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Resonance Raman spectroscopy is used for rapid detection of skin BCC cancer. The cross-validated classification accuracy is achieved to be as high as 98% using nonnegative matrix factorization along with support vector machine statistical method. © OSA 2017.

The purpose of this study is to examine optical spatial frequency spectroscopy analysis (SFSA) combined with visible resonance Raman (VRR) spectroscopic method, for the first time, to discriminate human brain metastases of lung cancers adenocarcinoma (ADC) and squamous cell carcinoma (SCC) from normal tissues. A total of 31 label-free micrographic images of three types of brain tissues were obtained using a confocal micro-Raman spectroscopic system. VRR spectra of the corresponding samples were synchronously collected using excitation wavelength of 532[Formula: see text]nm from the same sites of the tissues. Using SFSA method, the difference in the randomness of spatial frequency structures in the micrograph images was analyzed using Gaussian function fitting. The standard deviations, [Formula: see text] calculated from the spatial frequencies of the micrograph images were then analyzed using support vector machine (SVM) classifier. The key VRR biomolecular fingerprints of carotenoids, tryptophan, amide II, lipids and proteins (methylene/methyl groups) were also analyzed using SVM classifier. All three types of brain tissues were identified with high accuracy in the two approaches with high correlation. The results show that SFSA–VRR can potentially be a dual-modal method to provide new criteria for identifying the three types of human brain tissues, which are on-site, real-time and label-free and may improve the accuracy of brain biopsy.

A VRR-LRR analyzer with handheld fiber‐optic probe is reported for the first time for diagnosis of brain GBM in vivo. The sensitivity for identification is 80% compared with histopathology examination. © OSA 2019. The Author(s).

Alzheimer’s disease (AD) pathogenesis is widely believed to be associated with the production and deposition of the β-amyloid peptide (Aβ) and neurofibrillary tangles (NFTs) which are composed of a highly-phosphorylated form of the microtubule-associated protein tau. Based on the above hypothesis, there are currently no sufficiently effective technologies and drugs for early detection and treatment of AD. Even the most promising new drug Lecanemab that is based on an anti-amyloid monoclonal antibody therapy, has only partially slowed down the cognitive performance of patients with mild impairment caused by Alzheimer's disease. The main symptoms of AD brain tissue lesions in patients are the deposition of β-amyloid peptide and the hyperphosphorylation of tau protein, which aggregates the microtubule structure of neurons. Therefore, Aβ deposition and hyperphosphorylation of Tau are important pathological biomarkers of Alzheimer's disease. Therefore, the main targets of research for AD prevention, detection and pharmaceuticals are still Aβ and Tau protein. The aim of this study was to detect the changes of Aβ and Tau proteins in the mouse brain tissue with AD and control samples using Visible Resonance Raman (VRR) spectroscopic technology. An attempt was made to develop criteria for the detection of early AD lesions by optical spectroscopy technology. The VRR spectra of AD, the control mouse brain tissues, and Aβ and Tau proteins were recorded and analyzed. The AD and the control mouse brain tissue samples were selected from the thalamus, frontal lobe cortex and hippocampus brain areas. VRR technology with high spatial resolution and the resonance-enhanced features of certain protein molecules is first used in this study to detect and characterize the changes of Aβ and Tau proteins in AD mouse brain model. The optical spectroscopy biomarkers of AD and Control brain tissue were identified in fingerprint and the high-wavenumber regions. The Raman spectra of the secondary structure of protein in amide (I-II-III-B-A) are detected and analyzed. The results indicate that the intensity of Amide I decreased at the 1666 cm^-1 corresponding to the β-sheet structure, and the intensity of the amide III bands (1220- 1320 cm^-1) increased in all AD brain tissues. It was also observed that the Raman peaks of 1448 and 980 cm^-1 related to the abundance of proline, serine, and threonine at tau phosphorylation sites were significantly enhanced in the frontal lobe cortex and hippocampus of AD brain tissues. The intensity ratio biomarker of high phosphorylation in the high wavenumber range from 2898 to 2932 cm-1 increased in all AD brain tissues. Changes of protein secondary conformation and abnormally phosphorylated tau or tauopathies were observed. In summary, VRR is a sensitive tool for characterizing protein structural changes and monitoring the tau phosphorylation. It may potentially be used for early detection of AD.

