NR-SLAM: Non-Rigid Monocular SLAM

In this paper we present NR-SLAM, a novel non-rigid monocular SLAM system founded on the combination of a Dynamic Deformation Graph with a Visco-Elastic deformation model. The former enables our system to represent the dynamics of the deforming environment as the camera explores, while the later allows us to model general deformations in a simple way. The presented system is able to automatically initialize and extend a map modeled by a sparse point cloud in deforming environments, that is refined with a sliding-window Deformable Bundle Adjustment. This map serves as base for the estimation of the camera motion and deformation and enables us to represent arbitrary surface topologies, overcoming the limitations of previous methods. To assess the performance of our system in challenging deforming scenarios, we evaluate it in several representative medical datasets. In our experiments, NR-SLAM outperforms previous deformable SLAM systems, achieving millimeter reconstruction accuracy and bringing automated medical intervention closer. For the benefit of the community, we make the source code public.Comment: 12 pages, 7 figures, submited to the IEEE Transactions on Robotics (T-RO

Regulatory polymorphisms in extracellular matrix protease genes and susceptibility to rheumatoid arthritis: a case-control study

Many extracellular matrix (ECM) proteases seem to be important in rheumatoid arthritis (RA) and regulation of their transcription levels is a critical mechanism for controlling their activity. We have investigated, therefore, whether the best-characterized single nucleotide polymorphisms (SNPs) affecting transcription of the ECM proteases that have been related with joint pathology are associated with RA susceptibility. Nine SNPs in eight genes were selected by bibliographic search, including SNPs in the genes encoding matrix metalloproteinase (MMP)1, MMP2, MMP3, MMP7, MMP9, MMP13, plasminogen activator, tissue type (PLAT) and PAI-1. They were studied in a case-control setting that included 550 RA patients and 652 controls of Spanish ancestry from a single center. Genotyping was performed by single-base extension. Only two of the nine SNPs showed significant association with RA susceptibility. RA patients showed increased frequencies of the -7351 T allele of the gene encoding PLAT (36.4% versus 32.1% in controls, p = 0.026) and the -1306 T allele of the gene encoding MMP2 (24.5% versus 20.3% in controls, p = 0.013). These two alleles seemed to cooperate according to an additive model with respect to increased RA susceptibility (p = 0.004), and they were the low-expression alleles of the respective SNPs in a PLAT enhancer and the MMP2 promoter. These findings are in agreement with previous data suggesting that these two ECM proteases have a protective role in RA pathology. Confirmation of these associations will be needed to support these hypotheses. The remaining SNPs did not show association, either individually or collectively. Therefore, although regulatory SNPs in ECM proteases did not show any major effect on RA susceptibility, it was possible to find modest associations that, if replicated, will have interesting implications in the understanding of RA pathology

Removal of imidazolium- and pyridinium-based ionic liquids by Fenton oxidation

This is peer-post-review, pre-copyedit version of an article published in Environmental Science and Pollution Research. The final authenticated version is avilable online at: https://doi.org/10.1007/s11356-017-0867-4The oxidation of imidazolium (1-hexyl-3-methylimidazolium chloride, HmimCl) and pyridinium (1-butyl-4-methylpyridinium chloride, BmpyrCl) ionic liquids (ILs) by Fenton’s reagent has been studied. Complete conversion was achieved for both ILs using the stoichiometric H2O2dose at 70 °C, reaching final TOC conversion values around 45 and 55% for HmimCl and BmpyrCl, respectively. The decrease in hydrogen peroxide dose to substoichiometric concentrations (20–80% stoichiometric dose) caused a decrease in TOC conversion and COD removal and the appearance of hydroxylated oxidation by-products. Working at these substoichiometric H2O2doses allowed the depiction of a possible degradation pathway for the oxidation of both imidazolium and pyridinium ILs. The first step of the oxidation process consisted in the hydroxylation of the ionic liquid by the attack of the ·OH radicals, followed by the ring-opening and the formation of short-chain organic acids, which could be partially oxidized up to CO2and H2O. At H2O2doses near stoichiometric values (80%), the resulting effluents showed non-ecotoxic behaviour and more biodegradable character (BOD5/COD ratio around 0.38 and 0.58 for HmimCl and BmpyrCl, respectively) due to the formation of short-chain organic acids. [Figure not available: see fulltext.]The authors wish to thank the Spanish MINECO and Comunidad de Madrid for the financial support through the projects CTM2016-76564-R and S2013/MAE-2716, respectivel

