Management of neurogenic bladder in patients with spinal cord injuries/disorders and end stage renal disease: a case series.

INTRODUCTION: Patients with spinal cord injuries/disorders (SCI/D) often suffer from bladder dysfunction, commonly referred to as neurogenic bladder or neurogenic lower urinary tract dysfunction (NLUTD). Standard urologic evaluation and management help to minimize complications such as vesicoureteral reflux, urinary tract infection, and nephrolithiasis. However, we have further encountered patients with more complex issues, such as chronic kidney disease (CKD), end-stage renal disease (ESRD), bilateral nephrectomies, and urinary diversion/augmentation surgeries. Of particular interest, there is a lack of standardized guidance for bladder management in SCI/D patients with ESRD. These patients are at high risk for urological complications and would benefit from codified bladder management strategies. CASE PRESENTATION: In this article, we present eleven unique cases of NLUTD with associated ESRD and discuss recommendations utilizing simple and commonly available clinical interventions. DISCUSSION: The inherently small population size of SCI/D patients with NLUTD and ESRD makes detailing a large sample size case series difficult. Future studies must aim to include a larger sample size as able, however, to better determine standardized protocols for chronic bladder management in SCI/D patients with NLUTD and ESRD. Experiences from this small case series are offered for consideration.

Efficient Synthesis and HPLC-Based Characterization for Developing Vanadium-48-Labeled Vanadyl Acetylacetonate as a Novel Cancer Radiotracer for PET Imaging.

Bis(acetylacetonato)oxidovanadium(IV) [(VO(acac)2], generally known as vanadyl acetylacetonate, has been shown to be preferentially sequestered in malignant tissue. Vanadium-48 (48V) generated with a compact medical cyclotron has been used to label VO(acac)2 as a potential radiotracer in positron emission tomography (PET) imaging for the detection of cancer, but requires lengthy synthesis. Current literature protocols for the characterization of VO(acac)2 require macroscale quantities of reactants and solvents to identify products by color and to enable crystallization that are not readily adaptable to the needs of radiotracer synthesis. We present an improved method to produce vanadium-48-labeled VO(acac)2, [48V]VO(acac)2, and characterize it using high-performance liquid chromatography (HPLC) with radiation detection in combination with UV detection. The approach is suitable for radiotracer-level quantities of material. These methods are readily applicable for production of [48V]VO(acac)2. Preliminary results of preclinical, small-animal PET studies are presented.

A simplified protocol for the automated production of 2-[18 F]fluoro-3-[2-((S)-3-pyrrolinyl)methoxy]pyridine ([18 F]nifene) on an IBA Synthera® module.

The α4ß2 nicotinic acetylcholine receptor (nAChR) ligand 2-[18 F]fluoro-3-[2-((S)-3-pyrrolinyl)methoxy]pyridine ([18 F]nifene) has been synthesized in 10% decay-corrected radiochemical yield using the IBA Synthera® platform (IBA Cyclotron Solutions, Louvain-la-Neuve, Belgium) with an integrated fluidic processor (IFP). Boc-nitronifene served as the precursor, and 20% trifluoroacetic acid (TFA) was used to deprotect the Boc-group after radiolabeling. By omitting the solvent extraction step after radiolabeling, the process was simplified to a single step with no manual intervention. [18 F]Nifene was obtained in decay-corrected radiochemical yields of 10 ± 2% (n = 20) and radiochemical purity >99%. Typical specific radioactivities of 2700-4865 mCi/µmole (100-180 GBq/µmol) were measured at the end of synthesis; total synthesis times were about 1 h 40 min.

Evaluation of an Image-Derived Input Function for Kinetic Modeling of Nicotinic Acetylcholine Receptor-Binding PET Ligands in Mice.

