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Early detection of prostate cancer is critical for the success of cancer therapy. It is believed that the biochemical changes that cause the optical spectra changes would appear earlier than the histological aberration. The aim of this ex vivo study was to evaluate the ability of Stokes Shift Spectra (S3) to identify human prostate cancerous tissues from the normal. Fifteen (15) pairs of with pathologically confirmed human prostate cancerous and normal tissues underwent Stokes Shift Spectra measurements with selective wavelength interval of 40 nm. The spectra were then analyzed using machine learning (ML) algorithms to classify the two types of tissues. The ML algorithms including principal component analysis (PCA) and nonnegative matrix factorization (NMF) were used for dimension reduction and feature detection. The characteristic component spectra were used to identify the key fluorophores related to carcinogenesis. The results show that these key fluorophores within tissue, e.g., tryptophan, collagen, and NADH, have different relative concentrations between cancerous and normal tissues. A multi-class classification was performed using support vector machines (SVMs). A leave-one-out cross validation was used to evaluate the performance of the classification with the gold standard histopathological results as the ground truth. The results with high sensitivity and specificity indicate that the S3 method is effective for detecting changes of fluorophore composition in human prostate tissues due to the development of cancer. © 2021 SPIE.

Recent reports pointed out that the application of optical spectroscopy in the field of liquid biopsy has aroused great interest among researchers and demonstrated the potential of its clinical application. We report a preliminary investigation on the visible resonance Raman (VRR) spectra of human brain blood liquid collected from the scalp and around the meningeal tumor during surgery and a set of venous blood samples from healthy people and glioma grade III patients using a portable VRR-LRRTM, HR800, HR-Evolution and WITec300 Raman systems in vivo and ex vivo. The biochemical fingerprints and molecular biomarkers were found. These findings indicate that if VRR spectroscopy technology is combined with polymerase chain reaction (PCR) or genetic molecular biomarker methods (VRR-PCR), it will greatly increase the possibility for its clinical application. © 2021 SPIE.

Metastasis is the leading cause of mortalities in cancer patients due to the spreading of cancer cells to various organs. Detecting cancer and identifying its metastatic potential at the early stage is important. This may be achieved based on the quantification of the key biomolecular components within tissues and cells using recent optical spectroscopic techniques. The aim of this study was to develop a noninvasive label-free optical biopsy technique to retrieve the characteristic molecular information for detecting different metastatic potentials of prostate cancer cells. Herein we report using native fluorescence (NFL) spectroscopy along with machine learning (ML) to differentiate prostate cancer cells with different metastatic abilities. The ML algorithms including principal component analysis (PCA) and nonnegative matrix factorization (NMF) were used for dimension reduction and feature detection. The characteristic component spectra were used to identify the key biomolecules that are correlated with metastatic potentials. The relative concentrations of the molecular spectral components were retrieved and used to classify the cancer cells with different metastatic potentials. A multi-class classification was performed using support vector machines (SVMs). The NFL spectral data were collected from three prostate cancer cell lines with different levels of metastatic potentials. The key biomolecules in the prostate cancer cells were identified to be tryptophan, reduced nicotinamide adenine dinucleotide (NADH) and hypothetically lactate as well. The cancer cells with different metastatic potentials were classified with high accuracy using the relative concentrations of the key molecular components. The results suggest that the changes in the relative concentrations of these key fluorophores retrieved from NFL spectra may present potential criteria for detecting prostate cancer cells of different metastatic abilities.

We conducted speckle imaging observations of 53 stellar systems that were members of long-term radial velocity (RV) monitoring campaigns and exhibited substantial accelerations indicative of planetary or stellar companions in wide orbits. Our observations were made with blue and red filters using the Differential Speckle Survey Instrument at Gemini-South and the NN-Explore Exoplanet Stellar Speckle Imager at the WIYN telescope. The speckle imaging identifies eight luminous companions within 2" of the primary stars. In three of these systems-HD 1388, HD 87359, and HD 104304-the properties of the imaged companion are consistent with the RV measurements, suggesting that these companions may be associated with the primary and the cause of the RV variation. For all 53 stellar systems, we derive differential magnitude limits (i.e., contrast curves) from the imaging. We extend this analysis to include upper limits on companion mass in systems without imaging detections. In 25 systems, we rule out companions with masses greater than 0.2 M⊙, suggesting that the observed RV signals are caused by late-M dwarfs or substellar (potentially planetary) objects. On the other hand, the joint RV and imaging analysis almost entirely rules out planetary explanations of the RV signal for HD 19522 and suggests that the companion must have an angular separation below a few tenths of an arcsecond. This work highlights the importance of combined RV and imaging observations for characterizing the outer regions of nearby planetary systems. © 2021 Institute of Physics Publishing. All rights reserved.

