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Adverse health outcomes from exposure to chemical agents are of increasing interest in human and ecological risk assessment and require the development of new analytical methods. Such methods must be able to capture the essence of integrated networks of biochemical pathways in a mathematically feasible fashion. Over the past three decades, Biochemical Systems Theory has been successfully applied to numerous biological systems. It is suggested here that S‐system models derived from BST can provide the means for assessing chemical exposures and their effects at the metabolic level. This article briefly reviews essential concepts of S‐systems and provides generic examples of chemical exposure scenarios. S‐system models can be considered mechanistic, since their components are measurable quantities (e.g., concentrations, fluxes, enzyme activities, and rates). As dynamic models, they can be used to assess immediate and long‐term metabolic responses to environmental stimuli. Direct mathematical analysis for low exposures leads to simple dose‐response relationships, which have the form of power‐law functions. Thus, if the S‐system model yields an appropriate description of chemical exposure and its metabolic effects, the dose‐response relationship for low exposures is linear in logarithmic coordinates. This result includes as a special case the standard linear relationship in Cartesian coordinates with zero intercept.

AbstractAimTo identify the main barriers to dental care access for patients with inherited bleeding (IBD) and hemoglobin disorders (HbD).MethodsPatients with IBD and HbD were invited to participate in this study between August 2019 and March 2020. Data were collected through a questionnaire consisting of socioeconomic and demographic items and questions about access to dental services and history of dental treatment. Univariate and multiple Poisson regression model was used to determine associations between professional refusal of dental care and other co‐variables (p < .05).ResultsThe participants (29.1%) have already had professional refusal of dental care and participants with IBD (53.2%) did not feel confident with their local dentist due to their bleeding tendency. Most (64.6%) felt apprehensive about visiting the local dentist and high prevalence of refusal to provide dental care was associated with age (prevalence ratio [PR] = 1.021; 95% confidence interval [CI] = 1.010–1.032). Individuals with low bleeding risk were less likely to be denied dental care by a professional compared to those with high bleeding risk (PR = 0.536; 95%CI = 0.291–0.990).ConclusionProfessional refusal of dental care was high among patients with IBD, particularly older adults and with an increased risk of bleeding.

Recent evidence suggests that comorbidities between neuropsychiatric conditions and metabolic syndrome may precede and even exacerbate long-term side-effects of psychiatric medication, such as a higher risk of type 2 diabetes and cardiovascular disease, which result in increased mortality. In the present study we compare the expression of key metabolic proteins, including the insulin receptor (CD220), glucose transporter 1 (GLUT1) and fatty acid translocase (CD36), on peripheral blood mononuclear cell subtypes from patients across the neuropsychiatric spectrum, including schizophrenia, bipolar disorder, major depression and autism spectrum conditions (n = 25/condition), relative to typical controls (n = 100). This revealed alterations in the expression of these proteins that were specific to schizophrenia. Further characterization of metabolic alterations in an extended cohort of first-onset antipsychotic drug-naïve schizophrenia patients (n = 58) and controls (n = 63) revealed that the relationship between insulin receptor expression in monocytes and physiological insulin sensitivity was disrupted in schizophrenia and that altered expression of the insulin receptor was associated with whole genome polygenic risk scores for schizophrenia. Finally, longitudinal follow-up of the schizophrenia patients over the course of antipsychotic drug treatment revealed that peripheral metabolic markers predicted changes in psychopathology and the principal side effect of weight gain at clinically relevant time points. These findings suggest that peripheral blood cells can provide an accessible surrogate model for metabolic alterations in schizophrenia and have the potential to stratify subgroups of patients with different clinical outcomes or a greater risk of developing metabolic complications following antipsychotic therapy. ; This work was supported by grants from the Stanley Medical Research Institute (SMRI); the Engineering and Physical Sciences Research Council UK (EPSRC); the Dutch Government-funded Virgo consortium (ref. FES0908); the Netherlands Genomics Initiative (ref. 050-060-452); the European Union FP7 funding scheme: Marie Curie Actions Industry Academia Partnerships and Pathways (ref. 286334, PSYCH-AID project); SAF2016-76046-R and SAF2013-46292-R (MINECO) and PI16/00156 (ISCIII and FEDER).