Positron emission tomography (PET) radioligands that bind with high-affinity to α4ß2-type nicotinic receptors (α4ß2Rs) allow for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. Here, we investigate the use of an image-derived arterial input function and the cerebellum for kinetic analysis of radioligand binding in mice. Two radioligands were explored: 2-[18F]FA85380 (2-FA), displaying similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [18F]Nifene, displaying similar pKa and binding affinity to nicotine. Time-activity curves of the left ventricle of the heart displayed similar distribution across wild type mice, mice lacking the ß2-subunit for ligand binding, and acute nicotine-treated mice, whereas reference tissue binding displayed high variation between groups. Binding potential estimated from a two-tissue compartment model fit of the data with the image-derived input function were higher than estimates from reference tissue-based estimations. Rate constants of radioligand dissociation were very slow for 2-FA and very fast for Nifene. We conclude that using an image-derived input function for kinetic modeling of nicotinic PET ligands provides suitable results compared to reference tissue-based methods and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

Accelerator-Based Production of Scandium Radioisotopes for Applications in Prostate Cancer: Toward Building a Pipeline for Rapid Development of Novel Theranostics.

In the field of nuclear medicine, the ß+ -emitting 43Sc and ß- -emitting 47Sc are promising candidates in cancer diagnosis and targeted radionuclide therapy (TRT) due to their favorable decay schema and shared pharmacokinetics as a true theranostic pair. Additionally, scandium is a group-3 transition metal (like 177Lu) and exhibits affinity for DOTA-based chelators, which have been studied in depth, making the barrier to implementation lower for 43/47Sc than for other proposed true theranostics. Before 43/47Sc can see widespread pre-clinical evaluation, however, an accessible production methodology must be established and each isotope's radiolabeling and animal imaging capabilities studied with a widely utilized tracer. As such, a simple means of converting an 18 MeV biomedical cyclotron to support solid targets and produce 43Sc via the 42Ca(d,n)43Sc reaction has been devised, exhibiting reasonable yields. The NatTi(γ,p)47Sc reaction is also investigated along with the successful implementation of chemical separation and purification methods for 43/47Sc. The conjugation of 43/47Sc with PSMA-617 at specific activities of up to 8.94 MBq/nmol and the subsequent imaging of LNCaP-ENZaR tumor xenografts in mouse models with both 43/47Sc-PSMA-617 are also presented.

Cross-cultural adaptation and validation of the Bangla version of the Psoriasis Disability Index.

Background: The Psoriasis Disability Index (PDI) is used for the quality-of-life assessment of psoriasis patients. However, a locally adapted Bangla version of the PDI (B-PDI) instrument is currently lacking in Bangladesh. To translate the instrument, adapt, and validate it among psoriatic patients of the country was the objective of the study. Methods: Translation, adaptation, and back-to-back translation to Bangla were made from the original English PDI. The final Bangla instrument was applied among 83 psoriasis patients twice at 10 days intervals. The psychometric property of the instrument was evaluated. Item-level content-validity index (CVI) was used to check the content validity of the instrument. Convergent validity was tested by comparing the B-PDI with the validated Bangla version of Short Form 36(SF-36) and the Psoriasis Area Disability Index (PASI) score. Necessary testing was used to assess internal consistency and test-retest reliability. Result: The B-PDI was well-accepted by the patients. It showed good internal consistency (Cronbach's alpha = 0.76) and very high test-retest reliability (Pearson r = 0.92, p < 0.001). The scale demonstrated excellent content validity (Content Valid Index [CVI] = 1). The instrument had satisfactory convergent validity with four components of SF-36. Pearson correlation coefficient for physical, emotional, social, and pain domains of SF-36 was 0.663, 0.644, 0.808, and 0.862, respectively, and for PASI score was 0.812. Factor exploration using Principal Component Analysis revealed four factors reflecting working disabilities, social, and hygienic disabilities, lifestyle difficulties, and leisure-associated disabilities. Conclusion: This study supports the reliability and validity of the B-PDI instrument for measuring health-related quality-of-life for Bangla-speaking psoriasis patients.

