449 research outputs found
MOUSSE: scaling MOdelling and verification to complex heterogeneoUS embedded Systems Evolution
No full textThis work proposes an advanced methodology based on an open source virtual prototyping framework for verification of complex Heterogeneous Embedded Systems (HES). It supports early rapid modelling of complex HES through smooth refinements, an open interface based on IP-XACT extensions for secure composition of HES components, and automatic testbench generation over different abstraction levels
MosquirixTM malaria vaccine: an evaluation of patients' willingness to pay in Cameroon
No full textObjectives: The purpose of this study was to determine the average price that a patient living in Cameroon would be willing to pay for the MosquirixTM vaccine and the factors influencing the proposed price. Study design: Cross-sectional study Methods: Data were collected using a semi-open questionnaire in 5 hospitals in Cameroon. This study included all persons over 18 years who came for consultation in one of the 5 selected hospitals during the study period (from 02th to 14th April 2018 and from 02th to 22th July 2018). The factors associated with the price of the vaccine proposed by the patient were determined by linear multiple regression analysis. The average price was determined based on the patient's income and the percentage of that income proposed for the purchase of the vaccine. Results: We collected data from 1,187 participants aged 18 to 80 years. The average price that Cameroonian patients were willing to pay for the MosquirixTM vaccine was 1,514±475 XAF (2.3±0.73 Euro). The minimum and maximum purchase price of the vaccine were 1,178 XAF (1.8 Euro) and 1,850 XAF (2.8 Euro) respectively. We also noted that patients were willing to spend an average of 1.34% of their income on the vaccine. This percentage of income was significantly (lt;0.001) associated with the respondents' income, the fact that they had been consulted at least once for malaria in the 12 months preceding the survey (lt;0.001) and the fact that the respondent had at least one under- five year child (lt;0.001). Conclusion: Factors associated with the average price are elements that should be strongly considered by policy makers to introduce this vaccine in Cameroon. This pilot study can serve as a framework for a potential national population-based study
Rap and rapalogs induce TRPML1- and Ca<sup>2+</sup>-dependent TFEB nuclear translocation in TRPML1-overexpressing cells.
No full text(A) Rap (5 μM) and Tem (5 μM) induced TFEB nuclear translocation in TFEB-GFP stable cells overexpressing mCherry-TRPML1 (asterisks). TFEB nuclear translocation was not seen with Zota (5 μM). Scale bar = 10 μm. (B) Summary of rapalog effects on TFEB nuclear translocation. (C) Blockade of Tem-induced TFEB translocation by ML-SI3 (10 μM). Scale bar = 10 μm. (D) Quantification of ML-SI3 effect. (E) BAPTA-AM (5 μM, 1 h pretreatment) blocked Tem-induced TFEB nuclear translocation. (F) Tem (5 μM) induced TFEB nuclear translocation in TFEB-GFP stable cells overexpressing mCherry-TRPML2. Quantification is shown in the right panel. (G) The effects of Tem (5 μM, 2 h) and ML-SA1 (5 μM, 2 h) on TFEB nuclear translocation in TFEB-GFP stable cells that were transfected with mCherry-TRPML3. Data are quantified in the left panel. mCherry-positive cells are indicated by asterisks. Scale bar = 10 μm. Data shown in B and D–G were obtained from 30 to 40 cells from at least 3 independent experiments and are presented as mean ± SEM. The individual data supporting B and D–G can be found in S1 Data. ***P < 0.001, one-way ANOVA. BAPTA-AM, 1,2-Bis(2-aminophenoxy)ethane-N,N,N’,N’-tetraacetic acid tetrakis (acetoxymethyl ester); CTRL, control; Cyt, cytoplasm; Defo, deforolimus; Eve, everolimus; GFP, green fluorescent protein; mCh, mCherry; mCherry, monomeric red fluorescent protein; ML1, TRPML1; ML-SA1, TRPML1 synthetic agonist 1; ML-SI3, TRPML1 synthetic inhibitor 3; Nuc, nuclear; O/E, overexpression; Rap, rapamycin; Seco, seco-rapamycin; Tem, temsirolimus; TFEB, transcription factor EB; ML1/TRPML1, transient receptor potential channel mucolipin 1; Zota, zotarolimus.</p
Rap and rapalogs activate TRPML1 in an mTOR-independent manner.
