One-year regional brain volume changes as potential predictors of cognitive function in multiple sclerosis: a pilot study

BackgroundThe most reliable magnetic resonance imaging (MRI) marker of cognitive dysfunction in multiple sclerosis (MS) is brain atrophy. However, 1-year volumetric changes prior to cognitive assessment were never studied as potential predictors of cognition, which we aim to assess with this pilot work.MethodsTwenty-two MS patients were submitted to a baseline measure of 83 regional brain volumes with MRI and re-evaluated 1 year later; they were also tested with the Brief International Cognitive Assessment for MS (BICAMS): sustained attention and processing speed were examined with the Symbol Digit Modalities Test (SDMT), verbal and visuo-spatial learning and memory with the learning trials from the California Verbal Learning Test-II (CVLT) and the Brief Visuo-spatial Memory Test-revised (BVMT), respectively. Controlling for age, sex, and years of education, a multivariate linear regression model was created for each cognitive score at 1-year follow-up in a backward elimination manner, considering cross-sectional regional volumes and 1-year volume changes as potential predictors.ResultsDecreases in the volumes of the left amygdala and the right lateral orbitofrontal cortex in the year prior to assessment were identified as possible predictors of worse performance in verbal memory (P = 0.009) and visuo-spatial memory (P = 0.001), respectively, independently of cross-sectional brain regional volumes at time of testing.ConclusionOur work reveals novel 1-year regional brain volume changes as potential predictors of cognitive deficits in MS. This suggests a possible role of these regions in such deficits and might contribute to uncover cognitively deteriorating patients, whose detection is still unsatisfying in clinical practice.Open access funding provided by FCT|FCCN (b-on). Biogen, Fundacao para a Ciencia e Tecnologia, UIDB/50026/2020, Fundacao para a ciencia e tecnologia, UIDP/50026/2020, Fundacao para a Ciencia e a Tecnologia, EXPL/MEC-NEU/0888/2021, Torcato Meira

Bochdalek hernia with concomitant partial situs inversus in an adult

We report the case of 44-year-old woman with a left-sided Bochdalek hernia (BH) with concomitant partial situs inversus. The patient was presented from the outpatient clinic with lower chest discomfort. She had suffered from abdominal pain for one year, with no history of trauma, previous surgery, or extreme physical exertion. Chest radiograph revealed a large left-sided BH. The patient underwent thoracotomy. Intestinal organs, containing bowel, small intestine, caecum, and appendix were seen in the left hemithorax. Because of the failure to reduce the intestinal organs into the peritoneal cavity, laparotomy was performed. The right side of the abdominal cavity was empty. In conclusion, partial situs inversus was diagnosed. The diaphragmatic defect was repaired with non-absorbable sutures via laparotomy, and with a prolene mesh via thoracotomy. Bochdalek hernia with partial situs inversus is a rare clinical entity with none reported in medical literature. (Folia Morphol 2010; 69, 2: 119-122

A review of Morgagni and Bochdalek hernias in adults

The incidence of Bochdalek and Morgagni hernias among adults is very rare. The purpose of this study was to determine retrospectively the prevalence and characteristics of adult Bochdalek and Morgagni hernias in a decade. Consequently, we demonstrated 12 patients with Bochdalek and 8 patients with Morgagni hernias. We presented plain radiography, operation images, and computed tomography findings of an adult patient with symptoms due to Bochdalek and Morgagni hernias. In surgical repair, the Morgagni hernia is best approached via laparotomy, and the Bochdalek hernia can be treated through thoracotomy or laparotomy. (Folia Morphol 2011; 70, 1: 5-12

Materials with periodic internal structure: Computation based on homogenization and comparison with experiment

