Ceramide changes in abdominal subcutaneous and visceral adipose tissue among diabetic and nondiabetic patients.

BACKGROUND: This study profiles ceramides extracted from visceral and subcutaneous adipose tissue of human subjects by liquid chromatography-mass spectrometry to determine a correlation with status of diabetes and gender. METHODS: Samples of visceral and abdominal wall subcutaneous adipose tissue (n = 36 and n = 31, respectively) were taken during laparoscopic surgery from 36 patients (14 nondiabetic, 22 diabetic and prediabetic) undergoing bariatric surgery with a body mass index (BMI) >35 kg/m2 with ≥1 existing comorbidity or BMI ≥40 kg/m2 . Sphingolipids were extracted and analyzed using liquid chromatography-mass spectrometry. RESULTS: After logarithm 2 conversion, paired analysis of visceral to subcutaneous tissue showed differential accumulation of Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) in visceral tissue of prediabetic/diabetic female subjects, but not in males. Within-tissue analysis showed higher mean levels of ceramide species linked to insulin resistance, such as Cer(d18:1/18:0) and Cer(d18:1/16:0), in visceral tissue of prediabetic/diabetic patients compared with nondiabetic subjects and higher content of Cer(d18:1/14:0) in subcutaneous tissue of insulin-resistant female patients compared with prediabetic/diabetic males. Statistically significant differences in mean levels of ceramide species between insulin-resistant African American and insulin-resistant Caucasian patients were not evident in visceral or subcutaneous tissue. CONCLUSIONS: Analysis of ceramides is important for developing a better understanding of biological processes underlying type 2 diabetes, metabolic syndrome, and obesity. Knowledge of the accumulated ceramides/dihydroceramides may reflect on the prelipolytic state that leads the lipotoxic phase of insulin resistance and may shed light on the predisposition to insulin resistance by gender.

Reliable and highly sensitive biosensor from suspended MoS2 atomic layer on nano-gap electrodes.

The uneven morphology and the trapped charges at the surface of the traditionally used supporting substrate-based 2D biosensors produces a scattering effect, which leads to a irregular signals from individually fabricated devices. Though suspended 2D channel material has the potential to overcome scattering effects from the substrates but achieving reliability and selectivity, have been limiting the using of this biosensor technology. Here, we have demonstrated nanogap electrodes fabrication by using the self-assembly technique, which provides suspension to the 2D-MoS2. These nano-spacing electrodes not only give suspension but also provide robustness strength to the atomic layer, which remains freestanding after coating of the Hafnium oxide (HfO2) as well as linkers and antibodies. For evaluating the electrical characteristics of suspended MoS2 FET, gating potential was applied through an electrolyte on the suspended MoS2 transistor. This helped in achieved a lower subthreshold swing 70 mV/dec and ON/OFF ratio 107. Later, pH detection was conducted at room temperature, which showed an impressive sensitivity of ~880 by changing 1 unit of pH. We have also successfully shown Escherichia coli (E. coli) bacteria sensing from the suspended MoS2 transistor by functionalizing dielectric layer with E. coli antibodies. The reported biosensor has shown the ~9% of conductance changes with a lower concentration of E. coli (10 CFU/mL; colony-forming unit per mL) as well as maintain the constant sensitivity in three fabricated devices. The obtained enhancement in the sensitivity of devices and its effect on biomolecules detection can be extened to other biomolecules and this type of architecture has the potential to detect COVID-19 viruses based biomolecules.

A "New Radiation"-shining light on cancer.

There is renewed interest in novel spectroscopic techniques for molecular interrogation. Inelastic light scattering techniques can provide real-time phenotypic identification of tissue and cellular state. Here we review Raman spectroscopy as a powerful technique for the identification of cancerous tissue and tumor boundaries.

Accurate identification of breast cancer margins in microenvironments of ex-vivo basal and luminal breast cancer tissues using Raman spectroscopy.