Lack of association of a variable number of aspartic acid residues in the asporin gene with osteoarthritis susceptibility: case-control studies in Spanish Caucasians

A recent genetic association study has identified a microsatellite in the coding sequence of the asporin gene as a susceptibility factor for osteoarthritis (OA). Alleles of this microsatellite determine the variable number of aspartic acid residues in the amino-terminal end of the asporin protein. Asporin binds directly to the growth factor transforming growth factor beta and inhibits its anabolic effects in cartilage, which include stimulation of collagen and aggrecan synthesis. The OA-associated allele, with 14 aspartic acid residues, inhibits the anabolic effects of transforming growth factor beta more strongly than other asporin alleles, leading to increased OA liability. We have explored whether the association found in several cohorts of Japanese hip OA and knee OA patients was also present in Spanish Caucasians. We studied patients that had undergone total joint replacement for primary OA in the hip (n = 303) or the knee (n = 188) and patients with hand OA (n = 233), and we compared their results with controls (n = 294) lacking overt OA clinical symptoms. No significant differences were observed in any of the multiple comparisons performed, which included global tests of allele frequency distributions and specific comparisons as well as stratification by affected joint and by sex. Our results, together with reports from the United Kingdom and Greece, indicate that the stretch of aspartic acid residues in asporin is not an important factor in OA susceptibility among European Caucasians. It remains possible that lifestyle, environmental or genetic differences allow for an important effect of asporin variants in other ethnic groups as has been reported in the Japanese, but this should be supported by additional studies

Smartphone sensors for monitoring cancer-related Quality of Life: App design, EORTC QLQ-C30 mapping and feasibility study in healthy subjects

