Intraoperative Raman spectroscopy of soft tissue sarcomas.

BACKGROUND AND OBJECTIVE: Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated through surgical resection. Current intraoperative margin assessment methods are limited and highlight the need for an improved approach with respect to time and specificity. Here we investigate the potential of near-infrared Raman spectroscopy for the intraoperative differentiation of STS from surrounding normal tissue. MATERIALS AND METHODS: In vivo Raman measurements at 785 nm excitation were intraoperatively acquired from subjects undergoing STS resection using a probe based spectroscopy system. A multivariate classification algorithm was developed in order to automatically identify spectral features that can be used to differentiate STS from the surrounding normal muscle and fat. The classification algorithm was subsequently tested using leave-one-subject-out cross-validation. RESULTS: With the exclusion of well-differentiated liposarcomas, the algorithm was able to classify STS from the surrounding normal muscle and fat with a sensitivity and specificity of 89.5% and 96.4%, respectively. CONCLUSION: These results suggest that single point near-infrared Raman spectroscopy could be utilized as a rapid and non-destructive surgical guidance tool for identifying abnormal tissue margins in need of further excision. Lasers Surg. Med. 48:774-781, 2016. © 2016 Wiley Periodicals, Inc.

Large-scale production and structural and biophysical characterizations of the human hepatitis B virus polymerase.

UNLABELLED: Hepatitis B virus (HBV) is a major human pathogen that causes serious liver disease and 600,000 deaths annually. Approved therapies for treating chronic HBV infections usually target the multifunctional viral polymerase (hPOL). Unfortunately, these therapies--broad-spectrum antivirals--are not general cures, have side effects, and cause viral resistance. While hPOL remains an attractive therapeutic target, it is notoriously difficult to express and purify in a soluble form at yields appropriate for structural studies. Thus, no empirical structural data exist for hPOL, and this impedes medicinal chemistry and rational lead discovery efforts targeting HBV. Here, we present an efficient strategy to overexpress recombinant hPOL domains in Escherichia coli, purifying them at high yield and solving their known aggregation tendencies. This allowed us to perform the first structural and biophysical characterizations of hPOL domains. Apo-hPOL domains adopt mainly α-helical structures with small amounts of ß-sheet structures. Our recombinant material exhibited metal-dependent, reverse transcriptase activity in vitro, with metal binding modulating the hPOL structure. Calcomine orange 2RS, a small molecule that inhibits duck HBV POL activity, also inhibited the in vitro priming activity of recombinant hPOL. Our work paves the way for structural and biophysical characterizations of hPOL and should facilitate high-throughput lead discovery for HBV. IMPORTANCE: The viral polymerase from human hepatitis B virus (hPOL) is a well-validated therapeutic target. However, recombinant hPOL has a well-deserved reputation for being extremely difficult to express in a soluble, active form in yields appropriate to the structural studies that usually play an important role in drug discovery programs. This has hindered the development of much-needed new antivirals for HBV. However, we have solved this problem and report here procedures for expressing recombinant hPOL domains in Escherichia coli and also methods for purifying them in soluble forms that have activity in vitro. We also present the first structural and biophysical characterizations of hPOL. Our work paves the way for new insights into hPOL structure and function, which should assist the discovery of novel antivirals for HBV.

Near-infrared autofluorescence spectroscopy of in vivo soft tissue sarcomas.

Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated via surgical resection. Inadequate resection can lead to local recurrence and decreased survival rates. In this study, we investigate the hypothesis that near-infrared (NIR) autofluorescence can be utilized for tumor margin analysis by differentiating STS from the surrounding normal tissue. Intraoperative in vivo measurements were acquired from 30 patients undergoing STS resection and were characterized to differentiate between normal tissue and STS. Overall, normal muscle and fat were observed to have the highest and lowest autofluorescence intensities, respectively, with STS falling in between. With the exclusion of well-differentiated liposarcomas, the algorithm's accuracy for classifying muscle, fat, and STS was 93%, 92%, and 88%, respectively. These findings suggest that NIR autofluorescence spectroscopy has potential as a rapid and nondestructive surgical guidance tool that can inform surgeons of suspicious margins in need of immediate re-excision.

Community paramedicine in Central Oregon: A promising model to reduce non-urgent emergency department utilization among medically complex Medicaid beneficiaries.

Background: Community paramedicine has emerged as a promising model to redirect persons with nonmedically emergent conditions to more appropriate and less expensive community-based health care settings. Outreach through community paramedicine to patients with a history of high hospital emergency department (ED) use and chronic health conditions has been found to reduce ED use. This study examined the effect of community paramedicine implemented in 2 rural counties in reducing nonemergent ED use among a sample of Medicaid beneficiaries with complex medical conditions and a history of high ED utilization. Methods: A cluster randomized trial approach with a stepped wedge design was used to test the effect of the community paramedicine intervention. ED utilization for non-urgent care was measured by emergency medicine ED visits and avoidable ED visits. Results: The community paramedicine intervention reduced ED utilization among a sample of 102 medically complex Medicaid beneficiaries with a history of high ED utilization. In the unadjusted models, emergency medical ED visits decreased by 13.9% (incidence rate ratio [IRR], 0.86; 95% confidence interval [CI], 0.76-0.98) or 6.1 visits saved for every 100 people. Avoidable emergency department visits decreased by 38.9% (IRR, 0.61; 95% CI, 0.44-0.84) or 2.3 visits saved for every 100 people. Conclusion: Our results suggest community paramedicine is a promising model to achieve a reduction in ED utilization among medically complex patients by managing complex health conditions in a home-based setting.

Feature Selection and Rapid Characterization of Bloodstains on Different Substrates.

Establishing the precise timeline of a crime can be challenging as current analytical techniques used suffer from many limitations and are destructive to the body fluids encountered at crime scenes. Raman spectroscopy has demonstrated excellent potential in forensic science as it provides direct information about the structural and molecular changes without the need for processing or extracting samples. However, its current applicability is limited to pure body fluids, as signals from the substrate underlying these fluids greatly influence the current models used for age estimation. In this study, we utilized Raman spectroscopy to identify selective spectral markers that delineate the bloodstain age in the presence of interfering signals from the substrate. The pure bloodstains and the bloodstains on the substrate were aged for two weeks at 21 ± 2 ℃ in the dark. Least absolute shrinkage and selection operator (LASSO) regression was employed to guide the feature selection in the presence of interference from substrates to accurately predict the bloodstain age. Substrate-specific regression models guided by an automated feature selection algorithm yielded low values of predictive root mean square error (0.207, 0.204, 0.222 h in logarithmic scale) and high R2 (0.924, 0.926, 0.913) on test data consisting of blood spectra on floor tile, facial tissue, and linoleum-polymer substrates, respectively. This framework for an automated feature selection algorithm relies entirely on pure bloodstain spectra to train substrate-specific models for estimating the age of composite (blood on substrate) spectra. The model can thus be easily applied to any new composite spectra and is highly scalable to new environments. This study demonstrates that Raman spectroscopy coupled with LASSO could serve as a reliable and nondestructive technique to determine the age of bloodstains on any surface while aiding forensic investigations in real-world scenarios.