COVID-19 Severity Prediction from Chest X-ray Images Using an Anatomy-Aware Deep Learning Model.

The COVID-19 pandemic has been adversely affecting the patient management systems in hospitals around the world. Radiological imaging, especially chest x-ray and lung Computed Tomography (CT) scans, plays a vital role in the severity analysis of hospitalized COVID-19 patients. However, with an increasing number of patients and a lack of skilled radiologists, automated assessment of COVID-19 severity using medical image analysis has become increasingly important. Chest x-ray (CXR) imaging plays a significant role in assessing the severity of pneumonia, especially in low-resource hospitals, and is the most frequently used diagnostic imaging in the world. Previous methods that automatically predict the severity of COVID-19 pneumonia mainly focus on feature pooling from pre-trained CXR models without explicitly considering the underlying human anatomical attributes. This paper proposes an anatomy-aware (AA) deep learning model that learns the generic features from x-ray images considering the underlying anatomical information. Utilizing a pre-trained model and lung segmentation masks, the model generates a feature vector including disease-level features and lung involvement scores. We have used four different open-source datasets, along with an in-house annotated test set for training and evaluation of the proposed method. The proposed method improves the geographical extent score by 11% in terms of mean squared error (MSE) while preserving the benchmark result in lung opacity score. The results demonstrate the effectiveness of the proposed AA model in COVID-19 severity prediction from chest X-ray images. The algorithm can be used in low-resource setting hospitals for COVID-19 severity prediction, especially where there is a lack of skilled radiologists.

Trapping of Nicotinic Acetylcholine Receptor Ligands Assayed by In Vitro Cellular Studies and In Vivo PET Imaging.

A question relevant to nicotine addiction is how nicotine and other nicotinic receptor membrane-permeant ligands, such as the anti-smoking drug varenicline (Chantix), distribute in brain. Ligands, like varenicline, with high pKa and high affinity for α4ß2-type nicotinic receptors (α4ß2Rs) are trapped in intracellular acidic vesicles containing α4ß2Rs in vitro Nicotine, with lower pKa and α4ß2R affinity, is not trapped. Here, we extend our results by imaging nicotinic PET ligands in vivo in male and female mouse brain and identifying the trapping brain organelle in vitro as Golgi satellites (GSats). Two PET 18F-labeled imaging ligands were chosen: [18F]2-FA85380 (2-FA) with varenicline-like pKa and affinity and [18F]Nifene with nicotine-like pKa and affinity. [18F]2-FA PET-imaging kinetics were very slow consistent with 2-FA trapping in α4ß2R-containing GSats. In contrast, [18F]Nifene kinetics were rapid, consistent with its binding to α4ß2Rs but no trapping. Specific [18F]2-FA and [18F]Nifene signals were eliminated in ß2 subunit knock-out (KO) mice or by acute nicotine (AN) injections demonstrating binding to sites on ß2-containing receptors. Chloroquine (CQ), which dissipates GSat pH gradients, reduced [18F]2-FA distributions while having little effect on [18F]Nifene distributions in vivo consistent with only [18F]2-FA trapping in GSats. These results are further supported by in vitro findings where dissipation of GSat pH gradients blocks 2-FA trapping in GSats without affecting Nifene. By combining in vitro and in vivo imaging, we mapped both the brain-wide and subcellular distributions of weak-base nicotinic receptor ligands. We conclude that ligands, such as varenicline, are trapped in neurons in α4ß2R-containing GSats, which results in very slow release long after nicotine is gone after smoking.SIGNIFICANCE STATEMENT Mechanisms of nicotine addiction remain poorly understood. An earlier study using in vitro methods found that the anti-smoking nicotinic ligand, varenicline (Chantix) was trapped in α4ß2R-containing acidic vesicles. Using a fluorescent-labeled high-affinity nicotinic ligand, this study provided evidence that these intracellular acidic vesicles were α4ß2R-containing Golgi satellites (GSats). In vivo PET imaging with F-18-labeled nicotinic ligands provided additional evidence that differences in PET ligand trapping in acidic vesicles were the cause of differences in PET ligand kinetics and subcellular distributions. These findings combining in vitro and in vivo imaging revealed new mechanistic insights into the kinetics of weak base PET imaging ligands and the subcellular mechanisms underlying nicotine addiction.

