distributions have been measured since 5 May 1997 in Helsinki, Finland. The presented aerosol data represents size distributions within the particle diameter size range 8-400nm during the period from May 1997 to March 2003. The daily, monthly and annual patterns of the aerosol particle number concentrations were investigated. The temporal variation of the particle number concentration showed close correlations with traffic activities. The highest total number concentrations were observed during workdays; especially on Fridays, and the lowest concentrations occurred during weekends; especially Sundays. Seasonally, the highest total number concentrations were observed during winter and spring and lower concentrations were observed during June and July. More than 80% of the number size distributions had three modes: nucleation mode (30nm), Aitken mode (20-100nm) and accumulation mode (90nm). Less than 20% of the number size distributions had either two modes or consisted of more than three modes. Two different measurement sites were used; in the first (Siltavuori, 5.5.1997-5.3.2001), the arithmetic means of the particle number concentrations were 7000cm, 6500cm, and 1000cm respectively for nucleation, Aitken, and accumulation modes. In the second site (Kumpula, 6.3.2001-28.2.2003) they were 5500cm, 4000cm, and 1000cm. The total number concentration in nucleation and Aitken modes were usually significantly higher during workdays than during weekends. The temporal variations in the accumulation mode were less pronounced. The lower concentrations at Kumpula were mainly due to building construction and also the slight overall decreasing trend during these years. During the site changing a period of simultaneous measurements over two weeks were performed showing nice correlation at both sites

Withdrawal from long-term use of zopiclone, zolpidem and temazepam may improve perceived sleep and quality of life in older adults with primary insomnia

Long-term use of benzodiazepines or benzodiazepine receptor agonists is widespread, although guidelines recommend short-term use. Only few controlled studies have characterized the effect of discontinuation of their chronic use on sleep and quality of life. We studied perceived sleep and quality of life in 92 older (age 55-91 years) outpatients with primary insomnia before and after withdrawal from long-term use of zopiclone, zolpidem or temazepam (BZDA). BZDA was withdrawn during 1 month, during which the participants received psychosocial support and blindly melatonin or placebo. A questionnaire was used to study perceived sleep and quality of life before withdrawal, and 1 month and 6 months later. 89 participants completed the 6-month follow-up. As melatonin did not improve withdrawal, all participants were pooled and then separated based solely on the withdrawal results at 6 months (34 Withdrawers. 55 Nonwithdrawers) for this secondary analysis. At 6 months, the Withdrawers had significantly (P <0.05) shorter sleep-onset latency and less difficulty in initiating sleep than at baseline and when compared to Nonwithdrawers. Compared to baseline, both Withdrawers and Nonwithdrawers had at 6 months significantly (P <0.05) less fatigue during the morning and daytime. Stress was alleviated more in Withdrawers than in Nonwithdrawers (P <0.05). Satisfaction with life and expected health 1 year later improved (P <0.05) in Withdrawers. In conclusion, sleep disturbances, daytime fatigue and impaired quality of life may resolve within 6 months of BZDA withdrawal. These results encourage withdrawal from chronic use of benzodiazepine-type hypnotics, particularly in older subjects.Peer reviewe

Relationship between SDB and short-term outcome in Finnish ischemic stroke patients

Objectives Presence of sleep-disordered breathing (SDB) affects negatively recovery from stroke. The aim of this study is to evaluate the relationships between sleep-disordered breathing (SDB) and outcome measures in Finnish stroke unit cohort: mRS, need of rehabilitation and hospitalization time. Material and Methods An observational longitudinal study consisted of 95 patients referred to the Stroke Unit of Satakunta Hospital District over a period of November 2013 to March 2016. Patients were tested for SDB within 72 hr from the hospital admission because of ischemic stroke or TIA. The patients underwent polysomnography with NOX T3 wireless recorder. Results There are 37% (n = 35) non-OSA patients, 20% (n = 19) of patients have mild obstructive sleep apnea (OSA) and 39% (n = 37) have moderate/severe OSA and 4% (n = 4) have CSA. Patients with OSA have higher proportion of disability scores of mRS 3-5 (38%) compared to non-OSA (11%) and mild OSA (5%) patients on registration day (mRS0), and the same trend is seen at hospital discharge 35% versus 9% and 5%. (p = .009). Proportion of patients with OSA who needed rehabilitation is 65% (n = 19) versus non-OSA patients 17.5% (n = 4) and mild OSA patients 17.5% (n = 4;p = .039). We observed longer duration of hospitalization (5-15 days) in 29% of OSA patients compared to mild OSA patients 47% and OSA patients 54%. (p = .045). Conclusion Ischemic stroke patients with OSA have higher disability, higher need of rehabilitation, and longer hospitalization length. Prescreening tools for recognizing these stroke patients in acute phase could be valuable. That could result in earlier initiation of treatment and might prevent worse recovery from stroke