Recent evidence suggests that comorbidities between neuropsychiatric conditions and metabolic syndrome may precede and even exacerbate long-term side-effects of psychiatric medication, such as a higher risk of type 2 diabetes and cardiovascular disease, which result in increased mortality. In the present study we compare the expression of key metabolic proteins, including the insulin receptor (CD220), glucose transporter 1 (GLUT1) and fatty acid translocase (CD36), on peripheral blood mononuclear cell subtypes from patients across the neuropsychiatric spectrum, including schizophrenia, bipolar disorder, major depression and autism spectrum conditions (n = 25/condition), relative to typical controls (n = 100). This revealed alterations in the expression of these proteins that were specific to schizophrenia. Further characterization of metabolic alterations in an extended cohort of first-onset antipsychotic drug-naïve schizophrenia patients (n = 58) and controls (n = 63) revealed that the relationship between insulin receptor expression in monocytes and physiological insulin sensitivity was disrupted in schizophrenia and that altered expression of the insulin receptor was associated with whole genome polygenic risk scores for schizophrenia. Finally, longitudinal follow-up of the schizophrenia patients over the course of antipsychotic drug treatment revealed that peripheral metabolic markers predicted changes in psychopathology and the principal side effect of weight gain at clinically relevant time points. These findings suggest that peripheral blood cells can provide an accessible surrogate model for metabolic alterations in schizophrenia and have the potential to stratify subgroups of patients with different clinical outcomes or a greater risk of developing metabolic complications following antipsychotic therapy. ; This work was supported by grants from the Stanley Medical Research Institute (SMRI); the Engineering and Physical Sciences Research Council UK (EPSRC); the Dutch Government-funded Virgo consortium (ref. FES0908); the Netherlands Genomics Initiative (ref. 050-060-452); the European Union FP7 funding scheme: Marie Curie Actions Industry Academia Partnerships and Pathways (ref. 286334, PSYCH-AID project); SAF2016-76046-R and SAF2013-46292-R (MINECO) and PI16/00156 (isciii and FEDER).

AbstractWe examined the association between exposure to PM2.5, focused on individual exposure level, and metabolic dysfunction during pregnancy. APPO study (Air Pollution on Pregnancy Outcome) was a prospective, multicenter, observational cohort study conducted from January 2021 to March 2023. Individual PM2.5 concentrations were calculated using a time-weighted average model. Metabolic dysfunction during pregnancy was assessed based on a modified definition of metabolic syndrome and its components, accounting for pregnancy-specific criteria. Exposure to PM2.5 during pregnancy was associated with worsened metabolic parameters especially glucose metabolism. In comparison to participants exposed to the low PM2.5 group, those exposed to high PM2.5 levels exhibited increased odds of gestational diabetes mellitus (GDM) after adjusting for confounding variables in different adjusted models. Specifically, in model 1, the adjusted odds ratio (aOR) was 3.117 with a 95% confidence interval (CI) of 1.234–7.870; in model 2, the aOR was 3.855 with a 95% CI of 1.255–11.844; in model 3, the aOR was 3.404 with a 95% CI of 1.206–9.607; and in model 4, the aOR was 2.741 with a 95% CI of 0.712–10.547. Exposure to higher levels of PM2.5 during pregnancy was associated with a tendency to worsen metabolic dysfunction markers specifically in glucose homeostasis. Further research is needed to investigate the mechanisms underlying the effects of ambient PM2.5 on metabolic dysfunction during pregnancy.

In people with a hereditary predisposition, gluten consumption causes celiac disease, a multifactorial autoimmune condition. The ensuing small intestine inflammatory process develops specific antibodies and causes various gastrointestinal and extra-intestinal symptoms with varying degrees of severity. Evaluation of the blood iron profile at various histological celiac disease severity in Iraqi patients was the goal of the current study. Seventy-five Iraqi patients with celiac disease, with a mean age of 18.68± 11.13 years, were the study's participants. These people tested positive for celiac antibodies and experienced gastrointestinal symptoms. Based on the disease histological severity, they were divided into two groups: marsh (III a, b, c) group and marsh (0, I) group. For comparison purposes, 46 people who appeared to be in good health and matched in age and gender to the patients utilized in the study were also included. The levels of iron, transferrin, hemoglobin, ferritin, total iron binding capacity, unsaturated iron binding capacity, and the percentage of transferrin that is saturated with iron were all measured. In comparison to the other patient groups under study, celiac patients (marsh III) group, and particularly those of group (marsh III c), showed a substantial drop (p<0.05) in iron, the percentage of transferrin saturating with iron, the levels of each ferritin and of hemoglobin. The total iron binding capacity and the unsaturated iron binding capacity showed a significant elevation (p<0.05) in (marsh III c) patients' group, meanwhile non-significant differences (p> 0.05) were found in transferrin concentration. Moreover, significant differences (p< 0.05) were obtained in the iron profile between celiac patients who followed strict gluten free diet and those patients with gluten contained diet.

Newborn screening (NBS) programmes are essential in the diagnosis of inherited metabolic diseases (IMDs) and for access to disease modifying treatment. Most European countries follow the World Health Organisation (WHO) criteria to determine which disorders are appropriate for screening at birth; however, these criteria are interpreted and implemented by individual countries differently, creating disparities. Advances in research and diagnostics, together with the promise of new treatments, offer new possibilities to accelerate the expansion of evidence-based screening programmes. A novel and robust algorithm was built to objectively assess and prioritise IMDs for inclusion in NBS programmes. The Wilson and Jungner classic screening principles were used as a foundation to develop individual and measurable criteria. The proposed algorithm is a point-based system structured upon three pillars: condition, screening, and treatment. The algorithm was tested by applying the six IMDs currently approved in the United Kingdom NBS programme. The algorithm generates a weight-based score that could be used as the first step in the complex process of evaluating disorders for inclusion on NBS programmes. By prioritising disorders to be further evaluated, individual countries are able to assess the economic, societal and political aspects of a potential screening programme.