[EN] Quality of life (QoL) indicators are now being adopted as clinical outcomes in clinical trials on cancer treatments. Technology-free daily monitoring of patients is complicated, time-consuming and expensive due to the need for vast amounts of resources and personnel. The alternative method of using the patients¿ own phones could reduce the burden of continuous monitoring of cancer patients in clinical trials. This paper proposes monitoring the patients¿ QoL by gathering data from their own phones. We considered that the continuous multiparametric acquisition of movement, location, phone calls, conversations and data use could be employed to simultaneously monitor their physical, psychological, social and environmental aspects. An open access phone app was developed (Human Dynamics Reporting Service (HDRS)) to implement this approach. We here propose a novel mapping between the standardized QoL items for these patients, the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and define HDRS monitoring indicators. A pilot study with university volunteers verified the plausibility of detecting human activity indicators directly related to QoL.Funding for this study was provided by the authors' various departments, and partially by the CrowdHealth Project (Collective Wisdom Driving Public Health Policies (727560)) and the MTS4up project (DPI2016-80054-R).Asensio Cuesta, S.; Sánchez-García, Á.; Conejero, JA.; Sáez Silvestre, C.; Rivero-Rodriguez, A.; Garcia-Gomez, JM. (2019). Smartphone sensors for monitoring cancer-related Quality of Life: App design, EORTC QLQ-C30 mapping and feasibility study in healthy subjects. International Journal of Environmental research and Public Health. 16(3):1-18. https://doi.org/10.3390/ijerph16030461S118163Number of Smartphone Users Worldwide from 2014 to 2020 (in Billions)https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/Mirkovic, J., Kaufman, D. R., & Ruland, C. M. (2014). Supporting Cancer Patients in Illness Management: Usability Evaluation of a Mobile App. JMIR mHealth and uHealth, 2(3), e33. doi:10.2196/mhealth.3359Xing Su, Hanghang Tong, & Ping Ji. (2014). Activity recognition with smartphone sensors. Tsinghua Science and Technology, 19(3), 235-249. doi:10.1109/tst.2014.6838194Schmitz Weiss, A. (2013). Exploring News Apps and Location-Based Services on the Smartphone. Journalism & Mass Communication Quarterly, 90(3), 435-456. doi:10.1177/1077699013493788Higgins, J. P. (2016). Smartphone Applications for Patients’ Health and Fitness. The American Journal of Medicine, 129(1), 11-19. doi:10.1016/j.amjmed.2015.05.038Rivenson, Y., Ceylan Koydemir, H., Wang, H., Wei, Z., Ren, Z., Günaydın, H., … Ozcan, A. (2018). Deep Learning Enhanced Mobile-Phone Microscopy. ACS Photonics, 5(6), 2354-2364. doi:10.1021/acsphotonics.8b00146Priye, A., Ball, C. S., & Meagher, R. J. (2018). Colorimetric-Luminance Readout for Quantitative Analysis of Fluorescence Signals with a Smartphone CMOS Sensor. Analytical Chemistry, 90(21), 12385-12389. doi:10.1021/acs.analchem.8b03521Measuring Quality of Life for Cancer Patients: Where Are We Today and Where Are We Headed Tomorrow?http://blog.mdsol.com/measuring-quality-of-life-for-cancer-patients-where-are-we-today-and-where-are-we-headed-tomorrow/Zulueta, J., Piscitello, A., Rasic, M., Easter, R., Babu, P., Langenecker, S. A., … Leow, A. (2018). Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study. Journal of Medical Internet Research, 20(7), e241. doi:10.2196/jmir.9775Caruso, R., GiuliaNanni, M., Riba, M. B., Sabato, S., & Grassi, L. (2017). Depressive Spectrum Disorders in Cancer: Diagnostic Issues and Intervention. A Critical Review. Current Psychiatry Reports, 19(6). doi:10.1007/s11920-017-0785-7THE WHOQOL GROUP. (1998). Development of the World Health Organization WHOQOL-BREF Quality of Life Assessment. Psychological Medicine, 28(3), 551-558. doi:10.1017/s0033291798006667Basic Issues Concerning Health-Related Quality of Life. (2017). Central European Journal of Urology, 