The optimal 18F-fluoromisonidazole PET threshold to define tumor hypoxia in preclinical squamous cell carcinomas using pO2 electron paramagnetic resonance imaging as reference truth.

PURPOSE: To identify the optimal threshold in 18F-fluoromisonidazole (FMISO) PET images to accurately locate tumor hypoxia by using electron paramagnetic resonance imaging (pO2 EPRI) as ground truth for hypoxia, defined by pO2 [Formula: see text] 10 mmHg. METHODS: Tumor hypoxia images in mouse models of SCCVII squamous cell carcinoma (n = 16) were acquired in a hybrid PET/EPRI imaging system 2 h post-injection of FMISO. T2-weighted MRI was used to delineate tumor and muscle tissue. Dynamic contrast enhanced (DCE) MRI parametric images of Ktrans and ve were generated to model tumor vascular properties. Images from PET/EPR/MRI were co-registered and resampled to isotropic 0.5 mm voxel resolution for analysis. PET images were converted to standardized uptake value (SUV) and tumor-to-muscle ratio (TMR) units. FMISO uptake thresholds were evaluated using receiver operating characteristic (ROC) curve analysis to find the optimal FMISO threshold and unit with maximum overall hypoxia similarity (OHS) with pO2 EPRI, where OHS = 1 shows perfect overlap and OHS = 0 shows no overlap. The means of dice similarity coefficient, normalized Hausdorff distance, and accuracy were used to define the OHS. Monotonic relationships between EPRI/PET/DCE-MRI were evaluated with the Spearman correlation coefficient ([Formula: see text]) to quantify association of vasculature on hypoxia imaged with both FMISO PET and pO2 EPRI. RESULTS: FMISO PET thresholds to define hypoxia with maximum OHS (both OHS = 0.728 [Formula: see text] 0.2) were SUV [Formula: see text] 1.4 [Formula: see text] SUVmean and SUV [Formula: see text] 0.6 [Formula: see text] SUVmax. Weak-to-moderate correlations (|[Formula: see text]|< 0.70) were observed between PET/EPRI hypoxia images with vascular permeability (Ktrans) or fractional extracellular-extravascular space (ve) from DCE-MRI. CONCLUSION: This is the first in vivo comparison of FMISO uptake with pO2 EPRI to identify the optimal FMISO threshold to define tumor hypoxia, which may successfully direct hypoxic tumor boosts in patients, thereby enhancing tumor control.

Preliminary investigation of 48V-labeled VO(acac)2 for cancer imaging: An initial proof-of-concept study.

In this preliminary study, a procedure for synthesizing novel PET radiotracer vanadium-48-labeled-vanadyl acetylacetonate was developed, including radioisotope production via cyclotron, separation of 48V, chelation as 48VO(acac)2, and assessment through in vitro cellular studies. We employed the beam-stop setup in a cyclotron as the target holder to irradiate titanium foils in the reaction of natTi (p,n)48V. The radioisotope production rate was 4.84 ± 0.67 µCi/µA-h. Overall radiochemical yield was 12.86 ± 0.51% with gamma-ray spectroscopy showing no detectable contaminant peaks. HPLC of 48VO(acac)2 showed a retention time (1:48) corresponding closely to that (1:50) of commercial VO(acac)2, verifying the successful synthesis of 48VO(acac)2. In vitro cellular studies demonstrated radiotracer uptake and saturation around 0.48 nM. These studies pave the way for improving methodologies and in vivo experiments, including imaging studies, in future investigations.

