User surveys support designing a prosthetic wrist that incorporates the Dart Thrower's Motion

AIM

Prosthetic devices are not meeting the needs of people with upper limb amputations. Due to controlsidelimitations, prosthetic wrists cannot yet be fully articulated. This study sought to determine which wrist motions users felt were most important for completing activities of daily living. We specifically invstigated whether adding a combinationof flexion and deviation known as the Dart Thrower's Motion to a prosthetic wrist would help improve functionality.

METHODS

Fifteen participants with a trans-radial amputation, aged 25-64 years, who use a prosthesis completed an online survey and answered interview questions to determine which types of tasks pose particular challenges. Participants were asked what kinds of improvements they would like to see in a new prosthesis. A subset of five participants were interviewed in-depth to provide further information about difficulties they face using their device.

RESULTS

The survey showed that participants had difficulty performing activities of daily living that involve a combination of wrist flexion and deviation known as the "Dart Throwers Motion". Interview responses confirmed that users have difficulty performing these tasks, especially those that require tools. Additionally, users said that they were more interested in having flexion and deviation than rotation in a prosthetic wrist.

CONCLUSION

This research indicates that including the Dart Thrower's Motion in future designs of prosthetic wrists would improve these devices and people with upper limb amputations would be excited to see this improvement in their devices. Implications for Rehabilitation • Over one third of people with upper limb amputations do not use a prosthesis because prosthetic devices do not meet their needs.• The number of motions possible in state of the art prosthetic devices is limited by the small number of control sites available.• The Dart Thrower?s Motion is a wrist motion used for many activities of daily living but unavailable in commercial prosthetics leading many prosthetics users to have difficulty with these tasks.• Prosthetic use, and therefore quality of life, could be improved by including the Dart Thrower's Motion in a prosthesis.

Abstract A188: Harnessing synthetic lethality to predict the response to cancer treatments

Synthetic lethality (SL) describes an interaction between a pair of genes whereby their double knockout is lethal, while their respective knockout is not. The identification of SL interactions (SLi) via large-scale genomic screens offers promising opportunities for developing selective therapies in cancer. However, our analysis of the TCGA cohort shows that many of the interactions do not carry predictive signal of patient survival or drug response. Here we present a data-driven approach termed ISLE (Identification of clinically relevant Synthetic LEthality) that mines the TCGA cohort to identify a subset of clinically relevant SL interactions (cSLi). ISLE consists of the following inference steps, analysis of tumor, cell line, and gene evolutionary data. We first create an initial pool of SL pairs identified through direct double knockout screens/isogenic cell line screens or inferred from large-scale shRNA/sgRNA single-gene knockout screens. Starting from this initial SL pool, ISLE first identifies putative SL gene pairs whose co-inactivation is under-represented in tumors, testifying that it is selected against. Second, it prioritizes candidate SL pairs whose co-inactivation is associated with improved patient’s prognosis, testifying that it may hamper tumor progression. Finally, it prioritizes SL-gene pairs with similar evolutionary phylogenetic profiles based on the notion that SL interactions are conserved across multiple species. We validate the identified SL pairs using an unseen large-scale in vitro drug response screen by showing the SL pairs marks a decent prediction accuracy (AUC~0.8). We compare ISLE’s performance to the standard supervised drug response prediction approaches in DREAM challenges, and our prediction based on generic pretreatment tumor samples (from TCGA) was within top 3 in prediction accuracy among the top predictors. ISLE-based approach also successfully distinguishes responders vs nonresponders to drug treatment (for >70% of drugs) in mouse xenografts using the activity profile of the drug target’s SL-partners. We then experimentally show the utility of SL in predicting synergistic drug combinations in patient-derived cell lines based on the notion that the two drugs whose targets have SL interactions are synergistic. Most importantly, we demonstrate for the first time that an SL network can successfully predict the treatment outcome in cancer patients in multiple large-scale patient datasets including TCGA, where cSLi are successfully predict patients’ response for more than 70% of cancer drugs. ISLE is predictive of patients’ response for the majority of current cancer drugs without any drug-specific training. Of paramount importance, the predictions of ISLE are based on SLi between (potentially) all genes in the cancer genome, thus prioritizing treatments for patients whose tumors do not bear specific actionable mutations in cancer driver genes, offering a novel approach to precision-based cancer therapy.

