461 research outputs found
Correlation between mutans streptococci counts of parents and their children residing in Chandigarh, India
Objectives: To determine the prevalence of Mutans Streptococci (MS) in children and to evaluate the relationship
between the salivary levels of MS in children and their parents.
Material and Methods: 100 children aged 3-6 years along with their parents (100 mothers and fathers each) were
included in the study. The children were segregated depending upon their age and level of caries experience. The
children were examined clinically on an ordinary chair in natural daylight using the Møller's index criteria. Assays
for Mutans Streptococci (MS) were done for both the children and their parents using the Dentocult SM strip mu
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tans test. Collected data was assessed using SPSS software.
Results: The overall prevalence of MS in the children was 83%. A statistically significant correlation (p<0.05) was
observed between salivary MS counts of children and their mothers. No significant correlation was seen with the
fathers.
Conclusions: The findings conclude that if primary caregivers harbour high levels of MS in their saliva, it is likely
that their children will have the same
Detection and diabetic retinopathy grading using digital retinal images
Diabetic Retinopathy is an eye disorder that affects people suffering from diabetes. Higher sugar levels in blood leads to damage of blood vessels in eyes and may even cause blindness. Diabetic retinopathy is identified by red spots known as microanuerysms and bright yellow lesions called exudates. It has been observed that early detection of exudates and microaneurysms may save the patient’s vision and this paper proposes a simple and effective technique for diabetic retinopathy. Both publicly available and real time datasets of colored images captured by fundus camera have been used for the empirical analysis. In the proposed work, grading has been done to know the severity of diabetic retinopathy i.e. whether it is mild, moderate or severe using exudates and micro aneurysms in the fundus images. An automated approach that uses image processing, features extraction and machine learning models to predict accurately the presence of the exudates and micro aneurysms which can be used for grading has been proposed. The research is carried out in two segments; one for exudates and another for micro aneurysms. The grading via exudates is done based upon their distance from macula whereas grading via micro aneurysms is done by calculating their count. For grading using exudates, support vector machine and K-Nearest neighbor show the highest accuracy of 92.1% and for grading using micro aneurysms, decision tree shows the highest accuracy of 99.9% in prediction of severity levels of the disease
Removable silicon insertion stiffeners for neural probes using polyethylene glycol as a biodissolvable adhesive
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HIGH-DENSITY, BIO-COMPATIBLE, AND HERMETIC ELECTRICAL FEEDTHROUGHS USING EXTRUDED METAL VIAS
Implanted medical devices such as pacemakers and neural prosthetics require that the electronic components that power these devices are protected from the harsh chemical and biological environment of the body. Typically, the electronics are hermetically sealed inside a bio-compatible package containing feedthroughs that transmit electrical signals, while being impermeable to particles or moisture. We present a novel approach for fabricating one of the highest densities of biocompatible hermetic feedthroughs in alumina (Al{sub 2}O{sub 3}). Alumina substrates with laser machined vias of 200 {micro}m pitch were conformally metallized and lithographically patterned. Hermetic electrical feedthroughs were formed by extruding metal stud-bumps partially through the vias. Hermeticity testing showed leak rates better than 9 x 10{sup -10} torr-l/s. Based on our preliminary results and process optimization, this extruded metal via approach is a high-density, low temperature, cost-effective, and robust method of miniaturizing electrical feedthroughs for a wide range of implantable bio-medical device applications
Severe aortic and arterial aneurysms associated with a TGFBR2 mutation.
BACKGROUND: A 24-year-old man presented with previously diagnosed Marfan\u27s syndrome. Since the age of 9 years, he had undergone eight cardiovascular procedures to treat rapidly progressive aneurysms, dissection and tortuous vascular disease involving the aortic root and arch, the thoracoabdominal aorta, and brachiocephalic, vertebral, internal thoracic and superior mesenteric arteries. Throughout this extensive series of cardiovascular surgical repairs, he recovered without stroke, paraplegia or renal impairment.
INVESTIGATIONS: CT scans, arteriogram, genetic mutation screening of transforming growth factor beta receptors 1 and 2.
DIAGNOSIS: Diffuse and rapidly progressing vascular disease in a patient who met the diagnostic criteria for Marfan\u27s syndrome, but was later rediagnosed with Loeys-Dietz syndrome. Genetic testing also revealed a de novo mutation in transforming growth factor beta receptor 2.