Analyzing spectral or imaging data collected with various optical biopsy methods is often times difficult due to the complexity of the biological basis. Robust methods that can utilize the spectral or imaging data and detect the characteristic spectral or spatial signatures for different types of tissue is challenging but highly desired. In this study, we used various machine learning algorithms to analyze a spectral dataset acquired from human skin normal and cancerous tissue samples using resonance Raman spectroscopy with 532nm excitation. The algorithms including principal component analysis, nonnegative matrix factorization, and autoencoder artificial neural network are used to reduce dimension of the dataset and detect features. A support vector machine with a linear kernel is used to classify the normal tissue and cancerous tissue samples. The efficacies of the methods are compared.

College student mental health has been a critical concern for professional counselors. Anxiety and depressive disorders have become increasingly prevalent over the past decade. Utilizing machine learning, a subset of artificial intelligence (AI), we developed predictive models (i.e., eXtreme Gradient Boosting [XGBoost], Random Forest, Decision Tree, and Logistic Regression) to identify US college students at heightened risk of diagnosable anxiety and depressive disorders. The dataset included 61,619 students from 133 US higher education institutions and was partitioned into a 90:10 ratio for training and testing the models. We employed hyperparameter tuning and cross-validation to optimize model performance and examined multiple measures of predictive performance (e.g., area under the receiver operating characteristic curve [AUC], accuracy, sensitivity). Results revealed strong discriminative power in our machine learning predictive models with AUC of 0.74 and 0.77, indicating current financial situation, sense of belonging on campus, disability status, and age as the top predictors of anxiety and depressive disorders. This study provides a practical tool for professional counselors to proactively identify students for anxiety and depressive disorders before these conditions escalate. Application of machine learning in counseling research provides data-driven insights that help enhance the understanding of mental health determinants, guide prevention and intervention strategies, and promote the well-being of diverse student populations through counseling.

The accurate identification of the human brain tumor boundary and the complete resection of the tumor are two essential factors for the removal of the glioma tumor in brain surgery. We present a visible resonance Raman (VRR) spectroscopy technique for differentiating the brain tumor margin and glioma grading. Eighty-seven VRR spectra from twenty-one human brain specimens of four types of brain tissues, including the control, glioma grade II, III, and IV tissues, were observed. This study focuses on observing the characteristics of new biomarkers and their changes in the four types of brain tissue. We found that two new RR peaks at 1129 cm-1 and 1338 cm-1 associated with molecular vibrational bonds in four types of brain tissues are significantly different in peak intensities of VRR spectra. These two resonance enhanced peaks may arise from lactic acid/phosphatidic acid and adenosine triphosphate (ATP)/nicotinamide adenine dinucleotide, respectively. We found that lactic acid and ATP concentrations vary with glioma gratings. The higher the grade of malignancy, the more the increase in lactic acid and ATP concentrations. These two RR peaks may be considered as new molecular biomarkers and used to evaluate glioma grades and identify the margin of gliomas from the control tissues. The metabolic process of lactic acid and ATP in glioma cells based on the VRR spectral changes may reveal the Warburg hypothesis. © 2018 Author(s).

Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins.

For the past few years, immunotherapy has recently shown considerable clinical benefit in CRC therapy, and the application of immunologic therapies in cancer treatments continues to increase perennially. Interleukin-12, an ideal candidate for tumor immunotherapy, could activate both innate and adaptive immunities. In this study, we developed a novel gene delivery system with a self-assembly method by MPEG-PLA and DOTAP(DMP) with zeta-potential value of 38.5mV and size of 37.5nm. The supernatant of lymphocytes treated with supernatant from Ct26 transfected pIL12 with DMP could inhibit Ct26 cells growth ex vivo. Treatment of tumor-bearing mice with DMP-pIL12 complex has significantly inhibited tumor growth at both the subcutaneous and peritoneal model in vivo by inhibiting angiogenesis, promoting apoptosis and reducing proliferation. The IL-12 plasmid and DMP complex may be used to treat the colorectal cancer in clinical as a new drug. Copyright © 2017 Elsevier Inc. All rights reserved.