The combination of thermal and mechanical loading expected in practice means that constitutive equations of metal matrix composites must be developed which deal with time-independent and time-dependent irreversible deformation. Also, the internal state of composites is extremely complicated which underlines the need to formulate macroscopic constitutive equations with a limited number of state variables which represent the internal state at the micro level. One available method for calculating the macro properties of composites in terms of the distribution and properties of the constituent materials is the method of homogenization whose formulation is based on the periodicity of the substructure of the composite. A homogenization procedure was developed which lends itself to the use of the finite element procedure. The efficiency of these procedures, to determine the macroscopic properties of a composite system from its constituent properties, was demonstrated utilizing an aluminum plate perforated by directionally oriented slits. The selection of this problem is based on the fact that, extensive experimental results exist, the macroscopic response is highly anisotropic, and that the slits provide very high stress gradients which severely test the effectiveness of the computational procedures. Furthermore, both elastic and plastic properties were investigated so that the application to practical systems with inelastic deformation should be able to proceed without difficulty. The effectiveness of the procedures was rigorously checked against experimental results and with the predictions of approximate calculations. Using the computational results it is illustrated how macroscopic constitutive equations can be expressed in forms of the elastic and limit load behavior

Prevalence of metabolic syndrome-related disorders in a large adult population in Turkey

BACKGROUND: There are few existing large population studies on the epidemiology of metabolic syndrome-related disorders of Turkey. The purpose of this study was to assess the prevalence of metabolic syndrome-related disorders in the Turkish adult population, to address sex, age, educational and geographical differences, and to examine blood pressure, body mass index, fasting blood glucose and serum lipids in Turkey. METHODS: This study was executed under the population study "The Healthy Nutrition for Healthy Heart Study" conducted between December 2000 and December 2002 by the Health Ministry of Turkey. Overall, 15,468 Caucasian inhabitants aged over 30 were recruited in 14 centers in the seven main different regions of Turkey. The data were analyzed with the Students' t, ANOVA or Chi-Square tests. RESULTS: Overall, more than one-third (35.08 %) of the participants was obese. The hypertensive people ratio in the population was 13.66 %, while these ratios for DM and metabolic syndrome were 4.16 % and 17.91 %, respectively. The prevalence of hypertension, metabolic syndrome and obesity were higher in females than males, whereas diabetes mellitus was higher in males than females. The prevalence of metabolic syndrome and related disorders were found to be significantly different across educational attainments for both men and women. The prevalence of hypertension increased with age, while it was remarkable that in the age group of 60–69 years, prevalence of diabetes mellitus and metabolic syndrome reached a peak value and than decreased. For obesity, the peak prevalence occurred in the 50–59 year old group. The prevalence of metabolic syndrome and related disorders were found to be significantly different according to geographical region. CONCLUSION: In conclusion, high prevalence of obesity and metabolic syndrome, particularly among women, is one of the major public health problems in Turkey. Interestingly, obesity prevalence is relatively high, but the prevalence of hypertension and hypercholesterolemia is relatively low in Turkish people. Future studies may focus on elucidating the reasons behind this controversy. Our findings may be helpful in formulating public health policy and prevention strategies on future health in Turkey

Integrated modelling for sustainability assessment and decision making of alternative fuel buses

In this paper, a hybrid life cycle sustainability assessment (LCSA) model integrating multi region input–output analysis with novel multi-criteria decision-making techniques is proposed to assess three different fuel alternatives: compressed natural gas (CNG), electric buses (EBs), and diesel buses (DBs). A global hybrid LCSA model first quantified the environmental, economic, and social impacts of alternative fuel buses. The results were investigated in terms of multiple combinations of manufacturing and end-of-life scenarios by encompassing impacts embedded in the global supply chains taking Qatar as a case applied to the proposed model. The Interval-Valued Neutrosophic Fuzzy (IVNF)-Analytic Hierarchy Process with the Combined Compromise Solution (CoCoSo) approach is used to rank the alternative fuel buses based on their corresponding sustainability performance. The proposed model will help in quantitatively capturing the macrolevel life cycle socioeconomic and environmental impacts along with optimally selecting alternatives to support sustainable urban transport policy towards a net-zero transportation system globally