Better knowledge of the breast tumor microenvironment is required for surgical resection and understanding the processes of tumor development. Raman spectroscopy is a promising tool that can assist in uncovering the molecular basis of disease and provide quantifiable molecular information for diagnosis and treatment evaluation. In this work, eighty-eight frozen breast tissue sections, including forty-four normal and forty-four tumor sections, were mapped in their entirety using a 250-µm-square measurement grid. Two or more smaller regions of interest within each tissue were additionally mapped using a 25 µm-square step size. A deep learning algorithm, convolutional neural network (CNN), was developed to distinguish histopathologic features with-in individual and across multiple tissue sections. Cancerous breast tissue were discriminated from normal breast tissue with 90 % accuracy, 88.8 % sensitivity and 90.8 % specificity with an excellent Area Under the Receiver Operator Curve (AUROC) of 0.96. Features that contributed significantly to the model were identified and used to generate RGB images of the tissue sections. For each grid point (pixel) on a Raman map, color was assigned to intensities at frequencies of 1002 cm-1 (Phenylalanine), 869 cm-1 (Proline, CC stretching of hydroxyproline-collagen assignment, single bond stretching vibrations for the amino acids proline, valine and polysaccharides) and 1309 cm-1 (CH3/CH2 twisting or bending mode of lipids). The Raman images clearly associate with hematoxylin and eosin stained tissue sections and allow clear visualization of boundaries between normal adipose, connective tissue and tumor. We demonstrated that this simple imaging technique allows high-resolution, straightforward molecular interpretation of Raman images. Raman spectroscopy provides rapid, label-free imaging of microscopic features with high accuracy. This method has application as laboratory tool and can assist with intraoperative tissue assessment during Breast Conserving surgery.

Rapid Detection of Clostridium difficile Toxins in Stool by Raman Spectroscopy.

BACKGROUND: Clinical practice guidelines define Clostridium difficile infections (CDI) as diarrhea (≥3 unformed stools in 24 h) with either a positive C difficile stool test or detection of pseudomembranous colitis. Diagnostic modalities such as toxigenic culture and nucleic acid amplification testing can identify the presence of toxigenic C difficile in stools. But these tests are confounded by the presence of asymptomatic colonization of toxigenic C difficile and lead to overdiagnosis of CDI. The presence of two large toxins, toxin A and B (TcdA and TcdB) is necessary for pathogenicity. Detection of toxins using toxin enzyme immunoassay is difficult as it has low sensitivity and moderate specificity. Raman spectroscopy (RS) is a novel technology that is used to detect bacteria and their toxins. RS does not require any reagents for detection such as antibodies, enzymes, primers, or stains. We hypothesize that RS is a sensitive method to detect C difficile toxins in stool and will solve the problem of overdiagnosis of CDI. MATERIALS AND METHODS: CDI negative stool samples were spiked with concentrations (1 ng/mL, 100 pg/mL, 1 pg/mL, and 0.1 pg/mL) of TcdA and TcdB. RS was performed on air-dried smeared samples of stool supernatant on a mirror-polished stainless-steel slide. As RS of feces is difficult because of confounding background material and autofluorescence, samples were photo-bleached before spectral acquisition to reduce autofluorescence. Raman spectra were obtained, background corrected, and vector normalized. The data were split into training (70%) and test (30%) datasets. The machine learning methods used on the training data set were Support Vector Machine with Linear and Radial Kernels, Random Forest, Stochastic Gradient Boosting Machine, and Principle Component Analysis-Linear Discriminant Analysis. Results were validated using a test data set. The best model was chosen, and its accuracy, sensitivity, and specificity were determined. RESULTS: In our preliminary results, at all concentrations (1 ng/mL, 100 pg/mL, 1 pg/mL, and 0.1 pg/mL), TcdA or TcdB spiked stool was distinguished from unspiked stool by all models with accuracies ranging from 64% to 77%. Gradient Boosting Machine, Principle Component Analysis-Linear Discriminant Analysis, and Support Vector Machine Linear Kernel performed best with sensitivities ranging from 69% to 90% and specificities ranging from 43% to 78%. CONCLUSIONS: Using RS, we successfully detected TcdA and TcdB in stool samples albeit with moderate-to-high sensitivity and low-to-moderate specificity. Sensitivity and specificity could be further increased with the implementation of deep learning methods, which require large sample sizes. In terms of sensitivity, RS performs better than toxin enzyme immunoassay and has the potential to rapidly detect C difficile toxins in stool at clinically relevant concentrations and thereby help mitigate overdiagnosis of CDI.

