Trafficking in Women and Children: The U.S. and International Response - Updated August 1, 2001

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Prediction of progression in idiopathic pulmonary fibrosis using CT scans atbaseline: A quantum particle swarm optimization - Random forest approach

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease characterized by an unpredictable progressive declinein lung function. Natural history of IPF is unknown and the prediction of disease progression at the time ofdiagnosis is notoriously difficult. High resolution computed tomography (HRCT) has been used for the diagnosisof IPF, but not generally for monitoring purpose. The objective of this work is to develop a novel predictivemodel for the radiological progression pattern at voxel-wise level using only baseline HRCT scans. Mainly, thereare two challenges: (a) obtaining a data set of features for region of interest (ROI) on baseline HRCT scans andtheir follow-up status; and (b) simultaneously selecting important features from high-dimensional space, andoptimizing the prediction performance. We resolved the first challenge by implementing a study design andhaving an expert radiologist contour ROIs at baseline scans, depending on its progression status in follow-upvisits. For the second challenge, we integrated the feature selection with prediction by developing an algorithmusing a wrapper method that combines quantum particle swarm optimization to select a small number of featureswith random forest to classify early patterns of progression. We applied our proposed algorithm to analyzeanonymized HRCT images from 50 IPF subjects from a multi-center clinical trial. We showed that it yields aparsimonious model with 81.8% sensitivity, 82.2% specificity and an overall accuracy rate of 82.1% at the ROIlevel. These results are superior to other popular feature selections and classification methods, in that ourmethod produces higher accuracy in prediction of progression and more balanced sensitivity and specificity witha smaller number of selected features. Our work is the first approach to show that it is possible to use onlybaseline HRCT scans to predict progressive ROIs at 6 months to 1year follow-ups using artificial intelligence

INDAHNYA PERBEDAAN SEBAGAI TEMA PENCIPTAAN KARYA SENI LUKIS

Abstrak Manusia adalah makhluk yang indah dan yang menyenangi keindahan. Keindahan pada dasarnya meliputi sejumlah kualitas pokok tertentu yang terdapat pada suatu hal. Kualitas keindahan ditunjukkan oleh kesatuan (unity), keselarasan (harmony), kesetangkupan (symmetry), keseimbangan (balance), dan perlawanan (contrast). Tulisan ini menjelaskan berbagai macam keindahan dalam perbedaan yang pada dasarnya sudah ada sejak penciptaan segala sesuatu di dunia ini. Perbedaan yang asli menjadi sangat indah karena dibentuk oleh berbagai macam keunikan yang melekat pada setiap ciptaan, seperti jenis, ukuran, warna, bentuk, fungsi, isi dan lain-lain. Judul tulisan ini, yaitu “Indahnya Perbedaan” tidak hanya dapat diterapkan dalam kehidupan semua ciptaan yang lain, tetapi juga dapat diterapkan dalam kehidupan bersama sebagai satu masyarakat. Kata kunci: keindahan, perbedaan dan keaslia

INDAHNYA PERBEDAAN SEBAGAI TEMA PENCIPTAAN KARYA SENI LUKIS

Abstrak Manusia adalah makhluk yang indah dan yang menyenangi keindahan. Keindahan pada dasarnya meliputi sejumlah kualitas pokok tertentu yang terdapat pada suatu hal. Kualitas keindahan ditunjukkan oleh kesatuan (unity), keselarasan (harmony), kesetangkupan (symmetry), keseimbangan (balance), dan perlawanan (contrast). Tulisan ini menjelaskan berbagai macam keindahan dalam perbedaan yang pada dasarnya sudah ada sejak penciptaan segala sesuatu di dunia ini. Perbedaan yang asli menjadi sangat indah karena dibentuk oleh berbagai macam keunikan yang melekat pada setiap ciptaan, seperti jenis, ukuran, warna, bentuk, fungsi, isi dan lain-lain. Judul tulisan ini, yaitu “Indahnya Perbedaan” tidak hanya dapat diterapkan dalam kehidupan semua ciptaan yang lain, tetapi juga dapat diterapkan dalam kehidupan bersama sebagai satu masyarakat. Kata kunci: keindahan, perbedaan dan keaslia

Glycosylated proteins preserved over millennia: N-glycan analysis of Tyrolean Iceman, Scythian Princess and Warrior.