Unilääkevieroituksesta saatiin hyviä tuloksia Satauni-projektissa

Yleis­lää­kärin ja sairaan­hoi­tajan psy­ko­so­siaa­linen tu­ki aut­toi ikään­tyviä poti­ laita vieroit­tumaan pitkäai­kai­sesta uni­lääk­keiden käy­töstä. Terveys­kes­kuk­sessa toteu­ tettu vie­roitus pa­ransi ikään­tyvien poti­laiden lihas­voimaa ja tasa­painoa, mut­ta kogni­ tii­viset ky­vyt ei­vät paran­tuneet

Miten vieroittaa iäkäs potilas unilääkkeestä?

Hoito­suo­si­tusten vas­tainen bentso­diat­se­piinien pitkäai­kais­käyttö uni­lääk­keenä on yleistä, ja sii­hen liit­tyy mo­nia ris­kejä var­sinkin iäk­käille henki­löille. Asteit­tainen, tuet­tu vie­roitus tuot­taa par­haat tu­lokset. Vieroi­tuksen oh­jaus on mahdol­lista to­teuttaa myös terveys­kes­kuksen vastaa­not­to­käyn­neillä. An­noksen pienen­nys­nopeus so­vitaan yh­dessä po­tilaan kans­sa, ja on esi­mer­kiksi 10–25 % 1–3 vii­kon vä­lein. An­noksen pienen­tä­miseen liit­tyy usein ns. rebound-unet­to­muutta, jol­loin oi­reet pa­laavat voimis­tu­neina. Täs­tä kan­nattaa infor­moida poti­lasta ja ker­toa, et­tä il­miö on ohi­me­nevä.Peer reviewe

Parkinson's disease detection from 20-step walking tests using inertial sensors of a smartphone: Machine learning approach based on an observational case-control study

Parkinson's disease (PD) is a neurodegenerative disease inducing dystrophy of the motor system. Automatic movement analysis systems have potential in improving patient care by enabling personalized and more accurate adjust of treatment. These systems utilize machine learning to classify the movement properties based on the features derived from the signals. Smartphones can provide an inexpensive measurement platform with their built-in sensors for movement assessment. This study compared three feature selection and nine classification methods for identifying PD patients from control subjects based on accelerometer and gyroscope signals measured with a smartphone during a 20-step walking test. Minimum Redundancy Maximum Relevance (mRMR) and sequential feature selection with both forward (SFS) and backward (SBS) propagation directions were used in this study. The number of selected features was narrowed down from 201 to 4-15 features by applying SFS and mRMR methods. From the methods compared in this study, the highest accuracy for individual steps was achieved with SFS (7 features) and Naive Bayes classifier (accuracy 75.3%), and the second highest accuracy with SFS (4 features) and k Nearest neighbours (accuracy 75.1%). Leave-one-subject-out cross-validation was used in the analysis. For the overall classification of each subject, which was based on the majority vote of the classified steps, k Nearest Neighbors provided the most accurate result with an accuracy of 84.5% and an error rate of 15.5%. This study shows the differences in feature selection methods and classifiers and provides generalizations for optimizing methodologies for smartphone-based monitoring of PD patients. The results are promising for further developing the analysis system for longer measurements carried out in free-living conditions

Formation and destabilization of Ga interstitials in GaAsN: Experiment and theory

Using first-principles total energy calculations we have found complex defects induced by N incorporation in GaAsN. The formation energy of the Ga interstitial atom is very significantly decreased due to local effects within the defect complex. The stability of the Ga interstitials is further increased at surfaces. The present results suggest that the energetically favorable Ga interstitial atoms are much more abundant in GaAsN than the previously considered N defects, which have relatively large formation energies. Our synchrotron radiation core-level photoemission measurements support the computational results. The formation of harmful Ga interstitials should be reduced by incorporating large group IV B atoms in GaAsN