Fundamental Studies of New Ionization Technologies and Insights from IMS-MS.

Exceptional ion mobility spectrometry mass spectrometry (IMS-MS) developments by von Helden, Jarrold, and Clemmer provided technology that gives a view of chemical/biological compositions previously not achievable. The ionization method of choice used with IMS-MS has been electrospray ionization (ESI). In this special issue contribution, we focus on fundamentals of heretofore unprecedented means for transferring volatile and nonvolatile compounds into gas-phase ions singly and multiply charged. These newer ionization processes frequently lead to different selectivity relative to ESI and, together with IMS-MS, may provide a more comprehensive view of chemical compositions directly from their original environment such as surfaces, e.g., tissue. Similarities of results using solvent- and matrix-assisted ionization are highlighted, as are differences between ESI and the inlet ionization methods, especially with mixtures such as bacterial extracts. Selectivity using different matrices is discussed, as are results which add to our fundamental knowledge of inlet ionization as well as pose additional avenues for inquiry. IMS-MS provides an opportunity for comparison studies relative to ESI and will prove valuable using the new ionization technologies for direct analyses. Our hypothesis is that some ESI-IMS-MS applications will be replaced by the new ionization processes and by understanding mechanistic aspects to aid enhanced source and method developments this will be hastened.

Applications of Raman spectroscopy in cancer diagnosis.

Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.

Rapid Detection of Clostridium difficile Toxins in Serum by Raman Spectroscopy.

BACKGROUND: Clostridium difficile infection (CDI) is due to the effects of toxins, toxin A and toxin B on the host. Severe CDI is associated with systemic signs of infection. Animal models of CDI demonstrate a strong correlation between systemic toxemia and the occurrence of severe disease. However, current technologies have low sensitivity to detect C difficile toxemia in human subjects. Raman spectroscopy (RS) is an upcoming technology that is used to detect bacteria and their toxins. We speculate that RS may be a sensitive method to detect clinically relevant concentrations of C difficile toxins in serum. MATERIALS AND METHODS: Serum samples were spiked with varying concentrations of toxin A, toxin B, and both. RS was performed on an air-dried serum drop that was placed on a mirror-polished stainless steel slide. Raman spectra were obtained, background corrected, vector normalized, and analyzed by Partial Least Square Linear Discriminant Analysis and Support Vector Machine for Classification. Model accuracy was measured by cross-validation and bootstrap methods. RESULTS: Toxin-spiked sera of various concentrations (1 ng/mL, 1 pg/mL, and 0.1 pg/mL) were distinguished from control serum 100% with cross-validation error rate ranging from 0% to 18% and bootstrap error rate ranging from 0% to 12% for various concentrations. The sensitivity ranged from 87% to 100% and specificity ranged from 77% to 100% for various concentrations of toxin-spiked serum. CONCLUSIONS: We conclude that RS may be a sensitive method to detect clinically relevant concentrations of C difficile toxins in serum and thus to help diagnose severe CDI in patients in real-time at the point of care.

Doxycycline-loaded coaxial nanofiber coating of titanium implants enhances osseointegration and inhibits Staphylococcus aureus infection.

