Impact of a Diabetes Risk Score on Lifestyle Education and Patient Adherence (IDEA) in Prediabetes: A Multisite Randomized Controlled Trial.

BACKGROUND: To evaluate whether knowledge of a personalized Diabetes Risk Score (DRS) improved performance in a 12-week lifestyle change program for prediabetes. METHODS: Randomized subjects at four clinics provided samples for a DRS at baseline, 12, and 24 weeks. The intervention group received scores at each point, whereas the control group only received this information at 12 and 24 weeks. Outcomes included attendance and changes in weight, abdominal circumference, blood pressure, fasting glucose, hemoglobin A1c, cholesterol, and risk score. RESULTS: Baseline characteristics were similar in the groups (n = 192) and within risk-stratified subgroups. At 12 weeks, there were no differences in outcomes, with mean weight loss of 4.61 kg in the intervention group and 4.43 kg in the control group (p = 0.79). Both groups were given 12-week risk scores, with previously unseen baseline scores for the control group. The control group continued to lose additional weight (1.21 kg) by 24 weeks, whereas the intervention group regained previously lost weight (0.33 kg) (p = 0.04). CONCLUSIONS: The knowledge of a single baseline personalized DRS did not affect performance in a lifestyle modification program. However, the knowledge of an improvement in risk score, and the timing of this information, may impact further adherence.

Evaluation of pancreatic cancer with Raman spectroscopy in a mouse model.

OBJECTIVES: Detection of neoplastic changes using optical spectroscopy has been an active area of research in recent times. Raman spectroscopy is a vibrational spectroscopic technique that can be used to diagnose various tumors with high sensitivity and specificity. We evaluated the ability of Raman spectroscopy to differentiate normal pancreatic tissue from malignant tumors in a mouse model. METHODS: We collected 920 spectra, 475 from 31 normal pancreatic tissue and 445 from 29 tumor nodules using a 785-nm near-infrared laser excitation. Discriminant function analysis was used for classification of normal and tumor samples. RESULTS: Using principal component analysis, we were able to highlight subtle chemical differences in normal and malignant tissue. Using histopathology as the gold standard, Raman analysis gave sensitivities between 91% and 96% and specificities between 88% and 96%. CONCLUSIONS: Raman spectroscopy along with discriminant function analysis is a useful method to detect cancerous changes in the pancreas. Pancreatic tumors were characterized by increased collagen content and decreased DNA, RNA, and lipids components compared with normal pancreatic tissue.

Diagnosis of neuroblastoma and ganglioneuroma using Raman spectroscopy.

BACKGROUND: Raman spectroscopy has proven to be useful in studying premalignant and malignant lesions in adults. This is the first report to evaluate Raman spectroscopy in the diagnosis and classification of neuroblastoma in children. METHODS: A biopsy or resection of fresh tissue samples from normal adrenal glands, neuroblastomas, ganglioneuromas, nerve sheath tumors, and pheochromocytoma at our hospital were equally divided between routine histology and spectroscopic studies. At least 12 spectra were collected from different regions of each sample using a Renishaw Raman microscope. Raw spectra were processed to remove noise, fluorescence, and shot noise, and then analyzed using principle component analysis and discriminant function analysis. RESULTS: We collected 698 spectra from 16 neuroblastomas, 5 ganglioneuromas, 3 normal adrenal glands, 6 nerve sheath tumors, and 1 pheochromocytoma. Raman spectroscopy differentiated between normal adrenal gland, and neuroblastoma and ganglioneuroma with 100% sensitivity and 100% specificity. It correlated well with the Shimada histologic classification system with 100% sensitivity and 100% specificity. It was also able to differentiate neuroblastoma from nerve sheath tumors and pheochromocytoma with high sensitivity and specificity. CONCLUSION: This technique can differentiate neuroblastoma from ganglioneuroma and other tumors. It has a potential as a noninvasive real-time diagnostic tool in classifying pediatric tumors.

Raman spectroscopy can differentiate malignant tumors from normal breast tissue and detect early neoplastic changes in a mouse model.

Raman spectroscopy shows potential in differentiating tumors from normal tissue. We used Raman spectroscopy with near-infrared light excitation to study normal breast tissue and tumors from 11 mice injected with a cancer cell line. Spectra were collected from 17 tumors, 18 samples of adjacent breast tissue and lymph nodes, and 17 tissue samples from the contralateral breast and its adjacent lymph nodes. Discriminant function analysis was used for classification with principal component analysis scores as input data. Tissues were examined by light microscopy following formalin fixation and hematoxylin and eosin staining. Discriminant function analysis and histology agreed on the diagnosis of all contralateral normal, tumor, and mastitis samples, except one tumor which was found to be more similar to normal tissue. Normal tissue adjacent to each tumor was examined as a separate data group called tumor bed. Scattered morphologically suspicious atypical cells not definite for tumor were present in the tumor bed samples. Classification of tumor bed tissue showed that some tumor bed tissues are diagnostically different from normal, tumor, and mastitis tissue. This may reflect malignant molecular alterations prior to morphologic changes, as expected in preneoplastic processes. Raman spectroscopy not only distinguishes tumor from normal breast tissue, but also detects early neoplastic changes prior to definite morphologic alteration.