No full text(A) Effect of Torin-1 (10 μM), a potent ATP-competitive mTOR inhibitor, on ITRPML1. (B) Tem (10 μM) and Eve (10 μM) stimulation of ITRPML1. (C) No effects of Defo (10 μM), Zota (10 μM), and Seco-Rap (a Rap metabolite, 10 μM) on ITRPML1 measured at −120 mV. (D) Summary of differential effects of rapalogs on ITRPML1. Data are presented as mean ± SEM. (E) Rap and rapalogs inhibited mTOR activity, which was assayed by phosphorylation of the mTOR substrate S6K at Thr 389. (F) Rap activated ITRPML1 in cells transfected with WT mTOR (left) and a kinase-dead mTORD2357E mutant (right). (G) mTOR mutants did not alter Rap sensitivity of ITRPML1. Data are presented as mean ± SEM. (H) Rap activated ITRPML1 in both WT (left) and TSC2 KO (mTOR constitutively active, right) MEF cells. Inset shows the lack of TSC2 proteins in the TSC2 KO. (I) Rap effects on ITRPML1 in RagA and B KO (mTOR deficient, right) MEF cells. Inset shows the lack of RagA proteins in the RagA and B KO. (J) Rap activated larger endogenous ITRPML1 in p18 KO (right) compared with WT (left) HEK293 cells. Inset shows the lack of p18 proteins in the p18 KO. Note that in p18 KO cells, endogenous TFEB was localized in the nucleus, presumably due to mTOR deficiency (see S2K Fig), which in turn increased ITRPML1, because TRPML1 is the one of major target genes of TFEB [10]. Only representative data are presented in A–C, F, and H–J. The individual data underlying D and G can be found in S1 Data. CTRL, control; Defo, deforolimus; Eve, everolimus; HEK293, human embryonic kidney 293 cell; KO, knockout; MEF, mouse embryonic fibroblast; mTOR, mechanistic target of rapamycin; p18, late endosomal/lysosomal adaptor, MAPK and mTOR activator 1 (LAMTOR1); Rag, Ras-related GTP-binding protein; Rap, rapamycin; Seco, seco-rapamycin; S6K, S6 kinase; Tem, temsirolimus; TFEB, transcription factor EB; Thr 389, threonine 389; TRPML1, transient receptor potential channel mucolipin 1; TSC2, tuberous sclerosis complex 2; WT, wild type; Zota, zotarolimus.</p
The Existence of Pure-Strategy Nash Equilibrium in Games with Payoffs that are Not Quasiconcave
No full textThe pace and distribution of health improvements during the last 40 years: some preliminary results
No full textOPTIMUM CONDITIONS FOR DIFFERENTIAL SAR INTERFEROMETRY TECHNIQUE TO ESTIMATE HIMALAYAN GLACIER VELOCITY
No full textDifferential SAR Interferometry (DInSAR) is the process of differencing two Interferograms for measuring surface movement with an accuracy of millimeter range. The DInSAR process can be applied to observe glacier movement, earthquake deformations, volcanic activities and rate of subsidence or uplift caused due to the extraction of groundwater or coal. By using single pass interferometry technique we can also generate accurate DEM. In this paper, we are presenting the movement of a Chhota Shigri glacier with the help two pass DInSAR technique and mainly we concentrated on the optimum conditions for estimating glacier movement using DInSAR. We got good coherence and Interferogram fringes for L-band sensor with less temporal baseline. Therefore, we generated glacier velocity using ALOS-2 data with 14 days temporal baseline. Initially, we generated Interferogram (defo-pair) by taking 10th March 2015 image as a master and 24th March 2015 image as a slave. But this generated Interferogram also having topographic information and atmospheric errors with the displacement component. Therefore, we used SRTM DEM for removing topographic information from the Interferogram. Because we are using L-band data, results may not be affected by troposphere. Maximum glacier velocity we observed in the accumulation zone as 7.285 cm/day in the month of March and while it’s moving towards ablation zone the glacier velocity is decreasing
Evaluation of moments of ratios of quadratic forms in normal variables and related statistics