Effects of whole-body vibration on driver drowsiness: A review.

INTRODUCTION: Whole-body vibration has direct impacts on driver vigilance by increasing physical and cognitive stress on the driver, which leads to drowsiness, fatigue and road traffic accidents. Although sleep deprivation, sleep apnoea and alcohol consumption can also lead to driver drowsiness, exposure to steady vibration is the factor most readily controlled by changes to vehicle design, yet it has received comparatively less attention. METHODS: This review investigated interrelationships between the various components of whole-body vibration and the physiological and cognitive parameters that lead to driver drowsiness, as well as the effects of vibration parameters (frequency, amplitude, waveform and duration). Vibrations transmitted to the driver body from the vehicle floor and/or seat have been considered for this review, whereas hand-arm vibration, shocks, acute or transient vibration were excluded from consideration. RESULTS: Drowsiness is affected by interactions between the frequency, amplitude, waveform and duration of the vibration. Under optimal conditions, whole-body vibration can induce significant drowsiness within 30 min. Low frequency whole-body vibrations, particularly vibrations of 4-10 Hz, are most effective at inducing drowsiness. This review notes some limitations of current studies and suggests directions for future research. CONCLUSIONS: This review demonstrated a strong causal link exists between whole-body vibration and driver drowsiness. Since driver drowsiness has been established to be a significant contributor to motor vehicle accidents, research is needed to identify ways to minimise the components of whole-body vibration that contribute to drowsiness, as well as devising more effective ways to counteract drowsiness. PRACTICAL APPLICATIONS: By raising awareness of the vibrational factors that contribute to drowsiness, manufacturers will be prompted to design vehicles that reduce the influence of these factors.

Symptoms COVID 19 Positive Vapers Compared to COVID 19 Positive Non-vapers.

OBJECTIVES: The purpose of the present study was to assess and describe the severity of symptoms reported by Covid-19 positive patients who vaped (smoked e-cigarettes) when compared to those who did not vape or smoke at the time of the diagnosis of Covid-19. METHODS: Patients from this study are from a well-characterized patient cohort collected at Mayo Clinic between March 1, 2020 and February 28, 2021; with confirmed COVID-19 diagnosis defined as a positive result on reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assays from nasopharyngeal swab specimens. Among the 1734 eligible patients, 289 patients reported current vaping. The cohort of vapers (N = 289) was age and gender matched to 1445 covid-19 positive patients who did not vape. The data analyzed included: date of birth, gender, ethnicity, race, marital status, as well as lifestyle history such as vaping and smoking and reported covid-19 symptoms experienced. RESULTS: A logistic regression analysis was performed separately for each symptom using generalized estimating equations (GEE) with robust variance estimates in order to account for the 1:5 age, sex, and race matched set study design. Patients who vaped and developed Covid-19 infection were more likely to have chest pain or tightness (16% vs 10%, vapers vs non vapers, P = .005), chills (25% vs 19%, vapers vs non vapers, P = .0016), myalgia (39% vs 32%, vapers vs non vapers, P = .004), headaches (49% vs 41% vapers vs non vapers, P = .026), anosmia/dysgeusia (37% vs 30%, vapers vs non vapers, P = .009), nausea/vomiting/abdominal pain (16% vs 10%, vapers vs non vapers, P = .003), diarrhea (16% vs 10%, vapers vs non vapers, P = .004), and non-severe light-headedness (16% vs 9%, vapers vs non vapers, P < .001). CONCLUSION: Vapers experience higher frequency of covid-19 related symptoms when compared with age and gender matched non-vapers. Further work should examine the impact vaping has on post-covid symptom experience.

Correlated-Weighted Statistically Modeled Contourlet and Curvelet Coefficient Image-Based Breast Tumor Classification Using Deep Learning.

