820 research outputs found

    Using Latent Class Analyses to Examine Health Disparities among Young Children in Socially Disadvantaged Families during the COVID-19 Pandemic

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    Rising income inequality is strongly linked to health disparities, particularly in regions where uneven distribution of wealth and income has long been a concern. Despite emerging evidence of COVID-19-related health inequalities for adults, limited evidence is available for children and their parents. This study aimed to explore subtypes of families of preschoolers living in the disadvantaged neighborhoods of Hong Kong based on patterns of family hardship and to compare their patterns of parenting behavior, lifestyle practices, and wellbeing during the COVID-19 pandemic. Data were collected from 1338 preschoolers and their parents during March to June 2020. Latent class analysis was performed based on 11 socioeconomic and disease indicators. Multivariate logistic regressions were used to examine associations between identified classes and variables of interest during the COVID-19 pandemic. Four classes of family hardship were identified. Class 1 (45.7%) had the lowest disease and financial burden. Class 2 (14.0%) had the highest financial burden. Class 3 (5.9%) had the highest disease burden. Class 4 (34.5%) had low family income but did not receive government welfare assistance. Class 1 (low hardship) had lower risks of child maltreatment and adjustment problems than Class 2 (poverty) and Class 3 (poor health). However, children in Class 1 (low hardship) had higher odds of suffering psychological aggression and poorer physical wellbeing than those in Class 4 (low income), even after adjusting for child age and gender. The findings emphasize the need to adopt flexible intervention strategies in the time of large disease outbreak to address diverse problems and concerns among socially disadvantaged families

    Evidence of individual differences in the long-term social, psychological, and cognitive consequences of child maltreatment

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    Background: The prevalence and consequences of child maltreatment are alarming, but evidence from studies with long follow-up intervals are limited. This study examined the long-term consequences of child maltreatment in relation to age of onset and follow-up interval. / Methods: The exposed group comprised 63 individuals (aged 13–34 years) with a first-time diagnosis of child maltreatment between 2001 and 2010, whereas the unexposed group comprised 63 individuals who were matched upon gender, age of onset, follow-up period, and poverty status at the index hospital admission but had no medical records of maltreatment in Hong Kong. The participants completed a set of questionnaires on executive functions and mental health and provided blood samples for measurement of IL-6 and IL-10 levels during a health assessment session. / Results: Compared with the unexposed group, the exposed group reported poorer maternal care during childhood (β = −4.64, p < 0.001) and had lower family support (β = −2.97, p = 0.010) and higher inflammatory responses (IL-6: β = 0.15, p = 0.001; IL-10: β = 0.11, p = 0.011) at follow-up. Additionally, the associations of childhood maltreatment exposure with family support and maternal care differed by age of onset and the length of time since exposure. / Conclusions: This matched cohort study highlights childhood maltreatment as a risk factor for systemic inflammation and an indicator of suboptimal social environment, both of which could persist over a long period of time

    Associations between childhood maltreatment and psychiatric disorders: analysis from electronic health records in Hong Kong

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    There has been a lack of high-quality evidence concerning the association between childhood maltreatment and psychiatric diagnoses particularly for Axis II disorders. This study aimed to examine the association between childhood maltreatment exposure and Axis I and Axis II psychiatry disorders using electronic health records. In this study, the exposed group (n = 7473) comprised patients aged 0 to 19 years with a first-time record of maltreatment episode between January 1, 2001 and December 31, 2010, whereas the unexposed group (n = 26,834) comprised individuals of the same gender and age who were admitted into the same hospital in the same calendar year and month but had no records of maltreatment in the Hong Kong Clinical Data Analysis and Reporting System (CDARS). Data on their psychiatric diagnoses recorded from the date of admission to January 31, 2019 were extracted. A Cox proportional hazard regression model was fitted to estimate the hazard ratio (HR, plus 95% CIs) between childhood maltreatment exposure and psychiatric diagnoses, adjusting for age at index visit, sex, and government welfare recipient status. Results showed that childhood maltreatment exposure was significantly associated with subsequent diagnosis of conduct disorder/ oppositional defiant disorder (adjusted HR, 10.99 [95% CI 6.36, 19.01]), attention deficit hyperactivity disorder (ADHD) (7.28 [5.49, 9.65]), and personality disorders (5.36 [3.78, 7.59]). The risk of psychiatric disorders following childhood maltreatment did not vary by history of childhood sexual abuse, age at maltreatment exposure, and gender. Individuals with a history of childhood maltreatment are vulnerable to psychiatric disorders. Findings support the provision of integrated care within the primary health care setting to address the long-term medical and psychosocial needs of individuals with a history of childhood maltreatment

    Identification of plastic constitutive parameters at large deformations from three dimensional displacement fields

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    The aim of this paper is to provide a general procedure to extract the constitutive parameters of a plasticity model starting from displacement measurements and using the Virtual Fields Method. This is a classical inverse problem which has been already investigated in the literature, however several new features are developed here. First of all the procedure applies to a general three-dimensional displacement field which leads to large plastic deformations, no assumptions are made such as plane stress or plane strain although only pressure-independent plasticity is considered. Moreover the equilibrium equation is written in terms of the deviatoric stress tensor that can be directly computed from the strain field without iterations. Thanks to this, the identification routine is much faster compared to other inverse methods such as finite element updating. The proposed method can be a valid tool to study complex phenomena which involve severe plastic deformation and where the state of stress is completely triaxial, e.g. strain localization or necking occurrence. The procedure has been validated using a three dimensional displacement field obtained from a simulated experiment. The main potentialities as well as a first sensitivity study on the influence of measurement errors are illustrated