No full textThe correlates of infant and childhood mortality
No full textThis paper has two main goals. The first is to review the context for studying infant mortality, which includes a review of the theoretical framework, the covariates used to examine mortality over the first 60 months of life, and the major findings of empirical studies. Second, the paper adds some new empirical evidence that comes from the longitudinal reconstitution of church registers of Bejsce parish, located in the south of Poland. This rich database allows for an analysis of mortality trends of cohorts born between the 18th and 20th centuries in the parish. The analysis includes a reconstruction of descriptive measures of infant and childhood mortality, and a hazard model of mortality over the first 60 months of life. The hazard model has been calculated for each cohort separately in order to demonstrate the change in the relative importance of analyzed factors during the process of mortality decline in the parish. Obtained mortality patterns are discussed with reference to the theoretical context presented in the first part of the paper.event history analysis, historical population, infant and child mortality, multilevel model, parish registers
The Role of Functional Cerebral Asymmetry in Symptoms of Bipolar Disorder: A Scoping Review Protocol
No full textMental disorders are among the largest contributors to the global burden of disease (Vos et al., 2015; Vos et al., 2012). The Global Burden of Disease study attributes 21.2% of the total number of years lived with disability (YLD) to mental disorders, whereas a revised estimate attributes as much as 32.4% to mental disorders, making it the number one contributor to the global burden of disease when it comes to YLD (Vigo et al., 2016; Vos et al., 2015). Bipolar Disorders (BD) rank as the 17th leading cause of YLD and pose one of the highest suicidality rates of any mental disorder with a lifetime prevalence of 33.9% for attempted suicide (Dong et al., 2019; Vos et al., 2015). Additionally, loss of life due to premature mortality as a consequence of an increased risk for other medical conditions or suicide is estimated to be between 8–14 years for patients with BD (Chang et al., 2011; Kessing et al., 2015; Laursen, 2011). The World Mental Health Survey Initiative reported a worldwide lifetime prevalence of 2.4% for BD (Merikangas et al., 2011).
BD are classified under the overarching category of Bipolar and Related Disorders in the Diagnostic and Statistical Manual for Mental Disorders, 5th edition (DSM-5). The defining feature of all BD is a manic or hypomanic episode that is characterized by abnormally and persistently elevated, expansive, or irritable mood as well as increased goal-directed activity or energy. Additionally, frequently observed symptoms include inflated self-esteem or grandiosity, a decreased need for sleep, talkativeness or pressured speech, flight of ideas or racing thoughts, distractibility, psychomotor agitation and/or engagement in risky or reckless behavior. A hypomanic episode is distinct from a manic episode mainly due to its lesser severity and potentially lower time duration. Importantly, in the majority of patients and commonly in a biphasic relation to a manic or hypomanic episode is the occurrence of a major depressive episode that is characterized by prolonged symptoms of depressed mood and/or anhedonia as well as symptoms such as significant weight loss or gain, insomnia or hypersomnia, psychomotor agitation or retardation, fatigue or loss of energy, feelings of worthlessness, concentration difficulties and/or suicidal ideation. (American Psychiatric Association, 2013) In the International Classification of Diseases and related health problems, 11th revision (ICD-11) BD are classified under Bipolar or related disorders with a congruent description of the symptomology found in the DSM-5 (World Health Organization, 2019).