Deep learning-based automatic classification of breast tumors using parametric imaging techniques from ultrasound (US) B-mode images is still an exciting research area. The Rician inverse Gaussian (RiIG) distribution is currently emerging as an appropriate example of statistical modeling. This study presents a new approach of correlated-weighted contourlet-transformed RiIG (CWCtr-RiIG) and curvelet-transformed RiIG (CWCrv-RiIG) image-based deep convolutional neural network (CNN) architecture for breast tumor classification from B-mode ultrasound images. A comparative study with other statistical models, such as Nakagami and normal inverse Gaussian (NIG) distributions, is also experienced here. The weighted entitled here is for weighting the contourlet and curvelet sub-band coefficient images by correlation with their corresponding RiIG statistically modeled images. By taking into account three freely accessible datasets (Mendeley, UDIAT, and BUSI), it is demonstrated that the proposed approach can provide more than 98 percent accuracy, sensitivity, specificity, NPV, and PPV values using the CWCtr-RiIG images. On the same datasets, the suggested method offers superior classification performance to several other existing strategies.

Improving Tumor Hypoxia Location in 18F-Misonidazole PET with Dynamic Contrast-enhanced MRI Using Quantitative Electron Paramagnetic Resonance Partial Oxygen Pressure Images.

Purpose: To enhance the spatial accuracy of fluorine 18 (18F) misonidazole (MISO) PET imaging of hypoxia by using dynamic contrast-enhanced (DCE) MR images as a basis for modifying PET images and by using electron paramagnetic resonance (EPR) partial oxygen pressure (pO2) as the reference standard. Materials and Methods: Mice (n = 10) with leg-borne MCa4 mammary carcinomas underwent EPR imaging, T2-weighted and DCE MRI, and 18F-MISO PET/CT. Images were registered to the same space for analysis. The thresholds of hypoxia for PET and EPR images were tumor-to-muscle ratios greater than or equal to 2.2 mm Hg and less than or equal to 14 mm Hg, respectively. The Dice similarity coefficient (DSC) and Hausdorff distance (d H ) were used to quantify the three-dimensional overlap of hypoxia between pO2 EPR and 18F-MISO PET images. A training subset (n = 6) was used to calculate optimal DCE MRI weighting coefficients to relate EPR to the PET signal; the group average weights were then applied to all tumors (from six training mice and four test mice). The DSC and d H were calculated before and after DCE MRI-corrected PET images were obtained to quantify the improvement in overlap with EPR pO2 images for measuring tumor hypoxia. Results: The means and standard deviations of the DSC and d H between hypoxic regions in original PET and EPR images were 0.35 mm ± 0.23 and 5.70 mm ± 1.7, respectively, for images of all 10 mice. After implementing a preliminary DCE MRI correction to PET data, the DSC increased to 0.86 mm ± 0.18 and the d H decreased to 2.29 mm ± 0.70, showing significant improvement (P < .001) for images of all 10 mice. Specifically, for images of the four independent test mice, the DSC improved with correction from 0.19 ± 0.28 to 0.80 ± 0.29 (P = .02), and the d H improved from 6.40 mm ± 2.5 to 1.95 mm ± 0.63 (P = .01). Conclusion: Using EPR information as a reference standard, DCE MRI information can be used to correct 18F-MISO PET information to more accurately reflect areas of hypoxia.Keywords: Animal Studies, Molecular Imaging, Molecular Imaging-Cancer, PET/CT, MR-Dynamic Contrast Enhanced, MR-Imaging, PET/MR, Breast, Oncology, Tumor Mircoenvironment, Electron Paramagnetic ResonanceSupplemental material is available for this article.© RSNA, 2021.

Vibrio cholerae Sialidase-Specific Immune Responses Are Associated with Protection against Cholera.