Citation Format: Joo S. Lee, Avinash Das, Livnat Jerby-Arnon, Rand Arafeh, Matthew Davidson, Arnaud Amzallag, Seung Gu Park, Kuoyuan Cheng, Welles Robinson, Dikla Atias, Chani Stossel, Ella Buzhor, Gidi Stein, Joshua J. Waterfall, Paul S. Meltzer, Talia Golan, Sridhar Hannenhalli, Eyal Gottlieb, Cyril H. Benes, Yardena Samuels, Emma Shanks, Eytan Ruppin. Harnessing synthetic lethality to predict the response to cancer treatments [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr A188.

Simulated forward and backward self motion, based on realistic parameters, causes motion induced blindness

Motion Induced Blindness (MIB) is a well-established visual phenomenon whereby highly salient targets disappear when viewed against a moving background mask. No research has yet explored whether contracting and expanding optic flow can also trigger target disappearance. We explored MIB using mask speeds corresponding to driving at 35, 50, 65 and 80 km/h in simulated forward (expansion) and backward (contraction) motion as well as 2-D radial movement, random, and static mask motion types. Participants (n = 18) viewed MIB targets against masks with different movement types, speed, and target locations. To understand the relationship between saccades, pupil response and perceptual disappearance, we ran two additional eye-tracking experiments (n = 19). Target disappearance increased significantly with faster mask speeds and upper visual field target presentation. Simulated optic flow and 2-D radial movement caused comparable disappearance, and all moving masks caused significantly more disappearance than a static mask. Saccades could not entirely account for differences between conditions, suggesting that self-motion optic flow does cause MIB in an artificial setting. Pupil analyses implied that MIB disappearance induced by optic flow is not subjectively salient, potentially explaining why MIB is not noticed during driving. Potential implications of MIB for driving safety and Head-Up-Display (HUD) technologies are discussed.

Abstract 543: Harnessing synthetic lethality to predict clinical outcomes of cancer treatment

Significance: The identification of Synthetic Lethal interactions (SLi) has long been considered a foundation for the advancement of cancer treatment. The rapidly accumulating large-scale patient data now provides a golden opportunity to infer SLi directly from patient samples. Here we present a new data-driven approach termed ISLE for identifying SLi, which is then shown to be predictive of clinical outcomes of cancer treatment in an unsupervised manner, for the first time.

Methods: ISLE consists of four inference steps, analyzing tumor, cell line and gene evolutionary data: It first identifies putative SL gene pairs whose co-inactivation is underrepresented in tumors, testifying that they are selected against. Second, it further prioritizes candidate SL pairs whose co-inactivation is associated with better prognosis in patients, testifying that they may hamper tumor progression. Finally, it eliminates false positive SLi using gene essentiality screens (testifying to causal SLi relations) and prioritizing SLi paired genes with similar evolutionary phylogenetic profiles.

Results: We applied ISLE to analyze the TCGA tumor collection and generated the first clinically-derived pan-cancer SL-network, composed of SLi common across many cancer types. We validated that these SLi match the known, experimentally identified SLi (AUC=0.87), and show that the SL-network is predictive of patient survival in an independent breast cancer dataset (METABRIC). Based on the predicted SLi, we predicted drug response of single agents and drug combinations in a wide variety of in vitro, mouse xenograft and patient data, altogether encompassing >700 single drugs and >5,000 drug combinations in >1,000 cell lines, 375 xenograft models and >5,000 patient samples. Of note, these predictions were performed in an unsupervised manner, reducing the known risk of over-fitting the data commonly associated with supervised prediction methods. Our prediction is based on the notion that a drug is likely to be more effective in tumors where many of its targets’ SL-partners are inactive, and drug synergism may be mediated by underlying SLi between their targets. Most importantly, we demonstrate for the first time that an SL-network can successfully predict the treatment outcome in cancer patients in multiple large-scale patient datasets including the TCGA, where SLis successfully predict patients’ response for 75% of cancer drugs.