Few studies have been reported that focus on developing implant surface nanofiber (NF) coating to prevent infection and enhance osseointegration by local drug release. In this study, coaxial doxycycline (Doxy)-doped polycaprolactone/polyvinyl alcohol (PCL/PVA) NFs were directly deposited on a titanium (Ti) implant surface during electrospinning. The interaction of loaded Doxy with both PVA and PCL NFs was characterized by Raman spectroscopy. The bonding strength of Doxy-doped NF coating on Ti implants was confirmed by a stand single-pass scratch test. The improved implant osseointegration by PCL/PVA NF coatings in vivo was confirmed by scanning electron microscopy, histomorphometry and micro computed tomography (µCT) at 2, 4 and 8 weeks after implantation. The bone contact surface (%) changes of the NF coating group (80%) is significantly higher than that of the no NF group (<5%, p < 0.05). Finally, we demonstrated that a Doxy-doped NF coating effectively inhibited bacterial infection and enhanced osseointegration in an infected (Staphylococcus aureus) tibia implantation rat model. Doxy released from NF coating inhibited bacterial growth up to 8 weeks in vivo. The maximal push-in force of the Doxy-NF coating (38 N) is much higher than that of the NF coating group (6.5 N) 8 weeks after implantation (p < 0.05), which was further confirmed by quantitative histological analysis and µCT. These findings indicate that coaxial PCL/PVA NF coating doped with Doxy and/or other drugs have great potential in enhancing implant osseointegration and preventing infection.

Shining light on neurosurgery diagnostics using Raman spectroscopy.

Surgical excision of brain tumors provides a means of cytoreduction and diagnosis while minimizing neurologic deficit and improving overall survival. Despite advances in functional and three-dimensional stereotactic navigation and intraoperative magnetic resonance imaging, delineating tissue in real time with physiological confirmation is challenging. Raman spectroscopy is a promising investigative and diagnostic tool for neurosurgery, which provides rapid, non-destructive molecular characterization in vivo or in vitro for biopsy, margin assessment, or laboratory uses. The Raman Effect occurs when light temporarily changes a bond's polarizability, causing change in the vibrational frequency, with a corresponding change in energy/wavelength of the scattered photon. The recorded inelastic scattering results in a "fingerprint" or Raman spectrum of the constituent under investigation. The amount, location, and intensity of peaks in the fingerprint vary based on the amount of vibrational bonds in a molecule and their ensemble interactions with each other. Distinct differences between various pathologic conditions are shown as different intensities of the same peak, or shifting of a peak based on the binding conformation. Raman spectroscopy has potential for integration into clinical practice, particularly in distinguishing normal and diseased tissue as an adjunct to standard pathologic diagnosis. Further, development of fiber-optic Raman probes that fit through the instrument port of a standard endoscope now allows researchers and clinicians to utilize spectroscopic information for evaluation of in vivo tissue. This review highlights the need for such an instrument, summarizes neurosurgical Raman work performed to date, and discusses the future applications of neurosurgical Raman spectroscopy.

Raman spectroscopic modeling of early versus late T-lymphocyte activation via differential spectral detection of receptor expression.

The proven efficacy of renal transplantation has made it the definitive treatment for end-stage renal disease. Despite its wide acceptance, transplantation has been limited by organ shortages. In the face of this, preservation of allograft longevity is essential. The predominately T cell-driven process of acute rejection (AR) can lead to graft dysfunction and even graft loss. As a marker for AR screening, serum creatinine has a low sensitivity and specificity. This has warranted the development of more accurate screening/diagnostic tools such as Raman Spectroscopy (RS) which has been demonstrated in previous studies to accurately quantify T cell activation. In this study we further explore its application by modeling the dynamic process of cell surface receptor expression during T cell activation. 50 mitogen (Concanavalin A and pokeweed) activated T cells were stained with CD69, CD25, and CD71 monoclonal antibodies (mAbs) at 48 and 72 hour time points. In parallel, 50 activated T cells were analyzed using RS at these same time periods. At 4 8h there was high expression of the CD69 cell surface receptor detected via mAb staining with no appreciable binding of CD25/CD71 fluorescent tag. In conjunction, 48 hour RS-analyzed T cells demonstrated a significant peak difference at the 1585 cm(-1) position which represented a 63% (p=0.01) increase in peak magnitude when compared with the 72 hour samples. By contrast, the 72 hour data demonstrated an attenuation of the CD69 expression and increased CD25/CD71 expression. The corresponding RS analysis showed two significant peak differences at the 903 cm(-1) and 1449 cm(-1) positions that were not present at 48 h. These differences in Raman shifts resulted in a 40% (p=0.04) and a 59% (p=0.001) increase in peak magnitudes at these positions, respectively. This study serves to further validate RS as a screening modality capable of not only detecting T cells early in the activation process through the spectral signatures associated with CD69, but also quantifying the persistent expression of CD25 and CD71. This provides a foundation for the development of a system capable of the accurate assessment of acute and maintenance immunosuppression efficacy at the molecular level.