Visible resonant Raman (VRR) spectroscopy provides an effective way to enhance Raman signal from particular bonds associated with key molecules due to changes on molecular level. This paper reports on the VRR use for detection of human brain the control and gliomas of three grades. From the RR spectra additional two molecular vibrational biomarkers at 1129cm^-1 and 1338cm^-1, for the four types of brain tissues are significantly different in intensity. The new RR spectral peaks can be used as molecular biomarkers to evaluate glioma grades and identify the margin of gliomas from the controls. The metabolic process of glioma cells based on the RR spectral changes may reveal the Warburg hypothesis.

We combine new high resolution imaging and spectroscopy from Keck/NIRC2, Discovery Channel Telescope/DSSI, and Keck/HIRES with published astrometry and radial velocities to measure individual masses and orbital elements of the GJ 3305 AB system, a young (∼20 Myr) M+M binary (unresolved spectral type M0) member of the β Pictoris moving group comoving with the imaged exoplanet host 51 Eri. We measure a total system mass of 1.11 ± 0.04 , a period of 29.03 ± 0.50 year, a semimajor axis of 9.78 ± 0.14 AU, and an eccentricity of 0.19 ± 0.02. The primary component has a dynamical mass of 0.67 ± 0.05 and the secondary has a mass of 0.44 ± 0.05 . The recently updated BHAC15 models are consistent with the masses of both stars to within Given the observed masses the models predict an age of the GJ 3305 AB system of 37 ± 9 Myr. Based on the observed system architecture and our dynamical mass measurement, it is unlikely that the orbit of 51 Eri b has been significantly altered by the Kozai-Lidov mechanism. © 2015. The American Astronomical Society. All rights reserved..

Based on Visible Resonance Raman (VRR) method, we have developed a novel label-free portable VRR LRR2000 Raman analyzer with a portable fiber-optic probe and used it for the classification of human gliomas ex vivo and for the analysis of changes in tumor chemical compositions in molecular level. The purpose of this study was to examine the performance of the LRR2000 Raman analyzer as an optical biopsy tool for detecting human brain tumors compared to the commercial laboratory HR800 and WITec300 micro confocal Raman spectroscopy instruments. As of 2018, a total 1,938 VRR spectra were collected using LRR2000, HR800 and WITec300 Raman system, ex vivo. Identification of the four grades of glioma tumors and control tissues was performed based on the characteristic native molecular fingerprints. LRR2000 demonstrated consistent diagnostic results with HR800 and WITec300 Raman systems. LRR2000 showed the advantages of high speed, convenience and low cost compared to the two confocal micro Raman systems. Using artificial intelligence (AI)-based analysis of part of the data, the cross-validated accuracy for identifying glioma tumors is ~90% compared with gold standard histopathology examination.

Laser-induced fluorescence (LIF) technique was used to generate spectral signatures of endogenous fluorophores relevant to the tissue molecular composition changes in human brain glioma tumors. The goal is to study the changes of fluorescence emission spectra from endogenous fluorophores in human brain glioma of different grades, and to find new biomarkers for prognostic optical molecular pathological diagnosis. Two hundred and thirty-seven (237) native fluorescence spectra from 61 subjects were measured using LabRAM HR Evolution micro photoluminescence (PL) system for four grades of glioma tumors in ex-vivo. The differences of four grades of glioma tumors were identified by the characteristic fluorophores fingerprints under the excitation laser wavelength at UV 325nm. To our best knowledge, this is the first report for human brain study using this technique. The fluorescence peaks of biomarkers with major contribution were found, including tryptophan, collagen, elastin, reduced nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD) and phospholipids that play important roles in the cellular energy metabolism and glycolysis pathway. The ratios of peak intensities and the peak positions in fluorescence spectra of may be used to diagnose human brain diseases or to guide biopsy during surgical resection. © 2019 SPIE.