Conclusions: ISLE is predictive of the patients’ response for the majority of current cancer drugs. Of paramount importance, the predictions of ISLE are based on SLi between (potentially) all genes in the cancer genome, thus prioritizing treatments for patients whose tumors do not bear specific actionable mutations in cancer driver genes, offering a novel approach to precision-based cancer therapy. The predictive performance of ISLE is likely to further improve with the expected rapid accumulation of additional patient data.

Citation Format: Joo Sang Lee, Avinash Das, Livnat Jerby-Arnon, Seung Gu Park, Matthew Davidson, Dikla Atias, Arnaud Amzallag, Chani Stossel, Ella Buzhor, Welles Robinson, Kuoyuan Cheng, Joshua J. Waterfall, Paul S. Meltzer, Sridhar Hannenhalli, Cyril H. Benes, Talia Golan, Emma Shanks, Eytan Ruppin. Harnessing synthetic lethality to predict clinical outcomes of cancer treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 543. doi:10.1158/1538-7445.AM2017-543

A method for the improved detection of aerosolized influenza viruses and the male-specific (F+) RNA coliphage MS2

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Developed a method for viral bioaerosol sampling using anion exchange resin.

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MS2 and influenza viruses (A/B) detection improved by 8.26×, 6.77× and 3.33×.

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The anion exchange resin method can adapt to existing bioaerosol samplers.

The detection of aerosolized viruses can serve as an important surveillance and control tool in agriculture, human health, and environmental settings. Here, we adapted an anion exchange resin-based method, initially developed to concentrate negatively charged viruses from water, to liquid impingement-based bioaerosol sampling. In this method, aerosolized viruses are collected in a 20 ml liquid sample contained within widely used impingers, BioSamplers (SKC Inc., Eighty Four, PA), and further concentrated via adsorption to an anion exchange resin that is suspended within this liquid. Viral nucleic acids are then extracted from the resin to facilitate molecular analyses through a reduction in the effective sample volume. For this study, various quantities of two negatively charged viruses, type A and type B influenza viruses (FluMist Quadrivalent vaccine) and the male-specific (F+) RNA coliphage MS2 (MS2), were nebulized into a custom-built bioaerosolization chamber, and sampled using BioSamplers with and without anion exchange resin. Compared to direct testing of the BioSampler liquid, detection was improved by 6.77× and 3.33× for type A and type B influenza viruses, respectively, by using the anion exchange resin. For MS2, the anion exchange resin method allowed for an average improvement in detection of 8.26×.

Noble metal-free catalytic decarboxylation of oleic acid to n-heptadecane on nickel-based metal–organic frameworks (MOFs)

Herein we demonstrate novel noble metal-free catalytic systems based on Ni MOFs that can effectively convert oleic acid into heptadecane.

RAC1 activation drives pathologic interactions between the epidermis and immune cells

Interactions between the epidermis and the immune system govern epidermal tissue homeostasis. These epidermis-immune interactions are altered in the inflammatory disease psoriasis; however, the pathways that underlie this aberrant immune response are not well understood. Here, we determined that Ras-related C3 botulinum toxin substrate 1 (RAC1) is a key mediator of epidermal dysfunction. RAC1 activation was consistently elevated in psoriatic epidermis and primary psoriatic human keratinocytes (PHKCs) exposed to psoriasis-related stimuli, but not in skin from patients with basal or squamous cell carcinoma. Expression of a constitutively active form of RAC1 (RACV12) in mice resulted in the development of lesions similar to those of human psoriasis that required the presence of an intact immune system. RAC1V12-expressing mice and human psoriatic skin showed similar RAC1-dependent signaling as well as transcriptional overlap of differentially expressed epidermal and immune pathways. Coculture of PHKCs with immunocytes resulted in the upregulation of RAC1-dependent proinflammatory cytokines, an effect that was reproduced by overexpressing RAC1 in normal human keratinocytes. In keratinocytes, modulating RAC1 activity altered differentiation, proliferation, and inflammatory pathways, including STAT3, NFκB, and zinc finger protein 750 (ZNF750). Finally, RAC1 inhibition in xenografts composed of human PHKCs and immunocytes abolished psoriasiform hyperplasia and inflammation in vivo. These studies implicate RAC1 as a potential therapeutic target for psoriasis and as a key orchestrator of pathologic epidermis-immune interactions.