70(2). doi:10.5173/ceju.2017.923Sloan, J. A. (2011). Metrics to Assess Quality of Life After Management of Early-Stage Lung Cancer. The Cancer Journal, 17(1), 63-67. doi:10.1097/ppo.0b013e31820e15dcBordoni, R., Ciardiello, F., von Pawel, J., Cortinovis, D., Karagiannis, T., Ballinger, M., … Rittmeyer, A. (2018). Patient-Reported Outcomes in OAK: A Phase III Study of Atezolizumab Versus Docetaxel in Advanced Non–Small-cell Lung Cancer. Clinical Lung Cancer, 19(5), 441-449.e4. doi:10.1016/j.cllc.2018.05.011Hartkopf, A. D., Graf, J., Simoes, E., Keilmann, L., Sickenberger, N., Gass, P., … Wallwiener, M. (2017). Electronic-Based Patient-Reported Outcomes: Willingness, Needs, and Barriers in Adjuvant and Metastatic Breast Cancer Patients. JMIR Cancer, 3(2), e11. doi:10.2196/cancer.6996Wallwiener, M., Matthies, L., Simoes, E., Keilmann, L., Hartkopf, A. D., Sokolov, A. N., … Brucker, S. Y. (2017). Reliability of an e-PRO Tool of EORTC QLQ-C30 for Measurement of Health-Related Quality of Life in Patients With Breast Cancer: Prospective Randomized Trial. Journal of Medical Internet Research, 19(9), e322. doi:10.2196/jmir.8210Gresham, G., Hendifar, A. E., Spiegel, B., Neeman, E., Tuli, R., Rimel, B. J., … Shinde, A. M. (2018). Wearable activity monitors to assess performance status and predict clinical outcomes in advanced cancer patients. npj Digital Medicine, 1(1). doi:10.1038/s41746-018-0032-6BOHANNON, R. W. (1997). Comfortable and maximum walking speed of adults aged 20—79 years: reference values and determinants. Age and Ageing, 26(1), 15-19. doi:10.1093/ageing/26.1.15Pérez-García, V. M., Fitzpatrick, S., Pérez-Romasanta, L. A., Pesic, M., Schucht, P., Arana, E., & Sánchez-Gómez, P. (2016). Applied mathematics and nonlinear sciences in the war on cancer. Applied Mathematics and Nonlinear Sciences, 1(2), 423-436. doi:10.21042/amns.2016.2.00036Shin, W., Song, S., Jung, S.-Y., Lee, E., Kim, Z., Moon, H.-G., … Lee, J. E. (2017). The association between physical activity and health-related quality of life among breast cancer survivors. Health and Quality of Life Outcomes, 15(1). doi:10.1186/s12955-017-0706-9Wearable Fitness Monitors Useful in Cancer Treatment, Study Findswww.sciencedaily.com/releases/2018/05/180501130856.htmBade, B. C., Brooks, M. C., Nietert, S. B., Ulmer, A., Thomas, D. D., Nietert, P. J., … Silvestri, G. A. (2016). Assessing the Correlation Between Physical Activity and Quality of Life in Advanced Lung Cancer. Integrative Cancer Therapies, 17(1), 73-79. doi:10.1177/1534735416684016Fortner, B. V., Stepanski, E. J., Wang, S. C., Kasprowicz, S., & Durrence, H. H. (2002). Sleep and Quality of Life in Breast Cancer Patients. Journal of Pain and Symptom Management, 24(5), 471-480. doi:10.1016/s0885-3924(02)00500-6Mishra, S. I., Scherer, R. W., Snyder, C., Geigle, P., & Gotay, C. (2014). Are Exercise Programs Effective for Improving Health-Related Quality of Life Among Cancer Survivors? A Systematic Review and Meta-Analysis. Oncology Nursing Forum, 41(6), E326-E342. doi:10.1188/14.onf.e326-e342Ratcliff, C. G., Lam, C. Y., Arun, B., Valero, V., & Cohen, L. (2014). Ecological momentary assessment of sleep, symptoms, and mood during chemotherapy for breast cancer. Psycho-Oncology, 23(11), 1220-1228. doi:10.1002/pon.3525Cox, S. M., Lane, A., & Volchenboum, S. L. (2018). Use of Wearable, Mobile, and Sensor Technology in Cancer Clinical Trials. JCO Clinical Cancer Informatics, (2), 1-11. doi:10.1200/cci.17.00147Brown, W., Yen, P.-Y., Rojas, M., & Schnall, R. (2013). Assessment of the Health IT Usability Evaluation Model (Health-ITUEM) for evaluating mobile health (mHealth) technology. Journal of Biomedical Informatics, 46(6), 1080-1087. doi:10.1016/j.jbi.2013.08.001Darlow, S., & Wen, K.-Y. (2016). Development testing of mobile health interventions for cancer patient self-management: A review. 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Circulating GDF11 levels are decreased with age but are unchanged with obesity and type 2 diabetes