An improved understanding of glycosylation will provide new insights into many biological processes. In the analysis of oligosaccharides from biological samples, a strict regime is typically followed to ensure sample integrity. However, the fate of glycans that have been exposed to environmental conditions over millennia has not yet been investigated. This is also true for understanding the evolution of the glycosylation machinery in humans as well as in any other biological systems. In this study, we examined the glycosylation of tissue samples derived from four mummies which have been naturally preserved: - the 5,300 year old "Iceman called Oetzi", found in the Tyrolean Alps; the 2,400 year old "Scythian warrior" and "Scythian Princess", found in the Altai Mountains; and a 4 year old apartment mummy, found in Vienna/Austria. The number of N-glycans that were identified varied both with the age and the preservation status of the mummies. More glycan structures were discovered in the contemporary sample, as expected, however it is significant that glycan still exists in the ancient tissue samples. This discovery clearly shows that glycans persist for thousands of years, and these samples provide a vital insight into ancient glycosylation, offering us a window into the distant past

Novel lung imaging biomarkers and skin gene expression subsetting in dasatinib treatment of systemic sclerosis-associated interstitial lung disease.

BackgroundThere are no effective treatments or validated clinical response markers in systemic sclerosis (SSc). We assessed imaging biomarkers and performed gene expression profiling in a single-arm open-label clinical trial of tyrosine kinase inhibitor dasatinib in patients with SSc-associated interstitial lung disease (SSc-ILD).MethodsPrimary objectives were safety and pharmacokinetics. Secondary outcomes included clinical assessments, quantitative high-resolution computed tomography (HRCT) of the chest, serum biomarker assays and skin biopsy-based gene expression subset assignments. Clinical response was defined as decrease of >5 or >20% from baseline in the modified Rodnan Skin Score (MRSS). Pulmonary function was assessed at baseline and day 169.ResultsDasatinib was well-tolerated in 31 patients receiving drug for a median of nine months. No significant changes in clinical assessments or serum biomarkers were seen at six months. By quantitative HRCT, 65% of patients showed no progression of lung fibrosis, and 39% showed no progression of total ILD. Among 12 subjects with available baseline and post-treatment skin biopsies, three were improvers and nine were non-improvers. Improvers mapped to the fibroproliferative or normal-like subsets, while seven out of nine non-improvers were in the inflammatory subset (p = 0.0455). Improvers showed stability in forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLCO), while both measures showed a decline in non-improvers (p = 0.1289 and p = 0.0195, respectively). Inflammatory gene expression subset was associated with higher baseline HRCT score (p = 0.0556). Non-improvers showed significant increase in lung fibrosis (p = 0.0313).ConclusionsIn patients with SSc-ILD dasatinib treatment was associated with acceptable safety profile but no significant clinical efficacy. Patients in the inflammatory gene expression subset showed increase in skin fibrosis, decreasing pulmonary function and worsening lung fibrosis during the study. These findings suggest that target tissue-specific gene expression analyses can help match patients and therapeutic interventions in heterogeneous diseases such as SSc, and quantitative HRCT is useful for assessing clinical outcomes.Trial registrationClinicaltrials.gov NCT00764309

Comprehensive native glycan profiling with isomer separation and quantitation for the discovery of cancer biomarkers

Glycosylation is highly sensitive to the biochemical environment and has been implicated in many diseases including cancer. Glycan compositional profiling of human serum with mass spectrometry has already identified potential biomarkers for several types of cancer and diseases; however, composition alone does not fully describe glycan stereo-and regioisomeric diversity. The vast structural heterogeneity of glycans presents a formidable analytical challenge. We have developed a method to identify and quantify isomeric native glycans using nanoflow liquid chromatography (nano-LC)/mass spectrometry. A microfluidic chip packed with graphitized carbon was used to chromatographically separate the glycans. To determine the utility of this method for structure-specific biomarker discovery, we analyzed serum samples from two groups of prostate cancer patients with different prognoses. More than 300 N-glycan species (including isomeric structures) were identified, corresponding to over 100 N-glycan compositions. Statistical tests established significant differences in glycan abundances between patient groups. This method provides comprehensive, selective, and quantitative glycan profiling