We present high-resolution speckle interferometric imaging observations of TESS exoplanet host stars using the NN-EXPLORE Exoplanet and Stellar Speckle Imager instrument at the 3.5 m WIYN telescope. Eight TESS objects of interest that were originally discovered by Kepler were previously observed using the Differential Speckle Survey Instrument. Speckle observations of 186 TESS stars were carried out, and 45 (24%) likely bound companions were detected. This is approximately the number of companions we would expect to observe given the established 46% binarity rate in exoplanet host stars. For the detected binaries, the distribution of stellar mass ratio is consistent with that of the standard Raghavan distribution and may show a decrease in high-q systems as the binary separation increases. The distribution of binary orbital periods, however, is not consistent with the standard Ragahavan model, and our observations support the premise that exoplanet-hosting stars with binary companions have, in general, wider orbital separations than field binaries. We find that exoplanet-hosting binary star systems show a distribution peaking near 100 au, higher than the 40–50 au peak that is observed for field binaries. This fact led to earlier suggestions that planet formation is suppressed in close binaries.

To achieve healthy communities, addressing food insecurity (FI) is critical. This study describes a unique food distribution program combining a mobile Summer Food Service Program (SFSP) for children with a mobile pantry for adults. A survey (n = 153) of participants at six locations in New Haven Connecticut revealed that 36% reported FI and 76% were first-time pantry users. Three- quarters participated in SNAP, WIC, or both, and two-thirds had children who were fed by SFSP. Major federal programs do not eliminate FI, therefore local voluntary organizations are essential partners to address the food crisis caused by the COVID-19 pandemic.

The disproportionate impact of coronavirus disease 2019 (COVID-19) on African American communities necessitates an increased focus on the intersectional roles of racism, stigma, and other social determinants of health in influencing disease and mortality risk. The Weathering Framework is applied to demonstrate the dynamic interrelationships between these factors and to conceptualize COVID-19 as a stressful life event that will have profound health implications over the life course for African Americans. Recommendations for population health research, interventions and policies aimed at reducing COVID-19 incidence and mortality, and mitigation of the long-term impacts of the pandemic on communities of color are discussed.

Diabetes is one of the leading fatal diseases globally, putting a huge burden on the global healthcare system. Early diagnosis of diabetes is hence, of utmost importance and could save many lives. However, current techniques to determine whether a person has diabetes or has the risk of developing diabetes are primarily reliant upon clinical biomarkers. In this article, we propose a novel deep learning architecture to predict if a person has diabetes or not from a photograph of his/her retina. Using a relatively small-sized dataset, we develop a multi-stage convolutional neural network (CNN)-based model DiaNet that can reach an accuracy level of over 84% on this task, and in doing so, successfully identifies the regions on the retina images that contribute to its decision-making process, as corroborated by the medical experts in the field. This is the first study that highlights the distinguishing capability of the retinal images for diabetes patients in the Qatari population to the best of our knowledge. Comparing the performance of DiaNet against the existing clinical data-based machine learning models, we conclude that the retinal images contain sufficient information to distinguish the Qatari diabetes cohort from the control group. In addition, our study reveals that retinal images may contain prognosis markers for diabetes and other comorbidities like hypertension and ischemic heart disease. The results led us to believe that the inclusion of retinal images into the clinical setup for the diagnosis of diabetes is warranted in the near future.

An explorative survey pertaining to organization and execution of programs and events offered in public libraries across Connecticut revealed that library programs have been steadily increasing in recent years, with most libraries providing one hundred or more programs a year. The types of programs that are most popular vary throughout the library’s open hours. Children’s programming appears to be more popular during the day while adult programming is more popular in the evening. Program popularity is based on grouping and continuous support from external partners. While this study confirmed that both library space and library staff sizes are adequate for programming, a further investigation would assert that this is the case within nationwide library programming.

Hinges creak, and she swirls in the door, puts her finger to blue lips. Cold takes the old woodcutter, eyes open, breath frozen in his beard.  But crystals melt in your lashes as you gaze on her gl…

"Photovoice for Social Justice, the latest volume in Sage's Qualitative Research Methods Series, helps readers in the health and social sciences learn the foundations and applications of this exciting qualitative method. Authors Jean M. Breny and Shannon L. McMorrow approach photovoice as not only a community-based participatory research method, but as a method for social justice, centering community participants, organizations, and policy makers at the heart of this research method. Special topics relating to social justice include a focus on ethics and working with marginalized communities, sensitive concerns during data collection, and presenting the work to communities and policymakers, as well as academics. Written for students and researchers new to photovoice, this brief text takes readers from the process of conceptualizing and implementing a photovoice study to analyzing data and finally presenting the results of the study. The book concludes with suggestions for future iterations of photovoice, including web based resources and digital storytelling. The authors take into account the realities of photovoice as a method by providing practical, applied tools including sample consent forms, presentations, recruitment flyers, and photo-taking tips. Using Photovoice for Social Justice, new and experienced researchers can design, implement, and analyze their photovoice projects" --

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