178 research outputs found

    Differential expression patterns of metastasis suppressor proteins in basal cell carcinoma

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    Background: Basal cell carcinomas (BCCs) are common malignant skin tumors. Despite having a significant invasion capacity, they metastasize only rarely. Our aim in this study was to detect the expression patterns of the NM23-H1, NDRG1, E-cadherin, RHOGDI2, CD82/KAI1, MKK4, and AKAP12 metastasis suppressor proteins in BCCs. Methods: A total of 96 BCC and 10 normal skin samples were included for the immunohistochemical study. Eleven frozen BCC samples were also studied by quantitative real time polymerase chain reaction (qRT-PCR) to detect the gene expression profile. Results: NM23-H1 was strongly and diffusely expressed in all types of BCC. Significant cytoplasmic expression of NDRG1 and E-cadherin was also detected. However, AKAP12 and CD82/KAI1 expression was significantly decreased. The expressions of the other proteins were somewhere between the two extremes. Similarly, qRT-PCR analysis showed down-regulation of AKAP12 and up-regulation of NM23-H1 and NDRG1 in BCC. Morphologically aggressive BCCs showed significantly higher cytoplasmic NDRG1 expression scores and lower CD82/KAI1 scores than non-aggressive BCCs. Conclusion: The relatively preserved levels of NM23-H1, NDRG1, and E-cadherin proteins may have a positive effect on the non-metastasizing features of these tumors. © 2014 The International Society of Dermatology

    Bi-allelic JAM2 Variants Lead to Early-Onset Recessive Primary Familial Brain Calcification.

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    Primary familial brain calcification (PFBC) is a rare neurodegenerative disorder characterized by a combination of neurological, psychiatric, and cognitive decline associated with calcium deposition on brain imaging. To date, mutations in five genes have been linked to PFBC. However, more than 50% of individuals affected by PFBC have no molecular diagnosis. We report four unrelated families presenting with initial learning difficulties and seizures and later psychiatric symptoms, cerebellar ataxia, extrapyramidal signs, and extensive calcifications on brain imaging. Through a combination of homozygosity mapping and exome sequencing, we mapped this phenotype to chromosome 21q21.3 and identified bi-allelic variants in JAM2. JAM2 encodes for the junctional-adhesion-molecule-2, a key tight-junction protein in blood-brain-barrier permeability. We show that JAM2 variants lead to reduction of JAM2 mRNA expression and absence of JAM2 protein in patient's fibroblasts, consistent with a loss-of-function mechanism. We show that the human phenotype is replicated in the jam2 complete knockout mouse (jam2 KO). Furthermore, neuropathology of jam2 KO mouse showed prominent vacuolation in the cerebral cortex, thalamus, and cerebellum and particularly widespread vacuolation in the midbrain with reactive astrogliosis and neuronal density reduction. The regions of the human brain affected on neuroimaging are similar to the affected brain areas in the myorg PFBC null mouse. Along with JAM3 and OCLN, JAM2 is the third tight-junction gene in which bi-allelic variants are associated with brain calcification, suggesting that defective cell-to-cell adhesion and dysfunction of the movement of solutes through the paracellular spaces in the neurovascular unit is a key mechanism in CNS calcification

    What are the living conditions and health status of those who don't report their migration status? a population-based study in Chile

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    BACKGROUND: Undocumented immigrants are likely to be missing from population databases, making it impossible to identify an accurate sampling frame in migration research. No population-based data has been collected in Chile regarding the living conditions and health status of undocumented immigrants. However, the CASEN survey (Caracterizacion Socio- Economica Nacional) asked about migration status in Chile for the first time in 2006 and provides an opportunity to set the base for future analysis of available migration data. We explored the living conditions and health of self-reported immigrants and respondents who preferred not to report their migration status in this survey. METHODS: Cross-sectional secondary analysis of CASEN survey in Chile in 2006. Outcomes: any disability, illness/accident, hospitalization/surgery, cancer/chronic condition (all binary variables); and the number of medical/emergency attentions received (count variables). Covariates: Demographics (age, sex, marital status, urban/rural, ethnicity), socioeconomic status (education level, employment status and household income), and material standard of living (overcrowding, sanitation, housing quality). Weighted regression models were estimated for each health outcome, crude and adjusted by sets of covariates, in STATA 10.0. RESULTS: About 1% of the total sample reported being immigrants and 0.7% preferred not to report their migration status (Migration Status - Missing Values; MS-MV). The MS-MV lived in more deprived conditions and reported a higher rate of health problems than immigrants. Some gender differences were observed by health status among immigrants and the MS-MV but they were not statistically significant. Regressions indicated that age, sex, SES and material factors consistently affected MS-MVs’ chance of presenting poor health and these patterns were different to those found among immigrants. Great heterogeneity in both the MS-MV and the immigrants, as indicated by wide confidence intervals, prevented the identification of other significantly associated covariates. CONCLUSION: This is the first study to look at the living conditions and health of those that preferred not to respond their migration status in Chile. Respondents that do not report their migration status are vulnerable to poor health and may represent undocumented immigrants. Surveys that fail to identify these people are likely to misrepresent the experiences of immigrants and further quantitative and qualitative research is urgently required