Proceedings of the first international summit on intestinal anastomotic leak, Chicago, Illinois, October 4-5, 2012.

OBJECTIVE: The first international summit on anastomotic leak was held in Chicago in October, 2012 to assess current knowledge in the field and develop novel lines of inquiry. The following report is a summary of the proceedings with commentaries and future prospects for clinical trials and laboratory investigations. BACKGROUND: Anastomotic leakage remains a devastating problem for the patient, and a continuing challenge to the surgeon operating on high-risk areas of the gastrointestinal tract such as the esophagus and rectum. Despite the traditional wisdom that anastomotic leak is because of technique, evidence to support this is weak-to-non-existent. Outcome data continue to demonstrate that expert high-volume surgeons working in high-volume centers continue to experience anastomotic leaks and that surgeons cannot predict reliably which patients will leak. METHODS: A one and one-half day summit was held and a small working group assembled to review current practices, opinions, scientific evidence, and potential paths forward to understand and decrease the incidence of anastomotic leak. RESULTS: RESULTS of a survey of the opinions of the group demonstrated that the majority of participants believe that anastomotic leak is a complicated biologic problem whose pathogenesis remains ill-defined. The group opined that anastomotic leak is underreported clinically, it is not because of technique except when there is gross inattention to it, and that results from animal models are mostly irrelevant to the human condition. CONCLUSIONS: A fresh and unbiased examination of the causes and strategies for prevention of anastomotic leak needs to be addressed by a continuous working group of surgeons, basic scientists, and clinical trialists to realize a real and significant reduction in its incidence and morbidity. Such a path forward is discussed.

Raman molecular imaging of brain frozen tissue sections.

Raman spectroscopy provides a molecular signature of the region being studied. It is ideal for neurosurgical applications because it is non-destructive, label-free, not impacted by water concentration, and can map an entire region of tissue. The objective of this paper is to demonstrate the meaningful spatial molecular information provided by Raman spectroscopy for identification of regions of normal brain, necrosis, diffusely infiltrating glioma and solid glioblastoma (GBM). Five frozen section tissues (1 normal, 1 necrotic, 1 GBM, and 2 infiltrating glioma) were mapped in their entirety using a 300-µm-square step size. Smaller regions of interest were also mapped using a 25-µm step size. The relative concentrations of relevant biomolecules were mapped across all tissues and compared with adjacent hematoxylin and eosin-stained sections, allowing identification of normal, GBM, and necrotic regions. Raman peaks and peak ratios mapped included 1003, 1313, 1431, 1585, and 1659 cm(-1). Tissue maps identified boundaries of grey and white matter, necrosis, GBM, and infiltrating tumor. Complementary information, including relative concentration of lipids, protein, nucleic acid, and hemoglobin, was presented in a manner which can be easily adapted for in vivo tissue mapping. Raman spectroscopy can successfully provide label-free imaging of tissue characteristics with high accuracy. It can be translated to a surgical or laboratory tool for rapid, non-destructive imaging of tumor margins.

Emerging technology: applications of Raman spectroscopy for prostate cancer.