Growth differentiation factor 11 (GDF11) is a member of the transforming growth factor β (TGFβ) superfamily which declines with age and exerts anti‐aging regenerative effects in skeletal muscle in mice. However, recent data in humans and mice are conflicting casting doubts about its true functional actions. The aim of the present study was to compare the circulating concentrations of GDF11 in individuals of different ages as well as body weight and glycemic status. Serum concentrations of GDF11 were measured by ELISA in 319 subjects. There was a significant increase in GDF11 concentrations in people in the 41‐50 y group and a decline in the elder groups (61‐70 and 71‐80 y groups, P=0.008 for the comparison between all age groups). However, no significant correlation between fat‐free mass index (FFMI), a formula used to estimate the amount of muscle mass in relation to height, and logGDF11 was observed (r=0.08, P=0.197). Moreover, no significant differences in circulating concentrations of GDF11 regarding obesity or glycemic status were found. Serum GDF11 concentrations in humans decrease in older ages being unaltered in obesity and T2D. Further studies should determine the exact pathophysiological role of GDF11 in aging

Circulating concentrations of GDF11 are positively associated with TSH levels in humans

Growth differentiation factor 11 (GDF11) is a member of the transforming growth factor (TGF)-beta superfamily which declines with age and has been proposed as an anti-aging factor with regenerative effects in skeletal muscle in mice. However, recent data in humans and mice are conflicting, casting doubts about its true functional actions. The aim of the present study was to analyze the potential involvement of GFD11 in energy homeostasis in particular in relation with thyroid hormones. Serum concentrations of GDF11 were measured by enzyme-linked immunosorbent assay (ELISA) in 287 subjects. A highly significant positive correlation was found between GDF11 and thyroid-stimulating hormone (TSH) concentrations (r = 0.40, p 0.05 for both) with GDF11 levels. In a multiple linear regression analysis, the model that best predicted logGDF11 included logTSH, leptin, body mass index (BMI), age, and C-reactive protein (logCRP). This model explained 37% of the total variability of logGDF11 concentrations (p < 0.001), with only logTSH being a significant predictor of logGDF11. After segregating subjects by TSH levels, those within the low TSH group exhibited significantly decreased (p < 0.05) GDF11 concentrations as compared to the normal TSH group or the high TSH group. A significant correlation of GDF11 levels with logCRP (r = 0.19, p = 0.025) was found. GDF11 levels were not related to the presence of hypertension or cardiopathy. In conclusion, our results show that circulating concentrations of GDF11 are closely associated with TSH concentrations and reduced in subjects with low TSH levels. However, GDF11 is not related to the regulation of energy expenditure. Our data also suggest that GDF11 may be involved in the regulation of inflammation, without relation to cardiac function. Further research is needed to elucidate the role of GDF11 in metabolism and its potential involvement in thyroid pathophysiology

Synaptic Zn2+ potentiates the effects of cocaine on striatal dopamine neurotransmission and behavior

Cocaine binds to the dopamine (DA) transporter (DAT) to regulate cocaine reward and seeking behavior. Zinc (Zn2+) also binds to the DAT, but the in vivo relevance of this interaction is unknown. We found that Zn2+ concentrations in postmortem brain (caudate) tissue from humans who died of cocaine overdose were significantly lower than in control subjects. Moreover, the level of striatal Zn2+ content in these subjects negatively correlated with plasma levels of benzoylecgonine, a cocaine metabolite indicative of recent use. In mice, repeated cocaine exposure increased synaptic Zn2+ concentrations in the caudate putamen (CPu) and nucleus accumbens (NAc). Cocaine-induced increases in Zn2+ were dependent on the Zn2+ transporter 3 (ZnT3), a neuronal Zn2+ transporter localized to synaptic vesicle membranes, as ZnT3 knockout (KO) mice were insensitive to cocaine-induced increases in striatal Zn2+. ZnT3 KO mice showed significantly lower electrically evoked DA release and greater DA clearance when exposed to cocaine compared to controls. ZnT3 KO mice also displayed significant reductions in cocaine locomotor sensitization, conditioned place preference (CPP), self-administration, and reinstatement compared to control mice and were insensitive to cocaine-induced increases in striatal DAT binding. Finally, dietary Zn2+ deficiency in mice resulted in decreased striatal Zn2+ content, cocaine locomotor sensitization, CPP, and striatal DAT binding. These results indicate that cocaine increases synaptic Zn2+ release and turnover/metabolism in the striatum, and that synaptically released Zn2+ potentiates the effects of cocaine on striatal DA neurotransmission and behavior and is required for cocaine-primed reinstatement. In sum, these findings reveal new insights into cocaine's pharmacological mechanism of action and suggest that Zn2+ may serve as an environmentally derived regulator of DA neurotransmission, cocaine pharmacodynamics, and vulnerability to cocaine use disorders

New Sequence Variants in HLA Class II/III Region Associated with Susceptibility to Knee Osteoarthritis Identified by Genome-Wide Association Study

Osteoarthritis (OA) is a common disease that has a definite genetic component. Only a few OA susceptibility genes that have definite functional evidence and replication of association have been reported, however. Through a genome-wide association study and a replication using a total of ∼4,800 Japanese subjects, we identified two single nucleotide polymorphisms (SNPs) (rs7775228 and rs10947262) associated with susceptibility to knee OA. The two SNPs were in a region containing HLA class II/III genes and their association reached genome-wide significance (combined P = 2.43×10−8 for rs7775228 and 6.73×10−8 for rs10947262). Our results suggest that immunologic mechanism is implicated in the etiology of OA