    Therapeutic Effect of a Novel Oxazolidinone, DA-7867, in BALB/c Mice Infected with Nocardia brasiliensis

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    Actinomycetoma is an infectious disease of tropical and subtropical regions produced by actinobacteria of the genera Nocardia, Streptomyces, and Actinomadura. Therapeutic alternatives are scarce and include trimethoprim-sulfamethoxazole, diaminodiphenylsulfone, amoxicillin-clavulanate, imipenem, and amikacin. Oxazolidinones are a new class of antimicrobials with a completely different cellular target; the first compound in the market, linezolid, was introduced in the year 2000. It is active against many species of Nocardia and other aerobic actinomycetes; however, the long-term application in human subjects produces side effects including peripheral neuropathy and mielossupression. Therefore, it is important to screen other oxazolidinones with higher activity and less toxicity. In the present work, we tested DA-7867, a new oxazolidinone, in an experimental mouse model. The drug is active in vivo and decreases the production of lesions using only one dose a day in contrast to linezolid, which needs to be injected three times a day. Although it was tested on N. brasiliensis, it can possibly be active (once it is accepted for its use in humans) against Actinomadura spp and Streptomyces spp, which are frequently found in places of Africa and India where actinomycetoma is also an important consult in dermatology

    A maximum likelihood method for latent class regression involving a censored dependent variable

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    The standard tobit or censored regression model is typically utilized for regression analysis when the dependent variable is censored. This model is generalized by developing a conditional mixture, maximum likelihood method for latent class censored regression. The proposed method simultaneously estimates separate regression functions and subject membership in K latent classes or groups given a censored dependent variable for a cross-section of subjects. Maximum likelihood estimates are obtained using an EM algorithm. The proposed method is illustrated via a consumer psychology application.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45751/1/11336_2005_Article_BF02294647.pd

    Feasibility study of intelligent autonomous determination of the bladder voiding need to treat bedwetting using ultrasound and smartphone ML techniques

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    Unsatisfactory cure rates for the treatment of nocturnal enuresis (NE), i.e. bed-wetting, have led to the need to explore alternative modalities. New treatment methods that focus on preventing enuretic episodes by means of a pre-void alerting system could improve outcomes for children with NE in many aspects. No such technology exists currently to monitor the bladder to alarm before bed-wetting. The aim of this study is to carry out the feasibility of building, refining and evaluating a new, safe, comfortable and non-invasive wearable autonomous intelligent electronic device to monitor the bladder using a single-element low-powered low-frequency ultrasound with the help of Machine Learning techniques and to treat NE by warning the patient at the pre-void stage, enhancing quality of life for these children starting from the first use. The sensitivity and specificity values are 0.89 and 0.93 respectively for determining imminent voiding need. The results indicate that customised imminent voiding need based on the expansion of the bladder can be determined by applying a single-element transducer on a bladder in intermittent manner. The acquired results can be improved further with a comfortable non-invasive device by adding several more features to the current features employed in this pilot study

    Deriving ultrametric tree structures from proximity data confounded by differential stimulus familiarity

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    This paper presents a new procedure called TREEFAM for estimating ultrametric tree structures from proximity data confounded by differential stimulus familiarity. The objective of the proposed TREEFAM procedure is to quantitatively “filter out” the effects of stimulus unfamiliarity in the estimation of an ultrametric tree. A conditional, alternating maximum likelihood procedure is formulated to simultaneously estimate an ultrametric tree, under the unobserved condition of complete stimulus familiarity, and subject-specific parameters capturing the adjustments due to differential unfamiliarity. We demonstrate the performance of the TREEFAM procedure under a variety of alternative conditions via a modest Monte Carlo experimental study. An empirical application provides evidence that the TREEFAM outperforms traditional models that ignore the effects of unfamiliarity in terms of superior tree recovery and overall goodness-of-fit.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45752/1/11336_2005_Article_BF02294391.pd
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