The recent explosion of wearable technology and the associated concerns prompted the International Federation of Sports Medicine (FIMS) to create a quality assurance standard for wearable devices, which provides commissioned testing of marketing claims and endorsement of commercial wearables that test favorably. An open forum as announced in the conference advertising was held at the Annual Meeting of the New England Regional Chapter of the American College of Sports Medicine (NEACSM) November 7 to 8, 2019, in Providence, Rhode Island, USA for attending NEACSM members to voice their input on the process. Herein, we report the proceedings. The round table participants perceived the quality assurance standard to be important, but identified some practical process challenges that included the broad scope and complexity of the device universe, the need for a multiphase testing pathway, and the associated fees for product evaluation. The participants also supported the evaluation of device data analysis, behavioral influences, and user experience in the overall evaluation. Looking forward, the FIMS quality assurance standard faces the challenge of balancing these broader perspectives with practical constraints of budget, facilities, time, and human resources. © 2020 by the American College of Sports Medicine.

Open clusters have been the focus of several exoplanet surveys, but only a few planets have so far been discovered. The Kepler spacecraft revealed an abundance of small planets around small cool stars, therefore, such cluster members are prime targets for exoplanet transit searches. Kepler's new mission, K2, is targeting several open clusters and star-forming regions around the ecliptic to search for transiting planets around their low-mass constituents. Here, we report the discovery of the first transiting planet in the intermediate-age (800 Myr) Beehive cluster (Praesepe). K2-95 is a faint (Kp = 15.5 mag) dwarf from K2's Campaign 5 with an effective temperature of 3471 ±124 K, approximately solar metallicity and a radius of 0.402± 0.050.R⊕ We detected a transiting planet with a radius of3.47+0.78 -0.53R⊕ and an orbital period of 10.134 days. We combined photometry, medium/high-resolution spectroscopy, adaptive optics/speckle imaging, and archival survey images to rule out any false-positive detection scenarios, validate the planet, and further characterize the system. The planet's radius is very unusual as M-dwarf field stars rarely have Neptune-sized transiting planets. The comparatively large radius of K2-95b is consistent with the other recently discovered cluster planets K2-25b (Hyades) and K2-33b (Upper Scorpius), indicating systematic differences in their evolutionary states or formation. These discoveries from K2 provide a snapshot of planet formation and evolution in cluster environments and thus make excellent laboratories to test differences between field-star and cluster planet populations. © 2016. The American Astronomical Society. All rights reserved..

Millions of consumer sport and fitness wearables (CSFWs) are used worldwide, and millions of datapoints are generated by each device. Moreover, these numbers are rapidly growing, and they contain a heterogeneity of devices, data types, and contexts for data collection. Companies and consumers would benefit from guiding standards on device quality and data formats. To address this growing need, we convened a virtual panel of industry and academic stakeholders, and this manuscript summarizes the outcomes of the discussion. Our objectives were to identify (1) key facilitators of and barriers to participation by CSFW manufacturers in guiding standards and (2) stakeholder priorities. The venues were the Yale Center for Biomedical Data Science Digital Health Monthly Seminar Series (62 participants) and the New England Chapter of the American College of Sports Medicine Annual Meeting (59 participants). In the discussion, stakeholders outlined both facilitators of (e.g., commercial return on investment in device quality, lucrative research partnerships, and transparent and multilevel evaluation of device quality) and barriers (e.g., competitive advantage conflict, lack of flexibility in previously developed devices) to participation in guiding standards. There was general agreement to adopt Keadle et al.’s standard pathway for testing devices (i.e., benchtop, laboratory, field-based, implementation) without consensus on the prioritization of these steps. Overall, there was enthusiasm not to add prescriptive or regulatory steps, but instead create a networking hub that connects companies to consumers and researchers for flexible guidance navigating the heterogeneity, multi-tiered development, dynamicity, and nebulousness of the CSFW field. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