Etiological models of BD propose a complex interplay between a genetic diathesis of polygenic origin and environmental stressors, such as early trauma, substance or drug use and/or stressful life events that lead to neuronal changes and alteration in brain circuitry, which give rise to the symptomatology of BD (McIntyre et al., 2020; Vieta et al., 2018). The majority of pathophysiological models for BD emphasize a dysregulation in the monoamine neurotransmitter systems, like the serotonergic, noradrenergic and in particular dopaminergic system as well as a dysregulation in endocrine systems, such as the hypothalamic–pituitary–thyroid and hypothalamic–pituitary–adrenal axes – with consideration to the substantial interdependence between these systems (Carvalho et al., 2020; Vieta et al., 2018). A prominent model of pathophysiology that dates back to the 1970s proposes a dysregulation in dopaminergic neural transmission, in which hyperdopaminergia and hypodopaminergia can lead to manic and depressive symptomatology, respectively. This model is primarily corroborated by pharmacological evidence as dopamine agonists can induce mania and dopamine antagonists are an effective treatment of acute mania (Ashok et al., 2017; Cousins et al., 2009; Tissot, 1975; Wittenborn, 1974). Additionally, first-line drug treatments such as sodium valproate or lithium without direct affinity to dopamine receptors might indirectly regulate dopaminergic neural transmission (Cousins et al., 2009). A more complicated picture emerges in the treatment of bipolar depression, in which both dopamine agonists and antagonists show some beneficial effects – this highlights the complexity of dopamine’s involvement in BD symptomology and a lack of comprehensive, dopamine pathway-specific mechanistic understanding (Ashok et al., 2017; Cousins et al., 2009).
Not mutually exclusive and even potentially complementary to the aforementioned model is the pathophysiological model of functional cerebral asymmetry (FCA) with manic and hypomanic episodes as a consequence of prolonged left hemispheric dominance and major depressive episodes as a consequence of prolonged right hemispheric dominance (Levenberg et al., 2021). The overlap between the two models might be due to neurochemical asymmetries, in which dopaminergic neural transmission is dominant in the left hemisphere (Toga & Thompson, 2003). FCA describes an asymmetric activity pattern between homologous areas in the hemispheres during resting-state or task performance that is measured with brain imaging techniques. Importantly, hemispheric asymmetries are graded rather than binary, thus both hemispheres are active in all resting-states and task performances, although one hemisphere might dominate during a specific state or task performance (Esteves et al., 2020). Interestingly, FCA was proposed to play a key role in manic and major depressive episodes of BD several decades ago. In this early pathophysiological model, the brain supposedly becomes “stuck” in either a dominant left hemispheric processing mode leading to mania or right hemispheric processing mode leading to depression as a consequence of a “sticky” interhemispheric switch in patients with BD (Pettigrew & Miller, 1998). Importantly, the more recent pathophysiological model proposes dysfunctional signaling from the parvocellular neurons of the paraventricular hypothalamic nucleus (PVN), which mediates functional hemispheric lateralization, to result in prolonged FCA giving rise to the symptomology of BD (Levenberg et al., 2021).
This scoping review poses the question of how FCA relates to manic or depressive symptoms in patients with BD. The rationale for this scoping review is the rising burden of disease attributable to mental disorders in general and affective disorders in particular as well as the renewed interest in FCA as a pathophysiological model of BD and a lack of systematic or scoping reviews on the topic. On the 22nd of July 2021 a literature search found no pre-registered or published scoping or systematic reviews on the relationship between FCA and symptoms of BD on the Open Science Framework, Joanna Briggs Institute Evidence Synthesis and Epistemonikos or PubMed, Web of Science and PsycINFO databases. The objective of this scoping review is to identify the role of FCA in manic or depressive symptoms in patients with BD. A better understanding of its role in these opposing symptom clusters might inform diagnosis as a biomarker, prevention through early detection and treatment as a theoretical underpinning of neurofeedback training and brain stimulation protocols.