Unsupervised Medical Image Translation with Adversarial Diffusion Models

Imputation of missing images via source-to-target modality translation can improve diversity in medical imaging protocols. A pervasive approach for synthesizing target images involves one-shot mapping through generative adversarial networks (GAN). Yet, GAN models that implicitly characterize the image distribution can suffer from limited sample fidelity. Here, we propose a novel method based on adversarial diffusion modeling, SynDiff, for improved performance in medical image translation. To capture a direct correlate of the image distribution, SynDiff leverages a conditional diffusion process that progressively maps noise and source images onto the target image. For fast and accurate image sampling during inference, large diffusion steps are taken with adversarial projections in the reverse diffusion direction. To enable training on unpaired datasets, a cycle-consistent architecture is devised with coupled diffusive and non-diffusive modules that bilaterally translate between two modalities. Extensive assessments are reported on the utility of SynDiff against competing GAN and diffusion models in multi-contrast MRI and MRI-CT translation. Our demonstrations indicate that SynDiff offers quantitatively and qualitatively superior performance against competing baselines.Comment: M. Ozbey and O. Dalmaz contributed equally to this stud

PTPN22 gene polymorphism in Takayasu's arteritis

Objective. Takayasu's arteritis (TA) is a chronic, rare granulomatous panarteritis of unknown aetiology involving mainly the aorta and its major branches. In this study, genetic susceptibility to TA has been investigated by screening the functional single nucleotide polymorphism (SNP) of PTPN22 gene encoding the lymphoid-specific protein tyrosine phosphatase. Methods. Totally, 181 patients with TA and 177 healthy controls are genotyped by PCR-RFLP method for the SNP rs2476601 (A/G) of PTPN22 gene. Polymorphic region was amplified by PCR and digested with Xcm I enzyme. Results. Detected frequencies of heterozygous genotype (AG) were 5.1% (9/177) in control group and 3.8% (7/181) in TA group (P = 0.61, odds ratio: 0.75, 95% CI: 0.3, 2.0). No association with angiographic type, vascular involvement or prognosis of TA was observed either. Conclusion. The distribution of PTPN22 polymorphism did not reveal any association with TA in Turkey. © The Author 2008. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved

Missense mutation in the ATPase, aminophospholipid transporter protein ATP8A2 is associated with cerebellar atrophy and quadrupedal locomotion

Cataloged from PDF version of article.Cerebellar ataxia, mental retardation and dysequilibrium syndrome is a rare and heterogeneous condition. We investigated a consanguineous family from Turkey with four affected individuals exhibiting the condition. Homozygosity mapping revealed that several shared homozygous regions, including chromosome 13q12. Targeted next-generation sequencing of an affected individual followed by segregation analysis, population screening and prediction approaches revealed a novel missense variant, p.I376M, in ATP8A2. The mutation lies in a highly conserved C-terminal transmembrane region of E1 E2 ATPase domain. The ATP8A2 gene is mainly expressed in brain and development, in particular cerebellum. Interestingly, an unrelated individual has been identified, in whom mental retardation and severe hypotonia is associated with a de novo t(10;13) balanced translocation resulting with the disruption of ATP8A2. These findings suggest that ATP8A2 is involved in the development of the cerebro-cerebellar structures required for posture and gait in humans. © 2013 Macmillan Publishers Limited All rights reserved

Learning Fourier-Constrained Diffusion Bridges for MRI Reconstruction

Recent years have witnessed a surge in deep generative models for accelerated MRI reconstruction. Diffusion priors in particular have gained traction with their superior representational fidelity and diversity. Instead of the target transformation from undersampled to fully-sampled data, common diffusion priors are trained to learn a multi-step transformation from Gaussian noise onto fully-sampled data. During inference, data-fidelity projections are injected in between reverse diffusion steps to reach a compromise solution within the span of both the diffusion prior and the imaging operator. Unfortunately, suboptimal solutions can arise as the normality assumption of the diffusion prior causes divergence between learned and target transformations. To address this limitation, here we introduce the first diffusion bridge for accelerated MRI reconstruction. The proposed Fourier-constrained diffusion bridge (FDB) leverages a generalized process to transform between undersampled and fully-sampled data via random noise addition and random frequency removal as degradation operators. Unlike common diffusion priors that use an asymptotic endpoint based on Gaussian noise, FDB captures a transformation between finite endpoints where the initial endpoint is based on moderate degradation of fully-sampled data. Demonstrations on brain MRI indicate that FDB outperforms state-of-the-art reconstruction methods including conventional diffusion priors