There is a need in prostate cancer diagnostics and research for a label-free imaging methodology that is nondestructive, rapid, objective, and uninfluenced by water. Raman spectroscopy provides a molecular signature, which can be scaled from micron-level regions of interest in cells to macroscopic areas of tissue. It can be used for applications ranging from in vivo or in vitro diagnostics to basic science laboratory testing. This work describes the fundamentals of Raman spectroscopy and complementary techniques including surface enhanced Raman scattering, resonance Raman spectroscopy, coherent anti-Stokes Raman spectroscopy, confocal Raman spectroscopy, stimulated Raman scattering, and spatially offset Raman spectroscopy. Clinical applications of Raman spectroscopy to prostate cancer will be discussed, including screening, biopsy, margin assessment, and monitoring of treatment efficacy. Laboratory applications including cell identification, culture monitoring, therapeutics development, and live imaging of cellular processes are discussed. Potential future avenues of research are described, with emphasis on multiplexing Raman spectroscopy with other modalities.

Accurate gene expression-based biodosimetry using a minimal set of human gene transcripts.

PURPOSE: Rapid and reliable methods for conducting biological dosimetry are a necessity in the event of a large-scale nuclear event. Conventional biodosimetry methods lack the speed, portability, ease of use, and low cost required for triaging numerous victims. Here we address this need by showing that polymerase chain reaction (PCR) on a small number of gene transcripts can provide accurate and rapid dosimetry. The low cost and relative ease of PCR compared with existing dosimetry methods suggest that this approach may be useful in mass-casualty triage situations. METHODS AND MATERIALS: Human peripheral blood from 60 adult donors was acutely exposed to cobalt-60 gamma rays at doses of 0 (control) to 10 Gy. mRNA expression levels of 121 selected genes were obtained 0.5, 1, and 2 days after exposure by reverse-transcriptase real-time PCR. Optimal dosimetry at each time point was obtained by stepwise regression of dose received against individual gene transcript expression levels. RESULTS: Only 3 to 4 different gene transcripts, ASTN2, CDKN1A, GDF15, and ATM, are needed to explain ≥ 0.87 of the variance (R(2)). Receiver-operator characteristics, a measure of sensitivity and specificity, of 0.98 for these statistical models were achieved at each time point. CONCLUSIONS: The actual and predicted radiation doses agree very closely up to 6 Gy. Dosimetry at 8 and 10 Gy shows some effect of saturation, thereby slightly diminishing the ability to quantify higher exposures. Analyses of these gene transcripts may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations or in clinical radiation emergencies.

Raman spectroscopy to distinguish grey matter, necrosis, and glioblastoma multiforme in frozen tissue sections.

The need exists for a highly accurate, efficient and inexpensive tool to distinguish normal brain tissue from glioblastoma multiforme (GBM) and necrosis boundaries rapidly, in real-time, in the operating room. Raman spectroscopy provides a unique biochemical signature of a tissue type, with the potential to provide intraoperative identification of tumor and necrosis boundaries. We aimed to develop a database of Raman spectra from normal brain, GBM, and necrosis, and a methodology for distinguishing these pathologies. Raman spectroscopy was used to measure 95 regions from 40 frozen tissue sections using 785 nm excitation wavelength. Review of adjacent hematoxylin and eosin sections confirmed histology of each region. Three regions each of normal grey matter, necrosis, and GBM were selected as a training set. Ten regions were selected as a validation set, with a secondary validation set of tissue regions containing freeze artifact. Grey matter contained higher lipid (1061, 1081 cm(-1)) content, whereas necrosis revealed increased protein and nucleic acid content (1003, 1206, 1239, 1255-1266, 1552 cm(-1)). GBM fell between these two extremes. Discriminant function analysis showed 99.6, 97.8, and 77.5% accuracy in distinguishing tissue types in the training, validation, and validation with freeze artifact datasets, respectively. Decreased classification in the freeze artifact group was due to tissue preparation damage. This study shows the potential of Raman spectroscopy to accurately identify normal brain, necrosis, and GBM as a tool to augment pathologic diagnosis. Future work will develop mapped images of diffuse glioma and neoplastic margins toward development of an intraoperative surgical tool.