Cholera remains a major public health problem in resource-limited countries. Vaccination is an important strategy to prevent cholera, but currently available vaccines provide only 3 to 5 years of protection. Understanding immune responses to cholera antigens in naturally infected individuals may elucidate which of these are key to longer-term protection seen following infection. We recently identified Vibrio cholerae O1 sialidase, a neuraminidase that facilitates binding of cholera toxin to intestinal epithelial cells, as immunogenic following infection in two recent high-throughput screens. Here, we present systemic, mucosal, and memory immune responses to sialidase in cholera index cases and evaluated whether systemic responses to sialidase correlated with protection using a cohort of household contacts. Overall, we found age-related differences in antisialidase immune response following cholera. Adults developed significant plasma anti-sialidase IgA, IgG, and IgM responses following infection, whereas older children (≥5 years) developed both IgG and IgM responses, and younger children only developed IgM responses. Neither older children nor younger children had a rise in IgA responses over the convalescent phase of infection (day 7/day 30). On evaluation of mucosal responses and memory B-cell responses to sialidase, we found adults developed IgA antibody-secreting cell (ASC) and memory B-cell responses. Finally, in household contacts, the presence of serum anti-sialidase IgA, IgG, and IgM antibodies at enrollment was associated with a decrease in the risk of subsequent infection. These data show cholera patients develop age-related immune responses against sialidase and suggest that immune responses that target sialidase may contribute to protective immunity against cholera.IMPORTANCE Cholera infection can result in severe dehydration that may lead to death within a short period of time if not treated immediately. Vaccination is an important strategy to prevent the disease. Oral cholera vaccines provide 3 to 5 years of protection, with 60% protective efficacy, while natural infection provides longer-term protection than vaccination. Understanding the immune responses after natural infection is important to better understand immune responses to antigens that mediate longer-term protection. Sialidase is a neuraminidase that facilitates binding of cholera toxin to intestinal epithelial cells. We show here that patients with cholera develop systemic, mucosal, and memory B-cell immune responses to the sialidase antigen of Vibrio cholerae O1 and that plasma responses targeting this antigen correlate with protection.

A Lightweight CNN Model for Detecting Respiratory Diseases From Lung Auscultation Sounds Using EMD-CWT-Based Hybrid Scalogram.

Listening to lung sounds through auscultation is vital in examining the respiratory system for abnormalities. Automated analysis of lung auscultation sounds can be beneficial to the health systems in low-resource settings where there is a lack of skilled physicians. In this work, we propose a lightweight convolutional neural network (CNN) architecture to classify respiratory diseases from individual breath cycles using hybrid scalogram-based features of lung sounds. The proposed feature-set utilizes the empirical mode decomposition (EMD) and the continuous wavelet transform (CWT). The performance of the proposed scheme is studied using a patient independent train-validation-test set from the publicly available ICBHI 2017 lung sound dataset. Employing the proposed framework, weighted accuracy scores of 98.92% for three-class chronic classification and 98.70% for six-class pathological classification are achieved, which outperform well-known and much larger VGG16 in terms of accuracy by absolute margins of 1.10% and 1.11%, respectively. The proposed CNN model also outperforms other contemporary lightweight models while being computationally comparable.

Internal Medicine Physicians and Social media: Knowledge, Skills, and Attitudes.

OBJECTIVE: Increasing adoption of social media have revolutionized communications between individuals, groups, and organizations This research study was designed to assess the knowledge, skills, and attitudes of internal medicine physicians' awareness and engagement with social media (sometimes referred to as #SoMe) within the digital landscape of healthcare delivery. METHODS: An audience-response survey focused on social media "Social media in Healthcare: Physician Survey," was administered during the "A Systematic Approach to Medically Unexplained Symptoms" continuing medical education conference. The Conference took place between August 22, 2019 and August 24, 2019. Data was collected on August 23, 2019. A range of 103 (59.5%) to 112 (64.7%) of the total 173 attendees participated in this cross-sectional audience-response survey, depending on the questions answered. RESULTS: Most responders were between the ages of 35 and 65 years (79.6%) and female (60.2%). A majority of responders were aware of social media terminology (88.7%), and many had used it personally (46.7%), but only 12% knew how to use social media to search medical topics, 18% used it to network professionally and most (68.9%) had a distrust of social media when it came to the protection of their privacy or their patients' privacy. Overall, about 29.6% indicated an interest in future continued medical education focused on social media (and 27.4% were neutral). CONCLUSIONS: Approximately half of the responders used social media but far less engaged its platforms for professional use likely due to privacy related concerns. Distance from academic institutions, where professional social media use is more common likely, played a role in aversion. Awareness of social media's role in healthcare has increased among physicians in practice, however their participation and knowledge of opportunities remains limited.