We present 197 planet candidates discovered using data from the first year of the NASA K2 mission (Campaigns 0-4), along with the results of an intensive program of photometric analyses, stellar spectroscopy, high-resolution imaging, and statistical validation. We distill these candidates into sets of 104 validated planets (57 in multi-planet systems), false positives, and 63 remaining candidates. Our validated systems span a range of properties, with median values of RP= 2.3 R⊕, P = 8.6 days, Teff = 5300 K, and Kp = 12.7mag. Stellar spectroscopy provides precise stellar and planetary parameters for most of these systems. We show that K2 has increased by 30% the number of small planets known to orbit moderately bright stars (1-4 R R⊕, Kp = 9-13 mag). Of particular interest are planets smaller than 2 R⊕, orbiting stars brighter than Kp = 11.5 mag, 5 receiving Earth-like irradiation levels, and several multi-planet systems - including 4 planets orbiting the M dwarf K2-72 near mean-motion resonances. By quantifying the likelihood that each candidate is a planet we demonstrate that our candidate sample has an overall false positive rate of 15%-30%, with rates substantially lower for small candidates (<2R⊕) and larger for candidates with radii >8 R⊕ and/or with P<3 days. Extrapolation of the current planetary yield suggests that K2 will discover between 500 and 1000 planets in its planned four-year mission, assuming sufficient follow-up resources are available. Efficient observing and analysis, together with an organized and coherent follow-up strategy, are essential for maximizing the efficacy of planet-validation efforts for K2, TESS, and future large-scale surveys. © 2016. The American Astronomical Society. All rights reserved.

Background--Data are sparse regarding the value of physical activity (PA) surveillance among older adults-particularly among those with mobility limitations. The objective of this study was to examine longitudinal associations between objectively measured daily PA and the incidence of cardiovascular events among older adults in the LIFE (Lifestyle Interventions and Independence for Elders) study. Methods and Results--Cardiovascular events were adjudicated based on medical records review, and cardiovascular risk factors were controlled for in the analysis. Home-based activity data were collected by hip-worn accelerometers at baseline and at 6, 12, and 24 months postrandomization to either a physical activity or health education intervention. LIFE study participants (n=1590; age 78.9±5.2 [SD] years; 67.2% women) at baseline had an 11% lower incidence of experiencing a subsequent cardiovascular event per 500 steps taken per day based on activity data (hazard ratio, 0.89; 95% confidence interval, 0.84-0.96; P=0.001). At baseline, every 30 minutes spent performing activities ≥500 counts per minute (hazard ratio, 0.75; confidence interval, 0.65-0.89 [P=0.001]) were also associated with a lower incidence of cardiovascular events. Throughout follow-up (6, 12, and 24 months), both the number of steps per day (per 500 steps; hazard ratio, 0.90, confidence interval, 0.85-0.96 [P=0.001]) and duration of activity ≥500 counts per minute (per 30 minutes; hazard ratio, 0.76; confidence interval, 0.63-0.90 [P=0.002]) were significantly associated with lower cardiovascular event rates. Conclusions--Objective measurements of physical activity via accelerometry were associated with cardiovascular events among older adults with limited mobility (summary score > 10 on the Short Physical Performance Battery) both using baseline and longitudinal data. © 2017 The Authors.

Objective: The objective of this study was to evaluate cross-sectional and longitudinal associations between ankle-brachial index (ABI) and indicators of cognitive function. Design: Randomized clinical trial (Lifestyle Interventions and Independence for Elders Trial). Setting: Eight US academic centers. Participants: A total of 1601 adults ages 70-89 years, sedentary, without dementia, and with functional limitations. Measurements: Baseline ABI and interviewer- and computer-administered cognitive function assessments were obtained. These assessments were used to compare a physical activity intervention with a health education control. Cognitive function was reassessed 24 months later (interviewer-administered) and 18 or 30 months later (computer-administered) and central adjudication was used to classify individuals as having mild cognitive impairment, probable dementia, or neither. Results: Lower ABI had a modest independent association with poorer cognitive functioning at baseline (partial r= 0.09; P < .001). Although lower baseline ABI was not associated with overall changes in cognitive function test scores, it was associated with higher odds for 2-year progression to a composite of either mild cognitive impairment or probable dementia (odds ratio 2.60 per unit lower ABI; 95% confidence interval 1.06-6.37). Across 2 years, changes in ABI were not associated with changes in cognitive function. Conclusion: In an older cohort sedentary individuals with dementia and with functional limitations, lower baseline ABI was independently correlated with cognitive function and associated with greater 2-year risk for progression to mild cognitive impairment or probable dementia. © 2015 AMDA - The Society for Post-Acute and Long-Term Care Medicine.