Gene expression-based dosimetry by dose and time in mice following acute radiation exposure.

Rapid and reliable methods for performing biological dosimetry are of paramount importance in the event of a large-scale nuclear event. Traditional dosimetry approaches lack the requisite rapid assessment capability, ease of use, portability and low cost, which are factors needed for triaging a large number of victims. Here we describe the results of experiments in which mice were acutely exposed to (60)Co gamma rays at doses of 0 (control) to 10 Gy. Blood was obtained from irradiated mice 0.5, 1, 2, 3, 5, and 7 days after exposure. mRNA expression levels of 106 selected genes were obtained by reverse-transcription real time PCR. Stepwise regression of dose received against individual gene transcript expression levels provided optimal dosimetry at each time point. The results indicate that only 4-7 different gene transcripts are needed to explain ≥ 0.69 of the variance (R(2)), and that receiver-operator characteristics, a measure of sensitivity and specificity, of ≥ 0.93 for these statistical models were achieved at each time point. These models provide an excellent description of the relationship between the actual and predicted doses up to 6 Gy. At doses of 8 and 10 Gy there appears to be saturation of the radiation-response signals with a corresponding diminution of accuracy. These results suggest that similar analyses in humans may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations.

Comparative assessment of iridium oxide and platinum alloy wires using an in vitro glial scar assay.

The long-term effect of chronically implanted electrodes is the formation of a glial scar. Therefore, it is imperative to assess the biocompatibility of materials before employing them in neural electrode fabrication. Platinum alloy and iridium oxide have been identified as good candidates as neural electrode biomaterials due to their mechanical and electrical properties, however, effect of glial scar formation for these two materials is lacking. In this study, we applied a glial scarring assay to observe the cellular reactivity to platinum alloy and iridium oxide wires in order to assess the biocompatibility based on previously defined characteristics. Through real-time PCR, immunostaining and imaging techniques, we will advance the understanding of the biocompatibility of these materials. Results of this study demonstrate iridium oxide wires exhibited a more significant reactive response as compared to platinum alloy wires. Cells cultured with platinum alloy wires had less GFAP gene expression, lower average GFAP intensity, and smaller glial scar thickness. Collectively, these results indicated that platinum alloy wires were more biocompatible than the iridium oxide wires.

Identification of pediatric brain neoplasms using Raman spectroscopy.

PURPOSE: Raman spectroscopy can quickly and accurately diagnose tissue in near real-time. This study evaluated the capacity of Raman spectroscopy to diagnose pediatric brain tumors. EXPERIMENTAL DESIGN: Samples of untreated pediatric medulloblastoma (4 samples and 4 patients), glioma (i.e. astrocytoma, oligodendroglioma, ependymoma, ganglioglioma and other gliomas; 27 samples and 19 patients), and normal brain samples (33 samples and 5 patients) were collected fresh from the operating room or from our frozen tumor bank. Samples were divided and tested using routine pathology and Raman spectroscopy. Twelve Raman spectra were collected per sample. Support vector machine analysis was used to classify spectra using the pathology diagnosis as the gold standard. RESULTS: Normal brain (321 spectra), glioma (246 spectra) and medulloblastoma (82 spectra) were identified with 96.9, 96.7 and 93.9% accuracy, respectively, when compared with each other. High-grade ependymomas (41 spectra) were differentiated from low-grade ependymomas (25 spectra) with 100% sensitivity and 96.0% specificity. Normal brain tissue was distinguished from low-grade glioma (118 spectra) with 91.5% sensitivity and 97.8% specificity. For these analyses, the tissue-level classification was determined to be 100% accurate. CONCLUSION: These results suggest Raman spectroscopy can accurately distinguish pediatric brain neoplasms from normal brain tissue, similar tumor types from each other and high-grade from low-grade tumors.