In†Vivo Imaging of the Tumor-Associated Enzyme NCEH1 with a Covalent PET Probe.

Herein, we report the development of an 18 F-labeled, activity-based small-molecule probe targeting the cancer-associated serine hydrolase NCEH1. We undertook a focused medicinal chemistry campaign to simultaneously preserve potent and specific NCEH1 labeling in live cells and animals, while permitting facile 18 F radionuclide incorporation required for PET imaging. The resulting molecule, [18 F]JW199, labels active NCEH1 in live cells at nanomolar concentrations and greater than 1000-fold selectivity relative to other serine hydrolases. [18 F]JW199 displays rapid, NCEH1-dependent accumulation in mouse tissues. Finally, we demonstrate that [18 F]JW199 labels aggressive cancer tumor cells in vivo, which uncovered localized NCEH1 activity at the leading edge of triple-negative breast cancer tumors, suggesting roles for NCEH1 in tumor aggressiveness and metastasis.

Sleep stage classification using single-channel EOG.

Sleep stage classification is an important task for the timely diagnosis of sleep disorders and sleep-related studies. In this paper, automatic scoring of sleep stages using Electrooculogram (EOG) is presented. Single channel EOG signals are analyzed in Discrete Wavelet Transform (DWT) domain employing various statistical features such as Spectral Entropy, Moment-based Measures, Refined Composite Multiscale Dispersion Entropy (RCMDE) and Autoregressive (AR) Model Coefficients. The discriminating ability of the features is studied using the One Way Analysis of Variance (ANOVA) and box plots. A feature reduction algorithm based on Neighborhood Component Analysis is used to reduce the model complexity and select the features with highest discriminating abilities. Random Under-Sampling Boosting (RUSBoost), Random Forest (RF) and Support Vector Machine (SVM) are employed to classify various sleep stages for 2-6 stage classification problem. Performance of the proposed method is studied using three publicly available databases, the Sleep-EDF, Sleep-EDFX and ISRUC-Sleep databases consisting of 8, 20 and 10 subjects respectively. The proposed method outperforms the state-of-the-art EOG based techniques in accuracy. In addition, its performance is shown to be on par or better than those of various single channel EEG based methods. An important limitation of existing sleep detection methods is the low accuracy of the S1 sleep stage classification for which the proposed method using the RUSBoost classifier gives a superior accuracy as compared to those of EOG and EEG based techniques.

Automated Radiochemical Synthesis of [18F]3F4AP: A Novel PET Tracer for Imaging Demyelinating Diseases.

3-[18F]fluoro-4-aminopyridine, [18F]3F4AP, is a radiofluorinated analog of the FDA-approved drug for multiple sclerosis 4-aminopyridine (4AP). This compound is currently under investigation as a PET tracer for demyelination. We recently described a novel chemical reaction to produce metafluorinated pyridines consisting of direct fluorination of a pyridine N-oxide and the utilization of this reaction for the radiochemical synthesis of [18F]3F4AP. In this article, we demonstrate how to produce this tracer using an automated synthesizer and an in-house made flow hydrogenation reactor. We also show the standard quality control procedures performed before releasing the radiotracer for preclinical animal imaging studies. This semi-automated procedure may serve as the basis for future production of [18F]3F4AP for clinical studies.