Ashok, A. H., Marques, T. R., Jauhar, S., Nour, M. M., Goodwin, G. M., Young, A. H., & Howes, O. D. (2017). The dopamine hypothesis of bipolar affective disorder: the state of the art and implications for treatment. Mol Psychiatry, 22(5), 666-679. https://doi.org/10.1038/mp.2017.16
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Carvalho, A. F., Firth, J., & Vieta, E. (2020). Bipolar Disorder. N Engl J Med, 383(1), 58-66. https://doi.org/10.1056/NEJMra1906193
Chang, C. K., Hayes, R. D., Perera, G., Broadbent, M. T., Fernandes, A. C., Lee, W. E., Hotopf, M., & Stewart, R. (2011). Life expectancy at birth for people with serious mental illness and other major disorders from a secondary mental health care case register in London. PLoS One, 6(5), e19590. https://doi.org/10.1371/journal.pone.0019590
Cousins, D. A., Butts, K., & Young, A. H. (2009). The role of dopamine in bipolar disorder. Bipolar Disord, 11(8), 787-806. https://doi.org/10.1111/j.1399-5618.2009.00760.x
Dong, M., Lu, L., Zhang, L., Zhang, Q., Ungvari, G. S., Ng, C. H., Yuan, Z., Xiang, Y., Wang, G., & Xiang, Y. T. (2019). Prevalence of suicide attempts in bipolar disorder: a systematic review and meta-analysis of observational studies. Epidemiol Psychiatr Sci, 29, e63. https://doi.org/10.1017/S2045796019000593
Esteves, M., Lopes, S. S., Almeida, A., Sousa, N., & Leite-Almeida, H. (2020). Unmasking the relevance of hemispheric asymmetries-Break on through (to the other side). Prog Neurobiol, 192, 101823. https://doi.org/10.1016/j.pneurobio.2020.101823
Kessing, L. V., Vradi, E., & Andersen, P. K. (2015). Life expectancy in bipolar disorder. Bipolar Disord, 17(5), 543-548. https://doi.org/10.1111/bdi.12296
Laursen, T. M. (2011). Life expectancy among persons with schizophrenia or bipolar affective disorder. Schizophr Res, 131(1-3), 101-104. https://doi.org/10.1016/j.schres.2011.06.008
Levenberg, K., Hajnal, A., George, D. R., & Saunders, E. F. H. (2021). Prolonged functional cerebral asymmetry as a consequence of dysfunctional parvocellular paraventricular hypothalamic nucleus signaling: An integrative model for the pathophysiology of bipolar disorder. Med Hypotheses, 146, 110433. https://doi.org/10.1016/j.mehy.2020.110433
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Vos, T., Barber, R. M., Bell, B., Bertozzi-Villa, A., Biryukov, S., Bolliger, I., Charlson, F., Davis, A., Degenhardt, L., Dicker, D., Duan, L., Erskine, H., Feigin, V. L., Ferrari, A. J., Fitzmaurice, C., Fleming, T., Graetz, N., Guinovart, C., Haagsma, J., Hansen, G. M., Hanson, S. W., Heuton, K. R., Higashi, H., Kassebaum, N., Kyu, H., Laurie, E., Liang, X., Lofgren, K., Lozano, R., MacIntyre, M. F., Moradi-Lakeh, M., Naghavi, M., Nguyen, G., Odell, S., Ortblad, K., Roberts, D. A., Roth, G. A., Sandar, L., Serina, P. T., Stanaway, J. D., Steiner, C., Thomas, B., Vollset, S. E., Whiteford, H., Wolock, T. M., Ye, P., Zhou, M., Ãvila, M. A., Aasvang, G. M., Abbafati, C., Ozgoren, A. A., Abd-Allah, F., Aziz, M. I. A., Abera, S. F., Aboyans, V., Abraham, J. P., Abraham, B., Abubakar, I., Abu-Raddad, L. J., Abu-Rmeileh, N. M. E., Aburto, T. C., Achoki, T., Ackerman, I. N., Adelekan, A., Ademi, Z., Adou, A. K., Adsuar, J. C., Arnlov, J., Agardh, E. E., Al