MANAGEMENT: Regular cardiovascular surveillance for aneurysms and dissections, and aggressive surgical treatment of vascular disease
Medical students\u27 knowledge of HPV, HPV vaccine, and HPV-associated head and neck cancer
On the basis of their training, medical students are considered the best case scenario among university students in knowledge of the human papillomavirus (HPV). We evaluated differences in knowledge of HPV, HPV vaccine, and head and neck cancer (HNC) among medical students. A previously validated questionnaire was completed by 247 medical students at a Midwestern university. Outcomes of interest were knowledge score for HPV and HPV vaccine, and HNC, derived from combining questionnaire items to form HPV knowledge and HNC scores, and analyzed using multivariate linear regression. Mean scores for HPV knowledge were 19.4 out of 26, and 7.2 out of 12 for HNC knowledge. In the final multivariate linear regression model, sex, race, and year of study were independently associated with HPV and HPV vaccine knowledge. Males had significantly lower HPV vaccine knowledge than females (β = -1.53; 95% CI: -2.53, -0.52), as did nonwhite students (β = -1.05; 95% CI: -2.07, -0.03). There was a gradient in HPV vaccine knowledge based on the year of study, highest among fourth year students (β = 6.75; 95% CI: 5.17, 8.33). Results were similar for factors associated with HNC knowledge, except for sex. HNC knowledge similarly increased based on year of study, highest for fourth year students (β = 2.50; 95% CI: 1.72, 3.29). Among medical students, gaps remain in knowledge of HPV, HPV vaccine, and HPV-linked HNC. Male medical students have significantly lower knowledge of HPV. This highlights the need to increase medical student knowledge of HPV and HPV-linked HNC
Chronic, multi-contact, neural interface for deep brain stimulation
Abstract not provide
Optimal phase for coronary interpretations and correlation of ejection fraction using late-diastole and end-diastole imaging in cardiac computed tomography angiography: implications for prospective triggering
A typical acquisition protocol for multi-row detector computed tomography (MDCT) angiography is to obtain all phases of the cardiac cycle, allowing calculation of ejection fraction (EF) simultaneously with plaque burden. New MDCT protocols scanner, designed to reduce radiation, use prospectively acquired ECG gated image acquisition to obtain images at certain specific phases of the cardiac cycle with least coronary artery motion. These protocols do not we allow acquisition of functional data which involves measurement of ejection fraction requiring end-systolic and end-diastolic phases. We aimed to quantitatively identify the cardiac cycle phase that produced the optimal images as well as aimed to evaluate, if obtaining only 35% (end-systole) and 75% (as a surrogate for end-diastole) would be similar to obtaining the full cardiac cycle and calculating end diastolic volumes (EDV) and EF from the 35th and 95th percentile images. 1,085 patients with no history of coronary artery disease were included; 10 images separated by 10% of R–R interval were retrospectively constructed. Images with motion in the mid portion of RCA were graded from 1 to 3; with ‘1’ being no motion, ‘2’ if 0 to <1 mm motion, and ‘3’ if there is >1 mm motion and/or non-interpretable study. In a subgroup of 216 patients with EF > 50%, we measured left ventricular (LV) volumes in the 10 phases, and used those obtained during 25, 35, 75 and 95% phase to calculate the EF for each patient. The average heart rate (HR) for our patient group was 56.5 ± 8.4 (range 33–140). The distribution of image quality at all heart rates was 958 (88.3%) in Grade 1, 113 (10.42%) in Grade 2 and 14 (1.29%) in Grade 3 images. The area under the curve for optimum image quality (Grade 1 or 2) in patients with HR > 60 bpm for phase 75% was 0.77 ± 0.04 [95% CI: 0.61–0.87], while for similar heart rates the area under the curve for phases 75 + 65 + 55 + 45% combined was 0.92 ± 0.02. LV volume at 75% phase was strongly correlated with EDV (LV volume at 95% phase) (r = 0.970, P < 0.001). There was also a strong correlation between LVEF (75_35) and LVEF (95_35) (r = 0.93, P < 0.001). Subsequently, we developed a formula to correct for the decrement in LVEF using 35–75% phase: LVEF (95_35) = 0.783 × LVEF (75_35) + 20.68; adjusted R2 = 0.874, P < 0.001. Using 64 MDCT scanners, in order to acquire >90% interpretable studies, if HR < 60 bpm 75% phase of RR interval provides optimal images; while for HR > 60 analysis of images in 4 phases (75, 35, 45 and 55%) is needed. Our data demonstrates that LVEF can be predicted with reasonable accuracy by using data acquired in phases 35 and 75% of the R–R interval. Future prospective acquisition that obtains two phases (35 and 75%) will allow for motion free images of the coronary arteries and EF estimates in over 90% of patients
A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes
Large databases of high-resolution structural MR images are being assembled to quantitatively examine the relationships between brain anatomy, disease progression, treatment regimens, and genetic influences upon brain structure. Quantifying brain structures in such large databases cannot be practically accomplished by expert neuroanatomists using hand-tracing. Rather, this research will depend upon automated methods that reliably and accurately segment and quantify dozens of brain regions. At present, there is little guidance available to help clinical research groups in choosing such tools. Thus, our goal was to compare the performance of two popular and fully automated tools, FSL/FIRST and FreeSurfer, to expert hand tracing in the measurement of the hippocampus and amygdala. Volumes derived from each automated measurement were compared to hand tracing for percent volume overlap, percent volume difference, across-sample correlation, and 3-D group-level shape analysis. In addition, sample size estimates for conducting between-group studies were computed for a range of effect sizes. Compared to hand tracing, hippocampal measurements with FreeSurfer exhibited greater volume overlap, smaller volume difference, and higher correlation than FIRST, and sample size estimates with FreeSurfer were closer to hand tracing. Amygdala measurement with FreeSurfer was also more highly correlated to hand tracing than FIRST, but exhibited a greater volume difference than FIRST. Both techniques had comparable volume overlap and similar sample size estimates. Compared to hand tracing, a 3-D shape analysis of the hippocampus showed FreeSurfer was more accurate than FIRST, particularly in the head and tail. However, FIRST more accurately represented the amygdala shape than FreeSurfer, which inflated its anterior and posterior surfaces
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