    A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses

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    <p>Abstract</p> <p>Background</p> <p>Kawasaki disease is an acute vasculitis of infants and young children that is recognized through a constellation of clinical signs that can mimic other benign conditions of childhood. The etiology remains unknown and there is no specific laboratory-based test to identify patients with Kawasaki disease. Treatment to prevent the complication of coronary artery aneurysms is most effective if administered early in the course of the illness. We sought to develop a diagnostic algorithm to help clinicians distinguish Kawasaki disease patients from febrile controls to allow timely initiation of treatment.</p> <p>Methods</p> <p>Urine peptidome profiling and whole blood cell type-specific gene expression analyses were integrated with clinical multivariate analysis to improve differentiation of Kawasaki disease subjects from febrile controls.</p> <p>Results</p> <p>Comparative analyses of multidimensional protein identification using 23 pooled Kawasaki disease and 23 pooled febrile control urine peptide samples revealed 139 candidate markers, of which 13 were confirmed (area under the receiver operating characteristic curve (ROC AUC 0.919)) in an independent cohort of 30 Kawasaki disease and 30 febrile control urine peptidomes. Cell type-specific analysis of microarrays (csSAM) on 26 Kawasaki disease and 13 febrile control whole blood samples revealed a 32-lymphocyte-specific-gene panel (ROC AUC 0.969). The integration of the urine/blood based biomarker panels and a multivariate analysis of 7 clinical parameters (ROC AUC 0.803) effectively stratified 441 Kawasaki disease and 342 febrile control subjects to diagnose Kawasaki disease.</p> <p>Conclusions</p> <p>A hybrid approach using a multi-step diagnostic algorithm integrating both clinical and molecular findings was successful in differentiating children with acute Kawasaki disease from febrile controls.</p

    Hadronic Mass Moments in Inclusive Semileptonic B Meson Decays

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    We have measured the first and second moments of the hadronic mass-squared distribution in B -> X_c l nu, for P(lepton) > 1.5 GeV/c. We find <M_X^2 - M_D[Bar]^2> = 0.251 +- 0.066 GeV^2, )^2 > = 0.576 +- 0.170 GeV^4, where M_D[Bar] is the spin-averaged D meson mass. From that first moment and the first moment of the photon energy spectrum in b -> s gamma, we find the HQET parameter lambda_1 (MS[Bar], to order 1/M^3 and beta_0 alpha_s^2) to be -0.24 +- 0.11 GeV^2. Using these first moments and the B semileptonic width, and assuming parton-hadron duality, we obtain |V_cb| = 0.0404 +- 0.0013.Comment: 11 pages postscript, also available through http://w4.lns.cornell.edu/public/CLNS, submitted to PR

    Observation of the Ωc0\Omega_{c}^{0} Charmed Baryon at CLEO

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    The CLEO experiment at the CESR collider has used 13.7 fb−1^{-1} of data to search for the production of the Ωc0\Omega_c^0 (css-ground state) in e+e−e^{+}e^{-} collisions at s≃10.6\sqrt{s} \simeq 10.6 {\rm GeV}. The modes used to study the Ωc0\Omega_c^0 are Ω−π+\Omega^- \pi^+, Ω−π+π0\Omega^- \pi^+ \pi^0, Ξ−K−pi+π+\Xi^- K^- pi^+ \pi^+, Ξ0K−pi+\Xi^0 K^- pi^+, and Ω−π+π−π+\Omega^- \pi^+ \pi^- \pi^+. We observe a signal of 40.4±\pm9.0(stat) events at a mass of 2694.6±\pm2.6(stat)±\pm1.9(syst) {\rm MeV/c2c^2}, for all modes combined.Comment: 10 pages postscript, also available through http://w4.lns.cornell.edu/public/CLN

    Neuroinflammation, Mast Cells, and Glia: Dangerous Liaisons

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    The perspective of neuroinflammation as an epiphenomenon following neuron damage is being replaced by the awareness of glia and their importance in neural functions and disorders. Systemic inflammation generates signals that communicate with the brain and leads to changes in metabolism and behavior, with microglia assuming a pro-inflammatory phenotype. Identification of potential peripheral-to-central cellular links is thus a critical step in designing effective therapeutics. Mast cells may fulfill such a role. These resident immune cells are found close to and within peripheral nerves and in brain parenchyma/meninges, where they exercise a key role in orchestrating the inflammatory process from initiation through chronic activation. Mast cells and glia engage in crosstalk that contributes to accelerate disease progression; such interactions become exaggerated with aging and increased cell sensitivity to stress. Emerging evidence for oligodendrocytes, independent of myelin and support of axonal integrity, points to their having strong immune functions, innate immune receptor expression, and production/response to chemokines and cytokines that modulate immune responses in the central nervous system while engaging in crosstalk with microglia and astrocytes. In this review, we summarize the findings related to our understanding of the biology and cellular signaling mechanisms of neuroinflammation, with emphasis on mast cell-glia interactions
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