Khabouri, M. J., Alam, S. S., Alasfoor, D., Albittar, M. I., Alegretti, M. A., Aleman, A. V., Alemu, Z. A., Alfonso-Cristancho, R., Alhabib, S., Ali, R., Alla, F., Allebeck, P., Allen, P. J., AlMazroa, M. A., Alsharif, U., Alvarez, E., Alvis-Guzman, N., Ameli, O., Amini, H., Ammar, W., Anderson, B. O., Anderson, H. R., Antonio, C. A. T., Anwari, P., Apfel, H., Arsenijevic, V. S. A., Artaman, A., Asghar, R. J., Assadi, R., Atkins, L. S., Atkinson, C., Badawi, A., Bahit, M. C., Bakfalouni, T., Balakrishnan, K., Balalla, S., Banerjee, A., Barker-Collo, S. L., Barquera, S., Barregard, L., Barrero, L. H., Basu, S., Basu, A., Baxter, A., Beardsley, J., Bedi, N., Beghi, E., Bekele, T., Bell, M. L., Benjet, C., Bennett, D. A., Bensenor, I. M., Benzian, H., Bernabe, E., Beyene, T. J., Bhala, N., Bhalla, A., Bhutta, Z., Bienhoff, K., Bikbov, B., Abdulhak, A. B., Blore, J. D., Blyth, F. M., Bohensky, M. A., Basara, B. B., Borges, G., Bornstein, N. M., Bose, D., Boufous, S., Bourne, R. R., Boyers, L. N., Brainin, M., Brauer, M., Brayne, C. E. G., Brazinova, A., Breitborde, N. J. K., Brenner, H., Briggs, A. D. M., Brooks, P. M., Brown, J., Brugha, T. S., Buchbinder, R., Buckle, G. C., Bukhman, G., Bulloch, A. G., Burch, M., Burnett, R., Cardenas, R., Cabral, N. L., Nonato, I. R. C., Campuzano, J. C., Carapetis, J. R., Carpenter, D. O., Caso, V., Castaneda-Orjuela, C. A., Catala-Lopez, F., Chadha, V. K., Chang, J.-C., Chen, H., Chen, W., Chiang, P. P., Chimed-Ochir, O., Chowdhury, R., Christensen, H., Christophi, C. A., Chugh, S. S., Cirillo, M., Coggeshall, M., Cohen, A., Colistro, V., Colquhoun, S. M., Contreras, A. G., Cooper, L. T., Cooper, C., Cooperrider, K., Coresh, J., Cortinovis, M., Criqui, M. H., Crump, J. A., Cuevas-Nasu, L., Dandona, R., Dandona, L., Dansereau, E., Dantes, H. G., Dargan, P. I., Davey, G., Davitoiu, D. V., Dayama, A., De la Cruz-Gongora, V., de la Vega, S. F., De Leo, D., del Pozo-Cruz, B., Dellavalle, R. P., Deribe, K., Derrett, S., Des Jarlais, D. C., Dessalegn, M., deVeber, G. A., Dharmaratne, S. D., Diaz-Torne, C., Ding, E. L., Dokova, K., Dorsey, E. R., Driscoll, T. R., Duber, H., Durrani, A. M., Edmond, K. M., Ellenbogen, R. G., Endres, M., Ermakov, S. P., Eshrati, B., Esteghamati, A., Estep, K., Fahimi, S., Farzadfar, F., Fay, D. F. J., Felson, D. T., Fereshtehnejad, S.-M., Fernandes, J. G., Ferri, C. P., Flaxman, A., Foigt, N., Foreman, K. J., Fowkes, F. G. R., Franklin, R. C., Furst, T., Futran, N. D., Gabbe, B. J., Gankpe, F. G., Garcia-Guerra, F. A., Geleijnse, J. M., Gessner, B. D., Gibney, K. B., Gillum, R. F., Ginawi, I. A., Giroud, M., Giussani, G., Goenka, S., Goginashvili, K., Gona, P., de Cosio, T. G., Gosselin, R. A., Gotay, C. C., Goto, A., Gouda, H. N., Guerrant, R. l., Gugnani, H. C., Gunnell, D., Gupta, R., Gupta, R., Gutierrez, R. A., Hafezi-Nejad, N., Hagan, H., Halasa, Y., Hamadeh, R. R., Hamavid, H., Hammami, M., Hankey, G. J., Hao, Y., Harb, H. L., Haro, J. M., Havmoeller, R., Hay, R. 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