Religiosity as a protective factor against suicidal behaviour

OBJECTIVE

Data suggest that adherence to religious beliefs is associated with lower rates of suicide. A number of mediating factors have been hypothesized to explain this association, including enhanced social support, less substance abuse, and lower rates of psychopathology.

METHOD

We utilized data from a two-phase population-based, epidemiological study of mental disorders among young Jewish Israel born in a 10-year birth-cohort conducted in the 1980s. This study included data on religiosity and suicidal behaviour. Twenty-five years thereafter, mortality data were obtained from a national vital statistics registry.

RESULTS

Rates of suicidal ideation were similar among secular, partially observant, and religious subjects (9.4%, 6.7%, and 6.2%, respectively; adjusted OR for linear trend: 0.80, 95% CI: 0.58-1.09). Rates of suicide attempts were significantly lower among religious subjects (2.4%, 2.5%, and 0.4% for secular, partially observant, and religious, respectively; adjusted OR for linear trend: 0.62, 95% CI: 0.43-0.88). Of the 4914 subjects, eight died by suicide: Seven of them were secular and one was partially observant (χ(2) = 2.52, P = 0.09). There were no differences in social functioning or rates of psychopathology among the study groups.

CONCLUSION

Religiosity has a protective effect against suicide attempts, which is independent of social functioning, psychopathology, and substance use.

IQ and obesity in adolescence: a population-based, cross-sectional study

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

Low IQ is associated with high BMI in childhood. There are inconsistent findings on the association between low SES and high BMI. Youth with low IQ have been reported to have poorer health behaviors, such as poor nutrition and less physical activity.

WHAT THIS STUDY ADDS

Low IQ is significantly associated with obesity for both male and female adolescents, though more strongly for female adolescents. Physical activity has a mediating effect on the association between low IQ and obesity among both male and female adolescents, though more strongly for male adolescents. The association between low IQ and obesity is strongest among adolescents from high SES backgrounds.

BACKGROUND

Previous studies have shown an association between low intelligence quotient (IQ), high body mass index and low socioeconomic status (SES).

OBJECTIVES

This study examined the cross-sectional association between IQ and obesity, exploring the roles of gender, SES and physical activity in this association.

METHODS

Subjects were 235,663 male and 169,259 female adolescents assessed by the Israeli military draft board.

RESULTS

Low IQ was significantly associated with increased odds of obesity among male (odds ratio [OR] = 1.44, 95% confidence interval [CI] = 1.36-1.52) and female adolescents (OR = 1.61, 95% CI = 1.51-1.73); this association was significantly stronger among female adolescents. Sobel tests indicated that physical activity had a significant mediating effect on this association for male and female adolescents, although more strongly for male adolescents. Dividing the sample according to SES, the association between low IQ and obesity was strongest in the high SES group (male adolescents: OR = 1.26, 95% CI = 1.10-1.43, female adolescents: OR = 1.61, 95% CI = 1.38-1.89), even when controlling for physical activity.

CONCLUSIONS

The findings suggest that low IQ is associated with increased odds of obesity, particularly in female adolescents and in adolescents with high SES. Physical activity has a mediating effect on this association, although more strongly for male than for female adolescents. Public health measures on decreasing obesity might focus on these groups.