Objective: The aim of this study was to develop a method based on natural language processing (NLP) that automatically maps an entire clinical docume

The main purpose of the current research was to develop an abbreviated form of the Dyadic Adjustment Scale (DAS) with nonparametric item response theory. The authors conducted 5 studies, with a total participation of 8,256 married or cohabiting individuals. Results showed that the item characteristic curves behaved in a monotonically increasing function for all items of the brief 4-item version of the DAS (DAS-4). The DAS-4 proved to be informative at all levels of couple satisfaction. Compared with the 32-item version of the DAS (DAS-32), it was as effective in predicting couple dissolution and was significantly less contaminated by socially desirable responding. In addition, structural equation modeling demonstrated that the underlying latent construct measured by the DAS-4 was very stable over a 2-year period. This brief version has the advantage of being less time consuming and constitutes a promising alternative to the original DAS-32 for clinicians and researchers.

Genome-scale transcriptomic profiling of peripheral blood mononuclear cells from patients with idiopathic pulmonary fibrosis reveals that decreased expression ofCD28,ICOS,LCK, andITKpredicts mortality.

To facilitate rapid, unbiased, differential diagnosis of infectious diseases, we designed GreeneChipPm, a panmicrobial microarray comprising 29,455 sixty-mer oligonucleotide probes for vertebrate viruses, bacteria, fungi, and parasites. Methods for nucleic acid preparation, random primed PCR amplification, and labeling were optimized to allow the sensitivity required for application with nucleic acid extracted from clinical materials and cultured isolates. Analysis of nasopharyngeal aspirates, blood, urine, and tissue from persons with various infectious diseases confirmed the presence of viruses and bacteria identified by other methods, and implicated Plasmodium falciparum in an unexplained fatal case of hemorrhagic feverlike disease during the Marburg hemorrhagic fever outbreak in Angola in 2004–2005.

Cancer staging and treatment presumes a division into localized or metastatic disease. We proposed an intermediate state defined by ≤5 cumulative metastasis(es), termed oligometastases. In contrast to widespread polymetastases, oligometastatic patients may benefit from metastasis-directed local treatments. However, many patients who initially present with oligometastases progress to polymetastases. Predictors of progression could improve patient selection for metastasis-directed therapy. Here, we identified patterns of microRNA expression of tumor samples from oligometastatic patients treated with high-dose radiotherapy. Patients who failed to develop polymetastases are characterized by unique prioritized features of a microRNA classifier that includes the microRNA-200 family. We created an oligometastatic-polymetastatic xenograft model in which the patient-derived microRNAs discriminated between the two metastatic outcomes. MicroRNA-200c enhancement in an oligometastatic cell line resulted in polymetastatic progression. These results demonstrate a biological basis for oligometastases and a potential for using microRNA expression to identify patients most likely to remain oligometastatic after metastasis-directed treatment.

Strategies to stage and treat cancer rely on a presumption of either localized or widespread metastatic disease. An intermediate state of metastasis termed oligometastasis(es) characterized by limited progression has been proposed. Oligometastases are amenable to treatment by surgical resection or radiotherapy. We analyzed microRNA expression patterns from lung metastasis samples of patients with ≤5 initial metastases resected with curative intent. Patients were stratified into subgroups based on their rate of metastatic progression. We prioritized microRNAs between patients with the highest and lowest rates of recurrence. We designated these as high rate of progression (HRP) and low rate of progression (LRP); the latter group included patients with no recurrences. The prioritized microRNAs distinguished HRP from LRP and were associated with rate of metastatic progression and survival in an independent validation dataset. Oligo- and poly- metastasis are distinct entities at the clinical and molecular level.